Patent Application
20240044924
The present disclosure relates to a method for determining a likelihood of a subject to respond to lipid lowering therapy and to a method for determining whether a subject is at risk of developing or having atherosclerosis and/or a cardiovascular disease.
Hypercholesterolemia, i.e. an elevated serum cholesterol level in the blood, is currently a leading cause for cardiovascular disease (CVD) in many geographical areas. The regulation of serum cholesterol levels is controlled by dietary intake, endogenous production, and cellular metabolism.
Statins are often used as the first line medication for subjects suffering from hypercholesterolemia. However, often subjects do not respond or achieve a target cholesterol level immediately or in the long term. Some patients do not adhere to statin therapy. Further, a significant portion of patients who have had a heart attack have a second attack within one year of the first attack. Thus there may be a need to lower the cholesterol level of such patients without waiting for a prolonged period to see if they respond to statin treatment. Further, most cholesterol lowering treatments and therapies affect cellular mechanisms, and therefore it may be highly beneficial to be able to quantify such cellular mechanisms.
This Summary is provided to introduce a selection of concepts in a simplified form that are further described below in the Detailed Description. This Summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter.
A method for determining a likelihood of a subject to respond to lipid lowering therapy is disclosed. The method may comprise determining a quantitative value of the ability of cells obtained from a biological sample of the subject to take up low-density lipoprotein (LDL), a quantitative value of the expression of LDL receptor (LDLR) in the cells, a quantitative value of the lipid storage capability of the cells, and/or a quantitative value of the lipid mobilization capability of the cells;
A method for determining whether a subject is at risk of developing or having atherosclerosis and/or a cardiovascular disease is also disclosed. The method may comprise determining a quantitative value of the ability of cells obtained from a biological sample of the subject to take up low-density lipoprotein (LDL), a quantitative value of the expression of LDL receptor (LDLR) in the cells, a quantitative value of the lipid storage capability of the cells, and/or a quantitative value of the lipid mobilization capability of the cells;
The accompanying drawings, which are included to provide a further understanding of the invention and constitute a part of this specification, illustrate embodiments and together with the description help to explain the principles of the invention. In the drawings:
According to a first aspect, a method for determining a likelihood of a subject to respond to lipid lowering therapy is disclosed. The method may comprise
According to a second aspect, a method for determining whether a subject is at risk of developing or having atherosclerosis and/or a cardiovascular disease is disclosed. The method may comprise
Any embodiments described below in this specification may be understood as relating to either the first aspect, to the second aspect, or to both.
With the method, it may be possible to test and thereby predict a subject's response to lipid lowering therapy, for example to statin, PCSK9, ezetimibe, evinacumab, and/or bempedoic acid treatment.
Therefore, it may be possible to identify relatively quickly subjects who are not likely to respond to a certain lipid lowering treatment, such as statin treatment, alone, such that the subjects may be provided a better working therapy as soon as possible. It may also allow for more subjects to achieve their target lipid levels (for example, cholesterol levels) and/or reduce side effects due to better dosing. Thus the method may allow for reducing the incidence of cardiovascular disease.
In the context of this specification, the terms “therapy” and “treatment” may be understood as commonly in the art. At least in some embodiments, they may be used interchangeably.
In some embodiments, the determining a likelihood of a subject to respond to lipid lowering therapy may comprise or be determining which lipid concentration in the blood of the subject may be achieved by the lipid lowering therapy, and/or a likelihood of the subject to reach a target lipid concentration in the blood of the subject in response to the lipid lowering therapy. In such embodiments, the quantitative value of the ability of the cells to take up LDL, the quantitative value of the expression of LDLR in the cells, the quantitative value of the lipid storage capability of the cells, and/or the quantitative value of the lipid mobilization capability of the cells is/are indicative of the likelihood of the subject to reach a target lipid concentration in the blood of the subject in response to the lipid lowering therapy, and/or indicative of which lipid concentration in the blood of the subject may be achieved by the lipid lowering therapy. The (target) lipid concentration may be e.g. a (target) cholesterol concentration and/or a (target) LDL cholesterol concentration. In such embodiments, it may be possible to determine not only which subjects may respond to the lipid lowering therapy, at least to some extent, but also which subjects may achieve a desired result of the lipid lowering therapy, such as a target lipid concentration.
Any one of, or any combination of, the quantitative value of the ability of the cells to take up LDL, the quantitative value of the expression of LDLR in the cells, the quantitative value of the lipid storage capability of the cells, and/or the quantitative value of the lipid mobilization capability of the cells may be sufficient for determining the likelihood of the subject to respond to lipid lowering therapy, or for determining whether the subject is at risk of developing or having atherosclerosis and/or a cardiovascular disease.
Determining the quantitative value of the ability of cells obtained from the biological sample of the subject to take up low-density lipoprotein (LDL) and/or determining the quantitative value of the expression of LDL receptor (LDLR) in the cells, either alone or in combination, may be considered as determining a quantitative value of LDLR activity in the cells. LDL uptake may, at least in some embodiments, be a better measure of LDLR activity in the cells; however, they may be combined to obtain a more robust readout.
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The method may comprise comparing the quantitative value of the ability of the cells to take up LDL to a quantitative value of control cells or to a control value, wherein a decrease in the quantitative value of the ability of the cells to take up LDL is indicative of a decreased likelihood of the subject to respond to lipid lowering therapy and/or of having an increased risk of developing or having atherosclerosis and/or the cardiovascular disease, and/or wherein an increase in the quantitative value of the ability of the cells to take up LDL is indicative of an increased likelihood of the subject to respond to lipid lowering therapy and/or a reduced likelihood of having atherosclerosis and/or the cardiovascular disease.
The method may comprise comparing the quantitative value of the expression of LDL receptor (LDLR) in the cells to a quantitative value of control cells or to a control value, wherein a decrease in the quantitative value of the expression of LDLR in the cells is indicative of a decreased likelihood of the subject to respond to lipid lowering therapy and/or of having an increased risk of developing or having the cardiovascular disease, and/or wherein an increase in the quantitative value of the expression of LDLR in the cells is indicative of an increased likelihood of the subject to respond to lipid lowering therapy and/or a reduced likelihood of having atherosclerosis and/or the cardiovascular disease.
Identification of subjects having an increased likelihood of the subject to respond to lipid lowering therapy, i.e. good responders to lipid lowering therapy, may be useful in that if the subject does not subsequently respond to the therapy, it may indicate that the subject has not adhered to the therapy. If a subject is a good responder, it may also allow lower levels of medication (e.g. a lower dose of statin) to achieve a desired effect, and thereby reduction of potential side effects and/or improved adherence to the medication.
The method may comprise comparing the quantitative value of the lipid storage capability of the cells to a quantitative value of control cells or to a control value;
The method may comprise comparing the quantitative value of the lipid mobilization capability of the cells to a quantitative value of control cells or to a control value;
The quantitative value of the ability of the cells to take up LDL may be determined e.g. by contacting the cells with labelled LDL particles; incubating the resulting mixture thereby obtainable for a period sufficient to allow cellular internationalization of the labelled LDL particles; and determining the amount and/or the number of labelled LDL particles internalized by the cells. Alternatively or additionally, the intensity of the labelled LDL particles internalized by the cells and/or the quantification of organelles containing the labelled LDL particles may be used to determine the quantitative value of the ability of the cells to take up LDL. The labelled LDL particles may bind to an LDL receptor (or LDL receptors) on the surface of the cells, such that a complex is formed by the labelled LDL particles and the LDL receptor. The complex may then be internalized into the cells. However, other methods capable of measuring the ability of the cells to take up LDL may be contemplated, for example methods utilizing ApoB (apolipoprotein B) or artificial LDL molecules.
The quantitative value of the expression of LDLR in the cells may comprise or be surface expression and/or cellular expression of LDLR. Expression of LDLR may be determined e.g. by using an anti-LDLR antibody or other ligand capable of binding LDLR. However, other methods capable of measuring the expression of LDLR in the cells may be contemplated, for example methods quantifying LDLR mRNA abundance (e.g. by quantitative PCR or by RNA sequencing).
The quantitative value of the lipid storage capability may be determined e.g. by determining the quantitative value (e.g. the amount or relative amount, area, intensity and/or the number) of lipid droplets (LDs) in the cells (i.e. cellular lipid droplets).
The quantitative value of the lipid mobilization capability of the cells may be determined e.g. by determining the quantitative value of lipid droplets (LDs) in the cells in complete medium relative to the quantitative value of lipid droplets in the cells in lipoprotein depleted medium. This may be done e.g. by calculating a ratio of the quantitative value of lipid droplets in the cells in complete medium relative to the quantitative value of lipid droplets in the cells in lipoprotein depleted medium. The term “complete medium” may be understood as referring to a cell culture medium containing all components required for the maintenance and/or growth of the cells. An example of a suitable complete medium is a medium containing 10% FBS (fetal bovine serum). An example of a lipoprotein depleted medium is a comparable medium (i.e. a medium comparable to a corresponding complete medium) that does not contain FBS but contains 5% LPDS (lipoprotein deficient serum).
The quantitative value of lipid droplets (LDs) in the cells and quantitative value of the lipid storage capability may be determined by measuring the abundance of lipid droplets in intracellular lipid storage organelles. The cells may be immobilized e.g. to a plastic or glass substrates. Then the cells may be fixed and stained with a nuclear stain and a hydrophobic fluorophore which accumulates inside lipid droplets. Then the cells may be subjected to automatic imaging; software tools may be used to identify the cells and individual lipid droplets in each cell. This may allow for determining the exact number of cellular lipid droplets, their size and/or their fluorescent intensity. Details of the method have been described e.g. by Pfisterer et al., Nature Communications 2017; 8:14858. Based on this information it is possible to quantify the lipid mobilization.
However, other methods for determining the quantitative value of the lipid mobilization capacity of the cells may be contemplated, for example, biochemical determination of lipids under different conditions, or flow cytometry may be used to quantify LD intensities under the different conditions. Alternatively, the lipid mobilization may be measured by first exposing the cells to a high lipid load to stimulate a large number of lipid droplets and then switch to complete medium which contains less lipids, thereby monitoring lipid mobilization. With automated microscopy and image analysis it may be possible to achieve a more accurate quantification of lipid droplets. Flow cytometry could also be used to measure the cellular lipid droplet intensity, but not necessarily the number and the sizes of the lipid droplets. Nonetheless, the flow cytometry could be used to quantify intensity changes under different conditions and thus permit the calculation of lipid mobilization. Also, lipid droplets could be quantified by antibody stainings for a lipid droplet associated protein. Alternatively, cellular lipid content could be measured with biochemical methods, such as cellular lipid extraction with solvents and quantification via thin layer chromatography or mass spectrometry.
In the context of this specification, the term “lipid mobilization capacity” may be understood as referring to the capacity of the cells to utilize stored lipids. In an embodiment, the term “lipid mobilization capacity” may be understood as referring to a ratio and/or fold difference of lipid droplet numbers, cellular lipid droplet area, and/or cellular lipid droplet intensity in complete medium relative to lipid droplet numbers, cellular lipid droplet area, and/or cellular lipid droplet intensity in lipoprotein depleted medium (e.g. in the same or comparable cells). However, the quantitative value of the lipid mobilization capacity may, alternatively or additionally, be determined by determining the difference between lipid droplet numbers, cellular lipid droplet area, and/or cellular lipid droplet intensity in complete medium and in lipoprotein depleted medium.
The biological sample of the subject may be a blood sample or a sample derived from a blood sample, e.g. a buffy coat sample. Other biological samples may be contemplated, for example cell samples derived from tissues such as fibroblasts, keratinocytes and/or mesenchymal stem cells.
The cells (i.e. the cells obtained from the biological sample of the subject) may comprise or be peripheral blood mononuclear cells (PBMCs). PBMCs may be obtained from the biological sample, such as a blood sample or buffy coat sample, e.g. by density gradient centrifugation. PBMCs may also be selected by positive or negative antibody selection techniques.
The cells may, alternatively or additionally, comprise or be e.g. lymphocytes immortalized with Epstein-Barr virus (EBV lymphoblasts); neutrophils; and/or granulocytes.
The cells may be cryopreserved.
The subject may be human, but the subject may, additionally or alternatively, be an animal, such as a mammalian, for example, a primate, a non-human primate, a dog, a cat, a horse, a sheep, a goat, a bovine, a rabbit, a pig and/or a rodent, such as a mouse or a rat, or any other species.
The subject may have hyperlipidemia. In an embodiment, the subject has hypercholesterolemia and/or hypertriglyceridemia.
In the method according to the second aspect, the cardiovascular disease may comprise or be e.g. at least one of coronary artery disease, such as angina or myocardial infarction, stroke, heart attack, cerebrovascular disease or peripheral artery disease.
The subject may, in some embodiments, be receiving the lipid lowering therapy. In other words, the subject may be or has been on the lipid lowering therapy at the time the biological sample is obtained or has been obtained from the subject. In other embodiments, the biological sample may be obtainable or obtained from a subject that has not yet received lipid lowering therapy.
The lipid lowering therapy may comprise or be statin therapy. Statins are often used as the first line medication for subjects suffering from hypercholesterolemia. However, often subjects do not respond or achieve a target cholesterol level immediately or in the long term when receiving statin therapy. Some subjects do not adhere to statin therapy. Further, it has been observed that a significant portion of subjects who have had a heart attack have a second attack within one year of the first attack. Thus there may be a need to lower the cholesterol level(s) of such subjects without waiting for a prolonged period to see if they respond to statin therapy. Additionally or alternatively, the lipid lowering therapy may comprise or be PCSK9 inhibitor therapy, ezetimibe therapy, evinacumab therapy, and/or bempedoic acid therapy. Other possible therapies, treatments or lipid lowering agents may be contemplated or developed in the future.
The method may be performed using automated image and data analysis. The method may be performed using high content imaging followed by automated image and data analysis. The high content imaging may refer to or comprise automated microscopy, such as automated fluorescence microscopy. The automated microscopy may include e.g. automated wide-field fluorescence microscopy and/or confocal microscopy. High content imaging may allow better automation and/or flexibility. It may also reduce the time required for the method.
The method may be performed using a robotic platform.
However, other methods may, alternatively or additionally, be contemplated. For example, the method may be performed using flow cytometry and/or non-automated microscopy.
The cells may be immobilized on a surface. For example, they may be immobilized on the surface for high content imaging.
The cells may be immobilized on the surface as a monolayer. Suitable surfaces may include e.g. plastic and/or glass surfaces, such as high-content imaging plates. The immobilization may allow for storage and repeated analyses (e.g. image acquisition) of the (same) cells after storage. It may allow for grouping and/or discriminating between two or more cell populations. The immobilization may also prevent cell aggregation and allow for automation of staining and/or imaging of the cells. Immobilized cells may be suitable for imaging at a subcellular resolution that may enable determining the quantitative amount of lipid droplets and/or internalized LDL particles. The immobilization may also allow for the determination of the subcellular localization of the lipid droplets and/or internalized LDL particles.
The immobilized cells may adhere to the surface. To facilitate adhesion, the surface may be selected, treated and/or prepared such that it allows for improved adhesion. Suitable surfaces may be coated. Suitable coatings may include e.g. coatings that may facilitate cell adhesion to the surface, such as a Poly-D lysine (PDL), Poly-L-lysine, collagen, and/or laminin coatings.
The cells may be grouped to two or more (i.e. at least two) cell populations, and/or one or more cell populations may be selected from the cells, and the quantitative value of the ability to take up LDL, the quantitative value of the expression of LDLR, the quantitative value of the lipid storage capability, and/or the quantitative value of the lipid mobilization capability of at least one of the cell populations may be determined separately from the other cell populations. For this, the cells may be immobilized on a surface. Immobilizing the cells may however not be necessary. For example, the cells may be grouped to two or more cell populations e.g. by an antibody staining using an antibody specific for a cell population or other type of staining capable of differentiating between the two or more cell populations, and/or by their morphological properties. For example, the at least one cell population may be a cell population exhibiting the highest signal to noise ratio (as compared to the other cell population(s) within the cells). As another example, PBMC cells may be grouped to monocytes and lymphocytes (and optionally to other cell types), and the quantitative value(s) may be determined separately for the monocytes, lymphocytes, and any other optional cell populations. Monocytes and lymphocytes may be discriminated from each other based on size, as monocytes may spread out after adhesion to a surface, such as a coated imaging plate, resulting in an enlarged cytoplasmic region. However, at least in some embodiments, the quantitative value(s) determined separately for the monocytes, lymphocytes, and/or any other optional cell types or populations, may be combined and used e.g. in correlations.
However, grouping the cells to two or more cell populations may not be necessary for determining the quantitative value of the ability to take up LDL, the quantitative value of the expression of LDLR, the quantitative value of the lipid storage capability, and/or the quantitative value of the lipid mobilization capability of the cells. For example, the quantitative value(s) may be determined from an entire PBMC population (or a part thereof).
The quantitative value of the ability of the cells of the subject to take up LDL may be determined using labelled LDL particles. However, other means which may allow for the determination of the ability of the cells of the subject to take up LDL may also be contemplated. The LDL particles may be e.g. fluorescently or radioactively labelled. The LDL particles may be preserved e.g. by freezing.
The quantitative value of the ability of the cells of the subject to take up LDL may be determined using LDL particles preserved by snap freezing. The snap freezing may be done e.g. by lowering the temperature of the LDL particles to a temperature of −70° C. or lower very quickly, for example for a time period of at least 1 s, or at least 5 s, or at least 10 s, or at least 30 s, or at least 1 min. After the snap freezing, the LDL particles thus preserved may be stored e.g. at a temperature of about −70 to about −80° C.; however, they may also be stored at other temperatures, such as temperatures below about −10° C. or below about −20° C., or in the range of about −10° C. to about −20° C. The snap freezing and optionally storing the LDL particles at a suitable temperature may prevent the aggregation or modification of the LDL particles, which could alter the measurement of the quantitative value of the ability of the cells to take up LDL. Thus the LDL particles may be stored longer and/or provide more reliable results.
The quantitative value of the ability of the cells to take up LDL, the quantitative value of the expression of LDLR, the quantitative value of the lipid storage capability, and/or the quantitative value of the lipid mobilization capability may be normalized using a standard comprising a mixture of cells obtainable from biological samples of a plurality of subjects. The plurality of subjects may comprise or be e.g. at least 2, or at least 3, or at least 4, or at least 5, or at least 10 subjects, or at least 100 subjects. Thus it may be possible to obtain a standard that is more reproducible and/or more uniform than e.g. standards obtainable from a biological sample of a single person.
Large-scale control standards may be used to normalize the data. New control standards may be compared to previous control standards to allow comparison of samples over a long timeframe. The different overlapping control standards may be measured e.g. in 3 or more experiments to have enough values so as to compare them reliably. For example, this may be done by providing a mixed preparation of PBMCs from e.g. 4 or more individuals. These standards may be aliquoted and frozen so that each aliquot is sufficient for one experiment. For each test or experiment a new aliquot may be used. This may ensure that the standard is of the same or similar quality for each experiment. Once a new standard is made, the standard may be compared to a previous control standard, by quantifying e.g. LDL uptake and lipid droplet abundance after treatment with control medium and lipoprotein depleted medium. The background of the cells may also be quantified. For example, only standards which are similar in regard to background, LDL uptake and lipid droplet abundance to the previous standards may be considered as suitable standards for upcoming experiments. For long term comparability of experimental results, it may be beneficial to compare results obtained from one standard to results obtained with a different standard. Therefore, the different standards may be measured in multiple experiments to reduce effects from experimental variation.
The method may further comprise administering a treatment to the subject having a decreased likelihood to respond to lipid lowering therapy to thereby treat the subject in order to prevent or treat hypercholesterolemia in the subject. The treatment may comprise or be administration of a statin, ezetimibe, evinacumab, bempedoic acid, and/or a PCSK9 inhibitor. In an embodiment, the subject has a decreased likelihood to respond to statin therapy.
The treatment may comprise or be administration of a statin, ezetimibe, evinacumab, bempedoic acid, and/or a PCSK9 inhibitor. The treatment may comprise or be e.g. administration of a co-treatment, for example a co-treatment including a statin and ezetimibe, or a co-treatment including a statin and a PCSK9 inhibitor. The treatment may be different from the lipid lowering therapy, to which the subject has a decreased likelihood to respond. For example, if the subject is determined to have a decreased likelihood to respond to statin treatment (and wherein the subject may or may not already be receiving a lipid lowering therapy, such as statin therapy, at the time the biological sample is obtained or has been obtained from the subject), the treatment may comprise or be e.g. administration of a co-treatment including a statin and ezetimibe, or a co-treatment including a statin and a PCSK9 inhibitor. Other possible co-treatments may be contemplated or developed in the future.
In embodiments in which the subject is receiving a lipid lowering therapy (i.e. the subject may be or has been on the lipid lowering therapy at the time the biological sample is obtained or has been obtained from the subject), the treatment may be a co-treatment, i.e. it may comprise or be an additional lipid lowering treatment. The additional lipid lowering treatment may then be a different and/or an additional treatment from the lipid lowering therapy the subject is already receiving.
Results obtainable by the method may be combined with other measures to improve the determination of the likelihood of the subject to respond to lipid lowering therapy, and/or whether the subject is at risk of developing or having atherosclerosis and/or the cardiovascular disease.
The method may further comprise calculating a risk score based on the quantitative value of the ability of the cells to take up LDL, the quantitative value of the expression of LDLR, the quantitative value of the lipid storage capability, and/or the quantitative value of the lipid mobilization capability.
Various other characteristics, measures or values may be included in the calculation of the risk score. Such other characteristics, measures or values may include e.g. one or more of the following: age, gender, dietary habits, physical measurements such as body mass index (BMI), hip circumference, waist circumference, blood metabolites, circulating lipoprotein concentrations, genetic risk factors, family history and/or previous medical history. Such other characteristics, measures or values may be determined prior to, simultaneously, or after the biological sample is obtained from the subject. As a skilled person will understand, some of the characteristics, measures or values may be information collected e.g. using a questionnaire or clinical data collected earlier. Some of the characteristics, measures or values may be determined (or may have been determined) by biochemical or clinical diagnostic measurements and/or medical diagnosis.
The method may further comprise determining whether the subject is at risk of developing or having atherosclerosis and/or the cardiovascular disease on the basis of at least one genetic marker associated with atherosclerosis and/or the cardiovascular disease or the risk thereof, and/or the method further comprises calculating a risk score based on the presence of at least one genetic marker associated with atherosclerosis and/or the cardiovascular disease or the risk thereof and on the quantitative value of the ability of the cells to take up LDL, the quantitative value of the expression of LDLR, the quantitative value of the lipid storage capability, and/or the quantitative value of the lipid mobilization capability. Genetic analysis, i.e. using the at least one genetic marker, may improve the determination of whether the subject is at risk of developing or having atherosclerosis and/or the cardiovascular disease.
In an embodiment, the method comprises calculating a risk score based on the presence of at least one genetic marker associated with atherosclerosis and/or the cardiovascular disease or the risk thereof and on the quantitative value of the ability of the cells to take up LDL, and the quantitative value of the lipid mobilization capability. The risk score may, at least in some embodiments, be a polygenic risk score. In the context of this specification, the abbreviation “GRS” may be understood as referring to a genetic risk score.
The at least one genetic marker associated with the cardiovascular disease or the risk thereof, or the risk score, may comprise or be e.g. a marker for familiar hypercholesterolemia; a mutation in an LDL receptor gene (LDLR); a mutation in apolipoprotein-B gene (APOB); a mutation in LDLRAP1 (Low Density Lipoprotein Receptor Adaptor Protein 1, ARH); a mutation in proprotein convertase subtilisin kexin type 9 gene (PCSK9); and/or a polygenic risk score, such as LDL-GRS; GRS for hypertriglyceridemia; and/or GRS for cardiovascular disease.
A composition comprising a mixture of labelled LDL particles is also disclosed. The LDL particles in the mixture may be obtainable from a plurality of individual subjects, and the composition may be preserved by snap freezing the composition and/or the LDL particles prior or after the labelling. In other words, the composition may be obtainable by preserving it and/or the LDL particles by snap freezing prior or after the labelling. This may be referred to as cryopreservation of the LDL particles. In the context of the composition, the LDL particles may be any LDL particles according to one or more embodiments described in this specification.
The LDL particles obtainable from e.g. plasma samples of the plurality of individual subjects may be first quality checked before they are pooled e.g. for the labelling. For example, LDL particles from samples with a very high lipid content, e.g. based on a visual inspection and/or quantification of lipoprotein concentration(s), may be excluded from the mixture. This is because such LDL particles may not necessarily perform well.
The method may comprise normalizing the quantitative value of the ability of the cells to take up LDL using the composition.
Reference will now be made in detail to various embodiments, an example of which is illustrated in the accompanying drawings.
The description below discloses some embodiments in such a detail that a person skilled in the art is able to utilize the embodiments based on the disclosure. Not all steps or features of the embodiments are discussed in detail, as many of the steps or features will be obvious for the person skilled in the art based on this specification.
Various abbreviations and acronyms are used below in the examples as follows.
Apo-B: Apolipoprotein-B; BSA: Bovine serum albumin; EBV: Epstein-Barr virus; CI: Confidence interval; DAPI: Diamidino-2-phenylindole; DiI: 1,1′-dioctadecyl-3,3,3′,3′-tetramethylindocarbocyanine perchlorate; DMSO: Dimethyl sulfoxide; FBS: Fetal bovine serum, FH: Familial hypercholesterolemia; HEPES: 4-(2-hydroxyethyl)-1-piperazine ethanesulfonic acid; LD: Lipid droplet; LDL: Low-density lipoprotein; LDL-GRS: LDL genetic risk score; LDLR: Low-density lipoprotein receptor; CVD: Cardiovascular disease; LPDS: Lipoprotein deficient serum; PBMC: Peripheral blood mononuclear cells; PBS: Phosphate buffered saline; PCSK9: Proprotein convertase subtilisin/kexin type 9; PDL: Poly-D-lysine; VLDL: Very low-density lipoprotein.
Materials: Lipoprotein deficient serum (LPDS) was obtained from fetal bovine serum by ultracentrifugation (Goldstein et al., Methods Enzymol. 1983; 98:241-260). For DiI-LDL, fresh LDL from human plasma samples was first prepared (Finnish Red Cross permit 39/2016) by density centrifugation (Stephan and Yurachek, J Lipid Res. 1993; 34:325-330) and then labelled with 1,1′-dioctadecyl-3,3,3′,3′-tetramethyl-indocarbocyanine perchlorate (DiI) (Reynolds et al., Am J Pathol. 1985; 121:200-211). 4′,6-diamidino-2-phenylindole (DAPI), Poly-D lysine (PDL) and Histopacque Premium were obtained from Sigma. DiI, anti-mouse Alexa 568, HCS CellMask Deep Red and HCS CellMask Green where obtained from Thermo Fisher. Mouse anti-LDLR (clone 472413) was from R&D systems.
Peripheral blood mononuclear cells (PBMC) and blood samples: He-FH patients were identified in the Metabolic Syndrome in Men study (Laakso et al., J Lipid Res. 2017; 58:481-493) and blood samples obtained during patient follow-up in accordance with the declaration of Helsinki regarding experiments involving humans. Two He-FH patients (Cys325Tyr and Ser580Phe) for which obtained PBMC and EBV lymphoblast cell samples were obtained were described previously (Romano et al., J Lipid Res. 2011; 52:2095-2100). PBMC samples from the Finnish population survey, FINRISK 2012, and the donor linked data (including genotypes) were obtained from THL Biobank (www.thl.fi/biobank) and used under the Biobank agreements no (2016_15, 2016_117 and 2018_15). The donors with elevated LDL levels (LDL >5 mM) and normocholesterolemic (LDL 2.0-2.5 mM) study groups from the biobank were age, gender and BMI matched. The donors in either of the groups did not have cholesterol lowering medication by the time of sampling, and based on a food frequency questionnaire, did not receive an elevated proportion of energy intake as saturated or trans-fat. Buffy coat samples from healthy blood donors were obtained from the Finnish Red Cross (permit 392016).
Cell culture: Control EBV lymphoblasts (GM14664) were obtained from Coriell Cell Repository and cultured in RPMI-1640 supplemented with 15% FBS, penicillin/streptomycin (100 U/ml each) and 2 mM L-Glutamine. For continuous culturing of EBV lymphoblasts, 3×106 cells were transferred to 5 ml of fresh medium once a week. Single use cryopreserved EBV lymphoblast aliquots were used for experiments. Cells were cryopreserved in 70% PBMC medium (RPMI-1640, penicillin/streptomycin, 2 mM L-glutamine, 1 mM sodium pyruvate, and 1 mM HEPES), 20% FBS and 10% DMSO.
PBMC isolation: Blood or buffy coat samples were mixed 1:1 with phosphate buffered saline (PBS) including 2.5 mM EDTA (PBS-E). The blood mixture was gently layered over Histopacque Premium (1.0073, for mononuclear cells) and centrifuged 40 min at 400 g. The PBMC cell layer was removed, transferred to a new 15 ml reaction tube and mixed with PBS-E. Cells were centrifuged at 400 g for 10 min and incubated in 2 ml of red blood cell lysis buffer for 1 min (155 mM NH4Cl, 12 mM NaHCO3, 0.1 mM EDTA). 10 ml of PBS-E was added and cells were pelleted and washed with PBS-E. Then cells were resuspended in 5 ml PBMC medium (RPMI-1640, penicillin/streptomycin, 2 mM L-glutamine, 1 mM sodium pyruvate, and 1 mM HEPES), counted, pelleted and resuspended in freezing medium (70% PBMC-medium, 20% FBS, 10% DMSO) and cryopreserved in liquid nitrogen.
Cell treatments, DiI-LDL uptake, transfer to imaging plates and fixation: Cryopreserved EBV lymphoblasts or PBMCs were thawed in PBMC medium, and centrifuged at 400 g for 10 min. The cells were resuspended in PBMC medium and transferred to wells of a 96 well plate containing FBS (10% final concentration) or LPDS (5% final concentration) and incubated for 24 h. For DiI-LDL uptake experiments 30 μg/ml DiI-LDL was added for 1 h at 37° C. Subsequently, cells were transferred to conical 96 well plates and centrifuged at 400 g for 10 min. Using a robotic platform (Opentrons, New York, USA) medium was removed and cells were resuspended in PBMC medium. Cells were centrifuged, automatically resuspended in PBMC medium and transferred to PDL coated 384 well high-content imaging plates (Corning). After 30 min of incubation at 37° C. cells were automatically fixed with 4% paraformaldehyde in 250 mM HEPES, 1 mM CaCl2, 100 PM MgCl2, pH 7.4 and washed with PBS. For lipid droplet and LDLR surface stainings, cells were directly transferred to PDL coated 384 well high-content plates, adhered, automatically fixed and washed with PBS.
Lipid droplet analyses: Cells were processed as described before (Pfisterer et al., Nat Commun. 2017; 8:14858) with the following changes: Fixed cell samples were automatically stained with 1 μg/ml LD540 (Princeton BioMolecular Research) and 5 μg/ml DAPI. 3D stacks of optical slices were acquired automatically either with a Nikon Eclipse Ti-E inverted microscope equipped with a 40× Planfluor objective with NA 0.75 and 1.5 zoom. Or with a PerkinElmer Opera Phenix High Content Imaging system with a 63× water immersion objective, NA 1.15. Image stacks were automatically deconvolved either with Huygens software (Scientific Volume Imaging, b.v.) or a custom made Python tool based on the open source tools PSF generator and deconvolution lab. Maximum intensity projections were made from the deconvolved image stacks with custom Python tools. These tools can be accessed via: https://github.com/lopaavol/Oputils. Automated quantification of lipid droplets was performed as described previously (Pfisterer et al., Nat Commun. 2017; 8:14858; Salo et al., Dev Cell. 2019; 50:478-493.e9; Vanharanta et al., Traffic. 2020; 21:386-397). Lipid droplet counts were normalized to the average of two control standards which were included in each imaging plate.
LDLR surface staining: All staining procedures were performed automatically. Fixed cells were quenched with 50 mM NH4Cl for 15 min and washed twice with PBS. Cells were incubated with block solution (PBS, 1% BSA) for 10 min followed by staining with mouse anti-LDLR in block solution for 60 min. Cells were washed three times with PBS followed by incubation with secondary antibody solution (anti-mouse-Alexa 568, DAPI 5 μg/ml and HCS CellMask Green stain 0.25 μg/ml) for 45 min at room temperature. Cells were washed with PBS and 3D stacks of optical slices were acquired for DAPI (nuclei), CellMask Green (cytoplasm), Alexa 568 (LDLR surface) and Alexa 640 (background) channels using an Opera Phenix high-content imaging system with a 40× water immersion objective NA 1.1. LDLR surface and background images were automatically deconvolved with custom build Python deconvolution tools and maximum intensity projections were made. The resulting images were automatically analysed with CellProfiler (Kamentsky et al., Bioinformatics. 2011; 27:1179-1180). LDLR surface intensities were background subtracted for each individual cell and normalized by subtracting mean LDLR surface intensities from the two standards, which were included in each imaging plate.
Quantification of DiI-LDL uptake: DiI-LDL labelled and fixed cells (see section cell treatments) were automatically processed with a robotic platform (Opentrons). Cells were stained with 5 μg/ml DAPI and 0.5 μg/ml HCS CellMask Deep Red and image stacks for three channels, DAPI (nuclei), DiI-LDL and CellMask Deep Red (cytoplasm) were acquired. Automated microscopy and single cell quantifications with CellProfiler were performed as described in the section LDLR surface staining. The robotic work flow for washing and transferring DiI-LDL labeled PBMCs from multiple patients resulted in defined DiI-LDL intensity levels for individual columns of an imaging plate, which was determined with standards and combined with plate normalizations to make mean cellular DiI-LDL intensities and DiI-LDL organelle counts comparable from experiment to experiment.
LDL genetic risk score: The LDL GRS was calculated using the LDpred method based on both the previously published GRS by Talmud et al. and a European genome-wide association study (GWAS) meta-analysis with 56945 samples (Talmud et al., The Lancet. 2013; 381:1293-1301; Vilhjálmsson et al., Am J Hum Genet. 2015; 97:576-592). LDL uptake and lipid mobilization parameters were normalized to a range from 0 to 1 to generate uptake and mobilization scores. Hybrid scores represent the average of LDL-GRS and uptake and/or mobilization scores.
Data analysis: Python (Python Software Foundation, www.python.org) was used with the Pandas package (pandas.pydata.org) to analyse single cell data obtained from CellProfiler. With a cytoplasm area below 115 μm2 cells were classified as lymphocytes whereas cells with an area above 115 μm2 were classified as monocytes. Statistical significance was assessed with SciPy (scipy.org) using the “ttest_inde” function which calculates a two-tailed pvalue for independent samples. Data visualization was performed with Matplotlib (matplotlib.org) and Seaborn (seaborn.pydata.org).
Automated Pipeline for Multiplex Quantification of Hypercholesterolemia-Related Functional Defects in Primary Human Cells
An automated analysis pipeline was set up to quantify LDL uptake, LDLR surface expression and lipid storage under different conditions from less than two million peripheral blood mononuclear cells (PBMCs) (2-4 ml blood) in a scalable and robust manner (
The automated analysis pipeline enables simultaneous quantification of different white blood cell populations (
Due to low signal intensities in primary blood cells, lymphocytes immortalized with Epstein-Barr virus (EBV lymphoblasts) are often a preferred choice for LDL uptake studies. LDL uptake was therefore compared in EBV lymphoblasts and primary monocytes (
Heterogeneous LDL Uptake and LDLR Surface Expression in He-FH Patients with Identical LDLR Mutations.
Next, the analysis pipeline was used to characterize 21 FH patients from the Metabolic Syndrome in Men (METSIM) cohort study. The subjects comprise nine different LDLR variants of which Pro309Lysfs* (FH North Karelia), Glu626Ala, and Arg595Gln (FH Pogosta) were observed in several patients, and His203Tyr represents a novel LDLR variant (
Assessing LDL Internalization in Non-FH Individuals with Normal or Elevated Blood LDL.
A large majority of hypercholesterolemia patients does not carry FH-alleles. Therefore cellular LDL uptake was investigated in PBMCs from 20 biobank donors with elevated LDL levels (blood LDL >5 mM) (H-Chol) and 19 with normal LDL levels (blood LDL 2-2.5 mM) (N-Chol). DNA sequencing confirmed that common Finnish LDLR variants were not present among the subjects. However, a genetic risk score for high blood LDL concentration (LDL-GRS) (Ripatti et al., Circ Genomic Precis Med. 2020; 13:e002725) was increased in the H-Chol group (
Monocyte DiI-LDL intensities were quantified after lipoprotein starvation for N-Chol and H-Chol individuals (
To investigate additional factors potentially influencing the heterogenous LDL uptake responses in N-Chol and H-Chol individuals, correlations of two indicators available for obesity, body mass index (BMI) and hip circumference were performed. Strikingly, increased hip circumference correlated with reduced LDL uptake (
When comparing to the blood donor standards, cells from biobank donors showed on average 30% lower DiI-LDL uptake after lipoprotein starvation (
Assessment of Cellular Lipid Storage and Lipid Mobilization in Monocytes.
Cells store excess lipids in intracellular lipid droplets (LDs). It was reasoned that when cells have sufficient lipids available, they are less prone to take up lipoproteins. Therefore the quantification of cellular LDs was included in the analysis pipeline, and the system was verified with the standard samples. In complete medium (10% FBS), monocytes showed more LDs than lymphocytes (
Incubation in lipoprotein depleted medium (5% LPDS) for 24 h resulted in a significant reduction in the number of LDs in both cell populations, with more pronounced reductions in monocytes (
Next, a lipid mobilization assay was established to measure the cellular capacity to utilize stored lipids. Lipid mobilization was defined as the fold difference of LD numbers in complete medium vs. lipoprotein depleted medium (
Lipid Mobilization is Reduced in Hypercholesterolemia Patients and Correlates with LDL Uptake.
In He-FH patients' monocytes, lipid mobilization was significantly reduced in cells expressing the LDLR variants North Karelia and Glu626Ala as compared to the standards (
It was then investigated whether the cells from N-Chol and H-Chol biobank donors display differences in lipid mobilization. Analogously to LDL uptake, a large fluctuation in lipid mobilization in both subgroups was observed (
This prompted a scrutinization whether lipid mobilization correlates with LDL uptake potential in the biobank donors. It was observed that individuals with higher lipid mobilization also showed higher LDL internalization (
Hybrid Scores of Genetic and Functional Cell Data Improve Correlations with Circulating LDL
The H-Chol biobank donors of the FINRISK population cohort displayed an increased LDL-GRS (
Finally, a triple hybrid score of LDL-GRS, lipid mobilization and LDL uptake showed the best correlation with blood LDL levels (
In these examples, the multiplexed high-content analysis pipeline established integrates analysis of cellular LDL uptake and quantification of cellular lipid storage in an automated workflow. This provides several advantages over flow-cytometry based assays currently used to quantify LDL uptake in patient's white blood cells: 1) Immobilization of cells to coated surfaces prevents cell aggregation, allowing image acquisition after sample storage and straightforward detection of lymphocyte and monocyte populations. 2) Cell staining procedures can be automated easily. 3) Fewer cells are required, and 4) subcellular resolution enables quantification of lipid droplets and internalized LDL particles.
Fibroblasts, lymphocytes and EBV lymphoblasts are often considered as the cell types of choice for LDL uptake assays. Here it is shown that monocytes can provide larger detection windows than EBV lymphoblasts and yield DiI-LDL uptake signal intensities about twice as high as primary lymphocytes. Furthermore, it was found that monocytes are better suited for the quantification of intracellular lipid storage and lipid mobilization upon lipoprotein depletion.
In the current examples, over 310 conditions (combinations of assays and treatments) were analyzed for 62 patient samples. The processing speed depends on the number of assays and treatments performed for each PBMC sample. In its present stage, the automated pipeline enables 120 conditions (e.g. 30 PBMC samples with two assays and two treatments) to be analyzed in 3 days, when operated by a single person. The throughput can be increased considerably by adding more liquid handling systems to the pipeline and increasing computing resources for image processing.
The lipid mobilization assay was established to investigate how altered regulation of lipid storage might impact cellular LDL uptake and circulating LDL levels. Interestingly, lipid mobilization provided better correlations with blood LDL concentrations than cellular LDL uptake.
Quantification of lipid mobilization may therefore provide additional means to identify individuals at risk for hypercholesterolemia. Furthermore, the interrelationship of lipid mobilization and LDL uptake highlights the added value of combining multiple readouts to elucidate the underlying causes of hypercholesterolemia. This approach might also provide deeper insight into the cellular mechanisms underlying familial combined hyperlipidemia a frequent disorder, which is influenced by metabolic alterations. Obesity is known to predispose to elevated blood LDL levels and increased CVD risk. The results provide evidence that at the mechanistic level, obesity correlates with reduced cellular LDL uptake and lipid mobilization. Interestingly, clinical trials indicate that statins may be less effective in obese individuals. Considering that statins act by blocking cholesterol synthesis and increasing LDL internalization, it is plausible that the reduced LDL uptake and lipid mobilization potential contribute to the lower potency of statins in obese persons.
So far, the added value of quantifying cellular parameters to define risk groups or guide treatment decisions in the clinical management of hypercholesterolemia has not been clear. However, the genuinely high heterogeneity of cellular readouts that were observed in individuals with normal blood LDL concentrations, hypercholesterolemic persons and even He-FH patients carrying identical LDL variants, may provide new possibilities for personalized risk assessment and treatment recommendation.
The present study highlights two situations where this appears feasible. Firstly, it was observed that combining LDL-GRS with the quantification of LDL uptake and lipid mobilization to novel hybrid scores improved the correlation with circulating LDL. Especially for young individuals where clinical manifestations of hypercholesterolemia are not overt, such hybrid scores may improve personalized risk assessment for hypercholesterolemia and CVD. Secondly, it was found a significant correlation of low monocyte LDL uptake with high blood LDL for He-FH patients on statin treatment. This may suggest that monocyte LDL uptake potential may facilitate the anticipation of individual's statin responsiveness. For poor statin responders, co-treatments with ezetimibe or PCSK9 inhibitors might be warranted to achieve blood LDL target levels. Remarkably, response to statin therapy is highly heterogeneous and up to 80% of people with coronary heart disease do not achieve their blood LDL target levels, emphasizing that better intervention strategies are urgently needed.
In summary (see
Importantly, quantification of genetic plus cell-based hybrid scores for individual risk assessment and analysis of LDL uptake in He-FH patients on statin therapy open up new possibilities for personalized medicine in hypercholesterolemia.
It is obvious to a person skilled in the art that with the advancement of technology, the basic idea may be implemented in various ways. The embodiments are thus not limited to the examples described above; instead they may vary within the scope of the claims.
The embodiments described hereinbefore may be used in any combination with each other. Several of the embodiments may be combined together to form a further embodiment. A method, a product, a system, or a use, disclosed herein, may comprise at least one of the embodiments described hereinbefore. It will be understood that the benefits and advantages described above may relate to one embodiment or may relate to several embodiments. The embodiments are not limited to those that solve any or all of the stated problems or those that have any or all of the stated benefits and advantages. It will further be understood that reference to ‘an’ item refers to one or more of those items. The term “comprising” is used in this specification to mean including the feature(s) or act(s) followed thereafter, without excluding the presence of one or more additional features or acts.
| Number | Date | Country | Kind |
|---|---|---|---|
| 20206284 | Dec 2020 | FI | national |
| Filing Document | Filing Date | Country | Kind |
|---|---|---|---|
| PCT/FI2021/050861 | 12/10/2021 | WO |
