Accurate diagnosis and monitoring of neurodegenerative diseases require reliable biomarkers. Cerebrospinal fluid (CSF) proteins are promising candidates for reflecting brain pathology; however, their diagnostic utility may be compromised by natural variability between individuals, weakening their association with disease. Here, we measured the levels of 69 pre-selected proteins in cerebrospinal fluid using antibody-based suspension bead array technology in a multi-disease cohort of 499 individuals with neurodegenerative disorders including Alzheimer’s disease (AD), behavioral variant frontotemporal dementia, primary progressive aphasias, amyotrophic lateral sclerosis (ALS), corticobasal syndrome, primary supranuclear palsy, along with healthy controls. We identify significant inter-individual variability in overall CSF levels of brain-derived proteins, which could not be attributed to specific disease associations. Using linear modelling, we show that adjusting for median CSF levels of brain-derived proteins increases the diagnostic accuracy of proteins previously identified as altered in CSF in the context of neurodegenerative disorders. We further demonstrate a simplified approach for the adjustment using pairs of correlated proteins with opposite alteration in the diseases. With this approach, the proteins adjust for each other and further increase the biomarker performance through additive effect. When comparing the diseases, two proteins—neurofilament medium and myelin basic protein—showed increased levels in ALS compared to other diseases, and neurogranin showed a specific increase in AD. Several other proteins showed similar trends across the studied diseases, indicating that these proteins likely reflect shared processes related to neurodegeneration. Overall, our findings suggest that accounting for inter-individual variability is crucial in future studies to improve the identification and performance of relevant biomarkers. Importantly, we highlight the need for multi-disease studies to identify disease-specific biomarkers.

Alzheimer's disease and related dementias have a multifactorial aetiology and heterogeneous biology. The current study aims to identify different biological signatures in a deeply phenotyped memory clinic patient population. In this cross-sectional study, we analysed 49 pre-specified proteins using a multiplex antibody-based suspension bead array in 278 CSF samples from the real-world research database and biobank at the Karolinska University Hospital Memory Clinic, Solna, Sweden. Patients with a clinical diagnosis of subjective cognitive decline (N = 151), mild cognitive impairment (N = 61), Alzheimer's disease (N = 47), or other diagnoses (N = 19; vascular dementias, alcohol-related dementia, unspecified dementias, or other amnesias) were included. Principal component analyses were performed, and resulting principal components (PCs) were tested for associations with clinical variables and Alzheimer's disease biomarkers (CSF biomarkers beta-amyloid 42, beta-amyloid 42/40, phosphorylated tau 181, phosphorylated tau 181/beta-amyloid 42). PC 1 (explaining 52% of the variance between patients) was associated with the clinical Alzheimer's disease CSF biomarkers beta-amyloid 42, phosphorylated tau 181, and total tau but not with Alzheimer's disease-related neurodegeneration imaging markers, cognitive performance, or clinical diagnosis. PC 2 (explaining 9% of the variance) displayed an inflammatory profile with high contributions of chitinase 3 like 1 (CHI3L1) and triggering receptor expressed on myeloid cells 2 (TREM2) and significant correlation to CSF free light chain kappa. In contrast to PC 1, PC 3 (explaining 5% of the variance) showed associations with all the clinical Alzheimer's disease CSF biomarkers, the imaging markers, cognitive impairment and clinical diagnosis. Serpin family A member 3 (SERPINA3), chitinase 1 (CHIT1), and neuronal pentraxin 2 (NPTX2) contributed most to PC 3. PC 4 (explaining 4% of the variance) exhibited an inflammatory profile distinct from PC 2, with the largest contributions from TREM2, leucine-rich alpha-2-glycoprotein 1 (LRG1) and complement C9. The component was associated with peripheral inflammation. We found that CSF protein profiles in a memory clinic cohort reflect molecular differences across diagnostic groups. Our results emphasize that real-world memory clinic patients can have different ongoing biological processes despite receiving the same diagnosis. In the future, this information could be utilized to identify patient endotypes and uncover precision biomarkers and novel therapeutic targets.

Background: The effect of varying brain ventricular volume on the cerebrospinal fluid (CSF) proteome has been discussed as possible confounding factors in comparative protein level analyses. However, the relationship between CSF volume and protein levels remains largely unexplored. Moreover, the few existing studies provide conflicting findings, indicating the need for further research. Methods: Here, we explored the association between levels of 88 pre-selected CSF proteins and ventricular volume derived from magnetic resonance imaging (MRI) measurements in 157 cognitively healthy 70-year-olds from the H70 Gothenburg Birth Cohort Studies, including individuals with and without pathological levels of Alzheimer’s disease (AD) CSF markers (n = 123 and 34, respectively). Both left and right lateral, the inferior horn as well as the third and the fourth ventricular volumes were measured. Different antibody-based methods were employed for the protein measurements, with most being analyzed using a multiplex bead-based microarray technology. Furthermore, the associations between the protein levels and cortical thickness, fractional anisotropy, and mean diffusivity were assessed. Results: CSF levels of many brain-derived proteins correlated with ventricular volumes in A-T- individuals, with lower levels in individuals with larger ventricles. The strongest negative correlations with total ventricular volume were observed for neurocan (NCAN) and neurosecretory protein VGF (rho = -0.34 for both). Significant negative correlations were observed also for amyloid beta (Ab) 38, Ab40, total tau (t-tau), and phosphorylated tau (p-tau), with correlation ranging between − 0.34 and − 0.28, while no association was observed between ventricular volumes and Ab42 or neurofilament light chain (NfL). Proteins with negative correlations to ventricular volumes further demonstrated negative correlations to mean diffusivity and positive correlation to fractional anisotropy. However, only weak or no correlations were observed between the CSF protein levels and cortical thickness. A + T + individuals demonstrated higher CSF protein levels compared to A-T- individuals with the most significant differences observed for neurogranin (NRGN) and synuclein beta (SNCB). Conclusions: Our findings suggest that the levels of many brain-derived proteins in CSF may be subjected to dilution effects depending on the size of the brain ventricles in healthy individuals without AD pathology. This phenomenon could potentially contribute to the inter-individual variations observed in CSF proteomic studies.

Background: Amyloid and tau aggregates are considered to cause neurodegeneration and consequently cognitive decline in individuals with Alzheimer’s disease (AD). Here, we explore the potential of cerebrospinal fluid (CSF) proteins to reflect AD pathology and cognitive decline, aiming to identify potential biomarkers for monitoring outcomes of disease-modifying therapies targeting these aggregates. Method: We used a multiplex antibody-based suspension bead array to measure the levels of 49 proteins in CSF from the Swedish GEDOC memory clinic cohort at the Karolinska University Hospital. The cohort comprised 148 amyloid- and tau-negative individuals (A-T-) and 65 amyloid- and tau-positive individuals (A+T+). An independent sample set of 26 A-T- and 26 A+T+ individuals from the Amsterdam Dementia Cohort was used for validation. The measured proteins were clustered based on their correlation to CSF amyloid beta peptides, tau and NfL levels. Further, we used support vector machine modelling to identify protein pairs, matched based on their cluster origin, that reflect AD pathology and cognitive decline with improved performance compared to single proteins. Results: The protein-clustering revealed 11 proteins strongly correlated to t-tau and p-tau (tau-associated group), including mainly synaptic proteins previously found elevated in AD such as NRGN, GAP43 and SNCB. Another 16 proteins showed predominant correlation with Aβ42 (amyloid-associated group), including PTPRN2, NCAN and CHL1. Support vector machine modelling revealed that proteins from the two groups combined in pairs discriminated A-T- from A+T+ individuals with higher accuracy compared to single proteins, as well as compared to protein pairs composed of proteins originating from the same group. Moreover, combining the proteins from different groups in ratios (tau-associated protein/amyloid-associated protein) significantly increased their correlation to cognitive decline measured with cognitive scores. The results were validated in an independent cohort. Conclusions: Combining brain-derived proteins in pairs largely enhanced their capacity to discriminate between AD pathology-affected and unaffected individuals and increased their correlation to cognitive decline, potentially due to adjustment of inter-individual variability. With these results, we highlight the potential of protein pairs to monitor neurodegeneration and thereby possibly the efficacy of AD disease-modifying therapies.

Proteins are essential biomolecules that perform a vast array of functions within the human body. The abundance of proteins within cells, tissues, and bodily fluids is dy- namic and can be associated with different physiological and disease states. As such, studying proteins and protein profiles in health and disease can provide insights into the mechanisms and pathological processes associated with different diseases as well as different disease stages. Furthermore, protein biomarkers identified in research have the potential to aid clinical diagnostics and therapeutic development, leading to im- provement of patient care and outcomes. 

The majority of the work included in this thesis, revolves around the analysis of protein profiles in the context of neurodegenerative diseases, with the main focus on demen- tias. In the studies, preselected protein panels were measured in cerebrospinal fluid (CSF) samples employing the multiplexed high-throughput antibody-based suspension bead array technology. 

In paper I, the potential of using protein pairs to reflect Alzheimer’s disease pathology and cognitive decline was explored, with the aim to identify biomarkers which could possibly aid in monitoring the efficacy of disease-modifying treatments in clinical tri- als. A number of protein pairs was identified providing significantly higher performance compared to single proteins, likely due to adjustment for inter-individual variability in general protein levels. 

Paper II built upon the findings from paper I, expanding the investigation of CSF protein patterns across multiple neurodegenerative diseases. This study demonstrated that the performance of single brain-derived proteins in disease prediction is affected by variability in general protein levels, accounting for 70 % of protein variability be- tween individuals irrespective of disease. Adjusting for the general protein levels directly or through combining proteins in pairs improved the performance of proteins as biomarkers. However, the majority of the proteins with altered levels in CSF were not specific for a single disease, suggesting their association to processes common for the diseases, and highlighting the need for disease comparisons in biomarker studies. 

While paper I and II established the presence of variability in general CSF levels of brain-derived proteins between individuals, the factors underlying this variability re- mained unclear. Paper III explored whether the levels of proteins in CSF are influenced by CSF volume in a cohort of healthy individuals. The findings revealed negative correlations of brain-derived proteins with brain ventricular volumes, sug- gesting a dilution effect of proteins in CSF potentially contributing to differences in CSF levels of brain-derived proteins between individuals. In summary, these three Abstract i Abstract studies shed light on CSF protein patterns and their relevance in neurodegenerative diseases, pushing the boundaries of our current knowledge a step forward. 

A specific group of proteins present in the human body; the antibodies, are involved in the defense mechanisms against pathogens. These large molecules are produced by our immune system upon infection (or vaccination), and provide protection against future reinfections. However, the amount of antibodies produced and their protective effect through virus neutralization varies between individuals. Paper IV included in this thesis involved the development of a cell-free and virus-free bead-based assay for assessment of the neutralization capability of antibodies produced against the SARS- COV-2 virus. While this study can be considered an outlier in the theme of this thesis, it represents our contribution to the global research efforts which necessitated other activities to be put on hold in favor of endeavors in response to the rise of the Covid- 19 pandemic. 

Proteiner är essentiella biomolekyler som utför en mängd olika funktioner inom män- niskokroppen. Förekomsten av proteiner inom celler, vävnader och kroppsvätskor är dynamisk och kan associeras med olika fysiologiska tillstånd och sjukdomstillstånd. Att studera proteiner och proteinprofiler vid hälsa och sjukdom kan därför ge insikter om mekanismer och patologiska processer som är associerade med sjukdomar samt sjukdomsstadier. 

Proteiner som identifieras som associerade till en viss sjukdom har potential att under- lätta klinisk diagnostik och medicinsk utveckling, vilket i längden leder till förbättrad patientvård. Den övervägande delen av arbetet i denna avhandling fokuserar på analys av proteinprofiler hos patienter med neurodegenerativa sjukdomar, med huvudinrikt- ning på demenssjukdomar. I studierna mättes förvalda proteinpaneler i cerebrospinal- vätska (CSF) med hjälp av en multiplex antikroppsbaserad teknik. 

I avhandlingens första artikel (paper I) utforskades potentialen hos proteinpar för att reflektera patologi och kognitiv nedsättning hos patienter med Alzheimer's sjukdom, med syfte att identifiera biomarkörer som kan utvärdera effektivitet hos sjukdomsmo- difierande behandlingar i kliniska studier. Resultaten visade att par av proteiner med ursprung i hjärnan speglade sjukdomsprocesserna bättre jämfört med enskilda protei- ner, troligen på grund av att tillägget av ett andra protein kompenserar för inter- individuell variabilitet i generella proteinnivåer. 

Artikel II (paper II) bygger vidare på resultaten från artikel I genom att utvidga ut- forskandet av proteinmönster i CSF till flera neurodegenerativa sjukdomar. Denna studie visade att möjligheten till sjukdomsprediktion hos enskilda hjärnproteiner på- verkas av variationer i generella proteinnivåer, vilka förklarar 70% av variabiliteten mellan individer, oberoende av sjukdom. Direkt justering av proteinnivåer eller juste- ring genom kombination av proteiner i par förbättrade proteinernas prediktiva prestanda. Majoriteten av proteinerna med förändrade nivåer i CSF var emellertid inte specifika för en enskild sjukdom, vilket antyder att de är associerade till processer som är gemensamma för sjukdomarna. Detta visar på ett behov av att jämföra olika sjuk- domar mot varandra i framtida biomarkörsstudier. 

Även om artikel I och II fastställde generell variabilitet i nivåerna av hjärnproteiner mellan individer förblev faktorerna bakom denna variabilitet oklara. Paper III under- söker i en kohort med friska individer om nivåerna av proteiner i CSF påverkas av CSF-volymen. Resultaten påvisade negativ korrelation mellan nivåer av proteiner och hjärnventriklarnas volym, vilket antyder att en möjlig utspädningseffekt bidrar till skillnader i nivåer mellan individer med avseende på proteiner med ursprung i hjärnan. Sammanfattning iii Sammanfattning Sammanfattningsvis beskriver dessa tre studier proteinnivåer i CSF och deras relevans vid neurodegenerativa sjukdomar, vilket tänjer gränserna för vår nuvarande kunskap. 

En specifik grupp av proteiner i människokroppen; antikropparna, är involverade i för- svarsprocesser mot patogener. Dessa stora molekyler produceras av vårt immunsystem vid infektion (eller vaccination) och ger skydd mot framtida återinfektioner. Mängden antikroppar som produceras och deras skyddande effekt genom virusneutralisering va- rierar dock mellan individer. Artikel IV (paper IV) i denna avhandling beskriver utvecklingen av ett cellfritt och virusfritt neutraliseringstest för att bedöma antikropp- pars neutraliseringsförmåga mot SARS-COV-2-viruset. Även om denna studie kan betraktas som avvikande från temat för denna avhandling, representerar den vårt bi- drag till de globala forskningsinsatserna som krävde att andra aktiviteter sattes på paus till förmån för åtgärder som svar på uppkomsten av Covid-19-pandemin. 

Neurodegenerative dementias are progressive diseases that cause neuronal network breakdown in different brain regions often because of accumulation of misfolded proteins in the brain extracellular matrix, such as amyloids or inside neurons or other cell types of the brain. Several diagnostic protein biomarkers in body fluids are being used and implemented, such as for Alzheimer’s disease. However, there is still a lack of biomarkers for co-pathologies and other causes of dementia. Such biofluidbased biomarkers enable precision medicine approaches for diagnosis and treatment, allow to learn more about underlying disease processes, and facilitate the development of patient inclusion and evaluation tools in clinical trials. When designing studies to discover novel biofluidbased biomarkers, choice of technology is an important starting point. But there are so many technologies to choose among. To address this, we here review the technologies that are currently available in research settings and, in some cases, in clinical laboratory practice. This presents a form of lexicon on each technology addressing its use in research and clinics, its strengths and limitations, and a future perspective.

Highly accurate serological tests are key to assessing the prevalence of SARS-CoV-2 antibodies and the level of immunity in the population. This is important to predict the current and future status of the pandemic. With the recent emergence of new and more infectious SARS-CoV-2 variants, assays allowing for high throughput analysis of antibodies able to neutralize SARS-CoV-2 become even more important. Here, we report the development and validation of a robust, high throughput method, which enables the assessment of antibodies inhibiting the binding between the SARS-CoV-2 spike protein and angiotensin converting enzyme 2 (ACE2). The assay uses recombinantly produced spike-f and ACE2 and is performed in a bead array format, which allows analysis of up to 384 samples in parallel per instrument over seven hours, demanding only one hour of manual handling. The method is compared to a microneutralization assay utilising live SARS-CoV-2 and is shown to deliver highly correlating data. Further, a comparison with a serological method that measures all antibodies recognizing the spike protein shows that this type of assessment provides important insights into the neutralizing efficiency of the antibodies, especially for individuals with low antibody levels. This method can be an important and valuable tool for large-scale assessment of antibody-based neutralization, including neutralization of new spike variants that might emerge.

We studied clinical and immunological outcome of Covid-19 in consecutive CLL patients from a well-defined area during month 1–13 of the pandemic. Sixty patients (median age 71 y, range 43–97) were identified. Median CIRS was eight (4–20). Patients had indolent CLL (n = 38), had completed (n = 12) or ongoing therapy (n = 10). Forty-six patients (77%) were hospitalized due to severe Covid-19 and 11 were admitted to ICU. Severe Covid-19 was equally distributed across subgroups irrespective of age, gender, BMI, CLL status except CIRS (p < 0.05). Fourteen patients (23%) died; age ≥75 y was the only significant risk factor (p < 0.05, multivariate analysis with limited power). Comparing month 1–6 vs 7–13 of the pandemic, deaths were numerically reduced from 32% to 18%, ICU admission from 37% to 15% whereas hospitalizations remained frequent (86% vs 71%). Seroconversion occurred in 33/40 patients (82%) and anti-SARS-CoV-2 antibodies were detectable at six and 12 months in 17/22 and 8/11 patients, respectively. Most (13/17) had neutralizing antibodies and 19/28 had antibodies in saliva. SARS-CoV-2-specific T-cells (ELISpot) were detected in 14/17 patients. Covid-19 continued to result in high admission even among consecutive and young early- stage CLL patients. A robust and durable B and/or T cell immunity was observed in most convalescents.

Proteomics studies have shown differential expression of numerous proteins in dementias but have rarely led to novel biomarker tests for clinical use. The Marie Curie MIRIADE project is designed to experimentally evaluate development strategies to accelerate the validation and ultimate implementation of novel biomarkers in clinical practice, using proteomics-based biomarker development for main dementias as experimental case studies. We address several knowledge gaps that have been identified in the field. First, there is the technology-translation gap of different technologies for the discovery (e.g., mass spectrometry) and the large-scale validation (e.g., immunoassays) of biomarkers. In addition, there is a limited understanding of conformational states of biomarker proteins in different matrices, which affect the selection of reagents for assay development. In this review, we aim to understand the decisions taken in the initial steps of biomarker development, which is done via an interim narrative update of the work of each ESR subproject. The results describe the decision process to shortlist biomarkers from a proteomics to develop immunoassays or mass spectrometry assays for Alzheimer's disease, Lewy body dementia, and frontotemporal dementia. In addition, we explain the approach to prepare the market implementation of novel biomarkers and assays. Moreover, we describe the development of computational protein state and interaction prediction models to support biomarker development, such as the prediction of epitopes. Lastly, we reflect upon activities involved in the biomarker development process to deduce a best-practice roadmap for biomarker development.