Linda Kachuri

The paper identifies estrogen-modulated SNVs associated with breast cancer risk and shows their interaction with reproductive factors using polygenic risk scores.

The paper analyzes expression and splicing quantitative trait loci (e/sQTL) across multiple tissues in the TOPMed dataset and finds that secondary e/sQTL signals are still discoverable, with many GWAS signals colocalizing with these e/sQTL.

This study finds that allele frequencies at recessive disease genes are mainly shaped by pleiotropic effects in heterozygotes, not purely recessive selection.

This paper evaluates polygenic risk scores (PRSs) in diverse populations using absolute risk models, finding that PRSs can provide greater utility in risk stratification for certain diseases in non-European populations.

This paper develops a germline polygenic score (PRSagg) to predict prostate cancer aggressiveness and validates it across multiple datasets.

This study integrates MRI radiomics and germline genetics to predict IDH mutation status in gliomas, improving classification accuracy and prognostic risk assessment.

This study identifies genetic associations between blood cell traits and glioma risk and survival, highlighting immune-mediated mechanisms and subtype-specific effects.

The paper identifies a non-coding risk variant in GBA1 associated with Parkinson's disease in African ancestry populations, showing it disrupts splicing and reduces glucocerebrosidase activity.

This study identifies shared genetic determinants between type 1 diabetes, coronary artery disease, and leukocyte counts, showing genetic associations between leukocyte counts and both diseases.

This study develops a novel polygenic risk score (PRS-CS) for glioma that outperforms existing methods, improving risk prediction and subtype classification using genome-wide association study data.

The paper introduces SuShiE, a model that improves multi-ancestry fine-mapping of cis-molQTLs, identifying more genes and prioritizing functionally enriched variants.

Admix-kit provides tools for genetic analysis of admixed populations, enabling simulation, association testing, and polygenic scoring.

This study identifies 447 new genetic variants associated with prostate-specific antigen levels across multiple ancestries and shows improved cross-ancestry prediction of PSA, with implications for personalized prostate cancer screening.

This study develops a polygenic score to adjust PSA levels, improving the detection of aggressive prostate cancer while reducing unnecessary biopsies.

The paper identifies inverted genomic regions between human reference genome builds that affect imputation accuracy and association testing power, proposing a heuristic to correct these issues.

This study investigates the relationship between genetically predicted leukocyte telomere length and lung cancer risk, finding a causal association and novel susceptibility loci.

This study identifies eight novel lung cancer susceptibility loci and shows that germline variants related to smoking and DNA repair influence somatic mutation burden in lung tumors.

This study identifies 22 genetic variant-phenotype associations linked to multiple primary cancers using whole-exome sequencing in two large multi-ancestry cohorts.

This study uses Mendelian randomization to assess the causal effect of sexual behavior on oropharyngeal cancer risk, finding attenuated associations after adjusting for confounders.

This study identifies genetic variants influencing blood cell traits linked to increased susceptibility to childhood acute lymphoblastic leukemia.

The paper analyzes gene expression in African American and Latino children to show ancestry-specific genetic architecture and highlights the benefits of diverse genomic studies.

This study identifies IL-18 as a biomarker for reduced lung cancer risk using genetic, pre-diagnostic, and tumor expression data, with potential therapeutic implications.

This study evaluates polygenic risk scores across 17 cancer types in two large cohorts, identifying cross-cancer associations and non-cancer phenotype links.

This study identifies six novel genetic loci, including two rare variants, and shows that a polygenic risk score strongly predicts prostate cancer risk.

This study integrates polygenic risk scores with modifiable risk factors and family history to improve cancer risk prediction across 16 cancers using UK Biobank data.

This study identifies genetic loci and amino acid residues associated with immune response to viral infections using serological data from the UK Biobank.

The paper conducts pan-cancer GWAS in two cohorts, identifying novel risk variants and shared genetic basis across 18 cancer types.

The paper identifies genetic links between impaired pulmonary function and increased lung cancer risk, showing causal relationships through Mendelian randomization and highlighting immune-related pathways.