Comprehensive assessment of germline pathogenic variant detection in tumor-only sequencing.

BACKGROUND: Tumor-only sequencing, implemented for the identification of somatic variants, is oftentimes used for the detection of actionable germline variants. We sought to determine whether tumor-only sequencing assays are suitable for detection of actionable germline variants, given their importance for the delivery of targeted therapies and risk-reducing measures. PATIENTS AND METHODS: The detection of germline variants affecting moderate- and high-penetrance cancer susceptibility genes (CSGs) by tumor-only sequencing was compared to clinical germline testing in 21 333 cancer patients who underwent tumor and germline testing using the Food and Drug Administration (FDA)-authorized Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Targets (MSK-IMPACT) assay. Seven homologous recombination deficiency (HRD), two DNA damage response (DDR) and four mismatch repair (MMR) genes, as well as NF1, RB1 and TP53 were included in the analysis. FDA-authorized and New York State Department of Health-approved sequencing methods for germline, tumor/normal and tumor-only sequencing assays and analytical pipelines were employed. RESULTS: In patients who underwent tumor and germline sequencing, as compared to clinical genetic testing, tumor-only sequencing failed to detect 10.5% of clinically actionable pathogenic germline variants in CSGs, including 18.8%, 12.8% and 7.3% of germline variants in MMR, DDR and HRD genes, respectively. The sensitivity for detection of pathogenic germline variants by tumor-only sequencing was 89.5%. Whilst the vast majority of pathogenic germline exonic single-nucleotide variants (SNVs) and small indels were detected by tumor-only sequencing, large percentages of germline copy number variants, intronic variants and repetitive element insertions were not detected. CONCLUSIONS: Tumor-only sequencing is adequate for the detection of clinically actionable germline variants, particularly for SNVs and small indels; however, a small subset of alterations affecting HRD, DDR and MMR genes may not be detected optimally. Therefore, for high-risk patients with negative tumor-only sequencing results, clinical genetic testing could be considered given the impact of these variants on therapy and genetic counseling.

Precisión diagnóstica mejorada para la imagen de perfusión miocárdica usando redes neuronales artificiales en diferentes variables de entrada incluyendo datos clínicos y de cuantificación / Improved diagnostic accuracy for myocardial perfusion imaging using artificial neural networks on different input variables including clinical and quantification data

OBJETIVO: La precisión diagnóstica de la imagen de perfusión miocárdica (IPM) no es óptima para predecir el resultado de la angiografía. El objetivo del presente estudio es investigar la aplicación de la red neuronal artificial (RNA) para integrar los datos clínicos con el resultado y la cuantificación de la IPM. MÉTODOS: De 923 pacientes con IPM, se reclutaron 93 que se sometieron a angiografía. Se recogieron los datos clínicos, incluidos los factores de riesgo cardíaco, y se registraron los resultados de la IPM y la angiografía coronaria. Se calculó la cuantificación de las gráficas polares IPM (es decir, los recuentos de 20 segmentos de cada una de las gráficas polares de esfuerzo y de reposo) y la puntuación de Gensini de las angiografías. La RNA fue diseñada integrando datos clínicos y de cuantificación para predecir el resultado de la angiografía (normal vs. anormal), la enfermedad coronaria no obstructiva u obstructiva (EAC) y la puntuación de Gensini (≥10 y <10). Las RNA fueron diseñadas para predecir los resultados de la angiografía usando diferentes combinaciones de datos como sigue: informes de IPM, la cuantificación de 40 segmentos de diagramas polares de esfuerzo y reposo, y la cuantificación de estos 40 segmentos además de la edad, el sexo y el número de factores de riesgo. Se comparó el rendimiento diagnóstico de la IPM con diferentes RNA. RESULTADOS: La precisión de la IPM para predecir el resultado de la angiografía, la EAC obstructiva y la puntuación de Gensini aumentó del 81,7 al 92,9%, del 65,0 al 85,7% y del 50,5 al 92,9%, respectivamente, mediante la RNA con cuantificación y factores de riesgo clínicos. CONCLUSIÓN: La precisión diagnóstica de la IPM podría mejorarse mediante la RNA, utilizando datos clínicos y de cuantificación

OBJECTIVE: Diagnostic accuracy of myocardial perfusion imaging (MPI) is not optimal to predict the result of angiography. The current study aimed at investigating the application of artificial neural network (ANN) to integrate the clinical data with the result and quantification of MPI. METHODS: Out of 923 patients with MPI, 93 who underwent angiography were recruited. The clinical data including the cardiac risk factors were collected and the results of MPI and coronary angiography were recorded. The quantification of MPI polar plots (i. e. the counts of 20 segments of each stress and rest polar plots) and the Gensini score of angiographies were calculated. Feed-forward ANN was designed integrating clinical and quantification data to predict the result of angiography (normal vs. abnormal), non-obstructive or obstructive coronary artery disease (CAD), and Gensini score (≥10 and <10). The ANNs were designed to predict the results of angiography using different combinations of data as follows: reports of MPI, the counts of 40 segments of stress and rest polar plots, and the count of these 40 segments in addition to age, gender, and the number of risk factors. The diagnostic performance of MPI with different ANNs was compared. RESULTS: The accuracy of MPI to predict the result of angiography, obstructive CAD, and Gensini score increased from 81.7% to 92.9%, 65.0% to 85.7%, and 50.5% to 92.9%, respectively by ANN using counts and clinical risk factors. CONCLUSION: The diagnostic accuracy of MPI could be improved by ANN, using clinical and quantification data

Improved diagnostic accuracy for myocardial perfusion imaging using artificial neural networks on different input variables including clinical and quantification data. / Precisión diagnóstica mejorada para la imagen de perfusión miocárdica usando redes neuronales artificiales en diferentes variables de entrada incluyendo datos clínicos y de cuantificación.

OBJECTIVE: Diagnostic accuracy of myocardial perfusion imaging (MPI) is not optimal to predict the result of angiography. The current study aimed at investigating the application of artificial neural network (ANN) to integrate the clinical data with the result and quantification of MPI. METHODS: Out of 923 patients with MPI, 93 who underwent angiography were recruited. The clinical data including the cardiac risk factors were collected and the results of MPI and coronary angiography were recorded. The quantification of MPI polar plots (i.e. the counts of 20 segments of each stress and rest polar plots) and the Gensini score of angiographies were calculated. Feed-forward ANN was designed integrating clinical and quantification data to predict the result of angiography (normal vs. abnormal), non-obstructive or obstructive coronary artery disease (CAD), and Gensini score (≥10 and <10). The ANNs were designed to predict the results of angiography using different combinations of data as follows: reports of MPI, the counts of 40 segments of stress and rest polar plots, and the count of these 40 segments in addition to age, gender, and the number of risk factors. The diagnostic performance of MPI with different ANNs was compared. RESULTS: The accuracy of MPI to predict the result of angiography, obstructive CAD, and Gensini score increased from 81.7% to 92.9%, 65.0% to 85.7%, and 50.5% to 92.9%, respectively by ANN using counts and clinical risk factors. CONCLUSION: The diagnostic accuracy of MPI could be improved by ANN, using clinical and quantification data.

The efficacy of Helicobacter pylori eradication regimen with and without vitamin C supplementation.

BACKGROUND: Vitamin C in gastric juice and in vitro has been shown to inhibit the growth of Helicobacter pylori (H. pylori). AIMS: The purpose of this study was to investigate the effect of addition of vitamin C to eradication regimen on H. pylori eradication rate. PATIENTS: This randomised controlled clinical trial was conducted on 312 patients with H. pylori infection who had referred to the Taleghani Research Center of Gastroenterology and Liver Disease. METHODS: Patients were randomly divided into two groups. Group A patients (162 patients) received amoxicillin 1g and metronidazole 500 mg b.i.d., bismuth 240 mg b.i.d. and omeprazole 40 mg q.i.d. in two divided doses. Patients in group B (150 patients) received the same regimen plus 500 mg vitamin C per day. All patients received therapy for 2 weeks. Four weeks later all patients underwent urea breath test and results were compared. RESULTS: A total of 140 patients in group A and 141 in group B completed the study. On intention-to-treat analysis 48.8% of patients in group A in comparison to 78% in group B responded to eradication therapy and had negative urea breath test (p<0.0001). CONCLUSION: Addition of vitamin C to H. pylori treatment regimen of amoxicillin, metronidazole and bismuth can significantly increases H. pylori eradication rate.

Diagnosis and prevalence of enteropathogenic bacteria in children less than 5 years of age with acute diarrhea in Tehran children's hospitals.

INTRODUCTION: Acute diarrhea disease is the second cause of death among all infectious diseases in children younger than 5 years of age worldwide. The aim of this study was to employ a combination of biochemical, microbiological and molecular diagnostic techniques to investigate the stools of Iranian children with acute diarrhea for bacterial enteropathogens. METHOD: Diarrheagenic Escherichia coli, Shigella spp., Salmonella spp., Campylobacter spp. and Yersinia spp., were investigated from June 2003 to June 2005, in 1087 children less than 5 years old with acute diarrhea. Stool specimens from children were studied for enteropathogens both by standard culturing and molecular methods. This study was designed on hospital based. RESULT: The highest incidence values were found in the summer and in children less than 1-year-old (42.7%). The Pathogenic bacteria recovered out from fecal samples of 555 (55.1%) patients had the following profile: Shigella spp. (26.7%) was the most prevalent bacterial pathogen and Shiga-like toxin producing E. coli (STEC) and Enteroaggregative E. coli (EAEC) 105 (18.9%) and 92 (16.6%) had the second and third highest prevalence, respectively. Enteropathogenic E. coli (EPEC), Campylobacter, Salmonella and Enterotoxigenic E. coli (ETEC) were found in 70 (12.6%), 60 (10.8%), 42 (7.6%), and 38 (6.8%) positive samples, respectively. In this study neither Yersinia nor E. coli O157:H7 were found. Of the 30 co-infections detected, Shigella flexneri and Campylobacter jejuni accounted for more than 50%. CONCLUSION: Information about the prevalence of wide-range Shigella and STEC may facilitate the control and management of infant diarrhea diseases in Iran. The results of this study suggest that comprehensive surveys are needed in different parts of the country in order to identify the incidence of different enteropathogenic diarrhea, especially diarrheagenic E. coli in children in Iran.

Molecular epidemiology of hepatitis B virus in Iran.

Hepatitis B virus (HBV) infection is a major cause of liver disease worldwide. Eight genotypes and 24 subgenotypes of HBV have been identified. The aim of this study was to determine the distribution of HBV genotypes, subgenotypes and subtypes, and to understand HBV genetic variability in the HBV genome circulating in Iranian provinces. Two hundred and forty-nine sera from HBV-infected patients living in 25 provinces of Iran were collected (2004-2007). A part of the HBV S/pol and whole BCP/C genes were amplified, sequenced and then subjected to phylogenetic, recombination and genetic variability analysis. Results revealed genotype D of HBV in all samples and subgenotypes D1 (98.52%), D2 (0.74%) and D3 (0.74%) among Iranian patients living in different provinces of Iran. Subtypes ayw2 (94.4%), ayw1 (2.8%), ayw3 (2%) and ayw4 (0.4%) were deduced, on the basis of HBV small surface antigen (HBsAg) amino acid sequences. The mean percentage intra-genotypic distance of S plus core regions was 2.8%; the mean percentage inter-genotypic distance of this region between Iranian strains and genotype D isolates was 3.1%; and this rate for other genotypes was 5.2-11.4%. Various rates of point mutations have been found within different HBV genes, e.g. HBsAg (17.2%), precore-G1896A (59.5%) and Basal core promoter (BCP) double mutations (49.2%), whereas no recombination was found. In conclusion, these results indicate that the only genotype circulating in the provinces of Iran is genotype D. There exist high genetic variabilities in the S/pol and BCP/C regions among the Iranian HBV isolates.