TY - JOUR
T1 - Association of blood-based transcriptional risk scores with biomarkers for Alzheimer disease
AU - AddNeuroMed consortium and the Alzheimer's Disease Neuroimaging Initiative
AU - Park, Young Ho
AU - Hodges, Angela
AU - Simmons, Andrew
AU - Lovestone, Simon
AU - Weiner, Michael W.
AU - Kim, Sang Yun
AU - Saykin, Andrew J.
AU - Nho, Kwangsik
AU - Aisen, Paul
AU - Petersen, Ronald
AU - Jack, Clifford R.
AU - Jagust, William
AU - Trojanowki, John Q.
AU - Toga, Arthur W.
AU - Beckett, Laurel
AU - Green, Robert C.
AU - Saykin, Andrew J.
AU - Morris, John
AU - Shaw, Leslie M.
AU - Khachaturian, Zaven
AU - Sorensen, Greg
AU - Carrillo, Maria
AU - Kuller, Lew
AU - Raichle, Marc
AU - Paul, Steven
AU - Davies, Peter
AU - Fillit, Howard
AU - Hefti, Franz
AU - Holtzman, David
AU - Marcel Mesulam, M.
AU - Potter, William
AU - Snyder, Peter
AU - Hendrix, James
AU - Vasanthakumar, Aparna
AU - Montine, Tom
AU - Rafii, Michael
AU - Chow, Tiffany
AU - Raman, Rema
AU - Jimenez, Gustavo
AU - Donohue, Michael
AU - Gessert, Devon
AU - Harless, Kelly
AU - Salazar, Jennifer
AU - Cabrera, Yuliana
AU - Walter, Sarah
AU - Hergesheimer, Lindsey
AU - Beckett, Laurel
AU - Harvey, Danielle
AU - Donohue, Michael
AU - Bernstein, Matthew
N1 - Funding Information:
This work was supported by the National Research Foundation of Korea grant funded by the Korean government (Ministry of Science and ICT) (No. 2020R1C1C1013718). Data collection and sharing for this project was funded by the Alzheimer's Disease Neuroimaging Initiative (NIH Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH-12-2-0012). The ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: AbbVie, Alzheimer's Association, Alzheimer's Drug Discovery Foundation, Araclon Biotech, BioClinica, Inc., Biogen, Bristol-Myers Squibb Company, CereSpir, Inc., Cogstate, Eisai Inc., Elan Pharmaceuticals, Inc., Eli Lilly and Company, EuroImmun, F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc., Fujirebio, GE Healthcare, IXICO Ltd., Janssen Alzheimer Immunotherapy Research & Development, LLC., Johnson & Johnson Pharmaceutical Research & Development LLC., Lumosity, Lundbeck, Merck & Co., Inc., Meso Scale Diagnostics, LLC., NeuroRx Research, Neuro-track Technologies, Novartis Pharmaceuticals Corporation, Pfizer Inc., Piramal Imaging, Servier, Takeda Pharmaceutical Company, and Transition Therapeutics. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the NIH (fnih.org). The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer's Therapeutic Research Institute at the University of Southern California. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California. The collection and analysis of AddNeuroMed samples was supported by InnoMed (Innovative Medicines in Europe), an Integrated Project funded by the European Union of the Sixth Framework program priority FP6-2004-LIFESCIHEALTH-5, the Alzheimer's Research Trust, the John and Lucille van Geest Foundation and the NIHR Biomedical Research Centre for Mental Health at the South London and Maudsley NHS Foundation Trust and [Institute of Psychiatry] Kings College London. Additional support for data analysis was provided by NLM R01 LM012535, NIA R03 AG054936, NIA R01 AG19771, NIA P30 AG10133, NLM R01 LM011360, DOD W81XWH-14-2-0151, NIGMS P50GM115318, NCATS UL1 TR001108, NIA K01 AG049050, the Alzheimer's Association, the Indiana Clinical and Translational Science Institute, and the IU Health-IU School of Medicine Strategic Neuroscience Research Initiative.
Funding Information:
The Article Processing Charge was funded by the NIH.
Publisher Copyright:
Copyright © 2020 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.
PY - 2020/12
Y1 - 2020/12
N2 - Objective To determine whether transcriptional risk scores (TRSs), a summation of polarized expression levels of functional genes, reflect the risk of Alzheimer disease (AD). Methods Blood transcriptome data were from Caucasian participants, which included AD, mild cognitive impairment, and cognitively normal controls (CN) in the Alzheimer's Disease Neuroimaging Initiative (ADNI, n = 661) and AddNeuroMed (n = 674) cohorts. To calculate TRSs, we selected functional genes that were expressed under the control of the AD risk loci and were identified as being responsible for AD by using Bayesian colocalization and mendelian randomization methods. Regression was used to investigate the association of the TRS with diagnosis (AD vs CN) and MRI biomarkers (entorhinal thickness and hippocampal volume). Regression was also used to evaluate whether expression of each functional gene was associated with AD diagnosis. Results The TRS was significantly associated with AD diagnosis, hippocampal volume, and entorhinal cortical thickness in the ADNI. The association of the TRS with AD diagnosis and entorhinal cortical thickness was also replicated in AddNeuroMed. Among functional genes identified to calculate the TRS, CD33 and PILRA were significantly upregulated, and TRAPPC6A was significantly downregulated in patients with AD compared with CN, all of which were identified in the ADNI and replicated in AddNeuroMed. Conclusions The blood-based TRS is significantly associated with AD diagnosis and neuroimaging biomarkers. In blood, CD33 and PILRA were known to be associated with uptake of β-amyloid and herpes simplex virus 1 infection, respectively, both of which may play a role in the pathogenesis of AD. Classification of evidence The study is rated Class III because of the case control design and the risk of spectrum bias.
AB - Objective To determine whether transcriptional risk scores (TRSs), a summation of polarized expression levels of functional genes, reflect the risk of Alzheimer disease (AD). Methods Blood transcriptome data were from Caucasian participants, which included AD, mild cognitive impairment, and cognitively normal controls (CN) in the Alzheimer's Disease Neuroimaging Initiative (ADNI, n = 661) and AddNeuroMed (n = 674) cohorts. To calculate TRSs, we selected functional genes that were expressed under the control of the AD risk loci and were identified as being responsible for AD by using Bayesian colocalization and mendelian randomization methods. Regression was used to investigate the association of the TRS with diagnosis (AD vs CN) and MRI biomarkers (entorhinal thickness and hippocampal volume). Regression was also used to evaluate whether expression of each functional gene was associated with AD diagnosis. Results The TRS was significantly associated with AD diagnosis, hippocampal volume, and entorhinal cortical thickness in the ADNI. The association of the TRS with AD diagnosis and entorhinal cortical thickness was also replicated in AddNeuroMed. Among functional genes identified to calculate the TRS, CD33 and PILRA were significantly upregulated, and TRAPPC6A was significantly downregulated in patients with AD compared with CN, all of which were identified in the ADNI and replicated in AddNeuroMed. Conclusions The blood-based TRS is significantly associated with AD diagnosis and neuroimaging biomarkers. In blood, CD33 and PILRA were known to be associated with uptake of β-amyloid and herpes simplex virus 1 infection, respectively, both of which may play a role in the pathogenesis of AD. Classification of evidence The study is rated Class III because of the case control design and the risk of spectrum bias.
UR - http://www.scopus.com/inward/record.url?scp=85096974482&partnerID=8YFLogxK
U2 - 10.1212/NXG.0000000000000517
DO - 10.1212/NXG.0000000000000517
M3 - Article
C2 - 33134515
AN - SCOPUS:85096974482
SN - 2376-7839
VL - 6
JO - Neurology: Genetics
JF - Neurology: Genetics
IS - 6
M1 - e517
ER -