Changes in exercise capacity in subjects with cardiac asymptomatic hereditary hemochromatosis during a follow-up after 5 yrs

The relationship between hemoglobin and [Formula: see text]: A systematic review and meta-analysis

OBJECTIVE

There is widespread agreement about the key role of hemoglobin for oxygen transport. Both observational and interventional studies have examined the relationship between hemoglobin levels and maximal oxygen uptake ([Formula: see text]) in humans. However, there exists considerable variability in the scientific literature regarding the potential relationship between hemoglobin and [Formula: see text]. Thus, we aimed to provide a comprehensive analysis of the diverse literature and examine the relationship between hemoglobin levels (hemoglobin concentration and mass) and [Formula: see text] (absolute and relative [Formula: see text]) among both observational and interventional studies.

METHODS

A systematic search was performed on December 6th, 2021. The study procedures and reporting of findings followed Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Article selection and data abstraction were performed in duplicate by two independent reviewers. Primary outcomes were hemoglobin levels and [Formula: see text] values (absolute and relative). For observational studies, meta-regression models were performed to examine the relationship between hemoglobin levels and [Formula: see text] values. For interventional studies, meta-analysis models were performed to determine the change in [Formula: see text] values (standard paired difference) associated with interventions designed to modify hemoglobin levels or [Formula: see text]. Meta-regression models were then performed to determine the relationship between a change in hemoglobin levels and the change in [Formula: see text] values.

RESULTS

Data from 384 studies (226 observational studies and 158 interventional studies) were examined. For observational data, there was a positive association between absolute [Formula: see text] and hemoglobin levels (hemoglobin concentration, hemoglobin mass, and hematocrit (P<0.001 for all)). Prespecified subgroup analyses demonstrated no apparent sex-related differences among these relationships. For interventional data, there was a positive association between the change of absolute [Formula: see text] (standard paired difference) and the change in hemoglobin levels (hemoglobin concentration (P<0.0001) and hemoglobin mass (P = 0.006)).

CONCLUSION

These findings suggest that [Formula: see text] values are closely associated with hemoglobin levels among both observational and interventional studies. Although our findings suggest a lack of sex differences in these relationships, there were limited studies incorporating females or stratifying results by biological sex.

Reduction of Skeletal Muscle Power in Adolescent Males Carrying H63D Mutation in the HFE Gene

Iron overload resulting from the mutation of genes involved in iron metabolism or excess dietary intake has been reported to negatively influence human physical performance. The aim of this study was to test the hypothesis that adolescents bearing a hemochromatosis gene (HFE) mutation in contrast to adults with the same mutation will not experience iron accumulation and their aerobic capacity will be similar to that of age-matched controls. Thirteen boys participated in the study. Seven of them are carriers of H63D mutation in the HFE gene and six were wild type. Fitness levels were assessed using the cardiopulmonary exercise test. In addition, iron status and inflammatory markers were determined. We observed that cardiovascular fitness was significantly lower in the group bearing the HFE mutation compared to the control group. Moreover, the HFE mutation group achieved lower maximal power output compared to the control group. There were no differences in blood ferritin concentrations between the two groups which indicates similar amounts of stored iron. Obtained data do not confirm our hypothesis. On the contrary, it was demonstrated that HFE mutation is associated with a lower level of aerobic capacity, even in the absence of iron accumulation.

Evaluation of a 7-Gene Genetic Profile for Athletic Endurance Phenotype in Ironman Championship Triathletes

Polygenic profiling has been proposed for elite endurance performance, using an additive model determining the proportion of optimal alleles in endurance athletes. To investigate this model’s utility for elite triathletes, we genotyped seven polymorphisms previously associated with an endurance polygenic profile (ACE Ins/Del, ACTN3 Arg577Ter, AMPD1 Gln12Ter, CKMM 1170bp/985+185bp, HFE His63Asp, GDF8 Lys153Arg and PPARGC1A Gly482Ser) in a cohort of 196 elite athletes who participated in the 2008 Kona Ironman championship triathlon. Mean performance time (PT) was not significantly different in individual marker analysis. Age, sex, and continent of origin had a significant influence on PT and were adjusted for. Only the AMPD1 endurance-optimal Gln allele was found to be significantly associated with an improvement in PT (model p = 5.79 x 10⁻¹⁷, AMPD1 genotype p = 0.01). Individual genotypes were combined into a total genotype score (TGS); TGS distribution ranged from 28.6 to 92.9, concordant with prior studies in endurance athletes (mean±SD: 60.75±12.95). TGS distribution was shifted toward higher TGS in the top 10% of athletes, though the mean TGS was not significantly different (p = 0.164) and not significantly associated with PT even when adjusted for age, sex, and origin. Receiver operating characteristic curve analysis determined that TGS alone could not significantly predict athlete finishing time with discriminating sensitivity and specificity for three outcomes (less than median PT, less than mean PT, or in the top 10%), though models with the age, sex, continent of origin, and either TGS or AMPD1 genotype could. These results suggest three things: that more sophisticated genetic models may be necessary to accurately predict athlete finishing time in endurance events; that non-genetic factors such as training are hugely influential and should be included in genetic analyses to prevent confounding; and that large collaborations may be necessary to obtain sufficient sample sizes for powerful and complex analyses of endurance performance.