Variant Set Enrichment: an R package to identify disease-associated functional genomic regions

Untangling the genetics of beta cell dysfunction and death in type 1 diabetes

BACKGROUND

Type 1 diabetes (T1D) is a complex multi-system disease which arises from both environmental and genetic factors, resulting in the destruction of insulin-producing pancreatic beta cells. Over the past two decades, human genetic studies have provided new insight into the etiology of T1D, including an appreciation for the role of beta cells in their own demise.

SCOPE OF REVIEW

Here, we outline models supported by human genetic data for the role of beta cell dysfunction and death in T1D. We highlight the importance of strong evidence linking T1D genetic associations to bona fide candidate genes for mechanistic and therapeutic consideration. To guide rigorous interpretation of genetic associations, we describe molecular profiling approaches, genomic resources, and disease models that may be used to construct variant-to-gene links and to investigate candidate genes and their role in T1D.

MAJOR CONCLUSIONS

We profile advances in understanding the genetic causes of beta cell dysfunction and death at individual T1D risk loci. We discuss how genetic risk prediction models can be used to address disease heterogeneity. Further, we present areas where investment will be critical for the future use of genetics to address open questions in the development of new treatment and prevention strategies for T1D.

Genetic architecture of gene regulation in Indonesian populations identifies QTLs associated with global and local ancestries

Lack of diversity in human genomics limits our understanding of the genetic underpinnings of complex traits, hinders precision medicine, and contributes to health disparities. To map genetic effects on gene regulation in the underrepresented Indonesian population, we have integrated genotype, gene expression, and CpG methylation data from 115 participants across three island populations that capture the major sources of genomic diversity in the region. In a comparison with European datasets, we identify eQTLs shared between Indonesia and Europe as well as population-specific eQTLs that exhibit differences in allele frequencies and/or overall expression levels between populations. By combining local ancestry and archaic introgression inference with eQTLs and methylQTLs, we identify regulatory loci driven by modern Papuan ancestry as well as introgressed Denisovan and Neanderthal variation. GWAS colocalization connects QTLs detected here to hematological traits, and further comparison with European datasets reflects the poor overall transferability of GWAS statistics across diverse populations. Our findings illustrate how population-specific genetic architecture, local ancestry, and archaic introgression drive variation in gene regulation across genetically distinct and in admixed populations and highlight the need for performing association studies on non-European populations.

Determination of shared genetic etiology and possible causal relations between tobacco smoking and depression

BACKGROUNDS

Cigarette smoking is strongly associated with major depressive disorder (MDD). However, any genetic etiology of such comorbidity and causal relations is poorly understood, especially at the genome-wide level.

METHODS

In the present in silico research, we analyzed summary data from the genome-wide association study of the Psychiatric Genetic Consortium for MDD (n = 191 005) and UK Biobank for smoking (n = 337 030) by using various biostatistical methods including Bayesian colocalization analysis, LD score regression, variant effect size correlation analysis, and Mendelian randomization (MR).

RESULTS

By adopting a gene prioritization approach, we identified 43 genes shared by MDD and smoking, which were significantly enriched in membrane potential, gamma-aminobutyric acid receptor activity, and retrograde endocannabinoid signaling pathways, indicating that the comorbid mechanisms are involved in the neurotransmitter system. According to linkage disequilibrium score regression, we found a strong positive correlation between MDD and current smoking (rg = 0.365; p = 7.23 × 10-25) and a negative correlation between MDD and former smoking (rg = -0.298; p = 1.59 × 10-24). MR analysis suggested that genetic liability for depression increased smoking.

CONCLUSIONS

These findings inform the concomitant conditions of MDD and smoking and support the use of self-medication with smoking to counteract depression.

CRISPRi screens reveal a DNA methylation-mediated 3D genome dependent causal mechanism in prostate cancer

Prostate cancer (PCa) risk-associated SNPs are enriched in noncoding cis-regulatory elements (rCREs), yet their modi operandi and clinical impact remain elusive. Here, we perform CRISPRi screens of 260 rCREs in PCa cell lines. We find that rCREs harboring high risk SNPs are more essential for cell proliferation and H3K27ac occupancy is a strong indicator of essentiality. We also show that cell-line-specific essential rCREs are enriched in the 8q24.21 region, with the rs11986220-containing rCRE regulating MYC and PVT1 expression, cell proliferation and tumorigenesis in a cell-line-specific manner, depending on DNA methylation-orchestrated occupancy of a CTCF binding site in between this rCRE and the MYC promoter. We demonstrate that CTCF deposition at this site as measured by DNA methylation level is highly variable in prostate specimens, and observe the MYC eQTL in the 8q24.21 locus in individuals with low CTCF binding. Together our findings highlight a causal mechanism synergistically driven by a risk SNP and DNA methylation-mediated 3D genome architecture, advocating for the integration of genetics and epigenetics in assessing risks conferred by genetic predispositions.

Pioneer of prostate cancer: past, present and the future of FOXA1

Prostate cancer is the most commonly diagnosed non-cutaneous cancers in North American men. While androgen deprivation has remained as the cornerstone of prostate cancer treatment, resistance ensues leading to lethal disease. Forkhead box A1 (FOXA1) encodes a pioneer factor that induces open chromatin conformation to allow the binding of other transcription factors. Through direct interactions with the Androgen Receptor (AR), FOXA1 helps to shape AR signaling that drives the growth and survival of normal prostate and prostate cancer cells. FOXA1 also possesses an AR-independent role of regulating epithelial-to-mesenchymal transition (EMT). In prostate cancer, mutations converge onto the coding sequence and cis-regulatory elements (CREs) of FOXA1, leading to functional alterations. In addition, FOXA1 activity in prostate cancer can be modulated post-translationally through various mechanisms such as LSD1-mediated protein demethylation. In this review, we describe the latest discoveries related to the function and regulation of FOXA1 in prostate cancer, pointing to their relevance to guide future clinical interventions.

Combinatorial and statistical prediction of gene expression from haplotype sequence

MOTIVATION

Genome-wide association studies (GWAS) have discovered thousands of significant genetic effects on disease phenotypes. By considering gene expression as the intermediary between genotype and disease phenotype, expression quantitative trait loci studies have interpreted many of these variants by their regulatory effects on gene expression. However, there remains a considerable gap between genotype-to-gene expression association and genotype-to-gene expression prediction. Accurate prediction of gene expression enables gene-based association studies to be performed post hoc for existing GWAS, reduces multiple testing burden, and can prioritize genes for subsequent experimental investigation.

RESULTS

In this work, we develop gene expression prediction methods that relax the independence and additivity assumptions between genetic markers. First, we consider gene expression prediction from a regression perspective and develop the HAPLEXR algorithm which combines haplotype clusterings with allelic dosages. Second, we introduce the new gene expression classification problem, which focuses on identifying expression groups rather than continuous measurements; we formalize the selection of an appropriate number of expression groups using the principle of maximum entropy. Third, we develop the HAPLEXD algorithm that models haplotype sharing with a modified suffix tree data structure and computes expression groups by spectral clustering. In both models, we penalize model complexity by prioritizing genetic clusters that indicate significant effects on expression. We compare HAPLEXR and HAPLEXD with three state-of-the-art expression prediction methods and two novel logistic regression approaches across five GTEx v8 tissues. HAPLEXD exhibits significantly higher classification accuracy overall; HAPLEXR shows higher prediction accuracy on approximately half of the genes tested and the largest number of best predicted genes (r2>0.1) among all methods. We show that variant and haplotype features selected by HAPLEXR are smaller in size than competing methods (and thus more interpretable) and are significantly enriched in functional annotations related to gene regulation. These results demonstrate the importance of explicitly modeling non-dosage dependent and intragenic epistatic effects when predicting expression.

AVAILABILITY AND IMPLEMENTATION

Source code and binaries are freely available at https://github.com/rapturous/HAPLEX.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Transcription Factor Enrichment Analysis in Enhancers Identifies EZH2 as a Susceptibility Gene for Osteoporosis

PURPOSE

Genome-wide association studies (GWASs) have identified hundreds of single nucleotide polymorphisms (SNPs) associated with osteoporosis. Most of these SNPs are noncoding variants and could be mapped to enhancers. Transcription factors (TFs) play important roles in gene regulation via enhancers harboring these SNPs; thus, we aimed to identify common regulatory TFs binding to enhancers associated with osteoporosis.

METHODS

We first annotated all the osteoporosis-related SNPs identified by GWASs to enhancers and conducted TF enrichment analyses to identify common TFs binding to osteoporosis-associated enhancers. We further conducted genetic association analyses between the identified TFs and bone mineral density (BMD) in a Han Chinese population.

RESULTS

After functional annotation, a total of 5081 osteoporosis-related SNPs were mapped to enhancers. TF enrichment analyses identified 2 significant TFs after multiple testing adjustments, which are EZH2 (Padj = .028) and NRSF (Padj = .038). We also found 1 SNP, rs111851041, in EZH2 was significantly associated with BMD both at the hip and spine after multiple testing adjustments (hip BMD: P = 4.32 × 10-4; spine BMD: P = 2.72 × 10-3). The expression of EZH2 decreased significantly from 12 to 48 hours of osteogenic differentiation. And functional validation showed that EZH2 was associated with osteoporosis-related phenotypes in knockout mice.

CONCLUSIONS

By conducting TF enrichment analyses, we identified EZH2 as a common TF binding to osteoporosis-associated enhancers, and EZH2 was also associated with BMD in a Chinese population. EZH2 is functionally related to bone phenotypes. The identified gene could provide new insight into osteoporosis pathophysiology and highlight opportunities for future clinical and pharmacological research on osteoporosis.

Cistrome Partitioning Reveals Convergence of Somatic Mutations and Risk Variants on Master Transcription Regulators in Primary Prostate Tumors

Thousands of noncoding somatic single-nucleotide variants (SNVs) of unknown function are reported in tumors. Partitioning the genome according to cistromes reveals the enrichment of somatic SNVs in prostate tumors as opposed to adjacent normal tissue cistromes of master transcription regulators, including AR, FOXA1, and HOXB13. This parallels enrichment of prostate cancer genetic predispositions over these transcription regulators' tumor cistromes, exemplified at the 8q24 locus harboring both risk variants and somatic SNVs in cis-regulatory elements upregulating MYC expression. However, Massively Parallel Reporter Assays reveal that few SNVs can alter the transactivation potential of individual cis-regulatory elements. Instead, similar to inherited risk variants, SNVs accumulate in cistromes of master transcription regulators required for prostate cancer development.

The impact of proinflammatory cytokines on the β-cell regulatory landscape provides insights into the genetics of type 1 diabetes

Early stages of type 1 diabetes (T1D) are characterized by local autoimmune inflammation and progressive loss of insulin-producing pancreatic β cells. We show here that exposure to pro-inflammatory cytokines unmasks a marked plasticity of the β-cell regulatory landscape. We expand the repertoire of human islet regulatory elements by mapping stimulus-responsive enhancers linked to changes in the β-cell transcriptome, proteome and 3D chromatin structure. Our data indicate that the β cell response to cytokines is mediated by the induction of new regulatory regions as well as the activation of primed regulatory elements prebound by islet-specific transcription factors. We find that T1D-associated loci are enriched of the newly mapped cis-regulatory regions and identify T1D-associated variants disrupting cytokine-responsive enhancer activity in human β cells. Our study illustrates how β cells respond to a pro-inflammatory environment and implicate a role for stimulus-response islet enhancers in T1D.

Exploring Shared Susceptibility between Two Neural Crest Cells Originating Conditions: Neuroblastoma and Congenital Heart Disease

In the past years, genome wide association studies (GWAS) have provided evidence that inter-individual susceptibility to diverse pathological conditions can reveal a common genetic architecture. Through the analysis of congenital heart disease (CHD) and neuroblastoma (NB) GWAS data, we aimed to dissect the genetic susceptibility shared between these conditions, which are known to arise from neural crest cell (NCC) migration or development abnormalities, via identification and functional characterization of common regions of association. Two loci (2q35 and 3q25.32) harbor single nucleotide polymorphisms (SNPs) that are associated at a p-value < 10^-3 with conotruncal malformations and ventricular septal defect respectively, as well as with NB. In addition, the lead SNP in 4p16.2 for atrial septal defect and the lead SNP in 3q25.32 for tetralogy of Fallot are less than 250 Kb distant from the lead SNPs for NB at the same genomic regions. Some of these shared susceptibility loci regulate the expression of relevant genes involved in NCC formation and developmental processes (such as BARD1, MSX1, and SHOX2) and are enriched in several epigenetic markers from NB and fetal heart cell lines. Although the clinical correlation between NB and CHD is unclear, our exploration of a possible common genetic basis between NB and a subset of cardiac malformations can help shed light on their shared embryological origin and pathogenetic mechanisms.

Regulatory annotation of genomic intervals based on tissue-specific expression QTLs

MOTIVATION

Annotating a given genomic locus or a set of genomic loci is an important yet challenging task. This is especially true for the non-coding part of the genome which is enormous yet poorly understood. Since gene set enrichment analyses have demonstrated to be effective approach to annotate a set of genes, the same idea can be extended to explore the enrichment of functional elements or features in a set of genomic intervals to reveal potential functional connections.

RESULTS

In this study, we describe a novel computational strategy named loci2path that takes advantage of the newly emerged, genome-wide and tissue-specific expression quantitative trait loci (eQTL) information to help annotate a set of genomic intervals in terms of transcription regulation. By checking the presence or the absence of millions of eQTLs in a set of input genomic intervals, combined with grouping eQTLs by the pathways or gene sets that their target genes belong to, loci2path build a bridge connecting genomic intervals to functional pathways and pre-defined biological-meaningful gene sets, revealing potential for regulatory connection. Our method enjoys two key advantages over existing methods: first, we no longer rely on proximity to link a locus to a gene which has shown to be unreliable; second, eQTL allows us to provide the regulatory annotation under the context of specific tissue types. To demonstrate its utilities, we apply loci2path on sets of genomic intervals harboring disease-associated variants as query. Using 1 702 612 eQTLs discovered by the Genotype-Tissue Expression (GTEx) project across 44 tissues and 6320 pathways or gene sets cataloged in MSigDB as annotation resource, our method successfully identifies highly relevant biological pathways and revealed disease mechanisms for psoriasis and other immune-related diseases. Tissue specificity analysis of associated eQTLs provide additional evidence of the distinct roles of different tissues played in the disease mechanisms.

AVAILABILITY AND IMPLEMENTATION

loci2path is published as an open source Bioconductor package, and it is available at http://bioconductor.org/packages/release/bioc/html/loci2path.html.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Human pancreatic islet three-dimensional chromatin architecture provides insights into the genetics of type 2 diabetes

Genetic studies promise to provide insight into the molecular mechanisms underlying type 2 diabetes (T2D). Variants associated with T2D are often located in tissue-specific enhancer clusters or super-enhancers. So far, such domains have been defined through clustering of enhancers in linear genome maps rather than in three-dimensional (3D) space. Furthermore, their target genes are often unknown. We have created promoter capture Hi-C maps in human pancreatic islets. This linked diabetes-associated enhancers to their target genes, often located hundreds of kilobases away. It also revealed >1,300 groups of islet enhancers, super-enhancers and active promoters that form 3D hubs, some of which show coordinated glucose-dependent activity. We demonstrate that genetic variation in hubs impacts insulin secretion heritability, and show that hub annotations can be used for polygenic scores that predict T2D risk driven by islet regulatory variants. Human islet 3D chromatin architecture, therefore, provides a framework for interpretation of T2D genome-wide association study (GWAS) signals.

Common and Rare Coding Genetic Variation Underlying the Electrocardiographic PR Interval

BACKGROUND

Electrical conduction from the cardiac sinoatrial node to the ventricles is critical for normal heart function. Genome-wide association studies have identified more than a dozen common genetic loci that are associated with PR interval. However, it is unclear whether rare and low-frequency variants also contribute to PR interval heritability.

METHODS

We performed large-scale meta-analyses of the PR interval that included 83 367 participants of European ancestry and 9436 of African ancestry. We examined both common and rare variants associated with the PR interval.

RESULTS

We identified 31 genetic loci that were significantly associated with PR interval after Bonferroni correction (P<1.2×10-6), including 11 novel loci that have not been reported previously. Many of these loci are involved in heart morphogenesis. In gene-based analysis, we found that multiple rare variants at MYH6 (P=5.9×10-11) and SCN5A (P=1.1×10-7) were associated with PR interval. SCN5A locus also was implicated in the common variant analysis, whereas MYH6 was a novel locus.

CONCLUSIONS

We identified common variants at 11 novel loci and rare variants within 2 gene regions that were significantly associated with PR interval. Our findings provide novel insights to the current understanding of atrioventricular conduction, which is critical for cardiac activity and an important determinant of health.

A catalog of potential putative functional variants in psoriasis genome-wide association regions

Psoriasis is a common inflammatory skin disease, with considerable genetic contribution. Genome-wide association studies have successfully identified a number of genomic regions for the risk of psoriasis. However, it is challenging to pinpoint the functional causal variants and then further decipher the genetic mechanisms underlying each region. In order to prioritize potential functional causal variants within psoriasis susceptibility regions, we integrated the genetic association findings and functional genomic data publicly available, i.e. histone modifications in relevant immune cells. We characterized a pervasive enrichment pattern of psoriasis variants in five core histone marks across immune cells/tissues. We discovered that genetic alleles within psoriasis association regions might influence gene expression levels through significantly affecting the binding affinities of 17 transcription factors. We established a catalog of 654 potential functional causal variants for psoriasis and suggested that they significantly overlapped with causal variants for autoimmune diseases. We identified potential causal variant rs79824801 overlay with the peaks of five histone marks in primary CD4+ T cells. Its alternative allele affected the binding affinity of transcription factor IKZF1. This study highlights the complex genetic architecture and complicated mechanisms for psoriasis. The findings will inform the functional experiment design for psoriasis.

Exome-wide association study identifies four novel loci for systemic lupus erythematosus in Han Chinese population

OBJECTIVES

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease of considerable genetic predisposition. Genome-wide association studies have identified tens of common variants for SLE. However, the majority of them reside in non-coding sequences. The contributions of coding variants have not yet been systematically evaluated.

METHODS

We performed a large-scale exome-wide study in 5004 SLE cases and 8179 healthy controls in a Han Chinese population using a custom exome array, and then genotyped 32 variants with suggestive evidence in an independent cohort of 13 246 samples. We further explored the regulatory effect of one novel non-coding single nucleotide polymorphism (SNP) in ex vivo experiments.

RESULTS

We discovered four novel SLE gene regions (LCT, TPCN2, AHNAK2 and TNFRSF13B) encompassing three novel missense variants (XP_016859577.1:p.Asn1639Ser, XP_016859577.1:p.Val219Phe and XP_005267356.1:p.Thr4664Ala) and two non-coding variants (rs10750836 and rs4792801) with genome-wide significance (p_meta <5.00×10^-8). These variants are enriched in several chromatin states of primary B cells. The novel intergenic variant rs10750836 exhibited an expression quantitative trait locus effect on the TPCN2 gene in immune cells. Clones containing this novel SNP exhibited gene promoter activity for TPCN2 (P=1.38×10^-3) whose expression level was reduced significantly in patients with SLE (P<2.53×10^-2) and was suggested to be further modulated by rs10750836 in CD19+ B cells (P=7.57×10^-5) in ex vivo experiments.

CONCLUSIONS

This study identified three novel coding variants and four new susceptibility gene regions for SLE. The results provide insights into the biological mechanism of SLE.