PCDHA9 as a candidate gene for amyotrophic lateral sclerosis.

Amyotrophic lateral sclerosis (ALS) is a devastating neurodegenerative disease. To identify additional genetic factors, we analyzed exome sequences in a large cohort of Chinese ALS patients and found a homozygous variant (p.L700P) in PCDHA9 in three unrelated patients. We generated Pcdhα9 mutant mice harboring either orthologous point mutation or deletion mutation. These mice develop progressive spinal motor loss, muscle atrophy, and structural/functional abnormalities of the neuromuscular junction, leading to paralysis and early lethality. TDP-43 pathology is detected in the spinal motor neurons of aged mutant mice. Mechanistically, we demonstrate that Pcdha9 mutation causes aberrant activation of FAK and PYK2 in aging spinal cord, and dramatically reduced NKA-α1 expression in motor neurons. Our single nucleus multi-omics analysis reveals disturbed signaling involved in cell adhesion, ion transport, synapse organization, and neuronal survival in aged mutant mice. Together, our results present PCDHA9 as a potential ALS gene and provide insights into its pathogenesis.

Accurate and interpretable drug-drug interaction prediction enabled by knowledge subgraph learning.

BACKGROUND: Discovering potential drug-drug interactions (DDIs) is a long-standing challenge in clinical treatments and drug developments. Recently, deep learning techniques have been developed for DDI prediction. However, they generally require a huge number of samples, while known DDIs are rare. METHODS: In this work, we present KnowDDI, a graph neural network-based method that addresses the above challenge. KnowDDI enhances drug representations by adaptively leveraging rich neighborhood information from large biomedical knowledge graphs. Then, it learns a knowledge subgraph for each drug-pair to interpret the predicted DDI, where each of the edges is associated with a connection strength indicating the importance of a known DDI or resembling strength between a drug-pair whose connection is unknown. Thus, the lack of DDIs is implicitly compensated by the enriched drug representations and propagated drug similarities. RESULTS: Here we show the evaluation results of KnowDDI on two benchmark DDI datasets. Results show that KnowDDI obtains the state-of-the-art prediction performance with better interpretability. We also find that KnowDDI suffers less than existing works given a sparser knowledge graph. This indicates that the propagated drug similarities play a more important role in compensating for the lack of DDIs when the drug representations are less enriched. CONCLUSIONS: KnowDDI nicely combines the efficiency of deep learning techniques and the rich prior knowledge in biomedical knowledge graphs. As an original open-source tool, KnowDDI can help detect possible interactions in a broad range of relevant interaction prediction tasks, such as protein-protein interactions, drug-target interactions and disease-gene interactions, eventually promoting the development of biomedicine and healthcare.

Understanding how drugs interact is crucial for safe healthcare and the development of new medicines. We developed a computational tool that can analyze the data about medicines within large medical databases and predict the impact of being treated by multiple drugs at the same time on the person taking the drugs. Our tool, named KnowDDI, can predict which drugs interact with each other and also provide an explanation for why the interaction is likely to take place. We demonstrated that our tool can identify known drug interactions. It could potentially be used in the future to identify previously unknown or unanticipated interactions that could have negative consequences to people being treated with unusual combinations of medicines.

Mea6/cTAGE5 cooperates with TRAPPC12 to regulate PTN secretion and white matter development.

Mutations of TRAPPC12 are associated with progressive childhood encephalopathy including abnormal white matter. However, the underlying pathogenesis is still unclear. Here, we found that Trappc12 deficiency in CG4 and oligodendrocyte progenitor cells (OPCs) affects their differentiation and maturation. In addition, TRAPPC12 interacts with Mea6/cTAGE5, and Mea6/cTAGE5 ablation in OPCs affects their proliferation and differentiation, leading to marked hypomyelination, compromised synaptic functionality, and aberrant behaviors in mice. We reveal that TRAPPC12 is associated with COPII components at ER exit site, and Mea6/cTAGE5 cKO disrupts the trafficking pathway by affecting the distribution and/or expression of TRAPPC12, SEC13, SEC31A, and SAR1. Moreover, we observed marked disturbances in the secretion of pleiotrophin (PTN) in Mea6-deficient OPCs. Notably, exogenous PTN supplementation ameliorated the differentiation deficits of these OPCs. Collectively, our findings indicate that the association between TRAPPC12 and MEA6 is important for cargo trafficking and white matter development.

The Causal Associations between Adipokines and Alzheimer's Disease: A Two-Sample Mendelian Randomization Study.

Background: Observational studies have indicated the association of alteration of adipokines with Alzheimer's disease (AD). However, it remains unclear whether the associations are causal. Objective: To determine the causal associations between adipokines and AD. Methods: A Mendelian randomization (MR) method was applied to investigate the causal relationships of adipokines, including adiponectin and resistin, with risk of AD. Genetic proxies from genome-wide association studies (GWAS) of adiponectin and resistin were selected as instrumental variables. GWAS summary statistics for AD were extracted as outcome. Results: In this study, we found evidence of the causal effects of adiponectin on AD (OR: 0.850, 95% CI: 0.731-0.990, p = 0.037). However, no relationship between resistin and AD (OR: 0.936, 95% CI: 0.851-1.029, p = 0.171) was detected. In the reverse causation analysis, null associations of AD were found for adiponectin and resistin (all p > 0.05). Conclusions: This study provides evidence of causality between adiponectin and risk of AD. However, no genetic susceptibility of resistin was discovered for AD.

Property-Aware Relation Networks for Few-Shot Molecular Property Prediction.

Molecular property prediction plays a fundamental role in AI-aided drug discovery to identify candidate molecules, which is also essentially a few-shot problem due to lack of labeled data. In this paper, we propose Property-Aware Relation networks (PAR) to handle this problem. We first introduce a property-aware molecular encoder to transform the generic molecular embeddings to property-aware ones. Then, we design a query-dependent relation graph learning module to estimate molecular relation graph and refine molecular embeddings w.r.t. the target property. Thus, the facts that both property-related information and relationships among molecules change across different properties are utilized to better learn and propagate molecular embeddings. Generally, PAR can be regarded as a combination of metric-based and optimization-based few-shot learning method. We further extend PAR to Transferable PAR (T-PAR) to handle the distribution shift, which is common in drug discovery. The keys are joint sampling and relation graph learning schemes, which simultaneously learn molecular embeddings from both source and target domains. Extensive results on benchmark datasets show that PAR and T-PAR consistently outperform existing methods on few-shot and transferable few-shot molecular property prediction tasks, respectively. Besides, ablation and case studies are conducted to validate the rationality of our designs in PAR and T-PAR.

Induced formation of primordial germ cells from zebrafish blastomeres by germplasm factors.

The combination of genome editing and primordial germ cell (PGC) transplantation has enormous significance in the study of developmental biology and genetic breeding, despite its low efficiency due to limited number of donor PGCs. Here, we employ a combination of germplasm factors to convert blastoderm cells into induced PGCs (iPGCs) in zebrafish and obtain functional gametes either through iPGC transplantation or via the single blastomere overexpression of germplasm factors. Zebrafish-derived germplasm factors convert blastula cells of Gobiocypris rarus into iPGCs, and Gobiocypris rarus spermatozoa can be produced by iPGC-transplanted zebrafish. Moreover, the combination of genome knock-in and iPGC transplantation perfectly resolves the contradiction between high knock-in efficiency and early lethality during embryonic stages and greatly improves the efficiency of genome knock-in. Together, we present an efficient method for generating PGCs in a teleost, a technique that will have a strong impact in basic research and aquaculture.

Advances in Microfluidic Technologies in Organoid Research.

Organoids have emerged as major technological breakthroughs and novel organ models that have revolutionized biomedical research by recapitulating the key structural and functional complexities of their in vivo counterparts. The combination of organoid systems and microfluidic technologies has opened new frontiers in organoid engineering and offers great opportunities to address the current challenges of existing organoid systems and broaden their biomedical applications. In this review, the key features of the existing organoids, including their origins, development, design principles, and limitations, are described. Then the recent progress in integrating organoids into microfluidic systems is highlighted, involving microarrays for high-throughput organoid manipulation, microreactors for organoid hydrogel scaffold fabrication, and microfluidic chips for functional organoid culture. The opportunities in the nascent combination of organoids and microfluidics that lie ahead to accelerate research in organ development, disease studies, drug screening, and regenerative medicine are also discussed. Finally, the challenges and future perspectives in the development of advanced microfluidic platforms and modified technologies for building organoids with higher fidelity and standardization are envisioned.

The effect of a methylxanthine vasodilator: pentoxifylline on the treatment of diabetic nephropathy-a meta-analysis.

This meta-analysis aimed to comprehensively evaluate the efficacy and safety of pentoxifylline (PTF) in the treatment of diabetic nephropathy (DN) and to offer fresh perspectives and evidence-based references for this condition. Meta-analysis. Relevant randomized controlled trials (RCTs) were searched from PubMed, Embase, Cochrane Library, China Knowledge Network (CNKI), Wanfang, and China Biomedical Literature Database. All trials were screened for compliance with the inclusion and exclusion criteria, and relevant data were extracted after quality evaluation. Eighteen studies with a total of 1280 patients were finally included. Compared to the control group, high sensitivity C-reactive protein (hsCRP) was improved (MD = - 0.23. 95% CI = [- 0.41, - 0.05], P = 0.01); urinary albumin excretion (UAE) rate was reduced (MD = - 16.50, 95% CI = [- 18.87, - 14.13], P<0.00001); the change of serum creatinine (Scr) from baseline was reduced (MD = - 0.05, 95%CI = [- 0.08, - 0.01], P = 0.009); fasting plasma glucose (FPG) was decreased (MD = - 5.66, 95% CI = [- 9.79, - 1.53], P = 0.007); and the improvement of glomerular filtration rate (eGFR) from baseline was increased (MD = 4.38, 95% CI = [3.28, 5.48], P<0.00001) in the treatment group. No significant difference was observed between the two groups concerning systolic blood pressure, diastolic blood pressure, total cholesterol, and triglycerides. And in terms of safety, the use of PTF was relatively safe with some self-limiting adverse events. FPG was decreased by PTF more effectively, but there was no effect of PTF on glycated hemoglobin (HbA1c). PTF could improve hsCRP, decrease UAE and Scr, and raise eGFR in the treatment of DN.

Scaling up stem cell production: harnessing the potential of microfluidic devices.

Stem cells are specialised cells characterised by their unique ability to both self-renew and transform into a wide array of specialised cell types. The widespread interest in stem cells for regenerative medicine and cultivated meat has led to a significant demand for these cells in both research and practical applications. Despite the growing need for stem cell manufacturing, the industry faces significant obstacles, including high costs for equipment and maintenance, complicated operation, and low product quality and yield. Microfluidic technology presents a promising solution to the abovementioned challenges. As an innovative approach for manipulating liquids and cells within microchannels, microfluidics offers a plethora of advantages at an industrial scale. These benefits encompass low setup costs, ease of operation and multiplexing, minimal energy consumption, and the added advantage of being labour-free. This review presents a thorough examination of the prominent microfluidic technologies employed in stem cell research and explores their promising applications in the burgeoning stem cell industry. It thoroughly examines how microfluidics can enhance cell harvesting from tissue samples, facilitate mixing and cryopreservation, streamline microcarrier production, and efficiently conduct cell separation, purification, washing, and final cell formulation post-culture.

Knowledge Mapping of Macrophage in Spinal Cord Injury: A Bibliometric Analysis.

BACKGROUND: Spinal cord injury (SCI) is a devastating condition, often leading to significant disability and impairment. As crucial immune cells, macrophages play a critical role in the pathophysiology of SCI. Understanding the current state of knowledge and research trends related to macrophages in SCI is crucial for developing effective therapeutic interventions. METHODS: Using search strategies, we retrieved relevant articles from the Web of Science Core Collection (WOSCC), resulting in a robust dataset for analysis. VOSviewer, Citespace, and PRISM were employed for analysis and visualization. Various bibliometric indicators, including publication trends, citation analysis, co-authorship networks, and keyword analysis, were utilized to assess the scholarly landscape of macrophage research in SCI. RESULTS: Our findings revealed a steady increase in publications over the past 33 years, indicating a growing interest in this field. We identified Popovich Phillip G was the most influential author, Ohio State University was the most influential institution, and identification of 2 distinct macrophage subsets with divergent effects causing either neurotoxicity or regeneration in the injured mouse spinal cord was the most influential paper in this field. CONCLUSIONS: This bibliometric analysis provides a comprehensive overview of the current knowledge landscape and research trends regarding macrophages in SCI. Neuroinflammation and macrophage polarization, transplation and molecular mechanism were emerging research areas and novel directions. Our study serves as a valuable resource for researchers in spinal cord injury research and therapeutic development.

Water flow promoted charge separation in piezoelectric Bi4Ti3O12 for the enhanced photocatalytic degradation of antibiotic.

Addressing the issue of antibiotic residues in the environment is key to improving the quality of aquatic environments and reducing human health risks. In this study, piezoelectric bismuth titanate (Bi4Ti3O12) nanosheets are synthesized and employed to conduct antibiotic degradation. The piezoelectric potential induced by the water flow shear force is utilized to facilitate charge separation and migration in the photocatalytic process and enhance the catalytic degradation of antibiotic wastewater. As a result, 85% of tetracycline hydrochloride (TC) is degraded within 90 min. The piezo-photocatalytic process exhibits a 2.4 times faster reaction rate and a 15% higher mineralization rate than photocatalysis. Different environmental factors are investigated for their effects on the catalytic activity in piezo-photocatalysis. In situ electrochemical measurement and photoluminescence (PL) spectroscopy under stress demonstrated that the piezoelectric potential shifted the energy band of Bi4Ti3O12 and promoted the charge migration and separation, which produce more active species that favor the efficient catalytic degradation. Finally, the intermediate products of the tetracycline hydrochloride degradation process are analyzed and possible degradation pathways are suggested. This study elucidates the degradation mechanism of Bi4Ti3O12 as a piezo-photocatalyst for antibiotic pollutants, and meticulously investigates the charge transfer mechanism of the catalyst material in response to micro-stress. Hence, it provides an efficient solution for organic wastewater treatment and can potentially provide theoretical support for the development and performance optimization of catalyst materials applied in natural environments.

Relationship between ferroptosis and mitophagy in renal fibrosis: a systematic review.

Renal fibrosis, characterised by glomerulosclerosis and tubulointerstitial fibrosis, is a typical pathological alteration in the progression of chronic kidney disease (CKD) to end-stage renal disease (ESRD). However, the limited and expensive options for treating renal fibrosis place a heavy financial burden on patients and healthcare systems. Therefore, it is significant to find an effective treatment for renal fibrosis. Ferroptosis, a non-traditional form of cell death, has been found to play an important role in acute kidney injury (AKI), tumours, neurodegenerative diseases, and so on. Moreover, a growing body of research suggests that ferroptosis might be a potential target of renal fibrosis. Meanwhile, mitophagy is a type of selective autophagy that can selectively degrade damaged or dysfunctional mitochondria as a form of mitochondrial quality control, reducing the production of reactive oxygen species (ROS), the accumulation of which is the main cause of renal fibrosis. Additionally, as a receptor of mitophagy, NIX can release beclin1 to induce mitophagy, which can also bind to solute carrier family 7 member 11 (SLC7A11) to block the activity of cystine/glutamate antitransporter (system Xc-) and inhibit ferroptosis, thereby suggesting a link between mitophagy and ferroptosis. However, there have been only limited studies on the relationship among mitophagy, ferroptosis and renal fibrosis. In this paper, we review the mechanisms of mitophagy, and describe how ferroptosis and mitophagy are related to renal fibrosis in an effort to identify potential novel targets for the treatment of renal fibrosis.

Effects of Preoperative High-Intensity Interval Training Combined With Team Empowerment Education in Lung Cancer Patients With Surgery: A Quasi-experimental Trial.

BACKGROUND: Cancer itself and surgery put a heavy burden on lung cancer patients, physiologically and psychologically. Enhancing self-efficacy during high-intensity interval training is essential for achieving the full benefit of pulmonary rehabilitation in lung cancer patients. OBJECTIVE: This study aimed to explore the effects of high-intensity interval training combined with team empowerment education on patients with lung resection. METHODS: This is a quasi-experimental trial with a pretest-posttest design. Participants were assigned to one of the 3 groups according to the order of admission: (1) combined intervention group, (2) intervention group, or (3) routine care group. The outcome measures included dyspnea, exercise capacity, exercise self-efficacy, anxiety, depression, postoperative indwelling time of thoracic drainage tube, and total in-hospital stay. RESULTS: Per-protocol results showed that dyspnea, exercise capacity, exercise self-efficacy, anxiety, and depression of the patients in the combined intervention group were significantly improved. However, no significant difference was observed in postoperative indwelling time of thoracic drainage tube or total in-hospital stay among the 3 groups. CONCLUSION: This hospital-based short-term high-intensity interval training combined with team empowerment education for lung cancer patients undergoing surgery was safe and feasible, indicating this program can be a promising strategy to manage perioperative symptoms. IMPLICATIONS FOR PRACTICE: This study provides evidence supporting preoperative high-intensity interval training as a promising method to make the best use of preoperative time, thus improving adverse symptoms in lung cancer patients undergoing surgery, and also provides a new strategy to raise exercise self-efficacy and promote patients' rehabilitation.

Multidisciplinary molecular consultation increases the diagnosis of pediatric epileptic encephalopathy and neurodevelopmental disorders.

BACKGROUND: Epilepsy (EP) is a common neurological disease in which 70-80% are thought to have a genetic cause. In patients with epilepsy, neurodevelopmental delay (NDD) was prevalent. Next generation of sequencing has been widely used in diagnosing EP/NDD. However, the diagnostic yield remains to be 40%-50%. Many reanalysis pipelines and software have been developed for automated reanalysis and decision making for the diseases. Nevertheless, it is a highly challenging task for smaller genetic centers or a routine pediatric practice. To address the clinical and genetic "diagnostic odyssey," we organized a Multidisciplinary Molecular Consultation (MMC) team for molecular consultation for 202 children with EP/NDD patients referred by lower level hospitals. METHODS: All the patients had undergone an aligned and sequential consultations and discussions by a "triple reanalysis" procedure by clinical, genetic specialists, and researchers. RESULTS: Among the 202 cases for MMC, we totally identified 47 cases (23%) harboring causative variants in 24 genes and 15 chromosomal regions after the MMC. In the 15 cases with positive CNVs, 3 cases harbor the deletions or duplications in 16p11.2, and 2 cases for 1p36. The bioinformatical reanalysis revealed 47 positive cases, in which 12 (26%) were reported to be negative, VUS or incorrectly positive in pre-MMC reports. Additionally, among 87 cases with negative cases, 4 (5%) were reported to be positive in pre-MMC reports. CONCLUSION: We established a workflow allowing for a "one-stop" collaborative assessments by experts of multiple fields and helps for correct the diagnosis of cases with falsenegative and -positive and VUS genetic reports and may have significant influences for intervention, prevention and genetic counseling of pediatric epilepsy and neurodevelopmental disorders.

Understanding the cometabolic degradation of sulfadiazine by an enriched ammonia oxidizing bacteria culture from both extracellular and intracellular perspectives.

Antibiotics are widely used drugs in the world and pose serious threats to ecosystems and human health. Although it has been reported that ammonia oxidizing bacteria (AOB) can cometabolize antibiotics, little has been reported on how AOB would respond to the exposure of antibiotics on extracellular and enzymatic levels, as well as the impact of antibiotics on the bioactivity of AOB. Therefore, in this study, a typical antibiotic, sulfadiazine (SDZ), was selected, and a series short-term batch tests using enriched AOB sludge were conducted to investigate the intracellular and extracellular responses of AOB along the cometabolic degradation process of SDZ. The results showed the cometabolic degradation of AOB made the main contribution to SDZ removal. When the enriched AOB sludge was exposed to SDZ, ammonium oxidation rate, ammonia monooxygenase activity, adenosine triphosphate concentration and dehydrogenases activity were negatively affected. The amoA gene abundance increased 1.5 folds within 24 h, which may enhance the uptake and utilization of substrates and maintain stable metabolic activity. In the tests with and without ammonium, the concentration of total EPS increased from 264.9 to 231.1 mg/gVSS to 607.7 and 538.2 mg/gVSS, respectively, under the exposure to SDZ, which was mainly contributed by the increase of proteins in tightly bound extracellular polymeric substances (EPS) and polysacharides in tightly bound EPS and soluble microbial products. The proportion of tryptophan-like protein and humic acid-like organics in EPS also increased. Moreover, SDZ stress stimulated the secretion of three quorum sensing signal molecules, C4-HSL (from 140.3 to 164.9 ng/L), 3OC6-HSL (from 17.8 to 42.4 ng/L) and C8-HSL (from 35.8 to 95.9 ng/L) in the enriched AOB sludge. Among them, C8-HSL may be a key signal molecule that promoted the secretion of EPS. The findings of this study could shed more light on the cometabolic degradation of antibiotics by AOB.

Global trends and focuses of GLP-1RA in renal disease: a bibliometric analysis and visualization from 2005 to 2022.

Glucagon-like peptide 1 receptor agonist (GLP-1RA) is a new class of glucose-lowing agents with the kidney benefit effect. This paper aims at finding the current state and hotspots of the research on GLP-1RA in kidney disease by using bibliometric methodologies and visualization maps to analyze publications and provide the direction for future studies on that topic. Literature information was obtained by retrieving the WoSCC database. Then, software like Microsoft Excel, VOSviewer, and CiteSpace was used to analyze and process obtained data. Bibliometric analysis and visualization of nations, authors, organizations, journals, keywords, and references were also done by VOSviewer and CiteSpace. A total of 991 publications written by 4747 authors from 1637 organizations in 75 countries on GLP-1RA in renal disease in Web of Science Core Collection were retrieved. The number of publications and citations kept growing from 2015 to 2022. The USA, Univ Copenhagen, and Rossing Peter are the leading country, organization, and author on this topic, respectively. All literature was published in 346 journals, and DIABETES OBESITY & METABOLISM is the journal with the most contributions. Meanwhile, most references are from DIABETES CARE. "Cardiovascular outcome" is the most frequent keyword in the total publications, and the reference cited most times is "Liraglutide and Cardiovascular Outcomes in Type 2 Diabetes" by Marso SP. The topic of GLP-1RA in renal disease has attracted more and more attention all over the world. Existing studies are mainly about clinical use in patients with diabetes, and studies on the mechanism are lacking.

Blood-brain barrier injury and neuroinflammation induced by SARS-CoV-2 in a lung-brain microphysiological system.

In some patients, COVID-19 can trigger neurological symptoms with unclear pathogenesis. Here we describe a microphysiological system integrating alveolus and blood-brain barrier (BBB) tissue chips that recapitulates neuropathogenesis associated with infection by SARS-CoV-2. Direct exposure of the BBB chip to SARS-CoV-2 caused mild changes to the BBB, and infusion of medium from the infected alveolus chip led to more severe injuries on the BBB chip, including endothelial dysfunction, pericyte detachment and neuroinflammation. Transcriptomic analyses indicated downregulated expression of the actin cytoskeleton in brain endothelium and upregulated expression of inflammatory genes in glial cells. We also observed early cerebral microvascular damage following lung infection with a low viral load in the brains of transgenic mice expressing human angiotensin-converting enzyme 2. Our findings suggest that systemic inflammation is probably contributing to neuropathogenesis following SARS-CoV-2 infection, and that direct viral neural invasion might not be a prerequisite for this neuropathogenesis. Lung-brain microphysiological systems should aid the further understanding of the systemic effects and neurological complications of viral infection.

Cylindrin from Imperata cylindrica inhibits M2 macrophage formation and attenuates renal fibrosis by downregulating the LXR-α/PI3K/AKT pathway.

Imperata cylindrica, a medicinal plant used in Traditional Chinese Medicine, has been used to treat chronic kidney disease. Extracts of I. cylindrica display anti-inflammatory, immunomodulatory, and anti-fibrotic properties. However, the active components of the extracts and their protective mechanisms have not been fully elucidated. In this study, we explored the ability of cylindrin, the main active compound extracted from I. cylindrica, to protect against renal fibrosis and to investigate the potential mechanisms involved. At high doses, cylindrin exerted protective effects against folic acid-induced kidney fibrosis in mice. Bioinformatic analysis predicted the LXR-α/PI3K/AKT pathway as a target of regulation by cylindrin. This was supported by our in vitro and in vivo results showing that cylindrin significantly downregulated the expression of LXR-α and phosphorylated PI3K/AKT in M2 macrophages and mouse renal tissues. Furthermore, high-dose cylindrin inhibited M2 polarization of IL-4-stimulated macrophages in vitro. Our results suggest that cylindrin alleviates renal fibrosis by attenuating M2 macrophage polarization through inhibition of the PI3K/AKT pathway via downregulation of LXR-α.

Identification and validation of metabolism-related genes signature and immune infiltration landscape of rheumatoid arthritis based on machine learning.

Rheumatoid arthritis (RA) causes irreversible joint damage, but the pathogenesis is unknown. Therefore, it is crucial to identify diagnostic biomarkers of RA metabolism-related genes (MRGs). This study obtained transcriptome data from healthy individuals (HC) and RA patients from the GEO database. Weighted gene correlation network analysis (WGCNA), the least absolute shrinkage and selection operator (LASSO), and random forest (RF) algorithms were adopted to identify the diagnostic feature biomarker for RA. In addition, biomarkers were verified by qRT-PCR and Western blot analysis. We established a mouse model of collagen-induced arthritis (CIA), which was confirmed by HE staining and bone structure micro-CT analysis, and then further verified the biomarkers by immunofluorescence. In vitro NMR analysis was used to analyze and identify possible metabolites. The correlation of diagnostic feature biomarkers and immune cells was performed using the Spearman-rank correlation algorithm. In this study, a total of 434 DE-MRGs were identified. GO and KEGG enrichment analysis indicated that the DE-MRGs were significantly enriched in small molecules, catabolic process, purine metabolism, carbon metabolism, and inositol phosphate metabolism. AKR1C3, MCEE, POLE4, and PFKM were identified through WGCNA, LASSO, and RF algorithms. The nomogram result should have a significant diagnostic capacity of four biomarkers in RA. Immune infiltration landscape analysis revealed a significant difference in immune cells between HC and RA groups. Our findings suggest that AKR1C3, MCEE, POLE4, and PFKM were identified as potential diagnostic feature biomarkers associated with RA's immune cell infiltrations, providing a new perspective for future research and clinical management of RA.