Intra-Individual Variation and Reliability of Biomarkers of the Antioxidant Defense System by Considering Dietary and Lifestyle Factors in Premenopausal Women

Internal exposure to heat-induced food contaminants in omnivores, vegans and strict raw food eaters: biomarkers of exposure to acrylamide (hemoglobin adducts, urinary mercapturic acids) and new insights on its endogenous formation

The urinary mercapturic acids N-acetyl-S-(2-carbamoylethyl)-L-cysteine (AAMA) and N-acetyl-S-(2-carbamoyl-2-hydroxyethyl)-L-cysteine (GAMA) are short-term biomarkers of exposure from acrylamide and its metabolite glycidamide, respectively. The medium-term exposure to acrylamide and glycidamide is monitored by the adducts N-(2-carbamoylethyl)-Val (AA-Val) and N-(2-carbamoyl-2-hydroxyethyl)-Val (GA-Val) in hemoglobin (Hb), respectively. Three questions were addressed by application of these biomarkers in two diet studies including 36 omnivores, 36 vegans and 16 strict raw food eaters (abstaining from any warmed or heated food for at least four months): first, what is the internal acrylamide exposure following a vegan or a raw food diet in comparison to that in omnivores? Second, did the exposure change between 2017 and 2021? And third, what is the stability over time of AAMA/GAMA excretion compared to that of AA-Val/GA-Val levels in Hb between both time points? Median urinary AAMA excretion per day in non-smoking omnivores, vegans and raw food eaters were 62.4, 85.4 and 15.4 µg/day, respectively; the corresponding median AA-Val levels were 27.7, 39.7 and 13.3 pmol/g Hb, respectively. Median levels in strict raw food eaters were about 25% (AAMA excretion) and 48% (AA-Val) of those in omnivores. In comparison to 2017, AAMA and GAMA excretion levels were hardly altered in 2021, however, levels of AA-Val and GA-Val in 2021 slightly increased. There was a weak correlation between AAMA excretion levels determined four years apart (rS = 0.30), and a moderate correlation between levels of AA-Val (rS = 0.55) in this timeframe. Our data in strict raw food eaters confirm a significant endogenous formation to acrylamide in a size range, which is-based on the levels of AA-Val-distinctly higher than reported previously based on levels of urinary AAMA excretion. The relatively lower AAMA excretion in raw food eaters likely represents a lower extent of glutathione conjugation due to missing hepatic first-pass metabolism in case of endogenous formation of acrylamide, which leads to a higher systemic exposure.

CXCL10 upregulation in radiation-exposed human peripheral blood mononuclear cells as a candidate biomarker for rapid triage after radiation exposure

PURPOSE

In case of a nuclear accident, individuals with high-dose radiation exposure (>1-2 Gy) should be rapidly identified. While ferredoxin reductase (FDXR) was recently suggested as a radiation-responsive gene, the use of a single gene biomarker limits radiation dose assessment. To overcome this limitation, we sought to identify reliable radiation-responsive gene biomarkers.

MATERIALS AND METHODS

Peripheral blood mononuclear cells (PBMCs) were isolated from mice after total body irradiation, and gene expression was analyzed using a microarray approach to identify radiation-responsive genes.

RESULTS

In light of the essential role of the immune response following radiation exposure, we selected several immune-related candidate genes upregulated by radiation exposure in both mouse and human PBMCs. In particular, the expression of ACOD1 and CXCL10 increased in a radiation dose-dependent manner, while remaining unchanged following lipopolysaccharide (LPS) stimulation in human PBMCs. The expression of both genes was further evaluated in the blood of cancer patients before and after radiotherapy. CXCL10 expression exhibited a distinct increase after radiotherapy and was positively correlated with FDXR expression.

CONCLUSIONS

CXCL10 expression in irradiated PBMCs represents a potential biomarker for radiation exposure.

The Implication of Mechanistic Approaches and the Role of the Microbiome in Polycystic Ovary Syndrome (PCOS): A Review

As a complex endocrine and metabolic condition, polycystic ovarian syndrome (PCOS) affects women's reproductive health. These common symptoms include hirsutism, hyperandrogenism, ovulatory dysfunction, irregular menstruation, and infertility. No one knows what causes it or how to stop it yet. Alterations in gut microbiota composition and disruptions in secondary bile acid production appear to play a causative role in developing PCOS. PCOS pathophysiology and phenotypes are tightly related to both enteric and vaginal bacteria. Patients with PCOS exhibit changed microbiome compositions and decreased microbial diversity. Intestinal microorganisms also alter PCOS patient phenotypes by upregulating or downregulating hormone release, gut-brain mediators, and metabolite synthesis. The human body's gut microbiota, also known as the "second genome," can interact with the environment to improve metabolic and immunological function. Inflammation is connected to PCOS and may be caused by dysbiosis in the gut microbiome. This review sheds light on the recently discovered connections between gut microbiota and insulin resistance (IR) and the potential mechanisms of PCOS. This study also describes metabolomic studies to obtain a clear view of PCOS and ways to tackle it.

Ambient Air Pollutants and Traffic Factors Were Associated with Blood and Urine Biomarkers and Asthma Risk

The UK Biobank (UKBB) is a large population-based cohort that provides a unique opportunity to study the association between environmental exposure and biomarkers and to identify biomarkers as potential instruments for assessing exposure dose, health damage, and disease risks. On 462 063 participants of European ancestry, we characterized the relationship of 38 disease-relevant biomarkers, asthma diagnosis, ambient pollution, traffic factors, and genetic background. The air pollutant exposure on the UKBB cohort was fairly low (e.g., mean PM_2.5 concentration at 10.0 μg/m³). Nevertheless, 30 biomarkers were in association with at least one environmental factor; e.g., C-reactive protein levels were positively associated with NO (p_adj = 2.99 × 10^-4), NO₂ (p_adj = 4.15 × 10^-4), and PM_2.5 (p_adj = 1.92 × 10^-6) even after multiple testing adjustment. Asthma diagnosis was associated with four pollutants (NO, NO₂, PM_2.5, and PM₁₀). The largest effect size was observed in PM_2.5, where a 5 μg/m³ increment of exposure was associated with a 1.52 increase in asthma diagnosis (p = 4.41 × 10^-13). Further, environmental exposure and genetic predisposition influenced biomarker levels and asthma diagnosis in an additive model. The exposure-biomarker associations identified in this study could serve as potential indicators for environmental exposure induced health damages. Our results also shed light on possible mechanisms whereby environmental exposure influences disease-causing biomarkers and in turn increases disease risk.