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Whole genome methylation profiling difference in PBMC between responder and nonresponder of acute exacerbations of COPD patients treated with corticosteroid.

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Presentation on theme: "Whole genome methylation profiling difference in PBMC between responder and nonresponder of acute exacerbations of COPD patients treated with corticosteroid."— Presentation transcript:

1 Whole genome methylation profiling difference in PBMC between responder and nonresponder of acute exacerbations of COPD patients treated with corticosteroid Lawrence Wu, Ph.D Associate Professor Institute of Medical Sciences Tzu Chi University

2 COPD Chronic obstructive pulmonary disease (COPD) is a major cause of morbidity and mortality throughout the world, and further increases in its prevalence and mortality can be predicted in the coming decades. The World Health Organization has predicted that it will be the third leading cause of death in the world by the year The clinical course of the disease is characterized by progressive, irreversible airflow obstruction associated with chronic inflammation of the respiratory tract. However, there are still no effective drug therapies for COPD that alter disease progression.

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4 a cough that lasts a long time, or coughing up mucus feeling short of breath, especially when you are making an effort (climbing stairs, exercising) many lung infections that last a long time (the flu, acute bronchitis, pneumonia, etc.) wheezing (a whistling sound when you breathe) feeling tired (fatigue) losing weight without trying

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6 AECOPD Acute exacerbations are triggered mainly by respiratory tract infections. According to evidence-based reviews and current guidelines, systemic glucocorticoid therapy is an integral part of the management of COPD exacerbations

7 Steroids treatment Steroids are often used in the treatment of AECOPD. Use of corticosteroids has been shown to shorten recovery time, hasten improvement in lung function, reduce the risk of early relapse and reduce length of hospital stay. The existing guidelines suggest that oral administration of corticosteroids in a dose of 30– 40 mg prednisolone per day for 10–14 days is preferable.

8 Study subjects All 60 enrolled patients with COPD exacerbation were received medicine including Predisolone 2 tablet (5mg/tablet) three times a day, Medicon 1 tablet three times a day, Ventolin 1 tablet three times a day, and Bisolvon 1 tablet three time a day. The treatment duration is two weeks (14 days). Subjects were improved all evaluation (CAT, spirometry test) after treatment and defined as responder of corticosteroid treatment. Other subjects without improved CAT and spirometry test after treatment were defined as non-responder of corticosteroid treatment.

9 CAT is usefulness in evaluating COPD exacerbation Mackay AJ et al. Am J Respir Crit Care Med Vol 185, Iss. 11, pp 1218–1224, Jun 1, 2012 The CAT provides a reliable score of exacerbation severity. Baseline CAT scores are elevated in frequent exacerbators. CAT scores increase at exacerbation and reflect severity as determined by lung function and exacerbation duration.

10 COPD Assessment Test (CAT)

11 COPD is progressive disease, the FEV1and FVC is no significant alteration in many COPD patients in acute exacerbation during the two-week medical treatment FEV1, FEV1% and FVC are objective measurements. CAT is subjective questionnaire. Patients with better FEV1, FVC and CAT score (more than 5 points decrease) after treatment were defined as response to corticosteroid. The poor response group was defined as that FEV1 and FVC after 2 week treatment did not better than before treatment and CAT score didn’t decrease (more than 5 points) or increased after treatment.

12 Results Subjects characters The total 24 COPD patients were enrolled and DNA samples were obtained from subjects’ PBMC. The good response group included 9 males and 3 females and the poor response group was all males. All subjects were diagnosis to COPD at first time and never treated with corticosteroid before. The subject counts with different lung function in good and poor response groups are mild 4/5, moderate 5/4 and severe obstruction 3/3, respectively. The average age of two groups was no significant difference.

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16 Bisulfate conversion

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18 Genome-wide methylation chip 24 selected patients’ PBMC DNA were subjected to genome-wide methylation analysis 500 ng of each sample underwent bisulfite conversion using the EZ DNA methylation kit. Bisulfite converted DNA samples were then subjected to methylation profiling on the Infinium® HumanMethylation450 BeadChips

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20 Genomic location of selected methylation site

21 Figure 1. heatmap of methylation pattern, left side (12 subjects): good prognosis patients, right side (12 subjects) : poor prognosis patients

22 Gene with different methylation level between two study groups Genes with low methylation level in poor prognosis group Genes with higher methylation level in poor prognosis group MSTO2P HLA-DPA1LOC339788GSTM3 GAK NMNAT3PPP1R2P9RHPN1 MYADML DNAH2MIR1914 MAD1L1 SCGN MGMTRASA3TCEA2 HLA-DPA1 PSMD8GOLIM4ADAMTS17 FLRT2FOLR3 FLJ41941TMEM41A BST1BAI1 F3 NR3C1 MCCALOX5AP CMTM1 TP53INP2 ZNF235 B3GALT1LOC SH2D6 SLC38A7 MMP17 CHID1

23 False discovery rate adjust TargetIDGeneFDRpdiff(abs)Regulation cg ALOX5AP2.34E E up cg MIR1914;UCKL12.05E E down cg GSTM33.61E E down cg BST17.33E E up cg GAK1.17E E up cg PSMD81.17E E up cg F37.49E E down cg TMEM41A1.42E E down cg Not in gene region9.50E E up cg FOLR37.66E E up cg MSTO2P6.99E E up cg Not in gene region2.40E E down cg Not in gene region2.20E E down cg MMP173.80E E down cg GOLIM E down cg RASA E down cg Not in gene region E down cg ZNF E up cg SH2D E down cg NR3C E down cg TCEA E down cg CHID E down cg LOC E down

24 Several genes methylation status is powerful to distinguish different prognosis geneProbe ID △ AVG  AVG  of good prognosisAVG  of poor prognosis meanmaxminmeanmaxmin GSTM3cg TMEM41Acg MIR1914cg NR3C1cg GOLIM4cg F3cg MSTO2Pcg PSMD8cg BST1cg ALOX5APcg GAKcg AVG: methylation level;  △ AVG =AVG of good prognosis – AVG of poor prognosis; max: maximum value; min: minimal value

25 Genomic location….. geneProbe IDUCSC_CPG_ISLANDS_N AME UCSC_REF GENE_GRO UP RELATION_ TO_UCSC_C PG_ISLAND REGULATORY_FEATURE _GROUP GSTM3cg chr1: BodyIsland Promoter_Associated_Cell_type_specific TMEM41Acg chr3: TSS200Island Unclassified MIR1914cg chr20: BodyS_Shore Gene_Associated NR3C1cg chr5: BodyN_Shore Promoter_Associated_Cell_type_specific GOLIM4cg Chr3: Body F3cg chr1: TSS1500Island Unclassified MSTO2Pcg chr1: TSS1500Island Promoter_Associated PSMD8cg chr19: 'UTRN_Shelf BST1cg chr4: BodyS_Shelf ALOX5APcg Chr13: (rs )Body Gene_Associated_Cell_type_specific GAKcg chr4: BodyN_Shore Gene_Associated

26 Some thought about candidate genes FLAP (ALOX5AP) inhibitors for the treatment of inflammatory diseases ( Sampson AP. Curr Opin Investig Drugs Nov;10(11): ). Does patients with high level methylation reduce the ALOX5AP expression in PBMC cell and obtain the result similar to FLAP inhibitors treatment? Gene expression profiling of lung from emphysema patients identified seven candidate genes associated with emphysema severity including GSTM3. ( Francis SM et al. Respir Res Sep 2;10:81.) Glutathione S-transferases (GSTs) detoxify toxic compounds in tobacco smoke via glutathione-dependent mechanisms. Few studies have also found an increase in GSTM3 expression in mild/moderate COPD smokers; this strengthens their role as protective intracellular and extracellular lung mediators ( Bentley AR et al. Thorax 2008, 63(11): Harju T et al. Respiratory research 2008, 9:80.) Does low level methylation increase the GSTM3 expression in PBMC cell and protect the lung function decline? Many cases of glucocorticoid resistance may be due to mutations or polymorphisms present in the glucocorticoid receptor gene (GR/NR3C1). ( Bray PJ and Cotton RG. Hum Mutat. 2003;21: ) Does high level methylation decrease NR3C1 expression in PBMC cell and increase the risk of glucocorticoid resistance?

27 COPD methylation profiling : transcription factor analysis 50k probes 50 probes > 0.25 △ AVG Probe >0.25 Count probes (>0.1 △ AVG ) among upstream 50k and downstream 50k 3 probes with count 10 1 probe with count 7 3 probes with count 3 5 probes with count 2 38 probes with count 1 cg chr6 chr8 chr8,2,7 chrX,4,4,5,13

28 methylation probes (>0.1)

29 Arnt Xbp1 Tcfap4 Elf1 Max Srebf1 Myc Pax5 Klf12 Postn Runx2 Tcf12 Pax8 Akr1b3 Akr1b7 Areg Mafk Nfe2 Elk1 Sfpi1 Zbtb6 Nfkb1 Nr1h2 Nr1h3 Pou2f1 Pax2 Jun Gcgr Nr3c1 Pitx2 Crx Pax3 Mtf1 Cebpb Rest Cdx1 Tcfap2a Tcf12 Akr1b3 Akr1b7 Areg Nfe2l1 Egr1 Egr2 Gcgr Nr3c1 Nkx3-1 Jun Cdx1 Cebpg Cux1 Myod1 Zeb1 Tcf3 Pax5 Klf12 Tcfap2a Pou3f2 Gata6 Elk1 Sfpi1 Zbtb6 Pax2 Gcgr Nr3c1 Akr1b3 Akr1b7 Areg Srebf1 Pgr HLA-DPA1 chr6: HLA-DPA Human TFBS

30 Further thinking……. Do the different response groups indicate two subtypes of COPD? Is the pharmacoepigenetics helpful to reveal heterogeneity of COPD? HLA-DPA1 vs. COPD: MHC class II antigen involving pathological mechanism of COPD?

31 COPD vs. control COPD p vs. control COPD g vs. control Control subjects without lung diseases were selected from another study.

32 COPD vs. control Methylation level down ALOX5AP BST1 GAK PSMD8 CEND1 FAM20C MGMT PRDM16 LRRK1 CDK2AP1 PRKCA GJA3 MCF2L PCCA SCARB1 MCF2L FAM69B RNASE4 ABR SPRR2D RFTN1 UPF1 FRG1B GOLIM4 LOC MAST2 TEKT5 PRKAG2 Methylation level up GSTM3 MIR1914 HBE1 GALNT9 CLDN4 DDX11 RCAN1 SLC14A1 PYROXD1 HLA-DPB2 MYO3B UGT2B15 SEPT9 CLDN4 UGT2B15;UGT2B17 HLA-DQB1 GSTM3 MIR1914 HBE1 GALNT9 CLDN4 DDX1 GJA3 RCAN1 SLC14A1 PYROXD1 HLA-DPB2 MYO3B UGT2B15;UGT2B17 SEPT9 CLDN4 UGT2B15;UGT2B17 HLA-DQB1 MEGF6 CCDC85C SNCAIP CYP2U1 MIR518C;MIR520C DNAJA3 MAGEB3 HMOX2 TIAL1 EXOC7 RGMA MPPED1 ASAH2 HSD3B2 WDR90 KCTD2 OSBPL5 TAP2 ZFYVE28 TAP2 NME6 CCDC46 MCC TP73 MSTO2P FHOD3 FHIT SFRS8 NRGN RAB11B AP4E1 LYPD6B TAP2 POLE

33 Preliminary functional analysis by bioinformatics methods using DAVID Poor response COPD group: related genes located to membrane and associated to glycoprotein (p <0.02) Good response COPD group: related genes associated to Ubl conjugation pathway (p<0.003), nicotinamide nucleotide metabolism (p<0.008), alkaloid metabolic process (p<0.009) and regulation of glucose metabolic process (p<0.006) *DAVID: The Database for Annotation, Visualization and Integrated Discovery

34 35 genes plasma membrane (p=0.03) cell junction(p=0.04) serine/threonine-protein kinase (p=0.04) 43 genes negative regulation of kinase activity (p=0.004) purine ribonucleotide binding (p=0.03) DNA metabolic process/Purine metabolism(p=0.02) 43 genes (overlap of 3 circles) positive regulation of apoptosis (p=0.09) steroid metabolic process (p=0.02)

35 Non-COPD vs. All COPD Top five significant genes GeneFDR pnote OSBPL51.38E-18 DNA methylation differences at growth related genes correlate with birth weight: a molecular signature linked to developmental origins of adult disease? WDR61.19E-17 WDR6 participates in insulin/IGF-I signaling and the regulation of feeding behavior and longevity in the brain. PRKAG22.36E-17 hypertrophic cardiomyopathy NLRC53.05E-06 NLRC5: a key regulator of MHC class I-dependent immune responses. GIMAP41.53E-05 1.Gimap4 accelerates T-cell death. 2.Knock-down of PHF11 also decreased cell viability and was accompanied by reduced expression of GIMAP4 and 5 genes required for T-cell differentiation, viability and homeostasis.

36 Conclusion The DNA methylation should be a good biomarker for investigating the pharmaco- epigenetics of COPD. Methylation status of COPD susceptibility gene(s), inflammatory gene(s) and glucocorticoid receptor gene associate to outcome of 2-week corticosteroid treatment in AECOPD patients Responsiveness of corticosteroids, should reflect COPD heterogeneity, especially in pathology involving DNA methylation.

37 Future works To link the prognosis of COPD and DNA methylation. To find the new candidate gene(s) or pathological mechanism of COPD by DNA methylation approach

38 Acknowledgement Dr. Shih-Wei Lee (General Taoyuan Hospital) Dr. Paul Wei-Che Hsu (Bioinformatics service center, IMB, Academia Sinica) Dr. Jiu-Yao Wang (NCKU)

39 Thank you for your attention


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