A multiancestry analysis of Alzheimer's disease coexpressed gene networks identifies a common immune signaling pathway regulated by granulocyte‐colony stimulating factor (G‐CSF): Genetics/omics and systems biology. (7th December 2020)

• Record Type: Journal Article
• Authors: Gardner, Olivia K.; Ling, George; Van Booven, Derek; Whitehead, Patrice L.; Hamilton‐Nelson, Kara L.; Adams, Larry D.; Starks, Takiyah D.; Scott, Aja M.; Celis, Katrina; Lacroix, Faina C.; Hofmann, Natalia K.; Rodriguez, Vanessa C.; Tejada, Sergio; Mena, Pedro Ramon; Silva‐Vergara, Concepcion; Feliciano, Nereida I.; Acosta, Heriberto; Martin, Eden R.; Vance, Jeffery M.; Cuccaro, Michael L.; Feliciano‐Astacio, Briseida E.; Byrd, Goldie S.; Haines, Jonathan L.; Bush, William S.; Beecham, Gary W.; Pericak‐Vance, Margaret A.; Griswold, Anthony J.
• Is Part Of: Alzheimer's & dementia. Volume 16(2020)Supplement 2
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-12-07
• Subjects: Alzheimer's disease -- Periodicals; Alzheimer Disease -- Periodicals; Dementia -- Periodicals; Démence; Maladie d'Alzheimer; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 616.83
• DOI: 10.1002/alz.045361
• Languages: English
• ISSNs: 1552-5260

Abstract

Abstract: Background: Understanding the effects of genetic factors that drive Alzheimer's Disease (AD) pathogenesis, including genetic differences across diverse ancestral populations, will drive discovery of novel pharmacological targets. Weighted gene co‐expression network analysis (WGCNA) is a powerful method for finding gene clusters (modules) with correlated expression, relating these modules to phenotypes, and thus identifying key upstream regulatory elements. To study networks of transcriptional dysregulation in AD across ancestries, we performed WGCNA in African‐American (AA), Non‐Hispanic White (NHW), and Puerto Rican (PR) populations. Method: RNA sequencing was performed on peripheral blood specimens from 275 AD cases (115 AA, 121 NHW, 39 PR) and 276 age and sex matched controls (119 AA, 120 NHW, 37 PR), all over age 65. We performed WGCNA and calculated the correlation between each co‐expression module and AD affection status within each ancestry group, adjusting for sex, age, and sequencing batch. Ingenuity Pathway Analysis (IPA) was used to identify enriched pathways and upstream regulators. Result: We identified 13 co‐expression modules that were significantly associated with AD. Across all ancestries, modules were enriched for pathways related to endocytosis and inflammation. These modules largely differed between African and European ancestry, though there was some overlap in the admixed PR population. Only one module had significantly decreased expression in cases across all three ancestries. It was enriched for immune signaling pathways and showed especially strong enrichment (p = 1.09*10 −19 ) for upstream regulation by granulocyte‐colony stimulating factor (G‐CSF). G‐CSF activates JAK2 and STAT1, which were central hub genes within this module, as were AD‐associated genes CR1 and TLR4 . G‐CSF acts as a cytokine, hormone, and neurotrophic factor. In AD mouse models, G‐CSF decreases brain amyloid burden and reverses cognitive impairment. A recombinant form of G‐CSF is approved for use in neutropenia and has completed Phase II clinical trials for the treatment of AD (NCT01617577, NCT03656042). A current Phase II trial for the closely related GM‐CSF is ongoing (NCT01409915). Conclusion: Through analyses of multiple populations, we have identified AD‐associated gene expression networks. Though these networks largely differ by ancestral background, convergence on pathways relevant to AD pathology suggest that shared underlying disease etiology can be targeted pharmacologically.