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Record W4404788147 · doi:10.1101/2024.11.25.24317794

Multi-ancestry genome-wide association study reveals novel genetic signals for lung function decline

2024· preprint· en· W4404788147 on OpenAlexaff
Bonnie Patchen, Jingwen Zhang, Nathan Gaddis, Traci M. Bartz, Jing Chen, Catherine L. Debban, Hampton L. Leonard, Ngoc Quynh Nguyen, Courtney Tern, Richard J. Allen, Dawn L. DeMeo, Myriam Fornage, Carl Melbourne, Melyssa S. Minto, Matthew Moll, George O'connor, Tess D. Pottinger, Bruce M. Psaty, Stephen S. Rich, Edwin K. Silverman, Jeran K. Stratford, R. Graham Barr, Michael H. Cho, Sina A. Gharib, Ani Manichaikul, Kari North, Elizabeth C. Oelsner, Eleanor M. Simonsick, Martin D. Tobin, Bing Yu, Seung Hoan Choi, Josée Dupuis, Patricia A. Cassano, Dana B. Hancock

Bibliographic record

VenuemedRxiv · 2024
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Associations and Epidemiology
Canadian institutionsMcGill University
FundersNational Heart, Lung, and Blood InstituteNIHR Leicester Biomedical Research CentreNational Institutes of HealthNational Institute of Nursing ResearchUniversity of LeicesterNational Institute for Health and Care ResearchUK Research and InnovationBroad InstituteWellcome Trust
KeywordsGenome-wide association studyLung functionAssociation (psychology)Genetic associationBiologyFunction (biology)Evolutionary biologyComputational biologyGenomeGenetic genealogyGeneticsMedicineSingle-nucleotide polymorphismGenotypeLungEnvironmental healthInternal medicinePsychologyGenePopulation

Abstract

fetched live from OpenAlex

Abstract Rationale Accelerated decline in lung function contributes to the development of chronic respiratory disease. Despite evidence for a genetic component, few genetic associations with lung function decline have been identified. Objectives To evaluate genome-wide associations and putative downstream functionality of genetic variants with lung function decline in diverse general population cohorts. Methods We conducted genome-wide association study (GWAS) analyses of decline in the forced expiratory volume in the first second (FEV 1 ), forced vital capacity (FVC), and their ratio (FEV 1 /FVC) in participants across six cohorts in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the UK Biobank. Genotypes were imputed to TOPMed (CHARGE cohorts) or Haplotype Reference Consortium (HRC) (UK Biobank) reference panels, and GWAS analyses used generalized estimating equation models with robust standard error. Models were stratified by cohort, ancestry, and sex, and adjusted for important lung function confounders and genotype principal components. Results were combined in cross-ancestry and ancestry-specific meta-analyses. Selected top variants were tested for replication in two independent COPD-enriched cohorts. Measurements and Main Results Our discovery analyses included 52,056 self-reported White (N=44,988), Black (N=5,788), Hispanic (N=550), and Chinese American (N=730) participants with a mean of 2.3 spirometry measurements and 8.6 years of follow-up. Functional mapping of GWAS meta-analysis results identified 361 distinct genome-wide significant (p<5E-08) variants in one or more of the FEV 1 , FVC, and FEV 1 /FVC decline phenotypes, which overlapped with previously reported genetic signals for several related pulmonary traits. Of these, 8 variants, or 20.5% of the variant set available for replication testing, were nominally associated (p<0.05) with at least one decline phenotype in COPD-enriched cohorts (White [N=4,778] and Black [N=1,118]). Using the GWAS results, gene-level analysis implicated 38 genes, including eight ( XIRP2 , GRIN2D , SATB1 , MARCHF4 , SIPA1L2 , ANO5 , H2BC10 , and FAF2 ) with consistent associations across ancestries or decline phenotypes. Annotation class analysis revealed significant enrichment of several regulatory processes for corticosteroid biosynthesis and metabolism. Drug repurposing analysis identified 43 approved compounds targeting eight of the implicated 38 genes. Conclusions Our multi-ancestry GWAS meta-analyses identified numerous genetic loci associated with lung function decline. These findings contribute knowledge to the genetic architecture of lung function decline, provide evidence for a role of endogenous corticosteroids in the etiology of lung function decline, and identify drug targets that merit further study for potential repurposing to slow lung function decline and treat lung disease.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.040
GPT teacher head0.324
Teacher spread0.283 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

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