Renato Polimanti, PhD, MSc

My research group is developing analytic approaches to investigate the polygenicity and pleiotropy of human traits and diseases using large-scale genome-wide datasets and multi-omics information. We apply a range of methods, such as polygenic risk scoring, causal inference analyses, and structural equation modeling, to dissect the molecular basis of complex traits and to understand how genetic information can be used to improve the healthcare of diverse populations.

Investigating the systems genetics of the patterns of polysubstance abuse and addiction. The aim of this project is to conduct a genome-wide analysis of polysubstance use patterns and investigate the results with respect to longitudinal data and epigenetic information.

Genome-wide Investigation of the Interplay Between Age-Related Hearing Loss and Smoking Behaviors. The aim of this project is to conduct a genome-wide analysis to understand the mechanisms by which smoking is associated with hearing loss.

Genomics of Gulf War illness (GWI) in veterans. The primary objective is to identify genetic variants associated with GWI, and also understand their interplay with Gulf War environmental exposures associated with the risk of developing GWI.

Integrating trait-specific design and multi-omics information to increase the portability of polygenic risk scoring across internalizing disorders. The aim of this project is to integrate and optimize of multiple features to improve the portability of PRS instruments across internalizing disorders affecting diverse populations.

The impact of socioeconomic factors on psychiatric and somatic comorbidities of schizophrenia: a genetically-informed epidemiological study. Our goal is to generate information that can be used to design initiatives more effective in reducing the impact of health disparities on SCZ morbidity and mortality.

Leveraging genomic data to dissect the association of internalizing disorders with the risk, onset, and vulnerability of COVID-19. This study will leverage genome-wide information together with other omics datasets to dissect the epidemiological and biological network linking internalizing disorders to COVID-19.