GWAS Hits Research Articles

SliceIt: A genome-wide resource and visualization tool to design CRISPR/Cas9 screens for editing protein-RNA interaction sites in the human genome.

Several protein-RNA cross linking protocols have been established in recent years to delineate the molecular interaction of an RNA Binding Protein (RBP) and its target RNAs. However, functional dissection of the role of the RBP binding sites in modulating the post-transcriptional fate of the target RNA remains challenging. CRISPR/Cas9 genome editing system is being commonly employed to perturb both coding and noncoding regions in the genome. With the advancements in genome-scale CRISPR/Cas9 screens, it is now possible to not only perturb specific binding sites but also probe the global impact of protein-RNA interaction sites across cell types. Here, we present SliceIt (http://sliceit.soic.iupui.edu/), a database of in silico sgRNA (single guide RNA) library to facilitate conducting such high throughput screens. SliceIt comprises of ~4.8 million unique sgRNAs with an estimated range of 2-8 sgRNAs designed per RBP binding site, for eCLIP experiments of >100 RBPs in HepG2 and K562 cell lines from the ENCODE project. SliceIt provides a user friendly environment, developed using advanced search engine framework, Elasticsearch. It is available in both table and genome browser views facilitating the easy navigation of RBP binding sites, designed sgRNAs, exon expression levels across 53 human tissues along with prevalence of SNPs and GWAS hits on binding sites. Exon expression profiles enable examination of locus specific changes proximal to the binding sites. Users can also upload custom tracks of various file formats directly onto genome browser, to navigate additional genomic features in the genome and compare with other types of omics profiles. All the binding site-centric information is dynamically accessible via "search by gene", "search by coordinates" and "search by RBP" options and readily available to download. Validation of the sgRNA library in SliceIt was performed by selecting RBP binding sites in Lipt1 gene and designing sgRNAs. Effect of CRISPR/Cas9 perturbations on the selected binding sites in HepG2 cell line, was confirmed based on altered proximal exon expression levels using qPCR, further supporting the utility of the resource to design experiments for perturbing protein-RNA interaction networks. Thus, SliceIt provides a one-stop repertoire of guide RNA library to perturb RBP binding sites, along with several layers of functional information to design both low and high throughput CRISPR/Cas9 screens, for studying the phenotypes and diseases associated with RBP binding sites.

The inherited variations of a p53-responsive enhancer in 13q12.12 confer lung cancer risk by attenuating TNFRSF19 expression

BackgroundInherited factors contribute to lung cancer risk, but the mechanism is not well understood. Defining the biological consequence of GWAS hits in cancers is a promising strategy to elucidate the inherited mechanisms of cancers. The tag-SNP rs753955 (A>G) in 13q12.12 is highly associated with lung cancer risk in the Chinese population. Here, we systematically investigate the biological significance and the underlying mechanism behind 13q12.12 risk locus in vitro and in vivo.ResultsWe characterize a novel p53-responsive enhancer with lung tissue cell specificity in a 49-kb high linkage disequilibrium block of rs753955. This enhancer harbors 3 highly linked common inherited variations (rs17336602, rs4770489, and rs34354770) and six p53 binding sequences either close to or located between the variations. The enhancer effectively protects normal lung cell lines against pulmonary carcinogen NNK-induced DNA damages and malignant transformation by upregulating TNFRSF19 through chromatin looping. These variations significantly weaken the enhancer activity by affecting its p53 response, especially when cells are exposed to NNK. The effect of the mutant enhancer alleles on TNFRSF19 target gene in vivo is supported by expression quantitative trait loci analysis of 117 Chinese NSCLC samples and GTEx data. Differentiated expression of TNFRSF19 and its statistical significant correlation with tumor TNM staging and patient survival indicate a suppressor role of TNFRSF19 in lung cancer.ConclusionThis study provides evidence of how the inherited variations in 13q12.12 contribute to lung cancer risk, highlighting the protective roles of the p53-responsive enhancer-mediated TNFRSF19 activation in lung cells under carcinogen stress.

Comprehensive Multiple eQTL Detection and Its Application to GWAS Interpretation.

Expression QTL (eQTL) detection has emerged as an important tool for unraveling the relationship between genetic risk factors and disease or clinical phenotypes. Most studies are predicated on the assumption that only a single causal variant explains the association signal in each interval. This greatly simplifies the statistical modeling, but is liable to biases in scenarios where multiple local causal-variants are responsible. Here, our primary goal was to address the prevalence of secondary cis-eQTL signals regulating peripheral blood gene expression locally, utilizing two large human cohort studies, each >2500 samples with accompanying whole genome genotypes. The CAGE (Consortium for the Architecture of Gene Expression) dataset is a compendium of Illumina microarray studies, and the Framingham Heart Study is a two-generation Affymetrix dataset. We also describe Bayesian colocalization analysis of the extent of sharing of cis-eQTL detected in both studies as well as with the BIOS RNAseq dataset. Stepwise conditional modeling demonstrates that multiple eQTL signals are present for ∼40% of over 3500 eGenes in both microarray datasets, and that the number of loci with additional signals reduces by approximately two-thirds with each conditioning step. Although <20% of the peak signals across platforms fine map to the same credible interval, the colocalization analysis finds that as many as 50-60% of the primary eQTL are actually shared. Subsequently, colocalization of eQTL signals with GWAS hits detected 1349 genes whose expression in peripheral blood is associated with 591 human phenotype traits or diseases, including enrichment for genes with regulatory functions. At least 10%, and possibly as many as 40%, of eQTL-trait colocalized signals are due to nonprimary cis-eQTL peaks, but just one-quarter of these colocalization signals replicated across the gene expression datasets. Our results are provided as a web-based resource for visualization of multi-site regulation of gene expression and its association with human complex traits and disease states.

Evidence for Recent Polygenic Selection on Educational Attainment and Intelligence Inferred from Gwas Hits: A Replication of Previous Findings Using Recent Data

Genetic variants identified by three large genome-wide association studies (GWAS) of educational attainment (EA) were used to test a polygenic selection model. Weighted and unweighted polygenic scores (PGS) were calculated and compared across populations using data from the 1000 Genomes (n = 26), HGDP-CEPH (n = 52) and gnomAD (n = 8) datasets. The PGS from the largest EA GWAS was highly correlated to two previously published PGSs (r = 0.96–0.97, N = 26). These factors are both highly predictive of average population IQ (r = 0.9, N = 23) and Learning index (r = 0.8, N = 22) and are robust to tests of spatial autocorrelation. Monte Carlo simulations yielded highly significant p values. In the gnomAD samples, the correlation between PGS and IQ was almost perfect (r = 0.98, N = 8), and ANOVA showed significant population differences in allele frequencies with positive effect. Socioeconomic variables slightly improved the prediction accuracy of the model (from 78–80% to 85–89%), but the PGS explained twice as much of the variance in IQ compared to socioeconomic variables. In both 1000 Genomes and gnomAD, there was a weak trend for lower GWAS significance SNPs to be less predictive of population IQ. Additionally, a subset of SNPs were found in the HGDP-CEPH sample (N = 127). The analysis of this sample yielded a positive correlation with latitude and a low negative correlation with distance from East Africa. This study provides robust results after accounting for spatial autocorrelation with Fst distances and random noise via an empirical Monte Carlo simulation using null SNPs.

Evidence for Recent Polygenic Selection on Educational Attainment and Intelligence Inferred from Gwas Hits: A Replication of Previous Findings Using Recent Data

Genetic variants identified by three large genome-wide association studies (GWAS) of educational attainment (EA) were used to test a polygenic selection model. Weighted and unweighted polygenic scores (PGS) were calculated and compared across populations using data from the 1000 Genomes (n = 26), HGDP-CEPH (n = 52) and gnomAD (n = 8) datasets. The PGS from the largest EA GWAS was highly correlated to two previously published PGSs (r = 0.96–0.97, N = 26). These factors are both highly predictive of average population IQ (r = 0.9, N = 23) and Learning index (r = 0.8, N = 22) and are robust to tests of spatial autocorrelation. Monte Carlo simulations yielded highly significant p values. In the gnomAD samples, the correlation between PGS and IQ was almost perfect (r = 0.98, N = 8), and ANOVA showed significant population differences in allele frequencies with positive effect. Socioeconomic variables slightly improved the prediction accuracy of the model (from 78–80% to 85–89%), but the PGS explained twice as much of the variance in IQ compared to socioeconomic variables. In both 1000 Genomes and gnomAD, there was a weak trend for lower GWAS significance SNPs to be less predictive of population IQ. Additionally, a subset of SNPs were found in the HGDP-CEPH sample (N = 127). The analysis of this sample yielded a positive correlation with latitude and a low negative correlation with distance from East Africa. This study provides robust results after accounting for spatial autocorrelation with Fst distances and random noise via an empirical Monte Carlo simulation using null SNPs.

Functional SNPs in the Human Autoimmunity-Associated Locus 17q12-21.

Genome-wide association studies (GWASes) revealed several single-nucleotide polymorphisms (SNPs) in the human 17q12-21 locus associated with autoimmune diseases. However, follow-up studies are still needed to identify causative SNPs directly mediating autoimmune risk in the locus. We have chosen six SNPs in high linkage disequilibrium with the GWAS hits that showed the strongest evidence of causality according to association pattern and epigenetic data and assessed their functionality in a local genomic context using luciferase reporter system. We found that rs12946510, rs4795397, rs12709365, and rs8067378 influenced the reporter expression level in leukocytic cell lines. The strongest effect visible in three distinct cell types was observed for rs12946510 that is predicted to alter MEF2A/C and FOXO1 binding sites.

GOPHER: Generator Of Probes for capture Hi-C Experiments at high Resolution

BackgroundTarget enrichment combined with chromosome conformation capturing methodologies such as capture Hi-C (CHC) can be used to investigate spatial layouts of genomic regions with high resolution and at scalable costs. A common application of CHC is the investigation of regulatory elements that are in contact with promoters, but CHC can be used for a range of other applications. Therefore, probe design for CHC needs to be adapted to experimental needs, but no flexible tool is currently available for this purpose.ResultsWe present a Java desktop application called GOPHER (Generator Of Probes for capture Hi-C Experiments at high Resolution) that implements three strategies for CHC probe design. GOPHER’s simple approach is similar to the probe design of previous approaches that employ CHC to investigate all promoters, with one probe being placed at each margin of a single digest that overlaps the transcription start site (TSS) of each promoter. GOPHER’s simple-patched approach extends this methodology with a heuristic that improves coverage of viewpoints in which the TSS is located near to one of the boundaries of the digest. GOPHER’s extended approach is intended mainly for focused investigations of smaller gene sets. GOPHER can also be used to design probes for regions other than TSS such as GWAS hits or large blocks of genomic sequence. GOPHER additionally provides a number of features that allow users to visualize and edit viewpoints, and outputs a range of files useful for documentation, ordering probes, and downstream analysis.ConclusionGOPHER is an easy-to-use and robust desktop application for CHC probe design. Source code and a precompiled executable can be downloaded from the GOPHER GitHub page at https://github.com/TheJacksonLaboratory/Gopher.

SA91 - INCREASED PREDICTED C4A EXPRESSION IS ASSOCIATED WITH COGNITIVE DEFICIT IN BOTH SCHIZOPHRENIA AND ALZHEIMER'S DISEASE

Background Recently, Sekar et al. (Nature, 2016) reported that the top GWAS hit for schizophrenia in the Major Histocompatibility Complex (MHC) locus implicated structural variants in the C4 gene which are associated with C4A expression and may affect synaptic pruning. Synapse loss is associated with cognitive decline in a number of disorders, including Alzheimer's disease and schizophrenia. We hypothesised that C4A expression predicted from C4 structural alleles is associated with cognition. We tested this in the Western Australian Family Study of Schizophrenia (WAFSS) (n=770, including 402 schizophrenia cases and 368 controls), and the Australian Imaging, Biomarkers and Lifestyle Study (AIBL) (n=1,112, including 211 Alzheimer's disease cases, 133 with mild cognitive impairment and 768 controls). Methods Sekar et al. showed that C4 structural alleles could be imputed from GWAS data with an accuracy of ~70%. We used 222 reference haplotypes with C4 structural alleles measured by Sekar et al. to impute C4 alleles in all individuals using Beagle. C4A expression was predicted for each individual using the regression coefficients calculated by Sekar et al. Composite measures of cognition were available for both WAFSS and AIBL (Hallmeyer et al., Am J Hum Genet. 2005; Burnham et al., J Alzheimers Dis. 2015). Linear regression was used to assess their relationship with predicted C4A expression. P values for these relationships were calculated using linear mixed models to account for the relatedness between some WAFSS participants, and repeated measurements in the AIBL dataset. All analyses were adjusted for case status, age, sex, and education. Results Although mean C4A expression was not significantly different between schizophrenia cases and controls in the WAFSS (P=0.7), cases were overrepresented in those with the highest C4A expression levels. There was a small but consistent association between increased cognitive deficit and increased levels of C4A in both the WAFSS and the AIBL samples (P Discussion These data suggest that C4 structural variants previously shown to be associated with schizophrenia may specifically implicate the cognitive deficit which is a core feature of schizophrenia. Further, our finding that a similar relationship between C4A levels and cognition exists in patients with schizophrenia and Alzheimer's disease suggests that the locus may be pleiotropic and have implications for a range of neuropsychiatric disorders.

A Pipeline for Classifying Deleterious Coding Mutations in Agricultural Plants.

The impact of deleterious variation on both plant fitness and crop productivity is not completely understood and is a hot topic of debates. The deleterious mutations in plants have been solely predicted using sequence conservation methods rather than function-based classifiers due to lack of well-annotated mutational datasets in these organisms. Here, we developed a machine learning classifier based on a dataset of deleterious and neutral mutations in Arabidopsis thaliana by extracting 18 informative features that discriminate deleterious mutations from neutral, including 9 novel features not used in previous studies. We examined linear SVM, Gaussian SVM, and Random Forest classifiers, with the latter performing best. Random Forest classifiers exhibited a markedly higher accuracy than the popular PolyPhen-2 tool in the Arabidopsis dataset. Additionally, we tested whether the Random Forest, trained on the Arabidopsis dataset, accurately predicts deleterious mutations in Orýza sativa and Pisum sativum and observed satisfactory levels of performance accuracy (87% and 93%, respectively) higher than obtained by the PolyPhen-2. Application of Transfer learning in classifiers did not improve their performance. To additionally test the performance of the Random Forest classifier across different angiosperm species, we applied it to annotate deleterious mutations in Cicer arietinum and validated them using population frequency data. Overall, we devised a classifier with the potential to improve the annotation of putative functional mutations in QTL and GWAS hit regions, as well as for the evolutionary analysis of proliferation of deleterious mutations during plant domestication; thus optimizing breeding improvement and development of new cultivars.

PolyQTL: Bayesian multiple eQTL detection with control for population structure and sample relatedness.

Expression quantitative loci (eQTL) are being used widely to annotate and interpret GWAS hits. Recent studies have demonstrated that individual gene expression is often regulated by multiple independent cis-acting eQTL. Diverse methods, frequentist and Bayesian, have already been developed to simultaneously detect and fine-map such multiple eQTL, but most of these ignore sample relatedness and potential population structure. This can result in false positives and disrupt the accuracy of fine-mapping. Here we introduce PolyQTL software for identifying and estimating eQTL effects. The package incorporates a genetic relatedness matrix to remove the influence of population structure and sample relatedness, while utilizing a Bayesian multiple eQTL detection pipeline to identify the most plausible candidate causal variants at one or more independent loci influencing abundance of a transcript. Simulations demonstrate that our approach improves the rate of discovery of causal variants relative to methods that do not account for relatedness. The software is written in C++, and freely available for download at https://github.com/jxzb1988/PolyQTL.

Characterization of Coding and Noncoding Variants for Human CKD Using Novel Strategies

Interpreting the mechanism of genetic variants is one of the greatest challenges impeding the analysis of the rapidly increasing volume of patients' genomic data, particularly for rare variants that do not reach GWAS significance due to low population frequencies. There are 153 GWAS hits for altered kidney function due to commonly inherited genetic variants, yet minimal knowledge of the mechanism of these variations is known at the current time. Utilizing a computational strategy to filter 3,921 genetic variants that are found within linkage disequilibrium of the GWAS hits we have nominated 4 damaging protein coding variants and more importantly 30 noncoding variants predicted to alter transcription factor based gene regulation. One of these noncoding variants, rs17319721 associated with risk of chronic kidney disease (CKD), is found near the SHROOM3 gene and is thought to play a functional role in podocytes of the kidney. In this study we show this variant falls upstream of a novel transcriptional start site that results in a shorter SHROOM3 isoform lacking the PDZ domain. This variant disrupts binding of TCF7L2 in podocytes and the single variant (rs17319721) alters transcription levels of SHROOM3 as determined by variant mutation into the genome using CRISPR/Cas9 technology.To begin deciphering the role of rare variants within human genomes we performed a full assessment of the ExAC database for &gt;60,000 sequenced human exomes, revealing several coding variants in SHROOM3 that are likely to alter function, including a coding variant (P1244L) we show to have association to CKD in humans. We determined that P1244L attenuates the interaction of SHROOM3 with 14‐3‐3 binding and alters signaling through the Hippo pathway, a known mediator of CKD. Animal studies show a loss of function in zebrafish kidney due to the variant, resulting in increased glomerular permeability. These data demonstrate multiple new SHROOM3‐dependent genetic and molecular mechanisms that regulate CKD and demonstrate a novel analytical pipeline with broad application to systematically characterizing risk mechanisms of CKD and other complex diseases.Support or Funding InformationSupport for this study was from NIH‐K01ES025435 (to JWP), NIH‐R01HL069321 (to HJJ), NIH‐R01EY014167 (to BL), the Collaborative Research Centre 1093 through the Deutsche Forschungsgemeinschaft (DFG, to CO), and HudsonAlpha Institute for Biotechnology.This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.

P164 USING EXOME SEQUENCING TO EXPAND THE GENETIC ARCHITECTURE OF INFLAMMATORY BOWEL DISEASE

IBD studies over the past decade have confirmed association to 250 gene loci. A handful of associations have led to specific validated functional variants highlighting intracellular response to microbes and regulation of adaptive immunity in IBD pathogenesis. For the vast majority, however, the specific implicated gene and causal functional variants remain unknown. In partnership with IBD researchers around the world, we launched an exome sequencing initiative to define the full allelic spectrum of protein-altering variation in genes associated to CD and/or UC, assess their role in clinical course and response to therapy, and to determine whether truncating variants confer risk or protection in each IBD gene in order to highlight opportune therapeutic targets. We have already completed exomes of 13,000 IBD cases providing a high-resolution view of coding variation at each GWAS hit and demonstrated a convincing excess of rare exome signal collectively. The cases are drawn from individual substudies that focus on isolated populations (Ashkenazi, Finnish, French-Canadian), admixed populations and clinical extremes, each providing unique opportunities for discovery. Early findings include novel protective truncating variants, the complete allelic series (including unique founder population alleles), non-additive inheritance models at known genes such as NOD2, overlooked low-frequency coding variants that explain GWAS hits (PRDM1, NRIP1). The integration of low frequency and rare functional variants with GWAS is moving us much closer towards completion of the genetic architecture of IBD. Early analyses of the data have revealed novel non-coding associations in known IBD genes as well as coding variants that implicate genes at loci in which the ‘causative’ gene was unknown. Furthermore, initial results have suggested variation in enrichment of different processes across different ethnicities.

Tcf7l2 plays pleiotropic roles in the control of glucose homeostasis, pancreas morphology, vascularization and regeneration

Type 2 diabetes (T2D) is a disease characterized by impaired insulin secretion. The Wnt signaling transcription factor Tcf7l2 is to date the T2D-associated gene with the largest effect on disease susceptibility. However, the mechanisms by which TCF7L2 variants affect insulin release from β-cells are not yet fully understood. By taking advantage of a tcf7l2 zebrafish mutant line, we first show that these animals are characterized by hyperglycemia and impaired islet development. Moreover, we demonstrate that the zebrafish tcf7l2 gene is highly expressed in the exocrine pancreas, suggesting potential bystander effects on β-cell growth, differentiation and regeneration. Finally, we describe a peculiar vascular phenotype in tcf7l2 mutant larvae, characterized by significant reduction in the average number and diameter of pancreatic islet capillaries. Overall, the zebrafish Tcf7l2 mutant, characterized by hyperglycemia, pancreatic and vascular defects, and reduced regeneration proves to be a suitable model to study the mechanism of action and the pleiotropic effects of Tcf7l2, the most relevant T2D GWAS hit in human populations.

Gene Network Dysregulation in Dorsolateral Prefrontal Cortex Neurons of Humans with Cocaine Use Disorder

Metabolic and functional alterations of neurons in the dorsolateral prefrontal cortex (dlPFC) are thought to contribute to impulsivity, which is a hallmark of addictive behaviors that underlie compulsive drug seeking and taking in humans. To determine if there is a transcriptional signature in dlPFC neurons of humans with cocaine use disorder, we performed total RNA-sequencing on neuronal nuclei isolated from post-mortem dlPFC of cocaine addicts and healthy controls. Our results point toward a transcriptional mechanism whereby cocaine alters specific gene networks in dlPFC neurons. In particular, we identified an AP-1 regulated transcriptional network in dlPFC neurons associated with cocaine use disorder that contains several differentially expressed hub genes. Several of these hub genes are GWAS hits for traits that might involve dysfunction of brain reward circuitry (Body-Mass Index, Obesity) or dlPFC (Bipolar disorder, Schizophrenia). Further study is warranted to determine their potential pathophysiological role in cocaine addiction.

Genomic and phenotypic analysis of Vavilov\u2019s historic landraces reveals the impact of environment and genomic islands of agronomic traits

The Vavilov Institute of Plant Genetic Resources (VIR), in St. Petersburg, Russia, houses a unique genebank, with historical collections of landraces. When they were collected, the geographical distribution and genetic diversity of most crops closely reflected their historical patterns of cultivation established over the preceding millennia. We employed a combination of genomics, computational biology and phenotyping to characterize VIR’s 147 chickpea accessions from Turkey and Ethiopia, representing chickpea’s center of origin and a major location of secondary diversity. Genotyping by sequencing identified 14,059 segregating polymorphisms and genome-wide association studies revealed 28 GWAS hits in potential candidate genes likely to affect traits of agricultural importance. The proportion of polymorphisms shared among accessions is a strong predictor of phenotypic resemblance, and of environmental similarity between historical sampling sites. We found that 20 out of 28 polymorphisms, associated with multiple traits, including days to maturity, plant phenology, and yield-related traits such as pod number, localized to chromosome 4. We hypothesize that selection and introgression via inadvertent hybridization between more and less advanced morphotypes might have resulted in agricultural improvement genes being aggregated to genomic ‘agro islands’, and in genotype-to-phenotype relationships resembling widespread pleiotropy.

Genetic variations related to maternal whole blood mitochondrial DNA copy number: a genome-wide and candidate gene study

We conducted genome-wide (GWAS) and candidate gene association studies of maternal mitochondrial DNA copy number. Maternal peripheral blood was collected during labor and delivery admission from 471 participants of a placental abruption case-control study conducted in Lima, Peru. Single nucleotide polymorphism (SNP) genotyping was performed using the Illumina Cardio-Metabo Chip. Whole blood mitochondrial DNA (mtDNA) copy number was measured using qRT-PCR techniques. We evaluated 119,629 SNPs in the GWAS and 161 SNPs (in 29 mitochondrial biogenesis and oxidative phosphorylation genes) in the candidate association study. Top hits from GWAS and the candidate gene study were selected to compute weighted genetic risk scores (wGRS). Linear regression models were used to calculate effect size estimates and related nominal p values. The top hit in our GWAS was chr19:51063065 in FOXA3 (empirical p values = 2.20e − 6). A total of 134 SNPs had p values < 0.001 including rs17111633 in CNNM1 (p values = 6.32e − 6) and chr19:51083059 in MYPOP (p values = 3.23e − 5). In the candidate association study, several SNPs in PPARG, PRKCA, SP1 and THRB were associated with mtDNA copy number (p values < 0.05). mtDNA copy number was significantly associated with wGRS based on top GWAS hits (β = 0.49, 95% CI:0.38–0.60, p < 0.001). Variations in nuclear DNA are potentially associated with maternal mtDNA copy number.

Mouse Models of Human GWAS Hits for Obesity and Diabetes in the Post Genomic Era: Time for Reevaluation.

Mouse Models of Human GWAS Hits for Obesity and Diabetes in the Post Genomic Era: Time for Reevaluation.

High-Throughput Characterization of Blood Serum Proteomics of IBD Patients with Respect to Aging and Genetic Factors.

To date, no large scale, systematic description of the blood serum proteome has been performed in inflammatory bowel disease (IBD) patients. By using microarray technology, a more complete description of the blood proteome of IBD patients is feasible. It may help to achieve a better understanding of the disease. We analyzed blood serum profiles of 1128 proteins in IBD patients of European descent (84 Crohn’s Disease (CD) subjects and 88 Ulcerative Colitis (UC) subjects) as well as 15 healthy control subjects, and linked protein variability to patient age (all cohorts) and genetic components (genotype data generated from CD patients). We discovered new, previously unreported aging-associated proteomic traits (such as serum Albumin level), confirmed previously reported results from different tissues (i.e., upregulation of APOE with aging), and found loss of regulation of MMP7 in CD patients. In carrying out a genome wide genotype-protein association study (proteomic Quantitative Trait Loci, pQTL) within the CD patients, we identified 41 distinct proteomic traits influenced by cis pQTLs (underlying SNPs are referred to as pSNPs). Significant overlaps between pQTLs and cis eQTLs corresponding to the same gene were observed and in some cases the QTL were related to inflammatory disease susceptibility. Importantly, we discovered that serum protein levels of MST1 (Macrophage Stimulating 1) were regulated by SNP rs3197999 (p = 5.96E-10, FDR<5%), an accepted GWAS locus for IBD. Filling the knowledge gap of molecular mechanisms between GWAS hits and disease susceptibility requires systematically dissecting the impact of the locus at the cell, mRNA expression, and protein levels. The technology and analysis tools that are now available for large-scale molecular studies can elucidate how alterations in the proteome driven by genetic polymorphisms cause or provide protection against disease. Herein, we demonstrated this directly by integrating proteomic and pQTLs with existing GWAS, mRNA expression, and eQTL datasets to provide insights into the biological processes underlying IBD and pinpoint causal genetic variants along with their downstream molecular consequences.

Identification of long non-coding RNAs involved in neuronal development and intellectual disability.

Recently, exome sequencing led to the identification of causal mutations in 16–31% of patients with intellectual disability (ID), leaving the underlying cause for many patients unidentified. In this context, the noncoding part of the human genome remains largely unexplored. For many long non-coding RNAs (lncRNAs) a crucial role in neurodevelopment and hence the human brain is anticipated. Here we aimed at identifying lncRNAs associated with neuronal development and ID. Therefore, we applied an integrated genomics approach, harnessing several public epigenetic datasets. We found that the presence of neuron-specific H3K4me3 confers the highest specificity for genes involved in neurodevelopment and ID. Based on the presence of this feature and GWAS hits for CNS disorders, we identified 53 candidate lncRNA genes. Extensive expression profiling on human brain samples and other tissues, followed by Gene Set Enrichment Analysis indicates that at least 24 of these lncRNAs are indeed implicated in processes such as synaptic transmission, nervous system development and neurogenesis. The bidirectional or antisense overlapping orientation relative to multiple coding genes involved in neuronal processes supports these results. In conclusion, we identified several lncRNA genes putatively involved in neurodevelopment and CNS disorders, providing a resource for functional studies.

How far from the SNP may the causative genes be?

While GWAS identify many disease-associated SNPs, using them to decipher disease mechanisms is hindered by the difficulty in mapping SNPs to genes. Most SNPs are in non-coding regions and it is often hard to identify the genes they implicate. To explore how far the SNP may be from the affected genes we used a pathway-based approach. We found that affected genes are often up to 2 Mbps away from the associated SNP, and are not necessarily the closest genes to the SNP. Existing approaches for mapping SNPs to genes leave many SNPs unmapped to genes and reveal only 86 significant phenotype-pathway associations for all known GWAS hits combined. Using the pathway-based approach we propose here allows mapping of virtually all SNPs to genes and reveals 435 statistically significant phenotype-pathway associations. In search for mechanisms that may explain the relationships between SNPs and distant genes, we found that SNPs that are mapped to distant genes have significantly more large insertions/deletions around them than other SNPs, suggesting that these SNPs may sometimes be markers for large insertions/deletions that may affect large genomic regions.