Diabetes and CKD - Pitfalls: Cystatin C

Cystatin C has been proposed as an alternative marker of kidney function and studies have shown that CyC is a better predictor of mortality that serum creatinine. Although, when first introduced, it was thought that CyC was not influenced by factors apart from renal function, this assumption has been questioned in the recent past.

CyC is a 13 kDa cysteine protease inhibitor that is produced by all nucleated cells. It is freely filtered at the glomerulus and then catabolized in the proximal tubule such that very little appears in the urine. CyC levels are affected by renal function but also independently influenced by age, gender, BMI, fat mass, triglycerides and the presence of diabetes. Interestingly, these are all components of the metabolic syndrome.

In 2011, a paper was published in Diabetologia that found that elevated levels of CyC were associated with an increased incidence of type II diabetes. The thought was that CyC was potentially involved in the pathogenesis of diabetes. In July, a paper was published in NDT that shed a bit more light on this issue. The authors reported the results of a 3-year study of French adults in whom the incidence of diabetes was low. In this study, in common with previous research, CyC predicted incident diabetes. However, when stratified by BMI, CyC predicted incident diabetes only in participants with a BMI >25 at baseline.

So what is the explanation for this? CyC secretion has been shown to be 2-3 times higher in obese patients than in non-obese patients. CyC is also highly expressed in subcutaneous adipose tissue. Data from the Framingham Heart Study has shown that adipose tissue was not associated with CKD using creatinine-based estimating equations while it was associated with CKD using a CyC-based equation. CyC may play a role in preventing inflammation associated with increased adiposity explaining the increased secretion in obese patients.

The implications of this are that, although CyC may predict diabetes, it is unlikely that it adds any more to prediction algorithms considering that it is not independent of BMI and the metabolic syndrome - both of which are well known to be associated with diabetes. The second implication is that the fact that CyC is better at predicting mortality than creatinine (at the same level of eGFR) is related to non-renal factors - again, adiposity and the metabolic syndrome. It similarly suggests that in obese patients, estimating equations that utilize CyC may not be as accurate as previously suggested. The search for a better biomarker of GFR continues...

eJournal Club - Albuminuria and AKI

This month’s eJournal club concerns biomarkers of AKI. There has been considerable interest in developing novel biomarkers of AKI and CKD and a lot of effort has been focused on novel biomarkers such as NGAL, KIM-1 and IL-18. The TRIBE-AKI consortium has published a number of well-designedstudies investigating novel and traditional biomarkers. The reason that these biomarkers are desired is because creatinine elevations tend to occur relatively late in the course of AKI and therefore, the sense is that this is too late to initiate therapies which may prevent progression of AKI. However, the results of these biomarker studies have been relatively disappointing and they have not yet entered regular clinical practice.

This month in CJASN, a study was published looking at the performance of post-operative albuminuria as a biomarker of AKI in patients following cardiac surgery. The highest quintile of albuminuria was associated with a RR of 2.97 for AKI relative to the lowest quintile. While this appears good and the AUC for a model including albuminuria to predict AKI was 0.81, the majority of patients with albuminuria did not develop AKI and the model missed a significant number of patients with AKI. Still, when you combine this with other studies showing that the urinalysis is an excellent predictor of outcome in patients with AKI, older biomarkers are not looking so bad after all. Perhaps we will be able to come up with a combination of biomarkers which will allow us to better predict those patients at greater risk of AKI. To me, it seems that the bigger issue is low sensitivity rather than low specificity. I would rather have a model which will allow me to rapidly rule out those who will not develop AKI than one that will misclassify patients into a low risk group.

It was interesting in this study that ACR was not a good predictor of AKI – the absolute level of albumin performed better. This is at odds with the majority of studies which suggest that albumin should be corrected for creatinine level. This is possibly due to the large variation in creatinine generation in patients in the ICU – although relatively constant under normal circumstances, the amount of creatinine produced daily changes rapidly in sick patients – as was evidenced by a recent study of creatinine excretion in patients on CRRT.

Acute rejection: what do the circulating cells have to say about it?

One of the frequent situations that we face in the renal transplant clinic is the patient in otherwise good condition who presents with a slight rise in serum creatinine. Although this is sometimes due to reversible causes, such as high CNI levels or dehydration, acute rejection is of course in the differential. 

The fact that we still rely on an invasive procedure – the graft biopsy – for formal diagnosis of rejection clearly limits our ability for repetitive monitoring and potentially delays treatment. There is no doubt that a simple, non-invasive assay to monitor the immune status would be of great help in the day-to-day practice. Indeed this is currently a field of intense research in transplantation. We recently provided new insights into this issue. We optimized a simple assay to determine the level of activation of circulating blood mononuclear cells in renal transplant recipients. The method is relatively straightforward: peripheral blood is collected, cells are isolated and incubated overnight; cytokine production by the cultured cells is measured in the cell supernatant. The main objective was to determine if this assay, when used in patients for whom a biopsy was performed for an acute rise in serum creatinine, could identify those that would show histological signs of rejection. We found that the measurement of a single cytokine, IL-6, can predict rejection with a sensitivity of 92% and specificity of 63%. This tool could thus potentially be used to exclude rejection, which would be particularly helpful for low-risk or remote patients. 

Where do we go now? 

This work is a first step towards the development of a clinically useful tool. Ideally, a non-invasive test would be able to identify acute rejection well before the serum creatinine starts to rise. To achieve this, we now need to collect blood samples and study cell activation serially post transplant. What we need to determine more precisely is when the cells become activated before the usual signs of graft dysfunction occur. This will allow us to identify rejection early and by doing so, to prevent further graft damage. Although this sounds simple, from a research perspective this next step implies an enormous investment of human and lab resources. 

Sacha De Serres
Leonardo Riella