The respiratory system, including the lungs, is essential for terrestrial life. While recent research has advanced our understanding of lung development, much still relies on animal models and transcriptome analyses. In this study conducted within the Human Developmental Cell Atlas (HDCA) initiative, we describe the protein-level spatiotemporal organization of the lung during the first trimester of human gestation. Using high-parametric tissue imaging with a 30-plex antibody panel, we analyzed human lung samples from 6 to 13 post-conception weeks, generating data from over 2 million cells across five developmental timepoints. We present a resource detailing spatially resolved cell type composition of the developing human lung, including proliferative states, immune cell patterns, spatial arrangement traits, and their temporal evolution. This represents an extensive single-cell resolved protein-level examination of the developing human lung and provides a valuable resource for further research into the developmental roots of human respiratory health and disease.

Sountoulidis et al. provide a spatial gene expression atlas of human embryonic lung during the first trimester of gestation and identify 83 cell identities corresponding to stable cell types or transitional states. The lung contains numerous specialized cell types with distinct roles in tissue function and integrity. To clarify the origins and mechanisms generating cell heterogeneity, we created a comprehensive topographic atlas of early human lung development. Here we report 83 cell states and several spatially resolved developmental trajectories and predict cell interactions within defined tissue niches. We integrated single-cell RNA sequencing and spatially resolved transcriptomics into a web-based, open platform for interactive exploration. We show distinct gene expression programmes, accompanying sequential events of cell differentiation and maturation of the secretory and neuroendocrine cell types in proximal epithelium. We define the origin of airway fibroblasts associated with airway smooth muscle in bronchovascular bundles and describe a trajectory of Schwann cell progenitors to intrinsic parasympathetic neurons controlling bronchoconstriction. Our atlas provides a rich resource for further research and a reference for defining deviations from homeostatic and repair mechanisms leading to pulmonary diseases.

Longitudinal and high-dimensional measurements have become increasingly common in biomedical research. However, methods to predict survival outcomes using covariates that are both longitudinal and high-dimensional are currently missing. In this article, we propose penalized regression calibration (PRC), a method that can be employed to predict survival in such situations. PRC comprises three modeling steps: First, the trajectories described by the longitudinal predictors are flexibly modeled through the specification of multivariate mixed effects models. Second, subject-specific summaries of the longitudinal trajectories are derived from the fitted mixed models. Third, the time to event outcome is predicted using the subject-specific summaries as covariates in a penalized Cox model. To ensure a proper internal validation of the fitted PRC models, we furthermore develop a cluster bootstrap optimism correction procedure that allows to correct for the optimistic bias of apparent measures of predictiveness. PRC and the CBOCP are implemented in the R package pencal, available from CRAN. After studying the behavior of PRC via simulations, we conclude by illustrating an application of PRC to data from an observational study that involved patients affected by Duchenne muscular dystrophy, where the goal is predict time to loss of ambulation using longitudinal blood biomarkers.

Spatial and temporal variations among individual human cell proteomes are comprehensively mapped across the cell cycle using proteomic imaging and transcriptomics. The cell cycle, over which cells grow and divide, is a fundamental process of life. Its dysregulation has devastating consequences, including cancer(1-3). The cell cycle is driven by precise regulation of proteins in time and space, which creates variability between individual proliferating cells. To our knowledge, no systematic investigations of such cell-to-cell proteomic variability exist. Here we present a comprehensive, spatiotemporal map of human proteomic heterogeneity by integrating proteomics at subcellular resolution with single-cell transcriptomics and precise temporal measurements of individual cells in the cell cycle. We show that around one-fifth of the human proteome displays cell-to-cell variability, identify hundreds of proteins with previously unknown associations with mitosis and the cell cycle, and provide evidence that several of these proteins have oncogenic functions. Our results show that cell cycle progression explains less than half of all cell-to-cell variability, and that most cycling proteins are regulated post-translationally, rather than by transcriptomic cycling. These proteins are disproportionately phosphorylated by kinases that regulate cell fate, whereas non-cycling proteins that vary between cells are more likely to be modified by kinases that regulate metabolism. This spatially resolved proteomic map of the cell cycle is integrated into the Human Protein Atlas and will serve as a resource for accelerating molecular studies of the human cell cycle and cell proliferation.

Background: Duchenne Muscular Dystrophy is a severe, incurable disorder caused by mutations in the dystrophin gene. The disease is characterized by decreased muscle function, impaired muscle regeneration and increased inflammation. In a clinical context, muscle deterioration, is evaluated using physical tests and analysis of muscle biopsies, which fail to accurately monitor the disease progression. Objectives: This study aims to confirm and asses the value of blood protein biomarkers as disease progression markers using one of the largest longitudinal collection of samples. Methods: A total of 560 samples, both serum and plasma, collected at three clinical sites are analyzed using a suspension bead array platform to assess 118 proteins targeted by 250 antibodies in microliter amount of samples. Results: Nine proteins are confirmed as disease progression biomarkers in both plasma and serum. Abundance of these biomarkers decreases as the disease progresses but follows different trajectories. While carbonic anhydrase 3, microtubule associated protein 4 and collagen type I alpha 1 chain decline rather constantly over time, myosin light chain 3, electron transfer flavoprotein A, troponin T, malate dehydrogenase 2, lactate dehydrogenase B and nestin plateaus in early teens. Electron transfer flavoprotein A, correlates with the outcome of 6-minutes-walking-test whereas malate dehydrogenase 2 together with myosin light chain 3, carbonic anhydrase 3 and nestin correlate with respiratory capacity. Conclusions: Nine biomarkers have been identified that correlate with disease milestones, functional tests and respiratory capacity. Together these biomarkers recapitulate different stages of the disorder that, if validated can improve disease progression monitoring.

Abstract

Background

Duchenne muscular dystrophy (DMD) is a fatal disease for which no cure is available. Clinical trials have shown to be largely underpowered due to inter‐individual variability and noisy outcome measures. The availability of biomarkers able to anticipate clinical benefit is highly needed to improve clinical trial design and facilitate drug development.

Methods

In this study, we aimed to appraise the value of protein biomarkers to predict prognosis and monitor disease progression or treatment outcome in patients affected by DMD. We collected clinical data and 303 blood samples from 157 DMD patients in three clinical centres; 78 patients contributed multiple blood samples over time, with a median follow‐up time of 2 years. We employed linear mixed models to identify biomarkers that are associated with disease progression, wheelchair dependency, and treatment with corticosteroids and performed survival analysis to find biomarkers whose levels are associated with time to loss of ambulation.

Results

Our analysis led to the identification of 21 proteins whose levels significantly decrease with age and nine proteins whose levels significantly increase. Seven of these proteins are also differentially expressed in non‐ambulant patients, and three proteins are differentially expressed in patients treated with glucocorticosteroids. Treatment with corticosteroids was found to partly counteract the effect of disease progression on two biomarkers, namely, malate dehydrogenase 2 (MDH2, P = 0.0003) and ankyrin repeat domain 2 (P = 0.0005); however, patients treated with corticosteroids experienced a further reduction on collagen 1 serum levels (P = 0.0003), especially following administration of deflazacort. A time to event analysis allowed to further support the use of MDH2 as a prognostic biomarker as it was associated with an increased risk of wheelchair dependence (P = 0.0003). The obtained data support the prospective evaluation of the identified biomarkers in natural history and clinical trials as exploratory biomarkers.

Multiple sclerosis (MS) is a chronic inflammatory, likely autoimmune disease of the central nervous system with a combination of genetic and environmental risk factors, among which Epstein-Barr virus (EBV) infection is a strong suspect. We have previously identified increased autoantibody levels toward the chloride-channel protein Anoctamin 2 (ANO2) in MS. Here, IgG antibody reactivity toward ANO2 and EBV nuclear antigen 1 (EBNA1) was measured using bead-based multiplex serology in plasma samples from 8,746 MS cases and 7,228 controls. We detected increased anti-ANO2 antibody levels in MS (P = 3.5 x 10(-36)) with 14.6% of cases and 7.8% of controls being ANO2 seropositive (odds ratio [OR] = 1.6; 95% confidence intervals [95% CI]: 1.5 to 1.8). The MS risk increase in ANO2-seropositive individuals was dramatic when also exposed to 3 known risk factors for MS: HLA-DRB1*15: 01 carriage, absence of HLA-A*02: 01, and high anti-EBNA1 antibody levels (OR = 24.9; 95% CI: 17.9 to 34.8). Reciprocal blocking experiments with ANO2 and EBNA1 peptides demonstrated antibody cross-reactivity, mapping to ANO2 [aa 140 to 149] and EBNA1 [aa 431 to 440]. HLA gene region was associated with anti-ANO2 antibody levels and HLADRB1*04: 01 haplotype was negatively associated with ANO2 seropositivity (OR = 0.6; 95% CI: 0.5 to 0.7). Anti-ANO2 antibody levels were not increased in patients from 3 other inflammatory disease cohorts. The HLA influence and the fact that specific IgG production usually needs T cell help provides indirect evidence for a T cell ANO2 autoreactivity in MS. We propose a hypothesis where immune reactivity toward EBNA1 through molecular mimicry with ANO2 contributes to the etiopathogenesis of MS.

Multiple sclerosis (MS) treatment options have improved significantly over the past decades, but the consequences of MS can still be devastating and the needs for monitoring treatment surveillance are considerable. In the current study we used affinity proteomics technology to identify potential biomarkers which could ultimately be used to as facilitate treatment decisions. We profiled the intra-individual changes in the levels of 59 target proteins using an antibody suspension bead array in serial plasma samples from 44 MS patients during treatment with natalizumab followed by fingolimod. Nine proteins showed decreasing plasma levels during natalizumab treatment, with PEBP1 and RTN3 displaying the most significant changes. Protein levels remained stable during fingolimod treatment for both proteins. The decreasing PEBP1 levels during natalizumab treatment could be validated using ELISA and replicated in an independent cohort. These results support the use of this technology as a high throughput method of identifying potentially useful biomarkers of MS treatment.

Objective Anti-citrullinated protein antibodies (ACPAs) develop many years before the clinical onset of rheumatoid arthritis (RA). This study was undertaken to address the molecular basis of the specificity and cross-reactivity of ACPAs from patients with RA. Methods Antibodies isolated from RA patients were expressed as monoclonal chimeric antibodies with mouse Fc. These antibodies were characterized for glycosylation using mass spectrometry, and their cross-reactivity was assessed using Biacore and Luminex immunoassays. The crystal structures of the antigen-binding fragment (Fab) of the monoclonal ACPA E4 in complex with 3 different citrullinated peptides were determined using x-ray crystallography. The prevalence of autoantibodies reactive against 3 of the citrullinated peptides that also interacted with E4 was investigated by Luminex immunoassay in 2 Swedish cohorts of RA patients. Results Analysis of the crystal structures of a monoclonal ACPA from human RA serum in complex with citrullinated peptides revealed key residues of several complementarity-determining regions that recognized the citrulline as well as the neighboring peptide backbone, but with limited contact with the side chains of the peptides. The same citrullinated peptides were recognized by high titers of serum autoantibodies in 2 large cohorts of RA patients. Conclusion These data show, for the first time, how ACPAs derived from human RA serum recognize citrulline. The specific citrulline recognition and backbone-mediated interactions provide a structural explanation for the promiscuous recognition of citrullinated peptides by RA-specific ACPAs.

OBJECTIVES: The detection of anti-citrullinated peptide antibodies (ACPAs) is a serological hallmark of RA. Autoantibodies reactive with collagen type II (CII) are present in RA sera and synovial fluid and are potentially pathogenic. Here, we investigate the prevalence and specificity of the autoantibody responses to defined citrullinated cyclic peptides derived from CII in a China RA cohort. METHODS: Using bead-based multiplex assay, we examined the presence of autoantibodies binding to 54 cyclic 17-mer citrullinated CII peptides, encompassing all citrullinate epitopes in CII, and the corresponding unmodified peptides in 415 RA patients, in addition to 304 patients with OA. Furthermore, the autoantibody responses to a selected set of 10 cyclic citrullinated peptides were also examined in 203 healthy individuals. RESULTS: Autoantibody responses to cyclic citrullinated CII peptides were higher in RA patients as compared with OA patients or healthy individuals, whereas little or negligible antibody responses to cyclic unmodified CII peptides were observed. Interestingly, several novel citrullinated CII epitopes were identified. Antibodies to these novel citrullinated CII epitopes showed not only substantial overlapping reactivities but also had unique specificities. CONCLUSION: We found a high prevalence of autoantibodies against cyclic citrullinated CII in the sera of patients in a China RA cohort. The present study revealed heterogeneous binding patterns against novel citrullinated CII epitopes, which may help to stratify RA patients into different subgroups.