代谢组学分析技术在毒性生物标志物中的应用

代谢组学借鉴基因组学和蛋白质组学的科学思路,对机体内所有内源性小分子进行定量或定性分析,并探索内源性代谢物与机体生理病理变化的相互关系。分析对象多以分子质量1 ku以下的小分子。近年以来,代谢组学作为鉴定新的毒性生物标志物工具的巨大潜力已经被证实。通过非侵入性代谢组学分析鉴定哺乳动物中的生物标志物是特别有价值的工作。论文从代谢组学的研究平台、数据统计分析及其在毒性生物标志物的应用现状进行了综述。

蛋白质组学和代谢组学在间质性肺疾病研究中的应用

间质性肺疾病是一类异质性疾病,以炎症浸润、纤维化、细胞增殖等病理变化累及肺间质为共同特征。该病的临床病因目前尚未完全明确,尤其是在急性加重期,患者的预后往往较差。蛋白质组学和代谢组学联合使用,有希望成为筛选间质性肺疾病新型生物标志物的有力工具。本文综述了蛋白质组学和代谢组学技术在间质性肺疾病研究中的应用,以期明确当前的研究现状,并对未来的研究方向进行展望。

8-Hydroxydeoxyguanosine:Not mere biomarker for oxidative stress,but remedy for oxidative stress-implicated gastrointestinal diseases

Reactive oxygen species （ROS） attack guanine bases in DNA easily and form 8-hydroxydeoxyguanosine （8-OHdG）, which can bind to thymidine rather than cytosine, based on which, the level of 8-OHdG is gen- erally regarded as a biomarker of mutagenesis conse- quent to oxidative stress. For example, higher levels of 8-OHdG are noted in Helicobacter pylori-associated chronic atrophic gastritis as well as gastric cancer. However, we have found that exogenous 8-OHdG can paradoxically reduce ROS production, attenuate the nuclear factor-KB signaling pathway, and ameliorate the expression of proinflammatory mediators such as interleukin （IL）-I, IL-6, cyclo-oxygenase-2, and induc- ible nitric oxide synthase in addition to expression of nicotinamide adenine dinucleotide phosphate oxidase （NOX）-I, NOX organizer-1 and NOX activator-1 in vari- ous conditions of inflammation-based gastrointestinal （GI） diseases including gastritis, inflammatory bowel disease, pancreatitis, and even colitis-associated carci- nogenesis. Our recent finding that exogenous 8-OHdG was very effective in either inflammation-based or oxidative-stress-associated diseases of stress-related mucosal damage has inspired the hope that synthetic 8-OHdG can be a potential candidate for the treatment of inflammation-based GI diseases, as well as the pre- vention of inflammation-associated GI cancer. In this editorial review, the novel fact that exogenous 8-OHdG can be a functional molecule regulating oxidative- stress-induced gastritis through either antagonizing Rac-guanosine triphosphate binding or blocking the signals responsible for gastric inflammatory cascade is introduced.

Overview and developments in noninvasive diagnosis of nonalcoholic fatty liver disease

High prevalence of non-alcoholic fatty liver disease (NAFLD) and very diverse outcomes that are related to disease form and severity at presentation have made the search for noninvasive diagnostic tools in NAFLD one of the areas with most intense development in hepatology today.Various methods have been investigated in the recent years,including imaging methods like ultrasound and magnetic resonance imaging,different forms of liver stiffness measurement,various biomarkers of necroinflammatory processes (acute phase reactants,cytokines,markers of apoptosis),hyaluronic acid and other biomarkers of liver fibrosis.Multicomponent tests,scoring systems and diagnostic panels were also developed with the purposes of differentiating non-alcoholic steatohepatitis from simple steatosis or discriminating between various fibrosis stages.In all of the cases,performance of noninvasive methods was compared with liver biopsy,which is still considered to be a gold standard in diagnosis,but is by itself far from a perfect comparative measure.We present here the overview of the published data on various noninvasive diagnostic tools,some of which appear to be very promising,and we address as well some of still unresolved issues in this interesting field.

Novel biomarkers for cardiovascular risk prediction

Cardiovascular disease （CVD） is the leading cause of death and disability worldwide. The primary prevention of CVD is dependent upon the ability to identify high-risk individuals long before the development of overt events. This highlights the need for accurate risk strati- fication. An increasing number of novel biomarkers have been identified to predict cardiovascular events. Biomarkers play a critical role in the definition, prognostication, and decision-making regarding the management of cardiovascular events. This review focuses on a variety of promising biomarkers that provide diagnostic and prognostic information. The myocardial tissue-specific biomarker cardiac troponin, high- sensitivity assays for cardiac troponin, and heart-type fatty acid binding proteinall help diagnose myocardial infarction （MI） in the early hours following symptoms. Inflammatory markers such as growth differentiation factor-15, high-sensitivity C-reactive protein, fibrinogen, and uric acid predict MI and death. Pregnancy-associated plasma protein A, myeloperoxidase, and matrix metalloproteinases predict the risk of acute cor- onary syndrome. Lipoprotein-associated phospholipase A2 and secretory phospholipase A2 predict incident and recurrent cardiovascular events. Finally, elevated natriuretic peptides, ST2, endothelin-1, mid-regional-pro-adrenomedullin, copeptin, and galectin-3 have all been well validated to predict death and heart failure following a MI and provide risk stratification information for heart failure. Rapidly develop- ing new areas, such as assessment ofmicro-RNA, are also explored. All the biomarkers reflect different aspects of the development ofather- osclerosis.

microRNAs regulation and its role as biomarkers in diseases

MicroRNAs （miRNAs）, approximately 21 to 23 nucleotides （nt） in length, belong to a set of smal non-coding RNA molecules that were not thought to be functional until the recent decades. miRNAs play important roles in many diseases such as various kinds of cancers and immune disorders. Many studies have focused on the relationship between miRNAs and diseases. miRNAs are significant mediators in human growth and development and in the genesis and development of diseases. Almost 30% of the activity of protein-coding genes is forecasted to be regulated by miRNAs in mammals, and some miRNAs are regarded as potential therapeutic targets for various diseases. In this review, we outline some functions of miRNAs, especialy those related to diseases.

Advances and Challenges of Exosome Metabolomics in Body Fluids

Exosomes,ubiquitously present in body fluids,serve as non-invasive biomarkers for disease diagnosis,monitoring,and treatment.As intercellular messengers,exosomes encapsulate a rich array of proteins,nucleic acids,and metabolites,although most studies have primarily focused on proteins and RNA.Recently,exosome metabolomics has demonstrated clinical value and potential advantages in disease detection and pathophysiology,despite significant challenges,particularly in exosome isolation and metabolite detection.This review discusses the significant technical challenges in exosome isolation and metabolite detection,highlighting the advancements in these areas that support the clinical application of exosome metabolomics,and illustrates the potential of exosomal metabolites from various body fluids as biomarkers for early disease diagnosis and treatment.

Cardinal roles of miRNA in cardiac development and disease

MicroRNAs(miRNAs) are small noncoding RNAs that are emerging as pivotal modulators in virtually all aspects of cardiac biology,from cardiac development to cardiomyocyte survival and hypertrophy.The miRNA profiling,following gain-and loss-of-function studies using in vitro and in vivo models,has identified wide-ranging functions for miRNAs in the heart,providing new perspectives on their contributions to cardiac pathogenesis,and revealing potential therapeutic targets and diagnostic biomarkers.This review summarizes current progress in regulation of miRNAs in heart development and disease.

Dynamic optimal strategy for monitoring disease recurrence

Surveillance to detect cancer recurrence is an important part of care for cancer survivors.In this paper we discuss the design of optimal strategies for early detection of disease recurrence based on each patient's distinct biomarker trajectory and periodically updated risk estimated in the setting of a prospective cohort study.We adopt a latent class joint model which considers a longitudinal biomarker process and an event process jointly,to address heterogeneity of patients and disease,to discover distinct biomarker trajectory patterns,to classify patients into different risk groups,and to predict the risk of disease recurrence.The model is used to develop a monitoring strategy that dynamically modifies the monitoring intervals according to patients' current risk derived from periodically updated biomarker measurements and other indicators of disease spread.The optimal biomarker assessment time is derived using a utility function.We develop an algorithm to apply the proposed strategy to monitoring of new patients after initial treatment.We illustrate the models and the derivation of the optimal strategy using simulated data from monitoring prostate cancer recurrence over a 5-year period.