Modelling the influence of the gut microbiome on patterns of brain aging in the general population by combining constraint-based modelling approaches with large cohort magnet resonance imaging data

• Applicants: Dr. Fabian Frost; Professor Dr. Johannes Hertel
• Subject Area: Biological Psychiatry ; Bioinformatics and Theoretical Biology ; Gastroenterology
• Term: since 2022
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 497582271

The gut microbiome contributes crucially to human metabolism and thereby to human health and disease. It provides otherwise inaccessible nutrients and generates valuable metabolic products. At the same time, it also contributes harmful and toxic metabolites. The gut-brain-axis, describing the complex interplay between the human digestive tract and the central nervous system, is fundamentally shaped by the metabolic activity of the gut microbiome. Previous research has pointed out a connection between changes in the gut microbiome community composition and neurodegenerative disorders such as Alzheimer’s Diseases and Parkinson’s disease, both of which pathophysiology are closely related to brain aging. The core research aim of this proposal is now to shed light on the influence of the gut microbiome’s metabolic functions on processes of brain aging. The central hypothesis is that secondary bile acids and bacterial sulphur metabolism products are drivers of accelerated brain aging, constituting common risk factors for neurodegenerative diseases.To this end, we will integrate large cohort magnetic resonance imaging (MRI) and multi-omics data from the prospective general population-based Study of Health in Pomerania (SHIP) with personalised constraint-based modelling of gut microbial communities. In SHIP, biomaterials including stool samples are available for omics characterisation in the study’s biobank. Additionally, SHIP participants underwent MRI characterisation at multiple time-points, giving rise to longitudinal brain MRI data. This unique setting allows for the comprehensive longitudinal investigation of the gut-brain axis, while facilitating the integration of complex omics data into MRI analyses approaches. Constraint-based modelling provides thorough and quantitative in silico characterisations of the microbiome’s metabolic functions that can be validated against existing metabolome data. Importantly, recent advances enable personalized microbiome community modelling approaches that can be applied to cohort data. Making use of the methodological advances in the field of constraint-based modelling and the unique set-up of the SHIP cohorts, the proposal aims at integrating constraint-based microbiome community modelling with large cohort MRI data to elucidate the metabolic contribution of the gut microbiome to brain aging. The focus lies on the following research aims:i) To generate personalised in silico metabolic profiles of gut microbiomes quantified by metagenomics in the SHIP cohorts via constraint-based community modelling,ii) To characterise the influence of known determinants of the gut microbiome composition on microbial metabolic functions,iii) To analyse the impact of microbial metabolic capacities (focusing on bile acid and sulphur metabolism) as characterised by constraint-based modelling on brain-aging in longitudinal and cross-sectional association analyses utilizing structural MRI data.

• DFG Programme: Research Grants
• International Connection: Ireland
• Cooperation Partner: Professorin Dr. Ines Thiele