Harmonizing genotype array data to understand genetic risk for brain amyloid burden in the AMYPAD PNHS Consortium
Loading...
Date
Document Type
Document Version
Author
Luckett, Emma S.
Abakkouy, Yasmina
Lorenzini, Luigi
Collij, Lyduine E.
Vállez García, David
Visser, Pieter Jelle
den Braber, Anouk
Ritchie, Craig
Boada, Mercè
Genius, Patricia
Vilor Tejedor, Natàlia, 1988-
Gispert López, Juan Domingo
Vandenberghe, Rik
Barkhof, Frederik
Cleynen, Isabelle
AMYPAD Consortium
Abakkouy, Yasmina
Lorenzini, Luigi
Collij, Lyduine E.
Vállez García, David
Visser, Pieter Jelle
den Braber, Anouk
Ritchie, Craig
Boada, Mercè
Genius, Patricia
Vilor Tejedor, Natàlia, 1988-
Gispert López, Juan Domingo
Vandenberghe, Rik
Barkhof, Frederik
Cleynen, Isabelle
AMYPAD Consortium
License
Citation
Luckett ES, Abakkouy Y, Lorenzini L, Collij LE, Vallez Garcia D, Visser PJ, den Braber A, et al. Harmonizing genotype array data to understand genetic risk for brain amyloid burden in the AMYPAD PNHS Consortium. Alzheimers Dement. 2025 Sep;21(9):e70376. DOI: 10.1002/alz.70376
Abstract
Introduction: We sought to harmonize genotype data from the predementia AMYPAD (Amyloid Imaging to Prevent Alzheimer's Disease) Consortium, compute polygenic risk scores (PRS), and determine their association with global amyloid deposition. Methods: Genetic data from five AMYPAD parent cohorts were harmonized, and PRS were computed for Alzheimer's disease (AD) susceptibility, cerebrospinal fluid (CSF) amyloid beta (Aβ)42, and CSF phosphorylated tau181. Cross-sectional amyloid (Centiloid [CL]) burden was available for all participants, and regression models determined if PRS were associated with CL burden. Results: After harmonization, data for 867 participants showed that high CL burden was most strongly predicted by CSF Aβ42 PRS compared to traditional AD susceptibility PRS. Discussion: This work emphasizes the importance of data harmonization and pooling of cohorts for large-powered studies. Findings suggest a genetic predisposition to amyloid pathology that may predispose individuals early in the AD continuum. This validates the potential use of PRS in clinical (trial) settings as a non-invasive tool to assess AD risk. Highlights: We developed a robust harmonization pipeline for multi-cohort genotype array data. Cerebrospinal fluid amyloid beta (Aβ)-specific polygenic risk scores (PRS) more strongly predicted global Aβ positron emission tomography burden than other PRS. Results suggest a strong genetic predisposition to early Aβ pathology. This work highlights the need for robust data harmonization and data pooling. This work also validates the potential use of PRS as a non-invasive tool to assess Alzheimer's disease risk.
Introduction: We sought to harmonize genotype data from the predementia AMYPAD (Amyloid Imaging to Prevent Alzheimer's Disease) Consortium, compute polygenic risk scores (PRS), and determine their association with global amyloid deposition. Methods: Genetic data from five AMYPAD parent cohorts were harmonized, and PRS were computed for Alzheimer's disease (AD) susceptibility, cerebrospinal fluid (CSF) amyloid beta (Aβ)42, and CSF phosphorylated tau181. Cross-sectional amyloid (Centiloid [CL]) burden was available for all participants, and regression models determined if PRS were associated with CL burden. Results: After harmonization, data for 867 participants showed that high CL burden was most strongly predicted by CSF Aβ42 PRS compared to traditional AD susceptibility PRS. Discussion: This work emphasizes the importance of data harmonization and pooling of cohorts for large-powered studies. Findings suggest a genetic predisposition to amyloid pathology that may predispose individuals early in the AD continuum. This validates the potential use of PRS in clinical (trial) settings as a non-invasive tool to assess AD risk. Highlights: We developed a robust harmonization pipeline for multi-cohort genotype array data. Cerebrospinal fluid amyloid beta (Aβ)-specific polygenic risk scores (PRS) more strongly predicted global Aβ positron emission tomography burden than other PRS. Results suggest a strong genetic predisposition to early Aβ pathology. This work highlights the need for robust data harmonization and data pooling. This work also validates the potential use of PRS as a non-invasive tool to assess Alzheimer's disease risk.
Introduction: We sought to harmonize genotype data from the predementia AMYPAD (Amyloid Imaging to Prevent Alzheimer's Disease) Consortium, compute polygenic risk scores (PRS), and determine their association with global amyloid deposition. Methods: Genetic data from five AMYPAD parent cohorts were harmonized, and PRS were computed for Alzheimer's disease (AD) susceptibility, cerebrospinal fluid (CSF) amyloid beta (Aβ)42, and CSF phosphorylated tau181. Cross-sectional amyloid (Centiloid [CL]) burden was available for all participants, and regression models determined if PRS were associated with CL burden. Results: After harmonization, data for 867 participants showed that high CL burden was most strongly predicted by CSF Aβ42 PRS compared to traditional AD susceptibility PRS. Discussion: This work emphasizes the importance of data harmonization and pooling of cohorts for large-powered studies. Findings suggest a genetic predisposition to amyloid pathology that may predispose individuals early in the AD continuum. This validates the potential use of PRS in clinical (trial) settings as a non-invasive tool to assess AD risk. Highlights: We developed a robust harmonization pipeline for multi-cohort genotype array data. Cerebrospinal fluid amyloid beta (Aβ)-specific polygenic risk scores (PRS) more strongly predicted global Aβ positron emission tomography burden than other PRS. Results suggest a strong genetic predisposition to early Aβ pathology. This work highlights the need for robust data harmonization and data pooling. This work also validates the potential use of PRS as a non-invasive tool to assess Alzheimer's disease risk.
Introduction: We sought to harmonize genotype data from the predementia AMYPAD (Amyloid Imaging to Prevent Alzheimer's Disease) Consortium, compute polygenic risk scores (PRS), and determine their association with global amyloid deposition. Methods: Genetic data from five AMYPAD parent cohorts were harmonized, and PRS were computed for Alzheimer's disease (AD) susceptibility, cerebrospinal fluid (CSF) amyloid beta (Aβ)42, and CSF phosphorylated tau181. Cross-sectional amyloid (Centiloid [CL]) burden was available for all participants, and regression models determined if PRS were associated with CL burden. Results: After harmonization, data for 867 participants showed that high CL burden was most strongly predicted by CSF Aβ42 PRS compared to traditional AD susceptibility PRS. Discussion: This work emphasizes the importance of data harmonization and pooling of cohorts for large-powered studies. Findings suggest a genetic predisposition to amyloid pathology that may predispose individuals early in the AD continuum. This validates the potential use of PRS in clinical (trial) settings as a non-invasive tool to assess AD risk. Highlights: We developed a robust harmonization pipeline for multi-cohort genotype array data. Cerebrospinal fluid amyloid beta (Aβ)-specific polygenic risk scores (PRS) more strongly predicted global Aβ positron emission tomography burden than other PRS. Results suggest a strong genetic predisposition to early Aβ pathology. This work highlights the need for robust data harmonization and data pooling. This work also validates the potential use of PRS as a non-invasive tool to assess Alzheimer's disease risk.
Introduction: We sought to harmonize genotype data from the predementia AMYPAD (Amyloid Imaging to Prevent Alzheimer's Disease) Consortium, compute polygenic risk scores (PRS), and determine their association with global amyloid deposition. Methods: Genetic data from five AMYPAD parent cohorts were harmonized, and PRS were computed for Alzheimer's disease (AD) susceptibility, cerebrospinal fluid (CSF) amyloid beta (Aβ)42, and CSF phosphorylated tau181. Cross-sectional amyloid (Centiloid [CL]) burden was available for all participants, and regression models determined if PRS were associated with CL burden. Results: After harmonization, data for 867 participants showed that high CL burden was most strongly predicted by CSF Aβ42 PRS compared to traditional AD susceptibility PRS. Discussion: This work emphasizes the importance of data harmonization and pooling of cohorts for large-powered studies. Findings suggest a genetic predisposition to amyloid pathology that may predispose individuals early in the AD continuum. This validates the potential use of PRS in clinical (trial) settings as a non-invasive tool to assess AD risk. Highlights: We developed a robust harmonization pipeline for multi-cohort genotype array data. Cerebrospinal fluid amyloid beta (Aβ)-specific polygenic risk scores (PRS) more strongly predicted global Aβ positron emission tomography burden than other PRS. Results suggest a strong genetic predisposition to early Aβ pathology. This work highlights the need for robust data harmonization and data pooling. This work also validates the potential use of PRS as a non-invasive tool to assess Alzheimer's disease risk.
