Kristian Hveem

SAIGE-GENE is a scalable generalized linear mixed model for region-based association tests in large cohorts, efficiently handling over 400,000 samples with controlled type I error rates.

This study identifies five BMI-associated loci across 12 time points in children, highlighting transient effects of common genetic variation in the leptin signaling pathway during infancy.

This study identifies 42 genetic loci associated with excessive daytime sleepiness and links them to phenotypic subgroups and related traits.

This study identifies 147 genetic loci associated with eGFR, including 53 novel ones, and finds sex-specific effects on kidney function.

Exomes of 49,960 UK Biobank participants reveal 231,631 predicted loss-of-function variants (>10-fold more than imputed data); burden tests implicate PIEZO1, MEPE, and COL6A1 in disease traits.

The paper identifies 57 genomic regions associated with insomnia symptoms, linking them to phototransduction, ubiquitination, and potential causal relationships with coronary heart disease and depression.

This paper introduces SAIGE, a method that improves the accuracy of genetic association tests in unbalanced case-control studies by using saddlepoint approximation, and demonstrates its effectiveness on UK Biobank data.

This study identifies 111 genetic loci and 163 risk variants associated with atrial fibrillation using a GWAS of over 1 million individuals.

This paper estimates narrow-sense heritability using identity-by-descent information in unrelated individuals and finds that IBD-based methods can capture rare variant contributions but are affected by stratification.

This study identifies two new genetic loci associated with aortic valve stenosis through a large genome-wide association study.