Genetical genomics of Th1 and Th2 immune response in a baboon model of atherosclerosis risk factors

A. Vinson; J. E. Curran; M. P. Johnson; T. D. Dyer; E. K. Moses; J. Blangero; L. A. Cox; J. Rogers; L. M. Havill; J. L. VandeBerg; M. C. Mahaney

doi:10.1016/j.atherosclerosis.2011.06.015

Genetical genomics of Th1 and Th2 immune response in a baboon model of atherosclerosis risk factors

A. Vinson, J. E. Curran, M. P. Johnson, T. D. Dyer, E. K. Moses, J. Blangero, L. A. Cox, J. Rogers, L. M. Havill, J. L. VandeBerg, M. C. Mahaney

Research output: Contribution to journal › Article › peer-review

9 Scopus citations

Abstract

CD4 ⁺ T-cells mediate inflammation in atherosclerosis, but additive genetic effects on associated pathways of Th1 and Th2 immune response have not been described. We sought to characterize heritability, pleiotropy, and QTL effects on the expression of genes implicated in Th1 and Th2 immune response in a baboon model of risk factors for atherosclerosis. Methods: We employed a maximum likelihood-based variance decomposition approach to estimate additive genetic effects on transcript levels generated from a gene expression profile of lymphocytes in 499 pedigreed baboons maintained on a basal diet. Transcript levels for 57 genes implicated in Th1 and Th2 immune response were selected for analysis based on significant heritability in this profile. Multipoint whole genome scans were conducted on heritable transcript levels to localize QTLs influencing these measures. To evaluate pleiotropic effects on transcript levels, we estimated genetic and phenotypic correlations among transcript measures, and assessed their correspondence using a Mantel test. Network analysis using GeneGo's MetaCore™ software was conducted to characterize known interaction among coded proteins. Results: Heritabilities for candidate gene transcript levels ranged from 0.092-0.786 (median h ²=0.278, P=4.72×10 ^-4). Linkage analyses yielded significant evidence (LOD≥2.73) for 14 eQTLs (LOD score range 2.76-14.87, genome-wide P=4.9×10 ^-2-1.03×10 ^-14). Estimates of genetic correlation supported shared additive genetic effects incorporating all 57 transcripts (null hypothesis of ρ _G=0 rejected at FDR≤0.05 for 522 of 1596 estimates), and accounted for most of the observed phenotypic correlation among transcripts (Mantel test, r _[ρ _P], _[ρ _G]=0.781, P<0.0001). Network analysis revealed direct interactions among 54 of the 57 coded proteins. Conclusions: We conclude that major genetic effects influence expression levels of multiple genes implicated in Th1 and Th2 immune response. Additionally, we find that expression levels of these candidate genes are characterized by extensive pleiotropy, consistent with known interaction among their coded proteins, many of which are independently associated with atherosclerosis.

Original language	English (US)
Pages (from-to)	387-394
Number of pages	8
Journal	Atherosclerosis
Volume	217
Issue number	2
DOIs	https://doi.org/10.1016/j.atherosclerosis.2011.06.015
State	Published - Aug 2011
Externally published	Yes

Keywords

Atherosclerosis
Baboon
Gene expression
Inflammation
QTL
Th1
Th2

ASJC Scopus subject areas

Cardiology and Cardiovascular Medicine

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10.1016/j.atherosclerosis.2011.06.015

Cite this

@article{143f8ba10a8846aabffa4063b1f9a1f8,

title = "Genetical genomics of Th1 and Th2 immune response in a baboon model of atherosclerosis risk factors",

abstract = "CD4 + T-cells mediate inflammation in atherosclerosis, but additive genetic effects on associated pathways of Th1 and Th2 immune response have not been described. We sought to characterize heritability, pleiotropy, and QTL effects on the expression of genes implicated in Th1 and Th2 immune response in a baboon model of risk factors for atherosclerosis. Methods: We employed a maximum likelihood-based variance decomposition approach to estimate additive genetic effects on transcript levels generated from a gene expression profile of lymphocytes in 499 pedigreed baboons maintained on a basal diet. Transcript levels for 57 genes implicated in Th1 and Th2 immune response were selected for analysis based on significant heritability in this profile. Multipoint whole genome scans were conducted on heritable transcript levels to localize QTLs influencing these measures. To evaluate pleiotropic effects on transcript levels, we estimated genetic and phenotypic correlations among transcript measures, and assessed their correspondence using a Mantel test. Network analysis using GeneGo's MetaCore{\texttrademark} software was conducted to characterize known interaction among coded proteins. Results: Heritabilities for candidate gene transcript levels ranged from 0.092-0.786 (median h 2=0.278, P=4.72×10 -4). Linkage analyses yielded significant evidence (LOD≥2.73) for 14 eQTLs (LOD score range 2.76-14.87, genome-wide P=4.9×10 -2-1.03×10 -14). Estimates of genetic correlation supported shared additive genetic effects incorporating all 57 transcripts (null hypothesis of ρ G=0 rejected at FDR≤0.05 for 522 of 1596 estimates), and accounted for most of the observed phenotypic correlation among transcripts (Mantel test, r [ρ P], [ρ G]=0.781, P<0.0001). Network analysis revealed direct interactions among 54 of the 57 coded proteins. Conclusions: We conclude that major genetic effects influence expression levels of multiple genes implicated in Th1 and Th2 immune response. Additionally, we find that expression levels of these candidate genes are characterized by extensive pleiotropy, consistent with known interaction among their coded proteins, many of which are independently associated with atherosclerosis.",

keywords = "Atherosclerosis, Baboon, Gene expression, Inflammation, QTL, Th1, Th2",

author = "A. Vinson and Curran, {J. E.} and Johnson, {M. P.} and Dyer, {T. D.} and Moses, {E. K.} and J. Blangero and Cox, {L. A.} and J. Rogers and Havill, {L. M.} and VandeBerg, {J. L.} and Mahaney, {M. C.}",

note = "Funding Information: This study was made possible by research grants from the National Institutes of Health ( P01 HL028972 , R01 HL068922 , R01 RR008781 ); base grants from the National Center of Research Resources (NCRR) to the Oregon National Primate Research Center (ONPRC; P51 RR000163 ) and to the Southwest National Primate Research Center (SNPRC; P51 RR013986 ); and was conducted in facilities constructed with support from NCRR Research Facilities Improvement Program grants ( C06 RR014578 , C06 RR13556 , C06 RR15456 , C06 RR017515 ). Development and implementation of computational methods used in this study were supported by NIH grant MH059490 , and the high-speed distributed computing facilities used for this work at the AT&T Genetics Computing Center, Texas Biomed, were supported in part by a gift from the AT&T Foundation . The platform for lymphocyte expression profiling was supported by a generous donation from the Azar/Shepperd families , with additional funds from ChemGenex Pharmaceuticals, Ltd., Australia . ",

year = "2011",

month = aug,

doi = "10.1016/j.atherosclerosis.2011.06.015",

language = "English (US)",

volume = "217",

pages = "387--394",

journal = "Atherosclerosis",

issn = "0021-9150",

publisher = "Elsevier Ireland Ltd",

number = "2",

}

TY - JOUR

T1 - Genetical genomics of Th1 and Th2 immune response in a baboon model of atherosclerosis risk factors

AU - Vinson, A.

AU - Curran, J. E.

AU - Johnson, M. P.

AU - Dyer, T. D.

AU - Moses, E. K.

AU - Blangero, J.

AU - Cox, L. A.

AU - Rogers, J.

AU - Havill, L. M.

AU - VandeBerg, J. L.

AU - Mahaney, M. C.

N1 - Funding Information: This study was made possible by research grants from the National Institutes of Health ( P01 HL028972 , R01 HL068922 , R01 RR008781 ); base grants from the National Center of Research Resources (NCRR) to the Oregon National Primate Research Center (ONPRC; P51 RR000163 ) and to the Southwest National Primate Research Center (SNPRC; P51 RR013986 ); and was conducted in facilities constructed with support from NCRR Research Facilities Improvement Program grants ( C06 RR014578 , C06 RR13556 , C06 RR15456 , C06 RR017515 ). Development and implementation of computational methods used in this study were supported by NIH grant MH059490 , and the high-speed distributed computing facilities used for this work at the AT&T Genetics Computing Center, Texas Biomed, were supported in part by a gift from the AT&T Foundation . The platform for lymphocyte expression profiling was supported by a generous donation from the Azar/Shepperd families , with additional funds from ChemGenex Pharmaceuticals, Ltd., Australia .

PY - 2011/8

Y1 - 2011/8

N2 - CD4 + T-cells mediate inflammation in atherosclerosis, but additive genetic effects on associated pathways of Th1 and Th2 immune response have not been described. We sought to characterize heritability, pleiotropy, and QTL effects on the expression of genes implicated in Th1 and Th2 immune response in a baboon model of risk factors for atherosclerosis. Methods: We employed a maximum likelihood-based variance decomposition approach to estimate additive genetic effects on transcript levels generated from a gene expression profile of lymphocytes in 499 pedigreed baboons maintained on a basal diet. Transcript levels for 57 genes implicated in Th1 and Th2 immune response were selected for analysis based on significant heritability in this profile. Multipoint whole genome scans were conducted on heritable transcript levels to localize QTLs influencing these measures. To evaluate pleiotropic effects on transcript levels, we estimated genetic and phenotypic correlations among transcript measures, and assessed their correspondence using a Mantel test. Network analysis using GeneGo's MetaCore™ software was conducted to characterize known interaction among coded proteins. Results: Heritabilities for candidate gene transcript levels ranged from 0.092-0.786 (median h 2=0.278, P=4.72×10 -4). Linkage analyses yielded significant evidence (LOD≥2.73) for 14 eQTLs (LOD score range 2.76-14.87, genome-wide P=4.9×10 -2-1.03×10 -14). Estimates of genetic correlation supported shared additive genetic effects incorporating all 57 transcripts (null hypothesis of ρ G=0 rejected at FDR≤0.05 for 522 of 1596 estimates), and accounted for most of the observed phenotypic correlation among transcripts (Mantel test, r [ρ P], [ρ G]=0.781, P<0.0001). Network analysis revealed direct interactions among 54 of the 57 coded proteins. Conclusions: We conclude that major genetic effects influence expression levels of multiple genes implicated in Th1 and Th2 immune response. Additionally, we find that expression levels of these candidate genes are characterized by extensive pleiotropy, consistent with known interaction among their coded proteins, many of which are independently associated with atherosclerosis.

AB - CD4 + T-cells mediate inflammation in atherosclerosis, but additive genetic effects on associated pathways of Th1 and Th2 immune response have not been described. We sought to characterize heritability, pleiotropy, and QTL effects on the expression of genes implicated in Th1 and Th2 immune response in a baboon model of risk factors for atherosclerosis. Methods: We employed a maximum likelihood-based variance decomposition approach to estimate additive genetic effects on transcript levels generated from a gene expression profile of lymphocytes in 499 pedigreed baboons maintained on a basal diet. Transcript levels for 57 genes implicated in Th1 and Th2 immune response were selected for analysis based on significant heritability in this profile. Multipoint whole genome scans were conducted on heritable transcript levels to localize QTLs influencing these measures. To evaluate pleiotropic effects on transcript levels, we estimated genetic and phenotypic correlations among transcript measures, and assessed their correspondence using a Mantel test. Network analysis using GeneGo's MetaCore™ software was conducted to characterize known interaction among coded proteins. Results: Heritabilities for candidate gene transcript levels ranged from 0.092-0.786 (median h 2=0.278, P=4.72×10 -4). Linkage analyses yielded significant evidence (LOD≥2.73) for 14 eQTLs (LOD score range 2.76-14.87, genome-wide P=4.9×10 -2-1.03×10 -14). Estimates of genetic correlation supported shared additive genetic effects incorporating all 57 transcripts (null hypothesis of ρ G=0 rejected at FDR≤0.05 for 522 of 1596 estimates), and accounted for most of the observed phenotypic correlation among transcripts (Mantel test, r [ρ P], [ρ G]=0.781, P<0.0001). Network analysis revealed direct interactions among 54 of the 57 coded proteins. Conclusions: We conclude that major genetic effects influence expression levels of multiple genes implicated in Th1 and Th2 immune response. Additionally, we find that expression levels of these candidate genes are characterized by extensive pleiotropy, consistent with known interaction among their coded proteins, many of which are independently associated with atherosclerosis.

KW - Atherosclerosis

KW - Baboon

KW - Gene expression

KW - Inflammation

KW - QTL

KW - Th1

KW - Th2

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DO - 10.1016/j.atherosclerosis.2011.06.015

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C2 - 21762917

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SN - 0021-9150

VL - 217

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EP - 394

JO - Atherosclerosis

JF - Atherosclerosis

IS - 2

ER -

Genetical genomics of Th1 and Th2 immune response in a baboon model of atherosclerosis risk factors

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