Browsing by Author "Zhang, Juan"

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    Association of the OPRM1 Variant rs1799971 (A118G) with Non-Specific Liability to Substance Dependence in a Collaborative de novo Meta-Analysis of European-Ancestry Cohorts
    (Springer, 2016-03) Schwantes-An, Tae-Hwi; Zhang, Juan; Chen, Li-Shiun; Hartz, Sarah M.; Culverhouse, Robert C.; Chen, Xiangning; Coon, Hilary; Frank, Josef; Kamens, Helen M.; Konte, Bettina; Kovanen, Leena; Latvala, Antti; Legrand, Lisa N.; Maher, Brion S.; Melroy, Whitney E.; Nelson, Elliot C.; Reid, Mark W.; Robinson, Jason D.; Shen, Pei-Hong; Yang, Bao-Zhu; Andrews, Judy A.; Aveyard, Paul; Beltcheva, Olga; Brown, Sandra A.; Cannon, Dale S.; Cichon, Sven; Corley, Robin P.; Dahmen, Norbert; Degenhardt, Louisa; Foroud, Tatiana; Gaebel, Wolfgang; Giegling, Ina; Glatt, Stephen J.; Grucza, Richard A.; Hardin, Jill; Hartmann, Annette M.; Heath, Andrew C.; Herms, Stefan; Hodgkinson, Colin A.; Hoffmann, Per; Hops, Hyman; Huizinga, David; Ising, Marcus; Johnson, Eric O.; Johnstone, Elaine; Kaneva, Radka P.; Kendler, Kenneth S.; Kiefer, Falk; Kranzler, Henry R.; Krauter, Ken S.; Levran, Orna; Lucae, Susanne; Lynskey, Michael T.; Maier, Wolfgang; Mann, Karl; Martin, Nicholas G.; Mattheisen, Manuel; Montgomery, Grant W.; Müller-Myhsok, Bertram; Murphy, Michael F.; Neale, Michael C.; Nikolov, Momchil A.; Nishita, Denise; Nöthen, Markus M.; Nurnberger, John; Partonen, Timo; Pergadia, Michele L.; Reynolds, Maureen; Ridinger, Monika; Rose, Richard J.; Rouvinen-Lagerström, Noora; Scherbaum, Norbert; Schmäl, Christine; Soyka, Michael; Stallings, Michael C.; Steffens, Michael; Treutlein, Jens; Tsuang, Ming; Wallace, Tamara L.; Wodarz, Norbert; Yuferov, Vadim; Zill, Peter; Bergen, Andrew W.; Chen, Jingchun; Cinciripini, Paul M.; Edenberg, Howard J.; Ehringer, Marissa A.; Ferrell, Robert E.; Gelernter, Joel; Goldman, David; Hewitt, John K.; Hopfer, Christian J.; Iacono, William G.; Kaprio, Jaakko; Kreek, Mary Jeanne; Kremensky, Ivo M.; Madden, Pamela A.F.; McGue, Matt; Munafò, Marcus R.; Philibert, Robert A.; Rietschel, Marcella; Roy, Alec; Rujescu, Dan; Saarikoski, Sirkku T.; Swan, Gary E.; Todorov, Alexandre A.; Vanyukov, Michael M.; Weiss, Robert B.; Bierut, Laura J.; Saccone, Nancy L.; Department of Medical & Molecular Genetics, IU School of Medicine
    The mu1 opioid receptor gene, OPRM1, has long been a high-priority candidate for human genetic studies of addiction. Because of its potential functional significance, the non-synonymous variant rs1799971 (A118G, Asn40Asp) in OPRM1 has been extensively studied, yet its role in addiction has remained unclear, with conflicting association findings. To resolve the question of what effect, if any, rs1799971 has on substance dependence risk, we conducted collaborative meta-analyses of 25 datasets with over 28,000 European-ancestry subjects. We investigated non-specific risk for "general" substance dependence, comparing cases dependent on any substance to controls who were non-dependent on all assessed substances. We also examined five specific substance dependence diagnoses: DSM-IV alcohol, opioid, cannabis, and cocaine dependence, and nicotine dependence defined by the proxy of heavy/light smoking (cigarettes-per-day >20 vs. ≤ 10). The G allele showed a modest protective effect on general substance dependence (OR = 0.90, 95% C.I. [0.83-0.97], p value = 0.0095, N = 16,908). We observed similar effects for each individual substance, although these were not statistically significant, likely because of reduced sample sizes. We conclude that rs1799971 contributes to mechanisms of addiction liability that are shared across different addictive substances. This project highlights the benefits of examining addictive behaviors collectively and the power of collaborative data sharing and meta-analyses.
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    Complementary Embryonic and Adult Cell Populations Enhance Myocardial Repair in Rat Myocardial Injury Model
    (Hindawi, 2019-11-03) Li Calzi, Sergio; Cook, Todd; Della Rocca, Domenico G.; Zhang, Juan; Shenoy, Vinayak; Yan, Yuanqing; Espejo, Andrew; Rathinasabapathy, Anandharajan; Jacobsen, Max H.; Salazar, Tatiana; Sandusky, George E.; Shaw, Lynn C.; March, Keith; Raizada, Mohan K.; Pepine, Carl J.; Katovich, Michael J.; Grant, Maria B.; Medicine, School of Medicine
    We compared the functional outcome of Isl-1+ cardiac progenitors, CD90+ bone marrow-derived progenitor cells, and the combination of the two in a rat myocardial infarction (MI) model. Isl-1+ cells were isolated from embryonic day 12.5 (E12.5) rat hearts and expanded in vitro. Thy-1+/CD90+ cells were isolated from the bone marrow of adult Sprague-Dawley rats by immunomagnetic cell sorting. Six-week-old female Sprague-Dawley rats underwent permanent left anterior descending (LAD) coronary artery ligation and received intramyocardial injection of either saline, Isl-1+ cells, CD90+ cells, or a combination of Isl-1+ and CD90+ cells, at the time of infarction. Cells were delivered transepicardially to the peri-infarct zone. Left ventricular function was assessed by transthoracic echocardiography at 1- and 4-week post-MI and by Millar catheterization (-dP/dt and +dP/dt) at 4-week post-MI. Fluorescence in situ hybridization (Isl-1+cells) and monochrystalline iron oxide nanoparticles labeling (MION; CD90+ cells) were performed to assess biodistribution of transplanted cells. Only the combination of cells demonstrated a significant improvement of cardiac function as assessed by anterior wall contractility, dP/dt (max), and dP/dt (min), compared to Isl-1+ or CD90+ cell monotherapies. In the combination cell group, viable cells were detected at week 4 when anterior wall motion was completely restored. In conclusion, the combination of Isl-1+ cardiac progenitors and adult bone marrow-derived CD90+ cells shows prolonged and robust myocardial tissue repair and provides support for the use of complementary cell populations to enhance myocardial repair.
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    Nomogram for prediction of portal vein system thrombosis after splenectomy for hypersplenism in patients with Wilson disease
    (APM, 2022-12-28) Yao, Yu; Zhang, Juan; Jiang, Huaizhou; Li, Rui; Xie, Daojun; Jiang, Feng; Zhang, Wanqiu; Ma, Min; Biology, School of Science
    Background: The occurrence of portal vein system thrombosis (PVST) after splenectomy in patients with Wilson disease (WD) can lead to serious complications. The early identification of high-risk patients can help improve patient prognosis. This study aimed to establish and validate a personalized nomogram for assessing the risk of PVST after splenectomy in patients with WD and hypersplenism. Methods: We retrospectively collected the data from 81 patients with WD and hypersplenism who underwent splenectomy. Based on whether PVST occurred within a month after the operation, they were divided into the PVST group and the non-PVST group. The clinical data of the 2 groups were compared, and univariate analysis was used to select the statistically significant features and incorporated into the least absolute shrinkage and selection operator (LASSO) regression model for optimization. Multivariate logistic regression analysis was used to determine the independent risk factors for PVST after splenectomy, which were then applied to establish a personalized nomogram. We calculated the concordance (C)-index and drew the receiver operating characteristic (ROC) curve, the model calibration curve, and the clinical decision analysis (DCA) curve to evaluate the accuracy, calibration, and clinical applicability of the model, respectively. We used bootstrapping for internal validation of the model. Results: Univariate analysis showed that the differences in preoperative portal vein diameter and velocity of portal blood flow, postoperative mean platelet volume (MPV), mean platelet distribution width (PDW), D-dimer, prothrombin time (PT), and the increase of platelet count (PLT) were of statistical significance (P<0.05). According to the results of the LASSO and multivariate logistic regression analyses, a model including preoperative portal vein diameter, preoperative portal blood flow velocity, postoperative D-dimer, and the increase of PLT was established to predict the risk of PVST after splenectomy. The model showed good accuracy with a C-index of 0.838 (95% CI: 0.750–0.926) and had a well-fitted calibration curve. Furthermore, internal validation showed it achieved a moderate C-index of 0.805. The DCA curve indicated that the model has clinical applicability when patients are treated at thresholds of 2–100%. Conclusions: Establishing a predictive model for the risk of PVST in patients with WD and hypersplenism after splenectomy can help clinicians identify patients at high risk of PVST who require intervention measures.