Literature DB >> 34381170

Identification of novel drug targets for Alzheimer's disease by integrating genetics and proteomes from brain and blood.

Ya-Nan Ou1, Yu-Xiang Yang2, Yue-Ting Deng2, Can Zhang3, Hao Hu1, Bang-Sheng Wu2, Yi Liu1, Yan-Jiang Wang4, Ying Zhu5, John Suckling6, Lan Tan1, Jin-Tai Yu7.   

Abstract

Genome-wide association studies (GWASs) have discovered numerous risk genes for Alzheimer's disease (AD), but how these genes confer AD risk is challenging to decipher. To efficiently transform genetic associations into drug targets for AD, we employed an integrative analytical pipeline using proteomes in the brain and blood by systematically applying proteome-wide association study (PWAS), Mendelian randomization (MR) and Bayesian colocalization. Collectively, we identified the brain protein abundance of 7 genes (ACE, ICA1L, TOM1L2, SNX32, EPHX2, CTSH, and RTFDC1) are causal in AD (P < 0.05/proteins identified for PWAS and MR; PPH4 >80% for Bayesian colocalization). The proteins encoded by these genes were mainly expressed on the surface of glutamatergic neurons and astrocytes. Of them, ACE with its protein abundance was also identified in significant association with AD on the blood-based studies and showed significance at the transcriptomic level. SNX32 was also found to be associated with AD at the blood transcriptomic level. Collectively, our current study results on genetic, proteomic, and transcriptomic approaches has identified compelling genes, which may provide important leads to design future functional studies and potential drug targets for AD.
© 2021. The Author(s), under exclusive licence to Springer Nature Limited.

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Year:  2021        PMID: 34381170     DOI: 10.1038/s41380-021-01251-6

Source DB:  PubMed          Journal:  Mol Psychiatry        ISSN: 1359-4184            Impact factor:   15.992


  2 in total

1.  Conducting a Reproducible Mendelian Randomization Analysis Using the R Analytic Statistical Environment.

Authors:  Danielle Rasooly; Chirag J Patel
Journal:  Curr Protoc Hum Genet       Date:  2019-01-15

2.  Angiotensin-converting enzyme levels and activity in Alzheimer's disease: differences in brain and CSF ACE and association with ACE1 genotypes.

Authors:  Scott Miners; Emma Ashby; Shabnam Baig; Rachel Harrison; Hannah Tayler; Elizabeth Speedy; Jonathan A Prince; Seth Love; Patrick G Kehoe
Journal:  Am J Transl Res       Date:  2009-01-18       Impact factor: 4.060

  2 in total
  4 in total

Review 1.  Application of Bayesian genomic prediction methods to genome-wide association analyses.

Authors:  Anna Wolc; Jack C M Dekkers
Journal:  Genet Sel Evol       Date:  2022-05-13       Impact factor: 5.100

2.  Identification of novel proteins for lacunar stroke by integrating genome-wide association data and human brain proteomes.

Authors:  Chengcheng Zhang; Fengqin Qin; Xiaojing Li; Xiangdong Du; Tao Li
Journal:  BMC Med       Date:  2022-06-23       Impact factor: 11.150

3.  Single-nucleus RNA sequencing reveals the shared mechanisms inducing cognitive impairment between COVID-19 and Alzheimer's disease.

Authors:  Yifan Fu; Zhirong Guo; Yulin Wang; Haonan Zhang; Feifan Zhang; Zihao Xu; Xin Shen; Reiko T Roppongi; Shaocong Mo; Wenchao Gu; Takahito Nakajima; Yoshito Tsushima
Journal:  Front Immunol       Date:  2022-09-23       Impact factor: 8.786

4.  ICA1L Is Associated with Small Vessel Disease: A Proteome-Wide Association Study in Small Vessel Stroke and Intracerebral Haemorrhage.

Authors:  Natalia Cullell; Cristina Gallego-Fábrega; Jara Cárcel-Márquez; Elena Muiño; Laia Llucià-Carol; Miquel Lledós; Jesús M Martín-Campos; Jessica Molina; Laura Casas; Marta Almeria; Israel Fernández-Cadenas; Jerzy Krupinski
Journal:  Int J Mol Sci       Date:  2022-03-15       Impact factor: 5.923

  4 in total

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