Transcriptome-wide Association Analysis Research Articles

Causal relationship and shared genes between air pollutants and amyotrophic lateral sclerosis: A large-scale genetic analysis.

Air pollutants have been reported to have a potential relationship with amyotrophic lateral sclerosis (ALS). The causality and underlying mechanism remained unknown despite several existing observational studies. We aimed to investigate the potential causality between air pollutants (PM2.5, NOX, and NO2) and the risk of ALS and elucidate the underlying mechanisms associated with this relationship. The data utilized in our study were obtained from publicly available genome-wide association study data sets, in which single nucleotide polymorphisms (SNPs) were employed as the instrumental variantswith three principles. Two-sample Mendelian randomization and transcriptome-wide association (TWAS) analyses were conducted to evaluate the effects of air pollutants on ALS and identify genes associated with both pollutants and ALS, followed by regulatory network prediction. We observed that exposure to a high level of PM2.5 (OR: 2.40 [95% CI: 1.26-4.57], p = 7.46E-3) and NOx (OR: 2.35 [95% CI: 1.32-4.17], p = 3.65E-3) genetically increased the incidence of ALS in MR analysis, while the effects of NO2 showed a similar trend but without sufficient significance. In the TWAS analysis, TMEM175 and USP35 turned out to be the genes shared between PM2.5 and ALS in the same direction. Higher exposure to PM2.5 and NOX might causally increase the risk of ALS. Avoiding exposure to air pollutants and air cleaning might be necessary for ALS prevention.

Meta-Analysis of Genome-Wide Association Studies Reveals Genetic Mechanisms of Supraventricular Arrhythmias.

Substantial data support a heritable basis for supraventricular tachycardias, but the genetic determinants and molecular mechanisms of these arrhythmias are poorly understood. We sought to identify genetic loci associated with atrioventricular nodal reentrant tachycardia (AVNRT) and atrioventricular accessory pathways or atrioventricular reciprocating tachycardia (AVAPs/AVRT). We performed multiancestry meta-analyses of genome-wide association studies to identify genetic loci for AVNRT (4 studies) and AVAP/AVRT (7 studies). We assessed evidence supporting the potential causal effects of candidate genes by analyzing relations between associated variants and cardiac gene expression, performing transcriptome-wide analyses, and examining prior genome-wide association studies. Analyses comprised 2384 AVNRT cases and 106 489 referents, and 2811 AVAP/AVRT cases and 1,483 093 referents. We identified 2 significant loci for AVNRT, which implicate NKX2-5 and TTN as disease susceptibility genes. A transcriptome-wide association analysis supported an association between reduced predicted cardiac expression of NKX2-5 and AVNRT. We identified 3 significant loci for AVAP/AVRT, which implicate SCN5A, SCN10A, and TTN/CCDC141. Variant associations at several loci have been previously reported for cardiac phenotypes, including atrial fibrillation, stroke, Brugada syndrome, and electrocardiographic intervals. Our findings highlight gene regions associated with ion channel function (AVAP/AVRT), as well as cardiac development and the sarcomere (AVAP/AVRT and AVNRT) as important potential effectors of supraventricular tachycardia susceptibility.

Integrative multi-omics analyses to identify the genetic and functional mechanisms underlying ovarian cancer risk regions

To identify credible causal risk variants (CCVs) associated with different histotypes of epithelial ovarian cancer (EOC), we performed genome-wide association analysis for 470,825 genotyped and 10,163,797 imputed SNPs in 25,981 EOC cases and 105,724 controls of European origin. We identified five histotype-specific EOC risk regions (p value <5×10-8) and confirmed previously reported associations for 27 risk regions. Conditional analyses identified an additional 11 signals independent of the primary signal at six risk regions (pvalue <10-5). Fine mapping identified 4,008 CCVs in these regions, of which 1,452 CCVs were located in ovarian cancer-related chromatin marks with significant enrichment in active enhancers, active promoters, and active regions for CCVs from each EOC histotype. Transcriptome-wide association and colocalization analyses across histotypes using tissue-specific and cross-tissue datasets identified 86 candidate susceptibility genes in known EOC risk regions and 32 genes in 23 additional genomic regions that may represent novel EOC risk loci (false discovery rate <0.05). Finally, by integrating genome-wide HiChIP interactome analysis with transcriptome-wide association study (TWAS), variant effect predictor, transcription factor ChIP-seq, and motifbreakR data, we identified candidate gene-CCV interactions at each locus. This included risk loci where TWAS identified one or more candidate susceptibility genes (e.g., HOXD-AS2, HOXD8, and HOXD3 at 2q31) and other loci where no candidate gene was identified (e.g., MYC and PVT1 at 8q24) by TWAS. In summary, this study describes a functional framework and provides a greater understanding of the biological significance of risk alleles and candidate gene targets at EOC susceptibility loci identified by a genome-wide association study.

Genome sequence analyses identify novel risk loci for multiple system atrophy.

Multiple system atrophy (MSA) is an adult-onset, sporadic synucleinopathy characterized by parkinsonism, cerebellar ataxia, and dysautonomia. The genetic architecture of MSA is poorly understood, and treatments are limited to supportive measures. Here, we performed a comprehensive analysis of whole genome sequence data from 888 European-ancestry MSA cases and 7,128 controls to systematically investigate the genetic underpinnings of this understudied neurodegenerative disease. We identified four significantly associated risk loci using a genome-wide association study approach. Transcriptome-wide association analyses prioritized USP38-DT, KCTD7, and lnc-KCTD7-2 as novel susceptibility genes for MSA within these loci, and single-nucleus RNA sequence analysis found that the associated variants acted as cis-expression quantitative trait loci for multiple genes across neuronal and glial cell types. In conclusion, this study highlights the role of genetic determinants in the pathogenesis of MSA, and the publicly available data from this study represent a valuable resource for investigating synucleinopathies.

Exploration of the potential causative genes for inflammatory bowel disease: Transcriptome-wide association analysis, Mendelian randomization analysis and Bayesian colocalisation

BackgroundInflammatory bowel disease (IBD) poses a complex challenge due to its intricate underlying mechanisms, and curative treatments remain elusive. Consequently, there is an urgent need to identify genes causally associated with IBD. MethodsWe extracted blood eQTL data from the GTExv8.ALL.Whole_Blood database, genome-wide association studies (GWAS) summary statistics of IBD from the IEU GWAS database, and performed a three-fold analysis protocol, including transcriptome-wide association analysis, Mendelian randomisation analysis, Bayesian colocalisation, and subsequent potential therapeutic agents identification. ResultsWe identified four pathogenic genes, namely CARD9, RTEL1, STMN3 and ARFRP1, that promote the development of IBD, encompassing both ulcerative colitis (UC) and Crohn's disease (CD). Notably, ARFRP1 exhibited the ability to suppress IBD (encompassing UC and CD) development. Regarding drug prediction, cyclophosphamide emerged as a promising novel therapeutic option for IBD, encompassing UC and CD. ConclusionWe identified several potential genes related to IBD (UC and CD), including CARD9, RTEL1, STMN3 and ARFRP1, warranting further investigation in functional studies to elucidate underlying disease mechanisms. Additionally, clinical studies exploring the potential of cyclophosphamide as a treatment avenue for IBD are warranted.

A distinct class of pan-cancer susceptibility genes revealed by an alternative polyadenylation transcriptome-wide association study

Alternative polyadenylation plays an important role in cancer initiation and progression; however, current transcriptome-wide association studies mostly ignore alternative polyadenylation when identifying putative cancer susceptibility genes. Here, we perform a pan-cancer 3′ untranslated region alternative polyadenylation transcriptome-wide association analysis by integrating 55 well-powered (n > 50,000) genome-wide association studies datasets across 22 major cancer types with alternative polyadenylation quantification from 23,955 RNA sequencing samples across 7,574 individuals. We find that genetic variants associated with alternative polyadenylation are co-localized with 28.57% of cancer loci and contribute a significant portion of cancer heritability. We further identify 642 significant cancer susceptibility genes predicted to modulate cancer risk via alternative polyadenylation, 62.46% of which have been overlooked by traditional expression- and splicing- studies. As proof of principle validation, we show that alternative alleles facilitate 3′ untranslated region lengthening of CRLS1 gene leading to increased protein abundance and promoted proliferation of breast cancer cells. Together, our study highlights the significant role of alternative polyadenylation in discovering new cancer susceptibility genes and provides a strong foundational framework for enhancing our understanding of the etiology underlying human cancers.

Molecular quantitative trait loci in reproductive tissues impact male fertility in cattle.

Breeding bulls are well suited to investigate inherited variation in male fertility because they are genotyped and their reproductive success is monitored through semen analyses and thousands of artificial inseminations. However, functional data from relevant tissues are lackingin cattle, which prevents fine-mapping fertility-associated genomic regions. Here, we characterize gene expression and splicing variation in testis, epididymis, and vas deferens transcriptomes of 118 mature bulls and conduct association tests between 414,667 molecular phenotypes and 21,501,032 genome-wide variants to identify 41,156 regulatory loci. We show broad consensus in tissue-specific and tissue-enriched gene expression between the three bovine tissues and their human and murine counterparts. Expression- and splicing-mediating variants are more than three times as frequent in testis than epididymis and vas deferens, highlighting the transcriptional complexity of testis. Finally, we identify genes (WDR19, SPATA16, KCTD19, ZDHHC1) and molecular phenotypes that are associated with quantitative variation in male fertility through transcriptome-wide association and colocalization analyses.

Tissue factor: A link between metastatic colorectal cancer and thrombosis in patients in the CALGB (Alliance)/SWOG 80405 trial.

198 Background: Tissue factor (TF) is a transmembrane protein that plays a crucial role in thrombosis. TF expression is elevated in various types of cancer, including colorectal cancer (CRC) and is associated with more aggressive disease and poor prognosis. The aim of this study was to evaluate TF expression in patients (pts) with metastatic CRC (mCRC) enrolled in the CALGB (Alliance)/SWOG 80405 clinical trial. Understanding the relationship between TF expression and mCRC will provide insights into the role of coagulation in the progression and prognosis of this disease and may have therapeutic implications, particularly in the setting of recent approval of a TF antibody drug conjugate for metastatic cervical cancer and other agents in the pipeline. Methods: 433 pts with mCRC treated with bevacizumab (Bev, n = 226) or cetuximab (Cet, n =207) in combination with first-line chemotherapy in CALGB/SWOG 80405 were included in the analysis. TF RNA was isolated from FFPE tumor samples and sequenced on the HiSeq 2500 (Illumina). Overall survival (OS) and progression-free survival (PFS) were compared between groups of pts categorized by tertiles of TF expression: high (H), medium (M) and low (L). Sensitivity analyses were conducted after stratifying by side. Logrank P-values describe differences without adjustment for pt characteristics. Transcriptome-wide gene association analysis was performed using linear regression, adjusting for age, sex, ethnicity, ECOG PS, location, number of metastases, KRAS, MSI status, treatment with FOLFOX or FOLFIRI, and the first 3 principal components from the RNA-seq data. Gene Ontology enrichment analysis was conducted with the top 100 TF-associated genes. Results: TF expression is associated with genes related to maintenance of epithelium, cell adhesion, and migration, immunoregulatory cytokine production, and metabolic, HER2, and MAP/Kinase pathways. TF-L showed significantly longer median (m)PFS (13.4 vs 10.1 vs 9.2 months (mo), p=0.0022) and mOS (35.4 vs 30.9 vs 25.2, p=0.0051) in the entire cohort. In Cet treated pts, TF-L had significantly longer mOS (41.3 vs 29.9 vs 26.1 mo, p=0.0013). In pts treated with FOLFOX, TF-L had significantly longer PFS (13.2 vs 10.9 vs 8.2 mo, p=0.0014) and OS (33.4 vs 30.9 vs 22.4 mo, p=0.0044). Pts with liver metastases and TF-H had worse PFS (9.2 vs 9.9 vs 13.5 mo, p=0.006) and OS (23.6 vs 29.9 vs 35.1 mo, p=0.016). Conclusions: Our results suggest that pts with TF-L tumors with liver metastases have improved prognosis compared to pts with TF-H and may benefit from FOLFOX and Cet-based treatment. Findings provide rationale for further evaluation of TF as a predictive biomarker and potential therapeutic target in CRC. Trial Identifier NCT00265850. Support: P30CA014089, U10CA180821, U10CA180882, U10CA180820 and UG1CA233277; UG1CA180830, U10CA180888; Pfizer, Genentech. https://acknowledgments.alliancefound.org.

Transcriptome-wide association analyses reveal the impact of regulatory variants on rice panicle architecture and causal gene regulatory networks

Panicle architecture is a key determinant of rice grain yield and is mainly determined at the 1-2 mm young panicle stage. Here, we investigated the transcriptome of the 1-2 mm young panicles from 275 rice varieties and identified thousands of genes whose expression levels were associated with panicle traits. Multimodel association studies suggested that many small-effect genetic loci determine spikelet per panicle (SPP) by regulating the expression of genes associated with panicle traits. We found that alleles at cis-expression quantitative trait loci of SPP-associated genes underwent positive selection, with a strong preference for alleles increasing SPP. We further developed a method that integrates the associations of cis- and trans-expression components of genes with traits to identify causal genes at even small-effect loci and construct regulatory networks. We identified 36 putative causal genes of SPP, including SDT (MIR156j) and OsMADS17, and inferred that OsMADS17 regulates SDT expression, which was experimentally validated. Our study reveals the impact of regulatory variants on rice panicle architecture and provides new insights into the gene regulatory networks of panicle traits.

The molecular genetic landscape of human brain size variation

Human brain size changes dynamically through early development, peaks in adolescence, and varies up to 2-fold among adults. However, the molecular genetic underpinnings of interindividual variation in brain size remain unknown. Here, we leveraged postmortem brain RNA sequencing and measurements of brain weight (BW) in 2,531 individuals across three independent datasets to identify 928 genome-wide significant associations with BW. Genes associated with higher or lower BW showed distinct neurodevelopmental trajectories and spatial patterns that mapped onto functional and cellular axes of brain organization. Expression of BW genes was predictive of interspecies differences in brain size, and bioinformatic annotation revealed enrichment for neurogenesis and cell-cell communication. Genome-wide, transcriptome-wide, and phenome-wide association analyses linked BW gene sets to neuroimaging measurements of brain size and brain-related clinical traits. Cumulatively, these results represent a major step toward delineating the molecular pathways underlying human brain size variation in health and disease.

Dissecting human population variation in single-cell responses to SARS-CoV-2.

Humans display substantial interindividual clinical variability after SARS-CoV-2 infection1-3, the genetic and immunological basis of which has begun to be deciphered4. However, the extent and drivers of population differences in immune responses to SARS-CoV-2 remain unclear. Here we report single-cell RNA-sequencing data for peripheral blood mononuclear cells-from 222 healthy donors of diverse ancestries-that were stimulated with SARS-CoV-2 or influenza A virus. We show that SARS-CoV-2 induces weaker, but more heterogeneous, interferon-stimulated gene activity compared with influenza A virus, and a unique pro-inflammatory signature in myeloid cells. Transcriptional responses to viruses display marked population differences, primarily driven by changes in cell abundance including increased lymphoid differentiation associated with latent cytomegalovirus infection. Expression quantitative trait loci and mediation analyses reveal a broad effect of cell composition on population disparities in immune responses, with genetic variants exerting a strong effect on specific loci. Furthermore, we show that natural selection has increased population differences in immune responses, particularly for variants associated with SARS-CoV-2 response in East Asians, and document the cellular and molecular mechanisms by which Neanderthal introgression has altered immune functions, such as the response of myeloid cells to viruses. Finally, colocalization and transcriptome-wide association analyses reveal an overlap between the genetic basis of immune responses to SARS-CoV-2 and COVID-19 severity, providing insights into the factors contributing to current disparities in COVID-19 risk.

Genome-wide association study of lung adenocarcinoma in East Asia and comparison with a European population

Lung adenocarcinoma is the most common type of lung cancer. Known risk variants explain only a small fraction of lung adenocarcinoma heritability. Here, we conducted a two-stage genome-wide association study of lung adenocarcinoma of East Asian ancestry (21,658 cases and 150,676 controls; 54.5% never-smokers) and identified 12 novel susceptibility variants, bringing the total number to 28 at 25 independent loci. Transcriptome-wide association analyses together with colocalization studies using a Taiwanese lung expression quantitative trait loci dataset (n = 115) identified novel candidate genes, including FADS1 at 11q12 and ELF5 at 11p13. In a multi-ancestry meta-analysis of East Asian and European studies, four loci were identified at 2p11, 4q32, 16q23, and 18q12. At the same time, most of our findings in East Asian populations showed no evidence of association in European populations. In our studies drawn from East Asian populations, a polygenic risk score based on the 25 loci had a stronger association in never-smokers vs. individuals with a history of smoking (Pinteraction = 0.0058). These findings provide new insights into the etiology of lung adenocarcinoma in individuals from East Asian populations, which could be important in developing translational applications.

Gene expression in African Americans, Puerto Ricans and Mexican Americans reveals ancestry-specific patterns of genetic architecture

We explored ancestry-related differences in the genetic architecture of whole-blood gene expression using whole-genome and RNA sequencing data from 2,733 African Americans, Puerto Ricans and Mexican Americans. We found that heritability of gene expression significantly increased with greater proportions of African genetic ancestry and decreased with higher proportions of Indigenous American ancestry, reflecting the relationship between heterozygosity and genetic variance. Among heritable protein-coding genes, the prevalence of ancestry-specific expression quantitative trait loci (anc-eQTLs) was 30% in African ancestry and 8% for Indigenous American ancestry segments. Most anc-eQTLs (89%) were driven by population differences in allele frequency. Transcriptome-wide association analyses of multi-ancestry summary statistics for 28 traits identified 79% more gene–trait associations using transcriptome prediction models trained in our admixed population than models trained using data from the Genotype-Tissue Expression project. Our study highlights the importance of measuring gene expression across large and ancestrally diverse populations for enabling new discoveries and reducing disparities.

Mendelian Randomization and Transcriptome-Wide Association Analysis Identified Genes That Were Pleiotropically Associated with Intraocular Pressure.

Intraocular pressure (IOP) is a major modifiable risk factor for glaucoma. However, the mechanisms underlying the controlling of IOP remain to be elucidated. To prioritize genes that are pleiotropically associated with IOP. We adopted a two-sample Mendelian randomization method, named summary-based Mendelian randomization (SMR), to examine the pleiotropic effect of gene expression on IOP. The SMR analyses were based on summarized data from a genome-wide association study (GWAS) on IOP. We conducted separate SMR analyses using Genotype-Tissue Expression (GTEx) and Consortium for the Architecture of Gene Expression (CAGE) expression quantitative trait loci (eQTL) data. Additionally, we performed a transcriptome-wide association study (TWAS) to identify genes whose cis-regulated expression levels were associated with IOP. We identified 19 and 25 genes showing pleiotropic association with IOP using the GTEx and CAGE eQTL data, respectively. RP11-259G18.3 (PSMR = 2.66 × 10-6), KANSL1-AS1 (PSMR = 2.78 × 10-6), and RP11-259G18.2 (PSMR = 2.91 × 10-6) were the top three genes using the GTEx eQTL data. LRRC37A4 (PSMR = 1.19 × 10-5), MGC57346 (PSMR = 1.19 × 10-5), and RNF167 (PSMR = 1.53 × 10-5) were the top three genes using the CAGE eQTL data. Most of the identified genes were found in or near the 17q21.31 genomic region. Additionally, our TWAS analysis identified 18 significant genes whose expression was associated with IOP. Of these, 12 and 4 were also identified by the SMR analysis using the GTEx and CAGE eQTL data, respectively. Our findings suggest that the 17q21.31 genomic region may play a critical role in the regulation of IOP.

Antithrombin, Protein C, and Protein S: Genome and Transcriptome-Wide Association Studies Identify 7 Novel Loci Regulating Plasma Levels.

Antithrombin, PC (protein C), and PS (protein S) are circulating natural anticoagulant proteins that regulate hemostasis and of which partial deficiencies are causes of venous thromboembolism. Previous genetic association studies involving antithrombin, PC, and PS were limited by modest sample sizes or by being restricted to candidate genes. In the setting of the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium, we meta-analyzed across ancestries the results from 10 genome-wide association studies of plasma levels of antithrombin, PC, PS free, and PS total. Study participants were of European and African ancestries, and genotype data were imputed to TOPMed, a dense multiancestry reference panel. Each of the 10 studies conducted a genome-wide association studies for each phenotype and summary results were meta-analyzed, stratified by ancestry. Analysis of antithrombin included 25 243 European ancestry and 2688 African ancestry participants, PC analysis included 16 597 European ancestry and 2688 African ancestry participants, PSF and PST analysis included 4113 and 6409 European ancestry participants. We also conducted transcriptome-wide association analyses and multiphenotype analysis to discover additional associations. Novel genome-wide association studies and transcriptome-wide association analyses findings were validated by in vitro functional experiments. Mendelian randomization was performed to assess the causal relationship between these proteins and cardiovascular outcomes. Genome-wide association studies meta-analyses identified 4 newly associated loci: 3 with antithrombin levels (GCKR, BAZ1B, and HP-TXNL4B) and 1 with PS levels (ORM1-ORM2). transcriptome-wide association analyses identified 3 newly associated genes: 1 with antithrombin level (FCGRT), 1 with PC (GOLM2), and 1 with PS (MYL7). In addition, we replicated 7 independent loci reported in previous studies. Functional experiments provided evidence for the involvement of GCKR, SNX17, and HP genes in antithrombin regulation. The use of larger sample sizes, diverse populations, and a denser imputation reference panel allowed the detection of 7 novel genomic loci associated with plasma antithrombin, PC, and PS levels.

Twas_sim, a Python-based tool for simulation and power analysis of transcriptome-wide association analysis.

Genome-wide association studies (GWASs) have identified numerous genetic variants associated with complex disease risk; however, most of these associations are non-coding, complicating identifying their proximal target gene. Transcriptome-wide association studies (TWASs) have been proposed to mitigate this gap by integrating expression quantitative trait loci (eQTL) data with GWAS data. Numerous methodological advancements have been made for TWAS, yet each approach requires ad hoc simulations to demonstrate feasibility. Here, we present twas_sim, a computationally scalable and easily extendable tool for simplified performance evaluation and power analysis for TWAS methods. Software and documentation are available at https://github.com/mancusolab/twas_sim.

Genetic Modifiers of Cystic Fibrosis Lung Disease Severity: Whole-Genome Analysis of 7,840 Patients.

Rationale: Lung disease is the major cause of morbidity and mortality in persons with cystic fibrosis (pwCF). Variability in CF lung disease has substantial non-CFTR (CF transmembrane conductance regulator) genetic influence. Identification of genetic modifiers has prognostic and therapeutic importance. Objectives: Identify genetic modifier loci and genes/pathways associated with pulmonary disease severity. Methods: Whole-genome sequencing data on 4,248 unique pwCF with pancreatic insufficiency and lung function measures were combined with imputed genotypes from an additional 3,592 patients with pancreatic insufficiency from the United States, Canada, and France. This report describes association of approximately 15.9 million SNPs using the quantitative Kulich normal residual mortality-adjusted (KNoRMA) lung disease phenotype in 7,840 pwCF using premodulator lung function data. Measurements and Main Results: Testing included common and rare SNPs, transcriptome-wide association, gene-level, and pathway analyses. Pathway analyses identified novel associations with genes that have key roles in organ development, and we hypothesize that these genes may relate to dysanapsis and/or variability in lung repair. Results confirmed and extended previous genome-wide association study findings. These whole-genome sequencing data provide finely mapped genetic information to support mechanistic studies. No novel primary associations with common single variants or rare variants were found. Multilocus effects at chr5p13 (SLC9A3/CEP72) and chr11p13 (EHF/APIP) were identified. Variant effect size estimates at associated loci were consistently ordered across the cohorts, indicating possible age or birth cohort effects. Conclusions: This premodulator genomic, transcriptomic, and pathway association study of 7,840 pwCF will facilitate mechanistic and postmodulator genetic studies and the development of novel therapeutics for CF lung disease.

Identifying novel proteins underlying loneliness by integrating GWAS summary data with human brain proteomes.

Enduring loneliness is associated with mental disorders and physical diseases. Although genome-wide association studies (GWAS) have identified risk loci associated with loneliness, how these loci confer the risk remains largely unknown. In the current study, we aimed to investigate key proteins underlying loneliness in the brain by integrating human brain proteomes and transcriptomes with loneliness GWAS to perform a discovery proteome-wide association study (PWAS), followed by a confirmatory PWAS, transcriptome-wide association analysis (TWAS), Mendelian randomization (MR), Steigering filtering analysis and Bayesian colocalization analysis. Moreover, given the fact that loneliness is associated with mental disorders, we explored the shared genetic architecture between loneliness and mental disorders. Totally, we identified 18 genes to be associated with loneliness via their cis-regulated brain protein abundance. Eleven of the 18 genes (61.1%) were replicated in the confirmatory PWAS, and mRNA levels of 4 genes were further validated to be associated with loneliness.MR and genetic colocalization analysis further confirmed that the increased protein abundance of ALDH2 and ICA1L was protective against loneliness, while the increased protein abundance of GPX1 was a risk for developing loneliness. Furthermore, we found genetic correlations, bidirectional causal associations and overlapping phenotype-associated protein profiles between loneliness and mental disorders including major depression and schizophrenia. In summary, our findings provided clues about the brain-related molecular basis underlying loneliness, which warrants further investigation.

Lipid-induced transcriptomic changes in blood link to lipid metabolism and allergic response

Immune cell function can be altered by lipids in circulation, a process potentially relevant to lipid-associated inflammatory diseases including atherosclerosis and rheumatoid arthritis. To gain further insight in the molecular changes involved, we here perform a transcriptome-wide association analysis of blood triglycerides, HDL cholesterol, and LDL cholesterol in 3229 individuals, followed by a systematic bidirectional Mendelian randomization analysis to assess the direction of effects and control for pleiotropy. Triglycerides are found to induce transcriptional changes in 55 genes and HDL cholesterol in 5 genes. The function and cell-specific expression pattern of these genes implies that triglycerides downregulate both cellular lipid metabolism and, unexpectedly, allergic response. Indeed, a Mendelian randomization approach based on GWAS summary statistics indicates that several of these genes, including interleukin-4 (IL4) and IgE receptors (FCER1A, MS4A2), affect the incidence of allergic diseases. Our findings highlight the interplay between triglycerides and immune cells in allergic disease.

Transcriptome-wide association analyses identify an association between ARL14EP and polycystic ovary syndrome.

Polycystic ovary syndrome (PCOS) is a common endocrine disorder, which is accompanied by a variety of comorbidities including metabolic, reproductive, and psychiatric disorders. Genome-wide association studies have identified several genetic variants that are associated with PCOS. However, these variants often occur outside of coding regions and require further investigation to understand their contribution to PCOS. A transcriptome-wide association study (TWAS) was performed to uncover heritable gene expression profiles that are associated with PCOS in two independent cohorts. Causal gene prioritization was subsequently performed and expression of genes prioritized through these analyses was examined in 49 PCOS patients and 30 controls. TWAS analyses revealed that increased expression of ARL14EP was significantly associated with PCOS risk in the discovery (P = 1.6 × 10-6) and replication cohorts (P = 2.0 × 10-13). Gene prioritization pipelines provided further evidence that ARL14EP is the most likely causal gene at this locus. ARL14EP gene expression was shown to be significantly different between PCOS cases and controls, after adjusting for body mass index, age and testosterone levels (P = 1.2 × 10-13). This study has provided evidence for the role of ARL14EP in PCOS. Given that ARL14EP has been reported to play an important role in chromatin remodeling, variants affecting the expression of ARL14EP may also affect the expression of other genes that contribute to PCOS pathogenesis.