Abstract
Hundreds of genetic loci participate to schizophrenia liability. It is also known that impaired cerebral connectivity is directly related to the cognitive and affective disturbances in schizophrenia. How genetic susceptibility and brain neural networks interact to specify a pathological phenotype in schizophrenia remains elusive. Imaging genetics, highlighting brain variations, has proven effective to establish links between vulnerability loci and associated clinical traits. As previous imaging genetics works in schizophrenia have essentially focused on structural DNA variants, these findings could be blurred by epigenetic mechanisms taking place during gene expression. We explored the meaningful links between genetic data from peripheral blood tissues on one hand, and regional brain reactivity to emotion task assayed by blood oxygen level-dependent functional magnetic resonance imaging on the other hand, in schizophrenia patients and matched healthy volunteers. We applied Sparse Generalized Canonical Correlation Analysis to identify joint signals between two blocks of variables: (i) the transcriptional expression of 33 candidate genes, and (ii) the blood oxygen level-dependent activity in 16 region of interest. Results suggested that peripheral transcriptional expression is related to brain imaging variations through a sequential pathway, ending with the schizophrenia phenotype. Generalization of such an approach to larger data sets should thus help in outlining the pathways involved in psychiatric illnesses such as schizophrenia.
Highlights
Schizophrenia (SCZ) is a severe psychiatric disorder arising from complex and dynamic interactions between genetic and environmental factors
Concomitant advances in genomic technologies and massive increase in sample sizes through large consortia allowed mega genome-wide association study (GWAS) analysis that identified over 100 common variants conveying risk for SCZ at conventionally accepted standards of significance.[2]
In this context of translational emerging explorations of the intricate links between peripheral molecular changes, brain function and behavioral responses, we proposed to use Sparse Generalized Canonical Correlation Analysis (SGCCA) to explore how variations in the transcriptional expression of candidate genes and blood oxygen level-dependent (BOLD) activity in specific regions of interest (ROI) might infer the complex phenotype of SCZ patients
Summary
Schizophrenia (SCZ) is a severe psychiatric disorder arising from complex and dynamic interactions between genetic and environmental factors. SGCCA allows to jointly examine a set of more than two blocks of heterogeneous data, while taking into account a structural design describing the relationships between these blocks.[25] SGCCA has been successfully applied to several kinds of multi-block data sets.[25,26,27] In this context of translational emerging explorations of the intricate links between peripheral molecular changes, brain function and behavioral responses, we proposed to use SGCCA to explore how variations in the transcriptional expression of candidate genes and BOLD activity in specific regions of interest (ROI) might infer the complex phenotype of SCZ patients. Bilateral regions were very informative, and comprised the ACC, the DLPFC, the FG and the STG (shaded columns on the right side of Table 2)
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