4.6 Article

Plasma glial fibrillary acidic protein detects Alzheimer pathology and predicts future conversion to Alzheimer dementia in patients with mild cognitive impairment

期刊

ALZHEIMERS RESEARCH & THERAPY
卷 13, 期 1, 页码 -

出版社

BMC
DOI: 10.1186/s13195-021-00804-9

关键词

Blood biomarkers; GFAP; Alzheimer’ s disease; Mild cognitive impairment

资金

  1. Swedish Research Council
  2. Knut and Alice Wallenberg Foundation
  3. Marianne and Marcus Wallenberg Foundation
  4. Strategic Research Area MultiPark (Multidisciplinary Research in Parkinson's disease) at Lund University
  5. Swedish Alzheimer Foundation
  6. Swedish Brain Foundation
  7. Parkinson foundation of Sweden
  8. Parkinson Research Foundation
  9. Skane University Hospital Foundation
  10. Wallenberg Center for Molecular Medicine
  11. Medical Faculty at Lund University
  12. Swedish Medical Association
  13. Konung Gustaf V:s och Drottning Victorias Frimurarestiftelse
  14. Region Skane
  15. Bundy Academy
  16. Swedish federal government under the ALF agreement
  17. Lund University

向作者/读者索取更多资源

Plasma GFAP can detect AD pathology in patients with MCI and predict conversion to AD dementia, showing potential clinical utility.
Introduction Plasma glial fibrillary acidic protein (GFAP) is a marker of astroglial activation and astrocytosis. We assessed the ability of plasma GFAP to detect Alzheimer's disease (AD) pathology in the form of AD-related amyloid-beta (A beta) pathology and conversion to AD dementia in a mild cognitive impairment (MCI) cohort. Method One hundred sixty MCI patients were followed for 4.7 years (average). AD pathology was defined using cerebrospinal fluid (CSF) A beta 42/40 and A beta 42/total tau (T-tau). Plasma GFAP was measured at baseline and follow-up using Simoa technology. Results Baseline plasma GFAP could detect abnormal CSF A beta 42/40 and CSF A beta 42/T-tau with an AUC of 0.79 (95% CI 0.72-0.86) and 0.80 (95% CI 0.72-0.86), respectively. When also including APOE epsilon 4 status as a predictor, the accuracy of the model to detect abnormal CSF A beta 42/40 status improved (AUC = 0.86, p = 0.02). Plasma GFAP predicted subsequent conversion to AD dementia with an AUC of 0.84 (95% CI 0.77-0.91), which was not significantly improved when adding APOE epsilon 4 or age as predictors to the model. Longitudinal GFAP slopes for A beta-positive and MCI who progressed to dementia (AD or other) were significantly steeper than those for A beta-negative (p = 0.007) and stable MCI (p < 0.0001), respectively. Conclusion Plasma GFAP can detect AD pathology in patients with MCI and predict conversion to AD dementia.

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