The Pharmacogenetics of Statin Therapy on Clinical Events: No Evidence that Genetic Variation Affects Statin Response on Myocardial Infarction.

Background: The pharmacogenetic effect on cardiovascular disease reduction in response to statin treatment has only been assessed in small studies. In a pharmacogenetic genome wide association study (GWAS) analysis within the Genomic Investigation of Statin Therapy (GIST) consortium, we investigated whether genetic variation was associated with the response of statins on cardiovascular disease risk reduction. Methods: The investigated endpoint was incident myocardial infarction (MI) defined as coronary heart disease death and definite and suspect non-fatal MI. For imputed single nucleotide polymorphisms (SNPs), regression analysis was performed on expected allelic dosage and meta-analysed with a fixed-effects model, inverse variance weighted meta-analysis. All SNPs with p-values <5.0 × 10-4 in stage 1 GWAS meta-analysis were selected for further investigation in stage-2. As a secondary analysis, we extracted SNPs from the Stage-1 GWAS meta-analysis results based on predefined hypotheses to possibly modifying the effect of statin therapy on MI. Results: In stage-1 meta-analysis (eight studies, n = 10,769, 4,212 cases), we observed no genome-wide significant results (p < 5.0 × 10-8). A total of 144 genetic variants were followed-up in the second stage (three studies, n = 1,525, 180 cases). In the combined meta-analysis, no genome-wide significant hits were identified. Moreover, none of the look-ups of SNPs known to be associated with either CHD or with statin response to cholesterol levels reached Bonferroni level of significance within our stage-1 meta-analysis. Conclusion: This GWAS analysis did not provide evidence that genetic variation affects statin response on cardiovascular risk reduction. It does not appear likely that genetic testing for predicting effects of statins on clinical events will become a useful tool in clinical practice.

Low Birth Weight and Kidney Function in Middle-Aged Men and Women: The Netherlands Epidemiology of Obesity Study.

RATIONALE & OBJECTIVE: Chronic kidney disease (CKD), defined as estimated glomerular filtration rate (eGFR)<60mL/min/1.73m2, is a risk factor for cardiovascular morbidity and mortality. Little is known about low birth weight and risk for CKD in middle-aged adults in the general population. We estimated the causal association between birth weight and eGFR in a Dutch cohort of middle-aged men and women. STUDY DESIGN: Retrospective cohort study. SETTING & PARTICIPANTS: 6,671 participants in the Netherlands Epidemiology of Obesity (NEO) Study. Replication study using data for 133,814 participants studied by the CKDGen consortium. EXPOSURE: Birth weight was self-reported and also based on an instrumental variable, 59 birth weight-associated genetic variants, derived from an independent data source. OUTCOME: eGFR at the age of 45 to 65 years. ANALYTICAL APPROACH: We assessed the association between self-reported birth weight and eGFR in the NEO Study using multivariable linear regression, adjusted for age, sex, education, smoking, and alcohol use. The effect of the instrument on eGFR was estimated using separate 2-sample Mendelian randomization analyses: one using individual data from the NEO cohort and one using summary data from the CKDGen consortium. RESULTS: At baseline, mean eGFR was 86±12.4 (SD) mL/min/1.73m2. After multivariable adjustment, self-reported birth weight was not associated with kidney function in middle age. Two-sample Mendelian randomization analysis showed that in the NEO cohort, for each 500-g lower birth weight defined using genetic variants, there was a 3.7 (95% CI, 0.5-6.9)-mL/min/1.73m2 lower eGFR at the age of 45 to 65 years. However, using CKDGen summary-level data, there was a smaller nonsignificant relationship between birth weight and eGFR. LIMITATIONS: Birth weight was self-reported. CONCLUSIONS: Lower birth weight defined using genetic variants was associated with lower eGFRs in Dutch middle-aged adults. However, this finding was not replicated within the CKDGen consortium.

Metabolomics Profiling of Visceral Adipose Tissue: Results From MESA and the NEO Study.

Background Identifying associations between serum metabolites and visceral adipose tissue ( VAT ) could provide novel biomarkers of VAT and insights into the pathogenesis of obesity-related diseases. We aimed to discover and replicate metabolites reflecting pathways related to VAT . Methods and Results Associations between fasting serum metabolites and VAT area (by computed tomography or magnetic resonance imaging) were assessed with cross-sectional linear regression of individual-level data from participants in MESA (Multi-Ethnic Study of Atherosclerosis; discovery, N=1103) and the NEO (Netherlands Epidemiology of Obesity) study (replication, N=2537). Untargeted 1H nuclear magnetic resonance metabolomics profiling of serum was performed in MESA, and metabolites were replicated in the NEO study using targeted 1H nuclear magnetic resonance spectroscopy. A total of 30 590 metabolomic spectral variables were evaluated. After adjustment for age, sex, race/ethnicity, socioeconomic status, smoking, physical activity, glucose/lipid-lowering medication, and body mass index, 2104 variables representing 24 nonlipid and 49 lipid/lipoprotein subclass metabolites remained significantly associated with VAT ( P=4.88×10-20-1.16×10-3). These included conventional metabolites, amino acids, acetylglycoproteins, intermediates of glucose and hepatic metabolism, organic acids, and subclasses of apolipoproteins, cholesterol, phospholipids, and triglycerides. Metabolites mapped to 31 biochemical pathways, including amino acid substrate use/metabolism and glycolysis/gluconeogenesis. In the replication cohort, acetylglycoproteins, branched-chain amino acids, lactate, glutamine (inversely), and atherogenic lipids remained associated with VAT ( P=1.90×10-35-8.46×10-7), with most associations remaining after additional adjustment for surrogates of VAT (glucose level, waist circumference, and serum triglycerides), reflecting novel independent associations. Conclusions We identified and replicated a metabolite panel associated with VAT in 2 community-based cohorts. These findings persisted after adjustment for body mass index and appear to define a metabolic signature of visceral adiposity.

Relations between lipoprotein(a) concentrations, LPA genetic variants, and the risk of mortality in patients with established coronary heart disease: a molecular and genetic association study.

BACKGROUND: Lipoprotein(a) concentrations in plasma are associated with cardiovascular risk in the general population. Whether lipoprotein(a) concentrations or LPA genetic variants predict long-term mortality in patients with established coronary heart disease remains less clear. METHODS: We obtained data from 3313 patients with established coronary heart disease in the Ludwigshafen Risk and Cardiovascular Health (LURIC) study. We tested associations of tertiles of lipoprotein(a) concentration in plasma and two LPA single-nucleotide polymorphisms ([SNPs] rs10455872 and rs3798220) with all-cause mortality and cardiovascular mortality by Cox regression analysis and with severity of disease by generalised linear modelling, with and without adjustment for age, sex, diabetes diagnosis, systolic blood pressure, BMI, smoking status, estimated glomerular filtration rate, LDL-cholesterol concentration, and use of lipid-lowering therapy. Results for plasma lipoprotein(a) concentrations were validated in five independent studies involving 10 195 patients with established coronary heart disease. Results for genetic associations were replicated through large-scale collaborative analysis in the GENIUS-CHD consortium, comprising 106 353 patients with established coronary heart disease and 19 332 deaths in 22 studies or cohorts. FINDINGS: The median follow-up was 9·9 years. Increased severity of coronary heart disease was associated with lipoprotein(a) concentrations in plasma in the highest tertile (adjusted hazard radio [HR] 1·44, 95% CI 1·14-1·83) and the presence of either LPA SNP (1·88, 1·40-2·53). No associations were found in LURIC with all-cause mortality (highest tertile of lipoprotein(a) concentration in plasma 0·95, 0·81-1·11 and either LPA SNP 1·10, 0·92-1·31) or cardiovascular mortality (0·99, 0·81-1·2 and 1·13, 0·90-1·40, respectively) or in the validation studies. INTERPRETATION: In patients with prevalent coronary heart disease, lipoprotein(a) concentrations and genetic variants showed no associations with mortality. We conclude that these variables are not useful risk factors to measure to predict progression to death after coronary heart disease is established. FUNDING: Seventh Framework Programme for Research and Technical Development (AtheroRemo and RiskyCAD), INTERREG IV Oberrhein Programme, Deutsche Nierenstiftung, Else-Kroener Fresenius Foundation, Deutsche Stiftung für Herzforschung, Deutsche Forschungsgemeinschaft, Saarland University, German Federal Ministry of Education and Research, Willy Robert Pitzer Foundation, and Waldburg-Zeil Clinics Isny.

Thyroid Signaling, Insulin Resistance, and 2 Diabetes Mellitus: A Mendelian Randomization Study.

Context: Increasing evidence suggests an association between thyroid-stimulating hormone (TSH), free thyroxine (fT4), and deiodinases with insulin resistance and type 2 diabetes mellitus (T2D). Objective: We examined whether TSH and fT4 levels and deiodinases are causally associated with insulin resistance and T2D, using Mendelian randomization. Methods: We selected 20 genetic variants for TSH level and four for fT4 level (identified in a genome-wide association study (GWAS) meta-analysis of European-ancestry cohorts) as instrumental variables for TSH and fT4 levels, respectively. We used summary data from GWASs on the outcomes T2D [Diabetes, Genetics Replication and Meta-analysis (DIAGRAM), n = 12,171 cases and n = 56,862 control subjects] and glycemic traits in patients without diabetes [Meta-Analyses of Glucose and Insulin-Related Traits Consortium (MAGIC), n = 46,186 for fasting glucose and insulin and n = 46,368 for hemoglobin A1c]. To examine whether the associations between TSH/fT4 levels and the study outcomes were causal, we combined the effects of the genetic instruments. Furthermore, we examined the associations among 16 variants in DIO1, DIO2, DIO3, and T2D and glycemic traits. Results: We found no evidence for an association between the combined genetic instrumental variables for TSH and fT4 and the study outcomes. For example, we did not observe a genetically determined association between high TSH level and T2D (odds ratio, 0.91 per standard deviation TSH increase; 95% confidence interval, 0.78 to 1.07). Selected genetic variants in DIO1 (e.g., rs7527713) were associated with measures of insulin resistance. Conclusion: We found no evidence for a causal association between circulatory levels of TSH and fT4 with insulin resistance and T2D, but we found suggestive evidence that DIO1 affects glucose metabolism.