Publications by authors named "G Panagiotaropoulou"
Bipolar disorder is a leading contributor to the global burden of disease. Despite high heritability (60-80%), the majority of the underlying genetic determinants remain unknown. We analysed data from participants of European, East Asian, African American and Latino ancestries (n = 158,036 cases with bipolar disorder, 2.
View Article and Find Full Text PDFBackground: Accurate diagnosis of bipolar disorder (BPD) is difficult in clinical practice, with an average delay between symptom onset and diagnosis of about 7 years. A depressive episode often precedes the first manic episode, making it difficult to distinguish BPD from unipolar major depressive disorder (MDD).
Aims: We use genome-wide association analyses (GWAS) to identify differential genetic factors and to develop predictors based on polygenic risk scores (PRS) that may aid early differential diagnosis.
Recent advancements in Parkinson's disease (PD) drug development have been significantly driven by genetic research. Importantly, drugs supported by genetic evidence are more likely to be approved. While genome-wide association studies (GWAS) are a powerful tool to nominate genomic regions associated with certain traits or diseases, pinpointing the causal biologically relevant gene is often challenging.
View Article and Find Full Text PDFArticle Synopsis
- * The research identified 12 significant genetic markers linked to MG, with certain markers associated specifically with early-onset (under 50) and late-onset (50 and older) forms of the disease.
- * Additionally, the study highlighted the potential role of genetic factors in determining the age of disease onset and demonstrated that polygenic risk scores could help predict MG status, explaining over 4% of the variation in disease presence.
Background: Schizophrenia genome-wide association studies (GWASes) have identified >250 significant loci and prioritized >100 disease-related genes. However, gene prioritization efforts have mostly been restricted to locus-based methods that ignore information from the rest of the genome.
Methods: To more accurately characterize genes involved in schizophrenia etiology, we applied a combination of highly-predictive tools to a published GWAS of 67,390 schizophrenia cases and 94,015 controls.