TY - JOUR
T1 - Can genetic analysis of putative blood Alzheimer's disease biomarkers lead to identification of susceptibility loci?
AU - Barber, Robert C.
AU - Phillips, Nicole R.
AU - Tilson, Jeffrey L.
AU - Huebinger, Ryan M.
AU - Shewale, Shantanu J.
AU - Koenig, Jessica L.
AU - Mitchel, Jeffrey S.
AU - O'Bryant, Sid E.
AU - Waring, Stephen C.
AU - Diaz-Arrastia, Ramon
AU - Chasse, Scott
AU - Wilhelmsen, Kirk C.
N1 - Funding Information:
SJS, NRP, JSM acknowledge NIA Training grant T32 AG020494. RMH acknowledges a grant from NIGMS P30AG12300-20. KCW acknowledges grants 5R01DA030976, 5U01HG006487, 1U19HD077632, 1U01HG007437, 5P01-DK058335, 5U24 AA020024 and 1UL1TR001111.
Funding Information:
The replication data set was funded by the Alzheimer′s Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904; RC2 AG036535). ADNI is also funded by Department of Defense (award number W81XWH-12-2-0012). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: Alzheimer’s Association; Alzheimer’s Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc.; Biogen Idec Inc.; Bristol-Myers Squibb Company; 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.; Medpace, Inc.; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Neurotrack Technologies; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Synarc Inc.; and Takeda Pharmaceutical Company. 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 National Institutes of Health ( http://www.fnih.org ). The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer′s Disease Cooperative Study at the University of California, San Diego. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of California, Los Angeles. Investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. ADNI principal investigators and executive committee include; Michael W. Weiner MD, Paul Aisen MD, Ronald Petersen MD PhD, Clifford R. Jack, Jr. MD, William Jagust MD, John Q. Trojanowski MD PhD, Arthur W. Toga PhD, Laurel Beckett PhD, Robert C. Green MD MPH, Andrew J. Saykin PsyD, John Morris MD, Leslie M. Shaw.
Funding Information:
This study was made possible by the Texas Alzheimer’s Research and Care Consortium (TARCC), which is funded by the state of Texas through the Texas Council on Alzheimer’s Disease and Related Disorders.
PY - 2015/12/1
Y1 - 2015/12/1
N2 - Although 24 Alzheimer's disease (AD) risk loci have been reliably identified, a large portion of the predicted heritability for AD remains unexplained. It is expected that additional loci of small effect will be identified with an increased sample size. However, the cost of a significant increase in Case-Control sample size is prohibitive. The current study tests whether exploring the genetic basis of endophenotypes, in this case based on putative blood biomarkers for AD, can accelerate the identification of susceptibility loci using modest sample sizes. Each endophenotype was used as the outcome variable in an independent GWAS. Endophenotypes were based on circulating concentrations of proteins that contributed significantly to a published blood-based predictive algorithm for AD. Endophenotypes included Monocyte Chemoattractant Protein 1 (MCP1), Vascular Cell Adhesion Molecule 1 (VCAM1), Pancreatic Polypeptide (PP), Beta2 Microglobulin (B2M), Factor VII (F7), Adiponectin (ADN) and Tenascin C (TN-C). Across the seven endophenotypes, 47 SNPs were associated with outcome with a p-value -1x10-7. Each signal was further characterized with respect to known genetic loci associated with AD. Signals for several endophenotypes were observed in the vicinity of CR1, MS4A6A/MS4A4E, PICALM, CLU, and PTK2B. The strongest signal was observed in association with Factor VII levels and was located within the F7 gene. Additional signals were observed in MAP3K13, ZNF320, ATP9B and TREM1. Conditional regression analyses suggested that the SNPs contributed to variation in protein concentration independent of AD status. The identification of two putatively novel AD loci (in the Factor VII and ATP9B genes), which have not been located in previous studies despite massive sample sizes, highlights the benefits of an endophenotypic approach for resolving the genetic basis for complex diseases. The coincidence of several of the endophenotypic signals with known AD loci may point to novel genetic interactions and should be further investigated.
AB - Although 24 Alzheimer's disease (AD) risk loci have been reliably identified, a large portion of the predicted heritability for AD remains unexplained. It is expected that additional loci of small effect will be identified with an increased sample size. However, the cost of a significant increase in Case-Control sample size is prohibitive. The current study tests whether exploring the genetic basis of endophenotypes, in this case based on putative blood biomarkers for AD, can accelerate the identification of susceptibility loci using modest sample sizes. Each endophenotype was used as the outcome variable in an independent GWAS. Endophenotypes were based on circulating concentrations of proteins that contributed significantly to a published blood-based predictive algorithm for AD. Endophenotypes included Monocyte Chemoattractant Protein 1 (MCP1), Vascular Cell Adhesion Molecule 1 (VCAM1), Pancreatic Polypeptide (PP), Beta2 Microglobulin (B2M), Factor VII (F7), Adiponectin (ADN) and Tenascin C (TN-C). Across the seven endophenotypes, 47 SNPs were associated with outcome with a p-value -1x10-7. Each signal was further characterized with respect to known genetic loci associated with AD. Signals for several endophenotypes were observed in the vicinity of CR1, MS4A6A/MS4A4E, PICALM, CLU, and PTK2B. The strongest signal was observed in association with Factor VII levels and was located within the F7 gene. Additional signals were observed in MAP3K13, ZNF320, ATP9B and TREM1. Conditional regression analyses suggested that the SNPs contributed to variation in protein concentration independent of AD status. The identification of two putatively novel AD loci (in the Factor VII and ATP9B genes), which have not been located in previous studies despite massive sample sizes, highlights the benefits of an endophenotypic approach for resolving the genetic basis for complex diseases. The coincidence of several of the endophenotypic signals with known AD loci may point to novel genetic interactions and should be further investigated.
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U2 - 10.1371/journal.pone.0142360
DO - 10.1371/journal.pone.0142360
M3 - Article
C2 - 26625115
AN - SCOPUS:84961361382
SN - 1932-6203
VL - 10
JO - PLoS One
JF - PLoS One
IS - 12
M1 - e0142360
ER -