ScholarWorksIndianapolis
  • Communities & Collections
  • Browse ScholarWorks
  • English
  • Català
  • Čeština
  • Deutsch
  • Español
  • Français
  • Gàidhlig
  • Italiano
  • Latviešu
  • Magyar
  • Nederlands
  • Polski
  • Português
  • Português do Brasil
  • Suomi
  • Svenska
  • Türkçe
  • Tiếng Việt
  • Қазақ
  • বাংলা
  • हिंदी
  • Ελληνικά
  • Yкраї́нська
  • Log In
    or
    New user? Click here to register.Have you forgotten your password?
  1. Home
  2. Browse by Author

Browsing by Author "Chen, Brian"

Now showing 1 - 2 of 2
Results Per Page
Sort Options
  • Loading...
    Thumbnail Image
    Item
    A Genome-Wide Association Meta-Analysis of Circulating Sex Hormone–Binding Globulin Reveals Multiple Loci Implicated in Sex Steroid Hormone Regulation
    (Public Library of Science, 2012) Coviello, Andrea D.; Haring, Robin; Wellons, Melissa; Vaidya, Dhananjay; Lehtimäki, Terho; Keildson, Sarah; Lunetta, Kathryn L.; He, Chunyan; Fornage, Myriam; Lagou, Vasiliki; Mangino, Massimo; Onland-Moret, N. Charlotte; Chen, Brian; Eriksson, Joel; Garcia, Melissa; Liu, Yong Mei; Koster, Annemarie; Lohman, Kurt; Lyytikäinen, Leo-Pekka; Petersen, Ann-Kristin; Prescott, Jennifer; Stolk, Lisette; Vandenput, Liesbeth; Wood, Andrew R.; Zhuang, Wei Vivian; Ruokonen, Aimo; Hartikainen, Anna-Liisa; Pouta, Anneli; Bandinelli, Stefania; Biffar, Reiner; Brabant, Georg; Cox, David G.; Chen, Yuhui; Cummings, Steven; Ferrucci, Luigi; Gunter, Marc J.; Hankinson, Susan E.; Martikainen, Hannu; Hofman, Albert; Homuth, Georg; Illig, Thomas; Jansson, John-Olov; Johnson, Andrew D.; Karasik, David; Karlsson, Magnus; Kettunen, Johannes; Kiel, Douglas P.; Kraft, Peter; Liu, Jingmin; Ljunggren, Östen; Lorentzon, Mattias; Maggio, Marcello; Markus, Marcello R. P.; Mellström, Dan; Miljkovic, Iva; Mirel, Daniel; Nelson, Sarah; Papunen, Laure Morin; Peeters, Petra H. M.; Prokopenko, Inga; Raffel, Leslie; Reincke, Martin; Reiner, Alex P.; Rexrode, Kathryn; Rivadeneira, Fernando; Schwartz, Stephen M.; Siscovick, David; Soranzo, Nicole; Stöckl, Doris; Tworoger, Shelley; Uitterlinden, André G.; van Gils, Carla H.; Vasan, Ramachandran S.; Wichmann, H-Erich; Zhai, Guangju; Bhasin, Shalender; Bidlingmaier, Martin; Chanock, Stephen J.; De Vivo, Immaculata; Harris, Tamara B.; Hunter, David J.; Kähönen, Mika; Liu, Simin; Ouyang, Pamela; Spector, Tim D.; van der Schouw, Yvonne T.; Viikari, Jorma; Wallaschofski, Henri; McCarthy, Mark I.; Frayling, Timothy M.; Murray, Anna; Franks, Steve; Järvelin, Marjo-Riitta; de Jong, Frank H.; Raitakari, Olli; Teumer, Alexander; Ohlsson, Claes; Murabito, Joanne M.; Perry, John R. B.; Medicine, School of Medicine
    Sex hormone-binding globulin (SHBG) is a glycoprotein responsible for the transport and biologic availability of sex steroid hormones, primarily testosterone and estradiol. SHBG has been associated with chronic diseases including type 2 diabetes (T2D) and with hormone-sensitive cancers such as breast and prostate cancer. We performed a genome-wide association study (GWAS) meta-analysis of 21,791 individuals from 10 epidemiologic studies and validated these findings in 7,046 individuals in an additional six studies. We identified twelve genomic regions (SNPs) associated with circulating SHBG concentrations. Loci near the identified SNPs included SHBG (rs12150660, 17p13.1, p = 1.8 × 10(-106)), PRMT6 (rs17496332, 1p13.3, p = 1.4 × 10(-11)), GCKR (rs780093, 2p23.3, p = 2.2 × 10(-16)), ZBTB10 (rs440837, 8q21.13, p = 3.4 × 10(-09)), JMJD1C (rs7910927, 10q21.3, p = 6.1 × 10(-35)), SLCO1B1 (rs4149056, 12p12.1, p = 1.9 × 10(-08)), NR2F2 (rs8023580, 15q26.2, p = 8.3 × 10(-12)), ZNF652 (rs2411984, 17q21.32, p = 3.5 × 10(-14)), TDGF3 (rs1573036, Xq22.3, p = 4.1 × 10(-14)), LHCGR (rs10454142, 2p16.3, p = 1.3 × 10(-07)), BAIAP2L1 (rs3779195, 7q21.3, p = 2.7 × 10(-08)), and UGT2B15 (rs293428, 4q13.2, p = 5.5 × 10(-06)). These genes encompass multiple biologic pathways, including hepatic function, lipid metabolism, carbohydrate metabolism and T2D, androgen and estrogen receptor function, epigenetic effects, and the biology of sex steroid hormone-responsive cancers including breast and prostate cancer. We found evidence of sex-differentiated genetic influences on SHBG. In a sex-specific GWAS, the loci 4q13.2-UGT2B15 was significant in men only (men p = 2.5 × 10(-08), women p = 0.66, heterogeneity p = 0.003). Additionally, three loci showed strong sex-differentiated effects: 17p13.1-SHBG and Xq22.3-TDGF3 were stronger in men, whereas 8q21.12-ZBTB10 was stronger in women. Conditional analyses identified additional signals at the SHBG gene that together almost double the proportion of variance explained at the locus. Using an independent study of 1,129 individuals, all SNPs identified in the overall or sex-differentiated or conditional analyses explained ~15.6% and ~8.4% of the genetic variation of SHBG concentrations in men and women, respectively. The evidence for sex-differentiated effects and allelic heterogeneity highlight the importance of considering these features when estimating complex trait variance.
  • Loading...
    Thumbnail Image
    Item
    EndoPRS: Incorporating Endophenotype Information to Improve Polygenic Risk Scores for Clinical Endpoints
    (medRxiv, 2024-05-24) Kharitonova, Elena V.; Sun, Quan; Ockerman, Frank; Chen, Brian; Zhou, Laura Y.; Cao, Hongyuan; Mathias, Rasika A.; Auer, Paul L.; Ober, Carole; Raffield, Laura M.; Reiner, Alexander P.; Cox, Nancy J.; Kelada, Samir; Tao, Ran; Li, Yun; Biostatistics and Health Data Science, Richard M. Fairbanks School of Public Health
    Polygenic risk score (PRS) prediction of complex diseases can be improved by leveraging related phenotypes. This has motivated the development of several multi-trait PRS methods that jointly model information from genetically correlated traits. However, these methods do not account for vertical pleiotropy between traits, in which one trait acts as a mediator for another. Here, we introduce endoPRS, a weighted lasso model that incorporates information from relevant endophenotypes to improve disease risk prediction without making assumptions about the genetic architecture underlying the endophenotype-disease relationship. Through extensive simulation analysis, we demonstrate the robustness of endoPRS in a variety of complex genetic frameworks. We also apply endoPRS to predict the risk of childhood onset asthma in UK Biobank by leveraging a paired GWAS of eosinophil count, a relevant endophenotype. We find that endoPRS significantly improves prediction compared to many existing PRS methods, including multi-trait PRS methods, MTAG and wMT-BLUP, which suggests advantages of endoPRS in real-life clinical settings.
About IU Indianapolis ScholarWorks
  • Accessibility
  • Privacy Notice
  • Copyright © 2025 The Trustees of Indiana University