Affiliations: [a] Facultad de Medicina, Universidad de Málaga, Málaga, Spain
| [b] Centro de Investigaciones Médico-Sanitarias (CIMES), Málaga, Spain
| [c] Instituto de Investigación Biomédica de Málaga (IBIMA), Málaga, Spain
| [d] Departamento de Neurología, Hospital Universitario Virgen de la Victoria de Málaga, Málaga, Spain
Correspondence:
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Correspondence to: Natalia García-Casares, MD, PhD, Departamento de Medicina, Facultad de Medicina, Universidad de Málaga, Boulevard Louis Pasteur 32, C.P 29071 Málaga, Spain. E-mails: nagcasares@uma.es and nagcasares@gmail.com.
Note: [1] This article received a correction notice (Erratum) with the reference: 10.3233/JAD-JAD249011, available at http://doi.org/10.3233/JAD-249011.
Abstract: Background:Glucose metabolism and insulin signaling alterations play an important role in Alzheimer’s disease (AD) pathogenesis. Researchers have extensively attempted to characterize the exact pathophysiological mechanisms in the cerebrospinal fluid (CSF), as evidence concerning this fluid biomarkers is expected to enhance AD diagnosis’ specificity and accuracy and serve as an early disease detection tool. There is controversy about insulin levels in the CSF relationship with mild cognitive impairment (MCI) and AD. Objective:This systematic review provides an overview of the state-of-the-art knowledge about insulin-related CSF biomarkers in AD and MCI. Methods:We performed a qualitative systematic literature review of reported data of CSF glucose, insulin, or insulin-related molecules in humans with AD or MCI, consulting the electronic databases Medline, Scopus, Web of Science, Cochrane, and BASE until May 2022. Results:We selected 19 studies, 10 of them reporting data on CSF insulin and 8 on insulin-related molecules like growth factors or their binding proteins. They predominantly found decreased levels of CSF insulin and increased levels of CSF insulin-related growth factors and their binding proteins. Conclusion:Due to the studies’ protocols and results heterogeneity, we recommend a larger database of clinical trials with similar characteristics for a better understanding of this relationship.
