Maria Didriksen

Background: Blood donation causes iron loss and increases the risk of non‐anemic iron deficiency (NAID), which is not detected by hemoglobin screening alone. Evidence linking NAID to fatigue and insomnia symptoms in healthy blood donors remains limited and inconsistent. We aimed to investigate these associations in a large cohort of Danish blood donors. Study design and methods: This cross‐sectional study used data from the Danish Blood Donor Study collected from May 2015 to January 2025. Donors with both a ferritin measurement and questionnaire data on fatigue and insomnia within 90 days of the measurement were included. NAID was defined as ferritin <15 μg/L with normal hemoglobin level. Sex‐stratified multivariable logistic regression models were adjusted for age, body mass index, smoking status, region, and donation history. Ferritin was also modeled continuously using linear spline regression. Results: Among 59,668 donors, NAID was present in 9.5% of women and 2.0% of men. NAID was associated with fatigue among women (OR 1.22, 95% CI 1.06–1.40) and insomnia symptoms among men (OR 1.26, 95% CI 1.03–1.53). Continuous analyses suggested that lower ferritin concentrations were associated with higher odds of fatigue in both sexes and higher odds of insomnia symptoms in men. Conclusion: Low iron stores in non‐anemic blood donors were associated with fatigue in women and insomnia symptoms in men. These findings suggest that hemoglobin screening alone may be insufficient to identify donors with symptomatic iron depletion and support consideration of ferritin monitoring as part of donor health strategies.

Anti-cytokine autoantibodies are increasingly recognized as modulators of immune function and determinants of disease risk, yet their genetic basis and population-level impact remain unclear. Here we perform genome-wide association studies of autoantibodies against IL-1α, IL-6, IL-10, IFN-α, IFN-β, IFN-γ and GM-CSF in 15,000 individuals from the Danish Blood Donor Study. We identify 52 genome-wide significant loci, implicating genes enriched in antigen-presentation pathways. Using these data, we derive cytokine-specific polygenic risk scores and evaluate their associations across 300,000 individuals in the Copenhagen Hospital Biobank. Genetic predisposition to IL-1α autoantibodies is associated with reduced risk of rheumatoid arthritis and certain cancers, whereas genetic predisposition to IL-6 autoantibodies is associated with increased risk of diabetes, mirroring prior clinical observations. These findings define the genetic architecture of anti-cytokine autoantibodies and indicate their divergent effects on human disease risk at population scale, providing a framework for mechanistic investigation and potential clinical stratification.

Fibromyalgia is a common and debilitating chronic pain syndrome of poorly understood etiology. Here we conduct a multi-ancestry genome-wide association study meta-analysis across 2,563,755 individuals (54,629 cases and 2,509,126 controls) from 11 cohorts, identifying 26 risk loci for fibromyalgia. The strongest association was with a coding variant in HTT , the causal gene for Huntington’s disease. Gene prioritization implicated the HTT regulator GPR52 , as well as diverse genes with neural roles, including DCC , DRD2 / NCAM1 , MDGA2 and CELF4 . Fibromyalgia heritability was exclusively enriched within brain tissues and neural cell types. Fibromyalgia showed strong, positive genetic correlation with a wide range of chronic pain, psychiatric and somatic disorders, including genetic correlations above 0.7 with low back pain, post-traumatic stress disorder and irritable bowel syndrome. Despite large sex differences in fibromyalgia prevalence, the genetic architecture of fibromyalgia was nearly identical between males and females. This study provides robust genetic evidence defining fibromyalgia as a central nervous system disorder, thereby establishing a biological framework for its complex pathophysiology and extensive clinical comorbidities.

Background: Pre-existing psychiatric disorders have been associated with the severity of acute respiratory infections, including COVID-19, particularly in hospitalized populations. However, the underlying mechanisms, especially in community-based populations, remain unknown, limiting preparedness for future pandemics. We investigated the role of genetic liability for psychiatric disorders and related traits in COVID-19 and other respiratory infection severity among individuals reporting SARS-CoV-2 testing and available respiratory symptom data. Methods: We included population-based cohort data from Denmark, Estonia, Iceland, Norway, and the United Kingdom (N = 78,507; 62% female; 41% SARS-CoV-2-positive; May 2020—March 2023). Respiratory infection severity was defined by self-reported days bedridden and an eleven-symptom composite score during the acute illness phase. Polygenic scores (PGSs) for eight psychiatric disorders and the personality trait neuroticism indexed genetic liability. Meta-analysed estimates from stepwise-adjusted regression analyses controlling for education, lifestyle, and psychiatric and somatic diagnosis history were used to assess associations between PGSs and acute respiratory infection severity, stratified by COVID-19 status. Results: Higher genetic liability to insomnia, major depression (MD), and neuroticism was consistently associated with longer time bedridden (relative risk ratios per 1 SD change in PGS: 1.07–1.14, 95% confidence intervals [CIs]: 1.03–1.21) and more symptoms (incident rate ratios [IRRs]: 1.02–1.04, 95% CIs: 1.01–1.05) due to COVID-19. PGSs for insomnia, MD, neuroticism, anxiety disorder, bipolar disorder, and schizophrenia were also linked to higher non-COVID-19 symptom count (IRRs: 1.01–1.05, 95% CIs: 1.00–1.07). These associations remained robust after adjustment for lifestyle, education and medical comorbidities. Individuals in the highest MD PGS decile reported 20% more symptoms in non-COVID-19 illness and 10% more in COVID-19 compared with the bottom decile. No consistent associations were detected with attention-deficit/hyperactivity disorder, alcohol dependence and post-traumatic stress disorder. No genetic link was observed with ischaemic heart disease or type 2 diabetes. Conclusions: Shared genetics may contribute to the link between psychiatric conditions and respiratory infection severity in community settings. Our results underscore the role of psychiatric genetic liability, beyond diagnosed psychiatric disorders, in contributing to both COVID-19 and other respiratory infection severity. These findings provide insights that may improve future risk stratification and public health strategies targeting respiratory viruses.

Borderline personality disorder (BPD) is a severe mental health condition influenced by environmental risk factors (for example, interpersonal trauma) and genetic factors. We conducted the largest genome-wide association study (GWAS) meta-analysis of BPD so far, with a discovery sample of 12,339 cases and 1,041,717 controls, and a replication study of 685 cases and 107,750 controls (all participants of European ancestry). We identified 11 independent associated genomic loci and 9 risk genes in gene-based analyses. We observed a single-nucleotide polymorphism heritability of 17.3% and derived polygenic scores (PGS) that predicted 4.6% of the phenotypic variance in BPD on the liability scale. BPD showed the strongest positive genetic correlations with GWAS of post-traumatic stress disorder, depression, attention deficit hyperactivity disorder, antisocial behavior, and measures of suicide and self-harm. Phenome-wide analyses in Vanderbilt University Medical Center Biobank and UK Biobank using BPD-PGS confirmed these associations and also identified associations with other medical conditions, including obstructive pulmonary disease and diabetes. These analyses highlight BPD as a polygenic disorder, with the genetic risk showing substantial overlap with psychiatric and physical health conditions.

Aims: Obesity is a major risk factor for hypertension, but most evidence relies on single weight measurements. We examined associations between weight change and short-term risk of incident hypertension across body mass index (BMI) categories. Methods and results: We conducted a retrospective cohort study in the Danish Blood Donor Study of 81 954 participants aged 18–79 with at least two questionnaires (2010–2025). Weight change was the percentage difference between consecutive self-reported weights, grouped as stable, 2.5–5, 5–10, or more than 10% loss or gain. Incident hypertension was defined as first redemption of antihypertensive drugs. Associations were estimated using multivariable Cox models. During a median follow-up of 1.66 years (IQR 0.79–2.88; maximum 3 years), 5503 participants initiated antihypertensive treatment. In BMI-stratified analyses, weight gain was associated with higher risk of initiation in all BMI categories, while weight loss was associated with lower risk only in overweight or obesity relative to stable weight. Across BMI categories using stable normal weight as reference, associations were stronger at higher BMI. More than 10% weight gain was associated with hazard ratios of 1.60 (95% CI 1.30–1.96) in normal weight, 2.44 (2.02–2.96) in overweight and 4.51 (3.57–5.70) in obesity. Hazard ratios were comparable across sex and age groups, although higher in younger men with obesity, while rates were highest in older participants. Conclusion: Weight gain was associated with higher risk of antihypertensive treatment across BMI categories compared with stable weight, whereas weight loss was inversely associated with initiation among adults with overweight or obesity.

Hormonal contraceptive (HC) use is known to be associated with elevated CRP levels. However, evidence on the effect of HC on several circulating inflammatory biomarkers in healthy humans is limited. The aim of this study was to examine the association between hormonal contraceptives and circulating biomarker levels and differential cell counts. A cross‐sectional observational study design with biomarker measurements from 4,160 healthy females was used, coupled with registered HC prescriptions. We compared 752 high and low dose combined oral contraceptive (COC) users, 77 progestin‐only pill users, 417 levonorgestrel intrauterine device users, 65 hormonal therapy users, and 1,523 post‐menopausal women with a control group of 1,326 women below 50 years. Repeated differential cell counts from a different dataset of 16,231 females were analyzed for the effects of HC. Data were analyzed using various regression models. COC use was associated with higher vascular marker levels but lower chemokine levels. We found no association with progestin‐only use. The association with differential cell counts was limited for most HC types. This study emphasizes the widespread impact of HC on the immune and vascular systems and how the impact may differ between HC types. The biomarker associations found could be targets for elucidation in functional studies.

A bstract: Selective participation in biobanks often compromises inference to the general population, particularly when selection occurs across multiple stages, whether at recruitment or during subsequent participation. Inverse probability (IP) weighting can reduce systematic differences using suitable external benchmarks, but most applications assume a single selection process. Here, we present a multi-stage IP-weighting framework and apply it to the Danish Blood Donor Study (DBDS), a nationwide biobank embedded in Denmark’s blood-donation infrastructure. Using national registers, we estimated year-specific probabilities of (i) donation activity and (ii) DBDS enrolment conditional on donation activity, yielding two-stage inclusion weights for 169,893 participants. These weights reduced inclusion-associated imbalance across the 52 auxiliary variables in the probability models by 97.6% (median) and, despite strong health selection under donation-based recruitment, reduced relative-prevalence discrepancies across held-out prescription phenotypes by 69.7% (median). The effective sample size after weighting was 30,627 (18.0% of 169,893). Combining the inclusion weights with questionnaire-specific response weights across five DBDS questionnaires (>500 questions) produced the largest changes from unweighted to weighted responses for health behaviours and symptom severity, including tobacco and alcohol consumption, menstrual-pain severity, restless-legs severity, nocturia, sleep disturbance, and fatigue. These findings support multi-stage IP-weighting to improve population alignment in biobanks with staged selection.

The host genetics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have previously been studied based on cases from the earlier waves of the pandemic in 2020 and 2021, identifying 51 genomic loci associated with infection and/or severity. SARS-CoV-2 has shown rapid sequence evolution, increasing transmissibility, particularly for Omicron variants, which raises the question of whether this affected the host genetic factors. We performed a genome-wide association study of SARS-CoV-2 infection with Omicron variants, including more than 150,000 cases from four cohorts. We identified 13 genome-wide significant loci, of which only five were previously described as associated with SARS-CoV-2 infection. The strongest signal was a single nucleotide polymorphism in an intron of ST6GAL1, a gene affecting immune development and function, connected to three other associated loci (harboring MUC1, MUC5AC and MUC16) through O-glycan biosynthesis. Our study provides robust evidence for individual genetic variation related to glycosylation, translating into susceptibility to SARS-CoV-2 infections with Omicron variants.