Lead levels in blood of children exposed to metallurgical waste in Abra Pampa, Jujuy (Argentina)

Abra Pampa es una pequeña comunidad situada en el norte de Argentina, donde los desechos de plomo de una planta metalúrgica (Metal Huasi) se abandonaron por más de 40 años, dejándolos en el centro del pueblo. Con el fin de medir la exposición a estos residuos peligrosos, se determinaron los niveles de plomo ensangre en niños de edades comprendidas entre 5 y 14 años (n=234). Los niños incluidos en la muestra habían estado expuestos, por el aire y el suelo, al plomo durante cinco años por lo menos porque vivían alrededor de la montaña de residuos. Fueron evaluados clínicamente. Para determinar el estado nutricional se midió el peso y talla y se calculó el índice de masa corporal total. Se realizó el análisis de plombemia mediante la técnica de Espectrofotometría deAbsorción Atómica-atomización electrotérmica. La prevalencia de intoxicación (Pb> 10 µg / dL) fue de 28%. El 81% de los niños estudiados tenían niveles de plomo en sangre superiores a 5 µg / dL, lo que se considera un riesgo en el desarrollo neuromadurativo.También se encontraron diferencias significativas según la edad y ladistancia entre las casas de los niños y el sitio de disposición de losresiduos. Estos resultados mostraron que los residuos son una fuentede exposición al plomo para los niños que viven cerca del depósitode escorias y generaron estrategias de remediación para minimizarla exposición infantil.Abra Pampa is a small community located in North Argentina, where lead wastes from a metallurgical plant were improperly managed. Therefore, in order to define the exposure to this hazardous waste, blood lead levels in children aged between 5 and 14 years were determined. The prevailing state of poisoning (Pb > 10 µg / dL) was 28%. Furthermore, 81% of the studied children had blood-lead levels higher than 5 µg / dL, which is considered a neurocognitive risk. Significant differences according to age and distance between the children’s houses and the disposal site were also found. These results showed that the waste is a source of lead exposure for children living next to the disposal site; therefore, a remediation program is being performed in the area.Fil: Tschambler, Javier Alejandro. Universidad Nacional de Jujuy. Facultad de Ciencias Agrarias; ArgentinaFil: Wierna, Norma Rosario. Universidad Nacional de Jujuy. Facultad de Ciencias Agrarias; ArgentinaFil: Romero, A.E.. Universidad Nacional de Jujuy. Facultad de Ciencias Agrarias; ArgentinaFil: Rios, Francisco Teodoro. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Jujuy. Facultad de Ciencias Agrarias; ArgentinaFil: Ruggeri, María Alejandra. Universidad Nacional de Jujuy. Facultad de Ciencias Agrarias; ArgentinaFil: Bovi Mitre, M.G. Universidad Nacional de Jujuy. Facultad de Ciencias Agrarias; Argentin

Comprehensive analysis of epigenetic clocks reveals associations between disproportionate biological ageing and hippocampal volume

The concept of age acceleration, the difference between biological age and chronological age, is of growing interest, particularly with respect to age-related disorders, such as Alzheimer’s Disease (AD). Whilst studies have reported associations with AD risk and related phenotypes, there remains a lack of consensus on these associations. Here we aimed to comprehensively investigate the relationship between five recognised measures of age acceleration, based on DNA methylation patterns (DNAm age), and cross-sectional and longitudinal cognition and AD-related neuroimaging phenotypes (volumetric MRI and Amyloid-β PET) in the Australian Imaging, Biomarkers and Lifestyle (AIBL) and the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Significant associations were observed between age acceleration using the Hannum epigenetic clock and cross-sectional hippocampal volume in AIBL and replicated in ADNI. In AIBL, several other findings were observed cross-sectionally, including a significant association between hippocampal volume and the Hannum and Phenoage epigenetic clocks. Further, significant associations were also observed between hippocampal volume and the Zhang and Phenoage epigenetic clocks within Amyloid-β positive individuals. However, these were not validated within the ADNI cohort. No associations between age acceleration and other Alzheimer’s disease-related phenotypes, including measures of cognition or brain Amyloid-β burden, were observed, and there was no association with longitudinal change in any phenotype. This study presents a link between age acceleration, as determined using DNA methylation, and hippocampal volume that was statistically significant across two highly characterised cohorts. The results presented in this study contribute to a growing literature that supports the role of epigenetic modifications in ageing and AD-related phenotypes

Uncovering the heterogeneity and temporal complexity of neurodegenerative diseases with Subtype and Stage Inference

The heterogeneity of neurodegenerative diseases is a key confound to disease understanding and treatment development, as study cohorts typically include multiple phenotypes on distinct disease trajectories. Here we introduce a machine-learning technique\u2014Subtype and Stage Inference (SuStaIn)\u2014able to uncover data-driven disease phenotypes with distinct temporal progression patterns, from widely available cross-sectional patient studies. Results from imaging studies in two neurodegenerative diseases reveal subgroups and their distinct trajectories of regional neurodegeneration. In genetic frontotemporal dementia, SuStaIn identifies genotypes from imaging alone, validating its ability to identify subtypes; further the technique reveals within-genotype heterogeneity. In Alzheimer\u2019s disease, SuStaIn uncovers three subtypes, uniquely characterising their temporal complexity. SuStaIn provides fine-grained patient stratification, which substantially enhances the ability to predict conversion between diagnostic categories over standard models that ignore subtype (p = 7.18 7 10 124 ) or temporal stage (p = 3.96 7 10 125 ). SuStaIn offers new promise for enabling disease subtype discovery and precision medicine