Genome-wide Association Studies Single Nucleotide Polymorphisms Research Articles

Evaluating and improving health equity and fairness of polygenic scores

Polygenic scores (PGSs) are quantitative metrics for predicting phenotypic values, such as human height or disease status. Some PGS methods require only summary statistics of a relevant genome-wide association study (GWAS) for their score. One such method is Lassosum, which inherits the model selection advantages of Lasso to select a meaningful subset of the GWAS single-nucleotide polymorphisms as predictors from their association statistics. However, even efficient scores like Lassosum, when derived from European-based GWASs, are poor predictors of phenotype for subjects of non-European ancestry; that is, they have limited portability to other ancestries. To increase the portability of Lassosum, when GWAS information and estimates of linkage disequilibrium are available for both ancestries, we propose Joint-Lassosum (JLS). In the simulation settings we explore, JLS provides more accurate PGSs compared to other methods, especially when measured in terms of fairness. In analyses of UK Biobank data, JLS was computationally more efficient but slightly less accurate than a Bayesian comparator, SDPRX. Like all PGS methods, JLS requires selection of predictors, which are determined by data-driven tuning parameters. We describe a new approach to selecting tuning parameters and note its relevance for model selection for any PGS. We also draw connections to the literature on algorithmic fairness and discuss how JLS can help mitigate fairness-related harms that might result from the use of PGSs in clinical settings. While no PGS method is likely to be universally portable, due to the diversity of human populations and unequal information content of GWASs for different ancestries, JLS is an effective approach for enhancing portability and reducing predictive bias.

18th International HLA and Immunogenetics Workshop: Report on the SNP-HLA Reference Consortium (SHLARC) component.

The SNP-HLA Reference Consortium (SHLARC), a component of the 18th International HLA and Immunogenetics Workshop, is aimed at collecting diverse and extensive human leukocyte antigen (HLA) data to create custom reference panels and enhance HLA imputation techniques. Genome-wide association studies (GWAS) have significantly contributed to identifying genetic associations with various diseases. The HLA genomic region has emerged as the top locus in GWAS, particularly in immune-related disorders. However, the limited information provided by single nucleotide polymorphisms (SNPs), the hallmark of GWAS, poses challenges, especially in the HLA region, where strong linkage disequilibrium (LD) spans several megabases. HLA imputation techniques have been developed using statistical inference in response to these challenges. These techniques enable the prediction of HLA alleles from genotyped GWAS SNPs. Here we present the SHLARC activities, a collaborative effort to create extensive, and multi-ethnic reference panels to enhance HLA imputation accuracy.

Prioritizing cardiovascular disease-associated variants altering NKX2-5 and TBX5 binding through an integrative computational approach

Cardiovascular diseases (CVDs) are the leading cause of death worldwide and are heavily influenced by genetic factors. Genome-wide association studies (GWAS) have mapped > 90% of CVD-associated variants within the non-coding genome, which can alter the function of regulatory proteins, like transcription factors (TFs). However, due to the overwhelming number of GWAS single nucleotide polymorphisms (SNPs) (>500,000), prioritizing variants for in vitro analysis remains challenging. In this work, we implemented a computational approach that considers support vector machine (SVM)-based TF binding site classification and cardiac expression quantitative trait loci (eQTL) analysis to identify and prioritize potential CVD-causing SNPs. We identified 1,535 CVD-associated SNPs that occur within TF footprints and putative enhancers in the human heart and 14,218 variants in linkage disequilibrium (LD) with genotype-dependent gene expression in cardiac tissue. Using ChIP-seq data from two essential cardiac TFs (NKX2-5 and TBX5) in human induced pluripotent stem cell-derived cardiomyocytes (hIPSC-CM), we trained a large-scale gapped k-mer SVM (LS-GKM-SVM) model to identify CVD-associated SNPs that altered NKX2-5 and TBX5 binding sites. The model was tested by scoring human heart TF genomic footprints within putative enhancers and measuring in vitro binding through electrophoretic mobility shift assay (EMSA). Five variants predicted to alter NKX2-5 (rs59310144, rs6715570, and rs61872084) and TBX5 (rs7612445 and rs7790964) binding were prioritized for in vitro validation based on the magnitude of the predicted change in binding and because they are eQTLs in cardiac tissue. All five variants altered NKX2-5 and TBX5 DNA binding. In summary, we present a bioinformatic approach that considers tissue-specific eQTL analysis and SVM-based TF binding site classification to prioritize CVD-associated variants for in vitro experimental analysis.

Genome- and Exome-Wide Association Studies Revealed Candidate Genes Associated with DaTscan Imaging Features.

Despite remarkable progress in identifying Parkinson's disease (PD) genetic risk loci, the genetic basis of PD remains largely unknown. With the help of the endophenotype approach and using data from dopamine transporter single-photon emission computerized tomography (DaTscan), we identified potentially involved genes in PD. We conducted an imaging genetic study by performing exome-wide association study (EWAS) and genome-wide association study (GWAS) on the specific binding ratio (SBR) of six DaTscan anatomical areas between 489 and 559 subjects of Parkinson's progression markers initiative (PPMI) cohort and 83,623 and 36,845 single-nucleotide polymorphisms (SNPs)/insertion-deletion mutations (INDELs). We also investigated the association of cerebrospinal fluid (CSF) protein concentration of our significant genes with PD progression using PPMI CSF proteome data. Among 83,623 SNPs/INDELs in EWAS, one SNP (rs201465075) on 1 q32.1 locus was significantly (P value = 4.03 × 10-7) associated with left caudate DaTscan SBR, and 33 SNPs were suggestive. Among 36,845 SNPs in GWAS, one SNP (rs12450112) on 17 p.12 locus was significantly (P value = 1.34 × 10-6) associated with right anterior putamen DaTscan SBR, and 39 SNPs were suggestive among which 8 SNPs were intergenic. We found that rs201465075 and rs12450112 are most likely related to IGFN1 and MAP2K4 genes. The protein level of MAP2K4 in the CSF was significantly associated with PD progression in the PPMI cohort; however, proteomic data were not available for the IGFN1 gene. We have shown that particular variants of IGFN1 and MAP2K4 genes may be associated with PD. Since DaTscan imaging could be positive in other Parkinsonian syndromes, caution should be taken when interpreting our results. Future experimental studies are also needed to verify these findings.

Natural allelic variation in the EamA-like transporter, CmSN, is associated with fruit skin netting in melon.

A SNP mutation in CmSN, encoding an EamA-like transporter, is responsible for fruit skin netting in melon. In maturing melon (Cucumis melo L.), the rind becomes reticulated or netted, a unique characteristic that dramatically changes the appearance of the fruit. However, little is known about the molecular basis of fruit skin netting formation in this important cucurbit crop. Here, we conducted map-based cloning of a skin netting (CmSN) locus using segregating populations derived from the cross between the smooth-fruit line H906 and the netted-fruit line H581. The results showed that CmSN was controlled by a single dominant gene and was primarily positioned on melon chromosome 2, within a physical interval of ~ 351kb. Further fine mapping in a large F2 population narrowed this region to a 71-kb region harboring 5 genes. MELO3C010288, which encodes a protein in the EamA-like transporter family, is the best possible candidate gene for the netted phenotype. Two nonsynonymous single nucleotide polymorphisms (SNPs) were identified in the third and sixth exons of the CmSN gene and co-segregated with the skin netting (SN) phenotype among the genetic population. A genome-wide association study (GWAS) determined that CmSN is probably a domestication gene under selective pressure during the subspecies C. melo subsp. melo differentiation. The SNP in the third exon of CmSN (the leading SNP in GWAS) revealed a bi-allelic diversity in natural accessions with SN traits. Our results lay a foundation for deciphering the molecular mechanism underlying the formation of fruit skin netting in melon, as well as provide a strategy for genetic improvement of netted fruit using a marker-assisted selection approach.

CVD-associated SNPs with regulatory potential reveal novel non-coding disease genes

BackgroundCardiovascular diseases (CVDs) are the leading cause of death worldwide. Genome-wide association studies (GWAS) have identified many single nucleotide polymorphisms (SNPs) appearing in non-coding genomic regions in CVDs. The SNPs may alter gene expression by modifying transcription factor (TF) binding sites and lead to functional consequences in cardiovascular traits or diseases. To understand the underlying molecular mechanisms, it is crucial to identify which variations are involved and how they affect TF binding.MethodsThe SNEEP (SNP exploration and analysis using epigenomics data) pipeline was used to identify regulatory SNPs, which alter the binding behavior of TFs and link GWAS SNPs to their potential target genes for six CVDs. The human-induced pluripotent stem cells derived cardiomyocytes (hiPSC-CMs), monoculture cardiac organoids (MCOs) and self-organized cardiac organoids (SCOs) were used in the study. Gene expression, cardiomyocyte size and cardiac contractility were assessed.ResultsBy using our integrative computational pipeline, we identified 1905 regulatory SNPs in CVD GWAS data. These were associated with hundreds of genes, half of them non-coding RNAs (ncRNAs), suggesting novel CVD genes. We experimentally tested 40 CVD-associated non-coding RNAs, among them RP11-98F14.11, RPL23AP92, IGBP1P1, and CTD-2383I20.1, which were upregulated in hiPSC-CMs, MCOs and SCOs under hypoxic conditions. Further experiments showed that IGBP1P1 depletion rescued expression of hypertrophic marker genes, reduced hypoxia-induced cardiomyocyte size and improved hypoxia-reduced cardiac contractility in hiPSC-CMs and MCOs.ConclusionsIGBP1P1 is a novel ncRNA with key regulatory functions in modulating cardiomyocyte size and cardiac function in our disease models. Our data suggest ncRNA IGBP1P1 as a potential therapeutic target to improve cardiac function in CVDs.

Epigenomic profiling of isolated blood cell types reveals highly specific B cell smoking signatures and links to disease risk

BackgroundTobacco smoking alters the DNA methylation profiles of immune cells which may underpin some of the pathogenesis of smoking-associated diseases. To link smoking-driven epigenetic effects in specific immune cell types with disease risk, we isolated six leukocyte subtypes, CD14+ monocytes, CD15+ granulocytes, CD19+ B cells, CD4+ T cells, CD8+ T cells, and CD56+ natural killer cells, from whole blood of 67 healthy adult smokers and 74 nonsmokers for epigenome-wide association study (EWAS) using Illumina 450k and EPIC methylation arrays.ResultsNumbers of smoking-associated differentially methylated sites (smCpGs) at genome-wide significance (p < 1.2 × 10−7) varied widely across cell types, from 5 smCpGs in CD8+ T cells to 111 smCpGs in CD19+ B cells. We found unique smoking effects in each cell type, some of which were not apparent in whole blood. Methylation-based deconvolution to estimate B cell subtypes revealed that smokers had 7.2% (p = 0.033) less naïve B cells. Adjusting for naïve and memory B cell proportions in EWAS and RNA-seq allowed the identification of genes enriched for B cell activation-related cytokine signaling pathways, Th1/Th2 responses, and hematopoietic cancers. Integrating with large-scale public datasets, 62 smCpGs were among CpGs associated with health-relevant EWASs. Furthermore, 74 smCpGs had reproducible methylation quantitative trait loci single nucleotide polymorphisms (SNPs) that were in complete linkage disequilibrium with genome-wide association study SNPs, associating with lung function, disease risks, and other traits.ConclusionsWe observed blood cell-type-specific smCpGs, a naïve-to-memory shift among B cells, and by integrating genome-wide datasets, we identified their potential links to disease risks and health traits.

Predicting brain-regional gene regulatory networks from multi-omics for Alzheimer's disease phenotypes and Covid-19 severity.

Neuroinflammation and immune dysregulation play a key role in Alzheimer's disease (AD) and are also associated with severe Covid-19 and neurological symptoms. Also, genome-wide association studies found many risk single nucleotide polymorphisms (SNPs) for AD and Covid-19. However, our understanding of underlying gene regulatory mechanisms from risk SNPs to AD, Covid-19 and phenotypes is still limited. To this end, we performed an integrative multi-omics analysis to predict gene regulatory networks for major brain regions from population data in AD. Our networks linked transcription factors (TFs) to TF binding sites (TFBSs) on regulatory elements to target genes. Comparative network analyses revealed cross-region-conserved and region-specific regulatory networks, in which many immunological genes are present. Furthermore, we identified a list of AD-Covid genes using our networks involving known and Covid-19 genes. Our machine learning analysis prioritized 36AD-Covid candidate genes for predicting Covid severity. Our independent validation analyses found that these genes outperform known genes for classifying Covid-19 severity and AD. Finally, we mapped genome-wide association study SNPs of AD and severe Covid that interrupt TFBSs on our regulatory networks, revealing potential mechanistic insights of those disease risk variants. Our analyses and results are open-source available, providing an AD-Covid functional genomic resource at the brain region level.

S-22-6: RENAL EXPRESSION OF MICRORNAS AND THEIR ASSOCIATION WITH BLOOD PRESSURE REGULATION - INSIGHTS FROM SMALL RNA-SEQUENCING OF 493 HUMAN KIDNEYS

The kidney is a critical regulator of blood pressure (BP) and a contributor to cardiovascular health. Recently, microRNAs (miRNAs) have emerged as potential mediators of genetic predisposition to cardiovascular and kidney disorders, yet their overall role in blood pressure control has not been fully characterised. We sought to identify and catalogue all renal miRNAs, investigate which of them are genetically regulated and assess whether their expression-modifying single nucleotide polymorphisms (SNPs) overlap with genetic variants associated with BP in previous genome-wide association studies (GWAS). We first characterised the entire renal miRNA transcriptome through de novo small RNA-sequencing of 493 human kidney samples. We then integrated these expression profiles with genotype information to perform expression quantitative trait loci (eQTL) analysis - the largest of its kind - and identify genetically regulated miRNAs and their regulatory SNPs. We then examined the extent to which miRNA-regulating variants overlapped with the curated list of BP-associated GWAS SNPs. We identified 1,459 mature miRNAs expressed in the human kidney, and the top 50 most highly expressed miRNAs accounted for 24.2% of the measured expression. We also discovered that 78% of miRNA genes expressed in the kidney were intragenic to other genes and 58% mapped to an intron of those genes. After correction for multiple testing, our eQTL analysis had identified 140 genetically regulated miRNAs in the kidney. They were controlled by 19,901 unique SNPs (eSNPs) with a total of 21,805 miRNA-eSNP pairs. Functional annotation of miRNA eSNPs demonstrated 2.54-fold enrichment for kidney enhancer regions and 1.69-fold enrichment for kidney promoters when compared to randomly selected SNPs. Through overlap with GWAS SNPs for systolic, diastolic and pulse pressures, we identified 8 kidney BP miRNA eSNPs responsible for the regulation of 9 mature miRNAs. Collectively, we generated a catalogue of miRNAs expressed in the human kidney, annotated novel kidney relevant miRNAs and their regulatory variants and discovered 9 renal microRNAs that may act as mediators of genetic predisposition to high BP.

Causal relationship between insomnia and tuberculosis: A bi-directional Mendelian randomization analysis.

Previous observational studies appear to have established a bi-directional association between sleep disorders and tuberculosis. However, their conclusions are prone to be biased by confounding effects and reverse causation due to the nature of observational studies. Mendelian randomization (MR) approach provides unconfounded estimates of causal effects and overcomes the limitations of observational studies. We performed a bi-directional MR analysis to clarify whether there existed a causal effect of insomnia on tuberculosis, or tuberculosis on insomnia. In forward-direction MR, we chose genome-wide significant (P < .5 × 10-8) and independent (r2 < 0.001) single-nucleotide polymorphisms (SNPs) as instrumental variants (IVs), then extracted effect estimates of these IVs in tuberculosis genome-wide association study (GWAS) dataset to explore causal effect of genetically proxied insomnia on tuberculosis using inverse variance-weighted (IVW), MR-Egger, and weighted median methods. Additionally, we examined robustness and pleiotropy of effect estimates by heterogeneity and sensitivity analysis. Similarly, we investigated causal effect of genetically proxied tuberculosis on insomnia in reverse-direction MR. We revealed no causal relationship between genetically proxied insomnia and tuberculosis using 15 SNPs in forward-direction MR (IVW OR 5.305 [0.100-281.341], P = .410) and reverse-direction MR analysis (ORs and P values were not applicable due to no eligible SNPs in GWAS), with insignificant heterogeneity (Q = 22.6, I2 < 0.001, P = .066) and pleiotropy (intercept = 0.032, SE = 0.057, P = .592) in effect estimates. Our bi-directional MR analysis affirms no causal effect of insomnia on tuberculosis, or tuberculosis on insomnia.

Genome-wide variance quantitative trait locus analysis suggests small interaction effects in blood pressure traits

Genome-wide variance quantitative trait loci (vQTL) analysis complements genome-wide association study (GWAS) and has the potential to identify novel variants associated with the trait, explain additional trait variance and lead to the identification of factors that modulate the genetic effects. I conducted genome-wide analysis of the UK Biobank data and identified 27 vQTLs associated with systolic blood pressure (SBP), diastolic blood pressure (DBP) and pulse pressure (PP). The top single-nucleotide polymorphisms (SNPs) are enriched for expression QTLs (eQTLs) or splicing QTLs (sQTLs) annotated by GTEx, suggesting their regulatory roles in mediating the associations with blood pressure (BP). Of the 27 vQTLs, 14 are known BP-associated QTLs discovered by GWASs. The heteroscedasticity effects of the 13 novel vQTLs are larger than their genetic main effects, which were not detected by existing GWASs. The total R-squared of the 27 top SNPs due to variance heteroscedasticity is 0.28%, compared with 0.50% owing to their main effects. The overall effect size of the variance heteroscedasticity is small in GWAS SNPs compared with their main effects. For the 411, 384 and 285 GWAS SNPs associated with SBP, DBP and PP, respectively, their heteroscedasticity effects were 0.52%, 0.43%, and 0.16%, and their main effects were 5.13%, 5.61%, and 3.75%, respectively. The number and effects of the vQTLs are small, which suggests that the effects of gene–environment and gene–gene interactions are small. The main effects of the SNPs remain the major source of genetic variance for BP, which would probably be true for other complex traits as well.

NEAT-seq: simultaneous profiling of intra-nuclear proteins, chromatin accessibility and gene expression in single cells.

In this work, we describe NEAT-seq (sequencing of nuclear protein epitope abundance, chromatin accessibility and the transcriptome in single cells), enabling interrogation of regulatory mechanisms spanning the central dogma. We apply this technique to profile CD4 memory T cells using a panel of master transcription factors (TFs) that drive T cell subsets and identify examples of TFs with regulatory activity gated by transcription, translation and regulation of chromatin binding. We also link a noncoding genome-wide association study single-nucleotide polymorphism (SNP) within a GATA motif to a putative target gene, using NEAT-seq data to internally validate SNP impact on GATA3 regulation.

Abstract 403: A Common Polymorphism Connects Propionyl-coa Carboxylase To Coronary Artery Disease

Genome-Wide Association studies (GWAS) have identified more than 200 common genetic variants that cumulatively account for approximately 50% of individual risk for coronary artery disease (CAD). This information is relevant to CAD risk assessment but may also provide new insights into the underlying biology of atherosclerosis. The vast majority of these common single nucleotide polymorphisms (SNPs) are in non-coding regions of the genome and distal from protein coding genes; thus mechanistically linking GWAS identified SNPs to CAD is challenging. Here, we have investigated the relationship of rs667920, identified as a top CAD associated SNP in a recent GWAS, to CAD. Conditional analysis, using lipid traits and other phenotypes as covariates, is consistent with the hypothesis that hypercholesterolemia mediates the impact of rs667920 on CAD risk. Although rs667920 is intronic to STAG1, originally denoted as a possible risk gene, it is not associated with altered expression of STAG1 in CAD relevant tissues according to GTEx. Chromatin immunoprecipitation data indicate the presence of enhancer activity overlapping rs667920 in fibroblast and muscle cells, consistent with cis regulation Indeed, this SNP is a significant expression quantitative locus (eQTL) for a neighboring gene, PCCB, encoding the Propionyl-CoA carboxylase beta subunit, in vascular tissues and whole blood, with the common allele rs667920_T being linked to increased expression of PCCB, circulating lipids and CAD, suggesting that lower expression of PCCB may be beneficial. Although its eQTL relationship with rs667920 was considerably weaker, mendelian randomization analysis of whole blood datasets prioritized NCK1, another local gene. Additional experiments are currently underway in our laboratory to validate and complement these preliminary findings.

Epigenomic and Transcriptomic Prioritization of Candidate Obesity-Risk Regulatory GWAS SNPs.

Concern about rising rates of obesity has prompted searches for obesity-related single nucleotide polymorphisms (SNPs) in genome-wide association studies (GWAS). Identifying plausible regulatory SNPs is very difficult partially because of linkage disequilibrium. We used an unusual epigenomic and transcriptomic analysis of obesity GWAS-derived SNPs in adipose versus heterologous tissues. From 50 GWAS and 121,064 expanded SNPs, we prioritized 47 potential causal regulatory SNPs (Tier-1 SNPs) for 14 gene loci. A detailed examination of seven loci revealed that four (CABLES1, PC, PEMT, and FAM13A) had Tier-1 SNPs positioned so that they could regulate use of alternative transcription start sites, resulting in different polypeptides being generated or different amounts of an intronic microRNA gene being expressed. HOXA11 and long noncoding RNA gene RP11-392O17.1 had Tier-1 SNPs in their 3′ or promoter region, respectively, and strong preferences for expression in subcutaneous versus visceral adipose tissue. ZBED3-AS1 had two intragenic Tier-1 SNPs, each of which could contribute to mediating obesity risk through modulating long-distance chromatin interactions. Our approach not only revealed especially credible novel regulatory SNPs, but also helped evaluate previously highlighted obesity GWAS SNPs that were candidates for transcription regulation.

Polygenic risk score for general cognitive function is associated with measures of cognition in South Asians from the LASI-DAD Study.

Genome wide association studies (GWAS) conducted primarily in European Ancestry (EA) have identified hundreds of single nucleotide polymorphisms (SNPs) that are associated with general cognitive function. The association between these SNPs and cognitive function has not yet been evaluated in South Asians yet, either individually or in polygenic risk scores (PRS) which aggregate the effects from many SNPs across the genome. The goal of this study was to investigate whether SNPs identified in EA GWAS, either individually or as a PRS, were associated with a general cognitive factor and the Hindi version of the Mini-Mental State Examination (HMSE) score in 932 South Asians from the Diagnostic Assessment of Dementia for the Longitudinal Aging Study of India (LASI-DAD). Participants were genotyped using the Illumina Global Screening Array and imputed to 1000G Phase 3v5. We used linear models to assess the association between 130 top SNPs from the EA GWAS (p<5e-08) and both measures of cognitive function after controlling for age, gender, and population structure. We also evaluated the association between PRSs using the top GWAS SNPs and the cognitive measures using the same models. Finally, we estimated the variation in cognitive function explained by the cognitive function PRS, Alzheimer's disease (AD) PRSs, and/or APOE e2 and e4 genotypes individually or simultaneously. Preliminary analyses showed that none of the GWAS SNPs were significantly associated either of the cognitive measures after multiple testing correction. The PRS, however, was significantly associated with the general cognitive factor and HMSE score (p<0.025). The PRS explained 0.40% and 0.59% of the variance in the general cognitive factor and HMSE score, and explained 1.50% and 1.85% of the variance when coupled with AD PRSs and APOE genotypes. SNPs identified for cognitive function in EA GWAS may not be as strongly associated in South Asians. However, the genetic risk score for both general cognitive function and AD contribute additively to cognitive function in LASI-DAD participants. Future large scale GWAS of general cognitive function and AD are needed to identify specific risk variants for cognition in South Asians.

Revisiting tandem repeats in psychiatric disorders from perspectives of genetics, physiology, and brain evolution.

Genome-wide association studies (GWASs) have revealed substantial genetic components comprised of single nucleotide polymorphisms (SNPs) in the heritable risk of psychiatric disorders. However, genetic risk factors not covered by GWAS also play pivotal roles in these illnesses. Tandem repeats, which are likely functional but frequently overlooked by GWAS, may account for an important proportion in the "missing heritability" of psychiatric disorders. Despite difficulties in characterizing and quantifying tandem repeats in the genome, studies have been carried out in an attempt to describe impact of tandem repeats on gene regulation and human phenotypes. In this review, we have introduced recent research progress regarding the genomic distribution and regulatory mechanisms of tandem repeats. We have also summarized the current knowledge of the genetic architecture and biological underpinnings of psychiatric disorders brought by studies of tandem repeats. These findings suggest that tandem repeats, in candidate psychiatric risk genes or in different levels of linkage disequilibrium (LD) with psychiatric GWAS SNPs and haplotypes, may modulate biological phenotypes related to psychiatric disorders (e.g., cognitive function and brain physiology) through regulating alternative splicing, promoter activity, enhancer activity and so on. In addition, many tandem repeats undergo tight natural selection in the human lineage, and likely exert crucial roles in human brain evolution. Taken together, the putative roles of tandem repeats in the pathogenesis of psychiatric disorders is strongly implicated, and using examples from previous literatures, we wish to call for further attention to tandem repeats in the post-GWAS era of psychiatric disorders.

Investigation of gene\u2013environment interactions in relation to tic severity

Tourette syndrome (TS) is a neuropsychiatric disorder with involvement of genetic and environmental factors. We investigated genetic loci previously implicated in Tourette syndrome and associated disorders in interaction with pre- and perinatal adversity in relation to tic severity using a case-only (N = 518) design. We assessed 98 single-nucleotide polymorphisms (SNPs) selected from (I) top SNPs from genome-wide association studies (GWASs) of TS; (II) top SNPs from GWASs of obsessive–compulsive disorder (OCD), attention-deficit/hyperactivity disorder (ADHD), and autism spectrum disorder (ASD); (III) SNPs previously implicated in candidate-gene studies of TS; (IV) SNPs previously implicated in OCD or ASD; and (V) tagging SNPs in neurotransmitter-related candidate genes. Linear regression models were used to examine the main effects of the SNPs on tic severity, and the interaction effect of these SNPs with a cumulative pre- and perinatal adversity score. Replication was sought for SNPs that met the threshold of significance (after correcting for multiple testing) in a replication sample (N = 678). One SNP (rs7123010), previously implicated in a TS meta-analysis, was significantly related to higher tic severity. We found a gene–environment interaction for rs6539267, another top TS GWAS SNP. These findings were not independently replicated. Our study highlights the future potential of TS GWAS top hits in gene–environment studies.

Rare Germline Variant in NFATC4 Associated with Familial Chronic Lymphocytic Leukemia

Chronic lymphocytic leukemia (CLL) has one of the highest familial risks of any cancer, with up to eightfold increased risk in first degree relatives of CLL patients. Genome-wide association studies (GWAS) have identified multiple common single nucleotide polymorphisms (SNPs) associated with risk, but these have modest effect. Similarly, identified germline variants associated with disease account for just a small minority of CLL patients, making familial CLL an attractive target for research, that could provide direct insight into pathobiology.We used whole exome sequencing (WES; Illumina) to search for rare germline variants (<1% Minor Allele Frequency) in 36 patients from 17 families with Mendelian-like CLL inheritance, where at least two affected family members were sequenced. Median age at diagnosis was 56.4 (range 41-72), 61% were male, 10/23 (43%) were IGHV -unmutated, and 5/24 (21%) had del17p and/or TP53 mutation. We found 3819 rare variants shared within all affected members of a given family. Of those, 71 non-synonymous variants were shared across at least 2 families, and 39 of these were predicted to be pathogenic by at least two commonly-used phenotype prediction tools. None of these variants are within known somatic CLL driver genes, nor were any found in genes near known CLL GWAS SNPs. In order to prioritize these variants, we assessed whether they were enriched among CLL cases (n = 646) as compared to ethnically matched normal population controls (n=8,920), a dataset we have recently reported (Tiao, Improgo et al, Leukemia). Using Fisher's exact test with Benjamini-Hochberg (BH) correction for multiple tests, we found that 27 of the 71 shared variants across multiple families were also enriched in unrelated CLL patients compared to controls. Among those, a rare variant of nuclear factor of activated T-cells 4 (NFATC4), rs200328372, was the most highly enriched in CLL (OR 20.8, Fisher-q-BH 0.026). This variant affects a splice acceptor site predicted to have a deleterious effect on the protein (FATHMM for non-coding variants). In a pathway analysis (MSigDB, DAVID) of genes carrying shared variants across families, NFATC4 together with SOS1 and PTPN7 were associated with the T-cell receptor, B-cell receptor, and MAP-kinase pathways, suggesting a possible role in CLL pathogenesis.The NFATC4 protein, also known as NFAT3, is part of a DNA-binding transcriptional complex that translocates to the nucleus after activation through dephosphorylation by calcineurin. This complex is involved in the inducible expression of cytokine genes in T cells, including interleukin (IL)-2 and IL-4. While NFATC1 has been implicated in CLL pathogenesis and was associated with more aggressive disease in a mouse model of CLL, the role of NFATC4 has not been elucidated. To further investigate this as well as its association with familial CLL, we compared gene expression profiling (GEP; Affymetrix U133 plus 2.0 array) data between familial and sporadic CLL patients and normal B-cells. While NFATC4 expression did not differ between normal B-cells (n=16) and CLL (n=143), it was significantly down-regulated in familial (n=47) as compared to sporadic (n=96) CLL cases (Mann-Whitney, p=0.005). In the 4 cases that harbor the shared risk variant, GEP results showed additional significant down-regulation of NFATC4 expression (Kruskal-Wallis, p=0.003 for all comparisons) (Figure 1).RNA sequencing (Illumina) demonstrated NFATC4 down-regulation in all CLL samples (not specifically in familial CLL as with GEP; n=100) versus normal B-cells (n=6; Mann-Whitney, p=-0.00024), suggesting a putative role for NFATC4 as a tumor suppressor. Since NFATC4 has over 30 alternatively spliced transcripts potentially affected by the rs200328372 variant, we used Cufflinks software to look at isoform-level RNA sequencing data, available on two relatives who carried this variant, compared to CLL cases and controls. Both relatives had reduced expression of all isoforms (Figure 2), suggesting that this mutation may reduce NFATC4 expression altogether. Studies of protein expression are ongoing.In conclusion, through rare germline variant analysis in familial CLL, we found a potentially deleterious variant of NFATC4 that is enriched in CLL. Subsequently, we used RNA sequencing data to show, for the first time, that NFATC4 expression is decreased in CLL versus normal B-cells, revealing a potential tumor suppressor mechanism in CLL. [Display omitted] DisclosuresBrown:Sun BioPharma: Consultancy, Research Funding; Gilead: Consultancy, Research Funding; Pharmacyclics: Consultancy; Redx: Consultancy; AstraZeneca: Consultancy; Pfizer: Consultancy; Janssen Oncology: Honoraria; AbbVie: Consultancy, Honoraria; Roche/Genentech: Consultancy; Celgene: Consultancy; Janssen: Consultancy; Infinity Pharmaceuticals: Consultancy; Astellas Pharma: Consultancy.

A systematic analysis of protein-altering exonic variants in chronic obstructive pulmonary disease.

Genome-wide association studies (GWASs) have identified regions associated with chronic obstructive pulmonary disease (COPD). GWASs of other diseases have shown an approximately 10-fold overrepresentation of nonsynonymous variants, despite limited exonic coverage on genotyping arrays. We hypothesized that a large-scale analysis of coding variants could discover novel genetic associations with COPD, including rare variants with large effect sizes. We performed a meta-analysis of exome arrays from 218,399 controls and 33,851 moderate-to-severe COPD cases. All exome-wide significant associations were present in regions previously identified by GWAS. We did not identify any novel rare coding variants with large effect sizes. Within GWAS regions on chromosomes 5q, 6p, and 15q, four coding variants were conditionally significant (P < 0.00015) when adjusting for lead GWAS single-nucleotide polymorphisms A common gasdermin B (GSDMB) splice variant (rs11078928) previously associated with a decreased risk for asthma was nominally associated with a decreased risk for COPD [minor allele frequency (MAF) = 0.46, P = 1.8e-4]. Two stop variants in coiled-coil α-helical rod protein 1 (CCHCR1), a gene involved in regulating cell proliferation, were associated with COPD (both P < 0.0001). The SERPINA1 Z allele was associated with a random-effects odds ratio of 1.43 for COPD (95% confidence interval = 1.17-1.74), though with marked heterogeneity across studies. Overall, COPD-associated exonic variants were identified in genes involved in DNA methylation, cell-matrix interactions, cell proliferation, and cell death. In conclusion, we performed the largest exome array meta-analysis of COPD to date and identified potential functional coding variants. Future studies are needed to identify rarer variants and further define the role of coding variants in COPD pathogenesis.

Sequencing at lymphoid neoplasm susceptibility loci maps six myeloma risk genes.

Inherited genetic risk factors play a role in multiple myeloma (MM), yet considerable missing heritability exists. Rare risk variants at genome-wide association study (GWAS) loci are a new avenue to explore. Pleiotropy between lymphoid neoplasms (LNs) has been suggested in family history and genetic studies, but no studies have interrogated sequencing for pleiotropic genes or rare risk variants. Sequencing genetically enriched cases can help discover rarer variants. We analyzed exome sequencing in familial or early-onset MM cases to identify rare, functionally relevant variants near GWAS loci for a range of LNs. A total of 149 distinct and significant LN GWAS loci have been published. We identified six recurrent, rare, potentially deleterious variants within 5 kb of significant GWAS single nucleotide polymorphisms in 75 MM cases. Mutations were observed in BTNL2, EOMES, TNFRSF13B, IRF8, ACOXL and TSPAN32. All six genes replicated in an independent set of 255 early-onset MM or familial MM or precursor cases. Expansion of our analyses to the full length of these six genes resulted in a list of 39 rare and deleterious variants, seven of which segregated in MM families. Three genes also had significant rare variant burden in 733 sporadic MM cases compared with 935 control individuals: IRF8 (P = 1.0 × 10−6), EOMES (P = 6.0 × 10−6) and BTNL2 (P = 2.1 × 10−3). Together, our results implicate six genes in MM risk, provide support for genetic pleiotropy between LN subtypes and demonstrate the utility of sequencing genetically enriched cases to identify functionally relevant variants near GWAS loci.