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Sex-specific genetic effects on susceptibility to idiopathic pulmonary fibrosis

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posted on 2025-10-13, 10:16 authored by Olivia LeavyOlivia Leavy, Anne F Goemans, Tamara Hernandez-Beeftink, Amy D Stockwell, Richard J Allen, Beatriz Guillen-Guio, Ayodeji Adegunsoye, Helen L Booth, William A Fahy, Tasha E Fingerlin, Harvinder S Virk, Ian P Hall, Simon P Hart, Mike R Hill, Nik Hirani, Naftali Kaminski, Shwu-Fan Ma, Robin J McAnulty, X Rebecca Sheng, Ann B Millar, Maria Molina-Molina, Vidya Navaratnam, Margaret Neighbors, Helen Parfrey, Gauri Saini, Ian Sayers, Mary E Strek, Martin D Tobin, Moira KB Whyte, Yingze Zhang, Toby M Maher, Philip L Molyneaux, Justin M Oldham, Brian L Yaspan, Carlos Flores, Fernando Martinez, Carl J Reynolds, David A Schwartz, Imre Noth, R Gisli Jenkins, Louise WainLouise Wain
Background Idiopathic pulmonary fibrosis (IPF) is a chronic lung condition that is more prevalent in males than females. The reasons for this are not fully understood; differing environmental exposures due to historically sex-biased occupations and diagnostic bias are possible explanations. To date, over 20 independent genetic association signals have been reported for IPF susceptibility, but these have been discovered when combining males and females. The objectives of the present study were to assess whether there is a need to consider sex-specific effects when evaluating genetic risk in clinical prediction models for IPF and to test for sex-specific associations with IPF susceptibility. Methods We performed a genome-wide single nucleotide polymorphism (SNP)-by-sex interaction study meta-analysis of IPF risk in six independent case–control studies comprising 4561 cases (1280 females, 3281 males) and 22 888 controls (8360 females, 14 528 males) of European genetic ancestry. We used polygenic risk scores (PRSs) comprising common (minor allele frequency >1%) autosomal variants to assess differences in genetic risk prediction between males and females. Results The predictive accuracy of the PRSs were similar between males and females, regardless of whether using combined or sex-specific association results. Three new independent genetic association signals were identified (p<1×10−6). Conclusions The predictive accuracy of common autosomal SNP-based PRSs did not vary significantly between males and females. We prioritised three genetic variants whose effect on IPF risk may be modified by sex. These findings would not account for the differences in prevalence between males and females. Future studies should ensure adequate representation of both sexes.<p></p>

Funding

MICA: Defining Endotypes of Pulmonary Fibrosis by Understanding the Functional Consequences of Known, and Novel, Genetic Associations with Disease

Medical Research Council

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GSK/Asthma+Lung UK Chair in Respiratory Research (C17-1)

ational Institute for Health and Care Research (NIHR) Leicester Biomedical Research Centre and the NIHR Imperial Biomedical Research Centre

Developing a biomarker guided strategy to treat patients with pulmonary fibrosis

NIHR Academy

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Genomic epidemiology of acute respiratory distress syndrome and fibrosis in patients with COVID-19

Wellcome Trust

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Genomic Analysis of Tissue and Cellular Heterogeneity in IPF

National Heart Lung and Blood Institute

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Ministerio de Ciencia e Innovación RTC-2017-6471-1 (AEI/FEDER UE)

; Instituto de Salud Carlos III PI20/00876, co-financed by the European Regional Development Fund “A Way of Making Europe” from the European Union; and Instituto Tecnológico y de Energías Renovables agreement OA23/043

Proteomic Profiling of Idiopathic Pulmonary Fibrosis Progression Trajectory

National Heart Lung and Blood Institute

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History

Author affiliation

University of Leicester College of Life Sciences Medical Sciences

Version

  • VoR (Version of Record)

Published in

ERJ Open Research

Volume

11

Issue

5

Pagination

00200 - 2025

Publisher

European Respiratory Society (ERS)

issn

2312-0541

eissn

2312-0541

Copyright date

2025

Available date

2025-10-13

Spatial coverage

England

Language

en

Deposited by

Dr Olivia Leavy

Deposit date

2025-10-07

Data Access Statement

The summary statistics for the genome-wide SNP–sex interaction meta-analysis can be accessed from https://github.com/genomicsITER/PFgenetics.

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