Genetic Analysis of Obstructive Sleep Apnea and Its Relationship with Severe COVID-19.

RATIONALE: While patients with obstructive sleep apnea (OSA) have a higher risk for COVID-19 hospitalization, the causal relationship has remained unexplored. OBJECTIVES: To understand the causal relationship between OSA and COVID-19 leveraging data from vaccination and electronic health records, genetic risk factors from genome-wide association studies (GWAS) and Mendelian randomization. METHODS: We elucidated genetic risk factors for OSA using FinnGen (N total = 377,277 individuals) performing genome-wide association. We used the associated variants as instruments for univariate and multivariate Mendelian randomization (MR) analyses and computed absolute risk reduction (ARR) against COVID-19 hospitalization with or without vaccination. MEASUREMENTS AND MAIN RESULTS: We identified 9 novel loci for OSA and replicated our findings in the Million Veterans Program. Furthermore, MR analysis showed that OSA was a causal risk factor for severe COVID-19 (P=9.41x10-4). Probabilistic modelling showed that the strongest genetic risk factor for OSA at the FTO locus reflected a signal of higher BMI, whereas BMI independent association was seen with the earlier reported SLC9A4 locus and a MECOM locus which is a transcriptional regulator with 210-fold enrichment in the Finnish population. Similarly, Multivariate MR (MVMR) analysis showed that the causality for severe COVID-19 was driven by body mass index (BMI), (P MVMR = 5.97x10-6, beta=0.47). Finally, vaccination reduced the risk for COVID-19 hospitalization more in the OSA patients than in the non-OSA controls: ARR = 13.3% vs. ARR = 6.3% in the OSA vs. non-OSA population. CONCLUSIONS: Our analysis identified novel genetic risk factors for OSA and showed that OSA is a causal risk factor for severe COVID-19. The effect is predominantly explained by higher BMI and suggests BMI-dependent effects at the level of individual variants and at the level of comorbid causality.

Genetics of sleep medication purchases suggests causality from sleep problems to psychiatric traits.

STUDY OBJECTIVES: Over 10% of the population in Europe and in the United States use sleep medication to manage sleep problems. Our objective was to elucidate genetic risk factors and clinical correlates that contribute to sleep medication purchase and estimate the comorbid impact of sleep problems. METHODS: We performed epidemiological analysis for psychiatric diagnoses, and genetic association studies of sleep medication purchase in 797 714 individuals from FinnGen Release 7 (N = 311 892) and from the UK Biobank (N = 485 822). Post-association analyses included genetic correlation, co-localization, Mendelian randomization (MR), and polygenic risk estimation. RESULTS: In a GWAS we identified 27 genetic loci significantly associated with sleep medication, located in genes associated with sleep; AUTS2, CACNA1C, MEIS1, KIRREL3, PAX8, GABRA2, psychiatric traits; CACNA1C, HIST1H2BD, NUDT12. TOPAZ1 and TSNARE1. Co-localization and expression analysis emphasized effects on the KPNA2, GABRA2, and CACNA1C expression in the brain. Sleep medications use was epidemiologically related to psychiatric traits in FinnGen (OR [95% (CI)] = 3.86 [3.78 to 3.94], p < 2 × 10-16), and the association was accentuated by genetic correlation and MR; depression (rg = 0.55 (0.027), p = 2.86 × 10-89, p MR = 4.5 × 10-5), schizophrenia (rg = 0.25 (0.026), p = 2.52 × 10-21, p MR = 2 × 10-4), and anxiety (rg = 0.44 (0.047), p = 2.88 × 10-27, p MR = 8.6 × 10-12). CONCLUSIONS: These results demonstrate the genetics behind sleep problems and the association between sleep problems and psychiatric traits. Our results highlight the scientific basis for sleep management in treating the impact of psychiatric diseases.

Evidence from Finland and Sweden on the relationship between early-life diseases and lifetime childlessness in men and women.

The percentage of people without children over their lifetime is approximately 25% in men and 20% in women. Individual diseases have been linked to childlessness, mostly in women, yet we lack a comprehensive picture of the effect of early-life diseases on lifetime childlessness. We examined all individuals born in 1956-1968 (men) and 1956-1973 (women) in Finland (n = 1,035,928) and Sweden (n = 1,509,092) to the completion of their reproductive lifespan in 2018. Leveraging nationwide registers, we associated sociodemographic and reproductive information with 414 diseases across 16 categories, using a population and matched-pair case-control design of siblings discordant for childlessness (71,524 full sisters and 77,622 full brothers). The strongest associations were mental-behavioural disorders (particularly among men), congenital anomalies and endocrine-nutritional-metabolic disorders (strongest among women). We identified new associations for inflammatory and autoimmune diseases. Associations were dependent on age at onset and mediated by singlehood and education. This evidence can be used to understand how disease contributes to involuntary childlessness.

Use of electronic health record data mining for heart failure subtyping.

OBJECTIVE: To assess whether electronic health record (EHR) data text mining can be used to improve register-based heart failure (HF) subtyping. EHR data of 43,405 individuals from two Finnish hospital biobanks were mined for unstructured text mentions of ejection fraction (EF) and validated against clinical assessment in two sets of 100 randomly selected individuals. Structured laboratory data was then incorporated for a categorization by HF subtype (HF with mildly reduced EF, HFmrEF; HF with preserved EF, HFpEF; HF with reduced EF, HFrEF; and no HF). RESULTS: In 86% of the cases, the algorithm-identified EF belonged to the correct HF subtype range. Sensitivity, specificity, PPV and NPV of the algorithm were 94-100% for HFrEF, 85-100% for HFmrEF, and 96%, 67%, 53% and 98% for HFpEF. Survival analyses using the traditional diagnosis of HF were in concordance with the algorithm-based ones. Compared to healthy individuals, mortality increased from HFmrEF (hazard ratio [HR], 1.91; 95% confidence interval [CI], 1.24-2.95) to HFpEF (2.28; 1.80-2.88) to HFrEF group (2.63; 1.97-3.50) over a follow-up of 1.5 years. We conclude that quantitative EF data can be efficiently extracted from EHRs and used with laboratory data to subtype HF with reasonable accuracy, especially for HFrEF.

Overlap of Genetic Loci for Central Serous Chorioretinopathy With Age-Related Macular Degeneration.

Importance: Central serous chorioretinopathy (CSC) is a serous maculopathy of unknown etiology. Two of 3 previously reported CSC genetic risk loci are also associated with AMD. Improved understanding of CSC genetics may broaden our understanding of this genetic overlap and unveil mechanisms in both diseases. Objective: To identify novel genetic risk factors for CSC and compare genetic risk factors for CSC and AMD. Design, Setting, and Participants: Using International Classification of Diseases, Ninth (ICD-9) and Tenth (ICD-10) Revision code-based inclusion and exclusion criteria, patients with CSC and controls were identified in both the FinnGen study and the Estonian Biobank (EstBB). Also included in a meta-analysis were previously reported patients with chronic CSC and controls. Data were analyzed from March 1 to September 31, 2022. Main Outcomes and Measures: Genome-wide association studies (GWASs) were performed in the biobank-based cohorts followed by a meta-analysis of all cohorts. The expression of genes prioritized by the polygenic priority score and nearest-gene methods were assessed in cultured choroidal endothelial cells and public ocular single-cell RNA sequencing data sets. The predictive utility of polygenic scores (PGSs) for CSC and AMD were evaluated in the FinnGen study. Results: A total of 1176 patients with CSC and 526 787 controls (312 162 female [59.3%]) were included in this analysis: 552 patients with CSC and 343 461 controls were identified in the FinnGen study, 103 patients with CSC and 178 573 controls were identified in the EstBB, and 521 patients with chronic CSC and 3577 controls were included in a meta-analysis. Two previously reported CSC risk loci were replicated (near CFH and GATA5) and 3 novel loci were identified (near CD34/46, NOTCH4, and PREX1). The CFH and NOTCH4 loci were associated with AMD but in the opposite direction. Prioritized genes showed increased expression in cultured choroidal endothelial cells compared with other genes in the loci (median [IQR] of log 2 [counts per million], 7.3 [0.6] vs 4.7 [3.7]; P = .004) and were differentially expressed in choroidal vascular endothelial cells in single-cell RNA sequencing data (mean [SD] fold change, 2.05 [0.38] compared with other cell types; P < 7.1 × 10-20). A PGS for AMD was predictive of reduced CSC risk (odds ratio, 0.76; 95% CI, 0.70-0.83 per +1 SD in AMD-PGS; P = 7.4 × 10-10). This association may have been mediated by loci containing complement genes. Conclusions and Relevance: In this 3-cohort genetic association study, 5 genetic risk loci for CSC were identified, highlighting a likely role for genes involved in choroidal vascular function and complement regulation. Results suggest that polygenic AMD risk was associated with reduced risk of CSC and that this genetic overlap was largely due to loci containing complement genes.

FinnGen provides genetic insights from a well-phenotyped isolated population.

Population isolates such as those in Finland benefit genetic research because deleterious alleles are often concentrated on a small number of low-frequency variants (0.1% ≤ minor allele frequency < 5%). These variants survived the founding bottleneck rather than being distributed over a large number of ultrarare variants. Although this effect is well established in Mendelian genetics, its value in common disease genetics is less explored1,2. FinnGen aims to study the genome and national health register data of 500,000 Finnish individuals. Given the relatively high median age of participants (63 years) and the substantial fraction of hospital-based recruitment, FinnGen is enriched for disease end points. Here we analyse data from 224,737 participants from FinnGen and study 15 diseases that have previously been investigated in large genome-wide association studies (GWASs). We also include meta-analyses of biobank data from Estonia and the United Kingdom. We identified 30 new associations, primarily low-frequency variants, enriched in the Finnish population. A GWAS of 1,932 diseases also identified 2,733 genome-wide significant associations (893 phenome-wide significant (PWS), P < 2.6 × 10-11) at 2,496 (771 PWS) independent loci with 807 (247 PWS) end points. Among these, fine-mapping implicated 148 (73 PWS) coding variants associated with 83 (42 PWS) end points. Moreover, 91 (47 PWS) had an allele frequency of <5% in non-Finnish European individuals, of which 62 (32 PWS) were enriched by more than twofold in Finland. These findings demonstrate the power of bottlenecked populations to find entry points into the biology of common diseases through low-frequency, high impact variants.

Genome-wide screen of otosclerosis in population biobanks: 27 loci and shared associations with skeletal structure.

Otosclerosis is one of the most common causes of conductive hearing loss, affecting 0.3% of the population. It typically presents in adulthood and half of the patients have a positive family history. The pathophysiology of otosclerosis is poorly understood. A previous genome-wide association study (GWAS) identified a single association locus in an intronic region of RELN. Here, we report a meta-analysis of GWAS studies of otosclerosis in three population-based biobanks comprising 3504 cases and 861,198 controls. We identify 23 novel risk loci (p < 5 × 10-8) and report an association in RELN and three previously reported candidate gene or linkage regions (TGFB1, MEPE, and OTSC7). We demonstrate developmental stage-dependent immunostaining patterns of MEPE and RUNX2 in mouse otic capsules. In most association loci, the nearest protein-coding genes are implicated in bone remodelling, mineralization or severe skeletal disorders. We highlight multiple genes involved in transforming growth factor beta signalling for follow-up studies.

Inflammatory and infectious upper respiratory diseases associate with 41 genomic loci and type 2 inflammation.

Inflammatory and infectious upper respiratory diseases (ICD-10: J30-J39), such as diseases of the sinonasal tract, pharynx and larynx, are growing health problems yet their genomic similarity is not known. We analyze genome-wide association to eight upper respiratory diseases (61,195 cases) among 260,405 FinnGen participants, meta-analyzing diseases in four groups based on an underlying genetic correlation structure. Aiming to understand which genetic loci contribute to susceptibility to upper respiratory diseases in general and its subtypes, we detect 41 independent genome-wide significant loci, distinguishing impact on sinonasal or pharyngeal diseases, or both. Fine-mapping implicated non-synonymous variants in nine genes, including three linked to immune-related diseases. Phenome-wide analysis implicated asthma and atopic dermatitis at sinonasal disease loci, and inflammatory bowel diseases and other immune-mediated disorders at pharyngeal disease loci. Upper respiratory diseases also genetically correlated with autoimmune diseases such as rheumatoid arthritis, autoimmune hypothyroidism, and psoriasis. Finally, we associated separate gene pathways in sinonasal and pharyngeal diseases that both contribute to type 2 immunological reaction. We show shared heritability among upper respiratory diseases that extends to several immune-mediated diseases with diverse mechanisms, such as type 2 high inflammation.

Genetic predictors of lifelong medication-use patterns in cardiometabolic diseases.

Little is known about the genetic determinants of medication use in preventing cardiometabolic diseases. Using the Finnish nationwide drug purchase registry with follow-up since 1995, we performed genome-wide association analyses of longitudinal patterns of medication use in hyperlipidemia, hypertension and type 2 diabetes in up to 193,933 individuals (55% women) in the FinnGen study. In meta-analyses of up to 567,671 individuals combining FinnGen with the Estonian Biobank and the UK Biobank, we discovered 333 independent loci (P < 5 × 10-9) associated with medication use. Fine-mapping revealed 494 95% credible sets associated with the total number of medication purchases, changes in medication combinations or treatment discontinuation, including 46 credible sets in 40 loci not associated with the underlying treatment targets. The polygenic risk scores (PRS) for cardiometabolic risk factors were strongly associated with the medication-use behavior. A medication-use enhanced multitrait PRS for coronary artery disease matched the performance of a risk factor-based multitrait coronary artery disease PRS in an independent sample (UK Biobank, n = 343,676). In summary, we demonstrate medication-based strategies for identifying cardiometabolic risk loci and provide genome-wide tools for preventing cardiovascular diseases.

Integration of Biomarker Polygenic Risk Score Improves Prediction of Coronary Heart Disease.

There are several established biomarkers for coronary heart disease (CHD), including blood pressure, cholesterol, and lipoproteins. It is of high interest to determine how a combined polygenic risk score (PRS) of CHD-associated biomarkers (BioPRS) can further improve genetic prediction of CHD. We developed CHDBioPRS, combining BioPRS with PRS of CHD in the UK Biobank and tested it on FinnGen. We found that BioPRS was clearly predictive of CHD and that CHDBioPRS improved the standard CHD PRS. The largest effect was observed with early onset cases in FinnGen, with HRs above 2 per standard deviation of CHDBioPRS.

Efficient and accurate frailty model approach for genome-wide survival association analysis in large-scale biobanks.

With decades of electronic health records linked to genetic data, large biobanks provide unprecedented opportunities for systematically understanding the genetics of the natural history of complex diseases. Genome-wide survival association analysis can identify genetic variants associated with ages of onset, disease progression and lifespan. We propose an efficient and accurate frailty model approach for genome-wide survival association analysis of censored time-to-event (TTE) phenotypes by accounting for both population structure and relatedness. Our method utilizes state-of-the-art optimization strategies to reduce the computational cost. The saddlepoint approximation is used to allow for analysis of heavily censored phenotypes (>90%) and low frequency variants (down to minor allele count 20). We demonstrate the performance of our method through extensive simulation studies and analysis of five TTE phenotypes, including lifespan, with heavy censoring rates (90.9% to 99.8%) on ~400,000 UK Biobank participants with white British ancestry and ~180,000 individuals in FinnGen. We further analyzed 871 TTE phenotypes in the UK Biobank and presented the genome-wide scale phenome-wide association results with the PheWeb browser.

Genetic risk factors have a substantial impact on healthy life years.

The impact of genetic variation on overall disease burden has not been comprehensively evaluated. We introduce an approach to estimate the effect of genetic risk factors on disability-adjusted life years (DALYs; 'lost healthy life years'). We use genetic information from 735,748 individuals and consider 80 diseases. Rare variants had the highest effect on DALYs at the individual level. Among common variants, rs3798220 (LPA) had the strongest individual-level effect, with 1.18 DALYs from carrying 1 versus 0 copies. Being in the top 10% versus the bottom 90% of a polygenic score for multisite chronic pain had an effect of 3.63 DALYs. Some common variants had a population-level effect comparable to modifiable risk factors such as high sodium intake and low physical activity. Attributable DALYs vary between males and females for some genetic exposures. Genetic risk factors can explain a sizable number of healthy life years lost both at the individual and population level.

Mendelian randomization of genetically independent aging phenotypes identifies LPA and VCAM1 as biological targets for human aging.

Length and quality of life are important to us all, yet identification of promising drug targets for human aging using genetics has had limited success. In the present study, we combine six European-ancestry genome-wide association studies of human aging traits-healthspan, father and mother lifespan, exceptional longevity, frailty index and self-rated health-in a principal component framework that maximizes their shared genetic architecture. The first principal component (aging-GIP1) captures both length of life and indices of mental and physical wellbeing. We identify 27 genomic regions associated with aging-GIP1, and provide additional, independent evidence for an effect on human aging for loci near HTT and MAML3 using a study of Finnish and Japanese survival. Using proteome-wide, two-sample, Mendelian randomization and colocalization, we provide robust evidence for a detrimental effect of blood levels of apolipoprotein(a) and vascular cell adhesion molecule 1 on aging-GIP1. Together, our results demonstrate that combining multiple aging traits using genetic principal components enhances the power to detect biological targets for human aging.

Clinical Conditions and Their Impact on Utility of Genetic Scores for Prediction of Acute Coronary Syndrome.

BACKGROUND: Acute coronary syndrome (ACS) is a clinically significant presentation of coronary heart disease. Genetic information has been proposed to improve prediction beyond well-established clinical risk factors. While polygenic scores (PS) can capture an individual's genetic risk for ACS, its prediction performance may vary in the context of diverse correlated clinical conditions. Here, we aimed to test whether clinical conditions impact the association between PS and ACS. METHODS: We explored the association between 405 clinical conditions diagnosed before baseline and 9080 incident cases of ACS in 387 832 individuals from the UK Biobank. Results were replicated in 6430 incident cases of ACS in 177 876 individuals from FinnGen. RESULTS: We identified 80 conventional (eg, stable angina pectoris and type 2 diabetes) and unconventional (eg, diaphragmatic hernia and inguinal hernia) associations with ACS. The association between PS and ACS was consistent in individuals with and without most clinical conditions. However, a diagnosis of stable angina pectoris yielded a differential association between PS and ACS. PS was associated with a significantly reduced (interaction P=2.87×10-8) risk for ACS in individuals with stable angina pectoris (hazard ratio, 1.163 [95% CI, 1.082-1.251]) compared with individuals without stable angina pectoris (hazard ratio, 1.531 [95% CI, 1.497-1.565]). These findings were replicated in FinnGen (interaction P=1.38×10-6). CONCLUSIONS: In summary, while most clinical conditions did not impact utility of PS for prediction of ACS, we found that PS was substantially less predictive of ACS in individuals with prevalent stable coronary heart disease. PS may be more appropriate for prediction of ACS in asymptomatic individuals than symptomatic individuals with clinical suspicion for coronary heart disease.

Association of the MYOC p.(Gln368Ter) Variant With Glaucoma in a Finnish Population.

IMPORTANCE: The c.1102C>T, p.(Gln368Ter) variant in the myocilin (MYOC) gene is a known risk allele for glaucoma. It is the most common MYOC risk variant for glaucoma among individuals of European ancestry, and its prevalence is highest in Finland. Furthermore, exfoliation syndrome has high prevalence in Scandinavia, making the Finnish population ideal to study the association of the variant with different types of glaucoma. OBJECTIVES: To examine the association and penetrance of MYOC p.(Gln368Ter) (rs74315329) variant with different types of glaucoma in a Finnish population. DESIGN, SETTING, AND PARTICIPANTS: This genetic association study included individuals of Finnish ancestry in the FinnGen project. The participants were collected from Finnish biobanks, and the disease end points were defined using nationwide registries. The MYOC c.1102C>T variant was either directly genotyped or imputed with microarrays. Recruitment of samples to FinnGen was initiated in 2017, and data analysis was performed between December 2019 and May 2020. MAIN OUTCOMES AND MEASURES: The main outcomes were odds ratios (ORs) and penetrance with different types of glaucoma and in different age groups. RESULTS: A total of 218 792 individuals were included in this study (mean [SD] age 52.4 [17.5] years; 123 579 women [56.5%]), including 8591 (3.9%) with glaucoma, 3412 (1.6%) with primary open-angle glaucoma, 1515 (0.7%) with exfoliation glaucoma, 892 (0.4%) with normal-tension glaucoma, and 4766 (2.2%) with suspected glaucoma. The minor allele frequency of MYOC p.(Gln368Ter) was 0.28%. Individuals with the heterozygous variant had higher odds of primary open-angle glaucoma (OR, 3.36; 95% CI, 2.55-4.37), overall glaucoma (OR, 2.58; 95% CI, 2.12-3.13), suspected glaucoma (OR, 2.53; 95% CI, 1.93-3.26), exfoliation glaucoma (OR, 2.61; 95% CI, 1.60-4.02), and undergoing glaucoma-related operations (OR, 5.45; 95% CI, 2.95-9.28). The penetrance of heterozygous MYOC p.(Gln368Ter) was 5.2% in individuals with primary open-angle glaucoma, 9.6% in individuals with glaucoma, 5.4% in individuals with suspected glaucoma, and 1.9% in individuals with exfoliation glaucoma. There was no significant association with normal-tension glaucoma (OR, 1.69; 95% CI, 0.72-3.35). CONCLUSIONS AND RELEVANCE: This genetic association study found that the MYOC p.(Gln368Ter) variant was associated with exfoliation glaucoma. The association with normal-tension glaucoma could not be replicated. These findings suggest that MYOC p.(Gln368Ter) was associated with open-angle glaucoma and exfoliation glaucoma in a Finnish population.

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 × 10-9) and ANGPTL4 (-14.4[-18.6 to -9.8] mg/dL per rs746226153-G allele, P = 4.3 × 10-9). The risk of T2D was lower in carriers of the ANGPTL4 PTV (OR = 0.70[0.60-0.81], P = 2.2 × 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 × 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 × 10-6) compared to noncarriers. Our findings provide genetic evidence of potential long-term efficacy and safety of therapeutic targeting of dyslipidemias.

Correction: A missense variant in Mitochondrial Amidoxime Reducing Component 1 gene and protection against liver disease.

[This corrects the article DOI: 10.1371/journal.pgen.1008629.].