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Biol Psychiatry. 2015 Jan 1;77(1):75-83. doi: 10.1016/j.biopsych.2014.06.027. Epub 2014 Jul 21.

Discovering schizophrenia endophenotypes in randomly ascertained pedigrees.

Author information

1
Department of Psychiatry, Yale University School of Medicine, New Haven; Olin Neuropsychiatry Research Center, Institute of Living, Hartford Hospital, Hartford, Connecticut. Electronic address: david.glahn@yale.edu.
2
Department of Genetics, Texas Biomedical Research Institute, San Antonio, Texas.
3
Department of Psychiatry, Yale University School of Medicine, New Haven; Olin Neuropsychiatry Research Center, Institute of Living, Hartford Hospital, Hartford, Connecticut.
4
Research Imaging Institute, University of Texas Health Science Center San Antonio, San Antonio, Texas.
5
Centre for Functional MRI of the Brain, University of Oxford, Oxford, United Kingdom.
6
Department of Psychiatry, University of Texas Health Science Center San Antonio, San Antonio, Texas.
7
Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland.
8
Research Imaging Institute, University of Texas Health Science Center San Antonio, San Antonio, Texas; State Key Laboratory for Brain and Cognitive Sciences, University of Hong Kong.

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

PMID:
25168609
PMCID:
PMC4261014
DOI:
10.1016/j.biopsych.2014.06.027
[Indexed for MEDLINE]
Free PMC Article

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