Introduction diagnostic tool to check on the

Introduction

Biological
molecules found in body fluids or tissues that are an indication of usual or
unusual process, or of a condition or disease is known as a biomarker (Rehman, et al., 2017). Medical
practitioners commonly collect blood and urine sample as a diagnostic tool to
check on the biomarkers for identification and prognosis of a disease. Blood is
the gold standard test to diagnose disease but the collection of blood sample
is invasive and painful leading to anxiety and discomfort in patients. (Malathi, et al., 2016). Besides post
collection blood sample needs timely processing as blood clots easily while
collection of urine can be messy and patient have a tough time collecting
midstream urine and also it lacks presence of biomarkers on the other hand, one
of the body fluid that is extensively developed in the last decade for
diagnosis of diseases is saliva as it contains thousands of biomolecules.

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Saliva
characteristics

Saliva
is clear, has a pH of 6 to 7, and are composed of 99% of water, 0.3% proteins
and 0.2% inorganic substances (Yoshizawa, et al.,
2013).
Saliva is multifunctional, it helps in the breakdown of starch with amylase
enzyme present; creates food bolus to ease swallowing; has antimicrobial
effect; act as a buffer to prevent sudden changes in pH. Saliva can be
collected in two ways; stimulated and unstimulated saliva collection. Usually,
saliva sample that is going to be processed within 3 to 6 hours are
refrigerated at 4°C but if sample is needed to be kept longer, it is kept at a
lower temperature depending on the biomarker of interest (Nunes, et al., 2015). Self-collection
saliva sample using commercial kits are stored and ship using dry ice.

 

Advantages
and disadvantage

Saliva
contains thousands of biomolecules that are derived from the local capillary
bed and is non-invasive, easier and safer as compared to blood and urine.
Drawing blood or using other diagnostic tools is hard to be collected from a
certain population of people like children, disabled and elderly patients,
saliva is so much easier and safer (from infection and blood clot) to be taken
from this population (Madalli, et al., 2013). Saliva is a cheap, easy
storage, and non-invasive diagnostic
tool (Malathi,
et al., 2014).
Saliva can be collected by anyone while phlebotomy requires a trained
practitioner, saliva also can’t transmit any infectious disease such as human
immunodeficiency virus (HIV), unlike blood (Yoshizawa, et al., 2013). Besides that, in
certain diseases, saliva is better biomarkers than blood but also certain
markers gained in saliva is not always reliable compared to blood (Madalli, et al., 2013). Salivary biomarkers
are currently being successfully used to diagnose patients with HIV, viral
hepatitis, cytomegalovirus, human papillomavirus (HPV), malaria and dengue
fever (Yoshizawa,
et al., 2013).
In addition, dental studies, renal disease and drug abuse are monitored
successfully using salivary based test (Nunes, et al., 2015). There are salivary
biomarker kits available on the market that allow self-examination or
self-collection of saliva and send it to the lab to do required testing. Table
1 shows types of commercially available kits that uses salivary biomarkers to
identify a disease or condition.

Table 1 shows various product kits and their uses for measuring salivary
biomarkers (Goswami, et al., 2015).

Saliva
is a diagnostic tool that can be used in many fields such as medical, forensic,
genetic testing and so on. Papers from (Nunes, et al., 2015), (Madalli, et al., 2013), (Javaid, et al., 2016), and many more
papers have reported biomarkers of systemic disease in saliva that are
successfully being used to diagnose a disease or still undergoing research. The
purpose of this article is to be familiar with the potential salivary
components, yet to be recognized as biomarkers of cardiovascular disease,
diabetes and pancreatic cancer. This biomarker can also be used for prognosis,
diagnosis or monitoring a disease.

This
review will focus on advancement in salivary biomarkers for systemic and oral
disease. The research papers were selected based on the year of published, not
more than 10 years. Science Direct, Research Gate, Nature and PubMed are
databases that were used to achieve articles. Papers were selected by using key
terms: ‘Saliva biomarkers’, ‘Saliva as a diagnostic tool’, ‘latest saliva
biomarkers’ and ‘saliva biomarker with (individual disease mention below)’.

 

 

Body

Composition
of saliva and collection method

Saliva
originates from major salivary gland (sublingual, submandibular, sublingual)
and minor salivary glands (labial, palatoglossal, buccal, lingual, palatal) (Nunes, et al., 2015). It’s a constituent
oral fluid along with erythrocytes, leukocytes, mucosal transudations, gingival
crevicular fluid (GCF), serum and blood derivatives from oral wounds,
epithelial cells, expectorated bronchial and nasal secretions, bacteria and
bacterial products, viruses and fungi, other cellular components, and food
debris (Malathi, et al., 2014). Just like plasma,
saliva has antibodies, microbes and their products, enzymes, electrolytes,
hormones, minerals, growth factors and 600 ml of saliva is produced daily (Madalli, et al., 2013). Constituents from
blood enter saliva through active transport, passive diffusion or extracellular
ultrafiltration (Javaid, et al., 2016). Saliva production
and constituent can easily change due to several pathological conditions (e.g.,
multiple sclerosis, bleeding oral cavity, periodontitis, epilepsy) and
physiological (e.g., physical exercise, mastication, psychological stress) (Nunes, et al., 2015).

Unstimulated
saliva is collection of saliva naturally without using any exogenous source to
increase production and dehydration is the major factor affecting its flow
rate. (Malathi,
et al., 2016).
Stimulated saliva collection is done on patients who have difficulty in
stimulating enough saliva by using methods to gain higher salivary flow rate
such as citric acid, gustatory stimulation or mastication (Nunes, et al., 2015). The most
recommended method is unstimulated collection as it doesn’t affect the pH and
quantity of saliva, unlike stimulated collection.

 

Cardiovascular
diseases

Acute
myocardial infarction (AMI) is a life-threatening complication of coronary
heart disease (CHD). Electrocardiogram (ECG) is usually done for suspected AMI
patient to check for ST- elevation, but in no-ST-elevation myocardial
infarction (NSTEMI) serum biomarkers are measured to rule out AMI (myocardial
necrosis) (Miller, et
al., 2014).
Cardiac troponins (T and I; TnT, TnI), serum creatine kinase-MB (CK-MB), total
CK, and myoglobin (MYO) concentrations are biomarkers that are usually used to
diagnose AMI (Miller, et al., 2014). Serum biomarkers of
CHD are detectable in saliva and recent reports indicate that concentrations of
selected salivary markers are elevated early post-AMI and after myocardial
damage (Rehman, et
al., 2017).
Researched done by Miller C.S etc. shows C-reactive protein (CRP) was most
associated with AMI, also with Adip and cellular adhesion molecule-1 (sICAM-1) (Miller, et al., 2014). Studies have also
shown that plasma CRP correlates with salivary CRP. The major cause of AMI are
atherosclerosis, it is triggered by inflammation therefore inflammatory
cytokines such as CRP, TNF-alpha, IL-6, matrix metallo-perteinase-9 (MMP-9),
and myeloperoxidase (Miller, et al., 2010). However,
inflammatory cytokines are less specific to be an exclusive indicator for AMI
as it will be increased in any inflammatory disease in the body and increases
significantly in oral diseases. Therefore, inflammatory cytokines will not be
used in the review.

Certain studies showed that biomarker B-type natriuretic
peptide (BNP), a hormone released from the ventricles during myocardial stress
are found in saliva of AMI patient (III, et al., 2012) (Gerszten, et al.,
2011).
Salivary BNP can be used as a reliable biomarker as it is highly specific as
BNP is released directly from the heart. In a study done by Joharimoghadam et.
al., 35 admitted patients with decompensated heart failure (HF) diagnosis, 35
HF patient who comes for follow-ups, and 25 people without any history of
cardiac event as the control was use as subjects for the study to measure
saliva BNP. Figure 1 shows the results that are obtained.

Figure 1 shows the results obtain in Joharimoghadam et. al. study, the
concentration of salivary BNP was 9.372 pg/ml for
admitted HF patient, 6.62 pg/mL for HF outpatient and 4.69 pg/mL for control.

There
is a significant increase amount of salivary BNP in the admitted HF patient
compare to HF oupatient and control. Similar studies were done by Yang Foo, et.
al., showing that there is a significant increase of salivary BNP in HF patient
and showed 90.6% of overall diagnostic accuracy, therefore this study reaffirms
my statement. Salivary BNP can be used as a prognosis, diagnosis and monitoring
biomarker for AMI (Foo, et al., 2012).

Cardiac
troponin T (cTnT) and I (cTnI) are cardiac regulatory proteins and are released
only when there is a damage to the myocardium. This proteins are very sensitive
and specific biomarker measured in serum to identify AMI or unstable angina (Sharma, et al., 2004). Dizqah. M and E.
Riahi carried out a study on 30 acute AMI patient and 28 healty individual
(control) to measure cTnI level in the serum and saliva at 12 and 24 hours of
acute AMI. The salivary cTnI were significantly increase in AMI patient and it
correlates significantly with the serum cTnI concentration (Mirzaii-Dizgah & Riahi, 2013). Dizqah. M carried
out the similar research but on salivary cTnT and gain the same results as cTnI
experiment (Mirzaii-Dizgah & E., 2012). This salivary cTnI
is highly specific as it present in heart only, while cTnT present in the heart
and skeletal muscle, hence, cTnI can be a biomarker for early diagnosis of AMI.

Adhesion
molecules are expressed on the endothelium, and plaque destabilization/rupture
is associated with release of soluble CD40 ligand and specific adhesion
molecules (Rehman, et
al., 2017).
Studies showed salivary soluble ICAM-1 is significantly elevated in AMI while
salivary soluble CD40 ligand is significantly lower in AMI patients (Miller, et al., 2010).

In
a study done by Zheng et. al. to identify if there is any protein expressed
differently in obstructive sleep apnea (OSA) patients with CVD. Zheng et al.
reported that there is a decrease in salivary ?-2-HS-glycoprotein in CVD
patients with OSA compared to non-CVD OSA patient and believe can help in early
detection of CVD. Further research should be done on non-CVD OSA patient and
non-OSA healthy individual to check if the salivary ?-2-HS-glycoprotein is the
same in both groups, indirectly proving that salivary ?-2-HS-glycoprotein only
decreases because of CVD and not OSA (Zheng, et al., 2014). 

Salivary
BNP and cTnI is a reliable potential biomarker for CVD as it increases
significantly and is specific to the heart while other biomarker can be
significantly increase or decrease but they can be increased in other systemic
diseases too, therefore can’t be a reliable biomarker.

Diabetes Mellitus

Diabetes Mellitus (DM) is an endocrine disease
that is unable to absorb glucose either because of beta-cell destruction
leading to insulin deficiency (type 1) or tissues are resistant to insulin
(type 2) ((Vaziri,
et al., 2009)
(Lima?Aragão, et al.,
2016)
(Shahbaz, et al., 2015). Diabetes patient
have high free glucose in their body as the body can’t uptake it, therefore
studies show that there is a significant increase in the glucose level content
in saliva (Ladgotra,
et al., 2016)
(Lima?Aragão, et al.,
2016)
(Panchbhai, et al.,
2010).  Table 1 shows the studies that have been done
to identify salivary biomarkers for DM patients.

Table 2 shows researches that have been done on DM patient and the changes
in saliva composition in DM patient when is compared to control.

 

Sample Size

Results of DM patients compare to control

Method

Author

1

20 patients self-reported T2DM and HbA1c value,
20 healthy individual

-Salivary 1,5 anhydroglycitol or IL-6 have a
positive correlation with HbA1c

ELISA

(Srinivasan, et al.,
2015)

2

60 DM patients, 60 heallthy adults

– Salivary glucose is significantly higher
– Salivary amylase increase

 

(Ladgotra, et al.,
2016)

3

88 diabetic patients, 39 non-diabetic adults

-Increased in glucose, calcium, urea, anti-S
mutant IgA, total IgA anti-insulin IgA
-Decrease in salivary amylase, total protein
concentration

Colorimetric method

(Lima?Aragão, et al.,
2016)

4

40 uncontrolled DM patients, 40 controlled DM
patient, 40 healty adults

-Salivary glucose increase significantly in
controlled and uncontrolled patient
-Significant decrease in mean amylase
concentration in controlled DM patient

Glucose estimation kit, Alpha-amylase kit

(Panchbhai, et al.,
2010)

5

40 type 1 DM patients, 40 type DM patient, 40
healthy adults

-No salivary albumin difference in type 1 and
control but in type 2 compare to control salivary amylase significantly
increase
-Higher DMFT mean values in DM patient

Nephelometric method

(Vaziri, et al.,
2009)

6

13 T2DM patients, 13 healthy controls

– EGFR and PSMB2 down-regulated genes
-SLC13A2, KRAS, TMEM72, and SAT1 up-regulated
genes
-KRAS,EGFR,SAT1, PSMB2 significantly
distinguishes T2DM from control

reverse transcription quantitative real time
polymerase chain reaction

(Lee, et al., 2012)

7

30 type 1 DM patients, 30 healthy controls

-elevated salivary albumin in the type 1 DM
compared to control

Bromocresol green (BCG) dye method

(Shahbaz, et al.,
2015)

 

Most studies showed there is a decrease in
salivary amylase level and total salivary protein but in contrast, Ladgotra et
al. research shows that there is an increase of amylase concentration in saliva
in DM patient and Panchbhai, et al reported there is no significant difference
in the total salivary protein compared to control. (Ladgotra, et al.,
2016)
(Lima?Aragão, et al.,
2016)
(Panchbhai, et al.,
2010).
Periodontitis is commonly associated with diabetes and this is probably because
of the high glucose environment in the mouth that favours the bacterial growth,
therefore biomarkers used to diagnose periodontitis can be expressed in
diabetic patient too and studies have reported DM patient have poor oral
health. Salivary protein could be affected by the degree of periodontitis,
therefore, further research should be done to measure the salivary total
protein and amylase with a group of DM without PD and groups of DM patient with
different degree of PD in order to identify if PD affects the salivary
composition of DM patients.

Anti-insulin IgA can be a potential biomarker
for T1DM as Lima?Aragão have reported that there is high concentration of
anti-insulin IgA antibodies present in saliva and this antibody can help in
predicting T1DM risk earlier (Lima?Aragão, et al.,
2016).

HbA1c is glycosylated haemoglobin that is used
to diagnose diabetes and Srinivasan et.al found that there is a correlation
between HbA1c and salivary 1,5 anhydroglycitol or IL-6 (Srinivasan, et al.,
2015).
Therefore, salivary 1,5 anhydroglycitol should be used as a biomarker to
diagnose DM as IL-6 is a cytokine that increases for any inflammation in the
body.

Lee et al. research on transcriptome biomarker
and found that there was two (EGFR and PSMB2) down-regulated genes and four
(SLC13A2, KRAS, TMEM72, and SAT1) up-regulated genes expressed differently in
diabetic patient compare with control (Lee, et al., 2012). More research
should be done on these transcriptome biomarker to identify which are more
sensitive and specific to diagnose DM as it may be a potential biomarker.

Most of the salivary biomarker isn’t well
studied enough and can manipulate easily or not specific enough. The best
biomarker for DM would be salivary glucose as all the studies showed a
significant increase in salivary glucose in DM patients. Transcriptome
biomarkers can be reliable biomarker for DM patients too as it cannot be
manipulated and are specific.

 

 

Pancreatic Cancer

Symptoms shown in pancreatic cancer (PC)
patient is usually seen at the later stage. Therefore, a non-invasive test to
identify an early staging biomarker would be helpful in detection and higher
chances of survival. Table 3 shows a few salivary transcriptome studies were
done on pancreatic patient.

 

 

Sample
size

Results

Method

Author

1

30
PC, 30 pancreatitis patient and 30 healthy control


KRAS, MBD3L2, ACRV1, DPM1 mRnas can differentiate PC patients from non-cancer
subject.

This mRnas have 90% sensitivity and 95% specificity.

Affymmetrix
HG U133 Plus 2.0 array

(Zhang, et al., 2010)

2

30
newly diagnosed PC patient, 32 healthy control


miR-17, miR-21, miR-181a, miR-181b and miR-196a were significantly higher in
pancreatic patient

real-time
quantitative  polymerase chain reaction (qPCR)

 

3

7
PC, 4 pancreatitis, 2 IPMN patients, 4 healthy controls 

-hsa-miR-21,
hsa-miR-23a, hsa-miR-23b and miR-29c
-hsa-miR-216
was up-regulated help distinguish pancreatitis from PDAC

qPCR

(M,
et al., 2015)*

 

 

Two research in table 3 detected salivary
miR-21 and studies showed that miR-21 is the most sensitive and significant PC
biomarker (Vorvis, et
al., 2016).
Therefore, further studies should be done on miR-21 to check if it can be a
potential biomarker specific to PC.

Tumour-derived exosomes are microvesicle that
can be found in saliva and plays a role in producing salivary transcriptomic
biomarker specific for PC (Lau, et al., 2013). Studies showed that
there is an upregulation of Apbblip, a saliva transcriptomic biomarker in PC
patient (Lau, et
al., 2013).
Future research should be done on salivary tumour-derived exosomes as it can
contribute to a specific biomarker that will help to diagnose PC.

Research has showed that carbohydrate antigen
19-9 (CA19-9) is sensitive and specific serum biomarker (Loosen, et al., 2017) for PC. Rai et al.
reported that CA19-9 is present in saliva, hence further studies should be done
to check for CA19-9 sensitivity and significance in saliva for PC and if CA19-9
can be a potential salivary biomarker.  (Rai, et al., 2013)

Many studies have showed that there is KRAS
mRNA present in the saliva of PC patients. Therefore, KRAS mRNA can be a
reliable biomarker for PC and the rest of biomarker can be secondary biomarker.
Further research still should be done on KRAS mRNA to check if KRAS is present
in the saliva for other systemic disease or cancer for specificity.

http://ascopubs.org/doi/abs/10.1200/jco.2009.27.15_suppl.4630

(Wong, et al., 2009)

https://www.researchgate.net/publication/246728336_964_Multiple_Salivary_Biomarkers_for_Pancreatic_Cancer_Detection

 

 

 

 

 

Limitation

We know that blood is the gold standard test
for diseases but will saliva be a diagnostic tool as good as blood? Besides
that, even though there is potential salivary biomarker for the earlier stage
but without symptom, most patient would not be aware and check at the earlier
development of disease leading to severe condition, for instance, pancreatic
cancer. On top of all this, medical insurance company should believe that
salivary biomarkers are highly specific and cost-effective so that patient can
get coverage for salivary test.

 

 

 

 

 

 

 

 

 

 

 

 

Conclusion

Saliva collection is non-invasive, cheap and
easy. It contains many hormones, antibodies, growth factors, and enzymes that
are derived from blood. Therefore, biomarkers found in blood that act as an
indicator of certain disease can be found in saliva too. Hence, it supports the
phrase that ‘saliva is a mirror image of systemic health’. A salivary biomarker
can also help in monitoring a disease or for prognosis.

Saliva biomarker is already being used in
infectious disease like HIV, HCV and also for DNA testing (Yoshizawa, et al.,
2013).
There are commercial kits being sold to identify various biomarker in saliva (Anon., n.d.).

Implementing saliva test as a part of routine
medical check-up it will be beneficial to diagnose disease at earlier stage.
Diagnostic of disease for routine check-up should be wide-spread and as
dipstick can be used. Certain disease has common biomarker, hence, to
distinguish one disease from the other, a combination of biomarker should be
identified in future research to increase diagnosis specificity of a disease.
The drawback of all the studies is that the sample size is small, therefore,
further research should be done on this and identify appropriate cut-off point
of the biomarkers. Salivary biomarker can be a reliable biomarkers and can help
in early diagnosis of disease. Saliva test can substitute blood test.