Evidence map›Paper›PMID 40076571›Full record

ArticleInternational journal of molecular sciences2025

SERPINA3: A Novel Therapeutic Target for Diabetes-Related Cognitive Impairment Identified Through Integrated Machine Learning and Molecular Docking Analysis.

Yu An, Zhaoming Cao, Yage Du, Guangyi Xu, Jingya Wang, Yinchao Ma, Ziyuan Wang, Jie Zheng, Yanhui Lu

Abstract read
In one paragraph

Article in International journal of molecular sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Yu AnDepartment of Endocrinology, Beijing Chao-Yang Hospital, Capital Medical University, Beijing 100020, China.ORCID 0000-0002-8429-2500
Zhaoming CaoSchool of Nursing, Peking University, Beijing 100191, China.ORCID 0000-0001-7800-7366
Yage DuSchool of Nursing, Peking University, Beijing 100191, China.
Guangyi XuSchool of Nursing, Peking University, Beijing 100191, China.
Jingya WangSchool of Nursing, Peking University, Beijing 100191, China.
Yinchao MaNHC Key Laboratory of Medical Immunology, School of Basic Medical Sciences, Peking University, Beijing 100191, China.
Ziyuan WangNHC Key Laboratory of Medical Immunology, School of Basic Medical Sciences, Peking University, Beijing 100191, China.
Jie ZhengSchool of Nursing, Peking University, Beijing 100191, China.
Yanhui LuSchool of Nursing, Peking University, Beijing 100191, China.

Funding

The Beijing Hospitals Authority Youth Programme QML20230301the National Key Research and Development Program of China 2022YFA1103602the National Natural Science Foundation of China 82103811the National Natural Science Foundation of China 82473618the National Natural Science Foundation of China 92357305The Young Elite Scientists Sponsorship Program by China Association for Science and Technology 2020QNRC001
6 · The paper itself

Abstract

Diabetes-related cognitive impairment (DCI) is a severe complication of type 2 diabetes mellitus (T2DM), with limited understanding of its molecular mechanisms hindering effective therapeutic development. This study identified SERPINA3 as a potential therapeutic target for DCI through integrated machine learning and molecular docking analyses. Transcriptomic data from cortical neuronal samples of T2DM patients were analysed using support vector machine recursive feature elimination (SVM-RFE) and least absolute shrinkage and selection operator (LASSO) regression, revealing SERPINA3 as a significantly upregulated gene in DCI. Experimental validation via Western blot confirmed elevated SERPINA3 protein levels in DCI patient plasma. Molecular docking demonstrated the stable binding of sulfonylurea hypoglycaemic agents, such as gliclazide and glimepiride, to SERPINA3, with binding energies of -6.8 and -6.6 kcal/mol, respectively. These findings suggest that SERPINA3 plays a pivotal role in DCI pathogenesis and that sulfonylurea drugs may exert neuroprotective effects through SERPINA3-mediated pathways. This study provides novel insights into the molecular mechanisms of DCI and highlights the potential of SERPINA3-targeted therapies for early intervention and treatment. Further research is warranted to validate these findings in larger cohorts and explore their clinical applicability.

Indexed as

Cognitive DysfunctionDiabetes Mellitus, Type 2Machine LearningMolecular Docking SimulationSerpinsAgedFemaleHumansHypoglycemic AgentsMaleMiddle AgedSulfonylurea CompoundsHypoglycemic AgentsSERPINA3 protein, humanSerpinsSulfonylurea Compoundscognitive impairmentdiabetesmachine learningmolecular dockingneuroprotectionSERPINA3sulfonylurea drugs

Identifiers

PMID40076571
PMCPMC11899970

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.