My research is focused on network modeling of psychiatric disorders, especially ASD and its related comorbidities, like depression and anxiety. The goal of different projects is to shed light on the structure of psychopathologies and their differences at different states, for example structure of ASD as assessed by an instrument like ADOS or ADI-R in patients with and without co-existing depression or assessing this structure and its changes at different cross sections over a period of time during development of the children.
In (Anderson et al., 2015), ASD correlational networks were constructed, based on the “Autism Diagnostic Observation Schedule” (ADOS) items. This was the first Network Analysis of ASD, published in the literature. Among others, it revealed that “Reciprocal Social Interaction” nodes, are the most central behaviors affected in ASD, and are closely related to the “Communication” domain nodes. “Stereotyped Behaviors and Restricted Interests” behaviors were more peripheral. Moreover, Item E3 (Anxiety) was the most peripheral node, in almost all networks. Since targeting the most central nodes in these types of networks are proven to yield better therapeutic results, this study implies targeting “Reciprocal Social Interaction” behaviors would result in good therapeutic results.
Montazeri et al., 2018, further focused on the interaction of anxiety and ASD. Composite scores based on the sum of items from subscales of the “Revised Children’s Anxiety and Depression Scale” (RCADS), (“Social Anxiety”, “Generalized Anxiety”, “Panic Disorder” and “Separation Anxiety”) were included as nodes in a partial correlation network, which also included nodes representing different ASD behaviors. These composite anxiety nodes were consistently peripheral in all networks, further suggesting that anxiety, overall, does not play a central role in the psychopathology of ASD.
Montazeri et al., 2020, focuses on depression-ASD interaction. The ASD group had a higher rate of clinical depression and markedly higher “insomnia” and “restlessness” scores in the regularized partial correlation networks. Depression nodes clustered with the anxiety nodes, but remained separate from autism nodes, in a combined network. Moreover, compared to the controls, “insomnia” and “restlessness” nodes were more central in ASD network. Module preservation analysis showed that depression, in a network composed of depression-, anxiety-, and OCD behaviors, was the least preserved module compared to the controls and hence, “atypical”, in ASD.
Results of the genetic project I contributed to, were published in (Li et al., 2016) and indicated new mutations in the histone modifier PRDM6 were associated with isolated non-syndromic Patent Ductus Arteriosus.
In Montazeri et al., 2022 three defining domains of ASD in DSM, which are social, communication and restrictive/repetitive behaviors (RRBs) were network modeled. The Autism Diagnostic Interview-Revised (ADI-R) assessed behaviors in 139 pre-school cases at two cross-sections that averaged 34.8 months apart. Cross-sectional networks were based on the correlation matrix of the ADI-R behavioral items and the “bootCross” method was developed and enabled the estimation of a longitudinal network. At both stages, RRB items/nodes formed a consistent peripheral cluster, while social and communication nodes formed a core cluster that diverged with time. These differences in the nature and evolution of the RRB and socio-communicative dimensions indicate that their inter-behavior dynamics are very different. The most central behaviors across stages are proposed as prime targets for efficient therapeutic intervention.
Anxiety; Anxiety Disorders; Attention Deficit Disorder with Hyperactivity; Bipolar Disorder; Developmental Disabilities; Child Development Disorders, Pervasive; Depression; Software Design; Computational Biology; Attention Deficit and Disruptive Behavior Disorders; Autism Spectrum Disorder; Neurodevelopmental Disorders