Can genetic analysis of putative blood Alzheimer's disease biomarkers lead to identification of susceptibility loci?

Robert C. Barber, Nicole R. Phillips, Jeffrey L. Tilson, Ryan M. Huebinger, Shantanu J. Shewale, Jessica L. Koenig, Jeffrey S. Mitchel, Sid E. O'Bryant, Stephen C. Waring, Ramon Diaz-Arrastia, Scott Chasse, Kirk C. Wilhelmsen

Research output: Contribution to journalArticle

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Abstract

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.

Original languageEnglish
Article numbere0142360
JournalPLoS ONE
Volume10
Issue number12
DOIs
StatePublished - 1 Dec 2015

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Hematologic Diseases
Biomarkers
Alzheimer disease
Endophenotypes
genetic techniques and protocols
biomarkers
Alzheimer Disease
Blood
loci
blood
Sample Size
Factor VII
Single Nucleotide Polymorphism
pancreatic polypeptide
Genes
Tenascin
Pancreatic Polypeptide
sampling
adiponectin
Genetic Loci

Cite this

Barber, Robert C. ; Phillips, Nicole R. ; Tilson, Jeffrey L. ; Huebinger, Ryan M. ; Shewale, Shantanu J. ; Koenig, Jessica L. ; Mitchel, Jeffrey S. ; O'Bryant, Sid E. ; Waring, Stephen C. ; Diaz-Arrastia, Ramon ; Chasse, Scott ; Wilhelmsen, Kirk C. / Can genetic analysis of putative blood Alzheimer's disease biomarkers lead to identification of susceptibility loci?. In: PLoS ONE. 2015 ; Vol. 10, No. 12.
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title = "Can genetic analysis of putative blood Alzheimer's disease biomarkers lead to identification of susceptibility loci?",
abstract = "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.",
author = "Barber, {Robert C.} and Phillips, {Nicole R.} and Tilson, {Jeffrey L.} and Huebinger, {Ryan M.} and Shewale, {Shantanu J.} and Koenig, {Jessica L.} and Mitchel, {Jeffrey S.} and O'Bryant, {Sid E.} and Waring, {Stephen C.} and Ramon Diaz-Arrastia and Scott Chasse and Wilhelmsen, {Kirk C.}",
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Barber, RC, Phillips, NR, Tilson, JL, Huebinger, RM, Shewale, SJ, Koenig, JL, Mitchel, JS, O'Bryant, SE, Waring, SC, Diaz-Arrastia, R, Chasse, S & Wilhelmsen, KC 2015, 'Can genetic analysis of putative blood Alzheimer's disease biomarkers lead to identification of susceptibility loci?', PLoS ONE, vol. 10, no. 12, e0142360. https://doi.org/10.1371/journal.pone.0142360

Can genetic analysis of putative blood Alzheimer's disease biomarkers lead to identification of susceptibility loci? / Barber, Robert C.; Phillips, Nicole R.; Tilson, Jeffrey L.; Huebinger, Ryan M.; Shewale, Shantanu J.; Koenig, Jessica L.; Mitchel, Jeffrey S.; O'Bryant, Sid E.; Waring, Stephen C.; Diaz-Arrastia, Ramon; Chasse, Scott; Wilhelmsen, Kirk C.

In: PLoS ONE, Vol. 10, No. 12, e0142360, 01.12.2015.

Research output: Contribution to journalArticle

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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.

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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.

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