Tumor microbial diversity and compositional differences among women in Botswana with high-grade cervical dysplasia and cervical cancer

IntroductionWe characterized the cervical 16S rDNA microbiome of patients in Botswana with high-grade cervical dysplasia and locally advanced cervical cancer.MethodsThis prospective study included 31 patients: 21 with dysplasia and 10 with cancer. The Shannon diversity index was used to evaluate alpha (intra-sample) diversity, while the UniFrac (weighted and unweighted) and Bray–Curtis distances were employed to evaluate beta (inter-sample) diversity. The relative abundance of microbial taxa was compared among samples using linear discriminant analysis effect size.ResultsAlpha diversity was significantly higher in patients with cervical cancer than in patients with cervical dysplasia (P<0.05). Beta diversity also differed significantly (weighted UniFrac Bray–Curtis, P<0.01). Neither alpha diversity (P=0.8) nor beta diversity (P=0.19) varied by HIV status. The results of linear discriminant analysis effect size demonstrated that multiple taxa differed significantly between patients with cervical dysplasia vs cancer. Lachnospira bacteria (in the Clostridia class) were particularly enriched among cervical dysplasia patients, while Proteobacteria (members of the Firmicutes phyla and the Comamonadaceae family) were enriched in patients with cervical cancer.DiscussionThe results of our study suggest that differences exist in the diversity and composition of the cervical microbiota between patients with cervical dysplasia and patients with cervical cancer in Botswana. Additional studies are warranted to validate these findings and elucidate their clinical significance among women living in sub-Saharan Africa, as well as other regions of the world.

Download Full-text

Colorectal Cancer Classification and Survival Analysis Based on an Integrated RNA and DNA molecular signature

Current Bioinformatics ◽

10.2174/1574893615999200711170445 ◽

2020 ◽

Vol 15 ◽

Author(s):

Mohanad Mohammed ◽

Henry Mwambi ◽

Bernard Omolo

Keyword(s):

Colorectal Cancer ◽

Survival Analysis ◽

Discriminant Analysis ◽

Linear Discriminant Analysis ◽

Negative Binomial ◽

Sub Saharan Africa ◽

Support Vector ◽

Mutation Status ◽

Linear Discriminant ◽

Rnaseq Data

Background: Colorectal cancer (CRC) is the third most common cancer among women and men in the USA, and recent studies have shown an increasing incidence in less developed regions, including Sub-Saharan Africa (SSA). We developed a hybrid (DNA mutation and RNA expression) signature and assessed its predictive properties for the mutation status and survival of CRC patients. Methods: Publicly-available microarray and RNASeq data from 54 matched formalin-fixed paraffin-embedded (FFPE) samples from the Affymetrix GeneChip and RNASeq platforms, were used to obtain differentially expressed genes between mutant and wild-type samples. We applied the support-vector machines, artificial neural networks, random forests, k-nearest neighbor, naïve Bayes, negative binomial linear discriminant analysis, and the Poisson linear discriminant analysis algorithms for classification. Cox proportional hazards model was used for survival analysis. Results: Compared to the genelist from each of the individual platforms, the hybrid genelist had the highest accuracy, sensitivity, specificity, and AUC for mutation status, across all the classifiers and is prognostic for survival in patients with CRC. NBLDA method was the best performer on the RNASeq data while the SVM method was the most suitable classifier for CRC across the two data types. Nine genes were found to be predictive of survival. Conclusion: This signature could be useful in clinical practice, especially for colorectal cancer diagnosis and therapy. Future studies should determine the effectiveness of integration in cancer survival analysis and the application on unbalanced data, where the classes are of different sizes, as well as on data with multiple classes.

Download Full-text

IDDF2020-ABS-0025 The role of gut microbiota in clinical complications and treatment response in alcoholic hepatitis – a CIRCOS®, linear discriminant analysis effect size biomarker and CONET® co-occurrence network analysis

10.1136/gutjnl-2020-iddf.34 ◽

2020 ◽

Author(s):

Cyriac Philips ◽

Karthik Ganesan ◽

Shatakshi Ranade ◽

Varun Chopra ◽

Kunal Patil ◽

...

Keyword(s):

Discriminant Analysis ◽

Network Analysis ◽

Gut Microbiota ◽

Linear Discriminant Analysis ◽

Effect Size ◽

Alcoholic Hepatitis ◽

Hepatitis A ◽

Linear Discriminant ◽

Clinical Complications

Download Full-text

Effect Size Estimation and Misclassification Rate Based Variable Selection in Linear Discriminant Analysis

Journal of Data Science ◽

10.6339/jds.2013.11(3).1185 ◽

2021 ◽

Vol 11 (3) ◽

pp. 537-558

Author(s):

Bernd Klaus

Keyword(s):

Discriminant Analysis ◽

Variable Selection ◽

Linear Discriminant Analysis ◽

Effect Size ◽

Misclassification Rate ◽

Size Estimation ◽

Linear Discriminant ◽

Effect Size Estimation

Download Full-text

Altered Airway Microbiota Composition in Patients With Pulmonary Hypertension

Hypertension ◽

10.1161/hypertensionaha.120.15025 ◽

2020 ◽

Vol 76 (5) ◽

pp. 1589-1599 ◽

Cited By ~ 1

Author(s):

Chenting Zhang ◽

Tingting Zhang ◽

Wenju Lu ◽

Xin Duan ◽

Xiaoyun Luo ◽

...

Keyword(s):

Pulmonary Hypertension ◽

Discriminant Analysis ◽

Respiratory Tract ◽

Linear Discriminant Analysis ◽

Effect Size ◽

Bacterial Invasion ◽

Microbiota Composition ◽

Upper Respiratory Tract ◽

Pharyngeal Swab ◽

Linear Discriminant

Alteration in microbiota composition of respiratory tract has been reported in the progression of many chronic lung diseases, yet, the correlation and causal link between respiratory tract microbiota and the disease development of pulmonary hypertension (PH) remain largely unknown. This study aims to define and compare the respiratory microbiota composition in pharyngeal swab samples between patients with PH and reference subjects. A total of 118 patients with PH and 79 reference subjects were recruited, and the pharyngeal swab samples were collected to sequence the 16S ribosomal RNA (16S rRNA) V3-V4 region of respiratory microbiome. The relative abundances in patients with PH were profoundly different from reference subjects. The Ace and Sobs indexes indicated that the microbiota richness of pharynx value is significantly higher; while the community diversity value is markedly lower in patients with PH, comparing to those of the reference subjects. The microbiota on pharynx showed a different profile between the 2 groups by principal component analysis. The linear discriminant analysis effect size also revealed a significantly higher proportion of Streptococcus , Lautropia , and Ralstonia in patients with PH than reference subjects. The linear discriminant analysis effect size output, which represents the microbial gene functions, suggest genes related to bacterial invasion of epithelial cells, bacterial toxins were enhanced, while genes related to energy metabolism, protein digestion and absorption, and cell division pathways were attenuated in patients with PH versus reference subjects. In summary, our study reports the first systematic definition and divergent profile of the upper respiratory tract microbiota between patients with PH and reference subjects.

Download Full-text

An Integrated RNA and DNA Molecular Signature for Colorectal Cancer Classification

10.21203/rs.2.20271/v1 ◽

2020 ◽

Author(s):

Mohanad Mohammed ◽

Henry Mwambi ◽

Bernard Omolo

Keyword(s):

Colorectal Cancer ◽

Discriminant Analysis ◽

Linear Discriminant Analysis ◽

Negative Binomial ◽

Sub Saharan Africa ◽

Molecular Signature ◽

Support Vector ◽

Wild Type ◽

Mutation Status ◽

Linear Discriminant

Abstract Background: Colorectal cancer (CRC) is the third most common cancer among women and men in the USA and recent studies have shown an increasing incidence in less developed regions such as Sub-Saharan Africa (SSA). The KRAS gene is mutated in 40% of the CRC cases and hence the RAS pathway activation has become a major focus of drug targeting efforts. However, nearly 60% of patients with wild-type KRAS fail to respond to RAS-targeted therapies, for example the anti-epithelial growth factor receptor inhibitor (EGFRi) combination therapies. Thus, there is a need to develop more reliable molecular signatures to better predict mutation status. In this study, we develop a hybrid (DNA mutation and RNA expression) signature and assess its predictive properties for the mutation status and survival of CRC patients. Methods: Publicly-available microarray and RNASeq data from 54 matched formalin-fixed paraffin embedded (FFPE) samples from the Affymetrix GeneChip and RNASeq platforms, were used to obtain differentially expressed genes between mutant and wild-type samples. For classification, the support-vector machines, artificial neural networks, random forests, k-nearest neighbor, naïve Bayes, negative binomial linear discriminant analysis, and the Poisson linear discriminant analysis algorithms were employed. Results: Compared to the genelist from each of the individual platforms, the hybrid genelist had the highest accuracy, sensitivity, specificity and AUC for mutation status, across all the classifiers, and is prognostic for survival in patients with CRC. Conclusions: This signature could be useful in clinical practice, especially for colorectal cancer diagnosis and therapy.

Download Full-text

Increased Fecal Lactobacillus Is Associated With a Positive Glucose Hydrogen Breath Test in Bangladeshi Children

Open Forum Infectious Diseases ◽

10.1093/ofid/ofz266 ◽

2019 ◽

Vol 6 (7) ◽

Author(s):

Jeffrey R Donowitz ◽

Hardik I Parikh ◽

Mami Taniuchi ◽

Carol A Gilchrist ◽

Rashidul Haque ◽

...

Keyword(s):

Discriminant Analysis ◽

Linear Discriminant Analysis ◽

Low Income ◽

Effect Size ◽

Breath Test ◽

Bacterial Overgrowth ◽

Hydrogen Breath Test ◽

Noninvasive Test ◽

Linear Discriminant ◽

Breath Testing

Abstract Background Glucose hydrogen breath testing is a noninvasive test for small intestine bacterial overgrowth (SIBO). A positive glucose hydrogen breath test is common in children from low-income countries and has been found to be associated with malnutrition as measured by stunted growth. The microbiome associated with positive breath testing is relatively unstudied. Methods We performed 16 S V4 rDNA microbiome analysis on the stool of 90 Bangladeshi children aged 2 years from an impoverished neighborhood who were tested at the same time for SIBO by glucose hydrogen breath testing. Data were analyzed by linear discriminant analysis effect size with SIBO as the outcome. Any selected genera were tested individually by Wilcoxon’s rank-sum test to ensure that linear discriminant analysis effect size results were not outlier-skewed. Results Linear discriminant analysis effect size analysis identified Lactobacillus (linear discriminate analysis score, 4.59; P = .03) as over-represented in 15 out of the 90 children who were SIBO positive. Conclusions These results suggest that glucose hydrogen breath test positivity in children from low-income settings may be due to an upper intestinal Lactobacillus bloom, potentially explaining the association of SIBO with the gut damage and inflammation that leads to malnutrition.

Download Full-text