Abstract
Several GWAS reported Myocyte Enhancer Factor 2 C (MEF2C) gene associations with white matter microstructure and psychiatric disorders, and MEF2C involvement in pathways related to neuronal development suggests a common biological factor underlying these phenotypes. We aim to refine the MEF2C effects in the brain relying on an integrated analysis of white matter and psychiatric phenotypes in an extensively characterized sample. This study included 870 Brazilian adults (47% from an attention-deficit/hyperactivity disorder outpatient clinic) assessed through standardized psychiatric interviews, 139 of which underwent a magnetic resonance imaging scan. We evaluated variants in the MEF2C region using two approaches: 1) a gene-wide analysis, which uses the sum of polymorphism effects, and 2) SNP analyses, restricted to the independent variants within the gene. The outcomes included psychiatric phenotypes and fractional anisotropy for brain images. Results: The gene-wide analyses pointed to a nominal association between MEF2C and the Temporal Portion of the Superior Longitudinal Fasciculus (SLFTEMP). The SNP analysis identified four independent variants significantly associated with SLFTEMP and one (rs4218438) with Substance Use Disorder. Our findings showing specific associations of MEF2C variants with temporal−frontal circuitry components may help to elucidate how the MEF2C gene underlies a broad range of psychiatric phenotypes since these regions are relevant to executive and cognitive functions.
Similar content being viewed by others
Data availability
Our data is available under request.
References
APA. 2013. Diagnostic and Statistical Manual of Mental Disorders (5th Eds). Arlington, VA: American Psychiatric Association
Barbu MC, Zeng Y, Shen X, Cox SR, Clarke TK, Gibson J, Adams MJ et al (2019) Association of whole-genome and netrin1 signaling pathway-derived polygenic risk scores for major depressive disorder and white matter microstructure in the uk biobank. Biol Psychiat Cogn Neurosci Neuroimag 4(1):91–100. https://doi.org/10.1016/J.BPSC.2018.07.006
Basser PJ (1995) Inferring microstructural features and the physiological state of tissues from diffusion-weighted images. NMR Biomed 8:333–344
Bihan DL, Mangin JF, Poupon C, Clark CA, Pappata S, Molko N, Chabriat H (2001) Diffusion tensor imaging: concepts and applications. J Mag Res Imag. 13(4):534–546
Boyle AP, Hong EL, Hariharan M, Cheng Y, Schaub MA, Kasowski M, Karczewski KJ et al (2012) Annotation of functional variation in personal genomes using regulomeDB. Genome Res 22(9):1790–1797. https://doi.org/10.1101/gr.137323.112
Chang CC, Chow CC, Tellier LCAM., Vattikuti S, Purcell SM, Lee JJ (2015) Second-generation PLINK rising to the challenge of larger and richer datasets. GigaScience. https://doi.org/10.1186/s13742-015-0047-8
Ching CRK., Hibar DP, Gurholt TP, Nunes A, Thomopoulos SI, Abé C, Agartz I et al (2020) What we learn about bipolar disorder from large-scale neuroimaging: findings and future directions from the enigma bipolar disorder working group. Hum Brain Mapp. https://doi.org/10.1002/hbm.25098
Damatac CG, Chauvin RJM., Zwiers MP, van Rooij D, Akkermans SEA., Naaijen J, Hoekstra PJ et al (2020) White matter microstructure in attention-deficit/hyperactivity disorder a systematic tractography study in 654 Individuals. Biol Psychiat Cogn Neurosci Neuro. https://doi.org/10.1016/j.bpsc.2020.07.015
Deczkowska A, Matcovitch-Natan O, Tsitsou-Kampeli A, Ben-Hamo S, Dvir-Szternfeld R, Spinrad A, Singer O et al (2017) Mef2C restrains microglial inflammatory response and is lost in brain ageing in an ifn-i-dependent manner. Nature Commun. https://doi.org/10.1038/s41467-017-00769-0
Demontis D, Bragi Walters G, Athanasiadis G, Walters R, Therrien K, Farajzadeh L, Voloudakis G et al (2022) Genome-wide analyses of ADHD identify 27 risk loci, REFINE the genetic architecture and implicate several cognitive domains. MedRxiv 02:22270780
Demontis D, Walters RK, Martin J, Mattheisen M, Als TD, Agerbo E, Baldursson G et al (2019) Discovery of the first genome-wide significant risk loci for attention deficit/hyperactivity disorder. Nat Genet 51(1):63–75. https://doi.org/10.1038/s41588-018-0269-7
Dong C, Yang XZ, Zhang CY, Liu YY, Zhou RB, Di Cheng Q, Yan EK, Yin DC (2017) Myocyte enhancer factor 2C and Its directly-interacting proteins: A review. Prog Biophys Mol Biol 126:22–30. https://doi.org/10.1016/j.pbiomolbio.2017.02.002
First MB, Spitzer RL, Gibbon M, Williams JBW (1998) Structured clinical interview for dsm-iv axis i disorders. In: Din M (ed) Research Version, Patient Edition (SCID-I/P). Biometrics Research, Biometrics Research. New York
First, Michael B, Janet B W Williams, Rhonda S Karg, and Robert L Spitzer. 2015. Structured Clinical Interview for DSM-5—Research Version (SCID-5 for DSM-5, Research Version; SCID-5-RV). Arlington. American Psychiatric Association. 1–94.
Gao X, Haritunians T, Marjoram P, Mckean-Cowdin R, Torres M, Taylor KD, Rotter JI, Gauderman WJ, Varma R (2012) Genotype imputation for latinos using the hapmap and 1000 genomes project reference panels. Front Genet. https://doi.org/10.3389/FGENE.2012.00117
Grevet EH, Bau CHD, Salgado CAI, Ficher A, Victor MM, Garcia C, Sousa NOD, Nerung L, Belmonte-De-Abreu P (2005) Interrater reliability for diagnosis in adults of attention deficit hyperactivity disorder and oppositional defiant disorder using K-SADS-E. Arq Neuropsiquiatr 63(2):307–310. https://doi.org/10.1590/s0004-282x2005000200019
Guimarães-da-Silva PO, Rovaris DL, Silva KL, Karam RG, Rohde LA, Grevet EH, Bau CHD (2018) Exploring neuropsychological predictors of ADHD remission or persistence during adulthood. Cogn Neuropsych 23(5):321–328. https://doi.org/10.1080/13546805.2018.1506324
Hampton W, Hanik I, Olson I (2019) Substance abuse and white matter: findings, limitations, and future of diffusion tensor imaging research. Drug Alcohol Depend 197:288–298. https://doi.org/10.1016/j.drugalcdep.2019.02.005.Substance
Howard DM, Adams MJ, Clarke TK, Hafferty JD, Gibson J, Shirali M, Coleman JRI et al (2019) Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions. Nat Neurosci 22(3):343–352. https://doi.org/10.1038/s41593-018-0326-7
Huo Y, Li S, Liu J, Li X, Luo XJ (2019) Functional genomics reveal gene regulatory mechanisms underlying schizophrenia risk. Nature Commun. https://doi.org/10.1038/s41467-019-08666-4
Kamali A, Flanders AE, Brody J, Hunter JV, Hasan KM (2014) Tracing superior longitudinal fasciculus connectivity in the human brain using high resolution diffusion tensor tractography. Brain Struct Funct 219(1):269–281. https://doi.org/10.1007/s00429-012-0498-y
Karam RG, Breda V, Picon FA, Rovaris DL, Victor MM, Salgado CAI, Vitola ES et al (2015) Persistence and remission of adhd during adulthood: A 7-Year clinical follow-up study. Psychol Med 45(10):2045–2056. https://doi.org/10.1017/S0033291714003183
Karam RG, Rovaris DL, Breda V, Picon FA, Victor MM, Salgado CAI, Vitola ES et al (2017) Trajectories of attention-deficit/hyperactivity disorder dimensions in adults. Acta Psychiatr Scand 136(2):210–219. https://doi.org/10.1111/ACPS.12757
Kelly S, Jahanshad N, Zalesky A, Kochunov P, Agartz I, Alloza C, Andreassen OA et al (2018) Widespread white matter microstructural differences in schizophrenia across 4322 individuals: results from the enigma schizophrenia dti working group. Mol Psychiatry 23(5):1261–1269. https://doi.org/10.1038/mp.2017.170
Kessler RC (2005) The world health organization adult adhd self-repoprt scale (asrs): a short screening scale for use in the general population. Psychol Med 35:245–256
Lahiri DK, Nurnberger JI (1991) A rapid non-enzymatic method for the preparation of HMW DNA from blood for rflp studies. Nucleic Acid Res 19(19):5444
Lee JJ, Wedow R, Okbay A, Kong E, Maghzian O, Zacher M, Nguyen-Viet TA et al (2018) Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals. Nat Genet 50(8):1112–1121. https://doi.org/10.1038/s41588-018-0147-3
Lee PH, Anttila V, Won H, Yen CA, Feng JR, Zhu Z, Tucker-Drob EM et al (2019) Genomic relationships, novel loci, and pleiotropic mechanisms across eight psychiatric disorders. Cell 179(7):1469-1482.e11. https://doi.org/10.1016/j.cell.2019.11.020
Lesch KP (2019) Editorial: can dysregulated myelination be linked to ADHD pathogenesis and persistence? J Child Psychol Psychiatry 60(3):229–231. https://doi.org/10.1111/jcpp.13031
Linnér K, Richard PB, Edward Kong S, Meddens FW, Wedow R, Fontana MA, Lebreton M et al (2019) Genome-wide association analyses of risk tolerance and risky behaviors in over 1 million individuals identify hundreds of loci and shared genetic influences. Nat Genet 51(2):245–257. https://doi.org/10.1038/s41588-018-0309-3
Machiela MJ, Chanock SJ (2015) LDlink: A web-based application for exploring population-specific haplotype structure and linking correlated alleles of possible functional variants. Bioinform 31(21):3555–3557. https://doi.org/10.1093/BIOINFORMATICS/BTV402
Maurizio B, Farmer M, Shenton ME, Paul Hamilton J (2016) Applying a free-water correction to diffusion imaging data uncovers stress-related neural pathology in depression. NeuroImage Clinical. 10:336–342
Maldonado G, Greenland S (1993) Simulation study of confounder-selection strategies. Am J Epidemiol 138(11):923–936. https://doi.org/10.1093/oxfordjournals.aje.a116813
Mercadante, M T, Asbarh, F., Rosário, M. C., Ayres, A. M., Ferrari, M. C., Assumpção, F. B., & Miguel, E. C. 1995. “K-SADS, Entrevista Semi-Estruturada Para Diagnóstico Em Psiquiatria Da Infância, Versão Epidemiológica.” São Paulo: PROTOC-Hospital Das Clínicas Da FMUSP.
Meur N, Le M, Holder-Espinasse S, Jaillard A, Goldenberg S, Joriot P, Amati-Bonneau AG et al (2010) MEF2C haploinsufficiency caused by either microdeletion of the 5q14.3 region or mutation is responsible for severe mental retardation with stereotypic movements, epilepsy and/or cerebral malformations. J Med Genet 47(1):22–29. https://doi.org/10.1136/jmg.2009.069732
Mori S, Van Zijl P, Tamminga CA (2007) Human white matter atlas. Am J Psychiatry 164(7):1005. https://doi.org/10.1176/ajp.2007.164.7.1005
Mufford MS, Stein DJ, Dalvie S, Groenewold NA, Thompson PM, Jahanshad N (2017) Neuroimaging genomics in psychiatry-a translational approach. Genome Medicine 9(1):1–12. https://doi.org/10.1186/s13073-017-0496-z
Ohki CM, Yde LG, Alber E, Dwivedi T, Berger G, Werling AM, Walitza S, Grünblatt E (2020) The stress–Wnt-signaling axis: a hypothesis for attention-deficit hyperactivity disorder and therapy approaches. Translat Psychiat. 10(1):1–12. https://doi.org/10.1038/s41398-020-00999-9
Okbay A, Beauchamp JP, Fontana MA, Lee JJ, Pers TH, Rietveld CA, Turley P et al (2016) Genome-wide association study identifies 74 loci associated with educational attainment. Nature 533(7604):539–542. https://doi.org/10.1038/nature17671
Potthoff MJ, Olson EN (2007) A central regulator of diverse developmental programs. Development 4140:4131–4140. https://doi.org/10.1242/dev.008367
Ripke S, Neale BM, Corvin A, Walters JTR, Farh K-H, Holmans PA, Lee P et al (2014) Biological Insights from 108 Schizophrenia-Associated Genetic Loci. Nature 511(7510):421–427. https://doi.org/10.1038/nature13595
Rocha H, Sampaio M, Rocha R, Fernandes S, Leão M (2016) MEF2C Haploinsufficiency Syndrome: Report of a New MEF2C Mutation and Review. Eur J Med Genet 59(9):478–482. https://doi.org/10.1016/j.ejmg.2016.05.017
Rovira, Paula, Ditte Demontis, Cristina Sánchez-mora, and Tetyana Zayats. 2019. Shared Genetic Background between Children and Adults with Attention Deficit/Hyperactivity Disorder.
Ruderfer DM, Fanous AH, Ripke S, McQuillin A, Amdur RL, Gejman PV, O’Donovan MC et al (2014) Polygenic dissection of diagnosis and clinical dimensions of bipolar disorder and schizophrenia. Mol Psychiatry 19(9):1017–1024. https://doi.org/10.1038/MP.2013.138
Sáenz A, Ariadna TV, Massat I (2019) Structural and functional neuroimaging in attention-deficit/hyperactivity disorder. Dev Med Child Neurol 61(4):399–405. https://doi.org/10.1111/dmcn.14050
Savage JE, Jansen PR, Stringer S, Watanabe K, Bryois J, De Leeuw CA, Nagel M et al (2018) Genome-wide association meta-analysis in 269,867 individuals identifies new genetic and functional links to intelligence. Nat Genet 50(7):912–919. https://doi.org/10.1038/s41588-018-0152-6
Schmahmann JD, Pandya DN, Wang R, Dai G, D’Arceuil HE, De Crespigny AJ, Wedeen VJ (2007) Association fibre pathways of the brain: parallel observations from diffusion spectrum imaging and autoradiography. Brain 130(3):630–653. https://doi.org/10.1093/brain/awl359
Shalizi AK, Bonni A (2005) Brawn for brains: the role of mef2 proteins in the developing nervous system. Curr Top Dev Biol 69(05):239–266. https://doi.org/10.1016/S0070-2153(05)69009-6
Sullivan PF, Geschwind DH (2019) Defining the genetic, genomic, cellular, and diagnostic architectures of psychiatric disorders. Cell 177(1):162–183. https://doi.org/10.1016/j.cell.2019.01.015
Velzen LS, Van SK, Isaev D, Aleman A, Aftanas LI, Bauer J, Baune BT et al (2020) White matter disturbances in major depressive disorder: a coordinated analysis across 20 international cohorts in the enigma mdd working group. Mol Psychiatry 25(7):1511–1525. https://doi.org/10.1038/s41380-019-0477-2
Wakana S, Caprihan A, Panzenboeck MM, Fallon JH, Perry M, Gollub RL, Hua K et al (2007) Reproducibility of quantitative tractography methods applied to cerebral white matter. Neuroimage 36(3):630–644. https://doi.org/10.1016/j.neuroimage.2007.02.049
Wang W, Qian S, Liu K, Li Bo, Li M, Xin K, Sun G (2016) Reduced white matter integrity and its correlation with clinical symptom in first-episode, treatment-naive generalized anxiety disorder. Behav Brain Res 314:159–164. https://doi.org/10.1016/j.bbr.2016.08.017
Ward LD, Kellis M (2012) “HaploReg: A resource for exploring chromatin states, conservation, and regulatory motif alterations within sets of genetically linked variants. Nucleic Acid Res. https://doi.org/10.1093/nar/gkr917
Watanabe A, Nakamae T, Sakai Y, Nishida S, Abe Y, Yamada K, Yokota I, Narumoto J (2018) The detection of white matter alterations in obsessive-compulsive disorder revealed by tracts constrained by underlying anatomy (TRACULA). Neuropsychiatr Dis Treat 14:1635–1643. https://doi.org/10.2147/NDT.S164058
Watanabe K, Stringer S, Frei O, Mirkov MU, de Leeuw C, Polderman TJC, van der Sluis S, Andreassen OA, Neale BM, Posthuma D (2019) A Global overview of pleiotropy and genetic architecture in complex traits. Nat Genet 51(9):1339–1348. https://doi.org/10.1038/s41588-019-0481-0
Westra HJ, Peters MJ, Esko T, Yaghootkar H, Schurmann C, Kettunen J, Christiansen MW et al (2013) Systematic identification of trans EQTLS as putative drivers of known disease associations. Nat Genet 45(10):1238–1243. https://doi.org/10.1038/ng.2756
Yates A, Wasiu Akanni M, Amode R, Barrell D, Billis K, Carvalho-Silva D, Cummins C et al (2016) Ensembl 2016. Nucleic Acids Res 44(D1):D710–D716. https://doi.org/10.1093/nar/gkv1157
Zhao B, Li T, Yang Y, Wang X, Luo T, Shan Y, Zhu Z et al (2021) Common genetic variation influencing human white matter microstructure. Science 372:6548. https://doi.org/10.1126/science.abf3736
Zhao B, Zhang J, Ibrahim JG, Luo T, Santelli RC, Li Y, Li T et al (2019) Large-Scale GWAS reveals genetic architecture of brain white matter microstructure and genetic overlap with cognitive and mental health traits (n = 17,706). Mol Psychiatry. https://doi.org/10.1038/s41380-019-0569-z
Acknowledgements
We would like to acknowledge the patients assessed in ProDAH-A and all its members. This study was financed by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brasil (CAPES, Finance Code 001) and FIPE-HCPA 160600, GPPG-HCPA 01-321. In addition to the financial support received from the Conselho Nacional de Desenvolvimento Científico e Tecnológico (Grants 466722/2014-1, 424041/2016-2, 426905/2016-2, 140853/2019-7), grant #2020/05652-0 São Paulo Research Foundation (FAPESP), and the Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul (Grants PqG-19/2551-0001731-6; PqG-19/2551-0001668-9). The funding agencies mentioned were not involved in study design, in the collection, analysis and interpretation of data, in the writing of the report or in the decision to submit the article for publication.
Author information
Authors and Affiliations
Contributions
MEAT and RBC designed the study, performed the data analysis, and prepared the first drafts of the manuscript. CEB, MEAT, and RBC collected and processed the neuroimaging data, providing essential contributions to these analyses. ESV, BSS, FAP, and DLR provided substantial contributions to data acquisition, analyses, and interpretation of the results. CAIS and ESV were responsible for the clinical assessment of the patients and helped with the evaluation of the clinical outcomes. RSS contributed to the manuscript preparation and editing. DLR, LAR, and EHG provided critical discussion and insights into the intellectual content of the manuscript. CHDB contributed to the conception and design of the study and participated in all its stages of its preparation. All authors carefully revised and approved the final version of this manuscript.
Corresponding author
Ethics declarations
Conflict of interest
The authors declare the following potential conflict of interest: Dr. Grevet was on the speaker’s bureau for Novartis and Shire for three years and received travel awards (air tickets and hotel accommodations) for participating in two psychiatric meetings from Shire and Novartis. Luis Augusto Rohde has received grant or research support from, served as a consultant to, and served on the speakers’ bureau of Aché, Bial, Medice, Novartis/Sandoz, Pfizer/Upjohn, and Shire/Takeda in the last three years. The ADHD and Juvenile Bipolar Disorder Outpatient Programs chaired by Dr Rohde have received unrestricted educational and research support from the following pharmaceutical companies in the last three years: Novartis/Sandoz and Shire/Takeda. Dr. Rohde has received authorship royalties from Oxford Press and ArtMedAll other authors declare that they have no conflict of interest.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
Below is the link to the electronic supplementary material.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
de Araujo Tavares, M.E., Cupertino, R.B., Bandeira, C.E. et al. Refining patterns of MEF2C effects in white matter microstructure and psychiatric features. J Neural Transm 130, 697–706 (2023). https://doi.org/10.1007/s00702-023-02626-5
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00702-023-02626-5