Browsing by Author "Zhang, Pengyue"
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Item A comprehensive assessment of statin discontinuation among patients who concurrently initiate statins and CYP3A4-inhibitor drugs; a multistate transition model(Wiley, 2023) Donneyong, Macarius M.; Zhu, Yuxi; Zhang, Pengyue; Li, Yiting; Hunold, Katherine M.; Chiang, ChienWei; Unroe, Kathleen; Caterino, Jeffrey M.; Li, Lang; Medicine, School of MedicineAims: The aim of this study was to describe the 1-year direct and indirect transition probabilities to premature discontinuation of statin therapy after concurrently initiating statins and CYP3A4-inhibitor drugs. Methods: A retrospective new-user cohort study design was used to identify (N = 160 828) patients who concurrently initiated CYP3A4 inhibitors (diltiazem, ketoconazole, clarithromycin, others) and CYP3A4-metabolized statins (statin DDI exposed, n = 104 774) vs. other statins (unexposed to statin DDI, n = 56 054) from the MarketScan commercial claims database (2012-2017). The statin DDI exposed and unexposed groups were matched (2:1) through propensity score matching techniques. We applied a multistate transition model to compare the 1-year transition probabilities involving four distinct states (start, adverse drug events [ADEs], discontinuation of CYP3A4-inhibitor drugs, and discontinuation of statin therapy) between those exposed to statin DDIs vs. those unexposed. Statistically significant differences were assessed by comparing the 95% confidence intervals (CIs) of probabilities. Results: After concurrently starting stains and CYP3A, patients exposed to statin DDIs, vs. unexposed, were significantly less likely to discontinue statin therapy (71.4% [95% CI: 71.1, 71.6] vs. 73.3% [95% CI: 72.9, 73.6]) but more likely to experience an ADE (3.4% [95% CI: 3.3, 3.5] vs. 3.2% [95% CI: 3.1, 3.3]) and discontinue with CYP3A4-inhibitor therapy (21.0% [95% CI: 20.8, 21.3] vs. 19.5% [95% CI: 19.2, 19.8]). ADEs did not change these associations because those exposed to statin DDIs, vs. unexposed, were still less likely to discontinue statin therapy but more likely to discontinue CYP3A4-inhibitor therapy after experiencing an ADE. Conclusion: We did not observe any meaningful clinical differences in the probability of premature statin discontinuation between statin users exposed to statin DDIs and those unexposed.Item A multistate transition model for statin‐induced myopathy and statin discontinuation(Wiley, 2021) Zhu, Yuxi; Chiang, Chien-Wei; Wang, Lei; Brock, Guy; Milks, M. Wesley; Cao, Weidan; Zhang, Pengyue; Zeng, Donglin; Donneyong, Macarius; Li, Lang; Biostatistics and Health Data Science, Richard M. Fairbanks School of Public HealthThe overarching goal of this study was to simultaneously model the dynamic relationships among statin exposure, statin discontinuation, and potentially statin-related myopathic outcomes. We extracted data from the Indiana Network of Patient Care for 134,815 patients who received statin therapy between January 4, 2004, and December 31, 2008. All individuals began statin treatment, some discontinued statin use, and some experienced myopathy and/or rhabdomyolysis while taking the drug or after discontinuation. We developed a militate model to characterize 12 transition probabilities among six different states defined by use or discontinuation of statin and its associated myopathy or rhabdomyolysis. We found that discontinuation of statin therapy was common and frequently early, with 44.4% of patients discontinuing therapy after 1 month, and discontinuation is a strong indicator for statin-induced myopathy (risk ratio, 10.8; p < 0.05). Women more likely than men (p < 0.05) and patients aged 65 years and older had a higher risk than those aged younger than 65 years to discontinue statin use or experience myopathy. In conclusion, we introduce an innovative multistate model that allows clear depiction of the relationship between statin discontinuation and statin-induced myopathy. For the first time, we have successfully demonstrated and quantified the relative risk of myopathy between patients who continued and discontinued statin therapy. Age and sex were two strong risk factors for both statin discontinuation and incident myopathy.Item A Novel Perioperative Multidose Methadone-Based Multimodal Analgesic Strategy in Children Achieved Safe and Low Analgesic Blood Methadone Levels Enabling Opioid-Sparing Sustained Analgesia With Minimal Adverse Effects(Wolters Kluwer, 2021) Sadhasivam, Senthilkumar; Aruldhas, Blessed W.; Packiasabapathy, Senthil; Overholser, Brian R.; Zhang, Pengyue; Zang, Yong; Renschler, Janelle S.; Fitzgerald, Ryan E.; Quinney, Sara K.; Anesthesia, School of MedicineBackground: Intraoperative methadone, a long-acting opioid, is increasingly used for postoperative analgesia, although the optimal methadone dosing strategy in children is still unknown. The use of a single large dose of intraoperative methadone is controversial due to inconsistent reductions in total opioid use in children and adverse effects. We recently demonstrated that small, repeated doses of methadone intraoperatively and postoperatively provided sustained analgesia and reduced opioid use without respiratory depression. The aim of this study was to characterize pharmacokinetics, efficacy, and safety of a multiple small-dose methadone strategy. Methods: Adolescents undergoing posterior spinal fusion (PSF) for idiopathic scoliosis or pectus excavatum (PE) repair received methadone intraoperatively (0.1 mg/kg, maximum 5 mg) and postoperatively every 12 hours for 3-5 doses in a multimodal analgesic protocol. Blood samples were collected up to 72 hours postoperatively and analyzed for R-methadone and S-methadone, 2-ethylidene-1,5-dimethyl-3,3-diphenylpyrrolidene (EDDP) metabolites, and alpha-1 acid glycoprotein (AAG), the primary methadone-binding protein. Peak and trough concentrations of enantiomers, total methadone, and AAG levels were correlated with clinical outcomes including pain scores, postoperative nausea and vomiting (PONV), respiratory depression, and QT interval prolongation. Results: The study population included 38 children (10.8-17.9 years): 25 PSF and 13 PE patients. Median total methadone peak plasma concentration was 24.7 (interquartile range [IQR], 19.2-40.8) ng/mL and the median trough was 4.09 (IQR, 2.74-6.4) ng/mL. AAG concentration almost doubled at 48 hours after surgery (median = 193.9, IQR = 86.3-279.5 µg/mL) from intraoperative levels (median = 87.4, IQR = 70.6-115.8 µg/mL; P < .001), and change of AAG from intraoperative period to 48 hours postoperatively correlated with R-EDDP (P < .001) levels, S-EDDP (P < .001) levels, and pain scores (P = .008). Median opioid usage was minimal, 0.66 (IQR, 0.59-0.75) mg/kg morphine equivalents/d. No respiratory depression (95% Wilson binomial confidence, 0-0.09) or clinically significant QT prolongation (median = 9, IQR = -10 to 28 milliseconds) occurred. PONV occurred in 12 patients and was correlated with morphine equivalent dose (P = .005). Conclusions: Novel multiple small perioperative methadone doses resulted in safe and lower blood methadone levels, <100 ng/mL, a threshold previously associated with respiratory depression. This methadone dosing in a multimodal regimen resulted in lower blood methadone analgesia concentrations than the historically described minimum analgesic concentrations of methadone from an era before multimodal postoperative analgesia without postoperative respiratory depression and prolonged corrected QT (QTc). Larger studies are needed to further study the safety and efficacy of this methadone dosing strategy.Item Alcohol use disorder is associated with higher risks of Alzheimer's and Parkinson's diseases: A study of US insurance claims data(Wiley, 2022-11-21) Zhang, Pengyue; Edenberg, Howard J.; Nurnberger, John; Lai, Dongbing; Cheng, Feixiong; Liu, Yunlong; Biostatistics, School of Public HealthIntroduction: Alcohol use disorder (AUD) is on the ascendancy in the US older adult population. The association between AUD and adverse brain outcomes remains inconclusive. Method: In a retrospective cohort design using US insurance claim data (2007-2020), 129,182 individuals with AUD were matched with 129,182 controls by age, sex, race, and clinical characteristics. We investigated the association between AUD and adverse brain outcomes using Cox analysis, Kaplan-Meier analysis, and log-rank test. Results: After adjusting for covariates, AUD was associated with a higher risk of Alzheimer's disease (female adjusted hazard ratio [HR] = 1.78, 95% confidence interval [CI]: 1.68-1.90, p < 0.001; male adjusted HR = 1.80, 95% CI: 1.71-1.91, p < 0.001) and a higher risk of Parkinson's disease (female adjusted HR = 1.49, 95% CI: 1.32-1.68, p < 0.001; male adjusted HR = 1.42, 95% CI: 1.32-1.52, p < 0.001) in the overall sample. In separate analyses of Black, White, and Hispanic individuals, those with AUD had higher risk of Alzheimer's disease (adjusted HRs ≥1.58; Ps ≤ 0.001). A significantly elevated risk for Parkinson's disease was found only in the White subpopulation (female adjusted HR = 1.55, 95% CI: 1.36-1.77, p < 0.001; male adjusted HR = 1.45, 95% CI: 1.33-1.57, p < 0.001). Conclusions: AUD is associated with Alzheimer's disease. AUD is associated with Parkinson's disease in White people. Cognitive screening and neurological examination among older adults with AUD hold the promise for early detection of Alzheimer's disease and Parkinson's disease. Highlights: Alcohol use disorder is associated with Alzheimer's disease and dementia. Alcohol use disorder is associated with Parkinson's disease in White people.Item Artificial intelligence framework identifies candidate targets for drug repurposing in Alzheimer’s disease(BMC, 2022-01-10) Fang, Jiansong; Zhang, Pengyue; Wang, Quan; Chiang, Chien‑Wei; Zhou, Yadi; Hou, Yuan; Xu, Jielin; Chen, Rui; Zhang, Bin; Lewis, Stephen J.; Leverenz, James B.; Pieper, Andrew A.; Li, Bingshan; Li, Lang; Cummings, Jeffrey; Cheng, Feixiong; Biostatistics and Health Data Science, School of MedicineBackground: Genome-wide association studies (GWAS) have identified numerous susceptibility loci for Alzheimer's disease (AD). However, utilizing GWAS and multi-omics data to identify high-confidence AD risk genes (ARGs) and druggable targets that can guide development of new therapeutics for patients suffering from AD has heretofore not been successful. Methods: To address this critical problem in the field, we have developed a network-based artificial intelligence framework that is capable of integrating multi-omics data along with human protein-protein interactome networks to accurately infer accurate drug targets impacted by GWAS-identified variants to identify new therapeutics. When applied to AD, this approach integrates GWAS findings, multi-omics data from brain samples of AD patients and AD transgenic animal models, drug-target networks, and the human protein-protein interactome, along with large-scale patient database validation and in vitro mechanistic observations in human microglia cells. Results: Through this approach, we identified 103 ARGs validated by various levels of pathobiological evidence in AD. Via network-based prediction and population-based validation, we then showed that three drugs (pioglitazone, febuxostat, and atenolol) are significantly associated with decreased risk of AD compared with matched control populations. Pioglitazone usage is significantly associated with decreased risk of AD (hazard ratio (HR) = 0.916, 95% confidence interval [CI] 0.861-0.974, P = 0.005) in a retrospective case-control validation. Pioglitazone is a peroxisome proliferator-activated receptor (PPAR) agonist used to treat type 2 diabetes, and propensity score matching cohort studies confirmed its association with reduced risk of AD in comparison to glipizide (HR = 0.921, 95% CI 0.862-0.984, P = 0.0159), an insulin secretagogue that is also used to treat type 2 diabetes. In vitro experiments showed that pioglitazone downregulated glycogen synthase kinase 3 beta (GSK3β) and cyclin-dependent kinase (CDK5) in human microglia cells, supporting a possible mechanism-of-action for its beneficial effect in AD. Conclusions: In summary, we present an integrated, network-based artificial intelligence methodology to rapidly translate GWAS findings and multi-omics data to genotype-informed therapeutic discovery in AD.Item Association Between Tobacco Related Diagnoses and Alzheimer Disease: A population Study(2022-05) Almalki, Amwaj Ghazi; Zhang, Pengyue; Johnson, Travis; Fadel, WilliamBackground: Tobacco use is associated with an increased risk of developing Alzheimer's disease (AD). 14% of the incidence of AD is associated with various types of tobacco exposure. Additional real-world evidence is warranted to reveal the association between tobacco use and AD in age/gender-specific subpopulations. Method: In this thesis, the relationships between diagnoses related to tobacco use and diagnoses of AD in gender- and age-specific subgroups were investigated, using health information exchange data. The non-parametric Kaplan-Meier method was used to estimate the incidence of AD. Furthermore, the log-rank test was used to compare incidence between individuals with and without tobacco related diagnoses. In addition, we used semi-parametric Cox models to examine the association between tobacco related diagnoses and diagnoses of AD, while adjusting covariates. Results: Tobacco related diagnosis was associated with increased risk of developing AD comparing to no tobacco related diagnosis among individuals aged 60-74 years (female hazard ratio [HR] =1.26, 95% confidence interval [CI]: 1.07 – 1.48, p-value = 0.005; and male HR =1.33, 95% CI: 1.10 - 1.62, p-value =0.004). Tobacco related diagnosis was associated with decreased risk of developing AD comparing to no tobacco related diagnosis among individuals aged 75-100 years (female HR =0.79, 95% CI: 0.70 - 0.89, p-value =0.001; and male HR =0.90, 95% CI: 0.82 - 0.99, p-value =0.023). Conclusion: Individuals with tobacco related diagnoses were associated with an increased risk of developing AD in older adults aged 60-75 years. Among older adults aged 75-100 years, individuals with tobacco related diagnoses were associated with a decreased risk of developing AD.Item The Concurrent Initiation of Medications Is Associated with Discontinuation of Buprenorphine Treatment for Opioid Use Disorder(medRxiv, 2020) Zhang, Pengyue; Chiang, Chien-Wei; Quinney, Sara; Donneyong, Macarius; Lu, Bo; Huang, Lei Frank; Cheng, Feixiong; Obstetrics and Gynecology, School of MedicineIntroduction Retention in buprenorphine treatment for opioid use disorder (OUD) yields better opioid abstinence and reduces all-cause mortality for patients with OUD. Despite significant efforts have been made to expand the availability and use of buprenorphine in the United States, its retention rates remain on a low level. The current study examines discontinuation of buprenorphine with respect to concurrent initiation of other medications using real-world evidence. Methods Case-crossover study was conducted to examine discontinuation of buprenorphine using a large-scale longitudinal health dataset including 148,306 commercially-insured individuals initiated on medications for opioid use disorder (MOUD). Odds ratios and Bonferroni adjusted p-values were calculated for medications and therapeutic classes of medications. Results Clonidine was associated with increased discontinuation risk of buprenorphine both using the buprenorphine dataset alone (OR = 1.583 and adjusted p-value = 1.22 × 10−6) and using naltrexone as a comparison drug (OR = 2.706 and adjusted p-value = 4.11 × 10−5). Opioid medications (oxycodone, morphine and fentanyl) and methocarbamol were associated with increased discontinuation risk of buprenorphine using the buprenorphine dataset alone (adjusted p-value < 0.05), but not significant using naltrexone as a comparison drug. 6 drug therapeutic classes were associated with increased discontinuation risk of buprenorphine both using the buprenorphine dataset alone and using naltrexone as a comparison drug (adjusted p-value < 0.05). Conclusion Concurrent initiation of medications is associated with increased discontinuation risk of buprenorphine. Opioid medications are prescribed among patients on MOUD and associated with increased discontinuation risk of buprenorphine. Analgesics is associated with increased discontinuation risk of buprenorphine for patients without previous exposure of pain medications.Item DEPOT: graph learning delineates the roles of cancers in the progression trajectories of chronic kidney disease using electronic medical records(medRxiv, 2023-08-16) Song, Qianqian; Liu, Xiang; Li, Zuotian; Zhang, Pengyue; Eadon, Michael; Su, Jing; Biostatistics and Health Data Science, School of MedicineChronic kidney disease (CKD) is a common, complex, and heterogeneous disease impacting aging populations. Determining the landscape of disease progression trajectories from midlife to senior age in a real-world context allows us to better understand the progression of CKD, the heterogeneity of progression patterns among the risk population, and the interactions with other clinical conditions like cancers. In this study, we use electronic health records (EHRs) to outline the CKD progression trajectory roadmap for the Wake Forest Baptist Medical Center (WFBMC) patient population. We establish an EHR cohort (n = 79,434) with patients' health status identified by 18 Essential Clinical Indices across 508,732 clinical encounters. We develop the DisEase PrOgression Trajectory (DEPOT) approach to model CKD progression trajectories and individualize clinical decision support. The DEPOT is an evidence-driven, graph-based clinical informatics approach that addresses the unique challenges in longitudinal EHR data by systematically using the graph artificial intelligence (graph-AI) model for representation learning and reverse graph embedding for trajectory reconstruction. Moreover, DEPOT includes a prediction model to assign new patients along the progression trajectory. We successfully establish the EHR-based CKD progression trajectories with DEPOT in the WFUBMC cohort. We annotate the trajectories with clinical features, including kidney function, age, and other indices, including cancer. This CKD progression trajectory roadmap reveals diverse kidney failure pathways associated with different clinical conditions. Specifically, we have identified one high-risk trajectory and two low-risk trajectories. Switching pathways from low-risk trajectories to the high-risk one is associated with accelerated decline in kidney function. On this roadmap, high-risk patients are enriched in the skin and GU cancers, which differs from low-risk patients, suggesting fundamentally different disease progression mechanisms. Overall, the CKD progression trajectory roadmap reveals novel diverse renal failure pathways in type 2 diabetes mellitus and highlights disease progression patterns associated with cancer phenotypes.Item Downregulation of Organic Anion Transporting Polypeptide (OATP) 1B1 Transport Function by Lysosomotropic Drug Chloroquine: Implication in OATP-Mediated Drug-Drug Interactions(ACS, 2016-03) Alam, Khondoker; Pahwa, Sonia; Wang, Xueying; Zhang, Pengyue; Ding, Kai; Abuznait, Alaa H.; Li, Lang; Yue, Wei; Department of Medical & Molecular Genetics, IU School of MedicineOrganic anion transporting polypeptide (OATP) 1B1 mediates the hepatic uptake of many drugs including lipid-lowering statins. Decreased OATP1B1 transport activity is often associated with increased systemic exposure of statins and statin-induced myopathy. Antimalarial drug chloroquine (CQ) is also used for long-term treatment of rheumatoid arthritis and systemic lupus erythematosus. CQ is lysosomotropic and inhibits protein degradation in lysosomes. The current studies were designed to determine the effects of CQ on OATP1B1 protein degradation, OATP1B1-mediated transport in OATP1B1-overexpressing cell line, and statin uptake in human sandwich-cultured hepatocytes (SCH). Treatment with lysosome inhibitor CQ increased OATP1B1 total protein levels in HEK293-OATP1B1 cells and in human SCH as determined by OATP1B1 immunoblot. In HEK293-FLAG-tagged OATP1B1 stable cell line, co-immunofluorescence staining indicated that intracellular FLAG-OATP1B1 is colocalized with lysosomal associated membrane glycoprotein (LAMP)-2, a marker protein of late endosome/lysosome. Enlarged LAMP-2-positive vacuoles with FLAG-OATP1B1 protein retained inside were readily detected in CQ-treated cells, consistent with blocking lysosomal degradation of OATP1B1 by CQ. In HEK293-OATP1B1 cells, without pre-incubation, CQ concentrations up to 100 μM did not affect OATP1B1-mediated [3H]E217G accumulation. However, pre-incubation with CQ at clinically relevant concentration(s) significantly decreased [3H]E217G and [3H]pitavastatin accumulation in HEK293-OATP1B1 cells and [3H]pitavastatin accumulation in human SCH. CQ pretreatment (25 μM, 2 h) resulted in ∼1.9-fold decrease in Vmax without affecting Km of OATP1B1-mediated [3H]E217G transport in HEK293-OATP1B1 cells. Pretreatment with monensin and bafilomycin A1, which also have lysosome inhibition activity, significantly decreased OATP1B1-mediated transport in HEK293-OATP1B1 cells. Pharmacoepidemiologic studies using data from the U.S. Food and Drug Administration Adverse Event Reporting System indicated that CQ plus pitavastatin, rosuvastatin, and pravastatin, which are minimally metabolized by the cytochrome P450 enzymes, led to higher myopathy risk than these statins alone. In summary, the present studies report novel findings that lysosome is involved in degradation of OATP1B1 protein and that pre-incubation with lysosomotropic drug CQ downregulates OATP1B1 transport activity. Our in vitro data in combination with pharmacoepidemiologic studies support that CQ has potential to cause OATP-mediated drug–drug interactions.Item Elucidating Chemotherapy Resistance in Breast Cancer Through Advanced Subpathway Analysis Algorithm: A Novel Approach to Topological Interpretation of Transcriptomic Data(2024-08) Huo, Yang; Yan, Jingwen; Li, Lang; Zhang, Chi; Zhang, Pengyue; Wang, JuexinChemotherapy resistance in breast cancer, particularly Triple-Negative Breast Cancer (TNBC), poses a significant challenge to effective treatment, contributing to high mortality rates. This thesis investigates the molecular mechanisms underlying chemoresistance, focusing on enhancing the granularity of pathway analysis through an innovative sub-pathway analysis algorithm. Traditional pathway analyses, while providing fundamental insights, often overlook the intricate and individual-specific nature of chemoresistance. The research introduces an advanced sub-pathway analysis algorithm that dissects larger pathways into smaller, more detailed sub-pathways, allowing for precise exploration of molecular interactions driving chemoresistance. The methodology involves a comparative analysis of transcriptome profiles from breast cancer patients before and after chemotherapy, utilizing both established and new sub-pathway analytical techniques. This integrative approach aims to uncover previously unrecognized mechanisms of resistance and identify potential biomarkers for chemoresistance. Furthermore, the thesis presents the development of a new algorithm, i-Subway, designed to conduct sub-pathway analyses at the individual sample level. This algorithm incorporates both inhibitory and inductive relationships within sub-pathways and integrates the empirical Bayes statistical model with the topological structure of the sub-pathway, significantly improving computational efficiency. When applied to transcriptomic data from 56 breast cancer cell lines, i-Subway revealed substantial variation at the sub-pathway level, providing deeper insights into the molecular basis of chemoresistance. Overall, this thesis aims to enhance the understanding of the specific pathways and sub-pathways altered in response to chemotherapy, offering new insights into the molecular mechanisms of chemoresistance in breast cancer. The findings are expected to facilitate the identification of novel therapeutic targets and contribute to the development of more effective, individualized treatment strategies.