Addition of inflammation-related biomarkers to the CAIDE model for risk prediction of all-cause dementia, Alzheimer's disease and vascular dementia in a prospective study
© 2024. The Author(s)..
BACKGROUND: It is of interest whether inflammatory biomarkers can improve dementia prediction models, such as the widely used Cardiovascular Risk Factors, Aging and Dementia (CAIDE) model.
METHODS: The Olink Target 96 Inflammation panel was assessed in a nested case-cohort design within a large, population-based German cohort study (n = 9940; age-range: 50-75 years). All study participants who developed dementia over 20 years of follow-up and had complete CAIDE variable data (n = 562, including 173 Alzheimer's disease (AD) and 199 vascular dementia (VD) cases) as well as n = 1,356 controls were selected for measurements. 69 inflammation-related biomarkers were eligible for use. LASSO logistic regression and bootstrapping were utilized to select relevant biomarkers and determine areas under the curve (AUCs).
RESULTS: The CAIDE model 2 (including Apolipoprotein E (APOE) ε4 carrier status) predicted all-cause dementia, AD, and VD better than CAIDE model 1 (without APOE ε4) with AUCs of 0.725, 0.752 and 0.707, respectively. Although 20, 7, and 4 inflammation-related biomarkers were selected by LASSO regression to improve CAIDE model 2, the AUCs did not increase markedly. CAIDE models 1 and 2 generally performed better in mid-life (50-64 years) than in late-life (65-75 years) sub-samples of our cohort, but again, inflammation-related biomarkers did not improve their predictive abilities.
CONCLUSIONS: Despite a lack of improvement in dementia risk prediction, the selected inflammation-related biomarkers were significantly associated with dementia outcomes and may serve as a starting point to further elucidate the pathogenesis of dementia.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:21 |
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| Enthalten in: |
Immunity & ageing : I & A - 21(2024), 1 vom: 03. Apr., Seite 23 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Trares, Kira [VerfasserIn] |
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| Links: |
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| Themen: |
Alzheimer’s disease |
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| Anmerkungen: |
Date Revised 26.04.2024 published: Electronic Citation Status PubMed-not-MEDLINE |
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| doi: |
10.1186/s12979-024-00427-2 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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NLM370602404 |
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| 500 | |a Citation Status PubMed-not-MEDLINE | ||
| 520 | |a © 2024. The Author(s). | ||
| 520 | |a BACKGROUND: It is of interest whether inflammatory biomarkers can improve dementia prediction models, such as the widely used Cardiovascular Risk Factors, Aging and Dementia (CAIDE) model | ||
| 520 | |a METHODS: The Olink Target 96 Inflammation panel was assessed in a nested case-cohort design within a large, population-based German cohort study (n = 9940; age-range: 50-75 years). All study participants who developed dementia over 20 years of follow-up and had complete CAIDE variable data (n = 562, including 173 Alzheimer's disease (AD) and 199 vascular dementia (VD) cases) as well as n = 1,356 controls were selected for measurements. 69 inflammation-related biomarkers were eligible for use. LASSO logistic regression and bootstrapping were utilized to select relevant biomarkers and determine areas under the curve (AUCs) | ||
| 520 | |a RESULTS: The CAIDE model 2 (including Apolipoprotein E (APOE) ε4 carrier status) predicted all-cause dementia, AD, and VD better than CAIDE model 1 (without APOE ε4) with AUCs of 0.725, 0.752 and 0.707, respectively. Although 20, 7, and 4 inflammation-related biomarkers were selected by LASSO regression to improve CAIDE model 2, the AUCs did not increase markedly. CAIDE models 1 and 2 generally performed better in mid-life (50-64 years) than in late-life (65-75 years) sub-samples of our cohort, but again, inflammation-related biomarkers did not improve their predictive abilities | ||
| 520 | |a CONCLUSIONS: Despite a lack of improvement in dementia risk prediction, the selected inflammation-related biomarkers were significantly associated with dementia outcomes and may serve as a starting point to further elucidate the pathogenesis of dementia | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Alzheimer’s disease | |
| 650 | 4 | |a Cohort study | |
| 650 | 4 | |a Dementia | |
| 650 | 4 | |a Inflammation | |
| 650 | 4 | |a Risk prediction | |
| 650 | 4 | |a Vascular dementia | |
| 700 | 1 | |a Wiesenfarth, Manuel |e verfasserin |4 aut | |
| 700 | 1 | |a Stocker, Hannah |e verfasserin |4 aut | |
| 700 | 1 | |a Perna, Laura |e verfasserin |4 aut | |
| 700 | 1 | |a Petrera, Agnese |e verfasserin |4 aut | |
| 700 | 1 | |a Hauck, Stefanie M |e verfasserin |4 aut | |
| 700 | 1 | |a Beyreuther, Konrad |e verfasserin |4 aut | |
| 700 | 1 | |a Brenner, Hermann |e verfasserin |4 aut | |
| 700 | 1 | |a Schöttker, Ben |e verfasserin |4 aut | |
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