Predicting type 2 diabetes using genetic and environmental risk factors in a multi-ethnic Malaysian cohort.

OBJECTIVE: Malaysia has a high and rising prevalence of type 2 diabetes (T2D). While environmental (non-genetic) risk factors for the disease are well established, the role of genetic variations and gene-environment interactions remain understudied in this population. This study aimed to estimate the relative contributions of environmental and genetic risk factors to T2D in Malaysia and also to assess evidence for gene-environment interactions that may explain additional risk variation. STUDY DESIGN: This was a case-control study including 1604 Malays, 1654 Chinese and 1728 Indians from the Malaysian Cohort Project. METHODS: The proportion of T2D risk variance explained by known genetic and environmental factors was assessed by fitting multivariable logistic regression models and evaluating McFadden's pseudo R2 and the area under the receiver-operating characteristic curve (AUC). Models with and without the genetic risk score (GRS) were compared using the log likelihood ratio Chi-squared test and AUCs. Multiplicative interaction between genetic and environmental risk factors was assessed via logistic regression within and across ancestral groups. Interactions were assessed for the GRS and its 62 constituent variants. RESULTS: The models including environmental risk factors only had pseudo R2 values of 16.5-28.3% and AUC of 0.75-0.83. Incorporating a genetic score aggregating 62 T2D-associated risk variants significantly increased the model fit (likelihood ratio P-value of 2.50 × 10-4-4.83 × 10-12) and increased the pseudo R2 by about 1-2% and AUC by 1-3%. None of the gene-environment interactions reached significance after multiple testing adjustment, either for the GRS or individual variants. For individual variants, 33 out of 310 tested associations showed nominal statistical significance with 0.001 < P < 0.05. CONCLUSION: This study suggests that known genetic risk variants contribute a significant but small amount to overall T2D risk variation in Malaysian population groups. If gene-environment interactions involving common genetic variants exist, they are likely of small effect, requiring substantially larger samples for detection.

Heritability of young- and old-onset ischaemic stroke.

BACKGROUND AND PURPOSE: Although the genetic contribution to stroke risk is well known, it remains unclear if young-onset stroke has a stronger genetic contribution than old-onset stroke. This study aims to compare the heritability of ischaemic stroke risk between young and old, using common genetic variants from whole-genome array data in population-based samples. METHODS: This analysis included 4050 ischaemic stroke cases and 5765 controls from six study populations of European ancestry; 47% of cases were young-onset stroke (age < 55 years). To quantify the heritability for stroke risk in these unrelated individuals, the pairwise genetic relatedness was estimated between individuals based on their whole-genome array data using a mixed linear model. Heritability was estimated separately for young-onset stroke and old-onset stroke (age ≥ 55 years). RESULTS: Heritabilities for young-onset stroke and old-onset stroke were estimated at 42% (±8%, P < 0.001) and 34% (±10%, P < 0.001), respectively. CONCLUSIONS: Our data suggest that the genetic contribution to the risk of stroke may be higher in young-onset ischaemic stroke, although the difference was not statistically significant.

Characterizing the genetic risk for Type 2 diabetes in a Malaysian multi-ethnic cohort.

AIMS: To characterize the association with Type 2 diabetes of known Type 2 diabetes risk variants in people in Malaysia of Malay, Chinese and Indian ancestry who participated in the Malaysian Cohort project. METHODS: We genotyped 1604 people of Malay ancestry (722 cases, 882 controls), 1654 of Chinese ancestry (819 cases, 835 controls) and 1728 of Indian ancestry (851 cases, 877 controls). First, 62 candidate single-nucleotide polymorphisms previously associated with Type 2 diabetes were assessed for association via logistic regression within ancestral groups and then across ancestral groups using a meta-analysis. Second, estimated odds ratios were assessed for excess directional concordance with previously studied populations. Third, a genetic risk score aggregating allele dosage across the candidate single-nucleotide polymorphisms was tested for association within and across ancestral groups. RESULTS: After Bonferroni correction, seven individual single-nucleotide polymorphisms were associated with Type 2 diabetes in the combined Malaysian sample. We observed a highly significant excess in concordance of effect directions between Malaysian and previously studied populations. The genetic risk score was strongly associated with Type 2 diabetes in all Malaysian groups, explaining from 1.0 to 1.7% of total Type 2 diabetes risk variance. CONCLUSION: This study suggests there is substantial overlap of the genetic risk alleles underlying Type 2 diabetes in Malaysian and other populations.

A reanalysis of 409 European-Ancestry and African American schizophrenia pedigrees reveals significant linkage to 8p23.3 with evidence of locus heterogeneity.

The detection and replication of schizophrenia risk loci can require substantial sample sizes, which has prompted various collaborative efforts for combining multiple samples. However, pooled samples may comprise sub-samples with substantial population genetic differences, including allele frequency differences. We investigated the impact of population differences via linkage reanalysis of Molecular Genetics of Schizophrenia 1 (MGS1) affected sibling-pair data, comprising two samples of distinct ancestral origin: European (EA: 263 pedigrees) and African-American (AA: 146 pedigrees). To exploit the linkage information contained within these distinct continental samples, we performed separate analyses of the individual samples, allowing for within-sample locus heterogeneity, and the pooled sample, allowing for both within-sample and between-sample heterogeneity. Significance levels, corrected for the multiple tests, were determined empirically. For all suggestive peaks, stronger linkage evidence was obtained in either the EA or AA sample than the combined sample, regardless of how heterogeneity was modeled for the latter. Notably, we report genomewide significant linkage of schizophrenia to 8p23.3 and evidence for a second, independent susceptibility locus, reaching suggestive linkage, 29 cM away on 8p21.3. We also detected suggestive linkage on chromosomes 5p13.3 and 7q36.2. Many regions showed pronounced differences in the extent of linkage between the EA and AA samples. This reanalysis highlights the potential impact of population differences upon linkage evidence in pooled data and demonstrates a useful approach for the analysis of samples drawn from distinct continental groups.