Albuminuria in diabetic patients: how to measure it?—a narrative review

Introduction

Chronic kidney disease (CKD) demonstrates few symptoms until late stages. Early identification and management of CKD with detection of albuminuria is cost effective and reduces risk of progression of kidney diseases and cardiovascular outcomes in diabetic patients (1-5).

International guidelines recommend assessment of urine albumin to creatinine ratio (ACR), ideally on an early morning void, as the first method for initial testing of proteinuria since protein to creatinine ratio (PCR) has a lower level of sensitivity for low range proteinuria (6-10). Since creatinine excretion is quite constant through the day, ACR or PCR are preferred to quantify albuminuria or proteinuria alone in order to reduce the dilution variable of the spot sample. Spot urine samples are preferred since 24 hours collection is more cumbersome and prone to errors. Moreover, diabetic nephropathy (DN) is mainly characterized by glomerular injury, and ACR is thus again preferred, as it is more sensitive and specific for detection of changes in glomerular permeability. ACR is also predictive of cardiovascular events (11).

Several different methods exist for detecting albuminuria. However, quantification of urinary albumin is not standardized because of the absence of a reference system including a reference measurement procedure and certified reference materials (12,13). Hence the National Institute of Standards and Technology (NIST), the National Kidney Disease Education Program (NKDEP) and the Working Group for the Standardization of Albumin Assays in Urine (WG-SAU) of the International Federation of Clinical Chemistry (IFCC) are currently working on such a standardization of albuminuria measurement (12). Regarding urine protein measurement, it seems quite difficult to standardize because of the heterogeneity of urine protein composition and reactants.

In the current article, we will define diabetic kidney disease (DKD) and DN, then briefly discuss the analytical challenges of albuminuria and proteinuria measurement and eventually underline the limitations of the current methods used to quantify albuminuria in routine laboratories.

We present the following article in accordance with the Narrative Review reporting checklist (available at https://jlpm.amegroups.com/article/view/10.21037/jlpm-21-58/rc).


Definitions/natural history of DKD

GFR (divided in 6 stages) and albuminuria categories (A1-A2-A3 see below) define together the prognosis of CKD. Despite these recommendations, measuring the ACR in clinical practice is too often overlooked: an American study gathering half a million type 2 diabetes patients showed that only half of them underwent ACR testing in the previous year, and 74% in the previous 3 years, contrasting with the higher rate of eGFR testing (89.5% in the previous year and 97% in the 3 previous years) and HbA1c testing (91% in the previous year and 96% in the 3 previous years) (19). Inhibitors of the renin-angiotensin-aldosterone system (RAAS) are first line medications that slow down the loss of GFR and reduce albuminuria (20-22). Recently, sodium-glucose co-transporter 2 inhibitors (SGLT2is), Glucagon like peptide 1 receptor agonists (GLP-1 RA) and Finerenone also showed huge benefits with reduction of albuminuria and decrease of the slope of eGFR (23-27).

DKD

DKD is defined by the presence of albuminuria or decreased eGFR in patients with diabetes. DKD does not describe a specific pathological phenotype and many other aetiologies such as hypertensive nephrosclerosis, unresolved acute kidney failure, infections or other nephropathies might be intricated. The pathophysiology of DKD is multifactorial and includes metabolic and hemodynamic factors (15). Therefore, atypical features such as short duration of diabetes, absence of diabetic retinopathy, haematuria, nephrotic syndrome, fast progression of albuminuria or decline in GFR or other sign or symptoms associated with other causes of kidney damage should lead to kidney biopsy to exclude more specific renal diseases (15,17). Fiorentino et al. showed in a meta-analysis that non-diabetic renal disease is not rare in patients with diabetes which may lead to specific treatment for delaying ESKD (16).

DN

DN is a histological diagnosis based on structural and functional changes seen in the kidneys of patients with type 1 or type 2 diabetes directly caused by the effects of diabetes on the kidney. Clinical presentation includes albuminuria, hypertension and progressive decline in GFR. Typical histological findings include thickening of glomerular basement membrane, arteriolar hyalinosis, mesangial expansion with diffuse or nodular glomerulosclerosis (Kimmelstiel-Wilson lesion), interstitial fibrosis and progressive tubular atrophy (28,29).

Incipient nephropathy/“Microalbuminuria”/KDIGO A2

Microalbuminuria is the word generally used to define the presence of low quantity of albumin in urine (30–300 mg/g on a spot sample or 30–300 mg/24 h on a timed collection) (30). In 2012, the KDIGO Clinical Practice Guideline for the Evaluation and Management of Chronic Kidney Disease suggested that this term should no longer be used because it is confusing. Indeed, the term microalbuminuria could suggest a different, smaller form of albumin in urine, which is not the case (6). Microalbuminuria is now referred as A2 albuminuria (30–300 mg/g on a spot sample or 30–300 mg/24 h on a timed collection). The classification with cut-off ranges is more clinically relevant for the patient follow up and more representative of a continuous variable that affects morbidity and mortality.

Indeed, patients presenting low but detectable albumin concentrations in urine are prone to develop CKD, i.e., progression to higher ACR and/or towards more severe GFR stages. Early recognition of this A2 stage is crucial, since intervention in controlling hypertension and diabetes may slow down the progression to ESKD (31). Beyond the control of these risk factors, blocking the RAAS and SGLT2i administration ‘per se’ also slow down the progression of CKD and reduce the risk of cardiovascular disease. Of note, GFR is often preserved or even supranormal (hyperfiltration) in these patients (30).

Overt nephropathy/“Macroalbuminuria”/KDIGO A3


Measurement of urine albumin

Pre-analytical considerations

Exercise, posture, pregnancy and fever are well known factors that may increase urine albumin excretion (12,32). Therefore, sampling should be performed on a first morning sample to attenuate this effect.

A positive urine sediment (haematuria, pyuria, leukocyturia) overestimates albuminuria or proteinuria (33). Thus, a positive ACR in presence of haematuria and/or leukocyturia result should always be confirmed on another sample without haematuria and/or leukocyturia.

Albumin adhesion to the wall of the plastic containers is neglectable (<1%) and does not lead to falsely low concentrations (34).

A fresh midstream sample is always preferable (35). Albumin is stable in urine for at least one week and up to 8 weeks when stored at 4 °C. For long term storage, urine should be stored at −70 °C or lower since significant degradation is reported when stored at −20 °C (12,36). However, the stability of the analyte could be method dependent and immunonephelometry seems less affected than high performance liquid chromatography (HPLC) by long-term storage at −20 °C and even −80 °C (37). Urine creatinine appears to be stable for a week at 4 or 20 °C and is not affected by freezing at either −20 or −80 °C (13). Bacterial growth can affect creatinine stability when samples are stored at +4 °C (36).

Urine pH has a wider range than plasma and albuminuria is therefore subject to a wider ionic exposure. Other factors may also modify albumin such as high concentration of urea, ascorbate, or glucose. Other modification may also take place with glycation or cleavage as described below (13).

Spot or timed collection: limitations of the ratio

Twenty-four-hour timed collection remains the method of reference for albumin quantification, but numerous international guidelines recommend measuring ACR on a spot sample because creatinine excretion is fairly constant through the day (38). Indeed, 24-hour timed collection is cumbersome and prone to errors (spills, errors in timing, incomplete bladder emptying) and may lead to mis-estimation of albuminuria (1,6-9,38,40). There is a good concordance between ACR on a random urine sample and 24 hour collection sample (41,42).

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The day-to-day biological variation of ACR must carefully be taken into consideration when interpreting longitudinal follow-up of patients. Indeed, day-to-day variability is important and influenced by the basal concentration of urine albumin. Naresh et al. showed that, in lower concentrations, like in the A1 stage, an increase of 467% in ACR values is required to observe a clinically significant change with a 95% probability (43). In later stages, this relative increase will be less important, i.e., 170% for A2 and 83% for A3, respectively—even if the absolute values are more important in these later stages. In other words, a patient presenting a basal ACR at 15 mg/g whose ACR increases to 60 mg/g in the next sample (i.e., 300% relative increase but 45 mg/g absolute increase) will not present a significant variation of the ACR, but another patient presenting a basal ACR at 500 mg/g whose value would increase to 750 mg/g (i.e., 200% relative increase but 250 mg/g absolute increase) will present a clinically significant variation of the ACR. Reversely, this approach should also be considered when evaluating the impact of a therapeutic treatment on the ACR. The large intra-individual variability, especially in A1 stage, means that a single observation should always be confirmed by a second one (42).

From an analytical perspective, analytical performances specifications (APS) have been set for albuminuria and albumin excretion ratio (AER) based on a study involving 87 diabetic patients with persistent A2 albuminuria (36). In this study, the intra-individual biological variation of the AER on a 24-hour timed collection was 25.7% whereas biological variation of ACR was 11.8%. Accordingly, these data helped defining analytical objectives for imprecision for albuminuria [desirable coefficient of variations (CV) of 12.9% and 5.9% for AER and ACR, respectively].

Another limitation is that creatinine excretion may vary because of non-kidney related factors such as age, muscular mass, race or obesity. For instance, an old lady with a small urine creatinine excretion might have a raised ACR ratio without a pathologic proteinuria, just because urine creatinine excretion is very low (1). On the other hand, high creatininuria may lead to underestimation of the ACR ratio in individuals with high muscular mass. In those individuals with extreme muscle mass or diet, a 24-hour timed collection should be preferred with a result expressed as an AER. Some equations, based on an ACR and an estimated creatinine excretion ratio (eCER), have also been developed to approach the AER, but they are few used in daily practice (44,45). Finally, acute kidney injury provides a non-steady state for creatinine excretion which interferes with the ratio (7).

Multiple forms of urine albumin and work towards standardization

Albumin is a 583 amino-acid protein of 66 kDa with three homologous domains forming a heart shaped molecule (13,46). With 17 disulfide bonds, 4 globular domains, it binds to numerous ligands (fatty acids, bilirubin, calcium and magnesium). Multiple molecular forms of albumin can be found in urine due to proteolysis while passing through the urinary tract (filtration, tubular uptake), or truncation at both ends (N and C terminal) or chemical modifications (proteolysis, glycation, oxidants, free radicals and other ligands) during storage (46). Hence, fragmented, partially degraded, glycated forms of proteins are found in urine (47). Interference may also occur with the measurement methods due to the urine matrix. All these factors contribute to the complexity for measurement of urinary albumin since the composition of albumin molecules can vary significantly, even within healthy people (13).

The complexity is enhanced since there are several methods for quantifying albuminuria. Standardization of measurement is in progress with a reference measurement procedure based on liquid chromatography-isotope dilution tandem mass spectrometry (LC-IDMS/MS) using human serum albumin as calibration and urine albumin certified reference materials (12,36,48,49). This should allow calibration for routine methods (essentially immunoassays), and eventually lead to a standardization of the measurement in the future.

Laboratory methods for urine albumin quantification

Several methods are available to measure albuminuria: immunoassays, enzyme-linked immunosorbent assay (ELISA), electrophoresis, western blot, size exclusion HPLC, liquid chromatography with mass tandem spectometry (LCMS/MS) and point of care (POC) methods. In this article, we will focus on the most popular ones (POC and immunoassays) on one side and the reference method (LCMS/MS) on the other side.

LCMS/MS: the higher order method and Candidate Reference Method Procedure

Two candidate reference method procedures by LCMS/MS have been described so far for the quantification of urine albumin after trypsin digestion (50,51). These methods allow clinical urine albumin measurements of certified reference and high-order calibration materials. The limit of quantification (LOQ) of such methods is compatible with the detection of albumin in urine at the lower stage of A2 level. Accordingly, this is a great step toward standardization of albumin in urine (52).

Immunoassays: the routine measurements procedures

Numerous forms of albumin can be found in urine (fragments, glycated, partial degradation etc). Albuminuria fragmentation may be due to kidney degradation or chemical modification during sample conservation (53). Thus, albumin found in urine may differ in structure from plasma albumin and have a compromised immunoreactivity (49). In the last decade, it was assumed that some form of modified albumin (immune-unreactive albumin) was not detected by immunochemical assays, because size exclusion HPLC yielded higher values than immunoassays (46,54,55). The difference was mostly noted at lower levels of albuminuria. It was first suggested that assays that could quantify immunoreactive and immuno-unreactive albumin might better foresee the development of DN, cardiovascular events and mortality. However, the PREVEND (56) and HOPE (57) studies, as well as another study including 741 Aboriginal high risk patients by Wang et al. (58) did not show any difference in predicting a composite cardiovascular endpoint between HPLC and immunoassays.

Studies have shown that immunoassays are also able to recognize modified forms of albumin (47,49), probably because albumin is very antigenic. Even if proteolysis or chemical changes in albumin destroy some epitopes, there is a broad distribution of reactive sites on albumin for antibodies to react to and polyclonal antibodies will still bind to another epitope and lead to detection (49). Sviridov et al. showed that use of a monoclonal antibody leads to a very different sensitivity to structural modification of albumin (49). The NKDEP-IFCC and Laboratory Medicine Working Group on Standardization of Albumin recommend quantifying urine albumin with polyclonal immunoassays since they have higher sensitivity compared with monoclonal antibodies, because as explained above, they are able to detect multiple epitopes of albumin (35) since urinary albumin has multiple antigenic sites that may be recognized by polyclonal antibodies. However, difference in composition of said antibodies may also lead to significant difference between commercially available kits (59): in 2014, Bachmann et al. compared 17 (including 16 quantitative and one semiquantitative) immunoassays with an isotope dilution mass spectrometry (60). Bias was the main source of discordance among the routine kits with median biases between −35% and 34% at 15 mg/L. At the clinically relevant threshold of 30 mg/L, 9 measurement procedures had biases over ±10% in comparison to the LC-MS/MS measurement. The difference of results may lead to misclassification of patients regarding their risk of kidney disease. Another comparison of albumin measuring methods with LC-MS/MS drew the same conclusion and showed that mean biases are greater at lower albumin concentration (−20% at 16 mg/L; −12% at 36 mg/L; −11% at 184 mg/L) (12). The Laboratory Working Group of the NKDEP and the IFCC and Laboratory Medicine Working Group for Standardization of Albumin in Urine recommended that the higher order method used as reference system for calibration of clinical laboratory measurement should aim at a desirable bias goal of 13% and optimal bias goal of ≤7% (61). Shaikh et al. showed that comparability between a LC-MS and an immunoturbidimetric method substantially improved when both methods used the same calibrators with the same calibrator value assignments with a mean bias upgrading from −37.8% to 2.2% (62).

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POC methods: quick, but maybe not so cheap (and not that easy)


Total urinary protein measurement

Despite international recommendations, PCR is more frequently performed than ACR in the everyday clinical setting, because urine protein quantification is less expensive than urine albumin determination and because some countries do not allow refunding of albuminuria in all patients. Another reason to, theoretically, prefer PCR over ACR is that the presence of light or heavy chains of immunoglobulins or tubular proteinuria may not be detected when performing ACR alone (especially at the beginning of the disease, when damage from the immune deposit still does not lead to glomerular injury). It should be however noted that most methods aiming at proteinuria detection tend to react more strongly with albumin than with globulin or other proteins and lack precision at low concentration of these proteins (6). Hence, measuring PCR when non-albumin proteinuria is suspected may not meet the pathological threshold for proteinuria and therefeore the KDIGO guidelines recommend that if non-albumin proteinuria is suspected (when testing for tubular proteinuria of myeloma for instance), one should perform a specific assay (alpha 1 microglobulin, monoclonal heavy or light chains or immuno-electrophoresis). As previously mentioned, assessment of ACR is more sensitive and specific, compared with PCR (1,6). The heterogeneity of urinary protein composition makes it impossible for standardization since numerous available methods may react differently to the panel of proteins present in urine. Moreover, urinary total proteins measurement may not be sensitive enough for detecting clinically relevant urinary albumin concentration: indeed there is no global accepted definition of proteinuria (normal ranges between <150 mg/L to <300 mg/L) whereas normal albuminuria range has been defined <30 mg/L (1,13,66). Also, variability of non-protein molecules or important content of inorganic ionised compounds can interfere with the measurement. Finally, there are several methods of measurement for total urinary protein (colorimetry or turbidimetry for instance) that have different sensitivity and specificity for total proteins which may contribute to variability of the results (13).


Conclusions

Albuminuria is an important biomarker regarding not only kidney function and prognosis of CKD, but also cardiovascular events, morbidity and mortality. It is an early marker of renal involvement in diabetes and other kidney diseases. Accurate measurement of albuminuria is therefore of critical clinical interest for early therapeutic management (with initiation of effective treatments that slow down the loss of kidney function and progression toward ESRD) and follow up. Despite this recognized clinical importance, measuring albuminuria is not an easy task: urine is a very heterogeneous fluid in terms of pH and chemical composition, numerous methods are available with their own limitations and work towards standardization is in progress. LC-MS/MS measurement of albumin specific peptides after trypsin digestion in a controlled environment is foreseen as a reference method for measurement of urinary albumin. Development of a reference material based on pure human albumin is also a crucial step. This will allow standardized calibration for polyclonal immunoassays that are easier to perform in everyday clinical practice and able to recognise several modified form of albumin coming from its journey through the nephron.


Acknowledgments

Funding: None.


Footnote

Provenance and Peer Review: This article was commissioned by the Guest Editor (Rafael Noal Moresco) for the series “Laboratory Medicine in Diabetic Kidney Disease” published in Journal of Laboratory and Precision Medicine. The article has undergone external peer review.

Reporting Checklist: The authors have completed the Narrative Review reporting checklist. Available at https://jlpm.amegroups.com/article/view/10.21037/jlpm-21-58/rc

Peer Review File: Available at https://jlpm.amegroups.com/article/view/10.21037/jlpm-21-58/prf

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jlpm.amegroups.com/article/view/10.21037/jlpm-21-58/coif). The series “Laboratory Medicine in Diabetic Kidney Disease” was commissioned by the editorial office without any funding or sponsorship. Pierre Delanaye serves as an unpaid editorial board member of Journal of Laboratory and Precision Medicine. The authors have no other conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.


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doi: 10.21037/jlpm-21-58
Cite this article as: Résimont G, Cavalier E, Radermecker RP, Delanaye P. Albuminuria in diabetic patients: how to measure it?—a narrative review. J Lab Precis Med 2022;7:4.

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About the Author: Tung Chi