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Background: Sex hormones are implicated in the development of diabetes. However, whether genetic variations in sex hormone pathways (SHPs) contribute to the risk of type 2 diabetes mellitus (T2DM) remains to be determined. This study investigated associations between genetic variations in all candidate genes in SHPs and T2DM risk among a cohort of women participating in the Women's Health Initiative (WHI)., Methods: Single nucleotide polymorphisms (SNPs) located within 30 kb upstream and downstream of SHP genes were comprehensively examined in 8180 African American, 3498 Hispanic American, and 3147 European American women in the WHI. In addition, whether significant SNPs would be replicated in independent populations was examined., Results: After adjusting for age, region, and ancestry estimates and correcting for multiple testing, seven SNPs were significantly associated with the risk of T2DM among Hispanic American women were identified in the progesterone receptor (PGR) gene, with rs948516 showing the greatest significance (odds ratio 0.67; 95% confidence interval 0.57-0.78; P = 8.8 × 10 -7 ; false discovery rate, Q = 7.8 × 10 -4 ). These findings were not replicated in other ethnic groups in the WHI or in sex-combined analyses in replication studies., Conclusion: Significant signals were identified implicating the PGR gene in T2DM development in Hispanic American women in the WHI, which are consistent with genome-wide association studies findings linking PGR to glucose homeostasis. Nevertheless, the PGR SNPs-T2DM association was not statistically significant in other ethnic populations. Further studies, especially sex-specific analyses, are needed to confirm the findings and clarify the role of SHPs in T2DM., (© 2018 Ruijin Hospital, Shanghai Jiaotong University School of Medicine and John Wiley & Sons Australia, Ltd.)

Background and Purpose: Ischemic stroke (IS) shares many common risk factors with coronary artery disease (CAD). We hypothesized that genetic variants associated with myocardial infarction (MI) or CAD may be similarly involved in the etiology of IS. To test this hypothesis, we evaluated whether single-nucleotide polymorphisms (SNPs) at 11 different loci recently associated with MI or CAD through genome-wide association studies were associated with IS., Methods: Meta-analyses of the associations between the 11 MI-associated SNPs and IS were performed using 6865 cases and 11 395 control subjects recruited from 9 studies. SNPs were either genotyped directly or imputed; in a few cases a surrogate SNP in high linkage disequilibrium was chosen. Logistic regression was performed within each study to obtain study-specific βs and standard errors. Meta-analysis was conducted using an inverse variance weighted approach assuming a random effect model., Results: Despite having power to detect odds ratio of 1.09-1.14 for overall IS and 1.20-1.32 for major stroke subtypes, none of the SNPs were significantly associated with overall IS and/or stroke subtypes after adjusting for multiple comparisons., Conclusions: Our results suggest that the major common loci associated with MI risk do not have effects of similar magnitude on overall IS but do not preclude moderate associations restricted to specific IS subtypes. Disparate mechanisms may be critical in the development of acute ischemic coronary and cerebrovascular events.

Whereas moderate drinking may have health benefits, excessive alcohol consumption causes many important acute and chronic diseases and is the third leading contributor to preventable death in the United States. Twin studies suggest that alcohol-consumption patterns are heritable (50%); however, multiple genetic variants of modest effect size are likely to contribute to this heritable variation. Genome-wide association studies provide a tool for discovering genetic loci that contribute to variations in alcohol consumption. Opportunities exist to identify susceptibility loci with modest effect by meta-analyzing together multiple studies. However, existing studies assessed many different aspects of alcohol use, such as typical compared with heavy drinking, and these different assessments can be difficult to reconcile. In addition, many studies lack the ability to distinguish between lifetime and recent abstention or to assess the pattern of drinking during the week, and a variety of such concerns surround the appropriateness of developing a common summary measure of alcohol intake. Combining such measures of alcohol intake can cause heterogeneity and exposure misclassification, cause a reduction in power, and affect the magnitude of genetic association signals. In this review, we discuss the challenges associated with harmonizing alcohol-consumption data from studies with widely different assessment instruments, with a particular focus on large-scale genetic studies.