Browsing by Subject "Pharmacoepidemiology"
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Item Bile acid synthesis, modulation, and dementia: A metabolomic, transcriptomic, and pharmacoepidemiologic study(PLOS, 2021-05-27) Varma, Vijay R.; Wang, Youjin; An, Yang; Varma, Sudhir; Bilgel, Murat; Doshi, Jimit; Legido-Quigley, Cristina; Delgado, João C.; Oommen, Anup M.; Roberts, Jackson A.; Wong, Dean F.; Davatzikos, Christos; Resnick, Susan M.; Troncoso, Juan C.; Pletnikova, Olga; O’Brien, Richard; Hak, Eelko; Baak, Brenda N.; Pfeiffer, Ruth; Baloni, Priyanka; Mohmoudiandehkordi, Siamak; Nho, Kwangsik; Kaddurah-Daouk, Rima; Bennett, David A.; Gadalla, Shahinaz M.; Thambisetty, Madhav; Radiology and Imaging Sciences, School of MedicineBackground: While Alzheimer disease (AD) and vascular dementia (VaD) may be accelerated by hypercholesterolemia, the mechanisms underlying this association are unclear. We tested whether dysregulation of cholesterol catabolism, through its conversion to primary bile acids (BAs), was associated with dementia pathogenesis. Methods and findings: We used a 3-step study design to examine the role of the primary BAs, cholic acid (CA), and chenodeoxycholic acid (CDCA) as well as their principal biosynthetic precursor, 7α-hydroxycholesterol (7α-OHC), in dementia. In Step 1, we tested whether serum markers of cholesterol catabolism were associated with brain amyloid accumulation, white matter lesions (WMLs), and brain atrophy. In Step 2, we tested whether exposure to bile acid sequestrants (BAS) was associated with risk of dementia. In Step 3, we examined plausible mechanisms underlying these findings by testing whether brain levels of primary BAs and gene expression of their principal receptors are altered in AD. Step 1: We assayed serum concentrations CA, CDCA, and 7α-OHC and used linear regression and mixed effects models to test their associations with brain amyloid accumulation (N = 141), WMLs, and brain atrophy (N = 134) in the Baltimore Longitudinal Study of Aging (BLSA). The BLSA is an ongoing, community-based cohort study that began in 1958. Participants in the BLSA neuroimaging sample were approximately 46% male with a mean age of 76 years; longitudinal analyses included an average of 2.5 follow-up magnetic resonance imaging (MRI) visits. We used the Alzheimer's Disease Neuroimaging Initiative (ADNI) (N = 1,666) to validate longitudinal neuroimaging results in BLSA. ADNI is an ongoing, community-based cohort study that began in 2003. Participants were approximately 55% male with a mean age of 74 years; longitudinal analyses included an average of 5.2 follow-up MRI visits. Lower serum concentrations of 7α-OHC, CA, and CDCA were associated with higher brain amyloid deposition (p = 0.041), faster WML accumulation (p = 0.050), and faster brain atrophy mainly (false discovery rate [FDR] p = <0.001-0.013) in males in BLSA. In ADNI, we found a modest sex-specific effect indicating that lower serum concentrations of CA and CDCA were associated with faster brain atrophy (FDR p = 0.049) in males.Step 2: In the Clinical Practice Research Datalink (CPRD) dataset, covering >4 million registrants from general practice clinics in the United Kingdom, we tested whether patients using BAS (BAS users; 3,208 with ≥2 prescriptions), which reduce circulating BAs and increase cholesterol catabolism, had altered dementia risk compared to those on non-statin lipid-modifying therapies (LMT users; 23,483 with ≥2 prescriptions). Patients in the study (BAS/LMT) were approximately 34%/38% male and with a mean age of 65/68 years; follow-up time was 4.7/5.7 years. We found that BAS use was not significantly associated with risk of all-cause dementia (hazard ratio (HR) = 1.03, 95% confidence interval (CI) = 0.72-1.46, p = 0.88) or its subtypes. We found a significant difference between the risk of VaD in males compared to females (p = 0.040) and a significant dose-response relationship between BAS use and risk of VaD (p-trend = 0.045) in males.Step 3: We assayed brain tissue concentrations of CA and CDCA comparing AD and control (CON) samples in the BLSA autopsy cohort (N = 29). Participants in the BLSA autopsy cohort (AD/CON) were approximately 50%/77% male with a mean age of 87/82 years. We analyzed single-cell RNA sequencing (scRNA-Seq) data to compare brain BA receptor gene expression between AD and CON samples from the Religious Orders Study and Memory and Aging Project (ROSMAP) cohort (N = 46). ROSMAP is an ongoing, community-based cohort study that began in 1994. Participants (AD/CON) were approximately 56%/36% male with a mean age of 85/85 years. In BLSA, we found that CA and CDCA were detectable in postmortem brain tissue samples and were marginally higher in AD samples compared to CON. In ROSMAP, we found sex-specific differences in altered neuronal gene expression of BA receptors in AD. Study limitations include the small sample sizes in the BLSA cohort and likely inaccuracies in the clinical diagnosis of dementia subtypes in primary care settings. Conclusions: We combined targeted metabolomics in serum and amyloid positron emission tomography (PET) and MRI of the brain with pharmacoepidemiologic analysis to implicate dysregulation of cholesterol catabolism in dementia pathogenesis. We observed that lower serum BA concentration mainly in males is associated with neuroimaging markers of dementia, and pharmacological lowering of BA levels may be associated with higher risk of VaD in males. We hypothesize that dysregulation of BA signaling pathways in the brain may represent a plausible biologic mechanism underlying these results. Together, our observations suggest a novel mechanism relating abnormalities in cholesterol catabolism to risk of dementia.Item Cancer Pharmacogenomics and Pharmacoepidemiology: Setting a Research Agenda to Accelerate Translation(Oxford University Press, 2010-10-13) Freedman, Andrew N.; Sansbury, Leah B.; Figg, William D.; Potosky, Arnold L.; Smith, Sheila R. Weiss; Khoury, Muin J.; Nelson, Stefanie A.; Weinshilboum, Richard M.; Ratain, Mark J.; McLeod, Howard L.; Epstein, Robert S.; Ginsburg, Geoffrey S.; Schilsky, Richard L.; Liu, Geoffrey; Flockhart, David A.; Ulrich, Cornelia M.; Davis, Robert L.; Lesko, Lawrence J.; Zineh, Issam; Randhawa, Gurvaneet; Ambrosone, Christine B.; Relling, Mary V.; Rothman, Nat; Xie, Heng; Spitz, Margaret R.; Ballard-Barbash, Rachel; Doroshow, James H.; Minasian, Lori M.; Medicine, School of MedicineRecent advances in genomic research have demonstrated a substantial role for genomic factors in predicting response to cancer therapies. Researchers in the fields of cancer pharmacogenomics and pharmacoepidemiology seek to understand why individuals respond differently to drug therapy, in terms of both adverse effects and treatment efficacy. To identify research priorities as well as the resources and infrastructure needed to advance these fields, the National Cancer Institute (NCI) sponsored a workshop titled “Cancer Pharmacogenomics: Setting a Research Agenda to Accelerate Translation” on July 21, 2009, in Bethesda, MD. In this commentary, we summarize and discuss five science-based recommendations and four infrastructure-based recommendations that were identified as a result of discussions held during this workshop. Key recommendations include 1) supporting the routine collection of germline and tumor biospecimens in NCI-sponsored clinical trials and in some observational and population-based studies; 2) incorporating pharmacogenomic markers into clinical trials; 3) addressing the ethical, legal, social, and biospecimen- and data-sharing implications of pharmacogenomic and pharmacoepidemiologic research; and 4) establishing partnerships across NCI, with other federal agencies, and with industry. Together, these recommendations will facilitate the discovery and validation of clinical, sociodemographic, lifestyle, and genomic markers related to cancer treatment response and adverse events, and they will improve both the speed and efficiency by which new pharmacogenomic and pharmacoepidemiologic information is translated into clinical practice.Item Comparative risk of severe hypoglycemia among concomitant users of thiazolidinedione antidiabetic agents and antihyperlipidemics(Elsevier, 2016-05) Leonard, Charles E.; Han, Xu; Bilker, Warren B.; Flory, James H.; Brensinger, Colleen M.; Flockhart, David A.; Gagne, Joshua J.; Cardillo, Serena; Hennessy, Sean; Department of Medicine, IU School of MedicineWe conducted high-dimensional propensity score-adjusted cohort studies to examine whether thiazolidinedione use with a statin or fibrate was associated with an increased risk of severe hypoglycemia. We found that concomitant therapy with a thiazolidinedione+fibrate was associated with a generally delayed increased risk of severe hypoglycemia.Item Identification and mechanistic investigation of clinically important myopathic drug-drug interactions(2014) Han, Xu; Flockhart, David A.; Bies, Robert R.; Desta, Zeruesenay; Li, Lang; Queener, Sherry F.; Quinney, Sara K.; Zhang, Jian-TingDrug-drug interactions (DDIs) refer to situations where one drug affects the pharmacokinetics or pharmacodynamics of another. DDIs represent a major cause of morbidity and mortality. A common adverse drug reaction (ADR) that can result from, or be exacerbated by DDIs is drug-induced myopathy. Identifying DDIs and understanding their underlying mechanisms is key to the prevention of undesirable effects of DDIs and to efforts to optimize therapeutic outcomes. This dissertation is dedicated to identification of clinically important myopathic DDIs and to elucidation of their underlying mechanisms. Using data mined from the published cytochrome P450 (CYP) drug interaction literature, 13,197 drug pairs were predicted to potentially interact by pairing a substrate and an inhibitor of a major CYP isoform in humans. Prescribing data for these drug pairs and their associations with myopathy were then examined in a large electronic medical record database. The analyses identified fifteen drug pairs as DDIs significantly associated with an increased risk of myopathy. These significant myopathic DDIs involved clinically important drugs including alprazolam, chloroquine, duloxetine, hydroxychloroquine, loratadine, omeprazole, promethazine, quetiapine, risperidone, ropinirole, trazodone and simvastatin. Data from in vitro experiments indicated that the interaction between quetiapine and chloroquine (risk ratio, RR, 2.17, p-value 5.29E-05) may result from the inhibitory effects of quetiapine on chloroquine metabolism by cytochrome P450s (CYPs). The in vitro data also suggested that the interaction between simvastatin and loratadine (RR 1.6, p-value 4.75E-07) may result from synergistic toxicity of simvastatin and desloratadine, the major metabolite of loratadine, to muscle cells, and from the inhibitory effect of simvastatin acid, the active metabolite of simvastatin, on the hepatic uptake of desloratadine via OATP1B1/1B3. Our data not only identified unknown myopathic DDIs of clinical consequence, but also shed light on their underlying pharmacokinetic and pharmacodynamic mechanisms. More importantly, our approach exemplified a new strategy for identification and investigation of DDIs, one that combined literature mining using bioinformatic algorithms, ADR detection using a pharmacoepidemiologic design, and mechanistic studies employing in vitro experimental models.Item Pharmacogenomically actionable medications in a safety net health care system(2016) Carpenter, Janet S.; Rosenman, Marc B.; Knisely, Mitchell R.; Decker, Brian S.; Levy, Kenneth D.; Flockhart, David A.; IU School of NursingOBJECTIVE: Prior to implementing a trial to evaluate the economic costs and clinical outcomes of pharmacogenetic testing in a large safety net health care system, we determined the number of patients taking targeted medications and their clinical care encounter sites. METHODS: Using 1-year electronic medical record data, we evaluated the number of patients who had started one or more of 30 known pharmacogenomically actionable medications and the number of care encounter sites the patients had visited. RESULTS: Results showed 7039 unique patients who started one or more of the target medications within a 12-month period with visits to 73 care sites within the system. CONCLUSION: Findings suggest that the type of large-scale, multi-drug, multi-gene approach to pharmacogenetic testing we are planning is widely relevant, and successful implementation will require wide-scale education of prescribers and other personnel involved in medication dispensing and handling.Item Severe hypoglycemia in users of sulfonylurea antidiabetic agents and antihyperlipidemics(Wiley, 2016-05) Leonard, Charles E.; Bilker, Warren B.; Brensinger, Colleen M.; Han, Xu; Flory, James H.; Flockhart, David A.; Gagne, Joshua J.; Cardillo, Serena; Hennessy, Sean; Department of Medicine, IU School of MedicineDrug-drug interactions causing severe hypoglycemia due to antidiabetic drugs is a major clinical and public health problem. We assessed whether sulfonylurea use with a statin or fibrate was associated with severe hypoglycemia. We conducted cohort studies of users of glyburide, glipizide, and glimepiride plus a statin or fibrate within a Medicaid population. The outcome was a validated, diagnosis-based algorithm for severe hypoglycemia. Among 592,872 persons newly exposed to a sulfonylurea+antihyperlipidemic, the incidence of severe hypoglycemia was 5.8/100 person-years. Adjusted hazard ratios (HRs) for sulfonylurea+statins were consistent with no association. Most overall HRs for sulfonylurea+fibrate were elevated, with sulfonylurea-specific adjusted HRs as large as 1.50 (95% confidence interval (CI): 1.24-1.81) for glyburide+gemfibrozil, 1.37 (95% CI: 1.11-1.69) for glipizide+gemfibrozil, and 1.63 (95% CI: 1.29-2.06) for glimepiride+fenofibrate. Concomitant therapy with a sulfonylurea and fibrate is associated with an often delayed increased rate of severe hypoglycemia.Item Translational high-dimesional drug interaction discovery and validation using health record databases and pharmacokinetics models(2017-10-31) Chiang, Chien-Wei; Li, Lang; Wu, Huanmei; Liu, Yunlong; Liu, XiaowenPolypharmacy leads to increased risk of drug-drug interactions (DDI’s). In this dissertation, we create a database for quantifying fraction of metabolism (fm) of CYP450 isozymes for FDA approved drugs. A reproducible data collection protocol was developed to extract key information from publicly available in vitro selective CYP enzyme inhibition studies. The fm was then estimated from the curated data. Then, proposed a random control selection approach for nested case-control design for electronical health records (HER) and electronical medical records (EMR) databases. By relaxing the matching by case’s index time restriction, random control dramatically reduces the computational burden compared with traditional control selection approaches. Using the Observational Medical Outcomes Partnership gold standard and an EMR database, random control is demonstrated to have better performances as well. Finally, combining epidemiological studies and pharmacokinetic modeling with fm database, we detected and evaluated high-dimensional drug-drug interactions among thirty high frequency drugs. Multi-drug combinations that increased risk of myopathy were identified in the FAERS and EMR databases by a mixture drug-count response model (MDCM) model. Twenty-eight 3-way and 43 4-way DDI’s increased ratio of area under plasma concentration–time curve (AUCR) >2-fold and had significant myopathy risk in both databases. The predicted AUCR of omeprazole in the presence of fluconazole and clonidine was 9.35; and increased risk of myopathy was 6.41 (LFDR = 0.002) in FAERS and 18.46 (LFDR = 0.005) in EMR. We demonstrate that combining health record informatics and pharmacokinetic modeling is a powerful translational approach to detect high-dimensional DDI’s.