Profiling the metabolome of patients with dementia in the UK Biobank

Abstract

AbstractBackgroundThere is increasing interest in early metabolic changes in dementia, which may reflect the effects of genetic determinants of dementia, medical history and co‐morbidity, environmental risk factors, and aging. We studied the relation of blood‐based metabolites to the risk of dementia.MethodThe analyses are conducted in 121,389 participants of the UK Biobank (UKB) and include over 1172 incident dementia patients who developed dementia during the follow‐up. The metabolome was characterized using Nuclear Magnetic Resonance of the Nightingale Health platform. The platform covers 249 metabolic measures, including small molecules, fatty acids and detailed lipoprotein lipids. We integrated metabolic data measured before dementia onset with genetic data to determine whether the metabolites associations reflect causal pathways or rather consequences of the disease process. After log transformation of metabolites, scaling, and quality control, data were analysed using Cox‐regression. We adjusted for age, sex, BMI, technical variables ethnicity, smoking, alcohol, education, metabolic and neuropsychiatric medication and APOE genotypes.ResultWe identified 36 novel metabolites that are significantly associated with incident dementia (FDR<0.05), with positive associations of ketone bodies to the future risk of dementia and negative associations of fatty acids, various amino acids, and cholesterol subfractions. The metabolic pattern is remarkably similar for incident patients with Alzheimer disease and vascular dementia and overlaps substantially with the metabolic profile identified for incident Parkinson’s disease. We found evidence that a number of metabolites may mediate the association between the APOE e2 and APOE e4 variants and dementia.ConclusionOur findings suggest that changes in the metabolism that occur before the onset of disease are associated to the future risk of dementia.