Combined treatment with valproic acid and estrogen has neuroprotective effects in ovariectomized mice with Alzheimer’s disease

Li, Yanzhen; Liu, Yuanjie; Zhang, Wei; Luo, Shifang; Zhou, Xinping; He, Guiqiong

doi:10.4103/1673-5374.308103

Cited by 7 publications

(2 citation statements)

References 42 publications

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“…Furthermore, the use of valproic acid in AD mouse models reduced brain inflammation and helped ameliorate memory deficits [109]. Recently, the combination of valproic acid with estrogen showed some therapeutic benefit on ovariectomized mice with AD [110]. Conversely, excessive, chronic use of valproic acid contributes to atrophy and degeneration of the hippocampus and reduced brain volume [111].…”

Section: Chemicalsmentioning

confidence: 99%

Key Disease Mechanisms Linked to Alzheimer’s Disease in the Entorhinal Cortex

Bottero

Powers

Yalamanchi

et al. 2021

IJMS

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Alzheimer’s disease (AD) is a chronic, neurodegenerative brain disorder affecting millions of Americans that is expected to increase in incidence with the expanding aging population. Symptomatic AD patients show cognitive decline and often develop neuropsychiatric symptoms due to the accumulation of insoluble proteins that produce plaques and tangles seen in the brain at autopsy. Unexpectedly, some clinically normal individuals also show AD pathology in the brain at autopsy (asymptomatic AD, AsymAD). In this study, SWItchMiner software was used to identify key switch genes in the brain’s entorhinal cortex that lead to the development of AD or disease resilience. Seventy-two switch genes were identified that are differentially expressed in AD patients compared to healthy controls. These genes are involved in inflammation, platelet activation, and phospholipase D and estrogen signaling. Peroxisome proliferator-activated receptor γ (PPARG), zinc-finger transcription factor (YY1), sterol regulatory element-binding transcription factor 2 (SREBF2), and early growth response 1 (EGR1) were identified as transcription factors that potentially regulate switch genes in AD. Comparing AD patients to AsymAD individuals revealed 51 switch genes; PPARG as a potential regulator of these genes, and platelet activation and phospholipase D as critical signaling pathways. Chemical–protein interaction analysis revealed that valproic acid is a therapeutic agent that could prevent AD from progressing.

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Section: Chemicalsmentioning

confidence: 99%

Key Disease Mechanisms Linked to Alzheimer’s Disease in the Entorhinal Cortex

Bottero

Powers

Yalamanchi

et al. 2021

IJMS

View full text Add to dashboard Cite

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“…Valproic acid is the only therapeutic sharing targets with three different drug categories (anti‐inflammatory drugs, statins, and metabolic drugs) and may explain the neuroprotective effect of valproic acid in combination with estrogen. 51 …”

Section: Discussionmentioning

confidence: 99%

Preventing Alzheimer's disease within reach by 2025: Targeted‐risk‐AD‐prevention (TRAP) strategy

Vitali

Branigan

Brinton

2021

A&D Transl Res & Clin Interv

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Introduction Alzheimer's disease (AD) is a progressive neurodegenerative disease that currently affects 6.2 million people in the United States and is projected to impact 12.7 million worldwide in 2050 with no effective disease‐modifying therapeutic or cure. In 2011 as part of the National Alzheimer's Project Act, the National Plan to Address Alzheimer's Disease was signed into law which proposed to effectively prevent AD by 2025, which is rapidly approaching. The preclinical phase of AD can begin 20 years prior to diagnosis, which provides an extended window for preventive measures that would exert a transformative impact on incidence and prevalence of AD. Methods A novel combination of text‐mining and natural language processing strategies to identify (1) AD risk factors, (2) therapeutics that can target risk factor pathways, and (3) studies supporting therapeutics in the PubMed database was conducted. To classify the literature relevant to AD preventive strategies, a relevance score (RS) based on STRING (search tool for the retrieval of interacting genes/proteins) score for protein–protein interactions and a confidence score (CS) on Bayesian inference were developed. To address mechanism of action, network analysis of protein targets for effective drugs was conducted. Collectively, the analytic approach, referred to as a targeted‐risk‐AD‐prevention (TRAP) strategy, led to a ranked list of candidate therapeutics to reduce AD risk. Results Based on TRAP mining of 9625 publications, 364 AD risk factors were identified. Based on risk factor indications, 629 Food and Drug Administration‐approved drugs were identified. Computation of ranking scores enabled identification of 46 relevant high confidence (RS & CS > 0.7) drugs associated with reduced AD risk. Within these candidate therapeutics, 16 had more than one clinical study supporting AD risk reduction. Top‐ranked therapeutics with high confidence emerged within lipid‐lowering, anti‐inflammatory, hormone, and metabolic‐related drug classes. Discussion Outcomes of our novel bioinformatic strategy support therapeutic targeting of biological mechanisms and pathways underlying relevant AD risk factors with high confidence. Early interventions that target pathways associated with increased risk of AD have the potential to support the goal of effectively preventing AD by 2025.

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