Germline Genetic Variants Associated with Somatic TMPRSS2:ERG Fusion Status in Prostate Cancer: A Genome-Wide Association Study.

BACKGROUND: The prostate cancer subtype defined by the presence of TMPRSS2:ERG has been shown to be molecularly and epidemiologically distinct. However, few studies have investigated germline genetic variants associating with TMPRSS2:ERG fusion status. METHODS: We performed a genome-wide association study with 396 TMPRSS2:ERG(+) cases, 390 TMPRSS2:ERG(-) cases, and 2,386 cancer-free controls from the Physicians' Health Study (PHS), the Health Professionals Follow-up Study (HPFS), and a Seattle-based Fred Hutchinson (FH) Cancer Center Prostate Cancer Study. We applied logistic regression models to test the associations between ∼5 million SNPs with TMPRSS2:ERG fusion status accounting for population stratification. RESULTS: We did not identify genome-wide significant variants comparing the TMPRSS2:ERG(+) to the TMPRSS2:ERG(-) prostate cancer cases in the meta-analysis. When comparing TMPRSS2:ERG(+) prostate cancer cases with controls without prostate cancer, 10 genome-wide significant SNPs on chromosome 17q24.3 were observed in the meta-analysis. When comparing TMPRSS2:ERG(-) prostate cancer cases with controls without prostate cancer, two SNPs on chromosome 8q24.21 in the meta-analysis reached genome-wide significance. CONCLUSIONS: We observed SNPs at several known prostate cancer risk loci (17q24.3, 1q32.1, and 8q24.21) that were differentially and exclusively associated with the risk of developing prostate tumors either with or without the gene fusion. IMPACT: Our findings suggest that tumors with the TMPRSS2:ERG fusion exhibit a different germline genetic etiology compared with fusion negative cases.

Trans-ethnic polygenic risk scores for body mass index: An international hundred K+ cohorts consortium study.

BACKGROUND: While polygenic risk scores hold significant promise in estimating an individual's risk of developing a complex trait such as obesity, their application in the clinic has, to date, been limited by a lack of data from non-European populations. As a collaboration model of the International Hundred K+ Cohorts Consortium (IHCC), we endeavored to develop a globally applicable trans-ethnic PRS for body mass index (BMI) through this relatively new international effort. METHODS: The polygenic risk score (PRS) model was developed, trained and tested at the Center for Applied Genomics (CAG) of The Children's Hospital of Philadelphia (CHOP) based on a BMI meta-analysis from the GIANT consortium. The validated PRS models were subsequently disseminated to the participating sites. Scores were generated by each site locally on their cohorts and summary statistics returned to CAG for final analysis. RESULTS: We show that in the absence of a well powered trans-ethnic GWAS from which to derive marker SNPs and effect estimates for PRS, trans-ethnic scores can be generated from European ancestry GWAS using Bayesian approaches such as LDpred, by adjusting the summary statistics using trans-ethnic linkage disequilibrium reference panels. The ported trans-ethnic scores outperform population specific-PRS across all non-European ancestry populations investigated including East Asians and three-way admixed Brazilian cohort. CONCLUSIONS: Here we show that for a truly polygenic trait such as BMI adjusting the summary statistics of a well powered European ancestry study using trans-ethnic LD reference results in a score that is predictive across a range of ancestries including East Asians and three-way admixed Brazilians.

Genome-wide analyses characterize shared heritability among cancers and identify novel cancer susceptibility regions.

BACKGROUND: The shared inherited genetic contribution to risk of different cancers is not fully known. In this study, we leverage results from 12 cancer genome-wide association studies (GWAS) to quantify pairwise genome-wide genetic correlations across cancers and identify novel cancer susceptibility loci. METHODS: We collected GWAS summary statistics for 12 solid cancers based on 376 759 participants with cancer and 532 864 participants without cancer of European ancestry. The included cancer types were breast, colorectal, endometrial, esophageal, glioma, head and neck, lung, melanoma, ovarian, pancreatic, prostate, and renal cancers. We conducted cross-cancer GWAS and transcriptome-wide association studies to discover novel cancer susceptibility loci. Finally, we assessed the extent of variant-specific pleiotropy among cancers at known and newly identified cancer susceptibility loci. RESULTS: We observed widespread but modest genome-wide genetic correlations across cancers. In cross-cancer GWAS and transcriptome-wide association studies, we identified 15 novel cancer susceptibility loci. Additionally, we identified multiple variants at 77 distinct loci with strong evidence of being associated with at least 2 cancer types by testing for pleiotropy at known cancer susceptibility loci. CONCLUSIONS: Overall, these results suggest that some genetic risk variants are shared among cancers, though much of cancer heritability is cancer-specific and thus tissue-specific. The increase in statistical power associated with larger sample sizes in cross-disease analysis allows for the identification of novel susceptibility regions. Future studies incorporating data on multiple cancer types are likely to identify additional regions associated with the risk of multiple cancer types.

The genetic basis of endometriosis and comorbidity with other pain and inflammatory conditions.

Endometriosis is a common condition associated with debilitating pelvic pain and infertility. A genome-wide association study meta-analysis, including 60,674 cases and 701,926 controls of European and East Asian descent, identified 42 genome-wide significant loci comprising 49 distinct association signals. Effect sizes were largest for stage 3/4 disease, driven by ovarian endometriosis. Identified signals explained up to 5.01% of disease variance and regulated expression or methylation of genes in endometrium and blood, many of which were associated with pain perception/maintenance (SRP14/BMF, GDAP1, MLLT10, BSN and NGF). We observed significant genetic correlations between endometriosis and 11 pain conditions, including migraine, back and multisite chronic pain (MCP), as well as inflammatory conditions, including asthma and osteoarthritis. Multitrait genetic analyses identified substantial sharing of variants associated with endometriosis and MCP/migraine. Targeted investigations of genetically regulated mechanisms shared between endometriosis and other pain conditions are needed to aid the development of new treatments and facilitate early symptomatic intervention.

Trans-ethnic Polygenic Risk Scores for Body Mass Index: An International Hundred K+ Cohorts Consortium Study.

Background: While polygenic risk scores hold significant promise in estimating an individual's risk of developing a complex trait such as obesity, their application in the clinic has, to date, been limited by a lack of data from non-European populations. As a collaboration model of the International Hundred K+ Cohorts Consortium (IHCC), we endeavored to develop a globally applicable trans-ethnic PRS for body mass index (BMI) through this relatively new international effort. Methods: The PRS model was developed trained and tested at the Center for Applied Genomics (CAG) of The Children's Hospital of Philadelphia (CHOP) based on a BMI meta-analysis from the GIANT consortium. The validated PRS models were subsequently disseminated to the participating sites. Scores were generated by each site locally on their cohorts and summary statistics returned to CAG for final analysis. Results: We show that in the absence of a well powered trans-ethnic GWAS from which to derive SNPs and effect estimates, trans-ethnic scores can be generated from European ancestry GWAS using Bayesian approaches such as LDpred to adjust the summary statistics using trans-ethnic linkage disequilibrium reference panels. The ported trans-ethnic scores outperform population specific-PRS across all non-European ancestry populations investigated including East Asians and three-way admixed Brazilian cohort. Conclusions: Widespread use of PRS in the clinic is hampered by a lack of genotyping data in individuals of non-European ancestry for the vast majority of traits. Here we show that for a truly polygenic trait such as BMI adjusting the summary statistics of a well powered European ancestry study using trans-ethnic LD reference results in a score that is predictive across a range of ancestries including East Asians and three-way admixed Brazilians.

A genome-wide association study of mammographic texture variation.

BACKGROUND: Breast parenchymal texture features, including grayscale variation (V), capture the patterns of texture variation on a mammogram and are associated with breast cancer risk, independent of mammographic density (MD). However, our knowledge on the genetic basis of these texture features is limited. METHODS: We conducted a genome-wide association study of V in 7040 European-ancestry women. V assessments were generated from digitized film mammograms. We used linear regression to test the single-nucleotide polymorphism (SNP)-phenotype associations adjusting for age, body mass index (BMI), MD phenotypes, and the top four genetic principal components. We further calculated genetic correlations and performed SNP-set tests of V with MD, breast cancer risk, and other breast cancer risk factors. RESULTS: We identified three genome-wide significant loci associated with V: rs138141444 (6q24.1) in ECT2L, rs79670367 (8q24.22) in LINC01591, and rs113174754 (12q22) near PGAM1P5. 6q24.1 and 8q24.22 have not previously been associated with MD phenotypes or breast cancer risk, while 12q22 is a known locus for both MD and breast cancer risk. Among known MD and breast cancer risk SNPs, we identified four variants that were associated with V at the Bonferroni-corrected thresholds accounting for the number of SNPs tested: rs335189 (5q23.2) in PRDM6, rs13256025 (8p21.2) in EBF2, rs11836164 (12p12.1) near SSPN, and rs17817449 (16q12.2) in FTO. We observed significant genetic correlations between V and mammographic dense area (rg = 0.79, P = 5.91 × 10-5), percent density (rg = 0.73, P = 1.00 × 10-4), and adult BMI (rg = - 0.36, P = 3.88 × 10-7). Additional significant relationships were observed for non-dense area (z = - 4.14, P = 3.42 × 10-5), estrogen receptor-positive breast cancer (z = 3.41, P = 6.41 × 10-4), and childhood body fatness (z = - 4.91, P = 9.05 × 10-7) from the SNP-set tests. CONCLUSIONS: These findings provide new insights into the genetic basis of mammographic texture variation and their associations with MD, breast cancer risk, and other breast cancer risk factors.

Cross-Ancestry Investigation of Venous Thromboembolism Genomic Predictors.

BACKGROUND: Venous thromboembolism (VTE) is a life-threatening vascular event with environmental and genetic determinants. Recent VTE genome-wide association studies (GWAS) meta-analyses involved nearly 30 000 VTE cases and identified up to 40 genetic loci associated with VTE risk, including loci not previously suspected to play a role in hemostasis. The aim of our research was to expand discovery of new genetic loci associated with VTE by using cross-ancestry genomic resources. METHODS: We present new cross-ancestry meta-analyzed GWAS results involving up to 81 669 VTE cases from 30 studies, with replication of novel loci in independent populations and loci characterization through in silico genomic interrogations. RESULTS: In our genetic discovery effort that included 55 330 participants with VTE (47 822 European, 6320 African, and 1188 Hispanic ancestry), we identified 48 novel associations, of which 34 were replicated after correction for multiple testing. In our combined discovery-replication analysis (81 669 VTE participants) and ancestry-stratified meta-analyses (European, African, and Hispanic), we identified another 44 novel associations, which are new candidate VTE-associated loci requiring replication. In total, across all GWAS meta-analyses, we identified 135 independent genomic loci significantly associated with VTE risk. A genetic risk score of the significantly associated loci in Europeans identified a 6-fold increase in risk for those in the top 1% of scores compared with those with average scores. We also identified 31 novel transcript associations in transcriptome-wide association studies and 8 novel candidate genes with protein quantitative-trait locus Mendelian randomization analyses. In silico interrogations of hemostasis and hematology traits and a large phenome-wide association analysis of the 135 GWAS loci provided insights to biological pathways contributing to VTE, with some loci contributing to VTE through well-characterized coagulation pathways and others providing new data on the role of hematology traits, particularly platelet function. Many of the replicated loci are outside of known or currently hypothesized pathways to thrombosis. CONCLUSIONS: Our cross-ancestry GWAS meta-analyses identified new loci associated with VTE. These findings highlight new pathways to thrombosis and provide novel molecules that may be useful in the development of improved antithrombosis treatments.

Obesity, Adiposity, and Risk of Symptomatic Gallstone Disease According to Genetic Susceptibility.

BACKGROUND & AIMS: Adiposity has been consistently associated with gallstone disease risk. We aimed to characterize associations of anthropometric measures (body mass index [BMI], recent weight change, long-term weight change, waist circumference, and waist-to-hip ratio) with symptomatic gallstone disease according to strata of gallstone disease polygenic risk score (PRS). METHODS: We conducted analysis among 34,626 participants with available genome-wide genetic data within 3 large, prospective, U.S. cohorts-the Nurses' Health Study (NHS), Health Professionals Follow-Up Study, and NHS II. We characterized joint associations of PRS and anthropometric measures and tested for interactions on the relative and absolute risk scales. RESULTS: Women in the highest BMI and PRS categories (BMI ≥30 kg/m2 and PRS ≥1 SD above mean) had odds ratio for gallstone disease of 5.55 (95% confidence interval, 5.29 to 5.81) compared with those in the lowest BMI and PRS categories (BMI <25 kg/m2 and PRS <1 SD below the mean). The corresponding odds ratio among men was 1.65 (95% confidence interval, 1.02 to 2.29). Associations for BMI did not vary within strata of PRS on the relative risk scale. On the absolute risk scale, the incidence rate difference between obese and normal-weight individuals was 1086 per 100,000 person-years within the highest PRS category, compared with 666 per 100,000 person-years in the lowest PRS category, with strong evidence for interaction with the ABCG8 locus. CONCLUSIONS: While maintenance of a healthy body weight reduces gallstone disease risk among all individuals, risk reduction is higher among the subset with greater genetic susceptibility to gallstone disease.

Large-scale cross-cancer fine-mapping of the 5p15.33 region reveals multiple independent signals.

Genome-wide association studies (GWASs) have identified thousands of cancer risk loci revealing many risk regions shared across multiple cancers. Characterizing the cross-cancer shared genetic basis can increase our understanding of global mechanisms of cancer development. In this study, we collected GWAS summary statistics based on up to 375,468 cancer cases and 530,521 controls for fourteen types of cancer, including breast (overall, estrogen receptor [ER]-positive, and ER-negative), colorectal, endometrial, esophageal, glioma, head/neck, lung, melanoma, ovarian, pancreatic, prostate, and renal cancer, to characterize the shared genetic basis of cancer risk. We identified thirteen pairs of cancers with statistically significant local genetic correlations across eight distinct genomic regions. Specifically, the 5p15.33 region, harboring the TERT and CLPTM1L genes, showed statistically significant local genetic correlations for multiple cancer pairs. We conducted a cross-cancer fine-mapping of the 5p15.33 region based on eight cancers that showed genome-wide significant associations in this region (ER-negative breast, colorectal, glioma, lung, melanoma, ovarian, pancreatic, and prostate cancer). We used an iterative analysis pipeline implementing a subset-based meta-analysis approach based on cancer-specific conditional analyses and identified ten independent cross-cancer associations within this region. For each signal, we conducted cross-cancer fine-mapping to prioritize the most plausible causal variants. Our findings provide a more in-depth understanding of the shared inherited basis across human cancers and expand our knowledge of the 5p15.33 region in carcinogenesis.

A Genome-Wide Association Study of Childhood Body Fatness.

OBJECTIVE: This study aimed to uncover genetic contributors to adiposity in early life. METHODS: A genome-wide association study of childhood body fatness in 34,401 individuals within the Nurses' Health Studies and the Health Professionals Follow-up Study was conducted. Data were imputed to the 1000 Genomes Phase 3 version 5 reference panel. RESULTS: A total of 1,354 single-nucleotide polymorphisms (P < 10-4 ) were selected for replication in a previously published genome-wide association study of childhood BMI. Nineteen significant genome-wide (P < 5 × 10-8 ) regions were observed, fourteen of which were previously associated with childhood obesity and five were novel: BNDF (P = 7.58 × 10-13 ), PRKD1 (P = 1.43 × 10-10 ), 20p13 (P = 2.05 × 10-10 ), FHIT (P = 1.77 × 10-8 ), and LOC101927575 (P = 3.22 × 10-8 ). The BNDF, FHIT, and PRKD1 regions were previously associated with adult BMI. LOC101927575 and 20p13 regions have not previously been associated with adiposity phenotypes. In a transcriptome-wide analysis, associations for POMC at 2p23.3 (P = 3.36 × 10-6 ) and with TMEM18 at 2p25.3 (P = 3.53 × 10-7 ) were observed. Childhood body fatness was genetically correlated with hip (rg = 0.42, P = 4.44 × 10-16 ) and waist circumference (rg = 0.39, P = 5.56 × 10-16 ), as well as age at menarche (rg = -0.37, P = 7.96 × 10-19 ). CONCLUSIONS: Additional loci that contribute to childhood adiposity were identified, further explicating its genetic architecture.

The Mediterranean diet, plasma metabolome, and cardiovascular disease risk.

AIMS: To investigate whether metabolic signature composed of multiple plasma metabolites can be used to characterize adherence and metabolic response to the Mediterranean diet and whether such a metabolic signature is associated with cardiovascular disease (CVD) risk. METHODS AND RESULTS: Our primary study cohort included 1859 participants from the Spanish PREDIMED trial, and validation cohorts included 6868 participants from the US Nurses' Health Studies I and II, and Health Professionals Follow-up Study (NHS/HPFS). Adherence to the Mediterranean diet was assessed using a validated Mediterranean Diet Adherence Screener (MEDAS), and plasma metabolome was profiled by liquid chromatography-tandem mass spectrometry. We observed substantial metabolomic variation with respect to Mediterranean diet adherence, with nearly one-third of the assayed metabolites significantly associated with MEDAS (false discovery rate < 0.05). Using elastic net regularized regressions, we identified a metabolic signature, comprised of 67 metabolites, robustly correlated with Mediterranean diet adherence in both PREDIMED and NHS/HPFS (r = 0.28-0.37 between the signature and MEDAS; P = 3 × 10-35 to 4 × 10-118). In multivariable Cox regressions, the metabolic signature showed a significant inverse association with CVD incidence after adjusting for known risk factors (PREDIMED: hazard ratio [HR] per standard deviation increment in the signature = 0.71, P < 0.001; NHS/HPFS: HR = 0.85, P = 0.001), and the association persisted after further adjustment for MEDAS scores (PREDIMED: HR = 0.73, P = 0.004; NHS/HPFS: HR = 0.85, P = 0.004). Further genome-wide association analysis revealed that the metabolic signature was significantly associated with genetic loci involved in fatty acids and amino acids metabolism. Mendelian randomization analyses showed that the genetically inferred metabolic signature was significantly associated with risk of coronary heart disease (CHD) and stroke (odds ratios per SD increment in the genetically inferred metabolic signature = 0.92 for CHD and 0.91 for stroke; P < 0.001). CONCLUSIONS: We identified a metabolic signature that robustly reflects adherence and metabolic response to a Mediterranean diet, and predicts future CVD risk independent of traditional risk factors, in Spanish and US cohorts.

Fine-mapping of 150 breast cancer risk regions identifies 191 likely target genes.

Genome-wide association studies have identified breast cancer risk variants in over 150 genomic regions, but the mechanisms underlying risk remain largely unknown. These regions were explored by combining association analysis with in silico genomic feature annotations. We defined 205 independent risk-associated signals with the set of credible causal variants in each one. In parallel, we used a Bayesian approach (PAINTOR) that combines genetic association, linkage disequilibrium and enriched genomic features to determine variants with high posterior probabilities of being causal. Potentially causal variants were significantly over-represented in active gene regulatory regions and transcription factor binding sites. We applied our INQUSIT pipeline for prioritizing genes as targets of those potentially causal variants, using gene expression (expression quantitative trait loci), chromatin interaction and functional annotations. Known cancer drivers, transcription factors and genes in the developmental, apoptosis, immune system and DNA integrity checkpoint gene ontology pathways were over-represented among the highest-confidence target genes.

Colorectal cancer susceptibility variants and risk of conventional adenomas and serrated polyps: results from three cohort studies.

BACKGROUND: Increasing evidence suggests that conventional adenomas (CAs) and serrated polyps (SPs) represent two distinct groups of precursor lesions for colorectal cancer (CRC). The influence of common genetic variants on risk of CAs and SPs remain largely unknown. METHODS: Among 27 426 participants within three prospective cohort studies, we created a weighted genetic risk score (GRS) based on 40 CRC-related single nucleotide polymorphisms (SNPs) identified in previous genome-wide association studies; and we examined the association of GRS (per one standard deviation increment) with risk of CAs, SPs and synchronous CAs and SPs, by multivariable logistic regression. We also analysed individual variants in the secondary analysis. RESULTS: During 18-20 years of follow-up, we documented 2952 CAs, 1585 SPs and 794 synchronous CAs and SPs. Higher GRS was associated with increased risk of CAs [odds ratio (OR) = 1.17, 95% confidence interval (CI): 1.12-1.21] and SPs (OR = 1.09, 95% CI: 1.03-1.14), with a stronger association for CAs than SPs (Pheterogeneity=0.01). An even stronger association was found for patients with synchronous CAs and SPs (OR = 1.32), advanced CAs (OR = 1.22) and multiple CAs (OR = 1.25). Different sets of variants were associated with CAs and SPs, with a Spearman correlation coefficient of 0.02 between the ORs associating the 40 SNPs with the two lesions. After correcting for multiple testing, three variants were associated with CAs (rs3802842, rs6983267 and rs7136702) and two with SPs (rs16892766 and rs4779584). CONCLUSIONS: Common genetic variants play a potential role in the conventional and serrated pathways of CRC. Different sets of variants are identified for the two pathways, further supporting the aetiological heterogeneity of CRC.

Genome-Wide Association Study for Urinary and Fecal Incontinence in Women.

PURPOSE: Urinary incontinence and fecal incontinence are common disorders in women that negatively impact quality of life. In addition to known health and lifestyle risk factors, genetics may have a role in continence. Identification of genetic variants associated with urinary incontinence and fecal incontinence could result in a better understanding of etiologic pathways, and new interventions and treatments. MATERIALS AND METHODS: We previously generated genome-wide single nucleotide polymorphism data from Nurses' Health Studies participants. The participants provided longitudinal urinary incontinence and fecal incontinence information via questionnaires. Cases of urinary incontinence (6,120) had at least weekly urinary incontinence reported on a majority of questionnaires (3 or 4 across 12 to 16 years) while controls (4,811) consistently had little to no urinary incontinence reported. We classified cases of urinary incontinence in women into stress (1,809), urgency (1,942) and mixed (2,036) subtypes. Cases of fecal incontinence (4,247) had at least monthly fecal incontinence reported on a majority of questionnaires while controls (11,634) consistently had no fecal incontinence reported. We performed a genome-wide association study for each incontinence outcome. RESULTS: We identified 8 single nucleotide polymorphisms significantly associated (p <5×10-8) with urinary incontinence located in 2 loci, chromosomes 8q23.3 and 1p32.2. There were no genome-wide significant findings for the urinary incontinence subtype analyses. However, the significant associations for overall urinary incontinence were stronger for the urgency and mixed subtypes than for stress. While no single nucleotide polymorphism reached genome-wide significance for fecal incontinence, 4 single nucleotide polymorphisms had p <10-6. CONCLUSIONS: Few studies have collected genetic data and detailed urinary incontinence and fecal incontinence information. This genome-wide association study provides initial evidence of genetic associations for urinary incontinence and merits further research to replicate our findings and identify additional risk variants.

Genomic and transcriptomic association studies identify 16 novel susceptibility loci for venous thromboembolism.

Venous thromboembolism (VTE) is a significant contributor to morbidity and mortality. To advance our understanding of the biology contributing to VTE, we conducted a genome-wide association study (GWAS) of VTE and a transcriptome-wide association study (TWAS) based on imputed gene expression from whole blood and liver. We meta-analyzed GWAS data from 18 studies for 30 234 VTE cases and 172 122 controls and assessed the association between 12 923 718 genetic variants and VTE. We generated variant prediction scores of gene expression from whole blood and liver tissue and assessed them for association with VTE. Mendelian randomization analyses were conducted for traits genetically associated with novel VTE loci. We identified 34 independent genetic signals for VTE risk from GWAS meta-analysis, of which 14 are newly reported associations. This included 11 newly associated genetic loci (C1orf198, PLEK, OSMR-AS1, NUGGC/SCARA5, GRK5, MPHOSPH9, ARID4A, PLCG2, SMG6, EIF5A, and STX10) of which 6 replicated, and 3 new independent signals in 3 known genes. Further, TWAS identified 5 additional genetic loci with imputed gene expression levels differing between cases and controls in whole blood (SH2B3, SPSB1, RP11-747H7.3, RP4-737E23.2) and in liver (ERAP1). At some GWAS loci, we found suggestive evidence that the VTE association signal for novel and previously known regions colocalized with expression quantitative trait locus signals. Mendelian randomization analyses suggested that blood traits may contribute to the underlying risk of VTE. To conclude, we identified 16 novel susceptibility loci for VTE; for some loci, the association signals are likely mediated through gene expression of nearby genes.

Efficient cross-trait penalized regression increases prediction accuracy in large cohorts using secondary phenotypes.

We introduce cross-trait penalized regression (CTPR), a powerful and practical approach for multi-trait polygenic risk prediction in large cohorts. Specifically, we propose a novel cross-trait penalty function with the Lasso and the minimax concave penalty (MCP) to incorporate the shared genetic effects across multiple traits for large-sample GWAS data. Our approach extracts information from the secondary traits that is beneficial for predicting the primary trait based on individual-level genotypes and/or summary statistics. Our novel implementation of a parallel computing algorithm makes it feasible to apply our method to biobank-scale GWAS data. We illustrate our method using large-scale GWAS data (~1M SNPs) from the UK Biobank (N = 456,837). We show that our multi-trait method outperforms the recently proposed multi-trait analysis of GWAS (MTAG) for predictive performance. The prediction accuracy for height by the aid of BMI improves from R2 = 35.8% (MTAG) to 42.5% (MCP + CTPR) or 42.8% (Lasso + CTPR) with UK Biobank data.

Association studies of up to 1.2 million individuals yield new insights into the genetic etiology of tobacco and alcohol use.

Tobacco and alcohol use are leading causes of mortality that influence risk for many complex diseases and disorders1. They are heritable2,3 and etiologically related4,5 behaviors that have been resistant to gene discovery efforts6-11. 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.

A large-scale exome array analysis of venous thromboembolism.

Although recent Genome-Wide Association Studies have identified novel associations for common variants, there has been no comprehensive exome-wide search for low-frequency variants that affect the risk of venous thromboembolism (VTE). We conducted a meta-analysis of 11 studies comprising 8,332 cases and 16,087 controls of European ancestry and 382 cases and 1,476 controls of African American ancestry genotyped with the Illumina HumanExome BeadChip. We used the seqMeta package in R to conduct single variant and gene-based rare variant tests. In the single variant analysis, we limited our analysis to the 64,794 variants with at least 40 minor alleles across studies (minor allele frequency [MAF] ~0.08%). We confirmed associations with previously identified VTE loci, including ABO, F5, F11, and FGA. After adjusting for multiple testing, we observed no novel significant findings in single variant or gene-based analysis. Given our sample size, we had greater than 80% power to detect minimum odds ratios greater than 1.5 and 1.8 for a single variant with MAF of 0.01 and 0.005, respectively. Larger studies and sequence data may be needed to identify novel low-frequency and rare variants associated with VTE risk.

Body mass index and breast cancer survival: a Mendelian randomization analysis.

Background: There is increasing evidence that elevated body mass index (BMI) is associated with reduced survival for women with breast cancer. However, the underlying reasons remain unclear. We conducted a Mendelian randomization analysis to investigate a possible causal role of BMI in survival from breast cancer. Methods: We used individual-level data from six large breast cancer case-cohorts including a total of 36 210 individuals (2475 events) of European ancestry. We created a BMI genetic risk score (GRS) based on genotypes at 94 known BMI-associated genetic variants. Association between the BMI genetic score and breast cancer survival was analysed by Cox regression for each study separately. Study-specific hazard ratios were pooled using fixed-effect meta-analysis. Results: BMI genetic score was found to be associated with reduced breast cancer-specific survival for estrogen receptor (ER)-positive cases [hazard ratio (HR) = 1.11, per one-unit increment of GRS, 95% confidence interval (CI) 1.01-1.22, P = 0.03). We observed no association for ER-negative cases (HR = 1.00, per one-unit increment of GRS, 95% CI 0.89-1.13, P = 0.95). Conclusions: Our findings suggest a causal effect of increased BMI on reduced breast cancer survival for ER-positive breast cancer. There is no evidence of a causal effect of higher BMI on survival for ER-negative breast cancer cases.