Babak Moatamed

Analysis of a deeply-phenotyped familial hypercholesterolemia cohort from Mexico shows a role for both rare and common alleles across known dyslipidemia genes and reveals structural variation in a novel locus.

The paper analyzes a Mexican FH cohort to show rare and common alleles in FH genes and a novel locus contribute to disease risk, with replication in UK Biobank.

Polygenic risk score portability for common diseases across genetically diverse populations

This study evaluates polygenic risk score (PRS) performance across four ancestry groups for 14 diseases, finding that ancestry-specific PRS models improve accuracy and identifying cross-trait interactions.

Meta-analysis fine-mapping is often miscalibrated at single-variant resolution

This paper shows that meta-analysis fine-mapping is often miscalibrated due to cohort heterogeneity and introduces a QC method to identify suspicious loci.

Global Biobank Meta-analysis Initiative: powering genetic discovery across human diseases

Meta-analysis of harmonized GWAS from up to 18 biobanks (six ancestry groups) across 14 endpoints replicated 320 known loci and identified 188 apparently novel loci.

Validating and automating learning of cardiometabolic polygenic risk scores from direct-to-consumer genetic and phenotypic data: implications for scaling precision health research.

This study validates and automates polygenic risk score (PRS) development for cardiometabolic diseases using direct-to-consumer genetic and phenotypic data, showing comparable performance to larger clinical datasets.

Predicting the effects of epidural stimulation to improve hand function in patients with spinal cord injury: An active learning-based solution using dynamic sample weighting

This paper develops a deep learning framework with active learning to predict the effects of cervical epidural stimulation on hand function in spinal cord injury patients, achieving 15% prediction error.