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. 2023 May 11;15(1):36.
doi: 10.1186/s13073-023-01186-3.

Sex differences in the polygenic architecture of hearing problems in adults

Flavio De Angelis  1   2 , Oana A Zeleznik  3   4 , Frank R Wendt  1   2 , Gita A Pathak  1   2 , Daniel S Tylee  1   2 , Antonella De Lillo  1   5 , Dora Koller  1   2   6 , Brenda Cabrera-Mendoza  1   2 , Royce E Clifford  7   8 , Adam X Maihofer  8   9   10 , Caroline M Nievergelt  8   9   10 , Gary C Curhan  3   4 , Sharon G Curhan  3   4 , Renato Polimanti  11   12
Affiliations

Sex differences in the polygenic architecture of hearing problems in adults

Flavio De Angelis et al. Genome Med. .

Abstract

Background: Hearing problems (HP) in adults are common and are associated with several comorbid conditions. Its prevalence increases with age, reflecting the cumulative effect of environmental factors and genetic predisposition. Although several risk loci have been already identified, HP biology and epidemiology are still insufficiently investigated by large-scale genetic studies.

Methods: Leveraging the UK Biobank, the Nurses' Health Studies (I and II), the Health Professionals Follow-up Study, and the Million Veteran Program, we conducted a comprehensive genome-wide investigation of HP in 748,668 adult participants (discovery N = 501,825; replication N = 226,043; cross-ancestry replication N = 20,800). We leveraged the GWAS findings to characterize HP polygenic architecture, exploring sex differences, polygenic risk across ancestries, tissue-specific transcriptomic regulation, cause-effect relationships with genetically correlated traits, and gene interactions with HP environmental risk factors.

Results: We identified 54 risk loci and demonstrated that HP polygenic risk is shared across ancestry groups. Our transcriptomic regulation analysis highlighted the potential role of the central nervous system in HP pathogenesis. The sex-stratified analyses showed several additional associations related to peripheral hormonally regulated tissues reflecting a potential role of estrogen in hearing function. This evidence was supported by the multivariate interaction analysis that showed how genes involved in brain development interact with sex, noise pollution, and tobacco smoking in relation to their HP associations. Additionally, the genetically informed causal inference analysis showed that HP is linked to many physical and mental health outcomes.

Conclusions: The results provide many novel insights into the biology and epidemiology of HP in adults. Our sex-specific analyses and transcriptomic associations highlighted molecular pathways that may be targeted for drug development or repurposing. Additionally, the potential causal relationships identified may support novel preventive screening programs to identify individuals at risk.

Keywords: Ancestry; Polygenic risk scores; Causal inference; Genome-wide association study; Genome-wide gene-by-environment interaction; Hearing problems; Pleiotropy; Sex differences; Transcriptomic regulation.

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Conflict of interest statement

Dr. Clifford reported receiving personal fees from Decibel Therapeutics outside the submitted work. Dr. S. Curhan serves as a consultant to Decibel Therapeutics. Dr. G. Curhan serves as a consultant to Decibel Therapeutics, AstraZeneca, Shire, Allena Pharmaceuticals, RenalGuard, OrfanBiotech, OM1, and Merck. He receives royalties from UpToDate for being an author and Section Editor. Dr. Polimanti is paid for his editorial work on the journal Complex Psychiatry and received a research grant outside the scope of this study from Alkermes. The remaining authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Genetic correlation among hearing-problem traits assessed via questionnaire in the UK Biobank. The square shade intensity is proportional to the magnitude of the correlation. Details regarding the results shown are available in Additional file 1: Table S4
Fig. 2
Fig. 2
Multi-tissue transcriptome-wide association study of hearing problems based on the sex-combined meta-analysis. The y-axis corresponds to two-tailed − log10 (p-value of the S-MultiXcan association). The x-axis reports the genes grouped based on the best single-tissue S-PrediXcan association. The red line refers to the Bonferroni multiple testing correction accounting for the number of genes tested (N = 22,335; p < 2.24 × 10.−6). Bold labels are reported for the top-10 Bonferroni significant association. Additional labels are included for the top significant result for each tissue. Detailed results are available in Additional file 1: Table S16
Fig. 3
Fig. 3
Phenome-wide genetic correlation of hearing problems in the sex-combined analysis. The x-axis reports the genetic correlation of hearing problems with the traits tested. The y-axis corresponds to two-tailed − log10(p-value). Blue shades correspond to significance strength, from white, non-significant (p > 0.05), to light blue (nominal significance p < 0.05), to blue (Bonferroni correction p < 6.99 × 10.−6), and dark blue (top 10 results). Phenotype labels are included for the top 10 results. Full results are reported in Additional file 1: Table S19
Fig. 4
Fig. 4
Visual representation of the 22 Bonferroni-significant putative causal effects identified through the latent causal variable analysis. Brown labels: HP has causative effect on the trait in the label. Purple labels: Trait in the label has causative effect on HP. The absolute gcp (genetic causality proportion) value for each association is reported within the arrow, and the directions refer to the cause-effect relationship (Blue: HP causes Trait; Red: Trait causes HP). The shade intensity of the arrows is proportional to the statistical significance (i.e., − log10(p-value)) of the gcp estimates. A description of each trait and details of the associations are available in Additional file 1: Table S20
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