rs12708716

This meta-analysis of 7 genome-wide association studies identified three novel multiple sclerosis susceptibility loci: rs170934 near EOMES (3p24.1, OR=1.17, P=1.6×10⁻⁸), rs2150702 in MLANA (9p24.1, OR=1.16, P=3.3×10⁻⁸), and rs6718520 near THADA (2p21, OR=1.17, P=3.4×10⁻⁸). The analysis encompassed 5,545 cases and 12,153 controls and identified 10 additional loci with suggestive evidence of association (P<1×10⁻⁶), including IL12B, TAGAP, PLEK, and ZMIZ1, which are shared with other inflammatory diseases.

This paper applies a bias correction method for odds ratio estimates from GWAS discovery data, demonstrating that the 'winner's curse' affects initial effect size estimates. The authors applied conditional maximum likelihood estimation to correct bias in GWAS findings from multiple complex diseases (breast cancer, colorectal cancer, lung cancer, prostate cancer, type I and II diabetes) and show that bias-adjusted odds ratios are substantially more consistent with subsequent replication studies, with selection-adjusted confidence intervals providing better uncertainty quantification than uncorrected estimates.

This paper presents a statistical method for unbiased estimation of odds ratios from genome-wide association scans combined with replication studies. The authors develop a Uniformly Minimum Variance Conditionally Unbiased Estimator (UMVCUE) that corrects for selection bias arising from both rank ordering and significance thresholding in initial scans. Applied to type 1 diabetes and Crohn's disease data from the Wellcome Trust Case Control Consortium, the method shows improved efficiency over replication-only estimates, particularly when replication sample sizes are smaller.

A meta-analysis of 4,107 type 2 diabetes cases and 5,187 controls from three GWA studies found no evidence that common variants altering circulating inflammatory protein levels (IL-18, IL-6R, CRP, IL1RN, PAI1, MIF) or variants predisposing to autoimmune diseases (type 1 diabetes, rheumatoid arthritis, Crohn's disease, celiac disease, multiple sclerosis, SLE) are associated with type 2 diabetes risk. For example, rs2250417 in IL18 showed OR=1.00 (95% CI 0.99-1.03) versus the expected OR of ~1.15 if inflammation were causal, suggesting inflammatory markers are likely secondary rather than causative in type 2 diabetes.

This comprehensive review article traces the evolution of pharmacogenetics from single-gene analysis to whole-genome approaches. It discusses validated pharmacogenetic biomarkers with clinical impact including CYP2D6, CYP2C9, CYP2C19, TPMT, DPD, VKORC1, UGT1A1, and ADRB1/ADRB2, providing examples of how genetic variants affect drug metabolism and response. The paper emphasizes the importance of integrating pharmacogenetic information into clinical practice and drug development.

This review examines slowly progressive type 1 diabetes mellitus (SPIDDM), also known as latent autoimmune diabetes in adults (LADA), discussing its pathogenesis, diagnostic markers, and genetic associations. Key findings include T-cell-mediated insulitis and pseudoatrophic islets characteristic of type 1 diabetes, absence of amyloid deposition seen in type 2 diabetes, and identification of multiple genetic susceptibility loci including HLA haplotypes, PTPN22 rs2476601, INS rs689, CTLA4, TCF7L2 rs7903146, ZMIZ1 rs12571751, SH2B3 rs7310615, and PFKFB3 rs1983890. GAD autoantibodies and HLA genotypes are important risk factors for beta-cell failure progression.