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Song H, Dong T, Wang W, Yan X, Geng C, Bai S, Hu H. GWAS Enhances Genomic Prediction Accuracy of Caviar Yield, Caviar Color and Body Weight Traits in Sturgeons Using Whole-Genome Sequencing Data. Int J Mol Sci 2024; 25:9756. [PMID: 39273703 PMCID: PMC11395957 DOI: 10.3390/ijms25179756] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2024] [Revised: 09/05/2024] [Accepted: 09/07/2024] [Indexed: 09/15/2024] Open
Abstract
Caviar yield, caviar color, and body weight are crucial economic traits in sturgeon breeding. Understanding the molecular mechanisms behind these traits is essential for their genetic improvement. In this study, we performed whole-genome sequencing on 673 Russian sturgeons, renowned for their high-quality caviar. With an average sequencing depth of 13.69×, we obtained approximately 10.41 million high-quality single nucleotide polymorphisms (SNPs). Using a genome-wide association study (GWAS) with a single-marker regression model, we identified SNPs and genes associated with these traits. Our findings revealed several candidate genes for each trait: caviar yield: TFAP2A, RPS6KA3, CRB3, TUBB, H2AFX, morc3, BAG1, RANBP2, PLA2G1B, and NYAP1; caviar color: NFX1, OTULIN, SRFBP1, PLEK, INHBA, and NARS; body weight: ACVR1, HTR4, fmnl2, INSIG2, GPD2, ACVR1C, TANC1, KCNH7, SLC16A13, XKR4, GALR2, RPL39, ACVR2A, ADCY10, and ZEB2. Additionally, using the genomic feature BLUP (GFBLUP) method, which combines linkage disequilibrium (LD) pruning markers with GWAS prior information, we improved genomic prediction accuracy by 2%, 1.9%, and 3.1% for caviar yield, caviar color, and body weight traits, respectively, compared to the GBLUP method. In conclusion, this study enhances our understanding of the genetic mechanisms underlying caviar yield, caviar color, and body weight traits in sturgeons, providing opportunities for genetic improvement of these traits through genomic selection.
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Affiliation(s)
- Hailiang Song
- Fisheries Science Institute, Beijing Academy of Agriculture and Forestry Sciences & Beijing Key Laboratory of Fisheries Biotechnology, Beijing 100068, China
- Key Laboratory of Sturgeon Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Hangzhou 311799, China
- National Innovation Center for Digital Seed Industry, Beijing 100097, China
| | - Tian Dong
- Fisheries Science Institute, Beijing Academy of Agriculture and Forestry Sciences & Beijing Key Laboratory of Fisheries Biotechnology, Beijing 100068, China
- Key Laboratory of Sturgeon Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Hangzhou 311799, China
| | - Wei Wang
- Fisheries Science Institute, Beijing Academy of Agriculture and Forestry Sciences & Beijing Key Laboratory of Fisheries Biotechnology, Beijing 100068, China
- Key Laboratory of Sturgeon Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Hangzhou 311799, China
| | - Xiaoyu Yan
- Fisheries Science Institute, Beijing Academy of Agriculture and Forestry Sciences & Beijing Key Laboratory of Fisheries Biotechnology, Beijing 100068, China
- Key Laboratory of Sturgeon Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Hangzhou 311799, China
| | - Chenfan Geng
- Fisheries Science Institute, Beijing Academy of Agriculture and Forestry Sciences & Beijing Key Laboratory of Fisheries Biotechnology, Beijing 100068, China
- Key Laboratory of Sturgeon Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Hangzhou 311799, China
| | - Song Bai
- Fisheries Science Institute, Beijing Academy of Agriculture and Forestry Sciences & Beijing Key Laboratory of Fisheries Biotechnology, Beijing 100068, China
- Key Laboratory of Sturgeon Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Hangzhou 311799, China
| | - Hongxia Hu
- Fisheries Science Institute, Beijing Academy of Agriculture and Forestry Sciences & Beijing Key Laboratory of Fisheries Biotechnology, Beijing 100068, China
- Key Laboratory of Sturgeon Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Hangzhou 311799, China
- National Innovation Center for Digital Seed Industry, Beijing 100097, China
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Bojarczuk A, Egorova ES, Dzitkowska-Zabielska M, Ahmetov II. Genetics of Exercise and Diet-Induced Fat Loss Efficiency: A Systematic Review. J Sports Sci Med 2024; 23:236-257. [PMID: 38455434 PMCID: PMC10915602 DOI: 10.52082/jssm.2024.236] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2024] [Accepted: 02/21/2024] [Indexed: 03/09/2024]
Abstract
Physical exercise and dieting are well-known and effective methods for fat loss and improving cardiovascular health. However, different individuals often react differently to the same exercise regimen or dietary plan. While specific individuals may undergo substantial fat loss, others may observe only limited effects. A wide range of inter-individual variability in weight gain and changes in body composition induced by physical exercises and diets led to an investigation into the genetic factors that may contribute to the individual variations in such responses. This systematic review aimed at identifying the genetic markers associated with fat loss resulting from diet or exercise. A search of the current literature was performed using the PubMed database. Forty-seven articles met the inclusion criteria when assessing genetic markers associated with weight loss efficiency in response to different types of exercises and diets. Overall, we identified 30 genetic markers of fat-loss efficiency in response to different kinds of diets and 24 in response to exercise. Most studies (n = 46) used the candidate gene approach. We should aspire to the customized selection of exercise and dietary plans for each individual to prevent and treat obesity.
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Affiliation(s)
- Aleksandra Bojarczuk
- Faculty of Physical Culture, Gdansk University of Physical Education and Sport, Gdansk, Poland
| | - Emiliya S Egorova
- Laboratory of Genetics of Aging and Longevity, Kazan State Medical University, Kazan, Russia
| | | | - Ildus I Ahmetov
- Laboratory of Genetics of Aging and Longevity, Kazan State Medical University, Kazan, Russia
- Sports Genetics Laboratory, St Petersburg Research Institute of Physical Culture, St. Petersburg, Russia
- Center for Phygital Education and Innovative Sports Technologies, Plekhanov Russian University of Economics, Moscow, Russia
- Research Institute for Sport and Exercise Sciences, Liverpool John Moores University, Liverpool, UK
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3
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Yang M, Zhang R, Liu X, Shi G, Liu H, Wang L, Hou X, Shi L, Wang L, Zhang L. Integrating genome-wide association study with RNA-seq revealed DBI as a good candidate gene for intramuscular fat content in Beijing black pigs. Anim Genet 2023; 54:24-34. [PMID: 36305366 DOI: 10.1111/age.13270] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2022] [Revised: 10/04/2022] [Accepted: 10/08/2022] [Indexed: 01/07/2023]
Abstract
Increasing intramuscular fat (IMF) content can enhance the sensory quality of meat, including tenderness, juiciness, flavor, and color. Genome-wide association study and RNA-sequencing (RNA-seq) analysis were used to identify candidate IMF genes in Beijing Black pigs, a popular species among consumers in northern China. Two and three single nucleotide polymorphisms were significantly associated with IMF in SSC13 and SSC15 respectively. Solute carrier family 4 member 7 (SLC4A7) on SSC13 and insulin induced gene 2 (INSIG2), coiled-coil domain containing 93 (CCDC93), and diazepam binding inhibitor acyl-CoA binding protein (DBI) on SSC15 are good candidate genes in this population. Furthermore, RNA-seq analysis was performed between high and low IMF groups, and 534 differentially expressed genes were identified. In addition, based on differentially expressed genes, Kyoto Encyclopedia of Genes and Genomes analysis revealed that peroxisome proliferator-activated receptors and FoxO signaling pathway pathways might contribute to IMF. Moreover, the DBI gene was identified as a candidate for IMF both by genome-wide association study and RNA-seq analysis, suggesting that it might be a crucial candidate gene for influencing IMF in Beijing Black pigs.
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Affiliation(s)
- Man Yang
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Run Zhang
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Xiance Liu
- Beijing Heiliu Animal Husbandry Technology Co, Ltd, Beijing, China
| | - Guohua Shi
- Beijing Heiliu Animal Husbandry Technology Co, Ltd, Beijing, China
| | - Hai Liu
- Beijing Heiliu Animal Husbandry Technology Co, Ltd, Beijing, China
| | - Ligang Wang
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Xinhua Hou
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Lijun Shi
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Lixian Wang
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Longchao Zhang
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
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4
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Vann CG, Morton RW, Mobley CB, Vechetti IJ, Ferguson BK, Haun CT, Osburn SC, Sexton CL, Fox CD, Romero MA, Roberson PA, Oikawa SY, McGlory C, Young KC, McCarthy JJ, Phillips SM, Roberts MD. An intron variant of the GLI family zinc finger 3 (GLI3) gene differentiates resistance training-induced muscle fiber hypertrophy in younger men. FASEB J 2021; 35:e21587. [PMID: 33891350 PMCID: PMC8234740 DOI: 10.1096/fj.202100113rr] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2021] [Revised: 03/17/2021] [Accepted: 03/25/2021] [Indexed: 12/25/2022]
Abstract
We examined the association between genotype and resistance training-induced changes (12 wk) in dual x-ray energy absorptiometry (DXA)-derived lean soft tissue mass (LSTM) as well as muscle fiber cross-sectional area (fCSA; vastus lateralis; n = 109; age = 22 ± 2 y, BMI = 24.7 ± 3.1 kg/m2 ). Over 315 000 genetic polymorphisms were interrogated from muscle using DNA microarrays. First, a targeted investigation was performed where single nucleotide polymorphisms (SNP) identified from a systematic literature review were related to changes in LSTM and fCSA. Next, genome-wide association (GWA) studies were performed to reveal associations between novel SNP targets with pre- to post-training change scores in mean fCSA and LSTM. Our targeted investigation revealed no genotype-by-time interactions for 12 common polymorphisms regarding the change in mean fCSA or change in LSTM. Our first GWA study indicated no SNP were associated with the change in LSTM. However, the second GWA study indicated two SNP exceeded the significance level with the change in mean fCSA (P = 6.9 × 10-7 for rs4675569, 1.7 × 10-6 for rs10263647). While the former target is not annotated (chr2:205936846 (GRCh38.p12)), the latter target (chr7:41971865 (GRCh38.p12)) is an intron variant of the GLI Family Zinc Finger 3 (GLI3) gene. Follow-up analyses indicated fCSA increases were greater in the T/C and C/C GLI3 genotypes than the T/T GLI3 genotype (P < .05). Data from the Auburn cohort also revealed participants with the T/C and C/C genotypes exhibited increases in satellite cell number with training (P < .05), whereas T/T participants did not. Additionally, those with the T/C and C/C genotypes achieved myonuclear addition in response to training (P < .05), whereas the T/T participants did not. In summary, this is the first GWA study to examine how polymorphisms associate with the change in hypertrophy measures following resistance training. Future studies are needed to determine if the GLI3 variant differentiates hypertrophic responses to resistance training given the potential link between this gene and satellite cell physiology.
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Affiliation(s)
- Christopher G Vann
- School of Kinesiology, Auburn University, Auburn, AL, USA.,Duke Molecular Physiology Institute, Duke University School of Medicine, Duke University, Durham, NC, USA
| | - Robert W Morton
- Department of Kinesiology, McMaster University, Hamilton, Ontario, Canada
| | - Christopher B Mobley
- Department of Physiology, College of Medicine, University of Kentucky, Lexington, KY, USA.,The Center for Muscle Biology, University of Kentucky, Lexington, KY, USA
| | - Ivan J Vechetti
- Department of Nutrition and Health Sciences, University of Nebraska-Lincoln, Lincoln, NE, USA
| | | | | | | | - Casey L Sexton
- School of Kinesiology, Auburn University, Auburn, AL, USA
| | - Carlton D Fox
- School of Kinesiology, Auburn University, Auburn, AL, USA
| | | | | | - Sara Y Oikawa
- Department of Kinesiology, McMaster University, Hamilton, Ontario, Canada
| | - Chris McGlory
- Department of Kinesiology, McMaster University, Hamilton, Ontario, Canada
| | - Kaelin C Young
- School of Kinesiology, Auburn University, Auburn, AL, USA.,Department of Cell Biology and Physiology, Edward Via College of Osteopathic Medicine, Auburn, AL, USA
| | - John J McCarthy
- Department of Physiology, College of Medicine, University of Kentucky, Lexington, KY, USA.,The Center for Muscle Biology, University of Kentucky, Lexington, KY, USA
| | - Stuart M Phillips
- Department of Kinesiology, McMaster University, Hamilton, Ontario, Canada
| | - Michael D Roberts
- School of Kinesiology, Auburn University, Auburn, AL, USA.,Department of Cell Biology and Physiology, Edward Via College of Osteopathic Medicine, Auburn, AL, USA
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5
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Rodríguez-Pardo C, Segura A, Zamorano-León JJ, Martínez-Santos C, Martínez D, Collado-Yurrita L, Giner M, García-García JM, Rodríguez-Pardo JM, López-Farre A. Decision tree learning to predict overweight/obesity based on body mass index and gene polymporphisms. Gene 2019; 699:88-93. [DOI: 10.1016/j.gene.2019.03.011] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2018] [Revised: 03/06/2019] [Accepted: 03/07/2019] [Indexed: 12/26/2022]
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6
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Prakash J, Mittal B, Apurva S, Shally A, Pranjal S, Neena S. Common Genetic Variant of insig2 Gene rs7566605 Polymorphism Is Associated with Severe Obesity in North India. IRANIAN BIOMEDICAL JOURNAL 2017; 21:261-9. [PMID: 28160769 PMCID: PMC5459941 DOI: 10.18869/acadpub.ibj.21.4.261] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Background: Obesity is a very common disorder resulting from an imbalance between food intake and energy expenditure, and it has a substantial impact on the development of chronic diseases. The aim of this study was to examine the association of INSIG2 (rs7566605) gene polymorphism with obesity and obesity associated phenotypes in North Indian subjects. Methods: The variants were investigated for association in 642 obese and non-obese individuals. The genotyping of INSIG2 (rs7566605) single nucleotide polymorphism was analyzed by the TaqMan allelic discrimination protocol. Results: A significant association was observed for INSIG2 (rs7566605) single nucleotide polymorphism with obesity and obesity-related phenotypes. Furthermore, a significant relationship was found between the rs7566605 and insulin, homeostasis model of assessment-insulin resistance, the percentage of body fat, fat mass, leptin, and adiponectin. Conclusion: The present study observed significant association between INSIG2 (rs7566605) single nucleotide polymorphism and obesity, as well as obesity-associated phenotypes in North Indian population.
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Affiliation(s)
- Jai Prakash
- Department of Physiology, King George’s Medical University, Lucknow, Uttar Pradesh, India.,2Department of Pediatrics, King George’s Medical University, Lucknow, Uttar Pradesh, India
| | - Balraj Mittal
- 3Department of Genetics, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, U.P., India
| | - Srivastava Apurva
- Department of Physiology, King George’s Medical University, Lucknow, Uttar Pradesh, India
| | - Awasthi Shally
- 2Department of Pediatrics, King George’s Medical University, Lucknow, Uttar Pradesh, India
| | - Srivastava Pranjal
- Darbhanga Medical College and Hospital Near Karpuri Chowk Benta Laheriasarai Darbhanga Bihar 846003, India
| | - Srivastava Neena
- Department of Physiology, King George’s Medical University, Lucknow, Uttar Pradesh, India
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7
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Banting LK, Pushkarev VP, Cieszczyk P, Zarebska A, Maciejewska-Karlowska A, Sawczuk MA, Leońska-Duniec A, Dyatlov DA, Orekhov EF, Degtyarev AV, Pushkareva YE, Yan X, Birk R, Eynon N. Elite athletes' genetic predisposition for altered risk of complex metabolic traits. BMC Genomics 2015; 16:25. [PMID: 25612568 PMCID: PMC4320608 DOI: 10.1186/s12864-014-1199-0] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2014] [Accepted: 12/22/2014] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Genetic variants may predispose humans to elevated risk of common metabolic morbidities such as obesity and Type 2 Diabetes (T2D). Some of these variants have also been shown to influence elite athletic performance and the response to exercise training. We compared the genotype distribution of five genetic Single Nucleotide Polymorphisms (SNPs) known to be associated with obesity and obesity co-morbidities (IGF2BP2 rs4402960, LPL rs320, LPL rs328, KCJN rs5219, and MTHFR rs1801133) between athletes (all male, n = 461; endurance athletes n = 254, sprint/power athletes n = 207), and controls (all male, n = 544) in Polish and Russian samples. We also examined the association between these SNPs and the athletes' competition level ('elite' and 'national' level). Genotypes were analysed by Single-Base Extension and Real-Time PCR. Multinomial logistic regression analyses were conducted to assess the association between genotypes and athletic status/competition level. RESULTS IGF2BP2 rs4402960 and LPL rs320 were significantly associated with athletic status; sprint/power athletes were twice more likely to have the IGF2BP2 rs4402960 risk (T) allele compared to endurance athletes (OR = 2.11, 95% CI = 1.03-4.30, P <0.041), and non-athletic controls were significantly less likely to have the T allele compared to sprint/power athletes (OR = 0.62, 95% CI =0.43-0.89, P <0.0009). The control group was significantly more likely to have the LPL rs320 risk (G) allele compared to endurance athletes (OR = 1.26, 95% CI = 1.05-1.52, P <0.013). Hence, endurance athletes were the "protected" group being significantly (p < 0.05) less likely to have the risk allele compared to sprint/power athletes (IGF2BP2 rs4402960) and significantly (p < 0.05) less likely to have the risk allele compared to controls (LPL rs320). The other 3 SNPs did not show significant differences between the study groups. CONCLUSIONS Male endurance athletes are less likely to have the metabolic risk alleles of IGF2BP2 rs4402960 and LPL rs320, compared to sprint/power athletes and controls, respectively. These results suggest that some SNPs across the human genome have a dual effect and may predispose endurance athletes to reduced risk of developing metabolic morbidities, whereas sprint/power athletes might be predisposed to elevated risk.
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Affiliation(s)
- Lauren K Banting
- Institute of Sport, Exercise and Active Living (ISEAL), Victoria University, Melbourne, Australia, , VIC, 8001.
| | | | - Pawel Cieszczyk
- University of Szczecin, Department of Physical Culture and Health Promotion, Szczecin, Poland.
| | - Aleksandra Zarebska
- Academy of Physical Education and Sport, Department of Sport Education, Gdansk, Poland.
| | | | - M-Arek Sawczuk
- University of Szczecin, Department of Physical Culture and Health Promotion, Szczecin, Poland.
| | - Agata Leońska-Duniec
- University of Szczecin, Department of Physical Culture and Health Promotion, Szczecin, Poland.
| | | | | | | | | | - Xu Yan
- Institute of Sport, Exercise and Active Living (ISEAL), Victoria University, Melbourne, Australia, , VIC, 8001.
- Murdoch Childrens Research Institute, The Royal Children's Hospital, Melbourne, Australia.
| | - Ruth Birk
- Department of Nutrition, Faculty of Health Sciences, Ariel University, Ariel, Israel.
| | - Nir Eynon
- Institute of Sport, Exercise and Active Living (ISEAL), Victoria University, Melbourne, Australia, , VIC, 8001.
- Murdoch Childrens Research Institute, The Royal Children's Hospital, Melbourne, Australia.
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Abstract
The world is facing an epidemic rise in diabetes mellitus (DM) incidence, which is challenging health funders, health systems, clinicians, and patients to understand and respond to a flood of research and knowledge. Evidence-based guidelines provide uniform management recommendations for "average" patients that rarely take into account individual variation in susceptibility to DM, to its complications, and responses to pharmacological and lifestyle interventions. Personalized medicine combines bioinformatics with genomic, proteomic, metabolomic, pharmacogenomic ("omics") and other new technologies to explore pathophysiology and to characterize more precisely an individual's risk for disease, as well as response to interventions. In this review we will introduce readers to personalized medicine as applied to DM, in particular the use of clinical, genetic, metabolic, and other markers of risk for DM and its chronic microvascular and macrovascular complications, as well as insights into variations in response to and tolerance of commonly used medications, dietary changes, and exercise. These advances in "omic" information and techniques also provide clues to potential pathophysiological mechanisms underlying DM and its complications.
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Affiliation(s)
- Harry S. Glauber
- Department of Endocrinology, Northwest Permanente, Portland, Oregon, USA
- Galil Center for Telemedicine, Medical Informatics and Personalized Medicine, RB Rappaport Faculty of Medicine, Technion – Israel Institute of Technology, Haifa, Israel
| | | | - Eddy Karnieli
- Institute of Endocrinology, Diabetes and Metabolism, Rambam Medical Center, Haifa, Israel and
- Galil Center for Telemedicine, Medical Informatics and Personalized Medicine, RB Rappaport Faculty of Medicine, Technion – Israel Institute of Technology, Haifa, Israel
- To whom correspondence should be addressed. E-mail:
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9
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Pescatello LS, Devaney JM, Hubal MJ, Thompson PD, Hoffman EP. Highlights from the functional single nucleotide polymorphisms associated with human muscle size and strength or FAMuSS study. BIOMED RESEARCH INTERNATIONAL 2013; 2013:643575. [PMID: 24455711 PMCID: PMC3885233 DOI: 10.1155/2013/643575] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/05/2013] [Accepted: 11/20/2013] [Indexed: 01/08/2023]
Abstract
The purpose of the Functional Single Nucleotide Polymorphisms Associated with Human Muscle Size and Strength study or FAMuSS was to identify genetic factors that dictated the response of health-related fitness phenotypes to resistance exercise training (RT). The phenotypes examined were baseline muscle strength and muscle, fat, and bone volume and their response to RT. FAMuSS participants were 1300 young (24 years), healthy men (42%) and women (58%) that were primarily of European-American descent. They were genotyped for ~500 polymorphisms and completed the Paffenbarger Physical Activity Questionnaire to assess energy expenditure and time spent in light, moderate, and vigorous intensity habitual physical activity and sitting. Subjects then performed a 12-week progressive, unilateral RT program of the nondominant arm with the dominant arm used as a comparison. Before and after RT, muscle strength was measured with the maximum voluntary contraction and one repetition maximum, while MRI measured muscle, fat, and bone volume. We will discuss the history of how FAMuSS originated, provide a brief overview of the FAMuSS methods, and summarize our major findings regarding genotype associations with muscle strength and size, body composition, cardiometabolic biomarkers, and physical activity.
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Affiliation(s)
- Linda S. Pescatello
- Department of Kinesiology and Human Performance Laboratory, Neag School of Education, University of Connecticut, Gampel Pavilion Room 206, 2095 Hillside Road, U-1110, Storrs, CT 06269-1110, USA
| | - Joseph M. Devaney
- Children's National Medical Center, 111 Michigan Avenue, N.W., Washington, DC 20010-2970, USA
| | - Monica J. Hubal
- Children's National Medical Center, 111 Michigan Avenue, N.W., Washington, DC 20010-2970, USA
| | - Paul D. Thompson
- Division of Cardiology, Hartford Hospital, 85 Jefferson Street, Hartford, CT 06106, USA
| | - Eric P. Hoffman
- Children's National Medical Center, 111 Michigan Avenue, N.W., Washington, DC 20010-2970, USA
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10
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Popadic Gacesa JZ, Secher NH, Momcilovic M, Grujic NG. Association between intramuscular fat in the arm following arm training andINSIG2. Scand J Med Sci Sports 2013; 24:907-12. [DOI: 10.1111/sms.12102] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/01/2013] [Indexed: 12/25/2022]
Affiliation(s)
- J. Z. Popadic Gacesa
- Department of Physiology; Medical School; University of Novi Sad; Novi Sad Serbia
| | - N. H. Secher
- The Copenhagen Muscle Research Center; Department of Anesthesiology; Rigshospitalet; University of Copenhagen; Copenhagen Denmark
| | - M. Momcilovic
- Department of Biochemistry; Medical School; University of Novi Sad; Novi Sad Serbia
| | - N. G. Grujic
- Department of Physiology; Medical School; University of Novi Sad; Novi Sad Serbia
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11
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Devaney JM, Thompson PD, Visich PS, Saltarelli WA, Gordon PM, Orkunoglu-Suer EF, Gordish-Dressman H, Harmon BT, Bradbury MK, Panchapakesan K, Khianey R, Hubal MJ, Clarkson PM, Pescatello LS, Zoeller RF, Moyna NM, Angelopoulos TJ, Kraus WE, Hoffman EP. The 1p13.3 LDL (C)-associated locus shows large effect sizes in young populations. Pediatr Res 2011; 69:538-43. [PMID: 21297524 PMCID: PMC3606915 DOI: 10.1203/pdr.0b013e3182139227] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Genome-wide association studies (GWASs) have identified polymorphic loci associated with coronary artery disease (CAD) risk factors (i.e. serum lipids) in adult populations (42-69 y). We hypothesized that younger populations would show a greater relative genetic component due to fewer confounding variables. We examined the influence of 20 GWAS loci associated with serum lipids and insulin metabolism, in a university student cohort (n = 548; mean age = 24 y), and replicated statistically associated results in a second study cohort of primary school students (n = 810, mean age = 11.5 y). Nineteen loci showed no relationship with studied risk factors in young adults. However, the ancestral allele of the rs646776 (SORT1) locus was strongly associated with increased LDL (C) in young adults [TT: 97.6 ± 1.0 mg/dL (n = 345) versus CT/CC: 87.3 ± 1.0 mg/dL (n = 203); p = 3 × 10(x6)] and children [TT: 94.0 ± 1.3 mg/dL (n = 551) versus CT/CC: 84.7 ± 1.4 mg/dL (n = 259); p = 4 × 10(x6)]. This locus is responsible for 3.6% of population variance in young adults and 2.5% of population variance in children. The effect size of the SORT1 locus is considerably higher in young populations (2.5-4.1%) compared with older subjects (1%).
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Affiliation(s)
- Joseph M Devaney
- Department of Integrative Systems Biology, Research Center for Genetic Medicine, Children's National Medical Center, Washington, DC 20010, USA
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12
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Orkunoglu-Suer FE, Harmon BT, Gordish-Dressman H, Clarkson PM, Thompson PD, Angelopoulos TJ, Gordon PM, Hubal MJ, Moyna NM, Pescatello LS, Visich PS, Zoeller RF, Hoffman EP, Devaney JM. MC4R variant is associated with BMI but not response to resistance training in young females. Obesity (Silver Spring) 2011; 19:662-6. [PMID: 20725061 PMCID: PMC4147947 DOI: 10.1038/oby.2010.180] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
UNLABELLED Recently, a genome-wide association study (GWAS) that identified eight single-nucleotide polymorphisms (SNPs) associated with BMI highlighted a possible neuronal influence on the development of obesity. We hypothesized these SNPs would govern the response of BMI and subcutaneous fat to resistance training in young individuals (age = 24 years). We genotyped the eight GWAS-identified SNPs in the article by Willer et al. in a cohort (n = 796) that undertook a 12-week resistance-training program. Females with a copy of the rare allele (C) for rs17782313 (MC4R) had significantly higher BMIs ( CC/CT n = 174; 24.70 ± 0.33 kg/m², TT: n = 278; 23.41 ± 0.26 kg/m², P = 0.002), and the SNP explained 1.9% of overall variation in BMI. Males with a copy of the rare allele (T) for rs6548238 (TMEM18) had lower amounts of subcutaneous fat pretraining (CT/TT: n = 65; 156,534 ± 7,415 mm³, CC: n = 136; 177,825 ± 5,139 mm³, P = 0.019) and males with a copy of the rare allele (A) for rs9939609 (FTO) lost a significant amount of subcutaneous fat with exercise ( AT/AA n = 83; -798.35 ± 2,624.30 mm³, TT: n = 47; 9,435.23 ± 3,494.44 mm³, P = 0.021). Females with a copy of the G allele for a missense variant in the SH2B1 (rs7498665) was associated with less change of subcutaneous fat volume with exercise ( AG/GG n = 191; 9,813 ± 2,250 mm³ vs. AA: n = 126; 770 ± 2,772 mm³; P = 0.011). These data support the original finding that there is an association between measures of obesity and a variant near the MC4R gene and extends these results to a younger population and implicates FTO, TMEM18, and SH2B1 polymorphisms in subcutaneous fat regulation.
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Affiliation(s)
- Funda E. Orkunoglu-Suer
- Research Center for Genetic Medicine, Children’s National Medical Center, Washington, DC, USA
| | - Brennan T Harmon
- Research Center for Genetic Medicine, Children’s National Medical Center, Washington, DC, USA
| | | | | | - Paul D. Thompson
- Division of Cardiology, Henry Low Heart Center, Hartford Hospital, Hartford, Connecticut, USA
| | - Theodore J. Angelopoulos
- Center for Lifestyle Medicine, Department of Health Professions, University of Central Florida, Orlando, Florida, USA
| | - Paul M. Gordon
- Laboratory for Physical Activity and Exercise Intervention Research, University of Michigan, Ann Arbor, Michigan, USA
| | - Monica J. Hubal
- Research Center for Genetic Medicine, Children’s National Medical Center, Washington, DC, USA
| | - Niall M. Moyna
- School of Health and Human Performance, Dublin City University, Dublin, Ireland
| | - Linda S. Pescatello
- Department of Kinesiology, Human Performance Laboratory, University of Connecticut, Storrs, Connecticut, USA
| | - Paul S. Visich
- Human Performance Laboratory, Central Michigan University, Mount Pleasant, Michigan, USA
| | - Robert F. Zoeller
- Department of Exercise Science and Health Promotion, Florida Atlantic University, Davie, Florida, USA
| | - Eric P. Hoffman
- Research Center for Genetic Medicine, Children’s National Medical Center, Washington, DC, USA
| | - Joseph M. Devaney
- Research Center for Genetic Medicine, Children’s National Medical Center, Washington, DC, USA
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Heid IM, Huth C, Loos RJF, Kronenberg F, Adamkova V, Anand SS, Ardlie K, Biebermann H, Bjerregaard P, Boeing H, Bouchard C, Ciullo M, Cooper JA, Corella D, Dina C, Engert JC, Fisher E, Francès F, Froguel P, Hebebrand J, Hegele RA, Hinney A, Hoehe MR, Hu FB, Hubacek JA, Humphries SE, Hunt SC, Illig T, Järvelin MR, Kaakinen M, Kollerits B, Krude H, Kumar J, Lange LA, Langer B, Li S, Luchner A, Lyon HN, Meyre D, Mohlke KL, Mooser V, Nebel A, Nguyen TT, Paulweber B, Perusse L, Qi L, Rankinen T, Rosskopf D, Schreiber S, Sengupta S, Sorice R, Suk A, Thorleifsson G, Thorsteinsdottir U, Völzke H, Vimaleswaran KS, Wareham NJ, Waterworth D, Yusuf S, Lindgren C, McCarthy MI, Lange C, Hirschhorn JN, Laird N, Wichmann HE. Meta-analysis of the INSIG2 association with obesity including 74,345 individuals: does heterogeneity of estimates relate to study design? PLoS Genet 2009; 5:e1000694. [PMID: 19851442 PMCID: PMC2757909 DOI: 10.1371/journal.pgen.1000694] [Citation(s) in RCA: 56] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2008] [Accepted: 09/22/2009] [Indexed: 11/19/2022] Open
Abstract
The INSIG2 rs7566605 polymorphism was identified for obesity (BMI≥30 kg/m2) in one of the first genome-wide association studies, but replications were inconsistent. We collected statistics from 34 studies (n = 74,345), including general population (GP) studies, population-based studies with subjects selected for conditions related to a better health status (‘healthy population’, HP), and obesity studies (OB). We tested five hypotheses to explore potential sources of heterogeneity. The meta-analysis of 27 studies on Caucasian adults (n = 66,213) combining the different study designs did not support overall association of the CC-genotype with obesity, yielding an odds ratio (OR) of 1.05 (p-value = 0.27). The I2 measure of 41% (p-value = 0.015) indicated between-study heterogeneity. Restricting to GP studies resulted in a declined I2 measure of 11% (p-value = 0.33) and an OR of 1.10 (p-value = 0.015). Regarding the five hypotheses, our data showed (a) some difference between GP and HP studies (p-value = 0.012) and (b) an association in extreme comparisons (BMI≥32.5, 35.0, 37.5, 40.0 kg/m2 versus BMI<25 kg/m2) yielding ORs of 1.16, 1.18, 1.22, or 1.27 (p-values 0.001 to 0.003), which was also underscored by significantly increased CC-genotype frequencies across BMI categories (10.4% to 12.5%, p-value for trend = 0.0002). We did not find evidence for differential ORs (c) among studies with higher than average obesity prevalence compared to lower, (d) among studies with BMI assessment after the year 2000 compared to those before, or (e) among studies from older populations compared to younger. Analysis of non-Caucasian adults (n = 4889) or children (n = 3243) yielded ORs of 1.01 (p-value = 0.94) or 1.15 (p-value = 0.22), respectively. There was no evidence for overall association of the rs7566605 polymorphism with obesity. Our data suggested an association with extreme degrees of obesity, and consequently heterogeneous effects from different study designs may mask an underlying association when unaccounted for. The importance of study design might be under-recognized in gene discovery and association replication so far. A polymorphism of the INSIG2 gene was identified as being associated with obesity in one of the first genome-wide association studies. However, this association has since then been highly debated upon inconsistent subsequent reports. We collected association information from 34 studies including a total of 74,000 participants. In a meta-analysis of the 27 studies including 66,000 Caucasian adults, we found no overall association of this polymorphism rs7566605 with obesity, comparing subjects with a body-mass-index (BMI)≥30 kg/m2 with normal BMI subjects (BMI<30 kg/m2). Our data suggested an association of this polymorphism with extreme obesity (e.g., BMI≥37.5 kg/m2) compared to normal controls. Such an association with extreme obesity might induce heterogeneous effects from different study designs depending on the proportion of extreme obesity included by the design. However, further studies would be required to substantiate this finding. The importance of study design might be under-recognized in gene discovery and association replication so far.
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Affiliation(s)
- Iris M Heid
- Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
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Albrecht DE, Garg N, Rufibach LE, Williams BA, Monnier N, Hwang E, Mittal P. 3rd Annual Dysferlin Conference 2-5 June 2009, Boston, Massachusetts, USA. Neuromuscul Disord 2009; 19:867-73. [PMID: 19781937 DOI: 10.1016/j.nmd.2009.08.005] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2009] [Indexed: 11/26/2022]
Affiliation(s)
- Douglas E Albrecht
- Jain Foundation Inc., 2310 130th Ave. NE, Suite B101, Bellevue, Washington 98005, USA
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Cha S, Koo I, Choi SM, Park BL, Kim KS, Kim JR, Shin HD, Kim JY. Association analyses of the INSIG2 polymorphism in the obesity and cholesterol levels of Korean populations. BMC MEDICAL GENETICS 2009; 10:96. [PMID: 19772594 PMCID: PMC2759923 DOI: 10.1186/1471-2350-10-96] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/13/2009] [Accepted: 09/22/2009] [Indexed: 12/14/2022]
Abstract
Background While INSIG2 has been reported to be associated with BMI in many populations, conflicting results have prevented consensus over its role. In analyses of mice and cell cultures the gene has been found to be involved in the regulation of cholesterol synthesis; however, no relationship has been found with cholesterol metabolism in human epidemiological research. Therefore, this study attempts to assess the effect of rs7566605 near INSIG2 on both obesity- and cholesterol-related traits in Koreans. Methods The rs7566605 polymorphism was genotyped with 2,364 Koreans, and associations with obesity- and cholesterol-related traits were analyzed statistically via an ANOVA or T-test. Results Replication of an association with BMI, WHR, fat mass, fat percent, and abdominal fat area failed, and the C allele of rs7566605 was not associated significantly with total cholesterol, HDL cholesterol, or triglyceride. However, it was found in a meta-analysis of a dominant model that the C allele of rs7566605 appeared to affect the level of the total cholesterol, especially in female subjects. Conclusion We failed to show associations of rs7566605 with cholesterol- and obesity-related phenotypes, although we newly suggest the possible involvement of INSIG2 with the plasma level of the total cholesterol in women.
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Affiliation(s)
- Seongwon Cha
- Division of Constitutional Medicine Research, Korea Institute of Oriental Medicine, 483 Exporo, Daejeon, Republic of Korea.
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Mori M, Higuchi K, Sakurai A, Tabara Y, Miki T, Nose H. Genetic basis of inter-individual variability in the effects of exercise on the alleviation of lifestyle-related diseases. J Physiol 2009; 587:5577-84. [PMID: 19736300 DOI: 10.1113/jphysiol.2009.179283] [Citation(s) in RCA: 24] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
Habitual exercise training, including a high-intensity interval walking programme, improves cardiorespiratory fitness and alleviates lifestyle-related diseases, such as obesity, hypertension and dyslipidaemia. However, the extent of improvement has been shown to differ substantially among individuals for various exercise regimens. A body of literature has demonstrated that gene polymorphisms could account for the inter-individual variability in the improvement of risk factors for lifestyle-related diseases following exercise training. However, the fractions of the variability explained by the polymorphisms are small (5%). Also, it is likely that the effects of gene polymorphisms differ with exercise regimens and subject characteristics. These observations suggest the necessity for further studies to exhaustively identify such gene polymorphisms. More importantly, the physiological and molecular genetic mechanisms by which gene polymorphisms interact with exercise to influence the improvements of risk factors for lifestyle-related diseases differentially remain to be clarified. A better understanding of these issues should lead to more effective integration of exercise to optimize the treatment and management of individuals with lifestyle-related diseases.
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Affiliation(s)
- Masayuki Mori
- Department of Aging Biology, Institute on Aging and Adaptation, Shinshu University Graduate School of Medicine, 3-1-1 Asahi, Matsumoto 390-8621, Japan.
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Bressler J, Fornage M, Hanis CL, Kao WHL, Lewis CE, McPherson R, Dent R, Mosley TH, Pennacchio LA, Boerwinkle E. The INSIG2 rs7566605 genetic variant does not play a major role in obesity in a sample of 24,722 individuals from four cohorts. BMC MEDICAL GENETICS 2009; 10:56. [PMID: 19523229 PMCID: PMC2706232 DOI: 10.1186/1471-2350-10-56] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 11/25/2008] [Accepted: 06/12/2009] [Indexed: 02/08/2023]
Abstract
Background In a genome-wide association study performed in the Framingham Offspring Cohort, individuals homozygous for the rs7566605 C allele located upstream of insulin-induced gene 2 (INSIG2) were reported to incur an increased risk of obesity. This finding was later replicated in four out of five populations examined. The goal of the study reported here was to assess the role of the INSIG2 single nucleotide polymorphism (SNP) in susceptibility to obesity in the prospective longitudinal Atherosclerosis Risk in Communities (ARIC) study (n = 14,566) and in three other cohorts: the Coronary Artery Risk Development in Young Adults (CARDIA) study (n = 3,888), the Genetic Epidemiology Network of Arteriopathy (GENOA) study (n = 4,766), and extremely obese and lean individuals ascertained at the University of Ottawa (n = 1,502). The combined study sample is comprised of 24,722 white, African-American, and Mexican-American participants. Methods Differences in mean body mass index (BMI) and other anthropometric measures including weight, waist circumference, and waist-to-hip ratio were assessed by a general linear model in individuals categorized by INSIG2 rs7566605 genotype. Multivariable logistic regression was used to predict the risk of obesity (BMI ≥ 30 kg/m2). Results There was no discernable variation in the frequencies of the three INSIG2 SNP genotypes observed between white, Hispanic, and African-American obese individuals and non-obese study subjects. When the relationship between rs7566605 and BMI considered either as a categorical variable or a continuous variable was examined, no significant association with obesity was found for participants in any of the four study populations or in a combined analysis (p = 0.38) under a recessive genetic model. There was also no association between the INSIG2 polymorphism and the obesity-related quantitative traits except for a reduced waist-to-hip ratio in white ARIC study participants homozygous for the C allele, and an increased waist-to-hip ratio in African-Americans in the ARIC cohort with the same genotype (p = 0.04 and p = 0.01, respectively). An association with waist-to-hip ratio was not seen when the combined study sample was analyzed (p = 0.74). Conclusion These results suggest that the INSIG2 rs7566605 variant does not play a major role in determining obesity risk in a racially and ethnically diverse sample of 24,722 individuals from four cohorts.
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Affiliation(s)
- Jan Bressler
- Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX 77030, USA.
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