Vaidya, Dhananjay

Background: The new 2013 ACC/AHA cholesterol guidelines recommend statin therapy to reduce atherosclerotic cardiovascular disease. Statins inhibit cholesterol biosynthesis which may impair gonadal steroidogenesis. Higher levels of estradiol (E2) and lower levels of sex hormone binding globulin (SHBG) are associated with greater central obesity, metabolic syndrome and diabetes in both men and postmenopausal women. There is however limited information regarding the impact of statins on endogenous sex hormones in large population studies. Methods: We included 3163 men and 1977 women from the baseline examination of the MESA study who had measurement of serum sex hormones: total and bioavailable testosterone (T), E2, dehydroepiandrosterone (DHEA) and SHBG, and excluded those on hormone replacement therapy and non-statin lipid medications. Results: Of the 5140 individuals examined, statin users (n=812) were 67 + 9 years old, 57% males, 41% Whites, 29% Blacks, 11% Chinese and 19% Hispanics. After adjustment for age, gender and race, total cholesterol, HDL-c and BMI, compared to non-users of statins, statin users had significantly lower SHBG by 4.5 nmol/L (95% CI; -6.1, -2.9) and DHEAS by 0.9 nmol/L (95% CI; -1.4, -0.4). No significant gender interaction with statin was seen. No association was noted between statin use and E2, total and bioavailable T. Conclusion: Statin use is associated inversely with serum SHBG and DHEA levels. This is particularly interesting in light of the association of statin use and diabetes, raising the possibility of mediation by endogenous hormones.

We investigated the effect of candidate variants in AS3MT (arsenic (III) methyltransferase) with urinary arsenic metabolites and their principal components in a subset of 264 participants in the Multi-Ethnic Study of Atherosclerosis (MESA). Urinary arsenic species, including inorganic arsenic (iAs), monomethylarsonate (MMA), dimethylarsinate (DMA), and arsenobetaine (Ab), were measured using high performance liquid chromatography-inductively coupled plasma mass spectrometry (HPLC-ICPMS) and corrected for organic sources from seafood consumption by regressing Ab on arsenic species using a validated method. Principal components of arsenic metabolism were also used as independent phenotypes. We conducted linear regression of arsenic traits with allelic dosage of candidate single nucleotide polymorphisms (SNPs) rs12768205 (G > A), rs3740394 (A > G), and rs3740393 (G > C) measured using Illumina MetaboChip. Models were stratified by non-Hispanic white vs. all other race/ethnicity and adjusted for age, sex, arsenic exposure, study site, and population stratification. Consistent with previous studies, rs12768205 showed evidence for strongest association (non-Hispanic white: iAs% −0.14 (P 0.83), MMA% −0.66 (0.49), DMA% 0.81(0.49); other race/ethnicity: 0.13 (0.71), −1.21 (0.09), 1.08 (0.20)). No association, however, passed the strict Bonferroni p-value. This was a novel study among an ethnically diverse population exposed to low arsenic levels.

OBJECTIVE The metabolic syndrome (MetS) is defined as concomitant disorders of lipid and glucose metabolism, central obesity, and high blood pressure, with an increased risk of type 2 diabetes and cardiovascular disease. This study tests whether common genetic variants with pleiotropic effects account for some of the correlated architecture among five metabolic phenotypes that define MetS. RESEARCH DESIGN AND METHODS Seven studies of the STAMPEED consortium, comprising 22,161 participants of European ancestry, underwent genome-wide association analyses of metabolic traits using a panel of ∼2.5 million imputed single nucleotide polymorphisms (SNPs). Phenotypes were defined by the National Cholesterol Education Program (NCEP) criteria for MetS in pairwise combinations. Individuals exceeding the NCEP thresholds for both traits of a pair were considered affected. RESULTS Twenty-nine common variants were associated with MetS or a pair of traits. Variants in the genes LPL, CETP, APOA5 (and its cluster), GCKR (and its cluster), LIPC, TRIB1, LOC100128354/MTNR1B, ABCB11, and LOC100129150 were further tested for their association with individual qualitative and quantitative traits. None of the 16 top SNPs (one per gene) associated simultaneously with more than two individual traits. Of them 11 variants showed nominal associations with MetS per se. The effects of 16 top SNPs on the quantitative traits were relatively small, together explaining from ∼9% of the variance in triglycerides, 5.8% of high-density lipoprotein cholesterol, 3.6% of fasting glucose, and 1.4% of systolic blood pressure. CONCLUSIONS Qualitative and quantitative pleiotropic tests on pairs of traits indicate that a small portion of the covariation in these traits can be explained by the reported common genetic variants.