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Shang CY, Lin HY, Gau SSF. Effects of the dopamine transporter gene on striatal functional connectivity in youths with attention-deficit/hyperactivity disorder. Psychol Med 2021; 51:835-845. [PMID: 31907092 DOI: 10.1017/s0033291719003830] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
BACKGROUND The dopamine transporter gene (DAT1), striatal network dysfunction, and visual memory deficits have been consistently reported to be associated with attention-deficit/hyperactivity disorder (ADHD). This study aimed to examine the effects of the DAT1 rs27048 (C)/rs429699 (T) haplotype on striatal functional connectivity and visual memory performance in youths with ADHD. METHOD After excluding those who had excessive head motion, a total of 96 drug-naïve youths with ADHD and 114 typically developing (TD) youths were assessed with the resting-state functional magnetic resonance imaging and the delayed matching to sample (DMS) task for visual memory. We examined the effects of ADHD, DAT1 CT haplotype, and the ADHD × CT haplotype interaction on the functional connectivity of five striatal seeds. We also correlated visual memory performance with the functional connectivity of striatal subregions, which showed significant diagnosis × genotype interactions. RESULTS Compared with TD youths, ADHD youths showed significant hypoconnectivity of the left dorsal caudate (DC) with bilateral sensorimotor clusters. Significant diagnosis × genotype interactions were found in the connectivity between the left DC and the right sensorimotor cluster, and between the right DC and the left dorsolateral prefrontal/bilateral anterior cingulate clusters. Furthermore, the connectivity of the left DC showing significant diagnosis × genotype interactions was associated with DMS performance in youths with ADHD who carried the DAT1 CT haplotype. CONCLUSIONS A novel gene-brain-behavior association between the left DC functional connectivity and visual memory performance in ADHD youths with the DAT1 rs27048 (C)/rs429699 (T) haplotype suggests a differential effect of DAT1 genotype altering specific brain function causing neuropsychological dysfunction in ADHD.
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Affiliation(s)
- Chi-Yung Shang
- Department of Psychiatry, National Taiwan University Hospital and College of Medicine, Taipei, Taiwan
| | - Hsiang-Yuan Lin
- Department of Psychiatry, National Taiwan University Hospital and College of Medicine, Taipei, Taiwan
| | - Susan Shur-Fen Gau
- Department of Psychiatry, National Taiwan University Hospital and College of Medicine, Taipei, Taiwan
- Graduate Institute of Brain and Mind Sciences and Graduate Institute of Clinical Medicine, National Taiwan University, Taipei, Taiwan
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Vilor-Tejedor N, Ikram MA, Roshchupkin G, Vinke EJ, Vernooij MW, Adams HHH. Aging-Dependent Genetic Effects Associated to ADHD Predict Longitudinal Changes of Ventricular Volumes in Adulthood. Front Psychiatry 2020; 11:574. [PMID: 32714213 PMCID: PMC7344235 DOI: 10.3389/fpsyt.2020.00574] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/20/2019] [Accepted: 06/05/2020] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND Attention-Deficit/Hyperactivity Disorder (ADHD) is a childhood-onset disorder that can persist into adult life. Most genetic studies have focused on investigating biological mechanisms of ADHD during childhood. However, little is known about whether genetic variants associated with ADHD influence structural brain changes throughout adulthood. METHODS Participant of the study were drawn from a population-based sample of 3,220 healthy individuals drawn from the Rotterdam Study, with at least two magnetic resonance imaging (MRI)-scans (8,468 scans) obtained every 3-4 years. We investigate associations of genetic single nucleotide polymorphisms (SNPs) that have previously been identified in genome-wide association studies for ADHD, and trajectories of global and subcortical brain structures in an adult population (aged 50 years and older), acquired through MRI. We also evaluated the existence of age-dependent effects of these genetic variants on trajectories of brain structures. These analyses were reproduced among individuals 70 years of age or older to further explore aging-dependent mechanisms. We additionally tested baseline associations using the first MRI-scan of the 3,220 individuals. RESULTS We observed significant age-dependent effects on the rs212178 in trajectories of ventricular size (lateral ventricles, P= 4E-05; inferior lateral ventricles, P=3.8E-03; third ventricle, P=2.5E-03; fourth ventricle, P=5.5E-03). Specifically, carriers of the G allele, which was reported as protective for ADHD, had a smaller increase of ventricular size compared with homozygotes for the A allele in elder stages. Post hoc analysis on the subset of individuals older than 70 years of age reinforced these results (lateral ventricles, P=7.3E-05). In addition, the rs4916723, and the rs281324 displayed nominal significant age-dependent effects in trajectories of the amygdala volume (P=1.4E-03), and caudate volume (P=1.8E-03), respectively. CONCLUSIONS To the best of our knowledge, this is the first study suggesting the involvement of protective genetic variants for ADHD on prevention of brain atrophy during adulthood.
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Affiliation(s)
- Natalia Vilor-Tejedor
- Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, Barcelona, Spain
- BarcelonaBeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- Department of Clinical Genetics, Erasmus Medical Center, Rotterdam, Netherlands
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Mohammad Arfan Ikram
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, Netherlands
- Department of Radiology and Nuclear Medicine, Erasmus Medical Center, Rotterdam, Netherlands
- Department of Neurology, Erasmus Medical Center, Rotterdam, Netherlands
| | - Gennady Roshchupkin
- Department of Radiology and Nuclear Medicine, Erasmus Medical Center, Rotterdam, Netherlands
- Department of Medical Informatics, Erasmus Medical Center, Rotterdam, Netherlands
| | - Elisabeth J. Vinke
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, Netherlands
- Department of Radiology and Nuclear Medicine, Erasmus Medical Center, Rotterdam, Netherlands
| | - Meike W. Vernooij
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, Netherlands
- Department of Radiology and Nuclear Medicine, Erasmus Medical Center, Rotterdam, Netherlands
| | - Hieab H. H. Adams
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, Netherlands
- Department of Radiology and Nuclear Medicine, Erasmus Medical Center, Rotterdam, Netherlands
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Vilor-Tejedor N, Ikram MA, Roshchupkin GV, Cáceres A, Alemany S, Vernooij MW, Niessen WJ, van Duijn CM, Sunyer J, Adams HH, González JR. Independent Multiple Factor Association Analysis for Multiblock Data in Imaging Genetics. Neuroinformatics 2020; 17:583-592. [PMID: 30903541 DOI: 10.1007/s12021-019-09416-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
Multivariate methods have the potential to better capture complex relationships that may exist between different biological levels. Multiple Factor Analysis (MFA) is one of the most popular methods to obtain factor scores and measures of discrepancy between data sets. However, singular value decomposition in MFA is based on PCA, which is adequate only if the data is normally distributed, linear or stationary. In addition, including strongly correlated variables can overemphasize the contribution of the estimated components. In this work, we introduced a novel method referred as Independent Multifactorial Analysis (ICA-MFA) to derive relevant features from multiscale data. This method is an extended implementation of MFA, where the component value decomposition is based on Independent Component Analysis. In addition, ICA-MFA incorporates a predictive step based on an Independent Component Regression. We evaluated and compared the performance of ICA-MFA with both, the MFA method and traditional univariate analyses, in a simulation study. We showed how ICA-MFA explained up to 10-fold more variance than MFA and univariate methods. We applied the proposed algorithm in a study of 4057 individuals belonging to the population-based Rotterdam Study with available genetic and neuroimaging data, as well as information about executive cognitive functioning. Specifically, we used ICA-MFA to detect relevant genetic features related to structural brain regions, which in turn were involved, in the mechanisms of executive cognitive function. The proposed strategy makes it possible to determine the degree to which the whole set of genetic and/or neuroimaging markers contribute to the variability of the symptomatology jointly, rather than individually. While univariate results and MFA combinations only explained a limited proportion of variance (less than 2%), our method increased the explained variance (10%) and allowed the identification of significant components that maximize the variance explained in the model. The potential application of the ICA-MFA algorithm constitutes an important aspect of integrating multivariate multiscale data, specifically in the field of Neurogenetics.
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Affiliation(s)
- Natalia Vilor-Tejedor
- Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology., C. Doctor Aiguader 88, Edif. PRBB, 08003, Barcelona, Spain. .,BarcelonaBeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain. .,Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain. .,Universitat Pompeu Fabra (UPF), Barcelona, Spain. .,CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain.
| | | | - Gennady V Roshchupkin
- Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, the Netherlands.,Department of Medical Informatics, Erasmus MC, Rotterdam, the Netherlands
| | - Alejandro Cáceres
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain.,Universitat Pompeu Fabra (UPF), Barcelona, Spain.,CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain
| | - Silvia Alemany
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain.,Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Meike W Vernooij
- Department of Epidemiology, Erasmus MC, Rotterdam, the Netherlands.,Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, the Netherlands
| | - Wiro J Niessen
- Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, the Netherlands.,Department of Medical Informatics, Erasmus MC, Rotterdam, the Netherlands.,Faculty of Applied Sciences, Delft University of Technology, Delft, The Netherlands
| | | | - Jordi Sunyer
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain.,Universitat Pompeu Fabra (UPF), Barcelona, Spain.,CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
| | - Hieab H Adams
- Department of Epidemiology, Erasmus MC, Rotterdam, the Netherlands.,Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, the Netherlands.,Department of Medical Informatics, Erasmus MC, Rotterdam, the Netherlands
| | - Juan R González
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain.,Universitat Pompeu Fabra (UPF), Barcelona, Spain.,CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain
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Shang CY, Lin HY, Tseng WY, Gau SS. A haplotype of the dopamine transporter gene modulates regional homogeneity, gray matter volume, and visual memory in children with attention-deficit/hyperactivity disorder. Psychol Med 2018; 48:2530-2540. [PMID: 29433615 DOI: 10.1017/s0033291718000144] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
BACKGROUND The dopamine transporter gene (DAT1) and visual memory deficits have been consistently reported to be associated with attention-deficit/hyperactivity disorder (ADHD). This study aimed to examine whether a DAT1 haplotype affected functional and structural brain alterations in children with ADHD and whether those alterations were associated with visual memory. METHOD We recruited a total of 37 drug-naïve children with ADHD (17 with the DAT1 rs27048 (C)/rs429699 (T) haplotype and 20 without the CT haplotype) and 37 typically developing children (17 with the CT haplotype and 20 without the CT haplotype). Visual memory was assessed by the pattern recognition memory (PRM) and spatial recognition memory (SRM) tasks. We analyzed functional and structural brain architecture with regional homogeneity (ReHo) and gray matter volume (GMV). RESULTS The CT haplotype was associated with decreased ReHo in the left superior occipital gyrus, cuneus, and precuneus; and decreased GMV in the left superior occipital gyrus, cuneus, and precuneus, and in the right angular gyrus. Significant interactions of ADHD and the CT haplotype were found in the right postcentral gyrus for ReHo and in the right supplementary motor area for GMV. For the ADHD-CT group, we found negative correlations of total correct responses in PRM and SRM and positive correlations of mean latency of correct responses in PRM with the GMV in the left superior occipital gyrus, cuneus, and precuneus. CONCLUSIONS Our findings suggest that the DAT1-related GMV alterations in the posterior cortical regions may contribute to visual memory performance in children with ADHD.
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Affiliation(s)
- C Y Shang
- Department of Psychiatry,National Taiwan University Hospital and College of Medicine,Taipei,Taiwan
| | - H Y Lin
- Department of Psychiatry,National Taiwan University Hospital and College of Medicine,Taipei,Taiwan
| | - W Y Tseng
- Graduate Institute of Brain and Mind Sciences,National Taiwan University,Taipei,Taiwan
| | - S S Gau
- Department of Psychiatry,National Taiwan University Hospital and College of Medicine,Taipei,Taiwan
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Müller RA, Fishman I. Brain Connectivity and Neuroimaging of Social Networks in Autism. Trends Cogn Sci 2018; 22:1103-1116. [PMID: 30391214 DOI: 10.1016/j.tics.2018.09.008] [Citation(s) in RCA: 62] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2018] [Revised: 09/21/2018] [Accepted: 09/26/2018] [Indexed: 01/16/2023]
Abstract
Impairments in social communication (SC) predominate among the core diagnostic features of autism spectrum disorders (ASDs). Neuroimaging has revealed numerous findings of atypical activity and connectivity of 'social brain' networks, yet no consensus view on crucial developmental causes of SC deficits has emerged. Aside from methodological challenges, the deeper problem concerns the clinical label of ASD. While genetic studies have not comprehensively explained the causes of nonsyndromic ASDs, they highlight that the clinical label encompasses many etiologically different disorders. The question of how potential causes and etiologies converge onto a comparatively narrow set of SC deficits remains. Only neuroimaging designs searching for subtypes within ASD cohorts (rather than conventional group level designs) can provide translationally informative answers.
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Affiliation(s)
- Ralph-Axel Müller
- Brain Development Imaging Laboratories, SDSU Center for Autism and Developmental Disorders, San Diego State University, San Diego, CA, USA.
| | - Inna Fishman
- Brain Development Imaging Laboratories, SDSU Center for Autism and Developmental Disorders, San Diego State University, San Diego, CA, USA
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Vilor-Tejedor N, Alemany S, Cáceres A, Bustamante M, Mortamais M, Pujol J, Sunyer J, González JR. Sparse multiple factor analysis to integrate genetic data, neuroimaging features, and attention-deficit/hyperactivity disorder domains. Int J Methods Psychiatr Res 2018; 27:e1738. [PMID: 30105890 PMCID: PMC6877273 DOI: 10.1002/mpr.1738] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/05/2017] [Revised: 05/17/2018] [Accepted: 06/26/2018] [Indexed: 11/09/2022] Open
Abstract
OBJECTIVES We proposed the application of a multivariate cross-sectional framework based on a combination of a variable selection method and a multiple factor analysis (MFA) in order to identify complex meaningful biological signals related to attention-deficit/hyperactivity disorder (ADHD) symptoms and hyperactivity/inattention domains. METHODS The study included 135 children from the general population with genomic and neuroimaging data. ADHD symptoms were assessed using a questionnaire based on ADHD-DSM-IV criteria. In all analyses, the raw sum scores of the hyperactivity and inattention domains and total ADHD were used. The analytical framework comprised two steps. First, zero-inflated negative binomial linear model via penalized maximum likelihood (LASSO-ZINB) was performed. Second, the most predictive features obtained with LASSO-ZINB were used as input for the MFA. RESULTS We observed significant relationships between ADHD symptoms and hyperactivity and inattention domains with white matter, gray matter regions, and cerebellum, as well as with loci within chromosome 1. CONCLUSIONS Multivariate methods can be used to advance the neurobiological characterization of complex diseases, improving the statistical power with respect to univariate methods, allowing the identification of meaningful biological signals in Imaging Genetic studies.
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Affiliation(s)
- Natàlia Vilor-Tejedor
- ISGlobal, Barcelona Institute for Global Health, Barcelona, Spain.,Universitat Pompeu Fabra (UPF), Barcelona, Spain.,CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain.,Center for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain.,Barcelonabeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
| | - Silvia Alemany
- ISGlobal, Barcelona Institute for Global Health, Barcelona, Spain.,Universitat Pompeu Fabra (UPF), Barcelona, Spain.,CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain
| | - Alejandro Cáceres
- ISGlobal, Barcelona Institute for Global Health, Barcelona, Spain.,Universitat Pompeu Fabra (UPF), Barcelona, Spain.,CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain
| | - Mariona Bustamante
- ISGlobal, Barcelona Institute for Global Health, Barcelona, Spain.,Universitat Pompeu Fabra (UPF), Barcelona, Spain.,CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain.,Center for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Marion Mortamais
- ISGlobal, Barcelona Institute for Global Health, Barcelona, Spain.,Universitat Pompeu Fabra (UPF), Barcelona, Spain.,CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain
| | - Jesús Pujol
- MRI Research Unit, Hospital del Mar, and Centro de Investigación Biomédica en Red de Salud Mental, CIBERSAM G21, Barcelona, Spain
| | - Jordi Sunyer
- ISGlobal, Barcelona Institute for Global Health, Barcelona, Spain.,Universitat Pompeu Fabra (UPF), Barcelona, Spain.,CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
| | - Juan R González
- ISGlobal, Barcelona Institute for Global Health, Barcelona, Spain.,Universitat Pompeu Fabra (UPF), Barcelona, Spain.,CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain
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