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.

The sequences of 150,119 genomes in the UK Biobank.

Detailed knowledge of how diversity in the sequence of the human genome affects phenotypic diversity depends on a comprehensive and reliable characterization of both sequences and phenotypic variation. Over the past decade, insights into this relationship have been obtained from whole-exome sequencing or whole-genome sequencing of large cohorts with rich phenotypic data1,2. Here we describe the analysis of whole-genome sequencing of 150,119 individuals from the UK Biobank3. This constitutes a set of high-quality variants, including 585,040,410 single-nucleotide polymorphisms, representing 7.0% of all possible human single-nucleotide polymorphisms, and 58,707,036 indels. This large set of variants allows us to characterize selection based on sequence variation within a population through a depletion rank score of windows along the genome. Depletion rank analysis shows that coding exons represent a small fraction of regions in the genome subject to strong sequence conservation. We define three cohorts within the UK Biobank: a large British Irish cohort, a smaller African cohort and a South Asian cohort. A haplotype reference panel is provided that allows reliable imputation of most variants carried by three or more sequenced individuals. We identified 895,055 structural variants and 2,536,688 microsatellites, groups of variants typically excluded from large-scale whole-genome sequencing studies. Using this formidable new resource, we provide several examples of trait associations for rare variants with large effects not found previously through studies based on whole-exome sequencing and/or imputation.

A machine-learning method for biobank-scale genetic prediction of blood group antigens.

A key element for successful blood transfusion is compatibility of the patient and donor red blood cell (RBC) antigens. Precise antigen matching reduces the risk for immunization and other adverse transfusion outcomes. RBC antigens are encoded by specific genes, which allows developing computational methods for determining antigens from genomic data. We describe here a classification method for determining RBC antigens from genotyping array data. Random forest models for 39 RBC antigens in 14 blood group systems and for human platelet antigen (HPA)-1 were trained and tested using genotype and RBC antigen and HPA-1 typing data available for 1,192 blood donors in the Finnish Blood Service Biobank. The algorithm and models were further evaluated using a validation cohort of 111,667 Danish blood donors. In the Finnish test data set, the median (interquartile range [IQR]) balanced accuracy for 39 models was 99.9 (98.9-100)%. We were able to replicate 34 out of 39 Finnish models in the Danish cohort and the median (IQR) balanced accuracy for classifications was 97.1 (90.1-99.4)%. When applying models trained with the Danish cohort, the median (IQR) balanced accuracy for the 40 Danish models in the Danish test data set was 99.3 (95.1-99.8)%. The RBC antigen and HPA-1 prediction models demonstrated high overall accuracies suitable for probabilistic determination of blood groups and HPA-1 at biobank-scale. Furthermore, population-specific training cohort increased the accuracies of the models. This stand-alone and freely available method is applicable for research and screening for antigen-negative blood donors.

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.

A partial loss-of-function variant in STAT6 protects against T2 asthma.

BACKGROUND: Signal Transducer and Activator of Transcription 6 (STAT6) is central to Type 2 (T2) inflammation and common non-coding variants at the STAT6 locus associate with various T2 inflammatory traits, including diseases, and its pathway is widely targeted in asthma treatment. OBJECTIVE: To test the association of a rare missense variant in STAT6, p.L406P, with T2 inflammatory traits, including the risk of asthma and allergic diseases, and to characterize its functional consequences in cell culture. METHODS: We tested association of p.L406P with plasma protein levels, white blood cell counts and the risk of asthma and allergic phenotypes. We tested significant associations in other cohorts using a burden test. The effects of p.L406P on STAT6 protein function were examined in cell lines and by comparing CD4+ T-cell responses from carriers and non-carriers of the variant. RESULTS: p.L406P associated with reduced plasma levels of STAT6 and IgE as well as with lower eosinophil and basophil counts in blood. It also protected against asthma, mostly driven by severe T2 high asthma. We showed that p.L406P led to lower IL-4-induced activation in luciferase reporter assays and lower levels of STAT6 in CD4+ T cells. We identified multiple genes with expression that was affected by the p.L406P genotype upon IL-4 treatment of CD4+ T cells; the effect was consistent with a weaker IL-4 response in carriers than non-carriers of p.L406P. CONCLUSIONS: We report a partial loss-of-function variant in STAT6, resulting in dampened IL-4 responses and protection from T2 high asthma, implicating STAT6 as an attractive therapeutic target.

Meta-analysis of ACE inhibitor-induced angioedema identifies novel risk locus.

BACKGROUND: Angioedema is a rare but potentially life-threatening adverse drug reaction in patients receiving angiotensin-converting enzyme inhibitors (ACEis). Research suggests that susceptibility to ACEi-induced angioedema (ACEi-AE) involves both genetic and nongenetic risk factors. Genome- and exome-wide studies of ACEi-AE have identified the first genetic risk loci. However, understanding of the underlying pathophysiology remains limited. OBJECTIVE: We sought to identify further genetic factors of ACEi-AE to eventually gain a deeper understanding of its pathophysiology. METHODS: By combining data from 8 cohorts, a genome-wide association study meta-analysis was performed in more than 1000 European patients with ACEi-AE. Secondary bioinformatic analyses were conducted to fine-map associated loci, identify relevant genes and pathways, and assess the genetic overlap between ACEi-AE and other traits. Finally, an exploratory cross-ancestry analysis was performed to assess shared genetic factors in European and African-American patients with ACEi-AE. RESULTS: Three genome-wide significant risk loci were identified. One of these, located on chromosome 20q11.22, has not been implicated previously in ACEi-AE. Integrative secondary analyses highlighted previously reported genes (BDKRB2 [bradykinin receptor B2] and F5 [coagulation factor 5]) as well as biologically plausible novel candidate genes (PROCR [protein C receptor] and EDEM2 [endoplasmic reticulum degradation enhancing alpha-mannosidase like protein 2]). Lead variants at the risk loci were found with similar effect sizes and directions in an African-American cohort. CONCLUSIONS: The present results contributed to a deeper understanding of the pathophysiology of ACEi-AE by (1) providing further evidence for the involvement of bradykinin signaling and coagulation pathways and (2) suggesting, for the first time, the involvement of the fibrinolysis pathway in this adverse drug reaction. An exploratory cross-ancestry comparison implicated the relevance of the associated risk loci across diverse ancestries.

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.

Real-world Effectiveness of Fecal Microbiota Transplantation for First or Second Clostridioides difficile Infection.

BACKGROUND & AIMS: Clostridioides difficile infection (CDI) is associated with high mortality. Fecal microbiota transplantation (FMT) is an established treatment for recurrent CDI, but its use for first or second CDI remains experimental. We aimed to investigate the effectiveness of FMT for first or second CDI in a real-world clinical setting. METHODS: This multi-site Danish cohort study included patients with first or second CDI treated with FMT from June 2019 to February 2023. The primary outcome was cure of C. difficile-associated diarrhea (CDAD) 8 weeks after the last FMT treatment. Secondary outcomes included CDAD cure 1 and 8 weeks after the first FMT treatment and 90-day mortality following positive C. difficile test. RESULTS: We included 467 patients, with 187 (40%) having their first CDI. The median patient age was 73 years (interquartile range [IQR], 58-82 years). Notably, 167 (36%) had antibiotic-refractory CDI, 262 (56%) had severe CDI, and 89 (19%) suffered from fulminant CDI. Following the first FMT treatment, cure of CDAD was achieved in 353 patients (76%; 95% confidence interval [CI], 71%-79%) at week 1. At week 8, 255 patients (55%; 95% CI, 50%-59%) maintained sustained effect. In patients without initial effect, repeated FMT treatments led to an overall cure of CDAD in 367 patients (79%; 95% CI, 75%-82%). The 90-day mortality was 10% (95% CI, 8%-14%). CONCLUSION: Repeated FMT treatments demonstrate high effectiveness in managing patients with first or second CDI. Forwarding FMT in CDI treatment guidelines could improve patient survival. CLINICALTRIALS: gov, Number: NCT03712722.

A deep learning approach to prediction of blood group antigens from genomic data.

BACKGROUND: Deep learning methods are revolutionizing natural science. In this study, we aim to apply such techniques to develop blood type prediction models based on cheap to analyze and easily scalable screening array genotyping platforms. METHODS: Combining existing blood types from blood banks and imputed screening array genotypes for ~111,000 Danish and 1168 Finnish blood donors, we used deep learning techniques to train and validate blood type prediction models for 36 antigens in 15 blood group systems. To account for missing genotypes a denoising autoencoder initial step was utilized, followed by a convolutional neural network blood type classifier. RESULTS: Two thirds of the trained blood type prediction models demonstrated an F1-accuracy above 99%. Models for antigens with low or high frequencies like, for example, Cw, low training cohorts like, for example, Cob, or very complicated genetic underpinning like, for example, RhD, proved to be more challenging for high accuracy (>99%) DL modeling. However, in the Danish cohort only 4 out of 36 models (Cob, Cw, D-weak, Kpa) failed to achieve a prediction F1-accuracy above 97%. This high predictive performance was replicated in the Finnish cohort. DISCUSSION: High accuracy in a variety of blood groups proves viability of deep learning-based blood type prediction using array chip genotypes, even in blood groups with nontrivial genetic underpinnings. These techniques are suitable for aiding in identifying blood donors with rare blood types by greatly narrowing down the potential pool of candidate donors before clinical grade confirmation.

Blood donation and migraine relief: A national population cohort study in Denmark.

INTRODUCTION: Migraine is a prevalent neurological headache disorder. Due to challenges associated with finding effective treatment, many individuals with migraine feel compelled to explore alternative treatment strategies, such as blood donation, hypothesized to provide migraine relief. METHODS: Through logistic, Poisson, and Cox regression methods, we examined the links between migraine and blood donation activities in two population cohorts: Danish blood donors in the Scandinavian Donations and Transfusions Database (SCANDAT-DK, N >1 million) and the Danish Blood Donor Study (N ~ 100,000). RESULTS: SCANDAT-DK analyses showed no link between migraine and the propensity to become a blood donor among males (odds ratio [OR]Males = 0.95 [95% Confidence Interval: 0.86-1.04], and a reduced propensity among females ORFemales = 0.88 [0.83-0.93]). The incidence of migraine was not reduced upon blood donation (standardized incidence ratio [SIR]Males = 0.94 [0.83-1.06]; SIRFemales = 1.04 [0.99-1.10]). Donors with migraine demonstrated longer intervals between donations (hazard ratio [HR]Males = 0.87 [0.85-0.91], HRFemales = 0.80 [0.78-0.82]), and an increased risk of donor lapse (ORMales = 1.23 [1.14-1.32]; ORFemales = 1.28 [1.22-1.33]). Results were corroborated in DBDS using self-reported migraine. Genetic predisposition to migraine associated with longer intervals in females (HRFemales = 0.98 [0.97-0.99]), but not in males. DISCUSSION: Our findings do not support the hypothesis that blood donation serves as a viable treatment strategy among migraine patients. Future prospective investigations may help to elucidate the underlying biological mechanisms by which blood donation may influence migraine pathology.

Safety and protection of plasma donors: A scoping review and evidence gap map.

BACKGROUND AND OBJECTIVES: As part of a large-scale project to safely increase plasma collection in Europe, the current scoping review identifies the existing evidence (gaps) on adverse events (AEs) and other health effects in plasmapheresis donors, as well as factors that may be associated with such events/effects. MATERIALS AND METHODS: We searched six databases and three registries. Study characteristics (publication type, language, study design, population, outcomes, associated factors, time of assessment, duration of follow-up, number and frequency of donations, convalescent plasma [y/n], setting and location) were synthesized narratively and in an interactive evidence gap map (EGM). RESULTS: Ninety-four research articles and five registrations were identified. Around 90% were observational studies (57 controlled and 33 uncontrolled), and most of them were performed in Europe (55%) or the United States (20%). Factors studied in association with donor health included donor characteristics (e.g., sex, age) (n = 27), cumulative number of donations (n = 21), donation frequency (n = 11), plasma collection device or programme (n = 11), donor status (first time vs. repeat) (n = 10), donation volume per session (n = 8), time in donation programme (n = 3), preventive measures (n = 2) or other (n = 9). CONCLUSION: The current scoping review provides an accessible tool for researchers and policymakers to identify the available evidence (gaps) concerning plasmapheresis donation safety. Controlled prospective studies with long-term donor follow-up are scarce. Furthermore, additional experimental studies comparing the health effects of different donation frequencies are required to inform a safe upper limit for donation frequency.

The International Society of Blood Transfusion (ISBT) Public Health Research Toolkit: A report from the Surveillance, Risk Assessment and Policy Sub-group of the ISBT Transfusion Transmitted Infectious Diseases Working Party.

BACKGROUND AND OBJECTIVES: Data provided from blood donors have contributed to the understanding of public health epidemiology and policy decisions. A recent example was during the severe acute respiratory syndrome-related coronavirus (SARS-CoV-2) pandemic when blood services monitored the seroprevalence in blood donors. Based on this experience, blood services have the opportunity to expand their role and participate in public health surveillance and research. The aim of this report is to share available resources to assist blood services in this area. MATERIALS AND METHODS: The Surveillance, Risk Assessment and Policy (SRAP) Sub-group of the International Society of Blood Transfusion (ISBT) Transfusion Transmitted Infectious Diseases (TTID) Working Party developed a Public Health Research Toolkit to assist blood services and researchers interested in expanding their role in public health research. RESULTS: The ISBT Public Health Research Toolkit provides resources for what blood services can offer to public health, examples of donor research studies, the utility of donor data and website links to public health agencies. The toolkit includes a customizable template for those interested in establishing and managing a biobank. CONCLUSION: The ISBT Public Health Research Toolkit includes resources to increase the recognition of the role blood donors can play in public health and to help blood services gain commitment and funding from various agencies for new research and surveillance.

International review of blood donation nucleic acid amplification testing.

BACKGROUND AND OBJECTIVES: Nucleic acid amplification testing (NAT), in blood services context, is used for the detection of viral and parasite nucleic acids to reduce transfusion-transmitted infections. This project reviewed NAT for screening blood donations globally. MATERIALS AND METHODS: A survey on NAT usage, developed by the International Society of Blood Transfusion Working Party on Transfusion-transmitted Infectious Diseases (ISBT WP-TTID), was distributed through ISBT WP-TTID members. Data were analysed using descriptive statistics. RESULTS: Forty-three responses were received from 32 countries. Increased adoption of blood donation viral screening by NAT was observed over the past decade. NAT-positive donations were detected for all viruses tested in 2019 (proportion of donations positive by NAT were 0.0099% for human immunodeficiency virus [HIV], 0.0063% for hepatitis C virus [HCV], 0.0247% for hepatitis B virus [HBV], 0.0323% for hepatitis E virus [HEV], 0.0014% for West Nile virus [WNV] and 0.00005% for Zika virus [ZIKV]). Globally, over 3100 NAT-positive donations were identified as NAT yield or solely by NAT in 2019 and over 22,000 since the introduction of NAT, with HBV accounting for over half. NAT-positivity rate was higher in first-time donors for all viruses tested except WNV. During 2019, a small number of participants performed NAT for parasites (Trypanosoma cruzi, Babesia spp., Plasmodium spp.). CONCLUSION: This survey captures current use of blood donation NAT globally. There has been increased NAT usage over the last decade. It is clear that NAT contributes to improving blood transfusion safety globally; however, there is a need to overcome economic barriers for regions/countries not performing NAT.

An international review of the characteristics of viral nucleic acid-amplification testing (NAT) reveals a trend towards the use of smaller pool sizes and individual donation NAT.

BACKGROUND AND OBJECTIVES: Nucleic acid-amplification testing (NAT) is used for screening blood donations/donors for blood-borne viruses. We reviewed global viral NAT characteristics and NAT-yield confirmatory testing used by blood operators. MATERIALS AND METHODS: NAT characteristics and NAT-yield confirmatory testing used during 2019 was surveyed internationally by the International Society of Blood Transfusion Working Party Transfusion-Transmitted Infectious Diseases. Reported characteristics are presented herein. RESULTS: NAT was mainly performed under government mandate. Human immunodeficiency virus (HIV), hepatitis C virus (HCV) and hepatitis B virus (HBV) NAT was performed on all donors and donation types, while selective testing was reported for West Nile virus, hepatitis E virus (HEV), and Zika virus. Individual donation NAT was used for HIV, HCV and HBV by ~50% of responders, while HEV was screened in mini-pools by 83% of responders performing HEV NAT. Confirmatory testing for NAT-yield samples was generally performed by NAT on a sample from the same donation or by NAT and serology on samples from the same donation and a follow-up sample. CONCLUSION: In the last decade, there has been a trend towards use of smaller pool sizes or individual donation NAT. We captured characteristics of NAT internationally in 2019 and provide insights into confirmatory testing approaches used for NAT-yields, potentially benefitting blood operators seeking to implement NAT.

Revaccination of patients with systemic lupus erythematosus or rheumatoid arthritis without an initial COVID-19 vaccine response elicits seroconversion in half of the patients.

OBJECTIVES: To investigate the effect of COVID-19 mRNA revaccination (two doses) on the antibody response in patients with rheumatic diseases (RD) who were initial vaccine non-responders. Further, to examine if B-cell levels or T-cell responses before revaccination predicted seroconversion. METHODS: From a RD cohort vaccinated with the standard two-dose COVID-19 vaccinations, we enrolled cases without detectable antibody responses (n=17) and controls with detectable antibody response (n=29). Blood donors (n=32) were included as additional controls. Samples were collected before and six weeks after completed revaccination. Total antibodies and specific IgG, IgA, and IgM against SARS-CoV-2 spike protein, SARS-CoV-2 neutralising antibodies, and SARS-CoV-2 reacting CD4+ and CD8+ T-cells were measured before and after revaccination. B-cells (CD19+CD45+) were quantified before revaccination. RESULTS: Forty-seven percent of cases had detectable neutralising antibodies after revaccination. However, antibody levels were significantly lower than in controls and blood donors. Revaccination induced an antibody class switch in cases with a decrease in IgM and increase in IgG. No significant difference was observed in T-cell responses before and after revaccination between the three groups. Only 29% of cases had measurable B-cells compared to 100% of controls and blood donors. Fifty percent of revaccinated cases who seroconverted had measurable B-cells before revaccination. CONCLUSIONS: Forty-seven percent of initial non-responders seroconverted after two-dose revaccination but still had lower levels of SARS-CoV-2 antibodies compared with controls and blood donors. RD patients without a detectable serological response after the initial COVID-19 mRNA vaccine had a T-cell response similar to immunocompetent controls and blood donors.

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.

Dyslipidemia, inflammation, calcification, and adiposity in aortic stenosis: a genome-wide study.

AIMS: Although highly heritable, the genetic etiology of calcific aortic stenosis (AS) remains incompletely understood. The aim of this study was to discover novel genetic contributors to AS and to integrate functional, expression, and cross-phenotype data to identify mechanisms of AS. METHODS AND RESULTS: A genome-wide meta-analysis of 11.6 million variants in 10 cohorts involving 653 867 European ancestry participants (13 765 cases) was performed. Seventeen loci were associated with AS at P ≤ 5 × 10-8, of which 15 replicated in an independent cohort of 90 828 participants (7111 cases), including CELSR2-SORT1, NLRP6, and SMC2. A genetic risk score comprised of the index variants was associated with AS [odds ratio (OR) per standard deviation, 1.31; 95% confidence interval (CI), 1.26-1.35; P = 2.7 × 10-51] and aortic valve calcium (OR per standard deviation, 1.22; 95% CI, 1.08-1.37; P = 1.4 × 10-3), after adjustment for known risk factors. A phenome-wide association study indicated multiple associations with coronary artery disease, apolipoprotein B, and triglycerides. Mendelian randomization supported a causal role for apolipoprotein B-containing lipoprotein particles in AS (OR per g/L of apolipoprotein B, 3.85; 95% CI, 2.90-5.12; P = 2.1 × 10-20) and replicated previous findings of causality for lipoprotein(a) (OR per natural logarithm, 1.20; 95% CI, 1.17-1.23; P = 4.8 × 10-73) and body mass index (OR per kg/m2, 1.07; 95% CI, 1.05-1.9; P = 1.9 × 10-12). Colocalization analyses using the GTEx database identified a role for differential expression of the genes LPA, SORT1, ACTR2, NOTCH4, IL6R, and FADS. CONCLUSION: Dyslipidemia, inflammation, calcification, and adiposity play important roles in the etiology of AS, implicating novel treatments and prevention strategies.

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.

Rituximab-treated rheumatic patients: B cells predict seroconversion after COVID-19 boost or revaccination in initial vaccine non-responders.

OBJECTIVES: To investigate the effect of either a booster vaccine (one dose) or revaccination (two doses 3 weeks apart) on the antibody response to the COVID-19 mRNA vaccines in patients with rheumatic disease (RD) treated with rituximab (RTX) who had not produced vaccine-reactive antibodies after the initial two vaccine doses. Further, to examine if B cell levels in peripheral blood predicted seroconversion. METHODS: We included 91 RTX-treated RD patients previously vaccinated against COVID-19. Patients were offered revaccination or a single booster vaccination with an mRNA vaccine. Serum total antibodies against SARS-CoV-2 spike protein were measured before and 6 weeks after the last vaccine dose. B cells (CD19+CD45+) were measured by flow cytometry at inclusion. RESULTS: Of RD patients with undetectable SARS-CoV-2 antibody levels before inclusion, seroconversion was seen in 38% 6 weeks after the booster dose and 32% after revaccination. Patients receiving revaccination had significantly higher antibody levels than patients receiving a booster dose (P < 0.001). In both univariate and multivariate logistic regression analysis, only B cells higher than 10/µl before boost or revaccination were associated with seroconversion (P = 0.009 and P = 0.01, respectively). Seroconversion was independent of age, gender, diagnosis, cumulative RTX dose, RTX treatment time and time since last RTX treatment. CONCLUSION: Continuously impaired humoral response to mRNA vaccines was found in most RTX-treated patients after a booster dose or revaccination. Seroconversion was observed in approximately one-third of the patients. Measurable B cells before boosting or revaccination was the strongest predictor of antibody response after boost or revaccination.