Dataset Information

Integrative Multimodal Metabolomics to Early Predict Cognitive Decline Among Amyloid Positive Community-Dwelling Older Adults.

ABSTRACT: Alzheimer's disease is strongly linked to metabolic abnormalities. We aimed to distinguish amyloid-positive people who progressed to cognitive decline from those who remained cognitively intact. We performed untargeted metabolomics of blood samples from amyloid-positive individuals, before any sign of cognitive decline, to distinguish individuals who progressed to cognitive decline from those who remained cognitively intact. A plasma-derived metabolite signature was developed from Supercritical Fluid chromatography coupled with high-resolution mass spectrometry (SFC-HRMS) and nuclear magnetic resonance (NMR) metabolomics. The 2 metabolomics data sets were analyzed by Data Integration Analysis for Biomarker discovery using Latent approaches for Omics studies (DIABLO), to identify a minimum set of metabolites that could describe cognitive decline status. NMR or SFC-HRMS data alone cannot predict cognitive decline. However, among the 320 metabolites identified, a statistical method that integrated the 2 data sets enabled the identification of a minimal signature of 9 metabolites (3-hydroxybutyrate, citrate, succinate, acetone, methionine, glucose, serine, sphingomyelin d18:1/C26:0 and triglyceride C48:3) with a statistically significant ability to predict cognitive decline more than 3 years before decline. This metabolic fingerprint obtained during this exploratory study may help to predict amyloid-positive individuals who will develop cognitive decline. Due to the high prevalence of brain amyloid-positivity in older adults, identifying adults who will have cognitive decline will enable the development of personalized and early interventions.

SUBMITTER: Tremblay-Franco M

PROVIDER: S-EPMC11000317 | biostudies-literature | 2024 May

REPOSITORIES: biostudies-literature

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Integrative Multimodal Metabolomics to Early Predict Cognitive Decline Among Amyloid Positive Community-Dwelling Older Adults.

Tremblay-Franco Marie M Canlet Cécile C Carriere Audrey A Nakhle Jean J Galinier Anne A Portais Jean-Charles JC Yart Armelle A Dray Cédric C Lu Wan-Hsuan WH Bertrand Michel Justine J Guyonnet Sophie S Rolland Yves Y Vellas Bruno B Delrieu Julien J Barreto Philippe de Souto PS Pénicaud Luc L Casteilla Louis L Ader Isabelle I

The journals of gerontology. Series A, Biological sciences and medical sciences 20240501 5

Alzheimer's disease is strongly linked to metabolic abnormalities. We aimed to distinguish amyloid-positive people who progressed to cognitive decline from those who remained cognitively intact. We performed untargeted metabolomics of blood samples from amyloid-positive individuals, before any sign of cognitive decline, to distinguish individuals who progressed to cognitive decline from those who remained cognitively intact. A plasma-derived metabolite signature was developed from Supercritical ...[more]

PMID: 38452244

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Project description:ImportancePlasma measurement of amyloid-β (Aβ) peptides has been associated with cognitive function, but evidence of its ability to identify cognitive decline is still scarce.ObjectiveTo investigate the associations between plasma Aβ42/40 and cognitive decline over time among community-dwelling older adults with subjective memory concerns.Design, setting, and participantsThis multicenter cohort study used data from volunteers in the 5-year study Multidomain Alzheimer Preventive Trial (MAPT). Participants were aged 70 years or older and observed for a median (interquartile range) of 3.9 (2.0-4.0) years. Recruitment of participants started in May 2008 and ended in February 2011. Follow-up ended in April 2016. Data analysis was conducted from April to October 2020.ExposurePlasma Aβ42 and Aβ40 were measured at 12 months for 448 participants (92.8%) and at 24 months for the rest. The moment of Aβ assessment was defined as the baseline for this study.Main outcomes and measuresCognitive function was assessed at 12, 24, 36, 48, and 60 months by a composite cognitive score based on 4 tests; Mini Mental State Examination (MMSE); Clinical Dementia Rating, sum of boxes; and Alzheimer Disease Cooperative Study-Activities of Daily Living. Mixed-effect linear regressions were performed.ResultsA total of 483 participants (median [IQR] age, 76.0 [73.0-80.0]; 286 [59.2%] women) were analyzed. Of them, 161 (33.3%) were classified as low plasma Aβ42/40 (≤0.107). After adjusting for age, sex, education, body mass index, Geriatric Depression Scale score, apolipoprotein E ε4 genotype, and MAPT intervention groups, low plasma Aβ42/40 was associated with more pronounced decline in composite cognitive score (adjusted between-group mean difference: -0.20, 95% CI, -0.34 to -0.07; P = .004) and decline in MMSE score (adjusted between-group mean difference: -0.59; 95% CI, -1.07 to -0.11; P = .02) during the follow-up period compared with the group with an Aβ42/40 ratio greater than 0.107.Conclusions and relevanceIn this study, low plasma Aβ42/40 was associated with more pronounced decline in cognitive function (measured by multiple outcomes) over time. Findings suggest that plasma Aβ42/40 may be used to identify people at risk of cognitive decline, being an alternative to more complex and expensive measures, such as positron emission tomography imaging or cerebrospinal fluid measurement.

Project description:Subjective cognitive decline (SCD) as an indicator of preclinical Alzheimer's disease (AD) may precede mild cognitive impairment (MCI) over several decades. Self-reported cognitive decline as a typical clinical manifestation is critical in preclinical AD. Metacognition represents a person's ability to accurately assess cognition. Our study aimed to examine (1) the alternations of metamemory in a cohort across the Alzheimer's continuum, (2) the association between metamemory and cognition, and (3) the relationship of cortical thickness in four regions of interest (ROI) with metamemory scores. Six hundred ninety-seven participants were classified as 79 AD dementia, 161 aMCI, 261 SCD, and 196 cognitively unimpaired (CU) individuals, in which 418 participants aged above 65, 131 participants with Aβ+ after receiving positron emission tomography, and 602 participants received sMRI. The degree of confidence (DOC) was measured by calculating discrepancies between judgments and memory performance. We assessed the relationships between DOC tertiles and cognition and analyzed the screening power, then investigated the partial correlation between DOC and ROIs, controlled by age, sex, and cognition. In the Aβ+ subgroup, SCD showed significantly higher DOC scores than the CU group. There was an increasing trend of overconfidence with the decline of cognition across the AD spectrum (P for trend < 0.001). After adjusting for age, sex, and education, the lower degree of confidence-long-term delay recall (DOC-LD) tertiles were associated with lower odds ratio in SCD, aMCI, and AD in the Aβ+ subgroup (all P for trend < 0.05). The area under the curves of DOC scores for screening SCD from CU in the Aβ+ subgroup was better than that in all participants and the age ≥65 subgroup. Partial correlation showed that in the Aβ+ subgroup, DOC-SD (degree of confidence-short-term delay recall) was negatively correlated with the anterior cingulate cortex; DOC-LD was negatively correlated with the cortices of parahippocampal, anterior cingulate, posterior cingulate, and medial orbitofrontal. In individuals with Aβ+, SCD exhibited a detectable metamemory alternation before objective cognitive impairment could be tested, indicated by the overestimation in the memory performance. The pattern of an increasing trend of overconfidence across SCD, aMCI, and AD dementia supports the view of a continuum in Alzheimer's disease.

Project description:BackgroundCortical atrophy is associated with cognitive decline, but the association is not perfect. We aimed to identify factors explaining the discrepancy between the degree of cortical atrophy and cognitive decline in cognitively unimpaired elderly.MethodsThe discrepancy between atrophy and cognitive decline was measured using the residuals from a linear regression analysis between change in whole brain cortical thickness over time and change in a cognitive composite measure over time in 395 cognitively unimpaired participants from the Swedish BioFINDER study. We tested for bivariate associations of this residual measure with demographic, imaging, and fluid biomarker variables using Pearson correlations and independent-samples t-tests, and for multivariate associations using linear regression models. Mediation analyses were performed to explore possible paths between the included variables.ResultsIn bivariate analyses, older age (r = -0.11, p = 0.029), male sex (t = -3.00, p = 0.003), larger intracranial volume (r = -0.17, p < 0.001), carrying an APOEe4 allele (t = -2.71, p = 0.007), larger white matter lesion volume (r = -0.16, p = 0.002), lower cerebrospinal fluid (CSF) β-amyloid (Aβ) 42/40 ratio (t = -4.05, p < 0.001), and higher CSF levels of phosphorylated tau (p-tau) 181 (r = -0.22, p < 0.001), glial fibrillary acidic protein (GFAP; r = -0.15, p = 0.003), and neurofilament light (NfL; r = -0.34, p < 0.001) were negatively associated with the residual measure, i.e., associated with worse than expected cognitive trajectory given the level of atrophy. In a multivariate analysis, only lower CSF Aβ42/40 ratio and higher CSF NfL levels explained cognition beyond brain atrophy. Mediation analyses showed that associations between the residual measure and APOEe4 allele, CSF Aβ42/40 ratio, and CSF GFAP and p-tau181 levels were mediated by levels of CSF NfL, as were the associations with the residual measure for age, sex, and WML volume.ConclusionsOur results suggest that axonal degeneration and amyloid pathology independently affect the rate of cognitive decline beyond the degree of cortical atrophy. Furthermore, axonal degeneration mediated the negative effects of old age, male sex, and white matter lesions, and in part also amyloid and tau pathology, on cognition over time when accounting for cortical atrophy.

Dataset Information

Integrative Multimodal Metabolomics to Early Predict Cognitive Decline Among Amyloid Positive Community-Dwelling Older Adults.

Publications

Integrative Multimodal Metabolomics to Early Predict Cognitive Decline Among Amyloid Positive Community-Dwelling Older Adults.

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