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Stevenson-Hoare J, Heslegrave A, Leonenko G, Fathalla D, Bellou E, Luckcuck L, Marshall R, Sims R, Morgan BP, Hardy J, de Strooper B, Williams J, Zetterberg H, Escott-Price V. Plasma biomarkers and genetics in the diagnosis and prediction of Alzheimer's disease. Brain 2023; 146:690-699. [PMID: 35383826 PMCID: PMC9924904 DOI: 10.1093/brain/awac128] [Citation(s) in RCA: 28] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Revised: 02/14/2022] [Accepted: 03/13/2022] [Indexed: 11/12/2022] Open
Abstract
Plasma biomarkers for Alzheimer's disease-related pathologies have undergone rapid developments during the past few years, and there are now well-validated blood tests for amyloid and tau pathology, as well as neurodegeneration and astrocytic activation. To define Alzheimer's disease with biomarkers rather than clinical assessment, we assessed prediction of research-diagnosed disease status using these biomarkers and tested genetic variants associated with the biomarkers that may reflect more accurately the risk of biochemically defined Alzheimer's disease instead of the risk of dementia. In a cohort of Alzheimer's disease cases [n = 1439, mean age 68 years (standard deviation = 8.2)] and screened controls [n = 508, mean age 82 years (standard deviation = 6.8)], we measured plasma concentrations of the 40 and 42 amino acid-long amyloid-β (Aβ) fragments (Aβ40 and Aβ42, respectively), tau phosphorylated at amino acid 181 (P-tau181), neurofilament light (NfL) and glial fibrillary acidic protein (GFAP) using state-of-the-art Single molecule array (Simoa) technology. We tested the relationships between the biomarkers and Alzheimer's disease genetic risk, age at onset and disease duration. We also conducted a genome-wide association study for association of disease risk genes with these biomarkers. The prediction accuracy of Alzheimer's disease clinical diagnosis by the combination of all biomarkers, APOE and polygenic risk score reached area under receiver operating characteristic curve (AUC) = 0.81, with the most significant contributors being ε4, Aβ40 or Aβ42, GFAP and NfL. All biomarkers were significantly associated with age in cases and controls (P < 4.3 × 10-5). Concentrations of the Aβ-related biomarkers in plasma were significantly lower in cases compared with controls, whereas other biomarker levels were significantly higher in cases. In the case-control genome-wide analyses, APOE-ε4 was associated with all biomarkers (P = 0.011-4.78 × 10-8), except NfL. No novel genome-wide significant single nucleotide polymorphisms were found in the case-control design; however, in a case-only analysis, we found two independent genome-wide significant associations between the Aβ42/Aβ40 ratio and WWOX and COPG2 genes. Disease prediction modelling by the combination of all biomarkers indicates that the variance attributed to P-tau181 is mostly captured by APOE-ε4, whereas Aβ40, Aβ42, GFAP and NfL biomarkers explain additional variation over and above APOE. We identified novel plausible genome wide-significant genes associated with Aβ42/Aβ40 ratio in a sample which is 50 times smaller than current genome-wide association studies in Alzheimer's disease.
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Affiliation(s)
| | - Amanda Heslegrave
- Dementia Research Institute, University College London, London, UK
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
| | - Ganna Leonenko
- Dementia Research Institute, Cardiff University, Cardiff, UK
| | - Dina Fathalla
- Dementia Research Institute, Cardiff University, Cardiff, UK
| | - Eftychia Bellou
- Dementia Research Institute, Cardiff University, Cardiff, UK
| | - Lauren Luckcuck
- Dementia Research Institute, Cardiff University, Cardiff, UK
| | - Rachel Marshall
- Division of Neuroscience and Mental Health, Cardiff University, Cardiff, UK
| | - Rebecca Sims
- Division of Neuroscience and Mental Health, Cardiff University, Cardiff, UK
| | | | - John Hardy
- Dementia Research Institute, University College London, London, UK
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
| | - Bart de Strooper
- Dementia Research Institute, University College London, London, UK
- VIB Center for Brain and Disease Research, 3000 Leuven, Belgium
- KU Leuven, Leuven Brain Institute, 3000 Leuven, Belgium
| | - Julie Williams
- Dementia Research Institute, Cardiff University, Cardiff, UK
| | - Henrik Zetterberg
- Dementia Research Institute, University College London, London, UK
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Valentina Escott-Price
- Dementia Research Institute, Cardiff University, Cardiff, UK
- Division of Neuroscience and Mental Health, Cardiff University, Cardiff, UK
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