Alzheimer’s disease (AD) is a multifactorial disease with both genetic and environmental factors contributing to its etiology. Previous evidence has implicated disturbed insulin signaling as a key mechanism that plays a role in both neurodegenerative diseases such as AD and comorbid somatic diseases such as diabetes mellitus type 2 (DM2). In this study, we analysed available genome-wide association studies (GWASs) of AD and somatic insulin-related diseases and conditions (SID), i.e., DM2, metabolic syndrome and obesity, to identify genes associated with both AD and SID that could increase our insights into their molecular underpinnings. We then performed functional enrichment analyses of these genes. Subsequently, using (additional) GWAS data, we conducted shared genetic etiology analyses between AD and SID, on the one hand, and blood and cerebrospinal fluid (CSF) metabolite levels on the other hand. Further, integrating all these analysis results with elaborate literature searches, we built a molecular landscape of the overlap between AD and SID. From the landscape, multiple functional themes emerged, including insulin signaling, estrogen signaling, synaptic transmission, lipid metabolism and tau signaling. We also found shared genetic etiologies between AD/SID and the blood/CSF levels of multiple metabolites, pointing towards “energy metabolism” as a key metabolic pathway that is affected in both AD and SID. Lastly, the landscape provided leads for putative novel drug targets for AD (including MARK4, TMEM219, FKBP5, NDUFS3 and IL34) that could be further developed into new AD treatments.

Ruisch, I.H., Widomska, J., De Witte, W., Mota, N.R., Fanelli, G., Van Gils, V., et al. (2024). Molecular landscape of the overlap between Alzheimer’s disease and somatic insulin-related diseases. ALZHEIMER'S RESEARCH & THERAPY, 16(1), N/A-N/A [10.1186/s13195-024-01609-2].

Molecular landscape of the overlap between Alzheimer’s disease and somatic insulin-related diseases

Fanelli G.
Writing – Review & Editing
;
2024

Abstract

Alzheimer’s disease (AD) is a multifactorial disease with both genetic and environmental factors contributing to its etiology. Previous evidence has implicated disturbed insulin signaling as a key mechanism that plays a role in both neurodegenerative diseases such as AD and comorbid somatic diseases such as diabetes mellitus type 2 (DM2). In this study, we analysed available genome-wide association studies (GWASs) of AD and somatic insulin-related diseases and conditions (SID), i.e., DM2, metabolic syndrome and obesity, to identify genes associated with both AD and SID that could increase our insights into their molecular underpinnings. We then performed functional enrichment analyses of these genes. Subsequently, using (additional) GWAS data, we conducted shared genetic etiology analyses between AD and SID, on the one hand, and blood and cerebrospinal fluid (CSF) metabolite levels on the other hand. Further, integrating all these analysis results with elaborate literature searches, we built a molecular landscape of the overlap between AD and SID. From the landscape, multiple functional themes emerged, including insulin signaling, estrogen signaling, synaptic transmission, lipid metabolism and tau signaling. We also found shared genetic etiologies between AD/SID and the blood/CSF levels of multiple metabolites, pointing towards “energy metabolism” as a key metabolic pathway that is affected in both AD and SID. Lastly, the landscape provided leads for putative novel drug targets for AD (including MARK4, TMEM219, FKBP5, NDUFS3 and IL34) that could be further developed into new AD treatments.
2024
Ruisch, I.H., Widomska, J., De Witte, W., Mota, N.R., Fanelli, G., Van Gils, V., et al. (2024). Molecular landscape of the overlap between Alzheimer’s disease and somatic insulin-related diseases. ALZHEIMER'S RESEARCH & THERAPY, 16(1), N/A-N/A [10.1186/s13195-024-01609-2].
Ruisch, I. H.; Widomska, J.; De Witte, W.; Mota, N. R.; Fanelli, G.; Van Gils, V.; Jansen, W. J.; Vos, S. J. B.; Fothi, A.; Barta, C.; Berkel, S.; Ala...espandi
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/1003160
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