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Profiling the Blood Proteome in Autoimmune Disease Using Proximity Extension Assay
KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science.
2023 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAlternative title
Profilering av blod-proteomet i autoimmuna sjukdomar genom proximity extension assay (Swedish)
Abstract [sv]

Autoimmuna sjukdomar är en samling komplexa, kroniska, inflammatoriska sjukdomstillstånd som kännetecknas av dysreglering av immunsystemet, vilket resulterar i inflammation och skada av vävnader, celler och organ. Dessa sjukdomar har en betydande inverkan på individens livskvalitet och bidrar ofta till ökad dödsrisk där komorbiditeter föreligger. Emellertid medför den varierande symptombilden för olika autoimmuna sjukdomar betydande utmaningar för att uppnå noggrann diagnos, prognos och utvärdering av behandling. Det finns därför ett påtagligt behov av att upptäcka nya biomarkörer. 

I denna studie utfördes en omfattande analys av 944 plasmaprover med hjälp av OlinkR Explore-plattformen, vilket genererade data för 1463 unika proteiner. Baserat på uttrycksdata identifierades proteiner förknippade med de sex utvalda autoimmuna sjukdomarna multipel skleros, myosit, reumatoid artrit, systemisk skleros, Sjögrens sjukdom och systemisk lupus erythematosus samt några av deras definierade subgrupper. Dessa potentiella biomarkörer kommer eventuellt att underlätta tidig diagnos, sjukdomsdifferentiering och prognos. Flertalet av dessa proteiner har ännu aldrig kopplats till de här specifika sjukdomarna i litteraturen, särskilt inte från plasmaprover, vilket ger spännande nya perspektiv för biomarkörsutveckling. Det är dock av största vikt att genomföra robusta valideringsstudier i oberoende kohorter. 

Sammanfattningsvis belyser våra resultat den potentiella brukbarheten hos dessa proteomiska plasmabiomarkörer för att förbättra tidig sjukdomsdetektering, karakterisering av subgrupper och sjukdomsdifferentiering att stimulera. Förhoppningsvis kan dessa resultat stimulera till vidare forskning inom området för biomarkörer och potentiella framsteg inom individbaserad medicin. 

Abstract [en]

Autoimmune diseases are complex, chronic, inflammatory conditions characterized by dysregulation of the immune system, resulting in inflammation and damage to various tissues, cells and organs. These diseases significantly impact individuals’ quality of life and often contribute to increased mortality risk in the presence of comorbidities. However, due to the diverse array of symptoms associated with different autoimmune diseases, accurate diagnosis, prognosis, and treatment evaluation pose significant challenges. Thus, there is a pressing need for the discovery of novel biomarkers. 

In this study, a comprehensive analysis of 944 plasma samples using the OlinkR Explore platform was conducted, generating data on 1463 unique proteins. Based on the expression data, associated proteins were identified for six selected autoimmune diseases, namely multiple sclerosis, myositis, rheumatoid arthritis, systemic sclerosis, Sjögren’s syndrome, and systemic lupus erythematosus, as well as some of their defined subgroups. These are prospective biomarkers and have the potential to aid in early diagnosis, therapeutic intervention, subgroup identification, disease differentiation, and disease prognosis. Notably, some of these proteins have not been previously associated with the specific diseases in the existing literature, especially not in plasma samples, thereby offering intriguing new perspectives for biomarker development. However, it is of great importance to conduct robust validation studies in independent cohorts to confirm the outcomes of this study. 

In summary, our findings highlight the potential utility of these proteomic plasma biomarkers in improving the early detection, subgroup characterization, and disease differentiation of autoimmune diseases. The identification of these proteins will hopefully stimulate further investigation in the field of biomarker research and potential advancements in personalized medicine. 

Place, publisher, year, edition, pages
2023.
Series
TRITA-CBH-GRU ; 2023:197
Keywords [en]
Plasma proteomics, proximity extension assay, autoimmune disease, differential expression, machine learning, biomarkers
Keywords [sv]
Plasma proteomik, proximity extension assay, autoimmuna sjukdomar, differentiellt proteinuttryck, maskininlärning, biomarkörer
National Category
Medical Biotechnology (with a focus on Cell Biology (including Stem Cell Biology), Molecular Biology, Microbiology, Biochemistry or Biopharmacy)
Identifiers
URN: urn:nbn:se:kth:diva-329967OAI: oai:DiVA.org:kth-329967DiVA, id: diva2:1774737
External cooperation
Karolinska Institutet
Subject / course
Biotechnology
Educational program
Master of Science - Medical Biotechnology
Supervisors
Examiners
Available from: 2023-06-15 Created: 2023-06-26

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