Exome Array Analysis of Early-Onset Ischemic Stroke

Thomas Jaworek; Kathleen A. Ryan; Brady J. Gaynor; Patrick F. McArdle; Oscar C. Stine; Timothy D. Oconnor; Haley Lopez; Hugo J. Aparicio; Yan Gao; Xiaochen Lin; Megan L. Groves; Matthew L. Flaherty; Simin Liu; Qiong Yang; James Wilson; Sudha Seshadri; Steven J. Kittner; Braxton D. Mitchell; Huichun Xu; John W. Cole

doi:10.1161/STROKEAHA.120.031357

Exome Array Analysis of Early-Onset Ischemic Stroke

Thomas Jaworek, Kathleen A. Ryan, Brady J. Gaynor, Patrick F. McArdle, Oscar C. Stine, Timothy D. Oconnor, Haley Lopez, Hugo J. Aparicio, Yan Gao, Xiaochen Lin, Megan L. Groves, Matthew L. Flaherty, Simin Liu, Qiong Yang, James Wilson, Sudha Seshadri, Steven J. Kittner, Braxton D. Mitchell, Huichun Xu, John W. Cole

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

Abstract

Background and Purpose: The genetic contribution to ischemic stroke may include rare-or low-frequency variants of high-penetrance and large-effect sizes. Analyses focusing on early-onset disease, an extreme-phenotype, and on the exome, the protein-coding portion of genes, may increase the likelihood of identifying such rare functional variants. To evaluate this hypothesis, we implemented a 2-stage discovery and replication design, and then addressed whether the identified variants also associated with older-onset disease. Methods: Discovery was performed in UMD-GEOS Study (University of Maryland-Genetics of Early-Onset Stroke), a biracial population-based study of first-ever ischemic stroke cases 15 to 49 years of age (n=723) and nonstroke controls (n=726). All participants had prior GWAS (Genome Wide Association Study) and underwent Illumina exome-chip genotyping. Logistic-regression was performed to test single-variant associations with all-ischemic stroke and TOAST (Trial of ORG 10172 in Acute Stroke Treatment) subtypes in Whites and Blacks. Population level results were combined using meta-Analysis. Gene-based aggregation testing and meta-Analysis were performed using seqMeta. Covariates included age and gender, and principal-components for population structure. Pathway analyses were performed across all nominally associated genes for each stroke outcome. Replication was attempted through lookups in a previously reported meta-Analysis of early-onset stroke and a large-scale stroke genetics study consisting of primarily older-onset cases. Results: Gene burden tests identified a significant association with NAT10 in small-vessel stroke (P=3.79×10^-⁶). Pathway analysis of the top 517 genes (P<0.05) from the gene-based analysis of small-vessel stroke identified several signaling and metabolism-related pathways related to neurotransmitter, neurodevelopmental notch-signaling, and lipid/glucose metabolism. While no individual SNPs reached chip-wide significance (P<2.05×10^-7), several were near, including an intronic variant in LEXM (rs7549251; P=4.08×10^-⁷) and an exonic variant in TRAPPC11 (rs67383011; P=5.19×10^-⁶). Conclusions: Exome-based analysis in the setting of early-onset stroke is a promising strategy for identifying novel genetic risk variants, loci, and pathways.

Original language	English (US)
Pages (from-to)	3356-3360
Number of pages	5
Journal	Stroke
DOIs	https://doi.org/10.1161/STROKEAHA.120.031357
State	Accepted/In press - 2020
Externally published	Yes

Keywords

early-onset
exome
exons
glucose
penetrance
single nucleotide polymorphism
stroke

ASJC Scopus subject areas

Clinical Neurology
Cardiology and Cardiovascular Medicine
Advanced and Specialized Nursing

Access to Document

10.1161/STROKEAHA.120.031357

Cite this

Jaworek, T., Ryan, K. A., Gaynor, B. J., McArdle, P. F., Stine, O. C., Oconnor, T. D., Lopez, H., Aparicio, H. J., Gao, Y., Lin, X., Groves, M. L., Flaherty, M. L., Liu, S., Yang, Q., Wilson, J., Seshadri, S., Kittner, S. J., Mitchell, B. D., Xu, H., & Cole, J. W. (Accepted/In press). Exome Array Analysis of Early-Onset Ischemic Stroke. Stroke, 3356-3360. https://doi.org/10.1161/STROKEAHA.120.031357

Exome Array Analysis of Early-Onset Ischemic Stroke. / Jaworek, Thomas; Ryan, Kathleen A.; Gaynor, Brady J.; McArdle, Patrick F.; Stine, Oscar C.; Oconnor, Timothy D.; Lopez, Haley; Aparicio, Hugo J.; Gao, Yan; Lin, Xiaochen; Groves, Megan L.; Flaherty, Matthew L.; Liu, Simin; Yang, Qiong; Wilson, James; Seshadri, Sudha; Kittner, Steven J.; Mitchell, Braxton D.; Xu, Huichun; Cole, John W.

In: Stroke, 2020, p. 3356-3360.

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

Jaworek, Thomas ; Ryan, Kathleen A. ; Gaynor, Brady J. ; McArdle, Patrick F. ; Stine, Oscar C. ; Oconnor, Timothy D. ; Lopez, Haley ; Aparicio, Hugo J. ; Gao, Yan ; Lin, Xiaochen ; Groves, Megan L. ; Flaherty, Matthew L. ; Liu, Simin ; Yang, Qiong ; Wilson, James ; Seshadri, Sudha ; Kittner, Steven J. ; Mitchell, Braxton D. ; Xu, Huichun ; Cole, John W. / Exome Array Analysis of Early-Onset Ischemic Stroke. In: Stroke. 2020 ; pp. 3356-3360.

@article{3e61e083743f492e9e2e0f61a3bc4127,

title = "Exome Array Analysis of Early-Onset Ischemic Stroke",

abstract = "Background and Purpose: The genetic contribution to ischemic stroke may include rare-or low-frequency variants of high-penetrance and large-effect sizes. Analyses focusing on early-onset disease, an extreme-phenotype, and on the exome, the protein-coding portion of genes, may increase the likelihood of identifying such rare functional variants. To evaluate this hypothesis, we implemented a 2-stage discovery and replication design, and then addressed whether the identified variants also associated with older-onset disease. Methods: Discovery was performed in UMD-GEOS Study (University of Maryland-Genetics of Early-Onset Stroke), a biracial population-based study of first-ever ischemic stroke cases 15 to 49 years of age (n=723) and nonstroke controls (n=726). All participants had prior GWAS (Genome Wide Association Study) and underwent Illumina exome-chip genotyping. Logistic-regression was performed to test single-variant associations with all-ischemic stroke and TOAST (Trial of ORG 10172 in Acute Stroke Treatment) subtypes in Whites and Blacks. Population level results were combined using meta-Analysis. Gene-based aggregation testing and meta-Analysis were performed using seqMeta. Covariates included age and gender, and principal-components for population structure. Pathway analyses were performed across all nominally associated genes for each stroke outcome. Replication was attempted through lookups in a previously reported meta-Analysis of early-onset stroke and a large-scale stroke genetics study consisting of primarily older-onset cases. Results: Gene burden tests identified a significant association with NAT10 in small-vessel stroke (P=3.79×10-6). Pathway analysis of the top 517 genes (P<0.05) from the gene-based analysis of small-vessel stroke identified several signaling and metabolism-related pathways related to neurotransmitter, neurodevelopmental notch-signaling, and lipid/glucose metabolism. While no individual SNPs reached chip-wide significance (P<2.05×10-7), several were near, including an intronic variant in LEXM (rs7549251; P=4.08×10-7) and an exonic variant in TRAPPC11 (rs67383011; P=5.19×10-6). Conclusions: Exome-based analysis in the setting of early-onset stroke is a promising strategy for identifying novel genetic risk variants, loci, and pathways.",

keywords = "early-onset, exome, exons, glucose, penetrance, single nucleotide polymorphism, stroke",

author = "Thomas Jaworek and Ryan, {Kathleen A.} and Gaynor, {Brady J.} and McArdle, {Patrick F.} and Stine, {Oscar C.} and Oconnor, {Timothy D.} and Haley Lopez and Aparicio, {Hugo J.} and Yan Gao and Xiaochen Lin and Groves, {Megan L.} and Flaherty, {Matthew L.} and Simin Liu and Qiong Yang and James Wilson and Sudha Seshadri and Kittner, {Steven J.} and Mitchell, {Braxton D.} and Huichun Xu and Cole, {John W.}",

year = "2020",

doi = "10.1161/STROKEAHA.120.031357",

language = "English (US)",

pages = "3356--3360",

journal = "Stroke",

issn = "0039-2499",

publisher = "Lippincott Williams and Wilkins",

}

TY - JOUR

T1 - Exome Array Analysis of Early-Onset Ischemic Stroke

AU - Jaworek, Thomas

AU - Ryan, Kathleen A.

AU - Gaynor, Brady J.

AU - McArdle, Patrick F.

AU - Stine, Oscar C.

AU - Oconnor, Timothy D.

AU - Lopez, Haley

AU - Aparicio, Hugo J.

AU - Gao, Yan

AU - Lin, Xiaochen

AU - Groves, Megan L.

AU - Flaherty, Matthew L.

AU - Liu, Simin

AU - Yang, Qiong

AU - Wilson, James

AU - Seshadri, Sudha

AU - Kittner, Steven J.

AU - Mitchell, Braxton D.

AU - Xu, Huichun

AU - Cole, John W.

PY - 2020

Y1 - 2020

N2 - Background and Purpose: The genetic contribution to ischemic stroke may include rare-or low-frequency variants of high-penetrance and large-effect sizes. Analyses focusing on early-onset disease, an extreme-phenotype, and on the exome, the protein-coding portion of genes, may increase the likelihood of identifying such rare functional variants. To evaluate this hypothesis, we implemented a 2-stage discovery and replication design, and then addressed whether the identified variants also associated with older-onset disease. Methods: Discovery was performed in UMD-GEOS Study (University of Maryland-Genetics of Early-Onset Stroke), a biracial population-based study of first-ever ischemic stroke cases 15 to 49 years of age (n=723) and nonstroke controls (n=726). All participants had prior GWAS (Genome Wide Association Study) and underwent Illumina exome-chip genotyping. Logistic-regression was performed to test single-variant associations with all-ischemic stroke and TOAST (Trial of ORG 10172 in Acute Stroke Treatment) subtypes in Whites and Blacks. Population level results were combined using meta-Analysis. Gene-based aggregation testing and meta-Analysis were performed using seqMeta. Covariates included age and gender, and principal-components for population structure. Pathway analyses were performed across all nominally associated genes for each stroke outcome. Replication was attempted through lookups in a previously reported meta-Analysis of early-onset stroke and a large-scale stroke genetics study consisting of primarily older-onset cases. Results: Gene burden tests identified a significant association with NAT10 in small-vessel stroke (P=3.79×10-6). Pathway analysis of the top 517 genes (P<0.05) from the gene-based analysis of small-vessel stroke identified several signaling and metabolism-related pathways related to neurotransmitter, neurodevelopmental notch-signaling, and lipid/glucose metabolism. While no individual SNPs reached chip-wide significance (P<2.05×10-7), several were near, including an intronic variant in LEXM (rs7549251; P=4.08×10-7) and an exonic variant in TRAPPC11 (rs67383011; P=5.19×10-6). Conclusions: Exome-based analysis in the setting of early-onset stroke is a promising strategy for identifying novel genetic risk variants, loci, and pathways.

AB - Background and Purpose: The genetic contribution to ischemic stroke may include rare-or low-frequency variants of high-penetrance and large-effect sizes. Analyses focusing on early-onset disease, an extreme-phenotype, and on the exome, the protein-coding portion of genes, may increase the likelihood of identifying such rare functional variants. To evaluate this hypothesis, we implemented a 2-stage discovery and replication design, and then addressed whether the identified variants also associated with older-onset disease. Methods: Discovery was performed in UMD-GEOS Study (University of Maryland-Genetics of Early-Onset Stroke), a biracial population-based study of first-ever ischemic stroke cases 15 to 49 years of age (n=723) and nonstroke controls (n=726). All participants had prior GWAS (Genome Wide Association Study) and underwent Illumina exome-chip genotyping. Logistic-regression was performed to test single-variant associations with all-ischemic stroke and TOAST (Trial of ORG 10172 in Acute Stroke Treatment) subtypes in Whites and Blacks. Population level results were combined using meta-Analysis. Gene-based aggregation testing and meta-Analysis were performed using seqMeta. Covariates included age and gender, and principal-components for population structure. Pathway analyses were performed across all nominally associated genes for each stroke outcome. Replication was attempted through lookups in a previously reported meta-Analysis of early-onset stroke and a large-scale stroke genetics study consisting of primarily older-onset cases. Results: Gene burden tests identified a significant association with NAT10 in small-vessel stroke (P=3.79×10-6). Pathway analysis of the top 517 genes (P<0.05) from the gene-based analysis of small-vessel stroke identified several signaling and metabolism-related pathways related to neurotransmitter, neurodevelopmental notch-signaling, and lipid/glucose metabolism. While no individual SNPs reached chip-wide significance (P<2.05×10-7), several were near, including an intronic variant in LEXM (rs7549251; P=4.08×10-7) and an exonic variant in TRAPPC11 (rs67383011; P=5.19×10-6). Conclusions: Exome-based analysis in the setting of early-onset stroke is a promising strategy for identifying novel genetic risk variants, loci, and pathways.

KW - early-onset

KW - exome

KW - exons

KW - glucose

KW - penetrance

KW - single nucleotide polymorphism

KW - stroke

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EP - 3360

JO - Stroke

JF - Stroke

SN - 0039-2499

ER -

Exome Array Analysis of Early-Onset Ischemic Stroke

Abstract

Keywords

ASJC Scopus subject areas

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