Establishing correlates of maternal-fetal cytomegalovirus transmission-one step closer through predictive modeling.

BACKGROUND: Determinants of maternal-fetal cytomegalovirus (CMV) transmission and factors influencing the severity of congenital CMV (cCMV) infection are not well understood. METHODS: We conducted a descriptive, multi-center study in pregnant women ≥18 years old with primary CMV infection and their newborns (NCT01251744) to explore maternal immune responses to CMV and determine potential immunologic/virologic correlates of cCMV following primary infection during pregnancy. We developed alternative approaches looking into univariate/multivariate factors associated with cCMV, including a participant clustering/stratification approach and an interpretable predictive model-based approach using trained decision trees for risk prediction (post-hoc analyses). RESULTS: Pregnant women were grouped in three distinct clusters with similar baseline characteristics, particularly gestational age at diagnosis. We observed a trend for higher viral loads in urine and saliva samples from mothers of infants with cCMV versus without cCMV. When using a trained predictive-model approach that accounts for interaction effects between variables, anti-pentamer IgG antibody concentration and viral load in saliva were identified as biomarkers jointly associated with the risk of maternal-fetal CMV transmission. CONCLUSION: We identified biomarkers of CMV maternal-fetal transmission. After validation in larger studies, our findings will guide the management of primary infection during pregnancy and the development of vaccines against cCMV.

The human cytomegalovirus (CMV) is common and usually causes no symptoms in healthy individuals. However, CMV infections can be life-threatening in individuals with improperly functioning or immature immune systems, such as fetuses. Women can become infected with CMV for the first time (primary infection) during pregnancy. If CMV is transmitted from mother to fetus before the second trimester, the infant can suffer from severe disorders such as hearing loss and delayed development. We aimed to identify characteristics of pregnant women with a primary CMV infection that may increase the likelihood of transmitting CMV to the fetus. We considered demographical, clinical, and behavioral characteristics, as well as immune responses and the quantity of virus detected in the women's blood, urine, saliva, and vaginal mucus. Because we could not identify one single characteristic that could predict a high risk of CMV transmission, we developed new data analysis models to study how they can be combined. We found that antibodies targeting a pentameric antigen of the virus envelope and the presence of virus in saliva can together predict the risk of CMV transmission from mother to fetus. Our results can help improve the care of CMV-infected pregnant women and the design of CMV vaccines.

Modeling adaptive response profiles in a vaccine clinical trial.

BACKGROUND: Vaccine clinical studies typically provide time-resolved data on adaptive response read-outs in response to the administration of that particular vaccine to a cohort of individuals. However, modeling such data is challenged by the properties of these time-resolved profiles such as non-linearity, scarcity of measurement points, scheduling of the vaccine at multiple time points. Linear Mixed Models (LMM) are often used for the analysis of longitudinal data but their use in these time-resolved immunological data is not common yet. Apart from the modeling challenges mentioned earlier, selection of the optimal model by using information-criterion-based measures is far from being straight-forward. The aim of this study is to provide guidelines for the application and selection of LMMs that deal with the challenging characteristics of the typical data sets in the field of vaccine clinical studies. METHODS: We used antibody measurements in response to Hepatitis-B vaccine with five different adjuvant formulations for demonstration purposes. We built piecewise-linear, piecewise-quadratic and cubic models with transformations of the axes with pre-selected or optimized knot locations where time is a numerical variable. We also investigated models where time is categorical and random effects are shared intercepts between different measurement points. We compared all models by using Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), Deviance Information Criterion (DIC), variations of conditional AIC and by visual inspection of the model fit in the light of prior biological information. RESULTS: There are various ways of dealing with the challenges of the data which have their own advantages and disadvantages. We explain these in detail here. Traditional information-criteria-based measures work well for the coarse selection of the model structure and complexity, however are not efficient at fine tuning of the complexity level of the random effects. CONCLUSIONS: We show that common statistical measures for optimal model complexity are not sufficient. Rather, explicitly accounting for model purpose and biological interpretation is needed to arrive at relevant models. TRIAL REGISTRATION: Clinical trial registration number for this study: NCT00805389, date of registration: December 9, 2008 (pro-active registration).

Systems analysis of protective immune responses to RTS,S malaria vaccination in humans.

RTS,S is an advanced malaria vaccine candidate and confers significant protection against Plasmodium falciparum infection in humans. Little is known about the molecular mechanisms driving vaccine immunity. Here, we applied a systems biology approach to study immune responses in subjects receiving three consecutive immunizations with RTS,S (RRR), or in those receiving two immunizations of RTS,S/AS01 following a primary immunization with adenovirus 35 (Ad35) (ARR) vector expressing circumsporozoite protein. Subsequent controlled human malaria challenge (CHMI) of the vaccinees with Plasmodium-infected mosquitoes, 3 wk after the final immunization, resulted in ∼50% protection in both groups of vaccinees. Circumsporozoite protein (CSP)-specific antibody titers, prechallenge, were associated with protection in the RRR group. In contrast, ARR-induced lower antibody responses, and protection was associated with polyfunctional CD4+ T-cell responses 2 wk after priming with Ad35. Molecular signatures of B and plasma cells detected in PBMCs were highly correlated with antibody titers prechallenge and protection in the RRR cohort. In contrast, early signatures of innate immunity and dendritic cell activation were highly associated with protection in the ARR cohort. For both vaccine regimens, natural killer (NK) cell signatures negatively correlated with and predicted protection. These results suggest that protective immunity against P. falciparum can be achieved via multiple mechanisms and highlight the utility of systems approaches in defining molecular correlates of protection to vaccination.

Axonal transport deficits in multiple sclerosis: spiraling into the abyss.

The transport of mitochondria and other cellular components along the axonal microtubule cytoskeleton plays an essential role in neuronal survival. Defects in this system have been linked to a large number of neurological disorders. In multiple sclerosis (MS) and associated models such as experimental autoimmune encephalomyelitis (EAE), alterations in axonal transport have been shown to exist before neurodegeneration occurs. Genome-wide association (GWA) studies have linked several motor proteins to MS susceptibility, while neuropathological studies have shown accumulations of proteins and organelles suggestive for transport deficits. A reduced effectiveness of axonal transport can lead to neurodegeneration through inhibition of mitochondrial motility, disruption of axoglial interaction or prevention of remyelination. In MS, demyelination leads to dysregulation of axonal transport, aggravated by the effects of TNF-alpha, nitric oxide and glutamate on the cytoskeleton. The combined effect of all these pathways is a vicious cycle in which a defective axonal transport system leads to an increase in ATP consumption through loss of membrane organization and a reduction in available ATP through inhibition of mitochondrial transport, resulting in even further inhibition of transport. The persistent activity of this positive feedback loop contributes to neurodegeneration in MS.

Impaired hemodynamics of the patella in patients with patellofemoral pain: A case-control study.

Purpose: According to the homeostasis model, patellofemoral pain (PFP) arises as a consequence of disturbed homeostasis of anterior structures of the knee due to vascular insufficiency. Near-infrared spectroscopy (NIRS) allows to measure changes of concentrations (µmol/cm2) of (de)-oxygenated hemoglobine (HHb and O2Hb). The aim was to study differences in patellar hemodynamics between patients and healthy controls. Methods: Hemodynamics of patients (n = 30 [female = 20, age = 21.5, BMI = 22.9]) and controls (n = 30 (female = 18, age = 21.4, BMI = 22.4]) were evaluated for two activities ('Prolonged Sitting' and 'Stair Descent'). Blinding for health status was implemented. Results: During 'Prolonged Sitting', PFP patients exhibited smaller decreases in mean changes for HHb (PFP [M = -1.5 to -1.9], healthy controls [M = -2.0 to -2.3]) and O2Hb (PFP [M = -2.0 to -3.2], healthy controls [M = -3.4 to -4.1]). However, these differences were statistically non-significant (p = 0.14-0.82 and p = 0.056-0.18, respectively). Conversely, for 'Stair Descent', PFP patients showed statistically significant smaller decreases in mean changes for HHb (PFP [M = -1.9, SD = 1.8], healthy controls [M = -2.5, SD = 1.7], p = 0.043) and O2Hb (PFP [M = -3.2, SD = 3.2], healthy controls [M = -4.9, SD = 2.7], p = 0.004). Conclusions: The differences suggest potential impairment in patellar hemodynamics in PFP patients, providing support for the homeostasis model. Evidence-based treatment strategies targeting patellar hemodynamics should be further refined and subjected to evaluation in clinical trials. Level of Evidence: Level III.

Identification of delta/notch-like epidermal growth factor-related receptor as the Tr antigen in paraneoplastic cerebellar degeneration.

OBJECTIVE: Anti-Tr is among the better described autoantibodies in paraneoplastic cerebellar degeneration (PCD) combined with Hodgkin lymphoma (HL); however, the Tr antigen remains unidentified. METHODS: We used immunoprecipitation of total rat brain extract followed by mass spectrometry to identify the antigen recognized by anti-Tr-positive sera. By Western blotting and cell-based assays, we tested a total of 12 anti-Tr-positive and 246 control sera and determined the region of the epitope recognized by the anti-Tr antibodies. Deletion and mutant constructs were generated to further map the antigenic region. RESULTS: Mass spectrometry analysis of immunopurified rat brain extract using 4 different anti-Tr-positive sera led to the identification of Delta/Notch-like epidermal growth factor-related receptor (DNER) as the Tr antigen. All but 1 of 246 control samples were negative in the HeLa cell-based screening assay, whereas 12 of the 12 anti-Tr-positive sera stained hemagglutinin-tagged DNER-expressing cells. Only 1 control subject with HL but no ataxia was found to be both DNER and Tr positive. Using deletion constructs, we pinpointed the main epitope to the extracellular domain. Knockdown of endogenous DNER in hippocampal and N-glycosylation mutations abolished the anti-Tr staining, indicating that glycosylation of DNER is required for it to be recognized by anti-Tr antibodies. INTERPRETATION: DNER is the antigen detected by anti-Tr-positive sera. Presence of anti-Tr antibodies in patients with PCD and HL or HL only can now be screened quickly and reliably by using a cell-based screening assay.

Characterization of Clostridium thermocellum strains with disrupted fermentation end-product pathways.

Clostridium thermocellum is a thermophilic, cellulolytic anaerobe that is a candidate microorganism for industrial biofuels production. Strains with mutations in genes associated with production of L-lactate (Δldh) and/or acetate (Δpta) were characterized to gain insight into the intracellular processes that convert cellobiose to ethanol and other fermentation end-products. Cellobiose-grown cultures of the Δldh strain had identical biomass accumulation, fermentation end-products, transcription profile, and intracellular metabolite concentrations compared to its parent strain (DSM1313 Δhpt Δspo0A). The Δpta-deficient strain grew slower and had 30 % lower final biomass concentration compared to the parent strain, yet produced 75 % more ethanol. A Δldh Δpta double-mutant strain evolved for faster growth had a growth rate and ethanol yield comparable to the parent strain, whereas its biomass accumulation was comparable to Δpta. Free amino acids were secreted by all examined strains, with both Δpta strains secreting higher amounts of alanine, valine, isoleucine, proline, glutamine, and threonine. Valine concentration for Δldh Δpta reached 5 mM by the end of growth, or 2.7 % of the substrate carbon utilized. These secreted amino acid concentrations correlate with increased intracellular pyruvate concentrations, up to sixfold in the Δpta and 16-fold in the Δldh Δpta strain. We hypothesize that the deletions in fermentation end-product pathways result in an intracellular redox imbalance, which the organism attempts to relieve, in part by recycling NADP⁺ through increased production of amino acids.

Near-Infrared Spectroscopy measurements are reliable for studying patellar bone hemodynamics and affected by venous occlusion, but not by skin compression.

PURPOSE: According to the homeostasis model, patellofemoral pain (PFP) results from disturbed homeostasis due to vascular insufficiency in the anterior knee. Near-Infrared Spectroscopy (NIRS) measures relative changes in concentrations (in µmol/cm2) of (de-)oxygenated hemoglobine (HHb and O2Hb). The aims were to: 1) investigate the characteristics of the NIRS signal derived from the patella during experiments affecting hemodynamics in healthy controls, and 2) determine the test-retest reliability of NIRS in positions clinically relevant for PFP patients. METHODS: Two experiments were conducted on 10 healthy controls and analysed using Student's t-test. Reliability (ICC2,1) was evaluated for two activities ('Prolonged Sitting' and 'Stair Descent') in five PFP patients and 15 healthy controls, performed twice within five days. RESULTS: The NIRS signal (HHb and O2Hb) showed a statistically significant increase (p < .001 - .002) on all optodes (30, 35, 40 mm) during 'Venous Occlusion' (M = 1.0 - 2.0), while it showed no statistically significant change (p = .075 - .61) during 'Skin Compression' (M = -0.9 - 0.9) on the 30 and 35 mm optode. Reliability of NIRS (HHb and O2Hb) ranged from moderate to almost perfect (ICC2,1 = .47 - .95) on the 30 mm optode for 'Prolonged Sitting', and from moderate to substantial (ICC2,1 = .50 - .68) on the 35 mm optode for 'Stair Descent'. CONCLUSIONS: Patella NIRS measurements are affected by venous occlusion, but not by skin compression, and are sufficiently reliable as research application to compare real-time patellar bone hemodynamics. These insights may assist to improve effectiveness of evidence-based treatment strategies for PFP. TRIAL REGISTRATION: ISRCTN Trial Registration under number: 90377123.

Patients with patellofemoral pain have lower soft tissue flexibility of the kinetic chain compared to healthy controls: A case-control study.

INTRODUCTION: Patellofemoral pain (PFP) is a common musculoskeletal condition. Lower limb range of motion (LLROM) evaluates soft tissue flexibility over multiple joints as part of the kinetic chain. The aims were to study: 1) the reliability of a new LLROM test; 2) differences in LLROM between PFP patients and controls; and 3) the relationship between LLROM and pain-free knee function. METHODS: Patients with PFP and matched controls were recruited from a university campus and private physiotherapy clinics, while observers were blinded for health status. Testing LLROM for maximal knee flexion and hip adduction and the sum of these (total ROM) were performed. Measures of reliability (ICC2,1) were established. Univariate linear regression between LLROM and health status and multivariate analysis between LLROM and knee function were performed. RESULTS: Patients (n = 32 (7 male/25 female, age = 22, BMI = 22.7)) and controls (n = 32 (7 male/25 female, age = 20, BMI = 22.3)) were included. The ICC's for intra- and interobserver reliability ranged from 0.83 (95%CI 0.30-0.93) to 0.89 (0.72-0.95). Symptomatic legs had 7°(3-11, p = 0.014) lower knee flexion, 6°(4-8, p ≤ 0.001) lower hip adduction and 13°(8-17, p ≤ 0.001) lower total ROM than non-symptomatic legs. Multivariate analysis revealed an association between total ROM and pain-free knee function (R2 = 0.438, F = 6.544, p ≤ 0.001). CONCLUSIONS: The new LLROM test was found to be reliable. Patients with PFP had lower LLROM, which was associated with impaired pain-free knee function. Whether improving soft tissue flexibility results in enhanced pain-free knee function should be the subject of future research.

Molecular motors in cargo trafficking and synapse assembly.

Every production process, be it cellular or industrial, depends on a constant supply of energy and resources. Synapses, specialized junctions in the central nervous system through which neurons signal to each other, are no exception to this rule. In order to form new synapses and alter the strength of synaptic transmission, neurons need a regulatory mechanism to deliver and remove synaptic proteins at synaptic sites. Neurons make use of active transport driven by molecular motor proteins to move synaptic cargo over either microtubules (kinesin, dynein) or actin filaments (myosin) to their specific site of action. These mechanisms are crucial for the initial establishment of synaptic specializations during synaptogenesis and for activity-dependent changes in synaptic strength during plasticity. In this chapter, we address the organization of the neuronal cytoskeleton, focus on synaptic cargo transport activities that operate in axons and dendrites, and discuss the spatial and temporal regulation of motor protein-based transport.

Subsequent AS01-adjuvanted vaccinations induce similar transcriptional responses in populations with different disease statuses.

Transcriptional responses to adjuvanted vaccines can vary substantially among populations. Interindividual diversity in levels of pathogen exposure, and thus of cell-mediated immunological memory at baseline, may be an important determinant of population differences in vaccine responses. Adjuvant System AS01 is used in licensed or candidate vaccines for several diseases and populations, yet the impact of pre-existing immunity on its adjuvanticity remains to be elucidated. In this exploratory post-hoc analysis of clinical trial samples (clinicalTrials.gov: NCT01424501), we compared gene expression patterns elicited by two immunizations with the candidate tuberculosis (TB) vaccine M72/AS01, between three groups of individuals with different levels of memory responses to TB antigens before vaccination. Analyzed were one group of TB-disease-treated individuals, and two groups of TB-disease-naïve individuals who were (based on purified protein derivative [PPD] skin-test results) stratified into PPD-positive and PPD-negative groups. Although TB-disease-treated individuals displayed slightly stronger transcriptional responses after each vaccine dose, functional gene signatures were overall not distinctly different between groups. Considering the similarities with the signatures found previously for other AS01-adjuvanted vaccines, many features of the response appeared to be adjuvant-driven. Across groups, cell proliferation-related signals at 7 days post-dose 1 were associated with increased anti-M72 antibody response magnitudes. These early signals were stronger in the TB-disease-treated group as compared to both TB-disease-naïve groups. Interindividual homogeneity in gene expression levels was also higher for TB-disease-treated individuals post-dose 1, but increased in all groups post-dose 2 to attain similar levels between the three groups. Altogether, strong cell-mediated memory responses at baseline accelerated and amplified transcriptional responses to a single dose of this AS01-adjuvanted vaccine, resulting in more homogenous gene expression levels among the highly-primed individuals as compared to the disease-naïve individuals. However, after a second vaccination, response heterogeneity decreased and was similar across groups, irrespective of the degree of immune memory acquired at baseline. This information can support the design and analysis of future clinical trials evaluating AS01-adjuvanted vaccines.

A flexible framework for sparse simultaneous component based data integration.

BACKGROUND: High throughput data are complex and methods that reveal structure underlying the data are most useful. Principal component analysis, frequently implemented as a singular value decomposition, is a popular technique in this respect. Nowadays often the challenge is to reveal structure in several sources of information (e.g., transcriptomics, proteomics) that are available for the same biological entities under study. Simultaneous component methods are most promising in this respect. However, the interpretation of the principal and simultaneous components is often daunting because contributions of each of the biomolecules (transcripts, proteins) have to be taken into account. RESULTS: We propose a sparse simultaneous component method that makes many of the parameters redundant by shrinking them to zero. It includes principal component analysis, sparse principal component analysis, and ordinary simultaneous component analysis as special cases. Several penalties can be tuned that account in different ways for the block structure present in the integrated data. This yields known sparse approaches as the lasso, the ridge penalty, the elastic net, the group lasso, sparse group lasso, and elitist lasso. In addition, the algorithmic results can be easily transposed to the context of regression. Metabolomics data obtained with two measurement platforms for the same set of Escherichia coli samples are used to illustrate the proposed methodology and the properties of different penalties with respect to sparseness across and within data blocks. CONCLUSION: Sparse simultaneous component analysis is a useful method for data integration: First, simultaneous analyses of multiple blocks offer advantages over sequential and separate analyses and second, interpretation of the results is highly facilitated by their sparseness. The approach offered is flexible and allows to take the block structure in different ways into account. As such, structures can be found that are exclusively tied to one data platform (group lasso approach) as well as structures that involve all data platforms (Elitist lasso approach). AVAILABILITY: The additional file contains a MATLAB implementation of the sparse simultaneous component method.

Simultaneous analysis of coupled data matrices subject to different amounts of noise.

In many areas of science, research questions imply the analysis of a set of coupled data blocks, with, for instance, each block being an experimental unit by variable matrix, and the variables being the same in all matrices. To obtain an overall picture of the mechanisms that play a role in the different data matrices, the information in these matrices needs to be integrated. This may be achieved by applying a data-analytic strategy in which a global model is fitted to all data matrices simultaneously, as in some forms of simultaneous component analysis (SCA). Since such a strategy implies that all data entries, regardless the matrix they belong to, contribute equally to the analysis, it may obfuscate the overall picture of the mechanisms underlying the data when the different data matrices are subject to different amounts of noise. One way out is to downweight entries from noisy data matrices in favour of entries from less noisy matrices. Information regarding the amount of noise that is present in each matrix, however, is, in most cases, not available. To deal with these problems, in this paper a novel maximum-likelihood-based simultaneous component analysis method, referred to as MxLSCA, is proposed. Being a stochastic extension of SCA, in MxLSCA the amount of noise in each data matrix is estimated and entries from noisy data matrices are downweighted. Both in an extensive simulation study and in an application to data stemming from cross-cultural emotion psychology, it is shown that the novel MxLSCA strategy outperforms the SCA strategy with respect to disclosing the mechanisms underlying the coupled data.

Short-term effectiveness of an intervention targeting lower limb range of motion on pain and disability in patellofemoral pain patients: A randomized, non-concurrent multiple-baseline study.

INTRODUCTION: Patellofemoral pain (PFP) is a common and often long-standing musculoskeletal condition. Evidence of the effectiveness of interventions addressing soft tissue flexibility is conflicting and of inconsistent scientific quality. However, reduced soft tissue flexibility can negatively affect patellofemoral joint kinematics. Lower limb range of motion (LLROM) reflects soft tissue flexibility throughout the kinetic chain. The aim was to evaluate the short-term effectiveness of an intervention targeting LLROM on pain and disability in patients with PFP. METHODS: A randomized, non-concurrent, multiple-baseline single-case design with a two-week intervention phase and baseline and postintervention phase with varying length was conducted. Eight participants (5 females, 3 males) of age 19(±1.6) years, weekly sports participation 12(±3.1) hours and 17(±14) months symptom duration were included. The Anterior Knee Pain Scale - Dutch Version (AKPS-DV) and the Patient Specific Complaint Scale (PSCS) were administered twice a week. After allocating participants to one of four subgroups of reduced LLROM the intervention was applied. The intervention consisted of soft tissue techniques (mobilization, taping, and stretching). RESULTS: Participant 3 and 6 showed a medium and small but statistically significant positive effect on the AKPS-DV. Participant 2 showed a large and statistically significant positive effect on the PSCS. CONCLUSIONS: This study provides moderate evidence that an intervention targeting LLROM in patients with PFP reduces pain and disability in the short-term. Further research is needed to evaluate the long-term effectiveness and optimize individual treatment outcomes.

Identification of modules in Aspergillus niger by gene co-expression network analysis.

The fungus Aspergillus niger has been studied in considerable detail with respect to various industrial applications. Although its central metabolic pathways are established relatively well, the mechanisms that control the adaptation of its metabolism are understood rather poorly. In this study, clustering of co-expressed genes has been performed on the basis of DNA microarray data sets from two experimental approaches. In one approach, low amounts of inducer caused a relatively mild perturbation, while in the other approach the imposed environmental conditions including carbon source starvation caused severe perturbed stress. A set of conserved genes was used to construct gene co-expression networks for both the individual and combined data sets. Comparative analysis revealed the existence of modules, some of which are present in all three networks. In addition, experimental condition-specific modules were identified. Module-derived consensus expression profiles enabled the integration of all protein-coding A. niger genes to the co-expression analysis, including hypothetical and poorly conserved genes. Conserved sequence motifs were detected in the upstream region of genes that cluster in some modules, e.g., the binding site for the amino acid metabolism-related transcription factor CpcA as well as for the fatty acid metabolism-related transcription factors, FarA and FarB. Moreover, not previously described putative transcription factor binding sites were discovered for two modules: the motif 5'-CGACAA is overrepresented in the module containing genes encoding cytosolic ribosomal proteins, while the motif 5'-GGCCGCG is overrepresented in genes related to 'gene expression', such as RNA helicases and translation initiation factors.

Innate Immune Responses to Chimpanzee Adenovirus Vector 155 Vaccination in Mice and Monkeys.

Replication-deficient chimpanzee adenovirus (ChAd) vectors represent an attractive vaccine platform and are thus employed as vaccine candidates against several infectious diseases. Since inducing effective immunity depends on the interplay between innate and adaptive immunity, a deeper understanding of innate immune responses elicited by intramuscularly injected ChAd vectors in tissues can advance the platform's development. Using different candidate vaccines based on the Group C ChAd type 155 (ChAd155) vector, we characterized early immune responses in injected muscles and draining lymph nodes (dLNs) from mice, and complemented these analyses by evaluating cytokine responses and gene expression patterns in peripheral blood from ChAd155-injected macaques. In mice, vector DNA levels gradually decreased post-immunization, but local transgene mRNA expression exhibited two transient peaks [at 6 h and Day (D)5], which were most obvious in dLNs. This dynamic pattern was mirrored by the innate responses in tissues, which developed as early as 1-3 h (cytokines/chemokines) or D1 (immune cells) post-vaccination. They were characterized by a CCL2- and CXCL9/10-dominated chemokine profile, peaking at 6 h (with CXCL10/CCL2 signals also detectable in serum) and D7, and clear immune-cell infiltration peaks at D1/D2 and D6/D7. Experiments with a green fluorescent protein-expressing ChAd155 vector revealed infiltrating hematopoietic cell subsets at the injection site. Cell infiltrates comprised mostly monocytes in muscles, and NK cells, T cells, dendritic cells, monocytes, and B cells in dLNs. Similar bimodal dynamics were observed in whole-blood gene signatures in macaques: most of the 17 enriched immune/innate signaling pathways were significantly upregulated at D1 and D7 and downregulated at D3, and clustering analysis revealed stronger similarities between D1 and D7 signatures versus the D3 signature. Serum cytokine responses (CXCL10, IL1Ra, and low-level IFN-α) in macaques were predominantly observed at D1. Altogether, the early immune responses exhibited bimodal kinetics with transient peaks at D1/D2 and D6/D7, mostly with an IFN-associated signature, and these features were remarkably consistent across most analyzed parameters in murine tissues and macaque blood. These compelling observations reveal a novel aspect of the dynamics of innate immunity induced by ChAd155-vectored vaccines, and contribute to ongoing research to better understand how adenovectors can promote vaccine-induced immunity.

Transcriptional profiles of adjuvanted hepatitis B vaccines display variable interindividual homogeneity but a shared core signature.

The current routine use of adjuvants in human vaccines provides a strong incentive to increase our understanding of how adjuvants differ in their ability to stimulate innate immunity and consequently enhance vaccine immunogenicity. Here, we evaluated gene expression profiles in cells from whole blood elicited in naive subjects receiving the hepatitis B surface antigen formulated with different adjuvants. We identified a core innate gene signature emerging 1 day after the second vaccination and that was shared by the recipients of vaccines formulated with adjuvant systems AS01B, AS01E, or AS03. This core signature associated with the magnitude of the hepatitis B surface-specific antibody response and was characterized by positive regulation of genes associated with interferon-related responses or the innate cell compartment and by negative regulation of natural killer cell-associated genes. Analysis at the individual subject level revealed that the higher immunogenicity of AS01B-adjuvanted vaccine was linked to its ability to induce this signature in most vaccinees even after the first vaccination. Therefore, our data suggest that adjuvanticity is not strictly defined by the nature of the receptors or signaling pathways it activates but by the ability of the adjuvant to consistently induce a core inflammatory signature across individuals.

The Ratiometric Transcript Signature MX2/GPR183 Is Consistently Associated With RTS,S-Mediated Protection Against Controlled Human Malaria Infection.

The RTS,S/AS01 vaccine provides partial protection against Plasmodium falciparum infection but determinants of protection and/or disease are unclear. Previously, anti-circumsporozoite protein (CSP) antibody titers and blood RNA signatures were associated with RTS,S/AS01 efficacy against controlled human malaria infection (CHMI). By analyzing host blood transcriptomes from five RTS,S vaccination CHMI studies, we demonstrate that the transcript ratio MX2/GPR183, measured 1 day after third immunization, discriminates protected from non-protected individuals. This ratiometric signature provides information that is complementary to anti-CSP titer levels for identifying RTS,S/AS01 immunized people who developed protective immunity and suggests a role for interferon and oxysterol signaling in the RTS,S mode of action.

Integrating functional genomics data using maximum likelihood based simultaneous component analysis.

BACKGROUND: In contemporary biology, complex biological processes are increasingly studied by collecting and analyzing measurements of the same entities that are collected with different analytical platforms. Such data comprise a number of data blocks that are coupled via a common mode. The goal of collecting this type of data is to discover biological mechanisms that underlie the behavior of the variables in the different data blocks. The simultaneous component analysis (SCA) family of data analysis methods is suited for this task. However, a SCA may be hampered by the data blocks being subjected to different amounts of measurement error, or noise. To unveil the true mechanisms underlying the data, it could be fruitful to take noise heterogeneity into consideration in the data analysis. Maximum likelihood based SCA (MxLSCA-P) was developed for this purpose. In a previous simulation study it outperformed normal SCA-P. This previous study, however, did not mimic in many respects typical functional genomics data sets, such as, data blocks coupled via the experimental mode, more variables than experimental units, and medium to high correlations between variables. Here, we present a new simulation study in which the usefulness of MxLSCA-P compared to ordinary SCA-P is evaluated within a typical functional genomics setting. Subsequently, the performance of the two methods is evaluated by analysis of a real life Escherichia coli metabolomics data set. RESULTS: In the simulation study, MxLSCA-P outperforms SCA-P in terms of recovery of the true underlying scores of the common mode and of the true values underlying the data entries. MxLSCA-P further performed especially better when the simulated data blocks were subject to different noise levels. In the analysis of an E. coli metabolomics data set, MxLSCA-P provided a slightly better and more consistent interpretation. CONCLUSION: MxLSCA-P is a promising addition to the SCA family. The analysis of coupled functional genomics data blocks could benefit from its ability to take different noise levels per data block into consideration and improve the recovery of the true patterns underlying the data. Moreover, the maximum likelihood based approach underlying MxLSCA-P could be extended to custom-made solutions to specific problems encountered.

Identification of potential biomarkers of vaccine inflammation in mice.

Systems vaccinology approaches have been used successfully to define early signatures of the vaccine-induced immune response. However, the possibility that transcriptomics can also identify a correlate or surrogate for vaccine inflammation has not been fully explored. We have compared four licensed vaccines with known safety profiles, as well as three agonists of Toll-like receptors (TLRs) with known inflammatory potential, to elucidate the transcriptomic profile of an acceptable response to vaccination versus that of an inflammatory reaction. In mice, we looked at the transcriptomic changes in muscle at the injection site, the lymph node that drained the muscle, and the peripheral blood mononuclear cells (PBMCs)isolated from the circulating blood from 4 hr after injection and over the next week. A detailed examination and comparative analysis of these transcriptomes revealed a set of novel biomarkers that are reflective of inflammation after vaccination. These biomarkers are readily measurable in the peripheral blood, providing useful surrogates of inflammation, and provide a way to select candidates with acceptable safety profiles.