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.

Background: The cervicovaginal epithelial barrier is crucial for defending the female reproductive tract against sexually transmitted infections. Hormones, specifically estradiol and progesterone, along with their respective receptor expressions, play an important role in modulating this barrier. However, the influence of estradiol and progesterone on gene and protein expression in the ectocervical mucosa of naturally cycling women is not well understood. Methods: Mucosal and blood samples were collected from Kenyan female sex workers at high risk of sexually transmitted infections. All samples were obtained at two time points, separated by two weeks, aiming for the follicular and luteal phases of the menstrual cycle. Ectocervical tissue biopsies were analyzed by RNA-sequencing and in situ immunofluorescence staining, cervicovaginal lavage samples (CVL) were evaluated using protein profiling, and plasma samples were analyzed for hormone levels. Results: Unsupervised clustering of RNA-sequencing data was performed using Weighted gene co-expression network analysis (WGCNA). In the follicular phase, estradiol levels positively correlated with a gene module representing epithelial structure and function, and negatively correlated with a gene module representing cell cycle regulation. These correlations were confirmed using regression analysis including adjustment for bacterial vaginosis status. Using WGCNA, no gene module correlated with progesterone levels in the follicular phase. In the luteal phase, no gene module correlated with either estradiol or progesterone levels. Protein profiling on CVL revealed that higher levels of estradiol during the follicular phase correlated with increased expression of epithelial barrier integrity markers, including DSG1. This contrasted to the limited correlations of protein expression with estradiol levels in the luteal phase. In situ imaging analysis confirmed that higher estradiol levels during the follicular phase correlated with increased DSG1 expression. Conclusion: We demonstrate that estradiol levels positively correlate with specific markers of ectocervical epithelial structure and function, particularly DSG1, during the follicular phase of the menstrual cycle. Neither progesterone levels during the follicular phase nor estradiol and progesterone levels during the luteal phase correlated with any specific sets of gene markers. These findings align with the expression of estradiol and progesterone receptors in the ectocervical epithelium during these menstrual phases.

Autoantibodies have been shown to be implied in COVID-19 but the emerging autoantibody repertoire remains largely unexplored. We investigated the new-onset autoantibody repertoire in 525 healthcare workers and hospitalized COVID-19 patients at five time points over a 16-month period in 2020 and 2021 using proteome-wide and targeted protein and peptide arrays. Our results show that prevalent new-onset autoantibodies against a wide range of antigens emerged following SARS-CoV-2 infection in relation to pre-infectious baseline samples and remained elevated for at least 12 months. We found an increased prevalence of new-onset autoantibodies after severe COVID-19 and demonstrated associations between distinct new-onset autoantibodies and neuropsychiatric symptoms post-COVID-19. Using epitope mapping, we determined the main epitopes of selected new-onset autoantibodies, validated them in independent cohorts of neuro-COVID and pre-pandemic healthy controls, and identified sequence similarities suggestive of molecular mimicry between main epitopes and the conserved fusion peptide of the SARS-CoV-2 Spike glycoprotein. Our work describes the complexity and dynamics of the autoantibody repertoire emerging with COVID-19 and supports the need for continued analysis of the new-onset autoantibody repertoire to elucidate the mechanisms of the post-COVID-19 condition.

Background: Plasma biomarkers reflecting the pathology of frontotemporal dementia would add significant value to clinical practice, to the design and implementation of treatment trials as well as our understanding of disease mechanisms. The aim of this study was to explore the levels of multiple plasma proteins in individuals from families with genetic frontotemporal dementia. Methods: Blood samples from 693 participants in the GENetic Frontotemporal Dementia Initiative study were analysed using a multiplexed antibody array targeting 158 proteins. Results: We found 13 elevated proteins in symptomatic mutation carriers, when comparing plasma levels from people diagnosed with genetic FTD to healthy non-mutation controls and 10 proteins that were elevated compared to presymptomatic mutation carriers. Conclusion: We identified plasma proteins with altered levels in symptomatic mutation carriers compared to non-carrier controls as well as to presymptomatic mutation carriers. Further investigations are needed to elucidate their potential as fluid biomarkers of the disease process.

The detection of antibody responses using serological tests provides means to diagnose infections, follow disease transmission, and monitor vaccination responses. The coronavirus disease 2019 (COVID-19) pandemic, caused by the SARS-CoV-2 virus, highlighted the need for rapid development of robust and reliable serological tests to follow disease spreading. Moreover, the rise of SARS-CoV-2 variants emphasized the need to monitor their transmission and prevalence in the population. For this reason, multiplex and flexible serological assays are needed to allow for rapid inclusion of antigens representing new variants as soon as they appear. In this chapter, we describe the generation and application of a multiplex serological test, based on bead array technology, to detect anti-SARS-CoV-2 antibodies in a high-throughput manner, using only a few microliters of sample. This method is currently expanding to include a multi-disease antigen panel that will allow parallel detection of antibodies towards several infectious agents.

Background The majority of studies characterizing female genital tract microbiota have focused on luminal organisms, while the presence and impact of tissue-adherent ectocervical microbiota remain incompletely understood. Studies of luminal and tissue-associated bacteria in the gastrointestinal tract suggest that these communities may have distinct roles in health and disease. Here, we performed a multi-omics characterization of paired luminal and tissue samples collected from a cohort of Kenyan female sex workers.Results We identified a tissue-adherent bacterial microbiome, with a higher alpha diversity than the luminal microbiome, in which dominant genera overall included Gardnerella and Lactobacillus, followed by Prevotella, Atopobium, and Sneathia. About half of the L. iners-dominated luminal samples had a corresponding Gardnerella-dominated tissue microbiome. Broadly, the tissue-adherent microbiome was associated with fewer differentially expressed host genes than the luminal microbiome. Gene set enrichment analysis revealed that L. crispatus-dominated tissue-adherent communities were associated with protein translation and antimicrobial activity, whereas a highly diverse microbial community was associated with epithelial remodeling and pro-inflammatory pathways. Tissue-adherent communities dominated by L. iners and Gardnerella were associated with lower host transcriptional activity. Tissue-adherent microbiomes dominated by Lactobacillus and Gardnerella correlated with host protein profiles associated with epithelial barrier stability, although with a more pro-inflammatory profile for the Gardnerella-dominated microbiome group. Tissue samples with a highly diverse composition had a protein profile representing cell proliferation and pro-inflammatory activity.Conclusion We identified ectocervical tissue-adherent bacterial communities in all study participants of a female sex worker cohort. These communities were distinct from cervicovaginal luminal microbiota in a significant proportion of individuals. We further revealed that bacterial communities at both sites correlated with distinct host gene expression and protein levels. The tissue-adherent bacterial community could possibly act as a reservoir that seed the lumen with less optimal, non-Lactobacillus, bacteria.