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• Clinical Article •
Modulation of catechol-O-methyltransferase Val158Met polymorphism on topological reorganization of white-matter networks in attention-deficit/hyperactivity disorder children
TIAN Tian  WANG Jian  ZHANG Guiling  LI Jia 

Cite this article as: Tian T, Wang J, Zhang GL, et al. Modulation of catechol-o-methyltransferase Val158Met polymorphism on topological reorganization of white-matter networks in attention-deficit/hyperactivity disorder children. Chin J Magn Reson Imaging, 2019, 10(4): 241-248. DOI:10.12015/issn.1674-8034.2019.04.001.


[Abstract] Objective: Attention-deficit/hyperactivity disorder (ADHD) children showed the redistribution of structural connectivity involving large-scale brain systems beyond the prefrontal-striatal model. The dopamine system has been associated with symptoms of ADHD, and is important for pharmacologic treatments. The current study aims to discuss that how dopamine impact neural circuitry underlying behavior pathways occurs in ADHD.Materials and Methods: We used diffusion tensor imaging and deterministic tractography to construct individual white matter structural networks in 40 patients and 40 age-matched healthy control participants. The automated anatomic labeling template was used to parcel the brain into 90 regions of interest to define the network nodes for each subject. The number of connected fibers between each pairs of nodes was calculated and defined as the edge weight between nodes. Catechol-O-methyltransferase (COMT) rs4680 genotyping was performed. All network analyses were performed by using in-house software Gretna. Graph theory approaches were used to investigate the topologic alterations in the structural brain networks between groups and their interaction. We used a network based statistic (NBS) approach to localize specific pairs of regions in which structural connectivity were altered. Finally, the connection strength of linking between hub nodes to hub nodes, hub nodes to nonhub nodes, and nonhub nodes to nonhub nodes were calculated and analyzed between groups.Results: We found significant reorganization of white matter structural networks in ADHD Met allele carriers, manifested as increased nodal degree, nodal efficiency, fronto-striatal circuitry, parietal-cingulum-motor circuitry, feeder and local connections.Conclusions: Those diffuse white matter alterations were not only implicated in fronto-striatal networks mediating executive functions but were also involving in sensorimotor network, frontal, cingulum, and parietal areas during perception-motor, higher order cognitive, attention control and processing. Together, these genetic-based findings highlight large-scale brain systems reorganization in ADHD, might also have important implications on the clinical pharmacologic treatments and development of pharmacogenomics.
[Keywords] attention-deficit/hyperactivity disorder；catechol-O-methyltransferase；dopamine；graph theory approach；diffusion tensor imaging；white matter

TIAN Tian* Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China

WANG Jian Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China

ZHANG Guiling Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China

LI Jia Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China

*Correspondence to: Tian T, E-mail: tongjitiantian@163.com

Conflicts of interest   None.

ACKNOWLEDGMENTS  This work was part of National Natural Science Foundation of China No.81601475
Received  2018-10-15
Accepted  2018-12-19
DOI: 10.12015/issn.1674-8034.2019.04.001
Cite this article as: Tian T, Wang J, Zhang GL, et al. Modulation of catechol-o-methyltransferase Val158Met polymorphism on topological reorganization of white-matter networks in attention-deficit/hyperactivity disorder children. Chin J Magn Reson Imaging, 2019, 10(4): 241-248. DOI:10.12015/issn.1674-8034.2019.04.001.

[1]
Faraone SV, Biederman J, Spencer T, et al. Attention-deficit/hyperactivity disorder in adults: an overview. Biol Psychiatry, 2000, 48(1): 9-20.
[2]
Kobel M, Bechtel N, Specht K, et al. Structural and functional imaging approaches in attention deficit/hyperactivity disorder: does the temporal lobe play a key role?. Psychiatry Res, 2010, 183(3): 230-236.
[3]
Proal E, Reiss PT, Klein RG, et al. Brain gray matter deficits at 33- year follow-up in adults with attention-deficit/hyperactivity disorder established in childhood. Arch Gen Psychiatry, 2011, 68(11): 1122-1134.
[4]
Weyandt L, Swentosky A, Gudmundsdottir BG. Neuroimaging and ADHD: fMRI, PET, DTI findings, and methodological limitations. Dev Neuropsychol, 2013, 38(4): 211-225.
[5]
Peterson DJ, Ryan M, Rimrodt SL, et al. Increased regional fractional anisotropy in highly screened attention-deficit hyperactivity disorder(ADHD). J Child Neurol, 2011, 26(10): 1296-1302.
[6]
Sun H, Yuan F, Shen X, et al. Role of COMT in ADHD: a systematic meta-analysis. Mol Neurobiol, 2014, 49(1): 251-261.
[7]
Cao M, Shu N, Cao Q, et al. Imaging functional and structural brain connectomics in attention-deficit/hyperactivity disorder. Mol Neurobiol, 2014, 50(3): 1111-1123.
[8]
Hong SB, Zalesky A, Fornito A, et al. Connectomic disturbances in attention-deficit/hyperactivity disorder: a whole-brain tractography analysis. Biol Psychiatry, 2014, 76(8): 656-663.
[9]
Cao Q, Shu N, An L, et al. Probabilistic diffusion tractography and graph theory analysis reveal abnormal white matter structural connectivity networks in drug-naive boys with attention deficit/hyperactivity disorder. J Neurosci, 2013, 33(26): 10676-10687.
[10]
Sidlauskaite J, Caeyenberghs K, Sonuga-Barke E, et al. Whole-brain structural topology in adult attention-deficit/hyperactivity disorder: Preserved global- disturbed local network organization. Neuroimage Clin, 2015, 9: 506-512.
[11]
Beare R, Adamson C, Bellgrove MA, et al. Altered structural connectivity in ADHD: a network based analysis. Brain Imaging Behav, 2017, 11(3): 846-858.
[12]
Cui Z, Zhong S, Xu P, et al. PANDA: a pipeline toolbox for analyzing brain diffusion images. Front Hum Neurosci, 2013, 7: 42.
[13]
Wang J, Wang X, Xia M, et al. GRETNA: a graph theoretical network analysis toolbox for imaging connectomics. Front Hum Neurosci, 2015, 9: 386.
[14]
Xia M, Wang J, He Y. BrainNet viewer: a network visualization tool for human brain connectomics. PloS one, 2013, 8(7): e68910.
[15]
Shu N, Wang X, Bi Q, et al. Disrupted topologic efficiency of white matter structural connectome in individuals with subjective cognitive decline. Radiology, 2018, 286(1): 229-238.
[16]
McLeod KR, Langevin LM, Dewey D, et al. Atypical within- and between-hemisphere motor network functional connections in children with developmental coordination disorder and attention-deficit/hyperactivity disorder. Neuroimage Clin, 2016, 12: 157-164.
[17]
McLeod KR, Langevin LM, Goodyear BG, et al. Functional connectivity of neural motor networks is disrupted in children with developmental coordination disorder and attention-deficit/hyperactivity disorder. Neuroimage Clin, 2014, 4: 566-575.
[18]
Li S, Wang S, Li X, et al. Abnormal surface morphology of the central sulcus in children with attention-deficit/hyperactivity disorder. Front Hum Neurosci, 2015, 9: 114.
[19]
Sutcubasi Kaya B, Metin B, Tas ZC, et al. Gray matter increase in motor cortex in pediatric ADHD: A voxel-based morphometry study. J Attent Disor, 2018, 22(7): 611-618.
[20]
Tamm L, Menon V, Reiss AL. Parietal attentional system aberrations during target detection in adolescents with attention deficit hyperactivity disorder: event-related fMRI evidence. American J Psychiatry, 2006, 163(6): 1033-1043.
[21]
McGough JJ. Attention-deficit/hyperactivity disorder pharmacogenomics. Biol Psychiatry, 2005, 57(11): 1367-1373.
[22]
Goldman-Rakic PS. The cortical dopamine system: role in memory and cognition. Adv Pharmacol, 1998, 42: 707-711.
[23]
Seamans JK, Yang CR. The principal features and mechanisms of dopamine modulation in the prefrontal cortex. Prog Neurobiol, 2004, 74(1): 1-58.
[24]
Qin S, Cousijn H, Rijpkema M, et al. The effect of moderate acute psychological stress on working memory-related neural activity is modulated by a genetic variation in catecholaminergic function in humans. Front Integr Neurosci, 2012, 6: 16.
[25]
Honea R, Verchinski BA, Pezawas L, et al. Impact of interacting functional variants in COMT on regional gray matter volume in human brain. Neuro Image, 2009, 45(1): 44-51.
[26]
Kuppers E, Beyer C. Dopamine regulates brain-derived neurotrophic factor (BDNF) expression in cultured embryonic mouse striatal cells. Neuroreport, 2001, 12(6): 1175-1179.
[27]
Santiago M, Matarredona ER, Granero L, et al. Neurotoxic relationship between dopamine and iron in the striatal dopaminergic nerve terminals. Brain Res, 2000, 858(1): 26-32.
[28]
Fumagalli F, Racagni G, Colombo E, et al. BDNF gene expression is reduced in the frontal cortex of dopamine transporter knockout mice. Mol Psychiatry, 2003, 8(11): 898-899.
[29]
Xu M, Moratalla R, Gold LH, et al. Dopamine D1 receptor mutant mice are deficient in striatal expression of dynorphin and in dopamine-mediated behavioral responses. Cell, 1994, 79(4): 729-742.
[30]
Granon S, Passetti F, Thomas KL, et al. Enhanced and impaired attentional performance after infusion of D1 dopaminergic receptor agents into rat prefrontal cortex. J Neurosci, 2000, 20(3): 1208-1215.
[31]
Apud JA, Mattay V, Chen J, et al. Tolcapone improves cognition and cortical information processing in normal human subjects. Neuropsychopharmacology, 2007, 32(5): 1011-1020.
[32]
Mattay VS, Goldberg TE, Fera F, et al. Catechol O-methyltransferase val158-met genotype and individual variation in the brain response to amphetamine. Proc Natl Acad Sci U S A, 2003, 100(10): 6186-6191.
[33]
Mehta MA, Owen AM, Sahakian BJ, et al. Methylphenidate enhances working memory by modulating discrete frontal and parietal lobe regions in the human brain. J Neurosci, 2000, 20(6): RC65.
[34]
Tunbridge EM, Harrison PJ, Weinberger DR. Catechol-o-methyltransferase, cognition, and psychosis: Val158Met and beyond. Biol Psychiatry, 2006, 60(2): 141-151.
[35]
Bilder RM, Volavka J, Lachman HM, et al. The catechol- O-methyltransferase polymorphism: relations to the tonicphasic dopamine hypothesis and neuropsychiatric phenotypes. Neuropsychopharmacology, 2004, 29(11): 1943-1961.
[36]
Egan MF, Goldberg TE, Kolachana BS, et al. Effect of COMT Val108/158 Met genotype on frontal lobe function and risk for schizophrenia. Proc Natl Acad Sci U S A, 2001, 98(12): 6917-6922.
[37]
Crossley NA, Mechelli A, Scott J, et al. The hubs of the human connectome are generally implicated in the anatomy of brain disorders. Brain, 2014, 137(8): 2382-2395.

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