Background: Endometriosis is a chronic inflammatory condition affecting 10–15% of women of reproductive age. Genome-wide association studies (GWASs) have accounted for only a fraction of its high heritability, indicating the need for alternative approaches to identify rare genetic variants contributing to its etiology. To this end, we performed whole-exome sequencing (WES) in a multi-affected family. Methods: A multigenerational family was studied, comprising three sisters, their mother, grandmother, and a daughter, all diagnosed with endometriosis. WES was conducted on the three sisters and their mother. We used the enGenome-Evai and Varelect software to perform our analysis, which mainly focused on rare, missense, frameshift, and stop variants. Results: Bioinformatic analysis identified 36 co-segregating rare variants. Six missense variants in genes associated with cancer growth were prioritized. The top candidates were c.3319G>A (p.Gly1107Arg) in the LAMB4 gene and c.1414G>A (p.Gly472Arg) in the EGFL6 gene. Variants in NAV3, ADAMTS18, SLIT1, and MLH1 may also contribute to disease onset through a synergistic and additive model. Conclusions: We identified novel candidate genes for endometriosis in a multigenerational affected family, supporting a polygenic model of the disease. Our study is an exploratory family-based WES study, and replication and functional studies are warranted to confirm these preliminary findings.
Identification of Candidate Genes for Endometriosis in a Three-Generation Family with Multiple Affected Members Using Whole-Exome Sequencing
Lintas, Carla;Panasiti, Vincenzo;Gurrieri, Fiorella
2025-01-01
Abstract
Background: Endometriosis is a chronic inflammatory condition affecting 10–15% of women of reproductive age. Genome-wide association studies (GWASs) have accounted for only a fraction of its high heritability, indicating the need for alternative approaches to identify rare genetic variants contributing to its etiology. To this end, we performed whole-exome sequencing (WES) in a multi-affected family. Methods: A multigenerational family was studied, comprising three sisters, their mother, grandmother, and a daughter, all diagnosed with endometriosis. WES was conducted on the three sisters and their mother. We used the enGenome-Evai and Varelect software to perform our analysis, which mainly focused on rare, missense, frameshift, and stop variants. Results: Bioinformatic analysis identified 36 co-segregating rare variants. Six missense variants in genes associated with cancer growth were prioritized. The top candidates were c.3319G>A (p.Gly1107Arg) in the LAMB4 gene and c.1414G>A (p.Gly472Arg) in the EGFL6 gene. Variants in NAV3, ADAMTS18, SLIT1, and MLH1 may also contribute to disease onset through a synergistic and additive model. Conclusions: We identified novel candidate genes for endometriosis in a multigenerational affected family, supporting a polygenic model of the disease. Our study is an exploratory family-based WES study, and replication and functional studies are warranted to confirm these preliminary findings.| File | Dimensione | Formato | |
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