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Tong X, Liu C, Liang M, Ye X, Deng Z, Zhang X. Screening and validation of differentially expressed genes in adipose tissue of patients with obesity and type 2 diabetes mellitus. BIOMOLECULES & BIOMEDICINE 2024; 24:40-50. [PMID: 37597213 PMCID: PMC10787618 DOI: 10.17305/bb.2023.9498] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Revised: 08/01/2023] [Accepted: 08/01/2023] [Indexed: 08/21/2023]
Abstract
White adipose tissue (WAT) plays a pivotal role in the onset of type 2 diabetes mellitus (T2DM) and obesity. Despite its significance the underlying pathogenesis and key genes associated with it remain elusive. In our study, we screened the differentially expressed genes (DEGs) in intra-abdominal WAT of T2DM patients with obesity, as well as those with simple obesity, aiming to lay a foundational theory for an in-depth investigation of T2DM pathogenesis and the identification of novel therapeutic targets. Gene expression datasets (GSE16415 and GSE71416) were retrieved from the Gene Expression Omnibus (GEO) database. We employed R for screening DEGs and conducted a functional enrichment analysis using the Metascape database. Combined Lasso regression and Boruta feature selection algorithms were used to identify key DEGs. Subsequently, these were cross-verified using the GSE29231 dataset. Samples and medical records were collected from clinical study participants. The mRNA and protein expressions of the key DEGs were verified using qRT-PCR and western blotting, respectively. We discerned a total of 130 DEGs, with 40 being upregulated and 90 downregulated. Functional and pathway enrichment analyses illuminated that these genes are instrumental in mediating metabolite and energy production, neutrophil-mediated immunity, and other associated biological processes. This includes their involvement in the tricarboxylic acid cycle, glycolysis/gluconeogenesis, peroxisome proliferator-activated receptors, and other signalling pathways. Two genes, CIDEA and FSCN1 emerged as key DEGs. The low expression of CIDEA and high expression of FSCN1 in the T2DM and obesity group were verified in clinical samples (P < 0.05). We established that CIDEA and FSCN1 manifest significant differential expression in T2DM patients who are obese. This suggests their potential as risk assessment markers and therapeutic targets for T2DM.
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Affiliation(s)
- Xuewei Tong
- Department of Clinical Laboratory, Hospital of Xinjiang Production and Construction Corps/Second Affiliated Hospital, Medical School of Shihezi University, Urumqi, Xinjiang, China
- Clinical Laboratory Center, People’s Hospital of Xinjiang Uygur Autonomous Region, Urumqi, Xinjiang, China
| | - Chunyan Liu
- Department of Clinical Laboratory, Hospital of Xinjiang Production and Construction Corps/Second Affiliated Hospital, Medical School of Shihezi University, Urumqi, Xinjiang, China
| | - Mengjie Liang
- Department of Clinical Laboratory, Hospital of Xinjiang Production and Construction Corps/Second Affiliated Hospital, Medical School of Shihezi University, Urumqi, Xinjiang, China
| | - Xueyan Ye
- Department of Clinical Laboratory, Hospital of Xinjiang Production and Construction Corps/Second Affiliated Hospital, Medical School of Shihezi University, Urumqi, Xinjiang, China
- Prenatal Diagnosis Center, Urumqi Maternal and Child Health Hospital, Urumqi, Xinjiang, China
| | - Zhaohui Deng
- Department of Clinical Laboratory, Hospital of Xinjiang Production and Construction Corps/Second Affiliated Hospital, Medical School of Shihezi University, Urumqi, Xinjiang, China
| | - Xin Zhang
- Department of Clinical Laboratory, Hospital of Xinjiang Production and Construction Corps/Second Affiliated Hospital, Medical School of Shihezi University, Urumqi, Xinjiang, China
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Rathod YD, Abdelgawad R, Hübner CA, Di Fulvio M. Slc12a2 loss in insulin-secreting β-cells links development of overweight and metabolic dysregulation to impaired satiation control of feeding. Am J Physiol Endocrinol Metab 2023; 325:E581-E594. [PMID: 37819196 PMCID: PMC10864024 DOI: 10.1152/ajpendo.00197.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 10/02/2023] [Accepted: 10/02/2023] [Indexed: 10/13/2023]
Abstract
Male mice lacking the Na+-K+-2Cl- cotransporter Slc12a2 (Nkcc1) specifically in insulin-secreting β-cells (Slc12a2βKO) have reduced β-cell mass and mild β-cell secretory dysfunction associated with overweight, glucose intolerance, insulin resistance, and metabolic abnormalities. Here, we confirmed and extended previous results to female Slc12a2βKO mice, which developed a similar metabolic syndrome-like phenotype as males, albeit milder. Notably, male and female Slc12a2βKO mice developed overweight without consuming excess calories. Analysis of the feeding microstructure revealed that young lean Slc12a2βKO male mice ate meals of higher caloric content and at a relatively lower frequency than normal mice, particularly during the night. In addition, overweight Slc12a2βKO mice consumed significantly larger meals than lean mice. Therefore, the reduced satiation control of feeding precedes the onset of overweight and is worsened in older Slc12a2βKO mice. However, the time spent between meals remained intact in lean and overweight Slc12a2βKO mice, indicating conserved satiety responses to ad libitum feeding. Nevertheless, satiety was intensified during and after refeeding only in overweight males. In lean females, satiety responses to refeeding were delayed relative to age- and body weight-matched control mice but normalized in overweight mice. Since meal size did not change during refeeding, these data suggested that the satiety control of eating after fasting is impaired in lean Slc12a2βKO mice before the onset of overweight and independently of their reduced satiation responses. Therefore, our results support the novel hypothesis that reduced satiation precedes the onset of overweight and the development of metabolic dysregulation.NEW & NOTEWORTHY Obesity, defined as excess fat accumulation, increases the absolute risk for metabolic diseases. Although obesity is usually attributed to increased food intake, we demonstrate that body weight gain can be hastened without consuming excess calories. In fact, impaired meal termination control, i.e., satiation, is detectable before the development of overweight in an animal model that develops a metabolic syndrome-like phenotype.
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Affiliation(s)
- Yakshkumar Dilipbhai Rathod
- Department of Pharmacology and Toxicology, School of Medicine Dayton, Wright State University, Ohio, United States
| | - Rana Abdelgawad
- Department of Pharmacology and Toxicology, School of Medicine Dayton, Wright State University, Ohio, United States
| | - Christian A Hübner
- Institut für Humangenetik Am Klinikum 1, Universitätsklinikum Jena, Jena, Germany
| | - Mauricio Di Fulvio
- Department of Pharmacology and Toxicology, School of Medicine Dayton, Wright State University, Ohio, United States
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Wang F, Zha Z, He Y, Li J, Zhong Z, Xiao Q, Tan Z. Genome-Wide Re-Sequencing Data Reveals the Population Structure and Selection Signatures of Tunchang Pigs in China. Animals (Basel) 2023; 13:1835. [PMID: 37889708 PMCID: PMC10252034 DOI: 10.3390/ani13111835] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2023] [Revised: 05/26/2023] [Accepted: 05/30/2023] [Indexed: 09/29/2023] Open
Abstract
Tunchang pig is one population of Hainan pig in the Hainan Province of China, with the characteristics of delicious meat, strong adaptability, and high resistance to diseases. To explore the genetic diversity and population structure of Tunchang pigs and uncover their germplasm characteristics, 10 unrelated Tunchang pigs were re-sequenced using the Illumina NovaSeq 150 bp paired-end platform with an average depth of 10×. Sequencing data from 36 individuals of 7 other pig breeds (including 4 local Chinese pig breeds (5 Jinhua, 5 Meishan, 5 Rongchang, and 6 Wuzhishan), and 3 commonly used commercial pig breeds (5 Duorc, 5 Landrace, and 5 Large White)) were downloaded from the NCBI public database. After analysis of genetic diversity and population structure, it has been found that compared to commercial pigs, Tunchang pigs have higher genetic diversity and are genetically close to native Chinese breeds. Three methods, FST, θπ, and XP-EHH, were used to detect selection signals for three breeds of pigs: Tunchang, Duroc, and Landrace. A total of 2117 significantly selected regions and 201 candidate genes were screened. Gene enrichment analysis showed that candidate genes were mainly associated with good adaptability, disease resistance, and lipid metabolism traits. Finally, further screening was conducted to identify potential candidate genes related to phenotypic traits, including meat quality (SELENOV, CBR4, TNNT1, TNNT3, VPS13A, PLD3, SRFBP1, and SSPN), immune regulation (CD48, FBL, PTPRH, GNA14, LOX, SLAMF6, CALCOCO1, IRGC, and ZNF667), growth and development (SYT5, PRX, PPP1R12C, and SMG9), reproduction (LGALS13 and EPG5), vision (SLC9A8 and KCNV2), energy metabolism (ATP5G2), cell migration (EPS8L1), and olfaction (GRK3). In summary, our research results provide a genomic overview of the genetic variation, genetic diversity, and population structure of the Tunchang pig population, which will be valuable for breeding and conservation of Tunchang pigs in the future.
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Affiliation(s)
| | | | | | | | | | - Qian Xiao
- School of Animal Science and Technology, Hainan University, Haikou 570228, China; (F.W.)
| | - Zhen Tan
- School of Animal Science and Technology, Hainan University, Haikou 570228, China; (F.W.)
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Glunk V, Laber S, Sinnott-Armstrong N, Sobreira DR, Strobel SM, Batista TM, Kubitz P, Moud BN, Ebert H, Huang Y, Brandl B, Garbo G, Honecker J, Stirling DR, Abdennur N, Calabuig-Navarro V, Skurk T, Ocvirk S, Stemmer K, Cimini BA, Carpenter AE, Dankel SN, Lindgren CM, Hauner H, Nobrega MA, Claussnitzer M. A non-coding variant linked to metabolic obesity with normal weight affects actin remodelling in subcutaneous adipocytes. Nat Metab 2023; 5:861-879. [PMID: 37253881 DOI: 10.1038/s42255-023-00807-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Accepted: 04/12/2023] [Indexed: 06/01/2023]
Abstract
Recent large-scale genomic association studies found evidence for a genetic link between increased risk of type 2 diabetes and decreased risk for adiposity-related traits, reminiscent of metabolically obese normal weight (MONW) association signatures. However, the target genes and cellular mechanisms driving such MONW associations remain to be identified. Here, we systematically identify the cellular programmes of one of the top-scoring MONW risk loci, the 2q24.3 risk locus, in subcutaneous adipocytes. We identify a causal genetic variant, rs6712203, an intronic single-nucleotide polymorphism in the COBLL1 gene, which changes the conserved transcription factor motif of POU domain, class 2, transcription factor 2, and leads to differential COBLL1 gene expression by altering the enhancer activity at the locus in subcutaneous adipocytes. We then establish the cellular programme under the genetic control of the 2q24.3 MONW risk locus and the effector gene COBLL1, which is characterized by impaired actin cytoskeleton remodelling in differentiating subcutaneous adipocytes and subsequent failure of these cells to accumulate lipids and develop into metabolically active and insulin-sensitive adipocytes. Finally, we show that perturbations of the effector gene Cobll1 in a mouse model result in organismal phenotypes matching the MONW association signature, including decreased subcutaneous body fat mass and body weight along with impaired glucose tolerance. Taken together, our results provide a mechanistic link between the genetic risk for insulin resistance and low adiposity, providing a potential therapeutic hypothesis and a framework for future identification of causal relationships between genome associations and cellular programmes in other disorders.
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Affiliation(s)
- Viktoria Glunk
- Institute of Nutritional Medicine, School of Medicine, Technical University of Munich, Munich, Germany
- ZIEL Institute for Food & Health, Else Kröner-Fresenius-Center for Nutritional Medicine, School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Samantha Laber
- Broad Institute of MIT and Harvard, Medical and Population Genetics Program & Type 2 Diabetes Systems Genomics Initiative, Cambridge, MA, USA
| | - Nasa Sinnott-Armstrong
- Broad Institute of MIT and Harvard, Medical and Population Genetics Program & Type 2 Diabetes Systems Genomics Initiative, Cambridge, MA, USA
- Department of Genetics, Stanford University, Stanford, CA, USA
- Herbold Computational Biology Program, Publich Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Debora R Sobreira
- Department of Human Genetics, University of Chicago, Chicago, IL, USA
| | - Sophie M Strobel
- Institute of Nutritional Medicine, School of Medicine, Technical University of Munich, Munich, Germany
- ZIEL Institute for Food & Health, Else Kröner-Fresenius-Center for Nutritional Medicine, School of Life Sciences, Technical University of Munich, Freising, Germany
- Broad Institute of MIT and Harvard, Medical and Population Genetics Program & Type 2 Diabetes Systems Genomics Initiative, Cambridge, MA, USA
| | - Thiago M Batista
- Broad Institute of MIT and Harvard, Medical and Population Genetics Program & Type 2 Diabetes Systems Genomics Initiative, Cambridge, MA, USA
- Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Phil Kubitz
- Institute of Nutritional Medicine, School of Medicine, Technical University of Munich, Munich, Germany
- ZIEL Institute for Food & Health, Else Kröner-Fresenius-Center for Nutritional Medicine, School of Life Sciences, Technical University of Munich, Freising, Germany
- Broad Institute of MIT and Harvard, Medical and Population Genetics Program & Type 2 Diabetes Systems Genomics Initiative, Cambridge, MA, USA
- Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Bahareh Nemati Moud
- Institute of Nutritional Medicine, School of Medicine, Technical University of Munich, Munich, Germany
- ZIEL Institute for Food & Health, Else Kröner-Fresenius-Center for Nutritional Medicine, School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Hannah Ebert
- Institute of Nutritional Sciences, University of Hohenheim, Stuttgart, Germany
| | - Yi Huang
- Broad Institute of MIT and Harvard, Medical and Population Genetics Program & Type 2 Diabetes Systems Genomics Initiative, Cambridge, MA, USA
- Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Beate Brandl
- Institute of Nutritional Medicine, School of Medicine, Technical University of Munich, Munich, Germany
- ZIEL Institute for Food & Health, Else Kröner-Fresenius-Center for Nutritional Medicine, School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Garrett Garbo
- Broad Institute of MIT and Harvard, Medical and Population Genetics Program & Type 2 Diabetes Systems Genomics Initiative, Cambridge, MA, USA
| | - Julius Honecker
- Institute of Nutritional Medicine, School of Medicine, Technical University of Munich, Munich, Germany
- ZIEL Institute for Food & Health, Else Kröner-Fresenius-Center for Nutritional Medicine, School of Life Sciences, Technical University of Munich, Freising, Germany
| | - David R Stirling
- Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Nezar Abdennur
- Institute for Medical Engineering and Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Virtu Calabuig-Navarro
- Broad Institute of MIT and Harvard, Medical and Population Genetics Program & Type 2 Diabetes Systems Genomics Initiative, Cambridge, MA, USA
- Institute of Nutritional Sciences, University of Hohenheim, Stuttgart, Germany
| | - Thomas Skurk
- Institute of Nutritional Medicine, School of Medicine, Technical University of Munich, Munich, Germany
- ZIEL Institute for Food & Health, Else Kröner-Fresenius-Center for Nutritional Medicine, School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Soeren Ocvirk
- Division of Gastroenterology, Hepatology and Nutrition, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Intestinal Microbiology Research Group, Department of Molecular Toxicology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
| | - Kerstin Stemmer
- Molecular Cell Biology, Institute for Theoretical Medicine, University of Augsburg, Augsburg, Germany
- Institute for Diabetes and Obesity, Helmholtz Zentrum München, Neuherberg, Germany
- German Center for Diabetes Research, Neuherberg, Germany
| | - Beth A Cimini
- Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Anne E Carpenter
- Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Simon N Dankel
- Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Cecilia M Lindgren
- Broad Institute of MIT and Harvard, Medical and Population Genetics Program & Type 2 Diabetes Systems Genomics Initiative, Cambridge, MA, USA
- Big Data Institute at the Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
| | - Hans Hauner
- Institute of Nutritional Medicine, School of Medicine, Technical University of Munich, Munich, Germany
- ZIEL Institute for Food & Health, Else Kröner-Fresenius-Center for Nutritional Medicine, School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Marcelo A Nobrega
- Department of Human Genetics, University of Chicago, Chicago, IL, USA
| | - Melina Claussnitzer
- Broad Institute of MIT and Harvard, Medical and Population Genetics Program & Type 2 Diabetes Systems Genomics Initiative, Cambridge, MA, USA.
- Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
- Department of Medicine, Harvard Medical School, Boston, MA, USA.
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Streicher SA, Lim U, Park SL, Li Y, Sheng X, Hom V, Xia L, Pooler L, Shepherd J, Loo LWM, Ernst T, Buchthal S, Franke AA, Tiirikainen M, Wilkens LR, Haiman CA, Stram DO, Cheng I, Le Marchand L. Genome-wide association study of abdominal MRI-measured visceral fat: The multiethnic cohort adiposity phenotype study. PLoS One 2023; 18:e0279932. [PMID: 36607984 PMCID: PMC9821421 DOI: 10.1371/journal.pone.0279932] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Accepted: 12/16/2022] [Indexed: 01/07/2023] Open
Abstract
Few studies have explored the genetic underpinnings of intra-abdominal visceral fat deposition, which varies substantially by sex and race/ethnicity. Among 1,787 participants in the Multiethnic Cohort (MEC)-Adiposity Phenotype Study (MEC-APS), we conducted a genome-wide association study (GWAS) of the percent visceral adiposity tissue (VAT) area out of the overall abdominal area, averaged across L1-L5 (%VAT), measured by abdominal magnetic resonance imaging (MRI). A genome-wide significant signal was found on chromosome 2q14.3 in the sex-combined GWAS (lead variant rs79837492: Beta per effect allele = -4.76; P = 2.62 × 10-8) and in the male-only GWAS (lead variant rs2968545: (Beta = -6.50; P = 1.09 × 10-9), and one suggestive variant was found at 13q12.11 in the female-only GWAS (rs79926925: Beta = 6.95; P = 8.15 × 10-8). The negatively associated variants were most common in European Americans (T allele of rs79837492; 5%) and African Americans (C allele of rs2968545; 5%) and not observed in Japanese Americans, whereas the positively associated variant was most common in Japanese Americans (C allele of rs79926925, 5%), which was all consistent with the racial/ethnic %VAT differences. In a validation step among UK Biobank participants (N = 23,699 of mainly British and Irish ancestry) with MRI-based VAT volume, both rs79837492 (Beta = -0.026, P = 0.019) and rs2968545 (Beta = -0.028, P = 0.010) were significantly associated in men only (n = 11,524). In the MEC-APS, the association between rs79926925 and plasma sex hormone binding globulin levels reached statistical significance in females, but not in males, with adjustment for total adiposity (Beta = -0.24; P = 0.028), on the log scale. Rs79837492 and rs2968545 are located in intron 5 of CNTNAP5, and rs79926925, in an intergenic region between GJB6 and CRYL1. These novel findings differing by sex and racial/ethnic group warrant replication in additional diverse studies with direct visceral fat measurements.
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Affiliation(s)
- Samantha A. Streicher
- University of Hawaii Cancer Center, University of Hawaii at Mānoa, Honolulu, Hawaii, United States of America
| | - Unhee Lim
- University of Hawaii Cancer Center, University of Hawaii at Mānoa, Honolulu, Hawaii, United States of America
| | - S. Lani Park
- University of Hawaii Cancer Center, University of Hawaii at Mānoa, Honolulu, Hawaii, United States of America
| | - Yuqing Li
- Department of Epidemiology and Biostatistics, University of California–San Francisco, San Francisco, California, United States of America
| | - Xin Sheng
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, United States of America
| | - Victor Hom
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, United States of America
| | - Lucy Xia
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, United States of America
| | - Loreall Pooler
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, United States of America
| | - John Shepherd
- University of Hawaii Cancer Center, University of Hawaii at Mānoa, Honolulu, Hawaii, United States of America
| | - Lenora W. M. Loo
- University of Hawaii Cancer Center, University of Hawaii at Mānoa, Honolulu, Hawaii, United States of America
| | - Thomas Ernst
- University of Maryland School of Medicine, Baltimore, Maryland, United States of America
| | - Steven Buchthal
- University of Hawaii Cancer Center, University of Hawaii at Mānoa, Honolulu, Hawaii, United States of America
| | - Adrian A. Franke
- University of Hawaii Cancer Center, University of Hawaii at Mānoa, Honolulu, Hawaii, United States of America
| | - Maarit Tiirikainen
- University of Hawaii Cancer Center, University of Hawaii at Mānoa, Honolulu, Hawaii, United States of America
| | - Lynne R. Wilkens
- University of Hawaii Cancer Center, University of Hawaii at Mānoa, Honolulu, Hawaii, United States of America
| | - Christopher A. Haiman
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, United States of America
| | - Daniel O. Stram
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, United States of America
| | - Iona Cheng
- Department of Epidemiology and Biostatistics, University of California–San Francisco, San Francisco, California, United States of America
| | - Loïc Le Marchand
- University of Hawaii Cancer Center, University of Hawaii at Mānoa, Honolulu, Hawaii, United States of America
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Jin M, Fei X, Li T, Lu Z, Chu M, Di R, He X, Wang X, Wei C. Transcriptome study digs out BMP2 involved in adipogenesis in sheep tails. BMC Genomics 2022; 23:457. [PMID: 35725366 PMCID: PMC9210821 DOI: 10.1186/s12864-022-08657-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2022] [Accepted: 05/25/2022] [Indexed: 12/22/2022] Open
Abstract
Background Hu sheep and Tibetan sheep in China are characterized by fat tails and thin tails, respectively. Several transcriptomes have been conducted in different sheep breeds to identify the differentially expressed genes (DEGs) underlying this trait. However, these studies identified different DEGs in different sheep breeds. Results Hence, RNA sequencing was performed on Hu sheep and Tibetan sheep. We obtained a total of 45.57 and 43.82 million sequencing reads, respectively. Two libraries mapped reads from 36.93 and 38.55 million reads after alignment to the reference sequences. 2108 DEGs were identified, including 1247 downregulated and 861 upregulated DEGs. GO and KEGG analyses of all DEGs demonstrated that pathways were enriched in the regulation of lipolysis in adipocytes and terms related to the chemokine signalling pathway, lysosomes, and glycosaminoglycan degradation. Eight genes were selected for validation by RT–qPCR. In addition, the transfection of BMP2 overexpression into preadipocytes resulted in increased PPAR-γ expression and expression. BMP2 potentially induces adipogenesis through LOX in preadipocytes. The number of lipid drops in BMP2 overexpression detected by oil red O staining was also greater than that in the negative control. Conclusion In summary, these results showed that significant genes (BMP2, HOXA11, PPP1CC and LPIN1) are involved in the regulation of adipogenesis metabolism and suggested novel insights into metabolic molecules in sheep fat tails. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-022-08657-8.
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Affiliation(s)
- Meilin Jin
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China.,College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Xiaojuan Fei
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Taotao Li
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Zengkui Lu
- Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou, Gansu, China
| | - Mingxing Chu
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Ran Di
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Xiaoyun He
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Xiangyu Wang
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Caihong Wei
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China.
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7
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Qian Y, Xiong Z, Li Y, Kayser M, Liu L, Liu F. The effects of Tbx15 and Pax1 on facial and other physical morphology in mice. FASEB Bioadv 2021; 3:1011-1019. [PMID: 34938962 PMCID: PMC8664010 DOI: 10.1096/fba.2021-00094] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Revised: 08/19/2021] [Accepted: 08/23/2021] [Indexed: 12/13/2022] Open
Abstract
DNA variants in or close to the human TBX15 and PAX1 genes have been repeatedly associated with facial morphology in independent genome-wide association studies, while their functional roles in determining facial morphology remain to be understood. We generated Tbx15 knockout (Tbx15 -/-) and Pax1 knockout (Pax1 -/-) mice by applying the one-step CRISPR/Cas9 method. A total of 75 adult mice were used for subsequent phenotype analysis, including 38 Tbx15 mice (10 homozygous Tbx15 -/-, 18 heterozygous Tbx15 +/-, 10 wild-type Tbx15 +/+ WT littermates) and 37 Pax1 mice (12 homozygous Pax1 -/-, 15 heterozygous Pax1 +/-, 10 Pax1 +/+ WT littermates). Facial and other physical morphological phenotypes were obtained from three-dimensional (3D) images acquired with the HandySCAN BLACK scanner. Compared to WT littermates, the Tbx15 -/- mutant mice had significantly shorter faces (p = 1.08E-8, R2 = 0.61) and their ears were in a significantly lower position (p = 3.54E-8, R2 = 0.62) manifesting a "droopy ear" characteristic. Besides these face alternations, Tbx15 -/- mutant mice displayed significantly lower weight as well as shorter body and limb length. Pax1 -/- mutant mice showed significantly longer noses (p = 1.14E-5, R2 = 0.46) relative to WT littermates, but otherwise displayed less obvious morphological alterations than Tbx15 -/- mutant mice did. We provide the first direct functional evidence that two well-known and replicated human face genes, Tbx15 and Pax1, impact facial and other body morphology in mice. The general agreement between our findings in knock-out mice with those from previous GWASs suggests that the functional evidence we established here in mice may also be relevant in humans.
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Affiliation(s)
- Yu Qian
- CAS Key Laboratory of Genomic and Precision MedicineBeijing Institute of GenomicsChinese Academy of SciencesBeijingChina
- China National Center for BioinformationBeijingChina
- University of Chinese Academy of SciencesBeijingChina
| | - Ziyi Xiong
- Department of Genetic IdentificationErasmus MC University Medical Center RotterdamRotterdamthe Netherlands
- Department of EpidemiologyErasmus MC University Medical Center RotterdamRotterdamthe Netherlands
| | - Yi Li
- CAS Key Laboratory of Genomic and Precision MedicineBeijing Institute of GenomicsChinese Academy of SciencesBeijingChina
- China National Center for BioinformationBeijingChina
- University of Chinese Academy of SciencesBeijingChina
| | - Manfred Kayser
- Department of Genetic IdentificationErasmus MC University Medical Center RotterdamRotterdamthe Netherlands
| | - Lei Liu
- Department of Plastic and Burn SurgeryThe Second HospitalCheeloo College of MedicineShandong UniversityJinanChina
| | - Fan Liu
- CAS Key Laboratory of Genomic and Precision MedicineBeijing Institute of GenomicsChinese Academy of SciencesBeijingChina
- China National Center for BioinformationBeijingChina
- University of Chinese Academy of SciencesBeijingChina
- Department of Genetic IdentificationErasmus MC University Medical Center RotterdamRotterdamthe Netherlands
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Pan DZ, Miao Z, Comenho C, Rajkumar S, Koka A, Lee SHT, Alvarez M, Kaminska D, Ko A, Sinsheimer JS, Mohlke KL, Mancuso N, Muñoz-Hernandez LL, Herrera-Hernandez M, Tusié-Luna MT, Aguilar-Salinas C, Pietiläinen KH, Pihlajamäki J, Laakso M, Garske KM, Pajukanta P. Identification of TBX15 as an adipose master trans regulator of abdominal obesity genes. Genome Med 2021; 13:123. [PMID: 34340684 PMCID: PMC8327600 DOI: 10.1186/s13073-021-00939-2] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2020] [Accepted: 07/14/2021] [Indexed: 12/14/2022] Open
Abstract
Background Obesity predisposes individuals to multiple cardiometabolic disorders, including type 2 diabetes (T2D). As body mass index (BMI) cannot reliably differentiate fat from lean mass, the metabolically detrimental abdominal obesity has been estimated using waist-hip ratio (WHR). Waist-hip ratio adjusted for body mass index (WHRadjBMI) in turn is a well-established sex-specific marker for abdominal fat and adiposity, and a predictor of adverse metabolic outcomes, such as T2D. However, the underlying genes and regulatory mechanisms orchestrating the sex differences in obesity and body fat distribution in humans are not well understood. Methods We searched for genetic master regulators of WHRadjBMI by employing integrative genomics approaches on human subcutaneous adipose RNA sequencing (RNA-seq) data (n ~ 1400) and WHRadjBMI GWAS data (n ~ 700,000) from the WHRadjBMI GWAS cohorts and the UK Biobank (UKB), using co-expression network, transcriptome-wide association study (TWAS), and polygenic risk score (PRS) approaches. Finally, we functionally verified our genomic results using gene knockdown experiments in a human primary cell type that is critical for adipose tissue function. Results Here, we identified an adipose gene co-expression network that contains 35 obesity GWAS genes and explains a significant amount of polygenic risk for abdominal obesity and T2D in the UKB (n = 392,551) in a sex-dependent way. We showed that this network is preserved in the adipose tissue data from the Finnish Kuopio Obesity Study and Mexican Obesity Study. The network is controlled by a novel adipose master transcription factor (TF), TBX15, a WHRadjBMI GWAS gene that regulates the network in trans. Knockdown of TBX15 in human primary preadipocytes resulted in changes in expression of 130 network genes, including the key adipose TFs, PPARG and KLF15, which were significantly impacted (FDR < 0.05), thus functionally verifying the trans regulatory effect of TBX15 on the WHRadjBMI co-expression network. Conclusions Our study discovers a novel key function for the TBX15 TF in trans regulating an adipose co-expression network of 347 adipose, mitochondrial, and metabolically important genes, including PPARG, KLF15, PPARA, ADIPOQ, and 35 obesity GWAS genes. Thus, based on our converging genomic, transcriptional, and functional evidence, we interpret the role of TBX15 to be a main transcriptional regulator in the adipose tissue and discover its importance in human abdominal obesity. Supplementary Information The online version contains supplementary material available at 10.1186/s13073-021-00939-2.
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Affiliation(s)
- David Z Pan
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, USA.,Bioinformatics Interdepartmental Program, UCLA, Los Angeles, USA
| | - Zong Miao
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, USA.,Bioinformatics Interdepartmental Program, UCLA, Los Angeles, USA
| | - Caroline Comenho
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, USA
| | - Sandhya Rajkumar
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, USA.,Computational and Systems Biology Interdepartmental Program, UCLA, Los Angeles, USA
| | - Amogha Koka
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, USA
| | - Seung Hyuk T Lee
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, USA
| | - Marcus Alvarez
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, USA
| | - Dorota Kaminska
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, USA.,Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland
| | - Arthur Ko
- Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, USA
| | - Janet S Sinsheimer
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, USA.,Department of Computational Medicine, David Geffen School of Medicine at UCLA, Los Angeles, USA
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Nicholas Mancuso
- Center for Genetic Epidemiology, Department of Preventative Medicine, Keck School of Medicine, University of Southern California, Los Angeles, USA
| | - Linda Liliana Muñoz-Hernandez
- Tecnologico de Monterrey, Escuela de Medicina y Ciencias de la Salud, Ave. Morones Prieto 3000, Monterrey, N.L., México, 64710.,Unidad de Investigación de Enfermedades Metabólicas, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico.,Departamento de Endocrinología y Metabolismo del Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Miguel Herrera-Hernandez
- Departamento de Cirugía, Instituto Nacional de Ciencias Médicas y Nutrición, Mexico City, Mexico
| | - Maria Teresa Tusié-Luna
- Unidad de Biología Molecular y Medicina Genómica, Instituto de Investigaciones Biomédicas UNAM/ Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Carlos Aguilar-Salinas
- Unidad de Investigación de Enfermedades Metabólicas, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico.,Departamento de Endocrinología y Metabolismo del Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Kirsi H Pietiläinen
- Obesity Research Unit, Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland.,Obesity Center, Endocrinology, Abdominal Center, Helsinki University Central Hospital and University of Helsinki, Helsinki, Finland
| | - Jussi Pihlajamäki
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland.,Department of Medicine, Endocrinology and Clinical Nutrition, Kuopio University Hospital, Kuopio, Finland
| | - Markku Laakso
- Department of Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Kristina M Garske
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, USA
| | - Päivi Pajukanta
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, USA. .,Bioinformatics Interdepartmental Program, UCLA, Los Angeles, USA. .,Institute for Precision Health at UCLA, Los Angeles, USA.
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9
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Zayed MA, Jin X, Yang C, Belaygorod L, Engel C, Desai K, Harroun N, Saffaf O, Patterson BW, Hsu FF, Semenkovich CF. CEPT1-Mediated Phospholipogenesis Regulates Endothelial Cell Function and Ischemia-Induced Angiogenesis Through PPARα. Diabetes 2021; 70:549-561. [PMID: 33214136 PMCID: PMC7881870 DOI: 10.2337/db20-0635] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/15/2020] [Accepted: 11/12/2020] [Indexed: 11/13/2022]
Abstract
De novo phospholipogenesis, mediated by choline-ethanolamine phosphotransferase 1 (CEPT1), is essential for phospholipid activation of transcription factors such as peroxisome proliferator-activated receptor α (PPARα) in the liver. Fenofibrate, a PPARα agonist and lipid-lowering agent, decreases amputation incidence in patients with diabetes. Because we previously observed that CEPT1 is elevated in carotid plaque of patients with diabetes, we evaluated the role of CEPT1 in peripheral arteries and PPARα phosphorylation (Ser12). CEPT1 was found to be elevated in diseased lower-extremity arterial intima of individuals with peripheral arterial disease and diabetes. To evaluate the role of Cept1 in the endothelium, we engineered a conditional endothelial cell (EC)-specific deletion of Cept1 via induced VE-cadherin-CreERT2-mediated recombination (Cept1Lp/LpCre +). Cept1Lp/LpCre + ECs demonstrated decreased proliferation, migration, and tubule formation, and Cept1Lp/LpCre + mice had reduced perfusion and angiogenesis in ischemic hind limbs. Peripheral ischemic recovery and PPARα signaling were further compromised by streptozotocin-induced diabetes and ameliorated by feeding fenofibrate. Cept1 endoribonuclease-prepared siRNA decreased PPARα phosphorylation in ECs, which was rescued with fenofibrate but not PC16:0/18:1. Unlike Cept1Lp/LpCre + mice, Cept1Lp/LpCre + Ppara -/- mice did not demonstrate hind-paw perfusion recovery after feeding fenofibrate. Therefore, we demonstrate that CEPT1 is essential for EC function and tissue recovery after ischemia and that fenofibrate rescues CEPT1-mediated activation of PPARα.
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Affiliation(s)
- Mohamed A Zayed
- Section of Vascular Surgery, Department of Surgery, Washington University School of Medicine in St. Louis, St. Louis, MO
- Section of Vascular Surgery, Department of Surgery, Washington University School of Medicine in St. Louis, St. Louis, MO
- Section of Vascular Surgery, Department of Surgery, Washington University School of Medicine in St. Louis, St. Louis, MO
- VA St. Louis Health Care System, St. Louis, MO
| | - Xiaohua Jin
- Section of Vascular Surgery, Department of Surgery, Washington University School of Medicine in St. Louis, St. Louis, MO
| | - Chao Yang
- Section of Vascular Surgery, Department of Surgery, Washington University School of Medicine in St. Louis, St. Louis, MO
| | - Larisa Belaygorod
- Section of Vascular Surgery, Department of Surgery, Washington University School of Medicine in St. Louis, St. Louis, MO
| | - Connor Engel
- Section of Vascular Surgery, Department of Surgery, Washington University School of Medicine in St. Louis, St. Louis, MO
| | - Kshitij Desai
- Section of Vascular Surgery, Department of Surgery, Washington University School of Medicine in St. Louis, St. Louis, MO
| | - Nikolai Harroun
- Section of Vascular Surgery, Department of Surgery, Washington University School of Medicine in St. Louis, St. Louis, MO
| | - Omar Saffaf
- Section of Vascular Surgery, Department of Surgery, Washington University School of Medicine in St. Louis, St. Louis, MO
| | - Bruce W Patterson
- Center for Human Nutrition, Department of Medicine, Washington University School of Medicine in St. Louis, St. Louis, MO
| | - Fong-Fu Hsu
- Division of Endocrinology, Metabolism and Lipid Research, Department of Medicine, Washington University School of Medicine in St. Louis, St. Louis, MO
| | - Clay F Semenkovich
- Division of Endocrinology, Metabolism and Lipid Research, Department of Medicine, Washington University School of Medicine in St. Louis, St. Louis, MO
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10
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Li X, Yang J, Shen M, Xie XL, Liu GJ, Xu YX, Lv FH, Yang H, Yang YL, Liu CB, Zhou P, Wan PC, Zhang YS, Gao L, Yang JQ, Pi WH, Ren YL, Shen ZQ, Wang F, Deng J, Xu SS, Salehian-Dehkordi H, Hehua E, Esmailizadeh A, Dehghani-Qanatqestani M, Štěpánek O, Weimann C, Erhardt G, Amane A, Mwacharo JM, Han JL, Hanotte O, Lenstra JA, Kantanen J, Coltman DW, Kijas JW, Bruford MW, Periasamy K, Wang XH, Li MH. Whole-genome resequencing of wild and domestic sheep identifies genes associated with morphological and agronomic traits. Nat Commun 2020; 11:2815. [PMID: 32499537 PMCID: PMC7272655 DOI: 10.1038/s41467-020-16485-1] [Citation(s) in RCA: 124] [Impact Index Per Article: 31.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2019] [Accepted: 05/04/2020] [Indexed: 01/15/2023] Open
Abstract
Understanding the genetic changes underlying phenotypic variation in sheep (Ovis aries) may facilitate our efforts towards further improvement. Here, we report the deep resequencing of 248 sheep including the wild ancestor (O. orientalis), landraces, and improved breeds. We explored the sheep variome and selection signatures. We detected genomic regions harboring genes associated with distinct morphological and agronomic traits, which may be past and potential future targets of domestication, breeding, and selection. Furthermore, we found non-synonymous mutations in a set of plausible candidate genes and significant differences in their allele frequency distributions across breeds. We identified PDGFD as a likely causal gene for fat deposition in the tails of sheep through transcriptome, RT-PCR, qPCR, and Western blot analyses. Our results provide insights into the demographic history of sheep and a valuable genomic resource for future genetic studies and improved genome-assisted breeding of sheep and other domestic animals.
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Affiliation(s)
- Xin Li
- CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences (CAS), Beijing, 100101, China
- University of Chinese Academy of Sciences (UCAS), Beijing, 100049, China
| | - Ji Yang
- CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences (CAS), Beijing, 100101, China
- College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Min Shen
- Institute of Animal Husbandry and Veterinary Medicine, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, 832000, China
- State Key Laboratory of Sheep Genetic Improvement and Healthy Breeding, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, 832000, China
| | - Xing-Long Xie
- CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences (CAS), Beijing, 100101, China
- University of Chinese Academy of Sciences (UCAS), Beijing, 100049, China
| | - Guang-Jian Liu
- Novogene Bioinformatics Institute, Beijing, 100083, China
| | - Ya-Xi Xu
- CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences (CAS), Beijing, 100101, China
- College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Feng-Hua Lv
- CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences (CAS), Beijing, 100101, China
- College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Hua Yang
- Institute of Animal Husbandry and Veterinary Medicine, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, 832000, China
- State Key Laboratory of Sheep Genetic Improvement and Healthy Breeding, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, 832000, China
| | - Yong-Lin Yang
- Institute of Animal Husbandry and Veterinary Medicine, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, 832000, China
- State Key Laboratory of Sheep Genetic Improvement and Healthy Breeding, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, 832000, China
| | - Chang-Bin Liu
- Institute of Animal Husbandry and Veterinary Medicine, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, 832000, China
- State Key Laboratory of Sheep Genetic Improvement and Healthy Breeding, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, 832000, China
| | - Ping Zhou
- Institute of Animal Husbandry and Veterinary Medicine, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, 832000, China
- State Key Laboratory of Sheep Genetic Improvement and Healthy Breeding, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, 832000, China
| | - Peng-Cheng Wan
- Institute of Animal Husbandry and Veterinary Medicine, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, 832000, China
- State Key Laboratory of Sheep Genetic Improvement and Healthy Breeding, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, 832000, China
| | - Yun-Sheng Zhang
- Institute of Animal Husbandry and Veterinary Medicine, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, 832000, China
- State Key Laboratory of Sheep Genetic Improvement and Healthy Breeding, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, 832000, China
| | - Lei Gao
- Institute of Animal Husbandry and Veterinary Medicine, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, 832000, China
- State Key Laboratory of Sheep Genetic Improvement and Healthy Breeding, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, 832000, China
| | - Jing-Quan Yang
- Institute of Animal Husbandry and Veterinary Medicine, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, 832000, China
- State Key Laboratory of Sheep Genetic Improvement and Healthy Breeding, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, 832000, China
| | - Wen-Hui Pi
- Institute of Animal Husbandry and Veterinary Medicine, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, 832000, China
- State Key Laboratory of Sheep Genetic Improvement and Healthy Breeding, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, 832000, China
| | - Yan-Ling Ren
- Shandong Binzhou Academy of Animal Science and Veterinary Medicine, Binzhou, 256600, China
| | - Zhi-Qiang Shen
- Shandong Binzhou Academy of Animal Science and Veterinary Medicine, Binzhou, 256600, China
| | - Feng Wang
- Institute of Sheep and Goat Science, Nanjing Agricultural University, Nanjing, 210095, China
| | - Juan Deng
- CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences (CAS), Beijing, 100101, China
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Song-Song Xu
- CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences (CAS), Beijing, 100101, China
- University of Chinese Academy of Sciences (UCAS), Beijing, 100049, China
| | - Hosein Salehian-Dehkordi
- CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences (CAS), Beijing, 100101, China
- University of Chinese Academy of Sciences (UCAS), Beijing, 100049, China
| | - Eer Hehua
- Grass-Feeding Livestock Engineering Technology Research Center, Ningxia Academy of Agriculture and Forestry Sciences, Yinchuan, China
| | - Ali Esmailizadeh
- Department of Animal Science, Faculty of Agriculture, Shahid Bahonar University of Kerman, Kerman, Iran
| | | | - Ondřej Štěpánek
- Institute of Molecular Genetics of the ASCR, v. v. i., Vídeňská 1083, 142 20, Prague 4, Czech Republic
| | - Christina Weimann
- Institute of Animal Breeding and Genetics, Justus Liebig University, Giessen, Germany
| | - Georg Erhardt
- Institute of Animal Breeding and Genetics, Justus Liebig University, Giessen, Germany
| | - Agraw Amane
- Department of Microbial, Cellular and Molecular Biology, Addis Ababa University, Addis Ababa, Ethiopia
- LiveGene Program, International Livestock Research Institute, Addis Ababa, Ethiopia
| | - Joram M Mwacharo
- Small Ruminant Genomics, International Centre for Agricultural Research in the Dry Areas (ICARDA), Addis Ababa, Ethiopia
| | - Jian-Lin Han
- CAAS-ILRI Joint Laboratory on Livestock and Forage Genetic Resources, Institute of Animal Science, Chinese Academy of Agricultural Sciences (CAAS), Beijing, China
- Livestock Genetics Program, International Livestock Research Institute (ILRI), Nairobi, Kenya
| | - Olivier Hanotte
- LiveGene Program, International Livestock Research Institute, Addis Ababa, Ethiopia
- School of Life Sciences, University of Nottingham, University Park, Nottingham, NG7 2RD, UK
- Center for Tropical Livestock Genetics and Health (CTLGH), the Roslin Institute, University of Edinburgh, Easter Bush, Midlothian, EH25 9RG, Scotland, UK
| | - Johannes A Lenstra
- Faculty of Veterinary Medicine, Utrecht University, Utrecht, the Netherlands
| | - Juha Kantanen
- Production Systems, Natural Resources Institute Finland (Luke), FI-31600, Jokioinen, Finland
| | - David W Coltman
- Department of Biological Sciences, University of Alberta, Edmonton, Alberta, T6G 2E9, Canada
| | - James W Kijas
- CSIRO Livestock Industries, St Lucia, Brisbane, QLD, Australia
| | - Michael W Bruford
- School of Biosciences, Cardiff University, Cathays Park, Cardiff, CF10 3AX, Wales, UK
- Sustainable Places Research Institute, Cardiff University, CF10 3BA, Cardiff, Wales, UK
| | - Kathiravan Periasamy
- Animal Production and Health Laboratory, Joint FAO/IAEA Division of Nuclear Techniques in Food and Agriculture, International Atomic Energy Agency, Vienna, Austria
| | - Xin-Hua Wang
- Institute of Animal Husbandry and Veterinary Medicine, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, 832000, China.
- State Key Laboratory of Sheep Genetic Improvement and Healthy Breeding, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, 832000, China.
| | - Meng-Hua Li
- CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences (CAS), Beijing, 100101, China.
- College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China.
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11
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Gene-Environment Interactions on Body Fat Distribution. Int J Mol Sci 2019; 20:ijms20153690. [PMID: 31357654 PMCID: PMC6696304 DOI: 10.3390/ijms20153690] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2019] [Revised: 07/18/2019] [Accepted: 07/19/2019] [Indexed: 02/08/2023] Open
Abstract
The prevalence of obesity has been increasing markedly in the U.S. and worldwide in the past decades; and notably, the obese populations are signified by not only the overall elevated adiposity but also particularly harmful accumulation of body fat in the central region of the body, namely, abdominal obesity. The profound shift from “traditional” to “obesogenic” environments, principally featured by the abundance of palatable, energy-dense diet, reduced physical activity, and prolonged sedentary time, promotes the obesity epidemics and detrimental body fat distribution. Recent advances in genomics studies shed light on the genetic basis of obesity and body fat distribution. In addition, growing evidence from investigations in large cohorts and clinical trials has lent support to interactions between genetic variations and environmental factors, e.g., diet and lifestyle factors, in relation to obesity and body fat distribution. This review summarizes the recent discoveries from observational studies and randomized clinical trials on the gene–environment interactions on obesity and body fat distribution.
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12
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Coltell O, Asensio EM, Sorlí JV, Barragán R, Fernández-Carrión R, Portolés O, Ortega-Azorín C, Martínez-LaCruz R, González JI, Zanón-Moreno V, Gimenez-Alba I, Fitó M, Ros E, Ordovas JM, Corella D. Genome-Wide Association Study (GWAS) on Bilirubin Concentrations in Subjects with Metabolic Syndrome: Sex-Specific GWAS Analysis and Gene-Diet Interactions in a Mediterranean Population. Nutrients 2019; 11:nu11010090. [PMID: 30621171 PMCID: PMC6356696 DOI: 10.3390/nu11010090] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2018] [Revised: 12/27/2018] [Accepted: 12/27/2018] [Indexed: 01/30/2023] Open
Abstract
Although, for decades, increased serum bilirubin concentrations were considered a threatening sign of underlying liver disease and had been associated with neonatal jaundice, data from recent years show that bilirubin is a powerful antioxidant and suggest that slightly increased serum bilirubin concentrations are protective against oxidative stress-related diseases, such as cardiovascular diseases. Therefore, a better understanding of the gene-diet interactions in determining serum bilirubin concentrations is needed. None of the previous genome-wide association studies (GWAS) on bilirubin concentrations has been stratified by sex. Therefore, considering the increasing interest in incorporating the gender perspective into nutritional genomics, our main aim was to carry out a GWAS on total serum bilirubin concentrations in a Mediterranean population with metabolic syndrome, stratified by sex. Our secondary aim was to explore, as a pilot study, the presence of gene-diet interactions at the GWAS level. We included 430 participants (188 men and 242 women, aged 55–75 years, and with metabolic syndrome) in the PREDIMED Plus-Valencia study. Global and sex-specific GWAS were undertaken to analyze associations and gene-diet interaction on total serum bilirubin. Adherence (low and high) to the Mediterranean diet (MedDiet) was analyzed as the dietary modulator. In the GWAS, we detected more than 55 SNPs associated with serum bilirubin at p < 5 × 10−8 (GWAS level). The top-ranked were four SNPs (rs4148325 (p = 9.25 × 10−24), rs4148324 (p = 9.48 × 10−24), rs6742078 (p = 1.29 × 10−23), rs887829 (p = 1.39 × 10−23), and the rs4148324 (p = 9.48 × 10−24)) in the UGT1A1 (UDP glucuronosyltransferase family 1 member A1) gene, which replicated previous findings revealing the UGT1A1 as the major locus. In the sex-specific GWAS, the top-ranked SNPs at the GWAS level were similar in men and women (the lead SNP was the rs4148324-UGT1A1 in both men (p = 4.77 × 10−11) and women (p = 2.15 × 10−14), which shows homogeneous genetic results for the major locus. There was more sex-specific heterogeneity for other minor genes associated at the suggestive level of GWAS significance (p < 1 × 10−5). We did not detect any gene-MedDiet interaction at p < 1 × 10−5 for the major genetic locus, but we detected some gene-MedDiet interactions with other genes at p < 1 × 10−5, and even at the GWAS level for the IL17B gene (p = 3.14 × 10−8). These interaction results, however, should be interpreted with caution due to our small sample size. In conclusion, our study provides new data, with a gender perspective, on genes associated with total serum bilirubin concentrations in men and women, and suggests possible additional modulations by adherence to MedDiet.
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Affiliation(s)
- Oscar Coltell
- Department of Computer Languages and Systems, Universitat Jaume I, 12071 Castellón, Spain.
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain.
| | - Eva M Asensio
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain.
- Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, 46010 Valencia, Spain.
| | - José V Sorlí
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain.
- Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, 46010 Valencia, Spain.
| | - Rocio Barragán
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain.
- Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, 46010 Valencia, Spain.
| | - Rebeca Fernández-Carrión
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain.
- Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, 46010 Valencia, Spain.
| | - Olga Portolés
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain.
- Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, 46010 Valencia, Spain.
| | - Carolina Ortega-Azorín
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain.
- Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, 46010 Valencia, Spain.
| | - Raul Martínez-LaCruz
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain.
- Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, 46010 Valencia, Spain.
| | - José I González
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain.
- Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, 46010 Valencia, Spain.
| | - Vicente Zanón-Moreno
- Area of Health Sciences, Valencian International University, 46002 Valencia, Spain.
- Red Temática de Investigación Cooperativa OftaRed, Instituto de Salud Carlos III, 28029 Madrid, Spain.
- Ophthalmology Research Unit "Santiago Grisolia", Dr. Peset University Hospital, 46017 Valencia, Spain.
| | - Ignacio Gimenez-Alba
- Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, 46010 Valencia, Spain.
| | - Montserrat Fitó
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain.
- Instituto Hospital del Mar de Investigaciones Médicas, 08003 Barcelona, Spain.
| | - Emilio Ros
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain.
- Lipid Clinic, Endocrinology and Nutrition Service, Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), Hospital Clínic, University of Barcelona, 08036 Barcelona, Spain.
| | - Jose M Ordovas
- Nutrition and Genomics Laboratory, JM-USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA 02111, USA.
- Department of Cardiovascular Epidemiology and Population Genetics, Centro Nacional de Investigaciones Cardiovasculares (CNIC), 28029 Madrid, Spain.
- IMDEA Alimentación, 28049 Madrid, Spain.
| | - Dolores Corella
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain.
- Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, 46010 Valencia, Spain.
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Soares-Souza G, Borda V, Kehdy F, Tarazona-Santos E. Admixture, Genetics and Complex Diseases in Latin Americans and US Hispanics. CURRENT GENETIC MEDICINE REPORTS 2018. [DOI: 10.1007/s40142-018-0151-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
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Du C, Zhang C, Wu W, Liang Y, Wang A, Wu S, Zhao Y, Hou L, Ning Q, Luo X. Circulating MOTS-c levels are decreased in obese male children and adolescents and associated with insulin resistance. Pediatr Diabetes 2018; 19:1058-1064. [PMID: 29691953 DOI: 10.1111/pedi.12685] [Citation(s) in RCA: 53] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/06/2018] [Revised: 03/14/2018] [Accepted: 04/16/2018] [Indexed: 01/06/2023] Open
Abstract
BACKGROUND AND AIMS A novel bioactive peptide, mitochondrial-derived peptide (MOTS-c), has recently attracted attention as a potential prevention or therapeutic option for obesity and type 2 diabetes mellitus (T2DM). MOTS-c profiles have not yet been reported in human obesity and T2DM. We aimed to determine circulating MOTS-c levels in obesity and explore the association between MOTS-c levels and various metabolic parameters. METHODS In this case-control study, 40 obese children and adolescents (27 males) and 57 controls (40 males) were recruited in the Hubei Province of China in 2017. Circulating MOTS-c levels were measured, clinical data (eg, glucose, insulin, and lipid profile) were recorded, and anthropometric measurements were performed. Finally, we investigated correlations between MOTS-c levels and related variables. RESULTS MOTS-c levels were significantly decreased in the obese group compared with the control group (472.61 ±22.83 vs 561.64 ±19.19 ng/mL, P <.01). After classification by sex, MOTS-c levels were significantly decreased in obese male children and adolescents compared to their counterparts (465.26 ±24.53 vs 584.07 ±21.18 ng/mL, P <.001), while they were comparable between the obese and healthy female subjects (487.89 ±49.77 vs 508.85 ±38.76 ng/mL, P >.05). Further, MOTS-c levels were negatively correlated with body mass index (BMI), BMI SD score, waist circumference, waist-to-hip ratio, fasting insulin level, homeostasis model assessment of insulin resistance (HOMA-IR), and glycated hemoglobin (HbA1c) in the male cohort. CONCLUSIONS Circulating MOTS-c levels were decreased in obese male children and adolescents and correlated with markers of insulin resistance and obesity.
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Affiliation(s)
- Caiqi Du
- Department of Pediatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Cai Zhang
- Department of Pediatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Wei Wu
- Department of Pediatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yan Liang
- Department of Pediatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Anru Wang
- Department of Pediatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Department of Pediatrics, the Second Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Shimin Wu
- Department of Pediatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yue Zhao
- Department of Pediatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ling Hou
- Department of Pediatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Qin Ning
- Department of Infectious Diseases, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaoping Luo
- Department of Pediatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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