Genetic determinants of low-density lipoprotein cholesterol in type 2 diabetes individuals in Malaysia

Abstract

The Malaysian National Diabetes Registry Report 2020 (NDR 2020) indicates that 75.72% of individuals with diabetes have dyslipidemia. Despite 81.96% receiving statin treatment, only 45.68% achieved the recommended low-density lipoprotein cholesterol (LDL-C) target of less than 2.6 mmol/L. Elevated LDL-C levels, a precursor to atherosclerosis, significantly contribute to the heightened risk of CAD. Approximately 47.7% of Malaysians with type 2 diabetes mellitus (T2D) have CAD complications. Individuals with both T2D and CAD face a high risk of mortality, particularly from heart disease. Only a few studies in Malaysia have determined the genetic architecture of high LDL-C in T2D individuals. Recognizing the research gap in LDL-C genetics in individuals with T2D in Malaysia, this study aims to identify genetic variants associated with LDL-C levels and CAD outcomes in the Precision Medicine for Diabetic Individuals: a joint Malaysia-UK Effort (PRIME) cohort project. A total of 5000 DNA were genotyped using the Infinium Asian Screening Array. Data quality control using PLINK was performed on the samples and variants. Genome wide association study (GWAS) analysis using SNPTEST software was eventually conducted on data from 4443 samples. Polygenic risk scores (PRS) were calculated using the 'pgsc_calc' software based on scores published in the Polygenic Score Catalog. Genetic associations with LDL-C levels and CAD were assessed using regression analysis. Malays have the highest mean LDL-C levels compared to the Chinese and Indians at the baseline and follow-up (Malays: 3.95mmol/L and 3.52mmol/L, Chinese: 3.51mmol/L and 3.15mmol/L, and Indians: 3.55mmol/L and 3.20mmol/L, respectively, p-value<0.05). The prevalence of CAD was higher in Indians (9.2%) compared to the Malays (4.2%) and Chinese (3.3%) (P<0.05). Following the quality assessments, we identified one genome-wide significant variant (rs11102967, CELSR2) and two suggestive variants (rs1371047, TEX41 and rs406315, NECTIN2) that were associated with LDL-C levels. Linear regression analysis of individual variants revealed a significant correlation between individual LDL-C variants and LDL-C levels but no association between individual LDL-C variants and CAD outcomes. Linear regression of LDL-C-PRS scores analysis revealed a significant correlation between LDL-C-PRS scores and LDL-C levels. Malay individuals with 3rd quartile LDL-C-PRS scores (PGS000890) have a greater risk of having CAD (OR=2.401, CI=1.020,5.649). This is the first GWAS study for LDL-C and its associations with CAD in the Malaysian T2D population. These findings underscore the genetic burden of LDL-C and its relationship with CAD risk in diabetic populations. Through the integration of genetic, clinical, and demographic data, precision medicine and lifestyle modifications can be tailored to high-risk individuals to minimize CAD complications among those with T2D.