Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, we conducted genome-wide association meta-analyses of waist and hip circumference-related traits in up to 224,459 individuals. We identified 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (WHRadjBMI) and an additional 19 loci newly associated with related waist and hip circumference measures (P<5×10−8). Twenty of the 49 WHRadjBMI loci showed significant sexual dimorphism, 19 of which displayed a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation, and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms.

Summary Height is a highly heritable, classic polygenic trait with ∼700 common associated variants identified so far through genome-wide association studies. Here, we report 83 height-associated coding variants with lower minor allele frequencies (range of 0.1-4.8%) and effects of up to 2 cm/allele (e.g. in IHH, STC2, AR and CRISPLD2), >10 times the average effect of common variants. In functional follow-up studies, rare height-increasing alleles of STC2 (+1-2 cm/allele) compromised proteolytic inhibition of PAPP-A and increased cleavage of IGFBP-4 in vitro, resulting in higher bioavailability of insulin-like growth factors. These 83 height-associated variants overlap genes mutated in monogenic growth disorders and highlight new biological candidates (e.g. ADAMTS3, IL11RA, NOX4) and pathways (e.g. proteoglycan/glycosaminoglycan synthesis) involved in growth. Our results demonstrate that sufficiently large sample sizes can uncover rare and low-frequency variants of moderate to large effect associated with polygenic human phenotypes, and that these variants implicate relevant genes and pathways.

Importance The causal direction and magnitude of the association between telomere length and incidence of cancer and non-neoplastic diseases is uncertain owing to the susceptibility of observational studies to confounding and reverse causation. Objective To conduct a Mendelian randomization study, using germline genetic variants as instrumental variables, to appraise the causal relevance of telomere length for risk of cancer and non-neoplastic diseases. Data Sources Genomewide association studies (GWAS) published up to January 15, 2015. Study Selection GWAS of noncommunicable diseases that assayed germline genetic variation and did not select cohort or control participants on the basis of preexisting diseases. Of 163 GWAS of noncommunicable diseases identified, summary data from 103 were available. Data Extraction and Synthesis Summary association statistics for single nucleotide polymorphisms (SNPs) that are strongly associated with telomere length in the general population. Main Outcomes and Measures Odds ratios (ORs) and 95% confidence intervals (CIs) for disease per standard deviation (SD) higher telomere length due to germline genetic variation. Results Summary data were available for 35 cancers and 48 non-neoplastic diseases, corresponding to 420 081 cases (median cases, 2526 per disease) and 1 093 105 controls (median, 6789 per disease). Increased telomere length due to germline genetic variation was generally associated with increased risk for site-specific cancers. The strongest associations (ORs [95% CIs] per 1-SD change in genetically increased telomere length) were observed for glioma, 5.27 (3.15-8.81); serous low-malignant-potential ovarian cancer, 4.35 (2.39-7.94); lung adenocarcinoma, 3.19 (2.40-4.22); neuroblastoma, 2.98 (1.92-4.62); bladder cancer, 2.19 (1.32-3.66); melanoma, 1.87 (1.55-2.26); testicular cancer, 1.76 (1.02-3.04); kidney cancer, 1.55 (1.08-2.23); and endometrial cancer, 1.31 (1.07-1.61). Associations were stronger for rarer cancers and at tissue sites with lower rates of stem cell division. There was generally little evidence of association between genetically increased telomere length and risk of psychiatric, autoimmune, inflammatory, diabetic, and other non-neoplastic diseases, except for coronary heart disease (OR, 0.78 [95% CI, 0.67-0.90]), abdominal aortic aneurysm (OR, 0.63 [95% CI, 0.49-0.81]), celiac disease (OR, 0.42 [95% CI, 0.28-0.61]) and interstitial lung disease (OR, 0.09 [95% CI, 0.05-0.15]). Conclusions and Relevance It is likely that longer telomeres increase risk for several cancers but reduce risk for some non-neoplastic diseases, including cardiovascular diseases.

Across-nation differences in the mean of complex traits such as obesity and stature are common1–8, but the reasons for these differences are not known. Here, we find evidence that many independent loci of small effect combine to create population genetic differences in height and body mass index (BMI) in a sample of 9,416 individuals across 14 European countries. Using discovery data on over 250,000 individuals and unbiased estimates of effect sizes from 17,500 sib pairs, we estimate that 24% (95% CI: 9%, 41%) and 8% (95% CI: 4%, 16%) of the captured additive genetic variance for height and BMI across Europe are attributed to among-population genetic differences. Population genetic divergence differed significantly from that expected under a null model (P <3.94e−08 for height and P<5.95e−04 for BMI), and we find an among-population genetic correlation for tall and slender nations (r = −0.80 (95% CI: −0.95, −0.60), contrasting no genetic correlation between height and BMI within populations (r = −0.016, 95% CI: −0.041, 0.001), consistent with selection on height genes that also act to reduce BMI. Observations of mean height across nations correlated with the predicted genetic means for height (r = 0.51, P<0.001), so that a proportion of observed differences in height within Europe reflect genetic factors. In contrast, observed mean BMI did not correlate with the genetic estimates (P<0.58), implying that genetic differentiation in BMI is masked by environmental differences across Europe.

Genome-wide association studies (GWAS) have identified >250 loci for body mass index (BMI), implicating pathways related to neuronal biology. Most GWAS loci represent clusters of common, non-coding variants from which pinpointing causal genes remains challenging. Here, we combined data from 718,734 individuals to discover rare and low-frequency (MAF<5%) coding variants associated with BMI. We identified 14 coding variants in 13 genes, of which eight in genes (ZBTB7B, ACHE, RAPGEF3, RAB21, ZFHX3, ENTPD6, ZFR2, ZNF169) newly implicated in human obesity, two (MC4R, KSR2) previously observed in extreme obesity, and two variants in GIPR. Effect sizes of rare variants are ~10 times larger than of common variants, with the largest effect observed in carriers of an MC4R stop-codon (p.Tyr35Ter, MAF=0.01%), weighing ~7kg more than non-carriers. Pathway analyses confirmed enrichment of neuronal genes and provide new evidence for adipocyte and energy expenditure biology, widening the potential of genetically-supported therapeutic targets to treat obesity.

Nonalcoholic Fatty Liver Disease (NAFLD) is an obesity-related condition affecting over 50% of individuals in some populations and is expected to become the number one cause of liver disease worldwide by 2020. Common, robustly associated genetic variants in/near five genes were identified for hepatic steatosis, a quantifiable component of NAFLD, in European-ancestry individuals. Here we tested whether these variants were associated with hepatic steatosis in African and/or Hispanic Americans and fine-mapped the observed association signals. We measured hepatic steatosis using computed tomography in five African-American (n=3124) and one Hispanic-American (n=849) cohorts. All analyses controlled for variation in age, age2, gender, alcoholic drinks, and population substructure. Heritability of hepatic steatosis was estimated in three cohorts. Variants in/near PNPLA3, NCAN, LYPLAL1, GCKR, and PPP1R3B were tested for association with hepatic steatosis using a regression framework in each cohort and meta-analyzed. Fine-mapping across African-American cohorts was conducted using meta-analysis. African- and Hispanic-American cohorts were 33.9/37.5% male, with average age of 58.6/42.6 years and body mass index of 31.8/28.9kg/m2, respectively. Hepatic steatosis was 0.20–0.34 heritable in African-and Hispanic-American families (p<0.02 in each cohort). Variants in or near PNPLA3, NCAN, GCKR, PPP1R3B in African Americans and PNPLA3 and PPP1R3B in Hispanic Americans were significantly associated with hepatic steatosis; however, allele frequency and effect size varied across ancestries. Fine-mapping in African Americans highlighted missense variants at PNPLA3 and GCKR and redefined the association region at LYPLAL1. Conclusions We show for the first time that multiple genetic variants are associated with hepatic steatosis across ancestries and explain a substantial proportion of the genetic predisposition in African and Hispanic Americans. Missense variants in PNPLA3 and GCKR are likely functional across multiple ancestries.

Background High body mass index (BMI) is consistently linked to increased risk of colorectal cancer (CRC) for men, whereas the association is less clear for women. As risk estimates from observational studies may be biased and/or confounded, we conducted a Mendelian randomization study to estimate the causal association between BMI and CRC. Methods We used data from 10,226 CRC cases and 10,286 controls of European ancestry. The Mendelian randomization analysis used a weighted genetic risk score, derived from 77 genome-wide association study identified variants associated with higher BMI, as an instrumental variable (IV). We compared the IV odds ratio (IV-OR) with the OR obtained using a conventional covariate-adjusted analysis. Results Individuals carrying greater numbers of BMI-increasing alleles had higher CRC risk (per weighted allele OR, 1.31; 95% confidence interval [CI], 1.10–1.57). Our IV estimation results support the hypothesis that genetically influenced BMI is directly associated with risk for CRC (IV-OR per 5 kg/m2, 1.50; 95% CI, 1.13–2.01). In the sex-specific IV analyses higher BMI was associated with higher risk of CRC among women (IV-OR per 5 kg/m2, 1.82; 95% CI, 1.26–2.61). For men, genetically influenced BMI was not associated with CRC (IV-OR per 5 kg/m2, 1.18; 95% CI, 0.73–1.92). Conclusions High BMI was associated with increased CRC risk for women. Whether abdominal obesity, rather than overall obesity, is a more important risk factor for men requires further investigation. Impact Overall, conventional epidemiologic and Mendelian randomization studies suggest a strong association between obesity and the risk of CRC.

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