Nonalcoholic fatty liver disease is associated with an increased cardiovascular disease (CVD) risk, although the exact mechanism(s) are less clear. Moreover, the relationship between newly redefined metabolic-associated fatty liver disease (MAFLD) and CVD risk has been poorly investigated. Data-driven machine learning (ML) techniques may be beneficial in discovering the most important risk factors for CVD in patients with MAFLD.In this observational study, the patients with MAFLD underwent subclinical atherosclerosis assessment and blood biochemical analysis. Patients were split into two groups based on the presence of CVD .The ML techniques were utilized to construct a model which could identify individuals with the highest risk of CVD. We exploited the multiple logistic regression classifier operating on the most discriminative patient’s parameters selected by univariate feature ranking or extracted using principal component analysis (PCA). Receiver operating characteristic (ROC) curves and area under the ROC curve (AUC) were calculated for the investigated classifiers, and the optimal cut-point values were extracted from the ROC curves using the Youden index, the closest to  criteria and the Index of Union methods.p < 0.0001), 0.86  and 0.87 , whereas the classifier fitted over 10 principal components extracted using PCA followed by the parallel analysis obtained AUC of 0.86 . The best model operating on 5 most discriminative features correctly identified 114/144 (79.17%) low-risk and 40/47 (85.11%) high-risk patients.In 191 patients with MAFLD , there were 47 (25%) patients who had the history of CVD. The most important clinical variables included hypercholesterolemia, the plaque scores, and duration of diabetes. The five, ten and fifteen most discriminative parameters extracted using univariate feature ranking and utilized to fit the ML models resulted in AUC of 0.84 (95% confidence interval [CI]: 0.77–0.90, A ML approach demonstrated high performance in identifying MAFLD patients with prevalent CVD based on the easy-to-obtain patient parameters. According to the statistics from the Global Burden of Disease study 2017, a significant number of all deaths globally (over 70%) is caused by noncommunicable diseases, and CVD accounts for more than 43% [For the last 40 years, NAFLD was characterized as an excessive hepatic lipid accumulation associated with metabolic abnormalities in the absence of significant alcohol consumption and other known causes of liver disease , 6. BecaIt is important to note that both European and American guidelines recommend to screen for CVD in people with NAFLD , 12 and Predicting CVD events within the next 10 years with the use of the traditional risk factors is commonly applied . HoweverMachine learning (ML) is one method of artificial intelligence in which computers utilize statistical approaches to effectively learn from data without being explicitly programmed to tackle a specific task. A variety of ML techniques have been increasingly applied in the medical field, including for the prediction of ventilator-associated pneumonia in critical care patients , prolongWe applied ML to determine the MAFLD patients who are at high CVD risk, and to better define the underlying risk factors in a data-driven manner. To the best of our knowledge, there have been no studies performed to date that analyzed the associations between MAFLD and CVD risk using ML methods.This single center, observational, study was performed in a cohort of MAFLD patients. Patients who had been previously diagnosed with fatty liver disease based on the liver ultrasonography were invited to participate in the study through the advertisement placed in the University Hospital in Zabrze and in the outpatient diabetology clinics and family doctor clinics in the Upper Silesia region in Poland. The eligibility criteria were simple, ie. patients at age  ≥ 18 years who fulfilled diagnostic criteria of MAFLD. The only exclusion criteria was the lack of written informed consent for the participation in the study. We recorded demographic and clinical data (Table 2 (kg/m2). Additionally, the waist-to-hip ratio (WHR) was obtained. The obesity was diagnosed when BMI ≥ 30 whereas the overweight was diagnosed when BMI ≥ 25 but < 30. The patients were considered to have T2DM based on a known history of this disease. Blood pressure was measured three times after 5 min of rest in a sitting position, at least 2 min apart, and the mean blood pressure of the three measurements was calculated. Arterial hypertension was defined as a systolic blood pressure ≥ 140 mmHg and/or a diastolic blood pressure ≥ 90 mmHg or previous treatment with antihypertensive medications. Hypercholesterolemia was recognized when a patient had this diagnosis present in the documented medical history and/or there was newly recognized plasma high density lipoprotein cholesterol (HDL-C) < 1.0 mmol/l for men and < 1.3 mmol/l for women and/or patient was on statin therapy. Hypertriglyceridemia was recognized when a patient had this diagnosis present in the documented medical history and/or there was newly recognized plasma triglyceride ≥ 1.7 mmol/l and/or patient was on fibrate therapy. The history of all concomitant diseases was obtained from the patient and confirmed on the basis of documented medical data. No self-reported diseases without medically confirmed diagnosis were recorded.Anthropometric parameters, including height (meters) and weight (kilograms), as well as waist and hip circumference were measured (meters) by standard methods, and the body mass index (BMI) was calculated as weight/height2 or at least two metabolic risk abnormalities, i.e., waist circumference ≥ 102 cm in men and ≥ 88 cm in women, blood pressure ≥ 130/85 mmHg or specific drug treatment, prediabetes, plasma triglycerides ≥ 1.7 mmol/l or specific drug treatment, plasma HDL-C < 1.0 mmol/l for men and < 1.3 mmol/l for women or specific drug treatment,  Homeostatic Model Assessment of Insulin Resistance (HOMA- IR) ≥ 2.5, serum C-reactive protein level > 2 mg/l.The patients were diagnosed with MAFLD  if thereLiver elastography was performed with the use of the Fibroscan 502TOUCH F611100049 device exploiting the XL 8 80,685 probe (2.5 Hz). The liver was tested after 6 h of fasting, and the test lasted from 5 to 10 min. In the patient lying in the dorsal position with the right arm extended, a gel-coated ultrasound probe was applied to the skin in the intercostal space above the right lobe of the liver. The time motion ultrasound image allows the operator to locate a fragment of the liver at least 6 cm thick and devoid of large vascular structures or ribs. The median and interquartile range (IQR) values of at least 10 successful liver stiffness measurements (LSM) and the controlled attenuation parameter (CAP), adequately defining fibrosis and steatosis, respectively, were calculated by the device. The results included the median and IQR of the CAP values (dB/m) and the median, IQR, IQR/median LSM (kPa), the success rate , the determination of the degree of steatosis (S0-S3) and liver fibrosis (F0-F4). The LSM classified as reliable are characterized by having all three of the following: ≥ 10 passed measurements, ≥ 60% success rate, and IQR/ median < 0.30.The ultrasound examination of the carotid arteries was performed using a high-resolution Doppler ultrasound with double imaging and color coding of the flow  exploiting the Esaote MyLab60 ultrasound equipment by the same certified neurologist. The examinations were done in the supine position, without any additional preparation, with a linear ultrasound head emitting an ultrasonic wave with a variable frequency of 4 MHz to 15 MHz. In the 2D presentation, the common carotid artery (CCA), the separation (bifurcation) of the common carotid artery into the internal carotid artery and the external and internal carotid artery (ICA), alongside the external carotid artery (ECA) were determined. Measurement of the intima-media complex (KIM) thickness and the assessment of atherosclerotic lesions in the carotid arteries were performed.For these measurements, piezoelectric mechanical transducers in the cervical, femoral and radial areas were used . The velocity of the carotid-femoral pulse wave (cfPWV) was used to assess the stiffness of the central artery and the velocity of the carotid-radial pulse wave (crPWV) was used to assess the stiffness of the peripheral arteries. With the Seca mod. 207 height meter, the right carotid-femoral and carotid-radial distances were measured. Blood pressure was measured in the supine position after at least 5 min of rest with the Microlife BP A1 sphygmomanometer immediately prior to the PWV assessment, and the mean of the three measurements on both arms was calculated and recorded. Derivative variables such as the central blood pressure, central pulse pressure and the gain index were analyzed, calculated by the integrated software on the basis of the carotid pulse waveform.2 was calculated according to the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) formula [Hemoglobin A1c (HbA1c) was determined using a high-performance liquid chromatography (HPLC) method, and the results were expressed in the National Glycohemoglobin Standardization Program/Diabetes Control and Complications trial units . Cholest formula . Blood c formula . Serum C formula . Alanine formula .p-values of the chi-square test statistics—here, the importance of a feature is quantified as To automatically identify the patients with a high risk of overt CVD, we investigated biochemical (8 parameters), demographical , clinicacant PCs . For eaccant PCs . For theThere were 301 potentially eligible patients identified, and from these, only 191 individuals  fulfilled the inclusion/exclusion criteria for the study  which are summarized in Table p < 0.0001) for the model fitted to 15 most discriminative features (Top-15), whereas the worst AUC was 0.84  for the classifier operating on 5 features with the highest importance scores (Top-5). The multiple regression model fitted over 10 PCs resulted in AUC of 0.86 –utilizing 10 most important predictors led to the same AUC of 0.86 . Once the optimal cut-point values have been elaborated for all models, the results were further analyzed—the performance  of the multiple regression classifiers for the cut-point values determined using the i) IoU, ii) Distance and iii) Youden methods are reported in Table We investigated the performance of the multiple regression classifier fitted to ten PCs extracted by PCA, as ten PCs were found significant in the parallel analysis. The ROC analysis Fig.  of the mIn Fig. i) we determined the most discriminative patient's parameters which can be used to build a ML model for identifying MAFLD patients with high CVD risk, (ii) we showed that using five interpretable and easy-to-obtain clinical parameters  is enough to elaborate well-generalizing logistic regression classifiers to the above-mentioned task; and (iii) we demonstrated better clinical utility of the developed ML models when compared to the “treat all” and “no treatment” strategies.In this study our principal findings are as follows:  could correctly identify 85.11% patients who present with CVD. While the highest score was seen for traditional risk factors, such as hypercholesterolemia and the duration of diabetes, there were also plaque related risk factors (both the plaque score and the plaque area) when taking into account top 5 most discriminative CVD features. The plaque score has been indeed identified as a factor associated with the long-term coronary artery disease risk in middle-aged asymptomatic individuals , 47. HypWhen looking closer at the top 10 features which could discriminate the vulnerable patients, these are again the traditional risk factors—like being diagnosed with T2DM and hypertension—but also the use of betablocker, with all the features being positively associated with CVD. An interesting parameter which was among the top 15 ones associated with CVD is the parameter related to the arterial stiffness which is already recognized as the one which improves cardiovascular event prediction , and thiThe results obtained for PCA indicated that the best-generalizing multiple regression classifiers were elaborated using interpretable features, and the models operating on the five most important features outperformed all other classifiers (exploiting more features and PCs) for the selected cut-point values, and correctly classified 80.63% of all patients (Table Most of the studies targeting the prediction of the CVD risk focus on the self-reported patient parameters which are not necessarily proved by medical documentation, hence may lead to biased outcomes. In our study, we have addressed this issue, and we analyzed a very well-defined population of patients whose concomitant diseases were medically documented. We used ML, which has been increasingly used to assess the risk of adverse outcomes in chronic disease states, outperforming simple clinical risk assessments , 47. MosWe are aware that there are important limitations of our study, which was a proof of concept for a wider program of work. This would include larger cohorts and further external validation, as well as prospective observations for all of them. Also, the patients were not asked whether they had lost their weight before participating in the study, which could explain the negative association of obesity with CVD. An important aspect of cardiovascular pharmacologic management is antiplatelet treatment. However, we were unable to gather reliable information related to this type of treatment in patients without CVD, hence we excluded this parameter from the analysis due to a large amount of missing data. Moreover we included patients with at least 50% of carotid artery stenosis qualifying them as those with overt CVD since 50% is a cut point of stroke related to large artery atherosclerosis –53. In tThe use of a ML approach demonstrated high performance in identifying MAFLD patients with high CVD risk based on the subset of the most discriminative, interpretable and easy-to-obtain patient's parameters. Our approach has the potential to facilitate timely diagnoses and management of prevalent CVD risk in patients who present with MAFLD in routine clinical practice.


Background and Objectives: Subclinical atherosclerosis, reflected by abnormal carotid intima–media thickness (cIMT), is pervasive among chronic kidney disease patients on chronic renal replacement therapy (RRT), being mostly influenced by uremia-related rather than traditional risk factors. Materials and Methods: In this pilot study, we measured circulating levels of Omentin-1, a recently discovered adipokine with strong anti-atherogenic properties, in a heterogeneous cohort of 77 asymptomatic RRT individuals  and in 30 age-matched controls. Results: Omentin-1 was increased in RRT individuals as compared with controls (p = 0.03). When stratifying for renal replacement modality, we found Ktx patients to have significantly lower Omentin-1 than HD patients (p = 0.01). Lower Omentin-1 levels were also found among RRT individuals with pathological cIMT . Our multivariate correlations analysis revealed Omentin-1 as the most robust independent predictor of carotid atherosclerosis , even more than total cholesterol, diastolic BP and age, and this adipokine was at the crossroad of a complex interplay with sustained inflammation (high CRP and ferritin) and hyperphosphatemia in predicting higher cIMT values. Conclusion: The findings reported extend to renal patients with advanced disease, with the possible involvement of Omentin-1 in the pathogenesis of atherosclerosis. This may set the stage for future interventional studies of Omentin-1 replacement to retard atherosclerosis progression, as it is currently being investigated in other disease settings. Subclinical atherosclerosis, generally associated with abnormal carotid intima–media thickness (cIMT) values, is pervasive among chronic kidney disease patients on chronic renal replacement therapy (RRT) due to advanced renal disease, and impacts their cardiovascular (CV) risk profile . In contOmentin-1 is a newly identified adipokine which is involved in various dysmetabolic conditions, including diabetes, metabolic syndrome and obesity, as well as in bone–mineral disorders and systemic inflammatory diseases . ImportaStarting from these premises, we thus designed a pilot observational study to cross-analyze circulating Omentin-1, clinical risk factors and the severity of carotid atherosclerosis in a cohort of asymptomatic individuals on chronic RRT.From a source population of 99 adult uremic patients periodically referred to the Nephrology and Dialysis unit of the University Hospital of Catanzaro, Italy, we recruited 77 individuals on chronic renal replacement therapy. Of these, 37 were patients on stable HD treatment (RRT-HD) by high-flux bicarbonate dialysis, following a standard of 3 times/week regimen, while 40 were chronic kidney transplant recipients (RRT-Ktx) who were followed in an outpatient setting. We excluded individuals with unstable clinical conditions, malignancy, liver, thyroid or infectious diseases, recent acute CV episodes, infections, cancer, recent transplantation or dialysis onset (<6 months). The study was approved by the Local University Institutional Review Board, and all participating subjects provided written informed consent. Omentin-1 was measured in the blood by a commercially available ELISA kit , together with standard biochemical parameters. Blood pressure was calculated as the average of three consecutive measurements. Clinical, demographic and anthropometric data were recorded by using a standardized electronic case report form. Carotid intima–media thickness (cIMT) was measured in the posterior wall of both carotid arteries by mode B ultrasound and computed by measuring the thickness of the innermost two layers of intima–media, 5 mm before the bifurcation of the common carotid artery. Pathological (high) cIMT was assumed for mean (right/left) values > 0.9 mm and/or a unilateral cIMT over the 75th percentile of the established age- and sex-dependent reference ranges . All clit-test for normally distributed values, the Mann–Whitney U test for non-parametric values and the chi-square, followed by a Fisher’s exact test for frequency distributions. The Pearson (R) and the Spearman (Rho) correlation coefficients were employed to identify the univariate correlates of cIMT. Skewed variables were preliminarily log-transformed to approximate normal distributions. Various multiple regression models considering cIMT as the dependent variable were built, including univariate correlates in different combinations. All results were considered significant for p-values ≤ 0.05.The statistical analysis was performed by using the SPSS package  and the GraphPad prism package . Differences between groups were assessed by the unpaired 2. Omentin-1 levels were higher in the whole RRT cohort as compared with healthy controls  and RRT-Ktx (p = 0.01) (The main characteristics of the study population are summarized in  = 0.01) B.p = 0.001) and displayed higher phosphate (p = 0.03), cholesterol (p = 0.001), hs-CRP (p = 0.001) and ferritin (p = 0.03) levels, as well as lower diastolic BP (p = 0.001) and higher pulse pressure (p = 0.009). Marginal, although not statistically significant, differences between the two subpopulations were noticed with respect to the prevalence of diabetes, glycemia, potassium, albumin, LDL cholesterol and platelet levels . Omentin-1 was significantly lower in RRT individuals with pathological cIMT as compared to others , serum phosphate , total cholesterol , hs-CRP  and ferritin  as directly associated with cIMT values, while inverse correlations were found with diastolic BP  and Omentin-1 . Of note, during the exploratory subgroup analyses, no correlations were found between eGFR and Omentin-1 levels in Ktx.The mean cIMT in the whole study cohort was 0.78 ± 0.32 mm. On average, cIMT values were abnormal in 36 patients (46.7%). Such individuals were older (p = 0.03). Significant associations between cIMT and inflammatory indexes  re-emerged after excluding Omentin-1 from the model (Model 2), while phosphate remained an independent predictor of cIMT only in a model simultaneously excluding Omentin-1 and inflammation (Model 4). Data from multivariate models are detailed in In a fully adjusted multivariable model (Model 1) including all the univariate significant predictors of cIMT, the associations between the severity of carotid atherosclerosis and, respectively, Omentin-1, total cholesterol, diastolic BP and age remained significant, while those with ferritin, serum phosphate and hs-CRP were lost. Of note, in this model, Omentin-1 ranked as the strongest independent predictor of cIMT  and hyperphosphatemia remained significantly associated with cIMT severity only if Omentin-1 was not introduced in the model.Persistent inflammation is a renowned risk factor for progressive atherosclerosis in ESKD, as it elicits endothelial dysfunction, abnormal wall remodeling and microvascular damage . SimilarIn light of these observations, Omentin-1 might reasonably be placed in the casual pathways linking, respectively, inflammation and hyperphosphatemia to the severity of carotid atherosclerosis in patients with chronic kidney disease needing chronic renal replacement therapy. In this view, this adipokine would represent one missing link of the pro-atherogenic effects of altered mineral balance and chronic inflammation, thereby representing a potential therapeutic target for replacement therapy, as it is currently being investigated in other disease settings .


Despite a prospective consecutive evaluation of a large homogenous cohort  in the index study, certain points require authors’ comments and clarification to enhance the lucidity of their findings.Dear Editor, I read with great interest the Carrascal et al.-4. Moreover, the authors also fail to delineate their institutional perioperative glucose management protocol.While preoperative diabetes mellitus did not emerge as a baseline risk-predictor of CS-AKI , the lack of elucidation of perioperative glucose homeostasis in the present study captivates attention, particularly when poor glucose control has been linked to an enhanced propensity for CS-AKI owing to an augmented oxidative stress, endothelial dysfunction and systemic inflammatory response aimed at developing the ‘Acute Kidney Injury in Cardiac Surgery’ (AKICS) score, which adequately outline the superiority of postoperative CVP and low cardiac output as independent risk factors in predicting CS-AKI over other hemodynamic variables. Across the cardiac surgical population, the risk of AKI doubles once the postoperative CVP reaches a threshold value of 14 mmHg. Ahead of the fact that estimated CVP at 6 h postoperatively has been found to be significantly associated with CS-AKI in the non-congested cardiac surgical subset, possible links should definitely not be overlooked in valvular heart disease patients included in the present study who can be particularly prone to postoperative systemic venous congestion.Talking of the hemodynamic predisposition to CS-AKI, there are additional caveats that merit elaboration. It is noteworthy that systemic venous hypertension has been demonstrated to be associated with poor renal outcomes in cardiac surgical patients manifesting as a congestive renal failure, as an elevated central venous pressure (CVP) is potentially transmitted backwards, reflecting as an accentuated renal venous pressure (RVP) which reduces effective renal perfusion pressure , accelerating AKI progression. The aforementioned is heralded by the results of the study by Palomba et al.Lastly, the lack of comparative account for inotropes-vasopressors in the AKI and non-AKI groups or a standardized inotrope-vasopressor study protocol requires consideration while interpreting the findings.


To assess retinal and choroidal thickness changes in chronic kidney disease (CKD) patients using spectral domain optical coherence tomography (SD-OCT).CKD is a devastating health trouble. The eye and the kidney share similar structural and genetic pathways, so that kidney disease and ocular disease may be closely linked. OCT is a precise, fast method for high-definition scanning of the retina and choroid.2 group 2: CKD stage 3, GFR 30–59 ml/min/1.73m2 and group 3: CKD stage 4–5, eGFR < 29 ml/min/1.73m2. All patients underwent full ophthalmologic examination followed by OCT assessment of retinal, retinal nerve fiber layer (RNFL) and choroidal thickness.A cross sectional study was conducted at Menoufia University Hospital ophthalmology department on 144 eyes of 72 CKD patients divided into 3 groups according to the stage of CKD as follows: group 1: CKD stage 1–2, with Glomerular Filtration Rate (GFR) > 60 ml/min/1.73mRetinal and choroidal thickness were reduced in group 2 (CKD stage 3) and group 3 (CKD stage 4–5) compared with group 1 (CKD stage 1–2). The reduction was more severe in group 3 than group 2. RNFL thickness did not differ between groups. A thinner retina and choroid were associated with an elevated serum C-reactive protein (CRP) concentration, and greater degrees of proteinuria.Chorioretinal thinning in CKD is associated with a lower eGFR, a higher CRP, and greater proteinuria. Further studies, in a large scale of patients, are needed to detect whether these eye changes reflect the natural history of CKD. Stage 2 is characterized by a mild reduction in GFR (60–89 ml/min/1.73 m2), while stage 3 is characterized by a moderate reduction in GFR (30–59 ml/min/1.73 m2). Stage 4 is characterized by a severe reduction in GFR (15–29 ml/min/1.73 m2), and preparation for kidney replacement therapy is necessary. Stage 5, also known as end-stage kidney disease, is characterized by established kidney failure, requiring permanent kidney replacement therapy [Chronic kidney disease (CKD) is a significant health concern that affects a large portion of the population, leading to a considerable economic burden and reduced quality of life . The sevCKD not only affects the kidneys but also other organs in the body. The kidney and eye are strikingly similar in their developmental and pathogenic pathways. The renal podocyte, a stromal cell that supports vasculature and serves as a progenitor of interstitial myofibroblasts in renal fibrogenesis, is structurally and functionally similar to the vascular pericyte in the eye. As a result, diseases that affect one may also affect the other. Podocytes interact with endothelial cells through distinct signaling pathways, and their activation and detachment from capillaries after acute or chronic kidney injury may be critical for driving CKD progression .Retinal and choroidal changes have been observed in patients with CKD. Fundus examination is a valuable tool for visualizing the chorioretinal microvasculature that may be affected in CKD . OpticalThe aim of this study is to report retinal and choroidal thickness in association with renal function in patients with CKD. Furthermore, the study will be valuable for identifying patients at risk for developing CKD and for monitoring the progression of the disease. In so doing, we aim to provide a deeper understanding of the relationship between CKD and chorioretinal changes, paving the way for new strategies for early diagnosis and treatment of this prevalent disease.This cross-sectional study involved 144 eyes of 72 CKD patients who are over 18 years of age. Exclusion criteria include eyes with previous laser or surgical treatment, high myopia, corneal diseases, lens, and vitreous opacities that prevent fundus visualization, uveitis, glaucoma or other retinal diseases, and diabetes mellitus. The study was conducted at the department of Ophthalmology, Menoufia University Hospital from November 2020 to March 2021. All study procedures were carried out and approved by the Ethical Committee of Menoufia Faculty of Medicine and in accordance with the declaration of Helsinki. Written informed consent was obtained from each patient before his or her enrollment in the study.The study included a full systemic and ocular examinations for each subject. Ocular examination included best-corrected visual acuity , anterior segment examination using slit lamp biomicroscopy, intraocular pressure (IOP) by Goldman applanation tonometry, and fundus examination using 90-diopters lens. Renal function is assessed through serum creatinine values, estimated glomerular filtration rate (eGFR) calculated using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation, mean arterial blood pressure, body mass index (BMI), complete blood count, random blood sugar, traditional C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), serum albumin, and urine analysis.Retinal and choroidal thicknesses were obtained using SD-OCT  with EDI mode activated. OCT was scheduled to be performed in the morning (around 10–11 a.m) to minimize any potential diurnal variations in the measured choroidal thicknesses across the subjects. Tropicamide 1% eye drops achieved pupillary dilation in all patients. For patients on hemodialysis, OCT was obtained 24 hours after hemodialysis to allow recovery from post-dialysis fatigue and blood volume changes.A macular cube scan was performed which consisted of 61 horizontal B scans with a 120 μm separation covering the entire macular area. Retinal thickness measurements were conducted using the protocol from the Early Treatment Diabetic Retinopathy study (ETDRS). The ETDRS map divides the macula into 9 zones, with a circular grid centered on the fovea and consisting of 3 concentric rings of diameters 1, 3 and 6 mm respectively. These rings are further divided into quadrants: temporal, nasal, superior and inferior. The retinal thickness was determined as the area between the internal limiting membrane (ILM) and the inner boundary of the retinal pigment epithelium. (RPE)  curve of RNFL thickness . Qualitative data were described using number and percent. The Kolmogorov-Smirnov test was used to verify the normality of distribution. Quantitative data were described using range (minimum and maximum), mean, standard deviation (SD), median, and interquartile range (IQR). Student’s t-test and Analysis of Variance (ANOVA) were used to compare the mean values of the study groups. Correlations between different parameters were assessed using Pearson’s correlation. This study included 144 eyes from 72 patients, with a gender breakdown of 53 male and 19 female participants, and an age range of 18 to 68 years old. The diagnosis of the cause of CKD was identified based on a combination of medical history, clinical examination, and various investigations including laboratory tests, renal ultrasound, and renal biopsy. The study cohort was made up of 28 patients with hypertensive nephrosclerosis, 19 patients with chronic glomerulonephritis, 9 patients with obstructive uropathy, seven patients with lupus nephritis, three patients with adult polycystic kidney disease, two patients with myeloma kidney, two patients with immunoglobulin-A (Ig-A) nephropathy, and two patients with an unknown etiology of CKD.The mean IOP in the study participants was 16.7 mmHg, while the mean LogMAR value of BCVA was 0.13 ± 0.13. Approximately 38.9% of the participants were taking antihypertensive medication. A positive CRP was found in 33.3% of the participants, with a mean value of 35.75 ± 28.77 and a mean ESR level of 59.69 ± 34.72. The mean serum creatinine level was 3.86 ± 2.17 and the mean serum albumin level was 2.99 ± 0.85. The urine analysis showed albuminuria in 62.5% of the patients, with + 1 albuminuria in 15.3%, + 2 in 20.8%, and + 3 in 26.4%. The mean eGFR was 31.04 ± 24.83, and the patients were divided into three groups based on the stage of CKD: group 1 (CKD stage 1–2) included 11 patients, group 2 (CKD stage 3) included 19 patients, and group 3 (CKD stage 4–5) included 42 patients as shown in Table p = 0.015), inner temporal segment (p = 0.023), outer temporal segment (p = 0.046) and inner nasal segments (p < 0.001). No significant differences in retinal thickness were observed between CKD categories for the superior, inferior, and outer nasal segments. Additionally, individuals in earlier stage CKD (stage 3) also showed lower retinal thickness in the central/foveal segment (p = 0.022) and outer temporal segment (p = 0.027). Table Regarding retinal thickness, compared to those with earlier stages of CKD stages 1–2), individuals with advanced stages of CKD (stages 4–5) had significantly lower mean retinal thickness values the central/foveal segment , outer superior segment (P = 0.005) and outer temporal segment (P < 0.001). This suggests that as CRP levels increase, retinal thickness in these areas decreases  and inner and outer inferior segments (P = 0.027 and 0.004 respectively)  status of the patients in all ETDRS regions. However, a negative correlation was observed between retinal thickness and CRP in certain areas of the eye, including the central/foveal segment P = 0.03, outer sp < 0.001), superior segment (p < 0.001), inferior segment (p < 0.001), inner nasal segment (p = 0.016) and inner temporal segment (p = 0.034) compared to earlier stages of CKD (stages 1–2). No significant differences in choroidal thickness were observed between CKD categories only for outer nasal and outer temporal segments. Additionally, individuals in earlier stage CKD (stage 3) also showed lower choroidal thickness in the central/foveal segment (p < 0.001), superior segment (p < 0.001), inferior segment (p < 0.001) and inner temporal segment (p = 0.045) as shown in Table For choroidal thickness, we found that advanced stages of CKD (stages 4–5) had significantly lower mean choroidal thickness in the central/foveal segment (t p = 0.04 comparep = 0.003). A negative correlation was also observed between choroidal thickness and CRP in the superior segment (p = 0.012 for inner superior segment and < 0.001 for outer superior segment), inferior segment (p < 0.001 for inner inferior segment and 0.025 for outer inferior segment) and inner temporal segment (p = 0.023)  only in the outer inferior segment p = 0.00. A negatIn contrast to retinal and choroidal thicknesses, RNFL thickness was not significantly different among the three groups studied in any ETDRS segment as shown in Table In our study, we examined the relationship between thickness of the chorioretinal layers measured using SD-OCT and the stages CKD in 72 patients with 144 eyes. We found that thinner retina and choroid were associated with CKD stage 3 and even more thinning in CKD stage 4–5. There was no association found between retinal and choroidal thickness and hypertension. However, we did observe associations between CRP and albuminuria, which were inversely correlated with choroidal thickness in CKD and were independent predictors of thickness. These findings may be explained by the role of inflammation in the development of both vascular and renal disease.In this study, it was found that the choroidal thinning is more pronounced in advanced CKD. This thinning may be a reflection of a direct microvascular insult. As the vessels of the choroid supply the outer retinal layers and the RPE, it is possible that retinal abnormalities may occur as a result of choroidal pathology. The choroid plays a vital role in retinal function, as it nourishes the outer half of the retina. Abnormal choroidal circulation can lead to retinal photoreceptor dysfunction and death. Many diseases such as central serous retinopathy (CSR), age-related macular degeneration (AMD), pathological myopia and Vogt-Koyanagi-Harada (VKH) disease are related to choroidal changes. Identifying choroidal changes accurately will enable proper assessment of many posterior segment diseases. However, unlike the retina, choroidal structures do not have distinct, ordered layers and lack contrasting reflective properties, making it difficult to examine the choroid in as much detail as the retina . AdditioMaria Vadalà and colleagues  conducteIn end stage renal disease, Ali Kal and colleagues  found thIn our study, we found that there was no difference in Retinal nerve fiber layer (RNFL) thickness between the groups studied. This is in agreement with the findings of Craig Balmforth and colleagues , who conThere were several limitations in this study. First, the medications taken by our patients, such as angiotensin-converting enzyme inhibitors, β-blockers, and statins may have had effects on the OCT parameters studied. However, all patients were stabilized on their therapies and this was an unavoidable limitation of such studies. Secondly, the lack of any angiographic examination which can study in deep the retinal and choroidal vascular structure like indocyanine green (ICG), fluorescein fundus angiography (FFA) and optical coherence tomography angiography (OCTA) which can study in deep the retinal and choroidal vascular structure. Also, the cross-sectional nature of this study does not allow for the determination of causality of association. Saying that, the clinical relevance of these findings requires further consideration through longitudinal evaluation of changes in retinal thickness with declining kidney function with age. Lastly, the specificity of the observed associations with the underlying cause of CKD was not examined. Longitudinal studies are needed to establish the chronological correlation with CKD severity. As well, focused studies on CKD subgroups based on the underlying pathology.This study revealed that chorioretinal thinning in CKD is associated with a lower eGFR, a higher serum CRP, and greater proteinuria. These findings support the potential use of chorioretinal thickness profile as a biomarker for CKD progression.


Diabetic kidney disease (DKD) represents a heavy burden in type 2 diabetes mellitus (T2DM). Ferroptosis plays an important role in DKD, and it thus provides new perspectives to pursue more related biomarkers to assess the disease severity and prognosis. Glutathione peroxidase 4 (GPX4) is the mainstay in regulating ferroptosis. The current study investigated the predictive value of kidney GPX4 expression level in DKD progression.  We measured GPX4 levels in kidney paraffin sections of 85 biopsy-proven DKD patients by immunohistochemistry staining. The associations between the GPX4 level and clinicopathological parameters as well as renal outcomes were analyzed. r = −0.42, p < 0.001), urinary albumin-to-creatinine ratio (uACR) , serum creatinine (Scr) , estimated glomerular filtration rate (eGFR) , and the percentage of sclerosed glomeruli  in renal specimens. During follow-up, the GPX4 level positively correlated with eGFR slope , and GPX4-low patients showed a significantly higher probability of developing end-stage kidney disease (ESKD) compared with GPX4-high patients (p < 0.01). Moreover, after adjusting for other potential predictors, the GPX4 level was still an independent predictor of developing ESKD .  GPX4 is mainly expressed in kidney tubulointerstitium, especially in tubular epithelial cells of DKD patients. The GPX4 expression level was significantly lower in DKD patients than healthy controls. Besides, GPX4 level significantly correlated with proteinuria ( Kidney tubulointerstitial GPX4 expression level was associated with the disease severity and progression of DKD. The prevalence of diabetes mellitus (DM) is increasing steadily all over the world, and type 2 diabetes mellitus (T2DM) accounts for 90% of all DM patients , 2. DiabOxidative stress is one of the key aspects in the pathogenesis of DKD. Elevated prooxidant enzyme-induced reactive oxygen species (ROS) production together with insufficient antioxidants results in oxidative stress in DKD , 17. Lipn = 14) were obtained from the healthy kidney poles of individuals receiving tumor nephrectomies. These healthy controls did not have a history of hypertension, diabetes, cardiovascular diseases, or renal diseases. All kidney samples of diabetic patients with MCD and without DKD and healthy controls were confirmed by pathological examinations including direct immunofluorescence, light microscopy, and electron microscopy. The investigation was conducted according to the Declaration of Helsinki and was approved by the Ethics Committee of Peking University First Hospital (2017-1280). Written informed consent was obtained from each participant.A total of 85 patients with renal biopsy-proven DKD according to the criteria proposed by Renal Pathology Society  from JanClinical and laboratory data of these patients at the time of renal biopsy and follow-up were systematically recorded, including age, sex, diabetes history, proteinuria, urinary albumin-to-creatinine ratio (uACR), blood urea nitrogen (BUN), serum creatinine (Scr), eGFR, fasting blood glucose (FBG), hemoglobin A1c (HbA1c), hemoglobin (Hb), serum albumin, triglyceride (TG), high-density lipoprotein-cholesterol (HDL-C), and low-density lipoprotein-cholesterol (LDL-C). The eGFR was calculated using the CKD-EPI equation . The eGFRenal specimens were evaluated using direct immunofluorescence, light microscopy, and electron microscopy. Biopsies were scored independently by two experienced pathologists, respectively. Diabetic glomerulopathy was classified as class I through IV according to the criteria proposed by Renal Pathology Society . IFTA scFormalin-fixed paraffin-embedded kidney tissue sections were blocked by 3% bovine serum albumin after deparaffinization, rehydration, and heat-induced epitope retrieval and were stained with anti-GPX4 antibody  overnight at 4°C. Subsequently, an HRP-DAB system  was used for color development. Twenty images were randomly taken for each section under 400x magnification in a blind fashion and quantified by Image-Pro Plus software V.6.0 .α8  antibodies overnight at 4°C, respectively. Then, sections were incubated with Cy3-conjugated  or FITC-conjugated  secondary antibodies and stained nucleus with DAPI . Images were taken under 400x magnification using Leica DM2500 microscope .Formalin-fixed paraffin-embedded kidney tissue sections were blocked after heat-induced epitope retrieval and stained with anti-GPX4 , anti-AQP1 , anti-Calbindin D28k , anti-CD31 , anti-synaptopodin , and anti-integrin 2) leading to the need for a regular course of long-term dialysis or a kidney transplant to maintain life [ESKD, defined as an irreversible decline of kidney function  and clinicopathological parameters.Continuous data were presented as mean ± SD or median and interquartile range (IQR), as appropriate. Categorical data were described by absolute frequencies and percentages. Continuous clinical data were compared using Student's p value less than 0.05 was considered statistically significant .The Kaplan-Meier analysis was used to assess the association between IOD/area and outcomes. The Cox proportional hazard regression was employed to evaluate the association between potential risk variables and outcomes. The analysis was performed with SPSS statistical software package  as well as survival, rms, timeROC, and survminer package in R studio (based on R x64 4.0.3). A μmol/L and 37.2  mL/min/1.73 m2, respectively. As for the pathological type, 5/85 (5.9%), 14/84 (16.5%), 60/85 (70.6%), and 6/85 (7.0%) of patients were categorized as class I, class II, class III, and class IV according to diabetic glomerulopathy, respectively, and 20/85 (23.5%), 24/85 (28.2%), and 41/85 (48.3%) of patients got IFTA scores as 1, 2, and 3, respectively. The detailed general data are listed in Among the 85 DKD patients, 64 were male and 21 were female, with an age of 48.6 ± 12.6 years at renal biopsy. The median duration of diabetes was 120  months. The proteinuria and uACR of these patients were 4.0  g/24 h and 3223.6  mg/g, respectively. The Scr and eGFR of these patients were 174.3  p < 0.001) and diabetic patients with MCD and without DKD   and negatively correlated with proteinuria , uACR , Scr , and the percentage of sclerosed glomeruli in renal specimens   at kidney biopsy, which represents glomerular hyperfiltration of early DKD. The GPX4 level in the kidney was significantly higher in patients with higher eGFR (n = 9) than those patients with eGFR ≤ 90 mL/min/1.73 m2 (n = 76) (p < 0.01)  Figure . This wa) Figure  and did ) Figure .2/year. The eGFR slope was significantly higher in GPX4-high group than that in GPX4-low group  vs. -6.0  mL/min/1.73 m2/year, p < 0.001); i.e., eGFR decreased more rapidly in GPX4-low group .To investigate the association between the GPX4 level and renal outcomes, we performed time-dependent receiver operator curves  (p < 0.05) (p < 0.05)  months, 50/85 (58.8%) patients progressed to ESKD. The Kaplan-Meier analysis showed that compared with patients in the GPX4-high group, those in the GPX4-low group had a significantly higher probability of developing ESKD  . In the  < 0.05) . Nomogra < 0.05) , and the < 0.05) . In addi < 0.05) .p < 0.05)  to rule out the disturbance by the three-year time span. There are 39/85 endpoint events after a three-year follow-up. It was found that GPX4 level was still independently associated with developing ESKD  Table . This waA high glucose transport state in DKD exacerbates ROS production and results in oxidative stress , 40. PreIn the current study, we found GPX4 mainly expressed in tubulointerstitium, especially in tubular epithelial cells, in renal specimens of DKD patients. Previous studies in animal models found that ferroptosis occurred in renal tubules in diabetes –24. SincConsistent with our study, a previous study found that GPX4 mRNA level in kidney biopsy samples of diabetic patients was significantly lower than in nondiabetic patients, and tubular injury was significantly aggravated in GPX4-deficient mice, suggesting that GPX4 has a renal protective effect, especially in tubular cells . A functNuclear factor erythroid 2-related factor 2 (NRF2) was a transcription factor of various antioxidant genes including GPX4, and it is known to suppress oxidative stress and ferroptosis –57. SomeThere were some limitations in our study. The sample size of the current study was limited, and most patients enrolled in this study were advanced DKD. Moreover, the pathogenic mechanism of DKD was complicated, and whether these results could be extrapolated to a broader patient population remains further investigation.In conclusion, the current study showed that a lower GPX4 level was associated with more severe kidney disease and a higher risk of progression to ESKD in patients with DKD.


However, while tacrolimus (TAC) is the cornerstone immunosuppressant inhibiting adaptive alloimmunity, its blood exposure is directly impacted by different single-nucleotide polymorphisms (SNPs) in CYP3A TAC-metabolizing enzymes. Here, we investigated how functional TAC-CYP3A genetic variants (CYP3A4*22/CYP3A5*3) influence the main baseline clinical and immunological risk factors of biopsy-proven acute rejection (BPAR) by means of preformed donor-specific antibodies (DSAs) and donor-specific alloreactive T cells (DSTs) in a large European cohort of 447 kidney transplants receiving TAC-based immunosuppression. A total of 70 (15.7%) patients developed BPAR. Preformed DSAs and DSTs were observed in 12 (2.7%) and 227 (50.8%) patients, respectively. According to the different CYP3A4*22 and CYP3A5*3 functional allele variants, we found 4 differential new clusters impacting fasting TAC exposure after transplantation; 7 (1.6%) were classified as high metabolizers 1 (HM1), 71 (15.9%) as HM2, 324 (72.5%) as intermediate (IM), and 45 (10.1%) as poor metabolizers (PM1). HM1/2 showed significantly lower TAC trough levels and higher dose requirements than IM and PM (p < 0.001) and more frequently showed TAC underexposure (<5 ng/ml). Multivariate Cox regression analyses revealed that CYP3A HM1 and IM pharmacogenetic phenotypes (hazard ratio (HR) 12.566, 95% CI 1.99–79.36, p = 0.007, and HR 4.532, 95% CI 1.10–18.60, p = 0.036, respectively), preformed DSTs , DSAs , and delayed graft function (DGF)  independently predicted BPAR. Notably, a significant interaction between T-cell depletion and TAC underexposure was observed, showing a reduction of the BPAR risk . Such variables except for DSAs displayed a higher predictive risk for the development of T cell-mediated rejection (TCMR). Refinement of pretransplant monitoring by incorporating TAC CYP3A SNPs with preformed DSAs as well as DSTs may improve current rejection-risk stratification and help induction treatment decision-making.Achieving fast immunosuppression blood exposure after kidney transplantation is key to abrogating both preformed and  Alloreactive immune memory is the hallmark of adaptive immunity and is a key factor driving acute kidney transplant rejection and accelerated graft loss –3. Indeeex vivo studies have shown that calcineurin inhibitors, and especially tacrolimus (TAC), can more efficiently inhibit these cells  have significantly higher dose requirements to achieve similar TAC trough levels (C0) than patients homozygous for the CYP3A5*3 allele (CYP3A5 non-expressers)  , 24. Simgenotype , 26. Nevgenotype , 28. Of Therefore, since kidney transplant candidates with preformed anti-donor alloimmune memory might need a particularly fast exposure to TAC blood concentrations to effectively inhibit anti-donor recall immune responses, particularly in the early posttransplant period, we hypothesized that the impact of pretransplant DSTs and DSAs, together with other main baseline clinical variables and the different CYP3A TAC phenotypes, could significantly modulate the relative risk and types of BPAR. Thus, the primary endpoint of the study was to evaluate the value of preformed alloimmune memory (both DSAs and DSTs) together with different CYP3A TAC pharmacogenetic phenotypes to discriminate patients at risk of developing acute rejection after kidney transplantation.A total of 738 consecutive, adult, single-kidney-transplant recipients from four different European kidney transplant centers  in Prague, Czech Republic), who were transplanted between June 2012 and December 2017, were retrospectively analyzed on the basis of the availability of both donor and recipient pretransplant peripheral blood mononuclear cells (PBMCs) and recipient plasma samples to assess DSTs, DSAs, and the CYP3A genotypes for their value predicting acute rejection after transplantation. Furthermore, the main baseline and clinical variables such as the use of T cell-depleting agents, development of delayed graft function (DGF), and importantly distinct TAC blood exposures were also assessed in this study to evaluate their impact on modulating these pretransplant immunologic and pharmacogenetic variables facilitating the risk of acute rejection. As illustrated in All patients of the study received an immediate  or extended-release  TAC formulation, mycophenolate mofetil (MMF), 1 g bid, during the first 2 weeks and subsequently tapered to 500 mg bid, and steroids with oral prednisone at 5 mg/day, after the first month as maintenance immunosuppression. Either basiliximab (72.3%) or thymoglobulin (rATG) (27.7%) was given as induction therapy as per practice in each center. Initial TAC doses were adjusted by the respective patient’s body weight and given at 0.05 mg/kg bid for the immediate release (TAC-IR) and 0.12 mg/kg/day for the extended release (TAC-ER), to achieve TAC trough levels of 6–10 ng/ml during the first 6 months and 5–8 ng/ml thereafter. TAC trough levels were measured before the patient’s administration of the morning dose, on days 7, 14, 30, and 90 and at 180 days after transplantation. TAC intra-patient variability (IPV) was estimated through the coefficient of variation (SD/mean × 100).(*1/*22 or *22/*22) for CYP3A4 or they were *3/*3 genotype for CYP3A5 or as high metabolizers (HM) if they expressed the *1/*1 genotype for CYP3A4 or *1 carrier (*1/*3 or *1/*1) for CYP3A5. Furthermore, patients were clustered into different groups according to both CYP3A4*22 and CYP3A5*3 allelic status, specifically considering the functional *1 allele: high CYP3A metabolizers 1 (HM1) (CYP3A4*1/*1 and CYP3A5*1/*1), high metabolizers 2 (HM2) (either CYP3A4*1/*1 and CYP3A5*1 carriers or CYP3A4*1 carriers and CYP3A5*1/*1), intermediate (IM) (CYP3A4*1/*1 with CYP3A5*3/*3 or CYP3A4*22/*22 with CYP3A5*1/*1 or CYP3A4*22 carriers with CYP3A5*1 carriers), poor 1 (PM1) (CYP3A4*22 carriers with CYP3A5*3/*3 or CYP3A4*22/*22 with CYP3A5*1 carriers), and poor 2 (PM2) (CYP3A4*22/*22 with CYP3A5*3/*3). In the study cohort, there were no CYP3A4*22/*22 with CYP3A5*1/*1 patients (one of the combinations for IM) nor CYP3A4*22/*22 with CYP3A5*3/*3 (PM2).Genomic DNA was extracted from a peripheral whole-blood sample using the Wizard Genomic DNA Purification Kit  and was stored at −80°C. For the genotyping, allelic discrimination reactions were performed using specific TaqMan  genotyping assays on an ABI PRISM 7900 Fast Real-Time PCR Systems (Applied Biosystems) using 20 ng of genomic DNA and according to the manufacturer’s instructions. According to the functional CYP3A variants, patients were classified as poor TAC metabolizers (PM) if they were *22 carriers Peripheral blood samples were obtained in heparinized tubes from renal transplant recipients before kidney transplantation. Donor cells were obtained from donor spleens or PBMCs in deceased and living donors. PBMCs and splenocytes were isolated by standard Ficoll density gradient centrifugation, were frozen in liquid nitrogen, and subsequently used for the IFN-γ Enzyme-linked Immunosorbent Spot (ELISPOT) assay.Pretransplant humoral and cellular donor-specific alloimmune memory was assessed in all patients of the study in peripheral blood by means of serum DSAs and circulating donor-specific memory/effector T cells (DSTs), respectively. While pretransplant DSA data were available to the transplant physicians prior to transplantation, all data related to pretransplant DSTs were blinded and thus did not influence the type of immunosuppressive therapy used. Pretransplant DSAs were not detected at the time of transplantation and were confirmed later; therefore, these patients did not receive any desensitizing treatment before transplantation.Screening for circulating anti-HLA class I and II antibodies was carried out in serum samples before transplantation in all patients and at the time of a kidney transplant biopsy and was determined using single-antigen flow beads assays on a Luminex platform . Patients previously only screened for anti-HLA antibodies with the screening assay , were re-assessed for single-antigen flow beads assays to rule out the presence of donor (HLA)-specific antibodies (DSAs). All beads showing a normalized mean fluorescence intensity (MFI) >1,500 were considered positive if [MFI/(MFI lowest bead)] > 5.5 responder cells were placed in triplicate wells with 3 × 105 CD2-depleted splenocytes  or CD3-depleted living-donor PBMCs . Recipient cells were stimulated with complete medium alone , antibiotics, and l-glutamine) and Pokeweed  as negative and positive controls, respectively. Results were given as frequencies of IFN-γ-producing donor-specific T cells/3 × 105 PBMCs, subtracting responses of the negative control wells. As previously reported, 25 or higher IFN-γ-producing donor-specific T cells/3 × 105 PBMCs was considered a positive test  were monitored by an IFN-γ ELISPOT assay following recently described standard operating procedures , 30. BriRenal allograft biopsies were performed in patients undergoing acute clinical graft dysfunction, such as a change in serum creatinine levels, decreasing estimated glomerular filtration rate (eGFR), and the appearance of proteinuria and/or hematuria. All renal biopsies were blindly analyzed following the Banff 2013 score classification  and retr2-test for categorical variables and the one-way ANOVA analysis or Student’s t-test for normally distributed data for quantitative variables.All data are presented as mean ± SD or median and interquartile range. Groups were compared using the XCox regression analyses were performed to determine the significant univariate associations of pretransplantation factors with the risk of BPAR. An interaction analysis between ATG induction and low TAC exposure was also introduced, as it was suspected that a depleting ATG induction might dampen the effect of low TAC exposure. These interaction analyses were also carried out between ATG induction and DSTs, as well as ATG and DSAs. These interaction analyses were performed in Cox models with 2 covariates plus the interaction term. A multivariate Cox survival model was then built on these significant associations to evaluate the independent predictors of BPAR. Results were expressed as hazard ratios (HRs) with 95% CIs. Kaplan–Meier analyses were performed to represent allograft rejection-free survival, and log-rank tests were computed for the associated curves. The statistical significance level was defined as a 2-tailed p < 0.05. All statistical analyses were performed with IBM® SPSS Statistics (version 23) and R (version 4.1).The flowchart of the study is depicted in Since the patients of this study were treated with either an immediate (TAC-IR) or an extended-release (TAC-ER) TAC formulation, we first compared whether TAC trough concentrations and dose ratios (C/D ratio) between the two groups were comparable between the two formulations. As shown in CYP3A4*1/*1 and *1/*22 genotypes were 397 (88.8%) and 50 (11.2%), respectively. There were no CYP3A4*22/*22 homozygous patients. The CYP3A5*1/1*, *1/*3, and *3/*3 genotypes were observed in 7 (1.6%), 76 (17%), and 364 (81.4%) patients, respectively. As previously described (CYP3A4*1/*1 genotype were classified as high TAC metabolizers (HM) whereas *22 expressers as poor metabolizers (PM). Likewise, patients with CYP3A5*1/1*and *1/*3 genotypes were considered as TAC high metabolizers (HM) while *3/*3 genotype as poor metabolizers (PM). Since clustering patients according to both CYP3A4*22 and CYP3A5*3 allelic status may identify their metabolic status .The frequencies of the escribed , patientc status , we alsoc status Table 1.c status , most CYWhen considering the CYP3A phenotypes’ categorization and their impact on first TAC trough levels and dose adjustments, we first analyzed the clusters by merging all HM, IM, and PM from each CYP3A genotype. As illustrated in As described in low TAC exposure. The proportion of patients with TAC trough levels below 5 ng/ml, at least once within the study follow-up, according to each CYP3A cluster phenotype was significantly higher among HM as compared to IM and PM (p < 0.001) . Among patients experiencing BPAR, 27/70 (38.6%) had at least one TAC trough level <5 ng/ml at any time prior to BPAR, whereas only 79/377 (21%) of patients without BPAR did (p = 0.001). This threshold was therefore considered as As illustrated in When we analyzed BPAR-free survival curves according to main CYP3A phenotype clusters , only IM patients showed a significantly lower cumulative incidence of BPAR than the HM and PM  and late (>4 months) BPAR , leading to distinct functional phenotypes influencing TAC dose requirements to achieve whole blood pre-dose concentrations (C0) in kidney transplant recipients  barely independently correlated to BPAR, thus underscoring that initial low TAC trough levels may facilitate anti-donor alloimmune activation triggering allograft rejection. Moreover, a significant interaction between rATG and low TAC exposure was observed, leading to a reduction in the risk of BPAR. This interaction, together with the finding of the independent predictive value of TAC subexposure among patients not receiving rATG, strongly suggests that T-cell depletion induction therapy mitigates the risk of early low TAC exposures, conferring a protective umbrella in patients with insufficient immunosuppressive coverage, with HM patients the most suitable group. Alternatively, earlier TAC initiation or higher TAC dosage could eventually also counterbalance this deleterious effect.Another interesting finding in this work is that we confirm the independent negative effect of preformed DSTs and DSAs on the risk of BPAR. Previous studies by our group and others have reported a strong association between pretransplant DSTs and increased risk of BPAR, particularly TCMR, during the early period after transplantation, especially in patients not receiving T cell-depleting induction therapies , 18, 19.Our study has some limitations. Despite the high number of patients evaluated, the ethnicity of our study population, which is representative of most European kidney transplant programs, was mostly Caucasian; thus, certain CYP3A SNPs were less represented. Nevertheless, the similar distribution of main demographic, clinical, and immunological risk factors within all CYP3A pharmacogenetic clusters significantly counterbalance this constraint. We also acknowledge that there are other relevant variables that may directly influence TAC pharmacokinetics variability in whole blood in addition to the CYP3A genotypes, such as patient hematocrit, weight, corticosteroid dose, and a reduction of the hepatic function. Nevertheless, the impact of the TAC-metabolizing CYP3A genotypes on TAC dose requirements to achieve whole blood pre-dose concentrations highlights the important effects of the individual genetic susceptibility on TAC blood exposure. We did not include subclinical rejections; thus, a number of additional immune-mediated events may have occurred in our study population and have not been taken into account. Finally, the short follow-up period of the study may not have allowed us to observe some additional deleterious impacts in the long term.In conclusion, the results of our study strongly suggest that implementing pretransplant anti-donor alloimmune memory, both humoral and cellular, together with the individual genetic TAC-metabolizing susceptibility may significantly refine current immune-risk stratification of kidney transplant candidates prior to transplantation and may help in guiding treatment decision-making in a more personalized manner. Notably, these data warrant the development of large, prospective biomarker-guided trials, preferentially within multicenter international consortia.The original contributions presented in the study are included in the article/The studies involving human participants were reviewed and approved by the Investigator Research Board of Bellvitge University Hospital. The patients/participants provided their written informed consent to participate in this study.This article has been approved by all authors. NL and OB participated in the research design. EC, MS, SM, MM, and AT conducted the immune assay experiments. AV-A and PF performed the genotyping analysis. AS, MM, AF, JC, JG, FM, PR, and OB performed the clinical follow-up of patients of the study and the collection of clinical data. MG analyzed the histology. EC, AV-A, TJ, SM, LD, PH, OV, FB, NL, and OB performed the data collection and analysis. EC, TJ, NL, and OB wrote the article. PR, JG, NL, and OB developed refined study concepts, finalized the article draft, and secured the funding. All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.This work was supported by the Instituto de Salud Carlos III (ISCIII)  . Also, this work was partly supported by the SLT002/16/00183 grant, from the Department of Health of the Generalitat de Catalunya by the call “Acció instrumental de programes de recerca orientats en l’àmbit de la recerca i la innovació en salut.” The authors thank the Research Centers of Catalonia (CERCA) Programme/Generalitat de Catalunya for institutional support. OB was awarded an intensification grant from the “Instituto de Salud Carlos III” [NT19/00051].The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.The reviewer L.R has declared a shared affiliation with the author T.J to the handling editor at the time of review.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Introduction: Obesity is associated with severe asthma, but no specific treatment has been established. The gut microbiome is increasingly recognized as a crucial factor, but specific treatments focused on the gut microbiome have not been established. Recently, azithromycin has been found to have the capacity to attenuate exacerbations, a characteristic of severe asthma. The effect of azithromycin on obesity-induced severe asthma is not understood. Methods: The purpose of the present study is to clarify the effect of azithromycin on exacerbations in asthmatic patients with obesity. To explore the mechanism, the gut microbiome, metabolites of microbes such as short-chain fatty acids, and blood inflammatory cytokines will be analyzed to evaluate the correlation with the effect of azithromycin on exacerbations in obesity-induced severe asthma. A multi-center, prospective, single-arm intervention study is planned. Discussion: The present study will allow us to evaluate the effect of azithromycin on exacerbations, particularly in asthma patients with obesity, and explore biomarkers, targeting molecules including the gut microbiome, which are correlated with decreased exacerbations. The present results could contribute to identifying new therapeutic prospects and targeted microbes or molecules associated with severe clinical characteristics in asthmatic patients with obesity. Trial registration: This study has been registered as a prospective study with the University Hospital Medical Information Network (UMIN0000484389) and the Japan Registry of Clinical Trials (jRCTs071220023). Asthma is a common disease, and the majority of patients are well-controlled by treatment, including inhaled corticosteroids and bronchodilators, which are pivotal treatments for asthma ,2. HowevThere is increasing evidence that overweight and obesity are associated with the severity of asthma. For example, overweight increases the asthma exacerbation rate , and obeAkkermansia muciniphila, were found to be correlated with severity in obese asthmatic patients [Akkermansia muciniphila and others [The gut microbiome is recognized as essential in the severity mechanisms of obesity-induced asthma . For exapatients , and we patients . In addipatients ,26,27,28patients . For exapatients ,31,32. Id others ,34,35. Rd others . Notablyd others  and atted others . These d2) compared to asthma patients recruited in Australia and New Zealand regardless of their BMI in the AMAZES study. Considering efficacy and safety, the intervention dose of azithromycin is 250 mg per day in the present study compared to 500 mg, 3 times per week in the AMAZES study. Finally, the present study focuses on the gut microbiome and its metabolism as study endpoints. The present results will contribute to developing new therapies for obesity-induced severe asthma and identify targeted microbes or molecules associated with the regulation of asthma with obesity.The present study is a multi-center, prospective, single-arm intervention study involving treatment with azithromycin for 48 weeks to clarify whether such treatment reduces exacerbations of obesity-induced severe asthma. To explore the mechanism, the gut microbiome, metabolites produced by microbes such as short-chain fatty acids, and blood inflammatory cytokines will be assessed to evaluate their correlation with the reduction in exacerbations by azithromycin in obesity-induced severe asthma. Importantly, the present study is designed as a single-arm intervention considering the gut microbiome and biomarker diversity of individuals, which allows us to avoid individual diversity at baseline and explore specific microbes and biomarkers associated with clinical outcomes with a relatively small sample size, taking into account ethical concerns. Compared to the AMAZES study mentioned above, the study design, participants, intervention dose of azithromycin, and study endpoints are largely different. Briefly, the present study is planned as a single-arm intervention study compared to a randomized, double-blinded, placebo-controlled trial in the AMAZES study because of the sample size calculation considering gut microbiome diversity of individuals set as secondary endpoints. As study participants, the present study targets Japanese asthmatic patients with obesity (BMI > 25 kg/m2). Obesity is defined as a BMI greater than 25 kg/m2, referring to the Japanese criterion [The present study is a multi-center, open-label, prospective, single-arm intervention study. The duration of the intervention is 48 weeks. All patients with asthma are to be diagnosed by an expert pulmonary physician referring to the Global Initiative for Asthma (GINA) guidelines . Brieflyriterion . In the riterion . Severe riterion . The aziriterion . Anotherriterion . In termriterion . In addiriterion ,44. AccoThe present study was designed as a single-arm intervention considering the gut microbiome diversity of individuals. The composition of the gut microbiome differs depending on individual eating habits, medical history, and environmental factors ,46,47, w2 will be included. All patients must have experienced one or more episodes of moderate or severe exacerbations in the previous year. Written informed consent for participation in the present study will be obtained from all patients.Patients diagnosed with asthma, age older than 20 years and less than 75 years, with BMI greater than 25 kg/m2; and ineligible for the present study as determined by the researchers.Exclusion criteria are the following: aspartate aminotransferase or alanine aminotransferase greater than 100 IU/L; creatinine above 2.0 mg/dL; life-threatening arrhythmia or paroxysmal tachycardia with heart rate greater than 100 beats per minute; admitted for acute myocardial infarction or heart failure in the previous year; malignancy diagnosed in the previous 5 years, except for complete remission after treatment; macrolide antibiotic treatment in the previous 4 weeks; biologics including omalizumab, mepolizumab, benralizumab, and dupilumab in the previous 8 weeks at the start of azithromycin in the present study; QT interval requires correction for heart rate at more than 480 ms; pregnancy or breastfeeding; BMI less than 25 kg/m1), FEV1%, and %FEV1, and weight, BMI, level of fractional exhaled nitric oxide (FeNO), and scores on the asthma control test. Other secondary endpoints are to clarify the characteristics of the frequency of asthma exacerbations in improving/non-improving patients, and the diversity indices of the gut microbiome including the Chao 1, Shannon, and Simpson indices. For other exploratory endpoints, height, weight, BMI, and the tendency for decreased exacerbations will be assessed at 24 weeks of azithromycin treatment. In addition, biomarkers including cytokines, chemokines, short-chain fatty acids, metabolomics, and species of the gut microbiome will be compared between before and after azithromycin treatment and examined for relationships between changes and exacerbation at 48 weeks. The effects of sex and age attenuating the effect of azithromycin on exacerbations will also be assessed, because sex and age have been shown to have great impacts on the incidence and pathophysiology of asthma and obesity [The primary endpoint is reduction in the exacerbation rate after 48-week treatment with azithromycin compared to that before the intervention . The ast obesity ,48,49,50The present study consists of 7 visits: before intervention, at azithromycin initiation, 4 weeks later, 12 weeks later, 24 weeks later, 36 weeks later, and 48 weeks later. Informed consent will be obtained at visit 1 with recording of clinical information including treatment contexts for asthma, smoking index, exacerbation times in the previous year, and comorbidities. Physical measurements, electrocardiogram, and blood examination will be evaluated at all visits except for visit 1 to monitor adverse effects of azithromycin. Pulmonary function testing, FeNO, and asthma control tests are to be performed at visits 2, 5, and 7. Biomarker analyses of blood, including multiplex assay of cytokines and chemokines , short-chain fatty acids, and metabolomics analysis  are to be performed at visit 2 and visit 7. Gut microbiome analysis with 16s rRNA Sequencing  will be performed at visit 1 and visit 7. In terms of adverse effects of azithromycin, if the participants have any symptoms, physical and laboratory abnormalities of grade 2 level associated with azithromycin, the dose will be reduced to 250 mg 3 times per week. If the participants have any symptoms, physical and laboratory abnormalities of grade 3 level associated with azithromycin, administration of azithromycin will be terminated immediately.A previous study reported that the incidence rate ratio of asthma exacerbations for azithromycin compared to placebo was approximately 0.6 , but theFor 16s rRNA sequencing for gut microbiome analysis, stool DNA will be isolated using QIAamp DNA Mini Kit . A multiplex amplicon library converting the 16S rDNA gene V4 region will be generated from the DNA on the MiSeq machine . Microbial analysis will be performed using Qiime software with the Greengenes 99 database on the Nephele pipeline supported by the National Institutes of Health. The software will be used to calculate and generate alpha and beta diversities. For analysis of antibiotic resistance genes, tet(W), mel, msr(E), tet(M), erm(F), mef, and erm(B), which have been reported as genes related to antibiotic resistance , they wit-tests or McNemar’s tests will be used. The chi-squared test will be used to investigate the characteristics related to the frequency of asthma exacerbations. For other exploratory endpoints, height, weight, BMI, and tendency for an attenuation of the exacerbation rate at 24 weeks will be assessed by paired t-tests. Univariate analysis and multivariate analysis with a logistic regression model, adjusting BMI and body weight, will be performed to evaluate the relationships between the changes (improvement or no improvement in biomarker changes) and asthma exacerbation at 48 weeks.The primary and secondary endpoints and safety will be assessed in all patients completing 48 weeks of treatment. Then, patients without necessary exacerbation data for analysis or who withdrew consent before treatment will be excluded. For the primary endpoint, the asthma exacerbation rate at 48 weeks and its two-sided 95% confidence interval (CI) will be estimated with the normal approximation. The asthma exacerbation rate difference between pre- and post-treatment will also be tested binomially. For the clinical laboratory parameters and the diversity indices of the gut microbiome at pre-treatment and post-treatment as secondary endpoints, paired The present study focuses on asthma with obesity, which is one of the important forms of severe asthma , and thiBacteroidetes and the Firmicutes, are significantly changed between obese and lean human volunteers [Akkermansia muciniphila in the gut [The gut microbiome is increasingly recognized as a mechanistic basis of obesity-associated conditions, including asthma. For example, the prevalence and pathophysiology of type 2 diabetes mellitus, metabolic syndrome, non-alcoholic fatty liver disease, and cardiovascular disease are associated with the gut microbiome ,55,56. Elunteers . In an alunteers ,58. Unfo the gut ,59,60. TAkkermansia muciniphila, Turicibacter, and Lactobacillus are the candidates related to asthma pathophysiology in vivo and in humans [Future prospects for gut-microbiome-targeted therapy are mainly considered to include fecal microbiota transplantation (FMT), prebiotics, and probiotics . Indeed,n humans ,24. Unfon humans . We alson humans ,28. Accon humans , the pren humans . We do nThe limitations of the present study are that there are no control arms of lean subjects and placebo. The phenotypes of severe asthma in lean and obese subjects are different, and standardization of inflammatory and background characteristics of these two groups would be difficult given the need for an increased sample size caused by the huge standard deviation. Furthermore, there is no placebo group because of the gut microbiome diversity of individuals, as mentioned in the methods, even though triggers of asthma exacerbation and other factors associated with gut microbiome changes might not be standardized between before and after the azithromycin intervention. Thus, a single-arm intervention has been planned for the present study. Another limitation is that the inclusion criterion of 20–75 years of age is a wide range, which might affect the results of the metabolomics analysis.The present study will allow us to evaluate the effect of azithromycin on exacerbations, particularly in asthma patients with obesity, and explore biomarkers, targeting molecules including the gut microbiome, which are correlated with decreased exacerbations.


Intermediate coronary stenosis (ICS) is defined as a visually estimated percentage of diameter stenosis ranging between 40% and 70% by conventional coronary angiography (CAG). Whether to perform percutaneous coronary intervention (PCI) for these lesions is a challenge in clinical practice. The fractional flow reserve (FFR) can guide treatment by determining the functional significance of ICS. Studies have shown that some clinical indicators can be used to predict FFR. However, there is little research on this in the Chinese population. n = 280) and FFR >0.8 (n = 410). We compared the clinical factors between the two groups and performed multivariate logistic regression analyses to explore the risk factors. In addition, receiver-operating characteristic (ROC) curves were constructed for FFR ≤0.8 diagnoses.  We retrospectively analyzed 690 patients who underwent FFR measurements to determine the functional significance of a single ICS. Patients were divided into 2 groups: FFR ≤0.8 (p < 0.001). UHR corrects negatively with FFR . High-level UHR was an independent risk factor for the FFR ≤0.8 . The area under the curve (AUC) of the UHR diagnostic capacity for the FFR ≤0.8 is 0.77, with 77.3% sensitivity and 68.2% specificity.  The mean UHR (uric acid to high-density lipoprotein cholesterol ratio) level was significantly higher in the FFR ≤0.8 group ( UHR levels were significantly increased in patients with hemodynamically significant coronary lesions. UHR is a novel predictor of functionally significant lesions in patients with a single-vessel disease of ICS. The incidence of coronary artery disease (CAD) has markedly increased in the past 20–30 years in China . In clin∗ platelets/lymphocytes, can predict FFR ≤0.80, with 78.4% sensitivity and 64.0% specificity [Fortunately, several clinical studies have been performed that show finding an indicator to predict FFR is feasible. Erdoğan et al. suggest that the systemic immune-inflammation index, calculated by neutrophil cificity . Neverthcificity  and highcificity ) affecteAs we all know, UA and high-density lipoprotein cholesterol (HDL-C) disorders are both considered as risk factors for CAD. Previous studies showed that UHR is associated with hypertension control , hepaticIn this present study, we aim to investigate the relationship between UHR and FFR and find indicators to predict the functional significance for ICS in the Chinese population.n = 280) group or the FFR >0.8 (n = 410) group. The flow chart of the selection process is shown in In this observational retrospective study, 1500 inpatients with ICS discovered by CAG underwent FFR from February 2013 to October 2021 at the Anzhen Hospital  and were consecutively enrolled in this study. Patients were eligible if they fulfilled the following inclusion criteria: (1) a single angiographically intermediate lesion  in at least two major epicardial coronary arteries. Based on the result of FFR and patients' conditions, at least two cardiologists are involved in clinical treatment strategies.Both CAG and FFR were performed according to clinical standards. Intermediate coronary stenosis was defined as a coronary lesion with a visually estimated percentage diameter stenosis ranging between 40% and 70% of a major epicardial vessel. The CAG results were independently evaluated by two experienced interventional cardiologists who were blinded to this study. An FFR was carried out with the QUANTIEN platform . A pressure wire  was advanced distal to the stenosis. After the intravenous administration of 140 mg/kg/min adenosine, we obtained distal coronary artery pressure by pressure wire and aortic pressure by guiding catheter. The ratio of the two pressures is FFR.t-tests were used for comparison between groups. M  was used for measurement data that did not conform to a normal distribution, and the Mann–Whitney U test was used for comparison between groups. Categorical variables were presented as numbers and percentages and were compared using the χ2-test or Fisher's exact test. The receiver-operating characteristic (ROC) curves were constructed, and the AUCs were calculated to obtain the cutoff values. Variables that might be a possible confounding factor for the functionally significant stenosis, such as age, gender, hypertension, diabetes mellitus, smoking, white blood cells, monocytes, LDL-C, red blood cell distribution width, total bile acid, BMI ≥24, and UHR, were included in the univariate analyses. The variables which were determined as p < 0.1 in univariate analyses and some classic risk factors were included in a multivariate logistic regression analysis. To avoid multicollinearity, we did not include neutrophils, urea, and HDL-C in the regression models. A two-sided p-value <.05 was considered statistically significant. In addition, MedCalc (version 20.0.22) was used for the comparison of AUCs.SPSS 22.0  was used for statistical testing. Histograms and analytical Kolmogorov–Smirnov test methods to determine whether variables were normally distributed. The data of normal distribution were expressed as average value ± standard deviation, and Student's p < 0.05, p < 0.001, Baseline characteristic features are shown in r = 0.278, p < 0.001), hemoglobin , triglyceride , urea , creatinine , and homocysteine  showed significant positive correlations with the UHR  with a positive likelihood ratio of 2.08 for the UA and an AUC value of 0.692  with a positive likelihood ratio of 1.73 for HDL-C. The AUC of UHR was 0.770 , and the optimal cutoff value was 310.8, with a Youden index of 0.455. The sensitivity of the UHR for the diagnosis of the FFR ≤0.8 was 77.3%, the specificity was 68.2%, and the positive and negative likelihood ratios were 2.43 and 0.33, respectively. The AUC for UHR is 0.043 larger than UA  and is 0.078 larger than HDL-C , and quantitative coronary angiography FFR (QFR) [M et al. suggested a systemic immune-inflammation index, calculated by neutrophil  ∗ platelets/lymphocytes, can predict the FFR ≤0.8, with 78.4% sensitivity and 64.0% specificity [Research on the prediction of FFR has always been a hot issue in the cardiovascular field. On the one hand, some other functional indicators based on FFR are developing rapidly, such as instant wave-free ratio (iFR), coronary CT angiogram FFR (FFRFR (QFR) . These eFR (QFR) . Erdoğancificity . It is wcificity  were patcificity  and HDL cificity  affectedSerum uric acid is the final product of purine nucleotide metabolism and is widely regarded as a risk factor for CHD. Previous clinical studies showed that a high UA level is associated with CHD as well as its severity and prognosis , 26. SalHDL-C is a highly heterogeneous polymer composed of hundreds of proteins and lipids. In brief, it acts as an antiatherosclerosis agent by transporting cholesterol from tissues and cells outside the liver to the liver . In the As discussed above, the relationship between UA, HDL-C, and CAD has been widely accepted. Some basic experimental studies have shown that UA and HDL-C may interact with each other to exacerbate the progression of cardiovascular disease by damaging endothelial cell function and enhancing oxidative stress –19. In aOur study has some limitations. First, the single-center nature of this study and the relatively small number of enrolled patients may have introduced selection bias. Second, because this study only investigated the hemodynamic significance of a single vessel disease, further studies are needed to determine whether our conclusions are applicable to other patients, such as those with multivessel disease and previous PCI.In conclusion, our study suggest that UHR is independently associated with the FFR ≤0.8 and could predict functionally significant lesions in Chinese patients with a single vessel disease of intermediate stenosis.