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BACKGROUND: The emerging use of biomarkers in research and tailored care introduces a need for information about the association between biomarkers and basic demographics and lifestyle factors revealing expectable concentrations in healthy individuals while considering general demographic differences. METHODS: A selection of 47 biomarkers, including markers of inflammation and vascular stress, were measured in plasma samples from 9876 Danish Blood Donor Study participants. Using regression models, we examined the association between biomarkers and sex, age, Body Mass Index (BMI), and smoking. RESULTS: Here we show that concentrations of inflammation and vascular stress biomarkers generally increase with higher age, BMI, and smoking. Sex-specific effects are observed for multiple biomarkers. CONCLUSION: This study provides comprehensive information on concentrations of 47 plasma biomarkers in healthy individuals. The study emphasizes that knowledge about biomarker concentrations in healthy individuals is critical for improved understanding of disease pathology and for tailored care and decision support tools.
Blood-based biomarkers are circulating molecules that can help to indicate health or disease. Biomarker levels may vary depending on demographic and lifestyle factors such as age, sex, smoking status, and body mass index. Here, we examine the effects of these demographic and lifestyle factors on levels of biomarkers related to activation of the immune system and cardiovascular stress. Measurements of 47 different proteins were performed on blood samples from nearly 10,000 healthy Danish blood donors. Measurement data were linked with questionnaire data to assess effects of lifestyle. We found that immune activation and vascular stress generally increased with age, BMI, and smoking. As these measurements are from healthy blood donors they can serve as a reference for expectable effects and inflammation levels in healthy individuals. Knowledge about the healthy state is important for understanding disease progression and optimizing care.
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Background: Introduction of the Omicron variant caused a steep rise in SARS-CoV-2 infections despite high vaccination coverage in the Danish population. We used blood donor serosurveillance to estimate the percentage of recently infected residents in the similarly aged background population with no known comorbidity. Methods: To detect SARS-CoV-2 antibodies induced due to recent infection, and not vaccination, we assessed anti-nucleocapsid (anti-N) immunoglobulin G (IgG) in blood donor samples. Individual level data on SARS-CoV-2 RT-PCR results and vaccination status were available. Anti-N IgG was measured fortnightly from January 18 to April 3, 2022. Samples from November 2021 were analysed to assess seroprevalence before introduction of the Omicron variant in Denmark. Findings: A total of 43 088 donations from 35 309 Danish blood donors aged 17-72 years were screened. In November 2021, 1·2% (103/8 701) of donors had detectable anti-N IgG antibodies. Adjusting for test sensitivity (estimates ranging from 74%-81%) and November seroprevalence, we estimate that 66% (95% confidence intervals (CI): 63%-70%) of the healthy, similarly aged Danish population had been infected between November 1, 2021, and March 15, 2022. One third of infections were not captured by SARS-CoV-2 RT-PCR testing. The infection fatality rate (IFR) was 6·2 (CI: 5·1-7·5) per 100 000 infections. Interpretation: Screening for anti-N IgG and linkage to national registers allowed us to detect recent infections and accurately assess assay sensitivity in vaccinated or previously infected individuals during the Omicron outbreak. The IFR was lower than during previous waves. Funding: The Danish Ministry of Health.
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An amendment to this paper has been published and can be accessed via a link at the top of the paper.
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Transcriptional characterization and classification has potential to resolve the inter-tumor heterogeneity of colorectal cancer and improve patient management. Yet, robust transcriptional profiling is difficult using formalin-fixed, paraffin-embedded (FFPE) samples, which complicates testing in clinical and archival material. We present MethCORR, an approach that allows uniform molecular characterization and classification of fresh-frozen and FFPE samples. MethCORR identifies genome-wide correlations between RNA expression and DNA methylation in fresh-frozen samples. This information is used to infer gene expression information in FFPE samples from their methylation profiles. MethCORR is here applied to methylation profiles from 877 fresh-frozen/FFPE samples and comparative analysis identifies the same two subtypes in four independent cohorts. Furthermore, subtype-specific prognostic biomarkers that better predicts relapse-free survival (HR = 2.66, 95%CI [1.67-4.22], P value < 0.001 (log-rank test)) than UICC tumor, node, metastasis (TNM) staging and microsatellite instability status are identified and validated using DNA methylation-specific PCR. The MethCORR approach is general, and may be similarly successful for other cancer types.