Tag: proteomics

Bottom-up proteomics suggests an association between differential expression of mitochondrial proteins and chronic fatigue syndrome

Abstract:

Chronic fatigue syndrome (CFS) is a debilitating and complex disorder characterized by unexplained fatigue not improved by rest. An area of investigation is the likely connection of CFS with defective mitochondrial function.

In a previous work, we investigated the proteomic salivary profile in a couple of monozygotic twins discordant for CFS. Following this work, we analyzed mitochondrial proteins in the same couple of twins. Nano-liquid chromatography electrospray ionization mass spectrometry (nano-LC-MS) was used to study the mitochondria extracted from platelets of the twins. Subsequently, we selected three proteins that were validated using western blot analysis in a big cohort of subjects (n=45 CFS; n=45 healthy), using whole saliva (WS). The selected proteins were as follows: aconitate hydratase (ACON), ATP synthase subunit beta (ATPB) and malate dehydrogenase (MDHM).

Results for ATPB and ACON confirmed their upregulation in CFS. However, the MDHM alteration was not confirmed. Thereafter, seeing the great variability of clinical features of CFS patients, we decided to analyze the expression of our proteins after splitting patients according to clinical parameters. For each marker, the values were actually higher in the group of patients who had clinical features similar to the ill twin.

In conclusion, these results suggest that our potential markers could be one of the criteria to be taken into account for helping in diagnosis. Furthermore, the identification of biomarkers present in particular subgroups of CFS patients may help in shedding light upon the complex entity of CFS. Moreover, it could help in developing tailored treatments.

 

Source: Ciregia F, Kollipara L, Giusti L, Zahedi RP, Giacomelli C, Mazzoni MR, Giannaccini G, Scarpellini P, Urbani A, Sickmann A, Lucacchini A, Bazzichi L. Bottom-up proteomics suggests an association between differential expression of mitochondrial proteins and chronic fatigue syndrome. Transl Psychiatry. 2016 Sep 27;6(9):e904. doi: 10.1038/tp.2016.184. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5048217/ (Full article)

 

A multidisciplinary approach to study a couple of monozygotic twins discordant for the chronic fatigue syndrome: a focus on potential salivary biomarkers

Abstract:

BACKGROUND: Chronic Fatigue Syndrome (CFS) is a severe, systemic illness characterized by persistent, debilitating and medically unexplained fatigue. The etiology and pathophysiology of CFS remains obscure, and diagnosis is formulated through the patient’s history and exclusion of other medical causes. Thereby, the availability of biomarkers for CFS could be useful for clinical research. In the present study, we used a proteomic approach to evaluate the global changes in the salivary profile in a couple of monozygotic twins who were discordant for CFS. The aim was to evaluate differences of salivary protein expression in the CFS patient in respect to his healthy twin.

METHODS: Saliva samples were submitted to two-dimensional electrophoresis (2DE). The gels were stained with Sypro, and a comparison between CFS subject and the healthy one was performed by the software Progenesis Same Spot including the Analysis of variance (ANOVA test). The proteins spot found with a ≥2-fold spot quantity change and p<0.05 were identified by Nano-liquid chromatography electrospray ionization tandem mass spectrometry. To validate the expression changes found with 2DE of 5 proteins (14-3-3 protein zeta/delta, cyclophilin A, Cystatin-C, Protein S100-A7, and zinc-alpha-2-glycoprotein), we used the western blot analysis. Moreover, proteins differentially expressed were functionally analyzed using the Ingenuity Pathways Analysis software with the aim to determine the predominant canonical pathways and the interaction network involved.

RESULTS: The analysis of the protein profiles allowed us to find 13 proteins with a different expression in CFS in respect to control. Nine spots were up-regulated in CFS and 4 down-regulated. These proteins belong to different functional classes, such as inflammatory response, immune system and metabolism. In particular, as shown by the pathway analysis, the network built with our proteins highlights the involvement of inflammatory response in CFS pathogenesis.

CONCLUSIONS: This study shows the presence of differentially expressed proteins in the saliva of the couple of monozygotic twins discordant for CFS, probably related to the disease. Consequently, we believe the proteomic approach could be useful both to define a panel of potential diagnostic biomarkers and to shed new light on the comprehension of the pathogenetic pathways of CFS.

 

Source: Ciregia F, Giusti L, Da Valle Y, Donadio E, Consensi A, Giacomelli C, Sernissi F, Scarpellini P, Maggi F, Lucacchini A, Bazzichi L. A multidisciplinary approach to study a couple of monozygotic twins discordant for the chronic fatigue syndrome: a focus on potential salivary biomarkers. J Transl Med. 2013 Oct 2;11:243. doi: 10.1186/1479-5876-11-243. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3850462/ (Full article)

 

Meta analysis of Chronic Fatigue Syndrome through integration of clinical, gene expression, SNP and proteomic data

Abstract:

We start by constructing gene-gene association networks based on about 300 genes whose expression values vary between the groups of CFS patients (plus control). Connected components (modules) from these networks are further inspected for their predictive ability for symptom severity, genotypes of two single nucleotide polymorphisms (SNP) known to be associated with symptom severity, and intensity of the ten most discriminative protein features. We use two different network construction methods and choose the common genes identified in both for added validation. Our analysis identified eleven genes which may play important roles in certain aspects of CFS or related symptoms. In particular, the gene WASF3 (aka WAVE3) possibly regulates brain cytokines involved in the mechanism of fatigue through the p38 MAPK regulatory pathway.

 

Source: Pihur V, Datta S, Datta S. Meta analysis of Chronic Fatigue Syndrome through integration of clinical, gene expression, SNP and proteomic data. Bioinformation. 2011 Apr 22;6(3):120-4. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3089886/ (Full article)

 

Distinct cerebrospinal fluid proteomes differentiate post-treatment lyme disease from chronic fatigue syndrome

Abstract:

BACKGROUND: Neurologic Post Treatment Lyme disease (nPTLS) and Chronic Fatigue (CFS) are syndromes of unknown etiology. They share features of fatigue and cognitive dysfunction, making it difficult to differentiate them. Unresolved is whether nPTLS is a subset of CFS.

METHODS AND PRINCIPAL FINDINGS: Pooled cerebrospinal fluid (CSF) samples from nPTLS patients, CFS patients, and healthy volunteers were comprehensively analyzed using high-resolution mass spectrometry (MS), coupled with immunoaffinity depletion methods to reduce protein-masking by abundant proteins. Individual patient and healthy control CSF samples were analyzed directly employing a MS-based label-free quantitative proteomics approach. We found that both groups, and individuals within the groups, could be distinguished from each other and normals based on their specific CSF proteins (p<0.01). CFS (n = 43) had 2,783 non-redundant proteins, nPTLS (n = 25) contained 2,768 proteins, and healthy normals had 2,630 proteins. Preliminary pathway analysis demonstrated that the data could be useful for hypothesis generation on the pathogenetic mechanisms underlying these two related syndromes.

CONCLUSIONS: nPTLS and CFS have distinguishing CSF protein complements. Each condition has a number of CSF proteins that can be useful in providing candidates for future validation studies and insights on the respective mechanisms of pathogenesis. Distinguishing nPTLS and CFS permits more focused study of each condition, and can lead to novel diagnostics and therapeutic interventions.

 

Source: Schutzer SE, Angel TE, Liu T, Schepmoes AA, Clauss TR, Adkins JN, Camp DG, Holland BK, Bergquist J, Coyle PK, Smith RD, Fallon BA, Natelson BH. Distinct cerebrospinal fluid proteomes differentiate post-treatment lyme disease from chronic fatigue syndrome. PLoS One. 2011 Feb 23;6(2):e17287. doi: 10.1371/journal.pone.0017287. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3044169/ (Full article)

 

Bayesian biomarker identification based on marker-expression proteomics data

Abstract:

We are studying variable selection in multiple regression models in which molecular markers and/or gene-expression measurements as well as intensity measurements from protein spectra serve as predictors for the outcome variable (i.e., trait or disease state).

Finding genetic biomarkers and searching genetic-epidemiological factors can be formulated as a statistical problem of variable selection, in which, from a large set of candidates, a small number of trait-associated predictors are identified. We illustrate our approach by analyzing the data available for chronic fatigue syndrome (CFS).

CFS is a complex disease from several aspects, e.g., it is difficult to diagnose and difficult to quantify. To identify biomarkers we used microarray data and SELDI-TOF-based proteomics data. We also analyzed genetic marker information for a large number of SNPs for an overlapping set of individuals. The objectives of the analyses were to identify markers specific to fatigue that are also possibly exclusive to CFS. The use of such models can be motivated, for example, by the search for new biomarkers for the diagnosis and prognosis of cancer and measures of response to therapy. Generally, for this we use Bayesian hierarchical modeling and Markov Chain Monte Carlo computation.

 

Source: Bhattacharjee M, Botting CH, Sillanpää MJ. Bayesian biomarker identification based on marker-expression proteomics data. Genomics. 2008 Dec;92(6):384-92. doi: 10.1016/j.ygeno.2008.06.006. Epub 2008 Aug 15. http://www.sciencedirect.com/science/article/pii/S0888754308001420 (Full article)

 

A Chronic Fatigue Syndrome – related proteome in human cerebrospinal fluid

Abstract:

BACKGROUND: Chronic Fatigue Syndrome (CFS), Persian Gulf War Illness (PGI), and fibromyalgia are overlapping symptom complexes without objective markers or known pathophysiology. Neurological dysfunction is common. We assessed cerebrospinal fluid to find proteins that were differentially expressed in this CFS-spectrum of illnesses compared to control subjects.

METHODS: Cerebrospinal fluid specimens from 10 CFS, 10 PGI, and 10 control subjects (50 mul/subject) were pooled into one sample per group (cohort 1). Cohort 2 of 12 control and 9 CFS subjects had their fluids (200 mul/subject) assessed individually. After trypsin digestion, peptides were analyzed by capillary chromatography, quadrupole-time-of-flight mass spectrometry, peptide sequencing, bioinformatic protein identification, and statistical analysis.

RESULTS: Pooled CFS and PGI samples shared 20 proteins that were not detectable in the pooled control sample (cohort 1 CFS-related proteome). Multilogistic regression analysis (GLM) of cohort 2 detected 10 proteins that were shared by CFS individuals and the cohort 1 CFS-related proteome, but were not detected in control samples. Detection of >or=1 of a select set of 5 CFS-related proteins predicted CFS status with 80% concordance (logistic model). The proteins were alpha-1-macroglobulin, amyloid precursor-like protein 1, keratin 16, orosomucoid 2 and pigment epithelium-derived factor. Overall, 62 of 115 proteins were newly described.

CONCLUSION: This pilot study detected an identical set of central nervous system, innate immune and amyloidogenic proteins in cerebrospinal fluids from two independent cohorts of subjects with overlapping CFS, PGI and fibromyalgia. Although syndrome names and definitions were different, the proteome and presumed pathological mechanism(s) may be shared.

 

Source: Baraniuk JN, Casado B, Maibach H, Clauw DJ, Pannell LK, Hess S S. A Chronic Fatigue Syndrome – related proteome in human cerebrospinal fluid. BMC Neurol. 2005 Dec 1;5:22. http://www.ncbi.nlm.nih.gov/pubmed/16321154