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A meta-analysis of areas of structural variation in grey matter in individuals with Autism Spectrum Disorder (ASD) in relation to gene expression of candidate ASD genes

Camasio, A.; Panzeri, E.; Mancuso, L.; Liloia, D.; Manuello, J.; Ferraro, M.; Cauda, F.; Costa, T.

2021-04-02 neuroscience
10.1101/2021.04.01.438054 bioRxiv
Show abstract

Autism Spectrum Disorder (ASD) is a set of developmental pathologies with a strong genetic basis and high heritability. Although neuroimaging studies have indicated anatomical changes in grey matter (GM) morphometry, their associations with gene expression remain elusive. In the present study, we aim to understand how gene expression correlates with structural brain aberration in ASD and how it distributes in a functional network perspective. First, we performed an activation likelihood estimation (ALE) meta-analysis to determine GM alteration in the brain, then we selected genes from the SHANK, NRXN, NLGN family and MECP2, which have been implicated with ASD, particularly in regards to altered synaptic transmission. Gene expression maps were built. We then assessed the correlation between the gene expression maps and the GM alteration maps. We found that the default mode network regions were the most significantly correlated with gene expression of selected genes in both areas of GM decrease and increase. The dorsal attention and the cerebellar network regions are significantly correlated with ASD genes. Different networks, namely somatomotor, limbic and basal ganglia/thalamus network - were found in the increase; for each of these networks, however, only a few genes were significant. Our approach allowed to combine the well beaten path of genetic and brain imaging in a novel way, to specifically investigate the relation between gene expression and brain with structural damage, and individuate genes of interest for further investigation in specific functional networks.

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