Laura Kelly Vaughan1, Howard W Wiener2, Stella Aslibekyan3, David B Allison4, Peter J Havel5, Kimber L Stanhope6, Diane M O'Brien7, Scarlett E Hopkins8, Dominick J Lemas9, Bert B Boyer10, Hemant K Tiwari11. 1. Department of Biology, King University, 1350 King College Rd, Bristol, TN 37620, USA. Electronic address: lkvaughan@king.edu. 2. Department of Epidemiology, University of Alabama at Birmingham, 1665 University Blvd, Birmingham, AL 35294, USA. Electronic address: hwiener@uab.edu. 3. Department of Epidemiology, University of Alabama at Birmingham, 1665 University Blvd, Birmingham, AL 35294, USA. Electronic address: saslibek@uab.edu. 4. Section on Statistical Genetics, Department of Biostatistics, University of Alabama at Birmingham, 1665 University Blvd, Birmingham, AL 35294, USA. Electronic address: dallison@uab.edu. 5. Departments of Nutrition and Molecular Biosciences, University of California at Davis, 1 Shields Ave, Davis, CA 95616, USA. Electronic address: pjhavel@ucdavis.edu. 6. Departments of Nutrition and Molecular Biosciences, University of California at Davis, 1 Shields Ave, Davis, CA 95616, USA. Electronic address: klstanhope@ucdavis.edu. 7. USACenter for Alaska Native Health Research, Institute of Arctic Biology, 311 Irving I Building, University of Alaska Fairbanks, Fairbanks, AK 99775, USA. Electronic address: dmobrien@alaska.edu. 8. USACenter for Alaska Native Health Research, Institute of Arctic Biology, 311 Irving I Building, University of Alaska Fairbanks, Fairbanks, AK 99775, USA. Electronic address: scarlett.hopkins@gmail.com. 9. Department of Pediatrics, Section of Neonatology, University of Colorado Anschutz Medical Campus, 13123 East 16th Ave, Aurora, CO 80045, USA. Electronic address: dominick.lemas@ucdenver.edu. 10. USACenter for Alaska Native Health Research, Institute of Arctic Biology, 311 Irving I Building, University of Alaska Fairbanks, Fairbanks, AK 99775, USA. Electronic address: bboyer@alaska.edu. 11. Section on Statistical Genetics, Department of Biostatistics, University of Alabama at Birmingham, 1665 University Blvd, Birmingham, AL 35294, USA. Electronic address: htiwari@uab.edu.
Abstract
OBJECTIVE: To identify novel genetic markers of obesity-related traits and to identify gene-diet interactions with n-3 polyunsaturated fatty acid (n-3 PUFA) intake in Yup'ik people. MATERIAL AND METHODS: We measured body composition, plasma adipokines and ghrelin in 982 participants enrolled in the Center for Alaska Native Health Research (CANHR) Study. We conducted a genome-wide SNP linkage scan and targeted association analysis, fitting additional models to investigate putative gene-diet interactions. Finally, we performed bioinformatic analysis to uncover likely candidate genes within the identified linkage peaks. RESULTS: We observed evidence of linkage for all obesity-related traits, replicating previous results and identifying novel regions of interest for adiponectin (10q26.13-2) and thigh circumference (8q21.11-13). Bioinformatic analysis revealed DOCK1, PTPRE (10q26.13-2) and FABP4 (8q21.11-13) as putative candidate genes in the newly identified regions. Targeted SNP analysis under the linkage peaks identified associations between three SNPs and obesity-related traits: rs1007750 on chromosome 8 and thigh circumference (P=0.0005), rs878953 on chromosome 5 and thigh skinfold (P=0.0004), and rs1596854 on chromosome 11 for waist circumference (P=0.0003). Finally, we showed that n-3 PUFA modified the association between obesity related traits and two additional variants (rs2048417 on chromosome 3 for adiponectin, P for interaction=0.0006 and rs730414 on chromosome 11 for percentage body fat, P for interaction=0.0004). CONCLUSIONS: This study presents evidence of novel genomic regions and gene-diet interactions that may contribute to the pathophysiology of obesity-related traits among Yup'ik people.
OBJECTIVE: To identify novel genetic markers of obesity-related traits and to identify gene-diet interactions with n-3 polyunsaturated fatty acid (n-3 PUFA) intake in Yup'ik people. MATERIAL AND METHODS: We measured body composition, plasma adipokines and ghrelin in 982 participants enrolled in the Center for Alaska Native Health Research (CANHR) Study. We conducted a genome-wide SNP linkage scan and targeted association analysis, fitting additional models to investigate putative gene-diet interactions. Finally, we performed bioinformatic analysis to uncover likely candidate genes within the identified linkage peaks. RESULTS: We observed evidence of linkage for all obesity-related traits, replicating previous results and identifying novel regions of interest for adiponectin (10q26.13-2) and thigh circumference (8q21.11-13). Bioinformatic analysis revealed DOCK1, PTPRE (10q26.13-2) and FABP4 (8q21.11-13) as putative candidate genes in the newly identified regions. Targeted SNP analysis under the linkage peaks identified associations between three SNPs and obesity-related traits: rs1007750 on chromosome 8 and thigh circumference (P=0.0005), rs878953 on chromosome 5 and thigh skinfold (P=0.0004), and rs1596854 on chromosome 11 for waist circumference (P=0.0003). Finally, we showed that n-3 PUFA modified the association between obesity related traits and two additional variants (rs2048417 on chromosome 3 for adiponectin, P for interaction=0.0006 and rs730414 on chromosome 11 for percentage body fat, P for interaction=0.0004). CONCLUSIONS: This study presents evidence of novel genomic regions and gene-diet interactions that may contribute to the pathophysiology of obesity-related traits among Yup'ik people.
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