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Purpose: This study was conducted to elucidate the distribution and determinants of ocular biometric parameters and to assess the association between intraocular pressure (IOP) and single nucleotide polymorphisms (SNPs) in the Japanese population-based genome cohort studies.
Design: Cross-sectional analysis involving genome-wide association studies (GWASs).
Participants: In total, 22 150 participants aged >18 years from the population cohort (Community-Based Cohort [CommCohort]) and 11 302 participants from the Birth and Three-Generation (BirThree) Cohort of the Tohoku Medical Megabank Organization Eye Study were examined.
Methods: Participant underwent interviews, ophthalmic and physiological examinations, laboratory tests, and microarray analyses. Genome-wide association studies were conducted in the CommCohort (discovery stage) and the BirThree Cohort (replication stage), followed by a meta-analysis. Associations of SNPs and IOP were evaluated using a genome-wide significance threshold (5 × 10 ).
Main Outcome Measures: Association of SNPs with IOP and distributions of IOP by sex and age.
Results: In the discovery stage, the mean IOP of the right and left eye was 13.95 and 14.02 mmHg, respectively. In the replication stage, the corresponding values were 14.32 and 14.27 mmHg, respectively. A significant age-related reduction in IOP was observed in both stages ( < 0.001). Genome-wide association studies identified 573 and 2 genome-wide significant SNPs in the discovery and replication stages, respectively. Meta-analysis revealed 1601 significant SNPs across 21 loci on 11 chromosomes (Chrs). Of these loci, 17 were previously known to be associated with IOP or glaucoma, while four-septin-8 (; Chr5), aldehyde dehydrogenase 2 (; Chr12), collagen type VI alpha 2 chain (; Chr21), and Wnt family member 7B (; Chr22)-were newly identified.
Conclusions: This large-scale GWAS in a Japanese population identified 21 loci associated with IOP, including 4 novel loci. The findings highlight both genetic similarities and population-specific variations in SNPs influencing IOP and provide valuable insights to enhance eye health care, including glaucoma management.
Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.
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http://dx.doi.org/10.1016/j.xops.2025.100821 | DOI Listing |
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College of Horticulture, Gansu Agricultural University, Lanzhou 730070, China.
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View Article and Find Full Text PDFJ Clin Periodontol
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Int J Eat Disord
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Department of Physiology, Monash University, Clayton, Victoria, Australia.
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HGG Adv
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Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 21205, USA; Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 21205, USA. Electronic address:
Pleiotropy, the phenomenon where a genetic region confers risk to multiple traits, is widely observed, even among seemingly unrelated traits. Knowledge of pleiotropy can improve understanding of biological mechanisms of diseases/traits, and can potentially guide identification of molecular targets or help predict side-effects in drug development. However, statistical approaches for identifying pleiotropy genome-wide are limited, particularly for two correlated traits or case-control traits with unknown sample overlap or for disease traits from family studies.
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