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A/T/N polygenic risk score for cognitive decline in old age

Annah M. Moore, Teresa J. Filshtein, Logan Dumitrescu, Amal Harrati, Fanny Elahi, Elizabeth C. Mormino, Yuetiva Deming, Brian W. Kunkle, Dan M. Mungas, Trey Hedden, Liana G. Apostolova, View ORCID ProfileAndrew J. Saykin, Danai Chasioti, View ORCID ProfileQiongshi Lu, Jessica Dennis, Julia Sealock, Lea K. Davis, David W. Fardo, Rachel Buckley, Timothy J. Hohman
doi: https://doi.org/10.1101/838847
Annah M. Moore
Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, TNVanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TNDepartment of Pharmacology, Vanderbilt University Medical Center, Nashville, TN
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Teresa J. Filshtein
Department of Epidemiology and Biostatistics, University of California, San Francisco, CA
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Logan Dumitrescu
Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, TNVanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN
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Amal Harrati
School of Medicine, Stanford University School of Medicine, Palo Alto, CA
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Fanny Elahi
Department of Neurology, Memory and Aging Center, University of California, San Francisco, CA
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Elizabeth C. Mormino
Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Palo Alto, CA
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Yuetiva Deming
Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI
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Brian W. Kunkle
John P. Hussman Institute for Human Genomics, University of Miami, Miami, FL
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Dan M. Mungas
UC Davis Alzheimer’s Disease Research Center, University of California, Davis, CA
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Trey Hedden
Icahn School of Medicine at Mount Sinai, New York City, NY
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Liana G. Apostolova
Department of Neurology, Indiana University School of Medicine, Indianapolis, IN
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Andrew J. Saykin
Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN
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  • ORCID record for Andrew J. Saykin
Danai Chasioti
Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN
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Qiongshi Lu
University of Wisconsin, Madison, Madison, WI
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Jessica Dennis
Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN
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Julia Sealock
Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN
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Lea K. Davis
Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN
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David W. Fardo
Department of Biostatistics and Sanders-Brown Center on Aging, University of Kentucky, Lexington, KY
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Rachel Buckley
Department of Neurology, Massachusetts General Hospital/Harvard Medical School, Boston, MA
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Timothy J. Hohman
Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, TNVanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN
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  • For correspondence: Timothy.J.Hohman@vumc.org
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Abstract

INTRODUCTION We developed a novel polygenic risk score (PRS) based on the A/T/N (amyloid plaques (A), phosphorylated tau tangles (T), and neurodegeneration (N)) framework and compared a PRS based on clinical AD diagnosis to assess which was a better predictor of cognitive decline.

METHODS We used summary statistics from genome wide association studies of cerebrospinal fluid amyloid-β (Aβ42) and phosphorylated-tau (ptau181), left hippocampal volume (LHIPV), and late-onset AD dementia to calculate PRS for 1181 participants in the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Individual PRS were averaged to generate a composite A/T/N PRS. We assessed the association of PRS with baseline and longitudinal cognitive composites of executive function and memory.

RESULTS The A/T/N PRS showed superior predictive performance on AD biomarkers and executive function decline compared to the clinical AD PRS.

DISCUSSION Results suggest that integration of genetic risk across AD biomarkers may improve prediction of disease progression.

Systematic Review Authors reviewed relevant literature using PubMed and Google Scholar. Key studies that generated and validated polygenic risk scores (PRS) for clinical and pathologic AD were cited. PRS scores have been increasingly used in the literature but clinical utility continues to be questioned.

Interpretation In the current research landscape concerning PRS clinical utility in the AD space, there is room for model improvement and our hypothesis was that a PRS with integrated risk for AD biomarkers could yield a better model for cognitive decline.

Future Directions This study serves as proof-of-concept that encourages future study of integrated PRS across disease markers and utility in taking an A/T/N (amyloidosis, tauopathy and neurodegeneration) focused approach to genetic risk for cognitive decline and AD.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
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Posted November 12, 2019.
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A/T/N polygenic risk score for cognitive decline in old age
Annah M. Moore, Teresa J. Filshtein, Logan Dumitrescu, Amal Harrati, Fanny Elahi, Elizabeth C. Mormino, Yuetiva Deming, Brian W. Kunkle, Dan M. Mungas, Trey Hedden, Liana G. Apostolova, Andrew J. Saykin, Danai Chasioti, Qiongshi Lu, Jessica Dennis, Julia Sealock, Lea K. Davis, David W. Fardo, Rachel Buckley, Timothy J. Hohman
bioRxiv 838847; doi: https://doi.org/10.1101/838847
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A/T/N polygenic risk score for cognitive decline in old age
Annah M. Moore, Teresa J. Filshtein, Logan Dumitrescu, Amal Harrati, Fanny Elahi, Elizabeth C. Mormino, Yuetiva Deming, Brian W. Kunkle, Dan M. Mungas, Trey Hedden, Liana G. Apostolova, Andrew J. Saykin, Danai Chasioti, Qiongshi Lu, Jessica Dennis, Julia Sealock, Lea K. Davis, David W. Fardo, Rachel Buckley, Timothy J. Hohman
bioRxiv 838847; doi: https://doi.org/10.1101/838847

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