Certain Associations Between Iron Biomarkers and Total and γ' Fibrinogen and Plasma Clot Properties Are Mediated by Fibrinogen Genotypes
Bibliographic record
Abstract
Introduction: Evidence for the relationship between body iron and cardiovascular disease (CVD) is inconsistent and mechanisms involved remain poorly understood. Therefore, we first investigated whether there are linear or non-linear relationships between iron status and total and γ' fibrinogen as well as plasma fibrin clot properties and, second, determined whether there are interactions with iron biomarkers and fibrinogen and FXIII single nucleotide polymorphisms (SNPs) in relation to fibrinogen concentration and functionality. Methods: In this cross-sectional analysis of 2,010 apparently healthy Black South Africans we quantified total and γ' fibrinogen, serum iron, ferritin and transferrin using standardized methods and calculated transferrin saturation (TS). Clot architecture and lysis were explored with a global analytical turbidity assay. The SNPs were determined through an Illumina BeadXpress ® platform. Results: Total, but not %γ', fibrinogen negatively correlated with serum iron concentrations, although both decreased over iron tertiles. %γ' fibrinogen correlated negatively with transferrin and decreased over the transferrin tertiles. A weak negative association between total fibrinogen and TS was detected with fibrinogen decreasing over the TS tertiles and categories based on TS. Lag time correlated positively with transferrin and increased over transferrin tertiles, when adjusting for fibrinogen. Before adjusting for fibrinogen, lag time was shorter in those with adequate iron status based on TS than other iron subcategories. Clot lysis time (CLT) negatively correlated with ferritin and was longer in the first than in the third ferritin tertile. Among iron status categories based on ferritin, only CLT differed and was longer in those with adequate iron than with iron-overload. CLT negatively correlated with TS, albeit weakly, shortened over the TS tertiles and was shorter in those with adequate iron based on TS categories. Interactions were observed between FGB SNPs and some of the markers of iron status investigated, in relation to the clot properties with the most prominent associations detected in homozygous carriers of the variant alleles for whom increased iron status was more beneficial than for those harboring the wild-type alleles. Iron modulated the influence of the SNPs so that for the majority iron was beneficial in respect of clot properties, but even more so for a minority group harboring specific variant alleles. Conclusion: This is the first large-scale epidemiological study to relate fibrinogen concentration and functionality to markers of iron status and to take genetic factors into consideration. We have detected a relationship between iron biomarkers and fibrinogen as well as clot characteristics that are influenced by the genetic make-up of an individual.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".