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SAN DIEGO – A new scoring system based on a set of 18 informative genes was sufficient to diagnose cases of eosinophilic gastritis, results from a molecular analysis showed.
The system, known as EG diagnostic panel 18 (EGDP18), “can provide clinicians with a better diagnostic classification of ambiguous cases of eosinophilic gastritis, indicating a strong correlation with disease severity,” lead study author Tetsuo Shoda, MD, PhD, said at the annual Digestive Disease Week®.“The EG molecular profile also strongly correlates with particular endoscopic and histological features, thus providing insight into pathogenesis for EG.”
In an effort to develop an EG diagnostic panel, to validate its utility for EG diagnosis and management, and to better understand disease pathogenesis, Dr. Shoda and his colleagues used RNA sequencing to generate genome-wide gene expression profiles from gastric biopsies. Next, they developed an EG diagnostic panel focusing on a set of 48 informative genes, and analyzed its performance in a discovery cohort (55 EG and 39 controls) and subsequently an independent validation cohort (67 EG and 27 controls). The EGDP score was calculated by summation of delta CT values of the most highly dysregulated 18 genes. For diagnosis, the researchers calculated the area under the receiver operating characteristic curve (AUC), and used Spearman correlation to analyze associations.
Dr. Shoda, a research fellow at Cincinnati Children’s Hospital Medical Center, reported that the EGDP18 score identified active EG patients in both cohorts (P less than .0001, AUC equal to or greater than 0.95). In the discovery cohort, a score of less than zero resulted in a sensitivity of 95.2%, a specificity of 100%, a positive predictive value of 100%, and a negative predictive value of 95.8%. In the validation cohort, a score of less than zero resulted in a sensitivity of 88.9%, a specificity of 100%, a positive predictive value of 100%, and a negative predictive value of 94.1%.
The researchers observed a significant inverse correlation between the EGDP18 score and gastric eosinophil counts cross-sectionally and longitudinally. The score also showed comparable levels and high correlation between the gastric antrum and body. In addition, when analyzed by EGDP18 score, 63% of ambiguous tissue eosinophils were found to be molecularly equivalent to active EG, “suggesting the capacity to offer an objective cutoff for EG diagnosis,” Dr. Shoda said.
The researchers reported having no financial disclosures.
SOURCE: Shoda T et al. DDW 2019, Abstract 165. doi: 10.1016/S0016-5085(19)36878-7.
SAN DIEGO – A new scoring system based on a set of 18 informative genes was sufficient to diagnose cases of eosinophilic gastritis, results from a molecular analysis showed.
The system, known as EG diagnostic panel 18 (EGDP18), “can provide clinicians with a better diagnostic classification of ambiguous cases of eosinophilic gastritis, indicating a strong correlation with disease severity,” lead study author Tetsuo Shoda, MD, PhD, said at the annual Digestive Disease Week®.“The EG molecular profile also strongly correlates with particular endoscopic and histological features, thus providing insight into pathogenesis for EG.”
In an effort to develop an EG diagnostic panel, to validate its utility for EG diagnosis and management, and to better understand disease pathogenesis, Dr. Shoda and his colleagues used RNA sequencing to generate genome-wide gene expression profiles from gastric biopsies. Next, they developed an EG diagnostic panel focusing on a set of 48 informative genes, and analyzed its performance in a discovery cohort (55 EG and 39 controls) and subsequently an independent validation cohort (67 EG and 27 controls). The EGDP score was calculated by summation of delta CT values of the most highly dysregulated 18 genes. For diagnosis, the researchers calculated the area under the receiver operating characteristic curve (AUC), and used Spearman correlation to analyze associations.
Dr. Shoda, a research fellow at Cincinnati Children’s Hospital Medical Center, reported that the EGDP18 score identified active EG patients in both cohorts (P less than .0001, AUC equal to or greater than 0.95). In the discovery cohort, a score of less than zero resulted in a sensitivity of 95.2%, a specificity of 100%, a positive predictive value of 100%, and a negative predictive value of 95.8%. In the validation cohort, a score of less than zero resulted in a sensitivity of 88.9%, a specificity of 100%, a positive predictive value of 100%, and a negative predictive value of 94.1%.
The researchers observed a significant inverse correlation between the EGDP18 score and gastric eosinophil counts cross-sectionally and longitudinally. The score also showed comparable levels and high correlation between the gastric antrum and body. In addition, when analyzed by EGDP18 score, 63% of ambiguous tissue eosinophils were found to be molecularly equivalent to active EG, “suggesting the capacity to offer an objective cutoff for EG diagnosis,” Dr. Shoda said.
The researchers reported having no financial disclosures.
SOURCE: Shoda T et al. DDW 2019, Abstract 165. doi: 10.1016/S0016-5085(19)36878-7.
SAN DIEGO – A new scoring system based on a set of 18 informative genes was sufficient to diagnose cases of eosinophilic gastritis, results from a molecular analysis showed.
The system, known as EG diagnostic panel 18 (EGDP18), “can provide clinicians with a better diagnostic classification of ambiguous cases of eosinophilic gastritis, indicating a strong correlation with disease severity,” lead study author Tetsuo Shoda, MD, PhD, said at the annual Digestive Disease Week®.“The EG molecular profile also strongly correlates with particular endoscopic and histological features, thus providing insight into pathogenesis for EG.”
In an effort to develop an EG diagnostic panel, to validate its utility for EG diagnosis and management, and to better understand disease pathogenesis, Dr. Shoda and his colleagues used RNA sequencing to generate genome-wide gene expression profiles from gastric biopsies. Next, they developed an EG diagnostic panel focusing on a set of 48 informative genes, and analyzed its performance in a discovery cohort (55 EG and 39 controls) and subsequently an independent validation cohort (67 EG and 27 controls). The EGDP score was calculated by summation of delta CT values of the most highly dysregulated 18 genes. For diagnosis, the researchers calculated the area under the receiver operating characteristic curve (AUC), and used Spearman correlation to analyze associations.
Dr. Shoda, a research fellow at Cincinnati Children’s Hospital Medical Center, reported that the EGDP18 score identified active EG patients in both cohorts (P less than .0001, AUC equal to or greater than 0.95). In the discovery cohort, a score of less than zero resulted in a sensitivity of 95.2%, a specificity of 100%, a positive predictive value of 100%, and a negative predictive value of 95.8%. In the validation cohort, a score of less than zero resulted in a sensitivity of 88.9%, a specificity of 100%, a positive predictive value of 100%, and a negative predictive value of 94.1%.
The researchers observed a significant inverse correlation between the EGDP18 score and gastric eosinophil counts cross-sectionally and longitudinally. The score also showed comparable levels and high correlation between the gastric antrum and body. In addition, when analyzed by EGDP18 score, 63% of ambiguous tissue eosinophils were found to be molecularly equivalent to active EG, “suggesting the capacity to offer an objective cutoff for EG diagnosis,” Dr. Shoda said.
The researchers reported having no financial disclosures.
SOURCE: Shoda T et al. DDW 2019, Abstract 165. doi: 10.1016/S0016-5085(19)36878-7.
REPORTING FROM DDW 2019