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Hao Mei

Publications and source records attributed to Hao Mei.

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Genetic insights into the relationship between age at menarche and mental health-related phenotypes.

BACKGROUND: Multiple observational studies have reported associations between age at menarche (AAM) and mental health problems, yet their shared genetic architecture remains poorly characterized. METHODS: We leveraged genome-wide association study summary statistics for AAM and 15 mental health-related phenotypes. We conducted a multi-method integrative analysis encompassing linkage disequilibrium score regression, pleiotropic analysis under the composite null hypothesis, functional mapping and annotation, multi-marker analysis of genomic annotation, pathway enrichment, and bidirectional two-sample Mendelian randomization (MR) to explore shared genetic architecture and potential causal relationships. RESULTS: Our study identified significant genetic correlations between AAM and eight mental health-related phenotypes (miserableness, fed-up feelings, nervous feelings, ever thought that life is not worth living, ever self-harmed, depression, ever smoker, and age started smoking in former smokers). A total of 155 pleiotropic loci, 18 colocalized loci (e.g., 6q16.3), and 203 pleiotropic genes (e.g., LIN28B) were identified. These genes are expressed in multiple regions, including the cerebral cortex and hypothalamus, and are involved in various biological processes and signaling pathways. Additionally, MR analysis revealed causal associations between AAM and 5 mental health-related phenotypes (mood swings, miserableness, fed-up feelings, and age at which smokers started smoking in former/current smokers). CONCLUSIONS: Our study revealed extensive genetic associations between AAM and mental health-related phenotypes, and further explored the potential causal relationships between them. These findings enhance our understanding of the relationship from a genetic perspective and establish a foundation for future research to explore the biological pathways and environmental interactions contributing to these associations.

Genome-Wide Association Study