cfDNA Changes in Maximal Exercises as a Sport Adaptation Predictor

Harnessing the potential of genomic characterization of mutational profiles to improve early diagnosis of lung cancer

INTRODUCTION

Lung Cancer (LC) continues to be a leading cause of cancer-related mortality globally, largely due to the asymptomatic nature of its early stages and the limitations of current diagnostic methods such as Low-Dose Computed Tomography (LDCT), whose often result in late diagnosis, highlighting an urgent need for innovative, minimally invasive diagnostic techniques that can improve early detection rates.

AREAS COVERED

This review delves into the potential of genomic characterization and mutational profiling to enhance early LC diagnosis, exploring the current state and limitations of traditional diagnostic approaches and the revolutionary role of Liquid Biopsies (LB), including cell-free DNA (cfDNA) analysis through fragmentomics and methylomics. New genomic technologies that allow for earlier detection of LC are scrutinized, alongside a detailed discussion on the literature that shaped our understanding in this field.

EXPERT OPINION

Despite the promising advancements in genomic characterization techniques, several challenges remain, such as the heterogeneity of LC mutations, the high cost, and limited accessibility of Next-Generation Sequencing (NGS) technologies. Additionally, there is a critical need of standardized protocols for interpreting mutational data. Future research should focus on overcoming these barriers to integrate these novel diagnostic methods into standard clinical practice, potentially revolutionizing the management of LC patients.

Cell-free DNA kinetics in response to muscle-damaging exercise: A drop jump study

A significant increase in circulating cell-free DNA (cfDNA) occurs with physical exercise, which depends on the type of exertion and the duration. The aims of this study were as follows: (1) to investigate the time course of cfDNA and conventional markers of muscle damage from immediately after to 96 h after muscle-damaging exercise; and (2) to investigate the relationship between cfDNA and indicators of primary (low-frequency fatigue and maximal voluntary isometric contraction) and secondary (creatine kinase and delayed-onset muscle soreness) muscle damage in young healthy males. Fourteen participants (age, 22 ± 2 years; weight, 84.4 ± 11.2 kg; height, 184.0 ± 7.4 cm) performed 50 intermittent drop jumps at 20 s intervals. We measured cfDNA and creatine kinase concentrations, maximal voluntary isometric contraction torque, low-frequency fatigue and delayed-onset muscle soreness before and at several time points up to 96 h after exercise. Plasma cfDNA levels increased from immediately postexercise until 72 h postexercise (P < 0.01). Elevation of postexercise cfDNA was correlated with both more pronounced low-frequency fatigue (r = -0.52, P = 3.4 × 10-11) and delayed-onset muscle soreness (r = 0.32, P = 0.00019). Levels of cfDNA change in response to severe primary and secondary muscle damage after exercise. Levels of cfDNA exhibit a stronger correlation with variables related to primary muscle damage than to secondary muscle damage, suggesting that cfDNA is a more sensitive marker of acute loss of muscle function than of secondary inflammation or damaged muscle fibres.

The impact of preanalytical variables on the analysis of cell-free DNA from blood and urine samples

Cell-free DNA (cfDNA), a burgeoning class of molecular biomarkers, has been extensively studied across a variety of biomedical fields. As a key component of liquid biopsy, cfDNA testing is gaining prominence in disease detection and management due to the convenience of sample collection and the abundant wealth of genetic information it provides. However, the broader clinical application of cfDNA is currently impeded by a lack of standardization in the preanalytical procedures for cfDNA analysis. A number of fundamental challenges, including the selection of appropriate preanalytical procedures, prevention of short cfDNA fragment loss, and the validation of various cfDNA measurement methods, remain unaddressed. These existing hurdles lead to difficulties in comparing results and ensuring repeatability, thereby undermining the reliability of cfDNA analysis in clinical settings. This review discusses the crucial preanalytical factors that influence cfDNA analysis outcomes, including sample collection, transportation, temporary storage, processing, extraction, quality control, and long-term storage. The review provides clarification on achievable consensus and offers an analysis of the current issues with the goal of standardizing preanalytical procedures for cfDNA analysis.

Microbiome features associated with performance measures in athletic and non-athletic individuals: A case-control study

The influence of human gut microbiota on health and disease is now commonly appreciated. Therefore, it is not surprising that microbiome research has found interest in the sports community, hoping to improve health and optimize performance. Comparative studies found new species or pathways that were more enriched in elites than sedentary controls. In addition, sport-specific and performance-level-specific microbiome features have been identified. However, the results remain inconclusive and indicate the need for further assessment. In this case-control study, we tested two athletic populations (i.e. strength athletes, endurance athletes) and a non-athletic, but physically active, control group across two acute exercise bouts, separated by a 2-week period, that measured explosive and high intensity fitness level (repeated 30-s all-out Wingate test (WT)) and cardiorespiratory fitness level (Bruce Treadmill Test). While we did not identify any group differences in alpha and beta diversity or significant differential abundance of microbiome components at baseline, one-third of the species identified were unique to each group. Longitudinal sample (pre- and post-exercise) analysis revealed an abundance of Alistipes communis in the strength group during the WT and 88 species with notable between-group differences during the Bruce Test. SparCC recognized Bifidobacterium longum and Bifidobacterium adolescentis, short-chain fatty acid producers with probiotic properties, species strongly associated with VO2max. Ultimately, we identified several taxa with different baseline abundances and longitudinal changes when comparing individuals based on their VO2max, average power, and maximal power parameters. Our results confirmed that the health status of individuals are consistent with assumptions about microbiome health. Furthermore, our findings indicate that microbiome features are associated with better performance previously identified in elite athletes.

Effect of acute moderate-intensity cycling on cfDNA levels considering menstrual cycle phases

Introduction

We aimed to determine the effects of exercise on cell-free DNA (cfDNA) levels and concentration changes during the menstrual cycle in participants with regular menstrual cycles and no exercise habits.

Methods

Eleven sedentary female students with regular menstrual cycles and ovulation performed bicycle exercises at 60% VO2max for 30 min during the menstrual, ovulatory, and luteal phases. Blood samples were collected before (Pre), immediately after (Post 0), 30 min after (Post 30), and 60 min after (Post 60) exercise. Blood concentrations of ovarian hormones, cfDNA, prostaglandin F2a (PGF2α), interleukin-6 (IL-6), and aromatase were evaluated.

Results

Based on the concentration of ovarian hormones, seven individuals were finally analyzed. No significant phase difference was observed in cfDNA across all time points. cfDNA (menstrual phase: p = 0.028, ovulatory phase: p = 0.018, and luteal phase: p = 0.048) and aromatase concentrations (menstrual phase: p = 0.040, ovulatory phase: p = 0.039, and luteal phase: p = 0.045) significantly increased from Pre to Post 0 in all phases. Serum estradiol (E2) levels were significantly higher in the luteal phase at all time points than in the menstrual phase (Pre: p < 0.001, Post 0: p < 0.001, Post 30: p = 0.005, and Post 60: p = 0.011); however, serum progesterone (P4) levels were significantly higher in the luteal phase at all time points than in the menstrual (Pre: p < 0.001, Post 0: p < 0.001, Post 30: p < 0.001, and Post 60: p < 0.001) and ovulatory phases (Pre: p = 0.005, Post 0: p = 0.005, Post 30: p = 0.003, and Post 60: p = 0.003). E2 levels significantly increased from Pre to Post 0 in the ovulatory and luteal phases, whereas P4 levels increased in the luteal phase. Progesterone to estradiol level ratio (P4/E2) changes from Pre to Post 0 (%baseline) during the luteal phase were significantly negatively correlated (r = -0.82, p = 0.046) with the changes in cfDNA from Pre to Post 0. Furthermore, the repeated measures correlation between P4/E2 and cfDNA level showed a significant negative correlation in ovulatory and luteal phases.

Discussion

The results indicate that while resting cfDNA levels are unlikely to be affected by a woman's menstrual cycle, the increase in cfDNA after exercise is higher in the ovulatory phase (when only E2 increases) and lower in the luteal phase (when E2 and P4 increase with exercise) compared to that in the menstrual phase (when E2 and P4 are in low levels), suggesting the contribution of increased ovarian hormone levels after exercise.

Implications of Adipose Tissue Content for Changes in Serum Levels of Exercise-Induced Adipokines: A Quasi-Experimental Study

Human adipocytes release multiple adipokines into the bloodstream during physical activity. This affects many organs and might contribute to the induction of inflammation. In this study, we aimed to assess changes in circulating adipokine levels induced by intense aerobic and anaerobic exercise in individuals with different adipose tissue content. In the quasi-experimental study, 48 male volunteers (aged 21.78 ± 1.98 years) were assigned to groups depending on their body fat content (BF): LBF, low body fat (<8% BF, n = 16); MBF, moderate body fat (8−14% BF, n = 19); and HBF, high body fat (>14% BF, n = 13). The volunteers performed maximal aerobic effort (MAE) and maximal anaerobic effort (MAnE) exercises. Blood samples were collected at five timepoints: before exercise, immediately after, 2 h, 6 h, and 24 h after each exercise. The selected cytokines were analyzed: adiponectin, follistatin-like 1, interleukin 6, leptin, oncostatin M, and resistin. While the participants’ MAnE and MAE performance were similar regardless of BF, the cytokine response of the HBF group was different from that of the others. Six hours after exercise, leptin levels in the HBF group increased by 35%. Further, immediately after MAnE, resistin levels in the HBF group also increased, by approximately 55%. The effect of different BF was not apparent for other cytokines. We conclude that the adipokine exercise response is associated with the amount of adipose tissue and is related to exercise type.