Christian G. Schmahl

The paper examines how childhood maltreatment affects brain structure in 3,711 individuals with MDD and PTSD, finding age- and sex-specific brain morphometric differences.

IBMMA improves neuroimaging analysis by handling missing data and large datasets, revealing new brain region findings overlooked by traditional methods.

The paper investigates the neural basis of negative affective traits using fMRI data from 458 adults, finding that whole-brain machine learning models better predict stress vulnerability than region- or network-level measures.

This paper classifies PTSD vs. controls using MRI data from multiple sites, finding better performance when distinguishing PTSD from trauma-unexposed controls than trauma-exposed controls, and showing DVAE improves generalizability.

This study finds smaller total and subregional cerebellar volumes in PTSD compared to controls using a large dataset and advanced parcellation methods.

This paper compares four methods for harmonizing cortical thickness data across multiple sites and finds that ComBat-GAM is most effective in detecting case-control differences and age-related cortical thinning.

This paper conducts a multi-ancestry GWAS meta-analysis of suicide attempt, identifying 12 genome-wide significant loci and finding shared genetic risks with ADHD, smoking, and risk tolerance.

This study identifies genetic loci associated with suicide attempts and shows shared genetic architecture with psychiatric disorders and non-psychiatric risk factors.

This study examines structural covariance networks in PTSD using a large multisite dataset, finding differences in centrality measures between PTSD and control groups, and highlighting sex-based and comorbid differences.

This study identifies hippocampal subfield volume differences in PTSD and depression across 31 cohorts, finding depression has a stronger effect than PTSD, especially in CA1, with comorbid cases showing more pronounced changes.