Obstructive sleep apnoea and the risk for coronary heart disease and type 2 diabetes : a longitudinal population-based study in Finland

Objective To evaluate if obstructive sleep apnoea (OSA) modifies the risk of coronary heart disease, type 2 diabetes (T2D) and diabetic complications in a gender-specific fashion. Design and setting A longitudinal population-based study with up to 25-year follow-up data on 36 963 individuals (>500 000 person years) from three population-based cohorts: the FINRISK study, the Health 2000 Cohort Study and the Botnia Study. Main outcome measures Incident coronary heart disease, diabetic kidney disease, T2D and all-cause mortality from the Finnish National Hospital Discharge Register and the Finnish National Causes-of-Death Register. Results After adjustments for age, sex, region, high-density lipoprotein (HDL) and total cholesterol, current cigarette smoking, body mass index, hypertension, T2D baseline and family history of stroke or myocardial infarction, OSA increased the risk for coronary heart disease (HR=1.36, p=0.0014, 95% CI 1.12 to 1.64), particularly in women (HR=2.01, 95% CI 1.31 to 3.07, p=0.0012). T2D clustered with OSA independently of obesity (HR=1.48, 95% CI 1.26 to 1.73, p=9.11x10(-7)). The risk of diabetic kidney disease increased 1.75-fold in patients with OSA (95% CI 1.13 to 2.71, p=0.013). OSA increased the risk for coronary heart disease similarly among patients with T2D and in general population (HR=1.36). All-cause mortality was increased by OSA in diabetic individuals (HR=1.35, 95% CI 1.06 to 1.71, p=0.016). Conclusion OSA is an independent risk factor for coronary heart disease, T2D and diabetic kidney disease. This effect is more pronounced even in women, who until now have received less attention in diagnosis and treatment of OSA than men.Peer reviewe

ANGPTL8 protein-truncating variant associated with lower serum triglycerides and risk of coronary disease

Protein-truncating variants (PTVs) affecting dyslipidemia risk may point to therapeutic targets for cardiometabolic disease. Our objective was to identify PTVs that were associated with both lipid levels and the risk of coronary artery disease (CAD) or type 2 diabetes (T2D) and assess their possible associations with risks of other diseases. To achieve this aim, we leveraged the enrichment of PTVs in the Finnish population and tested the association of low-frequency PTVs in 1,209 genes with serum lipid levels in the Finrisk Study (n = 23,435). We then tested which of the lipid-associated PTVs were also associated with the risks of T2D or CAD, as well as 2,683 disease endpoints curated in the FinnGen Study (n = 218,792). Two PTVs were associated with both lipid levels and the risk of CAD or T2D: triglyceride-lowering variants in ANGPTL8 (-24.0[-30.4 to -16.9] mg/dL per rs760351239-T allele, P = 3.4 x 10(-9)) and ANGPTL4 (-14.4[-18.6 to -9.8] mg/dL per rs746226153-G allele, P = 4.3 x 10(-9)). The risk of T2D was lower in carriers of the ANGPTL4 PTV (OR = 0.70[0.60-0.81], P = 2.2 x 10(-6)) than noncarriers. The odds of CAD were 47% lower in carriers of a PTV in ANGPTL8 (OR = 0.53[0.37-0.76], P = 4.5 x 10(-4)) than noncarriers. Finally, the phenome-wide scan of the ANGPTL8 PTV showed that the ANGPTL8 PTV carriers were less likely to use statin therapy (68,782 cases, OR = 0.52[0.40-0.68], P = 1.7 x 10(-6)) compared to noncarriers. Our findings provide genetic evidence of potential long-term efficacy and safety of therapeutic targeting of dyslipidemias. Author summary Studying the health impacts of protein-truncating variants (PTVs) enables detecting the health impact of drugs that inhibit these same genes. Our study aimed to expand our knowledge of genes associated with cardiometabolic disease, along with the side effects of these genes. To detect PTVs associated with cardiometabolic disease, we first performed a genome-wide scan of PTVs associated with serum lipid levels in Finns. We found PTVs in two genes highly enriched in Finns, which were associated with both serum lipid levels and a lower risk of type 2 diabetes or coronary artery disease: ANGPTL4 and ANGPTL8. To evaluate the other health effects of these PTVs, we performed an association scan between the PTVs and 2,683 disease endpoints curated in the FinnGen Study (n = 218,792). We demonstrate that using human populations with PTV-enrichment, such as Finns, offers considerable boosts in statistical power to detect potential long-term efficacy and safety of pharmacologically targeting genes.Peer reviewe

High-resolution population-specific recombination rates and their effect on phasing and genotype imputation

Previous research has shown that using population-specific reference panels has a significant effect on downstream population genomic analyses like haplotype phasing, genotype imputation, and association, especially in the context of population isolates. Here, we developed a high-resolution recombination rate mapping at 10 and 50 kb scale using high-coverage (20-30x) whole-genome sequenced data of 55 family trios from Finland and compared it to recombination rates of non-Finnish Europeans (NFE). We tested the downstream effects of the population-specific recombination rates in statistical phasing and genotype imputation in Finns as compared to the same analyses performed by using the NFE-based recombination rates. We found that Finnish recombination rates have a moderately high correlation (Spearman's rho = 0.67-0.79) with NFE, although on average (across all autosomal chromosomes), Finnish rates (2.268 +/- 0.4209 cM/Mb) are 12-14% lower than NFE (2.641 +/- 0.5032 cM/Mb). Finnish recombination map was found to have no significant effect in haplotype phasing accuracy (switch error rates similar to 2%) and average imputation concordance rates (97-98% for common, 92-96% for low frequency and 78-90% for rare variants). Our results suggest that haplotype phasing and genotype imputation mostly depend on population-specific contexts like appropriate reference panels and their sample size, but not on population-specific recombination maps. Even though recombination rate estimates had some differences between the Finnish and NFE populations, haplotyping and imputation had not been noticeably affected by the recombination map used. Therefore, the currently available HapMap recombination maps seem robust for population-specific phasing and imputation pipelines, even in the context of relatively isolated populations like Finland.Peer reviewe

Fine-Scale Genetic Structure in Finland

Coupling dense genotype data with new computational methods offers unprecedented opportunities for individual-level ancestry estimation once geographically precisely defined reference data sets become available. We study such a reference data set for Finland containing 2376 such individuals from the FINRISK Study survey of 1997 both of whose parents were born close to each other. This sampling strategy focuses on the population structure present in Finland before the 1950s. By using the recent haplotype-based methods ChromoPainter (CP) and FineSTRUCTURE (FS) we reveal a highly geographically clustered genetic structure in Finland and report its connections to the settlement history as well as to the current dialectal regions of the Finnish language. The main genetic division within Finland shows striking concordance with the 1323 borderline of the treaty of Noteborg. In general, we detect genetic substructure throughout the country, which reflects stronger regional genetic differences in Finland compared to, for example, the UK, which in a similar analysis was dominated by a single unstructured population. We expect that similar population genetic reference data sets will become available for many more populations in the near future with important applications, for example, in forensic genetics and in genetic association studies. With this in mind, we report those extensions of the CP + FS approach that we found most useful in our analyses of the Finnish data.Peer reviewe

Mapping and characterization of structural variation in 17,795 human genomes

Structural variants in more than 17,000 human genomes are mapped and characterized using whole-genome sequencing, showing how this type of variation contributes to rare deleterious coding and noncoding alleles. A key goal of whole-genome sequencing for studies of human genetics is to interrogate all forms of variation, including single-nucleotide variants, small insertion or deletion (indel) variants and structural variants. However, tools and resources for the study of structural variants have lagged behind those for smaller variants. Here we used a scalable pipeline(1)to map and characterize structural variants in 17,795 deeply sequenced human genomes. We publicly release site-frequency data to create the largest, to our knowledge, whole-genome-sequencing-based structural variant resource so far. On average, individuals carry 2.9 rare structural variants that alter coding regions; these variants affect the dosage or structure of 4.2 genes and account for 4.0-11.2% of rare high-impact coding alleles. Using a computational model, we estimate that structural variants account for 17.2% of rare alleles genome-wide, with predicted deleterious effects that are equivalent to loss-of-function coding alleles; approximately 90% of such structural variants are noncoding deletions (mean 19.1 per genome). We report 158,991 ultra-rare structural variants and show that 2% of individuals carry ultra-rare megabase-scale structural variants, nearly half of which are balanced or complex rearrangements. Finally, we infer the dosage sensitivity of genes and noncoding elements, and reveal trends that relate to element class and conservation. This work will help to guide the analysis and interpretation of structural variants in the era of whole-genome sequencing.Peer reviewe

A data-driven medication score predicts 10-year mortality among aging adults

Health differences among the elderly and the role of medical treatments are topical issues in aging societies. We demonstrate the use of modern statistical learning methods to develop a data-driven health measure based on 21 years of pharmacy purchase and mortality data of 12,047 aging individuals. The resulting score was validated with 33,616 individuals from two fully independent datasets and it is strongly associated with all-cause mortality (HR 1.18 per point increase in score; 95% CI 1.14-1.22; p=2.25e-16). When combined with Charlson comorbidity index, individuals with elevated medication score and comorbidity index had over six times higher risk (HR 6.30; 95% CI 3.84-10.3; AUC=0.802) compared to individuals with a protective score profile. Alone, the medication score performs similarly to the Charlson comorbidity index and is associated with polygenic risk for coronary heart disease and type 2 diabetes.Peer reviewe

Geographic Variation and Bias in the Polygenic Scores of Complex Diseases and Traits in Finland

Polygenic scores (PSs) are becoming a useful tool to identify individuals with high genetic risk for complex diseases, and several projects are currently testing their utility for translational applications. It is also tempting to use PSs to assess whether genetic variation can explain a part of the geographic distribution of a phenotype. However, it is not well known how the population genetic properties of the training and target samples affect the geographic distribution of PSs. Here, we evaluate geographic differences, and related biases, of PSs in Finland in a geographically well-defined sample of 2,376 individuals from the National FINRISK study. First, we detect geographic differences in PSs for coronary artery disease (CAD), rheumatoid arthritis, schizophrenia, waist-hip ratio (WHR), body-mass index (BMI), and height, but not for Crohn disease or ulcerative colitis. Second, we use height as a model trait to thoroughly assess the possible population genetic biases in PSs and apply similar approaches to the other phenotypes. Most importantly, we detect suspiciously large accumulations of geographic differences for CAD, WHR, BMI, and height, suggesting bias arising from the population's genetic structure rather than from a direct genotype-phenotype association. This work demonstrates how sensitive the geographic patterns of current PSs are for small biases even within relatively homogeneous populations and provides simple tools to identify such biases. A thorough understanding of the effects of population genetic structure on PSs is essential for translational applications of PSs.Peer reviewe

Filaggriinin nollamutaatioiden hyödyllisyys atopian hoitovasteen ennusteelle: Havaintotutkimus suomalaisissa potilaissa

The contribution of filaggrin null mutations to predicting atopic dermatitis (AD) treatment response is not clear, nor have such mutations been studied in the Finnish population. This study tested the association of the 4 most prevalent European FLG null mutations, the 2 Finnish enriched FLG null mutations, the FLG 12-repeat allele, and 50 additional epidermal barrier gene variants, with risk of AD, disease severity, clinical features, risk of other atopic diseases, age of onset, and treatment response in 501 patients with AD and 1710 controls. AD, early-onset AD, palmar hyperlinearity, and asthma showed significant associations with the combined FLG null genotype. Disease severity and treatment response were independent of patient FLG status. Carrier frequencies of R501X, 2282del4, and S3247X were notably lower in Finns compared with reported frequencies in other populations. This data confirms FLG mutations as risk factors for AD in Finns, but also, questions their feasibility as biomarkers in predicting treatment response.The contribution of filaggrin null mutations to predicting atopic dermatitis (AD) treatment response is not clear, nor have such mutations been studied in the Finnish population. This study tested the association of the 4 most prevalent European FLG null mutations, the 2 Finnish enriched FLG null mutations, the FLG 12-repeat allele, and 50 additional epidermal barrier gene variants, with risk of AD, disease severity, clinical features, risk of other atopic diseases, age of onset, and treatment response in 501 patients with AD and 1,710 controls. AD, early-onset AD, palmar hyperlinearity, and asthma showed significant associations with the combined FLG null genotype. Disease severity and treatment response were independent of patient FLG status. Carrier frequencies of R501X, 2282del4, and S3247X were notably lower in Finns compared with reported frequencies in other populations. This data confirms FLG mutations as risk factors for AD in Finns, but also questions their feasibility as biomarkers in predicting treatment response.Peer reviewe

Genomic prediction of coronary heart disease

Aims Genetics plays an important role in coronary heart disease (CHD) but the clinical utility of genomic risk scores (GRSs) relative to clinical risk scores, such as the Framingham Risk Score (FRS), is unclear. Our aim was to construct and externally validate a CHD GRS, in terms of lifetime CHD risk and relative to traditional clinical risk scores. Methods and results We generated a GRS of 49 310 SNPs based on a CARDIoGRAMplusC4D Consortium meta-analysis of CHD, then independently tested it using five prospective population cohorts (three FINRISK cohorts, combined n = 12 676, 757 incident CHD events; two Framingham Heart Study cohorts (FHS), combined n = 3406, 587 incident CHD events). The GRS was associated with incident CHD (FINRISK HR = 1.74, 95% confidence interval (CI) 1.61-1.86 per S.D. of GRS; Framingham HR = 1.28, 95% CI 1.18-1.38), and was largely unchanged by adjustment for known risk factors, including family history. Integration of the GRS with the FRS or ACC/AHA13 scores improved the 10 years risk prediction (meta-analysis C-index: +1.5-1.6%, P = 60 years old (meta-analysis C-index: +4.6-5.1%, P <0.001). Importantly, the GRS captured substantially different trajectories of absolute risk, with men in the top 20% of attaining 10% cumulative CHD risk 12-18 y earlier than those in the bottom 20%. High genomic risk was partially compensated for by low systolic blood pressure, low cholesterol level, and non-smoking. Conclusions A GRS based on a large number of SNPs improves CHD risk prediction and encodes different trajectories of lifetime risk not captured by traditional clinical risk scores.Peer reviewe

Genomic prediction of alcohol-related morbidity and mortality

While polygenic risk scores (PRS) have been shown to predict many diseases and risk factors, the potential of genomic prediction in harm caused by alcohol use has not yet been extensively studied. Here, we built a novel polygenic risk score of 1.1 million variants for alcohol consumption and studied its predictive capacity in 96,499 participants from the FinnGen study and 39,695 participants from prospective cohorts with detailed baseline data and up to 25 years of follow-up time. A 1 SD increase in the PRS was associated with 11.2 g (=0.93 drinks) higher weekly alcohol consumption (CI = 9.85-12.58 g, p = 2.3 x 10(-58)). The PRS was associated with alcohol-related morbidity (4785 incident events) and the risk estimate between the highest and lowest quintiles of the PRS was 1.83 (95% CI = 1.66-2.01, p = 1.6 x 10(-36)). When adjusted for self-reported alcohol consumption, education, marital status, and gamma-glutamyl transferase blood levels in 28,639 participants with comprehensive baseline data from prospective cohorts, the risk estimate between the highest and lowest quintiles of the PRS was 1.58 (CI = 1.26-1.99, p = 8.2 x 10(-5)). The PRS was also associated with all-cause mortality with a risk estimate of 1.33 between the highest and lowest quintiles (CI = 1.20-1.47, p = 4.5 x 10(-8)) in the adjusted model. In conclusion, the PRS for alcohol consumption independently associates for both alcohol-related morbidity and all-cause mortality. Together, these findings underline the importance of heritable factors in alcohol-related health burden while highlighting how measured genetic risk for an important behavioral risk factor can be used to predict related health outcomes.Peer reviewe