Zootoca vivipara, as a model system. Our results demonstrated a correlation between risk‐averse and escape behavior at the among‐individual level, but only in gravid females. We found no significant correlations in either males or neonates. A striking result was the loss of association in postparturition females. This suggests that the “risk‐averse – escape” syndrome is ephemeral and only emerges in response to constraints on locomotion driven by reproductive burden. Moreover, parasites have the potential to dissociate the correlations between risk aversion and escape response in gravid females, yet the causal chain requires further examination. Overall, our findings provide evidence of differences in the association between behaviors within the lifetime of an individual and indicate that individual states, sex, and life stages can together influence the stability of behavioral syndromes.Mounting evidence has shown that personality and behavioral syndromes have a substantial influence on interspecific interactions and individual fitness. However, the stability of covariation among multiple behavioral traits involved in antipredator responses has seldom been tested. Here, we investigate whether sex, gravidity, and parasite infestations influence the covariation between risk aversion (hiding time within a refuge) and escape response  using a viviparous lizard,  Zootoca vivipara), we found that the “risk‐taking – escape” syndrome is contingent on sex, reproductive state, and parasite infestation, suggesting that individuals with different characteristics or life stages may choose specific combinations of behavioral traits as escape tactics. Our results may, to some extent, provide explanations for optimal escape theory and emphasize the importance of shifts in individual states in the variability of behavioral syndrome.The correlation of behaviors involved in an antipredator response is of paramount ecological importance, as premature flight or prolonged duration of remaining in a refuge can result in a loss of potential opportunities to increase fitness. Here, using common lizards ( We then quantified the “risk‐averse behavior” as (3) the time to emerge from a refuge after a simulated predator attack (T‐emerge). We characterized a “risk‐averse and escape” behavioral syndrome (hereafter “RAE syndrome”) by focusing on the correlation of T‐emerge with either Escape distance or Immobility. We predicted that (1) risk‐averse individuals will not only escape earlier  and further , but also emerge later once attacked. As such, T‐emerge should correlate positively with Escape distance, but negatively with Immobility Figure . Also, w22.1Z. vivipara is a small, terrestrial species  that has a broad distribution across northern Eurasia. In the Massif Central (France), females are live‐bearing, and gestation stage lasts approximately 2 months, from early June to mid‐July. After parturition, neonates emerge from a thin shell membrane within 1 h and thereafter are autonomous.The common lizard Ophionyssus  with a layer of sterilized soil as a substrate and a cardboard shelter  as a shelter. All lizards were reared under standardized conditions, with food and water provided ad libitum  followed a fixed order of behavioral assays: B1‐A1‐B2‐A2‐B3‐A3, while 49% (n = 51) followed a more flexible order: either B1‐A1‐A2‐B2‐A3‐B3 or B1‐B2‐A1‐B3‐A2‐A3. The different orders were used to test the effects of assay sequences. Risk‐averse and escape behavior tests were repeated twice for post‐parturition females. Neonates were also tested twice for both risk‐averse and escape behavior with 24 h rest between behavioral assays. Due to a time constraint (neonates have to be released within 3 days after birth), we were unable to arrange different orders of behavioral tests for neonates.We measured risk‐aversion (A) and escape behavior (B) for both adults and lab‐born neonates. All behavioral data were collected during the lizard's natural activity period (10 am–5 pm) at the same standard temperature (27 ± 2°C). Each behavioral test was repeated three times for adult males and gravid females. Due to logistical constraints, 51% of the adults (2.3.1L × W × H) equipped with an opaque plastic refuge  at one side and a heat source (25 W bulb) at the opposite side to provide a stimulus for basking. The wall of the box was opaque to prevent lizards from seeing their conspecifics during the trial. We filled the box with a layer of clean sand and changed the substrate for each trial. We also cleaned the terrarium and the refuge between each trial. The test started after an acclimation period of 5 min for each lizard. We then put lizards near the entrance of the refuge and simulated predation attacks with a paint brush to tap the tail until the lizard fled into the refuge . If the lizard was already inside the refuge (in rare cases), we simulated several attacks at the opening of the refuge. The experimental set‐up was isolated from the observer by being placed behind sheets. We used video cameras to record the behaviors and quantify the time until emergence. We calculated the latency time for the lizard's head to emerge from the refuge (T‐emerge) to quantify the risk‐averse behavior. If an individual did not emerge after 50 min , we arbitrarily assign the T‐emerge as the maximal recording time. Risk‐averse behavioral tests were conducted on the 8th, 11th, and 17th days of captivity for each adult individual.To assess the risk‐averse behavior, we followed the method in Le Galliard et al. . We reco2.3.2L × W × H) and recorded their behavioral responses to a simulated predator attack. We first placed the focal lizard under a darkened shelter for 1 min to acclimate the individual. We then lifted the shelter and immediately simulated continuous predation attacks by stimulating individuals with a paintbrush every second, until the lizard initiated an escape response. When the lizard stopped running for more than 2 s or ran to the end of the racetrack, the trial was considered finished. We defined the number of attacks to initiate a lizard's escape as the score of “Immobility” and the final escape distance as the “Escape‐distance.” The escape behavior was tested three times for each individual on the 6th, 10th, and 16th day of captivity of adult lizards. The same experimenter conducted all escape experiments to avoid any observer effects.To assess escape behavior, we chased lizards down a race track  for all traits of risk‐averse and escape behavior based on the formula:VRa is the among‐individual variance, VRw is the within‐individual variance, and VRsite is the among‐site variance.Repeatability, the measure of behavioral consistency, is often estimated by using the intra‐class correlation coefficient  to quantify the magnitude of differences in repeatability or variance components between different treatments:Vx,2 can be attributed to the values of the repeatability or variance component of females, while Vx,1 is the value of males. Similarly, when considering the effects of gravidity or infestation status, Vx,2 represents the repeatability or variance components of gravid females or parasite‐free individuals, while Vx,1 represents that of post‐gravid females or parasite‐infested individuals.Following Royauté and Dochtermann , we nextWe extracted the posterior distributions of effect size and computed the 95% credibility interval. The Bayesian model setting and inspection of convergence have been set the same as the models for examining behavioral syndromes afterward . This analysis allowed us to investigate whether the magnitude of the correlation significantly differed between different treatment groups. Similar model structures and analyses were also built for neonates following the procedures above.We used the mode of the posterior distribution as the point estimate at a given statistic and the 95% highest posterior density as the 95% credibility interval. Credibility intervals that do not overlap with zero were considered significant. We specified random intercepts for both individual identities and populations. We first ran the model for all adults with sex as a fixed effect and body condition as a covariate . We then ran similar models for different sexes and different individual states, with body condition included as a covariate. Moreover, gravid females tend to become less mobile as they approach parturition and may bear different reproductive burdens  compared with male neonates. The rest of behavioral traits for neonates exhibited no differences in either repeatability or variance components between the sexes  indicates that individuals are more behaviorally distinct from each other, whereas a higher within‐individual variance (VRw) reflects higher behavioral plasticity  than males in all three behavioral traits, and this intersexual discrepancy in behavioral plasticity is enhanced after parturition , a higher behavioral plasticity may, to some extent, reduce the overall predation risks for infested individuals  and a shorter escape distance (negative correlation between Immobility and T‐emerge). However, contrary to our expectations, the syndrome did not exist in neonates, males, or post‐gravid females. The expression of the syndrome therefore seems to mainly depend on the locomotor burden imposed by the litter  should be considered to better explore escape response. Further, traditional measurements on risk‐averse behavior may be affected by housing stress, activity, and explorative behavior, which should be controlled in future experimental designs. In addition, mechanisms of how parasites affect behavioral syndromes requires manipulated infestations to disentangle direct and indirect effects of parasitism on the stability of behavioral syndromes study. Last, we suggest expanding the types of measurements to quantify escape behavior. We encourage behavioral ecologists to incorporate more behaviors for a better understanding of behavioral covariation in the escape process.5In this study, we provide insights on how different sexes and state‐dependent factors can affect personality and the stability of behavioral syndromes. In the common lizards, the among‐individual correlation between risk‐averse and escape behavior is contingent on sex, reproductive state, and parasite infestation, indicating that individuals with different characteristics or life stages may exhibit specific combinations of behavioral traits as escape tactics. The variability of a behavioral syndrome can therefore be masked if one focuses on pooled sexes or fails to consider the life stage, individuals status, or the ecological environment of focal individuals. Our findings motivate future studies to integrate multiple attributes of organisms to provide underlying mechanisms of behavioral syndromes' variability and reveal how the emergence of behavioral syndromes may impact population dynamics and species interactions.Qiang Wu: Conceptualization ; formal analysis (lead); investigation ; methodology ; visualization (lead); writing – original draft (lead). Alexis Rutschmann: Data curation (supporting); investigation ; methodology ; writing – review and editing . Donald B. Miles: Investigation ; methodology ; supervision ; validation ; writing – review and editing . Murielle Richard: Data curation ; investigation ; methodology ; project administration ; supervision ; validation ; writing – review and editing . Jean Clobert: Funding acquisition ; investigation ; methodology ; supervision ; validation ; writing – original draft ; writing – review and editing .The authors declare that they have no competing interests.Figures S1–S6Click here for additional data file.


Semaglutide may therefore represent an important novel therapeutic option for obesity-related HFpEF. Obesity-related heart failure with preserved ejection fraction (HFpEF) has become a well-recognized HFpEF subphenotype. Targeting the unfavorable cardiometabolic profile may represent a rational treatment strategy. This study investigated semaglutide, a glucagon-like peptide-1 receptor agonist that induces significant weight loss in patients with obesity and/or type 2 diabetes mellitus and has been associated with improved cardiovascular outcomes. In a mouse model of HFpEF that was caused by advanced aging, female sex, obesity, and type 2 diabetes mellitus, semaglutide, compared with weight loss induced by pair feeding, improved the cardiometabolic profile, cardiac structure, and cardiac function. Mechanistically, transcriptomic, and proteomic analyses revealed that semaglutide improved left ventricular cytoskeleton function and endothelial function and restores protective immune responses in visceral adipose tissue. Strikingly, treatment with semaglutide induced a wide array of favorable cardiometabolic effects beyond the effect of weight loss by pair feeding. Glucagon-like peptide-1 receptor agonists may therefore represent an important novel therapeutic option for treatment of HFpEF, especially when obesity-related. Almost 50% of patients with HF suffer from heart failure with a preserved ejection fraction (HFpEF).,For a long time, no treatment options to improve outcomes in HFpEF were available, despite a large number of randomized clinical trials being executed.This is in line with data on other interventions that affect body weight. Indeed, marked weight loss achieved through bariatric surgery is associated with improvements in glucose levels and cardiac structure and function in patients with obesity and T2DM.,NCT04788511), STEP-HFpEF-DM , and a dual acting GLP-1/GIP in Participants With Heart Failure With Preserved Ejection Fraction and Obesity; NCT04847557)—are currently recruiting participants with obesity-related HFpEF for treatment with semaglutide or tirzepatide.A group of drugs that is of particular interest in this respect are the glucagon-like peptide-1 receptor agonists (GLP-1RAs). Long-acting GLP-1RAs exert substantial and sustained body weight losses,Possible mechanisms of action on the cardiovascular system of GLP-1RAs include anti-inflammatory, antiatherosclerotic, vasodilatory, and other hemodynamic effects, and life-long exposure of GLP-1 is associated with prevention of HF.,Therefore, we investigated the cardiometabolic effects of semaglutide in a representative mouse model of HFpEFA detailed methods section is provided in the All supporting data are available within this paper and the All animal studies were approved by the Centrale Commissie Dierproeven (CCD) license number AVD105002016487 and the Animal Care and User Committee of the Groningen University (permit number 16487-07-04) and conducted in accordance with the ARRIVE  guidelines.,We have shown previously that a murine model of HFpEF has several similarities with human HFpEF.After pump implantation, mice on HFD were assigned to a group with subcutaneous semaglutide treatment (n = 12) or vehicle treatment, phosphate-buffered saline (n = 16) during last 4 weeks of this study. Semaglutide was uptitrated over 5 days to a final dose of 9 nmol/kg/d, and this final dose was continued during 23 days.To determine the extent to which the cardiometabolic effects of semaglutide occurred by changes in body weight or body composition caused by reduced food intake, we designated a separate group of mice, after 8 weeks and pump implantation, to a pair feeding (PF) (n = 8) protocol. With this technique, the amount of food consumed by the semaglutide groups (grams of chow per day) is exactly matched to that consumed by the pair-fed group on a daily basis. A schematic overview of the experimental design is displayed in Exercise capacity was determined using voluntary wheel running. After 2 days of acclimatization to the running wheel, we measured running distance during 5 constitutive days in the week prior to sacrifice and the average running distance (km/d) was calculated afterward.After 12 weeks of intervention, mice were subjected to an oral glucose tolerance test. Fasting glucose was measured after 12 hours of fasting followed by administration of an oral bolus of glucose (2 g/kg) and tail vein blood samples were measured using an Accu-Chek Aviva glucose analyzer (Roche Diagnostics) at multiple time points . Area under the curve was calculated to determine the rate of glucose clearance, as described previously.Body mass composition  was determined using minispec LF90II body composition analyzer (Bruker Optics) in week 12 according to manufacturer’s protocol.Three days prior to sacrifice, echocardiographic measurements were performed using a Vevo 3100 system equipped with a 40-MHz MXX550D linear array transducer  to assess cardiac dimensional and functional parameters. Offline speckle tracking  was used to determine global longitudinal strain and reverse peak longitudinal strain rate.At week 12, mice were anesthetized with isoflurane and sacrificed. Blood was drawn using apical puncture, collected in EDTA tubes, and spun down, and then the plasma was collected and stored. The heart with all its compartments was rapidly excised, rinsed in ice cold 1 mol/L potassium chloride (Merck Millipore), weighed, and stored for further analyses. Lungs were excised and their wet weight was measured. Visceral adipose tissue (VAT) was collected and stored.2) was visualized with immunofluorescent staining with germ agglutinin fluorescein isothiocyanate (Sigma-Aldrich) as previously reported.Left ventricular (LV) mid-transverse sections were fixed in 4% paraformaldehyde before paraffin embedding and cut into 4-μm thick sections. Masson trichrome stain was performed to detect collagen deposition as a measurement of fibrosis, as previously described.Rplp0 (36B4), and presented as fold change to the Ctrl group. Primer sequences that were used are displayed in Total RNA from LV tissue was extracted using TRI Reagent (Sigma-Aldrich), and complementary DNA synthesis was performed using the QuantiTect RT kit (Qiagen). Gene expression levels were determined using iQ SYBR green super mix and the CFX384 Touch Real-Time PCR system (Bio-Rad). Expression levels were normalized to reference gene Individual cardiomyocytes were isolated mechanically from frozen cardiac tissue, and myofilament function measurements were executed as previously described.Total ketone bodies were measured in the plasma with the Autokit Total Ketone bodies (FUJIFILM) according to manufacturer’s instructions.RNA was extracted from VAT tissue using Lysing matrix D beads  and standard TRIzol extraction (Thermo Fisher Scientific). RNA quality was determined using RNA Pico Chips on Bioanalyzer 2100 (Agilent) and TruSeq Stranded mRNA Libraries (Illumina) were generated from high-quality total RNA (RNA integrity number >7.5). Samples were subjected to paired end sequencing with NovaSeq 6000 (Illumina HiSeq). Reads were aligned to mouse reference genome (GRCm38– mm10) using STAR (version 2.7.3a) and read quantification was performed with Salmon (version 1.2.0)Single-nucleus suspensions for LV tissue were generated by a series of cellular membrane lysis, differential centrifugation, and filtration steps. Isolated nuclei were loaded into the Chromium Controller  for an estimated recovery of 5,000 cells per sample. Processing of libraries was performed according to the manufacturer’s instructions with few modifications. Samples were sequenced on the NextSeq500/550 Illumina Platform using NextSeq 500/550 High Output Kit . After sequencing, preprocessing into unique molecular identifier matrices was performed using 10x Genomics Cell Ranger. Ambient messenger RNA was removed with SoupX (Sanger Institute), and cells were assigned a doublet score with Scrublet .35 Cell P < 0.05). Mass spectrometry data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with data set identifier PXD034625.Total proteins were isolated from LV and plasma followed by denaturation, reduction, alkylation, and tryptic digestion. Peptides were fractionated off-line with an Dionex Ultimate 3000 HPLC system (Thermo Fisher Scientific), and subsequently separated with Easy-nLC 1200 coupled online to an Orbitrap QExactive HF mass spectrometer (Thermo Fisher Scientific). Mass spectrometry data were acquired using a data-independent method as detailed in the extended methods in the P value using GraphPad Prism  or SPSS . The area under the curve was computed using the trapezoid rule. For proteomics, the false discovery rate was set to 0.01, and data are presented as difference of average (>0.5) and the −log10 Student’s t-test (P < 0.05) were used to compare between groups.All values are presented as mean ± SEM. Normality of data was tested with Shapiro-Wilk test. Kruskal-Wallis test was used for comparisons among >2 groups followed by Dunn multiple comparisons test with an adjusted P < 0.05 was considered statistically significant . For detailed transcriptomic and proteomic statistics, we refer to the extended methods in the Treatment with semaglutide was associated with reduced food intake during the first 14 days and normalized afterwards . Semagluversus vehicle-treated mice  . It alsoTo better understand the underlying mechanism of semaglutide treatment, we performed proteome analysis of the LV. For this analysis, we compared the effect of semaglutide vs vehicle and the effect of PF vs vehicle. Principal component analysis showed distinct clustering that was more prominent in semaglutide than in mice on PF . Both seTo dissect the semaglutide response in the LV further, we then performed single nucleus RNA sequencing in the LV of mice under conditions similar to the proteomics data. Cell clustering and combined manual and automatic annotation identified 13 major cell types: T cells, natural killer cells, B cells, macrophages, smooth muscle cells, pericytes, endothelial cells, fibroblasts, endocardial cells, Schwann cells, mesothelial cells, lymphatic cells, and ventricular cardiomyocytes, as visualized in a uniform manifold approximation and projection  for det and 4. WGPX1, SOD1, PRDX1, PRDX2, GSTP1, GPX3, G6PD—and cytoskeleton regulation with related genes—ACTR2, GMFG, ARPC4, ARPC5, RAC1  weight loss caused by lifestyle interventions in obesity-related HFpEF patients improved exercise capacity but had no effect on cardiac structure or function.,In our study, we used a PF protocol to match the semaglutide-induced reduction in food intake, with subsequent weight loss, to find out whether semaglutide exerts additional drug-induced effects beyond weight loss alone. Semaglutide resulted in an ∼60% food reduction in week 1, ∼30% in week 2, and ∼10% in weeks 3 and 4. Matching this food intake, however, was not enough to improve glucose homeostasis in our PF group, as observed with other (true) caloric restriction protocols used in mice. Pak et al,,,A distinct feature of HFpEF is the presence of multiple comorbidities and together with hypertension and aging, obesity is a main risk factor for HFpEF. Obesity indirectly promotes insulin resistance and hyperglycemia and has additional direct deleterious effect, given that adipose tissue is highly metabolically active and involved in promoting a systemic proinflammatory state.Inhibition of systemic metabolic inflammation with glucose-lowering drugs is thought to enhance endothelial and cardiomyocyte function,,,,Myocardial diastolic stiffness is among the hallmarks of HFpEF and results from both myocardial fibrosis and increased cardiomyocyte stiffness. Targeting these 2 components of myocardial diastolic stiffness may therefore be an attractive therapeutic intervention for HFpEF. In this study we observed that semaglutide improved cardiac structure and reduced LV hypertrophy through reduced fibrosis and fibrosis mediators. Other vitro studies observed a beneficial effect of GLP-1RAs on ANGII-induced cardiac fibrosis as well.Cardiomyocyte stiffness refers to changes in relaxation and filling properties and includes alterations in myofilament deactivation by titin (a giant sarcomeric protein)In this study we used a multifactorial preclinical HFpEF model that resembles the cardiometabolic human HFpEF phenotype to a large extent. Although this model includes aging, obesity, impaired glucose handling, and female sex, the model is still not representative of the entire spectrum of HFpEF. The number of comorbidities in humans with HFpEF often is even larger, and direct translation of our findings into clinical practice must be done cautiously. Also, we only used aged female mice with HFpEF. In humans, the HFpEF phenotype is more prevalent in aging women and less common in aging men,Given their promising cardiovascular effects in patients with T2DM, GLP-1RAs, including semaglutide, are currently being evaluated in patients with HFpEF. However, it remains unclear whether the potential effects of semaglutide are pathway- and drug-specific or whether they are indirectly caused by weight loss. Here, we evaluated the cardiometabolic effects of semaglutide in a validated HFpEF mouse model. We show that the cardiometabolic effects of semaglutide transcends those of weight loss alone, and we demonstrate that semaglutide induces structural and functional changes in the heart and adipose tissue that are associated with improved cardiac structure and cardiac function. Therefore, this study provides mechanistic evidence that semaglutide may represent an effective novel therapeutic option for patients with obesity-related HFpEF.NCT04788511) and STEP-HFpEF-DM (NCT04916470)NCT03574597) addresses whether semaglutide affects cardiovascular outcomes in patients with obesity. Preclinical studies such as this study help in understanding the mechanistic basis for observed clinical results.HFpEF is a major and growing public health problem.PerspectivesCOMPETENCY IN MEDICAL KNOWLEDGE: This study provides insights into the potential use of GLP-1RAs as body-weight and adipose-tissue modifying treatment options, and how they may have additional beneficial effects on the cardiometabolic profile, cardiac structure and cardiac function in obesity-related HFpEF.TRANSLATIONAL OUTLOOK: The present study is the first study to show that the GLP-RA semaglutide may be potentially useful for the treatment of patients with obesity-related HFpEF.In conclusion, we have shown that in a multifactorial experimental animal model of HFpEF, the cardiometabolic effects of semaglutide extend beyond the effects of weight reduction caused by PF alone. Our results provide mechanistic evidence that GLP-1RAs, particularly semaglutide, could be a potential novel therapeutic option for patients with obesity-related HFpEF.This study was supported in part by Novo Nordisk, the manufacturer of semaglutide, who financed the laboratory supplies and -omics studies. The University Medical Center Groningen, which employs several of the authors, has received research grants and/or fees from AstraZeneca, Abbott, Boehringer Ingelheim, Cardior Pharmaceuticals GmbH, Ionis Pharmaceuticals, Inc, Novo Nordisk, and Roche. Dr Lam has received support from a Clinician Scientist Award from the National Medical Research Council of Singapore; has received research support from Bayer and Roche Diagnostics; has served as consultant or on the Advisory Board/Steering Committee/ Executive Committee for Abbott, Actelion, Alleviant Medical, Allysta Pharma, Amgen, AnaCardio AB, Applied Therapeutics, AstraZeneca, Bayer, Boehringer Ingelheim, Boston Scientific, Cytokinetics, Darma Inc, EchoNous Inc, Impulse Dynamics, Ionis Pharmaceutical, Janssen Research and Development LLC, Medscape/WebMD Global LLC, Merck, Novartis, Novo Nordisk, Prosciento Inc, Radcliffe Group Ltd, Roche Diagnostics, Sanofi, Siemens Healthcare Diagnostics, and Us2.ai; and is a co-founder and a nonexecutive director of Us2.ai. Dr de Boer has received speaker fees from Abbott, AstraZeneca, Bayer, Novartis, and Roche. All Novo Nordisk authors disclose the company markets semaglutide for the treatment of diabetes and obesity, separately, and have multiple clinical studies ongoing. Also, all Novo Nordisk authors report they have minor amount of shares as part of employee benefits. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.


The genotyping of the 29 functional SNPs was carried out using real-time polymerase chain reaction (PCR) with TaqMan probes. Drug survival was evaluated with Cox regression and Kaplan–Meier curves. The multivariate analysis showed that the HLA-C rs12191877-T  and TNF-1031 (rs1799964-C)  polymorphisms are associated with anti-TNF drug survival, while TLR5 rs5744174-G , CD84 rs6427528-GG  and PDE3A rs11045392-T together with SLCO1C1 rs3794271-T  are related to UTK survival. The limitations are the sample size and the clustering of anti-TNF drugs; we used a homogeneous cohort of patients from 2 hospitals only. In conclusion, SNPs in the HLA-C, TNF, TLR5, CD84, PDE3A, and SLCO1C1 genes may be useful as biomarkers of drug survival of BTs indicated for psoriasis, making it possible to implement personalized medicine that will reduce financial healthcare costs, facilitate medical decision-making and improve patient quality of life. However, further pharmacogenetic studies need to be conducted to confirm these associations.Biological therapies (BTs) indicated for psoriasis are highly effective; however, not all patients obtain good results, and loss of effectiveness is the main reason for switching. Genetic factors may be involved. The objective of this study was to evaluate the influence of single-nucleotide polymorphisms (SNPs) on the drug survival of tumor necrosis factor inhibitors (anti-TNF) medications and ustekinumab (UTK) in patients diagnosed with moderate-to-severe psoriasis. We conducted an ambispective observational cohort study that included 379 lines of treatment with anti-TNF ( Psoriasis is a chronic autoimmune skin disease with a prevalence of 2–4% in Europe and the United States . It is cGenetic, immunological and environmental factors can trigger psoriatic lesions, which are maintained by abnormalities in cutaneous immune responses. Activation of plasmacytoid dendritic cells, keratinocytes, natural killer cells and macrophages that secrete cytokines such as interferons beta and gamma IFN-β and IFN-γ), interleukin 1-beta (IL1-β), and tumor necrosis factor alpha (TNF-α). This leads to the activation of myeloid dendritic cells, through TLRs (toll-like receptor) receptors, which promote the production of IL12 and IL23, which regulate the differentiation and proliferation of helper T lymphocytes Th1, Th17 and Th22). Th1 cells produce TNF-α and IFN-γ, Th2 cells produce IL22, while Th17 cells, in addition to producing TNF-α and IL22, also secrete IL17. These cytokines activate the hyperproliferation of keratinocytes in the epidermis and lead to the appearance of epidermal hyperplasia  and 23–40), whereas median survival for the CC genotype was only 14 months (11–24)  .TNF-1031 SNP and anti-TNF survival; however, in the TNF-238 and TNF-308 SNPs statistical significance was not maintained. The Kaplan–Meier anti-TNF survival curves for the TNF gene polymorphisms are shown in TNF-238 [rs361525], log-rank = 0.009, and log-rank = 0.007) and in TNF-308 [rs1800629], genotypic model; plog-rank = 0.04).Furthermore, an influence of the various polymorphisms of the TNF gene on increased survival of anti-TNF drugs was observed . SubsequTNF-1031 (rs1799964) SNP in patients treated with anti-TNF drugs . Median survival for the TNF-1031 (rs1799964)-CT heterozygotic genotype was 44 months (25–70), greater than median survival for the TT and CC homozygotic genotypes, respectively  and the C allele of the TNF-1031 (rs1799964) SNP  were associated with longer anti-TNF drug survival , and the median survival for the TT genotype was 48 (23–NA) months. It was 37 (26–94) months for heterozygotic and 25 (18–40) months for CC homozygotic patients . Median survival for the HLA-C rs12191877-T allele was 36 (21–112) months, while in CD84 rs6427528-GG it was 40 (27–66) months, 23 (18–40) for AG and 10 (NA–NA) in the case of patients carrying the AA genotype, respectively. Finally, median UTK survival in TLR5 rs5744174-G was 41 (26–67) months, compared to 34 months for patients carrying the AA genotype , CD84 rs6427528-A  and PDE3A rs11045392 together with SLCO1C1 rs3794271-T  SNPs, adjusted for the psoriatic arthritis variable  polymorphism, adjusted for age and bio-naivety, were associated with longer pharmacological survival of anti-TNF drugs, and that patients who had not developed psoriatic arthritis, and those carrying the G allele of the TLR5 rs5744174 polymorphism, the A allele of the CD84 rs6427528 polymorphism or the T allele of the PDE3A rs11045392 polymorphism, which was in linkage disequilibrium with SLCO1C1 rs3794271, were associated with longer survival of UTK.On the other hand, we evaluated the impact of the SNPs in functional genes selected for this study on the survival of the BTs used in psoriasis, finding that patients carrying the T allele of the HLA-C rs12191877 SNP with longer survival of anti-TNF drugs, compared to patients carrying the wild-type homozygous (CC) genotype  is in line with previous studies [HLA-C rs12191877 polymorphism was associated with the response to anti-TNF drugs (a reduction of 75% in psoriasis area and severity index score [PASI 75] at 3 months) in 144 white patients (from Spain)  [The association observed in the patients in this study carrying the T allele of the  studies . Human l studies ,34. Spec studies . Consequ studies ,27,36. I= 0.027) .HLA-C*0602 allele  [HLA-Cw*06 allele showed a higher risk of not responding to anti-TNF therapy  [p > 0.05) [Moreover, this SNP is in linkage disequilibrium with the  allele) . The pre allele) ,28,39,40 0.0001) ,41. Howe > 0.05) .TNF-1031 (rs1799964) polymorphism of the tumor necrosis factor gene promoter region and survival of anti-TNF  [p = 0.047; 85.5% vs. 65.7% in month 6, p = 0.038). Specifically, INF attained the greatest response at 3 months  and at 6 months  [Our study observed an association between the C allele of the  vs. TT) . The imp vs. TT) ,44,45. H= 0.019) .TLR5 rs5744174 SNP showed longer survival of UTK than those carrying the wild-type AA genotype . These results are in line with the study conducted by Loft and his team on 230 white patients (from Denmark) with psoriasis treated with UTK. It was observed that the patients carrying the TLR5 rs5744174-C allele  showed a better response (ΔPASI after 3 months) to UTK treatment  [TLR5 gene, belonging to the toll-like receptor (TLR) family, codes for a transmembrane protein in which the toll interleukin receptor (TIR)-type intracellular domain binds to IL-1, generating an inflammatory cascade when the exterior domain recognizes bacterial flagellin [TLR5 rs5744174 polymorphism, IL-1 levels decrease and CCL20 and IFN-γ levels increase, reducing the inflammatory response [With regard to treatment with UTK, it was found that patients carrying the G variant allele of the lagellin ,47. Therresponse ,49,50.CD84 rs6427528 receptor gene polymorphism on the response of autoimmune diseases to BTs has been studied. In particular, a meta-analysis of genome-wide association studies (GWAS) with white patients (13 studies/2706 patients) diagnosed with rheumatoid arthritis and treated with anti-TNF showed that the CD84 rs6427528-AG genotype was associated with greater effectiveness of treatment with ETN (733) (p = 0.004) [CD84 rs6427528-AG genotype was associated with a better response (ΔPASI at 12 weeks) to treatment with ETN  [CD84 rs6427528 polymorphism was associated with UTK survival . These results are interesting, since genetic abnormalities in the CD84 gene, belonging to the CD2 superfamily of cell surface receptors, even in the non-coding region (3′UTR), mean greater expression of this gene in mononuclear peripheral blood cells, and consequently deregulation of T and B cell signaling, as well as in the adhesion and activation of immune cells [The effect of the = 0.004) . In psor= 0.025) . Our stune cells ,52.PDE3A rs11045392 SNP, which is in linkage disequilibrium with SLCO1C1 rs3794271, showed a statistically significant association between the T allele or the TT and CT genotypes, compared to the CC genotype, and UTK survival . In psoriasis, a study evaluated the influence of the SLCO1C1 rs3794271 and PDE3A rs11045392 polymorphisms on anti-TNF response in 130 white patients (from Spain) and showed that patients carrying the C allele obtained a better response (ΔPASI after 3 months) (p = 0.00057) [PDE3A gene is expressed mainly in cardiac tissue and encodes a phosphodiesterase, which is responsible for internal control of nucleotide signaling, while the SLCO1C1 gene encodes a sodium-independent transporter with high affinity for the thyroid hormone in brain tissue.Finally, the Among the main limitations of our study that should be highlighted is the limited sample size, which may be responsible for the lack of statistical association found between the SNPs and pharmacological survival. Nevertheless, we obtained important and representative results which show the influence that certain genetic polymorphisms have on the probability of changing treatment with anti-TNF drugs or UTK in patients with moderate-to-severe psoriasis. The fact that the four anti-TNF drugs  were grouped together in the statistical analysis may seem to be a limitation; however, grouping them in this way increases the statistical power, and they are usually studied together. In addition, it should be pointed out that this study was carried out with patients from only two hospitals, all diagnosed with moderate-to-severe psoriasis, following the same therapeutic protocols, by the same team of dermatologists. This makes it possible to achieve a high degree of homogeneity in the cohort, as well as in the process of collecting the variables.HLA-C rs12191877 and TNF-1031 (rs1799964) SNPs are associated with anti-TNF drug survival, while TLR5 rs5744174, CD84 rs6427528 and PDE3A rs11045392 together with SLCO1C1 rs3794271 are associated with UTK survival. Consequently, these polymorphisms could act as survival biomarkers for the various BTs in patients with moderate-to-severe psoriasis and could be useful for direct selection of the appropriate biological therapy, thereby achieving more individualized medicine with lower pharmaceutical cost and better results for the patient. Although more studies in larger cohorts will be needed to confirm the prognostic value of the biomarkers, the information on the persistence, safety and tolerability of treatment in the short and long term may help patients and healthcare professionals in making decisions to begin treatment with a BT [To sum up, the results suggest that the We conducted a prospective and retrospective observational cohort study.This study was carried out with the approval of the Ethics and Research Committee of the Sistema Andaluz de Salud  and in accordance with the Declaration of Helsinki . The patients signed a written informed consent form for collection of saliva samples and their donation to the biobank. The samples were coded and treated confidentially.The study included 260 white patients diagnosed with modern-to-severe psoriasis treated with anti-TNF and UTK drugs, recruited at the Hospital Universitario Virgen de las Nieves, Granada, Spain, and at the Dermatology Clinic, Department of Clinical, Internal, Anesthesiological and Cardiovascular Sciences, La Sapienza Università di Roma, Italy, during the period from January 2019 to November 2021 . The incThe socio-demographic information, including sex, age and BMI, was collected from the patients’ medical records at the beginning of the study. We collected the clinical features of the psoriasis, including age at diagnosis of psoriasis, family history of psoriasis, baseline PASI, type of psoriasis  and location of the lesions, according to the consensus document on evaluation and treatment of moderate-to-severe psoriasis: Psoriasis Group of the Spanish Academy of Dermatology and Venereology [After the patients’ inclusion and signing of the informed consent, saliva samples were collected with buccal swabs . The DNA was extracted using the QIAamp DNA Mini extraction kit , following the specifications provided by the manufacture for purifying DNA from saliva, and stored at −20 °C. The DNA concentration and purity were measured using a NanoDrop 2000 UV spectrophotometer with the absorbance ratio at 280/260 and 280/230.p-value > 0.05 in the Hardy–Weinberg equilibrium test; (4) missing genotype rate between cases and control < 0.05.To assess the internal consistency of the genotyping, 10% of the results were confirmed by Sanger sequencing analysis. The real-time PCR and the Sanger sequencing were performed at the Pharmacogenetics Unit of the Hospital Universitario Virgen de las Nieves, Granada, Spain. Subsequently, quality control to eliminate rare variants and samples with missing data of the genotypes was carried out. The criteria for SNP quality control were (1) missing genotype rate per SNP < 0.05; (2) minor allele frequency > 0.01; (3) The data on treatment with anti-TNF and UTK biological therapies were recorded, including the dates of starting and finishing the therapy and the reasons for discontinuation. When treatment with a drug is discontinued, a new line of treatment with another drug is initiated. Therefore, the survival of the drug is defined as the time from initiation to discontinuation of treatment with the particular BT. The data were obtained from the patients’ medical records.First, the study sample size was calculated to obtain a precision of 1 unit in the estimate of the logarithm of an odds ratio using a two-sided 95% normal asymptotic confidence interval, based on previous studies.The patient characteristics were collected and presented as frequencies with percentages for the qualitative variables. The quantitative variables were expressed as mean (plus or minus standard deviation) for the variables with normal distribution or medians and percentiles (25 and 75) for those with non-normal distribution. The Lilliefors (Kolmogorov–Smirnov) test was used to evaluate normality.We used the Kaplan–Meier survival curve with the log-rank test to compare survival for patients treated with different BTs and the associations of demographic, clinical and genetic variables. The association with SNPs was evaluated in multiple models , which were defined as follows: genotypic (DD vs. Dd vs. dd), dominant  vs. dd) and recessive ), where D is the major (wild-type) allele and d the minor (variant) allele. Moreover, a univariate and multivariate Cox regression analysis was performed by calculating the hazard ratio (HR) and the 95% confidence interval (95% CI) to predict the risk factors of discontinuing treatment with BTs. For the multivariate analysis, we used the Cox proportional risks regression model, taking into account the variables associated with statistically significant results in the bivariate analysis of drug survival (backward stepwise selection method).p < 0.05. The data analysis was performed with the R 4.0.2 program [All the tests were two-sided, with a significance level of  program . The Har program ,57,58.HLA-C rs12191877 SNP or the C allele of the TNF-1031 (rs1799964) SNP are associated with greater pharmacological survival of anti-TNF drugs, while patients who have not developed psoriatic arthritis or are carriers of the G allele of the TLR5 rs5744174 polymorphism, the A allele of CD84 rs6427528 or the T allele of PDE3A rs11045392, which is in linkage disequilibrium with SLCO1C1 rs3794271, are associated with longer UTK survival. Consequently, these results confirm that these genetic polymorphisms could be useful as pharmacological survival biomarkers for biological therapies indicated for psoriasis, increasing the current scientific evidence. This information will make it possible to implement personalized medicine that would reduce economic healthcare costs, facilitate medical decision-making and improve patient quality of life. However, further pharmacogenetic studies need to be conducted to confirm these associations.Our results suggest that patients with moderate-to-severe psoriasis under treatment with TNF inhibitor drugs or UTK show greater pharmacological survival of UTK. Furthermore, various genetic polymorphisms associated with BT survival have been found. Patients carrying the T allele of the


Heart failure with preserved ejection fraction (HFpEF) comprises about 50% of the cases of heart failure (HF), but so far there is no effective treatment strategy. This study used bibliometric methods to analyze the scientific literature on HFpEF in 2009 to 2020, and evaluate the global scientific output of HFpEF research, in order to explore the research status and trends in this field.Documents about the HFpEF research published in 2009 to 2020 were retrieved from Science Citation Index Expanded (SCIE) in Web of Science. This study used bibliometrix R-package, VOSviewer, and CiteSpace to conduct the bibliometric analysis.A total of 1971 documents (1508 articles and 283 reviews) were retrieved to construct the local HFpEF literature collection for analysis. The number of annual documents had increased year by year in general, from 24 to 353. Relevant documents were mainly written in English, and mostly focused on the field of “Cardiovascular System Cardiology.” USA ranked first in the relevant countries/regions with most documents, and the leading affiliation was Mayo Clin. Shah SJ was the most productive author, while Borlaug BA ranked highest among the local cited authors and G-index. Circulation was the most local cited source, while Eur J Heart Fail published the most documents and was rated as the top source in terms of G-index. “Paulus WJ, 2013, J Am Coll Cardiol” was the top local cited document within the local HFpEF literature collection, while “Owan TE, 2006, New Engl J Med” outside the local HFpEF literature collection was the most local cited reference. The keywords such as “mortality,” “dysfunction,” “diagnosis,” “outcomes,” and “diastolic dysfunction” were most frequent, while “hemodynamics,” “comorbidity,” “myocardial infarction,” “inflammation,” and “phenotype” indicated research frontiers or emerging trends. Furthermore, this study also found some deeper bibliometric relationships through bibliographic networks.Due to the multi-dimensional bibliometric analysis, this study shows a wide view of scientific productivity related to HFpEF, and provides valuable guidance for researchers interested in HFpEF, assisting them in understanding the research status, identifying potential collaborators, discovering research hotspots and frontiers, and conducting more in-depth research. Heart failure with preserved ejection fraction (HFpEF) is the most common type of HF, and it accounts for more than half of the cases of HF.,4-14 HFpEF is characterized by normal or near normal left ventricular ejection fraction, so the prognosis of HFpEF patients is often falsely considered to be better than that of heart failure with reduced ejection fraction (HFrEF) patients. However, the morbidity, mortality, acute exacerbation rate, readmission rate, and prognosis of HFpEF are all similar to those of HFrEF.,11,13-17Heart failure (HF) is the terminal stage of various cardiac diseases, with significant morbidity and high mortality worldwide.,18 In the past 2 decades, the standard treatment of HF has been popularized, which has significantly reduced the hospitalization rate and improved the survival rate of patients with HFrEF. HFpEF currently lacks a successful treatment strategy to improve prognosis. This is attributed to incomplete understanding of HFpEF pathophysiology, patient heterogeneity, and mismatch between treatment mechanisms and major pathophysiologic processes. HFpEF is associated with a variety of medical complications and pathophysiological pathways or clinical phenotypes, accompanied by multiple organ system disorders.,12,24 The important clinical phenotypes of HFpEF include diabetes, hypertension, lung disease, chronic kidney disease, obesity, and so on. Personalized techniques based on individuals’ phenotypic traits, diagnosis, and pathophysiology stratification are needed to replace “one-size-fits-all” therapy for HFpEF.,22,25 HFpEF, in particular, should be handled differently depending on its phenotypes.,19 Only addressing phenotypic diversity of HFpEF can tailor more personalized therapies for specific HFpEF phenotypes. In summary, HFpEF represents one of the largest unmet clinical needs in the current cardiovascular medicine,,25-27 so there is an urgent need to develop new treatments for patients with HFpEF.In fact, the etiology, pathophysiology, and management of HFpEF and HFrEF are very different. Some bibliometric tools have been widely used by researchers to evaluate the impacts of documents, contributions of authors/affiliations/countries, patterns of authorship, and the main directions of future research in a clinical research topic. Clinical researchers should develop search strategies, retrieve relevant documents from literature databases, and use bibliometric methods to conduct multifaceted bibliometric analysis of these documents to find clinical research hotspots and determine research directions in a purposeful and targeted manner. At present, there are some bibliometric studies in the field of cardiovascular diseases,-32,45 one of which is on HFpEF. A bibliometric study conducted by Edlinger et al showed a great increase in research on HFpEF in the United States, Japan, and continental Europe, and identified RAAS-blockade and 5-phosphodiesterase-inhibition as a therapeutic trend in HFpEF. This study will take the bibliometric analysis of HFpEF a step further to provide a more comprehensive perspective for clinical researchers.Clinical researchers should extensively collect literature and accumulate relevant professional knowledge in the direction of related disciplines to ensure the innovation, scientificity, and non-repetitiveness of the clinical research topics. Bibliometrics is a widely accepted research method, which has been carried out in clinical research topics. Based on statistics and visualization technology, bibliometrics makes quantitative and qualitative analysis on the published academic literature in a specific clinical research topic, describes knowledge structure and tracks development trend. Bibliometric analysis usually includes the following steps: putting forward a research question, retrieving databases, collecting and analyzing data, drawing maps, preparing, and publishing the report.This study retrieved literature collection from Web of Science. Web of Science (WoS) is one of the world’s most trusted publisher-independent global citation databases, and it allows users to explore the literature of various scientific fields. The literature retrieval details in this study are as follows:Data Source: Web of Science.Database: Web of Science Core Collection.Edition: Science Citation Index Expanded (SCIE).Search Option: Advanced Search.Query: TI = (HFpEF Or heart failure with preserved ejection fraction) and PY = (2009-2020) and DT = (Article Or Review).Record Content: full record and cited references.Data Format: Plaintext.Query Data: July 7, 2021.In the query, TI, PY, and DT stand for title, year published, and document type respectively. In order to improve the accuracy of literature retrieval, this study used search terms “HFpEF” or “heart failure with preserved ejection fraction” in the title to retrieve articles or reviews between 2009 and 2020.-35 These bibliometrics tools can process the HFpEF literature collection, carry out various quantitative analyses, and build matrices for author collaboration, bibliographic coupling, references co-citation, and keyword co-occurrence networks.Most of data analyses in this study were carried out with bibliometrix R-package (version 3.1), VOSviewer (version 1.6.17), and CiteSpace (version 5.8.R1).This study used WoS Results Analysis Tool and bibliometrix R-package to perform a descriptive analysis of the local HFpEF literature collection. In Table The local HFpEF literature collection contained 1791 documents from 326 sources, including 1508 articles and 283 reviews. In these documents, a total of 7712 authors appeared 15,569 times and a total of 30,544 references were cited. WoS employs 2 types of keywords.Author Keywords (DE), listed by the original authors, and Keywords Plus (ID), annotated by an automatic computer algorithm. The number of all keywords including Author Keywords and Keywords Plus was 4127. Author Keywords and Keyword Plus had 1998 terms and 2565 terms respectively, and there were duplicates between them.Figure Figure Figure HFpEF documents in the local HFpEF literature collection covered 43 research areas. Figure A total of 79 countries/regions contributed to the global HFpEF document output. Figure The 1791 documents were published by 1983 research affiliations. Figure Authors and sources are important research constituents in bibliometrics. Figure The top-10 authors in terms of the total numbers of documents are listed in Fig. The top-10 most productive sources are presented in Fig. This paper introduced two concepts: global citation and local citation. Global citations means the citations that a local document has received from other documents indexed on WoS, while local citations means the citations that a reference, included in the bibliographies of the local documents, has received from the local documents. The diagram of global citations and local citations is shown in Fig. This paper lists the top-10 authors according to their local citations in Fig. Figure  This study adopted G-index to measure the local impact of authors and sources in the collection. The author local impact and source local impact by G-index are shown in Fig. Author impact metrics can be used to evaluate the impact of the academic documents of an author or a source, and they are usually based on the number of citations and the number of documents. The commonly used author impact metrics include H-index, G-index, and M-index. H-index is the most used author impact metric, while G-index that gives more weight to highlycited document is an alternative to H-index.As shown in Fig. The top-10 authors with most local impact were identified by G-index. Figure As listed in Table A total of 30,544 references were cited by the local documents. Top-20 most local cited references are listed in Table Keywords are terms that reflect the concept of a document topic and can provide a reasonable description of the research hotspot. This study integrated Author Keywords and Keywords Plus for overall keyword analysis. The local HFpEF literature collection contained 4127 keywords (including Author’s Keywords and Keywords Plus), and 3677 were left after manual processing of duplicate removal. The occurrences of 175 keywords reached or exceeded 20. After removing 6 keywords related to the search terms such as “heart failure,” “heart failure with preserved ejection fraction,” “preserved ejection fraction,” “HFpEF,” “left ventricular ejection fraction,” and “ejection fraction,” 169 keywords remained.As shown in Fig.  In this study, CiteSpace was used for burst keyword detection. A total of 54 burst keywords were found, and 20 meaningful keywords were selected and listed in Table Burst keywords are regarded as indicators of research frontiers or emerging trends over time.Bibliographic networks that include author collaboration network, bibliographic coupling network, references co-citation network, keyword co-occurrence network, and so on, can reveal the relationships between research constituents. This study used VOSviewer to perform bibliometric analysis and build networks. Contributions from a variety of authors can provide deeper insights, and their collaboration can raise the study level. Author cooperation networks can disclose regular study groups, hidden academic teams, and core authors by displaying interactions among authors in a research field. In this study, 100 authors with the most documents were chosen from a total of 7712 authors for author collaboration analysis. Figure Collaborations among authors have become more widespread as research methods and theories have become more complicated. Based on shared references, the analysis builds a similarity link between documents and classifies them into clusters. The clusters are constructed based on the citing documents, which is worth highlighting. In this analysis, 100 documents from the local HFpEF literature collection with the greatest global citations were chosen for bibliographic coupling analysis. Figure Bibliographic coupling posits that 2 documents with public references have content that is similar. When 2 references appear in a document’s reference list at the same time, they are connected in a co-citation network. The most influential references and clusters can be discovered via co-citation analysis. It is worth noting that the clusters are derived based on the cited references. For reference co-citation analysis, 100 references most cited by the local documents were selected. Figure Another well-known bibliometric technique is co-citation analysis. This analysis assumes references that are cited together frequently are similar thematically. Keywords that commonly appear together are assumed to have a topic relationship in this analysis. Keyword co-occurrence analysis can reveal the study field’s development trends and hotspots. From the 169 terms listed above, 100 keywords with the most occurrences were chosen for co-occurrence analysis. As shown in Fig. Keyword co-occurrence analysis is an approach that looks at the document’s real content. Because of the lack of a complete understanding of pathophysiology of HFpEF, modern heart failure medication has not improved the prognosis of HFpEF patients. The treatment of HFpEF patients is still a challenge for clinicians, and further research is urgently needed to evaluate new therapies to improve the treatment effect and longterm prognosis of HFpEF patients.The pathogenesis of HFpEF is multifactorial.Based on the literature of HFpEF research from 2009 to 2020, this paper made a bibliometric analysis to fully understand the research trend of HFpEF in the past 12 years. Annual scientific production can reflect the development trend of specific research fields. HFpEF research had been developing steadily during the period, which indicated that HFpEF research attracted more and more attention and was in the growth stage.Nine of the top-10 countries/regions with the highest productivity are developed countries/regions, including 2 in North America, 6 in Europe, and 1 in Asia. Seven of the top-10 affiliations of global HFpEF document output are in USA, 2 in Europe, and 1 in Asia. In addition, most of top-authors worked in USA and Europe. Developed countries/regions, especially USA, were particularly influential in the field of HFpEF research, while the majority of Asian, African, and Latin American countries/regions have relatively weak research capacity. There was an imbalance between countries/regions, and some research groups also lacked cooperation with the outside world. International cooperation that can pool the experience and wisdom of various countries/regions is an important way to accelerate scientific research progress and improve scientific research level. HFpEF research needs wider international cooperation.All sources involved in Fig.  this work reveals new research hotspots in the field of HFpEF in recent years through keyword analysis, one of which is phenotype. Phenotypes refer to identifiable patient groups, which are distinguished by both the presence of predominant presenting symptoms and/or predominant comorbidity profiles. The phenotypic heterogeneity of HFpEF is the main obstacle to HFpEF treatment. Phenotypic classification of HFpEF patients based on comorbidities and treatable etiologies can help determine the optimal management strategy for each individual patient. Therapeutics may need to shift from “one-size-fits-all” strategy to personalized approach based on phenotype characteristics.,22,38,39 After diagnosing HFpEF, a potential approach is to use biomarkers to identify HFpEF phenotypes, guiding towards more appropriate therapeutic strategies. In addition, echocardiography can provide valuable information for further understanding of pathophysiology and potential phenotype of HFpEF. Machine learning have become important tool for biomedical knowledge discovery.-43 Using machine learning to classify phenotypes of HFpEF patients without bias, high-quality evidence-based medical proofs may be produced, which can provide references for clinical decision-making. Oskouie et al has developed a method of machine learning to analyze phenotypes, which divides HFpEF patients into 3 phenotype groups with different clinical characteristics and results. Segar et al also used unsupervised clustering analysis method to classify HFpEF patients in high-dimensional mixed data queue. The results showed that cluster analysis based on machine learning can identify phenotype groups of HFpEF patients with different clinical characteristics. Using biomarkers from HFpEF patients for unsupervised cluster analysis, Woolley et al identified 4 mutually exclusive patient subgroups according to the characteristics of biomarkers, which suggested different underlying pathophysiological pathways. In view of the phenotypic heterogeneity of HFpEF, treatment and clinical research need to be individualized and targeted. Researchers should abandon the mindset of “a pair of shoes for all feet,” and use machine learning algorithm to divide HFpEF patients into different phenotype groups, which can make the patients better match the appropriate treatment and improve the prognosis. Using machine learning to classify the phenotypes of HFpEF patients is a very noteworthy research hotspot.Compared to the reference Edlinger et al,,47 This is another research hotspot worthy of attention. Furthermore, this study only processed the bibliographic database files from WoS, and did not consider other bibliographic databases, such as PubMed, Scopus, etc. These above deficiencies did not undermine the significance of this study.Despite an exhaustive bibliometric analysis of HFpEF study, deficiencies remain. Due to the time limit of WoS subscribed by our institution, this study could only query the literature after 2009, which might lead to the incompleteness of the local HFpEF literature collection. In addition, this study took title as the query item to search HFpEF literature, which improved the precision, but might reduce the recall. We have tried to search for HFpEF-related papers using keywords, but the search results are not satisfactory. Many of the documents are not very relevant to HFpEF research and may only cover a small part of the content. We believe that HFpEF-related document retrieval by title will maximize the inclusion of the most important documents. For the annual analysis of HFpEF literature, the local HFpEF literature collection did not contain the latest HFpEF documents since 2021. In August 2021, however, an important breakthrough was reported. The sodium-glucose cotransporter 2 inhibitors were shown to be effective in the treatment of HFpEF.With the sharp increase in the number of HFpEF patients, HFpEF is recognized as a major public health problem worldwide. Through bibliometric analysis of HFpEF literature from 2009 to 2020, this study provided a comprehensive reference and a summarized macroscopic overview of the research progress and performance related to HFpEF.The bibliometric analytic tools employed in this study gleaned relevant information from published documents, supplemented standard review and survey articles, and allowed researchers to gain useful information. Over time, there has been an increase in the amount of HFpEF documents, however HFpEF research has been relatively imbalanced amongst countries/regions. It is necessary to conduct more cooperative and collective global HFpEF research in order to conduct HFpEF research in a balanced manner around the world. This study aids HFpEF researchers in locating possible collaborators and identifying research trends and hotspots, all of which will assist improve the treatment and prognosis of HFpEF patients around the world.The authors are particularly grateful to Zhenyu Feng, Qinglian Hao, and Tao Lin.Conceptualization: Qiuju Dong, Junwei Zhang.Data curation: Qiuju Dong, Junwei Zhang.Funding acquisition: Qiuju Dong, Jianping Zhao.Investigation: Hongzhen Zhang, Meiling Wang.Methodology: Qiuju Dong, Junwei Zhang.Project administration: Jianping Zhao.Supervision: Qinghua Han.Visualization: Junwei Zhang.Writing - original draft: Qiuju Dong, Junwei Zhang, Qi Huang.


TNFR2 and Fn14 efficiently recruit TRAF2 along with the TRAF2 binding partners cIAP1 and cIAP2 and can thereby limit the availability of these molecules for other TRAF2/cIAP1/2-utilizing proteins including TNFR1. Accordingly, at the cellular level engagement of TNFR2 or Fn14 inhibits TNFR1-induced RIPK1-mediated effects reaching from activation of the classical NFκB pathway to induction of apoptosis and necroptosis. In this review, we summarize the effects of TNFR2- and Fn14-mediated depletion of TRAF2 and the cIAP1/2 on TNFR1 signaling at the molecular level and discuss the consequences this has in vivo.Tumor necrosis factor (TNF) receptor 1 (TNFR1), TNFR2 and fibroblast growth factor-inducible 14 (Fn14) belong to the TNF receptor superfamily (TNFRSF). From a structural point of view, TNFR1 is a prototypic death domain (DD)-containing receptor. In contrast to other prominent death receptors, such as CD95/Fas and the two TRAIL death receptors DR4 and DR5, however, liganded TNFR1 does not instruct the formation of a plasma membrane-associated death inducing signaling complex converting procaspase-8 into highly active mature heterotetrameric caspase-8 molecules. Instead, liganded TNFR1 recruits the DD-containing cytoplasmic signaling proteins TRADD and RIPK1 and empowers these proteins to trigger cell death signaling by cytosolic complexes after their release from the TNFR1 signaling complex. The activity and quality (apoptosis  The recne cells . Thus, dne cells . The recne cells .+ T cells and B cells but is also expressed by resting T cells, type 2 innate lymphoid cells (ILC2), mesenchymal stem cells and endothelial and epithelial cell types , activated CD8ll types . Proinflll types . During ll types . Worth mll types . Accordill types . Since tll types .2β heterotrimers (2β and LTαβ2 heterotrimers (2β) despite also binding the soluble ligand molecules  with high affinity , again a typical ligand of the TNFSF, and soluble TWEAK (sTWEAK), which originates by intracellular furin protease-mediated proteolytic processing of memTWEAK  . Ligandsotrimers . The solotrimers . Importaaffinity . Since smemTWEAK . SimilarmemTWEAK .TNF is expressed by a variety of cell types in response to a broad range of PAMPs and inflammatory cytokines, particularly in myeloid cells, T- and B cells and fibroblasts . SimilarThe death receptor subgroup of the TNFRSF can further be subdivided into three categories depending on whether and how these receptors use the DD-containing adapter protein FADD and the FADD-interacting caspase-8 molecule to induce apoptosis . CD95 F.versus RIPK1, FADD, caspase-8), regulation by linear ubiquitination and relevance of RIPK1’s kinase activity  pseudokinase triggering conformational changes in the latter resulting in translocation to the plasmamembrane, pore formation and cell lysis . Worth mAs mentioned above, in response to ligand-binding, TNFR1 recruits TRADD and RIPK1 by homotypic interactions of the DDs contained in these molecules. There is evidence that TRADD and RIPK1 compete for TNFR1 binding and that each of the two cytosolic DD-containing proteins is independently able to mediate TNFR1-induced apoptosis . AlthougSimilar to TNFR1, the CD95-type DRs also stimulate the classical NFκB pathway and various MAPK cascades  under crInduction of apoptosis by TNFR1 and other death receptors can also occur by indirect activation of effector caspases via the generation of reactive oxygen species (ROS) and triggering of prolonged JNK activation under crucial involvement of the MAP3K apoptosis signal-regulating kinase 1 (ASK1) and/or mammalian Ste20-like kinase 1 (MST1) . A majorDespite the ubiquitous expression of TNFR1, TNF fails to induce a robust cell death response in the huge majority of cell lines and primary cells and instead triggers a wide variety of cell death-independent processes reaching from induction of gene synthesis of hundred of proteins over cell migration to proliferation and cellular differentiation. Thus, there have to exist mechanisms that hold in check the cytotoxic branch(es) of TNFR1 signaling.The first mechanism that has been identified in this respect is TNFR1-induced activation of the classical NFκB pathway which results in the production of several proteins that interfere with death receptor-induced cell death signaling or protect from cell death processes more general at the effector level .The relevance of NFκB activation for the inhibition of cytotoxic signaling of TNFR1 is highlighted by the fact that deficiency in the transcription factor subunit RelA results in embryonal lethality which can be rescued by knockout of the TNF or TNFR1 gene . An impoThe most powerful and complex regulators of TNFR1- and CD95 type-induced cell killing seem to be caspase-8 and the protein isoforms of the cellular FLICE-like inhibitory protein (cFLIP) gene. There are three protein isoforms of FLIP: FLIP-L, FLIP-S and FLIP-R, which all interact with FADD and which all form heterodimers with procaspase-8 . The men+CD8+ double-positive thymocytes of TRAF2-deficient mice, TNF- but not anti-CD95 antibody-induced cell death was found to be enhanced and embryonal fibroblasts derived of TRAF2-defcient mice were also sensitized for TNF in the presence of cycloheximide . TNF-induced TNFR1-dependent cell death of IECs is well established and has been early on demonstrated nant TNF . More imnant TNF , infectinant TNF  and varinant TNF  and has nant TNF . Intrigunant TNF . TWEAK-dnant TNF . Intrigunant TNF . Evidencnant TNF . In thisnant TNF . Notewornant TNF . In linenant TNF .Colitis is associated with an increased risk to develop colon cancer. Interestingly, in the AOM-DSS- and the DSS-induced colitis models, the rate of tumor development after recovery from colitis is increased in Fn14-deficient mice but also in TNFR1-deficient mice possibly reflecting insufficient TNFR1/Fn14-mediated IEC apoptosis leading to uncontrolled compensatory proliferation and/or outgrowth of yet less apoptosis-sensitive precancerous cells eventually resulting in cancer development .The relevance of keeping in check the cytotoxic Fn14-TNFR1-crosstalk is also in accordance with observations derived of genetically engineered mice. RIPK1 deletion in the intestinal epithelium is associated with apoptosis of IECs but can be largely rescued by crossing with TNFR1-deficient mice . FurtherSequestration of TRAF2 and the cIAPs by Fn14 or TNFR2 could also be of relevance in cell death occurring during acute kidney injury or in pathogen-induced hyperinflammation in patients with X-linked inhibitor of apoptosis (XIAP)-deficiency triggered by TLR- and TNF- and TNFR2-mediated myeloid cell death .i) TNF-induced upregulation of PD-L1 on tumor infiltrating lymphocytes (TILs) and monocytes and macrophages ,+ TILs. Indeed, there is solid evidence from studies with the TNF-inhibitor Enbrel (=TNFR2-Fc) and studies using TNF- and TNFR1-deficient mice that TNF-dependent AICD limits the efficacy of anti-PD1 and anti CTLA-4 ICB (ii) induction of activation induced cell death in CD8LA-4 ICB . There iLA-4 ICB ,iii) therapy limiting immune-related adverse events including the induction of colitis  and+ T cell and/or NK cell derived TNF.iv) killing of tumor cells by CD8To evade the immune system, tumors, among other things, hijack proteins, such as PD-L1 and CTLA-4, which are otherwise used by the body to restrict immune responses. Indeed, the introduction of biologics blocking the activity of such immune checkpoints has profoundly improved cancer therapy. Perhaps not unexpected in view of the central role of TNF in immune regulation, there is growing evidence that immune checkpoint blockade (ICB) comes along with increased TNF production . Indeed,+ T cells and NK cells. While TNFR1, FADD and caspase-8 have been crucially implicated in the killing of tumor cells by CD8+ T cells and NK cells, the LUBAC components were found to antagonize the latter   . A cruci peptide . Reduced colitis . An invorgo AICD . First sckground . In lineced AICD .+ T cells has been mainly investigated in murine models but studies with TNF blockers and primary T cells also argue for a role of TNF in the AICD of human CD8+ T cells (+ T cells derived of patients that severely suffered from COVID-19 showed strong AICD in response to treatment with spike 1-derived peptides which could be rescued by treatment with an anti-TNF antibody (Infliximab) or an anti-TNFR1antibody  and memTNF (engages both TNFR1 and TNFR2) along with the fact that T cells can produce TNF in an autocrine fashion could sculpt the net effect of TNF on T cells in a complex fashion. Last but not least, AICD of T cells does not only involve the TNF-TNFR system but is redundantly mediated by other DRs, especially CD95 but possibly also TRAIL . Therefoted mice , openingIn view of the fact that cytotoxic TNFR1 signaling is more redundantly controlled than death signaling by the other DRs (see above), it is tempting to speculate that the cytotoxic TNFR1-TNFR2 crosstalk becomes particular relevant in immune cells under pathophysiologic conditions when one or more of the inhibitory checkpoints of cytotoxic TNFR1 signaling are defective, e.g., due to mutations, or inhibition by virus- or pathogen-encoded factors inhibiting NFκB signaling or other cell death checkpoints with particular relevance for TNFR1. Indeed, in the Do-11.10 T cell hybridoma model of anti-CD3 antibody-induced AICD, inhibition of classical NFκB signaling resulted in a switch from CD95-dependent cell death to TNF-dependent cell death which could be rescued by ectopic A20 expression . Worth min vivo. The exploding recognition of the broad relevance of TNFR1-induced cell death processes in infections and cancer development might now revitalize the interest in these in principle since over 25 years known crosstalk mechanism(s). Indeed, the expression patterns of TNFR1 (ubiquitous), TNFR2 (immune cells) and Fn14 (non-immune cells in injured tissue) and their ligands TNF and TWEAK, both expressed by activated myeloid cells, suggest that costimulation of TNFR1 and TNFR2 in immune cells and TNFR1 and Fn14 in non-immune cells are rather the rule then the exception when tissue homeostasis is disturbed. Future studies should now show to which extent TNFR2- and Fn14-mediated enhancement of TNFR1-induced cell contribute to pathophysiological scenarios in which TNFR1-induced cell death plays a crucial role. Since biologicals inhibiting or stimulating TNFR2 and Fn14 are already under preclinical investigation, it is tempting to speculate that new in vivo knowledge about the cytotoxic TNFR2/Fn14-TNFR1 crosstalk can straightforwardly foster new therapeutic strategies in the treatment of cancer and infections.Both TNFR2 and Fn14 recruit TRAF2 along with the TRAF2-interacting E3 ligases cIAP1 and cIAP2 and use these molecules for the stimulation of proinflammatory signaling pathways, e.g., the classical NFκB pathway. TNFR2-and Fn14-mediated recruitment of TRAF2 and the cIAPs is intimately linked to an impoverishment of the cytosolic pool of these molecules limiting their availability amongst others for TNFR1 signaling and regulated NIK degradation. In line with this, the most striking consequences of cytosolic impoverishment of TRAF2, cIAP1 and cIAP2 by TNFR2 and Fn14 are sensitization for TNFR1-induced cell death processes and activation of the alternative NFκB signaling pathway. While the physiological and pathophysiological relevance of “direct” TNFR2 and Fn14 signaling activities, such as classical and alternative NFκB signaling, have been intensively studied over the last two decades in animal models, the cytotoxic TNFR2-TNFR1 and Fn14-TNFR1 crosstalk have been poorly addressed


Heart failure (HF) with preserved ejection fraction (HFpEF) is a clinical syndrome in which patients have signs and symptoms of HF due to high left ventricular (LV) filling pressure despite normal or near normal LV ejection fraction. It is more common than HF with reduced ejection fraction (HFrEF), and its diagnosis and treatment are more challenging than HFrEF. Although hypertension is the primary risk factor, coronary artery disease and other comorbidities, such as atrial fibrillation (AF), diabetes, chronic kidney disease (CKD), and obesity, also play an essential role in its formation. This review summarizes current knowledge about HFpEF, its pathophysiology, clinical presentation, diagnostic challenges, current treatments, and promising novel treatments. It is essential to continue to be updated on the latest treatments for HFpEF so that patients always receive the most therapeutic treatments. The use of GnRH agonists in the management of HFpEF, infusion of Apo a-I nanoparticle, low-level transcutaneous vagal stimulation (LLTS), and estrogen only in post-menopausal women are promising strategies to prevent diastolic dysfunction and HFpEF; however, there is still no proven curative treatment for HFpEF yet. A significant problem for worldwide public health is heart failure (HF) with preserved ejection fraction (HFpEF) ,2. HFpEFDue to variations in diagnostic criteria and research populations, recent investigations have indicated that the prevalence of HFpEF ranges substantially from 13% to 74% -8. The pIt should be noted that the prevalence of HFpEF in the community rose with age and was greater in women; the reported age- and sex-specific prevalence increased from 0% (men) and 1% (women) in the age group of 25-49 years to around 4-6% in males and 8-10% in women for people 80 years and older .There are a few gaps in our understanding of the epidemiology of HFpEF that should be investigated in the future. Different investigations of HFpEF use different diagnostic cut-points to establish a normal left ventricular ejection fraction (LVEF), with ESC recommendations favoring a 50% threshold . The preOther information gaps concern the prevalence of HFpEF internationally (outside of the United States and Europe) and the variance in the disease burden by ethnicity. Future studies including multi-ethnic samples are required, as recent data suggest that Afro-Caribbeans may be more likely to suffer from diastolic dysfunction .Additional research is required to determine the factors that raise the risk for HFpEF in women because it is generally known that women are more likely to have the condition .This should be further researched because it is unknown whether HFpEF aggregates within families or if parental HFpEF increases the risk of the condition in the offspring . In addiThis review aims to comprehensively present the current understanding and knowledge regarding the pathogenesis, epidemiology, clinical presentation, and management of HFpEF, as well as thoroughly analyze information gaps, controversies, and challenges pertaining to this disease.Pathophysiology of HFpEFDiastolic Dysfunction and Its Role in HFpEFHFpEF is a syndrome with a variety of underlying causes and numerous alterations in physiological functions that add to the complexity of the illness. The left ventricular (LV) diastolic dysfunction plays a fundamental role in this illness ,21. ThisInitial observational studies on HFpEF revealed a common occurrence of concentric hypertrophy of the left ventricle alongside a normal chamber size ,26. HoweMyocardial Fibrosis and Its Impact on Ventricular ComplianceThe concept of diastolic function encompasses both an active pressure decay process (relaxation) occurring in early diastole, linked to myofilament separation and calcium reabsorption, as well as a "passive" stiffness associated with viscoelastic attributes influenced by mechanical shifts ranging from the sarcomere to the extracellular matrix, chamber, and pericardium ,33. HighThese changes result from specific modifications in the transcriptional and post-translational aspects of a significant sarcomeric protein known as titin -39. The Alterations in fibrillar collagen are closely tied to diastolic dysfunction. Conditions such as hypertension and aging, which are associated with diastolic dysfunction, often involve fibrosis . This fiImpaired Endothelial Function and Vascular Contributions to HFpEFApproximately 30% of HFpEF patients exhibit endothelium-dependent coronary microvascular dysfunction, while over 30% display endothelium-independent dysfunction seen as reduced coronary flow reserve . HFpEF pMicrovascular rarefaction, evidenced by diminished myocardial microvascular density, contributes to cardiac perfusion failure in HFpEF, reducing myocardial oxygen delivery ,53. ThisInflammatory Mechanisms and Their Involvement in HFpEFSeveral studies shed light on the cardioprotective impact of NO/sGC/cGMP/PKG signaling . EndotheInflammation significantly influences the development of HFpEF. This has been demonstrated through swine models with comorbidities, namely, arterial hypertension, diabetes, and hypercholesterolemia . DiabeteDiagnostic challengesLimitations of Current Diagnostic Criteria for HFpEFThe diagnostic criteria for HFpEF differ significantly among various society guidelines primarily because there is no consensus on how to define HFpEF. This lack of agreement is attributed to an incomplete understanding of the disease's pathobiology, the diversity in its presentation, and its natural progression over time .However, the majority of the studies have defined HFpEF as the appearance of physical manifestations of HF, an LVEF that is 50 or more, elimination of "HFpEF mimickers," such as infiltrative cardiomyopathies and indications of heightened LV filling pressure or non-invasive markers ) .Hospitalized HFpEF (congestion at rest): The diagnosis of this condition is dependent on the classic signs and symptoms, as well as the use of NPs and imaging techniques such as chest radiography and echocardiography. However, LV hypertrophy may not be present in three out of four individuals -83, and Exercise intolerance HFpEF: Diagnosing this condition is complex when congestion is not present at rest. Physical examination results may or may not be normal in the case of normal LV filling pressures at rest -87. For Multiple randomized controlled trials exploring HFpEF treatments have adopted lower LVEF thresholds (40-45%) to increase the occurrence of events, thereby achieving the necessary statistical strength to prove therapy efficacy. Individuals with HF mid-range ejection fraction (HFmrEF) exhibit comparable underlying mechanisms and responsiveness to treatment as those with HF reduced ejection fraction (HFrEF). Consequently, involving HFmrEF patients in HFpEF trials supports the evaluation of treatments that have proven beneficial in HFrEF cases -90.Two diagnostic approaches for HFpEF, namely the H2FPEF score  and the Role of Advanced Imaging Techniques in HFpEFFunctional imaging techniques, particularly cardiovascular magnetic resonance (CMR), have emerged as important tools for assessing the complex pathophysiology of HFpEF at a more detailed level. Conventional diagnostic methods often fail to capture the subtle changes associated with HFpEF, making functional imaging an essential complement. CMR provides high-resolution imaging, allowing accurate assessment of atrial and ventricular volumes, ejection fraction, and diastolic function. Pathologic changes such as left atrial and LV hypertrophy have been associated with HFpEF. Additionally, CMR can provide insights into myocardial stiffness evidenced by changes in blood flow patterns and myocardial strain -94.One novel CMR technique, known as "4D-flow," enables the quantification of three-dimensional blood flow velocities throughout the cardiac cycle which allows the study of filling dynamics in HFpEF patients, offering a further understanding of the fluid-dynamical alterations in the condition -96. ReceMetabolic imaging methods, such as phosphorus-31 cardiac magnetic resonance spectroscopy, provide valuable such as decreased phosphocreatine/adenosine triphosphate ratios in HFpEF patients, indicating altered myocardial energetics . MoreoveBiomarkers and their potential to aid in early diagnosis of HFpEFNPsLevels of NPs are increased in patients with HFpEF, reflecting the severity of cardiac structural and functional irregularities like LV hypertrophy, fibrosis, and impaired diastolic function -102. TheThe presence of other medical conditions has an impact on NP levels in both HFpEF and HFrEF, a particularly pertinent consideration given the higher prevalence of non-cardiac comorbidities in HFpEF. A number of conditions correlate with elevated NPs, including chronic obstructive pulmonary disease (COPD), AF, kidney disease, and diabetic ketosis, whereas obese patients may exhibit lower NP levels -109. AddTroponinIn individuals with HF, increased troponin levels generally correspond to the severity of HF, particularly in acute situations. However, elevated troponin levels have also been observed in chronic HF, possibly due to factors like inflammation, neurohormonal activation, myocardial strain, hypoxia, and cytotoxicity .Numerous studies have examined the predictive significance of troponin testing in patients admitted for HFpEF. In a group of 500 patients with an ejection fraction of 40% or more, troponin T (TnT) levels were directly linked to serum creatinine and the severity of symptoms. Furthermore, they independently predicted both all-cause mortality and the need for rehospitalization due to HF .Other BiomarkersHFpEF patients exhibit higher levels of certain biomolecules such as soluble suppression of tumorigenesis 2 (sST2), hs-CRP, and cystatin-C, TIMPs, N-terminal propeptide of type III procollagen (PIIINP), homocysteine, and resistin. The most extensively studied biomarkers in HFpEF include sST2, galectin-3 , and growth differentiation factor 15 (GDF-15). Whereas, in HFrEF, increased levels of NT-proBNP, hs-TnT, inflammatory biomarkers like pentraxin-3, tumor necrosis factor-alpha (TNF-a), IL-6, and IL-10 are more prominent ,114.Clinical presentation and comorbiditiesRisk Factors and Comorbidities in HFpEFCardiovascular risk factors play a significant role in HFpEF development and progression. Hypertension is a major risk factor, with a prevalence ranging from 55% to 90% among HFpEF patients. Proper blood pressure control is essential in managing hypertensive patients with HFpEF as it affects LV hypertrophy, fibrosis, and diastolic dysfunction -117.AF is another well-known risk factor and prognostic indicator in HFpEF. AF and HFpEF exhibit mutual causation; AF can lead to HFpEF and vice versa. AF complicates HFpEF diagnosis due to shared clinical manifestations, and it is an independent prognostic factor for mortality and HF hospitalization -120.Diabetes is prevalent in approximately one-third of HFpEF patients and contributes to oxidative stress and endothelial dysfunction. Proper management of diabetes is crucial in HFpEF patients to address its impact on pathophysiology -122.Obesity is a major risk factor for incident HFpEF, with nearly 80% of HFpEF patients being overweight or obese. Obesity leads to inflammation and altered cardiac hemodynamics, which require further investigation .Chronic kidney disease (CKD) is another significant risk factor for HFpEF, affecting around one-third of HFpEF patients. CKD worsens HFpEF outcomes, and its coexistence with HFpEF, known as cardiorenal syndrome, requires careful management -125.Other comorbidities impacting HFpEF outcomes include COPD, iron deficiency, and anemia ,126-128.Detecting specific secondary causes of HFpEF, such as infiltrative restrictive cardiomyopathy and restrictive cardiomyopathy due to various conditions, is crucial for effective treatment -130.HFpEF by AgeTraditionally, HFpEF has been associated with aging, and studies demonstrate an age-dependent increase in its prevalence. However, recent research indicates that younger individuals, particularly in Asia, are also affected, with up to 15% of HFpEF patients being young (<55 years). Younger HFpEF patients may have different risk factors and outcomes compared to older patients. Despite having fewer comorbidities, younger HFpEF patients have a higher risk of cardiovascular death, particularly sudden death. Preventative measures early in life in high-risk individuals may reduce the overall burden of HFpEF -132.Sex Differences in HFpEFHFpEF exhibits sex differences in prevalence, risk factors, pathophysiology, and outcomes. Women predominate in HFpEF cases, outnumbering men by 2:1 . While bTreatment strategiesOverview of Current HFpEF Management GuidelinesBased on the guidelines recommended by the American Heart Association (AHA), the American College of Cardiology (ACC), and the ESC, the management of HFpEF typically includes complex and individual approaches -143. AllPharmacological Interventions and Their LimitationsThere is no specific therapy proven to dramatically improve outcomes in HFpEF compared to HFrEF . ManagemDiuretics may help reduce fluid retention and congestion, which alleviates symptoms like shortness of breath and edema -150. BotRole of Lifestyle Modifications in HFpEF ManagementLifestyle modifications play a crucial role in HFpEF management. Such a change improves symptoms, enhances quality of life, reduces hospitalizations, and slows the progression of the condition . HFpEF pRegular physical activity is also essential. Patients should engage in aerobic exercises, such as walking, swimming, or cycling. Exercise regimens should be tailored to individual capabilities and monitored by a healthcare professional . Both diSmoking cessation is vital for overall cardiovascular health and is highly recommended for HFpEF patients -158. TheEmerging therapies and their potential for HFpEF treatmentSeveral novel treatment strategies for HFpEF are being studied. SGLT2 inhibitors are widely used to treat type 2 diabetes and HFrEF, as they block transporters responsible for the reabsorption of glucose with Na+ from the proximal tubules -161. BotSildenafil, a PDE-5 inhibitor, used commonly in the treatment of erectile dysfunction and pulmonary hypertension has been found to improve exercise capacity and quality of life in some HFpEF patients, but needs further research . Drugs lPersonalized Medicine Approaches Based on Patient PhenotypesPersonalized medicine approaches based on patient phenotypes in HFpEF aim to tailor treatment strategies to the specific needs of patients to improve outcomes and optimize care. Phenotyping and risk stratification are focused on involving the clinical, biochemical, and imaging parameters that categorize patients into subgroups with different pathophysiology of HF, comorbidity, and disease severity . Risk stBiomarker-guided therapies, such as BNP and NT-proBNP, are specific molecules found in the blood that provide valuable information about a patient’s health condition ,173. TheNovel insights and advancementsTargeting Inflammation and Fibrosis Pathways As Potential Therapeutic AvenuesChronic pro-inflammatory conditions can precipitate HFpEF . InflammAn additional approach is enhancing the endothelial function in patients with HF which involves focusing on the generation of NO. ACE inhibitors, like quinaprilat, improve endothelial function in patients with HF by reducing the breakdown of bradykinin -178. ThiNew Perspectives on Endothelial Function and Its Role in HFpEFRecently, a new idea has emerged to address endothelial dysfunction, and this idea focuses on discovering eNOS enhancers . The latThe endothelium has many roles in regulating vascular tension by producing different substances that induce relaxation. These are vasodilator prostaglandins, NO, and endothelium-dependent hyperpolarization factors. In addition, the endothelium produces substances that contribute to vasoconstriction. This redundant mechanism mediated proper vascular tension -187. In The role of precision medicineImportance of Identifying Distinct HFpEF SubtypesAt present, there are four potential classification frameworks for HFpEF, which we will detail. The first classification is based on pathophysiology. The second is a clinical/etiologic classification. The third classification is according to the type of clinical presentation. The fourth one is the phenomics (or "phenomapping") of HFpEF . It is iThe heterogeneity of HFpEF has been identified as a prime reason why clinical trials have not yielded effective results in HFpEF patients, therefore, suggesting that a "one-size-fits-all" approach does not work in HFpEF . A desirTailoring Treatment and Challenges Along With Opportunities in Implementing Precision Medicine in HFpEFOptimal treatment outcomes can be achieved by customizing interventions to individual patients who actively participate in their care and possess the skills to adhere to treatment plans. These patients experience improved survival rates and reduced hospital readmissions -198. In The presence of coexisting conditions significantly influences the outcomes of HFpEF. Managing conditions like hypertension, diabetes, and CKD requires customized interventions to mitigate their contributions to HFpEF development. For instance, optimizing blood pressure control has a favorable impact on cardiovascular health in HFpEF patients . TherefoChallenges in implementing precision medicine in HFpEF are multifaceted. A significant hurdle is the heterogeneity of HFpEF patients. Thus, it is important to emphasize the need to define subgroups within HFpEF based on distinct phenotypic and molecular profiles to guide targeted interventions . AnotherTechnological advancements, exemplified by high-throughput omics profiling, provide extensive insights into the molecular profiles of patients. Ongoing research is investigating the potential of transcriptomic and proteomic analyses in identifying unique pathways and potential therapeutic targets within specific HFpEF subgroups . The benFuture directionsPromising Areas for HFpEF Research and InvestigationSome studies have shown the GHRH receptor signaling pathway as a new molecular target against dysfunctional cardiac myocytes due to its effect on cardiomyocyte relaxation by phosphorylation and fibrosis. This opens the possibility of the use of GHRH agonists for the management of myocardial changes associated with HFpEF .A study model done on a group of mice with hypertension-induced HFpEF showed that infusion of Apo a-I nanoparticles caused a significant reduction in cardiomyocyte and perivascular fibrosis and improved myocardial capillary density. This study looks very promising as it shows that MDCO-216 completely reverses cardiac dysfunction and proves to be an effective therapy in this model .Another promising study done on a rat model with HFpEF showed improved cardiac function with the use of neuromodulation by the use of low-level transcutaneous vagal stimulation (LLTS). It has been shown that LLTS can improve diastolic dysfunction by decreasing LV inflammatory infiltration and fibrosis through pharmacological blockade of the α7nAchR. These results look quite promising and support the basis for the use of neuromodulation to treat selected patients with HFpEF for which further Randomized trials must be done .Integrating New Findings Into Clinical PracticeUsing investigations like speckle tracking echocardiography has proven useful in patients with HFpEF as an objective and quantitative measure by providing data about the myocardial mechanics, deformation, and strain parameters. It can be a tool for early indication and progression of HF. It can assess the impact of treatments in patients with HFpEF .Physicians can incorporate the use of models by advanced machine learning techniques to better estimate the prognosis of patients with HFpEF. These models also consider the quality of life and health status data, which may not usually be there in a clinical encounter .Potential Impact of Novel Therapeutic Interventions on HFpEF OutcomesThe role of estrogen and its mechanisms to prevent diastolic dysfunction of the heart looks promising for tackling HFpEF in post-menopausal women. Most of the proposed mechanisms involve a single E2 receptor in pathophysiology; therefore, it is plausible to develop therapy targeted toward this single receptor in order to avoid the non-cardiac effects of E2 therapy. This can have a huge impact on reducing the burden of HFpEF among post-menopausal women .HFpEF is a significant health problem with high mortality and morbidity. Its pathophysiology is known, yet, its clinical presentation is not specific, and its diagnosis is challenging. Diagnosis relies on the understanding of clinical symptoms, advanced imaging techniques such as CMR, semi-automatic cardiac image analysis, and segmentation software, frequently incorporating "AI" algorithms, metabolic imaging methods (phosphorus-31 cardiac magnetic resonance spectroscopy), and 11C-acetate PET, which provides valuable information about HFpEF. There has been a lot of focus on advancing the methods by which HFpEF is diagnosed, while treatment options remain the same. It's pertinent that future research establishes the efficacy of current therapy and explores novel treatment options. Further research is needed in the area of prevention of cardiomyocyte changes. The use of GnRH agonists in the management of HFpEF, infusion of Apo a-I nanoparticles, LLTS, and estrogen only in post-menopausal women are promising strategies to prevent diastolic dysfunction and HFpEF.