Sex-differential DNA methylation and associated regulation networks in human brain implicated in the sex-biased risks of psychiatric disorders
Open accessAbstract
Many psychiatric disorders are characterized by a strong sex difference, but the mechanisms behind sex-bias are not fully understood. DNA methylation plays important roles in regulating gene expression, ultimately impacting sexually different characteristics of the human brain. Most previous literature focused on DNA methylation alone without considering the regulatory network and its contribution to sex-bias of psychiatric disorders. Since DNA methylation acts in a complex regulatory network to connect genetic and environmental factors with high-order brain functions, we investigated the regulatory networks associated with different DNA methylation and assessed their contribution to the risks of psychiatric disorders. We compiled data from 1408 postmortem brain samples in 3 collections to identify sex-differentially methylated positions (DMPs) and regions (DMRs). We identified and replicated thousands of DMPs and DMRs. The DMR genes were enriched in neuronal related pathways. We extended the regulatory networks related to sex-differential methylation and psychiatric disorders by integrating methylation quantitative trait loci (meQTLs), gene expression, and protein-protein interaction data. We observed significant enrichment of sex-associated genes in psychiatric disorder-associated gene sets. We prioritized 2080 genes that were sex-biased and associated with psychiatric disorders, such as NRXN1, NRXN2, NRXN3, FDE4A, and SHANK2. These genes are enriched in synapse-related pathways and signaling pathways, suggesting that sex-differential genes of these neuronal pathways may cause the sex-bias of psychiatric disorders.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Sex biased genes are present in both sexes but express different quantities of protein products in men and women due to epigenetic factors or sex hormone levels.
“These are genes that are present in both sexes but that express different quantities of protein products in men and women due to the impact of either epigenetic factors or sex hormone levels (52).”
From Where Sex Meets Gender: How Sex and Gender Come Together to Cause Sex Differences in Mental Illness (2022) · cites this paper as [52]
The Introduction describes epigenetic modifications as candidates for explaining sex differences, and the Results section on regulatory networks links sex-differential DNA methylation with gene expression. The paper does not establish that men and women produce different quantities of the resulting proteins or that sex hormone levels cause such differences; it mentions hormones as a proposed explanation for sex bias in psychiatric disorders. (LLM, conf=0.84)
Experimental — accuracy not yet measuredPrevious studies have shown that epigenetics is an important contributor to the sex differences in brain functions and vulnerability to diseases.
“Previous studies have shown that epigenetics is an important contributor to the sex differences in brain functions and vulnerability to diseases [12–16]”
From Sex-specific DNA methylation differences in Alzheimer’s disease pathology (2021) · cites this paper as [16]
The Introduction says DNA methylation plays important roles in sexually differential characteristics of the human brain. It also says whether the associated regulatory networks influence sex bias in psychiatric disorders was unknown; the study investigates potential involvement and reports associations with disorder-related genes, rather than establishing epigenetics as a contributor to disease vulnerability. The claim states that contribution more firmly and broadly than this paper supports. (LLM, conf=0.82)
Experimental — accuracy not yet measuredAmong 451 unique CpGs identified in our sex-stratified analysis or sex-by-Braak stage interaction analysis, only 16 were also identified in Xia et al. and none were identified in Xu et al.
“Among 451 unique CpGs identified in our sex-stratified analysis or sex-by-Braak stage interaction analysis, only 16 were also identified in Xia et al. [16] and none were identified in Xu et al. [17]”
From Sex-specific DNA methylation differences in Alzheimer’s disease pathology (2021) · cites this paper as [16]
The comparison with Xia et al. and Xu et al. showed our results were largely distinct.
“The comparison with Xia et al. [16] and Xu et al. [17], which examined differential methylation between males and females in the prefrontal cortex, but without considering AD neuropathology [16, 17], showed our results were largely distinct.”
From Sex-specific DNA methylation differences in Alzheimer’s disease pathology (2021) · cites this paper as [16]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
The citation lists haven’t been fetched yet
References 80 · Cited by 80
Research works printed but not linked: 1
- [73]McCarthy NS, Melton PE, Cadby G, Yazar S, Franchina M, Moses EK Meta-analysis of human methylation data for evidence of sex-specific autosomal patterns. BMC genomics 2014; 15(981): 981. 25406947 PMC4255932
- Authors
- Xia, Y., Dai, R., Wang, K., Jiao, C., Zhang, C., Xu, Y., Li, H., Jing, X., Chen, Y., Jiang, Y., Kopp, R. F., Giase, G., Chen, C., & Liu, C.
- Affiliations
- Central South University (CN)
- SUNY Upstate Medical University (US)
- University of Illinois Chicago (US)
- Corresponding author
- Chen, Chao
- Liu, Chunyu
- ORCID
- Venue
- Molecular Psychiatry
- Published
- 2019-04-11
- Volume
- 26
- Issue
- 3
- Pages
- 835-848
- ISSN
- 1359-4184 (ISSN-L)
- 1476-5578
- PMC
- PMC6788945
- OpenAlex
- W2940280400
- Cited by
- 80
- References
- 80
- Citations by year
- 2026: 5 · 2025: 17 · 2024: 14 · 2023: 11 · 2022: 18 · 2021: 8 · 2020: 4 · 2019: 3
- FWCI
- 3.21
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- Locations
- Molecular Psychiatry (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (1R01ES024988, 1U01MH116489, 1R01MH110920, 1U01MH103340)
- National Natural Science Foundation of China (81401114, 31571312)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetics and Neurodevelopmental Disorders
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Sexual Differentiation and Disorders
- Keywords
- sex-biased gene expression, regulatory networks, methylation quantitative trait loci, postmortem brain, Shank2, neural pathways
- MeSH terms
- Mental Disorders, Brain, Female, Humans, Male, CpG Islands, DNA Methylation, Quantitative Trait Loci, Epigenesis, Genetic
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
