Gene set meta-analysis with Quantitative Set Analysis for Gene Expression (QuSAGE)

Immunogenicity of MVA-BN vaccine deployed as mpox prophylaxis: a prospective, single-centre, cohort study and analysis of transcriptomic predictors of response

BACKGROUND

Since 2022, mpox has emerged as a global health threat, with two clades (I and II) causing outbreaks of international public health concern. The third generation smallpox vaccine modified vaccinia Ankara, manufactured by Bavarian Nordic (MVA-BN), has emerged as a key component of mpox prevention. To date, the immunogenicity of this vaccine, including determinants of response, has been incompletely described, especially when MVA-BN has been administered intradermally at a fifth of the registered dose (so-called fractionated dosing), as recommended as a dose-sparing strategy. The aim of this study was to explore the immunogenicity of MVA-BN and baseline determinants of vaccine response in an observational public-health response setting.

METHODS

We conducted a prospective cohort study and immunological analysis of responses to MVA-BN in patients attending a sexual health vaccination clinic in Oxford, UK. Blood samples were taken at baseline, day 14, and day 28 after first vaccine, and 28 and 90 days following a second vaccine. A subcohort had additional blood samples collected day 1 following their first vaccine (optional timepoint). We assessed IgG responses to mpox and vaccinia antigens using Luminex assay (MpoxPlex) using generalised linear mixed modelling, and T-cell responses using IFN-γ enzyme-linked immunospot and activation-induced marker assay. Associations between blood transcriptomic signatures (baseline, day 1) and immunogenicity were assessed using differential expression analysis and gene set enrichment methods.

FINDINGS

We recruited 34 participants between Dec 1, 2022 and May 3, 2023 of whom 33 received fractionated dosing. Of the 30 without previous smallpox vaccination, 14 (47%) seroconverted by day 28, increasing to 25 (89%) 90 days after second vaccination. However, individuals seronegative on day 28 had persistently lower responses compared with individuals seropositive on day 28 (numerically lower antibody responses to six of seven dynamic antigens in the MPoxPlex assay, p<0·05). Serological response on day 28 was positively associated with type I and II interferon signatures 1 day after vaccination (n=18; median module score 0·13 vs 0·06; p=1·1 × 10-⁶), but negatively associated with these signatures at baseline (normalised enrichment score -2·81 and -2·86, respectively).

INTERPRETATION

Baseline inflammatory states might inhibit MVA-BN serological immunogenicity by inhibiting the upregulation of MVA-induced innate immune signalling. If confirmed mechanistically, these insights could inform improved vaccination strategies against mpox in diverse geographic and demographic settings. Given the likelihood of vaccine supply limitations presently and in future outbreak settings, the utility of dose-sparing vaccine strategies as a general approach to maximising population benefit warrants further study.

FUNDING

UKRI via the UK Monkeypox Research Consortium, Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences, the Kennedy Trust for Rheumatology Research, the John Climax Donation, the Medical Research Council (UK), the Wellcome Trust, the Center for Cooperative Human Immunology (National Institutes of Health), and the National Institute for Health and Care Research Oxford Biomedical Research Centre.

Aberrant expression of collagen type X in solid tumor stroma is associated with EMT, immunosuppressive and pro-metastatic pathways, bone marrow stromal cell signatures, and poor survival prognosis

BACKGROUND

Collagen type X (ColXα1, encoded by COL10A1) is expressed specifically in the cartilage-to-bone transition, in bone marrow cells, and in osteoarthritic (OA) cartilage. We have previously shown that ColXα1 is expressed in breast tumor stroma, correlates with tumor-infiltrating lymphocytes, and predicts poor adjuvant therapy outcomes in ER+/HER2+ breast cancer. However, the underlying molecular mechanisms for these effects are unknown. In this study, we performed bioinformatic analysis of COL10A1-associated gene modules in breast and pancreatic cancer as well as in cells from bone marrow and OA cartilage. These findings provide important insights into the mechanisms of transcriptional and extracellular matrix changes which impact the local stromal microenvironment and tumor progression.

METHODS

Immunohistochemistry was performed to examine collagen type X expression in solid tumors. WGCNA was used to generate COL10A1-associated gene networks in breast and pancreatic tumor cohorts using RNA-Seq data from The Cancer Genome Atlas. Computational analysis was employed to assess the impact of these gene networks on development and progression of cancer and OA. Data processing and statistical analysis was performed using R and various publicly-available computational tools.

RESULTS

Expression of COL10A1 and its associated gene networks highlights inflammatory and immunosuppressive microenvironments, which identify aggressive breast and pancreatic tumors and contribute to metastatic potential in a sex-dependent manner. Both cancer types are enriched in stroma, and COL10A1 implicates bone marrow-derived fibroblasts as contributors to the epithelial-to-mesenchymal transition (EMT) in these tumors. Heightened expression of COL10A1 and its associated gene networks is correlated with poorer patient outcomes in both breast and pancreatic cancer. Common transcriptional changes and chondrogenic activity are shared between cancer and OA cartilage, suggesting that similar microenvironmental alterations may underlie both diseases.

CONCLUSIONS

COL10A1-associated gene networks may hold substantial value as regulators and biomarkers of aggressive tumor phenotypes with implications for therapy development and clinical outcomes. Identification of tumors which exhibit high expression of COL10A1 and its associated genes may reveal the presence of bone marrow-derived stromal microenvironments with heightened EMT capacity and metastatic potential. Our analysis may enable more effective risk assessment and more precise treatment of patients with breast and pancreatic cancer.

Aberrant expression of collagen type X in solid tumor stroma is associated with EMT, immunosuppressive and pro-metastatic pathways, bone marrow stromal cell signatures, and poor survival prognosis

Background

Collagen type X (ColXα1, encoded by COL10A1) is expressed specifically in the cartilage-to-bone transition, in bone marrow cells, and in osteoarthritic (OA) cartilage. We have previously shown that ColXα1 is expressed in breast tumor stroma, correlates with tumor-infiltrating lymphocytes, and predicts poor adjuvant therapy outcomes in ER+/HER2+ breast cancer. However, the underlying molecular mechanisms for these effects are unknown. In this study, we performed bioinformatic analysis of COL10A1-associated gene modules in breast and pancreatic cancer as well as in cells from bone marrow and OA cartilage. These findings provide important insights into the mechanisms of transcriptional and extracellular matrix changes which impact the local stromal microenvironment and tumor progression.

Methods

Immunohistochemistry was performed to examine collagen type X expression in solid tumors. WGCNA was used to generate COL10A1-associated gene networks in breast and pancreatic tumor cohorts using RNA-Seq data from The Cancer Genome Atlas. Computational analysis was employed to assess the impact of these gene networks on development and progression of cancer and OA. Data processing and statistical analysis was performed using R and various publicly-available computational tools.

Results

Expression of COL10A1 and its associated gene networks highlights inflammatory and immunosuppressive microenvironments, which identify aggressive breast and pancreatic tumors and contribute to metastatic potential in a sex-dependent manner. Both cancer types are enriched in stroma, and COL10A1 implicates bone marrow-derived fibroblasts as drivers of the epithelial-to-mesenchymal transition (EMT) in these tumors. Heightened expression of COL10A1 and its associated gene networks is correlated with poorer patient outcomes in both breast and pancreatic cancer. Common transcriptional changes and chondrogenic activity are shared between cancer and OA cartilage, suggesting that similar microenvironmental alterations may underlie both diseases.

Conclusions

COL10A1-associated gene networks may hold substantial value as regulators and biomarkers of aggressive tumor phenotypes with implications for therapy development and clinical outcomes. Identification of tumors which exhibit high expression of COL10A1 and its associated genes may reveal the presence of bone marrow-derived stromal microenvironments with heightened EMT capacity and metastatic potential. Our analysis may enable more effective risk assessment and more precise treatment of patients with breast and pancreatic cancer.

Dissecting the Distinct Tumor Microenvironments of HRD and HRP Ovarian Cancer: Implications for Targeted Therapies to Overcome PARPi Resistance in HRD Tumors and Refractoriness in HRP Tumors

High-grade serous tubo-ovarian cancer (HGSTOC) is an aggressive gynecological malignancy including homologous recombination deficient (HRD) and homologous recombination proficient (HRP) groups. Despite the therapeutic potential of poly (ADP-ribose) polymerase inhibitors (PARPis) and anti-PDCD1 antibodies, acquired resistance in HRD and suboptimal response in HRP patients necessitate more precise treatment. Herein, single-cell RNA and single-cell T-cell receptor sequencing on 5 HRD and 3 HRP tumors are performed to decipher the heterogeneous tumor immune microenvironment (TIME), along with multiplex immunohistochemistry staining and animal experiments for validation. HRD tumors are enriched with immunogenic epithelial cells, FGFR1+PDGFRβ+ myCAFs, M1 macrophages, tumor reactive CD8+/CD4+ Tregs, whereas HRP tumors are enriched with HDAC1-expressing epithelial cells, indolent CAFs, M2 macrophages, and bystander CD4+/CD8+ T cells. Significantly, customized therapies are proposed. For HRD patients, targeting FGFR1+PDGFRβ+ myCAFs via tyrosine kinase inhibitors, targeting Tregs via anti-CCR8 antibodies/TNFRSF4 stimulation, and targeting CXCL13+ exhausted T cells by blocking PDCD1/CTLA-4/LAG-3/TIGIT are proposed. For HRP patients, targeting indolent CAFs, targeting M2 macrophages via CSF-1/CSF-1R inhibitors, targeting bystander T cells via tumor vaccines, and targeting epithelial cells via HDAC inhibitors. The study provides comprehensive insights into HRD and HRP TIME and tailored therapeutic approaches, addressing the challenges of PARPi-resistant HRD and refractory HRP tumors.

Longitudinal transcriptional immune profiles and persistent wheezing in moderate-to-late preterm infants

BACKGROUND

Prematurity is associated with an increased risk of persistent wheezing but the underlying mechanisms are not well defined. The aim of this study was to identify blood transcriptional profiles associated with the development of wheezing in a cohort of moderate to late preterm infants and to define immune gene expression changes associated with wheezing.

MATERIALS AND METHODS

A convenience sample of a multicenter birth cohort (SAREPREM) of moderate-late preterm children followed during the first 3 years of life was analyzed. Children were enrolled in the first 2 weeks of life (Y0) and longitudinally evaluated at 1 (Y1), 2 (Y2), and 3 years (Y3) of age, for the presence of wheezing and to obtain samples for transcriptional profile analysis. Samples were processed on Illumina HT12 chips and genomic expression analyses performed with R programming, modular analysis for biological function, and QuSAGE for quantitative gene expression.

RESULTS

Seventy-six children were included in the study; 33 were classified as non-wheezing and 43 (56.6%) in the wheezing group. At Y0, children who developed wheezing had decreased expression of interferon genes and increased expression of B cell genes compared with the non-wheezing group. These changes in IFN and B cell gene expression were especially significant in children with late/persistent wheezing compared with transient wheezers.

CONCLUSIONS

Changes in IFN and B lymphocyte gene expression identified in early life suggest the existence of specific immunological mechanisms that play an important role in the development of wheezing in late-preterm infants.

NetActivity enhances transcriptional signals by combining gene expression into robust gene set activity scores through interpretable autoencoders

Grouping gene expression into gene set activity scores (GSAS) provides better biological insights than studying individual genes. However, existing gene set projection methods cannot return representative, robust, and interpretable GSAS. We developed NetActivity, a machine learning framework that generates GSAS based on a sparsely-connected autoencoder, where each neuron in the inner layer represents a gene set. We proposed a three-tier training that yielded representative, robust, and interpretable GSAS. NetActivity model was trained with 1518 GO biological processes terms and KEGG pathways and all GTEx samples. NetActivity generates GSAS robust to the initialization parameters and representative of the original transcriptome, and assigned higher importance to more biologically relevant genes. Moreover, NetActivity returns GSAS with a more consistent definition and higher interpretability than GSVA and hipathia, state-of-the-art gene set projection methods. Finally, NetActivity enables combining bulk RNA-seq and microarray datasets in a meta-analysis of prostate cancer progression, highlighting gene sets related to cell division, key for disease progression. When applied to metastatic prostate cancer, gene sets associated with cancer progression were also altered due to drug resistance, while a classical enrichment analysis identified gene sets irrelevant to the phenotype. NetActivity is publicly available in Bioconductor and GitHub.

What Powers Trastuzumab's Cardiotoxicity? Decoding Mitochondrial-Related Gene Expression Through Integrative Review and Meta-Analysis in Cardiomyocytes

Trastuzumab is a monoclonal antibody used in oncotherapy for HER2-positive tumors. However, as an adverse effect, trastuzumab elevates the risk of heart failure, implying the involvement of energy production and mitochondrial processes. Past studies with transcriptome analysis have offered insights on pathways related to trastuzumab safety and toxicity but limited study sizes hinder conclusive findings. Therefore, we meta-analyzed mitochondria-related gene expression data in trastuzumab-treated cardiomyocytes. We searched the transcriptome databases for trastuzumab-treated cardiomyocytes in the ArrayExpress, DDBJ Omics Archive, Gene Expression Omnibus, Google Scholar, PubMed, and Web of Science repositories. A subset of 1270 genes related to mitochondrial functions (biogenesis, organization, mitophagy, and autophagy) was selected from the Kyoto Encyclopedia of Genes and Genomes and Gene Ontology Resource databases to conduct the present meta-analysis using the Metagen package (Study register at PROSPERO: CRD42021270645). Three datasets met the inclusion criteria and 1243 genes were meta-analyzed. We observed 69 upregulated genes after trastuzumab treatment which were related mainly to autophagy (28 genes) and mitochondrial organization (28 genes). We also found 37 downregulated genes which were related mainly to mitochondrial biogenesis (11 genes) and mitochondrial organization (24 genes). The present meta-analysis indicates that trastuzumab therapy causes an unbalance in mitochondrial functions, which could, in part, help explain the development of heart failure and yields a list of potential molecular targets. These findings contribute to our understanding of the molecular mechanisms underlying the cardiotoxic effects of trastuzumab and may have implications for the development of targeted therapies to mitigate such effects.

APPLICATION OF QUANTILE DISCRETIZATION AND BAYESIAN NETWORK ANALYSIS TO PUBLICLY AVAILABLE CYSTIC FIBROSIS DATA SETS

The availability of multiple publicly-available datasets studying the same phenomenon has the promise of accelerating scientific discovery. Meta-analysis can address issues of reproducibility and often increase power. The promise of meta-analysis is especially germane to rarer diseases like cystic fibrosis (CF), which affects roughly 100,000 people worldwide. A recent search of the National Institute of Health's Gene Expression Omnibus revealed 1.3 million data sets related to cancer compared to about 2,000 related to CF. These studies are highly diverse, involving different tissues, animal models, treatments, and clinical covariates. In our search for gene expression studies of primary human airway epithelial cells, we identified three studies with compatible methodologies and sufficient metadata: GSE139078, Sala Study, and PRJEB9292. Even so, experimental designs were not identical, and we identified significant batch effects that would have complicated functional analysis. Here we present quantile discretization and Bayesian network construction using the Hill climb method as a powerful tool to overcome experimental differences and reveal biologically relevant responses to the CF genotype itself, exposure to virus, bacteria, and drugs used to treat CF. Functional patterns revealed by cluster Profiler included interferon signaling, interferon gamma signaling, interleukins 4 and 13 signaling, interleukin 6 signaling, interleukin 21 signaling, and inactivation of CSF3/G-CSF signaling pathways showing significant alterations. These pathways were consistently associated with higher gene expression in CF epithelial cells compared to non-CF cells, suggesting that targeting these pathways could improve clinical outcomes. The success of quantile discretization and Bayesian network analysis in the context of CF suggests that these approaches might be applicable to other contexts where exactly comparable data sets are hard to find.

Music compensates for altered gene expression in age-related cognitive disorders

Extensive literature has explored the beneficial effects of music in age-related cognitive disorders (ACD), but limited knowledge exists regarding its impact on gene expression. We analyzed transcriptomes of ACD patients and healthy controls, pre-post a music session (n = 60), and main genes/pathways were compared to those dysregulated in mild cognitive impairment (MCI) and Alzheimer's disease (AD) as revealed by a multi-cohort study (n = 1269 MCI/AD and controls). Music was associated with 2.3 times more whole-genome gene expression, particularly on neurodegeneration-related genes, in ACD than in controls. Co-expressed gene-modules and pathways analysis demonstrated that music impacted autophagy, vesicle and endosome organization, biological processes commonly dysregulated in MCI/AD. Notably, the data indicated a strong negative correlation between musically-modified genes/pathways in ACD and those dysregulated in MCI/AD. These findings highlight the compensatory effect of music on genes/biological processes affected in MCI/AD, providing insights into the molecular mechanisms underlying the benefits of music on these disorders.

Mechanopathology of biofilm-like Mycobacterium tuberculosis cords

Mycobacterium tuberculosis (Mtb) cultured axenically without detergent forms biofilm-like cords, a clinical identifier of virulence. In lung-on-chip (LoC) and mouse models, cords in alveolar cells contribute to suppression of innate immune signaling via nuclear compression. Thereafter, extracellular cords cause contact-dependent phagocyte death but grow intercellularly between epithelial cells. The absence of these mechanopathological mechanisms explains the greater proportion of alveolar lesions with increased immune infiltration and dissemination defects in cording-deficient Mtb infections. Compression of Mtb lipid monolayers induces a phase transition that enables mechanical energy storage. Agent-based simulations demonstrate that the increased energy storage capacity is sufficient for the formation of cords that maintain structural integrity despite mechanical perturbation. Bacteria in cords remain translationally active despite antibiotic exposure and regrow rapidly upon cessation of treatment. This study provides a conceptual framework for the biophysics and function in tuberculosis infection and therapy of cord architectures independent of mechanisms ascribed to single bacteria.

Integrating spatial and single-nucleus transcriptomic data elucidates microglial-specific responses in female cynomolgus macaques with depressive-like behaviors

Major depressive disorder represents a serious public health challenge worldwide; however, the underlying cellular and molecular mechanisms are mostly unknown. Here, we profile the dorsolateral prefrontal cortex of female cynomolgus macaques with social stress-associated depressive-like behaviors using single-nucleus RNA-sequencing and spatial transcriptomics. We find gene expression changes associated with depressive-like behaviors mostly in microglia, and we report a pro-inflammatory microglia subpopulation enriched in the depressive-like condition. Single-nucleus RNA-sequencing data result in the identification of six enriched gene modules associated with depressive-like behaviors, and these modules are further resolved by spatial transcriptomics. Gene modules associated with huddle and sit alone behaviors are expressed in neurons and oligodendrocytes of the superficial cortical layer, while gene modules associated with locomotion and amicable behaviors are enriched in microglia and astrocytes in mid-to-deep cortical layers. The depressive-like behavior associated microglia subpopulation is enriched in deep cortical layers. In summary, our findings show cell-type and cortical layer-specific gene expression changes and identify one microglia subpopulation associated with depressive-like behaviors in female non-human primates.

Tumor collagens predict genetic features and patient outcomes

The extracellular matrix (ECM) is a critical determinant of tumor fate that reflects the output from myriad cell types in the tumor. Collagens constitute the principal components of the tumor ECM. The changing collagen composition in tumors along with their impact on patient outcomes and possible biomarkers remains largely unknown. The RNA expression of the 43 collagen genes from solid tumors in The Cancer Genome Atlas (TCGA) was clustered to classify tumors. PanCancer analysis revealed how collagens by themselves can identify the tissue of origin. Clustering by collagens in each cancer type demonstrated strong associations with survival, specific immunoenvironments, somatic gene mutations, copy number variations, and aneuploidy. We developed a machine learning classifier that predicts aneuploidy, and chromosome arm copy number alteration (CNA) status based on collagen expression alone with high accuracy in many cancer types with somatic mutations, suggesting a strong relationship between the collagen ECM context and specific molecular alterations. These findings have broad implications in defining the relationship between cancer-related genetic defects and the tumor microenvironment to improve prognosis and therapeutic targeting for patient care, opening new avenues of investigation to define tumor ecosystems.

Tracking early lung cancer metastatic dissemination in TRACERx using ctDNA

Circulating tumour DNA (ctDNA) can be used to detect and profile residual tumour cells persisting after curative intent therapy1. The study of large patient cohorts incorporating longitudinal plasma sampling and extended follow-up is required to determine the role of ctDNA as a phylogenetic biomarker of relapse in early-stage non-small-cell lung cancer (NSCLC). Here we developed ctDNA methods tracking a median of 200 mutations identified in resected NSCLC tissue across 1,069 plasma samples collected from 197 patients enrolled in the TRACERx study2. A lack of preoperative ctDNA detection distinguished biologically indolent lung adenocarcinoma with good clinical outcome. Postoperative plasma analyses were interpreted within the context of standard-of-care radiological surveillance and administration of cytotoxic adjuvant therapy. Landmark analyses of plasma samples collected within 120 days after surgery revealed ctDNA detection in 25% of patients, including 49% of all patients who experienced clinical relapse; 3 to 6 monthly ctDNA surveillance identified impending disease relapse in an additional 20% of landmark-negative patients. We developed a bioinformatic tool (ECLIPSE) for non-invasive tracking of subclonal architecture at low ctDNA levels. ECLIPSE identified patients with polyclonal metastatic dissemination, which was associated with a poor clinical outcome. By measuring subclone cancer cell fractions in preoperative plasma, we found that subclones seeding future metastases were significantly more expanded compared with non-metastatic subclones. Our findings will support (neo)adjuvant trial advances and provide insights into the process of metastatic dissemination using low-ctDNA-level liquid biopsy.

From SNP to pathway-based GWAS meta-analysis: do current meta-analysis approaches resolve power and replication in genetic association studies?

Genome-wide association studies (GWAS) have benefited greatly from enhanced high-throughput technology in recent decades. GWAS meta-analysis has become increasingly popular to highlight the genetic architecture of complex traits, informing about the replicability and variability of effect estimations across human ancestries. A wealth of GWAS meta-analysis methodologies have been developed depending on the input data and the outcome information of interest. We present a survey of current approaches from SNP to pathway-based meta-analysis by acknowledging the range of resources and methodologies in the field, and we provide a comprehensive review of different categories of Genome-Wide Meta-analysis methods employed. These methods highlight different levels at which GWAS meta-analysis may be done, including Single Nucleotide Polymorphisms, Genes and Pathways, for which we describe their framework outline. We also discuss the strengths and pitfalls of each approach and make suggestions regarding each of them.

TRIB1 regulates tumor growth via controlling tumor-associated macrophage phenotypes and is associated with breast cancer survival and treatment response

Molecular mechanisms that regulate tumor-associated macrophage (TAM) phenotype and function are incompletely understood. The pseudokinase TRIB1 has been reported as a regulator of macrophage phenotypes, both in mouse and human systems. Methods: Bioinformatic analysis was used to investigate the link between TRIB1 expression in breast cancer and therapeutic response to chemotherapy. In vivo models of breast cancer included immune-competent mice to characterize the consequences of altered (reduced or elevated) myeloid Trib1 expression on tumor growth and composition of stromal immune cell populations. Results: TRIB1 was highly expressed by TAMs in breast cancer and high TRIB1 expression correlated with response to chemotherapy and patient survival. Both overexpression and knockout of myeloid Trib1 promote mouse breast tumor growth, albeit through different molecular mechanisms. Myeloid Trib1 deficiency led to an early acceleration of tumor growth, paired with a selective reduction in perivascular macrophage numbers in vivo and enhanced oncogenic cytokine expression in vitro. In contrast, elevated levels of Trib1 in myeloid cells led to an increased late-stage mammary tumor volume, coupled with a reduction of NOS2 expressing macrophages and an overall reduction of macrophages in hypoxic tumor regions. In addition, we show that myeloid Trib1 is a previously unknown, negative regulator of the anti-tumor cytokine IL-15, and that increased myeloid Trib1 expression leads to reduced IL-15 levels in mammary tumors, with a consequent reduction in the number of T-cells that are key to anti-tumor immune responses. Conclusions: Together, these results define a key role for TRIB1 in chemotherapy responses for human breast cancer and provide a mechanistic understanding for the importance of the control of myeloid TRIB1 expression in the development of this disease.

Blood-derived mitochondrial DNA copy number is associated with gene expression across multiple tissues and is predictive for incident neurodegenerative disease

Mitochondrial DNA copy number (mtDNA-CN) is a proxy for mitochondrial function and is associated with aging-related diseases. However, it is unclear how mtDNA-CN measured in blood can reflect diseases that primarily manifest in other tissues. Using the Genotype-Tissue Expression Project, we interrogated relationships between mtDNA-CN measured in whole blood and gene expression from whole blood and 47 additional tissues in 419 individuals. mtDNA-CN was significantly associated with expression of 700 genes in whole blood, including nuclear genes required for mtDNA replication. Significant enrichment was observed for splicing and ubiquitin-mediated proteolysis pathways, as well as target genes for the mitochondrial transcription factor NRF1. In nonblood tissues, there were more significantly associated genes than expected in 30 tissues, suggesting that global gene expression in those tissues is correlated with blood-derived mtDNA-CN. Neurodegenerative disease pathways were significantly associated in multiple tissues, and in an independent data set, the UK Biobank, we observed that higher mtDNA-CN was significantly associated with lower rates of both prevalent (OR = 0.89, CI = 0.83; 0.96) and incident neurodegenerative disease (HR = 0.95, 95% CI = 0.91;0.98). The observation that mtDNA-CN measured in blood is associated with gene expression in other tissues suggests that blood-derived mtDNA-CN can reflect metabolic health across multiple tissues. Identification of key pathways including splicing, RNA binding, and catalysis reinforces the importance of mitochondria in maintaining cellular homeostasis. Finally, validation of the role of mtDNA CN in neurodegenerative disease in a large independent cohort study solidifies the link between blood-derived mtDNA-CN, altered gene expression in multiple tissues, and aging-related disease.

Seasonal Variability and Shared Molecular Signatures of Inactivated Influenza Vaccination in Young and Older Adults

The seasonal influenza vaccine is an important public health tool but is only effective in a subset of individuals. The identification of molecular signatures provides a mechanism to understand the drivers of vaccine-induced immunity. Most previously reported molecular signatures of human influenza vaccination were derived from a single age group or season, ignoring the effects of immunosenescence or vaccine composition. Thus, it remains unclear how immune signatures of vaccine response change with age across multiple seasons. In this study we profile the transcriptional landscape of young and older adults over five consecutive vaccination seasons to identify shared signatures of vaccine response as well as marked seasonal differences. Along with substantial variability in vaccine-induced signatures across seasons, we uncovered a common transcriptional signature 28 days postvaccination in both young and older adults. However, gene expression patterns associated with vaccine-induced Ab responses were distinct in young and older adults; for example, increased expression of killer cell lectin-like receptor B1 (KLRB1; CD161) 28 days postvaccination positively and negatively predicted vaccine-induced Ab responses in young and older adults, respectively. These findings contribute new insights for developing more effective influenza vaccines, particularly in older adults.