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CD33 , MEF2C , and SORL1 are associated with variability in macroscale functional brain architecture in AD
Author(s) -
Ramanan Vijay K,
Botha Hugo,
Radford Jonathan Graff,
Wiste Heather J.,
Senjem Matthew L.,
Gunter Jeffrey L.,
Boeve Bradley F.,
Knopman David S.,
Petersen Ronald C.,
Jack Clifford R.,
Lowe Val J.,
Jones David T.
Publication year - 2020
Publication title -
alzheimer's and dementia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.713
H-Index - 118
eISSN - 1552-5279
pISSN - 1552-5260
DOI - 10.1002/alz.046573
Subject(s) - genetic architecture , biology , linkage disequilibrium , multivariate statistics , alzheimer's disease , genetic variation , neuroimaging , genetic association , genetics , evolutionary biology , psychology , neuroscience , allele , disease , medicine , phenotype , genotype , single nucleotide polymorphism , haplotype , gene , statistics , mathematics
Background Alzheimer’s disease (AD) is marked by selective disruptions to anatomically‐distinct brain regions and their connectivity which collectively support cognition. Based on a variation of pattern‐recognition analysis of FDG‐PET images, we previously developed a framework, the global functional state space (GFSS), which captures this macroscale architecture by assigning each individual a series of weightings on 10 independent patterns (eigenbrains=EBs). In this study, we applied the GFSS as a quantitative endophenotype to test whether known AD genetic risk factors were associated with variability in large‐scale neurodynamics represented by the GFSS. Method The study sample included 410 participants from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) with evidence of cognitive impairment (CDR‐global>0) and amyloidosis (positive amyloid‐PET). The GFSS was estimated for each individual using the set of 10 EBs to describe global patterns of variation in glucose metabolism. AD genetic risk variants identified in prior large consortium case‐control studies were included for analysis if the variant (or a proxy by linkage disequilibrium r 2 >0.7) was assayed on both genotyping platforms used in the sample and if the minor allele frequency exceeded 1%. Genetic associations with the collective set of EBs were tested using multivariate linear regression under a dominant genetic model. Result Significant multivariate associations were identified for CD33 ( p =7.04x10 ‐4 ), MEF2C ( p =0.001), and SORL1 ( p =0.02). These findings remained significant after covarying for age and sex. The strongest component loadings for CD33 ( p =9.09x10 ‐4 ; std. β=‐0.16) and MEF2C ( p =1.59x10 ‐4 ; std. β=‐0.18) were for EB1, with the minor allele in each case associated with a negative axis deviation in the direction of the GFSS area representing episodic memory dysfunction. SORL1 displayed its strongest loading onto EB4 ( p =0.03, std. β=‐0.11). The association of APOE ɛ4 with the GFSS was marginally nonsignificant ( p =0.09). Conclusion We identified associations of risk variants in CD33 , MEF2C , and SORL1 with differences in patterns of FDG hypometabolism in persons with symptomatic AD. These findings establish the GFSS as a useful endophenotype for genetic analyses, particularly as an avenue toward a mechanistic understanding of how heritable factors may influence inter‐individual variability and syndromic diversity in AD. Further investigation in larger and independent cohorts is warranted.