Prediction of pneumoconiosis by serum and urinary biomarkers in workers exposed to asbestos-contaminated minerals

Abstract

Workers processing nephrite, antigorite, or talc may be exposed to paragenetic asbestos minerals. An effective screening method for pneumoconiosis in workers exposed to asbestos-contaminated minerals is still lacking. The objective of this study was to assess the diagnostic accuracy of serum and urinary biomarkers for pneumoconiosis in workers exposed to asbestos-contaminated minerals. We conducted a case-control study in a cohort of stone craft workers in Hualien, where asbestos, nephrite, antigorite, and talc are produced. A total of 140 subjects were screened between March 2013 and July 2014. All subjects received a questionnaire survey and a health examination that included a physical examination; chest X-ray; and tests for standard pulmonary function, fractional exhaled nitric oxide, serum soluble mesothelin-related peptide (SMRP), fibulin-3, carcinoembryonic antigen (CEA), and urinary 8-Oxo-2'-deoxyguanosine (8-OHdG)/creatinine. After excluding subjects with uraemia and chronic obstructive pulmonary disease (COPD), we included 48 subjects with pneumoconiosis and 90 control subjects without pneumoconiosis for analysis. In terms of occupational history, 43/48 (90%) case subjects and 68% (61/90) of the control subjects had processed asbestos-contaminated minerals, including nephrite, antigorite, and talc. The case group had decreased pulmonary function in forced vital capacity (FVC), forced expiratory volume in one second, and forced expiratory flow between 25% and 75% of the FVC. The levels of SMRP, fibulin-3, urinary 8-OHdG/creatinine, and CEA were higher in the case group than in the control group. Subjects exposed to nephrite had significantly higher SMRP levels (0.84 ± 0.52 nM) than subjects exposed to other types of minerals (0.60 ± 0.30 nM). A dose-response relationship was observed between the SMRP level and the severity of pneumoconiosis. Machine learning algorithms, including variables of sex, age, SMRP, fibulin-3, CEA, and 8-OHdG/creatinine, can predict pneumoconiosis with high accuracy. The areas under the receiver operating characteristic curves ranged from 0.7 to 1.0. We suggest that SMRP and fibulin-3 could be used as biomarkers of pneumoconiosis in workers exposed to asbestos-contaminated minerals.

Mesothelioma carcinogenesis of chrysotile and forsterite compared and validated by intraperitoneal injection in rat

“…Measuring 8-OHdG concentrations in white blood cells 25,26) and urine 27,28) of occupationally asbestos-exposed individuals is useful for assessing oxidative DNA damage. We have also reported that 8-OHdG effectively assesses lung injury (sustained inflammation) caused by chrysotile 21) .…”

“…More research is needed to conclude mesothelioma carcinogenesis concerning heating products of chrysotile. Currently, the technique for the clinical diagnosis of malignant mesothelioma caused by chrysotile exposure has advanced, and tests for 8-hydroxy-2′-deoxyguanosine (8-OHdG) [25][26][27][28] , serum N-ERC/mesothelin 29,30) , and CDKN2A/p16 gene 31,32) deletion have been reported to be effective. Therefore, these testing techniques may be useful for evaluating mesothelioma carcinogenesis using chrysotile heating products.…”

The Interstitial Emergence of Labor NGO Activism in China and Its Contradicting Institutionalization, 1996–2020

“…Several influential media reports were publicized. Among them, those arousing the most heated discussions was a report on the miserable living condition of rural migrant workers who suffered from pneumoconiosis (Yang 2009). To pacify the public anger, the state later incorporated the "pay in advance" suggestion in the Social Insurance Law.…”

Computer-Aided Diagnosis of Coal Workers’ Pneumoconiosis in Chest X-ray Radiographs Using Machine Learning: A Systematic Literature Review

“…There are several reviews on pneumoconiosis among coal miners; most of them discussed the prevalence, risk factors, survival rate, and prevention of CWP based on the pathological findings [ 7 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 ]. The past CAD studies of CWP disease indicate no significant review of machine learning applications that might help improve future work in the area.…”