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Zhu J, Liu H, Gao R, Gong R, Wang J, Zhou D, Yu M, Li Y. Genetic-informed proteome-wide scan reveals potential causal plasma proteins for idiopathic pulmonary fibrosis. Thorax 2024:thorax-2024-221398. [PMID: 38871465 DOI: 10.1136/thorax-2024-221398] [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: 06/15/2024]
Abstract
Idiopathic pulmonary fibrosis (IPF) is a lethal lung disease for which there are no reliable biomarkers or disease-modifying drugs. Here, we integrated human genomics and proteomics to investigate the causal associations between 2769 plasma proteins and IPF. Our Mendelian randomisation analysis identified nine proteins associated with IPF, of which three (FUT3, ADAM15 and USP28) were colocalised. ADAM15 emerged as the top candidate, supported by expression quantitative trait locus analysis in both blood and lung tissue. These findings provide novel insights into the aetiology of IPF and offer translational opportunities in response to the clinical challenges of this devastating disease.
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Affiliation(s)
- Jiahao Zhu
- Department of Epidemiology and Health Statistics, School of Public Health, Hangzhou Medical College, Hangzhou, China
| | - Houpu Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Hangzhou Medical College, Hangzhou, China
| | - Rui Gao
- Department of Epidemiology and Health Statistics, School of Public Health, Hangzhou Medical College, Hangzhou, China
| | - Ruicheng Gong
- Department of Epidemiology and Health Statistics, School of Public Health, Hangzhou Medical College, Hangzhou, China
| | - Jing Wang
- Department of Epidemiology and Health Statistics, School of Public Health, Hangzhou Medical College, Hangzhou, China
| | - Dan Zhou
- Department of Big Data in Health Science, School of Public Health, Zhejiang University School of Medicine, Hangzhou, China
- Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Min Yu
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
| | - Yingjun Li
- Department of Epidemiology and Health Statistics, School of Public Health, Hangzhou Medical College, Hangzhou, China
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2
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Villeneuve J, Tremblay É, Gaudreault N, Saavedra Armero V, Boudreau DK, Li Z, Renaut S, Dion G, Bossé Y. A Test to Comprehensively Capture the Known Genetic Component of Familial Pulmonary Fibrosis. Am J Respir Cell Mol Biol 2024; 70:437-445. [PMID: 38363828 PMCID: PMC11160413 DOI: 10.1165/rcmb.2024-0009ma] [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: 01/09/2024] [Accepted: 02/15/2024] [Indexed: 02/18/2024] Open
Abstract
The recent European Respiratory Society statement on familial pulmonary fibrosis supports the need for genetic testing in the care of patients and their relatives. However, no solution (i.e., a concrete test) was provided to implement genetic testing in daily practice. Herein, we tabulated and standardized the nomenclature of 128 genetic variants in 20 genes implicated in adult-onset pulmonary fibrosis. The objective was to develop a laboratory-developed test (LDT) on the basis of standard Sanger sequencing to capture all known familial pulmonary fibrosis-associated variants. Targeted DNA fragments were amplified using harmonized PCR conditions to perform the LDT in a single 96-well plate. The new genetic test was evaluated in 62 sporadic cases of idiopathic pulmonary fibrosis. As expected in this population, we observed a low yield of disease-causing mutations. More important, 100% of targeted variants by the LDT were successfully evaluated. Furthermore, four variants of uncertain significance with in silico-predicted deleterious scores were identified in three patients, suggesting novel pathogenic variants in genes known to cause idiopathic pulmonary fibrosis. Finally, the MUC5B promoter variant rs35705950 was strongly enriched in these patients with a minor allele frequency of 41.1% compared with 10.6% in a matched population-based cohort (n = 29,060), leading to an estimation that this variant may explain up to 35% of the population-attributable risk. This LDT provides a solution for rapid clinical translation. Technical laboratory details are provided so that specialized pulmonary centers can implement the LDT in house to expedite the clinical recommendations of expert panels.
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Affiliation(s)
- Judith Villeneuve
- Institut Universitaire de Cardiologie et de Pneumologie de Québec and
| | - Élody Tremblay
- Institut Universitaire de Cardiologie et de Pneumologie de Québec and
| | | | | | | | - Zhonglin Li
- Institut Universitaire de Cardiologie et de Pneumologie de Québec and
| | - Sébastien Renaut
- Institut Universitaire de Cardiologie et de Pneumologie de Québec and
| | - Geneviève Dion
- Institut Universitaire de Cardiologie et de Pneumologie de Québec and
| | - Yohan Bossé
- Institut Universitaire de Cardiologie et de Pneumologie de Québec and
- Département de Médecine Moléculaire, Université Laval, Québec, Québec, Canada
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3
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Zhang D, zhou Y, Lu T, Li J, Zhu L, Li S, Li Y, Duan X. Exploring the Common Genetic Underpinnings of Chronic Pulmonary Disease and Esophageal Carcinoma Susceptibility. J Cancer 2024; 15:3406-3417. [PMID: 38817868 PMCID: PMC11134432 DOI: 10.7150/jca.95437] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2024] [Accepted: 04/18/2024] [Indexed: 06/01/2024] Open
Abstract
Background: Pulmonary diseases and esophageal cancer are highly prevalent conditions with rising incidence worldwide. Prior evidence supports shared environmental and behavioral factors, but less is known regarding potential genetic links underlying this comorbidity. This study aimed to elucidate the complex genetic relationship between chronic lung diseases and esophageal cancer risk. Methods: Linkage disequilibrium score regression assessed the genetic correlation between esophageal cancer and asthma, COPD, and idiopathic pulmonary fibrosis leveraging extensive GWAS datasets. Pleiotropic analysis, gene-set enrichment, eQTL mapping, and mendelian randomization causality analyses were then conducted to identify specific shared genetic variants, enriched pathways, causal relationships and gene regulatory mechanisms connecting lung disease and cancer susceptibility. Results: Significant genetic correlations were observed between esophageal cancer and both COPD and asthma, but not idiopathic pulmonary fibrosis. Further analyses identified 13 pleiotropic loci and 6 shared genes including CHRNA4, ERBB3, and SMAD3, as well as pathways related to immune function. eQTL integration highlighted 53 genes like SOCS1, FGF2, and CHRNA5 with tissue-specific regulatory effects on disease risk. Bidirectional relationships were noted, whereby genetic predisposition to asthma and COPD increased esophageal cancer risk, while cancer liability reciprocally raised pulmonary fibrosis risk. Conclusions: These genomic analyses provide initial evidence that shared genetic factors may underpin the comorbidity between lung conditions and esophageal malignancy. The genes and pathways identified offer insights into biological mechanisms linking both diseases, aiding future screening, prevention and therapeutic efforts to mitigate this growing comorbidity burden.
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Affiliation(s)
- Dengfeng Zhang
- Department of Thoracic Surgery, The Second Hospital of Hebei Medical University, Shijiazhuang, China
| | - Yu zhou
- Department of Thoracic Surgery, Hebei Chest Hospital, Shijiazhuang, China
- Hebei Provincial Key Laboratory of Pulmonary Diseases, Shijiazhuang, China
| | - Tianxing Lu
- Department of Thoracic Surgery, The Second Hospital of Hebei Medical University, Shijiazhuang, China
| | - Jing Li
- Department of Thoracic Surgery, The Second Hospital of Hebei Medical University, Shijiazhuang, China
| | - Longyu Zhu
- Department of Radiotherapy, The Fourth Hospital of Hebei Medical University, Shijiazhuang, China
| | - Shujun Li
- Department of Thoracic Surgery, The Second Hospital of Hebei Medical University, Shijiazhuang, China
| | - Yishuai Li
- Department of Thoracic Surgery, Hebei Chest Hospital, Shijiazhuang, China
- Hebei Provincial Key Laboratory of Pulmonary Diseases, Shijiazhuang, China
| | - Xiaoliang Duan
- Department of Thoracic Surgery, Hebei Chest Hospital, Shijiazhuang, China
- Hebei Provincial Key Laboratory of Pulmonary Diseases, Shijiazhuang, China
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4
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Zhang J, Zhan J, Jin J, Ma C, Zhao R, O'Connell J, Jiang Y, Koelsch BL, Zhang H, Chatterjee N. An ensemble penalized regression method for multi-ancestry polygenic risk prediction. Nat Commun 2024; 15:3238. [PMID: 38622117 DOI: 10.1038/s41467-024-47357-7] [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: 03/21/2023] [Accepted: 03/28/2024] [Indexed: 04/17/2024] Open
Abstract
Great efforts are being made to develop advanced polygenic risk scores (PRS) to improve the prediction of complex traits and diseases. However, most existing PRS are primarily trained on European ancestry populations, limiting their transferability to non-European populations. In this article, we propose a novel method for generating multi-ancestry Polygenic Risk scOres based on enSemble of PEnalized Regression models (PROSPER). PROSPER integrates genome-wide association studies (GWAS) summary statistics from diverse populations to develop ancestry-specific PRS with improved predictive power for minority populations. The method uses a combination ofL 1 (lasso) andL 2 (ridge) penalty functions, a parsimonious specification of the penalty parameters across populations, and an ensemble step to combine PRS generated across different penalty parameters. We evaluate the performance of PROSPER and other existing methods on large-scale simulated and real datasets, including those from 23andMe Inc., the Global Lipids Genetics Consortium, and All of Us. Results show that PROSPER can substantially improve multi-ancestry polygenic prediction compared to alternative methods across a wide variety of genetic architectures. In real data analyses, for example, PROSPER increased out-of-sample prediction R2 for continuous traits by an average of 70% compared to a state-of-the-art Bayesian method (PRS-CSx) in the African ancestry population. Further, PROSPER is computationally highly scalable for the analysis of large SNP contents and many diverse populations.
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Affiliation(s)
- Jingning Zhang
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
| | | | - Jin Jin
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA, USA
| | - Cheng Ma
- Department of Statistics, University of Michigan, Ann Arbor, MI, USA
| | - Ruzhang Zhao
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | | | | | | | - Haoyu Zhang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Nilanjan Chatterjee
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
- Department of Oncology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA.
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5
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Zhang J, Zhan J, Jin J, Ma C, Zhao R, O’Connell J, Jiang Y, Koelsch BL, Zhang H, Chatterjee N. An Ensemble Penalized Regression Method for Multi-ancestry Polygenic Risk Prediction. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.03.15.532652. [PMID: 36993331 PMCID: PMC10055041 DOI: 10.1101/2023.03.15.532652] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 04/30/2023]
Abstract
Great efforts are being made to develop advanced polygenic risk scores (PRS) to improve the prediction of complex traits and diseases. However, most existing PRS are primarily trained on European ancestry populations, limiting their transferability to non-European populations. In this article, we propose a novel method for generating multi-ancestry Polygenic Risk scOres based on enSemble of PEnalized Regression models (PROSPER). PROSPER integrates genome-wide association studies (GWAS) summary statistics from diverse populations to develop ancestry-specific PRS with improved predictive power for minority populations. The method uses a combination of ℒ 1 (lasso) and ℒ 2 (ridge) penalty functions, a parsimonious specification of the penalty parameters across populations, and an ensemble step to combine PRS generated across different penalty parameters. We evaluate the performance of PROSPER and other existing methods on large-scale simulated and real datasets, including those from 23andMe Inc., the Global Lipids Genetics Consortium, and All of Us. Results show that PROSPER can substantially improve multi-ancestry polygenic prediction compared to alternative methods across a wide variety of genetic architectures. In real data analyses, for example, PROSPER increased out-of-sample prediction R2 for continuous traits by an average of 70% compared to a state-of-the-art Bayesian method (PRS-CSx) in the African ancestry population. Further, PROSPER is computationally highly scalable for the analysis of large SNP contents and many diverse populations.
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Affiliation(s)
- Jingning Zhang
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | | | - Jin Jin
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA, USA
| | - Cheng Ma
- Department of Statistics, University of Michigan, Ann Arbor, MI, USA
| | - Ruzhang Zhao
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | | | | | | | | | - Haoyu Zhang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Nilanjan Chatterjee
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Department of Oncology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
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6
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da Silva Rosa SC, Barzegar Behrooz A, Guedes S, Vitorino R, Ghavami S. Prioritization of genes for translation: a computational approach. Expert Rev Proteomics 2024; 21:125-147. [PMID: 38563427 DOI: 10.1080/14789450.2024.2337004] [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: 05/26/2023] [Accepted: 02/21/2024] [Indexed: 04/04/2024]
Abstract
INTRODUCTION Gene identification for genetic diseases is critical for the development of new diagnostic approaches and personalized treatment options. Prioritization of gene translation is an important consideration in the molecular biology field, allowing researchers to focus on the most promising candidates for further investigation. AREAS COVERED In this paper, we discussed different approaches to prioritize genes for translation, including the use of computational tools and machine learning algorithms, as well as experimental techniques such as knockdown and overexpression studies. We also explored the potential biases and limitations of these approaches and proposed strategies to improve the accuracy and reliability of gene prioritization methods. Although numerous computational methods have been developed for this purpose, there is a need for computational methods that incorporate tissue-specific information to enable more accurate prioritization of candidate genes. Such methods should provide tissue-specific predictions, insights into underlying disease mechanisms, and more accurate prioritization of genes. EXPERT OPINION Using advanced computational tools and machine learning algorithms to prioritize genes, we can identify potential targets for therapeutic intervention of complex diseases. This represents an up-and-coming method for drug development and personalized medicine.
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Affiliation(s)
- Simone C da Silva Rosa
- Department of Human Anatomy and Cell Science, Max Rady College of Medicine, Rady Faculty of Health Science, University of Manitoba, Winnipeg, Canada
| | - Amir Barzegar Behrooz
- Department of Human Anatomy and Cell Science, Max Rady College of Medicine, Rady Faculty of Health Science, University of Manitoba, Winnipeg, Canada
- Electrophysiology Research Center, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Sofia Guedes
- LAQV/REQUIMTE, Department of Chemistry, University of Aveiro, Aveiro, Portugal
| | - Rui Vitorino
- LAQV/REQUIMTE, Department of Chemistry, University of Aveiro, Aveiro, Portugal
- Department of Medical Sciences, Institute of Biomedicine-iBiMED, University of Aveiro, Aveiro, Portugal
- UnIC@RISE, Department of Surgery and Physiology, Faculty of Medicine of the University of Porto, Porto, Portugal
| | - Saeid Ghavami
- Department of Human Anatomy and Cell Science, Max Rady College of Medicine, Rady Faculty of Health Science, University of Manitoba, Winnipeg, Canada
- Faculty of Medicine in Zabrze, Academia of Silesia, Katowice, Poland
- Research Institute of Oncology and Hematology, Cancer Care Manitoba, University of Manitoba, Winnipeg, Canada
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7
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He Z, Wang R, Song C, Liu J, Chen R, Zheng M, Liu W, Jiang G, Mao W. Exploring the causal relationship between immune cells and idiopathic pulmonary fibrosis: a bi-directional Mendelian randomization study. BMC Pulm Med 2024; 24:145. [PMID: 38509507 PMCID: PMC10956372 DOI: 10.1186/s12890-024-02942-w] [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: 11/16/2023] [Accepted: 03/01/2024] [Indexed: 03/22/2024] Open
Abstract
BACKGROUND The potential pathogenic mechanism of idiopathic pulmonary fibrosis is widely recognized to involve immune dysregulation. However, the current pool of studies has yet to establish a unanimous agreement regarding the correlation between various types of immune cells and IPF. METHODS By conducting a two-sample Mendelian randomization analysis using publicly available genetic data, the study examined the causal relationship between IPF and 731 immune cells. To ensure the reliability of the results, combined sensitivity analyses and inverse Mendelian analyses were conducted. Moreover, within subgroups, multivariate Mendelian randomization analyses were utilized to investigate the autonomous causal connection between immune cell characteristics and IPF. RESULTS After adjusting for false discovery rate, it was discovered that 20 immunophenotypes exhibited a significant association with IPF. After subgrouping for multivariate Mendelian randomization analysis, there were six immunophenotypes that remained significantly associated with IPF. These included CD33 + HLA DR + CD14dim (OR = 0.96, 95% CI 0.93-0.99, P = 0.033), HLA DR + NK (OR = 0.92, 95% CI 0.85-0.98, P = 0.017), CD39 + CD8 + T cell %T cell (OR = 0.93, 95% CI 0.88-0.99, P = 0.024), CD3 on activated & secreting Treg (OR = 0.91, 95% CI 0.84-0.98, P = 0.026), PDL-1 on CD14- CD16 + monocyte (OR = 0.89, 95% CI 0.84-0.95, P = 8 × 10-4), and CD45 on CD33 + HLA DR + CD14- (OR = 1.08, 95% CI 1.01-1.15, P = 0.011). CONCLUSION Our study reveals a noteworthy association between IPF and various immune cells, providing valuable insights for clinical research and aiding the advancement of immunologically-based therapeutic strategies.
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Affiliation(s)
- Zhao He
- Department of Thoracic Surgery, The Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi People's Hospital, Wuxi Medical Center, Nanjing Medical University, No. 299 Qingyang Rd, Wuxi, 214023, China
| | - Ruixin Wang
- Department of Thoracic Surgery, The Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi People's Hospital, Wuxi Medical Center, Nanjing Medical University, No. 299 Qingyang Rd, Wuxi, 214023, China
| | - Chenghu Song
- Department of Thoracic Surgery, The Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi People's Hospital, Wuxi Medical Center, Nanjing Medical University, No. 299 Qingyang Rd, Wuxi, 214023, China
| | - Jiwei Liu
- Department of Thoracic Surgery, The Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi People's Hospital, Wuxi Medical Center, Nanjing Medical University, No. 299 Qingyang Rd, Wuxi, 214023, China
| | - Ruo Chen
- Department of Thoracic Surgery, The Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi People's Hospital, Wuxi Medical Center, Nanjing Medical University, No. 299 Qingyang Rd, Wuxi, 214023, China
| | - Mingfeng Zheng
- Department of Thoracic Surgery, The Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi People's Hospital, Wuxi Medical Center, Nanjing Medical University, No. 299 Qingyang Rd, Wuxi, 214023, China
| | - Weici Liu
- Department of Thoracic Surgery, The Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi People's Hospital, Wuxi Medical Center, Nanjing Medical University, No. 299 Qingyang Rd, Wuxi, 214023, China.
| | - Guanyu Jiang
- Department of Thoracic Surgery, The Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi People's Hospital, Wuxi Medical Center, Nanjing Medical University, No. 299 Qingyang Rd, Wuxi, 214023, China.
| | - Wenjun Mao
- Department of Thoracic Surgery, The Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi People's Hospital, Wuxi Medical Center, Nanjing Medical University, No. 299 Qingyang Rd, Wuxi, 214023, China.
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8
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Sayers I, John C, Chen J, Hall IP. Genetics of chronic respiratory disease. Nat Rev Genet 2024:10.1038/s41576-024-00695-0. [PMID: 38448562 DOI: 10.1038/s41576-024-00695-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/19/2024] [Indexed: 03/08/2024]
Abstract
Chronic respiratory diseases, such as chronic obstructive pulmonary disease (COPD), asthma and interstitial lung diseases are frequently occurring disorders with a polygenic basis that account for a large global burden of morbidity and mortality. Recent large-scale genetic epidemiology studies have identified associations between genetic variation and individual respiratory diseases and linked specific genetic variants to quantitative traits related to lung function. These associations have improved our understanding of the genetic basis and mechanisms underlying common lung diseases. Moreover, examining the overlap between genetic associations of different respiratory conditions, along with evidence for gene-environment interactions, has yielded additional biological insights into affected molecular pathways. This genetic information could inform the assessment of respiratory disease risk and contribute to stratified treatment approaches.
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Affiliation(s)
- Ian Sayers
- NIHR Nottingham Biomedical Research Centre, University of Nottingham, University Park, Nottingham, UK
- Biodiscovery Institute, School of Medicine, University of Nottingham, University Park, Nottingham, UK
| | - Catherine John
- University of Leicester, Leicester, UK
- University Hospitals of Leicester, Leicester, UK
| | - Jing Chen
- University of Leicester, Leicester, UK
| | - Ian P Hall
- NIHR Nottingham Biomedical Research Centre, University of Nottingham, University Park, Nottingham, UK.
- Biodiscovery Institute, School of Medicine, University of Nottingham, University Park, Nottingham, UK.
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9
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Leavy OC, Goemans AF, Stockwell AD, Allen RJ, Guillen-Guio B, Hernandez-Beeftink T, Adegunsoye A, Booth HL, Cullinan P, Fahy WA, Fingerlin TE, Virk HS, Hall IP, Hart SP, Hill MR, Hirani N, Hubbard RB, Kaminski N, Ma SF, McAnulty RJ, Sheng XR, Millar AB, Molina-Molina M, Navaratnam V, Neighbors M, Parfrey H, Saini G, Sayers I, Strek ME, Tobin MD, Whyte MK, Zhang Y, Maher TM, Molyneaux PL, Oldham JM, Yaspan BL, Flores C, Martinez F, Reynolds CJ, Schwartz DA, Noth I, Jenkins RG, Wain LV. Genome-wide SNP-sex interaction analysis of susceptibility to idiopathic pulmonary fibrosis. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.01.12.24301204. [PMID: 38293162 PMCID: PMC10827242 DOI: 10.1101/2024.01.12.24301204] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2024]
Abstract
Background Idiopathic pulmonary fibrosis (IPF) is a chronic lung condition that is more prevalent in males than females. The reasons for this are not fully understood, with differing environmental exposures due to historically sex-biased occupations, or diagnostic bias, being possible explanations. To date, over 20 independent genetic variants have been identified to be associated with IPF susceptibility, but these have been discovered when combining males and females. Our aim was to test for the presence of sex-specific associations with IPF susceptibility and assess whether there is a need to consider sex-specific effects when evaluating genetic risk in clinical prediction models for IPF. Methods We performed genome-wide single nucleotide polymorphism (SNP)-by-sex interaction studies of IPF risk in six independent IPF case-control studies and combined them using inverse-variance weighted fixed effect meta-analysis. In total, 4,561 cases (1,280 females and 2,281 males) and 23,500 controls (8,360 females and 14,528 males) of European genetic ancestry were analysed. We used polygenic risk scores (PRS) to assess differences in genetic risk prediction between males and females. Findings Three independent genetic association signals were identified. All showed a consistent direction of effect across all individual IPF studies and an opposite direction of effect in IPF susceptibility between females and males. None had been previously identified in IPF susceptibility genome-wide association studies (GWAS). The predictive accuracy of the PRSs were similar between males and females, regardless of whether using combined or sex-specific GWAS results. Interpretation We prioritised three genetic variants whose effect on IPF risk may be modified by sex, however these require further study. We found no evidence that the predictive accuracy of common SNP-based PRSs varies significantly between males and females.
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Affiliation(s)
- Olivia C Leavy
- Department of Population Health Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Leicester, UK
| | - Anne F Goemans
- Department of Population Health Sciences, University of Leicester, Leicester, UK
| | | | - Richard J Allen
- Department of Population Health Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Leicester, UK
| | - Beatriz Guillen-Guio
- Department of Population Health Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Leicester, UK
| | - Tamara Hernandez-Beeftink
- Department of Population Health Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Leicester, UK
| | | | | | | | | | | | | | - Ian P Hall
- University of Nottingham, Nottingham, UK
- National Institute for Health Research, Nottingham Biomedical Research Centre, Nottingham, UK
| | | | | | | | - Richard B Hubbard
- University of Nottingham, Nottingham, UK
- National Institute for Health Research, Nottingham Biomedical Research Centre, Nottingham, UK
| | | | | | | | | | | | - Maria Molina-Molina
- Servei de Pneumologia, Laboratori de Pneumologia Experimental, Instituto de Investigación Biomédica de Bellvitge (IDIBELL), Barcelona, Spain
- Campus de Bellvitge, Universitat de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Instituto de Salud Carlos III, Madrid, Spain
| | - Vidya Navaratnam
- Department of Respiratory Medicine, Sir Charles Gardiner Hospital, Perth, Australia
- Centre for Respiratory Research, University of Western Australia, Perth, Australia
| | | | - Helen Parfrey
- Royal Papworth Hospital NHS Foundation Trust, Cambridge, UK
| | | | - Ian Sayers
- Centre for Respiratory Research, NIHR Nottingham Biomedical Research Centre, School of Medicine, Biodiscovery Institute, University of Nottingham, Nottingham, UK
| | | | - Martin D Tobin
- Department of Population Health Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Leicester, UK
| | | | | | - Toby M Maher
- NIHR Imperial Biomedical Research Unit, National Heart and Lung Institute, Imperial College London, London, UK
- Division of Pulmonary and Critical Care Medicine, University of Southern California, Los Angeles, USA
| | - Philip L Molyneaux
- National Institute for Health Research Respiratory Clinical Research Facility, Royal Brompton Hospital, London, UK
- NIHR Imperial Biomedical Research Unit, National Heart and Lung Institute, Imperial College London, London, UK
| | | | | | - Carlos Flores
- Research Unit, Hospital Universitario Nuestra Señora de Candelaria, Santa Cruz de Tenerife, Spain
- Genomics Division, Instituto Tecnologico y de Energias Renovables, Santa Cruz de Tenerife, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Instituto de Salud Carlos III, Madrid, Spain
- Facultad de Ciencias de la Salud, Universidad Fernando Pessoa Canarias, Las Palmas de Gran Canaria, Spain
| | | | | | | | - Imre Noth
- University of Virginia, Virginia, USA
| | - R Gisli Jenkins
- NIHR Imperial Biomedical Research Unit, National Heart and Lung Institute, Imperial College London, London, UK
| | - Louise V Wain
- Department of Population Health Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Leicester, UK
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10
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Guillen-Guio B, Paynton ML, Allen RJ, Chin DP, Donoghue LJ, Stockwell A, Leavy OC, Hernandez-Beeftink T, Reynolds C, Cullinan P, Martinez F, Booth HL, Fahy WA, Hall IP, Hart SP, Hill MR, Hirani N, Hubbard RB, McAnulty RJ, Millar AB, Navaratnam V, Oballa E, Parfrey H, Saini G, Sayers I, Tobin MD, Whyte MK, Adegunsoye A, Kaminski N, Ma SF, Strek ME, Zhang Y, Fingerlin TE, Molina-Molina M, Neighbors M, Sheng XR, Oldham JM, Maher TM, Molyneaux PL, Flores C, Noth I, Schwartz DA, Yaspan BL, Jenkins RG, Wain LV, Hollox EJ. Association study of human leukocyte antigen variants and idiopathic pulmonary fibrosis. ERJ Open Res 2024; 10:00553-2023. [PMID: 38375425 PMCID: PMC10875457 DOI: 10.1183/23120541.00553-2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Accepted: 11/05/2023] [Indexed: 02/21/2024] Open
Abstract
Introduction Idiopathic pulmonary fibrosis (IPF) is a chronic interstitial pneumonia marked by progressive lung fibrosis and a poor prognosis. Recent studies have highlighted the potential role of infection in the pathogenesis of IPF, and a prior association of the HLA-DQB1 gene with idiopathic fibrotic interstitial pneumonia (including IPF) has been reported. Owing to the important role that the human leukocyte antigen (HLA) region plays in the immune response, here we evaluated if HLA genetic variation was associated specifically with IPF risk. Methods We performed a meta-analysis of associations of the HLA region with IPF risk in individuals of European ancestry from seven independent case-control studies of IPF (comprising 5159 cases and 27 459 controls, including a prior study of fibrotic interstitial pneumonia). Single nucleotide polymorphisms, classical HLA alleles and amino acids were analysed and signals meeting a region-wide association threshold of p<4.5×10-4 and a posterior probability of replication >90% were considered significant. We sought to replicate the previously reported HLA-DQB1 association in the subset of studies independent of the original report. Results The meta-analysis of all seven studies identified four significant independent single nucleotide polymorphisms associated with IPF risk. However, none met the posterior probability for replication criterion. The HLA-DQB1 association was not replicated in the independent IPF studies. Conclusion Variation in the HLA region was not consistently associated with risk in studies of IPF. However, this does not preclude the possibility that other genomic regions linked to the immune response may be involved in the aetiology of IPF.
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Affiliation(s)
- Beatriz Guillen-Guio
- Department of Population Health Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Leicester, UK
- Joint first authors
| | - Megan L. Paynton
- Department of Population Health Sciences, University of Leicester, Leicester, UK
- Joint first authors
| | - Richard J. Allen
- Department of Population Health Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Leicester, UK
| | - Daniel P.W. Chin
- Department of Population Health Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Leicester, UK
| | | | | | - Olivia C. Leavy
- Department of Population Health Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Leicester, UK
| | - Tamara Hernandez-Beeftink
- Department of Population Health Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Leicester, UK
| | - Carl Reynolds
- National Heart & Lung Institute, Imperial College London, London, UK
| | - Paul Cullinan
- National Heart & Lung Institute, Imperial College London, London, UK
| | | | - Helen L. Booth
- University College Hospital, University College London, London, UK
| | | | - Ian P. Hall
- School of Medicine, University of Nottingham, Nottingham, UK
- National Institute for Health Research, Nottingham Biomedical Research Centre, Nottingham, UK
| | - Simon P. Hart
- Hull York Medical School, University of Hull, Hull, UK
| | - Mike R. Hill
- MRC Population Health Unit, University of Oxford, Oxford, UK
| | - Nik Hirani
- Centre for Inflammation Research, University of Edinburgh, Edinburgh, UK
| | - Richard B. Hubbard
- School of Medicine, University of Nottingham, Nottingham, UK
- National Institute for Health Research, Nottingham Biomedical Research Centre, Nottingham, UK
| | | | - Ann B. Millar
- Bristol Medical School, University of Bristol, Bristol, UK
| | - Vidya Navaratnam
- Division of Epidemiology and Public Health, University of Nottingham, Nottingham, UK
- National Institute for Health Research, Nottingham Biomedical Research Centre, Nottingham University Hospitals NHS Trust, Nottingham, UK
- Queensland Lung Transplant Service, The Prince Charles Hospital, Brisbane, QLD, Australia
| | | | - Helen Parfrey
- Royal Papworth Hospital NHS Foundation Trust, Cambridge, UK
| | - Gauri Saini
- School of Medicine, University of Nottingham, Nottingham, UK
| | - Ian Sayers
- Centre for Respiratory Research, NIHR Nottingham Biomedical Research Centre, School of Medicine, Biodiscovery Institute, University of Nottingham, Nottingham, UK
| | - Martin D. Tobin
- Department of Population Health Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Leicester, UK
| | - Moira K.B. Whyte
- Centre for Inflammation Research, University of Edinburgh, Edinburgh, UK
| | | | - Naftali Kaminski
- Pulmonary, Critical Care and Sleep Medicine, Yale School of Medicine, New Haven, CT, USA
| | - Shwu-Fan Ma
- Department of Medicine, University of Virginia, Charlottesville, VA, USA
| | - Mary E. Strek
- Department of Medicine, University of Chicago, Chicago, IL, USA
| | - Yingze Zhang
- Division of Pulmonary, Allergy, Critical Care, and Sleep Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Tasha E. Fingerlin
- Department of Immunology and Genomic Medicine, National Jewish Health, Denver, CO, USA
| | - Maria Molina-Molina
- Servei de Pneumologia, Laboratori de Pneumologia Experimental, Instituto de Investigación Biomédica de Bellvitge (IDIBELL), Barcelona, Spain
- Campus de Bellvitge, Universitat de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Instituto de Salud Carlos III, Madrid, Spain
| | | | | | - Justin M. Oldham
- Division of Pulmonary and Critical Care Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Toby M. Maher
- National Heart and Lung Institute, Imperial College London, London, UK
- Division of Pulmonary and Critical Care Medicine, University of Southern California, Los Angeles, USA
| | - Philip L. Molyneaux
- National Heart and Lung Institute, Imperial College London, London, UK
- Royal Brompton and Harefield Hospitals, Guy's and St Thomas’ NHS Foundation Trust, London, UK
| | - Carlos Flores
- Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Instituto de Salud Carlos III, Madrid, Spain
- Research Unit, Hospital Universitario Nuestra Señora de Candelaria, Santa Cruz de Tenerife, Spain
- Genomics Division, Instituto Tecnologico y de Energias Renovables, Santa Cruz de Tenerife, Spain
- Facultad de Ciencias de la Salud, Universidad Fernando Pessoa Canarias, Las Palmas de Gran Canaria, Spain
| | - Imre Noth
- Department of Medicine, University of Virginia, Charlottesville, VA, USA
| | | | | | - R. Gisli Jenkins
- National Heart and Lung Institute, Imperial College London, London, UK
| | - Louise V. Wain
- Department of Population Health Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Leicester, UK
- Joint senior authors
| | - Edward J. Hollox
- Department of Genetics and Genome Biology, University of Leicester, Leicester, UK
- Joint senior authors
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11
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Hollmén M, Laaka A, Partanen JJ, Koskela J, Sutinen E, Kaarteenaho R, Ainola M, Myllärniemi M. KIF15 missense variant is associated with the early onset of idiopathic pulmonary fibrosis. Respir Res 2023; 24:240. [PMID: 37777755 PMCID: PMC10543873 DOI: 10.1186/s12931-023-02540-0] [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: 06/13/2023] [Accepted: 09/15/2023] [Indexed: 10/02/2023] Open
Abstract
BACKGROUND Idiopathic pulmonary fibrosis (IPF) has an unknown aetiology and limited treatment options. A recent meta-analysis identified three novel causal variants in the TERT, SPDL1, and KIF15 genes. This observational study aimed to investigate whether the aforementioned variants cause clinical phenotypes in a well-characterised IPF cohort. METHODS The study consisted of 138 patients with IPF who were diagnosed and treated at the Helsinki University Hospital and genotyped in the FinnGen FinnIPF study. Data on > 25 clinical parameters were collected by two pulmonologists who were blinded to the genetic data for patients with TERT loss of function and missense variants, SPDL1 and KIF15 missense variants, and a MUC5B variant commonly present in patients with IPF, or no variants were separately analysed. RESULTS The KIF15 missense variant is associated with the early onset of the disease, leading to progression to early-age transplantation or death. In patients with the KIF15 variant, the median age at diagnosis was 54.0 years (36.5-69.5 years) compared with 72.0 years (65.8-75.3 years) in the other patients (P = 0.023). The proportion of KIF15 variant carriers was 9- or 3.6-fold higher in patients aged < 55 or 65 years, respectively. The variants for TERT and MUC5B had similar effects on the patient's clinical course, as previously described. No distinct phenotypes were observed in patients with the SPDL1 variant. CONCLUSIONS Our study indicated the potential of KIF15 to be used in the genetic diagnostics of IPF. Further studies are needed to elucidate the biological mechanisms of KIF15 in IPF.
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Affiliation(s)
- Maria Hollmén
- Individrug, Heart and Lung Centre, The University of Helsinki and Helsinki University Hospital, Research Programs Unit, Helsinki, Finland
| | - Atte Laaka
- Individrug, Heart and Lung Centre, The University of Helsinki and Helsinki University Hospital, Research Programs Unit, Helsinki, Finland
| | - Juulia J. Partanen
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Jukka Koskela
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Eva Sutinen
- Individrug, Heart and Lung Centre, The University of Helsinki and Helsinki University Hospital, Research Programs Unit, Helsinki, Finland
| | - Riitta Kaarteenaho
- Research Unit of Biomedicine and Internal Medicine, University of Oulu and Oulu University Hospital, Oulu, Finland
| | - Mari Ainola
- Individrug, Heart and Lung Centre, The University of Helsinki and Helsinki University Hospital, Research Programs Unit, Helsinki, Finland
| | - Marjukka Myllärniemi
- Individrug, Heart and Lung Centre, The University of Helsinki and Helsinki University Hospital, Research Programs Unit, Helsinki, Finland
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12
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Zhang C, Zhang Y, Zhang Y, Zhao H. Benchmarking of local genetic correlation estimation methods using summary statistics from genome-wide association studies. Brief Bioinform 2023; 24:bbad407. [PMID: 37974509 PMCID: PMC10654488 DOI: 10.1093/bib/bbad407] [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: 03/29/2023] [Revised: 10/06/2023] [Accepted: 10/24/2023] [Indexed: 11/19/2023] Open
Abstract
Local genetic correlation evaluates the correlation of additive genetic effects between different traits across the same genetic variants at a genomic locus. It has been proven informative for understanding the genetic similarities of complex traits beyond that captured by global genetic correlation calculated across the whole genome. Several summary-statistics-based approaches have been developed for estimating local genetic correlation, including $\rho$-hess, SUPERGNOVA and LAVA. However, there has not been a comprehensive evaluation of these methods to offer practical guidelines on the choices of these methods. In this study, we conduct benchmark comparisons of the performance of these three methods through extensive simulation and real data analyses. We focus on two technical difficulties in estimating local genetic correlation: sample overlaps across traits and local linkage disequilibrium (LD) estimates when only the external reference panels are available. Our simulations suggest the likelihood of incorrectly identifying correlated regions and local correlation estimation accuracy are highly dependent on the estimation of the local LD matrix. These observations are corroborated by real data analyses of 31 complex traits. Overall, our findings illuminate the distinct results yielded by different methods applied in post-genome-wide association studies (post-GWAS) local correlation studies. We underscore the sensitivity of local genetic correlation estimates and inferences to the precision of local LD estimation. These observations accentuate the vital need for ongoing refinement in methodologies.
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Affiliation(s)
- Chi Zhang
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, United States
| | - Yiliang Zhang
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, United States
| | - Yunxuan Zhang
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, United States
| | - Hongyu Zhao
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, United States
- Program of Computational Biology and Bioinformatics, Yale University, New Haven, CT, United States
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13
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Spagnolo P, Lee JS. Recent advances in the genetics of idiopathic pulmonary fibrosis. Curr Opin Pulm Med 2023; 29:399-405. [PMID: 37410458 PMCID: PMC10470435 DOI: 10.1097/mcp.0000000000000989] [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] [Indexed: 07/07/2023]
Abstract
PURPOSE OF REVIEW Genetics contributes substantially to the susceptibility to idiopathic pulmonary fibrosis (IPF). Genetic studies in sporadic and familial disease have identified several IPF-associated variants, mainly in telomere-related and surfactant protein genes.Here, we review the most recent literature on genetics of IPF and discuss how it may contribute to disease pathogenesis. RECENT FINDINGS Recent studies implicate genes involved in telomere maintenance, host defence, cell growth, mammalian target of rapamycin signalling, cell-cell adhesion, regulation of TGF-β signalling and spindle assembly as biological processes involved in the pathogenesis of IPF. Both common and rare genetic variants contribute to the overall risk of IPF; however, while common variants (i.e. polymorphisms) account for most of the heritability of sporadic disease, rare variants (i.e. mutations), mainly in telomere-related genes, are the main contributors to the heritability of familial disease. Genetic factors are likely to also influence disease behaviour and prognosis. Finally, recent data suggest that IPF shares genetic associations - and probably some pathogenetic mechanisms - with other fibrotic lung diseases. SUMMARY Common and rare genetic variants are associated with susceptibility and prognosis of IPF. However, many of the reported variants fall in noncoding regions of the genome and their relevance to disease pathobiology remains to be elucidated.
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Affiliation(s)
- Paolo Spagnolo
- Respiratory Disease Unit, Department of Cardiac Thoracic, Vascular Sciences and Public Health, University of Padova, Padova, Italy
| | - Joyce S Lee
- University of Colorado Denver, Anschutz Medical Campus, Aurora, Colorado, USA
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14
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Stanel SC, Callum J, Rivera-Ortega P. Genetic and environmental factors in interstitial lung diseases: current and future perspectives on early diagnosis of high-risk cohorts. Front Med (Lausanne) 2023; 10:1232655. [PMID: 37601795 PMCID: PMC10435297 DOI: 10.3389/fmed.2023.1232655] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Accepted: 07/24/2023] [Indexed: 08/22/2023] Open
Abstract
Within the wide scope of interstitial lung diseases (ILDs), familial pulmonary fibrosis (FPF) is being increasingly recognized as a specific entity, with earlier onset, faster progression, and suboptimal responses to immunosuppression. FPF is linked to heritable pathogenic variants in telomere-related genes (TRGs), surfactant-related genes (SRGs), telomere shortening (TS), and early cellular senescence. Telomere abnormalities have also been identified in some sporadic cases of fibrotic ILD. Air pollution and other environmental exposures carry additive risk to genetic predisposition in pulmonary fibrosis. We provide a perspective on how these features impact on screening strategies for relatives of FPF patients, interstitial lung abnormalities, ILD multi-disciplinary team (MDT) discussion, and disparities and barriers to genomic testing. We also describe our experience with establishing a familial interstitial pneumonia (FIP) clinic and provide guidance on how to identify patients with telomere dysfunction who would benefit most from genomic testing.
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Affiliation(s)
- Stefan Cristian Stanel
- Interstitial Lung Disease Unit, Wythenshawe Hospital, Manchester University NHS Foundation Trust, Manchester, United Kingdom
- Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom
| | - Jack Callum
- Interstitial Lung Disease Unit, Wythenshawe Hospital, Manchester University NHS Foundation Trust, Manchester, United Kingdom
| | - Pilar Rivera-Ortega
- Interstitial Lung Disease Unit, Wythenshawe Hospital, Manchester University NHS Foundation Trust, Manchester, United Kingdom
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15
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Guillen-Guio B, Paynton ML, Allen RJ, Chin DP, Donoghue LJ, Stockwell A, Leavy OC, Hernandez-Beeftink T, Reynolds C, Cullinan P, Martinez F, Booth HL, Fahy WA, Hall IP, Hart SP, Hill MR, Hirani N, Hubbard RB, McAnulty RJ, Millar AB, Navaratnam V, Oballa E, Parfrey H, Saini G, Sayers I, Tobin MD, Whyte MKB, Adegunsoye A, Kaminski N, Shwu-Fan M, Strek ME, Zhang Y, Fingerlin TE, Molina-Molina M, Neighbors M, Sheng XR, Oldham JM, Maher TM, Molyneaux PL, Flores C, Noth I, Schwartz DA, Yaspan BL, Jenkins RG, Wain LV, Hollox EJ. Association study of human leukocyte antigen (HLA) variants and idiopathic pulmonary fibrosis. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.07.20.23292940. [PMID: 37546732 PMCID: PMC10402235 DOI: 10.1101/2023.07.20.23292940] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
Introduction Idiopathic pulmonary fibrosis (IPF) is a chronic interstitial pneumonia marked by progressive lung fibrosis and a poor prognosis. Recent studies have highlighted the potential role of infection in the pathogenesis of IPF and a prior association of the HLA-DQB1 gene with idiopathic fibrotic interstitial pneumonia (including IPF) has been reported. Due to the important role that the Human Leukocyte Antigen (HLA) region plays in the immune response, here we evaluated if HLA genetic variation was associated specifically with IPF risk. Methods We performed a meta-analysis of associations of the HLA region with IPF risk in individuals of European ancestry from seven independent case-control studies of IPF (comprising a total of 5,159 cases and 27,459 controls, including the prior study of fibrotic interstitial pneumonia). Single nucleotide polymorphisms, classical HLA alleles and amino acids were analysed and signals meeting a region-wide association threshold p<4.5×10-4 and a posterior probability of replication >90% were considered significant. We sought to replicate the previously reported HLA-DQB1 association in the subset of studies independent of the original report. Results The meta-analysis of all seven studies identified four significant independent single nucleotide polymorphisms associated with IPF risk. However, none met the posterior probability for replication criterion. The HLA-DQB1 association was not replicated in the independent IPF studies. Conclusion Variation in the HLA region was not consistently associated with risk in studies of IPF. However, this does not preclude the possibility that other genomic regions linked to the immune response may be involved in the aetiology of IPF.
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Affiliation(s)
- Beatriz Guillen-Guio
- Department of Population Health Sciences, University of Leicester, UK
- NIHR Leicester Biomedical Research Centre, Leicester, UK
| | - Megan L. Paynton
- Department of Population Health Sciences, University of Leicester, UK
| | - Richard J. Allen
- Department of Population Health Sciences, University of Leicester, UK
- NIHR Leicester Biomedical Research Centre, Leicester, UK
| | - Daniel P.W. Chin
- Department of Population Health Sciences, University of Leicester, UK
- NIHR Leicester Biomedical Research Centre, Leicester, UK
| | | | | | - Olivia C. Leavy
- Department of Population Health Sciences, University of Leicester, UK
- NIHR Leicester Biomedical Research Centre, Leicester, UK
| | - Tamara Hernandez-Beeftink
- Department of Population Health Sciences, University of Leicester, UK
- NIHR Leicester Biomedical Research Centre, Leicester, UK
| | | | | | | | | | | | | | - Ian P. Hall
- University of Nottingham, Nottingham, UK
- National Institute for Health Research, Nottingham Biomedical Research Centre, Nottingham, UK
| | | | | | | | - Richard B. Hubbard
- University of Nottingham, Nottingham, UK
- National Institute for Health Research, Nottingham Biomedical Research Centre, Nottingham, UK
| | | | | | - Vidya Navaratnam
- Division of Epidemiology and Public Health, University of Nottingham, Nottingham, UK
- National Institute for Health Research, Nottingham Biomedical Research Centre, Nottingham University Hospitals NHS Trust, Nottingham, UK
- Queensland Lung Transplant Service, The Prince Charles Hospital, Brisbane, QLD, Australia
| | | | - Helen Parfrey
- Royal Papworth Hospital NHS Foundation Trust, Cambridge, UK
| | | | - Ian Sayers
- Centre for Respiratory Research, NIHR Nottingham Biomedical Research Centre, School of Medicine, Biodiscovery Institute, University of Nottingham, Nottingham, UK
| | - Martin D. Tobin
- Department of Population Health Sciences, University of Leicester, UK
- NIHR Leicester Biomedical Research Centre, Leicester, UK
| | | | | | | | | | | | | | | | - Maria Molina-Molina
- Servei de Pneumologia, Laboratori de Pneumologia Experimental, Instituto de Investigación Biomédica de Bellvitge (IDIBELL), Barcelona, Spain
- Campus de Bellvitge, Universitat de Barcelona, Barcelona, Spain
- Centro de Investigacion Biomedica en Red de Enfermedades Respiratorias (CIBERES), Instituto de Salud Carlos III, Madrid, Spain
| | | | | | | | - Toby M. Maher
- National Heart and Lung Institute, Imperial College London, London, UK
- Division of Pulmonary and Critical Care Medicine, University of Southern California, Los Angeles, USA
| | - Philip L. Molyneaux
- National Heart and Lung Institute, Imperial College London, London, UK
- Royal Brompton and Harefield Hospitals, Guy’s and St Thomas’ NHS Foundation Trust, London, UK
| | - Carlos Flores
- Centro de Investigacion Biomedica en Red de Enfermedades Respiratorias (CIBERES), Instituto de Salud Carlos III, Madrid, Spain
- Research Unit, Hospital Universitario Nuestra Señora de Candelaria, Santa Cruz de Tenerife, Spain
- Genomics Division, Instituto Tecnologico y de Energias Renovables, Santa Cruz de Tenerife, Spain
- Facultad de Ciencias de la Salud, Universidad Fernando Pessoa Canarias, Las Palmas de Gran Canaria, Spain
| | - Imre Noth
- University of Virginia, Virginia, USA
| | | | | | - R. Gisli Jenkins
- National Heart and Lung Institute, Imperial College London, London, UK
| | - Louise V. Wain
- Department of Population Health Sciences, University of Leicester, UK
- NIHR Leicester Biomedical Research Centre, Leicester, UK
| | - Edward J. Hollox
- Department of Genetics and Genome Biology, University of Leicester, UK
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16
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Moss BJ, Rosas IO. Defining the Genetic Landscape of Idiopathic Pulmonary Fibrosis: Role of Common and Rare Variants. Am J Respir Crit Care Med 2023; 207:1118-1120. [PMID: 36796091 PMCID: PMC10161759 DOI: 10.1164/rccm.202301-0177ed] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/18/2023] Open
Affiliation(s)
- Benjamin J Moss
- Department of Medicine, Pulmonary, Critical Care, and Sleep Medicine Baylor College of Medicine Houston, Texas
| | - Ivan O Rosas
- Department of Medicine, Pulmonary, Critical Care, and Sleep Medicine Baylor College of Medicine Houston, Texas
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17
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Donoghue LJ, Stockwell AD, Neighbors M, Sheng RX, Prabhakaran R, Wolters PJ, Lancaster LH, Kropski JA, Blackwell TS, McCarthy MI, Yaspan BL. Identification of a Genetic Susceptibility Locus for Idiopathic Pulmonary Fibrosis in the 16p Subtelomere Using Whole-Genome Sequencing. Am J Respir Crit Care Med 2023; 207:941-944. [PMID: 36603154 PMCID: PMC10111979 DOI: 10.1164/rccm.202206-1139le] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023] Open
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18
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Wang Y, Namba S, Lopera E, Kerminen S, Tsuo K, Läll K, Kanai M, Zhou W, Wu KH, Favé MJ, Bhatta L, Awadalla P, Brumpton B, Deelen P, Hveem K, Lo Faro V, Mägi R, Murakami Y, Sanna S, Smoller JW, Uzunovic J, Wolford BN, Willer C, Gamazon ER, Cox NJ, Surakka I, Okada Y, Martin AR, Hirbo J. Global Biobank analyses provide lessons for developing polygenic risk scores across diverse cohorts. CELL GENOMICS 2023; 3:100241. [PMID: 36777179 PMCID: PMC9903818 DOI: 10.1016/j.xgen.2022.100241] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Revised: 08/28/2022] [Accepted: 12/03/2022] [Indexed: 01/06/2023]
Abstract
Polygenic risk scores (PRSs) have been widely explored in precision medicine. However, few studies have thoroughly investigated their best practices in global populations across different diseases. We here utilized data from Global Biobank Meta-analysis Initiative (GBMI) to explore methodological considerations and PRS performance in 9 different biobanks for 14 disease endpoints. Specifically, we constructed PRSs using pruning and thresholding (P + T) and PRS-continuous shrinkage (CS). For both methods, using a European-based linkage disequilibrium (LD) reference panel resulted in comparable or higher prediction accuracy compared with several other non-European-based panels. PRS-CS overall outperformed the classic P + T method, especially for endpoints with higher SNP-based heritability. Notably, prediction accuracy is heterogeneous across endpoints, biobanks, and ancestries, especially for asthma, which has known variation in disease prevalence across populations. Overall, we provide lessons for PRS construction, evaluation, and interpretation using GBMI resources and highlight the importance of best practices for PRS in the biobank-scale genomics era.
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Affiliation(s)
- Ying Wang
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Stanley Center for Psychiatric Research and Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Shinichi Namba
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita 565-0871, Japan
| | - Esteban Lopera
- Department of Genetics, UMCG, University of Groningen, Groningen, the Netherlands
| | - Sini Kerminen
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland
| | - Kristin Tsuo
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Stanley Center for Psychiatric Research and Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Kristi Läll
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Masahiro Kanai
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Stanley Center for Psychiatric Research and Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita 565-0871, Japan
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Wei Zhou
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Stanley Center for Psychiatric Research and Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Kuan-Han Wu
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48103, USA
| | | | - Laxmi Bhatta
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, 7030 Trondheim, Norway
| | - Philip Awadalla
- Ontario Institute for Cancer Research, Toronto, ON, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
| | - Ben Brumpton
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, 7030 Trondheim, Norway
- HUNT Research Centre, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, 7600 Levanger, Norway
- Clinic of Medicine, St. Olav’s Hospital, Trondheim University Hospital, 7030 Trondheim, Norway
| | - Patrick Deelen
- Department of Genetics, UMCG, University of Groningen, Groningen, the Netherlands
- Oncode Institute, Utrecht, the Netherlands
| | - Kristian Hveem
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, 7030 Trondheim, Norway
- HUNT Research Centre, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, 7600 Levanger, Norway
| | - Valeria Lo Faro
- Department of Ophthalmology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
- Department of Clinical Genetics, Amsterdam University Medical Center (AMC), Amsterdam, the Netherlands
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Reedik Mägi
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Yoshinori Murakami
- Division of Molecular Pathology, Institute of Medical Science, the University of Tokyo, Tokyo, Japan
| | - Serena Sanna
- Department of Genetics, UMCG, University of Groningen, Groningen, the Netherlands
- Institute for Genetics and Biomedical Research (IRGB), National Research Council (CNR), 09100 Cagliari, Italy
| | - Jordan W. Smoller
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | | | - Brooke N. Wolford
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48103, USA
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, 7030 Trondheim, Norway
| | - Cristen Willer
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, 7030 Trondheim, Norway
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI 48109, USA
- Department of Biostatistics and Center for Statistical Genetics, and Department of Human Genetics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Eric R. Gamazon
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University School of Medicine, Nashville, TN, USA
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Nancy J. Cox
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University School of Medicine, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Ida Surakka
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI 48109, USA
| | - Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita 565-0871, Japan
- Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC) and Center for Infectious Disease Education and Research (CiDER), Osaka University, Suita 565-0871, Japan
- Department of Genome Informatics, Graduate School of Medicine, the University of Tokyo, Tokyo 113-0033, Japan
| | - Alicia R. Martin
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Stanley Center for Psychiatric Research and Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Jibril Hirbo
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University School of Medicine, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
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19
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Alonso-Gonzalez A, Tosco-Herrera E, Molina-Molina M, Flores C. Idiopathic pulmonary fibrosis and the role of genetics in the era of precision medicine. Front Med (Lausanne) 2023; 10:1152211. [PMID: 37181377 PMCID: PMC10172674 DOI: 10.3389/fmed.2023.1152211] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Accepted: 04/03/2023] [Indexed: 05/16/2023] Open
Abstract
Idiopathic pulmonary fibrosis (IPF) is a chronic, rare progressive lung disease, characterized by lung scarring and the irreversible loss of lung function. Two anti-fibrotic drugs, nintedanib and pirfenidone, have been demonstrated to slow down disease progression, although IPF mortality remains a challenge and the patients die after a few years from diagnosis. Rare pathogenic variants in genes that are involved in the surfactant metabolism and telomere maintenance, among others, have a high penetrance and tend to co-segregate with the disease in families. Common recurrent variants in the population with modest effect sizes have been also associated with the disease risk and progression. Genome-wide association studies (GWAS) support at least 23 genetic risk loci, linking the disease pathogenesis with unexpected molecular pathways including cellular adhesion and signaling, wound healing, barrier function, airway clearance, and innate immunity and host defense, besides the surfactant metabolism and telomere biology. As the cost of high-throughput genomic technologies continuously decreases and new technologies and approaches arise, their widespread use by clinicians and researchers is efficiently contributing to a better understanding of the pathogenesis of progressive pulmonary fibrosis. Here we provide an overview of the genetic factors known to be involved in IPF pathogenesis and discuss how they will continue to further advance in this field. We also discuss how genomic technologies could help to further improve IPF diagnosis and prognosis as well as for assessing genetic risk in unaffected relatives. The development and validation of evidence-based guidelines for genetic-based screening of IPF will allow redefining and classifying this disease relying on molecular characteristics and contribute to the implementation of precision medicine approaches.
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Affiliation(s)
- Aitana Alonso-Gonzalez
- Unidad de Investigación, Hospital Universitario Nuestra Señora de Candelaria, Santa Cruz de Tenerife, Spain
- Universidad de Santiago de Compostela, Santiago de Compostela, Spain
| | - Eva Tosco-Herrera
- Unidad de Investigación, Hospital Universitario Nuestra Señora de Candelaria, Santa Cruz de Tenerife, Spain
| | - Maria Molina-Molina
- Servei de Pneumologia, Laboratori de Pneumologia Experimental, IDIBELL, Barcelona, Spain
- Campus de Bellvitge, Universitat de Barcelona, Barcelona, Spain
- CIBER de Enfermedades Respiratorias, Instituto de Salud Carlos III, Madrid, Spain
| | - Carlos Flores
- Unidad de Investigación, Hospital Universitario Nuestra Señora de Candelaria, Santa Cruz de Tenerife, Spain
- CIBER de Enfermedades Respiratorias, Instituto de Salud Carlos III, Madrid, Spain
- Genomics Division, Instituto Tecnológico y de Energías Renovables (ITER), Santa Cruz de Tenerife, Spain
- Facultad de Ciencias de la Salud, Universidad Fernando Pessoa Canarias, Las Palmas de Gran Canaria, Spain
- *Correspondence: Carlos Flores,
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20
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Kanai M, Elzur R, Zhou W, Daly MJ, Finucane HK. Meta-analysis fine-mapping is often miscalibrated at single-variant resolution. CELL GENOMICS 2022; 2:100210. [PMID: 36643910 PMCID: PMC9839193 DOI: 10.1016/j.xgen.2022.100210] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Meta-analysis is pervasively used to combine multiple genome-wide association studies (GWASs). Fine-mapping of meta-analysis studies is typically performed as in a single-cohort study. Here, we first demonstrate that heterogeneity (e.g., of sample size, phenotyping, imputation) hurts calibration of meta-analysis fine-mapping. We propose a summary statistics-based quality-control (QC) method, suspicious loci analysis of meta-analysis summary statistics (SLALOM), that identifies suspicious loci for meta-analysis fine-mapping by detecting outliers in association statistics. We validate SLALOM in simulations and the GWAS Catalog. Applying SLALOM to 14 meta-analyses from the Global Biobank Meta-analysis Initiative (GBMI), we find that 67% of loci show suspicious patterns that call into question fine-mapping accuracy. These predicted suspicious loci are significantly depleted for having nonsynonymous variants as lead variant (2.7×; Fisher's exact p = 7.3 × 10-4). We find limited evidence of fine-mapping improvement in the GBMI meta-analyses compared with individual biobanks. We urge extreme caution when interpreting fine-mapping results from meta-analysis of heterogeneous cohorts.
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Affiliation(s)
- Masahiro Kanai
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02142, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita 565-0871, Japan
- Corresponding author
| | - Roy Elzur
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02142, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Wei Zhou
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02142, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | | | - Mark J. Daly
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02142, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Hilary K. Finucane
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02142, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Corresponding author
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