Structural deviations of the posterior fossa and the cerebellum and their cognitive links in a neurodevelopmental deletion syndrome.
Journal
Molecular psychiatry
ISSN: 1476-5578
Titre abrégé: Mol Psychiatry
Pays: England
ID NLM: 9607835
Informations de publication
Date de publication:
14 May 2024
14 May 2024
Historique:
received:
07
10
2022
accepted:
23
04
2024
revised:
16
04
2024
medline:
15
5
2024
pubmed:
15
5
2024
entrez:
14
5
2024
Statut:
aheadofprint
Résumé
High-impact genetic variants associated with neurodevelopmental disorders provide biologically-defined entry points for mechanistic investigation. The 3q29 deletion (3q29Del) is one such variant, conferring a 40-100-fold increased risk for schizophrenia, as well as high risk for autism and intellectual disability. However, the mechanisms leading to neurodevelopmental disability remain largely unknown. Here, we report the first in vivo quantitative neuroimaging study in individuals with 3q29Del (N = 24) and neurotypical controls (N = 1608) using structural MRI. Given prior radiology reports of posterior fossa abnormalities in 3q29Del, we focused our investigation on the cerebellum and its tissue-types and lobules. Additionally, we compared the prevalence of cystic/cyst-like malformations of the posterior fossa between 3q29Del and controls and examined the association between neuroanatomical findings and quantitative traits to probe gene-brain-behavior relationships. 3q29Del participants had smaller cerebellar cortex volumes than controls, before and after correction for intracranial volume (ICV). An anterior-posterior gradient emerged in finer grained lobule-based and voxel-wise analyses. 3q29Del participants also had larger cerebellar white matter volumes than controls following ICV-correction and displayed elevated rates of posterior fossa arachnoid cysts and mega cisterna magna findings independent of cerebellar volume. Cerebellar white matter and subregional gray matter volumes were associated with visual-perception and visual-motor integration skills as well as IQ, while cystic/cyst-like malformations yielded no behavioral link. In summary, we find that abnormal development of cerebellar structures may represent neuroimaging-based biomarkers of cognitive and sensorimotor function in 3q29Del, adding to the growing evidence identifying cerebellar pathology as an intersection point between syndromic and idiopathic forms of neurodevelopmental disabilities.
Identifiants
pubmed: 38744992
doi: 10.1038/s41380-024-02584-8
pii: 10.1038/s41380-024-02584-8
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : U.S. Department of Health & Human Services | National Institutes of Health (NIH)
ID : R01MH118534
Organisme : U.S. Department of Health & Human Services | National Institutes of Health (NIH)
ID : R01MH118534
Informations de copyright
© 2024. The Author(s).
Références
Iafrate AJ, Feuk L, Rivera MN, Listewnik ML, Donahoe PK, Qi Y, et al. Detection of large-scale variation in the human genome. Nat Genet. 2004;36:949–51.
pubmed: 15286789
doi: 10.1038/ng1416
Sebat J, Lakshmi B, Troge J, Alexander J, Young J, Lundin P, et al. Large-scale copy number polymorphism in the human genome. Science. 2004;305:525–8.
pubmed: 15273396
doi: 10.1126/science.1098918
Redon R, Ishikawa S, Fitch KR, Feuk L, Perry GH, Andrews TD, et al. Global variation in copy number in the human genome. Nature. 2006;444:444–54.
pubmed: 17122850
pmcid: 2669898
doi: 10.1038/nature05329
Korbel JO, Urban AE, Affourtit JP, Godwin B, Grubert F, Simons JF, et al. Paired-end mapping reveals extensive structural variation in the human genome. Science. 2007;318:420–6.
pubmed: 17901297
pmcid: 2674581
doi: 10.1126/science.1149504
Carvalho CM, Zhang F, Lupski JR. Structural variation of the human genome: mechanisms, assays, and role in male infertility. Syst Biol Reprod Med. 2011;57:3–16.
pubmed: 21210740
pmcid: 3179416
doi: 10.3109/19396368.2010.527427
Zhang F, Gu W, Hurles ME, Lupski JR. Copy number variation in human health, disease, and evolution. Annu Rev Genomics Hum Genet. 2009;10:451–81.
pubmed: 19715442
pmcid: 4472309
doi: 10.1146/annurev.genom.9.081307.164217
Marshall CR, Howrigan DP, Merico D, Thiruvahindrapuram B, Wu W, Greer DS, et al. Contribution of copy number variants to schizophrenia from a genome-wide study of 41,321 subjects. Nat Genet. 2017;49:27–35.
pubmed: 27869829
doi: 10.1038/ng.3725
Sanders SJ, He X, Willsey AJ, Ercan-Sencicek AG, Samocha KE, Cicek AE, et al. Insights into autism spectrum disorder genomic architecture and biology from 71 risk loci. Neuron. 2015;87:1215–33.
pubmed: 26402605
pmcid: 4624267
doi: 10.1016/j.neuron.2015.09.016
Leppa VM, Kravitz SN, Martin CL, Andrieux J, Le Caignec C, Martin-Coignard D, et al. Rare inherited and de novo CNVs reveal complex contributions to ASD risk in multiplex families. Am J Hum Genet. 2016;99:540–54.
pubmed: 27569545
pmcid: 5011063
doi: 10.1016/j.ajhg.2016.06.036
Sebat J, Lakshmi B, Malhotra D, Troge J, Lese-Martin C, Walsh T, et al. Strong association of de novo copy number mutations with autism. Science. 2007;316:445–9.
pubmed: 17363630
pmcid: 2993504
doi: 10.1126/science.1138659
Girirajan S, Brkanac Z, Coe BP, Baker C, Vives L, Vu TH, et al. Relative burden of large CNVs on a range of neurodevelopmental phenotypes. PLoS Genet. 2011;7:e1002334.
pubmed: 22102821
pmcid: 3213131
doi: 10.1371/journal.pgen.1002334
Cooper GM, Coe BP, Girirajan S, Rosenfeld JA, Vu TH, Baker C, et al. A copy number variation morbidity map of developmental delay. Nat Genet. 2011;43:838–46.
pubmed: 21841781
pmcid: 3171215
doi: 10.1038/ng.909
Malhotra D, Sebat J. CNVs: harbingers of a rare variant revolution in psychiatric genetics. Cell. 2012;148:1223–41.
pubmed: 22424231
pmcid: 3351385
doi: 10.1016/j.cell.2012.02.039
Morris-Rosendahl DJ, Crocq MA. Neurodevelopmental disorders-the history and future of a diagnostic concept. Dialogues Clin Neurosci. 2020;22:65–72.
pubmed: 32699506
pmcid: 7365295
doi: 10.31887/DCNS.2020.22.1/macrocq
Zhang T, Koutsouleris N, Meisenzahl E, Davatzikos C. Heterogeneity of structural brain changes in subtypes of schizophrenia revealed using magnetic resonance imaging pattern analysis. Schizophr Bull. 2015;41:74–84.
pubmed: 25261565
doi: 10.1093/schbul/sbu136
Lenroot RK, Yeung PK. Heterogeneity within autism spectrum disorders: what have we learned from neuroimaging studies? Front Hum Neurosci. 2013;7:733.
pubmed: 24198778
pmcid: 3812662
doi: 10.3389/fnhum.2013.00733
Feczko E, Miranda-Dominguez O, Marr M, Graham AM, Nigg JT, Fair DA. The heterogeneity problem: approaches to identify psychiatric subtypes. Trends Cogn Sci. 2019;23:584–601.
pubmed: 31153774
pmcid: 6821457
doi: 10.1016/j.tics.2019.03.009
Sanchez Russo R, Gambello MJ, Murphy MM, Aberizk K, Black E, Burrell TL, et al. Deep phenotyping in 3q29 deletion syndrome: recommendations for clinical care. Genet Med. 2021;23:872–80.
pubmed: 33564151
pmcid: 8105170
doi: 10.1038/s41436-020-01053-1
Mosley TJ, Johnston HR, Cutler DJ, Zwick ME, Mulle JG. Sex-specific recombination patterns predict parent of origin for recurrent genomic disorders. BMC Med Genomics. 2021;14:154.
pubmed: 34107974
pmcid: 8190997
doi: 10.1186/s12920-021-00999-8
Klaiman C, White SP, Saulnier C, Murphy M, Burrell L, Cubells J, et al. A distinct cognitive profile in individuals with 3q29 deletion syndrome. J Intellect Disabil Res. 2023;67:216–27.
Pennington BF. From single to multiple deficit models of developmental disorders. Cognition. 2006;101:385–413.
pubmed: 16844106
doi: 10.1016/j.cognition.2006.04.008
Downing C, Caravolas M. Prevalence and cognitive profiles of children with comorbid literacy and motor disorders. Front Psychol. 2020;11:573580.
pubmed: 33362640
pmcid: 7759613
doi: 10.3389/fpsyg.2020.573580
Mulle JG. The 3q29 deletion confers >40-fold increase in risk for schizophrenia. Mol Psychiatry. 2015;20:1028–9.
pubmed: 26055425
pmcid: 4546529
doi: 10.1038/mp.2015.76
Levinson DF, Duan J, Oh S, Wang K, Sanders AR, Shi J, et al. Copy number variants in schizophrenia: confirmation of five previous findings and new evidence for 3q29 microdeletions and VIPR2 duplications. Am J Psychiatry. 2011;168:302–16.
pubmed: 21285140
pmcid: 4441324
doi: 10.1176/appi.ajp.2010.10060876
Mulle JG, Dodd AF, McGrath JA, Wolyniec PS, Mitchell AA, Shetty AC, et al. Microdeletions of 3q29 confer high risk for schizophrenia. Am J Hum Genet. 2010;87:229–36.
pubmed: 20691406
pmcid: 2917706
doi: 10.1016/j.ajhg.2010.07.013
Kirov G, Pocklington AJ, Holmans P, Ivanov D, Ikeda M, Ruderfer D, et al. De novo CNV analysis implicates specific abnormalities of postsynaptic signalling complexes in the pathogenesis of schizophrenia. Mol Psychiatry. 2012;17:142–53.
pubmed: 22083728
doi: 10.1038/mp.2011.154
Singh T, Poterba T, Curtis D, Akil H, Al Eissa M, Barchas JD, et al. Rare coding variants in ten genes confer substantial risk for schizophrenia. Nature. 2022;604:509–16.
pubmed: 35396579
pmcid: 9805802
doi: 10.1038/s41586-022-04556-w
Pollak RM, Murphy MM, Epstein MP, Zwick ME, Klaiman C, Saulnier CA, et al. Neuropsychiatric phenotypes and a distinct constellation of ASD features in 3q29 deletion syndrome: results from the 3q29 registry. Mol Autism. 2019;10:30.
pubmed: 31346402
pmcid: 6636128
doi: 10.1186/s13229-019-0281-5
Glassford MR, Rosenfeld JA, Freedman AA, Zwick ME, Mulle JG. Unique Rare Chromosome Disorder Support G. Novel features of 3q29 deletion syndrome: Results from the 3q29 registry. Am J Med Genet A. 2016;170 A:999–1006.
doi: 10.1002/ajmg.a.37537
Cox DM, Butler MG. A clinical case report and literature review of the 3q29 microdeletion syndrome. Clin Dysmorphol. 2015;24:89–94.
pubmed: 25714563
pmcid: 5125389
doi: 10.1097/MCD.0000000000000077
Sefik E, Purcell RH, Walker EF, Bassell GF, Mulle JG.Emory 3q P Convergent and distributed effects of the 3q29 deletion on the human neural transcriptome. Transl Psychiatry. 2021;11:357
pubmed: 34131099
pmcid: 8206125
doi: 10.1038/s41398-021-01435-2
Carroll LS, Williams HJ, Walters J, Kirov G, O’Donovan MC, Owen MJ. Mutation screening of the 3q29 microdeletion syndrome candidate genes DLG1 and PAK2 in schizophrenia. Am J Med Genet B Neuropsychiatr Genet. 2011;156B:844–9.
pubmed: 21850710
doi: 10.1002/ajmg.b.31231
Bosemani T, Orman G, Boltshauser E, Tekes A, Huisman TA, Poretti A. Congenital abnormalities of the posterior fossa. Radiographics. 2015;35:200–20.
pubmed: 25590398
doi: 10.1148/rg.351140038
Al-Holou WN, Terman S, Kilburg C, Garton HJ, Muraszko KM, Maher CO. Prevalence and natural history of arachnoid cysts in adults. J Neurosurg. 2013;118:222–31.
pubmed: 23140149
doi: 10.3171/2012.10.JNS12548
Al-Holou WN, Yew AY, Boomsaad ZE, Garton HJ, Muraszko KM, Maher CO. Prevalence and natural history of arachnoid cysts in children. J Neurosurg Pediatr. 2010;5:578–85.
pubmed: 20515330
doi: 10.3171/2010.2.PEDS09464
Rapoport M, van Reekum R, Mayberg H. The role of the cerebellum in cognition and behavior: a selective review. J Neuropsychiatry Clin Neurosci. 2000;12:193–8.
pubmed: 11001597
doi: 10.1176/jnp.12.2.193
Wang SS, Kloth AD, Badura A. The cerebellum, sensitive periods, and autism. Neuron. 2014;83:518–32.
pubmed: 25102558
pmcid: 4135479
doi: 10.1016/j.neuron.2014.07.016
Koziol LF, Budding D, Andreasen N, D’Arrigo S, Bulgheroni S, Imamizu H, et al. Consensus paper: the cerebellum’s role in movement and cognition. Cerebellum. 2014;13:151–77.
pubmed: 23996631
pmcid: 4089997
doi: 10.1007/s12311-013-0511-x
Schmahmann JD. The cerebellum and cognition. Neurosci Lett. 2019;688:62–75.
pubmed: 29997061
doi: 10.1016/j.neulet.2018.07.005
Cuthbert BN. The RDoC framework: facilitating transition from ICD/DSM to dimensional approaches that integrate neuroscience and psychopathology. World Psychiatry. 2014;13:28–35.
pubmed: 24497240
pmcid: 3918011
doi: 10.1002/wps.20087
Murphy MM, Lindsey Burrell T, Cubells JF, Espana RA, Gambello MJ, Goines KCB, et al. Study protocol for The Emory 3q29 Project: evaluation of neurodevelopmental, psychiatric, and medical symptoms in 3q29 deletion syndrome. BMC Psychiatry. 2018;18:183.
pubmed: 29884173
pmcid: 5994080
doi: 10.1186/s12888-018-1760-5
Bethlehem RAI, Seidlitz J, White SR, Vogel JW, Anderson KM, Adamson C, et al. Brain charts for the human lifespan. Nature. 2022;604:525–33.
pubmed: 35388223
pmcid: 9021021
doi: 10.1038/s41586-022-04554-y
White T, Andreasen NC, Nopoulos P. Brain volumes and surface morphology in monozygotic twins. Cereb Cortex. 2002;12:486–93.
pubmed: 11950766
doi: 10.1093/cercor/12.5.486
Blokland GA, de Zubicaray GI, McMahon KL, Wright MJ. Genetic and environmental influences on neuroimaging phenotypes: a meta-analytical perspective on twin imaging studies. Twin Res Hum Genet. 2012;15:351–71.
pubmed: 22856370
pmcid: 4291185
doi: 10.1017/thg.2012.11
Somerville LH, Bookheimer SY, Buckner RL, Burgess GC, Curtiss SW, Dapretto M, et al. The Lifespan Human Connectome Project in Development: A large-scale study of brain connectivity development in 5-21 year olds. Neuroimage. 2018;183:456–68.
pubmed: 30142446
doi: 10.1016/j.neuroimage.2018.08.050
Van Essen DC, Smith SM, Barch DM, Behrens TE, Yacoub E, Ugurbil K, et al. The WU-Minn Human Connectome Project: an overview. Neuroimage. 2013;80:62–79.
pubmed: 23684880
doi: 10.1016/j.neuroimage.2013.05.041
Mugler JP 3rd, Brookeman JR. Three-dimensional magnetization-prepared rapid gradient-echo imaging (3D MP RAGE). Magn Reson Med. 1990;15:152–7.
pubmed: 2374495
doi: 10.1002/mrm.1910150117
Mugler JP 3rd, Bao S, Mulkern RV, Guttmann CR, Robertson RL, Jolesz FA, et al. Optimized single-slab three-dimensional spin-echo MR imaging of the brain. Radiology. 2000;216:891–9.
pubmed: 10966728
doi: 10.1148/radiology.216.3.r00au46891
Harms MP, Somerville LH, Ances BM, Andersson J, Barch DM, Bastiani M, et al. Extending the Human Connectome Project across ages: Imaging protocols for the Lifespan Development and Aging projects. Neuroimage. 2018;183:972–84.
pubmed: 30261308
doi: 10.1016/j.neuroimage.2018.09.060
Van Essen DC, Ugurbil K, Auerbach E, Barch D, Behrens TE, Bucholz R, et al. The Human Connectome Project: a data acquisition perspective. Neuroimage. 2012;62:2222–31.
pubmed: 22366334
doi: 10.1016/j.neuroimage.2012.02.018
Glasser MF, Sotiropoulos SN, Wilson JA, Coalson TS, Fischl B, Andersson JL, et al. The minimal preprocessing pipelines for the Human Connectome Project. Neuroimage. 2013;80:105–24.
pubmed: 23668970
doi: 10.1016/j.neuroimage.2013.04.127
Fischl B, Salat DH, Busa E, Albert M, Dieterich M, Haselgrove C, et al. Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain. Neuron. 2002;33:341–55.
pubmed: 11832223
doi: 10.1016/S0896-6273(02)00569-X
Mayer KN, Latal B, Knirsch W, Scheer I, von Rhein M, Reich B, et al. Comparison of automated brain volumetry methods with stereology in children aged 2 to 3 years. Neuroradiology. 2016;58:901–10.
pubmed: 27380040
doi: 10.1007/s00234-016-1714-x
Dewey J, Hana G, Russell T, Price J, McCaffrey D, Harezlak J, et al. Reliability and validity of MRI-based automated volumetry software relative to auto-assisted manual measurement of subcortical structures in HIV-infected patients from a multisite study. Neuroimage. 2010;51:1334–44.
pubmed: 20338250
doi: 10.1016/j.neuroimage.2010.03.033
Carass A, Cuzzocreo JL, Han S, Hernandez-Castillo CR, Rasser PE, Ganz M, et al. Comparing fully automated state-of-the-art cerebellum parcellation from magnetic resonance images. Neuroimage. 2018;183:150–72.
pubmed: 30099076
doi: 10.1016/j.neuroimage.2018.08.003
Han S, Carass A, He Y, Prince JL. Automatic cerebellum anatomical parcellation using U-Net with locally constrained optimization. Neuroimage. 2020;218:116819.
pubmed: 32438049
doi: 10.1016/j.neuroimage.2020.116819
Diedrichsen J. A spatially unbiased atlas template of the human cerebellum. Neuroimage. 2006;33:127–38.
pubmed: 16904911
doi: 10.1016/j.neuroimage.2006.05.056
Diedrichsen J, Balsters JH, Flavell J, Cussans E, Ramnani N. A probabilistic MR atlas of the human cerebellum. Neuroimage. 2009;46:39–46.
pubmed: 19457380
doi: 10.1016/j.neuroimage.2009.01.045
Kerestes R, Han S, Balachander S, Hernandez-Castillo C, Prince JL, Diedrichsen J, et al. A standardized pipeline for examining human cerebellar grey matter morphometry using structural magnetic resonance imaging. J Vis Exp. 2022;180 https://doi.org/10.3791/63340 .
O’Brien LM, Ziegler DA, Deutsch CK, Frazier JA, Herbert MR, Locascio JJ. Statistical adjustments for brain size in volumetric neuroimaging studies: some practical implications in methods. Psychiatry Res. 2011;193:113–22.
pubmed: 21684724
pmcid: 3510982
doi: 10.1016/j.pscychresns.2011.01.007
Ueda K, Fujiwara H, Miyata J, Hirao K, Saze T, Kawada R, et al. Investigating association of brain volumes with intracranial capacity in schizophrenia. Neuroimage. 2010;49:2503–8.
pubmed: 19770046
doi: 10.1016/j.neuroimage.2009.09.006
Davis P, Wright E. A new method for measuring cranial cavity volume and its application to the assessment of cerebral atrophy at autopsy. Neuropathology and applied neurobiology. 1977;3:341–58.
doi: 10.1111/j.1365-2990.1977.tb00595.x
Voevodskaya O, Simmons A, Nordenskjold R, Kullberg J, Ahlstrom H, Lind L, et al. The effects of intracranial volume adjustment approaches on multiple regional MRI volumes in healthy aging and Alzheimer’s disease. Front Aging Neurosci. 2014;6:264.
pubmed: 25339897
pmcid: 4188138
doi: 10.3389/fnagi.2014.00264
Mathalon DH, Sullivan EV, Rawles JM, Pfefferbaum A. Correction for head size in brain-imaging measurements. Psychiatry Res. 1993;50:121–39.
pubmed: 8378488
doi: 10.1016/0925-4927(93)90016-B
Kollias SS, Ball WS Jr., Prenger EC. Cystic malformations of the posterior fossa: differential diagnosis clarified through embryologic analysis. Radiographics. 1993;13:1211–31.
pubmed: 8031352
doi: 10.1148/radiographics.13.6.8031352
McKinney AM. Mega Cisterna Magna and Retrocerebellar Arachnoid Cysts. Atlas of Normal Imaging Variations of the Brain, Skull, and Craniocervical Vasculature: Springer; 2017. 19-41.
Elliott CD. Differential abilities scales. 2 ed. San Antonio, TX: Harcourt Assessment; 2007.
Wechsler D Wechsler abbreviated scale of intelligence. 2 ed. Bloomington, MN: Pearson; 2011.
Beery KE, Buktenica NA, Beery NA. The Beery–Buktenica Developmental Test of Visual–Motor Integration: Administration, scoring, and teaching manual. 6 ed. Minneapolis, MN: Pearson; 2010.
R Development Core Team. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing; 2021.
MacKinnon JG, White H. Some heteroskedasticity-consistent covariance matrix estimators with improved finite sample properties. Journal of econometrics. 1985;29:305–25.
doi: 10.1016/0304-4076(85)90158-7
Kim TG, Kim DS, Choi JU. Are arachnoid cysts localized hydrocephali? Pediatr Neurosurg. 2010;46:362–7.
pubmed: 21389748
doi: 10.1159/000321597
Choi JU, Kim DS. Pathogenesis of arachnoid cyst: congenital or traumatic? Pediatr Neurosurg. 1998;29:260–6.
pubmed: 9917544
doi: 10.1159/000028733
Greene S, Ellenbogen RG. Congenital Malformations of the Brain and Spinal Cord. Pediatric Critical Care Mosby-Year Book (St Louis). 2005.
Citta S, Buono S, Greco D, Barone C, Alfei E, Bulgheroni S, et al. 3q29 microdeletion syndrome: Cognitive and behavioral phenotype in four patients. Am J Med Genet A. 2013;161:3018–22.
doi: 10.1002/ajmg.a.36142
Sargent C, Burn J, Baraitser M, Pembrey ME. Trigonocephaly and the Opitz C syndrome. J Med Genet. 1985;22:39–45.
pubmed: 3981579
pmcid: 1049376
doi: 10.1136/jmg.22.1.39
Nawa Y, Kushima I, Aleksic B, Yamamoto M, Kimura H, Banno M, et al. Treatment-resistant schizophrenia in patients with 3q29 deletion: A case series of four patients. Psychiatry Clin Neurosci. 2022;76:338–9.
pubmed: 35355370
doi: 10.1111/pcn.13361
van Essen MJ, Nayler S, Becker EBE, Jacob J. Deconstructing cerebellar development cell by cell. PLoS Genet. 2020;16:e1008630.
pubmed: 32298260
pmcid: 7161948
doi: 10.1371/journal.pgen.1008630
Gill JS, Sillitoe RV. Functional outcomes of cerebellar malformations. Front Cell Neurosci. 2019;13:441.
pubmed: 31636540
pmcid: 6787289
doi: 10.3389/fncel.2019.00441
Tiemeier H, Lenroot RK, Greenstein DK, Tran L, Pierson R, Giedd JN. Cerebellum development during childhood and adolescence: a longitudinal morphometric MRI study. Neuroimage. 2010;49:63–70.
pubmed: 19683586
doi: 10.1016/j.neuroimage.2009.08.016
Wierenga LM, Bos MGN, Schreuders E, Vd Kamp F, Peper JS, Tamnes CK, et al. Unraveling age, puberty and testosterone effects on subcortical brain development across adolescence. Psychoneuroendocrinology. 2018;91:105–14.
pubmed: 29547741
doi: 10.1016/j.psyneuen.2018.02.034
Wierenga L, Langen M, Ambrosino S, van Dijk S, Oranje B, Durston S. Typical development of basal ganglia, hippocampus, amygdala and cerebellum from age 7 to 24. Neuroimage. 2014;96:67–72.
pubmed: 24705201
doi: 10.1016/j.neuroimage.2014.03.072
Ostby Y, Tamnes CK, Fjell AM, Westlye LT, Due-Tonnessen P, Walhovd KB. Heterogeneity in subcortical brain development: A structural magnetic resonance imaging study of brain maturation from 8 to 30 years. J Neurosci. 2009;29:11772–82.
pubmed: 19776264
pmcid: 6666647
doi: 10.1523/JNEUROSCI.1242-09.2009
Wu KH, Chen CY, Shen EY. The cerebellar development in chinese children-a study by voxel-based volume measurement of reconstructed 3D MRI scan. Pediatr Res. 2011;69:80–3.
pubmed: 20924316
doi: 10.1203/PDR.0b013e3181ff2f6c
Sussman D, Leung RC, Chakravarty MM, Lerch JP, Taylor MJ. The developing human brain: age-related changes in cortical, subcortical, and cerebellar anatomy. Brain Behav. 2016;6:e00457.
pubmed: 27066310
pmcid: 4802426
doi: 10.1002/brb3.457
Romero JE, Coupe P, Lanuza E, Catheline G, Manjon JV. Alzheimer’s Disease Neuroimaging I. Toward a unified analysis of cerebellum maturation and aging across the entire lifespan: A MRI analysis. Hum Brain Mapp. 2021;42:1287–303.
pubmed: 33385303
pmcid: 7927303
doi: 10.1002/hbm.25293
Bray S, Krongold M, Cooper C, Lebel C. Synergistic effects of age on patterns of white and gray matter volume across childhood and adolescence. eNeuro. 2015;2:ENEURO.0003–15.2015.
Hallonet MER, Le Douarin NM. Tracing neuroepithelial cells of the mesencephalic and metencephalic alar plates during cerebellar ontogeny in quail – chick chimaeras. Eur J Neurosci. 1993;5:1145–55.
pubmed: 8281319
doi: 10.1111/j.1460-9568.1993.tb00969.x
Hallonet ME, Teillet MA, Le Douarin NM. A new approach to the development of the cerebellum provided by the quail-chick marker system. Development. 1990;108:19–31.
pubmed: 2351063
doi: 10.1242/dev.108.1.19
Xu F, Ge X, Shi Y, Zhang Z, Tang Y, Lin X, et al. Morphometric development of the human fetal cerebellum during the early second trimester. Neuroimage. 2020;207:116372.
pubmed: 31751665
doi: 10.1016/j.neuroimage.2019.116372
Kozareva V, Martin C, Osorno T, Rudolph S, Guo C, Vanderburg C, et al. A transcriptomic atlas of mouse cerebellar cortex comprehensively defines cell types. Nature. 2021;598:214–9.
pubmed: 34616064
pmcid: 8494635
doi: 10.1038/s41586-021-03220-z
Choe KY, Sanchez CF, Harris NG, Otis TS, Mathews PJ. Optogenetic fMRI and electrophysiological identification of region-specific connectivity between the cerebellar cortex and forebrain. Neuroimage. 2018;173:370–83.
pubmed: 29496611
doi: 10.1016/j.neuroimage.2018.02.047
Trampush JW, Yang MLZ, Yu J, Knowles E, Davies G, Liewald DC, et al. GWAS meta-analysis reveals novel loci and genetic correlates for general cognitive function: a report from the COGENT consortium. Mol Psychiatry. 2017;22:1651–2.
pubmed: 29068436
pmcid: 5659072
doi: 10.1038/mp.2017.197
Hubbard L, Tansey KE, Rai D, Jones P, Ripke S, Chambert KD, et al. Evidence of Common Genetic Overlap Between Schizophrenia and Cognition. Schizophr Bull. 2016;42:832–42.
pubmed: 26678674
doi: 10.1093/schbul/sbv168
Hagenaars SP, Harris SE, Davies G, Hill WD, Liewald DC, Ritchie SJ, et al. Shared genetic aetiology between cognitive functions and physical and mental health in UK Biobank (N = 112 151) and 24 GWAS consortia. Mol Psychiatry. 2016;21:1624–32.
pubmed: 26809841
pmcid: 5078856
doi: 10.1038/mp.2015.225
Alexander-Bloch A, Huguet G, Schultz LM, Huffnagle N, Jacquemont S, Seidlitz J, et al. Copy number variant risk scores associated with cognition, psychopathology, and brain structure in youths in the philadelphia neurodevelopmental cohort. JAMA Psychiatry. 2022;79:699–709.
Neelam K, Garg D, Marshall M. A systematic review and meta-analysis of neurological soft signs in relatives of people with schizophrenia. BMC Psychiatry. 2011;11:139.
pubmed: 21859445
pmcid: 3173301
doi: 10.1186/1471-244X-11-139
Meyer-Lindenberg A, Weinberger DR. Intermediate phenotypes and genetic mechanisms of psychiatric disorders. Nat Rev Neurosci. 2006;7:818–27.
pubmed: 16988657
doi: 10.1038/nrn1993
Esposito G, Pasca SP. Motor abnormalities as a putative endophenotype for Autism Spectrum Disorders. Front Integr Neurosci. 2013;7:43.
pubmed: 23781177
pmcid: 3678087
doi: 10.3389/fnint.2013.00043
Bhat AN, Galloway JC, Landa RJ. Relation between early motor delay and later communication delay in infants at risk for autism. Infant Behav Dev. 2012;35:838–46.
pubmed: 22982285
pmcid: 3538350
doi: 10.1016/j.infbeh.2012.07.019
Walther S, van Harten PN, Waddington JL, Cuesta MJ, Peralta V, Dupin L, et al. Movement disorder and sensorimotor abnormalities in schizophrenia and other psychoses - European consensus on assessment and perspectives. Eur Neuropsychopharmacol. 2020;38:25–39.
pubmed: 32713718
doi: 10.1016/j.euroneuro.2020.07.003
Hirjak D, Kubera KM, Thomann PA, Wolf RC. Motor dysfunction as an intermediate phenotype across schizophrenia and other psychotic disorders: Progress and perspectives. Schizophr Res. 2018;200:26–34.
pubmed: 29074330
doi: 10.1016/j.schres.2017.10.007
Zhong Y, An L, Wang Y, Yang L, Cao Q. Functional abnormality in the sensorimotor system attributed to NRXN1 variants in boys with attention deficit hyperactivity disorder. Brain Imaging Behav. 2022;16:967–76.
pubmed: 34687402
doi: 10.1007/s11682-021-00579-5
Mosconi MW, Sweeney JA. Sensorimotor dysfunctions as primary features of autism spectrum disorders. Sci China Life Sci. 2015;58:1016–23.
pubmed: 26335740
pmcid: 5304941
doi: 10.1007/s11427-015-4894-4
MacLullich AM, Ferguson KJ, Deary IJ, Seckl JR, Starr JM, Wardlaw JM. Intracranial capacity and brain volumes are associated with cognition in healthy elderly men. Neurology. 2002;59:169–74.
pubmed: 12136052
doi: 10.1212/WNL.59.2.169
Farias ST, Mungas D, Reed B, Carmichael O, Beckett L, Harvey D, et al. Maximal brain size remains an important predictor of cognition in old age, independent of current brain pathology. Neurobiol Aging. 2012;33:1758–68.
pubmed: 21531482
doi: 10.1016/j.neurobiolaging.2011.03.017
Thier P, Dicke PW, Haas R, Thielert CD, Catz N. The role of the oculomotor vermis in the control of saccadic eye movements. Ann N Y Acad Sci. 2002;978:50–62.
pubmed: 12582041
doi: 10.1111/j.1749-6632.2002.tb07555.x
Takagi M, Zee DS, Tamargo RJ. Effects of lesions of the oculomotor cerebellar vermis on eye movements in primate: smooth pursuit. J Neurophysiol. 2000;83:2047–62.
pubmed: 10758115
doi: 10.1152/jn.2000.83.4.2047
MacLullich AM, Edmond CL, Ferguson KJ, Wardlaw JM, Starr JM, Seckl JR, et al. Size of the neocerebellar vermis is associated with cognition in healthy elderly men. Brain Cogn. 2004;56:344–8.
pubmed: 15522773
doi: 10.1016/j.bandc.2004.08.001
Badura A, Verpeut JL, Metzger JW, Pereira TD, Pisano TJ, Deverett B, et al. Normal cognitive and social development require posterior cerebellar activity. Elife. 2018;7:e36401.
Verpeut JL, Bergeler S, Kislin M, William Townes F, Klibaite U, Dhanerawala ZM, et al. Cerebellar contributions to a brainwide network for flexible behavior in mice. Commun Biol. 2023;6:605.
pubmed: 37277453
pmcid: 10241932
doi: 10.1038/s42003-023-04920-0
Pisano TJ, Dhanerawala ZM, Kislin M, Bakshinskaya D, Engel EA, Hansen EJ, et al. Homologous organization of cerebellar pathways to sensory, motor, and associative forebrain. Cell Rep. 2021;36:109721.
pubmed: 34551311
pmcid: 8506234
doi: 10.1016/j.celrep.2021.109721
Buckner RL, Krienen FM, Castellanos A, Diaz JC, Yeo BT. The organization of the human cerebellum estimated by intrinsic functional connectivity. J Neurophysiol. 2011;106:2322–45.
pubmed: 21795627
pmcid: 3214121
doi: 10.1152/jn.00339.2011
Stoodley CJ, Valera EM, Schmahmann JD. Functional topography of the cerebellum for motor and cognitive tasks: an fMRI study. Neuroimage. 2012;59:1560–70.
pubmed: 21907811
doi: 10.1016/j.neuroimage.2011.08.065
Guell X, Schmahmann JD, Gabrieli J, Ghosh SS. Functional gradients of the cerebellum. Elife. 2018;7:e36652.
Strick PL, Dum RP, Fiez JA. Cerebellum and nonmotor function. Annu Rev Neurosci. 2009;32:413–34.
pubmed: 19555291
doi: 10.1146/annurev.neuro.31.060407.125606
Schmahmann JD. The role of the cerebellum in cognition and emotion: personal reflections since 1982 on the dysmetria of thought hypothesis, and its historical evolution from theory to therapy. Neuropsychol Rev. 2010;20:236–60.
pubmed: 20821056
doi: 10.1007/s11065-010-9142-x
Van Overwalle F, Manto M, Cattaneo Z, Clausi S, Ferrari C, Gabrieli JDE, et al. Consensus paper: cerebellum and social cognition. Cerebellum. 2020;19:833–68.
pubmed: 32632709
pmcid: 7588399
doi: 10.1007/s12311-020-01155-1
Ito M. Movement and thought: identical control mechanisms by the cerebellum. Trends Neurosci. 1993;16:448–50. discussion 53-4.
pubmed: 7507615
doi: 10.1016/0166-2236(93)90073-U
Ito M. Control of mental activities by internal models in the cerebellum. Nat Rev Neurosci. 2008;9:304–13.
pubmed: 18319727
doi: 10.1038/nrn2332
Leiner HC, Leiner AL, Dow RS. The human cerebro-cerebellar system: its computing, cognitive, and language skills. Behav Brain Res. 1991;44:113–28.
pubmed: 1751002
doi: 10.1016/S0166-4328(05)80016-6
Popa LS, Hewitt AL, Ebner TJ. The cerebellum for jocks and nerds alike. Front Syst Neurosci. 2014;8:113.
pubmed: 24987338
pmcid: 4060457
doi: 10.3389/fnsys.2014.00113
Argyropoulos GPD, van Dun K, Adamaszek M, Leggio M, Manto M, Masciullo M, et al. The Cerebellar Cognitive Affective/Schmahmann Syndrome: a Task Force Paper. Cerebellum. 2020;19:102–25.
pubmed: 31522332
doi: 10.1007/s12311-019-01068-8
Ramnani N. The primate cortico-cerebellar system: anatomy and function. Nat Rev Neurosci. 2006;7:511–22.
pubmed: 16791141
doi: 10.1038/nrn1953
Kelly RM, Strick PL. Cerebellar loops with motor cortex and prefrontal cortex of a nonhuman primate. J Neurosci. 2003;23:8432–44.
pubmed: 12968006
pmcid: 6740694
doi: 10.1523/JNEUROSCI.23-23-08432.2003
Keser Z, Hasan KM, Mwangi BI, Kamali A, Ucisik-Keser FE, Riascos RF, et al. Diffusion tensor imaging of the human cerebellar pathways and their interplay with cerebral macrostructure. Front Neuroanat. 2015;9:41.
pubmed: 25904851
pmcid: 4389543
doi: 10.3389/fnana.2015.00041
Chen EKH, Ho SH, Desmond MH. JE. A meta-analysis of cerebellar contributions to higher cognition from PET and fMRI studies. Hum Brain Mapp. 2014;35:593–615.
pubmed: 23125108
doi: 10.1002/hbm.22194
King M, Hernandez-Castillo CR, Poldrack RA, Ivry RB, Diedrichsen J. Functional boundaries in the human cerebellum revealed by a multi-domain task battery. Nat Neurosci. 2019;22:1371–8.
pubmed: 31285616
pmcid: 8312478
doi: 10.1038/s41593-019-0436-x
Schmahmann JD, Sherman JC. Cerebellar cognitive affective syndrome. Int Rev Neurobiol. 1997;41:433–40.
pubmed: 9378601
doi: 10.1016/S0074-7742(08)60363-3
Schmahmann JD. Disorders of the cerebellum: ataxia, dysmetria of thought, and the cerebellar cognitive affective syndrome. J Neuropsychiatry Clin Neurosci. 2004;16:367–78.
pubmed: 15377747
doi: 10.1176/jnp.16.3.367
Levisohn L, Cronin-Golomb A, Schmahmann JD. Neuropsychological consequences of cerebellar tumour resection in children: cerebellar cognitive affective syndrome in a paediatric population. Brain. 2000;123:1041–50.
pubmed: 10775548
doi: 10.1093/brain/123.5.1041
Schmahmann JD, Macmore J, Vangel M. Cerebellar stroke without motor deficit: clinical evidence for motor and non-motor domains within the human cerebellum. Neuroscience. 2009;162:852–61.
pubmed: 19531371
doi: 10.1016/j.neuroscience.2009.06.023
Diedrichsen J, King M, Hernandez-Castillo C, Sereno M, Ivry RB. Universal transform or multiple functionality? understanding the contribution of the human cerebellum across task domains. Neuron. 2019;102:918–28.
pubmed: 31170400
pmcid: 6686189
doi: 10.1016/j.neuron.2019.04.021
Moberget T, Alnaes D, Kaufmann T, Doan NT, Cordova-Palomera A, Norbom LB, et al. Cerebellar gray matter volume is associated with cognitive function and psychopathology in adolescence. Biol Psychiatry. 2019;86:65–75.
pubmed: 30850129
doi: 10.1016/j.biopsych.2019.01.019
Romer AL, Knodt AR, Houts R, Brigidi BD, Moffitt TE, Caspi A, et al. Structural alterations within cerebellar circuitry are associated with general liability for common mental disorders. Mol Psychiatry. 2018;23:1084–90.
pubmed: 28397842
doi: 10.1038/mp.2017.57
Limperopoulos C, Bassan H, Gauvreau K, Robertson RL Jr, Sullivan NR, Benson CB, et al. Does cerebellar injury in premature infants contribute to the high prevalence of long-term cognitive, learning, and behavioral disability in survivors? Pediatrics. 2007;120:584–93.
pubmed: 17766532
doi: 10.1542/peds.2007-1041
Koning IV, Tielemans MJ, Hoebeek FE, Ecury-Goossen GM, Reiss IKM, Steegers-Theunissen RPM, et al. Impacts on prenatal development of the human cerebellum: a systematic review. J Matern Fetal Neonatal Med. 2017;30:2461–8.
pubmed: 27806674
doi: 10.1080/14767058.2016.1253060
Stoodley CJ. The Cerebellum and Neurodevelopmental Disorders. Cerebellum. 2016;15:34–7.
pubmed: 26298473
pmcid: 4811332
doi: 10.1007/s12311-015-0715-3
Moussa-Tooks AB, Rogers BP, Huang AS, Sheffield JM, Heckers S, Woodward ND. Cerebellar Structure and Cognitive Ability in Psychosis. Biol Psychiatry. 2022;92:385–95.
pubmed: 35680432
pmcid: 9378489
doi: 10.1016/j.biopsych.2022.03.013
Robinson EB, Lichtenstein P, Anckarsater H, Happe F, Ronald A. Examining and interpreting the female protective effect against autistic behavior. Proc Natl Acad Sci USA. 2013;110:5258–62.
pubmed: 23431162
pmcid: 3612665
doi: 10.1073/pnas.1211070110
Jacquemont S, Coe BP, Hersch M, Duyzend MH, Krumm N, Bergmann S, et al. A higher mutational burden in females supports a “female protective model” in neurodevelopmental disorders. Am J Hum Genet. 2014;94:415–25.
pubmed: 24581740
pmcid: 3951938
doi: 10.1016/j.ajhg.2014.02.001
De Rubeis S, He X, Goldberg AP, Poultney CS, Samocha K, Cicek AE, et al. Synaptic, transcriptional and chromatin genes disrupted in autism. Nature. 2014;515:209–15.
pubmed: 25363760
pmcid: 4402723
doi: 10.1038/nature13772
Haijma SV, Van Haren N, Cahn W, Koolschijn PC, Hulshoff Pol HE, Kahn RS. Brain volumes in schizophrenia: a meta-analysis in over 18 000 subjects. Schizophr Bull. 2013;39:1129–38.
pubmed: 23042112
doi: 10.1093/schbul/sbs118
Chambers T, Escott-Price V, Legge S, Baker E, Singh KD, Walters JTR, et al. Genetic common variants associated with cerebellar volume and their overlap with mental disorders: a study on 33,265 individuals from the UK-Biobank. Mol Psychiatry. 2022;27:2282–90.
Tsai PT, Hull C, Chu Y, Greene-Colozzi E, Sadowski AR, Leech JM, et al. Autistic-like behaviour and cerebellar dysfunction in Purkinje cell Tsc1 mutant mice. Nature. 2012;488:647–51.
pubmed: 22763451
pmcid: 3615424
doi: 10.1038/nature11310
Ellegood J, Anagnostou E, Babineau BA, Crawley JN, Lin L, Genestine M, et al. Clustering autism: using neuroanatomical differences in 26 mouse models to gain insight into the heterogeneity. Mol Psychiatry. 2015;20:118–25.
pubmed: 25199916
doi: 10.1038/mp.2014.98
Schmitt JE, DeBevits JJ, Roalf DR, Ruparel K, Gallagher RS, Gur RC, et al. A comprehensive analysis of cerebellar volumes in the 22q11.2 deletion syndrome. Biol Psychiatry Cogn Neurosci Neuroimaging. 2023;8:79–90.
Cupolillo D, Hoxha E, Faralli A, De Luca A, Rossi F, Tempia F, et al. Autistic-Like Traits and Cerebellar Dysfunction in Purkinje Cell PTEN Knock-Out Mice. Neuropsychopharmacology. 2016;41:1457–66.
pubmed: 26538449
doi: 10.1038/npp.2015.339
Modenato C, Kumar K, Moreau C, Martin-Brevet S, Huguet G, Schramm C, et al. Effects of eight neuropsychiatric copy number variants on human brain structure. Transl Psychiatry. 2021;11:399.
pubmed: 34285187
pmcid: 8292542
doi: 10.1038/s41398-021-01490-9
Kloth AD, Badura A, Li A, Cherskov A, Connolly SG, Giovannucci A, et al. Cerebellar associative sensory learning defects in five mouse autism models. Elife. 2015;4:e06085.
pubmed: 26158416
pmcid: 4512177
doi: 10.7554/eLife.06085
Uhlen M, Oksvold P, Fagerberg L, Lundberg E, Jonasson K, Forsberg M, et al. Towards a knowledge-based human protein atlas. Nat Biotechnol. 2010;28:1248–50.
pubmed: 21139605
doi: 10.1038/nbt1210-1248
Uhlen M, Fagerberg L, Hallstrom BM, Lindskog C, Oksvold P, Mardinoglu A, et al. Proteomics. Tissue-based map of the human proteome. Science. 2015;347:1260419.
pubmed: 25613900
doi: 10.1126/science.1260419
Howard MA, Elias GM, Elias LA, Swat W, Nicoll RA. The role of SAP97 in synaptic glutamate receptor dynamics. Proc Natl Acad Sci USA. 2010;107:3805–10.
pubmed: 20133708
pmcid: 2840522
doi: 10.1073/pnas.0914422107
Otsuka H, Kimura T, Ago Y, Nakama M, Aoyama Y, Abdelkreem E, et al. Deficiency of 3-hydroxybutyrate dehydrogenase (BDH1) in mice causes low ketone body levels and fatty liver during fasting. J Inherit Metab Dis. 2020;43:960–8.
pubmed: 32279332
doi: 10.1002/jimd.12243
Haider A, Wei YC, Lim K, Barbosa AD, Liu CH, Weber U, et al. PCYT1A Regulates Phosphatidylcholine Homeostasis from the Inner Nuclear Membrane in Response to Membrane Stored Curvature Elastic Stress. Dev Cell. 2018;45:481–95.e8.
pubmed: 29754800
pmcid: 5971203
doi: 10.1016/j.devcel.2018.04.012
Cotter L, Ozcelik M, Jacob C, Pereira JA, Locher V, Baumann R, et al. Dlg1-PTEN interaction regulates myelin thickness to prevent damaging peripheral nerve overmyelination. Science. 2010;328:1415–8.
pubmed: 20448149
doi: 10.1126/science.1187735
Firestein BL, Rongo C. DLG-1 is a MAGUK similar to SAP97 and is required for adherens junction formation. Mol Biol Cell. 2001;12:3465–75.
pubmed: 11694581
pmcid: 60268
doi: 10.1091/mbc.12.11.3465
Stonnington CM, Tan G, Kloppel S, Chu C, Draganski B, Jack CR Jr, et al. Interpreting scan data acquired from multiple scanners: a study with Alzheimer’s disease. Neuroimage. 2008;39:1180–5.
pubmed: 18032068
doi: 10.1016/j.neuroimage.2007.09.066
Rutkowski TP, Purcell RH, Pollak RM, Grewenow SM, Gafford GM, Malone T, et al. Behavioral changes and growth deficits in a CRISPR engineered mouse model of the schizophrenia-associated 3q29 deletion. Mol Psychiatry. 2021;26:772–83.
pubmed: 30976085
doi: 10.1038/s41380-019-0413-5