Gina Marie Peloso

A genomic-led strategy to anticipate drug safety effects

The paper uses Mendelian Randomization to predict adverse drug reactions by linking genetic variants to gene expression and protein abundance across large datasets.

Exome wide association study for blood lipids in 1,158,017 individuals from diverse populations

The paper identifies 800 exome-wide significant rare coding variants associated with blood lipids in over a million diverse individuals, including 130 driven by non-European-like populations.

The Biobank Rare Variant consortium powers the discovery of rare genetic associations through global collaboration

The paper establishes a global consortium to discover rare genetic associations by integrating data from multiple biobanks, identifying 514 gene-trait associations, many detectable only through cross-ancestry meta-analysis.

Machine learning cross-platform proteomic imputation enables protein quality scoring and replication of epidemiological associations

This paper develops a machine learning framework to impute cross-platform proteomic data, improving replication of epidemiological findings and protein quality scoring.

The expected polygenic risk score (ePRS) framework: an equitable metric for quantifying polygenetic risk via modeling of ancestral makeup

The paper introduces the expected polygenic risk score (ePRS) framework to address population stratification in polygenic risk score analysis by modeling ancestral makeup, showing it provides equitable risk quantification across diverse populations.

Leveraging Large-Scale Biobanks for Therapeutic Target Discovery

This study uses large biobanks to identify gene-trait pairs with causal evidence, rediscover approved drug targets, and develop a predictive model for drug development.

Human Plasma Proteomic Profile of Clonal Hematopoiesis

The paper identifies plasma proteins associated with clonal hematopoiesis and links them to cardiovascular disease through proteomic and genetic analyses.

Learning Gaussian Graphical Models from Correlated Data

This paper introduces a Bootstrap algorithm to infer Gaussian Graphical Models from correlated data, showing it controls Type I error better than conventional methods in simulations and a real family-based study.

Proteome-Wide Association Studies for Blood Lipids and Comparison with Transcriptome-Wide Association Studies

The paper conducts proteome-wide and transcriptome-wide association studies for blood lipids, finding high-level consistency between proteome and transcriptome-lipid associations across tissues.

Association of Common and Rare Variants with Alzheimer's Disease in over 13,000 Diverse Individuals with Whole-Genome Sequencing from the Alzheimer's Disease Sequencing Project

The paper investigates the association of common and rare variants with Alzheimer's Disease in 13,371 diverse individuals using whole-genome sequencing, identifying significant genetic loci and population-specific associations.

Protein identification for stroke progression via Mendelian Randomization in Million Veteran Program and UK Biobank

This study uses Mendelian randomization to identify two proteins, CCL27 and TNFRSF14, that influence subsequent cardiovascular events after a stroke, suggesting inflammation as a contributing factor.

Key variants via Alzheimer's Disease Sequencing Project whole genome sequence data

This study uses whole genome sequence data from the ADSP to identify 17 significant variants in five genomic regions associated with Alzheimer's disease.

Rare variants in long non-coding RNAs are associated with blood lipid levels in the TOPMed Whole Genome Sequencing Study

The paper identifies 83 rare lncRNA variant sets associated with blood lipid levels using WGS data from the TOPMed program and validates some in UK Biobank data.

Genetic modification of inflammation and clonal hematopoiesis-associated cardiovascular risk

The paper identifies IL1RAP and AIM2 as key modifiers of CHIP-associated cardiovascular risk using UK Biobank data and CRISPR experiments in mice.

Genome-wide association analysis and Mendelian randomization proteomics identify novel protein biomarkers and drug targets for primary prevention of heart failure

This study identifies novel genetic risk variants and potential drug targets for heart failure using GWAS and Mendelian randomization proteomics.

Human gain-of-function variants in HNF1A confer protection from diabetes but independently increase hepatic secretion of multiple cardiovascular disease risk factors

Genome-wide Discovery for Diabetes-Dependent Triglycerides-Associated Loci

This study identifies a genetic variant near HLA-DQB1 associated with lower triglycerides in type 2 diabetes but not in non-diabetic individuals, suggesting immune-related mechanisms.

Polygenic Risk Prediction using Gradient Boosted Trees Captures Non-Linear Genetic Effects and Allele Interactions in Complex Phenotypes

This paper uses gradient boosted trees to improve polygenic risk prediction by capturing non-linear genetic effects and SNP interactions, showing significant increases in variance explained for multiple complex traits.

Bidirectional Mendelian randomization supports bidirectional causality between telomere length and clonal hematopoiesis of intermediate potential

The paper uses bidirectional Mendelian randomization to show LTL lengthening increases CHIP risk, while CHIP accelerates LTL shortening, with modest mediation between CHIP and CAD via LTL.

Alternative splicing of OAS1 alters the risk for severe COVID-19

The paper identifies an alternative splicing variant of OAS1 that provides protection against severe COVID-19 in people of African ancestry, independent of Neanderthal haplotypes.

Exploiting Family History in Aggregation Unit-based Genetic Association Tests

This paper introduces FHAT and FHAT-O methods to incorporate family history in genetic association tests, showing improved power and type I error control in exome-wide analyses of dementia and hypertension.

A system for phenotype harmonization in the NHLBI Trans-Omics for Precision Medicine (TOPMed) Program

The paper describes a system for harmonizing phenotype data across multiple studies in the TOPMed program, enabling reproducible and shared phenotype data for over 80 studies.

Robust, flexible, and scalable tests for Hardy-Weinberg Equilibrium across diverse ancestries

This paper introduces RUTH, a new HWE test that accounts for population structure and genotype uncertainty, showing it reduces false positives compared to traditional methods.

Diverse transcriptomic signatures across human tissues identify functional rare genetic variation

Integrating expression, allelic expression and splicing across tissues identifies rare variants with relevance to traits.

Heterozygous ATP-binding Cassette Transporter G5 Gene Deficiency and Risk of Coronary Artery Disease

This study investigates the impact of heterozygous ABCG5 LoF variants on LDL-C levels and CAD risk, finding a significant association with elevated LDL-C and doubled CAD risk.

EDEM3 modulates plasma triglyceride level through its regulation of LRP1 expression

The paper identifies a missense variant in EDEM3 associated with lower blood triglyceride levels and shows EDEM3 deficiency increases LRP1 expression, reducing plasma TG through enhanced lipoprotein uptake.

Deep-coverage whole genome sequences and blood lipids among 16,324 individuals

The paper analyzes whole genome sequences from 16,324 individuals to identify genetic variants associated with blood lipid levels and develops a polygenic score for LDL-C.

Deep coverage whole genome sequences and plasma lipoprotein(a) in individuals of European and African ancestries

The paper uses whole genome sequencing to identify genetic variants associated with plasma lipoprotein(a) levels and finds high heritability and inter-ethnic differences in Lp(a) risk.

FastSKAT: Sequence kernel association tests for very large sets of markers

FastSKAT improves SKAT's efficiency by approximating tail probabilities with fewer eigenvalues, enabling faster analysis of large genetic datasets.

Refining The Accuracy Of Validated Target Identification Through Coding Variant Fine-Mapping In Type 2 Diabetes

This study identifies 16 causal coding variants in type 2 diabetes using fine-mapping and shows that one third of signals are false leads.