Plasma biomarkers and genetics in the diagnosis and prediction of Alzheimer's disease

Stevenson-Hoare, Joshua, Heslegrave, Amanda, Leonenko, Ganna ORCID: https://orcid.org/0000-0001-8025-661X, Fathalla, Dina, Bellou, Eftychia, Luckcuck, Lauren, Marshall, Rachel, Sims, Rebecca ORCID: https://orcid.org/0000-0002-3885-1199, Morgan, Bryan Paul ORCID: https://orcid.org/0000-0003-4075-7676, Hardy, John, de Strooper, Bart, Williams, Julie ORCID: https://orcid.org/0000-0002-4069-0259, Zetterberg, Henrik and Escott-Price, Valentina ORCID: https://orcid.org/0000-0003-1784-5483 2023. Plasma biomarkers and genetics in the diagnosis and prediction of Alzheimer's disease. Brain 146 (2) , pp. 690-699. 10.1093/brain/awac128

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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 [SD=8.2]) and screened controls (N=508, mean age 82 years [SD=6.8]), we measured plasma concentrations of the 40 and 42 amino acid-long amyloid β 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 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<4.3x10-5). 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- 4.78x10-8), except NfL. No novel genome-wide significant SNPs 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 fifty times smaller than current genome-wide association studies in Alzheimer’s disease.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Advanced Research Computing @ Cardiff (ARCCA) MRC Centre for Neuropsychiatric Genetics and Genomics (CNGG) Medicine Psychology
Publisher:	Oxford University Press
ISSN:	0006-8950
Funders:	MRC
Date of First Compliant Deposit:	16 March 2022
Date of Acceptance:	13 March 2022
Last Modified:	25 Oct 2024 01:09
URI:	https://orca.cardiff.ac.uk/id/eprint/148424

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