Publications by authors named "P H Berthet"
Objective: The clinical diversity of schizophrenia is reflected by structural brain variability. It remains unclear how this variability manifests across different gray and white matter features. In this meta- and mega-analysis, the authors investigated how brain heterogeneity in schizophrenia is distributed across multimodal structural indicators.
View Article and Find Full Text PDFArticle Synopsis
- Solving mRNA transcript structures is challenging with traditional methods, but long-read sequencing addresses this by providing direct sequence information.
- A new targeted enrichment method was developed to capture transcripts of genes related to hereditary breast and ovarian cancer, leading to the identification of 1,231 unique transcripts in eight patients.
- The SOSTAR pipeline successfully annotated transcript structures and discovered key splicing events, including the identification of a retrotransposon related to unexplained inheritance cases.
Background: Clinical forecasting models have potential to optimize treatment and improve outcomes in psychosis, but predicting long-term outcomes is challenging and long-term follow-up data are scarce. In this 10-year longitudinal study, we aimed to characterize the temporal evolution of cortical correlates of psychosis and their associations with symptoms.
Design: Structural magnetic resonance imaging (MRI) from people with first-episode psychosis and controls (n = 79 and 218) were obtained at enrollment, after 12 months (n = 67 and 197), and 10 years (n = 23 and 77), within the Thematically Organized Psychosis (TOP) study.
Background: pathogenic variants (PV) have been recently identified as the most frequent variants predisposing to Sonic Hedgehog (SHH) medulloblastomas (MB); however, guidelines are still lacking for genetic counseling in this new syndrome.
Methods: We retrospectively reviewed clinical and genetic data of a French series of 29 -mutated MB.
Results: All patients developed SHH-MB, with a biallelic inactivation of found in 24 tumors.
Article Synopsis
- The study checked how well the BOADICEA model predicts breast cancer risk for people who carry certain gene changes (called pathogenic variants).
- They looked at information from a group of over 1,600 participants and found that the model worked really well, especially when considering family history and other risk factors.
- The results can help doctors and patients make better choices about cancer management, and the model can be accessed for free on the CanRisk website.