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Detecting genes that affect specific traits (such as human diseases and crop yields) is important for treating complex diseases and improving crop quality. A genome-wide association study (GWAS) provides new insights and directions for understanding complex traits by identifying important single nucleotide polymorphisms. Many GWAS summary statistics data related to various complex traits have been gathered recently. Studies have shown that GWAS risk loci and expression quantitative trait loci (eQTLs) often have a lot of overlaps, which makes gene expression gradually become an important intermediary to reveal the regulatory role of GWAS. In this review, we review three types of gene-trait association detection methods of integrating GWAS summary statistics and eQTLs data, namely colocalization methods, transcriptome-wide association study-oriented approaches, and Mendelian randomization-related methods. At the theoretical level, we discussed the differences, relationships, advantages, and disadvantages of various algorithms in the three kinds of gene-trait association detection methods. To further discuss the performance of various methods, we summarize the significant gene sets that influence high-density lipoprotein, low-density lipoprotein, total cholesterol, and triglyceride reported in 16 studies. We discuss the performance of various algorithms using the datasets of the four lipid traits. The advantages and limitations of various algorithms are analyzed based on experimental results, and we suggest directions for follow-up studies on detecting gene-trait associations. [ABSTRACT FROM AUTHOR]

Chronic pain is a common, poorly understood condition. Genetic studies including genome-wide association studies have identified many relevant variants, which have yet to be translated into full understanding of chronic pain. Transcriptome-wide association studies using transcriptomic imputation methods such as S-PrediXcan can help bridge this genotype-phenotype gap. We carried out transcriptomic imputation using S-PrediXcan to identify genetically regulated gene expression associated with multisite chronic pain in 13 brain tissues and whole blood. Then, we imputed genetically regulated gene expression for over 31,000 Mount Sinai Bio Me participants and performed a phenome-wide association study to investigate clinical relationships in chronic pain–associated gene expression changes. We identified 95 experiment-wide significant gene-tissue associations (p < 7.97 × 10−7), including 36 unique genes and an additional 134 gene-tissue associations reaching within-tissue significance, including 53 additional unique genes. Of the 89 unique genes in total, 59 were novel for multisite chronic pain and 18 are established drug targets. Chronic pain genetically regulated gene expression for 10 unique genes was significantly associated with cardiac dysrhythmia, metabolic syndrome, disc disorders/dorsopathies, joint/ligament sprain, anemias, and neurologic disorder phecodes. Phenome-wide association study analyses adjusting for mean pain score showed that associations were not driven by mean pain score. We carried out the largest transcriptomic imputation study of any chronic pain trait to date. Results highlight potential causal genes in chronic pain development and tissue and direction of effect. Several gene results were also drug targets. Phenome-wide association study results showed significant associations for phecodes including cardiac dysrhythmia and metabolic syndrome, thereby indicating potential shared mechanisms. [ABSTRACT FROM AUTHOR]

Psoriasis is a chronic inflammatory skin disease characterized by cutaneous eruptions and pruritus. Because the genetic backgrounds of psoriasis are only partially revealed, an integrative and rigorous study is necessary. We conducted a transcriptome-wide association study (TWAS) with the new Genotype-Tissue Expression version 8 reference panels, including some tissue and multi-tissue panels that were not used previously. We performed tissue-specific heritability analyses on genome-wide association study data to prioritize the tissue panels for TWAS analysis. TWAS and colocalization (COLOC) analyses were performed with eight tissues from the single-tissue panels and the multi-tissue panels of context-specific genetics (CONTENT) to increase tissue specificity and statistical power. From TWAS, we identified the significant associations of 101 genes in the single-tissue panels and 64 genes in the multi-tissue panels, of which 26 genes were replicated in the COLOC. Functional annotation and network analyses identified that the genes were associated with psoriasis and/or immune responses. We also suggested drug candidates that interact with jointly significant genes through a conditional and joint analysis. Together, our findings may contribute to revealing the underlying genetic mechanisms and provide new insights into treatments for psoriasis. [ABSTRACT FROM AUTHOR]

Abstract Background Mammographic density (MD) phenotypes, including percent density (PMD), area of dense tissue (DA), and area of non-dense tissue (NDA), are associated with breast cancer risk. Twin studies suggest that MD phenotypes are highly heritable. However, only a small proportion of their variance is explained by identified genetic variants. Methods We conducted a genome-wide association study, as well as a transcriptome-wide association study (TWAS), of age- and BMI-adjusted DA, NDA, and PMD in up to 27,900 European-ancestry women from the MODE/BCAC consortia. Results We identified 28 genome-wide significant loci for MD phenotypes, including nine novel signals (5q11.2, 5q14.1, 5q31.1, 5q33.3, 5q35.1, 7p11.2, 8q24.13, 12p11.2, 16q12.2). Further, 45% of all known breast cancer SNPs were associated with at least one MD phenotype at p

Summary: Background: Gastric cancer (GC) is clinically heterogenous according to location (cardia/non-cardia) and histopathology (diffuse/intestinal). We aimed to characterize the genetic risk architecture of GC according to its subtypes. Another aim was to examine whether cardia GC and oesophageal adenocarcinoma (OAC) and its precursor lesion Barrett’s oesophagus (BO), which are all located at the gastro-oesophageal junction (GOJ), share polygenic risk architecture. Methods: We did a meta-analysis of ten European genome-wide association studies (GWAS) of GC and its subtypes. All patients had a histopathologically confirmed diagnosis of gastric adenocarcinoma. For the identification of risk genes among GWAS loci we did a transcriptome-wide association study (TWAS) and expression quantitative trait locus (eQTL) study from gastric corpus and antrum mucosa. To test whether cardia GC and OAC/BO share genetic aetiology we also used a European GWAS sample with OAC/BO. Findings: Our GWAS consisting of 5816 patients and 10,999 controls highlights the genetic heterogeneity of GC according to its subtypes. We newly identified two and replicated five GC risk loci, all of them with subtype-specific association. The gastric transcriptome data consisting of 361 corpus and 342 antrum mucosa samples revealed that an upregulated expression of MUC1, ANKRD50, PTGER4, and PSCA are plausible GC-pathomechanisms at four GWAS loci. At another risk locus, we found that the blood-group 0 exerts protective effects for non-cardia and diffuse GC, while blood-group A increases risk for both GC subtypes. Furthermore, our GWAS on cardia GC and OAC/BO (10,279 patients, 16,527 controls) showed that both cancer entities share genetic aetiology at the polygenic level and identified two new risk loci on the single-marker level. Interpretation: Our findings show that the pathophysiology of GC is genetically heterogenous according to location and histopathology. Moreover, our findings point to common molecular mechanisms underlying cardia GC and OAC/BO. Funding: German Research Foundation (DFG).

Objective: To identify novel candidate genes whose expression is associated with bone mineral density (BMD) and body lean mass (LM) in children. Methods: A tissue-specific transcriptome-wide association study (TWAS) was conducted utilizing a large-scale genome-wide association study (GWAS) dataset associated with BMD and LM and involving 10,414 participants. The measurement of BMD and LM phenotypes was made based on total-body dual-energy X-ray absorptiometry (TB-DXA) scans. TWAS was conducted by using FUSION software. Reference panels for muscle skeleton (MS), peripheral blood (NBL) and whole blood (YBL) were used for TWAS analysis. Functional enrichment and protein–protein interaction (PPI) analyses of the genes identified by TWAS were performed by using the online tool Metascape (http://metascape.org). Results: For BMD, we identified 174 genes with P < 0.05, such as IKZF1 (P = 1.46 × 10−9) and CHKB (P = 8.31 × 10−7). For LM, we identified 208 genes with P < 0.05, such as COPS5 (P = 3.03 × 10−12) and MRPS33 (P = 5.45 × 10−10). Gene ontology (GO) enrichment analysis of the BMD-associated genes revealed 200 GO terms, such as protein catabolic process (Log P = −5.09) and steroid hormone-mediated signaling pathway (Log P = −3.13). GO enrichment analysis of the LM-associated genes detected 287 GO terms, such as the apoptotic signaling pathway (Log P = −8.08) and lipid storage (Log P = −3.55). Conclusion: This study identified several candidate genes for BMD and LM in children, providing novel clues to the genetic mechanisms underlying the development of childhood BMD and LM. [ABSTRACT FROM AUTHOR]

Amyotrophic lateral sclerosis, a fatal neurodegeneration disease affecting motor neurons in the brain and spinal cord, is difficult to diagnose and treat. The objective of this study is to identify novel candidate genes related to ALS. Transcriptome-wide association study of ALS was conducted by integrating the genome-wide association study summary data (including 1234 ALS patients and 2850 controls) and pre-computed gene expression weights of different tissues. The ALS-associated genes identified by TWAS were further compared with the differentially expressed genes detected by the mRNA expression profiles of the sporadic ALS. Functional enrichment and annotation analysis of identified genes were performed by an R package and the functional mapping and annotation software. TWAS identified 761 significant genes (PTWAS < 0.05), 627 Gene ontology terms, and 8 Kyoto Encyclopedia of Genes and Genomes pathways for ALS, such as C9orf72, with three expression quantitative trait loci were found significantly: rs2453554 (PTWAS CBRS = 4.68 × 10–10, PTWAS CBRS = 2.54 × 10–9), rs10967976 (PTWAS CBRS = 7.85 × 10–10, PTWAS CBRS = 8.91 × 10–9, PTWAS CBRS = 1.49 × 10–7, PTWAS CBRS = 5.59 × 10–7), rs3849946 (PTWAS CBRS = 7.69 × 10–4, PTWAS YBL = 4.02 × 10–2), Mitochondrion (Padj = 4.22 × 10–16), and Cell cycle (Padj = 2.04 × 10–3). Moreover, 107 common genes, 4 KEGG pathways and 41 GO terms were detected by integrating mRNA expression profiles of sALS, such as CPVL (FC = 2.06, PmRNA = 6.99 × 10–6, PTWAS CBR = 2.88 × 10–2, PTWAS CBR = 4.37 × 10–2), Pyrimidine Metabolism (Padj = 2.43 × 10–2), and Cell Activation (Padj = 5.54 × 10–3). Multiple candidate genes and pathways were detected for ALS. Our findings may provide novel clues for understanding the genetic mechanism of ALS. [ABSTRACT FROM AUTHOR]

Several genes associated with periodontitis have been identified through genome-wide association studies (GWAS); however, known genes only explain a minority of the estimated heritability. We aimed to explore more susceptibility genes and the underlying mechanisms of periodontitis. Firstly, a genome-wide meta-analysis of 38,532 patients and 316,185 healthy controls was performed. Then, cross- and single-tissue transcriptome-wide association studies (TWAS) were conducted based on GWAS summary statistics and the Genotype-Tissue Expression (GTEx) project. Risk genes were evaluated to determine if they were differentially expressed in periodontitis sites compared with unaffected sites using public datasets. Finally, gene co-expression network analysis was conducted to identify the functional biology of the susceptible genes. A total of eight single nucleotide polymorphisms (SNPs) within the introns of lncRNA LINC02141 approached genome-wide significance after meta-analysis. EZH1 was identified as a novel susceptibility gene for periodontitis by TWAS and was significantly upregulated in periodontitis-affected gingival tissues. EZH1 co-expression genes were greatly enriched in the cell-substrate junction, focal adhesion and other important pathways. Our findings may offer a fundamental clue for comprehending the genetic mechanisms of periodontitis. [ABSTRACT FROM AUTHOR]

Nasopharyngeal carcinoma (NPC) is an Asia-prevalent malignancy, yet its genetic underpinnings remain incompletely understood. Here, a transcriptome-wide association study (TWAS) is conducted on NPC, leveraging gene expression prediction models based on epithelial tissues and genome-wide association study (GWAS) summary statistics from 1577 NPC cases and 6359 controls of southern Chinese descent. The TWAS identifies VAMP8 on chromosome 2p11.2 as a novel susceptibility gene for NPC. Further fine-mapping analyses pinpoint rs1058588, located within VAMP8, as a causal variant through eQTL colocalization, and GWAS analyses across multiple cohorts, achieving GWAS significance (OR = 1.18, P = 3.09 × 10 -10 ). Functional assays demonstrate that VAMP8 exerts a tumorigenic role in NPC, enhancing cell proliferation, migration, and tumor growth. Mechanically, it is uncovered that rs1058588 modulates VAMP8 expression by altering its binding affinity to miR-185. Furthermore, the results show that VAMP8 interacts with DHX9 to facilitate the nuclear recruitment of p65, activating the NF-κB pathway. Collectively, the findings shed light on the genetic predisposition to NPC and underscore the critical role of the functional axis involving miR-185, VAMP8, DHX9, and the NF-κB pathway in NPC pathogenesis., (© 2025 The Author(s). Advanced Science published by Wiley‐VCH GmbH.)

Summary: The regulation of gene expression plays an essential role in both the phenotype and adaptation of plants. Transcriptome sequencing enables simultaneous identification of exonic variants and quantification of gene expression. Here, we sequenced the leaf transcriptomes of 287 rice accessions from around the world and obtained a total of 177 853 high‐quality single nucleotide polymorphisms after filtering. Genome‐wide association study identified 44 354 expression quantitative trait loci (eQTLs), which regulate the expression of 13 201 genes, as well as 17 local eQTL hotspots and 96 distant eQTL hotspots. Furthermore, a transcriptome‐wide association study screened 21 candidate genes for starch content in the flag leaves at the heading stage. HS002 was identified as a significant distant eQTL hotspot with five downstream genes enriched for diterpene antitoxin synthesis. Co‐expression analysis, eQTL analysis, and linkage mapping together demonstrated that bHLH026 acts as a key regulator to activate the expression of downstream genes. The transgenic assay revealed that bHLH026 is an important regulator of diterpenoid antitoxin synthesis and enhances the disease resistance of rice. These findings improve our knowledge of the regulatory mechanisms of gene expression variation and complex regulatory networks of the rice genome and will facilitate genetic improvement of cultivated rice varieties. [ABSTRACT FROM AUTHOR]

Abstract 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.

Abstract Background Osteoarthritis (OA) is a common skeletal system disease that has been partially attributed to genetic factors. The hand is frequently affected, which seriously affects the patient’s quality of life. However, the pathogenetic mechanism of hand osteoarthritis (hand OA) is still elusive. Methods A genome-wide association study (GWAS) summary of hand OA was obtained from the UK Biobank dataset, which contains data from a total of 452,264 White British individuals, including 37,782 OA patients. The transcriptome-wide association study (TWAS) of hand OA was performed using FUnctional Summary-based ImputatiON (FUSION) with the skeletal muscle and blood as gene expression references. The significant genes identified by TWAS were further subjected to gene set enrichment analysis (GSEA) with the Database for Annotation, Visualization and Integrated Discovery (DAVID) tool. Furthermore, we compared the genes and gene sets identified by our TWAS with that of a knee OA mRNA expression profile to detect the genes and gene sets shared by TWAS and mRNA expression profiles in OA. The mRNA expression profiles of 18 normal knee cartilages and 20 OA knee cartilages were acquired from the Gene Expression Omnibus database (accession number: GSE114007). Results TWAS identified 177 genes with P

Abstract Objective To identify rheumatoid arthritis (RA)-associated susceptibility genes and pathways through integrating genome-wide association study (GWAS) and gene expression profile data. Methods A transcriptome-wide association study (TWAS) was conducted by the FUSION software for RA considering EBV-transformed lymphocytes (EL), transformed fibroblasts (TF), peripheral blood (NBL), and whole blood (YBL). GWAS summary data was driven from a large-scale GWAS, involving 5539 autoantibody-positive RA patients and 20,169 controls. The TWAS-identified genes were further validated using the mRNA expression profiles and made a functional exploration. Results TWAS identified 692 genes with P TWAS values

This study aimed to identify susceptibility genes and pathways associated with ankylosing spondylitis (AS) by integrating whole transcriptome-wide association study (TWAS) analysis and mRNA expression profiling data. AS genome-wide association study (GWAS) summary data from the large GWAS database were used. This included data of 1265 AS patients and 452264 controls. A TWAS of AS was conducted using these data. The analysis software used was FUSION, and Epstein-Barr virus–transformed lymphocytes, transformed fibroblasts, peripheral blood, and whole blood were used as gene expression references. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed for the important genes identified via TWAS. Protein-protein interaction (PPI) network analysis based on the STRING database was also performed to detect genes shared by TWAS and mRNA expression profiles in AS. TWAS identified 920 genes (P <0.05) and analyzed mRNA expression profiles to obtain 1183 differential genes. Following comparison of the TWAS results and mRNA expression characteristics, we obtained 70 overlapping genes and performed GO and KEGG enrichment analyses of these genes to obtain 16 pathways. Via PPI network analysis, we obtained the protein interaction network and performed MCODE analysis to acquire the HUB genes. Similarly, we performed GO and KEGG analyses on the genes identified by TWAS, obtained 98 pathways after screening, and analyzed protein interactions via the PPI network. Through the integration of TWAS and mRNA expression analysis, genes related to AS and GO and KEGG terms were determined, providing new evidence and revealing the pathogenesis of AS. Our AS TWAS work identified novel genes associated with AS, as well as suggested potential tissues and pathways of action for these TWAS AS genes, providing a new direction for research into the pathogenesis of AS. [ABSTRACT FROM AUTHOR]

Background: Mammographic density (MD) phenotypes, including percent density (PMD), area of dense tissue (DA), and area of non-dense tissue (NDA), are associated with breast cancer risk. Twin studies suggest that MD phenotypes are highly heritable. However, only a small proportion of their variance is explained by identified genetic variants.Methods: We conducted a genome-wide association study, as well as a transcriptome-wide association study (TWAS), of age- and BMI-adjusted DA, NDA, and PMD in up to 27,900 European-ancestry women from the MODE/BCAC consortia.Results: We identified 28 genome-wide significant loci for MD phenotypes, including nine novel signals (5q11.2, 5q14.1, 5q31.1, 5q33.3, 5q35.1, 7p11.2, 8q24.13, 12p11.2, 16q12.2). Further, 45% of all known breast cancer SNPs were associated with at least one MD phenotype at p < 0.05. TWAS further identified two novel genes (SHOX2 and CRISPLD2) whose genetically predicted expression was significantly associated with MD phenotypes.Conclusions: Our findings provided novel insight into the genetic background of MD phenotypes, and further demonstrated their shared genetic basis with breast cancer. [ABSTRACT FROM AUTHOR]

This study aimed to identify susceptibility genes and pathways associated with ankylosing spondylitis (AS) by integrating whole transcriptome-wide association study (TWAS) analysis and mRNA expression profiling data. AS genome-wide association study (GWAS) summary data from the large GWAS database were used. This included data of 1265 AS patients and 452264 controls. A TWAS of AS was conducted using these data. The analysis software used was FUSION, and Epstein-Barr virus–transformed lymphocytes, transformed fibroblasts, peripheral blood, and whole blood were used as gene expression references. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed for the important genes identified via TWAS. Protein-protein interaction (PPI) network analysis based on the STRING database was also performed to detect genes shared by TWAS and mRNA expression profiles in AS. TWAS identified 920 genes (P

Background: Endometrial cancer (EC) is the most common gynecological malignancy in developed countries, with incidence rates continuing to rise globally. However, the precise mechanisms underlying EC pathogenesis remain largely unexplored. This study aims to prioritize genes associated with EC by leveraging multi-omics data through various bioinformatic methods., Methods: We utilized the Open Targets Genetics (OTG) database to pinpoint potential causal variants and target genes for EC. To explore the pleiotropic effects of gene expression on EC, we applied the Summary-based Mendelian Randomization (SMR) using summary data from a genome-wide association study (GWAS) on EC and expression quantitative trait loci (eQTL) data from the Consortium for the Architecture of Gene Expression (CAGE). We also conducted a cross-tissue transcriptome-wide association study (TWAS) employing sparse canonical correlation analysis (sCCA). Results from the sCCA TWAS and single-tissue TWAS for 22 tissues were combined using the aggregated Cauchy association test (sCCA + ACAT) to identify genes with cis-regulated expression levels linked to EC., Results: The OTG database recognized 15 genomic loci showing independent association with EC. Gene prioritization highlighted nine genes with relatively high locus-to-gene (L2G) scores (≥0.5), the majority of which aligned with those identified using the closest gene. Colocalization analysis identified 11 additional genes at these loci. Our SMR analysis revealed two genes, EVI2A and SRP14 , exhibiting a significant pleiotropic association with EC. Cross-tissue TWAS identified 31 genes whose expression was significantly associated with EC after correction for multiple testing, with four genes ( EIF2AK4 , EVI2A , EVI2B , and NF1 ) also confirmed by gene colocalization in the OTG analysis., Conclusions: We confirmed the involvement of EVI2A in the pathogenesis of EC and identified several other genes that may contribute to EC development. These findings offer new insights into the genetic mechanisms underlying EC and may inform future research and therapeutic strategies., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tcr.amegroups.com/article/view/10.21037/tcr-24-887/coif). The authors have no conflicts of interest to declare., (2024 AME Publishing Company. All rights reserved.)

Instrumental variable (IV) analysis has been widely applied in epidemiology to infer causal relationships using observational data. Genetic variants can also be viewed as valid IVs in Mendelian randomization and transcriptome-wide association studies. However, most multivariate IV approaches cannot scale to high-throughput experimental data. Here, we leverage the flexibility of our previous work, a hierarchical model that jointly analyzes marginal summary statistics (hJAM), to a scalable framework (SHA-JAM) that can be applied to a large number of intermediates and a large number of correlated genetic variants-situations often encountered in modern experiments leveraging omic technologies. SHA-JAM aims to estimate the conditional effect for high-dimensional risk factors on an outcome by incorporating estimates from association analyses of single-nucleotide polymorphism (SNP)-intermediate or SNP-gene expression as prior information in a hierarchical model. Results from extensive simulation studies demonstrate that SHA-JAM yields a higher area under the receiver operating characteristics curve (AUC), a lower mean-squared error of the estimates, and a much faster computation speed, compared to an existing approach for similar analyses. In two applied examples for prostate cancer, we investigated metabolite and transcriptome associations, respectively, using summary statistics from a GWAS for prostate cancer with more than 140,000 men and high dimensional publicly available summary data for metabolites and transcriptomes., (© 2024 The Authors. Genetic Epidemiology published by Wiley Periodicals LLC.)

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 (PPERM.ANL = 1.68 × 10–3) and SFTPD for an unclassified genus of Proteobacteria in transverse colon (PPERM.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. [ABSTRACT FROM AUTHOR]

Age-related hearing loss (ARHL) is associated with cognitive dysfunction; however, the detailed underlying mechanisms remain unclear. The aim of this study is to investigate the potential underlying mechanism with a system genetics approach. A transcriptome-wide association study was performed on aged (12–32 months old) BXD mice strains. The hippocampus gene expression was obtained from 56 BXD strains, and the hearing acuity was assessed from 54 BXD strains. Further correlation analysis identified a total of 1,435 hearing-related genes in the hippocampus (p < 0.05). Pathway analysis of these genes indicated that the impaired glutamatergic synapse pathway is involved in ARHL (p = 0.0038). Further gene co-expression analysis showed that the expression level of glutamine synthetase (Gls), which is significantly correlated with ARHL (n = 26, r = −0.46, p = 0.0193), is a crucial regulator in glutamatergic synapse pathway and associated with learning and memory behavior. In this study, we present the first systematic evaluation of hippocampus gene expression pattern associated with ARHL, learning, and memory behavior. Our results provide novel potential molecular mechanisms involved in ARHL and cognitive dysfunction association. [ABSTRACT FROM AUTHOR]

Abstract Background Chondropathies are a group of cartilage diseases, which share some common pathogenetic features. The etiology of chondropathies is still largely obscure now. Methods A transcriptome-wide association study (TWAS) was performed using the UK Biobank genome-wide association study (GWAS) data of chondropathies (including 1314 chondropathy patients and 450,950 controls) with gene expression references of muscle skeleton (MS) and peripheral blood (YBL). The candidate genes identified by TWAS were further compared with three gene expression profiles of osteoarthritis (OA), cartilage tumor (CT), and spinal disc herniation (SDH), to confirm the functional relevance between the chondropathies and the candidate genes identified by TWAS. Functional mapping and annotation (FUMA) was used for the gene ontology enrichment analyses. Immunohistochemistry (IHC) was conducted to validate the accuracy of integrative analysis results. Results Integrating TWAS and mRNA expression profiles detected 84 candidate genes for knee OA, such as DDX20 (P TWAS YBL = 1.79 × 10− 3, fold change (FC) = 2.69), 10 candidate genes for CT, such as SRGN (P TWAS YBL = 1.46 × 10− 3, FC = 3.36), and 4 candidate genes for SDH, such as SUPV3L1 (P TWAS YBL = 3.59 × 10− 3, FC = 3.22). Gene set enrichment analysis detected 73 GO terms for knee OA, 3 GO terms for CT, and 1 GO term for SDH, such as mitochondrial protein complex (P = 7.31 × 10− 5) for knee OA, cytokine for CT (P = 1.13 × 10− 4), and ion binding for SDH (P = 3.55 × 10− 4). IHC confirmed that the protein expression level of DDX20 was significantly different between knee OA cartilage and healthy control cartilage (P = 0.0358). Conclusions Multiple candidate genes and GO terms were detected for chondropathies. Our findings may provide a novel insight in the molecular mechanisms of chondropathies.

ObjectiveThis study aims to identify novel candidate genes associated with osteonecrosis of the femoral head (ONFH).MethodsA transcriptome-wide association study (TWAS) was performed by integrating the genome-wide association study dataset of osteonecrosis (ON) in the UK Biobank with pre-computed mRNA expression reference weights of muscle skeleton (MS) and blood. The ON-associated genes identified by TWAS were further subjected to gene ontology (GO) analysis by the DAVID tool. Finally, a trans-omics comparative analysis of TWAS and genome-wide mRNA expression profiling was conducted to identify the common genes and the GO terms shared by both DNA-level TWAS and mRNA-level expression profile for ONFH.ResultsTWAS totally identified 564 genes that were with PTWAS value

Objective: This study aims to identify novel candidate genes associated with osteonecrosis of the femoral head (ONFH). Methods: A transcriptome-wide association study (TWAS) was performed by integrating the genome-wide association study dataset of osteonecrosis (ON) in the UK Biobank with pre-computed mRNA expression reference weights of muscle skeleton (MS) and blood. The ON-associated genes identified by TWAS were further subjected to gene ontology (GO) analysis by the DAVID tool. Finally, a trans-omics comparative analysis of TWAS and genome-wide mRNA expression profiling was conducted to identify the common genes and the GO terms shared by both DNA-level TWAS and mRNA-level expression profile for ONFH. Results: TWAS totally identified 564 genes that were with P TWAS value <0.05 for MS and blood, such as CBX1 (P TWAS = 0.0001 for MS), SRPK2 (P TWAS = 0.0002 for blood), and MYO5A (P TWAS = 0.0005 for blood). After comparing the genes detected by TWAS with the differentially expressed genes identified by mRNA expression profiling, we detected 59 overlapped genes, such as STEAP4 [ P TWAS = 0.0270, FC (fold change)mRNA = 7.03], RABEP1 (P TWAS = 0.010, FCmRNA = 2.22), and MORC3 (P TWAS = 0.0053, FCmRNA = 2.92). The GO analysis of TWAS-identified genes discovered 53 GO terms for ON. Further comparing the GO results of TWAS and mRNA expression profiling identified four overlapped GO terms, including cysteine-type endopeptidase activity (P TWAS = 0.0006, P mRNA = 0.0227), extracellular space (P TWAS = 0.0342, P mRNA = 0.0012), protein binding (P TWAS = 0.0112, P mRNA = 0.0106), and ATP binding (P TWAS = 0.0464, P mRNA = 0.0033). Conclusion: Several ONFH-associated genes and GO terms were identified by integrating TWAS and mRNA expression profiling. It provides novel clues to reveal the pathogenesis of ONFH. [ABSTRACT FROM AUTHOR]

Genome-wide association studies (GWAS) have identified multiple causal genes associated with amyotrophic lateral sclerosis (ALS); however, the genetic architecture of ALS remains completely unknown and a large number of causal genes have yet been discovered. To full such gap in part, we implemented an integrative analysis of transcriptome-wide association study (TWAS) for ALS to prioritize causal genes with summary statistics from 80,610 European individuals and employed 13 GTEx brain tissues as reference transcriptome panels. The summary-level TWAS analysis with single brain tissue was first undertaken and then a flexible p-value combination strategy, called summary data-based Cauchy Aggregation TWAS (SCAT), was proposed to pool association signals from single-tissue TWAS analysis while protecting against highly positive correlation among tests. Extensive simulations demonstrated SCAT can produce well-calibrated p-value for the control of type I error and was often much more powerful to identify association signals across various scenarios compared with single-tissue TWAS analysis. Using SCAT, we replicated three ALS-associated genes (i.e., ATXN3, SCFD1, and C9orf72) identified in previous GWASs and discovered additional five genes (i.e., SLC9A8, FAM66D, TRIP11, JUP, and RP11-529H20.6) which were not reported before. Furthermore, we discovered the five associations were largely driven by genes themselves and thus might be new genes which were likely related to the risk of ALS. However, further investigations are warranted to verify these results and untangle the pathophysiological function of the genes in developing ALS.

Genome-wide association studies (GWAS) have identified multiple causal genes associated with amyotrophic lateral sclerosis (ALS); however, the genetic architecture of ALS remains completely unknown and a large number of causal genes have yet been discovered. To full such gap in part, we implemented an integrative analysis of transcriptome-wide association study (TWAS) for ALS to prioritize causal genes with summary statistics from 80,610 European individuals and employed 13 GTEx brain tissues as reference transcriptome panels. The summary-level TWAS analysis with single brain tissue was first undertaken and then a flexible p -value combination strategy, called summary data-based Cauchy Aggregation TWAS (SCAT), was proposed to pool association signals from single-tissue TWAS analysis while protecting against highly positive correlation among tests. Extensive simulations demonstrated SCAT can produce well-calibrated p -value for the control of type I error and was often much more powerful to identify association signals across various scenarios compared with single-tissue TWAS analysis. Using SCAT, we replicated three ALS-associated genes (i.e., ATXN3 , SCFD1 , and C9orf72) identified in previous GWASs and discovered additional five genes (i.e., SLC9A8 , FAM66D , TRIP11 , JUP , and RP11-529H20.6) which were not reported before. Furthermore, we discovered the five associations were largely driven by genes themselves and thus might be new genes which were likely related to the risk of ALS. However, further investigations are warranted to verify these results and untangle the pathophysiological function of the genes in developing ALS. [ABSTRACT FROM AUTHOR]

Summary: To scan novel candidate genes associated with osteoporosis, a two-stage transcriptome-wide association study (TWAS) of bone mineral density (BMD) was conducted. The BMD-associated genes identified by TWAS were then compared with the gene expression profiling of BMD in bone cells, B cells, and mesenchymal stem cells. We identified multiple candidate genes and gene ontology (GO) terms associated with BMD. Introduction: Osteoporosis (OP) is a metabolic bone disease characterized by decrease in BMD. Our objective is to scan novel candidate genes associated with OP. Methods: A transcriptome-wide association study (TWAS) was performed by integrating the genome-wide association study (GWAS) summary of bone mineral density (BMD) with two pre-computed mRNA expression weights of peripheral blood and muscle skeleton. Then, another independent GWAS data of BMD was used to verify the discovery results. The BMD-associated genes identified between discovery and replicate TWAS were further subjected to gene ontology (GO) analysis implemented by DAVID. Finally, the BMD-associated genes and GO terms were further compared with the mRNA expression profiling results of BMD to detect the common genes and GO terms shared by both DNA-level TWAS and mRNA expression profile analysis. Results: TWAS identified 95 common genes with permutation P value < 0.05 for peripheral blood and muscle skeleton, such as TMTC4 in muscle skeleton and DDX17 in peripheral blood. Further comparing the genes detected by discovery-replicate TWAS with the differentially expressed genes identified by mRNA expression profiling of OP patients found 18 overlapped genes, such as MUL1 in muscle skeleton and SPTBN1 in peripheral blood. GO analysis of the genes identified by discovery-replicate TWAS detected 12 BMD-associated GO terms, such as negative regulation of cell growth and regulation of glycogen catabolic process. Further comparing the GO results of discovery-replicate TWAS and mRNA expression profiles found 6 overlapped GO terms, such as membrane and cell adhesion. Conclusion: Our study identified multiple candidate genes and GO terms for BMD, providing novel clues for understanding the genetic mechanism of OP. [ABSTRACT FROM AUTHOR]

Two new gene-based association analysis methods, called PrediXcan and TWAS for GWAS individual-level and summary data, respectively, were recently proposed to integrate GWAS with eQTL data, alleviating two common problems in GWAS by boosting statistical power and facilitating biological interpretation of GWAS discoveries. Based on a novel reformulation of PrediXcan and TWAS, we propose a more powerful gene-based association test to integrate single set or multiple sets of eQTL data with GWAS individual-level data or summary statistics. The proposed test was applied to several GWAS datasets, including two lipid summary association datasets based on ~100; 000 and ~189; 000 samples, respectively, and uncovered more known or novel trait-associated genes, showcasing much improved performance of our proposed method. The software implementing the proposed method is freely available as an R package. [ABSTRACT FROM AUTHOR]

Although genome-wide association studies (GWASs) have identified thousands of risk loci for many complex traits and diseases, the causal variants and genes at these loci remain largely unknown. Here, we introduce a method for estimating the local genetic correlation between gene expression and a complex trait and utilize it to estimate the genetic correlation due to predicted expression between pairs of traits. We integrated gene expression measurements from 45 expression panels with summary GWAS data to perform 30 multi-tissue transcriptome-wide association studies (TWASs). We identified 1,196 genes whose expression is associated with these traits; of these, 168 reside more than 0.5 Mb away from any previously reported GWAS significant variant. We then used our approach to find 43 pairs of traits with significant genetic correlation at the level of predicted expression; of these, eight were not found through genetic correlation at the SNP level. Finally, we used bi-directional regression to find evidence that BMI causally influences triglyceride levels and that triglyceride levels causally influence low-density lipoprotein. Together, our results provide insight into the role of gene expression in the susceptibility of complex traits and diseases. [ABSTRACT FROM AUTHOR]

• Different TWAS approaches were used in the cannabis use disorder (CUD) study. • A total of 26 CUD TWAS-related genes were identified. • The FOCUS method was utilized to prioritize CUD causal genes. • GO and KEGG revealed several terms related to CUD. • The study contributes to uncovering the CUD mechanism. Cannabis is one of the most commonly used psychoactive substances, which could induce moderate-severe cannabis use disorders (CUD). Here, a tissue-specific transcriptome-wide association study (TWAS) of CUD was performed by FUSION and S-PrediXcan, utilizing a genome-wide association study (GWAS) dataset of CUD (including 43,380 cases and 141,385 controls of European ancestry) and gene expression reference data from 17 different brain-related and non-brain related tissues, with totally 26 TWAS-associated genes were identified, including CADM2 (P = 2.13 × 10-17), SRR (P = 8.09 × 10-9) and TUFM (P = 1.24 × 10-8). Fine-mapping of causal gene sets (FOCUS) was used to prioritize genes with strong evidence for causality, and SRR , CADM2-AS1 , and SH2B1 were prioritized with a posterior probability of 0.973, 0.951, and 0.788, respectively. Furthermore, gene ontology (GO) and pathway enrichment analysis on CUD-associated genes were performed, including cytosol, protein binding, nucleoplasm, metabolic pathways, and herpes simplex virus 1 infection. These findings could provide new insights for understanding the mechanism of CUD. [ABSTRACT FROM AUTHOR]

Background: Obesity, defined as pathologically increased body mass index (BMI), is strongly related to an increased risk for numerous common cardiovascular and metabolic diseases. It is particularly associated with insulin resistance, hyperglycemia, and systemic oxidative stress and represents the most important risk factor for type 2 diabetes (T2D). However, the pathophysiological mechanisms underlying these associations are still not completely understood. Therefore, in order to identify potentially disease-relevant BMI-associated gene expression signatures, a transcriptome-wide association study (TWAS) on BMI was performed. Methods: Whole-blood mRNA levels determined by array-based transcriptional profiling were correlated with BMI in two large independent population-based cohort studies (KORA F4 and SHIP-TREND) comprising a total of 1977 individuals. Results: Extensive alterations of the whole-blood transcriptome were associated with BMI: More than 3500 transcripts exhibited significant positive or negative BMI-correlation. Three major whole-blood gene expression signatures associated with increased BMI were identified. The three signatures suggested: i) a ratio shift from mature erythrocytes towards reticulocytes, ii) decreased expression of several genes essentially involved in the transmission and amplification of the insulin signal, and iii) reduced expression of several key genes involved in the defence against reactive oxygen species (ROS). Conclusions: Whereas the first signature confirms published results, the other two provide possible mechanistic explanations for well-known epidemiological findings under conditions of increased BMI, namely attenuated insulin signaling and increased oxidative stress. The putatively causative BMI-dependent down-regulation of the expression of numerous genes on the mRNA level represents a novel finding. BMI-associated negative transcriptional regulation of insulin signaling and oxidative stress management provide new insights into the pathogenesis of metabolic syndrome and T2D. [ABSTRACT FROM AUTHOR]

Transcriptome-wide association studies (TWAS) systematically investigate the association of genetically predicted gene expression with disease risk, providing an effective approach to identify novel susceptibility genes. Osteoporosis is the most common metabolic bone disease, associated with reduced bone mineral density (BMD) and increased risk of osteoporotic fractures, whereas genetic factors explain approximately 70% of the variance in phenotypes associated with bone. BMD is commonly assessed using dual-energy X-ray absorptiometry (DXA) to obtain measurements (g/cm2) of areal BMD. However, quantitative computed tomography (QCT) measured 3D volumetric BMD (vBMD) (g/cm3) has important advantages compared with DXA since it can evaluate cortical and trabecular microstructural features of bone quality, which can be used to directly predict fracture risk. Here, we performed the first TWAS for volumetric BMD (vBMD) by integrating genome-wide association studies (GWAS) data from two independent cohorts, namely the Framingham Heart Study (FHS, n = 3298) and the Osteoporotic Fractures in Men (MrOS, n = 4641), with tissue-specific gene expression data from the Genotype-Tissue Expression (GTEx) project. We first used stratified linkage disequilibrium (LD) score regression approach to identify 12 vBMD-relevant tissues, for which vBMD heritability is enriched in tissue-specific genes of the given tissue. Focusing on these tissues, we subsequently leveraged GTEx expression reference panels to predict tissue-specific gene expression levels based on the genotype data from FHS and MrOS. The associations between predicted gene expression levels and vBMD variation were then tested by MultiXcan, an innovative TWAS method that integrates information available across multiple tissues. We identified 70 significant genes associated with vBMD, including some previously identified osteoporosis-related genes such as LYRM2 and NME8 , as well as some novel loci such as DNAAF2 and SPAG16. Our findings provide novel insights into the pathophysiological mechanisms of osteoporosis and highlight several novel vBMD-associated genes that warrant further investigation. • We performed the first TWAS for volumetric BMD across multiple tissues. • We identified 70 significant genes associated with vBMD. • NME8 and LYRM2 have been revalidated to have a connection with BMD/osteoporosis. • DNAAF2 and SPAG16 were identified to be putative vBMD associated genes. [ABSTRACT FROM AUTHOR]

• TWAS identified 503 genes associated with the susceptibility to dental caries. • We identified 6 common candidate genes and 5 common GO terms associated with dental caries. • Our study results may provide novel clues for understanding the genetic mechanisms of dental caries. The aim of this study was to identify candidate genes and gene sets associated with dental caries by an integrative analysis of transcriptome-wide association study (TWAS) and messenger RNA (mRNA) expression profiling of dental caries. A genome-wide association study (GWAS) dataset of dental caries was obtained from the UK Biobank. A TWAS of dental caries was conducted with the FUSION tool using the gene expression reference weights of musculoskeletal, whole blood, and peripheral blood genes. The dental caries-associated genes identified by the TWAS were further subjected to gene ontology (GO) and pathway enrichment analyses to explore dental caries-related gene sets. Finally, the TWAS results of dental caries were compared with genome-wide mRNA expression profiling of dental caries to detect common genes and gene sets. The TWAS identified 165 musculoskeletal genes, 110 whole blood genes, and 228 peripheral blood genes. GO analysis of the genes identified by the TWAS detected 57 GO terms. For pathway enrichment analysis, we detected 12 candidate pathways. After comparing the TWAS-identified genes with the mRNA expression profiling data, we detected 6 common genes. Further comparing the GO results of the TWAS and mRNA expression profiling identified 5 common GO terms. We identified a group of dental caries-associated genes and GO terms, providing novel clues for understanding the genetic mechanisms of dental caries. [ABSTRACT FROM AUTHOR]

Introduction: Humans and viruses have co-evolved for millennia resulting in a complex host genetic architecture. Understanding the genetic mechanisms of immune response to viral infection provides insight into disease etiology and therapeutic opportunities., Methods: We conducted a comprehensive study including genome-wide and transcriptome-wide association analyses to identify genetic loci associated with immunoglobulin G antibody response to 28 antigens for 16 viruses using serological data from 7924 European ancestry participants in the UK Biobank cohort., Results: Signals in human leukocyte antigen (HLA) class II region dominated the landscape of viral antibody response, with 40 independent loci and 14 independent classical alleles, 7 of which exhibited pleiotropic effects across viral families. We identified specific amino acid (AA) residues that are associated with seroreactivity, the strongest associations presented in a range of AA positions within DRβ1 at positions 11, 13, 71, and 74 for Epstein-Barr Virus (EBV), Varicella Zoster Virus (VZV), Human Herpes virus 7, (HHV7) and Merkel cell polyomavirus (MCV). Genome-wide association analyses discovered 7 novel genetic loci outside the HLA associated with viral antibody response ( P <5.×10 -8 ), including FUT2 (19q13.33) for human polyomavirus BK (BKV), STING1 (5q31.2) for MCV, as well as CXCR5 (11q23.3) and TBKBP1 (17q21.32) for HHV7. Transcriptome-wide association analyses identified 114 genes associated with response to viral infection, 12 outside of the HLA region, including ECSCR : P =5.0×10 -15 (MCV), NTN5 : P =1.1×10 -9 (BKV), and P2RY13 : P =1.1×10 -8 EBV nuclear antigen. We also demonstrated pleiotropy between viral response genes and complex diseases; from autoimmune disorders to cancer to neurodegenerative and psychiatric conditions., Conclusions: Our study confirms the importance of the HLA region in host response to viral infection and elucidates novel genetic determinants beyond the HLA that contribute to host-virus interaction., Competing Interests: COMPETING INTERESTS The authors declare no competing interests.

• For brain tissue, TWAS identified 148 genes with TWAS p value < 0.05, such as TDO2, CHD1L, KIAA0319L and CCDC138. • Eleven common genes were identified, such as ACSM5, CCDC24, MCM6 and MVP though comparing TWAS and mRNA expression profiles. • We detected 23 GO terms with DAVID p value < 0.05 for ADHD and 3 pathways. Attention-deficit/hyperactivity disorder (ADHD) is a common neurodevelopmental disorder, but the genetic mechanism of ADHD remains elusive now. Tissue specific transcriptome-wide association study (TWAS) of ADHD was performed by FUSION utilizing a genome-wide association study (GWAS) dataset of ADHD (including 20,183 ADHD cases and 35,191 healthy controls) and gene expression reference from brain and blood. Furthermore, the genes identified by TWAS were compared with the differently expressed genes detected by mRNA expression profiles of ADHD rat model and autism spectrum disorders (ASD) patients. Functional enrichment and annotation analysis of the identified genes were performed by DAVID and FUMAGWAS tool. For brain tissue, TWAS identified 148 genes with P value < 0.05, such as TDO2 (P TWAS =4.01×10−2), CHD1L (P TWAS =9.64×10−3) and KIAA0319L (P TWAS =4.05×10−4). Further 11 common genes were examined in the mRNA expression datasets, such as ACSM5 (P TWAS =3.62×10−2, P mRNA =0.005), CCDC24 (P TWAS =1.49×10−2, P mRNA =2.35×10−3) and MVP (P TWAS =5.55×10−3, P mRNA =5.40×10−3). Pathway enrichment analysis of the genes identified by TWAS detected 3 pathways for ADHD, including Other glycan degradation (P value=0.021), Viral myocarditis (P value=0.034) and Endocytosis (P value=0.041). Through integrating GWAS and mRNA expression data, we identified a group of ADHD-associated genes and pathways, providing novel clues for understanding the genetic mechanism of ADHD. [ABSTRACT FROM AUTHOR]