This repository contains the code used to process and analyse the data presented in the "Neuropsychiatric mutations delineate functional brain connectivity dimensions contributing to autism and schizophrenia" paper.
16p11.2 and 22q11.2 Copy Number Variants (CNVs) confer high risk for Autism Spectrum Disorder (ASD), schizophrenia (SZ), and Attention-Deficit-Hyperactivity-Disorder (ADHD), but their impact on functional connectivity (FC) networks remains unclear.
We analyzed resting-state functional magnetic resonance imaging data from 101 CNV carriers, 755 individuals with idiopathic ASD, SZ, or ADHD and 1,072 controls. We used CNV FC-signatures to identify major dimensions contributing to complex idiopathic conditions.
CNVs had large mirror effects on FC at the global and regional level, and their effect-sizes were twice as large as those of idiopathic conditions. Thalamus, somatomotor, and posterior insula regions played a critical role in dysconnectivity shared across deletions, duplications, idiopathic ASD, SZ but not ADHD. Individuals with higher similarity to deletion FC-signatures exhibited worse behavioral and cognitive symptoms.
The FC-signatures of both deletions were associated with the spatial expression pattern of genes within as well genes outside these 2 loci. This genetic redundancy may represent a factor underlying shared FC signatures between both deletions and idiopathic conditions.
Requirements
- NIAK
cnvfc(included in this repository)gene_expression(submodule included in this repository)
To download the code of this repository, run the following command in a terminal:
git clone git@github.com:surchs/Neuropsychiatric_CNV_code_supplement.git --recursive
The --recursive flag will ensure that you also download the analysis code in the gene_expression submodule.
The analysis scripts included in this repository make use of a number of custom python functions included in the cnvfc package. This package does not have to be installed but is locally referenced.
The notebooks in Notebooks/16p_FC_profile.ipynb and Notebooks/22q_FC_profile.ipynb illustrate the identified FC signatures for the 16p11.2 and 22q11.2 deletion carriers respectively. These findings are based on the analysis scripts in the Scripts folder that have been run in the following order:
Scripts/preprocess_data.mis an exampleNIAKpreprocessing script to preprocess the raw anatomical and functional data.Scripts/generate_connectomes.mis an exampleNIAKanalysis script to compute the seed-based functional connectome for the MIST_64 atlas. This analysis step also implements the regression of noise confounds from the preprocessed functional time series data.Scripts/recast_vectorized_connectome_to_matrix.pyis a helper script to re-organize the vectorized connectome from the Matlab style column major ordering to the numpy style row major ordering.Scripts/FC_case_control_contrast.pyis an analysis script to compute the case-control FC profiles reported in the paper (including the 16p11.2 and 22q11.2 CNV FC profiles)Scripts/CNV_FC_profile_enrichment.pyis an analysis script to compute the similarity between the FC connectomes of individuals in the idiopathic neuropsychiatric samples and the identified CNV FC profiles.Scripts/null_model.pyis a helper script to compute a distribution of randomly permuted FC profiles to compute exact p-values against.