Identification of novel serum peptide biomarkers for high-altitude adaptation: a comparative approach

Identification of novel urine proteomic biomarkers for high stamina in high-altitude adaptation

Introduction: We aimed to identify urine biomarkers for screening individuals with adaptability to high-altitude hypoxia with high stamina levels. Although most non-high-altitude natives experience rapid decline in physical ability when ascending to high altitudes, some individuals with high-altitude adaptability continue to maintain high endurance levels. Methods: We divided the study population into two groups: the LC group (low change in endurance from low to high altitude) and HC group (high change in endurance from low to high altitude). We performed blood biochemistry testing for individuals at high altitudes and sea level. We used urine peptidome profiling to compare the HH (high-altitude with high stamina) and HL (high-altitude with low stamina) groups and the LC and HC groups to identify urine biomarkers. Results: Routine blood tests revealed that the concentration of white blood cells, lymphocytes and platelets were significantly higher in the HH group than in the HL group. Urine peptidome profiling showed that the proteins ITIH1, PDCD1LG2, NME1-NME2, and CSPG4 were significantly differentially expressed between the HH and HL groups, which was tested using ELISA. Urine proteomic analysis showed that LRG1, NID1, VASN, GPX3, ACP2, and PRSS8 were urine proteomic biomarkers of high stamina during high-altitude adaptation. Conclusion: This study provides a novel approach for identifying potential biomarkers for screening individuals who can adapt to high altitudes with high stamina.

Urinary Metabolites as Predictors of Acute Mountain Sickness Severity

Individuals sojourning at high altitude (≥2,500m) often develop acute mountain sickness (AMS). However, substantial unexplained inter-individual variability in AMS severity exists. Untargeted metabolomics assays are increasingly used to identify novel biomarkers of susceptibility to illness, and to elucidate biological pathways linking environmental exposures to health outcomes. This study used untargeted nuclear magnetic resonance (NMR)-based metabolomics to identify urine metabolites associated with AMS severity during high altitude sojourn. Following a 21-day stay at sea level (SL; 55m), 17 healthy males were transported to high altitude (HA; 4,300m) for a 22-day sojourn. AMS symptoms measured twice daily during the first 5days at HA were used to dichotomize participants according to AMS severity: moderate/severe AMS (AMS; n=11) or no/mild AMS (NoAMS; n=6). Urine samples collected on SL day 12 and HA days 1 and 18 were analyzed using proton NMR tools and the data were subjected to multivariate analyses. The SL urinary metabolite profiles were significantly different (p≤0.05) between AMS vs. NoAMS individuals prior to high altitude exposure. Differentially expressed metabolites included elevated levels of creatine and acetylcarnitine, and decreased levels of hypoxanthine and taurine in the AMS vs. NoAMS group. In addition, the levels of two amino acid derivatives (4-hydroxyphenylpyruvate and N-methylhistidine) and two unidentified metabolites (doublet peaks at 3.33ppm and a singlet at 8.20ppm) were significantly different between groups at SL. By HA day 18, the differences in urinary metabolites between AMS and NoAMS participants had largely resolved. Pathway analysis of these differentially expressed metabolites indicated that they directly or indirectly play a role in energy metabolism. These observations suggest that alterations in energy metabolism before high altitude exposure may contribute to AMS susceptibility at altitude. If validated in larger cohorts, these markers could inform development of a non-invasive assay to screen individuals for AMS susceptibility prior to high altitude sojourn.

Methamphetamine exacerbates pathophysiology of traumatic brain injury at high altitude. Neuroprotective effects of nanodelivery of a potent antioxidant compound H-290/51

Military personnel are often exposed to high altitude (HA, ca. 4500-5000m) for combat operations associated with neurological dysfunctions. HA is a severe stressful situation and people frequently use methamphetamine (METH) or other psychostimulants to cope stress. Since military personnel are prone to different kinds of traumatic brain injury (TBI), in this review we discuss possible effects of METH on concussive head injury (CHI) at HA based on our own observations. METH exposure at HA exacerbates pathophysiology of CHI as compared to normobaric laboratory environment comparable to sea level. Increased blood-brain barrier (BBB) breakdown, edema formation and reductions in the cerebral blood flow (CBF) following CHI were exacerbated by METH intoxication at HA. Damage to cerebral microvasculature and expression of beta catenin was also exacerbated following CHI in METH treated group at HA. TiO2-nanowired delivery of H-290/51 (150mg/kg, i.p.), a potent chain-breaking antioxidant significantly enhanced CBF and reduced BBB breakdown, edema formation, beta catenin expression and brain pathology in METH exposed rats after CHI at HA. These observations are the first to point out that METH exposure in CHI exacerbated brain pathology at HA and this appears to be related with greater production of oxidative stress induced brain pathology, not reported earlier.

CoffeeProt: an online tool for correlation and functional enrichment of systems genetics data

The integration of genomics, transcriptomics, proteomics and phenotypic traits across genetically diverse populations is a powerful approach to discover novel biological regulators. The increasing volume of complex data require new and easy-to-use tools accessible to a variety of scientists for the discovery and visualization of functionally relevant associations. To meet this requirement, we developed CoffeeProt, an open-source tool that analyses genetic variants associated to protein networks, other omics datatypes and phenotypic traits. CoffeeProt uses transcriptomics or proteomics data to perform correlation network analyses and annotates results with protein-protein interactions, subcellular localisations and drug associations. It then integrates genetic variants associated with gene expression (eQTLs) or protein abundance (pQTLs) and includes predictions of the potential consequences of variants on gene function. Finally, genetic variants are co-mapped to molecular or phenotypic traits either provided by the user or retrieved directly from publicly available GWAS results. We demonstrate its utility with the analysis of mouse and human population data enabling the rapid identification of genetic variants associated with druggable proteins and clinical traits. We expect that CoffeeProt will serve the systems genetics and basic science research communities, leading to the discovery of novel biologically relevant associations. CoffeeProt is available at www.coffeeprot.com.

Using serum peptidomics to discovery the diagnostic marker for different stage of ulcerative colitis

The use of peptidomics to find diagnostic markers has attracted increasing clinical attention. Ulcerative colitis (UC) is a type of inflammatory bowel disease, and the traditional auxiliary diagnostic technique is colonoscopy. However, this invasive method is not effective in distinguishing between patients with endoscopic remission and healthy people, which carries the risk of delayed diagnosis of UC. In this study, we used peptidomics to find serum diagnostic markers for different stages of UC. A total of 78 serum samples were collected to form a training set (60 samples) and a testing set (18 samples). Among them, patients with active UC, remitting UC and healthy people accounted for one third each. The nano-liquid chromatography coupled with hybrid linear trap quadrupole orbitrap mass spectrometry was used for detection of low molecular weight peptides in serum. According to the protein database search and de novo sequencing algorithm, forty peptides were simultaneously identified in all samples. Six biomarker peptides were screened in the training set through orthogonal partial least-squares-discriminant analysis and receiver operating characteristic curve analysis. These six peptides were derived from proteins involved in coagulation and complement activation. We evaluated the diagnostic ability of the six peptides in the testing set through hierarchical cluster analysis, and showed that perturbation of these peptides could distinguish patients with active UC, patients with remitting UC and healthy people. This study validated the feasibility of serum peptidomics for the discovery of diagnostic markers, and provided a potential method for diagnosing different stages of UC.

Hypertensive disorders of pregnancy: Strategy to develop clinical peptide biomarkers for more accurate evaluation of the pathophysiological status of this syndrome

Hypertensive disorders of pregnancy (HDP) is the most common and widely known as serious complication of pregnancy. As this syndrome is a major leading cause of maternal, fetal, and neonatal morbidity/mortality worldwide, many studies have sought to identify candidate molecules as potential disease biomarkers (DBMs) for use in clinical examinations. Accumulating evidence over the past 2 decades that the many proteolytic peptides appear in human humoral fluids, including peripheral blood, in association with an individual's health condition. This review provides the potential utility of peptidomic analysis for monitoring for pathophysiological status in HDP, and presents an overview of current status of peptide quantification technology. Especially, the technical limitations of the methods used for DBM discovery in the blood are discussed.