In:
Alzheimer's Research & Therapy, Springer Science and Business Media LLC, Vol. 14, No. 1 ( 2022-09-09)
Abstract:
Chronic inflammation is a central feature of several forms of dementia. However, few details on the associations of blood-based inflammation-related proteins with dementia incidence have been explored yet. Methods The Olink Target 96 Inflammation panel was measured in baseline serum samples (collected 07/2000–06/2002) of 1782 older adults from a German, population-based cohort study in a case-cohort design. Logistic regression models were used to assess the associations of biomarkers with all-cause dementia, Alzheimer’s disease, and vascular dementia incidence. Results During 17 years of follow-up, 504 participants were diagnosed with dementia, including 163 Alzheimer’s disease and 195 vascular dementia cases. After correction for multiple testing, 58 out of 72 tested (80.6%) biomarkers were statistically significantly associated with all-cause dementia, 22 with Alzheimer’s disease, and 33 with vascular dementia incidence. We identified four biomarker clusters, among which the strongest representatives, CX3CL1, EN-RAGE, LAP TGF-beta-1, and VEGF-A, were significantly associated with dementia endpoints independently from other inflammation-related proteins. CX3CL1 (odds ratio [95% confidence interval] per 1 standard deviation increase: 1.41 [1.24–1.60] ) and EN-RAGE (1.41 [1.25–1.60]) were associated with all-cause dementia incidence, EN-RAGE (1.51 [1.25–1.83] ) and LAP TGF-beta-1 (1.46 [1.21–1.76]) with Alzheimer’s disease incidence, and VEGF-A (1.43 [1.20–1.70] ) with vascular dementia incidence. All named associations were stronger among APOE ε4-negative subjects. Conclusion With this large, population-based cohort study, we show for the first time that the majority of inflammation-related proteins measured in blood samples are associated with total dementia incidence. Future studies should concentrate not only on single biomarkers but also on the complex relationships in biomarker clusters.
Type of Medium:
Online Resource
ISSN:
1758-9193
DOI:
10.1186/s13195-022-01063-y
Language:
English
Publisher:
Springer Science and Business Media LLC
Publication Date:
2022
detail.hit.zdb_id:
2506521-X
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