Humans are constantly exposed to a wide range of reactive and toxic chemicals from the different sources in everyday life. Identification of the exposed chemical helps in the detection and understanding the exposure associated adverse health effects. Covalent adducts of proteins and DNA formed after xenobiotics exposure may serve as readily measurable indicators of these exposures. Measuring the exposed chemicals with focus on adducts resulting from the nucleophilic interactions with blood proteins is useful in the development of diagnostic markers. Particularly, the most abundant proteins such as albumin and hemoglobin acts as dominant scavengers for many reactive chemicals in blood and can serve as excellent diagnostic candidates to determine the type of chemical exposure. This review focuses on the potential application of an adductomics approach for the screening of bimolecular adducts of chemical warfare agents (CWAs). Recent incidents of CWAs use in Syria, Malaysia, and the UK illustrate the continuing threat of chemical warfare agents in the modern world. Detection of CWAs and their metabolites in blood or in other body fluids of victims depends on immediate access to victims. Concentrations of intact CWAs in body fluids of surviving victims may decline rapidly within a few days. Certain CWAs, particularly nerve agents and vesicants, form covalent bonds with certain amino acids to form CWA-protein adducts. Proteins that are abundant in the blood, including albumin and hemoglobin, may carry these adducts longer after the original exposure. We searched MEDLINE and ISI Web of Science databases using the key terms "adductomics" "adducts of CWAs," "CWAs adducts detection in the biological samples," "protein adducts of CWAs," alone and in combination with the keywords "detection" "intoxication" "exposure" "adverse effects" and "toxicity." We also included non-peer-reviewed sources such as text books, relevant newspaper reports, and applicable Internet resources. We screened bibliographies of identified articles for additional relevant studies including non-indexed reports. These searches produced 1931 citations of which only relevant and nonduplicate citations were considered for this review. The analysis of biomedical samples has several purposes including detecting and identifying the type of chemical agent exposed, understanding the biological mechanism, assists in giving adequate treatment, determining the cause of death and providing evidence in a court of justice for forensic investigations. Rapid advances in the mass spectrometry to acquire high-quality data with greater resolution enabled the analysis of protein and DNA adducts of xenobiotics including CWAs and place the rapidly advancing 'adductomics' next to the other "-omics" technologies. Adductomics can serve as a powerful bioanalytical tool for the verification of CWAs exposure. This review mostly describes the protein adducts for nerve agents and vesicants, outlines the procedures for measuring adducts, and suggests the evolving (or future) use of adducts in the detection and verification of CWAs.
The most important factor that complicates the work of dysmorphologists is the significant phenotypic variability of the human face. Next-Generation Phenotyping (NGP) tools that assist clinicians with recognizing characteristic syndromic patterns are particularly challenged when confronted with patients from populations different from their training data. To that end, we systematically analyzed the impact of genetic ancestry on facial dysmorphism. For that purpose, we established the GestaltMatcher Database (GMDB) as a reference dataset for medical images of patients with rare genetic disorders from around the world. We collected 10,980 frontal facial images - more than a quarter previously unpublished - from 8,346 patients, representing 581 rare disorders. Although the predominant ancestry is still European (67%), data from underrepresented populations have been increased considerably via global collaborations (19% Asian and 7% African). This includes previously unpublished reports for more than 40% of the African patients. The NGP analysis on this diverse dataset revealed characteristic performance differences depending on the composition of training and test sets corresponding to genetic relatedness. For clinical use of NGP, incorporating non-European patients resulted in a profound enhancement of GestaltMatcher performance. The top-5 accuracy rate increased by +11.29%. Importantly, this improvement in delineating the correct disorder from a facial portrait was achieved without decreasing the performance on European patients. By design, GMDB complies with the FAIR principles by rendering the curated medical data findable, accessible, interoperable, and reusable. This means GMDB can also serve as data for training and benchmarking. In summary, our study on facial dysmorphism on a global sample revealed a considerable cross ancestral phenotypic variability confounding NGP that should be counteracted by international efforts for increasing data diversity. GMDB will serve as a vital reference database for clinicians and a transparent training set for advancing NGP technology.
The most important factor that complicates the work of dysmorphologists is the significant phenotypic variability of the human face. Next-Generation Phenotyping (NGP) tools that assist clinicians with recognizing characteristic syndromic patterns are particularly challenged when confronted with patients from populations different from their training data. To that end, we systematically analyzed the impact of genetic ancestry on facial dysmorphism. For that purpose, we established the GestaltMatcher Database (GMDB) as a reference dataset for medical images of patients with rare genetic disorders from around the world. We collected 10,980 frontal facial images - more than a quarter previously unpublished - from 8,346 patients, representing 581 rare disorders. Although the predominant ancestry is still European (67%), data from underrepresented populations have been increased considerably via global collaborations (19% Asian and 7% African). This includes previously unpublished reports for more than 40% of the African patients. The NGP analysis on this diverse dataset revealed characteristic performance differences depending on the composition of training and test sets corresponding to genetic relatedness. For clinical use of NGP, incorporating non-European patients resulted in a profound enhancement of GestaltMatcher performance. The top-5 accuracy rate increased by +11.29%. Importantly, this improvement in delineating the correct disorder from a facial portrait was achieved without decreasing the performance on European patients. By design, GMDB complies with the FAIR principles by rendering the curated medical data findable, accessible, interoperable, and reusable. This means GMDB can also serve as data for training and benchmarking. In summary, our study on facial dysmorphism on a global sample revealed a considerable cross ancestral phenotypic variability confounding NGP that should be counteracted by international efforts for increasing data diversity. GMDB will serve as a vital reference database for clinicians and a transparent training set for advancing NGP technology.