Title
|
|
|
|
Multivariate GWAS of Alzheimer's disease CSF biomarker profiles implies GRIN2D in synaptic functioning
| |
Author
|
|
|
|
| |
Institution/Organisation
|
|
|
|
EMIF-AD ADNI Study Group
| |
Abstract
|
|
|
|
Background Genome-wide association studies (GWAS) of Alzheimer's disease (AD) have identified several risk loci, but many remain unknown. Cerebrospinal fluid (CSF) biomarkers may aid in gene discovery and we previously demonstrated that six CSF biomarkers (beta-amyloid, total/phosphorylated tau, NfL, YKL-40, and neurogranin) cluster into five principal components (PC), each representing statistically independent biological processes. Here, we aimed to (1) identify common genetic variants associated with these CSF profiles, (2) assess the role of associated variants in AD pathophysiology, and (3) explore potential sex differences.Methods We performed GWAS for each of the five biomarker PCs in two multi-center studies (EMIF-AD and ADNI). In total, 973 participants (n = 205 controls, n = 546 mild cognitive impairment, n = 222 AD) were analyzed for 7,433,949 common SNPs and 19,511 protein-coding genes. Structural equation models tested whether biomarker PCs mediate genetic risk effects on AD, and stratified and interaction models probed for sex-specific effects.Results Five loci showed genome-wide significant association with CSF profiles, two were novel (rs145791381 [inflammation] and GRIN2D [synaptic functioning]) and three were previously described (APOE, TMEM106B, and CHI3L1). Follow-up analyses of the two novel signals in independent datasets only supported the GRIN2D locus, which contains several functionally interesting candidate genes. Mediation tests indicated that variants in APOE are associated with AD status via processes related to amyloid and tau pathology, while markers in TMEM106B and CHI3L1 are associated with AD only via neuronal injury/inflammation. Additionally, seven loci showed sex-specific associations with AD biomarkers.Conclusions These results suggest that pathway and sex-specific analyses can improve our understanding of AD genetics and may contribute to precision medicine. |
| |
Language
|
|
|
|
English
| |
Source (journal)
|
|
|
|
Genome medicine
| |
Publication
|
|
|
|
2023
| |
ISSN
|
|
|
|
1756-994X
| |
DOI
|
|
|
|
10.1186/S13073-023-01233-Z
| |
Volume/pages
|
|
|
|
15
:1
(2023)
, p. 1-23
| |
Article Reference
|
|
|
|
79
| |
ISI
|
|
|
|
001100029100001
| |
Pubmed ID
|
|
|
|
37794492
| |
Medium
|
|
|
|
E-only publicatie
| |
Full text (Publisher's DOI)
|
|
|
|
| |
Full text (open access)
|
|
|
|
| |
|