Co-expression in tissue-specific gene networks links genes in cancer-susceptibility loci to known somatic driver genes.

BACKGROUND: The genetic background of cancer remains complex and challenging to integrate. Many somatic mutations within genes are known to cause and drive cancer, while genome-wide association studies (GWAS) of cancer have revealed many germline risk factors associated with cancer. However, the overlap between known somatic driver genes and positional candidate genes from GWAS loci is surprisingly small. We hypothesised that genes from multiple independent cancer GWAS loci should show tissue-specific co-regulation patterns that converge on cancer-specific driver genes. RESULTS: We studied recent well-powered GWAS of breast, prostate, colorectal and skin cancer by estimating co-expression between genes and subsequently prioritising genes that show significant co-expression with genes mapping within susceptibility loci from cancer GWAS. We observed that the prioritised genes were strongly enriched for cancer drivers defined by COSMIC, IntOGen and Dietlein et al. The enrichment of known cancer driver genes was most significant when using co-expression networks derived from non-cancer samples of the relevant tissue of origin. CONCLUSION: We show how genes within risk loci identified by cancer GWAS can be linked to known cancer driver genes through tissue-specific co-expression networks. This provides an important explanation for why seemingly unrelated sets of genes that harbour either germline risk factors or somatic mutations can eventually cause the same type of disease.

KidneyNetwork: using kidney-derived gene expression data to predict and prioritize novel genes involved in kidney disease.

Genetic testing in patients with suspected hereditary kidney disease may not reveal the genetic cause for the disorder as potentially pathogenic variants can reside in genes that are not yet known to be involved in kidney disease. We have developed KidneyNetwork, that utilizes tissue-specific expression to inform candidate gene prioritization specifically for kidney diseases. KidneyNetwork is a novel method constructed by integrating a kidney RNA-sequencing co-expression network of 878 samples with a multi-tissue network of 31,499 samples. It uses expression patterns and established gene-phenotype associations to predict which genes could be related to what (disease) phenotypes in an unbiased manner. We applied KidneyNetwork to rare variants in exome sequencing data from 13 kidney disease patients without a genetic diagnosis to prioritize candidate genes. KidneyNetwork can accurately predict kidney-specific gene functions and (kidney disease) phenotypes for disease-associated genes. The intersection of prioritized genes with genes carrying rare variants in a patient with kidney and liver cysts identified ALG6 as plausible candidate gene. We strengthen this plausibility by identifying ALG6 variants in several cystic kidney and liver disease cases without alternative genetic explanation. We present KidneyNetwork, a publicly available kidney-specific co-expression network with optimized gene-phenotype predictions for kidney disease phenotypes. We designed an easy-to-use online interface that allows clinicians and researchers to use gene expression and co-regulation data and gene-phenotype connections to accelerate advances in hereditary kidney disease diagnosis and research. TRANSLATIONAL STATEMENT: Genetic testing in patients with suspected hereditary kidney disease may not reveal the genetic cause for the patient's disorder. Potentially pathogenic variants can reside in genes not yet known to be involved in kidney disease, making it difficult to interpret the relevance of these variants. This reveals a clear need for methods to predict the phenotypic consequences of genetic variation in an unbiased manner. Here we describe KidneyNetwork, a tool that utilizes tissue-specific expression to predict kidney-specific gene functions. Applying KidneyNetwork to a group of undiagnosed cases identified ALG6 as a candidate gene in cystic kidney and liver disease. In summary, KidneyNetwork can aid the interpretation of genetic variants and can therefore be of value in translational nephrogenetics and help improve the diagnostic yield in kidney disease patients.

Fine-mapping and functional studies highlight potential causal variants for rheumatoid arthritis and type 1 diabetes.

To define potentially causal variants for autoimmune disease, we fine-mapped1,2 76 rheumatoid arthritis (11,475 cases, 15,870 controls)3 and type 1 diabetes loci (9,334 cases, 11,111 controls)4. After sequencing 799 1-kilobase regulatory (H3K4me3) regions within these loci in 568 individuals, we observed accurate imputation for 89% of common variants. We defined credible sets of ≤5 causal variants at 5 rheumatoid arthritis and 10 type 1 diabetes loci. We identified potentially causal missense variants at DNASE1L3, PTPN22, SH2B3, and TYK2, and noncoding variants at MEG3, CD28-CTLA4, and IL2RA. We also identified potential candidate causal variants at SIRPG and TNFAIP3. Using functional assays, we confirmed allele-specific protein binding and differential enhancer activity for three variants: the CD28-CTLA4 rs117701653 SNP, MEG3 rs34552516 indel, and TNFAIP3 rs35926684 indel.

High-throughput identification of noncoding functional SNPs via type IIS enzyme restriction.

Genome-wide association studies (GWAS) have identified many disease-associated noncoding variants, but cannot distinguish functional single-nucleotide polymorphisms (fSNPs) from others that reside incidentally within risk loci. To address this challenge, we developed an unbiased high-throughput screen that employs type IIS enzymatic restriction to identify fSNPs that allelically modulate the binding of regulatory proteins. We coupled this approach, termed SNP-seq, with flanking restriction enhanced pulldown (FREP) to identify regulation of CD40 by three disease-associated fSNPs via four regulatory proteins, RBPJ, RSRC2 and FUBP-1/TRAP150. Applying this approach across 27 loci associated with juvenile idiopathic arthritis, we identified 148 candidate fSNPs, including two that regulate STAT4 via the regulatory proteins SATB2 and H1.2. Together, these findings establish the utility of tandem SNP-seq/FREP to bridge the gap between GWAS and disease mechanism.

Analysis of five chronic inflammatory diseases identifies 27 new associations and highlights disease-specific patterns at shared loci.

We simultaneously investigated the genetic landscape of ankylosing spondylitis, Crohn's disease, psoriasis, primary sclerosing cholangitis and ulcerative colitis to investigate pleiotropy and the relationship between these clinically related diseases. Using high-density genotype data from more than 86,000 individuals of European ancestry, we identified 244 independent multidisease signals, including 27 new genome-wide significant susceptibility loci and 3 unreported shared risk loci. Complex pleiotropy was supported when contrasting multidisease signals with expression data sets from human, rat and mouse together with epigenetic and expressed enhancer profiles. The comorbidities among the five immune diseases were best explained by biological pleiotropy rather than heterogeneity (a subgroup of cases genetically identical to those with another disease, possibly owing to diagnostic misclassification, molecular subtypes or excessive comorbidity). In particular, the strong comorbidity between primary sclerosing cholangitis and inflammatory bowel disease is likely the result of a unique disease, which is genetically distinct from classical inflammatory bowel disease phenotypes.

Association analyses identify 38 susceptibility loci for inflammatory bowel disease and highlight shared genetic risk across populations.

Ulcerative colitis and Crohn's disease are the two main forms of inflammatory bowel disease (IBD). Here we report the first trans-ancestry association study of IBD, with genome-wide or Immunochip genotype data from an extended cohort of 86,640 European individuals and Immunochip data from 9,846 individuals of East Asian, Indian or Iranian descent. We implicate 38 loci in IBD risk for the first time. For the majority of the IBD risk loci, the direction and magnitude of effect are consistent in European and non-European cohorts. Nevertheless, we observe genetic heterogeneity between divergent populations at several established risk loci driven by differences in allele frequency (NOD2) or effect size (TNFSF15 and ATG16L1) or a combination of these factors (IL23R and IRGM). Our results provide biological insights into the pathogenesis of IBD and demonstrate the usefulness of trans-ancestry association studies for mapping loci associated with complex diseases and understanding genetic architecture across diverse populations.

Disentangling the Effects of Colocalizing Genomic Annotations to Functionally Prioritize Non-coding Variants within Complex-Trait Loci.

Identifying genomic annotations that differentiate causal from trait-associated variants is essential to fine mapping disease loci. Although many studies have identified non-coding functional annotations that overlap disease-associated variants, these annotations often colocalize, complicating the ability to use these annotations for fine mapping causal variation. We developed a statistical approach (Genomic Annotation Shifter [GoShifter]) to assess whether enriched annotations are able to prioritize causal variation. GoShifter defines the null distribution of an annotation overlapping an allele by locally shifting annotations; this approach is less sensitive to biases arising from local genomic structure than commonly used enrichment methods that depend on SNP matching. Local shifting also allows GoShifter to identify independent causal effects from colocalizing annotations. Using GoShifter, we confirmed that variants in expression quantitative trail loci drive gene-expression changes though DNase-I hypersensitive sites (DHSs) near transcription start sites and independently through 3' UTR regulation. We also showed that (1) 15%-36% of trait-associated loci map to DHSs independently of other annotations; (2) loci associated with breast cancer and rheumatoid arthritis harbor potentially causal variants near the summits of histone marks rather than full peak bodies; (3) variants associated with height are highly enriched in embryonic stem cell DHSs; and (4) we can effectively prioritize causal variation at specific loci.

Cell Specific eQTL Analysis without Sorting Cells.

The functional consequences of trait associated SNPs are often investigated using expression quantitative trait locus (eQTL) mapping. While trait-associated variants may operate in a cell-type specific manner, eQTL datasets for such cell-types may not always be available. We performed a genome-environment interaction (GxE) meta-analysis on data from 5,683 samples to infer the cell type specificity of whole blood cis-eQTLs. We demonstrate that this method is able to predict neutrophil and lymphocyte specific cis-eQTLs and replicate these predictions in independent cell-type specific datasets. Finally, we show that SNPs associated with Crohn's disease preferentially affect gene expression within neutrophils, including the archetypal NOD2 locus.

Gene expression analysis identifies global gene dosage sensitivity in cancer.

Many cancer-associated somatic copy number alterations (SCNAs) are known. Currently, one of the challenges is to identify the molecular downstream effects of these variants. Although several SCNAs are known to change gene expression levels, it is not clear whether each individual SCNA affects gene expression. We reanalyzed 77,840 expression profiles and observed a limited set of 'transcriptional components' that describe well-known biology, explain the vast majority of variation in gene expression and enable us to predict the biological function of genes. On correcting expression profiles for these components, we observed that the residual expression levels (in 'functional genomic mRNA' profiling) correlated strongly with copy number. DNA copy number correlated positively with expression levels for 99% of all abundantly expressed human genes, indicating global gene dosage sensitivity. By applying this method to 16,172 patient-derived tumor samples, we replicated many loci with aberrant copy numbers and identified recurrently disrupted genes in genomically unstable cancers.

Mediation analysis demonstrates that trans-eQTLs are often explained by cis-mediation: a genome-wide analysis among 1,800 South Asians.

A large fraction of human genes are regulated by genetic variation near the transcribed sequence (cis-eQTL, expression quantitative trait locus), and many cis-eQTLs have implications for human disease. Less is known regarding the effects of genetic variation on expression of distant genes (trans-eQTLs) and their biological mechanisms. In this work, we use genome-wide data on SNPs and array-based expression measures from mononuclear cells obtained from a population-based cohort of 1,799 Bangladeshi individuals to characterize cis- and trans-eQTLs and determine if observed trans-eQTL associations are mediated by expression of transcripts in cis with the SNPs showing trans-association, using Sobel tests of mediation. We observed 434 independent trans-eQTL associations at a false-discovery rate of 0.05, and 189 of these trans-eQTLs were also cis-eQTLs (enrichment P<0.0001). Among these 189 trans-eQTL associations, 39 were significantly attenuated after adjusting for a cis-mediator based on Sobel P<10-5. We attempted to replicate 21 of these mediation signals in two European cohorts, and while only 7 trans-eQTL associations were present in one or both cohorts, 6 showed evidence of cis-mediation. Analyses of simulated data show that complete mediation will be observed as partial mediation in the presence of mediator measurement error or imperfect LD between measured and causal variants. Our data demonstrates that trans-associations can become significantly stronger or switch directions after adjusting for a potential mediator. Using simulated data, we demonstrate that this phenomenon is expected in the presence of strong cis-trans confounding and when the measured cis-transcript is correlated with the true (unmeasured) mediator. In conclusion, by applying mediation analysis to eQTL data, we show that a substantial fraction of observed trans-eQTL associations can be explained by cis-mediation. Future studies should focus on understanding the mechanisms underlying widespread cis-mediation and their relevance to disease biology, as well as using mediation analysis to improve eQTL discovery.

Novel loci affecting iron homeostasis and their effects in individuals at risk for hemochromatosis.

Variation in body iron is associated with or causes diseases, including anaemia and iron overload. Here, we analyse genetic association data on biochemical markers of iron status from 11 European-population studies, with replication in eight additional cohorts (total up to 48,972 subjects). We find 11 genome-wide-significant (P<5 × 10(-8)) loci, some including known iron-related genes (HFE, SLC40A1, TF, TFR2, TFRC, TMPRSS6) and others novel (ABO, ARNTL, FADS2, NAT2, TEX14). SNPs at ARNTL, TF, and TFR2 affect iron markers in HFE C282Y homozygotes at risk for hemochromatosis. There is substantial overlap between our iron loci and loci affecting erythrocyte and lipid phenotypes. These results will facilitate investigation of the roles of iron in disease.

Copper metabolism domain-containing 1 represses genes that promote inflammation and protects mice from colitis and colitis-associated cancer.

BACKGROUND & AIMS: Activation of the transcription factor nuclear factor-κB (NF-κB) has been associated with the development of inflammatory bowel disease (IBD). Copper metabolism MURR1 domain containing 1 (COMMD1), a regulator of various transport pathways, has been shown to limit NF-κB activation. We investigated the roles of COMMD1 in the pathogenesis of colitis in mice and IBD in human beings. METHODS: We created mice with a specific disruption of Commd1 in myeloid cells (Mye-knockout [K/O] mice); we analyzed immune cell populations and functions and expression of genes regulated by NF-κB. Sepsis was induced in Mye-K/O and wild-type mice by cecal ligation and puncture or intraperitoneal injection of lipopolysaccharide (LPS), colitis was induced by administration of dextran sodium sulfate, and colitis-associated cancer was induced by administration of dextran sodium sulfate and azoxymethane. We measured levels of COMMD1 messenger RNA in colon biopsy specimens from 29 patients with IBD and 16 patients without (controls), and validated findings in an independent cohort (17 patients with IBD and 22 controls). We searched for polymorphisms in or near COMMD1 that were associated with IBD using data from the International IBD Genetics Consortium and performed quantitative trait locus analysis. RESULTS: In comparing gene expression patterns between myeloid cells from Mye-K/O and wild-type mice, we found that COMMD1 represses expression of genes induced by LPS. Mye-K/O mice had more intense inflammatory responses to LPS and developed more severe sepsis and colitis, with greater mortality. More Mye-K/O mice with colitis developed colon dysplasia and tumors than wild-type mice. We observed a reduced expression of COMMD1 in colon biopsy specimens and circulating leukocytes from patients with IBD. We associated single-nucleotide variants near COMMD1 with reduced expression of the gene and linked them with increased risk for ulcerative colitis. CONCLUSIONS: Expression of COMMD1 by myeloid cells has anti-inflammatory effects. Reduced expression or function of COMMD1 could be involved in the pathogenesis of IBD.

Correlation of genetic risk and messenger RNA expression in a Th17/IL23 pathway analysis in inflammatory bowel disease.

BACKGROUND: The Th17/IL23 pathway has both genetically and biologically been implicated in the pathogenesis of the inflammatory bowel diseases (IBD), Crohn's disease, and ulcerative colitis. So far, it is unknown whether and how associated risk variants affect expression of the genes encoding for Th17/IL23 pathway proteins. METHODS: Ten IBD-associated SNPs residing near Th17/IL23 genes were used to construct a genetic risk model in 753 Dutch IBD cases and 1045 controls. In an independent cohort of 40 Crohn's disease, 40 ulcerative colitis, and 40 controls, the genetic risk load and presence of IBD were correlated to quantitative PCR-generated messenger RNA (mRNA) expression of 9 representative Th17/IL23 genes in both unstimulated and PMA/CaLo stimulated peripheral blood mononuclear cells. In 1240 individuals with various immunological diseases with whole genome genotype and mRNA-expression data, we also assessed correlation between genetic risk load and differential mRNA expression and sought for SNPs affecting expression of all currently known Th17/IL23 pathway genes (cis-expression quantitative trait locus). RESULTS: The presence of IBD, but not the genetic risk load, was correlated to differential mRNA expression for IL6 in unstimulated peripheral blood mononuclear cells and to IL23A and RORC in response to stimulation. The cis-expression quantitative trait locus analysis showed little evidence for correlation between genetic risk load and mRNA expression of Th17/IL23 genes, because we identified for only 2 of 22 Th17/IL23 genes a cis-expression quantitative trait locus single nucleotide polymorphism that is also associated to IBD (STAT3 and CCR6). CONCLUSIONS: Our results suggest that only the presence of IBD and not the genetic risk load alters mRNA expression levels of IBD-associated Th17/IL23 genes.

Genetics of rheumatoid arthritis contributes to biology and drug discovery.

A major challenge in human genetics is to devise a systematic strategy to integrate disease-associated variants with diverse genomic and biological data sets to provide insight into disease pathogenesis and guide drug discovery for complex traits such as rheumatoid arthritis (RA). Here we performed a genome-wide association study meta-analysis in a total of >100,000 subjects of European and Asian ancestries (29,880 RA cases and 73,758 controls), by evaluating ∼10 million single-nucleotide polymorphisms. We discovered 42 novel RA risk loci at a genome-wide level of significance, bringing the total to 101 (refs 2 - 4). We devised an in silico pipeline using established bioinformatics methods based on functional annotation, cis-acting expression quantitative trait loci and pathway analyses--as well as novel methods based on genetic overlap with human primary immunodeficiency, haematological cancer somatic mutations and knockout mouse phenotypes--to identify 98 biological candidate genes at these 101 risk loci. We demonstrate that these genes are the targets of approved therapies for RA, and further suggest that drugs approved for other indications may be repurposed for the treatment of RA. Together, this comprehensive genetic study sheds light on fundamental genes, pathways and cell types that contribute to RA pathogenesis, and provides empirical evidence that the genetics of RA can provide important information for drug discovery.

Discovery and fine mapping of serum protein loci through transethnic meta-analysis.

Many disorders are associated with altered serum protein concentrations, including malnutrition, cancer, and cardiovascular, kidney, and inflammatory diseases. Although these protein concentrations are highly heritable, relatively little is known about their underlying genetic determinants. Through transethnic meta-analysis of European-ancestry and Japanese genome-wide association studies, we identified six loci at genome-wide significance (p < 5 × 10(-8)) for serum albumin (HPN-SCN1B, GCKR-FNDC4, SERPINF2-WDR81, TNFRSF11A-ZCCHC2, FRMD5-WDR76, and RPS11-FCGRT, in up to 53,190 European-ancestry and 9,380 Japanese individuals) and three loci for total protein (TNFRS13B, 6q21.3, and ELL2, in up to 25,539 European-ancestry and 10,168 Japanese individuals). We observed little evidence of heterogeneity in allelic effects at these loci between groups of European and Japanese ancestry but obtained substantial improvements in the resolution of fine mapping of potential causal variants by leveraging transethnic differences in the distribution of linkage disequilibrium. We demonstrated a functional role for the most strongly associated serum albumin locus, HPN, for which Hpn knockout mice manifest low plasma albumin concentrations. Other loci associated with serum albumin harbor genes related to ribosome function, protein translation, and proteasomal degradation, whereas those associated with serum total protein include genes related to immune function. Our results highlight the advantages of transethnic meta-analysis for the discovery and fine mapping of complex trait loci and have provided initial insights into the underlying genetic architecture of serum protein concentrations and their association with human disease.

A genome-wide association study of circulating galectin-3.

Galectin-3 is a lectin involved in fibrosis, inflammation and proliferation. Increased circulating levels of galectin-3 have been associated with various diseases, including cancer, immunological disorders, and cardiovascular disease. To enhance our knowledge on galectin-3 biology we performed the first genome-wide association study (GWAS) using the Illumina HumanCytoSNP-12 array imputed with the HapMap 2 CEU panel on plasma galectin-3 levels in 3,776 subjects and follow-up genotyping in an additional 3,516 subjects. We identified 2 genome wide significant loci associated with plasma galectin-3 levels. One locus harbours the LGALS3 gene (rs2274273; P = 2.35 × 10(-188)) and the other locus the ABO gene (rs644234; P = 3.65 × 10(-47)). The variance explained by the LGALS3 locus was 25.6% and by the ABO locus 3.8% and jointly they explained 29.2%. Rs2274273 lies in high linkage disequilibrium with two non-synonymous SNPs (rs4644; r(2) = 1.0, and rs4652; r(2) = 0.91) and wet lab follow-up genotyping revealed that both are strongly associated with galectin-3 levels (rs4644; P = 4.97 × 10(-465) and rs4652 P = 1.50 × 10(-421)) and were also associated with LGALS3 gene-expression. The origins of our associations should be further validated by means of functional experiments.