Applying novel genome-wide linkage strategies to search for loci influencing type 2 diabetes and adult height in American Samoa

Type 2 diabetes mellitus (T2DM) is a common complex phenotype that by the year 2010 is predicted to affect 221 million people globally. In the present study we performed a genome-wide linkage scan using the allele-sharing statistic Sall implemented in Allegro and a novel two-dimensional genome-wide strategy implemented in Merloc that searches for pairwise interaction between genetic markers located on different chromosomes linked to T2DM. In addition, we used a robust score statistic from the newly developed QTL-ALL software to search for linkage to variation in adult height. The strategies were applied to a study sample consisting of 238 sib-pairs affected with T2DM from American Samoa. We did not detect any genome-wide significant susceptibility loci for T2DM. However, our two-dimensional linkage investigation detected several loci pairs of interest, including 11q22 and 21q21, 9q21 and 11q22, 1p22-p21 and 4p15, and 4p15 and 15q11-q14, with a two-loci maximum LOD score (MLS) greater than 2.00. Most detected individual loci have previously been identified as susceptibility loci for diabetes-related traits. Our two-dimensional linkage results may facilitate the selection of potential candidate genes and molecular pathways for further diabetes studies because these results, besides providing candidate loci, also demonstrate that polygenic effects may play an important role in T2DM. Linkage was detected (p value of 0.005) for variation in adult height on chromosome 9q31, which was reported previously in other populations. Our finding suggests that the 9q31 region may be a strong quantitative trait locus for adult height, which is likely to be of importance across populations.     

A genomewide scan for type 1-diabetes susceptibility in Scandinavian families: identification of new loci with evidence of interactions

Type 1 diabetes mellitus (TIDM) has a multifactorial etiology, with major genetic-susceptibility determinants located in the HLA and insulin-gene (INS) regions. Linkage data implicating other disease-susceptibility loci are conflicting. This is likely due to (1) the limited power for detection of contributions of additional susceptibility loci, given the limited number of informative families available for study, (2) factors such as genetic heterogeneity between populations, and (3) potential gene-gene and gene-environment interactions. To circumvent some of these problems, we have conducted a genomewide linkage analysis for T1DM-susceptibility loci in 408 multiplex families from Scandinavia, a population expected to be homogeneous for genetic and environmental factors. In addition to verifying the HLA and INS susceptibility loci, the study provides confirmation of IDDM15 on chromosome 6q21. Suggestive evidence of additional susceptibility loci was found on chromosomes 2p, 5q, and 16p. For some loci, the support for linkage increased substantially when families were stratified on the basis of HLA or INS genotypes, with statistically significant heterogeneity between the stratified subgroups. Our data support both the existence of non-HLA genes of significance for T1DM and interaction between HLA and non-HLA loci in the determination of the T1DM phenotype.     

Log-linear models for gene mapping with affected sib pair data

In genome-wide screens of genetic marker loci, non-mendelian inheritance of a marker is taken to indicate its vicinity to a disease locus. Heritable complex traits are thought to be under the influence of multiple possibly interacting susceptibility loci yet the most frequently used methods of linkage and association analysis focus on one susceptibility locus at a time. Here we introduce log-linear models for the joint analysis of multiple marker loci and interaction effects between them. Our approach focuses on affected sib pair data and identical by descent (IBD) allele sharing values observed on them. For each heterozygous parent, the IBD values at linked markers represent a sequence of dependent binary variables. We develop log-linear models for the joint distribution of these IBD values. An independence log-linear model is proposed to model the marginal means and the neighboring interaction model is advocated to account for associations between adjacent markers. Under the assumption of conditional independence, likelihood methods are applied to simulated data containing one or two susceptibility loci. It is shown that the neighboring interaction log-linear model is more efficient than the independence model, and incorporating interaction in the two-locus analysis provides increased power and accuracy for mapping of the trait loci.     

Linkage and Association Studies of the Susceptibility Genes for Type 2 Diabetes

Type 2 diabetes mellitus (T2DM) is a complex disease characterized by hyperglycemia, insulin resistance, and impaired insulin secretion. T2DM is under strong genetic control. Identification and characterization of genes involved in determining T2DM will contribute to a greater understanding of the pathogenesis of T2DM, and ultimately might lead to the development of better diagnosis, prevention and treatment strategies. Efforts to identify T2DM susceptibility genes have focused on candidate gene approach (association studies) and genome-wide scans (linkage analyses). In this article, we review the current status for mapping and identification of genes for T2DM, with a focus on some promising regions (or genes) and future prospects.     

一种有效的复杂疾病基因定位的检测法

连锁不平衡（LD）应用于某些复杂疾病基因的定位,近年来发展了许多LD定位方法,除TDT外,大多数LD定位方法须先假定无人群混和,人群混合可增大在疾病基因定位时犯Ⅰ类错误的机率,产生无效结果。此方法利用LD来检测标记位点和疾病敏感位点（DSL）的连锁（有连锁不平衡）相关（有连锁）。分析时采用不相关样本,已知其父母基因型和至少父母之一为杂合子,再将随机样本依基因型不同分类,然后对来自不同类的数据应用有力的统计方法进行单独和联合分析。此LD定位法不仅适用于患病和正常个体,而且有效消除据父母基因分类的样本定位时人群混合的影响,分析结果和模拟结果也表明此方法解决了在检测标记位点和疾病敏感位点之间的连锁和相关时人群混和的问题,但与TDT比,此法在检测的位点为DSL时丙能有效和充分地利用矫正数据,检测位点不是DSL时,此法和TDT法可相互补充更有效地检测连锁的DSL。     

The mutation of the LEW.1AR1-<Emphasis Type="Italic">iddm</Emphasis> rat maps to the telomeric end of rat chromosome 1

The LEW.1AR1-iddm rat is an animal model of human type 1 diabetes mellitus (T1DM) with an autosomal recessive mode of inheritance. T1DM susceptibility loci could be localized on chromosome (RNO) 20 in the major histocompatibility complex region (Iddm1) and on RNO1 (Iddm8, Iddm9) in a BN backcross cohort. In this study the impact of the different susceptibility regions on diabetes development was investigated in a backcross population of the diabetes-resistant PAR strain. A cohort of 130 [(PAR × LEW.1AR1-iddm) × LEW.1AR1-iddm] N2 rats was monitored for blood glucose and analyzed by linkage analysis. Sixteen percent of the PAR backcross animals developed T1DM. Genetic analysis revealed significant linkage to T1DM in the MHC region on RNO20p12. In contrast to the linkage analysis of the BN backcross cohort, only one susceptibility locus for T1DM could be identified on RNO1. This susceptibility region on RNO1 mapped to the telomeric end corresponding to Iddm8. Eighty-nine percent of diabetic PAR backcross animals were homozygous for Iddm8. The Iddm9 diabetes susceptibility region showed no linkage to diabetes in the PAR backcross cohort. The data of this study provide evidence that the mutation leading to T1DM in the LEW.1AR1-iddm rat is located at the telomeric end of RNO1 corresponding to Iddm8. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users. H. Weiss and T. Arndt contributed equally to this study.     

Integrated Enrichment Analysis of Variants and Pathways in Genome-Wide Association Studies Indicates Central Role for IL-2 Signaling Genes in Type 1 Diabetes,and Cytokine Signaling Genes in Crohn's Disease

Pathway analyses of genome-wide association studies aggregate information over sets of related genes, such as genes in common pathways, to identify gene sets that are enriched for variants associated with disease. We develop a model-based approach to pathway analysis, and apply this approach to data from the Wellcome Trust Case Control Consortium (WTCCC) studies. Our method offers several benefits over existing approaches. First, our method not only interrogates pathways for enrichment of disease associations, but also estimates the level of enrichment, which yields a coherent way to promote variants in enriched pathways, enhancing discovery of genes underlying disease. Second, our approach allows for multiple enriched pathways, a feature that leads to novel findings in two diseases where the major histocompatibility complex (MHC) is a major determinant of disease susceptibility. Third, by modeling disease as the combined effect of multiple markers, our method automatically accounts for linkage disequilibrium among variants. Interrogation of pathways from eight pathway databases yields strong support for enriched pathways, indicating links between Crohn''s disease (CD) and cytokine-driven networks that modulate immune responses; between rheumatoid arthritis (RA) and “Measles” pathway genes involved in immune responses triggered by measles infection; and between type 1 diabetes (T1D) and IL2-mediated signaling genes. Prioritizing variants in these enriched pathways yields many additional putative disease associations compared to analyses without enrichment. For CD and RA, 7 of 8 additional non-MHC associations are corroborated by other studies, providing validation for our approach. For T1D, prioritization of IL-2 signaling genes yields strong evidence for 7 additional non-MHC candidate disease loci, as well as suggestive evidence for several more. Of the 7 strongest associations, 4 are validated by other studies, and 3 (near IL-2 signaling genes RAF1, MAPK14, and FYN) constitute novel putative T1D loci for further study.     

Subsets of Finns with high HDL to total cholesterol ratio show evidence for linkage to type 2 diabetes on chromosome 6q

OBJECTIVES: The purpose of this study was to examine carefully heterogeneity underlying evidence for linkage to type 2 diabetes (T2DM) on chromosome 6q from two sets of FUSION families. METHODS: Ordered subsets analysis (OSA) was performed on two sets of FUSION families. For OSA results showing significant improvement in evidence for linkage, T2DM-related phenotypes were compared between individuals with T2DM within the subset versus the complement. RESULTS: OSA analysis revealed 105 families with the highest average HDL to total cholesterol ratio (HDL ratio) that had strongly increased evidence for linkage (MLS = 7.91 at 78.0 cM; uncorrected p = 0.00002). Subjects with T2DM within this subset were significantly leaner, had lower fasting glucose, insulin, and C-peptide, and more favorable cardiovascular risk profile compared to the complement set of subjects with T2DM. OSA also revealed 33 families with the lowest average fasting insulin that had increased evidence for linkage at a second locus (MLS = 3.45 at 128 cM; uncorrected p = 0.017) coincident with quantitative trait locus linkage analysis results for fasting and 2-hour insulin in subjects without T2DM. CONCLUSIONS: These results suggest two diabetes susceptibility loci on chromosome 6q that may affect subsets of individuals with a milder form of T2DM.     

2型糖尿病易感基因的连锁和关联研究

2型糖尿病（T2DM）是由于胰岛素抵抗和β细胞分泌缺陷导致高血糖的一种复杂多基因疾病。遗传因素在T2DM的发生发展中起着重要的作用,其遗传率估计为70％～80％。鉴定2型糖尿病基因将有助于阐明其发病机制,发展更好的诊断、预防和治疗策略。2型糖尿病易感基因的鉴定方法主要有候选基因关联研究和全基因组连锁分析。有3种类型的候选基因：功能候选基因、图位候选基因和表达候选基因。虽然许多候选基因与T2DM的关联分析已经进行,但多数都没有得到一致的重复,过氧化物酶体增殖物激活受-γ,体和β-细胞ATP敏感性钾通道基因是目前最好重复的基因。迄今为止,T2DM的全基因组扫描已在20多个不同的群体中进行,包括欧洲人、美国白人、墨西哥裔美国人、美国本地印度人、非洲裔美国人和亚洲人,这些研究鉴定了一些与T2DM相关的QTLs区域。与T2DM显著和证实连锁的区域包括1q25、2q37．3q28、3p24、6q22、8p23、10q26、12q24、18p11、20q13等,与T2DM提示连锁的区域有1q42、2p21、2q24、4q34、5q13、5q31、7q32、9p24、9q21、10p14、11p13、11q13、12q15、14q23、20p12、Xq23等。鉴定这些区域的T2DMQTLs基因及其作用机制是未来的主要挑战。把DNA微阵列和蛋白质组学技术结合起来应用于传统的连锁分析和关联研究,研究基因-基因间、基因-环境间的互作和多个基因对T2DM的加性效应和综合作用,进一步加强国际协作,T2DM的遗传机制可望在不远的将来得到阐明。本文总结了2型糖尿病基因鉴定的现状,重点在一些得到重复的区域和未来的展望。     

Multidimensional approaches in dealing with prostate cancer

Prostate cancer is one of the most prevalent malignancies worldwide affecting the human male population. Different case-control, cohort or twin studies and segregation analyses point towards the presence of prostate cancer-susceptibility genes in the population. The studies have shown linkage of prostate susceptibility genes to multiple loci on chromosome 1 and single locus each on chromosomes 4, 8, 16, 17, 19, 20 and X chromosome. However, differences right from the mode of inheritance (autosomal dominant or X-linked recessive) to the target genes exist. There have been reports supporting no or weak linkage to these loci as well. Also, region (environmental factors), age and dietary habits have implications in different aspects of the disease. The important targets for treating prostate cancer are androgens and estrogen (synthesized from androgens by the action of enzyme aromatase) owing to their involvement in development and progression of prostate cancer. Further, prostate gland needs androgens (male hormones) for its normal maintenance and functioning. Besides, radiation therapy and surgical methods have also been used. The emerging areas include identifying and preparing successful vaccines from candidate peptides and gene therapy in several forms. This review deals with the paradox of linkage analyses and the various approaches in practice for treatment and management of prostate cancer.     

Use of multivariate linkage analysis for dissection of a complex cognitive trait

Replication of linkage results for complex traits has been exceedingly difficult, owing in part to the inability to measure the precise underlying phenotype, small sample sizes, genetic heterogeneity, and statistical methods employed in analysis. Often, in any particular study, multiple correlated traits have been collected, yet these have been analyzed independently or, at most, in bivariate analyses. Theoretical arguments suggest that full multivariate analysis of all available traits should offer more power to detect linkage; however, this has not yet been evaluated on a genomewide scale. Here, we conduct multivariate genomewide analyses of quantitative-trait loci that influence reading- and language-related measures in families affected with developmental dyslexia. The results of these analyses are substantially clearer than those of previous univariate analyses of the same data set, helping to resolve a number of key issues. These outcomes highlight the relevance of multivariate analysis for complex disorders for dissection of linkage results in correlated traits. The approach employed here may aid positional cloning of susceptibility genes in a wide spectrum of complex traits.     

A genome-wide association search for type 2 diabetes genes in African Americans

African Americans are disproportionately affected by type 2 diabetes (T2DM) yet few studies have examined T2DM using genome-wide association approaches in this ethnicity. The aim of this study was to identify genes associated with T2DM in the African American population. We performed a Genome Wide Association Study (GWAS) using the Affymetrix 6.0 array in 965 African-American cases with T2DM and end-stage renal disease (T2DM-ESRD) and 1029 population-based controls. The most significant SNPs (n = 550 independent loci) were genotyped in a replication cohort and 122 SNPs (n = 98 independent loci) were further tested through genotyping three additional validation cohorts followed by meta-analysis in all five cohorts totaling 3,132 cases and 3,317 controls. Twelve SNPs had evidence of association in the GWAS (P<0.0071), were directionally consistent in the Replication cohort and were associated with T2DM in subjects without nephropathy (P<0.05). Meta-analysis in all cases and controls revealed a single SNP reaching genome-wide significance (P<2.5×10⁻⁸). SNP rs7560163 (P = 7.0×10⁻⁹, OR (95% CI) = 0.75 (0.67–0.84)) is located intergenically between RND3 and RBM43. Four additional loci (rs7542900, rs4659485, rs2722769 and rs7107217) were associated with T2DM (P<0.05) and reached more nominal levels of significance (P<2.5×10⁻⁵) in the overall analysis and may represent novel loci that contribute to T2DM. We have identified novel T2DM-susceptibility variants in the African-American population. Notably, T2DM risk was associated with the major allele and implies an interesting genetic architecture in this population. These results suggest that multiple loci underlie T2DM susceptibility in the African-American population and that these loci are distinct from those identified in other ethnic populations.     

Linkage analysis of "necessary" disease loci versus "susceptibility" loci.

The association of some diseases with specific alleles of certain genetic markers has been difficult to explain. Several explanations have been proposed for the phenomenon of association, e.g. the existence of multiple, interacting genes (epistasis) or a disease locus in linkage disequilibrium with the marker locus. One might suppose that when marker data from families with associated diseases are analyzed for linkage, the existence of the association would assure that linkage will be found, and found at a tight recombination fraction. In fact, however, linkage analyses of some diseases associated with HLA, as well as diseases associated with alleles at other loci located throughout the genome, show significant evidence against linkage, and others show loose linkage, to the puzzlement of many researchers. In part, the puzzlement arises because linkage analysis is ideal for looking for loci that are necessary, even if not sufficient, for disease expression but may be much less useful for finding loci that are neither necessary nor sufficient for disease expression (so-called susceptibility loci). This work explores what happens when one looks for linkage to susceptibility loci. A susceptibility locus in this case means that the allele increases risk but is neither necessary nor sufficient for disease expression. It might be either an allele at the marker locus itself that is increasing susceptibility or an allele at a locus in linkage disequilibrium with the marker. This work uses computer simulation to examine how linkage analyses behave when confronted with data from such a model.(ABSTRACT TRUNCATED AT 250 WORDS)     

Novel susceptibility locus at 22q11 for diabetic nephropathy in type 1 diabetes

Background

Diabetic nephropathy (DN) affects about 30% of patients with type 1 diabetes (T1D) and contributes to serious morbidity and mortality. So far only the 3q21–q25 region has repeatedly been indicated as a susceptibility region for DN. The aim of this study was to search for new DN susceptibility loci in Finnish, Danish and French T1D families.

Methods and Results

We performed a genome-wide linkage study using 384 microsatellite markers. A total of 175 T1D families were studied, of which 94 originated from Finland, 46 from Denmark and 35 from France. The whole sample set consisted of 556 individuals including 42 sib-pairs concordant and 84 sib-pairs discordant for DN. Two-point and multi-point non-parametric linkage analyses were performed using the Analyze package and the MERLIN software. A novel DN locus on 22q11 was identified in the joint analysis of the Finnish, Danish and French families by genome-wide multipoint non-parametric linkage analysis using the Kong and Cox linear model (NPL_pairs LOD score 3.58). Nominal or suggestive evidence of linkage to this locus was also detected when the three populations were analyzed separately. Suggestive evidence of linkage was found to six additional loci in the Finnish and French sample sets.

Conclusions

This study identified a novel DN locus at chromosome 22q11 with significant evidence of linkage to DN. Our results suggest that this locus may be of importance in European populations. In addition, this study supports previously indicated DN loci on 3q21–q25 and 19q13.     

Confirmation of the HPCX prostate cancer predisposition locus in large Utah prostate cancer pedigrees

Several genetic predisposition loci for prostate cancer have been identified through linkage analysis, and it is now generally recognized that no single gene is responsible for more than a small proportion of prostate cancers. However, published confirmations of these loci have been few, and failures to confirm have been frequent. The genetic etiology of prostate cancer is clearly complex and includes significant genetic heterogeneity, phenocopies, and reduced penetrance. Powerful analyses that involve robust statistics and methods to reduce genetic heterogeneity are therefore necessary. We have performed linkage analysis on 143 Utah pedigrees for the previously published Xq27-28 (HPCX) prostate cancer susceptibility locus. We employed a robust multipoint statistic (TLOD) and a novel splitting algorithm to reduce intra-familial heterogeneity by iteratively removing the top generation from the large Utah pedigrees. In a dataset containing pedigrees having no more than five generations, we observed a multipoint TLOD of 2.74 (P=0.0002), which is statistically significant after correction for multiple testing. For both the full-structure pedigrees (up to seven generations) and the smaller sub-pedigrees, the linkage evidence was much reduced. This study thus represents the first significant confirmation of HPCX (Xq27-28) and argues for the continued utility of large pedigrees in linkage analyses for complex diseases.     

A novel linkage to generalized vitiligo on 4q13-q21 identified in a genomewide linkage analysis of Chinese families

Generalized vitiligo is a common, autoimmune, familial-clustering depigmentary disorder of the skin and hair that results from selective destruction of melanocytes. Generalized vitiligo is likely a heterogeneous disease, with five susceptibility loci reported so far--on chromosomes 1p31, 6p21, 7q, 8p, and 17p13--in white populations. To investigate vitiligo susceptibility loci in the Chinese population, we performed a genomewide linkage analysis in 57 multiplex Chinese families, each with at least two affected siblings, and we identified interesting linkage evidence on 1p36, 4q13-q21, 6p21-p22, 6q24-q25, 14q12-q13, and 22q12. Subsequently, to extract more linkage information, we investigated our initial genomewide linkage findings in a follow-up analysis of 49 new families and additional markers. Our initial genomewide linkage analysis and our subsequent follow-up analysis have identified a novel linkage to vitiligo on 4q13-q21, with highly significant linkage evidence (a nonparametic LOD score of 4.62 [P=.000003] and a heterogeneity LOD score of 4.01, under a recessive inheritance model), suggesting that 4q13-q21 likely harbors a major susceptibility locus for vitiligo in the Chinese population. We observed a minimal overlap between the linkage results of our current genomewide analysis in the Chinese population and the results of previous analyses in white populations, and we thus hypothesize that, as a polygenic disorder, vitiligo may be associated with great genetic heterogeneity and a substantial difference in its genetic basis between ethnic populations.     

Identification of Allelic Heterogeneity at Type-2 Diabetes Loci and Impact on Prediction

Although over 60 single nucleotide polymorphisms (SNPs) have been identified by meta-analysis of genome-wide association studies for type-2 diabetes (T2D) among individuals of European descent, much of the genetic variation remains unexplained. There are likely many more SNPs that contribute to variation in T2D risk, some of which may lie in the regions surrounding established SNPs - a phenomenon often referred to as allelic heterogeneity. Here, we use the summary statistics from the DIAGRAM consortium meta-analysis of T2D genome-wide association studies along with linkage disequilibrium patterns inferred from a large reference sample to identify novel SNPs associated with T2D surrounding each of the previously established risk loci. We then examine the extent to which the use of these additional SNPs improves prediction of T2D risk in an independent validation dataset. Our results suggest that multiple SNPs at each of 3 loci contribute to T2D susceptibility (TCF7L2, CDKN2A/B, and KCNQ1; p<5×10⁻⁸). Using a less stringent threshold (p<5×10⁻⁴), we identify 34 additional loci with multiple associated SNPs. The addition of these SNPs slightly improves T2D prediction compared to the use of only the respective lead SNPs, when assessed using an independent validation cohort. Our findings suggest that some currently established T2D risk loci likely harbor multiple polymorphisms which contribute independently and collectively to T2D risk. This opens a promising avenue for improving prediction of T2D, and for a better understanding of the genetic architecture of T2D.     

Genomewide linkage searches for Mendelian disease loci can be efficiently conducted using high-density SNP genotyping arrays

Genomewide linkage searches aimed at identifying disease susceptibility loci are generally conducted using 300–400 microsatellite markers. Genotyping bi-allelic single nucleotide polymorphisms (SNPs) provides an alternative strategy. The availability of dense SNP maps coupled with recent technological developments in highly paralleled SNP genotyping makes it practical to now consider the use of these markers for whole-genome genetic linkage analyses. Here, we report the findings from three successful genomewide linkage analyses of families segregating autosomal recessively inherited neonatal diabetes, craniosynostosis and dominantly inherited renal dysplasia using the Affymetrix 10K SNP array. A single locus was identified for each disease state, two of which are novel. The performance of the SNP array, both in terms of efficiency and precision, indicates that such platforms will become the dominant technology for performing genomewide linkage searches.     

The Uyghur population and genetic susceptibility to type 2 diabetes: potential role for variants in CAPN10, APM1 and FUT6 genes

Genome‐wide association studies have successfully identified over 70 loci associated with the risk of type 2 diabetes mellitus (T2DM) in multiple populations of European ancestry. However, the risk attributable to an individual variant is modest and does not yet provide convincing evidence for clinical utility. Association between these established genetic variants and T2DM in general populations is hitherto understudied in the isolated populations, such as the Uyghurs, resident in Hetian, far southern Xinjiang Uyghur Autonomous Region, China. In this case–control study, we genotyped 13 single‐nucleotide polymorphisms (SNPs) at 10 genes associated with diabetes in 130 cases with T2DM and 135 healthy controls of Uyghur, a Chinese minority ethnic group. Three of the 13 SNPs demonstrated significant association with T2DM in the Uyghur population. There were significant differences between the T2DM patients and controls in the risk allele distributions of rs3792267 (CAPN10) (P = 0.002), rs1501299 (APM1) (P = 0.017), and rs3760776 (FUT6) (P = 0.031). Allelic carriers of rs3792267‐A, rs1501299‐T, and rs3760776‐T had a 2.24‐fold [OR (95% CI): 1.35–3.71], 0.59‐fold [OR (95% CI): 0.39–0.91], 0.57‐fold [OR (95% CI): 0.34–0.95] increased risk for T2DM respectively. We further confirmed that the cumulative risk allelic scores calculated from the 13 susceptibility loci for T2DM differed significantly between the T2DM patients and controls (P = 0.001), and the effect of obesity/overweight on T2DM was only observed in the subjects with a combined risk allelic score under a value of 17. This study observed that the SNPs rs3792267 in CAPN10, rs1501299 in APM1, and rs3760776 in FUT6 might serve as potential susceptible biomarkers for T2DM in Uyghurs. The cumulative risk allelic scores of multiple loci with modest individual effects are also significant risk factors in Uyghurs for T2DM, particularly among non‐obese individuals. This is the first investigation having observed/found genetic variations on genetic loci functionally linked with glycosylation associated with the risk of T2DM in a Uyghur population.