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Meta-Analysis
. 2023 Mar;55(3):410-422.
doi: 10.1038/s41588-023-01314-0. Epub 2023 Mar 13.

Multi-ancestry genome-wide association analyses improve resolution of genes and pathways influencing lung function and chronic obstructive pulmonary disease risk

Nick Shrine #  1 Abril G Izquierdo #  2 Jing Chen #  2 Richard Packer #  2 Robert J Hall  3 Anna L Guyatt  2 Chiara Batini  2   4 Rebecca J Thompson  3 Chandan Pavuluri  5 Vidhi Malik  5 Brian D Hobbs  5   6 Matthew Moll  5 Wonji Kim  5 Ruth Tal-Singer  7 Per Bakke  8 Katherine A Fawcett  2 Catherine John  2   4 Kayesha Coley  2 Noemi Nicole Piga  2 Alfred Pozarickij  9 Kuang Lin  9 Iona Y Millwood  9   10 Zhengming Chen  9   10 Liming Li  11 China Kadoorie Biobank Collaborative GroupSara R A Wijnant  12   13   14 Lies Lahousse  13   14 Guy Brusselle  12   14 Andre G Uitterlinden  15 Ani Manichaikul  16 Elizabeth C Oelsner  17 Stephen S Rich  16 R Graham Barr  17 Shona M Kerr  18 Veronique Vitart  18 Michael R Brown  19 Matthias Wielscher  20 Medea Imboden  21   22 Ayoung Jeong  21   22 Traci M Bartz  23 Sina A Gharib  24 Claudia Flexeder  25   26   27 Stefan Karrasch  25   26   27 Christian Gieger  27   28 Annette Peters  27   29 Beate Stubbe  30 Xiaowei Hu  16 Victor E Ortega  31 Deborah A Meyers  32 Eugene R Bleecker  32 Stacey B Gabriel  33 Namrata Gupta  33 Albert Vernon Smith  34   35 Jian'an Luan  36 Jing-Hua Zhao  37 Ailin F Hansen  38 Arnulf Langhammer  39   40 Cristen Willer  41   42   43 Laxmi Bhatta  38 David Porteous  44 Blair H Smith  45 Archie Campbell  44 Tamar Sofer  46   47   48 Jiwon Lee  46 Martha L Daviglus  49 Bing Yu  50 Elise Lim  51 Hanfei Xu  51 George T O'Connor  52 Gaurav Thareja  53 Omar M E Albagha  54   55 Qatar Genome Program Research (QGPR) ConsortiumKarsten Suhre  53   56 Raquel Granell  57 Tariq O Faquih  58 Pieter S Hiemstra  59 Annelies M Slats  59 Benjamin H Mullin  60   61 Jennie Hui  62   63   64 Alan James  62 John Beilby  61   62 Karina Patasova  65   66 Pirro Hysi  65   67 Jukka T Koskela  68 Annah B Wyss  69 Jianping Jin  70 Sinjini Sikdar  69   71 Mikyeong Lee  69 Sebastian May-Wilson  72 Nicola Pirastu  72 Katherine A Kentistou  72   73 Peter K Joshi  72 Paul R H J Timmers  72 Alexander T Williams  2 Robert C Free  4   74 Xueyang Wang  4   74 John L Morrison  75 Frank D Gilliland  75 Zhanghua Chen  75 Carol A Wang  76   77 Rachel E Foong  78   79 Sarah E Harris  80 Adele Taylor  80 Paul Redmond  80 James P Cook  81 Anubha Mahajan  82   83 Lars Lind  84 Teemu Palviainen  85 Terho Lehtimäki  86 Olli T Raitakari  87   88 Jaakko Kaprio  85 Taina Rantanen  89 Kirsi H Pietiläinen  90   91 Simon R Cox  80 Craig E Pennell  76   77   92 Graham L Hall  78   79 W James Gauderman  75 Chris Brightling  4   93 James F Wilson  72   94 Tuula Vasankari  95   96 Tarja Laitinen  97 Veikko Salomaa  98 Dennis O Mook-Kanamori  58   99 Nicholas J Timpson  57   100 Eleftheria Zeggini  101   102   103 Josée Dupuis  104 Caroline Hayward  18 Ben Brumpton  39   105 Claudia Langenberg  36   106   107 Stefan Weiss  108 Georg Homuth  108 Carsten Oliver Schmidt  109 Nicole Probst-Hensch  21   22 Marjo-Riitta Jarvelin  20   110   111   112 Alanna C Morrison  19 Ozren Polasek  113 Igor Rudan  114 Joo-Hyeon Lee  115   116 Ian Sayers  3 Emma L Rawlins  117 Frank Dudbridge  2 Edwin K Silverman  5 David P Strachan  118 Robin G Walters  9   10 Andrew P Morris  119 Stephanie J London  69 Michael H Cho  5 Louise V Wain  2   4 Ian P Hall #  3 Martin D Tobin #  120   121
Collaborators, Affiliations
Meta-Analysis

Multi-ancestry genome-wide association analyses improve resolution of genes and pathways influencing lung function and chronic obstructive pulmonary disease risk

Nick Shrine et al. Nat Genet. 2023 Mar.

Erratum in

  • Author Correction: Multi-ancestry genome-wide association analyses improve resolution of genes and pathways influencing lung function and chronic obstructive pulmonary disease risk.
    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; China Kadoorie Biobank Collaborative Group; 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; Qatar Genome Program Research (QGPR) Consortium; 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,… See abstract for full author list ➔ Shrine N, et al. Nat Genet. 2023 Oct;55(10):1778-1779. doi: 10.1038/s41588-023-01531-7. Nat Genet. 2023. PMID: 37749248 Free PMC article. No abstract available.

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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Conflict of interest statement

M.D.T. and L.V.W. have previously received funding from GSK for collaborative research projects outside of the submitted work. I.P.H. has funded research collaborations with GSK, Boehringer Ingelheim and Orion. M.H.C. has received grant funding from GSK and Bayer, and speaking or consulting fees from AstraZeneca, Illumina and Genentech. B.D.H. has received grant funding from Bayer and speaking or consulting fees from AstraZeneca. I.S. has funded research collaborations with GSK, Boehringer Ingelheim and Orion outside of the submitted work. R.J.P., M.D.T., C.J. and L.V.W. have a funded research collaboration with Orion for collaborative research projects outside of the submitted work. The other authors declare no competing interests.

Figures

Fig. 1
Fig. 1. Study overview.
a, Discovery meta-analysis. *For signals present in more than one trait, the signal is only counted once (for the most significant trait). b, Pathway analyses, GRS analyses and PheWAS studies.
Fig. 2
Fig. 2. 135 genes prioritized with ≥3 variant-to-gene criteria.
The number of variant-to-gene criteria implicating the gene is in brackets after the gene name. The gray in the first eight columns indicates that at least one variant implicates the gene as causal via the evidence for that column. The last four columns indicate the level of association of the most significant variant implicating the gene as causal with respect to the FEV1/FVC decreasing allele; red indicates that this association is in the same direction of effect as the FEV1/FVC decreasing allele and blue indicates the opposite direction with the shade indicating P < the corresponding value in the legend.
Fig. 3
Fig. 3. GRS performance.
a, Prediction performance of three GRSs across ancestry groups for FEV1/FVC shown as the s.d. change in FEV1/FVC per s.d. increase in GRS for individuals in the UK Biobank grouped according to ancestry. Sample sizes: AFR, n = 4,227; AMR, n = 2,798; EAS, n = 1,564; and EUR, n = 320,656. b, Prediction performance of three GRSs for COPD shown as COPD odds ratio per s.d. increase in GRS. Sample sizes: AFR, 250 cases and 3,977 controls; AMR, n = 151 cases and 2,647 controls; EUR, 24,062 cases and 296,594 controls. UKB, UK Biobank. c, Odds ratio for COPD per s.d. change in GRS in COPD case–control studies. P values were calculated from a logistic regression adjusted for age, age squared, sex, height and principal components, followed by fixed-effect meta-analysis. d, Decile analysis meta-analyzed across five EUR studies shown as the COPD odds ratio compared between members of each decile and the reference decile. n = 11,074 (4,328 cases and 6,746 controls). Statistical tests were two-sided, the height of the bars show the point estimate of the effect and whiskers show the 95% CI. OR, odds ratio.
Fig. 4
Fig. 4. PheWAS for FEV1/FVC-weighted GRS partitioned according to elastic fiber formation.
Reactome pathway database. CP, composite phenotype and DFP, Data-Field ID phenotype (Methods). The peach-colored line means FDR 1%.
Fig. 5
Fig. 5. PheWAS for FEV1/FVC-weighted GRS partitioned according to the PI3K–Akt signaling pathway in Homo sapiens.
Kyoto Encyclopedia of Genes and Genomes. CP, composite phenotype; DFP, Data-Field ID phenotype (Methods). The peach-colored line means FDR 1%.
Fig. 6
Fig. 6. PheWAS for FEV1/FVC-weighted GRS partitioned according to hypertrophic cardiomyopathy in H. sapiens.
Kyoto Encyclopedia of Genes and Genomes. CP, composite phenotype; DFP, Data-Field ID phenotype (Methods). The peach-colored line means FDR 1%.
Fig. 7
Fig. 7. PheWAS for FEV1/FVC-weighted GRS partitioned according to signal transduction.
Reactome pathway database. CP, composite phenotype (Methods). The peach-colored line means FDR 1%.

Comment in

References

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