Genetic Associations of Type 2 Diabetes with Islet Amyloid Polypeptide Processing and Degrading Pathways in Asian Populations

10.1371/journal.pone.0062378PLoS ONE86

Transferability of Type 2 Diabetes Implicated Loci in Multi-Ethnic Cohorts from Southeast Asia

Recent large genome-wide association studies (GWAS) have identified multiple loci which harbor genetic variants associated with type 2 diabetes mellitus (T2D), many of which encode proteins not previously suspected to be involved in the pathogenesis of T2D. Most GWAS for T2D have focused on populations of European descent, and GWAS conducted in other populations with different ancestry offer a unique opportunity to study the genetic architecture of T2D. We performed genome-wide association scans for T2D in 3,955 Chinese (2,010 cases, 1,945 controls), 2,034 Malays (794 cases, 1,240 controls), and 2,146 Asian Indians (977 cases, 1,169 controls). In addition to the search for novel variants implicated in T2D, these multi-ethnic cohorts serve to assess the transferability and relevance of the previous findings from European descent populations in the three major ethnic populations of Asia, comprising half of the world's population. Of the SNPs associated with T2D in previous GWAS, only variants at CDKAL1 and HHEX/IDE/KIF11 showed the strongest association with T2D in the meta-analysis including all three ethnic groups. However, consistent direction of effect was observed for many of the other SNPs in our study and in those carried out in European populations. Close examination of the associations at both the CDKAL1 and HHEX/IDE/KIF11 loci provided some evidence of locus and allelic heterogeneity in relation to the associations with T2D. We also detected variation in linkage disequilibrium between populations for most of these loci that have been previously identified. These factors, combined with limited statistical power, may contribute to the failure to detect associations across populations of diverse ethnicity. These findings highlight the value of surveying across diverse racial/ethnic groups towards the fine-mapping efforts for the casual variants and also of the search for variants, which may be population-specific

A statistical method for region-based meta-analysis of genome-wide association studies in genetically diverse populations

Genome-wide association studies (GWAS) have become the preferred experimental design in exploring the genetic etiology of complex human traits and diseases. Standard SNP-based meta-analytic approaches have been utilized to integrate the results from multiple experiments. This fundamentally assumes that the patterns of linkage disequilibrium (LD) between the underlying causal variants and the directly genotyped SNPs are similar across the populations for the same SNPs to emerge with surrogate evidence of disease association. We introduce a novel strategy for assessing regional evidence of phenotypic association that explicitly incorporates the extent of LD in the region. This provides a natural framework for combining evidence from multi-ethnic studies of both dichotomous and quantitative traits that (i) accommodates different patterns of LD, (ii) integrates different genotyping platforms and (iii) allows for the presence of allelic heterogeneity between the populations. Our method can also be generalized to perform gene-based or pathway-based analyses. Applying this method on real GWAS data in type 2 diabetes (T2D) boosted the association evidence in regions well-established for T2D etiology in three diverse South-East Asian populations, as well as identified two novel gene regions and a biologically convincing pathway that are subsequently validated with data from the Wellcome Trust Case Control Consortium

Meta-analysis of genome-wide association studies identifies eight new loci for type 2 diabetes in east Asians

We conducted a three-stage genetic study to identify susceptibility loci for type 2 diabetes (T2D) in East Asian populations. The first stage meta-analysis of eight T2D genome-wide association studies (6,952 cases and 11,865 controls) was followed by a second stage in silico replication analysis (5,843 cases and 4,574 controls) and a stage 3 de novo replication analysis (12,284 cases and 13,172 controls). The combined analysis identified eight new T2D loci reaching genome-wide significance, which were mapped in or near GLIS3, PEPD, FITM2-R3HDML-HNF4A, KCNK16, MAEA, GCC1-PAX4, PSMD6 and ZFAND3. GLIS3, involved in pancreatic beta cell development and insulin gene expression1,2, is known for its association with fasting glucose levels3,4. The evidence of T2D association for PEPD5 and HNF4A6,7 has been detected in previous studies. KCNK16 may regulate glucose-dependent insulin secretion in the pancreas. These findings derived from East Asians provide new perspectives on the etiology of T2D

Genome-wide association study identifies a novel locus contributing to type 2 diabetes susceptibility in Sikhs of Punjabi origin from India.

We performed a genome-wide association study (GWAS) and a multistage meta-analysis of type 2 diabetes (T2D) in Punjabi Sikhs from India. Our discovery GWAS in 1,616 individuals (842 case subjects) was followed by in silico replication of the top 513 independent single nucleotide polymorphisms (SNPs) (P < 10⁻³) in Punjabi Sikhs (n = 2,819; 801 case subjects). We further replicated 66 SNPs (P < 10⁻⁴) through genotyping in a Punjabi Sikh sample (n = 2,894; 1,711 case subjects). On combined meta-analysis in Sikh populations (n = 7,329; 3,354 case subjects), we identified a novel locus in association with T2D at 13q12 represented by a directly genotyped intronic SNP (rs9552911, P = 1.82 × 10⁻⁸) in the SGCG gene. Next, we undertook in silico replication (stage 2b) of the top 513 signals (P < 10⁻³) in 29,157 non-Sikh South Asians (10,971 case subjects) and de novo genotyping of up to 31 top signals (P < 10⁻⁴) in 10,817 South Asians (5,157 case subjects) (stage 3b). In combined South Asian meta-analysis, we observed six suggestive associations (P < 10⁻⁵ to < 10⁻⁷), including SNPs at HMG1L1/CTCFL, PLXNA4, SCAP, and chr5p11. Further evaluation of 31 top SNPs in 33,707 East Asians (16,746 case subjects) (stage 3c) and 47,117 Europeans (8,130 case subjects) (stage 3d), and joint meta-analysis of 128,127 individuals (44,358 case subjects) from 27 multiethnic studies, did not reveal any additional loci nor was there any evidence of replication for the new variant. Our findings provide new evidence on the presence of a population-specific signal in relation to T2D, which may provide additional insights into T2D pathogenesis

Meta-analysis of genome-wide association studies identifies eight new loci for type 2 diabetes in east Asians

We conducted a three-stage genetic study to identify susceptibility loci for type 2 diabetes (T2D) in east Asian populations. We followed our stage 1 meta-analysis of eight T2D genome-wide association studies (6,952 cases with T2D and 11,865 controls) with a stage 2 in silico replication analysis (5,843 cases and 4,574 controls) and a stage 3 de novo replication analysis (12,284 cases and 13,172 controls). The combined analysis identified eight new T2D loci reaching genome-wide significance, which mapped in or near GLIS3, PEPD, FITM2-R3HDML-HNF4A, KCNK16, MAEA, GCC1-PAX4, PSMD6 and ZFAND3. GLIS3, which is involved in pancreatic beta cell development and insulin gene expression1,2, is known for its association with fasting glucose levels3,4. The evidence of an association with T2D for PEPD5 and HNF4A6,7 has been shown in previous studies. KCNK16 may regulate glucose-dependent insulin secretion in the pancreas. These findings, derived from an east Asian population, provide new perspectives on the etiology of T2D

Transferability of type 2 diabetes implicated loci in multi-ethnic cohorts from Southeast Asia.

Recent large genome-wide association studies (GWAS) have identified multiple loci which harbor genetic variants associated with type 2 diabetes mellitus (T2D), many of which encode proteins not previously suspected to be involved in the pathogenesis of T2D. Most GWAS for T2D have focused on populations of European descent, and GWAS conducted in other populations with different ancestry offer a unique opportunity to study the genetic architecture of T2D. We performed genome-wide association scans for T2D in 3,955 Chinese (2,010 cases, 1,945 controls), 2,034 Malays (794 cases, 1,240 controls), and 2,146 Asian Indians (977 cases, 1,169 controls). In addition to the search for novel variants implicated in T2D, these multi-ethnic cohorts serve to assess the transferability and relevance of the previous findings from European descent populations in the three major ethnic populations of Asia, comprising half of the world's population. Of the SNPs associated with T2D in previous GWAS, only variants at CDKAL1 and HHEX/IDE/KIF11 showed the strongest association with T2D in the meta-analysis including all three ethnic groups. However, consistent direction of effect was observed for many of the other SNPs in our study and in those carried out in European populations. Close examination of the associations at both the CDKAL1 and HHEX/IDE/KIF11 loci provided some evidence of locus and allelic heterogeneity in relation to the associations with T2D. We also detected variation in linkage disequilibrium between populations for most of these loci that have been previously identified. These factors, combined with limited statistical power, may contribute to the failure to detect associations across populations of diverse ethnicity. These findings highlight the value of surveying across diverse racial/ethnic groups towards the fine-mapping efforts for the casual variants and also of the search for variants, which may be population-specific

Familial Young-Onset Diabetes, Pre-Diabetes and Cardiovascular Disease Are Associated with Genetic Variants of DACH1 in Chinese

In Asia, young-onset type 2 diabetes (YOD) is characterized by obesity and increased risk for cardiovascular disease (CVD). In a genome-wide association study (GWAS) of 99 Chinese obese subjects with familial YOD diagnosed before 40-year-old and 101 controls, the T allele of rs1408888 in intron 1 of DACH1(Dachshund homolog 1) was associated with an odds ratio (OR) of 2.49(95% confidence intervals: 1.57-3.96, P = 8.4610(-5)). Amongst these subjects, we found reduced expression of DACH1 in peripheral blood mononuclear cells (PBMC) from 63 cases compared to 65 controls (P = 0.02). In a random cohort of 1468 cases and 1485 controls, amongst top 19 SNPs from GWAS, rs1408888 was associated with type 2 diabetes with a global P value of 0.0176 and confirmation in a multiethnic Asian case-control cohort (7370/7802) with an OR of 1.07(1.02-1.12, P-meta = 0.012). In 599 Chinese non-diabetic subjects, rs1408888 was linearly associated with systolic blood pressure and insulin resistance. In a case-control cohort (n = 953/953), rs1408888 was associated with an OR of 1.54(1.07-2.22, P = 0.019) for CVD in type 2 diabetes. In an autopsy series of 173 non-diabetic cases, TT genotype of rs1408888 was associated with an OR of 3.31(1.19-9.19, P = 0.0214) and 3.27(1.25-11.07, P = 0.0184) for coronary heart disease (CHD) and coronary arteriosclerosis. Bioinformatics analysis revealed that rs1408888 lies within regulatory elements of DACH1 implicated in islet development and insulin secretion. The T allele of rs1408888 of DACH1 was associated with YOD, prediabetes and CVD in Chinese

Meta-analysis of risk associations of <i>CPE</i> rs1583645 and <i>IDE</i> rs6583813 with Type 2 diabetes (T2D) using data from <i>de novo</i> genotyping and <i>in silico</i> analysis in a multi-ethnic population.

a<p>Risk alleles were underlined.^bThe allele frequency was based on HapMap Caucasian (CEU) population. ^cMeta-analysis for the Chinese from Hong Kong, Shanghai.</p><p>and Singapore, Korean and Japanese cohorts.</p

Associations of genetic risk scores (GRS) with beta cell function in Hong Kong Chinese unrelated controls (N = 419) with 1 risk allele of rs1583645 of <i>CPE</i> and rs6583813 of <i>IDE</i> each given 1 point.

<p>Data were shown as mean±SD or <b>^a</b>median(interquartile range) and analyzed by the linear regression with adjustment of age, sex and BMI under additive models after log-transformation. <i>P</i> values in bold indicated significance for the phenotypes. AUC: area under the curve.</p