More and more patients worldwide suffer from end-stagerenal disease which often is secondary to diabetes (e.g.36.9% of all US patients with end-stage renal disease havea diabetic nephropathy [1]). Indeed, both types of diabetesare burdened by long-term complications, including retin-opathy and nephropathy. Nephropathy occurs in 25–40%of type 1 and type 2 diabetic patients [2], and is character-izedbythepresenceofabnormalamountsofproteinsintheurine, a sign of alteration in the renal filtration capabilitiesof the nephron. In many patients, diabetic nephropathy(DN) progresses to end-stage renal disease. However, it iscurrently impossible to reliably predict which and whendiabetic patients will develop nephropathy and progressto kidney failure. The persistent presence of albumin inthe urine is considered predictive of the subsequent devel-opment and clinical progression of DN [3,4]. Currently,microalbuminuria (MA) is considered the first clinicalevidence of incipient diabetic nephropathy. It is definedas an urinary albumin excretion of 30–300 mg/day andcharacterizes the stage III of diabetic nephropathy accord-ing to Mogensen’s classification [5]. However, despite itscapacity to highlight nephron damage, MA is a non-spe-cific marker of DN especially in subjects with type 2 dia-betes. Indeed, only 30–45% of microalbuminuric type 2diabetic patients will develop overt proteinuria over morethan 10 years [6], and MA is also proposed as a markerof high cardiovascular risk in diabetic and non-diabeticpatients [7], as recently highlighted [8]. Thus, MA shouldnot be considered an early and specific marker of DN.Urineandplasmaproteomicshavegainedmuchattentionas tools for the identification of diagnostic and prognosticbiomarkers of renal diseases. For many years now, it hasbeen hoped that proteomic methods would unveil earlierandmorespecificbiomarkersthanMA[9].Someprevious-ly published reviews have focused on the methodologicalaspects of proteomics [10,11] or on the approaches for dis-coveringandvalidatingdiagnosticmarkers[12,13].Aspro-teomics studies devoted to DN biomarker discovery begantobepublishedin2004[14],inthisarticle,wewillcompre-hensively review the available information published sincethen.Targeting DN biomarkers: an overview of the experimentalmethodsTable 1 summarizes the key information available from theanalysis of the literature. Urine is the biological fluid thatattracted most of the interest in the proteomic quest of DNbiomarkers. This makes sense because the protein compos-ition of urine might correctly reflect the renal functionalabnormalities associated with DN [15]. Moreover, urinehas some unique advantages such as its availability in largequantities as well as the solubility and stability of its pro-tein content [16]. Nevertheless, serum from type 2 diabeticpatients (four studies) [17–20] and pooled haemofiltratesfrom patients suffering from chronic renal insufficiency(most of them were also diabetics) (one work) [21] werealso analysed.Concerning the choice of separation and identificationtechniques (Table 1), two-dimensional gel electrophoresis(2D-GE) was frequently employed (however in differentexperimental set-ups). This is likely due to the fact that2D-GE easily provides a semi-quantitative estimation ofthe amount of each separated protein (spot intensity) andsome qualitative information about the size and the post-translational modifications of such proteins. These positivefeatures compensate for the limitations of 2D-GE such aslow throughput and a possible lack of sensitivity. Profilingmethods were chosen for several studies (indicated inTable 1). They generate a list of mass peaks which needthen to be assigned to a specific peptidic/protein se-quence. Surface-enhanced laser desorption/ionizationtime-of-flight (SELDI-TOF) mass spectrometry (a prote-omic method that enables mass fingerprinting of proteinsretained onto an affinity chip) was used in four differentstudies [18,22–24]. Interestingly, in each work, a differentseparationsurface(ProteinChip)wasconsideredasthemost
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Jul 20, 2020
N B Zakharova + 9
Open Access
