Metabolic correlates of late midlife cognitive outcomes: findings from the 1946 British Birth Cohort

Abstract

Investigating associations between metabolites and late midlife cognitive function could reveal potential markers and mechanisms relevant to early dementia. Here, we systematically explored the metabolic underpinnings of cognitive outcomes measured across the 7th decade of life, while untangling influencing life course factors. Using levels of 1019 metabolites profiled by liquid chromatography-mass spectrometry (age 60-64), we evaluated relationships between metabolites and cognitive outcomes in the British 1946 Birth Cohort (N = 1740). We additionally conducted pathway and network analyses to allow for greater insight into underlying mechanisms, and sequentially adjusted for life course factors across four models, including: sex and blood collection (model 1), model 1 + body mass index and lipid medication (model 2), model 2 + social factors and childhood cognition (model 3), and model 3 + lifestyle influences (model 4). After adjusting for multiple tests, 155 metabolites, 10 pathways and 5 network modules demonstrated relationships with cognitive outcomes. Of the 155, 35 metabolites were highly connected in their network module (termed “hub” metabolites), presenting as functionally important marker candidates. Notably, we report relationships between a module comprised of acylcarnitines and processing speed which remained robust to life course adjustment, revealing palmitoylcarnitine (C16) as a hub (model 4: ß= -0.10, 95%CI=-0.15 to -0.052, p = 5.99 × 10−5). Most associations were sensitive to adjustment for social factors and childhood cognition; in the final model, four metabolites remained after multiple testing correction, and 80 at p < 0.05. Two modules demonstrated associations that were partly or largely attenuated by life course factors: one enriched in modified nucleosides and amino acids (overall attenuation = 39.2 to 55.5%), and another in vitamin A and C metabolites (overall attenuation = 68.6 to 92.6%). Our other findings, including a module enriched in sphingolipid pathways, were entirely explained by life course factors, particularly childhood cognition and education. Using a large birth cohort study with information across the life course, we highlighted potential metabolic mechanisms underlying cognitive function in late midlife, suggesting marker candidates and life course relationships for further study.

Investigating associations between blood metabolites, later life brain imaging measures, and genetic risk for Alzheimer’s disease

“…In line with our previous analysis in the full NSHD (10,19), covariables were: sex, blood collection information (clinic location, age, fasting status), age at scan, APOE genotype (ε4 carrier/non carrier; blood samples at age 53 or 69y), BMI (60-64y nurse visit), lipid medication (yes/no; self-reported use in 24 hours preceding blood collection at 60-64y), childhood cognition (15y), highest level of educational attainment (no qualifications/'O level'/'A level' or higher; 26y), childhood socioeconomic position (SEP) (Father's current or last known occupation categorised according to the UK Registrar General; 11y), and midlife SEP (own occupation categorised as for childhood SEP; 53y).…”

“…Fourteen modules of highly connected metabolites were then identified, and the first principal component of each module (termed “module eigenvalue”) was derived to allow for relationships between modules and outcomes to be examined. Overrepresentation analyses were conducted, using the hypergeometric test, to identify enriched pathways within the module and provide insight into potential biological function (10). Modules were allocated an arbitrary colour name using the WGCNA package for ease of discussion.…”

“…To explore associations of clusters (termed "modules") of co-expressed metabolites, we applied weighted gene coexpression network analysis (WGCNA) (21)(22)(23) to metabolite data, as detailed previously (10). First, metabolite data were adjusted for sex and blood clinic information and the standardised residuals were used for WGCNA.…”

“…Metabolite data underwent strict quality control (QC), as detailed in (10), resulting in 1019 metabolites (Supplementary Notes).…”

“…Additionally, little is known about the involvement of groups of interrelated metabolites; utilising systems-level approaches could offer an improved understanding of these complex relationships and facilitate the identification of candidate markers. We previously employed a systems-level approach to explore the metabolic correlates of late midlife cognition in the Medical Research Council National Survey of Health and Development (NSHD; the British 1946 birth cohort) (10). We identified groups of highly coexpressed metabolites that associated with cognitive outcomes and key metabolites within these to explore further, including acylcarnitines, modified nucleotides and amino acids, vitamins, and sphingolipids; although many associations with late midlife cognition were explained by social factors and childhood cognition (10).…”