Methods, computer program products and apparatus determine a subject's risk of having or developing CHD using a calculated HDL particle risk number and/or a mathematical model of risk associated with HDL particles that adjusts concentrations of at least one of the subclasses of small, medium and large HDL particle measurements to reflect predicted CHD risk. A calculated LDL particle risk number may also be generated as well as a lipoprotein particle index derived from the ratio of R.sub.LDL/R.sub.HDL.

The present invention inter alia provides a method, and use thereof, of diagnosing and/or predicting atherosclerosis or CVD by detecting the lipid concentrations or lipid ratios of a biological sample and comparing it to a control and has identified specific lipid markers that are more specific and sensitive in detecting and predicting atherosclerosis and CVD than currently utilized clinical markers. Also provided is an antibody towards said lipids, and the use thereof for predicting, diagnosing, preventing and/or treating atherosclerosis or CVD. The invention additionally relates to kits comprising lipids and/or an antibody thereto, for use in the prediction and/or diagnosis of atherosclerosis or CVD.

Methods of characterizing a test subject's risk of having or developing cardiovascular disease are provided. The methods include using an analytic device to determine levels of choline-related trimethylamine-containing compounds such as trimethylamine N-oxide, choline, or betaine in a biological sample obtained from the subject and comparing the levels of the choline-related trimethylamine-containing compound in the subject's biological sample to a control value. The test subject's risk of having cardiovascular disease is then characterized as higher if the levels of the choline-related trimethylamine-containing compound are higher than the control value. Also provided are methods of identifying a subject at risk of experiencing a complication of atherosclerotic cardiovascular disease, and methods of evaluating the efficacy of a cardiovascular therapeutic agent in a subject with cardiovascular disease using levels of choline-related trimethylamine-containing compounds.

An object of the present invention is to provide a highly versatile, simple and safe method for measuring Lp-PLA.sub.2 activity. Another object of the present invention is to provide an accurate and highly sensitive method for measuring Lp-PLA.sub.2 activity. Provided is a method for measuring lipoprotein-associated phospholipase A.sub.2 (Lp-PLA.sub.2) activity in a sample containing Lp-PLA.sub.2, the method comprising the following steps (A) to (C): (A) converting PAFs into lyso-PAFs by reacting the PAFs with the Lp-PLA.sub.2 in the sample; (B) hydrolyzing the lyso-PAFs produced in the step (A) with an enzyme (lyso-PAF-PLD) to obtain hydrolysate; and (C) measuring Lp-PLA.sub.2 activity in the sample by utilizing a quantitative change attributable to the hydrolysate obtained in step (B) as an indicator.

The present invention concerns machine learning based methods and systems for diagnosing and treating genetic diseases characterized by mitochondrial dysfunctions. A library of reference learning models is developed based on in vitro reference samples obtained from cell-cultures exposed to specific mitochondrial inhibitors. Each model is able to predict a specific labeled mitochondrial dysfunction induced in the cell-culture by the inhibitor/stressor. The reference models are then applied to target samples drawn in vivo from target subjects who are known to have specific genetic mitochondrial diseases. A mapping is developed between mitochondrial dysfunctions predicted in the subjects and their known mitochondrial diseases. This mapping and the reference models are then applied to a clinical sample of an undiagnosed patient in whom a diagnosis of a mitochondrial dysfunction and an associated mitochondrial disease is made. If there is a known rescuer for the mitochondrial dysfunction, it may be recommended in a personalized, targeted therapy.

The present invention relates to an antibody, or an antigen-binding fragment thereof, specifically binding to APRIL for use in the prevention and/or treatment of hypertriglyceridemia, metabolic syndrome, non-alcoholic steatohepatitis, diabetes mellitus type 2, abdominal aortic aneurysm, atherogenic dyslipidemia, cardiovascular events (e.g., myocardial infarction and stroke) and/or atherosclerosis. The invention further relates to a polynucleotide that encodes and/or a pharmaceutical composition that comprises the antibody or an antigen-binding fragment of the invention. The invention also relates to a kit and/or method for quantifying the concentration of nc-APRIL, canonical APRIL or total APRIL in a sample. Further, the invention relates to a nephelometric assay for quantifying nc-APRIL. Further, the invention relates to a method for predicting mortality risk in subjects suffering from, and/or for determining whether a subject is susceptible to the treatment of hypertriglyceridemia, metabolic syndrome, abdominal aortic aneurysm, non-alcoholic steatohepatitis, diabetes mellitus type 2, atherogenic dyslipidemia, cardiovascular events and/or atherosclerosis.

Methods, computer program products and apparatus determine a subject's risk of having or developing CHD using a calculated HDL particle risk number and/or a mathematical model of risk associated with HDL particles that adjusts concentrations of at least one of the subclasses of small, medium and large HDL particle measurements to reflect predicted CHD risk. A calculated LDL particle risk number may also be generated as well as a lipoprotein particle index derived from the ratio of R.sub.LDL/R.sub.HDL.

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; wherein 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 respond to lipid lowering therapy.

Methods, computer program products and apparatus determine a subject's risk of having or developing CHD using a calculated HDL particle risk number and/or a mathematical model of risk associated with HDL particles that adjusts concentrations of at least one of the subclasses of small, medium and large HDL particle measurements to reflect predicted CHD risk. A calculated LDL particle risk number may also be generated as well as a lipoprotein particle index derived from the ratio of R.sub.LDL/R.sub.HDL.

A computer-implemented method for providing a personalized evaluation of assessment of atherosclerotic plaques for a patient acquiring patient data comprising non-invasive patient data, medical images of the patient, and blood biomarkers. Features of interest are extracted from the patient data and one or more machine learning models are applied to the features of interest to predict one or more measures of interest related to atherosclerotic plaque.