Selection of Biomarkers in ME/CFS for Patient Stratification and Treatment Surveillance/Optimisation

Modra Murovska; Angelika Krūmiņa; Sabīne Grāvelsiņa; Anda Vilmane; Santa Rasa-Dzelzkaleja; Zaiga Nora-Krūkle; Diāna Arāja; Šimons Svirskis; Uldis Berķis

Abstract

Objective
We hypothesized the cohort of ME/CFS patients is divided into several groups/
subsets of which one is having primary autoimmune aetiology, another one is triggered by viral infection. The group/subset triggered by viral infection also could have markers of autoimmunity. This study aimed to examine diagnostic potential of serum biomarkers depending on the presence/absence of viral infection biomarkers by direct comparing ME/CFS cases to healthy controls and applying the results from laboratory testing and pathology to the pattern recognition algorithm random forest to widen marker patterns usable in ME/CFS patient stratification.
Methods
Various PCRs were used to detect presence of viral infection, activity phase
and viral load; ELISA to detect antibodies against beta-2 adrenergic and M3/M4
acetylcholine receptors, and activin B level; Luminex multiplex technology to detect anti-human immunoglobulin class antibodies and cytokines’ level. Selected statistical/machine learning methods were undertaken to explore the joint potential of biomarkers for classification of ME/CFS patients into severity groups, and this way also monitor the course and treatment effects.
Results
A dataset was used originating from 188 persons, including 54 healthy
controls, 30 patients classified as “mild”, 73 as “moderate”, and 31 as “severe”,
clinically assessed by ICC 2011 criteria. Activin B concentration was detected
higher in subgroups of moderate and severe ME/CFS. The ROC analysis showed
that anti-β2AdR has the best potential to be a good marker of ME/CFS in general,
but, as with anti-M4, cannot be a discriminating factor for the severity of ME/CFS.
Differences between ME/CFS and control group were observed IgG4 and also IgA
levels. The high scores of IgG4 and IL-2 may indicate the presence of an autoimmune process underlying the ME/CFS onset.
Conclusion
The highest classification power from data analysis is attributed to anti-β2AdR,
anti-M4, IgG4, but also IL-2 (autoimmune processes marker) and IL-6 (marker for
innate immunity).

Original language	English
Pages	23-24
Number of pages	2
Publication status	Published - 9 Nov 2023
Event	International Conference Autoimmune Diseases: Main Problems and Solutions - Riga, Latvia Duration: 9 Nov 2023 → 10 Nov 2023

Conference

Conference	International Conference Autoimmune Diseases
Country/Territory	Latvia
City	Riga
Period	9/11/23 → 10/11/23

Keywords*

ME/CFS
stratification
biomarkers

Field of Science*

3.2 Clinical medicine
3.1 Basic medicine
3.3 Health sciences
1.6 Biological sciences
5.4 Sociology
5.2 Economy and Business

Publication Type*

3.4. Other publications in conference proceedings (including local)

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Cite this

@conference{b84528ba432c48ffb0ca6e74f25664c5,

title = "Selection of Biomarkers in ME/CFS for Patient Stratification and Treatment Surveillance/Optimisation",

abstract = "ObjectiveWe hypothesized the cohort of ME/CFS patients is divided into several groups/subsets of which one is having primary autoimmune aetiology, another one is triggered by viral infection. The group/subset triggered by viral infection also could have markers of autoimmunity. This study aimed to examine diagnostic potential of serum biomarkers depending on the presence/absence of viral infection biomarkers by direct comparing ME/CFS cases to healthy controls and applying the results from laboratory testing and pathology to the pattern recognition algorithm random forest to widen marker patterns usable in ME/CFS patient stratification.MethodsVarious PCRs were used to detect presence of viral infection, activity phaseand viral load; ELISA to detect antibodies against beta-2 adrenergic and M3/M4acetylcholine receptors, and activin B level; Luminex multiplex technology to detect anti-human immunoglobulin class antibodies and cytokines{\textquoteright} level. Selected statistical/machine learning methods were undertaken to explore the joint potential of biomarkers for classification of ME/CFS patients into severity groups, and this way also monitor the course and treatment effects.ResultsA dataset was used originating from 188 persons, including 54 healthycontrols, 30 patients classified as “mild”, 73 as “moderate”, and 31 as “severe”,clinically assessed by ICC 2011 criteria. Activin B concentration was detectedhigher in subgroups of moderate and severe ME/CFS. The ROC analysis showedthat anti-β2AdR has the best potential to be a good marker of ME/CFS in general,but, as with anti-M4, cannot be a discriminating factor for the severity of ME/CFS.Differences between ME/CFS and control group were observed IgG4 and also IgAlevels. The high scores of IgG4 and IL-2 may indicate the presence of an autoimmune process underlying the ME/CFS onset.ConclusionThe highest classification power from data analysis is attributed to anti-β2AdR,anti-M4, IgG4, but also IL-2 (autoimmune processes marker) and IL-6 (marker forinnate immunity).",

keywords = "ME/CFS, stratification, biomarkers",

author = "Modra Murovska and Angelika Krūmiņa and Sabīne Grāvelsiņa and Anda Vilmane and Santa Rasa-Dzelzkaleja and Zaiga Nora-Krūkle and Diāna Arāja and {\v S}imons Svirskis and Uldis Berķis",

year = "2023",

month = nov,

day = "9",

language = "English",

pages = "23--24",

note = "International Conference Autoimmune Diseases : Main Problems and Solutions ; Conference date: 09-11-2023 Through 10-11-2023",

}

TY - CONF

T1 - Selection of Biomarkers in ME/CFS for Patient Stratification and Treatment Surveillance/Optimisation

AU - Murovska, Modra

AU - Krūmiņa, Angelika

AU - Grāvelsiņa, Sabīne

AU - Vilmane, Anda

AU - Rasa-Dzelzkaleja, Santa

AU - Nora-Krūkle, Zaiga

AU - Arāja, Diāna

AU - Svirskis, Šimons

AU - Berķis, Uldis

PY - 2023/11/9

Y1 - 2023/11/9

N2 - ObjectiveWe hypothesized the cohort of ME/CFS patients is divided into several groups/subsets of which one is having primary autoimmune aetiology, another one is triggered by viral infection. The group/subset triggered by viral infection also could have markers of autoimmunity. This study aimed to examine diagnostic potential of serum biomarkers depending on the presence/absence of viral infection biomarkers by direct comparing ME/CFS cases to healthy controls and applying the results from laboratory testing and pathology to the pattern recognition algorithm random forest to widen marker patterns usable in ME/CFS patient stratification.MethodsVarious PCRs were used to detect presence of viral infection, activity phaseand viral load; ELISA to detect antibodies against beta-2 adrenergic and M3/M4acetylcholine receptors, and activin B level; Luminex multiplex technology to detect anti-human immunoglobulin class antibodies and cytokines’ level. Selected statistical/machine learning methods were undertaken to explore the joint potential of biomarkers for classification of ME/CFS patients into severity groups, and this way also monitor the course and treatment effects.ResultsA dataset was used originating from 188 persons, including 54 healthycontrols, 30 patients classified as “mild”, 73 as “moderate”, and 31 as “severe”,clinically assessed by ICC 2011 criteria. Activin B concentration was detectedhigher in subgroups of moderate and severe ME/CFS. The ROC analysis showedthat anti-β2AdR has the best potential to be a good marker of ME/CFS in general,but, as with anti-M4, cannot be a discriminating factor for the severity of ME/CFS.Differences between ME/CFS and control group were observed IgG4 and also IgAlevels. The high scores of IgG4 and IL-2 may indicate the presence of an autoimmune process underlying the ME/CFS onset.ConclusionThe highest classification power from data analysis is attributed to anti-β2AdR,anti-M4, IgG4, but also IL-2 (autoimmune processes marker) and IL-6 (marker forinnate immunity).

AB - ObjectiveWe hypothesized the cohort of ME/CFS patients is divided into several groups/subsets of which one is having primary autoimmune aetiology, another one is triggered by viral infection. The group/subset triggered by viral infection also could have markers of autoimmunity. This study aimed to examine diagnostic potential of serum biomarkers depending on the presence/absence of viral infection biomarkers by direct comparing ME/CFS cases to healthy controls and applying the results from laboratory testing and pathology to the pattern recognition algorithm random forest to widen marker patterns usable in ME/CFS patient stratification.MethodsVarious PCRs were used to detect presence of viral infection, activity phaseand viral load; ELISA to detect antibodies against beta-2 adrenergic and M3/M4acetylcholine receptors, and activin B level; Luminex multiplex technology to detect anti-human immunoglobulin class antibodies and cytokines’ level. Selected statistical/machine learning methods were undertaken to explore the joint potential of biomarkers for classification of ME/CFS patients into severity groups, and this way also monitor the course and treatment effects.ResultsA dataset was used originating from 188 persons, including 54 healthycontrols, 30 patients classified as “mild”, 73 as “moderate”, and 31 as “severe”,clinically assessed by ICC 2011 criteria. Activin B concentration was detectedhigher in subgroups of moderate and severe ME/CFS. The ROC analysis showedthat anti-β2AdR has the best potential to be a good marker of ME/CFS in general,but, as with anti-M4, cannot be a discriminating factor for the severity of ME/CFS.Differences between ME/CFS and control group were observed IgG4 and also IgAlevels. The high scores of IgG4 and IL-2 may indicate the presence of an autoimmune process underlying the ME/CFS onset.ConclusionThe highest classification power from data analysis is attributed to anti-β2AdR,anti-M4, IgG4, but also IL-2 (autoimmune processes marker) and IL-6 (marker forinnate immunity).

KW - ME/CFS

KW - stratification

KW - biomarkers

UR - https://dspace.rsu.lv/jspui/bitstream/123456789/14984/1/RSU_VirA_konf-2023_ISBN-9789934618338.pdf

M3 - Abstract

SP - 23

EP - 24

T2 - International Conference Autoimmune Diseases

Y2 - 9 November 2023 through 10 November 2023

ER -