Kristina Zguro

The paper introduces the Proteomic Sex Index (PSI), a continuous measure of plasma proteome alignment with chromosomal sex, showing its association with health and disease traits.

This study identifies genetic variants associated with healthcare costs across multiple systems, finding polygenic influences and large effects from specific loss-of-function variants.

The paper compares genetic effects on disease susceptibility and progression, finding limited overlap and suggesting larger samples or different progression measures are needed.

The paper develops a machine learning model to predict COVID-19 severity using exonic variants from whole exome sequencing data, finding that variants across all frequency categories contribute to severity.

The paper identifies a genetic variant in the SELP gene associated with increased thrombosis risk in male COVID-19 patients, suggesting potential for anti-P-selectin antibody therapy.

The paper proposes a post-Mendelian genetic model integrating common and rare variants to predict severe vs. mild COVID-19 outcomes in an Italian cohort.