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Genetic analysis of activity, brain and behavioral associations in extended families with heavy genetic loading for bipolar disorder
- Annabel Vreeker, Scott C. Fears, Susan K. Service, Lucia Pagani, Joseph S. Takahashi, Carmen Araya, Xinia Araya, Julio Bejarano, Maria C. Lopez, Gabriel Montoya, Claudia Patricia Montoya, Terri M. Teshiba, Javier Escobar, Rita M. Cantor, Carlos López-Jaramillo, Gabriel Macaya, Julio Molina, Victor I. Reus, Chiara Sabatti, Roel A. Ophoff, Nelson B. Freimer, Carrie E. Bearden
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- Journal:
- Psychological Medicine / Volume 51 / Issue 3 / February 2021
- Published online by Cambridge University Press:
- 09 December 2019, pp. 494-502
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- Article
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Background
Disturbed sleep and activity are prominent features of bipolar disorder type I (BP-I). However, the relationship of sleep and activity characteristics to brain structure and behavior in euthymic BP-I patients and their non-BP-I relatives is unknown. Additionally, underlying genetic relationships between these traits have not been investigated.
MethodsRelationships between sleep and activity phenotypes, assessed using actigraphy, with structural neuroimaging (brain) and cognitive and temperament (behavior) phenotypes were investigated in 558 euthymic individuals from multi-generational pedigrees including at least one member with BP-I. Genetic correlations between actigraphy-brain and actigraphy-behavior associations were assessed, and bivariate linkage analysis was conducted for trait pairs with evidence of shared genetic influences.
ResultsMore physical activity and longer awake time were significantly associated with increased brain volumes and cortical thickness, better performance on neurocognitive measures of long-term memory and executive function, and less extreme scores on measures of temperament (impulsivity, cyclothymia). These associations did not differ between BP-I patients and their non-BP-I relatives. For nine activity-brain or activity-behavior pairs there was evidence for shared genetic influence (genetic correlations); of these pairs, a suggestive bivariate quantitative trait locus on chromosome 7 for wake duration and verbal working memory was identified.
ConclusionsOur findings indicate that increased physical activity and more adequate sleep are associated with increased brain size, better cognitive function and more stable temperament in BP-I patients and their non-BP-I relatives. Additionally, we found evidence for pleiotropy of several actigraphy-behavior and actigraphy-brain phenotypes, suggesting a shared genetic basis for these traits.
9 - Multivariate Linear Models for GWAS
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- By Chiara Sabatti, Stanford University
- Edited by Kim-Anh Do, Zhaohui Steve Qin, Emory University, Atlanta, Marina Vannucci, Rice University, Houston
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- Book:
- Advances in Statistical Bioinformatics
- Published online:
- 05 June 2013
- Print publication:
- 10 June 2013, pp 188-207
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- Chapter
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Summary
Introduction
Research in genetics in the first decade of the twenty-first century has been dominated by the attempt to characterize common variation in the human genome and its impact on complex phenotypes. The decade opened with the announcement of the completion of the first draft(s) of the human genome (Lander et al., 2001; Venter et al., 2001), which provided one reference sequence. An international effort (The HapMap, 2003), analogous to the one that had facilitated this first achievement, was then devoted to the characterization of common variants in different human populations (originally focusing on trios to represent European, Yoruba, Beijing Chinese, and Japanese populations). By 2007, commercial enterprises had developed technologies that allowed hundreds of thousands of single nucleotide polymorphisms (SNPs) to be genotyped in thousands of individuals at reasonable costs: genome-wide association studies (GWAS), first described in Risch and Merikangas (1996), became possible and popular. These studies aim to identify genetic loci that influence complex phenotypes: that is, traits whose genetic underpinning is not ascribable to one, or even a handful, of genes. When very many loci influence a trait, it is reasonable to assume that the effect of any of these might be quite modest, requiring a large sample size for detection. GWAS, which recruit individuals from a population, without need to study relatives, represent a convincing design in this context, and indeed, they have become the method of choice for many groups.