1
|
Saferali A, Kim W, Xu Z, Chase RP, Cho MH, Laederach A, Castaldi PJ, Hersh CP. Colocalization analysis of 3' UTR alternative polyadenylation quantitative trait loci reveals novel mechanisms underlying associations with lung function. Hum Mol Genet 2024; 33:1164-1175. [PMID: 38569558 DOI: 10.1093/hmg/ddae055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Revised: 02/02/2024] [Indexed: 04/05/2024] Open
Abstract
While many disease-associated single nucleotide polymorphisms (SNPs) are expression quantitative trait loci (eQTLs), a large proportion of genome-wide association study (GWAS) variants are of unknown function. Alternative polyadenylation (APA) plays an important role in posttranscriptional regulation by allowing genes to shorten or extend 3' untranslated regions (UTRs). We hypothesized that genetic variants that affect APA in lung tissue may lend insight into the function of respiratory associated GWAS loci. We generated alternative polyadenylation (apa) QTLs using RNA sequencing and whole genome sequencing on 1241 subjects from the Lung Tissue Research Consortium (LTRC) as part of the NHLBI TOPMed project. We identified 56 179 APA sites corresponding to 13 582 unique genes after filtering out APA sites with low usage. We found that a total of 8831 APA sites were associated with at least one SNP with q-value < 0.05. The genomic distribution of lead APA SNPs indicated that the majority are intronic variants (33%), followed by downstream gene variants (26%), 3' UTR variants (17%), and upstream gene variants (within 1 kb region upstream of transcriptional start site, 10%). APA sites in 193 genes colocalized with GWAS data for at least one phenotype. Genes containing the top APA sites associated with GWAS variants include membrane associated ring-CH-type finger 2 (MARCHF2), nectin cell adhesion molecule 2 (NECTIN2), and butyrophilin subfamily 3 member A2 (BTN3A2). Overall, these findings suggest that APA may be an important mechanism for genetic variants in lung function and chronic obstructive pulmonary disease (COPD).
Collapse
Affiliation(s)
- Aabida Saferali
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Boston, MA 02115, United States
| | - Wonji Kim
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Boston, MA 02115, United States
| | - Zhonghui Xu
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Boston, MA 02115, United States
| | - Robert P Chase
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Boston, MA 02115, United States
| | - Michael H Cho
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Boston, MA 02115, United States
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, 75 Francis St, Boston, MA 02115, United States
| | - Alain Laederach
- Department of Biology, University of North Carolina at Chapel Hill, 120 South Road, Chapel Hill, NC 27599, United States
| | - Peter J Castaldi
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Boston, MA 02115, United States
- Division of General Medicine and Primary Care, Brigham and Women's Hospital, 75 Francis Street, Boston, MA 02115, United States
| | - Craig P Hersh
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Boston, MA 02115, United States
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, 75 Francis St, Boston, MA 02115, United States
| |
Collapse
|
2
|
Werder RB, Zhou X, Cho MH, Wilson AA. Breathing new life into the study of COPD with genes identified from genome-wide association studies. Eur Respir Rev 2024; 33:240019. [PMID: 38811034 PMCID: PMC11134200 DOI: 10.1183/16000617.0019-2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2024] [Accepted: 02/23/2024] [Indexed: 05/31/2024] Open
Abstract
COPD is a major cause of morbidity and mortality globally. While the significance of environmental exposures in disease pathogenesis is well established, the functional contribution of genetic factors has only in recent years drawn attention. Notably, many genes associated with COPD risk are also linked with lung function. Because reduced lung function precedes COPD onset, this association is consistent with the possibility that derangements leading to COPD could arise during lung development. In this review, we summarise the role of leading genes (HHIP, FAM13A, DSP, AGER and TGFB2) identified by genome-wide association studies in lung development and COPD. Because many COPD genome-wide association study genes are enriched in lung epithelial cells, we focus on the role of these genes in the lung epithelium in development, homeostasis and injury.
Collapse
Affiliation(s)
- Rhiannon B Werder
- Murdoch Children's Research Institute, Melbourne, Australia
- Center for Regenerative Medicine of Boston University and Boston Medical Center, Boston, MA, USA
| | - Xiaobo Zhou
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Michael H Cho
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Andrew A Wilson
- Center for Regenerative Medicine of Boston University and Boston Medical Center, Boston, MA, USA
- The Pulmonary Center and Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| |
Collapse
|
3
|
Salvato I, Ricciardi L, Nucera F, Nigro A, Dal Col J, Monaco F, Caramori G, Stellato C. RNA-Binding Proteins as a Molecular Link between COPD and Lung Cancer. COPD 2023; 20:18-30. [PMID: 36655862 DOI: 10.1080/15412555.2022.2107500] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
Chronic obstructive pulmonary disease (COPD) represents an independent risk factor for lung cancer development. Accelerated cell senescence, induced by oxidative stress and inflammation, is a common pathogenic determinant of both COPD and lung cancer. The post transcriptional regulation of genes involved in these processes is finely regulated by RNA-binding proteins (RBPs), which regulate mRNA turnover, subcellular localization, splicing and translation. Multiple pro-inflammatory mediators (including cytokines, chemokines, proteins, growth factors and others), responsible of lung microenvironment alteration, are regulated by RBPs. Several mouse models have shown the implication of RBPs in multiple mechanisms that sustain chronic inflammation and neoplastic transformation. However, further studies are required to clarify the role of RBPs in the pathogenic mechanisms shared by lung cancer and COPD, in order to identify novel biomarkers and therapeutic targets. This review will therefore focus on the studies collectively indicating the role of RBPs in oxidative stress and chronic inflammation as common pathogenic mechanisms shared by lung cancer and COPD.
Collapse
Affiliation(s)
- Ilaria Salvato
- Pneumologia, Dipartimento di Scienze Biomediche, Odontoiatriche e delle Immagini Morfologiche e Funzionali (BIOMORF), Università degli Studi di Messina, Italy
| | - Luca Ricciardi
- Pneumologia, Dipartimento di Scienze Biomediche, Odontoiatriche e delle Immagini Morfologiche e Funzionali (BIOMORF), Università degli Studi di Messina, Italy
| | - Francesco Nucera
- Pneumologia, Dipartimento di Scienze Biomediche, Odontoiatriche e delle Immagini Morfologiche e Funzionali (BIOMORF), Università degli Studi di Messina, Italy
| | - Annunziata Nigro
- Department of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", University of Salerno, Salerno, Italy
| | - Jessica Dal Col
- Department of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", University of Salerno, Salerno, Italy
| | - Francesco Monaco
- Chirurgia Toracica, Dipartimento di Scienze Biomediche, Odontoiatriche e delle Immagini Morfologiche e Funzionali (BIOMORF), Università degli Studi di Messina, Italy
| | - Gaetano Caramori
- Pneumologia, Dipartimento di Scienze Biomediche, Odontoiatriche e delle Immagini Morfologiche e Funzionali (BIOMORF), Università degli Studi di Messina, Italy
| | - Cristiana Stellato
- Department of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", University of Salerno, Salerno, Italy
| |
Collapse
|
4
|
Willett JDS, Lu T, Nakanishi T, Yoshiji S, Butler-Laporte G, Zhou S, Farjoun Y, Richards JB. Colocalization of expression transcripts with COVID-19 outcomes is rare across cell states, cell types and organs. Hum Genet 2023; 142:1461-1476. [PMID: 37640912 PMCID: PMC10511363 DOI: 10.1007/s00439-023-02590-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2022] [Accepted: 06/30/2023] [Indexed: 08/31/2023]
Abstract
Identifying causal genes at GWAS loci can help pinpoint targets for therapeutic interventions. Expression studies can disentangle such loci but signals from expression quantitative trait loci (eQTLs) often fail to colocalize-which means that the genetic control of measured expression is not shared with the genetic control of disease risk. This may be because gene expression is measured in the wrong cell type, physiological state, or organ. We tested whether Mendelian randomization (MR) could identify genes at loci influencing COVID-19 outcomes and whether the colocalization of genetic control of expression and COVID-19 outcomes was influenced by cell type, cell stimulation, and organ. We conducted MR of cis-eQTLs from single cell (scRNA-seq) and bulk RNA sequencing. We then tested variables that could influence colocalization, including cell type, cell stimulation, RNA sequencing modality, organ, symptoms of COVID-19, and SARS-CoV-2 status among individuals with symptoms of COVID-19. The outcomes used to test colocalization were COVID-19 severity and susceptibility as assessed in the Host Genetics Initiative release 7. Most transcripts identified using MR did not colocalize when tested across cell types, cell state and in different organs. Most that did colocalize likely represented false positives due to linkage disequilibrium. In general, colocalization was highly variable and at times inconsistent for the same transcript across cell type, cell stimulation and organ. While we identified factors that influenced colocalization for select transcripts, identifying 33 that mediate COVID-19 outcomes, our study suggests that colocalization of expression with COVID-19 outcomes is partially due to noisy signals even after following quality control and sensitivity testing. These findings illustrate the present difficulty of linking expression transcripts to disease outcomes and the need for skepticism when observing eQTL MR results, even accounting for cell types, stimulation state and different organs.
Collapse
Affiliation(s)
- Julian Daniel Sunday Willett
- Centre for Clinical Epidemiology, Department of Medicine, Lady Davis Institute, Jewish General Hospital, McGill University, 3755 Cote Ste Catherine, Pavillon H-413, Montréal, Québec, H3T 1E2, Canada
- McGill University, Montreal, QC, Canada
- Quantitative Life Sciences Program, McGill University, Montreal, QC, Canada
- Genome Centre, McGill University, Montreal, QC, Canada
| | - Tianyuan Lu
- Centre for Clinical Epidemiology, Department of Medicine, Lady Davis Institute, Jewish General Hospital, McGill University, 3755 Cote Ste Catherine, Pavillon H-413, Montréal, Québec, H3T 1E2, Canada
- McGill University, Montreal, QC, Canada
- Quantitative Life Sciences Program, McGill University, Montreal, QC, Canada
- Genome Centre, McGill University, Montreal, QC, Canada
| | - Tomoko Nakanishi
- Centre for Clinical Epidemiology, Department of Medicine, Lady Davis Institute, Jewish General Hospital, McGill University, 3755 Cote Ste Catherine, Pavillon H-413, Montréal, Québec, H3T 1E2, Canada
- McGill University, Montreal, QC, Canada
- Department of Human Genetics, McGill University, Montreal, QC, Canada
- Graduate School of Medicine, Kyoto-McGill International Collaborative Program in Genomic Medicine, Kyoto University, Kyoto, Japan
- Japan Society for the Promotion of Science, Tokyo, Japan
- Genome Centre, McGill University, Montreal, QC, Canada
| | - Satoshi Yoshiji
- Centre for Clinical Epidemiology, Department of Medicine, Lady Davis Institute, Jewish General Hospital, McGill University, 3755 Cote Ste Catherine, Pavillon H-413, Montréal, Québec, H3T 1E2, Canada
- McGill University, Montreal, QC, Canada
- Department of Human Genetics, McGill University, Montreal, QC, Canada
- Graduate School of Medicine, Kyoto-McGill International Collaborative Program in Genomic Medicine, Kyoto University, Kyoto, Japan
- Japan Society for the Promotion of Science, Tokyo, Japan
- Genome Centre, McGill University, Montreal, QC, Canada
| | - Guillaume Butler-Laporte
- Centre for Clinical Epidemiology, Department of Medicine, Lady Davis Institute, Jewish General Hospital, McGill University, 3755 Cote Ste Catherine, Pavillon H-413, Montréal, Québec, H3T 1E2, Canada
| | - Sirui Zhou
- Centre for Clinical Epidemiology, Department of Medicine, Lady Davis Institute, Jewish General Hospital, McGill University, 3755 Cote Ste Catherine, Pavillon H-413, Montréal, Québec, H3T 1E2, Canada
- McGill University, Montreal, QC, Canada
- Genome Centre, McGill University, Montreal, QC, Canada
| | - Yossi Farjoun
- Centre for Clinical Epidemiology, Department of Medicine, Lady Davis Institute, Jewish General Hospital, McGill University, 3755 Cote Ste Catherine, Pavillon H-413, Montréal, Québec, H3T 1E2, Canada
- Genome Centre, McGill University, Montreal, QC, Canada
| | - J Brent Richards
- Centre for Clinical Epidemiology, Department of Medicine, Lady Davis Institute, Jewish General Hospital, McGill University, 3755 Cote Ste Catherine, Pavillon H-413, Montréal, Québec, H3T 1E2, Canada.
- McGill University, Montreal, QC, Canada.
- Genome Centre, McGill University, Montreal, QC, Canada.
- Departments of Medicine, Human Genetics, Epidemiology and Biostatistics, McGill University, Montréal, QC, Canada.
- Department of Twin Research, King's College London, London, UK.
- Five Prime Sciences Inc, Montréal, Québec, Canada.
| |
Collapse
|
5
|
Luyapan J, Bossé Y, Li Z, Xiao X, Rosenberger A, Hung RJ, Lam S, Zienolddiny S, Liu G, Kiemeney LA, Chen C, McKay J, Johansson M, Johansson M, Tardon A, Fernandez-Tardon G, Brennan P, Field JK, Davies MP, Woll PJ, Cox A, Taylor F, Arnold SM, Lazarus P, Grankvist K, Landi MT, Christiani DC, MacKenzie TA, Amos CI. Candidate pathway analysis of surfactant proteins identifies CTSH and SFTA2 that influences lung cancer risk. Hum Mol Genet 2023; 32:2842-2855. [PMID: 37471639 PMCID: PMC10481107 DOI: 10.1093/hmg/ddad095] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Revised: 05/22/2023] [Accepted: 05/24/2023] [Indexed: 07/22/2023] Open
Abstract
Pulmonary surfactant is a lipoprotein synthesized and secreted by alveolar type II cells in lung. We evaluated the associations between 200,139 single nucleotide polymorphisms (SNPs) of 40 surfactant-related genes and lung cancer risk using genotyped data from two independent lung cancer genome-wide association studies. Discovery data included 18,082 cases and 13,780 controls of European ancestry. Replication data included 1,914 cases and 3,065 controls of European descent. Using multivariate logistic regression, we found novel SNPs in surfactant-related genes CTSH [rs34577742 C > T, odds ratio (OR) = 0.90, 95% confidence interval (CI) = 0.89-0.93, P = 7.64 × 10-9] and SFTA2 (rs3095153 G > A, OR = 1.16, 95% CI = 1.10-1.21, P = 1.27 × 10-9) associated with overall lung cancer in the discovery data and validated in an independent replication data-CTSH (rs34577742 C > T, OR = 0.88, 95% CI = 0.80-0.96, P = 5.76 × 10-3) and SFTA2 (rs3095153 G > A, OR = 1.14, 95% CI = 1.01-1.28, P = 3.25 × 10-2). Among ever smokers, we found SNPs in CTSH (rs34577742 C > T, OR = 0.89, 95% CI = 0.85-0.92, P = 1.94 × 10-7) and SFTA2 (rs3095152 G > A, OR = 1.20, 95% CI = 1.14-1.27, P = 4.25 × 10-11) associated with overall lung cancer in the discovery data and validated in the replication data-CTSH (rs34577742 C > T, OR = 0.88, 95% CI = 0.79-0.97, P = 1.64 × 10-2) and SFTA2 (rs3095152 G > A, OR = 1.15, 95% CI = 1.01-1.30, P = 3.81 × 10-2). Subsequent transcriptome-wide association study using expression weights from a lung expression quantitative trait loci study revealed genes most strongly associated with lung cancer are CTSH (PTWAS = 2.44 × 10-4) and SFTA2 (PTWAS = 2.32 × 10-6).
Collapse
Affiliation(s)
- Jennifer Luyapan
- Quantitative Biomedical Science Program, Geisel School of Medicine, Dartmouth College, Hanover, NH 03755, USA
- Department of Biomedical Data Science, Geisel School of Medicine, Dartmouth College, Lebanon, NH 03756, USA
| | - Yohan Bossé
- Institut Universitaire de Cardiologie et de Pneumologie de Québec, Université Laval, Quebec City, G1V 0A6, Canada
- Department of Molecular Medicine, Laval University, Quebec City, G1V 0A6, Canada
| | - Zhonglin Li
- Institut Universitaire de Cardiologie et de Pneumologie de Québec, Université Laval, Quebec City, G1V 0A6, Canada
| | - Xiangjun Xiao
- Department of Medicine, Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Albert Rosenberger
- Institut für Genetische Epidemiologie, Georg-August-Universität Göttingen, Gottingen, Niedersachsen, Germany
| | - Rayjean J Hung
- Prosserman Centre for Population Health Research, Lunenfeld-Tanenbuaum Research Institute, Sinai Health System, Toronto, ON, M5G 1X5, Canada
| | - Stephen Lam
- Department of Integrative Oncology, British Columbia Cancer Agency, Vancouver, BC, V5Z 4E6, Canada
| | - Shanbeh Zienolddiny
- Department of Toxicology, National Institute of Occupational Health, Oslo 0033, Norway
| | - Geoffrey Liu
- Princess Margaret Cancer Centre, Princess Margaret Research Institute, Epidemiology Division,Toronto, ON, M5G 1L7, Canada
| | - Lambertus A Kiemeney
- Department for Health Evidence, Radboud University Medical Center, Nijmegen, 6525 GA, the Netherlands
| | - Chu Chen
- Program in Epidemiology, Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
| | - James McKay
- International Agency for Research on Cancer (IARC/WHO), Genomic Epidemiology Branch Lyon 69008, France
| | - Mattias Johansson
- International Agency for Research on Cancer (IARC/WHO), Genomic Epidemiology Branch Lyon 69008, France
| | - Mikael Johansson
- Department of Radiation Sciences, Oncology, Umeå University, Umeå, 901 87, Sweden
| | - Adonina Tardon
- Health Research Institute of the Principality of Asturias, University of Oviedo and CIBERSP, Oviedo, Asturias, 33071, Spain
| | - Guillermo Fernandez-Tardon
- Health Research Institute of the Principality of Asturias, University of Oviedo and CIBERSP, Oviedo, Asturias, 33071, Spain
| | - Paul Brennan
- Institute of Medical Informatics, Biometry and Epidemiology, Chair of Epidemiology, Ludwig Maximillians University, Munich, Bavaria, 80539, Germany
| | - John K Field
- Molecular and Clinical Cancer Medicine, Roy Castle Lung Cancer Research Programme, The University of Liverpool Institute of Translational Medicine, Liverpool, L69 7ZX, UK
| | - Michael P Davies
- Molecular and Clinical Cancer Medicine, Roy Castle Lung Cancer Research Programme, The University of Liverpool Institute of Translational Medicine, Liverpool, L69 7ZX, UK
| | - Penella J Woll
- Academic Unit of Clinical Oncology, University of Sheffield, Sheffield, S10 2AH, UK
| | - Angela Cox
- Department of Oncology and Metabolism, University of Sheffield, Sheffield, S10 2AH, UK
| | - Fiona Taylor
- Department of Oncology and Metabolism, University of Sheffield, Sheffield, S10 2AH, UK
| | - Susanne M Arnold
- Division of Medical Oncology, Cancer Center, University of Kentucky, Lexington, KY 40508, USA
| | - Philip Lazarus
- Department of Pharmaceutical Sciences, College of Pharmacy and Pharmaceutical Sciences, Washington State University, Spokane, WA, 99163, USA
| | - Kjell Grankvist
- Department of Medical Biosciences, Clinical Chemistry, Umeå University, Umeå, 901 87, Sweden
| | - Maria T Landi
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, 20892, USA
| | - David C Christiani
- Department of Environmental Health, Harvard School of Public Health, Boston, MA 02115, USA
- Department of Medicine, Massachusetts General Hospital, Boston, MA 02115, USA
| | - Todd A MacKenzie
- Quantitative Biomedical Science Program, Geisel School of Medicine, Dartmouth College, Hanover, NH 03755, USA
- Department of Biomedical Data Science, Geisel School of Medicine, Dartmouth College, Lebanon, NH 03756, USA
| | - Christopher I Amos
- Quantitative Biomedical Science Program, Geisel School of Medicine, Dartmouth College, Hanover, NH 03755, USA
- Department of Biomedical Data Science, Geisel School of Medicine, Dartmouth College, Lebanon, NH 03756, USA
- Department of Medicine, Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX 77030, USA
| |
Collapse
|
6
|
Zhu Z, Chen X, Wang C, Zhang S, Yu R, Xie Y, Yuan S, Cheng L, Shi L, Zhang X. An integrated strategy to identify COVID-19 causal genes and characteristics represented by LRRC37A2. J Med Virol 2023; 95:e28585. [PMID: 36794676 DOI: 10.1002/jmv.28585] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Revised: 01/15/2023] [Accepted: 01/29/2023] [Indexed: 02/17/2023]
Abstract
Genome-wide association study (GWAS) could identify host genetic factors associated with coronavirus disease 2019 (COVID-19). The genes or functional DNA elements through which genetic factors affect COVID-19 remain uncharted. The expression quantitative trait locus (eQTL) provides a path to assess the correlation between genetic variations and gene expression. Here, we firstly annotated GWAS data to describe genetic effects, obtaining genome-wide mapped genes. Subsequently, the genetic mechanisms and characteristics of COVID-19 were investigated by an integrated strategy that included three GWAS-eQTL analysis approaches. It was found that 20 genes were significantly associated with immunity and neurological disorders, including prior and novel genes such as OAS3 and LRRC37A2. The findings were then replicated in single-cell datasets to explore the cell-specific expression of causal genes. Furthermore, associations between COVID-19 and neurological disorders were assessed as a causal relationship. Finally, the effects of causal protein-coding genes of COVID-19 were discussed using cell experiments. The results revealed some novel COVID-19-related genes to emphasize disease characteristics, offering a broader insight into the genetic architecture underlying the pathophysiology of COVID-19.
Collapse
Affiliation(s)
- Zijun Zhu
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China
| | - Xinyu Chen
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China
| | - Chao Wang
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China
| | - Sainan Zhang
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China
| | - Rui Yu
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China
| | - Yubin Xie
- Department of Microbiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
- State Key Laboratory of Emerging Infectious Diseases, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Shuofeng Yuan
- Department of Microbiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
- State Key Laboratory of Emerging Infectious Diseases, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Liang Cheng
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China
- NHC Key Laboratory of Molecular Probe and Targeted Diagnosis and Therapy, Harbin Medical University, Harbin, Heilongjiang, China
| | - Lei Shi
- NHC Key Laboratory of Molecular Probe and Targeted Diagnosis and Therapy, Harbin Medical University, Harbin, Heilongjiang, China
| | - Xue Zhang
- NHC Key Laboratory of Molecular Probe and Targeted Diagnosis and Therapy, Harbin Medical University, Harbin, Heilongjiang, China
- 3McKusick-Zhang Center for Genetic Medicine, State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| |
Collapse
|
7
|
Phelan J, Gomez-Gonzalez PJ, Andreu N, Omae Y, Toyo-Oka L, Yanai H, Miyahara R, Nedsuwan S, de Sessions PF, Campino S, Sallah N, Parkhill J, Smittipat N, Palittapongarnpim P, Mushiroda T, Kubo M, Tokunaga K, Mahasirimongkol S, Hibberd ML, Clark TG. Genome-wide host-pathogen analyses reveal genetic interaction points in tuberculosis disease. Nat Commun 2023; 14:549. [PMID: 36725857 PMCID: PMC9892022 DOI: 10.1038/s41467-023-36282-w] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2022] [Accepted: 01/24/2023] [Indexed: 02/03/2023] Open
Abstract
The genetics underlying tuberculosis (TB) pathophysiology are poorly understood. Human genome-wide association studies have failed so far to reveal reproducible susceptibility loci, attributed in part to the influence of the underlying Mycobacterium tuberculosis (Mtb) bacterial genotype on the outcome of the infection. Several studies have found associations of human genetic polymorphisms with Mtb phylo-lineages, but studies analysing genome-genome interactions are needed. By implementing a phylogenetic tree-based Mtb-to-human analysis for 714 TB patients from Thailand, we identify eight putative genetic interaction points (P < 5 × 10-8) including human loci DAP and RIMS3, both linked to the IFNγ cytokine and host immune system, as well as FSTL5, previously associated with susceptibility to TB. Many of the corresponding Mtb markers are lineage specific. The genome-to-genome analysis reveals a complex interactome picture, supports host-pathogen adaptation and co-evolution in TB, and has potential applications to large-scale studies across many TB endemic populations matched for host-pathogen genomic diversity.
Collapse
Affiliation(s)
- Jody Phelan
- Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | | | - Nuria Andreu
- Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Yosuke Omae
- Department of Human Genetics, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Licht Toyo-Oka
- Department of Human Genetics, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Hideki Yanai
- Fukujuji Hospital and Research Institute of Tuberculosis, Japan Anti-Tuberculosis Association, Kiyose, Japan
| | - Reiko Miyahara
- Genome Medical Science Project, National Center for Global Health and Medicine, Tokyo, Japan
| | | | | | - Susana Campino
- Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Neneh Sallah
- Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Julian Parkhill
- Department of Veterinary Medicine, University of Cambridge, Cambridge, UK
| | - Nat Smittipat
- National Center for Genetic Engineering and Biotechnology, National Science and Technology Development Agency, Pathumthani, Thailand
| | - Prasit Palittapongarnpim
- National Center for Genetic Engineering and Biotechnology, National Science and Technology Development Agency, Pathumthani, Thailand
| | | | - Michiaki Kubo
- RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Katsushi Tokunaga
- Department of Human Genetics, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Surakameth Mahasirimongkol
- Medical Genetics Center, Medical Life Sciences Institute, Department of Medical Sciences, Ministry of Public Health, Nonthaburi, Thailand
| | - Martin L Hibberd
- Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom.
| | - Taane G Clark
- Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom.
- Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, Keppel Street, London, WC1E 7HT, United Kingdom.
| |
Collapse
|
8
|
Mumby S, Adcock IM. Recent evidence from omic analysis for redox signalling and mitochondrial oxidative stress in COPD. J Inflamm (Lond) 2022; 19:10. [PMID: 35820851 PMCID: PMC9277949 DOI: 10.1186/s12950-022-00308-9] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Accepted: 06/27/2022] [Indexed: 11/30/2022] Open
Abstract
COPD is driven by exogenous and endogenous oxidative stress derived from inhaled cigarette smoke, air pollution and reactive oxygen species from dysregulated mitochondria in activated inflammatory cells within the airway and lung. This is compounded by the loss in antioxidant defences including FOXO and NRF2 and other antioxidant transcription factors together with various key enzymes that attenuate oxidant effects. Oxidative stress enhances inflammation; airway remodelling including fibrosis and emphysema; post-translational protein modifications leading to autoantibody generation; DNA damage and cellular senescence. Recent studies using various omics technologies in the airways, lungs and blood of COPD patients has emphasised the importance of oxidative stress, particularly that derived from dysfunctional mitochondria in COPD and its role in immunity, inflammation, mucosal barrier function and infection. Therapeutic interventions targeting oxidative stress should overcome the deleterious pathologic effects of COPD if targeted to the lung. We require novel, more efficacious antioxidant COPD treatments among which mitochondria-targeted antioxidants and Nrf2 activators are promising.
Collapse
|
9
|
Ni J, Wang P, Yin KJ, Yang XK, Cen H, Sui C, Wu GC, Pan HF. Novel insight into the aetiology of rheumatoid arthritis gained by a cross-tissue transcriptome-wide association study. RMD Open 2022; 8:e002529. [PMID: 37582060 PMCID: PMC9462377 DOI: 10.1136/rmdopen-2022-002529] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Accepted: 08/23/2022] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND Although genome-wide association studies (GWASs) have identified more than 100 loci associated with rheumatoid arthritis (RA) susceptibility, the causal genes and biological mechanisms remain largely unknown. METHODS A cross-tissue transcriptome-wide association study (TWAS) using the unified test for molecular signaturestool was performed to integrate GWAS summary statistics from 58 284 individuals (14 361 RA cases and 43 923 controls) with gene-expression matrix in the Genotype-Tissue Expression project. Subsequently, a single tissue by using FUSION software was conducted to validate the significant associations. We also compared the TWAS with different gene-based methodologies, including Summary Data Based Mendelian Randomization (SMR) and Multimarker Analysis of Genomic Annotation (MAGMA). Further in silico analyses (conditional and joint analysis, differential expression analysis and gene-set enrichment analysis) were used to deepen our understanding of genetic architecture and comorbidity aetiology of RA. RESULTS We identified a total of 47 significant candidate genes for RA in both cross-tissue and single-tissue test after multiple testing correction, of which 40 TWAS-identified genes were verified by SMR or MAGMA. Among them, 13 genes were situated outside of previously reported significant loci by RA GWAS. Both TWAS-based and MAGMA-based enrichment analyses illustrated the shared genetic determinants among autoimmune thyroid disease, asthma, type I diabetes mellitus and RA. CONCLUSION Our study unveils 13 new candidate genes whose predicted expression is associated with risk of RA, providing new insights into the underlying genetic architecture of RA.
Collapse
Affiliation(s)
- Jing Ni
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China
| | - Peng Wang
- Teaching Center for Preventive Medicine, School of Public Health, Anhui Medical University, Hefei, China
| | - Kang-Jia Yin
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China
| | - Xiao-Ke Yang
- Department of Rheumatology and Immunology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Han Cen
- Department of Preventive Medicine, Ningbo University Medical School, Ningbo, Zhejiang, China
| | - Cong Sui
- Department of Orthopedics Trauma, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Guo-Cui Wu
- Department of Obstetrics and Gynecological Nursing, School of Nursing, Anhui Medical University, Hefei, Anhui, China
| | - Hai-Feng Pan
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China
| |
Collapse
|
10
|
Cho MH, Hobbs BD, Silverman EK. Genetics of chronic obstructive pulmonary disease: understanding the pathobiology and heterogeneity of a complex disorder. THE LANCET. RESPIRATORY MEDICINE 2022; 10:485-496. [PMID: 35427534 PMCID: PMC11197974 DOI: 10.1016/s2213-2600(21)00510-5] [Citation(s) in RCA: 37] [Impact Index Per Article: 18.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Revised: 10/20/2021] [Accepted: 11/09/2021] [Indexed: 12/20/2022]
Abstract
Chronic obstructive pulmonary disease (COPD) is a deadly and highly morbid disease. Susceptibility to and heterogeneity of COPD are incompletely explained by environmental factors such as cigarette smoking. Family-based and population-based studies have shown that a substantial proportion of COPD risk is related to genetic variation. Genetic association studies have identified hundreds of genetic variants that affect risk for COPD, decreased lung function, and other COPD-related traits. These genetic variants are associated with other pulmonary and non-pulmonary traits, demonstrate a genetic basis for at least part of COPD heterogeneity, have a substantial effect on COPD risk in aggregate, implicate early-life events in COPD pathogenesis, and often involve genes not previously suspected to have a role in COPD. Additional progress will require larger genetic studies with more ancestral diversity, improved profiling of rare variants, and better statistical methods. Through integration of genetic data with other omics data and comprehensive COPD phenotypes, as well as functional description of causal mechanisms for genetic risk variants, COPD genetics will continue to inform novel approaches to understanding the pathobiology of COPD and developing new strategies for management and treatment.
Collapse
Affiliation(s)
- Michael H Cho
- Channing Division of Network Medicine and Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA.
| | - Brian D Hobbs
- Channing Division of Network Medicine and Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Edwin K Silverman
- Channing Division of Network Medicine and Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| |
Collapse
|
11
|
Yu CT, Chao BN, Barajas R, Haznadar M, Maruvada P, Nicastro HL, Ross SA, Verma M, Rogers S, Zanetti KA. An evaluation of the National Institutes of Health grants portfolio: identifying opportunities and challenges for multi-omics research that leverage metabolomics data. Metabolomics 2022; 18:29. [PMID: 35488937 PMCID: PMC9056487 DOI: 10.1007/s11306-022-01878-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Accepted: 02/28/2022] [Indexed: 11/29/2022]
Abstract
BACKGROUND Through the systematic large-scale profiling of metabolites, metabolomics provides a tool for biomarker discovery and improving disease monitoring, diagnosis, prognosis, and treatment response, as well as for delineating disease mechanisms and etiology. As a downstream product of the genome and epigenome, transcriptome, and proteome activity, the metabolome can be considered as being the most proximal correlate to the phenotype. Integration of metabolomics data with other -omics data in multi-omics analyses has the potential to advance understanding of human disease development and treatment. AIM OF REVIEW To understand the current funding and potential research opportunities for when metabolomics is used in human multi-omics studies, we cross-sectionally evaluated National Institutes of Health (NIH)-funded grants to examine the use of metabolomics data when collected with at least one other -omics data type. First, we aimed to determine what types of multi-omics studies included metabolomics data collection. Then, we looked at those multi-omics studies to examine how often grants employed an integrative analysis approach using metabolomics data. KEY SCIENTIFIC CONCEPTS OF REVIEW We observed that the majority of NIH-funded multi-omics studies that include metabolomics data performed integration, but to a limited extent, with integration primarily incorporating only one other -omics data type. Some opportunities to improve data integration may include increasing confidence in metabolite identification, as well as addressing variability between -omics approach requirements and -omics data incompatibility.
Collapse
Affiliation(s)
- Catherine T Yu
- Division of Cancer Control and Population Sciences, National Cancer Institute, Rockville, MD, USA
| | - Brittany N Chao
- Office of Workforce Planning and Development, National Cancer Institute, Rockville, MD, USA
| | - Rolando Barajas
- Division of Cancer Control and Population Sciences, National Cancer Institute, Rockville, MD, USA
| | - Majda Haznadar
- Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Rockville, MD, USA
| | - Padma Maruvada
- Division of Digestive Diseases and Nutrition, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD, USA
| | - Holly L Nicastro
- Office of Nutrition Research, National Institutes of Health, Bethesda, MD, USA
| | - Sharon A Ross
- Division of Cancer Prevention, National Cancer Institute, Rockville, MD, USA
| | - Mukesh Verma
- Division of Cancer Control and Population Sciences, National Cancer Institute, Rockville, MD, USA
| | - Scott Rogers
- Division of Cancer Control and Population Sciences, National Cancer Institute, Rockville, MD, USA
| | - Krista A Zanetti
- Division of Cancer Control and Population Sciences, National Cancer Institute, Rockville, MD, USA.
| |
Collapse
|
12
|
Multi-tissue transcriptome-wide association study identifies eight candidate genes and tissue-specific gene expression underlying endometrial cancer susceptibility. Commun Biol 2021; 4:1211. [PMID: 34675350 PMCID: PMC8531339 DOI: 10.1038/s42003-021-02745-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Accepted: 09/27/2021] [Indexed: 11/24/2022] Open
Abstract
Genome-wide association studies (GWAS) have revealed sixteen risk loci for endoemtrial cancer but the identification of candidate susceptibility genes remains challenging. Here, we perform transcriptome-wide association study (TWAS) analyses using the largest endometrial cancer GWAS and gene expression from six relevant tissues, prioritizing eight candidate endometrial cancer susceptibility genes, one of which (EEFSEC) is located at a potentially novel endometrial cancer risk locus. We also show evidence of biologically relevant tissue-specific expression associations for CYP19A1 (adipose), HEY2 (ovary) and SKAP1 (whole blood). A phenome-wide association study demonstrates associations of candidate susceptibility genes with anthropometric, cardiovascular, diabetes, bone health and sex hormone traits that are related to endometrial cancer risk factors. Lastly, analysis of TWAS data highlights candidate compounds for endometrial cancer repurposing. In summary, this study reveals endometrial cancer susceptibility genes, including those with evidence of tissue specificity, providing insights into endometrial cancer aetiology and avenues for therapeutic development. Pik Fang Kho et al. conduct multi-tissue transcriptome-wide association studies of endometrial cancer risk. Their results identify potential susceptibility genes for endometrial cancer, and provide avenues for the development of future treatments for this disease.
Collapse
|
13
|
Tang Y, Chen Z, Fang Z, Zhao J, Zhou Y, Tang C. Multi-Omics study on biomarker and pathway discovery of chronic obstructive pulmonary disease. J Breath Res 2021; 15. [PMID: 34280912 DOI: 10.1088/1752-7163/ac15ea] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Accepted: 07/19/2021] [Indexed: 11/12/2022]
Abstract
Chronic obstructive pulmonary disease (COPD) is a common heterogeneous respiratory disease characterized by persistent and incompletely reversible airflow limitation. Due to the heterogeneity and phenotypes complexity of COPD, traditionally diagnostic methods can only give limited information on predicted results and treatment, which are not sufficient for accurate diagnosis and evaluation. With the development of omics technologies in recent years, genomics, proteomics, and metabolomics are widely used in the study of COPD, providing good tools for discovering biomarkers to diagnose and elucidate the complex mechanism of COPD. In this review, we summarized the biomarkers of COPD based on metabolomic, proteomic and transcriptomic studies that have been reported in recent years. Furthermore, protein-protein interactions and multi-omics integrated analysis were carried out to explore the important metabolites and proteins that involved in significant pathways in the progression of COPD for explanation the pathogenesis of COPD. Finally, the prospective and challenges in the study of COPD were proposed. It is expected that this review will provide some references for the development of diagnostic methods and elucidation of the pathogenesis of COPD.
Collapse
Affiliation(s)
- Yuqing Tang
- Ningbo University Medical School, The Affiliated Hospital of Medical School, Ningbo University, Ningbo 315020, China, Ningbo, Zhejiang, 315020, CHINA
| | - Zhengjun Chen
- Ningbo University Medical School, The Affiliated Hospital of Medical School, Ningbo University, Ningbo 315020, China, Ningbo, Zhejiang, 315020, CHINA
| | - Zhiling Fang
- Ningbo University Medical School, Ningbo University School of Medicine, Ningbo 315211, China, Ningbo, Zhejiang, 315211, CHINA
| | - Jinshun Zhao
- Ningbo University Medical School, Ningbo University School of Medicine, Ningbo 315211, China, Ningbo, Zhejiang, 315211, CHINA
| | - Yuping Zhou
- Ningbo University Medical School, The Affiliated Hospital of Medical School, Ningbo University, Ningbo 315020, China, Ningbo, Zhejiang, 315020, CHINA
| | - Chunlan Tang
- Ningbo University Medical School, The Affiliated Hospital of Medical School, Ningbo University, Ningbo 315020, China, Ningbo, Zhejiang, 315020, CHINA
| |
Collapse
|
14
|
Prioritization of candidate causal genes for asthma in susceptibility loci derived from UK Biobank. Commun Biol 2021; 4:700. [PMID: 34103634 PMCID: PMC8187656 DOI: 10.1038/s42003-021-02227-6] [Citation(s) in RCA: 67] [Impact Index Per Article: 22.3] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Accepted: 05/17/2021] [Indexed: 12/12/2022] Open
Abstract
To identify candidate causal genes of asthma, we performed a genome-wide association study (GWAS) in UK Biobank on a broad asthma definition (n = 56,167 asthma cases and 352,255 controls). We then carried out functional mapping through transcriptome-wide association studies (TWAS) and Mendelian randomization in lung (n = 1,038) and blood (n = 31,684) tissues. The GWAS reveals 72 asthma-associated loci from 116 independent significant variants (PGWAS < 5.0E-8). The most significant lung TWAS gene on 17q12-q21 is GSDMB (PTWAS = 1.42E-54). Other TWAS genes include TSLP on 5q22, RERE on 1p36, CLEC16A on 16p13, and IL4R on 16p12, which all replicated in GTEx lung (n = 515). We demonstrate that the largest fold enrichment of regulatory and functional annotations among asthma-associated variants is in the blood. We map 485 blood eQTL-regulated genes associated with asthma and 50 of them are causal by Mendelian randomization. Prioritization of druggable genes reveals known (IL4R, TSLP, IL6, TNFSF4) and potentially new therapeutic targets for asthma.
Collapse
|
15
|
Lesseur C, Ferreiro-Iglesias A, McKay JD, Bossé Y, Johansson M, Gaborieau V, Landi MT, Christiani DC, Caporaso NC, Bojesen SE, Amos CI, Shete S, Liu G, Rennert G, Albanes D, Aldrich MC, Tardon A, Chen C, Triantafillos L, Field JK, Teare MD, Kiemeney LA, Diergaarde B, Ferris RL, Zienolddiny S, Lam S, Olshan AF, Weissler MC, Lacko M, Risch A, Bickeböller H, Ness AR, Thomas S, Le Marchand L, Schabath MB, Wünsch-Filho V, Tajara EH, Andrew AS, Clifford GM, Lazarus P, Grankvist K, Johansson M, Arnold S, Melander O, Brunnström H, Boccia S, Cadoni G, Timens W, Obeidat M, Xiao X, Houlston RS, Hung RJ, Brennan P. Genome-wide association meta-analysis identifies pleiotropic risk loci for aerodigestive squamous cell cancers. PLoS Genet 2021; 17:e1009254. [PMID: 33667223 PMCID: PMC7968735 DOI: 10.1371/journal.pgen.1009254] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2020] [Revised: 03/17/2021] [Accepted: 11/05/2020] [Indexed: 11/20/2022] Open
Abstract
Squamous cell carcinomas (SqCC) of the aerodigestive tract have similar etiological risk factors. Although genetic risk variants for individual cancers have been identified, an agnostic, genome-wide search for shared genetic susceptibility has not been performed. To identify novel and pleotropic SqCC risk variants, we performed a meta-analysis of GWAS data on lung SqCC (LuSqCC), oro/pharyngeal SqCC (OSqCC), laryngeal SqCC (LaSqCC) and esophageal SqCC (ESqCC) cancers, totaling 13,887 cases and 61,961 controls of European ancestry. We identified one novel genome-wide significant (Pmeta<5x10-8) aerodigestive SqCC susceptibility loci in the 2q33.1 region (rs56321285, TMEM273). Additionally, three previously unknown loci reached suggestive significance (Pmeta<5x10-7): 1q32.1 (rs12133735, near MDM4), 5q31.2 (rs13181561, TMEM173) and 19p13.11 (rs61494113, ABHD8). Multiple previously identified loci for aerodigestive SqCC also showed evidence of pleiotropy in at least another SqCC site, these include: 4q23 (ADH1B), 6p21.33 (STK19), 6p21.32 (HLA-DQB1), 9p21.33 (CDKN2B-AS1) and 13q13.1(BRCA2). Gene-based association and gene set enrichment identified a set of 48 SqCC-related genes rel to DNA damage and epigenetic regulation pathways. Our study highlights the importance of cross-cancer analyses to identify pleiotropic risk loci of histology-related cancers arising at distinct anatomical sites.
Collapse
Affiliation(s)
- Corina Lesseur
- Section of Genetics, Genetic Epidemiology Group, International Agency for Research on Cancer, World Health Organization, Lyon, France
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Aida Ferreiro-Iglesias
- Section of Genetics, Genetic Epidemiology Group, International Agency for Research on Cancer, World Health Organization, Lyon, France
| | - James D. McKay
- Section of Genetics, Genetic Cancer Susceptibility Group, International Agency for Research on Cancer, World Health Organization, Lyon, France
| | - Yohan Bossé
- Department of Molecular Medicine, Institut universitaire de cardiologie et de pneumologie de Québec, Laval University, Quebec City, Canada
| | - Mattias Johansson
- Section of Genetics, Genetic Epidemiology Group, International Agency for Research on Cancer, World Health Organization, Lyon, France
| | - Valerie Gaborieau
- Section of Genetics, Genetic Epidemiology Group, International Agency for Research on Cancer, World Health Organization, Lyon, France
| | - Maria Teresa Landi
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, United States of America
| | - David C. Christiani
- Department of Environmental Health, Harvard TH Chan School of Public Health, Massachusetts General Hospital, Boston, Massachusetts, United States of America
| | - Neil C. Caporaso
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Stig E. Bojesen
- Copenhagen General Population Study, Herlev and Gentofte Hospital, Copenhagen, Denmark
| | - Christopher I. Amos
- Department of Medicine, Baylor college of Medicine, Houston, Texas, United States of America
| | - Sanjay Shete
- Department of Biostatistics, The University of Texas M.D. Anderson Cancer Center, Houston, Texas, United States of America
| | - Geoffrey Liu
- Lunenfeld-Tanenbaum Research Institute of Sinai Health System, University of Toronto, Toronto, Canada
| | - Gadi Rennert
- Clalit National Cancer Control Center, Carmel Medical Center and Technion Faculty of Medicine, Haifa, Israel
| | - Demetrius Albanes
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Melinda C. Aldrich
- Department of Thoracic Surgery, Division of Epidemiology, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America
| | - Adonina Tardon
- Faculty of Medicine, University of Oviedo and CIBERESP, Oviedo, Spain
| | - Chu Chen
- Department of Epidemiology, University of Washington School of Public Health and Community Medicine, Seattle, Washington, United States of America
| | | | - John K. Field
- Institute of Translational Medicine, University of Liverpool, Liverpool, United Kingdom
| | - Marion Dawn Teare
- School of Health and Related Research, University Of Sheffield, Sheffield, United Kingdom
| | | | - Brenda Diergaarde
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
- Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
- UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Robert L. Ferris
- UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | | | - Stephen Lam
- British Columbia Cancer Agency, Vancouver, Canada
| | - Andrew F. Olshan
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Mark C. Weissler
- Department of Otolaryngology/Head and Neck Surgery, UNC Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Martin Lacko
- Department of Otorhinolaryngology, Head and Neck Surgery, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Angela Risch
- University of Salzburg, Department of Biosciences and Cancer Cluster Salzburg, Salzburg, Austria
- Division of Epigenomics, DKFZ – German Cancer Research Center, Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC-H), Member of the German Center for Lung Research (DZL), Heidelberg, Germany
| | - Heike Bickeböller
- Department of Genetic Epidemiology, University Medical Center, Georg-August-University Göttingen, Göttingen, Germany
| | - Andy R. Ness
- National Institute for Health Research (NIHR) Bristol Biomedical Research Centre, University Hospitals Bristol NHS Foundation Trust, Bristol, United Kingdom
- Bristol Dental School, University of Bristol, Bristol, United Kingdom
| | - Steve Thomas
- Bristol Dental School, University of Bristol, Bristol, United Kingdom
| | - Loic Le Marchand
- Epidemiology Program, University of Hawaii Cancer Center, University of Hawaii, Honolulu, Hawaii, United States of America
| | - Matthew B. Schabath
- Department of Cancer Epidemiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida, United States of America
| | | | - Eloiza H. Tajara
- Department of Molecular Biology, School of Medicine of São José do Rio Preto, São José do Rio Preto, Brazil
| | - Angeline S. Andrew
- Biomedical Data Science, Geisel School of Medicine at Dartmouth, Dartmouth College, Hanover, New Hampshire, United States of America
| | - Gary M. Clifford
- Infections Section, Infections and Cancer Epidemiology Group, International Agency for Research on Cancer, World Health Organization, Lyon, France
| | - Philip Lazarus
- Department of Pharmaceutical Sciences, College of Pharmacy, Washington State University, Spokane, Washington, United States of America
| | - Kjell Grankvist
- Department of Medical Biosciences, Umeå University, Umeå, Sweden
| | | | - Susanne Arnold
- Markey Cancer Center, University of Kentucky, Lexington, Kentucky, United States of America
| | - Olle Melander
- Department of Clinical Sciences Malmö, Lund University, Malmö, Sweden
- Department of Internal Medicine, Skåne University Hospital, Malmö, Sweden
| | - Hans Brunnström
- Department of Clinical Sciences, Lund University, Lund, Sweden
| | - Stefania Boccia
- Section of Hygiene, University Department of Life Sciences and Public Health, Università Cattolica del Sacro Cuore, Roma, Italia
- Department of Woman and Child Health and Public Health - Public Health Area, Fondazione Policlinico Universitario A. Gemelli IRCCS, Roma, Italia
| | - Gabriella Cadoni
- Dipartimento Patologia Testa Collo e Organi di Senso, Istituto di Clinica Otorinolaringoiatrica, Università Cattolica del Sacro Cuore, Roma, Italia
- Dipartimento di Scienze dell’Invecchiamento, Neurologiche, Ortopediche e della Testa-Collo, Fondazione Policlinico Universitario A. Gemelli IRCCS, Roma, Italia
| | - Wim Timens
- Department of Pathology and Medical Biology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
- GRIAC Research Institute, University of Groningen, Groningen, The Netherlands
| | - Ma’en Obeidat
- Centre for Heart Lung Innovation, St Paul’s Hospital, The University of British Columbia, Vancouver, Canada
| | - Xiangjun Xiao
- Department of Medicine, Baylor college of Medicine, Houston, Texas, United States of America
| | - Richard S. Houlston
- Division of Genetics and Epidemiology, The Institute of Cancer Research, London, United Kingdom
| | - Rayjean J. Hung
- Prosserman Centre for Population Health Research, Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, Canada
| | - Paul Brennan
- Section of Genetics, Genetic Epidemiology Group, International Agency for Research on Cancer, World Health Organization, Lyon, France
| |
Collapse
|
16
|
Gong L, Luo Z, Tang H, Tan X, Xie L, Lei Y, He C, Ma J, Han S. Integrative, genome-wide association study identifies chemicals associated with common women's malignancies. Genomics 2020; 112:5029-5036. [PMID: 32911025 DOI: 10.1016/j.ygeno.2020.09.011] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2020] [Revised: 07/21/2020] [Accepted: 09/03/2020] [Indexed: 01/13/2023]
Abstract
BACKGROUND Breast cancer, cervical cancer, and ovarian cancer are three of the most commonly diagnosed malignancies in women, and more cancer prevention research is urgently needed. METHODS Summary data of a large genome-wide association study of female cancers were derived from the UK biobank. We performed a transcriptome-wide association study and a gene set enrichment analysis to identify correlations between chemical exposure and aberrant expression, repression, or mutation of genes related to cancer using the Comparative Toxicogenomics Database. RESULTS We identified five chemicals (NSC668394, glafenine, methylnitronitrosoguanidine, fenofibrate, and methylparaben) that were associated with the incidence of both breast cancer and cervical cancer. CONCLUSION Using a transcriptome-wide association study and gene set enrichment analysis we identified environmental chemicals that are associated with an increased risk of breast cancer, cervical cancer, and ovarian cancer.
Collapse
Affiliation(s)
- Liuyun Gong
- Department of Oncology, The First Affiliated Hospital, Xi'an Jiaotong University, Xi'an, Shanxi 710061, PR China
| | - Zhenzhen Luo
- Department of Oncology, The First Affiliated Hospital, Xi'an Jiaotong University, Xi'an, Shanxi 710061, PR China
| | - Hanmin Tang
- Department of Oncology, The First Affiliated Hospital, Xi'an Jiaotong University, Xi'an, Shanxi 710061, PR China
| | - Xinyue Tan
- Department of Oncology, The First Affiliated Hospital, Xi'an Jiaotong University, Xi'an, Shanxi 710061, PR China
| | - Lina Xie
- Department of Oncology, The First Affiliated Hospital, Xi'an Jiaotong University, Xi'an, Shanxi 710061, PR China
| | - Yutiantian Lei
- Department of Oncology, The First Affiliated Hospital, Xi'an Jiaotong University, Xi'an, Shanxi 710061, PR China
| | - Chenchen He
- Department of Oncology, The First Affiliated Hospital, Xi'an Jiaotong University, Xi'an, Shanxi 710061, PR China
| | - Jinlu Ma
- Department of Oncology, The First Affiliated Hospital, Xi'an Jiaotong University, Xi'an, Shanxi 710061, PR China
| | - Suxia Han
- Department of Oncology, The First Affiliated Hospital, Xi'an Jiaotong University, Xi'an, Shanxi 710061, PR China.
| |
Collapse
|
17
|
Evans P, Cox NJ, Gamazon ER. The regulatory genome constrains protein sequence evolution: implications for the search for disease-associated genes. PeerJ 2020; 8:e9554. [PMID: 32765967 PMCID: PMC7380284 DOI: 10.7717/peerj.9554] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2020] [Accepted: 06/24/2020] [Indexed: 11/20/2022] Open
Abstract
The development of explanatory models of protein sequence evolution has broad implications for our understanding of cellular biology, population history, and disease etiology. Here we analyze the GTEx transcriptome resource to quantify the effect of the transcriptome on protein sequence evolution in a multi-tissue framework. We find substantial variation among the central nervous system tissues in the effect of expression variance on evolutionary rate, with highly variable genes in the cortex showing significantly greater purifying selection than highly variable genes in subcortical regions (Mann-Whitney U p = 1.4 × 10-4). The remaining tissues cluster in observed expression correlation with evolutionary rate, enabling evolutionary analysis of genes in diverse physiological systems, including digestive, reproductive, and immune systems. Importantly, the tissue in which a gene attains its maximum expression variance significantly varies (p = 5.55 × 10-284) with evolutionary rate, suggesting a tissue-anchored model of protein sequence evolution. Using a large-scale reference resource, we show that the tissue-anchored model provides a transcriptome-based approach to predicting the primary affected tissue of developmental disorders. Using gradient boosted regression trees to model evolutionary rate under a range of model parameters, selected features explain up to 62% of the variation in evolutionary rate and provide additional support for the tissue model. Finally, we investigate several methodological implications, including the importance of evolutionary-rate-aware gene expression imputation models using genetic data for improved search for disease-associated genes in transcriptome-wide association studies. Collectively, this study presents a comprehensive transcriptome-based analysis of a range of factors that may constrain molecular evolution and proposes a novel framework for the study of gene function and disease mechanism.
Collapse
Affiliation(s)
- Patrick Evans
- Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, United States of America
| | - Nancy J Cox
- Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, United States of America
| | - Eric R Gamazon
- Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, United States of America.,Clare Hall, University of Cambridge, Cambridge, United Kingdom.,MRC Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom.,Data Science Institute, Vanderbilt University, Nashville, TN, United States of America
| |
Collapse
|
18
|
Keys KL, Mak ACY, White MJ, Eckalbar WL, Dahl AW, Mefford J, Mikhaylova AV, Contreras MG, Elhawary JR, Eng C, Hu D, Huntsman S, Oh SS, Salazar S, Lenoir MA, Ye JC, Thornton TA, Zaitlen N, Burchard EG, Gignoux CR. On the cross-population generalizability of gene expression prediction models. PLoS Genet 2020; 16:e1008927. [PMID: 32797036 PMCID: PMC7449671 DOI: 10.1371/journal.pgen.1008927] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2019] [Revised: 08/26/2020] [Accepted: 06/10/2020] [Indexed: 11/21/2022] Open
Abstract
The genetic control of gene expression is a core component of human physiology. For the past several years, transcriptome-wide association studies have leveraged large datasets of linked genotype and RNA sequencing information to create a powerful gene-based test of association that has been used in dozens of studies. While numerous discoveries have been made, the populations in the training data are overwhelmingly of European descent, and little is known about the generalizability of these models to other populations. Here, we test for cross-population generalizability of gene expression prediction models using a dataset of African American individuals with RNA-Seq data in whole blood. We find that the default models trained in large datasets such as GTEx and DGN fare poorly in African Americans, with a notable reduction in prediction accuracy when compared to European Americans. We replicate these limitations in cross-population generalizability using the five populations in the GEUVADIS dataset. Via realistic simulations of both populations and gene expression, we show that accurate cross-population generalizability of transcriptome prediction only arises when eQTL architecture is substantially shared across populations. In contrast, models with non-identical eQTLs showed patterns similar to real-world data. Therefore, generating RNA-Seq data in diverse populations is a critical step towards multi-ethnic utility of gene expression prediction.
Collapse
Affiliation(s)
- Kevin L. Keys
- Department of Medicine, University of California, San Francisco, California, United States of America
- Berkeley Institute for Data Science, University of California, Berkeley, California, United States of America
| | - Angel C. Y. Mak
- Department of Medicine, University of California, San Francisco, California, United States of America
| | - Marquitta J. White
- Department of Medicine, University of California, San Francisco, California, United States of America
| | - Walter L. Eckalbar
- Department of Medicine, University of California, San Francisco, California, United States of America
| | - Andrew W. Dahl
- Department of Medicine, University of California, San Francisco, California, United States of America
| | - Joel Mefford
- Department of Medicine, University of California, San Francisco, California, United States of America
| | - Anna V. Mikhaylova
- Department of Biostatistics, University of Washington, Seattle, Washington, United States of America
| | - María G. Contreras
- Department of Medicine, University of California, San Francisco, California, United States of America
- San Francisco State University, San Francisco, California, United States of America
| | - Jennifer R. Elhawary
- Department of Medicine, University of California, San Francisco, California, United States of America
| | - Celeste Eng
- Department of Medicine, University of California, San Francisco, California, United States of America
| | - Donglei Hu
- Department of Medicine, University of California, San Francisco, California, United States of America
| | - Scott Huntsman
- Department of Medicine, University of California, San Francisco, California, United States of America
| | - Sam S. Oh
- Department of Medicine, University of California, San Francisco, California, United States of America
| | - Sandra Salazar
- Department of Medicine, University of California, San Francisco, California, United States of America
| | | | - Jimmie C. Ye
- Department of Epidemiology and Biostatistics, University of California, San Francisco, California, United States of America
- Department of Bioengineering and Therapeutic Biosciences, University of California, San Francisco, California, United States of America
| | - Timothy A. Thornton
- Department of Biostatistics, University of Washington, Seattle, Washington, United States of America
| | - Noah Zaitlen
- Department of Neurology, University of California, Los Angeles, California, United States of America
| | - Esteban G. Burchard
- Department of Medicine, University of California, San Francisco, California, United States of America
- Department of Bioengineering and Therapeutic Biosciences, University of California, San Francisco, California, United States of America
| | - Christopher R. Gignoux
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States of America
- Department of Biostatistics and Informatics, School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States of America
| |
Collapse
|
19
|
Huang QQ, Tang HHF, Teo SM, Mok D, Ritchie SC, Nath AP, Brozynska M, Salim A, Bakshi A, Holt BJ, Khor CC, Sly PD, Holt PG, Holt KE, Inouye M. Neonatal genetics of gene expression reveal potential origins of autoimmune and allergic disease risk. Nat Commun 2020; 11:3761. [PMID: 32724101 PMCID: PMC7387553 DOI: 10.1038/s41467-020-17477-x] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2019] [Accepted: 06/29/2020] [Indexed: 12/12/2022] Open
Abstract
Chronic immune-mediated diseases of adulthood often originate in early childhood. To investigate genetic associations between neonatal immunity and disease, we map expression quantitative trait loci (eQTLs) in resting myeloid cells and CD4+ T cells from cord blood samples, as well as in response to lipopolysaccharide (LPS) or phytohemagglutinin (PHA) stimulation, respectively. Cis-eQTLs are largely specific to cell type or stimulation, and 31% and 52% of genes with cis-eQTLs have response eQTLs (reQTLs) in myeloid cells and T cells, respectively. We identified cis regulatory factors acting as mediators of trans effects. There is extensive colocalisation between condition-specific neonatal cis-eQTLs and variants associated with immune-mediated diseases, in particular CTSH had widespread colocalisation across diseases. Mendelian randomisation shows causal neonatal gene expression effects on disease risk for BTN3A2, HLA-C and others. Our study elucidates the genetics of gene expression in neonatal immune cells, and aetiological origins of autoimmune and allergic diseases. Some immune-mediated diseases may originate in early childhood. The authors mapped eQTLs and response eQTLs to various stimuli in neonatal myeloid cells and T cells, and revealed their potential role in immune-mediated diseases using colocalisation and Mendelian randomisation.
Collapse
Affiliation(s)
- Qin Qin Huang
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, VIC, 3004, Australia. .,Department of Clinical Pathology, University of Melbourne, Parkville, VIC, 3010, Australia. .,Department of Human Genetics, Wellcome Sanger Institute, Cambridge, UK.
| | - Howard H F Tang
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, VIC, 3004, Australia.,School of BioSciences, The University of Melbourne, Parkville, VIC, 3010, Australia
| | - Shu Mei Teo
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, VIC, 3004, Australia.,Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK
| | - Danny Mok
- Telethon Kids Institute, The University of Western Australia, Perth, WA, 6009, Australia
| | - Scott C Ritchie
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, VIC, 3004, Australia.,Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK.,British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.,National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge and Cambridge University Hospitals, Cambridge, UK
| | - Artika P Nath
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, VIC, 3004, Australia.,Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK
| | - Marta Brozynska
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, VIC, 3004, Australia.,Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK
| | - Agus Salim
- Baker Heart and Diabetes Institute, Melbourne, VIC, 3004, Australia.,School of Mathematics and Statistics, The University of Melbourne, Parkville, VIC, 3010, Australia.,Melbourne School of Population and Global Health, Carlton, VIC, 3053, Australia
| | - Andrew Bakshi
- Monash Biomedicine Discovery Institute, Prostate Cancer Research Group, Department of Anatomy and Developmental Biology, Monash University, Clayton, VIC, 3800, Australia
| | - Barbara J Holt
- Telethon Kids Institute, The University of Western Australia, Perth, WA, 6009, Australia
| | - Chiea Chuen Khor
- Human Genetics, Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, 138672, Singapore.,Singapore Eye Research Institute, Singapore, Singapore.,Duke-NUS Medical School, Singapore, Singapore
| | - Peter D Sly
- Child Health Research Centre, The University of Queensland, Brisbane, QLD, 4101, Australia
| | - Patrick G Holt
- Telethon Kids Institute, The University of Western Australia, Perth, WA, 6009, Australia.,Child Health Research Centre, The University of Queensland, Brisbane, QLD, 4101, Australia
| | - Kathryn E Holt
- Department of Infectious Diseases, Central Clinical School, Monash University, Melbourne, VIC, 3004, Australia.,The London School of Hygiene and Tropical Medicine, London, WC1E 7TH, UK
| | - Michael Inouye
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, VIC, 3004, Australia. .,Department of Clinical Pathology, University of Melbourne, Parkville, VIC, 3010, Australia. .,Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK. .,British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK. .,National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge and Cambridge University Hospitals, Cambridge, UK. .,The Alan Turing Institute, London, UK. .,British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, UK. .,Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK.
| |
Collapse
|
20
|
Wallace C. Eliciting priors and relaxing the single causal variant assumption in colocalisation analyses. PLoS Genet 2020; 16:e1008720. [PMID: 32310995 PMCID: PMC7192519 DOI: 10.1371/journal.pgen.1008720] [Citation(s) in RCA: 142] [Impact Index Per Article: 35.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2019] [Revised: 04/30/2020] [Accepted: 03/17/2020] [Indexed: 01/03/2023] Open
Abstract
Horizontal integration of summary statistics from different GWAS traits can be used to evaluate evidence for their shared genetic causality. One popular method to do this is a Bayesian method, coloc, which is attractive in requiring only GWAS summary statistics and no linkage disequilibrium estimates and is now being used routinely to perform thousands of comparisons between traits. Here we show that while most users do not adjust default software values, misspecification of prior parameters can substantially alter posterior inference. We suggest data driven methods to derive sensible prior values, and demonstrate how sensitivity analysis can be used to assess robustness of posterior inference. The flexibility of coloc comes at the expense of an unrealistic assumption of a single causal variant per trait. This assumption can be relaxed by stepwise conditioning, but this requires external software and an LD matrix aligned to study alleles. We have now implemented conditioning within coloc, and propose a new alternative method, masking, that does not require LD and approximates conditioning when causal variants are independent. Importantly, masking can be used in combination with conditioning where allelically aligned LD estimates are available for only a single trait. We have implemented these developments in a new version of coloc which we hope will enable more informed choice of priors and overcome the restriction of the single causal variant assumptions in coloc analysis.
Collapse
Affiliation(s)
- Chris Wallace
- Cambridge Institute for Therapeutic Immunology & Infectious Disease, and MRC Biostatistics Unit, University of Cambridge, Cambridge, United Kingdom
| |
Collapse
|
21
|
Bossé Y, Li Z, Xia J, Manem V, Carreras-Torres R, Gabriel A, Gaudreault N, Albanes D, Aldrich MC, Andrew A, Arnold S, Bickeböller H, Bojesen SE, Brennan P, Brunnstrom H, Caporaso N, Chen C, Christiani DC, Field JK, Goodman G, Grankvist K, Houlston R, Johansson M, Johansson M, Kiemeney LA, Lam S, Landi MT, Lazarus P, Le Marchand L, Liu G, Melander O, Rennert G, Risch A, Rosenberg SM, Schabath MB, Shete S, Song Z, Stevens VL, Tardon A, Wichmann HE, Woll P, Zienolddiny S, Obeidat M, Timens W, Hung RJ, Joubert P, Amos CI, McKay JD. Transcriptome-wide association study reveals candidate causal genes for lung cancer. Int J Cancer 2020; 146:1862-1878. [PMID: 31696517 PMCID: PMC7008463 DOI: 10.1002/ijc.32771] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2019] [Revised: 10/09/2019] [Accepted: 10/10/2019] [Indexed: 12/17/2022]
Abstract
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.
Collapse
Affiliation(s)
- Yohan Bossé
- Institut universitaire de cardiologie et de pneumologie de Québec, Université Laval, Quebec City, Canada
- Department of Molecular Medicine, Laval University, Quebec City, Canada
| | - Zhonglin Li
- Institut universitaire de cardiologie et de pneumologie de Québec, Université Laval, Quebec City, Canada
| | - Jun Xia
- Baylor College of Medicine, The Institute for Clinical and Translational Research, Houston, TX
| | - Venkata Manem
- Institut universitaire de cardiologie et de pneumologie de Québec, Université Laval, Quebec City, Canada
| | | | - Aurélie Gabriel
- International Agency for Research on Cancer, World Health Organization, Lyon, France
| | - Nathalie Gaudreault
- Institut universitaire de cardiologie et de pneumologie de Québec, Université Laval, Quebec City, Canada
| | - Demetrius Albanes
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD
| | - Melinda C Aldrich
- Thoracic Surgery, Division of Epidemiology, Vanderbilt University Medical Center, Nashville, TN
| | - Angeline Andrew
- Department of Neurology, Dartmouth-Hitchcock Medical Center, Lebanon, NH
| | - Susanne Arnold
- Markey Cancer Center, University of Kentucky, Lexington, KY
| | - Heike Bickeböller
- Department of Genetic Epidemiology, University Medical Center Goettingen, Goettingen, Germany
| | - Stig E Bojesen
- Department of Clinical Biochemistry, Copenhagen University Hospital, Copenhagen, Denmark
| | - Paul Brennan
- International Agency for Research on Cancer, World Health Organization, Lyon, France
| | | | - Neil Caporaso
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD
| | - Chu Chen
- Program in Epidemiology, Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA
| | - David C Christiani
- Program in Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA
| | - John K Field
- Molecular and Clinical Cancer Medicine, Roy Castle Lung Cancer Research Programme, The University of Liverpool Institute of Translational Medicine, Liverpool, United Kingdom
| | - Gary Goodman
- Public Health Sciences Division, Swedish Cancer Institute, Seattle, WA
| | - Kjell Grankvist
- Department of Medical Biosciences, Umeå University, Umea, Sweden
| | - Richard Houlston
- German Research Center for Environmental Health, Institute for Cancer Research, London, United Kingdom
| | - Mattias Johansson
- International Agency for Research on Cancer, World Health Organization, Lyon, France
| | | | - Lambertus A Kiemeney
- Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Stephen Lam
- Department of Integrative Oncology, British Columbia Cancer Agency, Vancouver, BC, Canada
| | | | - Philip Lazarus
- Department of Pharmaceutical Sciences, College of Pharmacy and Pharmaceutical Sciences, Washington State University, Pullman, WA
| | - Loic Le Marchand
- Department of Epidemiology, University of Hawaii Cancer Center, Honolulu, HI
| | - Geoffrey Liu
- Epidemiology Division, Princess Margaret Cancer Center, Toronto, ON, Canada
| | | | - Gadi Rennert
- Technion Faculty of Medicine, Carmel Medical Center, Haifa, Israel
| | - Angela Risch
- Cancer Center Cluster Salzburg at PLUS, Department of Molecular Biology, University of Salzburg, Salzburg, Austria
| | - Susan M Rosenberg
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX
- Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX
| | - Matthew B Schabath
- Cancer Epidemiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL
| | - Sanjay Shete
- Epidemiology, The University of Texas, MD Anderson Cancer Center, Houston, TX
| | - Zhuoyi Song
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX
- Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX
| | | | - Adonina Tardon
- Faculty of Medicine, University of Oviedo and CIBERESP, Oviedo, Spain
| | - H-Erich Wichmann
- Institute of Epidemiology, Helmholtz Center Munich, Oberschleißheim, Germany
| | - Penella Woll
- Academic Unit of Clinical Oncology, University of Sheffield, Sheffield, United Kingdom
| | | | - Ma'en Obeidat
- The University of British Columbia Centre for Heart Lung Innovation, St Paul's Hospital, Vancouver, BC, Canada
| | - Wim Timens
- Department of Pathology and Medical Biology, GRIAC Research Institute, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Rayjean J Hung
- Prosserman Centre for Population Health Research, Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada
| | - Philippe Joubert
- Institut universitaire de cardiologie et de pneumologie de Québec, Université Laval, Quebec City, Canada
| | - Christopher I Amos
- Baylor College of Medicine, The Institute for Clinical and Translational Research, Houston, TX
| | - James D McKay
- International Agency for Research on Cancer, World Health Organization, Lyon, France
| |
Collapse
|
22
|
Musolf AM, Moiz BA, Sun H, Pikielny CW, Bossé Y, Mandal D, de Andrade M, Gaba C, Yang P, Li Y, You M, Govindan R, Wilson RK, Kupert EY, Anderson MW, Schwartz AG, Pinney SM, Amos CI, Bailey-Wilson JE. Whole Exome Sequencing of Highly Aggregated Lung Cancer Families Reveals Linked Loci for Increased Cancer Risk on Chromosomes 12q, 7p, and 4q. Cancer Epidemiol Biomarkers Prev 2019; 29:434-442. [PMID: 31826912 DOI: 10.1158/1055-9965.epi-19-0887] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2019] [Revised: 10/15/2019] [Accepted: 12/04/2019] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND Lung cancer kills more people than any other cancer in the United States. In addition to environmental factors, lung cancer has genetic risk factors as well, though the genetic etiology is still not well understood. We have performed whole exome sequencing on 262 individuals from 28 extended families with a family history of lung cancer. METHODS Parametric genetic linkage analysis was performed on these samples using two distinct analyses-the lung cancer only (LCO) analysis, where only patients with lung cancer were coded as affected, and the all aggregated cancers (AAC) analysis, where other cancers seen in the pedigree were coded as affected. RESULTS The AAC analysis yielded a genome-wide significant result at rs61943670 in POLR3B at 12q23.3. POLR3B has been implicated somatically in lung cancer, but this germline finding is novel and is a significant expression quantitative trait locus in lung tissue. Interesting genome-wide suggestive haplotypes were also found within individual families, particularly near SSPO at 7p36.1 in one family and a large linked haplotype spanning 4q21.3-28.3 in a different family. The 4q haplotype contains potential causal rare variants in DSPP at 4q22.1 and PTPN13 at 4q21.3. CONCLUSIONS Regions on 12q, 7p, and 4q are linked to increased cancer risk in highly aggregated lung cancer families, 12q across families and 7p and 4q within a single family. POLR3B, SSPO, DSPP, and PTPN13 are currently the best candidate genes. IMPACT Functional work on these genes is planned for future studies and if confirmed would lead to potential biomarkers for risk in cancer.
Collapse
Affiliation(s)
- Anthony M Musolf
- Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Baltimore, Maryland
| | - Bilal A Moiz
- Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Baltimore, Maryland
| | - Haiming Sun
- Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Baltimore, Maryland.,Laboratory of Medical Genetics, Harbin Medical University, Harbin, China
| | | | - Yohan Bossé
- Institut universitaire de cardiologie et de pneumologie de Québec, Department of Molecular Medicine, Laval University, Québec, Québec, Canada
| | - Diptasri Mandal
- Department of Genetics, Louisiana State University Health Sciences Center, New Orleans, Louisiana
| | | | - Colette Gaba
- Department of Medicine, University of Toledo Dana Cancer Center, Toledo, Ohio
| | | | - Yafang Li
- Baylor College of Medicine, Houston, Texas
| | - Ming You
- Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Ramaswamy Govindan
- Division of Oncology, Washington University School of Medicine, St. Louis, Missouri
| | - Richard K Wilson
- Institute for Genomic Medicine, Nationwide Children's Hospital, Columbus, Ohio
| | | | | | - Ann G Schwartz
- Karmanos Cancer Institute, Wayne State University, Detroit, Michigan
| | - Susan M Pinney
- Department of Environmental Health, University of Cincinnati College of Medicine, Cincinnati, Ohio
| | | | - Joan E Bailey-Wilson
- Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Baltimore, Maryland.
| |
Collapse
|
23
|
Abstract
Genome-wide association studies (GWAS) have identified more than 20 genomic regions associated with chronic obstructive pulmonary disease (COPD) susceptibility. However, the functional genetic variants within these COPD GWAS loci remain largely unidentified, thus limiting translation of these GWAS discoveries to new disease insights. Whole-exome and whole-genome sequencing studies have the potential to identify rare genetic determinants of COPD. Efforts to understand the biological effects of novel COPD genetic loci include gene-targeted murine models, integration of additional omics data (including transcriptomics and epigenetics), and functional variant identification. COPD genetic determinants likely act through biological networks, and a variety of network-based approaches have been used to gain insights into COPD susceptibility and heterogeneity.
Collapse
|
24
|
Li Y, Xiao X, Bossé Y, Gorlova O, Gorlov I, Han Y, Byun J, Leighl N, Johansen JS, Barnett M, Chen C, Goodman G, Cox A, Taylor F, Woll P, Wichmann HE, Manz J, Muley T, Risch A, Rosenberger A, Han J, Siminovitch K, Arnold SM, Haura EB, Bolca C, Holcatova I, Janout V, Kontic M, Lissowska J, Mukeria A, Ognjanovic S, Orlowski TM, Scelo G, Swiatkowska B, Zaridze D, Bakke P, Skaug V, Zienolddiny S, Duell EJ, Butler LM, Houlston R, Artigas MS, Grankvist K, Johansson M, Shepherd FA, Marcus MW, Brunnström H, Manjer J, Melander O, Muller DC, Overvad K, Trichopoulou A, Tumino R, Liu G, Bojesen SE, Wu X, Le Marchand L, Albanes D, Bickeböller H, Aldrich MC, Bush WS, Tardon A, Rennert G, Teare MD, Field JK, Kiemeney LA, Lazarus P, Haugen A, Lam S, Schabath MB, Andrew AS, Bertazzi PA, Pesatori AC, Christiani DC, Caporaso N, Johansson M, McKay JD, Brennan P, Hung RJ, Amos CI. Genetic interaction analysis among oncogenesis-related genes revealed novel genes and networks in lung cancer development. Oncotarget 2019; 10:1760-1774. [PMID: 30956756 PMCID: PMC6442994 DOI: 10.18632/oncotarget.26678] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2018] [Accepted: 01/22/2019] [Indexed: 12/31/2022] Open
Abstract
The development of cancer is driven by the accumulation of many oncogenesis-related genetic alterations and tumorigenesis is triggered by complex networks of involved genes rather than independent actions. To explore the epistasis existing among oncogenesis-related genes in lung cancer development, we conducted pairwise genetic interaction analyses among 35,031 SNPs from 2027 oncogenesis-related genes. The genotypes from three independent genome-wide association studies including a total of 24,037 lung cancer patients and 20,401 healthy controls with Caucasian ancestry were analyzed in the study. Using a two-stage study design including discovery and replication studies, and stringent Bonferroni correction for multiple statistical analysis, we identified significant genetic interactions between SNPs in RGL1:RAD51B (OR=0.44, p value=3.27x10-11 in overall lung cancer and OR=0.41, p value=9.71x10-11 in non-small cell lung cancer), SYNE1:RNF43 (OR=0.73, p value=1.01x10-12 in adenocarcinoma) and FHIT:TSPAN8 (OR=1.82, p value=7.62x10-11 in squamous cell carcinoma) in our analysis. None of these genes have been identified from previous main effect association studies in lung cancer. Further eQTL gene expression analysis in lung tissues provided information supporting the functional role of the identified epistasis in lung tumorigenesis. Gene set enrichment analysis revealed potential pathways and gene networks underlying molecular mechanisms in overall lung cancer as well as histology subtypes development. Our results provide evidence that genetic interactions between oncogenesis-related genes play an important role in lung tumorigenesis and epistasis analysis, combined with functional annotation, provides a valuable tool for uncovering functional novel susceptibility genes that contribute to lung cancer development by interacting with other modifier genes.
Collapse
Affiliation(s)
- Yafang Li
- Baylor College of Medicine, Houston, TX, USA
| | | | | | - Olga Gorlova
- Department of Biomedical Data Science, Dartmouth College, Hanover, NH, USA
| | - Ivan Gorlov
- Department of Biomedical Data Science, Dartmouth College, Hanover, NH, USA
| | | | | | - Natasha Leighl
- University Health Network, The Princess Margaret Cancer Centre, Toronto, CA, USA
| | - Jakob S. Johansen
- Department of Oncology, Herlev and Gentofte Hospital, Copenhagen University Hospital, Copenhagen, Denmark
| | - Matt Barnett
- Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Chu Chen
- Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | | | - Angela Cox
- Department of Oncology, University of Sheffield, Sheffield, UK
| | - Fiona Taylor
- Department of Oncology, University of Sheffield, Sheffield, UK
| | - Penella Woll
- Department of Oncology, University of Sheffield, Sheffield, UK
| | - H. Erich Wichmann
- Research Unit of Molecular Epidemiology, Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Judith Manz
- Research Unit of Molecular Epidemiology, Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Thomas Muley
- Thoraxklinik at University Hospital Heidelberg, Translational Lung Research Center Heidelberg (TLRC-H), Heidelberg, Germany
| | - Angela Risch
- Translational Lung Research Center Heidelberg (TLRC-H), Heidelberg, Germany
- German Center for Lung Research (DKFZ), Heidelberg, Germany
- University of Salzburg and Cancer Cluster, Salzburg, Austria
| | - Albert Rosenberger
- Department of Genetic Epidemiology, University Medical Center, Georg-August-University Göttingen, Göttingen, Germany
| | - Jiali Han
- Indiana University, Bloomington, IN, USA
| | | | | | - Eric B. Haura
- Department of Thoracic Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Ciprian Bolca
- Institute of Pneumology “Marius Nasta”, Bucharest, Romania
| | - Ivana Holcatova
- Faculty of Medicine, University of Ostrava, Ostrava, Czech Republic
| | - Vladimir Janout
- Faculty of Medicine, University of Ostrava, Ostrava, Czech Republic
| | - Milica Kontic
- Clinical Center of Serbia, School of Medicine, University of Belgrade, Belgrade, Serbia
| | - Jolanta Lissowska
- M. Sklodowska-Curie Cancer Center, Institute of Oncology, Warsaw, Poland
| | - Anush Mukeria
- Department of Epidemiology and Prevention, N.N. Blokhin Russian Cancer Research Center, Moscow, Russian Federation
| | - Simona Ognjanovic
- International Organization for Cancer Prevention and Research, Belgrade, Serbia
| | - Tadeusz M. Orlowski
- Department of Surgery, National Tuberculosis and Lung Diseases Research Institute, Warsaw, Poland
| | - Ghislaine Scelo
- International Agency for Research on Cancer, World Health Organization, Lyon, France
| | - Beata Swiatkowska
- Nofer Institute of Occupational Medicine, Department of Environmental Epidemiology, Lodz, Poland
| | - David Zaridze
- Department of Epidemiology and Prevention, N.N. Blokhin Russian Cancer Research Center, Moscow, Russian Federation
| | - Per Bakke
- Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Vidar Skaug
- National Institute of Occupational Health, Oslo, Norway
| | | | - Eric J. Duell
- Unit of Nutrition and Cancer, Catalan Institute of Oncology (ICO-IDIBELL), Barcelona, Spain
| | | | | | - María Soler Artigas
- Department of Health Sciences, Genetic Epidemiology Group, University of Leicester, Leicester, UK
- National Institute for Health Research (NIHR) Leicester Respiratory Biomedical Research Unit, Glenfield Hospital, Leicester, UK
| | - Kjell Grankvist
- Department of Medical Biosciences, Umeå University, Umeå, Sweden
| | | | | | - Michael W. Marcus
- Institute of Translational Medicine, University of Liverpool, Liverpool, UK
| | | | - Jonas Manjer
- Faculty of Medicine, Lund University, Lund, Sweden
| | | | - David C. Muller
- School of Public Health, St. Mary’s Campus, Imperial College London, London, UK
| | - Kim Overvad
- Section for Epidemiology, Department of Public Health, Aarhus University, Aarhus, Denmark
| | | | - Rosario Tumino
- Molecular and Nutritional Epidemiology Unit CSPO (Cancer Research and Prevention Centre), Scientific Institute of Tuscany, Florence, Italy
| | - Geoffrey Liu
- Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital, University of Toronto, Toronto, Canada
| | - Stig E. Bojesen
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Denmark
- Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Copenhagen General Population Study, Herlev and Gentofte Hospital, Copenhagen, Denmark
| | - Xifeng Wu
- Department of Epidemiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Loic Le Marchand
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Demetrios Albanes
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Heike Bickeböller
- Department of Genetic Epidemiology, University Medical Center, Georg-August-University Göttingen, Göttingen, Germany
| | - Melinda C. Aldrich
- Department of Thoracic Surgery, Division of Epidemiology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - William S. Bush
- Department of Epidemiology and Biostatistics, School of Medicine, Case Western Reserve University, Cleveland, OH, USA
| | - Adonina Tardon
- IUOPA, University of Oviedo and CIBERESP, Faculty of Medicine, Campus del Cristo s/n, Oviedo, Spain
| | - Gad Rennert
- Clalit National Cancer Control Center at Carmel Medical Center and Technion Faculty of Medicine, Haifa, Israel
| | - M. Dawn Teare
- School of Health and Related Research, University of Sheffield, Sheffield, UK
| | - John K. Field
- Institute of Translational Medicine, University of Liverpool, Liverpool, UK
| | | | - Philip Lazarus
- Department of Pharmaceutical Sciences, College of Pharmacy, Washington State University, Spokane, WA, USA
| | - Aage Haugen
- National Institute of Occupational Health, Oslo, Norway
| | - Stephen Lam
- British Columbia Cancer Agency, Vancouver, Canada
| | - Matthew B. Schabath
- Department of Cancer Epidemiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | | | - Pier Alberto Bertazzi
- Department of Preventive Medicine, IRCCS Foundation Ca’ Granda Ospedale Maggiore Policlinico, Milan, Italy
- Department of Clinical Sciences and Community Health, University of Milan, Milan, Italy
| | - Angela C. Pesatori
- Department of Clinical Sciences and Community Health, University of Milan, Milan, Italy
| | - David C. Christiani
- Department of Epidemiology, Program in Molecular and Genetic Epidemiology Harvard School of Public Health, Boston, MA, USA
| | - Neil Caporaso
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Mattias Johansson
- Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital, University of Toronto, Toronto, Canada
| | - James D. McKay
- Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital, University of Toronto, Toronto, Canada
| | - Paul Brennan
- Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital, University of Toronto, Toronto, Canada
| | - Rayjean J. Hung
- International Agency for Research on Cancer, World Health Organization, Lyon, France
| | | |
Collapse
|
25
|
Sakornsakolpat P, Prokopenko D, Lamontagne M, Reeve NF, Guyatt AL, Jackson VE, Shrine N, Qiao D, Bartz TM, Kim DK, Lee MK, Latourelle JC, Li X, Morrow JD, Obeidat M, Wyss AB, Bakke P, Barr RG, Beaty TH, Belinsky SA, Brusselle GG, Crapo JD, de Jong K, DeMeo DL, Fingerlin TE, Gharib SA, Gulsvik A, Hall IP, Hokanson JE, Kim WJ, Lomas DA, London SJ, Meyers DA, O'Connor GT, Rennard SI, Schwartz DA, Sliwinski P, Sparrow D, Strachan DP, Tal-Singer R, Tesfaigzi Y, Vestbo J, Vonk JM, Yim JJ, Zhou X, Bossé Y, Manichaikul A, Lahousse L, Silverman EK, Boezen HM, Wain LV, Tobin MD, Hobbs BD, Cho MH. Genetic landscape of chronic obstructive pulmonary disease identifies heterogeneous cell-type and phenotype associations. Nat Genet 2019; 51:494-505. [PMID: 30804561 PMCID: PMC6546635 DOI: 10.1038/s41588-018-0342-2] [Citation(s) in RCA: 205] [Impact Index Per Article: 41.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2018] [Accepted: 12/20/2018] [Indexed: 11/09/2022]
Abstract
Chronic obstructive pulmonary disease (COPD) is the leading cause of respiratory mortality worldwide. Genetic risk loci provide new insights into disease pathogenesis. We performed a genome-wide association study in 35,735 cases and 222,076 controls from the UK Biobank and additional studies from the International COPD Genetics Consortium. We identified 82 loci associated with P < 5 × 10-8; 47 of these were previously described in association with either COPD or population-based measures of lung function. Of the remaining 35 new loci, 13 were associated with lung function in 79,055 individuals from the SpiroMeta consortium. Using gene expression and regulation data, we identified functional enrichment of COPD risk loci in lung tissue, smooth muscle, and several lung cell types. We found 14 COPD loci shared with either asthma or pulmonary fibrosis. COPD genetic risk loci clustered into groups based on associations with quantitative imaging features and comorbidities. Our analyses provide further support for the genetic susceptibility and heterogeneity of COPD.
Collapse
Affiliation(s)
- Phuwanat Sakornsakolpat
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Department of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | - Dmitry Prokopenko
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Genetics and Aging Research Unit, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Maxime Lamontagne
- Institut Universitaire de Cardiologie et de Pneumologie de Québec, Québec, Quebec, Canada
| | - Nicola F Reeve
- Genetic Epidemiology Group, Department of Health Sciences, University of Leicester, Leicester, UK
| | - Anna L Guyatt
- Genetic Epidemiology Group, Department of Health Sciences, University of Leicester, Leicester, UK
| | - Victoria E Jackson
- Genetic Epidemiology Group, Department of Health Sciences, University of Leicester, Leicester, UK
| | - Nick Shrine
- Genetic Epidemiology Group, Department of Health Sciences, University of Leicester, Leicester, UK
| | - Dandi Qiao
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Traci M Bartz
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, USA
- Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Deog Kyeom Kim
- Seoul National University College of Medicine, SMG-SNU Boramae Medical Center, Seoul, South Korea
| | - Mi Kyeong Lee
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Raleigh, NC, USA
| | - Jeanne C Latourelle
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Xingnan Li
- Department of Medicine, University of Arizona, Tucson, AZ, USA
| | - Jarrett D Morrow
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Ma'en Obeidat
- University of British Columbia Center for Heart Lung Innovation, St. Paul's Hospital, Vancouver, British Columbia, Canada
| | - Annah B Wyss
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Raleigh, NC, USA
| | - Per Bakke
- Department of Clinical Science, University of Bergen, Bergen, Norway
| | - R Graham Barr
- Department of Medicine, College of Physicians and Surgeons and Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Terri H Beaty
- Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA
| | | | - Guy G Brusselle
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
- Department of Respiratory Medicine, Ghent University Hospital, Ghent, Belgium
- Department of Respiratory Medicine, Erasmus Medical Center, Rotterdam, the Netherlands
| | - James D Crapo
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, National Jewish Health, Denver, CO, USA
| | - Kim de Jong
- University of Groningen, University Medical Center Groningen, Department of Epidemiology, Groningen, the Netherlands
- University of Groningen, University Medical Center Groningen, Groningen Research Institute for Asthma and COPD (GRIAC), Groningen, the Netherlands
| | - Dawn L DeMeo
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Tasha E Fingerlin
- Center for Genes, Environment and Health, National Jewish Health, Denver, CO, USA
- Department of Biostatistics and Informatics, University of Colorado Denver, Aurora, CO, USA
| | - Sina A Gharib
- Computational Medicine Core, Center for Lung Biology, UW Medicine Sleep Center, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Amund Gulsvik
- Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Ian P Hall
- Division of Respiratory Medicine, Queen's Medical Centre, University of Nottingham, Nottingham, UK
- National Institute for Health Research Nottingham Biomedical Research Centre, Nottingham, UK
| | - John E Hokanson
- Department of Epidemiology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Woo Jin Kim
- Department of Internal Medicine and Environmental Health Center, School of Medicine, Kangwon National University, Chuncheon, South Korea
| | - David A Lomas
- UCL Respiratory, University College London, London, UK
| | - Stephanie J London
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Raleigh, NC, USA
| | | | - George T O'Connor
- National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, USA
- Pulmonary Center, Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | - Stephen I Rennard
- Pulmonary, Critical Care, Sleep and Allergy Division, Department of Internal Medicine, University of Nebraska Medical Center, Omaha, NE, USA
- Clinical Discovery Unit, AstraZeneca, Cambridge, UK
| | - David A Schwartz
- Department of Medicine, School of Medicine, University of Colorado Denver, Aurora, CO, USA
- Department of Immunology, School of Medicine, University of Colorado Denver, Aurora, CO, USA
| | - Pawel Sliwinski
- 2nd Department of Respiratory Medicine, Institute of Tuberculosis and Lung Diseases, Warsaw, Poland
| | - David Sparrow
- VA Boston Healthcare System and Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | - David P Strachan
- Population Health Research Institute, St. George's University of London, London, UK
| | | | | | - Jørgen Vestbo
- School of Biological Sciences, University of Manchester, Manchester, UK
| | - Judith M Vonk
- University of Groningen, University Medical Center Groningen, Department of Epidemiology, Groningen, the Netherlands
- University of Groningen, University Medical Center Groningen, Groningen Research Institute for Asthma and COPD (GRIAC), Groningen, the Netherlands
| | - Jae-Joon Yim
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Seoul National University College of Medicine, Seoul, South Korea
| | - Xiaobo Zhou
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Yohan Bossé
- Institut Universitaire de Cardiologie et de Pneumologie de Québec, Québec, Quebec, Canada
- Department of Molecular Medicine, Laval University, Québec, Québec, Canada
| | - Ani Manichaikul
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
- Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA
| | - Lies Lahousse
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
- Department of Bioanalysis, Ghent University, Ghent, Belgium
| | - Edwin K Silverman
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - H Marike Boezen
- University of Groningen, University Medical Center Groningen, Department of Epidemiology, Groningen, the Netherlands
- University of Groningen, University Medical Center Groningen, Groningen Research Institute for Asthma and COPD (GRIAC), Groningen, the Netherlands
| | - Louise V Wain
- Genetic Epidemiology Group, Department of Health Sciences, University of Leicester, Leicester, UK
- National Institute for Health Research Leicester Respiratory Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Martin D Tobin
- Genetic Epidemiology Group, Department of Health Sciences, University of Leicester, Leicester, UK
- National Institute for Health Research Leicester Respiratory Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Brian D Hobbs
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Michael H Cho
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA.
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA.
| |
Collapse
|
26
|
Zhang X, Guo Y, Yang J, Niu J, Du L, Li H, Li X. A functional variant alters binding of activating protein 1 regulating expression of FGF7 gene associated with chronic obstructive pulmonary disease. BMC MEDICAL GENETICS 2019; 20:33. [PMID: 30777021 PMCID: PMC6380023 DOI: 10.1186/s12881-019-0761-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/13/2018] [Accepted: 01/29/2019] [Indexed: 02/07/2023]
Abstract
Background Genome-wide association studies (GWASs) of a large cohort of subjects with chronic obstructive pulmonary disease (COPD) have successfully identified multiple risk genes, including fibroblast growth factor 7 (FGF7). However, the underlying molecular mechanism influencing function of FGF7 and risk of COPD remains further study. Methods In this study, we replicated the genetic association of variants near the FGF7 gene in 258 Chinese Han patients with COPD and 311 healthy controls. Additionally, we functionally evaluated a candidate causal variant upstream of the FGF7 gene. Results The most significant association was observed at rs12905203 (P = 5.9 × 10− 3, odd ratio, OR = 1.516) that explains associations of previously reported variants at the FGF7 locus. Electrophoretic mobility shift assay (EMSA) and chromatin immunoprecipitation-quantitative polymerase chain reaction (ChIP-qPCR) assays showed that the risk allele of the variant was bound to activator protein 1 transcription factors (c-Fos and c-Jun) with a significantly reduced affinity and associated with decreased mRNA expression of FGF7 in fibroblast cells at both resting and PMA/Ionomycin-stimulated conditions. Overexpression of c-Fos and c-Jun proteins or stimulation with PMA/Ionomycin significantly increases mRNA expression of FGF7 in fibroblast cells. Bioinformatic analysis showed that the variant overlaps with multiple genetic regulatory marks, suggesting the regulatory DNA element might function as an enhancer for the FGF7 gene. Luciferase enhancer activity assays demonstrated that the DNA sequences carrying the variant produce enhancer activity while the risk allele of the variant reduces its activity. Conclusions In this study, we demonstrated a consistent association of the FGF7 gene with COPD and mechanistically characterized a candidate functional variant upstream of the FGF7 gene. These data highlighted the important role of the risk variant and the FGF7 gene in influencing risk for COPD. Electronic supplementary material The online version of this article (10.1186/s12881-019-0761-7) contains supplementary material, which is available to authorized users.
Collapse
Affiliation(s)
- Xiaomei Zhang
- College of Life Science, Engineering Research Center of the Chinese Ministry of Education for Bioreactor and Pharmaceutical Development, Jilin Agricultural University, NO. 2888, XinCheng Avenue, Changchun, 130118, China.
| | - Yongxin Guo
- College of Life Science, Engineering Research Center of the Chinese Ministry of Education for Bioreactor and Pharmaceutical Development, Jilin Agricultural University, NO. 2888, XinCheng Avenue, Changchun, 130118, China
| | - Jing Yang
- College of Life Science, Engineering Research Center of the Chinese Ministry of Education for Bioreactor and Pharmaceutical Development, Jilin Agricultural University, NO. 2888, XinCheng Avenue, Changchun, 130118, China
| | - Jianlou Niu
- School of Pharmacy, Wenzhou Medical University, Chashan Avenue, Wenzhou, 325035, Zhejiang, China
| | - Lina Du
- College of Life Science, Engineering Research Center of the Chinese Ministry of Education for Bioreactor and Pharmaceutical Development, Jilin Agricultural University, NO. 2888, XinCheng Avenue, Changchun, 130118, China
| | - Haiyan Li
- College of Life Science, Engineering Research Center of the Chinese Ministry of Education for Bioreactor and Pharmaceutical Development, Jilin Agricultural University, NO. 2888, XinCheng Avenue, Changchun, 130118, China.
| | - Xiaokun Li
- College of Life Science, Engineering Research Center of the Chinese Ministry of Education for Bioreactor and Pharmaceutical Development, Jilin Agricultural University, NO. 2888, XinCheng Avenue, Changchun, 130118, China. .,School of Pharmacy, Wenzhou Medical University, Chashan Avenue, Wenzhou, 325035, Zhejiang, China.
| |
Collapse
|
27
|
Peng S, Deyssenroth MA, Di Narzo AF, Cheng H, Zhang Z, Lambertini L, Ruusalepp A, Kovacic JC, Bjorkegren JLM, Marsit CJ, Chen J, Hao K. Genetic regulation of the placental transcriptome underlies birth weight and risk of childhood obesity. PLoS Genet 2018; 14:e1007799. [PMID: 30596636 PMCID: PMC6329610 DOI: 10.1371/journal.pgen.1007799] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2018] [Revised: 01/11/2019] [Accepted: 10/30/2018] [Indexed: 12/13/2022] Open
Abstract
GWAS identified variants associated with birth weight (BW), childhood obesity (CO) and childhood BMI (CBMI), and placenta is a critical organ for fetal development and postnatal health. We examined the role of placental transcriptome and eQTLs in mediating the genetic causes for BW, CO and CBMI, and applied integrative analysis (Colocalization and MetaXcan). GWAS loci associated with BW, CO, and CBMI were substantially enriched for placenta eQTLs (6.76, 4.83 and 2.26 folds, respectively). Importantly, compared to eQTLs of adult tissues, only placental eQTLs contribute significantly to both anthropometry outcomes at birth (BW) and childhood phenotypes (CO/CBMI). Eight, six and one transcripts colocalized with BW, CO and CBMI risk loci, respectively. Our study reveals that placental transcription in utero likely plays a key role in determining postnatal body size, and as such may hold new possibilities for therapeutic interventions to prevent childhood obesity.
Collapse
Affiliation(s)
- Shouneng Peng
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Maya A. Deyssenroth
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Antonio F. Di Narzo
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Haoxiang Cheng
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Zhongyang Zhang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Luca Lambertini
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- Department of Obstetrics, Gynecology and Reproductive Science, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Arno Ruusalepp
- Department of Cardiac Surgery, Tartu University Hospital, Tartu, Estonia
| | - Jason C. Kovacic
- Cardiovascular Research Centre, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Johan L. M. Bjorkegren
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- Integrated Cardio Metabolic Centre, Department of Medicine, Karolinska Institutet, Karolinska Universitetssjukhuset, Huddinge, Sweden
| | - Carmen J. Marsit
- Environmental Health at Rollins School of Public Health, Emory University, Atlanta, Georgia, United States of America
| | - Jia Chen
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- Department of Oncological Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- Department of Hematology and Medical Oncology, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Ke Hao
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- Department of Respiratory Medicine, Shanghai Tenth People’s Hospital, Tongji University, Shanghai, China
- College of Environmental Science and Engineering, Tongji University, Shanghai, China
- * E-mail:
| |
Collapse
|
28
|
Gong L, Zhang D, Lei Y, Qian Y, Tan X, Han S. Transcriptome-wide association study identifies multiple genes and pathways associated with pancreatic cancer. Cancer Med 2018; 7:5727-5732. [PMID: 30334361 PMCID: PMC6247024 DOI: 10.1002/cam4.1836] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2018] [Revised: 09/25/2018] [Accepted: 09/26/2018] [Indexed: 12/12/2022] Open
Abstract
AIM To identify novel candidate genes for pancreatic cancer. METHODS We performed a transcriptome-wide association study (TWAS) analysis of pancreatic cancer (PC). GWAS summary data were driven from the published studies of PC, totally involving 558 542 SNPs in 1896 individuals with pancreatic cancer and 1939 healthy controls. FUSION software was applied to the PC GWAS summary data for tissue-related TWAS analysis, including whole blood, peripheral blood, adipose, and pancreas. The functional relevance of identified genes with PC was further validated by Oncomine, STRING, and CluePedia tool. RESULTS Transcriptome-wide association study analysis identified 19 genes significantly associated with PC, such as LRP5L (P value = 5.21 × 10-5 ), SOX4 (P value = 3.2 × 10-4 ), and EGLN3 (P value = 6.2 × 10-3 ). KEGG pathway enrichment analysis detected several PC-associated pathways, such as One carbon pool by folate (P value = 1.60 × 10-16 ), Cell cycle (P value = 1.27 × 10-7 ), TGF-beta signaling pathway (P value = 4.64 × 10-6 ). Further comparing the 19 genes with previously identified overexpressed genes in PC patients found one overlapped gene SOX4. CONCLUSION We identified some novel candidate genes and pathways associated with PC. Our results provide novel clues for the genetic mechanism studies of pancreatic cancer.
Collapse
Affiliation(s)
- Liuyun Gong
- Department of Oncology, The First Affiliated Hospital, College of Medicine, Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Dan Zhang
- Department of Cell Biology and Genetics, School of Basic Medical Sciences, Xi'an Jiaotong University Health Science Center, Xi'an, China
| | - Yutiantian Lei
- Department of Oncology, The First Affiliated Hospital, College of Medicine, Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Yuanjie Qian
- Department of Oncology, The First Affiliated Hospital, College of Medicine, Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Xinyue Tan
- Department of Oncology, The First Affiliated Hospital, College of Medicine, Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Suxia Han
- Department of Oncology, The First Affiliated Hospital, College of Medicine, Xi'an Jiaotong University, Xi'an, Shaanxi, China
| |
Collapse
|