Found 1 record
Genetic interaction partners
|Confidence||Stringent (ε>0.16 or ε<-0.12)||Intermediate (-0.16≤ε≤-0.08 or 0.08≤ε≤0.16)||Lenient (|ε|<0.08)|
Altered onset time(1)
Variant 1:Gene:Genomic location:chr14:102315916dbSNP ID:Target disease:Alzheimer's Disease(DOID_10652)Effect type:ExpressivityModifier effect:Altered onset timeEvidence:P=0.009017Effect:Genetic variation in these new candidate genes affects the risk of late-onset Alzheimer’s disease.Reference:Title:Beta-amyloid toxicity modifier genes and the risk of Alzheimer's disease.Species studied:HumanAbstract:Late-onset Alzheimer's disease (LOAD) is a complex and multifactorial disease. So far ten loci have been identified for LOAD, including APOE, PICALM, CLU, BIN1, CD2AP, CR1, CD33, EPHA1, ABCA7, and MS4A4A/MS4A6E, but they explain about 50% of the genetic risk and thus additional risk genes need to be identified. Amyloid beta (Aβ) plaques develop in the brains of LOAD patients and are considered to be a pathological hallmark of this disease. Recently 12 new Aβ toxicity modifier genes (ADSSL1, PICALM, SH3KBP1, XRN1, SNX8, PPP2R5C, FBXL2, MAP2K4, SYNJ1, RABGEF1, POMT2, and XPO1) have been identified that potentially play a role in LOAD risk. In this study, we have examined the association of 222 SNPs in these 12 candidate genes with LOAD risk in 1291 LOAD cases and 958 cognitively normal controls. Single site and haplotype analyses were performed using PLINK. Following adjustment for APOE genotype, age, sex, and principal components, we found single nucleotide polymorphisms (SNPs) in PPP2R5C, PICALM, SH3KBP1, XRN1, and SNX8 that showed significant association with risk of LOAD. The top SNP was located in intron 3 of PPP2R5C (P=0.009017), followed by an intron 19 SNP in PICALM (P=0.0102). Haplotype analysis revealed significant associations in ADSSL1, PICALM, PPP2R5C, SNX8, and SH3KBP1 genes. Our data indicate that genetic variation in these new candidate genes affects the risk of LOAD. Further investigation of these genes, including additional replication in other case-control samples and functional studies to elucidate the pathways by which they affect Aβ, are necessary to determine the degree of involvement these genes have for LOAD risk.