Racial disparities in cancer incidence and outcome rates are prevalent in the US, with a variety of contributing factors, such as socioeconomic status, differences in lifestyle, environmental exposures, and biological and genetic determinants. The goal of this research was to broadly analyze public data to identify critical differences in molecular signatures and pathway regulation between races. Additionally, to support the clinical translatability of our work, we evaluated the association of differences in gene expression with patients’ survival outcomes. Our findings help inform the use of novel biomarkers in clinical settings and the future development of race-adjusted precision therapies.CCNB1, CCNE1, CCNE2, and FOXM1. In contrast, most other genes, such as transcriptional factor ETS1 and apoptotic gene BAK1, were differentially expressed and clinically significant only in specific cancer types. Our analyses also revealed race-dependent, cancer-specific regulation of biological pathways. Importantly, homology-directed repair and ERBB4-mediated nuclear signaling were both upregulated in Black samples compared to White samples in four carcinoma types. This large-scale pan-cancer study refines our understanding of the cancer health disparity and can help inform the use of novel biomarkers in clinical settings and the future development of precision therapies.Epidemiological studies reveal disparities in cancer incidence and outcome rates between racial groups in the United States. In our study, we investigated molecular differences between racial groups in 10 carcinoma types. We used publicly available data from The Cancer Genome Atlas to identify patterns of differential gene expression in tumor samples obtained from 4112 White, Black/African American, and Asian patients. We identified race-dependent expression of numerous genes whose mRNA transcript levels were significantly correlated with patients’ survival. Only a small subset of these genes was differentially expressed in multiple carcinomas, including genes involved in cell cycle progression such as  Race is a very broad categorizer that groups populations according to common ancestral and phenotypic characteristics. Racial groups are social constructs that exhibit immense biological variation within them. Even so, previous work has identified genetic, epigenetic, and expression-level differences between racial groups that are implicated in a wide range of biological mechanisms . Cancer The debate is ongoing regarding the relative contribution of intrinsic and extrinsic factors in the cancer disparity. Some studies suggest that differences in poor outcomes cannot fully be explained by disparate access to care ,7,8, whiAmerican cancer registries have shown that five-year cancer survival rates are lower in Black people at each stage of diagnosis across a wide spectrum of cancer types . The curXKR9 gene, implicated in the exposure of phosphatidylserine during apoptosis, as being differentially expressed between Asian Americans, Caucasian Americans, and African Americans in many cancer types and significantly associated with overall survival. The authors suggest that XKR9 could act as a potential race-dependent target for immunotherapy [AR, BCL2, CCND1, CDKN1A, CDKN1B, CDKN2A, ERBB2, ESR1, GATA3, IGFBP2, IL6ST, KRT19, MUC1, PGR, and SERPINE1 are differentially expressed in non-Hispanic White and African American breast cancer patients [AKT1, ALOX12, IL8, CXCR4, FASN, and TIMP3, in prostate cancer, suggesting opportunities for targeted therapies [Regardless of the relative importance of biological and non-biological factors, racial differences in incidence and survival are linked to many differentially expressed genes (DEGs). For example, Li et al. identified the otherapy . Howeverpatients . Vazquezpatients . Powell herapies . Other pherapies . Table 1herapies .In this study, we aimed to analyze pre-existing datasets from The Cancer Genome Atlas (TCGA) with a focus on molecular differences between three races: White, Black, and Asian patients. We described the definitions of these race categories in detail in the Methodology section below. While poorer cancer prognoses and incidence rates have been associated with specific racial groups ,31, the Cell studies, namely, Invasive Breast Carcinoma  [We used TCGA datasets generated as part of the PanCancer Atlas tumor molecular analysis project, cataloged in n = 684)  and Prosn = 684) . These tIn the TCGA database, each sample is assigned to only one of five racial categories, although in this study, we considered only three: “White”, “Black or African American”, and “Asian”. In this study, we use the term “Black” samples to refer to samples categorized as “Black or African American”. We excluded samples assigned to “American Indian or Alaska Native” and “Native Hawaiian or other Pacific Islander” due to low sample sizes, and samples for which race data were absent or unknown. The racial categories reported by TCGA are based on the definitions used by the US Census Bureau in classifying written responses to the race question ,39. Othep-value ≤ 0.05 was considered statistically significant.We performed race-based survival analysis for each cancer type in the cBioPortal web tool using race as the comparison factor. For BRCA-C, BRCA-P, CORE, KIRC, KIRP, LUAD, and UCEC, we compared samples labeled as “White” against “Black”. For LIHC, STAD, and THCA, samples labeled “White” were compared against samples labeled “Asian”. In addition to these baseline racial analyses, we performed separate analyses after stratifying the racial groups by sex . Due to unequal levels of racial representation in the different cancer datasets, the racial groups that we selected for analyses varied. Survival was evaluated using four different survival metrics: disease-free survival, progression-free survival, disease-specific survival, and overall survival. We used log rank tests performed by cBioPortal to assess statistical significance; a To determine the most clinically relevant genes for each cancer type, we used the Kaplan–Meier (KM) Plotter web tool . The KM p-values and hazard ratios with 95% confidence intervals were calculated. To reduce the false discovery rate (FDR), we used p ≤ 0.01 as a threshold of statistical significance.For each gene, samples were divided into two groups of low and high mRNA expression levels, based on the median expression, and the overall patients’ survival rates were compared. In the cBioPortal web tool, we performed group comparison analyses with race as the comparison factor. For BRCA-C, BRCA-P, CORE, KIRC, KIRP, LUAD, PRAD, and UCEC, we compared “White” with “Black” samples, as reported. For LIHC, STAD, and THCA, “White” was compared against “Asian” samples. The racial groups selected for analysis varied due to unequal levels of racial representation in the different cancer datasets. For each study, results from mRNA and protein expression analyses  were downloaded as tab-separated values (TSV) files. We wrote and used a pandas-based Python (version 3.7.7) program to filter the data for the 155 target genes. Statistically significant differences in mRNA and protein expression between the two racial cohorts, as determined by the Benjamini–Hochberg procedure performed by the cBioPortal web tool, were identified.https://github.com/brian-lei/cancer-racial-disparity, accessed on 18 January 2021) to format and export the data to Reactome, an open-source, open-access peer-reviewed pathway database [To perform integrative pathway analysis, we downloaded the PanCancer Atlas Reverse-phase protein arrays (RPPA) and clinical data from the original publication ,43. Thesdatabase ,45. We gp-values less than or equal to 0.01 in gene-based KM survival analyses were considered “clinically significant”. The survival relationship, as evaluated by KM analysis, is denoted in subsequent tables with a “+” for positive and a “−“ for negative correlations between specific mRNA gene expression and overall survival. The associated log rank p-value is denoted in parentheses.Genes that received higher mRNA expression of the gene, followed by the associated q-value in parentheses. The race denoted in tables under “Protein” is the race with higher protein expression and the associated q-value. “NS” represents non-significant values. Empty cells represent missing data from the original TCGA database.Genes that received q-values less than or equal to 0.05 in cBioPortal Benjamini-Hochberg comparison analysis were considered “differentially expressed” for mRNA expression, protein expression, or both. The race denoted in tables under “mRNA” is the racial group with Each table in the results section presents gene expression information for a particular cancer type. In all cases, we only included genes that were both clinically significant and differentially expressed between the denoted races. We excluded genes for which neither mRNA nor protein expression was significantly different.p-value ≤ 0.05 and denoted in parentheses in each table header.In the Reactome Pathway Analysis subsection, differential regulation of pathways was considered significant with an adjusted The analyses are organized alphabetically by cancer type. Each section reports the results of cBioPortal differential expression analysis. All sections, except for PRAD, include cBioPortal race-based survival and KM gene-based survival analysis results. Gene methylation analyses were performed for only two studies for which data were available, BRCA-C and PRAD. Gene expression analysis was performed on only one dataset for each section/cancer type, except for Breast Invasive Carcinoma, which includes results from both BRCA-C and BRCA-P with significant overlap in samples. However, it is important to emphasize that even when BRCA-P included almost two-fold “Black” samples and an additional 132 “White” samples than BRCA-C, the overall analyses yielded similar results. Complete results and statistical significance on all 155 target genes are included in In BRCA-C and BRCA-P, no significant differences were identified between White patients and Black patients for any of the survival metrics.High BCL3, FHIT, and IGF1R transcript levels were correlated with increased overall patient survival, while high CCNE1 and TGFBR1 transcript levels were correlated with decreased overall patient survival.BRCA-C and BRCA-P data revealed a relatively high number of differentially expressed genes compared to the other studies. Most notably, in BRCA-C, CCNE1 mRNA and protein levels were significantly increased in Black samples compared to White samples. However, in BRCA-P, only the mRNA levels were significant, while protein levels remained non-significant . SimilarIn BRCA-C, CCNE1 methylation was significantly increased in White samples compared to Black samples. Thirty-eight other target genes exhibited differential methylation across racial groups, including tumor-suppressor genes, BRCA2 (higher methylation in White samples), and PTEN (higher methylation in Black samples).p = 0.0476) than White patients, while differences in disease-free (p = 0.443), disease-specific (p = 0.0513), and overall survival (p = 0.961) were not significant. While survival of Black vs. and White females did not differ significantly in any metric, Black males had significantly worse progression-free (p = 0.004526) and disease-specific survival (p = 0.0362) than White males.In CORE, Black patients suffered from significantly worse progression-free survival , while FHIT expression was higher in Black samples (protein data not available). A total of 24 genes exhibited differential protein expression: BAK1, BIRC2, FASN, FOXM1, IRS1, MSH2, and STMN1 protein levels were significantly increased in Black samples, while CCNE2, CDH2, CDKN1A, CHEK1, DIRAS3, ERCC1, ETS1, GAPDH, HSPA1A, MAPK9, MYC, NF2, PRDX1, TGM2, TIGAR, VHL, and XRCC1 protein levels were significantly increased in White samples. The remaining clinically non-significant genes either had no data in TCGA or transcript levels did not differ between the examined races.No significant differences were identified between White patients and Black patients, even after stratifying by sex, for any of the survival metrics.High APC, BCL2, CCND1, CDKN1B, CTNNB1, ERBB2, ERBB3, ERCC4, ERG, ETS1, FGF1, FGF12, FLT1, GAB2, IGF1R, IL6R, KDR, KRAS, MAPK1, MAPK9, MSH2, MYCN, NRAS, PDGFC, PDGFD, PTCH1, PTEN, RAD50, RASSF8, RB1, SCFD2, SMAD4, TAL2, TGFA, TGFBR2, and TGFBR3 transcript levels were correlated with increased overall patient survival.High AXL, BAK1, BCL3, CCNB1, CCNE1, CCNE2, CRP, ERCC1, ETV4, FASN, FGF5, FGF8, FGF17, FGF21, FGF23, FOXM1, GAPDH, GNAS, GRP, IL6, NKX2-5, NKX3-1, NTRK1, SHBG, and SRC transcript levels were correlated with decreased overall patient survival.AXL, FGF5, KRAS, NKX2-5, RB1, and TAL2 transcript levels were significantly higher in White samples compared to Black samples, although protein data were absent from the original TCGA data. NRAS transcript levels were also increased in White samples, but protein expression was not significantly different across races. ETV4 and FGF17 transcript levels were higher in Black samples, although protein data were absent. ERBB2 transcript levels were higher in Black samples, but protein did not differ significantly across races. ETS1, MAPK1, MAPK9, and RAD50 mRNA, and protein levels were significantly increased in White samples. BCL2, CCNE2, ERCC1, and GAPDH protein levels were also increased in White samples, although transcript levels were not significantly different across races. Interestingly, CCNB1, MSH2, FOXM1, and RAD51 protein levels were increased in Black samples, while transcript levels were increased in White samples .Other 37 genes exhibited differential expression across races but were clinically non-significant without any impact on overall survival. Interestingly, BAP1 transcript levels were increased in Black samples, while protein levels were higher in White samples. Several other genes had differential protein expression but not differential mRNA expression, namely, BECN1, BIRC2, CDKN1A, DIABLO, DIRAS3, IRS1, NF2, PRDX1, RAF1, STMN1, TGM2, TP53, VHL, and XRCC1.No significant differences were identified between White patients and Black patients, even after stratifying by sex, for any of the survival metrics.High AXL and SMAD4 transcript levels were correlated with increased overall patient survival, while high BRCA2, CCNE1, CCNE2, FASN, FGF5, FGF7, FGF8, FGF11, FGF18, FOXM1, GRP, IGF2, and PDGFRB transcript levels were correlated with decreased overall patient survival.For all 155 target genes, including the genes identified by KM analysis as clinically significant for kidney renal papillary cell carcinoma, mRNA expression levels were not significantly different across races. Differences in protein levels were either not significant  or indeterminable due to a lack of associated protein data .No significant differences were identified between White patients and Asian patients, even after stratifying by sex, for any of the survival metrics.High BAK1, CCNB1, CCNE2, CDK4, CDKN2A, CHEK1, DIABLO, ETV1, ETV4, FOXM1, GAPDH, HRAS, MEN1, MSH2, NKX2-5, NRAS, PRDX1, RAD51, RASSF7, STMN1, TIGAR, and VHL transcript levels were all correlated with decreased overall patient survival. Interestingly, none of the target genes were correlated with improved survival.In LIHC, protein data for the genes identified by KM analysis as clinically significant were either absent or displayed non-significant differences across races, except for BAK1, whose protein levels were significantly increased in White samples compared to Asian samples. BAK1 transcript levels, however, were not significantly different across races. CCNB1, CCNE2, CHEK1, FOXM1, HRAS, MSH2, RAD51, and STMN1 transcript levels were significantly higher in Asian samples, while TIGAR transcripts were increased in White samples .Other 31 genes exhibited differential expression across races but were clinically non-significant without any impact on overall survival; all these genes differed in mRNA expression only. Specifically, AKT1, ALK, BCL2, CDKN1A, CRP, EGFR, ERCC4, ETS1, FGF7, FLT1, GDNF, GRP, HBEGF, IGF1, IL6, IL6R, KIT, MDM2, NKX3-1, PDGFC, PDGFD, PTCH1, PTCH2, RASSF6, RET, TGFBR1, TGFBR2, and TGFBRAP1 mRNA levels were enriched in White samples, while CCNE1, GNAS, and MAPK9 mRNA levels were enriched in Asian samples. Protein expression data for these genes were either not significant or unavailable from the original TCGA database.No significant differences were identified between White patients and Black patients, even after stratifying by sex, for any of the survival metrics.High BCL2, FGF18, GAB2, KIT, NTRK1, PTCH1, RASSF2, and TMPRSS2 transcript levels were correlated with increased overall patients’ survival, while high CCNB1, CCNE2, FGF5, FGF19, FOXM1, GAPDH, IRS1, TGFA, and VEGFC transcript levels were correlated with decreased overall survival.The mRNA transcript levels were not significantly different between White samples and Black samples for any of the genes identified by KM analysis as clinically significant for lung adenocarcinoma. Notably, IRS1 protein levels were significantly increased in Black samples .Seven clinically non-significant genes exhibited differential expression across races. ERCC1 and TIGAR protein expression was significantly increased in White samples, while NOTCH1 and RAD51 protein levels were increased in Black samples. mRNA levels for these four genes were not different between White samples and Black samples. MAPK1, MAPK9, and TGFBR1 transcript levels were enriched in White samples compared to Black samples; protein data were not significant for MAPK1/MAPK9 and absent for TGFBR1.The mRNA transcript levels of CTNNB1, FGF19, NF2, PTCH1, and RB1 were elevated in White samples, while transcript levels of FGFR4 and RASSF7 were elevated in Black samples. Protein data for these genes were either not significant or missing. SMAD4 protein levels were increased in White samples, although mRNA levels were not significantly different between Black samples and White samples.No significant methylation differences were identified in PRAD for any of the 155 examined genes.p = 0.0145) than White patients, while differences in progression-free (p = 0.729), disease-specific (p = 0.901), and overall survival (p = 0.304) were not significant. White females suffered from significantly worse overall survival compared to Asian females (p = 0.0453), while Asian males suffered from significantly worse disease-free survival compared to White males (p = 0.009962).In STAD, Asian patients suffered from significantly worse disease-free survival , while differences in progression-free (p = 0.263), disease-free (p = 0.272), and overall survival (p = 0.331) were not significant.In UCEC, Black patients suffered from significantly worse disease-specific survival  due to decreased XRCC1 and ERCC1 protein expression.In CORE, nucleotide excision repair was significantly downregulated in Black samples compared to White samples (adjusted p = 0.024). Additionally, the G2/M DNA damage checkpoint pathway was upregulated in Asian samples in LIHC (adjusted p = 0.018). In Asian samples, ATM levels were higher while CDK1, TP53, YWHAB, and YWHAE levels were lower compared to White samples.In LIHC, DNA mismatch repair pathways were upregulated in Asian samples compared to White samples due to elevated MSH6 protein levels : Black samples exhibited higher protein levels of ATM and BID, while TP53 and BAX expression was not significantly different between Black samples and White samples. In THCA, TP53 regulation of apoptotic gene transcription was increased in Asian samples compared to White samples (adjusted p = 0.017): Asian samples exhibited higher levels of BID protein. ATM, TP53, and BAX expression was also higher in Asian samples, although these differences were not significant.In LUAD, TP53-mediated regulation of apoptotic gene transcription was increased in Black samples compared to White samples (adjusted p = 0.014).In STAD, FOXO-mediated transcription of cell cycle genes was downregulated in Asian samples compared to White samples  to identify molecular differences between White, Black, and Asian samples that correlate with cancer health disparities. It is important to re-emphasize that TCGA data do not include detailed ancestry information, and hence, we have used the available racial categories instead. Although these racial categories are inherently subjective, others have emphasized the usefulness of race as it mostly aligns with genetic ancestry and can be a proxy to explain total variance that cannot be fully explained otherwise ,4,5. ThuCCNE1 was both differentially expressed and implicated in patient survival in breast and endometrial cancer. Additionally, the DNA repair gene MSH2 exhibited differential expression and clinical significance in kidney clear cell, liver, and endometrial cancer. CCNB1, CCNE2, and FOXM1 were three other genes that were differentially expressed in more than one carcinoma with survival implications, specifically in kidney clear cell and liver carcinoma. The clinical implications of multiple members of the cyclin family of proteins and the cell cycle regulator FOXM1 across multiple cancer types suggest that differences in cell cycle regulation are associated with survival disparities. Previous cancer-specific studies have also proposed this connection in breast [We observed that most of the targeted genes were both differentially expressed and clinically significant in no more than one cancer type, except for a few that were significant in at least two cancer types; this is suggestive of cancer-specific variations in gene expression. For example, the cell cycle progression gene n breast  and endon breast .It is important to note that although we focused on genes that had a significant correlation with overall survival, we also identified many genes that had no impact on overall clinical survival yet were differentially expressed between the examined races. It may be useful to perform further research on this subset of genes and their relevant pathways to uncover any unapparent relationships, if any, between expression and patients’ survival.Additionally, the source datasets varied in their abundance of differentially expressed biomarkers. While several pathways were identified in multiple cancer types as being regulated in a race-dependent manner with direct correlation to altered molecular patterns, in stomach adenocarcinoma, none of the clinically significant genes were differentially expressed between White and Asian samples.RAD50, RAD51, MRE11, ERCC1, and BRCA2, were observed in five cancer types. Moreover, genes involved in nucleotide excision repair and DNA mismatch repair were differentially expressed in colorectal and liver cancer, respectively. Nuclear signaling mediated by ERBB4 was upregulated in Black samples in four cancer types, an important finding considering that overexpression of the kinase is associated with cancer development [A striking group of pathways that were significantly associated with race was DNA repair mechanisms. Most notably, racial differences between Black and White samples in the expression of genes pertaining to homology-directed repair, including elopment . Table 1CDKN2A were absent from the original TCGA datasets; even so, our study corroborates the reported enrichment of CDKN2A transcript levels in Black patients with endometrial cancer [MDM2 oncogene expression was higher in White samples, a result consistent with the reported elevation of MDM2 protein expression in Caucasian Americans when compared to African Americans in prostate cancer [FGF12 in Black samples in UCEC conflict with the reported enrichment of fibroblast growth factor 12 in White patients [Protein data for many genes such as l cancer . We can e cancer . Howeverpatients . We founIGF1 mRNA and elevated levels of SHBG mRNA in Black samples in both BRCA-P and BRCA-C studies.The autocrine-paracrine growth factor, insulin-like growth factor 1 (IGF-1), has been reported to be a promoter of cancer that inhibits the sex hormone-binding globulin (SHBG) and exists in elevated levels in African American individuals [This study provides a methodological pipeline to identify clinically valuable molecular targets with preexisting datasets. However, we recognize certain limitations. The use of broadly defined racial groups and cancer types in our analyses neglects their great variability and diversity . Genetic ancestry and tumor typing information would certainly be of interest to consider in future research. There is also a consistent lack of representation of Black and Asian patients in the data, an issue that must be adequately addressed by the broader research community. The source data only included protein information for a few hundred genes; hence our pathway analyses are not conclusive. We were unable to perform a comprehensive analysis of the prostate adenocarcinoma dataset as it lacked survival data. Finally, we were unable to perform multiple analyses of similar datasets, except BRCA-C and BRCA-P, as other datasets in TCGA and cBioPortal are predominantly represented by White patients and contain limited or no data for Black and Asian patients for adequate statistical comparison.Nevertheless, in this study, we highlight correlative trends between patients’ survival and differentially expressed genes, suggesting that disparities in cancer outcomes overlap with key molecular differences. Future research should work with larger tumor datasets with a greater representation of Asian and Black patients to yield more statistically accurate analyses. Additionally, further work is needed to clarify the root causes of observed molecular differences to find direct relationships between differential expression and disparate outcomes. Ultimately, observed differences in cancer incidence and survival outcome are the result of a combination of many factors, including genetic polymorphisms, distinct molecular signatures, the synergistic effects of many traits, lifestyle, and environmental influences. Associations between self-reported race and disease outcome as presented in this study are thus valuable in predicting health impact of such structural inequalities along with genetic variations. With more proportional racial representation in tumor datasets and increased collection of proteomics data, we will be able to solidify our knowledge of molecular racial differences and work towards the development of personalized cancer therapeutics. Genome projects, such as the “1000 Genomes Project”  and the CCNB1, CCNE1, CCNE2, and FOXM1) was race-dependent in several cancer types and correlated with significant survival differences. We observed racial variation in the regulation of several DNA repair mechanisms and oncogenic pathways. Importantly, homology-directed repair pathway was upregulated in Black samples compared to White samples in breast, endometrial, kidney renal clear cell, and lung carcinomas. ERBB4-mediated nuclear signaling, which is associated with cancer development, was upregulated in Black samples compared to White samples in breast, colorectal, kidney renal clear cell, and lung carcinomas. Mapping race-dependent differentially expressed genes that influence overall patients’ survival and illustrating their impact on proteomics and functional molecular pathways may provide valuable insights into targeting disparities in cancer.Racial patterns of differential gene expression and pathways’ regulation varied between carcinomas. The expression of certain cell cycle genes (


Diabetic kidney disease (DKD), one of the most severe complications of diabetes mellitus (DM), has received considerable attention owing to its increasing prevalence and contribution to chronic kidney disease (CKD) and end-stage kidney disease (ESRD). However, the use of drugs targeting DKD remains limited. Recent data suggest that long non-coding RNAs (lncRNAs) play a vital role in the development of DKD. The lncRNA H19 is the first imprinted gene, which is expressed in the embryo and down-regulated at birth, and its role in tumors has long been a subject of controversy, however, in recent years, it has received increasing attention in kidney disease. The LncRNA H19 is engaged in the pathological progression of DKD, including glomerulosclerosis and tubulointerstitial fibrosis via the induction of inflammatory responses, apoptosis, ferroptosis, pyroptosis, autophagy, and oxidative damage. In this review, we highlight the most recent research on the molecular mechanism and regulatory forms of lncRNA H19 in DKD, including epigenetic, post-transcriptional, and post-translational regulation, providing a new predictive marker and therapeutic target for the management of DKD. AddiLong non-coding RNAs (LncRNAs), which are linear transcripts longer than 200 nucleotides that lack protein-translation potential, are of low abundance and stability making up the majority of non-coding RNAs (ncRNAs) in the genome , 14. TypAmong them, lncRNA H19, the first imprinted and maternally expressed gene to be discovered in eukaryotes , is loca22.1Hyperglycemia affects nearly all renal components, including the glomeruli, tubules, and interstitium. However, the glomerulus is traditionally classified as the first step in DKD. The Renal Pathology Society established four categories of glomerular lesions in 2010: Class I, glomerular basement membrane (GBM) thickening; Class II, mesangial expansion; Class III, nodular sclerosis (Kimmelstiel-Wilson lesions); and Class IV, advanced diabetic glomerulosclerosis .GBM thicking, glomerular hypertrophy, and glomerular filtration barrier (GFB) deficiencies are early signs of glomerular alterations . Among tThe dominant alteration in the glomerulus is glomerular podocyte dysfunction or podocytopathy, which is marked by podocyte loss, cellular hypertrophy, and foot process effacement , 32. ReaAdditional glomerular lesions include deletion of endothelial fenestrations and expansion of the mesangial matrix. The negatively charged glycocalyx decorated on fenestrated endothelial cells is essential for maintaining fluidic equilibrium and controlling vascular permeability, as well as preventing blood cells from attaching to the vascular wall , 39. HenFurthermore, hyperglycemia accelerates matrix expansion and alterations in glomerular mesangial cells (GMCs), which are the central stalk of the glomerulus making up 30-40% of all glomerular cells and role as a functional unit with endothelial cells and podocytes , 45. The2.2In contrast to careful studies on glomerular degeneration over the past few years, renal tubule interstitial impairment in DKD has largely been disregarded. Currently, the particular role of the renal tubule is of great interest in scientific research. Situated in the outer layer of the renal tubule, renal tubular epithelial cells (TECs) reabsorb chemicals such as amino acids and glucose from the urine, which is crucial for preserving the glomerulotubular balance. Additionally, TECs also influence the glomerular filtration rate by regulating concentrations of ions like Na+ and Cl-; this procedure is known as tubule-glomerular feedback , 55. In 3Considering that the underlying cellular processes resulting in the aforementioned histological presentations are considerably complex, continued attention to the pathophysiology of DKD is required. There is general agreement that critical metabolic derangements affect kidney hemodynamics and encourage immune dysregulation in early diabetes . Owing t4LncRNAs are abundant as functional units in eukaryotes, performing precise expression patterns in their various subcellular localizations, which has recently been the focus of intense debate. Numerous lncRNAs are limited to and abundant in the nucleus, governing transcriptional programs via chromatin remodeling and interactions in trans or cis . HoweverDepending on their roles, lncRNAs are commonly categorized as signals, decoys, scaffolds, and guides molecules that engage in diverse biological processes that affect gene expression, including epigenetic, transcriptional, post-transcriptional, translational, and post-translational regulation , 86. Lnc5Thus, understanding lncRNAs in eukaryotes has broadened our understanding of the role of lncRNAs in regulating gene expression and other biological processes. Reports on the interactions between lncRNAs and DKD have emerged in recent years, suggesting their essential roles in the pathogenesis of DKD. LncRNAs regulate many crucial factors linked to the DKD progression in different cell masses .5.1in vitro experiments explain that it encourages the recruitment of histone 3 lysine 27 trimethylation (H3K27me3) in the forkhead box A1(FOXA1) promoter region by recruiting enhancer of zeste homolog 2 (EZH2), which lessens FOXA1 expression, thereby increasing apoptosis and damage levels in podocytes  is situated very close to the sirt1 gene, which is recognized as a modulator of autophagy and insulin sensitivity, contributing to the onset of DKD through the regulation of podocyte autophagy and the thickness of GBM . Furtherodocytes .5.2Overexpression of lncRNA NEAT1 is observed in the TECs which further promotes EMT and fibrosis through the ERK1/2 pathway resulting in the accumulation of critical cytokines like connective tissue growth factor (CTGF), TGF-β, vimentin, and α-SMA . Additio5.3LncRNA NR_033515, competitively binding to miR-743b-5p, is engaged in fibrosis, EMT, and proliferation in DKD as evidenced by the rise in fibrogenic proteins and epithelial cell markers such P38, α-SMA, FN, E-cadherin, as well as mesenchymal marker Vimentin . Moreove6In addition to the aforementioned lncRNAs, H19 has received an avalanche of interest from researchers because of its unique biological characteristics. Because of its differential expression during the endocrine progenitor stage of pancreatic-islet development, H19 is crucial for pancreatic-islet development and function . LncRNA 6.1LncRNA H19 serves as a miRNA sponge to regulate EndMT, proliferation, inflammation, EMT, fibrosis, oxidative stress, ferroptosis, and pyroptosis Figure 3Another recent study demonstrated a favorable correlation between lncRNA H19 and renal fibrosis. Using TGF-β-induced HK-2 cells, StarBase 2.0 to identify miRNA recognition sites associated with lncRNA H19 during renal fibrosis, including miR-20, miR-93, miR-106, miR-18, and miR-17. It was shown that lncRNA H19 can function as an endogenous RNA to decrease miR-17 levels and boost the production of α-SMA, FN, Col. IV, and Col. I but reduce E-cadherin in unilateral ureteral obstruction mice. These findings collectively show that lncRNA H19 exacerbates renal fibrosis in DKD via the miR-17/fibronectin regulatory networks . MoreoveFerroptosis is another potential target of lncRNA H19 in DKD. Previous studies revealed that curcumin therapy markedly decreases the production of the lncRNA H19 in lung cancer cells to induce ferroptosis. Mechanistically, lncRNA H19, which works as a rival endogenous RNA bounding to miR-19b-3p, suppresses ferroptosis as shown by the increased transcriptional activity of ferritin heavy chain 1 (FTH1), a gene that is both an endogenous target of miR-19b-3p and a depressor of ferroptosis . AdditioGiven the crucial role of autophagy and pyroptosis in the progression of DKD, the regulatory relationship between lncRNA H19 and regulated cell death (RCD) cannot be neglected. Previous research has illustrated that lncRNA H19 also serves as a sponge for miR-22-3p and miR-423-5p to boost the activity of the Nod-like receptor family pyrin domain-containing 3 (NLRP3) , 139, a Apart from a miRNA sponge, lncRNA H19 exhibits its regulating effects in gene methylation, protein interaction, and transcription of small RNAs Figure 46.2In addition to acting as a miRNA sponge, lncRNA H19 influences the gene methylation of downstream cytokines. These findings suggest that lncRNA H19 binds to and inhibits the enzyme S-adenosylhomocysteine hydrolase (SAHH), resulting in the build-up of SAH, which prevents the transcription factor DNA methyltransferase 3 B (DNMT3B) from methylating the Beclin1 promoter. As a consequence, lncRNA H19 encouraged Beclin1 transcription to trigger autophagy . However6.3Regarding the unique structures of miR-675 and H19, scientists have revealed some interesting findings. MiR-675, which is embedded in the first exon of H19 gene , is acti6.4LncRNA H19 also influences downstream protein expression via direct binding. By binding to heterogeneous nuclear ribonucleoprotein A2B1(hnRNPA2B1), lncRNA H19 maintains and increases the expression of Raf-1 to activate the Raf-ERK signaling linked to EMT . In addi6.5However, some studies did not explain the specific working patterns of lncRNA H19 in DKD, leading to the following conclusions. One study showed that lncRNA H19 is highly expressed in both DKD rats and rat glomerular endothelial cells (rGEnCs). Further experiments demonstrated that lncRNA H19 knockdown reduced the GBM and ameliorated GEC impairment, as indicated by the high levels of the principal glycocalyx components WGA and Syndecan-1, as well as the essential tight junction proteins ZO-1 and Occludin. Additional research has demonstrated that lncRNA H19 has a deleterious effect on DKD by blocking Akt/eNOS signaling, which is essential for podocyte and GEC damage –126. AccIn other disease models, lncRNA H19 plays a role in collective pathogenesis, providing more possibilities for the role of lncRNA H19 in DKD. For instance, lncRNA H19 promoted oxidative stress and released inflammatory factors IL-6, IL-1β, and TNF- by stimulating the NF-kB pathway in intracerebral hemorrhage (ICH) rats . Additio7Nondiabetic kidney disease (NDKD) refers to kidney diseases unrelated to diabetes, including glomerulonephritis, acute kidney injury (AKI), focal segmental glomerulosclerosis, and minimal change disease. Nevertheless, renal biopsy in diabetic patients with chronic kidney diseases may indicate the following three possibilities: DKD, NDKD, or a mixture of both DKD and NDKD . TherefoIn vivo experiments then confirm that lncRNA H19, which sponges miR-30a-5p, could attenuate apoptosis and inflammation while also stimulating pro-angiogenic signaling, suggesting a protective role against kidney injury. It proves that capillary density and tubular epithelial integrity can be preserved in the lncRNA H19/miR-30a-5p axis  nephrocalcinosis mouse models. Their additional findings that lncRNA H19 accelerates renal epithelial cell injury in a miR-216b-5p manner, thereby up-regulating the expression of HMGB1, another target of miR-216b-5p that is negatively linked with it. Then HMGB1 interacted with toll-like receptor 4 (TLR4) to promote the transcription and expression of several chemokines and proinflammatory cytokines like IL-6, IL-1β, and TNF-α via NF-kB or NADPH oxidase ways . It is r8This review focuses on the primary pathogenic alterations and mechanisms of DKD, as well as the functions of lncRNAs in DKD, highlighting lncRNA H19. Substantial evidence supports the essential role of lncRNA H19 in the physiology and pathology of the diabetic kidney. As a result, we outlined how lncRNA H19 might affect the phenotypes associated with DKD, including inflammation, oxidative stress, autophagy, mitochondrial dysfunction, EMT, EndMT, ECM buildup, and fibrosis. We divided the mechanisms of lncRNA H19 in controlling DKD into four groups at the molecular level: regulation of gene methylation, protein interactions, miRNA sponges, and small RNA precursors. Among these, we find that serving as miRNA sponges is more common for lncRNA H19, which sponge miRNA to regulate downstream factors to modulate fibrosis-related progressions and hastens the development of DKD. Previous research revealed that lncRNA H19 is an independent risk factor for T2DM. Increased renal indicators  and nephropathy are more frequently linked to H19 expression , 171. InQW wrote and revised the manuscript. FH critically revised the manuscript. All authors contributed to the article and approved the submitted version.


Nitrogen is an important nutrient for plant growth and essential metabolic processes. Roots integrally obtain nutrients from soil and are closely related to the growth and development of plants. In this study, the morphological analysis of rice root tissues collected at different time points under low-nitrogen and normal nitrogen conditions demonstrated that, compared with normal nitrogen treatment, the root growth and nitrogen use efficiency (NUE) of rice under low-nitrogen treatment were significantly improved. To better understand the molecular mechanisms of the rice root system’s response to low-nitrogen conditions, a comprehensive transcriptome analysis of rice seedling roots under low-nitrogen and control conditions was conducted in this study. As a result, 3171 differentially expressed genes (DEGs) were identified. Rice seedling roots enhance NUE and promote root development by regulating the genes related to nitrogen absorption and utilization, carbon metabolism, root growth and development, and phytohormones, thereby adapting to low-nitrogen conditions. A total of 25,377 genes were divided into 14 modules using weighted gene co-expression network analysis (WGCNA). Two modules were significantly associated with nitrogen absorption and utilization. A total of 8 core genes and 43 co-expression candidates related to nitrogen absorption and utilization were obtained in these two modules. Further studies on these genes will contribute to the understanding of low-nitrogen adaptation and nitrogen utilization mechanisms in rice. Rice is one of the most widely grown food crops in the world. Approximately 50% of the world’s population uses rice as their staple food . Rice yiRoots are essential for the growth and development of plants . The morOsNRT2.4 promotes nitrogen absorption and lateral root growth [OsWOX11 and OsWOX3A regulate primary and lateral root development [Root architecture is regulated by intrinsic factors such as root development genes, transcription factors, small RNAs, and phytohormones and is influenced by some extrinsic factors. The cumulative effect of all these factors ultimately determines root formation ,14,15. Tt growth , and OsWelopment ,18. Planelopment ,20,21. Relopment . It has elopment ,24,25. TWeighted gene co-expression network analysis (WGCNA) is a method that is based on the expression data specified module of gene chip or RNA-seq. It uses system biology to understand co-expression networks and explores the associations between genes and target traits . In riceThis paper aims to better understand the morphological changes and molecular mechanism of nitrogen absorption and utilization of rice roots under low nitrogen. To achieve this, we investigated the morphological traits, such as root length, lateral root number, average root diameter, dry weight, nitrogen content, and NUE, of aboveground and underground parts and conducted transcriptome analysis at different time points. The transcriptome analyses indicated that the rice roots adapted to low-nitrogen conditions by regulating the genes related to nitrogen absorption and utilization, carbon metabolism, and root growth and development. Using WGCNA and constructing co-expression modules, the core genes and their co-expression candidates related to nitrogen absorption and utilization were obtained. The identified genes and their transcriptome analysis provided more useful information clarifying the molecular mechanisms of plant adaptation to nitrogen starvation.Low-nitrogen conditions have a significant effect on the root development of rice. In this study, we measured the total root length, lateral root number, and the average root diameter, dry weight of aboveground and underground parts, and nitrogen content of rice seedlings under low-nitrogen and controlled conditions. It was found that low nitrogen significantly increased the root length, lateral root count, root diameter, and dry weight of underground roots, and significantly decreased the dry weight of aboveground roots and nitrogen content of the whole plant. The NUE was significantly increased under low-nitrogen conditions .RNA-seq generated a total of 183.33 GB of clean readings from 18 root samples at three time points  after low-nitrogen and control treatments. The data from each sample were larger than 7.26 GB with GC contents ranging from 51.4% to 53.1%, and the Q30 base percentage was more than 91.1%. The alignment efficiency of each sample was between 86.1% and 94.1% . These rThe GO terms were similar on the first and third day after low-nitrogen treatment. The response to hypoxia, decreased oxygen levels, and oxygen levels were three of the most significantly enriched GO terms on the first day A. The ceOsLBD37 and OsLBD38 were down-regulated and two peptide transporters (PTRs) (Os06g0706100 and Os01g0902700) were up-regulated on the first day; OsNRT2.4 and Os01g0902700 (PTR) were up-regulated and OsNRT1.1B, OsLBD37, OsLBD38, Os01g0902800, and Os10g0112500 were down-regulated on the third day; and nine DEGs  were down-regulated on the seventh day. Among the DEGs related to nitrogen assimilation, OsNR2 was down-regulated at all three time points; OsNIA1, OsNADH-GOGAT2, and OsAS1 were only down-regulated on the third day (Sixteen DEGs related to nitrogen transport (containing three transcription factors (TFs)) and four DEGs related to nitrogen assimilation were identified in this study. Among the DEGs related to nitrogen transport, hird day .OsPPDKA, OsPDC1, OsRRJ2, OsPEPCK, and Os06g0104900 were down-regulated on the first day; eleven DEGs, including OsALDH11A3, OsADH2, OsADH3, OsPPDKA, OsPDC1, etc., were down-regulated on the third day; OsADH3 was up-regulated on the seventh day. Among the DEGs related to oxidative phosphorylation, Os02g0791400 was down-regulated on the first day; Os08g0496000 was down-regulated on the third day; and Os03g0759000 and Os05g0438500 were down-regulated on the seventh day. Among the DEGs related to pentose phosphate, OsPPi-PFK was down-regulated on the first day; OsG6PDH5, PGI-a, OsPPi-PFK, and OsPFPA3 were down-regulated and Os04g0266900 was up-regulated on the third day; and OsRPI, OsG6PDH3, Os01g0723600, and Os07g0406350 were down-regulated and PFPβ was up-regulated on the seventh day. Among the DEGs related to starch and sucrose metabolism, OsGns13 was up-regulated on the first and third day; Os9bglu33 was up-regulated on the third day; and OsGH9B2, Amy2A, and OsSTA246 were up-regulated on the seventh day  were selected as core genes and 43 candidate genes were obtained that may have mechanisms in the regulation of the low-nitrogen response and nitrogen absorption and utilization ; Os01g0965900 was co-expressed with Os01g0960900; Os01g0944100 and Os06g0662550 were co-expressed with Os01g0902800; OsFBO17, OsFLZ13, OsRLCK113, and ONAC83 were simultaneously co-expressed with two PTRs (Os03g0235700 and Os01g0960900); Os12g0410150, OsAK3, Os11g0602750, and Os11g0164200 were simultaneously co-expressed with three PTRs ; OsWNK6 was simultaneously co-expressed with four PTRs ; OsFbox445 was simultaneously co-expressed with two PTRs (Os01g0960900 and Os03g0235700); and OsDRE2a, OsTRXh5, and OsERF66 were simultaneously co-expressed with three PTRs   . The exp RNA-seq .Roots are plants’ main nitrogen-absorbing organ. The adaptive changes in root morphology and physiological characteristics are an important material basis for the effective use of nitrogen by plants . PreviouOsNRT1.1B, OsNRT2.1, OsNRT2.2, OsNPF4.5, OsNPF7.3, and OsNAR2.1 and the three peptide transporters (PTRs)  were down-regulated in this study. The expressions of two dual-affinity nitrate transporters (OsNRT1.1B and OsNRT2.4), two high-affinity nitrate transporters (OsNRT2.1 and OsNRT2.2), two low-affinity nitrate transporters (OsNPF4.5 and OsNPF7.3), and one nitrate transporter chaperone protein (OsNAR2.1) were regulated by the NO3− concentration [OsNRT2.1, OsNRT2.2, and OsNAR2.1 were up-regulated by NO3−, and the expressions of OsNRT2.1 and OsNRT2.2 were significantly down-regulated in the OsNAR2.1 knockdown mutants [OsNAR2.1 led to the down-regulated expression of OsNRT2.1 and OsNRT2.2 under low-nitrogen conditions. OsNRT2.4 and two PTRs (Os06g0706100 and Os01g0902700) were up-regulated in this study. A previous study found that the number and length of lateral roots of rice and the total nitrogen absorption would be reduced by knocking out OsNRT2.4 [OsLBD37, OsLBD38, and OsLBD39 of the LOB transcription factors family, which negatively regulate NO3− absorption [OsNIA1, OsNR2, OsAS1, and OsNADH-GOGAT2, were down-regulated in this study, which may have been caused by feedback inhibition. Moreover, the accumulation of glutamate inhibits the expression of nitrate reduction and transport genes. Therefore, under low-nitrogen conditions [Inorganic nitrogen is absorbed and transported by specific transfer proteins, such as nitrate transporter (NRT) and ammonium transporter (AMT). Many of the nitrogen transporters of rice, such as ntration ,43,44. T mutants . TherefoOsNRT2.4 . TranscrOsNRT2.4 . The expsorption , were donditions ,49, riceOsGH9B2, Amy2A, OsGns13, Os9bglu33, and OsSTA246) were up-regulated, which may be related to root-growth-oriented carbon allocation, because sucrose stimulates the formation of lateral roots [Os06g0104900  and OsGapC1 , which are involved in the glycolytic pathways, were down-regulated. These genes are particularly relevant to the reduction ability. The expressions of two rate-limiting enzymes, OsG6PDH3 and OsG6PDH5 (glucose 6-phosphate dehydrogenase), which provide reducing power (NADPH) in the pentose phosphate pathway, were down-regulated. The up-regulated expression of glucose 6-phosphate dehydrogenase probably increases NADPH production [+) pump ATPase, thus leading to the accumulation of excess reactive oxygen species (ROS) and disrupting normal metabolism [Nitrogen stress caused changes in gene expression related to the carbon metabolism in rice. The assimilation pathways of carbon and nitrogen are closely related . Carbon al roots . Root stal roots . Therefooduction . Transcrtabolism ,61,62. TOsAUX4, an auxin input vector, positively regulate the growth and development of rice roots [OsAUX4 were up-regulated in this study. The asymmetric distribution of auxin efflux transport protein PIN (PIN-FORMED) determines the polar transport of auxin [OsPIN5b negatively regulates root growth [OsPIN5b and OsPIN9 were down-regulated and OsPIN5c was up-regulated. One of the pathways for the root itself to synthesize indole-3-acetic acid (IAA) involves acetaldehyde dehydrogenase catalyzing indole-3-acetaldehyde to produce indoleacetic acid. The expressions of acetaldehyde dehydrogenase genes in rice roots, such as OsALDH3H1, OsALDH7, and OsALDH11A3, were down-regulated under low-nitrogen conditions in this study. The polar transport of IAA moves from the top of the plant to the base, which promotes the initiation and development of lateral roots. According to the changes in the genes related to IAA synthesis and transport, it was speculated that the IAA synthesis ability and the output of rice roots decreased under low-nitrogen conditions, while the IAA input to the roots was enhanced, thus promoting root development. The ethylene-activated signaling pathways, cellular responses to ethylene stimulation, and jasmonic-acid-mediated signaling pathways were three of the most significantly enriched GO terms on the seventh day. The growth of rice adventitious roots was directly controlled by ethylene (ETH), which promotes cell division and elongation growth [OsDERF1 and OsERF2, which negatively regulate the ethylene pathway and root growth [OsWR3 and Sub1B were up-regulated. Jasmonic acid (JA) promotes the root growth of rice and Arabidopsis [OsWRKY30, the down-regulated expressions of OsWRKY42, OsJAZ8, and OsJAZ13, and the up-regulated expression of OsJAMyb followed by its down-regulated expression. A previous study indicated that OsWRKY30 promotes JA accumulation [OsWRKY42, OsJAZ8, and OsJAZ13 inhibit JA signaling transduction [Low nitrogen induces rice root elongation, and growth is the result of metabolic changes caused by a series of gene expression changes. Among them, the change in auxin plays an important role in the growth and development of rice roots . OsCrll1ce roots ,64. The of auxin . OsPIN5bt growth . In thisn growth . The expt growth ,68, werebidopsis ,69. In tmulation , OsWRKY4sduction ,72,73, asduction . In concOsNAC36, were identified using WGCNA [OsNRT2.1, OsNRT2.2, OsNRT2.4, OsNPF4.5, and four peptide transporters (PTRs) . Among them, OsNRT2.1, OsNRT2.2, OsNRT2.4, and OsNPF4.5 were verified as being related to nitrogen absorption and utilization [OsNPF2.2, OsPTR6, and OsPTR9, have also been shown to play important roles in nitrogen absorption and utilization [Os01g0902800, Os01g0960900, Os03g0235700, and Os10g0112500) could act as core genes and play a role in nitrogen absorption and utilization. In this study, 43 candidate genes co-expressed with core genes were obtained using WGCNA. WGCNA is widely used in transcriptome analyses, such as those performed in research involving growth and development regulation, environmental stress response, yield and quality formation, etc., especially for complex data models [DAO, which encodes a growth-hormone-oxidizing dioxygenase, was able to rapidly respond to nitrogen stress [OsSultr1;1, the sulfate transporter protein, was regulated by nitrogen in a previous study [Os08g0533300 was presumed to be ACR5 (accumulation and replication of chloroplasts 5), which has been significantly and positively correlated with plant growth [OsWNK6 may be functionally similar to OsWNK9, which negatively regulated root elongation [WGCNA is a very useful method for studying the correlation between genes, identifying modules with high phenotype correlation, and mining hub genes in different modules. Some transcription factors and hub genes that responded to nitrate deficiency in rice roots, such as PtaRAP2.11 and ng WGCNA ,75,76. Tlization ,45,77. Nlization . Some PTlization ,79,80. Ta models ,82,83. Sa models ,84,85. An stress ; OsSultrus study ; Os08g05t growth ; and OsWongation ,90. ThesLong Japonica 31, a variety of Japonica rice, was used in this experiment. The main stem has 11 leaves, the plant height is about 92 cm, the spike length is about 15.7 cm, the number of grains per spike is about 86, and the thousand grain weight is about 26.3 g. We identified Long Japonica 31 as a high-NUE rice variety using pre-screening. The plump seeds were kept in an incubator at 48 °C for 48 h to break the dormancy. The seeds were then sown on a 96-well PCR plate, with one seed per well. The seeds were sterilized by soaking them in a 1% sodium hypochlorite solution for 30 min. The sterilized seeds were washed 3 times using distilled water and then placed in an incubator at 30 °C for 2 days to germinate. The germinated seeds were incubated in a greenhouse . Ammonium nitrate was chosen as the nitrogen source. The concentrations of the low-nitrogen and control conditions were 8 ppm and 40 ppm, respectively. For 5 days, 192 seedlings were incubated under control nitrogen conditions (40 ppm). Then, 96 seedlings were kept in the same solution for 7 days and the remaining 96 seedlings were transplanted to low-nitrogen conditions (8 ppm) for 7 days. The formulation of the hydroponic nutrient solution was based on the conventional nutrient solution formulation of the International Rice Research Institute .After 0 d, 1 d, 3 d, and 7 d of treatment, the total root length, lateral root number, and root diameter were measured using an LA-S plant root analysis system (Microtek Scan Maker 800). The above- and underground parts of the seedlings were collected and dried in an oven at 105 °C for 30 min. The weight of the dry matter was measured. An elemental analyzer (Primacs SNC100-IC-E) was adopted to analyze the nitrogen content of the above- and underground parts, and each sample included 3 replicates, with 10 plants per replicate. The nitrogen use efficiency was calculated using the following formulas:Phenotypic data were analyzed descriptively using SPSS 26.0 and Origin 2021b.p < 0.05 and |log2FC| > 1 were adopted as the thresholds with which to identify the differentially expressed genes between any two comparative groups using edgeR v3.24.3 [Eighteen root samples that underwent low-nitrogen treatment and control treatment were collected on the first, third, and seventh days of treatment. This was repeated three times for each sampling point. The total RNA was extracted using the TransZol Up RNA Kit . The complementary DNA was synthesized from total RNA using the HiFiScrip Gene Synthesis Kit . An Illumina library was constructed according to the manufacturer’s instructions . High-throughput RNA sequencing was performed using the Illumina HiSeq 2500 platform. The indexing was carried out using HISat v2.1.0 and clean reads were mapped to the genome sequence. The gene matching and FPKM were calculated using FeatureCounts v1.6 software . p < 0.0 v3.24.3 .TM SYBR Green qPCR Master Mix 2.0  and reactions were run on Roche Lightcycler 96 real-time PCR equipment in accordance with the manufacturer’s instructions . Each sample had three technical replicates and Actian1 was used as an internal control. Finally, the expressions of 43 candidate genes were calculated using the 2−∆∆CT method. All the primers are listed in The primer design was performed using Primer Premier 5.0. The total RNA was extracted using the TransZol Up RNA Kit  and stored at −80 °C. The first-strand cDNA (10 µL) was synthesized according to the instructions for the PrimeScript™ RT Master Mix  Co., Ltd., Beijing, China). The BlazeTaqThe Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed using the top GO and ClusterProfiler R packages, respectively (default parameters) .In order to construct the gene co-expression network, the WGCNA package in R was chosen to screen the genes , and theIn this study, the morphological analysis of rice root tissues collected at different time points of low- and normal-nitrogen-level treatments showed that root growth and NUE were significantly increased under low-nitrogen treatment. The transcriptomic analysis indicated that nitrogen assimilation in rice is inhibited by feedback regulation and that the pathways involved in carbon metabolism that provide reducing power may also be inhibited due to the lower requirement for reducing power under low-nitrogen conditions. To maintain growth and developmental homeostasis, rice may promote nitrogen absorption by promoting the expression of amphipathic and nitrogen transport proteins and inhibiting the expression of the transcription factors negatively regulating nitrogen transport. It also regulates plant-hormone-related genes, promotes the polar transport of auxin to the root, and inhibits the genes that negatively regulate ethylene and jasmonic-acid-related pathways to promote root growth and development. This work not only provides insight into the molecular mechanism of rice root systems’ response to low-nitrogen conditions, but may also be significant for uncovering the as-of-now unknown nitrogen absorption and utilization genes, thus benefiting the breeding of high-NUE rice cultivars.


We searched electronic databases from inception to 30 June 2023 and assessed the risk of bias and the certainty of evidence. In 21 eligible studies, compared to healthy controls, patients with stable COPD had significantly lower methionine  and folic acid , and higher homocysteine  and cysteine concentrations . Additionally, COPD was associated with significantly higher ADMA , SDMA , and ornithine concentrations . In subgroup analysis, the SMD of homocysteine was significantly associated with the biological matrix assessed and the forced expiratory volume in the first second to forced vital capacity ratio, but not with age, study location, or analytical method used. Our study suggests that the presence of significant alterations in metabolites within the arginine, transsulfuration, and folic acid pathways can be useful for assessing nitric oxide dysregulation and oxidative stress and identifying novel treatment targets in COPD. (PROSPERO registration number: CRD42023448036.)There is an increasing interest in biomarkers of nitric oxide dysregulation and oxidative stress to guide management and identify new therapeutic targets in patients with chronic obstructive pulmonary disease (COPD). We conducted a systematic review and meta-analysis of the association between circulating metabolites within the arginine , transsulfuration  and folic acid (folic acid, vitamin B The global public health and financial burden of chronic obstructive pulmonary disease (COPD) remains unacceptably high despite the availability of different pharmacological and non-pharmacological treatments in this ever-increasing patient group ,4,5,6,7.6  appraising the available evidence, through a systematic review and meta-analysis, of the association between the circulating concentrations of key metabolites within the arginine, transsulfuration, and folic acid metabolic pathways and COPD, and (b) assessing, where possible, the relationship between the effect size of the observed differences vs. healthy controls and clinical and demographic characteristics.12” OR “cobalamin” OR “B6” OR “pyridoxine” OR “arginine” OR “asymmetric dimethylarginine” OR “ADMA” OR “symmetric dimethylarginine” OR “citrulline” OR “ornithine”.A systematic search of publications was conducted in the electronic databases PubMed, Web of Science, and Scopus from inception to 30 June 2023. The search utilized the following terms and their combinations: “COPD” OR “chronic obstructive pulmonary disease” AND “methionine” OR “homocysteine” OR “cysteine” OR “cystathionine” OR “S-adenosylmethyonine” OR “S-adenosylhomocysteine” OR “S-adenosyl-methyonine” OR “S-adenosyl-homocysteine” OR “betaine” OR “dimethylglycine” OR “folates” OR “folic acid” OR “B6, vitamin B12, folic acid, arginine, ADMA, SDMA, citrulline, or ornithine in plasma or serum, (b) the study of patients with stable COPD and healthy controls using a case–control design, (c) the inclusion of participants ≥18 years, and (d) the availability of full text in English language. The main exclusion criterion was the assessment of patients with acute exacerbations of COPD. The two investigators independently extracted the following variables into an electronic spreadsheet for further analysis: year of publication, first author, study country, participant number, age, male to female ratio, forced expiratory volume in the first second (FEV1), FEV1/forced vital capacity (FVC), biological matrix (plasma or serum), and analytical method used. A third investigator was involved in case of disagreement.Two investigators independently screened the abstracts, full-text articles, and relevant references according to the following inclusion criteria: (a) the assessment of homocysteine, cysteine, methionine, vitamin BThe Joanna Briggs Institute Critical Appraisal Checklist was used to assess the risk of bias , whereasp-value < 0.05 for statistical significance), and estimated means and standard deviations from medians and interquartile ranges or ranges [p < 0.10) [1, FEV1/FVC, biological matrix, and analytical method used. Statistical analyses were performed using Stata 14 .We created forest plots of standardized mean differences (SMDs) and 95% confidence intervals (CIs)  ,81. Sens < 0.10) . The Egg < 0.10) ,84,85. UFrom a total of 1788 articles, we excluded 1759, as they were either duplicates or irrelevant. A full-text revision of the remaining 29 articles led to the exclusion of further eight because they had missing data (n = 2), unsuitable (not case–control) design (n = 4), or included patients with acute exacerbation of COPD (n = 2). The 21 studies included in the final analysis were published between 1998 and 2020  86,87,8,105,106.1 was reported in eight studies (range between 39% and 70%) [1/FVC in five (range between 53% and 68%) [Homocysteine was measured in 11 studies investigating a total of 610 COPD patients  and 468 healthy controls  ,105,106,and 70%) ,105,106,and 68%) ,105,106.p < 0.001; I2 = 79.4%, p < 0.001; p = 0.64); Egger’s test, p = 0.51). No additional study was identified using the “trim-and-fill” method , number of participants , or publication year . In subgroup analysis, no significant differences (p = 0.47) in the pooled SMD were observed between studies in patients ≤70 years , or >70 years  in effect size were observed between studies conducted in Europe  and Asia  in the pooled SMD were observed between studies using high performance liquid chromatography  and other methods  in the pooled SMD were observed between studies using ultraviolet detection , and fluorimetric detection , but not serum , but not FEV1 ˃55% , but not FEV1/FVC ˃60%  after considering the low risk of bias in all studies, the high but partially explainable heterogeneity, the lack of indirectness, the relatively low imprecision, the moderate effect size, and the lack of publication bias.Cysteine was measured plasma in two European studies including a total of 73 COPD patients  and 83 healthy controls  ,106. Liqp = 0.038; I2 = 0.0%, p = 0.83; Cysteine concentrations were significantly higher in COPD patients compared to controls  after considering the low risk of bias in all studies, the virtually absent heterogeneity, the lack of indirectness, the relatively low imprecision, the relatively small effect size, and the lack of assessment of publication bias (downgrade one level).Two studies investigated plasma methionine in a total of 42 COPD patients and 38 healthy controls ,88. One p = 0.029; I2 = 0.0%, p = 0.80; Methionine concentrations were significantly lower in COPD patients compared to controls  after considering the low risk of bias in all studies, the virtually absent heterogeneity, the lack of indirectness, the relatively low imprecision, the relatively moderate effect size, and the lack of assessment of publication bias (downgrade one level).12 was measured in three studies including a total of 125 patients  and 85 healthy controls  [Vitamin B% males) ,92,99. O% males) , one in % males) , the sec% males) ,92, and 12 concentrations between COPD patients and controls  after considering the low risk of bias in all studies, the moderate heterogeneity, the lack of indirectness, and the lack of assessment of publication bias (downgrade one level).Three studies measured folic acid in a total of 125 COPD patients  and 85 healthy controls  ,92,99. Op = 0.009; I2 = 0.0%, p = 0.88; Folic acid concentrations were significantly lower in COPD patients compared to controls  after considering the low risk of bias in all studies, the virtually absent heterogeneity, the lack of indirectness, the relatively low imprecision, the relatively moderate effect size, and the lack of assessment of publication bias (downgrade one level).Arginine was measured in four studies including a total of 117 COPD patients (mean age: 67 years) and 111 healthy controls (mean age: 64 years) ,88,94,95p = 0.18; I2 = 97.7%, p < 0.001; There were non-significant between-group differences in arginine concentrations  after considering the low risk of bias in all studies, the high and unexplained heterogeneity (downgrade one level), the lack of indirectness), and the lack of assessment of publication bias (downgrade one level).ADMA was measured in six studies including a total of 314 COPD patients  and 218 healthy controls  were evaluated ,98,101. p = 0.037; I2 = 97.2%, p < 0.001; ADMA concentrations were significantly higher in COPD patients compared to controls  after considering the low risk of bias in all studies, the high and unexplained heterogeneity (downgrade one level), the lack of indirectness, the relatively low imprecision, the relatively large effect size (upgrade one level), and the lack of assessment of publication bias (downgrade one level).Three European studies measured SDMA in a total of 104 COPD patients  and 88 healthy controls  ,95,102. p = 0.014; I2 = 98.1%, p < 0.001; SDMA concentrations were significantly higher in COPD patients compared to controls  after considering the low risk of bias in all studies, the high and unexplained heterogeneity (downgrade one level), the lack of indirectness, the relatively low imprecision, the relatively large effect size (upgrade one level), and the lack of assessment of publication bias (downgrade one level).Plasma ornithine was measured in three studies including a total of 117 COPD patients (mean age: 69 years) and 82 healthy controls (mean age: 58 years) ,88,103. p = 0.015; I2 = 62.9%, p = 0.067; Ornithine concentrations were significantly higher in COPD patients than controls  after considering the low risk of bias in all studies, the moderate heterogeneity, the lack of indirectness, the relatively low imprecision, the moderate effect size, and the lack of assessment of publication bias (downgrade one level).6 concentrations compared to controls  using a radioimmunoassay method [In a study comparing 42 COPD patients (71 ± 8 years) and 29 age-matched healthy controls (71 ± 6 years), COPD patients had significantly lower vitamin By method .In a study comparing 12 COPD patients (66 ± 2 years) and eight age-matched healthy controls (64 ± 3 years), there were non-significant differences in plasma citrulline concentrations between the two groups (48 ± 6 vs. 54 ± 7 μmol/L) using a liquid chromatography assay with fluorimetric detection .1 to FVC ratio, but not with age, study location, or analytical method used.We observed significant alterations in the circulating concentrations of key metabolites within the arginine, transsulfuration, and folic acid metabolic pathways in COPD using targeted metabolomic analysis. Compared to healthy controls, patients with stable COPD had significantly lower concentrations of methionine and folic acid, and higher concentrations of homocysteine and cysteine. In the context of arginine pathways, COPD was also associated with significant elevations of ADMA, SDMA, and ornithine. Subgroup analysis, which was only possible for studies investigating homocysteine, showed that the SMD of this metabolite was significantly associated with the biological matrix assessed (plasma vs. serum) and the FEV12 stimulate the conversion of homocysteine into methionine [Homocysteine, a highly reactive sulfur-containing amino acid and a metabolite of methionine , has beethionine , with co1 and FVC [1 and FVC have been reported specifically in healthy smokers [p < 0.001) [1 and FVC values compared to patients in the bottom quartile. In a more recent nationwide survey of COPD patients, folic acid concentrations were positively associated with FEV1 and FVC values, particularly in males and in current smokers [12, can improve symptoms, lung function, and clinical outcomes in patients with COPD.The results of our systematic review and meta-analysis, particularly the increased circulating concentrations of homocysteine and ADMA, and the reduced concentrations of folic acid and methionine suggests a significant dysregulation of these pathways in COPD. Such dysregulation would manifest biologically as an impaired synthesis of NO via ADMA accumulation, a pro-oxidative state via homocysteine accumulation, and an overall pro-atherosclerotic state. Furthermore, epidemiological studies have reported that higher ADMA concentrations are independently associated with a significant reduction in FEV and FVC . Similar smokers . In furt< 0.001) . Notably smokers . Given t smokers ,71,112,  smokers ,125,126,The observed increases in circulating SDMA and cysteine in COPD are intriguing. Like ADMA, SDMA is derived from the methylation of arginine residues in proteins by PRMT 2 ,128 Fig. HoweverAnother interesting observation in our systematic review and meta-analysis was the higher concentration of circulating ornithine in patients with stable COPD compared to healthy controls. As previously described , ornithi6, given that our systematic search identified only one relevant study for each metabolite. Another significant limitation was the paucity of data reported in the selected studies regarding specific comorbidities, e.g., neurological and cardiovascular disease states, dietary patterns, and medications, factors which could also affect the concentrations of the studied metabolites [6, and B12 may indirectly reflect dietary behaviours given their associations with specific food sources [Our study had several strengths, including the comprehensive assessment of arginine, transsulfuration, and folic acid metabolomics in stable COPD and the robust evaluation of the risk of bias and the certainty of evidence for each studied metabolite. Limitations included the small group of selected studies for most metabolites, with the exception of homocysteine, which prevented sensitivity analysis, the assessment of publication bias, and the conduct of meta-regressions and subgroup analyses to investigate associations between the effect size and several clinical and demographic variables, e.g., age, sex, and markers of inflammation, and to identify possible sources of heterogeneity. Further studies are also necessary to investigate the potential pathophysiological role of citrulline and vitamin Babolites ,155,156. sources ,158.Our study showed significant alterations in the circulating concentrations of methionine, homocysteine, and cysteine (transsulfuration pathway), folic acid (folic acid pathway), and ADMA, SDMA, and ornithine (arginine pathway) in COPD. These alterations are suggestive of impaired NO synthesis and redox balance and may also explain the frequent occurrence of specific comorbidities, particularly atherosclerotic cardiovascular disease, in this patient group. Further research is warranted to confirm these findings, to investigate further associations between these metabolites and age, sex, markers of inflammation, specific comorbidities, dietary patterns, and medications, and to assess the effects of ADMA/homocysteine-lowering therapies and arginase inhibitors on lung function, symptom burden, disease progression, and mortality in COPD.


However, magnolol supplementation remarkably increased (p < 0.05) the serum content of albumin, total protein, immunoglobulin G, immunoglobulin M, and interleukin-22. In addition, dietary magnolol supplementation altered the amino acid (AA) profiles in serum and dorsal muscle and particularly increased (p < 0.05) the serum content of arginine and muscle glutamate. Simultaneously, the mRNA expression of genes associated with AA transport in jejunum  and ileum (SLC1A5 and SLC7A1) was higher (p < 0.05) in the Mag group than in the Con group. Additionally, the serum metabolomics analysis showed that the addition of magnolol significantly enhanced (p < 0.05) arginine biosynthesis, as well as D-glutamine and D-glutamate metabolism. Overall, these results suggested that dietary supplementation with magnolol has the potential to improve the accumulation of AAs, protein synthesis, immunity, and body health in growing pigs by increasing intestinal absorption and the transport of AAs.This study investigated whether dietary supplementation with magnolol affects growth performance, anti-inflammatory abilities, serum and muscle amino acid profiles, and metabolisms in growing pigs. A total of 42 seventy-days-old growing barrows (Duroc × Landrace × Yorkshire) were randomly allocated into two dietary groups: Con, control group ; and Mag, magnolol group . The results revealed that dietary supplementation with magnolol had no effect ( In recent decades, the use of subtherapeutic doses of antibiotics over extended periods in animal production has been identified as a major contributor to the rapid dissemination of antimicrobial resistance . AlthougThe rapid growth of skeletal muscle is a prominent characteristic in growing pigs that is heavily reliant on the availability of amino acids (AAs) for protein synthesis . AA absoSLC7A1 in intestinal porcine enterocyte J2 cell line and middle-jejunum segments [In recent years, the beneficial effects of polyphenols on growth promotion , intestisegments . Additiosegments . HoweverMagnolia officinalis, has a wide range of pharmacological effects on humans and animals [Magnolol, a natural and nontoxic polyphenolic compound found in the bark of the Chinese herbal medicine  animals . Recentl animals , exert a animals ,25, incr animals , promote animals , and reg animals . DespiteFindings from our previous study supported the growth-promoting effects of magnolol and its ability to enhance the apparent digestibility of crude protein in weaning piglets . Therefop > 0.05). Similarly, no significant differences in the average daily feed intake (ADFI) and feed conversion rate (F:G) were observed between the two groups (p > 0.05).The growth performance of growing pigs in different diet groups is summarized in p < 0.05). The serum level of high-density lipoprotein cholesterol (HDL-C) tended to increase with magnolol supplementation (p < 0.10). The concentration of diamine oxidase (DAO) showed a decreasing trend in response to magnolol supplementation (p < 0.10). However, there was no significant difference in the other serum biochemical indices  between the two groups (p > 0.05).The serum biochemical indices of pigs fed a magnolol-supplemented diet are shown in p < 0.05). There was a decreasing tendency shown by the interferon-gamma (IFN-γ) concentration in the Mag group in comparison to the Con group (p < 0.10). However, there were no significant differences in immunoglobulin A (IgA), interleukin-2 (IL-2), interleukin-10 (IL-10), and tumor necrosis factor-alpha (TNF-α) levels between the Con and Mag groups (p > 0.05).The serum immunological markers were measured to evaluate the immune status of growing pigs . Concernon group G . Additionally, dietary supplementation with magnolol showed an increasing trend in the serum concentrations of methionine, aspartate, and cysteine (p < 0.10). However, there were no marked changes in the serum concentrations of isoleucine, lysine, phenylalanine, threonine, tryptophan, valine, alanine, glutamate, glycine, serine, tyrosine, asparagine, glutamine, essential, nonessential, and total AAs between the Con and Mag groups (p > 0.05).The AA profiles of serum detected using high-performance liquid chromatography (HPLC) are shown in p < 0.05). Moreover, pigs fed a magnolol-supplemented diet tended to have higher dorsal muscle histidine, leucine, methionine, alanine, cysteine, and total AA contents (p < 0.10). Conversely, no significant differences in dorsal muscle arginine, isoleucine, lysine, phenylalanine, threonine, tryptophan, valine, aspartate, glycine, serine, asparagine, glutamine, and proline contents were detected between the two groups (p > 0.05).The AA profiles in the dorsal muscle, as determined using HPLC, are shown in SLC38A2/SNAT2), solute carrier family 1 member 5 (SLC1A5/ASCT2), and solute carrier family 7 member 1 (SLC7A1/CAT1), compared with the Con group (p < 0.05). However, there were no differences in the relative mRNA expression levels of AA transporters such as solute carrier family 7 member 9 , solute carrier family 3 member 1 (SLC3A1/rBAT), solute carrier family 1 member 3 (SLC1A3/EAAT1), solute carrier family 7 member 8 (SLC7A8/LAT2), solute carrier family 7 member 7 (+LAT1SLC7A7/y), and argininosuccinate synthase 1 (ASS1) between the Con and Mag groups (p > 0.05).Given the changes influenced by magnolol supplementation in serum AA profiles and the importance of AA transporters in the regulation of AA transport, the mRNA expression levels of the genes associated with AA transporters in both jejunum and ileum were examined . In the SLC1A5 and SLC7A1 were markedly higher in the Mag group than those in the Con group (p < 0.05). However, dietary magnolol supplementation did not affect the relative mRNA expression levels of SLC38A2, SLC7A9, SLC3A1, SLC1A3, SLC7A8, SLC7A7, and ASS1 (p > 0.05).In the ileum B, the reTo further investigate the serum metabolic profiles in growing pigs fed a magnolol-supplemented diet , the untp < 0.05, was used to identify the significantly different metabolites. In total, 20 metabolites with VIP > 1 and p < 0.05 were ultimately identified  were enriched and 16 metabolites  were decreased in the Mag group compared with the Con group.Next, the response permutation test (RPT) models B revealeentified . As showentified C, 4 metaD-glutamine and D-glutamate metabolism; phenylalanine metabolism; lysine degradation; alanine; aspartate and glutamate metabolism; and glycine, serine, and threonine metabolism), carbohydrate metabolism (butanoate metabolism and citrate cycle (tricarboxylic acid (TCA) cycle)), nucleotide metabolism (pyrimidine metabolism and aminoacyl-tRNA biosynthesis), and lipid metabolism (steroid hormone biosynthesis).Furthermore, a Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis A was perL-arginine was identified as the most crucial metabolite influencing AA metabolic pathway. A fold-change analysis obtained from the arginine concentration detection by UPLC-Orbitrap-MS/MS (p < 0.05), resulting in respective 2.42-fold and 1.59-fold increases.Through the analysis of key metabolites associated with the AA metabolic pathway, ap-MS/MS B and HPLap-MS/MS C was perEnsuring adequate nutrition during the animal’s growth period is crucial in modern agriculture to maximize genetic potential for growth . InsuffiThe assessment of the growth performance in animals provides critical evidence to support the use of magnolol as a feed additive in animal production. Although the beneficial effects of magnolol on poultry production and health have been extensively documented ,24,26,31Linwu ducklings [The serum biochemical indices serve as functional indicators that reflect the metabolic processes and nutrient deposition in animals . Althougucklings . These sHDL-C, which acts as a “lipid scavenger” in the bloodstream, not only promotes hepatic health and regulates cholesterol homeostasis but also participates in interactions with plasma proteins that have anti-inflammatory effects . Our stuDAO serves as a valuable blood biomarker to assess the integrity of the mechanical intestinal barrier, with increased levels indicating impaired mechanical barrier function. Moreover, the mechanical barrier function serves as the histological foundation that maintains intestinal barrier function and prevents the entry of harmful substances, such as bacteria and endotoxins, across the intestinal mucosa into bloodstream . DietaryOreochromis niloticus), demonstrating that dietary supplementation with magnolol significantly increases serum levels of IgG and IgM. Previous studies have also demonstrated that IgM production is dependent on ALB as its primary substrate [An increase in serum immunoglobulin levels is a clear indication of the enhanced innate immunity of animals, with IgG and IgM being the primary immunoglobulins that protect against pathogen invasion into the bloodstream and promote disease resistance . Our finubstrate , and an ubstrate ,45. TherThe cytokine IL-22, which is involved in tissue signaling, plays a pivotal role in hepatoprotection, tissue proliferation, and repair. Additionally, it also serves as a protective barrier against bacterial-induced damage and inflammation of the intestinal epithelium, while preserving the integrity of the intestinal barrier ,47. PrioSimilarly, IFN-γ, a proinflammatory cytokine, can enhance the ongoing immune response and facilitate apoptosis induction. The level of IFN-γ was modulated by IL-22, which exerted antagonistic effects on its activity . TherefoAAs not only serve as the fundamental building blocks for protein synthesis but also play pivotal roles in both development and the immune response . Blood fSkeletal muscles, which serve as the largest reservoir of AAs , can effSLC38A2, SLC1A5, and SLC7A1 in the jejunum was significantly higher in the Mag group than in the Con group. Additionally, the relative expressions of mRNA levels of SLC1A5 and SLC7A1 were also significantly higher in the ileum of pigs fed a magnolol-supplemented diet. Alanine–serine–cysteine amino acid transporter 2, encoded by SLC1A5, is capable of transporting a wide range of AAs, particularly methionine and proline in conjunction with the sodium-dependent neutral amino acid transporter 2, which is encoded by the SLC38A2 gene [SLC7A1, serves as an AA transporter mainly responsible for the transport of arginine, histidine, and lysine [As secondary transporters, AA transporters facilitated the transfer of AAs . To inve8A2 gene ,66. Addid lysine . The incd lysine ,68. TherD-glutamine and D-glutamate metabolism. Previous studies in mice showed that dietary supplementation with magnolol mainly regulated metabolic pathways associated with arginine and proline metabolism; alanine, aspartate, and glutamate metabolism; and tryptophan metabolism [Metabolomics is an effective tool to determine alterations in various metabolic pathways and biomarkers . Our stutabolism ,71, and A total of 42 healthy 70-day-old crossbred growing barrows (Duroc × Landrace × Large White) were randomly divided into 2 groups according to their body weight . Each group consisted of 7 replicates, with 3 pigs per replicate (pen). Pigs in 2 groups were fed the basal diet (CON) and the basal diet supplemented with 400 mg/kg magnolol (Mag), respectively. The experiment lasted for 35 days, including a 5-day adaptation period and a 30-day experimental period. The reared trial was selected from June to July at the Institute of Animal Science, Guangdong Academy of Agricultural Sciences, China. During the feeding experiment, the temperature was not controlled. The ambient temperature was within the range of 25–31 °C, and the humidity was approximately 65%, with a 13-hour natural light and 11-hour dark cycle. There were 14 pens in total, and all pens were located in one building. Pigs resided in adjacent individual concrete pens (4.5 m × 1.6 m) with concrete floors and catered with nipple drinkers and manual metal feeders and allowed ad libitum access to the diet and fresh water throughout the trial. The basal diet  meets thEach pig was weighed on day 1  and day 35  after fasting for 6 h to calculate the ADG (per pig). The feed intake of pigs was recorded for each pen weekly to calculate the ADFI (per pig), which was calculated based on the total feed intake per pen divided by the number of trial days (35 days) and the number of pigs in each pen (3 pigs). The F:G was computed as the average of feed intake divided by BW gain in each replicate.At the end of the trial, a fasting period of 6 h was implemented for all pigs, and one pig with approximately average BW (each group) was selected from each replicate. Blood was collected from the jugular vein, using non-heparin-coated vacutainer tubes, and centrifuged and separated to obtain serum. Pigs were euthanized by electrical stunning, followed by exsanguination, and the tissue of the mid-jejunum and mid-ileum was collected and placed into sterile Eppendorf tubes. Then, all samples were stored at −80 °C until measurement for serum biochemical indices, antioxidant capacity, inflammatory cytokines, AA profiles, and metabolome analysis.The basic serum biochemical indices, including TP, LDL-C, HDL-C, ALT, AST, ALB, Glu, urea, UA, and DAO, were analyzed using a Selectra XL Autoanalyzer . The assay kits were purchased from Biosino Bio-Tec . Furthermore, the levels of TNF-α, IFN-γ, IgG, IgA, IgM, IL-2, IL-10, and IL-22 were measured using commercial ELISA kits .w/v) and centrifuged . After filtering the supernatant with a 0.22 μm filter, a HPLC-L-8900 Amino Acid Analyzer  was used to measure the AA levels. Essential AAs included histidine, leucine, isoleucine, lysine, methionine, phenylalanine, threonine, valine, arginine, and tryptophan; and nonessential AAs consisted of alanine, aspartate, glutamate, glutamine, glycine, serine, tyrosine, cysteine, and asparagine.The serum and dorsal muscle samples were prepared according to a previously described method . Approxi−(∆∆Ct) [target − Ctβ−actin)treatment − (Cttarget − Ctβ−actin)control, and β-actin served as the reference housekeeping gene.Total RNA was extracted from jejunal and ileum tissue homogenates, using the TRIzol reagent . A Nanodrop 1000 spectrophotometer  was used to measure the concentrations of total RNA. Subsequently, the synthesis of cDNA was performed using a cDNA Synthesis Kit . Primers of selected genes are described in −(∆∆Ct) , where ∆p < 0.05 criteria. To make a further exploration of metabolic changes, the differential metabolites were analyzed on MetaboAnalyst 5.0 , utilizing the KEGG pathway enrichment analysis.The serum metabolite samples were pretreated and extracted, referring to previous studies ,74, but t-test, and GraphPad Prism 8.0.3 software  was used for graphical representation. All of the data are expressed as the mean ± standard error of the mean (SEM). Statistical significance was based on p < 0.05, and the trend of difference was considered to be 0.05 < p ≤ 0.10.The experimental raw data were processed using Microsoft Excel 2019. Then, the SPSS 26.0 software  was used to perform an independent sample The current study suggested that dietary supplementation with magnolol was able to enhance the absorption and utilization of AAs in growing pigs by upregulating the gene expression of key small intestinal AA transporters, promoting anti-inflammatory ability and potentially contributing to the improvement of intestinal barrier functions. The metabolomic analysis and KEGG enrichment analysis further showed that magnolol regulates AA metabolism pathways to promote skeletal muscle growth and development. However, the information regarding the biomarker of intestinal barrier functions in response to magnolol supplementation and the mechanisms underlying the effect of magnolol on the conversion of arginine to glutamate was limited. This study highlights the underlying mechanism by which magnolol exerted its effects on protein production, providing a potential alternative for harnessing the growth potential of pigs.