Diet-Related Metabolites Associated with Cognitive Decline Revealed by Untargeted Metabolomics in a Prospective Cohort

SCOPE

Untargeted metabolomics may reveal preventive targets in cognitive aging, including within the food metabolome.

METHODS AND RESULTS

A case-control study nested in the prospective Three-City study includes participants aged ≥65 years and initially free of dementia. A total of 209 cases of cognitive decline and 209 controls (matched for age, gender, education) with slower cognitive decline over up to 12 years are contrasted. Using untargeted metabolomics and bootstrap-enhanced penalized regression, a baseline serum signature of 22 metabolites associated with subsequent cognitive decline is identified. The signature includes three coffee metabolites, a biomarker of citrus intake, a cocoa metabolite, two metabolites putatively derived from fish and wine, three medium-chain acylcarnitines, glycodeoxycholic acid, lysoPC(18:3), trimethyllysine, glucose, cortisol, creatinine, and arginine. Adding the 22 metabolites to a reference predictive model for cognitive decline (conditioned on age, gender, education and including ApoE-ε4, diabetes, BMI, and number of medications) substantially increases the predictive performance: cross-validated Area Under the Receiver Operating Curve = 75% [95% CI 70-80%] compared to 62% [95% CI 56-67%].

CONCLUSIONS

The untargeted metabolomics study supports a protective role of specific foods (e.g., coffee, cocoa, fish) and various alterations in the endogenous metabolism responsive to diet in cognitive aging.

Association of LIfestyle for BRAin health risk score (LIBRA) and genetic susceptibility with incident dementia and cognitive decline

INTRODUCTION

Evaluating whether genetic susceptibility modifies the impact of lifestyle-related factors on dementia is critical for prevention.

METHODS

We studied 5170 participants from a French cohort of older persons free of dementia at baseline and followed for up to 17 years. The LIfestyle for BRAin health risk score (LIBRA) including 12 modifiable factors was constructed at baseline (higher score indicating greater risk) and was related to both subsequent cognitive decline and dementia incidence, according to genetic susceptibility to dementia (reflected by the apolipoprotein E [APOE] ε4 allele and a genetic risk score [GRS]).

RESULTS

The LIBRA was associated with higher dementia incidence, with no significant effect modification by genetics (hazard ratio for one point score = 1.09 [95% confidence interval, 1.05; 1.13]) in APOE ε4 non-carriers and = 1.15 [1.08; 1.22] in carriers; P = 0.15 for interaction). Similar findings were obtained with the GRS and with cognitive decline.

DISCUSSION

Lifestyle-based prevention may be effective whatever the genetic susceptibility to dementia.

Prediction of dementia risk from multimodal repeated measures: The added value of brain MRI biomarkers

Abstract

The utility of brain magnetic resonance imaging (MRI) for predicting dementia is debated. We evaluated the added value of repeated brain MRI, including atrophy and cerebral small vessel disease markers, for dementia prediction. We conducted a landmark competing risk analysis in 1716 participants of the French population-based Three-City Study to predict the 5-year risk of dementia using repeated measures of 41 predictors till year 4 of follow-up. Brain MRI markers improved significantly the individual prediction of dementia after accounting for demographics, health measures, and repeated measures of cognition and functional dependency (area under the ROC curve [95% CI] improved from 0.80 [0.79 to 0.82] to 0.83 [0.81 to 0.84]). Nonetheless, accounting for the change over time through repeated MRIs had little impact on predictive abilities. These results highlight the importance of multimodal analysis to evaluate the added predictive abilities of repeated brain MRI for dementia and offer new insights into the predictive performances of various MRI markers.

Highlights

We evaluated whether repeated brain volumes and cSVD markers improve dementia prediction.The 5-year prediction of dementia is slightly improved when considering brain MRI markers.Measures of hippocampus volume are the main MRI predictors of dementia.Adjusted on cognition, repeated MRI has poor added value over single MRI for dementia prediction.We utilized a longitudinal analysis that considers error-and-missing-prone predictors, and competing death.

Associations among hypertension, dementia biomarkers, and cognition: The MEMENTO cohort

INTRODUCTION

Approximately 40% of dementia cases could be delayed or prevented acting on modifiable risk factors including hypertension. However, the mechanisms underlying the hypertension-dementia association are still poorly understood.

METHODS

We conducted a cross-sectional analysis in 2048 patients from the MEMENTO cohort, a French multicenter clinic-based study of outpatients with either isolated cognitive complaints or mild cognitive impairment. Exposure to hypertension was defined as a combination of high blood pressure (BP) status and antihypertensive treatment intake. Pathway associations were examined through structural equation modeling integrating extensive collection of neuroimaging biomarkers and clinical data.

RESULTS

Participants treated with high BP had significantly lower cognition compared to the others. This association was mediated by higher neurodegeneration and higher white matter hyperintensities load but not by Alzheimer's disease (AD) biomarkers.

DISCUSSION

These results highlight the importance of controlling hypertension for prevention of cognitive decline and offer new insights on mechanisms underlying the hypertension-dementia association.

HIGHLIGHTS

Paths of hypertension-cognition association were assessed by structural equation models. The hypertension-cognition association is not mediated by Alzheimer's disease biomarkers. The hypertension-cognition association is mediated by neurodegeneration and leukoaraiosis. Lower cognition was limited to participants treated with uncontrolled blood pressure. Blood pressure control could contribute to promote healthier brain aging.

Polygenic score integrating neurodegenerative and vascular risk informs dementia risk stratification

INTRODUCTION

An integrative polygenic risk score (iPRS) capturing the neurodegenerative and vascular contribution to dementia could identify high-risk individuals and improve risk prediction.

METHODS

We developed an iPRS for dementia (iPRS-DEM) in Europeans (aged 65+), comprising genetic risk for Alzheimer's disease (AD) and 23 vascular or neurodegenerative traits (excluding apolipoprotein E [APOE]). iPRS-DEM was evaluated across cohorts comprising older community-dwelling people (N = 3702), a multi-ancestry biobank (N = 130,797 Europeans; 105,404 non-Europeans), and dementia-free memory clinic participants (N = 2032).

RESULTS

iPRS-DEM was associated with dementia risk independently of APOE in the elderly (subdistribution hazard ratio [sHR]per1SD = 1.15, 95% confidence interval [CI]: 1.03 to 1.28), which generalized to Europeans (EUR-sHRper1SD = 1.28, 95% CI: 1.09 to 1.51]), East-Asians (EAS-sHRper1SD = 5.29, 95% CI: 1.43 to 34.36), and memory-clinic participants (sHRper1SD = 1.25, 95% CI: 1.11 to 1.42). Prediction was comparable to clinical risk factors in older community-dwelling people, with improved performance among memory-clinic patients. Risk stratification was enhanced by defining four genetic risk groups with iPRS-DEM and APOE ε4, reaching five-fold increased risk in APOE ε4+/iPRS-DEM+ memory-clinic participants.

DISCUSSION

Alongside APOE ε4, iPRS-DEM may refine risk stratification for the enrichment of dementia clinical trials and prevention programs.

HIGHLIGHTS

iPRS-DEM reflects neurodegenerative and vascular contribution to dementia. We show iPRS-DEM captures additional dementia genetic risk beyond APOE and AD-PRS. iPRS-DEM, in combination with APOE ε4, shows promise for dementia risk stratification. Our results generalize across both population-based and memory-clinic settings. We show transportability of iPRS-DEM to East Asian ancestry.

White matter hyperintensity spatial patterns: Risk factors and clinical correlates

INTRODUCTION

White matter hyperintensities (WMHs), a major cerebral small vessel disease (cSVD) marker, may arise from different pathologies depending on their location. We explored clinical and genetic correlates of agnostically derived spatial WMH patterns in two longitudinal population-based cohorts (Three-City Study [3C]-Dijon, LIFE-Adult).

METHODS

We derived seven WMH spatial patterns using Bullseye segmentation in 2878 individuals aged 65+ and explored their associations with vascular and genetic risk factors, cognitive performance, dementia and stroke incidence.

RESULTS

WMHs in the frontoparietal and anterior periventricular region were associated with blood pressure traits, WMH genetic risk score (GRS), baseline and decline in general cognitive performance, incident all-cause dementia, and ischemic stroke. Juxtacortical-deep occipital WMHs were not associated with vascular risk factors and WMH GRS, but with incident all-cause dementia and intracerebral hemorrhage.

DISCUSSION

Accounting for WMH spatial distribution is key to deciphering mechanisms underlying cSVD subtypes, an essential step towards personalized therapeutic approaches.

HIGHLIGHTS

We studied spatial patterns of WMHs in 2878 participants. Blood pressure was associated with frontoparietal and anterior PV WMHs. Anterior PV WMHs predicted dementia and stroke risk. Juxtacortical-deep occipital WMH burden was not associated with blood pressure or WMH genetic risk. Juxtacortical-deep occipital WMH burden predicted dementia and intracerebral hemorrhage.