Establishment and validation of a risk score model based on EUS: assessment of lymph node metastasis in early gastric cancer.

BACKGROUND AND AIMS: Lymph node metastasis significantly affects the prognosis of early gastric cancer patients. EUS plays a crucial role in the preoperative assessment of early gastric cancer. This study evaluated the efficacy of EUS in identifying lymph node metastasis in early gastric cancer patients and developed a risk score model to aid in choosing the best treatment options. METHODS: We retrospectively analyzed the effectiveness of EUS for detecting lymph node metastasis in early gastric cancer patients. A risk score model for predicting lymph node metastasis preoperatively was created using independent risk factors identified through binary logistic regression analysis and subsequently validated. Receiver operating characteristic curves were generated for both the development and validation cohorts. RESULTS: The overall accuracy of EUS in identifying lymph node metastasis was 85.3%, although its sensitivity (29.2%) and positive predictive value (38.7%) were relatively low. Patients were categorized based on preoperative risk factors for lymph node metastasis, including tumor size of ≥20 mm, lymph nodes of ≥10 mm, body mass index of ≥24 kg/m2, and lymph node metastasis on CT scans. A 7-point risk score model was developed to assess the likelihood of lymph node metastasis. The areas under the receiver operating characteristic curve for the development and validation sets were 0.842 and 0.837, respectively, with sensitivities of 64% and 79%, respectively. CONCLUSIONS: We developed a practical risk score model based on preoperative factors to help EUS predict lymph node metastasis in early gastric cancer patients, guiding the selection of optimal treatment approaches for these patients.

CLEC4D as a Novel Prognostic Marker Boosts the Proliferation and Migration of Gastric Cancer via the NF-κB/AKT Signaling Pathway.

Purpose: The functions of C-type lectin domain family 4 member D (CLEC4D), one member of the C-type lectin/C-type lectin-like domain superfamily, in immunity have been well described, but its roles in cancer biology remain largely unknown. Patients and Methods: This study aims to explore the role of CLEC4D in gastric cancer (GC). Bioinformatics preliminarily analyzed the expression of CLEC4D in gastric cancer. Immunohistochemical staining was used to detect the expression level and clinical pathological characteristics of CLEC4D in gastric cancer. The biological function of CLEC4D in gastric cancer cell lines was verified through in vitro and in vivo experiments. Results: In this study, CLEC4D expression was found to be markedly increased in gastric cancer (GC) tissues compared with matched normal gastric tissues, and high CLEC4D expression independently predicted unfavorable overall survival in patients with GC. Knockdown of CLEC4D markedly inhibited GC cell proliferation and migration. Mechanistically, CLEC4D knockdown deactivated the Akt and NF-κB signaling pathways in GC cells. Conclusion: Together, these results demonstrate that aberrantly increased CLEC4D expression promotes cancer phenotypes via the Akt and NF-κB signaling pathways in GC cells.

Comparison of short­term outcomes and 3-year overall survival between robotic and laparoscopic gastrectomy for gastric cancer: a propensity score matching analysis.

BACKGROUND: Despite the increasing use of robotic gastrectomy (RG) as an alternative to laparoscopic gastrectomy (LG) in treating gastric cancer, controversy remains over the advantages of RG compared to LG and there is a paucity of studies comparing the two techniques regarding patient survival. METHODS: In this retrospective cohort study, 675 patients undergoing minimally invasive gastrectomy were recruited from January 2016 to January 2018 (LG: n = 567; RG: n = 108). A one-to-one propensity score matching (PSM) analysis was applied to minimize the selection bias due to confounding factors, yielding 104 patients in each of the RG and LG groups. After matching, the short-term outcomes and 3-year overall survival were compared in the two groups. RESULTS: The PSM cohort analysis showed a similar 3-year overall survival between RG and LG groups (p = .249). Concerning the short-term outcomes, the RG compared to LG resulted in lower blood loss (p = .01), lower postoperative complications (p = .001), lower postoperative pain (p = .016), earlier initiation of soft diet (p = .011), shorter hospital stay |(p = .012), but higher hospitalization expenses (p = .001). CONCLUSION: Our findings suggest that RG may offer advantages in terms of blood loss, surgical complications, recovery time, and pain management compared to LG while maintaining similar overall survival rates. However, RG is associated with higher hospital costs, potentially limiting its wider adoption. Further research, including large, multi-center randomized controlled trials with longer patient follow-up, particularly for advanced gastric cancer, is needed to confirm these findings.

Macrophage Migration Inhibitory Factor as a Potential Plasma Biomarker of Cognitive Impairment in Cerebral Small Vessel Disease.

As the pathogenesis of cerebral small vessel disease with cognitive impairment (CSVD-CI) remains unclear, identifying effective biomarkers can contribute to the clinical management of CSVD-CI. This study recruited 54 healthy controls (HCs), 60 CSVD-CI patients, and 57 CSVD cognitively normal (CSVD-CN) patients. All participants underwent neuropsychological assessments and multimodal magnetic resonance imaging. Macrophage migration inhibitory factors (MIFs) were assessed in plasma. The least absolute shrinkage and selection operator model was used to determine a composite marker. Compared with HCs or CSVD-CN patients, CSVD-CI patients had significantly increased plasma MIF levels. In CSVD-CI patients, plasma MIF levels were significantly correlated with multiple cognitive assessment scores, plasma levels of blood-brain barrier (BBB)-related indices, white matter hyperintensity Fazekas scores, and the mean amplitude of low-frequency fluctuation in the right superior temporal gyrus. Higher plasma MIF levels were significantly associated with worse global cognition and information processing speed in CSVD-CI patients. The composite marker (including plasma MIF) distinguished CSVD-CI patients from CSVD-CN and HCs with >80% accuracy. Meta-analysis indicated that blood MIF levels were significantly increased in CSVD-CI patients. In conclusion, plasma MIF is a potential biomarker for early identification of CSVD-CI. Plasma MIF may play a role in cognitive decline in CSVD through BBB dysfunction and changes in white matter hyperintensity and brain activity.

Spatially resolved current density distribution in GaN-based flip-chip green mini-LEDs by microscopic hyperspectral imaging and modified two-level modeling.

A modified two-level model is proposed to study the spatially resolved current density distribution of GaN-based green miniaturized light-emitting diodes (mini-LEDs), combining with microscopic hyperspectral imaging. We found that the spatially resolved current density distribution reveals both the radiative and non-radiative recombination mappings, which can also be provided separately by this model. In addition, higher current density is not necessarily correlated with higher photon emission, especially for the regions around the electrode edges, where the high current density suggests current crowding and defect-related non-radiative recombination. The current density distribution of mini-LEDs is further verified by the laser-beam-induced current (LBIC) and the spatially resolved mappings of peak wavelength and FWHM. The modified two-level model also offers radiative/non-radiative mappings and is proved to be beneficial to determine the micro-zone current density distribution and to reveal the intrinsic radiative/non-radiative recombination mechanism of mini-LEDs.

Multifunctional Material Building Blocks from Plant Pollen.

With its multifaceted nature, plant pollen serves not only as a key element in the reproductive cycle of seed plants but also as an influential contributor to environmental, human health, safety, and climate-related concerns. Pollen functions as a carrier of nutrients and organisms and holds a pivotal role in sustaining pollinator populations. Moreover, it is vital in ensuring the safety and quality of our food supply while presenting potential therapeutic applications. Pollen, often referred to as the diamond of the organic world due to its distinctive physical structures and properties, has been underappreciated from a material science and engineering standpoint. We propose adopting a more interdisciplinary and comprehensive approach to its study. Recent groundbreaking research has focused on the development of pollen-based building blocks that transform practically indestructible plant pollen into microgel, paper, and sponge, thereby unveiling numerous potential applications. In this review, we highlight the transformative potential of plant pollen as it is converted into a variety of building blocks, thereby unlocking myriad prospective applications through eco-friendly processing.

ACAT2 suppresses the ubiquitination of YAP1 to enhance the proliferation and metastasis ability of gastric cancer via the upregulation of SETD7.

The contributions of aberrantly expressed metabolic enzymes to gastric cancer (GC) initiation and progression have been widely appreciated in recent years. Acetyl-CoA acetyltransferase 2 (ACAT2) is one member of the acetyl- CoA thiolase family. Previous studies demonstrated that ACAT2 either promotes or suppresses tumor progression in different conditions. However, the function and mechanisms of ACAT2 in GC remain unknown. We found that the expression of this enzyme was significantly increased in GC tissues compared with normal counterparts, which prompted us to further investigate the roles of this protein in GC biology. In vitro functional studies showed that ACAT2 knockdown markedly halted the proliferation and the motility of GC cells; these functions favoring malignant phenotypes of GC cells were further validated in animal experiments. Mechanistically, ACAT2 depletion significantly reduced the transcription of SETD7, which is a histone methyltransferase and plays critical roles in GC cells. We found that the pro-tumoral functions of ACAT2 were largely dependent on SETD7. Moreover, SETD7 decreased the ubiquitination level of Yes-associated protein 1 (YAP1), thereby protecting YAP1 from proteasome degradation. Increased YAP1 protein expression remarkably activated the YAP1/TAZ-TEAD1 signaling pathway, which further boosted the malignant phenotypes in GC cells. In conclusion, these findings highlight the pro-tumoral functions and molecular underpinnings of ACAT2 in GC cells, and suggest that ACAT2 could be a promising target in GC treatment.

Ketohexokinase-A deficiency attenuates the proliferation via reducing ß-catenin in gastric cancer cells.

Overconsumption of fructose is closely related to cancer. Ketohexokinase (KHK) catalyzes the conversion from fructose to fructose-1-phosphate (F1P), which is the first and committed step of fructose metabolism. Recently, aberrant KHK activation has been identified in multiple malignancies. However, the roles of KHK in gastric cancer (GC) cells are largely unclear. Herein, we reveal that the expression of ketohexokinase-A (KHK-A), one alternatively spliced KHK isoform that possesses low affinity for fructose, was markedly increased in GC cells. Depletion of endogenous KHK-A expression using lentiviruses encoding short hairpin RNAs (shRNAs) or pharmaceutical disruption of KHK-A activity using KHK-IN-1 hydrochloride in GC NCI-N87 and HGC-27 cells inhibited the proliferation in vitro and in vivo. Additionally, the mitochondrial respiration in the GC cells with KHK-A deficiency compared with the control cells was significantly impaired. One commercially-available antibody array was used to explore the effects of KHK-A knockdown on signaling pathways, showing that ß-catenin was remarkably reduced in the KHK-A deficient GC cells compared with the control ones. Pharmaceutical reduction in ß-catenin levels slowed down the proliferation of GC cells. These data uncover that KHK-A promotes the proliferation in GC cells, indicating that this enzyme might be a promising therapeutical target for GC treatment.

The Key Role of Tumor Budding in Predicting the Status of Lymph Node Involvement in Early Gastric Cancer Patients: A Clinical Multicenter Validation in China.

BACKGROUND: Accurate preoperative prediction of lymph node (LN) involvement is essential for the management of early gastric cancer (EGC). Our objective was to formulate a potent nomogram for predicting LN involvement in EGC by leveraging an innovative predictor of tumor budding. METHODS: We assembled a cohort of EGC patients who underwent radical surgery at two tertiary cancer centers. Tumor budding was stratified by using an optimal cutoff value and integrated with other clinicopathological variables to ascertain the risk factors associated with LN involvement. A nomogram was developed and its predictive performance was assessed by using receiver operating characteristic (ROC) curves and calibration plots. In addition, we conducted decision curve analysis to evaluate its clinical utility. Finally, an external validation was conducted by using an independent cohort. RESULTS: Finally, 307 eligible patients (215 in the primary cohort and 92 in the validation cohort) were included. Tumor budding, categorized by a count of two, exhibited a robust association with LN involvement (OR 14.12, p = 0.012). Other significant risk factors include lymphovascular invasion, depth of tumor invasion, ulceration, and tumor differentiation. Notably, the nomogram demonstrated exceptional discriminative power (area under the ROC curve, 0.872 in the primary cohort and 0.885 in the validation cohort) and precise predictive capabilities. Furthermore, the nomogram showed notable clinical applicability through decision curve analysis, particularly in endoscopic curability C-2, by mitigating the risk of overtreatment. CONCLUSIONS: Tumor budding is a robust predictor of LN involvement in EGC. The incorporation of tumor budding into a nomogram is an effective strategy, thereby informing and enhancing clinical decision-making.

Association of survival with adjuvant chemotherapy in patients with stage IB gastric cancer: a multicentre, observational, cohort study.

Background: Recurrence following radical resection in patients with stage IB gastric cancer (GC) is not uncommon. However, whether postoperative adjuvant chemotherapy could reduce the risk of recurrence in stage IB GC remains contentious. Methods: We collected data on 2110 consecutive patients with pathologic stage IB (T1N1M0 or T2N0M0) GC who were admitted to 8 hospitals in China from 2009 to 2018. The survival of patients who received adjuvant chemotherapy was compared with that of postoperative observation patients using propensity score matching (PSM). Two survival prediction models were constructed to estimate the predicted net survival gain attributable to adjuvant chemotherapy. Findings: Of the 2110 patients, 1344 received adjuvant chemotherapy and 766 received postoperative observation. Following the 1-to-1 matching, PSM yielded 637 matched pairs. Among matched pairs, adjuvant chemotherapy was not associated with improved survival compared with postoperative observation (OS: hazard ratio [HR], 0.72; 95% CI, 0.52-1.00; DFS: HR, 0.91; 95% CI, 0.64-1.29). Interestingly, in the subgroup analysis, reduced mortality after adjuvant chemotherapy was observed in the subgroups with elevated serum CA19-9 (HR, 0.22; 95% CI, 0.08-0.57; P = 0.001 for multiplicative interaction), positive lymphovascular invasion (HR, 0.32; 95% CI, 0.17-0.62; P < 0.001 for multiplicative interaction), or positive lymph nodes (HR, 0.17; 95% CI, 0.07-0.38; P < 0.001 for multiplicative interaction). The survival prediction models mainly based on variables associated with chemotherapy benefits in the subgroup analysis demonstrated good calibration and discrimination, with relatively high C-indexes. The C-indexes for OS were 0.74 for patients treated with adjuvant chemotherapy and 0.70 for patients treated with postoperative observation. Two nomograms were built from the models that can calculate individualized estimates of expected net survival gain attributable to adjuvant chemotherapy. Interpretation: In this cohort study, pathologic stage IB alone was not associated with survival benefits from adjuvant chemotherapy compared with postoperative observation in patients with early-stage GC. High-risk clinicopathologic features should be considered simultaneously when evaluating patients with stage IB GC for adjuvant chemotherapy. Funding: National Natural Science Foundation of China; the National Key R&D Program of China.

Genome-scale transcriptional activation by non-homologous end joining-mediated integration in Yarrowia lipolytica.

BACKGROUND: Genome-scale screening can be applied to efficiently mine for unknown genes with phenotypes of interest or special functions. It is also useful to identify new targets for engineering desirable properties of cell factories. RESULTS: Here, we designed a new approach for genome-scale transcription activation using non-homologous end joining (NHEJ)-mediated integration in Yarrowia lipolytica. We utilized this approach to screen for genes that, upon activation, confer phenotypes including improved acetic acid tolerance and xylose metabolism. The candidates were validated using gene overexpression, and functional changes including improved growth performance under multiple stressors and activated pentose metabolism were identified. CONCLUSIONS: This study provides a simple and effective approach to randomly activate endogenous genes and mine for key targets associated with phenotypes of interest. The specific gene targets identified here will be useful for cell factory construction and biorefining lignocellulose.

EGLN3 attenuates gastric cancer cell malignant characteristics by inhibiting JMJD8/NF-κB signalling activation independent of hydroxylase activity.

BACKGROUND: The expression of Egl-9 family hypoxia-inducible factor 3 (EGLN3) is notably decreased in various malignancies, including gastric cancer (GC). While the predominant focus has been on the hydroxylase activity of EGLN3 for its antitumour effects, recent findings have suggested nonenzymatic roles for EGLN3. METHODS: This study assessed the clinical significance of EGLN3 expression in GC and explored the connection between EGLN3 DNA promoter methylation and transcriptional silencing. To investigate the effect of EGLN3 on GC cells, a gain-of-function strategy was adopted. RNA sequencing was conducted to identify the key effector molecules and signalling pathways associated with EGLN3. RESULTS: EGLN3 expression was significantly reduced in GC tissues, correlating with poorer patient prognosis. EGLN3 hypermethylation disrupts transcriptional equilibrium, contributing to deeper tumour invasion and lymph node metastasis, thus exacerbating GC progression. Conversely, restoration of EGLN3 expression in GC cells substantially inhibited cell proliferation and metastasis. EGLN3 was also found to impede the malignant progression of GC cells by downregulating Jumonji C domain-containing protein 8-mediated activation of the NF-κB pathway, independent of its hydroxylase activity. CONCLUSIONS: EGLN3 has the potential to hinder the spread of GC cells through a nonenzymatic mechanism, thereby shedding light on the complex nature of GC progression.

Deep learning-based radiomics model can predict extranodal soft tissue metastasis in gastric cancer.

BACKGROUND: The potential prognostic value of extranodal soft tissue metastasis (ESTM) has been confirmed by increasing studies about gastric cancer (GC). However, the gold standard of ESTM is determined by pathologic examination after surgery, and there are no preoperative methods for assessment of ESTM yet. PURPOSE: This multicenter study aimed to develop a deep learning-based radiomics model to preoperatively identify ESTM and evaluate its prognostic value. METHODS: A total of 959 GC patients were enrolled from two centers and split into a training cohort (N = 551) and a test cohort (N = 236) for ESTM evaluation. Additionally, an external survival cohort (N = 172) was included for prognostic analysis. Four models were established based on clinical characteristics and multiphase computed tomography (CT) images for preoperative identification of ESTM, including a deep learning model, a hand-crafted radiomic model, a clinical model, and a combined model. C-index, decision curve, and calibration curve were utilized to assess the model performances. Survival analysis was conducted to explore the ability of stratifying overall survival (OS). RESULTS: The combined model showed good discrimination of the ESTM [C-indices (95% confidence interval, CI): 0.770 (0.729-0.812) and 0.761 (0.718-0.805) in training and test cohorts respectively], which outperformed deep learning model, radiomics model, and clinical model. The stratified analysis showed this model was not affected by patient's tumor size, the presence of lymphovascular invasion, and Lauren classification (p < 0.05). Moreover, the model score showed strong consistency with the OS [C-indices (95%CI): 0.723 (0.658-0.789, p < 0.0001) in the internal survival cohort and 0.715 (0.650-0.779, p < 0.0001) in the external survival cohort]. More interestingly, univariate analysis showed the model score was significantly associated with occult distant metastasis (p < 0.05) that was missed by preoperative diagnosis. CONCLUSIONS: The model combining CT images and clinical characteristics had an impressive predictive ability of both ESTM and prognosis, which has the potential to serve as an effective complement to the preoperative TNM staging system.

Reconfiguration of the reductive TCA cycle enables high-level succinic acid production by Yarrowia lipolytica.

Succinic acid (SA) is an important C4-dicarboxylic acid. Microbial production of SA at low pH results in low purification costs and hence good overall process economics. However, redox imbalances limited SA biosynthesis from glucose via the reductive tricarboxylic acid (TCA) cycle in yeast. Here, we engineer the strictly aerobic yeast Yarrowia lipolytica for efficient SA production without pH control. Introduction of the reductive TCA cycle into the cytosol of a succinate dehydrogenase-disrupted yeast strain causes arrested cell growth. Although adaptive laboratory evolution restores cell growth, limited NADH supply restricts SA production. Reconfiguration of the reductive SA biosynthesis pathway in the mitochondria through coupling the oxidative and reductive TCA cycle for NADH regeneration results in improved SA production. In pilot-scale fermentation, the engineered strain produces 111.9 g/L SA with a yield of 0.79 g/g glucose within 62 h. This study paves the way for industrial production of biobased SA.

Construction and testing of a risk prediction classifier for cardia carcinoma.

OBJECTIVES: This research aimed to construct a prediction model for stages II and III cardia carcinoma (CC), and provide an effective preoperative evaluation tool for clinicians. METHODS: CC mRNA expression matrix was obtained from Gene Expression Omnibus and The Cancer Genome Atlas databases. Non-negative matrix factorization was used to cluster data to obtain subgroup information, and weighted gene co-expression network analysis was used to uncover key modules linked to different subgroups. Gene-set enrichment analysis analyzed biological pathways of different subgroups. The related pathways of multiple modules were scrutinized with Kyoto Encyclopedia of Genes and Genomes. Key modules were manually annotated to screen CC-related genes. Subsequently, quantitative real-time polymerase chain reaction assessed CC-related gene expression in fresh tissues and paraffin samples, and Pearson correlation analysis was performed. A classification model was constructed and the predictive ability was evaluated by the receiver operating characteristic curve. RESULTS: CC patients had four subgroups that were associated with brown, turquoise, red, and black modules, respectively. The CC-related modules were mainly associated with abnormal cell metabolism and inflammatory immune pathways. Then, 76 CC-elated genes were identified. Pearson correlation analysis presented that THBS4, COL14A1, DPYSL3, FGF7, and SVIL levels were relatively stable in fresh and paraffin tissues. The area under the curve of 5-gene combined prediction for staging was 0.8571, indicating good prediction ability. CONCLUSIONS: The staging classifier for CC based on THBS4, COL14A1, DPYSL3, FGF7, and SVIL has a good predictive effect, which may provide effective guidance for whether CC patients need emergency surgery.

Potential Association of Neutrophil Extracellular Traps With Cognitive Impairment in Cerebral Small Vessel Disease.

No acceptable biomarker can facilitate the early identification of cognitive impairment associated with cerebral small vessel disease (CSVD) in the older persons. The neutrophil extracellular traps (NETs) in the inflammation response of circulatory and central systems are essential in destroying the blood-brain barrier. The present study aims to explore the potential associations of plasma NETs with cognitive performance in CSVD. We recruited 146 CSVD patients and 66 healthy controls (HCs), and comprehensive neuropsychological assessments and multimodal magnetic resonance imaging were conducted. Three NETs markers, namely citrullination of histone H3, neutrophil elastase-DNA, and myeloperoxidase (MPO)-DNA, and 4 oxidative stress-related indexes in plasma samples, were measured. The plasma levels of 3 NETs markers were more significantly elevated in CSVD patients than in HCs. Significant correlations of the 3 NETs markers were observed with multiple cognitive domain scores. Furthermore, higher plasma malondialdehyde and NETs levels were significantly associated with the worse Montreal Cognitive Assessment scores among CSVD patients. Moreover, plasma MPO-DNA levels significantly mediated the effect of the amplitude of low-frequency fluctuation value within the bilateral caudate and the scores of global cognitive function, executive function, and information processing speed. Additionally, a panel of 3 NETs markers had the highest area under the curve value to distinguish the cognitively impaired CSVD patients from HCs and nonimpaired ones. Therefore, plasma NETs may be potential biomarkers for early diagnosis of CSVD-related cognitive impairment. Activated lipid peroxidation in circulation and impaired caudate function support potential associations of plasma NETs in cognitively impaired CSVD patients.

Imaging lymph node regression can predict the pathological tumor regression grade in gastric cancer after neoadjuvant treatment.

BACKGROUND: Neoadjuvant chemotherapy has become the standard treatment for locally advanced gastric cancer. The tumor regression grade system is an effective and widely used tool for the evaluation of treatment response to neoadjuvant chemotherapy. However, whether tumor regression grade could be predicted using clinical characteristics is uncertain. METHODS: A total of 287 locally advanced gastric cancer patients from 2014 to 2021 were retrospectively included. According to the College of American Pathologists' tumor regression grade system, patients were classified into response group (tumor regression grade 0-1) and non-response group (tumor regression grade 2-3). Associations between clinical characteristics and neoadjuvant chemotherapy response were performed by the logistic regression model. The Kaplan-Meier method was used to estimate the survival. A prediction scoring system was constructed based on the ß coefficients of multivariate analysis. The receiver operating characteristic curve and decision curve analysis were used to evaluate the performance of the predictive scoring system. RESULTS: Survival analysis showed that patients with tumor regression grades 0 to 1 had significantly better disease-free survival and overall survival than the tumor regression grades 2 to 3. Tumor differentiation, ycT stage, immunotherapy, and lymph node regression were independent predictors of pathological response to neoadjuvant chemotherapy. We further developed a scoring system to predict the tumor regression grade. The receiver operating characteristic and decision curve analysis showed good predictive performance of the scoring system. CONCLUSION: Lymph node regression could be used as a predictor for pathological response. We developed a scoring system to predict the treatment response of patients with gastric cancer receiving neoadjuvant chemotherapy. The scoring system based on the predictors could provide guidance for making clinical decisions.

Alteration and clinical potential in gut microbiota in patients with cerebral small vessel disease.

Background: Cerebral small vessel disease (CSVD) is a cluster of microvascular disorders with unclear pathological mechanisms. The microbiota-gut-brain axis is an essential regulatory mechanism between gut microbes and their host. Therefore, the compositional and functional gut microbiota alterations lead to cerebrovascular disease pathogenesis. The current study aims to determine the alteration and clinical value of the gut microbiota in CSVD patients. Methods: Sixty-four CSVD patients and 18 matched healthy controls (HCs) were included in our study. All the participants underwent neuropsychological tests, and the multi-modal magnetic resonance imaging depicted the changes in brain structure and function. Plasma samples were collected, and the fecal samples were analyzed with 16S rRNA gene sequencing. Results: Based on the alpha diversity analysis, the CSVD group had significantly decreased Shannon and enhanced Simpson compared to the HC group. At the genus level, there was a significant increase in the relative abundances of Parasutterella, Anaeroglobus, Megasphaera, Akkermansia, Collinsella, and Veillonella in the CSVD group. Moreover, these genera with significant differences in CSVD patients revealed significant correlations with cognitive assessments, plasma levels of the blood-brain barrier-/inflammation-related indexes, and structural/functional magnetic resonance imaging changes. Functional prediction demonstrated that lipoic acid metabolism was significantly higher in CSVD patients than HCs. Additionally, a composite biomarker depending on six gut microbiota at the genus level displayed an area under the curve of 0.834 to distinguish CSVD patients from HCs using the least absolute shrinkage and selection operator (LASSO) algorithm. Conclusion: The evident changes in gut microbiota composition in CSVD patients were correlated with clinical features and pathological changes of CSVD. Combining these gut microbiota using the LASSO algorithm helped identify CSVD accurately.