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Meta-analysis of data from genome-wide association studies (GWAS) of Alzheimer's disease (AD) has confirmed the high risk of APOE and identified twenty other risk genes/loci with moderate effect size. However, many more risk genes/loci remain to be discovered to account for the missing heritability. The contributions from individual singe-nucleotide polymorphisms (SNPs) have been thoroughly examined in traditional GWAS data analysis, while SNP-SNP interactions can be explored by a variety of alternative approaches. Here we applied generalized multifactor dimensionality reduction to the re-analysis of four publicly available GWAS datasets for AD. When considering 4-order intragenic SNP interactions, we observed high consistency of discovered potential risk genes among the four independent GWAS datasets. Ten potential risk genes were observed across all four datasets, including PDE1A, RYR3, TEK, SLC25A21, LOC729852, KIRREL3, PTPN5, FSHR, PARK2, and NR3C2. These potential risk genes discovered by generalized multifactor dimensionality reduction are highly relevant to AD pathogenesis based on multiple layers of evidence. The genetic contributions of these genes warrant further confirmation in other independent GWAS datasets for AD.

The brain transcriptome of Alzheimer's disease (AD) reflects the prevailing disease mechanism at the gene expression level. However, thousands of genes have been reported to be dysregulated in AD brains in existing studies, and the consistency or discrepancy among these studies has not been thoroughly examined. Toward this end, we conducted a comprehensive survey of the brain transcriptome datasets for AD and other neurological diseases. We first demonstrated that the frequency of observed dysregulation in AD was highly correlated with the reproducibility of the dysregulation. Based on this observation, we selected 100 genes with the highest frequency of dysregulation to illustrate the core perturbation in AD brains. The dysregulation of these genes was validated in several independent datasets for AD. We further identified 12 genes with strong correlation of gene expression with disease progression. The relevance of these genes to disease progression was also validated in an independent dataset. Interestingly, we found a transcriptional "cushion" for these 100 genes in the less vulnerable visual cortex region, which may be a critical component of the protection mechanism for less vulnerable brain regions. To facilitate the research in this field, we have provided the expression information of ~8000 relevant genes on a publicly accessible web server AlzBIG (http://alz.big.ac.cn).

Genetic studies have identified several genomic loci including chr19p13.2 relevant to Alzheimer's disease (AD) susceptibility. However, the functional roles of these genomic loci in AD pathogenesis require further clarification. Transcriptome as an endophenotype is critical for the understanding of disease mechanism. Here we demonstrate that chr19p is the most significantly perturbed chromosome region in AD brain transcriptome. With dual evidence from genome and transcriptome, chr19p likely play a special role in AD pathogenesis.

Blood transcriptome has emerged as a potential resource for the discovery of biomarkers for Alzheimer's disease (AD). However, the validity of blood transcriptome in the early diagnosis of AD has yet to be extensively tested. In this work, we analyzed published data on AD blood transcriptome and revealed the characteristic perturbation of cellular functional units, including upregulation of environmental responses (immune response, survival/death signaling, and cellular recycling) and down-regulation of core metabolism (energy metabolism and translation/splicing). This characteristic perturbation was unique to AD based on the comparison with blood transcriptome from other neurological disorders and complex diseases. More importantly, similar perturbation was observed in both AD and mild cognitive impairment (MCI) groups. This perturbation pattern was further validated in our independent microarray experiment in a small Chinese cohort. In addition, the potential effect of aging and lifestyle on blood transcriptome was discussed. Based on the analyses, we propose that the transformation of the blood transcriptome in AD is an integrated part of the disease mechanism and has potential to serve as a reliable biomarker for assisting the early diagnosis as well as monitoring purpose. Therefore, more independent studies on blood transcriptome of AD and MCI with larger sample size are warranted.