The volume-regulated anion channel LRRC8C suppresses T cell function by regulating cyclic dinucleotide transport and STING-p53 signaling.

The volume-regulated anion channel (VRAC) is formed by LRRC8 proteins and is responsible for the regulatory volume decrease (RVD) after hypotonic cell swelling. Besides chloride, VRAC transports other molecules, for example, immunomodulatory cyclic dinucleotides (CDNs) including 2'3'cGAMP. Here, we identify LRRC8C as a critical component of VRAC in T cells, where its deletion abolishes VRAC currents and RVD. T cells of Lrrc8c-/- mice have increased cell cycle progression, proliferation, survival, Ca2+ influx and cytokine production-a phenotype associated with downmodulation of p53 signaling. Mechanistically, LRRC8C mediates the transport of 2'3'cGAMP in T cells, resulting in STING and p53 activation. Inhibition of STING recapitulates the phenotype of LRRC8C-deficient T cells, whereas overexpression of p53 inhibits their enhanced T cell function. Lrrc8c-/- mice have exacerbated T cell-dependent immune responses, including immunity to influenza A virus infection and experimental autoimmune encephalomyelitis. Our results identify cGAMP uptake through LRRC8C and STING-p53 signaling as a new inhibitory signaling pathway in T cells and adaptive immunity.

The polar oxy-metabolome reveals the 4-hydroxymandelate CoQ10 synthesis pathway.

Oxygen is critical for a multitude of metabolic processes that are essential for human life. Biological processes can be identified by treating cells with 18O2 or other isotopically labelled gases and systematically identifying biomolecules incorporating labeled atoms. Here we labelled cell lines of distinct tissue origins with 18O2 to identify the polar oxy-metabolome, defined as polar metabolites labelled with 18O under different physiological O2 tensions. The most highly 18O-labelled feature was 4-hydroxymandelate (4-HMA). We demonstrate that 4-HMA is produced by hydroxyphenylpyruvate dioxygenase-like (HPDL), a protein of previously unknown function in human cells. We identify 4-HMA as an intermediate involved in the biosynthesis of the coenzyme Q10 (CoQ10) headgroup in human cells. The connection of HPDL to CoQ10 biosynthesis provides crucial insights into the mechanisms underlying recently described neurological diseases related to HPDL deficiencies1-4 and cancers with HPDL overexpression5.

CRL4AMBRA1 is a master regulator of D-type cyclins.

D-type cyclins are central regulators of the cell division cycle and are among the most frequently deregulated therapeutic targets in human cancer1, but the mechanisms that regulate their turnover are still being debated2,3. Here, by combining biochemical and genetics studies in somatic cells, we identify CRL4AMBRA1 (also known as CRL4DCAF3) as the ubiquitin ligase that targets all three D-type cyclins for degradation. During development, loss of Ambra1 induces the accumulation of D-type cyclins and retinoblastoma (RB) hyperphosphorylation and hyperproliferation, and results in defects of the nervous system that are reduced by treating pregnant mice with the FDA-approved CDK4 and CDK6 (CDK4/6) inhibitor abemaciclib. Moreover, AMBRA1 acts as a tumour suppressor in mouse models and low AMBRA1 mRNA levels are predictive of poor survival in cancer patients. Cancer hotspot mutations in D-type cyclins abrogate their binding to AMBRA1 and induce their stabilization. Finally, a whole-genome, CRISPR-Cas9 screen identified AMBRA1 as a regulator of the response to CDK4/6 inhibition. Loss of AMBRA1 reduces sensitivity to CDK4/6 inhibitors by promoting the formation of complexes of D-type cyclins with CDK2. Collectively, our results reveal the molecular mechanism that controls the stability of D-type cyclins during cell-cycle progression, in development and in human cancer, and implicate AMBRA1 as a critical regulator of the RB pathway.

Patient subtyping analysis of baseline multi-omic data reveals distinct pre-immune states associated with antibody response to seasonal influenza vaccination.

Understanding the molecular mechanisms underpinning diverse vaccination responses is critical for developing efficient vaccines. Molecular subtyping can offer insights into heterogeneous nature of responses and aid in vaccine design. We analyzed multi-omic data from 62 haemagglutinin seasonal influenza vaccine recipients (2019-2020), including transcriptomics, proteomics, glycomics, and metabolomics data collected pre-vaccination. We performed a subtyping analysis on the integrated data revealing five subtypes with distinct molecular signatures. These subtypes differed in the expression of pre-existing adaptive or innate immunity signatures, which were linked to significant variation in baseline immunoglobulin A (IgA) and hemagglutination inhibition (HAI) titer levels. It is worth noting that these differences persisted through day 28 post-vaccination, indicating the effect of initial immune state on vaccination response. These findings highlight the significance of interpersonal variation in baseline immune status as a crucial factor in determining the effectiveness of seasonal vaccines. Ultimately, incorporating molecular profiling could enable personalized vaccine optimization.

Longitudinal dynamics of the gut microbiome and metabolome in peanut allergy development.

BACKGROUND: Rising rates of peanut allergy (PA) motivate investigations of its development to inform prevention and therapy. Microbiota and the metabolites they produce shape food allergy risk. OBJECTIVE: We sought to gain insight into gut microbiome and metabolome dynamics in the development of PA. METHODS: We performed a longitudinal, integrative study of the gut microbiome and metabolome of infants with allergy risk factors but no PA from a multicenter cohort followed through mid-childhood. We performed 16S rRNA sequencing, short chain fatty acid measurements, and global metabolome profiling of fecal samples at infancy and at mid-childhood. RESULTS: In this longitudinal, multicenter sample (n = 122), 28.7% of infants developed PA by mid-childhood (mean age 9 years). Lower infant gut microbiome diversity was associated with PA development (P = .014). Temporal changes in the relative abundance of specific microbiota and gut metabolite levels significantly differed in children who developed PA. PA-bound children had different abundance trajectories of Clostridium sensu stricto 1 sp (false discovery rate (FDR) = 0.015) and Bifidobacterium sp (FDR = 0.033), with butyrate (FDR = 0.045) and isovalerate (FDR = 0.036) decreasing over time. Metabolites associated with PA development clustered within the histidine metabolism pathway. Positive correlations between microbiota, butyrate, and isovalerate and negative correlations with histamine marked the PA-free network. CONCLUSION: The temporal dynamics of the gut microbiome and metabolome in early childhood are distinct for children who develop PA. These findings inform our thinking on the mechanisms underlying and strategies for potentially preventing PA.

Intestinal microbiome and metabolome signatures in patients with chronic granulomatous disease.

BACKGROUND: Chronic granulomatous disease (CGD) is caused by defects in any 1 of the 6 subunits forming the nicotinamide adenine dinucleotide phosphate oxidase complex 2 (NOX2), leading to severely reduced or absent phagocyte-derived reactive oxygen species production. Almost 50% of patients with CGD have inflammatory bowel disease (CGD-IBD). While conventional IBD therapies can treat CGD-IBD, their benefits must be weighed against the risk of infection. Understanding the impact of NOX2 defects on the intestinal microbiota may lead to the identification of novel CGD-IBD treatments. OBJECTIVE: We sought to identify microbiome and metabolome signatures that can distinguish individuals with CGD and CGD-IBD. METHODS: We conducted a cross-sectional observational study of 79 patients with CGD, 8 pathogenic variant carriers, and 19 healthy controls followed at the National Institutes of Health Clinical Center. We profiled the intestinal microbiome (amplicon sequencing) and stool metabolome, and validated our findings in a second cohort of 36 patients with CGD recruited through the Primary Immune Deficiency Treatment Consortium. RESULTS: We identified distinct intestinal microbiome and metabolome profiles in patients with CGD compared to healthy individuals. We observed enrichment for Erysipelatoclostridium spp, Sellimonas spp, and Lachnoclostridium spp in CGD stool samples. Despite differences in bacterial alpha and beta diversity between the 2 cohorts, several taxa correlated significantly between both cohorts. We further demonstrated that patients with CGD-IBD have a distinct microbiome and metabolome profile compared to patients without CGD-IBD. CONCLUSION: Intestinal microbiome and metabolome signatures distinguished patients with CGD and CGD-IBD, and identified potential biomarkers and therapeutic targets.

Metabolomic, proteomic, and transcriptomic changes in adults with epilepsy on modified Atkins diet.

OBJECTIVE: High-fat and low-carbohydrate diets can reduce seizure frequency in some treatment-resistant epilepsy patients, including the more flexible modified Atkins diet (MAD), which is more palatable, mimicking fasting and inducing high ketone body levels. Low-carbohydrate diets may shift brain energy production, particularly impacting neuron- and astrocyte-linked metabolism. METHODS: We evaluated the effect of short-term MAD on molecular mechanisms in adult epilepsy patients from surgical brain tissue and plasma compared to control participants consuming a nonmodified higher carbohydrate diet (n = 6 MAD, mean age = 43.7 years, range = 21-53, diet for average 10 days; n = 10 control, mean age = 41.9 years, range = 28-64). RESULTS: By metabolomics, there were 13 increased metabolites in plasma (n = 15 participants with available specimens), which included 4.10-fold increased ketone body 3-hydroxybutyric acid, decreased palmitic acid in cortex (n = 16), and 11 decreased metabolites in hippocampus (n = 6), which had top associations with mitochondrial functions. Cortex and plasma 3-hydroxybutyric acid levels had a positive correlation (p = .0088, R2  = .48). Brain proteomics and RNAseq identified few differences, including 2.75-fold increased hippocampal MT-ND3 and trends (p < .01, false discovery rate > 5%) in hippocampal nicotinamide adenine dinucleotide (NADH)-related signaling pathways (activated oxidative phosphorylation and inhibited sirtuin signaling). SIGNIFICANCE: Short-term MAD was associated with metabolic differences in plasma and resected epilepsy brain tissue when compared to control participants, in combination with trending expression changes observed in hippocampal NADH-related signaling pathways. Future studies should evaluate how brain molecular mechanisms are altered with long-term MAD in a larger cohort of epilepsy patients, with correlations to seizure frequency, epilepsy syndrome, and other clinical variables. [Clinicaltrials.gov NCT02565966.].

Perturbed mitochondria-ER contacts in live neurons that model the amyloid pathology of Alzheimer's disease.

The use of fixed fibroblasts from familial and sporadic Alzheimer's disease patients has previously indicated an upregulation of mitochondria-ER contacts (MERCs) as a hallmark of Alzheimer's disease. Despite its potential significance, the relevance of these results is limited because they were not extended to live neurons. Here we performed a dynamic in vivo analysis of MERCs in hippocampal neurons from McGill-R-Thy1-APP transgenic rats, a model of Alzheimer's disease-like amyloid pathology. Live FRET imaging of neurons from transgenic rats revealed perturbed 'lipid-MERCs' (gap width <10 nm), while 'Ca2+-MERCs' (10-20 nm gap width) were unchanged. In situ TEM showed no significant differences in the lipid-MERCs:total MERCs or lipid-MERCs:mitochondria ratios; however, the average length of lipid-MERCs was significantly decreased in neurons from transgenic rats as compared to controls. In accordance with FRET results, untargeted lipidomics showed significant decreases in levels of 12 lipids and bioenergetic analysis revealed respiratory dysfunction of mitochondria from transgenic rats. Thus, our results reveal changes in MERC structures coupled with impaired mitochondrial functions in Alzheimer's disease-related neurons.This article has an associated First Person interview with the first author of the paper.

Sheath fluid impacts the depletion of cellular metabolites in cells afflicted by sorting induced cellular stress (SICS).

Flow cytometrists have long observed a spectrum of cell-type-specific changes ranging from minor functional defects to outright cell destruction after purification of cells using conventional droplet cell sorters. We have described this spectrum of cell perturbations as sorter induced cellular stress, or SICS (Lopez and Hulspas, Cytometry, 2020, 97, 105-106). Despite the potential impact of this issue and ubiquitous anecdotes, little has been reported about this phenomenon in the literature, and the underlying mechanism has been elusive. Inspired by others' observations (Llufrio et al., Redox Biology, 2018, 16, 381-387 and Binek et al., Journal of Proteome Research, 2019, 18, 169-181), we set out to examine SICS at the metabolic level and use this information to propose a working model. Using representative suspension (Jurkat) and adherent (NIH/3T3) cell lines we observed broad and consistent metabolic perturbations after sorting using a high-speed droplet cell sorter. Our results suggest that the SICS metabolic phenotype is a common cell-type-independent manifestation and may be the harbinger of a wide-range of functional defects either directly related to metabolism, or cell stress response pathways. We further demonstrate a proof of concept that a modification to the fluidic environment (complete media used as sheath fluid) in a droplet cell sorter can largely rescue the intracellular markers of SICS, and that this rescue is not due to a contribution of metabolites found in media. Future studies will focus on characterizing the potential electro-physical mechanisms inherent to the droplet cell sorting process to determine the major contributors to the SICS mechanism.

Regioselectivity significantly impacts microsomal glucuronidation efficiency of R/S-6, 7-, and 8-hydroxywarfarin.

Coumadin (R/S-warfarin) metabolism plays a critical role in patient response to anticoagulant therapy. Several cytochrome P450s oxidize warfarin into R/S-6-, 7-, 8-, 10, and 4'-hydroxywarfarin that can undergo subsequent glucuronidation by UDP-glucuronosyltransferases (UGTs); however, current studies on recombinant UGTs cannot be adequately extrapolated to microsomal glucuronidation capacities for the liver. Herein, we estimated the capacity of the average human liver to glucuronidate hydroxywarfarin and identified UGTs responsible for those metabolic reactions through inhibitor phenotyping. There was no observable activity toward R/S-warfarin, R/S-10-hydroxywarfarin or R/S-4'-hydroxywarfarin. The observed metabolic efficiencies (Vmax/Km) toward R/S-6-, 7-, and especially 8-hydroxywarfarin indicated a high glucuronidation capacity to metabolize these compounds. UGTs demonstrated strong regioselectivity toward the hydroxywarfarins. UGT1A6 and UGT1A1 played a major role in R/S-6- and 7-hydroxywarfarin glucuronidation, respectively, whereas UGT1A9 accounted for almost all of the generation of the R/S-8-hydroxywarfarin glucuronide. In summary, these studies expanded insights to glucuronidation of hydroxywarfarins by pooled human liver microsomes, novel roles for UGT1A6 and 1A9, and the overall degree of regioselectivity for the UGT reactions.

Generating retinoic acid gradients by local degradation during craniofacial development: One cell's cue is another cell's poison.

Retinoic acid (RA) is a vital morphogen for early patterning and organogenesis in the developing embryo. RA is a diffusible, lipophilic molecule that signals via nuclear RA receptor heterodimeric units that regulate gene expression by interacting with RA response elements in promoters of a significant number of genes. For precise RA signaling, a robust gradient of the morphogen is required. The developing embryo contains regions that produce RA, and specific intracellular concentrations of RA are created through local degradation mediated by Cyp26 enzymes. In order to elucidate the mechanisms by which RA executes precise developmental programs, the kinetics of RA metabolism must be clearly understood. Recent advances in techniques for endogenous RA detection and quantification have paved the way for mechanistic studies to shed light on downstream gene expression regulation coordinated by RA. It is increasingly coming to light that RA signaling operates not only at precise concentrations but also employs mechanisms of degradation and feedback inhibition to self-regulate its levels. A global gradient of RA throughout the embryo is often found concurrently with several local gradients, created by juxtaposed domains of RA synthesis and degradation. The existence of such local gradients has been found especially critical for the proper development of craniofacial structures that arise from the neural crest and the cranial placode populations. In this review, we summarize the current understanding of how local gradients of RA are established in the embryo and their impact on craniofacial development.

Target-Decoy-Based False Discovery Rate Estimation for Large-Scale Metabolite Identification.

Metabolite identification is a crucial step in mass spectrometry (MS)-based metabolomics. However, it is still challenging to assess the confidence of assigned metabolites. We report a novel method for estimating the false discovery rate (FDR) of metabolite assignment with a target-decoy strategy, in which the decoys are generated through violating the octet rule of chemistry by adding small odd numbers of hydrogen atoms. The target-decoy strategy was integrated into JUMPm, an automated metabolite identification pipeline for large-scale MS analysis and was also evaluated with two other metabolomics tools, mzMatch and MZmine 2. The reliability of FDR calculation was examined by false data sets, which were simulated by altering MS1 or MS2 spectra. Finally, we used the JUMPm pipeline coupled to the target-decoy strategy to process unlabeled and stable-isotope-labeled metabolomic data sets. The results demonstrate that the target-decoy strategy is a simple and effective method for evaluating the confidence of high-throughput metabolite identification.

Isotope Labeling-Assisted Evaluation of Hydrophilic and Hydrophobic Liquid Chromatograph-Mass Spectrometry for Metabolomics Profiling.

High throughput untargeted metabolomics usually relies on complementary liquid chromatography-mass spectrometry (LC-MS) methods to expand the coverage of diverse metabolites, but the integration of those methods is not fully characterized. We systematically investigated the performance of hydrophilic interaction liquid chromatography (HILIC)-MS and nanoflow reverse-phase liquid chromatography (nRPLC)-MS under 8 LC-MS settings, varying stationary phases (HILIC and C18), mobile phases (acidic and basic pH), and MS ionization modes (positive and negative). Whereas nRPLC-MS optimization was previously reported, we found in HILIC-MS (2.1 mm × 150 mm) that the optimal performance was achieved in a 90 min gradient with 100 µL/min flow rate by loading metabolite extracts from 2 mg of cell/tissue samples. Since peak features were highly compromised by contaminants, we used stable isotope labeled yeast to enhance formula identification for comparing different LC-MS conditions. The 8 LC-MS settings enabled the detection of a total of 1050 formulas, among which 78%, 73%, and 62% formulas were recovered by the best combination of 4, 3, and 2 LC-MS settings, respectively. Moreover, these yeast samples were harvested in the presence or absence of nitrogen starvation, enabling quantitative comparisons of altered formulas and metabolite structures, followed by validation with selected synthetic metabolites. The results revealed that nitrogen starvation downregulated amino acid components but upregulated uridine-related metabolism. In summary, this study introduces a thorough evaluation of hydrophilicity and hydrophobicity based LC-MS and provides information for selecting complementary settings to balance throughput and efficiency during metabolomics experiments.

U1 small nuclear ribonucleoprotein complex and RNA splicing alterations in Alzheimer's disease.

Deposition of insoluble protein aggregates is a hallmark of neurodegenerative diseases. The universal presence of ß-amyloid and tau in Alzheimer's disease (AD) has facilitated advancement of the amyloid cascade and tau hypotheses that have dominated AD pathogenesis research and therapeutic development. However, the underlying etiology of the disease remains to be fully elucidated. Here we report a comprehensive study of the human brain-insoluble proteome in AD by mass spectrometry. We identify 4,216 proteins, among which 36 proteins accumulate in the disease, including U1-70K and other U1 small nuclear ribonucleoprotein (U1 snRNP) spliceosome components. Similar accumulations in mild cognitive impairment cases indicate that spliceosome changes occur in early stages of AD. Multiple U1 snRNP subunits form cytoplasmic tangle-like structures in AD but not in other examined neurodegenerative disorders, including Parkinson disease and frontotemporal lobar degeneration. Comparison of RNA from AD and control brains reveals dysregulated RNA processing with accumulation of unspliced RNA species in AD, including myc box-dependent-interacting protein 1, clusterin, and presenilin-1. U1-70K knockdown or antisense oligonucleotide inhibition of U1 snRNP increases the protein level of amyloid precursor protein. Thus, our results demonstrate unique U1 snRNP pathology and implicate abnormal RNA splicing in AD pathogenesis.

A nano ultra-performance liquid chromatography-high resolution mass spectrometry approach for global metabolomic profiling and case study on drug-resistant multiple myeloma.

Global metabolomics relies on highly reproducible and sensitive detection of a wide range of metabolites in biological samples. Here we report the optimization of metabolome analysis by nanoflow ultraperformance liquid chromatography coupled to high-resolution orbitrap mass spectrometry. Reliable peak features were extracted from the LC-MS runs based on mandatory detection in duplicates and additional noise filtering according to blank injections. The run-to-run variation in peak area showed a median of 14%, and the false discovery rate during a mock comparison was evaluated. To maximize the number of peak features identified, we systematically characterized the effect of sample loading amount, gradient length, and MS resolution. The number of features initially rose and later reached a plateau as a function of sample amount, fitting a hyperbolic curve. Longer gradients improved unique feature detection in part by time-resolving isobaric species. Increasing the MS resolution up to 120000 also aided in the differentiation of near isobaric metabolites, but higher MS resolution reduced the data acquisition rate and conferred no benefits, as predicted from a theoretical simulation of possible metabolites. Moreover, a biphasic LC gradient allowed even distribution of peak features across the elution, yielding markedly more peak features than the linear gradient. Using this robust nUPLC-HRMS platform, we were able to consistently analyze ~6500 metabolite features in a single 60 min gradient from 2 mg of yeast, equivalent to ~50 million cells. We applied this optimized method in a case study of drug (bortezomib) resistant and drug-sensitive multiple myeloma cells. Overall, 18% of metabolite features were matched to KEGG identifiers, enabling pathway enrichment analysis. Principal component analysis and heat map data correctly clustered isogenic phenotypes, highlighting the potential for hundreds of small molecule biomarkers of cancer drug resistance.

Chemosensory detection of polyamine metabolites guides C. elegans to nutritive microbes.

Much is known about molecular mechanisms by which animals detect pathogenic microbes, but how animals sense beneficial microbes remains poorly understood. The roundworm Caenorhabditis elegans is a microbivore that must distinguish nutritive microbes from pathogens. We characterized a neural circuit used by C. elegans to rapidly discriminate between nutritive bacteria and pathogens. Distinct sensory neuron populations responded to chemical cues from nutritive Escherichia coli and pathogenic Enterococcus faecalis, and these neural signals are decoded by downstream AIB interneurons. The polyamine metabolites cadaverine, putrescine, and spermidine produced by E. coli activate this neural circuit and elicit positive chemotaxis. Our study shows how polyamine odorants can be sensed by animals as proxies for microbe identity and suggests that, hence, polyamines might have widespread roles brokering host-microbe interactions.

Dietary and water restriction leads to increased susceptibility to antimicrobial resistant pathogens.

Dehydration and malnutrition are common and often underdiagnosed in hospital settings. Multidrug-resistant bacterial infections result in more than 35,000 deaths a year in nosocomial patients. The effect of temporal dietary and water restriction (DWR) on susceptibility to multidrug-resistant pathogens is unknown. We report that DWR markedly increased susceptibility to systemic infection by ESKAPE pathogens. Using a murine bloodstream model of methicillin-resistant Staphylococcus aureus infection, we show that DWR leads to significantly increased mortality and morbidity. DWR causes increased bacterial burden, severe pathology, and increased numbers of phagocytes in the kidney. DWR appears to alter the functionality of these phagocytes and is therefore unable to control infection. Mechanistically, we show that DWR impairs the ability of macrophages to phagocytose multiple bacterial pathogens and efferocytose apoptotic neutrophils. Together, this work highlights the crucial impact that diet and hydration play in protecting against infection.

Targeting pancreatic cancer metabolic dependencies through glutamine antagonism.

Pancreatic ductal adenocarcinoma (PDAC) cells use glutamine (Gln) to support proliferation and redox balance. Early attempts to inhibit Gln metabolism using glutaminase inhibitors resulted in rapid metabolic reprogramming and therapeutic resistance. Here, we demonstrated that treating PDAC cells with a Gln antagonist, 6-diazo-5-oxo-L-norleucine (DON), led to a metabolic crisis in vitro. In addition, we observed a profound decrease in tumor growth in several in vivo models using sirpiglenastat (DRP-104), a pro-drug version of DON that was designed to circumvent DON-associated toxicity. We found that extracellular signal-regulated kinase (ERK) signaling is increased as a compensatory mechanism. Combinatorial treatment with DRP-104 and trametinib led to a significant increase in survival in a syngeneic model of PDAC. These proof-of-concept studies suggested that broadly targeting Gln metabolism could provide a therapeutic avenue for PDAC. The combination with an ERK signaling pathway inhibitor could further improve the therapeutic outcome.

Patient Subtyping Analysis of Baseline Multi-omic Data Reveals Distinct Pre-immune States Predictive of Vaccination Responses.

Understanding the molecular mechanisms that underpin diverse vaccination responses is a critical step toward developing efficient vaccines. Molecular subtyping approaches can offer valuable insights into the heterogeneous nature of responses and aid in the design of more effective vaccines. In order to explore the molecular signatures associated with the vaccine response, we analyzed baseline transcriptomics data from paired samples of whole blood, proteomics and glycomics data from serum, and metabolomics data from urine, obtained from influenza vaccine recipients (2019-2020 season) prior to vaccination. After integrating the data using a network-based model, we performed a subtyping analysis. The integration of multiple data modalities from 62 samples resulted in five baseline molecular subtypes with distinct molecular signatures. These baseline subtypes differed in the expression of pre-existing adaptive or innate immunity signatures, which were linked to significant variation across subtypes in baseline immunoglobulin A (IgA) and hemagglutination inhibition (HAI) titer levels. It is worth noting that these significant differences persisted through day 28 post-vaccination, indicating the effect of initial immune state on vaccination response. These findings highlight the significance of interpersonal variation in baseline immune status as a crucial factor in determining vaccine response and efficacy. Ultimately, incorporating molecular profiling could enable personalized vaccine optimization.