Mendelian Randomization studies, which use genetic instrumental variables (IVs) as quasi-experiments to estimate causal effects, report inconsistent findings regarding effects of body mass index (BMI) on mental health. We used genetic IV to estimate effects of BMI on depression and evaluated validity of a commonly used IV. Female Nurse's Health Study participants (n=6989, average age 56.4, [Standard Deviation 6.91] years at first depression assessment) self-reported BMI, which was averaged across eight reports prior to depression assessment (mean=24.96, SD 4.50). Genetic instruments included fat mass and obesity-associated protein (FTO) alleles, melanocortin receptor 4 (MC4R) alleles, and polygenic risk scores based on 32 established polymorphisms for BMI. Depression was assessed using multiple symptom measures, scaled to the Geriatric Depression Scale 15, averaged across up to 7 biennial waves. We used over-identification tests to assess the validity of genetic IVs. In conventional estimates, each additional BMI point predicted 0.024 (95% Confidence Interval (CI): 0.020-0.029) higher average depression scores. Genetic IV estimates were not significant when based on FTO (beta: 0.064, CI: -0.014, 0.142), MC4R (beta: 0.005, CI: -0.146, 0.156), polygenic score excluding FTO (beta=-0.003, 95%-CI -0.051, 0.045), or mechanism-specific scores. The over-identification test comparing IV estimates based on FTO to estimates based on the polygenic score excluding FTO rejected equality of estimated effects (P=0.014). Results provide no evidence against a null effect of BMI on depression and call into question validity of FTO as an instrument for BMI in Mendelian Randomization studies.

Adherence to Mediterranean-DASH Diet Intervention for Neurodegenerative Delay (MIND) may lower the risk of dementia by impacting immunity and cholesterol, which are pathways also implicated by genome-wide association studies of Alzheimer’s Dementia (AD). We examined whether adherence to the MIND diet could modify the association of genetic risk for AD with incident dementia. We used three ongoing US cohorts: Chicago Health and Aging Project (CHAP, n = 2449), Rush Memory and Aging Project (MAP, n = 725), and Women’s Health Initiative Memory Study (WHIMS, n = 5308). Diagnosis of dementia was based on clinical neurological examination and standardized criteria. Repeated measures of global cognitive function were available in MAP and CHAP. Self-reported adherence to MIND was estimated using food-frequency questionnaires. Global and pathway-specific genetic scores (GS) for AD were derived. Cox proportional hazard, logistic regression, and mixed models were used to examine associations of MIND, GS, and GS-MIND interactions with incident dementia and cognitive decline. Higher adherence to MIND and lower GS were associated with a lower risk of dementia in MAP and WHIMS and a slower rate of cognitive decline in MAP (p < 0.05). MIND or GS were not associated with incident dementia or cognitive decline in CHAP. No gene−diet interaction was replicated across cohorts. Genetic risk and MIND adherence are independently associated with dementia among older US men and women.

Plasma fetuin-A is associated with type 2 diabetes, and AHSG, the gene encoding fetuin-A, has been identified as a susceptibility locus for diabetes and metabolic syndrome. Thus far, unbiased investigations of the genetic determinants of plasma fetuin-A concentrations have not been conducted. We searched for single nucleotide polymorphisms (SNPs) related to fetuin-A concentrations by a genome-wide association study in six population-based studies. We examined the association of fetuin-A levels with ∼ 2.5 million genotyped and imputed SNPs in 9,055 participants of European descent and 2,119 African Americans. In both ethnicities, the strongest associations were centered in a region with a high degree of LD near the AHSG locus. Among 136 genome-wide significant (P < 0.05 × 10-8) SNPs near the AHSG locus, the top SNP was rs4917 (P =1.27 × 10-303), a known coding SNP in exon 6 that is associated with a 0.06 g/l (∼13%) lower fetuin-A level. This variant alone explained 14% of the variation in fetuin-A levels. Analyses conditioned on rs4917 indicated that the strong association with the AHSG locus stems from additional independent associations of multiple variants among European Americans. In conclusion, levels of fetuin-A in plasma are strongly associated with SNPs in its encoding gene, AHSG, but not elsewhere in the genome. Given the strength of the associations observed for multiple independent SNPs, the AHSG gene is an example of a candidate locus suitable for additional investigations including fine mapping to elucidate the biological basis of the findings and further functional experiments to clarify AHSG as a potential therapeutic target.

Early menopause (EM) affects up to 10% of the female population, reducing reproductive lifespan considerably. Currently, it constitutes the leading cause of infertility in the western world, affecting mainly those women who postpone their first pregnancy beyond the age of 30 years. The genetic aetiology of EM is largely unknown in the majority of cases. We have undertaken a meta-analysis of genome-wide association studies (GWASs) in 3493 EM cases and 13 598 controls from 10 independent studies. No novel genetic variants were discovered, but the 17 variants previously associated with normal age at natural menopause as a quantitative trait (QT) were also associated with EM and primary ovarian insufficiency (POI). Thus, EM has a genetic aetiology which overlaps variation in normal age at menopause and is at least partly explained by the additive effects of the same polygenic variants. The combined effect of the common variants captured by the single nucleotide polymorphism arrays was estimated to account for ∼30% of the variance in EM. The association between the combined 17 variants and the risk of EM was greater than the best validated non-genetic risk factor, smoking.

Background

Regular fish and omega-3 consumption may have several health benefits and are recommended by major dietary guidelines. Yet, their intakes remain remarkably variable both within and across populations, which could partly owe to genetic influences.

Objective

To identify common genetic variants that influence fish and dietary eicosapentaenoic acid plus docosahexaenoic acid (EPA+DHA) consumption.

Design

We conducted genome-wide association (GWA) meta-analysis of fish (n = 86,467) and EPA+DHA (n = 62,265) consumption in 17 cohorts of European descent from the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium Nutrition Working Group. Results from cohort-specific GWA analyses (additive model) for fish and EPA+DHA consumption were adjusted for age, sex, energy intake, and population stratification, and meta-analyzed separately using fixed-effect meta-analysis with inverse variance weights (METAL software). Additionally, heritability was estimated in 2 cohorts.

Results

Heritability estimates for fish and EPA+DHA consumption ranged from 0.13-0.24 and 0.12-0.22, respectively. A significant GWA for fish intake was observed for rs9502823 on chromosome 6: each copy of the minor allele (FreqA = 0.015) was associated with 0.029 servings/day (~1 serving/month) lower fish consumption (P = 1.96x10-8). No significant association was observed for EPA+DHA, although rs7206790 in the obesity-associated FTO gene was among top hits (P = 8.18x10-7). Post-hoc calculations demonstrated 95% statistical power to detect a genetic variant associated with effect size of 0.05% for fish and 0.08% for EPA+DHA.

Conclusions

These novel findings suggest that non-genetic personal and environmental factors are principal determinants of the remarkable variation in fish consumption, representing modifiable targets for increasing intakes among all individuals. Genes underlying the signal at rs72838923 and mechanisms for the association warrant further investigation.

Background

Coffee consumption has been shown to be associated with various health outcomes in observational studies. However, evidence for its association with epithelial ovarian cancer (EOC) is inconsistent and it is unclear whether these associations are causal.

Methods

We used single nucleotide polymorphisms associated with (i) coffee and (ii) caffeine consumption to perform Mendelian randomization (MR) on EOC risk. We conducted a two-sample MR using genetic data on 44 062 individuals of European ancestry from the Ovarian Cancer Association Consortium (OCAC), and combined instrumental variable estimates using a Wald-type ratio estimator.

Results

For all EOC cases, the causal odds ratio (COR) for genetically predicted consumption of one additional cup of coffee per day was 0.92 [95% confidence interval (CI): 0.79, 1.06]. The COR was 0.90 (95% CI: 0.73, 1.10) for high-grade serous EOC. The COR for genetically predicted consumption of an additional 80 mg caffeine was 1.01 (95% CI: 0.92, 1.11) for all EOC cases and 0.90 (95% CI: 0.73, 1.10) for high-grade serous cases.

Conclusions

We found no evidence indicative of a strong association between EOC risk and genetically predicted coffee or caffeine levels. However, our estimates were not statistically inconsistent with earlier observational studies and we were unable to rule out small protective associations.

Background

Depression is a heritable trait that exists on a continuum of varying severity and duration. Yet, the search for genetic variants associated with depression has had few successes. We exploit the entire continuum of depression to find common variants for depressive symptoms.

Methods

In this genome-wide association study, we combined the results of 17 population-based studies assessing depressive symptoms with the Center for Epidemiological Studies Depression Scale. Replication of the independent top hits (p<1×10(-5)) was performed in five studies assessing depressive symptoms with other instruments. In addition, we performed a combined meta-analysis of all 22 discovery and replication studies.

Results

The discovery sample comprised 34,549 individuals (mean age of 66.5) and no loci reached genome-wide significance (lowest p = 1.05×10(-7)). Seven independent single nucleotide polymorphisms were considered for replication. In the replication set (n = 16,709), we found suggestive association of one single nucleotide polymorphism with depressive symptoms (rs161645, 5q21, p = 9.19×10(-3)). This 5q21 region reached genome-wide significance (p = 4.78×10(-8)) in the overall meta-analysis combining discovery and replication studies (n = 51,258).

Conclusions

The results suggest that only a large sample comprising more than 50,000 subjects may be sufficiently powered to detect genes for depressive symptoms.

Background

Depression is a heritable trait that exists on a continuum of varying severity and duration. Yet, the search for genetic variants associated with depression has had few successes. We exploit the entire continuum of depression to find common variants for depressive symptoms.

Methods

In this genome-wide association study, we combined the results of 17 population-based studies assessing depressive symptoms with the Center for Epidemiological Studies Depression Scale. Replication of the independent top hits (p<1×10(-5)) was performed in five studies assessing depressive symptoms with other instruments. In addition, we performed a combined meta-analysis of all 22 discovery and replication studies.

Results

The discovery sample comprised 34,549 individuals (mean age of 66.5) and no loci reached genome-wide significance (lowest p = 1.05×10(-7)). Seven independent single nucleotide polymorphisms were considered for replication. In the replication set (n = 16,709), we found suggestive association of one single nucleotide polymorphism with depressive symptoms (rs161645, 5q21, p = 9.19×10(-3)). This 5q21 region reached genome-wide significance (p = 4.78×10(-8)) in the overall meta-analysis combining discovery and replication studies (n = 51,258).

Conclusions

The results suggest that only a large sample comprising more than 50,000 subjects may be sufficiently powered to detect genes for depressive symptoms.

Tobacco and alcohol use are leading causes of mortality that influence risk for many complex diseases and disorders¹. They are heritable^2,3 and etiologically related^4,5 behaviors that have been resistant to gene discovery efforts^6-11. In sample sizes up to 1.2 million individuals, we discovered 566 genetic variants in 406 loci associated with multiple stages of tobacco use (initiation, cessation, and heaviness) as well as alcohol use, with 150 loci evidencing pleiotropic association. Smoking phenotypes were positively genetically correlated with many health conditions, whereas alcohol use was negatively correlated with these conditions, such that increased genetic risk for alcohol use is associated with lower disease risk. We report evidence for the involvement of many systems in tobacco and alcohol use, including genes involved in nicotinic, dopaminergic, and glutamatergic neurotransmission. The results provide a solid starting point to evaluate the effects of these loci in model organisms and more precise substance use measures.

To characterize type 2 diabetes (T2D)-associated variation across the allele frequency spectrum, we conducted a meta-analysis of genome-wide association data from 26,676 T2D case and 132,532 control subjects of European ancestry after imputation using the 1000 Genomes multiethnic reference panel. Promising association signals were followed up in additional data sets (of 14,545 or 7,397 T2D case and 38,994 or 71,604 control subjects). We identified 13 novel T2D-associated loci (P < 5 × 10^-8), including variants near the GLP2R, GIP, and HLA-DQA1 genes. Our analysis brought the total number of independent T2D associations to 128 distinct signals at 113 loci. Despite substantially increased sample size and more complete coverage of low-frequency variation, all novel associations were driven by common single nucleotide variants. Credible sets of potentially causal variants were generally larger than those based on imputation with earlier reference panels, consistent with resolution of causal signals to common risk haplotypes. Stratification of T2D-associated loci based on T2D-related quantitative trait associations revealed tissue-specific enrichment of regulatory annotations in pancreatic islet enhancers for loci influencing insulin secretion and in adipocytes, monocytes, and hepatocytes for insulin action-associated loci. These findings highlight the predominant role played by common variants of modest effect and the diversity of biological mechanisms influencing T2D pathophysiology.