Browsing by Subject "Factor analysis"
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- ItemOpen AccessMultivariate data analysis identifies natural clusters of Tuberous Sclerosis Complex Associated Neuropsychiatric Disorders (TAND)(2021-10-24) de Vries, Petrus J.; Leclezio, Loren; Gardner-Lubbe, Sugnet; Krueger, Darcy; Sahin, Mustafa; Sparagana, Steven; De Waele, Liesbeth; Jansen, AnnaBackground 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.
- ItemOpen AccessNatural clusters of tuberous sclerosis complex (TSC)-associated neuropsychiatric disorders (TAND): new findings from the TOSCA TAND research project(2020-09-01) de Vries, Petrus J; Belousova, Elena; Benedik, Mirjana P; Carter, Tom; Cottin, Vincent; Curatolo, Paolo; D’Amato, Lisa; Beure d’Augères, Guillaume; Ferreira, José C; Feucht, Martha; Fladrowski, Carla; Hertzberg, Christoph; Jozwiak, Sergiusz; Lawson, John A; Macaya, Alfons; Marques, Ruben; Nabbout, Rima; O’Callaghan, Finbar; Qin, Jiong; Sander, Valentin; Sauter, Matthias; Shah, Seema; Takahashi, Yukitoshi; Touraine, Renaud; Youroukos, Sotiris; Zonnenberg, Bernard; Kingswood, J. Chris; Jansen, Anna CAbstract Background Tuberous sclerosis complex (TSC)-associated neuropsychiatric disorders (TAND) have unique, individual patterns that pose significant challenges for diagnosis, psycho-education, and intervention planning. A recent study suggested that it may be feasible to use TAND Checklist data and data-driven methods to generate natural TAND clusters. However, the study had a small sample size and data from only two countries. Here, we investigated the replicability of identifying natural TAND clusters from a larger and more diverse sample from the TOSCA study. Methods As part of the TOSCA international TSC registry study, this embedded research project collected TAND Checklist data from individuals with TSC. Correlation coefficients were calculated for TAND variables to generate a correlation matrix. Hierarchical cluster and factor analysis methods were used for data reduction and identification of natural TAND clusters. Results A total of 85 individuals with TSC (female:male, 40:45) from 7 countries were enrolled. Cluster analysis grouped the TAND variables into 6 clusters: a scholastic cluster (reading, writing, spelling, mathematics, visuo-spatial difficulties, disorientation), a hyperactive/impulsive cluster (hyperactivity, impulsivity, self-injurious behavior), a mood/anxiety cluster (anxiety, depressed mood, sleep difficulties, shyness), a neuropsychological cluster (attention/concentration difficulties, memory, attention, dual/multi-tasking, executive skills deficits), a dysregulated behavior cluster (mood swings, aggressive outbursts, temper tantrums), and an autism spectrum disorder (ASD)-like cluster (delayed language, poor eye contact, repetitive behaviors, unusual use of language, inflexibility, difficulties associated with eating). The natural clusters mapped reasonably well onto the six-factor solution generated. Comparison between cluster and factor solutions from this study and the earlier feasibility study showed significant similarity, particularly in cluster solutions. Conclusions Results from this TOSCA research project in an independent international data set showed that the combination of cluster analysis and factor analysis may be able to identify clinically meaningful natural TAND clusters. Findings were remarkably similar to those identified in the earlier feasibility study, supporting the potential robustness of these natural TAND clusters. Further steps should include examination of larger samples, investigation of internal consistency, and evaluation of the robustness of the proposed natural clusters.