Abstract

Background The gut microbiome has been linked to multiple complex human traits and diseases, including Alzheimer’s disease (AD). However, it is unclear from existing studies whether these relationships are causal.

Methods Two-sample bidirectional Mendelian randomisation (MR) was used to explore the causal relationship between the human gut microbiome with AD risk and two markers of cognitive function (fluid intelligence and reaction time). Sensitivity analyses explored validity of MR assumptions. We used data from the genome-wide association study (GWAS) meta-analysis of the gut microbiome (N=3890) in the Flemish Gut Flora Project (FGFP), Food-Chain Plus (FoCus) study and PopGen, two GWAS meta-analyses of late-onset, clinically diagnosed AD combined with proxy cases (N=455,258; clinically diagnosed cases only N=79,145), and GWASs of two cognitive function phenotypes in the UK Biobank: reaction time (N=459,523) and fluid intelligence (N=149,051).

Results Initial results indicated that the abundance of an unclassified group of bacteria within the Firmicutes phylum decreased fluid intelligence and that presence vs. absence of bacteria within the Dialister genus increased the risk of AD (both clinical and proxy cases combined and clinical cases only). Five microbial traits had effect estimates that were directionally consistent across AD and cognitive phenotypes including those in the Dialister, Parabacteroides and Ruminococcus genera, the Firmicutes phylum and the Porphyromonadaceae family. Sensitivity analyses indicated that our results were likely biased either by horizontal pleiotropy, genetic confounding or reverse causation and, thus, unlikely to reflect a causal relationship, further highlighting the importance of conducting such sensitivity analyses and caution in causal interpretation.

Conclusions Whilst our analyses initially provided evidence that features of the gut microbiome may influence the risk of AD and cognition, further sensitivity analyses indicated that these results were likely not reflective of causality.

Competing Interest Statement

The authors have declared no competing interest.

Funding Statement

GM is a PhD student funded by the University of Bristol. CH was funded by A Cancer Research UK (CRUK) Population Research Postdoctoral Fellowship [grant number RCCPDF\100007; awarded to KW in 2022]. EA is funded by a UKRI Future Leaders Fellowship [MR/W011581/1]. KW is supported by the University of Bristol.

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I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

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This study used only openly available human data. Summary GWAS data for both Alzheimer's Disease GWASs was obtained from Jansen et al. (2019) at https://pmc.ncbi.nlm.nih.gov/articles/PMC6836675/. Summary GWAS data for fluid intelligence and reaction time were obtained from IEU GWAS pipeline (https://data.bris.ac.uk/data/dataset/pnoat8cxo0u52p6ynfaekeigi).

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AbbreviationsADAlzheimer’s diseaseABBacteria abundanceP/ABacteria presence or absenceIV1Core MR assumption 1IV2Core MR assumption 2IV3Core MR assumption 3FGFPFlemish Gut Flora ProjectFoCusFood-Chain PlusGWASGenome-wide association studyIGAPInternational Genomics of Alzheimer’s ProjectIVWInverse variance weightedLDLinkage disequilibriumMRCMedical Research CouncilMRMendelian randomisationPGCPsychiatric Genomics ConsortiumSNPSingle nucleotide polymorphismSDStandard deviationSEStandard errorSTROBE-MRStrengthening the Reporting of Observational Studies in Epidemiology MR