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Unravelling the GSK3?-related genotypic interaction network influencing hippocampal volume in recurrent major depressive disorder.

ABSTRACT: OBJECTIVE:Glycogen synthase kinase 3? (GSK3?) has been implicated in mood disorders. We previously reported associations between a GSK3? polymorphism and hippocampal volume in major depressive disorder (MDD). We then reported similar associations for a subset of GSK3?-regulated genes. We now investigate an algorithm-derived comprehensive list of genes encoding proteins that directly interact with GSK3? to identify a genotypic network influencing hippocampal volume in MDD. PARTICIPANTS AND METHODS:We used discovery (N=141) and replication (N=77) recurrent MDD samples. Our gene list was generated from the NetworKIN database. Hippocampal measures were derived using an optimized Freesurfer protocol. We identified interacting single nucleotide polymorphisms using the machine learning algorithm Random Forest and verified interactions using likelihood ratio tests between nested linear regression models. RESULTS:The discovery sample showed multiple two-single nucleotide polymorphism interactions with hippocampal volume. The replication sample showed a replicable interaction (likelihood ratio test: P=0.0088, replication sample; P=0.017, discovery sample; Stouffer's combined P=0.0007) between genes associated previously with endoplasmic reticulum stress, calcium regulation and histone modifications. CONCLUSION:Our results provide genetic evidence supporting associations between hippocampal volume and MDD, which may reflect underlying cellular stress responses. Our study provides evidence of biological mechanisms that should be further explored in the search for disease-modifying therapeutic targets for depression.

SUBMITTER: Inkster B

PROVIDER: S-EPMC6531290 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature

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Unravelling the GSK3β-related genotypic interaction network influencing hippocampal volume in recurrent major depressive disorder.

Inkster Becky B Simmons Andy A Cole James H JH Schoof Erwin E Linding Rune R Nichols Tom T Muglia Pierandrea P Holsboer Florian F Sämann Philipp G PG McGuffin Peter P Fu Cynthia H Y CHY Miskowiak Kamilla K Matthews Paul M PM Zai Gwyneth G Nicodemus Kristin K

Psychiatric genetics 20181001 5

<h4>Objective</h4>Glycogen synthase kinase 3β (GSK3β) has been implicated in mood disorders. We previously reported associations between a GSK3β polymorphism and hippocampal volume in major depressive disorder (MDD). We then reported similar associations for a subset of GSK3β-regulated genes. We now investigate an algorithm-derived comprehensive list of genes encoding proteins that directly interact with GSK3β to identify a genotypic network influencing hippocampal volume in MDD.<h4>Participants ...[more]

PMID: 30080747

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Project description:Background: Major Depressive Disorder (MDD) is a moderately heritable disorder with a high lifetime prevalence. At present, laboratory blood tests to support MDD diagnosis are not available. Methods: We used a classifier approach on blood gene expression profiles of a unique set of non-medicated subjects (MDD patients and controls) to select genes of which expression is predictive for disease status. To reveal blood gene expression changes related to MDD disease, we applied a powerful ex vivo stimulus to the blood, i.e. incubation with lipopolysaccharide (LPS; 10 ng/ml blood). Results: Based on LPS-stimulated blood gene expression using whole-genome microarrays in 42 subjects (primary cohort; 21 MDD patients (mean age 42.3 years), 21 healthy controls (mean age 41.9 years)), we identified a set of genes (CAPRIN1, CLEC4A, KRT23, MLC1, PLSCR1, PROK2, ZBTB16) that serves as a molecular signature of MDD. These findings were validated for the primary cohort using an independent quantitative PCR method (P = 0.007). The difference between depressive patients and controls was confirmed (P = 0.019) in a replication cohort of 13 patients with MDD (mean age 42.8 years) and 14 controls (mean age 45.6 years). The MDD-signature score comprised of expression levels of 7 genes could discriminate depressive patients from controls with sensitivity of 76.9% and specificity of 71.8%. Conclusions: We show for the first time that molecular analysis of stimulated blood cells can be used as an endophenotype for MDD diagnosis, which is a milestone in establishing biomarkers for neuropsychiatric disorders with moderate heritability in general. Our results may provide a new entry point for following and predicting treatment outcome, as well as prediction of severity and recurrence of MDD. In total, 33 MDD patients and 34 healthy controls were analyzed using basal gene expression in whole blood, and gene expression from whole blood that was stimulated with LPS for 5-6 h, using microarrays. Patients were arbitrarily selected from all patients to serve as primary cohort (nMDD = 21 (MDD01-MDD21); nControls = 21 (Con01-Con21)), or replication cohort (nMDD = 12 (MDD22-MDD35); nControls = 13 (Con22-Con37)) using microarrays. This submission does not include Samples CON21_LPS or CON30_LPS.

Dataset Information

Unravelling the GSK3?-related genotypic interaction network influencing hippocampal volume in recurrent major depressive disorder.

Publications

Unravelling the GSK3β-related genotypic interaction network influencing hippocampal volume in recurrent major depressive disorder.

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