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.

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.

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.

Cluster Headache Genomewide Association Study and Meta-Analysis Identifies Eight Loci and Implicates Smoking as Causal Risk Factor.

OBJECTIVE: The objective of this study was to aggregate data for the first genomewide association study meta-analysis of cluster headache, to identify genetic risk variants, and gain biological insights. METHODS: A total of 4,777 cases (3,348 men and 1,429 women) with clinically diagnosed cluster headache were recruited from 10 European and 1 East Asian cohorts. We first performed an inverse-variance genomewide association meta-analysis of 4,043 cases and 21,729 controls of European ancestry. In a secondary trans-ancestry meta-analysis, we included 734 cases and 9,846 controls of East Asian ancestry. Candidate causal genes were prioritized by 5 complementary methods: expression quantitative trait loci, transcriptome-wide association, fine-mapping of causal gene sets, genetically driven DNA methylation, and effects on protein structure. Gene set and tissue enrichment analyses, genetic correlation, genetic risk score analysis, and Mendelian randomization were part of the downstream analyses. RESULTS: The estimated single nucleotide polymorphism (SNP)-based heritability of cluster headache was 14.5%. We identified 9 independent signals in 7 genomewide significant loci in the primary meta-analysis, and one additional locus in the trans-ethnic meta-analysis. Five of the loci were previously known. The 20 genes prioritized as potentially causal for cluster headache showed enrichment to artery and brain tissue. Cluster headache was genetically correlated with cigarette smoking, risk-taking behavior, attention deficit hyperactivity disorder (ADHD), depression, and musculoskeletal pain. Mendelian randomization analysis indicated a causal effect of cigarette smoking intensity on cluster headache. Three of the identified loci were shared with migraine. INTERPRETATION: This first genomewide association study meta-analysis gives clues to the biological basis of cluster headache and indicates that smoking is a causal risk factor. ANN NEUROL 2023;94:713-726.

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.

Cluster Analysis Identifies Clinical Phenotypes of Primary Hyperhidrosis.

INTRODUCTION: Identifying subgroups of patients with primary hyperhidrosis (PHH) can improve the understanding of the disease pathophysiology. The study objective was to determine the naturally occurring subgroups of patients with PHH based on clinical characteristics. METHODS: In this retrospective cohort study, data were collected from participants included in a clinical trial. The data were collected between January 2020 and June 2021 from outpatients with PHH attending a dermatologic department in Denmark. Overall, 84 patients with PHH were screened for inclusion in the clinical trial. Of these, 41 met the eligibility criteria. Four participants were excluded because of missing data. The main outcome was the identification of subgroups of patients with PHH using an unsupervised hierarchical cluster analysis. RESULTS: Overall, 37 patients were included {28 (76.7%) females; median age at inclusion 28.0 (interquartile range [IQR] 24.0-38.3); median body mass index 24.9 (IQR 20.9-27.4); median age of onset 13.0 (IQR 9.5-18.5); and 26 (70.3%) had a familial disposition toward PHH}. Two clusters of 18 and 17 patients were identified. The first cluster had, when compared to the second, a younger age of onset (median age 11.0 [IQR 0-13.0] vs. 17.0 [IQR 15.0-21.0], p = 0.003) and higher sweat rates on gravimetry (median 175.0 [IQR 121.2-252.5] vs. 40.0 [IQR 20.0-60.0] milligrams of sweat/5 min, p < 0.001) and transepidermal water loss (median 93.7 [IQR 91.2-97.8] vs. 59.0 [IQR 44.4-73.2] g/m2/h, p < 0.001). No differences were observed for the other variables. CONCLUSIONS: This study identifies 2 subgroups of patients with PHH. The patients with an onset of PHH during childhood had a substantially higher sweat and evaporation rate in adulthood than those with an onset during adolescence. These findings may imply a changed understanding of the pathophysiology of PHH, by indicating that an early disease onset can lead to a worse disease course.

The healthy donor effect and survey participation, becoming a donor and donor career.

BACKGROUND: The healthy donor effect (HDE) is a selection bias caused by the health criteria blood donors must meet. It obscures investigations of beneficial/adverse health effects of blood donation and complicates the generalizability of findings from blood donor cohorts. To further characterize the HDE we investigated how self-reported health and lifestyle are associated with becoming a blood donor, lapsing, and donation intensity. Furthermore, we examined differences in mortality based on donor status. STUDY DESIGN AND METHODS: The Danish National Health Survey was linked to the Scandinavian Donations and Transfusions (SCANDAT) database and Danish register data. Logistic- and normal regression was used to compare baseline characteristics and participation. Poisson regression was used to investigate future donation choices. Donation intensity was explored by the Anderson-Gill model and Poisson regression. Mortality was investigated using Poisson regression. RESULTS: Blood donors were more likely to participate in the surveys, OR = 2.45 95% confidence interval (2.40-2.49) than non-donors. Among survey participants, better self-reported health and healthier lifestyle were associated with being or becoming a blood donor, donor retention, and to some extent donation intensity, for example, current smoking conveyed lower likelihood of becoming a donor, OR = 0.70 (0.66-0.75). We observed lower mortality for donors and survey participants, respectively, compared with non-participating non-donors. CONCLUSION: We provide evidence that blood donation is associated with increased likelihood to participate in health surveys, possibly a manifestation of the HDE. Furthermore, becoming a blood donor, donor retention, and donation intensity was associated with better self-reported health and healthier lifestyles.

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.

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.

Perioperative changes in cell-free DNA for patients undergoing surgery for colon cancer.

BACKGROUND: Various conditions with cellular decay are associated with elevated cell-free DNA (cfDNA). This study aimed to investigate if perioperatively measured cfDNA levels were associated with the surgical approach, complications, or recurrence. METHODS: Plasma was obtained from patients who underwent surgery for colon cancer at admission and at the time of discharge. Quantitative measurement of cfDNA was performed by amplifying two amplicons of 102 base pairs (bp) and 132 bp of Beta-2-Microglobulin (B2M) and Peptidyl-Prolyl cis-trans Isomerase A (PPIA), respectively. RESULTS: cfDNA was measured in 48 patients who underwent surgery for colonic cancer. Sixteen patients had recurrence during the follow-up period, fifteen developed a postoperative complication, and seventeen patients developed neither, acting as the control group. Postoperative cfDNA levels were significantly elevated from baseline samples, across all groups, with a median preoperatively B2M level of 48.3 alleles per mL and postoperatively of 220 alleles per mL and a median preoperatively level PPIA of 26.9 alleles per mL and postoperatively of 111.6 alleles per mL (p < 0.001 for B2M and p < 0.001 for PPIA). Postoperative levels of PPIA, but not B2M, were significantly higher in patients experiencing complications than in the control group (p = 0.036). However, a tendency towards an association between the surgical approach and the changes in cfDNA levels was found for PPIA (p = 0.058), and B2M (p = 0.087). CONCLUSIONS: Plasma cfDNA was increased after surgery in all patients with colon cancer. Postoperative PPIA levels were significantly higher in patients experiencing surgical complications but not in B2M levels.

The health-related quality of life in hyperhidrosis and co-morbidities.

PURPOSE: Hyperhidrosis has been associated with a reduced health-related quality of life (HRQoL). The role of common confounding factors of this association such as stress and socioeconomic status, however, remain largely unexplored, and may affect the management strategy for hyperhidrosis. Therefore, the study objective was to compare the HRQoL in individuals with and without hyperhidrosis while adjusting for confounders. METHODS: In this retrospective cohort study, data on the HRQoL measured by the short-form-12 questionnaire and self-reported hyperhidrosis were collected from the Danish Blood Donor Study-cohort. Data on international classification of disease-10 codes and redeemed prescriptions were collected from nationwide registries. Linear regression investigated the association between hyperhidrosis and HRQoL. RESULTS: Total 2794 (9.1%) of 30,808 blood donors had self-reported hyperhidrosis and 284 (0.2%) of 122,225 had hospital diagnosed hyperhidrosis. Self-reported hyperhidrosis was associated with a reduced mental HRQoL (adjusted beta coefficient - 1.10; 95% confidence interval - 1.37, - 0.82; p < 0.001) and physical HRQoL (adjusted beta coefficient - 0.90; 95% confidence interval - 1.09, - 0.70; p < 0.001). Hospital diagnosed hyperhidrosis was associated with a reduced mental HRQoL (adjusted beta coefficient - 0.91; 95% confidence interval - 1.82, - 0.04; p = 0.049). CONCLUSION: Hyperhidrosis is associated with a reduced HRQoL, independently of confounders or mode of diagnosis. This supports an approach primarily targeting 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.

Low vs high hemoglobin trigger for transfusion in vascular surgery: a randomized clinical feasibility trial.

Current guidelines advocate to limit red blood cell (RBC) transfusion during surgery, but the feasibility and safety of such a strategy remain unclear, as the majority of evidence is based on postoperatively stable patients. We assessed the effects of a protocol aiming to restrict RBC transfusion throughout hospitalization for vascular surgery. Fifty-eight patients scheduled for lower limb bypass or open abdominal aortic aneurysm repair were randomly assigned, on hemoglobin drop below 9.7 g/dL, to either a low-trigger (hemoglobin < 8.0 g/dL) or a high-trigger (hemoglobin < 9.7 g/dL) group for RBC transfusion. Near-infrared spectroscopy assessed intraoperative oxygen desaturation in brain and muscle. Explorative outcomes included nationwide registry data on death and major vascular complications. The primary outcome, mean hemoglobin within 15 days of surgery, was significantly lower in the low-trigger group, at 9.46 vs 10.33 g/dL in the high-trigger group (mean difference, -0.87 g/dL; P = .022), as were units of RBCs transfused (median [interquartile range (IQR)], 1 [0-2] vs 3 [2-6]; P = .0015). Although the duration and magnitude of cerebral oxygen desaturation increased in the low-trigger group (median [IQR], 421 [42-888] vs 127 [11-331] minutes × %; P = .0036), muscle oxygenation was unaffected. The low-trigger group associated to a higher rate of death or major vascular complications (19/29 vs 8/29; hazard ratio, 3.20; P = .006) and fewer days alive outside the hospital within 90 days (median [IQR], 76 [67-82] vs 82 [76-84] days; P = .049). In conclusion, a perioperative protocol restricting RBC transfusion successfully separated hemoglobin levels and RBC units transfused. Exploratory outcomes suggested potential harm with the low-trigger group and warrant further trials before such a strategy is universally adopted. This trial was registered at www.clinicaltrials.gov as #NCT02465125.

The impact of health-related quality of life and depressive symptoms on blood donor career-Results from the Danish blood donor study.

BACKGROUND: Blood donors report better health-related quality of life (HRQL) than non-donors. Likewise, donors reporting good health are less likely to stop donating and have a higher donation frequency. This is evidence of the healthy donor effect (HDE). This study is the first to investigate the impact of HRQL and depressive symptoms on subsequent donor career. STUDY DESIGN AND METHODS: Prospective cohort study includes 102,065 participants from the Danish Blood Donor Study applying the 12-item short-form health survey (SF-12) measuring a mental (MCS) and a physical component score (PCS) and the Major Depression Inventory (MDI). Poisson and Cox regression models were used to assess the effect of SF-12 and MDI scores on donation frequency and donor cessation. Higher MCS/PCS scores indicate good HRQL, while higher MDI score indicates higher experience of depressive symptoms. RESULTS: For both sexes, MCS was positively correlated with donation frequency for up to 5 years, and similarly for PCS among women. A negative correlation between MDI score and donation frequency in the year following assessment was observed only among men. No correlation was observed among women. An increase in both MCS and PCS was associated with a lower risk of donation cessation in both sexes, while an increase in MDI score was only associated with an increased risk of donation cessation in men. CONCLUSION: MCS, PCS, and MDI score affect donor career. Thus, adjusting for donation frequency may reduce HDE-bias in donor health research. However, because of the small effect sizes, other ways of quantifying HDE may be beneficial.

Risk of Hidradenitis Suppurativa Comorbidities Over Time: A Prospective Cohort Study of Danish Blood Donors.

Hidradenitis suppurativa is a common recurrent inflammatory skin disease. It is associated with multiple comorbidities whose temporal relationships are unknown due to long diagnostic delays. This study of otherwise healthy blood donors with self-reported symptoms of hidradenitis suppurativa investigated the temporal relationships of comorbidities. A prospective survival analysis on a nationwide cohort of blood donors, using registry data on drug prescription, was used to calculate the hazard ratio of time until first prescription of medical treatment for the following hidradenitis suppurativa-related comorbidities: heart disease, diabetes, depression, thyroid disease and pain. Hidradenitis suppurativa status was determined by a validated questionnaire, and the survival analysis was adjusted for age, sex, body mass index, smoking status and having an International Classification of Diseases Version 10 (ICD-10) diagnosis of hidradenitis suppurativa. Of the participants, 1,012 reported hidradenitis suppurativa symptoms, and these symptoms increased the hazard ratio of antidepressants (1.73, 95% confidence interval 1.17-2.56, p ≈ 0.006) and analgesics (hazard ratio 1.24, 95% confidence interval 1.11-1.39, p < 0.001). Pain and depression are the first comorbidities to present in hidradenitis suppurativa pathogenesis.

Epidemiology of Hyperhidrosis in Danish Blood Donors.

The risk factors and disease implications of hyper-hidrosis are unknown. The objectives of this retrospective cohort study were to estimate the prevalence of hyperhidrosis and to compare demographic, life-style, and socioeconomic parameters in blood donors with and without self-reported or hospital-diagnosed hyperhidrosis. The study included blood donors from the Danish Blood Donor Study for the period 2010-2019. Registry data were collected from Statistics Denmark. Overall, 2,794 of 30,808 blood donors (9.07%; 95% confidence interval (95% CI) 8.75-9.40) had self- reported hyperhidrosis and 284 of 122,225 (0.23%; 95% CI 0.21-0.26) had hospital-diagnosed hyperhidrosis. Self-reported hyperhidrosis was associated with smoking (odds ratio (OR) 1.17; 95% CI 1.05-1.31), overweight (OR 1.72; 95% CI 1.58-1.87), "unemployed" (OR 1.60; 95% CI 1.24-2.08), "short education" (OR 0.76; 95% CI 0.64-0.90), and lower income (beta-coefficient -26,121; 95% CI -37,931, -14,311). Hospital-diagnosed hyperhidrosis did not differ from controls. Thus, self-reported hyperhidrosis was associated with potential hyperhidrosis risk factors (smoking, overweight) and disease implications (unemployment, low education level and income).

Effect of low vs high haemoglobin transfusion trigger on cardiac output in patients undergoing elective vascular surgery: Post-hoc analysis of a randomized trial.

BACKGROUND: During vascular surgery, restricted red-cell transfusion reduces frontal lobe oxygen (ScO2 ) saturation as determined by near-infrared spectroscopy. We evaluated whether inadequate increase in cardiac output (CO) following haemodilution explains reduction in ScO2 . METHODS: This is a post-hoc analysis of data from the Transfusion in Vascular surgery (TV) Trial where patients were randomized on haemoglobin drop below 9.7 g/dL to red-cell transfusion at haemoglobin below 8.0 (low-trigger) vs 9.7 g/dL (high-trigger). Fluid administration was guided by optimizing stroke volume. We compared mean intraoperative levels of CO, haemoglobin, oxygen delivery, and CO at nadir ScO2 with linear regression adjusted for age, operation type and baseline. Data for 46 patients randomized before end of surgery were included for analysis. RESULTS: The low-trigger resulted in a 7.1% lower mean intraoperative haemoglobin level (mean difference, -0.74 g/dL; P < .001) and reduced volume of red-cell transfused (median [inter-quartile range], 0 [0-300] vs 450 mL [300-675]; P < .001) compared with the high-trigger group. Mean CO during surgery was numerically 7.3% higher in the low-trigger compared with the high-trigger group (mean difference, 0.36 L/min; 95% confidence interval (CI.95), -0.05 to 0.78; P = .092; n = 42). At the nadir ScO2 -level, CO was 11.9% higher in the low-trigger group (mean difference, 0.58 L/min; CI.95, 0.10-1.07; P = .024). No difference in oxygen delivery was detected between trial groups (MD, 1.39 dLO2 /min; CI.95, -6.16 to 8.93; P = .721). CONCLUSION: Vascular surgical patients exposed to restrictive RBC transfusion elicit the expected increase in CO making it unlikely that their potentially limited cardiac capacity explains the associated ScO2 decrease.