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Schöneberg T. Modulating vertebrate physiology by genomic fine-tuning of GPCR functions. Physiol Rev 2025; 105:383-439. [PMID: 39052017 DOI: 10.1152/physrev.00017.2024] [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: 04/22/2024] [Revised: 07/08/2024] [Accepted: 07/20/2024] [Indexed: 07/27/2024] Open
Abstract
G protein-coupled receptors (GPCRs) play a crucial role as membrane receptors, facilitating the communication of eukaryotic species with their environment and regulating cellular and organ interactions. Consequently, GPCRs hold immense potential in contributing to adaptation to ecological niches and responding to environmental shifts. Comparative analyses of vertebrate genomes reveal patterns of GPCR gene loss, expansion, and signatures of selection. Integrating these genomic data with insights from functional analyses of gene variants enables the interpretation of genotype-phenotype correlations. This review underscores the involvement of GPCRs in adaptive processes, presenting numerous examples of how alterations in GPCR functionality influence vertebrate physiology or, conversely, how environmental changes impact GPCR functions. The findings demonstrate that modifications in GPCR function contribute to adapting to aquatic, arid, and nocturnal habitats, influencing camouflage strategies, and specializing in particular dietary preferences. Furthermore, the adaptability of GPCR functions provides an effective mechanism in facilitating past, recent, or ongoing adaptations in animal domestication and human evolution and should be considered in therapeutic strategies and drug development.
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Affiliation(s)
- Torsten Schöneberg
- Rudolf Schönheimer Institute of Biochemistry, Molecular Biochemistry, Medical Faculty, University of Leipzig, Leipzig, Germany
- School of Medicine, University of Global Health Equity, Kigali, Rwanda
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2
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Sayers I, John C, Chen J, Hall IP. Genetics of chronic respiratory disease. Nat Rev Genet 2024; 25:534-547. [PMID: 38448562 DOI: 10.1038/s41576-024-00695-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [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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Lin WD, Liao WL, Chen WC, Liu TY, Chen YC, Tsai FJ. Genome-wide association study identifies novel susceptible loci and evaluation of polygenic risk score for chronic obstructive pulmonary disease in a Taiwanese population. BMC Genomics 2024; 25:607. [PMID: 38886662 PMCID: PMC11184693 DOI: 10.1186/s12864-024-10526-5] [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: 12/09/2023] [Accepted: 06/14/2024] [Indexed: 06/20/2024] Open
Abstract
BACKGROUND Chronic Obstructive Pulmonary Disease (COPD) describes a group of progressive lung diseases causing breathing difficulties. While COPD development typically involves a complex interplay between genetic and environmental factors, genetics play a role in disease susceptibility. This study used genome-wide association studies (GWAS) and polygenic risk score (PRS) to elucidate the genetic basis for COPD in Taiwanese patients. RESULTS GWAS was performed on a Taiwanese COPD case-control cohort with a sample size of 5,442 cases and 17,681 controls. Additionally, the PRS was calculated and assessed in our target groups. GWAS results indicate that although there were no single nucleotide polymorphisms (SNPs) of genome-wide significance, prominent COPD susceptibility loci on or nearby genes such as WWTR1, EXT1, INTU, MAP3K7CL, MAMDC2, BZW1/CLK1, LINC01197, LINC01894, and CFAP95 (C9orf135) were identified, which had not been reported in previous studies. Thirteen susceptibility loci, such as CHRNA4, AFAP1, and DTWD1, previously reported in other populations were replicated and confirmed to be associated with COPD in Taiwanese populations. The PRS was determined in the target groups using the summary statistics from our base group, yielding an effective association with COPD (odds ratio [OR] 1.09, 95% confidence interval [CI] 1.02-1.17, p = 0.011). Furthermore, replication a previous lung function trait PRS model in our target group, showed a significant association of COPD susceptibility with PRS of Forced Expiratory Volume in one second (FEV1)/Forced Vital Capacity (FCV) (OR 0.89, 95% CI 0.83-0.95, p = 0.001). CONCLUSIONS Novel COPD-related genes were identified in the studied Taiwanese population. The PRS model, based on COPD or lung function traits, enables disease risk estimation and enhances prediction before suffering. These results offer new perspectives on the genetics of COPD and serve as a basis for future research.
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Affiliation(s)
- Wei-De Lin
- Department of Medical Research, China Medical University Hospital, Taichung, 404327, Taiwan
- School of Post Baccalaureate Chinese Medicine, China Medical University, Taichung, 404333, Taiwan
| | - Wen-Ling Liao
- Graduate Institute of Integrated Medicine, College of Chinese Medicine, China Medical University, Taichung, 404333, Taiwan
- Center for Personalized Medicine, China Medical University Hospital, Taichung, 404327, Taiwan
| | - Wei-Cheng Chen
- Department of Internal Medicine, Pulmonary and Critical Care Medicine, China Medical University Hospital, Taichung, 404333, Taiwan
- Graduate Institute of Biomedical Sciences, China Medical University, Taichung, 404327, Taiwan
| | - Ting-Yuan Liu
- Department of Medical Research, Million-Person Precision Medicine Initiative, China Medical University Hospital, Taichung, 404327, Taiwan
| | - Yu-Chia Chen
- Department of Medical Research, Million-Person Precision Medicine Initiative, China Medical University Hospital, Taichung, 404327, Taiwan
| | - Fuu-Jen Tsai
- Department of Medical Research, China Medical University Hospital, Taichung, 404327, Taiwan.
- School of Chinese Medicine, China Medical University, Taichung, 404333, Taiwan.
- Division of Genetics and Metabolism, China Medical University Children's Hospital, Taichung, 404327, Taiwan.
- Department of Medical Genetics, China Medical University Hospital, Taichung, 404327, Taiwan.
- Department of Medical Laboratory Science and Biotechnology, Asia University, Taichung, 413305, Taiwan.
- Department of Medical Research, China Medical University Hospital, No. 2, Yude Road, North District, Taichung, 404327, Taiwan.
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Zhu Y, Bai Y, Yan W, Li M, Wu F, Xu M, Wu N, Ge H, Liu Y. A mutation in CCDC91, Homo sapiens coiled-coil domain containing 91 protein, cause autosomal-dominant acrokeratoelastoidosis. Eur J Hum Genet 2024; 32:647-655. [PMID: 38627542 PMCID: PMC11153616 DOI: 10.1038/s41431-024-01573-3] [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: 11/14/2023] [Revised: 01/26/2024] [Accepted: 02/20/2024] [Indexed: 06/07/2024] Open
Abstract
Acrokeratoelastoidosis (AKE) is a rare autosomal dominant hereditary skin disease characterized by small, round-oval, flat-topped keratotic papules on the palms, soles and dorsal aspect of hands or feet. The causative gene for AKE remains unidentified. This study aims to identify the causative gene of AKE and explore the underlying biological mechanisms. A large, three-generation Chinese family exhibiting classic AKE symptoms was identified. A genome-wide linkage analysis and whole-exome sequencing were employed to determine the causative gene. shRNA knockdown in human skin fibroblasts and CRISPR/Cas9 knockout in HEK293T cells were utilized to assess gene functions in the progression of elastic fiber biosynthesis. The linkage analysis identified a susceptibility region between rs7296765 to rs10784618 on chromosome 12. Whole-exome sequencing confirmed a splicing mutation of 1101 + 1 G > A in the CCDC91 gene, resulting in exon 11 skipping and a subsequent 59-amino-acid-residue loss (residues L309-Q367del). Further functional analysis revealed distended Golgi cisternae, cytoplasmic vesicle accumulation, and lysosome presence. Immnunostaining of si-CCDC91-HSF cells demonstrated tropoelastin accumulation in the Golgi and abnormal extracellular aggregates. There are no significant changes in Fibrillin-1 microfibril assembly and lysyl oxidase activity. The findings strongly suggest that the protein product of the CCDC91 gene plays a crucial role in elastin transport. This discovery enhances our understanding of CCDC91's function and broadens the known pathogenic mechanisms of AKE.
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Affiliation(s)
- Yunlu Zhu
- Shanghai Skin Disease Hospital, School of Medicine, Tongji Medical University, Shanghai, China
- Department of Dermatology, Anhui Provincial Children's Hospital, Hefei City, Anhui Province, China
| | - Yun Bai
- Shanghai Skin Disease Hospital, School of Medicine, Tongji Medical University, Shanghai, China
| | - Wannian Yan
- Shanghai Skin Disease Hospital, School of Medicine, Tongji Medical University, Shanghai, China
| | - Ming Li
- Department of Dermatology, Children's Hospital of Fudan University, Shanghai, 200032, China
| | - Fei Wu
- Shanghai Skin Disease Hospital, School of Medicine, Tongji Medical University, Shanghai, China
| | - Mingyuan Xu
- Shanghai Skin Disease Hospital, School of Medicine, Tongji Medical University, Shanghai, China
| | - Nanhui Wu
- Shanghai Skin Disease Hospital, School of Medicine, Tongji Medical University, Shanghai, China
| | - HongSong Ge
- Department of Dermatology, Anhui Provincial Children's Hospital, Hefei City, Anhui Province, China.
| | - Yeqiang Liu
- Shanghai Skin Disease Hospital, School of Medicine, Tongji Medical University, Shanghai, China.
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Lazarev D, Chau G, Bloemendal A, Churchhouse C, Neale BM. GUIDE deconstructs genetic architectures using association studies. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.03.592285. [PMID: 38766146 PMCID: PMC11100597 DOI: 10.1101/2024.05.03.592285] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
Genome-wide association studies have revealed that the genetic architecture of most complex traits is characterized by a large number of distinct effects scattered across the genome. Functional enrichment analyses of these results suggest that the associations for any given complex trait are not purely random. Thus, we set out to leverage the genetic association results from many traits with a view to identifying the set of modules, or latent factors, that mediate these associations. The identification of such modules may aid in disease classification as well as the elucidation of complex disease mechanisms. We propose a method, Genetic Unmixing by Independent Decomposition (GUIDE), to estimate a set of statistically independent latent factors that best express the patterns of association across many traits. The resulting latent factors not only have desirable mathematical properties, such as sparsity and a higher variance explained (for both traits and variants), but are also able to single out and prioritize key biological features or pathophysiological mechanisms underlying a given trait or disease. Moreover, we show that these latent factors can index biological pathways as well as epidemiological and environmental influences that compose the genetic architecture of complex traits.
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Seo J, Gaddis NC, Patchen BK, Xu J, Barr RG, O'Connor G, Manichaikul AW, Gharib SA, Dupuis J, North KE, Cassano PA, Hancock DB. Exploiting meta-analysis of genome-wide interaction with serum 25-hydroxyvitamin D to identify novel genetic loci associated with pulmonary function. Am J Clin Nutr 2024; 119:1227-1237. [PMID: 38484975 PMCID: PMC11130669 DOI: 10.1016/j.ajcnut.2024.03.007] [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: 08/11/2023] [Revised: 02/12/2024] [Accepted: 03/07/2024] [Indexed: 04/01/2024] Open
Abstract
BACKGROUND Higher 25-hydroxyvitamin D (25(OH)D) concentrations in serum has a positive association with pulmonary function. Investigating genome-wide interactions with 25(OH)D may reveal new biological insights into pulmonary function. OBJECTIVES We aimed to identify novel genetic variants associated with pulmonary function by accounting for 25(OH)D interactions. METHODS We included 211,264 participants from the observational United Kingdom Biobank study with pulmonary function tests (PFTs), genome-wide genotypes, and 25(OH)D concentrations from 4 ancestral backgrounds-European, African, East Asian, and South Asian. Among PFTs, we focused on forced expiratory volume in the first second (FEV1) and forced vital capacity (FVC) because both were previously associated with 25(OH)D. We performed genome-wide association study (GWAS) analyses that accounted for variant×25(OH)D interaction using the joint 2 degree-of-freedom (2df) method, stratified by participants' smoking history and ancestry, and meta-analyzed results. We evaluated interaction effects to determine how variant-PFT associations were modified by 25(OH)D concentrations and conducted pathway enrichment analysis to examine the biological relevance of our findings. RESULTS Our GWAS meta-analyses, accounting for interaction with 25(OH)D, revealed 30 genetic variants significantly associated with FEV1 or FVC (P2df <5.00×10-8) that were not previously reported for PFT-related traits. These novel variant signals were enriched in lung function-relevant pathways, including the p38 MAPK pathway. Among variants with genome-wide-significant 2df results, smoking-stratified meta-analyses identified 5 variants with 25(OH)D interactions that influenced FEV1 in both smoking groups (never smokers P1df interaction<2.65×10-4; ever smokers P1df interaction<1.71×10-5); rs3130553, rs2894186, rs79277477, and rs3130929 associations were only evident in never smokers, and the rs4678408 association was only found in ever smokers. CONCLUSION Genetic variant associations with lung function can be modified by 25(OH)D, and smoking history can further modify variant×25(OH)D interactions. These results expand the known genetic architecture of pulmonary function and add evidence that gene-environment interactions, including with 25(OH)D and smoking, influence lung function.
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Affiliation(s)
- Jungkyun Seo
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, United States
| | - Nathan C Gaddis
- RTI International, Research Triangle Park, NC, United States
| | - Bonnie K Patchen
- Division of Nutritional Sciences, Cornell University, Ithaca, NY, United States
| | - Jiayi Xu
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, United States
| | - R Graham Barr
- Divisions of Pulmonary, Allergy, and Critical Care Medicine, Columbia University Medical Center, New York, NY, United States
| | - George O'Connor
- Pulmonary Center and Department of Medicine, Boston University School of Medicine, Boston, MA, United States
| | - Ani W Manichaikul
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, United States
| | - Sina A Gharib
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, United States; Division of Pulmonary, Critical Care and Sleep Medicine, Computational Medicine Core, Center for Lung Biology, University of Washington, Seattle, WA, United States
| | - Josée Dupuis
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Quebec, Canada
| | - Kari E North
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, United States
| | - Patricia A Cassano
- Division of Nutritional Sciences, Cornell University, Ithaca, NY, United States; Division of Epidemiology, Department of Population Health Sciences, Weill Cornell Medicine, NY, United States
| | - Dana B Hancock
- RTI International, Research Triangle Park, NC, United States.
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Gao J, Yang Y, Xiang X, Zheng H, Yi X, Wang F, Liang Z, Chen D, Shi W, Wang L, Wu D, Feng S, Huang Q, Li X, Shu W, Chen R, Zhong N, Wang Z. Human genetic associations of the airway microbiome in chronic obstructive pulmonary disease. Respir Res 2024; 25:165. [PMID: 38622589 PMCID: PMC11367891 DOI: 10.1186/s12931-024-02805-2] [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: 09/20/2023] [Accepted: 04/04/2024] [Indexed: 04/17/2024] Open
Abstract
Little is known about the relationships between human genetics and the airway microbiome. Deeply sequenced airway metagenomics, by simultaneously characterizing the microbiome and host genetics, provide a unique opportunity to assess the microbiome-host genetic associations. Here we performed a co-profiling of microbiome and host genetics with the identification of over 5 million single nucleotide polymorphisms (SNPs) through deep metagenomic sequencing in sputum of 99 chronic obstructive pulmonary disease (COPD) and 36 healthy individuals. Host genetic variation was the most significant factor associated with the microbiome except for geography and disease status, with its top 5 principal components accounting for 12.11% of the microbiome variability. Within COPD individuals, 113 SNPs mapped to candidate genes reported as genetically associated with COPD exhibited associations with 29 microbial species and 48 functional modules (P < 1 × 10-5), where Streptococcus salivarius exhibits the strongest association to SNP rs6917641 in TBC1D32 (P = 9.54 × 10-8). Integration of concurrent host transcriptomic data identified correlations between the expression of host genes and their genetically-linked microbiome features, including NUDT1, MAD1L1 and Veillonella parvula, TTLL9 and Stenotrophomonas maltophilia, and LTA4H and Haemophilus influenzae. Mendelian randomization analyses revealed a potential causal link between PARK7 expression and microbial type III secretion system, and a genetically-mediated association between COPD and increased relative abundance of airway Streptococcus intermedius. These results suggest a previously underappreciated role of host genetics in shaping the airway microbiome and provide fresh hypotheses for genetic-based host-microbiome interactions in COPD.
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Affiliation(s)
- Jingyuan Gao
- Institute of Ecological Sciences, School of Life Sciences, South China Normal University, Guangzhou, Guangdong Province, China
| | - Yuqiong Yang
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong Province, China
| | - Xiaopeng Xiang
- The Hong Kong Polytechnic University, Hong Kong, Hung Hom Kowloon, China
| | - Huimin Zheng
- Department of Obstetrics and Gynecology, The First People's Hospital of Foshan, Foshan, Guangdong Province, China
| | - Xinzhu Yi
- Institute of Ecological Sciences, School of Life Sciences, South China Normal University, Guangzhou, Guangdong Province, China
| | - Fengyan Wang
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong Province, China
| | - Zhenyu Liang
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong Province, China
| | - Dandan Chen
- Department of Pulmonary and Critical Care Medicine, Shenzhen Institute of Respiratory Diseases, Shenzhen People's Hospital, The Second Clinical Medical College, Jinan University, The First Affiliated Hospital, Southern University of Science and Technology, Shenzhen, Guangdong Province, China
| | - Weijuan Shi
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong Province, China
| | - Lingwei Wang
- Department of Pulmonary and Critical Care Medicine, Shenzhen Institute of Respiratory Diseases, Shenzhen People's Hospital, The Second Clinical Medical College, Jinan University, The First Affiliated Hospital, Southern University of Science and Technology, Shenzhen, Guangdong Province, China
| | - Di Wu
- Department of Pulmonary and Critical Care Medicine, Shenzhen Institute of Respiratory Diseases, Shenzhen People's Hospital, The Second Clinical Medical College, Jinan University, The First Affiliated Hospital, Southern University of Science and Technology, Shenzhen, Guangdong Province, China
| | - Shengchuan Feng
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong Province, China
| | - Qiaoyun Huang
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong Province, China
| | - Xueping Li
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong Province, China
| | - Wensheng Shu
- Institute of Ecological Sciences, School of Life Sciences, South China Normal University, Guangzhou, Guangdong Province, China.
| | - Rongchang Chen
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong Province, China.
- Department of Pulmonary and Critical Care Medicine, Shenzhen Institute of Respiratory Diseases, Shenzhen People's Hospital, The Second Clinical Medical College, Jinan University, The First Affiliated Hospital, Southern University of Science and Technology, Shenzhen, Guangdong Province, China.
| | - Nanshan Zhong
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong Province, China.
| | - Zhang Wang
- Institute of Ecological Sciences, Biomedical Research Center, School of Life Sciences, State Key Laboratory of Respiratory Disease, South China Normal University, Guangzhou, Guangdong Province, China.
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Zhu D, Zhao Y, Zhang R, Wu H, Cai G, Wu Z, Wang Y, Hu X. Genomic prediction based on selective linkage disequilibrium pruning of low-coverage whole-genome sequence variants in a pure Duroc population. Genet Sel Evol 2023; 55:72. [PMID: 37853325 PMCID: PMC10583454 DOI: 10.1186/s12711-023-00843-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: 09/23/2022] [Accepted: 09/14/2023] [Indexed: 10/20/2023] Open
Abstract
BACKGROUND Although the accumulation of whole-genome sequencing (WGS) data has accelerated the identification of mutations underlying complex traits, its impact on the accuracy of genomic predictions is limited. Reliable genotyping data and pre-selected beneficial loci can be used to improve prediction accuracy. Previously, we reported a low-coverage sequencing genotyping method that yielded 11.3 million highly accurate single-nucleotide polymorphisms (SNPs) in pigs. Here, we introduce a method termed selective linkage disequilibrium pruning (SLDP), which refines the set of SNPs that show a large gain during prediction of complex traits using whole-genome SNP data. RESULTS We used the SLDP method to identify and select markers among millions of SNPs based on genome-wide association study (GWAS) prior information. We evaluated the performance of SLDP with respect to three real traits and six simulated traits with varying genetic architectures using two representative models (genomic best linear unbiased prediction and BayesR) on samples from 3579 Duroc boars. SLDP was determined by testing 180 combinations of two core parameters (GWAS P-value thresholds and linkage disequilibrium r2). The parameters for each trait were optimized in the training population by five fold cross-validation and then tested in the validation population. Similar to previous GWAS prior-based methods, the performance of SLDP was mainly affected by the genetic architecture of the traits analyzed. Specifically, SLDP performed better for traits controlled by major quantitative trait loci (QTL) or a small number of quantitative trait nucleotides (QTN). Compared with two commercial SNP chips, genotyping-by-sequencing data, and an unselected whole-genome SNP panel, the SLDP strategy led to significant improvements in prediction accuracy, which ranged from 0.84 to 3.22% for real traits controlled by major or moderate QTL and from 1.23 to 11.47% for simulated traits controlled by a small number of QTN. CONCLUSIONS The SLDP marker selection method can be incorporated into mainstream prediction models to yield accuracy improvements for traits with a relatively simple genetic architecture, however, it has no significant advantage for traits not controlled by major QTL. The main factors that affect its performance are the genetic architecture of traits and the reliability of GWAS prior information. Our findings can facilitate the application of WGS-based genomic selection.
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Affiliation(s)
- Di Zhu
- State Key Laboratory of Animal Biotech Breeding, College of Biological Sciences, China Agricultural University, Beijing, China
| | - Yiqiang Zhao
- State Key Laboratory of Animal Biotech Breeding, College of Biological Sciences, China Agricultural University, Beijing, China
| | - Ran Zhang
- State Key Laboratory of Animal Biotech Breeding, College of Biological Sciences, China Agricultural University, Beijing, China
| | - Hanyu Wu
- State Key Laboratory of Animal Biotech Breeding, College of Biological Sciences, China Agricultural University, Beijing, China
- National Research Facility for Phenotypic and Genotypic Analysis of Model Animals (Beijing), China Agricultural University, Beijing, China
| | - Gengyuan Cai
- National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, China
| | - Zhenfang Wu
- National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, China.
| | - Yuzhe Wang
- National Research Facility for Phenotypic and Genotypic Analysis of Model Animals (Beijing), China Agricultural University, Beijing, China.
| | - Xiaoxiang Hu
- State Key Laboratory of Animal Biotech Breeding, College of Biological Sciences, China Agricultural University, Beijing, China.
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Ahmed E, Lahmar ZM, Bourdin A. Revisiting Peter Macklem's old dream through the PRISm of lung volumes. ERJ Open Res 2023; 9:00469-2023. [PMID: 37753277 PMCID: PMC10518892 DOI: 10.1183/23120541.00469-2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Accepted: 07/13/2023] [Indexed: 09/28/2023] Open
Abstract
In healthy asymptomatic smokers with normal FEV1/FVC, abnormal CT lung volumes that reflect small airway dysfunction and emphysema could be used as a biomarker to identify susceptible smokers at increased risk of progressing to COPD https://bit.ly/3XZDj1s.
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Affiliation(s)
- Engi Ahmed
- Department of Respiratory Diseases, Univ Montpellier, CHU Montpellier, Montpellier, France
- PhyMedExp, Univ Montpellier, CNRS, INSERM, CHU Montpellier, Montpellier, France
- Laboratory of Immunoregulation and Mucosal Immunology, VIB-UGent Center for Inflammation Research, Ghent, Belgium
| | - Zakaria Mohamed Lahmar
- Department of Respiratory Diseases, Univ Montpellier, CHU Montpellier, Montpellier, France
- PhyMedExp, Univ Montpellier, CNRS, INSERM, CHU Montpellier, Montpellier, France
| | - Arnaud Bourdin
- Department of Respiratory Diseases, Univ Montpellier, CHU Montpellier, Montpellier, France
- PhyMedExp, Univ Montpellier, CNRS, INSERM, CHU Montpellier, Montpellier, France
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10
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Li JX, Huang XZ, Fu WP, Zhang XH, Mauki DH, Zhang J, Sun C, Dai LM, Zhong L, Yu L, Zhang YP. Remote regulation of rs80245547 and rs72673891 mediated by transcription factors C-Jun and CREB1 affect GSTCD expression. iScience 2023; 26:107383. [PMID: 37609638 PMCID: PMC10440715 DOI: 10.1016/j.isci.2023.107383] [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: 06/16/2022] [Revised: 12/30/2022] [Accepted: 07/11/2023] [Indexed: 08/24/2023] Open
Abstract
Chronic obstructive pulmonary disease (COPD), the third leading cause of death worldwide, is influenced by genetic factors. The genetic signal rs10516526 in the glutathione S-transferase C-terminal domain containing (GSTCD) gene is a highly significant and reproducible signal associated with lung function and COPD on chromosome 4q24. In this study, comprehensive bioinformatics analyses and experimental verifications were detailly implemented to explore the regulation mechanism of rs10516526 and GSTCD in COPD. The results suggested that low expression of GSTCD was associated with COPD (p = 0.010). And C-Jun and CREB1 transcription factors were found to be essential for the regulation of GSTCD by rs80245547 and rs72673891. Moreover, rs80245547T and rs72673891G had a stronger binding ability to these transcription factors, which may promote the allele-specific long-range enhancer-promoter interactions on GSTCD, thus making COPD less susceptible. Our study provides a new insight into the relationship between rs10516526, GSTCD, and COPD.
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Affiliation(s)
- Jin-Xiu Li
- State Key Laboratory for Conservation and Utilization of Bio-Resource in Yunnan, School of Life Sciences, Yunnan University, Kunming 650000, China
- State Key Laboratory of Genetic Resources and Evolution, and Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650000, China
| | - Xue-Zhen Huang
- State Key Laboratory for Conservation and Utilization of Bio-Resource in Yunnan, School of Life Sciences, Yunnan University, Kunming 650000, China
| | - Wei-ping Fu
- Department of Respiratory Critical Care Medicine, The First Affiliated Hospital of Kunming Medical University, Kunming 650000, China
| | - Xiao-hua Zhang
- State Key Laboratory for Conservation and Utilization of Bio-Resource in Yunnan, School of Life Sciences, Yunnan University, Kunming 650000, China
| | - David H. Mauki
- Faculty of Pharmaceutical Sciences, Institute of Biomedicine and Biotechnology, Center for Cancer Immunology, Chinese Academy of Sciences, Shenzhen Institute of Advanced Technology, Shenzhen 518000, Guangdong China
| | - Jing Zhang
- Department of Respiratory Critical Care Medicine, The First Affiliated Hospital of Kunming Medical University, Kunming 650000, China
| | - Chang Sun
- State Key Laboratory for Conservation and Utilization of Bio-Resource in Yunnan, School of Life Sciences, Yunnan University, Kunming 650000, China
- College of Life Sciences, Shaanxi Normal University, Xi’an 710000, China
| | - Lu-Ming Dai
- Department of Respiratory Critical Care Medicine, The First Affiliated Hospital of Kunming Medical University, Kunming 650000, China
| | - Li Zhong
- State Key Laboratory for Conservation and Utilization of Bio-Resource in Yunnan, School of Life Sciences, Yunnan University, Kunming 650000, China
- College of Life Sciences, Shaanxi Normal University, Xi’an 710000, China
- Provincial Demonstration Center for Experimental Biology Education, Shaanxi Normal University, Xi’an 710000, China
| | - Li Yu
- State Key Laboratory for Conservation and Utilization of Bio-Resource in Yunnan, School of Life Sciences, Yunnan University, Kunming 650000, China
| | - Ya-ping Zhang
- State Key Laboratory for Conservation and Utilization of Bio-Resource in Yunnan, School of Life Sciences, Yunnan University, Kunming 650000, China
- State Key Laboratory of Genetic Resources and Evolution, and Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650000, China
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11
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Herrera-Luis E, Forno E, Celedón JC, Pino-Yanes M. Asthma Exacerbations: The Genes Behind the Scenes. J Investig Allergol Clin Immunol 2023; 33:76-94. [PMID: 36420738 PMCID: PMC10638677 DOI: 10.18176/jiaci.0878] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
Abstract
The clinical and socioeconomic burden of asthma exacerbations (AEs) constitutes a major public health problem. In the last 4 years, there has been an increase in ethnic diversity in candidate-gene and genome-wide association studies of AEs, which in the latter case led to the identification of novel genes and underlying pathobiological processes. Pharmacogenomics, admixture mapping analyses, and the combination of multiple "omics" layers have helped to prioritize genomic regions of interest and/or facilitated our understanding of the functional consequences of genetic variation. Nevertheless, the field still lags behind the genomics of asthma, where a vast compendium of genetic approaches has been used (eg, gene-environment nteractions, next-generation sequencing, and polygenic risk scores). Furthermore, the roles of the DNA methylome and histone modifications in AEs have received little attention, and microRNA findings remain to be validated in independent studies. Likewise, the most recent transcriptomic studies highlight the importance of the host-airway microbiome interaction in the modulation of risk of AEs. Leveraging -omics and deep-phenotyping data from subtypes or homogenous subgroups of patients will be crucial if we are to overcome the inherent heterogeneity of AEs, boost the identification of potential therapeutic targets, and implement precision medicine approaches to AEs in clinical practice.
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Affiliation(s)
- E Herrera-Luis
- Genomics and Health Group, Department of Biochemistry, Microbiology, Cell Biology and Genetics, Universidad de La Laguna (ULL), La Laguna, Tenerife, Spain
| | - E Forno
- Division of Pediatric Pulmonary Medicine, UPMC Children´s Hospital of Pittsburgh, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - J C Celedón
- Division of Pediatric Pulmonary Medicine, UPMC Children´s Hospital of Pittsburgh, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - M Pino-Yanes
- Genomics and Health Group, Department of Biochemistry, Microbiology, Cell Biology and Genetics, Universidad de La Laguna (ULL), La Laguna, Tenerife, Spain
- CIBER de Enfermedades Respiratorias, Instituto de Salud Carlos III, Madrid, Spain 4 Instituto de Tecnologías Biomédicas (ITB), Universidad de La Laguna (ULL), La Laguna, Tenerife, Spain
- Instituto de Tecnologías Biomédicas (ITB), Universidad de La Laguna (ULL), La Laguna, Tenerife, Spain
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12
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Cosentino J, Behsaz B, Alipanahi B, McCaw ZR, Hill D, Schwantes-An TH, Lai D, Carroll A, Hobbs BD, Cho MH, McLean CY, Hormozdiari F. Inference of chronic obstructive pulmonary disease with deep learning on raw spirograms identifies new genetic loci and improves risk models. Nat Genet 2023; 55:787-795. [PMID: 37069358 DOI: 10.1038/s41588-023-01372-4] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Accepted: 03/14/2023] [Indexed: 04/19/2023]
Abstract
Chronic obstructive pulmonary disease (COPD), the third leading cause of death worldwide, is highly heritable. While COPD is clinically defined by applying thresholds to summary measures of lung function, a quantitative liability score has more power to identify genetic signals. Here we train a deep convolutional neural network on noisy self-reported and International Classification of Diseases labels to predict COPD case-control status from high-dimensional raw spirograms and use the model's predictions as a liability score. The machine-learning-based (ML-based) liability score accurately discriminates COPD cases and controls, and predicts COPD-related hospitalization without any domain-specific knowledge. Moreover, the ML-based liability score is associated with overall survival and exacerbation events. A genome-wide association study on the ML-based liability score replicates existing COPD and lung function loci and also identifies 67 new loci. Lastly, our method provides a general framework to use ML methods and medical-record-based labels that does not require domain knowledge or expert curation to improve disease prediction and genomic discovery for drug design.
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Affiliation(s)
| | | | | | | | - Davin Hill
- Department of Electrical and Computer Engineering, Northeastern University, Boston, MA, USA
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Tae-Hwi Schwantes-An
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
- Division of Cardiology, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Dongbing Lai
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | | | - 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
- Harvard Medical School, 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
- Harvard Medical School, Boston, MA, USA
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13
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Shrine N, Izquierdo AG, Chen J, Packer R, Hall RJ, Guyatt AL, Batini C, Thompson RJ, Pavuluri C, Malik V, Hobbs BD, Moll M, Kim W, Tal-Singer R, Bakke P, Fawcett KA, John C, Coley K, Piga NN, Pozarickij A, Lin K, Millwood IY, Chen Z, Li L, Wijnant SRA, Lahousse L, Brusselle G, Uitterlinden AG, Manichaikul A, Oelsner EC, Rich SS, Barr RG, Kerr SM, Vitart V, Brown MR, Wielscher M, Imboden M, Jeong A, Bartz TM, Gharib SA, Flexeder C, Karrasch S, Gieger C, Peters A, Stubbe B, Hu X, Ortega VE, Meyers DA, Bleecker ER, Gabriel SB, Gupta N, Smith AV, Luan J, Zhao JH, Hansen AF, Langhammer A, Willer C, Bhatta L, Porteous D, Smith BH, Campbell A, Sofer T, Lee J, Daviglus ML, Yu B, Lim E, Xu H, O'Connor GT, Thareja G, Albagha OME, Suhre K, Granell R, Faquih TO, Hiemstra PS, Slats AM, Mullin BH, Hui J, James A, Beilby J, Patasova K, Hysi P, Koskela JT, Wyss AB, Jin J, Sikdar S, Lee M, May-Wilson S, Pirastu N, Kentistou KA, Joshi PK, Timmers PRHJ, Williams AT, Free RC, Wang X, Morrison JL, Gilliland FD, Chen Z, Wang CA, Foong RE, Harris SE, Taylor A, Redmond P, Cook JP, Mahajan A, Lind L, Palviainen T, Lehtimäki T, Raitakari OT, Kaprio J, Rantanen T, Pietiläinen KH, Cox SR, Pennell CE, Hall GL, Gauderman WJ, Brightling C, Wilson JF, Vasankari T, Laitinen T, Salomaa V, Mook-Kanamori DO, Timpson NJ, Zeggini E, Dupuis J, Hayward C, Brumpton B, Langenberg C, Weiss S, Homuth G, Schmidt CO, Probst-Hensch N, Jarvelin MR, Morrison AC, Polasek O, Rudan I, Lee JH, Sayers I, Rawlins EL, Dudbridge F, Silverman EK, Strachan DP, Walters RG, Morris AP, London SJ, Cho MH, Wain LV, Hall IP, Tobin MD. Multi-ancestry genome-wide association analyses improve resolution of genes and pathways influencing lung function and chronic obstructive pulmonary disease risk. Nat Genet 2023; 55:410-422. [PMID: 36914875 PMCID: PMC10011137 DOI: 10.1038/s41588-023-01314-0] [Citation(s) in RCA: 49] [Impact Index Per Article: 24.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Accepted: 01/25/2023] [Indexed: 03/16/2023]
Abstract
Lung-function impairment underlies chronic obstructive pulmonary disease (COPD) and predicts mortality. In the largest multi-ancestry genome-wide association meta-analysis of lung function to date, comprising 580,869 participants, we identified 1,020 independent association signals implicating 559 genes supported by ≥2 criteria from a systematic variant-to-gene mapping framework. These genes were enriched in 29 pathways. Individual variants showed heterogeneity across ancestries, age and smoking groups, and collectively as a genetic risk score showed strong association with COPD across ancestry groups. We undertook phenome-wide association studies for selected associated variants as well as trait and pathway-specific genetic risk scores to infer possible consequences of intervening in pathways underlying lung function. We highlight new putative causal variants, genes, proteins and pathways, including those targeted by existing drugs. These findings bring us closer to understanding the mechanisms underlying lung function and COPD, and should inform functional genomics experiments and potentially future COPD therapies.
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Affiliation(s)
- Nick Shrine
- Department of Population Health Sciences, University of Leicester, Leicester, UK.
| | - Abril G Izquierdo
- Department of Population Health Sciences, University of Leicester, Leicester, UK
| | - Jing Chen
- Department of Population Health Sciences, University of Leicester, Leicester, UK
| | - Richard Packer
- Department of Population Health Sciences, University of Leicester, Leicester, UK
| | - Robert J Hall
- Division of Respiratory Medicine and NIHR Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, UK
| | - Anna L Guyatt
- Department of Population Health Sciences, University of Leicester, Leicester, UK
| | - Chiara Batini
- Department of Population Health Sciences, University of Leicester, Leicester, UK
- Leicester National Institute for Health and Care Research, Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Rebecca J Thompson
- Division of Respiratory Medicine and NIHR Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, UK
| | - Chandan Pavuluri
- Channing Division of Network Medicine, Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Vidhi Malik
- Channing Division of Network Medicine, Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Brian D Hobbs
- Channing Division of Network Medicine, Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Matthew Moll
- Channing Division of Network Medicine, Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Wonji Kim
- Channing Division of Network Medicine, Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | | | - Per Bakke
- Department of Clinical Science, Unversity of Bergen, Bergen, Norway
| | - Katherine A Fawcett
- Department of Population Health Sciences, University of Leicester, Leicester, UK
| | - Catherine John
- Department of Population Health Sciences, University of Leicester, Leicester, UK
- Leicester National Institute for Health and Care Research, Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Kayesha Coley
- Department of Population Health Sciences, University of Leicester, Leicester, UK
| | - Noemi Nicole Piga
- Department of Population Health Sciences, University of Leicester, Leicester, UK
| | - Alfred Pozarickij
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Kuang Lin
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Iona Y Millwood
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- MRC Population Health Research Unit, University of Oxford, Oxford, UK
| | - Zhengming Chen
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- MRC Population Health Research Unit, University of Oxford, Oxford, UK
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Sara R A Wijnant
- Department of Respiratory Diseases, Ghent Universital Hospital, Ghent, Belgium
- Department of Bioanalysis, Faculty of Pharmaceutical Sciences, Ghent University, Ghent, Belgium
- Department of Epidemiology, Eramus Medical Center, Rotterdam, The Netherlands
| | - Lies Lahousse
- Department of Bioanalysis, Faculty of Pharmaceutical Sciences, Ghent University, Ghent, Belgium
- Department of Epidemiology, Eramus Medical Center, Rotterdam, The Netherlands
| | - Guy Brusselle
- Department of Respiratory Diseases, Ghent Universital Hospital, Ghent, Belgium
- Department of Epidemiology, Eramus Medical Center, Rotterdam, The Netherlands
| | - Andre G Uitterlinden
- Department of Internal Medicine, Eramus Medical Center, Rotterdam, The Netherlands
| | - Ani Manichaikul
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Elizabeth C Oelsner
- Department of Medicine, Columbia University Medical Center, New York, NY, USA
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - R Graham Barr
- Department of Medicine, Columbia University Medical Center, New York, NY, USA
| | - Shona M Kerr
- Medical Research Council Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Veronique Vitart
- Medical Research Council Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Michael R Brown
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Matthias Wielscher
- MRC Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Medea Imboden
- Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Allschwil, Switzerland
- Department of Public Health, University of Basel, Basel, Switzerland
| | - Ayoung Jeong
- Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Allschwil, Switzerland
- Department of Public Health, University of Basel, Basel, Switzerland
| | - Traci M Bartz
- Cardiovascular Health Research Unit, Departments of Medicine and Biostatistics, University of Washington, Seattle, WA, USA
| | - Sina A Gharib
- Computational Medicine Core, Center for Lung Biology, Division of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Claudia Flexeder
- Institute and Clinic for Occupational, Social and Environmental Medicine, University Hospital, LMU Munich, Munich, Germany
- Comprehensive Pneumology Center Munich (CPC-M), German Center for Lung Research (DZL), Munich, Germany
- Institute of Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Stefan Karrasch
- Institute and Clinic for Occupational, Social and Environmental Medicine, University Hospital, LMU Munich, Munich, Germany
- Comprehensive Pneumology Center Munich (CPC-M), German Center for Lung Research (DZL), Munich, Germany
- Institute of Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Christian Gieger
- Institute of Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
- Institute for Medical Information Processing, Biometry and Epidemiology, Medical Faculty, Ludwig Maximilian University, Munich, Germany
| | - Beate Stubbe
- Department of Internal Medicine B-Cardiology, Intensive Care, Pulmonary Medicine and Infectious Diseases, University Medicine Greifswald, Greifswald, Germany
| | - Xiaowei Hu
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Victor E Ortega
- Division of Respiratory Medicine, Department of Internal Medicine, Center for Individualized Medicine, Mayo Clinic, Scottsdale, AZ, USA
| | | | | | | | - Namrata Gupta
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Albert Vernon Smith
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA
- Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Jian'an Luan
- MRC Epidemiology Unit, Institute of Metabolic Science, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Jing-Hua Zhao
- Department of Public and Primary Care, Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
| | - Ailin F Hansen
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU Norwegian University of Science and Technology, Trondheim, Norway
| | - Arnulf Langhammer
- HUNT Research Centre, Department of Public Health and Nursing, NTNU Norwegian University of Science and Technology, Levanger, Norway
- Levanger Hospital, Nord-Trøndelag Hospital Trust, Levanger, Norway
| | - Cristen Willer
- Division of Cardiology, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Laxmi Bhatta
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU Norwegian University of Science and Technology, Trondheim, Norway
| | - David Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Blair H Smith
- Division of Population Health and Genomics, Ninewells Hospital and Medical School, University of Dundee, Dundee, UK
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Tamar Sofer
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Jiwon Lee
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
| | - Martha L Daviglus
- Institute for Minority Health Research, University of Illinois at Chicago, Chicago, IL, USA
| | - Bing Yu
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Elise Lim
- Department of Biostatistics, School of Public Health, Boston University, Boston, MA, USA
| | - Hanfei Xu
- Department of Biostatistics, School of Public Health, Boston University, Boston, MA, USA
| | - George T O'Connor
- Pulmonary Center, School of Medicine, Boston University, Boston, MA, USA
| | - Gaurav Thareja
- Bioinformatics Core, Weill Cornell Medicine-Qatar, Education City, Doha, Qatar
| | - Omar M E Albagha
- College of Health and Life Sciences, Hamad Bin Khalifa University, Doha, Qatar
- Center for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Karsten Suhre
- Bioinformatics Core, Weill Cornell Medicine-Qatar, Education City, Doha, Qatar
- Department of Biophysics and Physiology, Weill Cornell Medicine, New York, NY, USA
| | - Raquel Granell
- MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Tariq O Faquih
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Pieter S Hiemstra
- Department of Pulmonology, Leiden University Medical Center, Leiden, The Netherlands
| | - Annelies M Slats
- Department of Pulmonology, Leiden University Medical Center, Leiden, The Netherlands
| | - Benjamin H Mullin
- Department of Endocrinology and Diabetes, Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia
- School of Biomedical Sciences, University of Western Australia, Crawley, Western Australia, Australia
| | - Jennie Hui
- Busselton Population Medical Research Institute, QEII Medical Centre, Nedlands, Western Australia, Australia
- School of Population and Global Health, University of Western Australia, Crawley, Western Australia, Australia
- PathWest Laboratory Medicine of WA, Nedlands, Western Australia, Australia
| | - Alan James
- Busselton Population Medical Research Institute, QEII Medical Centre, Nedlands, Western Australia, Australia
| | - John Beilby
- School of Biomedical Sciences, University of Western Australia, Crawley, Western Australia, Australia
- Busselton Population Medical Research Institute, QEII Medical Centre, Nedlands, Western Australia, Australia
| | - Karina Patasova
- Department of Twin Research and Genetic Epidemiology, King's College London School of Medicine, London, UK
- Division of Respiratory Medicine, Department of Medicine Solna, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden
| | - Pirro Hysi
- Department of Twin Research and Genetic Epidemiology, King's College London School of Medicine, London, UK
- UCL Institute of Ophthalmology, University College London, London, UK
| | - Jukka T Koskela
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Annah B Wyss
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC, USA
| | | | - Sinjini Sikdar
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC, USA
- Department of Mathematics and Statistics, Old Dominion University, Norfolk, VA, USA
| | - Mikyeong Lee
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC, USA
| | - Sebastian May-Wilson
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Nicola Pirastu
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Katherine A Kentistou
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
- Centre for Cardiovascular Sciences, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
| | - Peter K Joshi
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Paul R H J Timmers
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Alexander T Williams
- Department of Population Health Sciences, University of Leicester, Leicester, UK
| | - Robert C Free
- Leicester National Institute for Health and Care Research, Biomedical Research Centre, Glenfield Hospital, Leicester, UK
- Department of Respiratory Sciences, University of Leicester, Leicester, UK
| | - Xueyang Wang
- Leicester National Institute for Health and Care Research, Biomedical Research Centre, Glenfield Hospital, Leicester, UK
- Department of Respiratory Sciences, University of Leicester, Leicester, UK
| | - John L Morrison
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Frank D Gilliland
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Zhanghua Chen
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Carol A Wang
- School of Medicine and Public Health, College of Health, Medicine and Wellbeing, University of Newcastle, Newcastle, New South Wales, Australia
- Hunter Medical Research Institute, Newcastle, New South Wales, Australia
| | - Rachel E Foong
- Wal-yan Respiratory Research Centre, Telethon Kids Institute, Perth, Western Australia, Australia
- School of Allied Health, Faculty of Health Sciences, Curtin University, Perth, Western Australia, Australia
| | - Sarah E Harris
- Lothian Birth Cohorts group, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Adele Taylor
- Lothian Birth Cohorts group, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Paul Redmond
- Lothian Birth Cohorts group, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - James P Cook
- Department of Health Data Science, University of Liverpool, Liverpool, UK
| | - Anubha Mahajan
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- Genentech, South San Francisco, CA, USA
| | - Lars Lind
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Teemu Palviainen
- Institute for Molecular Medicine Finland-FIMM, University of Helsinki, Helsinki, Finland
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, and Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Olli T Raitakari
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland-FIMM, University of Helsinki, Helsinki, Finland
| | - Taina Rantanen
- Faculty of Sport and Health Sciences, University of Jyvaskyla, Jyvaskyla, Finland
| | - Kirsi H Pietiläinen
- Obesity Research Unit, Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Obesity and Abdominal Centers, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | - Simon R Cox
- Lothian Birth Cohorts group, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Craig E Pennell
- School of Medicine and Public Health, College of Health, Medicine and Wellbeing, University of Newcastle, Newcastle, New South Wales, Australia
- Hunter Medical Research Institute, Newcastle, New South Wales, Australia
- Department of Maternity and Gynaecology, John Hunter Hospital, Newcastle, New South Wales, Australia
| | - Graham L Hall
- Wal-yan Respiratory Research Centre, Telethon Kids Institute, Perth, Western Australia, Australia
- School of Allied Health, Faculty of Health Sciences, Curtin University, Perth, Western Australia, Australia
| | - W James Gauderman
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Chris Brightling
- Leicester National Institute for Health and Care Research, Biomedical Research Centre, Glenfield Hospital, Leicester, UK
- Department of Infection, Inflammation and Immunity, Institute for Lung Health, University of Leicester, Leicester, UK
| | - James F Wilson
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - Tuula Vasankari
- FILHA-Finnish Lung Health Association, Helsinki, Finland
- Department of Respiratory Diseases and Allergology, University of Turku, Turku, Finland
| | - Tarja Laitinen
- Administration Center, Tampere University Hospital and University of Tampere, Tampere, Finland
| | - Veikko Salomaa
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Dennis O Mook-Kanamori
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
- Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, The Netherlands
| | - Nicholas J Timpson
- MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- ALSPAC, Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Eleftheria Zeggini
- Wellcome Sanger Institute, Cambridge, UK
- Institute of Translational Genomics, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
- Technical University of Munich (TUM) and Klinikum Rechts der Isar, TUM School of Medicine, Munich, Germany
| | - Josée Dupuis
- Department of Epidemiology, Biostatistics, and Occupational Health, School of Population and Global Health, McGill University, Montreal, Quebec, Canada
| | - Caroline Hayward
- Medical Research Council Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Ben Brumpton
- HUNT Research Centre, Department of Public Health and Nursing, NTNU Norwegian University of Science and Technology, Levanger, Norway
- Clinic of Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Claudia Langenberg
- MRC Epidemiology Unit, Institute of Metabolic Science, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- Precision Healthcare University Research Institute, Queen Mary University of London, London, UK
- Computational Medicine, Berlin Institute of Health at Charité, Universitätsmedizin Berlin, Berlin, Germany
| | - Stefan Weiss
- Interfaculty Institute for Genetics and Functional Genomics, Department of Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Georg Homuth
- Interfaculty Institute for Genetics and Functional Genomics, Department of Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Carsten Oliver Schmidt
- Institute for Community Medicine, SHIP-Clinical Epidemiological Research, University Medicine Greifswald, Greifswald, Germany
| | - Nicole Probst-Hensch
- Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Allschwil, Switzerland
- Department of Public Health, University of Basel, Basel, Switzerland
| | - Marjo-Riitta Jarvelin
- MRC Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
- Biocenter Oulu, University of Oulu, Oulu, Finland
- Unit of Primary Health Care, Oulu University Hospital, OYS, Oulu, Finland
| | - Alanna C Morrison
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Ozren Polasek
- School of Medicine, University of Split, Split, Croatia
| | - Igor Rudan
- Centre for Global Health, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Joo-Hyeon Lee
- Jeffrey Cheah Biomedical Centre, Wellcome-MRC Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK
- Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK
| | - Ian Sayers
- Division of Respiratory Medicine and NIHR Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, UK
| | - Emma L Rawlins
- Wellcome Trust-CRUK Gurdon Institute and Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK
| | - Frank Dudbridge
- Department of Population Health Sciences, University of Leicester, Leicester, UK
| | - Edwin K Silverman
- Channing Division of Network Medicine, Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - David P Strachan
- Population Health Research Institute, St George's University of London, London, UK
| | - Robin G Walters
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- MRC Population Health Research Unit, University of Oxford, Oxford, UK
| | - Andrew P Morris
- Centre for Genetics and Genomics Versus Arthritis, Division of Musculoskeletal and Dermatological Sciences, Centre for Musculoskeletal Research, The University of Manchester, Manchester, UK
| | - Stephanie J London
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC, USA
| | - Michael H Cho
- Channing Division of Network Medicine, Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Louise V Wain
- Department of Population Health Sciences, University of Leicester, Leicester, UK
- Leicester National Institute for Health and Care Research, Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Ian P Hall
- Division of Respiratory Medicine and NIHR Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, UK
| | - Martin D Tobin
- Department of Population Health Sciences, University of Leicester, Leicester, UK.
- Leicester National Institute for Health and Care Research, Biomedical Research Centre, Glenfield Hospital, Leicester, UK.
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14
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Sinkala M, Elsheikh SSM, Mbiyavanga M, Cullinan J, Mulder NJ. A genome-wide association study identifies distinct variants associated with pulmonary function among European and African ancestries from the UK Biobank. Commun Biol 2023; 6:49. [PMID: 36641522 PMCID: PMC9840173 DOI: 10.1038/s42003-023-04443-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2022] [Accepted: 01/09/2023] [Indexed: 01/16/2023] Open
Abstract
Pulmonary function is an indicator of well-being, and pulmonary pathologies are the third major cause of death worldwide. We analysed the UK Biobank genome-wide association summary statistics of pulmonary function for Europeans and individuals of recent African descent to identify variants associated with the trait in the two ancestries. Here, we show 627 variants in Europeans and 3 in Africans associated with three pulmonary function parameters. In addition to the 110 variants in Europeans previously reported to be associated with phenotypes related to pulmonary function, we identify 279 novel loci, including an ISX intergenic variant rs369476290 on chromosome 22 in Africans. Remarkably, we find no shared variants among Africans and Europeans. Furthermore, enrichment analyses of variants separately for each ancestry background reveal significant enrichment for terms related to pulmonary phenotypes in Europeans but not Africans. Further analysis of studies of pulmonary phenotypes reveals that individuals of European background are disproportionally overrepresented in datasets compared to Africans, with the gap widening over the past five years. Our findings extend our understanding of the different variants that modify the pulmonary function in Africans and Europeans, a promising finding for future GWASs and medical studies.
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Affiliation(s)
- Musalula Sinkala
- Computational Biology Division, Faculty of Health Sciences, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Anzio Rd, Observatory, 7925, Cape Town, South Africa.
| | - Samar S M Elsheikh
- Pharmacogenetics Research Clinic, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Mamana Mbiyavanga
- Computational Biology Division, Faculty of Health Sciences, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Anzio Rd, Observatory, 7925, Cape Town, South Africa
| | - Joshua Cullinan
- Computational Biology Division, Faculty of Health Sciences, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Anzio Rd, Observatory, 7925, Cape Town, South Africa
| | - Nicola J Mulder
- Computational Biology Division, Faculty of Health Sciences, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Anzio Rd, Observatory, 7925, Cape Town, South Africa
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15
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Hayden LP, Hobbs BD, Busch R, Cho MH, Liu M, Lopes-Ramos CM, Lomas DA, Bakke P, Gulsvik A, Silverman EK, Crapo JD, Beaty TH, Laird NM, Lange C, DeMeo DL. X chromosome associations with chronic obstructive pulmonary disease and related phenotypes: an X chromosome-wide association study. Respir Res 2023; 24:38. [PMID: 36726148 PMCID: PMC9891756 DOI: 10.1186/s12931-023-02337-1] [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: 04/21/2022] [Accepted: 01/18/2023] [Indexed: 02/03/2023] Open
Abstract
BACKGROUND The association between genetic variants on the X chromosome to risk of COPD has not been fully explored. We hypothesize that the X chromosome harbors variants important in determining risk of COPD related phenotypes and may drive sex differences in COPD manifestations. METHODS Using X chromosome data from three COPD-enriched cohorts of adult smokers, we performed X chromosome specific quality control, imputation, and testing for association with COPD case-control status, lung function, and quantitative emphysema. Analyses were performed among all subjects, then stratified by sex, and subsequently combined in meta-analyses. RESULTS Among 10,193 subjects of non-Hispanic white or European ancestry, a variant near TMSB4X, rs5979771, reached genome-wide significance for association with lung function measured by FEV1/FVC ([Formula: see text] 0.020, SE 0.004, p 4.97 × 10-08), with suggestive evidence of association with FEV1 ([Formula: see text] 0.092, SE 0.018, p 3.40 × 10-07). Sex-stratified analyses revealed X chromosome variants that were differentially trending in one sex, with significantly different effect sizes or directions. CONCLUSIONS This investigation identified loci influencing lung function, COPD, and emphysema in a comprehensive genetic association meta-analysis of X chromosome genetic markers from multiple COPD-related datasets. Sex differences play an important role in the pathobiology of complex lung disease, including X chromosome variants that demonstrate differential effects by sex and variants that may be relevant through escape from X chromosome inactivation. Comprehensive interrogation of the X chromosome to better understand genetic control of COPD and lung function is important to further understanding of disease pathology. Trial registration Genetic Epidemiology of COPD Study (COPDGene) is registered at ClinicalTrials.gov, NCT00608764 (Active since January 28, 2008). Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints Study (ECLIPSE), GlaxoSmithKline study code SCO104960, is registered at ClinicalTrials.gov, NCT00292552 (Active since February 16, 2006). Genetics of COPD in Norway Study (GenKOLS) holds GlaxoSmithKline study code RES11080, Genetics of Chronic Obstructive Lung Disease.
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Affiliation(s)
- Lystra P. Hayden
- grid.38142.3c000000041936754XDivision of Pulmonary Medicine, Boston Children’s Hospital, Harvard Medical School, Boston, MA USA ,grid.38142.3c000000041936754XChanning Division of Network Medicine, Brigham and Women’s Hospital, Harvard Medical School, 181 Longwood Ave, Boston, MA 02115 USA
| | - Brian D. Hobbs
- grid.38142.3c000000041936754XChanning Division of Network Medicine, Brigham and Women’s Hospital, Harvard Medical School, 181 Longwood Ave, Boston, MA 02115 USA ,grid.38142.3c000000041936754XDivision of Pulmonary and Critical Care Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA USA
| | - Robert Busch
- grid.417587.80000 0001 2243 3366Division of Pulmonology, Allergy, and Critical Care, U.S. Food and Drug Administration, Silver Spring, MD USA
| | - Michael H. Cho
- grid.38142.3c000000041936754XChanning Division of Network Medicine, Brigham and Women’s Hospital, Harvard Medical School, 181 Longwood Ave, Boston, MA 02115 USA ,grid.38142.3c000000041936754XDivision of Pulmonary and Critical Care Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA USA
| | - Ming Liu
- grid.268323.e0000 0001 1957 0327Bioinformatics and Computational Biology Program, Worcester Polytechnic Institute, Worcester, MA USA
| | - Camila M. Lopes-Ramos
- grid.38142.3c000000041936754XChanning Division of Network Medicine, Brigham and Women’s Hospital, Harvard Medical School, 181 Longwood Ave, Boston, MA 02115 USA ,grid.38142.3c000000041936754XDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA USA
| | - David A. Lomas
- grid.83440.3b0000000121901201UCL Respiratory, University College London, London, UK
| | - Per Bakke
- grid.7914.b0000 0004 1936 7443Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Amund Gulsvik
- grid.7914.b0000 0004 1936 7443Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Edwin K. Silverman
- grid.38142.3c000000041936754XChanning Division of Network Medicine, Brigham and Women’s Hospital, Harvard Medical School, 181 Longwood Ave, Boston, MA 02115 USA ,grid.38142.3c000000041936754XDivision of Pulmonary and Critical Care Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA USA
| | - James D. Crapo
- grid.240341.00000 0004 0396 0728Division of Pulmonary Sciences and Critical Care Medicine, National Jewish Health, Denver, CO USA
| | - Terri H. Beaty
- grid.21107.350000 0001 2171 9311Johns Hopkins School of Public Health, Baltimore, MD USA
| | - Nan M. Laird
- grid.38142.3c000000041936754XDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA USA
| | - Christoph Lange
- grid.38142.3c000000041936754XDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA USA
| | - Dawn L. DeMeo
- grid.38142.3c000000041936754XChanning Division of Network Medicine, Brigham and Women’s Hospital, Harvard Medical School, 181 Longwood Ave, Boston, MA 02115 USA ,grid.38142.3c000000041936754XDivision of Pulmonary and Critical Care Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA USA
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16
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Zhang Q, Zhang X, Zhang J, Jiang M, Zhang Y, Zheng D, Wu L, Wang W, Wang B, Wang Y. Genetic association and causal inference between lung function and venous thromboembolism. Respir Res 2023; 24:36. [PMID: 36717884 PMCID: PMC9885683 DOI: 10.1186/s12931-023-02335-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2022] [Accepted: 01/18/2023] [Indexed: 01/31/2023] Open
Abstract
BACKGROUND Previous studies have indicated that lower lung function is related to a higher risk of venous thromboembolism (VTE). However, causal inferences may be affected by confounders, coheritability or reverse causality. We aimed to explore the causal association between lung function and VTE. METHODS Summary data from public genome-wide association studies (GWAS) for lung function and VTE were obtained from published meta-analysis studies and the FinnGen consortium, respectively. Independent genetic variables significantly related to exposure were filtered as proxy instruments. We adopted linkage disequilibrium score regression (LDSC) and two-sample Mendelian randomization (MR) analyses to infer the genetic backgrounds and causal associations between different lung functions and VTE events. RESULTS LDSC showed a genetic correlation between forced expiratory volume in one second (FEV1) and deep vein thrombosis (DVT) (rg = - 0.189, P = 0.005). In univariate MR (UVMR), there was suggestive evidence for causal associations of genetically predicted force vital capacity (FVC) with DVT (odds ratio (OR) 0.774; 95% confidence interval (CI) 0.641-0.934) via forwards analysis and genetically predicted pulmonary embolism (PE) with FVC (OR 0.989; 95% CI 0.979-0.999) via reverse analysis. Multivariate MR (MVMR) analyses of lung function-specific SNPs suggested no significant direct effects of lung function on VTE, and vice versa. Of note is the borderline causal effect of PE on FEV1 (OR 0.921; 95% CI 0.848-1.000). CONCLUSIONS Our findings identified a coheritability of FEV1 (significant) and FVC (suggestive) with DVT. There was no convincing causal relationship between lung function and the risk of VTE events. The borderline causal effect of PE on FEV1 and the significant genetic correlation of FEV1 with DVT may have clinical implications for improving the quality of existing prevention and intervention strategies.
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Affiliation(s)
- Qiaoyun Zhang
- grid.24696.3f0000 0004 0369 153XBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, No. 10 Xitoutiao, Youanmenwai Street, Fengtai District, Beijing, 100069 China ,grid.24696.3f0000 0004 0369 153XDepartment of Anesthesiology, Beijing Sanbo Brain Hospital, Capital Medical University, 50 Yikesong Road, Haidian District, Beijing, 100093 China
| | - Xiaoyu Zhang
- grid.24696.3f0000 0004 0369 153XBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, No. 10 Xitoutiao, Youanmenwai Street, Fengtai District, Beijing, 100069 China ,grid.24696.3f0000 0004 0369 153XDepartment of Anesthesiology, Beijing Sanbo Brain Hospital, Capital Medical University, 50 Yikesong Road, Haidian District, Beijing, 100093 China
| | - Jie Zhang
- grid.24696.3f0000 0004 0369 153XBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, No. 10 Xitoutiao, Youanmenwai Street, Fengtai District, Beijing, 100069 China
| | - Mengyang Jiang
- grid.24696.3f0000 0004 0369 153XDepartment of Anesthesiology, Beijing Sanbo Brain Hospital, Capital Medical University, 50 Yikesong Road, Haidian District, Beijing, 100093 China
| | - Yiqiang Zhang
- grid.24696.3f0000 0004 0369 153XDepartment of Anesthesiology, Beijing Sanbo Brain Hospital, Capital Medical University, 50 Yikesong Road, Haidian District, Beijing, 100093 China
| | - Deqiang Zheng
- grid.24696.3f0000 0004 0369 153XBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, No. 10 Xitoutiao, Youanmenwai Street, Fengtai District, Beijing, 100069 China
| | - Lijuan Wu
- grid.24696.3f0000 0004 0369 153XBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, No. 10 Xitoutiao, Youanmenwai Street, Fengtai District, Beijing, 100069 China
| | - Wei Wang
- grid.24696.3f0000 0004 0369 153XBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, No. 10 Xitoutiao, Youanmenwai Street, Fengtai District, Beijing, 100069 China ,grid.1038.a0000 0004 0389 4302Centre for Precision Medicine, Edith Cowan University, Joondalup, WA Australia
| | - Baoguo Wang
- grid.24696.3f0000 0004 0369 153XDepartment of Anesthesiology, Beijing Sanbo Brain Hospital, Capital Medical University, 50 Yikesong Road, Haidian District, Beijing, 100093 China
| | - Youxin Wang
- grid.24696.3f0000 0004 0369 153XBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, No. 10 Xitoutiao, Youanmenwai Street, Fengtai District, Beijing, 100069 China ,grid.1038.a0000 0004 0389 4302Centre for Precision Medicine, Edith Cowan University, Joondalup, WA Australia
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17
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Principe S, Vijverberg SJH, Abdel-Aziz MI, Scichilone N, Maitland-van der Zee AH. Precision Medicine in Asthma Therapy. Handb Exp Pharmacol 2023; 280:85-106. [PMID: 35852633 DOI: 10.1007/164_2022_598] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Asthma is a complex, heterogeneous disease that necessitates a proper patient evaluation to decide the correct treatment and optimize disease control. The recent introduction of new target therapies for the most severe form of the disease has heralded a new era of treatment options, intending to treat and control specific molecular pathways in asthma pathophysiology. Precision medicine, using omics sciences, investigates biological and molecular mechanisms to find novel biomarkers that can be used to guide treatment selection and predict response. The identification of reliable biomarkers indicative of the pathological mechanisms in asthma is essential to unravel new potential treatment targets. In this chapter, we provide a general description of the currently available -omics techniques, focusing on their implications in asthma therapy.
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Affiliation(s)
- Stefania Principe
- Department of Respiratory Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.
- Dipartimento Universitario di Promozione della Salute, Materno Infantile, Medicina Interna e Specialistica di Eccellenza "G. D'Alessandro" (PROMISE) c/o Pneumologia, AOUP "Policlinico Paolo Giaccone", University of Palermo, Palermo, Italy.
| | - Susanne J H Vijverberg
- Department of Respiratory Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Mahmoud I Abdel-Aziz
- Department of Respiratory Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
- Department of Clinical Pharmacy, Faculty of Pharmacy, Assiut University, Assiut, Egypt
| | - Nicola Scichilone
- Dipartimento Universitario di Promozione della Salute, Materno Infantile, Medicina Interna e Specialistica di Eccellenza "G. D'Alessandro" (PROMISE) c/o Pneumologia, AOUP "Policlinico Paolo Giaccone", University of Palermo, Palermo, Italy
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18
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Marcos S, Parejo M, Estonba A, Alberdi A. Recovering High-Quality Host Genomes from Gut Metagenomic Data through Genotype Imputation. ADVANCED GENETICS (HOBOKEN, N.J.) 2022; 3:2100065. [PMID: 36620197 PMCID: PMC9744478 DOI: 10.1002/ggn2.202100065] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/27/2021] [Revised: 03/05/2022] [Indexed: 01/11/2023]
Abstract
Metagenomic datasets of host-associated microbial communities often contain host DNA that is usually discarded because the amount of data is too low for accurate host genetic analyses. However, genotype imputation can be employed to reconstruct host genotypes if a reference panel is available. Here, the performance of a two-step strategy is tested to impute genotypes from four types of reference panels built using different strategies to low-depth host genome data (≈2× coverage) recovered from intestinal samples of two chicken genetic lines. First, imputation accuracy is evaluated in 12 samples for which both low- and high-depth sequencing data are available, obtaining high imputation accuracies for all tested panels (>0.90). Second, the impact of reference panel choice in population genetics statistics on 100 chickens is assessed, all four panels yielding comparable results. In light of the observations, the feasibility and application of the applied imputation strategy are discussed for different species with regard to the host DNA proportion, genomic diversity, and availability of a reference panel. This method enables leveraging insofar discarded host DNA to get insights into the genetic structure of host populations, and in doing so, facilitates the implementation of hologenomic approaches that jointly analyze host and microbial genomic data.
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Affiliation(s)
- Sofia Marcos
- Applied Genomics and BioinformaticsUniversity of the Basque Country (UPV/EHU)LeioaBilbao48940Spain
| | - Melanie Parejo
- Applied Genomics and BioinformaticsUniversity of the Basque Country (UPV/EHU)LeioaBilbao48940Spain
| | - Andone Estonba
- Applied Genomics and BioinformaticsUniversity of the Basque Country (UPV/EHU)LeioaBilbao48940Spain
| | - Antton Alberdi
- Center for Evolutionary HologenomicsGLOBE InstituteUniversity of CopenhagenCopenhagen1353Denmark
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19
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Sharma M, Bellio MA, Benny M, Kulandavelu S, Chen P, Janjindamai C, Han C, Chang L, Sterling S, Williams K, Damianos A, Batlahally S, Kelly K, Aguilar-Caballero D, Zambrano R, Chen S, Huang J, Wu S, Hare JM, Schmidt A, Khan A, Young K. Mesenchymal Stem Cell-derived Extracellular Vesicles Prevent Experimental Bronchopulmonary Dysplasia Complicated By Pulmonary Hypertension. Stem Cells Transl Med 2022; 11:828-840. [PMID: 35758326 PMCID: PMC9397655 DOI: 10.1093/stcltm/szac041] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2021] [Accepted: 04/18/2022] [Indexed: 11/12/2022] Open
Abstract
Mesenchymal stem cell (MSC) extracellular vesicles (EVs) have beneficial effects in preclinical bronchopulmonary dysplasia and pulmonary hypertension (BPD-PH) models. The optimal source, dosing, route, and duration of effects are however unknown. The objectives of this study were to (a) compare the efficacy of GMP-grade EVs obtained from Wharton’s Jelly MSCs (WJ-MSCs) and bone marrow (BM-MSCs), (b) determine the optimal dosing and route of administration, (c) evaluate its long-term effects, and (d) determine how MSC EVs alter the lung transcriptome. Newborn rats exposed to normoxia or hyperoxia (85% O2) from postnatal day (P)1-P14 were given (a) intra-tracheal (IT) BM or WJ-MSC EVs or placebo, (b) varying doses of IT WJ-MSC EVs, or (c) IT or intravenous (IV) WJ-MSC EVs on P3. Rats were evaluated at P14 or 3 months. Early administration of IT BM-MSC or WJ-MSC EVs had similar beneficial effects on lung structure and PH in hyperoxia-exposed rats. WJ-MSC EVs however had superior effects on cardiac remodeling. Low, medium, and high dose WJ-MSC EVs had similar cardiopulmonary regenerative effects. IT and IV WJ-MSC EVs similarly improved vascular density and reduced PH in hyperoxic rats. Gene-set enrichment analysis of transcripts differentially expressed in WJ-MSC EV-treated rats showed that induced transcripts were associated with angiogenesis. Long-term studies demonstrated that a single early MSC EV dose has pulmonary vascular protective effects 3 months after administration. Together, our findings have significant translational implications as it provides critical insight into the optimal source, dosing, route, mechanisms of action, and duration of effects of MSC-EVs for BPD-PH.
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Affiliation(s)
- Mayank Sharma
- Department of Pediatrics, University of Miami Miller School of Medicine, Miami, FL, USA.,Batchelor Children's Research Institute, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Michael A Bellio
- Interdisciplinary Stem Cell Institute, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Merline Benny
- Department of Pediatrics, University of Miami Miller School of Medicine, Miami, FL, USA.,Batchelor Children's Research Institute, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Shathiyah Kulandavelu
- Department of Pediatrics, University of Miami Miller School of Medicine, Miami, FL, USA.,Interdisciplinary Stem Cell Institute, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Pingping Chen
- Department of Pediatrics, University of Miami Miller School of Medicine, Miami, FL, USA.,Batchelor Children's Research Institute, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Chawisa Janjindamai
- Department of Pediatrics, University of Miami Miller School of Medicine, Miami, FL, USA.,Batchelor Children's Research Institute, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Chenxu Han
- Batchelor Children's Research Institute, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Liming Chang
- Batchelor Children's Research Institute, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Shanique Sterling
- Department of Pediatrics, University of Miami Miller School of Medicine, Miami, FL, USA.,Batchelor Children's Research Institute, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Kevin Williams
- Department of Pediatrics, University of Miami Miller School of Medicine, Miami, FL, USA.,Batchelor Children's Research Institute, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Andreas Damianos
- Department of Pediatrics, University of Miami Miller School of Medicine, Miami, FL, USA.,Batchelor Children's Research Institute, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Sunil Batlahally
- Department of Pediatrics, University of Miami Miller School of Medicine, Miami, FL, USA.,Batchelor Children's Research Institute, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Kaitlyn Kelly
- Department of Pediatrics, University of Miami Miller School of Medicine, Miami, FL, USA.,Batchelor Children's Research Institute, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Daniela Aguilar-Caballero
- Department of Pediatrics, University of Miami Miller School of Medicine, Miami, FL, USA.,Batchelor Children's Research Institute, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Ronald Zambrano
- Department of Pediatrics, University of Miami Miller School of Medicine, Miami, FL, USA.,Batchelor Children's Research Institute, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Shaoyi Chen
- Department of Pediatrics, University of Miami Miller School of Medicine, Miami, FL, USA.,Batchelor Children's Research Institute, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Jian Huang
- Department of Pediatrics, University of Miami Miller School of Medicine, Miami, FL, USA.,Batchelor Children's Research Institute, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Shu Wu
- Department of Pediatrics, University of Miami Miller School of Medicine, Miami, FL, USA.,Batchelor Children's Research Institute, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Joshua M Hare
- Interdisciplinary Stem Cell Institute, University of Miami Miller School of Medicine, Miami, FL, USA.,Department of Medicine, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Augusto Schmidt
- Department of Pediatrics, University of Miami Miller School of Medicine, Miami, FL, USA.,Batchelor Children's Research Institute, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Aisha Khan
- Interdisciplinary Stem Cell Institute, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Karen Young
- Department of Pediatrics, University of Miami Miller School of Medicine, Miami, FL, USA.,Batchelor Children's Research Institute, University of Miami Miller School of Medicine, Miami, FL, USA.,Interdisciplinary Stem Cell Institute, University of Miami Miller School of Medicine, Miami, FL, USA
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20
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Wilson CL, Hung CF, Schnapp LM. Endotoxin-induced acute lung injury in mice with postnatal deletion of nephronectin. PLoS One 2022; 17:e0268398. [PMID: 35552565 PMCID: PMC9097991 DOI: 10.1371/journal.pone.0268398] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Accepted: 04/28/2022] [Indexed: 11/18/2022] Open
Abstract
Acute injury of the lung involves damage to the epithelium and its underlying extracellular matrix (ECM), the basement membrane (BM). How BMs contribute to injury resolution is poorly understood. Nephronectin (NPNT) is a high-affinity ligand for integrin α8β1 and, although first identified in the mouse kidney, is prominently expressed in the lung, where it localizes to BMs in the alveoli. To determine if NPNT plays a role in acute injury and inflammation of the lung, we developed a model for postnatal deletion of NPNT using mice with a floxed allele of Npnt in combination with a tamoxifen-inducible Cre recombinase expressed at the ROSA locus. Expression of NPNT was substantially reduced in lungs from tamoxifen-treated Cre+ animals. Cre+ mice and Cre- controls were given E. coli LPS by oropharyngeal aspiration to induce injury and inflammation. In Cre- lungs, although both Npnt and Itga8 (integrin α8) transcripts were downregulated at the peak of inflammation, NPNT protein was still detectable. While the onset of inflammation was similar for Cre+ and Cre-, NPNT-deficient lungs still had thickened alveolar septa and there were increased macrophages in the bronchoalveolar lavage fluid (BALF) in the resolution phase. BALF from Cre+ lungs was more chemotactic for bone marrow-derived macrophages than Cre- in in vitro experiments, but there were no differences in the elaboration of chemokines in vivo. We speculate that absence of NPNT in BMs of the alveoli impairs or delays inflammatory and injury resolution in this model, but further studies are needed to establish the precise role of NPNT in tissue repair.
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Affiliation(s)
- Carole L. Wilson
- Division of Pulmonary, Critical Care, Allergy, Sleep Medicine, Dept of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
- * E-mail:
| | - Chi F. Hung
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, University of Washington, Seattle, Washington, United States of America
| | - Lynn M. Schnapp
- Division of Pulmonary, Critical Care, Allergy, Sleep Medicine, Dept of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
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21
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Progesterone activates GPR126 to promote breast cancer development via the Gi pathway. Proc Natl Acad Sci U S A 2022; 119:e2117004119. [PMID: 35394864 PMCID: PMC9169622 DOI: 10.1073/pnas.2117004119] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023] Open
Abstract
The steroid hormone progesterone is highly involved in different physiological–pathophysiological processes, including bone formation and cancer progression. Understanding the working mechanisms, especially identifying the receptors of progesterone hormones, is of great value. In the present study, we identified GPR126 as a membrane receptor for both progesterone and 17-hydroxyprogesterone and triggered its downstream G protein signaling. We further characterized the residues of GPR126 that interact with these two ligands and found that progesterone promoted the progression of a triple-negative breast cancer model through GPR126-dependent Gi-SRC signaling. Therefore, developing antagonists targeting GPR126-Gi may provide an alternative therapeutic option for patients with triple-negative breast cancer. GPR126 is a member of the adhesion G protein-coupled receptors (aGPCRs) that is essential for the normal development of diverse tissues, and its mutations are implicated in various pathological processes. Here, through screening 34 steroid hormones and their derivatives for cAMP production, we found that progesterone (P4) and 17-hydroxyprogesterone (17OHP) could specifically activate GPR126 and trigger its downstream Gi signaling by binding to the ligand pocket in the seven-transmembrane domain of the C-terminal fragment of GPR126. A detailed mutagenesis screening according to a computational simulated structure model indicated that K1001ECL2 and F1012ECL2 are key residues that specifically recognize 17OHP but not progesterone. Finally, functional analysis revealed that progesterone-triggered GPR126 activation promoted cell growth in vitro and tumorigenesis in vivo, which involved Gi-SRC pathways in a triple-negative breast cancer model. Collectively, our work identified a membrane receptor for progesterone/17OHP and delineated the mechanisms by which GPR126 participated in potential tumor progression in triple-negative breast cancer, which will enrich our understanding of the functions and working mechanisms of both the aGPCR member GPR126 and the steroid hormone progesterone.
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22
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Shen R, Murphy CJ, Xu X, Hu M, Ding J, Wu C. Ras and Rab Interactor 3: From Cellular Mechanisms to Human Diseases. Front Cell Dev Biol 2022; 10:824961. [PMID: 35359443 PMCID: PMC8963869 DOI: 10.3389/fcell.2022.824961] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Accepted: 02/18/2022] [Indexed: 11/13/2022] Open
Abstract
Ras and Rab interactor 3 (RIN3) functions as a Guanine nucleotide Exchange Factor (GEF) for some members of the Rab family of small GTPase. By promoting the activation of Rab5, RIN3 plays an important role in regulating endocytosis and endocytic trafficking. In addition, RIN3 activates Ras, another small GTPase, that controls multiple signaling pathways to regulate cellular function. Increasing evidence suggests that dysregulation of RIN3 activity may contribute to the pathogenesis of several disease conditions ranging from Paget’s Disease of the Bone (PDB), Alzheimer’s Disease (AD), Chronic Obstructive Pulmonary Disease (COPD) and to obesity. Recent genome-wide association studies (GWAS) identified variants in the RIN3 gene to be linked with these disease conditions. Interestingly, some variants appear to be missense mutations in the functional domains of the RIN3 protein while most variants are located in the noncoding regions of the RIN3 gene, potentially altering its gene expression. However, neither the protein structure of RIN3 nor its exact function(s) (except for its GEF activity) has been fully defined. Furthermore, how the polymorphisms/variants contribute to disease pathogenesis remain to be understood. Herein, we examine, and review published studies in an attempt to provide a better understanding of the physiological function of RIN3; More importantly, we construct a framework linking the polymorphisms/variants of RIN3 to altered cell signaling and endocytic traffic, and to potential disease mechanism(s).
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Affiliation(s)
- Ruinan Shen
- Institute of Neurology, Ruijing Hospital, Shanghai JiaoTong University School of Medicine, Shanghai, China
- Department of Neurosciences, University of California San Diego School of Medicine, La Jolla, CA, United States
| | - Caitlin J Murphy
- Department of Neurosciences, University of California San Diego School of Medicine, La Jolla, CA, United States
| | - Xiaowen Xu
- Department of Neurosciences, University of California San Diego School of Medicine, La Jolla, CA, United States
| | - Mingzheng Hu
- Department of Neurosciences, University of California San Diego School of Medicine, La Jolla, CA, United States
| | - Jianqing Ding
- Institute of Neurology, Ruijing Hospital, Shanghai JiaoTong University School of Medicine, Shanghai, China
| | - Chengbiao Wu
- Department of Neurosciences, University of California San Diego School of Medicine, La Jolla, CA, United States
- *Correspondence: Chengbiao Wu,
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23
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Zhang Q, Zhang X, Zhang J, Wang B, Meng X, Tian Q, Zhang J, Jiang M, Zhang Y, Zheng D, Wu L, Wang W, Wang B, Wang Y. Causal Relationship Between Lung Function and Atrial Fibrillation: A Two Sample Univariable and Multivariable, Bidirectional Mendelian Randomization Study. Front Cardiovasc Med 2021; 8:769198. [PMID: 34869686 PMCID: PMC8635999 DOI: 10.3389/fcvm.2021.769198] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Accepted: 10/21/2021] [Indexed: 12/02/2022] Open
Abstract
Background: Observational studies have identified impaired lung function accessed by forced expiratory volume in one second (FEV1), forced vital capacity (FVC) or the ratio of FEV1 over FVC (FEV1/FVC) as an independent risk factor for atrial fibrillation (AF). However, the result may be affected by confounders or reverse causality. Methods: We performed univariable MR (uvMR), multivariable MR (mvMR) and bidirectional two-sample MR to jointly estimate the causality of lung function with AF. Apart from the inverse variance weighted (IVW) approach as the main MR analysis, three complementary sensitive analyses approaches including MR-Egger regression, weighted median (WM) MR and Pleiotropy Residual Sum and Outlier (MR-PRESSO) in uvMR as well as mvMR-Egger and mvMR-PRESSO in mvMR were applied to control for pleiotropy. Linkage disequilibrium score (LDSC) regression was applied to estimate genetic correlation between lung function and AF. Results: All forward and reverse uvMR analyses consistently suggested absent causal relations between lung function and AF risk [forward IVW: odds ratio (OR)FEV1 = 1.031, 95% CI = 0.909–1.169, P = 0.630; ORFVC = 1.002, 95% CI = 0.834–1.204, P = 0.982; ORFEV1/FVC = 1.076, 95% CI = 0.966–1.199, P = 0.182; reverse IVW: ORFEV1 = 0.986, 95% CI = 0.966–1.007, P = 0.187; ORFVC = 0.985, 95% CI = 0.965–1.006, P = 0.158; ORFEV1/FVC = 0.994, 95% CI = 0.973–1.015, P = 0.545]. The forward MR-Egger showed that each standard deviation (SD) increase in FEV1/FVC was related to a higher AF risk (OR = 1.502, 95% CI = 1.178–1.915, P = 0.006) without heterogeneity (Q_pval = 0.064), but pleiotropy effect exist (intercept = −0.017, P = 0.012). However, this significant effect disappeared after adjustment of FEV1 and FVC (OR = 1.523, 95% CI = 0.445–5.217, P = 0.503) in mvMR. No evidence was found for independent causal effects of FEV1 and FVC on AF in mvMR analysis by using mvIVW method (ORFEV1 = 0.501, 95% CI = 0.056–4.457, P = 0.496; ORFVC = 1.969, 95% CI = 0.288–13.474, P = 0.490). Notably, the association between lung function and AF were replicated using the FinnGen cohort data. Conclusions: Our findings reported no coheritability between lung function and AF, and failed to find substantial causal relation between decreased lung function and risk of AF. However, lung function and AF were both associated with inflammation, which may be potential pathway, warranting further study.
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Affiliation(s)
- Qiaoyun Zhang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
| | - Xiaoyu Zhang
- Department of Anesthesiology, Sanbo Brain Hospital, Capital Medical University, Beijing, China
| | - Jie Zhang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
| | - Biyan Wang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
| | - Xiaoni Meng
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
| | - Qiuyue Tian
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
| | - Jinxia Zhang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
| | - Mengyang Jiang
- Department of Anesthesiology, Sanbo Brain Hospital, Capital Medical University, Beijing, China
| | - Yiqiang Zhang
- Department of Anesthesiology, Sanbo Brain Hospital, Capital Medical University, Beijing, China
| | - Deqiang Zheng
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
| | - Lijuan Wu
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
| | - Wei Wang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China.,Centre for Precision Health, Edith Cowan University, Joondalup, WA, Australia
| | - Baoguo Wang
- Department of Anesthesiology, Sanbo Brain Hospital, Capital Medical University, Beijing, China
| | - Youxin Wang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China.,Centre for Precision Health, Edith Cowan University, Joondalup, WA, Australia
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24
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Zhu Z, Li J, Si J, Ma B, Shi H, Lv J, Cao W, Guo Y, Millwood IY, Walters RG, Lin K, Yang L, Chen Y, Du H, Yu B, Hasegawa K, Camargo CA, Moffatt MF, Cookson WOC, Chen J, Chen Z, Li L, Yu C, Liang L. A large-scale genome-wide association analysis of lung function in the Chinese population identifies novel loci and highlights shared genetic aetiology with obesity. Eur Respir J 2021; 58:2100199. [PMID: 33766948 PMCID: PMC8513692 DOI: 10.1183/13993003.00199-2021] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2020] [Accepted: 03/02/2021] [Indexed: 01/25/2023]
Abstract
BACKGROUND Lung function is a heritable complex phenotype with obesity being one of its important risk factors. However, knowledge of their shared genetic basis is limited. Most genome-wide association studies (GWASs) for lung function have been based on European populations, limiting the generalisability across populations. Large-scale lung function GWASs in other populations are lacking. METHODS We included 100 285 subjects from the China Kadoorie Biobank (CKB). To identify novel loci for lung function, single-trait GWAS analyses were performed on forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC) and FEV1/FVC in the CKB. We then performed genome-wide cross-trait analysis between lung function and obesity traits (body mass index (BMI), BMI-adjusted waist-to-hip ratio and BMI-adjusted waist circumference) to investigate the shared genetic effects in the CKB. Finally, polygenic risk scores (PRSs) of lung function were developed in the CKB and their interaction with BMI's association on lung function were examined. We also conducted cross-trait analysis in parallel with the CKB using up to 457 756 subjects from the UK Biobank (UKB) for replication and investigation of ancestry-specific effects. RESULTS We identified nine genome-wide significant novel loci for FEV1, six for FVC and three for FEV1/FVC in the CKB. FEV1 and FVC showed significant negative genetic correlation with obesity traits in both the CKB and UKB. Genetic loci shared between lung function and obesity traits highlighted important biological pathways, including cell proliferation, embryo, skeletal and tissue development, and regulation of gene expression. Mendelian randomisation analysis suggested significant negative causal effects of BMI on FEV1 and on FVC in both the CKB and UKB. Lung function PRSs significantly modified the effect of change in BMI on change in lung function during an average follow-up of 8 years. CONCLUSION This large-scale GWAS of lung function identified novel loci and shared genetic aetiology between lung function and obesity. Change in BMI might affect change in lung function differently according to a subject's polygenic background. These findings may open new avenues for the development of molecular-targeted therapies for obesity and lung function improvement.
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Affiliation(s)
- Zhaozhong Zhu
- Program in Genetic Epidemiology and Statistical Genetics, Dept of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Dept of Emergency Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- These four authors contributed equally to this article
| | - Jiachen Li
- Dept of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
- These four authors contributed equally to this article
| | - Jiahui Si
- Program in Genetic Epidemiology and Statistical Genetics, Dept of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Dept of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
- These four authors contributed equally to this article
| | - Baoshan Ma
- College of Information Science and Technology, Dalian Maritime University, Dalian, China
- These four authors contributed equally to this article
| | - Huwenbo Shi
- Program in Genetic Epidemiology and Statistical Genetics, Dept of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Jun Lv
- Dept of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
- Key Laboratory of Molecular Cardiovascular Sciences (Peking University), Ministry of Education, Beijing, China
- Peking University Institute of Environmental Medicine, Beijing, China
| | - Weihua Cao
- Dept of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Yu Guo
- Chinese Academy of Medical Sciences, Beijing, China
| | - Iona Y Millwood
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, UK
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Dept of Population Health, University of Oxford, Oxford, UK
| | - Robin G Walters
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, UK
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Dept of Population Health, University of Oxford, Oxford, UK
| | - Kuang Lin
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, UK
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Dept of Population Health, University of Oxford, Oxford, UK
| | - Ling Yang
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, UK
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Dept of Population Health, University of Oxford, Oxford, UK
| | - Yiping Chen
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, UK
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Dept of Population Health, University of Oxford, Oxford, UK
| | - Huaidong Du
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, UK
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Dept of Population Health, University of Oxford, Oxford, UK
| | - Bo Yu
- NCDs Prevention and Control Dept, Nangang CDC, Harbin, China
| | - Kohei Hasegawa
- Dept of Emergency Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Carlos A Camargo
- Program in Genetic Epidemiology and Statistical Genetics, Dept of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Dept of Emergency Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Miriam F Moffatt
- Section of Genomic Medicine, National Heart and Lung Institute, Imperial College London, London, UK
| | - William O C Cookson
- Section of Genomic Medicine, National Heart and Lung Institute, Imperial College London, London, UK
| | - Junshi Chen
- China National Center for Food Safety Risk Assessment, Beijing, China
| | - Zhengming Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Dept of Population Health, University of Oxford, Oxford, UK
| | - Liming Li
- Dept of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Canqing Yu
- Dept of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
- These two authors contributed equally to this article as lead authors and supervised the work
| | - Liming Liang
- Program in Genetic Epidemiology and Statistical Genetics, Dept of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Dept of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- These two authors contributed equally to this article as lead authors and supervised the work
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25
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Rare and low-frequency exonic variants and gene-by-smoking interactions in pulmonary function. Sci Rep 2021; 11:19365. [PMID: 34588469 PMCID: PMC8481467 DOI: 10.1038/s41598-021-98120-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2020] [Accepted: 09/02/2021] [Indexed: 02/08/2023] Open
Abstract
Genome-wide association studies have identified numerous common genetic variants associated with spirometric measures of pulmonary function, including forced expiratory volume in one second (FEV1), forced vital capacity, and their ratio. However, variants with lower minor allele frequencies are less explored. We conducted a large-scale gene-smoking interaction meta-analysis on exonic rare and low-frequency variants involving 44,429 individuals of European ancestry in the discovery stage and sought replication in the UK BiLEVE study with 45,133 European ancestry samples and UK Biobank study with 59,478 samples. We leveraged data on cigarette smoking, the major environmental risk factor for reduced lung function, by testing gene-by-smoking interaction effects only and simultaneously testing the genetic main effects and interaction effects. The most statistically significant signal that replicated was a previously reported low-frequency signal in GPR126, distinct from common variant associations in this gene. Although only nominal replication was obtained for a top rare variant signal rs142935352 in one of the two studies, interaction and joint tests for current smoking and PDE3B were significantly associated with FEV1. This study investigates the utility of assessing gene-by-smoking interactions and underscores their effects on potential pulmonary function.
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26
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Santanasto AJ, Wojczynski MK, Cvejkus RK, Lin S, Wang L, Thyagarajan B, Christensen K, Schupf N, Feitosa MF, An P, Zmuda JM. Identification of a Novel Locus for Gait Speed Decline With Aging: The Long Life Family Study. J Gerontol A Biol Sci Med Sci 2021; 76:e307-e313. [PMID: 34156441 PMCID: PMC8436996 DOI: 10.1093/gerona/glab177] [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: 12/11/2020] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND Gait speed is a powerful indicator of health with aging. Potential genetic contributions to gait speed and its decline with aging are not well defined. We determined the heritability of and potential genetic regions underlying change in gait speed using longitudinal data from 2379 individuals belonging to 509 families in the Long Life Family Study (mean age 64 ± 12, range 30-110 years; 45% men). METHODS Gait speed was measured over 4 m at baseline and follow-up (7 ± 1 years). Quantitative trait linkage analyses were completed using pedigree-based maximum likelihood methods with logarithm of the odds (LOD) scores greater than 3.0, indicating genome-wide significance. We also performed linkage analysis in the top 10% of families contributing to LOD scores to allow for heterogeneity among families (HLOD). Data were adjusted for age, sex, height, and field center. RESULTS At baseline, 26.9% of individuals had "slow" gait speed less than 1.0 m/s (mean: 1.1 ± 0.2 m/s) and gait speed declined at a rate of -0.02 ± 0.03 m/s per year (p < .0001). Baseline and change in gait speed were significantly heritable (h2 = 0.24-0.32, p < .05). We did not find significant evidence for linkage for baseline gait speed; however, we identified a significant locus for change in gait speed on chromosome 16p (LOD = 4.2). A subset of 21 families contributed to this linkage peak (HLOD = 6.83). Association analyses on chromosome 16 showed that the strongest variant resides within the ADCY9 gene. CONCLUSION Further analysis of the chromosome 16 region, and ADCY9 gene, may yield new insight on the biology of mobility decline with aging.
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Affiliation(s)
- Adam J Santanasto
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pennsylvania, USA
| | - Mary K Wojczynski
- Department of Genetics, Division of Statistical Genomics, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Ryan K Cvejkus
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pennsylvania, USA
| | - Shiow Lin
- Department of Genetics, Division of Statistical Genomics, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Lihua Wang
- Department of Genetics, Division of Statistical Genomics, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Bharat Thyagarajan
- Department of Laboratory Medicine and Pathology, School of Medicine, University of Minnesota, Minneapolis, USA
| | - Kaare Christensen
- The Danish Aging Research Center, Epidemiology Unit, Institute of Public Health, University of Southern Denmark, Odense, Denmark
| | - Nicole Schupf
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, USA
| | - Mary F Feitosa
- Department of Genetics, Division of Statistical Genomics, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Ping An
- Department of Genetics, Division of Statistical Genomics, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Joseph M Zmuda
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pennsylvania, USA
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27
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Slob EMA, Richards LB, Vijverberg SJH, Longo C, Koppelman GH, Pijnenburg MWH, Bel EHD, Neerincx AH, Herrera Luis E, Perez-Garcia J, Tim Chew F, Yie Sio Y, Andiappan AK, Turner SW, Mukhopadhyay S, Palmer CNA, Hawcutt D, Jorgensen AL, Burchard EG, Hernandez-Pacheco N, Pino-Yanes M, Maitland-van der Zee AH. Genome-wide association studies of exacerbations in children using long-acting beta2-agonists. Pediatr Allergy Immunol 2021; 32:1197-1207. [PMID: 33706416 PMCID: PMC8328929 DOI: 10.1111/pai.13494] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/06/2021] [Revised: 03/01/2021] [Accepted: 03/03/2021] [Indexed: 12/30/2022]
Abstract
BACKGROUND Some children with asthma experience exacerbations despite long-acting beta2-agonist (LABA) treatment. While this variability is partly caused by genetic variation, no genome-wide study until now has investigated which genetic factors associated with risk of exacerbations despite LABA use in children with asthma. We aimed to assess whether genetic variation was associated with exacerbations in children treated with LABA from a global consortium. METHODS A meta-analysis of genome-wide association studies (meta-GWAS) was performed in 1,425 children and young adults with asthma (age 6-21 years) with reported regular use of LABA from six studies within the PiCA consortium using a random effects model. The primary outcome of each study was defined as any exacerbation within the past 6 or 12 months, including at least one of the following: 1) hospital admissions for asthma, 2) a course of oral corticosteroids or 3) emergency room visits because of asthma. RESULTS Genome-wide association results for a total of 82 996 common single nucleotide polymorphisms (SNPs, MAF ≥1%) with high imputation quality were meta-analysed. Eight independent variants were suggestively (P-value threshold ≤5 × 10-6 ) associated with exacerbations despite LABA use. CONCLUSION No strong effects of single nucleotide polymorphisms (SNPs) on exacerbations during LABA use were identified. We identified two loci (TBX3 and EPHA7) that were previously implicated in the response to short-acting beta2-agonists (SABA). These loci merit further investigation in response to LABA and SABA use.
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Affiliation(s)
- Elise M A Slob
- Department of Respiratory Disease, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands.,Pediatric Respiratory Medicine, Emma Children's Hospital, Amsterdam UMC, Amsterdam, The Netherlands
| | - Levi B Richards
- Department of Respiratory Disease, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Susanne J H Vijverberg
- Department of Respiratory Disease, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands.,Pediatric Respiratory Medicine, Emma Children's Hospital, Amsterdam UMC, Amsterdam, The Netherlands.,Division of Pharmacoepidemiology and Clinical Pharmacology, Faculty of Science, Utrecht University, Utrecht, Netherlands
| | - Cristina Longo
- Department of Respiratory Disease, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Gerard H Koppelman
- Department of Paediatric, Pulmonology & Paediatric Allergology, University Medical Center Groningen, Beatrix Children's Hospital, University of Groningen, Groningen, The Netherlands.,University Medical Center Groningen, Groningen Research Institute for Asthma & COPD (GRIAC), University of Groningen, Groningen, The Netherlands
| | - Mariëlle W H Pijnenburg
- Division of Respiratory Medicine and Allergology, Department of Paediatrics, Erasmus MC - Sophia, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Elisabeth H D Bel
- Department of Respiratory Disease, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Anne H Neerincx
- Department of Respiratory Disease, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Esther Herrera Luis
- Genomics and Health Group, Department of Biochemistry, Microbiology, Cell Biology and Genetics, Universidad de La Laguna, Santa Cruz de Tenerife, Spain
| | - Javier Perez-Garcia
- Genomics and Health Group, Department of Biochemistry, Microbiology, Cell Biology and Genetics, Universidad de La Laguna, Santa Cruz de Tenerife, Spain
| | - Fook Tim Chew
- Singapore Immunology Network (SIgN), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
| | - Yang Yie Sio
- Singapore Immunology Network (SIgN), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
| | - Anand K Andiappan
- Singapore Immunology Network (SIgN), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore.,Department of Biological Sciences, National University of Singapore, Singapore, Singapore
| | - Steve W Turner
- Department of Child Health, University of Aberdeen, Aberdeen, UK
| | - Somnath Mukhopadhyay
- Academic Department of Paediatrics, Royal Alexandra Children's Hospital, Brighton and Sussex Medical School, Brighton, UK.,Population Pharmacogenetics Group, Biomedical Research Institute, Ninewells Hospital and Medical School, University of Dundee, Dundee, UK
| | - Colin N A Palmer
- Population Pharmacogenetics Group, Biomedical Research Institute, Ninewells Hospital and Medical School, University of Dundee, Dundee, UK
| | - Daniel Hawcutt
- Department of Women's and Children's Health, University of Liverpool, Liverpool, UK.,NIHR Alder Hey Clinical Research Facility, Alder Hey Children's Hospital, Liverpool, UK
| | - Andrea L Jorgensen
- Department of Health Data Science, University of Liverpool, Liverpool, UK
| | - Esteban G Burchard
- Department of Medicine, University of California San Francisco, San Francisco, CA, USA.,Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA
| | - Natalia Hernandez-Pacheco
- Genomics and Health Group, Department of Biochemistry, Microbiology, Cell Biology and Genetics, Universidad de La Laguna, Santa Cruz de Tenerife, Spain
| | - Maria Pino-Yanes
- Genomics and Health Group, Department of Biochemistry, Microbiology, Cell Biology and Genetics, Universidad de La Laguna, Santa Cruz de Tenerife, Spain.,Research Unit, Hospital Universitario N.S. de Candelaria, Universidad de La Laguna, Santa Cruz de Tenerife, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Instituto de Salud Carlos III, Madrid, Spain.,Instituto de Tecnologías Biomédicas (ITB), Universidad de La Laguna, Santa Cruz de Tenerife, Spain
| | - Anke H Maitland-van der Zee
- Department of Respiratory Disease, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands.,Pediatric Respiratory Medicine, Emma Children's Hospital, Amsterdam UMC, Amsterdam, The Netherlands.,Division of Pharmacoepidemiology and Clinical Pharmacology, Faculty of Science, Utrecht University, Utrecht, Netherlands
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Harbaum L, Hennigs JK, Simon M, Oqueka T, Watz H, Klose H. Genetic evidence for a causative effect of airflow obstruction on left ventricular filling: a Mendelian randomisation study. Respir Res 2021; 22:199. [PMID: 34233669 PMCID: PMC8261939 DOI: 10.1186/s12931-021-01795-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Accepted: 06/30/2021] [Indexed: 11/10/2022] Open
Abstract
Background Observational studies on the general population have suggested that airflow obstruction associates with left ventricular (LV) filling. To limit the influence of environmental risk factors/exposures, we used a Mendelian randomisation (MR) approach based on common genetic variations and tested whether a causative relation between airflow obstruction and LV filling can be detected. Methods We used summary statistics from large genome-wide association studies (GWAS) on the ratio of forced expiratory volume in 1 s to forced vital capacity (FEV1/FVC) measured by spirometry and the LV end-diastolic volume (LVEDV) as assessed by cardiac magnetic resonance imaging. The primary MR was based on an inverse variance weighted regression. Various complementary MR methods and subsets of the instrument variables were used to assess the plausibility of the findings. Results We obtained consistent evidence in our primary MR analysis and subsequent sensitivity analyses that reducing airflow obstruction leads to increased inflow to the LV (odds ratio [OR] from inverse variance weighted regression 1.05, 95% confidence interval [CI] 1.01–1.09, P = 0.0172). Sensitivity analyses indicated a certain extent of negative horizontal pleiotropy and the estimate from biased-corrected MR-Egger was adjusted upward (OR 1.2, 95% CI 1.09–1.31, P < 0.001). Prioritisation of single genetic variants revealed rs995758, rs2070600 and rs7733410 as major contributors to the MR result. Conclusion Our findings indicate a causal relationship between airflow obstruction and LV filling in the general population providing genetic context to observational associations. The results suggest that targeting (even subclinical) airflow obstruction can lead to direct cardiac improvements, demonstrated by an increase in LVEDV. Functional annotation of single genetic variants contributing most to the causal effect estimate could help to prioritise biological underpinnings. Supplementary Information The online version contains supplementary material available at 10.1186/s12931-021-01795-9.
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Affiliation(s)
- Lars Harbaum
- Abteilung für Pneumologie, Centrum für Pulmonal Arterielle Hypertonie Hamburg (CPAHH), Universitätsklinikum Hamburg-Eppendorf, Hamburg, Germany.
| | - Jan K Hennigs
- Abteilung für Pneumologie, Centrum für Pulmonal Arterielle Hypertonie Hamburg (CPAHH), Universitätsklinikum Hamburg-Eppendorf, Hamburg, Germany
| | - Marcel Simon
- Abteilung für Pneumologie, Centrum für Pulmonal Arterielle Hypertonie Hamburg (CPAHH), Universitätsklinikum Hamburg-Eppendorf, Hamburg, Germany
| | - Tim Oqueka
- Abteilung für Pneumologie, Centrum für Pulmonal Arterielle Hypertonie Hamburg (CPAHH), Universitätsklinikum Hamburg-Eppendorf, Hamburg, Germany
| | - Henrik Watz
- Pneumologische Forschungsinstitut an der LungenClinic Grosshansdorf, Airway Research Center North (ARCN), German Center for Lung Research (DZL), Grosshansdorf, Germany
| | - Hans Klose
- Abteilung für Pneumologie, Centrum für Pulmonal Arterielle Hypertonie Hamburg (CPAHH), Universitätsklinikum Hamburg-Eppendorf, Hamburg, Germany
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29
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Hall RJ, O'Loughlin J, Billington CK, Thakker D, Hall IP, Sayers I. Functional genomics of GPR126 in airway smooth muscle and bronchial epithelial cells. FASEB J 2021; 35:e21300. [PMID: 34165809 DOI: 10.1096/fj.202002073r] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Revised: 12/01/2020] [Accepted: 12/07/2020] [Indexed: 12/12/2022]
Abstract
GPR126 is an adhesion G protein-coupled receptor which lies on chromosome 6q24. Genetic variants in this region are reproducibly associated with lung function and COPD in genome wide association studies (GWAS). The aims of this study were to define the role of GPR126 in the human lung and in pulmonary disease and identify possible casual variants. Online tools (GTEx and LDlink) identified SNPs which may have effects on GPR126 function/ expression, including missense variant Ser123Gly and an intronic variant that shows eQTL effects on GPR126 expression. GPR126 signaling via cAMP-mediated pathways was identified in human structural airway cells when activated with the tethered agonist, stachel. RNA-seq was used to identify downstream genes/ pathways affected by stachel-mediated GPR126 activation in human airway smooth muscle cells. We identified ~350 differentially expressed genes at 4 and 24 hours post stimulation with ~20% overlap. We identified that genes regulated by GPR126 activation include IL33, CTGF, and SERPINE1, which already have known roles in lung biology. Pathways altered by GPR126 included those involved in cell cycle progression and cell proliferation. Here, we suggest a role for GPR126 in airway remodeling.
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Affiliation(s)
- Robert J Hall
- Division of Respiratory Medicine, National Institute for Health Research, Nottingham Biomedical Research Centre, Biodiscovery Institute, University of Nottingham, Nottingham, UK
| | - Jonathan O'Loughlin
- Division of Respiratory Medicine, National Institute for Health Research, Nottingham Biomedical Research Centre, Biodiscovery Institute, University of Nottingham, Nottingham, UK
| | - Charlotte K Billington
- Division of Respiratory Medicine, National Institute for Health Research, Nottingham Biomedical Research Centre, Biodiscovery Institute, University of Nottingham, Nottingham, UK
| | - Dhruma Thakker
- Division of Respiratory Medicine, National Institute for Health Research, Nottingham Biomedical Research Centre, Biodiscovery Institute, University of Nottingham, Nottingham, UK
| | - Ian P Hall
- Division of Respiratory Medicine, National Institute for Health Research, Nottingham Biomedical Research Centre, Biodiscovery Institute, University of Nottingham, Nottingham, UK
| | - Ian Sayers
- Division of Respiratory Medicine, National Institute for Health Research, Nottingham Biomedical Research Centre, Biodiscovery Institute, University of Nottingham, Nottingham, UK
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30
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Zhang PD, Zhang XR, Zhang A, Li ZH, Liu D, Zhang YJ, Mao C. Associations of genetic risk and smoking with incident chronic obstructive pulmonary disease. Eur Respir J 2021; 59:13993003.01320-2021. [PMID: 34172472 DOI: 10.1183/13993003.01320-2021] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Accepted: 06/14/2021] [Indexed: 11/05/2022]
Abstract
BACKGROUND Genetic and smoking contribute to chronic obstructive pulmonary disease (COPD), but whether a combined polygenic risk score (PRS) is associated with incident COPD and whether it has a synergistic effect on the smoking remains unclear. We aimed to investigate the association of PRS with COPD and explore whether smoking behaviors could modify such association. METHODS Multivariable Cox proportional models were used to estimate hazard ratios (HRs) and 95% confidence intervals (95% CIs) for the association of the PRS and smoking with COPD. RESULTS The study included 439 255 participants (mean age 56.5; 53.9% female), with a median follow-up of 9.0 years. The PRSlasso containing 2.5 million variants showed better discrimination and a stronger association for incident COPD than the PRS279 containing 279 genome-wide significance variants. Compared with the low genetic risk, the HRs of the medium and high genetic risk were 1.39 (95% CI, 1.31-1.48) and 2.40 (95% CI, 2.24-2.56), respectively. The HR of high genetic risk and current smoking was 11.62 (95% CI, 10.31-13.10) times of low genetic risk and never smoking. There were significant interactions between the PRSlasso and smoking status for incident COPD (p for interaction<0.001). From low genetic risk to high genetic risk, the HRs of current smoking increased from 4.32 (95% CI, 3.69-5.06) to 6.89 (95% CI, 6.21-7.64), and the population-attributable risks of smoking increased from 42.7% to 61.1%. CONCLUSION PRS constructed from millions of variants below genome-wide significance showed significant associations with incident COPD. Participants with a high genetic risk may be more susceptible to developing COPD when exposed to smoking.
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Affiliation(s)
- Pei-Dong Zhang
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, Guangdong, China.,The Laboratory for Precision Neurosurgery, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China.,Pei-Dong Zhang and Xi-Ru Zhang contributed to the work equally
| | - Xi-Ru Zhang
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, Guangdong, China.,Pei-Dong Zhang and Xi-Ru Zhang contributed to the work equally
| | - Ao Zhang
- State Key Laboratory of Molecular Neuroscience and Center of Systems Biology and Human Health, Division of Life Science, Hong Kong University of Science and Technology, Hong Kong, China
| | - Zhi-Hao Li
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, Guangdong, China
| | - Dan Liu
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, Guangdong, China
| | - Yu-Jie Zhang
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, Guangdong, China
| | - Chen Mao
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, Guangdong, China .,Department of Laboratory Medicine, Microbiome Medicine Center, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China
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31
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Fawcett KA, Obeidat M, Melbourne C, Shrine N, Guyatt AL, John C, Luan J, Richmond A, Moksnes MR, Granell R, Weiss S, Imboden M, May-Wilson S, Hysi P, Boutin TS, Portas L, Flexeder C, Harris SE, Wang CA, Lyytikäinen LP, Palviainen T, Foong RE, Keidel D, Minelli C, Langenberg C, Bossé Y, Van den Berge M, Sin DD, Hao K, Campbell A, Porteous D, Padmanabhan S, Smith BH, Evans DM, Ring S, Langhammer A, Hveem K, Willer C, Ewert R, Stubbe B, Pirastu N, Klaric L, Joshi PK, Patasova K, Massimo M, Polasek O, Starr JM, Karrasch S, Strauch K, Meitinger T, Rudan I, Rantanen T, Pietiläinen K, Kähönen M, Raitakari OT, Hall GL, Sly PD, Pennell CE, Kaprio J, Lehtimäki T, Vitart V, Deary IJ, Jarvis D, Wilson JF, Spector T, Probst-Hensch N, Wareham NJ, Völzke H, Henderson J, Strachan DP, Brumpton BM, Hayward C, Hall IP, Tobin MD, Wain LV. Variants associated with HHIP expression have sex-differential effects on lung function. Wellcome Open Res 2021; 5:111. [PMID: 33728380 PMCID: PMC7938335 DOI: 10.12688/wellcomeopenres.15846.2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/19/2021] [Indexed: 02/02/2023] Open
Abstract
Background: Lung function is highly heritable and differs between the sexes throughout life. However, little is known about sex-differential genetic effects on lung function. We aimed to conduct the first genome-wide genotype-by-sex interaction study on lung function to identify genetic effects that differ between males and females. Methods: We tested for interactions between 7,745,864 variants and sex on spirometry-based measures of lung function in UK Biobank (N=303,612), and sought replication in 75,696 independent individuals from the SpiroMeta consortium. Results: Five independent single-nucleotide polymorphisms (SNPs) showed genome-wide significant (P<5x10 -8) interactions with sex on lung function, and 21 showed suggestive interactions (P<1x10 -6). The strongest signal, from rs7697189 (chr4:145436894) on forced expiratory volume in 1 second (FEV 1) (P=3.15x10 -15), was replicated (P=0.016) in SpiroMeta. The C allele increased FEV 1 more in males (untransformed FEV 1 β=0.028 [SE 0.0022] litres) than females (β=0.009 [SE 0.0014] litres), and this effect was not accounted for by differential effects on height, smoking or pubertal age. rs7697189 resides upstream of the hedgehog-interacting protein ( HHIP) gene and was previously associated with lung function and HHIP lung expression. We found HHIP expression was significantly different between the sexes (P=6.90x10 -6), but we could not detect sex differential effects of rs7697189 on expression. Conclusions: We identified a novel genotype-by-sex interaction at a putative enhancer region upstream of the HHIP gene. Establishing the mechanism by which HHIP SNPs have different effects on lung function in males and females will be important for our understanding of lung health and diseases in both sexes.
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Affiliation(s)
| | - Ma'en Obeidat
- The University of British Columbia Centre for Heart Lung Innovation, St Paul’s Hospital, Vancouver, BC, Canada
| | - Carl Melbourne
- Department of Health Sciences, University of Leicester, Leicester, LE1 7RH, UK
| | - Nick Shrine
- Department of Health Sciences, University of Leicester, Leicester, LE1 7RH, UK
| | - Anna L. Guyatt
- Department of Health Sciences, University of Leicester, Leicester, LE1 7RH, UK
| | - Catherine John
- Department of Health Sciences, University of Leicester, Leicester, LE1 7RH, UK
| | - Jian'an Luan
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0QQ, UK
| | - Anne Richmond
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK
| | - Marta R. Moksnes
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Raquel Granell
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, BS8 2BN, UK
| | - Stefan Weiss
- Department of Functional Genomics, Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, 17475, Germany
| | - Medea Imboden
- Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Sebastian May-Wilson
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, UK
| | - Pirro Hysi
- The Department of Twin Research & Genetic Epidemiology, King’s College London, St Thomas’ Campus, Lambeth Palace Road, London, UK
| | - Thibaud S. Boutin
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK
| | - Laura Portas
- Population Health and Occupational Disease, National Heart and Lung Institute, Imperial College London, London, UK
| | - Claudia Flexeder
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, 85764, Germany
| | - Sarah E. Harris
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
- Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Carol A. Wang
- School of Medicine and Public Health, Faculty of Medicine and Health, The University of Newcastle, Callaghan, Australia
| | - Leo-Pekka Lyytikäinen
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, 33520, Finland
- Department of Clinical Chemistry, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, 33014, Finland
- Department of Cardiology, Heart Center, Tampere University Hospital, Tampere, 33521, Finland
| | - Teemu Palviainen
- Institute for Molecular Medicine FIMM, University of Helsinki, Helsinki, FI-00014, Finland
| | - Rachel E. Foong
- Telethon Kids Institute, Perth, Australia
- School of Physiotherapy and Exercise Science, Faculty of Health Sciences, Curtin University, Perth, Australia
| | - Dirk Keidel
- Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Cosetta Minelli
- Population Health and Occupational Disease, National Heart and Lung Institute, Imperial College London, London, UK
| | - Claudia Langenberg
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0QQ, UK
| | - Yohan Bossé
- Institut universitaire de cardiologie et de pneumologie de Québec, Department of Molecular Medicine, Laval University, Québec, Canada
| | - Maarten Van den Berge
- University Medical Center Groningen, Department of Pulmonology, GRIAC Research Institute, University of Groningen, Groningen, The Netherlands
| | - Don D. Sin
- The University of British Columbia Centre for Heart Lung Innovation, St Paul’s Hospital, Vancouver, BC, Canada
- Respiratory Division, Department of Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Ke Hao
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, EH4 2XU, UK
| | - David Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, EH4 2XU, UK
| | - Sandosh Padmanabhan
- British Heart Foundation Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, G12 8TA, UK
| | - Blair H. Smith
- Division of Population Health Sciences, Ninewells Hospital and Medical School, University of Dundee, Dundee, DD1 9SY, UK
| | - David M. Evans
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, BS8 2BN, UK
- Population Health Sciences Bristol Medical School, University of Bristol, Bristol, BS8 2BN, UK
- University of Queensland Diamantina Institute, Translational Research Institute, Brisbane, QLD 4072, Australia
| | - Sue Ring
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, BS8 2BN, UK
- Population Health Sciences Bristol Medical School, University of Bristol, Bristol, BS8 2BN, UK
| | - Arnulf Langhammer
- Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Kristian Hveem
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Cristen Willer
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, USA
- Department of Internal Medicine, University of Michigan, Ann Arbor, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, USA
| | - Ralf Ewert
- Department of Internal Medicine B, Cardiology, Pneumology, Infectious Diseases, Intensive Care Medicine, University Medicine Greifswald, Greifswald, 17475, Germany
| | - Beate Stubbe
- Department of Internal Medicine B, Cardiology, Pneumology, Infectious Diseases, Intensive Care Medicine, University Medicine Greifswald, Greifswald, 17475, Germany
| | - Nicola Pirastu
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, UK
| | - Lucija Klaric
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK
| | - Peter K. Joshi
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, UK
| | - Karina Patasova
- The Department of Twin Research & Genetic Epidemiology, King’s College London, St Thomas’ Campus, Lambeth Palace Road, London, UK
| | - Mangino Massimo
- The Department of Twin Research & Genetic Epidemiology, King’s College London, St Thomas’ Campus, Lambeth Palace Road, London, UK
| | - Ozren Polasek
- University of Split School of Medicine, Split, Croatia
| | - John M. Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
- Alzheimer Scotland Research Centre, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Stefan Karrasch
- Institute and Outpatient Clinic for Occupational, Social and Environmental Medicine, Ludwig-Maximilians-Universität, Munich, 80336, Germany
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, 85764, Germany
- Comprehensive Pneumology Center Munich (CPC-M), Member of the German Center for Lung Research (DZL), Munich, 81377, Germany
| | - Konstantin Strauch
- Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, 85764, Germany
- Chair of Genetic Epidemiology, IBE, Faculty of Medicine, LMU Munich, Munich, 81377, Germany
| | - Thomas Meitinger
- Institute of Human Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, 85764, Germany
- Institute of Human Genetics, Klinikum rechts der Isar der TU Muenchen, Muenchen, 81675, Germany
| | - Igor Rudan
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, UK
| | - Taina Rantanen
- Faculty of Sport and Health Sciences, Gerontology Research Center, University of Jyväskylä, Jyväskylä, Finland
| | - Kirsi Pietiläinen
- Obesity Research Unit, Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, FI-00014, Finland
- Obesity Centre, Abdominal Centre, Helsinki University Hospital and University of Helsinki, Helsinki, FI-00029, Finland
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital, Tampere, 33521, Finland
- Department of Clinical Physiology, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, 33014, Finland
| | - Olli T. Raitakari
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
| | - Graham L. Hall
- Telethon Kids Institute, Perth, Australia
- School of Physiotherapy and Exercise Science, Faculty of Health Sciences, Curtin University, Perth, Australia
| | - Peter D. Sly
- Children's Health and Environment Program, The University of Queensland, Brisbane, Australia
| | - Craig E. Pennell
- School of Medicine and Public Health, Faculty of Medicine and Health, The University of Newcastle, Callaghan, Australia
| | - Jaakko Kaprio
- Institute for Molecular Medicine FIMM, University of Helsinki, Helsinki, FI-00014, Finland
- Department of Public Health, University of Helsinki, Helsinki, FI-00014, Finland
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, 33520, Finland
- Department of Clinical Chemistry, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, 33014, Finland
| | - Veronique Vitart
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK
| | - Ian J. Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
- Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Debbie Jarvis
- Population Health and Occupational Disease, National Heart and Lung Institute, Imperial College London, London, UK
- MRC-PHE Centre for the Environment and Health, London, UK
| | - James F. Wilson
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, UK
| | - Tim Spector
- The Department of Twin Research & Genetic Epidemiology, King’s College London, St Thomas’ Campus, Lambeth Palace Road, London, UK
| | - Nicole Probst-Hensch
- Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Nicholas J. Wareham
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0QQ, UK
| | - Henry Völzke
- Intitute for Community Medicine, University Medicine Greifswald, Greifswald, 17487, Germany
| | - John Henderson
- Population Health Sciences Bristol Medical School, University of Bristol, Bristol, BS8 2BN, UK
| | - David P. Strachan
- Population Health Research Institute, St George's, University of London, London, SW17 0RE, UK
| | - Ben M. Brumpton
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Clinic of Thoracic and Occupational Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK
| | - Ian P. Hall
- Division of Respiratory Medicine and NIHR-Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, UK
| | - Martin D. Tobin
- Department of Health Sciences, University of Leicester, Leicester, LE1 7RH, UK
- National Institute for Health Research, Leicester Respiratory Biomedical Research Centre, Glenfield Hospital, Leicester, LE3 9QP, UK
| | - Louise V. Wain
- Department of Health Sciences, University of Leicester, Leicester, LE1 7RH, UK
- National Institute for Health Research, Leicester Respiratory Biomedical Research Centre, Glenfield Hospital, Leicester, LE3 9QP, UK
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32
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Geibel J, Reimer C, Pook T, Weigend S, Weigend A, Simianer H. How imputation can mitigate SNP ascertainment Bias. BMC Genomics 2021; 22:340. [PMID: 33980139 PMCID: PMC8114708 DOI: 10.1186/s12864-021-07663-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2021] [Accepted: 04/28/2021] [Indexed: 12/30/2022] Open
Abstract
Background Population genetic studies based on genotyped single nucleotide polymorphisms (SNPs) are influenced by a non-random selection of the SNPs included in the used genotyping arrays. The resulting bias in the estimation of allele frequency spectra and population genetics parameters like heterozygosity and genetic distances relative to whole genome sequencing (WGS) data is known as SNP ascertainment bias. Full correction for this bias requires detailed knowledge of the array design process, which is often not available in practice. This study suggests an alternative approach to mitigate ascertainment bias of a large set of genotyped individuals by using information of a small set of sequenced individuals via imputation without the need for prior knowledge on the array design. Results The strategy was first tested by simulating additional ascertainment bias with a set of 1566 chickens from 74 populations that were genotyped for the positions of the Affymetrix Axiom™ 580 k Genome-Wide Chicken Array. Imputation accuracy was shown to be consistently higher for populations used for SNP discovery during the simulated array design process. Reference sets of at least one individual per population in the study set led to a strong correction of ascertainment bias for estimates of expected and observed heterozygosity, Wright’s Fixation Index and Nei’s Standard Genetic Distance. In contrast, unbalanced reference sets (overrepresentation of populations compared to the study set) introduced a new bias towards the reference populations. Finally, the array genotypes were imputed to WGS by utilization of reference sets of 74 individuals (one per population) to 98 individuals (additional commercial chickens) and compared with a mixture of individually and pooled sequenced populations. The imputation reduced the slope between heterozygosity estimates of array data and WGS data from 1.94 to 1.26 when using the smaller balanced reference panel and to 1.44 when using the larger but unbalanced reference panel. This generally supported the results from simulation but was less favorable, advocating for a larger reference panel when imputing to WGS. Conclusions The results highlight the potential of using imputation for mitigation of SNP ascertainment bias but also underline the need for unbiased reference sets. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-021-07663-6.
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Affiliation(s)
- Johannes Geibel
- Department of Animal Sciences, Animal Breeding and Genetics Group, University of Goettingen, Albrecht-Thaer-Weg 3, 37075, Göttingen, Germany. .,Center for Integrated Breeding Research, University of Goettingen, Albrecht-Thaer-Weg 3, 37075, Göttingen, Germany.
| | - Christian Reimer
- Department of Animal Sciences, Animal Breeding and Genetics Group, University of Goettingen, Albrecht-Thaer-Weg 3, 37075, Göttingen, Germany.,Center for Integrated Breeding Research, University of Goettingen, Albrecht-Thaer-Weg 3, 37075, Göttingen, Germany
| | - Torsten Pook
- Department of Animal Sciences, Animal Breeding and Genetics Group, University of Goettingen, Albrecht-Thaer-Weg 3, 37075, Göttingen, Germany.,Center for Integrated Breeding Research, University of Goettingen, Albrecht-Thaer-Weg 3, 37075, Göttingen, Germany
| | - Steffen Weigend
- Center for Integrated Breeding Research, University of Goettingen, Albrecht-Thaer-Weg 3, 37075, Göttingen, Germany.,Institute of Farm Animal Genetics, Friedrich-Loeffler-Institut, Höltystrasse 10, 31535, Neustadt-Mariensee, Germany
| | - Annett Weigend
- Institute of Farm Animal Genetics, Friedrich-Loeffler-Institut, Höltystrasse 10, 31535, Neustadt-Mariensee, Germany
| | - Henner Simianer
- Department of Animal Sciences, Animal Breeding and Genetics Group, University of Goettingen, Albrecht-Thaer-Weg 3, 37075, Göttingen, Germany.,Center for Integrated Breeding Research, University of Goettingen, Albrecht-Thaer-Weg 3, 37075, Göttingen, Germany
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33
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Baxendale S, Asad A, Shahidan NO, Wiggin GR, Whitfield TT. The adhesion GPCR Adgrg6 (Gpr126): Insights from the zebrafish model. Genesis 2021; 59:e23417. [PMID: 33735533 PMCID: PMC11475505 DOI: 10.1002/dvg.23417] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2021] [Accepted: 02/16/2021] [Indexed: 12/13/2022]
Abstract
Adhesion GPCRs are important regulators of conserved developmental processes and represent an untapped pool of potential targets for drug discovery. The adhesion GPCR Adgrg6 (Gpr126) has critical developmental roles in Schwann cell maturation and inner ear morphogenesis in the zebrafish embryo. Mutations in the human ADGRG6 gene can result in severe deficits in peripheral myelination, and variants have been associated with many other disease conditions. Here, we review work on the zebrafish Adgrg6 signaling pathway and its potential as a disease model. Recent advances have been made in the analysis of the structure of the Adgrg6 receptor, demonstrating alternative structural conformations and the presence of a conserved calcium-binding site within the CUB domain of the extracellular region that is critical for receptor function. Homozygous zebrafish adgrg6 hypomorphic mutants have been used successfully as a whole-animal screening platform, identifying candidate molecules that can influence signaling activity and rescue mutant phenotypes. These compounds offer promise for further development as small molecule modulators of Adgrg6 pathway activity.
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Affiliation(s)
- Sarah Baxendale
- Department of Biomedical Science, Bateson Centre and Neuroscience InstituteUniversity of SheffieldSheffieldUK
| | - Anzar Asad
- Department of Biomedical Science, Bateson Centre and Neuroscience InstituteUniversity of SheffieldSheffieldUK
| | - Nahal O. Shahidan
- Department of Biomedical Science, Bateson Centre and Neuroscience InstituteUniversity of SheffieldSheffieldUK
| | | | - Tanya T. Whitfield
- Department of Biomedical Science, Bateson Centre and Neuroscience InstituteUniversity of SheffieldSheffieldUK
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34
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Lee KS, Kim KH, Oh YM, Han B, Kim WJ. A genome wide association study for lung function in the Korean population using an exome array. Korean J Intern Med 2021; 36:S142-S150. [PMID: 32336055 PMCID: PMC8009153 DOI: 10.3904/kjim.2019.204] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/20/2019] [Accepted: 01/09/2020] [Indexed: 12/17/2022] Open
Abstract
BACKGROUND/AIMS Lung function is an objective indicator of diagnosis and prognosis of respiratory diseases. Many common genetic variants have been associated with lung function in multiple ethnic populations. We looked for coding variants associated with forced expiratory volume in 1 second (FEV1) and FEV1/forced vital capacity (FVC) in the Korean general population. METHODS We carried out exome array analysis and lung function measurements of the FEV1 and FEV1/FVC in 7,524 individuals of the Korean population. We evaluated single variants with minor allele frequency greater than 0.5%. We performed look-ups for candidate coding variants associations in the UK Biobank, SpiroMeta, and CHARGE consortia. RESULTS We identified coding variants in the SMIM29 (C6orf1) (p = 1.2 × 10-5) and HMGA1 locus on chromosome 6p21, the GIT2 (p = 6.5 × 10-5) locus on chromosome 12q24, and the ARHGEF40 (p = 9.9 × 10-5) locus on chromosome 14q11 as having a significant association with lung function (FEV1). We also confirmed a previously reported association with lung function and chronic obstructive pulmonary disease in the FAM13A (p = 4.54 × 10-6) locus on chromosome 4q22, in TNXB (p = 1.30 × 10-6) and in AGER (p = 1.09 × 10-8) locus on chromosome 6p21. CONCLUSION Our exome array analysis identified that several protein coding variants were associated with lung function in the Korean population. Common coding variants in SMIM29 (C6orf1), HMGA1, GIT2, FAM13A, TNXB, AGER and low-frequency variant in ARHGEF40 potentially affect lung function, which warrant further study.
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Affiliation(s)
- Kyu-Sun Lee
- Department of Internal Medicine, Kangwon National University School of Medicine, Chuncheon, Korea
| | - Kun Hee Kim
- Department of Convergence Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Yeon-Mok Oh
- Department of Pulmonary and Critical Care Medicine and Clinical Research Center for Chronic Obstructive Airway Disease, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Buhm Han
- Department of Medical Science, Seoul National University College of Medicine, Seoul, Korea
| | - Woo Jin Kim
- Department of Internal Medicine, Kangwon National University School of Medicine, Chuncheon, Korea
- Correspondence to Woo Jin Kim, M.D. Department of Internal Medicine, Kangwon National University School of Medicine, 156 Baengnyeong-ro, Chuncheon 24289, Korea Tel: +82-33-250-7815 Fax: +82-33-255-6567 E-mail:
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35
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Hartwig FP, Tilling K, Davey Smith G, Lawlor DA, Borges MC. Bias in two-sample Mendelian randomization when using heritable covariable-adjusted summary associations. Int J Epidemiol 2021; 50:1639-1650. [PMID: 33619569 PMCID: PMC8580279 DOI: 10.1093/ije/dyaa266] [Citation(s) in RCA: 58] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2019] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND Two-sample Mendelian randomization (MR) allows the use of freely accessible summary association results from genome-wide association studies (GWAS) to estimate causal effects of modifiable exposures on outcomes. Some GWAS adjust for heritable covariables in an attempt to estimate direct effects of genetic variants on the trait of interest. One, both or neither of the exposure GWAS and outcome GWAS may have been adjusted for covariables. METHODS We performed a simulation study comprising different scenarios that could motivate covariable adjustment in a GWAS and analysed real data to assess the influence of using covariable-adjusted summary association results in two-sample MR. RESULTS In the absence of residual confounding between exposure and covariable, between exposure and outcome, and between covariable and outcome, using covariable-adjusted summary associations for two-sample MR eliminated bias due to horizontal pleiotropy. However, covariable adjustment led to bias in the presence of residual confounding (especially between the covariable and the outcome), even in the absence of horizontal pleiotropy (when the genetic variants would be valid instruments without covariable adjustment). In an analysis using real data from the Genetic Investigation of ANthropometric Traits (GIANT) consortium and UK Biobank, the causal effect estimate of waist circumference on blood pressure changed direction upon adjustment of waist circumference for body mass index. CONCLUSIONS Our findings indicate that using covariable-adjusted summary associations in MR should generally be avoided. When that is not possible, careful consideration of the causal relationships underlying the data (including potentially unmeasured confounders) is required to direct sensitivity analyses and interpret results with appropriate caution.
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Affiliation(s)
- Fernando Pires Hartwig
- Postgraduate Program in Epidemiology, Federal University of Pelotas, Pelotas, Brazil.,Medical Research Council Integrative Epidemiology Unit, at the University of Bristol, Bristol, UK
| | - Kate Tilling
- Medical Research Council Integrative Epidemiology Unit, at the University of Bristol, Bristol, UK.,Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - George Davey Smith
- Medical Research Council Integrative Epidemiology Unit, at the University of Bristol, Bristol, UK.,Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Deborah A Lawlor
- Medical Research Council Integrative Epidemiology Unit, at the University of Bristol, Bristol, UK.,Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Maria Carolina Borges
- Medical Research Council Integrative Epidemiology Unit, at the University of Bristol, Bristol, UK.,Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
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36
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Córdova-Palomera A, Tcheandjieu C, Fries JA, Varma P, Chen VS, Fiterau M, Xiao K, Tejeda H, Keavney BD, Cordell HJ, Tanigawa Y, Venkataraman G, Rivas MA, Ré C, Ashley E, Priest JR. Cardiac Imaging of Aortic Valve Area From 34 287 UK Biobank Participants Reveals Novel Genetic Associations and Shared Genetic Comorbidity With Multiple Disease Phenotypes. CIRCULATION-GENOMIC AND PRECISION MEDICINE 2020; 13:e003014. [DOI: 10.1161/circgen.120.003014] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background:
The aortic valve is an important determinant of cardiovascular physiology and anatomic location of common human diseases.
Methods:
From a sample of 34 287 white British ancestry participants, we estimated functional aortic valve area by planimetry from prospectively obtained cardiac magnetic resonance imaging sequences of the aortic valve. Aortic valve area measurements were submitted to genome-wide association testing, followed by polygenic risk scoring and phenome-wide screening, to identify genetic comorbidities.
Results:
A genome-wide association study of aortic valve area in these UK Biobank participants showed 3 significant associations, indexed by rs71190365 (chr13:50764607,
DLEU1
,
P
=1.8×10
−9
), rs35991305 (chr12:94191968,
CRADD
,
P
=3.4×10
−8
), and chr17:45013271:C:T (
GOSR2
,
P
=5.6×10
−8
). Replication on an independent set of 8145 unrelated European ancestry participants showed consistent effect sizes in all 3 loci, although rs35991305 did not meet nominal significance. We constructed a polygenic risk score for aortic valve area, which in a separate cohort of 311 728 individuals without imaging demonstrated that smaller aortic valve area is predictive of increased risk for aortic valve disease (odds ratio, 1.14;
P
=2.3×10
−6
). After excluding subjects with a medical diagnosis of aortic valve stenosis (remaining n=308 683 individuals), phenome-wide association of >10 000 traits showed multiple links between the polygenic score for aortic valve disease and key health-related comorbidities involving the cardiovascular system and autoimmune disease. Genetic correlation analysis supports a shared genetic etiology with between aortic valve area and birth weight along with other cardiovascular conditions.
Conclusions:
These results illustrate the use of automated phenotyping of cardiac imaging data from the general population to investigate the genetic etiology of aortic valve disease, perform clinical prediction, and uncover new clinical and genetic correlates of cardiac anatomy.
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Affiliation(s)
- Aldo Córdova-Palomera
- Department of Pediatrics, Division of Pediatric Cardiology, Stanford University School of Medicine, Stanford, CA (A.C.-P., C.T., K.X., H.T., J.R.P.)
| | - Catherine Tcheandjieu
- Department of Pediatrics, Division of Pediatric Cardiology, Stanford University School of Medicine, Stanford, CA (A.C.-P., C.T., K.X., H.T., J.R.P.)
| | - Jason A. Fries
- Department of Computer Science (J.F., V.S.C., M.F., C.R.), Stanford University, CA
- Center for Biomedical Informatics Research (J.F.), Stanford University, CA
| | - Paroma Varma
- Department of Electrical Engineering (P.V.), Stanford University, CA
| | - Vincent S. Chen
- Department of Computer Science (J.F., V.S.C., M.F., C.R.), Stanford University, CA
| | - Madalina Fiterau
- Department of Computer Science (J.F., V.S.C., M.F., C.R.), Stanford University, CA
| | - Ke Xiao
- Department of Pediatrics, Division of Pediatric Cardiology, Stanford University School of Medicine, Stanford, CA (A.C.-P., C.T., K.X., H.T., J.R.P.)
| | - Heliodoro Tejeda
- Department of Pediatrics, Division of Pediatric Cardiology, Stanford University School of Medicine, Stanford, CA (A.C.-P., C.T., K.X., H.T., J.R.P.)
| | - Bernard D. Keavney
- Division of Cardiovascular Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United Kingdom (B.K.)
- Division of Medicine, Manchester University National Health Service Foundation Trust, Manchester Academic Health Science Centre, Manchester, United Kingdom (B.K.)
| | - Heather J. Cordell
- Population Health Sciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle Upon Tyne, United Kingdom (H.J.C.)
| | - Yosuke Tanigawa
- Department of Biomedical Data Science (Y.T., G.V., M.R.), Stanford University, CA
| | - Guhan Venkataraman
- Department of Biomedical Data Science (Y.T., G.V., M.R.), Stanford University, CA
| | - Manuel A. Rivas
- Department of Biomedical Data Science (Y.T., G.V., M.R.), Stanford University, CA
| | - Christopher Ré
- Department of Computer Science (J.F., V.S.C., M.F., C.R.), Stanford University, CA
| | - Euan Ashley
- Department of Medicine (E.A.), Stanford University, CA
- Chan Zuckerberg Biohub, San Francisco, CA (E.A., J.R.P.)
| | - James R. Priest
- Department of Pediatrics, Division of Pediatric Cardiology, Stanford University School of Medicine, Stanford, CA (A.C.-P., C.T., K.X., H.T., J.R.P.)
- Chan Zuckerberg Biohub, San Francisco, CA (E.A., J.R.P.)
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37
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The Utility of Resolving Asthma Molecular Signatures Using Tissue-Specific Transcriptome Data. G3-GENES GENOMES GENETICS 2020; 10:4049-4062. [PMID: 32900903 PMCID: PMC7642926 DOI: 10.1534/g3.120.401718] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
An integrative analysis focused on multi-tissue transcriptomics has not been done for asthma. Tissue-specific DEGs remain undetected in many multi-tissue analyses, which influences identification of disease-relevant pathways and potential drug candidates. Transcriptome data from 609 cases and 196 controls, generated using airway epithelium, bronchial, nasal, airway macrophages, distal lung fibroblasts, proximal lung fibroblasts, CD4+ lymphocytes, CD8+ lymphocytes from whole blood and induced sputum samples, were retrieved from Gene Expression Omnibus (GEO). Differentially regulated asthma-relevant genes identified from each sample type were used to identify (a) tissue-specific and tissue-shared asthma pathways, (b) their connection to GWAS-identified disease genes to identify candidate tissue for functional studies, (c) to select surrogate sample for invasive tissues, and finally (d) to identify potential drug candidates via connectivity map analysis. We found that inter-tissue similarity in gene expression was more pronounced at pathway/functional level than at gene level with highest similarity between bronchial epithelial cells and lung fibroblasts, and lowest between airway epithelium and whole blood samples. Although public-domain gene expression data are limited by inadequately annotated per-sample demographic and clinical information which limited the analysis, our tissue-resolved analysis clearly demonstrated relative importance of unique and shared asthma pathways, At the pathway level, IL-1b signaling and ERK signaling were significant in many tissue types, while Insulin-like growth factor and TGF-beta signaling were relevant in only airway epithelial tissue. IL-12 (in macrophages) and Immunoglobulin signaling (in lymphocytes) and chemokines (in nasal epithelium) were the highest expressed pathways. Overall, the IL-1 signaling genes (inflammatory) were relevant in the airway compartment, while pro-Th2 genes including IL-13 and STAT6 were more relevant in fibroblasts, lymphocytes, macrophages and bronchial biopsies. These genes were also associated with asthma in the GWAS catalog. Support Vector Machine showed that DEGs based on macrophages and epithelial cells have the highest and lowest discriminatory accuracy, respectively. Drug (entinostat, BMS-345541) and genetic perturbagens (KLF6, BCL10, INFB1 and BAMBI) negatively connected to disease at multi-tissue level could potentially repurposed for treating asthma. Collectively, our study indicates that the DEGs, perturbagens and disease are connected differentially depending on tissue/cell types. While most of the existing literature describes asthma transcriptome data from individual sample types, the present work demonstrates the utility of multi-tissue transcriptome data. Future studies should focus on collecting transcriptomic data from multiple tissues, age and race groups, genetic background, disease subtypes and on the availability of better-annotated data in the public domain.
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38
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Saferali A, Xu Z, Sheynkman GM, Hersh CP, Cho MH, Silverman EK, Laederach A, Vollmers C, Castaldi PJ. Characterization of a COPD-Associated NPNT Functional Splicing Genetic Variant in Human Lung Tissue via Long-Read Sequencing. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2020:2020.10.20.20203927. [PMID: 33173926 PMCID: PMC7654922 DOI: 10.1101/2020.10.20.20203927] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Chronic obstructive pulmonary disease (COPD) is a leading cause of death worldwide. Genome-wide association studies (GWAS) have identified over 80 loci that are associated with COPD and emphysema, however for most of these loci the causal variant and gene are unknown. Here, we utilize lung splice quantitative trait loci (sQTL) data from the Genotype-Tissue Expression project (GTEx) and short read sequencing data from the Lung Tissue Research Consortium (LTRC) to characterize a locus in nephronectin ( NPNT ) associated with COPD case-control status and lung function. We found that the rs34712979 variant is associated with alternative splice junction use in NPNT , specifically for the junction connecting the 2nd and 4th exons (chr4:105898001-105927336) (p=4.02×10 -38 ). This association colocalized with GWAS data for COPD and lung spirometry measures with a posterior probability of 94%, indicating that the same causal genetic variants in NPNT underlie the associations with COPD risk, spirometric measures of lung function, and splicing. Investigation of NPNT short read sequencing revealed that rs34712979 creates a cryptic splice acceptor site which results in the inclusion of a 3 nucleotide exon extension, coding for a serine residue near the N-terminus of the protein. Using Oxford Nanopore Technologies (ONT) long read sequencing we identified 13 NPNT isoforms, 6 of which are predicted to be protein coding. Two of these are full length isoforms which differ only in the 3 nucleotide exon extension whose occurrence differs by genotype. Overall, our data indicate that rs34712979 modulates COPD risk and lung function by creating a novel splice acceptor which results in the inclusion of a 3 nucelotide sequence coding for a serine in the nephronectin protein sequence. Our findings implicate NPNT splicing in contributing to COPD risk, and identify a novel serine insertion in the nephronectin protein that warrants further study.
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39
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Genetic regulation of gene expression of MIF family members in lung tissue. Sci Rep 2020; 10:16980. [PMID: 33046825 PMCID: PMC7552402 DOI: 10.1038/s41598-020-74121-w] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2019] [Accepted: 09/08/2020] [Indexed: 12/18/2022] Open
Abstract
Macrophage migration inhibitory factor (MIF) is a cytokine found to be associated with chronic obstructive pulmonary disease (COPD). However, there is no consensus on how MIF levels differ in COPD compared to control conditions and there are no reports on MIF expression in lung tissue. Here we studied gene expression of members of the MIF family MIF, D-Dopachrome Tautomerase (DDT) and DDT-like (DDTL) in a lung tissue dataset with 1087 subjects and identified single nucleotide polymorphisms (SNPs) regulating their gene expression. We found higher MIF and DDT expression in COPD patients compared to non-COPD subjects and found 71 SNPs significantly influencing gene expression of MIF and DDTL. Furthermore, the platform used to measure MIF (microarray or RNAseq) was found to influence the splice variants detected and subsequently the direction of the SNP effects on MIF expression. Among the SNPs found to regulate MIF expression, the major LD block identified was linked to rs5844572, a SNP previously found to be associated with lower diffusion capacity in COPD. This suggests that MIF may be contributing to the pathogenesis of COPD, as SNPs that influence MIF expression are also associated with symptoms of COPD. Our study shows that MIF levels are affected not only by disease but also by genetic diversity (i.e. SNPs). Since none of our significant eSNPs for MIF or DDTL have been described in GWAS for COPD or lung function, MIF expression in COPD patients is more likely a consequence of disease-related factors rather than a cause of the disease.
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40
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Portas L, Pereira M, Shaheen SO, Wyss AB, London SJ, Burney PGJ, Hind M, Dean CH, Minelli C. Lung Development Genes and Adult Lung Function. Am J Respir Crit Care Med 2020; 202:853-865. [PMID: 32392078 PMCID: PMC7491406 DOI: 10.1164/rccm.201912-2338oc] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2019] [Accepted: 05/11/2020] [Indexed: 12/25/2022] Open
Abstract
Rationale: Poor lung health in adult life may occur partly through suboptimal growth and development, as suggested by epidemiological evidence pointing to early life risk factors.Objectives: To systematically investigate the effects of lung development genes on adult lung function.Methods: Using UK Biobank data, we tested the association of 391 genes known to influence lung development with FVC and FEV1/FVC. We split the dataset into two random subsets of 207,616 and 138,411 individuals, using the larger subset to select the most promising signals and the smaller subset for replication.Measurements and Main Results: We identified 55 genes, of which 36 (16 for FVC, 19 for FEV1/FVC, and one for both) had not been identified in the largest, most recent genome-wide study of lung function. Most of these 36 signals were intronic variants; expression data from blood and lung tissue showed that the majority affect the expression of the genes they lie within. Further testing of 34 of these 36 signals in the CHARGE and SpiroMeta consortia showed that 16 replicated after Bonferroni correction and another 12 replicated at nominal significance level. Of the 55 genes, 53 fell into four biological categories whose function is to regulate organ size and cell integrity (growth factors; transcriptional regulators; cell-to-cell adhesion; extracellular matrix), suggesting that these specific processes are important for adult lung health.Conclusions: Our study demonstrates the importance of lung development genes in regulating adult lung function and influencing both restrictive and obstructive patterns. Further investigation of these developmental pathways could lead to druggable targets.
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Affiliation(s)
- Laura Portas
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
| | - Miguel Pereira
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
- Congenica Ltd., Wellcome Genome Campus, Cambridge, United Kingdom
| | - Seif O Shaheen
- Institute of Population Health Sciences, Queen Mary University of London, London, United Kingdom
| | - Annah B Wyss
- Department of Health and Human Services, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, North Carolina
| | - Stephanie J London
- Department of Health and Human Services, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, North Carolina
| | - Peter G J Burney
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
| | - Matthew Hind
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
- Department of Respiratory Medicine, Royal Brompton & Harefield NHS Foundation Trust, London, United Kingdom; and
| | - Charlotte H Dean
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
- MRC Harwell Institute, Oxfordshire, United Kingdom
| | - Cosetta Minelli
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
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41
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Mak ACY, Sajuthi S, Joo J, Xiao S, Sleiman PM, White MJ, Lee EY, Saef B, Hu D, Gui H, Keys KL, Lurmann F, Jain D, Abecasis G, Kang HM, Nickerson DA, Germer S, Zody MC, Winterkorn L, Reeves C, Huntsman S, Eng C, Salazar S, Oh SS, Gilliland FD, Chen Z, Kumar R, Martínez FD, Wu AC, Ziv E, Hakonarson H, Himes BE, Williams LK, Seibold MA, Burchard EG. Lung Function in African American Children with Asthma Is Associated with Novel Regulatory Variants of the KIT Ligand KITLG/SCF and Gene-By-Air-Pollution Interaction. Genetics 2020; 215:869-886. [PMID: 32327564 PMCID: PMC7337089 DOI: 10.1534/genetics.120.303231] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2020] [Accepted: 04/22/2020] [Indexed: 01/12/2023] Open
Abstract
Baseline lung function, quantified as forced expiratory volume in the first second of exhalation (FEV1), is a standard diagnostic criterion used by clinicians to identify and classify lung diseases. Using whole-genome sequencing data from the National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine project, we identified a novel genetic association with FEV1 on chromosome 12 in 867 African American children with asthma (P = 1.26 × 10-8, β = 0.302). Conditional analysis within 1 Mb of the tag signal (rs73429450) yielded one major and two other weaker independent signals within this peak. We explored statistical and functional evidence for all variants in linkage disequilibrium with the three independent signals and yielded nine variants as the most likely candidates responsible for the association with FEV1 Hi-C data and expression QTL analysis demonstrated that these variants physically interacted with KITLG (KIT ligand, also known as SCF), and their minor alleles were associated with increased expression of the KITLG gene in nasal epithelial cells. Gene-by-air-pollution interaction analysis found that the candidate variant rs58475486 interacted with past-year ambient sulfur dioxide exposure (P = 0.003, β = 0.32). This study identified a novel protective genetic association with FEV1, possibly mediated through KITLG, in African American children with asthma. This is the first study that has identified a genetic association between lung function and KITLG, which has established a role in orchestrating allergic inflammation in asthma.
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Affiliation(s)
- Angel C Y Mak
- Department of Medicine, University of California, San Francisco, California 94143
| | - Satria Sajuthi
- Center for Genes, Environment, and Health, National Jewish Health, Denver, Colorado 80206
| | - Jaehyun Joo
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - Shujie Xiao
- Center for Individualized and Genomic Medicine Research, Department of Internal Medicine, Henry Ford Health System, Detroit, Michigan 48202
| | - Patrick M Sleiman
- Center for Applied Genomics, Children's Hospital of Philadelphia, Pennsylvania, 19104
- Division of Human Genetics, Department of Pediatrics, The Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - Marquitta J White
- Department of Medicine, University of California, San Francisco, California 94143
| | - Eunice Y Lee
- Department of Medicine, University of California, San Francisco, California 94143
| | - Benjamin Saef
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - Donglei Hu
- Department of Medicine, University of California, San Francisco, California 94143
| | - Hongsheng Gui
- Center for Individualized and Genomic Medicine Research, Department of Internal Medicine, Henry Ford Health System, Detroit, Michigan 48202
| | - Kevin L Keys
- Department of Medicine, University of California, San Francisco, California 94143
- Berkeley Institute for Data Science, University of California, Berkeley, California 94720
| | | | - Deepti Jain
- Department of Biostatistics, University of Washington, Seattle, Washington 98195
| | - Gonçalo Abecasis
- Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan 48109
| | - Hyun Min Kang
- Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan 48109
| | - Deborah A Nickerson
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195
- Northwest Genomics Center, Seattle, Washington, 98195
- Brotman Baty Institute for Precision Medicine, Seattle, Washington, 98195
| | | | | | | | | | - Scott Huntsman
- Department of Medicine, University of California, San Francisco, California 94143
| | - Celeste Eng
- Department of Medicine, University of California, San Francisco, California 94143
| | - Sandra Salazar
- Department of Medicine, University of California, San Francisco, California 94143
| | - Sam S Oh
- Department of Medicine, University of California, San Francisco, California 94143
| | - Frank D Gilliland
- Department of Preventive Medicine, Division of Environmental Health, Keck School of Medicine, University of Southern California, Los Angeles, California 90033
| | - Zhanghua Chen
- Department of Preventive Medicine, Division of Environmental Health, Keck School of Medicine, University of Southern California, Los Angeles, California 90033
| | - Rajesh Kumar
- Ann and Robert H. Lurie Children's Hospital of Chicago, Chicago, Illinois 60611
| | - Fernando D Martínez
- Asthma and Airway Disease Research Center, University of Arizona, Tucson, Arizona 85721
| | - Ann Chen Wu
- Precision Medicine Translational Research (PRoMoTeR) Center, Department of Population Medicine, Harvard Medical School and Pilgrim Health Care Institute, Boston, Massachusetts 02215
| | - Elad Ziv
- Department of Medicine, University of California, San Francisco, California 94143
| | - Hakon Hakonarson
- Center for Applied Genomics, Children's Hospital of Philadelphia, Pennsylvania, 19104
- Division of Human Genetics, Department of Pediatrics, The Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - Blanca E Himes
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - L Keoki Williams
- Center for Individualized and Genomic Medicine Research, Department of Internal Medicine, Henry Ford Health System, Detroit, Michigan 48202
| | - Max A Seibold
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - Esteban G Burchard
- Department of Medicine, University of California, San Francisco, California 94143
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, California 94143
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42
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Fawcett KA, Obeidat M, Melbourne C, Shrine N, Guyatt AL, John C, Luan J, Richmond A, Moksnes MR, Granell R, Weiss S, Imboden M, May-Wilson S, Hysi P, Boutin TS, Portas L, Flexeder C, Harris SE, Wang CA, Lyytikäinen LP, Palviainen T, Foong RE, Keidel D, Minelli C, Langenberg C, Bossé Y, Van den Berge M, Sin DD, Hao K, Campbell A, Porteous D, Padmanabhan S, Smith BH, Evans DM, Ring S, Langhammer A, Hveem K, Willer C, Ewert R, Stubbe B, Pirastu N, Klaric L, Joshi PK, Patasova K, Massimo M, Polasek O, Starr JM, Karrasch S, Strauch K, Meitinger T, Rudan I, Rantanen T, Pietiläinen K, Kähönen M, Raitakari OT, Hall GL, Sly PD, Pennell CE, Kaprio J, Lehtimäki T, Vitart V, Deary IJ, Jarvis D, Wilson JF, Spector T, Probst-Hensch N, Wareham NJ, Völzke H, Henderson J, Strachan DP, Brumpton BM, Hayward C, Hall IP, Tobin MD, Wain LV. Variants associated with HHIP expression have sex-differential effects on lung function. Wellcome Open Res 2020; 5:111. [PMID: 33728380 PMCID: PMC7938335 DOI: 10.12688/wellcomeopenres.15846.1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/19/2020] [Indexed: 02/02/2023] Open
Abstract
Background: Lung function is highly heritable and differs between the sexes throughout life. However, little is known about sex-differential genetic effects on lung function. We aimed to conduct the first genome-wide genotype-by-sex interaction study on lung function to identify genetic effects that differ between males and females. Methods: We tested for interactions between 7,745,864 variants and sex on spirometry-based measures of lung function in UK Biobank (N=303,612), and sought replication in 75,696 independent individuals from the SpiroMeta consortium. Results: Five independent single-nucleotide polymorphisms (SNPs) showed genome-wide significant (P<5x10 -8) interactions with sex on lung function, and 21 showed suggestive interactions (P<1x10 -6). The strongest signal, from rs7697189 (chr4:145436894) on forced expiratory volume in 1 second (FEV 1) (P=3.15x10 -15), was replicated (P=0.016) in SpiroMeta. The C allele increased FEV 1 more in males (untransformed FEV 1 β=0.028 [SE 0.0022] litres) than females (β=0.009 [SE 0.0014] litres), and this effect was not accounted for by differential effects on height, smoking or pubertal age. rs7697189 resides upstream of the hedgehog-interacting protein ( HHIP) gene and was previously associated with lung function and HHIP lung expression. We found HHIP expression was significantly different between the sexes (P=6.90x10 -6), but we could not detect sex differential effects of rs7697189 on expression. Conclusions: We identified a novel genotype-by-sex interaction at a putative enhancer region upstream of the HHIP gene. Establishing the mechanism by which HHIP SNPs have different effects on lung function in males and females will be important for our understanding of lung health and diseases in both sexes.
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Affiliation(s)
| | - Ma'en Obeidat
- The University of British Columbia Centre for Heart Lung Innovation, St Paul’s Hospital, Vancouver, BC, Canada
| | - Carl Melbourne
- Department of Health Sciences, University of Leicester, Leicester, LE1 7RH, UK
| | - Nick Shrine
- Department of Health Sciences, University of Leicester, Leicester, LE1 7RH, UK
| | - Anna L. Guyatt
- Department of Health Sciences, University of Leicester, Leicester, LE1 7RH, UK
| | - Catherine John
- Department of Health Sciences, University of Leicester, Leicester, LE1 7RH, UK
| | - Jian'an Luan
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0QQ, UK
| | - Anne Richmond
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK
| | - Marta R. Moksnes
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Raquel Granell
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, BS8 2BN, UK
| | - Stefan Weiss
- Department of Functional Genomics, Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, 17475, Germany
| | - Medea Imboden
- Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Sebastian May-Wilson
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, UK
| | - Pirro Hysi
- The Department of Twin Research & Genetic Epidemiology, King’s College London, St Thomas’ Campus, Lambeth Palace Road, London, UK
| | - Thibaud S. Boutin
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK
| | - Laura Portas
- Population Health and Occupational Disease, National Heart and Lung Institute, Imperial College London, London, UK
| | - Claudia Flexeder
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, 85764, Germany
| | - Sarah E. Harris
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
- Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Carol A. Wang
- School of Medicine and Public Health, Faculty of Medicine and Health, The University of Newcastle, Callaghan, Australia
| | - Leo-Pekka Lyytikäinen
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, 33520, Finland
- Department of Clinical Chemistry, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, 33014, Finland
- Department of Cardiology, Heart Center, Tampere University Hospital, Tampere, 33521, Finland
| | - Teemu Palviainen
- Institute for Molecular Medicine FIMM, University of Helsinki, Helsinki, FI-00014, Finland
| | - Rachel E. Foong
- Telethon Kids Institute, Perth, Australia
- School of Physiotherapy and Exercise Science, Faculty of Health Sciences, Curtin University, Perth, Australia
| | - Dirk Keidel
- Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Cosetta Minelli
- Population Health and Occupational Disease, National Heart and Lung Institute, Imperial College London, London, UK
| | - Claudia Langenberg
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0QQ, UK
| | - Yohan Bossé
- Institut universitaire de cardiologie et de pneumologie de Québec, Department of Molecular Medicine, Laval University, Québec, Canada
| | - Maarten Van den Berge
- University Medical Center Groningen, Department of Pulmonology, GRIAC Research Institute, University of Groningen, Groningen, The Netherlands
| | - Don D. Sin
- The University of British Columbia Centre for Heart Lung Innovation, St Paul’s Hospital, Vancouver, BC, Canada
- Respiratory Division, Department of Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Ke Hao
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, EH4 2XU, UK
| | - David Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, EH4 2XU, UK
| | - Sandosh Padmanabhan
- British Heart Foundation Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, G12 8TA, UK
| | - Blair H. Smith
- Division of Population Health Sciences, Ninewells Hospital and Medical School, University of Dundee, Dundee, DD1 9SY, UK
| | - David M. Evans
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, BS8 2BN, UK
- Population Health Sciences Bristol Medical School, University of Bristol, Bristol, BS8 2BN, UK
- University of Queensland Diamantina Institute, Translational Research Institute, Brisbane, QLD 4072, Australia
| | - Sue Ring
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, BS8 2BN, UK
- Population Health Sciences Bristol Medical School, University of Bristol, Bristol, BS8 2BN, UK
| | - Arnulf Langhammer
- Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Kristian Hveem
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Cristen Willer
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, USA
- Department of Internal Medicine, University of Michigan, Ann Arbor, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, USA
| | - Ralf Ewert
- Department of Internal Medicine B, Cardiology, Pneumology, Infectious Diseases, Intensive Care Medicine, University Medicine Greifswald, Greifswald, 17475, Germany
| | - Beate Stubbe
- Department of Internal Medicine B, Cardiology, Pneumology, Infectious Diseases, Intensive Care Medicine, University Medicine Greifswald, Greifswald, 17475, Germany
| | - Nicola Pirastu
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, UK
| | - Lucija Klaric
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK
| | - Peter K. Joshi
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, UK
| | - Karina Patasova
- The Department of Twin Research & Genetic Epidemiology, King’s College London, St Thomas’ Campus, Lambeth Palace Road, London, UK
| | - Mangino Massimo
- The Department of Twin Research & Genetic Epidemiology, King’s College London, St Thomas’ Campus, Lambeth Palace Road, London, UK
| | - Ozren Polasek
- University of Split School of Medicine, Split, Croatia
| | - John M. Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
- Alzheimer Scotland Research Centre, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Stefan Karrasch
- Institute and Outpatient Clinic for Occupational, Social and Environmental Medicine, Ludwig-Maximilians-Universität, Munich, 80336, Germany
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, 85764, Germany
- Comprehensive Pneumology Center Munich (CPC-M), Member of the German Center for Lung Research (DZL), Munich, 81377, Germany
| | - Konstantin Strauch
- Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, 85764, Germany
- Chair of Genetic Epidemiology, IBE, Faculty of Medicine, LMU Munich, Munich, 81377, Germany
| | - Thomas Meitinger
- Institute of Human Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, 85764, Germany
- Institute of Human Genetics, Klinikum rechts der Isar der TU Muenchen, Muenchen, 81675, Germany
| | - Igor Rudan
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, UK
| | - Taina Rantanen
- Faculty of Sport and Health Sciences, Gerontology Research Center, University of Jyväskylä, Jyväskylä, Finland
| | - Kirsi Pietiläinen
- Obesity Research Unit, Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, FI-00014, Finland
- Obesity Centre, Abdominal Centre, Helsinki University Hospital and University of Helsinki, Helsinki, FI-00029, Finland
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital, Tampere, 33521, Finland
- Department of Clinical Physiology, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, 33014, Finland
| | - Olli T. Raitakari
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
| | - Graham L. Hall
- Telethon Kids Institute, Perth, Australia
- School of Physiotherapy and Exercise Science, Faculty of Health Sciences, Curtin University, Perth, Australia
| | - Peter D. Sly
- Children's Health and Environment Program, The University of Queensland, Brisbane, Australia
| | - Craig E. Pennell
- School of Medicine and Public Health, Faculty of Medicine and Health, The University of Newcastle, Callaghan, Australia
| | - Jaakko Kaprio
- Institute for Molecular Medicine FIMM, University of Helsinki, Helsinki, FI-00014, Finland
- Department of Public Health, University of Helsinki, Helsinki, FI-00014, Finland
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, 33520, Finland
- Department of Clinical Chemistry, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, 33014, Finland
| | - Veronique Vitart
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK
| | - Ian J. Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
- Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Debbie Jarvis
- Population Health and Occupational Disease, National Heart and Lung Institute, Imperial College London, London, UK
- MRC-PHE Centre for the Environment and Health, London, UK
| | - James F. Wilson
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, UK
| | - Tim Spector
- The Department of Twin Research & Genetic Epidemiology, King’s College London, St Thomas’ Campus, Lambeth Palace Road, London, UK
| | - Nicole Probst-Hensch
- Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Nicholas J. Wareham
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0QQ, UK
| | - Henry Völzke
- Intitute for Community Medicine, University Medicine Greifswald, Greifswald, 17487, Germany
| | - John Henderson
- Population Health Sciences Bristol Medical School, University of Bristol, Bristol, BS8 2BN, UK
| | - David P. Strachan
- Population Health Research Institute, St George's, University of London, London, SW17 0RE, UK
| | - Ben M. Brumpton
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Clinic of Thoracic and Occupational Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK
| | - Ian P. Hall
- Division of Respiratory Medicine and NIHR-Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, UK
| | - Martin D. Tobin
- Department of Health Sciences, University of Leicester, Leicester, LE1 7RH, UK
- National Institute for Health Research, Leicester Respiratory Biomedical Research Centre, Glenfield Hospital, Leicester, LE3 9QP, UK
| | - Louise V. Wain
- Department of Health Sciences, University of Leicester, Leicester, LE1 7RH, UK
- National Institute for Health Research, Leicester Respiratory Biomedical Research Centre, Glenfield Hospital, Leicester, LE3 9QP, UK
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43
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Williams PT. Spirometric traits show quantile-dependent heritability, which may contribute to their gene-environment interactions with smoking and pollution. PeerJ 2020; 8:e9145. [PMID: 32461834 PMCID: PMC7233273 DOI: 10.7717/peerj.9145] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2019] [Accepted: 04/17/2020] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND "Quantile-dependent expressivity" refers to a genetic effect that is dependent upon whether the phenotype (e.g., spirometric data) is high or low relative to its population distribution. Forced vital capacity (FVC), forced expiratory volume in 1 second (FEV1), and the FEV1/FVC ratio are moderately heritable spirometric traits. The aim of the analyses is to test whether their heritability (h2 ) is constant over all quantiles of their distribution. METHODS Quantile regression was applied to the mean age, sex, height and smoking-adjusted spirometric data over multiple visits in 9,993 offspring-parent pairs and 1,930 sibships from the Framingham Heart Study to obtain robust estimates of offspring-parent (βOP), offspring-midparent (βOM), and full-sib regression slopes (βFS). Nonparametric significance levels were obtained from 1,000 bootstrap samples. βOPs were used as simple indicators of quantile-specific heritability (i.e., h 2 = 2βOP/(1+rspouse), where rspouse was the correlation between spouses). RESULTS βOP ± standard error (SE) decreased by 0.0009 ± 0.0003 (P = 0.003) with every one-percent increment in the population distribution of FEV1/FVC, i.e., βOP ± SE were: 0.182 ± 0.031, 0.152 ± 0.015; 0.136 ± 0.011; 0.121 ± 0.013; and 0.099 ± 0.013 at the 10th, 25th, 50th, 75th, and 90th percentiles of the FEV1/FVC distribution, respectively. These correspond to h2 ± SEs of 0.350 ± 0.060 at the 10th, 0.292 ± 0.029 at the 25th, 0.262 ± 0.020 at the 50th, 0.234 ± 0.025 at the 75th, and 0.191 ± 0.025 at the 90th percentiles of the FEV1/FVC ratio. Maximum mid-expiratory flow (MMEF) h2 ± SEs increased 0.0025 ± 0.0007 (P = 0.0004) with every one-percent increment in its distribution, i.e.: 0.467 ± 0.046, 0.467 ± 0.033, 0.554 ± 0.038, 0.615 ± 0.042, and 0.675 ± 0.060 at the 10th, 25th, 50th, 75th, and 90th percentiles of its distribution. This was due to forced expiratory flow at 75% of FVC (FEF75%), whose quantile-specific h2 increased an average of 0.0042 ± 0.0008 for every one-percent increment in its distribution. It is speculated that previously reported gene-environment interactions may be partially attributable to quantile-specific h2 , i.e., greater heritability in individuals with lower FEV1/FVC due to smoking or airborne particles exposure vs. nonsmoking, unexposed individuals. CONCLUSION Heritabilities of FEV1/FVC, MMEF, and FEF75% from quantile-regression of offspring-parent and sibling spirometric data suggest their quantile-dependent expressivity.
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Affiliation(s)
- Paul T. Williams
- Molecular Biophysics & Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, United States of America
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44
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Ragland MF, Benway CJ, Lutz SM, Bowler RP, Hecker J, Hokanson JE, Crapo JD, Castaldi PJ, DeMeo DL, Hersh CP, Hobbs BD, Lange C, Beaty TH, Cho MH, Silverman EK. Genetic Advances in Chronic Obstructive Pulmonary Disease. Insights from COPDGene. Am J Respir Crit Care Med 2020; 200:677-690. [PMID: 30908940 DOI: 10.1164/rccm.201808-1455so] [Citation(s) in RCA: 58] [Impact Index Per Article: 11.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023] Open
Abstract
Chronic obstructive pulmonary disease (COPD) is a common and progressive disease that is influenced by both genetic and environmental factors. For many years, knowledge of the genetic basis of COPD was limited to Mendelian syndromes, such as alpha-1 antitrypsin deficiency and cutis laxa, caused by rare genetic variants. Over the past decade, the proliferation of genome-wide association studies, the accessibility of whole-genome sequencing, and the development of novel methods for analyzing genetic variation data have led to a substantial increase in the understanding of genetic variants that play a role in COPD susceptibility and COPD-related phenotypes. COPDGene (Genetic Epidemiology of COPD), a multicenter, longitudinal study of over 10,000 current and former cigarette smokers, has been pivotal to these breakthroughs in understanding the genetic basis of COPD. To date, over 20 genetic loci have been convincingly associated with COPD affection status, with additional loci demonstrating association with COPD-related phenotypes such as emphysema, chronic bronchitis, and hypoxemia. In this review, we discuss the contributions of the COPDGene study to the discovery of these genetic associations as well as the ongoing genetic investigations of COPD subtypes, protein biomarkers, and post-genome-wide association study analysis.
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Affiliation(s)
- Margaret F Ragland
- Division of Pulmonary Sciences and Critical Care Medicine, School of Medicine, and
| | | | | | | | - Julian Hecker
- Harvard T. H. Chan School of Public Health, Boston, Massachusetts; and
| | - John E Hokanson
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Denver, Aurora, Colorado
| | | | | | - Dawn L DeMeo
- Channing Division of Network Medicine and.,Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, Massachusetts
| | - Craig P Hersh
- Channing Division of Network Medicine and.,Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, Massachusetts
| | - Brian D Hobbs
- Channing Division of Network Medicine and.,Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, Massachusetts
| | - Christoph Lange
- Harvard T. H. Chan School of Public Health, Boston, Massachusetts; and
| | - Terri H Beaty
- Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland
| | - Michael H Cho
- Channing Division of Network Medicine and.,Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, Massachusetts
| | - Edwin K Silverman
- Channing Division of Network Medicine and.,Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, Massachusetts
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45
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Balliu B, Durrant M, Goede OD, Abell N, Li X, Liu B, Gloudemans MJ, Cook NL, Smith KS, Knowles DA, Pala M, Cucca F, Schlessinger D, Jaiswal S, Sabatti C, Lind L, Ingelsson E, Montgomery SB. Genetic regulation of gene expression and splicing during a 10-year period of human aging. Genome Biol 2019; 20:230. [PMID: 31684996 PMCID: PMC6827221 DOI: 10.1186/s13059-019-1840-y] [Citation(s) in RCA: 34] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2019] [Accepted: 09/27/2019] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Molecular and cellular changes are intrinsic to aging and age-related diseases. Prior cross-sectional studies have investigated the combined effects of age and genetics on gene expression and alternative splicing; however, there has been no long-term, longitudinal characterization of these molecular changes, especially in older age. RESULTS We perform RNA sequencing in whole blood from the same individuals at ages 70 and 80 to quantify how gene expression, alternative splicing, and their genetic regulation are altered during this 10-year period of advanced aging at a population and individual level. We observe that individuals are more similar to their own expression profiles later in life than profiles of other individuals their own age. We identify 1291 and 294 genes differentially expressed and alternatively spliced with age, as well as 529 genes with outlying individual trajectories. Further, we observe a strong correlation of genetic effects on expression and splicing between the two ages, with a small subset of tested genes showing a reduction in genetic associations with expression and splicing in older age. CONCLUSIONS These findings demonstrate that, although the transcriptome and its genetic regulation is mostly stable late in life, a small subset of genes is dynamic and is characterized by a reduction in genetic regulation, most likely due to increasing environmental variance with age.
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Affiliation(s)
- Brunilda Balliu
- Department of Pathology, Stanford University School of Medicine, Stanford, USA.
| | - Matthew Durrant
- Department of Genetics, Stanford University School of Medicine, Stanford, USA
| | - Olivia de Goede
- Department of Genetics, Stanford University School of Medicine, Stanford, USA
| | - Nathan Abell
- Department of Genetics, Stanford University School of Medicine, Stanford, USA
| | - Xin Li
- Department of Pathology, Stanford University School of Medicine, Stanford, USA
| | - Boxiang Liu
- Department of Biology, Stanford University School of Medicine, Stanford, USA
| | | | - Naomi L Cook
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Kevin S Smith
- Department of Pathology, Stanford University School of Medicine, Stanford, USA
| | | | - Mauro Pala
- Dipartimento di Scienze Biomediche, Universita di Sassari, Sassari, Italy
| | - Francesco Cucca
- Dipartimento di Scienze Biomediche, Universita di Sassari, Sassari, Italy
| | | | - Siddhartha Jaiswal
- Department of Pathology, Stanford University School of Medicine, Stanford, USA
| | - Chiara Sabatti
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, USA
| | - Lars Lind
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Erik Ingelsson
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, USA.
- Stanford Cardiovascular Institute, Stanford University, Stanford, USA.
- Stanford Diabetes Research Center, Stanford University, Stanford, USA.
| | - Stephen B Montgomery
- Department of Pathology, Stanford University School of Medicine, Stanford, USA.
- Department of Genetics, Stanford University School of Medicine, Stanford, USA.
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46
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Imkamp K, Bernal V, Grzegorzcyk M, Horvatovich P, Vermeulen CJ, Heijink IH, Guryev V, Kerstjens HAM, van den Berge M, Faiz A. Gene network approach reveals co-expression patterns in nasal and bronchial epithelium. Sci Rep 2019; 9:15835. [PMID: 31676779 PMCID: PMC6825243 DOI: 10.1038/s41598-019-50963-x] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2019] [Accepted: 09/13/2019] [Indexed: 12/20/2022] Open
Abstract
Nasal gene expression profiling is a new approach to investigate the airway epithelium as a biomarker to study the activity and treatment responses of obstructive pulmonary diseases. We investigated to what extent gene expression profiling of nasal brushings is similar to that of bronchial brushings. We performed genome wide gene expression profiling on matched nasal and bronchial epithelial brushes from 77 respiratory healthy individuals. To investigate differences and similarities among regulatory modules, network analysis was performed on correlated, differentially expressed and smoking-related genes using Gaussian Graphical Models. Between nasal and bronchial brushes, 619 genes were correlated and 1692 genes were differentially expressed (false discovery rate <0.05, |Fold-change|>2). Network analysis of correlated genes showed pro-inflammatory pathways to be similar between the two locations. Focusing on smoking-related genes, cytochrome-P450 pathway related genes were found to be similar, supporting the concept of a detoxifying response to tobacco exposure throughout the airways. In contrast, cilia-related pathways were decreased in nasal compared to bronchial brushes when focusing on differentially expressed genes. Collectively, while there are substantial differences in gene expression between nasal and bronchial brushes, we also found similarities, especially in the response to the external factors such as smoking.
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Affiliation(s)
- Kai Imkamp
- University of Groningen, University Medical Center Groningen, Department of Pulmonology, Groningen, The Netherlands. .,University of Groningen, University Medical Center Groningen, GRIAC (Groningen Research Institute for Asthma and COPD), Groningen, The Netherlands.
| | - Victor Bernal
- University of Groningen, Bernoulli Institute (JBI), Groningen, The Netherlands.,University of Groningen, Department of Pharmacy, Analytical Biochemistry, Groningen, The Netherlands
| | - Marco Grzegorzcyk
- University of Groningen, Bernoulli Institute (JBI), Groningen, The Netherlands
| | - Peter Horvatovich
- University of Groningen, Department of Pharmacy, Analytical Biochemistry, Groningen, The Netherlands
| | - Cornelis J Vermeulen
- University of Groningen, University Medical Center Groningen, Department of Pulmonology, Groningen, The Netherlands.,University of Groningen, University Medical Center Groningen, GRIAC (Groningen Research Institute for Asthma and COPD), Groningen, The Netherlands
| | - Irene H Heijink
- University of Groningen, University Medical Center Groningen, Department of Pulmonology, Groningen, The Netherlands.,University of Groningen, University Medical Center Groningen, GRIAC (Groningen Research Institute for Asthma and COPD), Groningen, The Netherlands.,University of Groningen, University Medical Center Groningen, Department of Pathology & Medical Biology, section Medical Biology, Groningen, The Netherlands
| | - Victor Guryev
- University of Groningen, University Medical Center Groningen, GRIAC (Groningen Research Institute for Asthma and COPD), Groningen, The Netherlands.,European Research Institute for the Biology of Ageing, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Huib A M Kerstjens
- University of Groningen, University Medical Center Groningen, Department of Pulmonology, Groningen, The Netherlands.,University of Groningen, University Medical Center Groningen, GRIAC (Groningen Research Institute for Asthma and COPD), Groningen, The Netherlands
| | - Maarten van den Berge
- University of Groningen, University Medical Center Groningen, Department of Pulmonology, Groningen, The Netherlands.,University of Groningen, University Medical Center Groningen, GRIAC (Groningen Research Institute for Asthma and COPD), Groningen, The Netherlands
| | - Alen Faiz
- University of Groningen, University Medical Center Groningen, Department of Pulmonology, Groningen, The Netherlands.,University of Groningen, University Medical Center Groningen, GRIAC (Groningen Research Institute for Asthma and COPD), Groningen, The Netherlands.,University of Groningen, University Medical Center Groningen, Department of Pathology & Medical Biology, section Medical Biology, Groningen, The Netherlands.,University of Technology Sydney, Respiratory Bioinformatics and Molecular Biology (RBMB), School of life sciences, Sydney, Australia.,Woolcock Emphysema Centre, Woolcock Institute of Medical Research, University of Sydney, Sydney, NSW, Australia
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47
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Musa G, Srivastava S, Petzold J, Cazorla-Vázquez S, Engel FB. miR-27a/b is a posttranscriptional regulator of Gpr126 (Adgrg6). Ann N Y Acad Sci 2019; 1456:109-121. [PMID: 31596512 DOI: 10.1111/nyas.14245] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2019] [Revised: 09/10/2019] [Accepted: 09/13/2019] [Indexed: 12/17/2022]
Abstract
Gpr126 (Adgrg6), a member of the adhesion G protein-coupled receptor family, has been associated with a variety of human diseases. Yet, despite its clinical importance, the mechanisms regulating Gpr126 expression are poorly understood. Here, we aimed at identifying upstream regulatory mechanisms of Gpr126 expression utilizing the heart as model organ in which Gpr126 regulates trabeculation. Here, we focused on possible regulation of Gpr126 regulation by microRNAs, which have emerged as key players in regulating development, have a critical role in disease progression, and might serve as putative therapeutic targets. In silico analyses identified one conserved binding site in the 3' UTR of Gpr126 for microRNA 27a and 27b (miR-27a/b). In addition, miR-27a/b and Gpr126 expression were differentially expressed during rat heart development. A regulatory role of miR-27a/b in controlling Gpr126 expression was substantiated by reduced Gpr126 mRNA levels upon ectopic expression of miR-27a/b in HEK293T cells and miR-27b in zebrafish embryos. Regulation of Gpr126 expression by direct binding of miR-27a/b to the 3' UTR of Gpr126 was verified by luciferase reporter assays in HEK293T cells. Finally, the modulation of gpr126 expression in zebrafish by injection of either miR-27b or miR-27b inhibitor in single cell-stage embryos resulted in hypo- or hypertrabeculation, respectively. Collectively, the data indicate that Gpr126 expression is regulated by miR-27a/b.
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Affiliation(s)
- Gentian Musa
- Experimental Renal and Cardiovascular Research, Department of Nephropathology, Institute of Pathology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Swati Srivastava
- Experimental Renal and Cardiovascular Research, Department of Nephropathology, Institute of Pathology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Jana Petzold
- Experimental Renal and Cardiovascular Research, Department of Nephropathology, Institute of Pathology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Salvador Cazorla-Vázquez
- Experimental Renal and Cardiovascular Research, Department of Nephropathology, Institute of Pathology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Felix B Engel
- Experimental Renal and Cardiovascular Research, Department of Nephropathology, Institute of Pathology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
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48
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Association of rs8444 polymorphism in the LASS2 3'-UTR and bladder cancer risk in Chinese population. Eur J Cancer Prev 2019; 29:329-337. [PMID: 31577563 DOI: 10.1097/cej.0000000000000551] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
The aim of the present study was to explore the correlations between single nucleotide polymorphisms in LASS2 gene 3'-untranslated regions and bladder cancer risk in Chinese population. We first performed PCR and sequence for LASS2-3'-UTR in 105 bladder cancer patients and 100 control subjects. Next, multivariate logistic regression analysis was used to determine the relationship between single nucleotide polymorphisms frequency and susceptibility of bladder cancer, and clinical features in 105 cases. In addition, survival curves and Cox Regression analysis were used to investigate the effect of single nucleotide polymorphisms on clinical outcome in 58 cases. Finally, quantitative reverse-transcription PCR and immunohistochemical were performed to explore the influence of single nucleotide polymorphisms on LASS2 expression. We found that a single nucleotide polymorphism (rs8444 C>T) located in the 3'-UTR of LASS2 was significantly associated with the risk of bladder cancer. We also showed the frequency of rs8444 T genotype was higher in bladder cancer group and correlated with the risk of clinical prognosis. Yet, there were no significant correlations between T/C allele frequencies and the distributions of rs8444 genotype and tumor-node-metastasis stage, histological grade and distant metastasis in bladder cancer. Furthermore, we demonstrated that rs8444 C>T could affect LASS2 expression by single nucleotide polymorphism-related mRNA stability. Our results showed that LASS2-3'-UTR rs8444 C>T polymorphism was significantly associated with the individual risk and the poor overall survival of bladder cancer, suggesting that rs8444 TT genotype maybe act as an independent risk factor of susceptibility and clinical prognosis for bladder cancer in Chinese population.
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49
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Ranjan A, Singh A, Walia GK, Sachdeva MP, Gupta V. Genetic underpinnings of lung function and COPD. J Genet 2019; 98:76. [PMID: 31544798] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Spirometry based measurement of lung function is a global initiative for chronic obstructive lung disease (GOLD) standard to diagnose chronic obstructive pulmonary disease (COPD), one of the leading causes of mortality worldwide. The environmental and behavioural risk factors for COPD includes tobacco smoking, air pollutants and biomass fuel exposure, which can induce one or more abnormal lung function patterns. While smoking remains the primary risk factor, only 15-20% smokers develop COPD, indicating that the genetic factors are also likely to play a role. According to the study of Global Burden of Disease 2015, ∼174 million people across the world have COPD. From a comprehensive literature search conducted using the 'PubMed' and 'GWAS Catalogue' databases, and reviewing the literature available, only a limited number of studies were identified which had attempted to investigate the genetics of COPD and lung volumes, implying a huge research gap. With the advent of genomewide association studies several genetic variants linked to lung function and COPD, like HHIP, HTR4, ADAM19 and GSTCD etc., have been found and validated in different population groups, suggesting their potential role in determining lung volume and risk for COPD. This article aims at reviewing the present knowledge of the genetics of lung function and COPD.
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Affiliation(s)
- Astha Ranjan
- Department of Anthropology, University of Delhi, Delhi 110 007, India.
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50
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Henry AP, Probert K, Stewart CE, Thakker D, Bhaker S, Azimi S, Hall IP, Sayers I. Defining a role for lung function associated gene GSTCD in cell homeostasis. Respir Res 2019; 20:172. [PMID: 31370853 PMCID: PMC6676530 DOI: 10.1186/s12931-019-1146-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2019] [Accepted: 07/25/2019] [Indexed: 12/11/2022] Open
Abstract
Genome wide association (GWA) studies have reproducibly identified signals on chromosome 4q24 associated with lung function and COPD. GSTCD (Glutathione S-transferase C-terminal domain containing) represents a candidate causal gene in this locus, however little is currently known about the function of this protein. We set out to further our understanding of the role of GSTCD in cell functions and homeostasis using multiple molecular and cellular approaches in airway relevant cells. Recombinant expression of human GSTCD in conjunction with a GST activity assay did not identify any enzymatic activity for two GSTCD isoforms questioning the assignment of this protein to this family of enzymes. Protein structure analyses identified a potential methyltransferase domain contained within GSTCD, with these enzymes linked to cell viability and apoptosis. Targeted knockdown (siRNA) of GSTCD in bronchial epithelial cells identified a role for GSTCD in cell viability as proliferation rates were not altered. To provide greater insight we completed transcriptomic analyses on cells with GSTCD expression knocked down and identified several differentially expressed genes including those implicated in airway biology; fibrosis e.g. TGFBR1 and inflammation e.g. IL6R. Pathway based transcriptomic analyses identified an over-representation of genes related to adipogenesis which may suggest additional functions for GSTCD. These findings identify potential additional functions for GSTCD in the context of airway biology beyond the hypothesised GST activity and warrant further investigation.
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Affiliation(s)
- Amanda P Henry
- Division of Respiratory Medicine, National Institute for Health Research, Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, UK.
| | - Kelly Probert
- Division of Respiratory Medicine, National Institute for Health Research, Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, UK
| | - Ceri E Stewart
- Division of Respiratory Medicine, National Institute for Health Research, Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, UK
| | - Dhruma Thakker
- Division of Respiratory Medicine, National Institute for Health Research, Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, UK
| | - Sangita Bhaker
- Division of Respiratory Medicine, National Institute for Health Research, Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, UK
| | - Sheyda Azimi
- Division of Respiratory Medicine, National Institute for Health Research, Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, UK
| | - Ian P Hall
- Division of Respiratory Medicine, National Institute for Health Research, Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, UK
| | - Ian Sayers
- Division of Respiratory Medicine, National Institute for Health Research, Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, UK
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