Saturday, January 17, 2015

NSMC Inaugural Internship Class Announced

The Nephrology Social Media Collective (NSMC) is proud to announce the inaugural class of the 2015 internship. This is a new initiative with the goal to help foster individuals interested in finding their voice in social media.
The 2015 internship class is:

The collective consists of: Swapnil Hiremath, Joel Topf, Edgar Lerma, Kenar Jhaveri, Paul Phelan, Joshua Schwimmer, Matt Sparks, Jordan Weinstein. Interns will rotate through the various blogs (UKidney, RFN, NephJC, NephronPower) and projects (NephJC, NephMadness, NephPearls) and complete projects related to medical education and nephrology. Go to the NSMC Internship Blog to follow their progress. Congrats to the new intern class. This will be a fun and exciting year.

Monday, January 12, 2015

#NephWorkForce TwitterChat on Tuesday January 13 at 9pm EST

Join Mark Parker (@kidneyfuture), Chair of the ASN Workforce Committee on Tuesday, January 13th at 9pm EST for the discussion about the recently released ASN-GWU Nephrology Fellow Survey. This will be an excellent opportunity for everyone to discuss the recent trends and future of nephrology training. Joel Topf has a nice interview with Mark Parker and summarizes the results of the study over at PBFluids. Take a few moments on Tuesday night to watch the discussion and voice your opinion.

Thursday, December 25, 2014

Top nephrology-related stories of 2014

Another year has come and gone. 2014 featured some novel therapies for hyperkalemia and the notable failure of the SYMPLICITY-3 trial for renal denervation in resistant hypertension. ASN Kidney Week continues to grow and each year includes more and more social media. Its fun to be a part of it.

I also want to make a last minute honorable mention:

The new US Kidney Allocation System- This had been in the works for several years and was implemented on December 4th of this year. Some of the highlights of the new system are; 1. credit is given for time on dialysis prior to listing 2. patients with blood type B will be able to receive a blood type A2 kidney and highly sensitized patients will receive points to allow for more of a change for transplant. 3. an attempt to match kidneys based on "longevitiy". 4. increased sharing across the country. These changes are supposed to level the field so kidney transplants are allocated equitably across socioeconomic lines. It also attempts to find ways to offer more kidneys to patients that are highly sensitized while pair a kidney with the right donor. How this plays out across the US will be the true test.

Below are links to the last 4 years of the top nephrology stories polls

2010
2011
2012
2013

And now for the top 10 of 2014 and the 5th straight year of top nephrology stories on RFN...

10. POSEIDEN Trial showing fluid administration guided by LV end diastolic pressure reduced contrast-induced AKI (6%)- Coming in at number 10 this year was an interesting study reported in the Lancet. This was also covered during NephJC journal club as well. POSEIDEN was a single center study with ~400 patients with high risk for contrast-induced AKI undergoing coronary angiography. Patients were randomized to either control (0.9% NS 1hr before and 4hr after cardiac cath) or the intervention arm (the same 1hr pre NS dose but gave NS post cath based on LVEDP). The strategy was to maximize fluid administration while minimizing volume overload in order to prevent AKI. The patients in the intervention ended up getting more fluids and thus a reduction in AKI from ~16% to ~7%. How can these results be translated to other settings (such as CT scan with contrast)? Measures of LVEDP are more difficult to obtain when you are not performing a heart cath. My take away from this study is that patients at high risk for AKI need significant volume expansion and the more you can safely give the better. Strategies to minimize fluid overload will be needed to mitigate the risk of volume overload .

9. Gestational HTN or preeclampsia was more common in kidney donors (6%)- This was an interesting study reported in the NEJM in November. This group utilized a retrospective cohort of 85 healthy women in Ontario, Canada who underwent kidney donation who later became pregnant. These women were compared in a 1:6 ratio with 510 healthy non-donors in the general population who became pregnant. They reported that gestational hypertension or preeclampsia were more common in the donor population compared to healthy controls (11% versus 5%). This finding comes on the heals of several reports linking kidney donation to small by statistically significant increase in ESRD. Paul has a nice review on RFN. The caveat to each of these studies is that they are retrospective case-control studies. While kidney donation might confer some risk, the benefit conferred to the recipient in terms of quantity and quality of life are substantial.

8. Patiromer OPAL-HK trial for hyperkalemia (7%)- It is likely that patiromer and ZS-9 will be in a death match for potassium binding supremacy. The OPAL-HK trial (reported in NEJM) studied 243 patients with mild (av 5.3 mmol/l) and moderate-to-severe (av 5.7 mmol/l) hyperkalemia to treatment with patiromer (a nonabsorbed polymer that binds potassium in exchange for calcium). The study showed remarkable efficacy in lowering potassium in both groups. During the randomized withdrawal phase the majority of patients assigned to placebo had recurrent hyperkalemia. Safety signals include mild to moderate constipation. It will be interesting to see how this drug will stack up against ZS-9. Having 2 drugs in the fight could equal a win in the pricing war. We will see.

7. IgA Nephropathy GWAS implicates genes involved in helminth immune response (7%)- This was the surprise of the year in my opinion. This was a genome wide association study (GWAS) in IgA Nephrology and was reported in Nature Genetics. This group performed GWAS on ~2,700 patients with biopsy proven IgA Nephropathy and ~3,900 controls of European and Chinese ancestry. They found 6 new associations, 4 in ITGAM-ITGAX, VAV3 and CARD9 and 2 new independent signals at HLA-DQB1 and DEFA. "Most loci were either directly associated with risk of inflammatory bowel disease or maintenance of the intestinal epithelial barrier and response to mucosal pathogens. The risk alleles were highly suggestive of helminth diversity adaptation". So it appears that yet another kidney disease could be linked to infectious pathogens (see APOL1 and Trypanosoma brucei rhodesiense).

6. HALT-PKD Trials of low BP target and ACEi/ARB combo (10%)-  The much awaited dual release of the HALT-PKD trials were presented and simultaneously reported in NEJM at kidney week this year. HALT-PKD consisted of 2 trials: the first study was termed "early" in which patients had preserved renal function and the other termed "late" in which patients had a decline in renal function. They both tested dual ACEi/ARB blockade and the "early" study had an additional focus on blood pressure reduction. 120/70 to 130/80mmHg (Standard BP) and the low blood-pressure target group was quite low at 95/60 to 110/75 mm Hg (Low BP). Both the "early" and "late" trial dual ACEi/ARB combo groups had no additional benefit over monotherapy. However the "low BP" arm of the "early" study had benefits in LVH, kidney size and urinary albumin excretion at the expense of dizziness and light-headedness. However, this did not confer eGFR benefit. How these results would translate into clinical benefit is uncertain. It is clear that combo ACEi/ARB therapy is done in this patient population as it is for diabetic kidney disease (see Nephron-D). Will it be feasible to push blood pressure this low in patients with PKD. Without changes in eGFR or another solid end-point my guess is no.

5. Anti-Phospholipase A2 receptor assay licensed for commercial testing (13%)- Another exciting development in the field was the news that the anti-phospholipase A2 receptor assay gained clearance for commercial use by the FDA. This test has the potential to really help guide therapy in patients with membranous nephropathy. A recent paper in CJASN and covered in CJASNeJC discusses the potential application of this assay in membranous. Much is still to be learned about how the measurement of anti-PLA2R will affect treatment but this could be a much needed non invasive insight into the disease process. 2015 will surely be filled with more research into the topic. Some questions that remain to be answered. 1. Would you re-initiate immunosuppression if titers increase in absence of worsening proteinuria or worsening renal function in a patient with biopsy proven membranous? 2. Could this test bypass invasive biopsy in select patients? 3. How often should you measure titers? 4. Could anti-PLAR2 offer another index to gauge prognosis and potentially lengthen or intensify therapy?

4. ZS-9 trials for hyperkalemia (14%)-  Coming in a number 4 is ZS-9. Another "potassium buster" drug for hyperkalemia. The company ZS Pharma reported the results of 2 trials, the HARMONIZE trial in JAMA and a phase 3 trial in NEJM. Both these studies showed efficient potassium lowering versus placebo and rebound once the drug is discontinued. NephJC hosted a lively twitter discussion about the HARMONIZE trial. Concerns for how ZS-9 will be tolerated long term and why it was compared to placebo and not kayexalate or diet. Also, in the high dose group more patients had peripheral edema. ZS-9 has the potential to really change the landscape of hyperkalemia treatment, but long term safety data is needed. The other positive from all of the hyperkalemia trials is that the medical community is finally actually starting to study this.

3. SYMPLICITY-3 trial for renal denervation in resistant HTN (19%)-  Probably the biggest disappointment of the year was the SYMPLICITY-3 trial. An introduction isn't even needed as the results have been widely publicized and critiqued. You can read a summary from NOD Kidney Konnection. The SYMPLICITY-3 trial was performed in response to the FDA who requested a sham procedure group be used as a control against renal denervation in patients with resistant hypertension. The results have reverberated across the medical community. Both the sham and denervation groups had impressive drops in blood pressure by ~15 mm Hg. This was the problem. What went wrong? Was it ineffective denervation? Was it a powerful placebo effect? Was it the Hawthorne effect? Bottom line is this trial didn't achieve a significant benefit in renal denervation. Questions remain as to the effectiveness of the actual denervation technique. Will industry put money back into this technology after the results of SYMPLICITY-3? We will see.

2. JNC8 Hypertension Guidelines published in JAMA (22%)- Coming in at number 2 and the winner of NephMadness 2014 is JNC-8. This was an honorable mention in 2013 as it was published online after the end of the year poll. These guidelines were much anticipated and sometimes referred to has JNC-late. JNC-8 attempted to answer questions using randomized controlled data while carefully adjudicating the available evidence. JNC-8 is far narrower in scope than JNC-7 and was not a “how to” document. JNC-8 explicitly states places where we do not have evidence for and what we really need to know. Lastly, the document simplifies the blood pressure goals. Some have expressed concern about raising the systolic blood pressure target in patients over 60 (without DM or CKD) from 140 to 150 mm Hg. For a review of the major changes with JNC-8 see the NephMadness champion post.

1. Perivascular Gli1+ progenitors contribute to myofibroblast pool leading to fibrosis in multiple organs including kidney (57%)- Coming in at number 1 this year is an interesting report from Cell Stem Cell. I'll have to add an asterix to this win though. It appears the stem cell community really got the word out to vote for this one. It is still deserving of a top story of the year as it paves a new paradigm in the pathogenesis of fibrosis. In a real tour de force Kramann et al not only define this process in kidney fibrosis but also look at lung, liver and heart fibrosis. They utilized lineage tracing to show that tissue-resident (not circulating) Gli1+ cells (pericytes) proliferate after kidney, lung, liver, or heart injury to generate myofibroblasts. This has been a hot topic and covered in detail in this years NephMadness. Next, they genetically ablated these cells and induced organ injury in various mouse models. They showed that kidney and heart fibrosis was substantially less compared to controls. These are exciting studies that have the potential to open new therapeutic targets for chronic kidney disease and other chronic disease such as cirrhosis, lung fibrosis and heart failure. This could be a candidate for the next basic science NephJC discussion. An exciting development and it will be fun to watch where this goes.

Another busy and exciting year in the world of nephrology in 2014. Thanks to all of the contributors and readers for keeping the site fun, interesting and educational.

Thanks for supporting RFN and happy holidays. Can't wait to see what 2015 has in store!

Tuesday, December 23, 2014

Tacrolimus Formulations

Tacrolimus comes in oral, intravenous and topical formulations. Prograf is the most commonly used oral tacrolimus formulation and is dosed twice daily.

Prograf pharmacokinetics 

Absorption:
Absorption occurs in the small intestine.
Drug levels reach a maximum concentration in 1 to 2 hrs.
Tacrolimus is poorly soluble and oral bioavailability is about 11 to 20%.

Metabolism:
Cytochrome P450 3A4 metabolizes tacrolimus to at least 10 metabolites, some of which retain significant activity. Biliary excretion is the route of elimination for these tacrolimus metabolites. Gastrointestinal tract mucosal cells also contain CYP P450 3A4 activity and contribute significantly to metabolism.

Elimination:
The terminal elimination half-life of tacrolimus is approximately 12 hours. Elimination is prolonged in hepatic dysfunction.

Poor solubility, first pass metabolism, small bowel CYP450 metabolism and p-glycoprotein activity (pumps drug back into the bowel lumen) all cause reduced oral bioavailability of tacrolimus. Low oral bioavailability is a common pharmacological problem and 30% of marketed PO drugs have poor solubility defined as water solubility below 20ug/ml. An oral drug can only be absorbed once dissolved.

LCP-Tacrolimus 
LCP-Tacrolimus was designed to achieve greater bioavailability by increasing the solubility of tacrolimus. LCP is Life Cycle Pharma, a Danish company now trading as Veloxis Pharmaceuticals. This new tacrolimus formulation uses ‘Meltdose’ technology to achieve this goal. LCP Meltdose technology works by decreasing the particle size of the drug to the molecular scale thus increasing particle surface area. Increased surface area increases solubility. Tacrolimus is heated into a ‘liquid like’ state and then atomized and sprayed onto an inert particle carrier. This then solidifies in a state of ‘solid solution’ into granulates and is compressed into tablets. These granulates retain their particle sizes and dissolution characteristics. Thus, once delivered to the small bowel these very small particles of tacrolimus go into solution easily and are better absorbed.

Phase 2 trials of LCP-tacrolimus in de novo kidney transplant patients have shown a more consistent concentration profile, increased bioavailability of about 30% and reduced peak to peak and peak to trough variation compared with bid tacrolimus (Prograf).


This month in AJT
Budde et al report on a phase III study of LCP-Tacrolimus vs bid tacrolimus in de novo kidney transplants.

This was a worldwide, double blind, double-dummy, randomized study in 543 de novo kidney transplants comparing LCP-tacrolimus with Prograf (bid tacrolimus). It was designed as a non-inferiority trial with a primary endpoint of treatment failure at 12 months (death, graft failure, biopsy-proven acute rejection).

More LCPT patients were in ‘target range’ (6-11) after initial doses. Trough/dose ratio increased (reflecting better absorption) over time with LCPT and was statistically higher than Prograf. Trough levels were similar. Total daily doses were lower for LCPT at 1 and 12 months and the cumulative dose over the whole study was 14% lower for LCPT.

The overall incidence of treatment failure was 18.3% for patients in the LCPT group and 19.6% for patients in the tacrolimus twice-daily group. The treatment difference (95% CI) was −1.35% (−7.94% to +5.27%), well below the noninferiority margin of 10%.

There were no significant differences in adverse events between groups. Interestingly 97% of each group had an AE over the 12 months the most common being diarrhea, anemia, UTI, hypertension and constipation. There was a numerical trend towards more NODAT with LCPT that may be explained by higher LCPT exposure in the first 3 weeks. There was a trend towards a smaller rise in lipid abnormalities in the LCPT group.

This was a well-powered and well conducted trial. LCP-Tacrolimus is safe and as efficacious as Prograf. Cumulative doses are lower and therapeutic range was reached earlier and is more likely to remain stable. This is a promising once daily preparation, however, pricing is likely to determine whether this formulation becomes standard of care in kidney transplantation.

What about Advagraf/Astagraf?
 

Advagraf was approved for the European market in 2007 and the FDA approved Astagraf in 2013. Advagraf contains the same active drug, tacrolimus, as Prograf. Advagraf contains ethylcellulose, which controls water penetration and changes its dissolution properties. The drug also contains a hypromellose protective coat. Both these factors cause the active drug to be released more slowly and further along the GI tract.

In mostly industry sponsored trials Advagraf showed lower peak drug concentrations but equivalent AUC(0-24) and Cmin(trough) concentrations when compared to Prograf. Thus, a 1:1 conversion is suggested in the package insert. However, subsequent experience with Advagraft has demonstrated lower Cmin values and high inter-individual variability leading to the need for higher Advagraft dosing and difficulty with trough interpretation. Furthermore, a phase III study in de novo kidney recipients has shown higher rates of acute rejection with Advagraf, possibly explained by the differing C(max) values achieved with the two preparations. Biopsy-proven acute rejection rate at 24 weeks (primary endpoint, per-protocol analysis) was 15.8% for Tacrolimus BID versus 20.4% for Tacrolimus QD (p = 0.182; treatment difference 4.5%, 95% confidence interval-1.8%, 10.9%) just outside the prespecified 10% noninferiority margin.

In Europe where this formulation has been approved since 2007 use of the drug is still minimal. It will remain to be seen whether the same trend occurs in the US. Experiences so far make it unlikely that this formulation will become first line therapy in kidney transplantation.

Wednesday, December 17, 2014

The future of nephrology training: A fellow's perspective


Much is being said about the steady and dramatic decline in applications to nephrology training programs. The recent match shows a continuation of this trend: 67.9 percent of offered positions filled, leaving 50% of US programs unfilled on match day. The writing is on the wall: the number nephrology training positions needs to shrink. However, there is going to be no agreeable and easy way to decide which program should reduce size or close its doors. Should we let programs decide what to do individually or should we defer decisions to some governing body? Should programs that go unfilled be forced to reduce numbers or shut down, the so-called “survival of the fittest” model? Or should we create an algorithm to decide how to reduce positions more equitably?

Tejas Desai posted a paper that describes a more equitable model by allocating training positions according to ESRD prevalence in US states/jurisdictions. In his model, he estimates that fewer jurisdictions would reduce in size under an equitable model compared to the “survival of the fittest” model. An “equitable” process using an algorithm is attractive because it would distribute the allocation of positions based on some objective measure, like ESRD prevalence. This would benefit training programs that have a harder time recruiting. An equal proportions model may “share the pain” so certain regions are not affected disproportionately than others, thus retaining program directors and training infrastructure for when applications rebound (assuming they will).

As a fellow in training, I worry that any algorithmic approach to this problem will be focused too heavily on the needs of the training program and not the applicants. In that sense, the “survival of the fittest” model is more oriented to a fellow’s actual needs. Program desirability is likely driven by a mix of perceived program quality and factors unrelated to quality like geographic region, cost of living, or job opportunities for spouses, for example. In this thin market with so few applicants, program quality is not as much of a distinguishing factor. I think it’s safe to assume that fellows will work hard everywhere and that training program directors and faculty truly care about fellow education at all programs. In that sense, these factors not directly related to program quality will likely influence an applicant’s decision. I think it’s safe to assume that if these factors matter today, then they will likely be valued again by applicants in future years. If we are truly on board with a mission to increase interest in nephrology, we can start by paying attention to where people want to train and why. The NRMP Match rank list is a reasonable way to understand this.

Simply allocating positions based on ESRD prevalence or any other equitable algorithm favors at-risk programs, but it does not take into account trainee preferences. Many trainees desire specialized training in transplantation, glomerulonephritis, interventional nephrology, clinical research, basic science research, medical education, quality improvement, or health informatics. Some programs are more desirable because they can provide these individualized opportunities for career development. Access to one of these programs might be more limited through an algorithmic approach to training position allocation. Who knows, if word got out that positions have been weighted to regions based on ESRD prevalence alone, it may perpetuate the stereotype among residents that nephrologists are nothing more than dialysis technicians, missing the breadth and depth of actual practice. If fewer positions are made available in highly desirable programs, then it would be wrong to assume an applicant will be just as happy or available to train elsewhere. Given that some applicants desire certain locations due to factors like job opportunities for spouses, reducing positions in those desirable locations may be enough to convince the applicant to choose an alternative career like hospital medicine for example, where opportunity is abundant.

The nephrology community should remember that the primary issue is lack of interest. Efforts to increase interest should be at the center of the discussion. Deciding how to reduce positions will be controversial and it will be tough to find agreement. Maybe the best solution will need to consider everyone’s needs equally: considering applicant choices/preferences and also minimizing program dissolution. One model for position allocation could be based on an incentive for producing more nephrology applicants: You get fellowship training positions if you contribute to the applicant pool by mentoring/developing the residents and students at your institution. This would actually address the underlying problem wouldn't it? I applaud Dr. Desai for starting this conversation. Even if some final complex algorithm is required, I just hope that applicant and fellow preferences are not ignored.

Friday, December 12, 2014

Effects of Intensive Low-Salt Diet Education on Albuminuria: CJASN e-Journal Club

This month’s CJASN e-journal club was hosted at the Department of Nephrology at the Royal Infirmary of Edinburgh. It discussed a trial designed to investigate the efficacy of an intensive low salt diet intervention (weekly 30 minutes phone feedback by a dietary consultant) on albuminuria in non-diabetic hypertensive patients already on an ARB. This study is an open-label, case-control, randomized clinical trial based in South Korea. 

It is important to note that selected patients were a relatively healthy, homogenous population with good blood pressure control and an already low urinary sodium excretion. Very few were active smokers and many took regular exercise. All RAAS antagonists and diuretic agents were stopped for an 8 week run in and blood pressure was controlled with alternative agents. At week 0, Olmesartan was then commenced, and at 8 weeks, subjects were randomised to control or intensive education groups. 
The primary endpoint was the decrement in albuminuria by week 16 and was reached in the intensive salt reduction group. They demonstrated a significant reduction in albuminuria (278 mg/d to 178 mg/d) compared to the conventional therapy group (258 mg/d to 231 mg/d). There was a greater reduction in urinary sodium excretion in the intensive education group than the conventional group, but no change in blood pressure or renal function. In subgroup analyses, the authors examined those that received a reduction of > 25% of their dietary salt and those who did not, irrespective of treatment group. Notably, only 60% of those who achieved this reduction came from the intensive group. 

Overall this is an interesting, well-performed study which successfully demonstrates that lower salt excretion correlates with lower albuminuria. This occurred despite no effect on BP in a cohort with already excellent BP control. It may be better to interpret this as a “proof of concept” that salt restriction in humans could influence albuminuria. For clinical practice however, there are issues around the generalizability of these findings to everyday patients, given this was a highly selected, compliant group of patients. Also, as we know in the nephrology community from previous trials, an improvement in a relatively soft endpoint like albuminuria will not necessarily translate into improvements in renal/cardiovascular events or mortality. 

Check out the full text of the paper, our complete post and discussion over at the CJASN eJC website.

Authored by Eoin O’Sullivan & Paul Phelan

Wednesday, December 3, 2014

SHROOM3, Making sense of GWAS risk alleles

In this months edition of JCI a group led by Dr B Murphy from Icahn School of Medicine at Mount Sinai describe a beautiful set of experiments that explain the mechanism by which the CKD and eGFR risk allele rs17319721 causes chronic kidney allograft damage.

The single nucleotide polymorphism rs17319721 is in intron 1 of a gene called SHROOM3. The risk allele A (major allele G) of rs17319721 was found in large GWAS studies of European ancestry to be associated with GFR (p=1*10−12), incident CKD (p=0.005) and GFR in type 2 diabetic patients (P= 3.18E-03). The risk allele, A, frequency is about 40% in caucasian populations but is less frequent in non-caucasian populations.

The authors decided to investigate the effect of rs17319721, the SHROOM3 risk genotype, on kidney allograft fibrosis and chronic allograft nephropathy (CAN). Furthermore, they sought to determine what role, if any, SHROOM3, plays in allograft fibrosis. The risk locus was genotyped in over 500 allograft recipients and 500 allograft donors from the GoCAR transplant cohort. Also, SHROOM3 transcript levels in 3month protocol allograft biopsies were recorded in some of these patients. Donor genotype carrying one risk allele A (A/A or A/G) was associated with higher 3month SHROOM3 expression levels compared to the normal donor G/G genotype. Interestingly, correlation occurred only in Caucasian donors when analyzed separately and there was no association with the recipient risk genotype.

The authors then looked at 12month allograft GFR and chronic allograft dysfunction index score at 12 months (CADI-12). 3month SHROOM3 expression levels were inversely related to 12 month GFR, predictive of CADI-12 and were predictive of worsening CADI score (3m to 12m)(termed ‘progressors’). These associations were not found in non-Caucasian donors.

To assess whether 3M SHROOM3 levels could predict CAN they generated logistic models that included recipient age, sex, race, AR and CIT with or without 3M SHROOM3 levels to predict 12M CADI ≥2 or 3-12M CADI change (ΔCADI) of ≥2. AUC for prediction of high CADI-12 and ΔCADI were improved in each subgroup when SHROOM3-3M level was added. For Caucasian donors AUC for ‘progression’ was 0.81 with SHROOM3 and 0.74 without SHROOM3. Furthermore, the A allele in the donor was associated with greater risk of CADI-12≥2 in all allografts (OR 1.98; CI, 1.10–3.59), indicating a higher risk of CAN with the risk allele.

This work demonstrates that the A risk allele (rs17319721) in donors is associated with higher 3M SHROOM3 levels and increase risk of CAN. Also, 3M SHROOM3 levels predict CAN and 12M GFR.

So what is the mechanistic consequence of having the A allele vs the G allele? rs17319721 is located in a transcription factor binding motif. The authors found that the transcription factor TCF7L2 binds more strongly to this motif when A is present vs when G is present. Wnt agonist increased TCF7L2/β-catenin complex binding to the A allele binding site but not the G allele site. TGF-β1 is a known key growth factor regulating renal fibrosis. The authors found that TGF-β1 induced increases in SHROOM3 expression via the Wnt/β-catenin/TGF-β1 pathway in renal tubular cells.

Then they showed SHROOM3, in turn, enhances the TGF-β1/SMAD3–induced expression of profibrotic genes including CTGF, Vimentin, and Collagen IV (downstream targets of TGF-β1/SMAD3 signaling) and these genes were significantly upregulated in allografts within the highest quartile of SHROOM3 expression. Finally the authors verified these data in a mouse model of fibrosis.

Taken together, this data suggest an increased profibrotic program in the presence of the enhancer function of the risk allele and/or increased SHROOM3 expression. This schema is illustrated below.

This paper nicely describes the mechanism of action conferred by a single risk allele found in large GWAS studies. Until recently there has been little data to explain the relevance of the many risk SNPs described in GWAS studies. Without an understanding of the mechanism through which these SNPs confer disease there can be no progress towards identifying potential therapeutic targets. This study has identified SHROOM3 as a potential therapeutic target for chronic allograft nephropathy.

Monday, December 1, 2014

Vote for the Top Nephrology Stories of 2014

This is the 5th year RFN has hosted the Top Nephrology Stories of the year poll. This is an attempt to look at the year in nephrology voted by the readers of RFN. Take a few moments and vote for any of the stories you feel are worthy of making the top 10 list. You can vote for as many as you wish. Write a quick blog post about a story you think deserves the vote. If we missed anything please feel free to comment below. Note, the story must be published after the year end poll of 2013.

Please go to the right hand side -----> of the RFN page and make your selection until Dec 12th. Results will be posted on Dec 25, 2014

Below contains links to each of the stories for more information.

JNC8 Hypertension Guidelines published in JAMA (this was published online after the poll last year)

ZS-9 trials for hyperkalemia in JAMA and NEJM (Nov 2014)

Patiromer OPAL-HK trial for hyperkalemia in NEJM (Nov 2014)

The PREDIAN Trial: pentoxifylline for diabetic kidney disease in JASN (June 2014) 

SYMPLICITY-3 trial for renal denervation in resistant HTN in NEJM (March 2014)

Mesoamerican nephropathy continues to unfold

Dendritic cell isoketals activate T cells and promote HTN in JCI (October 2014)

Sustainable Growth Rate legislation in March 2014 pushed inclusion of oral only meds (phos binders) in ESRD out of bundle until 2024

α–Intercalated cells defend the urinary system from bacterial infection in JCI

Peritoneal dialysis solution shortage 

IgA Nephropathy GWAS implicates genes involved in helminth immune response in Nature Genetics (Sept 2014) 

Anti-Phospholipase A2 receptor assay licensed for commercial testing

Co-trimoxazole and sudden death in patients receiving RAS inhibitors in BMJ (Oct 2014)

Identification of thrombospondin type-1 domain-containing 7A in idiopathic membranous nephropathy in NEJM (Nov 2014)

Perivascular Gli1+ progenitors contribute to myofibroblast pool leading to fibrosis in multiple organs including kidney Cell Stem Cell (Nov 2014)

HALT-PKD Trials of low BP target and ACEi/ARB combo in NEJM (Nov 2014) 

CORONARY Trial of on-pump versus off-pump CABG and subsequent CKD (June 2014)

POSEIDEN Trial fluid administration guided by LV end diastolic pressure in Lancet (May 2014)

Gestational HTN or preeclampsia was more common in kidney donors in NEJM (Nov 2014)

Please go to the right hand side -----> of the RFN page and make your selection until Dec 12th. Results will be posted on Dec 25, 2014


Wednesday, November 26, 2014

A cause and a cure of hyperkalemia? The next #NephJC

There has been a flurry of publications in the field of hyperkalemia with 3 separate trials of oral potassium binding agents within a week of each other (Sodium Zirconium in JAMA, and NEJM and Patiromer in NEJM) and a potentially related observational trial on the risks of co-trimoxazole in patients on RAAS blockade in the BMJ. With all that reading to get through, the next NephJC on Tuesday Dec 2nd will be a double whammy. We will look at the HARMONISE trial of ZS-9, and a large study of co-trimoxazole and potential associations. 

Trim-Sulfa and Sudden Death in patients receiving inhibitors of renin-angiotensin system. 

The first paper for discussion is a large, Canadian, case control series, by the Canadian Drug Safety and Research Effectiveness Network, published in the BMJ. The hypothesis is the risk of sudden death in patients on RAAS blockade is higher following administration of specific antibiotics rather than amoxicillin. To answer their question, they searched 17 years of records representing over 1.6 million patients. They identified 39,879 with a label of sudden death and a subsequent group of 1,027 that had a prescription for the target antibiotics in the 7 days prior to dying. 
The authors write: “In the primary analysis, co-trimoxazole was associated with a significantly increased risk of sudden death within seven days relative to amoxicillin (OR 1.8 C.I 1.5-2.24)” Ciprofloxacin was associated with a somewhat lower risk of sudden death. I found it strange that norfloxacin, which has similar QT prolonging properties to ciprofloxacin, had had no such risk. The authors speculate this observed association may be due to trimethoprim’s activity as an ENaC antagonist. There are a number of important limitations to consider. There was no indication for antibiotics recorded. Also, the cases and controls had some important differences in terms of diuretic use and co-morbidities. Only 8.2% of the cases had renal disease, the stage of which was unclassified. The authors can only speculate about a possible mechanism involving hyperkalaemia as no K levels were obtained for any of these patients, nor any ECG to help explain the effect of ciprofloxacin. 

Harmonise: Effect of Sodium Zirconium Cyclosilicate on Potassium Lowering for 28 Days Among Outpatients With Hyperkalemia. 

ZS-9 is a zirconium silicate, a non-absorbable potassium binding agent. It is an inorganic cation exchanger crystalline with the capacity to bind both potassium and ammonium in the GI tract. Its creators tout its non-absorbable nature as the key to minimising systemic side effects. HARMONISE is a phase 3, multicenter, randomized, double-blind, placebo-controlled trial spanning 44 centres. Inclusion criteria was simply a serum K of ≥ 5.1 on 2 occasions. Initially, 258 patients who met eligibility criteria were given ZS-9 10g three times daily. If they achieve normokalaemia within 48 hours, they were then randomized to a placebo, or increasing doses of ZS-9 once daily. The mean eGFR was 46 ml/min/1.73m2 and no ESKD patients are represented. 
Did it work? The short answer is yes. ZS-9 had a reasonable rapid rate of onset and within 2 hours, serum Potassium has dropped by −0.4 mEq/L (95% CI, −0.5 to−0.4) and was - 1.1 mEq/L by 48hours. Encouragingly, it seems generally well tolerated with some edema and hypokalemia as the doses increased. In conclusion, this is a well executed phase 3 trial and ZS-9 has potential to be a well tolerated and predictable treatment option for hyperkalemia. The authors quite rightly point out we still have no data beyond 4 weeks, nor have we any meaningful endpoint such as mortality or hospital admissions. It is an encouraging study none the less, and should lead to FDA approval and another tool in our kit.

Full post can be seen at www.nephjc.com 

Authored by Eoin O'Sullivan.

Creatininase

There was a fascinating case published a couple of months ago in the American Journal of Medicine. I have a particular interest in this case as it was my clinic mentor, Julian Seifter, who made the diagnosis and published the case. I have waiting for a long time to write a post about it but couldn't until the paper came out.
The case is a 50yr old man with a history of CKD, quadraplegia and an ileal conduit who was being investigated for CKD. His serum creatinine was 3mg/dl and a creatinine clearance was done to estimate his GFR. His urine creatinine concentration was 175mg and his calculated creatinine clearance was only 3 mls/min. At this point, RRT was recommended and the suggestion was that his serum creatinine overestimated his GFR because of reduced muscle mass. 
However, because the urine creatinine still seemed inordinately low and he had no symptoms, an inulin clearance was done which revealed a true GFR of 21 ml/min. What could explain this discrepancy?
A urine culture grew diphtheroids, staphlococcus and streptococcus. Although creatinine, once it is produced in the muscle cannot be metabolized in humans, some bacteria produce creatininase and as a result are able to break it down. Corynebacterium is a diphtheroid that has been associated with the production of creatininase. Dr. Seifter suspected that there was a creatininase-producing bacterium in the ileal conduit that was metabolizing the creatinine leading to a falsely low creatinine clearance. To confirm this, he took a sample of the patient's urine, added a known quantity of creatinine and incubated it for 24 hours at 20 degrees. The results are shown in the figure below.


Our GI tract has some creatininase-containing bacteria but under normal circumstances, the amount of creatinine clearance that they contribute is negligible - less than 2 ml/min GFR equivalent. However, in individuals with advanced CKD, both the relative and total clearance contributed by these GI bacteria increases such that in people with a GFR <10 the contribution of gut clearance can be as high as 4ml/min or approximately 50%. The opposite can also occur. The highest serum creatinine I ever saw was in a 50yr old woman with inflammatory bowel disease. She weighed 40kg but her admission creatinine was 38mg/dl. Despite this, she felt relatively well. She had previously undergone multiple bowel resections and had almost no functional bowel remaining. As a result, she had no gut clearance of creatinine and no upper limit to her serum creatinine concentration.

One final note, the urea clearance was not useful in the above patient either - his urine also contained urease -  the clue to this was a very high urine pH (>9) in the presence of a mild metabolic acidosis and no history of RTA.

Thursday, November 20, 2014

EDELMAN IS THE ROOT OF ALMOST ALL GOOD IN NEPHROLOGY

Almost all the formulas we use in the management of the disorders of water homeostasis are derived from the Edelman equation. I am presenting where these formulas come from for the math aficionados.

Edelman equation

·         Original Edelman equation (J Clin Invest. 1958;37:1236-56):
[Na+] = {1.1 x (Nae + Ke)/TBW} – 25.6
Where [Na+] = plasma sodium concentration, Nae=total body exchangeable sodium, Ke=total body exchangeable potassium, TBW = total body water.

·         Simplified Edelman equation: [Na+] = (Na + K)/TBW
·         [Na+] x TBW = Na + K
·         Na + K = [Na+] x TBW

Calculating Free Water Deficit (FWD)

Method #1 (Using baseline weight, certainty about what % of body weight is water)

1.       Assuming only pure water has been lost, the total body sodium and potassium remain constant so the total body sodium and potassium at baseline (Na + K)baseline and the total body sodium and potassium after water loss (Na + K)current are equal:

·          (Na + K)baseline = (Na + K)current

2.       Total body sodium and potassium can be expressed as sodium concentration ([Na+]) multiplied by total body water (TBW):

·         [Na+]baseline x TBWbaseline = [Na+]baseline x TBWcurrent
·         TBWcurrent = [Na+]baseline x TBWbaseline/[Na+]current … (1)

3.       Free water deficit can be expressed as:

·         FWD = TBWbaseline – TBWcurrent … (2)

4.       Then replacing (1) in (2):

·         FWD = TBWbaseline – ([Na+]baseline x TBWbaseline)/[Na+]current
·         FWD = TBWbaseline x (1 – [Na+]baseline/[Na+]current)

5.       If [Na+]baseline is considered normal at 140 mEq/L then:

·         FWD = TBWbaseline x (1 – 140/[Na+]current)

Method #2 (Using current weight, uncertainty about what % of body weight is water)

1.       Assuming only pure water has been lost, the total body sodium and potassium remain constant so the total body sodium and potassium at baseline (Na + K)baseline and the total body sodium and potassium after water loss (Na + K)current are equal:

·         (Na + K)baseline = (Na + K)current

2.       Sodium and potassium masses can be expressed as sodium concentration ([Na+]) multiplied by total body water (TBW):

·         [Na+]baseline x TBWbaseline = [Na+]current x TBWcurrent
·         TBWbaseline = [Na+]current x TBWcurrent/[Na+]baseline … (1)

3.       Free water deficit can be expressed as:

·         FWD = TBWbaseline – TBWcurrent … (2)

4.       Then replacing (1) in (2):

·         FWD = [Na+]current x TBWcurrent/[Na+]baseline – TBWcurrent
·         FWD = TBWcurrent x ([Na+]current/[Na+]baseline - 1)

5.       If [Na+]baseline is considered normal at 140 mEq/L then:

·         FWD = TBWcurrent x ([Na+]current/140 - 1)

Calculating Rate of Infusion of Hypertonic Saline

Method # 1: Na deficit formula

Deriving Na deficit formula

1.       Na deficit = Nagoal – Nacurrent … (1)

2.       Since Na + K = [Na+] x TBW, then Na = [Na+] x TBW – K … (2)

3.       Replacing (2) in (1)
·         Na deficit = TBWgoal x [Na+]goal – Kgoal – {TBWcurrent  x [Na+]current – Kcurrent}

4.       Assuming TBW and K remain constant, so TBWgoal = TBWcurrent, and Kgoal = Kcurrent, then TBW = TBWgoal = TBWcurrent and K is cancelled out from equation:

·         Na deficit = TBW x [Na+]goal – TBW x [Na+]current
·         Na deficit = TBW x ([Na+]goal – [Na+]current)

5.       Since now we aim for an increase in [Na+] of 6 mEq/L, so [Na+]goal – [Na+]current = 6 mEq/L then:

·         Na deficit = TBW x 6 mEq/L

Calculating volume of infusate

·         Volume of infusate = Na deficit x (1000 mL/513 mEq)

Calculating rate of infusion

·         Rate of infusion = volume of infusate/24h

Method #2: Adrogue-Madias formula

Deriving Adrogue-Madias formula

1.       [Na+] = (Na + K)/TBW … (Edelman equation)

·         [Na+]current = (Nacurrent + Kcurrent)/TBWcurrent
·         [Na+]current x TBWcurrent = (Nacurrent + Kcurrent) … (1)

2.       [Na+]goal will be the new [Na+] that results when we administer 1L of an infusate containing Nainfusate and Kinfusate, then:

·         [Na+]goal = (Nacurrent + Kcurrent + Nainfusate + Kinfusate)/(TBWcurrent + 1) …(2)

3.       Substracting [Na+]current from both terms of equation (2), then:

·         [Na+]goal – [Na+]current = (Nacurrent + Kcurrent + Nainfusate + Kinfusate)/(TBWcurrent + 1) – [Na+]current

4.       But [Na+]goal – [Na+]current is the same as change in [Na+], then:

·         Change in [Na+] = (Nacurrent + Kcurrent + Nainfusate + Kinfusate)/(TBWcurrent + 1) – [Na+]current
·         Change in [Na+] = {(Nacurrent + Kcurrent + Nainfusate + Kinfusate) – (TBWcurrent + 1) x Nacurrent}/(TBWcurrent + 1)
·         Change in [Na+] = {Nacurrent + Kcurrent + Nainfusate + Kinfusate – ([Na+]current x TBWcurrent –[Na+]current)}/(TBWcurrent + 1) … (3)

5.       Replacing equation (1) in (3), then:

·         Change in [Na+] = {Nacurrent + Kcurrent + Nainfusate + Kinfusate – (Nacurrent + Kcurrent) - [Na+]current}/(TBW + 1)

6.       Cancelling out Nacurrent + Kcurrent then:

·         Change in [Na+] = {Nainfusate + Kinfusate - [Na+]current}/(TBWcurrent + 1)

Calculating volume of infusate

·         Volume of infusate = {1000 mL x (Change in [Na+])goal}/(Change in [Na+])
·         Volume of infusate = {1000 mL x 6 mEq/L}/(Change in [Na+])

Calculating rate of infusion

·         Rate of infusion = volume of infusate/24h