Candidate Biomarkers For Disease Research Articles

Altered Gene Expression of IL-35 and IL-36α in the Skin of Patients with Atopic Dermatitis.

A comprehensive understanding of atopic dermatitis (AD) pathogenesis is desired, especially in the current era of novel biologics and small molecule drugs. In recent years, new cytokines have emerged that may play a significant role in the pathogenesis of AD. Using the tape stripping (TS) method, this study analyzed the gene expression of IL-35 and IL-36α in lesional and nonlesional AD skin compared with healthy skin and their association with the clinical features of AD among the Polish population. Ten AD patients and seven healthy individuals were enrolled. The lesional skin of the AD patients showed significantly higher expression levels of IL-35 compared to healthy skin (p = 0.0001). The expression level of IL-36α was significantly higher in lesional AD skin than in nonlesional AD skin (p = 0.0039) and healthy skin (p = 0.0045). There was a significant negative correlation between AD severity and the expression level of IL-35 in both lesional (R = -0.66, p = 0.048) and nonlesional skin (R = -0.9, p = 0.0016). In summary, both IL-35 and IL-36α appear to play a role in the pathogenesis of AD. Furthermore, it might be speculated that IL-35 and IL-36α may be potential candidates for disease biomarkers. However, further studies are needed to verify these assumptions and comprehensively elucidate their importance in the pathogenesis of AD.

Quantitative proteomics and phosphoproteomics of urinary extracellular vesicles define putative diagnostic biosignatures for Parkinson’s disease

BackgroundMutations in the leucine-rich repeat kinase 2 (LRRK2) gene have been recognized as genetic risk factors for Parkinson’s disease (PD). However, compared to cancer, fewer genetic mutations contribute to the cause of PD, propelling the search for protein biomarkers for early detection of the disease.MethodsUtilizing 138 urine samples from four groups, healthy individuals (control), healthy individuals with G2019S mutation in the LRRK2 gene (non-manifesting carrier/NMC), PD individuals without G2019S mutation (idiopathic PD/iPD), and PD individuals with G2019S mutation (LRRK2 PD), we applied a proteomics strategy to determine potential diagnostic biomarkers for PD from urinary extracellular vesicles (EVs).ResultsAfter efficient isolation of urinary EVs through chemical affinity followed by mass spectrometric analyses of EV peptides and enriched phosphopeptides, we identify and quantify 4476 unique proteins and 2680 unique phosphoproteins. We detect multiple proteins and phosphoproteins elevated in PD EVs that are known to be involved in important PD pathways, in particular the autophagy pathway, as well as neuronal cell death, neuroinflammation, and formation of amyloid fibrils. We establish a panel of proteins and phosphoproteins as novel candidates for disease biomarkers and substantiate the biomarkers using machine learning, ROC, clinical correlation, and in-depth network analysis. Several putative disease biomarkers are further partially validated in patients with PD using parallel reaction monitoring (PRM) and immunoassay for targeted quantitation.ConclusionsThese findings demonstrate a general strategy of utilizing biofluid EV proteome/phosphoproteome as an outstanding and non-invasive source for a wide range of disease exploration.

Altered phosphatidylcholine metabolism in children with atopic dermatitis

Disturbances in circulating phospholipids levels and their association with the phenotype have been observed in inflammatory disorders and allergic diseases, such as asthma. However, the role and related mechanisms of metabolites in the development of AD are rarely known. We sought to apply serum untargeted metabolomic profiling to identify pathogenic mechanisms and candidate disease biomarkers in children with AD.

Metabolome and microbiome multi-omics integration from a murine lung inflammation model of bronchopulmonary dysplasia.

Respiratory tract microbial dysbiosis can exacerbate inflammation and conversely inflammation may cause dysbiosis. Dysbiotic microbiome metabolites may lead to bronchopulmonary dysplasia (BPD). Hyperoxia and lipopolysaccharide (LPS) interaction alters lung microbiome and metabolome, mediating BPD lung injury sequence. C57BL6/J mice were exposed to 21% (normoxia) or 70% (hyperoxia) oxygen during postnatal days (PND) 1-14. Pups were injected with LPS (6 mg/kg) or equal PBS volume, intraperitoneally on PND 3, 5, and 7. At PND14, the lungs were collected for microbiome and metabolomic analyses (n = 5/group). Microbiome alpha and beta diversity were similar between groups. Metabolic changes included hyperoxia 31 up/18 down, LPS 7 up/4 down, exposure interaction 8. Hyperoxia increased Intestinimonas abundance, whereas LPS decreased Clostridiales, Dorea, and Intestinimonas; exposure interaction affected Blautia. Differential co-expression analysis on multi-omics data identified exposure-altered modules. Hyperoxia metabolomics response was integrated with a published matching transcriptome, identifying four induced genes (ALDOA, GAA, NEU1, RENBP), which positively correlated with BPD severity in a published human newborn cohort. We report hyperoxia and LPS lung microbiome and metabolome signatures in a clinically relevant BPD model. We identified four genes correlating with BPD status in preterm infants that are promising targets for therapy and prevention. Using multi-omics, we identified and correlated key biomarkers of hyperoxia and LPS on murine lung micro-landscape and examined their potential clinical implication, which shows strong clinical relevance for future research. Using a double-hit model of clinical relevance to bronchopulmonary dysplasia, we are the first to report integrated metabolomic/microbiome landscape changes and identify novel disease biomarker candidates.

Serum antibodies to surface proteins of Chlamydia trachomatis as candidate biomarkers of disease: results from the Baltimore Chlamydia Adolescent/Young Adult Reproductive Management (CHARM) cohort.

We previously observed that the nine-member family of autotransported polymorphic membrane proteins (Pmps) of Chlamydia trachomatis is variably expressed in cell culture. Additionally, C. trachomatis-infected patients display variable Pmp-specific serum antibody profiles indirectly suggesting expression of unique Pmp profiles is an adaptive response to host-specific stimuli during infection. Here, we propose that the host response to Pmps and other outer surface proteins may correlate with disease severity. This study tests this hypothesis using an ELISA that measures serum IgG antibodies specific for the nine C. trachomatis Pmp subtypes and four immunodominant antigens (MOMP, OmcB, Hsp60, ClpP) in 265 participants of the Chlamydia Adolescent/Young Adult Reproductive Management (CHARM) cohort. More C. trachomatis-infected females displayed high Pmp-specific antibody levels (cut-off Indexes) than males (35.9%-40.7% of females vs. 24.2%-30.0% of males), with statistical significance for PmpC, F and H (P < 0.05). Differences in Pmp-specific antibody profiles were not observed between C. trachomatis-infected females with a clinical diagnosis of pelvic inflammatory disease (PID) and those without. However, a statistically significant association between high levels of OmcB-specific antibody and a PID diagnosis (P< 0.05) was observed. Using antibody levels as an indirect measure of antigen expression, our results suggest that gender- and/or site-specific (cervix in females vs. urethra in males) stimuli may control pmp expression in infected patients. They also support the possible existence of immune biomarkers of chlamydial infection associated with disease and underline the need for high resolution screening in human serum.

ROSIE: RObust Sparse ensemble for outlIEr detection and gene selection in cancer omics data

The extraction of novel information from omics data is a challenging task, in particular, since the number of features (e.g. genes) often far exceeds the number of samples. In such a setting, conventional parameter estimation leads to ill-posed optimization problems, and regularization may be required. In addition, outliers can largely impact classification accuracy.Here we introduce ROSIE, an ensemble classification approach, which combines three sparse and robust classification methods for outlier detection and feature selection and further performs a bootstrap-based validity check. Outliers of ROSIE are determined by the rank product test using outlier rankings of all three methods, and important features are selected as features commonly selected by all methods.We apply ROSIE to RNA-Seq data from The Cancer Genome Atlas (TCGA) to classify observations into Triple-Negative Breast Cancer (TNBC) and non-TNBC tissue samples. The pre-processed dataset consists of genes and more than samples. We demonstrate that ROSIE selects important features and outliers in a robust way. Identified outliers are concordant with the distribution of the commonly selected genes by the three methods, and results are in line with other independent studies. Furthermore, we discuss the association of some of the selected genes with the TNBC subtype in other investigations. In summary, ROSIE constitutes a robust and sparse procedure to identify outliers and important genes through binary classification. Our approach is ad hoc applicable to other datasets, fulfilling the overall goal of simultaneously identifying outliers and candidate disease biomarkers to the targeted in therapy research and personalized medicine frameworks.

Characterization of tick salivary gland and saliva alphagalactome reveals candidate alpha-gal syndrome disease biomarkers

ABSTRACT Background Ticks are obligate hematophagous arthropods that synthesize the glycan Galα1-3Galβ1-(3)4GlcNAc-R (α-Gal) associated with the alpha-gal syndrome (AGS) or allergy to mammalian meat consumption. Research design and methods In this study, we used a proteomics approach to characterize tick proteins in salivary glands (sialome SG), secreted saliva (sialome SA) and with α-Gal modification (alphagalactome SG and SA) in model tick species associated with the AGS in the United States (Amblyomma americanum) and Australia (Ixodes holocyclus). Selected proteins reactive to sera (IgE) from patients with AGS were identified to advance in the identification of possible proteins associated with the AGS. For comparative analysis, the α-Gal content was measured in various tick species. Results The results confirmed that ticks produce proteins with α-Gal modifications and secreted into saliva during feeding. Proteins identified in tick alphagalactome SA by sera from patients with severe AGS symptomatology may constitute candidate disease biomarkers. Conclusions The results support the presence of tick-derived proteins with α-Gal modifications in the saliva with potential implications in AGS and other disorders and protective capacity against tick infestations and pathogen infection. Future research should focus on the characterization of the function of tick glycoproteins with α-Gal in tick biology and AGS.

Deletion of pancreas-specific miR-216a reduces beta-cell mass and inhibits pancreatic cancer progression in mice

SummarymiRNAs have crucial functions in many biological processes and are candidate biomarkers of disease. Here, we show that miR-216a is a conserved, pancreas-specific miRNA with important roles in pancreatic islet and acinar cells. Deletion of miR-216a in mice leads to a reduction in islet size, β-cell mass, and insulin levels. Single-cell RNA sequencing reveals a subpopulation of β-cells with upregulated acinar cell markers under a high-fat diet. miR-216a is induced by TGF-β signaling, and inhibition of miR-216a increases apoptosis and decreases cell proliferation in pancreatic cells. Deletion of miR-216a in the pancreatic cancer-prone mouse line KrasG12D;Ptf1aCreER reduces the propensity of pancreatic cancer precursor lesions. Notably, circulating miR-216a levels are elevated in both mice and humans with pancreatic cancer. Collectively, our study gives insights into how β-cell mass and acinar cell growth are modulated by a pancreas-specific miRNA and also suggests miR-216a as a potential biomarker for diagnosis of pancreatic diseases.

Extracellular Vesicles in Multiple Sclerosis: Role in the Pathogenesis and Potential Usefulness as Biomarkers and Therapeutic Tools.

Although extracellular vesicles (EVs) were initially relegated to a waste disposal role, nowadays, they have gained multiple fundamental functions working as messengers in intercellular communication as well as exerting active roles in physiological and pathological processes. Accumulating evidence proves the involvement of EVs in many diseases, including those of the central nervous system (CNS), such as multiple sclerosis (MS). Indeed, these membrane-bound particles, produced in any type of cell, carry and release a vast range of bioactive molecules (nucleic acids, proteins, and lipids), conferring genotypic and phenotypic changes to the recipient cell. This means that not only EVs per se but their content, especially, could reveal new candidate disease biomarkers and/or therapeutic agents. This review is intended to provide an overview regarding current knowledge about EVs’ involvement in MS, analyzing the potential versatility of EVs as a new therapeutic tool and source of biomarkers.

CSF extracellular vesicles and risk of disease activity after a first demyelinating event

Background: Extracellular vesicles (EVs), a recently described mechanism of cell communication, are released from activated microglial cells and macrophages and are a candidate biomarker in diseases characterized by chronic inflammatory process such as multiple sclerosis (MS). Methods: We explored cerebrospinal fluid extracellular vesicle (CSF EV) of myeloid origin (MEVs), cytokine and chemokine levels in patients with clinically isolated syndrome (CIS). Results: We found that CSF MEVs were significantly higher in CIS patients than in controls and were inversely correlated to CSF CCL2 levels. MEVs level were significantly associated with an shorter time to evidence of disease activity (hazard ratio: 1.01, 95% confidence interval: 1.00–1.02, p < 0.01) independently from other known prognostic markers. Conclusion: After a first demyelinating event, CSF EVs may improve risk stratification of these patients and allow more targeted intervention strategies.

Novel circRNA discovery in sheep shows evidence of high backsplice junction conservation

Circular RNAs (circRNAs) are covalently closed circular non-coding RNAs. Due to their structure, circRNAs are more stable and have longer half-lives than linear RNAs making them good candidates for disease biomarkers. Despite the scientific relevance of these molecules, the study of circRNAs in non-model organisms is still in its infancy. Here, we analyse total RNA-seq data to identify circRNAs in sheep from peripheral blood mononuclear cells (PBMCs) and parietal lobe cortex. Out of 2510 and 3403 circRNAs detected in parietal lobe cortex and in PBMCs, a total of 1379 novel circRNAs were discovered. Remarkably, around 63% of all detected circRNAs were found to be completely homologous to a circRNA annotated in human. Functional enrichment analysis was conducted for both tissues based on GO terms and KEGG pathways. The enriched terms suggest an important role of circRNAs from encephalon in synaptic functions and the involvement of circRNAs from PBMCs in basic immune system functions. In addition to this, we investigated the role of circRNAs in repetitive vaccination experiments via differential expression analysis and did not detect any significant relationship. At last, our results support both the miRNA sponge and the miRNA shuttle functions of CDR1-AS in sheep brain. To our knowledge, this is the first study on circRNA annotation in sheep PBMCs or parietal lobe cortex samples.

ALL-074: Exosomal MicroRNAs as Minimal Residual Disease Biomarker Candidates in Childhood Acute Lymphoblastic Leukemia

Context Acute lymphoblastic leukemia (ALL) is the most common childhood malignancy. Five-year survival rate is nearly 90%. Measurement of minimal residual disease (MRD) at set time points has become a fundamental part of stratified treatment in ALL. Treatment response is assessed using bone marrow samples. Exosomal microRNAs are putative biomarkers in many malignancies. In childhood leukemia, the potential of exosomal microRNAs as biomarker candidates has not established yet. Objectives The aim of this study was to evaluate exosomal microRNAs in peripheral blood and associated with flow cytometry (FC) MRD in childhood ALL. Design and settings Exosomal fractions of 52 platelet-free plasma samples were obtained from 13 newly diagnosed de novo ALL patients and 6 healthy controls by ultracentrifugation. RNA isolation was carried out using miRNeasy Serum/Plasma Kit (Qiagen). Quantitative real-time PCR was carried out using TaqMan advanced qPCR methodology. Results The expression of the tested microRNAs in exosomal fraction as well as in platelet-free fraction correlated in diagnostic samples but not any other sampling times during the induction therapy. Significant decrease was observed in both miRs between the day of diagnosis and day 15 of induction therapy. Expression changes in one of the tested exosomal microRNAs correlated in every given time point with day 15 FC MRD (p Conclusion Based on our results, certain exosomal microRNAs' expression changes seem to be a better biomarker candidate than circulating microRNAs detected in platelet-free plasma of de novo childhood ALL.

Abstract 3119: Comparison of circulating tumor cell (CTC) derived DNA and circulating cell-free DNA (cfDNA) from simultaneous blood sampling of patients with metastatic breast cancer (MBC)

Abstract Purpose: Blood-based candidate biomarkers of disease can be monitored by analyzing CTCs and/or circulating cfDNA isolated from the peripheral blood. Our primary objective is to understand the relative contributions of these circulating factors (i.e., CTCs and cfDNA) to the overall disease profile in MBC. Methods: Clinically archived FFPE tumor tissue and prospective blood samples are collected through a minimal risk protocol approved by the Mayo Clinic IRB (#16-001540) from patients with MBC and objective evidence of disease progression. Blood samples include 20 mL whole blood in Streck blood collection tubes (BCTs) for platelet poor plasma (PPP); 20 mL whole blood in AccuCyte BCTs for CTCs, WBCs, and PPP; and 10 mL whole blood in EDTA BCTs for PPP. Nucleated, EpCAM+/cytokeratin+/CD45- CTCs are identified, assessed for ER/HER2 status, and isolated using a centrifugation and direct imaging platform that allows for single cell retrieval (RareCyte). DNA is extracted from PPP, CTCs, WBCs, and FFPE tumor tissue using established methods. Targeted sequencing for SNVs/indels is performed on paired WBCs and CTC-DNA, AccuCyte-cfDNA, Streck-cfDNA, EDTA-cfDNA, and tumor tissue derived DNA using the same NGS panel and informatics pipeline (65 genes; CleanPlex OncoZoom; Paragon Genomics). Results: Tissue and blood samples were collected from 40 patients with metastatic breast cancer. 10 cases were selected for initial analyses on the basis of CTC yield (range 3-113 per 3.75 mL blood); up to 5 CTCs per subject were isolated and pooled for DNA extraction. Plasma cfDNA yields and variant allele frequencies were highly comparable between AccuCyte and Streck collected blood samples. Mutations (range 1-3) were identified in CTC-DNA and/or cfDNA in 9 of 10 cases for a total of 18 detected mutations: 10 in CTC-DNA and cfDNA (BRCA2 N372H, PIK3CA E542K, PIK3CA E545K (x3), PIK3CA H1047R, PTEN R130P, RET G691S, TP53 C135W, TP53 Q192*); 5 in CTC-DNA only (EGFR R521K, EGFR T790M, PIK3CA H1047R, SMAD4 C363Y, TP53 N263D); and 3 in cfDNA only (DNMT3A W893S, DNMT3A S714C, TP53 Q136E). Parallel analyses of samples from 10 more subjects are in progress. Analysis of tumor tissue for all 20 subjects and of EDTA-cfDNA and single CTCs for a subset of cases is ongoing. Updated results will be presented at the meeting. Conclusions: It is feasible to isolate high quality CTCs and cfDNA from the same blood collection tube to perform targeted sequencing; this streamlines specimen processing, decreases overall costs, and minimizes required blood volumes. Importantly, there is overlap in the majority of mutations identified in CTC-DNA and cfDNA, but actionable mutations (e.g., PIK3CA, EGFR) were detected in CTC-DNA only. The clinical and theranostic relevance of these findings is unclear and warrants further investigation. Citation Format: Minetta C. Liu, Karthik V. Giridhar, Roberto A. Leon Ferre, Jamie L. Carroll, Matthew P. Goetz, Tufia C. Haddad, Deanne R. Smith, Siddhartha Yadav, Vidushi Kapoor, Guoying Liu, Tad George, Nolan Ericson, Arturo B. Ramirez, Eric Kaldjian, Keegan E. Haselkorn. Comparison of circulating tumor cell (CTC) derived DNA and circulating cell-free DNA (cfDNA) from simultaneous blood sampling of patients with metastatic breast cancer (MBC) [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3119.

Identifying unknown metabolites using NMR-based metabolic profiling techniques.

Metabolic profiling of biological samples provides important insights into multiple physiological and pathological processes but is hindered by a lack of automated annotation and standardized methods for structure elucidation of candidate disease biomarkers. Here we describe a system for identifying molecular species derived from nuclear magnetic resonance (NMR) spectroscopy-based metabolic phenotyping studies, with detailed information on sample preparation, data acquisition and data modeling. We provide eight different modular workflows to be followed in a recommended sequential order according to their level of difficulty. This multi-platform system involves the use of statistical spectroscopic tools such as Statistical Total Correlation Spectroscopy (STOCSY), Subset Optimization by Reference Matching (STORM) and Resolution-Enhanced (RED)-STORM to identify other signals in the NMR spectra relating to the same molecule. It also uses two-dimensional NMR spectroscopic analysis, separation and pre-concentration techniques, multiple hyphenated analytical platforms and data extraction from existing databases. The complete system, using all eight workflows, would take up to a month, as it includes multi-dimensional NMR experiments that require prolonged experiment times. However, easier identification cases using fewer steps would take 2 or 3 days. This approach to biomarker discovery is efficient and cost-effective and offers increased chemical space coverage of the metabolome, resulting in faster and more accurate assignment of NMR-generated biomarkers arising from metabolic phenotyping studies. It requires a basic understanding of MATLAB to use the statistical spectroscopic tools and analytical skills to perform solid phase extraction (SPE), liquid chromatography (LC) fraction collection, LC-NMR-mass spectroscopy and one-dimensional and two-dimensional NMR experiments.

Islet-expressed circular RNAs are associated with type 2 diabetes status in human primary islets and in peripheral blood

BackgroundCircular RNAs are non-coding RNA molecules with gene regulatory potential that have been associated with several human diseases. They are stable and present in the circulation, making them excellent candidates for biomarkers of disease. Despite their promise as biomarkers or future therapeutic targets, information on their expression and functionality in human pancreatic islets is a relatively unexplored subject.MethodsHere we aimed to produce an enriched circRNAome profile for human pancreatic islets by CircleSeq, and to explore the relationship between circRNA expression, diabetes status, genotype at T2D risk loci and measures of glycaemia (insulin secretory index; SI and HbA1c) in human islet preparations from healthy control donors and donors with type 2 diabetes using ANOVA or linear regression as appropriate. We also assessed the effect of elevated glucose, cytokine and lipid and hypoxia on circRNA expression in the human beta cell line EndoC-βH1.ResultsWe identified over 2600 circRNAs present in human islets. Of the five most abundant circRNAs in human islets, four (circCIRBP, circZKSCAN, circRPH3AL and circCAMSAP1) demonstrated marked associations with diabetes status. CircCIRBP demonstrated an association with insulin secretory index in isolated human islets and circCIRBP and circRPH3AL displayed altered expression with elevated fatty acid in treated EndoC-βH1 cells. CircCAMSAP1 was also noted to be associated with T2D status in human peripheral blood. No associations between circRNA expression and genotype at T2D risk loci were identified in our samples.ConclusionsOur data suggest that circRNAs are abundantly expressed in human islets, and that some are differentially regulated in the islets of donors with type 2 diabetes. Some islet circRNAs are also expressed in peripheral blood and the expression of one, circCAMSAP1, correlates with diabetes status. These findings highlight the potential of circRNAs as biomarkers for T2D.

MOTA: Network-Based Multi-Omic Data Integration for Biomarker Discovery.

The recent advancement of omic technologies provides researchers with the possibility to search for disease-associated biomarkers at the system level. The integrative analysis of data from a large number of molecules involved at various layers of the biological system offers a great opportunity to rank disease biomarker candidates. In this paper, we propose MOTA, a network-based method that uses data acquired at multiple layers to rank candidate disease biomarkers. The networks constructed by MOTA allow users to investigate the biological significance of the top-ranked biomarker candidates. We evaluated the performance of MOTA in ranking disease-associated molecules from three sets of multi-omic data representing three cohorts of hepatocellular carcinoma (HCC) cases and controls with liver cirrhosis. The results demonstrate that MOTA allows the identification of more top-ranked metabolite biomarker candidates that are shared by two different cohorts compared to traditional statistical methods. Moreover, the mRNA candidates top-ranked by MOTA comprise more cancer driver genes compared to those ranked by traditional differential expression methods.

Comparison of methods for miRNA isolation and quantification from ovine plasma

microRNA (miRNA) are promising candidates for disease biomarkers as they are abundant in circulation, highly stable in biological fluids and may yield diagnostic biomarker signatures. The reported issues with miRNA isolation using traditional RNA reagents necessitates the optimisation of miRNA isolation from challenging samples. In this study we compared six commercial RNA extraction kits to evaluate their ability to isolate miRNA from ovine plasma. We also compared three methods for quantification of small RNA extracted from plasma to determine the most reliable. Using minimal sample inputs of fresh and frozen plasma from five sheep, we compared the six kits (Kit A-F) using quantitative PCR. Operational factors were also assessed for each kit. Kits A and B provided the best detection of the miRNA qPCR reference genes across fresh and frozen samples (p < 0.001) followed by Kit C. The Qubit and microRNA assay provided the least variation (% CV 5.47, SEM ± 0.07), followed by the NanoDrop (% CV 7.01, SEM ± 0.92) and Agilent Bioanalyzer (% CV 59.21, SEM ± 1.31). We identify Kit A to be optimal for isolating miRNA from small volumes of fresh and frozen ovine plasma, and Kit B the top performing kit taking into consideration miRNA detection and operational factors. The Qubit fluorometer using a microRNA assay was the most reliable miRNA quantification method.

Untargeted metabolomic profiling identifies disease-specific signatures in food allergy and asthma

Food allergy (FA) affects an increasing proportion of children for reasons that remain obscure. Novel disease biomarkers and curative treatment options are strongly needed. We sought to apply untargeted metabolomic profiling to identify pathogenic mechanisms and candidate disease biomarkers in patients with FA. Mass spectrometry-based untargeted metabolomic profiling was performed on serum samples of children with either FA alone, asthma alone, or both FA and asthma, as well as healthy pediatric control subjects. In this pilot study patients with FA exhibited a disease-specific metabolomic signature compared with both control subjects and asthmatic patients. In particular, FA was uniquely associated with a marked decrease in sphingolipid levels, as well as levels of a number of other lipid metabolites, in the face of normal frequencies of circulating natural killer T cells. Specific comparison of patients with FA and asthmatic patients revealed differences in the microbiota-sensitive aromatic amino acid and secondary bile acid metabolism. Children with both FA and asthma exhibited a metabolomic profile that aligned with that of FA alone but not asthma. Among children with FA, the history of severe systemic reactions and the presence of multiple FAs were associated with changes in levels of tryptophan metabolites, eicosanoids, plasmalogens, and fatty acids. Children with FA have a disease-specific metabolomic profile that is informative of disease mechanisms and severity and that dominates in the presence of asthma. Lower levels of sphingolipids and ceramides and other metabolomic alterations observed in children with FA might reflect the interplay between an altered microbiota and immune cell subsets in the gut.

Deoxysphingolipids as candidate biomarkers for a novel SPTLC1 mutation associated with HSAN-I.

Hereditary sensory and autonomic neuropathy type 1 (HSAN-I)—an autosomal dominant, mainly sensory neuropathy—typically affects patients in their second and third decades, presenting with ulcerations and lancinating pain attacks.1 Diagnosis is heavily dependent on genetic analysis, focusing on 6 genes: serine palmitoyltransferase ( SPT ) long chain base subunits 1 and 2 ( SPTLC1 and SPTLC2 ), atlastin 1 ( ATL1 ) and 3 ( ATL3 ), DNA methyltransferase 1, and Ras-related protein ( RAB7 ). Most patients carry SPTLC1 mutations (OMIM*605712) that affect sphingolipids biosynthesis by modifying SPT substrate specificity to produce atypical neurotoxic deoxysphingoid bases (DSBs). Along with their accumulation in mutant cells, elevated DSBs were also found in plasma samples, thus becoming a candidate biomarker of disease.2

MOTA: Multi-omic integrative analysis for biomarker discovery.

Recent advancement of omic technologies provides researchers with opportunities to search for disease biomarkers at the systems level. However, selection of biomarker candidates from a large number of molecules involved at various layers of the biological system is challenging. In this paper, we propose multi-omic integrative analysis (MOTA), a network-based method that uses information from multi-omic data to identify candidate disease biomarkers. We evaluated the performance of MOTA in selecting disease-associated molecules from four sets of multi-omic data representing three cohorts of hepatocellular carcinoma (HCC) cases and patients with liver cirrhosis. The results demonstrate that MOTA leads to selection of more biomarker candidates that shared by two different cohorts compared to traditional statistical methods. Also, the networks constructed by MOTA allow users to investigate biological significance of the selected biomarker candidates.