Distinct baseline immune characteristics associated with responses to conjugated and unconjugated pneumococcal polysaccharide vaccines in older adults.

Pneumococcal infections cause serious illness and death among older adults. The capsular polysaccharide vaccine PPSV23 and conjugated alternative PCV13 can prevent these infections; yet, underlying immunological responses and baseline predictors remain unknown. We vaccinated 39 older adults (>60 years) with PPSV23 or PCV13 and observed comparable antibody responses (day 28) and plasmablast transcriptional responses (day 10); however, the baseline predictors were distinct. Analyses of baseline flow cytometry and bulk and single-cell RNA-sequencing data revealed a baseline phenotype specifically associated with weaker PCV13 responses, which was characterized by increased expression of cytotoxicity-associated genes, increased frequencies of CD16+ natural killer cells and interleukin-17-producing helper T cells and a decreased frequency of type 1 helper T cells. Men displayed this phenotype more robustly and mounted weaker PCV13 responses than women. Baseline expression levels of a distinct gene set predicted PPSV23 responses. This pneumococcal precision vaccinology study in older adults uncovered distinct baseline predictors that might transform vaccination strategies and initiate novel interventions.

A genomic approach to human autoimmune diseases.

The past decade has seen an explosion in the use of DNA-based microarrays. These techniques permit assessment of RNA abundance on a genome-wide scale. Medical applications emerged in the field of cancer, with studies of both solid tumors and hematological malignancies leading to the development of tests that are now used to personalize therapeutic options. Microarrays have also been used to analyze the blood transcriptome in a wide range of diseases. In human autoimmune diseases, these studies are showing potential for identifying therapeutic targets as well as biomarkers for diagnosis, assessment of disease activity, and response to treatment. More quantitative and sensitive high-throughput RNA profiling methods are starting to be available and will be necessary for transcriptome analyses to become routine tests in the clinical setting. We expect this to crystallize within the coming decade, as these methods become part of the personalized medicine armamentarium.

Human Adaptive Immunity Rescues an Inborn Error of Innate Immunity.

The molecular basis of the incomplete penetrance of monogenic disorders is unclear. We describe here eight related individuals with autosomal recessive TIRAP deficiency. Life-threatening staphylococcal disease occurred during childhood in the proband, but not in the other seven homozygotes. Responses to all Toll-like receptor 1/2 (TLR1/2), TLR2/6, and TLR4 agonists were impaired in the fibroblasts and leukocytes of all TIRAP-deficient individuals. However, the whole-blood response to the TLR2/6 agonist staphylococcal lipoteichoic acid (LTA) was abolished only in the index case individual, the only family member lacking LTA-specific antibodies (Abs). This defective response was reversed in the patient, but not in interleukin-1 receptor-associated kinase 4 (IRAK-4)-deficient individuals, by anti-LTA monoclonal antibody (mAb). Anti-LTA mAb also rescued the macrophage response in mice lacking TIRAP, but not TLR2 or MyD88. Thus, acquired anti-LTA Abs rescue TLR2-dependent immunity to staphylococcal LTA in individuals with inherited TIRAP deficiency, accounting for incomplete penetrance. Combined TIRAP and anti-LTA Ab deficiencies underlie staphylococcal disease in this patient.

Author Correction: Progression of whole-blood transcriptional signatures from interferon-induced to neutrophil-associated patterns in severe influenza.

In the version of this article initially published, a source of funding was not included in the Acknowledgements section. That section should include the following: P.J.M.O. was supported by EU FP7 PREPARE project 602525. The error has been corrected in the HTML and PDF version of the article.

Progression of whole-blood transcriptional signatures from interferon-induced to neutrophil-associated patterns in severe influenza.

Transcriptional profiles and host-response biomarkers are used increasingly to investigate the severity, subtype and pathogenesis of disease. We now describe whole-blood mRNA signatures and concentrations of local and systemic immunological mediators in 131 adults hospitalized with influenza, from whom extensive clinical and investigational data were obtained by MOSAIC investigators. Signatures reflective of interferon-related antiviral pathways were common up to day 4 of symptoms in patients who did not require mechanical ventilator support; in those who needed mechanical ventilation, an inflammatory, activated-neutrophil and cell-stress or death ('bacterial') pattern was seen, even early in disease. Identifiable bacterial co-infection was not necessary for this 'bacterial' signature but was able to enhance its development while attenuating the early 'viral' signature. Our findings emphasize the importance of timing and severity in the interpretation of host responses to acute viral infection and identify specific patterns of immune-system activation that might enable the development of novel diagnostic and therapeutic tools for severe influenza.

Baseline immune states (BIS) associated with vaccine responsiveness and factors that shape the BIS.

Vaccines are among the greatest inventions in medicine, leading to the elimination or control of numerous diseases, including smallpox, polio, measles, rubella, and, most recently, COVID-19. Yet, the effectiveness of vaccines varies among individuals. In fact, while some recipients mount a robust response to vaccination that protects them from the disease, others fail to respond. Multiple clinical and epidemiological factors contribute to this heterogeneity in responsiveness. Systems immunology studies fueled by advances in single-cell biology have been instrumental in uncovering pre-vaccination immune cell types and genomic features (i.e., the baseline immune state, BIS) that have been associated with vaccine responsiveness. Here, we review clinical factors that shape the BIS, and the characteristics of the BIS associated with responsiveness to frequently studied vaccines (i.e., influenza, COVID-19, bacterial pneumonia, malaria). Finally, we discuss potential strategies to enhance vaccine responsiveness in high-risk groups, focusing specifically on older adults.

Molecular signatures of antibody responses derived from a systems biology study of five human vaccines.

Many vaccines induce protective immunity via antibodies. Systems biology approaches have been used to determine signatures that can be used to predict vaccine-induced immunity in humans, but whether there is a 'universal signature' that can be used to predict antibody responses to any vaccine is unknown. Here we did systems analyses of immune responses to the polysaccharide and conjugate vaccines against meningococcus in healthy adults, in the broader context of published studies of vaccines against yellow fever virus and influenza virus. To achieve this, we did a large-scale network integration of publicly available human blood transcriptomes and systems-scale databases in specific biological contexts and deduced a set of transcription modules in blood. Those modules revealed distinct transcriptional signatures of antibody responses to different classes of vaccines, which provided key insights into primary viral, protein recall and anti-polysaccharide responses. Our results elucidate the early transcriptional programs that orchestrate vaccine immunity in humans and demonstrate the power of integrative network modeling.

A narrow repertoire of transcriptional modules responsive to pyogenic bacteria is impaired in patients carrying loss-of-function mutations in MYD88 or IRAK4.

Loss of function of the kinase IRAK4 or the adaptor MyD88 in humans interrupts a pathway critical for pathogen sensing and ignition of inflammation. However, patients with loss-of-function mutations in the genes encoding these factors are, unexpectedly, susceptible to only a limited range of pathogens. We employed a systems approach to investigate transcriptome responses following in vitro exposure of patients' blood to agonists of Toll-like receptors (TLRs) and receptors for interleukin 1 (IL-1Rs) and to whole pathogens. Responses to purified agonists were globally abolished, but variable residual responses were present following exposure to whole pathogens. Further delineation of the latter responses identified a narrow repertoire of transcriptional programs affected by loss of MyD88 function or IRAK4 function. Our work introduces the use of a systems approach for the global assessment of innate immune responses and the characterization of human primary immunodeficiencies.

Immunodeficiency, autoinflammation and amylopectinosis in humans with inherited HOIL-1 and LUBAC deficiency.

We report the clinical description and molecular dissection of a new fatal human inherited disorder characterized by chronic autoinflammation, invasive bacterial infections and muscular amylopectinosis. Patients from two kindreds carried biallelic loss-of-expression and loss-of-function mutations in HOIL1 (RBCK1), a component of the linear ubiquitination chain assembly complex (LUBAC). These mutations resulted in impairment of LUBAC stability. NF-κB activation in response to interleukin 1ß (IL-1ß) was compromised in the patients' fibroblasts. By contrast, the patients' mononuclear leukocytes, particularly monocytes, were hyper-responsive to IL-1ß. The consequences of human HOIL-1 and LUBAC deficiencies for IL-1ß responses thus differed between cell types, consistent with the unique association of autoinflammation and immunodeficiency in these patients. These data suggest that LUBAC regulates NF-κB-dependent IL-1ß responses differently in different cell types.

Harnessing large language models (LLMs) for candidate gene prioritization and selection.

BACKGROUND: Feature selection is a critical step for translating advances afforded by systems-scale molecular profiling into actionable clinical insights. While data-driven methods are commonly utilized for selecting candidate genes, knowledge-driven methods must contend with the challenge of efficiently sifting through extensive volumes of biomedical information. This work aimed to assess the utility of large language models (LLMs) for knowledge-driven gene prioritization and selection. METHODS: In this proof of concept, we focused on 11 blood transcriptional modules associated with an Erythroid cells signature. We evaluated four leading LLMs across multiple tasks. Next, we established a workflow leveraging LLMs. The steps consisted of: (1) Selecting one of the 11 modules; (2) Identifying functional convergences among constituent genes using the LLMs; (3) Scoring candidate genes across six criteria capturing the gene's biological and clinical relevance; (4) Prioritizing candidate genes and summarizing justifications; (5) Fact-checking justifications and identifying supporting references; (6) Selecting a top candidate gene based on validated scoring justifications; and (7) Factoring in transcriptome profiling data to finalize the selection of the top candidate gene. RESULTS: Of the four LLMs evaluated, OpenAI's GPT-4 and Anthropic's Claude demonstrated the best performance and were chosen for the implementation of the candidate gene prioritization and selection workflow. This workflow was run in parallel for each of the 11 erythroid cell modules by participants in a data mining workshop. Module M9.2 served as an illustrative use case. The 30 candidate genes forming this module were assessed, and the top five scoring genes were identified as BCL2L1, ALAS2, SLC4A1, CA1, and FECH. Researchers carefully fact-checked the summarized scoring justifications, after which the LLMs were prompted to select a top candidate based on this information. GPT-4 initially chose BCL2L1, while Claude selected ALAS2. When transcriptional profiling data from three reference datasets were provided for additional context, GPT-4 revised its initial choice to ALAS2, whereas Claude reaffirmed its original selection for this module. CONCLUSIONS: Taken together, our findings highlight the ability of LLMs to prioritize candidate genes with minimal human intervention. This suggests the potential of this technology to boost productivity, especially for tasks that require leveraging extensive biomedical knowledge.

Unveiling the dynamics of the breast milk microbiome: impact of lactation stage and gestational age.

BACKGROUND: Breast milk (BM) provides complete nutrition for infants for the first six months of life and is essential for the development of the newborn's immature immune and digestive systems. While BM was conventionally believed to be sterile, recent advanced high throughput technologies have unveiled the presence of diverse microbial communities in BM. These insights into the BM microbiota have mainly originated from uncomplicated pregnancies, possibly not reflecting the circumstances of mothers with pregnancy complications like preterm birth (PTB). METHODS: In this article, we investigated the BM microbial communities in mothers with preterm deliveries (before 37 weeks of gestation). We compared these samples with BM samples from healthy term pregnancies across different lactation stages (colostrum, transitional and mature milk) using 16S rRNA gene sequencing. RESULTS: Our analysis revealed that the microbial communities became increasingly diverse and compositionally distinct as the BM matured. Specifically, mature BM samples were significantly enriched in Veillonella and lactobacillus (Kruskal Wallis; p < 0.001) compared to colostrum. The comparison of term and preterm BM samples showed that the community structure was significantly different between the two groups (Bray Curtis and unweighted unifrac dissimilarity; p < 0.001). Preterm BM samples exhibited increased species richness with significantly higher abundance of Staphylococcus haemolyticus, Propionibacterium acnes, unclassified Corynebacterium species. Whereas term samples were enriched in Staphylococcus epidermidis, unclassified OD1, and unclassified Veillonella among others. CONCLUSION: Our study underscores the significant influence of pregnancy-related complications, such as preterm birth (before 37 weeks of gestation), on the composition and diversity of BM microbiota. Given the established significance of the maternal microbiome in shaping child health outcomes, this investigation paves the way for identifying modifiable factors that could optimize the composition of BM microbiota, thereby promoting maternal and infant health.

SysInflam HuDB, a Web Resource for Mining Human Blood Cells Transcriptomic Data Associated with Systemic Inflammatory Responses to Sepsis.

Sepsis develops after a dysregulated host inflammatory response to a systemic infection. Identification of sepsis biomarkers has been challenging because of the multifactorial causes of disease susceptibility and progression. Public transcriptomic data are a valuable resource for mechanistic discoveries and cross-studies concordance of heterogeneous diseases. Nonetheless, the approach requires structured methodologies and effective visualization tools for meaningful data interpretation. Currently, no such database exists for sepsis or systemic inflammatory diseases in human. Hence we curated SysInflam HuDB (http://sepsis.gxbsidra.org/dm3/geneBrowser/list), a unique collection of human blood transcriptomic datasets associated with systemic inflammatory responses to sepsis. The transcriptome collection and the associated clinical metadata are integrated onto a user-friendly and Web-based interface that allows the simultaneous exploration, visualization, and interpretation of multiple datasets stemming from different study designs. To date, the collection encompasses 62 datasets and 5719 individual profiles. Concordance of gene expression changes with the associated literature was assessed, and additional analyses are presented to showcase database utility. Combined with custom data visualization at the group and individual levels, SysInflam HuDB facilitates the identification of specific human blood gene signatures in response to infection (e.g., patients with sepsis versus healthy control subjects) and the delineation of major genetic drivers associated with inflammation onset and progression under various conditions.

Transcriptomic profile investigations highlight a putative role for NUDT16 in sepsis.

Sepsis is an aberrant systemic inflammatory response mediated by the acute activation of the innate immune system. Neutrophils are important contributors to the innate immune response that controls the infection, but harbour the risk of collateral tissue damage such as thrombosis and organ dysfunction. A better understanding of the modulations of cellular processes in neutrophils and other blood cells during sepsis is needed and can be initiated via transcriptomic profile investigations. To that point, the growing repertoire of publicly accessible transcriptomic datasets serves as a valuable resource for discovering and/or assessing the robustness of biomarkers. We employed systematic literature mining, reductionist approach to gene expression profile and empirical in vitro work to highlight the role of a Nudix hydrolase family member, NUDT16, in sepsis. The relevance and implication of the expression of NUDT16 under septic conditions and the putative functional roles of this enzyme are discussed.

BloodGen3Module: blood transcriptional module repertoire analysis and visualization using R.

MOTIVATION: We previously described the construction and characterization of fixed reusable blood transcriptional module repertoires. More recently we released a third iteration ('BloodGen3' module repertoire) that comprises 382 functionally annotated modules and encompasses 14 168 transcripts. Custom bioinformatic tools are needed to support downstream analysis, visualization and interpretation relying on such fixed module repertoires. RESULTS: We have developed and describe here an R package, BloodGen3Module. The functions of our package permit group comparison analyses to be performed at the module-level, and to display the results as annotated fingerprint grid plots. A parallel workflow for computing module repertoire changes for individual samples rather than groups of samples is also available; these results are displayed as fingerprint heatmaps. An illustrative case is used to demonstrate the steps involved in generating blood transcriptome repertoire fingerprints of septic patients. Taken together, this resource could facilitate the analysis and interpretation of changes in blood transcript abundance observed across a wide range of pathological and physiological states. AVAILABILITY AND IMPLEMENTATION: The BloodGen3Module package and documentation are freely available from Github: https://github.com/Drinchai/BloodGen3Module. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Systems scale interactive exploration reveals quantitative and qualitative differences in response to influenza and pneumococcal vaccines.

Systems immunology approaches were employed to investigate innate and adaptive immune responses to influenza and pneumococcal vaccines. These two non-live vaccines show different magnitudes of transcriptional responses at different time points after vaccination. Software solutions were developed to explore correlates of vaccine efficacy measured as antibody titers at day 28. These enabled a further dissection of transcriptional responses. Thus, the innate response, measured within hours in the peripheral blood, was dominated by an interferon transcriptional signature after influenza vaccination and by an inflammation signature after pneumococcal vaccination. Day 7 plasmablast responses induced by both vaccines was more pronounced after pneumococcal vaccination. Together, these results suggest that comparing global immune responses elicited by different vaccines will be critical to our understanding of the immune mechanisms underpinning successful vaccination.

Influence of the transcription factor RORgammat on the development of NKp46+ cell populations in gut and skin.

NKp46+CD3- natural killer lymphocytes isolated from blood, lymphoid organs, lung, liver and uterus can produce granule-dependent cytotoxicity and interferon-gamma. Here we identify in dermis, gut lamina propria and cryptopatches distinct populations of NKp46+CD3- cells with a diminished capacity to degranulate and produce interferon-gamma. In the gut, expression of the transcription factor RORgammat, which is involved in the development of lymphoid tissue-inducer cells, defined a previously unknown subset of NKp46+CD3- lymphocytes. Unlike RORgammat- lamina propria and dermis natural killer cells, gut RORgammat+NKp46+ cells produced interleukin 22. Our data show that lymphoid tissue-inducer cells and natural killer cells shared unanticipated similarities and emphasize the heterogeneity of NKp46+CD3- cells in innate immunity, lymphoid organization and local tissue repair.

Annexin A3 in sepsis: novel perspectives from an exploration of public transcriptome data.

According to publicly available transcriptome datasets, the abundance of Annexin A3 (ANXA3) is robustly increased during the course of sepsis; however, no studies have examined the biological significance or clinical relevance of ANXA3 in this pathology. Here we explored this interpretation gap and identified possible directions for future research. Based on reference transcriptome datasets, we found that ANXA3 expression is restricted to neutrophils, is upregulated in vitro after exposure to plasma obtained from septic patients, and is associated with adverse clinical outcomes. Secondly, an increase in ANXA3 transcript abundance was also observed in vivo, in the blood of septic patients in multiple independent studies. ANXA3 is known to mediate calcium-dependent granules-phagosome fusion in support of microbicidal activity in neutrophils. More recent work has also shown that ANXA3 enhances proliferation and survival of tumour cells via a Caspase-3-dependent mechanism. And this same molecule is also known to play a critical role in regulation of apoptotic events in neutrophils. Thus, we posit that during sepsis ANXA3 might either play a beneficial role, by facilitating microbial clearance and resolution of the infection; or a detrimental role, by prolonging neutrophil survival, which is known to contribute to sepsis-mediated organ damage.

Three Copies of Four Interferon Receptor Genes Underlie a Mild Type I Interferonopathy in Down Syndrome.

Down syndrome (DS) is characterized by the occurrence of three copies of human chromosome 21 (HSA21). HSA21 contains a cluster of four interferon receptor (IFN-R) genes: IFNAR1, IFNAR2, IFNGR2, and IL10RB. DS patients often develop mucocutaneous infections and autoimmune diseases, mimicking patients with heterozygous gain-of-function (GOF) STAT1 mutations, which enhance cellular responses to three types of interferon (IFN). A gene dosage effect at these four loci may contribute to the infectious and autoimmune manifestations observed in individuals with DS. We report high levels of IFN-αR1, IFN-αR2, and IFN-γR2 expression on the surface of monocytes and EBV-transformed-B (EBV-B) cells from studying 45 DS patients. Total and phosphorylated STAT1 (STAT1 and pSTAT1) levels were constitutively high in unstimulated and IFN-α- and IFN-γ-stimulated monocytes from DS patients but lower than those in patients with GOF STAT1 mutations. Following stimulation with IFN-α or -γ, but not with IL-6 or IL-21, pSTAT1 and IFN-γ activation factor (GAF) DNA-binding activities were significantly higher in the EBV-B cells of DS patients than in controls. These responses resemble the dysregulated responses observed in patients with STAT1 GOF mutations. Concentrations of plasma type I IFNs were high in 12% of the DS patients tested (1.8% in the healthy controls). Levels of type I IFNs, IFN-Rs, and STAT1 were similar in DS patients with and without recurrent skin infections. We performed a genome-wide transcriptomic analysis based on principal component analysis and interferon modules on circulating monocytes. We found that DS monocytes had levels of both IFN-α- and IFN-γ-inducible ISGs intermediate to those of monocytes from healthy controls and from patients with GOF STAT1 mutations. Unlike patients with GOF STAT1 mutations, patients with DS had normal circulating Th17 counts and a high proportion of terminally differentiated CD8+ T cells with low levels of STAT1 expression. We conclude a mild interferonopathy in Down syndrome leads to an incomplete penetrance at both cellular and clinical level, which is not correlate with recurrent skin bacterial or fungal infections. The constitutive upregulation of type I and type II IFN-R, at least in monocytes of DS patients, may contribute to the autoimmune diseases observed in these individuals.

A modular framework for the development of targeted Covid-19 blood transcript profiling panels.

BACKGROUND: Covid-19 morbidity and mortality are associated with a dysregulated immune response. Tools are needed to enhance existing immune profiling capabilities in affected patients. Here we aimed to develop an approach to support the design of targeted blood transcriptome panels for profiling the immune response to SARS-CoV-2 infection. METHODS: We designed a pool of candidates based on a pre-existing and well-characterized repertoire of blood transcriptional modules. Available Covid-19 blood transcriptome data was also used to guide this process. Further selection steps relied on expert curation. Additionally, we developed several custom web applications to support the evaluation of candidates. RESULTS: As a proof of principle, we designed three targeted blood transcript panels, each with a different translational connotation: immunological relevance, therapeutic development relevance and SARS biology relevance. CONCLUSION: Altogether the work presented here may contribute to the future expansion of immune profiling capabilities via targeted profiling of blood transcript abundance in Covid-19 patients.