Patent Application
20220026446
The invention relates generally to methods for the diagnosis and/or prognosis of amyloid-associated diseases, methods of treating amyloid-associated diseases, and methods for identifying an agent for the treatment of amyloid-associated diseases, as well as related uses and kits.
Amyloid-associated diseases are characterised by the presence and accumulation of amyloid fibrils and aggregates in a patient. Well known examples of amyloid-associated diseases are Alzheimer's disease, Huntington's disease and Parkinson's disease. These diseases often lead to a deterioration of a patient's health and mental well-being, sometimes over a long period of time, and often result in death. The pathogenesis and symptoms of the amyloid-associated diseases are often very traumatic for the patient, and his/her family. Alzheimer's disease is the most common cause of dementia worldwide (Prince et al., World Alzheimer Report 2016. London, UK: 2016 and Alzheimer's Disease Facts and Figures. Alzheimer's Association. 2017).
Key to treating and managing the symptoms of amyloid-associated diseases is an early diagnosis, as well as a clear prognosis of disease progression. However, since amyloid-associated diseases often develop slowly and there is a lack of known early biomarkers of the disease, a patient usually has a well-established disease before receiving any diagnosis and/or prognosis. In some cases, methods to identify the disease using biomarkers can only be conducted post-mortem, which provide no benefit to the patient. This drastically delays the patient being able to receive timely and appropriate treatment, which is detrimental to health.
Accordingly, there is a need for the development of methods for the early diagnosis and prognosis of amyloid-associated diseases.
U.S. Pat. No. 6,498,017 discloses a method for detection of diseases associated with protein 30 depositions. An important characteristic of the method is the use of probes which typically are of the same type of compound as the target to be detected. The probes are suitably obtained by subjecting pathological protein deposits by physical and/or chemical means (e.g. ultrasonication, detergents). The probes in conjunction with disease associated deposits serving as nuclei provides for a polymerisation process thereby amplifying the measured signal.
WO 2016/04090 A1 presents a methodology for determining the presence of a misfolded Aβ protein in a sample. Indispensable to the method is the integration of a step amplifying the Aβ protein prior to analysis.
Tiiman et al. (Biochemistry 2015, 54, 7203-7211) relates to the kinetics of Aβ aggregation and more specifically the time dependent growth of structured Aβ aggregates. The kinetic studies are performed on model solutions comprising recombinant lyophilized Aβ42.
Guan et al. (ACS Chem. Neurosci. 2015, 6, 1503-1508) and WO 2017/004560 disclose a novel fluorescent market (ARCAM-1) having valuable spectroscopic characteristics especially when associating to protein aggregates of Aβ. When ARCAM-1 associates to Aβ aggregates a significant increase in fluorescence emission is achieved compared to un-bound ARCAM-1. The spectroscopic properties of ARCAM-1 are evaluated using a model system incorporating synthesized Aβ42.
Wennmalm et al. (Anal. Chem. 2015, 87, 11700-11705) presents a system for detection of amyloid beat oligomers with high sensitivity by the provision of FRET and FCS (Fluorescence Correlation Spectroscopy). Synthetic fluorescent labelled Aβ40 and Aβ42 are used as model substances.
Against this background, the inventors have developed a new method allowing for the early diagnosis and prognosis of amyloid-associated diseases.
The inventors' development involves the determination of the presence and/or amount and/or concentration and/or size of individual amyloid aggregates in the patient, and is based on the surprising finding that individual amyloid aggregates that occur in patients with amyloid-associated diseases can be identified in a patient's bodily fluid such as blood or cerebrospinal fluid (CSF). The inventors have found that these individual amyloid aggregates can be identified well before the disease is well-established and detectable using other known methods, and that the detection of the individual amyloid aggregates provides a highly effective diagnosis and/or prognosis of the disease. A further advantage of the inventors' technology is that individual amyloid aggregates can be detected at low levels; since low levels of individual amyloid aggregates are sometimes present at an early stage of an amyloid-associated disease, this aids in determining an early diagnosis and/or prognosis.
Accordingly, a first aspect of the invention provides a method for the diagnosis and/or prognosis of an amyloid-associated disease in a subject, wherein the method comprises the steps of:
Preferably, the method further comprises the step of providing a diagnosis and/or prognosis of the amyloid-associated disease on the basis of the determination. Most preferably, the step of providing a diagnosis and/or prognosis of the amyloid-associated disease on the basis of the determination follows the step of determining the presence and/or amount and/or concentration and/or size of individual amyloid aggregates in the sample.
Accordingly, the invention provides a highly effective early and non-invasive method for the diagnosis and prognosis of amyloid-associated diseases in living patients, which is also applicable to following the effects of the treatment of amyloid-associated diseases. The methods are further useful for treating amyloid-associated diseases, as well as identifying and developing agents to treat amyloid-related diseases. Particularly useful for these applications is that the methods described herein can be used to routinely identify and characterise the levels of amyloid aggregates in the same patient repeatedly over time. The invention also provides kits corresponding to the methods described herein.
An additional advantage of the method of the invention is that as it is conducted on bodily fluid it is non-, or minimally, invasive, so less unpleasant for the patient. Additionally, as the method is able to detect early signs of the disease, it can be conducted on living patients and not just post-mortem. This also allows the method to be repeated multiple times, in order to monitor the progress of the disease in a living patient.
The term “amyloid-associated disease” would be known to one skilled in medicine. An amyloid-associated disease is sometimes referred to as amyloidosis, and encompasses diseases in which amyloids accumulate in a subject. Amyloids are accumulations of a number of copies of particular peptides or particular proteins that stick together to form aggregates, which in turn combine to form fibrils. Hence, fibrils may be larger structures than aggregates. In the aggregate and/or fibril form, the peptides or proteins no longer have their physiological function. When the amyloid aggregates and fibrils accumulate in the tissues of the subject, they often disrupt the function of those tissues which can lead to the pathology of the amyloid-associated disease.
By “determining the presence and/or amount and/or concentration and/or size of individual amyloid aggregates”, we include that individual aggregates are determined. The determination does not involve determining the total amount or concentration of aggregates, but instead the presence and/or amount and/or concentration and/or size of individual amyloid aggregates within the total present. Accordingly, the claimed method differs from current methods, if and where available, in which only the total amount and/or large groups of amyloid fibrils are detected. As discussed herein, the “individual amyloid aggregates” are early biomarkers for amyloid-associated diseases, which allows for an early diagnosis and/or prognosis.
By “individual amyloid aggregates” we include accumulations of peptides or proteins, which are, or form, structures associated with the amyloid-associated disease. The term “individual amyloid aggregates” can be referred to as structured amyloid aggregates, which include amyloid aggregates that have a defined secondary structure, such as amyloid aggregates that comprise β-pleated sheets. The term “amyloid aggregate” is used to refer to any peptide or protein that can form structures associated with an amyloid-associated disease. Whilst that term is sometimes used in the art to refer to amyloid R peptide (which form structures associated with Alzheimer's disease), for the purposes of the present application, it is not limited to that peptide.
A “peptide” is generally considered to be a molecule comprising two or more amino acids, but not more than about 50 amino acids; for example: about three to about 50 amino acids; about four to about 50 amino acids; about five to about 50 amino acids; about six to about 50 amino acids; about seven to about 50 amino acids; about eight to about 50 amino acids; about nine to about 50 amino acids; about ten to about 50 amino acids; about 20 to about 50 amino acids; about 30 to about 50 amino acids; or about 40 to about 50 amino acids.
A “protein” is generally considered to be a molecule comprising about 50 or more amino acids; for example: about 60 or more; about 70 or more; about 80 or more; about 90 or more; about 100 or more; about 150 or more; about 200 or more; about 250 or more; about 300 or more; about 350 or more; about 400 or more; about 450 or more; or about 500 or more amino acids.
In one embodiment, the individual amyloid aggregates do not comprise amorphous amyloid aggregates. By “amorphous amyloid aggregates”, we include amyloid aggregates that do not have a well-defined secondary structure, such as amyloid aggregates that do not have a su-pleated sheet structure.
The invention generally relates to the detection of individual amyloid aggregates, and the characterisation of the individual amyloid aggregates. That detection and characterisation is described as “determining the presence and/or amount and/or concentration and/or size of individual amyloid aggregates in the sample”, and by that we include “identifying and/or calculating and/or detecting” the presence and/or amount and/or concentration and/or size of individual amyloid aggregates in the sample.
By “determining the presence of individual amyloid aggregates in the sample”, we include determining whether individual amyloid aggregates are present in the sample or not. As discussed further below, where the sample is a bodily fluid from a patient and if individual amyloid aggregates are present in the bodily fluid of the patient, then that patient is diagnosed with an amyloid-associated disease.
By “determining the amount of individual amyloid aggregates in the sample”, we include determining the total number of the individual amyloid aggregates in the sample. As discussed further below, where the sample is a bodily fluid from a patient, the higher the amount of individual amyloid aggregates in the bodily fluid of the patient, the worse the diagnosis and/or prognosis of the amyloid-associated disease.
By “determining the size of individual amyloid aggregates in the sample”, we include determining the number of peptides in the individual amyloid aggregates, and/or determining the dimensions of the individual amyloid aggregates in the sample, and/or determining the measurements of the individual amyloid aggregates in the sample; and/or determining the molecular weight of the individual amyloid aggregates in the sample. As discussed further below, where the sample is a bodily fluid from a patient, the larger the size of individual amyloid aggregates in the bodily fluid of the patient, the worse the diagnosis and/or prognosis of the amyloid-associated disease.
By “determining the concentration of individual amyloid aggregates in the sample”, we include identifying the relative amount of the individual amyloid aggregates in the sample. As discussed further below, where the sample is a bodily fluid from a patient, the higher the concentration of individual amyloid aggregates in the bodily fluid of the patient, the worse the diagnosis and/or prognosis of the amyloid-associated disease.
In a preferred embodiment of the first aspect of the invention, the method comprises the steps in the order of:
An additional embodiment relates to a method for the diagnosis and/or prognosis of an amyloid-associated disease in a subject, wherein the method comprises the steps of:
The terms “diagnosis” and “prognosis” would be known to one skilled in medicine.
By “diagnosis” we include that the method can be used to identify whether the subject has an amyloid-associated disease. By “prognosis” we include that the method can be used to identify how quickly the amyloid-associated disease is likely to progress in the subject, and/or how severe the symptoms and/or signs of the amyloid-associated disease are likely to become in the subject, and/or if the subject is likely to die from the amyloid-associated disease, and/or how soon the subject is likely to die from the amyloid-associated disease, and/or an assessment of the effectiveness of a treatment for the amyloid-associated disease that has already been administered to, or practised on, the subject, and/or the likely effectiveness of a treatment for the amyloid-associated disease that might be administered to, or practised on, the subject in future. To put another way, by prognosis we include following the effectiveness of a treatment for an amyloid-associated disease that has previously been administered to, or practised on, the subject.
Treatments for amyloid-associated diseases, if and where available, would be known to one skilled in medicine.
By “treatment”, we include a treatment that is intended to cure the amyloid-associated disease, and/or a treatment that is intended to reduce the number and/or severity of the symptoms and/or signs of the amyloid-associated disease, and/or a palliative treatment, and/or an experimental treatment, and/or a physical therapy. Specific treatments for amyloid-associated diseases are discussed herein.
In one embodiment, the bodily fluid is one or more from the group comprising or consisting of: blood and/or cerebrospinal fluid (CSF) and/or saliva and/or urine and/or synovial fluid and/or faeces. In a preferable embodiment, the bodily fluid comprises blood. In an alternative preferable embodiment, the bodily fluid comprises saliva. In a further alternative preferable embodiment, the bodily fluid comprises urine. In a further embodiment the bodily fluid is selected from blood plasma and/or blood serum. In a still further embodiment the bodily fluid is selected from blood serum. [A3] In an alternative embodiment bodily fluid comprises blood cells, specifically erythrocytes, leukocytes and thrombocytes. According to a further embodiment the blood cells may be lysated.
A particularly surprising development of the current invention is that it is possible to diagnose, or reach a prognosis for, an amyloid-associated disease using blood, urine, synovial fluid, faeces and/or saliva bodily fluid samples. Previously, studies have shown that using known methods it was not possible to diagnose the amyloid-associated disease Alzheimer's disease using a blood sample—in particular, as described herein (Oh et al., Neuromolecular medicine. 2008; 10(3):195-207 and Toledo et al., Alzheimer's research & therapy. 2013; 5(2):8). However, the problems identified in those previous methods are overcome in the present invention by detecting individual amyloid aggregates, as they have now been shown to be effective early biomarkers for amyloid-associated diseases. For urine, saliva, synovial fluid, faeces and CSF samples, it had not previously been suggested that detecting individual amyloid aggregates in those bodily fluids could be used in the diagnosis or prognosis of amyloid-associated diseases, such as Alzheimer's disease.[A4]
A particular advantage of the bodily fluids of urine, saliva, faeces and blood is that they can be provided from the subject using minimally invasive methods, with the provision of the urine, faeces and saliva samples not requiring the assistance of a medical professional.
It would be known to one skilled in medicine how a bodily fluid sample can be provided, for the purposes of the present invention. For example, a blood bodily fluid sample could be obtained by a medical professional, by removing blood from a vein using a needle.
In one embodiment, the blood sample is one or more from the group comprising or consisting of: whole blood; blood serum; blood plasma; blood cells: rythrocytes, leukocytes and/or thrombocytes[A5]; blood cell lysates.
Blood collected from a subject comprises inter alia blood cells suspended in blood plasma. The major types of blood cells are erythrocytes (red blood cells), leukocytes (white blood cells) and thrombocytes (platelets). According to an embodiment it may be expedient to separate the blood cells from blood and thereby obtain the blood plasma. Furthermore, the clotting factors may be removed from the blood plasma thereby receiving the blood serum. Whole blood can be fractionated by centrifugation. By centrifugation the whole blood is fractioned into blood plasma and erythrocytes and in between these two fractions a thin layer of leukocytes and platelets. While whole blood can be used directly as the sample to be analysed it might be preferable in certain cases to remove the blood cells and used the blood plasma as the sample for the analysis. Further, it may also be advisable to remove any clotting factor from the blood plasma and use the blood serum (as the sample) for analysis.
By “cell lysates”, we include erythrocyte, leukocytes and/or thrombocyte (i.e. platelet) cell lysates.
Particular components of blood (such as erythrocytes, leukocytes and/or thrombocytes) can be isolated using methods known in art, such as by blood fractionation which involves centrifuging the whole blood sample.
In some circumstances, FAD enzymes and lipopigments and NADH enzymes and lipopigments may lead to a reduction in the sensitivity of the method, as they autofluoresce. Accordingly, there might be some advantages in removing these molecules from the bodily fluid sample before using the method.
In one embodiment, the bodily fluid sample does not comprise one or more from the group comprising or consisting of: flavin adenine dinucleotide (FAD) enzymes and/or FAD lipopigments; and/or pyridinic (NADH) enzymes and/or NADH lipopigments.
In a particular embodiment, the blood sample does not comprise one or more from the group comprising or consisting of: flavin adenine dinucleotide (FAD) enzymes and/or FAD lipopigments; and/or pyridinic (NADH) enzymes and/or NADH lipopigments.
In a particular embodiment, the CSF sample does not comprise one or more from the group comprising or consisting of: flavin adenine dinucleotide (FAD) enzymes and/or FAD lipopigments; and/or pyridinic (NADH) enzymes and/or NADH lipopigments.
How to remove flavin adenine dinucleotide (FAD) enzymes, FAD lipopigments, pyridinic (NADH) enzymes, and/or NADH lipopigments from the sample would be known to one skilled in chemistry. For example, FAD is completely hydrolyzed to FMN in 5% trichloroacetic within 20 hours at 37° C., as described in Burch H B, Bessey O A, Lowry O H. Fluorometric Measurements of Riboflavin and its Natural Derivatives in Small Quantities of Blood Serum and Cells. J Biol Chem. 1948 175(1):457-470.
In one embodiment, the individual amyloid aggregate is selected from the group comprising: an amyloid oligomer; an amyloid nano-aggregate; and/or an amyloid senile aggregate; and/or an amyloid fibril; and/or an amyloid protofibril. Preferably, the individual amyloid aggregate is an amyloid nano-aggregate. These amyloid aggregates are formed by the cross-reacting of peptides and/or proteins susceptible to forming amyloid aggregates in the subject.
The amyloid nano-aggregate can be referred to as an amyloid nano-plaque or a structured amyloid nano-plaque, such as those that comprise a β-pleated sheet secondary structure. The term “amyloid nano-aggregate” describes that comprise higher numbers of peptides than dimers and trimers (and which can be described as structured supramolecular assemblies), but which have not yet formed amyloid fibrils or senile amyloid aggregates (which can be known as senile plaques). These distinctions would be understood by one skilled in biology or chemistry.
Amyloid oligomers and amyloid protofibrils are soluble peptide assemblies observed during the growth of amyloid fibrils. They contain a significant amount of β-sheet structure so are able to bind ThT, so can give rise to ThT fluorescence. Whilst amyloid oligomers and amyloid protofibrils comprise structurally heterogeneous supramolecular assemblies, it is typically regarded that oligomers are smaller and precede protofibril formation. Additionally, oligomers are regarded to assume more often globular rather than elongated and ring-like shapes that is characteristic of protofibrils. The degree of structural order in protofibrils is intermediate between that found in oligomers and in fibrils. The molecular weight of oligomers and protofibrils is in the range from 40-3000 kDa (Nichols et al. Biochemistry. 2015 54 (13): 2193-2204; Byron & Vestergaard Curr. Opin. Struct. Biol. 2015 35: 76-86.).
Amyloid protofibrils are elongated, single-chain like supramolecular assemblies of elongated or ring-like shape that grow and consolidate into amyloid fibrils. Protofibrils can have diameters ranging from 2-10 nm and are about 100-200 nm long. Amyloid fibrils are elongated, multiple-chain like assemblies of molecules with high length-to-diameter ratio, and a diameter ranging from 10-100 nm. Fibrils give rise to senile plaques, which are heterogeneous structures consisting of intricately interwoven mature fibrils (Nichols M R, Colvin B A, Hood E A, Paranjape G S, Osborn D C, Terrill-Usery S E. Biophysical comparison of soluble amyloid-β(1-42) protofibrils, oligomers, and protofilaments. Biochemistry. 2015 54 (13): 2193-2204. doi: 10.1021/bi500957g; Byron 0, Vestergaard B. Protein-protein interactions: a supra-structural phenomenon demanding trans-disciplinary biophysical approaches. Curr. Opin. Struct. Biol. 2015 35: 76-86; Relini A. Amyloid like protofibrils with different physical properties. Bio-nanoimaging: Protein Misfolding and Aggregation, Vladimir Uversky and Yuri Lyubchenko Ed. 2013 Technology & Engineering.)
In one embodiment, the individual amyloid aggregates comprise one or more beta (β)-sheets (such as a β-pleated sheet). As would be known to one skilled in biology or chemistry, a beta (β)-sheet is a secondary protein structure, which is generally a twisted stretch of amino acids. The association of two or more beta (β)-sheets is often a mediator of peptide accumulation, such as to form individual amyloid aggregates relevant to amyloid-associated diseases.
In one embodiment, the individual amyloid aggregates can be bound by 2-(4-(Dimethylamino)phenyl)-3,6-dimethylbenzo[d]thiazol-3-ium chloride (Thioflavin T (ThT)) (Groenning, M. (2010) Binding mode of Thioflavin T and other molecular probes in the context of amyloid fibrils-current status. Journal of Chemical Biology 3, 1-18). ThT is a molecule that binds beta (β)-sheet structures, and is available from Sigma-Aldrich.
In one embodiment, the individual amyloid aggregate comprises about 20 or more peptides or proteins; for example: about 30 or more; about 40 or more; about 50 or more; about 60 or more; about 70 or more; about 80 or more; about 90 or more; about 100 or more; about 200 or more; about 300 or more; about 400 or more; about 500 or more; about 600 or more; about 700 or more; about 800 or more; about 900 or more; about 1,000 or more; about 2,000 or more; about 3,000 or more; about 4,000 or more; about 5,000 or more; about 6,000 or more; about 7,000 or more; about 8,000 or more; about 9,000 or more; about 10,000 or more; about 20,000 or more; about 30,000 or more; about 40,000 or more; about 50,000 or more; about 60,000 or more; about 70,000 or more; about 80,000 or more; about 90,000 or more; about 100,000 or more; about 200,000 or more; about 300,000 or more; about 400,000 or more; about 500,000 or more; or about 1,000,000 or more peptides or proteins, preferably about 40 or more peptides or proteins.
As will be appreciated, the amyloid nano-aggregate can comprise about 20 proteins or peptides to 100,000 proteins or peptides, such as: about 30 proteins or peptides to 100,000 proteins or peptides; about 40 proteins or peptides to 100,000 proteins or peptides; about 50 proteins or peptides to 100,000 proteins or peptides; about 60 proteins or peptides to 100,000 proteins or peptides; about 70 proteins or peptides to 100,000 proteins or peptides; about 80 proteins or peptides to 100,000 proteins or peptides; about 90 proteins or peptides to 100,000 proteins or peptides; about 100 proteins or peptides to 100,000 proteins or peptides; about 200 proteins or peptides to 100,000 proteins or peptides; about 300 proteins or peptides to 100,000 proteins or peptides; about 400 proteins or peptides to 100,000 proteins or peptides; about 500 proteins or peptides to 100,000 proteins or peptides; about 600 proteins or peptides to 100,000 proteins or peptides; about 700 proteins or peptides to 100,000 proteins or peptides; about 800 proteins or peptides to 100,000 proteins or peptides; about 900 proteins or peptides to 100,000 proteins or peptides; about 1,000 proteins or peptides to 100,000 proteins or peptides; about 2,000 proteins or peptides to 100,000 proteins or peptides; about 3,000 proteins or peptides to 100,000 proteins or peptides; about 4,000 proteins or peptides to 100,000 proteins or peptides; about 5,000 proteins or peptides to 100,000 proteins or peptides; about 6,000 proteins or peptides to 100,000 proteins or peptides; about 7,000 proteins or peptides to 100,000 proteins or peptides; about 8,000 proteins or peptides to 100,000 proteins or peptides; about 9,000 proteins or peptides to 100,000 proteins or peptides; about 10,000 proteins or peptides to 100,000 proteins or peptides; about 40 proteins or peptides to about 1,000 proteins or peptides; about 1,000 proteins or peptides to about 2,000 proteins or peptides; about 1,000 proteins or peptides to about 3,000 proteins or peptides; about 1,000 proteins or peptides to about 4,000 proteins or peptides; about 1,000 proteins or peptides to about 5,000 proteins or peptides; about 1,000 proteins or peptides to about 6,000 proteins or peptides; about 1,000 proteins or peptides to about 7,000 proteins or peptides; about 1,000 proteins or peptides to about 8,000 proteins or peptides; about 1,000 proteins or peptides to about 8,000 proteins or peptides; or about 1,000 proteins or peptides to about 10,000 proteins or peptides.
As will be appreciated, amyloid fibrils can comprise more than 100,000 peptides or proteins to 1,000,000 peptides or proteins, such as: about 200,000 peptides or proteins to 1,000,000 peptides or proteins; about 300,000 peptides or proteins to 1,000,000 peptides or proteins; about 400,000 peptides or proteins to 1,000,000 peptides or proteins; or about 500,000 peptides or proteins to 1,000,000 peptides or proteins.
As will be appreciated, senile amyloid aggregates can comprise more than 1,000,000 peptides or proteins.
In one embodiment, the method further comprises the step of adding a detection agent to the sample.
Preferably, the step of “adding a detection agent to the sample” precedes the step of “determining the presence and/or amount and/or concentration and/or size of individual amyloid aggregates in the sample”.
More preferably, the step of “adding a detection agent to the sample” precedes the step of “determining the presence and/or amount and/or concentration and/or size of individual amyloid aggregates in the sample” and follows the step of “providing a sample of bodily fluid from the subject”.
In one embodiment, the detection agent binds to and/or associates with and/or reacts with individual amyloid aggregates. Preferably, the detection agent binds to and/or associates with and/or reacts with individual amyloid aggregates; leading the detection agent to become detectable and/or measurable, or to become more easily detectable and/or more easily measurable and/or to produce a higher measurable output.
By “the detection agent binds to individual amyloid aggregates”, we include that the detection agent forms a molecular bond (such as covalent bond) with the individual amyloid aggregates.
By “the detection agent associates with individual amyloid aggregates”, we include that the detection agent forms a non-covalent interaction (such as an electrostatic interaction, and/or a pi (π)-interaction, and/or a van der Waals interaction, and/or a hydrophobic interaction) with the individual amyloid aggregates.
By “the detection agent reacts with individual amyloid aggregates”, we include that the detection agent does not necessarily need to be bound to or associated with the individual amyloid aggregates and/or in proximity to the individual amyloid aggregates in order to function.
By “leading the detection agent to become detectable”, we include that when the detection agent is bound to and/or associated with and/or reacting in the presence of individual amyloid aggregates, it is possible to identify or detect the presence of the detection agent. To put another way, if the sample comprised no individual amyloid aggregates it would not be possible to identify or detect the presence of the detection agent, using the method described herein.
By “leading the detection agent to become measurable”, we include that when the detection agent is bound to and/or associated with and/or reacting in the presence of individual amyloid aggregates, it is possible to quantify the amount of detection agent and/or assess the relative amount or relative level of the detection agent. The amount or level of the detection agent can be used to quantify the amount and/or concentration and/or size of the individual amyloid aggregates.
In one embodiment, the determination comprises the detection and/or measurement of the detection agent. For the avoidance of doubt, this determination can occur as part of the step of: “determining the presence and/or amount and/or concentration and/or size of individual amyloid aggregates in the sample”.
By “detection of the detection agent”, we include that the presence of the detection agent is detected or identified. By “measurement of the detection agent”, we include quantifying the amount of detection agent and/or assessing the relative amount or relative level of the detection agent. The amount or level of the detection agent can be used to quantify the amount and/or concentration and/or size of the individual amyloid aggregates.
In one embodiment, the detection agent binds to and/or associates with and/or reacts with individual amyloid aggregates that comprise one or more beta β-sheets.
In one embodiment, the detection agent comprises a fluorescent moiety and/or a bioluminescent moiety. One skilled in biology and/or chemistry would understand what is encompassed by the terms “fluorescent moiety” and “bioluminescent moiety”.
In one embodiment, the detection agent comprises a fluorescent moiety and produces or releases fluorescence when it binds to and/or associates with and/or reacts with individual amyloid aggregates.
In a preferred embodiment, a detection agent comprising a fluorescent agent is added, and the measurement and/or detection of fluorescence from the detection agent is used to determine the presence and/or amount and/or concentration and/or size of individual amyloid aggregates in the sample.
In a further alternative embodiment, the detection agent comprises a bioluminescence moiety and produces or releases luminescence when it binds to and/or associates with and/or reacts with individual amyloid aggregates.
In one embodiment, the detection agent is one or more from the group comprising or consisting of: Thioflavin T (ThT) and/or ARCAM1 and/or pentameric formyl thiophene acetic acid (pFTAA) and/or 4-(dicyanovinyl)-julolidine (DCVJ) and/or 1-amino-8-naphtalene sulphonate (ANS) and/or bis-ANS and/or 2-[N-bis-(3-dimethylaminopropyl)-amino]-4-[2,3-dihydro-3-methyl-(benzo-1,3-thiazol-2-yl)-methylidene]-1-phenyl-quinolinium (PicoGreen).
Preferably, the detection agent comprises Thioflavin T (ThT) and/or ARCAM1. More preferably, the detection agent comprises Thioflavin T (ThT).
ARCAM1 is an aryl cyano amide, which binds to beta (β)-sheets (Guan et al., 2015, ACS Chemical Neuroscience, 6: 1503-1508).
In one embodiment, the detection agent is one or more from the group comprising or consisting of: a variant or derivative or modified Thioflavin T (ThT) and/or ARCAM1 and/or pentameric formyl thiophene acetic acid (pFTAA) and/or 4-(dicyanovinyl)-julolidine (DCVJ) and/or 1-amino-8-naphtalene sulphonate (ANS) and/or bis-ANS and/or 2-[N-bis-(3-dimethylaminopropyl)-amino]-4-[2,3-dihydro-3-methyl-(benzo-1,3-thiazol-2-yl)-methylidene]-1-phenyl-quinolinium (PicoGreen).
In one embodiment, the amyloid-associated disease is associated with the individual amyloid aggregates, preferably individual amyloid aggregates comprising one or more beta (β)-sheets.
By “the amyloid-associated disease is associated with the individual amyloid aggregates”, we include that the amyloid-associated disease is caused or worsened by the presence and/or accumulation of the individual amyloid aggregates.
In one embodiment, the amyloid-associated disease is one or more selected from the group comprising: Alzheimer's disease; and/or Parkinson's disease; and/or Huntington's disease; and/or amyotrophic lateral sclerosis (ALS); and/or type 2 diabetes; and/or systemic amyloidosis; and/or a prion disease (such as Creutzfeldt-Jakob disease (CJD)); and/or amyloid light-chain amyloidosis; and/or multiple myeloma; and/or inflammation; and/or kidney failure; and/or Leukocyte Chemotactic Factor 2 (LECT2) amyloidosis; and/or transthyretin-related hereditary amyloidosis with polyneuropathy (also known as Familial Amyloid Polyneuropathy (FAP) or Skelleftesjukan); and/or haemodialysis-associated amyloidosis; and/or Cerebral amyloid angiopathy; and/or familial visceral amyloidosis; and/or primary cutaneous amyloidosis; and/or cerebral amyloid angiopathy; and/or prolactinoma; and/or familial corneal amyloidosis; and/or senile amyloid of the atria of heart; and/or medullary carcinoma of the thyroid; and/or pharmaceutical insulin-derived amyloidosis. The aforementioned diseases would be known to one skilled in medicine.
In a preferred embodiment, the amyloid-associated disease is Alzheimer's disease.
In an alternative preferred embodiment, the amyloid-associated disease is Parkinson's disease.
In a further alternative embodiment, the amyloid-associated disease is Huntington's disease.
In a further alternative embodiment, the amyloid-associated disease is amyotrophic lateral sclerosis (ALS).
Alzheimer's disease is a chronic neurodegenerative disease, which slowly develops over time and for which there is usually of life expectancy of three to nine years following diagnosis. However, the diagnosis of Alzheimer's is often very delayed due to a lack of reliable earlier markers of the disease. Currently, diagnosis relies on a patient exhibiting behavioural symptoms which are often quite subtle and difficult to observe, such as short term memory of loss. Based on the current methods, it is also quite difficult to provide a prognosis for how quickly the patient is likely to deteriorate. Therefore, there is a particular need for an effective method to diagnose Alzheimer's disease early, and to be able to provide a reliable prognosis. The current invention solves this problem by detecting the individual amyloid aggregates, which the inventors have demonstrated provide an effective early diagnostic marker, and a reliable marker by which to assess prognosis.
Similarly, Parkinson's disease Huntington's disease and ALS are chronic diseases that are diagnosed using behavioural symptoms, and which lack effective early diagnostic and prognostic markers. As with all the amyloid-associated diseases described herein, there is a particular need for effective methods to diagnose Parkinson's disease, Huntington's disease and ALS early, and to be able to provide a reliable prognosis. The current invention solves this problem by detecting the individual amyloid aggregates, which the inventors have demonstrated provide an effective early diagnostic marker, and a reliable marker by which to assess prognosis.
In one embodiment, the Alzheimer's disease is selected from the group comprising: Subjective Cognitive Impairment; Mild Cognitive impairment; Alzheimer's disease; and Alzheimer's disease with vascular dementia. These types of Alzheimer's disease would be known to one skilled in medicine.
Subjective Cognitive Impairment (SCI), also known as subjective memory disorder, relates to a subject having a worsening of their cognitive abilities, including memory impairment, but where that worsening cannot be verified by standard tests. In the absence of objective cognitive dysfunction or depression, SCI is sometimes regarded to be a common transitional stage in normal aging.
Mild Cognitive Impairment (MCI), also known as incipient dementia or isolated memory impairment, is a brain function syndrome involving the onset and evolution of cognitive impairments beyond those expected based on the age of the subject, but which are not significant enough to interfere with their daily activities. MCI may occur as a transitional stage between normal aging and dementia. The cause of MCI is unknown and there is therefore no prevention and no treatment. In the US, MCI has been designated the designated as G31.84 in the American ICD-10-CM medical diagnosis code.
Alzheimer's disease (AD) is a progressive neurodegenerative disease that is characterised by irreversible destruction of nerve cells and neural connections in the cerebral cortex of the brain and by a significant loss of brain mass. As a result, dementia symptoms occur that worsen over time. Eventually, the disease becomes severe enough to render the subject incapable of performing daily tasks and unable of living without constant care. While much is known about underlying biochemical changes, the cause of AD is still not known and there is presently no cure for AD. As discussed herein, there are also no reliable biomarkers for early AD diagnosis and no reliable disease progression biomarkers. Therapeutic agents commonly used for AD treatment slow disease progression and alleviate some symptoms and/or signs, but don't cure the patient.
Alzheimer's disease with vascular dementia also known as mixed dementia is an often encountered comorbidity that includes both AD and vascular dementia, i.e. cognitive decay caused by reduced blood supply to the brain. In Alzheimer's disease with vascular dementia symptoms of dementia, such as memory and language problems, loss of the ability to focus and pay attention, difficulties with reasoning and judgement, trouble with visual perception etc. are potentiated due to dual causes.
In one embodiment, the individual amyloid aggregates comprise one or more peptide or protein selected from the list comprising: amyloid beta (β) peptide (β peptide) (such as: beta (β)40 and/or beta (β)42 and/or beta (β)43); and/or amyloid light chain; and/or serum amyloid A protein (SAA); and/or Leukocyte Chemotactic Factor 2 (LECT2); and/or transthyretin; and/or beta (β)2 microglobulin; and/or amylin; and/or prion protein; and/or cystatin C (CST3); and/or apolipoprotein A1 (APOA1); and/or fibrinogen alpha chain (FGA); and/or lysozyme (LYZ); and/or oncostatin-M specific receptor subunit beta (OSMR); and/or integral membrane protein 2B (ITM2B); and/or prolactin; and/or keratoepithelin; and/or atrial natriuretic factor; and/or calcitonin; and/or Huntingtin; and/or alpha (α)-Synuclein; and/or insulin.
In one embodiment, the amyloid-associated disease is Alzheimer's disease, and the individual amyloid aggregates comprise an amyloid beta (β) peptide, for example 040 and/or 042 and/or 043. In a preferred embodiment, the amyloid-associated disease is Alzheimer's disease, and the individual amyloid aggregates comprise 040 and 042. In an alternative preferred embodiment, the amyloid-associated disease is Alzheimer's disease, and the individual amyloid aggregates comprise 040. In a further alternative preferred embodiment, the amyloid-associated disease is Alzheimer's disease, and the individual amyloid aggregates comprise 042. In an additional alternative embodiment, the amyloid-associated disease is Alzheimer's disease, and the individual amyloid aggregates comprise 040 and/or 042 alone or in co-aggregates with other peptides and/or proteins.
In various embodiments of the invention:
It will be appreciated that whilst an amyloid aggregate might primarily comprise a single type of peptide or protein (for example, when the amyloid-associated disease is amyloid light chain amyloidosis, the individual amyloid aggregates may primarily comprise amyloid light chain), in some circumstances the amyloid aggregate may also comprise additional types of peptide and/or protein.
In one embodiment, the (in particular, wherein the amyloid-associated disease is Alzheimer's disease) method further comprises the steps of:
Tau is a marker of neuro degeneration, can be used in the diagnosis and prognosis of Alzheimer's disease, and can be detected in bodily fluids, such as cerebrospinal fluid (CSF), serum, saliva and urine (Hei-Nga Chan, Di Xu, See-Lok Ho, Man Shing Wong ORCID logo* and Hung-Wing Li, Ultra-sensitive detection of protein biomarkers for diagnosis of Alzheimer's disease. Chem. Sci., 2017, 8, 4012-4018). Combining the identification of biomarkers generally can improve methods of diagnosis and prognosis, as could be the case with combining the methods described herein relating to individual amyloid aggregates, and methods relating to Tau.
In one embodiment, the Tau protein is phosphorylated Tau protein.
In one embodiment in which the presence and/or amount and/or concentration and/or size of Tau protein is determined, the method further comprises the step of adding a further detection agent that binds to and/or associates with and/or reacts in the presence of Tau, such as pentameric formyl thiophene acetic acid (pFTAA).
Methods of detecting of Tau using pFTAA were described by Brelstaff and colleagues (Brelstaff et al. Front Neurosci. 2015 May 29; 9:184). Additional guidance on detecting Tau protein can be found in Chan et al., 2017 (Hei-Nga Chan, Di Xu, See-Lok Ho, Man Shing Wong ORCID logo* and Hung-Wing Li, Ultra-sensitive detection of protein biomarkers for diagnosis of Alzheimer's disease. Chem. Sci., 2017, 8, 4012-4018).
In one embodiment, determining the presence and/or amount and/or concentration and/or size of individual amyloid aggregates is at an individual amyloid aggregate resolution.
By “individual amyloid aggregate resolution”, we include that the method detects and/or measures single amyloid aggregates in the sample (i.e. the method does not simultaneously detect and/or measure a number of individual amyloid aggregates in the sample), and/or the method detects and/or measures each individual amyloid aggregate in the sample. Alternatively, “individual amyloid aggregate resolution” may be referred to as a “single particle resolution” or “single molecule resolution”.
In one embodiment, determining the presence and/or amount and/or concentration and/or size of individual amyloid aggregates comprises time-resolved detection. Put another way, determining the presence and/or amount and/or concentration and/or size of individual amyloid aggregates is conducted using time-resolved detection. “Time-resolved detection” methods would be well known to those skilled in chemistry, and are described in detail in the Examples herein. As discussed in the Examples, time-resolved detection is particularly effective for use with the methods described herein.
In one embodiment the method encompasses an analysis means based on fluorescence correlation spectroscopy, where the number of observed molecules/particles/aggregates in an observation volume element is sufficiently low to enable individual molecules/particles/aggregates substantially to contribute to the measured signal. The number of molecules/particles/aggregates in the volume element should preferably be below about 1000, below about 500, below about 100, such as below about 50, below about 251[A9]. The number of observed molecules/particles/aggregates in a volume element is inter alia a function of the size (volume) of the observation volume element and the concentration of the aggregates in the solution. As the number of molecules/particles/aggregates in the observation volume element increases, the contribution of individual aggregates to a measured signal decreases. At a high number of aggregates in the volume element, the correlation of an individual aggregate to a measured signal is low and eventually goes towards zero. If, however, the number of molecules/particles/aggregates is low, the passage of individual molecules/particles/aggregates through the observation volume element is being observed. In this case, the measured signal may therefore be referred to as a single event occurrence (seo).
It is also advantageous that the aggregates have a high fluorescent yield, which implies that it is preferred to have a detection agent that is capable of associating with individual amyloid aggregates of interest to yield an inclusion compound with high fluorescent yield whilst the detection compound is non/weakly fluorescent when on its own. A detection agent with a high fluorescent yield is capable of providing a high number of photons when reverting to a lower energy level. It is further beneficial for the fluorescence correlation spectroscopy-based analysis to include a detector having single-photon sensitivity.
According to an embodiment there is no need for amplification of any amyloidal compound such as amyloid peptide (protein), amyloid monomer, amyloid multimer, amyloid aggregate, amyloid macro aggregate, before the analysis. There is specifically no need for further amplification of amyloidal entities if an analysis technology is implemented providing single molecule (particle) resolution. Hence, there is no need for the implementation of an amyloid amplification step in the method of the present invention comprising fluorescent spectroscopy analysis, such as single molecule resolution fluorescent spectroscopy.
According to yet a further embodiment the method does not necessitate the use of non-target amyloid molecules/peptides/proteins/aggregates (amyloid entities) or the inclusion of a step comprising mixing target amyloid molecules/peptides/proteins/aggregates and non-target amyloid molecules/aggregates. Non-target amyloid entities include any amyloid entities not stemming from the body fluid to be analysed or manipulated amyloid entities from the body fluid to be analysed. Examples of non-target amyloid entities include recombinantly formed amyloid entities or amyloid entities derived from pathological depositions (which may originate from the amyloid entities found in the body fluid to be analysed). The mixture of non-target and target amyloid entities induces agglomeration (polymerisation) amplifying the amount of aggregated amyloid.
Hence, an embodiment relates to a method for the diagnosis and/or prognosis of an amyloid-associated disease in a subject, wherein the method comprises the steps of:
In time-resolved detection, the step of “determining the presence and/or amount and/or concentration and/or size of individual amyloid aggregates” is not undertaken on the whole sample simultaneously. Instead, a fraction of the sample is measured at a time with numerous measurements of fractions of the sample being taken over a unit of time. In some embodiments, the fraction of the sample being measured is the “observation volume element”, as described below. When using time-resolved detection only individual amyloid aggregates that are present within the fraction of the sample are measured and/or detected. Accordingly, the presence and/or amount and/or concentration and/or size of individual amyloid aggregates is determined based on the frequency of sample fractions in which individual amyloid aggregates are detected and/or measured, and/or based on the characteristics of those individual amyloid aggregates. As would be appreciated, “time-resolved detection” could be defined as photon counting with sub-microsecond resolution.
Accordingly, in one embodiment the step of “determining the presence and/or amount and/or concentration and/or size of individual amyloid aggregates in the sample” comprises determining the frequency (such as the frequency of occurrence) of individual amyloid aggregates in the sample (such as in fractions of a sample), where the method is conducted using time-resolved detection.
In this embodiment, the higher the frequency of the individual amyloid aggregates, the higher the amount and/or concentration of the individual amyloid aggregates. The concepts of measuring frequency are explained herein (in particular in the Examples), and are applicable to each of the aspects of the invention described herein.
In a further embodiment determining the presence and/or amount and/or concentration and/or size of individual amyloid aggregates in the sample comprises determining the frequency of individual amyloid aggregates in a unit of time.
In some embodiments, the frequency of individual amyloid aggregates is referred to as the frequency of single event occurrences (fSEO). The relevance of single event occurrence (fSEO) to the diagnosis and/or prognosis of the amyloid-associated disease is exemplified in Table 1. A single event occurrence equates to the detection of an individual amyloid aggregate. In one embodiment, the frequency of single event occurrence (fSEO) can be proportional to the concentration of individual amyloid aggregates. In a related embodiment, the frequency of single event occurrences (fSEO) is calculated as the average number of single event occurrences per unit of time.
In one embodiment, the unit of time is about 0.05 microseconds (μs) or more; for example, about 0.1 μs or more; about 0.15 μs or more; about 0.2 μs or more; about 0.25 μs or more; about 0.3 μs or more; about 0.35 μs or more; about 0.4 μs or more; about 0.45 μs or more; about 0.5 μs or more; about 0.6 μs or more; about 0.7 μs or more; about 0.8 μs or more; about 0.9 μs or more; about 1 μs or more; about 1.5 us or more; about 2 μs or more; about 2.5 us or more; about 3 μs or more; about 4 us or more; about 5 us or more; about 6 μs or more; about 7 μs or more; about 8 μs or more; about 9 μs or more; about 10 μs or more; about 20 μs or more; about 30 μs or more; about 40 μs or more; about 50 μs or more; about 60 μs or more; about 70 μs or more; about 80 μs or more; about 90 μs or more; about 0.1 millisecond or more; about 0.2 millisecond or more; about 0.3 millisecond or more; about 0.4 millisecond or more; about 0.5 millisecond or more; about 0.6 millisecond or more; about 0.7 millisecond or more; about 0.8 millisecond or more; about 0.9 millisecond or more; about 1 millisecond or more; about 2 milliseconds or more; about 3 milliseconds or more; about 4 milliseconds or more; about 5 milliseconds or more; about 6 milliseconds or more; about 7 milliseconds or more; about 8 milliseconds or more; about 9 milliseconds or more; about 10 milliseconds or more; about 20 milliseconds or more; about 30 milliseconds or more; about 40 milliseconds or more; about 50 milliseconds or more; about 60 milliseconds or more; about 70 milliseconds or more; about 80 milliseconds or more; about 90 milliseconds or more; about 0.1 second or more; about 0.2 second or more; about 0.3 second or more; about 0.4 second or more; about 0.5 second or more; about 0.6 second or more; about 0.7 second or more; about 0.8 second or more; about 0.9 second or more; about 1 second or more; about 2 seconds or more; about 3 seconds or more; about 4 second or more; about 5 seconds or more; about 6 seconds or more; about 7 seconds or more; about 8 seconds or more; about 9 seconds or more; about 10 seconds or more; about 20 seconds or more; about 30 seconds or more; about 40 seconds or more; about 50 seconds or more; about 60 seconds or more; about 120 seconds or more; about 180 seconds or more; about 240 seconds or more; about 300 seconds or more; about 360 seconds or more; about 420 seconds or more; about 480 seconds or more; about 540 seconds or more; about 600 seconds or more; about 1200 seconds or more; about 1800 seconds or more; about 2400 seconds or more; about 3000 seconds or more; or about 3600 seconds or more, preferably about 0.2 μs or more or about 3,000 seconds or more.
In one embodiment, a diagnosis and/or prognosis of the amyloid-associated disease is provided if the frequency of individual amyloid aggregates (such as the frequency of the single event occurrence (fSEO)) is about 0.1 or more; for example: about 0.2 or more; about 0.3 or more; about 0.4 or more; about 0.5 or more; about 0.6 or more; about 0.7 or more; about 0.8 or more; about 0.9 or more; about 1 or more; about 1.1 or more; about 1.2 or more; about 1.3 or more; about 1.4 or more; about 1.5 or more; about 1.6 or more; about 1.7 or more; about 1.8 or more; about 1.9 or more; about 2 or more; about 2.2 or more; about 2.4 or more; about 2.6 or more; about 2.8 or more; about 3 or more; about 3.2 or more; about 3.4 or more; about 3.6 or more; about 3.8 or more; about 4 or more; about 4.2 or more; about 4.4 or more; about 4.6 or more; about 4.8 or more; about 5 or more; about 5.5 or more; about 6 or more; about 6.5 or more; about 7 or more; about 7.5 or more; about 8 or more; about 8.5 or more; about 9 or more; about 9.5 or more; or about 10 or more, preferably about 1.5 or more.
In a further embodiment, a diagnosis and/or prognosis of the amyloid-associated disease is provided if the frequency of individual amyloid aggregates (such as the frequency of the single event occurrence (fSEO)) is about 0.1×10−3 s−1 or more; for example: about 0.2×10−3 s−1 or more; about 0.3×10−3 s−1 or more; about 0.4×10−3 s−1 or more; about 0.5×10−3 s−1 or more; about 0.6×10−3 s−1 or more; about 0.7×10−3 s−1 or more; about 0.8×10−3 s−1 or more; about 0.9×10−3 s−1 or more; about 1×10−3 s−1 or more; about 1.1×10−3 s−1 or more; about 1.2×10−3 s−1 or more; about 1.3×10−3 s−1 or more; about 1.4×10−3 s−1 or more; about 1.5×10−3 s−1 or more; about 1.6×10−3 s−1 or more; about 1.7×10−3 s−1 or more; about 1.8×10−3 s−1 or more; about 1.9×10−3 s−1 or more; about 2×10−3 s−1 or more; about 2.2×10−3 s−1 or more; about 2.4×10−3 s−1 or more; about 2.6×10−3 s−1 or more; about 2.8×10−3 s−1 or more; about 3×10−3 s−1 or more; about 3.2×10−3 s−1 or more; about 3.4×10−3 s−1 or more; about 3.6×10−3 s−1 or more; about 3.8×10−3 s−1 or more; about 4×10−3 s−1 or more; about 4.2×10−3 s−1 or more; about 4.4×10−3 s−1 or more; about 4.6×10−3 s−1 or more; about 4.8×10−3 s−1 or more; about 5×10−3 s−1 or more; about 5.5×10−3 s−1 or more; about 6×10−3 s−1 or more; about 6.5×10−3 s−1 or more; about 7×10−3 s−1 or more; about 7.5×10−3 s−1 or more; about 8×10−3 s−1 or more; about 8.5×10−3 s−1 or more; about 9×10−3 s−1 or more; about 9.5×10−3 s−1 or more; or about 10×10−3 s−1 or more, preferably about 1.5×10−3 s−1 or more.
In a preferred embodiment, determining the presence and/or amount and/or concentration and/or size of individual amyloid aggregates in the sample comprises determining the frequency of individual amyloid aggregates in a unit of time of about 50 minutes or more, and a diagnosis and/or prognosis of the amyloid-associated disease is provided if the frequency of single event occurrence (fSEO) is about 1.5 (such as 1.5×10−3 s−1) or more.
In one embodiment, the characteristics of a single event occurrence (fSEO) and the decay time, i.e. the diffusion time (τD) can be proportional to the amount and size of individual amyloid aggregates, respectively. By characteristics of a single event occurrence (fSEO), we include the signal (or intensity) of the single event occurrence. By characteristics of the decay time we include the intensity of the |diffusion[A10] time (τD).
From the distribution of diffusion times, a profile of molecules/particles/aggregates sizes can be determined for each individual. The distribution of sizes may reflect on the disease state and provide information about disease prognosis. [A11]
In one embodiment, a diagnosis and/or prognosis of the amyloid-associated disease is provided if the decay time of the single event occurrence (fSEO) or the diffusion [A12]time (τD) is increased.
Observing single event occurrences (such as the passage of individual structured soluble amyloid aggregates one at a time) allows an analysis of the time that it takes for the amyloid aggregate to pass through the observation volume element (such as to analyse the width of the individual fluorescence intensity bursts). The larger the structured soluble amyloid aggregates, the slower their movement, and the wider is the burst. To determine the average time that it takes for a structured soluble amyloid aggregate to pass through the observation volume element, temporal autocorrelation is used to analyse the signal and derive a temporal autocorrelation curve (tACC). The characteristic decay time of the tACC is short for small structured soluble amyloid aggregates, and it is long for large structured soluble amyloid aggregates.
Accordingly, in one embodiment the step of “determining the presence and/or amount and/or concentration and/or size of individual amyloid aggregates in the sample” comprises providing a temporal autocorrelation curve (tACC), in particular wherein the method comprises determining the frequency of individual amyloid aggregates. A further explanation of how to provide (or derive) a tACC is provided in the Examples.
Data analysis presented in
In one embodiment, if the decay time (in particular, the decay time of the tACC) is longer in the sample when compared to one or more control samples (such one or more samples from one or more control subjects, as described below), a diagnosis and/or prognosis of the amyloid-associated disease is provided.
In one embodiment, if the molecular weight of the amyloid aggregates in the sample is about 2 or more times higher when compared to one or more control samples (such one or more samples from one or more control subjects, as described below), a diagnosis and/or prognosis of the amyloid-associated disease is provided; for example: about three or more times higher; about four or more times higher; about five or more times higher; about six or more times higher; about seven or more times higher; about eight or more times higher; about nine or more times higher; about 10 or more times higher; about 11 or more times higher; about 12 or more times higher; about 13 or more times higher; about 14 or more times higher; about 15 or more times higher; about 16 or more times higher; about 17 or more times higher; about 18 or more times higher; about 19 or more times higher; about 20 or more times higher; about 21 or more times higher; about 22 or more times higher; about 23 or more times higher; about 24 or more times higher; about 25 or more times higher; about 26 or more times higher; about 27 or more times higher; about 28 or more times higher; about 29 or more times higher; or about 30 or more times higher, preferably about 27 or more times higher.
In one embodiment, if the decay time (i.e. the diffusion time (τD)) (in particular, the decay time of the tACC) is about 6 ms or more a diagnosis and/or prognosis of the amyloid-associated disease is provided; for example: about 7 ms or more; about 8 ms or more; about 9 ms or more; about 10 ms or more; about 11 ms or more; about 12 ms or more; about 13 ms or more; about 14 ms or more; about 15 ms or more; about 16 ms or more; about 17 ms or more; about 18 ms or more; about 19 ms or more; or about 20 ms or more, preferably about 15 ms or more.
In an alternative embodiment, determining the presence and/or amount and/or concentration and/or size of individual amyloid aggregates comprises Total Internal Fluorescence Microscopy (TIRF); and/or image correlation spectroscopy; and/or enzyme-linked immunosorbent assay (ELISA); and/or massively parallel Fluorescence Correlation Spectroscopy (mpFCS). Put another way, determining the presence and/or amount and/or concentration and/or size of individual amyloid aggregates is conducted using Total Internal Fluorescence Microscopy (TIRF); and/or image correlation spectroscopy; and/or enzyme-linked immunosorbent assay (ELISA); and/or massively parallel Fluorescence Correlation Spectroscopy (mpFCS). Preferably, determining the presence and/or amount and/or concentration and/or size of individual amyloid aggregates comprises Total Internal Reflexion Fluorescence Microscopy (TIRF) and image correlation spectroscopy.
Fluorescence correlation spectroscopy is a suitable methodology providing single particle/aggregate/molecule resolution. In order to satisfactory achieve single molecule resolution it is important that the observation volume element detected by a suitable detector is small. The smaller the observation volume element, the fewer the number of particles that are present/observed at a given moment. Hence, the signal-to-background ratio improves with decreasing the observation volume element size. One option to achieve a small observation volume element is to have a specific arrangement of optical elements in the optical pathway between the sample and the detector, such as the conjugate focal plane arrangement in a confocal microscope. The volume of a thus obtained confocal observation volume element is smaller than about 10−11 litres and typically from about 10−13 down to about 10−16 litres.
Even smaller observation volume elements can be achieved by implementation of Total Internal Reflection (TIR). One alternative to provide TIR is to focus light on the back-focal plane of an optical element generating exiting, typically collimated, light angular to the (main) optical axis of the optical element. Dependent on the location of the focussing of the incident light at the back focal plane of the optical element the angle with respect to the optical axis of the optical element of the exiting light will vary. The optical element is suitably an objective. The objective for providing TIR of the exiting light has preferably a high numerical aperture, suitably above about 0.9, above about 1.0, above about 1.1, above about 1.2. The numerical aperture may be as high as around 2.0.[A14]
A further possibility to provide a very small observation volume element is the implementation of Stimulated Emission Depletion (STED) optical arrangement. Here, a light of specific wavelength and a distinct intensity profile (with an intensity minimum in the centre) is used to reduce the volume from which fluorescence is being emitted (Mueller et al Biophys. J. 2011 101(7): 1651-1660 doi: 10.1016/j.bpj.2011.09.006.)[A15]
Yet another [A16]possibility to provide a very small observation volume element is the implementation of a transparent substrate on which a thin layer of a material is deposited that is capable of essentially blocking electromagnetic radiation from the UV-VIS region of the spectrum (
Fluorescence correlation spectroscopy using confocal volume elements can be parallelized by the implementation of an optical element capable of splitting up the incident beam of light into an array of light beams (plurality of light beams). A suitable optical element for splitting a beam is a diffractive optical element (DOE).
In one embodiment, the time-resolved detection comprises Fluorescence Correlation Spectroscopy (FCS), which is using temporal autocorrelation analysis to analyse the data. Put another way, the time-resolved detection is conducted using Fluorescence Correlation Spectroscopy (FCS). “Fluorescence Correlation Spectroscopy (FCS)” is a method used to detect fluorescence which would be known to those skilled in chemistry, and is described in detail in the Examples herein. As discussed in the Examples, Fluorescence Correlation Spectroscopy (FCS) is particularly effective for use with the methods of the invention.
In one embodiment, the FCS is a multiplex FCS. A multiplex FCS allows for the measurement of more samples by allowing more than one sample to be measured simultaneously, and so is advantageous as it increases the throughput of the method.
In one embodiment, fluorescence detected by Fluorescence Correlation Spectroscopy (FCS) represents the presence and/or amount and/or concentration and/or size of the individual amyloid aggregates. In a preferred embodiment, the method further comprises the step of adding a detection agent comprising a fluorescent moiety to the sample, and the fluorescence emitted by the fluorescent moiety is detected by Fluorescence Correlation Spectroscopy (FCS) and represents the presence and/or amount and/or concentration and/or size of the individual amyloid aggregates.
In one embodiment, the frequency of individual amyloid aggregates is calculated using fluorescence intensity fluctuation analysis (FIFA). FIFA can be calculated as the number of peaks (i.e. individual amyloid aggregates) per unit of time, wherein the peak has an intensity which is larger than at least two or five standard deviations of the control sample such as “a control level of fluorescence in the sample”, as discussed below (preferably, at least five times larger than the standard deviation of the control sample).
In one embodiment, a diagnosis and/or prognosis of the amyloid-associated disease is provided if the presence and/or amount and/or concentration of the individual amyloid aggregates in the sample is higher than the presence and/or amount and/or concentration of the individual amyloid aggregates in a control sample; and/or the size of the individual amyloid aggregates in the sample is larger than the size of the individual amyloid aggregates in a control sample.
A control sample suitable for use as part of the invention would be known to one skilled in biology or medicine, which includes, but is not limited to, the controls outlined herein. In some embodiments, the control sample is one or more selected from the list comprising or consisting of: a control sample from one or more control subjects; an in vitro control sample; a negative control sample; and a control level of fluorescence in the sample.
By “control subject”, we include a subject that does not have an amyloid-associated disease. In the methods of the invention, the control subjects may be matched by age and/or sex. Preferably, the control subjects are matched by age and/or sex when compared to the subject. By “matched by age and/or sex”, we include that the control subjects are selected so that they are all of the same or similar age and/or sex. How to select appropriate control subjects for the method of the invention would be known to one skilled in medicine.
By “in vitro control sample” we include that the control sample is prepared in a laboratory so that it has a known presence and/or amount and/or concentration and/or size of individual amyloid aggregates. How to produce such an in vitro control sample would be known to one skilled in chemistry, for example the production of peptide and protein monomers from which the individual amyloid aggregates could be formed may be undertaken using solid phase synthesis.
By “a negative control sample”, we include that the control sample is removed from the bodily fluid sample, and the methods described herein are undertaken on the control sample but without the detection agent being added. For example, the bodily fluid sample is split into two (or more) volumes, with the first volume being the “sample of bodily fluid” and the having the detection agent added to it, and with the second volume being the “negative control sample” not having the detection agent added to it. This control sample therefore provides a background reading for the sample, under the experimental conditions of the method.
As discussed herein, a particularly preferred embodiment of the invention is determining the presence and/or amount and/or concentration and/or size of individual amyloid aggregates in the sample using time-resolved detection and fluorescence. Using this method, a control (or background) level of fluorescence can be determined in the same sample of bodily fluid which is subject of the methods described herein, and this is discussed further below.
In one embodiment, the presence and/or amount and/or concentration of the individual amyloid aggregates in the sample is about 20% or more higher than the presence and/or amount and/or concentration and/or size of individual amyloid aggregates in a control sample; for example: about 25% or more higher; about 30% or more higher; about 35% or more higher; about 40% or more higher; about 45% or more higher; about 50% or more higher; about 55% or more higher; about 60% or more higher; about 65% or more higher; about 70% or more higher; about 75% or more higher; about 80% or more higher; about 85% or more higher; about 90% or more higher; about 95% or more higher, preferably about 50% or more higher; and/or
the size of the individual amyloid aggregates in the sample is about 20% or more larger than the size of individual amyloid aggregates in a control sample; for example: about 25% or more larger; about 30% or more larger; about 35% or more larger; about 40% or more larger; about 45% or more larger; about 50% or more larger; about 55% or more larger; about 60% or more larger; about 65% or more larger; about 70% or more larger; about 75% or more larger; about 80% or more larger; about 85% or more larger; about 90% or more larger; about 95% or more larger, preferably about 50% or more larger.
When we refer to the individual amyloid aggregates in the sample being “larger” than the size of the individual amyloid aggregates in a control sample, we include that the individual amyloid aggregates in the sample have more peptides per aggregate than the aggregates found in the control sample, and/or that they have a higher molecular weight.
In one embodiment, the size of the individual amyloid aggregates in the sample is about 10 times or more of the molecular weight of the individual amyloid aggregates in the control sample; for example: about 11 times or more of the molecular weight; about 12 times or more of the molecular weight; about 13 times or more of the molecular weight; about 14 times or more of the molecular weight; about 15 times or more of the molecular weight; about 16 times or more of the molecular weight; about 17 times or more of the molecular weight; about 18 times or more of the molecular weight; about 19 times or more of the molecular weight; about 20 times or more of the molecular weight; about 21 times or more of the molecular weight; about 22 times or more of the molecular weight; about 23 times or more of the molecular weight; about 24 times or more of the molecular weight; about 25 times or more of the molecular weight; about 26 times or more of the molecular weight; about 27 times or more of the molecular weight; about 28 times or more of the molecular weight; about 29 times or more of the molecular weight; about 30 times or more of the molecular weight; about times or more of the molecular weight; about 40 times or more of the molecular weight; about 45 times or more of the molecular weight; or about 50 times or more of the molecular weight the individual amyloid aggregates in the control sample, preferably about 27 times or more of the molecular weight the individual amyloid aggregates in the control sample.
In one embodiment, the presence and/or amount and/or concentration of the individual amyloid aggregates in the sample is about two times or more higher than in a control sample; for example, about three times or more higher; about four times or more higher; about five times or more higher; about six times or more higher; about seven times or more higher; about eight times or more higher; about nine times or more higher; about ten times or more higher than in a control sample, preferably about five times or more higher than in a control sample; and/or the size of the individual amyloid aggregates in the sample is about two times or more larger than in a control sample; for example, about three times or more larger; about four times or more larger; about five times or more larger; about six times or more larger; about seven times or more larger; about eight times or more larger; about nine times or more larger; about ten times or more larger than in a control sample, preferably about five times or more larger than in a control sample
In one embodiment, the presence and/or amount and/or concentration of the individual amyloid aggregates in the sample is about two standard deviations or more higher than in a control sample; for example, about three standard deviations or more higher; about four standard deviations or more higher; about five standard deviations or more higher; about six standard deviations or more higher; about seven standard deviations or more higher; about eight standard deviations or more higher; about nine standard deviations or more higher; about ten standard deviations or more higher than in a control sample, preferably about five standard deviations or more higher than in a control sample; and/or
the size of the individual amyloid aggregates in the sample is about two standard deviations or more larger than in a control sample; for example, about three standard deviations or more larger; about four standard deviations or more larger; about five standard deviations or more larger; about six standard deviations or more larger; about seven standard deviations or more larger; about eight standard deviations or more larger; about nine standard deviations or more larger; about ten standard deviations or more larger than in a control sample, preferably about five standard deviations or more larger than in a control sample.
In one embodiment, the higher the amount and/or concentration of the individual amyloid aggregates in the sample, the more serious the diagnosis and/or the more serious the prognosis.
In one embodiment, the larger the size of the individual amyloid aggregates in the sample, the more serious the diagnosis and/or the more serious the prognosis.
By “serious” in the context of the diagnosis and/or prognosis, we include that the likelihood that the onset and/or progression of the amyloid-associated disease will proceed quickly is high, and/or that the subject might soon exhibit one or more symptoms of an amyloid-associated disease, and/or that the subject will exhibit severe symptoms of the amyloid-associated disease, and/or that the subject might die soon.
In one embodiment, the size of the individual amyloid aggregates is the mean size.
One skilled in biology and/or statistics would understand, and would be able to calculate, the mean size of the individual amyloid aggregates. By “mean size”, we include that the mean is the average mean.
As would be appreciated by one skilled in the art, the type of bodily fluid sample used in the method of the invention might dictate, to some extent, the size of the individual amyloid aggregates that can be detected. For example, for urine as a bodily fluid sample the maximum size of the individual amyloid aggregates detectable might be defined by size limitations caused by glomerular filtration.
In the methods of the invention, the control sample may comprise a bodily fluid sample from one or more control subjects that do not have an amyloid-associated disease; for example: about two or more control subjects; about three or more control subjects; about four or more control subjects; about five or more control subjects; about six or more control subjects; about seven or more control subjects; about eight or more control subjects; about nine or more control subjects; about ten or more control subjects; about 11 or more control subjects; about 12 or more control subjects; about 13 or more control subjects; about 14 or more control subjects; about 15 or more control subjects; about 16 or more control subjects; about 17 or more control subjects; about 18 or more control subjects; about 19 or more control subjects; about 20 or more control subjects; about 25 or more control subjects; about 30 or more control subjects; about 35 or more control subjects; about 40 or more control subjects; about or more control subjects; about 50 or more control subjects; about 60 or more control subjects; about 70 or more control subjects; about 80 or more control subjects; about 90 or more control subjects; about 100 or more control subjects, preferably bodily fluid samples from about 30 or more control subjects.
In one embodiment, where there are two or more control subjects the control sample is the mean (preferably the average mean) of the presence and/or amount and/or concentration and/or size of individual amyloid aggregates in the two or more control subjects.
In one embodiment where the measurement and/or detection of fluorescence is used to determine the presence and/or amount and/or concentration and/or size of individual amyloid aggregates in the sample, the control sample is “a control level of fluorescence in the sample” (for example, the “overall signal”) and the fluorescence (i.e. the fluorescence signal) comprises a level of fluorescence higher than the control level of fluorescence in the sample. Put another way, the level of fluorescence being higher than the control level of fluorescence represents the presence and/or amount and/or concentration and/or size of the individual amyloid aggregates.
In some embodiments, the “level of fluorescence” is the peak of fluorescence (i.e. the measured value of the fluorescence that is larger than five times the standard deviation of the signal), such as a peak of fluorescence which is detectable above the control level of fluorescence in the sample.
In one embodiment, the method comprises the step of detecting and/or measuring the control level of fluorescence in the sample, such as detecting and/or measuring the fluorescence fluctuations. In one embodiment, the step of “detecting and/or measuring the control level of fluorescence in the sample” precedes the step of “adding a detection agent to the sample”.
In one embodiment, the fluorescence comprises a level of fluorescence (such as a peak in fluorescence) about two times or more higher than a control level of fluorescence; for example, about three times or more; about four times or more; about five times or more; about six times or more; about seven times or more; about eight times or more; about nine times or more; about ten times or more higher than a control level of fluorescence (for example, the “overall signal”), preferably about five times or more higher than a control level of fluorescence (for example, the “overall signal”).
In one embodiment, the fluorescence comprises a level of fluorescence (such as a peak in fluorescence) about two standard deviations or more higher than a control level of fluorescence; for example, about three standard deviations or more; about four standard deviations or more; about five standard deviations or more; about six standard deviations or more; about seven standard deviations or more; about eight standard deviations or more; about nine standard deviations or more; about ten standard deviations or more higher than a control level of fluorescence (for example, the “overall signal”), preferably about five standard deviations or more higher than a control level of fluorescence (for example, the “overall signal”).
As discussed herein, in one embodiment, the control level of fluorescence is the background level of fluorescence in the sample, which can be referred to as the variance of the background level of fluorescence or baseline signal (it can also be referred to as the overall signal). As would be understood by one skilled in biology, a sample of bodily fluid might have a certain level of auto fluorescence, which may differ between bodily fluid samples. An example of this is provided in
In one embodiment in which time-resolved detection is used, the control level of fluorescence in the sample is the baseline signal or variance of the background level of fluorescence of the time resolved detection. In this particular embodiment, the baseline signal or variance of the background level of fluorescence can be time-resolved detection measurement(s) in a fraction(s) of the sample of bodily fluid which do not comprise any individual amyloid aggregates or the overall signal of the sample. The overall signal is the fluorescence measurements that are taken during the course of the time-resolved detection. Accordingly, the baseline signal or variance of the background level of fluorescence can be provided throughout the unit of time of the time-resolved detection.
In one embodiment, each peak of fluorescence (such as a single event occurrence (fSEO)) above a baseline signal or variance of the background level of fluorescence is indicative of an individual amyloid aggregate (preferably, the peak of fluorescence is at least five standard deviations higher than the overall signal). Put another way, each peak of fluorescence (such as a single event occurrence (fSEO)) above a baseline signal or variance of the background level of fluorescence represents a frequency of one, and two peaks represents a frequency of two, and so on. In a particularly preferred embodiment, the peak of fluorescence (such as the single event occurrence (fSEO)) is a sharp and brief increase of the level of fluorescence above the baseline signal or variance of the background level of fluorescence (for example, the overall signal), which is indicative of an individual amyloid aggregate.
In one embodiment, the control level of fluorescence (such as the baseline signal or variance of the background level of fluorescence) is the mean level of fluorescence measured throughout the unit of time of the time-resolved detection (such as Fluorescence Correlation Spectroscopy (FCS)), preferably the average mean.
In a preferred embodiment, the fluorescence comprises a peak of fluorescence about two times or more higher than a baseline signal or variance of the background level of fluorescence; for example, about three times or more; about four times or more; about five times or more; about six times or more; about seven times or more; about eight times or more; about nine times or more; about ten times or more higher than a variance of the background level of fluorescence (for example, the overall signal), preferably about five times or more higher than a baseline signal or variance of the background level of fluorescence (for example, the overall signal).
In a preferred embodiment, the fluorescence comprises a peak of fluorescence about two standard deviations or more higher than a baseline signal or variance of the background level of fluorescence; for example, about three standard deviations or more; about four standard deviations or more; about five standard deviations or more; about six standard deviations or more; about seven standard deviations or more; about eight standard deviations or more; about nine standard deviations or more; about ten standard deviations or more higher than a variance of the background level of fluorescence (for example, the overall signal), preferably about five standard deviations or more higher than a baseline signal or variance of the background level of fluorescence (for example, the overall signal).
In one embodiment, the sample comprises a volume of about 30 microlitres (μl) to about 300 microlitres (μl).
In one embodiment, the sample comprises a volume of about 500 microlitres (μl) or less; for example, about 490 microlitres (μl) or less; about 480 microlitres (μl) or less; about 470 microlitres (μl) or less; about 460 microlitres (μl) or less; about 450 microlitres (μl) or less; about 440 microlitres (μl) or less; about 430 microlitres (μl) or less; about 420 microlitres (μl) or less; about 410 microlitres (μl) or less; about 400 microlitres (μl) or less; about 390 microlitres (μl) or less; about 380 microlitres (μl) or less; about 370 microlitres (μl) or less; about 360 microlitres (μl) or less; about 350 microlitres (μl) or less; about 340 microlitres (μl) or less; about 330 microlitres (μl) or less; about 320 microlitres (μl) or less; about 310 microlitres (μl) or less; about 300 microlitres (μl) or less; about 290 microlitres (μl) or less; about 280 microlitres (μl) or less; about 270 microlitres (μl) or less; about 260 microlitres (μl) or less; about 250 microlitres (μl) or less; about 240 microlitres (μl) or less; about 230 microlitres (μl) or less; about 220 microlitres (μl) or less; about 210 microlitres (μl) or less; about 200 microlitres (μl) or less; about 190 microlitres (μl) or less; about 180 microlitres (μl) or less; about 170 microlitres (μl) or less; about 160 microlitres (μl) or less; about 150 microlitres (μl) or less; about 140 microlitres (μl) or less; about 130 microlitres (μl) or less; about 120 microlitres (μl) or less; about 110 microlitres (μl) or less; about 100 microlitres (μl) or less; about 90 microlitres (μl) or less; about 80 microlitres (μl) or less; about 70 microlitres (μl) or less; about 60 microlitres (μl) or less; about 50 microlitres (μl) or less; about 40 microlitres (μl) or less; about 30 microlitres (μl) or less; about 20 microlitres (μl) or less; or about 10 microlitres (μl) or less. In a preferred embodiment, the sample comprises a volume of 150 microlitres (μl) or less. In an alternative preferred embodiment, the sample comprises a volume of 200 microlitres (μl) or less.
When the method is undertaken using time-resolved detection (such as Fluorescence Correlation Spectroscopy (FCS)), the sample may be processed into fractions, such as observation volume elements (OVE), as explained in the Examples.
In one embodiment, the fractions (such as observation volume element) comprises a volume of about 1 microlitre (μl) or less; for example, about 0.1 microlitre (μl) or less; about 0.01 microlitre (μl) or less; about 0.001 microlitre (μl) or less; about 0.0001 microlitre (μl) or less; about 0.00001 microlitre (μl) or less; about 0.000001 microlitre (μl) or less; about 0.0000001 microlitre (μl) or less; about 0.00000001 microlitre (μl) or less; about 1 femtolitre (fl) or less; about 0.1 femtolitre (fl) or less; about 0.2 femtolitre (fl) or less; about 0.3 femtolitre (fl) or less; about 0.4 femtolitre (fl) or less; about 0.5 femtolitre (fl) or less; about 0.6 femtolitre (fl) or less; about 0.7 femtolitre (fl) or less; about 0.8 femtolitre (fl) or less; about 0.9 femtolitre (fl) or less; about 0.01 femtolitre (fl) or less; about 0.001 femtolitre (fl) or less; or about 0.0001 femtolitre (fl) or less, preferably about 0.2 femtolitre (fl) or less. According to an embodiment the observation volume can be from about 10−20 litre down to about 10−22 litres, such as in in the zepto-litre range.
In one embodiment, the method comprises the use of a flow cell to circulate the sample while determining the presence and/or amount and/or concentration of individual amyloid aggregates. A flow cell is a device which would be known to one skilled in microscopy. A flow cell can be used to circulate the sample through the device while doing time-resolved detection. In this way the frequency of encountering nano-plaques can be increased—instead of waiting for aggregates to freely diffuse, one is propelling their movement by the flow. This can be advantageous as it may expedite the measurements, thus shortening the analysis time. Exemplary flow cells suitable for the described method can be obtained from Warner Instruments—US (www.warneronline.com), such as the are RC-30HV and RC-30WA chambers.
In one embodiment, a diagnosis and/or prognosis of the amyloid-associated disease is provided if the presence and/or amount of the individual amyloid aggregates is one individual amyloid aggregate or more; for example: about two individual amyloid aggregates or more; about three individual amyloid aggregates or more; about four individual amyloid aggregates or more; about five individual amyloid aggregates or more; about six individual amyloid aggregates or more; about seven individual amyloid aggregates or more; about eight individual amyloid aggregates or more; about nine individual amyloid aggregates or more; about 10 individual amyloid aggregates or more; about 15 individual amyloid aggregates or more; about 20 individual amyloid aggregates or more; about 25 individual amyloid aggregates or more; about 30 individual amyloid aggregates or more; about 50 individual amyloid aggregates or more; about 100 individual amyloid aggregates or more; about 200 individual amyloid aggregates or more; about 300 individual amyloid aggregates or more; about 400 individual amyloid aggregates or more; about 500 individual amyloid aggregates or more; about 1,000 individual amyloid aggregates or more; about 2,000 individual amyloid aggregates or more; about 3,000 individual amyloid aggregates or more; about 4,000 individual amyloid aggregates or more; about 5,000 individual amyloid aggregates or more; or about 10,000 individual amyloid aggregates or more.
In one embodiment, the method is repeated at intervals, such as two times or more; for example, three times or more; four times or more; five times or more; six times or more; seven times or more; eight times or more; nine times or more; 10 times or more; 11 times or more; 12 times or more; 13 times or more; 14 times or more; 15 times or more; 16 times or more; 17 times or more; 18 times or more; 19 times or more; 20 times or more; 25 times or more; 30 times or more; 35 times or more; 40 times or more; 45 times or more; or times or more; or 50 times or more.
Repeating the method over time allows for the diagnosis and/or prognosis to be followed over time, which allows for the diagnosis and/or prognosis to be reviewed and revised. Accordingly, when the method is repeated two or more times, for the second or subsequent repeat the step of providing a diagnosis and/or prognosis of the amyloid-associated disease on the basis of the determination can be the step revising the diagnosis and/or the prognosis of the amyloid-associated disease on the basis of the determination.
In one embodiment, the period between the method of the first aspect of the invention being repeated is one day or more; for example, about two days or more; about three days or more; about four days or more; about five days or more; about six days or more; about one week or more; about two weeks or more; about three weeks or more; about four weeks or more; about one month or more; about five weeks or more; about six weeks or more; about seven weeks or more; about eight weeks or more; about two months or more; about three months or more; about four months or more; about five months or more; about six months or more; about seven months or more; about eight months or more; about nine months or more; about 10 months or more; about 11 months or more; about 1 year or more; about two years or more; about 3 years or more; about 4 years or more; about 5 years or more; about 6 years or more; about 7 years or more; about 8 years or more; about nine years or more; or about ten years or more, preferably about one month or more.
In one embodiment, the subject and/or the control subject is one or more from the group comprising: a rodent (for example, a mouse, and/or a rat, and/or a hamster, and/or a guinea pig, and/or a gerbil, and/or a rabbit); and/or a canine (for example, a dog); and/or a feline (for example, a cat); a primate (for example, a human; and/or a monkey; and/or an ape); and/or an equine (for example, a horse); and/or a bovine (for example, a cow); and/or a porcine (for example, a pig); and/or a non-human mammal. Preferably the subject is human, preferably both the subject and control subject are human.
In an embodiment, the subject and/or the control subject is alive. In a preferred embodiment, the subject is alive.
In one embodiment, the method further comprises the step of selecting and/or providing a treatment for the amyloid-associated disease to the subject.
By “selecting and/or providing a treatment”, we include that based on the diagnosis and/or prognosis of the amyloid-associated disease an appropriate treatment for that disease can be identified. Based on the diagnosis and/or prognosis of the amyloid-associated disease, one skilled in medicine would be able to select and/or provide an appropriate treatment.
Preferably, the step of “selecting and/or providing a treatment for the amyloid-associated disease to the subject” follows the step of “providing a diagnosis and/or prognosis of the amyloid-associated disease on the basis of the determination”.
In one embodiment, the treatment is one that reduces the number and/or severity of the symptoms and/or signs of the amyloid-associated disease, and/or treats the cause of the amyloid-associated disease; and/or improves neuromodulator processes; and/or improves neurotransmission processes; and/or reduces the presence and/or amount and/or concentration and/or size of individual amyloid aggregates.
As disclosed herein, by treatment we include a palliative treatment, and/or an experimental treatment, and/or a physical therapy.
In one embodiment, the treatment is one or more selected from the group comprising: Levodopa (L-DOPA); acetylcholinesterase inhibitors (AChEIs, such as Donepezil, Galantamine and Rivastigmine); N-methyl-D-aspartate (NMDA) inhibitors (such as Memantine); secretase 1 (BACE1) inhibitors; monoclonal antibodies (including monoclonal antibodies analogues); and/or Tafamidis. One skilled in medicine would be familiar with the treatments discussed herein, and would know when they should be selected and/or provided.
AChEIs inhibit the acetylcholinesterase enzyme from breaking down acetylcholine, thereby increasing both the level and duration of action of the neurotransmitter acetylcholine. The NMDA receptor antagonist Memantine, regulates the activity of glutamate, an important neurotransmitter in the brain involved in learning and memory, by partially blocking the NMDA receptors to which glutamate released from damaged cells is being released. Tafamidis (trade name Vyndaqel) stabilizes the correctly folded tetrameric form of transthyretin (TTR), thereby slowing down the rate at which TTR aggregates are being formed and accumulate in the diseased individual. Monoclonal antibodies are capable of crossing the blood-brain barrier and selectively target soluble amyloid β aggregates (in particular, insoluble fibrils in the brain), which reduces the amyloid β aggregate load. It was shown in preclinical studies, that a monoclonal antibody analogue could clear Aβ from plaque-bearing transgenic mouse brains (Sevigny et al. Nature 2016 537:50-56 doi:10.1038/nature19323).
In a preferred embodiment, the amyloid-associated disease is Parkinson's disease and the treatment comprises L-DOPA.
In an alternative preferred embodiment, the amyloid-associated disease is Familial Amyloid Polyneuropathy (FAP) and the treatment comprises Tafamidis.
In a further alternative preferred embodiment, the amyloid-associated disease is Alzheimer's disease and the treatment comprises secretase 1 (BACE1) inhibitors and/or monoclonal antibodies (including monoclonal antibodies analogues).
In one embodiment, the secretase 1 (BACE1) inhibitors exclude verubecestat.
In one embodiment, the treatment comprises administering a treatment for the amyloid-associated disease to the subject. In a preferred embodiment, the step of “administering a treatment for the amyloid-associated disease to the subject” follows the step of “selecting and/or providing a treatment for the amyloid-associated disease to the subject”.
A second aspect of the invention provides a method for the treatment of an amyloid-associated disease in a subject, wherein the method comprises the steps of:
It will be appreciated that the features defined above in relation to the first aspect of the invention apply to the method of the second aspect of the invention. For example, the features discussed in relation to “providing a diagnosis and/or prognosis of the amyloid-associated disease on the basis of the determination” in the first aspect of the invention can be used for “identifying the subject as having the amyloid-associated disease on the basis of the determination”.
In a preferred embodiment of the second aspect of the invention, the method comprises the steps in the order of:
In one embodiment, the treatment comprises administering a treatment for the amyloid-associated disease to the subject. In a preferred embodiment, the step of “administering a treatment for the amyloid-associated disease to the subject” follows the step of “selecting and/or providing a treatment for the amyloid-associated disease to the subject”.
A third aspect of the invention provides a method for identifying an agent for the treatment of an amyloid-associated disease, wherein the method comprises the steps of:
By “identifying an agent for the treatment of an amyloid-associated disease”, we include determining whether a treatment that has not previously been identified is useful for treating an amyloid-associated disease, and/or is useful for reducing the number and/or severity of the symptoms and/or signs of the amyloid-associated disease, and/or is useful for improving neuromodulator processes; and/or is useful for improving neurotransmission processes, and/or is useful for reducing the presence and/or amount and/or concentration and/or size of individual amyloid aggregates. Alternatively, by “identifying an agent for the treatment of an amyloid-associated disease” we include determining the effectiveness of a treatment for the amyloid-associated disease on the subject. To put another way, we include following the effectiveness of a treatment for an amyloid-associated disease in a subject.
The third aspect of the invention relates to an in vivo method of identifying an agent for the treatment of an amyloid-associated disease.
It will be appreciated that the features defined above in relation to the first aspect and/or second aspect of the invention apply to the method of the third aspect of the invention. For example, the features discussed in relation to “providing a diagnosis and/or prognosis of the amyloid-associated disease on the basis of the determination” in the first aspect of the invention can be used for “identifying the agent as being for the treatment of the amyloid-associated disease based on the comparison”.
In a preferred embodiment of the third aspect of the invention, the method comprises the steps in the order of:
In one embodiment, an agent is identified as being for the treatment of the amyloid-associated disease if the presence and/or amount and/or concentration of the individual amyloid aggregates in the second sample is lower than the presence and/or amount and/or concentration of the individual amyloid aggregates in the first sample; and/or the size of the individual amyloid aggregates in the second sample is smaller than the size of the individual amyloid aggregates in the first sample.
When we refer to the individual amyloid aggregates in the second sample being “smaller” than the size of the individual amyloid aggregates in a first sample, we include that the individual amyloid aggregates in the second sample have fewer peptides per aggregate than the aggregates found in the first sample, or have a lower molecular weight.
Without wishing to be bound by any theory, the inventors believe that if the test subject has fewer and/or the smaller individual amyloid aggregates after administration of the agent, then that agent is likely to have a role in treating the amyloid-associated disease. The bigger the reduction in number and/or size of the individual amyloid aggregates the more effective the agent is likely to be in treating the amyloid-associated disease.
In one embodiment, the presence and/or amount and/or concentration of the individual amyloid aggregates in the second sample is about 20% or more lower than the presence and/or amount and/or concentration and/or size of individual amyloid aggregates in a first sample; for example: about 25% or more lower; about 30% or more lower; about 35% or more lower; about 40% or more lower; about 45% or more lower; about 50% or more lower; about 55% or more lower; about 60% or more lower; about 65% or more lower; about 70% or more lower; about 75% or more lower; about 80% or more lower; about 85% or more lower; about 90% or more lower; about 95% or more lower, preferably about 50% or more lower; and/or
the size of the individual amyloid aggregates in the second sample is about 20% or more smaller than the size of individual amyloid aggregates in a first sample; for example: about 25% or more smaller; about 30% or more smaller; about 35% or more smaller; about 40% or more smaller; about 45% or more smaller; about 50% or more smaller; about 55% or more smaller; about 60% or more smaller; about 65% or more smaller; about 70% or more smaller; about 75% or more smaller; about 80% or more smaller; about 85% or more smaller; about 90% or more smaller; about 95% or more smaller, preferably about 50% or more smaller.
In one embodiment, the size of the individual amyloid aggregates in the first sample is about times or more of the molecular weight of the individual amyloid aggregates in the second sample; for example: about 11 times or more of the molecular weight; about 12 times or more of the molecular weight; about 13 times or more of the molecular weight; about 14 times or more of the molecular weight; about 15 times or more of the molecular weight; about 16 times or more of the molecular weight; about 17 times or more of the molecular weight; about 18 times or more of the molecular weight; about 19 times or more of the molecular weight; about 20 times or more of the molecular weight; about 21 times or more of the molecular weight; about 22 times or more of the molecular weight; about 23 times or more of the molecular weight; about 24 times or more of the molecular weight; about 25 times or more of the molecular weight; about 26 times or more of the molecular weight; about 27 times or more of the molecular weight; about 28 times or more of the molecular weight; about 29 times or more of the molecular weight; about 30 times or more of the molecular weight; about times or more of the molecular weight; about 40 times or more of the molecular weight; about 45 times or more of the molecular weight; or about 50 times or more of the molecular weight the individual amyloid aggregates in the second sample, preferably about 27 times or more of the molecular weight the individual amyloid aggregates in the second sample.
In one embodiment, the presence and/or amount and/or concentration of the individual amyloid aggregates in the first sample is about two times or more higher than in the second sample; for example, about three times or more higher; about four times or more higher; about five times or more higher; about six times or more higher; about seven times or more higher; about eight times or more higher; about nine times or more higher; about ten times or more higher than in a first sample, preferably about five times or more higher than in the second sample; and/or
the size of the individual amyloid aggregates in the first sample is about two times or more larger than in the second sample; for example, about three times or more larger; about four times or more larger; about five times or more larger; about six times or more larger; about seven times or more larger; about eight times or more larger; about nine times or more larger; about ten times or more larger than in a first sample, preferably about five times or more larger than in the second sample
In one embodiment, the presence and/or amount and/or concentration of the individual amyloid aggregates in the first sample is about two standard deviations or more higher than in the second sample; for example, about three standard deviations or more higher; about four standard deviations or more higher; about five standard deviations or more higher; about six standard deviations or more higher; about seven standard deviations or more higher; about eight standard deviations or more higher; about nine standard deviations or more higher; about ten standard deviations or more higher than in a first sample, preferably about five standard deviations or more higher than in the second sample; and/or
the size of the individual amyloid aggregates in the first sample is about two standard deviations or more larger than in the second sample; for example, about three standard deviations or more larger; about four standard deviations or more larger; about five standard deviations or more larger; about six standard deviations or more larger; about seven standard deviations or more larger; about eight standard deviations or more larger; about nine standard deviations or more larger; about ten standard deviations or more larger than in a first sample, preferably about five standard deviations or more larger than in the second sample.
Similarly as discussed in relation to the first aspect of the invention, in one embodiment “determining the presence and/or amount and/or concentration and/or size of individual amyloid aggregates in the first sample” and/or “determining the presence and/or amount and/or concentration and/or size of individual amyloid aggregates in the second sample” comprises determining the frequency of individual amyloid aggregates (such as single event occurrence (fSEO)) in a unit of time. In a preferred embodiment, the frequency of individual amyloid aggregates in the first sample and the second sample is compared, and the agent is identified as being for the treatment of the amyloid-associated disease if the frequency of individual amyloid aggregates in the second sample is lower than the frequency of individual amyloid aggregates in the first sample.
In one embodiment, the following steps are repeated at intervals:
In one embodiment, where the steps of:
In one embodiment, where the steps of:
In one embodiment, the following steps are repeated at intervals:
In one embodiment, where the steps of:
In one embodiment, where the steps of:
In a preferred embodiment, where the steps of:
In one embodiment, the test subject is one or more from the group comprising: a rodent (for example, a mouse, and/or a rat, and/or a hamster, and/or a guinea pig, and/or a gerbil, and/or a rabbit); and/or a canine (for example, a dog); and/or a feline (for example, a cat); a primate (for example, a human; and/or a monkey; and/or an ape); and/or an equine (for example, a horse); and/or a bovine (for example, a cow); and/or a porcine (for example, a pig); and/or a fish (for example, a zebrafish); and/or an insect (for example, a Drosophila melanogaster); and/or a amphibian (for example, Xenopus laevis); and/or a reptile; and/or a nematode (for example, Caenorhabditis elegans).
In one embodiment, the test subject is a non-human, for example a non-human mammal. In a preferred embodiment, the non-human mammal is one or more from the group comprising: a rodent (for example, a mouse, and/or a rat, and/or a hamster, and/or a guinea pig, and/or a gerbil, and/or a rabbit); and/or a canine (for example, a dog); and/or a feline (for example, a cat); a non-human primate (for example, a monkey; and/or an ape); and/or an equine (for example, a horse); and/or a bovine (for example, a cow); and/or a porcine (for example, a pig).
A fourth aspect of the invention provides a method for identifying an agent for the treatment of an amyloid-associated disease, wherein the method comprises the steps of:
The third aspect of the invention relates to an in vitro and/or ex vivo method of identifying an agent for the treatment of an amyloid-associated disease.
It will be appreciated that the features defined above in relation to the first aspect and/or second aspect and/or third aspect of the invention apply to the method of the fourth aspect of the invention. For example, the features discussed in relation to “providing a diagnosis and/or prognosis of the amyloid-associated disease on the basis of the determination” in the first aspect of the invention can be used for “identifying the agent as being for the treatment of the amyloid-associated disease based on the comparison”. Similarly, the features discussed in relation to “determining the presence and/or amount and/or concentration and/or size of individual amyloid aggregates in the first sample” and/or “determining the presence and/or amount and/or concentration and/or size of individual amyloid aggregates in the second sample” in the third aspect of the invention can also be used for the fourth aspect of the invention.
In a preferred embodiment of the fourth aspect of the invention, the method comprises the steps in the order of:
Without wishing to be bound by any theory, the inventors believe that if the test fluid has fewer and/or the smaller individual amyloid aggregates after administration of the agent, then that agent is likely to have a role in treating the amyloid-associated disease. The bigger the reduction in number and/or size of the individual amyloid aggregates the more effective the agent is likely to be in treating the amyloid-associated disease.
In one embodiment, the following steps are repeated at intervals:
In one embodiment, where the steps of:
In one embodiment, where the steps of:
In one embodiment, the following steps are repeated at intervals:
In one embodiment, where the steps of:
In one embodiment, where the steps of:
In a preferred embodiment, where the steps of:
In one embodiment, the method is performed in vitro and/or ex vivo.
In one embodiment, the test fluid is a bodily fluid.
In a preferred embodiment, the test fluid is one or more bodily fluid from the group comprising or consisting of: blood and/or cerebrospinal fluid (CSF) and/or saliva and/or synovial fluid and/or faeces and/or urine, preferably blood.
In an alternative embodiment, the test fluid is an in vitro test fluid.
By “in vitro test fluid”, we include that the test fluid was prepared in a laboratory, and that the in vitro test fluid has a known presence and/or amount and/or concentration and/or size of individual amyloid aggregates.
A fifth aspect of the invention provides a use for determining the presence and/or amount and/or concentration of individual amyloid aggregates in a subject for the diagnosis and/or prognosis of an amyloid-associated disease in the subject, for example using a method of the invention as defined herein.
A sixth aspect of the invention provides a use of time resolved detection for the diagnosis and/or prognosis of an amyloid-associated disease in a subject, for example using a method of the invention as defined herein.
A seventh aspect of the invention provides a use for determining the presence and/or amount and/or concentration and/or size of individual amyloid aggregates for identifying an agent for the treatment of an amyloid-associated disease, for example using a method of the invention as defined herein.
An eighth aspect of the invention provides a use of time resolved detection for identifying an agent for the treatment of an amyloid-associated disease, for example using a method of the invention as defined herein.
It will be appreciated that the features defined above in relation to the first aspect and/or second aspect and/or third aspect and/or fourth aspect of the invention apply to the uses of the fifth aspect and/or sixth aspect and/or seventh aspect and/or eighth aspect of the invention.
A ninth aspect of the invention provides a kit of parts for the method of the first aspect and/or the second aspect and/or the third aspect and/or the fourth aspect of the invention and/or the use of any one of fifth aspect and/or sixth aspect and/or seventh aspect and/or eighth aspect of the invention, for example using a method of the invention as defined herein.
In one embodiment, the kit of parts comprises one or more from the list comprising or consisting of:
In one embodiment of the ninth aspect of the invention, the kit of parts comprises instructions. The instructions can be descriptive, instructional, marketing or other material that relates to the uses, and/or methods, and/or compositions described herein.
The informational material of the kits is not limited in its form. The information can be provided in a variety of formats, include printed text, computer readable material, video recording, or audio recording, or information that provides a link or address to substantive material, e.g., on the internet.
In a preferred embodiment, the kit of parts comprises instructions for the diagnosis and/or prognosis of an amyloid-associated disease in a subject and/or for identifying an agent for the treatment of an amyloid-associated disease.
The present invention will now be described with reference to one or more non-limiting figures and examples.
The listing or discussion of an apparently prior-published document in this specification should not necessarily be taken as an acknowledgement that the document is part of the state of the art or is common general knowledge.
By using time-resolved detection of Thioflavin T (ThT) fluorescence intensity fluctuations in a sub-femtoliter sized observation volume element, we were able to detect with single-molecule sensitivity very low levels of small structured amyloidogenic nano-plaques in the blood serum of apparently healthy individuals and in patients diagnosed with Alzheimer's disease (AD). The frequency of encountering small structured amyloidogenic nano-plaques and their size were significantly higher in the blood serum of individuals diagnosed with AD than in control subjects. The results of our study show that unlike bulk fluorescence ThT spectroscopy, time-resolved ThT fluorescence intensity fluctuation analysis allows direct detection, quantification and size determination of small structured amyloidogenic nano-plaques in the blood serum. The method neither relies on the use of immune-based probes, nor on the use of radiotracers, signal-amplification or protein separation techniques, and provides a minimally invasive test for fast and cost-effective early determination of structurally modified proteins in bodily fluid, including the peripheral blood circulation (
Alzheimer's disease (AD) is a devastating neurodegenerative ailment and the most common cause of dementia worldwide (1,2). AD progressively destroys vital mental abilities of the affected individuals and significantly reduces their cognitive capacity. The extent of damage induced by AD is such that the affected persons are eventually no longer able to take care of themselves, and are in need of constant care and assistance for the rest of their lives. Unfortunately, despite intensive research and a great societal need, methods for reliable and cost-effective early diagnosis of AD are still in their infancy. This also presents an impediment for the development of new drugs, and there is presently no cure for AD.
The main obstacle for further progress is the lack of important basic knowledge about complex dynamic processes that lie beneath the development of AD. While molecular mechanisms are not yet fully understood, it is well established that an imbalance in the production and clearance of amyloid beta (Aβ) peptides, accompanied by their self-assembly into structured aggregates and accumulation into so-called senile plaques in the central nervous system (CNS) of affected individuals, is a very early sign of AD. In view of that notion, the Amyloid Cascade Hypothesis proposes that misfolding, aggregation and deposition of Aβ peptides is a major cause of AD (3). Aβ peptides are 39-42 amino acids long peptides that are derived from the Amyloid Precursor Protein (APP) via proteolytic processing. The most common forms of Aβ peptides are Aβ40 and Aβ42 (reviewed in (4)).
The aggregation mechanisms of Aβ are complex. They have been investigated using a variety of different analytical techniques, including fluorescence spectroscopy and fluorescence correlation spectroscopy ((5) and references therein). Early on the benzothiazole salt Thioflavin T (ThT) fluorescence assay became a standard method for amyloid detection by fluorescence spectroscopy and microscopy (6,7). As more recent studies have shown, amyloidogenic aggregates enriched with pleated D-sheet secondary structure readily bind ThT and significantly alter its spectral properties, shifting the absorption spectrum towards longer wavelengths and significantly increasing the fluorescence quantum yield (
Diagnostic methods for AD are still under heavy debate (13-16). For diagnosis before a potential patient's mental decline is noticeable, it is required that reliable biomarkers are available (17). Serum and CSF autoantibodies against Aβ have shown promise and warrant further investigations (18,19), but the results have not been particularly encouraging so far. Brain imaging using PET and radiotracers will reflect reliably on fibrillar deposits of amyloid in the brain that are >1 mm in size (20-22). Measuring the content of Aβ peptides (and Tau protein) in the cerebrospinal fluid (CSF) using immunochemical techniques is also considered reliable (23-25). However, both PET and CSF methodologies are invasive and expensive. In topical reviews (13,14) the authors list drawbacks of simply measuring Aβ in blood plasma as a diagnostic method, and show that attempts to correlate blood studies and PET or CSF results are not convincing so far. The heterogeneous and different structural states of Aβ measured by the two technologies are one probable reason for the experimental difficulties: the immunochemical methods measure the soluble forms of the Aβ peptide(s), whereas the PET method measures the precipitated insoluble peptide aggregates in the brain. There is no clear direct connection between the two types of measurements, even if both relate back to the presence and behaviour of the Aβ peptide. There is obviously a strong need for a novel, non-invasive and reliable method for early AD diagnostics based on an additional biomarker methodology. The lack of such methods also presents an impediment for the development of new drugs—the development of novel therapies aiming to reduce the amyloid burden in the brain critically depends on the possibility to routinely identify and characterize the levels of structured amyloidogenic aggregates in the same individual repeatedly over time.
Here we present a fluorescence-based study of blood serum, simply labelled with the amyloid-sensitive dye ThT. The method is based on observations using a time-resolved and highly sensitive single-molecule fluorescence technology for Fluorescence Correlation Spectroscopy (FCS). We have earlier used the ThT based FCS assay (ThT-FCS), to study the heterogeneity and turnover of Aβ peptide aggregates during their fibril formation process in vitro (5). In the present study we demonstrate that there is a significant difference between the blood serum from diagnosed AD patients and control individuals, seen in the number and size of ThT-reactive structured amyloidogenic oligomeric aggregates, hereby named nano-plaques, visible in the serum of patients. The passages of these single nano-plaque particles through an extremely small (<femtoliter) observation volume can be observed in real time and counted. The number of passages, proportional to the concentration of nano-plaques, is significantly different in the blood serum from AD patients and controls.
Blood samples were obtained upon informed consent from apparently healthy blood donors (control group) and from individuals who were, after examination in primary care settings, referred to the Memory Clinic, Karolinska University Hospital, Huddinge (patient cohort).
Collection and handling of blood samples was approved by a regional ethics committee in Stockholm, permit nr. 2012/1019-31/1.
At the moment of admission AD diagnosis was not yet established and the patients did not take any pharmacological substances, such as cholinesterase inhibitors or N-methyl-D-aspartate (NMDA) receptor antagonists, typically used for the treatment of AD symptoms. However, due to their advanced age, many individuals in the patient cohort had age-related health problems and were on some prescribed medications. Detailed demographics and other relevant patient information are given in Table 1.
Blood from superficial veins of the upper limbs is collected using the evacuated tube system for venepuncture (BD Vacutainer® tubes, Becton, Dickinson and Company) and treated as described below to yield blood serum. ThT was added to the sample before submission to time resolved Fluorescence Intensity Fluctuation Analysis (FIFA).
Blood serum: To extract blood serum, 5 ml of blood is collected in a BD Vacutainer® Plastic Serum tube with Red BD Hemogard™ Closure, which contains micronized silica particles with SiO2 as the main clot activator component sprayed on the inner walls of the tube to accelerate the clotting process and does not contain thrombin. To activate blood clotting, the tube is gently inverted 1800 and back 5-6 times and the blood is allowed to clot for 60 min. Thereafter, the tube is centrifuged for 10 min at 2500×g and the supernatant above the clot, i.e. the blood serum is visually inspected for turbidity and for evidence of hemolysis. Turbid blood serum samples and samples with grossly visible pink discoloration were not subjected to further analysis even though we have established in separate control experiments that moderate turbidity and hemolysis do not affect the outcome of the results (data not shown).
For immediate use, 200 μl of the blood serum is aliquoted into a well of an 8-well chambered coverglass (Lab-Tek Chambered Coverglass, Thermo Scientific, USA), mixed with 1.6 μl of 2.5 mM ThT to a final concentration of 20 μM ThT and subjected to FIFA as described below. All experiments are run in duplicates.
In order to assess the effect of short-term serum storage on the outcome of the analysis, the serum is suspended and 200 μl aliquots are transferred to 0.5 ml Eppendorf Safe-Lock Centrifuge Tubes and stored at −20° C. for 2, 4 or 24 weeks. Only one freeze-and-thaw cycle was allowed.
Blood plasma: To extract blood plasma, 5 ml of blood is collected in a BD Vacutainer® Plastic K3EDTA tube with Lavender BD Hemogard™ Closure that contains 1.8 mg of the anticoagulant K3EDTA per 1 ml of blood, yielding an EDTA concentration of ˜7 mM. This concentration of EDTA neither interferes with Aβ aggregation, nor with the ThT assay, based on bulk ThT fluorescence spectroscopy measurements showing no effect of high EDTA concentrations (up to 10 mM) neither on the length of the lag phase nor on the slope of the fluorescence growth curve during the in vitro Aβ peptide aggregation process (data not shown). The tube is gently inverted 1800 and back 10 times and allowed to sediment for 60 min. Thereafter, the tube is centrifuged for 10 min at 2500×g and the supernatant above the cell layers, i.e. the blood plasma, is visually inspected for turbidity and for evidence of hemolysis. As described above, turbid blood plasma samples and blood plasma samples with grossly visible pink discoloration were discarded and not subjected to further analysis. For immediate use, 200 μl of blood plasma is aliquoted into a well of an 8-well chambered coverglass, mixed with 1.6 μl of 2.5 mM ThT to a final concentration of 20 μM ThT and subjected to FIFA following the same procedure as described for the blood serum.
In a limited set of experiments blood plasma is collected in BD Vacutainer® CTAD tube with Light Blue BD Hemogard™ Closure in order to assess the advantages of using citrate buffer. Differences between EDTA or citrate plasma samples were not observed.
Cell lysate: To prepare blood cell lysates, 0.1 ml of 1% Triton X-100 in 150 mM NaCl is added to the cell pellet remaining at the bottom of the BD Vacutainer® Plastic K3EDTA tube with Lavender BD Hemogard™ Closure after removal of the blood plasma; the content is centrifuged for 10 min at 2500×g and the cell lysate is removed for analysis. For immediate analysis, 200 μl of cell lysate is aliquoted into a well of an 8-well chambered coverglass, mixed with 1.6 μl of 2.5 mM ThT to a final concentration of 20 μM ThT and subjected to FIFA following the same procedure as described for the blood serum.
Fluorescence Correlation Spectroscopy (FCS) is a quantitative analytical method with the ultimate, single-molecule sensitivity for the detection of bright fluorescent molecules in dilute aqueous solutions (26-32). FCS achieves single-molecule sensitivity by observing with high temporal resolution the time course of spontaneous fluorescence intensity fluctuations in a very small volume that is in conventional instrumental setups about 2×10−16 1-10×10−16 1. In such a tiny volume the background noise originating from molecules present in large access, such as the solvent molecules, is significantly reduced by looking at a small number of molecules at a time. Hence, the passage of a bright fluorescent molecule through the small observation volume gives rise to a prominent change in fluorescence intensity that can be readily detected.
To generate the tiny observation volume the instrumentation for FCS takes advantage of the specific arrangement of optical elements in a confocal microscope to sharply focus incident laser light into the sample through a high numerical aperture (NA) objective and further reduce the volume from which fluorescence is detected by placing a pinhole in the optically conjugate plane in front of the detector to eliminate out-of-focus light (
Different methods can be used to analyse the florescence intensity fluctuations recorded in an FCS experiment (28,30). Typically, temporal autocorrelation analysis is applied to derive a temporal autocorrelation curve (tACC) and read out the average number of molecules in the OVE from the amplitude of the tACC and the diffusion time from the characteristic decay time of the tACC (26,27,30). Details of temporal autocorrelation analysis and how to derive the average number of molecules in the OVE and the translational diffusion coefficient of the investigated particles is given in “Temporal autocorrelation analysis of fluorescence intensity fluctuations”. In this study, temporal autocorrelation analysis is used for instrument calibration, while the actual data analysis is performed by analysing the frequency of single events occurrence as described below, in Data analysis. This method is validated using standard series of dilute aqueous suspension of fluospheres (d=100 nm), described in detail in “Validation of data analysis using dilute aqueous suspension of 100 nm fluospheres”.
Time-resolved fluorescence intensity fluctuation measurements are performed using a ConfoCor 2 system (Carl Zeiss, Jena, Germany), consisting of an inverted microscope equipped with a C-Apochromat 40×, NA=1.2, water immersion UV-VIS-IR objective. ThT fluorescence is excited using the 458 nm line of the Argon laser. The incident laser light is tightly focused into the sample by passing through the objective lens; laser intensity measured at the objective is 6 μW. The elastically scattered light and the spectrally distinct fluorescence light are collected backward through the same objective lens and separated using the HFT 458 main dichroic beam splitter. The emitted light is spatially filtered by passing through a pinhole to the silicon avalanche photodiode detector (SPCM-AQR-1×; PerkinElmer, USA). The pinhole size in front of the detector was set to 70 μm (1 Airy).
Instrument calibration: Standard aqueous solutions of Rhodamine 6G (Rh6G), 10−25 nM, are used for instrument calibration. For this purpose, temporal autocorrelation analysis was applied (as described in “Temporal autocorrelation analysis of fluorescence intensity fluctuations”). The same optical setting that is used for ThT, as described above, is used for Rh6G and the signal was recorded in a series of 10 consecutive measurements, each measurement lasting 10 s. Under these settings, the translation diffusion time of Rh6G was determined to be τD,Rh6G=(24±2) pts (n=460); the counts per molecule and second (CPMS) was CPMS=(5.1±0.6) kHz, and the structural parameter was S=7 (
Measurement on blood serum: ThT serum fluorescence intensity fluctuations were recorded in a series of 300 measurements, each measurement lasting 10 s, yielding a total run time of 3000 s. All measurements were performed at 20° C. in an air conditioned room. The data were evaluated as described below.
The frequency with which the structured amyloidogenic nano-plaques pass through the OVE is determined by performing an automated single event counting analysis to identify rare bursts in ThT fluorescence intensity that reflect the occasional passage of ThT-reactive structured amyloidogenic nano-plaques through the OVE. For this purpose a program was written using the Matlab software. A fluorescence peak, i.e. “a single event”, is defined as an increase in fluorescence intensity, ΔF(t), that differs from the mean fluorescence intensity of the whole time series, (F(t)), by a value that is five times larger than the standard deviation (SD) of the whole time series, ΔF(t)=(F(t)−(F(t)))>5×SD. The number of observed fluorescence peaks is then normalized to the total measurement time (here 3000 s) and the thus obtained frequency of single events occurrence (fSEO) is expressed in s−1 and compared across samples.
The size of the ThT-reactive structured amyloidogenic oligomeric aggregates is determined in the following way. All recorded time traces were subjected to temporal autocorrelation analysis. Time traces where passage of ThT-reactive structured amyloidogenic oligomeric aggregates is observed gave rise to a tACCs, whereas time traces that only contained background signal did not show any tACC and were excluded from further analysis. All tACCs were then normalized to the same amplitude, G(τ)=1 at τ=10 μs, and all tACCs from the same group, patient or the control group, were combined to yield an average tACC for the patient and the control groups, respectively. Difference in size is then assessed from the difference in characteristic decay time of the tACCs—the longer the characteristic decay time of the tACC, the larger is the nano-plaque size.
The above described procedures for determining the fSEO and the size of the ThT-reactive structured amyloidogenic oligomeric aggregates were validated using dilute aqueous suspension of 100 nm fluospheres, as described in “Validation of data analysis using dilute aqueous suspension of 100 nm fluospheres”,
Researchers performing the time-resolved ThT serum FIFA were blinded as to the individual diagnoses until the data analysis was completed. Likewise, the diagnosis was established using standard clinical tests and results of the time-resolved ThT serum fluorescence intensity fluctuation analysis were not known by the clinicians until the study was completed and the code was revealed. In order to assess whether the mean fSEO values in the control and the patient cohorts are significantly different, unpaired t-test analysis was performed using the online available GraphPad Software tool (http://www.graphpad.com/quickcalcs/ttestl.cfm?Format=SD).
All chemicals were used without further purification and purchased from commercial sources as follows: Rhodamine 6G (Sigma-Aldrich); Thioflavin T (Sigma-Aldrich); Carboxylate functionalized quantum dot nanocrystals, d=20 nm, emission maxima at 525 nm (Qdot® 525 ITK™ Carboxyl Quantum Dots) and yellow-green fluorescent (Ex/Em: 505/515) carboxylate-modified polystyrene nano/microspheres of diameter d=100 nm (FluoSpheres® Size Kit #2) from Molecular Probes. Fluosphere suspension was sonicated 30-60 min before use.
In temporal autocorrelation analysis, signal self-similarity analysis is performed to detect non-randomness in data, and to identify an appropriate time series model if the data are not random. As a first step in this process, the so-called normalized intensity autocorrelation function G(z) is calculated:
where F(t)
is the mean fluorescence intensity over the whole time series; δF(t)=F(t)-
(F(t)
a fluctuation in fluorescence intensity recorded at the time point t; δF(t+z)=F(t+τ)−
F(t)
is a fluctuation in fluorescence intensity in the same time series recorded at a later time point, t+τ; and τ is the time lag between them.
The normalized autocorrelation function G(t) is then plotted as a function of different time lags z, to yield an autocorrelation curve ACC. For processes that are random, G(t) 1 for all lag time values. For processes that are not random, the ACC has a maximal limiting value of G (τ) as τ→0, which decreases to the value of G(τ)=1 at long time lags, indicating that the correlation between the initial and the current property value of the fluorescence signal has been lost. For the simplest case of fluorescence intensity fluctuations generated by free three-dimensional (3D) translational diffusion of fluorescent molecules, the ACC has one characteristic decay time, which represents the average time that it takes for a molecule to pass through the OVE, i.e. it is equal to the translational diffusion time (τD). The limiting value of G(t) at t=0, is inversely related to the average number of molecules (N) in the OVE and thus is representative of their concentration (26,27).
In order to extract N and τD values, the experimentally obtained ACC is fitted using a theoretical autocorrelation function (AFt). For example, if one fluorescent species is present in the sample and transition between the singlet and the triplet state is the only intramolecular process affecting the fluorescence of the observed molecule, the ACC can be described using the following AFt:
In equation (2) N is the average number of molecules in the OVE; S is the spatial parameter, also called structural parameter,
where
Spatial properties of the OVE are determined experimentally in instrument calibration measurements. The calibration is performed using a standard solution of a reference fluorescent dye for which the concentration and the translational diffusion coefficient are known. The experimentally derived ACC recorded for the standard solution is fitted by the autocorrelation function (2) allowing all parameters to freely vary and the values for N, τD, S2, T and τT are determined by fitting. Using the known value of the translational diffusion coefficient D for the reference dye and the determined values of τD, the radial radius of the OVE can be determined from:
and the axial radius
For our system, standard solutions of Rh6G in water were used for instrument calibration (
Dilute aqueous suspension of fluospheres (d=100 nm) of known concentration, 1 fM≤c≤50 nM, were used to validate the diffusion time determination procedure (
Serum without ThT was used as a control for assessing the effect of random disturbances on the obtained results (
Blood serum is a complex aqueous mixture of different classes of chemical compounds, of which lipids (in the form of triglycerides) and proteins (albumin and immunoglobulins) are most abundant. Many of the compounds that blood serum is comprised of are natively fluorescent and absorb light at 458 nm, such as flavin (FAD) and pyridinic (NADH) coenzymes and lipopigments. As a consequence, blood serum exhibits autofluorescence and gives also rise to a distinct tACC with an amplitude Aserum=(0.003±0.002) and a single characteristic decay time τserum=(55±15) μs (
When ThT is added to blood serum, several important differences are observed. Most notably, the amplitude of the tACC decreases markedly (AThT=(0.0014±0.0007)) and a small but discernible contribution of one or more components with long characteristic decay time is observed (
Decrease in the amplitude of the ACC, which indicates that the average number of observable molecules increases in the OVE upon ThT addition, is consistent with making otherwise invisible ThT-reactive entities visible. ThT fluorescence in blood serum was in detail characterized by bulk fluorescence spectroscopy by Chauhan et al. (34) and Griffin et al. (35). Using flotation fractionation, Griffin et al. were able to show that about 94% of ThT reactivity in blood serum is associated with the non-apoB containing fraction of blood serum and identified glycated and other chemical adducts of water-soluble serum albumin as the main contributors to the baseline ThT serum fluorescence (35). The observed appearance of a second component with significantly longer diffusion time is consistent with making visible large ThT-reactive entities that are present at very low levels, hence the small relative amplitude of the second component.
As expected based on previously published results (34,35), the mean serum ThT fluorescence intensities showed considerable variation between individuals (Table 1). However, in contrast to previous observations by bulk ThT fluorescence spectroscopy, the mean count rate values between the patient, CRp=(202±92) kHz, and the control groups, CRc=(155±43) kHz, differed significantly, as evident from the two-tailed P value, P=0.0126.
Time-resolved detection of ThT serum fluorescence reveals the infrequent occurrence of very well identifiable peaks in fluorescence intensity that differ from the mean fluorescence intensity by a value that is more than five times larger than the standard deviation (SD) of the time series, (F(t)−<F(t)))>5×SD (
In order to ascertain that these outbursts do not reflect electrical disturbances or occasional passage of small air bubbles or dust particles through the OVE, but rather reflect the passage of ThT-reactive amyloidogenic structured nano-plaques, control measurements were performed in the serum without ThT. As can be seen (
We therefore present the occurrence of fluorescence intensity bursts, i.e. the occurrence of single events and the frequency of their appearance, termed “frequency of single event occurrence” (fSEO), as our direct measure of the concentration of structured nano-plaques in the blood serum.
The Frequency of Single Events Occurrence in the Blood Serum of AD Patients is Higher than in the Blood Serum of Apparently Healthy Controls
The frequency of single event occurrence, calculated as described in the Materials and Methods: Data analysis subsection, differs between the patient group, fSEOp=(2.3±1.7)×10−3 s−1, and the control group, fSEOc=(1.5±1.2)×10−3 s−1. A two-tailed P value, P=0.0418, determined by unpaired t-test analysis suggests that the difference in the frequency of single events occurrence between the patient group and the control group is statistically significant (
Our analysis also shows that the serum concentration of structured amyloidogenic nano-plaques increases somewhat with aging, as evident from the frequency of single event occurrence that increases with a slope of (1.6±1.0)×10−5 s−1 year−1 and an intercept of (9.4±0.6)×10−4 s−1 (
The Size of the ThT-Reactive Amyloidogenic Structured Nano-Plagues in the Blood Serum of AD Patients is Larger than in the Blood Serum of Apparently Healthy Controls
Temporal autocorrelation analysis, performed as described in Materials and Methods: Data analysis, shows an obvious difference in the characteristic decay time between the tACCs recorded for the two groups, with a markedly longer decay time for the patient group (
We have compared the results obtained by time-resolved ThT FIFA in blood serum with the results obtained using established biochemical biomarkers in the cerebrospinal fluid (CSF), including CSF levels of the 42 amino acid form of the Amyloid beta peptide (Aβ42) and the total CSF levels of the tau protein (t-Tau). The comparison shows that the results obtained by time-resolved ThT blood serum FIFA obviously match the results obtained by CSF biochemical analysis (
In the presence of amyloid fibrils and structured amyloidogenic oligomers ThT acquires fluorescence excitation and emission spectra that are markedly distinct from those of the free dye (
While classical bulk ThT fluorescence spectroscopy is very important for basic studies of Aβ aggregation kinetics (43), this method also has serious limitations. Most notably, classical bulk ThT fluorescence spectroscopy involves ThT fluorescence signal averaging over all Aβ aggregation states that are present in the sample, and temporal averaging of ThT fluorescence intensity with a signal integration time that is typically of the order of 1-10 s (43). Under such measurement conditions, the contribution of the signal that originates from rare amyloidogenic structured aggregates is too small to be discernible from the background. Hence, the usefulness of bulk ThT fluorescence spectroscopy in biomedical diagnostics of amyloid-featuring diseases has been shown to be limited (34,35).
In contrast to bulk ThT fluorescence spectroscopy, time-resolved detection of fluctuations in ThT fluorescence intensity in a sub-femtoliter OVE does not involve such averaging (5), allowing us to identify with fidelity the passage of ThT-active structured amyloidogenic aggregates through the OVE (
Immune-based assays can be used to confirm the results of the method, such as the most frequently used Enzyme-Linked Immunosorbent Assay (ELISA), digital ELISA, sandwich ELISA (45,46) sandwich ELISA (47) and associated methods recently reviewed by Andreasson et al. (48), and immunoprecipitation-mass spectrometry (IP-MS) (49) all have in common inherent limitations that are related to the specificity and the sensitivity of the antibody-antigen reaction (50-52). In the case of Aβ immune-based assays, the following difficulties, to name but a few, are typically encountered: monomeric Aβ that is present in excess can occupy binding sites on the antibody, thereby interfering with the detection of Aβ oligomers (53); interference from the p3 peptide and Aβ-catabolic peptides derived from the non-amyloidogenic pathway of APP processing my introduce uncertainty in the interpretation of results (54); substrates for signal amplification and detection are inherently unstable and may produce signal even in the absence of enzyme (48). Proteomic approaches using Sodium Dodecyl Sulfate-PolyAcrylamide Gel Electrophoresis (SDS-PAGE), 2D-PAGE, Liquid Chromatography (LC), Mass Spectrometry (MS), Matrix Assisted Laser Desorption/Ionization-Time of Flight (MALDI-TOF) mass spectrometry, Electrospray ionization (ESI) mass spectrometry, Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS) and related techniques, characterize directly the molecule of interest with high sensitivity and specificity, thereby providing invaluable information (55). However, these techniques are complicated by the difficulty to detect low-abundance proteins in complex mixtures such as biological fluids due to limitations in the dynamic range; inability to measure intact larger proteins and involved sample preparation procedures (56). As a consequence, there is to date no CSF biomarker discovered in proteomic studies that has reached the clinic (57).
In summary, we would like to underline that currently available immune-based methods clinically used for CSF and blood plasma biochemical analysis show that the concentration of Aβ42 decreases in the CSF and blood plasma of AD patients (23,36,49,58-60). This is very likely due to the fact that the antibodies largely recognize monomeric Aβ peptides, whereas aggregation renders Aβ peptides into states that are not easily recognized by immunochemistry as discussed by Klaver et al. (53) and references cited therein. In contrast, our method measures the ThT active states in the blood serum that corresponds to the actual amyloid states present in the fibrils seen in the brain. Obviously, the two types of observations both correlate with the AD pathology of the patient, as can be seen from the data presented in
0.5 ml Cerebral Spinal Fluid (CSF) aliquot stored at −80° C. in a polypropylene tube without any additives was used. The sample was allowed to taw for 60 min at room temperature. Thereafter, 200 μl aliquots were transferred to an 8-well chambered coverslide containing 10 μl of aqueous ThT solution in each well. The sample was gently mixed by dispensing/drawing several times and subjected to analysis. Analysis was performed in duplicates.
A midstream first morning urine specimen from apparently healthy donors was collected into a sterile container without any urine preservatives. The specimen was allowed to sediment for 60 min at room temperature. Thereafter, 200 μl aliquots were transferred to an 8-well chambered coverslide containing 10 μl of aqueous ThT solution in each well. The sample was gently mixed by dispensing/drawing several times and subjected to analysis. Analysis was performed in duplicates.
Saliva samples from apparently healthy donors were taken in the morning, 2 hours after breakfast and after morning hygienic procedures. During this time the donor was allowed to take water only. After cursory cleaning the mouth by flushing with deionized water just before sample collection, 2 ml of naturally flowing saliva were passively sampled (without aspiration) and collected into a sterile container immersed in an ice-bath. After collection, 200 μl aliquots were transferred to an 8-well chambered coverslide containing μl of aqueous ThT solution in each well. The sample was gently mixed by dispensing/drawing several times, allowed to temperate for 15 min and subjected to analysis. Analysis was performed in duplicates.
| Number | Date | Country | Kind |
|---|---|---|---|
| 1805466.8 | Apr 2018 | GB | national |
| Filing Document | Filing Date | Country | Kind |
|---|---|---|---|
| PCT/EP2019/058206 | 4/1/2019 | WO | 00 |
