Serum anti-AP3D1 antibodies are risk factors for acute ischemic stroke related with atherosclerosis.

Atherosclerosis has been considered as the main cause of morbidity, mortality, and disability worldwide. The first screening for antigen markers was conducted using the serological identification of antigens by recombinant cDNA expression cloning, which has identified adaptor-related protein complex 3 subunit delta 1 (AP3D1) as an antigen recognized by serum IgG antibodies of patients with atherosclerosis. Serum antibody levels were examined using the amplified luminescent proximity homogeneous assay-linked immunosorbent assay (AlphaLISA) using a recombinant protein as an antigen. It was determined that the serum antibody levels against AP3D1 were higher in patients with acute ischemic stroke (AIS), transient ischemic attack, diabetes mellitus (DM), cardiovascular disease, chronic kidney disease (CKD), esophageal squamous cell carcinoma (ESCC), and colorectal carcinoma than those in the healthy donors. The area under the curve values of DM, nephrosclerosis type of CKD, and ESCC calculated using receiver operating characteristic curve analysis were higher than those of other diseases. Correlation analysis showed that the anti-AP3D1 antibody levels were highly associated with maximum intima-media thickness, which indicates that this marker reflected the development of atherosclerosis. The results of the Japan Public Health Center-based Prospective Study indicated that this antibody marker is deemed useful as risk factors for AIS.

Use of a gene score of multiple low-modest effect size variants can predict the risk of obesity better than the individual SNPs.

BACKGROUND: Obesity is a complex disorder, the development of which is modulated by a multitude of environmental, behavioral and genetic factors. The common forms of obesity are polygenic in nature which means that many variants in the same or different genes act synergistically and affect the body weight quantitatively. The aim of the current study was to use information from many common variants previously identified to affect body weight to construct a gene score and observe whether it improves the associations observed. The SNPs selected were G2548A in leptin (LEP) gene, Gln223Arg in leptin receptor (LEPR) gene, Ala54Thr in fatty acid binding protein 2 (FABP2) gene, rs1121980 in fat mass and obesity associated (FTO) gene, rs3923113 in Growth Factor Receptor Bound Protein 14 (GRB14), rs16861329 in Beta-galactoside alpha-2,6-sialyltransferase 1 (ST6GAL1), rs1802295 in Vacuolar protein sorting-associated protein 26A (VPS26A), rs7178572 in high mobility group 20A (HMG20A), rs2028299 in adaptor-related protein complex 3 (AP3S2), and rs4812829 in Hepatocyte Nuclear Factor 4 Alpha (HNF4A). METHODS: A total of 475 subjects were genotyped for the selected SNPs in different genes using different genotyping techniques. The study subjects' age, weight, height, BMI, waist and hip circumference, serum total cholesterol, triglycerides, LDL and HDL were measured. A summation term, genetic risk score (GRS), was calculated using SPSS. RESULTS: The results showed a significantly higher mean gene score in obese cases than in non-obese controls (9.1 ± 2.26 vs 8.35 ± 2.07, p = 2 × 10- 4). Among the traits tested for association, gene score appeared to significantly affect BMI, waist circumference, and all lipid traits. CONCLUSION: In conclusion, the use of gene score is a better way to calculate the overall genetic risk from common variants rather than individual risk variants.