Krumsiek, Jan

AbstractBackgroundOur Alzheimer Disease Metabolomics Consortium (ADMC), part of the Accelerating Medicines Partnership for AD (AMP‐AD) and in partnership with AD Neuroimaging Initiative (ADNI), applied state‐of‐the‐art metabolomics and lipidomics technologies combined with genomic and imaging data to map metabolic failures across the trajectory of the disease. Our studies confirmed that peripheral metabolic changes influenced by the exposome inform about cognitive changes, brain imaging changes, and ATN markers for disease confirming that peripheral and central changes are connected, in part through the metabolome.MethodsTo map the biochemical changes in AD, we used various targeted and untargeted metabolic platforms to profile ∼800 postmortem brain tissue, and ∼ 5000 blood samples.ResultsRecently, we built a comprehensive reference map of extensive AD‐related metabolic changes in brain, spanning multiple AD‐related traits, including neuropathological b‐amyloid and tau tangle burden, as well as late‐life cognitive performance. Using this resource, we extracted novel metabolic including bioenergetic pathways, cholesterol metabolism, neuroinflammation, broad impairment of osmoregulation, an imbalance between excitatory/inhibitory neurotransmitter ratios and identification of tau load as a potential driver of metabolic dysfunction in the AD brain, with minimal contributions from b‐amyloid load. As AD and progressive supranuclear palsy (PSP) share the pathological feature of tauopathy and metabolic alterations, we compared their metabolomic profiles to identify shared biological pathways that could be targeted for therapeutic interventions. Our findings indicate that both diseases display oxidative stress, mitochondrial dysfunction, and tau‐induced polyamine stress response.ConclusionOverall, through our studies, (1) We identified biochemical processes altered in AD, with findings supported across both metabolomic and proteomic data, indicating multimodal deregulation. (2) Our research pinpointed widespread AD‐related biochemical changes across various brain regions with differing levels of neuropathology. While there are many overlapping changes across the brain regions, each region also has its distinct metabolic alterations. (3) We identified biochemical processes disrupted by AD, with parallel findings in other neurodegenerative diseases, hinting at broader implications in neurodegenerative research. Currently, we are working on mapping widespread connections of the brain metabolome with various determinants of AD namely genome, gut microbiome, exposome, and linking with peripheral metabolic alterations in AD.

AbstractBackgroundBrain glucose hypometabolism is among the earliest pathogenic changes in Alzheimer’s disease (AD). This metabolic dysfunction points to the personal bioenergetic capacity, defined as the ability to maintain energy homeostasis under all circumstances including deregulated glucose uptake, as a potential source of resilience to the disease. Fasting blood acylcarnitine profiles are a central readout for this capacity in the absence of dietary glucose and capture the activity and efficiency of glucose‐independent routes of mitochondrial energy metabolism.MethodWe used fasting serum acylcarnitine profiles of 1,531 participants (465 with normal cognition, 762 with mild cognitive impairment, and 304 with clinical AD) from the AD Neuroimaging Initiative to perform unsupervised subgroup identification using hierarchical clustering. Identified subgroups were investigated for differences in A/T/N biomarker profiles and cognitive status. The contributions of genetic and potentially modifiable factors defining the subgroups were quantified using analysis of explained variance. The influence of the strongest determining factors on longitudinal cognitive trajectories was estimated using linear mixed‐effects models and gene‐by‐environment interaction analysis.ResultWe found several bioenergetically distinct subgroups with significant differences in AD biomarker profiles and cognitive function. The strongest genetic contribution to this bioenergetic endophenotype seems to be specifically linked to succinylcarnitine metabolism and significantly modulates the rate of future cognitive decline. In contrast, potentially modifiable sustainment of beta‐oxidation efficiency seems to decelerate bioenergetic aging, thus creating a bioenergetic reserve that delays progression of cognitive decline. Using gene‐by‐environment interaction analysis, we demonstrate that this molecular framework identifies a subgroup of individuals that is likely to benefit significantly from personalized therapeutic, dietary or lifestyle interventions tailored to increase resilience against bioenergetic disturbances in AD.ConclusionOur study reports on a set of genetic and metabolic markers that define bioenergetically distinct subgroups with significant differences on the AD biomarker and cognitive level. Longitudinal data suggest that targeting the modifiable fraction of this endophenotype might be a promising strategy to slow down disease progression in individuals with specific allelic configurations.

AbstractBackgroundMetabolic dysregulation is one of the hallmarks of Alzheimer’s disease (AD). Alterations in metabolism have been associated with AD‐related comorbidities, cognitive decline, and AD brain pathology. Brain regions are differentially affected with AD neuropathology and exhibit metabolic heterogeneity. Therefore, to build a more comprehensive picture of metabolic impact of AD, region‐specific AD‐associated metabolic changes need to be determined.MethodWe profiled 344 brain samples from the Mayo Clinic brain bank using Metabolon’s untargeted metabolomics platform, covering 182 samples from the cerebellum (CER) and 162 samples from the temporal cortex (TCX). Generalized linear models were used to assess the association of metabolic profiles with AD. Models included confounder correction for age at death, sex, and number of APOE‐ε4 alleles. To extend this study to four more brain regions, we included results from previously published brain metabolomics studies based on samples from three independent cohorts, including dorsolateral prefrontal cortex (DLPFC) from ROS/MAP, parietal lobe (PTL) from Washington University School of Medicine (WUSM), inferior temporal gyrus (ITG) and middle frontal gyrus (MFG) from Baltimore Longitudinal Study of Aging (BLSA).ResultIn the Mayo cohort, a total of 190 out of the 658 metabolites were significantly associated with AD. Out of the 190, 127 metabolites associated only in the CER region, 37 metabolites associated only in the TCX region, and 26 metabolites were associated in both brain regions. There were no metabolites commonly regulated in all the 6 brain regions under investigation. DLPFC and CER had the highest overlap of 70 metabolites, followed by DLPFC and PTL with 64 metabolites, and CER and PTL with 47 metabolites. For functional interpretation of our findings, each metabolite was further categorized with a sub‐pathway annotation provided by Metabolon. 3 of the 88 pathways including methionine cycle, phospholipid metabolism, and glutathione metabolism, were commonly regulated in the six brain regions under investigation.ConclusionWe present a first global perspective on AD‐associated metabolic alterations across six brain regions. This study will pave the way to fill the gap in our understanding of region‐specific metabolic deregulations associated with AD pathophysiology.