Improved diagnosis, prognosis and disease follow-up is a fundamental procedure and a constant challenge in medicine.  Among the different molecular biomarkers, proteins are the essential regulatory component in blood; hence, by developing enhanced specific and sensitive molecular tools will gives great insight into the different processes in disease treatment.  In this thesis, we build on the proximity ligation assay to develop and apply new adaptable methods to facilitate protein detection. In paper I, I present a variant of the proximity ligation assay (we call PLARCA) using micro titer plate for detection and quantification of protein using optical density as readout in the fluorometer. PLARCA detected femtomolar levels of these proteins in patient samples, which was considerably below the detection threshold for ELISA. In paper II, we developed and adapted a new method into the in situ PLA methods for detection and identification of extracellular vesicles (EVs) using flow cytometry as readout (a method we call ExoPLA).  We identified five target proteins on the surface of the Evs and using three colors, we identified the EV using flow cytometer. In paper III, we aim to improve the efficiency of in situ PLA by creating and developing new designs and versions of the assay we called Unfold probes Through comparison of detection of protein using in situ PLA versus Unfold probes, we observed considerable decrease in non-specific signals, and also a lower detection threshold. In paper IV, we describe the development of a solid phase proximity extension (sp-PEA) assay for protein detection and quantification. We compared detection of IL-8, TNF-alpha, IL-10 and IL-6 using spPEA and PEA; spPEA demonstrations over 2 orders of magnitudes in the lower detection concentrations by decreased in background noise.

Cross-reactivity occurs when an antibody binds to the epitope of a protein that is not the targeted antigen. This is problematic in the analysis of immunoassay diagnostics. Detecting a protein incorrectly might cause issues such as incorrect mapping of metabolic conditions for research or diagnosis. In this study, articles have been collected within two main fields. The first of which is focused on bioinformatic tools to predict cross-reactivity risk and the second field investigates how single substitutions affect the antibody-antigen binding. The results from the collected articles were analyzed with the aim of providing as much information surrounding the topic as possible, to gain a further understanding of how protein similarities impact cross-reactivity. FASTA alignments proved to be efficient in classifying cross-reactive proteins based on sequence similarity. Moreover, epitope analysis, using PD tool or Cross-React, can provide an even more precise subset of proteins with risk of causing cross-reactivity. Individual residues of the epitopes of the subset can then be analyzed. Specific residue’s physicochemical properties such as hydrophobicity, polarity, size and charge have proven to be relevant for the binding affinity, with charge having the largest impact. The position of an amino acid has also shown great importance. More centrally located amino acids within the epitope contribute more to paratope affinity than those on the outer positions. However, a conclusive classifier based on specific residues within epitopes is difficult to implement in cross-reactivity analysis. A workflow of the different prediction steps has been constructed into a workflow that may be implemented as an automated pipeline in the future.

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. / 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.

Venös tromboembolism (VTE) inkluderar både djup ventrombos (DVT) och lungemboli (PE) och är en vanlig och komplex kardiovaskulär sjukdom med allvarliga kortsiktiga och långsiktiga komplikationer. I dagens kliniska praxis skulle diagnoseringen av VTE gynnas av en plasmaproteinpanel som antingen kan utesluta fall av akut VTE på egen hand eller komplettera den nuvarande biomarkören D-dimer, som i sig är begränsad av låg specificitet. På grund av den höga återfallsfrekvensen och de allvarliga post-syndromen skulle en plasmaproteinpanel som kan bedöma risken för återkommande VTE underlätta för kliniker i efterbehandlingsbeslut. Mot denna bakgrund syftade denna studie till att föreslå två separata plasmaproteinpaneler, en för att utesluta akuta VTE-patienter och en annan för att bedöma risken för återkommande VTE. Med 1463 unika plasmaproteiner screenades plasmaproteomet hos 194 individer från två undergrupper av venös tromboembolism-biomarkörstudien (VEBIOS), närmare bestämt VEBIOS ER och VEBIOS Coag, med hjälp av proximity extension assay (PEA). Både genuttryck (DE) -analys och maskininlärning (ML) -algoritmer användes för att identifiera signifikanta respektive viktiga proteiner. För akut VTE identifierades 10 signifikanta proteiner genom DE, samt en panel bestående av fem proteiner tillsammans med D-dimer hade tillsammans en area under kurvan (AUC) på 0,97 genom ML. För återkommande VTE identifierades inga signifikanta proteiner och den bästa proteinpanelen hade en AUC på 0,62. Vissa av dessa proteiner har tidigare rapporterats vara associerade med VTE och vissa inte, vilket resulterar i ortogonal validering eller påvisande av en potentiell ny biomarkör. Sammanfattningsvis hittades flera intressanta plasmaproteiner som potentiellt skulle kunna användas för att utesluta fall av akut VTE. GP1BA och S100A12 var särskilt intressanta då de var återkommande som högt ansenliga enligt DE och ML. Resultaten från denna studie kommer förhoppningsvis bidra till forskningen gällande förbättrad diagnos av VTE-patienter genom användning av plasmaproteinmarkörer och argumentationen för ytterligare undersökningar för dessa identifierade plasmaproteiner. / Venous thromboembolism (VTE) is a common and complex cardiovascular disorder with serious short- and long-term complications, comprising both deep vein thrombosis (DVT) and pulmonary embolism (PE). In current clinical practice, diagnosis of acute VTE would greatly benefit from a plasma protein panel that can exclude cases of VTE on its own or complement the current biomarker, D-dimer, which is limited by low specificity. Because of the high recurrence rate and serious post-syndromes, a protein panel that can assess the risk of VTE recurrence would help clinicians in post-treatment decision-making. Hence, this study sought out to propose two separate plasma biomarker panels, one to exclude acute VTE patients and another to risk-assess VTE recurrence.  To accomplish this, 1463 unique plasma proteins were used to investigate the plasma proteome of 194 individuals from two subgroups of the venous thromboembolism biomarker study (VEBIOS), specifically VEBIOS ER and VEBIOS Coag, using proximity extension assay (PEA). Both differential expression (DE) analysis and machine learning (ML) algorithms were used to find significant and important proteins respectively. For acute VTE, 10 significant proteins were identified through DE, and a panel of five proteins together with D-dimer had together an area under the curve (AUC) of 0.97 through ML. For VTE recurrency, no significant proteins were identified, and the best protein panel had an AUC of 0.62. Some of these proteins have previously been reported as associated to VTE and some not, resulting in some orthogonal validation or novelty. In summary, several interesting plasma proteins were found that could potentially be used to exclude cases of VTE in an acute setting. GP1BA and S100A12 were particularly interesting as they performed well in both DE and ML. The results in this study will hopefully aid the research of improving diagnosis of VTE patients using plasma biomarkers, strengthening the claim and further investigations for these identified plasma proteins.

Infertility affects 15% of reproductive-aged couples. The milieu surrounding the growing embryo is of outmost importance, and should be optimised during in vitro fertilisation (IVF). Many biological processes, such as angiogenesis, coagulation, and immune processes need to be well regulated for a pregnancy to occur and progress normally. Histidine-rich glycoprotein (HRG) is a plasma protein that regulates components of these systems by building complexes with various ligands. A single nucleotide polymorphism (SNP) in HRG, denoted HRG C633T, seem to be of importance for IVF treatment outcomes. The aim of this thesis was to further investigate the proposed human fertility effects of the HRG C633T SNP. According to the findings of this thesis, the HRG C633T genotype is associated with primary recurrent miscarriage. Male HRG C633T genotype is associated with semen characteristics in infertile men, and pregnancy rates following IVF. However, the distribution of the HRG C633T SNP does not differ between infertile and fertile couples. We further examined the role of the region surrounding the HRG C633T SNP for regulation of endometrial angiogenesis and human embryo development. The region affects primary endometrial endothelial cell migration, proliferation and tube-formation in vitro but does not appear to affect human embryo development. No effect of the HRG peptide was noted on the secretome of human embryos. However, early embryos secrete proteins into the surrounding culture media and the level of secretion of VEGF-A, IL-6, EMMPRIN and PlGF is greater in embryos of higher developmental stages. In conclusion, the HRG C633T genotype appears to play a role only if infertility is established. The region surrounding HRG C633T SNP is of relevance in vitro for regulation of human endometrial endothelial cell angiogenesis. To predict which embryos to transfer in IVF, we have highlighted a number of proteins of interest for further investigation.

Along with proteins, a myriad of different molecular biomarkers, such as post-translational modifications and autoantibodies, could be used in an attempt to improve disease detection and progression. In this thesis, I build on several iterations of the proximity ligation assay to develop and apply new adaptable methods to facilitate detection of proteins, autoantibodies and post-translational modifications. In paper I, we present an adaptation of the solid-phase proximity ligation assay (SP-PLA) for the detection of post-translational modification of proteins (PTMs). The assay was adapted for the detection of two of the most commons PTMs present in proteins, glycosylation and phosphorylation, offering the encouraging prospect of using detection of PTMs in a diagnostic or prognostic capacity.  In paper II, we developed a variant of the proximity ligation assay using micro titer plate for detection and quantification of protein using optical density as readout in the fluorometer, termed PLARCA. With a detection limit considerably lower than ELISA, PLARCA detected femtomolar levels of these proteins in patient samples. In paper III, we aim to compare detection values of samples collected from earlobe capillary, venous plasma, as well as capillary plasma stored in dried plasma spots (DPS) assessed with a 92-plex inflammation panel using multiplex proximity extension assay (PEA). Despite the high variability in protein measurements between the three sample sources, we were able to conclude that earlobe capillary sampling is a suitable less invasive alternative, to venipuncture. In paper IV, we describe the application of PLARCA and proximity extension assay (PEA) for the detection of GAD65 autoantibodies (GADA). Thus, offering highly sensitive and specific autoimmunity detection.

Chronic pain affects 20 % of the global population, causes suffering, is difficult to treat, and constitutes a large economic burden for society. So far, the characterization of molecular mechanisms of chronic pain-like behaviors in animal models has not translated into effective treatments. In this thesis, consisting of five studies, pain patient biofluids were analyzed with modern proteomic methods to identify biomarker candidates that can be used to improve our understanding of the pathophysiology chronic pain and lead to more effective treatments. Paper I is a proof of concept study, where a multiplex solid phase-proximity ligation assay (SP-PLA) was applied to cerebrospinal fluid (CSF) for the first time. CSF reference protein levels and four biomarker candidates for ALS were presented. The investigated proteins were not altered by spinal cord stimulation (SCS) treatment for neuropathic pain. In Paper II, patient CSF was explored by dimethyl and label-free mass spectrometric (MS) proteomic methods. Twelve proteins, known for their roles in neuroprotection, nociceptive signaling, immune regulation, and synaptic plasticity, were identified to be associated with SCS treatment of neuropathic pain. In Paper III, proximity extension assay (PEA) was used to analyze levels of 92 proteins in serum from patients one year after painful disc herniation. Patients with residual pain had significantly higher serum levels of 41 inflammatory proteins. In Paper IV, levels of 55 proteins were analyzed by a 100-plex antibody suspension bead array (ASBA) in CSF samples from two neuropathic pain patient cohorts, one cohort of fibromyalgia patients and two control cohorts. CSF protein profiles consisting of levels of apolipoprotein C1, ectonucleotide pyrophosphatase/phosphodiesterase family member 2, angiotensinogen, prostaglandin-H2 D-isomerase, neurexin-1, superoxide dismutases 1 and 3 were found to be associated with neuropathic pain and fibromyalgia. In Paper V, higher CSF levels of five chemokines and LAPTGF-beta-1were detected in two patient cohorts with neuropathic pain compared with healthy controls. In conclusion, we demonstrate that combining MS proteomic and multiplex antibody-based methods for analysis of patient biofluid samples is a viable approach for discovery of biomarker candidates for the pathophysiology and treatment of chronic pain. Several biomarker candidates possibly reflecting systemic inflammation, lipid metabolism, and neuroinflammation in different pain conditions were identified for further investigation. / Uppsala Berzelii Technology Centre for Neurodiagnostics