Complex effects of sequence variants on lipid levels and coronary artery disease.

Many sequence variants have additive effects on blood lipid levels and, through that, on the risk of coronary artery disease (CAD). We show that variants also have non-additive effects and interact to affect lipid levels as well as affecting variance and correlations. Variance and correlation effects are often signatures of epistasis or gene-environmental interactions. These complex effects can translate into CAD risk. For example, Trp154Ter in FUT2 protects against CAD among subjects with the A1 blood group, whereas it associates with greater risk of CAD in others. His48Arg in ADH1B interacts with alcohol consumption to affect lipid levels and CAD. The effect of variants in TM6SF2 on blood lipids is greatest among those who never eat oily fish but absent from those who often do. This work demonstrates that variants that affect variance of quantitative traits can allow for the discovery of epistasis and interactions of variants with the environment.

Deep integrative models for large-scale human genomics.

Polygenic risk scores (PRSs) are expected to play a critical role in precision medicine. Currently, PRS predictors are generally based on linear models using summary statistics, and more recently individual-level data. However, these predictors mainly capture additive relationships and are limited in data modalities they can use. We developed a deep learning framework (EIR) for PRS prediction which includes a model, genome-local-net (GLN), specifically designed for large-scale genomics data. The framework supports multi-task learning, automatic integration of other clinical and biochemical data, and model explainability. When applied to individual-level data from the UK Biobank, the GLN model demonstrated a competitive performance compared to established neural network architectures, particularly for certain traits, showcasing its potential in modeling complex genetic relationships. Furthermore, the GLN model outperformed linear PRS methods for Type 1 Diabetes, likely due to modeling non-additive genetic effects and epistasis. This was supported by our identification of widespread non-additive genetic effects and epistasis in the context of T1D. Finally, we constructed PRS models that integrated genotype, blood, urine, and anthropometric data and found that this improved performance for 93% of the 290 diseases and disorders considered. EIR is available at https://github.com/arnor-sigurdsson/EIR.

Determinants of plasma levels of proglucagon and the metabolic impact of glucagon receptor signalling: a UK Biobank study.

AIMS/HYPOTHESES: Glucagon and glucagon-like peptide-1 (GLP-1) are derived from the same precursor; proglucagon, and dual agonists of their receptors are currently being explored for the treatment of obesity and metabolic dysfunction-associated steatotic liver disease (MASLD). Elevated levels of endogenous glucagon (hyperglucagonaemia) have been linked with hyperglycaemia in individuals with type 2 diabetes but are also observed in individuals with obesity and MASLD. GLP-1 levels have been reported to be largely unaffected or even reduced in similar conditions. We investigated potential determinants of plasma proglucagon and associations of glucagon receptor signalling with metabolic diseases based on data from the UK Biobank. METHODS: We used exome sequencing data from the UK Biobank for ~410,000 white participants to identify glucagon receptor variants and grouped them based on their known or predicted signalling. Data on plasma levels of proglucagon estimated using Olink technology were available for a subset of the cohort (~40,000). We determined associations of glucagon receptor variants and proglucagon with BMI, type 2 diabetes and liver fat (quantified by liver MRI) and performed survival analyses to investigate if elevated proglucagon predicts type 2 diabetes development. RESULTS: Obesity, MASLD and type 2 diabetes were associated with elevated plasma levels of proglucagon independently of each other. Baseline proglucagon levels were associated with the risk of type 2 diabetes development over a 14 year follow-up period (HR 1.13; 95% CI 1.09, 1.17; n=1562; p=1.3×10-12). This association was of the same magnitude across strata of BMI. Carriers of glucagon receptor variants with reduced cAMP signalling had elevated levels of proglucagon (ß 0.847; 95% CI 0.04, 1.66; n=17; p=0.04), and carriers of variants with a predicted frameshift mutation had higher levels of liver fat compared with the wild-type reference group (ß 0.504; 95% CI 0.03, 0.98; n=11; p=0.04). CONCLUSIONS/INTERPRETATION: Our findings support the suggestion that glucagon receptor signalling is involved in MASLD, that plasma levels of proglucagon are linked to the risk of type 2 diabetes development, and that proglucagon levels are influenced by genetic variation in the glucagon receptor, obesity, type 2 diabetes and MASLD. Determining the molecular signalling pathways downstream of glucagon receptor activation may guide the development of biased GLP-1/glucagon co-agonist with improved metabolic benefits. DATA AVAILABILITY: All coding is available through https://github.com/nicwin98/UK-Biobank-GCG.

Longitudinal metabolite and protein trajectories prior to diabetes mellitus diagnosis in Danish blood donors: a nested case-control study.

AIMS/HYPOTHESIS: Metabolic risk factors and plasma biomarkers for diabetes have previously been shown to change prior to a clinical diabetes diagnosis. However, these markers only cover a small subset of molecular biomarkers linked to the disease. In this study, we aimed to profile a more comprehensive set of molecular biomarkers and explore their temporal association with incident diabetes. METHODS: We performed a targeted analysis of 54 proteins and 171 metabolites and lipoprotein particles measured in three sequential samples spanning up to 11 years of follow-up in 324 individuals with incident diabetes and 359 individuals without diabetes in the Danish Blood Donor Study (DBDS) matched for sex and birth year distribution. We used linear mixed-effects models to identify temporal changes before a diabetes diagnosis, either for any incident diabetes diagnosis or for type 1 and type 2 diabetes mellitus diagnoses specifically. We further performed linear and non-linear feature selection, adding 28 polygenic risk scores to the biomarker pool. We tested the time-to-event prediction gain of the biomarkers with the highest variable importance, compared with selected clinical covariates and plasma glucose. RESULTS: We identified two proteins and 16 metabolites and lipoprotein particles whose levels changed temporally before diabetes diagnosis and for which the estimated marginal means were significant after FDR adjustment. Sixteen of these have not previously been described. Additionally, 75 biomarkers were consistently higher or lower in the years before a diabetes diagnosis. We identified a single temporal biomarker for type 1 diabetes, IL-17A/F, a cytokine that is associated with multiple other autoimmune diseases. Inclusion of 12 biomarkers improved the 10-year prediction of a diabetes diagnosis (i.e. the area under the receiver operating curve increased from 0.79 to 0.84), compared with clinical information and plasma glucose alone. CONCLUSIONS/INTERPRETATION: Systemic molecular changes manifest in plasma several years before a diabetes diagnosis. A particular subset of biomarkers shows distinct, time-dependent patterns, offering potential as predictive markers for diabetes onset. Notably, these biomarkers show shared and distinct patterns between type 1 diabetes and type 2 diabetes. After independent replication, our findings may be used to develop new clinical prediction models.

Intervening on the storage time of RBC units and its effects on adverse recipient outcomes using real-world data.

Randomized controlled trials (RCTs) have found no evidence that the storage time of transfused red blood cell (RBC) units affects recipient survival. However, inherent difficulties in conducting RBC transfusion RCTs have prompted critique of their design, analyses, and interpretation. Here, we address these issues by emulating hypothetical randomized trials using large real-world data to further clarify the adverse effects of storage time. We estimated the comparative effect of transfusing exclusively older vs fresher RBC units on the primary outcome of death, and the secondary composite end point of thromboembolic events, or death, using inverse probability weighting. Thresholds were defined as 1, 2, 3, and 4 weeks of storage. A large Danish blood transfusion database from the period 2008 to 2018 comprising >900 000 transfusion events defined the observational data. A total of 89 799 patients receiving >340 000 RBC transfusions during 28 days of follow-up met the eligibility criteria. Treatment with RBC units exclusively fresher than 1, 2, 3, and 4 weeks of storage was found to decrease the 28-day recipient mortality with 2.44 percentage points (pp) (0.86 pp, 4.02 pp), 1.93 pp (0.85 pp, 3.02 pp), 1.06 pp (-0.20 pp, 2.33 pp), and -0.26 pp (-1.78 pp, 1.25 pp) compared with transfusing exclusively older RBC units, respectively. The 28-day risk differences for the composite end point were similar. This study suggests that transfusing exclusively older RBC units stored for >1 or 2 weeks increases the 28-day recipient mortality and risk of thromboembolism or death compared with transfusing fresher RBC units.

Multi-omics analysis reveals drivers of loss of ß-cell function after newly diagnosed autoimmune type 1 diabetes: An INNODIA multicenter study.

AIMS: Heterogeneity in the rate of ß-cell loss in newly diagnosed type 1 diabetes patients is poorly understood and creates a barrier to designing and interpreting disease-modifying clinical trials. Integrative analyses of baseline multi-omics data obtained after the diagnosis of type 1 diabetes may provide mechanistic insight into the diverse rates of disease progression after type 1 diabetes diagnosis. METHODS: We collected samples in a pan-European consortium that enabled the concerted analysis of five different omics modalities in data from 97 newly diagnosed patients. In this study, we used Multi-Omics Factor Analysis to identify molecular signatures correlating with post-diagnosis decline in ß-cell mass measured as fasting C-peptide. RESULTS: Two molecular signatures were significantly correlated with fasting C-peptide levels. One signature showed a correlation to neutrophil degranulation, cytokine signalling, lymphoid and non-lymphoid cell interactions and G-protein coupled receptor signalling events that were inversely associated with a rapid decline in ß-cell function. The second signature was related to translation and viral infection was inversely associated with change in ß-cell function. In addition, the immunomics data revealed a Natural Killer cell signature associated with rapid ß-cell decline. CONCLUSIONS: Features that differ between individuals with slow and rapid decline in ß-cell mass could be valuable in staging and prediction of the rate of disease progression and thus enable smarter (shorter and smaller) trial designs for disease modifying therapies as well as offering biomarkers of therapeutic effect.

BALDR: A Web-based platform for informed comparison and prioritization of biomarker candidates for type 2 diabetes mellitus.

Novel biomarkers are key to addressing the ongoing pandemic of type 2 diabetes mellitus. While new technologies have improved the potential of identifying such biomarkers, at the same time there is an increasing need for informed prioritization to ensure efficient downstream verification. We have built BALDR, an automated pipeline for biomarker comparison and prioritization in the context of diabetes. BALDR includes protein, gene, and disease data from major public repositories, text-mining data, and human and mouse experimental data from the IMI2 RHAPSODY consortium. These data are provided as easy-to-read figures and tables enabling direct comparison of up to 20 biomarker candidates for diabetes through the public website https://baldr.cpr.ku.dk.

No association between migraine and HLA alleles in a cohort of 13,210 individuals with migraine from the Danish Blood Donor Study.

OBJECTIVE: To determine the association between human leukocyte antigen (HLA) alleles and migraine, migraine subtypes, and sex-specific factors. BACKGROUND: It has long been hypothesized that inflammation contributes to migraine pathophysiology. This study examined the association between migraine and alleles in the HLA system, a key player in immune response and genetic diversity. METHODS: We performed a case-control study and included 13,210 individuals with migraine and 86,738 controls. All participants were part of the Danish Blood Donor Study Genomic Cohort. Participants were genotyped and 111 HLA alleles on 15 HLA genes were imputed. We examined the association between HLA alleles and migraine subtypes, considering sex-specific differences. RESULTS: We found no association between HLA alleles and migraine, neither overall, nor in the sex-specific analysis. In the migraine subtype analysis, three HLA alleles were associated with migraine without aura; however, these associations could not be replicated in an independent Icelandic cohort (2191 individuals with migraine without aura and 278,858 controls). Furthermore, we found no association between HLA alleles and migraine with aura or chronic migraine. CONCLUSION: We found no evidence of an association between the HLA system and migraine, suggesting that genetic factors related to the HLA system do not play a significant role in migraine susceptibility.

Genetic variants associated with syncope implicate neural and autonomic processes.

AIMS: Syncope is a common and clinically challenging condition. In this study, the genetics of syncope were investigated to seek knowledge about its pathophysiology and prognostic implications. METHODS AND RESULTS: This genome-wide association meta-analysis included 56 071 syncope cases and 890 790 controls from deCODE genetics (Iceland), UK Biobank (United Kingdom), and Copenhagen Hospital Biobank Cardiovascular Study/Danish Blood Donor Study (Denmark), with a follow-up assessment of variants in 22 412 cases and 286 003 controls from Intermountain (Utah, USA) and FinnGen (Finland). The study yielded 18 independent syncope variants, 17 of which were novel. One of the variants, p.Ser140Thr in PTPRN2, affected syncope only when maternally inherited. Another variant associated with a vasovagal reaction during blood donation and five others with heart rate and/or blood pressure regulation, with variable directions of effects. None of the 18 associations could be attributed to cardiovascular or other disorders. Annotation with regard to regulatory elements indicated that the syncope variants were preferentially located in neural-specific regulatory regions. Mendelian randomization analysis supported a causal effect of coronary artery disease on syncope. A polygenic score (PGS) for syncope captured genetic correlation with cardiovascular disorders, diabetes, depression, and shortened lifespan. However, a score based solely on the 18 syncope variants performed similarly to the PGS in detecting syncope risk but did not associate with other disorders. CONCLUSION: The results demonstrate that syncope has a distinct genetic architecture that implicates neural regulatory processes and a complex relationship with heart rate and blood pressure regulation. A shared genetic background with poor cardiovascular health was observed, supporting the importance of a thorough assessment of individuals presenting with syncope.

Genome-wide association meta-analysis of knee and hip osteoarthritis uncovers genetic differences between patients treated with joint replacement and patients without joint replacement.

OBJECTIVES: Osteoarthritis is a common and severe, multifactorial disease with a well-established genetic component. However, little is known about how genetics affect disease progression, and thereby the need for joint placement. Therefore, we aimed to investigate whether the genetic associations of knee and hip osteoarthritis differ between patients treated with joint replacement and patients without joint replacement. METHODS: We included knee and hip osteoarthritis cases along with healthy controls, altogether counting >700 000 individuals. The cases were divided into two groups based on joint replacement status (surgical vs non-surgical) and included in four genome-wide association meta-analyses: surgical knee osteoarthritis (N = 22 525), non-surgical knee osteoarthritis (N = 38 626), surgical hip osteoarthritis (N = 20 221) and non-surgical hip osteoarthritis (N = 17 847). In addition, we tested for genetic correlation between the osteoarthritis groups and the pain phenotypes intervertebral disc disorder, dorsalgia, fibromyalgia, migraine and joint pain. RESULTS: We identified 52 sequence variants associated with knee osteoarthritis (surgical: 17, non-surgical: 3) or hip osteoarthritis (surgical: 34, non-surgical: 1). For the surgical phenotypes, we identified 10 novel variants, including genes involved in autophagy (rs2447606 in ATG7) and mechanotransduction (rs202127176 in PIEZO1). One variant, rs13107325 in SLC39A8, associated more strongly with non-surgical knee osteoarthritis than surgical knee osteoarthritis. For all other variants, significance and effect sizes were higher for the surgical phenotypes. In contrast, genetic correlations with pain phenotypes tended to be stronger in the non-surgical groups. CONCLUSIONS: Our results indicate differences in genetic associations between knee and hip osteoarthritis depending on joint replacement status.

A large cohort study of the effects of Lewis, ABO, 13 other blood groups, and secretor status on COVID-19 susceptibility, severity, and long COVID-19.

BACKGROUND: Previous studies have reported Blood type O to confer a lower risk of SARS-CoV-2 infection, while secretor status and other blood groups have been suspected to have a similar effect as well. STUDY DESIGN AND METHODS: To determine whether any other blood groups influence testing positive for SARS-CoV-2, COVID-19 severity, or prolonged COVID-19, we used a large cohort of 650,156 Danish blood donors with varying available data for secretor status and blood groups ABO, Rh, Colton, Duffy, Diego, Dombrock, Kell, Kidd, Knops, Lewis, Lutheran, MNS, P1PK, Vel, and Yt. Of these, 36,068 tested positive for SARS-CoV-2 whereas 614,088 tested negative between 2020-02-17 and 2021-08-04. Associations between infection and blood groups were assessed using logistic regression models with sex and age as covariates. RESULTS: The Lewis blood group antigen Lea displayed strongly reduced SARS-CoV-2 susceptibility OR 0.85 CI[0.79-0.93] p < .001. Compared to blood type O, the blood types B, A, and AB were found more susceptible toward infection with ORs 1.1 CI[1.06-1.14] p < .001, 1.17 CI[1.14-1.2] p < .001, and 1.2 CI[1.14-1.26] p < .001, respectively. No susceptibility associations were found for the other 13 blood groups investigated. There was no association between any blood groups and COVID-19 hospitalization or long COVID-19. No secretor status associations were found. DISCUSSION: This study uncovers a new association to reduced SARS-CoV-2 susceptibility for Lewis type Lea and confirms the previous link to blood group O. The new association to Lea could be explained by a link between mucosal microbiome and SARS-CoV-2.

Genetic prediction of 33 blood group phenotypes using an existing genotype dataset.

BACKGROUND: Accurate blood type data are essential for blood bank management, but due to costs, few of 43 blood group systems are routinely determined in Danish blood banks. However, a more comprehensive dataset of blood types is useful in scenarios such as rare blood type allocation. We aimed to investigate the viability and accuracy of predicting blood types by leveraging an existing dataset of imputed genotypes for two cohorts of approximately 90,000 each (Danish Blood Donor Study and Copenhagen Biobank) and present a more comprehensive overview of blood types for our Danish donor cohort. STUDY DESIGN AND METHODS: Blood types were predicted from genome array data using known variant determinants. Prediction accuracy was confirmed by comparing with preexisting serological blood types. The Vel blood group was used to test the viability of using genetic prediction to narrow down the list of candidate donors with rare blood types. RESULTS: Predicted phenotypes showed a high balanced accuracy >99.5% in most cases: A, B, C/c, Coa /Cob , Doa /Dob , E/e, Jka /Jkb , Kna /Knb , Kpa /Kpb , M/N, S/s, Sda , Se, and Yta /Ytb , while some performed slightly worse: Fya /Fyb , K/k, Lua /Lub , and Vel ~99%-98% and CW and P1 ~96%. Genetic prediction identified 70 potential Vel negatives in our cohort, 64 of whom were confirmed correct using polymerase chain reaction (negative predictive value: 91.5%). DISCUSSION: High genetic prediction accuracy in most blood groups demonstrated the viability of generating blood types using preexisting genotype data at no cost and successfully narrowed the pool of potential individuals with the rare Vel-negative phenotype from 180,000 to 70.

Sex differences in clinical characteristics of migraine and its burden: a population-based study.

BACKGROUND AND PURPOSE: Understanding migraine in a sex-specific manner is crucial for improving clinical care, diagnosis and therapy for both females and males. Here, data on sex differences are provided in the presentation of migraine in a large European-based population cohort, which is representative of the general population. METHODS: A population-based study of 62,672 Danish blood donors (both present and previous donors), of whom 12,658 had migraine, was performed. All participants completed a 105-item diagnostic migraine questionnaire sent via an electronic mailing system (e-Boks) between May 2020 and August 2020. The questionnaire allowed for correct diagnosis of migraine according to the International Classification of Headache Disorders, third edition. RESULTS: The migraine questionnaire was in-cohort validated and had a positive predictive value of 97% for any migraine, a specificity of 93% and a sensitivity of 93%. There were 9184 females (mean age 45.1 years) and 3434 males (mean age 48.0 years). The 3-month prevalence of migraine without aura was 11% in females and 3.59% in males. The 3-month prevalence of migraine with aura was 1.72% in females and 1.58% in males. In females, the age-related 3-month prevalence of migraine without aura increased markedly during childbearing age. In males, migraine both with and without aura showed less age variation. Females had a higher frequency of migraine attacks (odds ratio [OR] 1.22) but a lower frequency of non-migraine headaches (OR = 0.35). Females also had a greater intensity of pain, more unilateral and pulsatile pain, and exacerbation by physical activity (OR = 1.40-1.49) as well as more associated symptoms (OR = 1.26-1.98). Females carried 79% of the total migraine disease burden, which was almost exclusively driven by migraine without aura (77%), whilst there was no sex difference in the disease burden of migraine with aura. CONCLUSION: Females have more severe disease, resulting in a much higher migraine disease burden than indicated by prevalence alone.

Genome-wide association study of febrile seizures implicates fever response and neuronal excitability genes.

Febrile seizures represent the most common type of pathological brain activity in young children and are influenced by genetic, environmental and developmental factors. In a minority of cases, febrile seizures precede later development of epilepsy. We conducted a genome-wide association study of febrile seizures in 7635 cases and 83 966 controls identifying and replicating seven new loci, all with P < 5 × 10-10. Variants at two loci were functionally related to altered expression of the fever response genes PTGER3 and IL10, and four other loci harboured genes (BSN, ERC2, GABRG2, HERC1) influencing neuronal excitability by regulating neurotransmitter release and binding, vesicular transport or membrane trafficking at the synapse. Four previously reported loci (SCN1A, SCN2A, ANO3 and 12q21.33) were all confirmed. Collectively, the seven novel and four previously reported loci explained 2.8% of the variance in liability to febrile seizures, and the single nucleotide polymorphism heritability based on all common autosomal single nucleotide polymorphisms was 10.8%. GABRG2, SCN1A and SCN2A are well-established epilepsy genes and, overall, we found positive genetic correlations with epilepsies (rg = 0.39, P = 1.68 × 10-4). Further, we found that higher polygenic risk scores for febrile seizures were associated with epilepsy and with history of hospital admission for febrile seizures. Finally, we found that polygenic risk of febrile seizures was lower in febrile seizure patients with neuropsychiatric disease compared to febrile seizure patients in a general population sample. In conclusion, this largest genetic investigation of febrile seizures to date implicates central fever response genes as well as genes affecting neuronal excitability, including several known epilepsy genes. Further functional and genetic studies based on these findings will provide important insights into the complex pathophysiological processes of seizures with and without fever.

Polygenic risk score for ACE-inhibitor-associated cough based on the discovery of new genetic loci.

AIMS: To search for sequence variants associated with ACEi discontinuation and to test their association with ACEi-associated adverse drug reactions (ADRs). METHODS AND RESULTS: A genome-wide association study (GWAS) on ACEi discontinuation was conducted, including 33 959 ACEi-discontinuers and 44 041 controls. Cases were defined as persons who switched from an ACEi treatment to an angiotensin receptor blocker. Controls were defined as persons who continued ACEi treatment for at least 1 year. Odds ratios (ORs) and 95% confidence intervals (95% CIs) were computed for ACEi discontinuation risk by mixed model regression analysis. Summary statistics from the individual cohorts were meta-analyzed with a fixed-effects model. To test for association with specific ACEi-associated ADRs, any genome-wide significant (P < 5 × 10-8) ACEi discontinuation variants was tested for association with ACEi-associated cough and angioedema. A polygenetic risk score (PRS) based on ACEi discontinuation GWAS data was constructed and tested for association with ACEi-associated cough and angioedema in two population-based samples. In total, seven genetic genome-wide loci were identified, of which six were previously unreported. The strongest association with ACEi discontinuation was at 20q13.3 (NTSR1; OR: 1.21; 95% CI: 1.17-1.24; P = 2.1 × 10-34). Five of seven lead variants were associated with ACEi-associated cough, whereas none were associated with ACEi-associated angioedema. The ACEi discontinuation PRS was associated with ACEi-associated cough in a dose-response manner but not with ACEi-associated angioedema. ACEi discontinuation was genetically correlated with important causes for cough, including gastro-esophageal reflux disease, allergic rhinitis, hay fever, and asthma, which indicates partly shared genetic underpinning between these traits. CONCLUSION: This study showed the advantage of using prescription patterns to discover genetic links with ADRs. In total, seven genetic loci that associated with ACEi discontinuation were identified. There was evidence of a strong association between our ADR phenotype and ACEi-associated cough. Taken together, these findings increase insight into the pathophysiological processes that underlie ACEi-associated ADRs.

Multiomics analysis of rheumatoid arthritis yields sequence variants that have large effects on risk of the seropositive subset.

OBJECTIVES: To find causal genes for rheumatoid arthritis (RA) and its seropositive (RF and/or ACPA positive) and seronegative subsets. METHODS: We performed a genome-wide association study (GWAS) of 31 313 RA cases (68% seropositive) and ~1 million controls from Northwestern Europe. We searched for causal genes outside the HLA-locus through effect on coding, mRNA expression in several tissues and/or levels of plasma proteins (SomaScan) and did network analysis (Qiagen). RESULTS: We found 25 sequence variants for RA overall, 33 for seropositive and 2 for seronegative RA, altogether 37 sequence variants at 34 non-HLA loci, of which 15 are novel. Genomic, transcriptomic and proteomic analysis of these yielded 25 causal genes in seropositive RA and additional two overall. Most encode proteins in the network of interferon-alpha/beta and IL-12/23 that signal through the JAK/STAT-pathway. Highlighting those with largest effect on seropositive RA, a rare missense variant in STAT4 (rs140675301-A) that is independent of reported non-coding STAT4-variants, increases the risk of seropositive RA 2.27-fold (p=2.1×10-9), more than the rs2476601-A missense variant in PTPN22 (OR=1.59, p=1.3×10-160). STAT4 rs140675301-A replaces hydrophilic glutamic acid with hydrophobic valine (Glu128Val) in a conserved, surface-exposed loop. A stop-mutation (rs76428106-C) in FLT3 increases seropositive RA risk (OR=1.35, p=6.6×10-11). Independent missense variants in TYK2 (rs34536443-C, rs12720356-C, rs35018800-A, latter two novel) associate with decreased risk of seropositive RA (ORs=0.63-0.87, p=10-9-10-27) and decreased plasma levels of interferon-alpha/beta receptor 1 that signals through TYK2/JAK1/STAT4. CONCLUSION: Sequence variants pointing to causal genes in the JAK/STAT pathway have largest effect on seropositive RA, while associations with seronegative RA remain scarce.

Hyperhidrosis and human leucocyte antigens in the Danish Blood Donor Study.

Familial clustering of the skin disease primary hyperhidrosis suggests a genetic component to the disease. The human leucocyte antigen (HLA) is implicated in a range of diseases, including many comorbidities to hyperhidrosis. No study has investigated whether the HLA genes are involved in the pathogenesis of hyperhidrosis. We, therefore, compared HLA alleles in individuals with and without hyperhidrosis in this study of 65 000 blood donors. In this retrospective cohort study, we retrieved information on individuals with and without hyperhidrosis using self-reported questionnaires, the Danish National Patient Registry and the Danish National Prescription Registry on participants recruited to the Danish Blood Donor Study between 2010 and 2019. Association tests using logistic regression were conducted for each HLA allele corrected for sex, age, body mass index, smoking and principal components. Overall, 145 of 65 795 (0.2%) participants had hospital diagnosed hyperhidrosis. Similarly, 1379 of 15 530 (8.9%) participants had moderate-severe self-reported hyperhidrosis, of whom 447 (2.9%) had severe self-reported hyperhidrosis. Altogether, 28 participants had both hospital diagnosed and moderate-severe self-reported hyperhidrosis. Severe self-reported hyperhidrosis was associated with HLA-A*80:01 (adjusted odds ratio 26.97; 95% confidence interval 5.32-136.70; n = 7; P < .001). Moderate-severe self-reported hyperhidrosis and hospital diagnosed hyperhidrosis were not associated with any HLA. The association between hyperhidrosis and HLA-A*80:01 was based on a very small number of cases and not replicated in other patient subsets, and therefore likely a chance finding. Thus, this study suggests that genes other than the HLA are involved in the pathogenesis of hyperhidrosis.

Genetic insight into sick sinus syndrome.

AIMS: The aim of this study was to use human genetics to investigate the pathogenesis of sick sinus syndrome (SSS) and the role of risk factors in its development. METHODS AND RESULTS: We performed a genome-wide association study of 6469 SSS cases and 1 000 187 controls from deCODE genetics, the Copenhagen Hospital Biobank, UK Biobank, and the HUNT study. Variants at six loci associated with SSS, a reported missense variant in MYH6, known atrial fibrillation (AF)/electrocardiogram variants at PITX2, ZFHX3, TTN/CCDC141, and SCN10A and a low-frequency (MAF = 1.1-1.8%) missense variant, p.Gly62Cys in KRT8 encoding the intermediate filament protein keratin 8. A full genotypic model best described the p.Gly62Cys association (P = 1.6 × 10-20), with an odds ratio (OR) of 1.44 for heterozygotes and a disproportionally large OR of 13.99 for homozygotes. All the SSS variants increased the risk of pacemaker implantation. Their association with AF varied and p.Gly62Cys was the only variant not associating with any other arrhythmia or cardiovascular disease. We tested 17 exposure phenotypes in polygenic score (PGS) and Mendelian randomization analyses. Only two associated with the risk of SSS in Mendelian randomization, AF, and lower heart rate, suggesting causality. Powerful PGS analyses provided convincing evidence against causal associations for body mass index, cholesterol, triglycerides, and type 2 diabetes (P > 0.05). CONCLUSION: We report the associations of variants at six loci with SSS, including a missense variant in KRT8 that confers high risk in homozygotes and points to a mechanism specific to SSS development. Mendelian randomization supports a causal role for AF in the development of SSS.

Genetic insight into sick sinus syndrome.

AIMS: The aim of this study was to use human genetics to investigate the pathogenesis of sick sinus syndrome (SSS) and the role of risk factors in its development. METHODS AND RESULTS: We performed a genome-wide association study of 6469 SSS cases and 1 000 187 controls from deCODE genetics, the Copenhagen Hospital Biobank, UK Biobank, and the HUNT study. Variants at six loci associated with SSS, a reported missense variant in MYH6, known atrial fibrillation (AF)/electrocardiogram variants at PITX2, ZFHX3, TTN/CCDC141, and SCN10A and a low-frequency (MAF = 1.1-1.8%) missense variant, p.Gly62Cys in KRT8 encoding the intermediate filament protein keratin 8. A full genotypic model best described the p.Gly62Cys association (P = 1.6 × 10-20), with an odds ratio (OR) of 1.44 for heterozygotes and a disproportionally large OR of 13.99 for homozygotes. All the SSS variants increased the risk of pacemaker implantation. Their association with AF varied and p.Gly62Cys was the only variant not associating with any other arrhythmia or cardiovascular disease. We tested 17 exposure phenotypes in polygenic score (PGS) and Mendelian randomization analyses. Only two associated with the risk of SSS in Mendelian randomization, AF, and lower heart rate, suggesting causality. Powerful PGS analyses provided convincing evidence against causal associations for body mass index, cholesterol, triglycerides, and type 2 diabetes (P > 0.05). CONCLUSION: We report the associations of variants at six loci with SSS, including a missense variant in KRT8 that confers high risk in homozygotes and points to a mechanism specific to SSS development. Mendelian randomization supports a causal role for AF in the development of SSS.

Genome-wide analysis of 944 133 individuals provides insights into the etiology of haemorrhoidal disease.

OBJECTIVE: Haemorrhoidal disease (HEM) affects a large and silently suffering fraction of the population but its aetiology, including suspected genetic predisposition, is poorly understood. We report the first genome-wide association study (GWAS) meta-analysis to identify genetic risk factors for HEM to date. DESIGN: We conducted a GWAS meta-analysis of 218 920 patients with HEM and 725 213 controls of European ancestry. Using GWAS summary statistics, we performed multiple genetic correlation analyses between HEM and other traits as well as calculated HEM polygenic risk scores (PRS) and evaluated their translational potential in independent datasets. Using functional annotation of GWAS results, we identified HEM candidate genes, which differential expression and coexpression in HEM tissues were evaluated employing RNA-seq analyses. The localisation of expressed proteins at selected loci was investigated by immunohistochemistry. RESULTS: We demonstrate modest heritability and genetic correlation of HEM with several other diseases from the GI, neuroaffective and cardiovascular domains. HEM PRS validated in 180 435 individuals from independent datasets allowed the identification of those at risk and correlated with younger age of onset and recurrent surgery. We identified 102 independent HEM risk loci harbouring genes whose expression is enriched in blood vessels and GI tissues, and in pathways associated with smooth muscles, epithelial and endothelial development and morphogenesis. Network transcriptomic analyses highlighted HEM gene coexpression modules that are relevant to the development and integrity of the musculoskeletal and epidermal systems, and the organisation of the extracellular matrix. CONCLUSION: HEM has a genetic component that predisposes to smooth muscle, epithelial and connective tissue dysfunction.