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Stefan Kloiber

Publications and source records attributed to Stefan Kloiber.

2 recordsLinked to original sources

Exploring sex differences in endocannabinoid system biomarkers and their relationship with antidepressant treatment outcomes in major depressive disorder: a CAN-BIND 1 secondary analysis.

BACKGROUND: Sex differences in major depressive disorder (MDD) are well documented, but it remains unclear whether sex-related variation in peripheral endocannabinoid system (ECS)-related biomarkers is detectable in MDD. OBJECTIVES: To examine baseline sex differences in ECS-related mRNA expression, DNA methylation, and single nucleotide polymorphisms (SNPs) in MDD, and associations between baseline ECS markers and antidepressant outcomes in sex-stratified analyses. METHODS: Among 178 participants with MDD from CAN-BIND-1, all received escitalopram for 8 weeks; non-responders then received adjunctive aripiprazole from Weeks 8-16.Response was defined as ≥ 50% reduction in MADRS score, and remission as MADRS ≤ 10. ANCOVAs examined baseline sex differences and sex-stratified biomarker associations with percent MADRS reduction at Weeks 8 and 16, as well as categorical response and remission outcomes. Covariates included site, baseline MADRS, age, and ethnicity. False discovery rate correction was applied. RESULTS: Baseline sex differences in methylation were observed for CACNA1H, GABRB2, MAGL, and GABRR2, though none survived correction. No baseline sex differences in mRNA expression or SNPs were detected after correction. Lower baseline DAGLA mRNA in males was associated with greater Week 8 symptom improvement (FDR corrected). This association was not observed in females. No associations with response or remission at Weeks 8 or 16 survived correction. IMPLICATIONS: Baseline sex differences in peripheral ECS-related markers were not detected in this sample. Larger studies are needed to verify whether ECS-related biomarkers, particularly DAGLA, contribute to antidepressant outcomes in a sex-specific manner.

Humans

Pharmacogenomics of antipsychotic-induced weight gain: A systematic review.

BACKGROUND: Antipsychotic-induced weight gain (AIWG) is a major clinical concern, affecting approximately 30% of patients. Clinical predictors explain only part of AIWG risk. Genetic and molecular variations are hypothesized to contribute to susceptibility. The purpose of this review is to summarize recent results to identify replicated and novel findings. STUDY DESIGN: Applying PRISMA guidelines, we searched MEDLINE, Embase, and PsycINFO (May 2018-May 2026) for studies on genetic and molecular associations with AIWG, extending our prior review. Reviews, editorials, and conference abstracts were excluded. We extracted study characteristics (design, diagnosis, antipsychotic exposure, sample size, ancestry, genetic variants, and AIWG outcomes) (e.g., ≥7% weight gain, BMI change). RESULTS: Fifty-three studies met inclusion criteria. In candidate gene studies, the most consistently replicated genes associated with AIWG were observed for DRD2, HTR2C, and MC4R. Multiple novel associations were identified by genome-wide association studies (GWAS) (e.g., MAP2K1, ZDBF2, PEPD), polygenic risk scores (PRS) (e.g., body mass index PRS), gene expression (e.g., CYP3A4, EP300), and epigenetic analyses (e.g., cg12034943 at CRTC1). CONCLUSIONS: Polymorphisms in candidate genes related to neurotransmission and appetite regulation continue to be investigated for associations with AIWG, while novel findings have emerged from GWAS, gene expression, and epigenetic studies. Evidence remains inconsistent due to limited replication, methodological variability, sparse ancestry data, and geographical underrepresentation. No single genetic variant is ready for clinical use, and multi-omic and multi-ancestry models are needed to improve prediction and clinical utility.

Humans