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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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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.
Whole blood transcriptome analysis in bipolar disorder reveals strong lithium effect
- Catharine E. Krebs, Anil P.S. Ori, Annabel Vreeker, Timothy Wu, Rita M. Cantor, Marco P. M. Boks, Rene S. Kahn, Loes M. Olde Loohuis, Roel A. Ophoff
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- Journal:
- Psychological Medicine / Volume 50 / Issue 15 / November 2020
- Published online by Cambridge University Press:
- 07 October 2019, pp. 2575-2586
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Background
Bipolar disorder (BD) is a highly heritable mood disorder with complex genetic architecture and poorly understood etiology. Previous transcriptomic BD studies have had inconsistent findings due to issues such as small sample sizes and difficulty in adequately accounting for confounders like medication use.
MethodsWe performed a differential expression analysis in a well-characterized BD case-control sample (Nsubjects = 480) by RNA sequencing of whole blood. We further performed co-expression network analysis, functional enrichment, and cell type decomposition, and integrated differentially expressed genes with genetic risk.
ResultsWhile we observed widespread differential gene expression patterns between affected and unaffected individuals, these effects were largely linked to lithium treatment at the time of blood draw (FDR < 0.05, Ngenes = 976) rather than BD diagnosis itself (FDR < 0.05, Ngenes = 6). These lithium-associated genes were enriched for cell signaling and immune response functional annotations, among others, and were associated with neutrophil cell-type proportions, which were elevated in lithium users. Neither genes with altered expression in cases nor in lithium users were enriched for BD, schizophrenia, and depression genetic risk based on information from genome-wide association studies, nor was gene expression associated with polygenic risk scores for BD.
ConclusionsThese findings suggest that BD is associated with minimal changes in whole blood gene expression independent of medication use but emphasize the importance of accounting for medication use and cell type heterogeneity in psychiatric transcriptomic studies. The results of this study add to mounting evidence of lithium's cell signaling and immune-related mechanisms.
A Multivariate Genetic Analysis of Ridge Count Data From the Offspring of Monozygotic Twins
- Rita M. Cantor
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- Journal:
- Acta geneticae medicae et gemellologiae: twin research / Volume 32 / Issue 3-4 / July 1983
- Published online by Cambridge University Press:
- 01 August 2014, pp. 161-207
- Print publication:
- July 1983
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Inheritance patterns of digital ridge counts have been analyzed using multivariate statistical methods and data from the offspring of half-sib twin kinships. Prior studies found the univariate measure total ridge count to be highly heritable and the counts on individual fingers to be somewhat less heritable, and exploratory factor analytic studies indicated that at least two, and possibly three, independent genetic influences are responsible for this ten variable multivariate trait.
Two statistical methods have been employed to elucidate the factors controlling ridge count development on all ten fingers. An exploratory method developed by Bock and Vandenberg [4] has been applied to the among and between mean square matrices from a multivariate nested analysis of variance on thirty balanced male twin kinships. A principal component analysis on the resulting matrix of pure genetic effects has revealed two substantial genetic factors. One strongly influences the counts on all ten fingers, with the largest loadings on the three central fingers of each hand, while the other has an impact on the thumbs and fifth fingers. For both factors the loadings on homologous fingers are nearly equal. This exploratory procedure is wasteful of the data that is available in half-sib twin kinships, however.
Confirmatory factor analyses, employing the LISREL IV program, have been conducted on all available ridge count data from the offspring of forty-eight unbalanced male twin kinships and fiftynine unbalanced female twin kinships. Nested analyses of variance performed on sex-adjusted data yielded five 10 × 10 variance-covariance matrices containing 275 unique statistics for the estimation of genetic and environmental parameters and the testing of hypotheses.
A series of ten genetic and environmental hypothetical models for ridge count development, each more complex than the previous one, have been tested. They include a simple environmental model, an additive genetic and environmental model proposed by Holt [16], a full additive genetic model including five separate finger factors, two laterality factors and a general genetic factor, and seven models augmenting this full additive genetic model with factors for maternal epistatic and general environmental effects. The most complete model, which includes eight additive (one general, two laterality, and five finger) as well as maternal, epistatic, and general environmental factors cannot be rejected at a .05 level of significance. This model accounts for 99% of the variance that cannot be accounted for by a simple environmental model, and 95% of the variance unaccounted for by Holt's model. It suggests that while a strong genetic factor influences the ridge counts on all ten fingers, there are other factors affecting the counts on the homologous fingers separately as well as different factors affecting the counts on the left and right hands. In addition to these additive effects, influences due to the maternal environment common to all pregnancies of the mother, and those due to the unique environment of each pregnancy of the mother, and those due to the interaction of genes at separate loci have also been detected.
Results of the Bock and Vandenberg analysis are concordant with those obtained by the LISREL program. While the former only requires the availability of standard statistical packages, it is wasteful of data from the half-sib families. The latter, on the other hand, while it requires the use of a specific program, LISREL or its equivalent, uses all half-sibship data and allows one to test genetic and environmental hypotheses as well as conduct exploratory factor analyses.