Renato Polimanti, PhD, MSc

My research focuses on dissecting the epidemiology and biology of neuropsychiatric disorders, behavioral traits, and other complex phenotypes using molecular, clinical, and imaging data to translate Big Data Analytics into improved healthcare for diverse populations.

Main areas of research include:

Internalizing Disorders. My colleagues and I are investigating the predisposition to internalizing disorders and symptoms, integrating genetic information with multi-omics data, brain imaging phenotypes, and electronic health records. Our findings highlighted how pleiotropic mechanisms contribute to disorders across internalizing spectrum through direct, mediated, and interactive effects.

Mental and Physical Health. My group is developing and applying analytic approaches to investigate comorbidities between mental and physical health using large-scale genome-wide datasets and multi-omics information. Our studies uncovered how the interplay among different genomic features and environmental factors contributes to comorbidity risk, symptoms, and prognosis.

Social Determinants of Health. Leveraging large-scale datasets and genetically informed study designs, my colleagues and I contributed to disentangling dynamics by which social determinants of health contribute to the risk of psychiatric disorders and symptoms. Specifically, our findings highlighted how social determinants of health differentially affected mental health outcomes through direct and indirect effects.

Sex Differences. I am leading multiple studies to understand the biological processes contributing to sex differences in psychiatric disorders and other brain-related outcomes using genomic, clinical, and imaging data. These efforts uncovered how sex-specific mechanisms affecting genomic regulatory mechanisms can differentiate the predisposition to pathological conditions in females and males.

Human Evolution. My collaborators and I are developing and applying multiple analytic approaches to integrate evolutionary biology and human genetics, aiming to uncover genetic signatures of population dynamics across human phenome. Our findings highlighted how local adaptation, purifying selection, introgression from archaic humans, and assortative mating can shape the genetic architecture of complex traits in worldwide populations.