Jacob Bergstedt

Bakgrund: Major depressive disorder (MDD) is associated with a substantial reduction in life expectancy due to comorbidity with cardiovascular disease (CVD). Despite repeated calls for action, limited progress has been made in addressing this mortality gap. This failure reflects a lack of understanding of pathophysiological mechanisms linking MDD with CVD. Målsättning: This research program hypothesizes that an atherogenic circulating metabolite and protein signature is responsible for the link between MDD and CVD. The program aims to 1) map how MDD relates to progression, localization, and composition of atherosclerotic plaque, 2) comprehensively assess atherogenic metabolite and protein pathways linking MDD with CVD, and finally 3) leverage the large-scale metabolomics and proteomics data together with state-of-the-art machine learning models to build models capable of predicting CVD in individuals with MDD with enough accuracy to be clinically useful. Arbetsplan: The program will triangulate population-level, discordant twin, and Mendelian randomization (MR) analyses to yield stronger evidence by overcoming the weaknesses of any single approach. Discordant twin analysis adjusts for all genetic and environmental factors shared between co-twins, while MR adjusts for unmeasured confounding. Moreover, by leveraging multiple international cohorts, this program will compare and aggregate results across countries, which provides built-in replication and improves the generalizability of the results. Betydelse: This program has the potential to substantially advance the state-of-the-art in the field of MDD-CVD comorbidity and to provide models capable of predicting CVD in individuals with MDD with enough accuracy to form the basis for secondary prevention screening programs.

Children with autism are transitioning into adulthood. Emerging evidence suggests an increased risk of early-onset dementia among individuals with autism and a higher risk of any dementia among their family members. However, existing studies have primarily treated autism and dementia as binary variables, overlooking the fact that autism represents a continuum of symptoms, while dementia likely involves a prolonged neurodegenerative process leading to its onset.The overarching aim of this project is to utilize pre-existing cohorts with individual-level data on genotyping and various neurodegeneration markers to examine the relationship between genetic liability for autism and neurodegeneration. We will compare: 1) the risk of cognitive decline and its progression to dementia

2) measures of brain aging

and 3) the burden of known risk factors and antecedent conditions for dementia between individuals with high versus low genetic liability for autism. Additionally, we will conduct -omics analyses to investigate biological pathways for the link between autism and dementia.The large sample size, unique data access, cutting-edge analytical approaches, cross-country comparisons, and an experienced and dedicated research team underscore the scientific novelty and significance of this project. The findings from this research will have important implications for developing targeted interventions aimed at preventing or delaying the onset of dementia in the autistic population.