Carla Kallen

The paper uses AI-derived retinal thickness phenotypes from 2D images to identify novel genetic loci for neurodegenerative diseases.

This study performs genome-wide association meta-analyses on optic nerve structure biomarkers, identifying novel loci and potential drug targets independent of intraocular pressure.

The paper maps cis- and trans-eQTLs in blood samples to infer gene regulatory networks and prioritize trait-relevant pathways.

The paper develops interpretable neural networks for multi-omics data to predict smoking status, age, and LDL levels, showing improved performance and generalizability across cohorts.

The paper identifies 818 genes influencing DNA methylation in blood using genetic anchors and causal inference, revealing both transcription factors and non-DNA-binding proteins with regulatory roles.

The paper identifies 49 gene drivers of downstream transcriptional changes using population genomics data and RNA-sequencing from 3,072 individuals.