Animal Models and Renal Biomarkers of Diabetic Nephropathy

Abstract

Diabetes mellitus (DM) is the first cause of end stage chronic kidney disease (CKD). Animal models of the disease can shed light on the pathogenesis of the diabetic nephropathy (DN) and novel and earlier biomarkers of the condition may help to improve diagnosis and prognosis. This review summarizes the most important features of animal models used in the study of DN and updates the most recent progress in biomarker research.

Full text

Adv Exp Med Biol - Advances in Internal Medicine
https://doi.org/10.1007/5584_2020_527
#Springer Nature Switzerland AG 2020
Animal Models and Renal Biomarkers
of Diabetic Nephropathy
Laura Pérez-López, Mauro Boronat, Carlos Melián,
Yeray Brito-Casillas, and Ana M. Wägner
Abstract
Diabetes mellitus (DM) is the first cause of end
stage chronic kidney disease (CKD). Animal
models of the disease can shed light on the
pathogenesis of the diabetic nephropathy
(DN) and novel and earlier biomarkers of the
condition may help to improve diagnosis and
prognosis. This review summarizes the most
important features of animal models used in
the study of DN and updates the most recent
progress in biomarker research.
Keywords
Animal models · Chronic kidney disease ·
Creatinine · Cystatin C · Diabetes mellitus ·
Diabetic nephropathy · Early markers ·
Glomerular filtration rate · Kidney injury
molecule-1 · Obesity · Symmetric
dimethylarginine
1 Introduction
Diabetic nephropathy (DN) is a common compli-
cation of diabetes mellitus (DM) occurring in
20–40% of people with diabetes (Dronavalli
et al. 2008). Although cardiovascular diseases
are the first cause of death, approximately
10–20% of people with DM die because of kid-
ney failure, and DM is considered the first cause
of end stage chronic kidney disease (CKD)
(World Health Organization (WHO) 2019).
Improved diagnosis and treatment of renal dis-
ease has led to better prognosis (Andrésdóttir
et al. 2014). Furthermore, detecting the disease
at an earlier stage and building on our understand-
ing of the mechanisms of the disease may help to
improve diagnosis further.
Recently, many reports have proposed a wide
number of markers of CKD, and it has been
shown that many of them reflect damage of one
specific part of the nephron (Colhoun and
Marcovecchio 2018; Domingos et al. 2016; Kim
et al. 2013; Kem et al. 2010; Carlsson et al. 2017;
L. Pérez-López and Y. Brito-Casillas
Institute of Biomedical and Health Research (IUIBS),
University of Las Palmas de Gran Canaria (ULPGC), Las
Palmas de Gran Canaria, Spain
M. Boronat and A. M. Wägner (*)
Institute of Biomedical and Health Research (IUIBS),
University of Las Palmas de Gran Canaria (ULPGC), Las
Palmas de Gran Canaria, Spain
Department of Endocrinology and Nutrition, Complejo
Hospitalario Universitario Insular Materno-Infantil, Las
Palmas de Gran Canaria, Spain
e-mail: ana.wagner@ulpgc.es
C. Melián
Institute of Biomedical and Health Research (IUIBS),
University of Las Palmas de Gran Canaria (ULPGC), Las
Palmas de Gran Canaria, Spain
Department of Animal Pathology, Veterinary Faculty,
University of Las Palmas de Gran Canaria, Las Palmas de
Gran Canaria, Arucas, Las Palmas, Spain

Colombo et al. 2019a). Albuminuria and
microalbuminuria have traditionally been consid-
ered as markers of glomerular damage, and they
have also been considered the first alterations that
can be detected in DN (American Diabetes Asso-
ciation 2004). However, recent studies have
shown that some patients with DM have CKD
in the absence of microalbuminuria (MacIsaac
et al. 2004; Lamacchia et al. 2018; Nauta et al.
2011; Zeni et al. 2017). In addition, the renal
tubule could also play an important role in the
development of DN (Colombo et al. 2019a). In
fact, proteinuria mainly occurs after increased
glomerular capillary permeability, but it is also a
result of impaired reabsorption by the epithelial
cells of the proximal tubule (D’Amico and Bazzi
2003). Thus, the use of tubular markers could also
be beneficial for the diagnosis of DN. Indeed, the
search for new renal biomarkers could lead to an
earlier detection of renal damage. Likewise, ani-
mal models are important for improved under-
standing of the development and progression of
DN. This review updates the most recent progress
in biomarker research and summarizes the most
important features of animal models used in the
study of DN.
2 Brief Review of Kidney
Anatomy and Physiology
The main functions of the kidney are filtration and
excretion of metabolic waste products from the
bloodstream, regulation of electrolytes, acidity
and blood volume, and contribution to blood
cell production (Rayner et al. 2016).
The nephron is the functional unit of the kid-
ney. Each nephron is formed by a glomerulus, a
proximal convoluted tubule, loop of Henle, and
distal convoluted tubule. The last part of the
nephron is the common collecting duct, and is
shared by many nephrons (Rayner et al. 2016;
National Institute of Diabetes and Digestive and
Kidney Disaese (NIDDK) 2019).
The glomerulus is the filtering unit of the
nephron. Within the glomerulus, the podocytes
are specialized cells lining the outer surfaces of
the bed of capillaries, which have interdigitated
foot processes that play an important role in the
process of filtration. In fact, podocyte damage
leads to proteinuria (Pavenstädt 2000) Podocytes
are part of the glomerular barrier, and protein
barrier passage of a normal kidney is mainly
composed by low molecular weight protein.
However, after its structural integrity is affected,
high molecular weight proteins can pass through
the glomerulus (D’Amico and Bazzi 2003).
In regard to the anatomy of the glomerulus, it
has two poles: (1) a vascular pole with the afferent
and the efferent arterioles; and (2) a urinary pole
with the exit to the proximal tubule. The blood is
filtered in a specialized capillary network through
the glomerular barrier, which yields the filtrated
substances into Bowman’s capsule space, and
then into the renal tubules. The glomerular barrier
is composed by five layers: (1) the inner layer is
the glycocalyx covering the surface of the endo-
thelial cells; (2) the fenestrated endothelium,
(3) the glomerular basement membrane, (4) the
slit diaphragm between the foot-processes of the
podocytes; and (5) the sub-podocyte space
between the slit diaphragm and the podocyte
cell body (Rayner et al. 2016).
Another important structure for the process of
filtration and for the regulation of blood pressure
is the juxtaglomerular apparatus, which is adja-
cent to the glomerulus. This structure is formed
by the macula densa (cells inside the cortical of
the thick ascending limb of Henle), mesangial
cells, and the terminal parts of the afferent arteri-
ole that include renin-producing cells. Release of
renin is stimulated by decreased sodium concen-
tration in the macula densa, systemic volume loss
or reduced blood pressure (Peti-Peterdi and Harris
2010; Castrop and Schießl 2014).
3 Pathophysiology of Diabetic
Nephropathy
Hyperglycemia, hypertension and obesity are
considered risk factors for DN (Mogensen et al.
1983; Câmara et al. 2017; Kanasaki et al. 2013).
Therefore, DN is a heterogeneous syndrome that
is common in people with type 1 (T1) and type
2 (T2) DM, although in patients with T2DM and
L. Pérez-López et al.

metabolic syndrome, more heterogeneous
mechanisms are involved. DN has been classi-
cally considered a process with the following
sequence of disorders: glomerular hyperfiltration,
progression of albuminuria, decline of glomerular
filtration rate (GFR) and, finally end stage renal
disease (Mogensen et al. 1983); and different
pathways that involve hemodynamic, metabolic
and inflammatory factors play a role in its devel-
opment (Table 1).
3.1 Hemodynamic Factors
Glomerular hyperfiltration is considered an alter-
ation of early DN and it has been identified in
10–40% of people with early T1DM, and around
40% of patients with T2DM (Mogensen et al. 1983;
Premaratne et al. 2015). However, its role as a
leading cause of DN needs further research. In addi-
tion, the hyperfiltration mechanism is not well
understood yet: it could be the result of a combina-
tion of hemodynamic, vasoactive, and tubular
factors (Dronavalli et al. 2008;Zenietal.2017).
Moreover, inhibition of tubuloglomerular feedback
could be the main mechanism involved (Zeni et al.
2017). Persistent hyperglycemia produces tubular
growth and increased tubular sodium reabsorption,
and reduces the delivery of sodium to the macula
densa, eliciting the release of renin and the activation
of the renin-angiotensin system (RAS). This leads to
an inhibition of the tubuloglomerular feedback,
causing vasodilation of the afferent arteriole, which
increases single-nephron glomerular filtration rate
and consequently leads to hyperfiltration
(Premaratne et al. 2015; Vallon and Thomson
2012). An implication of the sodium-glucose
co-transporter 2 (SGLT2) in this process has been
suggested. SGLT2s are expressed in the proximal
tubule and their function is the reuptake of glucose
and sodium (ratio 1:1), thus their activity is
stimulated by the increased glucose filtration in dia-
betic subjects (Zeni et al. 2017; Premaratne et al.
2015; Hans-Joachim et al. 2016). Vasodilating
substances, such as nitric oxide and cyclo-
oxygenase 2 derived prostanoids, also take part in
the hyperfiltration process (Wolf et al. 2005).
Whether they play a key or secondary role in the
pathogenesis of hyperfiltration is not well defined.
This process, which is associated with increased
intraglomerular pressure, could lead to podocyte
stress and nephron loss (Hans-Joachim et al.
2016). Additionally, obesity has been considered
as an independent risk factor for CKD, and
hyperfiltration has also been detected in
non-diabetic obese subjects. In addition, the kidney
produces components of the RAS that specifically
constrain the efferent rather than the afferent arteri-
ole, increasing GFR and glomerular pressure
(Yacoub and Campbell 2015). Several studies
have demonstrated local production of RAS
components in adipose tissue (Sharma and Engeli
2006; Giacchetti et al. 2002) and it has been
suggested that RAS could be overactivated in
patients with obesity (Sharma and Engeli 2006;Xu
et al. 2017). Indeed, a decrease in RAS activity has
been reported in obese women after weight loss
(Engeli et al. 2005).
Table 1 Main factors involved in the development of diabetic nephropathy
Mechanisms involved in the pathogenesis of diabetic nephropathy
Hemodynamic factors Metabolic and inflammatory factors
Vasodilation of the afferent arteriole of
the glomerulus
Increased formation of advanced glycation end-products
Increased glomerular filtration rate Podocyte stress
Implication of RAS, nitric oxide and
cyclo-oxygenase 2
TGF-β1 is a profibrotic cytokine that plays an essential role in inflammatory
and fibrotic processes
Increased glomerular pressure Obesity leads to increased leptin concentration, decreased adiponectin
concentration, and increased cytokine production
Abbreviations: RAS renin angiotensin system, TGF-β1transforming growth factor β1
Animal Models and Renal Biomarkers of Diabetic Nephropathy

3.2 Metabolic and Inflammatory
Factors
Formation of advanced glycation end-products
(AGE), resulting from the reduction of sugars, is
increased during chronic hyperglycemia. Accu-
mulation of AGE appears to stimulate production
of cytokines and renal fibrosis (Forbes and Coo-
per 2007). Infiltration by inflammatory cells
(monocytes, macrophages and lymphocytes)
precedes fibrosis, and these inflammatory cells
are responsible for the production of reactive
oxygen species, inflammatory cytokines and
profibrotic cytokines (Kanasaki et al. 2013).
Among the latter, transforming growth factor
beta 1 (TGF-β1) plays an essential role in inflam-
mation and fibrosis, and together with other
cytokines such as connective tissue growth factor,
platelet-derived growth factor and fibroblast
growth factor 2; TGF-β1 is involved in fibroblast
activation (Kanasaki et al. 2013). This produces
an increased deposition of extracellular matrix in
the interstitial space, as well as glomerular base-
ment membrane thickening, which could lead to
podocyte apoptosis and, as a consequence, to
increased vascular permeability in the glomerulus
(Wolf et al. 2005).
Additionally, in obese people, high leptin and
low adiponectin concentrations result in an
increased secretion of several adipokines
(i.e. tumor necrosis factor-a, interleukin-6,
interleukin-18) that promote an inflammatory state,
also leading to extracellular matrix accumulation
and renal fibrosis (Câmara et al. 2017; Straczkowski
et al. 2007;Kernetal.2001). In obese mice, reduced
plasma adiponectin contributes to albuminuria and
podocyte disfunction (Sharma et al. 2008).
3.3 Histologic Changes
The main histologic changes observed in kidneys
of people with diabetes are located in the glomer-
ulus, and include glomerular sclerosis
(Kimmelstiel-Wilson nodules), basement mem-
brane thickening and mesangial expansion.
Tubulo-interstitial and arteriolar lesions have
been commonly described as late lesions in
patients with T1DM. Nevertheless, some patients
with T2DM can show tubulo-interstitial and/or
arteriolar lesions with preserved glomerular struc-
ture (Fioretto and Mauer 2007).
4 Animal Models
4.1 Rodents
4.1.1 Mouse Models
Rodents are the most studied animal models of
human DN. They can show spontaneous or
induced diabetes (Kachapati et al. 2012; Song
et al. 2009), and DN might develop in the course
of the disease, or by induction of renal damage by
unilateral nephrectomy, or ischemia and reperfu-
sion (Song et al. 2009; Kitada et al. 2016). How-
ever, an animal model that develops all of the
features of DN is not available (Betz and Conway
2014). Based on the clinical characteristics of DN
in humans, the Animal Models of Diabetic
Complications Consortium (AMDCC) has
published some criteria to define acceptable
models of renal disease in mice with diabetes:
(1) 50% decline in GFR; (2) 100 fold increase in
proteinuria in comparison to matched controls of
the same strain, age and gender; (3) presence of
pathologic alterations such as mesangial sclerosis,
arterial hyalinosis, 50% thickening of the glomer-
ular basement membrane or tubulointerstitial
fibrosis. Nonetheless, to date, no animal model
fulfills all these criteria (Diabetes Complications
Consortium (DiaComp) 2003).
T1DM rodent models include streptozotocin
induced DM or spontaneous models due to genetic
mutations, such as AKITA and OVE26 mice.
T2DM genetic models are leptin deficient (ob/ob
mice) or have inactivating mutations in the leptin
receptor (db/db mice) (Kitada et al. 2016;Alpersand
Hudkins 2011), but there are also models of induced
T2DM, usually through a high fat diet (De Francesco
et al. 2019; Ingvorsen et al. 2017). Hypertension
plays an important role in the progression of
human DN, and the deficiency of endothelial nitric
oxide synthase (eNOS) through knockout of eNOS
genes, has led to accelerated renal damage in db/db
L. Pérez-López et al.

and streptozotocin-treated mice. eNOS
/
C57BL/
J
db
mice can develop T2DM, obesity, hypertension,
albuminuria, marked mesangial expansion and
mesangiolysis (Nakagawa et al. 2007).
Recently, the black and tan, brachyury (BTBR
obese) mouse strain, which is spontaneously insu-
lin resistant, has gained importance in the field of
the study of DN. This strain with ob/ob leptin
deficiency mutation on BTBR mouse back-
ground, has been considered one of the best
models of human DN because it rapidly develops
pathological changes seen in human DN, such as
increased glomerular basement membrane thick-
ness, mesangial sclerosis, focal arteriolar
hyalinosis, mesangiolysis, mild interstitial fibro-
sis and podocyte loss (Hudkins et al. 2010).
4.1.2 Rat Models
The most studied rat models are the Zucker dia-
betic fatty (ZDF-fa/fa) rat and the Wistar fatty rat
(Kitada et al. 2016; Hoshi et al. 2002). Both have
an autosomal recessive mutation in the fa gene
that encodes the leptin receptor, and both are
crossbred with the insulin resistant Wistar Kyoto
rats. The ZDF-fa/fa and Wistar fatty rats can
develop albuminuria and renal alterations, such
as tubular cell damage and tubulointerstitial fibro-
sis, although nodular glomerular lesions or
mesangiolysis have not been observed (Kitada
et al. 2016; Hoshi et al. 2002). Another rat strain
that is considered a model of DN is The Otsuka
Long-Evans Tokushima Fatty (OLETF), in which
multiple recessive genes are involved in the
development of DM. These rats exhibit mild obe-
sity, hyperinsulinemia with late onset of
hyperglycaemia, and can present mesangial
matrix expansion, glomerulosclerosis and tubular
cell damage (Kawano et al. 1994,1992).
4.2 Companion Animals
These animals have a great interest as animal
models since they develop spontaneous DM and
share the human environment (Brito-Casillas
et al. 2016). However, it is unclear if dogs and
cats with diabetes develop DN.
4.2.1 Cats
Around 80% of cats with DM have T2DM (Nel-
son and Reusch 2014). As in humans, obesity is a
risk factor for DM, which also represents a prob-
lem of an epidemic proportion since approxi-
mately 35–50% of domestic cats are overweight
or obese (Hoenig 2012). Obese cats also show
some of the disorders observed in people with the
metabolic syndrome; they can present insulin
resistance and higher concentrations of very
low-density lipoproteins (VLDL), triglycerides
and cholesterol (Hoenig 2012; Jordan et al.
2008). Despite these alterations, hypertension
has not been linked to feline obesity or DM, and
atherosclerosis has not been described either
(Jordan et al. 2008; Payne et al. 2017). Lower
concentration of angiotensin-converting enzyme
2 has been found in the subcutaneous adipose
tissue of overweight or obese cats compared to
those with a low body condition score, but
whether this could represents a negative mecha-
nism against blood pressure is unknown (Riedel
et al. 2006).
Additionally, the link between DM and renal
disease is unclear in cats, and discrepancies can
be found in the literature. In two retrospective,
epidemiological studies, no relationship was
found between both diseases (Greene et al.
2014; Barlett et al. 2010). In contrast, higher
prevalences of proteinuria and microalbuminuria
have been detected in cats with DM compared to
age matched controls (Al-Ghazlat et al. 2011)
and, recently, in a retrospective study of a popu-
lation of 561 adult cats, age-adjusted multivariate
regression analysis showed an association
between both diseases (Pérez-López et al. 2019).
Thus, the cat could be a useful model of DN,
although prospective studies are still needed for
a better understanding and evaluation of the asso-
ciation between feline DM and renal disease.
4.2.2 Dogs
Obesity in dogs is able to induce
hyperinsulinemia, to increase blood pressure and
to produce glomerular hyperfiltration. Dogs with
obesity can develop structural changes in the kid-
ney, such as glomerular basal membrane
Animal Models and Renal Biomarkers of Diabetic Nephropathy

thickening and mesangial expansion (Henegar
et al. 2001). Insulin sensitivity decreases around
35% in obese dogs. However, obesity does not
cause T2DM in these animals (Chandler et al.
2017). Indeed, T1DM is the most commonly
recognized form of DM in dogs, although they
can also develop DM secondarily to dioestrus,
Cushing’s syndrome or medications (Nelson and
Reusch 2014). Regarding the relationship
between DM and CKD, it has not been fully
investigated in dogs. However, some studies
have shown that markers of vascular resistance
(ultrasound renal resistive index and pulsatility
index), which are associated with progression of
kidney disease and hypertension in humans, are
also positively correlated with glycemic status in
dogs (Priyanka et al. 2018; Novellas et al. 2010).
In a case-control and age-matched study, dogs
with alloxan-induced DM, uninephrectomized
4 weeks after the induction of DM, were proposed
as a valuable model for the study of DN, since
they developed greater glomerular basement
membrane thickening and mesangial expansion,
compared to controls, already 1 year after DM
induction (Steffes et al. 1982).
4.3 Production Animals
Mainly two species could represent this group as
animal models of DN: rabbits and swine. How-
ever, few studies have been reported on rabbits,
and they have been mainly focused on the role of
obesity in kidney function (Dwyer et al. 2000;
Antic et al. 1999). One study showed an increased
hyaluronean content in the renal medulla of
rabbits with induced high-fat diet induced obesity
(Dwyer et al. 2000). Higher renal medullary
hyaluronean content has also been reported in
humans and rodent models with DM or with
renal alterations (Stridh et al. 2012). In regard to
the swine, it is considered a more valuable animal
model, since it closely resembles human anatomy
and physiology (Zhang and Lerman 2016;Li
et al. 2011; Rodríguez-Rodríguez et al. 2020;
Spurlock and Gabler 2008). Metabolic syndrome
can be induced through high fat diet in the
Ossabaw and Iberian swine. These pigs exhibit
obesity, insulin resistance, hypertension and
dyslipidemia. Regarding renal disease, kidney
hypertrophy, increased GFR, renal tubular fibro-
sis and renal adiposity have all been reported
(Zhang and Lerman 2016; Li et al. 2011;
Rodríguez-Rodríguez et al. 2020).
Further information in relation to animal
models can be found in Table 2.
5 Assessment of Renal Function
Criteria to diagnose CKD are well established in
human medicine. However, there are a large num-
ber of markers, many still under investigation,
that could allow an early detection of impaired
renal function. The assortment of markers also
represents a variety of mechanisms involved in
kidney injury, reflecting damage of different parts
of the nephron as well (Fig. 1).
5.1 Routine Evaluation of DN
and Gold Standard Methods
In humans, CKD is defined as abnormalities of
kidney structure or function, present for more
than 3 months, and with implications for health.
Patients with altered kidney function present
albuminuria and/or a decline in GFR (Levin
et al. 2013).
Human DN is diagnosed when urinary albu-
min to creatinine ratio (ACR) is above 30 mg/g,
although some guidelines recommend the use of
different ACR thresholds for men (>25 mg/g) and
women (>35 mg/g). Despite ACR being the main
tool used to diagnose DN, some patients with
either T1 or T2DM who have decreased GFR do
not show elevated ACR (Gross et al. 2005;
Caramori et al. 2003). Therefore, GFR should
also be measured in patients with DM to rule
out CKD. In fact, estimation of GFR is considered
the routine method to evaluate renal function in
patients with CKD. The most recent guidelines
recommend the interpretation of both albuminuria
and GFR for the diagnosis and staging of CKD
(Levin et al. 2013).
L. Pérez-López et al.

Table 2 Animal models of diabetic nephropathy
Animal models of induced diabetes with development of DN
Animal models of spontaneous diabetes
with development of DN
Spontaneous animal model of diabetes and unclear
development of DN
Animal model Advantages Disadvantages
Animal
model Advantages Disadvantages
Animal
model Advantages Disadvantages
Models
of
T1DM
Streptozotocin
treated
C57BL/6
mouse
The most studied
strain
Less susceptibility to
develop renal injury
than other strains
AKITA
mouse.
Early
pathological
changes of DN
Strain-
dependent
susceptibility
Diabetic
dog
Gene-environment
interaction
Development
of DN is still
unclear
Easy to breed and
long life span
Environmental
factors shared with
humans
Streptozotocin
treated DBA/2
mouse
More susceptible to
renal injury than
C57BL/6 mouse
Tubulointerstitial
fibrosis does not occur
OVE26
mouse
To study
advanced DN
Poor viability
Models
of
T2DM
C57BL/6
mouse on high
fat diet
Develops
metabolic
syndrome
(increased SBP and
lipids)
Inter-individual
phenotypic variability
of the amount of food
intake after receiving a
high fat diet
eNOS
/
/db/
db
mouse
Development
of glomerular
lesions
characteristic
of advanced
DN
Few studies,
possible
difficulties
with breeding
Diabetic
cat
Similar mechanisms
of human T2DM,
with environmental
factors and polygenic
interactions
Development
of DN is still
unclear
Renal injury could
be due to renal
lipid accumulation
Phenotype more
pronounced in males
Zucker
diabetic fatty
(ZDF-fa/fa) rat
Development of
tubulointerstitial
fibrosis
Does not develop
features of advanced
DN
BTBR
ob/ob
mice
Rapidly
resembles
alterations of
advanced
human DN
Modest
interstitial
fibrosis
Ossabaw pig
on high fat diet
Develops
metabolic
syndrome,
increased GFR,
renal tubular
fibrosis, renal
adiposity
Expensive and
specialized
husbandry
Abbreviations: IgG immunoglobulin G; kidney injury molecule -1, NGAl neutrophil gelatinase-associated lipocalin, SDMA symmetric dimethylarginine, VEGF vascular
endothelial growth factor, RBP4 retinol binding protein 4, suPAR soluble urokinase type plasminogen activator receptor, TGFβ1transforming growth factor β-1
Animal Models and Renal Biomarkers of Diabetic Nephropathy

The gold standard for assessing GFR is the
plasma or urinary clearance of an exogenous fil-
tration marker, such as inulin (Stevens and Levey
2009), Cr-EDTA,
125
I-iothalamate or iohexol.
However, direct GFR measurement is difficult to
perform and is time-consuming; it requires the
injection of a suitable marker and several urine
sample collections (Stevens and Levey 2009;
Levey et al. 2003). Alternatively, equations for
estimation of GFR, generally based on serum
creatinine levels, are used in clinical practice,
and their use is recommended in conjunction
with other markers of renal function, such as
cystatin C (Levin et al. 2013). However, early
alterations of DN are usually associated with
hyperfiltration, and these equations are less pre-
cise at higher values of GFR, and tend to under-
estimate GFR in the hyperfiltration state (Levin
et al. 2013; Tuttle et al. 2014). Among available
formulas, the Chronic Kidney Disease Epidemi-
ology Collaboration (CKD-EPI) has been
suggested to be the best one to evaluate early
renal impairment in patients with DM,
normoalbuminuria and hyperfiltration (Lovrenčić
et al. 2012).
.
Recent studies suggest that the
CKD-EPI cystatin C based equations for estima-
tion of GFR, are those that best fit the GFR
measurement in patients with DM. However, in
general, it is considered that GFR equations show
high variability in people with DM (Cheuiche
et al. 2019).
As stated above, the development of DN is
unclear in companion animals, but diagnosis of
CKD is based on serum creatinine or symmetric
dimethylarginine (SDMA) concentration together
with urinary protein-creatinine ratio (International
Renal Interest Society (IRIS) 2015a,2017), and
there is still a lack of standardization in the
methods of GFR measurement and their interpre-
tation (International Renal Interest Society (IRIS)
2015b). Only one study proposed a method to
estimate GFR in cats. It was based on serum
creatinine and it was adjusted for a marker of
muscle mass. However, this formula did not
prove to be a reliable estimation of GFR (Finch
et al. 2018).
Glomerular filtration:
Creatinine
SDMA
Cystatin C
Glomerular barrier:
IgG
Albumin
Proximal tubule:
Cystatin C
RBP4
KIM-1
Thick ascending
limb of Henle’s
loop and distal
tubule:
Uromodulin
NGAL
Collecting duct:
NGAL
Inflammation and fibrosis:
TGFβ1
VEGF
suPAR
Fig. 1 Classification of markers of renal damage according to part of the nephron involved
L. Pérez-López et al.

5.2 Indirect Markers of Glomerular
Filtration Rate
5.2.1 Serum Creatinine
Creatinine is a break-down product of creatine
phosphate in muscle tissue (113 Daltons). It is
not metabolized and is entirely cleared by the
kidneys with minimal reabsorption by the renal
tubules (Ferguson and Waikar 2012; Kavarikova
2018). Thus, blood creatinine concentration
increases when GFR declines. However, in the
early stage of CKD, subtle changes in GFR do not
alter creatinine concentration. In humans, other
markers seems to correlate better with GFR than
creatinine (El-khoury et al. 2016) and, in dogs, its
concentrations increase only when around 50% of
renal function has been lost (Hokamp and Nabity
2016; Nabity et al. 2015). In addition, both in
humans and companion animals, creatinine con-
centration depends on lean body mass, and it has
high inter-individual variability (Delanaye et al.
2017; Hall et al. 2014a,2015). Other factors, such
as hydration and blood volume status, urinary
obstructions or urinary infections, can also affect
creatinine concentration (Hokamp and Nabity
2016; Blantz 1998).
5.2.2 Symmetric Dimethylarginine
SDMA is a catabolic product of arginine-
methylated proteins (202 daltons), which is
mainly excreted through the kidneys and is not
reabsorbed or secreted by the tubules (Nabity
et al. 2015; McDermott 1976). Thus, SDMA con-
centration is affected by GFR in inverse linear
relationship in humans and in companion animals
(Pelander et al. 2019; Hall et al. 2014b; Relford
et al. 2016). Studies in companion animals have
shown that, in contrast to creatinine, SDMA is not
affected by muscle mass (International Renal
Interest Society (IRIS) 2015a,2017). On the
other hand, human studies have found no correla-
tion or an inverse correlation between SDMA and
body mass index (Schepers et al. 2011;
Schewedhelm et al. 2011; Potočnjak et al.
2018). Furthermore, discrepancies in the levels
of SDMA in patients with DM have been reported
among different studies. The offspring cohort
study from the Framingham Heart Study did not
find a relationship between SDMA and insulin
resistance (Schewedhelm et al. 2011). Moreover,
an inverse correlation between SDMA and
glycosylated hemoglobin or fructosamine levels
has been reported in T2DM patients, i.e. those
with poor glycemic control had lower SDMA
concentration (Can et al. 2011). In another
study, SDMA was increased in patients with
T2DM and microalbuminuria, and this marker
predicted impaired renal function and cardiovas-
cular disease in this population (Zobel et al.
2017). Additionally, SDMA has been positively
associated with proteinuria and inversely
associated with GFR in patients with CKD
and T2DM, and SDMA to asymmetric
dimethylarginine (ADMA) ratio was one of the
strongest predictive markers of renal function
decline (Looker et al. 2015). ADMA is another
byproduct of the proteolytic breakdown of
nuclear proteins. It is an inhibitor of NOS and is
considered to play a role in endothelial dysfunc-
tion (Sibal et al. 2010).
Interestingly, another study showed that young
patients with T1DM and microalbuminuria and
high GFR, had lower SDMA concentrations com-
pared to normoalbuminuric T1DM patients; and
over time, microalbuminuric patients showed an
increment in SDMA concentration, probably
reflecting a decline in GFR (Marcovecchio et al.
2010). Therefore, the lower levels of SDMA
observed in patients with DM might be explained
by hyperfiltration occurring in the early stages of
DN. However, this requires further investigation,
as other explanations have been suggested (Zsuga
et al. 2007; Closs et al. 1997; Simmons et al.
1996; Siroen et al. 2005; Nijveldt et al. 2003).
In cats with DM, lower levels of SDMA have
also been observed. However, in this species,
further research on the relationship between DM
and CKD is still needed (Langhorn et al. 2018).
In relation to the inverse association observed
between SDMA and GFR, one study in humans,
comparing SDMA to the renal clearance of an
exogenous molecule (
125
I–sodium iothalamate),
showed that SDMA had a stronger inverse corre-
lation with GFR than creatinine (El-khoury et al.
2016). In contrast, in dogs, the inverse correlation
Animal Models and Renal Biomarkers of Diabetic Nephropathy

between SDMA and GFR determined through
iohexol clearance was similar to the correlation
observed between creatinine and GFR. However,
SDMA was considered an earlier marker of GFR
than creatinine, as SDMA was able to detect a
decrease in renal function <20% on average,
whereas creatinine increased when renal function
was reduced by 50% (Hall et al. 2016). Similarly,
in cats, the inverse correlation between SDMA
and GFR measured by iohexol clearance was
similar to the correlation observed between creat-
inine and GFR, but the sensitivity to detect
impaired renal function was higher using SDMA
(100 vs 17%) (Hall et al. 2014b). The established
International Renal Interest Society guidelines
consider that SDMA persistently >14 ng/ml is
consistent with CKD (International Renal Interest
Society (IRIS) 2015a). This cut-off (>14 ng/ml)
of SDMA is able to detect a decrease of 24% from
the median of GFR established for healthy cats,
with a sensitivity of 91% (Hall et al. 2014b).
5.3 Markers of Glomerular Damage
5.3.1 Urine Albumin
Albumin is an intermediate molecular weight pro-
tein (69 KD) and its urinary concentration could
increase with moderate disorders affecting the
permeability of the glomerular barrier (D’Amico
and Bazzi 2003). The initial alterations of the
glomerular barrier usually involve a loss of
restriction to passage of negatively charged
proteins (especially albumin). Albuminuria can
also occur when the tubular cells are damaged
and tubular reabsorption is impaired, although
intense albuminuria is usually glomerular in ori-
gin (Nauta et al. 2011;D’Amico and Bazzi 2003).
The evaluation of a single albumin measurement
is not recommended because it can vary during
the day. Therefore, the measurement of urinary
ACR in a random or first morning sample, or
through a 24 h urine collection, with a measure-
ment of creatinine, is advised (Basi et al. 2008). In
addition, diabetic rodent models that develop
albuminuria are considered particularly useful
for the study of human DN (Diabetes
Complications Consortium (DiaComp) 2003). In
rats, microalbuminuria has been associated with
reduced albumin reabsorption in the proximal
tubule in early DN (Tojo et al. 2001). Some
studies have used ACR to study renal function
in dogs (Tvari-jonaviciute 2013). However, in
clinical practice of small domestic animals, the
protein creatinine ratio is used instead of albumin.
Although clinical interpretation of albuminuria is
not well established in dogs and cats, borderline
protein-creatinine ratio between 0.2 and 0.5 mg/
mg in dogs, and between 0.2 and 0.4 mg/mg in
cats, are suggestive of microalbuminuria, and its
monitorization is recommended (International
Renal Interest Society (IRIS) 2017). It should
also be highlighted that albuminuria is not spe-
cific for kidney function and it could appear in the
presence of non-renal diseases (i.e., hyperadreno-
corticism, urinary tract infections or neoplasms)
(Kivarikova 2015).
5.3.2 Urine Immunoglobulin G
Immunoglobulin (IgG) is a high molecular weight
protein (160 kDa) that is involved in antibody-
mediated immunity. Due to its size, this protein
cannot pass through an intact glomerular barrier.
Therefore, urine detection of IgG reflects glomer-
ular damage (D’Amico and Bazzi 2003). IgG has
been associated with albuminuria in patients with
DM (Carlsson et al. 2017), but few studies have
investigated IgG in animals. In dogs, urine detec-
tion of IgG has been associated with X-linked
hereditary nephropathy even before the onset of
proteinuria. The authors hypothesized that in
dogs some degree of alteration of the glomerular
basement membrane could allow the passage of
proteins not detected by the usual assays to mea-
sure proteinuria (Nabity et al. 2012). Similarly, in
humans, IgG has been detected in normo-
albuminuric patients with T2DM, and it has
been considered a predictive marker of albumin-
uria (Narita et al. 2006).
5.4 Markers of Tubular Damage
5.4.1 Serum and Urine Cystatin C
Cystatin C is a low molecular weight protein
(13 kDa) that is considered as a marker of both
L. Pérez-López et al.

GFR and proximal tubular damage. Cystatin C is
freely filtered by the glomerulus, and it is almost
entirely reabsorbed in the proximal tubule by
megalin-mediated endocytosis (Mussap and
Plebani 2004; Kaseda et al. 2007). Its inverse
correlation with GFR is better than that observed
between creatinine and GFR (El-khoury et al.
2016). In addition, studies in animal models
have suggested that cystatin C could reflect
impaired kidney function earlier than creatinine
(Song et al. 2009; Togashi and Miyamoto 2013).
For example, after ischaemia-reperfusion injury,
partial unilateral nephrectomy and bilateral
nephrectomy, serum cystatin C concentration
increased before creatinine in BALB/c mice
models (Song et al. 2009). Another report
observed that, in comparison to Zucker diabetic
lean rats, Zucker Diabetic Fatty rats showed
elevations of urinary cystatin C concentration,
along with other renal biomarkers of kidney injury
(β2-microglobulin, clusterin, mu-glutathione
S-transferase and kidney injury molecule-1
(KIM-1)), but not of serum creatinine, before the
appearance of kidney histopathological changes
(Togashi and Miyamoto 2013). Additionally, in
this study, the authors observed that immunohisto-
chemical cystatin C expression was predominantly
localized in the proximal tubules of the renal cor-
tex, supporting a role of tubular damage in the
development of kidney injury due to obesity
(Togashi and Miyamoto 2013).
Furthermore, some advantages of cystatin C as
a marker of CKD compared to creatinine should
be highlighted. In humans, it is less affected by
muscle mass than creatinine and it has lower
inter-individual variability (Stevens et al. 2009).
However, it should be taken into account that the
concentration of cystatin C is subjected to
changes in people with thyroid disorders or glu-
cocorticoid treatment (Risch and Huber 2002;
Fricker et al. 2003).
In human medicine, clinical practice
guidelines for the evaluation and management of
CKD recommend the measurement of cystatin C,
especially in those patients in whom estimated
GFR, based on serum creatinine, might be
expected to be less accurate, or in those patients
with early stages of CKD (estimated GFR
between 45–59 ml/min/1.73 m
2
), who do not
have other markers of kidney damage (Levin
et al. 2013). Additionally, cystatin C might be a
predictor of impaired renal function in patients
with T2DM and, although its concentration can
reach higher levels in macroalbuminuric patients,
it is independently associated with GFR, and an
increase in serum and urine cystatin C concentra-
tion has been observed in subjects with DM,
normoalbuminuria and decreased GFR (Kim
et al. 2013; Jeon et al. 2011). Thus, cystatin C
might predict DN in the early stages of impaired
renal function in patients with T2DM (Kim et al.
2013; Jeon et al. 2011).
In contrast, in veterinary medicine, the use of
cystatin C does not seem so advantageous. In cats,
serum cystatin C was not found to be a reliable
marker of GFR, and in regard to urinary cystatin C,
one study showed higher concentrations of this
marker in cats with CKD compared to healthy
cats, although, urinary Cystatin C was below the
detection limit of the assay in some of the cats with
CKD (Ghys et al. 2016; Williams and Archer
2016). In addition, one study reported lower
cystatin C concentration in cats with DM com-
pared to healthy cats (Paepe et al. 2015), although
in this species it is not clear whether CKD could
occur secondarily to DM (Greene et al. 2014;
Barlett et al. 2010;Al-Ghazlatetal.2011; Pérez-
López et al. 2019;Zinietal.2014).
In a similar manner, in dogs, serum cystatin C
does not seem to be superior to creatinine, either,
and the sensitivity of cystatin C to detect CKD
has been considered similar to SDMA and creati-
nine, whereas its specificity was lower (Pelander
et al. 2019; Almy et al. 2002; Marynissen et al.
2016).
5.4.2 Retinol-Binding Protein 4 (RBP4)
Retinol-binding protein is a low molecular weight
protein (21 kDa) that acts as the transport protein
for retinol in plasma. It is produced in the liver
and circulates in plasma bound to transthyretin
(TTR), a protein with a molecular weight of
54 kDa that is too large to pass through the
glomerular barrier. However, around 4–5% of
serum RBP4 circulates freely and can pass
through this barrier, to be then reabsorbed by
Animal Models and Renal Biomarkers of Diabetic Nephropathy

tubular epithelial cells (Christensen et al. 1999).
When tubular damage occurs, reabsorption of
retinol is decreased, with subsequent loss of
RBP4 into the urine (Zeni et al. 2017). Urinary
RBP4 has been considered as a predictive marker
of CKD in humans and of microalbuminuria in
patients with T2DM (Domingos et al. 2016; Park
et al. 2014). However, one study suggested that
serum RBP4 does not seem to be a better marker
than creatinine or cystatin C to detect GFR
impairment (Donadio et al. 2001). On the other
hand, serum retinol has also been considered a
marker of insulin resistance and cardiovascular
risk factors in humans and animal models (Park
et al. 2014; Cabré et al. 2007; Mohapatra et al.
2011; Graham et al. 2006; Yang et al. 2005;
Akbay et al. 2010), and it could be interesting
for the study of early renal alterations in patients
with metabolic syndrome. Mouse models have
demonstrated that transgenic overexpression of
human RBP4, or injection of recombinant
RBP4, leads to insulin resistance (Yang et al.
2005), although a few reports disagree on this
association (Von Eynatten et al. 2007; Henze
et al. 2008).
In dogs and cats, higher urinary RBP4 concen-
tration has been observed in animals with CKD
compared to healthy animals (van Hoek et al.
2008; Chakar et al. 2017).
5.4.3 Uromodulin (Tamm-Horsfall
Protein)
Uromodulin is a 100 kDa protein synthetized by
the epithelial cells of the thick ascending limb of
Henle’s loop and the distal convoluted tubule
(Hokamp and Nabity 2016). Therefore, in healthy
individuals it is normal to find uromodulin in
urine samples, whereas in patients with tubular
damage its urinary concentration is low or even
absent (Chakraborty et al. 2004; Steubl et al.
2016). Correlation between uromodulin and
GFR has only been assessed through equations
of estimated GFR, and conflicting results have
been reported. Whereas urinary uromodulin is
positively correlated to GFR, the correlation
between GFR and serum uromodulin has been
reported as positive or negative, depending on
the study (Möllsten and Torffvit 2010; Prajczer
et al. 2010; Fedak and Kuźniewski 2016;
Wiromrat et al. 2019). Nonetheless, several
reports have observed that plasma or serum
uromodulin concentrations are lower in patients
with nephropathy. Uromodulin could be an indi-
cator of renal damage in people with and without
DM (Chakraborty et al. 2004; Steubl et al. 2016;
Möllsten and Torffvit 2010). Kidneys of patients
with very low levels of serum and urinary
uromodulin show more tubular atrophy and
decreased concentration is present at the earliest
stages of CKD (Prajczer et al. 2010). However, in
dogs, uromodulin has been considered a progres-
sion marker rather than an early marker of CKD
(Chakar et al. 2017).
Additionally, studies in uromodulin knockout
mice showed that it has a protective role against
urinary tract infections and renal stone formation
(Rampoldi et al. 2011; Bates et al. 2004; Liu et al.
2010). However, in humans, mutations in the
gene encoding uromodulin lead to a rare autoso-
mal dominant disease, which causes tubuloin-
terstitial damage, but these patients do not show
increased rates of urinary tract infections or renal
stone formation (Rampoldi et al. 2011).
5.4.4 Neutrophil Gelatinase-Associated
Lipocalin (NGAL)
NGAL is a low molecular weight protein of
25 kDa belonging to the lipocalin protein super-
family that is produced in the renal tubules (thick
ascending limb of Henle’s loop, distal tubule, and
collecting duct) after inflammation or tissue
injury (Singer et al. 2013). Its concentration may
also be increased in case of impaired proximal
tubular reabsorption (Singer et al. 2013).
In patients with DM, urinary NGAL shows an
inverse correlation with GFR and a positive cor-
relation with albuminuria (Kem et al. 2010;Fu
et al. 2012a; Nielsen et al. 2011; Vijay et al.
2018). In addition, NGAL concentrations are
higher in normoalbuminuric patients with DM,
compared to non-diabetic control subjects,
which might suggest that tubular damage could
be one of the earliest alterations in patients with
DN (Nauta et al. 2011; Vijay et al. 2018). More-
over, higher levels of urinary NAGL have been
observed in T2DM diabetic patients with
L. Pérez-López et al.

glomerular hyperfiltration compared to T2DM
with normal GFR and control subjects (Fu et al.
2012b).
In addition, NGAL has been proposed as a
useful indicator of acute kidney injury in human
medicine (Singer et al. 2013; Haase et al. 2011)
and most studies in animal models focus on its
utility to detect acute kidney injury. In dogs,
plasma and urinary NGAL are able to distinguish
dogs with CKD from those with acute kidney
injury (Steinbach et al. 2014). In contrast, in cats
with CKD, this marker did not increase until the
cats reached an advanced stage of the disease
(Wang et al. 2017). Additionally, it should be
highlighted that NGAL concentration could be
influenced by other conditions, such as urinary
tract infections, different types of neoplasms, pre-
eclampsia and obstructive pulmonary disease
(Giasson et al. 2011; Fjaertoft et al. 2005;
Keatings and Barnes 1997; Bolignano et al.
2010).
5.4.5 Kidney Injury Molecule -1 (KIM-1)
KIM-1 is a type 1 transmembrane glycoprotein
(90 kDa) located in the proximal tubules and,
after tubular injury, its concentration rises before
serum creatinine, whereas it is not detected in the
urine of humans or other species without kidney
damage (Moresco et al. 2018). KIM-1 is a well-
known marker of acute kidney injury, and some
studies suggest that it might be a good marker for
CKD since its concentrations are high in humans
with low GFR or albuminuria. Additionally, in
humans with T2DM and normoalbuminuria or
mild albuminuria, an increment of the urinary
concentration of this marker has been observed
(De Carvalho et al. 2016). Its ability to predict
DN requires further investigation since
discrepancies have been observed (Colombo
et al. 2019a; Nauta et al. 2011). Two longitudinal
studies showed that, the use of KIM-1 in T2DM,
together with pro b-type natriuretic peptide or
beta 2 microglobulin, GFR and albuminuria,
seemed to improve prediction of kidney function
decline (Kammer et al. 2019; Colombo et al.
2019b). In contrast, another study reported that
KIM-1 was not associated with albuminuria
(Nauta et al. 2011), and, in a longitudinal, multi-
center study in T1DM, it did not improve the
prediction of progression of DN compared to
albuminuria and estimated GFR, either (Panduru
et al. 2015). In another large study, from an
extensive set of biomarkers, KIM-1 and CD27
antigen combined, were the most important
predictors of DN progression, although their pre-
dictive power did not improve that of historical
estimated GFR and albuminuria. (Colombo et al.
2019a). It should also be highlighted that other
conditions such as sepsis and urinary tract disease
can increase urinary KIM-1 (Moresco et al.
2018).
In animal models, higher concentrations of this
marker have been observed in a rat model of
T2DM (Otsuka Long-Evans Tokushima Fatty
rats) than in healthy rats (Otsuka Long-Evans
Tokushima rats), and an increase of its concentra-
tion was observed prior to the development of
hyperfiltration and prior to the increment of
serum creatinine concentration (Hosohata et al.
2014).
5.5 Markers of Fibrosis
and Inflammation
5.5.1 Transforming Growth Factor-b1
(TGFb1)
TGFβ1 is a cytokine and pro-fibrotic mediator of
kidney damage. It is secreted in an inactivated
form associated with the large latent complex
(LLC) and it has a biological effect only after it
is liberated from the LLC as active TGFβ1, a
process which takes part in the extracellular
matrix (August and Suthanthiran 2003; Lawson
et al. 2016; Sureshbabu et al. 2016; Hinz 2015).
In kidneys, increased production of active TGFβ1
leads to interstitial fibrosis, mesangial matrix
expansion and glomerular membrane thickening,
and, as a consequence, kidney damage and reduc-
tion in GFR (August and Suthanthiran 2003;
Sureshbabu et al. 2016; Ziyadeh 2004). Animal
models have shown that TGFβ1 could also par-
ticipate in podocyte detachment or apoptosis,
stimulating podocyte expression of VEGF that
Animal Models and Renal Biomarkers of Diabetic Nephropathy

acts in an autocrine loop, leading to increased
production of 3(IV) collagen, which probably
contributes to the thickening of the glomerular
basement membrane (Chen et al. 2004).
According to an in vitro study, TGFβ1 could
also cause oxidative stress in podocytes by itself
(Lee et al. 2003). As a consequence of podocyte
injury, proteinuria can occur (Nagata 2016).
In vitro studies have also demonstrated that
high glucose concentration stimulates TGFβ1
secretion and activation, and this marker has
been proposed as an important mediator of DN
in animal models (Ziyadeh 2004; Rocco et al.
1992; Hoffman et al. 1998). Also, in humans,
high levels of serum and urinary TGFβ1 have
been observed in a systematic review that
included T2DM patients, showing a positive cor-
relation with albuminuria (Qiao et al. 2017).
Treatment with angiotensin-converting enzyme
inhibitors has been demonstrated to decrease uri-
nary ACR and plasma TGFβ1, and the latter has
been put forward as a mechanism mediating their
nephroprotective effects (Andrésdóttir et al.
2014). Moreover, in the db/db mouse, treatment
with a neutralizing anti-TGFβ1 antibody avoids
the progression of diabetic renal hypertrophy,
mesangial matrix expansion, and the develop-
ment of renal insufficiency, albeit in the absence
of a significant reduction in albuminuria (Ziyadeh
et al. 2000).
In companion animals, this marker has been
studied to investigate DN in cats, where an incre-
ment of urinary activated TGFβ1:creatinine ratio
precedes the onset of azotemia by 6 months
(Lawson et al. 2016).
5.5.2 Vascular Endothelial Growth
Factor (VEGF)
VEGF, also named vasopermeability factor, is a
homodimeric glycoprotein with different
isoforms and heparin-binding properties. VEGF
promotes permeability, has mitogenic functions
in endothelial cells and is an important angio-
genic factor (Khamaisi et al. 2003; Neufeld et al.
1999). In the kidney, reduction of oxygen deliv-
ery contributes to inflammation pathways and is
the main stimulus for VEGF expression. (Mayer
2011; Ramakrishnan et al. 2014).
In regard to DN, although in vitro studies have
demonstrated that chronic hyperglycemia is able
to increase the production of the VEGF protein
and VEGF mRNA expression (Cha et al. 2000;
Williams et al. 1997), in humans with DM it is
uncertain whether VEGF levels increase or
decrease with DN. Down-regulation of VEGF-A
mRNA expression has been observed in renal
biopsies of patients with DM, and its lower
expression was associated with podocyte loss
(Baelde et al. 2007). However, two other studies
have shown higher concentrations of plasma and
urinary VEGF in people with T1DM and T2DM,
respectively (Hovind et al. 2000; Kim et al.
2004), and higher urinary VEGF was found in
those with advanced DN. Indeed, intervention
studies also show conflicting results: both VEGF
inhibition and VEGF administration improve kid-
ney function (Schrijvers et al. 2005; Kang et al.
2001).
Additionally, there is scarce information on
the role of VEGF in kidney function in compan-
ion animals, in which the study of VEGF has been
focused on its role in tumor angiogenesis
(Millanta et al. 2002; Clifford et al. 2001; Platt
et al. 2006). One study detected lower
concentrations of urinary VEGF-A creatinine
ratio in cats with CKD compared to healthy cats
(Habenicht et al. 2013).
5.5.3 Soluble Urokinase Type
Plasminogen Activator Receptor
(suPAR)
Soluble urokinase-type plasminogen activator
receptor (suPAR) is the circulating form of mem-
brane protein urokinase receptor (uPAR), which
is a glycosyl-phosphatidylinositol–anchored
three-domain membrane protein that is expressed
on podocytes and other cells (immunologically
active cells and endothelial cells). Both suPAR
and uPAR regulate cell adhesion and migration
(Salim et al. 2016). Increased levels of plasma or
serum suPAR are considered independent risk
factors of cardiovascular diseases and CKD.
suPAR seems to be a reliable marker of early
L. Pérez-López et al.

CKD since its concentration increases before a
decline in GFR is identified (Salim et al. 2016). A
cohort study showed that, in patients with T1DM,
suPAR predicts cardiovascular events and a
decline in GFR, although it was not correlated
with albuminuria (Curovic et al. 2019). In con-
trast, a cross-sectional study showed a positive
correlation between suPAR concentration and
albuminuria in patients with T1DM (Theilade
et al. 2015). Likewise, in patients with T2DM,
suPAR concentration showed a positive correla-
tion with albuminuria. Indeed, it was associated
with an increased risk of new-onset
microalbuminuria in subjects at risk for T2DM
(Guthoff et al. 2017). In transgenic mice models,
it has also been shown that increased uPAR activ-
ity in podocytes leads to proteinuria (Wei et al.
2008).
5.6 Panels of Candidate Biomarkers,
Proteomic and Metabolomic
Approaches
“Omics”approaches have been used to search for
novel biomarkers and different aspects of the
pathophysiology of kidney damage (Colhoun
and Marcovecchio 2018; Carlsson et al. 2017;
Abbiss et al. 2019; Darshi et al. 2016). Each
individual biomarker of kidney disease represents
a specific pathway. Depending on these
pathways, some renal markers can be correlated
with others. Therefore, the selection of panels of
biomarkers that have low correlation with each
other could potentially be beneficial for the pre-
diction of impaired kidney function (Colhoun and
Marcovecchio 2018). For example, a set of
297 biomarkers was evaluated in a recent pro-
spective study in two different cohorts of patients
with T1DM, and only two biomarkers, CD27, a
member of the tumor necrosis factor receptor
superfamily, and KIM-1 were considered to give
predictive information of DN. This yielded simi-
lar predictive power than using historical
estimated GFR and albuminuria (Colombo et al.
2019a). Similarly, another study examined
42 biomarkers in 840 serum samples of patients
with T2DM and found that prediction of the
decline in renal function could be improved by
the use of two single markers: KIM-1 and
β2 microglobulin (Colombo et al. 2019b). In con-
trast, in one study in patients with T1DM, KIM-1
did not seem to predict progression of CKD inde-
pendently of albuminuria (Panduru et al. 2015)
(Table 3).
6 Conclusions
DN is a common complication in patients with
DM and research in animal models can be useful
to fully understand the mechanisms underlying its
development and progression. However, since
various renal markers are not equally useful in
all species, further studies are required in humans.
The differences and similarities between people
and animals with DN could also bring the oppor-
tunity to investigate new treatments for DN in
humans. Although rodent models are the most
studied, other animals, such as dogs and cats,
could provide important information, since they
share the human environment.
Regarding the potential use of markers of early
kidney damage, cystatin C in humans, and
SDMA in companion animals, have already
been incorporated to the guidelines for the Evalu-
ation and Management of CKD and of the Inter-
national Renal Interest Society, respectively.
Nonetheless, many other markers have been pro-
posed, but results are conflicting for most of them.
In fact, those biomarkers that have been identified
as predictors of CKD or its progression, do not
seem to add to established diagnostic tools. It is
also important to highlight that most studies
performed to date are cross-sectional in their
design. More prospective and intervention studies
are needed to replicate reported findings and to
assess the predictive value of novel biomarkers of
DN. Indeed, large consortia such as the SysKid
(Systems Biology Towards Novel Chronic
Animal Models and Renal Biomarkers of Diabetic Nephropathy

Table 3 Epidemiological studies that provide information for the diagnosis of kidney disease or DN in both humans and animal models (histological, immunochemistry or
intervention studies were not included)
Marker Species
Author
(reference) N Study design Main results Potential clinical application
Plasma SDMA and cystatin C Humans El-khoury
et al. (2016)
40 patients who had clinical
indication for measuring GFR
Cross-
sectional
SDMA and cystatin C are
highly and inversely correlated
with GFR, more than
creatinine
SDMA and cystatin C could
detect an earlier decline in
GFR
Plasma SDMA and ADMA Humans Zobel et al.
(2017)
200 patients with T2DM Longitudinal Higher SDMA was associated
with incident cardiovascular
disease, and deterioration in
renal function
SDMA could be a marker of
DN and cardiovascular
disease in patients with
T2DM
Serum SDMA Dogs Hall et al.
(2016)
19 dogs with CKD and
20 control dogs
Retrospective SDMA detected CKD earlier
than creatinine
SDMA should also be used to
evaluate kidney function in
dogs
Serum SDMA Cats Hall et al.
(2014)
21 cats with CKD and
21 healthy control cats
Retrospective SDMA detects CKD earlier
than creatinine
SDMA should also be used to
evaluate kidney function in
cats
Serum SDMA Cats Langhorn
et al. (2018)
17 with CKD, 40 with HCM,
17 with DM, and 20 healthy
controls
Cross-
sectional
Cats with DM had
significantly lower SDMA
concentrations than controls
SDMA is probabli not a
useful marker of DN in cats;
and further research about DN
is still needed in cats
Serum cystatin C BALB/c
mice
Song et al.
(2009)
23 partial nephrectomy
6 ischaemia reperfusion injury
model
Cross-
sectional
Cystatin C increases before
creatinine in mice with kidney
damage. CysC levels show an
earlier and sharper increase
than creatinine after bilateral
nephrectomy
Cystatin C could be a more
precise marker compared to
creatinine
8 controls
Urinary cystatin C Humans Jeon et al.
(2011)
335 T2DM patients with
normoalbuminuria (n ¼210),
those with microalbuminuria
(n ¼83) and those with
macroalbuminuria (n ¼42)
Retrospective Cystatin C was independently
associated with GFR, and was
increased in people with
diabetes, normoalbuminuria
and decreased GFR
Might predict early stages of
DN in T2DM patients
Serum and urinary Cystatin C Cats Ghys et al.
(2016)
49 cats with CKD and
41 healthy cats
Cross-
sectional
Sensitivity and specificity to
detect CKD were 22 and 100%
for Cystatin C and 83 and 93%
for creatinine
Cystatin C should not be used
to evaluated kidney function
in cats
L. Pérez-López et al.

Serum SDMA and Cystatin C Dogs Pelander
et al. (2019)
30 healthy dogs and 67 dogs
with diagnosis or suspicion of
CKD
Cross-
sectional
Creatinine and SDMA were
similar to detect reduced GFR,
whereas cystatin C was
inferior
SDMA should be measured
together with creatinine as it
might add information of
kidney function in dogs
Urinary Cystatin C- creatinine
ratio and nonalbumin protein –
creatinine ratio
Humans Kim et al.
(2013)
237 T2DM patients Longitudinal After adjusting for several
clinical factors, both urinary
Cystatin C could be a useful
marker of renal function
decline in patients with
T2DM
Cystatin C- creatinine ratio
and non albuminuric protein –
creatinine ratio had significant
associations with the decline
of the estimated glomerular
filtration rate (eGFR)
β2-microglobulin, calbindin,
clusterin, EGF, GST-α,
GST-μ, KIM-1, NGAL,
osteopontin, TIMP-1, and
VEGF
Zucker
diabetic
fatty
rats
Togashi and
Miyamoto
(2013)
5 Male Zucker diabetic fatty
rats (ZDF/CrlCrlj-Leptfa/fa)
and 5 Male nondiabetic lean
rats (ZDF/CrlCrlj-Lept?/+
Cross-
sectional
Urinary levels of cystatin C,
β2-microglobulin, clusterin,
GST-μ, KIM-1 were increased
before the development of
histophatological changes
consistent with DN
Cystatin C, β2-microglobulin,
clusterin, GST-μ, KIM-1
could be used as markers of
DN in mice models of DN
Urinary RBP4 Humans Domingos
et al. (2016)
454 participants with stages
3 and 4 CKD
Cross-
sectional
A logistic regression model
showed an inverse association
between CKD-EPI eGFR and
urinary retinol binding protein
Urinary retinol binding
protein might be a promising
marker of chronic kidney
disease progression
Urinary RBP4 Humans Park et al.
(2014)
471 type 2 diabetes patients,
143 with impaired glucose
tolerance and 75 controls
Cross-
sectional
Urinary RBP4 concentration
was higher in insulin resistant
patients, and it was highly
associated with
microalbuminuria (odds ratio
2.6, 95% CI 1.6–4.2),
Kidney function of diabetic
patients with higher levels of
urinary RBP4 should be
evaluated closely, and it could
be useful in the management
and stratifications of insulin
resistant patients. Further
investigation is needed
Serum RBP4, CysC, b2M Humans Donadio
et al. (2001)
110 patients with various
kidney diseases
Cross-
sectional
Serum concentrations of
CysC, b2M and RBP4
increase with the reduction of
GFR
Cys, b2M and RBP4 do not
seems more reliable markers
to detect a decline in kidney
function compared to
creatinine
ROC analysis showed that
diagnostic accuracy of CysC
and b2M was similar to
(continued)
Animal Models and Renal Biomarkers of Diabetic Nephropathy

Table 3 (continued)
Marker Species
Author
(reference) N Study design Main results Potential clinical application
creatinine and better than
RBP4
Plasma RBP4 Humans Cabré et al.
(2007)
165 T2DM patients Cross-
sectional
Patients with moderate renal
dysfunction (MDRD-GFR
<60 mL min
1
1.73 m
2
had
higher plasma RBP4 than
those with normal renal
function
RBP4 might predict early
decline in GFR in patients
with DN
Albuminuria was not
associated with RBP4
Serum RBP4 Humans Akbay et al.
(2010)
53 T2DM patients and
30 controls
Cross-
sectional
Logistic regression analysis
showed that microalbuminuria
is associated with increased
serum RBP4 concentration
RBP4 might predict early DN
Serum RBP4 Cats van Hoek
et al. (2008)
10 cats with CKD, 10 cats with
hyperthyroidism and
10 healthy cats
Cross-
sectional
Cats with CKD and
hyperthyroidism had higher
concentration of RBP4 than
healthy cats
RBP4 should be investigated
as a marker of impaired
kidney function in cats
Urinary and serum uromodulin Humans Prajczer
et al. (2010)
77 patients with CKD and
14 healthy subjects
Cross-
sectional
Urinary uromodulin was
positively correlated with GFR
and negatively correlated with
serum creatinine. Patients with
lower uromodulin values
showed higher degree of
tubular atrophy (assessed
through biopsy)
Urinary uromodulin might be
a early marker of tubular
damage
Serum uromodulin Humans Wiromrat
et al. (2019)
179 T1DM adolescents
patients and 61 control
subjects
Cross-
sectional
Lower levels of serum
uromodulin are associated
with albumin excretion
Serum uromodulin should be
assessed as a marker of DN
Urinary uromodulin Humans Möllsten
and Torffvit
(2010)
301 patients with T1DM,
164 with normoalbuminuria,
91 with microalbuminuria and
46 with macroalbuminuria
Cross-
sectional
Patients with albuminuria had
lower uromodulin
concentrations
Urinary uromodulin might
reflect tubular damage in
patients with T1DM
L. Pérez-López et al.

Serum uromodulin Humans Fedak and
Kuźniewski
(2016)
170 patients with CKD and
30 healthy subjects
Cross-
sectional
Serum uromodulin was
inversely correlated with other
renal markers and positively
correlated with estimated GFR
Serum uromodulin might be
assessed as an early marker of
CKD
Urinary albumin excretion
ratio (AER), N-acetyl-β-D-
glucosaminidase, and the
advanced glycosylation
end-products (AGEs)
pentosidine and
AGE-fluorescence
Humans Kem et al.
(2010)
55 T1DM patietns with and
110 without macroalbuminuria
91 T1DM patients with and
178 without microalbuminuria
Retrospective
case-control
N-acetyl-β-D-glucosaminidase
independently is associated
with both macroalbuminuria
and microalbuminuria. Other
markers did not independently
predict macro or
microalbuminuria.
Tubular damage occurs in
patients with T1DM and
measurement of urinary
albumin excretion ratio and
urinary N-acetyl-β-D-
glucosaminidase might
predict early impaired kidney
function
Plasma, urinary NGAL, and
urinary NGAL-to-creatinine
ratio (UNCR)
Cats Wang et al.
(2017)
80 cats with CKD and
18 healthy cats
Longitudinal NGAL values were
statistically different between
healthy cats and cats with
stage 3 or 4 CKD, however, no
statistical differents were
found between healthy cats
and cats with those with stage
2 CKD
Plasma NGAL cannot
distinguish CKD in cats
Urinary NGAL does not
detect early stages of CKD in
cats
Plasma NGAL and UNCR Dogs Steinbach
et al. (2014)
17 dogs with CKD 48 dogs
with AKI and 18 controls
subjects
Cross-
sectional
Plasma NGAL concentration
and UNCR was significantly
higher in dogs with AKI or
CKD compared to healthy
dogs. In addition, these
markers were higher in dogs
with AKI compared with dogs
with CKD
Although NGAL is an
established marker for AKI, it
might also be useful to
distinguish dogs with CKD
from healthy dogs, although
further research is needed
Urinary NAGL, NAG and
KIM-1
Human Fu et al.
(2012b)
101 T2DM patients Cross-
sectional
All marker showed higher
levels in patients with
DM. NGAL and NAG were
positively correlated with
albuminuria. NGAL showed
significant differences between
micro and macroalbuminuric
patients
NAGL and KIM-1 could be
early markers of DN. Those
patients with glomerular
hyperfiltration and higher
levels of urinary NAGL or
KIM-1, should be closely
monitored
28 control subjects
KIM-1 was not associated
with albuminuria
(continued)
Animal Models and Renal Biomarkers of Diabetic Nephropathy

Table 3 (continued)
Marker Species
Author
(reference) N Study design Main results Potential clinical application
Urinary KIM-1 and NGAL Humans de Carvalho
et al. (2016)
117 T2DM patients Cross-
sectional
Both markers were observed in
patients with T2DM with
normal or mild albuminuria,
and they were independently
associated with albuminuria
Tubular markers could help in
the early detection of DN
Urinary KIM-1, NGAL and
vanin-1
Rats Hosohata
et al. (2014)
8 male spontaneous type
2 diabetic OLETF rats and
8 male non-diabetic Long-
Evans
Cross-
sectional
Urinary KIM-1 was more
sensitive than albumin to
detect DN
KIM-1 detect early tubular
damage
Tokushima Otsuka (LETO)
rats
Urinary KIM-1 Humans Panduru
et al. (2015)
1573 T1DM patients Longitudinal
multicenter
study
Mendelian randomization
(MR) approach suggested a
causal link between increased
urinary KIM-1 and decreased
GFR. KIM-1 did not predict
progression of albuminuria
Further studies to evaluate
KIM-1 as an early marker of
DN could be interesting
Urinary active TGFβ1:
creatinine ratio
Cats Lawson
et al. (2016)
6 non-azotaemic cats that
developed azotaemia within
24 months; 6 cats and with
renal azotaemia at baseline;
and 6 non-azotemic cats
Longitudinal Increased active TGFβ1:
creatinine ratio was observed
6 month before the
development of azotemia
Urinary active TGFβ1:
creatinine ratio might be an
early marker of CKD in cats,
this marker should be
assessed in a larger sample.
Serum and urinary TGFβ1 Humans Qiao et al.
(2017)
63 case-control studies
(364 T2DM patients, 1604
T2DM and DN patients, and
2100 healthy controls)
Systematic
review
TGFβ1 levels were higher in
T2DM patients and were
positively correlated with
albuminuria
TGFβ1 could be a promising
marker of DN, although
future research is needed
Plasma uromodulin and
cystatin C
Humans Steubl et al.
(2016)
426 individuals of whom
71 healthy subjects and
355 had CKD (stages I-V)
Cross-
sectional
Multiple linear regression
modeling showed significant
association between
uromodulin and eGFR
(coefficient estimate b.0.696,
95% confidence interval
[CI] 0.603–0.719, P < 0.001)
Uromodulin could be an
earlier marker of CKD
compared to creatinine and
CysC
Uromodulin was able to
differentiate between patients
in stage 0 and I
L. Pérez-López et al.

Neither cystatin C nor
creatinine distinguished
between stages 0 and I
Urinary Ig G, KIM-1, NAGL,
NAG
Humans Nauta et al.
(2011)
94 T1DM and T2DM, and
45 control subjects
Cross-
sectional
Glomerular and tubular
markers were associated with
albuminuria independently of
GFR (except KIM-1)
Markers of glomerular and
tubular damage should be
evaluated in patients with DN
Urinary RBP4,b2-
microglobulin, NAGL, NAG,
and IgG creatinine ratios
Dogs Nabity et al.
(2015)
20–25 dogs with X-linked
hereditary nephropathy and
10–19 dogs control subjects
Retrospective Urinary RBP4 was the most
strongly correlated with serum
creatinine and GFR. Although
logistic regression analysis
showed serum creatinine,
uIgG/c, and uB2M, but not
uRBP4/c, as significant
independent predictors of GFR
b2-microglobulin, NAGL/c,
NAG/c, IgG/ could allow
early detection of CKD, and
RBP4/c is a marker of CKD
progression in dogs
Urinary albumin vitamin
D-binding protein, RBP4,
uromodulin,
Dogs Chakar et al.
(2017)
40 dogs with CKD and
9 control subjects
Cross-
sectional
Increased vitamin D-binding
protein and RBP4 were
detected in early stages of
CKD with or without
albuminuria
Vitamin D binding protein
and RBP4 should be studied
as an early marker of CKD,
whereas uromodulin could be
a marker of progression of
CKD in dogs
Dogs with CKD had
undetectable or lower RBP4
than controls, although
among dogs in early stages of
CKD there were no
differences
Plasma and urinary VEGF Humans Kim et al.
(2004)
147 patients with T2DM and
47 healthy controls
Cross-
sectional
VEGF concentration was
higher in T2DM patients and
was associated with
albuminuria
VEGF might be a useful
marker of DN in patients with
T2DM
Plasma VEGF Humans Hovind
et al. (2000)
199 patients with T1DM and
DN, and 188 patients with
T1DM and normoalbuminuria
Cross-
sectional
Men with DN had higher
concentration of VEGF than
normoalbuminuric patients
Sex differences might affect
VEGF concentration
Urinary cytokine (IL-8,
MCP-1. TGF- β1, VEGF):
urine creatinine ratios
Cats Habenicht
et al. (2013)
26 cats with CKD and
18 healthy cats
Cross-
sectional
Cats with CKD had a
significantly lower urinary
levels of VEGF and higher
urinary levels of IL-8 and
Further research is needed to
evaluate the utility of measure
urinary cytokines in cats with
CKD, but it markers might
(continued)
Animal Models and Renal Biomarkers of Diabetic Nephropathy

Table 3 (continued)
Marker Species
Author
(reference) N Study design Main results Potential clinical application
TGF-β1 compared to healthy
cats
reflect kidney inflammaniton
and fibrosis
Plasma suPar Humans Salim et al.
(2016)
2292 patients from Emory
cardiovascular biobank whose
renal function was sequentially
evaluated
Longitudinal suPAR concentration
increased before a decline in
estimated GFR was observed
Kidney function of patients
with elevated suPAR should
be monitored closely
Plasma suPar Humans Curovic
et al. (2019)
667 patients with T1DM and
different levels of albuminuria
Longitudinal suPAR predicted
cardiovascular events and a
decline in GFR but was not
associated with albuminuria
suPAR is useful to detect
early DN
Plasma suPAR Humans Theilade
et al. (2015)
667 patients with T1DM and
51 control subjects
Cross-
sectional
suPAR levels were higher in
patients with cardiovascular
disease and in patients with
albuminuria. Multivariate
logistic regression analysis
showed an association
between suPAR and
albuminuria in patients with
DM
suPAR and its relations with
albuminuria should be
investigated
Plasma suPAR Humans Guthoff
et al. (2017)
258 patients at risk of T2DM Longitudinal Higher suPAR levels are
associated with an increased
risk of new-onset
microalbuminuria in subjects
at risk for type 2 diabetes
suPAR might be a useful
marker of early DN in T2DM
patients
Panel of 42 serum biomarkers Humans Colombo
et al.
(2019b)
840 patients with T2DM Longitudinal
multicenter
study
Kim-1 and β2-microglobulin
improve prediction of renal
function decline
Until further validation Kim-1
and β2-microglobulin could
be useful in clinical trials to
select those patients with
higher risk of DN
Panel of 297 serum biomarkers Humans Colombo
et al.
(2019a)
1174 patients with T1DM Longitudinal
multicenter
study
Predictive information can be
obtained using just two
biomarkers (CD27 and
KIM-1)
Few biomarkers are necessary
to gain prediction of DN
diagnosis.
Panel of 207 serum biomarkers Humans Looker et al.
(2015)
154 cases (40% reduction in
GFR) and 153 controls
Longitudinal
multicenter
study
14 biomarkers were associated
with CKD progression
(SDMA, SDMA/ADMA ratio,
These panel detected some
novel biomarkers that require
further investigation
L. Pérez-López et al.

Kim-1, creatinine, β2-
Microglobulin, α1 Antitrypsin,
Uracil, N-terminal
prohormone of brain
natriuretic peptide,
C16-acylcarnitine,
Hydroxyproline, Fibroblast
growth factor-21, Fatty acid-
binding protein heart,
Creatine, Adrenomedullin)
Panel of 402 plasma
biomarkers
Humans Kammer
et al. (2019)
481 T2DM patients with
incident or early CKD
(comparing patients with
stable GFR and patients with a
rapid decline of GFR)
Longitudinal
multicenter
study
KIM-1 was the most important
predictor of GFR decline
KIM-1 might be a useful
marker of DN in patients with
T2DM
Abbreviations: eGFR estimated glomerular filtration rate, DN diabetic nephropathy, T1DM patients with type 1 diabetes, T2DM patients with type 2 diabetes, SDMA symmetric
dimethylarginine, NGAl neutrophil gelatinase-associated lipocalin, AER Albumin excretion ratio, AGEs advanced glycosylation end-products, AKI acute kidney injury, CKD
chronic kidney disease, DN diabetic nephropathy, UNCR urinary NGAL-to-creatinine ratio, KIM-1, kidney injury molecule 1, IgG immunoglobulin G, MCP-1 urinary
monocyte chemoattractant protein-1, NAG N-acetyl-β-D-glucosaminidase, GST-αalpha glutation S transferasa, GST-μmu glutation S transferasa, IL-8 interleukin 8, TIMP-1
tissue inhibitor of metalloprotease-1, VEGF vascular endothelial growth factor, RBP4 retinol binding protein 4, suPAR soluble urokinase type plasminogen activator receptor,
TGFβ1transforming growth factor β-1
Animal Models and Renal Biomarkers of Diabetic Nephropathy

Kidney Disease Diagnosis and Treatment), SUM-
MIT (Surrogate markers for micro and
macrovascular hard endpoints for innovative dia-
betes tools) and BEAt-DKD (Biomarker Enter-
prise to Attack Diabetic Kidney Disease) are
providing and will provide important results in
the near future.
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