The dyslipidemia of chronic renal disease: effects of statin therapy

PURPOSE OF REVIEW: Dyslipidemia is a prevalent condition in patients with chronic renal disease, but is often left untreated. Statin treatment constitutes an effective way to improve lipid abnormalities. This review summarizes present studies on dyslipidemia and its treatment in patients with chronic renal disease. RECENT FINDINGS: The specific dyslipidemia in renal disease is associated with the presence of proteinuria and decreased creatinine clearance, and may even adversely affect the progression of chronic renal disease. Statin therapy may have renoprotective effects due to a combination of lipid lowering and pleiotropic effects. Statins exert several anti-inflammatory properties and lead to a decrease of proteinuria. Post-hoc analyses of large-scale lipid lowering trials have shown that the reduction of cardiovascular risk was equivalent to the reduction achieved in patients without chronic renal failure. We feel, however, that if intervention with statins is postponed until patients reach end-stage renal disease, statins have limited benefit. SUMMARY: Present studies suggest that patients with renal disease should be screened early for dyslipidemia and that statins have to be considered as the lipid lowering therapy of choice. These drugs reduce cardiovascular risk. Further studies are needed to firmly establish whether statins preserve renal function.     

Apelin and copeptin: Two opposite biomarkers associated with kidney function decline and cyst growth in autosomal dominant polycystic kidney disease

Vasopressin (AVP) plays a detrimental role in autosomal dominant polycystic kidney disease (ADPKD). Copeptin represents a measurable substitute for circulating AVP whereas apelin counteracts AVP signaling. The aim of this study was to investigate the predictive value of apelin and copeptin for the progression of ADPKD disease. 52 ADPKD patients were enrolled and followed until the end of the observation period or the primary study endpoint was reached, defined by the combined outcome of decrease of glomerular filtration rate associated with a total renal volume increase. Receiver operating characteristics (ROC) analysis was employed for identifying the progression of renal disease and Kaplan–Meier curves assessed the renal survival. Adjusted risk estimates for progression endpoint and incident renal replacement therapy (RRT) were calculated using Cox proportional hazard regression analysis. ADPKD patients were characterized by lower apelin levels and higher copeptin levels when compared with healthy subjects. These biomarkers were strictly correlated with osmolality and markers of renal function. At ROC analysis, apelin and copeptin showed a very good diagnostic profile in identifying ADPKD progression. After the follow up of 24 months, 33 patients reached the endpoint. Cox proportional hazard regression analysis showed that apelin predicted renal disease progression and incident RRT independently of other potential confounders. Apelin is associated with kidney function decline in ADPKD, suggesting that it may be a new marker to predict kidney outcome.     

Analysis of covariance in parallel-group clinical trials with pretreatment baselines

Analysis of covariance (ANCOVA) techniques are often employed in the analysis of clinical trials to try to account for the effects of varying pretreatment baseline values of an outcome variable on posttreatment measurements of the same variable. Baseline measurements of outcome variables are typically random variables, which violates the usual ANCOVA assumption that covariate values are fixed. Therefore, the usual ANCOVA hypothesis tests of treatment effects may be invalid, and the ANCOVA slope parameter estimator biased, for this application. We show, however, that if the pretreatment - posttreatment measurements have a bivariate normal distribution, then (i) the ANCOVA model with residual error independent of the covariate is a valid expression of the relationship between pretreatment and posttreatment measurements; (ii) the usual (fixed-covariate analysis) ANCOVA estimates of the slope parameter and treatment effect contrasts are unbiased; and (iii) the usual ANCOVA treatment effect contrast t-tests are valid significance tests for treatment effects. Moreover, as long as the magnitudes of the treatment effects do not depend on the "true" pretreatment value of the outcome variable, the true slope parameter must lie in the interval (0, 1) and the ANCOVA model has a clear interpretation as an adjustment (based on between- and within-subject variability) to an analysis of variance model applied to the posttreatment-pretreatment differences.     

Micronutrients in HIV: A Bayesian Meta-Analysis

BackgroundApproximately 28.5 million people living with HIV are eligible for treatment (CD4<500), but currently have no access to antiretroviral therapy. Reduced serum level of micronutrients is common in HIV disease. Micronutrient supplementation (MNS) may mitigate disease progression and mortality.ObjectivesWe synthesized evidence on the effect of micronutrient supplementation on mortality and rate of disease progression in HIV disease.MethodsWe searched MEDLINE, EMBASE, the Cochrane Central, AMED and CINAHL databases through December 2014, without language restriction, for studies of greater than 3 micronutrients versus any or no comparator. We built a hierarchical Bayesian random effects model to synthesize results. Inferences are based on the posterior distribution of the population effects; posterior distributions were approximated by Markov chain Monte Carlo in OpenBugs.ConclusionsMNS significantly and substantially slows disease progression in HIV+ adults not on ARV, and possibly reduces mortality. Micronutrient supplements are effective in reducing progression with a posterior probability of 97.9%. Considering MNS low cost and lack of adverse effects, MNS should be standard of care for HIV+ adults not yet on ARV.     

Effects of gender on response to treatment with rivastigmine in mild cognitive impairment: A post hoc statistical modeling approach

Background: Epidemiologic studies have identified several demographic factors, including gender, that may influence the progression from mild cognitive impairment (MCI) to Alzheimer's disease (AD).Objective: This analysis aimed to develop a sensitive model for detecting treatment benefits in patients with MCI by controlling for factors that predict progression to AD. The study used this statistical modeling to investigate the effect of gender on treatment response in patients with MCI.Methods: This post hoc analysis used data from the InDDEx (Investigation in Delay to Diagnosis of Alzheimer's disease with Exelon) study, a long-term (3- to 4-year), multicenter, randomized, double-blind, placebo-controlled trial of rivastigmine 3- to 12-mg/d capsules in 1018 patients with MCI. Baseline variables that were significantly associated with progression to AD within the InDDEx study population were identified. A Cox proportional hazards multivariate regression model that adjusted for these predictive factors was applied to the overall study population and to the gender subgroups.Results: Of 31 baseline variables analyzed, 13 were found to be significantly associated with progression to AD in the overall population. After adjustment using the Cox proportional hazards regression model, rivastigmine was associated with a significantly lower risk for progression to AD compared with placebo in the overall population (1016 patients; hazard ratio [HR] = 0.747; P = 0.045). This effect of rivastigmine was evident in women (530 patients; HR = 0.676; P = 0.046) but not in men.Conclusions: In these patients with MCI, a significant decrease in the risk for progression to AD was found with rivastigmine over 3 to 4 years. The proportion of women whose disease progressed to AD was significantly lower in the rivastigmine group than the placebo group (P = 0.046). This effect was not found in men. These data suggest that prospectively adjusting for predictive factors could lead to a more accurate estimation of treatment benefits in future studies of MCI.     

Estimated Glomerular Filtration Rate Decline Is a Better Risk Factor for Outcomes of Systemic Disease-Related Nephropathy than for Outcomes of Primary Renal Diseases

Background

Currently, the contribution of kidney function decline in renal and patient outcomes is unclear. There are few data on the associations of different etiologies of estimated glomerular filtration rate (eGFR) decline with outcomes in multidisciplinary care. The purpose of this investigation was to establish whether eGFR decline in patients with disease is an important risk factor for developing end-stage renal disease (ESRD) and death.

Methods

From December 1, 2001 to December 31, 2011, 5097 adults with chronic kidney disease (CKD) received biochemical tests, physical examinations, a pathological examination, and a comprehensive questionnaire. We used linear regression models and multivariate Cox proportional hazards model to examine the outcome of eGFR decline in renal diseases with different etiologies.

Results

Mean age was 68.1±16.1 (standard deviation, SD) years, and 63.3% patients were male. In the studied cohort, 58.2% of the patients had systemic disease-related nephropathy (SDRN), 29.4% had primary renal diseases (PRDs), and 12.4% had other etiologies. The eGFR decline in SDRN had a significant association with dialysis in the Cox proportional hazards model [crude hazard ratio (HR) = 1.07, 95% confidence interval (CI), 1.04 to 1.10; adjusted HR 1.05, 95% CI, 1.02 to 1.08]. Diabetic nephropathy (DN) had the most severe eGFR decline in CKD stages 3, 4, and 5, and all contributed to the initiation of dialysis and death regardless of whether DN with or without eGFR decline was considered to be the cause. Although hypertensive nephropathy (HN) was related to significant acceleration of eGFR decline, it did not lead to poor outcome. There were still discrepancies between eGFR decline and outcomes in PRDs, hypertensive nephropathy, and lupus nephritis.

Conclusions

eGFR decline and CKD staging provide an informative guide for physicians to make proper clinical judgments in the treatment of CKD, especially SDRN. Poor control of the underlying systemic disease will thus lead to more rapid progression of SDRN.     

Cost-Effectiveness and Cost Thresholds of Generic and Brand Drugs in a National Chronic Hepatitis B Treatment Program in China

Chronic liver disease and liver cancer associated with chronic hepatitis B (CHB) are leading causes of death among adults in China. Although newborn hepatitis B immunization has successfully reduced the prevalence of CHB in children, about 100 million Chinese adults remain chronically infected. If left unmanaged, 15–25% will die from liver cancer or liver cirrhosis. Antiviral treatment is not necessary for all patients with CHB, but when it is indicated, good response to treatment would prevent disease progression and reduce disease mortality and morbidity, and costly complications. The aim of this study is to analyze the cost-effectiveness of generic and brand antiviral drugs for CHB treatment in China, and assessing various thresholds at which a highly potent, low resistance antiviral drug would be cost-saving and/or cost-effective to introduce in a national treatment program. We developed a Markov simulation model of disease progression using effectiveness and cost data from the medical literature. We measured life-time costs, quality adjusted life years (QALYs), incremental cost-effectiveness ratios (ICERs), and clinical outcomes. The no treatment strategy incurred the highest health care costs ($12,932-$25,293) per patient, and the worst health outcomes, compared to the antiviral treatment strategies. Monotherapy with either entecavir or tenofovir yielded the most QALYs (14.10–19.02) for both HBeAg-positive and negative patients, with or without cirrhosis. Threshold analysis showed entercavir or tenofovir treatment would be cost saving if the drug price is $32–75 (195–460 RMB) per month, highly cost-effective at $62–110 (379–670 RMB) per month and cost-effective at $63–120 (384–734 RMB) per month. This study can support policy decisions regarding the implementation of a national health program for chronic hepatitis B treatment in China at the population level.     

Antidepressants are a rational complementary therapy for the treatment of Alzheimer's disease

There is a high prevalence rate (30-50%) of Alzheimer's disease (AD) and depression comorbidity. Depression can be a risk factor for the development of AD or it can be developed secondary to the neurodegenerative process. There are numerous documented diagnosis and treatment challenges for the patients who suffer comorbidity between these two diseases. Meta analysis studies have provided evidence for the safety and efficacy of antidepressants in treatment of depression in AD patients. Preclinical and clinical studies show the positive role of chronic administration of selective serotonin reuptake inhibitor (SSRI) antidepressants in hindering the progression of the AD and improving patient performance. A number of clinical studies suggest a beneficial role of combinatorial therapies that pair antidepressants with FDA approved AD drugs. Preclinical studies also demonstrate a favorable effect of natural antidepressants for AD patients. Based on the preclinical studies there are a number of plausible antidepressants effects that may modulate the progression of AD. These effects include an increase in neurogenesis, improvement in learning and memory, elevation in the levels of neurotrophic factors and pCREB and a reduction of amyloid peptide burden. Based on this preclinical and clinical evidence, antidepressants represent a rational complimentary strategy for the treatment of AD patients with depression comorbidity.     

Recognition of genetic factors influencing the progression of hepatitis C : potential for personalized therapy

Infection with hepatitis C virus (HCV) is a major cause of chronic liver disease. Hepatic fibrosis may develop in subjects with chronic HCV infection, culminating in cirrhosis and an increased risk of hepatocellular carcinoma. The rate of development of fibrosis varies substantially between individuals; while it is influenced by a number of demographic and environmental factors, these account for only a small proportion of the variability.There are no clinical markers or tests that predict the rate of fibrosis progression in an individual subject. Thus, there has been increasing interest in the influence of host genetic factors on the rate of disease progression, and whether a genetic signature can be developed to reliably identify individuals at risk of severe disease. Numerous case-control, candidate gene, allele-association studies have examined the relationship between host single nucleotide polymorphisms or other genetic mutations and fibrosis in patients with chronic HCV infection. However, these studies have generally been irreproducible and disappointing. As seen with genetic studies for other diseases, small study cohorts and poor study design have contributed to limited meaningful findings. The successful determination of genetic signatures for fibrosis progression in chronic HCV will require multicenter collaborations using genome-wide association studies, with large, phenotypically well-defined sample sets. While these studies will require a significant financial commitment, a successful outcome offers the potential for personalized therapy and better patient management.     

Fenretinide favorably affects mucins (MUC5AC/MUC5B) and fatty acid imbalance in a manner mimicking CFTR-induced correction

Cystic fibrosis (CF) is the most common genetic disease in Caucasians. CF is manifested by abnormal accumulation of mucus in the lungs, which serves as fertile ground for the growth of microorganisms leading to recurrent infections and ultimately, lung failure. Mucus in CF patients consists of DNA from dead neutrophils as well as mucins produced by goblet cells. MUC5AC mucin leads to pathological plugging of the airways whereas MUC5B has a protective role against bacterial infection. Therefore, decreasing the level of MUC5AC while maintaining MUC5B intact would in principle be a desirable mucoregulatory treatment outcome.Fenretinide prevented the lipopolysaccharide-induced increase of MUC5AC gene expression, without affecting the level of MUC5B, in a lung goblet cell line. Additionally, fenretinide treatment reversed the pro-inflammatory imbalance of fatty acids by increasing docosahexaenoic acid and decreasing the levels of arachidonic acid in a lung epithelial cell line and primary leukocytes derived from CF patients. Furthermore, for the first time we also demonstrate the effect of fenretinide on multiple unsaturated fatty acids, as well as differential effects on the levels of long- compared to very-long-chain saturated fatty acids which are important substrates of complex phospholipids. Finally, we demonstrate that pre-treating mice with fenretinide in a chronic model of P. aeruginosa lung infection efficiently decreases the accumulation of mucus. These findings suggest that fenretinide may offer a new approach to therapeutic modulation of pathological mucus production in CF.     

Computational framework to understand the clinical stages of COVID-19 and visualization of time course for various treatment strategies

Coronavirus disease 2019 is known to be regulated by multiple factors such as delayed immune response, impaired T cell activation, and elevated levels of proinflammatory cytokines. Clinical management of the disease remains challenging due to interplay of various factors as drug candidates may elicit different responses depending on the staging of the disease. In this context, we propose a computational framework which provides insights into the interaction between viral infection and immune response in lung epithelial cells, with an aim of predicting optimal treatment strategies based on infection severity. First, we formulate the model for visualizing the nonlinear dynamics during the disease progression considering the role of T cells, macrophages and proinflammatory cytokines. Here, we show that the model is capable of emulating the dynamic and static data trends of viral load, T cell, macrophage levels, interleukin (IL)-6 and TNF-α levels. Second, we demonstrate the ability of the framework to capture the dynamics corresponding to mild, moderate, severe, and critical condition. Our result shows that, at late phase (>15 days), severity of disease is directly proportional to pro-inflammatory cytokine IL6 and tumor necrosis factor (TNF)-α levels and inversely proportional to the number of T cells. Finally, the simulation framework was used to assess the effect of drug administration time as well as efficacy of single or multiple drugs on patients. The major contribution of the proposed framework is to utilize the infection progression model for clinical management and administration of drugs inhibiting virus replication and cytokine levels as well as immunosuppressant drugs at various stages of the disease.     

Protein microarrays discover angiotensinogen and PRKRIP1 as novel targets for autoantibodies in chronic renal disease

Biomarkers for early detection of chronic kidney disease are needed, as millions of patients suffer from chronic diseases predisposing them to kidney failure. Protein microarrays may also hold utility in the discovery of auto-antibodies in other conditions not commonly considered auto-immune diseases. We hypothesized that proteins are released as a consequence of damage at a cellular level during end-organ damage from renal injury, not otherwise recognized as self-antigens, and an adaptive humoral immune response to these proteins might be detected in the blood, as a noninvasive tracker of this injury. The resultant antibodies (Ab) detected in the blood would serve as effective biomarkers for occult renal injury, enabling earlier clinical detection of chronic kidney disease than currently possible, because of the redundancy of the serum creatinine as a biomarker for early kidney injury. To screen for novel autoantibodies in chronic kidney disease, 24 protein microarrays were used to compare serum Ab from patients with chronic kidney disease against matched controls. From a panel of 38 antigens with increased Ab binding, four were validated in 71 individuals, with (n=50) and without (n=21) renal insufficiency. Significant elevations in the titer of novel auto-Ab were noted against angiotensinogen and PRKRIP1 in renal insufficiency. Current validation is underway to evaluate if these auto-Ab can provide means to follow the evolution of chronic kidney disease in patients with early stages of renal insufficiency, and if these rising titers of these auto-Ab correlate with the rate of progression of chronic kidney disease.     

A left ventricle model to predict post-revascularization ejection fraction based on cine magnetic resonance images

The left ventricular ejection fraction (LVEF) is an important clinical indicator of the cardiac function and long-term outcome for patients with coronary artery disease. A biomechanical model of the left ventricle was developed to quantitatively predict post-revascularization LVEF based on noninvasive magnetic resonance imaging. The myocardium was categorized into normal, hibernating, and infarcted regions from the ventricular short-axis images. Assuming that hibernating tissue would potentially regain contractility after revascularization, the expected maximum post-revascularization LVEF was calculated for four patients with chronic left ventricular dysfunction. The predictions were within three ejection fraction points of the follow-up LVEFs. This model may be useful to estimate the outcome and efficacy of revascularization plans.     

HIV and HCV： from Co-infection to Epidemiology, Transmission, Pathogenesis, and Treatment

Human immunodeficiency virus (HIV) is the infectious agent causing acquired immu-nodeficiency syndrome (AIDS),a deadliest scourge of human society. Hepatitis C virus (HCV) is a major causative agent of chronic liver disease and infects an estimated 170 million people worldwide,resulting in a serious public health burden. Due to shared routes of transmission,co-infection with HIV and HCV has become common among individuals who had high risks of blood exposures. Among hemophiliacs the co-infection rate accounts for 85%; while among injection drug users (IDU) the rate can be as high as 90%. HIV can accelerate the progression of HCV-related liver disease,particularly when immunodeficiency has developed. Although the effect of HCV on HIV infection is controversial,most studies showed an increase in mortality due to liver disease. HCV may act as a direct cofactor to fasten the progression of AIDS and decrease the tolerance of highly active antiretroviral therapy (HARRT). Conversely,HAART-related hepatotoxicity may enhance the progression of liver fibrosis. Due to above complications,co-infection with HCV and HIV-1 has imposed a critical challenge in the management of these patients. In this review,we focus on the epidemiology and transmission of HIV and HCV,the impact of the two viruses on each other,and their treatment.     

HIV and HCV: from Co-infection to epidemiology, transmission, pathogenesis, and treatment

Human immunodeficiency virus (HIV) is the infectious agent causing acquired immunodeficiency syndrome (AIDS), a deadliest scourge of human society. Hepatitis C virus (HCV) is a major causative agent of chronic liver disease and infects an estimated 170 million people worldwide, resulting in a serious public health burden. Due to shared routes of transmission, co-infection with HIV and HCV has become common among individuals who had high risks of blood exposures. Among hemophiliacs the co-infection rate accounts for 85%; while among injection drug users (IDU) the rate can be as high as 90%. HIV can accelerate the progression of HCV-related liver disease, particularly when immunodeficiency has developed. Although the effect of HCV on HIV infection is controversial, most studies showed an increase in mortality due to liver disease. HCV may act as a direct cofactor to fasten the progression of AIDS and decrease the tolerance of highly active antiretroviral therapy (HARRT). Conversely, HAART-related hepatotoxicity may enhance the progression of liver fibrosis. Due to above complications, co-infection with HCV and HIV-1 has imposed a critical challenge in the management of these patients. In this review, we focus on the epidemiology and transmission of HIV and HCV, the impact of the two viruses on each other, and their treatment.      

Effect of Aqueous Extract of Phenolic Compounds Obtained from Red Wine in Experimental Model of Colitis in Mice

Background: Inflammatory bowel disease (IBD) is a chronic relapsing inflammatory disorder represented by Crohn’s disease and ulcerative colitis. Currently, there is no cure and pharmacological treatment aims to induce and maintain remission on patients. Because the therapy reveals a relatively high toxicity, during a long-term utilization, it is essential to investigate new pharmacological approaches. Polyphenols, commonly present on red wine, have shown health-beneficial effects related to their antioxidant and anti-inflammatory effects through the inhibition of NF-kB activation, COX-2 and iNOS induction. In this sense, it would be interesting to study their effects in an IBD context. Therefore, this study aims to evaluate the effects of an aqueous extract of phenolic compounds in a 2,4,6-Trinitrobenzenesulfonic acid (TNBS)-induced model of colitis. Method: Experimental colitis was induced in mice through an intrarectal administration of TNBS and then the mice were treated with an aqueous extract of phenolic compounds intraperitoneally for four days. Results and Discussion: The extract demonstrated an anti-inflammatory effect, reducing TNF-α levels in the colon, and had a beneficial effect on the extraintestinal manifestations related to IBD, without any significant side effects. The extract of phenolic compounds demonstrated to be a valuable object of study for the management of IBD in the future.     

Predicting the impact of a nonsterilizing vaccine against human immunodeficiency virus

Studies of human immunodeficiency virus (HIV) vaccines in animal models suggest that it is difficult to induce complete protection from infection (sterilizing immunity) but that it is possible to reduce the viral load and to slow or prevent disease progression following infection. We have developed an age-structured epidemiological model of the effects of a disease-modifying HIV vaccine that incorporates the intrahost dynamics of infection, a transmission rate and host mortality that depend on the viral load, the possible evolution and transmission of vaccine escape mutant viruses, a finite duration of vaccine protection, and possible changes in sexual behavior. Using this model, we investigated the long-term outcome of a disease-modifying vaccine and utilized uncertainty analysis to quantify the effects of our lack of precise knowledge of various parameters. Our results suggest that the extent of viral load reduction in vaccinated infected individuals (compared to unvaccinated individuals) is the key predictor of vaccine efficacy. Reductions in viral load of about 1 log(10) copies ml(-1) would be sufficient to significantly reduce HIV-associated mortality in the first 20 years after the introduction of vaccination. Changes in sexual risk behavior also had a strong impact on the epidemic outcome. The impact of vaccination is dependent on the population in which it is used, with disease-modifying vaccines predicted to have the most impact in areas of low prevalence and rapid epidemic growth. Surprisingly, the extent to which vaccination alters disease progression, the rate of generation of escape mutants, and the transmission of escape mutants are predicted to have only a weak impact on the epidemic outcome over the first 25 years after the introduction of a vaccine.     

Natural history of hepatitis C virus infection

Hepatitis C virus (HCV) is a common transmissible agent responsible for a significant proportion of chronic liver disease, cirrhosis and hepatocellular carcinoma worldwide. The natural history of acute HCV infection is characterized by a high rate of progression to persistent infection. The resulting chronic liver disease is dependent upon a delicate balance of host, viral and environmental factors which may significantly influence its clinical outcome.     

Accelerated clinical discovery using self-reported patient data collected online and a patient-matching algorithm

Patients with serious diseases may experiment with drugs that have not received regulatory approval. Online patient communities structured around quantitative outcome data have the potential to provide an observational environment to monitor such drug usage and its consequences. Here we describe an analysis of data reported on the website PatientsLikeMe by patients with amyotrophic lateral sclerosis (ALS) who experimented with lithium carbonate treatment. To reduce potential bias owing to lack of randomization, we developed an algorithm to match 149 treated patients to multiple controls (447 total) based on the progression of their disease course. At 12 months after treatment, we found no effect of lithium on disease progression. Although observational studies using unblinded data are not a substitute for double-blind randomized control trials, this study reached the same conclusion as subsequent randomized trials, suggesting that data reported by patients over the internet may be useful for accelerating clinical discovery and evaluating the effectiveness of drugs already in use.