Discovering schizophrenia endophenotypes in randomly ascertained pedigrees

David C. Glahn, Jeff T. Williams, D. Reese McKay, Emma E. Knowles, Emma Sprooten, Samuel R. Mathias, Joanne E. Curran, Jack W. Kent, Melanie A. Carless, Harald H H Göring, Thomas D. Dyer, Mary D. Woolsey, Anderson M. Winkler, Rene L Olvera, Peter Kochunov, Peter T Fox, Ravi Duggirala, Laura Almasy, John Blangero

Research output: Contribution to journalArticle

17 Citations (Scopus)

Abstract

Background Although case-control approaches are beginning to disentangle schizophrenia's complex polygenic burden, other methods will likely be necessary to fully identify and characterize risk genes. Endophenotypes, traits genetically correlated with an illness, can help characterize the impact of risk genes by providing genetically relevant traits that are more tractable than the behavioral symptoms that classify mental illness. Here, we present an analytic approach for discovering and empirically validating endophenotypes in extended pedigrees with very few affected individuals. Our approach indexes each family member's risk as a function of shared genetic kinship with an affected individual, often referred to as the coefficient of relatedness. To demonstrate the utility of this approach, we search for neurocognitive and neuroanatomic endophenotypes for schizophrenia in large unselected multigenerational pedigrees. Methods A fixed-effects test within the variance component framework was performed on neurocognitive and cortical surface area traits in 1606 Mexican-American individuals from large, randomly ascertained extended pedigrees who participated in the Genetics of Brain Structure and Function study. As affecteds were excluded from analyses, results were not influenced by disease state or medication usage. Results Despite having sampled just 6 individuals with schizophrenia, our sample provided 233 individuals at various levels of genetic risk for the disorder. We identified three neurocognitive measures (digit-symbol substitution, facial memory, and emotion recognition) and six medial temporal and prefrontal cortical surfaces associated with liability for schizophrenia. Conclusions With our novel analytic approach, one can discover and rank endophenotypes for schizophrenia, or any heritable disease, in randomly ascertained pedigrees.

Original languageEnglish (US)
Pages (from-to)75-83
Number of pages9
JournalBiological Psychiatry
Volume77
Issue number1
DOIs
StatePublished - Jan 1 2015

Fingerprint

Endophenotypes
Pedigree
Schizophrenia
Behavioral Symptoms
Inborn Genetic Diseases
Genetic Structures
Genes
Emotions
Brain

Keywords

  • Coefficient of Relatedness
  • Cognition
  • Cortical Surface Area
  • Endophenotype
  • Family Study
  • Schizophrenia

ASJC Scopus subject areas

  • Biological Psychiatry

Cite this

Glahn, D. C., Williams, J. T., McKay, D. R., Knowles, E. E., Sprooten, E., Mathias, S. R., ... Blangero, J. (2015). Discovering schizophrenia endophenotypes in randomly ascertained pedigrees. Biological Psychiatry, 77(1), 75-83. https://doi.org/10.1016/j.biopsych.2014.06.027

Discovering schizophrenia endophenotypes in randomly ascertained pedigrees. / Glahn, David C.; Williams, Jeff T.; McKay, D. Reese; Knowles, Emma E.; Sprooten, Emma; Mathias, Samuel R.; Curran, Joanne E.; Kent, Jack W.; Carless, Melanie A.; Göring, Harald H H; Dyer, Thomas D.; Woolsey, Mary D.; Winkler, Anderson M.; Olvera, Rene L; Kochunov, Peter; Fox, Peter T; Duggirala, Ravi; Almasy, Laura; Blangero, John.

In: Biological Psychiatry, Vol. 77, No. 1, 01.01.2015, p. 75-83.

Research output: Contribution to journalArticle

Glahn, DC, Williams, JT, McKay, DR, Knowles, EE, Sprooten, E, Mathias, SR, Curran, JE, Kent, JW, Carless, MA, Göring, HHH, Dyer, TD, Woolsey, MD, Winkler, AM, Olvera, RL, Kochunov, P, Fox, PT, Duggirala, R, Almasy, L & Blangero, J 2015, 'Discovering schizophrenia endophenotypes in randomly ascertained pedigrees', Biological Psychiatry, vol. 77, no. 1, pp. 75-83. https://doi.org/10.1016/j.biopsych.2014.06.027
Glahn DC, Williams JT, McKay DR, Knowles EE, Sprooten E, Mathias SR et al. Discovering schizophrenia endophenotypes in randomly ascertained pedigrees. Biological Psychiatry. 2015 Jan 1;77(1):75-83. https://doi.org/10.1016/j.biopsych.2014.06.027
Glahn, David C. ; Williams, Jeff T. ; McKay, D. Reese ; Knowles, Emma E. ; Sprooten, Emma ; Mathias, Samuel R. ; Curran, Joanne E. ; Kent, Jack W. ; Carless, Melanie A. ; Göring, Harald H H ; Dyer, Thomas D. ; Woolsey, Mary D. ; Winkler, Anderson M. ; Olvera, Rene L ; Kochunov, Peter ; Fox, Peter T ; Duggirala, Ravi ; Almasy, Laura ; Blangero, John. / Discovering schizophrenia endophenotypes in randomly ascertained pedigrees. In: Biological Psychiatry. 2015 ; Vol. 77, No. 1. pp. 75-83.
@article{ad72b30c09864fcf84cddb6e9a1a6b8b,
title = "Discovering schizophrenia endophenotypes in randomly ascertained pedigrees",
abstract = "Background Although case-control approaches are beginning to disentangle schizophrenia's complex polygenic burden, other methods will likely be necessary to fully identify and characterize risk genes. Endophenotypes, traits genetically correlated with an illness, can help characterize the impact of risk genes by providing genetically relevant traits that are more tractable than the behavioral symptoms that classify mental illness. Here, we present an analytic approach for discovering and empirically validating endophenotypes in extended pedigrees with very few affected individuals. Our approach indexes each family member's risk as a function of shared genetic kinship with an affected individual, often referred to as the coefficient of relatedness. To demonstrate the utility of this approach, we search for neurocognitive and neuroanatomic endophenotypes for schizophrenia in large unselected multigenerational pedigrees. Methods A fixed-effects test within the variance component framework was performed on neurocognitive and cortical surface area traits in 1606 Mexican-American individuals from large, randomly ascertained extended pedigrees who participated in the Genetics of Brain Structure and Function study. As affecteds were excluded from analyses, results were not influenced by disease state or medication usage. Results Despite having sampled just 6 individuals with schizophrenia, our sample provided 233 individuals at various levels of genetic risk for the disorder. We identified three neurocognitive measures (digit-symbol substitution, facial memory, and emotion recognition) and six medial temporal and prefrontal cortical surfaces associated with liability for schizophrenia. Conclusions With our novel analytic approach, one can discover and rank endophenotypes for schizophrenia, or any heritable disease, in randomly ascertained pedigrees.",
keywords = "Coefficient of Relatedness, Cognition, Cortical Surface Area, Endophenotype, Family Study, Schizophrenia",
author = "Glahn, {David C.} and Williams, {Jeff T.} and McKay, {D. Reese} and Knowles, {Emma E.} and Emma Sprooten and Mathias, {Samuel R.} and Curran, {Joanne E.} and Kent, {Jack W.} and Carless, {Melanie A.} and G{\"o}ring, {Harald H H} and Dyer, {Thomas D.} and Woolsey, {Mary D.} and Winkler, {Anderson M.} and Olvera, {Rene L} and Peter Kochunov and Fox, {Peter T} and Ravi Duggirala and Laura Almasy and John Blangero",
year = "2015",
month = "1",
day = "1",
doi = "10.1016/j.biopsych.2014.06.027",
language = "English (US)",
volume = "77",
pages = "75--83",
journal = "Biological Psychiatry",
issn = "0006-3223",
publisher = "Elsevier USA",
number = "1",

}

TY - JOUR

T1 - Discovering schizophrenia endophenotypes in randomly ascertained pedigrees

AU - Glahn, David C.

AU - Williams, Jeff T.

AU - McKay, D. Reese

AU - Knowles, Emma E.

AU - Sprooten, Emma

AU - Mathias, Samuel R.

AU - Curran, Joanne E.

AU - Kent, Jack W.

AU - Carless, Melanie A.

AU - Göring, Harald H H

AU - Dyer, Thomas D.

AU - Woolsey, Mary D.

AU - Winkler, Anderson M.

AU - Olvera, Rene L

AU - Kochunov, Peter

AU - Fox, Peter T

AU - Duggirala, Ravi

AU - Almasy, Laura

AU - Blangero, John

PY - 2015/1/1

Y1 - 2015/1/1

N2 - Background Although case-control approaches are beginning to disentangle schizophrenia's complex polygenic burden, other methods will likely be necessary to fully identify and characterize risk genes. Endophenotypes, traits genetically correlated with an illness, can help characterize the impact of risk genes by providing genetically relevant traits that are more tractable than the behavioral symptoms that classify mental illness. Here, we present an analytic approach for discovering and empirically validating endophenotypes in extended pedigrees with very few affected individuals. Our approach indexes each family member's risk as a function of shared genetic kinship with an affected individual, often referred to as the coefficient of relatedness. To demonstrate the utility of this approach, we search for neurocognitive and neuroanatomic endophenotypes for schizophrenia in large unselected multigenerational pedigrees. Methods A fixed-effects test within the variance component framework was performed on neurocognitive and cortical surface area traits in 1606 Mexican-American individuals from large, randomly ascertained extended pedigrees who participated in the Genetics of Brain Structure and Function study. As affecteds were excluded from analyses, results were not influenced by disease state or medication usage. Results Despite having sampled just 6 individuals with schizophrenia, our sample provided 233 individuals at various levels of genetic risk for the disorder. We identified three neurocognitive measures (digit-symbol substitution, facial memory, and emotion recognition) and six medial temporal and prefrontal cortical surfaces associated with liability for schizophrenia. Conclusions With our novel analytic approach, one can discover and rank endophenotypes for schizophrenia, or any heritable disease, in randomly ascertained pedigrees.

AB - Background Although case-control approaches are beginning to disentangle schizophrenia's complex polygenic burden, other methods will likely be necessary to fully identify and characterize risk genes. Endophenotypes, traits genetically correlated with an illness, can help characterize the impact of risk genes by providing genetically relevant traits that are more tractable than the behavioral symptoms that classify mental illness. Here, we present an analytic approach for discovering and empirically validating endophenotypes in extended pedigrees with very few affected individuals. Our approach indexes each family member's risk as a function of shared genetic kinship with an affected individual, often referred to as the coefficient of relatedness. To demonstrate the utility of this approach, we search for neurocognitive and neuroanatomic endophenotypes for schizophrenia in large unselected multigenerational pedigrees. Methods A fixed-effects test within the variance component framework was performed on neurocognitive and cortical surface area traits in 1606 Mexican-American individuals from large, randomly ascertained extended pedigrees who participated in the Genetics of Brain Structure and Function study. As affecteds were excluded from analyses, results were not influenced by disease state or medication usage. Results Despite having sampled just 6 individuals with schizophrenia, our sample provided 233 individuals at various levels of genetic risk for the disorder. We identified three neurocognitive measures (digit-symbol substitution, facial memory, and emotion recognition) and six medial temporal and prefrontal cortical surfaces associated with liability for schizophrenia. Conclusions With our novel analytic approach, one can discover and rank endophenotypes for schizophrenia, or any heritable disease, in randomly ascertained pedigrees.

KW - Coefficient of Relatedness

KW - Cognition

KW - Cortical Surface Area

KW - Endophenotype

KW - Family Study

KW - Schizophrenia

UR - http://www.scopus.com/inward/record.url?scp=84920658472&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84920658472&partnerID=8YFLogxK

U2 - 10.1016/j.biopsych.2014.06.027

DO - 10.1016/j.biopsych.2014.06.027

M3 - Article

VL - 77

SP - 75

EP - 83

JO - Biological Psychiatry

JF - Biological Psychiatry

SN - 0006-3223

IS - 1

ER -