4.6 Review

Dissecting Complex and Multifactorial Nature of Alzheimer's Disease Pathogenesis: a Clinical, Genomic, and Systems Biology Perspective

期刊

MOLECULAR NEUROBIOLOGY
卷 53, 期 7, 页码 4833-4864

出版社

SPRINGER
DOI: 10.1007/s12035-015-9390-0

关键词

Alzheimer's disease; Etiology; Endophenotype; Genome-wide linkage; Genome-wide association; Genome-wide expression studies; Epigenetics

资金

  1. Council of Scientific and Industrial Research (CSIR) [BSC0123]
  2. CSIR, Government of India
  3. UGC, Government of India

向作者/读者索取更多资源

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by loss of memory and other cognitive functions. AD can be classified into familial AD (FAD) and sporadic AD (SAD) based on heritability and into early onset AD (EOAD) and late onset AD (LOAD) based on age of onset. LOAD cases are more prevalent with genetically complex architecture. In spite of significant research focused on understanding the etiological mechanisms, search for diagnostic biomarker(s) and disease-modifying therapy is still on. In this article, we aim to comprehensively review AD literature on established etiological mechanisms including role of beta-amyloid and apolipoprotein E (APOE) along with promising newer etiological factors such as epigenetic modifications that have been associated with AD suggesting its multifactorial nature. As genomic studies have recently played a significant role in elucidating AD pathophysiology, a systematic review of findings from genome-wide linkage (GWL), genome-wide association (GWA), genome-wide expression (GWE), and epigenome-wide association studies (EWAS) was conducted. The availability of multi-dimensional genomic data has further coincided with the advent of computational and network biology approaches in recent years. Our review highlights the importance of integrative approaches involving genomics and systems biology perspective in elucidating AD pathophysiology. The promising newer approaches may provide reliable means of early and more specific diagnosis and help identify therapeutic interventions for LOAD.

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