Molecular EPISTOP, a comprehensive multi-omic analysis of blood from Tuberous Sclerosis Complex infants age birth to two years
Jazyk angličtina Země Velká Británie, Anglie Médium electronic
Typ dokumentu časopisecké články
Grantová podpora
602391-2
European Commission (EC)
PubMed
37996417
PubMed Central
PMC10667269
DOI
10.1038/s41467-023-42855-6
PII: 10.1038/s41467-023-42855-6
Knihovny.cz E-zdroje
- MeSH
- epilepsie * genetika MeSH
- klinické zkoušky jako téma MeSH
- kojenec MeSH
- lidé MeSH
- multiomika MeSH
- novorozenec MeSH
- předškolní dítě MeSH
- prospektivní studie MeSH
- tuberózní skleróza * genetika MeSH
- vigabatrin terapeutické užití MeSH
- Check Tag
- kojenec MeSH
- lidé MeSH
- novorozenec MeSH
- předškolní dítě MeSH
- Publikační typ
- časopisecké články MeSH
- Názvy látek
- vigabatrin MeSH
We present a comprehensive multi-omic analysis of the EPISTOP prospective clinical trial of early intervention with vigabatrin for pre-symptomatic epilepsy treatment in Tuberous Sclerosis Complex (TSC), in which 93 infants with TSC were followed from birth to age 2 years, seeking biomarkers of epilepsy development. Vigabatrin had profound effects on many metabolites, increasing serum deoxycytidine monophosphate (dCMP) levels 52-fold. Most serum proteins and metabolites, and blood RNA species showed significant change with age. Thirty-nine proteins, metabolites, and genes showed significant differences between age-matched control and TSC infants. Six also showed a progressive difference in expression between control, TSC without epilepsy, and TSC with epilepsy groups. A multivariate approach using enrollment samples identified multiple 3-variable predictors of epilepsy, with the best having a positive predictive value of 0.987. This rich dataset will enable further discovery and analysis of developmental effects, and associations with seizure development in TSC.
Chalfont Centre for Epilepsy Chalfont St Peter UK
Child Neurology and Psychiatry Unit Systems Medicine Department Tor Vergata University Rome Italy
Department of Child Neurology Brain Center University Medical Center Utrecht Utrecht The Netherlands
Department of Child Neurology Charité University Medicine Berlin Berlin Germany
Department of Child Neurology Medical University of Warsaw Warsaw Poland
Department of Clinical and Experimental Epilepsy UCL Queen Square Institute of Neurology London UK
Department of Internal Medicine Erasmus MC Rotterdam Netherlands
Department of Medicine Brigham and Women's Hospital Boston MA USA
Department of Pathology University Medical Center Utrecht Utrecht The Netherlands
Developmental Neurology Bambino Gesù Children's Hospital IRCCS Rome Italy
Diagnose und Behandlungszentrum für Kinder Vivantes Klinikum Neukölln Berlin Germany
GenomeScan Leiden The Netherlands
International Institute of Molecular and Cell Biology Warsaw Poland
Neurogenetics Research Group Vrije Universiteit Brussel Brussels Belgium
Neurosciences Unit Queensland Children's Hospital South Brisbane Queensland Australia
Proteome Factory AG Berlin Germany
School of Medicine University of Queensland St Lucia Queensland Australia
Stichting Epilepsie Instellingen Nederland Heemstede the Netherlands Utrecht The Netherlands
Transition Technologies Science Warsaw Poland
Warsaw University of Technology Institute of Heat Engineering Warsaw Poland
Warsaw University of Technology The Institute of Computer Science Warsaw Poland
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Salussolia CL, Klonowska K, Kwiatkowski DJ, Sahin M. Genetic Etiologies, Diagnosis, and Treatment of Tuberous Sclerosis Complex. Annu Rev. Genom. Hum. Genet. 2019;20:217–240. doi: 10.1146/annurev-genom-083118-015354. PubMed DOI
Henske EP, Jozwiak S, Kingswood JC, Sampson JR, Thiele EA. Tuberous sclerosis complex. Nat. Rev. Dis. Prim. 2016;2:16035. doi: 10.1038/nrdp.2016.35. PubMed DOI
Curatolo P, Specchio N, Aronica E. Advances in the genetics and neuropathology of tuberous sclerosis complex: edging closer to targeted therapy. Lancet Neurol. 2022;21:843–856. doi: 10.1016/S1474-4422(22)00213-7. PubMed DOI
Curatolo P, et al. Management of epilepsy associated with tuberous sclerosis complex: Updated clinical recommendations. Eur. J. Paediatr. Neurol. 2018;22:738–748. doi: 10.1016/j.ejpn.2018.05.006. PubMed DOI
de Vries PJ, et al. Tuberous sclerosis associated neuropsychiatric disorders (TAND) and the TAND Checklist. Pediatr. Neurol. 2015;52:25–35. doi: 10.1016/j.pediatrneurol.2014.10.004. PubMed DOI PMC
Cembrowski MS, Spruston N. Heterogeneity within classical cell types is the rule: lessons from hippocampal pyramidal neurons. Nat. Rev. Neurosci. 2019;20:193–204. doi: 10.1038/s41583-019-0125-5. PubMed DOI
Jozwiak S, et al. Antiepileptic treatment before the onset of seizures reduces epilepsy severity and risk of mental retardation in infants with tuberous sclerosis complex. Eur. J. Paediatr. Neurol. 2011;15:424–431. doi: 10.1016/j.ejpn.2011.03.010. PubMed DOI
Kotulska K, et al. Prevention of Epilepsy in Infants with Tuberous Sclerosis Complex in the EPISTOP Trial. Ann. Neurol. 2021;89:304–314. doi: 10.1002/ana.25956. PubMed DOI PMC
Ogorek B, et al. TSC2 pathogenic variants are predictive of severe clinical manifestations in TSC infants: results of the EPISTOP study. Genet. Med. 2020;22:1489–1497. doi: 10.1038/s41436-020-0823-4. PubMed DOI
Petroff OA, Hyder F, Collins T, Mattson RH, Rothman DL. Acute effects of vigabatrin on brain GABA and homocarnosine in patients with complex partial seizures. Epilepsia. 1999;40:958–964. doi: 10.1111/j.1528-1157.1999.tb00803.x. PubMed DOI
Walters DC, et al. Preclinical tissue distribution and metabolic correlations of vigabatrin, an antiepileptic drug associated with potential use-limiting visual field defects. Pharm. Res Perspect. 2019;7:e00456. doi: 10.1002/prp2.456. PubMed DOI PMC
Ball D, Rose E, Alpert E. Alpha-fetoprotein levels in normal adults. Am. J. Med Sci. 1992;303:157–159. doi: 10.1097/00000441-199203000-00004. PubMed DOI
Clemson CM, McNeil JA, Willard HF, Lawrence JB. XIST RNA paints the inactive X chromosome at interphase: evidence for a novel RNA involved in nuclear/chromosome structure. J. Cell Biol. 1996;132:259–275. doi: 10.1083/jcb.132.3.259. PubMed DOI PMC
Li K, et al. Age-dependent changes of total and differential white blood cell counts in children. Chin. Med J. (Engl.) 2020;133:1900–1907. doi: 10.1097/CM9.0000000000000854. PubMed DOI PMC
Olin A, et al. Longitudinal analyses of development of the immune system during the first five years of life in relation to lifestyle. Allergy. 2022;77:1583–1595. doi: 10.1111/all.15232. PubMed DOI
Song W, et al. Age and sex specific reference intervals of 13 hematological analytes in Chinese children and adolescents aged from 28 days up to 20 years: the PRINCE study. Clin. Chem. Lab Med. 2022;60:1250–1260. doi: 10.1515/cclm-2022-0304. PubMed DOI
Newman AM, et al. Robust enumeration of cell subsets from tissue expression profiles. Nat. Methods. 2015;12:453–457. doi: 10.1038/nmeth.3337. PubMed DOI PMC
Hoxhaj G, Manning BD. The PI3K-AKT network at the interface of oncogenic signalling and cancer metabolism. Nat. Rev. Cancer. 2020;20:74–88. doi: 10.1038/s41568-019-0216-7. PubMed DOI PMC
Boughorbel S, Jarray F, El-Anbari M. Optimal classifier for imbalanced data using Matthews Correlation Coefficient metric. PLoS One. 2017;12:e0177678. doi: 10.1371/journal.pone.0177678. PubMed DOI PMC
Lee AH, et al. Dynamic molecular changes during the first week of human life follow a robust developmental trajectory. Nat. Commun. 2019;10:1092. doi: 10.1038/s41467-019-08794-x. PubMed DOI PMC
Bennike TB, et al. Preparing for Life: Plasma Proteome Changes and Immune System Development During the First Week of Human Life. Front. Immunol. 2020;11:578505. doi: 10.3389/fimmu.2020.578505. PubMed DOI PMC
McDavid A, et al. Aberrant newborn T cell and microbiota developmental trajectories predict respiratory compromise during infancy. iScience. 2022;25:104007. doi: 10.1016/j.isci.2022.104007. PubMed DOI PMC
Thiele EA. Managing epilepsy in tuberous sclerosis complex. J. Child Neurol. 2004;19:680–686. doi: 10.1177/08830738040190090801. PubMed DOI
Curatolo P, Verdecchia M, Bombardieri R. Vigabatrin for tuberous sclerosis complex. Brain Dev. 2001;23:649–653. doi: 10.1016/S0387-7604(01)00290-X. PubMed DOI
Krauss GL, Johnson MA, Miller NR. Vigabatrin-associated retinal cone system dysfunction: electroretinogram and ophthalmologic findings. Neurology. 1998;50:614–618. doi: 10.1212/WNL.50.3.614. PubMed DOI
Eke T, Talbot JF, Lawden MC. Severe persistent visual field constriction associated with vigabatrin. BMJ. 1997;314:180–181. doi: 10.1136/bmj.314.7075.180. PubMed DOI PMC
Kalviainen R, et al. Vigabatrin, a gabaergic antiepileptic drug, causes concentric visual field defects. Neurology. 1999;53:922–926. doi: 10.1212/WNL.53.5.922. PubMed DOI
Wild JM, Smith PEM, Knupp C. Objective Derivation of the Morphology and Staging of Visual Field Loss Associated with Long-Term Vigabatrin Therapy. CNS Drugs. 2019;33:817–829. doi: 10.1007/s40263-019-00634-2. PubMed DOI
Foroozan R. Vigabatrin: Lessons Learned From the United States Experience. J. Neuroophthalmol. 2018;38:442–450. doi: 10.1097/WNO.0000000000000609. PubMed DOI
Zhang H, et al. Loss of Tsc1/Tsc2 activates mTOR and disrupts PI3K-Akt signaling through downregulation of PDGFR. J. Clin. Invest. 2003;112:1223–1233. doi: 10.1172/JCI200317222. PubMed DOI PMC
Kobayashi K, Koide Y, Yoshino K, Shohmori T. [P-hydroxyphenylacetic acid concentrations in cerebrospinal fluid] No Shinkei. 1982;34:769–774. PubMed
Matsumoto H. Role of serum periostin in the management of asthma and its comorbidities. Respir. Investig. 2020;58:144–154. doi: 10.1016/j.resinv.2020.02.003. PubMed DOI
Cox J, et al. Andromeda: a peptide search engine integrated into the MaxQuant environment. J. Proteome Res. 2011;10:1794–1805. doi: 10.1021/pr101065j. PubMed DOI
Cox J, Mann M. MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nat. Biotechnol. 2008;26:1367–1372. doi: 10.1038/nbt.1511. PubMed DOI
Tyanova S, et al. The Perseus computational platform for comprehensive analysis of (prote)omics data. Nat. Methods. 2016;13:731–740. doi: 10.1038/nmeth.3901. PubMed DOI
Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114–2120. doi: 10.1093/bioinformatics/btu170. PubMed DOI PMC
Trapnell C, et al. Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks. Nat. Protoc. 2012;7:562–578. doi: 10.1038/nprot.2012.016. PubMed DOI PMC
Liao Y, Smyth GK, Shi W. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics. 2014;30:923–930. doi: 10.1093/bioinformatics/btt656. PubMed DOI
Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26:139–140. doi: 10.1093/bioinformatics/btp616. PubMed DOI PMC
Tiwari D, Peariso K, Gross C. MicroRNA-induced silencing in epilepsy: Opportunities and challenges for clinical application. Dev. Dyn. 2018;247:94–110. doi: 10.1002/dvdy.24582. PubMed DOI PMC
Trelinska J, et al. Abnormal serum microRNA profiles in tuberous sclerosis are normalized during treatment with everolimus: possible clinical implications. Orphanet. J. Rare Dis. 2016;11:129. doi: 10.1186/s13023-016-0512-1. PubMed DOI PMC
Kichukova TM, Popov NT, Ivanov IS, Vachev TI. Profiling of Circulating Serum MicroRNAs in Children with Autism Spectrum Disorder using Stem-loop qRT-PCR Assay. Folia Med (Plovdiv.) 2017;59:43–52. doi: 10.1515/folmed-2017-0009. PubMed DOI
Raoof R, et al. Cerebrospinal fluid microRNAs are potential biomarkers of temporal lobe epilepsy and status epilepticus. Sci. Rep. 2017;7:3328. doi: 10.1038/s41598-017-02969-6. PubMed DOI PMC
Hicks SD, Ignacio C, Gentile K, Middleton FA. Salivary miRNA profiles identify children with autism spectrum disorder, correlate with adaptive behavior, and implicate ASD candidate genes involved in neurodevelopment. BMC Pediatr. 2016;16:52. doi: 10.1186/s12887-016-0586-x. PubMed DOI PMC
Ramakers C, Ruijter JM, Deprez RH, Moorman AF. Assumption-free analysis of quantitative real-time polymerase chain reaction (PCR) data. Neurosci. Lett. 2003;339:62–66. doi: 10.1016/S0304-3940(02)01423-4. PubMed DOI
Yuan M, Breitkopf SB, Yang X, Asara JM. A positive/negative ion-switching, targeted mass spectrometry-based metabolomics platform for bodily fluids, cells, and fresh and fixed tissue. Nat. Protoc. 2012;7:872–881. doi: 10.1038/nprot.2012.024. PubMed DOI PMC
Durinck S, et al. BioMart and Bioconductor: a powerful link between biological databases and microarray data analysis. Bioinformatics. 2005;21:3439–3440. doi: 10.1093/bioinformatics/bti525. PubMed DOI
Durinck S, Spellman PT, Birney E, Huber W. Mapping identifiers for the integration of genomic datasets with the R/Bioconductor package biomaRt. Nat. Protoc. 2009;4:1184–1191. doi: 10.1038/nprot.2009.97. PubMed DOI PMC
Yu G, He QY. ReactomePA: an R/Bioconductor package for reactome pathway analysis and visualization. Mol. Biosyst. 2016;12:477–479. doi: 10.1039/C5MB00663E. PubMed DOI
Yu G, Wang LG, Han Y, He QY. clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS. 2012;16:284–287. doi: 10.1089/omi.2011.0118. PubMed DOI PMC
Wu T, et al. clusterProfiler 4.0: A universal enrichment tool for interpreting omics data. Innov. (Camb.) 2021;2:100141. PubMed PMC
Jassal B, et al. The reactome pathway knowledgebase. Nucleic Acids Res. 2020;48:D498–D503. PubMed PMC
Glowacka-Walas J., Molecular EPISTOP, a comprehensive multi-omic analysis of blood from Tuberous Sclerosis Complex infants age birth to two years. https://github.com/JagGlo/molecular_EPISTOP; 10.5281/zenodo.8389826 (2023). PubMed PMC