Type 2 diabetes mellitus (T2DM), a chronic low-grade inflammatory disease with high morbidity and mortality, is a serious threat to public health. Previously we demonstrated that a traditional Chinese medicine formulation, Jiedu Tongluo Tiaogan Formula (JDTL), exerted a favorable hypoglycemic effect due to unknown molecular mechanisms involving interactions among JDTL compounds and various cellular components. This study aimed to explore JDTL mechanisms for alleviating hyperglycemia using an integrated strategy incorporating system pharmacology, bioinformatics analysis, and experimental verification. This strategy entailed initial elucidation of JDTL chemical composition using fingerprint analysis via high performance liquid chromatography (HPLC). Next, functions of putative shared target genes and associated pathways were deduced using GO and KEGG pathway enrichment and molecular docking analyses. Ultimately, targets associated with JTDL anti-T2DM effects were found to be functionally associated with biological functions related to lipopolysaccharide and cytokine receptor binding. These results implicated PI3K-Akt signaling pathway involvement in JDTL anti-T2DM effects, as this pathway had been previously shown to play significant roles in glucose and lipid metabolism-related diseases. Furthermore, addition of JDTL to INS-1 and HepG2 cell cultures stimulated cellular mRNA-level and protein-level expression leading to enhanced production of IRS1, Akt, and PI3K. In summary, here JDTL bioactive ingredients, potential targets, and molecular mechanisms underlying JDTL anti-T2DM effects were identified using a multi-component, multi-target, and multi-channel analytical approach, thus providing an important scientific foundation to facilitate development of new drugs mechanistic strategies for preventing and treating T2DM. The prevalence of T2DM, one of the greatest emerging health crises worldwide, is projected to increase by >50% globally by 2045 , with hiTraditional Chinese medicine (TCM) treats diseases based on a holistic viewpoint that recognizes the interconnectedness of all body systems. Therefore, TCM possesses advantages based on its pleiotropic, multi-target, prospective, and stable features that enable it to alleviate T2DM and other complex chronic diseases . MoreoveNetwork pharmacology, an indispensable method for exploring the potential mechanism underlying TCM effects, provides a new research paradigm that may transform the clinical viewpoint of TCM from that of an empirical medicine into that of an evidence-based medicine . Networkin vitro experiments were conducted with INS-1 and HepG2 cells to further explore whether JDTL-associated anti-T2DM mechanisms predicted using integrated network pharmacological analysis played significant roles in observed JDTL anti-T2DM effects in cultured cells. The workflow of this study is shown in The aim of this study was to investigate potential targets and mechanisms of action associated with JDTL alleviation of T2DM. First, active JDTL ingredients against T2DM were identified. Next, potential molecular mechanisms associated with JDTL effects were determined using network pharmacology-based analysis followed by molecular docking analysis to predict binding affinities among JDTL constituent compounds and putative molecular network hub protein targets. Finally, in order to elucidate mechanisms underlying JDTL alleviation of T2DM, Based on reference standard data, chromatographic elution behaviors, chemical composition data, mass fragment patterns, and HPLC results, five major peaks corresponding to five major compound constituents of a water-based JDTL extract  were detFollowing the chemical profiling detected by HPLC system and collected from the existing database, we predicted the putative targets of the chemical constituents containing in JDTL based on the similarities in drug structures and functions as described in our previous studies. A total of 205 active compounds with structural and functional similarities to JDTL constituent compounds were identified by searching the database . ThereafShared JDTL and T2DM common targets were imported into the STRING database then their interrelationships were visualized as a PPI network with an average node degree value of 17.1 that contained 148 nodes and 1305 edges. In order to better explain interrelationships among targets, data in tab-separated value (TSV) format were imported into Cytoscape 3.6.2 then results were depicted as network nodes of various sizes and colors based on numbers of combined targets  for each protein, as shown in The degree values of the first 30 genes are shown in Taking into account the complex mechanisms underlying JDTL treatment effects on T2DM, integration of key functional terms and pathways were identified via corresponding GO and KEGG database searches using R software that resulted in construction of a complete T2DM-related path diagram. GO analysis was then conducted to assign identified drug targets to the three functional GO categories, namely molecular function (MF), cellular composition (CC), and biological process (BP), as shown in In this study, molecular docking was used to identify potential binding interactions between JDTL bioactive components and T2DM-associated hub gene targets . To confMTT assays were performed that demonstrated that 24-hour treatment with JDTL at concentrations of 50, 100, and 200 μg/mL had no effect on viability of INS-1 and HepG2 cells . Thus, tResults of GSIS analysis showed that after glucose starvation by culture under low glucose (LG) conditions (5.0 mM glucose) for one hour, normal GSIS by INS-1 cells was observed for the 5.0 mM group, while relatively lower levels of GSIS by INS-1 cells in high-glucose (HG) groups were observed. Following the same glucose starvation protocol, INS-1 cells were stimulated with a high level of glucose (30 mM) that led to decreased insulin secretion as compared to that of the control group. Conversely, insulin secretion function was greatly increased after JDTL treatment . In addiAccording to network pharmacology analysis and molecular docking results obtained in this study, we speculated that JDTL treatment-based alleviation of T2DM might reflect JDTL-induced regulation of glucose and lipid metabolism through activation of the PI3K-Akt signaling pathway. To test this hypothesis, Western blot and qRT-PCR analyses were conducted to determine total protein-level and mRNA-level expression associated with PI3K and Akt target proteins.PI3K and Akt mRNA expression levels in INS-1 and HepG2 cells were assessed using qRT-PCR. As shown in In order to determine molecular mechanisms underlying JDTL effects, we conducted network pharmacological analysis of key proteins within integrated “T2DM-related pathways,” including the PI3K-Akt signaling pathway. To confirm activation of the PI3K-Akt signaling pathway, we measured IRS, PI3K and Akt proteins in INS-1 cells and HepG2 cells using Western blotting. To assess PI3K-Akt signaling pathway activation status, we measured IRS, PI3K, and Akt protein levels in INS-1 and HepG2 cells using Western blot analysis. The results showed that the HG-exposed INS-1 group cells exhibited significantly decreased expression of p-IRS, p-PI3K, and p-Akt proteins relative to corresponding control levels of these proteins, while JDTL treatment inhibited decreases in levels of these proteins in HG-exposed INS-1 cells , 12B. GLT2DM is one of the most prominent and detrimental chronic diseases of humans, due to its many complications, low cure rate, and management challenges. Nevertheless, T2DM may be treatable with TCM formulations, which are based on highly intuitive principles for achieving clinically curative effects that have shown to be effective in clinical practice .Notably, results of various research reports suggest that JDTL active ingredients may regulate glucose levels. For example, bioactive components of Coptidis Rhizoma have been shown to improve disordered glucose and lipid metabolism in T2DM animal models by acting on a variety of signaling pathways to ultimately reduce effects of glucose toxicity , 22. Meain vitro experiments were conducted to assess the reliability of our network pharmacology prediction results. The results of these analyses led to identification of potential JDTL bioactive compounds, targets and signaling pathways associated with JDTL alleviation of T2DM that we report here for the first time. In addition, results of PPI network topology analysis highlighted AKT1, TNF, TP53, IL6, and JUN as the top five most important JDTL targets. Moreover, molecular docking results demonstrated that JDTL constituent compounds chlorogenic acid, calycosin-7-glucoside, salvianolic acid B, aloe-emodin, and haragoside could interact with Akt with good binding affinity.In this study, we attempted to identify JDTL active components, potential targets, and mechanisms of action using HPLC and network pharmacology. HPLC results revealed that bioactive components of JDTL included chlorogenic acid, calycosin-7-glucoside, salvianolic acid B, aloe-emodin, and haragoside, among others. Network pharmacology analysis revealed that mechanisms underlying JDTL effects for alleviating T2DM involved a total of 210 active components, 153 potential targets, and 167 related signaling pathways. Specifically, network hub proteins  and certain signaling pathways  were found to be associated with mechanisms linked to JDTL anti-T2DM effects. Next, AutoDockTools was used to conduct molecular docking of JDTL compounds with hub proteins belonging to the three key pathways predicted by KEGG analysis to be associated with JDTL anti-T2DM effects. After that, KEGG pathway enrichment and molecular docking analyses focusing on the PI3K-Akt signaling pathway were conducted to more precisely determine the JDTL mechanism of action. Finally, Pivotal JDTL active ingredients most highly related to biological functions associated with lipopolysaccharide and cell proliferation included chlorogenic acid, calycosin-7-glucoside, salvianolic acid B, aloe-emodin, and haragoside. These compounds may thus play key roles in JDTL amelioration of T2DM, warranting future studies. Intriguingly, chlorogenic acid has been shown to modulate lipid and glucose metabolic regulation associated with both genetically and environmentally induced metabolic disorders, such as hepatic steatosis, cardiovascular disease, diabetes, and obesity , 28. CalAkt is a serine/threonine protein kinase, a downstream signal protein of PI3K, which mediates cell proliferation, migration, differentiation, survival, or glucose metabolism , 39. Aktin vitro cell experiments conducted in this work, JDTL treatment markedly increased levels of PI3K and Akt proteins that exhibited abnormally decreased expression in HG-exposed INS-1 and HepG2 cells, implying that JDTL exerted regulatory effects on the PI3K-Akt signaling pathway. Finally, we added the selective PI3K inhibitor LY294002 to cells to verify that JDTL acted through the PI3K-Akt pathway, as predicted here using network pharmacology and molecular docking analyses. Ultimately, the results of this study demonstrated that JDTL exerted a therapeutic anti-T2DM effect based on a mechanism of action predicted in advance using network pharmacology analysis .Oral bioavailability (OB) and drug similarity (DL) are two important parameters used to evaluate active components of drugs during research and development stages to assess drug absorption and distribution characteristics in the human body. In this study, active compounds of JDTL were screened against the Traditional Chinese Medicine Systems Pharmacology (TCMSP) chemical database based on thresholds of OB ≥ 30% and DL ≥ 0.18. Next, prospective targets were analyzed using the UniProt knowledge database (http://www.genecards.org/) network library, was searched for T2DM-related targets, with results filtered based on a correlation value of ≥30 as the screening parameter. The other database, the Online Mendelian Inheritance in Man (OMIM) database (http://www.omim.org/), was used for target evaluation. In order to ensure the accurateness of the final results, redundant and erroneous targets were removed then the final set of prospective targets was evaluated using UniProt.To investigate roles of JDTL putative targets in T2DM, we collected a list of known T2DM-related genes from two databases. One database, the GeneCards v4.14 (https://string-db.org/). Interaction relationship results were limited to the species “Homo sapiens” with confidence scores of >0.7. Next, the results were analyzed using Cytoscape 3.6.2 to construct a PPI network.Intersecting results obtained for drug targets and T2DM-related genes were depicted using a Venn diagram then intersecting results were imported into the STRING database  was used to perform cluster analysis of PPI networks. Screening conditions included node score cutoff = 0.2, k core = 2, maximum depth = 100, and degree cutoff = 2.http://www.bioconductor.org/about/) to perform GO function enrichment analysis on common targets, draw GO analysis entry diagrams, and obtain GO terms from categories of biological process (BP), molecular function (MF) and cell component (CC) followed by selection of results with P values < 0.05. Next, targets enriched for common KEGG pathways (P < 0.05) were identified and the results were expressed as a bubble chart.In order to investigate key cell functions and signaling pathways that were mainly affected by key T2DM-associated targets of JDTL treatment, we used clusterProfile version 3.6.2 of the R package of Bioconductor . According to the standard procedure described in the Chinese Pharmacopoeia (2015 edition), 15 g of Huanglian (Coptis chinensis Franch), 9 g of Dahuang (Radix Rhei Et Rhizome), 15 g of Huangqi , 15 g of Danshen , and 10 g of Chaihu (Bupleuri Radix) were suspended in 1000 mL of reverse osmosis water then the mixture was simmered at 100° C for approximately 30 min until the volume was 300 mL to generate an extract. This procedure was repeated three times to generate a final aqueous extract, which was filtered and centrifuged then the supernatant was freeze-dried under vacuum to produce a powder with a yield of 13.64% . The powINS-1 and HepG2 cells were purchased from the Cell Center of Peking Union Medical College Hospital and maintained separately in RPMI-1640 medium  or DMEM (Gibco or Thermo Fisher Scientific) containing 10% fetal bovine serum, 100 U/mL penicillin, and 100 μg/mL streptomycin in an incubator maintained at 37° C with 5% CO2 and humidification. Throughout the entire cell culture process, strict sterility was maintained. In order to explore JDTL effects and its mechanism of action, INS-1 and HepG2 cells were incubated with 30 mM glucose (HG) for 24 h in the presence or absence of JDTL (50-200 mg/mL). Meanwhile, cells of the control group were cultured in 1640 or DMEM medium for 24 h. All cells used in experiments were initially collected from maintenance cultures in logarithmic growth phase.4 cells/well) then were cultured for 24 h prior to supplementation with JDTL of known concentration . Next, spent medium was removed and replaced with MTT -2,5-diphenyltetrazolium bromide) solution (0.5 mg/mL in PBS) followed by incubation of cells for 4 h at 37° C. Next, 150 μL of DMSO was added to each well then absorbance readings (at 570 nm) were recorded using a microplate reader .INS-1 and HepG2 cells were respectively seeded into wells of 96-well plates (105 cells/well) were seeded into wells of 96-well plates containing glucose (5 or 30 mM) followed by incubation for 48 h then incubation with 0, 50, 100, 200 μg/mL JDTL for 24 h. Thereafter, the cells were washed thoroughly with PBS followed by incubation in Krebs-Ringer bicarbonate HEPES buffer , pH 7.4) for 1 h. The buffer was replaced with KRBB buffer containing 5 mmol/L glucose (LG) or 30 mmol/L glucose (HG) followed by incubation at 37° C for 1 h. Next, the supernatant was collected then the insulin concentration in the supernatant was determined using a Rat/Mouse Insulin Elisa Kit .INS-1 cells  at an excitation wavelength of 485 nm and emission wavelength of 538 nm.Total RNA was extracted from INS-1 and HepG2 cells using TRIzol reagent  and reverse transcribed using the First Strand cDNA synthesis kit  according to manufacturer’s instructions. The RT-qPCR procedure was performed as follows: denaturation at 95° C for 15 min followed by 40 cycles that included denaturation at 95° C for 10 s, annealing at 60° C for 20 s, and elongation at 72° C for 30 s. The primers used to amplify PI3K, Akt, and GAPDH genes, were synthesized by Invitrogen :The expression level of GAPDH was used as internal control.Western blot procedures were performed as previously described. First, INS-1 and HepG2 cells that received different treatments were harvested and lysed with radioimmunoprecipitation assay (RIPA) buffer  supplemented with protease and phosphatase inhibitors . The following primary antibodies were used as probes: anti-IRS, anti-phosphor-Ser612-IRS-1, anti-PI3K, anti-phosphor-Thy458-PI3K, anti-Akt, anti-phosphor-Ser473-Akt, GIUT4, and anti-GAPDH, which were obtained from Cell Signaling Technology . Quantification of relative changes in protein levels (arbitrary units expressed as percentage of the control protein level) was performed using Image J software.P < 0.05.GraphPad Prism 6.0 software was used for statistical analysis of the data. Data are presented as mean ± SD from three different experiments. The results were considered statistically significant at The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation, to any qualified researcher.Supplementary Table 1


ERT. This study reports that MKK7 is required for JNK activation both in vitro and in vivo. Additionally, we demonstrated that MKK7 in macrophages is necessary for lipopolysaccharide (LPS)-induced cytokine production, M1 polarization, and migration, which appear to be a major contributor to the inflammatory response in vivo. Conversely, MKK4 plays a significant, but minor role in cytokine production in vivo.Mitogen kinase kinase 4 (MKK4) and mitogen kinase kinase 7 (MKK7) are members of the MAP2K family that can activate downstream mitogen-activated protein kinases (MAPKs). MKK4 has been implicated in the activation of both c-Jun N-terminal kinase (JNK) and p38 MAPK, while MKK7 has been reported to activate only JNK in response to different stimuli. The stimuli, as well as the cell type determine which MAP2K member will mediate a given response. In various cell types, MKK7 contributes to the activation of downstream MAPKs, JNK, which is known to regulate essential cellular processes, such as cell death, differentiation, stress response, and cytokine secretion. Previous studies have also implicated the role of MKK7 in stress signaling pathways and cytokine production. However, little is known about the degree to which MKK4 and MKK7 contribute to innate immune responses in macrophages or during inflammation in vivo. To address this question and to elucidate the role of MKK4 and MKK7 in macrophage and in vivo, we developed MKK4- and MKK7-deficient mouse models with tamoxifen-inducible Rosa26 Cre The mitogen-activated protein kinases (MAPKs) are an evolutionarily conserved signaling mechanism that controls a range of important cellular functions, including differentiation, stress response, and apoptosis ,2. StresBoth mitogen kinase kinase 4 (MKK4) and mitogen kinase kinase 7 (MKK7) are MAP2K family members. While MKK4 has been implicated in the activation of both downstream stress-activated MAPKs, JNK and p38 ,10, MKK7The innate immune response is an evolutionarily conserved response and the first line of defense against harmful pathogens . The infPro-inflammatory cytokines, such as tumor necrosis factor-alpha (TNFα) and bacterial lipopolysaccharides (LPS), activate MAPKs, JNK, and p38 . HoweverERT mice (ERT-Mkk4-floxed (Mkk4∆/∆) and Rosa26-CreERT-Mkk7-floxed (Mkk7∆/∆) mice demonstrated the specific disruption of the Mkk4 and Mkk7 genes  on the cell surface which activates the signal transduction mechanisms leading to the phosphorylation of MKK4 and MKK7 protein kinases . We usedn of JNK A. Conver reduced A.ERT-Mkk4-floxed and Rosa26-CreERT-Mkk7-floxed conditional mice were treated with 4-hydroxytamoxifen for respective gene deletion. Similar to the MEFs, treatment with TNFα to MKK4-deficient BMDMs caused only minor changes in TNFα-stimulated JNK activation  isolated from Rosa26-Cretivation B. Howevetivation B. We alsMkk4∆/∆ and Mkk7∆/∆ BMDMs to LPS treatment. Our data showed that, similar to TNFα-induced MEFs, MKK4 deficiency produces only a moderate decrease in JNK and p38 activation in LPS-induced macrophages  than the wild-type control cells A. Howeve Mkk4∆/∆ A. We als Mkk4∆/∆ B. CollecMAPK signaling has been implicated in macrophage migration and invasion. Healthy macrophages require robust migration and invasion to execute their proper function; thus, highlighting the importance of determining the role of MKK4 and MKK7 in macrophage migration and invasion. We found that MKK4 deficiency leads to a modest disruption of cell migration and invasion in macrophages , while MERT, Rosa26-CreERT-Mkk4-floxed and Rosa26-CreERT-Mkk7-floxed conditional mice were injected with a single dose of tamoxifen for respective gene deletion. After 2 weeks of gene deletion, all three group of mice injected with endotoxin LPS. Treatment of wild-type mice with LPS caused increased production of inflammatory cytokines TNFα, IL6, IL1α, and IL1β in the blood  and M2 (IL6) macrophages in isolated BMDM cells of the controls, Mkk4∆/∆ and Mkk7∆/∆ mice. Results from RT-qPCR analysis demonstrated that macrophage-specific MKK7-deficiency decreased the expression of M1 marker genes (TNFα) in comparison to the controls (Macrophage polarization plays an important role during inflammation . The maccontrols A. Moreovcontrols B. These ERT and Rosa26-CreERT-Jnk1-floxed Jnk2−/− mice and treated them with 4-hydroxytamoxifen for gene deletion (Jnk1∆/∆−/−Jnk2). These control Rosa26-CreERT and Jnk1∆/∆−/−Jnk2 macrophages were treated with LPS for 24 h. Similar to MKK7, LPS-treated JNK1/2- deficient BMDMs secrete markedly less TNFα and IL6 than wild-type cells  pathways both play an essential role in cytokine production . SpecifiJNK requires phosphorylation on both Thr180 and Tyr182 for its complete activation . JNK phoJNK and p38 are long-studied stress signaling cascades essential for a broad range of vital cellular and organismal activities. Therefore, the use of small molecular inhibitors against JNK or p38 to prevent cytokine production and inflammation would likely be accompanied by severe side effects, making them poor drug targets. Several members of the MAP2K and MAP3K tier of kinases were shown to activate JNK and p38 pathways ,16,26. SMkk4 gene  with proteinase inhibitors  and phosphatase inhibitors . Protein extracts (50 µg of protein) in β-mercaptoethanol containing SDS sample buffer were separated in 4% to 12% gradient SDS-polyacrylamide gels (Bio-Rad #456-8094) and transferred to nitrocellulose membranes  and incubated with a primary antibody with 1:1000 dilution overnight. Membranes were washed in Tris-buffered saline (TBS) with 0.1% Tween-20 for three times and incubated in HRP conjugated secondary antibody for 1 h. Immunocomplexes were visualized with horseradish peroxidase-conjugated secondary antibodies and detected with a Clarity Western ECL substrate . Images were acquired on a chemiluminescent imager  and quantified using Image J .Plasma cytokines and cytokines secreted in cell culture media were measured using ELISA  by following the manufacturer’s instructions .Primary antibodies were obtained from Cell Signaling , BD Pharmingen , and Sigma .p value < 0.05 was considered significant. All statistics were done using StatView version 5.0  or GraphPad Prism version 5 .All data are expressed as mean ± SE, and the numbers of independent experiments are indicated. Statistical comparisons were conducted between 2 groups by use of Student t-test or Mann–Whitney U test as appropriate. Multiple groups were compared with either 1-way Kruskal–Wallis or ANOVA with a post hoc Tukey–Kramer multiple comparisons test as indicated in legends. A


Intrinsically disordered proteins (IDPs) can engage in promiscuous interactions with their protein targets; however, it is not clear how this feature is encoded in the primary sequence of the IDPs and to what extent the surface properties and the shape of the binding cavity dictate the binding mode and the final bound conformation. Here we show, using a combination of nuclear magnetic resonance (NMR) spectroscopy and isothermal titration calorimetry (ITC), that the promiscuous interaction of the intrinsically disordered regulatory domain of the mitogen-activated protein kinase kinase MKK4 with p38α and JNK1 is facilitated by folding-upon-binding into two different conformations, despite the high sequence conservation and structural homology between p38α and JNK1. Our results support a model whereby the specific surface properties of JNK1 and p38α dictate the bound conformation of MKK4 and that enthalpy–entropy compensation plays a major role in maintaining comparable binding affinities for MKK4 towards the two kinases. Over the last two decades, it has become increasingly clear that a large fraction up to 40%) of the human proteome is intrinsically disordered or contains disordered regions of significant length ,2,3,4. T0% of theIn addition to these thermodynamic considerations, IDPs can be promiscuous in nature i.e., they can interact with different partner proteins, even via the same linear motif . One pro1–5–X1–6–ΦL–X1–3–ΦA–X–ΦB  [We study the promiscuous interaction of an IDP within the mitogen-activated protein kinase (MAPK) cell signaling pathways. The MAPK pathways are essential components of eukaryotic signal transduction networks that direct appropriate responses to cellular stress , and fouresidue) . Dockingresidue) ,32. Thisresidue) .Here we show, using a combination of nuclear magnetic resonance (NMR) spectroscopy and isothermal titration calorimetry (ITC), that the promiscuous interaction of the disordered regulatory domain of MKK4 with p38α and JNK1 is facilitated by folding-upon-binding into two different conformations, despite the high sequence conservation and structural homology between the two kinases. Our results support a model whereby the specific surface properties of the two kinases dictate the bound conformation of MKK4 and that enthalpy–entropy compensation plays a major role in maintaining comparable binding affinities for MKK4 towards p38α and JNK1.15N-labeled (for NMR) or unlabeled (for ITC). The regulatory domain of MKK4 , the JNK1 kinase (residues 1–364 of human JNK1 (isoform α1) with a C-terminal 6xHis tag, Uniprot P45983) and the p38α kinase  were expressed and purified as described previously ,35. The v/v), 0.5 mM TCEP). MKK4 with a concentration of 570 μM was titrated into a solution of JNK1 with a concentration of 42 μM. ITC experiments were carried out in the presence of the N-terminal thioredoxin and 6xHis tag on MKK4 to allow for accurate protein concentration determination by UV absorbance using the theoretical molar extinction coefficient calculated from the primary sequence of the fusion protein. A control experiment shows that JNK1 does not bind to the his-tagged thioredoxin [ITC measurements of the JNK1:MKK4 complex were performed on a MicroCal iTC200  at 20 °C. Injections of 1.5 μL were carried out every 180 s, 26 in total at a stirring speed of 800 rpm. Prior to the experiments, any impurities or aggregates of MKK4 and JNK1 were removed by size-exclusion chromatography in the ITC buffer  in 50 mM HEPES pH 7.1, 150 mM NaCl, 2 mM dithiothreitol (DTT), 5% (v/v) glycerol at 5 °C. The spectral assignments of MKK4 were obtained previously at 5 °C [15N-labeled MKK4 with unlabeled JNK1 was carried out for the following concentrations of MKK4 and JNK1: 120:0 μM (0%), 120:24 μM (20%), 120:48 μM (40%), 68:46 μM (68%), 50:45 μM (90%). For each titration point, an 1H-15N HSQC spectrum was measured at a 1H frequency of 600 MHz, and the intensities were extracted and normalized to the intensities in the spectrum recorded in the absence of JNK1 by accounting for the difference in protein concentration and the number of scans. All NMR experiments were carried out using  at 5 °C . A titra15N spin relaxation rates R1 and R1ρ in MKK4 were measured at 5 °C and a 1H frequency of 600 MHz using HSQC-detected pulse sequences [R1ρ experiments. The decay of magnetization was sampled at 70, 130, 10, 90, 230, 30, 210, 50, 170, 1 ms with a repeat at 70 ms for the R1ρ experiments, and at 0, 0.6, 0.08, 1.6, 0.4, 1.8, 1.04, 0.8, 0.2 s with a repeat at 0.6 s for the R1 experiments. Errors on the relaxation rates were estimated from Monte-Carlo simulations using the noise in each plane of the pseudo-3D spectra as errors on measured peak intensities. The concentration of MKK4 (200 μM) was kept constant, while varying the amount JNK1 kinase: 0%, 10%, 30% and 50% molar fraction for the R1ρ experiments and 0%, 30% and 50% for the R1 experiments. The measured 15N R1 rates are identical within experimental error for all molar fractions of JNK1, allowing us to use the most precise R1 dataset (molar fraction of 0% JNK1) to correct for resonance offset [R2 = (R1ρ − R1cos2θ)/sin2θ where θ = arctan (ω1/Δω), ω1 being the spin lock field strength (1.5 kHz in this case) and Δω the resonance offset from the 15N carrier frequency. Errors on the derived R2 relaxation rates were calculated from the experimental errors on R1ρ and R1.equences . A spin e offset . To thisR2, of the MKK4:JNK1 complex, we first assumed that the rotational correlation time of JNK1 is similar to its structural homologue p38α. A rotational correlation time of τc = 21.8 ns of p38α at 25 °C was determined previously from a global analysis of 15N relaxation rates. Under our experimental conditions (5 °C and 5% glycerol), we obtained a correlation time of 47.1 ns by accounting for the change in viscosity [R2 rate of 69 s−1 at 600 MHz. This value represents a lower value for the relaxation rate in the MKK4:JNK1 complex, as the disordered chain of MKK4 presumably would induce a dragging effect leading to a significantly larger τc value, as predicted previously [To estimate a lower limit for the transverse relaxation rate, eviously .15N chemical exchange saturation transfer (CEST) experiments [1H frequency of 700 MHz or 850 MHz. A B1 saturating field of 30 Hz (free MKK4) and 21 Hz (MKK4 with JNK1) was used during a constant period of 300 ms. The data were analyzed according to a two-site exchange model using ChemEx (https://github.com/gbouvignies/ChemEx accessed on 25 May 2021) as described in the main text. The eriments  were carThe NMR exchange experiments (CEST and CPMG relaxation dispersion) on MKK4 with the p38α kinase were previously acquired . Here, w1H-15N HSQC spectra of MKK4 with increasing amounts of JNK1. Line broadening is observed for multiple residues upon addition of JNK1 demonstrating a clear interaction, while chemical shift changes are negligible (40KRKALKLNF48) experiencing the most pronounced line broadening (We studied the interaction between the regulatory domain of MKK4 (residues 12–86) with the JNK1 kinase by recording gligible . We quanoadening . This su15N R1ρ relaxation rates using a spin lock field of 1.5 kHz for different molar fractions of JNK1 . The rates were converted into R2 relaxation rates by taking off-resonance effects into account . The small contribution from this large R2 rate to the measured relaxation rates in MKK4 suggests that the exchange between free and bound MKK4 is slow on the chemical shift time scale.To study the dynamics of the complex in more detail, we acquired  account a. Only aobserved b. In theR2 relaxation rates of MKK4 with 50% and 6% molar ratio of JNK1 and p38α, respectively, are similar, demonstrating the influence of the two different exchange regimes on the mea-sured relaxation rates  than the p38α complex (KD = 4.1 μM). Dissection of the binding free energies into enthalpic and entropic contributions shows that the JNK1 complex is characterized by a small, unfavorable entropic contribution to binding  and the basic residues (CD groove). This is in agreement with the observation that p38α displays a wider binding groove and a larger distance between the ΦL pocket and the CD groove compared to JNK1 [We compared these observations to solved crystal structures of docking site motifs in complex with JNK1 or p38α b–i. We f to JNK1 .L and ΦA pockets with the basic residues immediately preceding the ΦL pocket. In contrast, the docking motif of the substrate NFAT4 has only one residue between each hydrophobic pocket, but with two residues between the basic part of the motif and the ΦL pocket  [Interestingly, the activator MKK7 shows two different conformations in complex with JNK1 that differ in the specific residues occupying the three hydrophobic pockets (Φ and ΦB) . Thus, c and ΦB)   arising from the formation of two intra-helical hydrogen bonds. The exchange experiments demonstrate that the three-times higher binding affinity for the JNK1 complex mainly arises from an off-rate contribution. The on-rate for IDP complexes is in many cases dominated by electrostatic interactions (“steering”) through charged re-sidues surrounding the binding pocket . The higWe note that extensive crystallization trials, carried out by us and others , have sy


Introduction: Heart failure with preserved ejection fraction (HFpEF) is associated with disrupted intestinal epithelial function, resulting from intestinal congestion. Intestinal congestion changes the morphology and permeability of the intestinal wall, and it becomes easy for the gut microbiota to change and transfer. Intervention on gut microbiota may become a new target for HFpEF treatment. However, the characteristics of gut microbiota in patients with HFpEF remain unknown. This preliminary report aims to detect the structure of gut microbiota in HFpEF patients so as to explore their characteristic changes, thereby providing a theoretical basis for future research.Methods: This research recruited 30 patients diagnosed with HFpEF and 30 healthy individuals. Stool specimens of research subjects were collected separately, and the microarray analyses of gut microbiota were conducted by Illumina high-throughput DNA sequencing. The differences in gut microbiota composition, alpha diversity, and beta diversity between the two groups were finally obtained.Results: The composition of gut microbiota was significantly different between the two groups. At the phylum classification level, the abundance of Synergistetes tended to be higher in the HFpEF group (P = 0.012). At genus classification level, the abundance of Butyricicoccus (P < 0.001), Sutterella (P = 0.004), Lachnospira (P = 0.003), and Ruminiclostridium (P = 0.009) in the HFpEF group were lower, while the abundance of Enterococcus (P < 0.001) and Lactobacillus (P = 0.005) were higher. According to the Chao index of alpha diversity analysis, HFpEF patients showed a nominally significant lower species richness when compared with controls (P = 0.046). However, there was no statistical difference in the Shannon index (P = 0.159) and Simpson index (P = 0.495), indicating that there was no difference in species diversity between the two groups. Beta diversity analysis revealed a highly significant separation of HFpEF patients and controls.Conclusions: An imbalance in the gut microbiota of HFpEF patients was observed. Patients with HFpEF have an increased abundance of microbiota associated with inflammation and a decreased abundance of microbiota associated with anti-inflammatory effects in the gut environment. In line with that, the species richness of gut microbiota in HFpEF patients tended to be lower. Heart failure with preserved ejection fraction (HFpEF) is a common cardiovascular disease with a poor prognosis . In spitThe gut microbiota resides in the intestine of hosts and participates in various physiological processes of hosts. According to the classification method of biological research, gut microbiota can be classified into several types with different characteristics at seven levels, which are called a kingdom, phylum, class, order, family, genus, and species. At the phylum classification level, the gut microbiota in the human body can be divided into six main subtypes, including Bacteroidetes, Firmicutes, Proteobacteria, Actinobacteria, Fusobacteria, and Verrucomicrobia. Among them, Firmicutes and Bacteroidetes are the dominant microbiota in the healthy human body. The gut microbiota remains relatively stable. However, the changes in physiological functions can cause an imbalance of gut microbiota, which in turn can further cause a series of pathological changes in the human body. Dysbiosis of gut microbiota has been proposed to be related to several diseases including diabetes, hypertension, atherosclerosis, thrombotic events, and infectious diseases (such as tuberculosis) –6. For eThe gut hypothesis of heart failure (HF) is a hot spot in the field of cardiovascular research. It has been proposed that HF is associated with disrupted intestinal epithelial function, likely as a consequence of reduced intestinal perfusion. HF patients are also accompanied by intestinal congestion. Intestinal ischemia and congestion change the morphology and permeability of the intestinal wall, and the gut microbiota is prone to change and shift. The imbalance and displacement of gut microbiota further induce or aggravate systemic inflammation, which affects the progression of HF –12. The Heart failure with preserved ejection fraction is a kind of heart failure characterized by diastolic dysfunction. HFpEF is associated with disrupted intestinal epithelial function, likely as a consequence of intestinal congestion, which also changes the morphology and permeability of the intestinal wall, and the gut microbiota is prone to change and shift –19.However, recently published research investigating this topic is all aimed at patients diagnosed with heart failure with reduced ejection fraction (HFrEF). Studies on the gut microbiota in HFrEF patients have identified a reduction in gut microbial diversity . WhetherThis study has been approved by the Ethics Review Board of the First Affiliated Hospital of Soochow University and Dushu Lake Hospital Affiliated to Soochow University and is a preliminary report of study registered in the Chinese Clinical Trial Registry (ChiCTR2100050121). Research subjects were assessed for eligibility and written informed consent.This research recruited 30 patients diagnosed with HFpEF between August 2020 and October 2021 and 30 people who underwent physical examination in the same hospital. HFpEF patients were approached during their regular clinic visits.The inclusion criteria of the HFpEF group required compliance with the HFpEF diagnostic criteria in the “2021 ESC Guidelines for the Heart Failure” , New York Heart Association (NYHA) classification, main diagnosis, and past medical history of the two groups were available at the inception of the study. Laboratory tests such as blood routine, liver function, kidney function, and blood lipids were carried out within 24 h. Echocardiographic data of HFpEF patients such as left ventricular ejection fraction (LVEF) were also recorded. Clinical characteristics are presented in The DNA of gut microbiota was extracted by using the QIAamp DNA stool kit. We designed the target region and fusion primers according to the requirements of the sequencing platform and used a two-step method for PCR amplification. Variable regions V4–V5 of the 16S rRNA gene were amplified. The PCR amplification product obtained in the previous step was recovered by using 2% agarose gel. We used the AxyPrep DNA Gel Extraction Kit to purify the amplified PCR product. Finally, we used the Illumina sequencing platform to perform high-throughput sequencing on the samples that we collected.t-test was used when there was no deviation. Rank-abundance distribution curves and VEEN picture based on an operational taxonomic unit (OTU) were also used to compare the composition of gut microbiota between the two groups. When testing the differences in alpha diversity, the Wilcoxon rank sum test was used to compare three indexes  between the two groups when the value distribution deviated from normality. The principal co-ordinates analysis (PCoA) chart based on Bray-Curtis was used to present the results of beta diversity analysis, and Anosim analysis was carried out further. We also performed a subgroup analysis of the HFpEF group according to their etiologies. Alpha diversity analysis and beta diversity analysis were calculated by using R.The differences in gut microbiota between the two groups were mainly presented in three aspects, which included the composition of gut microbiota, alpha diversity, and beta diversity. The composition of gut microbiota between the two groups was presented at the classification level of phylum and genus. Wilcoxon rank sum test was used to compare the abundance of each microbiota when the value distribution deviated from normality, while two samples This study mainly analyzed the composition of gut microbiota at the classification levels of phylum and genus and compared the differences in gut microbiota composition between the two groups.P = 0.012). In other words, the abundance of Synergistetes tended to be higher in the HFpEF group when compared with the control group . The result indicated that the HFpEF group mainly included Bacteroides, Firmicutes, Proteobacteria, Actinobacteria, Fusobacteria, Tenerictes, Verrucomicrobia, Synergetes, Lentisphaerae, Cyanobacteria, Spirochaeta, and Unclassified microbiota. On the other hand, the control group consisted of Bacteroides, Firmicutes, Proteobacteria, Actinobacteria, Fusobacteria, Tenerictes, Verrucomicrobia, Synergistetes, Lentisphaerae, and Unclassified. The microbiota with the highest abundance in HFpEF patients and controls were Bacteroides, Firmicutes, and Proteobacteria. The microbiota with a statistically significant difference at the phylum classification level was Synergistetes (ol group .P < 0.001), Sutterella (P = 0.004), Lachnospira (P = 0.003), and Ruminiclostridium (P=0.009) in the HFpEF group were lower than that in the control group, while the abundance of Enterococcus (P < 0.001) and Lactobacillus (P = 0.005) were higher  analysis showed that the characteristic microbiota in the HFpEF group was Enterococcus, Lactobacillus, et al., while in the control group were Sutterella, Lachnospira, Ruminiclostridium, Butyricicoccus, et al. .The detected sequences in Illumina high-throughput DNA sequencing can be classified according to a certain similarity. Operational taxonomic unit (OTU) refers to the sequences grouped by a certain similarity. We set 97% as the critical value, that is, if the sequence similarity ≥ 97%, it can be divided into the same OTU.We drew Rank-abundance distribution curves and VEEN picture based on OTUs. The ordinate of Rank-abundance distribution curves represents the relative abundance of each OTU and the abscissa is the OTU arranged from high to low. The width of the curve reflects the species richness, while the shape of the curve can be used to explain the species evenness. As shown in P = 0.046), which meant that the species richness of gut microbiota in the HFpEF group was lower than that in the control group. However, there was no statistical difference in the Shannon index (P = 0.159) and Simpson index (P = 0.495), indicating that there was no difference in the species diversity between the two groups  were evaluated. There was a difference in the Chao index between the two groups (o groups .P < 0.05). The results provided evidence for a shift in the composition of gut microbiota induced by HFpEF. The PcoA chart based on Bray-Curtis was used to present the results of beta diversity analysis .Assessment of beta diversity, a parameter that represents inter-individual variances, showed a significant separation of HFpEF patients and controls , Selenomonas (P = 0.006), and Dialister (P = 0.007), was statistically different between HFpEF patients, which was caused by different etiologies. In alpha diversity analysis, the Shannon index (P = 0.025) and Simpson index (P = 0.016) were statistically different, which indicated that the species diversity of gut microbiota in the CHD group was higher than that in the hypertensive heart disease group and hypertrophic cardiomyopathy group . To sum up, the composition and species diversity of gut microbiota was also different between HFpEF patients, which was caused by different etiologies.We divided 30 HFpEF patients into three subgroups according to their etiologies: hypertensive heart disease group, coronary heart disease (CHD) group, and hypertrophic cardiomyopathy group. At the phylum classification level, there was no significant difference in the abundance of each microbiota. However, at the genus classification level, the abundance of 10 microbiota, such as Weissella . In addition, clinical research demonstrated that Enterococcus is associated with endocarditis and urinary tract infections .The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: NCBI with BioProject ID PRJNA786060  for the publication of any potentially identifiable images or data included in this article.ZH, YJ, and YZ designed the study. ZH and XM wrote the first draft of this report. YZ, TC, and YJ helped to write the final version. All authors read and met the criteria for authorship and agree with the results and conclusions of the report.This work was supported by grants from the National Natural Science Foundation of China (81873486), Suzhou Promoting Health through Science and Education Youth Science and Technology Project (KJXW2020001), Medical research project of Jiangsu Provincial Health Commission (Z2021011), Biomedical translational medicine innovation and applied research project (SZM2021020) and Project of Suzhou Science and Technology Development Program .The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


TNF is a central cytokine in the pathogenesis of rheumatoid arthritis (RA). Elevated level of TNF causes local inflammation that affects immune cells and fibroblast-like synoviocytes (FLS). Nowadays, only 20–30% of patients experience remission after the standard of care therapy—antibodies against TNF. Interestingly, responders show reduced levels of GLUT1 and GAPDH, highlighting a potential link to cellular metabolism. The aim of the study was to investigate whether TNF directly affects the metabolic phenotype of FLS. Real-time respirometry displayed TNF-induced upregulation of glycolysis along with a modest increase of oxidative phosphorylation in FLS from healthy donors. In addition, TNF stimulation enhanced HIF1A and GLUT1 expression. The upregulation of HIF1A and GLUT1 reflects their enriched level in FLS from RA patients (RA-FLS). The inhibition of TAK1, HIF1a and hexokinase deciphered the importance of TNF/TAK1/HIF1A/glycolysis signaling axis. To prove that inhibition of glycolysis reduced the pathogenic phenotype, we showed that 2-deoxyglucose, a hexokinase inhibitor, partially decreased secretion of RA biomarkers. In summary, we identified a direct role of TNF on glycolytic reprogramming of FLS and confirmed the potency of immunometabolism for RA. Further studies are needed to evaluate the therapeutic impact especially regarding non-responder data. Fibroblast-like synoviocytes (FLS) together with macrophage-like synovial cells form the intimal lining layer of the synovial membrane. FLS proliferation and accumulation of immune cells trigger the inflammation and lead to membrane thickness, known as synovial hyperplasia – one of the primary symptoms of RA. Along with immune cells, FLS are considered the key players in the development of RA3. FLS from RA patients (RA-FLS) share several characteristics with tumor cells e.g. increased proliferation rate and apoptosis resistance7. The microenvironment of inflamed cartilage comprises a mixture of cytokines, that are secreted by FLS and immune cells. TNF promotes the generation of cytokines and chemokines, expression of endothelial cell adhesion molecules, angiogenesis and induction of pain in RA8. TNF mediates cell proliferation and survival via nuclear factor ´kappa-light-chain-enhancer´ of activated B-cells (NF-kB) and mitogen-activated protein kinases (MAPK) pathways9. One of the essential steps in NF-kB activation is receptor-interacting protein (RIP) mediated TAK1 (TGF-Beta Activated Kinase 1) recruitment10. The relevance of TNF in several autoimmune diseases is well-known and illustrated by five approved antibodies. Despite reducing synovial inflammation, the current standard of care therapy do not cure the disease and only 20–30% of patients experience remission11.Inflamed synovial cavity in RA is characterized by infiltration of immune cells and stromal cell activation12. Furthermore, a decreased glucose uptake was demonstrated using FDG-PET/CT in patients after anti-TNF treatment14. In general upregulated glucose metabolism in RA-FLS was already published in 1991 as a specific feature of RA disease development15. In addition, RA-FLS are more glycolytic than FLS from OA patients16. Nutrient demand is much higher in RA-FLS to enable rapid growth and cytokine production17. The significant upregulation of GLUT1 and reduction in mitochondrial respiration confirms the importance of metabolic changes in RA-FLS19.Our interest is focused on the fact that patients responding to anti-TNF therapies showed a downregulation of GLUT1 and GAPDH, a rate-limiting enzyme in glycolysisWe questioned whether a single cytokine like TNF is able to induce metabolic reprogramming and pro-inflammatory phenotype in FLS from healthy donors (H-FLS) similarly to the described phenotype of RA-FLS.Fibroblast-like synoviocytes from healthy and RA donors and the corresponding Synoviocyte Growth Medium were commercially purchased from Cell Applications, Inc. Glucose, oligomycin, HIF inhibitor V and 2-Deoxyglucose were from Sigma-Aldrich. Recombinant human TNF was from R&D systems, (5Z)-7-oxozeanol from Tocris. We used a highly potent Glut1 inhibitor from the 1H-pyrazolopyrimidine class.l-glutamine and incubated for 45 min at 37 °C. Afterwards glycolysis stress test was performed in the Seahorse XFe 96 analyzer (Seahorse Bioscience) in real-time according to the protocol provided by the manufacturer. Glycolysis, Glycolytic capacity, and glycolytic reserve were studied by treatment of FLS subsequently with 24 mM glucose, 1 µM Oligomycin and 100 mM 2-deoxyglucose. Measurements were done in at least 6 replicates per plate and normalized to the amount of protein using bicinchoninic acid (BCA) assay .20.000 H-FLS were seeded in a Seahorse 96 well-plate (XF96 cell culture microplate). Cells were stimulated on the following day with recombinant TNF with and without inhibitors for 24 h. On the day of the experiment, first the medium was removed from the cell plate and the cells were washed three times with Seahorse XF base medium with 3 mM FLS were stimulated after overnight attachment to 96 well-plates with recombinant TNF with and without inhibitors for 24 h. Afterwards supernatants were collected and frozen at − 20 °C. The analysis was carried out according to the manufacturer´s user guide  using the ProcartaPlex™Multiplex Immunoassay Kit.RNA was isolated from stimulated or unstimulated FLS with the RNeasy® Mini Kit from QIAGEN. The isolation was carried out according to the manufacturer protocol  using the automated system QIAcube. After reverse transcription with the Applied Biosystems ™ High Capacity cDNA Reverse Transcription Kit from Thermo Fisher, TaqMan Assay was performed with the ViiA™7 Real Time PCR System from Applied Biosystems®. For quantitative normalization (endogenous control) the housekeeping gene RPL37a was used. For the relative quantification of the obtained results the comparative CT method was chosen.20, GSE7729821, GSE2974622, GSE191923. Heatmap comparison of these search results was done with R package pheatmap24.Expression of certain genes was queried in archival studies comparing RA case and control synovial tissues. Records for this search were extracted from OmicSoft DiseaseLand Database, release HumanDisease_B37 . Analyzed datasets series: GSE8940825 was used, and pheatmap24 was applied with agglomerative clustering method (Euclidean distance) for hierarchical clustering.The statistical analysis of the experiments was done using Microsoft Excel 2010 (Microsoft Corporation) and GraphPad Prism 7.02 (GraphPad Software). To calculate p-values, the unpaired t-test for the comparison of two groups or the one-way analysis of variance (ANOVA) followed by pairwise comparison were used. Visualization was done using RStudio . R package tidyverse26. To find out whether stimulation with TNF directly promotes metabolic changes in FLS (or it is rather a consequence of inflammation induction), Seahorse glycolysis stress test was performed in FLS from healthy donors (H-FLS) upon treatment with TNF. Thereby we can analyze real-time consumption of glucose as well as the glycolytic capacity and glycolytic reserve of H-FLS by injection of different substrates using extracellular acidification rate (ECAR) as parameter for proton release by glycolysis. Our Seahorse data indicate that TNF stimulation dose dependently increases glycolysis, glycolytic capacity, and glycolytic reserve . TNF dose-dependently upregulated known downstream targets like IL-6 Fig. a. In addWe observed TNF-induced glycolytic reprogramming of healthy FLS and a similar glycolytic signature in FLS from RA donors. Next, we wondered whether inhibition of HIF1A and glycolysis would block TNF-induced proinflammatory effects in healthy FLS similar to TAK1 inhibition. We focused on the major TNF-dependent RA biomarkers described before Fig. a e.g. prWe compared whether the above mentioned biomarkers are upregulated in RA-FLS. We observed—despite a high donor variation—a trend towards increased secretion of these biomarkers in RA-FLS compared to healthy controls , a rate-limiting enzyme of glycolysis, is known to regulate FLS aggressive functions30. Our data show high expression level of GLUT1, HIF1A, and its glycolytic downstream targets in RA-FLS compared to H-FLS. These results support already published data describing changes between FLS from osteoarthritis (OA) and RA patients16. Enhanced glucose uptake, glycolytic rate, as well as increased levels of GLUT and HIF1A are known for RA-FLS18.The first evidence of glycolysis upregulation in RA joints was elevated lactate and reduced glucose levels in synovial fluid26. Moreover, responders to TNF blockade display lower level of GLUT1 and GAPDH expression12. Very few papers are focused on the impact of TNF on FLS. We demonstrate that TNF promotes secretion of RA biomarkers e.g. pro-inflammatory cytokines and MMPs in H-FLS. Furthermore, TNF induces glycolysis and expression of metabolic genes. Recently the link between TNF signaling and glycolysis was suggested in different cell types. In endothelial cells TNF increases 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 3 (PFKFB3) expression and inhibition of PFKFB3 reduces TNF-induced monocyte adhesion and transmigration31. We also observed a slight increase in PFKFB3 after TNF stimulation in healthy FLS supporting a general role for TNF in glycolysis. According to published data the exposure to TNF enhances the NF-κB pathway in FLS32 and alters chromatin states33. TAK1 binding to TNF receptor 1 is shown to be essential for TNF-induced NF-κB activation10. We show that TAK1 inhibition attenuates TNF-induced secretion of RA biomarkers and metabolic changes in H-FLS.In our study treatment with TNF induces glycolysis and expression of metabolic genes in H-FLS. TNF is a crucial cytokine that mediates RA pathology. Anti-TNF therapy diminishes inflammation and downregulates glucose uptake in RA joints12. Hypoxia induced accumulation of HIF1A modulates the expression and distribution of GLUT1 in many cell types36. HIF1A activation promotes glycolysis, ROS production and epithelial–mesenchymal transition in RA-FLS in vitro37. Thus, HIF1A induced GLUT1 upregulation is a potential mechanism of RA-FLS phenotype development. Our analysis of the potential impact of HIF1A and GLUT1 inhibition on cytokine secretion was probably limited by the availability of potent HIF1A inhibitors, their variable mode of actions and compensatory mechanisms from glucose transporters. The used HIF inhibitor promotes for example HIF1A degradation via upregulation of von Hippel-Lindau expression in hypoxia. We therefore focused on the importance of glycolysis by using 2-DG, a competitive inhibitor of glucose. Inhibition of glycolysis with 2-DG partly blocked TNF’s proinflammatory effects on MMP1 and MCP-3 highlighting the strong connection between cytokine signaling and cellular metabolism. Moreover, 2-DG treatment inhibited RA biomarkers secretion, supporting the idea of a therapeutic potential for glycolysis inhibition in RA-FLS, innate and adaptive immune cells and in vivo disease models38. To our knowledge our work is the first one displaying glycolysis inhibition in unstimulated RA-FLS with anti-inflammatory effects.Interestingly, Biniecka et al. hypothesized a connection between TNF, glycolysis, and hypoxia. The study determines an inverse correlation between tissue oxygen levels, glycolytic gene expression and lactate levels in FLS cultures as well as in synovial biopsies from anti-TNF responders vs. anti-TNF non-respondersFinally, we identified a direct impact of TNF on H-FLS (and RA-FLS) metabolism. TNF stimulation seems to reflect the metabolic and pro-inflammatory phenotype of RA-FLS via HIF1A and GLUT1 signaling Fig. . These rSupplementary Information.


Female adult rats were injected with morphine before gestation and until 14 days after giving birth. On postnatal day 14 (P14), rat offspring from morphine-addicted mothers were subjected to an opioid-withdrawal protocol and were analyzed 2 or 8 h after administration of that protocol. Expressions of the TNF-α protein, H3K4me3 in the tnf-α promoter gene, and neural cell apoptosis within the ventral-medial striatum of neonatal rat offspring were evaluated. In the absence of significant opioid withdrawal , prenatal morphine exposure led to increased levels of H3K4me3 in the tnf-α promoter gene, of the TNF-α protein, and of neural cell apoptosis within the ventral-medial striatum of neonatal rat offspring. Following opioid withdrawal , differential expression of H3K4me3 in the tnf-α promoter gene locus and upregulation of the level of TNF-α protein expression were further enhanced in these offspring. In addition, increased levels of caspase-3 and neural cell apoptosis were also observed. Taken together, this study revealed that prenatal opioid exposure can activate an epigenetic histone mechanism which regulates proinflammatory factor generation, which hence, led to cell apoptotic damage within the ventral-medial striatum of neonatal rat offspring from morphine-addicted mothers. More importantly, the opioid-withdrawal episode may provide augmented effects for the abovementioned alterations and could lead to deleterious effects in the neonatal brain of such offspring.Prenatal opioid exposure might disturb epigenetic programming in the brain of neonatal offspring with various consequences for gene expressions and behaviors. This study determined whether altered trimethylation of histone 3 at lysine 4 (H3K4me3) in the promoter of the tumor necrosis factor- Early life adversity is related to increased risks for developing many behavioral and psychiatric disorders . A spectα, interleukin- (IL-) 1, and IL-6 [in vivo [α release from neural cells [α expression levels were found to increase in the amygdala during morphine-withdrawal episodes [α production in the hippocampus [During the fetal and neonatal periods, the central nervous system (CNS) displays highly significant plasticity and is vulnerable to changes by prenatal influences such as prenatal opioid exposure –8. The mand IL-6 –14. Chro[in vivo . In addial cells . Recentlpocampus . Prenatapocampus . Taken ttnf-α gene expression within the promoter region [tnf-α promoter gene and is associated with neural cell apoptosis in the ventral-medial striatum of neonatal rat offspring .The epigenetic histone regulation in a target promoter gene locus might play a role in the molecular basis of mammalian drug-craving and addiction , 19. Recr region , 20. In r region . HoweverFemale adult Sprague-Dawley (SD) rats which underwent the opioid-withdrawal protocol were housed under a 12 h light/dark cycle with humidity maintained around 60% ~70% and were initially injected with morphine hydrochloride (2 mg/kg body weight (BW), subcutaneously twice daily with the dosage progressively increased at a rate of 1 mg/kg BW every 7 days with a maximum dose of 7 mg/kg BW) , 22. Then = 48 rats); and the late group represented rat offspring for observation of opioid-withdrawal behaviors for 2 h starting from the 6th hour after transfer. These rat offspring were then sacrificed for biochemical experiments . Rat offspring from the vehicle-control group were transferred to an observational chamber on P14 and were observed for opioid-withdrawal behaviors for 2 h starting from the 6th hour after transfer. These rat offspring were then sacrificed for biochemical experiments . There were no differences in sex among the three groups.We evaluated the growth of BW of rat offspring on postnatal day 7 (P7) and P14 (an age regarded as a neonate in the human lifespan) . On P14,All experimental protocols were approved by the Animal Care and Use Committee at the National Defense Medical Center, Taiwan (NDMC-04-088 and IACUC-04-085) with all actions undertaken being designed to lessen suffering and decrease the number of animals used.μm) containing the ventral-medial striatum brain region were immediately harvested with a vibro-slicer . Brain slices were selectively transferred to an incubation chamber perfused with oxygenated artificial cerebrospinal fluid  for 1 h. Artificial cerebrospinal fluid consisted of (in mM) NaCl (124), MgCl2 (1), CaCl2 (2), KCl (3.5), NaH2PO4 (1.25), NaHCO3 (26), and D-glucose (10) at pH 7.4 and with an osmolarity of 305 ± 5 mOsm.After the opioid-withdrawal protocol was completed on P14, the pups were sacrificed, and brain slices  and cleaved caspase-3 . Depending on the different types of primary antibody, either rabbit anti-mouse immunoglobulin G (IgG) or goat anti-rabbit IgG (1: 3000) was chosen as the secondary antibody. Immunoreactive proteins were detected using the BioSpectrum 810 Imaging System (UVP).Cells of the ventral-medial striatum were lysed in buffer . The protein concentration was clarified with a BCA assay . Cell lysates were sorted on sodium dodecylsulfate polyacrylamide gel electrophoresis (SDS-PAGE), later transferred to nitrocellulose membranes, and then probed with antibodies against TNF-α: forward (5′-CCCTACGGGTCATTGAGAGA-3′) and reverse (5′-GGTTGTGGACTGCCTTTTGT-3′); and 18s ribosomal (r)RNA: forward (5′-CCAGTAAGTGCGGGTCATAA-3′) and reverse (5′-TAGTCAAGTTCGACCGTCTTC-3′). The thermal protocol of the PCR was set to 95°C (for 4 min), followed by 30 amplification cycles of 94°C (for 30 s), 62°C (for 1 min), and 72°C (for 1 min), with a final melting curve analysis. Amplicons were analyzed by the melting curve (Light Cycler software) and agarose gel electrophoresis; the LightCycler analytical system was applied to decide cycle threshold (CT) values, and the relative messenger (m)RNA level of each experiment was assessed by a real-time PCR followed by measurement by the relative CT method (ΔΔCT)  and compared to a calibrator (cDNA from a pooled sample)).Isolation of RNA, including synthesis of complementary (c)DNA, and DNase treatment was accomplished using the Transcriptor First Strand cDNA Synthesis Kit RT-PCR System™  following the manufacturer's instructions. The two-step real-time PCR with the LightCycler™ System (Roche) and Sybr Green I dye was used for monitoring the PCR. FastStart DNA Master SYBR Green I (Roche) was performed according to the producer's instructions and used for the real-time PCR. This study utilized the following set of primers: TNF-5 cells were treated with 1% formaldehyde at room temperature (for 10 min) accompanied by sonication of DNA and immunoprecipitation of chromatin overnight with antibodies of trimethylated H3K4  and later purification with a ChIP kit . Probes and primers were planned by exploring the proximal promoter and intronic enhancer areas of the tnf-α gene [tnf-α 1 (-2686 to -2667); forward, 5′-CCCTAGTCCTCCTGGGATGT-3′ and reverse, 5′-GCCTGCTGCAACAGAGAGA-3′; tnf-α 2 (-2202 to -2183); forward, 5′-CGTCTCACTATGCCTGGGTCT-3′ and reverse, 5′-AAGCAAAGCACTTCTACCAAAT-3′; tnf-α 3 (-1672 to -1653); forward, 5′-AAACTCAGACCAGGCTGCAT-3′ and reverse, 5′-CAGGTCATCTCTTGACGTGGT-3′; tnf-α 4 (-502 to -480); forward, 5′-GAGTTCTGCATGTATTGGATAGG-3′ and reverse, 5′-TGCTACCAAGCCTAAAGACC-3′; and tnf-α 5 (-230 to -213); forward, 5′-GGTTCAGTTCCCAGCACCTA-3′ and reverse, 5′-ATGGGCATATCTGCACAGCA-3′. PCRs were conducted on the ABI Gene Amp ⓐ PCR System (Applied Biosystems). The quantity of immunoprecipitated DNA was calculated and compared to the quantity of total input DNA.A ChIP assay was performed as previously described , 25. Brif-α gene , 25, incμm and then stained with an antineuronal nuclei (NeuN) antibody  to identify neuronal cells in the presence or absence of terminal uridine nick-end labeling , and immunostaining was used to detect DNA break-down. A Cy3-conjugated anti-mouse antibody for staining NeuN and a fluorescein-conjugated antibody for staining TUNEL were used for a secondary amplification that was visualized with a Zeiss LSM510 laser microscope . Quantitative analyses of the NeuN-sensitive cell density, TUNEL-sensitive cell density, and NeuN/TUNEL-sensitive cell density were performed in the ventral-medial striatum according to the brain atlas [A double immunofluorescence investigation by laser-scanning confocal microscopy was applied to examine apoptosis in neurons of brain sections of the ventral-medial striatum, which were cut at a coronal plane and measured 30 in atlas . Averagep < 0.05.Data are shown as mean ± standard error of the mean (SEM). Data were analyzed using SigmaPlot 10.0 and Sigmastat 3.5. A one-way analysis of variance (ANOVA) with Bonferroni's test for post hoc comparisons was applied with the level of significance set to p < 0.05, n = 96 rats vs. the vehicle-control group: 16.3 ± 1.3 g, n = 48 rats; P14: the prenatally opioid-exposure group: 29.2 ± 1.6 g, p < 0.05, n = 96 rats vs. the vehicle-control group: 37.6 ± 1.7, n = 48 rats).We observed whether prenatal opioid exposure disrupted the growth in BW after birth. In p > 0.05, n = 48 rats in each group, data not shown). In contrast, as shown in p < 0.05, n = 48 rats in each group).Rat offspring in the early group did not express significant opioid-withdrawal behaviors, compared to the control group  from morphine-addicted mothers. There were significant increases at the mRNA and protein levels of the TNF-α expression in the early group compared to the control group . In addition, mRNA and protein levels of the TNF-α expression were further enhanced in the late group compared to the early group .tnf-α promoter gene was associated with increased levels of TNF-α as seen in tnf-α promoter gene were performed in the ventral-medial striatum of neonatal rat offspring. As shown in tnf-α promoter gene . Furthermore, in the late group, there were further increased levels of H3K4me3 activity in subregions 3 and 4 of the tnf-α promoter gene locus compared to the early group .To determine whether activation of H3K4me3 in the α enhancement combined with cell apoptosis, cleaved caspase-3 activity was evaluated in the ventral-medial striatum of neonatal rat offspring (P14) from morphine-addicted mothers. As shown in p < 0.05). In addition, the level of cleaved caspase-3 expression in the late group did not statistically differ compared to the early group .To observe whether prenatal opioid exposure caused the abovementioned TNF-p < 0.05, n = 12 rats in each group). In addition, a further increase in TUNEL-sensitive cells was observed in the late group compared to the early group  (p < 0.05). The number of NeuN-sensitive cells in the late group did not statistically differ compared to the early group  . These results reveal that prenatal opioid exposure can induce neural cell apoptosis in the ventral-medial striatum of neonatal rat offspring from morphine-addicted mothers.To confirm the increased levels of the above-described caspase-3 activity, confocal laser-scanning microscopy was applied to study neonatal rat offspring (P14) from morphine-addicted mothers. Figures h group) .  Figureh group) . In Figutnf-α gene and was associated with cell apoptosis in the ventral-medial striatum of neonatal rat offspring from morphine-addicted mothers, suggesting possible early life adversity within the ventral-medial striatum of the mammalian brain.The major findings of this study revealed that prenatal opioid exposure activated differential trimethylation of H3K4 modifications in the promoter locus of the tnf-α promoter gene as detected from human gingiva with periodontitis [tnf-α gene [tnf-α promoter gene locus of the ventral-medial striatum of neonatal rat offspring from morphine-addicted mothers, and this enhancement over a different promoter locus of the tnf-α gene implies that respective transcriptional factors can be recruited into transcription and become affected by prenatal opioid exposure. For example, signal transducer and activator of transcription 6 (STAT6) (located in the tnf-α 2 subregion) were reported to mediate neuroinflammation caused by ethanol in mice with a traumatic brain injury [tnf-α 3 subregion) and pituitary homeobox 3 (Pitx3) (located in the tnf-α 4 subregion) are involved in dopaminergic neuronal development, which is related to drug addiction and reward behaviors [tnf-α promoter gene in the ventral-medial striatum of neonatal rat offspring from morphine-addicted mothers (α mRNA and protein (α). However, which transcription factors are involved and are affected by epigenetic histone modifications in offspring due to prenatal opioid exposure are still unclear.Previous studies suggested that epigenetic histone modifications regulate gene expressions through a specific site over a promoter in response to various stimuli . Howeverdontitis , 29; addf-α gene . This stn injury . Engrailehaviors . In this mothers , accompa protein . These rtnf-α promoter gene in this study. And as the late group presented opioid-withdrawal behaviors, there was a further enhancement of H3K4me3 activity in specific subregions. Taken together, epigenetic histone modifications seem to be related to mediation of priming or desensitization of specific genes in illicit drug exposure, and such epigenetic histone modifications can be latent, while persistently altering the chromatin structure after withdrawal episodes [Epigenetic histone modifications persistently appear not only during acute or chronic exposure but are long-lasting as well, even after withdrawal episodes , 33. Metepisodes . Howeverα production was associated with cell apoptosis within the ventral-medial striatum by prenatal opioid exposure which increases the neurobiological basis of risks for neuropsychiatric disorders in later life. Such enhanced TNF-α release indicates an early proinflammatory response leading to activation of apoptotic pathways such as caspase-3 signaling [in vitro, but it seemed that chronic morphine exposure might not affect glial cells at an early age in vivo from animal models [α production might lead to neural cell apoptosis in the ventral-medial striatum. In addition, opioid exposure might also enhance apoptosis in selected, specific brain areas, such as the amygdala, ventral-medial striatum, or prefrontal cortex in vivo [Enhancement of TNF-ignaling –38. Howel models , 37. The in vivo , 38. Pre in vivo . Those rα expression was associated with increased neural cell apoptosis in the ventral-medial striatum, which might contribute to neurological impairments. Such neural cell apoptotic damage within the ventral-medial striatum during early life might lead to increased dose requirements for opioid drugs to satisfy the need to increase the dosage and to fulfill drug-craving and addictive behaviors later in life. In addition, prenatal opioid exposure may initiate long-lasting alterations in the gene expressions of the synapse structure in the ventral-medial striatum in rat offspring [Recently, a closely interactive and related relationship between inflammation and neuropsychiatric disorders was proposed in the mammalian brain . For insffspring , 22. SucIn summary, this study revealed that prenatal opioid exposure can activate an epigenetic histone mechanism for regulating proinflammatory factor generation and hence lead to cell apoptotic damage within the ventral-medial striatum of neonatal rat offspring from morphine-addicted mothers. More importantly, the opioid-withdrawal episode may provide augmented effects for such abovementioned alterations and may lead to adverse effects in the neonatal brain of these offspring.


TNF-α polymorphisms and tendinopathy in athletes.High levels of the tumor necrosis factor alpha (TNF-α) induce apoptosis and pro-inflammatory effects for primary degeneration of tendon and development of tendinopathy. The aim of this study was to investigate the association between the TNF-α -1031T > C; -857 C > T; -308G > A) using TaqMan validated assays. The association of the polymorphisms with tendinopathy was evaluated by a multivariate logistic regression model, using odds ratios (OR) and 95 % confidence intervals (CI).Two hundred and seventy athletes (135 tendinopathy cases and 135 controls) were included and genotyped  or Achilles tendinopathies . No significant differences were found in allele or genotype distributions of the − 1031T > C and − 857 C > T polymorphisms between cases and controls. TNF-α TCA haplotype was associated with increased tendinopathies risk, either considering all cases , patellar , rotator cuff  or Achilles tendinopathies .The variant allele TNF-α polymorphisms could influence the susceptibility to developing tendinopathy among athletes. Knowledge of the TNF-α polymorphisms associated to tendinopathy in athletes can further understanding of the inflammatory role in the early stages of the disease and contribute for sports injury surveillance programmes, in which athletes with TNF-α TCA haplotype could be early subjected to cryotherapy after training and competition to avoid tendinopathy development.These results suggest that the The online version contains supplementary material available at 10.1186/s13102-021-00276-2. Tendinopathy is characterized by pain, swelling, structural change and functional limitation of the tendon due to overuse , 2. It iTNF-α mRNA was increased 11-fold in torn supraspinatus tendon compared to controls [Single nucleotide polymorphisms (SNPs), a variation of the nucleotide at a single position in DNA sequence, involved with inflammatory process were associated as non-modifiable factors for developing tendinopathies –8. Pro-icontrols , and in controls .HLA-B) and human leukocyte antigen-DR (HLA-DR) genes at the major histocompatibility complex class III region [TNF-α gene, such as -1031T > C (rs1799964), -857 C > T (rs1799724) and − 308G > A (rs1800629), have shown potential to alters the binding of transcription factors in the DNA, regulating TNF-a expression [TNF-α SNPs was due to their biological relevance in altering the expression of the gene and for have relatively high frequency in different populations [TNF-α SNPs with some diseases, such as inflammatory bowel diseases [TNF-α is encoded by the gene of the same name, located on chromosome 6p21.3 between the human leukocyte antigen-B . All participating athletes provided written informed consent and answered a questionnaire about their epidemiological, clinical, sport and training characteristics, as well as tendon injury history and their specific information such as type, location and number of tendinopathy episodes, as previously described [This case-control study was approved by the Human Ethics Committee of the The inclusion criteria were Brazilian competitive levels athletes aged 18–45 years old who were recruited between March 2018 and September 2019 at different sports training centres and competitions.N = 135) consisted of athletes without previous imaging diagnosis of tendinopathy and who were matched with tendinopathy cases for age (difference of ± 2 years), sex and sport modality. The sample size was calculated using Epi Info 7, version 7.1.3. (http://wwwn.cdc.gov/epiinfo/html/downloads.htm) to detect a difference between case and control groups, assuming an odds ratio (OR) of 2.0 with a power of 0.8 and 5 % type I error. The OR was based on previous evidence [One hundred thirty-five athletes had tendinopathy clinically diagnosed by medical practitioners and confirmed with magnetic resonance image examination (MRI). All tendinopathy diagnoses were confirmed by two blinded specialized orthopaedic surgeons, as described in previous studies , 21. Theevidence –24, and TNF-α -1031T > C (rs1799964), -857 C > T (rs1799724) and − 308G > A (rs1800629) polymorphisms were genotyped using a TaqMan allelic discrimination assay obtained from Applied Biosystems . For all polymorphisms real-time polymerase chain reaction (PCR) reactions were performed on a 7500 Real-Time System , and the genotypes were then determined directly. To assure genotyping quality, in each reaction two standardized positive controls of each polymorphism genotype were used.Genomic DNA was obtained from oral mucosa collected from each athlete by swab. The The normally distribution of studied population was determined by the Shapiro-Wilk test. Comparisons of continuous variables between tendinopathy cases and controls groups were performed using the Student’s t test, and data were presented as mean ± standard deviation (SD). According to distribution and clinical significance the continuous variables  were divided into quartiles. Categorical data were shown in proportions and differences between the two groups were evaluated using the Chi-squared (χ2) statistic test or Fischer exact test, when applicable.TNF-α  allele frequency and genotype distribution were derived by gene counting and frequencies between the two groups were compared using the χ2 test or, when appropriate, the Fisher’s exact test. The haplotype patterns and linkage disequilibrium coefficients  were inferred using Haploview, as previously described [Deviations from Hardy–Weinberg equilibrium (HWE) were assessed by the goodness-of-fit χ2 test. escribed .P ≤ 0.25) and output significance was 0.05 (P ≤ 0.05) at the regression model. The difference was statistically significant when P < 0.05. All analyses were performed using the Statistical Package for Social Sciences .Multivariate logistic regression analyses model were performed to evaluate the possible associations between epidemiological, clinic, sport and training characteristics as much as of the polymorphisms with tendinopathy, which was estimated by the OR with a 95 % confidence interval (95 % CI). As a final regression model used to control possible confounding factors, each variable was introduced considering the biological and statistical significance of the univariate analysis, which a input significance level less than 0.25 , rotator cuff , Achilles , wrist  and elbow tendinopathy   reported more than one diseased tendon. The cases reported tendinopathies of the patellar , alcohol consumption (P = 0.25), nutritional follow-up by a specialist during a sports career (P = 0.002), declared preference member (P = 0.21) and weekly training hours (P = 0.15) were inserted in the logistic regression model. After multivariate analysis, only BMI and nutritional follow-up remained in this model.The demographic, clinical, sport and training characteristics variables of all tendinopathy cases and controls were presented in Table TNF-α  SNPs was in Hardy–Weinberg equilibrium. The minor allele frequencies of the TNF-α SNPs in the study population are shown in Fig. TNF-α-308 A allele was significantly associated with patellar and Achilles tendinopathies. Moreover, the TNF-α -308AA genotype was only present in the tendinopathy cases, either considering all cases, patellar, rotator cuff or Achilles tendinopathies. Considering the recessive co-dominance model (TNF-α -308GG + GA versus AA) the TNF-α -308AA genotype was significantly associated with tendinopathy cases, either considering all cases, patellar and Achilles tendinopathies  there was not statistical power due to the decrease of the sample size (data not shown). In addition, no significant differences were found in allele or genotype distributions of the TNF-α -1031T > C and TNF-α -857 C > T polymorphisms between tendinopathy cases and controls (data not shown).The distribution of es Table . DespiteTNF-α  SNPs were inferred, which account 100 % of the study population. The TCG haplotype was considered wild-type/reference haplotype due to present the highest frequency in the study population . After adjusting for confounding variables , the TNF-α TCA haplotype was associated with increased tendinopathies risk, either considering all cases (P = 0.006), patellar (P = 0.004), rotator cuff (P = 0.008) or Achilles tendinopathies (P = 0.03) , which is observed when analyzing only the patellar, rotator cuff or Achilles subgroups. The TNF-α TCA  haplotype characterized by the presence of the variant allele of TNF-α – 308 A, which promotes loss of transcription factors like activator protein-2 binding, increasing the level of gene transcription [TNF-α SNPs in the promoter region site are strongly in linkage disequilibrium and creates established haplotypes that affect differently gene expression and activity than those of each SNP evaluated separately [TNF-α mRNA found in the degenerate tendon [Despite the different risk factors different types of tendinopathies, overloading and mechanical stress may induce the secretion of TNF-α by tenocytes and cause change cellular proliferation, onset of pain and ECM degradation . Under ncription . The TNFparately , 34. Thie tendon , 13; andTNF-α-308AA genotype is rarer (approximately 0–2 %) [Within the Brazilian population the y 0–2 %) , 35, 36,TNF-α TCA haplotype could be early subjected to cryotherapy after training and competition to avoid tendinopathy development. Whole-body cryotherapy decreased serum TNF-α (around 60 %) 24 h following exercise [It is essential to understand the molecular mechanism involved in the etiology of the disease and for control mechanical stress on the tendon of athletes most likely to develop overuse injuries . The chaexercise . Thus, tTNF-α -308G > A SNP was potential non-modifiable risk associated with development of disease.The Additional file 1.


Cardiovascular diseases are the leading cause of mortality in the world. Heart failure with preserved ejection fraction (HFpEF) accounts for about half of all heart failure. Unfortunately, the mechanisms of HFpEF are still unclear, leading to little progress of effective treatment of HFpEF. Arterial stiffness is the decrement of arterial compliance. The media of large arteries degenerate in both physiological and pathological conditions. Many studies have proven that arterial stiffness is an independent risk factor for cardiovascular disorders including diastolic dysfunction. In this perspective, we discussed if arterial stiffness is related to HFpEF, and how does arterial stiffness contribute to HFpEF. Finally, we briefly summarized current treatment strategies on arterial stiffness and HFpEF. Though some new drugs were developed, the safety and effectiveness were not adequately assessed. New pharmacologic treatment for arterial stiffness and HFpEF are urgently needed. Cardiovascular diseases are the leading cause of mortality in the world. Heart failure (HF), as the consequence of so many factors that damage the heart, is a progressive and serious condition with high rate of mortality . Heart fArterial stiffness is the decrement of arterial compliance. A lot of parameters were used in clinical practice to assess arterial stiffness , for exaBecause arterial stiffness is closely related to LV diastolic function, physicians are paying great attention to the contribution of arterial stiffness to HFpEF. In this perspective, we summarized current understanding of the relationship between arterial stiffness and HFpEF, the mechanism of arterial stiffness contributing to HFpEF, and the treatment and potential future directions of HFpEF focusing on arterial stiffness.Many conditions were reported to be associated with HFpEF, for example, aging, hypertension, obesity, diabetes. Diastolic dysfunction is one of the most important contributor to HFpEF , and artAlthough many studies reported the associations among arterial stiffness, diastolic dysfunction, and HFpEF, till now there is very few evidence to prove that arterial stiffness is a key factor which drives the development of HFpEF. A study conducted by Wan et al.  showed tIn conclusion, though there is a little controversy, arterial stiffness is more likely to be regarded as a harmful factor for LV diastolic function and HFpEF. Especially for the arterial stiffness induced by metabolic disorders, it may play a major role in the development of HFpEF.As we described previously, many studies have demonstrated that the magnitude of arterial stiffness in HFpEF is significantly increased compared to those without HFpEF. This accelerated arterial stiffness leads to the increment of arterial pulse pressure and LV afterload , 20. ThiThe vascular effect of arterial stiffness on HFpEF is similar to other organ damage induced by arterial stiffness. The former leader of the vascular group of Framingham study, Professor Mitchell, proposed a theory of “arteriosclerosis-related organ damage” . In thisThe change of arterial hemodynamics plays a key role in HFpEF. Arterial stiffness is a determinant of pulsatile afterload, which is one of the two major components of arterial load. Arterial wave reflections increases with arterial stiffness, leading to the increment of mid-to-late systolic load, and subsequent left ventricular abnormalities including concentric remodeling, myocardial fibrosis, contractile dysfunction, and ejection duration reduction. These changes further contribute to the increment of mid-to-late systolic load, resulting in a vicious circle . There mThe ventricular–vascular interaction effect is more complicated. In HFpEF, not only arteries but also left ventricle become stiff. The end-systolic elastance  and arterial elastance  are the indicators for left ventricle systolic stiffness and arterial stiffness, respectively. In resting situations, though both Ees and Ea elevated in HFpEF, stroke volume and pulse energy are close to physiological conditions. However, since the slopes of Ees and Ea are sharp, a small change in blood pressure may lead to a dramatic change in Ees and Ea, leading to the mismatch between left ventricle and arteries . This veEndothelial function plays an important role in arterial stiffness and HFpEF. The relationship between endothelial dysfunction and HFpEF is well-established by a lot of studies . EndotheUnlikely to the treatment of heart failure with reduced EF, there is no dramatic progress in the treatment of HFpEF, and the survival rate of HFpEF patients is not significantly improved . Thus, lLifestyle management is fundamental to HFpEF patients. Proper diet and exercise are of critical importance. The continuities between good diet and cardiovascular health are obvious. For example, the sodium-restricted diet was able to improve ventricular-arterial coupling together with the arterial elastance of hypertensive HFpEF patients . ExercisThe control of comorbidities is also important in arterial stiffness and HFpEF. We take hypertension and diabetes as examples. Hypertension is a major risk factor of HFpEF. According to the recommendations of guidelines, blood pressure control of HFpEF hypertensive patients should be strict and even aggressive . Long-teclinicaltrials.gov (NCT01157481). Diuretics might be necessary in HFpEF patients. Despite their significant effects on symptoms in HFpEF patients, results from the ALLHAT trial suggested that, compared to amlodipine, lisinopril, or doxazosin, chlorthalidone significantly reduced the occurrence of new-onset HFpEF  blockades, beta-blockers, calcium channel blockers, and diuretics. No matter which mechanism is, arterial stiffness parameters like PWV could be reduced by most kinds of anti-hypertensive drugs. However, these drugs have their own features. RAS blockades are reported to protect from the change of vascular structure and subsequent arterial stiffness, other drugs may reduce PWV because of their influence on hemodynamics . But effet HFpEF . Even thSome advances were made in recent years. Though ACEI/ARB did not show much protective effect on HFpEF, the inhibition of RAAS is still an important approach to the management of HFpEF patients. Sacubitril/Valsartan (LCZ696) is a new superstar in the management of heart failure and hypertension. Two recently-released independent studies showed that sacubitril/valsartan inhibits the progress of diastolic dysfunction and arterial stiffness to HFpEF in rat models , 45. HowAs for the new treatment strategy for arterial stiffness, Tsai et al.  summarizHFpEF accounts for about half of the total heart failure. However, the understand of HFpEF is poor. Arterial stiffness is a well-established cardiovascular risk factor, and it is able to accelerate the pathogenesis and development of diastolic dysfunction. Mechanisms of the contribution of arterial stiffness to HFpEF are owing to the vascular effect, the ventricular-vascular interaction effect, and the linkage of renal function. Endothelial cells play key roles in this process. Unfortunately, current therapy on HFpEF did not significantly improve the mortality in HFpEF patients. Therapies aiming at arterial stiffness may become a new strategy for the improvement of HFpEF treatment in the future.The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author/s.DX: conception and design. CC and YL: manuscript writing. DX, CC, YL, and YX: final approval of manuscript. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.