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- Barregård, Lars, 1948, et al.
(author)
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Human and Methodological Sources of Variability in the Measurement of Urinary 8-Oxo-7,8-dihydro-2 '-deoxyguanosine
- 2013
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In: Antioxidants and Redox Signaling. - : Mary Ann Liebert Inc. - 1523-0864 .- 1557-7716. ; 18:18, s. 2377-2391
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Journal article (peer-reviewed)abstract
- Aims: Urinary 8-oxo-7,8-dihydro-2'-deoxyguanosine (8-oxodG) is a widely used biomarker of oxidative stress. However, variability between chromatographic and ELISA methods hampers interpretation of data, and this variability may increase should urine composition differ between individuals, leading to assay interference. Furthermore, optimal urine sampling conditions are not well defined. We performed inter-laboratory comparisons of 8-oxodG measurement between mass spectrometric-, electrochemical- and ELISA-based methods, using common within-technique calibrants to analyze 8-oxodG-spiked phosphate-buffered saline and urine samples. We also investigated human subject- and sample collection-related variables, as potential sources of variability. Results: Chromatographic assays showed high agreement across urines from different subjects, whereas ELISAs showed far more inter-laboratory variation and generally overestimated levels, compared to the chromatographic assays. Excretion rates in timed 'spot' samples showed strong correlations with 24 h excretion (the 'gold' standard) of urinary 8-oxodG (r(p) 0.67-0.90), although the associations were weaker for 8-oxodG adjusted for creatinine or specific gravity (SG). The within-individual excretion of 8-oxodG varied only moderately between days (CV 17% for 24 h excretion and 20% for first void, creatinine-corrected samples). Innovation: This is the first comprehensive study of both human and methodological factors influencing 8-oxodG measurement, providing key information for future studies with this important biomarker. Conclusion: ELISA variability is greater than chromatographic assay variability, and cannot determine absolute levels of 8-oxodG. Use of standardized calibrants greatly improves intra-technique agreement and, for the chromatographic assays, importantly allows integration of results for pooled analyses. If 24 h samples are not feasible, creatinine- or SG-adjusted first morning samples are recommended.
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| 6. |
- Lofgren, P, et al.
(author)
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Secretion of tumor necrosis factor-alpha shows a strong relationship to insulin-stimulated glucose transport in human adipose tissue
- 2000
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In: Diabetes. - : American Diabetes Association. - 0012-1797 .- 1939-327X. ; 49:5, s. 688-692
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Journal article (peer-reviewed)abstract
- Some animal models suggest that tumor necrosis factor (TNF)-alpha is a key component in obesity-linked insulin resistance because it inhibits insulin receptor signaling and glucose transport in insulin-sensitive tissues. However, in vivo data in humans have given conflicting results regarding the relationship between circulating TNF-alpha levels and insulin sensitivity. In the present study, the potential local role of TNF-alpha on insulin action in human subcutaneous adipose tissue was studied in 42 obese women (BMI 39+/-10 kg/m2). We found a strong inverse correlation between adipose TNF-alpha secretion and maximum insulin-stimulated glucose transport in adipocytes that was independent of fat cell volume, age, and BMI (P < 0.001, r = 0.58). As much as one-third of the variation in insulin-stimulated glucose transport could be accounted for by variations in TNF-alpha secretion. There was no significant correlation (r = 0.11) between secretion of adipose plasminogen activator inhibitor 1 and glucose transport. Furthermore, subcutaneous adipose tissue of 4 obese women (BMI 40+/-4) incubated with TNF-A for 24 h showed a one-third concentration-dependent inhibition of insulin-stimulated glucose transport (P < 0.01). In conclusion, adipose TNF-alpha may be an important specific and local factor in adipose tissue that influences the ability of insulin to stimulate glucose transport in human fat cells, at least in obese women.
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| 7. |
- Norppa, H., et al.
(author)
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Chromosomal aberrations and SCEs as biomarkers of cancer risk
- 2006
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In: Mutation Research - Fundamental and Molecular Mechanisms of Mutagenesis. - : Elsevier BV. - 1879-2871 .- 0027-5107. ; 600:1-2, s. 37-45
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Journal article (peer-reviewed)abstract
- Previous studies have suggested that the frequency of chromosomal aberrations (CAs), but not of sister chromatid exchanges (SCEs), predicts cancer risk. We have further examined this relationship in European cohorts comprising altogether almost 22,000 subjects, in the framework of a European collaborative project (CancerRiskBiomarkers). The present paper gives an overview of some of the results of the project, especially as regards CAs and SCEs. The results confirm that a high level of CAs is associated with an increased risk of cancer and indicate that this association does not depend on the time between CA analysis and cancer detection, i.e., is obviously not explained by undetected cancer. The present evidence indicates that both chromatid-type and chromosome-type CAs predict cancer, even though some data suggest that chromosome-type CAs may have a more pronounced predictive value than chromatid-type CAs. CA frequency appears to predict cancers at various sites, although there seems to be a particular association with gastrointestinal cancers. SCE frequency does not appear to have cancer predictive value, at least partly due to uncontrollable technical variation. A number of genetic polymorphisms of xenobiotic metabolism, DNA repair, and folate metabolism affect the level of CAs and might collectively contribute to the cancer predictivity of CAs. Other factors that may influence the association between CAs and cancer include, e.g., exposure to genotoxic carcinogens and internal generation of genotoxic species. Although the association between CA level and cancer is seen at the group level, an association probably also exists for the individual, although it is not known if an individual approach could be feasible. However, group level evidence should be enough to support the use of CA analysis as a tool in screening programs and prevention policies in occupational and environmental health.
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