Manifestations of Alzheimer’s Disease Genetic Risk in the Blood: A Cross-Sectional Multi-Omic Analysis in Healthy Adults Aged 18-90+

Abstract

Background: Genetics play an important role in late-onset Alzheimer’s Disease (AD) etiology and dozens of genetic variants have been implicated in AD risk through large-scale GWAS meta-analyses. However, the precise mechanistic effects of most of these variants have yet to be determined. Deeply phenotyped cohort data can reveal physiological changes associated with genetic risk for AD across an age spectrum that may provide clues to the biology of the disease.Methods: We utilized over 2000 high-quality quantitative measurements obtained from blood of 2831 cognitively normal adult clients of a consumer-based scientific wellness company, each with CLIA-certified whole-genome sequencing data. Measurements included: clinical laboratory blood tests, targeted chip-based proteomics, and metabolomics. We performed a phenome-wide association study utilizing this diverse blood marker data and 25 known AD genetic variants, adjusting for sex, age, vendor (for clinical labs), and the first four genetic principal components; sex-SNP interactions were also assessed.Results: We observed statistically significant SNP-analyte associations for five genetic variants after correction for multiple testing (for SNPs in or near NYAP1, ABCA7, INPP5D, and APOE), with effects detectable from early adulthood. The ABCA7 SNP and the APOE2 and APOE4 encoding alleles were associated with lipid variability, as seen in previous studies; in addition, six novel proteins were associated with the e2 allele. The most statistically significant finding was between the NYAP1 variant and PILRA and PILRB protein levels, supporting previous functional genomic studies in the identification of a putative causal variant within the PILRA gene. Sex modified the effects of four genetic variants, with multiple interrelated immune-modulating effects associated with the PICALM variant. In post-hoc analysis, sex-stratified GWAS results from an independent AD case-control meta-analysis supported sex-specific disease effects of the PICALM variant, highlighting the importance of sex as a biological variable.Conclusions: Known AD genetic variation influenced lipid metabolism and immune response systems in a population of non-AD individuals, with associations observed from early adulthood onward. Further research is needed to determine whether and how these effects are implicated in early-stage biological pathways to AD. These analyses aim to complement ongoing work on the functional interpretation of AD-associated genetic variants.

Sex differences in the genetic architecture of cognitive resilience to Alzheimer’s disease

“…A recent study of cognitively unimpaired individuals demonstrated a negative association in males as well as a sex-interaction association at a protective PICALM variant. 74 This finding is consistent with what we observed, as we saw a negative association with resilience at a PICALM risk variant in males but a positive association in females. It is also noteworthy that PICALM contributes to multiple mechanisms involved in the Alzheimer’s disease neuropathological cascade, including neuroimmune processes.…”

“…It is also noteworthy that PICALM contributes to multiple mechanisms involved in the Alzheimer’s disease neuropathological cascade, including neuroimmune processes. 74 Taken together, this evidence may suggest that subtle sex differences at Alzheimer’s disease genetic loci may contribute to sex differences in the downstream response to Alzheimer’s disease pathology.…”

Top Alzheimer's disease risk allele frequencies differ in HABS‐HD Mexican‐ versus Non‐Hispanic White Americans

“…Additionally, many questions remain about the implication of different genes, proteins, pathways, and related networks in disease manifestation. [2][3][4][20][21][22]24,[43][44][45][46] Further investigation into these pathways may also aid accurate diagnosis. Currently, there is no curative treatment for AD that has proven effective.…”

“…Despite the fact that AD has a variety of associated risk factors including genetics, lifestyle, and environmental, 12,39–42 it is unclear why diverse ethnic groups experience such large differential health outcomes compared to NHWs. Additionally, many questions remain about the implication of different genes, proteins, pathways, and related networks in disease manifestation 2–4,20–22,24,43–46 . Further investigation into these pathways may also aid accurate diagnosis.…”