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      The association of genetic variation in CACNA1C with resting-state functional connectivity in youth bipolar disorder

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          Abstract

          Background

          CACNA1C rs1006737 A allele, identified as a genetic risk variant for bipolar disorder (BD), is associated with anomalous functional connectivity in adults with and without BD. Studies have yet to investigate the association of CACNA1C rs1006737 with resting-state functional connectivity (rsFC) in youth BD.

          Methods

          Participants included 139 youth with BD-I, -II, or -not otherwise specified, ages 13–20 years, including 27 BD A-carriers, 41 BD non-carriers, 32 healthy controls (HC) A-carriers, and 39 HC non-carriers. Anterior cingulate cortex (ACC), amygdala, and orbitofrontal cortex (OFC) were examined as regions-of-interest in seed-to-voxel analyses. General linear models included main effects of diagnosis and rs1006737, and an interaction term, controlling for age, sex, and race.

          Results

          We observed a main effect of BD diagnosis on rsFC between the right amygdala and the right occipital pole ( p = 0.02), and a main effect of rs1006737 genotypes on rsFC between the right OFC and bilateral occipital cortex ( p < 0.001). Two significant BD diagnosis-by-CACNA1C rs1006737 interactions were also identified. The A allele was associated with positive rsFC between the right ACC and right amygdala in BD but negative rsFC in HC ( p = 0.01), and negative rsFC between the left OFC and left putamen in BD but positive rsFC in HC ( p = 0.01).

          Conclusion

          This study found that the rs1006737 A allele, identified as a genetic risk variant for BD in adults, was differentially associated with rsFC in youth with BD in regions relevant to emotion, executive function, and reward. Future task-based approaches are warranted to better understand brain connectivity in relation to CACNA1C in BD.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s40345-022-00281-5.

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          Most cited references53

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          PLINK: a tool set for whole-genome association and population-based linkage analyses.

          Whole-genome association studies (WGAS) bring new computational, as well as analytic, challenges to researchers. Many existing genetic-analysis tools are not designed to handle such large data sets in a convenient manner and do not necessarily exploit the new opportunities that whole-genome data bring. To address these issues, we developed PLINK, an open-source C/C++ WGAS tool set. With PLINK, large data sets comprising hundreds of thousands of markers genotyped for thousands of individuals can be rapidly manipulated and analyzed in their entirety. As well as providing tools to make the basic analytic steps computationally efficient, PLINK also supports some novel approaches to whole-genome data that take advantage of whole-genome coverage. We introduce PLINK and describe the five main domains of function: data management, summary statistics, population stratification, association analysis, and identity-by-descent estimation. In particular, we focus on the estimation and use of identity-by-state and identity-by-descent information in the context of population-based whole-genome studies. This information can be used to detect and correct for population stratification and to identify extended chromosomal segments that are shared identical by descent between very distantly related individuals. Analysis of the patterns of segmental sharing has the potential to map disease loci that contain multiple rare variants in a population-based linkage analysis.
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            Conn: a functional connectivity toolbox for correlated and anticorrelated brain networks.

            Resting state functional connectivity reveals intrinsic, spontaneous networks that elucidate the functional architecture of the human brain. However, valid statistical analysis used to identify such networks must address sources of noise in order to avoid possible confounds such as spurious correlations based on non-neuronal sources. We have developed a functional connectivity toolbox Conn ( www.nitrc.org/projects/conn ) that implements the component-based noise correction method (CompCor) strategy for physiological and other noise source reduction, additional removal of movement, and temporal covariates, temporal filtering and windowing of the residual blood oxygen level-dependent (BOLD) contrast signal, first-level estimation of multiple standard functional connectivity magnetic resonance imaging (fcMRI) measures, and second-level random-effect analysis for resting state as well as task-related data. Compared to methods that rely on global signal regression, the CompCor noise reduction method allows for interpretation of anticorrelations as there is no regression of the global signal. The toolbox implements fcMRI measures, such as estimation of seed-to-voxel and region of interest (ROI)-to-ROI functional correlations, as well as semipartial correlation and bivariate/multivariate regression analysis for multiple ROI sources, graph theoretical analysis, and novel voxel-to-voxel analysis of functional connectivity. We describe the methods implemented in the Conn toolbox for the analysis of fcMRI data, together with examples of use and interscan reliability estimates of all the implemented fcMRI measures. The results indicate that the CompCor method increases the sensitivity and selectivity of fcMRI analysis, and show a high degree of interscan reliability for many fcMRI measures.
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              Schedule for Affective Disorders and Schizophrenia for School-Age Children-Present and Lifetime Version (K-SADS-PL): initial reliability and validity data.

              To describe the psychometric properties of the Schedule for Affective Disorders and Schizophrenia for School-Age Children-Present and Lifetime version (K-SADS-PL) interview, which surveys additional disorders not assessed in prior K-SADS, contains improved probes and anchor points, includes diagnosis-specific impairment ratings, generates DSM-III-R and DSM-IV diagnoses, and divides symptoms surveyed into a screening interview and five diagnostic supplements. Subjects were 55 psychiatric outpatients and 11 normal controls (aged 7 through 17 years). Both parents and children were used as informants. Concurrent validity of the screen criteria and the K-SADS-PL diagnoses was assessed against standard self-report scales. Interrater (n = 15) and test-retest (n = 20) reliability data were also collected (mean retest interval: 18 days; range: 2 to 36 days). Rating scale data support the concurrent validity of screens and K-SADS-PL diagnoses. Interrater agreement in scoring screens and diagnoses was high (range: 93% to 100%). Test-retest reliability kappa coefficients were in the excellent range for present and/or lifetime diagnoses of major depression, any bipolar, generalized anxiety, conduct, and oppositional defiant disorder (.77 to 1.00) and in the good range for present diagnoses of posttraumatic stress disorder and attention-deficit hyperactivity disorder (.63 to .67). Results suggest the K-SADS-PL generates reliable and valid child psychiatric diagnoses.
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                Author and article information

                Contributors
                benjamin.goldstein@camh.ca
                Journal
                Int J Bipolar Disord
                Int J Bipolar Disord
                International Journal of Bipolar Disorders
                Springer Berlin Heidelberg (Berlin/Heidelberg )
                2194-7511
                13 January 2023
                13 January 2023
                2023
                : 11
                : 3
                Affiliations
                [1 ]GRID grid.155956.b, ISNI 0000 0000 8793 5925, Centre for Youth Bipolar Disorder, , Centre for Addiction and Mental Health, ; Toronto, ON Canada
                [2 ]GRID grid.17063.33, ISNI 0000 0001 2157 2938, Department of Pharmacology & Toxicology, , University of Toronto, ; Toronto, ON Canada
                [3 ]GRID grid.155956.b, ISNI 0000 0000 8793 5925, Tanenbaum Centre for Pharmacogenetics, Psychiatric Neurogenetics Section, Campbell Family Mental Health Research Institute, , Centre for Addiction and Mental Health, ; Toronto, ON Canada
                [4 ]GRID grid.17063.33, ISNI 0000 0001 2157 2938, Department of Psychiatry, , University of Toronto, ; Toronto, Canada
                [5 ]GRID grid.17063.33, ISNI 0000 0001 2157 2938, Heart and Stroke Foundation, Canadian Partnership for Stroke Recovery, , Sunnybrook Research Institute, ; Toronto, ON Canada
                [6 ]GRID grid.17063.33, ISNI 0000 0001 2157 2938, Department of Medical Biophysics, , University of Toronto, ; Toronto, ON Canada
                [7 ]GRID grid.17063.33, ISNI 0000 0001 2157 2938, Hurvitz Brain Sciences Program, , Sunnybrook Research Institute, ; Toronto, ON Canada
                Article
                281
                10.1186/s40345-022-00281-5
                9839925
                36637564
                4a2cbb41-13d0-4028-a963-0895f8b59fc4
                © The Author(s) 2022

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 24 May 2022
                : 13 December 2022
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100000024, Canadian Institutes of Health Research;
                Award ID: MOP 136947
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100012120, Ontario Mental Health Foundation;
                Categories
                Research
                Custom metadata
                © The Author(s) 2023

                bipolar disorder,youth,fmri,resting-state functional connectivity,cacna1c rs1006737,seed-to-voxel analysis,anterior cingulate cortex,orbitofrontal cortex,amygdala

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