Kristi Läll

Novel loci and multi-omics risk models for rheumatoid arthritis through a million-participant genome-wide association meta-analysis

This paper identifies novel genetic loci and polygenic risk scores for rheumatoid arthritis using a million-participant meta-analysis and shows improved risk prediction with metabolomic integration.

Polygenic Risk Links to the Gut Microbiome: The MAGI Catalog

The paper links polygenic risk scores to gut microbiome traits using the Estonian Microbiome Cohort, identifying 282 species-level associations and suggesting microbiome mediation of genetic risk.

Disentangling Type 2 Diabetes Risk and Comorbidity Using Genomic Structural Equation Modeling

This study uses genomic structural equation modeling to identify latent genetic factors underlying T2D and its comorbidities, showing distinct risk profiles and broader associations with complications.

Transferability and accuracy of electronic health record-based predictors compared to polygenic scores

This study compares EHR-based phenotype risk scores (PheRS) and polygenic scores (PGS) for predicting 13 diseases, finding they capture independent information and improve prediction when combined.

From Biobanking to Personalized Medicine: the journey of the Estonian Biobank

The paper reviews the Estonian Biobank's role in advancing genomics research and personalized medicine through its comprehensive data and translational focus.

Genome-wide association meta-analysis identifies novel ancestry-specific primary open-angle glaucoma loci and shared biology with vascular mechanisms and cell proliferation

This study identifies ancestry-specific and sex-specific genetic loci for primary open-angle glaucoma through a meta-analysis of 15 biobanks, highlighting shared biology with vascular mechanisms and cell proliferation.

Evaluation of polygenic scoring methods in five biobanks reveals greater variability between biobanks than between methods and highlights benefits of ensemble learning

This study evaluates polygenic scoring methods across five biobanks and finds that biobank differences outweigh method differences, with ensemble learning improving performance.

Genetic insights into the age-specific biological mechanisms governing human ovarian ageing

The paper identifies age-specific genetic effects on age at natural menopause using UK Biobank data, revealing varying biological pathways and health outcomes across menopause timing.

Global biobank analyses provide lessons for developing polygenic risk scores across diverse cohorts

This study evaluates polygenic risk score methods across diverse biobanks and ancestries, finding that European reference panels often yield better performance, while PRS-CS outperforms P+T for high-heritability traits.

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.

Improving GWAS discovery and genomic prediction accuracy in Biobank data

This paper improves genomic prediction and GWAS discovery in biobank data using a Bayesian grouped mixture of regressions model, achieving higher accuracy and detecting more loci than existing methods.

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.

Novel discoveries and enhanced genomic prediction from modelling genetic risk of cancer age-at-onset

This paper improves cancer genomic prediction by analyzing age-at-diagnosis instead of case-control data, finding new genomic regions and enhancing prediction accuracy using Bayesian time-to-event modeling.

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.

Genomic architecture and prediction of censored time-to-event phenotypes with a Bayesian genome-wide analysis

This paper introduces BayesW, a Bayesian method for analyzing time-to-event phenotypes, showing improved statistical power and prediction accuracy for age-at-onset traits in large-scale datasets.

Advantages of genotype imputation with ethnically matched reference panel for rare variant association analyses

This study compares the effectiveness of ethnically matched and mixed reference panels for imputing rare variants in GWAS, showing improved detection of rare variant associations with matched panels.

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.

Genomic underpinnings of lifespan allow prediction and reveal basis in modern risks

The paper identifies genetic loci associated with lifespan using genome-wide association and shows that variants linked to modern diseases explain most lifespan variation.

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.

Fine-mapping of an expanded set of type 2 diabetes loci to single-variant resolution using high-density imputation and islet-specific epigenome maps

This study fine-maps type 2 diabetes loci to single-variant resolution using high-density imputation and islet-specific epigenome maps, identifying 73 variants with >80% posterior probability of association.