Arden Moscati

This study quantifies cancer risk and penetrance in CHEK2 heterozygotes using genomic data from two large biobanks, finding increased risks for several cancers and younger age of onset.

This study identifies 53 genetic loci associated with hearing loss, including 15 novel ones, using genome-wide and exome-sequencing data from multiple cohorts.

The paper identifies a rare variant that lowers ACE2 expression and reduces COVID-19 risk, and develops a genetic risk score predicting severe disease.

This study links genomic data with EHRs to identify health outcomes enriched in sub-populations, revealing both known and novel associations.

This paper reports on a pilot genomic screening program in a diverse population, finding higher return rates for hATTR results in African/African American and Hispanic/Latinx participants.

This study identifies 59 sentinel variants and two novel genes associated with telomere length using whole genome sequences from 109,122 trans-ethnic individuals.

This study identifies 5,552 blood-cell trait-variant associations across 746,667 individuals from 5 global populations, including 71 novel loci and ancestry-specific variants not found in European ancestry populations.

This study identifies 5,106 new genetic variants associated with blood cell traits using large-scale GWAS, highlighting the polygenic and monogenic basis of hematopoiesis.

The paper uses exome sequencing and EHR data to find BRCA1/2 pathogenic variants in a diverse biobank population, revealing high prevalence in certain ancestry groups and gaps in knowledge for non-European populations.

The paper identifies germline genetic variants associated with clonal hematopoiesis of indeterminate potential (CHIP) using whole genome sequences from the TOPMed program.

This study evaluates polygenic risk scores for schizophrenia in electronic health records, finding strong associations with schizophrenia and pleiotropic effects on other psychiatric and medical conditions.

The paper constructs a polygenic risk atlas for 33 traits in emerging adults and finds genetic risks for schizophrenia, neuroticism, and depression predict various phenotypes.

The paper uses GWAS data to identify polygenic risk scores for drug metabolism pathways, finding that the GO:17144 pathway is significantly predictive of recurrent depressive disorder.

This paper investigates how global polygenic risk scores, sex, and their interaction predict schizophrenia risk using a classification model, finding sex and polygenic risk are the strongest predictors.