Use of human teardrop fluid for the determination of trace elements in healthy individuals and diabetic patients

Ways to Measure Metals: From ICP-MS to XRF

PURPOSE OF REVIEW

This review explores the use of Inductively Coupled Plasma Mass Spectrometry (ICP-MS) and X-ray Fluorescence (XRF) for quantifying metals and metalloids in biological matrices such as hair, nails, blood, bone, and tissue. It provides a comprehensive overview of these methodologies, detailing their technological limitations, application scopes, and practical considerations for selection in both laboratory and field settings. By examining traditional and novel aspects of each method, this review aims to guide researchers and clinical practitioners in choosing the most suitable analytical tool based on their specific needs for sensitivity, precision, speed, and sample preparation.

RECENT FINDINGS

Recent studies highlight enhanced capabilities of both ICP-MS and XRF technologies, making them more adaptable to various analytical needs. ICP-MS is renowned for its unmatched sensitivity and precision in detecting ultra-trace metals and metalloids in complex biological samples, such as lead in plasma or seawater. XRF advancements include lower detection limits and reduced sample preparation time, enabling rapid, non-destructive analyses, ideal for quick field assessments. Portable XRF analyzers have revolutionized on-the-spot testing, providing robust data without traditional wet-lab constraints. Moreover, hybrid techniques combining ICP-MS and XRF features are emerging, offering rapid and precise metal analysis for environmental monitoring, clinical diagnostics, and epidemiological studies. Matching analytical methods to specific research demands is critical. ICP-MS is the gold standard for detailed quantitative analysis in laboratories, while XRF excels in non-destructive, immediate field applications. Selection should consider sample complexity, sensitivity, speed, and cost-efficiency. Integrating ICP-MS and XRF offers a versatile approach to metals analysis, transforming practices in environmental science and healthcare diagnostics. As these technologies evolve, they are promising to expand capabilities in detecting and understanding the roles of metals and metalloids in health and the environment.

Recent advances in the application of ionomics in metabolic diseases

Trace elements and minerals play a significant role in human health and diseases. In recent years, ionomics has been rapidly and widely applied to explore the distribution, regulation, and crosstalk of different elements in various physiological and pathological processes. On the basis of multi-elemental analytical techniques and bioinformatics methods, it is possible to elucidate the relationship between the metabolism and homeostasis of diverse elements and common diseases. The current review aims to provide an overview of recent advances in the application of ionomics in metabolic disease research. We mainly focuses on the studies about ionomic or multi-elemental profiling of different biological samples for several major types of metabolic diseases, such as diabetes mellitus, obesity, and metabolic syndrome, which reveal distinct and dynamic patterns of ion contents and their potential benefits in the detection and prognosis of these illnesses. Accumulation of copper, selenium, and environmental toxic metals as well as deficiency of zinc and magnesium appear to be the most significant risk factors for the majority of metabolic diseases, suggesting that imbalance of these elements may be involved in the pathogenesis of these diseases. Moreover, each type of metabolic diseases has shown a relatively unique distribution of ions in biofluids and hair/nails from patients, which might serve as potential indicators for the respective disease. Overall, ionomics not only improves our understanding of the association between elemental dyshomeostasis and the development of metabolic disease but also assists in the identification of new potential diagnostic and prognostic markers in translational medicine.

Associations between whole blood trace elements concentrations and HbA1c levels in patients with type 2 diabetes

Previous researches have been conducted to study the associations of trace elements on Type 2 diabetes (T2D) risk. The present study focuses on the evaluation of potential associations between trace elements and Hemoglobin A1c (HbA1c) in patients with T2D, via the determination of their levels in human whole blood. 100 diabetes without complications, 75 prediabetes and 40 apparently healthy subjects were studied. The levels of eleven trace elements including lithium (Li), vanadium (V), chromium (Cr), manganese (Mn), iron (Fe), cobalt (Co), copper (Cu), zinc (Zn), selenium (Se), strontium (Sr) and molybdenum (Mo) were measured using inductively coupled plasma mass spectrometry (ICP-MS). The levels of fasting glucose, HbA1c, Hemoglobin, lipid, liver function, kidney function, thyroid function and demographic data were obtained from the Laboratory Information System. Nonparametric correlation (Spearman) was used to analyze the relationship between trace elements and HbA1c. The contents of V, Cr, Mn, Fe, Co, Cu, Zn and Mo in diabetes increased comparing with the healthy subject while Li decreased. But the levels of Li, V, Cr, Mn, Co, Se and Mo negatively correlated with HbA1c in the diabetes subjects (r value: - 0.2189, - 0.2421, - 0.3260, - 0.2744, - 0.2812, - 0.2456, - 0.2240; 95% confidence interval - 0.4032 to - 0.0176, - 0.4235 to - 0.0420, - 0.4955 to - 0.1326, - 0.4515 to - 0.0765, - 0.4573 to - 0.0838, - 0.4266 to - 0.0458, - 0.4076 to - 0.0229; p < 0.05, p < 0.05, p < 0.001, p < 0.01, p < 0.01, p < 0.05, p < 0.05). Accordingly, the contents of V, Cr, Mn and Se showed lower in HbA1c ≥ 7.0% group in contrast to HbA1c < 7.0% group. No correlation of HbA1c (or FBG) and trace elements was found in the healthy subjects. Trace element levels and metabolic abnormalities of blood glucose may be mutually affected. The extra supplement of trace elements needs to be cautious.

Simultaneous quantification of 70 elements in biofluids within 5 min using inductively coupled plasma mass spectrometry to reveal elementomic phenotypes of healthy Chinese adults

High-throughput quantification of the composition of all chemical elements (elementome) in biological samples is essential for understanding their diverse functions in large cohort studies. We, here, established an ICP-MS method to simultaneously quantify 70 elements in 50 μL biofluids within 5 min. This validated method had excellent quantification linearity (R² > 0.998), sensitivity (with LOD as low as 1.0 ng/L), precision (CV<15%), accuracy (|RE|<20% except Hg), recovery (80-120%), throughput and coverage with minute samples. The method also showed good applicability to multiple biofluids including human serum, plasma, urine and goat serum samples. By using this method, we furture measured 70 elements in blood plasma samples from 758 Chinese adult participants and established the first reference intervals for the concentration of these elements from 127 healthy adults in this population. This offers a high-throughput quantitative elementomics method to define population elementomic phenotypes and for investigating the diverse biological functions of many elements in multiple biological matrices.

Cadmium exposure and risk of diabetes and prediabetes: A systematic review and dose-response meta-analysis

BACKGROUND

Cadmium exposure has been associated with increased diabetes risk in several studies, though there is still considerable debate about the magnitude and shape of the association.

OBJECTIVE

To perform a systematic review and meta-analysis of observational studies investigating the relation between cadmium exposure and risk of type 2 diabetes and prediabetes, and to summarize data on the magnitude and shape of the association.

DATA SOURCE

After conducting an online literature search through October 1, 2021, we identified 42 eligible studies investigating the association between cadmium exposure and risk of diabetes and prediabetes.

STUDY ELIGIBILITY CRITERIA

We included studies that assessed cadmium exposure through biomarker levels; examined type 2 diabetes or prediabetes among outcomes; and reported effect estimates for cadmium exposure for meta-analysis only.

STUDY APPRAISAL AND SYNTHESIS METHODS

Studies were evaluated using ROBINS-E risk of bias tool. We quantitively assessed the relation between exposure and study outcomes using one-stage dose-response meta-analysis with a random effects meta-analytical model.

RESULTS

In the meta-analysis, comparing highest-versus-lowest cadmium exposure levels, summary relative risks (RRs) for type 2 diabetes were 1.24 (95% confidence interval 0.96-1.59), 1.21 (1.00-1.45), and 1.47 (1.01-2.13) for blood, urinary, and toenail matrices, respectively. Similarly, there was an increased risk of prediabetes for cadmium concentrations in both urine (RR = 1.41, 95% CI: 1.15-1.73) and blood (RR = 1.38, 95% CI: 1.16-1.63). In the dose-response meta-analysis, we observed a consistent linear positive association between cadmium exposure and diabetes risk, with RRs of 1.25 (0.90-1.72) at 2.0 µg/g of creatinine. Conversely for blood cadmium, diabetes risk appeared to increase only above 1 µg/L. Prediabetes risk increased up to approximately 2 µg/g creatinine above which it reached a plateau with RR of 1.42 (1.12-1.76) at 2 µg/g creatinine.

LIMITATIONS AND CONCLUSIONS

This analysis provides moderate-certainty evidence for a positive association between cadmium exposure (measured in multiple matrices) and risk of both diabetes and prediabetes.

Instrumental neutron activation analysis (INAA) of zinc concentrations in scalp hair and fingernails samples of Algerian females with breast cancer

In the present work, zinc levels were measured in scalp hair and fingernails in order to identify potential risk factors for breast cancer. The samples were collected from 40 Algerian breast cancer female patients and from 20 normal subjects matching the same age range. The concentration of zinc was analyzed using Instrumental neutron activation analysis technique (INAA). In scalp hair samples it was found in the range 119–792 μg/g for the normal subjects and in the range 82–806 μg/g for the patients, with an increase rate of 10.9%. The range of concentration of zinc in fingernails was found between 89 and 247 μg/g for normal subjects and between 75 and 276 μg/g for the patients with an increase rate of 2.5%. The influence of age on zinc concentration was also investigated. The obtained results show some consistency with those obtained by other groups.