Lucía De Hoyos

Publications

Displaying 1 - 3 of 3
  • González-Peñas, J., De Hoyos, L., Díaz-Caneja, C. M., Andreu-Bernabeu, Á., Stella, C., Gurriarán, X., Fañanás, L., Bobes, J., González-Pinto, A., Crespo-Facorro, B., Martorell, L., Vilella, E., Muntané, G., Molto, M. D., Gonzalez-Piqueras, J. C., Parellada, M., Arango, C., & Costas, J. (2023). Recent natural selection conferred protection against schizophrenia by non-antagonistic pleiotropy. Scientific Reports, 13: 15500. doi:10.1038/s41598-023-42578-0.

    Abstract

    Schizophrenia is a debilitating psychiatric disorder associated with a reduced fertility and decreased life expectancy, yet common predisposing variation substantially contributes to the onset of the disorder, which poses an evolutionary paradox. Previous research has suggested balanced selection, a mechanism by which schizophrenia risk alleles could also provide advantages under certain environments, as a reliable explanation. However, recent studies have shown strong evidence against a positive selection of predisposing loci. Furthermore, evolutionary pressures on schizophrenia risk alleles could have changed throughout human history as new environments emerged. Here in this study, we used 1000 Genomes Project data to explore the relationship between schizophrenia predisposing loci and recent natural selection (RNS) signatures after the human diaspora out of Africa around 100,000 years ago on a genome-wide scale. We found evidence for significant enrichment of RNS markers in derived alleles arisen during human evolution conferring protection to schizophrenia. Moreover, both partitioned heritability and gene set enrichment analyses of mapped genes from schizophrenia predisposing loci subject to RNS revealed a lower involvement in brain and neuronal related functions compared to those not subject to RNS. Taken together, our results suggest non-antagonistic pleiotropy as a likely mechanism behind RNS that could explain the persistence of schizophrenia common predisposing variation in human populations due to its association to other non-psychiatric phenotypes.
  • Díaz-Caneja, C. M., Alloza, C., Gordaliza, P. M., Fernández Pena, A., De Hoyos, L., Santonja, J., Buimer, E. E. L., Van Haren, N. E. M., Cahn, W., Arango, C., Kahn, R. S., Hulshoff Pol, H. E., Schnack, H. G., & Janssen, J. (2021). Sex differences in lifespan trajectories and variability of human sulcal and gyral morphology. Cerebral Cortex, 31(11), 5107-5120. doi:10.1093/cercor/bhab145.

    Abstract

    Sex differences in development and aging of human sulcal morphology have been understudied. We charted sex differences in trajectories and inter-individual variability of global sulcal depth, width, and length, pial surface area, exposed (hull) gyral surface area, unexposed sulcal surface area, cortical thickness, and cortex volume across the lifespan in a longitudinal sample (700 scans, 194 participants two scans, 104 three scans, age range: 16-70 years) of neurotypical males and females. After adjusting for brain volume, females had thicker cortex and steeper thickness decline until age 40 years; trajectories converged thereafter. Across sexes, sulcal shortening was faster before age 40, while sulcal shallowing and widening were faster thereafter. While hull area remained stable, sulcal surface area declined and was more strongly associated with sulcal shortening than with sulcal shallowing and widening. Males showed greater variability for cortex volume and thickness and lower variability for sulcal width. Across sexes, variability decreased with age for all measures except for cortical volume and thickness. Our findings highlight the association between loss of sulcal area, notably through sulcal shortening, with cortex volume loss. Studying sex differences in lifespan trajectories may improve knowledge of individual differences in brain development and the pathophysiology of neuropsychiatric conditions.

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  • Janssen, J., Díaz-Caneja, C. M., Alloza, C., Schippers, A., De Hoyos, L., Santonja, J., Gordaliza, P. M., Buimer, E. E. L., van Haren, N. E. M., Cahn, W., Arango, C., Kahn, R. S., Hulshoff Pol, H. E., & Schnack, H. G. (2021). Dissimilarity in sulcal width patterns in the cortex can be used to identify patients with schizophrenia with extreme deficits in cognitive performance. Schizophrenia Bulletin, 47(2), 552-561. doi:10.1093/schbul/sbaa131.

    Abstract

    Schizophrenia is a biologically complex disorder with multiple regional deficits in cortical brain morphology. In addition, interindividual heterogeneity of cortical morphological metrics is larger in patients with schizophrenia when compared to healthy controls. Exploiting interindividual differences in the severity of cortical morphological deficits in patients instead of focusing on group averages may aid in detecting biologically informed homogeneous subgroups. The person-based similarity index (PBSI) of brain morphology indexes an individual’s morphometric similarity across numerous cortical regions amongst a sample of healthy subjects. We extended the PBSI such that it indexes the morphometric similarity of an independent individual (eg, a patient) with respect to healthy control subjects. By employing a normative modeling approach on longitudinal data, we determined an individual’s degree of morphometric dissimilarity to the norm. We calculated the PBSI for sulcal width (PBSI-SW) in patients with schizophrenia and healthy control subjects (164 patients and 164 healthy controls; 656 magnetic resonance imaging scans) and associated it with cognitive performance and cortical sulcation index. A subgroup of patients with markedly deviant PBSI-SW showed extreme deficits in cognitive performance and cortical sulcation. Progressive reduction of PBSI-SW in the schizophrenia group relative to healthy controls was driven by these deviating individuals. By explicitly leveraging interindividual differences in the severity of PBSI-SW deficits, neuroimaging-driven subgrouping of patients is feasible. As such, our results pave the way for future applications of morphometric similarity indices for subtyping of clinical populations.

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