Mendelian randomization study of whole blood viscosity and cardiovascular diseases

AIMS

Association between whole blood viscosity (WBV) and an increased risk of cardiovascular disease (CVD) has been reported. However, the causal relationship between WBV and CVD remains not thoroughly investigated. The aim of this study was to investigate the causal relation between WBV and CVD.

METHODS

Two-sample Mendelian randomization (MR) was employed, with inverse variance weighting (IVW) as the primary method, to investigate the casual relationship between WBV and CVD. The calculated WBV and medical records of 378,210 individuals participating in the UK Biobank study were divided into halves and analyzed.

RESULTS

The means of calculated WBVs were 16.9 (standard deviation: 0.8) and 55.1 (standard deviation: 17.2) for high shear rate (HSR) and low shear rate (LSR), respectively. 37,859 (10.0%) major cardiovascular events (MACE) consisted of 23,894 (6.3%) cases of myocardial infarction (MI), 9,245 (2.4%) cases of ischemic stroke, 10,377 (2.7%) cases of revascularization, and 5,703 (1.5%) cases of coronary heart disease-related death. In the MR analysis, no evidence was found indicating a causal effect of WBV on MACE (IVW p-value for HSR = 0.81, IVW p-value for LSR = 0.47), MI (0.92, 0.83), ischemic stroke (0.52, 0.74), revascularization (0.71, 0.54), and coronary heart disease-related death (0.83, 0.70). The lack of sufficient evidence for causality persisted in other MR methods, including weighted median and MR-egger.

CONCLUSIONS

The Mendelian randomization analysis conducted in this study does not support a causal relationship between calculated WBV and CVD.

A compendium of genetic regulatory effects across pig tissues

The Farm Animal Genotype-Tissue Expression (FarmGTEx) project has been established to develop a public resource of genetic regulatory variants in livestock, which is essential for linking genetic polymorphisms to variation in phenotypes, helping fundamental biological discovery and exploitation in animal breeding and human biomedicine. Here we show results from the pilot phase of PigGTEx by processing 5,457 RNA-sequencing and 1,602 whole-genome sequencing samples passing quality control from pigs. We build a pig genotype imputation panel and associate millions of genetic variants with five types of transcriptomic phenotypes in 34 tissues. We evaluate tissue specificity of regulatory effects and elucidate molecular mechanisms of their action using multi-omics data. Leveraging this resource, we decipher regulatory mechanisms underlying 207 pig complex phenotypes and demonstrate the similarity of pigs to humans in gene expression and the genetic regulation behind complex phenotypes, supporting the importance of pigs as a human biomedical model.

Gene expression and RNA splicing explain large proportions of the heritability for complex traits in cattle

Many quantitative trait loci (QTLs) are in non-coding regions. Therefore, QTLs are assumed to affect gene regulation. Gene expression and RNA splicing are primary steps of transcription, so DNA variants changing gene expression (eVariants) or RNA splicing (sVariants) are expected to significantly affect phenotypes. We quantify the contribution of eVariants and sVariants detected from 16 tissues (n = 4,725) to 37 traits of ∼120,000 cattle (average magnitude of genetic correlation between traits = 0.13). Analyzed in Bayesian mixture models, averaged across 37 traits, cis and trans eVariants and sVariants detected from 16 tissues jointly explain 69.2% (SE = 0.5%) of heritability, 44% more than expected from the same number of random variants. This 69.2% includes an average of 24% from trans e-/sVariants (14% more than expected). Averaged across 56 lipidomic traits, multi-tissue cis and trans e-/sVariants also explain 71.5% (SE = 0.3%) of heritability, demonstrating the essential role of proximal and distal regulatory variants in shaping mammalian phenotypes.

Fine-mapping of retinal vascular complexity loci identifies Notch regulation as a shared mechanism with myocardial infarction outcomes

There is increasing evidence that the complexity of the retinal vasculature measured as fractal dimension, D_f, might offer earlier insights into the progression of coronary artery disease (CAD) before traditional biomarkers can be detected. This association could be partly explained by a common genetic basis; however, the genetic component of D_f is poorly understood. We present a genome-wide association study (GWAS) of 38,000 individuals with white British ancestry from the UK Biobank aimed to comprehensively study the genetic component of D_f and analyse its relationship with CAD. We replicated 5 D_f loci and found 4 additional loci with suggestive significance (P < 1e-05) to contribute to D_f variation, which previously were reported in retinal tortuosity and complexity, hypertension, and CAD studies. Significant negative genetic correlation estimates support the inverse relationship between D_f and CAD, and between D_f and myocardial infarction (MI), one of CAD's fatal outcomes. Fine-mapping of D_f loci revealed Notch signalling regulatory variants supporting a shared mechanism with MI outcomes. We developed a predictive model for MI incident cases, recorded over a 10-year period following clinical and ophthalmic evaluation, combining clinical information, D_f, and a CAD polygenic risk score. Internal cross-validation demonstrated a considerable improvement in the area under the curve (AUC) of our predictive model (AUC = 0.770 ± 0.001) when comparing with an established risk model, SCORE, (AUC = 0.741 ± 0.002) and extensions thereof leveraging the PRS (AUC = 0.728 ± 0.001). This evidences that D_f provides risk information beyond demographic, lifestyle, and genetic risk factors. Our findings shed new light on the genetic basis of D_f, unveiling a common control with MI, and highlighting the benefits of its application in individualised MI risk prediction.

GWAS and meta-analysis identifies 49 genetic variants underlying critical COVID-19

Critical illness in COVID-19 is an extreme and clinically homogeneous disease phenotype that we have previously shown1 to be highly efficient for discovery of genetic associations2. Despite the advanced stage of illness at presentation, we have shown that host genetics in patients who are critically ill with COVID-19 can identify immunomodulatory therapies with strong beneficial effects in this group3. Here we analyse 24,202 cases of COVID-19 with critical illness comprising a combination of microarray genotype and whole-genome sequencing data from cases of critical illness in the international GenOMICC (11,440 cases) study, combined with other studies recruiting hospitalized patients with a strong focus on severe and critical disease: ISARIC4C (676 cases) and the SCOURGE consortium (5,934 cases). To put these results in the context of existing work, we conduct a meta-analysis of the new GenOMICC genome-wide association study (GWAS) results with previously published data. We find 49 genome-wide significant associations, of which 16 have not been reported previously. To investigate the therapeutic implications of these findings, we infer the structural consequences of protein-coding variants, and combine our GWAS results with gene expression data using a monocyte transcriptome-wide association study (TWAS) model, as well as gene and protein expression using Mendelian randomization. We identify potentially druggable targets in multiple systems, including inflammatory signalling (JAK1), monocyte-macrophage activation and endothelial permeability (PDE4A), immunometabolism (SLC2A5 and AK5), and host factors required for viral entry and replication (TMPRSS2 and RAB2A).

Frequency and Phenotype Associations of Rare Variants in 5 Monogenic Cerebral Small Vessel Disease Genes in 200,000 UK Biobank Participants

BACKGROUND AND OBJECTIVES

Based on previous case reports and disease-based cohorts, a minority of patients with cerebral small vessel disease (cSVD) have a monogenic cause, with many also manifesting extracerebral phenotypes. We investigated the frequency, penetrance, and phenotype associations of putative pathogenic variants in cSVD genes in the UK Biobank (UKB), a large population-based study.

METHODS

We used a systematic review of previous literature and ClinVar to identify putative pathogenic rare variants in CTSA, TREX1, HTRA1, and COL4A1/2. We mapped phenotypes previously attributed to these variants (phenotypes-of-interest) to disease coding systems used in the UKB's linked health data from UK hospital admissions, death records, and primary care. Among 199,313 exome-sequenced UKB participants, we assessed the following: the proportion of participants carrying ≥1 variant(s); phenotype-of-interest penetrance; and the association between variant carrier status and phenotypes-of-interest using a binary (any phenotype present/absent) and phenotype burden (linear score of the number of phenotypes a participant possessed) approach.

RESULTS

Among UKB participants, 0.5% had ≥1 variant(s) in studied genes. Using hospital admission and death records, 4%-20% of variant carriers per gene had an associated phenotype. This increased to 7%-55% when including primary care records. Only COL4A1 variant carrier status was significantly associated with having ≥1 phenotype-of-interest and a higher phenotype score (OR = 1.29, p = 0.006).

DISCUSSION

While putative pathogenic rare variants in monogenic cSVD genes occur in 1:200 people in the UKB population, only approximately half of variant carriers have a relevant disease phenotype recorded in their linked health data. We could not replicate most previously reported gene-phenotype associations, suggesting lower penetrance rates, overestimated pathogenicity, and/or limited statistical power.

The conservation of human functional variants and their effects across livestock species

Despite the clear potential of livestock models of human functional variants to provide important insights into the biological mechanisms driving human diseases and traits, their use to date has been limited. Generating such models via genome editing is costly and time consuming, and it is unclear which variants will have conserved effects across species. In this study we address these issues by studying naturally occurring livestock models of human functional variants. We show that orthologues of over 1.6 million human variants are already segregating in domesticated mammalian species, including several hundred previously directly linked to human traits and diseases. Models of variants linked to particular phenotypes, including metabolomic disorders and height, are preferentially shared across species, meaning studying the genetic basis of these phenotypes is particularly tractable in livestock. Using machine learning we demonstrate it is possible to identify human variants that are more likely to have an existing livestock orthologue, and, importantly, we show that the effects of functional variants are often conserved in livestock, acting on orthologous genes with the same direction of effect. Consequently, this work demonstrates the substantial potential of naturally occurring livestock carriers of orthologues of human functional variants to disentangle their functional impacts.

An investigation of genetic variants that exist across human and livestock species supports the clear potential of livestock models in providing insights into the mechanisms driving human diseases and traits.

Comparative transcriptome in large-scale human and cattle populations

BACKGROUND

Cross-species comparison of transcriptomes is important for elucidating evolutionary molecular mechanisms underpinning phenotypic variation between and within species, yet to date it has been essentially limited to model organisms with relatively small sample sizes.

RESULTS

Here, we systematically analyze and compare 10,830 and 4866 publicly available RNA-seq samples in humans and cattle, respectively, representing 20 common tissues. Focusing on 17,315 orthologous genes, we demonstrate that mean/median gene expression, inter-individual variation of expression, expression quantitative trait loci, and gene co-expression networks are generally conserved between humans and cattle. By examining large-scale genome-wide association studies for 46 human traits (average n = 327,973) and 45 cattle traits (average n = 24,635), we reveal that the heritability of complex traits in both species is significantly more enriched in transcriptionally conserved than diverged genes across tissues.

CONCLUSIONS

In summary, our study provides a comprehensive comparison of transcriptomes between humans and cattle, which might help decipher the genetic and evolutionary basis of complex traits in both species.

A multi-tissue atlas of regulatory variants in cattle

Characterization of genetic regulatory variants acting on livestock gene expression is essential for interpreting the molecular mechanisms underlying traits of economic value and for increasing the rate of genetic gain through artificial selection. Here we build a Cattle Genotype-Tissue Expression atlas (CattleGTEx) as part of the pilot phase of the Farm animal GTEx (FarmGTEx) project for the research community based on 7,180 publicly available RNA-sequencing (RNA-seq) samples. We describe the transcriptomic landscape of more than 100 tissues/cell types and report hundreds of thousands of genetic associations with gene expression and alternative splicing for 23 distinct tissues. We evaluate the tissue-sharing patterns of these genetic regulatory effects, and functionally annotate them using multiomics data. Finally, we link gene expression in different tissues to 43 economically important traits using both transcriptome-wide association and colocalization analyses to decipher the molecular regulatory mechanisms underpinning such agronomic traits in cattle.

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2-4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes-including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)-in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease.

A common TMPRSS2 variant has a protective effect against severe COVID-19

BACKGROUND

The human protein transmembrane protease serine type 2 (TMPRSS2) plays a key role in SARS-CoV-2 infection, as it is required to activate the virus' spike protein, facilitating entry into target cells. We hypothesized that naturally-occurring TMPRSS2 human genetic variants affecting the structure and function of the TMPRSS2 protein may modulate the severity of SARS-CoV-2 infection.

METHODS

We focused on the only common TMPRSS2 non-synonymous variant predicted to be damaging (rs12329760 C>T, p.V160M), which has a minor allele frequency ranging from 0.14 in Ashkenazi Jewish to 0.38 in East Asians. We analysed the association between the rs12329760 and COVID-19 severity in 2,244 critically ill patients with COVID-19 from 208 UK intensive care units recruited as part of the GenOMICC (Genetics Of Mortality In Critical Care) study. Logistic regression analyses were adjusted for sex, age and deprivation index. For in vitro studies, HEK293 cells were co-transfected with ACE2 and either TMPRSS2 wild type or mutant (TMPRSS2V160M). A SARS-CoV-2 pseudovirus entry assay was used to investigate the ability of TMPRSS2V160M to promote viral entry.

RESULTS

We show that the T allele of rs12329760 is associated with a reduced likelihood of developing severe COVID-19 (OR 0.87, 95%CI:0.79-0.97, p = 0.01). This association was stronger in homozygous individuals when compared to the general population (OR 0.65, 95%CI:0.50-0.84, p = 1.3 × 10-3). We demonstrate in vitro that this variant, which causes the amino acid substitution valine to methionine, affects the catalytic activity of TMPRSS2 and is less able to support SARS-CoV-2 spike-mediated entry into cells.

CONCLUSION

TMPRSS2 rs12329760 is a common variant associated with a significantly decreased risk of severe COVID-19. Further studies are needed to assess the expression of TMPRSS2 across different age groups. Moreover, our results identify TMPRSS2 as a promising drug target, with a potential role for camostat mesilate, a drug approved for the treatment of chronic pancreatitis and postoperative reflux esophagitis, in the treatment of COVID-19. Clinical trials are needed to confirm this.

Physician-Confirmed and Administrative Definitions of Stroke in UK Biobank Reflect the Same Underlying Genetic Trait

Background

Stroke in UK Biobank (UKB) is ascertained via linkages to coded administrative datasets and self-report. We studied the accuracy of these codes using genetic validation.

Methods

We compiled stroke-specific and broad cerebrovascular disease (CVD) code lists (Read V2/V3, ICD-9/-10) for medical settings (hospital, death record, primary care) and self-report. Among 408,210 UKB participants, we identified all with a relevant code, creating 12 stroke definitions based on the code type and source. We performed genome-wide association studies (GWASs) for each definition, comparing summary results against the largest published stroke GWAS (MEGASTROKE), assessing genetic correlations, and replicating 32 stroke-associated loci.

Results

The stroke case numbers identified varied widely from 3,976 (primary care stroke-specific codes) to 19,449 (all codes, all sources). All 12 UKB stroke definitions were significantly correlated with the MEGASTROKE summary GWAS results (rg.81-1) and each other (rg.4-1). However, Bonferroni-corrected confidence intervals were wide, suggesting limited precision of some results. Six previously reported stroke-associated loci were replicated using ≥1 UKB stroke definition.

Conclusions

Stroke case numbers in UKB depend on the code source and type used, with a 5-fold difference in the maximum case-sample size. All stroke definitions are significantly genetically correlated with the largest stroke GWAS to date.

Rare variant analysis in eczema identifies exonic variants in DUSP1, NOTCH4 and SLC9A4

Previous genome-wide association studies revealed multiple common variants involved in eczema but the role of rare variants remains to be elucidated. Here, we investigate the role of rare variants in eczema susceptibility. We meta-analyze 21 study populations including 20,016 eczema cases and 380,433 controls. Rare variants are imputed with high accuracy using large population-based reference panels. We identify rare exonic variants in DUSP1, NOTCH4, and SLC9A4 to be associated with eczema. In DUSP1 and NOTCH4 missense variants are predicted to impact conserved functional domains. In addition, five novel common variants at SATB1-AS1/KCNH8, TRIB1/LINC00861, ZBTB1, TBX21/OSBPL7, and CSF2RB are discovered. While genes prioritized based on rare variants are significantly up-regulated in the skin, common variants point to immune cell function. Over 20% of the single nucleotide variant-based heritability is attributable to rare and low-frequency variants. The identified rare/low-frequency variants located in functional protein domains point to promising targets for novel therapeutic approaches to eczema.

Genetic studies of eczema to date have mostly explored common genetic variation. Here, the authors perform a large meta-analysis for common and rare variants and discover 8 loci associated with eczema. Over 20% of the heritability of the condition is attributable to rare variants.

Sex differences in genetic architecture in the UK Biobank

Males and females present differences in complex traits and in the risk of a wide array of diseases. Genotype by sex (GxS) interactions are thought to account for some of these differences. However, the extent and basis of GxS are poorly understood. In the present study, we provide insights into both the scope and the mechanism of GxS across the genome of about 450,000 individuals of European ancestry and 530 complex traits in the UK Biobank. We found small yet widespread differences in genetic architecture across traits. We also found that, in some cases, sex-agnostic analyses may be missing trait-associated loci and looked into possible improvements in the prediction of high-level phenotypes. Finally, we studied the potential functional role of the differences observed through sex-biased gene expression and gene-level analyses. Our results suggest the need to consider sex-aware analyses for future studies to shed light onto possible sex-specific molecular mechanisms.

Pan-ancestry exome-wide association analyses of COVID-19 outcomes in 586,157 individuals

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causes coronavirus disease 2019 (COVID-19), a respiratory illness that can result in hospitalization or death. We used exome sequence data to investigate associations between rare genetic variants and seven COVID-19 outcomes in 586,157 individuals, including 20,952 with COVID-19. After accounting for multiple testing, we did not identify any clear associations with rare variants either exome wide or when specifically focusing on (1) 13 interferon pathway genes in which rare deleterious variants have been reported in individuals with severe COVID-19, (2) 281 genes located in susceptibility loci identified by the COVID-19 Host Genetics Initiative, or (3) 32 additional genes of immunologic relevance and/or therapeutic potential. Our analyses indicate there are no significant associations with rare protein-coding variants with detectable effect sizes at our current sample sizes. Analyses will be updated as additional data become available, and results are publicly available through the Regeneron Genetics Center COVID-19 Results Browser.

Genetic mechanisms of critical illness in COVID-19

Host-mediated lung inflammation is present1, and drives mortality2, in the critical illness caused by coronavirus disease 2019 (COVID-19). Host genetic variants associated with critical illness may identify mechanistic targets for therapeutic development3. Here we report the results of the GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study in 2,244 critically ill patients with COVID-19 from 208 UK intensive care units. We have identified and replicated the following new genome-wide significant associations: on chromosome 12q24.13 (rs10735079, P = 1.65 × 10-8) in a gene cluster that encodes antiviral restriction enzyme activators (OAS1, OAS2 and OAS3); on chromosome 19p13.2 (rs74956615, P = 2.3 × 10-8) near the gene that encodes tyrosine kinase 2 (TYK2); on chromosome 19p13.3 (rs2109069, P = 3.98 ×  10-12) within the gene that encodes dipeptidyl peptidase 9 (DPP9); and on chromosome 21q22.1 (rs2236757, P = 4.99 × 10-8) in the interferon receptor gene IFNAR2. We identified potential targets for repurposing of licensed medications: using Mendelian randomization, we found evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte-macrophage chemotactic receptor CCR2 is associated with severe COVID-19. Our results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19. Both mechanisms may be amenable to targeted treatment with existing drugs. However, large-scale randomized clinical trials will be essential before any change to clinical practice.

Evidence of horizontal indirect genetic effects in humans

Indirect genetic effects, the effects of the genotype of one individual on the phenotype of other individuals, are environmental factors associated with human disease and complex trait variation that could help to expand our understanding of the environment linked to complex traits. Here, we study indirect genetic effects in 80,889 human couples of European ancestry for 105 complex traits. Using a linear mixed model approach, we estimate partner indirect heritability and find evidence of partner heritability on ~50% of the analysed traits. Follow-up analysis suggests that in at least ~25% of these traits, the partner heritability is consistent with the existence of indirect genetic effects including a wide variety of traits such as dietary traits, mental health and disease. This shows that the environment linked to complex traits is partially explained by the genotype of other individuals and motivates the need to find new ways of studying the environment.

A catalog of associations between rare coding variants and COVID-19 outcomes

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causes coronavirus disease-19 (COVID-19), a respiratory illness that can result in hospitalization or death. We investigated associations between rare genetic variants and seven COVID-19 outcomes in 543,213 individuals, including 8,248 with COVID-19. After accounting for multiple testing, we did not identify any clear associations with rare variants either exome-wide or when specifically focusing on (i) 14 interferon pathway genes in which rare deleterious variants have been reported in severe COVID-19 patients; (ii) 167 genes located in COVID-19 GWAS risk loci; or (iii) 32 additional genes of immunologic relevance and/or therapeutic potential. Our analyses indicate there are no significant associations with rare protein-coding variants with detectable effect sizes at our current sample sizes. Analyses will be updated as additional data become available, with results publicly browsable at https://rgc-covid19.regeneron.com.

Epigenomics and genotype-phenotype association analyses reveal conserved genetic architecture of complex traits in cattle and human

Background

Lack of comprehensive functional annotations across a wide range of tissues and cell types severely hinders the biological interpretations of phenotypic variation, adaptive evolution, and domestication in livestock. Here we used a combination of comparative epigenomics, genome-wide association study (GWAS), and selection signature analysis, to shed light on potential adaptive evolution in cattle.

Results

We cross-mapped 8 histone marks of 1300 samples from human to cattle, covering 178 unique tissues/cell types. By uniformly analyzing 723 RNA-seq and 40 whole genome bisulfite sequencing (WGBS) datasets in cattle, we validated that cross-mapped histone marks captured tissue-specific expression and methylation, reflecting tissue-relevant biology. Through integrating cross-mapped tissue-specific histone marks with large-scale GWAS and selection signature results, we for the first time detected relevant tissues and cell types for 45 economically important traits and artificial selection in cattle. For instance, immune tissues are significantly associated with health and reproduction traits, multiple tissues for milk production and body conformation traits (reflecting their highly polygenic architecture), and thyroid for the different selection between beef and dairy cattle. Similarly, we detected relevant tissues for 58 complex traits and diseases in humans and observed that immune and fertility traits in humans significantly correlated with those in cattle in terms of relevant tissues, which facilitated the identification of causal genes for such traits. For instance, PIK3CG, a gene highly specifically expressed in mononuclear cells, was significantly associated with both age-at-menopause in human and daughter-still-birth in cattle. ICAM, a T cell-specific gene, was significantly associated with both allergic diseases in human and metritis in cattle.

Conclusion

Collectively, our results highlighted that comparative epigenomics in conjunction with GWAS and selection signature analyses could provide biological insights into the phenotypic variation and adaptive evolution. Cattle may serve as a model for human complex traits, by providing additional information beyond laboratory model organisms, particularly when more novel phenotypes become available in the near future.

Linking protein to phenotype with Mendelian Randomization detects 38 proteins with causal roles in human diseases and traits

To efficiently transform genetic associations into drug targets requires evidence that a particular gene, and its encoded protein, contribute causally to a disease. To achieve this, we employ a three-step proteome-by-phenome Mendelian Randomization (MR) approach. In step one, 154 protein quantitative trait loci (pQTLs) were identified and independently replicated. From these pQTLs, 64 replicated locally-acting variants were used as instrumental variables for proteome-by-phenome MR across 846 traits (step two). When its assumptions are met, proteome-by-phenome MR, is equivalent to simultaneously running many randomized controlled trials. Step 2 yielded 38 proteins that significantly predicted variation in traits and diseases in 509 instances. Step 3 revealed that amongst the 271 instances from GeneAtlas (UK Biobank), 77 showed little evidence of pleiotropy (HEIDI), and 92 evidence of colocalization (eCAVIAR). Results were wide ranging: including, for example, new evidence for a causal role of tyrosine-protein phosphatase non-receptor type substrate 1 (SHPS1; SIRPA) in schizophrenia, and a new finding that intestinal fatty acid binding protein (FABP2) abundance contributes to the pathogenesis of cardiovascular disease. We also demonstrated confirmatory evidence for the causal role of four further proteins (FGF5, IL6R, LPL, LTA) in cardiovascular disease risk.

Comprehensive analyses of 723 transcriptomes enhance genetic and biological interpretations for complex traits in cattle

By uniformly analyzing 723 RNA-seq data from 91 tissues and cell types, we built a comprehensive gene atlas and studied tissue specificity of genes in cattle. We demonstrated that tissue-specific genes significantly reflected the tissue-relevant biology, showing distinct promoter methylation and evolution patterns (e.g., brain-specific genes evolve slowest, whereas testis-specific genes evolve fastest). Through integrative analyses of those tissue-specific genes with large-scale genome-wide association studies, we detected relevant tissues/cell types and candidate genes for 45 economically important traits in cattle, including blood/immune system (e.g., CCDC88C) for male fertility, brain (e.g., TRIM46 and RAB6A) for milk production, and multiple growth-related tissues (e.g., FGF6 and CCND2) for body conformation. We validated these findings by using epigenomic data across major somatic tissues and sperm. Collectively, our findings provided novel insights into the genetic and biological mechanisms underlying complex traits in cattle, and our transcriptome atlas can serve as a primary source for biological interpretation, functional validation, studies of adaptive evolution, and genomic improvement in livestock.

Statistical and Functional Studies Identify Epistasis of Cardiovascular Risk Genomic Variants From Genome-Wide Association Studies

Background

Epistasis describes how gene‐gene interactions affect phenotypes, and could have a profound impact on human diseases such as coronary artery disease (CAD). The goal of this study was to identify gene‐gene interactions in CAD using an easily generalizable multi‐stage approach.

Methods and Results

Our forward genetic approach consists of multiple steps that combine statistical and functional approaches, and analyze information from global gene expression profiling, functional interactions, and genetic interactions to robustly identify gene‐gene interactions. Global gene expression profiling shows that knockdown of ANRIL (DQ485454) at 9p21.3 GWAS (genome‐wide association studies) CAD locus upregulates TMEM100 and TMEM106B. Functional studies indicate that the increased monocyte adhesion to endothelial cells and transendothelial migration of monocytes, 2 critical processes in the initiation of CAD, by ANRIL knockdown are reversed by knockdown of TMEM106B, but not of TMEM100. Furthermore, the decreased monocyte adhesion to endothelial cells and transendothelial migration of monocytes induced by ANRIL overexpression was reversed by overexpressing TMEM106B. TMEM106B expression was upregulated by >2‐fold in CAD coronary arteries. A significant association was found between variants in TMEM106B (but not in TMEM100) and CAD (P=1.9×10⁻⁸). Significant gene‐gene interaction was detected between ANRIL variant rs2383207 and TMEM106B variant rs3807865 (P=0.009). A similar approach also identifies significant interaction between rs6903956 in ADTRP and rs17465637 in MIA3 (P=0.005).

Conclusions

We demonstrate 2 pairs of epistatic interactions between GWAS loci for CAD and offer important insights into the genetic architecture and molecular mechanisms for the pathogenesis of CAD. Our strategy has broad applicability to the identification of epistasis in other human diseases.

Using regulatory variants to detect gene-gene interactions identifies networks of genes linked to cell immortalisation

The extent to which the impact of regulatory genetic variants may depend on other factors, such as the expression levels of upstream transcription factors, remains poorly understood. Here we report a framework in which regulatory variants are first aggregated into sets, and using these as estimates of the total cis-genetic effects on a gene we model their non-additive interactions with the expression of other genes in the genome. Using 1220 lymphoblastoid cell lines across platforms and independent datasets we identify 74 genes where the impact of their regulatory variant-set is linked to the expression levels of networks of distal genes. We show that these networks are predominantly associated with tumourigenesis pathways, through which immortalised cells are able to rapidly proliferate. We consequently present an approach to define gene interaction networks underlying important cellular pathways such as cell immortalisation.

Functional annotation of the cattle genome through systematic discovery and characterization of chromatin states and butyrate-induced variations

BACKGROUND

The functional annotation of genomes, including chromatin accessibility and modifications, is important for understanding and effectively utilizing the increased amount of genome sequences reported. However, while such annotation has been well explored in a diverse set of tissues and cell types in human and model organisms, relatively little data are available for livestock genomes, hindering our understanding of complex trait variation, domestication, and adaptive evolution. Here, we present the first complete global landscape of regulatory elements in cattle and explore the dynamics of chromatin states in rumen epithelial cells induced by the rumen developmental regulator-butyrate.

RESULTS

We established the first global map of regulatory elements (15 chromatin states) and defined their coordinated activities in cattle, through genome-wide profiling for six histone modifications, RNA polymerase II, CTCF-binding sites, DNA accessibility, DNA methylation, and transcriptome in rumen epithelial primary cells (REPC), rumen tissues, and Madin-Darby bovine kidney epithelial cells (MDBK). We demonstrated that each chromatin state exhibited specific enrichment for sequence ontology, transcription, methylation, trait-associated variants, gene expression-associated variants, selection signatures, and evolutionarily conserved elements, implying distinct biological functions. After butyrate treatments, we observed that the weak enhancers and flanking active transcriptional start sites (TSS) were the most dynamic chromatin states, occurred concomitantly with significant alterations in gene expression and DNA methylation, which was significantly associated with heifer conception rate and stature economic traits.

CONCLUSION

Our results demonstrate the crucial role of functional genome annotation for understanding genome regulation, complex trait variation, and adaptive evolution in livestock. Using butyrate to induce the dynamics of the epigenomic landscape, we were able to establish the correlation among nutritional elements, chromatin states, gene activities, and phenotypic outcomes.

Publisher Correction: Parent of origin genetic effects on methylation in humans are common and influence complex trait variation

In the original version of this Article, the legend in the upper panel of Figure 2 incorrectly read 'paternal imprinting' and should have read 'maternal imprinting'. This has been corrected in both the PDF and HTML versions of the Article.

Parent of origin genetic effects on methylation in humans are common and influence complex trait variation

Parent-of-origin effects (POE) exist when there is differential expression of alleles inherited from the two parents. A genome-wide scan for POE on DNA methylation at 639,238 CpGs in 5,101 individuals identifies 733 independent methylation CpGs potentially influenced by POE at a false discovery rate ≤ 0.05 of which 331 had not previously been identified. Cis and trans methylation quantitative trait loci (mQTL) regulate methylation variation through POE at 54% (399/733) of the identified POE-influenced CpGs. The combined results provide strong evidence for previously unidentified POE-influenced CpGs at 171 independent loci. Methylation variation at 14 of the POE-influenced CpGs is associated with multiple metabolic traits. A phenome-wide association analysis using the POE mQTL SNPs identifies a previously unidentified imprinted locus associated with waist circumference. These results provide a high resolution population-level map for POE on DNA methylation sites, their local and distant regulators and potential consequences for complex traits.

Genome-wide scan of the effect of common nsSNPs on colorectal cancer survival outcome

BACKGROUND

We conducted a genome-wide scan to identify non-synonymous SNPs (nsSNPs) that might influence survival after a diagnosis of colorectal cancer (CRC).

METHODS

We genotyped 7679 nsSNPs in 1939 Scottish patients from the Scottish Colorectal Cancer Study recruited soon after a CRC diagnosis and prospectively followed for survival outcomes. All-cause and CRC-specific survival analyses were conducted using Cox proportional hazard models adjusted for stage, age and sex for all cancer cases, after cancer type stratification and assuming additive and recessive models of inheritance. For all the SNPs that had a p-value < 0.10 a meta-analysis was performed combining the results of the discovery set and a replication set of 899 Scottish CRC patients. The p-value threshold of significance was set as at p < 10-8.

RESULTS

897 and 894 nsSNPs were associated with all-cause and CRC-specific mortality, respectively, at a p-value level < 0.10 in the discovery set. Meta-analysis of the results from the discovery and replication sets was performed overall and for cancers of colon and rectum separately and none of the variants reached a p-value < 10-8.

CONCLUSIONS

This large scale well-powered analysis demonstrates that common nsSNPs are not associated with CRC prognosis overall.

Abstract A37: Genome-wide association study of colorectal tumors in Latin American individuals from Colombia

Introduction: Colorectal cancer (CRC) is one of the most common cancers worldwide, with higher incidence among more developed countries. However, mortality rates are higher and increasing in less-developed regions, including Colombia. Incidence and mortality rates of CRC vary across the country, with the lowest rates among populations with increased concentration of Native Americans. Our group previously reported that increased European and African ancestry was associated with higher adenomatous polyps (AP) and CRC risk in Colombians. Based on this observation we hypothesize that genetic contribution to the observed regional variation on CRC development in Colombia might be partly explained by the influence of genetic variants with different frequency distribution in the European, Amerindian, and African ancestral components.

Objective: To test our hypothesis we performed a genome-wide association study (GWAS) of colorectal tumors in Colombian CRC and AP cases and controls.

Materials and Methods: We conducted a GWAS of Colombians from different regions of the country that included 162 CRC cases, 122 AP cases, and 131 controls. Only SNPs with MAF ≥ 0.05 were included. The role of these common variants was assessed by logistic regression models adjusted for age, sex, and the first 10 principal components (PCs) of the genetic variation. Analyses were performed for a total of 606410 SNPs. The P value threshold for genome-wide significant SNPs was set at the traditional value of ≤ 5 × 10−8.

Results: We replicated some of the previously reported associations (8 out of 44 SNPs, P ≤ 0.05) of which 7 had directionally concordant ORs. Regarding the remaining 36 published risk variants, 25 had directionally concordant ORs, even though neither of them was significant at nominal P ≤ 0.05. None of the SNPs analyzed passed the threshold for genome-wide significance. However, we found multiple suggestive associations. One novel SNP within the region 2q11.2-q12 near the gene MAP4K4 was associated with the risk of AP (rs4280476-G; OR 0.36; 95% CI 0.23-0.56; P = 8.7 x 10-6). We also found four novel SNPs across three regions with suggestive CRC risk associations: rs10514122-A located in the locus 5q14 near the TBCA gene (OR 0.30; 95% CI 0.18-0.49; P = 3.6 x 10-6), rs10746883-G (OR 0.37; 95% CI 0.25-0.56; P = 3.2 x 10-6) and the rs10781032-A (OR 0.35; 95% CI 0.22-0.53; P = 1.7 x 10-6), in high LD with each other (R2 = 0.81), located in the locus 9q21.1-q21.2 near the genes TRPM3 and TMEM2 and the SNP rs2800641-G located in the region 6q25.2 near the MYCT1 gene (OR 2.96; 95% CI 1.83-4.77; P = 8.9 x 10-6). The inflation factors (λ), when comparing AP or CRC cases vs controls, were 1.05 and 1.04, respectively, indicating appropriate control for population stratification. Finally, it is of note that the MAF reported for the 5 novel SNPs identified in our study shows important differences between European, Asian, and African reference populations from the public database 1,000 genomes.

Conclusions: In this GWAS of AP and CRC in individuals from Colombia, we replicated some of the previously reported associations and identified suggestive signals for 5 novel risk alleles located at four loci (2q11.2-q12, 5q14, 9q21.1-q21.2, and 6q25.2). Further work is needed to replicate our findings in other Latin American populations.

Citation Format: Maria Carolina Sanabria-Salas, Laura Fejerman, Konrad Rawlik, Albert Tenesa, Martha L. Serrano-Lopez, Jovanny Zabaleta, Gustavo A. Hernandez-Suarez. Genome-wide association study of colorectal tumors in Latin American individuals from Colombia [abstract]. In: Proceedings of the Tenth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2017 Sep 25-28; Atlanta, GA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2018;27(7 Suppl):Abstract nr A37.

Shared activity patterns arising at genetic susceptibility loci reveal underlying genomic and cellular architecture of human disease

Genetic variants underlying complex traits, including disease susceptibility, are enriched within the transcriptional regulatory elements, promoters and enhancers. There is emerging evidence that regulatory elements associated with particular traits or diseases share similar patterns of transcriptional activity. Accordingly, shared transcriptional activity (coexpression) may help prioritise loci associated with a given trait, and help to identify underlying biological processes. Using cap analysis of gene expression (CAGE) profiles of promoter- and enhancer-derived RNAs across 1824 human samples, we have analysed coexpression of RNAs originating from trait-associated regulatory regions using a novel quantitative method (network density analysis; NDA). For most traits studied, phenotype-associated variants in regulatory regions were linked to tightly-coexpressed networks that are likely to share important functional characteristics. Coexpression provides a new signal, independent of phenotype association, to enable fine mapping of causative variants. The NDA coexpression approach identifies new genetic variants associated with specific traits, including an association between the regulation of the OCT1 cation transporter and genetic variants underlying circulating cholesterol levels. NDA strongly implicates particular cell types and tissues in disease pathogenesis. For example, distinct groupings of disease-associated regulatory regions implicate two distinct biological processes in the pathogenesis of ulcerative colitis; a further two separate processes are implicated in Crohn's disease. Thus, our functional analysis of genetic predisposition to disease defines new distinct disease endotypes. We predict that patients with a preponderance of susceptibility variants in each group are likely to respond differently to pharmacological therapy. Together, these findings enable a deeper biological understanding of the causal basis of complex traits.

Genome-wide association study and meta-analysis in Northern European populations replicate multiple colorectal cancer risk loci

Genome-wide association studies have been successful in elucidating the genetic basis of colorectal cancer (CRC), but there remains unexplained variability in genetic risk. To identify new risk variants and to confirm reported associations, we conducted a genome-wide association study in 1,701 CRC cases and 14,082 cancer-free controls from the Finnish population. A total of 9,068,015 genetic variants were imputed and tested, and 30 promising variants were studied in additional 11,647 cases and 12,356 controls of European ancestry. The previously reported association between the single-nucleotide polymorphism (SNP) rs992157 (2q35) and CRC was independently replicated (p = 2.08 × 10-4 ; OR, 1.14; 95% CI, 1.06-1.23), and it was genome-wide significant in combined analysis (p = 1.50 × 10-9 ; OR, 1.12; 95% CI, 1.08-1.16). Variants at 2q35, 6p21.2, 8q23.3, 8q24.21, 10q22.3, 10q24.2, 11q13.4, 11q23.1, 14q22.2, 15q13.3, 18q21.1, 20p12.3 and 20q13.33 were associated with CRC in the Finnish population (false discovery rate < 0.1), but new risk loci were not found. These results replicate the effects of multiple loci on the risk of CRC and identify shared risk alleles between the Finnish population isolate and outbred populations.

Evidence of epigenetic admixture in the Colombian population

DNA methylation (DNAm) measured in lymphoblastoid cell lines has been repeatedly demonstrated to differ between various human populations. Due to the role that DNAm plays in controlling gene expression, these differences could significantly contribute to ethnic phenotypic differences. However, because previous studies have compared distinct ethnic groups where genetic and environmental context are confounded, their relative contribution to phenotypic differences between ethnicities remains unclear. Using DNAm assayed in whole blood and colorectal tissue of 132 admixed individuals from Colombia, we identified sites where differential DNAm levels were associated with the local ancestral genetic context. Our results are consistent with population specific DNAm being primarily driven by between population genetic differences in cis, with little environmental contribution, and with consistent effects across tissues. The findings offer new insights into a possible mechanism driving phenotypic differences among different ethnic groups, and could help explain ethnic differences in colorectal cancer incidence.

Abstract LB-162: Common genetic variants within TEP1 gene (14q11.2 locus) and TK1 gene (17q25.3 locus) are associated with the risk of colorectal tumors in Latinos

Introduction: Around 63 common risk variants have been associated with colorectal cancer (CRC) through genome-wide association studies (GWAS) in European and Asian populations; these variants, together with the high penetrance genes responsible for 5% of the cases, do not completely explain the CRC heritability estimated at ~ 35%.

Objective: To discover new common variants associated with the risk of colorectal tumors, taking advantage of the high level of admixture in Latino populations.

Materials and methods: We performed a candidate gene association (CG) and GWAS analyses, in a multicenter case-control study that included 313 cases of CRC, 200 cases of adenomatous polyps (AP) and 506 controls from six Colombian cities. The role of these common variants was assessed by basic SNP association analyses (X2) and logistic regressions adjusted for age, sex and ancestry proportions. Selected SNPs were genotyped by TaqMan in additional samples.

Results: European ancestry was associated with the risk of AP while African ancestry was associated with the risk of both, AP and CCR, (P ≤ 0.01). In the adjusted logistic regression analyses of the CG study, we found that the minor allele (A) of the SNP 14q11.2:rs1760898 (C&gt;A) was associated with the risk of CRC (OR 0.48; 95% CI 0.33-0.69; UNADJ P = 6.8 x 10-5; 100,000 Pperm = 0.03). This association persisted in the adjusted logistic regressions analyses with additional samples genotyped by TaqMan (P = 0.03). In the basic SNP association analyses (X2) of the GWAS study, we found that the minor allele (A) of the SNP 17q25.3:rs1065768 (G&gt;A) was associated with the risk of AP (OR 0.35; 95% CI 0.24 -0.51; UNADJ P = 3.4 x 10-8; Bonferroni corrected P = 0.02). This association persisted after including additional samples genotyped by TaqMan, both, in the basic SNP analysis (P = 1.7 x 10-7) and in the adjusted logistic regressions analysis (P = 9.7 x 10-5). Moreover, the association remained when other variables were also included in the model, such as the first 10 major principal components of genetic variability, ancestry proportions along chromosome 17 and locus-specific ancestry (P = 1.7 x 10-4).

Conclusions: The SNP rs1760898 (TEP1, Telomerase Associated Protein 1 gene) confers a change of Asparagine (Asn) to Lysine (Lys) within the RNA binding domain, TROVE. This change could affect the activity of telomerase enzyme that has an important role in cancer development. The SNP rs1065768 (3'UTR TK1, Thymidine kinase 1 gene) could affect mRNA stability and protein production of TK1, which is essential in DNA synthesis. Although, functional analyses are required to confirm their potential role in colorectal tumorogenesis, our findings help increase our understanding about the biological basis for the development of colorectal tumors, as well as will contribute to the overall knowledge on the heritability of CRC.

Citation Format: María Carolina Sanabria-Salas, Konrad Rawlik, Albert Tenesa, Adriana Umaña-Pérez, Martha Lucía Serrano-López, Myriam Sánchez de Gómez, Jovanny Zabaleta, Gustavo Hernández-Suárez. Common genetic variants within TEP1 gene (14q11.2 locus) and TK1 gene (17q25.3 locus) are associated with the risk of colorectal tumors in Latinos [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr LB-162. doi:10.1158/1538-7445.AM2017-LB-162

IL1B-CGTC haplotype is associated with colorectal cancer in admixed individuals with increased African ancestry

Single-nucleotide polymorphisms (SNPs) in cytokine genes can affect gene expression and thereby modulate inflammation and carcinogenesis. However, the data on the association between SNPs in the interleukin 1 beta gene (IL1B) and colorectal cancer (CRC) are conflicting. We found an association between a 4-SNP haplotype block of the IL1B (-3737C/-1464G/-511T/-31C) and CRC risk, and this association was exclusively observed in individuals with a higher proportion of African ancestry, such as individuals from the Coastal Colombian region (odds ratio, OR 2.06; 95% CI 1.31–3.25; p < 0.01). Moreover, a significant interaction between this CRC risk haplotype and local African ancestry dosage was identified in locus 2q14 (p = 0.03). We conclude that Colombian individuals with high African ancestry proportions at locus 2q14 harbour more IL1B-CGTC copies and are consequently at an increased risk of CRC. This haplotype has been previously found to increase the IL1B promoter activity and is the most frequent haplotype in African Americans. Despite of limitations in the number of samples and the lack of functional analysis to examine the effect of these haplotypes on CRC cell lines, our results suggest that inflammation and ethnicity play a major role in the modulation of CRC risk.

Evaluating the contribution of genetics and familial shared environment to common disease using the UK Biobank

Genome-wide association studies have detected many loci underlying susceptibility to disease, but most of the genetic factors that contribute to disease susceptibility remain unknown. Here we provide evidence that part of the 'missing heritability' can be explained by an overestimation of heritability. We estimated the heritability of 12 complex human diseases using family history of disease in 1,555,906 individuals of white ancestry from the UK Biobank. Estimates using simple family-based statistical models were inflated on average by ∼47% when compared with those from structural equation modeling (SEM), which specifically accounted for shared familial environmental factors. In addition, heritabilities estimated using SNP data explained an average of 44.2% of the simple family-based estimates across diseases and an average of 57.3% of the SEM-estimated heritabilities, accounting for almost all of the SEM heritability for hypertension. Our results show that both genetics and familial environment make substantial contributions to familial clustering of disease.

Evidence for sex-specific genetic architectures across a spectrum of human complex traits

BACKGROUND

Sex differences are a common feature of human traits; however, the role sex determination plays in human genetic variation remains unclear. The presence of gene-by-sex (GxS) interactions implies that trait genetic architecture differs between men and women. Here, we show that GxS interactions and genetic heterogeneity among sexes are small but common features of a range of high-level complex traits.

RESULTS

We analyzed 19 complex traits measured in 54,040 unrelated men and 59,820 unrelated women from the UK Biobank cohort to estimate autosomal genetic correlations and heritability differences between men and women. For 13 of the 19 traits examined, there is evidence that the trait measured is genetically different between males and females. We find that estimates of genetic correlations, based on ~114,000 unrelated individuals and ~19,000 related individuals from the same cohort, are largely consistent. Genetic predictors using a sex-specific model that incorporated GxS interactions led to a relative improvement of up to 4 % (mean 1.4 % across all relevant phenotypes) over those provided by a sex-agnostic model. This further supports the hypothesis of the presence of sexual genetic heterogeneity across high-level phenotypes.

CONCLUSIONS

The sex-specific environment seems to play a role in changing genotype expression across a range of human complex traits. Further studies of GxS interactions for high-level human traits may shed light on the molecular mechanisms that lead to biological differences between men and women. However, this may be a challenging endeavour due to the likely small effects of the interactions at individual loci.

Genome-wide autozygosity is associated with lower general cognitive ability

Inbreeding depression refers to lower fitness among offspring of genetic relatives. This reduced fitness is caused by the inheritance of two identical chromosomal segments (autozygosity) across the genome, which may expose the effects of (partially) recessive deleterious mutations. Even among outbred populations, autozygosity can occur to varying degrees due to cryptic relatedness between parents. Using dense genome-wide single-nucleotide polymorphism (SNP) data, we examined the degree to which autozygosity associated with measured cognitive ability in an unselected sample of 4854 participants of European ancestry. We used runs of homozygosity-multiple homozygous SNPs in a row-to estimate autozygous tracts across the genome. We found that increased levels of autozygosity predicted lower general cognitive ability, and estimate a drop of 0.6 s.d. among the offspring of first cousins (P=0.003-0.02 depending on the model). This effect came predominantly from long and rare autozygous tracts, which theory predicts as more likely to be deleterious than short and common tracts. Association mapping of autozygous tracts did not reveal any specific regions that were predictive beyond chance after correcting for multiple testing genome wide. The observed effect size is consistent with studies of cognitive decline among offspring of known consanguineous relationships. These findings suggest a role for multiple recessive or partially recessive alleles in general cognitive ability, and that alleles decreasing general cognitive ability have been selected against over evolutionary time.

Variation at 2q35 (PNKD and TMBIM1) influences colorectal cancer risk and identifies a pleiotropic effect with inflammatory bowel disease

To identify new risk loci for colorectal cancer (CRC), we conducted a meta-analysis of seven genome-wide association studies (GWAS) with independent replication, totalling 13 656 CRC cases and 21 667 controls of European ancestry. The combined analysis identified a new risk association for CRC at 2q35 marked by rs992157 (P = 3.15 × 10-8, odds ratio = 1.10, 95% confidence interval = 1.06-1.13), which is intronic to PNKD (paroxysmal non-kinesigenic dyskinesia) and TMBIM1 (transmembrane BAX inhibitor motif containing 1). Intriguingly this susceptibility single-nucleotide polymorphism (SNP) is in strong linkage disequilibrium (r2 = 0.90, D' = 0.96) with the previously discovered GWAS SNP rs2382817 for inflammatory bowel disease (IBD). Following on from this observation we examined for pleiotropy, or shared genetic susceptibility, between CRC and the 200 established IBD risk loci, identifying an additional 11 significant associations (false discovery rate [FDR]) < 0.05). Our findings provide further insight into the biological basis of inherited genetic susceptibility to CRC, and identify risk factors that may influence the development of both CRC and IBD.

The heritability and patterns of DNA methylation in normal human colorectum

DNA methylation (DNAm) has been linked to changes in chromatin structure, gene expression and disease. The DNAm level can be affected by genetic variation; although, how this differs by CpG dinucleotide density and genic location of the DNAm site is not well understood. Moreover, the effect of disease causing variants on the DNAm level in a tissue relevant to disease has yet to be fully elucidated. To this end, we investigated the phenotypic profiles, genetic effects and regional genomic heritability for 196080 DNAm sites in healthy colorectum tissue from 132 unrelated Colombian individuals. DNAm sites in regions of low-CpG density were more variable, on average more methylated and were more likely to be significantly heritable when compared with DNAm sites in regions of high-CpG density. DNAm sites located in intergenic regions had a higher mean DNAm level and were more likely to be heritable when compared with DNAm sites in the transcription start site (TSS) of a gene expressed in colon tissue. Within CpG-dense regions, the propensity of the DNAm level to be heritable was lower in the TSS of genes expressed in colon tissue than in the TSS of genes not expressed in colon tissue. In addition, regional genetic variation was associated with variation in local DNAm level no more frequently for DNAm sites within colorectal cancer risk regions than it was for DNAm sites outside such regions. Overall, DNAm sites located in different genomic contexts exhibited distinguishable profiles and may have a different biological function.

Abstract PR08: The role of genetic structure in Colombian coastal and Andean populations on disparities in colorectal adenomas and cancer risk

Background: Latin-Americans have different proportions of Amerindian, African and European genetic ancestry. Particularly, in Colombia the degree of admixture varies across the country as a result of very complex demographic events taken place since 16th century (colonization) and sex-bias gene flow effects. Colorectal cancer (CRC) mortality rates are heterogeneous across Colombian territory and this variation could be explained by regional differences in Colombian genetic background.

Methods: To evaluate the association of genetic ancestry and colorectal adenomas and cancer risk, we genotyped 813 samples from Colombian coastal and andean regions, including 349 controls, 292 CRC cases and 172 adenomatous polyps (AP). Autosomal and X-chromosome individual ancestries were estimated using ADMIXTURE software with 556 AIMS (Fst &gt; 0.5 among HAPMAP reference populations; k=3) and differences in ancestry proportions were assessed using a t-test. Multinomial logit model analysis between phenotype and ancestry proportions (covariates: sex, age, NSAIDs consumption, city of provenance and educational level) were conducted in R.

Results: We found statistical differences (p &lt; 0.05) between African, European and Asian (as a measure of Amerindian) ancestry means of autosomes versus X-chromosome (sex bias). As expected, ancestry means were different between the coast versus andean regions (African 0.27 vs 0.09; European 0.44 vs 0.57 and Asian/Amerindian 0.29 vs 0.35, respectively), reflecting differences among cities. For controls, AP and CRC the respective ancestry means were: African (0.17, 0.18 and 0,20), European (0.50, 0.53 and 0.48) and Asian/Ameridian (0.33, 0.29, 0.32). Univariate analysis showed that European ancestry was associated with an increased risk of AP (p &lt; 0.05) and that African ancestry was associated with an increased risk of CRC (p &lt; 0.05); no differences were found for phenotype among cities. After running full multinomial model, the association between European ancestry and the risk of AP remained (OR 8.50; 95%CI 1.65-43.78; p = 0.011); on the other hand, the association between African ancestry and CRC risk had the same direction but was not significant (OR 1.06; 95%CI 1.00-1.13, p = 0.065). On the full model, we also found that Colombians with no education have more CRC than those with at least high school degree, and this was consistent with univariate analysis. No differences were seeing between educational level and AP, neither in the univariate nor in the multivariate analysis, even though multinomial model of education by ancestry (corrected by city), showed that Colombians with high European ancestry are more likely to hold advance education degree.

Conclusions: Colombian regions have differences in the degree of admixture as a consequence of the highly asymmetric pattern of mating of European men with Native American women and the African slavery trade in the coasts since the colonization period, according to this study and others on Y-chromosome and mtDNA. There was no signal of sampling bias in our study (no differences in phenotypes by city). The association of CRC risk and African ancestry did not remain in the full model, probably due to a small effect, small sample size or the fact that people without education (low socioeconomical status) have less access to health system. The association of AP risk with European ancestry remained after controlling with covariates (including educational level); this probably indicates that there are European genetic factors (ej: SNPs) modifying the risk of AP in Colombians. Our results highlight the importance of performing Local Admixture Inference analysis in order to estimate the ancestry of specific chromosomal regions in admixed individuals in the study of human evolutionary history and genetic association studies.

This abstract is also presented as Poster C37.

Citation Format: Maria Carolina Sanabria-Salas, Gustavo Adolfo Hernández-Suárez, Adriana Umaña-Pérez, Martha Lucía Serrano-Pérez, Myriam Sánchez de Gómez, Martha Patricia Rojas, Jovanny Zabaleta, Konrad Rawlik, Albert Tenesa. The role of genetic structure in Colombian coastal and Andean populations on disparities in colorectal adenomas and cancer risk. [abstract]. In: Proceedings of the Eighth AACR Conference on The Science of Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; Nov 13-16, 2015; Atlanta, GA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2016;25(3 Suppl):Abstract nr PR08.

Genetic determination of height-mediated mate choice

BACKGROUND

Numerous studies have reported positive correlations among couples for height. This suggests that humans find individuals of similar height attractive. However, the answer to whether the choice of a mate with a similar phenotype is genetically or environmentally determined has been elusive.

RESULTS

Here we provide an estimate of the genetic contribution to height choice in mates in 13,068 genotyped couples. Using a mixed linear model we show that 4.1% of the variation in the mate height choice is determined by a person's own genotype, as expected in a model where one's height determines the choice of mate height. Furthermore, the genotype of an individual predicts their partners' height in an independent dataset of 15,437 individuals with 13% accuracy, which is 64% of the theoretical maximum achievable with a heritability of 0.041. Theoretical predictions suggest that approximately 5% of the heritability of height is due to the positive covariance between allelic effects at different loci, which is caused by assortative mating. Hence, the coupling of alleles with similar effects could substantially contribute to the missing heritability of height.

CONCLUSIONS

These estimates provide new insight into the mechanisms that govern mate choice in humans and warrant the search for the genetic causes of choice of mate height. They have important methodological implications and contribute to the missing heritability debate.

A new tool called DISSECT for analysing large genomic data sets using a Big Data approach

Large-scale genetic and genomic data are increasingly available and the major bottleneck in their analysis is a lack of sufficiently scalable computational tools. To address this problem in the context of complex traits analysis, we present DISSECT. DISSECT is a new and freely available software that is able to exploit the distributed-memory parallel computational architectures of compute clusters, to perform a wide range of genomic and epidemiologic analyses, which currently can only be carried out on reduced sample sizes or under restricted conditions. We demonstrate the usefulness of our new tool by addressing the challenge of predicting phenotypes from genotype data in human populations using mixed-linear model analysis. We analyse simulated traits from 470,000 individuals genotyped for 590,004 SNPs in ∼4 h using the combined computational power of 8,400 processor cores. We find that prediction accuracies in excess of 80% of the theoretical maximum could be achieved with large sample sizes.

Availability of computing power can limit computational analysis of large genetic and genomic datasets. Here, Canela-Xandri, et al. describe a software called DISSECT that is capable of analyzing large-scale genetic data by distributing the work across thousands of networked computers.

Meta-analysis of genome-wide association studies identifies common susceptibility polymorphisms for colorectal and endometrial cancer near SH2B3 and TSHZ1

High-risk mutations in several genes predispose to both colorectal cancer (CRC) and endometrial cancer (EC). We therefore hypothesised that some lower-risk genetic variants might also predispose to both CRC and EC. Using CRC and EC genome-wide association series, totalling 13,265 cancer cases and 40,245 controls, we found that the protective allele [G] at one previously-identified CRC polymorphism, rs2736100 near TERT, was associated with EC risk (odds ratio (OR) = 1.08, P = 0.000167); this polymorphism influences the risk of several other cancers. A further CRC polymorphism near TERC also showed evidence of association with EC (OR = 0.92; P = 0.03). Overall, however, there was no good evidence that the set of CRC polymorphisms was associated with EC risk, and neither of two previously-reported EC polymorphisms was associated with CRC risk. A combined analysis revealed one genome-wide significant polymorphism, rs3184504, on chromosome 12q24 (OR = 1.10, P = 7.23 × 10(-9)) with shared effects on CRC and EC risk. This polymorphism, a missense variant in the gene SH2B3, is also associated with haematological and autoimmune disorders, suggesting that it influences cancer risk through the immune response. Another polymorphism, rs12970291 near gene TSHZ1, was associated with both CRC and EC (OR = 1.26, P = 4.82 × 10(-8)), with the alleles showing opposite effects on the risks of the two cancers.

Evaluation of the linkage-disequilibrium method for the estimation of effective population size when generations overlap: an empirical case

BACKGROUND

Within the genetic methods for estimating effective population size (N e ), the method based on linkage disequilibrium (LD) has advantages over other methods, although its accuracy when applied to populations with overlapping generations is a matter of controversy. It is also unclear the best way to account for mutation and sample size when this method is implemented. Here we have addressed the applicability of this method using genome-wide information when generations overlap by profiting from having available a complete and accurate pedigree from an experimental population of Iberian pigs. Precise pedigree-based estimates of N e were considered as a baseline against which to compare LD-based estimates.

METHODS

We assumed six different statistical models that varied in the adjustments made for mutation and sample size. The approach allowed us to determine the most suitable statistical model of adjustment when the LD method is used for species with overlapping generations. A novel approach used here was to treat different generations as replicates of the same population in order to assess the error of the LD-based N e estimates.

RESULTS

LD-based N e estimates obtained by estimating the mutation parameter from the data and by correcting sample size using the 1/2n term were the closest to pedigree-based estimates. The N e at the time of the foundation of the herd (26 generations ago) was 20.8 ± 3.7 (average and SD across replicates), while the pedigree-based estimate was 21. From that time on, this trend was in good agreement with that followed by pedigree-based N e.

CONCLUSIONS

Our results showed that when using genome-wide information, the LD method is accurate and broadly applicable to small populations even when generations overlap. This supports the use of the method for estimating N e when pedigree information is unavailable in order to effectively monitor and manage populations and to early detect population declines. To our knowledge this is the first study using replicates of empirical data to evaluate the applicability of the LD method by comparing results with accurate pedigree-based estimates.

Recurrent Coding Sequence Variation Explains Only A Small Fraction of the Genetic Architecture of Colorectal Cancer

Whilst common genetic variation in many non-coding genomic regulatory regions are known to impart risk of colorectal cancer (CRC), much of the heritability of CRC remains unexplained. To examine the role of recurrent coding sequence variation in CRC aetiology, we genotyped 12,638 CRCs cases and 29,045 controls from six European populations. Single-variant analysis identified a coding variant (rs3184504) in SH2B3 (12q24) associated with CRC risk (OR = 1.08, P = 3.9 × 10(-7)), and novel damaging coding variants in 3 genes previously tagged by GWAS efforts; rs16888728 (8q24) in UTP23 (OR = 1.15, P = 1.4 × 10(-7)); rs6580742 and rs12303082 (12q13) in FAM186A (OR = 1.11, P = 1.2 × 10(-7) and OR = 1.09, P = 7.4 × 10(-8)); rs1129406 (12q13) in ATF1 (OR = 1.11, P = 8.3 × 10(-9)), all reaching exome-wide significance levels. Gene based tests identified associations between CRC and PCDHGA genes (P < 2.90 × 10(-6)). We found an excess of rare, damaging variants in base-excision (P = 2.4 × 10(-4)) and DNA mismatch repair genes (P = 6.1 × 10(-4)) consistent with a recessive mode of inheritance. This study comprehensively explores the contribution of coding sequence variation to CRC risk, identifying associations with coding variation in 4 genes and PCDHG gene cluster and several candidate recessive alleles. However, these findings suggest that recurrent, low-frequency coding variants account for a minority of the unexplained heritability of CRC.

A new GWAS and meta-analysis with 1000Genomes imputation identifies novel risk variants for colorectal cancer

Genome-wide association studies (GWAS) of colorectal cancer (CRC) have identified 23 susceptibility loci thus far. Analyses of previously conducted GWAS indicate additional risk loci are yet to be discovered. To identify novel CRC susceptibility loci, we conducted a new GWAS and performed a meta-analysis with five published GWAS (totalling 7,577 cases and 9,979 controls of European ancestry), imputing genotypes utilising the 1000 Genomes Project. The combined analysis identified new, significant associations with CRC at 1p36.2 marked by rs72647484 (minor allele frequency [MAF] = 0.09) near CDC42 and WNT4 (P = 1.21 × 10(-8), odds ratio [OR] = 1.21 ) and at 16q24.1 marked by rs16941835 (MAF = 0.21, P = 5.06 × 10(-8); OR = 1.15) within the long non-coding RNA (lncRNA) RP11-58A18.1 and ~500 kb from the nearest coding gene FOXL1. Additionally we identified a promising association at 10p13 with rs10904849 intronic to CUBN (MAF = 0.32, P = 7.01 × 10(-8); OR = 1.14). These findings provide further insights into the genetic and biological basis of inherited genetic susceptibility to CRC. Additionally, our analysis further demonstrates that imputation can be used to exploit GWAS data to identify novel disease-causing variants.

Modulation of genetic associations with serum urate levels by body-mass-index in humans

We tested for interactions between body mass index (BMI) and common genetic variants affecting serum urate levels, genome-wide, in up to 42569 participants. Both stratified genome-wide association (GWAS) analyses, in lean, overweight and obese individuals, and regression-type analyses in a non BMI-stratified overall sample were performed. The former did not uncover any novel locus with a major main effect, but supported modulation of effects for some known and potentially new urate loci. The latter highlighted a SNP at RBFOX3 reaching genome-wide significant level (effect size 0.014, 95% CI 0.008-0.02, Pinter= 2.6 x 10-8). Two top loci in interaction term analyses, RBFOX3 and ERO1LB-EDARADD, also displayed suggestive differences in main effect size between the lean and obese strata. All top ranking loci for urate effect differences between BMI categories were novel and most had small magnitude but opposite direction effects between strata. They include the locus RBMS1-TANK (men, Pdifflean-overweight= 4.7 x 10-8), a region that has been associated with several obesity related traits, and TSPYL5 (men, Pdifflean-overweight= 9.1 x 10-8), regulating adipocytes-produced estradiol. The top-ranking known urate loci was ABCG2, the strongest known gout risk locus, with an effect halved in obese compared to lean men (Pdifflean-obese= 2 x 10-4). Finally, pathway analysis suggested a role for N-glycan biosynthesis as a prominent urate-associated pathway in the lean stratum. These results illustrate a potentially powerful way to monitor changes occurring in obesogenic environment.