Search

Lipidomics is an emerging and promising omic that analyzes different lipid molecules in a biological sample. It is considered as a branch of metabolomics, which is defined as the comprehensive analysis of metabolites in a biological specimen. Nonetheless, in recent years lipidomics is being considered a distinct discipline in the biomedicine field. Lipids play important roles in many biological pathways and could work as biomarkers of disease or as therapeutic targets for treatment diseases. The major lipidomics strategies are shotgun lipidomics and liquid chromatography coupled with mass spectrometry. Gastrointestinal diseases such as irritable bowel syndrome or inflammatory bowel disease are chronic diseases that need non-invasive biomarkers for prognosis and diagnosis. Even more, patients with inflammatory bowel disease are at a significantly increased risk of colorectal cancer, principally resulting from the pro-neoplastic effects of chronic intestinal inflammation. Current screening methods utilized globally include sigmoidoscopy, or standard colonoscopy but it is important to develop non-invasive and accurate screening tools to facilitate early detection and precise staging of colorectal cancer. Disease progression and response to treatment may benefit also from the application of these potential new tools. This review is focused on studies that use lipidomics approaches to discover potential biomarkers for monitoring the mentioned intestinal diseases and, particularly, tumour progression.

En: Allergy e-ISSN:1398-9995, 2021, nov. 2, 14 pp Allergic diseases and asthma are heterogenous chronic inflammatory conditions with several distinct complex endotypes. Both environmental and genetic factors can influence the development and progression of allergy. Complex pathogenetic pathways observed in allergic disorders present a challenge in patient management and successful targeted treatment strategies. The increasing availability of high-throughput omics technologies, such as genomics, epigenomics, transcriptomics, proteomics, and metabolomics allows studying biochemical systems and pathophysiological processes underlying allergic responses. Additionally, omics techniques present clinical applicability by functional identification and validation of biomarkers. Therefore, finding molecules or patterns characteristic for distinct immune-inflammatory endotypes, can subsequently influence its development, progression, and treatment. There is a great potential to further increase the effectiveness of single omics approaches by integrating them with other omics, and nonomics data. Systems biology aims to simultaneously and longitudinally understand multiple layers of a complex and multifactorial disease, such as allergy, or asthma by integrating several, separated data sets and generating a complete molecular profile of the condition. With the use of sophisticated biostatistics and machine learning techniques, these approaches provide in-depth insight into individual biological systems and will allow efficient and customized healthcare approaches, called precision medicine. In this EAACI Position Paper, the Task Force “Omics technologies in allergic research” broadly reviewed current advances and applicability of omics techniques in allergic diseases and asthma research, with a focus on methodology and data analysis, aiming to provide researchers (basic and clinical) with a desk reference in the field. The potential of omics strategies in understanding disease pathophysiology and key tools to reach unmet needs in allergy precision medicine, such as successful patients’ stratification, accurate disease prognosis, and prediction of treatment efficacy and successful prevention measures are highlighted.

Prenatal stress (PS) impacts early postnatal behavioural and cognitive development. This process of 'fetal programming' is mediated by the effects of the prenatal experience on the developing hypothalamic-pituitary-adrenal (HPA) axis and autonomic nervous system (ANS). The HPA axis is a dynamic system regulating homeostasis, especially the stress response, and is highly sensitive to adverse early life experiences. We review the evidence for the effects of PS on fetal programming of the HPA axis and the ANS. We derive a multi-scale multi-species approach to devising preclinical and clinical studies to identify early non-invasively available pre- and postnatal biomarkers of these programming effects. Such approach would identify adverse postnatal brain developmental trajectories, a prerequisite for designing therapeutic interventions. The multiple scales include the biomarkers reflecting changes in the brain epigenome, metabolome, microbiome and the ANS activity gauged via an array of advanced non-invasively obtainable properties of fetal heart rate fluctuations. The proposed framework has the potential to reveal mechanistic links between maternal stress during pregnancy and changes across these physiological scales. Such biomarkers may hence be useful as early and non-invasive predictors of neurodevelopmental trajectories influenced by the PS. We conclude that studies into PS effects must be conducted on multiple scales derived from concerted observations in multiple animal models and human cohorts performed in an interactive and iterative manner and deploying machine learning for data synthesis, identification and validation of the best non-invasive biomarkers., Comment: Focused review, 13 pages, 5 figures

Fibrosis is the strongest predictor for disease-specific mortality in non-alcoholic fatty liver diseases (NAFLD), but the need for liver biopsy limits its diagnosis. We assessed the performance of plasma ficolin-2 (FCN-2) as a biomarker of fibrosis identified by an in silico discovery strategy. Two hundred and thirty-five morbidly obese (MO) subjects with biopsy-proven NAFLD stratified by fibrosis stage (F0, n = 44; F1, n = 134; F2, n = 46; F3/F4, n = 11) and 40 cirrhotic patients were enrolled. The cohort was subdivided into discovery (n = 76) and validation groups (n = 159). The plasma level of FCN-2 and other candidate markers was determined. FCN-2 was inversely correlated with the stage of liver fibrosis (ρ = −0.49, p < 0.001) independently of steatosis (p = 0.90), inflammation (p = 0.57), and ballooning (p = 0.59). In the global cohort, FCN-2 level decreased significantly in a stepwise fashion from F0/F1 (median 4753 ng/mL) to F2–F3–F4 (2760 ng/mL) and in cirrhotic subjects (1418 ng/mL). The diagnostic performance of FCN-2 in detecting F ≥ 2 was higher than other indexes (APRI, FIB-4) (AUROC 0.82, 0.68, and 0.6, respectively). The accuracy improved when combined with APRI score and HDL values (FCNscore, AUROC 0.85). Overall, the FCN-2 plasma level can accurately discriminate liver fibrosis status (minimal vs. moderate/advanced) significantly improving the fibrosis diagnostic algorithms.

IntroductionThe development of next generation sequencing technology has enabled cost-efficient, large scale, multiple ‘omic’ analysis, including epigenomic, genomic, metabolomic, phenomic, proteomic and transcriptomic research. These integrated approaches hold significant promise for rare disease research, with the potential to aid biomarker discovery, improve our understanding of disease pathogenesis and identify novel therapeutic targets. In this paper we outline a systematic approach for a scoping review designed to evaluate what primary research has been performed to date on multi-omics and rare disease.Methods and analysisThis protocol was designed using the Joanna Briggs Institute methodology for scoping reviews. Databases to be searched will include: MEDLINE, EMBASE, PubMed, Web of Science, Scopus and Google Scholar for primary studies relevant to the key terms ‘multi-omics’ and ‘rare disease’, published prior to 30thDecember 2018. Grey literature databases GreyLit and OpenGrey will also be searched, as well as reverse citation screening of relevant articles and forward citation searching using Web of Science Cited Reference Search Tool. Data extraction will be performed using customised forms and a narrative synthesis of the results will be presented.Ethics and disseminationAs a secondary analysis study with no primary data generated, this scoping review does not require ethical approval. We anticipate this review will highlight a gap in rare disease research and provide direction for novel research. The completed review will be submitted for publication in peer-reviewed journals and presented at relevant conferences discussing rare disease research and/or molecular strategies.

Precision medicine is a new paradigm that combines diagnostic, imaging, and analytical tools to produce accurate diagnoses and therapeutic interventions tailored to the individual patient. This approach stands in contrast to the traditional "one size fits all" concept, according to which researchers develop disease treatments and preventions for an "average" patient without considering individual differences. The "one size fits all" concept has led to many ineffective or inappropriate treatments, especially for pathologies such as Alzheimer's disease and cancer. Now, precision medicine is receiving massive funding in many countries, thanks to its social and economic potential in terms of improved disease prevention, diagnosis, and therapy. Bioanalytical chemistry is critical to precision medicine. This is because identifying an appropriate tailored therapy requires researchers to collect and analyze information on each patient's specific molecular biomarkers (e.g., proteins, nucleic acids, and metabolites). In other words, precision diagnostics is not possible without precise bioanalytical chemistry. This Trend article highlights some of the most recent advances, including massive analysis of multilayer omics, and new imaging technique applications suitable for implementing precision medicine. Graphical abstract Precision medicine combines bioanalytical chemistry, molecular diagnostics, and imaging tools for performing accurate diagnoses and selecting optimal therapies for each patient.

Maternal thromboembolism and a spectrum of placenta-mediated complications including the pre-eclampsia syndromes, fetal growth restriction, fetal loss, and abruption manifest a shared etiopathogenesis and predisposing risk factors. Furthermore, these maternal and fetal complications are often linked to subsequent maternal health consequences that comprise the metabolic syndrome, namely, thromboembolism, chronic hypertension, and type II diabetes. Traditionally, several lines of evidence have linked vasoconstriction, excessive thrombosis and inflammation, and impaired trophoblast invasion at the uteroplacental interface as hallmark features of the placental complications. "Omic" technologies and biomarker development have been largely based upon advances in vascular biology, improved understanding of the molecular basis and biochemical pathways responsible for the clinically relevant diseases, and increasingly robust large cohort and/or registry based studies. Advances in understanding of innate and adaptive immunity appear to play an important role in several pregnancy complications. Strategies aimed at improving prediction of these pregnancy complications are often incorporating hemodynamic blood flow data using non-invasive imaging technologies of the utero-placental and maternal circulations early in pregnancy. Some evidence suggests that a multiple marker approach will yield the best performing prediction tools, which may then in turn offer the possibility of early intervention to prevent or ameliorate these pregnancy complications. Prediction of maternal cardiovascular and non-cardiovascular consequences following pregnancy represents an important area of future research, which may have significant public health consequences not only for cardiovascular disease, but also for a variety of other disorders, such as autoimmune and neurodegenerative diseases.