Browsing by Author "Alzheimer’s Disease Metabolomics Consortium"

Now showing 1 - 7 of 7
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    Bile acids targeted metabolomics and medication classification data in the ADNI1 and ADNIGO/2 cohorts
    (Nature Research, 2019-10-17) St. John-Williams, Lisa; Mahmoudiandehkordi, Siamak; Arnold, Matthias; Massaro, Tyler; Blach, Colette; Kastenmüller, Gabi; Louie, Gregory; Kueider-Paisley, Alexandra; Han, Xianlin; Baillie, Rebecca; Motsinger-Reif, Alison A.; Rotroff, Daniel; Nho, Kwangsik; Saykin, Andrew J.; Risacher, Shannon L.; Koal, Therese; Moseley, M. Arthur; Tenenbaum, Jessica D.; Thompson, J. Will; Kaddurah-Daouk, Rima; Alzheimer’s Disease Neuroimaging Initiative; Alzheimer’s Disease Metabolomics Consortium; Radiology and Imaging Sciences, School of Medicine
    Alzheimer’s disease (AD) is the most common cause of dementia. The mechanism of disease development and progression is not well understood, but increasing evidence suggests multifactorial etiology, with a number of genetic, environmental, and aging-related factors. There is a growing body of evidence that metabolic defects may contribute to this complex disease. To interrogate the relationship between system level metabolites and disease susceptibility and progression, the AD Metabolomics Consortium (ADMC) in partnership with AD Neuroimaging Initiative (ADNI) is creating a comprehensive biochemical database for patients in the ADNI1 cohort. We used the Biocrates Bile Acids platform to evaluate the association of metabolic levels with disease risk and progression. We detail the quantitative metabolomics data generated on the baseline samples from ADNI1 and ADNIGO/2 (370 cognitively normal, 887 mild cognitive impairment, and 305 AD). Similar to our previous reports on ADNI1, we present the tools for data quality control and initial analysis. This data descriptor represents the third in a series of comprehensive metabolomics datasets from the ADMC on the ADNI.
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    Circulating lipid profiles are associated with cross-sectional and longitudinal changes of central biomarkers for Alzheimer's disease
    (medRxiv, 2023-06-21) Kim, Jun Pyo; Nho, Kwangsik; Wang, Tingting; Huynh, Kevin; Arnold, Matthias; Risacher, Shannon L.; Bice, Paula J.; Han, Xianlin; Kristal, Bruce S.; Blach, Colette; Baillie, Rebecca; Kastenmüller, Gabi; Meikle, Peter J.; Saykin, Andrew J.; Kaddurah-Daouk, Rima; Alzheimer’s Disease Neuroimaging Initiative; Alzheimer’s Disease Metabolomics Consortium; Radiology and Imaging Sciences, School of Medicine
    Investigating the association of lipidome profiles with central Alzheimer's disease (AD) biomarkers, including amyloid/tau/neurodegeneration (A/T/N), can provide a holistic view between the lipidome and AD. We performed cross-sectional and longitudinal association analysis of serum lipidome profiles with AD biomarkers in the Alzheimer's Disease Neuroimaging Initiative cohort (N=1,395). We identified lipid species, classes, and network modules that were significantly associated with cross-sectional and longitudinal changes of A/T/N biomarkers for AD. Notably, we identified the lysoalkylphosphatidylcholine (LPC(O)) as associated with "A/N" biomarkers at baseline at lipid species, class, and module levels. Also, GM3 ganglioside showed significant association with baseline levels and longitudinal changes of the "N" biomarkers at species and class levels. Our study of circulating lipids and central AD biomarkers enabled identification of lipids that play potential roles in the cascade of AD pathogenesis. Our results suggest dysregulation of lipid metabolic pathways as precursors to AD development and progression.
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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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    Individual bioenergetic capacity as a potential source of resilience to Alzheimer's disease
    (Springer Nature, 2025-02-24) 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 an early presymptomatic manifestation of Alzheimer's disease (AD), with symptom-free periods of varying duration that likely reflect individual differences in metabolic resilience. We propose a systemic "bioenergetic capacity", the individual ability to maintain energy homeostasis under pathological conditions. Using fasting serum acylcarnitine profiles from the AD Neuroimaging Initiative as a blood-based readout for this capacity, we identified subgroups with distinct clinical and biomarker presentations of AD. Our data suggests that improving beta-oxidation efficiency can decelerate bioenergetic aging and disease progression. The estimated treatment effects of targeting the bioenergetic capacity were comparable to those of recently approved anti-amyloid therapies, particularly in individuals with specific mitochondrial genotypes linked to succinylcarnitine metabolism. Taken together, our findings provide evidence that therapeutically enhancing bioenergetic health may reduce the risk of symptomatic AD. Furthermore, monitoring the bioenergetic capacity via blood acylcarnitine measurements can be achieved using existing clinical assays.
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    Peripheral inflammation is associated with brain atrophy and cognitive decline linked to mild cognitive impairment and Alzheimer's disease
    (Springer Nature, 2024-07-29) Liang, Nuanyi; Nho, Kwangsik; Newman, John W.; Arnold, Matthias; Huynh, Kevin; Meikle, Peter J.; Borkowski, Kamil; Kaddurah‑Daouk, Rima; Alzheimer’s Disease Metabolomics Consortium; Radiology and Imaging Sciences, School of Medicine
    Inflammation is an important factor in Alzheimer’s disease (AD). An NMR measurement in plasma, glycoprotein acetyls (GlycA), captures the overall level of protein production and glycosylation implicated in systemic inflammation. With its additional advantage of reducing biological variability, GlycA might be useful in monitoring the relationship between peripheral inflammation and brain changes relevant to AD. However, the associations between GlycA and these brain changes have not been fully evaluated. Here, we performed Spearman’s correlation analyses to evaluate these associations cross-sectionally and determined whether GlycA can inform AD-relevant longitudinal measurements among participants in the Alzheimer’s Disease Neuroimaging Initiative (n = 1506), with additional linear models and stratification analyses to evaluate the influences of sex or diagnosis status and confirm findings from Spearman’s correlation analyses. We found that GlycA was elevated in AD patients compared to cognitively normal participants. GlycA correlated negatively with multiple concurrent regional brain volumes in females diagnosed with late mild cognitive impairment (LMCI) or AD. Baseline GlycA level was associated with executive function decline at 3–9 year follow-up in participants diagnosed with LMCI at baseline, with similar but not identical trends observed in the future decline of memory and entorhinal cortex volume. Results here indicated that GlycA is an inflammatory biomarker relevant to AD pathogenesis and that the stage of LMCI might be relevant to inflammation-related intervention.
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    Peripheral metabolism informs on future cognitive decline and development of Alzheimer’s disease in population at risk
    (Wiley, 2025-01-03) Liang, Nuanyi; Nho, Kwangsik; Newman, John W.; Arnold, Matthias; Huynh, Kevin; Meikle, Peter J.; Borkowski, Kamil; Kaddurah-Daouk, Rima; Alzheimer’s GutMicrobiome Project Consortium (AGMP); Alzheimer’s Disease Metabolomics Consortium; Radiology and Imaging Sciences, School of Medicine
    Background: Peripheral metabolic health status can reflect and/or contribute to the risk of Alzheimer’s disease (AD). Peripheral metabolic health status can be indicated by metabolic health markers, such as inflammatory biomarker glycoprotein acetyls (GlycA) and specific components of lipoproteins (e.g., triacylglycerol of high‐density lipoprotein). However, it is unclear if the relationship between peripheral metabolism and AD‐related markers is heterogenous among diverse populations and throughout the disease progression. Methods: Utilizing Alzheimer’s Disease Neuroimaging Initiative data, we determined whether baseline plasma GlycA can inform on cognitive and brain structural changes among sub‐populations with different diagnosis status. Furthermore, correlation analyses were performed between blood metabolomics and cerebrospinal fluid (CSF) proteomics data in sub‐populations with different diagnosis status or different mild cognitive impairment (MCI)/AD outcomes in 3 years. Results: GlycA was elevated in AD patients compared to cognitively normal participants. Baseline GlycA level was associated with executive function decline at 3‐9 year follow‐up in participants diagnosed with late mild cognitive impairment (LMCI) at baseline, with similar but not identical trends observed in the future decline of memory and entorhinal cortex volume. In addition, peripheral metabolomics signatures of CSF proteomics were well‐distinguished between cognitive normal participants and AD patients. Moreover, different peripheral‐central metabolic connection was also observed in MCI‐AD converters vs. MCI‐MCI non‐converters across 3 years follow up. Conclusion: Peripheral inflammation was linked to future cognitive decline and brain structural atrophy for population at risk. In addition, peripheral metabolomics‐CSF proteomics correlation reveals distinguishing peripheral‐central connection patterns in AD patients as well as MCI participant soon to develop AD in 3 years. Findings here point to peripheral systemic inflammation and metabolic health in general as risk factors in AD development, pointing to therapeutic intervention related to periphery metabolic health for patients at risk.
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    Predictive metabolic networks reveal sex- and APOE genotype-specific metabolic signatures and drivers for precision medicine in Alzheimer's disease
    (Wiley, 2023) Chang, Rui; Trushina, Eugenia; Zhu, Kuixi; Zaidi, Syed Shujaat Ali; Lau, Branden M.; Kueider-Paisley, Alexandra; Moein, Sara; He, Qianying; Alamprese, Melissa L.; Vagnerova, Barbora; Tang, Andrew; Vijayan, Ramachandran; Liu, Yanyun; Saykin, Andrew J.; Brinton, Roberta D.; Kaddurah-Daouk, Rima; Alzheimer’s Disease Neuroimaging Initiative; Alzheimer’s Disease Metabolomics Consortium; Radiology and Imaging Sciences, School of Medicine
    Introduction: Late-onset Alzheimer's disease (LOAD) is a complex neurodegenerative disease characterized by multiple progressive stages, glucose metabolic dysregulation, Alzheimer's disease (AD) pathology, and inexorable cognitive decline. Discovery of metabolic profiles unique to sex, apolipoprotein E (APOE) genotype, and stage of disease progression could provide critical insights for personalized LOAD medicine. Methods: Sex- and APOE-specific metabolic networks were constructed based on changes in 127 metabolites of 656 serum samples from the Alzheimer's Disease Neuroimaging Initiative cohort. Results: Application of an advanced analytical platform identified metabolic drivers and signatures clustered with sex and/or APOE ɛ4, establishing patient-specific biomarkers predictive of disease state that significantly associated with cognitive function. Presence of the APOE ɛ4 shifts metabolic signatures to a phosphatidylcholine-focused profile overriding sex-specific differences in serum metabolites of AD patients. Discussion: These findings provide an initial but critical step in developing a diagnostic platform for personalized medicine by integrating metabolomic profiling and cognitive assessments to identify targeted precision therapeutics for AD patient subgroups through computational network modeling.