Bioinformatic-driven search for metabolic biomarkers in disease

The search and validation of novel disease biomarkers requires the complementary power of professional study planning and execution, modern profiling technologies and related bioinformatics tools for data analysis and interpretation. Biomarkers have considerable impact on the care of patients and are urgently needed for advancing diagnostics, prognostics and treatment of disease. This survey article highlights emerging bioinformatics methods for biomarker discovery in clinical metabolomics, focusing on the problem of data preprocessing and consolidation, the data-driven search, verification, prioritization and biological interpretation of putative metabolic candidate biomarkers in disease. In particular, data mining tools suitable for the application to omic data gathered from most frequently-used type of experimental designs, such as case-control or longitudinal biomarker cohort studies, are reviewed and case examples of selected discovery steps are delineated in more detail. This review demonstrates that clinical bioinformatics has evolved into an essential element of biomarker discovery, translating new innovations and successes in profiling technologies and bioinformatics to clinical application

Reflection of neuroblastoma intratumor heterogeneity in the new OHC-NB1 disease model

Accurate modeling of intratumor heterogeneity presents a bottleneck against drug testing. Flexibility in a preclinical platform is also desirable to support assessment of different endpoints. We established the model system, OHC-NB1, from a bone marrow metastasis from a patient diagnosed with MYCN-amplified neuroblastoma and performed whole-exome sequencing on the source metastasis and the different models and passages during model development (monolayer cell line, 3D spheroid culture and subcutaneous xenograft tumors propagated in mice). OHC-NB1 harbors a MYCN amplification in double minutes, 1p deletion, 17q gain and diploid karyotype, which persisted in all models. A total of 80-540 single-nucleotide variants (SNVs) was detected in each sample, and comparisons between the source metastasis and models identified 34 of 80 somatic SNVs to be propagated in the models. Clonal reconstruction using the combined copy number and SNV data revealed marked clonal heterogeneity in the originating metastasis, with 4 clones being reflected in the model systems. The set of OHC-NB1 models represents 43% of somatic SNVs and 23% of the cellularity in the originating metastasis with varying clonal compositions, indicating that heterogeneity is partially preserved in our model system

A Pharmaceutical Paradigm for Cardiovascular Composite Risk Assessment Using Novel Radiogenomics Risk Predictors in Precision Explainable Artificial Intelligence Framework: Clinical Trial Tool

Cardiovascular disease (CVD) is challenging to diagnose and treat since symptoms appear late during the progression of atherosclerosis. Conventional risk factors alone are not always sufficient to properly categorize at-risk patients, and clinical risk scores are inadequate in predicting cardiac events. Integrating genomic-based biomarkers (GBBM) found in plasma/serum samples with novel non-invasive radiomics-based biomarkers (RBBM) such as plaque area, plaque burden, and maximum plaque height can improve composite CVD risk prediction in the pharmaceutical paradigm. These biomarkers consider several pathways involved in the pathophysiology of atherosclerosis disease leading to CVD.This review proposes two hypotheses: (i) The composite biomarkers are strongly correlated and can be used to detect the severity of CVD/Stroke precisely, and (ii) an explainable artificial intelligence (XAI)-based composite risk CVD/Stroke model with survival analysis using deep learning (DL) can predict in preventive, precision, and personalized (aiP3) framework benefiting the pharmaceutical paradigm.The PRISMA search technique resulted in 214 studies assessing composite biomarkers using radiogenomics for CVD/Stroke. The study presents a XAI model using AtheroEdgeTM 4.0 to determine the risk of CVD/Stroke in the pharmaceutical framework using the radiogenomics biomarkers.Our observations suggest that the composite CVD risk biomarkers using radiogenomics provide a new dimension to CVD/Stroke risk assessment. The proposed review suggests a unique, unbiased, and XAI model based on AtheroEdgeTM 4.0 that can predict the composite risk of CVD/Stroke using radiogenomics in the pharmaceutical paradigm

A Pharmaceutical Paradigm for Cardiovascular Composite Risk Assessment Using Novel Radiogenomics Risk Predictors in Precision Explainable Artificial Intelligence Framework: Clinical Trial Tool

Background: Cardiovascular disease (CVD) is challenging to diagnose and treat since symptoms appear late during the progression of atherosclerosis. Conventional risk factors alone are not always sufficient to properly categorize at-risk patients, and clinical risk scores are inadequate in predicting cardiac events. Integrating genomic-based biomarkers (GBBM) found in plasma/serum samples with novel non-invasive radiomics-based biomarkers (RBBM) such as plaque area, plaque burden, and maximum plaque height can improve composite CVD risk prediction in the pharmaceutical paradigm. These biomarkers consider several pathways involved in the pathophysiology of atherosclerosis disease leading to CVD. Objective: This review proposes two hypotheses: (i) The composite biomarkers are strongly correlated and can be used to detect the severity of CVD/Stroke precisely, and (ii) an explainable artificial intelligence (XAI)-based composite risk CVD/Stroke model with survival analysis using deep learning (DL) can predict in preventive, precision, and personalized (aiP 3 ) framework benefiting the pharmaceutical paradigm. Method: The PRISMA search technique resulted in 214 studies assessing composite biomarkers using radiogenomics for CVD/Stroke. The study presents a XAI model using AtheroEdge TM 4.0 to determine the risk of CVD/Stroke in the pharmaceutical framework using the radiogenomics biomarkers. Conclusions: Our observations suggest that the composite CVD risk biomarkers using radiogenomics provide a new dimension to CVD/Stroke risk assessment. The proposed review suggests a unique, unbiased, and XAI model based on AtheroEdge TM 4.0 that can predict the composite risk of CVD/Stroke using radiogenomics in the pharmaceutical paradigm

Potentially pathogenic Vibrio species in the Norwegian marine environment, characterisation of virulence and antibiotic resistance determinants

Masteroppgave i biologiBIO399MAMN-BI

DNA hydroxymethylation and improved growth of Nile tilapia (Oreochromis niloticus) during domestication

Doctoral thesis (PhD) - Nord University, 2020The worldwide demand for fish consumption is highly dependent on aquaculture production because commercial fishing reached its maximum exploitation since the 90’s. However, continued expansion of the aquaculture industry in a sustainable manner is dependent on several factors, including domestication of new species and establishment of selective breeding programmes. Domestication of new fish species is a rather complex and long process but the deployment of new molecular tools could improve and accelerate it through the holistic characterization of fish genomes. This thesis is based on the hypothesis that epigenetic mechanisms underlie genome-wide adaptation under captivity, since genetic mutations and allele shifts alone cannot explain the rapid transcriptomic changes of fish undergoing domestication. In a series of experiments, we investigated the role of DNA hydroxymethylation during the early stages of fish domestication, and its potential involvement in regulating somatic growth. At first, we discovered that the DNA hydroxymethylome in fast muscle changes rapidly within a single generation of domestication. As a result of our 5-hydroxymethylcytosine (5hmC) profiling at single nucleotide resolution, we were able to identify that 5hmCs are largely enriched within gene bodies, which supports the notion that they are functionally relevant epigenetic modifications. The annotation of differentially hydroxymethylated genes between wild and first-generation of fish under captivity revealed that the changes occurred primarily within genes involved in immunity, growth and neuronal activity. By comparing gene expression profiles in muscle between wild and first generation of Nile tilapia in captivity, we showed that immune-related genes were upregulated in the wild fish, while genes involved in metabolism and muscle-specific functions were downregulated. These findings revealed that the first generation of fish undergoing domestication is strongly influenced by the environmental conditions under captivity, namely the lack of pathogens and the optimal conditions of water temperature, oxygen, pH and diet. Thus, we provided for the first time a link between environmentally-mediated DNA hydroxymethylation and gene regulation in fish undergoing domestication. To further explore the connection between DNA hydroxymethylation and somatic growth, we compared the liver hydroxymethylomes of slow- and fast-growing full siblings and examined the 5hmC abundance in three major tissues that compose the somatotropic axis. Interestingly, we identified several differentially hydroxymethylated genes between slowand fast-growers. These genes were involved in signaling pathways related to cell growth, survival and proliferation such as the PI3K-Akt, the Ras- and Rho- protein signal transduction pathways. By comparing the DNA hydroxymethylomes among the muscle, liver and pituitary, we identified several differentially hydroxymethylated growth factors, receptors and enhancers with major implications in growth, metabolism and skeletal muscle development. Taken together, this thesis provides for the first time a direct link between DNA hydroxymethylation and fish domestication and associates epigenetic marks at single nucleotide resolution to somatic growth using cutting-edge molecular tools. When validated, these epigenetic markers can potentially improve current breeding strategies in aquaculture by providing a holistic approach for broodstock selection.publishedVersio