Association of genetic polymorphisms in detoxifying systems and urinary metal(loid) levels with excess body weight among Spanish children: A proof-of-concept study.

Exposure to metal(loid)s during critical developmental windows could result in permanent damage to the target organ system, increasing susceptibility to disease later in life. In view of the fact that metals(loid)s have been shown to work as obesogens, the aim of the present case-control study was to evaluate the modification effect of exposure to metal(loid)s on the association between SNPs in genes involved in metal(loid) detoxification and excess body weight among children. A total of 134 Spanish children aged 6-12 years old were included (88 controls and 46 cases). Seven SNPs (GSTP1 rs1695 and rs1138272; GCLM rs3789453, ATP7B rs1061472, rs732774 and rs1801243; and ABCC2 rs1885301) were genotyped on GSA microchips, and ten metal(loid)s were analysed in urine samples through Inductively coupled plasma mass spectrometry (ICP-MS). Multivariable logistic regressions were conducted to assess the genetic and metal exposures' main association and interaction effects. GSTP1 rs1695 and ATP7B rs1061472 showed significant effects on excess weight increase in those children carrying two copies of the risk G allele and being highly exposed to chromium (ORa = 5.38, p = 0.042, p interaction = 0.028 for rs1695; and ORa = 4.20, p = 0.035, p interaction = 0.012 for rs1061472) and lead (ORa = 7.18, p = 0.027, p interaction = 0.031 for rs1695, and ORa = 3.42, p = 0.062, p interaction = 0.010 for rs1061472). Conversely, GCLM rs3789453 and ATP7B rs1801243 appeared to play a protective role against excess weight in those exposed to copper (ORa = 0.20, p = 0.025, p interaction = 0.074 for rs3789453) and lead (ORa = 0.22, p = 0.092, p interaction = 0.089 for rs1801243). Our findings provide the first proof that interaction effects could exist between genetic variants within GSH and metal transporting systems and exposure to metal(loid)s, on excess body weight among Spanish children.

Melatonin Improves Levels of Zn and Cu in the Muscle of Diabetic Obese Rats.

Melatonin improves metabolic alterations associated with obesity and its diabetes (diabesity). We intend to determine whether this improvement is exerted by changing Zn and/or Cu tissue levels in liver, muscle, pancreas, and brain, and in internal (perirenal, perigonadal, and omentum) and subcutaneous lumbar white adipose tissues (IWAT and SWAT, respectively). Male Zücker diabetic fatty (ZDF) rats and lean littermates (ZL) were orally supplemented either with melatonin (10 mg/kg body weight/day) or vehicle for 6 weeks. Zn and Cu concentrations were not significantly influenced by diabesity in the analyzed tissues (p > 0.05), with the exception of Zn in liver. In skeletal muscle Zn and Cu, and in perirenal WAT, only Zn levels increased significantly with melatonin supplementation in ZDF rats (p < 0.05). This cytoplasmic Zn enhancement would be probably associated with the upregulation of several Zn influx membrane transporters (Zips) and could explain the amelioration in the glycaemia and insulinaemia by upregulating the Akt and downregulating the inhibitor PTP1B, in obese and diabetic conditions. Enhanced Zn and Cu levels in muscle cells could be related to the reported antioxidant melatonin activity exerted by increasing the Zn, Cu-SOD, and extracellular Cu-SOD activity. In conclusion, melatonin, by increasing the muscle levels of Zn and Cu, joined with our previously reported findings improves glycaemia, insulinaemia, and oxidative stress in this diabesity animal model.

Neurotoxicity by mercury is not associated with autism spectrum disorders in Spanish children.

BACKGROUND: The pathophysiological etiologies related with the development of Autism Spectrum Disorders (ASD) remain controversial. Different authors have studied neurotoxins such as mercury (Hg) and their relationship with ADS. The objective of this study was to assess the levels of Hg in hair in a group of ASD children (chronic exposure) and in urinary excretion (acute exposure), in comparison to a healthy group. METHODS: A case-control study was conducted in Spanish children. We compared 54 ASD children (aged 2-6) with no other associated pathology to a normally-developing control group (54 subjects). RESULTS: There were no differences in urine (p:0.631) and hair (p:1.000) samples percentages below the limits of detection between the control and the ASD groups, and also between patients in the regression ASD subgroup (AMR) (p:0.08) and the non-regression ASD subgroup (ANMR) (p:0.705). When the analysis was adjusted for age and sex, the differences between Hg levels maintained not significant. There were no correlations between Hg concentrations in the ASD group as a whole (p: 0.739), or when they were subdivided into ASD-AMR (p: 0.739) and ASD-ANMR (p: 0.363). CONCLUSIONS: The present study shows no evidence in our geographical area to support an association between mercury neurotoxicity and the etiopathogenesis of ASD.

El papel de los biomarcadores en Toxicología Humana / The role of biomarkers in human toxicology

El uso de biomarcadores en la evaluación del riesgo frente a determinadas patologías ha aumentado de forma notable en la última década. Los marcadores biológicos son variables que indican un determinado momento en el proceso conducente a la enfermedad. Tienen especial interés en la evaluación de enfermedades progresivas donde los sintomas se manifiestan tras un largo periodo de exposición. En general los biomarcadores se clasifican en tres grupos: de exposición, efecto o susceptibilidad. Los biomarcadores de exposición permiten la medida de la dosis interna mediante el análisis químico del compuesto tóxico o un metabolito del mismo en fluidos corporales, los biomarcadores de susceptibildiad sirven como indicadores de la respuesta individual frente a la agresión de un tóxico o grupo de tóxicos y los biomarcadores de efecto indican cambios bioquímicos y los biomarcadores de efecto indican cambios bioquímicos que acontecen tras la expocición a xenobióticos. En esta revisión se consideran varios ejemplos de biomarcadores en la espcie humana (AU)