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Original Investigation |

Multisystem Component Phenotypes of Bipolar Disorder for Genetic Investigations of Extended Pedigrees

Scott C. Fears, MD, PhD1; Susan K. Service, MS1; Barbara Kremeyer, PhD2; Carmen Araya, Lic3; Xinia Araya, Lic3; Julio Bejarano, MS3; Margarita Ramirez, Lic3; Gabriel Castrillón, BSc4; Juliana Gomez-Franco, MD5; Maria C. Lopez, MSW5; Gabriel Montoya, MD, MSc5; Patricia Montoya, MA5; Ileana Aldana, MPH1; Terri M. Teshiba, BA1; Zvart Abaryan, BSc1; Noor B. Al-Sharif, BSc1; Marissa Ericson, PhD1; Maria Jalbrzikowski, PhD1; Jurjen J. Luykx, MD, PhD1,6; Linda Navarro, MS1; Todd A. Tishler, PhD1; Lori Altshuler, MD1; George Bartzokis, MD1; Javier Escobar, MD7; David C. Glahn, PhD8,9; Jorge Ospina-Duque, MD5; Neil Risch, PhD10; Andrés Ruiz-Linares, MD, PhD11; Paul M. Thompson, PhD1; Rita M. Cantor, PhD1; Carlos Lopez-Jaramillo, MD, PhD5,12; Gabriel Macaya, PhD3; Julio Molina, MD1,13; Victor I. Reus, MD14; Chiara Sabatti, PhD15; Nelson B. Freimer, MD1; Carrie E. Bearden, PhD1
[+] Author Affiliations
1Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles
2Wellcome Trust Sanger Institute, Hinxton, England
3Cell and Molecular Biology Research, Universidad de Costa Rica, San Pedro de Montes de Oca, Costa Rica
4Instituto de Alta Tecnología Médica de Antioquia, Medellín, Colombia
5Grupo de Investigación en Psiquiatría, Departamento de Psiquiatría, Facultad de Medicina, Universidad de Antioquia, Medellín, Colombia
6Department of Psychiatry, ZNA Stuivenberg, Antwerp, Belgium
7Department of Psychiatry and Family Medicine, University of Medicine and Dentistry of New Jersey–Robert Wood Johnson Medical School, New Brunswick
8Department of Psychiatry, Yale University, New Haven, Connecticut
9Olin Neuropsychiatric Research Center, Institute of Living, Hartford Hospital, Hartford, Connecticut
10Institute for Human Genetics, University of California, San Francisco
11Department of Genetics, Evolution, and Environment, University College London, London, England
12Mood Disorders Program, Hospital San Vicente Fundacion, Medellín, Colombia
13BioCiencias Lab, Guatemala, Guatemala
14Department of Psychiatry, University of California, San Francisco
15Department of Health Research and Policy, Stanford University, Stanford, California
JAMA Psychiatry. 2014;71(4):375-387. doi:10.1001/jamapsychiatry.2013.4100.
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Importance  Genetic factors contribute to risk for bipolar disorder (BP), but its pathogenesis remains poorly understood. A focus on measuring multisystem quantitative traits that may be components of BP psychopathology may enable genetic dissection of this complex disorder, and investigation of extended pedigrees from genetically isolated populations may facilitate the detection of specific genetic variants that affect BP as well as its component phenotypes.

Objective  To identify quantitative neurocognitive, temperament-related, and neuroanatomical phenotypes that appear heritable and associated with severe BP (bipolar I disorder [BP-I]) and therefore suitable for genetic linkage and association studies aimed at identifying variants contributing to BP-I risk.

Design, Setting, and Participants  Multigenerational pedigree study in 2 closely related, genetically isolated populations: the Central Valley of Costa Rica and Antioquia, Colombia. A total of 738 individuals, all from Central Valley of Costa Rica and Antioquia pedigrees, participated; among them, 181 have BP-I.

Main Outcomes and Measures  Familial aggregation (heritability) and association with BP-I of 169 quantitative neurocognitive, temperament, magnetic resonance imaging, and diffusion tensor imaging phenotypes.

Results  Of 169 phenotypes investigated, 126 (75%) were significantly heritable and 53 (31%) were associated with BP-I. About one-quarter of the phenotypes, including measures from each phenotype domain, were both heritable and associated with BP-I. Neuroimaging phenotypes, particularly cortical thickness in prefrontal and temporal regions as well as volume and microstructural integrity of the corpus callosum, represented the most promising candidate traits for genetic mapping related to BP based on strong heritability and association with disease. Analyses of phenotypic and genetic covariation identified substantial correlations among the traits, at least some of which share a common underlying genetic architecture.

Conclusions and Relevance  To our knowledge, this is the most extensive investigation of BP-relevant component phenotypes to date. Our results identify brain and behavioral quantitative traits that appear to be genetically influenced and show a pattern of BP-I association within families that is consistent with expectations from case-control studies. Together, these phenotypes provide a basis for identifying loci contributing to BP-I risk and for genetic dissection of the disorder.

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Figure 1.
Summary of Analyses of Heritability and Association With Bipolar I Disorder

The results of analyses of heritability and of association with bipolar I disorder (BP-I) are shown as 2 histograms stacked on top of each other. Inner histogram purple bars show the magnitude of the heritability estimate for each component phenotype, and the blue box next to the trait name at the outer edge of the plot indicates estimates that passed the significance threshold. Outer histogram shows the magnitude of the estimated regression coefficient for the BP-I association test. Orange bars show positive coefficients representing traits that are higher in participants with BP-I compared with family members without BP-I. Green bars show negative coefficients representing traits that are lower in participants with BP-I. A red box at the outer edge of the circle indicates traits that exceeded the significance threshold for association with BP-I. AIM indicates Abstraction, Inhibition, and Working Memory Task; BART, Balloon Analogue Risk Task; CVLT, California Verbal Learning Test; IP-CPT, Identical Pairs Continuous Performance Test; MRI, magnetic resonance imaging; PCET, Penn Conditional Exclusion Test; SCAP, Spatial Capacity Delayed Response Test; SST, Stop Signal Task; TEMPS, Temperament Evaluation of Memphis, Pisa, Paris, and San Diego; TONI, Test of Nonverbal Intelligence; VWM, verbal working memory; WASI, Wechsler Abbreviated Scale of Intelligence; and WMS, Wechsler Memory Scale.

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Figure 2.
Structural Neuroimaging Phenotypes

A, Results of the heritability and bipolar I disorder (BP-I) association analyses of volumetric magnetic resonance imaging phenotypes. The 3 representative T1-weighted coronal magnetic resonance images depict the results of the Freesurfer segmentation overlaid as colored masks selected to better distinguish the anatomy. Mask colors are not related to the results. The colors of the text labels indicate structures that showed significant evidence of familial aggregation (blue) and structures that were both heritable and associated with BP-I (magenta). B, Cortical thickness phenotypes and results of the heritability and BP-I association analysis for cortical gray matter thickness. The medial surface is rotated upward by 60° to provide a view of the ventral surface.

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Figure 3.
Network Graph of Correlations Among Phenotypes

Network representations of pairwise phenotypic correlations (A) and genetic correlations (B). All trait pairs were included in the phenotypic correlation analysis, and only pairs in which both traits were heritable were included in the genetic correlation analysis. Nodes are colored according to their assigned subdomain (see Subdomain column in eTable 1 in Supplement). Circular nodes indicate significantly heritable phenotypes; square nodes, nonheritable phenotypes. Traits that were significantly associated with bipolar I disorder have a red border. Nodes are connected with an edge when the hypothesis of correlation = 0 was rejected using false discovery rate–controlled thresholds. Numbers correspond to plot identification numbers for phenotypes detailed in eTable 1 in the Supplement. MRI indicates magnetic resonance imaging. B, Examples of genetically correlated traits mentioned in the text include the hippocampus (67), amygdala (56), and surface area of the pars opercularis (97) as well as Stroop Color-Word Interference Test errors (34) with surface area measures from the inferior parietal (87) and rostral middle frontal (107) regions of interest.

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