bioRxiv Science⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/2020.08.04.235994

Genetic analysis of obstructive sleep apnoea discovers a strong association with cardiometabolic health

Strausz, S.·Ruotsalainen, S. E.·Ollila, H. M.·Karjalainen, J.·Reeve, M.·Kurki, M.·Mars, N.·Havulinna, A. S.·Kiiskinen, T.·Mansour Aly, D.·Ahlqvist, E.·Teder-Laving, M.·Palta, P.·Groop, L.·Magi, R.·Makitie, A.·Salomaa, V.·Bachour, A.·Tuomi, T.·Palotie, A.·Palotie, T.·Ripatti, S.
View original source ↗Export metadata ↓

Abstract

There is currently only limited understanding of the genetic aetiology of obstructive sleep apnoea (OSA). The aim of our study is to identify genetic loci associated with OSA risk and to test if OSA and its comorbidities share a common genetic background. We conducted the first large-scale genome-wide association study of OSA using FinnGen Study (217,955 individuals) with 16,761 OSA patients identified using nationwide health registries. We estimated 8.3% [0.06-0.11] heritability and identified five loci associated with OSA (P < 5.0 x 10-8): rs4837016 near GTPase activating protein and VPS9 domains 1 (GAPVD1), rs10928560 near C-X-C motif chemokine receptor 4 (CXCR4), rs185932673 near Calcium/calmodulin-dependent protein kinase ID (CAMK1D) and rs9937053 near Fat mass and obesity-associated protein (FTO) - a variant previously associated with body mass index (BMI). In a BMI-adjusted analysis, an association was observed for rs10507084 near Rhabdomyosarcoma 2 associated transcript (RMST)/NEDD1 gamma-tubulin ring complex targeting factor (NEDD1). We found genetic correlations between OSA and BMI (rg=0.72 [0.62-0.83]) and with comorbidities including hypertension, type 2 diabetes (T2D), coronary heart disease (CHD), stroke, depression, hypothyroidism, asthma and inflammatory rheumatic diseases (IRD) (rg > 0.30). Polygenic risk score (PRS) for BMI showed 1.98-fold increased OSA risk between the highest and the lowest quintile and Mendelian randomization supported a causal relationship between BMI and OSA. Our findings support the causal link between obesity and OSA and joint genetic basis between OSA and comorbidities.

Source connections

Explore related subjects

geneticsPreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Strausz, S., Ruotsalainen, S. E., Ollila, H. M., Karjalainen, J., Reeve, M., Kurki, M., Mars, N., Havulinna, A. S., Kiiskinen, T., Mansour Aly, D., Ahlqvist, E., Teder-Laving, M., Palta, P., Groop, L., Magi, R., Makitie, A., Salomaa, V., Bachour, A., Tuomi, T., Palotie, A., Palotie, T., Ripatti, S.. 2020-08-04. Genetic analysis of obstructive sleep apnoea discovers a strong association with cardiometabolic health. https://doi.org/10.1101/2020.08.04.235994

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

A genetic screen to identify host factors required for commensal bacterial adherence to the gut epithelia

Bacterial adherence to gut epithelial cells likely involves host genetic components. We isolated a gut commensal bacterium, Lelliottia jeotgali, that can robustly colonize C. elegans through attachment to intestinal epithelial cells. Here, we developed a novel screen in C. elegans to identify host genes required for microbiome bacterial colonization. Using transgenic L. jeotgali strain expressing tdTomato, we conducted forward genetic screens in C. elegans to select for mutants that completely lost colonization. We identified multiple allelic mutations in five different C. elegans genes, termed knockout of Lelliottia adherence (kola) mutants, with a near complete loss of adherence. Each of kola-1-5 is uncharacterized and predicted to encode for a secreted or membrane-bound protein. We also identified gly-5, a GalNAc transferase that initiates O-linked glycosylation. Overall, we describe the first C. elegans screen to identify host factors that control microbiome bacterial colonization in the gut.

genetics↗
bioRxiv2026

Deciphering the Dynamics of Leukemogenic Transformation from Clonal Hematopoiesis in Congenital Neutropenia

Inherited neutropenia syndromes, severe congenital neutropenia (CN) and Shwachman-Diamond syndrome (SDS), confer a high cumulative risk of MDS and AML. It is not yet clear which somatic mutations, in which combination, allele frequency and sequence identify patients at high risk. We analyzed clonal hematopoiesis (CH) in the largest representative cohort of inherited neutropenia patients to date - 658 samples from 309 patients - using error-corrected panel sequencing with longitudinal sampling. This was complemented in selected cases by single-cell DNA sequencing and genotyping of single-cell derived colonies. CH was detected in early childhood, affecting 37.7% of CN and 60% of SDS patients. The somatic mutation burden remained essentially unchanged over decades. In CN, CSF3R mutations were dominant across genetic subtypes, while additional mutations were rare and included ASXL1, TET2, and DNMT3A. ASXL1 mutations most frequently co-occurred with CSF3R mutations. Co-occurring CSF3R and TP53 mutations were only found in SRP54-CN and CLPB-CN patients. In SDS, TP53 was the most frequently mutated gene, followed by low-prevalence somatic mutations in DNMT3A, IDH1, PTPN11, and RUNX1. In CN-MDS/AML, RUNX1 and SETBP1 mutations emerged shortly before progression to MDS/AML, and membrane-proximal CSF3R mutations only at the leukemic stage. In SDS, biallelic TP53-mutant clones expanded prior to transformation, and a variant allele frequency (VAF) of dominant TP53 clone above 0.074 discriminated between patients who progressed and those who did not. Peripheral blood reflected bone marrow genotype for most key drivers. Leukemic transformation in inherited neutropenia is therefore not stochastic, but rather follows a defined mutational sequence, initiated in childhood.

genetics↗
bioRxiv2026

A largely shared genetic architecture underlies Saccharomyces cerevisiae persistence across different mouse host genotypes

The extent to which interactions between microbial and host genotypes shape opportunistic pathogen persistence within hosts is an important open question. To assess the contribution of these interactions to persistence, we used Saccharomyces cerevisiae , a genetically tractable model for studying opportunistic fungal persistence in mammalian hosts. A pooled panel of barcoded haploid segregants from a cross between a laboratory strain and a clinical isolate, together with both parents, was introduced intravenously into seven genetically diverse mouse strains. We measured the relative persistence of segregants in mouse brains and livers using barcode sequencing. Persistence showed transgressive segregation in both organs. On average across the two organs, yeast genotype explained 45.2% of the variance in segregant persistence, whereas yeast genotype-by-host genotype interactions explained only 2.9%. Linkage mapping showed that loci detected in more host genotypes generally explained more phenotypic variance than those detected in fewer host genotypes. At some loci, genetic variation correlated with increased yeast persistence across multiple organs (general loci) while at others increased persistence in one organ came at the cost of decreased persistence in another (antagonistic loci). General loci contributed disproportionately to brain persistence, whereas liver persistence reflected contributions from both classes. The clinical parent showed greater persistence than the laboratory parent in every host-organ combination, and the additive effects of detected loci predicted the direction of this advantage. Overall, this work shows that in this system, relative microbial persistence is polygenic, with a strong additive component and only a very small contribution from microbial genotype-by-host genotype interactions.

genetics↗