# Behavioral Features in Phelan–McDermid Syndrome: Characteristics and Genetic and Metabolic Contributions in a Cohort of 56 Individuals

## TL;DR

This study examines the behavioral features and genetic/metabolic factors in 56 individuals with Phelan–McDermid syndrome, a rare neurodevelopmental disorder.

## Contribution

The study identifies SHANK3's role in adaptive behavior and reveals distinct metabolic profiles linked to behavioral outcomes in PMS.

## Key findings

- Individuals with SHANK3 variants had lower adaptive behavioral skills than those with 22q13 deletions.
- Metabolic profiling showed unique patterns in PMS individuals compared to controls and based on ASD cutoff scores.
- Cluster analyses identified groups with distinct ASD and clinical features.

## Abstract

Background/Objectives: Phelan–McDermid syndrome (PMS), caused by either chromosome 22q13.3 deletions or pathogenic/likely pathogenic variants in the SHANK3 gene, is a rare neurodevelopmental disorder. Behavioral issues greatly impair the quality of life for affected individuals and their families. This genotype–phenotype study intended to further characterize key behavioral features and their genetic and metabolic correlates in PMS. Methods: We conducted a cross-sectional analysis of data on 56 individuals with PMS. Autistic and related behaviors were assessed with the Autism Diagnosis Interview—Revised (ADI-R) and adaptive behavior skills were assessed with the Vineland Adaptive Behavior Scales-Third Edition (Vineland-3), both covering multiple aspects of communication, socialization and abnormal behaviors. Genetic diagnostic information on deletions or pathogenic variants was supplemented with the sequencing data of nine candidate genes on 22q13.3. Metabolic data were obtained using the Biolog Phenotype Mammalian MicroArray plates (PM-M). Results. Every subject in the cohort presented either prominent autistic behavior or adaptive behavior impairment, 55.4% of them meeting the ASD cutoff in every ADI-R domain and 92.9% scoring in the lowest level of adaptive behavior (range of 20–70). Individuals with SHANK3 variants had lower adaptive behavioral skills than those with 22q13 deletions regardless of deletion size, while genomic parameters were largely unrelated to ADI-R scores. Metabolic profiling identified unique profiles of individuals with PMS compared with controls, while distinct profiles distinguished those who met or did not meet the ADI-R ASD cutoff. Cluster analyses revealed groups of individuals with ASD and other clinical features. Conclusion. This study highlighted the importance of SHANK3 in adaptive behavioral skills and uncovered potential metabolic biomarkers of therapeutic relevance.