Humoral Immunity Profiling of Subjects with Myalgic Encephalomyelitis Using a Random Peptide Microarray Differentiates Cases from Controls with High Specificity and Sensitivity

Singh, Sahajpreet; Stafford, Phillip; Schlauch, Karen; Tillett, Richard R.; Gollery, Martin; Johnston, Stephen Albert; Khaiboullina, Svetlana F.; Meirleir, Kenny L. De; Rawat, Shanti; Mijatovic, Tatjana; Subramanian, Krishnamurthy; Palotás, András; Lombardi, Vincent

doi:10.1007/s12035-016-0334-0

Cited by 21 publications

(20 citation statements)

References 56 publications

(46 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…A recent publication using the same immunosignature platform proposed a 25-peptide ME/CFS signature [35]. There was no direct overlap between this signature and CPS001A, and little overlap with our other candidate signatures (Online Resource 1).…”

Section: Discussionmentioning

confidence: 79%

Immunosignature Analysis of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS)

Günther¹,

Gardy

Stafford

et al. 2018

Mol Neurobiol

Self Cite

View full text Add to dashboard Cite

A random-sequence peptide microarray can interrogate serum antibodies in a broad, unbiased fashion to generate disease-specific immunosignatures. This approach has been applied to cancer detection, diagnosis of infections, and interrogation of vaccine response. We hypothesized that there is an immunosignature specific to ME/CFS and that this could aid in the diagnosis. We studied two subject groups meeting the Canadian Consensus Definition of ME/CFS. ME/CFS ( n = 25) and matched control ( n = 25) sera were obtained from a Canadian study. ME/CFS ( n = 25) sera were obtained from phase 1/2 Norwegian trials (NCT01156909). Sera from six healthy controls from the USA were included in the analysis. Canadian cases and controls were tested for a disease immunosignature. By combining results from unsupervised and supervised analyses, a candidate immunosignature with 654 peptides was able to differentiate ME/CFS from controls. The immunosignature was tested and further refined using the Norwegian and USA samples. This resulted in a 256-peptide immunosignature with the ability to separate ME/CFS cases from controls in the international data sets. We were able to identify a 256-peptide signature that separates ME/CFS samples from healthy controls, suggesting that the hit-and-run hypothesis of immune dysfunction merits further investigation. By extending testing of both our signature and one previously reported in the literature to larger cohorts, and further interrogating the specific peptides we and others have identified, we may deepen our understanding of the origins of ME/CFS and work towards a clinically meaningful diagnostic biomarker. Electronic supplementary material The online version of this article (10.1007/s12035-018-1354-8) contains supplementary material, which is available to authorized users.

show abstract

Section: Discussionmentioning

confidence: 79%

Immunosignature Analysis of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS)

Günther¹,

Gardy

Stafford

et al. 2018

Mol Neurobiol

Self Cite

View full text Add to dashboard Cite

show abstract

“…In the prehospital setting, these assessments are even less effective, in which some studies have documented levels of accuracy as low as 51% [27]. Although it is important to note that no direct comparisons were made, the antibody-based signature identified in our analysis displayed levels of accuracy which, if validated, would constitute a 6 APFGQKDVALGL <9.6 IS IS IS SM HS HS HS SM 4 GASVHDGVALSG <8.9 11 PKPHGFPGQEYV <9.6 17 QRPDPKDGQAKD >7.9 13 NSLKENGVALSG <9.0 12 In terms of the biological significance of our findings, our results suggest that the circulating antibody pool is altered in stroke; however, the timing and mechanism of these alterations are unclear. The scalability and unbiased nature of non-native peptide arrays make them well suited for use as diagnostic tools, but because they are not comprised of biologically occurring proteins, it is difficult to elucidate the true antigens associated with differential binding.…”

Section: Discussionmentioning

confidence: 83%

“…Machine learning-based analysis of peptide array data was performed using a similar approach as described previously [17]. Random forest models were generated via the BrandomForest^package for R [18].…”

Section: Random Forestmentioning

confidence: 99%

High-Throughput Profiling of Circulating Antibody Signatures for Stroke Diagnosis Using Small Volumes of Whole Blood

et al. 2019

Self Cite

View full text Add to dashboard Cite

Accurate stroke recognition during triage can streamline care and afford patients earlier access to life-saving interventions. However, the tools currently available to clinicians for prehospital and early in-hospital identification of stroke are limited. The peripheral immune system is intricately involved in stroke pathology and thus may be targetable for the development of immunodiagnostics. In this preliminary study, we sought to determine whether the circulating antibody pool is altered early in stroke, and whether such alterations could be leveraged for diagnosis. One hundred microliters of peripheral whole blood was sampled from 19 ischemic stroke patients, 17 hemorrhagic stroke patients, and 20 stroke mimics in the acute phase of care. A custom-fabricated high-density peptide array comprising 125,000 unique probes was used to assess the binding characteristics of blood-borne antibodies, and a random forest-based approach was used to select a parsimonious set of probes with an optimal ability to discriminate between groups. The coordinate antibody binding intensities of the top 17 probes identified in our analysis displayed an ability to differentiate the total pool of stroke patients from stroke mimics with 92% sensitivity and 90% specificity, as well as detect hemorrhage with 88% sensitivity and 87% specificity, as determined using a same-set cross-validation. These preliminary findings suggest that stroke-associated alterations in the circulating antibody pool may have clinical utility for diagnosis during triage, and that such a possibility warrants further investigation.

show abstract

“…Метод иммуносигнатуры был использован для дифференциальной диагностики опухолей различной этиологии [28], болезни Альцгеймера [24,25], синдрома хронической усталости [27], что позволило нам применить его для диагностики расстройств аутистического спектра (РАС), которые включают гетерогенные изменения, связанные с различными нарушениями/отклонениями нейроразвития. РАС описывается рядом характерных симптомов/дефицитов, формирующих основные коровые домены: трудности социальной коммуникации, ошибочные социальные взаимодействия, ограниченные и/или повторяющиеся поведение и интересы [3,7,18]…”

Section: иммуносигнатура в диагностике расunclassified

Method of Immunosignature in Differential Diagnosis of Autism Spectrum Disorders. A Pilot Study

Филиппова¹,

Нохрин²,

Бурмистрова³

2019

Med. immunol.

View full text Add to dashboard Cite

A large and diverse repertoire of antibodies encodes the history of past immunological experience, creating a global network of the body’s regulation system. In this article, we propose to use a peptide microarray (“immunosignature”) for evaluating global individual antibody patterns and bioinformatic data analysis for differential diagnosis of autism spectrum disorders. The peptide microarray consists of 124 000 antigen mimetics with random sequences covalently bound to the surface of the glass slide. A drop of plasma is tested for the presence of antibodies of distinct specificity, by measuring their binding to each antigen mimetic in the microarray detectable by fluorescent staining with secondary IgG antibodies, and this reaction is registered by laser activation assay. For bioinformatic analysis, we used the files of digitalized fluorescence intensity data, which presented the reactivity of plasma antibodies bound to antigen mimetics. Data processing was carried out by packages of the Bioconductor project for the R software environment to perform statistical evaluation. At the stage of primary data processing, the quantile normalization was used in order to equalize the distributions of antibodies’ reactivity. The sample data and other necessary information were combined into the discrete ExpessionSet container files. To compare the control and experimental groups, the Welch’s one-way ANOVA (for unequal variances) was used. The obtained estimates of the mean value differences and statistical significance of P levels were used further for constructing a volcano diagram, in order of ranking and selecting the most promising antibody reactivity parameters. For differential diagnosis of autism, and evaluation of diagnostic significance of the immunosignature method, a heatmap was constructed. The standardized values of the logarithms of antibody reactivity, and the results of the hierarchical cluster analysis performed by the Ward method using Pearson correlation, as a measure of similarity were used in constructing the heatmap. As a result of the bioinformatiс analysis of the data, 73 antibodies were selected whose reactivity had statistically significant differences in groups of children with autism and normally developing children. These antibodies were used for differential diagnosis, the value of which was determined in the heatmap construction. It was found that the group of children with autism spectrum disorders by the antibody reactivity exhibits marked heterogeneity, and consists of at least two subgroups. In addition, 60 antibodies in children with autism showed predominantly medium and low reactivity, i.e. these antibodies had a weak binding power with antigenic mimetics, and only 13 antibodies showed high reactivity. In general, diagnostic specificity of the autism spectrum disorders using immunosignature approach was 96.0% (95% CI 82.8 to 99.6%), sensitivity was 78.3% (95% CI 64.9 to 88.2%), and diagnostic efficiency was 82.7%. Our pilot study allows us to propose a method of immunosignature for differential diagnosis of autism and, possibly, to expand our understanding of autism spectrum disorders.

show abstract

Humoral Immunity Profiling of Subjects with Myalgic Encephalomyelitis Using a Random Peptide Microarray Differentiates Cases from Controls with High Specificity and Sensitivity

Cited by 21 publications

References 56 publications

Immunosignature Analysis of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS)

Immunosignature Analysis of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS)

High-Throughput Profiling of Circulating Antibody Signatures for Stroke Diagnosis Using Small Volumes of Whole Blood

Method of Immunosignature in Differential Diagnosis of Autism Spectrum Disorders. A Pilot Study

Contact Info

Product

Resources

About