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Shujuan Yin

Guangzhou Psychiatric Hospital

Publishes on Genetic Associations and Epidemiology, Obstructive Sleep Apnea Research, Sleep and related disorders. 2 papers and 16 citations.

2Publications
16Total Citations

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Top publicationsby citations

Dissecting shared genetic architecture between depression and body mass index
Hengyu Zhang, Rui Zheng, Binhe Yu et al.|BMC Medicine|2024
Cited by 15Open Access

A growing body of evidence supports the comorbidity between depression (DEP) and obesity, yet the genetic mechanisms underlying this association remain unclear. Our study explored the shared genetic architecture and causal associations of DEP with BMI. We investigated the multigene overlap and genetic correlation between DEP (N > 1.3 million) and BMI (N = 806,834) based on genome-wide association studies (GWAS) and using the bivariate causal mixture model and linkage disequilibrium score regression (LDSC). The causal association was explored by bi-directional Mendelian randomization (MR). Common risk loci were identified through cross-trait meta-analyses. Stratified LDSC and multi-marker gene annotation analyses were applied to investigate single-nucleotide polymorphisms enrichment across tissue types, cell types, and functional categories. Finally, we explored shared functional genes by Summary Data-Based Mendelian Randomization (SMR) and further detected differential expression genes (DEG) in brain tissues of individuals with depression and obesity. We found a positive genetic correlation between DEP and BMI (rg = 0.19, P = 4.07 × 10−26), which was more evident in local genomic regions. Cross-trait meta-analyses identified 16 shared genetic loci, 5 of which were newly identified, and they had influence on both diseases in the same direction. MR analysis showed a bidirectional causal association between DEP and BMI, with comparable effect sizes estimated in both directions. Combined with gene expression information, we found that genetic correlations between DEP and BMI were enriched in 6 brain regions, predominantly in the nucleus accumbens and anterior cingulate cortex. Moreover, 6 specific cell types and 23 functional genes were found to have an impact on both DEP and BMI across the brain regions. Of which, NEGR1 was identified as the most significant functional gene and associated with DEP and BMI at the genome-wide significance level (P < 5 × 10−8). Compared with healthy controls, the expression levels of NEGR1 gene were significant lower in brain tissues of individuals with depression and obesity. Our study reveals shared genetic basis underpinnings between DEP and BMI, including genetic correlations and common genes. These insights offer novel opportunities and avenues for future research into their comorbidities.

Investigating the shared genetic architecture between obstructive sleep apnea and sleep‐related traits
Sizhi Ai, Hengyu Zhang, Jiaqi Liu et al.|Sleep research.|2025
Cited by 1Open Access

Abstract Background Despite a strong link between obstructive sleep apnea (OSA) and sleep traits, the shared genetic architecture remains unclear. This study aims to explore the shared genetic basis and bidirectional causal between OSA and sleep traits. Methods Using large‐scale genome‐wide association studies summary statistics for OSA and sleep traits, we employed linkage disequilibrium score regression (LDSR) and MiXeR to examine genetic correlations and quantify polygenic overlaps. The causal association was explored by bidirectional Mendelian randomization. In addition, we identified shared genomic loci through conditional and conjunctional false discovery rate (cond/conjFDR) analysis, followed by annotation to identify shared genes. Finally, we performed enrichment, developmental trajectory, and phenome‐wide association study analysis of the shared genes to explore underlying mechanisms. Results We found that both LDSR and MiXeR results revealed substantial genetic correlations and polygenic overlaps between OSA and most of sleep traits. MR analysis supported bidirectional causality between OSA and sleep traits such as insomnia and snoring. Subsequent conjFDR analysis pinpointed 168 distinct shared loci, which encompassed 695 unique genes, and these genes are predominantly enriched in the neurodevelopmental and metabolic process pathways. Notably, the expression of 38 shared genes exhibits a significant correlation with both OSA and sleep traits. These shared genes exhibit specific developmental trajectories and demonstrate significant pleiotropic associations with phenotypes such as metabolism, immunity, and brain structure. Conclusion This study uncovers the broad pleiotropy of the genetic architecture shared between OSA and sleep traits, highlighting neurodevelopmental and metabolic pathways as the key shared biological underpinnings.