HLA-A2-matched peripheral blood mononuclear cells from type 1 diabetic patients, but not nondiabetic donors, transfer insulitis to NOD-scid/γc(null)/HLA-A2 transgenic mice concurrent with the expansion of islet-specific CD8+ T cells

OBJECTIVE

Type 1 diabetes is an autoimmune disease characterized by the destruction of insulin-producing β-cells. NOD mice provide a useful tool for understanding disease pathogenesis and progression. Although much has been learned from studies with NOD mice, increased understanding of human type 1 diabetes can be gained by evaluating the pathogenic potential of human diabetogenic effector cells in vivo. Therefore, our objective in this study was to develop a small-animal model using human effector cells to study type 1 diabetes.

RESEARCH DESIGN AND METHODS

We adoptively transferred HLA-A2–matched peripheral blood mononuclear cells (PBMCs) from type 1 diabetic patients and nondiabetic control subjects into transgenic NOD-scid/γc^null/HLA-A*0201 (NOD-scid/γc^null/A2) mice. At various times after adoptive transfer, we determined the ability of these mice to support the survival and proliferation of the human lymphoid cells. Human lymphocytes were isolated and assessed from the blood, spleen, pancreatic lymph node and islets of NOD-scid/γc^null/A2 mice after transfer.

RESULTS

Human T and B cells proliferate and survive for at least 6 weeks and were recovered from the blood, spleen, draining pancreatic lymph node, and most importantly, islets of NOD-scid/γc^null/A2 mice. Lymphocytes from type 1 diabetic patients preferentially infiltrate the islets of NOD-scid/γc^null/A2 mice. In contrast, PBMCs from nondiabetic HLA-A2–matched donors showed significantly less islet infiltration. Moreover, in mice that received PBMCs from type 1 diabetic patients, we identified epitope-specific CD8⁺ T cells among the islet infiltrates.

CONCLUSIONS

We show that insulitis is transferred to NOD-scid/γc^null/A2 mice that received HLA-A2–matched PBMCs from type 1 diabetic patients. In addition, many of the infiltrating CD8⁺ T cells are epitope-specific and produce interferon-γ after in vitro peptide stimulation. This indicates that NOD-scid/γc^null/A2 mice transferred with HLA-A2–matched PBMCs from type 1 diabetic patients may serve as a useful tool for studying epitope-specific T-cell–mediated responses in patients with type 1 diabetes.NOD mice develop spontaneous diabetes due to autoimmune destruction of pancreatic β-cells. These mice have served as a useful tool for understanding many aspects of type 1 diabetes (1,2). For example, the identification of certain pathogenic epitopes were originally found in NOD mice and subsequently observed in the blood of type 1 diabetic patients (3). The major shortcoming of these studies is their inability to evaluate the human autoreactive effector cells directly. Researchers have identified a number of pathogenic autoreactive epitopes of CD4⁺ and CD8⁺ T cells that recognize and result in β-cell killing. Epitopes for islet-specific glucose-6-phosphatase catalytic subunit-related protein (IGRP), insulin, and preproinsulin have been identified in the islets of NOD mice (4). T cells specific for epitopes from these proteins and other islet proteins, including islet amyloid polypeptide (IAPP), have been found in the blood of type 1 diabetic patients (5). At the same time, however, many of the findings in NOD mice have not directly translated to human type 1 diabetes. Importantly, a large number of therapies appear to “cure” diabetes in NOD mice, but these therapies have not readily translated to humans. Anti-CD3 antibody therapy, which is extremely effective in NOD mice (6,7), is less effective in patients (8,9). These immunomodulatory therapies still leave concerns about their effects, as discussed by Santamaria (10). Other immune therapies aimed at targeting B cells, such as anti-CD20 monoclonal antibody treatment, also offer short-term CD19⁺ B-cell depletion and partially preserve β-cell function (11).Development of humanized mice in which HLA-matched peripheral blood mononuclear cells (PBMCs) from type 1 diabetic patients are adoptively transferred into immune-deficient mice would provide a means of studying human immune cells without the restrictions inherent to human studies (12). Specifically, it would be possible to identify human autoreactive epitope-specific T cells that infiltrate the islets directly ex vivo. A small-animal model that recapitulates the clinical manifestations of type 1 diabetes would also assist in identifying novel therapeutic targets and in developing and testing novel immunotherapeutic agents. Furthermore, we would be able to investigate the mechanisms involved in disease pathogenesis of many other autoimmune diseases, especially those with disease-associated epitopes, shared between humans and mice (13,14).During the past several years, many investigators have used human hematopoietic stem cells (HSCs) for engraftment into immunodeficient mice (15–17). These studies have attempted to develop a complete human immune system in a murine host. In many cases, successful engraftment and cell differentiation was observed. Most recently, investigators showed that functional human CD4⁺ and CD8⁺ T cells developed after being transferred into immune-deficient HLA transgenic mice and that these T cells demonstrated HLA-restricted responses (18). In contrast, our goal was not to recapitulate the entire autoimmune process; rather, we sought to develop a humanized mouse model that would be useful for identifying pre-existing autoreactive diabetogenic circulating T cells from type 1 diabetic patients that are important in the direct pathogenesis of type 1 diabetes.In NOD mice, β-cell–specific CD8⁺ T-cell clones are found in the peripheral blood and pancreatic islets (19). In patients with type 1 diabetes, epitope-specific T cells display T-lymphocyte cytotoxic activity toward human β-cells (20). Humans and mice also share many of the protein sequences of identified epitopes (21). Therefore, because it is likely that lymphocytes that have been exposed to islet antigens circulate within the blood of patients with type 1 diabetes, we adoptively transferred peripheral blood mononuclear cells (PBMCs) from HLA-A2–matched type 1 diabetic patients into transgenic NOD-scid/γc^null/HLA-A*0201 (NOD-scid/γc^null/A2) mice (22).

TABLE 1

Type 1 diabetic and nondiabetic haplotype-matched PBMC donors used in transfer experiments^*

Adenopathy and Extensive Skin Patch Overlying a Plasmacytoma (AESOP) Syndrome

Adenopathy and extensive skin patch overlying a plasmacytoma is a very rare syndrome featuring a red-to-brown, violaceous skin patch along with a plasmacytoma. Only 11 case reports exist in the literature. Skin biopsies from the cutaneous patch overlying the plasmacytoma exhibit a dermal vascular hyperplasia with increased surrounding dermal mucin. Radiation therapy is used to treat and cure the plasmacytoma.Adenopathy and extensive skin patch overlying a plasmacytoma (AESOP) syndrome is a very rare constellation of findings seen in patients with a yet-to-be diagnosed solitary plasmacytoma.1,2 There are only 11 cases reported in the literature; the first report dates back to Sheinker in 1938 (3

TABLE 1

Summary of patients with AESOP syndrome ranked by ascending age

Cost-Effectiveness of Aliskiren in Type 2 Diabetes,Hypertension, and Albuminuria

The Aliskiren in the Evaluation of Proteinuria in Diabetes (AVOID) trial demonstrated that adding aliskiren, an oral direct renin inhibitor, at a dosage of 300 mg/d to the highest approved dosage of losartan and optimal antihypertensive therapy reduces albuminuria over 6 mo among patients with type 2 diabetes, hypertension, and albuminuria. The cost-effectiveness of this therapy, however, is unknown. Here, we used a Markov model to project progression to ESRD, life years, quality-adjusted life years, and lifetime costs for aliskiren plus losartan versus losartan. We used data from the AVOID study and the Irbesartan in Diabetic Nephropathy Trial (IDNT) to estimate probabilities of progression of renal disease. We estimated probabilities of mortality for ESRD and other comorbidities using data from the US Renal Data System, US Vital Statistics, and published studies. We based pharmacy costs on wholesale acquisition costs and based costs of ESRD and transplantation on data from the US Renal Data System. We found that adding aliskiren to losartan increased time free of ESRD, life expectancy, and quality-adjusted life expectancy by 0.1772, 0.1021, and 0.0967 yr, respectively. Total expected lifetime health care costs increased by $2952, reflecting the higher pharmacy costs of aliskiren and losartan ($7769), which were partially offset by savings in costs of ESRD ($4860). We estimated the cost-effectiveness of aliskiren to be $30,500 per quality-adjusted life year gained. In conclusion, adding aliskiren to losartan and optimal therapy in patients with type 2 diabetes, hypertension, and albuminuria may be cost-effective from a US health care system perspective.Recent clinical trials have shown that reductions in albuminuria with agents that inhibit the renin-angiotensin-aldosterone system (RAAS; e.g., angiotensin-converting enzyme inhibitors or angiotensin receptor blockers), as defined by a urinary albumin-creatinine ratio (UACR) or urinary albumin excretion rate (UAER), can delay progression of renal disease in patients with hypertension and type 2 diabetes.^1–5 Albuminuria is associated with fatal and nonfatal cardiovascular events and progression toward ESRD,^1,2,6 and reductions in albuminuria have been widely used as surrogate markers of renoprotection.^7,8The Aliskiren in the Evaluation of Proteinuria in Diabetes (AVOID) trial was a multicenter, randomized, double-blind study to assess the efficacy and safety of adding aliskiren, an oral direct renin inhibitor, at a dosage of 300 mg/d to the highest approved dosage of losartan (100 mg/d) and optimal antihypertensive therapy in patients with type 2 diabetes, hypertension, and albuminuria.⁹ At the end of 6 mo of follow-up, aliskiren 300 mg/d significantly reduced mean UACR by 20% (P = 0.0009) and overnight UAER by 18% versus placebo (P = 0.009). Although the AVOID trial demonstrated that adjunctive treatment with aliskiren 300 mg/d reduces albuminuria during 6 mo in these patients, it did not examine the potential long-term clinical and economic consequences of such treatment.The objective of this study was to evaluate, from the US health care system perspective, the potential cost-effectiveness of lifetime treatment with aliskiren 300 mg/d plus losartan 100 mg/d and optimal antihypertensive therapy (aliskiren plus losartan) versus lifetime treatment with losartan 100 mg/d and optimal antihypertensive therapy alone (losartan only) in patients with type 2 diabetes, hypertension, and albuminuria. We evaluated cost-effectiveness using a Markov model (Figure 1).¹⁰ The initial distribution of the population across disease states and probabilities of progression from microalbuminuria (MA) and early overt nephropathy (EON) to advanced overt nephropathy (AON) were from the AVOID trial (11Open in a separate windowFigure 1.Markov state transition model. Ovals represent health states. Patients are assumed to transition among states every 6 mo on the basis of transition probabilities in

Primary Cutaneous Blastomycosis as a Cause of Acute Respiratory Distress Syndrom: Case Report and Literature Review

Blastomycosis is a fungal infection caused by Blastomyces dermatitidis. Exposure in endemic regions frequently occurs when spores in soil are disturbed and subsequently inhaled. Less commonly, primary cutaneous blastomycosis may follow after traumatic inoculation of the fungus into the skin. Most patients infected with blastomycosis are asymptomatic, but an unfortunate small number present with fulminant disease. Rarely, the infection can affect organs, such as the skin, bone, or genitourinary system. In a small percentage of cases, blastomycosis may cause acute respiratory distress syndrome, which is associated with a very high mortality rate. Increased survival rates have been shown when the clinician has a high index of suspicion and facilitates rapid evaluation and initiation of the appropriate therapy. We present a rare case of a patient presenting with primary cutaneous blastomycosis that progressed to disseminated disease causing acute respiratory distress syndrome. High clinical suspicion, prompt diagnostic testing, and therapy with amphotericin B, confirmed the diagnosis and resulted in a swift recovery.Blastomycosis is an infection caused by the fungus Blastomyces dermatitidis, which is endemic to areas of the United States and Canada including the Great Lakes Region and the Mississippi and Ohio River Valleys.^1,2 Exposure occurs in moist wooded areas during outdoor activities when fungal microhabitats existing in soil are disturbed. Inhaled conidia can result in a primary lung infection, which may then become disseminated.^3,4 Pulmonary disease is the most common manifestation of blastomycosis with isolated lung disease occurring in 60 to 75 percent of infected people.⁵ In the remaining group, dissemination to skin, bone, genitourinary, and other organ systems can be seen.⁴ In fewer than 10 percent of cases, blastomycosis can progress to acute respiratory distress syndrome (ARDS) with dyspnea, tachypnea, and hypoxemia as systemic manifestations.^6–12Palmer and McFadden reported the first case of disseminated blastomycosis causing ARDS in 1968.¹³ Since then, few studies have identified disseminated blastomycosis as a cause of ARDS (14 Thus, early suspicion of disseminated disease is especially helpful in endemic areas since rapid institution of therapy can improve morbidity and mortality.

Table 1

Case reports of blastomycosis causing acute respiratory distress syndrome in the literature

Association between Body Composition and Frailty among Prevalent Hemodialysis Patients: A US Renal Data System Special Study

Studies of frailty among patients on hemodialysis have relied on definitions that substitute self-reported functioning for measures of physical performance and omit weight loss or substitute alternate criteria. We examined the association between body composition and a definition of frailty that includes measured physical performance and weight loss in a cross-sectional analysis of 638 adult patients receiving maintenance hemodialysis at 14 centers. Frailty was defined as having three of following characteristics: weight loss, weakness, exhaustion, low physical activity, and slow gait speed. We performed logistic regression with body mass index (BMI) and bioelectrical impedance spectroscopy (BIS)-derived estimates of intracellular water (ICW), fat mass, and extracellular water (ECW) as the main predictors, and age, sex, race, and comorbidity as covariates. Overall, 30% of participants were frail. Older age (odds ratio [OR], 1.31 per 10 years; 95% confidence interval [95% CI], 1.14 to 1.50), diabetes (OR, 1.65; 95% CI, 1.13 to 2.40), higher fat mass (OR, 1.18; 95% CI, 1.02 to 1.37), and higher ECW (OR, 1.33; 95% CI, 1.20 to 1.47) associated with higher odds of frailty. Higher ICW associated with lower odds of frailty (OR, 0.80 per kg; 95% CI, 0.73 to 0.87). The addition of BMI data did not change the area under the receiver operating characteristics curve (AUC; AUC=0.66 versus 0.66; P=0.71), but the addition of BIS data did change the AUC (AUC=0.72; P<0.001). Thus, individual components of body composition but not BMI associate strongly with frailty in this cohort of patients receiving hemodialysis.Patients on dialysis frequently experience protein energy wasting or loss of protein mass and energy stores, which is likely multifactorial.¹ It has recently been appreciated that the same disorders that underlie protein energy wasting as well as muscle wasting itself are also commonly associated with frailty.^2–4 Although frailty is generally considered to be a geriatric syndrome, individuals with chronic diseases, such as CKD, may be at risk for premature frailty.^5,6 In fact, as many as two thirds to three quarters of patients new to dialysis may be frail by definitions that rely on patient self-report of physical functioning and omit weight loss or substitute alternate criteria for wasting (6,⁷

Table 1.

Definitions of frailty adapted from the Cardiovascular Health Study definition

Estimated GFR Reporting Influences Recommendations for Dialysis Initiation

Automated reporting of estimated GFR (eGFR) with serum creatinine measurement is now common. We surveyed nephrologists in four countries to determine whether eGFR reporting influences nephrologists’ recommendations for dialysis initiation. Respondents were randomly allocated to receive a survey of four clinical vignettes that included either serum creatinine concentration only or serum creatinine and the corresponding eGFR. For each scenario, the respondent was asked to rank his or her likelihood of recommending dialysis initiation on a modified 8-point Likert scale, ranging from 1 (“definitely not”) to 8 (“definitely would”). Analysis of the 822 eligible responses received showed that the predicted likelihood of recommending dialysis increased by 0.55 points when eGFR was reported (95% confidence interval, 0.33 to 0.76), and this effect was larger for eGFRs >5 ml/min per 1.73 m² (P<0.001). Subgroup analyses suggested that physicians who had been in practice ≥13 years were more affected by eGFR reporting (P=0.03). These results indicate that eGFR reporting modestly increases the likelihood that dialysis is recommended, and physicians should be aware of this effect when assessing patients with severe CKD.Serum creatinine concentration is commonly used to calculate the estimated GFR (eGFR). The eGFR can identify patients with significant CKD even when the serum creatinine level is not markedly abnormal. As such, clinical practice guidelines recommend using eGFR, rather than serum creatinine, to identify, risk stratify, and manage patients with CKD.^1–3Automatically reporting eGFR when serum creatinine is measured is becoming commonplace to enhance the identification of patients with CKD.⁴ Observational studies have demonstrated that eGFR reporting improved CKD detection and increased referrals of patients with early CKD to nephrologists.^5–8 Furthermore, eGFR reporting is associated with increased appropriate treatment in patients with CKD.⁹ However, the effects of eGFR reporting on nephrologists’ practices are uncertain.Whether eGFR reporting influences the decision to initiate dialysis is important to patients, physicians, and health care systems. We conducted a randomized survey to determine whether eGFR reporting influences the likelihood that a nephrologist will recommend the initiation of dialysis. The survey randomly allocated half of the recipients to receive only serum creatinine information for clinical vignettes of CKD and half to receive both serum creatinine and eGFR information.Of the 5576 surveys distributed, 579 were returned to the sender, leaving 4997 potential respondents. Of the 938 surveys (19%) that were returned, 822 (16%) were analyzed (Figure 1). Respondents were similar between groups (Open in a separate windowFigure 1.Flow of surveys and respondents throughout the study.

Table 1.

Respondent characteristics

Comparisons between Novel Oral Anticoagulants and Vitamin K Antagonists in Patients with CKD

Novel oral anticoagulants (NOACs) (rivaroxaban, dabigatran, apixaban) have been approved by international regulatory agencies to treat atrial fibrillation and venous thromboembolism in patients with kidney dysfunction. However, altered metabolism of these drugs in the setting of impaired kidney function may subject patients with CKD to alterations in their efficacy and a higher risk of bleeding. This article examined the efficacy and safety of the NOACs versus vitamin K antagonists (VKAs) for atrial fibrillation and venous thromboembolism in patients with CKD. A systematic review and meta-analyses of randomized controlled trials were conducted to estimate relative risk (RR) with 95% confidence interval (95% CIs) using a random-effects model. MEDLINE, Embase, and the Cochrane Library were searched to identify articles published up to March 2013. We selected published randomized controlled trials of NOACs compared with VKAs of at least 4 weeks’ duration that enrolled patients with CKD (defined as creatinine clearance of 30–50 ml/min) and reported data on comparative efficacy and bleeding events. Eight randomized controlled trials were eligible. There was no significant difference in the primary efficacy outcomes of stroke and systemic thromboembolism (four trials, 9693 participants; RR, 0.64 [95% CI, 0.39 to 1.04]) and recurrent thromboembolism or thromboembolism-related death (four trials, 891 participants; RR, 0.97 [95% CI, 0.43 to 2.15]) with NOACs versus VKAs. The risk of major bleeding or the combined endpoint of major bleeding or clinically relevant nonmajor bleeding (primary safety outcome) (eight trials, 10,616 participants; RR 0.89 [95% CI, 0.68 to 1.16]) was similar between the groups. The use of NOACs in select patients with CKD demonstrates efficacy and safety similar to those with VKAs. Proactive postmarketing surveillance and further studies are pivotal to further define the rational use of these agents.The introduction of the novel oral anticoagulants (NOACs) rivaroxaban (Xarelto, Bayer, Munich Germany), apixaban (Elequis, Pfizer, Bristol-Myers Squibb), and dabigatran (Pradax/Pradaxa/Prazaxa, Boehringer Ingelheim) as alternatives to vitamin K antagonists (VKAs) has been met with enthusiasm among clinicians. These agents are currently available for prophylaxis and treatment of venous thromboembolism (VTE) and for prophylaxis of stroke and systemic thromboembolism in the setting of atrial fibrillation. Furthermore, they have demonstrated similar or greater efficacy and safety in relation to conventional anticoagulants in large trials.^1–6NOACs differ from traditional oral VKAs mechanistically and pharmacokinetically. Dabigatran directly inhibits the final effector of coagulation, thrombin (factor IIa), while rivaroxaban and apixaban directly inhibit the rate-limiting step of coagulation, factor Xa activation. Thrombin and factor Xa are targeted by the NOACs for anticoagulant therapy given their roles in clot formation.^7,8 Advantages of the NOACs include their rapid onset of action, shorter half-lives, lack of requirement for regular laboratory monitoring, and absence of food interactions compared with VKAs.Although the NOACs differ in their degree of kidney excretion, their elimination is differentially impaired with worsening kidney function, with accumulating levels predisposing patients to an increased risk of bleeding events.^9,10 CKD is increasing in prevalence and is associated with an increased risk of atrial fibrillation and venous thrombosis, both of which are indications for NOAC use.^11,12 In North America, these agents have been approved by the US Food and Drug Administration and Health Canada for use in patients with varying degrees of kidney dysfunction. However, these agencies have extrapolated the efficacy and safety data from the NOAC trials and approved dabigatran and rivaroxaban for use in patients with more severe CKD, despite the exclusion of such patients from the trials (13–¹⁸ Serious bleeding has been reported with the NOACs in patients with CKD.^19,20

Table 1.

Regulatory agency recommendations for NOACs in patients with CKD

Linkage Disequilibrium Mapping of the Replicated Type 2 Diabetes Linkage Signal on Chromosome 1q

OBJECTIVE

Linkage of the chromosome 1q21–25 region to type 2 diabetes has been demonstrated in multiple ethnic groups. We performed common variant fine-mapping across a 23-Mb interval in a multiethnic sample to search for variants responsible for this linkage signal.

RESEARCH DESIGN AND METHODS

In all, 5,290 single nucleotide polymorphisms (SNPs) were successfully genotyped in 3,179 type 2 diabetes case and control subjects from eight populations with evidence of 1q linkage. Samples were ascertained using strategies designed to enhance power to detect variants causal for 1q linkage. After imputation, we estimate ∼80% coverage of common variation across the region (r ² > 0.8, Europeans). Association signals of interest were evaluated through in silico replication and de novo genotyping in ∼8,500 case subjects and 12,400 control subjects.

RESULTS

Association mapping of the 23-Mb region identified two strong signals, both of which were restricted to the subset of European-descent samples. The first mapped to the NOS1AP (CAPON) gene region (lead SNP: rs7538490, odds ratio 1.38 [95% CI 1.21–1.57], P = 1.4 × 10⁻⁶, in 999 case subjects and 1,190 control subjects); the second mapped within an extensive region of linkage disequilibrium that includes the ASH1L and PKLR genes (lead SNP: rs11264371, odds ratio 1.48 [1.18–1.76], P = 1.0 × 10⁻⁵, under a dominant model). However, there was no evidence for association at either signal on replication, and, across all data (>24,000 subjects), there was no indication that these variants were causally related to type 2 diabetes status.

CONCLUSIONS

Detailed fine-mapping of the 23-Mb region of replicated linkage has failed to identify common variant signals contributing to the observed signal. Future studies should focus on identification of causal alleles of lower frequency and higher penetrance.Genome-wide association (GWA) analysis has provided a powerful stimulus to the discovery of common variants influencing type 2 diabetes risk, and, to date, ∼20 susceptibility loci have been identified with high levels of statistical confidence (1). However, these known variants account for only a small proportion of the inherited component of disease risk (probably <10%), and the molecular basis of the majority of the genetic predisposition to type 2 diabetes has yet to be established (1).The success of the GWA approach contrasts with the slow progress that characterized previous efforts to map susceptibility loci through genome-wide linkage (2). However, now that many of the common variants of largest effect have been identified (in European-descent populations at least), there are cogent reasons to revisit regions previously identified through genome-wide linkage. First, variants within the genomic intervals representing replicated linkage signals can be considered to have raised prior odds for a susceptibility effect, and this information can be used to prioritize GWA signals (particularly those with only modest evidence of association) for targeted replication. Second, genuine linkage signals are likely to be driven by causal variants—particularly low-frequency SNPs or copy number variants not captured by the commodity GWA arrays—with effect sizes larger than those currently detectable by GWA (3). Because alleles with these characteristics will have a more marked impact on individual disease predisposition than the common variants found by GWA, identification of causal variants underpinning replicated linkage signals should accelerate efforts to obtain better predictors of disease (4).For type 2 diabetes, there appears to be only limited overlap between the regions identified by genome-wide linkage and those revealed by GWA (5). Although the discovery of TCF7L2 was prompted by a search for causal variants within a region of replicated type 2 diabetes linkage, neither the common variants in TCF7L2 nor those in HHEX and IDE (a second nearby GWA signal) account for that linkage signal (6). Thus, the discovery of TCF7L2 reflects either serendipity or the co-localization of common and rare causal variants in the same locus—the former driving the association and the latter the linkage. Similarly, whereas common variants in HNF4A have been reported to explain the chromosome 20 linkage signals seen in Finns and Ashkenazim (7,8), these associations have proved difficult to replicate (9).Chromosome 1q (in particular the 30-Mb stretch adjacent to the centromere) ranks alongside the regions on chromosomes 10 and 20 as among the strongest in terms of the replicated evidence for genome-wide linkage to type 2 diabetes. Linkage has been reported in samples of European (U.K., French, Amish, Utah), East Asian (Chinese, Hong Kong), and Native American (Pima) origin (summarized in Supplementary Table 1, which is available in the online-only appendix at http://diabetes.diabetesjournals.org/cgi/content/full/db09-0081/DC1; ref. (2). The region concerned is gene rich and contains a disproportionate share of excellent biological candidates (2). The homologous region has also emerged as a diabetes susceptibility locus from mapping efforts in several well-characterized rodent models (10–13).The International 1q Consortium represents a coordinated effort by the groups with the strongest evidence for 1q linkage to identify variants causal for that signal. Here, we report efforts to map causal variants using a custom linkage-disequilibrium (LD) mapping approach, predominantly based around common SNP variants, applied to a well-powered set of multiethnic samples.To improve power, ascertainment of type 2 diabetes cases for this study aimed to enrich for 1q causal alleles through 1) a focus on populations and samples that had shown 1q linkage; 2) selection for positive family history; and 3) for some samples, preferential recruitment on the basis of patterns of identity by descent sharing in the 1q region. For each set of case subjects, we selected a control sample of individuals from the same population. Details of the recruitment have been reported previously (14) and are summarized in the supplementary material available in the online appendix. In all, the case-control part of the study included 2,198 samples (1,000 case subjects, 1,198 control subjects) of European descent, 281 (140 case subjects, 141 control subjects) of East Asian origin, and 285 (144 case subjects, 141 control subjects) who were Native American (Pima) (supplementary Table 2). We also included a small sample of individuals of African American origin (242 case subjects, 173 control subjects) and an additional 599 Pima individuals (520 affected, 79 nondiabetic after age 45 years) from 255 families who, after combination with the Pima case-control set, were used for family-based association analyses.These samples were submitted to dense-map SNP typing of the core region of interest (from 147.0 to 169.7 Mb [Build 35]) using a series of 1,536-plex BeadArray designs (Golden Gate, Illumina, San Diego, CA). Design of these arrays was contemporaneous with development of dbSNP and HapMap (15). Thus, whereas the first arrays were LD-agnostic and compiled using genomic localization as the primary consideration for inclusion, subsequent arrays used LD information from the CEU (European ancestry) and CHB/JPT (Asian ancestry) components of HapMap to guide SNP selection and maximize coverage of the region. In all, we designed assays for 6,023 SNPs, of which 5,290 provided reliable data in all populations after passing through our extensive quality control (see the supplementary material). We estimate that after imputation (using the appropriate set of HapMap data as a reference), coverage of the region (minor allele frequency >0.05; r² > 0.8) reaches ∼80% in the European and ∼72% in the East Asian samples. Coverage is harder to estimate (and imputation likely to be less valuable) in Pima and African American samples, since reference data from these populations are not available, although we estimate ∼49% coverage in West Africans based on YRI data.Genotyping quality was generally good, with over 91% of SNPs passing quality control in each population (see the supplementary material) and <0.45% of SNPs failing (P < 10⁻⁴) tests of within-sample Hardy-Weinberg equilibrium. Significant departures from expectation in the distributions of test statistics observed in the Amish and Pima samples (as revealed by QQ plots; see supplementary material) likely reflect residual relatedness between subjects from those populations. We adjusted for this (and any population stratification effects) through genomic control methods (16). Association analyses treated each study as a separate stratum and used standard meta-analysis approaches to deliver estimates of joint effect size and statistical significance (see supplementary material). A series of nested meta-analyses were performed including 1) European-descent samples only (“4-way”); 2) non–African-descent samples only (“7-way”); and 3) all samples (“8-way”).Under an additive model with allele frequency of 0.25, our sample provides ∼80% power to detect per-allele odds ratios (ORs) of >1.36 (“8-way”) or >1.43 (“4-way”) for α = 5 × 10⁻⁶. Given that the region covers ∼1% of the genome, we consider this a reasonable benchmark for “region-wide” significance (equivalent to consensus genome-wide thresholds of 5 × 10⁻⁸). These power calculations are conservative: given the case ascertainment enrichment strategies used in this study, we would expect to detect variants with population-level effects in the 1.2–1.3 range. Under reasonable assumptions (three independent alleles contributing to a linkage signal with a locus-specific sibling relative risk of ∼1.15), we can expect the effect size of the variants we were seeking to detect (i.e., those responsible for the 1q linkage) to be substantially greater than this (e.g., allelic OR 1.6 for a variant with risk allele frequency of 25%). Our study was therefore well powered to detect putatively causal alleles within the European and/or combined datasets.Across these analyses, none of the SNPs showed an association with type 2 diabetes that withstood genome-wide correction (P < 5 × 10⁻⁸) (17). However, two clusters of SNPs showed association signals that approached or exceeded “region-wide” significance thresholds. The first of these, involving rs7538490 and nearby SNPs, mapped to a 51.4-kb interval (at ∼160.35 Mb) within the first intron of NOS1AP (nitric oxide synthase 1 [neuronal] adaptor protein) with an estimated per allele OR (in the 4-way, European-only analysis) of 1.38 (95% CI 1.21–1.57, P = 1.4 × 10⁻⁶, additive model, Fig. 1). Rs7538490 lies ∼5.6 kb from one of the SNPs (rs10494366) previously shown to influence cardiac repolarization and QT interval (18): the two SNPs are in modest LD (r² = 0.47 in HapMap CEU), and rs10494366 shows some evidence for association with type 2 diabetes (P = 3.1 × 10⁻⁴) in the same 4-way meta-analysis.

TABLE 1

Association results for rs7538490 in the NOS1AP gene

Adolescent Scalp Psoriasis: Update on Topical Combination Therapy

Plaque psoriasis can begin early in life and negatively affect quality of life. Topical agents are generally recommended as first-line therapy for plaque psoriasis. The synergy of a vitamin D analog and a steroid in a topical fixed-combination formulation provides more favorable effectiveness and tolerability as compared with either agent alone. The safety and effectiveness of a once-daily calcipotriene/betamethasone dipropionate topical suspension have been established in children 12 to 17 years of age with scalp plaque psoriasis. Combination topical formulations and once-daily dosing decrease regimen complexity and may increase adherence. Accommodation of vehicle preference may also improve adherence and real-life effectiveness.Psoriasis, a common dermatologic disorder affecting individuals of all ages, can begin early in life. Up to 35 percent of cases begin before 18 years of age, affecting 0.7 percent of children.1-3 This incidence doubled between 1970 and 1999 and is currently 40.8 cases per 100,000.4 The median age at diagnosis (10.6 years) has remained stable in the United States.4It is important for clinicians to appreciate the impact of psoriasis on children and teenagers. Even mild forms of psoriasis can affect childhood psychosocial functioning and quality of life (QoL).2,5-7 The scalp plaques and possible associated alopecia can be particularly troublesome during adolescence and detrimental to the individual’s sense of self during the transition to adulthood.8,9Topical therapy can be safe and effective in juvenile psoriasis. Topical treatments are a first-line option in adults, and some have been approved for use in adolescents (10-19 This article reviews the distinguishing features of psoriasis in younger patients and the considerations that enter into the choice of treatment.

TABLE 1

Approved topical corticosteroid formulations for adolescents10-14, 16-19

Functional Effector Memory T Cells Enrich the Peritoneal Cavity of Patients Treated with Peritoneal Dialysis

The frequency and severity of episodes of peritonitis adversely affect the structure and function of the peritoneal membrane in patients treated with peritoneal dialysis (PD), but the underlying mechanisms are not well understood. Alterations in the phenotype and function of resident peritoneal cells may contribute. Because effector memory T cells play a pivotal role in maintaining peripheral tissue immunity, we hypothesized that these cells may initiate or perpetuate the peritoneal inflammatory response. Here, we characterized the phenotype and effector function of peritoneal memory T cells. We found that functional effector memory T cells capable of mounting long-term recall responses enrich the peritoneal cavity of PD patients. Peritoneal T cells were able to mount a Th1-polarized response to recall antigens, and these responses were greater in peritoneal T cells compared with T cells in the peripheral blood. We also observed that the peritoneal T cells had altered telomeres; some cells had ultrashort telomeres, suggesting a highly differentiated local population. In summary, we describe a resident population of memory T cells in the peritoneum of PD patients and speculate that these cells form part of the first line of defense against invading pathogens.Despite advances in treatment, peritoneal infection remains one of the main causes of technique failure in peritoneal dialysis (PD) patients. There is a strong association between peritonitis (frequency and severity) and the loss of membrane function.^1–3 In view of this, there has been considerable interest in understanding the basic processes that regulate peritoneal early responses to infection. Most of these studies have focused on the contribution of peritoneal macrophages or mesothelial cells to these processes.^4–9 Despite representing up to 25% of the resident peritoneal leukocyte population and forming a significant proportion of the leukocyte population present in resolving peritonitis, the function and phenotype of human peritoneal T cells is poorly defined.^10–12 Consequently we understand very little about the adaptive arm of the peritoneal immune responseRecent developments in the field of immunology have greatly enhanced our understanding of T cell phenotype, activation status, differentiation, and tissue homing capacity. Many studies have highlighted the important role of T cells in providing long-term immunological memory.^13–19 According to current definitions, memory T cells are distinguished from naïve T cells (which are yet to encounter their cognate antigen) by the expression of CD45RO (rather than CD45RA).²⁰ Within the memory T cell population, distinct functional subsets have been characterized based on the expression the lymph node homing signal CCR7.^13–19 These subsets differ in both their tissue homing capability and in their response to antigenic stimulation.^15,17,18 Central memory (T_CM) cells (CD45RO/CCR7⁺) are thought to migrate through lymph tissue, whereas effector memory (T_EM) cells (CD45RO /CCR7⁻), which lack lymph node homing signals, are thought to reside primarily in peripheral tissue.^16,17 The T_EM subset rapidly produces effector cytokines such as IFN-γ and IL-4 and are thought to form a first line of defense in vulnerable peripheral tissues. In contrast, T_CM cells lack immediate effector function but retain proliferative capacity and are capable of generating a secondary wave of antigen-specific effector T cells.^17–19 The memory subsets also differ in their replicative history and degree of differentiation. Within the T cell population, telomere lengths decrease from naïve through T_CM through T_EM cells, suggesting that the latter have undergone more cell divisions and are a more highly differentiated population.^17,20Most of our current understanding of T cell memory is derived from murine data or from experiments performed on peripheral blood T cells. Because of the logistical difficulties involved in sample collection, there are very little data available regarding the phenotype and function of memory T cells in human peripheral tissue. The aim of our study was to characterize the phenotype, replicative history, and effector function of the peritoneal memory T cell population during steady-state (non-infected) PD.Our results demonstrate that as compared with peripheral blood, the peritoneal cavity is enriched in cells displaying a T_EM phenotype, with very few intraperitoneal naïve T cells (Figure 1, A and B) (we found no significant difference in the proportion of T_CM cells between blood and peritoneum). Subgroup analysis shows that neither time on PD nor recurrent peritonitis have a significant effect on the proportion of T_EM within the peritoneal cavity, suggesting that T_EM enrichment is a characteristic of the quiescent peritoneal cavity (Supplementary Figure 1). Further phenotypic analysis demonstrated increased expression of the proinflammatory chemokine receptor CCR5 on the T_EM subset, but only low-level expression of the lymph node homing signal CD62L (Figure 1C).Open in a separate windowFigure 1.Paired samples of peripheral blood mononuclear cells (PBMCs) and peritoneal leukocytes were collected from PD patients. Cells were labeled with fluorescently conjugated monoclonal antibody directed against CD4/CD8/CCR7 and CD45RO. A combined gate was set on peritoneal T cells on the basis of CD4 or CD8 expression and their FSC:SSC profiles. (A) Representative example of CD4 data. (B) Summary of data obtained from paired blood and peritoneal T cells obtained from 20 patients. Differences between groups were tested using the Wilcoxon signed ranks test (*P < 0.05). (C) Peritoneal leukocytes were collected from ten separate PD patients. Cells were labeled with fluorescently conjugated monoclonal antibody directed against CD4/CCR7/CD45RO and CD62L or CCR5. A combined gate was set on peritoneal T cells on the basis of CD4 expression and their FSC:SSC profiles. Further gate was plotted on the T_EM subset and percentage CD62L⁺/CCR5⁺ within this calculated subset. See ​and22 for patient demographics.

Table 1.

Patient demographics

Endothelin-A Receptor Antagonism Modifies Cardiovascular Risk Factors in CKD

Arterial stiffness and impaired nitric oxide (NO) bioavailability contribute to the high risk for cardiovascular disease in CKD. Both asymmetric dimethylarginine (ADMA), an endogenous inhibitor of NO production, and endothelin-1 (ET-1) oppose the actions of NO, suggesting that ET-1 receptor antagonists may have a role in cardiovascular protection in CKD. We conducted a randomized, double-blind, three-way crossover study in 27 patients with proteinuric CKD to compare the effects of the ET_A receptor antagonist sitaxentan, nifedipine, and placebo on proteinuria, BP, arterial stiffness, and various cardiovascular biomarkers. After 6 weeks of treatment, placebo and nifedipine did not affect plasma urate, ADMA, or urine ET-1/creatinine, which reflects renal ET-1 production; in contrast, sitaxentan led to statistically significant reductions in all three of these biomarkers. No treatment affected plasma ET-1. Reductions in proteinuria and BP after sitaxentan treatment was associated with increases in urine ET-1/creatinine, whereas reduction in pulse-wave velocity, a measure of arterial stiffness, was associated with a decrease in ADMA. Taken together, these data suggest that ET_A receptor antagonism may modify risk factors for cardiovascular disease in CKD.CKD is common, affecting 6%–11% of the population globally.¹ It is strongly associated with incident cardiovascular disease (CVD).² This increased cardiovascular risk is not adequately explained by conventional (Framingham) risk factors, such as hypertension, hypercholesterolemia, diabetes mellitus, and smoking, all of which are common in patients with CKD. Thus, emerging cardiovascular risk factors have been an area of intense investigation.³ Arterial stiffness⁴ makes an important independent contribution to CVD risk in CKD, and this is promoted by both conventional and emerging cardiovascular risk factors.Hyperuricemia and a shift in the balance of the vasodilator nitric oxide (NO) and vasoconstrictor endothelin (ET) systems have been identified as potential contributors to increased cardiovascular risk in patients with CKD.⁵ These are all common in a typical CKD population.^3,6 Epidemiologic studies report a relationship between serum uric acid and a wide variety of cardiovascular conditions, including hypertension, diabetes mellitus, coronary artery disease, cerebrovascular disease, and CKD.⁷ Indeed, serum uric acid is considered by some to be an independent risk factor for both CVD^8,9 and CKD.¹⁰ Others have noted that an elevated serum uric acid level predicts the development of hypertension and CKD.⁷ Of note, emerging clinical data show that decreasing serum uric acid levels has both cardiovascular and renal benefits.^11–13Asymmetric dimethylarginine (ADMA) is an endogenous inhibitor of NO synthases. By inhibiting NO formation, ADMA causes endothelial dysfunction, vasoconstriction, elevation of BP, and progression of experimental atherosclerosis.¹⁴ ADMA concentrations are increased in patients with CKD,¹⁴ and clinical data support ADMA as an independent marker of CKD progression, cardiovascular morbidity, and overall mortality.^15–17 Studies have shown a reduction in ADMA after therapy in patients with hypertension and hypercholesterolemia,^18,19 but not in patients with CKD.ET-1 is a potent endogenous vasoconstrictor produced within the vasculature. It is implicated in both the development and progression of CKD.²⁰ Its effects are mediated via two receptors, the ET_A and ET_B receptors; the major pathologic effects are ET_A receptor mediated.²⁰ We have recently shown that long-term selective ET_A receptor antagonist therapy using the orally active drug sitaxentan reduces proteinuria, BP, and arterial stiffness in patients with proteinuric CKD,²¹ effects that are potentially renoprotective. We hypothesized that in this same cohort of patients with CKD, sitaxentan would also reduce levels of serum uric acid, ADMA, and urine ET-1 (as a measure of renal ET-1 production) and so provide broader cardiovascular and renal protection. The current data show the effects of sitaxentan, as well as placebo and an active control agent, nifedipine, on these novel cardiovascular risk factors.As described elsewhere,²¹ after 6 weeks of dosing no significant differences were seen between sitaxentan and nifedipine in the reductions from baseline in BP measures. Despite this, sitaxentan reduced proteinuria to a significantly greater extent than did nifedipine. Pulse-wave velocity (PWV)—a measure of arterial stiffness—decreased to a similar degree with nifedipine as with sitaxentan. Placebo did not affect proteinuria, BP, or PWV (see VariablePlaceboSitaxentanNifedipineBaselineWeek 6BaselineWeek 6BaselineWeek 624-hr proteinuria (g/d)2.06±0.382.00±0.332.07±0.341.46±0.26^a1.95±0.301.99±0.33Protein-to-creatinine ratio (mg/mmol)155±31153±27157±28114±23^b155±27152±29Mean arterial pressure (mmHg)94.6±2.294.3±1.794.4±1.890.7±1.8^c95.5±2.091.7±1.7^cSystolic BP (mmHg)125.4±2.7124.2±1.9124.3±2.2120.7±1.9^c125.7±2.4120.7±1.6^cDiastolic BP (mmHg)77.9±1.577.5±1.277.9±1.374.3±1.3^a78. 9±1.575.7±1.2^aPWV (m/s)7.7±0.38.0±0.48.0±0.37.6±0.3^c7.9±0.37.6±0.3^cCentral augmentation index (%)20±220±220±215±2^a19±217±2Plasma ET-1 (pg/ml)3.6±0.53.7±0.63.6±0.53.7±0.53.5±0.53.5±0.5Urine ET-1 (pg/ml)4.5±0.44.7±0.45.1±0.44.2±2.1^c5.1±0.44.7±0.4Open in a separate windowValues are given as predosing baseline ± SEM.^aP<0.01 for week 6 versus baseline.^bP=0.01 for week 6 versus baseline.^cP<0.05 for week 6 versus baseline.

Table 2.

Renal substudy data from clearance studies performed at baseline and week 6 of each study period

A Practical Approach to Monitoring Patients on Biological Agents for the Treatment of Psoriasis

Psoriasis is a chronic, systemic, inflammatory skin condition that manifests predominantly as well-demarcated, erythematous, scaly plaques on the elbows, knees, and scalp. While mild cases (minimal body surface) often respond to various topical treatments and light therapy, patients with extensive disease (larger body surface and possibly joint involvement) may require systemic medications for remission. The development of biological agents provides dermatologists valuable ways to help treat psoriatic disease quite efficiently, but literature regarding the monitoring of patients on biological treatments is sparse. Clinical practice varies widely since there is modest strong evidence to recommend or refute most tests currently recommended by the United States Food and Drug Administration. The purpose of this article is to present a practical approach to monitoring patients on biological therapy based on the most up-to-date literature.The use of biological treatments has grown significantly since their introduction and now account for a significant proportion of the systemic therapies used for the treatment of psoriasis. Biological therapies target precise segments of the immune system, offering the advantage of being less immunosuppressive compared to the traditional systemic therapies that broadly cause immunosuppression. Currently, five biological agents (e.g., alefacept, etanercept, infliximab, adalimumab, and ustekinumab) are approved by the United States Food and Drug Administration (FDA) for the treatment of psoriasis, and other newer agents (e.g., ABT-874) are in various stages of development and clinical trials (1–6 The biologicals at present are divided into either tumor necrosis factor alpha (TNF-α) or T-cell lymphocyte inhibitors. Recently, CD4+ T helper (Th) 17 cells and interleukins (IL)-12 and IL-23 have been important in the pathogenesis of T-cell mediated disorders, such as psoriasis, and have influenced the development of medications that specifically target these key immunological players. Both IL-12 and IL-23 stimulate differentiation of naive T-cells into Th1 and Th17 cells, key cells that regulate the production of other pro-inflammatory cytokines significant in the pathogenesis of psoriasis.^7,8 Understanding of these immune cascade complexities has divulged this new class of biological agents that target cytokines (e.g., ustekinumab) important in the pathogenesis of inflammatory skin disease. Each drug class that is used in the treatment of psoriasis works by blocking different steps along the same immune-dysregulation pathway leading to psoriatic disease.

Table 1

Currently approved biological medications for the treatment of psoriasis^1–4,6

New National Allocation Policy for Deceased Donor Kidneys in the United States and Possible Effect on Patient Outcomes

In 2013, the Organ Procurement and Transplantation Network in the United States approved a new national deceased donor kidney allocation policy that introduces the kidney donor profile index (KDPI), which gives scores of 0%–100% based on 10 donor factors. Kidneys with lower KDPI scores are associated with better post-transplant survival. Important features of the new policy include first allocating kidneys from donors with a KDPI≤20% to candidates in the top 20th percentile of estimated post-transplant survival, adding waiting time from dialysis initiation, conferring priority points for a calculated panel-reactive antibody (CPRA)>19%, broader sharing of kidneys for candidates with a CPRA≥99%, broader sharing of kidneys from donors with a KDPI>85%, eliminating the payback system, and allocating blood type A2 and A2B kidneys to blood type B candidates. We simulated the distribution of kidneys under the new policy compared with the current allocation policy. The simulation showed increases in projected median allograft years of life with the new policy (9.07 years) compared with the current policy (8.82 years). With the new policy, candidates with a CPRA>20%, with blood type B, and aged 18–49 years were more likely to undergo transplant, but transplants declined in candidates aged 50–64 years (4.1% decline) and ≥65 years (2.7% decline). These simulations demonstrate that the new deceased donor kidney allocation policy may improve overall post-transplant survival and access for highly sensitized candidates, with minimal effects on access to transplant by race/ethnicity and declines in kidney allocation for candidates aged ≥50 years.The current deceased donor kidney allocation policy has not changed substantially in >20 years.¹ During this time, the gap between supply and demand has widened. Waiting time has become the dominant factor in allocation, and less emphasis has been placed on biologic criteria such as the degree of immune system sensitization or HLA matching. For minority candidates, such as African Americans, who have difficulty gaining access to the waiting list, delay in listing contributes to racial disparities in access to transplant.^2–4 The current allocation system favors candidates who have waited the longest, but does not improve outcomes after transplant and discourages use of kidneys with a potentially shorter duration of functioning. These shortcomings have created inequities. Waiting times for blood type B candidates are much longer than waiting times for blood type A candidates.^5,6 Kidneys with the potential to function longer may be allocated to candidates with shorter life expectancy; conversely, candidates with a longer estimated life span may be allocated kidneys with limited duration of functioning. These types of transplants result in high retransplant rates and increase the demand for donor kidneys. A new allocation policy was approved by the Organ Procurement and Transplantation Network (OPTN) on June 24, 2013.The new allocation policy risk-stratifies deceased donors using the kidney donor profile index (KDPI).^7,8 The KDPI takes into account donor age, height, weight, ethnicity, history of hypertension and diabetes, cause of death, serum creatinine level, hepatitis C status, and donation after circulatory death status (Wait-Listed CandidatesKDPI≤0.20KDPI 0.21–0.34KDPI 0.35–0.85KDPI>0.85Local CPRA 100%Local CPRA 100%Local CPRA 100%Local CPRA 100%Regional CPRA 100%Regional CPRA 100%Regional CPRA 100%Regional CPRA 100%National CPRA 100%National CPRA 100%National CPRA 100%National CPRA 100%Local CPRA 99%Local CPRA 99%Local CPRA 99%Local CPRA 99%Regional CPRA 99%Regional CPRA 99%Regional CPRA 99%Regional CPRA 99%Local CPRA 98%Local CPRA 98%Local CPRA 98%Local CPRA 98%0 HLA mm top 200 HLA mm0 HLA mm0 HLA mmPrior living donorsPrior living donorsPrior living donorsLocal, regional adultLocal pediatricLocal pediatricLocalNational adultLocal top 20Local adultRegional0 HLA mm bottom 80Regional pediatricNationalLocal bottom 80Regional adultRegional pediatricNational pediatricRegional top 20National adultRegional bottom 80National pediatricNational top 20National bottom 80Open in a separate window0 HLA mm designates candidates with zero HLA mismatch at A, B, and DR loci; top 20 designates candidates in the top 20th percentile of survival; bottom 80 designates candidates not in the top 20th percentile of survival. Both the new and the current allocation policies give priority to candidates listed for simultaneous kidney and non-kidney organ transplants, including kidney-pancreas, kidney-liver, and kidney-heart transplants. This is not shown in the table above and is not included in the KPSAM modeling. Prior living donors represent a small number of candidates who are not included in the KPSAM modeling. SCr, serum creatinine; CVA, cerebrovascular accident.^aKDPI is derived from the kidney donor risk index (KDRI) developed by Rao et al.⁷ The KDPI includes only the donor-specific elements of the KDRI, and is mapped to a reference population from the previous year, in order to yield percentiles. For KDRI, the reference population is all kidneys recovered for transplant between January 1, 2007, and December 31, 2009. The calculation is as follows: KDRI=exp(−0.0194×I[age<18 yr]×[age−18 yr]+0.0128×[age−40 yr]+0.0107×I[age>50 yr]+0.179×I[race=African American]+0.126×I [hypertensive]+0.130×I[diabetic]+0.220×[SCr−1 mg/dl] −0.209×I[SCr>1.5 mg/dl]×[SCr−1.5 mg/dl]+0.0881×I[cause of death=CVA]−0.0464×[{height−170 cm}/10]−0.0199×I[weight<80 kg]×[{weight–80 kg}/5]+0.133×I[donation after cardiac death] +0.240×I[hepatitis C]−0.0766, where I is equal to 1 if the condition is true and I is equal to 0 if the condition is false.^bEPTS score=0.047×MAX (Age−25, 0)−0.015×Diabetes×MAX(Age–25,0)+0.398×Prior Organ Transplant−0.237×Diabetes×Prior Organ Transplant+0.315×log(Years on Dialysis+1)−0.099×Diabetes×log(Years on Dialysis+1)+0.130×(Years on Dialysis=0)−0.348×Diabetes×(Years on Dialysis=0)+1.262×Diabetes.As in the current system, points will be used to rank candidates in each category listed in ​and3).3). This scale was based inversely on the probability of receiving an organ offer. Other points will be awarded as in the current allocation policy (1 Other features of the current and new kidney allocation policies are compared in FactorPoints AwardedFor qualified time spent waiting1 per year (as 1/365 per day)Degree of sensitization (CPRA)0–202Prior living organ donor4Pediatric candidate if donor KDPI<0.351Pediatric candidate (age 0–10 yr at time of match) when offered a zero antigen mismatch4Pediatric candidate (age 11–17 yr at time of match) when offered a zero antigen mismatch3Share a single HLA-DR mismatch with donor1Share a zero HLA-DR mismatch with donor2Open in a separate windowThese points will be used to rank candidates in each of the categories listed in CPRA (%)Points0–19020–290.0830–390.2140–490.3450–590.4860–690.8170–741.0975–791.5880–842.4685–894.0590–946.719510.829612.179717.39824.49950.09100202.1Open in a separate window

Table 4.

Comparison of allocation concepts for current and new allocation policy

Nonlinear Trajectory of GFR in Children before RRT

GFR decline in patients with CKD has been widely approximated using linear models, but this linearity assumption is not well validated. We conducted a matched case-control study in children from the Chronic Kidney Disease in Children (CKiD) cohort ages 1–16 years with mild to moderate CKD to assess whether GFR decline follows a nonlinear trajectory as CKD approaches ESRD. Children (n=125) who initiated RRT (cases) during follow-up were individually matched by CKD stage at baseline and glomerular/nonglomerular diagnosis with children (n=125) who remained RRT-free when the corresponding case initiated RRT (controls). GFR trajectories were compared using log-linear and piecewise log-linear mixed effects models adjusted for baseline characteristics. From study entry to 18 months before RRT, GFR declined 7% faster among cases compared with controls. However, GFR declined 26% faster among cases compared with controls (P<0.001) during the 18 months before RRT. Nonlinearity in the rate of kidney function loss, which was shown in this cohort, may preclude accurate clinical prediction of the timing of RRT and adequate patient preparation. This study should prompt the characterization of predictive factors that may contribute to an acceleration of kidney function decline.GFR is a key measurement of kidney function, and the degree of GFR decline over time is a reflection of the severity of CKD progression. GFR decline has been approximated as linear or log-linear in most analyses of progression, an assumption that has been consistent with available data.^1–4 However, many studies rely on relatively short follow-up periods and few repeated measures. Given the convenience of assuming a linear GFR trajectory, which results from the ease of modeling and interpreting linear slopes, few studies have sought to validate the linearity assumption and explore the possibility of nonlinear GFR decline. However, nonlinearity in GFR decline has been observed in some epidemiologic studies,^5–7 and the implications on the risk for adverse outcomes have generated interest.⁸ A CKD cohort study in France found that about one half of its patients experienced nonlinear GFR decline during the last year before dialysis.⁵ A study by Li et al.⁹ used a flexible approach to model nonlinearity in GFR trajectories. Li et al.⁹ found evidence of nonlinear GFR trajectory behavior in adult patients with CKD, and furthermore, the probability of having nonlinear features in an individual trajectory was associated with known risk factors for CKD progression. O’Hare et al.¹⁰ found several distinct nonlinear patterns of GFR decline in the 2 years before dialysis initiation in Veterans Affairs patients.Clinical strategies and subsequent patient response to care could potentially benefit from new insights into the variable paths of progression in patients with CKD.^10,11 The question of whether characterizing the nonlinearity in the GFR trajectory can assist the identification of risk groups for outcomes, such as ESRD, remains unexplored. The implications on future outcomes of an increased rate of GFR decline could inform clinical decisions about screening frequencies, treatment, or preparation for RRT.The Chronic Kidney Disease in Children (CKiD) study is an ongoing cohort study of children with CKD who, at baseline, had an eGFR between 30 and 90 ml/min per 1.73 m³ and were ages 1–16 years. An end point of the study is RRT defined as transplant or dialysis. To determine whether trajectories of GFR accelerate before RRT, we nested a case-control study, in which cases were children observed to have received RRT and controls were children with CKD who remained RRT-free at the time when the corresponding case initiated RRT.There were 147 children who experienced RRT during follow-up. Each case was matched individually to an eligible control at the time of the case occurrence. The matching factors included baseline CKD stage, glomerular/nonglomerular diagnosis, and, through design, the amount of follow-up time from study entry. Matching was done without replacement, and 22 cases were excluded from the analyses, because no appropriate control was available. We used a random sequence to determine the order of matching. The analysis was, thus, based on 125 matched case-control pairs. Demographic and clinical characteristics of cases and controls at baseline are shown in CharacteristicsCases (n=125)Controls (n=125)Age, yr12.64 (9.23–14.53)12.33 (8.71–14.74)Sex (girls), N (%)38 (30.4)57 (45.6)Race (nonwhite), N (%)51 (40.8)36 (28.8)Urine protein/creatinine ratio1.74 (0.48–4.04)0.60 (0.26–1.76)Proteinuria, N (%) 0.2≤protein/creatinine ratio<256 (46.7)71 (59.7) Protein/creatinine ratio≥251 (42.5)23 (19.3)Baseline GFR^a32.21 (26.43–39.64)35.77 (27.86–43.78)Glomerular diagnosis, N (%)^a47 (37.6)47 (37.6)Open in a separate windowMedian (interquartile range) unless otherwise indicated.^aBaseline GFR and glomerular/nonglomerular diagnosis were matching factors.We compared the GFR trajectories using log-linear and piecewise log-linear mixed effects models, with the piecewise model specified to allow a change of the GFR slope at 18 months before RRT. Models were adjusted for baseline characteristics, including age, race, sex, and proteinuria status. ​and33 show the adjusted results from the mixed effects model analyses. The Akaike Information Criterion indicated that the piecewise log-linear model (including a spline or changing slope at 18 months before RRT) was a better fit to the data than the log-linear model that assumed a single slope across the entire period of observation. The GFR of cases declined at an adjusted rate of 6.8% per year (P <0.001) during the time before the spline in the earlier period of observation and 32.4% per year (P <0.001) after the spline within 18 months of RRT. The GFR of controls did not change significantly (P=1.00) before the spline and declined at an adjusted rate of 9.0% (P <0.001) after the spline. Although the rates of GFR decline comparing cases with controls differed by only 7% before the spline, the GFR of cases declined 26% faster (P <0.001) compared with controls within 18 months of RRT, suggesting an acceleration in the GFR decline during this period in the case group. This acceleration, which was quantified by the piecewise log-linear mixed effects model, could be clearly seen from the data and nonparametric smooth fits (Figure 1). The variability around the piecewise log-linear fit was assessed by the root mean square error (RMSE) and found to be similar between cases and controls (RMSE for controls=0.303; RMSE for cases=0.303), indicating an equally good fit. When a single slope was fit to the data, the GFR decline rate for cases was overestimated before the spline and considerably underestimated within 18 months of RRT. To assess whether the acceleration in decline was a function of the log scale, models were rerun with GFR in the natural scale. The results showed similar nonlinear patterns but a poorer model fit to the data.

Table 2.

The adjusted expected percent GFR change rates in the log-linear mixed effects model