Multivariate data analysis identifies natural clusters of Tuberous Sclerosis Complex Associated Neuropsychiatric Disorders (TAND)

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dc.contributor.authorde Vries, Petrus J.
dc.contributor.authorLeclezio, Loren
dc.contributor.authorGardner-Lubbe, Sugnet
dc.contributor.authorKrueger, Darcy
dc.contributor.authorSahin, Mustafa
dc.contributor.authorSparagana, Steven
dc.contributor.authorDe Waele, Liesbeth
dc.contributor.authorJansen, Anna
dc.date.accessioned2021-11-02T12:48:18Z
dc.date.available2021-11-02T12:48:18Z
dc.date.issued2021-10-24
dc.date.updated2021-10-31T04:18:38Z
dc.description.abstractBackground Tuberous Sclerosis Complex (TSC), a multi-system genetic disorder, is associated with a wide range of TSC-Associated Neuropsychiatric Disorders (TAND). Individuals have apparently unique TAND profiles, challenging diagnosis, psycho-education, and intervention planning. We proposed that identification of natural TAND clusters could lead to personalized identification and treatment of TAND. Two small-scale studies showed cluster and factor analysis could identify clinically meaningful natural TAND clusters. Here we set out to identify definitive natural TAND clusters in a large, international dataset. Method Cross-sectional, anonymized TAND Checklist data of 453 individuals with TSC were collected from six international sites. Data-driven methods were used to identify natural TAND clusters. Mean squared contingency coefficients were calculated to produce a correlation matrix, and various cluster analyses and exploratory factor analysis were examined. Statistical robustness of clusters was evaluated with 1000-fold bootstrapping, and internal consistency calculated with Cronbach’s alpha. Results Ward’s method rendered seven natural TAND clusters with good robustness on bootstrapping. Cluster analysis showed significant convergence with an exploratory factor analysis solution, and, with the exception of one cluster, internal consistency of the emerging clusters was good to excellent. Clusters showed good clinical face validity. Conclusions Our findings identified a data-driven set of natural TAND clusters from within highly variable TAND Checklist data. The seven natural TAND clusters could be used to train families and professionals and to develop tailored approaches to identification and treatment of TAND. Natural TAND clusters may also have differential aetiological underpinnings and responses to molecular and other treatments.en_US
dc.identifier.apacitationde Vries, Petrus J., Leclezio, L., Gardner-Lubbe, S., Krueger, D., Sahin, M., Sparagana, S., ... Jansen, A. (2021). Multivariate data analysis identifies natural clusters of Tuberous Sclerosis Complex Associated Neuropsychiatric Disorders (TAND). <i>Orphanet Journal of Rare Diseases</i>, 16(Article number: 447), http://hdl.handle.net/11427/35301en_ZA
dc.identifier.chicagocitationde Vries, Petrus J., Loren Leclezio, Sugnet Gardner-Lubbe, Darcy Krueger, Mustafa Sahin, Steven Sparagana, Liesbeth De Waele, and Anna Jansen "Multivariate data analysis identifies natural clusters of Tuberous Sclerosis Complex Associated Neuropsychiatric Disorders (TAND)." <i>Orphanet Journal of Rare Diseases</i> 16, Article number: 447. (2021) http://hdl.handle.net/11427/35301en_ZA
dc.identifier.citationde Vries, Petrus J., Leclezio, L., Gardner-Lubbe, S., Krueger, D., Sahin, M., Sparagana, S., De Waele, L. & Jansen, A. et al. 2021. Multivariate data analysis identifies natural clusters of Tuberous Sclerosis Complex Associated Neuropsychiatric Disorders (TAND). <i>Orphanet Journal of Rare Diseases.</i> 16(Article number: 447) http://hdl.handle.net/11427/35301en_ZA
dc.identifier.ris TY - Journal Article AU - de Vries, Petrus J. AU - Leclezio, Loren AU - Gardner-Lubbe, Sugnet AU - Krueger, Darcy AU - Sahin, Mustafa AU - Sparagana, Steven AU - De Waele, Liesbeth AU - Jansen, Anna AB - Background Tuberous Sclerosis Complex (TSC), a multi-system genetic disorder, is associated with a wide range of TSC-Associated Neuropsychiatric Disorders (TAND). Individuals have apparently unique TAND profiles, challenging diagnosis, psycho-education, and intervention planning. We proposed that identification of natural TAND clusters could lead to personalized identification and treatment of TAND. Two small-scale studies showed cluster and factor analysis could identify clinically meaningful natural TAND clusters. Here we set out to identify definitive natural TAND clusters in a large, international dataset. Method Cross-sectional, anonymized TAND Checklist data of 453 individuals with TSC were collected from six international sites. Data-driven methods were used to identify natural TAND clusters. Mean squared contingency coefficients were calculated to produce a correlation matrix, and various cluster analyses and exploratory factor analysis were examined. Statistical robustness of clusters was evaluated with 1000-fold bootstrapping, and internal consistency calculated with Cronbach’s alpha. Results Ward’s method rendered seven natural TAND clusters with good robustness on bootstrapping. Cluster analysis showed significant convergence with an exploratory factor analysis solution, and, with the exception of one cluster, internal consistency of the emerging clusters was good to excellent. Clusters showed good clinical face validity. Conclusions Our findings identified a data-driven set of natural TAND clusters from within highly variable TAND Checklist data. The seven natural TAND clusters could be used to train families and professionals and to develop tailored approaches to identification and treatment of TAND. Natural TAND clusters may also have differential aetiological underpinnings and responses to molecular and other treatments. DA - 2021-10-24 DB - OpenUCT DP - University of Cape Town IS - Article number: 447 J1 - Orphanet Journal of Rare Diseases KW - Tuberous Sclerosis Complex KW - TAND KW - Natural TAND clusters KW - Neuropsychiatric KW - Autism spectrum disorder KW - Cluster analysis KW - Factor analysis KW - Precision medicine LK - https://open.uct.ac.za PY - 2021 T1 - Multivariate data analysis identifies natural clusters of Tuberous Sclerosis Complex Associated Neuropsychiatric Disorders (TAND) TI - Multivariate data analysis identifies natural clusters of Tuberous Sclerosis Complex Associated Neuropsychiatric Disorders (TAND) UR - http://hdl.handle.net/11427/35301 ER - en_ZA
dc.identifier.urihttps://doi.org/10.1186/s13023-021-02076-w
dc.identifier.urihttp://hdl.handle.net/11427/35301
dc.identifier.vancouvercitationde Vries Petrus J, Leclezio L, Gardner-Lubbe S, Krueger D, Sahin M, Sparagana S, et al. Multivariate data analysis identifies natural clusters of Tuberous Sclerosis Complex Associated Neuropsychiatric Disorders (TAND). Orphanet Journal of Rare Diseases. 2021;16(Article number: 447) http://hdl.handle.net/11427/35301.en_ZA
dc.language.isoenen_US
dc.language.rfc3066en
dc.publisher.departmentDivision of Child and Adolescent Psychiatryen_US
dc.publisher.facultyFaculty of Health Sciencesen_US
dc.rights.holderThe Author(s)
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_US
dc.sourceOrphanet Journal of Rare Diseasesen_US
dc.source.journalissueArticle number: 447en_US
dc.source.journalvolume16en_US
dc.source.urihttps://ojrd.biomedcentral.com/
dc.subjectTuberous Sclerosis Complexen_US
dc.subjectTANDen_US
dc.subjectNatural TAND clustersen_US
dc.subjectNeuropsychiatricen_US
dc.subjectAutism spectrum disorderen_US
dc.subjectCluster analysisen_US
dc.subjectFactor analysisen_US
dc.subjectPrecision medicineen_US
dc.titleMultivariate data analysis identifies natural clusters of Tuberous Sclerosis Complex Associated Neuropsychiatric Disorders (TAND)en_US
dc.typeJournal Articleen_US
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