NORMENT, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway.
Mol Psychiatry. 2024 Aug;29(8):2467-2477. doi: 10.1038/s41380-024-02513-9. Epub 2024 Mar 19.
Sex differences in the epidemiology and clinical characteristics of schizophrenia are well-known; however, the molecular mechanisms underlying these differences remain unclear. Further, the potential advantages of sex-stratified meta-analyses of epigenome-wide association studies (EWAS) of schizophrenia have not been investigated. Here, we performed sex-stratified EWAS meta-analyses to investigate whether sex stratification improves discovery, and to identify differentially methylated regions (DMRs) in schizophrenia. Peripheral blood-derived DNA methylation data from 1519 cases of schizophrenia (male n = 989, female n = 530) and 1723 controls (male n = 997, female n = 726) from three publicly available datasets, and the TOP cohort were meta-analyzed to compare sex-specific, sex-stratified, and sex-adjusted EWAS. The predictive power of each model was assessed by polymethylation score (PMS). The number of schizophrenia-associated differentially methylated positions identified was higher for the sex-stratified model than for the sex-adjusted one. We identified 20 schizophrenia-associated DMRs in the sex-stratified analysis. PMS from sex-stratified analysis outperformed that from sex-adjusted analysis in predicting schizophrenia. Notably, PMSs from the sex-stratified and female-only analyses, but not those from sex-adjusted or the male-only analyses, significantly predicted schizophrenia in males. The findings suggest that sex-stratified EWAS meta-analyses improve the identification of schizophrenia-associated epigenetic changes and highlight an interaction between sex and schizophrenia status on DNA methylation. Sex-specific DNA methylation may have potential implications for precision psychiatry and the development of stratified treatments for schizophrenia.
性别在精神分裂症的流行病学和临床特征方面存在差异,这是众所周知的;然而,这些差异背后的分子机制仍不清楚。此外,尚未研究精神分裂症表观基因组全基因组关联研究(EWAS)的性别分层荟萃分析的潜在优势。在这里,我们进行了性别分层的 EWAS 荟萃分析,以研究性别分层是否可以提高发现率,并确定精神分裂症中差异甲基化区域(DMR)。我们对来自三个公开数据集和 TOP 队列的 1519 例精神分裂症病例(男性 n=989,女性 n=530)和 1723 例对照(男性 n=997,女性 n=726)的外周血源性 DNA 甲基化数据进行了性别分层 EWAS 荟萃分析,以比较特定性别、性别分层和性别调整的 EWAS。通过多甲基化评分(PMS)评估每个模型的预测能力。与性别调整模型相比,性别分层模型确定的与精神分裂症相关的差异甲基化位置数量更高。我们在性别分层分析中确定了 20 个与精神分裂症相关的 DMR。性别分层分析的 PMS 在预测精神分裂症方面优于性别调整分析的 PMS。值得注意的是,来自性别分层和女性独有的分析的 PMS,而不是来自性别调整或男性独有的分析的 PMS,在男性中显著预测了精神分裂症。这些发现表明,性别分层的 EWAS 荟萃分析可以提高与精神分裂症相关的表观遗传变化的识别能力,并强调了性别和精神分裂症状态对 DNA 甲基化的相互作用。性别特异性 DNA 甲基化可能对精准精神病学和精神分裂症分层治疗的发展具有潜在意义。