Maarja Lepamets

Genetic determinants of plasma protein levels in the Estonian population

This study identifies genetic determinants of plasma protein levels in the Estonian population, including common, rare, and copy number variants, and provides fine-mapped credible sets for 151 proteins.

A cross-disorder dosage sensitivity map of the human genome

This study identifies 114 genome-wide significant rare CNV-disease associations across 30 neurological disorders, revealing 38 novel triplosensitive genes and developing a model to predict dosage sensitivity.

Omics-informed CNV calls reduce false positive rate and improve power for CNV-trait associations

The paper introduces an omics-informed quality score to improve CNV detection and association analysis by reducing false positives and increasing statistical power.

Advancing our understanding of genetic risk factors and potential personalized strategies in pelvic organ prolapse: largest GWAS to date reveals 19 novel associated loci

This paper identifies 19 novel genetic loci associated with pelvic organ prolapse through the largest GWAS to date and presents a polygenic risk score with predictive value for POP risk.

The individual and global impact of copy number variants on complex human traits

This study identifies 131 CNV signals associated with 47 complex traits in the UK Biobank, revealing new gene functions and linking CNVs to decreased longevity and health outcomes.

Genome-wide association study identifies five risk loci for pernicious anemia and implicates the role of HLA-DR15 haplotype

This study identifies five genetic risk loci for pernicious anemia through a genome-wide association analysis and links the disease to the HLA-DR15 haplotype.

GWAS meta-analysis and gene expression data link reproductive tract development, immune response and cellular proliferation/apoptosis with cervical cancer and clarify overlap with other cervical phenotypes

The paper performs a GWAS meta-analysis of cervical cancer and links it to reproductive tract development, immune response, and cellular proliferation/apoptosis, while also identifying genetic risk factors for other cervical phenotypes.

Genome-wide study identifies association between HLA-B*55:01 and penicillin allergy

The paper identifies HLA-B*55:01 as a genetic risk factor for penicillin allergy through genome-wide analysis of electronic health records and imputed HLA data.

Leveraging biobank-scale rare and common variant analyses to identify ASPHD1 as the main driver of reproductive traits in the 16p11.2 locus

The paper identifies ASPHD1 as a key driver of reproductive traits in the 16p11.2 locus using biobank data, Mendelian randomization, and animal models.

Gene content of the fish-hunting cone snail Conus consors

The paper analyzes transcriptomic and genomic data from Conus consors to identify protein sequences and conopeptides.

The genetic architecture of sporadic and recurrent miscarriage

This study identifies genetic variants associated with sporadic and recurrent miscarriage through large-scale association analyses and Mendelian randomization.

Polygenic prediction of breast cancer: comparison of genetic predictors and implications for screening

This paper compares genetic risk scores for breast cancer, finding that a combined metaGRS2 provides the strongest predictive ability in two cohorts.

The complement system supports normal postnatal development and gonadal function in both sexes

The paper identifies CSMD1 variants linked to gonadal function in both sexes and shows that Csmd1 knockout mice have reproductive defects, implicating the complement system in postnatal development.

FastGT: an alignment-free method for calling common SNVs directly from raw sequencing reads

FastGT calls common SNVs from raw sequencing reads using k-mer frequency analysis, achieving high concordance with reference genotypes.

StrainSeeker: fast identification of bacterial strains from unassembled sequencing reads using user-provided guide trees.

StrainSeeker identifies bacterial strains from unassembled sequencing reads using guide trees, successfully detecting Escherichia coli strains in mixed samples within 5 minutes.