Lipidoconnectomics–A large-scale analysis of the interconnection between the lipidome and white matter brain connectivity across the affective disorder spectrum

• Applicants: Professor Dr. Jonathan Repple; Professorin Dr. Eva-Christina Schulte
• Subject Area: Biological Psychiatry ; Human Cognitive and Systems Neuroscience
• Term: since 2025
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 565437584

Affective disorders, including depression and bipolar disorder, are complex conditions with substantial heterogeneity in their clinical presentation, underlying biology, and treatment responses. To address these challenges, this project seeks to leverage cutting-edge lipidomics and multiomics techniques in conjunction with neuroimaging to uncover novel molecular insights into affective disorders. The central research question aims at identifying a mechanistic pathway from lipidome alterations to clinical phenomenology via white matter microstructural brain disturbances in affective disorders. Building on the deeply phenotyped DFG-funded MACS cohort of 3,000 individuals with affective disorders and healthy controls, this study will achieve the following aims: 1) Generate Comprehensive Lipidomic Profiles. This will develop one of the world’s largest plasma lipidomic datasets for affective disorders, providing unprecedented resources and granularity to explore lipid-based biomarkers and pathways. 2) Expand and Refine Lipidomic Associations. This will validate and broaden current findings in lipidomics by integrating the MACS cohort’s extensive deep-phenotyping data, enabling greater specificity in identifying lipidomic markers linked to affective disorders. 3) Link Lipidomics to Brain Connectivity. We will perform integrative analyses of plasma lipidomic profiles and measures of brain connectivity to elucidate how lipidomic alterations influence the connectome in individuals with affective disorders or vice versa. 4) Identify Multimodal Molecular Biotypes. Finally, we will use a multiomics approach—integrating genomic, lipidomic, and neuroimaging data—to uncover molecular subtypes across the affective spectrum, focusing on biotypes associated with clinical outcomes and treatment responses. By combining lipidomics with genomic and neuroimaging data using data augmentation approaches in an existing dataset, this project will push the boundaries of precision psychiatry, revealing novel biomarkers and mechanistic insights into the biological underpinnings of affective disorders. The results will provide actionable targets for improving diagnosis, prognosis, and personalized treatment strategies, with broad implications for mental health research and care.

• DFG Programme: Research Grants