Family-based association analyses of imputed genotypes reveal genome-wide significant association of Alzheimer’s disease with OSBPL6, PTPRG, and PDCL3

Abstract

The genetic basis of Alzheimer's disease (AD) is complex and heterogeneous. Over 200 highly penetrant pathogenic variants in the genes APP, PSEN1 and PSEN2 cause a subset of early-onset familial Alzheimer's disease (EOFAD). On the other hand, susceptibility to late-onset forms of AD (LOAD) is indisputably associated to the ε4 allele in the gene APOE, and more recently to variants in more than two-dozen additional genes identified in the large-scale genome-wide association studies (GWAS) and meta-analyses reports. Taken together however, although the heritability in AD is estimated to be as high as 80%, a large proportion of the underlying genetic factors still remain to be elucidated. In this study we performed a systematic family-based genome-wide association and meta-analysis on close to 15 million imputed variants from three large collections of AD families (~3,500 subjects from 1,070 families). Using a multivariate phenotype combining affection status and onset age, meta-analysis of the association results revealed three single nucleotide polymorphisms (SNPs) that achieved genome-wide significance for association with AD risk: rs7609954 in the gene PTPRG (P-value = 3.98·10−08), rs1347297 in the gene OSBPL6 (P-value = 4.53·10−08), and rs1513625 near PDCL3 (P-value = 4.28·10−08). In addition, rs72953347 in OSBPL6 (P-value = 6.36·10−07) and two SNPs in the gene CDKAL1 showed marginally significant association with LOAD (rs10456232, P-value: 4.76·10−07; rs62400067, P-value: 3.54·10−07). In summary, family-based GWAS meta-analysis of imputed SNPs revealed novel genomic variants in (or near) PTPRG, OSBPL6, and PDCL3 that influence risk for AD with genome-wide significance.

Genome‐wide association analysis of autism identified multiple loci that have been reported as strong signals for neuropsychiatric disorders

“…This locus is significant in Alzheimer disease and age of onset [Herold et al, ]; Psychosis [Ikeda et al, ]; Neuroticism [Luciano et al, ]; Response to anti‐depressant treatment in major depressive [Clark et al, ]; Schizophrenia [Sullivan et al, ];Loneliness [Gao et al, ] in GWAS study.…”

“…Locus and supporting evidence Gene function a KCNMB2 chr3:178276488-178562217 This locus is significant in schizophrenia and bipolar disorder [Bergen et al, 2012]; Amyotrophic lateral sclerosis [Xie et al, 2014]; Hippocampal sclerosis [Beecham et al, 2014]; Suicide attempts [Kimbrel et al, 2018];Recurrent major depressive disorder [Hall et al, 2018] [Herold et al, 2016]; Psychosis [Ikeda et al, 2013]; Neuroticism ; Response to anti-depressant treatment in major depressive ; Schizophrenia [Sullivan et al, 2008];Loneliness [Gao et al, 2017] Lee et al, 2018] in GWAS study. Two de novo and rare variants in SNX29 have been reported in autism [Iossifov et al, 2014;RK et al, 2017] [Davenport et al, 2015], Preschool internalizing problems [Benke et al, 2014], Educational attainment (MTAG) [Lee et al, 2018], Chronotype [Jones et al, 2019] in GWAS study PCSK2, Proprotein Convertase Subtilisin/Kexin type 2 Involved in the processing of hormone and other protein precursors at sites comprised of pairs of basic amino acid residues.…”

A variant in PPP4R3A protects against alzheimer‐related metabolic decline

“…In a follow-up search for previous associations between PPP4R3A and AD risk, we found that a distinct variant in PPP4R3A passed the suggestive threshold for association with risk of AD in a familybased GWAS, lending additional support for the involvement of this gene in AD. 43 Further investigations will be needed to identify the protective mechanisms by which PPP4R3A affects disease vulnerability.…”

Overlap in synaptic neurological condition susceptibility pathways and the neural pannexin 1 interactome revealed by bioinformatics analyses

“…Intersecting (Chang et al, 2017;Hamza et al, 2010;Hu et al, 2016;Liu et al, 2011;Simon-Sanchez et al, 2009) [2] (Chung et al, 2018;Cummings et al, 2012;Furney et al, 2011;Herold et al, 2016;Jun et al, 2016;Jun et al, 2017;Kunkle et al, 2019;Lee et al, 2017;Logue et al, 2011;Marioni et al, 2018;Mez et al, 2017;Nazarian et al, 2019;Zhu et al, 2019) [3] (Moss et al, 2017) [4] (Xie et al, 2014) [5] (Aberg et al, 2013;Amare et al, 2018;Athanasiu et al, 2015 (Fig. 12A).…”