Omic Profile in Autism Spectrum Disorder: From Cellular Level Towards Future Treatments

NCT07427940 | Recruiting

• 2 other identifiers: PNRR-MCNT1-2023-12377520PNNR Funding
• Study Type: interventional
• Target: 100
• Locations: 1 country
• Sites: 1

Brief Summary

This is an interventional non pharmacological study in pediatric patientis affected by Autism Spectrum Disorder. It ams to create a collection of iPSCs and hiNSCs derived from deeply characterized ASD patients, to omics-characterize the cells, and to study the behavioral pattern of microglia-like cells in the onset of ASD.

Conditions

Autism Spectrum Disorder

Keywords

Autism Spectrum Disorder; Neurodevelopmental disorders; iPSCs; hiNSCs; Microglia

Outcome Measures

Primary Outcomes (10)

• Measurement of severity of ASD core symptoms with ADOS2

  Outcome unity of measure: Calibrated Severity Scores - Measure range: 1-10

  1 year

• Measurement of severity of ASD core symptoms with SRS 2

  Outcome unity of measure: T-score - Measure range: 30-90

  1 year

• Measurement of developmental abilities with Griffiths III scales

  Outcome unity of measure: GQ - Measure range: \<20-150

  1 year

• Measurement of cognitive abilities with Wechsler scales

  Outcome unity of measure: IQ - Measure range: \<20-160

  1 year

• Measurement of cognitive abilities with Leiter 3 scales

  Outcome unity of measure: IQ - Measure range: 40-160

  1 year

• Quantification of emotional and behavioral problems with CBCL

  Outcome unity of measure: Raw score - Measure range: 0-200 for children \<6 years old / and 0-226 for children 6-18 years old

  1 year

• Verification on iPSs of presence/absence of expression of stem cell genes and genes from the three embryonic layers

  Outcome unity of measure: Gene expression - Measure range: yes/no

  1 year

• Percentage of hiNSCs differentiating into astrocytes, oligodendrocytes, and neurons

  Outcome unity of measure: % cells differentiated/tot numeber of cells - Measure range: 0-100%

  1 year

• Measurement of length of neurite growth in hiNSCs

  Outcome unity of measure: µm - Measure range 0-500 µm

  1 year

• Measurement of concentration of distinct lipid molecular species in ASD derived cells and control derived cells in order to assess the differences in lipidomic profiles

  Outcome unity of measure: µmol/L - Measure range: 0.001 µmol/L - \>10,000 µmol/L

  1 year

Study Arms (1)

Single arm study

EXPERIMENTAL

the arm is constituted by 100 pediatric patients (aged -15) with ASD diagnosis

Biological: Blood sample collection for ASD cells model production and Omic studies

Interventions

Blood sample collection for ASD cells model production and Omic studies BIOLOGICAL

The blood sample collection performed in the study is for research purposes only and therefore not collected for clinical purposes. The patient cohort is extensively studied and well stratified, so cell models production and subsequent Omic analyses could be cross-referenced with detailed phenotype data.

Single arm study

Eligibility Criteria

• Age: 3 Years - 15 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Child (0-17)

You may qualify if:

• Defined ASD diagnosis according to DSM-5 criteria
• Age 3-15 years
• Informed consent signed by the guardians/legal representatives.

You may not qualify if:

• No standardized test to establish diagnosis
• Parents refusing to complete the consent form
• Impossible blood sample collection.

Sponsors & Collaborators

• Fondazione I.R.C.C.S. Istituto Neurologico Carlo Besta: lead

Study Sites (1)

Foundation IRCCS Carlo Besta Neurological Institute

Milan, 20133, Italy

RECRUITING

Related Publications (19)

• Willsey AJ, Sanders SJ, Li M, Dong S, Tebbenkamp AT, Muhle RA, Reilly SK, Lin L, Fertuzinhos S, Miller JA, Murtha MT, Bichsel C, Niu W, Cotney J, Ercan-Sencicek AG, Gockley J, Gupta AR, Han W, He X, Hoffman EJ, Klei L, Lei J, Liu W, Liu L, Lu C, Xu X, Zhu Y, Mane SM, Lein ES, Wei L, Noonan JP, Roeder K, Devlin B, Sestan N, State MW. Coexpression networks implicate human midfetal deep cortical projection neurons in the pathogenesis of autism. Cell. 2013 Nov 21;155(5):997-1007. doi: 10.1016/j.cell.2013.10.020.

  PMID: 24267886 BACKGROUND

• Wen Z, Nguyen HN, Guo Z, Lalli MA, Wang X, Su Y, Kim NS, Yoon KJ, Shin J, Zhang C, Makri G, Nauen D, Yu H, Guzman E, Chiang CH, Yoritomo N, Kaibuchi K, Zou J, Christian KM, Cheng L, Ross CA, Margolis RL, Chen G, Kosik KS, Song H, Ming GL. Synaptic dysregulation in a human iPS cell model of mental disorders. Nature. 2014 Nov 20;515(7527):414-8. doi: 10.1038/nature13716. Epub 2014 Aug 17.

  PMID: 25132547 BACKGROUND

• Waizbard-Bartov E, Fein D, Lord C, Amaral DG. Autism severity and its relationship to disability. Autism Res. 2023 Apr;16(4):685-696. doi: 10.1002/aur.2898. Epub 2023 Feb 14.

  PMID: 36786314 BACKGROUND

• Vargas DL, Nascimbene C, Krishnan C, Zimmerman AW, Pardo CA. Neuroglial activation and neuroinflammation in the brain of patients with autism. Ann Neurol. 2005 Jan;57(1):67-81. doi: 10.1002/ana.20315.

  PMID: 15546155 BACKGROUND

• Turco EM, Giovenale AMG, Sireno L, Mazzoni M, Cammareri A, Marchioretti C, Goracci L, Di Veroli A, Marchesan E, D'Andrea D, Falconieri A, Torres B, Bernardini L, Magnifico MC, Paone A, Rinaldo S, Della Monica M, D'Arrigo S, Postorivo D, Nardone AM, Zampino G, Onesimo R, Leoni C, Caicci F, Raimondo D, Binda E, Trobiani L, De Jaco A, Tata AM, Ferrari D, Cutruzzola F, Mazzoccoli G, Ziviani E, Pennuto M, Vescovi AL, Rosati J. Retinoic acid-induced 1 gene haploinsufficiency alters lipid metabolism and causes autophagy defects in Smith-Magenis syndrome. Cell Death Dis. 2022 Nov 21;13(11):981. doi: 10.1038/s41419-022-05410-7.

  PMID: 36411275 BACKGROUND

• Sellgren CM, Sheridan SD, Gracias J, Xuan D, Fu T, Perlis RH. Patient-specific models of microglia-mediated engulfment of synapses and neural progenitors. Mol Psychiatry. 2017 Feb;22(2):170-177. doi: 10.1038/mp.2016.220. Epub 2016 Dec 13.

  PMID: 27956744 BACKGROUND

• Ryan KJ, White CC, Patel K, Xu J, Olah M, Replogle JM, Frangieh M, Cimpean M, Winn P, McHenry A, Kaskow BJ, Chan G, Cuerdon N, Bennett DA, Boyd JD, Imitola J, Elyaman W, De Jager PL, Bradshaw EM. A human microglia-like cellular model for assessing the effects of neurodegenerative disease gene variants. Sci Transl Med. 2017 Dec 20;9(421):eaai7635. doi: 10.1126/scitranslmed.aai7635.

  PMID: 29263232 BACKGROUND

• Rosati J, Ferrari D, Altieri F, Tardivo S, Ricciolini C, Fusilli C, Zalfa C, Profico DC, Pinos F, Bernardini L, Torres B, Manni I, Piaggio G, Binda E, Copetti M, Lamorte G, Mazza T, Carella M, Gelati M, Valente EM, Simeone A, Vescovi AL. Establishment of stable iPS-derived human neural stem cell lines suitable for cell therapies. Cell Death Dis. 2018 Sep 17;9(10):937. doi: 10.1038/s41419-018-0990-2.

  PMID: 30224709 BACKGROUND

• Prince N, Chu SH, Chen Y, Mendez KM, Hanson E, Green-Snyder L, Brooks E, Korrick S, Lasky-Su JA, Kelly RS. Phenotypically driven subgroups of ASD display distinct metabolomic profiles. Brain Behav Immun. 2023 Jul;111:21-29. doi: 10.1016/j.bbi.2023.03.026. Epub 2023 Mar 31.

  PMID: 37004757 BACKGROUND

• Rolland T, Cliquet F, Anney RJL, Moreau C, Traut N, Mathieu A, Huguet G, Duan J, Warrier V, Portalier S, Dry L, Leblond CS, Douard E, Amsellem F, Malesys S, Maruani A, Toro R, Borglum AD, Grove J, Baron-Cohen S, Packer A, Chung WK, Jacquemont S, Delorme R, Bourgeron T. Phenotypic effects of genetic variants associated with autism. Nat Med. 2023 Jul;29(7):1671-1680. doi: 10.1038/s41591-023-02408-2. Epub 2023 Jun 26.

  PMID: 37365347 BACKGROUND

• Ormel PR, Bottcher C, Gigase FAJ, Missall RD, van Zuiden W, Fernandez Zapata MC, Ilhan D, de Goeij M, Udine E, Sommer IEC, Priller J, Raj T, Kahn RS, Hol EM, de Witte LD. A characterization of the molecular phenotype and inflammatory response of schizophrenia patient-derived microglia-like cells. Brain Behav Immun. 2020 Nov;90:196-207. doi: 10.1016/j.bbi.2020.08.012. Epub 2020 Aug 13.

  PMID: 32798663 BACKGROUND

• Nimmerjahn A, Kirchhoff F, Helmchen F. Resting microglial cells are highly dynamic surveillants of brain parenchyma in vivo. Science. 2005 May 27;308(5726):1314-8. doi: 10.1126/science.1110647. Epub 2005 Apr 14.

  PMID: 15831717 BACKGROUND

• Maenner MJ, Warren Z, Williams AR, Amoakohene E, Bakian AV, Bilder DA, Durkin MS, Fitzgerald RT, Furnier SM, Hughes MM, Ladd-Acosta CM, McArthur D, Pas ET, Salinas A, Vehorn A, Williams S, Esler A, Grzybowski A, Hall-Lande J, Nguyen RHN, Pierce K, Zahorodny W, Hudson A, Hallas L, Mancilla KC, Patrick M, Shenouda J, Sidwell K, DiRienzo M, Gutierrez J, Spivey MH, Lopez M, Pettygrove S, Schwenk YD, Washington A, Shaw KA. Prevalence and Characteristics of Autism Spectrum Disorder Among Children Aged 8 Years - Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States, 2020. MMWR Surveill Summ. 2023 Mar 24;72(2):1-14. doi: 10.15585/mmwr.ss7202a1.

  PMID: 36952288 BACKGROUND

• Liu X, Campanac E, Cheung HH, Ziats MN, Canterel-Thouennon L, Raygada M, Baxendale V, Pang AL, Yang L, Swedo S, Thurm A, Lee TL, Fung KP, Chan WY, Hoffman DA, Rennert OM. Idiopathic Autism: Cellular and Molecular Phenotypes in Pluripotent Stem Cell-Derived Neurons. Mol Neurobiol. 2017 Aug;54(6):4507-4523. doi: 10.1007/s12035-016-9961-8. Epub 2016 Jun 29.

  PMID: 27356918 BACKGROUND

• Lim M, Carollo A, Dimitriou D, Esposito G. Recent Developments in Autism Genetic Research: A Scientometric Review from 2018 to 2022. Genes (Basel). 2022 Sep 14;13(9):1646. doi: 10.3390/genes13091646.

  PMID: 36140813 BACKGROUND

• Kinsner-Ovaskainen A, Lanzoni M, Garne E, Loane M, Morris J, Neville A, Nicholl C, Rankin J, Rissmann A, Tucker D, Martin S. A sustainable solution for the activities of the European network for surveillance of congenital anomalies: EUROCAT as part of the EU Platform on Rare Diseases Registration. Eur J Med Genet. 2018 Sep;61(9):513-517. doi: 10.1016/j.ejmg.2018.03.008. Epub 2018 Mar 27.

  PMID: 29597096 BACKGROUND

• Genovese A, Butler MG. The Autism Spectrum: Behavioral, Psychiatric and Genetic Associations. Genes (Basel). 2023 Mar 9;14(3):677. doi: 10.3390/genes14030677.

  PMID: 36980949 BACKGROUND

• Di Lullo E, Kriegstein AR. The use of brain organoids to investigate neural development and disease. Nat Rev Neurosci. 2017 Oct;18(10):573-584. doi: 10.1038/nrn.2017.107. Epub 2017 Sep 7.

  PMID: 28878372 BACKGROUND

• Chiarotti F, Venerosi A. Epidemiology of Autism Spectrum Disorders: A Review of Worldwide Prevalence Estimates Since 2014. Brain Sci. 2020 May 1;10(5):274. doi: 10.3390/brainsci10050274.

  PMID: 32370097 BACKGROUND

MeSH Terms

Conditions

Autism Spectrum Disorder; Neurodevelopmental Disorders

Condition Hierarchy (Ancestors)

Child Development Disorders, Pervasive; Mental Disorders

Central Study Contacts

Stefano D'Arrigo, M.D.

CONTACT

02.2394.2210; stefano.darrigo@istituto-besta.it

Sara Bulgheroni

CONTACT

sara.bulgheroni@istituto-besta.it

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NA
• Masking: NONE
• Purpose: BASIC SCIENCE
• Intervention Model: SINGLE GROUP
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: December 19, 2024
• First Posted: February 23, 2026
• Study Start: August 31, 2024
• Primary Completion (Estimated): August 31, 2026
• Study Completion (Estimated): August 31, 2026
• Last Updated: February 23, 2026

Record last verified: 2026-02

Data Sharing

• IPD Sharing: Will share
• Shared Documents: STUDY PROTOCOL, SAP, ICF, CSR
• Time Frame: 25 years, from August 31st 2024 to August 31st 2049.
• Access Criteria: Clinical and neuropsychological data are collected on paper support and than entered in REDCap by UO1 staff. Cellular and molecular data are collected and entered in REDCap by UO2 staff. Only the clinical personnel involved in the study will have access to data, that could be accessed anytime but only from the Institutional Organizations participating in the study.

Locations

IT (1)