Abstract
Catechol-O-methyltransferase (COMT) affects brain connectivity via modulating the dopamine system, with an expected greater effect of haplotypes than single-nucleotide polymorphism (SNP). The action pathway from COMT to dopamine to connectivity is theoretically dependent on the gene expression of dopamine receptors. Here, we aimed to investigate the impact of COMT haplotypes on brain functional connectivity density (FCD) in hundreds of healthy young subjects, and to disclose the association between the COMT-FCD statistical map and the spatial expression of the dopamine receptor genes. We found an inverted U-shaped modulation of COMT haplotypes on FCD in the left inferior parietal lobule that is mainly connected to the frontal and parietal cortices, with APS homozygotes exhibiting greater FCD than the other five groups. However, we failed to identify any significant effect of any SNP on FCD. Utilizing gene expression data collected from Allen human brain atlas, we found the COMT-FCD statistical map was significantly associated with the expression patterns of the dopamine receptor genes. Our results suggest that COMT haplotypes have greater impact on functional connectivity than a single genetic variation and that the association between COMT and functional connectivity may be dependent on the gene expression of dopamine receptors.
Similar content being viewed by others
References
Albaugh MD, Orr C, Chaarani B, Althoff RR, Allgaier N, D’Alberto N, Hudson K, Mackey S, Spechler PA, Banaschewski T, Bruhl R, Bokde ALW, Bromberg U, Buchel C, Cattrell A, Conrod PJ, Desrivieres S, Flor H, Frouin V, Gallinat J, Goodman R, Gowland P, Grimmer Y, Heinz A, Kappel V, Martinot JL, Paillere Martinot ML, Nees F, Orfanos DP, Penttila J, Poustka L, Paus T, Smolka MN, Struve M, Walter H, Whelan R, Schumann G, Garavan H, Potter AS (2017) Inattention and reaction time variability are linked to ventromedial prefrontal volume in adolescents. Biol Psychiatry 82(9):660–668
Barrett JC, Fry B, Maller J, Daly MJ (2005) Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics 21(2):263–265. https://doi.org/10.1093/bioinformatics/bth457
Chen CY, Yeh YW, Kuo SC, Ho PS, Liang CS, Yen CH, Lu RB, Huang SY (2016) Catechol-O-methyltransferase gene variants may associate with negative symptom response and plasma concentrations of prolactin in schizophrenia after amisulpride treatment. Psychoneuroendocrinology 65:67–75
Ciric R, Wolf DH, Power JD, Roalf DR, Baum GL, Ruparel K, Shinohara RT, Elliott MA, Eickhoff SB, Davatzikos C, Gur RC, Gur RE, Bassett DS, Satterthwaite TD (2017) Benchmarking of participant-level confound regression strategies for the control of motion artifact in studies of functional connectivity. Neuroimage 154:174–187. https://doi.org/10.1016/j.neuroimage.2017.03.020
Costas J, Sanjuan J, Ramos-Rios R, Paz E, Agra S, Ivorra JL, Paramo M, Brenlla J, Arrojo M (2011) Heterozygosity at catechol-O-methyltransferase Val158Met and schizophrenia: new data and meta-analysis. J Psychiatr Res 45(1):7–14. https://doi.org/10.1016/j.jpsychires.2010.04.021
Cristina M, Russel NS, Robinson SW, Mohamed J, Caron MG (1998) Dopamine receptors: from structure to function. Physiol Rev 78(1):189–225
Diatchenko L, Slade GD, Nackley AG, Bhalang K, Sigurdsson A, Belfer I, Goldman D, Xu K, Shabalina SA, Shagin D, Max MB, Makarov SS, Maixner W (2005) Genetic basis for individual variations in pain perception and the development of a chronic pain condition. Hum Mol Genet 14(1):135–143. https://doi.org/10.1093/hmg/ddi013
Egan MF, Goldberg TE, Kolachana BS, Callicott JH, Mazzanti CM, Straub RE et al (2001) Effect of comt val108/158 met genotype on frontal lobe function and risk for schizophrenia. Proc Natl Acad Sci 98(12):6917–6922. https://doi.org/10.1073/pnas
Fan JB, Zhang CS, Gu NF, Li XW, Sun WW, Wang HY, Feng GY, St Clair D, He L (2005) Catechol-O-methyltransferase gene Val/Met functional polymorphism and risk of schizophrenia: a large-scale association study plus meta-analysis. Biol Psychiatry 57(2):139–144. https://doi.org/10.1016/j.biopsych.2004.10.018
Giakoumaki SG, Roussos P, Bitsios P (2008) Improvement of prepulse inhibition and executive function by the COMT inhibitor tolcapone depends on COMT Val158Met polymorphism. Neuropsychopharmacology 33(13):3058–3068. https://doi.org/10.1038/npp.2008.82
Glatt SJ, Faraone SV, Tsuang MT (2003) Association between a functional catechol O-methyltransferase gene polymorphism and schizophrenia: meta-analysis of case-control and family-based studies. Am J Psychiatry 160(3):469–476
Gonzalez-Castro TB, Hernandez-Diaz Y, Juarez-Rojop IE, Lopez-Narvaez ML, Tovilla-Zarate CA, Fresan A (2016) The role of a catechol-O-methyltransferase (COMT) Val158Met genetic polymorphism in schizophrenia: a systematic review and updated meta-analysis on 32,816 subjects. Neuromol Med 18(2):216–231. https://doi.org/10.1007/s12017-016-8392-z
Gorgolewski KJ, Fox AS, Chang L et al. (2014) Tight fitting genes: finding relations between statistical maps and gene expression patterns. F1000 Posters 5:1607
Guo JF, Kuang Yang Y, Tsing Chiu N, Lieh Yeh T, See Chen P, Lee IH, Lin Chu C (2006) The correlation between striatal dopamine D2/D3 receptor availability and verbal intelligence quotient in healthy volunteers. Psychol Med 36(4):547–554. https://doi.org/10.1017/S0033291705006732
Hall H, Sedvall G, Magnusson O, Kopp J, Halldin C, Farde L (1994) Distribution of d1- and d2-dopamine receptors, and dopamine and its metabolites in the human brain. Neuropsychopharmacology 11(4):245–256
Hawrylycz MJ, Lein ES, Guillozet-Bongaarts AL, Shen EH, Ng L, Miller JA, van de Lagemaat LN, Smith KA, Ebbert A, Riley ZL, Abajian C, Beckmann CF, Bernard A, Bertagnolli D, Boe AF, Cartagena PM, Chakravarty MM, Chapin M, Chong J, Dalley RA, David Daly B, Dang C, Datta S, Dee N, Dolbeare TA, Faber V, Feng D, Fowler DR, Goldy J, Gregor BW, Haradon Z, Haynor DR, Hohmann JG, Horvath S, Howard RE, Jeromin A, Jochim JM, Kinnunen M, Lau C, Lazarz ET, Lee C, Lemon TA, Li L, Li Y, Morris JA, Overly CC, Parker PD, Parry SE, Reding M, Royall JJ, Schulkin J, Sequeira PA, Slaughterbeck CR, Smith SC, Sodt AJ, Sunkin SM, Swanson BE, Vawter MP, Williams D, Wohnoutka P, Zielke HR, Geschwind DH, Hof PR, Smith SM, Koch C, Grant SGN, Jones AR (2012) An anatomically comprehensive atlas of the adult human brain transcriptome. Nature 489(7416):391–399. https://doi.org/10.1038/nature11405
Honea R, Verchinski BA, Pezawas L, Kolachana BS, Callicott JH, Mattay VS, Weinberger DR, Meyer-Lindenberg A (2009) Impact of interacting functional variants in COMT on regional gray matter volume in human brain. Neuroimage 45(1):44–51. https://doi.org/10.1016/j.neuroimage.2008.10.064
International HapMap C (2005) A haplotype map of the human genome. Nature 437(7063):1299–1320. https://doi.org/10.1038/nature04226
Jenkinson M, Beckmann CF, Behrens TEJ, Woolrich MW, Smith SM (2012) FSL. Neuroimage 62(2):782–790
Kuppers E, Beyer C (2001) Dopamine regulates brain-derived neurotrophic factor (bdnf) expression in cultured embryonic mouse striatal cells. NeuroReport 12(6):1175–1179
Lee A, Qiu A (2016) Modulative effects of COMT haplotype on age-related associations with brain morphology. Hum Brain Mapp 37(6):2068–2082. https://doi.org/10.1002/hbm.23161
Li W, Liu B, Xu J, Jiang T, Yu C (2016) Interaction of COMT rs4680 and BDNF rs6265 polymorphisms on functional connectivity density of the left frontal eye field in healthy young adults. Hum Brain Mapp 37(7):2468–2478. https://doi.org/10.1002/hbm.23187
Liu B, Li J, Yu C, Li Y, Liu Y, Song M, Fan M, Li K, Jiang T (2010) Haplotypes of catechol-O-methyltransferase modulate intelligence-related brain white matter integrity. Neuroimage 50(1):243–249. https://doi.org/10.1016/j.neuroimage.2009.12.020
Lorenz AJ, Hamblin MT, Jannink JL (2010) Performance of single nucleotide polymorphisms versus haplotypes for genome-wide association analysis in barley. PLoS One 5(11):e14079. https://doi.org/10.1371/journal.pone.0014079
Luquin-Piudo MR, Sanz P (2011) Dopamine receptors, motor responses, and dopaminergic agonists. Neurologist 17(6 Suppl 1):S2–S8. https://doi.org/10.1097/NRL.0b013e3182396688
Mannisto PTKS (1999) Catechol-O-methyltransferase (COMT): biochemistry, molecular biology, pharmacology, and clinical efficacy of the new selective COMT inhibitors. Pharmacol Rev 51(4):593–598
Mattay VS, Goldberg TE, Fera F, Hariri AR, Tessitore A, Egan MF et al (2003) Catechol O-methyltransferase val158-met genotype and individual variation in the brain response to amphetamine. Proc Natl Acad Sci 100(10):6186–6191
McIntosh AM, Baig BJ, Hall J, Job D, Whalley HC, Lymer GK, Moorhead TW, Owens DG, Miller P, Porteous D, Lawrie SM, Johnstone EC (2007) Relationship of catechol-O-methyltransferase variants to brain structure and function in a population at high risk of psychosis. Biol Psychiatry 61(10):1127–1134. https://doi.org/10.1016/j.biopsych.2006.05.020
Meyer-Lindenberg A, Nichols T, Callicott JH, Ding J, Kolachana B, Buckholtz J, Mattay VS, Egan M, Weinberger DR (2006) Impact of complex genetic variation in COMT on human brain function. Mol Psychiatry 11(9):867–877. https://doi.org/10.1038/sj.mp.4001860
Mohr H, Wolfensteller U, Betzel RF, Misic B, Sporns O, Richiardi J, Ruge H (2016) Integration and segregation of large-scale brain networks during short-term task automatization. Nat Commun 7:13217. https://doi.org/10.1038/ncomms13217
Nackley AG, Shabalina SA, Tchivileva IE, Satterfield K, Korchynskyi O, Makarov SS et al (2006) Human catechol-O-methyltransferase haplotypes modulate protein expression by altering mrna secondary structure. Science 314(5807):1930–1933
Nicodemus KK, Kolachana BS, Vakkalanka R, Straub RE, Giegling I, Egan MF, Rujescu D, Weinberger DR (2007) Evidence for statistical epistasis between catechol-O-methyltransferase (COMT) and polymorphisms in RGS4, G72 (DAOA), GRM3, and DISC1: influence on risk of schizophrenia. Hum Genet 120(6):889–906. https://doi.org/10.1007/s00439-006-0257-3
Parent A, Hazrati LN (1995) Functional anatomy of the basal ganglia. I. the cortico-basal ganglia-thalamo-cortical loop. Brain Res Rev 20(1):127–163
Power JD, Barnes KA, Snyder AZ, Schlaggar BL, Petersen SE (2012) Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion. Neuroimage 59(3):2142–2154. https://doi.org/10.1016/j.neuroimage.2011.10.018
Power JD, Barnes KA, Snyder AZ, Schlaggar BL, Petersen SE (2013) Steps toward optimizing motion artifact removal in functional connectivity MRI; a reply to Carp. Neuroimage 76:439–441. https://doi.org/10.1016/j.neuroimage.2012.03.017
Pruim RHR, Mennes M, Buitelaar JK, Beckmann CF (2015a) Evaluation of ICA-AROMA and alternative strategies for motion artifact removal in resting state fMRI. Neuroimage 112:278–287. https://doi.org/10.1016/j.neuroimage.2015.02.063
Pruim RHR, Mennes M, van Rooij D, Llera A, Buitelaar JK, Beckmann CF (2015b) ICA-AROMA: a robust ICA-based strategy for removing motion artifacts from fMRI data. Neuroimage 112:267–277. https://doi.org/10.1016/j.neuroimage.2015.02.064
Santiago M, Matarredona ER, Granero L, Cano J, Machado A (2000) Neurotoxic relationship between dopamine and iron in the striatal dopaminergic nerve terminals. Brain Res Rev 858(1):26–32
Satterthwaite TD, Elliott MA, Gerraty RT, Ruparel K, Loughead J, Calkins ME, Eickhoff SB, Hakonarson H, Gur RC, Gur RE, Wolf DH (2013) An improved framework for confound regression and filtering for control of motion artifact in the preprocessing of resting-state functional connectivity data. Neuroimage 64:240–256. https://doi.org/10.1016/j.neuroimage.2012.08.052
Seamans JK, Yang CR (2004) The principal features and mechanisms of dopamine modulation in the prefrontal cortex. Prog Neurobiol 74(1):1–58. https://doi.org/10.1016/j.pneurobio.2004.05.006
Shafiei G, Zeighami Y, Clark CA, Coull JT, Nagano-Saito A, Leyton M, Dagher A, Misic B (2019) Dopamine signaling modulates the stability and integration of intrinsic brain networks. Cereb Cortex 29(1):397–409. https://doi.org/10.1093/cercor/bhy264
Sheffield JM, Repovs G, Harms MP, Carter CS, Gold JM, MacDonald AW 3rd, Daniel Ragland J, Silverstein SM, Godwin D, Barch DM (2015) Fronto-parietal and cingulo-opercular network integrity and cognition in health and schizophrenia. Neuropsychologia 73:82–93. https://doi.org/10.1016/j.neuropsychologia.2015.05.006
Stephens M, Scheet P (2005) Accounting for decay of linkage disequilibrium in haplotype inference and missing-data imputation. Am J Hum Genet 76(3):449–462. https://doi.org/10.1086/428594
Stephens M, Smith NJ, Donnelly P (2001) A new statistical method for haplotype reconstruction from population data. Am J Hum Genet 68(4):978–989. https://doi.org/10.1086/319501
Tan HY, Chen Q, Goldberg TE, Mattay VS, Meyer-Lindenberg A, Weinberger DR, Callicott JH (2007) Catechol-O-methyltransferase Val158Met modulation of prefrontal–parietal–striatal brain systems during arithmetic and temporal transformations in working memory. J Neurosci 27(49):13393–13401. https://doi.org/10.1523/JNEUROSCI.4041-07.2007
Thompson PM, Hayashi KM, Simon SL, Geaga JA, Hong MS, Sui Y, Lee JY, Toga AW, Ling W, London ED (2004) Structural abnormalities in the brains of human subjects who use methamphetamine. J Neurosci 24(26):6028–6036. https://doi.org/10.1523/JNEUROSCI.0713-04.2004
Tomasi D, Volkow ND (2010) Functional connectivity density mapping. Proc Natl Acad Sci USA 107(21):9885–9890. https://doi.org/10.1073/pnas.1001414107
Tomasi D, Volkow ND (2011) Association between functional connectivity hubs and brain networks. Cereb Cortex 21(9):2003–2013. https://doi.org/10.1093/cercor/bhq268
Tsang J, Fullard JF, Giakoumaki SG, Katsel P, Eirini Karagiorga V, Greenwood TA, Braff DL, Siever LJ, Bitsios P, Haroutunian V, Roussos P (2015) Erratum: the relationship between dopamine receptor D1 and cognitive performance. NPJ Schizophr 1:15018. https://doi.org/10.1038/npjschz.2015.18
Tunbridge EM, Farrell SM, Harrison PJ, Mackay CE (2013) Catechol-O-methyltransferase (COMT) influences the connectivity of the prefrontal cortex at rest. Neuroimage 68:49–54. https://doi.org/10.1016/j.neuroimage.2012.11.059
Wang Y, Hu Y, Fang Y, Zhang K, Yang H, Ma J, Xu Q, Shen Y (2009) Evidence of epistasis between the catechol-O-methyltransferase and aldehyde dehydrogenase 3B1 genes in paranoid schizophrenia. Biol Psychiatry 65 (12):1048–1054. https://doi.org/10.1016/j.biopsych.2008.11.027
Xu J, Qin W, Liu B, Jiang T, Yu C (2016) Interactions of genetic variants reveal inverse modulation patterns of dopamine system on brain gray matter volume and resting-state functional connectivity in healthy young adults. Brain Struct Funct 221(8):3891–3901. https://doi.org/10.1007/s00429-015-1134-4
Yan CG, Cheung B, Kelly C, Colcombe S, Craddock RC, Di Martino A, Li Q, Zuo XN, Castellanos FX, Milham MP (2013) A comprehensive assessment of regional variation in the impact of head micromovements on functional connectomics. Neuroimage 76:183–201. https://doi.org/10.1016/j.neuroimage.2013.03.004
Yi P, Chen Z, Zhao Y, Guo J, Fu H, Zhou Y, Yu L, Li L (2009) PCR/LDR/capillary electrophoresis for detection of single-nucleotide differences between fetal and maternal DNA in maternal plasma. Prenat Diagn 29(3):217–222. https://doi.org/10.1002/pd.2072
Acknowledgements
The authors thank the members of the Brainnetome Center of Institute of Automation of Chinese Academy of Sciences for the collection of data.
Funding
This research was supported by the National Key Research and Development Program of China (Grant No. 2018YFC1314301) and the Natural Science Foundation of China (grant numbers: 81425013, 81501451 and 81301201).
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no conflict of interest.
Ethical approval
All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.
Informed consent
Informed consent was obtained from all individual participants included in the study.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Rights and permissions
About this article
Cite this article
Tang, J., Li, Y., Xu, J. et al. Impact of COMT haplotypes on functional connectivity density and its association with the gene expression of dopamine receptors. Brain Struct Funct 224, 2619–2630 (2019). https://doi.org/10.1007/s00429-019-01924-7
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00429-019-01924-7