Genetic variation associated with human longevity and Alzheimer’s disease risk act through microglia and oligodendrocyte cross-talk

Ageing is the greatest global healthcare challenge, as it underlies age-related functional decline and is the primary risk factor for a range of common diseases, including neurodegenerative conditions such as Alzheimer’s disease (AD). However, the molecular mechanisms defining chronological age versus biological age, and how these underlie AD pathogenesis, are not well understood. The objective of this study was to integrate common human genetic variation associated with human lifespan or AD from Genome-Wide Association Studies (GWAS) with co-expression networks altered with age in the central nervous system, to gain insights into the biological processes which connect ageing with AD and lifespan. Initially, we identified common genetic variation in the human population associated with lifespan and AD by performing a gene-based association study using GWAS data. We also identified preserved co-expression networks associated with age in the brains of C57BL/6J mice from bulk and single-cell RNA-sequencing (RNA-seq) data, and in the brains of humans from bulk RNA-seq data. We then intersected the human gene-level common variation with these co-expression networks, representing the different cell types and processes of the brain. We found that genetic variation associated with AD was enriched in both microglial and oligodendrocytic bulk RNA-seq gene networks, which show increased expression with ageing in the human hippocampus, in contrast to synaptic networks which decreased with age. Further, longevity-associated genetic variation was modestly enriched in a single-cell gene network expressed by homeostatic microglia. Finally, we performed a transcriptome-wide association study (TWAS), to identify and confirm new risk genes associated with ageing that show variant-dependent changes in gene expression. In addition to validating known ageing-related genes such as APOE and FOXO3 , we found that Caspase 8 ( CASP8 ) and APOC1 show genetic variation associated with longevity. We observed that variants contributing to ageing and AD balance different aspects of microglial function suggesting that ageing-related processes affect multiple cell types in the brain. Specifically, changes in homeostatic microglia are associated with lifespan, and allele-dependent expression changes in age-related genes control microglial activation and myelination influencing the risk of developing AD. We identified putative molecular drivers of these genetic networks, as well as module genes whose expression in relevant human tissues are significantly associated with AD-risk or longevity, and may drive “inflammageing.” Our study also shows allele-dependent expression changes with ageing for genes classically involved in neurodegeneration, including MAPT and HTT , and demonstrates that PSEN1 is a prominent member/hub of an age-dependent expression network. In conclusion, this work provides new insights into cellular processes associated with ageing in the brain, and how these may contribute to the resilience of the brain against ageing or AD-risk. Our findings have important implications for developing markers indicating the physiological age and pre-pathological state of the brain, and provide new targets for therapeutic intervention. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This work was funded by the UK DRI, which receives its funding from the DRI Ltd, funded by the UK Medical Research Council, Alzheimer's Society and Alzheimer's Research UK (ARUK). DAS also received funding from the ARUK pump priming scheme via the UCL network. JH is supported by the Dolby Foundation, and by the National Institute for Health Research University College London Hospitals Biomedical Research Centre. The Genotype-Tissue Expression (GTEx) Project was supported by the Common Fund of the Office of the Director of the National Institutes of Health, and by NCI, NHGRI, NHLBI, NIDA, NIMH, and NINDS. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The data used for this study are publicly available for non-commercial research purposes, accession numbers are given in Methods. Transcripts per million (TPM) normalised bulk RNA-seq datasets generated from wild-type C57BL/6J mice (8-, 16-, 32-, and 72-weeks-of-age; data available from Mouseac.org), and non-diseased human hippocampi (from 196 individuals; v8 TPM counts downloaded from gtexportal.org/home/datasets). Normalised bulk RNA-seq datasets generated from the hippocampi of wild-type mice of different ages, used to assess module preservation, were downloaded from Synapse accession syn20808171, GSO: GSE110741, and GSO: GSE61918, respectively. The TWAS weights were downloaded from the FUSION website (GTEX7 Brain (13 tissues), GTEX7 Whole blood), YFS blood, NTR blood, and for all monocytes in the dataset produced by Fairfax et al. (2014) (samples: CD14, LPS2, LPS24 and IFN-gamma), downloaded from https://github.com/janetcharwood/MONOCYTE_TWAS (see Harwood et al. (2021) for details). I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes The R code for performing the data analysis described in this manuscript will be made freely available via GitHub, and all data produced in the present work are contained in the manuscript.