Association of urinary arsenic concentration with incident diabetes was examined in American Indians from Arizona who have a high prevalence of type 2 diabetes and were screened for diabetes between 1982 and 2007. The population resides where drinking water contains arsenic at concentrations above federally recommended limits. A total of 150 nondiabetic subjects aged ≥25 years who subsequently developed type 2 diabetes were matched by year of examination and sex to 150 controls who remained nondiabetic for ≥10 years. Total urinary arsenic concentration, adjusted for urinary creatinine level, ranged from 6.6 µg/L to 123.1 µg/L, and inorganic arsenic concentration ranged from 0.1 µg/L to 36.0 µg/L. In logistic regression models adjusted for age, sex, body mass index, and urinary creatinine level, the odds ratios for incident diabetes were 1.11 (95% confidence interval (CI): 0.79, 1.57) and 1.16 (95% CI: 0.89, 1.53) for a 2-fold increase in total arsenic and inorganic arsenic, respectively. Categorical analyses suggested a positive relationship between quartiles of inorganic arsenic and incident diabetes (P = 0.056); post-hoc comparison of quartiles 2-4 with quartile 1 revealed 2-fold higher odds of diabetes in the upper quartiles (OR = 2.14, 95% CI: 1.19, 3.85). Modestly elevated exposure to inorganic arsenic may predict type 2 diabetes in American Indians. Larger studies that include measures of speciated arsenic are required for confirmation.
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http://dx.doi.org/10.1093/aje/kws329 | DOI Listing |
Sci Rep
January 2025
School of Sports and Health, Nanjing Sport Institute, Nanjing, China.
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Broad Institute of MIT and Harvard, Cambridge, MA, USA.
A key challenge of the modern genomics era is developing empirical data-driven representations of gene function. Here we present the first unbiased morphology-based genome-wide perturbation atlas in human cells, containing three genome-wide genotype-phenotype maps comprising CRISPR-Cas9-based knockouts of >20,000 genes in >30 million cells. Our optical pooled cell profiling platform (PERISCOPE) combines a destainable high-dimensional phenotyping panel (based on Cell Painting) with optical sequencing of molecular barcodes and a scalable open-source analysis pipeline to facilitate massively parallel screening of pooled perturbation libraries.
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January 2025
Food Is Medicine Institute, Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA.
Sci Rep
January 2025
Department of Endocrinology and Metabolism, Affiliated Hospital of Southwest Medical University, Luzhou, 646000, China.
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