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A cross-sectional study of the association of PTH on bone quality across levels of propionic acid among adult patients with uremia

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A cross-sectional study of the association of PTH on bone quality across levels of propionic acid among adult patients with uremia

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A CROSS-SECTIONAL STUDY OF THE ASSOCIATION OF PTH ON BONE QUALITY
ACROSS LEVELS OF PROPIONIC ACID AMONG ADULT PATIENTS WITH UREMIA

By

Elizabeth Kermgard

A Thesis Presented to the
FACULTY OF THE USC KECK SCHOOL OF MEDICINE
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
MASTER OF SCIENCE
(CLINICAL, BIOMEDICAL AND TRANSLATIONAL INVESTIGATIONS)

August 2023

Copyright 2023 Elizabeth Kermgard
ii
TABLE OF CONTENTS

Abstract…………………….………………………………………………………………………………1
Chapter 1: Introduction…………………….…………………...………………………….……3
Chapter 2: Methods………………………………………………...…………………………...5
Chapter 3: Results…………………………….………...………………………………………7
Chapter 4: Discussion.……………………….………..………………………………………10
Funding………………….….……………………………………………………………………………13
References………………………….…………………………………………………………...………14
Tables………………………………...…………………………………………………….……………16
Figures………………….…………………………………………………………….………………….21

iii
LIST OF TABLES

Table 1: Histomorphometry Descriptive Statistics…………………….………………….……….…16
Table 2: Histomorphometry Generalized Linear Regression Osteoid Thickness………....….….17
Table 3: Radius HR-pQCT Generalized Linear Regression……………………….………….……17
Table 4: Tibia HR-pQCT Generalized Linear Regression……………………….….………………19
iv
LIST OF FIGURES

Figure 1: Association of Log(iPTH) and Osteoid thickness separated by high and low propionic
acid……………………………………………………………………………………………………….21
Figure 2: Associations of Log(iPTH) and HR-pQCT imaging data separated by high and low
propionic acid……………………………………………………………………………………………22

1

ABSTRACT

Background: Chronic kidney disease (CKD) associated hyperparathyroidism (HPT) among
adults results in impaired bone quality and strength. While calcitriol deficiency partially drives
elevations in parathyroid hormone (PTH), skeletal resistance to PTH also contributes to
progressive HPT. In mice with normal kidney function, short-chain fatty acids (SCFAs) produced
by the gut microbiome were shown to modulate PTH effects on bone. However, interactions
between SCFAs and PTH on bone quality in humans with CKD are unknown. We hypothesized
that SCFAs positively influence the skeletal effects of PTH in CKD in adults.

Methods: In a retrospective cross-sectional study of 60 CKD adult patients with double-label
transiliac crest bone biopsies, we measured dynamic histomorphometry parameters, PTH, and
24 SCFA metabolites (Metabolon, Inc. https://www.metabolon.com/). The study population
included adults 29-88 years of age of which 40% were male and 13% were on dialysis. High-
resolution peripheral quantitative computed tomography imaging (HR-pQCT; resolution 60 μm3)
of the radius and tibia for cortical (Ct) and trabecular (Tb) geometry, density, and
microarchitecture previously was performed in a subset of 45 patients. SCFAs were modeled as
categorical variables dichotomized at the median. Descriptive statistics were used to
characterize the population and generalized linear regression models were used to evaluate the
associations between PTH, SCFA, SCFA-PTH, bone, and SCFA-sex interactions.

Results: We found that the SCFA, propionic acid (PA), modified relationships between PTH and
bone outcomes. In contrast to low levels of PA, high levels of PA and PTH were associated with
thicker osteoid (β=3.32, SE 1.58, p=0.041) on histomorphometry, thicker cortices at the radius
(β=12.50, SE 3.43, p=0.001) and tibia (β=24.46, SE 8.34, p=0.006) and greater Tb volumetric
density (β=26.59, SE 11.28, p=0.024) at the radius by HR-pQCT.
2

Conclusion: In conclusion, we observed that in a cohort of adult CKD patients from Columbia
University Medical Center (CUMC) with bone biopsy and HR-pQCT imaging, PA modified the
skeletal response to PTH in adults with uremia. When PA levels were elevated, higher PTH was
associated with better bone quality. In contrast, when PA levels were low, higher PTH levels
were associated with negative effects on bone quality. Prospective studies are needed to
evaluate whether PA has a therapeutic role in the management of renal osteodystrophy.

Keywords: microbiome, kidney disease, short-chain fatty acids, propionic acid, parathyroid
hormone, bone and mineral disease, CKD-MBD, PTH

3
INTRODUCTION

Chronic kidney disease – mineral and bone disorder (CKD-MBD) leads to an imbalance
in calcium and phosphorous homeostasis resulting in poor bone quality and cardiovascular
disease in adult and pediatric patients with abnormal kidney function. Current treatments in
CKD-MBD focus on targeting PTH, calcium, and phosphorous levels as surrogate markers of
bone quality, but unfortunately, they have shown limited predictive capabilities on true bone
quality.
1
PTH levels alone are an imperfect biomarker of bone and mineral homeostasis in
patients with CKD due to skeletal PTH resistance requiring levels two to nine times normal to
theoretically achieve appropriate bone turnover.
2,3
The cause of skeletal PTH resistance in CKD
continues to be poorly understood. Although mechanisms of 7-84 PTH fragment accumulation
and decreased osteoblast PTH receptors play a role, they do not completely explain the
etiology.
4
Targeting PTH levels is also imperfect because of patient variability in bone
histomorphometry despite levels being within goal range for CKD stage.

The gut microbiome plays a significant role in bone and mineral homeostasis through
immune system interactions and the production of active metabolites.
5
One important group of
microbiome metabolites is short-chain fatty acids (SCFAs), which are produced by anaerobic
bacteria metabolism of indigestible carbohydrates (fiber). The most abundant SCFAs found in
the human intestines are acetate, propionate, and butyrate.
6,7
Mouse models have shown that
an intact gut microbiome is essential for PTH-induced bone remodeling, specifically through
these SCFAs, but little is known about how SCFAs may interact with PTH in patients with
CKD.
8-11

The current gold standard of diagnosing renal osteodystrophy is a bone biopsy with
dynamic histomorphometry. However, new bone imaging with high-resolution peripheral
4
quantitative computed tomography (HR-pQCT) allows for non-invasive three-dimensional
analysis of the macro- and microstructure of bone.
12
HR-pQCT allows for analysis of both
trabecular and cortical bone, whereas bone histomorphometry typically only looks at trabecular
bone from the iliac crest. However, few studies have evaluated the predictive capabilities of HR-
pQCT alongside histomorphometry in assessing bone quality.
13

Ultimately, mechanisms through which the gut microbiome and SCFAs affect bone
homeostasis in adult patients with CKD are not known. We therefore evaluated bone
biochemical values, serum SCFA concentrations, and bone tissue in a cohort of adult patients
with CKD. We hypothesize that SCFAs modify the effects of PTH on bone tissue, analyzed with
histomorphometry, as well as cortical (Ct) and trabecular (Tb) microarchitecture, analyzed with
HR-pQCT, in adult patients with CKD.

5
MATERIALS AND METHODS

The reporting quality follows the STROBE guidelines for cross-sectional study.

Study Population
This was a cross-sectional study of sixty adult participants with CKD who underwent
double-label trans-iliac crest bone biopsy at CUMC. The sixty participants were a part of a
repository that included three prior studies with the same inclusion and exclusion criteria
collected between 2006-2022. We included male and female patients at least 18 years of age
with CKD, including dialysis dependent, who had serum and bone samples, and had stable
vitamin D supplementation for 2 months. Patients were excluded if there was exposure to bone
active agents, had a diagnosis of bone disease other than renal osteodystrophy, or weighed
greater than 300 pounds. The study size was decided based on available data. From these sixty
adult patients, a subset of forty-five who had HR-pQCT (XtremeCT2, nominal resolution 60μm
3
)
imaging of the distal radius and tibia for Ct and Tb geometry, density, and microarchitecture
were included. The study was approved by the CUCM institutional review board, and informed
consent was previously obtained from all adult patients.

Data Analysis
Demographic, biochemical, histomorphometric, and HR-pQCT data were collected from
the repository database at CUCM. Demographical data included sex, age, and race.
Biochemical data included eGFR, calcium, phosphorous, PTH, alkaline phosphatase, and
SCFAs. Histomorphometric data included osteoid thickness, mineral apposition rate (MAR),
bone formation rate (BFR), osteoid maturation time (OMT), mineralization lag time (MLT),
adjusted apposition rate (AjAR), mineralizing surface, bone volume, bone surface area and
tissue volume. Bone biopsies were from the iliac crest in all patients. Prior to the biopsy, double-
6
labeling with tetracycline was done. Bone biopsy was performed using a 7.5 mm trephine.
Specimen were fixed in 70% ethanol for processing. HR-pQCT data included volumetric bone
mineral density, thickness, area, number, and separation. Frozen serum samples were sent to
Metabolon Inc., for SCFA analysis and returned to CUCM in the Fall of 2022. A targeted SCFA
panel was performed with specific concentration analysis on 24 different SCFAs.

Statistical Analysis
Descriptive statistics of demographic data was summarized. Biochemical, bone
histomorphometry, and imaging data were kept as continuous variables. Skewed values were
log-transformed before statistical analysis. SCFAs were dichotomized to indicate SCFA levels at
or above the medians versus below the medians. We decided as a research group to
dichotomize SCFAs at the median because the threshold level that may change effects is
unknown at this time. Generalized linear regression models were used to examine whether
SCFAs modulate the association between PTH and bone parameters. Our model included
SCFAs, PTH, sex, and interaction terms between SCFAs-PTH and sex-PTH. All clinical
variables were examined for confounding (β change of ≥20%), though none were observed. Sex
was still included as a confounder in the model due to the known effect on bone.
Multicollinearity was examined using variance inflation factor (VIF) > 10, though none was
observed. Sensitivity analysis was also performed to exclude potential outliers, with no
substantial differences observed. Outliers were defined as any value less than or greater than
1.5-times the interquartile range (IQR). There were no missing data points. All statistical
analyses were performed using SAS/STAT
®
(Version 8, SAS Institute Inc.). Assumptions of the
statistical model were evaluated.

7
RESULTS

Study Participants
Sixty participants previously randomly selected were included in analyses of
histomorphometric parameters. A subset of forty-five participants had undergone HR-pQCT
imaging of the distal radius and tibia and were included in imaging analyses. The study
participants ranged from 29 to 88 years of age with a mean of 61 years and median of 62.5
years, of which 40% were male, 13% were on hemodialysis, and 88% had CKD stage 3 or
higher. For subjects who underwent HR-pQCT imaging, age ranged from 43 to 88 years of age
with a mean of 62.3 years and median of 62 years, of which 45% were male, 13% were on
hemodialysis, and 95% had CKD stage 3 or higher (Table 1). There were no significant
associations between blood SCFA levels and CKD stage.

Histology
Correlations between dynamic and static measures of histomorphometry, PTH and
SCFAs were assessed. Bivariate analysis demonstrated a positive correlation between osteoid
thickness and propionic acid (𝑟
"
=0.316, p=0.014). PTH was positively correlated with
mineralizing surface/bone surface (𝑟
"
=0.515, p=<0.001), osteoid surface/bone surface (𝑟
"

=0.462, p=0.026), BFR (𝑟
"
=0.425, p=<0.001), AjAR (𝑟
"
=0.459, p=<0.001) and negatively
correlated with MLT (𝑟
"
=-0.420, p=<0.001). Propionic acid was positively correlated with OMT
(𝑟
"
=0.534, p=<0.001). Acetic acid and butyric acid did not have any statistically significant
correlation with any bone parameters.

In our final linear regression model with osteoid thickness as our outcome, the
interaction between PTH and propionic acid was clinically meaningful and statistically significant
(β = 3.31, SE 1.58, p = 0.041), suggesting that propionic acid is an effect modifier between PTH
8
and osteoid thickness (Table2; Figure1). Thus, those with high levels of both PTH and propionic
acid levels had thicker osteoid compared to those with high PTH and low propionic acid. There
were no statistically significant or clinically meaningful associations between propionic acid and
the bone histomorphometry measures of MAR, BFR or bone volume. There were no clinically or
statistically significant associations between histomorphometry measures for either acetic acid
or butyric acid. All models were viewed graphically to assess for clinical significance. Clinical
significance was determined based on slope differences between high and low SCFA groups.
Post-hoc power analysis showed that the study had 44% power.

Imaging
For HR-pQCT, we used general linear regression models to evaluate relationships
between Ct and Tb volumetric density, geometry and microarchitecture at the radius and tibia,
and PTH with SCFAs. No statistically significant associations were found with acetic acid or
butyric acid models. All models were viewed graphically to assess for clinical significance.
Clinical significance was determined based on slope differences between high and low SCFA
groups. Models including propionic acid showed the following results. Post-hoc power analysis
for all variables was less than 50%.

Radius
At the radius, bivariate analysis demonstrated no statistically significant correlation
between PTH, acetic acid, butyric acid, propionic acid, Ct or Tb vBMD, Ct or Tb area or Ct
thickness.

As with osteoid thickness, there was a statistically significant interaction between PTH
and propionic acid seen for cortical thickness (β=0.12, SE 0.05, p=0.01) and area (β=12.50, SE
3.43, p=0.001) and trabecular volumetric density (β=26.59, SE 11.28, p=0.024) in our linear
9
regression model suggesting that propionic acid acts as an effect modifier between PTH and
cortical thickness and trabecular vBMD at the radius. Thus, those with high levels of both PTH
and propionic acid levels had increased cortical thickness and trabecular vBMD compared to
those with high PTH and low propionic acid at the radius (Table3; Figure 2). There were no
statistically significant relationships between propionic acid and radius Ct vBMD or Tb area.

Tibia
At the tibia, there was a statistically significant negative correlation between PTH and Tb
vBMD (𝑟
"
=-0.315, p=0.035) and positive correlation between propionic acid and Tb area
(𝑟
"
=0.337, p=0.024). There were no statistically significant correlations between acetic acid or
butyric acid with Ct or Tb vBMD, Ct or Tb area or Ct thickness.

In our linear regression model, there was a statistically significant interaction between
propionic acid and PTH seen for the cortical area (β=24.46, SE 8.34, p=0.006), suggesting that
propionic acid acts as an effect modifier between PTH and cortical area. Thus, those with high
levels of both PTH and propionic acid levels had increased cortical area compared to those with
high PTH and low propionic acid at the tibia (Table4; Figure2). There were no statistically
significant relationships between propionic acid and tibia Ct thickness, Ct vBMD, Tb area or Tb
vBMD.

10
DISCUSSION

In this study, we analyzed bone homeostasis with bone histomorphometry and HR-
pQCT imaging, to evaluate the associations between serum SCFAs, specifically propionic acid,
butyric acid, and acetic acid, and PTH, on bone quality among sixty adult participants with CKD.
We observed that propionic acid modifies the skeletal response to PTH in this population.
Higher PTH concentrations were associated with anabolic effects on bone quality at the tissue
and microarchitectural levels in the setting of higher propionic concentrations. In contrast, higher
PTH concentrations were associated with catabolic effects on bone quality in the setting of
lower propionic concentrations.

This study involves a heterogenous population of adult patients with CKD with varying
ages and severity of kidney disease, including patients on dialysis and with diabetes. These
demographical characteristics increase the generalizability of these results to the diverse CKD
adult patient population in the United States. This study is also unique in looking at both bone
histomorphometry and imaging data. Bone biopsies are invasive procedures, limiting their ability
to be used as a marker of adequate treatment. Despite its radiation exposure, HR-pQCT is not
invasive and may allow for more frequent evaluation of bone quality in order to better guide
treatment. HR-pQCT also allows for the analysis of both the radius versus tibia and cortical
bone versus trabecular bone, which is not possible with bone biopsies. Analysis of the radius
versus the tibia compares non-weight bearing versus weight-bearing bones. In contrast, bone
biopsies sample the iliac crest, which is weight-bearing and mostly trabecular. Overall, the data
demonstrates that propionic acid modifies the relationship of PTH on bone parameters in both
histomorphometry and imaging analysis.

11
Some limitations of the study include limited racial and ethnic diversity, small sample
size, and lack of standardization for the timing of when the blood samples were obtained. With a
larger sample size, other bone parameters analyzed during this study may have shown
statistical significance due to having increased power or at least a clinical significance with an
increase in effect size. In addition, previous studies have shown that SCFAs fluctuate
throughout the day with meals.
14
Since we did not standardize the time of blood sample
collection in relation to eating, it is unknown how this would have affected our results. In future
studies for all participants, complete diet histories and specimens (e.g., blood and stool) should
be obtained using a prespecified protocol for all participants.

Environmental factors can significantly change the gut microbiome composition, which is
known to be true for those with kidney disease. When alterations lead to an imbalance in the gut
microbiome, it is known as dysbiosis. Dysbiosis is associated with many systemic diseases,
including but not limited to obesity, inflammatory bowel disease and Parkinson’s disease.
15-19

Dysbiosis in patients with kidney disease is multifactorial, including influences of dietary
changes, uremia, and medications.
7,20,21
Uremia plays a significant role in altering the organisms
in the gut. When urea enters the gut, it is converted to ammonia by urease-producing bacteria
which increases the pH and causes mucosal damage and inflammation. This disruption leads to
increased growth of urease-producing bacteria as well as those that produce the uremic toxins
p-cresly sulfate and indoxyl sulfate.
16,21
In addition to the increased inflammation, the expansion
of these organisms can result in a decrease in SCFA-producing organisms.
5,22,23

The gut microbiome production of SCFAs has been found to be critical for the regulatory
pathways needed for both catabolic and anabolic action of PTH on bone.
8,10
SCFAs have not
only been found to be both absorbed from the gastrointestinal tract and cause distal host organ
changes, but also facilitate immune-mediated changes directly in the gastrointestinal system.
12
More specifically, regulatory T cell (Treg) expansion due to SCFAs contributes to immune
tolerance and symbiosis between host and microbiota.
24
Previous studies have shown that
supplementation with lactobacillus and fiber can alter the gut flora. Since production of SCFAs
varies based on gut microbiome composition and diet, it may be an integral part of future
treatment of bone disease.
7,20

Ultimately, this study showed that the SCFA, propionic acid, produced by the anaerobic
gut microbiota modifies the effect PTH has on osteoid thickness, Tb radius vBMD, Ct radius and
tibia area, and Ct radius thickness in adult patients with CKD. The modifying effect that SCFAs,
particularly, propionic acid, have on PTH and bone may significantly affect future treatment
guidelines and should be further investigated. We suggest that depletion of SCFAs in patients
with CKD occurs secondary to environmental changes and dysbiosis and may in part explain
abnormal bone mineralization and renal osteodystrophy despite PTH levels being in target
range. Future studies of supplementation with lactobacillus, SCFAs, or fiber in patients with
CKD are needed to determine future treatment possibilities.

13
FUNDING

Elizabeth Kermgard, MD., was partially funded by the American Kidney Fund through the
Clinical Nephrology Scientist program from 7/2021-6/2023

14
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16
TABLES
Table 1: Histomorphometry Descriptive Statistics (n = 60)
n % Mean SD Median Q1 Q3
Parathyroid hormone (ng/L) 160.0 (186.4) 83.4 [45.0, 195.6]
Propionic acid (ng/mL) 230.2 (80.2) 238.2 [178.7, 280.0]
Butyric acid (ng/mL) 80.7 (25.7) 77.7 [62.8, 95.4]
Acetic acid (ng/mL) 2680.8 (1417.6) 2298.0 [1645.5, 3640.8]
Age (years) 61.1 (12.7) 62.5 [53.2, 68.4]
eGFR (mL/min/1.73m2)
Osteoid thickness (µm)
30.0
11.5
(21.2)
(6.3)
30.2
9.6
[11.5,
[6.3,
47.5]
16.3]

Chronic kidney disease stage
1 1 1.7%
2 5 8.3%
3 24 40.0%
4 10 16.7%
5 12 20.0%
5D 8 13.3%
Race
White 31 51.7%
Black/African American 13 21.7%
Asian 2 3.3%
Other 14 23.3%
Sex
Male 24 40.0%
Female 36 60.0%
Hemodialysis
No 52 86.7%
Yes 8 13.3%

HR-pQCT Descriptive Statistics (n = 45)
n % Mean SD Median Q1 Q3
Parathyroid hormone (ng/L) 180.1 (208.8) 80.8 [40.8, 279.5]
Propionic acid (ng/mL) 237.8 (72.2) 235.4 [196.3, 279.8]
Butyric acid (ng/mL) 85.0 (25.4) 81.0 [65.9, 104.2]
Acetic acid (ng/mL) 2680.4 (1391.2) 2298.0 [1698.8, 3680.5]
Age (years) 62.3 (11.9) 62.0 [54.8, 68.9]
eGFR (mL/min/1.73m2)
Radius

30.0 (21.2) 30.2 [11.5, 47.5]
Ct vBMD (mgHA/cm3)
Ct thickness (mm)
Ct area (mm2)
Tb vBMD (mgHA/cm3)
Tb area (mm2)
Tibia
Ct vBMD (mgHA/cm3)
Ct thickness (mm)
Ct area (mm2)
Tb vBMD (mgHA/cm3)
Tb area (mm2)

844.8
0.86
58.7
146.8
245.5

795.5
1.22
123.3
153.8
654.1

(62.2)
(0.17)
(15.8)
(43.5)
(66.7)

(91.7)
(0.28)
(37.6)
(43.8)
(142.1)

852.0
0.88
58.0
142.2
243.1

818.1
1.25
114.7
152.6
654.7

[805.8,
[0.75,
[47.9,
[124.2,
[200.6,

[759.7,
[1.04,
[95.4,
[139.3,
[586.9,

875.9]
0.96]
68.7]
177.9]
294.2]

853.0]
1.44]
149.5]
176.4]
755.5]

17
CKD stage
1 0 0%
2 2 4.5%
3 15 33.3%
4 10 22.2%
5 12 26.7%
5D 6 13.3%
Race
White 22 48.9%
Black/African American 12 26.7%
Asian 1 2.2%
Other 10 22.2%
Sex
Male 20 45.5%
Female 25 55.6%
Hemodialysis
No 39 86.7%
Yes 6 13.3%

Table 2. Histomorphometry Generalized Linear Regression Osteoid Thickness
Osteoid Thickness β Coef.
SE t-value p-value
Intercept 20.50 12.46 1.65 0.11
Propionic acid -11.60 8.32 -1.39 0.17
Log(iPTH) -3.32 2.30 -1.44 0.15
Sex -0.36 5.29 0.07 0.95
Propionic acid *Log(iPTH) 3.31 1.58 2.09 0.04
†

Propionic acid*Sex 0.13 3.24 0.04 0.97
†p-value < 0.05
††
p-value < 0.01

Table 3. Radius HR-pQCT Generalized Linear Regression

β Coef.
SE t-value p-value
Cortical vBMD

Intercept 1213.49 149.82 8.10 <0.0001
††

Propionic acid -214.27 98.07 -2.18 0.04
†

Log(iPTH) -52.66 26.07 -2.02 0.05
†

Sex -72.34 63.77 -1.13 0.26
Propionic acid *Log(iPTH) 31.94 17.51 1.82 0.08
Propionic acid*Sex 35.55 39.07 0.91 0.37

Cortical Area
18
Intercept 126.79 29.33 4.32 0.0001
††

Propionic acid -63.48 19.20 -3.31 0.002
††

Log(iPTH) -18.25 5.11 -3.58 0.001
††

Sex 12.19 12.49 0.98 0.33
Propionic acid *Log(iPTH) 12.50 3.43 3.65 0.0008
††

Propionic acid*Sex 3.29 7.65 0.43 0.67

Cortical Thickness
Intercept 1.73 0.40 4.38 <0.0001
††

Propionic acid -0.64 0.26 -2.49 0.02
†

Log(iPTH) -0.19 0.07 -2.70 0.01
††

Sex 0.05 0.17 0.30 0.76
Propionic acid *Log(iPTH) 0.12 0.05 2.68 0.01
††

Propionic acid*Sex 0.01 0.10 0.09 0.93

Trabecular vBMD
Intercept 345.33 96.49 3.58 0.001
††

Propionic acid -132.36 63.16 -2.10 0.04
†

Log(iPTH) -47.83 16.79 -2.85 0.007
††

Sex 9.63 41.07 0.23 0.82
Propionic acid *Log(iPTH) 26.59 11.28 2.36 0.02
†

Propionic acid*Sex 10.37 25.16 0.41 0.68
Trabecular Area
Intercept 103.87 125.49 0.83 0.41
Propionic acid -21.17 82.14 -0.26 0.80
Log(iPTH) -3.30 21.84 -0.15 0.88
Sex 115.93 53.41 2.17 0.04
†

Propionic acid *Log(iPTH) 8.31 14.67 0.57 0.57

Propionic acid*Sex -16.17 32.72 -0.49 0.62

†p-value < 0.05
††
p-value < 0.01

19
Table 4. Tibia HR-pQCT Generalized Linear Regression

β Coef.
SE t-value p-value
Cortical vBMD

Intercept 971.73 233.06 4.17 0.0002
††

Propionic acid -123.50 152.55 -0.81 0.42

Log(iPTH) -36.91 40.56 -0.91 0.37

Sex -3.59 99.20 -0.04 0.97
Propionic acid *Log(iPTH) 19.43 27.24 0.71
0.48
Propionic acid*Sex 22.45 60.77 0.37 0.71

Cortical Area
Intercept 200.26 71.33 2.1 0.01
††

Propionic acid -103.84 46.69 -2.22 0.03
†

Log(iPTH) -32.17 12.41 -2.59 0.01
††

Sex 42.73 30.36 1.41 0.16
Propionic acid *Log(iPTH) 24.46 8.34 2.93 0.01
††

Propionic acid*Sex -1.55 18.60 -0.08 0.94

Cortical Thickness
Intercept 1.12 0.65 1.72 0.09
Propionic acid -0.28 0.43 -0.67 0.51

Log(iPTH) -0.09 0.11 -0.80 0.43

Sex 0.34 0.28 1.22 0.23
Propionic acid *Log(iPTH) 0.09 0.08 1.22
0.23
Propionic acid*Sex -0.08 -0.17 -0.47 0.64

Trabecular vBMD
Intercept 305.54 104.00 2.94 0.01
††

Propionic acid -69.32 68.07 -1.02 0.31

Log(iPTH) -37.95 18.10 -2.10 0.04
†

Sex 4.56 44.27 0.10 0.92
Propionic acid *Log(iPTH) 17.51 12.15 1.44 0.16

Propionic acid*Sex 0.01 27.12 0.00 1.00

20
Trabecular Area
Intercept 925.71 335.10 2.76 0.01
††

Propionic acid -271.37 219.34 -1.24
0.22
Log(iPTH) -93.79 58.32 -1.61
0.12
Sex 155.64 142.64 1.09 0.28
Propionic acid *Log(iPTH) 60.05 39.16 1.53 0.13

Propionic acid*Sex -31.38 87.38 -0.36 0.72

†p-value < 0.05
††
p-value < 0.01

21
FIGURES

Figure 1: Association of Log(iPTH) and Osteoid thickness separated by high and low propionic
acid. Blue is the combined total data slope, red is the slope of the below median propionic acid
group and green is the above median propionic acid group. Graphical representation of the
inverse relationship of propionic acid acting as an effect modifier on the relationship between
Log(iPTH) and osteoid thickness. P-value is for the Log(iPTH) and propionic acid interaction
term.
22
Figure 2: Associations of Log(iPTH) and HR-pQCT imaging data separated by high and low
propionic acid. Blue is the combined total data slope, red is the slope of the below median
propionic acid group and green is the above median propionic acid group. Graphical
representation of the inverse relationship of propionic acid acting as an effect modifier on the
relationship between Log(iPTH) and multiple bone parameters showing the inverse relationship.
P-value is for the Log(iPTH) and propionic acid interaction term.

Abstract (if available)

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Asset Metadata

Creator Kermgard, Elizabeth Mary (author)

Core Title A cross-sectional study of the association of PTH on bone quality across levels of propionic acid among adult patients with uremia

School Keck School of Medicine

Degree Master of Science

Degree Program Clinical, Biomedical and Translational Investigations

Degree Conferral Date 2023-08

Publication Date 08/21/2023

Defense Date 08/20/2023

Publisher Los Angeles, California (original), University of Southern California (original), University of Southern California. Libraries (digital)

Tag bone and mineral disease,CKD-MBD,kidney disease,microbiome,OAI-PMH Harvest,parathyroid hormone,propionic acid,PTH,short-chain fatty acids

Format theses (aat)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Patino-Sutton, Cecilia (committee chair), Khouzam, Nadine (committee member), Lemley, Kevin (committee member), Wesseling-Perry, Katherine (committee member)

Creator Email ekermgard@gmail.com,kermgard@usc.edu

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