Increased dystrophin expression in muscle has been accepted as a surrogate endpoint for accelerated approval of gene therapies within Duchenne Muscular Dystrophy (DMD). Previous studies identified an N-terminal titin fragment in urine as a biomarker suitable for monitoring disease progression and therapeutic interventions. Plasma levels of a titin fragment comprising aa 2,229-2,352 were found to negatively correlate with dystrophin expression in mdx mice treated with AAV9-CK8-mu Dys5 micro-dystrophin gene therapy. In this study, we sought to investigate which titin fragments can be detected in serum from patients with DMD and Becker muscular dystrophy (BMD). Using bottom-up selected reaction monitoring tandem mass spectrometry, we identified several serum peptides originating from the central region of titin. Six monospecific antibodies targeting this fragment could recognise a proteolytic titin product at 100 kDa, present in serum from DMD and BMD patients, but not healthy controls. This fragment showed a steeper age-related decline in patients with DMD compared to those with BMD. We further developed a quantitative sandwich immunoassay and showed that the concentrations of this fragment were between 130 and 2,390 pM in DMD patients and 110 and 3,970 pM in BMD patients. The same assay showed titin concentration, between 170 and 990 pM in plasma from treated mdx mice, that had a significant Pearson correlation of -0.76 (P=1.53e-08) with (micro)dystrophin expression in quadriceps. If the negative correlation with dystrophin expression in muscle is also confirmed in DMD patients treated with micro-dystrophin therapies, this serum titin fragment may serve as a potential pharmacodynamic biomarker.

The human blood proteome provides a holistic readout of health states through the assessment of thousands of circulating proteins. In this study, we present a pan-disease resource to enable the study of diverse disease phenotypes within a harmonized proteomics dataset. By profiling protein concentrations across 59 diseases and healthy cohorts, we identified proteins associated with age, sex, and body mass index, as well as disease-specific signatures. This study highlights shared and distinct protein patterns across conditions, demonstrating the power of a unified proteomics approach to uncover biological insights. The dataset, covering 8262 individuals and up to 5416 proteins, serves as an online resource for exploring disease-specific protein profiles and advancing precision medicine research.

Background: Becker muscular dystrophy (BMD) is a rare and heterogeneous form of dystrophinopathy caused by expression of altered dystrophin proteins, as a consequence of in-frame genetic mutations. The majority of the BMD biomarker studies employ targeted approaches and focus on translating findings from Duchenne Muscular Dystrophy (DMD), a more severe disease form with clinical similarities but caused by out-of-frame mutations in the dystrophin gene. Importantly, DMD therapies assume that disease progression can be slowed by promoting the expression of truncated dystrophin comparable to what occurs in BMD patients. In this study, we explore similarities and differences in protein trajectories over time between BMD and DMD serum, and explore proteins related to motor function performance.

Methods: Serum samples collected from 34 BMD patients, in a prospective longitudinal 3-year study, and 19 DMD patients, were analyzed by using Data Independent Acquisition Tandem Mass Spectrometry (DIA-MS). Subsequent normalization, linear mixed effects model was employed to identify proteins associated with physical tests and dystrophin expression in skeletal muscle. Analysis was also performed to explore the discrepancy between DMD and BMD biomarker abundance trajectories over time.

Results: Linear mixed effects models identified 20 proteins with altered longitudinal signatures between DMD and BMD, including creatine kinase M-type (CKM) pyruvate kinase (PKM), fibrinogen gamma chain (FGG), lactate dehydrogenase B (LDHB) and alpha-2-macroglobulin (A2M). Furthermore, several proteins related to innate immune response were associated with motor function in BMD patients. In particular, A2M displayed an altered time-dependent decline in relation to dystrophin expression in the tibialis anterior muscle.

Conclusions: Our study revealed differences in the serum proteome between BMD and DMD, which comprises proteins involved in the immune response, extracellular matrix organization and hemostasis but not muscle leakage proteins significantly associated with disease progression in DMD. If further evaluated and validated, these biomarker candidates may offer means to monitor disease progression in BMD patients. A2M is of particular interest due to its association with dystrophin expression in BMD muscle and higher abundance in DMD patients in comparison to BMD. If validated, A2M could be used as a pharmacodynamic biomarker in therapeutic clinical trials aiming to restore dystrophin expression.

Background: Developing and implementing new patient-centric strategies for drug trials lowers the barrier to participation for some patients by reducing the need to travel to research sites. In early chronic kidney disease (CKD) trials, albuminuria is the key measure for determining treatment effect prior to pivotal kidney outcome trials. Methods: To facilitate albuminuria sample collection outside of a clinical research site, we developed 2 quantitative microsampling methods to determine the urinary albumin to creatinine ratio (UACR). Readout was performed by LC-MS/MS. Results: For the Mitra device the within-batch precision (CV%) was 2.8% to 4.6% and the between-batch precision was 5.3% to 6.1%. Corresponding data for the Capitainer device were 4.0% to 8.6% and 6.7% to 9.0%, respectively. The storage stability at room temperature for 3 weeks was 98% to 103% for both devices. The recovery for the Mitra and Capitainer devices was 104% (SD 7.0%) and 95 (SD 7.4%), respectively. The inter-assay comparison of UACR assessment generated results that were indistinguishable regardless of microsampling technique. The accuracy based on LC-MS/MS vs analysis of neat urine using a clinical chemistry analyzer was assessed in a clinical setting, resulting in 102 ± 8.0% for the Mitra device and 95 ± 10.0% for the Capitainer device. Conclusions: Both UACR microsampling measurements exhibit excellent accuracy and precision compared to a clinical chemistry analyzer using neat urine. We applied our patient-centric sampling strategy to subjects with heart failure in a clinical setting. Precise UACR measurements using quantitative microsampling at home would be beneficial in clinical drug development for kidney therapies.

Mass spectrometry based on data-independent acquisition (DIA) has developed into a powerful quantitative tool with a variety of implications, including precision medicine. Combined with stable isotope recombinant protein standards, this strategy provides confident protein identification and precise quantification on an absolute scale. Here, we describe a comprehensive targeted proteomics approach to profile a pan-cancer cohort consisting of 1800 blood plasma samples representing 15 different cancer types. We successfully performed an absolute quantification of 253 proteins in multiplex. The assay had low intra-assay variability with a coefficient of variation below 20% (CV = 17.2%) for a total of 1013 peptides quantified across almost two thousand injections. This study identified a potential biomarker panel of seven protein targets for the diagnosis of multiple myeloma patients using differential expression analysis and machine learning. The combination of markers, including the complement C1 complex, JCHAIN, and CD5L, resulted in a prediction model with an AUC of 0.96 for the identification of multiple myeloma patients across various cancer patients. All these proteins are known to interact with immunoglobulins.

Mass spectrometry-based bottom-up proteomics is rapidly evolving and routinely applied in large-scale biomedical studies. Proteases are a central component of every bottom-up proteomics experiment, digesting proteins into peptides. Trypsin has been the most widely applied protease in proteomics due to its characteristics. With ever-larger cohort sizes and possible future clinical application of mass spectrometry-based proteomics, the technical impact of trypsin becomes increasingly relevant. To assess possible biases introduced by trypsin digestion, we evaluated the impact of eight commercially available trypsins in a variety of bottom-up proteomics experiments and across a range of protease concentrations and storage times. To investigate the universal impact of these technical attributes, we included bulk HeLa cell lysate, human plasma, and single HEK293 cells, which were analyzed over a range of selected reaction monitoring (SRM), data-independent acquisition (DIA), and data-dependent acquisition (DDA) instrument methods on three LC-MS instruments. The quantification methods employed encompassed both label-free approaches and absolute quantification utilizing spike-in heavy-labeled recombinant protein fragment standards. Based on this extensive data set, we report variations between commercial trypsins, their source, and their concentration. Furthermore, we provide suggestions on the handling of trypsin in large-scale studies.

Background

Molecular components in blood, such as proteins, are used as biomarkers to detect or predict disease states, guide clinical interventions and aid in the development of therapies. While multiplexing proteomics methods promote discovery of such biomarkers, their translation to clinical use is difficult due to the lack of substantial evidence regarding their reliability as quantifiable indicators of disease state or outcome. To overcome this challenge, a novel orthogonal strategy was developed and used to assess the reliability of biomarkers and analytically corroborate already identified serum biomarkers for Duchenne muscular dystrophy (DMD). DMD is a monogenic incurable disease characterized by progressive muscle damage that currently lacks reliable and specific disease monitoring tools.

Methods

Two technological platforms are used to detect and quantify the biomarkers in 72 longitudinally collected serum samples from DMD patients at 3 to 5 timepoints. Quantification of the biomarkers is achieved by detection of the same biomarker fragment either through interaction with validated antibodies in immuno-assays or through quantification of peptides by Parallel Reaction Monitoring Mass Spectrometry assay (PRM-MS).

Results

Five, out of ten biomarkers previously identified by affinity-based proteomics methods, were confirmed to be associated with DMD using the mass spectrometry-based method. Two biomarkers, carbonic anhydrase III and lactate dehydrogenase B, were quantified with two independent methods, sandwich immunoassays and PRM-MS, with Pearson correlations of 0.92 and 0.946 respectively. The median concentrations of CA3 and LDHB in DMD patients was elevated in comparison to those in healthy individuals by 35- and 3-fold, respectively. Levels of CA3 vary between 10.26 and 0.36 ng/ml in DMD patients whereas those of LDHB vary between 15.1 and 0.8 ng/ml.

Conclusions

These results demonstrate that orthogonal assays can be used to assess the analytical reliability of biomarker quantification assays, providing a means to facilitate the translation of biomarkers to clinical practice. This strategy also warrants the development of the most relevant biomarkers, markers that can be reliably quantified with different proteomics methods.

Lipoprotein(a), also known as Lp(a), is an LDL-like particle composed of apolipoprotein(a) (apo(a)) bound covalently to apolipoprotein B100. Plasma concentrations of Lp(a) are highly heritable and vary widely between individuals. Elevated plasma concentration of Lp(a) is considered as an independent, causal risk factor of cardiovascular disease (CVD). Targeted mass spectrometry (LC-SRM/MS) combined with stable isotope-labeled recombinant proteins provides robust and precise quantification of proteins in the blood, making LC-SRM/ MS assays appealing for monitoring plasma proteins for clinical implications. This study presents a novel quantitative approach, based on proteotypic peptides, to determine the absolute concentration of apo(a) from two microliters of plasma and qualified according to guideline requirements for targeted proteomics assays. After optimization, assay parameters such as linearity, lower limits of quantification (LLOQ), intra-assay variability (CV: 4.7%) and inter-assay repeatability (CV: 7.8%) were determined and the LC-SRM/MS results were benchmarked against a commercially available immunoassay. In summary, the measurements of an apo(a) single copy specific peptide and a kringle 4 specific peptide allow for the determination of molar concentration and relative size of apo(a) in individuals.

Protein quantification strategies using multiple proteases have been shown to deliver poor interprotease accuracy in label-free mass spectrometry experiments. By utilizing six different proteases with different cleavage sites, this study explores the protease bias and its effect on accuracy and precision by using recombinant protein standards. We established 557 SRM assays, using a recombinant protein standard resource, toward 10 proteins in human plasma and determined their concentration with multiple proteases. The quantified peptides of these plasma proteins spanned 3 orders of magnitude (0.02-70 μM). In total, 60 peptides were used for absolute quantification and the majority of the peptides showed high robustness. The retained reproducibility was achieved by quantifying plasma proteins using spiked stable isotope standard recombinant proteins in a targeted proteomics workflow. 

Proteins are key components of any living organism and an essential part of life itself. They can provide cells with structure and perform life-sustaining intracellular reactions. As organisms grow more complex, this task expands even further. The proteins’ areas of responsibility suddenly also include communication and coordination between cells and throughout entire organisms, such as the human body. Everything that can be touched and felt on a living organism is composed of millions and millions of proteins tightly packed together. They are even the molecules responsible for propagating the signals that make up the sense of feeling. Understanding the role of proteins in the complex system of life is essential for understanding what makes up a healthy human and what causes disease. This knowledge makes up the foundation of modern medicine, and to further this knowledge, allowing for new treatments and preventative interventions, the study of proteins is crucial. The large-scale study of proteins, proteomics, is an extensive field of research where a vast toolbox of technologies has been implemented. The foundation for this toolbox is made up of mass spectrometry- and affinity-based technologies.

In this thesis, both mass spectrometry-based proteomics and affinity-based proteomics will be explored. The first part, Paper I and Paper II, describe the use of selected reaction monitoring for measuring proteins of clinical relevance in human blood plasma. The second part, Paper III and Paper IV, highlight the importance of validating reagents used for affinity-based proteomics and how this can be achieved in a high throughput manner. Lastly, Paper V showcases how a combined strategy, relying on both affinity-based proteomics and mass spectrometry-based proteomics, can capitalize on the best properties of each technology and how this combined strategy can even be utilized for diagnostic purposes.

Proteiner är livsviktiga molekyler som både förser celler med struktur och utför diverse reaktioner och uppgifter som håller cellerna vid liv. Ju mer komplex en organism är, desto svårare blir proteinernas uppgifter. I en organism som består av flera celler, såsom människor och djur, räcker det inte längre att varje cell sköter sina reaktioner och undertaganden separat, utan alla sådana processer måste koordineras. Denna koordinering utförs också av proteinerna. Proteinerna utgör en så stor del av livet att om du rör vid något levande så är det i regel proteiner som bygger upp den yta du känner. De är till och med så tätt ordnade att varje liten cell består av miljoner och åter miljoner proteiner. Inte nog med detta. Att du ens kan känna att du tar på en annan varelse eller föremål är också något som proteiner ser till. De ansvarar för att föra vidare signalerna från handen till hjärnan och att du sedan uppfattar detta som ett föremål. Det är därför inte förvånande att man måste förstå proteinernas uppgifter i alla möjliga situationer för att kunna veta hur en frisk människa fungerar och därmed avgöra när någon är sjuk. Detta ligger till grund för hela medicinfältet. För att kunna komma på nya behandlingar och för att rentav kunna förebygga sjukdomar är det nödvändigt att ha så mycket kunskap som möjligt om hur proteiner fungerar. Att studera proteiner i stor skala brukar kallas för proteomik och detta område har utvecklats något oerhört de senaste årtionden och det finns en mängd olika tekniker för att undersöka proteiner på. De flesta av dessa tekniker bygger dock på två huvudområden: masspektrometri och affinitetsreagens.

I den här avhandlingen har båda dessa områden utforskats. Den första delen av avhandlingen, som utgörs av Artikel I och Artikel II, bygger på masspektrometri. Här används så kallad riktad proteomik för att mäta proteinnivåerna av kliniska markörer i blodplasma. I del två, som utgörs av Artikel III och Artikel IV, undersöks istället affinitetsreagens och hur man kan försäkra sig om att de binder till de protein som man tror att de binder till i en stor skala. Slutligen kombineras båda dessa två områden i Artikel V och används för att undersöka förekomsten av SARS-CoV-2 i en asymtomatisk grupp människor.