Your browser doesn't support javascript.
loading
Integrating brain imaging endophenotypes with GWAS for Alzheimer's disease.
Knutson, Katherine A; Pan, Wei.
Afiliação
  • Knutson KA; Division of Biostatistics, University of Minnesota, Minneapolis, MN 55455, USA.
  • Pan W; Division of Biostatistics, University of Minnesota, Minneapolis, MN 55455, USA.
Quant Biol ; 9(2): 185-200, 2021 Jun.
Article em En | MEDLINE | ID: mdl-35399757
ABSTRACT

Background:

Genome wide association studies (GWAS) have identified many genetic variants associated with increased risk of Alzheimer's disease (AD). These susceptibility loci may effect AD indirectly through a combination of physiological brain changes. Many of these neuropathologic features are detectable via magnetic resonance imaging (MRI).

Methods:

In this study, we examine the effects of such brain imaging derived phenotypes (IDPs) with genetic etiology on AD, using and comparing the following

methods:

two-sample Mendelian randomization (2SMR), generalized summary statistics based Mendelian randomization (GSMR), transcriptome wide association studies (TWAS) and the adaptive sum of powered score (aSPU) test. These methods do not require individual-level genotypic and phenotypic data but instead can rely only on an external reference panel and GWAS summary statistics.

Results:

Using publicly available GWAS datasets from the International Genomics of Alzheimer's Project (IGAP) and UK Biobank's (UKBB) brain imaging initiatives, we identify 35 IDPs possibly associated with AD, many of which have well established or biologically plausible links to the characteristic cognitive impairments of this neurodegenerative disease.

Conclusions:

Our results highlight the increased power for detecting genetic associations achieved by multiple correlated SNP-based methods, i.e., aSPU, GSMR and TWAS, over MR methods based on independent SNPs (as instrumental variables).
Palavras-chave

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Clinical_trials / Prognostic_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Clinical_trials / Prognostic_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article