Genome-wide expression quantitative trait loci analysis in asthma

Asthma Phenotypes in the Era of Personalized Medicine

Asthma is a widespread disease affecting approximately 300-million people globally. This condition leads to significant morbidity, mortality, and economic strain worldwide. Recent clinical and laboratory research advancements have illuminated the immunological factors contributing to asthma. As of now, asthma is understood to be a heterogeneous disease. Personalized medicine involves categorizing asthma by its endotypes, linking observable characteristics to specific immunological mechanisms. Identifying these endotypic mechanisms is paramount in accurately profiling patients and tailoring therapeutic approaches using innovative biological agents targeting distinct immune pathways. This article presents a synopsis of the key immunological mechanisms implicated in the pathogenesis and manifestation of the disease's phenotypic traits and individualized treatments for severe asthma subtypes.

Transcriptome-wide association study identified candidate genes associated with gut microbiota

Background

Gut microbiota is closely associated with host health and disease occurrence. Host genetic factor plays an important role in shaping gut microbial communities. The specific mechanism of host-regulated gene expression affecting gut microbiota has not been elucidated yet. Here we conducted a transcriptome-wide association study (TWAS) for gut microbiota by leveraging expression imputation from large-scale GWAS data sets.

Results

TWAS detected multiple tissue-specific candidate genes for gut microbiota, such as FUT2 for genus Bifidobacterium in transverse colon (P_PERM.ANL = 1.68 × 10^–3) and SFTPD for an unclassified genus of Proteobacteria in transverse colon (P_PERM.ANL = 5.69 × 10^–3). Fine mapping replicated 3 candidate genes in TWAS, such as HELLS for Streptococcus (PIP = 0.685) in sigmoid colon, ANO7 for Erysipelotrichaceae (PIP = 0.449) in sigmoid colon. Functional analyses detected 94 significant GO terms and 11 pathways for various taxa in total, such as GO_NUCLEOSIDE_DIPHOSPHATASE_ACTIVITY for Butyrivibrio (FDR P = 1.30 × 10^–4), KEGG_RENIN_ANGIOTENSIN_SYSTEM for Anaerostipes (FDR P = 3.16 × 10^–2). Literature search results showed 12 genes prioritized by TWAS were associated with 12 diseases. For instance, SFTPD for an unclassified genus of Proteobacteria was related to atherosclerosis, and FUT2 for Bifidobacterium was associated with Crohn’s disease.

Conclusions

Our study results provided novel insights for understanding the genetic mechanism of gut microbiota, and attempted to provide clues for revealing the influence of genetic factors on gut microbiota for the occurrence and development of diseases.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13099-021-00474-w.

Novel association between a transient receptor potential cation channel subfamily M member 5 expression quantitative trait locus rs35197079 and decreased susceptibility of gestational diabetes mellitus in a Chinese population

AIMS/INTRODUCTION

Emerging evidence suggests that expression quantitative trait loci (eQTLs) are more likely to associate with complex diseases. Transient receptor potential cation channel subfamily M member 5 (TRPM5) is a ubiquitously expressed voltage-gated cation channel that acts indispensably to trigger insulin secretion in pancreatic β-cells. The present study evaluated the association between TRPM5 eQTL single-nucleotide polymorphisms and the risk of gestational diabetes mellitus (GDM) in a Chinese population.

MATERIALS AND METHODS

A total of 380 unrelated Chinese pregnant women including 241 GDM patients and 139 controls were included in this study. The eQTL single-nucleotide polymorphisms of TRPM5 were obtained from the GTEx eQTL Browser, and were subsequently genotyped using the Agena MassARRAY iPLEX platform.

RESULTS

Logistic regression analysis and linear regression analysis showed that rs35197079 and rs74848824 were significantly associated with reduced GDM risk and lower fasting plasma glucose levels after adjusting confounder factors in dominant genetic models. Stratification analysis based on pre-pregnancy body mass index validated a strong association between rs35197079 and GDM susceptibility in underweight and normal weight individuals. Luciferase and electrophoretic mobility shift assays carried out in rat pancreatic β-cells showed that rs35197079 was functional.

CONCLUSIONS

The TRPM5 eQTL single-nucleotide polymorphism rs35197079 was associated with decreased GDM susceptibility in a Chinese population, especially in underweight and normal weight pregnant women, and it was functional in modulating gene transcription.

Transcriptome-wide association study reveals candidate causal genes for lung cancer

We have recently completed the largest GWAS on lung cancer including 29,266 cases and 56,450 controls of European descent. The goal of our study has been to integrate the complete GWAS results with a large-scale expression quantitative trait loci (eQTL) mapping study in human lung tissues (n = 1,038) to identify candidate causal genes for lung cancer. We performed transcriptome-wide association study (TWAS) for lung cancer overall, by histology (adenocarcinoma, squamous cell carcinoma and small cell lung cancer) and smoking subgroups (never- and ever-smokers). We performed replication analysis using lung data from the Genotype-Tissue Expression (GTEx) project. DNA damage assays were performed in human lung fibroblasts for selected TWAS genes. As expected, the main TWAS signal for all histological subtypes and ever-smokers was on chromosome 15q25. The gene most strongly associated with lung cancer at this locus using the TWAS approach was IREB2 (pTWAS = 1.09E-99), where lower predicted expression increased lung cancer risk. A new lung adenocarcinoma susceptibility locus was revealed on 9p13.3 and associated with higher predicted expression of AQP3 (pTWAS = 3.72E-6). Among the 45 previously described lung cancer GWAS loci, we mapped candidate target gene for 17 of them. The association AQP3-adenocarcinoma on 9p13.3 was replicated using GTEx (pTWAS = 6.55E-5). Consistent with the effect of risk alleles on gene expression levels, IREB2 knockdown and AQP3 overproduction promote endogenous DNA damage. These findings indicate genes whose expression in lung tissue directly influences lung cancer risk.

Omics for the future in asthma

Asthma is a common, complex, multifaceted disease. It comprises multiple phenotypes, which might benefit from treatment with different types of innovative targeted therapies. Refining these phenotypes and understanding their underlying biological structure would help to apply precision medicine approaches. Using different omics methods, such as (epi)genomics, transcriptomics, proteomics, metabolomics, microbiomics, and exposomics, allowed to view and investigate asthma from diverse angles. Technological advancement led to a large increase in the application of omics studies in the asthma field. Although the use of omics technologies has reduced the gap between bench to bedside, several design and methodological challenges still need to be tackled before omics can be applied in asthma patient care. Collaborating under a centralized harmonized work frame (such as in consortia, under consistent methodologies) could help worldwide research teams to tackle these challenges. In this review, we discuss the transition of single biomarker research to multi-omics studies. In addition, we deliberate challenges such as the lack of standardization of sampling and analytical methodologies and validation of findings, which comes in between omics and personalized patient care. The future of omics in asthma is encouraging but not completely clear with some unanswered questions, which have not been adequately addressed before. Therefore, we highlight these questions and emphasize on the importance of fulfilling them.

Identifying Multi-Omics Causers and Causal Pathways for Complex Traits

The central dogma of molecular biology delineates a unidirectional causal flow, i.e., DNA → RNA → protein → trait. Genome-wide association studies, next-generation sequencing association studies, and their meta-analyses have successfully identified ~12,000 susceptibility genetic variants that are associated with a broad array of human physiological traits. However, such conventional association studies ignore the mediate causers (i.e., RNA, protein) and the unidirectional causal pathway. Such studies may not be ideally powerful; and the genetic variants identified may not necessarily be genuine causal variants. In this article, we model the central dogma by a mediate causal model and analytically prove that the more remote an omics level is from a physiological trait, the smaller the magnitude of their correlation is. Under both random and extreme sampling schemes, we numerically demonstrate that the proteome-trait correlation test is more powerful than the transcriptome-trait correlation test, which in turn is more powerful than the genotype-trait association test. In conclusion, integrating RNA and protein expressions with DNA data and causal inference are necessary to gain a full understanding of how genetic causal variants contribute to phenotype variations.

Leveraging lung tissue transcriptome to uncover candidate causal genes in COPD genetic associations

Causal genes of chronic obstructive pulmonary disease (COPD) remain elusive. The current study aims at integrating genome-wide association studies (GWAS) and lung expression quantitative trait loci (eQTL) data to map COPD candidate causal genes and gain biological insights into the recently discovered COPD susceptibility loci. Two complementary genomic datasets on COPD were studied. First, the lung eQTL dataset which included whole-genome gene expression and genotyping data from 1038 individuals. Second, the largest COPD GWAS to date from the International COPD Genetics Consortium (ICGC) with 13 710 cases and 38 062 controls. Methods that integrated GWAS with eQTL signals including transcriptome-wide association study (TWAS), colocalization and Mendelian randomization-based (SMR) approaches were used to map causality genes, i.e. genes with the strongest evidence of being the functional effector at specific loci. These methods were applied at the genome-wide level and at COPD risk loci derived from the GWAS literature. Replication was performed using lung data from GTEx. We collated 129 non-overlapping risk loci for COPD from the GWAS literature. At the genome-wide scale, 12 new COPD candidate genes/loci were revealed and six replicated in GTEx including CAMK2A, DMPK, MYO15A, TNFRSF10A, BTN3A2 and TRBV30. In addition, we mapped candidate causal genes for 60 out of the 129 GWAS-nominated loci and 23 of them were replicated in GTEx. Mapping candidate causal genes in lung tissue represents an important contribution to the genetics of COPD, enriches our biological interpretation of GWAS findings, and brings us closer to clinical translation of genetic associations.

Dynamic changes in gene expression and alternative splicing mediate the response to acute alcohol exposure in Drosophila melanogaster

Environmental changes typically cause rapid gene expression responses in the exposed organisms, including changes in the representation of gene isoforms with different functions or properties. Identifying the genes that respond to environmental change, including in genotype-specific ways, is an important step in treating the undesirable physiological effects of stress, such as exposure to toxins or ethanol. Ethanol is a unique environmental stress in that chronic exposure results in permanent physiological changes and the development of alcohol use disorders. Drosophila is a classic model for deciphering the mechanisms of the response to alcohol exposure, as it meets the criteria for the development of alcohol use disorders, and has similar physiological underpinnings with vertebrates. Because many studies on the response to ethanol have relied on a priori candidate genes, broad surveys of gene expression and splicing are required and have been investigated here. Further, we expose Drosophila to ethanol in an environment that is genetically, socially, and ecologically relevant. Both expression and splicing differences, inasmuch as they can be decomposed, contribute to the response to ethanol in Drosophila melanogaster. However, we find that while D. melanogaster responds to ethanol, there is very little genetic variation in how it responds to ethanol. In addition, the response to alcohol over time is dynamic, suggesting that incorporating time into studies on the response to the environment is important.

Environmental perturbations lead to extensive directional shifts in RNA processing

Environmental perturbations have large effects on both organismal and cellular traits, including gene expression, but the extent to which the environment affects RNA processing remains largely uncharacterized. Recent studies have identified a large number of genetic variants associated with variation in RNA processing that also have an important role in complex traits; yet we do not know in which contexts the different underlying isoforms are used. Here, we comprehensively characterized changes in RNA processing events across 89 environments in five human cell types and identified 15,300 event shifts (FDR = 15%) comprised of eight event types in over 4,000 genes. Many of these changes occur consistently in the same direction across conditions, indicative of global regulation by trans factors. Accordingly, we demonstrate that environmental modulation of splicing factor binding predicts shifts in intron retention, and that binding of transcription factors predicts shifts in alternative first exon (AFE) usage in response to specific treatments. We validated the mechanism hypothesized for AFE in two independent datasets. Using ATAC-seq, we found altered binding of 64 factors in response to selenium at sites of AFE shift, including ELF2 and other factors in the ETS family. We also performed AFE QTL mapping in 373 individuals and found an enrichment for SNPs predicted to disrupt binding of the ELF2 factor. Together, these results demonstrate that RNA processing is dramatically changed in response to environmental perturbations through specific mechanisms regulated by trans factors.

Using omics approaches to understand pulmonary diseases

Omics approaches are high-throughput unbiased technologies that provide snapshots of various aspects of biological systems and include: 1) genomics, the measure of DNA variation; 2) transcriptomics, the measure of RNA expression; 3) epigenomics, the measure of DNA alterations not involving sequence variation that influence RNA expression; 4) proteomics, the measure of protein expression or its chemical modifications; and 5) metabolomics, the measure of metabolite levels. Our understanding of pulmonary diseases has increased as a result of applying these omics approaches to characterize patients, uncover mechanisms underlying drug responsiveness, and identify effects of environmental exposures and interventions. As more tissue- and cell-specific omics data is analyzed and integrated for diverse patients under various conditions, there will be increased identification of key mechanisms that underlie pulmonary biological processes, disease endotypes, and novel therapeutics that are efficacious in select individuals. We provide a synopsis of how omics approaches have advanced our understanding of asthma, chronic obstructive pulmonary disease (COPD), acute respiratory distress syndrome (ARDS), idiopathic pulmonary fibrosis (IPF), and pulmonary arterial hypertension (PAH), and we highlight ongoing work that will facilitate pulmonary disease precision medicine.

Combining genomewide association study and lung eQTL analysis provides evidence for novel genes associated with asthma

BACKGROUND

Genomewide association studies (GWASs) of asthma have identified single-nucleotide polymorphisms (SNPs) that modestly increase the risk for asthma. This could be due to phenotypic heterogeneity of asthma. Bronchial hyperresponsiveness (BHR) is a phenotypic hallmark of asthma. We aim to identify susceptibility genes for asthma combined with BHR and analyse the presence of cis-eQTLs among replicated SNPs. Secondly, we compare the genetic association of SNPs previously associated with (doctor's diagnosed) asthma to our GWAS of asthma with BHR.

METHODS

A GWAS was performed in 920 asthmatics with BHR and 980 controls. Top SNPs of our GWAS were analysed in four replication cohorts, and lung cis-eQTL analysis was performed on replicated SNPs. We investigated association of SNPs previously associated with asthma in our data.

RESULTS

A total of 368 SNPs were followed up for replication. Six SNPs in genes encoding ABI3BP, NAF1, MICA and the 17q21 locus replicated in one or more cohorts, with one locus (17q21) achieving genomewide significance after meta-analysis. Five of 6 replicated SNPs regulated 35 gene transcripts in whole lung. Eight of 20 asthma-associated SNPs from previous GWAS were significantly associated with asthma and BHR. Three SNPs, in IL-33 and GSDMB, showed larger effect sizes in our data compared to published literature.

CONCLUSIONS

Combining GWAS with subsequent lung eQTL analysis revealed disease-associated SNPs regulating lung mRNA expression levels of potential new asthma genes. Adding BHR to the asthma definition does not lead to an overall larger genetic effect size than analysing (doctor's diagnosed) asthma.

Future clinical implications emerging from recent genome-wide expression studies in asthma

Host susceptibility to environmental triggers is the most likely explanation for the development of asthma. Quantifying gene expression levels in disease-relevant tissues and cell types using fast evolving genomic technologies have generated new hypotheses about the pathogenesis of asthma and identified new therapeutic targets to treat asthma and asthma-exacerbations. New biomarkers and distinct transcriptomic phenotypes in blood, sputum and other tissues were also identified and proved effective to refine asthma classification and guide targeted therapies. The wealth of information provided by transcriptomic studies in asthma is yet to be fully exploited, but discoveries in this field may soon be implemented in clinical settings to improve diagnosis and treatment of patients afflicted with this common disease.

Synthesis of 53 tissue and cell line expression QTL datasets reveals master eQTLs

BACKGROUND

Gene expression genetic studies in human tissues and cells identify cis- and trans-acting expression quantitative trait loci (eQTLs). These eQTLs provide insights into regulatory mechanisms underlying disease risk. However, few studies systematically characterized eQTL results across cell and tissues types. We synthesized eQTL results from >50 datasets, including new primary data from human brain, peripheral plaque and kidney samples, in order to discover features of human eQTLs.

RESULTS

We find a substantial number of robust cis-eQTLs and far fewer trans-eQTLs consistent across tissues. Analysis of 45 full human GWAS scans indicates eQTLs are enriched overall, and above nSNPs, among positive statistical signals in genetic mapping studies, and account for a significant fraction of the strongest human trait effects. Expression QTLs are enriched for gene centricity, higher population allele frequencies, in housekeeping genes, and for coincidence with regulatory features, though there is little evidence of 5' or 3' positional bias. Several regulatory categories are not enriched including microRNAs and their predicted binding sites and long, intergenic non-coding RNAs. Among the most tissue-ubiquitous cis-eQTLs, there is enrichment for genes involved in xenobiotic metabolism and mitochondrial function, suggesting these eQTLs may have adaptive origins. Several strong eQTLs (CDK5RAP2, NBPFs) coincide with regions of reported human lineage selection. The intersection of new kidney and plaque eQTLs with related GWAS suggest possible gene prioritization. For example, butyrophilins are now linked to arterial pathogenesis via multiple genetic and expression studies. Expression QTL and GWAS results are made available as a community resource through the NHLBI GRASP database [http://apps.nhlbi.nih.gov/grasp/].

CONCLUSIONS

Expression QTLs inform the interpretation of human trait variability, and may account for a greater fraction of phenotypic variability than protein-coding variants. The synthesis of available tissue eQTL data highlights many strong cis-eQTLs that may have important biologic roles and could serve as positive controls in future studies. Our results indicate some strong tissue-ubiquitous eQTLs may have adaptive origins in humans. Efforts to expand the genetic, splicing and tissue coverage of known eQTLs will provide further insights into human gene regulation.