Analysis of the Repeated Measurement Data using the Hierarchical Clustering and Nonlinear Regression Methods in Asthma Pharmacogenetic Study

OBJECTIVE: We examined several analytic methods for predicting therapeutic response to drug in Korea asthmatics and tried to develop a clinical model to predict the drug response to asthma drug. BACKGROUND: Long acting β2-agonists (LABA) is the most powerful bronchodilator and inhaled corticosteroid (ICS) was the most effective anti-inflammatory drug currently available in asthma management. The combination treatment including LABA and ICS has been considered as an essential drug to achieve optimal asthma control. METHODS: The eighty-six mild to moderate asthmatic patients were enrolled. With using combination inhaler (budesonide/formoterol 320μg/d) for 80 days, we monitored morning and evening peak expiratory flow daily and pulmonary function every 8 weeks. Twelve SNPs from 9 candidate genes including ADCY9 132007 T>C (Ile772Met), ALOX5 -1708 G>A, CysLTR1 -634 C>T, CysLTR2 2079 C>T, 2534 A>G, IL10 -1082 A>G, IL13 -1510 A>C, LTC4S -1072 G>A, LTC4S -444 A>C, NK2R 7853 G>A (Gly231Glu), TNFα -1031 T>C and TNFα -308 G>A were analyzed. First, we tested the therapeutic response to combination inhaler according to genetic polymorphisms of each SNP, level of asthma control and pulmonary function tests. The changes of pulmonary function tests such as predicted FEV1, MMEF and FEV1/FVC were analyzed using repeated measures ANOVA in the generalized linear model (GLM). A hierarchical clustering method was applied to get daily change (%) of PEFR to combination inhaler. The asthmatics were divided into two groups (favorable vs. poor responses) according to the changes of PEFR using the hierarchical clustering method. Each SNP was analyzed by testing for independence between two groups. For predicting drug response, the associations between each SNP and time trend of response were analyzed and the equation for the predicted PEFR was constructed by nonlinear regression method. RESULT: Among the 12 SNPs, the ADCY9 132007 T>C polymorphism was significantly associated with response to combination inhaler. The patients with CT or CC genotype at the ADCY9 132007 T>C polymorphism are more in well controlled state than those with TT genotype in the initiate stage (0~8 week). A possible interaction between ADCY9 132007 T>C polymorphism and IL13 -1510 A>C polymorphism was noted by generalized linear model (GLM). The rank of candidate SNPs was determined using decision tree forest. A clinical model for predicting a drug response to combination inhaler using nonlinear regression method was constructed. CONCLUSION: The ADCY9 132007 T>C polymorphism may affect on drug response to a combination inhaler in Korean asthmatics. We suggest a clinical model using an alternative statistical analysis including hierarchical clustering and nonlinear regression methods for predicting a drug response to a combination inhaler.

Author dc:creator

• 이, 현영

Contributors dc:contributor

• 박, 해심
• 대학원 의학과
• 200624181

• 천식
• 계층적 군집분석
• 비선형 회귀분석
• 반복측정 분산분석
• 단일염기변이
• 약물유전체학
• asthma
• hierarchical clustering method
• nonlinear regression method
• repeated measures analysis of variance
• single nucleotide polymorphism and pharmacogenetics

Language dc:language

ko

Identifier

http://dcoll.ajou.ac.kr:9080/dcollection/jsp/common/DcLoOrgPer.jsp?sItemId=000000005952
000000005952

OAI identifier oai:identifier

oai:repository.ajou.ac.kr:201003/1846