Microglial P2Y6 calcium signaling promotes phagocytosis and shapes neuroimmune responses in epileptogenesis.

Microglial calcium signaling is rare in a baseline state but strongly engaged during early epilepsy development. The mechanism(s) governing microglial calcium signaling are not known. By developing an in vivo uridine diphosphate (UDP) fluorescent sensor, GRABUDP1.0, we discovered that UDP release is a conserved response to seizures and excitotoxicity across brain regions. UDP can signal through the microglial-enriched P2Y6 receptor to increase calcium activity during epileptogenesis. P2Y6 calcium activity is associated with lysosome biogenesis and enhanced production of NF-κB-related cytokines. In the hippocampus, knockout of the P2Y6 receptor prevents microglia from fully engulfing neurons. Attenuating microglial calcium signaling through calcium extruder ("CalEx") expression recapitulates multiple features of P2Y6 knockout, including reduced lysosome biogenesis and phagocytic interactions. Ultimately, P2Y6 knockout mice retain more CA3 neurons and better cognitive task performance during epileptogenesis. Our results demonstrate that P2Y6 signaling impacts multiple aspects of myeloid cell immune function during epileptogenesis.

Safety, feasibility, and impact on the gut microbiome of kefir administration in critically ill adults.

BACKGROUND: Dysbiosis of the gut microbiome is frequent in the intensive care unit (ICU), potentially leading to a heightened risk of nosocomial infections. Enhancing the gut microbiome has been proposed as a strategic approach to mitigate potential adverse outcomes. While prior research on select probiotic supplements has not successfully shown to improve gut microbial diversity, fermented foods offer a promising alternative. In this open-label phase I safety and feasibility study, we examined the safety and feasibility of kefir as an initial step towards utilizing fermented foods to mitigate gut dysbiosis in critically ill patients. METHODS: We administered kefir in escalating doses (60 mL, followed by 120 mL after 12 h, then 240 mL daily) to 54 critically ill patients with an intact gastrointestinal tract. To evaluate kefir's safety, we monitored for gastrointestinal symptoms. Feasibility was determined by whether patients received a minimum of 75% of their assigned kefir doses. To assess changes in the gut microbiome composition following kefir administration, we collected two stool samples from 13 patients: one within 72 h of admission to the ICU and another at least 72 h after the first stool sample. RESULTS: After administering kefir, none of the 54 critically ill patients exhibited signs of kefir-related bacteremia. No side effects like bloating, vomiting, or aspiration were noted, except for diarrhea in two patients concurrently on laxatives. Out of the 393 kefir doses prescribed for all participants, 359 (91%) were successfully administered. We were able to collect an initial stool sample from 29 (54%) patients and a follow-up sample from 13 (24%) patients. Analysis of the 26 paired samples revealed no increase in gut microbial α-diversity between the two timepoints. However, there was a significant improvement in the Gut Microbiome Wellness Index (GMWI) by the second timepoint (P = 0.034, one-sided Wilcoxon signed-rank test); this finding supports our hypothesis that kefir administration can improve gut health in critically ill patients. Additionally, the known microbial species in kefir were found to exhibit varying levels of engraftment in patients' guts. CONCLUSIONS: Providing kefir to critically ill individuals is safe and feasible. Our findings warrant a larger evaluation of kefir's safety, tolerability, and impact on gut microbiome dysbiosis in patients admitted to the ICU. TRIAL REGISTRATION: NCT05416814; trial registered on June 13, 2022.

Cerebrospinal fluid proteomic signatures are associated with symptom severity of first-episode psychosis.

Apart from their diagnostic, monitoring, or prognostic utility in clinical settings, molecular biomarkers may be instrumental in understanding the pathophysiology of psychiatric disorders, including schizophrenia. Using untargeted metabolomics, we recently identified eight cerebrospinal fluid (CSF) metabolites unique to first-episode psychosis (FEP) subjects compared to healthy controls (HC). In this study, we sought to investigate the CSF proteomic signatures associated with FEP. We employed 16-plex tandem mass tag (TMT) mass spectrometry (MS) to examine the relative protein abundance in CSF samples of 15 individuals diagnosed with FEP and 15 age-and-sex-matched healthy controls (HC). Multiple linear regression model (MLRM) identified 16 differentially abundant CSF proteins between FEP and HC at p < 0.01. Among them, the two most significant CSF proteins were collagen alpha-2 (IV) chain (COL4A2: standard mean difference [SMD] = -1.12, p = 1.64 × 10-4) and neuron-derived neurotrophic factor (NDNF: SMD = -1.03, p = 4.52 × 10-4) both of which were down-regulated in FEP subjects compared to HC. We also identified several potential CSF proteins associated with the pathophysiology and the symptom profile and severity in FEP subjects, including COL4A2, NDNF, hornerin (HRNR), contactin-6 (CNTN6), voltage-dependent calcium channel subunit alpha-2/delta-3 (CACNA2D3), tropomyosin alpha-3 chain (TPM3 and TPM4). Moreover, several protein signatures were associated with cognitive performance. Although the results need replication, our exploratory study suggests that CSF protein signatures can be used to increase the understanding of the pathophysiology of psychosis.

Retinal neurodegeneration in diabetic retinopathy with systemic hypertension.

PURPOSE: To identify the impact of hypertension (HTN) on inner retinal layer thickness in patients with diabetic retinopathy (DR). METHODS: In this retrospective cross-sectional study, participants were divided into three groups: type 2 diabetes patients without DR (DM group), patients with DR (DR group), and patients with both DR and HTN (DR+HTN group). The peripapillary retinal nerve fiber layer (pRNFL) and ganglion cell-inner plexiform layer (GC-IPL) thicknesses, measured using optical coherence tomography, were compared among the groups. RESULTS: A total of 470 eyes were enrolled: 224 eyes in the DM group, 131 eyes in the DR group, and 115 eyes in the DR+HTN group. The mean RNFL thicknesses were 95.0 ± 7.7, 92.5 ± 10.1, and 89.2 ± 11.2 µm, and the mean GC-IPL thicknesses were 84.0 ± 5.7, 82.0 ± 7.6, and 79.2 ± 8.1 µm in each group, respectively (all P < 0.001). In the DR+HTN group, the DR stage showed a significant association with pRNFL (B = - 5.38, P = 0.014) and GC-IPL (B = - 5.18, P = 0.001) thicknesses in multivariate analyses. Subgroup analyses revealed that pRNFL (P = 0.007) and GC-IPL (P = 0.005) thicknesses decreased significantly as DR progressed only in the DR+HTN group. CONCLUSIONS: Patients with both DR and HTN exhibited much thinner pRNFL and GC-IPL, compared with patients with DR only. These results may have been related to the amplified diabetic retinal neurodegeneration and synergistic impact of ischemia in DR patients with concurrent HTN. Additionally, the progression of DR resulted in more severe inner retinal damage when combined with HTN.

The human gut microbiome in critical illness: disruptions, consequences, and therapeutic frontiers.

With approximately 39 trillion cells and over 20 million genes, the human gut microbiome plays an integral role in both health and disease. Modern living has brought a widespread use of processed food and beverages, antimicrobial and immunomodulatory drugs, and invasive procedures, all of which profoundly disrupt the delicate homeostasis between the host and its microbiome. Of particular interest is the human gut microbiome, which is progressively being recognized as an important contributing factor in many aspects of critical illness, from predisposition to recovery. Herein, we describe the current understanding of the adverse impacts of standard intensive care interventions on the human gut microbiome and delve into how these microbial alterations can influence patient outcomes. Additionally, we explore the potential association between the gut microbiome and post-intensive care syndrome, shedding light on a previously underappreciated avenue that may enhance patient recuperation following critical illness. There is an impending need for future epidemiological studies to encompass detailed phenotypic analyses of gut microbiome perturbations. Interventions aimed at restoring the gut microbiome represent a promising therapeutic frontier in the quest to prevent and treat critical illnesses.

Changes in peripapillary microvasculature in patients with type 2 diabetes patients: effect of systemic hypertension.

To determine the effect of hypertension (HTN) on the peripapillary microvasculature in type 2 diabetes mellitus (T2DM) patients without diabetic retinopathy (DR). The patients were classified into three groups: the control group (group 1), T2DM group (group 2), and both T2DM and HTN group (group 3). Peripapillary vessel density (VD) was compared using analysis of covariance and linear regression analysis was performed to identify the factors affecting the peripapillary VD. A total of 286 eyes were enrolled: 124 in group 1, 111 in group 2, and 51 in group 3. The peripapillary VDs for the full area were 18.3 ± 0.6, 17.8 ± 1.0, and 17.3 ± 1.2 mm-1 in group 1, group 2, and group 3, respectively, which were significantly different after adjustment for age and best-corrected visual acuity (P < 0.001). In post hoc analyses, group 1 versus group 2 (P < 0.001), group 1 versus group 3 (P < 0.001), and group 2 versus group 3 (P = 0.001) showed significant differences. In linear regression analysis, HTN (B = - 0.352, P = 0.043) and peripapillary retinal nerve fiber layer (pRNFL) thickness (B = 0.045, P < 0.001) were significantly associated with peripapillary VD in T2DM patients. Peripapillary VD in T2DM patients without clinical DR were lower compared to normal controls, and they were more decreased when HTN was comorbid. The combination of ischemic damage by high blood pressure and impairment of the neurovascular unit by hyperglycemia would result in more severe deterioration of peripapillary microvasculature, and this impairment could be also reflected by pRNFL thinning.

Analyses of the ratio of ganglion cell-inner plexiform layer thickness to vessel density according to age in healthy eyes.

PURPOSE: To identify how the inner retinal layer and microvasculature change with age by analyzing the relationships of ganglion cell-inner plexiform layer (GC-IPL) thickness, vessel density (VD), and the ratio of these measurements with age in healthy eyes. METHODS: Participants were divided into five groups according to age. The GC-IPL thickness, VD, and GC-IPL/VD ratio were compared among the groups. Linear regression analyses were performed to identify relationships of GC-IPL/VD ratio with age. RESULTS: The average GC-IPL thicknesses were 84.84 ± 5.28, 84.22 ± 5.30, 85.20 ± 6.29, 83.29 ± 7.06, and 82.26 ± 5.62 µm in the 20s, 30s, 40s, 50s, and 60s age groups, respectively. The VDs were 20.94 ± 1.50, 21.06 ± 1.50, 20.99 ± 1.03, 20.71 ± 0.93, and 19.74 ± 1.73 mm-1 in the 20s, 30s, 40s, 50s, and 60s age groups, respectively. The GC-IPL/VD ratio was 4.05, 4.00, 4.06, 4.02, and 4.17 in each group, respectively, and the ratio of the 60s age group was significantly higher than that of other groups. In linear regression analyses, the GC-IPL/VD ratio was significantly associated with age in the participants aged ≥ 50 years (B = 0.014, P = 0.013), whereas it was not in the participants aged < 50 years (B = 0.003, P = 0.434). CONCLUSIONS: GC-IPL thickness and macular VD showed a tendency to decrease beginning in the 50s age group and the GC-IPL/VD ratio was significantly increased in the 60s age group. Additionally, the GC-IPL/VD ratio was positively associated with age in subjects aged ≥ 50 years, which implies a more pronounced decline over time in VD rather than GC-IPL thickness.

Gut Microbiome Wellness Index 2 for Enhanced Health Status Prediction from Gut Microbiome Taxonomic Profiles.

Recent advancements in human gut microbiome research have revealed its crucial role in shaping innovative predictive healthcare applications. We introduce Gut Microbiome Wellness Index 2 (GMWI2), an advanced iteration of our original GMWI prototype, designed as a robust, disease-agnostic health status indicator based on gut microbiome taxonomic profiles. Our analysis involved pooling existing 8069 stool shotgun metagenome data across a global demographic landscape to effectively capture biological signals linking gut taxonomies to health. GMWI2 achieves a cross-validation balanced accuracy of 80% in distinguishing healthy (no disease) from non-healthy (diseased) individuals and surpasses 90% accuracy for samples with higher confidence (i.e., outside the "reject option"). The enhanced classification accuracy of GMWI2 outperforms both the original GMWI model and traditional species-level α-diversity indices, suggesting a more reliable tool for differentiating between healthy and non-healthy phenotypes using gut microbiome data. Furthermore, by reevaluating and reinterpreting previously published data, GMWI2 provides fresh insights into the established understanding of how diet, antibiotic exposure, and fecal microbiota transplantation influence gut health. Looking ahead, GMWI2 represents a timely pivotal tool for evaluating health based on an individual's unique gut microbial composition, paving the way for the early screening of adverse gut health shifts. GMWI2 is offered as an open-source command-line tool, ensuring it is both accessible to and adaptable for researchers interested in the translational applications of human gut microbiome science.

Microglial P2Y6 calcium signaling promotes phagocytosis and shapes neuroimmune responses in epileptogenesis.

Microglial calcium signaling is rare in a baseline state but shows strong engagement during early epilepsy development. The mechanism and purpose behind microglial calcium signaling is not known. By developing an in vivo UDP fluorescent sensor, GRABUDP1.0, we discovered that UDP release is a conserved response to seizures and excitotoxicity across brain regions. UDP signals to the microglial P2Y6 receptor for broad increases in calcium signaling during epileptogenesis. UDP-P2Y6 signaling is necessary for lysosome upregulation across limbic brain regions and enhances production of pro-inflammatory cytokines-TNFα and IL-1ß. Failures in lysosome upregulation, observed in P2Y6 KO mice, can also be phenocopied by attenuating microglial calcium signaling in Calcium Extruder ("CalEx") mice. In the hippocampus, only microglia with P2Y6 expression can perform full neuronal engulfment, which substantially reduces CA3 neuron survival and impairs cognition. Our results demonstrate that calcium activity, driven by UDP-P2Y6 signaling, is a signature of phagocytic and pro-inflammatory function in microglia during epileptogenesis.

Evaluating the prebiotic effect of oligosaccharides on gut microbiome wellness using in vitro fecal fermentation.

We previously proposed the Gut Microbiome Wellness Index (GMWI), a predictor of disease presence based on a gut microbiome taxonomic profile. As an application of this index for food science research, we applied GMWI as a quantitative tool for measuring the prebiotic effect of oligosaccharides. Mainly, in an in vitro anaerobic batch fermentation system, fructooligosaccharides (FOS), galactooligosaccharides (GOS), xylooligosaccharides (XOS), inulin (IN), and 2'-fucosyllactose (2FL), were mixed separately with fecal samples obtained from healthy adult volunteers. To find out how 24 h prebiotic fermentation influenced the GMWI values in their respective microbial communities, changes in species-level relative abundances were analyzed in the five prebiotics groups, as well as in two control groups (no substrate addition at 0 h and for 24 h). The GMWI of fecal microbiomes treated with any of the five prebiotics (IN (0.48 ± 0.06) > FOS (0.47 ± 0.03) > XOS (0.33 ± 0.02) > GOS (0.26 ± 0.02) > 2FL (0.16 ± 0.06)) were positive, which indicates an increase of relative abundances of microbial species previously found to be associated with a healthy, disease-free state. In contrast, the GMWI of samples without substrate addition for 24 h (-0.60 ± 0.05) reflected a non-healthy, disease-harboring microbiome state. Compared to the original prebiotic index (PI) and α-diversity metrics, GMWI provides a more data-driven, evidence-based indexing system for evaluating the prebiotic effect of food components. This study demonstrates how GMWI can be applied as a novel PI in dietary intervention studies, with wider implications for designing personalized diets based on their impact on gut microbiome wellness.

Patients with ACPA-positive and ACPA-negative rheumatoid arthritis show different serological autoantibody repertoires and autoantibody associations with disease activity.

Patients with rheumatoid arthritis (RA) can test either positive or negative for circulating anti-citrullinated protein antibodies (ACPA) and are thereby categorized as ACPA-positive (ACPA+) or ACPA-negative (ACPA-), respectively. In this study, we aimed to elucidate a broader range of serological autoantibodies that could further explain immunological differences between patients with ACPA+ RA and ACPA- RA. On serum collected from adult patients with ACPA+ RA (n = 32), ACPA- RA (n = 30), and matched healthy controls (n = 30), we used a highly multiplex autoantibody profiling assay to screen for over 1600 IgG autoantibodies that target full-length, correctly folded, native human proteins. We identified differences in serum autoantibodies between patients with ACPA+ RA and ACPA- RA compared with healthy controls. Specifically, we found 22 and 19 autoantibodies with significantly higher abundances in ACPA+ RA patients and ACPA- RA patients, respectively. Among these two sets of autoantibodies, only one autoantibody (anti-GTF2A2) was common in both comparisons; this provides further evidence of immunological differences between these two RA subgroups despite sharing similar symptoms. On the other hand, we identified 30 and 25 autoantibodies with lower abundances in ACPA+ RA and ACPA- RA, respectively, of which 8 autoantibodies were common in both comparisons; we report for the first time that the depletion of certain autoantibodies may be linked to this autoimmune disease. Functional enrichment analysis of the protein antigens targeted by these autoantibodies showed an over-representation of a range of essential biological processes, including programmed cell death, metabolism, and signal transduction. Lastly, we found that autoantibodies correlate with Clinical Disease Activity Index, but associate differently depending on patients' ACPA status. In all, we present candidate autoantibody biomarker signatures associated with ACPA status and disease activity in RA, providing a promising avenue for patient stratification and diagnostics.

GMWI-webtool: a user-friendly browser application for assessing health through metagenomic gut microbiome profiling.

SUMMARY: We recently introduced the Gut Microbiome Wellness Index (GMWI), a stool metagenome-based indicator for assessing health by determining the likelihood of disease given the state of one's gut microbiome. The calculation of our wellness index depends on the relative abundances of health-prevalent and health-scarce species. Encouragingly, GMWI has already been utilized in various studies focusing on differences in the gut microbiome between cases and controls. Herein, we introduce the GMWI-webtool, a user-friendly browser application that computes GMWI, health-prevalent/-scarce species' relative abundances, and α-diversities from stool shotgun metagenome taxonomic profiles. Users of our interactive online tool can visualize their results and compare them side-by-side with those from our pooled reference dataset of metagenomes, as well as export data in.csv format and high-resolution figures. AVAILABILITY AND IMPLEMENTATION: GMWI-webtool is freely available here: https://gmwi-webtool.github.io/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Different characteristics of retinal damage between chronic hypertension and hypertensive retinopathy.

The purpose of this study was to identify how chronic hypertension (HTN) and hypertensive retinopathy (HTNR) have different effects on retinal damage including inner retinal thinning and microvasculature impairment. The subjects were divided into three groups: controls, HTN patients without HTNR (HTN group), and patients with relieved HTNR (HTNR group). The ganglion cell-inner plexiform layer (GC-IPL) thickness, vessel density (VD), and GC-IPL/VD ratio were compared among the groups. A total of 241 eyes were enrolled; 101 in the control group, 92 in the HTN group, and 48 in the HTNR group. The mean GC-IPL thicknesses were 83.5 ± 5.7, 82.1 ± 6.2, and 75.9 ± 10.7 µm in each group, respectively (P < 0.001). The VD was 20.5 ± 1.3, 19.6 ± 1.4, and 19.5 ± 1.6 mm-1 in each group, respectively (P = 0.001). The GC-IPL/VD ratio was 4.10 ± 0.33, 4.20 ± 0.40, and 3.88 ± 0.56 in each group, respectively (P < 0.001). In the HTNR group, HTN duration (B = 0.054, P = 0.013) and systolic blood pressure (SBP) (B = -0.012, P = 0.004) were significantly associated with the GC-IPL/VD ratio. In conclusion, inner retinal reduction and retinal microvasculature impairment were observed in patients with HTN and HTNR, and the GC-IPL/VD ratio of HTNR patients was significantly lower than that of HTN patients, indicating more prominent damage to the inner retina than microvasculature in HTNR patients. Additionally, the GC-IPL/VD ratio was significantly associated with SBP in HTNR patients, so more strict BP control is required in HTNR patients.

TaxiBGC: a Taxonomy-Guided Approach for Profiling Experimentally Characterized Microbial Biosynthetic Gene Clusters and Secondary Metabolite Production Potential in Metagenomes.

Biosynthetic gene clusters (BGCs) in microbial genomes encode bioactive secondary metabolites (SMs), which can play important roles in microbe-microbe and host-microbe interactions. Given the biological significance of SMs and the current profound interest in the metabolic functions of microbiomes, the unbiased identification of BGCs from high-throughput metagenomic data could offer novel insights into the complex chemical ecology of microbial communities. Currently available tools for predicting BGCs from shotgun metagenomes have several limitations, including the need for computationally demanding read assembly, predicting a narrow breadth of BGC classes, and not providing the SM product. To overcome these limitations, we developed taxonomy-guided identification of biosynthetic gene clusters (TaxiBGC), a command-line tool for predicting experimentally characterized BGCs (and inferring their known SMs) in metagenomes by first pinpointing the microbial species likely to harbor them. We benchmarked TaxiBGC on various simulated metagenomes, showing that our taxonomy-guided approach could predict BGCs with much-improved performance (mean F1 score, 0.56; mean PPV score, 0.80) compared with directly identifying BGCs by mapping sequencing reads onto the BGC genes (mean F1 score, 0.49; mean PPV score, 0.41). Next, by applying TaxiBGC on 2,650 metagenomes from the Human Microbiome Project and various case-control gut microbiome studies, we were able to associate BGCs (and their SMs) with different human body sites and with multiple diseases, including Crohn's disease and liver cirrhosis. In all, TaxiBGC provides an in silico platform to predict experimentally characterized BGCs and their SM production potential in metagenomic data while demonstrating important advantages over existing techniques. IMPORTANCE Currently available bioinformatics tools to identify BGCs from metagenomic sequencing data are limited in their predictive capability or ease of use to even computationally oriented researchers. We present an automated computational pipeline called TaxiBGC, which predicts experimentally characterized BGCs (and infers their known SMs) in shotgun metagenomes by first considering the microbial species source. Through rigorous benchmarking techniques on simulated metagenomes, we show that TaxiBGC provides a significant advantage over existing methods. When demonstrating TaxiBGC on thousands of human microbiome samples, we associate BGCs encoding bacteriocins with different human body sites and diseases, thereby elucidating a possible novel role of this antibiotic class in maintaining the stability of microbial ecosystems throughout the human body. Furthermore, we report for the first time gut microbial BGC associations shared among multiple pathologies. Ultimately, we expect our tool to facilitate future investigations into the chemical ecology of microbial communities across diverse niches and pathologies.

Adenosine A2A receptor blockade prevents cisplatin-induced impairments in neurogenesis and cognitive function.

Chemotherapy-induced cognitive impairment (CICI) has emerged as a significant medical problem without therapeutic options. Using the platinum-based chemotherapy cisplatin to model CICI, we revealed robust elevations in the adenosine A2A receptor (A2AR) and its downstream effectors, cAMP and CREB, by cisplatin in the adult mouse hippocampus, a critical brain structure for learning and memory. Notably, A2AR inhibition by the Food and Drug Administration-approved A2AR antagonist KW-6002 prevented cisplatin-induced impairments in neural progenitor proliferation and dendrite morphogenesis of adult-born neurons, while improving memory and anxiety-like behavior, without affecting tumor growth or cisplatin's antitumor activity. Collectively, our study identifies A2AR signaling as a key pathway that can be therapeutically targeted to prevent cisplatin-induced cognitive impairments.

The Ganglion Cell-Inner Plexiform Layer Thickness/Vessel Density of Superficial Vascular Plexus Ratio According to the Progression of Diabetic Retinopathy.

Purpose: The purpose of this study was to identify the relationship between the gangion cell-inner plexiform layer (GC-IPL) and retinal vasculature in the context of the progression of diabetic retinopathy (DR). Methods: The subjects were divided into four groups according to DR stage: normal controls (group 1), patients with diabetes mellitus (DM) without DR (group 2), patients with mild or moderate nonprogressive DR (NPDR; group 3), and patients with severe NPDR (group 4). GC-IPL thickness, vessel density of superficial vascular plexus (SVD), and the GC-IPL/SVD ratio were compared among the groups. Results: A total of 556 eyes were enrolled; 288 in group 1, 140 in group 2, 76 in group 3, and 52 in group 4. The mean GC-IPL thicknesses were 83.57 ± 7.35, 82.74 ± 7.22, 81.33 ± 6.74, and 79.89 ± 9.16 µm in each group, respectively (P = 0.006). The mean SVDs were 20.40 ± 1.26, 19.70 ± 1.56, 18.86 ± 2.04, and 17.82 ± 2.04 mm-1 in each group, respectively (P < 0.001). The GC-IPL/SVD ratios were 4.11 ± 0.38, 4.22 ± 0.40, 4.36 ± 0.54, and 4.54 ± 0.55 in each group, respectively (P < 0.001). In Pearson's correlation analysis, DR stage was significantly correlated with the GC-IPL/SVD ratio (coefficient = 0.301; P < 0.001). Conclusions: As the DR stage progressed, the GC-IPL thickness tended to decrease, with the macular SVD showing a significant reduction. Additionally, the impairment of retinal vasculature was more prominent than GC-IPL thinning as DR progressed, which suggests that retinal vasculature changes may precede diabetic retinal neurodegeneration.

Global Transcriptomic Profiling Identifies Differential Gene Expression Signatures Between Inflammatory and Noninflammatory Aortic Aneurysms.

OBJECTIVE: To identify hallmark genes and biomolecular processes in aortitis using high-throughput gene expression profiling, and to provide a range of potentially new drug targets (genes) and therapeutics from a pharmacogenomic network analysis. METHODS: Bulk RNA sequencing was performed on surgically resected ascending aortic tissues from inflammatory aneurysms (giant cell arteritis [GCA] with or without polymyalgia rheumatica, n = 8; clinically isolated aortitis [CIA], n = 17) and noninflammatory aneurysms (n = 25) undergoing surgical aortic repair. Differentially expressed genes (DEGs) between the 2 patient groups were identified while controlling for clinical covariates. A protein-protein interaction model, drug-gene target information, and the DEGs were used to construct a pharmacogenomic network for identifying promising drug targets and potentially new treatment strategies in aortitis. RESULTS: Overall, tissue gene expression patterns were the most associated with disease state than with any other clinical characteristic. We identified 159 and 93 genes that were significantly up-regulated and down-regulated, respectively, in inflammatory aortic aneurysms compared to noninflammatory aortic aneurysms. We found that the up-regulated genes were enriched in immune-related functions, whereas the down-regulated genes were enriched in neuronal processes. Notably, gene expression profiles of inflammatory aortic aneurysms from patients with GCA were no different than those from patients with CIA. Finally, our pharmacogenomic network analysis identified genes that could potentially be targeted by immunosuppressive drugs currently approved for other inflammatory diseases. CONCLUSION: We performed the first global transcriptomics analysis in inflammatory aortic aneurysms from surgically resected aortic tissues. We identified signature genes and biomolecular processes, while finding that CIA may be a limited presentation of GCA. Moreover, our computational network analysis revealed potential novel strategies for pharmacologic interventions and suggests future biomarker discovery directions for the precise diagnosis and treatment of aortitis.

Multi-omics reveals microbiome, host gene expression, and immune landscape in gastric carcinogenesis.

To date, there has been no multi-omic analysis characterizing the intricate relationships between the intragastric microbiome and gastric mucosal gene expression in gastric carcinogenesis. Using multi-omic approaches, we provide a comprehensive view of the connections between the microbiome and host gene expression in distinct stages of gastric carcinogenesis (i.e., healthy, gastritis, cancer). Our integrative analysis uncovers various associations specific to disease states. For example, uniquely in gastritis, Helicobacteraceae is highly correlated with the expression of FAM3D, which has been previously implicated in gastrointestinal inflammation. In addition, in gastric cancer but not in adjacent gastritis, Lachnospiraceae is highly correlated with the expression of UBD, which regulates mitosis and cell cycle time. Furthermore, lower abundances of B cell signatures in gastric cancer compared to gastritis may suggest a previously unidentified immune evasion process in gastric carcinogenesis. Our study provides the most comprehensive description of microbial, host transcriptomic, and immune cell factors of the gastric carcinogenesis pathway.

Resource-allocation constraint governs structure and function of microbial communities in metabolic modeling.

Predictive modeling tools for assessing microbial communities are important for realizing transformative capabilities of microbiomes in agriculture, ecology, and medicine. Constraint-based community-scale metabolic modeling is unique in its potential for making mechanistic predictions regarding both the structure and function of microbial communities. However, accessing this potential requires an understanding of key physicochemical constraints, which are typically considered on a per-species basis. What is needed is a means of incorporating global constraints relevant to microbial ecology into community models. Resource-allocation constraint, which describes how limited resources should be distributed to different cellular processes, sets limits on the efficiency of metabolic and ecological processes. In this study, we investigate the implications of resource-allocation constraints in community-scale metabolic modeling through a simple mechanism-agnostic implementation of resource-allocation constraints directly at the flux level. By systematically performing single-, two-, and multi-species growth simulations, we show that resource-allocation constraints are indispensable for predicting the structure and function of microbial communities. Our findings call for a scalable workflow for implementing a mechanistic version of resource-allocation constraints to ultimately harness the full potential of community-scale metabolic modeling tools.

Stochastic block models reveal a robust nested pattern in healthy human gut microbiomes.

A key question in human gut microbiome research is what are the robust structural patterns underlying its taxonomic composition. Herein, we use whole metagenomic datasets from healthy human guts to show that such robust patterns do exist, albeit not in the conventional enterotype sense. We first introduce the concept of mixed-membership enterotypes using a network inference approach based on stochastic block models. We find that gut microbiomes across a group of people (hosts) display a nested structure, which has been observed in a number of ecological systems. This finding led us to designate distinct ecological roles to both microbes and hosts: generalists and specialists. Specifically, generalist hosts have microbiomes with most microbial species, while specialist hosts only have generalist microbes. Moreover, specialist microbes are only present in generalist hosts. From the nested structure of microbial taxonomies, we show that these ecological roles of microbes are generally conserved across datasets. Our results show that the taxonomic composition of healthy human gut microbiomes is associated with robustly structured combinations of generalist and specialist species.