Biology subjects

Gonzalez-Penas, J.

Publications and source records attributed to Gonzalez-Penas, J..

3 recordsLinked to original sources

bioRxiv2026

Sulcal Widening in Schizophrenia Maps onto Sulcal Hubs and Energy-Synaptic Genes

Schizophrenia (SZ) is increasingly framed as a disorder of large-scale brain networks emerging from atypical early neurodevelopment, yet how network architecture relates to cortical folding abnormalities remains unclear. Here, we introduce a sulcal morphological-centred network framework that integrates normative modelling of sulcal width with diffusion-derived structural connectivity and transcriptomic data in a large multisite cohort (n = 5,392; 377 SZ). Individuals with SZ showed widespread sulcal widening, affecting 30 of 40 sulci and most pronounced in frontal, temporal and occipital regions. Critically, sulci with higher degree centrality, reflecting greater embedding within the structural connectome, exhibited disproportionately greater widening in SZ (pspin = 0.02), indicating that network hubs of cortical folding are preferentially affected. Transcriptomic integration using partial least squares regression identified a single component explaining 56.5% of SZ-related sulcal widening variance (pperm = 0.041), implicating genes enriched for synaptic signalling and energy metabolism with adult cortical expression bias and genetic enrichment for cross-disorder psychiatric risk. In contrast, oppositely weighted genes showed prenatal expression bias and enrichment for rare disruptive variants in autism spectrum disorder. Together, these findings link aberrant sulcal morphology in SZ to the brains network topology and molecular architecture, positioning cortical folding as a network-embedded phenotype in SZ.

neuroscience↗

bioRxiv2024

Heterogeneity of morphometric similarity networks in health and schizophrenia

IntroductionMorphometric similarity is a recently developed neuroimaging phenotype of inter-regional connectivity by quantifying the similarity of a region to other regions based on multiple MRI parameters. Altered average morphometric similarity has been reported in psychotic disorders at the group level, with considerable heterogeneity across individuals. We used normative modeling to address cross-sectional and longitudinal inter-individual heterogeneity of morphometric similarity in health and schizophrenia. MethodsMorphometric similarity for 62 cortical regions was obtained from baseline and follow-up T1-weighted scans of healthy individuals and patients with chronic schizophrenia. Cortical regions were classified into seven predefined brain functional networks. Using Bayesian Linear Regression and taking into account age, sex, image quality and scanner, we trained and validated normative models in healthy controls from eleven datasets (n = 4310). Individual deviations from the norm (z-scores) in morphometric similarity were computed for each participant for each network and region at both timepoints. A z-score [greater double equals] than 1.96 was considered supra-normal and a z-score [less double equals] -1.96 infra-normal. As a longitudinal metric, we calculated the change over time of the total number of infra- or supra-normal regions per participant. ResultsAt baseline, patients with schizophrenia had decreased morphometric similarity of the default mode network and increased morphometric similarity of the somatomotor network when compared with healthy controls. The percentage of patients with infra- or supra-normal values for any region at baseline and follow-up was low (<6%) and did not differ from healthy controls. Mean intra-group changes over time in the total number of infra- or supra-normal regions were small in schizophrenia and healthy control groups (<1) and there were no significant between-group differences. ConclusionsIn a case-control setting, a decrease of morphometric similarity within the default mode network may be a robust finding implicated in schizophrenia. However, normative modeling suggests that significant reductions and changes over time of regional morphometric similarity are evident only in a minority of patients.

neuroscience↗

bioRxiv2019

Analyses of rare and common alleles in parent-proband trios implicate rare missense variants in SLC6A1 in schizophrenia and confirm the involvement of loss of function intolerant and neurodevelopmental disorder genes.

Schizophrenia is a highly polygenic disorder with important contributions coming from both common and rare risk alleles, the latter including CNVs and rare coding variants (RCVs), sometimes occurring as de novo variants (DNVs). We performed DNV analysis in whole exome-sequencing data obtained from a new sample of 613 schizophrenia trios, and combined this with published data for a total of 3,444 trios. Loss-of-function (LoF) DNVs were significantly enriched among 3,488 LoF intolerant genes in our new trio data (rate ratio (RR) (95% CI) = 2.23 (1.31, 3.79); p = 2.2 x 10-3), supporting previous findings. In the full dataset, genes associated with neurodevelopmental disorders (NDD; n=160) were significantly enriched for LoF DNVs (RR (95% CI) = 3.32 (2.0, 5.21); p = 7.4 x 10-6). Within this set of NDD genes, SLC6A1, encoding a gamma-aminobutyric acid transporter, was associated with missense-damaging DNVs (p = 5.2 x 10-5). Using data from a subset of 1,122 trios for which we had genome-wide common variant data, schizophrenia polygenic risk was significantly over-transmitted to probands (p = 2.6 x 10-60), as was bipolar disorder common variant polygenic risk (p = 5.7 x 10-17). We defined carriers of candidate schizophrenia-related DNVs as those with LoF or deletion DNVs in LoF intolerant or NDD genes. These individuals had significantly less over-transmission of common risk alleles than non-carriers (p = 3.5 x 10-4), providing robust support for the hypothesis that this set of DNVs is enriched for those related to schizophrenia.

genetics↗