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Genetic variants beyond amyloid and tau associated cognitive decline: a cohort study

Citation

Jeong, Yong; Kim, Hang-Rai; Lee, Taeyeop; Choi, Jung Kyoon (2020), Genetic variants beyond amyloid and tau associated cognitive decline: a cohort study, Dryad, Dataset, https://doi.org/10.5061/dryad.9kd51c5d9

Abstract

Objective: To identify single nucleotide polymorphisms (SNPs) associated with cognitive decline independent of amyloid &[beta] (A&[beta]) and tau pathology in Alzheimer’s disease (AD). Methods: Discovery and replication datasets consisting of 414 subjects (94 cognitively normal control [CN), 185 with mild cognitive impairment [MCI], and 135 AD) and 72 subjects (22 CN, 39 MCI, and 11 AD), respectively, were obtained from the Alzheimer’s Disease Neuroimaging Initiative database. Genome-wide association analysis was conducted to identify SNPs associated with individual cognitive function (measured using the MMSE and ADAS-cog) while controlling for the level of A&[beta] and tau (measured as CSF p-tau/A&[beta]1-42). Gene ontology analysis was performed on SNP associated genes.

Results: We identified one significant (rs55906536, &[beta]=-1.91,standard error 0.34, P =4.07×10-8) and four suggestive variants on chromosome 6, which were associated with poorer cognitive function. Congruent results were found in the replication data. A structural equation model showed that the identified SNP deteriorated cognitive function partially through cortical thinning of the brain in a region-specific manner. Furthermore, a bioinformatics analysis showed that the identified SNPs were associated with genes related to glutathione metabolism.

Conclusions: In this study, we identified SNPs related to cognitive decline, in a manner which could not be explained by A&[beta] and tau levels. Our findings provide insight into the complexity of AD pathogenesis and support the growing literature on the role of glutathione in AD. This study suggests anti-oxidative agents may serve therapeutic for AD subjects with the identified SNPs.

Methods

The dataset which supports the conclusions from our genome-wide association analysis is available in the ADNI public database (http://adni.loni.usc.edu/data-samples/access-data/). Anonymized patient identification numbers, imaging, genetic, and biospecimen data are available from the ADNI database at the request of qualified researchers.

Funding

Ministry of Health and Welfare, Award: HI14C2768

Ministry of Science and Information & Communication Technology, Award: 2016M3C7A1913844

Ministry of Science and Information & Communication Technology, Award: 2016941946

Ministry of Science and Information & Communication Technology, Award: 2016M3C7A1913844