Patent Application
20230088285
The present invention relates to aortic aneurysm growth progression and to materials, apparatus and methods for determining a risk factor or value indicative of predicted growth of an abdominal aortic aneurysm of a patient. In particular, the aspects of the invention may be used to predict future progression of abdominal aortic aneurysms.
Abdominal aortic aneurysms (AAA) are pathological dilatations of the abdominal aorta which can result in rupture and mortality. Patients with AAAs have an increased risk of cardiovascular morbidity. Aortic aneurysms, in particular abdominal aortic aneurysms, are associated with biological changes in the vasculature, features of systemic inflammation and endothelial dysfunction. Rupture of an AAA results in death, even in >50% of those who receive prompt surgery. AAAs may present in a subject in a variety of sizes. An AAA is typically defined as a region of an abdominal aortic artery having an outer aortic diameter greater than 30 millimetres. If the outer diameter of the aorta in the region of the aneurysm is 55 millimetres or greater, the abdominal aortic aneurysm is considered to be large. Surgery to treat AAAs is considered where an AAA is identified having a diameter of 55 millimetres or greater because the risk of rupture of the AAA is greater than the traditional risks associated with surgery. In current practice, surgery is typically not considered where the identified AAA has a diameter less than 55 millimetres as the risks of surgery are generally considered to outweigh the risk of aneurysm rupture. Currently, where an AAA is identified in a patient, and the AAA has a size between approximately 30 millimetres and 55 millimetres, the size of the AAA is monitored over time. Aneurysms may grow at different rates, if at all. If the aneurysm grows to exceed 55 millimetres, then surgery will typically be performed to treat the aneurysm.
In our earlier application, WO 2017/212210, to which further reference should be made, we observed accelerated systemic endothelial dysfunction as measured by brachial artery flow-mediation vasodilation (FMD) in AAA patients and were able to correlate FMD values with future AAA growth.
AAAs have been shown to contain intra-luminal thrombus (ILT). It can also be observed that systemic endothelial dysfunction is reversed by AAA repair. Since ILT is either removed or excluded from circulation after successful repair of AAAs, the present inventors have hypothesised ILT to be the source of mediators that contribute to AAA growth. It is with this in mind that the present invention has been devised.
In one aspect, the present invention provides the use of at least one protein selected from at least one of Group A, Group B, Group C and/or Group D as a biomarker for determining a risk value of aneurysm future growth for a subject.
Group A is a group of proteins determined to be present at differentially expressed concentrations in subjects showing fast aneurysm growth compared with subjects showing slow aneurysm growth.
Group B is a group of proteins determined to be significantly different in the systemic circulation of subjects following aneurysm surgery.
Group C is a group of proteins determined to be present in thrombus of an aneurysm.
Group D is a group of proteins determined to be present in supernatant of an extracted thrombus sample (in other words, is released from the thrombus).
In another aspect, the present invention provides a method of determining a risk value of future aneurysm growth for a subject, the method comprising receiving a blood sample of the subject, determining a protein concentration in the blood sample for at least one protein selected from at least one of Group A, Group B, Group C and/or Group D as defined in claim 1; comparing the determined protein concentration with a reference value for the protein and an index of aneurysm growth for the protein; and determining the risk value of future aneurysm growth based on the comparison.
In a further aspect, the present invention provides an apparatus for determining a risk value of future aneurysm growth for a subject, the apparatus comprising a data input to receive at least one value of protein concentration of a blood sample of the subject, the protein being at least one protein selected from at least one of Group A, Group B, Group C and/or Group D as defined in claim 1; at least one processor; and a memory comprising instructions executable by the at least one processor to: i) compare the or each protein concentration with a respective protein reference value and an index of aneurysm growth for the protein; and ii) determining the risk value of future aneurysm growth based on the comparison.
Optionally, the apparatus further comprises a blood sample analysis module.
Preferably, the at least one protein is selected from at least two of Group A, Group B, Group C and Group D; or at least three of Group A, Group B, Group C and Group D; or is selected from Group A, Group B, Group C and Group D.
In certain examples, the at least one protein is at least one protein selected from proteins present in both Group A and Group B.
In certain examples, the at least one protein is at least one protein selected from proteins present in both Group A and Group B and at least one of Group C and Group D.
In a preferred embodiment, the at least one protein is at least one protein selected from proteins present in Group A, Group B, Group C and Group D.
Preferably, the at least one protein is at least one of attractin, Apolipoprotein A4, Complement C8 and HSP90AA5P.
In certain examples, Group A is a group of proteins as set out in Table 1 below; and/or Group B is a group of proteins as set out in Table 2 below; and/or Group C is a group of proteins as set out in Table 3 below; and/or Group D is a group of proteins as set out in Table 4 below.
The above and other aspects of the present invention will now be described in further detail, by way of example only, with reference to the following examples and the accompanying drawings, in which:
In accordance with the present invention there is provided a method for determining a risk value indicative of predicted growth of an abdominal aortic aneurysm of a patient. The method comprises determining or receiving a value representative of or representing a blood concentration of at least one protein which the present inventors have determined to be indicative biomarkers of aneurysm progression. The method also comprises determining a risk value indicative of predicted growth by evaluating the received values with reference values in an aneurysm risk model.
The aneurysm risk model relates to a risk value indicative of predicted growth of an abdominal aortic aneurysm for a given value representative of or representing the size of an abdominal aorta/aortic aneurysm and a given protein concentration. The value representative of or representing the size of an abdominal aortic aneurysm may be the size of the aneurysm.
The reference value may be an average or expected value for the index of blood protein concentration.
In some embodiments, the aneurysm risk model is a look-up table.
The risk value indicative of predicted growth of an abdominal aortic aneurysm of a patient may be a qualitative (e.g. fast, medium or slow) or quantitative (e.g. mm per unit time or percentage per unit time) measurement.
In current practice, the size of a patient's abdominal aortic aneurysm is used to guide a decision on whether or not the abdominal aortic aneurysm should be surgically repaired. As mentioned above, surgical intervention is recommended once the aneurysm reaches a surgical threshold size of, for example, 55 mm. Below this threshold, the risks of surgery are generally considered to outweigh the benefits of aneurysm removal.
It has been found that this prior approach has intrinsic shortcomings because aneurysm size may not an absolute predictor of the risk of rupture. Furthermore, the rate of AAA progression may vary significantly between individuals. For example, there may be a risk of rupture in those individuals with relatively smaller AAAs (e.g. 35-55 mm or 40-55 mm), and many patients with an initially small/moderate size AAA may progress and require surgery within 5 years. This may be an important consideration in ageing populations, as the risks associated with undergoing interventions increase with age.
Thus, in a preferred embodiment, the method is used to determine a risk value indicative of predicted growth of an abdominal aortic aneurysm of a patient identified as having an abdominal aorta/aortic aneurysm that is less than 55 mm, for example, 30 to 55 mm, preferably 35 to 55 mm, more preferably 40 to 55 mm in size. Thus, the method may comprise receiving a value representative of or representing a size of the abdominal aorta/aortic aneurysm, wherein the size of the abdominal aorta is less than 55 mm, for example, 30 to 55 mm or, preferably, 35 to 55 mm or 40 to 55 mm. The subgroup of patients with AAA size between 35 and 55 mm or preferably 40 and 55 mm may be particularly important in terms of potential for change in clinical practice. Surgeons may be convinced to provide surgical intervention in this subgroup (e.g. 35-40 mm or 40-55 mm) of patients when there is sufficient justification based, for example, on predicted growth rate.
The method of the present invention may further comprise guiding a decision on a clinical intervention of the patient based on the determined risk value. For example, if the determined risk value of a patient is high, the patient's aneurysm may be fast-growing. Thus, the patient in question may benefit from surgery even though his/her aneurysm is below a surgical threshold (e.g. 55 mm) size at which surgery is usually performed. The method of the present invention may be used to identify patients who may benefit from early invasive clinical intervention, for example, even before the patient's aneurysm reaches a surgical threshold (e.g. 55 mm) size. In some embodiments, the clinical intervention may be an invasive clinical intervention, for example, if the size of the abdominal aorta/aortic aneurysm is below a surgical threshold, for instance, from 40 to 55 millimetres. Thus, the method of the present invention can be used to negate unnecessary delay in surgery (as those patients with fast growing AAAs would require surgery in the near future).
The method of the present invention may also be used to guide a decision on a clinical intervention that is non-invasive or cognitive. For example, where the determined risk value of a patient is low, the patient's aneurysm may be slow-growing. Thus, the patient in question need not be monitored highly frequently even, for example, if the patient's aneurysm is relatively close to the threshold size (e.g. 55 mm) at which surgery is usually performed. Accordingly, a schedule e.g. for the patient's future check-ups may be determined at least in part by the determined risk value. Thus, in some embodiments, the method of the present invention may be used to guide a physician's decision as to, for example, the time interval between the patient's follow-up appointment(s). In some embodiments, this surveillance or time interval may be individualised to the patient based on the predicted propensity of future AAA growth.
The aneurysm risk model may be generated based on: protein concentration measurements of at least one patient taken at a first time; and protein concentration measurements of the at least one patient taken at a second time different from the first time.
In certain embodiments, the aneurysm risk model may also generated on the basis of a value representative of a size of the abdominal aorta/aortic aneurysm at the first time and a size of the abdominal aorta/aortic aneurysm artery at the second time.
In some examples, the aneurysm risk model is generated from data collected from a number of patients e.g. in a clinical trial.
The method may also comprise measuring the size of the abdominal aorta/aortic aneurysm of a patient. Any suitable method of measurement may be employed. For example, the maximal anteroposterior diameter (outer-to-outer) of an abdominal aorta/aortic aneurysm may be determined by, for example, by ultrasound scans, computerised tomography, or magnetic resonance imaging.
In one embodiment, the present disclosure provides a method for determining a risk value indicative of predicted growth of an abdominal aortic aneurysm of a patient having an abdominal aortic aneurysm that is less than 55 mm, preferably 30 to 55 mm, more preferably 35 to 55 mm, yet more preferably 40 to 55 mm in size. The method comprises receiving a value representative of or representing a size of the abdominal aorta/aortic aneurysm, wherein the received value is representative of an abdominal aorta/aortic aneurysm that is less than 55 mm, preferably 30 to 55 mm, more preferably 35 to 55 mm, yet more preferably 40 to 55 mm in size. The method also comprises receiving a protein concentration value for at least one protein in a blood sample of the patient. The method further comprises determining a risk value indicative of predicted growth by evaluating the received values with those in an aneurysm risk model. The aneurysm risk model relates to a risk value indicative of predicted growth of an abdominal aortic aneurysm for a given value representative of or representing the size of an abdominal aorta/aortic aneurysm and a given protein concentration value. The given value representative of or representing the size of an abdominal aorta/aortic aneurysm of the risk model may be a value that is representative of or representing an abdominal aorta/aortic aneurysm that is less than 55 mm, preferably 30 to 55 mm, more preferably 35 to 55 mm, yet more preferably 40 to 55 mm in size.
In some examples, the method can be used to determine a risk value indicative of predicted growth of an abdominal aortic aneurysm of a patient having an abdominal aortic aneurysm that is 35 to 55 mm in size, preferably 36 to 53 mm, more preferably 38 to 50 mm in size. The method may involve receiving a value representative of or representing a size of the abdominal aorta/aortic aneurysm, wherein the received value is representative of or representing an abdominal aorta/aortic aneurysm that is 35 to 55 mm in size, preferably 36 to 53 mm, more preferably 38 to 50 mm in size. The given value representative of or representing the size of an abdominal aorta/aortic aneurysm of the risk model may be a value that is representative of or representing an abdominal aorta/aortic aneurysm that is 35 to 55 mm in size, preferably 36 to 53 mm, more preferably 38 to 50 mm in size.
In accordance with a further aspect of the present invention, there is provided an apparatus for determining a risk value indicative of predicted growth of an abdominal aortic aneurysm of a patient. The apparatus comprises a data input to receive a value representative of or representing a size of an abdominal aorta/aortic aneurysm of a patient; and a protein concentration value for at least one protein in a sample of blood of the patient. The apparatus also comprises at least one processor; and a memory comprising an aneurysm risk model relating to a risk value indicative of predicted growth of an abdominal aortic aneurysm for a given value representative of or representing the size of an abdominal aorta/aortic aneurysm and a given blood protein concentration value. The memory also comprises instructions executable by the at least one processor to cause the processor to retrieve from the aneurysm risk model, using the received data inputs, a risk value indicative of predicted growth of an abdominal aortic aneurysm.
In the apparatus described herein, the data input may receive a value representative of or representing a size of the abdominal aorta/aortic aneurysm; and a protein concentration value for at least one protein in the blood of the patient.
In some embodiments, the data input may be a user input device such as a touchscreen interface or a keypad. The data input may be a removable memory connector to receive a removable storage medium to store a value representative of or representing a size of an abdominal aorta/aortic aneurysm of a patient; and a protein concentration value for a blood sample of the patient.
In some embodiments, the apparatus may further comprise a blood sample analysis module in data communication with the data input and configured to analyse one or more predetermined proteins in a blood sample.
Where the apparatus comprises a data memory in data communication with the data input, the data memory may be configured to store one or more of the at least one value representative of or representing a size of an abdominal aorta/aortic aneurysm of a patient; and a blood protein concentration value for at least one protein in a blood sample of the patient. The memory may comprise instructions to cause the processor to read the one or more of the value representative of or representing a size of an abdominal aorta/aortic aneurysm of a patient; and a blood protein concentration value for at least one protein in a blood sample of the patient from the data memory. The memory may further comprise instructions to cause the processor to measure the size of the abdominal aorta/aortic aneurysm.
In yet another aspect, the present invention provides a non-transitory machine-readable storage medium encoded with instructions executable by a processor for determining a risk value indicative of predicted growth of an abdominal aortic aneurysm of a patient. The machine-readable storage medium comprises instructions to receive a value representative of or representing a size of the abdominal aorta/aortic aneurysm; and a blood protein concentration value of the patient. The machine-readable storage medium also comprises instructions to determine the risk value indicative of predicted growth by evaluating the received values with those in an aneurysm risk model, the aneurysm risk model relating to a risk value indicative of predicted growth of an abdominal aortic aneurysm for a given value representative of or representing the size of an abdominal aortic aneurysm and a given blood protein concentration value
The non-transitory machine-readable storage medium may further comprise instructions to receive a value representative of or representing a size of the abdominal aortic aneurysm; and a blood protein concentration value of an artery of the patient.
The non-transitory machine-readable storage medium may further comprise an aneurysm risk model in the form of a look-up table.
In yet a further aspect, there is provided an apparatus for determining an index of aortic aneurysm future growth for a subject. The apparatus comprises a data input for receiving at least one index of blood protein concentration of a subject, at least one processor, and a memory comprising instructions executable by the at least one processor. The instructions are to cause the at least one processor to compare the or each index of blood protein concentration with at least one of a respective reference value. The instructions may further cause the processor to determine the index or risk of aortic aneurysm future growth based on the comparison. The method may determine an index of abdominal aortic aneurysm future growth. It will be understood that the future growth of the aortic aneurysm is a determination of the future progression of the aortic aneurysm.
Thus, there is provided apparatus for determining an index of aneurysm future progression (e.g. growth) for a subject. The apparatus may be used on subjects regardless of knowledge of the presence of an aneurysm in the subject. In many examples, the apparatus may be used on subjects where the presence and size of an aneurysm are already known.
The index of aneurysm future progression may be qualitative or quantitative.
The blood protein concentration is at least one protein selected from Group A proteins, Group B proteins, Group C proteins and Group D proteins as defined below; or at least one protein selected from two, three or all four groups.
In preferred embodiments, the at least one protein is at least one of attractin (UniProt ID 075882), Apolipoprotein A4 (UniProt ID P06727), Complement C8 (UniProt ID P07360) and HSP90AA5P (UniProt ID Q58FG0).
The memory may further comprise instructions to cause the processor to analyse, in vitro using a blood sample analysis module, a sample derived from a blood sample of the subject.
There is also provided a computer-implemented method for determining an index or risk of aneurysm future growth for a subject. The method is implemented on a computer comprising at least one processor and a memory comprising instructions to be executed by the at least one processor. The method comprises: the memory of the computer receiving at least one value of protein concentration in a sample of blood of the subject. The method further comprises the at least one processor comparing the at least one value with at least one respective reference value. The method further comprises the at least one processor determining the index of aneurysm future growth based on the comparison.
The computer-implemented method may further comprise storing index of aneurysm future growth in the memory or a further memory.
The invention extends to a non-transitory machine-readable storage medium encoded with instructions executable by a processor. The machine-readable storage medium comprises instructions to receive at least one value of protein concentration in a sample of blood of the subject. The machine-readable storage medium further comprises instructions to compare the value of protein concentration in a sample of blood of the subject with at least one respective reference value. The machine-readable storage medium further comprises instructions to determine an index of aneurysm future growth based on the comparison.
It will be understood that the present disclosure extends to any of the steps of a method performed by the apparatus disclosed herein.
The present invention also relates to the use of the proteins as defined in Group A, Group B, Group C and Group D, as defined below, as biomarkers for the determination of a risk value or index for future aneurysm growth for a subject.
Plasma samples from patients recruited to the study were collected at baseline and at one year from each patient. Plasma samples were also collected before and at 10-12 weeks after surgery from each patient (n=29). Paired aneurysm wall, ILT and omental biopsies were collected intra-operatively during open surgical repair (n=3). In addition to analyses of the tissue, supernatant was obtained from ex vivo culture of these paired tissue samples. Samples were subjected to non-targeted LC-MSMS workflow after trypsin digest, using the Universal method to discover novel proteins. LC-MSMS data was analysed using the Progenesis QI pipeline.
The median AAA size at baseline was 48 mm. 59 patients were prospectively followed for 12 months. The median growth rate of AAA was 3.8%/year (IQR 1.9% to 6.8%).
Venous blood samples were collected in tubes containing an anticoagulant such as ethylenediamine tetraacetic acid (EDTA). Plasma samples were centrifuged at room temperature for 12 minutes at 1300 g. Thereafter, the plasma supernatants from the blood were aspirated and centrifuged again for 15 mins at 2500 g. This two stage centrifugation process results in separation of platelet poor plasma. Aliquots of the EDTA plasma were stored at −80° C. for subsequent analysis.
In a designated area of theatre, a pre-prepared trolley housed all the necessary equipment and consumables required for specimen retrieval. Upon entering the abdominal cavity, the surgeon removed a wedge of omentum and an omental artery (OA) was dissected from within it. Some of the omentum was stored in ice-cold RPMI 1640+FCS 5% for the secretome experiments. The remaining omentum and OA were biobanked and some was also fixed using optimum cutting temperature (OCT) solution and paraformaldehyde (PFA) techniques. Prior to the aortic clamp being placed, the surgeon marked the maximal area of the aneurysm. Once the clamps were placed, a cranio-caudal incision was made into the aortic sac, and any residual blood was cleared with suction. The intraluminal thrombus (ILT) was delivered through the aortic incision and on the research table was rinsed thoroughly with 0.9% normal saline to remove any contaminating blood. This was then split up in to pieces, from the luminal and abluminal areas respectively. Fragments were snap frozen for subsequent analysis.
A cranio-caudal aortic anterior aneurysm wall strip from the renal arteries to the iliac bifurcation was trimmed away, spanning, approximately 15 mm in width. A Ligaclip® on the proximal (cranial) aspect denoted the orientation of the specimen. The aortic wall was rinsed through thoroughly with sterile 0.9% normal saline to remove any blood and debris. Any visible fat was trimmed off the adventitia. The specimen was divided in fragments and snap frozen for subsequent analysis.
Working under sterile aseptic conditions in a tissue culture hood, six pieces of each tissue type (ILT, aortic wall, omentum) were dissected out in 3 mm×3 mm blocks and placed in a 6-well plate (Corning, USA) and resuspended in 2 mL of RPMI 1640+5% FCS. One well was used as a control, following the same sequential washing and media change steps with no tissue in it. The 6-well plates were then placed in to the incubator at 37° C. with 5% CO2.
Giving the tissue a chance to recover and equilibrate, after an hour they were removed and washed with pre-warmed phosphate-buffered saline (PBS-Lonza) and then serum free RPMI media (Lonza) was added. After 24 hours in the incubator, the plates were removed, and the conditioned media was collected. It was then centrifuged at 3000 g for 10 mins to pellet the remaining cells and cellular debris, and the secretome supernatants were then aspirated and stored at −80° C. in 250 μL aliquots (Cryovial).
Protein Extraction from Plasma/Tissue/Supernatant for Proteomic Analysis
Frozen tissues were placed on a dry ice-chilled Steel BioPulverizer (BioSpec, USA) and the frozen tissues were shattered into fine powder by a sharp blow with a hammer. Broken tissue powder was weighed (20-30 mg) and aliquoted into Beads beater tube kept on dry ice. Pulverized tissues were homogenised in beads-beater tubes containing RIPA lysis buffer (25 mM Tris HCl, pH 7.6, 150 mM NaCl, 1% NP-40, 1% sodium deoxycholate, 0.1% SDS) to make it 20 mg/ml. Tissues were homogenized for 4 times at 6,500 Hz for 40s in a beads-beater (Stretton, UK) with chill on ice during each interval. The samples were centrifuged at 10,000 g for 5 min at 4° C. to remove insoluble tissue debris.
The protein concentration in the homogenates were determined by BCA protein assay (bicinchoninic acid) (Thermo Fisher, UK) and 100 μg of total proteins were reduced by adding 200 mM of dithiothreitol (DTT) (Sigma, Germany) to a final concentration of 5 mM for 30 mins at room temperature. Then, alkylated by adding 200 mM of indole acetic acid (IAA) (Sigma, Germany) to a final concentration of 20 mM and incubate for 30 mins at dark. The samples were top up to 200 μl with 6M urea, 100 mM TrisHCL (tris(hydroxymethyl)aminomethane hydrochloride) pH 8.5. Six hundred microliter of Methanol and 150 μl of Chloroform were added and mixed by brief vortex. Then 450 μl of MilluQ-H2O was added and sample centrifuged for 1 min at 12,000 g. The upper aqueous phase was removed and 450 μl of Methanol were added to samples and centrifuged at 12,000 g for 5 min. The supernatant were removed and pellets resuspended in 50 μl of 6M Urea, 100 mM TrisHCL, pH 8.5. Urea concentration was reduced to less than 1M by adding 250 μl of Mil1Q-H2O. Trypsin was added in 1:30 ratio (trypsin:protein) and digested for overnight at 37° C. The peptides were purified by a SepPak C18 cartridge (Waters, UK), dried by Speed Vac centrifugation, and resuspended in 200 μl of buffer A (2% acetonitrile 0.1% formic acid) for LC-MS/MS analysis.
Plasma samples were selected from the cohort, based on the AAA growth characteristics. 10× fastest and 10× slowest growth were selected. 10 μl of EDTA plasma from each patient's samples was retrieved. The plasma samples were pooled in each group for the analysis (Fast vs Slow). Depletion of the top 12 abundant proteins was performed using the Thermos Top 12 Protein Depletion Spin Column (Catalogue #85164). The depleted samples were then processed through reduction, alkylation, chloroform precipitation and trypsin digest.
Tissue supernatant samples were assessed for their protein content using BCA assay. Volume required for ˜40 μg of protein was retrieved from each sample type for subsequent reduction, alkylation, chloroform precipitation and trypsin digest.
For peptide analysis, an uHPLC was coupled to a Hybrid Quadrupole-Orbitrap mass spectrometer (LUMOS Fusion, Thermo Scientific, UK). One microliter of 0.5 μg/μL tryptic digested peptides were injected into the LUMOS for analysis. Peptides were separated by a BEH130 C18 column (1.7 mm×25 cm, Waters) at a flow rate of 250 nL/min. The mobile phases consisted of water with 0.1% formic acid, 5% DMSO (buffer A) and 95% acetonitrile with 5% DMSO, 0.1% formic acid (buffer B). A 60 minutes linear gradient from 3% buffer A to 40% buffer B was used. The peptides were ionised by electro spray ionisation and the 20 most abundant ions per MS scan were fragmented by collision-induced dissociation (CID).
LC-MS/MS spectra was searched against Uniprot human database (version 2017, 20,205 entries) for peptide homology identification. The Uniprot IDs are given in the results below. Analysis of the dataset was performed using the Progenesis QI software (Nonlinear Dynamics). At least two unique peptides were used for protein quantitation using match between runs. The false discovery rate (FDR) was set to 1% for protein and peptide identification. Label free quantitation (LFQ) intensity data were used for further statistical analysis to compare across the different group of tissues. Differentially expressed proteins in the analysis were defined as proteins presenting a statistical difference across the group (P<0.05).
Statistical analyses were performed in Graphpad Prism Version 8.01. Exploratory data analysis was performed for the initial examination of the dataset. Summary statistics are presented in mean (with SD) or median (with IQR) depending on the normality of distribution. We opted to use non-parametric tests for all comparative analyses (Wilcoxon matched pairs signed rank test, Mann-Whitney test, Kruskal-Wallis test, and Spearman rank correlation), as many variables demonstrated non-Gaussian distributions. No transformation of data was performed.
From October 2013, 162 patients with AAAs were recruited (Male n=147; Females n=15). The median AAA diameter was 50 mm (IQR: 40-57 mm). The average age of participants was 75 (+1-7) years old at the time of consent. The majority were ex-smokers (66%) and 19% were current smokers. A history of symptomatic atherosclerotic arterial disease was prevalent in this group (ischaemic heart disease: 40%; peripheral arterial disease: 20%; cerebral vascular disease: 12%). The majority of participants reported a prior diagnosis of arterial hypertension (65%) and hypercholesterolemia (59%). However, these were well controlled by long term medical therapy [anti-hypertensive(s): 71%, statin: 75%, anti-platelet(s): 62%], as reflected by their controlled SBP/DBP (138/79±17/12 mmHg) and overall normal cholesterol profiles [median=3.9 mmol/L (IQR 3.3-4.7), lower than 5.2 mmol/L in 82% of participants] at the time of recruitment. Seventeen percent of the participants reported a history of diabetes mellitus, 19% had chronic respiratory disease, 19% had treated neoplasms, 24% had chronic kidney disease with eGFR<60 (Table 1). There was no correlation between flow mediation vasodilation at baseline with any demographic variables except the AP diameter of AAA.
Experiment 1: Comparison Between Plasma Samples of Those with Fast Vs Slow Growth of AAA in the Future 12 Months
The concentrations of 117 proteins were observed to be significantly different between the plasma samples between those patients showing fast AAA growth between the baseline and one-year analyses and those patients showing slow growth of AAA over the same period. These proteins are listed in Table 1 below and are referred to in the following discussion as Group A, or ‘Fast-v-Slow AAA growth’.
Experiment 2: Comparison Between Plasma Samples of Before and After Surgical AAA Repair
The concentrations of 258 proteins were observed to be significantly different between the plasma samples between those before and after surgery to repair the abdominal aortic aneurysms. These proteins are most likely to be released from the thrombus of the AAA, and are thus removed from entering circulation as the thrombus is removed en-bloc during the surgical repair. These proteins are listed in Table 2 below and are referred to in the following discussion as Group B proteins or ‘Before-v-After’ (surgery).
Experiment 3: Comparison Between Thrombus Tissue Samples Vs Controls
The abundance of 254 proteins was observed to be significantly higher in the thrombus tissue/ILT tissue compared with control (non-thrombus) tissue. These proteins are listed in Table 3 below and referred to in the following discussion as Group C proteins or ‘Thrombus tissue’.
Experiment 4: Comparison Between Thrombus Culture Supernatant Vs Controls
It was observed that 125 proteins were significantly more abundant in the supernatant obtained from culture of the thrombus tissue compared with the control samples. These proteins are listed in Table 4 below and referred to in the following discussion as Group D proteins or ‘Thrombus supernatant’.
The results of the above experiments are represented in
Comparison of the proteomics profile of aneurysm tissue, ILT, and omental artery show 128 proteins to be uniquely present in ILT. Analyses of the tissue culture supernatant further revealed four proteins: (i) that are uniquely present in ILT; (ii) that are released by ILT; (iii) systemic levels of which change after AAA surgery; and (iv) which differ between fast and slow growth AAAs.
These proteins are attractin (UniProt ID 075882), Apolipoprotein A4 (UniProt ID P06727), Complement C8 (UniProt ID P07360) and HSP90AA5P (UniProt ID Q58FG0).
To validate the LC-MSMS data, attractin was selected for further study. Attractin is present in Groups A, B and C. The attractin level in the bloodstream of an individual patient was measured by ELISA (R&D Quantikine DATRNO). Plasma attractin level is significantly higher in patients with fast AAA growth (
The data is set out in Table 6 below for slow or no growth over 12 months and Table 7 for fast growth.
Corresponding data for the other proteins of Groups A, B, C and D can be derived in a similar manner.
The logistic regression analysis allowed us to generate indices representing a probability of an individual's AAA being fast growth or slow/no growth in the subsequent 12 months. Setting a cut off value of 0.39 for the probability for slow or no growth (establishing an ‘Aneurysm Slow Growth Index’ or ASGI), the prediction had a sensitivity of 54% (7/13), a specificity 94% (46/49) and an accuracy 85% (53/62). For the prediction of fast growth, the logistic regression analysis generated a probability of an individual's AAA being fast growth in the subsequent 12 months. Using a cut off value of 0.42 for the probability of fast growth (establishing an ‘Aneurysm Fast Growth Index’ or AFGI), the prediction had a sensitivity 66% (14/21), specificity 85% (35/41) and accuracy 79% (49/62).
As taking the diameter of an AAA is routine practice in monitoring an AAA patient, the skilled clinician will, in practice, always have a value for the diameter of a particular patient's AAA available. Accordingly, given an AAA diameter at a particular moment in time, combined with a prediction of growth rate prediction derived from the protein concentrations determined as above, the clinician will be readily able to predict the time period over which an AAA is likely to grow in size to a point at which surgery needs to be considered. The clinician can consequently assess an appropriate time for a follow-up consultation.
This data supports the use of the proteins in each of groups A, B, C and D circulating in the blood as biomarker indicators of future aneurysm growth. The proteins can be used, either individually or in combinations, to predict future growth rates and, accordingly, provide a physician with information from which they can determine the frequency of follow-up monitoring and timing of surgical procedures to treat the aneurysm.
In some examples, the one or more protein levels are determined in respect of at least one protein in at least one of Group A, Group B, Group C and/or Group D.
It will be appreciated that examples described herein can be realised in the form of hardware, or a combination of hardware and software. Any such software may be stored in the form of volatile or non-volatile storage such as, for example, a storage device like a ROM, whether erasable or rewritable or not, or in the form of memory such as, for example, RAM, memory chips, device or integrated circuits or on an optically or magnetically readable medium such as, for example, a CD, DVD, magnetic disk or magnetic tape. It will be appreciated that the storage devices and storage media are examples of non-transitory machine-readable storage that are suitable for storing a program or programs that, when executed, implement examples described herein. Accordingly, examples provide a program comprising code for implementing a system or method as described herein and a machine readable storage storing such a program.
The proteins that are significantly different between the experiment and control groups from the above experiment thus fulfil the following criteria:
Consequently, we can conclude that these are proteins originating from thrombus of an AAA, and can be used as individual biomarkers within the bloodstream, or in combinations, for the prediction of AAA growth.
The present invention represents a significant breakthrough from previous methods of AAA growth prediction. Prior predictive models, including those set out in our previous application, WO 2017/212210, required the inclusion of a physiological measurement (FMD of brachial artery). Such procedures require a dedicated ultrasound measurement and cannot be derived by plasma sample measurement alone. By focusing on the role of thrombus as a source of systemic mediator release, we have determined novel protein sets that have a specific utility for AAA growth prediction.
Our previous model included nine proteins (Thrombospondin, CXCL10, IL6, IL8, RAGE, MIP1a, MIP1b, leptin, ICAM1) selected by the analysis of plasma samples of fast vs slow/no growth patients using an antibody array (R&D Proteome Profiler). Attractin has the same utility for AAA growth prediction as compared to the other 9 proteins combined. The present invention provides a method requiring, a minimum of only two input variables (AAA diameter and attractin or other marker selected from Group A or other groups or combinations of markers), both of which are readily measured in an outpatient setting. Consequently, with a point-of-care testing device (to measure attractin levels and those of other markers), it is now feasible to apply the present developments at the time of AAA screening and follow-up surveillance scans.
Throughout the description and claims of this specification, the words “comprise” and “contain” and variations of them mean “including but not limited to”, and they are not intended to (and do not) exclude other moieties, additives, components, integers or steps. Throughout the description and claims of this specification, the singular encompasses the plural unless the context otherwise requires. In particular, where the indefinite article is used, the specification is to be understood as contemplating plurality as well as singularity, unless the context requires otherwise.
Features, integers, characteristics, compounds, chemical moieties or groups described in conjunction with a particular aspect, embodiment or example of the invention are to be understood to be applicable to any other aspect, embodiment or example described herein unless incompatible therewith. All of the features disclosed in this specification (including any accompanying claims, abstract and drawings), and/or all of the steps of any method or process so disclosed, may be combined in any combination, except combinations where at least some of such features and/or steps are mutually exclusive. The invention is not restricted to the details of any foregoing embodiments. The invention extends to any novel one, or any novel combination, of the features disclosed in this specification (including any accompanying claims, abstract and drawings), or to any novel one, or any novel combination, of the steps of any method or process disclosed.
| Number | Date | Country | Kind |
|---|---|---|---|
| 2002930.2 | Feb 2020 | GB | national |
| 2014375.6 | Sep 2020 | GB | national |
| Filing Document | Filing Date | Country | Kind |
|---|---|---|---|
| PCT/GB2021/050511 | 3/1/2021 | WO |
