Kyungho Jang1, Tao Tong2, Jinhui Lee3, Taesun Park3, Howard Lee4,5. 1. Center for Clinical Pharmacology, Biomedical Research Institute, Jeonbuk National University Hospital, Jeonju, Republic of Korea. 2. Beijing Advanced Innovation Center for Food Nutrition and Human Health, College of Food Science and Nutritional Engineering, China Agricultural University, Beijing, China. 3. Department of Food and Nutrition, Brain Korea 21 PLUS Project, Yonsei University, Seoul, Republic of Korea. 4. Department of Clinical Pharmacology and Therapeutics, Seoul National University College of Medicine and Hospital, Seoul, Republic of Korea, howardlee@snu.ac.kr. 5. Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, Republic of Korea, howardlee@snu.ac.kr.
Abstract
INTRODUCTION: Gene expression profiles in human peripheral blood mononuclear cells (PBMCs) may act as a useful tool to better understand obesity. We investigated gene expression levels in PMBCs for possible differences between obese and non-obese subjects (19-55 years) and evaluated correlations between gene expression in PBMCs and clinical obesity indices. METHODS: Body weight, BMI, fat amount, fat percentage, waist/hip ratio, leptin, and adiponectin levels were determined in 30 obese and 20 non-obese subjects. Expression levels of 19 genes, which were differentially expressed by clinical obesity indices in the PBMCs of high fat-fed rats, were determined in their PBMCs using real-time PCR. RESULTS: The expression of 9 of 19 previously selected genes was significantly correlated with one or more clinical obesity indices. Both TFEC and CCL2 expression were negatively correlated with BMI, fat amount, fat percentage, waist/hip ratio, and leptin concentration. Similarly, TNFAIP2, VCAN, ASSI, IRF1, and HK3 expression negatively correlated with some clinical obesity indices, such as TNFAIP2 for BMI, fat amount, fat percentage, and waist/hip ratio, VCAN for fat amount, fat percentage, and waist/hip ratio, ASS1 for BMI and fat amount, IRF1 for BMI, fat amount, and fat percentage, and HK3 for fat amount. In contrast, both TNF-α and LPL expression were positively correlated with waist/hip ratio. CONCLUSION: We identified 9 of 19 genes in human PBMCs that significantly correlated with one or more clinical obesity indices. Because these genes have a mechanistic basis for the development or progression of obesity and its metabolic derangements, they may help to determine possible underlying mechanisms for obesity.
INTRODUCTION: Gene expression profiles in human peripheral blood mononuclear cells (PBMCs) may act as a useful tool to better understand obesity. We investigated gene expression levels in PMBCs for possible differences between obese and non-obese subjects (19-55 years) and evaluated correlations between gene expression in PBMCs and clinical obesity indices. METHODS: Body weight, BMI, fat amount, fat percentage, waist/hip ratio, leptin, and adiponectin levels were determined in 30 obese and 20 non-obese subjects. Expression levels of 19 genes, which were differentially expressed by clinical obesity indices in the PBMCs of high fat-fed rats, were determined in their PBMCs using real-time PCR. RESULTS: The expression of 9 of 19 previously selected genes was significantly correlated with one or more clinical obesity indices. Both TFEC and CCL2 expression were negatively correlated with BMI, fat amount, fat percentage, waist/hip ratio, and leptin concentration. Similarly, TNFAIP2, VCAN, ASSI, IRF1, and HK3 expression negatively correlated with some clinical obesity indices, such as TNFAIP2 for BMI, fat amount, fat percentage, and waist/hip ratio, VCAN for fat amount, fat percentage, and waist/hip ratio, ASS1 for BMI and fat amount, IRF1 for BMI, fat amount, and fat percentage, and HK3 for fat amount. In contrast, both TNF-α and LPL expression were positively correlated with waist/hip ratio. CONCLUSION: We identified 9 of 19 genes in human PBMCs that significantly correlated with one or more clinical obesity indices. Because these genes have a mechanistic basis for the development or progression of obesity and its metabolic derangements, they may help to determine possible underlying mechanisms for obesity.
Authors: Michael E Burczynski; Ron L Peterson; Natalie C Twine; Krystyna A Zuberek; Brendan J Brodeur; Lori Casciotti; Vasu Maganti; Padma S Reddy; Andrew Strahs; Fred Immermann; Walter Spinelli; Ulrich Schwertschlag; Anna M Slager; Monette M Cotreau; Andrew J Dorner Journal: J Mol Diagn Date: 2006-02 Impact factor: 5.568
Authors: Victoria Catalán; Javier Gómez-Ambrosi; Beatriz Ramirez; Fernando Rotellar; Carlos Pastor; Camilo Silva; Amaia Rodríguez; María J Gil; Javier A Cienfuegos; Gema Frühbeck Journal: Obes Surg Date: 2007-11 Impact factor: 4.129
Authors: Marie Ng; Tom Fleming; Margaret Robinson; Blake Thomson; Nicholas Graetz; Christopher Margono; Erin C Mullany; Stan Biryukov; Cristiana Abbafati; Semaw Ferede Abera; Jerry P Abraham; Niveen M E Abu-Rmeileh; Tom Achoki; Fadia S AlBuhairan; Zewdie A Alemu; Rafael Alfonso; Mohammed K Ali; Raghib Ali; Nelson Alvis Guzman; Walid Ammar; Palwasha Anwari; Amitava Banerjee; Simon Barquera; Sanjay Basu; Derrick A Bennett; Zulfiqar Bhutta; Jed Blore; Norberto Cabral; Ismael Campos Nonato; Jung-Chen Chang; Rajiv Chowdhury; Karen J Courville; Michael H Criqui; David K Cundiff; Kaustubh C Dabhadkar; Lalit Dandona; Adrian Davis; Anand Dayama; Samath D Dharmaratne; Eric L Ding; Adnan M Durrani; Alireza Esteghamati; Farshad Farzadfar; Derek F J Fay; Valery L Feigin; Abraham Flaxman; Mohammad H Forouzanfar; Atsushi Goto; Mark A Green; Rajeev Gupta; Nima Hafezi-Nejad; Graeme J Hankey; Heather C Harewood; Rasmus Havmoeller; Simon Hay; Lucia Hernandez; Abdullatif Husseini; Bulat T Idrisov; Nayu Ikeda; Farhad Islami; Eiman Jahangir; Simerjot K Jassal; Sun Ha Jee; Mona Jeffreys; Jost B Jonas; Edmond K Kabagambe; Shams Eldin Ali Hassan Khalifa; Andre Pascal Kengne; Yousef Saleh Khader; Young-Ho Khang; Daniel Kim; Ruth W Kimokoti; Jonas M Kinge; Yoshihiro Kokubo; Soewarta Kosen; Gene Kwan; Taavi Lai; Mall Leinsalu; Yichong Li; Xiaofeng Liang; Shiwei Liu; Giancarlo Logroscino; Paulo A Lotufo; Yuan Lu; Jixiang Ma; Nana Kwaku Mainoo; George A Mensah; Tony R Merriman; Ali H Mokdad; Joanna Moschandreas; Mohsen Naghavi; Aliya Naheed; Devina Nand; K M Venkat Narayan; Erica Leigh Nelson; Marian L Neuhouser; Muhammad Imran Nisar; Takayoshi Ohkubo; Samuel O Oti; Andrea Pedroza; Dorairaj Prabhakaran; Nobhojit Roy; Uchechukwu Sampson; Hyeyoung Seo; Sadaf G Sepanlou; Kenji Shibuya; Rahman Shiri; Ivy Shiue; Gitanjali M Singh; Jasvinder A Singh; Vegard Skirbekk; Nicolas J C Stapelberg; Lela Sturua; Bryan L Sykes; Martin Tobias; Bach X Tran; Leonardo Trasande; Hideaki Toyoshima; Steven van de Vijver; Tommi J Vasankari; J Lennert Veerman; Gustavo Velasquez-Melendez; Vasiliy Victorovich Vlassov; Stein Emil Vollset; Theo Vos; Claire Wang; XiaoRong Wang; Elisabete Weiderpass; Andrea Werdecker; Jonathan L Wright; Y Claire Yang; Hiroshi Yatsuya; Jihyun Yoon; Seok-Jun Yoon; Yong Zhao; Maigeng Zhou; Shankuan Zhu; Alan D Lopez; Christopher J L Murray; Emmanuela Gakidou Journal: Lancet Date: 2014-05-29 Impact factor: 79.321