Browsing by Author "Krumsiek, Jan"

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    Individual bioenergetic capacity as a potential source of resilience to Alzheimer's disease
    (medRxiv, 2024-01-24) Arnold, Matthias; Buyukozkan, Mustafa; Doraiswamy, P. Murali; Nho, Kwangsik; Wu, Tong; Gudnason, Vilmundur; Launer, Lenore J.; Wang-Sattler, Rui; Adamski, Jerzy; The Alzheimer’s Disease Neuroimaging Initiative; Alzheimer’s Disease Metabolomics Consortium; De Jager, Philip L.; Ertekin-Taner, Nilüfer; Bennett, David A.; Saykin, Andrew J.; Peters, Annette; Suhre, Karsten; Kaddurah-Daouk, Rima; Kastenmüller, Gabi; Krumsiek, Jan; Radiology and Imaging Sciences, School of Medicine
    Impaired glucose uptake in the brain is one of the earliest presymptomatic manifestations of Alzheimer's disease (AD). The absence of symptoms for extended periods of time suggests that compensatory metabolic mechanisms can provide resilience. Here, we introduce the concept of a systemic 'bioenergetic capacity' as the innate ability to maintain energy homeostasis under pathological conditions, potentially serving as such a compensatory mechanism. We argue that fasting blood acylcarnitine profiles provide an approximate peripheral measure for this capacity that mirrors bioenergetic dysregulation in the brain. Using unsupervised subgroup identification, we show that fasting serum acylcarnitine profiles of participants from the AD Neuroimaging Initiative yields bioenergetically distinct subgroups with significant differences in AD biomarker profiles and cognitive function. To assess the potential clinical relevance of this finding, we examined factors that may offer diagnostic and therapeutic opportunities. First, we identified a genotype affecting the bioenergetic capacity which was linked to succinylcarnitine metabolism and significantly modulated the rate of future cognitive decline. Second, a potentially modifiable influence of beta-oxidation efficiency seemed to decelerate bioenergetic aging and disease progression. Our findings, which are supported by data from more than 9,000 individuals, suggest that interventions tailored to enhance energetic health and to slow bioenergetic aging could mitigate the risk of symptomatic AD, especially in individuals with specific mitochondrial genotypes.
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    Integrative metabolomics-genomics approach reveals key metabolic pathways and regulators of Alzheimer's disease
    (Wiley, 2022) Horgusluoglu, Emrin; Neff, Ryan; Song, Won-Min; Wang, Minghui; Wang, Qian; Arnold, Matthias; Krumsiek, Jan; Galindo-Prieto, Beatriz; Ming, Chen; Nho, Kwangsik; Kastenmüller, Gabi; Han, Xianlin; Baillie, Rebecca; Zeng, Qi; Andrews, Shea; Cheng, Haoxiang; Hao, Ke; Goate, Alison; Bennett, David A.; Saykin, Andrew J.; Kaddurah-Daouk, Rima; Zhang, Bin; Alzheimer's Disease Neuroimaging Initiative (ADNI); Alzheimer Disease Metabolomics Consortium; Radiology and Imaging Sciences, School of Medicine
    Metabolites, the biochemical products of the cellular process, can be used to measure alterations in biochemical pathways related to the pathogenesis of Alzheimer's disease (AD). However, the relationships between systemic abnormalities in metabolism and the pathogenesis of AD are poorly understood. In this study, we aim to identify AD‐specific metabolomic changes and their potential upstream genetic and transcriptional regulators through an integrative systems biology framework for analyzing genetic, transcriptomic, metabolomic, and proteomic data in AD. Metabolite co‐expression network analysis of the blood metabolomic data in the Alzheimer's Disease Neuroimaging Initiative (ADNI) shows short‐chain acylcarnitines/amino acids and medium/long‐chain acylcarnitines are most associated with AD clinical outcomes, including episodic memory scores and disease severity. Integration of the gene expression data in both the blood from the ADNI and the brain from the Accelerating Medicines Partnership Alzheimer's Disease (AMP‐AD) program reveals ABCA1 and CPT1A are involved in the regulation of acylcarnitines and amino acids in AD. Gene co‐expression network analysis of the AMP‐AD brain RNA‐seq data suggests the CPT1A‐ and ABCA1‐centered subnetworks are associated with neuronal system and immune response, respectively. Increased ABCA1 gene expression and adiponectin protein, a regulator of ABCA1, correspond to decreased short‐chain acylcarnitines and amines in AD in the ADNI. In summary, our integrated analysis of large‐scale multiomics data in AD systematically identifies novel metabolites and their potential regulators in AD and the findings pave a way for not only developing sensitive and specific diagnostic biomarkers for AD but also identifying novel molecular mechanisms of AD pathogenesis.
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    Interplay of Metabolome and Gut Microbiome in Individuals With Major Depressive Disorder vs Control Individuals
    (American Medical Association, 2023) Amin, Najaf; Liu, Jun; Bonnechere, Bruno; MahmoudianDehkordi, Siamak; Arnold, Matthias; Batra, Richa; Chiou, Yu-Jie; Fernandes, Marco; Ikram, M. Arfan; Kraaij, Robert; Krumsiek, Jan; Newby, Danielle; Nho, Kwangsik; Radjabzadeh, Djawad; Saykin, Andrew J.; Shi, Liu; Sproviero, William; Winchester, Laura; Yang, Yang; Nevado-Holgado, Alejo J.; Kastenmüller, Gabi; Kaddurah-Daouk, Rima; van Duijn, Cornelia M.; Radiology and Imaging Sciences, School of Medicine
    Importance: Metabolomics reflect the net effect of genetic and environmental influences and thus provide a comprehensive approach to evaluating the pathogenesis of complex diseases, such as depression. Objective: To identify the metabolic signatures of major depressive disorder (MDD), elucidate the direction of associations using mendelian randomization, and evaluate the interplay of the human gut microbiome and metabolome in the development of MDD. Design, setting and participants: This cohort study used data from participants in the UK Biobank cohort (n = 500 000; aged 37 to 73 years; recruited from 2006 to 2010) whose blood was profiled for metabolomics. Replication was sought in the PREDICT and BBMRI-NL studies. Publicly available summary statistics from a 2019 genome-wide association study of depression were used for the mendelian randomization (individuals with MDD = 59 851; control individuals = 113 154). Summary statistics for the metabolites were obtained from OpenGWAS in MRbase (n = 118 000). To evaluate the interplay of the metabolome and the gut microbiome in the pathogenesis of depression, metabolic signatures of the gut microbiome were obtained from a 2019 study performed in Dutch cohorts. Data were analyzed from March to December 2021. Main outcomes and measures: Outcomes were lifetime and recurrent MDD, with 249 metabolites profiled with nuclear magnetic resonance spectroscopy with the Nightingale platform. Results: The study included 6811 individuals with lifetime MDD compared with 51 446 control individuals and 4370 individuals with recurrent MDD compared with 62 508 control individuals. Individuals with lifetime MDD were younger (median [IQR] age, 56 [49-62] years vs 58 [51-64] years) and more often female (4447 [65%] vs 2364 [35%]) than control individuals. Metabolic signatures of MDD consisted of 124 metabolites spanning the energy and lipid metabolism pathways. Novel findings included 49 metabolites, including those involved in the tricarboxylic acid cycle (ie, citrate and pyruvate). Citrate was significantly decreased (β [SE], -0.07 [0.02]; FDR = 4 × 10-04) and pyruvate was significantly increased (β [SE], 0.04 [0.02]; FDR = 0.02) in individuals with MDD. Changes observed in these metabolites, particularly lipoproteins, were consistent with the differential composition of gut microbiota belonging to the order Clostridiales and the phyla Proteobacteria/Pseudomonadota and Bacteroidetes/Bacteroidota. Mendelian randomization suggested that fatty acids and intermediate and very large density lipoproteins changed in association with the disease process but high-density lipoproteins and the metabolites in the tricarboxylic acid cycle did not. Conclusions and relevance: The study findings showed that energy metabolism was disturbed in individuals with MDD and that the interplay of the gut microbiome and blood metabolome may play a role in lipid metabolism in individuals with MDD.
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    Sex and APOE ε4 genotype modify the Alzheimer’s disease serum metabolome
    (Springer Nature, 2020) Arnold, Matthias; Nho, Kwangsik; Kueider-Paisley, Alexandra; Massaro, Tyler; Huynh, Kevin; Brauner, Barbara; MahmoudianDehkordi, Siamak; Louie, Gregory; Moseley, M. Arthur; Thompson, J. Will; St. John-Williams, Lisa; Tenenbaum, Jessica D.; Blach, Colette; Chang, Rui; Brinton, Roberta D.; Baillie, Rebecca; Han, Xianlin; Trojanowski, John Q.; Shaw, Leslie M.; Martins, Ralph; Weiner, Michael W.; Trushina, Trushina; Toledo, Jon B.; Meikle, Peter J.; Bennett, David A.; Krumsiek, Jan; Doraiswamy, P. Murali; Saykin, Andrew J.; Kaddurah-Daouk, Rima; Kastenmüller, Gabi; Radiology and Imaging Sciences, School of Medicine
    Late-onset Alzheimer’s disease (AD) can, in part, be considered a metabolic disease. Besides age, female sex and APOE ε4 genotype represent strong risk factors for AD that also give rise to large metabolic differences. We systematically investigated group-specific metabolic alterations by conducting stratified association analyses of 139 serum metabolites in 1,517 individuals from the AD Neuroimaging Initiative with AD biomarkers. We observed substantial sex differences in effects of 15 metabolites with partially overlapping differences for APOE ε4 status groups. Several group-specific metabolic alterations were not observed in unstratified analyses using sex and APOE ε4 as covariates. Combined stratification revealed further subgroup-specific metabolic effects limited to APOE ε4+ females. The observed metabolic alterations suggest that females experience greater impairment of mitochondrial energy production than males. Dissecting metabolic heterogeneity in AD pathogenesis can therefore enable grading the biomedical relevance for specific pathways within specific subgroups, guiding the way to personalized medicine.