Alz Res Therapy: Genome-wide penetrance relationship analysis may predict the genetic risk of dementia

Alzheimer's disease (AD) is a chronic neurodegenerative disease characterized by extracellular deposition of β-amyloid and intracellular accumulation of phosphorylated tau protein
.
AD is the most common cause of dementia in the elderly.

Early-onset AD is usually caused by mutations in APP, PSEN1 or PSEN2, while late-onset AD (LOAD) is the most common form of AD, showing more complex genetic mechanisms
.

The apolipoprotein ε4 allele (APOE4) is the only common high-risk genetic variant associated with LOAD.
Previous large-scale genome-wide association studies ( GWAS s) have found dozens of low-impact loci, which indicates that LOAD A large part of the genetic component of the disease remains unexplained

Rare variants, structural variants and genetic interactions are possible reasons for the genetic loss of complex diseases
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Previous studies have identified rare coding variants of SORL1 and ABCA7, which can affect APP processing

The single nucleotide polymorphisms (SNPs) found in genome-wide association studies can only explain part of the inheritance of Alzheimer's disease (AD)
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Penetrance is considered to be one of the main reasons for the "lost heredity" of AD

In this way, Hui Wang and others of Huazhong Agricultural University used three popular methods to carry out genome-wide penetrance screening for the clinical diagnosis of AD (N = 10,389)
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The subsequent analysis is to eliminate false associations caused by possible confounding factors

Then, the co-expression of candidate gene interactions in the brains of AD patients was examined, and their association with the intermediate phenotype of AD was analyzed
.

In addition, a new method has been developed to compile the apparent risk factors into an apparent risk score (ERS) based on multi-factor dimensionality reduction
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Two independent data sets were used to evaluate the feasibility of ERS in AD risk prediction

They found interactions between two candidate genes with PFDR<0.
05 (RAMP3-SEMA3A and NSMCE1-DGKE/C17orf67) and five other genes with PFDR<0.

The co-expression of the discovered interactions supports the biological interactions that may exist behind the observed statistical significance
.

In addition, they found that ERSs can identify high-risk individuals with early-onset AD
.

The combined risk score of SNPs and SNP-SNP interaction showed a slight but stable AUC in predicting the clinical status of AD
.

The important significance of this research lies in the discovery: Through the epigenetic analysis of the whole genome, new genetic interactions that may be involved in AD can be determined; ERS can be used as an indicator of AD genetic risk
.