Data Mining: Applying the AD&FTD Mutation Database to Progranulin

Evolution of genetic testing supports precision medicine for caring Alzheimer's disease patients

Genetic testing for Alzheimer's disease offers a molecular diagnosis to patients and their relatives and provides information on personal risk, reproductive choices, clinical trial eligibility, and treatment options. In the past, molecular testing was limited to detecting single variations in single genes. Currently, with the advent of next-generation sequencing, simultaneous analysis of more than 100 genes using the same DNA sample is possible. This approach allows the determination of gene mutations, genetic risk factors, genotypes at many pharmacogenomic loci, and the determination of a polygenic risk scores for stratification of risk. This article reviews the diagnostic genetic testing of Alzheimer's disease, from the first molecular approaches to recent advances in NGS, focusing on a precision medicine approach.

From beta amyloid to altered proteostasis in Alzheimer's disease

Alzheimer's disease (AD) is an age related neurodegenerative disorder causing severe disability and important socio-economic burden, but with no cure available to date. To disentangle this puzzling disease genetic studies represented an important way for the comprehension of pathogenic mechanisms. Abnormal processing and accumulation of amyloid-β peptide (Aβ) has been considered the main cause and trigger factor of the disease. The amyloid cascade theory has fallen into crisis because the failure of several anti-amyloid drugs trials and because of the simple equation AD = abnormal Aβ deposition is not always the case. We now know that multiple neurodegenerative diseases share common pathogenic mechanisms leading to accumulation of misfolded protein species. Genome Wide Association studies (GWAS) led to the identification of large numbers of DNA common variants (SNPs) distributed on different chromosomes and modulating the Alzheimer's risk. GWAS genes fall into several common pathways such as immune system and neuroinflammation, lipid metabolism, synaptic dysfunction and endocytosis, all of them addressing to novel routes for different pathogenic mechanisms. Other hints could be derived from epidemiological and experimental studies showing some lifestyles may have a major role in the pathogenesis of many age-associated diseases by modifying cell metabolism, proteostasis and microglia mediated neuroinflammation.

Genomic mechanisms in Alzheimer's disease

Alzheimer's disease (AD) is the most common neurodegenerative disease and, owing to its increasing prevalence, represents one of the leading public health problems in aging populations. The molecular causes underlying the onset and progression of AD are manifold and hitherto still incompletely understood. Research over nearly four decades has clearly delineated genetics to play a crucial role in AD susceptibility, likely in concert with non-genetic factors. The field has gained considerable momentum and novel insights over the past 10 years owing to the advent and application of high-throughput genomics technologies in datasets of increasing size. In this contribution to the Mini-Symposium on the Molecular Etiology of Alzheimer's Disease, we review the current status of genomics research in AD. To this end, we scrutinize and discuss the main findings from the two largest and most current genome-wide association studies (GWAS) in the field, that is, the papers published by Jansen et al (Nat Genet 51:404-413) and Kunkle et al (Nat Genet 51:414-430). Particular focus is laid on genomics findings overlapping across both studies and on the novel insights they provide in terms of improving our understanding of the "genomic mechanisms" underlying this devastating disease.

Gene biomarker discovery at different stages of Alzheimer using gene co-expression network approach

Alzheimer's disease (AD) is a chronic neurodegenerative disorder. It is the most common type of dementia that has remained as an incurable disease in the world, which destroys the brain cells irreversibly. In this study, a systems biology approach was adopted to discover novel micro-RNA and gene-based biomarkers of the diagnosis of Alzheimer's disease. The gene expression data from three AD stages (Normal, Mild Cognitive Impairment, and Alzheimer) were used to reconstruct co-expression networks. After preprocessing and normalization, Weighted Gene Co-Expression Network Analysis (WGCNA) was used on a total of 329 samples, including 145 samples of Alzheimer stage, 80 samples of Mild Cognitive Impairment (MCI) stage, and 104 samples of the Normal stage. Next, three gene-miRNA bipartite networks were reconstructed by comparing the changes in module groups. Then, the functional enrichment analyses of extracted genes of three bipartite networks and miRNAs were done, respectively. Finally, a detailed analysis of the authentic studies was performed to discuss the obtained biomarkers. The outcomes addressed proposed novel genes, including MBOAT1, ARMC7, RABL2B, HNRNPUL1, LAMTOR1, PLAGL2, CREBRF, LCOR, and MRI1and novel miRNAs comprising miR-615-3p, miR-4722-5p, miR-4768-3p, miR-1827, miR-940 and miR-30b-3p which were related to AD. These biomarkers were proposed to be related to AD for the first time and should be examined in future clinical studies.