Proteins are molecules that play central roles in almost all biological processes. Their abundance in cells, tissues, and body fluids is dynamic, reflecting both physiological states and disease-related changes. When studying proteins, a major challenge is distinguishing normal biological variation from alterations that indicate early or ongoing disease. Using proteomics, a term that describes measuring hundreds of proteins at the same time, will deepen our understanding of how protein signatures relate to health and disease. This will assist to establish molecular measurements of so-called biomarkers that support precision medicine through earlier detection, better disease stratification, and more individualized treatment strategies. 

In the studies included in this thesis, we applied affinity proteomics techniques to investigate how levels of antibodies and proteins in blood samples related to health and disease and to expand our understanding of protein-protein interactions of drug targets. 

Although proteins can be measured in different sample types, blood offers a minimally invasive window into our body and to measure molecules coming from many organs and biological processes. Home-sampled dried blood spots (DBS) has gained renewed interest due to the recent development of newer and more accurate sampling cards. In several studies included in this thesis, we demonstrate that DBS can be used in the general population sampling without relying on or involving clinical facilities and healthcare resources. In Paper I, we established an analytical procedure for measuring home-sampled DBS for antibodies against SARS-CoV-2. In Paper II, we expanded this effort to protein measurements and longitudinal sampling. In Paper III, we showed the importance of even more frequent DBS sampling for capturing the dynamic changes of inflammation-related proteins following infection. This demonstrated how these early changes in DBS protein levels can support the timing of clinical interventions. Together, these findings of our studies highlight the potential of DBS for remote and continuous health monitoring for precision health approaches.

Proteins are also among the most common targets of therapeutic drugs. Still, many proteins interact also with other proteins, and such complexes can critically influence how a drug binds to its target, its therapeutic efficacy, and the risk of side effects. In Paper IV, we established an affinity proteomics workflow for validating binding reagents, which we then applied in Paper V to investigate potential protein-protein interactions of membrane proteins. The gained insights and knowledge can contribute to improve our understanding of biologically relevant protein interactions aiding the development of more selective and effective drug candidates. 

Overall, the studies presented in this thesis contribute with valuable insights to the transition toward precision health by enabling scalable remote sampling and by deepening our understanding of protein interactions relevant to both normal physiology and disease.

Proteiner är molekyler som spelar centrala roller i nästan alla biologiska processer. Deras nivåer i celler, vävnader och kroppsvätskor är dynamiska och speglar både normala fysiologiska tillstånd och sjukdomsrelaterade förändringar. En stor utmaning med att studera proteiner är att kunna skilja normal biologisk variation från förändringar som kan indikera tidig eller pågående sjukdom. Genom att använda proteomik, en term för att beskriva mätningen av hundratals proteiner samtidigt, kan vi fördjupa vår förståelse för hur proteinsignaturer relaterar till hälsa och sjukdom. Detta kan i sin tur bidra till att etablera molekylära mätningar av så kallade biomarkörer som kan stödja precisionsmedicin genom tidigare diagnos, bättre riskstratifiering och mer individanpassade behandlingsstrategier.

I studierna som ingår i denna avhandling har vi tillämpat affinitetsbaserade proteomikmetoder. Först för att undersöka hur nivåer av antikroppar och proteiner i blodprover relaterar till hälsa och sjukdom. Sedan för att utöka vår förståelse för protein-protein-interaktioner mellan potentiella läkemedelsmål.

Proteiner kan mätas i många olika provtyper, men blod erbjuder ett minimalt invasivt provmaterial som innehåller molekyler från många organ och biologiska processer. Hemprovtagna torkade blodfläckar (Dried Blood Spots, DBS) har fått förnyat intresse tack vare utvecklingen av nyare och mer tillförlitliga provtagningskort. I flera av studierna i denna avhandling visar vi att DBS är lämpligt för provtagning i befolkningen utan att förlita sig på eller involvera vården. I Artikel I utvecklade vi en analysmetod för att mäta antikroppar mot SARS-CoV-2 i hemtagna DBS-prover. I Artikel II utökade vi detta till proteinmätningar och longitudinell provtagning. I Artikel III visade vi vikten av ännu mer frekvent DBS-provtagning för att fånga de dynamiska förändringarna av inflammationsrelaterade proteiner efter infektion. Detta visade hur dessa tidiga förändringar I DBS-nivåer kan stödja tidpunkten för kliniska ingrepp. Dessa studier visar på potentialen hos DBS som ett verktyg för övervakning och kontinuerlig hälsokontroll inom precisionshälsa utanför sjukhus eller vårdcentraler.

Proteiner är också bland de vanligaste målen för terapeutiska läkemedel, men många proteiner bildar komplex och interagerar med andra proteiner. Dessa interaktioner kan påverka hur läkemedel binder, deras effektivitet och risken för biverkningar. I Artikel IV etablerade vi ett protokoll för att validera bindningsreagens med hjälp av affinitetsmetoder. Den validerade reagensen tillämpade vi sedan i Artikel V för att undersöka potentiella protein-protein-interaktioner hos membranproteiner. Denna kunskap kan i framtiden bidra till att utveckla mer selektiva och effektiva läkemedel.

Sammanfattningsvis bidrar avhandlingens arbeten med värdefulla insikter som stödjer övergången mot precisionshälsa, genom att möjliggöra provtagning utanför sjukhusmiljö och genom att öka vår förståelse för proteininteraktioner som är relevanta för både normal fysiologi och sjukdom.

Aims/hypothesis: Type 1 diabetes manifests after irreversible beta cell damage, highlighting the crucial need for markers of the presymptomatic phase to enable early and effective interventions. Current efforts to identify molecular markers of disease-triggering events lack resolution and convenience. Analysing frequently self-collected dried blood spots (DBS) could enable the detection of early disease-predictive markers and facilitate tailored interventions. Here, we present a novel strategy for monitoring transient molecular changes induced by environmental triggers that enable timely disease interception.

Methods: Whole blood (10 μl) was sampled regularly (every 1–5 days) from adult NOD mice infected with Coxsackievirus B3 (CVB3) or treated with vehicle alone. Blood samples (5 μl) were dried on filter discs. DBS samples were analysed by proximity extension assay. Generalised additive models were used to assess linear and non-linear relationships between protein levels and the number of days post infection (p.i.). A multi-layer perceptron (MLP) classifier was developed to predict infection status. CVB3-infected SOCS-1-transgenic (tg) mice were treated with immune- or non-immune sera on days 2 and 3 p.i., followed by monitoring of diabetes development.

Results: Frequent blood sampling and longitudinal measurement of the blood proteome revealed transient molecular changes in virus-infected animals that would have been missed with less frequent sampling. The MLP classifier predicted infection status after day 2 p.i. with over 90% accuracy. Treatment with immune sera on day 2 p.i. prevented diabetes development in all (100%) of CVB3-infected SOCS-1-tg NOD mice while five out of eight (62.5%) of the CVB3-infected controls treated with non-immune sera developed diabetes.

Conclusions/interpretation: Our study demonstrates the utility of frequently collected DBS samples to monitor dynamic proteome changes induced by an environmental trigger during the presymptomatic phase of type 1 diabetes. This approach enables disease interception and can be translated into human initiatives, offering a new method for early detection and intervention in type 1 diabetes.

Data and code availability: Additional data available at https://doi.org/10.17044/scilifelab.27368322 . Additional visualisations are presented in the Shiny app interface https://mouse-dbs-profiling.serve.scilifelab.se/

Background: Circulating proteins are routinely quantified from liquid biopsies to deduce health and disease. Among these are endocrine protein hormones, which regulate human growth, development, metabolism, and reproduction. Most commonly, these proteins are analyzed in plasma or serum prepared from venous blood draws. Recently, devices for quantitative capillary sampling from a finger prick have emerged, but their utility for clinical testing remains to be explored. Methods: To study the analytical capabilities of quantitative dried blood spots (qDBS), we quantified the luteinizing hormone subunit beta (LHB), follicle-stimulating hormone subunit beta (FSHB), thyroid-stimulating hormone subunit beta (TSHB), prolactin (PRL), and growth hormone 1 (GH1) by multiplexed immunoassays. We determined the performance of the endocrine hormone assays in paired qDBS and EDTA plasma samples from 100 donors (90% females) aged 4 to 78. Lastly, we compared the protein levels with those from an accredited clinical chemistry laboratory. Results: The multiplexed analysis showed precise protein quantifications in qDBS (mean CV = 8.3%), high concordance with plasma levels (r = 0.88 to 0.99), and accuracy being matrix- and protein-dependent (recovery: 80–225%). Using the current protocol and sample dilutions, reported protein concentrations were 1.2 to 7.5 times higher in plasma than in qDBS eluates. Concentrations from multiplexed plasma assays agreed with the clinical data (r = 0.87 to 0.99) and decreased slightly when comparing clinical plasma data with multiplexed qDBS assays (r = 0.76 to 0.98). Significant increases in age-related FSHB and LHB levels were observed in females in all specimens and assays (p < 0.01). Conclusions: This study shows the suitability of modern qDBS devices for quantifying clinically informative proteins in multiplexed assays and highlights the need for future work on specimen-specific optimization and standards. Volumetric DBS sampling offers new routines for accurate protein quantification for precision medicine.

Receptor activity-modifying proteins (RAMPs) form complexes with G protein-coupled receptors (GPCRs) and may regulate their cellular trafficking and pharmacology. RAMP interactions have been identified for about 50 GPCRs, but only a few GPCR-RAMP complexes have been studied in detail. To elucidate a comprehensive GPCR-RAMP interactome, we created a library of 215 dual epitope-tagged (DuET) GPCRs representing all GPCR subfamilies and coexpressed each GPCR with each of the three RAMPs. Screening the GPCR-RAMP pairs with customized multiplexed suspension bead array (SBA) immunoassays, we identified 122 GPCRs that showed strong evidence for interaction with at least one RAMP. We screened for interactions in three cell lines and found 23 endogenously expressed GPCRs that formed complexes with RAMPs. Mapping the GPCR-RAMP interactome expands the current system-wide functional characterization of RAMP-interacting GPCRs to inform the design of selective therapeutics targeting GPCR-RAMP complexes.

Background Self-sampling of dried blood spots (DBS) offers new routes to gather valuable health-related information from the general population. Yet, the utility of using deep proteome profiling from home-sampled DBS to obtain clinically relevant insights about SARS-CoV-2 infections remains largely unexplored.Methods Our study involved 228 individuals from the general Swedish population who used a volumetric DBS sampling device and completed questionnaires at home during spring 2020 and summer 2021. Using multi-analyte COVID-19 serology, we stratified the donors by their response phenotypes, divided them into three study sets, and analyzed 276 proteins by proximity extension assays (PEA). After normalizing the data to account for variances in layman-collected samples, we investigated the association of DBS proteomes with serology and self-reported information.Results Our three studies display highly consistent variance of protein levels and share associations of proteins with sex (e.g., MMP3) and age (e.g., GDF-15). Studying seropositive (IgG+) and seronegative (IgG-) donors from the first pandemic wave reveals a network of proteins reflecting immunity, inflammation, coagulation, and stress response. A comparison of the early-infection phase (IgM+IgG-) with the post-infection phase (IgM-IgG+) indicates several proteins from the respiratory system. In DBS from the later pandemic wave, we find that levels of a virus receptor on B-cells differ between seropositive (IgG+) and seronegative (IgG-) donors.Conclusions Proteome analysis of volumetric self-sampled DBS facilitates precise analysis of clinically relevant proteins, including those secreted into the circulation or found on blood cells, augmenting previous COVID-19 reports with clinical blood collections. Our population surveys support the usefulness of DBS, underscoring the role of timing the sample collection to complement clinical and precision health monitoring initiatives. The COVID-19 pandemic has posed multiple challenges to healthcare systems. A significant gap that remains is a lack of understanding of the impact of SARS-CoV-2 on individuals who did not seek or require hospitalization. To address this, we distribute self-sampling devices to random citizens, aiming to analyze how blood protein levels are affected in people who have had COVID-19 but had no or mild symptoms. Conducting multiple molecular measurements in dried blood, our study confirms clinically known markers and their relationship to infection stages, even if the donors themselves collect the sample. Our work highlights the potential of combining self-sampling with laboratory methods to provide useful information on human health. This convenient patient-centric sampling approach may potentially be useful when studying other diseases. Fredolini et al. present a proteomics analysis of home-sampled dried blood spots taken from the general population in Stockholm during the COVID-19 pandemic. The study provides insights into the molecular effects of SARS-CoV-2 infection in non-hospitalized individuals and demonstrates the compatibility of self-sampled blood spots with proteomics.

Objective: Current breast cancer risk prediction scores and algorithms can potentially be further improved by including molecular markers. To this end, we studied the association of circulating plasma proteins using Proximity Extension Assay (PEA) with incident breast cancer risk. Subjects: In this study, we included 1577 women participating in the prospective KARMA mammographic screening cohort. Results: In a targeted panel of 164 proteins, we found 8 candidates nominally significantly associated with short-term breast cancer risk (P < 0.05). Similarly, in an exploratory panel consisting of 2204 proteins, 115 were found nominally significantly associated (P < 0.05). However, none of the identified protein levels remained significant after adjustment for multiple testing. This lack of statistically significant findings was not due to limited power, but attributable to the small effect sizes observed even for nominally significant proteins. Similarly, adding plasma protein levels to established risk factors did not improve breast cancer risk prediction accuracy. Conclusions: Our results indicate that the levels of the studied plasma proteins captured by the PEA method are unlikely to offer additional benefits for risk prediction of short-term overall breast cancer risk but could provide interesting insights into the biological basis of breast cancer in the future.

Blood sampling is a common practice to monitor health, but it entails a series of drawbacks for patients including pain and discomfort. Thus, there is a demand for more convenient ways to obtain samples. Modern analytical techniques enable monitoring of multiple bioanalytes in smaller samples, opening possibilities for new matrices, and microsampling technologies to be adopted. Interstitial fluid (ISF) is an attractive alternative matrix that shows good correlation with plasma concentration dynamics for several analytes and can be sampled in a minimally invasive and painless manner from the skin at the point-of-care. However, there is currently a lack of sampling devices compatible with clinical translation. Here, to tackle state-of-the-art limitations, a cost-effective and compact single-microneedle-based device designed to painlessly collect precisely 1.1 µL of dermal ISF within minutes is presented. The fluid is volume-metered, dried, and stably stored into analytical-grade paper within the microfluidic device. The obtained sample can be mailed to a laboratory, quantitatively analyzed, and provide molecular insights comparable to blood testing. In a human study, the possibility to monitor various classes of molecular analytes is demonstrated in ISF microsamples, including caffeine, hundreds of proteins, and SARS-CoV-2 antibodies, some being detected in ISF for the first time.

G protein-coupled receptors (GPCRs) control critical cellular signaling pathways. Therapeutic agents including anti-GPCR antibodies (Abs) are being developed to modulate GPCR function. However, validating the selectivity of anti-GPCR Abs is challenging because of sequence similarities among individual receptors within GPCR sub-families. To address this challenge, we developed a multiplexed immunoassay to test >400 anti-GPCR Abs from the Human Protein Atlas targeting a customized library of 215 expressed and solubilized GPCRs representing all GPCR subfamilies. We found that-61% of Abs tested were selective for their intended target,-11% bound off -target, and-28% did not bind to any GPCR. Antigens of on-target Abs were, on average, significantly longer, more disordered, and less likely to be buried in the interior of the GPCR protein than the other Abs. These results provide important insights into the immunogenicity of GPCR epitopes and form a basis for designing therapeu-tic Abs and for detecting pathological auto-Abs against GPCRs.

The definitive diagnosis and early treatment of many immune-mediated inflammatory diseases (IMIDs) is hindered by variable and overlapping clinical manifestations. Psoriatic arthritis (PsA), which develops in similar to 30% of people with psoriasis, is a key example. This mixed-pattern IMID is apparent in entheseal and synovial musculoskeletal structures, but a definitive diagnosis often can only be made by clinical experts or when an extensive progressive disease state is apparent. As with other IMIDs, the detection of multimodal molecular biomarkers offers some hope for the early diagnosis of PsA and the initiation of effective management and treatment strategies. However, specific biomarkers are not yet available for PsA. The assessment of new markers by genomic and epigenomic profiling, or the analysis of blood and synovial fluid/tissue samples using proteomics, metabolomics and lipidomics, provides hope that complex molecular biomarker profiles could be developed to diagnose PsA. Importantly, the integration of these markers with high-throughput histology, imaging and standardized clinical assessment data provides an important opportunity to develop molecular profiles that could improve the diagnosis of PsA, predict its occurrence in cohorts of individuals with psoriasis, differentiate PsA from other IMIDs, and improve therapeutic responses. In this review, we consider the technologies that are currently deployed in the EU IMI2 project HIPPOCRATES to define biomarker profiles specific for PsA and discuss the advantages of combining multi-omics data to improve the outcome of PsA patients.

Protein biomarkers in biological fluids represent an important resource for improving the clinical management of diseases. Current proteomics technologies are capable of performing high-throughput and multiplex profiling in different types of fluids, often leading to the shortlisting of tens of candidate biomarkers per study. However, before reaching any clinical setting, these discoveries require thorough validation and an assay that would be suitable for routine analyses. In the path from biomarker discovery to validation, the performance of the assay implemented for the intended protein quantification is extremely critical toward achieving reliable and reproducible results. Development of robust sandwich immunoassays for individual candidates is challenging and labor and resource intensive, and multiplies when evaluating a panel of interesting candidates at the same time. Here we describe a versatile pipeline that facilitates the systematic and parallel development of multiple sandwich immunoassays using a bead-based technology.