the term  biomarker ' has been defined as a  quantitative indicator of biologic or pathologic processes that vary continuously with progression of the process ' . this was further refined by the national institutes of health working group report in 2001 and included its role in measuring and monitoring pharmacologic responses to a particular therapeutic intervention . biomarkers used in nephrology can be measured from blood and urine specimens , and more recently from dna and microrna analyses , kidney biopsy specimens , and from imaging modalities . ideally , biomarker levels vary continuously with the activity or degree of progression of the disease process . increasingly , biomarkers are measurable intermediary components of molecular or cellular pathways involved in the biologic process , which may be disease specific or relevant to treatment toxicity . as such , single biomarker measurements represent a temporal slice through one of possibly many pathways that converge to define that process and its treatment . for instance , the estimated glomerular filtration rate ( egfr ) and albuminuria are generally accepted as  standard ' biomarkers for the prediction of cardiovascular mortality and risk of eskd . however , the classification inherently implies that those with renal impairment are likely to progress . the challenge is to identify those at risk of complications and progressive renal disease earlier in its development . most known risk factors for ckd can rarely distinguish patients who will develop ckd from those who will not . conversely , surrogate end points can also be described as biomarkers that are strongly associated with a distant clinical event . they can reliably substitute for hard clinical end points in predicting clinical benefit , lack of benefit , or harm from a treatment . for that reason , albuminuria has been widely used as a surrogate marker in large - scale clinical trials for both cardiovascular and renal end points to improve clinical trial efficiency and decrease the need for lengthy studies of slowly progressive diseases such as ckd . however , the use of albuminuria as a surrogate marker for such end points is controversial . therefore , we need biomarkers that can : 
 accurately predict an individual 's risk of developing ckd or hard renal end points such as eskd or death , identify additional risk factors other than known conventional risk factors for ckd , identify and quantify a pathological process within the kidney , which may or may not be modifiable , andact as an indicator of treatment response accurately predict an individual 's risk of developing ckd or hard renal end points such as eskd or death , identify additional risk factors other than known conventional risk factors for ckd , identify and quantify a pathological process within the kidney , which may or may not be modifiable , and act as an indicator of treatment response emerging technologies in the field of genomics , metabolomics , and proteomics are providing new platforms for biomarker discovery . although molecular genetic typing of kidney biopsy specimens may eventually replace classical renal pathology in diagnosis of various nephropathies , the vast majority of patients with the potential for development of ckd , or indeed existing ckd , will not undergo a renal biopsy . hence peripheral blood biomarkers are still required . the role of epigenetic modification is increasingly recognized to be associated with disease phenotype and an area of active investigation , but its predictive association with progression of ckd is as yet unclear . targeted pathophysiologic investigations , especially in animal models of disease , have been the predominant method of biomarker discovery in the past . the primary goal of these studies has been an understanding of disease mechanisms , and biomarker discovery was usually a secondary outcome . a  fishing ' approach involves exhaustive quantitative analyses of mrna or proteins in patient samples ( tissue , blood , urine ) and the use of analytical methods to search for patterns in the resulting large data sets . the major drawback of this approach is data overload , with the potential for overfitting of models , and lack of immediate pathophysiological insight . however , with the recent advances in urinary proteomic and gene expression arrays , this approach allows rapid screening of huge numbers of possible associations and the increased likelihood of serendipitous discovery . once new target biomarkers are identified , or existing ones are refined , preclinical trials are used to validate them in individuals with or without disease . subsequently , retrospective case - control studies are used to determine assay sensitivity and specificity . finally , the biomarker is validated as a disease - predictive tool in alternative cohort studies or randomized controlled trials . most biomarker studies are conducted within population - based studies , epidemiological cohorts , or in clinical trials . these investigations are generally designed as either a cohort study or a nested case - control study extracted from a larger cohort . participants are selected based on criteria including the absence of ckd at baseline and the subsequent outcome based on defined end points of ckd during follow - up . the methodology is usually based on the availability of specimens ( blood or urine , single or two time points ) , and the cost and feasibility of the assay to be performed , which generally is not factored into the cost of the primary study . in either case , multivariate analysis is typically used to control for confounding variables that may alter associations between the biomarkers and risk of progressive ckd . validation of the performance of a new biomarker is the most problematic aspect of biomarker development and is best achieved by prospective validation with a separate cohort of patients . relative risk indicators , such as odds ratio or risk ratios , are the most frequently used measures of association between a biomarker and outcomes . owing to the nature of distribution of biomarker levels , which typically overlap in cases and controls , the risk ratios do not provide direct information as to whether a biomarker affects risk prediction . the c - statistic is more commonly known as the area under the receiver - operating characteristic curve . the c - statistic ranges from 0.5 ( no better than random guessing ) to 1 ( perfect discrimination ) , and represents the trade - off between sensitivity and specificity of a candidate biomarker . an ideal biomarker should provide a c - statistic value over and above that of the conventional risk factor or the gold standard for the outcomes . for example , in the framingham offspring study , the b - type natriuretic peptide level and urinary albumin to creatinine ratio were found to be good predictors of major cardiovascular events . the highest quartile of these markers , by a  multimarker ' score method , gave a fourfold increase in all - cause mortality and a twofold increase in cardiovascular events . however , the c - statistic for models of major cardiovascular disease events was 0.68 ( with age and sex as conventional predictors ) , with only marginal improvement to 0.7 ( with age , sex , and the addition of b - type natriuretic peptide or albumin to creatinine ratio to the predictive equation ) . the net reclassification index ( nri ) is a more recent method of analysis that interprets the value of a biomarker by exploring whether the incorporation of a biomarker leads to a change in assigned risk categories . the categorical nri method requires the specification of risk thresholds ( such as low , intermediate , and high risk ) and whether a biomarker will move individuals across these risk thresholds into different risk categories . the risk reclassification is considered appropriate if persons who are moved to a higher - risk category do in fact have a higher risk for the outcome , or vice versa . another measure , the integrated discrimination improvement ( idi ) , may be regarded as a continuous version of the nri , with reclassification measured in terms of differences in predicted probabilities . c - statistics do not provide any information on the ability of a model to predict probabilities , which are often important in decision - making in a clinical setting . sensitivity and there is also increasing recognition that even modest improvements in the c - statistic require extremely strong associations between a novel biomarker and an outcome , which most biomarkers fail to achieve . similarly , reclassifying an individual using nri at low risk of disease to an intermediate - risk category may have the same effect upon the nri as reclassifying an individual at intermediate - risk to a high - risk group . incorrect down - classification of a few individuals at high risk may result in significantly more clinical harm . most importantly , useful biomarkers must demonstrate that they can distinguish between individuals with risks of developing ckd in a clinically meaningful way . two modifications to the nri have been attempted to address the above - mentioned limitations . the  clinical nri ' examines reclassification only for individuals starting in the intermediate - risk group , with the assumption that these are individuals in whom clinical decision - making is most likely to be altered . the other modification is a  weighted nri ' , which takes into consideration factors such as perceived costs or savings . other statistical methods such as akaike 's information criterion and schwartz 's bayesian information criterion are also used to measure the  fitness ' of a model , by incorporating existing risk factors with or without the biomarkers in predicting ckd risk . typically , the lower the akaike 's information criterion and bayesian information criterion values , the closer the fitness to the model , hence a better marker of risk . it is well known that the degree and extent of tubulointerstitial fibrosis are accurate predictors of future renal function . hence markers indicating progressive fibrosis and subsequent risk of ckd progressive are needed . transforming growth factor-1 ( tgf-1 ) is well known as a pro - fibrotic cytokine that has a pivotal role in kidney fibrosis . tgf-1 levels can be measured in both serum and urine . in cross - sectional studies , suthanthiran and et al . showed that serum levels of tgf-1 were higher in african american subjects with eskd relative to caucasians , and hypertensive compared with normotensive individuals . hence they hypothesized that tgf-1 may be a contributing risk factor for renal disease progression in the african american hypertensive subjects . increasing evidence suggests circulating tgf-1 levels are linked to vascular target organ damage in both the diabetic and non - diabetic population . bone morphogenetic protein-7 ( bmp-7 ) is recognized as a natural antagonist to tgf-1 , with antifibrotic and anti - inflammatory properties . the role of tgf-1 and bmp-7 in the pathogenesis of kidney fibrosis has been highlighted by a growing body of research over recent years . our group has examined the levels of circulating total and active tgf-1 and bmp-7 in the baseline blood samples from 281 participants enrolled the action in diabetes and vascular disease : preterax and diamicron modified release controlled evaluation study . we then determined the utility of these measurements in predicting the development of progressive kidney disease using hard renal end points . using a nested case - control study and propensity - scoring methodology , cases were defined as those who developed a renal end point during the study ; i.e. , doubling of serum creatinine to at least 200  umol / l , the need for renal replacement therapy , or death due to renal disease . individuals who developed renal end points had higher total tgf1 and lower bmp-7 levels ( all p<0.0001 ) at baseline . a graded increase in risk was observed in individuals with lower bmp-7 levels ( odds ratio 24.07 , 95% confidence interval ( ci ) 8.0872.73 , p<0.0001 , for the lowest vs. the highest tertile ) , or higher tgf-1 levels ( odds ratio for the highest vs. the lowest third 8.43 , ci 4.0317.67 , p<0.0001 ) . the c - statistic for conventional predictors ( i.e. , albuminuria and reduced glomerular filtration rate ) was 0.73 . using bmp-7 , total and active tgf-1 , the receiver - operating characteristic was 0.94 ( p<0.0001 vs. conventional predictors)(figure 1 ) . in summary , we showed that by incorporating total or active tgf-1 , or bmp-7 to the conventional predictors model ( urinary albumin to creatinine ratio , egfr in addition to the clinical parameters , age , sex , body mass index , duration of diabetes mellitus , hba1c , history of macrovascular events , and retinopathy known as the baseline model ) provided a higher predictive value for the development of predefined renal end points . the strongest predictive ability was observed when circulating bmp-7 , along with total and active tgf-1 were incorporated into the baseline model ( c - statistic=0.96 , p<0.0001 vs. the baseline model ) , suggestive of an additive effect on ckd risk prediction by these markers . sensitivity analyses were performed using akaike 's information criterion and the bayesian information criterion , which showed the lowest value of akaike 's information criterion and bayesian information criterion when the cytokines were combined . the results suggest these novel kidney markers are better predictors of renal progression than albuminuria and reduced glomerular filtration rate in patients with type 2 diabetes mellitus . these data further suggest the role of pro - fibrotic and antifibrotic cytokines in maintaining the physiological balance in kidney fibrosis , and translates the pathophysiology of kidney fibrosis to potential clinical practice . clearly , validation of these results using these biomarkers in a separate population , with a cost effectiveness assessment , is required . in addition , the results can not necessarily be extrapolated to cohorts other than patients with diabetes mellitus . with better understanding of the molecular mechanisms underpinning ckd , the roles of inflammation and fibrosis in progressive renal functional decline are becoming increasingly inseparable . despite the fact that markers of inflammation are known to be associated with an increased risk of cardiovascular disease , the association of these markers with the onset and progression of kidney disease has remained unclear . tumor necrosis factor ( tnf)- is a transmembrane protein that has an essential role in mediating inflammatory processes . tnf- and its receptors , tnf receptor 1 and tnf receptor 2 are shed from the cell surface , which can be detected in the plasma as free or bound to circulating tnfrs . examined the levels of tnf- and its receptors in 410 patients with type 2 diabetes in a 12-year prospective study . they reported the cumulative incidence of eskd for patients in the highest tnf receptor 1 quartile was 54% , but only 3% for the other quartiles ( p<0.001 ) . this association with eskd is seen in both proteinuric and non - proteinuric patients with type 2 diabetes . in a separate study of 628 non - proteinuric and normal renal function patients with type 1 diabetes mellitus , the same group reported a cumulative incidence of stage 3 ckd ( egfr<60  ml / min per 1.73  m ) for patients in the highest tnf receptor 2 quartile and they were threefold more likely to experience renal decline than patients in the lower quartiles ( hazard ratio 3.0 , 95% ci 1.75.5 ) , independent of relevant clinical covariates such as age , hba1c , urinary albumin creatinine ratio , baseline cystatin - c - based egfr ( egfrcys ) , blood pressure , or treatment with renin  angiogtensin system inhibitors . together , these associations point to the involvement of tnfrs and their independent role in leading to early and late renal function loss in both types 1 and type 2 diabetes mellitus . numerous promising biomarkers for risk of ckd progression have been evaluated in the past decade but to date , evidence to support their use in routine clinical practice remains limited . key limitations limiting the use of current biomarkers include variable and inappropriate analytical methods to define predictive risk and the lack of a validation cohort . hence , the ability to use these biomarkers to predict ckd risk more accurately than current methodology remains to be tested . however , it is evident that combination of biomarkers with conventional risk factors is necessary to substantially improve risk prediction . further research is needed to identify new biomarkers that can successfully stratify risk of ckd in a general population , as well as to determine whether management strategies informed by biomarker testing improve the targeting and efficiency of health - care services compared with current  standard of care ' .
with the escalating cost of monitoring and follow - up required in the care of patients with chronic kidney disease ( ckd ) , biomarkers are increasingly being investigated for their utility in predicting patients most at risk of decline in renal function in order to rationalize and target care . 
 putative biomarkers have also emerged as treatment targets , with the potential to develop novel therapeutics . however , biomarker studies in ckd are largely derived from single - sample collections in observational or nested case - control studies that are suboptimal in study design , analyses , and end points relevant to confirm the utility of specific biomarkers . 
 it has been demonstrated that biomarker expression may be modified by declining kidney function . 
 hence , their value in predicting future kidney dysfunction is limited . 
 therefore , understanding the nature , mechanism of action , and how specific biomarkers interact with the ckd disease process is a crucial step in defining the potential for biomarkers to predict outcome , or alternatively , develop as a therapeutic target . unlike conventional risk factors that , albeit partly , enable us to distinguish an individual at risk of cardiovascular disease , biomarkers in patients with ckd may not be required to be modifiable either directly or indirectly in the disease process or by therapy . 
 reproducibility and prospective validation remain major challenges for the burgeoning number of purported biomarkers in patients with ckd . 
 it is highly likely a combination of conventional and novel biomarkers will be needed to accurately predict the risk of end - stage kidney disease . 
 this review will focus on recently identified biomarkers and their utility in predicting progressive kidney fibrosis .