Stefan Ehrlich

This study identifies small but consistent anatomical correlates of negative symptom dimensions in schizophrenia, linking them to prefrontal cortical thickness and limbic subcortical volumes.

The paper conducts GWAS on brain volumes, identifies genetic loci, and develops polygenic scores with cross-ancestry predictive ability and causal links to neuropsychiatric disorders.

This study investigates how structural brain alterations in schizophrenia relate to network architecture, finding hub susceptibility and shared epicenters across disease stages and disorders.

The paper demonstrates a data harmonization process for memory testing across 53 studies, reducing inter-site variance while preserving covariate effects.

The paper shows that different behavioral patterns in mice lead to distinct brain connectivity patterns in an enriched environment.

The paper examines hemispheric asymmetry in structural covariance networks in ASD across 43 datasets, finding altered topological features in specific brain regions.

The paper analyzes cortical thickness trajectories in 17,075 individuals to show peak thickness in childhood, steep decline in early adulthood, and slower decline later, with notable exceptions and significant inter-individual variability.

The paper analyzes sex differences in brain structure variability across the lifespan using a large dataset, finding greater male variability in subcortical volumes, cortical surface area, and thickness in most regions.

This study analyzes subcortical volume changes across the lifespan using MRI data from 18,605 individuals, finding age-related declines in some structures and increases in others.

This study identifies cell types associated with brain complex traits using GWAS and single-cell transcriptomics, revealing novel roles for oligodendrocytes in Parkinson's disease.

The paper identifies genetic loci associated with human cortical structure and finds genetic correlations with neuropsychiatric disorders.

The paper estimates genetic correlations between eating disorder and substance-use-related phenotypes using GWAS data, finding both positive and negative associations.

The paper reports epigenome-wide meta-analyses of blood DNA methylation with subcortical brain volumes, identifying significant associations with hippocampal volume and potential biological mechanisms.

This study identifies altered structural brain asymmetry in autism spectrum disorder using a large-scale meta-analysis of MRI data from 1,774 ASD cases and 1,809 controls.

This study compares structural brain differences across ADHD, ASD, and OCD using MRI data from multiple cohorts, finding disorder-specific alterations in brain volume and cortical thickness.

The paper develops deep learning models to assess the quality of subcortical brain shape models from MRI, reducing human rater time by 46-70%.

This paper uses transcriptomic imputation to identify gene-tissue associations linked to Anorexia Nervosa risk, finding significant links in both brain and metabolic tissues.

The paper identifies 25 genetic loci associated with subcortical brain structure volumes in over 40,000 individuals, revealing novel biology and potential drug targets.