Untangling huge literature to disinter genetic underpinnings of Alzheimer's Disease: A systematic review and meta-analysis.

Autor: G N S HS; Faculty of Pharmacy, M. S. Ramaiah University of Applied Sciences, Bangalore, India., Marise VLP; Faculty of Pharmacy, M. S. Ramaiah University of Applied Sciences, Bangalore, India., Satish KS; Faculty of Pharmacy, M. S. Ramaiah University of Applied Sciences, Bangalore, India., Yergolkar AV; Faculty of Pharmacy, M. S. Ramaiah University of Applied Sciences, Bangalore, India., Krishnamurthy M; Faculty of Pharmacy, M. S. Ramaiah University of Applied Sciences, Bangalore, India., Ganesan Rajalekshmi S; Faculty of Pharmacy, M. S. Ramaiah University of Applied Sciences, Bangalore, India. Electronic address: saraswathypradish@gmail.com., Radhika K; M. S. Ramaiah Medical College, Bangalore, India., Burri RR; Dr. Reddy's Laboratories, Hyderabad, India.
Jazyk: angličtina
Zdroj: Ageing research reviews [Ageing Res Rev] 2021 Nov; Vol. 71, pp. 101421. Date of Electronic Publication: 2021 Aug 08.
DOI: 10.1016/j.arr.2021.101421
Abstrakt: Drug discovery for Alzheimer's Disease (AD) is channeled towards unravelling key disease specific drug targets/genes to predict promising therapeutic candidates. Though enormous literature on AD genetics is available, there exists dearth in data pertinent to drug targets and crucial pathological pathways intertwined in disease progression. Further, the research findings revealing genetic associations failed to demonstrate consistency across different studies. This scenario prompted us to initiate a systematic review and meta-analysis with an aim of unearthing significant genetic hallmarks of AD. Initially, a Boolean search strategy was developed to retrieve case-control studies from PubMed, Cochrane, ProQuest, Europe PMC, grey literature and HuGE navigator. Subsequently, certain inclusion and exclusion criteria were framed to shortlist the relevant studies. These studies were later critically appraised using New Castle Ottawa Scale and Q-Genie followed by data extraction. Later, meta-analysis was performed only for those Single Nucleotide Polymorphisms (SNPs) which were evaluated in at least two different ethnicities from two different reports. Among, 204,351 studies retrieved, 820 met our eligibility criteria and 117 were processed for systematic review after critical appraisal. Ultimately, meta-analysis was performed for 23 SNPs associated with 15 genes which revealed significant associations of rs3865444 (CD33), rs7561528 (BIN1) and rs1801133 (MTHFR) with AD risk.
(Copyright © 2021 Elsevier B.V. All rights reserved.)
Databáze: MEDLINE
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