Heart failure is the leading cardiovascular comorbidity in chronic kidney disease (CKD) patients. Among the types of heart failure according to ejection fraction, heart failure with preserved ejection fraction (HFpEF) is the most common type of heart failure in CKD patients. However, the specific animal model of HFpEF afer CKD is currently missing. In this study, we determined the heart failure characteristics and dynamic progression in CKD mice. Based on these features, we established the practical HFpEF after CKD mouse model using 5/6 subtotal nephrectomy and retinol administration. Active apoptosis, impaired calcium handling, an imbalance between eNOS and oxidative stress and engaged endoplasmic reticulum stress were observed in our model. RNSseq revealed distinct gene expression patterns between HFpEF after CKD and metabolic induced-HFpEF. Furthermore, we revealed the potential mechanism of the pro-HFpEF effect of retinol. Serum accumulation of retinol in CKD prompts myocardial hypertrophy and fibrosis by activating JAK2 and phosphorylating STAT5. Finally, using small molecule inhibitor AC-4-130, we found STAT5 phosphorylation inhibitor may be a potential intervention target for HFpEF after CKD. In conclusion, we provide a novel animal model and a potential drug target for HFpEF intervention in CKD. As a clinical common disease affecting multiple organs throughout the body, chronic kidney disease (CKD) impacts 9.1% global population causing severe burden and various complications from cognitive impairment to peripheral arterial stiffness Considering the different factors driving HFpEF, the practicable animal models of HFpEF can also be classified into 3 subtypes according to the accompanying complications, such as metabolic stress induced db/db mouse model and 2-hit mouse model, hypertension induced AIU mouse model and aortic coarctation-induced AC feline model In this study, we established the practical HFpEF after CKD mouse model by using subtotal nephrectomy and retinol administration. We also determined the optimum observation and operation window for HFpEF after CKD in our mouse model. Cardiomyocyte hypertrophy, interstitial fibrosis, apoptosis, impaired calcium handling, endoplasmic reticulum stress and macrophage infiltration were observed in HFpEF after CKD mouse model. The differences of gene expression patterns between HFpEF after CKD and metabolic stress-induced HFpEF were revealed. And we demonstrated retinol may prompt HFpEF progression in CKD through Stra6-JAK2-STAT5 signals and restraining phosphorylation of STAT5 may attenuated HFpEF development in CKD by using STAT5 phosphorylation inhibitor AC-4-130.db/db mice (db/db mice) were purchased from Gem Pharma Tech LLC  and raised for 20 weeks to develop HFpEF. All experimental procedures were conducted in accordance with the Guide for the Care and Use of Laboratory Animals published by the US National Institutes of Health , the Guide for the Care and Use of Laboratory Animals  and the Chinese Regulations for the Administration of Affairs Concerning Experimental Animals. The animal experiments were approved by the Animal Ethics Committee at Zhongshan Hospital, Fudan University . All the animal procedures were performed in the Department of Experimental Animal Research Centre, Zhongshan Hospital, Fudan University .Male C57BL/6J mice aged 5 weeks (weight 16-21g) were purchased from Gem Pharma Tech LLC . All mice were fed in a 12/12-h light/dark cycle room at 24 ± 1 °C and 60% ± 10% humidity. Animals are free to access water and normal diet containing 4000 IU of vitamin A/kg or a vitamin A-free AIN-93G diet . Before surgery, mice were synchronized to new environment for 2 weeks. At the age of 7 weeks, CKD mice were subjected to two step 5/6 nephrectomy(5/6Nx). First, two-third of the left kidney were removed by cutting upper and lower poles and gelatin sponge hemostasis. After seven days recovery, the right kidney was ligated and removed entirely. After the operation, mice housed and given 0.5ml 300mg/kg vitamin A water solution  every day for 6 weeks to establish CKD-HFpEF. Sham mice were subjected to laparotomy on the same days as the 5/6Nx surgeries. To establish the suitable mouse model of HFpEF after CKD, typical HFpEF inducing methods such as 1% NaCl administration referring to AIU HFpEF mouse model, L- NG- nitro arginine methyl ester (L-NAME) or high-fat diet from 2-hit HFpEF mouse model were administrated in 5/6 nephrectomy mice. To downregulate Stra6, anti-Stra6 siRNA or control siRNA were injected into mice  encapsulated in HVJ-E (Cosmo Bio) through tail vein every week for 6 weeks during vitamin A administration. The siRNA oligonucleotide sequences were as follows: anti-Stra6 siRNA sense 5′-GCUGCUGUCUUUGUGGUCCUCUUCA-3′ and antisense 5′-UGAAGAGGACCACAAAGACAGCAGC-3′; control siRNA sense, 5′-GCUGUCUUUGUGUUGCCCUUCGUCA-3′ and antisense 5′-UGACGAAGGGCAACACAAAGACAGC-3′. Mice were also injected with either STAT5 SH2 domain small molecule inhibitor AC-4-130 (25mg/kg) or vehicle . AC-4-130 administration via intraperitoneal injection was well tolerated with no toxicity. To evaluate the effect of AC-4-130 in CKD, mice were injected with either AC-4-130 (25mg/kg) or vehicle intraperitoneally in 8 weeks after first stage surgery of CKD for two weeks. We collected the blood and kidney tissues after 4 weeks of CKD surgery completion when mice were 13 weeks. Lepr2 and a urinary albumin-to-creatinine ratio (UACR) between 200 and 500 mg/g. The estimated glomerular filtration rate (eGFR) was calculated by the Modification of Diet in Renal Disease formula The CKD patients (n=12) and HFpEF after CKD (CKD-HFpEF) patients (n=12) were enrolled in Zhongshan Hospital, Fudan University from April 2019 to December 2022. The inclusion criteria for CKD-HFpEF patients were as follows: (1) provision of a signed informed consent form, (2) age of ≥ 18, (3) diagnosed HFpEF based on current guideline definitions of HFpEF Hearts, livers and skins were immersed in 4% paraformaldehyde in phosphate-buffered saline (PBS) for 12 h after removal. The processed tissues were stained with Hematoxylin Eosin (HE) and Masson's staining, respectively. For HE staining, tissues were soaked in 10% neutral buffered formalin (NBF) for 24 hours and embedded in paraffin, and cut into 4mm -thick slices for microscope observation. As for Masson staining, tissues were stained by Masson's reagent, rinsed by 15% or 30% sucrose and snap-frozen. Collagen volume fraction was calculated by dividing the blue-stained fibrotic area by the total area using Image J.Frozen slices of heart were used for immunofluorescence histochemical staining. Cryostat cardiac sections fixed with 4% paraformaldehyde were blocked in solution containing 10% FBS and 0.1% Triton X-100 for 1 h at 4 °C, followed by incubation with antibodies against WGA , GRP78 , eNOS , Serca2 or F4/80  at 4 °C for 24 h. After washing and incubating with a fluorescent secondary antibody  at 4 °C for 2 h, the slices were mounted using Vectashield hard-set mounting medium with 4′,6-diamidino-2-phenylindole .Paraffin sections of heart tissue were cut into 4mm-thick slices. Then, slices were washed with xylene two times for 5 min each and immersed in a graded series of ethanols. After that, proteinase K working fluid was added for 15-30 min at 21-37 °C. After two washes with PBS, the TUNEL-converter-POD solution reaction mixture was added and reacted with 3,3' diaminobenzidine (DAB) for colour development.We performed transthoracic ultrasound cardiography on mice under lightly anesthesia. Two-dimensional targeted M-mode tracings were recorded using a diagnostic ultrasound system  equipped with a 15 MHz transducer. The LVEF was calculated using Pombo's method. The %FS was calculated as follows: LVFS =[(LVIDd - LVIDs)/LVIDd] × 100.We used the non-invasive methods to measure the blood pressure of conscious mice by a computerized tail-cuff system . First, mice were trained for 3 consecutive days to adapt to the procedure. Then, heart rate and blood pressure were record. For each mouse, 10 measurements were obtained and the mean values were calculated.Serum concentrations of creatinine, urea nitrogen, angiotensin II, aldosterone, BNP, ALT, AST, KIM-1, NGAL, RBP4 were detected by using Creatinine Kit , Blood Urea Nitrogen Kit , Angiotensin II ELISA kit , Aldosterone ELISA kit , Brain Natriuretic Peptide EIA Kit , ALT Kit , AST Kit , Mouse KIM-1 ELISA Kit , Mouse NGAL ELISA Kit , Mouse RBP4 ELISA Kit . Plasma concentrations of IL-1β, IL-6 and TNF-α were measured by Mouse IL-1β ELISA Kit , Mouse IL-6 ELISA Kit ab222503, Abcam), Mouse TNF-α ELISA Kit . Serum levels of retinol and retinoic acid were measured by liquid chromatography/mass spectrometry analysis following the previous methods 03, AbcamExercise capacity test was conducted in a 6-lane rodent treadmill system . First, mice were put to run at low speed (1m/min) for 10 minutes to acclimatization. Then, exercise testing was performed by gradually elevating running speed (increasing 1m/min every 2 minutes). After mice left the lane and remained on a pad for 5s, maximal speed and running distance were record. Exercise capacity was demonstrated as workload, calculated as running distance multiplied by body weight.After removing the lungs completely, we used bibulous paper to wipe off the blood and water on surface and record the weight of lung as lung wet weight. Then we wrap the lungs in tin foil and dry it in a thermotank at 72°C for 72 hours. After that, we weighed the dried lung and record it as lung dry weight. pulmonary water content was calculated by dividing lung dry weight by lung wet weight.We used the Micro Malondialdehyde (MDA) Assay Kit  to evaluate the level of lipid oxidation. After weighing 0.1g heart tissue, we add 1mL extracting solution and homogenize it in ice bath. Then, we centrifuge it at 8000g 4°C for 10min and take the supernatant. After adding the working solution to the supernatant, we can calculate the MDA concentration by a microplate reader.After adding cold RIPA lysis buffer  to heart tissues, we homogenized the tissues in ice bath for 3 min and then centrifuged at 16300g, 4°C for 20 min. We collect the supernatant and evaluate the protein concentration by using Enhanced BCA Protein Assay Kit . Equal amounts of protein were separated by SDS-PAGE and electrophoretically transferred to PVDF membranes. Then we blocked the membranes in Blocking buffer for 2h and then incubated it with primary antibodies overnight at 4°C. Antibodies are described below: anti-Bax , anti-Bcl-2 , anti-Caspase 3 , anti-Serca2 , anti-GRP78 , anti-CHOP , anti-JAK2 , anti-STAT5 , anti-p-STAT5 . Expression levels were normalized by probing the same blots with an anti-GAPDH antibody .The heart tissue of Sham group (n=6), CKD-HFpEF group (n=6) and db/db group (n=6) were sent for RNA sequencing. The RNA was sequenced by next-generation RNA sequencing using Illumina HiSeqTM 2000 in Novogene . Differentially expressed genes were screened using the following criteria: (1) fold change >2 for upregulation or fold change<0.5 for downregulation, (2) P value <0.05. Principal component analysis and venn diagram was used to demonstrate the similarity and difference between CKD-HFpEF group and db/db group. GO and KEGG analysis were applied to predict the underlying mechanism and pathways. the protein-protein interaction network was also drawn to predict the possible relationship among differentially expressed molecules.-▲▲CT method. All reactions were repeated in triplicate.RNA was extracted with TRIzol™ Reagent . The concentration and purity of RNA were assessed with NanoDrop 2000 spectrophotometer (Thermo Fisher Scientific). Samples with 1000 ng or higher and an A260/A280 ratio of 1.8-2.0 were considered qualified for use. Qualified RNA was stored at -80°C for further analysis. cDNA was reverse transcribed using PrimeScrip Reverse Transcription Master mix . A total of 20 μL reaction system was used, including DNA template 1.6 μL and SYBR 10 μL, and primers 0.4 μL and ddH2O 7.6 μL. Primers used in this study were as follows: JAK2 forward primer: 5′-GGAATGGCCTGCCTTACAATG-3′, JAK2 reverse primer: 5′-TGGCTCTATCTGCTTCACAGAAT-3′, STAT5 forward primer: 5′-CAGCCGTGGGATGCTATTGA-3′, STAT5 reverse primer: 5′-GGGACAGCGGTCATACGTG-3′. The quantitative PCR was performed in a CFX Connect Real-Time system  and the PCR reaction cycles were set as follows: 30 s at 95 °C, then 5 s at 95 °C and 30 s at 60 °C for 40 cycles. The relative expression levels were normalized to those of the reference gene GAPDH and calculated using the 2Continuous variables are presented as means±SEs or medians (with 25th and 75th percentiles). Student's t test was used to determine the differences between two groups of Gaussian distributed variables. Among multiple groups of Gaussian distributed variables, ANOVA was used to tell the differences. While variables that were not Gaussian distributed, Wilcoxon rank sum test and Kruskal-Wallis test were used for differences between two groups and more than two groups of variables, respectively. Categorical variables are reported as percentages and were analysed by either the chi-square test or Fisher's exact test. Pearson correlation analysis and Spearman correlation analysis were performed to analyse Gaussian and non-normally distributed variables, respectively. Receiver operating characteristic curves were used to establish cut-off values for HFpEF after CKD predictions. All P values are 2-sided, and P values of less than 0.05 were considered statistically significant. All statistical analyses were carried out by using SPSS 16.0 and R 3.3.0 software.First, we evaluated the classic chronic kidney disease (CKD) mouse model in a long observation period, in order to determine whether CKD model can develop into heart failure with preserved ejection fraction (HFpEF) over time spontaneously without drug induction. The 5/6 subtotal nephrectomy (5/6Nx) model is a classical CKD mice model which is widely used to mimic human CKD in mice. 5/6 subtotal nephrectomy can induce the progressive renal failure involving glomerulosclerosis and tubulointerstitial fibrosis, which present as persistent serum creatinine elevation for more than 4 weeks Not like renal function and blood pressure, cardiac function decline and myocardial hypertrophy were appeared andante. Though brain natriuretic peptide (BNP) level was progressing right after surgery, LVPWs and LVPWd were significantly increased 18 weeks after surgery  or high-fat diet from 2-hit HFpEF mouse model. However, 1% NaCl or L- NG- nitro arginine methyl ester (L-NAME) injection caused high death rate and high-fat diet could not induce HFpEF in CKD. Therefore, we reviewed the articles of heart failure in CKD to find an appropriate way to induce HFpEF after CKD. Recent research reported retinol could prompt heart failure occurrence in CKD by accelerating inflammation and fibrosis through Clock/Arntl/GPR68 signal Since the retinol could promote myocardial hypertrophy and fibrosis but not HFrEF progression, we explored whether retinol induction could accelerate HFpEF in CKD mice before LVEF and LVFS declined. We conduct a vitamin A dosage gradient experiment by giving vitamin A 100mg/kg, 300mg/kg, 500mg/kg and 800mg/kg intragastrically every day for 6 weeks right after 5/6Nx. Observing after vitamin A administration, serum retinol level was climbing with the dosage of vitamin A increased, but blood pressure, aldosterone and angiotensin Ⅱ keep no significant difference Fig. A. SignifFurthermore, we observed the 5/6 Nx mice receiving vitamin A 300mg/kg for 32 weeks to determine the progression of heart failure in CKD mice. Comparing to the 5/6 Nx mice, 5/6 Nx mice receiving vitamin A 300mg/kg demonstrated concentric cardiac hypertrophy, preserved ejection fraction and fibrosis in the early period of CKD. Finally, them would enter HFrEF stage in the same time in the late period of CKD Fig. A and B. A qualified HFpEF mouse model should fulfil the major features including ejection fraction ≥50%, diastolic dysfunction, exercise intolerance, pulmonary edema and concentric cardiac hypertrophy + macrophage and the increase of serum IL-1β, IL-6 and TNF-α showed inflammatory state in HFpEF after CKD mice | >1 and P<0.01 A. CombinAlso, we compared RNA profile of HFpEF after CKD mice to the db/db HFpEF mice, in order to explore the RNA heterogeneity between HFpEF after CKD and metabolic induced-HFpEF. Principal component analysis (PCA) showed HFpEF after CKD group, db/db group and control group were separated clearly. Although samples from HFpEF after CKD group and db/db group were close to each other, there was no overlap between these two groups Fig. A. UnsupeTo explore the potential mechanism that retinol induces HFpEF in CKD, we reviewed on the metabolism of retinol. Circulating retinol is carried by retinol binding protein 4 (RBP4). After reaching the target cell, retinol was released from RBP4 and the unloaded RBP4 can stimulate Toll-like receptor 4 and activation c-Fos/c-Jun pathway. After uptake by Stra6, retinol is converted into retinoic acid intracellularly, which activates retinoic acid receptor (RAR) and retinoid X receptor (RXR). These receptors form heterodimers and activate JAK/STAT pathway by upregulating JAK2 and phosphorylating STAT5 We used STAT5 phosphorylation small molecule inhibitor AC-4-130 to explore the role p-STAT5 mediated by retinol plays in the HFpEF progression in CKD 2PEF clinical score. Since the strong link between serum retinol and HFpEF after CKD, we explored the prediction value of serum retinol for HFpEF occurrence in CKD patients. We discovered serum retinol could predict the HFpEF occurrence in CKD patients with AUC 0.917 [0.789-1.000] , db/db mouse model and ZSF1 rat model (classified as obesity and diabetes induced HFpEF) and multi-hit mouse model (classified as multi-comorbidities induced HFpEF model) are representative HFpEF models considering the stability and manifestation Our study has several limitations. First, the stability of HFpEF after CKD mouse model need to be improved because HFpEF would switch to HFrEF in the late period of CKD. Though it is rare in clinical, progression to HFrEF or others within a variable amount of time is a common problem for many HFpEF animal model including Fischer 344 rat (evolving into eccentric hypertrophy), Dahl salt-sensitive rat (evolving into HFrEF), db/db mouse (evolving into diabetic cardiomyopathy) In conclusion, this study offers a novel method to establish the HFpEF after CKD mouse model and the first analysis of the differences of gene expression patterns between HFpEF after CKD and metabolic induced-HFpEF. An underlying mechanism was revealed. Serum accumulation of retinol in CKD prompts myocardial hypertrophy and fibrosis by activating JAK2/STAT5. And the STAT5 phosphorylation inhibitor may be a potential intervention target for HFpEF after CKD.Supplementary figures and table.Click here for additional data file.


Primary immune thrombocytopenia (ITP) is a common autoimmune disorder. Secretion of TNF-α, TNF-β and IFN-γ plays a major role in the pathogenesis of ITP. This cross-sectional study aimed to detect TNF-α (−308 G/A) and TNF-β (+ 252 A/G) gene polymorphism in a cohort of Egyptian children with chronic ITP (cITP) to clarify their possible association with progression to chronic disease.The study included 80 Egyptian cITP patients and 100 unrelated age- and sex-matched controls. Genotyping was performed using polymerase chain reaction–restriction fragment length polymorphism (PCR–RFLP).p values 0.005, 0.024 and 0.008, respectively). TNF-α wild (G/G) genotype was significantly more frequent among responders (p = 0.049). Complete response was more frequent among wild (A/A) TNF-β genotype patients (p = 0.011), and platelet count was significantly lower among homozygous (G/G) genotype (p = 0.018) patients. Combined polymorphisms were strongly associated with susceptibility to chronic ITP.Patients with TNF-α homozygous (A/A) genotype had significantly higher mean age, longer disease duration and lower platelet counts (Homozygosity in either gene might contribute to a worse course of disease, increased severity and poor response to therapy. Patients expressing combined polymorphisms are more prone to progression to chronic disease, severe thrombocytopenia and longer disease duration.The online version contains supplementary material available at 10.1007/s12185-023-03551-9. Better understanding of the underlying pathophysiology of ITP allowed recent recognition of other mechanisms that are clearly involved. These include T cell-mediated apoptosis of megakaryocytes, inhibition of platelet production and T cell-mediated destruction of platelets [9/L with no clear initiating and/or underlying causes as the diagnostic threshold for primary ITP [. In children with chronic ITP (cITP), the disease often has a gradual onset occurring in older children lasting for more than 12 months with rare incidence of spontaneous remission and commonly requires therapy [.Primary immune thrombocytopenia (ITP) is an autoimmune disease associated with reduced peripheral circulating platelets count. The reduced peripheral blood platelets count is a result of a combination of premature platelet destruction  and a relatelets . Expertsmary ITP . In chil therapy , 7.. A disruption in the balance of Th1, Th2 and Th17 with secretion of proinflammatory cytokines plays a major role in the pathogenesis of ITP [. This includes dysfunction of regulatory T cells, increased T lymphocyte-mediated cytotoxicity and elevated Th17 cells, on one hand [. Such proinflammatory cytokines may play a fundamental role in the pathogenesis of chronic course of the disease, which might be the base for future specific immunomodulatory therapies for cITP in children. This cross-sectional study aimed at detecting TNF-α (-308 G/A) and TNF-β (+ 252 A/G) gene polymorphism in a cohort of Egyptian children with cITP to clarify their possible association with chronic evolution of the disease.Several genes are involved in immune system regulation like cytokine genes, FcγR gene, cytotoxic T lymphocyte-associated protein-4 (CTLA-4) gene, and human leukocyte antigen (HLA) gene , 9. A dis of ITP , 11. Thione hand . Such prThe present work included 80 Egyptian patients diagnosed to have cITP (defined as immune thrombocytopenia that lasted longer than 12 months duration) followed up at the Pediatric Hematology Outpatient Clinic of Cairo University Children Hospital, Faculty of Medicine, Cairo University. One hundred age- and sex-matched unrelated Egyptian healthy children were included as a control group. An informed consent was willingly obtained from all parents prior to the study. The study protocol was approved by the Research Committee of Faculty of Medicine, Cairo University on 21/12/2016.The patient group included 44 males (55%); their age ranged from 2 to 14 years with a mean of 7.08 ± 3.64 years. whereas the age- and sex-matched Egyptian healthy unrelated control group (n = 100) had a mean age of 7.64 ± 3.52 years with 56% being males. Patients with secondary causes of ITP such as HCV, SLE, underlying malignancy or drug-induced thrombocytopenia were excluded. None of the patients had positive ANA, anti-HCV antibody or anticardiolipin antibody. All patients had normal levels of C3 and C4. A thorough review of medical records and direct examination of all subjects were performed.9/L and response (R) was defined as any platelet count between 30 and 100 × 109/L and at least doubling of the baseline count. On the other hand, no response (NR) was defined as any platelet count lower than 30 × 109/L or less than doubling of the baseline count [. Refractory patients were those fulfilling two criteria: first, those who failed splenectomy or relapsed thereafter; second, those who exhibit severe ITP or have a risk of bleeding and require therapy.Complete response (CR) was defined as any platelet count of at least 100 × 10ne count . RefractClinical and hematological characteristics for cITP patients are attached as a supplementary file.Ten ml blood samples were collected under aseptic conditions by means of clean venipuncture in a vacutainer containing EDTA, of which 2 ml was for performing CBC, 5 ml for laboratory screening and 3 ml blood for PCR–RFLP analysis of TNF-α (-308G/A) and TNF-β (+ 252A/G) gene polymorphisms.One hundred microliters (100 μl) of the sample (whole blood) was worked upon for extracting DNA using the Quick-gDNA™ MiniPrep kit . Amplification was performed through repetitive cycles of DNA denaturation, primer annealing and extension by DNA polymerase using MyTaq™ Red Mix . The primers for TNF-α and TNF-β genes were provided by . The restriction enzyme (RE) used is NcoI-HF . TNF-α (-308 G/A) and TNF-β (+ 252 A/G) gene polymorphisms among cITP patients and control group were interpreted according to the number of bands and bp of each genotype .Wild G/G genotype gives two bands at 87 bp and 20 bp.Heterozygous G/A genotype gives three bands at 107, 87 and 20 bp.Homozygous A/A genotype gives a single band at 107 bp.Wild A/A genotype gives a single band at 782 bp.Heterozygous A/G genotype gives three bands at 782, 586 bp and 196 bp.Homozygous G/G genotype gives two bands at 586 bp and 196 bp.p values less than 0.05 were considered statistically significant.Data were coded and entered using the statistical package SPSS version 23. Data were expressed using mean, standard deviation, median, minimum and maximum for quantitative variables, and frequencies (number of cases) and relative frequencies (percentages) for categorical variables. Comparisons between quantitative variables were done using the non-parametric Kruskal–Wallis and Mann–Whitney tests. For comparing categorical data, Chi-square (χ2) test was performed. Exact test was used instead when the expected frequency was less than 5. Genotype and allele frequencies were compared between the disease and the control groups using Chi-square tests. Odds ratio (OR) with 95% confidence intervals was calculated. In this study, TNF-α genotyping revealed that the frequency of wild G/G, heterozygous G/A and homozygous A/A genotypes among cITP patients were 81.2%, 15.0% and 3.8% versus 79.0%, 20.0% and 1.0% among the control group, respectively, with no statistically significant difference between both groups. TNF-β genotyping revealed that the frequency of wild A/A, heterozygous A/G and homozygous G/G genotypes among cITP patients was 55%, 40% and 5% versus 60%, 28% and 12% in the control group, respectively ; patients with homozygous (A/A) genotype showed significantly higher mean age, longer disease duration and lower platelet count , heterozygous (G/A) and homozygous (A/A) genotypes of TNF-α gene showed a statistically significant difference with regard to age, disease duration and platelet count  and platelet count was significantly lower among homozygous (G/G) genotype   genotype (18) Fig. . No otheComparison between TNF-α and TNF-β genotypes among cITP patients with regard to demographic clinical and hematological data are shown in a supplementary file.p values 0.006, 0.002 and 0.047, respectively) [Fig. Comparison was done between patients exhibiting polymorphism of either TNF-α or TNF-β genes (a single gene polymorphism) and patients exhibiting polymorphisms of both TNF-α and TNF-β genes (combined gene polymorphism). Combined gene polymorphisms revealed statistically significant difference regarding age, disease duration and platelet count (ly) Fig. ; age andComparing single and combined TNF-α and TNF-β gene polymorphisms in cITP patients and the control group with regard to risk of cITP development, a statistically significant difference between the two groups was noted (p = 0.015). Calculated risk estimation revealed that combined gene polymorphisms conferred threefold increased risk of development of cITP  [Table . However, findings from various studies were conflicting. This cross-sectional study aimed at detecting TNF-α (-308 G/A) and TNF-β (+ 252 A/G) gene polymorphisms in a cohort of Egyptian children with cITP to clarify their possible association with chronic evolution of the disease.It has been suggested that susceptibility to autoimmune diseases may be directly related to polymorphisms in the TNF genes, such as TNF-α (-308G/A) gene –16 and T. In contrast, Pehlivan et al. (2011) and Mokhtar et al. (2016) reported higher frequency of A/G genotype in patients with ITP [.In this study, TNF-α (308 G/A) genotyping showed no significant difference in the frequencies of genotypes between cITP patients and controls. This is in concordance with the findings by other studies , 17–19. with ITP , 20.. However, two studies reported higher frequency of A allele in ITP patients than controls [.Our work revealed no significant difference in the frequencies of TNF-β (+ 252 A/G) genotypes between patients and controls. This is in agreement with other reports , 21. Howcontrols , 17.Discrepancies in findings between studies might be attributed to variations in sample size and dissimilarity in patients' selection including disease stage or ethnic differences in some populations.Our observation that patients with homozygous TNF-α (A/A) or TNF-β (G/G) genotypes or combined genetic polymorphisms had significantly lower platelet counts suggests that these genetic polymorphisms could be implicated in the severity of thrombocytopenia and might affect disease severity. In addition, patients with homozygous TNF-α (A/A) genotype or combined gene polymorphisms were significantly older and had longer disease duration, affecting disease duration and course.. Another study reported significantly higher TNF-α A/G phenotype in steroid-refractory and splenectomized cases at the end of the first year than in steroid-responsive and remission cases [. Thus, TNF-α (308 G/A) gene polymorphism may contribute to therapy resistance in cITP.In our study, TNF-α wild (G/G) genotype was significantly more frequent among responsive cITP patients, while heterozygous (G/A) and homozygous (A/A) genotypes were more frequent among unresponsive patients. In agreement, one study showed that the A allele of TNF-α (308G/A) was more frequent in patients with unresponsive ITP . Anotheron cases . Thus, T. A possible explanation may be differences in patients’ sample size, age group, disease stage and ethnic or geographic background.Our study showed that the probability of having a complete response to treatment was highest among the wild A/A genotype of TNF-β (+ 252 A/G) and the least among the heterozygous A/G genotype. In contrast, two studies did not show any effect of TNF-β (+ 252 A/G) gene polymorphisms on treatment response , 21. A p. Thus, TNF-β (+ 252G/A) polymorphism affects the expression of both genes and the concentration of TNF-α and TNF-β proteins in plasma [. Our study showed that neither the variant genotypes of TNF-α GA/AA and its minor A allele nor variant genotypes of TNF-β AG/GG, and its minor G allele alone are risk factors for the susceptibility to cITP in pediatric Egyptian patients. However, patients expressing combined gene polymorphisms are more prone to the development of chronicity; combined gene polymorphisms conferred threefold increased risk of development of cITP. Few studies suggested that the homozygous G/G genotype of TNF-β may be associated with increased susceptibility to ITP or increased risk for chronic ITP development [. In contrast, Morgan et al., 2018 showed no increased risk for developing ITP was associated with any TNF-β allele/genotype [. However, Okulu et al., 2011 reported no association between TNF-α gene polymorphism and the risk of developing ITP or its clinical progress [. A systematic meta-analysis of eight high-quality case–control studies, including 947 patients and 1911 controls, revealed that TNF-α -308G/A under the dominant model (AA + AG versus GG) might significantly increase ITP risk in Caucasians, however, no statistically significant association was observed in overall and Asian populations, revealing that allele A carrier (AA + AG) of rs1800629 might increase predisposition to ITP in Caucasians. This was explained by the higher frequency of A allele in Caucasian population and relatively small sample size in cases and control among Asian populations. Besides, TNF-α −308G/A polymorphism was reported to affect gene transcription by increasing TNF-α production and regulating cell proliferation and differentiation, leading to potentially exacerbate the outcomes of ITP [. Discrepancies between studies could be a reflection of several factors, such as sample size, patients’ selection criteria, and genetic heterogeneity of various ethnic populations or different age groups or that these two gene polymorphisms are in linkage disequilibrium with other neighboring genes. It also may be attributed to differences in disease pathogenesis and disease progression between different age groups.Both studied genes are present within the MHC locus on chromosome 6p. The TNF-α gene is located in the class III region of the MHC on chromosome 6p21.33. TNF-α −308G/A polymorphism has been previously found to increase TNF-α transcription by six- to eightfold and has been associated with increased TNF-α production and development of several autoimmune diseases including ITP. The TNF-β gene is adjacent to the TNF-α gene within a 7-kb locus in the MHC. The TNF-β + 252G/A) polymorphism is located in the first intron and it correlates with the level of TNF-β protein production by lymphocytes , 23. Ind2G/A polyn plasma . Our stuelopment , 18. In genotype , 15. Howprogress . A systes of ITP . DiscrepOur results indicate that homozygous genotypes of either TNF-α or TNF-β genes might contribute to worsening of disease course, aggravating disease severity and having poor response to therapy. A novel finding in our study is that patients expressing combined studied gene polymorphisms are more prone for disease chronicity and severe thrombocytopenia with longer disease duration. Thus, the expression of TNF-α and TNF-β gene polymorphisms seems to play an important role in the pathogenesis of childhood cITP and may contribute to modification of the disease course and response to treatment. However, multiple other genetic and environmental factors play a role in the pathogenesis of ITP. The possible contribution of TNF-α (308 G/A) gene polymorphism to therapy resistance is worth further studying.Further research needs to be extended including larger cohorts of patients and longer periods of follow-up to allow for the development of novel therapeutic targets and hence a better disease outcome.A novel finding in our present study is the significant association between combined polymorphisms of both TNF-α and TNF-β genes and susceptibility to developing chronicity of ITP in Egyptian children. Patients expressing combined gene polymorphisms have a more severe disease form and prolonged disease duration. Screening for TNF-α and TNF-β gene polymorphism might be of value for ITP patients to predict disease severity and response to treatment.Supplementary file1 (DOCX 755 KB)Below is the link to the electronic supplementary material.


Despite their fundamental role in resolving viral infections, our understanding of how polyclonal neutralizing antibody responses target non-enveloped viruses remains limited. To define these responses, we obtained the full antigenic profile of multiple human and mouse polyclonal sera targeting the capsid of a prototypical picornavirus, coxsackievirus B3. Our results uncover significant variation in the breadth and strength of neutralization sites targeted by individual human polyclonal responses, which contrasted with homogenous responses observed in experimentally infected mice. We further use these comprehensive antigenic profiles to define key structural and evolutionary parameters that are predictive of escape, assess epitope dominance at the population level, and reveal a need for at least two mutations to achieve significant escape from multiple sera. Overall, our data provide a comprehensive analysis of how polyclonal sera target a non-enveloped viral capsid and help define both immune dominance and escape at the population level. Neutralizing antibodies are key to resolving viral infections and confer long-term protection. This work provides a detailed analysis of how murine and human sera neutralize a non-enveloped human virus, coxsackievirus B3, and how the virus can escape them. Consequently, vaccination strategies frequently aim to elicit polyclonal neutralizing antibody responses utilizing these same viral proteins2. In turn, viruses must overcome these immune responses for their successful spread in previously infected or immunized populations, establishing a continuous evolutionary arms race to alter immunodominant epitopes and refine antibody responses3.Neutralizing antibodies are key to resolving viral infections and can provide long-term protection against reinfection. These antibodies mostly target viral proteins involved in cell entry, namely membrane proteins in enveloped viruses and capsid proteins in non-enveloped viruses9. These studies have revealed the breadth and relative strength of neutralization sites induced by both natural infection as well as vaccination and helped define mutations conferring escape from neutralization. However, our knowledge of how non-enveloped viruses are targeted by polyclonal sera remains limited, despite the fact that they constitute >40% of mammalian viruses10. Moreover, fundamental differences between capsid proteins and viral envelope proteins could preclude the extrapolation of results from enveloped to non-enveloped viruses. In particular, carbohydrate modifications that alter the sensitivity of viral membrane proteins to antibody neutralization11 are absent in viral capsids. Additionally, non-enveloped viral capsids encode multiple functions not found in viral membrane proteins, including the information for assembly, genome packaging, and genome release, which could significantly constrain their ability to tolerate mutations conferring immune escape. Obtaining a deep understanding of how viral capsid proteins are targeted by, and escape, polyclonal antibody responses is therefore of key importance for understanding host-pathogen interactions and viral evolution of this large fraction of viruses.Recent high-throughput approaches have provided new insights into how viral membrane proteins are targeted by polyclonal antibody responses for several enveloped viruses, including human immunodeficiency virus, influenza A virus, and SARS-CoV-212, revealing an icosahedral capsid whose symmetry is conserved across all capsids of non-enveloped viruses in vertebrates. The picornavirus capsid is comprised of 60 copies of four structural proteins, three of which are surface-exposed  and one that lines the internal capsid surface (VP4)13. A depression in the capsid, termed the canyon, frequently harbors residues involved in receptor binding14. Antibody neutralization in picornaviruses has been mapped to four surface-exposed structural regions using escape from monoclonal antibodies (mAbs) and structural studies: the canyon northern rim (five-fold axis), inner surface (canyon floor), and southern rim (canyon outer surface) as well as the two and three-fold plateau . Our results reveal a conserved antigenic profile in mice that focuses on a single common antigenic site. In contrast, we find human polyclonal responses to be diverse, targeting anywhere from a single dominant site strongly to several sites across the capsid with reduced potency. Capitalizing on the large dataset of antibody-escape mutations defined in our study, we show that a few key structural and evolutionary parameters are sufficient to predict escape with relatively high accuracy. Finally, we define the immune dominance of the identified escape sites at the population level and demonstrate that a combination of two mutations can confer significant evasion from neutralization by multiple human sera. Overall, our results provide a comprehensive understanding of how polyclonal neutralizing antibody responses target a prototypical human picornavirus and reveal epitope dominance at the population level.21 . To define which mutations reduce sensitivity to antibody neutralization, these populations are treated with either a monoclonal antibody (mAb) or neutralizing sera so that infectivity is reduced by 90–99% relative to mock treatment, balancing sufficient selection to observe escape without losing mutations with intermediate phenotypes .To define how picornaviruses are targeted by polyclonal antibody responses, we modified an experimental workflow that provides a quantitative evaluation of how mutations in a viral population confer escape from antibody neutralization, termed deep mutational antigenic profiling21 Fig. . Brieflypes Fig. . Mutants23 Fig. r of 0.72–0.81; Figure r of 0.67–0.69; Figure 24. Mapping of the positive differential selection values to the structure of the CVB3 capsid locates these sites in a single region of escape on the outer surface of the canyon, as expected for a mAb .To validate our ability to identify mutations conferring escape from antibody neutralization, we first treated the CVB3 populations using a commercially available mouse mAb . All mutants from the three principal escape sites strongly evaded neutralization  from the three most relevant sites of escape and two mutations predicted to confer low (K650Y) or no (K723E) escape . We next evaluated the antigenic profile of these sera. Unexpectedly, all three sera showed a similar antigenic profile, suggesting that the response of experimentally immunized mice is relatively invariable . Overall, 60% of sera was neutralizing , 3.69 (K827V), and 2.91  presented escape mutations across two capsid regions: the canyon inner surface  and the northern rim  were broadly distributed across the capsid. Some of the main escape sites mapped to the VP2 EF loop and the VP1 C-terminal loop in the canyon outer surface, which are secondary structure elements also involved in the escape profile of serum h75 . In agreement with the profile of serum h19, mutation K227S (VP2 EF loop) and K723E (northern rim of the canyon) conferred fold changes in the IC50 of 4.4 and 5.19, respectively Fig. . The h75n = 5776) a dataset comprising structural, physicochemical, and evolutionary parameters. In addition, we predicted the effects of all such mutations on protein stability, aggregation propensity, and disorder . This data was combined with a Boolean feature indicating whether the mutation led to strong escape in the antigenic profiling experiments (“escape”) or not (“no escape”). Specifically, we define escape mutations (n = 213) as those conferring strong escape on their own  and occurring in a residue with a strong overall contribution to escape .Having obtained a comprehensive dataset of mutations conferring escape from eight different human sera, we next examined whether these mutations can be predicted based on different attributes using a machine-learning approach. To this end, we compiled for all possible mutations in surface-exposed capsid residues  output  but could also result from incomplete identification of some mutations conferring escape in the antigenic profiling experiments. To address this possibility, we reran the RF algorithm on 1000 different random samples of training and testing datasets and identified mutations that were consistently classified as conferring escape by the RF algorithm (>70% probability) but not in the antigenic profiling experiments . In total, 27 such mutations were identified. Interestingly, all of these occurred in 12 sites where strong escape was already observed with other mutations in the antigenic profiling experiments, strongly suggesting these are likely to confer escape. Reclassification of these 27 instances in the dataset increased the predictability of the RF classifier by 53% in every testing dataset following training (accuracy The reduced predictability observed in the testing dataset for mutations conferring escape could stem from their low number in the dataset (~4% or 35 and Shapley additive explanations (SHAP) values36 , and leucine in particular (p < 0.01 by Fisher’s exact test), was observed at escape sites  and depleted in others  but this was not generalizable to other AA with the same characteristics s36 Fig. . Of the tes Fig. . On the To validate the relevance of the top seven features identified above for predicting escape, we trained and tested an RF classifier using only these features on the dataset including the 27 reclassified instances from above. Notably, the predictability of the RF classifier increased appreciably when evaluated on the testing dataset using only the top seven features versus the full set of features . Of these, 39.5% (30/76) were located on the northern rim of the canyon, 34.2% (26/76) on the outer surface of the canyon, 17.1% (13/76) on the inner surface of the canyon, and 9.2% (7/76) in the three-fold plateau Fig. . Most sap = 0.01 and p = 1.08 × 10−5 vs. K723E and P798H, respectively, by a two-tail t test). Moreover, in nearly 20% of the sera (5/26 sera), the K723E + P798H double mutant reduced neutralization by >20-fold versus the WT virus. Such escape was not observed for any of the single mutants, suggesting strong escape from antibody neutralization requires the combination of at least two mutations.When single mutations conferred escape, their effects on neutralization were relatively moderate (average IC50 fold-change of 5.1 ± 4.0). As viruses can accumulate multiple mutations during adaptation, we assessed the ability of viral mutants encoding two escape mutations to evade neutralization by the top 26 most neutralizing sera. Surprisingly, a double mutant encoding the two most prevalent escape mutations at the population level, D535T and K723E, did not reduce neutralization compared to the single mutations alone and even reduced the degree of escape in some cases Fig. . Indeed,p = 0.01 and p = 0.003 by two-tail t-test for D535T and K723E, respectively; Fig. p value = 0.0007 and p = 0.0021 versus D535T and K723E by two-tail t test, respectively). The fitness of the mutant showing the strongest escape (K723E + P798H) was 50% lower than the WT (p = 0.011 by two-tail t test) but was not significantly different from the fitness of the individual mutants . Overall, mutants conferring escape from multiple sera (>20% of the sera tested) had strong fitness costs (average fitness of 0.28 ± 0.11), while those conferring escape from only a few sera (<20% of the sera tested) were less deleterious (average fitness of 0.73 ± 0.35), although this difference did not reach statistical significance (p = 0.08 by a two-tail t-test). Together, these results suggest that escape from existing immunity may come at a significant cost to viral fitness, in particular for mutations in the most common sites.The ability of a virus to successfully infect a host is dependent on viral fitness. As some of the mutations examined above-conferred escape from nearly all sera, we sought to determine whether variation at these particular sites is not observed due to strong effects on viral fitness. We therefore directly assayed the effect of all single and double escape mutations on viral fitness in the absence of antibody selection. Of the eight single mutants tested, five incurred a fitness cost compared to the WT virus. In particular, the two mutations conferring escape in all sera (D535T and K723E), reduced viral fitness to 20% and 30% relative to the WT virus, respectively  are unknown. In this sense, analysis of the antigenic profiles from children may be informative to distinguish these possibilities as, unlike adults, they are likely to have been exposed to a single CVB3 variant. Finally, cross-neutralization by different picornaviruses has been recently demonstrated in mice42, and could also influence the breadth of neutralizing antibody responses. However, this does not seem to underlie the difference between sera showing narrow or broad neutralization profiles as a preliminary analysis showed these to have similar neutralization capacity against five different CVB clinical strains  protein, which were focused on a single region and could be efficiently evaded by individual mutationsity Fig. , repeateHaving obtained a comprehensive dataset of mutations conferring escape in eight human sera, we sought to understand whether such mutations could be predicted using machine-learning approaches and to define the most relevant attributes for such prediction. We found that an RF could predict escape to relatively high accuracy based on only seven features, indicating that mutations conferring escape have unique, typifying attributes Fig. . Specifi43. However, several additional observations were made from this analysis. First, the two mutants conferring the most significant escape in the antigenic profiles, K227S and A473L  and mutation of both residues showed similar fitness to that of the individual mutants, suggesting escape could rapidly arise  did not lead to increased escape compared to the individual mutations Fig. . In contise Fig. .13). Nevertheless, it is important to note that the methodology used in this study can only detect the effects of single mutations. Indeed, only by combining two of the mutations identified in the different profiles were we able to show the prevalent and, at times, dominant escape conferred by combined mutations at sites 723 and 728  while others can reach much higher antigenic diversity , integrated in the Spanish National Biobanks Network and in the Valencian Biobanking Network. Animal work was approved by the Valencian government’s ethics committee . Experiments with infectious viruses and genetically modified organisms were approved by the Spanish committee on genetically modified organisms, the University of Valencia’s biosafety committee, and the institute’s biosafety committee.49. The titer of these reporter viruses was obtained by infecting Hela H1 cells with serial dilutions of each virus in 96-well plates and counting the number of fluorescent cells at 8 h post-infection using an Incucyte SX5 Live-Cell Analysis System (Sartorious). The CVB3 populations harboring high diversity in the capsid region have been previously described22. Briefly, a reverse genetics plasmid encoding CVB3 genome was mutagenized at the codon level to generate viral populations containing >96% of all possible single amino acid mutations in the capsid region. The virus populations were then passaged at low multiplicity of infection (MOI) to create a passage 1 population in which there is a genotype-phenotype link between the capsid proteins of each virus and the genome it carries. The viral titers in these libraries were determined by plaque assay in Hela H1 cells. The coxsackievirus clinical strains were obtained from EVAg and were: CVB1 , CVB3 , CVB4 , CVB5 , and CVB6 50. These viruses were treated with chloroform to remove mycoplasma, amplified in HeLa H1 cells for 2 passages, and titered by limiting dilution at 7 days post-infection. All virus experiments were carried out under BSL2 conditions after obtaining approval from the biosafety committees of both I2SysBio and the University of Valencia. All work with genetically modified organisms was approved by the relevant national committees.HeLa H1  and HEK293T cells (CRL-3216) were obtained from ATCC and were periodically validated to be free of mycoplasma. Cells were cultured in culture media  supplemented with 10% or 2% heat-inactivated fetal bovine serum for culturing or infection, respectively. The anti-Coxsackievirus B3 monoclonal antibody was obtained from Merck . The human codon-optimized T7 polymerase plasmid was obtained from Addgene (#65974) and the CVB3 infectious clones encoding mCherry (CVB3-mCherry) or eGFP (CVB3-eGFP) were previously described4 (m1) or 105 (m2 and m3) PFUs of CVB3 and sera were collected three weeks post-infection. All sera were heat-inactivated for 30 min at 55 °C before use.The 140 human sera used in this study were provided by the IBSP-CV Biobank (PT17/0015/0017), integrated into the Spanish National Biobanks Network and in the Valencian Biobanking Network and they were processed following standard operating procedures with the appropriate approval of the Ethics and Scientific Committees and with signed informed consent from the participants. All samples were collected from healthy donors between 2010-2021 and included 74 females and 66 males. No information was available on the CVB3 infection record of these individuals. For mouse sera , five-week-old male Balb/C mice  were infected via intraperitoneal injection with 1022. For each serum or antibody, we performed two biological replicates , with one or two replicates of each of the virus libraries . Briefly, 106 PFU of each virus library were mixed with sera or antibodies at the indicated dilutions to have 1% to 10% of the virus library survive the neutralization treatment, as judged by qPCR (see below). Mock-neutralized controls were included for each neutralized library replicate. After a 1 h incubation at 37 °C, Hela H1 cells plated the day before in six-well plates were infected with the virus-antibody mix or virus alone. At 8hpi, cells were subjected to three freeze–thaw cycles, cell debris was removed by centrifugation at 500 × g, and the supernatants were collected. Finally, 200 μL of each sample were treated with 2 μL of RNase-Free DNaseI (ThermoFisher) for 30 min at 37 °C, and viral RNA was extracted using the Quick-RNA Viral Kit (Zymo Research), eluting in 20 μL.For mutational antigenic profiling, we used the passage 1 mutant virus populations derived from libraries 1 and 2 (L1 and L2) described inTo estimate the fraction of virus surviving the neutralization treatment, viral RNA was quantified by RT-qPCR using the GoTaq Probe 1-Step RT-qPCR System (Promega) on a QuantStudio3 (ThermoFisher Scientific). Ten-fold serial dilutions of RNA extracted from a known titer virus stock were used to generate a standard curve. RT-qPCR was performed using 2 μL of template RNA of neutralized and control samples (forward primer: RTqPCR_F (GAT CGC ATA TGG TGA TGA TGT GA), reverse primer: RTqPCR_R (AGC TTC AGC GAG TAA AGA TGC A), and TaqManProbe: CVB3_probe (6FAM-CGC ATC GTA CCC ATG G-TAMRA). RT-qPCR Ct values were interpolated to the standard curve to quantify viral RNA in each sample and the fraction of virus surviving neutralization was determined versus the untreated controls . As before, all single mutations in codons were omitted from the analysis to increase the signal-to-noise ratio22.For sequencing, viral RNA extracted as indicated above was reverse transcribed with the high-fidelity OneScript Plus Reverse Transcriptase  using 8 μL of RNA and the primer CVB3_RT_3450 (GTGCTGTGGTCGTGCTCACTAA). To ensure sufficient diversity was present in the cDNA, the number of capsid copies in the cDNA was quantified via qPCR using PowerUp SYBR Green Master Mix (ThermoFisher Scientific) in a 10 μL total reaction, using 1 μL of the template and the primers CVB3_qPCR_F (CCCTGAATGCGGCTAATCC) and CVB3_qPCR_R (AAACACGGACACCCAAAGTAGTC). A standard curve was generated using the original reverse genetic plasmid encoding the CVB3 genome. The full capsid region was then amplified from the cDNA using KOD polymerase Mastermix (Novagen) and the primers CVB3_P1_seq_F (CCCTTTGTTGGGTTTATACCACTTAG) and CVB3_P1_seq_R (CCTGTAGTTCCCCACATACACTG). Duplex sequencing libraries were prepared as previously described51 with the default settings. Two batches of experiments were performed with a different number of replicates. The first batch included samples mAb, m1, m2, m3, h4, h8, h39, and h46, and three non-neutralized controls for each library. Four replicates were performed for each sample . Differential selection of each sample was calculated versus the mean of the three controls. In the second batch, 2 biological replicates (libraries 1 and 2) were performed for samples h19, h75, h87, and h112 together with an individual non-neutralized control for each library. One of the replicates of h87 (library 1) had to be discarded due to the low mutation rate observed in this sample after sequencing , and positive differential selection was calculated versus the individual control of each library. All positive differential selection plots in the main figures represent the mean differential selection for each mutation at each particular site across replicates. Line plots represent the mean positive differential selection per site and logoplots represent the mean positive differential selection for each amino acid mutation at selected sites. Differential selection tables and positive differential selection logoplots of the full capsid region are available on GitHub23 (sections 2–4). Interactive visualization of the antigenic profiles using the dms-view software52 is available on GitHub23 (section 6).Codon tables were analyzed for differential selection versus mock-neutralized controls of each library using the DMS_tools2 package3 fluorescent virus units of WT or mutant CVB3 mCherry virus were mixed in duplicate with serial dilutions of each antibody or sera sample and incubated for 1 h at 37 °C. Virus-only samples without antibodies were used as a control to measure maximal fluorescence in the absence of neutralization. Virus-antibody mixes were then transferred to 96-well plates containing Hela H1 cells plated the day before. After an 8-hour incubation at 37 °C, mCherry-derived red fluorescent signal was measured using an Incucyte SX5 Live-Cell Analysis System (Sartorious) to determine fluorescent virus units per well. The antibody concentration resulting in a 50% reduction of virus signal (IC50) was obtained using the two-parameter log-logistic function LL2 from the R drc package (version 3.0.1). All IC50 values represent the mean and standard error of the curve fitting of two replicate curves run in the same 96-well plate. Results of the human samples neutralization screening (section 7) and the neutralization assays performed with different CVB3 mutants (section 8) are available on GitHub23.For fluorescence-based neutralization assays, 2.5 × 1023 (section 8)For cytopathic effect (CPE)-based neutralization assays, two-fold serial diluted sera were mixed with an equal volume of virus containing 100 TCID50/well of the virus. The virus-antibody mix was incubated at 37 °C for 1 h and then transferred to 96-well plates containing Hela H1 cells plated the day before. After an incubation of 5 days, cells were fixed with 5% PFA and stained with crystal violet. The neutralization titer was determined as the reciprocal of the highest dilution at which at least 50% of wells showed complete inhibition of CPE. All neutralizations were tested in duplicates. Results of the neutralization assay of different CVB strains are available on GitHub49. For each mutant, non-overlapping primers containing the desired mutation in one of the primers were used to introduce the mutation with Q5 polymerase, followed by DpnI (Thermo Scientific) treatment, phosphorylation, ligation, and transformation of chemically competent bacteria . Successful mutagenesis was verified by Sanger sequencing. Subsequently, plasmids were linearized with SalI-HF (ThermoFisher), and 600 ng of plasmid were transfected into 5 × 104 HEK293T cells, together with 600 ng of a plasmid encoding the T7 polymerase (Addgene 65974) using Lipofectamine 2000 (ThermoFisher) according to manufacturer’s instructions of use. Cells were then incubated until cytopathic effect (CPE) was observed and passage 0 virus was collected. Infectious virus titer was determined using an Incucyte system (Sartorius) to quantify the red fluorescence from the mCherry reporter signal as detailed above. If needed, mutants with low titers were amplified for an additional passage. The capsid region of the mutant virus populations was reverse transcribed, PCR-amplified, and sequenced to ensure no compensatory mutations or reversions arose during replication.CVB3 mutants were generated by site-directed mutagenesis using the mCherry-CVB3 fluorescent infectious clone mentioned above20hpi) provides a measure of the relative success of both the WT and mutant virus following several rounds of infection. The ratio of mCherry to eGFP signal at 8hpi (Ratio8hpi) reflects the initial relative abundance of each virus before the competition. To calculate the fitness of each mutant versus that of the WT virus, the formula (Ratio20hpiMutant/Ratio8hpiMutant)/(Ratio20hpiWT/ Ratio8hpiWT) was used. The results of the competition assay are available on GitHub23 (section 9).A 1:1 mixture of CVB3-eGFP and either CVB3-mCherry viruses encoding the WT or mutant capsid was used to infect Hela H1 cells at an MOI of 0.001 in a 24-well plate. Automated real-time quantitative fluorescence microscopy was used to track the spread of each virus in an Incucyte SX5 Live-Cell Analysis System (Sartorious). The ratio of the mCherry signal (derived from the WT or mutant virus) to the eGFP signal of the reference virus at 20hpi , ggplot2 and ggh4x (plotting), ggseqlogo (logoplots), ComplexHeatmap (heatmaps), viridis , ggcorrplot (correlation matrices), igraph , DECIPHER and Biostrings. R57 as previously reported22. Outer surface residues were defined as residues with a distance to the center of the capsid >130 Å and a surface exposure >2.5 Å2 based on the FindSurfaceResidues script in PyMol54. The relative surface area (RSA) of residues in the pentamer was calculated using PSAIA58. For entropy calculation, all available enterovirus A, B, and C full polyprotein sequences in BV-BRC (bv-brc.org) were downloaded on May 14th, 2022. Duplicate sequences were removed, and the alignments were randomly subsampled to harbor the same number of sequences using the Biostrings package in R. Sequences were then combined and aligned using the DECIPHER package in R. All gaps versus the CVB3 Nancy capsid sequence were removed, and Shannon’s entropy was calculated using a custom R script. Both the alignment file and the Shannon entropy can be found on GitHub23 (section 11). Finally, B factors were obtained from the PDB file, distance to center was calculated in PyMol using the command distance (cmd.dist),disorder was calculated on the capsid sequence using IUpred359 and Snap2 scores were obtained from SNAP260. The ΔΔG grantham, aggregation, and aa properties were calculated as previously described22. Tables used for the analysis of the characteristics of the main escape sites and mutations are available on GitHub23 (section 10).All structural features were calculated based on a CVB3 capsid pentamer (PDB ID: 4GB3) mutated to encode the Nancy strain amino acid sequence with FoldX23, section 10). To implement the analysis, the data was preprocessed. Specifically, some of the numerical features in the original dataset had nearly as many different values as the number of instances (n = 5776). This complexity  was reduced to increase the predictive capabilities of ML by implementing a binning approach that assumes an underlying smooth distribution of values and assigning all the instances falling within a bin the same value . For example, ΔΔG, which had 5,772 values originally, was reduced to 93 values following binning.The initial dataset used for the machine-learning analyses was obtained by merging the structural, physicochemical, and evolutionary features for all surface-exposed capsid residues . Sites of escape were defined as surface-exposed residues with a positive differential selection value above the mean+2 SD value per sample. Within these sites, escape mutations for each sample were defined as mutations with a >2-fold positive differential selection value  and testing (25%) datasets for each iteration of training and testing. The training dataset was balanced in terms of “escape” and “no escape” entries by repeating the “escape” entries. Following training, we evaluated the performance of three algorithms: neural network, support vector machine, and random forest Table . Given t23, section 10). All machine-learning analyses were performed using Mathematica 13.061 and the code is available on GitHub23 (section 12).Finally, to identify mutations that were consistently misclassified in the ML compared to the antigenic profiling dataset, we estimated the expected number of times that the same instance is wrongly classified in 53. ns: p > 0.05, *p < 0.05, **p < 0.01, ***p < 0.005, ****p < 0.001. All tests were two-tailed.Wilcoxon tests, Fisher’s exact tests, and t-tests were performed in RFurther information on research design is available in the Supplementary InformationPeer Review FileReporting SummaryDescription of Additional Supplementary FilesSupplementary Data 1Source Data


ICAM1 variant rs5491 (p.K56M) is common among Black individuals and has been associated with risk of heart failure with preserved ejection fraction (HFpEF). The pathways by which rs5491 leads to HFpEF are not known.The Among Black individuals within the Multi-Ethnic Study of Atherosclerosis, we evaluated associations of rs5491 with 3 inflammatory biomarkers .P = 0.02). Each additional rs5491 allele was associated with higher TNFR-1 , but not IL-6 . The association between rs5491 and HFpEF remained significant after adjustment for hsCRP.Among 1558 Black participants , each additional rs5491 allele was associated with higher hsCRP after covariate adjustment  is associated with higher hsCRP and higher TNFR-1, but not IL-6.In Black individuals, rs5491 ( Interceof HFpEF . The patof HFpEF –5. We ev2.https://biolincc.nhlbi.nih.gov/home). MESA study personnel recruited community-dwelling adults aged 45 to 84 years from 4 self-identified race/ethnic groups  across 6 US field centers. IRB approval was obtained at each site and all participants provided informed consent. Participants were free of cardiovascular disease at Exam 1. Genotyping in MESA was performed using the Affymetrix Genome-Wide SNP Array 6.0 ; rs5491 was imputed [p values <0.05 were considered significant. All analyses were performed in R version 4.0.2 .Details of the MESA study have been previously described . Data ar imputed . Inflamm imputed . Due to 3.P = 0.02; P = 0.02). Among 1507 individuals with IL-6 available, there was no association between rs5491 and IL-6 . The associations of rs5491 with higher hsCRP and TNFR-1 were consistent by gender . The association of rs5491 with hsCRP was consistent after further adjustment for income  and use of lipid-lowering medication . Consistency was noted in associations of rs5491 with TNFR-1 after further adjustment for income  and lipid-lowering medication . There were 42 HFpEF events over a median follow-up of 16.5 years. Each additional rs5491 allele was associated with incident HFpEF in the covariate-adjusted model without hsCRP , with similar results after further adjustment for hsCRP  and healthcare insurance .Of 6450 individuals in MESA who consented to genotyping and had adequate data availability, there were 1688 Black individuals. Among these 1688 Black individuals, 77 did not have rs5491 genotyping data and 53 were missing covariate data. The final analytic cohort was therefore 1558 participants. Among 1558 Black participants  with hsCRP available, the MAF of rs5941 was 21 %. After covariate adjustment, each additional rs5491 allele was associated with higher hsCRP  is associated with incident HFpEF, higher hsCRP, and higher TNFR-1, but not IL-6. The association between rs5491 and incident HFpEF persisted after adjustment for hsCRP. Serial hsCRP levels were not available in a sufficient number of participants for analysis and other inflammatory biomarkers, including interleukin-1β, were not available. hsCRP and TNFR-1 are considered biomarkers of inflammation that have been associated with HFpEF, and TNFR-1 may be more sensitive to HFpEF than IL-6 [In Black individuals, rs5491 (han IL-6 ,4. Based


The deep ocean, characterized by its immense depths and absence of global positioning system (GPS) functionality, presents considerable challenges for search and rescue missions. Inspired by the geolocalization capabilities of migratory marine animals, Bai et al. present a novel method for underwater geolocalization using the polarization patterns of light in the underwater environment. Emulating a sextant using these underwater polarization patterns, the study determines geolocation in underwater settings. Despite prior skepticism, even in low-visibility waters, these patterns, learned through a deep neural network, provide geolocation accuracies of 55 km at 8 m and 255 km at 50 m. This pioneering approach offers implications for search and rescue and hints at navigation mechanisms in marine animals. Our enduring fascination with the deep ocean has been further underscored by the recent incident involving the Ocean Gate submersible. This small underwater vehicle, specifically designed to transport tourists to depths of nearly 4 km for a glimpse of the remnants of the Titanic, vanished during its journey. In response, a multinational search and rescue mission was swiftly launched, with time being of the essence in the race to save the stranded passengers. The formidable challenges posed by search and rescue operations in the ocean became immediately apparent. The underwater environment is devoid of global positioning system (GPS) functionality, and the immense pressure exerts significant strain on the capabilities of submersible designs. Additionally, autonomous search robots capable of unrestricted exploration are absent. The entire search and rescue effort relied on tethered vehicles equipped with sonar, which posed limitations on the area that could be covered and hindered the urgency of the search operation.1. These polarization patterns, found in ocean waters at depths of up to 300 m, are primarily influenced by the positioning of the sun or moon on the horizon. When unpolarized light emanates from these celestial bodies, it penetrates the water and scatters upon encountering suspended particles. Consequently, the underwater polarization patterns serve as a direct indicator of the sun’s or moon’s celestial position. By incorporating precise time and date references, a unique position can be estimated.In the pursuit of untethered underwater geolocalization, Bai et al. propose a solution that leverages the polarization patterns of light observed in the underwater environmentThe proposed geolocalization method can be likened to a contemporary sextant, a historical navigational tool used for estimating solar heading and elevation angles in GPS-free environments both above water and in aerial navigation. To validate their approach, the authors amassed a vast dataset of underwater polarization videos captured at four distinct locations across the globe, encompassing coastal waters and low-visibility lakes Fig. .Fig. 1UsContrary to the prevailing belief in the research community that low-visibility waters lack discernible underwater polarization patterns or exhibit solely horizontal polarization, the authors successfully demonstrate that the polarization field surrounding the camera is heterogeneous and reliant on solar polarization. While conventional parametric models for single scattering fail to replicate the observed polarization signatures, a deep neural network proves adept at learning these underwater patterns and aids in estimating the position of the sun. By incorporating temporal information regarding the sun’s trajectory throughout the day, the authors employ a particle filter to determine the camera’s geolocation. This approach achieves a longitudinal accuracy of 55 km at depths of 8 m and 255 km at 50 m of depth.What is particularly remarkable about this study is that the proposed method also enables geolocalization during nighttime. This represents the first instance in literature where underwater polarization patterns have been recorded and utilized for geolocalization at night, resulting in an impressive accuracy of 1000 km. Notably, this geolocalization accuracy remains consistent regardless of the phase of the moon.This groundbreaking research on optical-based underwater geolocalization establishes a solid foundation for future advancements in this field. Enhancements to geolocalization accuracy can likely be achieved through the utilization of improved polarization sensors and more sophisticated machine learning algorithms, such as incorporating foundational models. Additionally, enabling geolocalization at greater depths will be crucial for expanding the range of potential applications.The ultimate question pertains to determining the fundamental limit of geolocalization accuracy and identifying the level of accuracy that suffices for underwater applications. Even with the current method, it can be employed for search and rescue missions, providing rough geolocation initially and subsequently facilitating a more precise search. Furthermore, this research opens up intriguing possibilities for marine animals with polarization vision to utilize similar mechanisms for geolocation and navigation.