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Di Camillo, F.

Publications and source records attributed to Di Camillo, F..

2 recordsLinked to original sources

Liquidity of gene co-expression trajectories across the lifespan highlights delayed maturation and the perinatal GABA switch in schizophrenia risk

Schizophrenia genetic and environmental risk factors play out largely in early life, biasing development toward a pathogenic trajectory that becomes clinically apparent in early adulthood, when the disorder typically onsets. Here, we convert snapshots of gene expression in postmortem brain at a moment in time into a dynamic lifetime series employing the "liquidity" metric, a novel tool to track the evolution of networks across time from a multi-systemic perspective. The landscape of normal prefrontal cortical development becomes increasingly "liquid" during the first two decades of post-natal life, with sharp discontinuities in known critical periods such as birth and adolescence. Neurotypical individuals free of apparent neuropathology with relatively elevated polygenic risk scores for schizophrenia exhibit a generalized delay in the dynamics of liquidity across these trajectories compared to below-average-risk individuals. Impacted biological processes strongly converge on delayed GABA-A receptor functional maturation, involved in establishing Excitatory/Inhibitory balance in brain during early development. Similar to patients with schizophrenia, neurotypical high-risk individuals show an increased expression ratio between the genes SLC12A2 (protein NKCC1) and SLC12A5 (protein KCC2) relative to low-risk, involved in the control of the equilibrium potential of chloride ions that regulates GABA-A function. These results provide evidence that genetic risk for schizophrenia is associated with a delayed maturational profile and delayed maturation of GABAergic signaling without detectable neuropathology and well before the age of clinical onset. Interestingly, the same effect is not observed in the hippocampus and is not observed with genetic risk for other neuropsychiatric and immune conditions. The dynamics of maturation of GABA-A signaling in the dorsolateral prefrontal cortex emerge as an early contributor to translating genetic risk into an altered developmental trajectory associated with schizophrenia.

genomics↗

Co-expression-based models improve eQTL predictions and highlightnovel transcriptome-wide genes associated with schizophrenia

Non-coding genetic variants statistically associated with complex heritability phenotypes are thought to act primarily through transcriptome regulatory mechanisms. Predictions of gene expression in tissue like the human brain traditionally rely primarily on cis-eQTLs. Here, we introduce INGENE and MODULE, trans-eQTLs models designed to enhance the prediction of gene expression by capturing the collective impact of candidate trans-eQTLs acting within co-expression networks. Exploiting RNA-seq data in six post-mortem brain regions (amygdala, caudate nucleus, dorsal/subgenual anterior cingulate cortex, dorsolateral prefrontal cortex, and hippocampus), we validate our models on two testing datasets, demonstrating increased gene predictability compared to both an original cis-based model and to EpiXcan, the leading benchmark in cis-model performance. Integration of cis- and trans-predictions significantly improves gene-level expression imputation (MLE = 0.05) for 18,744 genes across the six brain regions considered. Applying cis and trans models to PGC wave 3 genotypes identifies 766 SCZ-associated genes across brain regions (pFDR < .01), emphasizing the complementary nature of cis and trans predictions in trait association discovery. Of these genes, 641 represent novel transcriptome-wide associations with schizophrenia, highlighting the role of trans-heritability and genetic interactions underlying risk for this disorder, in addition to further supporting 125 previous candidates.

genomics↗