# New insights into neurodevelopmental disorders by whole genome sequencing of 100 families from Italy

## TL;DR

This study uses whole genome sequencing of 100 Italian families to uncover genetic factors contributing to neurodevelopmental disorders.

## Contribution

The study identifies new candidate genes and highlights genetic heterogeneity in neurodevelopmental disorders using WGS and an evolutionary constraint model.

## Key findings

- 32 likely phenotype-causing variants were identified in 26.4% of probands in known NDD-associated genes.
- A diagnostic yield gradient was observed, with the highest yield in intellectual disability cases.
- 42 variants of uncertain significance were found, including 14 in potentially new NDD candidate genes.

## Abstract

Neurodevelopmental disorders (NDDs) have a strong but largely unexplained genetic basis. Moreover, the genetic architecture of these complex disorders in under-represented communities is poorly studied. We analyzed 110 probands from 100 families (for a total of 298 individuals), using whole genome sequencing (WGS) to identify genetic contributors to NDDs. This study is part of the ‘5000genomi@VdA’ project characterizing Valle d’Aosta (Italy) genomic landscape in health and disease. Probands were stratified into three diagnostic categories: ASD (autism spectrum disorder without intellectual disability), ID (intellectual disability without ASD), and ASD-ID (autism spectrum disorder with comorbid intellectual disability). Following the ACMG guidelines, we identified 32 likely phenotype-causing variants in known NDD-associated genes in 26.4% of the probands. We observed a diagnostic yield gradient, lowest in ASD, intermediate in ASD-ID, and highest in ID. We also identified 42 variants of uncertain significance, 14 of which were located in genes not previously linked to NDDs but relevant to neurodevelopment, and may thus represent new NDD candidate genes. Furthermore, we used Evo 2, an evolutionary constraint-based model, to refine variant interpretation and identify VUS with pathogenic-like signatures. These findings highlight the utility of WGS in exploring the genetic heterogeneity within stratified NDD clinical groups.