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Abstract 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.

BackgroundThe 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.MethodsMucosal 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.ResultsUnsupervised 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.ConclusionWe 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.

Abstract 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.

Abstract 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.

Abstract 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. Video Abstract

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 correlatedwith 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 proteinexpressionwithestradiol levels inthe 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. [ABSTRACT FROM AUTHOR]

Abstract Background Cellular immune memory responses post coronavirus disease 2019 (COVID‐19) have been difficult to assess due to the risks of contaminating the immune response readout with memory responses stemming from previous exposure to endemic coronaviruses. The work herein presents a large‐scale long‐term follow‐up study investigating the correlation between symptomology and cellular immune responses four to five months post seroconversion based on a unique severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2)‐specific peptide pool that contains no overlapping peptides with endemic human coronaviruses. Methods Peptide stimulated memory T cell responses were assessed with dual interferon‐gamma (IFNγ) and interleukin (IL)‐2 Fluorospot. Serological analyses were performed using a multiplex antigen bead array. Results Our work demonstrates that long‐term SARS‐CoV‐2‐specific memory T cell responses feature dual IFNγ and IL‐2 responses, whereas cross‐reactive memory T cell responses primarily generate IFNγ in response to SARS‐CoV‐2 peptide stimulation. T cell responses correlated to long‐term humoral immune responses. Disease severity as well as specific COVID‐19 symptoms correlated with the magnitude of the SARS‐CoV‐2‐specific memory T cell response four to five months post seroconversion. Conclusion Using a large cohort and a SARS‐CoV‐2‐specific peptide pool we were able to substantiate that initial disease severity and symptoms correlate with the magnitude of the SARS‐CoV‐2‐specific memory T cell responses.

Current SARS-CoV-2 serological assays generate discrepant results, and the longitudinal characteristics of antibodies targeting various antigens after asymptomatic to mild COVID-19 are yet to be established. This longitudinal cohort study including 1965 healthcare workers, of which 381 participants exhibited antibodies against the SARS-CoV-2 spike antigen at study inclusion, reveal that these antibodies remain detectable in most participants, 96%, at least four months post infection, despite having had no or mild symptoms. Virus neutralization capacity was confirmed by microneutralization assay in 91% of study participants at least four months post infection. Contrary to antibodies targeting the spike protein, antibodies against the nucleocapsid protein were only detected in 80% of previously anti-nucleocapsid IgG positive healthcare workers. Both anti-spike and anti-nucleocapsid IgG levels were significantly higher in previously hospitalized COVID-19 patients four months post infection than in healthcare workers four months post infection (p = 2*10−23 and 2*10−13 respectively). Although the magnitude of humoral response was associated with disease severity, our findings support a durable and functional humoral response after SARS-CoV-2 infection even after no or mild symptoms. We further demonstrate differences in antibody kinetics depending on the antigen, arguing against the use of the nucleocapsid protein as target antigen in population-based SARS-CoV-2 serological surveys.

Healthcare workers (HCWs) are a risk group for SARS-CoV-2 infection, but which healthcare work that conveys risk and to what extent such risk can be prevented is not clear. Starting on April 24th, 2020, all employees at work (n = 15,300) at the Karolinska University Hospital, Stockholm, Sweden were invited and 92% consented to participate in a SARS-CoV-2 cohort study. Complete SARS-CoV-2 serology was available for n = 12,928 employees and seroprevalences were analyzed by age, sex, profession, patient contact, and hospital department. Relative risks were estimated to examine the association between type of hospital department as a proxy for different working environment exposure and risk for seropositivity, adjusting for age, sex, sampling week, and profession. Wards that were primarily responsible for COVID-19 patients were at increased risk (adjusted OR 1.95 (95% CI 1.65–2.32) with the notable exception of the infectious diseases and intensive care units (adjusted OR 0.86 (95% CI 0.66–1.13)), that were not at increased risk despite being highly exposed. Several units with similar types of work varied greatly in seroprevalences. Among the professions examined, nurse assistants had the highest risk (adjusted OR 1.62 (95% CI 1.38–1.90)). Although healthcare workers, in particular nurse assistants, who attend to COVID-19 patients are a risk group for SARS-CoV-2 infection, several units caring for COVID-19 patients had no excess risk. Large variations in seroprevalences among similar units suggest that healthcare work-related risk of SARS-CoV-2 infection may be preventable.

To describe the diagnostic and prognostic performance, and longitudinal trajectories, of potential biomarkers of neuroaxonal degeneration and neuroinflammation in amyotrophic lateral sclerosis (ALS). This case-control study included 192 incident ALS patients, 42 ALS mimics, 114 neurological controls, and 117 healthy controls from Stockholm, Sweden. Forty-four ALS patients provided repeated measurements. We assessed biomarkers of (1)neuroaxonal degeneration: neurofilament light (NfL) and phosphorylated neurofilament heavy (pNfH) in cerebrospinal fluid (CSF) and NfL in serum, and (2)neuroinflammation: chitotriosidase-1 (CHIT1) and monocyte chemoattractant protein 1 (MCP-1) in CSF. To evaluate diagnostic performance, we calculated the area under the curve (AUC). To estimate prognostic performance, we applied quantile regression and Cox regression. We used linear regression models with robust standard errors to assess temporal changes over time. Neurofilaments performed better at differentiating ALS patients from mimics (AUC: pNfH 0.92, CSF NfL 0.86, serum NfL 0.91) than neuroinflammatory biomarkers (AUC: CHIT1 0.71, MCP-1 0.56). Combining biomarkers did not improve diagnostic performance. Similarly, neurofilaments performed better than neuroinflammatory biomarkers at predicting functional decline and survival. The stratified analysis revealed differences according to the site of onset: in bulbar patients, neurofilaments and CHIT1 performed worse at predicting survival and correlations were lower between biomarkers. Finally, in bulbar patients, neurofilaments and CHIT1 increased longitudinally but were stable in spinal patients. Biomarkers of neuroaxonal degeneration displayed better diagnostic and prognostic value compared with neuroinflammatory biomarkers. However, in contrast to spinal patients, in bulbar patients neurofilaments and CHIT1 performed worse at predicting survival and seemed to increase over time. [ABSTRACT FROM AUTHOR]

The article titled "Theme 10 - Disease Stratification and Phenotyping of Patients" discusses the importance of accurately categorizing and studying patients with amyotrophic lateral sclerosis (ALS) and frontotemporal degeneration (FTD). The authors emphasize the need for precise disease stratification and phenotyping in order to better understand the underlying mechanisms and develop targeted treatments. The article includes contributions from numerous authors and researchers from various institutions, highlighting the collaborative effort in advancing research on ALS and FTD. [Extracted from the article]

Objective: To test whether high-sensitivity cardiac troponin T (hs-cTnT) could act as a diagnostic or prognostic biomarker in ALS, comparing hs-cTnT to neurofilament light (NfL). Methods: We performed a case-control study, including 150 ALS patients, 28 ALS mimics, and 108 healthy controls, and a follow-up study of the ALS patients, during 2014–2020 in Stockholm, Sweden. We compared concentrations of hs-cTnT in plasma and NfL in the cerebrospinal fluid between cases and controls. To evaluate the diagnostic performance, we calculated the area under the curve (AUC). Hazard ratios (HRs) were estimated from Cox models to assess associations between hs-cTnT and NfL at ALS diagnosis and risk of death. The longitudinal analysis measured changes of hs-cTnT and NfL since ALS diagnosis. Results: We noted higher levels of hs-cTnT in ALS patients (median: 16.5 ng/L) than in ALS mimics (11 ng/L) and healthy controls (6 ng/L). Both hs-cTnT and NfL could distinguish ALS patients from ALS mimics, with higher AUC noted for NfL (AUC 0.88; 95%CI 0.79–0.97). Disease progression correlated weakly with hs-cTnT (Pearson's r = 0.18, p = 0.04) and moderately with NfL (Pearson's r = 0.41, p < 0.001). Shorter survival was associated with higher levels of NfL at diagnosis (HR 1.08, 95%CI 1.04–1.11), but not hs-cTnT. hs-cTnT increased (12.61 ng/L per year, 95%CI 7.14–18.06) whereas NfL decreased longitudinally since ALS diagnosis. Conclusions: NfL is a stronger diagnostic and prognostic biomarker than hs-cTnT for ALS. However, hs-cTnT might constitute a disease progression biomarker as it increases longitudinally. The underlying causes for this increase need to be investigated. [ABSTRACT FROM AUTHOR]