Olli Carpén

This study uses spatial transcriptomics to identify interferon pathway enrichment in early relapsing high-grade serous carcinoma, linking it to poor prognosis and suggesting C3 as a biomarker.

This study identifies 1,242 novel genetic variants and 31 novel genes associated with frailty through genome-wide association and proteomics integration.

This study conducts a genome-wide meta-analysis across three biobanks to identify new genetic loci associated with lumbar disc herniation, expanding the known genetic landscape.

This study conducts a GWAS of preeclampsia and hypertensive disorders of pregnancy, identifying 18 genome-wide significant loci, including novel associations with blood pressure and placental function.

Finnish-enriched low-frequency variants, often coding, underlie many GWAS signals across 1,932 register endpoints in 218,792 Finns; a 15-disease meta-analysis with Estonian and UK biobanks adds 30 unreported associations.

This study creates a single-cell atlas of human fetal lung development between 14 and 19 weeks of gestation using snRNA-seq, identifying cell types, trajectories, and communication networks.

This study shows that GANP deficiency in human motor neurons disrupts gene regulation and RNA metabolism, affecting nearly 40% of expressed genes and splicing patterns.

The paper introduces a multivariate GWAS framework that identifies functional variants and disease associations by transforming multivariate results into univariate phenotypes for follow-up analysis.

The paper introduces an interactive workflow called Cyto for analyzing mass cytometry data, demonstrating its ability to capture immune cell sub-populations and tumor compositions in blood and ovarian cancer samples.

The paper identifies a stress-related transcriptional profile in ovarian cancer linked to chemotherapy resistance and poor survival, suggesting MEK1/2 inhibitors as a potential treatment.

PRISM recovers cell type specific expression profiles from composite RNA-seq data, improving patient response prediction compared to raw bulk data.

The paper presents a computational method to identify differentially methylated sites in heterogeneous tumor samples with varying cancer cell fractions, without needing normal controls or prior purity estimates.