Adjuvanted influenza-H1N1 vaccination reveals lymphoid signatures of age-dependent early responses and of clinical adverse events.

Adjuvanted vaccines afford invaluable protection against disease, and the molecular and cellular changes they induce offer direct insight into human immunobiology. Here we show that within 24 h of receiving adjuvanted swine flu vaccine, healthy individuals made expansive, complex molecular and cellular responses that included overt lymphoid as well as myeloid contributions. Unexpectedly, this early response was subtly but significantly different in people older than ∼35 years. Wide-ranging adverse clinical events can seriously confound vaccine adoption, but whether there are immunological correlates of these is unknown. Here we identify a molecular signature of adverse events that was commonly associated with an existing B cell phenotype. Thus immunophenotypic variation among healthy humans may be manifest in complex pathophysiological responses.

Enhancing reproducibility of gene expression analysis with known protein functional relationships: The concept of well-associated protein.

Identification of differentially expressed genes (DEGs) is well recognized to be variable across independent replications of genome-wide transcriptional studies. These are often employed to characterize disease state early in the process of discovery and prioritize novel targets aimed at addressing unmet medical need. Increasing reproducibility of biological findings from these studies could potentially positively impact the success rate of new clinical interventions. This work demonstrates that statistically sound combination of gene expression data with prior knowledge about biology in the form of large protein interaction networks can yield quantitatively more reproducible observations from studies characterizing human disease. The novel concept of Well-Associated Proteins (WAPs) introduced herein-gene products significantly associated on protein interaction networks with the differences in transcript levels between control and disease-does not require choosing a differential expression threshold and can be computed efficiently enough to enable false discovery rate estimation via permutation. Reproducibility of WAPs is shown to be on average superior to that of DEGs under easily-quantifiable conditions suggesting that they can yield a significantly more robust description of disease. Enhanced reproducibility of WAPs versus DEGs is first demonstrated with four independent data sets focused on systemic sclerosis. This finding is then validated over thousands of pairs of data sets obtained by random partitions of large studies in several other diseases. Conditions that individual data sets must satisfy to yield robust WAP scores are examined. Reproducible identification of WAPs can potentially benefit drug target selection and precision medicine studies.

An integrated approach using orthogonal analytical techniques to characterize heparan sulfate structure.

Heparan sulfate (HS), a glycosaminoglycan present on the surface of cells, has been postulated to have important roles in driving both normal and pathological physiologies. The chemical structure and sulfation pattern (domain structure) of HS is believed to determine its biological function, to vary across tissue types, and to be modified in the context of disease. Characterization of HS requires isolation and purification of cell surface HS as a complex mixture. This process may introduce additional chemical modification of the native residues. In this study, we describe an approach towards thorough characterization of bovine kidney heparan sulfate (BKHS) that utilizes a variety of orthogonal analytical techniques (e.g. NMR, IP-RPHPLC, LC-MS). These techniques are applied to characterize this mixture at various levels including composition, fragment level, and overall chain properties. The combination of these techniques in many instances provides orthogonal views into the fine structure of HS, and in other instances provides overlapping / confirmatory information from different perspectives. Specifically, this approach enables quantitative determination of natural and modified saccharide residues in the HS chains, and identifies unusual structures. Analysis of partially digested HS chains allows for a better understanding of the domain structures within this mixture, and yields specific insights into the non-reducing end and reducing end structures of the chains. This approach outlines a useful framework that can be applied to elucidate HS structure and thereby provides means to advance understanding of its biological role and potential involvement in disease progression. In addition, the techniques described here can be applied to characterization of heparin from different sources.

Efficacy and tolerability of an endogenous metabolic modulator (AXA1125) in fatigue-predominant long COVID: a single-centre, double-blind, randomised controlled phase 2a pilot study.

Background: 'Long COVID' describes persistent symptoms, commonly fatigue, lasting beyond 12 weeks following SARS-CoV-2 infection. Potential causes include reduced mitochondrial function and cellular bioenergetics. AXA1125 has previously increased ß-oxidation and improved bioenergetics in preclinical models along with certain clinical conditions, and therefore may reduce fatigue associated with Long COVID. We aimed to assess the efficacy, safety and tolerability of AXA1125 in Long COVID. Methods: Patients with fatigue-dominant Long COVID were recruited in this single-centre, double-blind, randomised controlled phase 2a pilot study completed in the UK. Patients were randomly assigned (1:1) using an Interactive Response Technology to receive either AXA1125 or matching placebo in a clinical-based setting. Each dose (33.9 g) of AXA1125 or placebo was administered orally in a liquid suspension twice daily for four weeks with a two-week follow-up period. The primary endpoint was the mean change from baseline to day 28 in the phosphocreatine (PCr) recovery rate following moderate exercise, assessed by 31P-magnetic resonance spectroscopy (MRS). All patients were included in the intention to treat analysis. This trial was registered at ClinicalTrials.gov, NCT05152849. Findings: Between December 15th 2021, and May 23th 2022, 60 participants were screened, and 41 participants were randomised and included in the final analysis. Changes in skeletal muscle phosphocreatine recovery time constant (τPCr) and 6-min walk test (6MWT) did not significantly differ between treatment (n = 21) and placebo group (n = 20). However, treatment with AXA1125 was associated with significantly reduced day 28 Chalder Fatigue Questionnaire [CFQ-11] fatigue score when compared with placebo (least squares mean difference [LSMD] -4.30, 95% confidence interval (95% CI) -7.14, -1.47; P = 0.0039). Eleven (52.4%, AXA1125) and four (20.0%, placebo) patients reported treatment-emergent adverse events; none were serious or led to treatment discontinuation. Interpretation: Although treatment with AXA1125 did not improve the primary endpoint (τPCr-measure of mitochondrial respiration), when compared to placebo, there were significant improvements in fatigue-based symptoms among patients living with Long COVID following a four-week treatment period. Further multicentre studies are needed to validate our findings in a larger cohort of patients with fatigue-dominant Long COVID. Funding: Axcella Therapeutics.

Multiomic study of skin, peripheral blood, and serum: is serum proteome a reflection of disease process at the end-organ level in systemic sclerosis?

BACKGROUND: Serum proteins can be readily assessed during routine clinical care. However, it is unclear to what extent serum proteins reflect the molecular dysregulations of peripheral blood cells (PBCs) or affected end-organs in systemic sclerosis (SSc). We conducted a multiomic comparative analysis of SSc serum profile, PBC, and skin gene expression in concurrently collected samples. METHODS: Global gene expression profiling was carried out in skin and PBC samples obtained from 49 SSc patients enrolled in the GENISOS observational cohort and 25 unaffected controls. Levels of 911 proteins were determined by Olink Proximity Extension Assay in concurrently collected serum samples. RESULTS: Both SSc PBC and skin transcriptomes showed a prominent type I interferon signature. The examination of SSc serum profile revealed an upregulation of proteins involved in pro-fibrotic homing and extravasation, as well as extracellular matrix components/modulators. Notably, several soluble receptor proteins such as EGFR, ERBB2, ERBB3, VEGFR2, TGFBR3, and PDGF-Rα were downregulated. Thirty-nine proteins correlated with severity of SSc skin disease. The differential expression of serum protein in SSc vs. control comparison significantly correlated with the differential expression of corresponding transcripts in skin but not in PBCs. Moreover, the differentially expressed serum proteins were significantly more connected to the Well-Associated-Proteins in the skin than PBC gene expression dataset. The assessment of the concordance of between-sample similarities revealed that the molecular profile of serum proteins and skin gene expression data were significantly concordant in patients with SSc but not in healthy controls. CONCLUSIONS: SSc serum protein profile shows an upregulation of profibrotic cytokines and a downregulation of soluble EGF and other key receptors. Our multilevel comparative analysis indicates that the serum protein profile in SSc correlates more closely with molecular dysregulations of skin than PBCs and might serve as a reflection of disease severity at the end-organ level.

Edge-count probabilities for the identification of local protein communities and their organization.

We present a computational approach based on a local search strategy that discovers sets of proteins that preferentially interact with each other. Such sets are referred to as protein communities and are likely to represent functional modules. Preferential interaction between module members is quantified via an analytical framework based on a network null model known as the random graph with given expected degrees. Based on this framework, the concept of local protein community is generalized to that of community of communities. Protein communities and higher-level structures are extracted from two yeast protein interaction data sets and a network of published interactions between human proteins. The high level structures obtained with the human network correspond to broad biological concepts such as signal transduction, regulation of gene expression, and intercellular communication. Many of the obtained human communities are enriched, in a statistically significant way, for proteins having no clear orthologs in lower organisms. This indicates that the extracted modules are quite coherent in terms of function.

Combining measurements to estimate properties and characterization extent of complex biochemical mixtures; applications to Heparan Sulfate.

Complex mixtures of molecular species, such as glycoproteins and glycosaminoglycans, have important biological and therapeutic functions. Characterization of these mixtures with analytical chemistry measurements is an important step when developing generic drugs such as biosimilars. Recent developments have focused on analytical methods and statistical approaches to test similarity between mixtures. The question of how much uncertainty on mixture composition is reduced by combining several measurements still remains mostly unexplored. Mathematical frameworks to combine measurements, estimate mixture properties, and quantify remaining uncertainty, i.e. a characterization extent, are introduced here. Constrained optimization and mathematical modeling are applied to a set of twenty-three experimental measurements on heparan sulfate, a mixture of linear chains of disaccharides having different levels of sulfation. While this mixture has potentially over two million molecular species, mathematical modeling and the small set of measurements establish the existence of nonhomogeneity of sulfate level along chains and the presence of abundant sulfate repeats. Constrained optimization yields not only estimations of sulfate repeats and sulfate level at each position in the chains but also bounds on these levels, thereby estimating the extent of characterization of the sulfation pattern which is achieved by the set of measurements.

Analyzing protein lists with large networks: edge-count probabilities in random graphs with given expected degrees.

We present an analytical framework to analyze lists of proteins with large undirected graphs representing their known functional relationships. We consider edge-count variables such as the number of interactions between a protein and a list, the size of a subgraph induced by a list, and the number of interactions bridging two lists. We derive approximate analytical expressions for the probability distributions of these variables in a model of a random graph with given expected degrees. Probabilities obtained with the analytical expressions are used to mine a protein interaction network for functional modules, characterize the connectedness of protein functional categories, and measure the strength of relations between modules.

Equivalent Gene Expression Profiles between Glatopa™ and Copaxone®.

Glatopa™ is a generic glatiramer acetate recently approved for the treatment of patients with relapsing forms of multiple sclerosis. Gene expression profiling was performed as a means to evaluate equivalence of Glatopa and Copaxone®. Microarray analysis containing 39,429 unique probes across the entire genome was performed in murine glatiramer acetate--responsive Th2-polarized T cells, a test system highly relevant to the biology of glatiramer acetate. A closely related but nonequivalent glatiramoid molecule was used as a control to establish assay sensitivity. Multiple probe-level (Student's t-test) and sample-level (principal component analysis, multidimensional scaling, and hierarchical clustering) statistical analyses were utilized to look for differences in gene expression induced by the test articles. The analyses were conducted across all genes measured, as well as across a subset of genes that were shown to be modulated by Copaxone. The following observations were made across multiple statistical analyses: the expression of numerous genes was significantly changed by treatment with Copaxone when compared against media-only control; gene expression profiles induced by Copaxone and Glatopa were not significantly different; and gene expression profiles induced by Copaxone and the nonequivalent glatiramoid were significantly different, underscoring the sensitivity of the test system and the multiple analysis methods. Comparative analysis was also performed on sets of transcripts relevant to T-cell biology and antigen presentation, among others that are known to be modulated by glatiramer acetate. No statistically significant differences were observed between Copaxone and Glatopa in the expression levels (magnitude and direction) of these glatiramer acetate-regulated genes. In conclusion, multiple methods consistently supported equivalent gene expression profiles between Copaxone and Glatopa.

Demonstration of equivalence of a generic glatiramer acetate (Glatopa™).

Glatiramer acetate (GA) has been available under the brand name Copaxone® for nearly two decades. Recently, the US Food and Drug Administration (FDA) approved the first generic GA, Glatopa™, as fully substitutable for all indications for which Copaxone 20mg is approved; Glatopa also represents the first FDA-approved "AP-rated," substitutable generic for treating patients with MS. Glatiramer acetate is a complex mixture of polypeptides and, consequently, its characterization presented challenges not generally encountered in drug development. Despite its complexity, and without requiring any clinical data, approval was accomplished through an Abbreviated New Drug Application in which equivalence to Copaxone was evaluated across four criteria: starting materials and basic chemistry; structural signatures for polymerization, depolymerization, and purification; physicochemical properties; and biological and immunological properties. This article describes the rigorous overall scientific approach used to successfully establish equivalence between Glatopa and Copaxone, and presents key representative data from several of the comprehensive sets of physicochemical (structural) and biological (functional) assays that were conducted.

Detection of activity centers in cellular pathways using transcript profiling.

We present a new computational method for identifying regulated pathway components in transcript profiling (TP) experiments by evaluating transcriptional activity in the context of known biological pathways. We construct a graph representing thousands of protein functional relationships by integrating knowledge from public databases and review articles. We use the notion of distance in a graph to define pathway neighborhoods. The pathways perturbed in an experiment are then identified as the subgraph induced by the genes, referred to as activity centers, having significant density of transcriptional activity in their functional neighborhoods. We illustrate the predictive power of this approach by performing and analyzing an experiment of TP53 overexpression in NCI-H125 cells. The detected activity centers are in agreement with the known TP53 activation effects and our independent experimental results. We also apply the method to a serum starvation experiment using HEY cells and investigate the predicted activity of the transcription factor MYC. Finally, we discuss interesting properties of the activity center approach and its possible applications beyond the comparison of two experiments.

Computational knowledge integration in biopharmaceutical research.

An initiative to increase biopharmaceutical research productivity by capturing, sharing and computationally integrating proprietary scientific discoveries with public knowledge is described. This initiative involves both organisational process change and multiple interoperating software systems. The software components rely on mutually supporting integration techniques. These include a richly structured ontology, statistical analysis of experimental data against stored conclusions, natural language processing of public literature, secure document repositories with lightweight metadata, web services integration, enterprise web portals and relational databases. This approach has already begun to increase scientific productivity in our enterprise by creating an organisational memory (OM) of internal research findings, accessible on the web. Through bringing together these components it has also been possible to construct a very large and expanding repository of biological pathway information linked to this repository of findings which is extremely useful in analysis of DNA microarray data. This repository, in turn, enables our research paradigm to be shifted towards more comprehensive systems-based understandings of drug action.