to my husband and family for their never-ending love
TRANSCRIPT
1
MICRORNAS AS BIOMARKERS IN GINGIVAL CREVICULAR FLUID
By
KELSEY CRONAUER WAHL
A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE
UNIVERSITY OF FLORIDA
2020
2
© 2020 Kelsey Cronauer Wahl
3
To my husband and family for their never-ending love, encouragement, and support
4
ACKNOWLEDGMENTS
I would like to thank my mentor, Dr. L. Shannon Holliday, for his guidance and
support with this project. I would like to thank Dr. Calogero Dolce and Dr. Robert Caudle
for their assistance. I would like to thank all faculty, staff, and residents in the University
of Florida Orthodontic Department for their support during residency. I would also like to
thank my wonderful husband and my family for their love, support, and encouragement
to pursue my passion.
5
TABLE OF CONTENTS page
ACKNOWLEDGMENTS .................................................................................................. 4
LIST OF TABLES ............................................................................................................ 6
LIST OF FIGURES .......................................................................................................... 7
LIST OF ABBREVIATIONS ............................................................................................. 8
ABSTRACT ................................................................................................................... 10
CHAPTER
1 INTRODUCTION .................................................................................................... 12
2 MATERIALS AND METHODS ................................................................................ 22
Participants and Eligibility ....................................................................................... 22
Study Design .......................................................................................................... 22 Sample Collection ................................................................................................... 23
PerioPaper ....................................................................................................... 23
Durapore Filter Membrane ............................................................................... 24 Microcapillary Tube .......................................................................................... 24
RNA Isolation .......................................................................................................... 25 cDNA Synthesis ...................................................................................................... 26
Real-Time PCR ....................................................................................................... 26 Statistical Considerations ........................................................................................ 27
3 RESULTS ............................................................................................................... 31
4 DISCUSSION ......................................................................................................... 42
5 CONCLUSIONS ..................................................................................................... 47
LIST OF REFERENCES ............................................................................................... 48
BIOGRAPHICAL SKETCH ............................................................................................ 54
6
LIST OF TABLES
Table page 2-1 Sample Collection Pattern for Subjects .............................................................. 27
2-2 Sample Identifiers ............................................................................................... 28
3-1 Ct Values for PerioPaper Samples ..................................................................... 39
3-2 Ct Values for Durapore Samples ........................................................................ 39
3-3 Ct Values for Microcapillary Tube Samples ........................................................ 39
3-4 ANOVA Descriptive Statistics for Full Data Set (Ten Samples) .......................... 40
3-5 ANOVA Descriptive Statistics for Subset of Data (Six Samples) ........................ 40
3-6 t-test for Treated and Untreated Subjects ........................................................... 41
7
LIST OF FIGURES
Figure page 2-1 Microfuge® 18 Centrifuge ................................................................................... 28
2-2 2720 Thermal Cycler .......................................................................................... 29
2-3 96-well Plate ....................................................................................................... 29
2-4 C1000 Thermal Cycler ........................................................................................ 30
3-1 Amplification Plot of A1 and B1 Samples ........................................................... 35
3-2 Amplification Plot of C1 and D1 Samples ........................................................... 35
3-3 Amplification Plot of E1 and F1 Samples ............................................................ 36
3-4 Amplification Plot of A2, F2, M1 and M2 Samples .............................................. 36
3-5 Bar Graph Showing Full Dataset (Green) and Subset (Blue) of Mean Ct Values for miRNA-146a ...................................................................................... 37
3-6 Bar Graph Showing Full Dataset (Green) and Subset (Blue) of Mean Ct Values for miRNA-103-3p ................................................................................... 37
3-7 Bar Graph Showing Mean Ct Values for miRNA-146a (Blue) and miRNA 103-3p (Green) and ΔCt (Gold) in Treated and Untreated Subjects .......................... 38
8
LIST OF ABBREVIATIONS
ALP Alkaline phosphatase
ANOVA Analysis of variance
cDNA Complementary deoxyribonucleic acid
Ct Cycle threshold
DNA Deoxyribonucleic acid
EV Extracellular vesicle
GCF Gingival crevicular fluid
HGF Human gingival fibroblast
IL-1β Interleukin one beta
IL-6 Interleukin six
IL-8 Interleukin eight
IRAK1 Interleukin one receptor associated kinase one
miRNA Micro-ribonucleic acid
mRNA Messenger ribonucleic acid
NF-κB Nuclear factor kappa B
PB Processing body
PCR Polymerase chain reaction
pre-mRNA Precursor messenger ribonucleic acid
pri-miRNA Primary micro-ribonucleic acid
qPCR Quantitative polymerase chain reaction
RANK Receptor activator nuclear kappa B
RANKL Receptor activator nuclear kappa B ligand
RT-PCR Real-time polymerase chain reaction
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RISC Ribonucleic acid induced silencing complex
RNA Ribonucleic acid
SLE Systemic lupus erythematosus
TNF-α Tumor necrosis factor alpha
TRAF6 Tumor necrosis factor receptor associated factor six
UTR Untranslated region
ΔCt Delta cycle threshold
ΔΔCt Delta delta cycle threshold
10
Abstract of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science
MICRORNAS AS BIOMARKERS IN GINGIVAL CREVICULAR FLUID
By
Kelsey Cronauer Wahl
May 2020
Chair: Lexie Shannon Holliday Major: Dental Sciences – Orthodontics
In medicine and dentistry there is a significant focus on improving patient
diagnosis and outcomes. With the identification of exosomes as methods of intercellular
communication and genetic exchange, another avenue for biomarker discovery
presented itself. Released from osteoclasts and inflammatory cells, extracellular
vesicles carry genetic information, such as microRNAs (miRNAs), which can alter gene
transcription in target cells and affect the inflammatory and bone remodeling processes.
Gingival crevicular fluid (GCF) is a commonly used fluid for detection of biomarkers,
including miRNAs. The objective of this study was to determine if miRNA-146a could be
sufficiently collected by GCF methods and which method was best for collecting this
miRNA. This study compared three different methods which are the following:
Periopaper strips, Durapore filter membrane, and micropipettes. Twelve adult
volunteers were sampled and sampling took place over two visits. For each subject
three teeth were sampled, each tooth with one of the proposed methods. A pattern was
established so that collection method varied per tooth but repeated every fourth subject,
for comparison. Collections were taken on the mesial and distal surfaces of each
specified tooth. RNA isolation, cDNA synthesis, and real-time polymerase chain
11
reaction (RT-PCR) were performed on each sample to assess expression of miRNA-
146a. A reference gene, miRNA-103-3p, was also used for assessment and
normalization of data. Samples from seven subjects were analyzed and the results
showed that there was no significant difference in method of collection for identifying
and expressing miRNA-146a. However, a secondary analysis of samples showed that
there was a significant difference in expression of miRNA-146a between subjects who
were undergoing orthodontic treatment and those who were untreated. This study
concluded that there is no advantage to using one of the three collection methods over
another for expression of miRNA-146a.
12
CHAPTER 1 INTRODUCTION
For many years, miRNAs have been studied to determine their roles in health
and disease.1 Comprising 1-2% of all genes in mammals, nearly all biological processes
are affected by miRNA control.2 Structurally, miRNA is a single-stranded RNA, 21-25
nucleotides in length.2 miRNAs are present in multiple organisms, including plants,
worms, and humans, and many are conserved across species.3 Remarkably,
components of miRNA machinery have been found in archaea and eubacteria, showing
their lasting presence from ancient times to today.4 Originally found to regulate
developmental timing in worms, the function of miRNA was determined to be even
greater, with the discovery of its involvement in networking and coordination of gene
expression.5 miRNAs have been shown to participate in cell cycle control, cardiac and
skeletal muscle development, and neurogenesis.6 Additionally, they have been
implicated in a number of diseases including cancers, heart disease, and neurological
diseases.7,8 Consequently, miRNAs are studied as markers of disease progression and
for diagnostic purposes.8
Production of miRNA takes places in the nucleus and cytoplasm of a cell.9 In the
nucleus, different areas of a gene are transcribed by RNA Polymerase II into long
primary miRNAs (pri-miRNA).10 These pieces are either inserted into noncoding RNAs,
fixed into introns of protein-coding genes, or are clustered in polycistronic transcripts.11
Processing of the pri-mRNAs occurs by two Ribonuclease-III enzymes, Drosha and
Dicer.12 In the nucleus, the enzyme Drosha attaches to a pri-mRNA and excises the
next precursor, pre-mRNA.10 The pre-mRNA is about seventy nucleotides long and can
fold into a stem-loop structure.10 The pre-mRNA is exported from the nucleus into the
13
cytoplasm by Exportin-5.13 Once in the cytoplasm, it is cleaved by the enzyme Dicer,
producing a miRNA duplex intermediate that is about twenty base pairs in length.14 The
duplex contains one strand of mature miRNA, which becomes bound by a large
Argonaute protein and becomes part of the RNA-induced silencing complex (RISC).15
The mechanism of action of miRNA is achieved through the RISC and is
attributed mainly to the Argonaute core.15 The Argonaute protein not only binds the
miRNA in forming the RISC, but it also joins with other Argonaute proteins to form the
center of the RISC complex.16 This Argonaute core is highly conserved amongst
species and is responsible for the slicing activity that cleaves messenger RNA (mRNA),
as instructed by the miRNA.17 The RISC binds to a 3’ untranslated region of the target
mRNA (mRNA-3’-UTR), regulating the expression of the mRNA, and subsequently, the
expression of genes.18
Once bound, the RISC cleaves the target mRNA, inhibiting protein synthesis and
degrading the target mRNA.19 If destined for degradation, the cleaved mRNA associates
with cytoplasmic processing bodies (PBs).20 The PBs localize to the RISC’s Argonaute
core and contain enzymes needed for mRNA degradation, such as decapping enzymes
and exonucleases.20 Together, the PBs and RISC carry out the actions determined by
their associated miRNA.9 Furthermore, a single miRNA can regulate multiple targets,
emphasizing the widespread effect of miRNAs throughout the body.21
miRNAs have been studied as potential biomarkers of health and disease.1
Biomarkers are considered any structure or substance objectively measured in a
sample to indicate health and disease.22 Cytokines, such as interleukin-1β (IL-1β) and
tumor necrosis factor alpha (TNF-α) have been studied as biomarkers in the medical
14
and dental fields.23 Studies of tooth movement have also observed interleukin-6 (IL-6),
interleukin-8 (IL-8), dentine sialophosphoprotein and alkaline phosphatase (ALP) as
biomarker candidates in orthodontic tooth movement.24-26 Furthermore, receptor
activator of nuclear factor kappa B (RANK), RANK ligand (RANKL), and osteoprotegerin
(OPG) have been studied as biomarkers of bone resorption.27 Studies show the
presence of RANKL, a transmembrane protein, and RANK in extracellular vesicles
(EVs) and suggest that EVs and their components can be detected in gingival crevicular
fluid.28,29
The term “exosome” was initially suggested to identify extracellular vesicles of
endosomal origin.30 Once regarded as cellular trash, exosomes are now known as a
form of intercellular communication that can alter functions of target cells.31 microRNAs
are found in exosomes and function by regulating gene expression post-
transcriptionally.32 Some studies have observed the role of miRNAs in bone remodeling
and inflammation.33,34 One miRNA proposed as a key regulatory molecule of the
inflammatory response is miRNA-146.35
The miRNA-146 family consists of miRNA-146a and miRNA-146b.35 Both can be
induced by pro-inflammatory cytokines, such as IL-1β and TNF-α.35 It is also reported
that miRNA-146a negatively regulates the innate immune response by repressing IL-1
receptor-associated kinase 1 (IRAK1) and tumor necrosis factor receptor-associated
factor 6 (TRAF6).36 IRAK1 and TRAF6 are significant because they are two crucial
molecules in the nuclear factor kappa B (NF-κB) pathway.36 IRAK1 and TRAF6 are
significant because they are two crucial molecules in the nuclear factor kappa B (NF-κB)
pathway.36 They act by increasing NF-κB activity, resulting in an increased expression
15
of the pro-inflammatory cytokines IL-6 and IL-8, which are key mediators of
inflammation.36
In medicine, some chronic inflammatory diseases are shown to be related to
miRNA-146a dysregulation.35 Psoriasis, systemic lupus erythematosus (SLE), and
rheumatoid arthritis are a few of the most significant.37-39 In dentistry, studies have
proposed miRNA-146a as an inflammatory biomarker by observing its expression in
patients with periodontitis.40,41 A study by Motedayyen et al. assessed miRNA-146a
expression in subjects with healthy periodontium versus chronic periodontitis.41 They
found that subjects with chronic periodontitis had significantly higher levels of miRNA-
146a.41 Furthermore, they found that elevated miRNA-146a was accompanied by a
reduction in TNF-α and IL-6, two pro-inflammatory cytokines.41
These results are similar to another study by Xie et al. which analyzed miRNA-
146a expression in the inflammatory response in human gingival fibroblasts (HGFs).41,42
In this study, they used polymerase chain reaction (PCR) to measure the expression of
miRNA-146a after Porphyromonas gingivalis (P. gingivalis) lipopolysaccharide
stimulation.42 Their results showed a significant difference in miRNA-146a expression in
the P. gingivalis stimulated HGFs, with a greater expression of miRNA-146a in these
HGFs.42
MicroRNA-146a expression in bone has also been of interest.43 A study by
Nakasa et al. aimed to determine whether overexpression of miRNA-146a inhibits
osteoclastogenesis.44 In their animal study, they administered an intravenous injection
of double-stranded miRNA-146a into mice with arthritis.44 They observed that while not
completely suppressed, the mice injected with miRNA-146a showed a reduction of pro-
16
inflammatory cytokines TNF-α, IL-1β, and IL-6.44 Radiographically and histologically,
those injected with the microRNA showed less destruction of cartilage and bone.44
Further assessing the role of miRNA-146a in bone remodeling, a study by
Holliday et al. looked at osteoclast exosomes, exosomal components and bone
remodeling processes.34 They discussed candidate molecules identified in exosome-
based regulation of bone remodeling.34 Two of these candidates were miRNA-146a and
miRNA-214.34 Studies by Li et al. and Sun et al. detected miRNA-214 as enriched in
osteoclast exosomes compared with exosomes from precursors.33,45 The Holliday et al.
study found similar results to Sun et al. regarding miRNA-214, which Sun et al. reported
to be enriched 4-fold in osteoclasts.33,34 Significantly, Holliday et al. found that miRNA-
146a was enriched over 80-fold in osteoclasts compared with precursors, making it a
potential biomarker for bone remodeling and providing a rationale for further study of
miRNA-146a as a candidate biomarker for orthodontic tooth movement.34
A recent study of orthodontic tooth movement by Atsawasuwan et al. analyzed
gingival crevicular fluid (GCF) samples of orthodontically treated and untreated subjects
to observe the expression of microRNA-29.46 GCF samples were collected five times
throughout treatment and the results showed the greatest expression of microRNA-29 in
the subjects who underwent canine retraction.46 Furthermore, they found that the
highest concentration of their miRNA of interest was present in the fraction of GCF
containing EVs.46 Their results showed an increased expression of miRNA-29 in the
treated subjects, revealing a correlation between this miRNA, orthodontic tooth
movement, and osteoclast function.46 Furthermore, this study suggests that miRNAs in
GCF can be candidate biomarkers for orthodontic tooth movement.46
17
Of the many miRNAs that impact physiologic and disease processes there are
some deemed “reference” miRNAs.47 One such reference miRNA is miRNA-103-3p.47
While found to promote human gastric cancer cell proliferation, it is an endogenous
miRNA present in serum, plasma, urine, and cerebrospinal fluid.48 A study by Song et
al. identified suitable reference genes for quantitative PCR (qPCR) analysis of serum.49
Of six candidate reference microRNAs, microRNA103-3p was found to be moderately
abundant in serum samples, suggesting it as a suitable miRNA for comparison.49
For many years, GCF has been collected and analyzed for potential
biomarkers.50 Rather than collecting and examining saliva or other oral fluids, GCF is
preferred due to its site-specific nature and better ability to express the metabolic status
of localized tissue.51 Its inclusion of bacterial and host cell molecules makes it ideal for
evaluating cellular metabolism.51 Considered a serum transudate or inflammatory
exudate, GCF accumulates in the gingival crevice by leakage through postcapillary
venules in tissue.51,52 When the lymphatic system is unable to remove the fluid, due to a
greater filtrate volume, leakage occurs and fluid escapes into the gingival sulcus.52 It is
in the sulcus or at the gingival margin that GCF is collected.53 Experimentally, this
process is supported by an animal study by Del Fabbro et al.54 They observed gingival
fluid flow by measuring osmotic pressure at different points in the gingival crevice.*
They also observed the thickness of epithelium to distinguish absorption or fluid
release.54 These methods of measurement are an improvement from past techniques,
where quantities were primarily based on estimates.55
Collection of available GCF is a sensitive process because contamination of any
kind can affect analysis and results.53 If blood contaminates the sample it must be
18
discarded, and plaque and saliva must be removed from the area.56 Furthermore,
collecting GCF samples is a challenge when fluid is sparse.53 Enough fluid must be
gathered for adequate analysis, but increasing collection time can increase the risk for
contamination.53 It has been shown that GCF can be isolated from a healthy sulcus,
although only in small amounts.51 It has been clinically demonstrated that GCF
production greatly increases when gingival inflammation is present.57 Damage to the
epithelium leads to localized periodontal inflammation and increased vascular
permeability, which increases the flow.57 A healthy periodontium releases about 3
μl/hour of fluid into the gingival sulcus, while sites with periodontal disease can release
up to 44 μl/hour.58 Regardless of these limitations, many studies in health care have
successfully used GCF collection techniques to obtain adequate fluid samples for
analysis.59,60
The gingival washing method, use of micropipettes, and use of filter paper strips
are three main techniques for collecting GCF.53 Each technique has its advantages and
disadvantages, with the washing method best suited for samples that need cells
collected.53 This technique involves injecting and aspirating a balanced salt solution of
known amount into the gingival sulcus repeatedly, before collecting the final sample.53
By mixing the fluids in this way it is difficult to determine the sample dilution and to
control the final volume.53 As described, the gingival washing method is not the most
efficient system for gathering GCF but can be useful if sample dilution is not of
concern.53
Using capillary tubes to collect GCF is more beneficial than gingival washing, if
standardization of the GCF volume is desirable.53 Because the micropipettes have a
19
known diameter, GCF volume is easy to determine.53 Tubes of varying diameters are
available for GCF collection, and filling the tube fully with GCF would provide an
accurate measurement of sample volume.61 The tubes are placed in the gingival crevice
and fluid flows into the micropipettes by capillary action.53,61,62 The disadvantage of this
method is that it may require more time to obtain an adequate volume of GCF.53
Using absorbent paper strips is the favored technique for GCF collection
because it is fast and least traumatic.63 Many types and sizes of paper strips are
available, such as Whatman chromatography paper and PerioPaper™.64 When using
the strips the sample tooth is cleaned with a cotton pellet, isolated with cotton rolls,
dried, and then the paper strip is placed.56 The strip is typically placed into the gingival
sulcus until slight resistance is felt, or at the coronal edge of the gingival sulcus.53
Placement of the strip causes little to no irritation, and GCF is collected by fluid
migration through the paper.53
To observe miRNAs from GCF, RT-PCR is often used.65 PCR is a method for
amplifying fragments of DNA.65 This technique allows for segments of specific
chromosomes to be amplified more than a million-fold, and for testing of very small
sequences of DNA, which could not otherwise be tested.66 RT-PCR is the ability to
monitor the progress of the PCR as it occurs, since data is collected throughout the
PCR process.65 RT-PCR records the point during cycling when the target is first
detected and amplified, rather than reporting the amount of target gathered after a fixed
number of cycles, as in conventional PCR.67
The real-time PCR process consists of twenty-five to fifty cycles, and each cycle
undergoes three phases at different temperatures.65 The initial phase is denaturation,
20
when the DNA helix is separated into two strands.65 Denaturation occurs at a high
temperature.65 The second phase, annealing, occurs when the sample is cooled and the
added primer attaches to the 3’ end of the target DNA to be amplified.65 The third phase
is amplification, which occurs at a high temperature and is when elongation of the
primer occurs, creating a complementary DNA strand to the target.65
Significantly, a fluorescent dye is used in qPCR and binds to double-stranded
DNA molecules by inserting between the base pairs.68 The fluorescence is measured
with each amplification cycle to determine relatively how much DNA has been
amplified.68 With the use of dye in PCR, the higher the starting amount of the target
DNA, the sooner an increase in fluorescence is observed.68 qPCR data is represented
in an amplification plot, which shows each sample as a curve using cycle number and
fluorescent signal.69
At first glance, an amplification plot allows for basic interpretation of the data
without numerical values.69 In a plot, the curve farthest to the left signifies the highest
concentration of the target and earliest signal amplification.69 The curve farthest to the
right signifies the lowest initial concentration of the target and subsequent latest signal
amplification.69 The data can be understood more specifically by observing key points in
the amplification plot.70 A horizontal line is present in each plot and denotes a threshold
value, set by the machine.70 The section of the curve below the threshold represents
fluorescence that cannot be distinguished from background fluorescence.70 The point at
which fluorescence can be sufficiently detected is when the curve just passes the
threshold value.70 This point is easily identified by the intersection between the curve
21
and threshold line and is referred to as the cycle threshold, or Ct.70 The ability to
determine Ct values provides an easy method for comparison between samples.70
22
CHAPTER 2 MATERIALS AND METHODS
Participants and Eligibility
The University of Florida Institutional Review Board for the Protection of Human
Subjects approved this project (UF-IRB-01, IRB201801700). Additional funding for this
project was provided by the Southern Association of Orthodontists (SAO). Gingival
crevicular fluid samples were collected from twelve adult volunteers using the inclusion
and exclusion criteria. The inclusion criteria consisted of the following: an age range of
18 to 40 years old, the presence of all six maxillary and mandibular anterior teeth, and
the presence of all four maxillary premolars. Exclusion criteria included the presence of
extremely poor oral hygiene or a history of smoking or tobacco use within the past year.
The patient population was representative of the patient population of the University of
Florida College of Dentistry Department of Orthodontics, with patients of all races,
genders, and ethnicities included in the study.
Study Design
Collections of all GCF samples were carried out in two visits for each subject.
The second visit was at least twenty-four hours after the first visit. At the initial visit, all
subjects confirmed that they did not eat, drink, brush their teeth, or use mouthwash at
least two hours prior to sample collection. Subjects confirmed this again at the second
visit, prior to collection. At enrollment and prior to sample collection, all subjects
provided written informed consent. Three methods of GCF collection were used and are
the following: PerioPaper, Durapore filter membrane, and microcapillary tubes. Teeth
numbers 5, 7, and 9, were used as collection sites. For each participant, the collection
method varied per tooth, following the pattern listed in Table 2-1.
23
Sample Collection
Each sample collection Eppendorf tube was labeled with a specific subject
identifier. The subject was assigned a letter, with the first subject being “A.” Directly
following that letter was a number designating the first visit, “1,” or the second visit, “2.”
A hyphen then separated a label designating which method was performed, either “P”
for PerioPaper, “D” for Durapore filter membrane, or “M” for microcapillary tube,
followed by the tooth number that was collected. Table 2-2 shows the identifiers listed
for the samples that were analyzed.
For each subject at each visit six total samples were collected, with two samples
per technique. Plaque was removed from the buccal surface of each tooth along the
gingival margin and samples were collected on the mesial and distal of each tooth. If
any sample was visually contaminated with blood it was discarded and a new sample
was taken. The specific collection techniques for each method are as follows:
PerioPaper
The tooth designated for sampling was cleaned of any plaque on the buccal
surface using a cotton pellet. The tooth was then isolated with cotton rolls to prevent
contamination by saliva and was air dried for five seconds. A PerioPaper® GCF strip
(Oraflow Inc., Plainview, NY) was inserted about 2mm into the gingival sulcus, until mild
resistance was felt, on the mesial aspect of the tooth. The strip was left in place for thirty
seconds and was removed using a sterilized cotton plier. It was placed in a sterilized
Eppendorf tube with the appropriate subject/sample label and 100 μl of phosphate
buffered salien (PBS; pH 7.4, RNase free). The same process was repeated with a new
PerioPaper strip on the distal aspect of the tooth. The samples were immediately placed
in a freezer and kept at -80°C for further analysis.
24
Durapore Filter Membrane
For each sample collection a Durapore filter membrane was cut to the same
length and width as a PerioPaper strip, 2x8mm. The tooth designated for sampling was
cleaned of any plaque on the buccal surface using a cotton pellet. The tooth was then
isolated with cotton rolls to prevent contamination by saliva and was air dried for five
seconds. A cut, sterilized Durapore filter membrane strip (pore size of 0.22μm; Millipore
Corp., Bedford, Mass., USA) was inserted about 2mm into the gingival sulcus, until mild
resistance was felt, on the mesial aspect of the tooth. The strip was left in place for thirty
seconds and was removed using a sterilized cotton plier. It was placed in a sterilized
Eppendorf tube with the appropriate subject/sample label and 100 μl of PBS (pH 7.4,
RNase free). The same process was repeated with a new Durapore filter membrane
strip on the distal aspect of the tooth. The samples were immediately placed in a freezer
and kept at -80°C for further analysis.
Microcapillary Tube
The tooth designated for sampling was cleaned of any plaque on the buccal
surface using a cotton pellet. The tooth was then isolated with cotton rolls to prevent
contamination by saliva and was air dried for five seconds. A 1 μL microcapillary tube
(Drummond Scientific Co., Broomall, Pennsylvania, USA) was placed on the mesial
aspect of the tooth at the entrance to the gingival sulcus. The micropipette was held in
place by the operator for five minutes. GCF was taken up into the micropipette by
capillary action. After five minutes the GCF was eluted from the micropipette using a
bulb provided by the company. The bulb is attached to one end of the micropipette and
produces gentle air pressure, dispensing the GCF into a sterilized Eppendorf tube
containing 100 μL of PBS (pH 7.4, RNase free). The same process was repeated with a
25
new microcapillary tube on the distal aspect of the tooth. The samples were immediately
placed in a freezer and kept at -80°C for further analysis.
RNA Isolation
A total of seven subjects and samples from ten visits were used for analysis, as
shown in Table 2-2. The QIAGEN kit protocol, miRNeasy Serum/Plasma Advanced Kit,
for RNA isolation was used and began by thawing each sample and placing them on
ice. 60μl Buffer RNA Proximity Ligation (RPL) was added to each Eppendorf tube
containing thawed sample with PBS. Each tube was closed and vortexed for more than
five seconds. The samples then rested at room temperature for three minutes. The
samples were centrifuged at 13,000 times gravity (×g) for three minutes at room
temperature, to precipitate the pellet, as shown in Figure 2-1. The supernatant from
each was transferred to a new, labeled, reaction tube. 1 volume isopropanol was added
and mixed by vortexing. Each entire sample was transferred to an RNeasy UCP
MinElute column, the lids were closed, and the columns were centrigured for fifteen
seconds at greater than 8,000 ×g. The flow-through was discarded. 700 μl Buffer RWT
was pipetted into the Rneasy UCP MinElute spin column. The lids were closed and they
were centrifuged for fifteen seconds at greater than 8,000 ×g. The flow-through was
discarded. 500μl Buffer RPE was placed onto the RNeasy UCP MinElute spin column.
The lids were closed and they were centrifuged for fifteen second at greater than 8,000
×g. The flow-through was discarded. 500μl of 80% ethanol was added to the Rneasy
UCP MinElute spin column. The lids were closed and they were centrifuged for two
minutes at greater than 8,000 ×g. The flow-through and collection tubes were discarded.
The Rneasy UCP MinElute spin columns were placed in new 2 mL collection tubes,
supplied in the kit. The lids of the spin columns were kept open and they were
26
centrifuged at full speed for five minutes to dry the membrane. The flow-through and
collection tubes were discarded. The Rneasy UCP Min elute spin columns were placed
in new 1.5 mL collection tubes, supplied in the kit, and 20 μl Rnase-free water was
added diretly to the center of each spin column membrane. Incubation then occurred for
one minute. The lids were closed and they were centrifuged for one minute at full
speed. The RNA was then eluted. If ready for cDNA synthesis it was kept on ice for the
next step, otherwise it was frozen at -80°C for further analysis.
cDNA Synthesis
cDNA synthesis was accomplished using the QIAGEN kit protocol, specifically
the miRCURY LNA Universal RT microRNA PCR protocol. If frozen, the RNA samples
were thawed and kept on ice. From the kit, the 5x Reaction Buffer, Enzyme mix, and
RNA spike were thawed in the fridge. A master mix was made by adding 2 μl of the 5x
Reaction Buffer, 1 μl of the enzyme mix, and 0.5 μl of the RNA spike to an Eppendorf
tube. This tube was kept on ice. New, Eppendorf tubes were labeled with
subject/sample identifiers and each RNA sample was added to the appropriately labeled
tube. Master Mix was added to each tube and then each tube was ready for cDNA
synthesis. The samples were incubated in a 2720 Thermal Cycler (Figure 2-2) for 65
minutes with the following specifications: 60 minutes at 42°C, 5 minutes at 95°C, at
least 3 minutes at 4°C.
Real-Time PCR
To prepare for qPCR, a 96-well plate was used. A total of four 96-well plates
were used and four runs of qPCR were completed. The first round of qPCR was for
subjects A and B. The second round was for subjects C and D. The third round was for
subjects E and F. The fourth round was for subjects A, F, and M. An example of a
27
planned and labeled 96-well plate used for qPCR is shown in Figure 2-3. The QIAGEN
kit protocol, miRCURY LNA Universal RT microRNA PCR protocol, was used for
sample preparation in the PCR plate and for setting the Thermal Cycler machine. In
each labeled well the appropriate cDNA sample was added, along with nuclease-free
water, PCR master mix, and SYBR green dye. A total of 10 μl was present in each well.
The plate was sealed, spun in a Microplate Spinner for a few seconds and placed into
the C1000 Touch Thermal Cycler (Figure 2-4) to undergo real-time PCR. The settings
were as follows: 39 amplification cycles at 95°C for 10 seconds, 60°C for 1 minute, and
a ramp-rate of 1/6 C/s^7 optical read. qPCR data was retrieved using the Bio-Rad
qPCR Analysis Software. From this software, raw data was retrieved as Ct values and
amplification plots.
Statistical Considerations
One-way ANOVA and student t-test were performed to determine statistical
significance, with statistical significance represented by a p-value less than 0.05.
Table 2-1. Sample Collection Pattern for Subjects
Subject Tooth #5 Tooth #7 Tooth #9
A PerioPaper Durapore Micropipette B Durapore Micropipette PerioPaper C Micropipette PerioPaper Durapore D PerioPaper Durapore Micropipette
28
Table 2-2. Sample Identifiers
Subject PerioPaper Durapore Micropipette
A A1-P5 A1-P5 A1-D7 A1-D7 A1-M9 A1-M9 A2-P5 A2-P5 A2-D7 A2-D7 A2-M9 A2-M9 B B1-P9 B1-P9 B1-D5 B1-D5 B1-M7 B1-M7 C C1-P7 C1-P7 C1-D9 C1-D9 C1-M5 C1-M5 D D1-P5 D1-P5 D1-D7 D1-D7 D1-M9 D1-M9 E E1-P9 E1-P9 E1-D5 E1-D5 E1-M7 E1-M7 F F1-P7 F1-P7 F1-D9 F1-D9 F1-M5 F1-M5 F2-P7 F2-P7 F2-D9 F2-D9 F2-M9 F2-M9 M M1-P7 M1-P7 M1-D9 M1-D9 M1-M5 M1-M5 M2-P7 M2-P7 M2-D9 M2-D9 M2-M5 M2-M5
Figure 2-1. Microfuge® 18 Centrifuge. Courtesy of Dr. Kelsey Cronauer Wahl.
Centrifugation of Samples for RNA Isolation
29
Figure 2-2. 2720 Thermal Cycler. Courtesy of Dr. Kelsey Cronauer Wahl. cDNA
Synthesis
Figure 2-3. 96-well Plate Organized and Labeled. Courtesy of Dr. Kelsey Cronauer
Wahl. Plate Prepared for Fourth Run of qPCR
30
Figure 2-4. C1000 Thermal Cycler. Courtesy of Dr. Kelsey Cronauer Wahl. Plate
Loaded and Machine Prepared for qPCR
31
CHAPTER 3 RESULTS
Samples from seven of the twelve subjects were analyzed, and samples from
only the first visit were analyzed for all seven subjects. For three of the seven subjects,
their second visit samples were analyzed. Samples were collected using the three
techniques of PerioPaper strips, Durapore filter membrane, and microcapillary tubes.
qPCR was performed four times and amplification plots from all four runs were obtained
using the Bio-Rad qPCR Analysis Software and are shown from Figure 3-1 to Figure 3-
4. Using this software, numerical raw data was also obtained as Ct values. Table 3-1 to
Table 3-3 shows the Ct values obtained for each subject and organized based on GCF
collection technique and miRNA. These tables also include the calculated ΔCt values
for each subject, which uses miRNA-103-3p to normalize the data of miRNA-146a. ΔCt
values were calculate by subtracting the Ct value of miRNA-146a from the Ct value of
miRNA-103-3p.
For each of the three collection techniques, the mean Ct value for miRNA-146a
and miRNA-103-3p and the mean ΔCt value were calculated. A series of one-way
ANOVAs were conducted on the entire dataset of seven subjects (ten sample
groupings) and the descriptive statistics are presented in Table 3-4. This was done in
order to determine whether there are significant differences in the mean values of
miRNA-146a, miRNA-103-3p, and ΔCt on the basis of condition, which consisted of
Periopaper, Durapore, and microcapillary tubes. Significant mean differences were not
found with regard to miR146a, F(2, 27) = 1.539, p = .233, miR103-3p, F(2, 27) = 1.103,
p = .347, or ΔCt, F(2, 27) = 1.978, p = .158. All p-values were above 0.05. As shown,
32
means differed slightly by condition, while these mean differences were not significantly
different.
A series of one-way ANOVAs were conducted on a subset of the data, which
excluded four sample groupings. Four sample groupings were excluded because the
subjects were undergoing orthodontic treatment at the time of collection, as noted at the
visit. Six sample groupings were run for this one-way ANOVA series and descriptive
statistics are presented in Table 3-5. These analyses also failed to find significant mean
differences on the basis of miR146a, F(2, 15) = 1.970, p = .174, miR103-3p, F(2, 15) =
1.347, p = .290, or ΔCt, F(2, 15) = .529, p = .600. All p-values were above 0.05. Mean
differences were again found here on the basis of condition, while these mean
differences also failed to achieve statistical significance. Graphical representations of
data from the full dataset (ten sample) and subset (six sample) are shown in Figure 3-5
and Figure 3-6. Based on the statistical analysis we therefore fail to reject our null
hypothesis and conclude that there is no significant difference in the recovery of
miRNA-146a in GCF using Periopaper, Durapore filter membrane, or microcapillary
tubes.
An additional method of comparison was completed to determine the fold change
in expression of miRNA-146a between the GCF collection methods.71 The Livak Method
was used to calculate the fold change of gene expression, referred to as 2^-(ΔΔCt).71 In
this method, a reference is needed to compare conditions. PerioPaper was used as the
reference condition. Therefore the 2^-(ΔΔCt) values were calculated to compare fold
change expression of miRNA-146a for Durapore in relation to PerioPaper and for
microcapillary tubes in relation to PerioPaper. For Durapore the 2^-(ΔΔCt) was a 1.63
33
fold change decrease and the 2^-(ΔΔCt) for microcapillary tubes was a 3.12 fold change
decrease.
Since a few subjects were undergoing orthodontic treatment, the data was
analyzed further to assess whether there is a significant difference in miRNA-146a
expression between two groups, defined as treated and untreated. GCF collection
technique was not a factor of interest in this analysis. The treated and untreated groups
each consisted of five sampling groups. It is necessary to note that for one subject, the
samples from the initial visit were included in the untreated group, while the samples
from the second visit were included in the treated group. This was done since
orthodontic treatment did not begin until the second visit for that subject.
Independent-sample t-tests were conducted specifically comparing the untreated
subjects, with healthy periodontium, and treated subjects, with inflamed periodontium,
on their mean values of miRNA-146a, miRNA-103-3p, and ΔCt. In these analyses,
significant differences between these two groups were found with respect to miR146a,
t(22.103) = 2.253, p < .05, and ΔCt, t(28) = 4.844, p < .001, though not with respect to
miR103-3p, t(27.115) = .047, p = .963. As stated, p-values were less than 0.05 for
miRNA146a and the ΔCt. Table 3-6 presents the descriptive statistics associated with
these analyses, which indicate small mean differences on the basis of untreated
subjects and subjects undergoing orthodontic treatment. In the two cases in which
statistical significance was achieved, significantly higher means were found in the case
of untreated subjects. This data is graphically shown in Figure 3-7. Furthermore, the
Livak Method was used to calculate the fold change of gene expression between the
treated and untreated groups.71 For this calculation the mean ΔCt for the target miRNA-
34
146a and the mean ΔCt for the reference miRNA-103-3p were used to calculate the fold
change of gene expression of miRNA-146a between the two groups. The 2^-(ΔΔCt) was
an increase of 5.81.
35
Figure 3-1. Amplification Plot of A1 and B1 Samples
Figure 3-2. Amplification Plot of C1 and D1 Samples
36
Figure 3-3. Amplification Plot of E1 and F1 Samples
Figure 3-4. Amplification Plot of A2, F2, M1 and M2 Samples
37
Figure 3-5. Bar Graph Showing Full Dataset (Green) and Subset (Blue) of Mean Ct Values for miRNA-146a Based on GCF Collection Method
Figure 3-6. Bar Graph Showing Full Dataset (Green) and Subset (Blue) of Mean Ct
Values for miRNA-103-3p Based on GCF Collection Method
38
Figure 3-7. Bar Graph Showing Mean Ct Values for miRNA-146a (Blue) and miRNA
103-3p (Green) and ΔCt (Gold) in Treated and Untreated Subjects
39
Table 3-1. Ct Values for PerioPaper Samples
Subject microRNA-146a microRNA-103-3p ΔCt
A1 29.2545
27.3836 1.87092
A2 25.375
26.36 -0.985
B1 32.1364
28.8240 3.3124
C1 31.8422
27.8092 4.03296
D1 25.4571
23.2879 2.1692
E1 29.6349
24.7220 4.9128
F1 35.6996
31.2679 4.4317
F2 34.49
37.40 -2.91
M1 28.935
28.45 0.485
M2 29.03
27.66 1.37
Table 3-2. Ct Values for Durapore Samples
Subject microRNA-146a microRNA-103-3p ΔCt
A1 27.0819 25.4094 1.672 A2 26.685 25.12 1.565 B1 28.1666 24.7352 3.431 C1 34.0511 30.8830 3.168 D1 26.9159 23.8072 3.109 E1 29.4507 25.5267 3.924 F1 29.4714 24.7691 4.702 F2 28.765 26.9 1.865 M1 28.69 27.7 .990 M2 29.01 27.72 1.290
Table 3-3. Ct Values for Microcapillary Tube Samples
Subject microRNA-146a microRNA-103-3p ΔCt
A1 30.639 27.5900 3.049 A2 30.555 28.06 2.495 B1 28.531 23.3338 5.197 C1 33.996 33.1189 .877 D1 37.628 31.9406 5.687 E1 29.951 25.3635 4.588 F1 37.303 32.0536 5.249 F2 28.925 25.86 3.065 M1 26.97 24.49 2.480 M2 28.59 26.18 2.410
40
Table 3-4. ANOVA Descriptive Statistics for Full Data Set (Ten Samples)
Measure Condition Mean Standard Deviation
Standard Error
95% Confidence Interval Lower Limit
95% Confidence Interval Upper Limit
miRNA- 146a
PerioPaper 30.186 3.417 1.080 27.741 32.630
Durapore 28.829 2.105 .666 27.323 30.335 Micropipette 31.309 3.735 1.181 28.637 33.981 Total 30.108 3.223 .589 28.904 21.311 miRNA- 103-3p
PerioPaper 28.316 3.874 1.225 25.545 31.088
Durapore 26.257 2.085 .659 24.766 27.748 Micropipette 27.799 3.446 1.090 25.334 30.264 Total 27.458 3.238 .591 26.249 28.667 ΔCt PerioPaper 1.869 2.491 .788 0.087 3.651 Durapore 2.572 1.257 .397 1.673 3.471 Micropipette 3.510 1.578 .499 2.381 4.639 Total 2.650 1.912 .349 1.936 3.364
Table 3-5. ANOVA Descriptive Statistics for Subset of Data (Six Samples)
Measure Condition Mean Standard Deviation
Standard Error
95% Confidence Interval Lower Limit
95% Confidence Interval Upper Limit
miRNA- 146a
PerioPaper 30.671 3.437 1.403 27.064 34.278
Durapore 29.190 2.625 1.071 26.435 31.944 Micropipette 33.008 3.893 1.403 28.923 37.093 Total 30.956 3.546 0.836 29.193 32.719 miRNA- 103-3p
PerioPaper 27.216 2.865 1.170 24.209 30.222
Durapore 25.855 2.538 1.036 23.191 28.519 Micropipette 28.900 4.054 1.170 24.645 33.155 Total 27.324 3.284 0.774 25.691 28.957 ΔCt PerioPaper 3.455 1.233 0.503 2.162 4.749 Durapore 3.335 1.007 0.411 2.278 4.391 Micropipette 4.108 1.831 0.748 2.186 6.030 Total 3.632 1.362 0.321 2.955 4.310
41
Table 3-6. t-test for Treated and Untreated Subjects
Measure Group Mean Standard Deviation
Standard Error
miRNA-146a Untreated 28.866 2.099 0.542 Treated 31.349 3.717 0.960 miRNA-103-3p Untreated 27.486 2.983 0.770 Treated 27.430 3.580 0.920 ΔCt Untreated 1.381 1.574 0.406 Treated 3.919 1.282 0.331
42
CHAPTER 4 DISCUSSION
Candidate biomarkers have been studied in dentistry for many years, with a long-
term goal of identifying biomarkers to aid in early detection of disease or undesired
outcomes.72 Periodontal studies have assessed GCF for potential biomarkers to
indicate periodontal inflammation and periodontal disease.73 Some studies have
identified potential biomarkers including cytokines and miRNAs.72 Significantly, miRNAs
have been detected within extracellular vesicles, revealing their ability transfer genetic
information between cells.74 As shown in a study by Atsawasuwan et al., miRNA-29 was
detected in GCF of orthodontically treated subjects and untreated subject.46
Furthermore, the greatest amount of this miRNA-29 was detected in a portion of the
sample containing EVs.46 Other studies also identified miRNA in exosomes, with studies
by Sun et al. and Li et al. showing the presence of miRNA-214 in exosomes of
osteoclasts.33,45 Holliday et al. showed that miRNA-146a was enriched over 80-fold in
osteoclasts, providing a foundation for further study of miRNA-146a as a candidate
biomarker for bone remodeling processes and orthodontic tooth movement.34
Identifying biomarkers of tooth movement can improve orthodontic diagnosis and
treatment planning. Using a non-invasive method to collect and identify constituents of a
patient’s GCF could aid practitioners in providing the best and most efficient treatment
for the patient. This could be especially beneficial for patients at risk for adverse
treatment outcomes, such as root resorption during orthodontic treatment or ankylosis
of impacted teeth. Furthermore, determining the most cost-effective and reliable method
for sample collection would be beneficial so that in the future these practices can be
easily implemented in a clinical setting and available to practitioners.
43
GCF collection has been done for many years and shows local processes at the
site of collection.51 Studies have used GCF to identify miRNA in EVs and proteins in
EVs.34,75 While many studies use PerioPaper for GCF collection, other techniques have
been suggested, with advantages and disadvantages to each. Therefore, we performed
our study to determine whether miRNA-146a could be adequately identified within GCF
samples and whether a difference in miRNA-146a expression is noted between
collection techniques.
The results of our study show that there is no statistically significant difference in
miRNA-146a expression between the PerioPaper, Durapore, or Microcapillary tube
techniques. Using one-way ANOVA we analyzed the data twice, first with the entire
dataset (Table 3-4) and second with a subset of data (Table 3-5). Statistical analysis of
the full dataset and the subset of data did not yield p-values less than 0.05 for
expression of miRNA-146a and miRNA-103-3p between the three techniques.
Furthermore, the p-value for the normalized ΔCt was not less than the significance
value of 0.05 for the full dataset or subset of data.
Two data sets were analyzed for significance because some subjects were noted
to be in orthodontic treatment. For completion of data analysis, the subset of data
(Table 3-5) did not include samples taken from subjects that were noted at one or both
of their collection visits to be in active orthodontic treatment. Analysis of both data sets
suggests that there is no significant difference in the expression of miRNA-146a
between the three collection methods. With studies often using multiple strips or
micropipettes in one sulcus to obtain GCF, we designed our study as described to be
more clinically applicable.
44
Many studies using GCF for analysis use PerioPaper. These strips come cut,
sterilized, packaged and are easy to insert and remove from the gingival sulcus. If
interested in determining the volume of a sample, a Periotron 8000® (Oraflow,
Plainview, NY, USA) machine can be purchased and used. Durapore filter membrane is
less widely used and must be cut into strips to be used. While this requires more time
for the operator, it is a more economic material. Both PerioPaper and Durapore are
easy to use and comfortable for the subject but due to the nature of the materials,
elution of the sample can lead to particles from both strips entering the media.
Contrasting, a microcapillary tube would collect and elute a more pure sample.
Depending on the volume needed, microcapillary tubes can be purchased with different
diameters. The microcapillary tube has a defined volume and should be an efficient way
to calculate volume. However, GCF volume is minimal and often the tube is not filled
entirely, making it difficult to determine sample volume. Additionally, this technique is
tiring for both the operator and the subject. Collection at each gingival sulcus occurred
for five minutes, which is much longer than the thirty second collection time for
PerioPaper and Durapore strips. The calculated fold change in gene expression of
miRNA-146a was 1.63 for Durapore strips and 3.12 for microcapillary tubes. These
values represent a decrease in fold change expression of miRNA-146a compared to
Periopaper, with the microcapillary tubes showing the largest decrease in fold change of
gene expression. While our results showed no significant difference in miRNA-146a
expression between the three techniques, the micropipettes are more challenging to
use, require more time for GCF collection, and are less clinically applicable than the
PerioPaper and Durapore strips.
45
With some subjects undergoing orthodontic treatment, an additional analysis was
performed to determine whether there was a difference in miRNA-146a expression
between treated and untreated subjects. The data is shown in Table 3-6 as the average
Ct values for each group for miRNA-146a, miRNA-103-3p and ΔCt. Independent-
sample t-tests were performed and the p-values for miRNA-146a and ΔCt are p < .05
and p <.001, respectively. Both p-values are less than the significance value of 0.05,
meaning there is a significant difference in expression of miRNA-146a between treated
and untreated subjects. These results show a significantly greater expression of
miRNA-146a in the treated subjects. The p-value for miRNA-103-3p is greater than 0.05
and, as seen in Table 3-6, the mean Ct values for both groups only differ by 0.056. With
mean values so similar for miRNA-103-3p, it suggests that it is stable and a good choice
for a reference gene. Furthermore, the calculated fold change in gene expression of
miRNA-146a, 5.81, signifies a greater expression of miRNA-146a in subjects
undergoing orthodontic treatment. This study agrees with a study by Holliday et al.,
which detected an 80-fold change in miRNA-146a expression in osteoclasts.34 The
results of this study suggest miRNA-146a as a potential biomarker for orthodontic tooth
movement and is promising for future studies.
A limitation of our study is the small sample size. Increasing the number of
subjects would be beneficial and provide more power to the study. While we aimed to
be more practical in sample collection, the use of two collection strips or tubes per tooth
is still not ideal for a clinical scenario. The use of one strip, or tube, would be more
clinically applicable. RNA isolation, cDNA synthesis, and preparation of the PCR plate
wells are technique sensitive and prone to error and contamination. Error in these
46
processes can affect the quality and quantity of target miRNA expressed. Our study
does include subjects having orthodontic treatment. In retrospect, making treatment an
exclusion criteria would make the data set more homogenous for comparison of GCF
collection techniques.
47
CHAPTER 5 CONCLUSIONS
GCF collection is non-invasive and identification of biomarkers in GCF can
improve treatment planning, assist in early identification of adverse outcomes, and may
lead to therapeutic treatment approaches. The objective of this study was to determine
if miRNA-146a could be sufficiently collected by GCF methods and which method was
best for collecting this miRNA. Results from this study suggest there is no difference in
the PerioPaper, Durapore filter membrane, or microcapillary tube techniques for
expression of miRNA-146a in GCF.
Additional analysis of the data shows a significantly greater expression of
miRNA-146a in subjects undergoing orthodontic treatment compared with untreated
subjects. These results suggest there is promise for identification of miRNA-146a as a
candidate biomarker for orthodontic tooth movement.
48
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BIOGRAPHICAL SKETCH
Kelsey Cronauer Wahl was born and raised in South Florida by her parents
Edward and Julie Cronauer. She completed her undergraduate education at Vanderbilt
University where she majored in History of Art with a Pre-Dental concentration. She
pursued a career in dentistry and was accepted into the University of Florida College of
Dentistry. Upon graduating, she began her specialty training in orthodontics at the
University of Florida College of Dentistry, Department of Orthodontics. In April 2019 she
married her wonderful husband, Tyler Wahl. Her husband, brother, Edward, and
parents, Edward and Julie, have supported her every step of the way. Kelsey plans to
practice orthodontics in Florida after graduation in May 2020.