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.

Exploring TNFi drug-levels and anti-drug antibodies during tapering among patients with inflammatory arthritis: secondary analyses from the randomised BIODOPT trial.

To evaluate tumour necrosis factor inhibitor (TNFi) drug-levels and presence of anti-drug antibodies (ADAb) in patients with inflammatory arthritis who taper TNFi compared to TNFi continuation. Patients with rheumatoid arthritis, psoriatic arthritis, or axial spondyloarthritis on stable TNFi dose and in low disease activity ≥ 12 months were randomised (2:1) to disease activity-guided tapering or control. Blood samples at baseline, 12- and 18-months were evaluated for TNFi drug-levels and ADAb. In total, 129 patients were randomised to tapering (n = 88) or control (n = 41). Between baseline and month 18, a significant shift in TNFi drug-levels were observed in the tapering group resulting in fewer patients with high drug-levels (change: - 14% [95% CI - 27 to - 1%]) and more with low drug-levels (change: 18% [95% CI 5-31%]). Disease activity was equivalent between groups at 18 months, mean difference: RA - 0.06 (95% CI - 0.44 to 0.33), PsA 0.03 (95% CI - 0.36 to 0.42), and axSpA 0.16 (- 0.17 to 0.49), equivalence margins ± 0.5 disease activity points. ADAb were detected in eight patients, all from the tapering group. TNFi drug-level category or ADAb were not predictive for achieving successful tapering at 18 months. TNFi drug-levels decreased during tapering which indicate adherence to the tapering algorithm. Despite the difference in TNFi drug-levels at 18 months, disease activity remained equivalent, and only few tapering patients had detectable ADAb. These data do not support using TNFi drug-level and/or ADAb to guide the tapering decision but future research with larger trials is needed.Trial registration: EudraCT: 2017-001970-41, December 21, 2017.

Genome-wide meta-analyses of restless legs syndrome yield insights into genetic architecture, disease biology and risk prediction.

Restless legs syndrome (RLS) affects up to 10% of older adults. Their healthcare is impeded by delayed diagnosis and insufficient treatment. To advance disease prediction and find new entry points for therapy, we performed meta-analyses of genome-wide association studies in 116,647 individuals with RLS (cases) and 1,546,466 controls of European ancestry. The pooled analysis increased the number of risk loci eightfold to 164, including three on chromosome X. Sex-specific meta-analyses revealed largely overlapping genetic predispositions of the sexes (rg = 0.96). Locus annotation prioritized druggable genes such as glutamate receptors 1 and 4, and Mendelian randomization indicated RLS as a causal risk factor for diabetes. Machine learning approaches combining genetic and nongenetic information performed best in risk prediction (area under the curve (AUC) = 0.82-0.91). In summary, we identified targets for drug development and repurposing, prioritized potential causal relationships between RLS and relevant comorbidities and risk factors for follow-up and provided evidence that nonlinear interactions are likely relevant to RLS risk prediction.

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.

Rare variants with large effects provide functional insights into the pathology of migraine subtypes, with and without aura.

Migraine is a complex neurovascular disease with a range of severity and symptoms, yet mostly studied as one phenotype in genome-wide association studies (GWAS). Here we combine large GWAS datasets from six European populations to study the main migraine subtypes, migraine with aura (MA) and migraine without aura (MO). We identified four new MA-associated variants (in PRRT2, PALMD, ABO and LRRK2) and classified 13 MO-associated variants. Rare variants with large effects highlight three genes. A rare frameshift variant in brain-expressed PRRT2 confers large risk of MA and epilepsy, but not MO. A burden test of rare loss-of-function variants in SCN11A, encoding a neuron-expressed sodium channel with a key role in pain sensation, shows strong protection against migraine. Finally, a rare variant with cis-regulatory effects on KCNK5 confers large protection against migraine and brain aneurysms. Our findings offer new insights with therapeutic potential into the complex biology of migraine and its subtypes.

Population-Based Characterization of Menstrual Migraine and Proposed Diagnostic Criteria.

Importance: There is a need for better recognition and more extensive research into menstrual migraine (MM) in the general population, and a revision of the diagnostic criteria for MM is warranted to move the field forward. Increased understanding of MM is crucial for improving clinical care, diagnosis, and therapy for MM. Objectives: To assess the clinical characteristics of MM, including severity and treatment response, and to propose new diagnostic criteria for pure MM and menstrually related migraine. Design, Setting, and Participants: This is a case-control study of Danish individuals with migraine. All individuals completed a 105-item validated diagnostic migraine questionnaire, sent via the Danish electronic mailing system (e-Boks) between May and August 2020, allowing diagnosis of pure MM and menstrually related migraine by the International Classification of Headache Disorders, Third Edition (ICHD-3). Data analysis was performed from September 2021 to November 2022. Exposure: Diagnosis of migraine. Main Outcomes and Measures: Clinical characteristics of women with MM and women with nonmenstrual migraine (non-MM) were compared using the ICHD-3 diagnostic criteria. A simulation of the risk of randomly misclassifying MM was based on number of migraine attacks during 3 menstrual cycles (3 × 28 days), and simulation analyses were performed using 100 000 permutations of random migraine attacks in migraine patients. Results: A total of 12 618 individuals, including 9184 women, with migraine participated in the study. Among the women with migraine, the prevalence of MM was 16.6% (1532 women), and the prevalence of non-MM was 45.9% (4216 women). The mean (SD) age was 38.7 (8.7) years for women with MM and 37.0 (9.2) years for women with non-MM. Of the 1532 women with MM, 410 (26.8%) fulfilled ICHD-3 diagnostic criteria for pure MM, 1037 (67.7%) fulfilled ICHD-3 diagnostic criteria for menstrually related migraine, and 152 (9.9%) fulfilled proposed diagnostic criteria for rare pure MM. MM was associated with a higher frequency of migraine-accompanying symptoms (odds ratio [OR], 1.98; 95% CI, 1.71-2.29), more frequent (OR, 7.21; 95% CI, 5.77-9.03) and more severe (OR, 1.17; 95% CI, 1.13-1.21) migraine attacks, lower frequency of nonmigraine headache (OR, 0.31; 95% CI, 0.18-0.49), an overall greater response to treatment with triptans (OR, 1.66; 95% CI, 1.24-2.24), better improvement of migraine attacks during late pregnancy (OR, 5.10; 95% CI, 2.17-14.00), and faster reappearance of migraine attacks post partum (OR, 3.19; 95% CI, 2.40-4.25). Hormonal contraceptive-related MM was associated with a higher prevalence of migraine without aura than migraine related to spontaneous menstruation (OR, 1.82; 95% CI, 1.62-2.06). Otherwise, no differences between hormonal and spontaneous MM were observed. The risk of random diagnostic misclassification of ICHD-3 menstrually related migraine in women with high frequency episodic migraine was 43%. This risk was reduced to 3% when applying the proposed criteria for menstrually related migraine. Conclusions and Relevance: In this case-control study, MM in the general population had clinical characteristics that were quantitively different from those of non-MM. Detailed descriptive data and suggested improved diagnostic criteria for pure MM and menstrually related migraine were provided.

Combining sCD163 with CA 19-9 Increases the Predictiveness of Pancreatic Ductal Adenocarcinoma.

The objective of this study was to evaluate the diagnostic and prognostic potential of soluble CD163 (sCD163) in patients with pancreatic ductal adenocarcinoma (PDAC). Preoperative serum samples from 255 patients with PDAC were analyzed for sCD163 using a commercially available enzyme-linked immunosorbent assay. The diagnostic value of sCD163 was evaluated using receiver operating characteristic (ROC) curves. The prognostic significance of sCD163 was evaluated by Cox regression analysis and Kaplan-Meier survival curves. sCD163 was significantly increased in patients with PDAC, across all stages, compared to healthy subjects (stage 1: p value = 0.033; stage 2-4: p value ≤ 0.0001). ROC curves showed that sCD163 combined with CA 19-9 had the highest diagnostic potential compared to sCD163 and CA 19-9 alone both in patients with local PDAC and patients with advanced PDAC. Univariate and multivariate analysis showed no association between sCD163 and overall survival. This study found elevated levels of circulating sCD163 in patients with PDAC, regardless of stage, compared to healthy subjects. This suggests that sCD163 may have a clinical value as a novel diagnostic biomarker in PDAC.

Smoking is associated with infection risk in healthy blood donors.

OBJECTIVES: There is a gap in knowledge about the effects of smoking on overall infection risk in otherwise healthy populations, possibly leading to underestimation of the dangers of smoking. The present study aimed to examine the association of smoking with the risk of infections in a large cohort of healthy blood donors. METHODS: This cohort study used questionnaire and health register data from 127 831 Danish blood donors. Multivariable Cox proportional hazards analysis was applied to estimate the association of current smoking with the risk of all-cause infection defined as hospital-based treatment for infection or filled prescriptions of antimicrobials stratified for age and adjusted for relevant confounders. RESULTS: Among 18 272 current smokers, 12 272 filled an antimicrobial prescription and 2035 received hospital-based treatment for infections. Among 101 974 non-smokers, 65 117 filled a prescription and 8501 received hospital-based treatment for infections. Smokers had a higher risk of all-cause infection than non-smokers (hazard ratio estimates were 1.27 in males and 1.33 in females for hospital-based treatment and 1.11 in males and up to 1.20 in females for filled prescriptions). Smoking was most strongly associated with an increased incidence of respiratory tract infection, abscesses, skin infection, and prescriptions for these ailments (hazard ratio up to 2.29). Furthermore, smokers' risk of filled prescriptions of broad-spectrum penicillin was increased (hazard ratio up to 1.96). CONCLUSIONS: Current smoking was strongly associated with the risk of hospital-based treatment of infection and filled prescriptions of antimicrobials in a large cohort of healthy individuals. These findings warrant an increased focus on infectious disease risk among smokers.

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.

Prevalence of major depressive disorder in 51,658 otherwise healthy adult Danes: Sex differences in symptomatology and prediction of future anti-depressive medication.

Major Depressive Disorder (MDD) is a heterogeneous disease, which displays sex differences in symptomatology. This study aimed to assess point prevalence of MDD in undiagnosed, healthy adults as well as sex differences in symptomatology and clarify if specific symptoms increased the later need for anti-depressive medication. The study included 51,658 blood donors. Depressive symptoms were assessed according to ICD-10 using the Major Depression Inventory. Demographics, previous MDD, anti-depressive medication were collected from questionnaires and population registers. Descriptive, Logistic and Cox regression analyses were conducted. In total, 1.15% participants met the criteria for MDD. Women were significantly more likely to experience "increased appetite" and less likely to experience "a feeling of life not worth living", compared to men. MDD significantly associated with an increased hazard of later receiving a prescription for anti-depressive medication. The risk increased proportionally with increasing MDD severity. The two symptoms, "feeling that life is not worth living" and "trouble sleeping" were the strongest individual predictive symptoms of future anti-depressive medication in women and men, respectively. The results confirm findings in MDD patient groups. The diagnostic and prognostic value should be investigated further to address their potential as part of the clinical assessment.

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.

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.

Hyperhidrosis and the risk of being treated for skin infections.

BACKGROUND: A few studies have described an increased prevalence of skin infections in individuals with hyperhidrosis compared to others. However, it remains uncertain whether hyperhidrosis is an independent risk factor for skin infections. OBJECTIVE: To compare the risk of skin infections in individuals with and without hyperhidrosis. METHODS: In this retrospective cohort study, data on hyperhidrosis were collected from the Danish Blood Donor Study. Blood donors included in 2010-2019 were followed from inclusion until December 2019. Data on redeemed prescriptions against skin infections were collected from the National Prescription Register. The intensity of prescription-use by hyperhidrosis status was assessed in Andersen-Gill models. RESULTS: Overall, 4,176 (9.6%) of 43,477 blood donors had self-reported hyperhidrosis and 437 (0.34%) of 127,823 blood donors had hospital diagnosed hyperhidrosis. Self-reported hyperhidrosis was associated with the use of antibiotic prescriptions (adjusted hazard ratio = 1.21; 95% confidence interval 1.00-1.45, p = 0.047). Hospital diagnosed hyperhidrosis was associated with the use of antibiotic (adjusted hazard ratio = 1.33; 95% confidence interval 1.03-1.68, p = 0.028) and topical antifungal prescriptions (adjusted hazard ratio = 1.43; 95% confidence interval 1.04-1.97, p = 0.027). CONCLUSIONS: Hyperhidrosis is associated with the use of prescriptions for antibiotics and topical antifungals. This suggests a clinically relevant association between hyperhidrosis and skin infections.

A life course approach to understanding associations between natural environments and mental well-being for the Danish blood donor cohort.

Natural environments have been associated with mental health benefits, but globally access to these benefits is threatened by urban development and densification. However, it remains unclear how natural environments relate to mental health and how consistent the association is across populations. Here we use a life-course approach with a population consisting of 66 194 individuals from the Danish Blood Donor Study (DBDS) to investigate the association between green and blue space (e.g. parks and lakes) and self-evaluated mental well-being. Green and blue space was identified from remotely-sensed images from the Landsat program, while mental well-being was based on the mental component score (MCS) calculated using the 12-item short form health survey. We use multivariate linear regression models and logistic regression models to quantify the associations. We adjust for additional environmental (urbanization, and air pollution) and lifestyle factors (smoking, body mass index, socioeconomic status, and physical activity) and specifically evaluate the role of physical activity and air pollution as possible mediating factors. We found a positive association between the MCS and current and childhood green space, and a non-significant association for current and childhood blue space. Adjusting for environmental and the other factors attenuated the effect sizes indicating that a broad range of factors determine mental well-being. Physical activity and air pollution were both associated with the MCS as possible mediators of green space associations. In addition, the odds for successfully completing tasks', seeing others, and feeling less downhearted increased with higher levels of green space, and the odds of feeling calm increased with higher levels of blue space. In conclusion, we found support for an association between green and, to less degree, blue space and mental well-being throughout different life stages. In addition, we found a positive association with individual indicators of mental well-being such as being productive, feeling less downhearted and calmer, and being social. The healthy blood donor effect and the bias towards urban residency may explain why we found smaller effect sizes between green and blue space and mental well-being for this generally healthy and resourceful cohort compared to previous studies.

Impact of COVID-19 Pandemic on Sleep Quality, Stress Level and Health-Related Quality of Life-A Large Prospective Cohort Study on Adult Danes.

The everyday lives of Danish inhabitants have been affected by the COVID-19 pandemic, e.g., by social distancing, which was employed by the government in March 2020 to prevent the spread of SARS-CoV-2. Moreover, the pandemic has entailed economic consequences for many people. This study aims to assess changes in physical and mental health-related quality of life (MCS, PCS), in stress levels, and quality of sleep during the COVID-19 pandemic and to identify factors that impact such changes, using a prospective national cohort study including 26,453 participants from the Danish Blood Donor Study who answered a health questionnaire before the pandemic and during the pandemic. Descriptive statistics, multivariable linear and multinomial logistic regression analyses were applied. A worsening of MCS and quality of sleep was found, and an overall decrease in stress levels was observed. PCS was decreased in men and slightly increased in women. The extent of health changes was mainly affected by changes in job situation, type of job, previous use of anti-depressive medication and the participants' level of personal stamina. Thus, living under the unusual circumstances that persisted during the COVID-19 pandemic has had a negative impact on the health of the general population. This may, in time, constitute a public health problem.

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.

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).