1. Biomarkers of Chronic Kidney Disease
10thAnnual International Conference on Nephrology and Hypertension
Lesley Roberts MB.,B.S, FRCPC
January 19th 2018.
Good morning, I would like to thank the organizing Committee of the 10th Annual International Conference on Nephrology and Hypertension sponsored by the Caribbean Institute of Nephrology and the ISN for inviting me to present this talk on Biomarkers of Chronic Kidney Disease.

2. Objectives Objectives Define the ideal biomarker
Describe the purpose of biomarkers in kidney disease- why use biomarkers?
Discuss conventional, emerging and novel biomarkers in kidney diseases
Biomarkers in Diabetic and Membranous Nephropathy
Summary
During the next 20minutes, I hope to define an Ideal Biomarker, discuss the importance of biomarkers, address Conventional, Emerging and Novel Biomarkers. Specifically address Biomarkers that can be used in Diabetic CKD and Membranous Nephropathy and End with some Specific take home messages.

3. Definition of a biomarker
A biological marker:
“a characteristic that is objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention”
Surrogate endpoint:
type of biomarker that functions as substitute for a clinical endpoint/ therapeutic intervention
Surrogate Marker- discouraged- suggests that the substitute is for the marker and not the clinical endpoint
So because of the anticipated use of biomarkers in clinical trials, the National Institutes of Health put a working group together for a consensus on the definition of a biomarker as the field moved forward, which is, a biological marker is “a characteristic that is objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention.”1 Thus, biomarkers can be powerful tools that have the capacity to shape the diagnosis, management and prognostic determinants of a disease entity.
Biomarkers Definitions Working Group: Biomarkers And
Surrogate Endpoints: Preferred Definitions And Conceptual
Framework. Clin Pharmacol Ther 2001;69:89-95 .

4. Biomarkers can be system specific Diagnostic Prognostic
Identify the disease entity
Prognostic
Indicate likelihood of patient outcome regardless of specific treatment
Predictive
Assist in optimizing the ideal treatment and indicate the likelihood of treatment benefits
Biomarkers are used in every Biological System , Cardiac- Troponins; Auto Immune conditions Anti Nuclear factor. Biomarkers may be Diagnostic, Prognostic or Predictive.

5. The Ideal Biomarker
Non-invasive, easily measured, rapid results, reproducibility
Up regulated in diseased samples, modifiable with treatment
Consistent across gender and ethnic groups
Prognostic value
Selection of appropriate therapy
Maximize efficacy or minimize toxicity
Sensitive, specific ,accurate and robust
Monitor outcomes (good or bad)
So given the above, What makes an ideal Biomarker? Some of the characteristics of the ideal biomarker have been described by Janet Woodcock and Michael Bennett as being non-invasive, and easily measured, that can provide rapid results; it is Reproducible; it can be from a readily available source such as urine; it should be upregulated in diseased samples and provide insight into the underlying disease mechanism and thus have some prognostic value. The ideal biomarker should provide information that would allow us to either to maximize efficacy or minimize toxicity of appropriate therapy, select the correct dose and monitor outcomes whether good or bad. And therein lies the problem with Biomarkers in CKD

6. EFFECTIVE CKD BIOMARKER
Allow for detection early in the disease process
Effectively risk stratify patients who will progress to ESRD
Prognosticate CKD progression and mortality
Widely available, cost effective, stable in solution (Urine/Blood), timely results
Independent of or represent different pathophysiological pathways
Tummalapalli et al Nov 2016
Tummalapalli et al have suggested that an effective Biomarker inn CKD should display the following attributes: The Biomarker should allow for dtection early in the disease process and not years after the injury has occurred ;Should be able to risk stratify which patients will progress and develop ESRD, Be able to prognosticate on CKD progress and the development of adverse effect; Be cost effective, readily available and provide timely results.

7. CLASSIFICATION OF BIOMARKERS
CONVENTIONAL
EMERGING
NOVEL
Serum Creatinine
Cystatin C
Klotho
EGFR Equations
ß2 Microglobulin
Vimentin
Albuminuria
NGAL
“OMICS”
KIM-1
There are a number of CKD biomarkers, but how effective each is , is the question? These biomarmarkers can be descibed as Coventional, Rmerging and Novel. Emerging and Novel being determined by the level of their evidence. Emerging markers have been examined in multiple studies and have been validated independently in separate cohorts while Novel Biomarkers may only show an association in a single or couple observational studies with smaller numbers.

8. Serum Creatinine Derived from Creatine degradation
Freely filtered, not reabsorbed or metabolized, but a significant percentage is secreted by PCT when renal function is poor.
Only of value when Renal function is stable.
Affected by non glomerular determinants as variation in production, diet and muscle mass
Not sensitive to detect early kidney disease or determine progression.
Let us look at our first CKD Biomarker Serum Creatinine. It is a reasonable endogenous fitration marker, but does not detect disease early and underestimates level of function in severe cases. It I only of value in a stable renal function so of not much use in monitoring progression.

9. Estimating Equations
Effersoe in 1957 developed the first equation to estimate GFR.
The CKD-EPI equation (2009) is the best performing in clinical practice to identify CKD.
It has been validated in blacks, renal transplants and diabetics.
Performs better than MDRD for those with GFR >60ml/min/1.73m²
These are equations which estimate the Glomerular fitration rate. GFR, being the gold standard of Kidney function. First developed by Effersoe in The cohort used for validation of CKD EPI is more diversified than that used for MDRD and seems to perform at an earlier stage.

10. ALBUMINURIA Can be determined with:
24hr. Collection
Spot Urine collection for Albumin to Creatinine Ratio
Requires 2 out of 3 samples during a 3 to 6 month period.
3 stages:
A1 - ACR <30mg/g (<3.4mg/mmol)
A2 – ACR mg/g(3.4mg/mmol - 34mg/mmol)
A3 – ACR >299mg/g (>34mg/mmol)
Albuminuria is a fundamental pillar in the definition of CKD and can be determined in the following ways.

11. Significance of ALBUMINURIA
Present when injury is already established.
There is a graded risk of Mortality, Progression of CKD and ESRD at higher levels of albuminuria , and all cause mortality.
All this being independent of egfR
Staging Albuminuria has been added to KDIGO guidelines to Risk stratify in CKD since 2012.
Albuminuria is present after the disease is already established, and thus can not be considered an early identifier of disease.It can prognosticate given the graded risk of mortality, progression at higher levels. Consequently since 2012, Albuminuria has been added to KDIGO guidelines to determine risk stratification

12. Classification/staging of CKD: eGFR + ACR
Heat map: risk of progression, M & M
This is the current classification and staging of CKD based on MDRD eGFR kidney function and level of albumin to creatinine ratio. It is a heat map that shows the color coordinated level of risk of progression of CKD, in that individuals with the lowest eGFR and highest ACR are also at highest risk of morbidity and mortality.
The definition was advanced in 2012 by KDIGO to include both eGFR and CKD stages on the left and ACR on the top in a heat map so that the colors represent the risk for progression, morbidity and mortality. Green: low risk (if no other markers of kidney disease, no CKD); Yellow: moderately increased risk; Orange: high risk; Red, very high risk. This also helps to orient the clinician on when to implement strategies to slow progression or protect against complications in collaboration with a nephrologist.
In October 2009, KDIGO initiated a collaborative meta-analysis and sponsored a an intern’ Controversies Conference to examine the relationship of eGFR and albuminuria from existing data to mortality and kidney outcomes.
On the basis of analyses in 45 cohorts that included 1,555,332 participants from general, high-risk, and kidney disease populations, conference attendees agreed to retain the current definition for chronic kidney disease of a GFR o60 ml/min per 1.73m2 or a urinary albumin-to-creatinine ratio 430mg/g, and to modify the classification by adding albuminuria stage, subdivision of stage 3, and emphasizing clinical diagnosis. Prognosis could then be assigned based on the clinical diagnosis, stage, and other key factors relevant to specific outcomes. KDIGO has now convened a workgroup to develop a global clinical practice guideline for the definition, classification, and prognosis of chronic kidney disease. Kidney International (2011)
Figure 6 | Composite Ranking for Relative Risks by glomerular filtration rate (GFR) and Albuminuria (Kidney Disease: Improving Global Outcomes (KDIGO) 2009). As in Figure 5, colors reflect the ranking of adjusted relative risk. The ranks assigned in Figure 5 were averaged across all five outcomes for the 28 GFR and albuminuria categories. The categories with mean rank numbers 1–8 are green, mean rank numbers 9–14 are yellow, mean rank numbers 15–21 are orange, and mean rank numbers 22–28 are red. Color for twelve additional cells with diagonal hash marks is extrapolated based on results from the meta-analysis of chronic kidney disease cohorts. The highest level of albuminuria is termed ‘nephrotic’ to correspond with nephrotic range albuminuria and is expressed here as X2000 mg/g. Column and row labels are combined to be consistent with the number of estimated GFR (eGFR) and albuminuria stages agreed on at the conference.
Moderate
risk
High
risk
Low risk
Very high risk
KDIGO
2012

13. Limitations of albuminuria
Neither a specific nor reliable biomarker of:
Underlying renal structural pathology, progression of DKD
Relative to natural history or benefit to intervention in DKD
Not a sensitive biomarker
Low GFR may be present in ≥50% DM without  albuminuria
microalbuminuria may spontaneously remit
up to 40% of T1DKD and
30-40% T1DKD may not progress to macroalbuminuria (>5-10y)
Serial biopsies in T1DKD have revealed
progressive mesangial matrix accumulation despite persistent normoalbuminuria, and
others with normoalbuminuria may have reduced renal function (DCCT/EPIC)
Demonstrates day-to-day variability ~40% time (→first am urine)
Associated with episodic increases with:
fever, UTIs, exercise, CHF, HTN, hyperglycemia and high protein diets.
2008, NKF and US FDA
Explored the strengths and limitations of albuminuria
concluded that there was insufficient evidence, further research needed
This reflects issues as a biomarker in DKD , but some relavent points are raised in Non Diabetic cases as well. Its non GFR determinants, its variability and the ability to spontaneously remit
deBoer et al Arc Int Med 2010

14. Cystatin C
An inhibitor of cysteine protease , produced by all nucleated cells
Freely filtered, reabsorbed and completely metabolized in tubular cells. There is no tubular secretion.
Influenced by NGfR determinants as Thyroid disease , corticosteroids, smoking and obesity.
Shlipak et al reported a better association with its level and all cause mortality across all GFR stages than Serum Creatinine
We now examine some Emerging Biomarkers – Cystatin C , An excellent endogenous filtratrion marker, having no tubular secretion and not affected by generation. There is a stable rate of production.

15. THE COMBINED EQUATION of egfR Creatinine- Cystatin C
The best performing equation to determine progression and risk stratification is:
THE COMBINED EQUATION of egfR Creatinine- Cystatin C
Schaeffner E.S. Ann. Int Med :
Longitudinal studies are in place and the role in Ethnic minorities has to be analyzed.

16. Emerging Biomarkers – ß2M;FGF 23;KIM-1;NGAL
COMPOSITION
ATTRIBUTE
USE
LIMITATION
ß2 Microglobulin
Small molecule 11.8Kda, found on all nucleated cells
Good endogenous marker of egfR
Increase seen before increase in Cr, due to fall in GFR
Increase seen in a variety of other diseases.
Not ready for clinical use as yet.
FGF 23
Circulating peptide that mediates phosphate metabolism
Elevation occurs early in CKD
Serum FGF23 is an independent predictor of CKD progression.
A Marker for CVD complication in CKD
Further investigations ongoing to seek FGF23 as a therapeutic target
Beta 2 microglobulin can detect very early disease but is not specific for CKD. FGF23 might be seen early as well but could be a specific maker for CVD complicationss.

17. BIOMARKER COMPOSITION ATTRIBUTE USE LIMITATION
KIM -1
A transmembrane glycoprotein expressed on PCT in response to injury
U- KIM 1 rises early with tubular injury
P- KIM-1 associated with Incident CKD and rapid decline of egfR.
Progression of CKD in Type 1 Diabetics
Conflicting data with regards to CKD.
Larger studies involving diverse cohorts are needed
NGAL
Iron carrying protein expressed in Renal Tubular epithelium and released following injury
Established marker in AKI.
U NGAL increase shows a higher risk of CKD 3
U NGAL /Cr was associated with progression, mortality and the need for ESRD treatment
UKIM 1 has been controversally associated with incident CKD and rapid renal decline. In a diabetic study retrospective with 107 Type 1 Stages 1to 3, Stage 3 albuminuria63% pats with >97pg progressed to ESRD vs 20.
NGAL, Neutrophil Galatinase associated Lipocalin best known in AKI

19. Urinary monocyte chemotactic protein – 1
This is a chemokine that promotes recruitment and transformation into macrophages
Upregulated in kidney diseases that have a sustained inflammatory response eg,D.M.
It is an independent predictor in Diabetic KD and predicts egfR decline independent of albuminuria
Biomarkers in Diabetic Nephropathy – Urinary MCP 1 and Tumor Necrosis Factor Receptor 1 2

20. TUMOR NECROSIS FACTOR Receptor 1&2
Several recent studies have shown soluble TNFR1/2 are robust markers for prognostication of renal function decline in DKD
Their role in clinical practice is still to be assessed

21. Panel of markers which look at pathogenesis:
Markers for glomerular disease (albumin)
Tubular damage (KIM-1 and NGAL)
Inflammation (TNFR1 and 2)
Oxidative stress (ADMA)

22. Biomarkers qualified for limited use in nonclinical and clinical drug development for AKI
As a result of rigorous testing, there is a list of biomarkers that have qualified for limited use in nonclinical and clinical drug development: KIM-1, albumin, CLU- clustering, TFF3-urinary Trefoil Factor 3, total protein, Cystatin C, and b2-microglobulin.
Some have qualified for clinical use on a case by case context.
Dieter et al Nature Biotechnology, 2010

23. Antiphospholipase A2 receptor
Developed as a result of proteomics , FDA approved biomarker
Elevated levels are seen with 60 70% of patients with Primary Membranous Nephropathy
Clear association between Antibody titres and disease activity.
AdvCKD 2014 Mar21(2)
APLA2R

24. The Future
The horizons for biomarker discovery have been expanded with advances in “omics” and improved computational approaches.
Panel of markers will be considered.
The cost, feasibility and accessibility of laboratory testing would be limiting factors with regards introduction in clinical practice.
Disease progression makers for CKD in Ethnic Minorities have to be examined.

25. SUMMARY
KDIGO CPG recommends that CKD be diagnosed, classified and staged by eGFR and the CKD – EPI equation is preferred.
Combination of biomarkers lends to a better risk stratification of CKD and progression to ESRD
Emerging biomarkers are promising but are not as yet in clinical practice.

26. SUMMARY
MCP -1 is of particular importance to predict progression of Diabetic Nephropathy
Special attention must be paid to the use and benefit of biomarkers in Ethnic Minorities, considering that because of their vulnerability they would most benefit.

27. Avoid Acute Kidney Attack! Stop Chronic Kidney Disease!
The End
Avoid Acute Kidney Attack!
Stop Chronic Kidney Disease!

28. Emerging and novel biomarker for CKD
List of emerging and novel biomarker and broad pathophysiologic characteristics. ADMA, asymmetric dimethylarginine; b2M, b2-microglobulin; CKD, chronic kidney disease; FGF23, fibroblast growth factor 23; KIM-1, kidney injury molecule-1; MCP-1, monocyte chemotactic protein-1; NGAL, neutrophil gelatin-associated lipocalin; PIIINP, procollagen type III N-terminal propeptide; sE, soluble E-selectin; sTNFR1/2, soluble tumor necrosis factors receptor 1 and 2; suPAR, soluble urokinase-type plasminogen activator receptor; sVCAM, soluble vascular adhesion molecule-1; TMAO, trimethylamine-N-oxide; vWF, von Willebrand factor.
Lekha Tummalapalli, Girish N. Nadkarni, and Steven G. Coca