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University of Tennessee Health Science Center University of Tennessee Health Science Center
UTHSC Digital Commons UTHSC Digital Commons
Theses and Dissertations (ETD) College of Graduate Health Sciences
8-2015
Adverse Effects of Asparaginase in Pediatric Patients with Acute Adverse Effects of Asparaginase in Pediatric Patients with Acute
Lymphoblastic Leukemia Lymphoblastic Leukemia
Chengcheng Liu University of Tennessee Health Science Center
Follow this and additional works at: https://dc.uthsc.edu/dissertations
Part of the Diseases Commons, Medical Sciences Commons, and the Therapeutics Commons
Recommended Citation Recommended Citation Liu, Chengcheng , "Adverse Effects of Asparaginase in Pediatric Patients with Acute Lymphoblastic Leukemia" (2015). Theses and Dissertations (ETD). Paper 157. http://dx.doi.org/10.21007/etd.cghs.2015.0185.
This Dissertation is brought to you for free and open access by the College of Graduate Health Sciences at UTHSC Digital Commons. It has been accepted for inclusion in Theses and Dissertations (ETD) by an authorized administrator of UTHSC Digital Commons. For more information, please contact [email protected].
Adverse Effects of Asparaginase in Pediatric Patients with Acute Lymphoblastic Adverse Effects of Asparaginase in Pediatric Patients with Acute Lymphoblastic Leukemia Leukemia
Abstract Abstract Acute lymphoblastic leukemia (ALL) is the most common type of childhood cancer. Asparaginase is a critical treatment component for ALL. However, its use is complicated by adverse effects, such as hypersensitivity, osteonecrosis and pancreatitis.
Hypersensitivity to asparaginase typically requires discontinuation of current formulation and substitution with other formulations, but the differential diagnosis can be challenging, and the diagnostic utility of antibody tests is unclear. We comprehensively analyzed anti-Elspar (native E.coli asparaginase) IgG antibodies in 410 pediatric patients treated on an asparaginaseintensive front-line clinical trial. Of 169 patients (41.2%) who exhibited clinical allergy, 147 (87.0%) were positive for anti-Elspar antibody. Of 241 patients without clinical allergy, 89 (36.9%) had detectable antibody. Among those positive for antibody, the antibody titers were higher in those who developed allergy than in those who did not (P < 1.0 × 10-15). Antibody measures at week 7 of continuation therapy had a sensitivity of 87%-88% and a specificity of 68%-69% for predicting or confirming clinical reactions. Antibodies were inversely associated with serum asparaginase activity (P = 7.0 × 10-6 ). Interestingly, high antibodies were associated with a lower risk of osteonecrosis (odds ratio = 0.83; 95% confidence interval, 0.78-0.89; P = 0.007), which is a dose-limiting adverse effect of glucocorticoids but has also been linked to asparaginase treatment. We conclude that antibodies were related to clinical allergy and to low systemic exposure to asparaginase, leading to lower risk of other adverse effects of therapy. Measures of serum antibodies to asparaginase can be useful in patients with ALL.
Osteonecrosis is a common dose-limiting toxicity of glucocorticoids. Data from clinical trials suggest that other medications can increase the risk of glucocorticoid-induced osteonecrosis. Here we utilized a mouse model to study the effect of asparaginase treatment on dexamethasone-induced osteonecrosis. After 6 weeks of treatment, mice receiving asparaginase along with dexamethasone had a higher rate of osteonecrosis than those receiving only dexamethasone (44% vs. 10%, P = 0.006). Primary epiphyseal arteriopathy, an initiating event for osteonecrosis, was observed in 58% of mice receiving asparaginase and dexamethasone compared to 17% of mice receiving dexamethasone only (P = 0.007). As in the clinic, greater exposure to asparaginase was associated with greater plasma exposure to dexamethasone (P = 0.0001). This model also recapitulated other clinical risk factors for osteonecrosis, including age at start of treatment, and association with the systemic exposure to dexamethasone (P = 0.027) and asparaginase (P = 0.036). We conclude that asparaginase can potentiate the osteonecrotic effect of glucocorticoids.
Acute pancreatitis is a serious complication of asparaginase with no definitive treatment. Risk factors for asparaginase-induced pancreatitis, especially the genetic predisposition, have not been clearly identified. We studied 5398 pediatric patients with ALL and showed that older age, higher exposure to asparaginase, higher Native American ancestry or African ancestry were independent clinical risk factors for pancreatitis. To determine genetic risk factors, we performed a genome-wide association study. A rare nonsense variant rs199695765 in CPA2, a pancreatic enzyme, was highly associated with pancreatitis (odds ratio = 588, 95% confidence interval 66.8- 5166, P = 9.0 ×10-9 ). A gene-level analysis showed an excess of additional CPA2 variants in those who did versus did not develop pancreatitis (P = 0.018). Furthermore, common variants in genes critical to purine metabolism and cytoskeleton function were also associated with development of pancreatitis. Our findings are consistent with a mixed genetic architecture underlying serious adverse drug effects, wherein a combination of rare but highly penetrant and common but weakly penetrant genetic risk factors contribute to genetic risk. For the patients carrying the highly penetrant variants, consideration should be given to treatment with a nonasparaginase
containing ALL chemotherapy regimens.
Overall, we studied the major adverse effects of asparaginase in patients treated for ALL. These findings will provide important guidance for precision medicine.
Document Type Document Type Dissertation
Degree Name Degree Name Doctor of Philosophy (PhD)
Program Program Biomedical Sciences
Research Advisor Research Advisor Mary V. Relling, Pharm.D.
Keywords Keywords Acute lymphoblastic leukemia Asparaginase, GWAS, Hypersensitivity, Osteonecrosis, Pancreatitis
Subject Categories Subject Categories Diseases | Medical Sciences | Medicine and Health Sciences | Therapeutics
This dissertation is available at UTHSC Digital Commons: https://dc.uthsc.edu/dissertations/157
ADVERSE EFFECTS OF ASPARAGINASE IN PEDIATRIC PATIENTS WITH ACUTE LYMPHOBLASTIC LEUKEMIA
DEDICATION
This work is dedicated to my parents Haiying Liu Hua Cheng
and my husband Hao Wu
Thank you for all of your love and support along the way.
ACKNOWLEDGEMENTS
ABSTRACT
E.coli
P
PP
P
PP
P P
CPA2P
CPA2P
TABLE OF CONTENTS
CHAPTER 1. BACKGROUND ........................................................................................1
E.coli
Erwinia
CHAPTER 2. ASPARAGINASE HYPERSENSITIVITY ...........................................10
Ex vivo
CHAPTER 3. POTENTIATING EFFECT OF ASPARAGINASE ONGLUCOCORTICOID-INDUCED OSTEONECROSIS ..............................................38
CHAPTER 4. ASPARAGINASE-INDUCED ACUTE PANCREATITIS .................51
CPA2
CPA2
CHAPTER 5. SUMMARY ..............................................................................................82
LIST OF REFERENCES ................................................................................................83
APPENDIX A. SUPPLEMENTARY INFORMATION FOR CHAPTER 2 .............97
APPENDIX B. SUPPLEMENTARY INFORMATION FOR CHAPTER 3 ...........111
APPENDIX C. SUPPLEMENTARY INFORMATION FOR CHAPTER 4 ...........139
VITA................................................................................................................................171
LIST OF TABLES
CPA2
P
P
LIST OF FIGURES
Ex vivo
P
LIST OF ABBREVIATIONS
CHAPTER 1. BACKGROUND
Acute Lymphoblastic Leukemia (ALL)
BCR ABL1
Asparaginase
Introduction
Escherichia coli
E.coli
E.coli- Erwinia chrysanthemi
Formulations
E.coli E.coli Erwinia
chrysanthemi
Native E.coli asparaginase
E.coli
E.coli
E.coli
E.coli
PEG-asparaginase
E.coli
E.coli E.coli
E.coli
Erwinia asparaginase
ErwiniaE.coli
Erwinia
E.coli Erwinia E.coli
ErwiniaErwinia
Erwinia
Adverse effects
Hypersensitivity
E.coli
E. coli Erwinia
E.coli
E.coli
Acute pancreatitis
PRSS1 and PRSS2SPINK1
CFTR
CTRC CASR CLDN2CPA1 HLA-DRB1
Drug interaction with glucocorticoids
Effect on glucocorticoid-induced osteonecrosis
Figure 1-1
Figure 1-1. Proposed mechanisms of glucocorticoid-induced osteonecrosis
Pharmacogenomics: A Brief Introduction
Cohort study
Case-control study
Candidate-gene approach
TPMTTPMT
TPMTa priori
GWAS
CHAPTER 2. ASPARAGINASE HYPERSENSITIVITY*
Introduction
Methods
Patients
Table 2 1
Asparaginase regimen and sample collection
Leukemia.
Table 2-1. Clinical features of patients with (n = 410) and without (n = 88) samples evaluable for anti-asparaginase antibodies
Clinical features Patients with samplesn (%)
Patients without samplesn (%)
P
Figure 2 1
Erwinia
Phenotyping of clinical allergy to asparaginase
Anti-asparaginase antibodies
Antibody assay
Table 2 2
Appendix A Table A 1Figures A 1 A 3
Figure 2-1. Total XV asparaginase regimen and anti-asparaginase antibody measurements
Table 2-2. Number of patients with evaluable blood samples at each time point
Time point of antibody test Number of patients (samples)
Day 5 19 34 Week 7 Week 17
Induction Consolidation Continuation (Reinduction I) (Reinduction II)
10000 U/m2
Weeks 1 4 7 1 4 7 1 4 7 10 14 17 20 47
10000 U/m2
25000 U/m210000 U/m2
ASP (LR)
( )( )
ANTI-ASP
ASP (SHR)
Induction AUC Continuation AUCANTI-ASPAUC
Data analysis
Equation 2 1 Equation 2 2Equation 2 3
Appendix A
(Eq. 2 1)
(Eq. 2 2)
(Eq. 2 3)
Estimation of antibody area-under-the-curve (AUC)
Figure 2 1
Figure A 4
Asparaginase activity
Figure 2-2
Figure 2-2. Enzyme reactions in asparaginase activity assay
E. coli
Ex vivo asparaginase neutralization assay
ex vivo
Prognostic value of antibody tests
Sensitivity, specificity and predictive values
Receiver-operator-characteristic (ROC) curves
Asparaginase adverse effects in Total XV
Statistical analysis
rpart
Results
Asparaginase allergy
P =
P = Figure 2-3
Table 2-3
Table 2-4 Table 2-5P = P
=
P =
P = P =
P =
Antibodies and allergy
P
P = P = P
(P
Figure 2-4
P =
P =
Figure 2-3. Frequency of hypersensitivity to Elspar
PP =
Table 2-3. Timing of allergic reaction to Elspar
Phase Low-risk(n = 100)
Standard/high-risk(n = 69)
Total(n = 169)
Table 2-4. Clinical features and allergic reactions to Elspar
All patients (n = 410) Low-risk arm (n = 197) Standard/high-risk arm (n = 213)
Clinicalfeatures
n Allergyn (%)
No allergyn (%)
P n Allergyn (%)
No allergyn (%)
P n Allergyn (%)
No allergyn (%)
P
Table 2-5. Clinical features and anti-Elspar antibody status
All patients (n = 410) Low-risk arm (n = 197) Standard/high-risk arm (n = 213)
Clinicalfeatures
n Positiven (%)
Negativen (%)
P n Positiven (%)
Negativen (%)
P n Positiven (%)
Negativen (%)
P
Figure 2-4. Antibody levels in patients with and without clinical reactions
P = P =
Figure 2-5
Table 2-6
Table A-2 Figure A-5
Figure 2-6
Figure 2-6
P = P = Figure 2-7
Figure 2-4
P = Figure A-6
Figure 2-8
Figure 2-5. Anti-Elspar antibody level relative to the time of clinical reaction to Elspar
Table 2-6. Sensitivity, specificity and predictive values of three anti-Elspar antibody tests for predicting or confirming clinical reactions to Elspar
Risk arm N of patients
Time of Ab test
Time of Rxn
Time between test and rxn
(weeks)
Sensitivity(%)
Specificity(%)
PPV(%)
NPV(%)
Figure 2-6. ROC curves of the antibody tests
Figure 2-7. Association between week 7 anti-Elspar antibody level and the proportion of patients reacting to Elspar around week 7
Figure 2-8. The frequency of hypersensitivity to Oncaspar and Erwinase
Antibodies and serum asparaginase activity
in vivo
P = P = Figure 2–9
in vivo
P =
P =
exvivo Figure 2–10
= P = Figure 2–10A
= P = Figure 2–10B
Antibodies and adverse effects
P = Table 2–7
Figure 2–11
P= P = P =
P = Figure 2–11
Figure 2-9. Correlation between serum asparaginase activity and antibody level
Figure 2-10. Ex vivo neutralization of patient sera with antibodies
Table 2-7. Multivariate analysis showed that low anti-Elspar antibody area-under-curve (AUC) was a risk factor of osteonecrosis (n = 360)
Patient characteristics P Hazard ratio (95% CI)
Figure 2-11. Cumulative incidence of osteonecrosis based on anti-asparaginase antibody AUC
P PP =
P = P =
Discussion
Table 2-6
Figure A-7
Figure 2-7
Figures 2-6 and A-5
Figure 2-9ex vivo
Figure2-10
Figure 2-9
Figure2-11
Figure 2-11D
Table 2-7
P =
P = P =
Conclusion
CHAPTER 3. POTENTIATING EFFECT OF ASPARAGINASE ON GLUCOCORTICOID-INDUCED OSTEONECROSIS
Introduction
Methods
Chemicals
Animals
Appendix B Table B-1 Figure B-1
Asparaginase and dexamethasone pharmacokinetics
Figure 3-1
Figure 3-2 Appendix B
Mouse model of dexamethasone-induced osteonecrosis
Appendix B Tables B-1 B-2 Figures B-1 B-7
Figure 3-1. Dexamethasone and asparaginase treatment regimens
Effect of asparaginase on osteonecrosis
Figure 3-1
Plasma dexamethasone concentration and asparaginase activity
Appendix B
Histological evaluation of osteonecrosis and arteriopathy
Statistical analysis
Results
Plasma dexamethasone concentration was increased by asparaginase treatment
Figure 3-1
P =
P = Figure 3-2
Asparaginase treatment potentiated osteonecrosis and arteriopathy in dexamethasone-treated mice
Figure 3-1
P
P =
P = Figure 3-3
P =
P = Appendix B Figure B-8
P = P = Figure 3-4
Figure 3-2. Plasma dexamethasone concentration was positively associated with asparaginase activity in PK experiment
Figure 3-3. Asparaginase treatment potentiated osteonecrosis and arteriopathy in dexamethasone-treated mice
Figure 3-4. Osteonecrosis was associated with higher plasma dexamethasone and asparaginase levels in mice receiving both dexamethasone and asparaginasetreatment
P P
Arteriopathy was likely the initiating event of osteonecrosis
P =
Figure 3-5Figure 3-5D
Figure 3-5E
Figure 3-5F
Figure 3-5IFigure 3-5G
Discussion
Figure 3-2 Figure B-8
P = P =
P = P = Figure 3-4 P = P =
Figure 3-5. Histology of osteonecrosis and arteriopathy
E.coli
Appendix B
Figure B-9Figure B-10
Figure B-11Figure B-12
P Figure B-13
Table B-3P <
Figure B-14
Conclusion
CHAPTER 4. ASPARAGINASE-INDUCED ACUTE PANCREATITIS
Introduction
PRSS1 and PRSS2 SPINK1CFTR
CTRC CASR CLDN2CPA1 HLA-DRB1
Methods
Patients and treatment
Table 4-1 Figure 4-1
Table 4-1. Comparison of asparaginase regimens
Protocol Induction Consolidation Interim Maintenance (IM) and Delayed
Intensification (DI)
Maintenance Total ASP doseb
(U/m2)
Total ASP
weeksc
N (%) of patients
developingpancreatitis
E. coli E. coli
E. coli E. coli
E. coli
E. coli
E. coli E. coli E. coli
Table 4-1. (Continued)
Protocol Induction Consolidation Interim Maintenance (IM) and Delayed
Intensification (DI)
Maintenance Total ASP doseb
(U/m2)
TotalASP
weeksc
N (%) of patients
developing pancreatitis
E.coli
E.coli E.coli E.coli E.coli E.coli
Figure 4-1. Study design
P
Table 4-2
Diagnosis of acute pancreatitis
Genotyping
Figure 4-1
Figure 4-1
Table 4-5 Figure C-1
Figure 4-2
Table 4-2. Number of patients included in this study
Study Protocol N ofpatients
N (%) with array dataa
N (%) with deep sequencing datab
Figure 4-2. Race group assignments based on the ancestral composition of patients in the cohort (n = 5185) by treatment protocol
SNP-based analysis for pancreatitis
P
Gene-level analysis of nonsense variants using SKAT
Deep sequencing of selected genes
Table 4-2
Table 4-3Appendix C
Appendix C
Table 4-3. Putative genes associated with pancreatitis (n = 42) selected for deep sequencing based on GWAS result or literature review
Gene Official full name Function* SourceADAMTS18
AGER
ALS2CL
C11orf63
C12orf40
C9orf117
CASR
CD52CFTR
CLDN2
CPA1
Table 4 3. (Continued)
Gene Official full name Function* SourceCPA2
CTRC
DDX49
DOCK5
FHIT
GCKR
HOGA1
HSD17B2
IFNA5INMT
ITFG1
KLHDC1 HCFC2
Table 4 3. (Continued)
Gene Official full name Function* SourceLRRC39 LRSAM1
MICAL2
MPZL3NMI
PHKB
PRSS1
PRSS2
RANBP10
RUFY4 FYCO1
Table 4 3. (Continued)
Gene Official full name Function* SourceSCAMP3
SERPINA9
SLC6A18
SNTG2
SPAG8
SPINK1
TRAP1
ZNF233
ZNF701
ZRANB3
Statistical analysis
ctree party
Results
Pancreatitis associated with asparaginase
Figure 4-3A
Figure 4-3AFigure 4-4
P = = P = Figure
4-3B CP =
Clinical risk factors
Figure 4-5P =
P =
Table 4-1
Figure 4-3. Incidence of pancreatitis differed by protocols
E. coli
E. coli
Figure 4-4. Time of pancreatitis in the cohort (n = 5185) during the first year of therapy
Figure 4-5. The incidence of pancreatitis based on clinical characteristics *
P = Table 4-4
Figure 4-6Table 4-1
E.coli
Figure 4-7
P =
P =
Gene-level analysis of nonsense variants identified CPA2
PTable 4-5 CPA2
P = Figure 4-8A
Figure 4-8B
GWAS of common SNPs
FHIT P = P =
DOCK5 ACTN2 MICAL2 Table4-6
P
Appendix C Tables C-1, C-2 C-3
Table 4-4. Multivariate analysis for clinical risk of pancreatitis in the cohort study (n = 5185)
Patient characteristics P Odds ratio (95% CI)
§
E.coli
§ E.coli
Figure 4-6. Association between Native American ancestry and pancreatitis
Figure 4-7. CART analysis of clinical risk factors for pancreatitis in the cohort (n = 5185)
Table 4-5. Six genes associated with pancreatitis from the gene-level analysis of nonsense SNPs
Cohort (n = 3256) Case-control (n = 213)Gene Chr Nonsense
SNPs(major
allele/risk allele)
Population RAF%
(n)a
CADDscore
RAF% in
patients with AP(n = 95)
RAF% in patients without
AP(n = 3161)
Coeff-icientc
(SE)
Pc RAF% in
cases(n =71)
RAF% in
controls(n =142)
Coeff-icientd
(SE)
Pd PPV/NPVe
(n = 3256)
CPA2
SERPINA9
HSD17B2
GCKR
ZNF233
SLC6A18
Table 4-5. (Continued)
Figure 4-8. Nonsense SNP rs199695765 in CPA2 associated with pancreatitis
CPA2
P =
Table 4-6. Top 20 common SNPs (cohort risk allele frequency > 1%) significantly associated with pancreatitis in the cohort
Cohort(n = 5185)
Case-control(n = 213)
Cohort RAF vs race(n = 5185)
SNP Gene Chr Location Major allele/risk
allele
RAF% in patients with AP(n = 117)
RAF% in patients
without AP(n = 5068)
Coeff-icientb
(SE)
P RAF% in cases(n = 71)
RAF% in controls(n = 142)
Coeff-icientc
(SE)
P Hispanic Black
(n = 1527)
White Asian
(n = 3168)
FHIT
DOCK5
ACTN2
ITFG1
AGPAT4
FHIT
ITFG1
MICAL2
AGPAT4
MICAL2
ACTN2
PHKB
DOCK5
MICAL2
Table 4-6. (Continued)
P
Deep sequencing detected novel variants in CPA2 and other candidate genes
apriori
PRSS1 PRSS2SPINK1 CFTR CASR CTRC CPA1 CLDN2 Table 4-3
CPA2Appendix
C Table C-4 CPA2 P
CPA2CPA2
P = Figure 4-8B
P =
Table4-5
Appendix C Table C-5 P
P P =
Figure C-2Table 4-3
Figure C-3
HOGA1P =
CPA2 P = P =
P =
Table C-6P
CFTRP =
P
Discussion
CPA2
Figure 4-8AFigure 4-8B
CPA2Table C-4
CPA2CPA2
CPA2
CPA1
CPA2
HOGA1
CPA2 HOGA1Table 4-6
FHIT
DOCK5 ACTN2 MICAL2
DOCK5
ACTN2
MICAL2
Table 4-6
PRSS1 PRSS2 SPINK1 CTRC CFTR, CASR CPA1 CLDN2
Table C-6P Table C-5 HLA-
DRB1*07:01P =
Figure 4-3
E.coli E.coli
E. coli
Figure 4-4Figure 4-3B C
Table 4-4 Figures 4-6 4-7Table 4-6
PCPA2
Conclusion
CPA2
CPA2
CHAPTER 5. SUMMARY
CPA2
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APPENDIX A. SUPPLEMENTARY INFORMATION FOR CHAPTER 2
Anti-asparaginase Antibody ELISA
Positive and negative controls
Asparaginase antigens
Measurement of anti-asparaginase IgG antibodies by ELISA
o
Normalization of Antibody Readings
Table A-1 Figure A-1
Equation A-1Equation A-2
(Eq. A 1)
(Eq. A 2)
Figure A-2
Table A-1. Comparison between antibody OD readings obtained at SJCRH (n = 1539) and UTHSC (n = 665)
Antigen Facility Positivecut-offa
Median (range) Mean (SD) ofpositive readings
Pb Mean (SD) ofnegative readings
Pb
Figure A-1. Anti-Elspar OD readings obtained at SJCRH (n = 1539) and UTHSC (n = 665) relative to the time of clinical reaction
Figure A-2. Fitted curves for (A) anti-Elspar, (B) anti-Erwinase and (C) anti-Oncaspar OD readings of the samples (n = 194) measured at both SJCRH and UTHSC
Figure A-2. (Continued)
Figure A-2A
Figure A-2B
Figure A-2C
Table A-1Figure A-3
Figure A-3. UTHSC OD readings before and after normalization
Figure A-4. Determination of AUC threshold
Table A-2. Sensitivity, specificity and predictive values of anti-Elspar antibody test at week 7 for predicting or confirming clinical reactions to Elspar using current positivity cutoff and optimized cutoff by recursive partitioning
Risk arm N of patients
Time of Ab test
Time of Rxn
Time between test and rxn
(weeks)
Cutoff OD value
Sensitivity(%)
Specificity(%)
PPV(%)
NPV(%)
Figure A-5. Week-7 optimal threshold of OD value to predict or to confirm clinical reactions
Figure A-6. Elspar has stronger cross-reactivity with Oncaspar than with Erwinase
Figure A-7. Sensitivity of antibody tests within 30 days of reactions
APPENDIX B. SUPPLEMENTARY INFORMATION FOR CHAPTER 3
Mouse Model of Dexamethasone-induced Osteonecrosis
Methods
Chemicals
Animals
Mycoplasma pulmonis
Treatments
Enteric and blood cultures
Measurement of plasma concentration of dexamethasone and corticosterone
m/zm/z m/z
m/z
Results
Body weight differed by substrains
PFigure B-1
P =
P =
P
Effect of substrain, source, age and treatment regimens on survival and development of osteonecrosis
Figure B-2
Figure B-1. Body weight of mice before and after treatment
PP
Figure B-2. Incidence of osteonecrosis increased with longer treatment duration
Figure B-3
P = Table B-1 P = Figure B-4A
Table B-1 Figure B-4B
P = Figure B-4A
Enterococcus faecalis
Figure B-4A
P = Figure B-4AP = Table B-1
Table B-2E. faecalis Staphylococcus xylosus Lactococcus lactis
E. faecalis
E. faecalis
Figure B-3. Similar histologic appearance of osteonecrosis in mice of different substrain, age and treatment groups
Table B-1. Incidence of ON in male BALB/c mice from different experiments
Substrain Source Age DEX Treatmentduration(weeks)
Frequency of ONa
(n positive/n analyzed)
Figure B-4. Survival differed by substrains, sources, regimens and age of mice
Table B-2. Enteric culture isolates from BALB/cJ mice from vendor and in-house breeding colony
Vendor-derived In-house bredTime Isolate TCN
sensitivityTMP
sensitivityIsolate TCN
sensitivityTMP
sensitivityEnterococcus faecalis Enterococcus faecalis
Staphylococcus xylosus Lactococcus lactisStaphylococcus epidermidis Escherichia coli
Enterococcus faecalis Enterococcus faecalisEnterococcus gallinarum Enterococcus gallinarum
Dexamethasone pharmacokinetics and pharmacodynamics
P = P = Figure B-5A
Table B-1P = Figure B-5B
Figure B-6
Gender-dependent difference in susceptibility to osteonecrosis
P = Figure B-7A
P Figure B-7BP =
Figure B-7C
Discussion
Figure B-5. Plasma concentrations of dexamethasone
Figure B-6. Inverse association between plasma corticosterone and dexamethasone levels
Figure B-7. Gender-dependent differences in susceptibility to osteonecrosis
Table B-1
Figure B-4B
E. faecalis
Table B-1 Figure B-5B
Figure B-5A P
Table B-1
P Figure B-7B
Conclusion
Effect of Asparaginase Treatment on Dexamethasone Pharmacokinetics
Figure B-8. Plasma dexamethasone concentration was positively associated with asparaginase activity in osteonecrosis experiment
Effect of asparaginase and dexamethasone on plasma protein and lipid levels
Figure B-9. Mouse plasma amylase level after treatment with dexamethasone and asparaginase
Figure B-10. Mouse plasma lipase level after treatment with dexamethasone and asparaginase
P
Figure B-11. Mouse plasma triglyceride level after treatment with dexamethasone and asparaginase
Figure B-12. Mouse plasma albumin level after treatment with dexamethasone and asparaginase
P
P
Figure B-13. Mouse plasma cortisol level after treatment with dexamethasone and asparaginase
P
Table B-3. Inhibition of plasma protein level in human and mouse by asparaginase treatment
Protein Data source Inhibition% N of ASN/total AA
ASN% N of GLN/total AA
GLN% ASN+GLN%
Table B-3. (Continued)
Protein Data source Inhibition% N of ASN/total AA
ASN% N of GLN/total AA
GLN% ASN+GLN%
Figure 3-1
Figure B-14. Correlation between asparagine content in the protein and theextent of inhibition by asparaginase treatment
Figure 3-1Table B-3
APPENDIX C. SUPPLEMENTARY INFORMATION FOR CHAPTER 4
Deep Sequencing of Selected Genes
Table4-3
SNP-based and Gene-based Analysis of Variants Identified by Deep Sequencing
Figure C-1. CADD score in all SNPs on exome array (n = 162586) and pancreatitis-associated SNPs (P < 0.05; n = 8018)
P
Table C-1. Top 10 SNPs from genome-wide analysis of nonsense SNPs; n = 2,357 SNPs
Cohort (n = 3256) a Case/control (n = 213)SNP Gene Chr Location Major
allele/risk
allele
PopulationRAF% (n)b
RAF% in patients with AP(n = 95)
RAF% in patients
without AP(n = 3161)
Coeff-icientc
Pc RAF% in cases(n = 71)
RAF% in
controls(n = 142)
Coeff-icientd
Pd
CPA2
ZNF701
C17orf66
C9orf117
SLC26A10
SERPINA9
HEATR7B2
CCL26
ERV3-1
GCKR
Table C-2. Top 10 SNPs from genome-wide analysis of missense SNPs (excluding nonsense SNPs); n = 144,349 SNPs
Cohort (n = 3256) a Case/control (n = 213)SNP Gene Chr Location Major
allele/risk
allele
PopulationRAF% (n)b
RAF% in patients with AP(n = 95)
RAF% in patients
without AP(n = 3161)
Coeff-icientc
Pc RAF% in cases(n = 71)
RAF% in
controls(n = 142)
Coeff-icientd
Pd
ADAMTS18
CDC20
PDLIM5
C3orf20
NTF4
C8orf84
NEB
MICAL1
MYOM2
TAS2R16
Table C-3. Top 10 SNPs from genome-wide analysis of synonymous and non-coding SNPs; n = 774,238 SNPs
Cohort (n = 3256) a Case/ctrl (n = 213)SNP Gene Chr Location FunctionMajor
allele/risk
allele
Popu-lation
RAF% (n)b
RAF% in
patients with AP(n = 95)
RAF% in patients without
AP(n = 3161)
Coeff-icientc
Pc RAF% in
cases(n = 71)
RAF% in
controls(n = 142)
Coeff-icientd
Pd
HOGA1
FHIT
-
SPATA21
-
-
C9orf5
FHIT
-
MICAL2
Table C-4. All 380 CPA2 variants identified in the cohort (n = 4217) and the case-control group (n = 162)
Cohort (n = 4217) Case-control (n = 162)Chr:Loca RSID Loca-
tionFunction MAF% in
patients with AP(n = 97)
MAF% in patientswithout
AP(n = 3220)
Coeff-icientb
Pb MAF% in cases(n = 47)
MAF% in controls(n = 115)
Coeff-icientc
Pc
Table C-4. (Continued)
Cohort (n = 4217) Case-control (n = 162)Chr:Loca RSID Loca-
tionFunction MAF% in
patients with AP(n = 97)
MAF% in patients without
AP(n = 3220)
Coeff-icientb
Pb MAF% in cases(n = 47)
MAF% in controls(n = 115)
Coeff-icientc
Pc
Table C-4. (Continued)
Cohort (n = 4217) Case-control (n = 162)Chr:Loca RSID Loca-
tionFunction MAF% in
patients with AP(n = 97)
MAF% in patients without
AP(n = 3220)
Coeff-icientb
Pb MAF% in cases(n = 47)
MAF% in controls(n = 115)
Coeff-icientc
Pc
Table C-4. (Continued)
Cohort (n = 4217) Case-control (n = 162)Chr:Loca RSID Loca-
tionFunction MAF% in
patients with AP(n = 97)
MAF% in patients without
AP(n = 3220)
Coeff-icientb
Pb MAF% in cases(n = 47)
MAF% in controls(n = 115)
Coeff-icientc
Pc
Table C-4. (Continued)
Cohort (n = 4217) Case-control (n = 162)Chr:Loca RSID Loca-
tionFunction MAF% in
patients with AP(n = 97)
MAF% in patients without
AP(n = 3220)
Coeff-icientb
Pb MAF% in cases(n = 47)
MAF% in controls(n = 115)
Coeff-icientc
Pc
Table C-4. (Continued)
Cohort (n = 4217) Case-control (n = 162)Chr:Loca RSID Loca-
tionFunction MAF% in
patients with AP(n = 97)
MAF% in patients without
AP(n = 3220)
Coeff-icientb
Pb MAF% in cases(n = 47)
MAF% in controls(n = 115)
Coeff-icientc
Pc
Table C-4. (Continued)
Cohort (n = 4217) Case-control (n = 162)Chr:Loca RSID Loca-
tionFunction MAF% in
patients with AP(n = 97)
MAF% in patients without
AP(n = 3220)
Coeff-icientb
Pb MAF% in cases(n = 47)
MAF% in controls(n = 115)
Coeff-icientc
Pc
Table C-4. (Continued)
Cohort (n = 4217) Case-control (n = 162)Chr:Loca RSID Loca-
tionFunction MAF% in
patients with AP(n = 97)
MAF% in patients without
AP(n = 3220)
Coeff-icientb
Pb MAF% in cases(n = 47)
MAF% in controls(n = 115)
Coeff-icientc
Pc
Table C-4. (Continued)
Cohort (n = 4217) Case-control (n = 162)Chr:Loca RSID Loca-
tionFunction MAF% in
patients with AP(n = 97)
MAF% in patients without
AP(n = 3220)
Coeff-icientb
Pb MAF% in cases(n = 47)
MAF% in controls(n = 115)
Coeff-icientc
Pc
Table C-4. (Continued)
Cohort (n = 4217) Case-control (n = 162)Chr:Loca RSID Loca-
tionFunction MAF% in
patients with AP(n = 97)
MAF% in patients without
AP(n = 3220)
Coeff-icientb
Pb MAF% in cases(n = 47)
MAF% in controls(n = 115)
Coeff-icientc
Pc
Table C-4. (Continued)
Cohort (n = 4217) Case-control (n = 162)Chr:Loca RSID Loca-
tionFunction MAF% in
patients with AP(n = 97)
MAF% in patients without
AP(n = 3220)
Coeff-icientb
Pb MAF% in cases(n = 47)
MAF% in controls(n = 115)
Coeff-icientc
Pc
Table C-4. (Continued)
Cohort (n = 4217) Case-control (n = 162)Chr:Loca RSID Loca-
tionFunction MAF% in
patients with AP(n = 97)
MAF% in patients without
AP(n = 3220)
Coeff-icientb
Pb MAF% in cases(n = 47)
MAF% in controls(n = 115)
Coeff-icientc
Pc
Table C-4. (Continued)
Cohort (n = 4217) Case-control (n = 162)Chr:Loca RSID Loca-
tionFunction MAF% in
patients with AP(n = 97)
MAF% in patients without
AP(n = 3220)
Coeff-icientb
Pb MAF% in cases(n = 47)
MAF% in controls(n = 115)
Coeff-icientc
Pc
Table C-4. (Continued)
Cohort (n = 4217) Case-control (n = 162)Chr:Loca RSID Loca-
tionFunction MAF% in
patients with AP(n = 97)
MAF% in patients without
AP(n = 3220)
Coeff-icientb
Pb MAF% in cases(n = 47)
MAF% in controls(n = 115)
Coeff-icientc
Pc
Table C-4. (Continued)
Cohort (n = 4217) Case-control (n = 162)Chr:Loca RSID Loca-
tionFunction MAF% in
patients with AP(n = 97)
MAF% in patients without
AP(n = 3220)
Coef-ficientb
Pb MAF% in cases(n = 47)
MAF% in controls(n = 115)
Coef-ficientc
Pc
Table C-4. (Continued)
Cohort (n = 4217) Case-control (n = 162)Chr:Loca RSID Loca-
tionFunction MAF% in
patients with AP(n = 97)
MAF% in patients without
AP(n = 3220)
Coeff-icientb
Pb MAF% in cases(n = 47)
MAF% in controls(n = 115)
Coeff-icientc
Pc
Table C-4. (Continued)
Cohort (n = 4217) Case-control (n = 162)Chr:Loca RSID Loca-
tionFunction MAF% in
patients with AP(n = 97)
MAF% in patients without
AP(n = 3220)
Coeff-icientb
Pb MAF% in cases(n = 47)
MAF% in controls(n = 115)
Coeff-icientc
Pc
CPA2
Table C-5. Top genes (P < 0.05) in the gene-level analysis of nonsense variants identified in putative pancreatitis (n = 42) and non-pancreatitis genes (n = 241) based on variants identified by deep sequencing
Ranka Gene N of SNPsb Cohort SKAT P(n = 4217)
Case-control SKAT P(n = 162)
Pancreatitis-associatedc
HOGA1CPA2
ZNF233C9orf117LRRC39
XDHXRCC1IFNA5QPCT
C11orf63ZRANB3C12orf40DDX49GCKRSNTG2RUFY4MPZL3DAPL1ALS2CLCENPQ
NMI
Figure C-2. Top pathways and functions of pancreatitis-associated genes (n = 42) Table 4-3
Figure C-3. Top pathways and functions of pancreatitis-associated genes identified by GWAS (n = 34)
Table 4-3
Table C-6. SNPs (n = 81) identified by deep sequencing in previously reported pancreatitis-associated candidate genes (n = 8) at the P < 0.05 level (highlighted) in either the cohort or the case-control group
Cohort (n = 4217) Case-control (n = 162)Gene
(n of SNPs at P < 0.05/n of
all SNPs)a
Chr:Locb RSID Function Majorallele/minor allele
MAF% in
patients with AP
(n = 95)
MAF% in
patients without
AP(n = 3161)
Coeff-icientc
Pc MAF% in cases
(n = 47)
MAF% in con-trols(n =115)
Coeff-icientd
Pd Dire-ctione
CTRC
CASR
SPINK1
Table C-6. (Continued)
Cohort (n = 4217) Case-control (n = 162)
Gene(n of SNPs at P < 0.05/n of
all SNPs)a
Chr:Locb RSID Function Majorallele/minor allele
MAF% in
patients with AP(n = 95)
MAF% in patients
without AP(n = 3,161)
Coeff-icientc
Pc MAF% in cases(n = 47)
MAF% in con-trols(n = 115)
Coeff-icientd
Pd Dire-ctione
CFTR
Table C-6. (Continued)
Cohort (n = 4217) Case-control (n = 162)
Gene(n of SNPs at P < 0.05/n of
all SNPs)a
Chr:Locb RSID Function Majorallele/minor allele
MAF% in
patients with AP(n = 95)
MAF% in patients
without AP(n = 3,161)
Coeff-icientc
Pc MAF% in cases(n = 47)
MAF% in con-trols(n = 115)
Coeff-icientd
Pd Dire-ctione
CFTR
Table C-6. (Continued)
Cohort (n = 4217) Case-control (n = 162)
Gene(n of SNPs at P < 0.05/n of
all SNPs)a
Chr:Locb RSID Function Majorallele/
minor allele
MAF% in
patients with AP(n = 95)
MAF% in
patients without
AP(n =
3,161)
Coeff-icientc
Pc MAF% in cases(n = 47)
MAF% in con-trols(n = 115)
Coeff-icientd
Pd Dire-ctione
CPA180,81
PRSS1
Table C-6. (Continued)
Cohort (n = 4217) Case-control (n = 162)Gene
(n of SNPs at P < 0.05/n of
all SNPs)a
Chr:Locb RSID Function Majorallele/minor allele
MAF% in
patients with AP(n = 95)
MAF% in
patients without
AP(n =
3,161)
Coeff-icientc
Pc MAF% in cases(n = 47)
MAF% in con-trols(n = 115)
Coeff-icientd
Pd Dire-ctione
PRSS1
PRSS266,69
CLDN266,69
Table C-6. (Continued)
P
VITA