Spatially Resolved Mapping of Cells Associated with Human Complex Traits

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Authors include: Liyang Song (Zhejiang University Medical College), research direction: low back pain, clinical applications, decellularized tendons, extracellular matrix, recellularization; Wenhao Chen, Junren Hou, Minmin Guo (all from the School of Life Sciences at Westlake University); and Jian Yang (Statistics and Genetics Laboratory, School of Life Sciences at Westlake University), research direction: genome-wide association studies, integration, interdisciplinary science, humanities and social sciences. Jian Yang has achieved significant accomplishments in statistical genetics and genomic research, has won multiple international awards, and has been selected as a Clarivate Highly Cited Researcher for several consecutive years.

Abstract

• A comprehensive GWAS study was conducted on individuals of African ancestry to understand the genetic architecture of glaucoma.
• Forty-six loci significantly associated with glaucoma were identified.
• Variants in the ROCK1P1, ARHGEF12, and DBF4P2 genes may have pathophysiological significance.

Introduction

• Glaucoma is a neurodegenerative disease affecting the optic nerve, leading to progressive vision loss.
• The prevalence of glaucoma is higher in individuals of African ancestry.
• Genetic studies can help elucidate the underlying mechanisms of glaucoma.
• This study aims to identify genetic variants associated with glaucoma in individuals of African ancestry and to gain deeper insights into the genetics of this blinding familial disease.

Study Dataset

• Discovery cohort: ADAGES, GGLAD, and POAAGG studies.
• Replication cohort: GGLAD-2, All of Us, Penn Medicine BioBank, and Million Veteran Program.
• Multi-ancestry GWAS results: GBMI and NHGRI-EBI GWAS Catalog.

Discovery of Known and Previously Undescribed POAG Loci

• A total of 1,110 loci associated with POAG were identified, of which 46 reached genome-wide significance.
• Thirty-seven previously reported POAG loci were replicated.
• Variants in genes such as ROCK1P1, ARHGEF12, and DBF4P2 were discovered.

Sex-Specific Effects

• Thirty-seven loci with stronger effects in females were identified.

Replication and Meta-Analysis of POAG Associations in African Ancestry Data Sets

• Variants in the ROCK1P1 and DBF4P2 genes were replicated.

Cross-Ancestry Comparison

• Previously undescribed variants identified in African ancestry individuals had larger effect sizes.
• Variants identified in African ancestry individuals explained a substantial part of the POAG variance.

Prioritization of Causal Variants, Genes, and Pathways

• Functional fine-mapping identified 51 credible causal variant sets.
• Pathway analysis identified three pathways associated with POAG.

Quantitative Expression of POAG-Associated Genes in Human Eye Tissues

• Under oxidative stress conditions, ARHGEF12 and ROCK1P1 genes were upregulated in TM cells and iPSC-RGCs.
• The DBF4P2 gene was upregulated in retinal tissue of POAG patients.

Computational Analysis of Gene Expression in Eye Tissues

• ARHGEF12 and ROCK1P1 genes were expressed in eye tissues.

Polygenic Prediction of POAG in African Ancestry

• The PRS of African ancestry individuals had better predictive ability than that of European ancestry individuals.

Discussion

• This study expands our understanding of the genetic landscape of POAG in individuals of African ancestry.
• Variants identified in African ancestry individuals may have pathophysiological significance.
• Variants identified in African ancestry individuals may help in developing new screening and treatment methods.

Study Limitations

• The sample size of the discovery cohort is relatively small.
• The diversity of African ancestry populations may lead to low replication rates.
• Cases-controls defined by diagnostic codes may have biases.

Conclusion

• This study has made an important contribution to the genetic study of POAG in individuals of African ancestry.
• Variants identified in African ancestry individuals may help in developing new screening and treatment methods.

Q: What specific research methods were used in the paper?

• Genome-Wide Association Study (GWAS): Conducted large-scale GWAS in individuals of African ancestry to analyze the association between genetic variants and glaucoma risk.
• Meta-analysis: Integrated individual-level data from three African ancestry datasets to perform meta-analysis, enhancing statistical power.
• Functional validation: Validated the functional significance of discovered genetic variants through gene expression analysis, pathway analysis, and Mendelian randomization.
• Cross-population comparison: Compared GWAS results between African and non-African ancestry populations to analyze genetic differences across populations.
• Polygenic Risk Score (PRS): Constructed PRS based on the identified genetic variants to assess their predictive ability for glaucoma risk.

Q: What are the main research findings and outcomes?

• 46 risk loci significantly associated with glaucoma were identified: 44 of which were discovered for the first time in African ancestry populations.
• Two risk loci were validated in independent datasets: Variants in the ROCK1P1 and DBF4P2 genes were validated in independent African ancestry datasets.
• One risk locus was associated with baseline cup-to-disc ratio (CDR): Variant in the ARHGEF12 gene was associated with baseline CDR, suggesting its relevance to the pathogenesis of glaucoma.
• Genetic architecture in African ancestry populations differs from non-African ancestry populations: The genetic variants identified in African ancestry populations had larger effect sizes and lower genetic correlation with non-African ancestry populations.
• PRS can effectively predict glaucoma risk in African ancestry populations: PRS constructed based on African ancestry GWAS results outperformed PRS constructed based on non-African ancestry GWAS results in predicting glaucoma risk in African ancestry populations.

Q: What are the current limitations of this study?

• Relatively small sample size of African ancestry populations: Although it is the largest GWAS of glaucoma in African ancestry populations to date, the sample size is still smaller than many GWAS in non-African ancestry populations.
• High genetic diversity within African ancestry populations: The high genetic diversity within African ancestry populations may result in some risk loci not being validated across different subgroups.
• Some datasets used diagnostic codes to define cases/controls: The use of diagnostic codes to define cases/controls in some datasets may introduce bias.
• Study origin may serve as a confounding factor: Study origin may act as a confounding factor affecting the results, necessitating further control.