Manolis Kogevinas

This paper develops a germline polygenic score (PRSagg) to predict prostate cancer aggressiveness and validates it across multiple datasets.

This study identifies novel genetic risk loci for pancreatic ductal adenocarcinoma in African ancestry individuals through admixture mapping and GWAS.

This study identifies genetic risk loci and factors underlying clinical subtypes of bipolar disorder using GWAS and meta-analysis.

This paper develops a multi-cancer PRS constellation model integrating genetic and lifestyle factors to predict cancer risk, finding that lifestyle PRSs have limited utility but genetic PRSs remain important.

The paper improves prostate cancer risk stratification across multiple ancestries using a new polygenic hazard score with additional SNPs, showing higher hazard ratios and positive predictive value for clinically significant prostate cancer.

This study improves a polygenic hazard score for prostate cancer by adding 120 SNPs, enhancing hazard ratios but not positive predictive value of PSA testing.

The paper examines common genetic variants' contribution to bipolar disorder risk in multiplex families and finds higher polygenic risk scores in affected individuals compared to controls and unaffected family members.

This study identifies genetic effects on birth weight and their impact on cardio-metabolic traits, distinguishing fetal and maternal contributions.

This study integrates a large prostate cancer GWAS with gene expression data to identify 235 genes associated with risk, prioritizing causal genes through Bayesian credible sets.

This paper conducts a GWAS on suicide attempt across psychiatric disorders, identifying genetic loci and showing polygenic risk for major depression predicts suicide attempt in multiple disorders.

This study identifies maternal genetic variants associated with offspring birth weight using GWAS and SEM, showing independent effects from fetal genetics.

This study investigates the genetic contributions to gestational weight gain, finding that maternal common variants explain about 20% of variability, while fetal variants have a minor role.