Bahram Namjou1,2, Ian B Stanaway3, Todd Lingren4,5, Frank D Mentch6, Barbara Benoit7, Ozan Dikilitas8, Xinnan Niu9, Ning Shang10, Ashley H Shoemaker11, David J Carey12, Tooraj Mirshahi12, Rajbir Singh13, Jordan G Nestor14, Hakon Hakonarson6,15, Joshua C Denny9, David R Crosslin3, Gail P Jarvik16,17, Iftikhar J Kullo8, Marc S Williams18, John B Harley19,4,20. 1. Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center (CCHMC), Cincinnati, OH, USA. bahram.namjou@cchmc.org. 2. College of Medicine, University of Cincinnati, Cincinnati, OH, USA. bahram.namjou@cchmc.org. 3. Department of Biomedical Informatics Medical Education, School of Medicine, University of Washington, Seattle, WA, USA. 4. College of Medicine, University of Cincinnati, Cincinnati, OH, USA. 5. Division of Biomedical Informatics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA. 6. Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, USA. 7. Research Information Science and Computing, Partners HealthCare, Somerville, MA, USA. 8. Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA. 9. Departments of Biomedical Informatics and Medicine, Vanderbilt University, Nashville, TN, USA. 10. Department of Biomedical Informatics, Columbia University, New York, NY, USA. 11. Department of Pediatrics, Division of Endocrinology and Diabetes, Vanderbilt University Medical Center, Nashville, TN, USA. 12. Department of Molecular and Functional Genomics, Geisinger, Danville, PA, USA. 13. Meharry Medical College, Nashville, TN, USA. 14. Department of Medicine, Division of Nephrology, Columbia University, New York, NY, USA. 15. Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. 16. Department of Medicine (Medical Genetics), University of Washington Medical Center, Seattle, WA, USA. 17. Department Genome Sciences, University of Washington Medical Center, Seattle, WA, USA. 18. Genomic Medicine Institute (M.S.W.), Geisinger, Danville, PA, USA. 19. Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center (CCHMC), Cincinnati, OH, USA. 20. U.S. Department of Veterans Affairs Medical Center, Cincinnati, OH, USA.
Abstract
BACKGROUND/ OBJECTIVES: Melanocortin-4 receptor (MC4R) plays an essential role in food intake and energy homeostasis. More than 170 MC4R variants have been described over the past two decades, with conflicting reports regarding the prevalence and phenotypic effects of these variants in diverse cohorts. To determine the frequency of MC4R variants in large cohort of different ancestries, we evaluated the MC4R coding region for 20,537 eMERGE participants with sequencing data plus additional 77,454 independent individuals with genome-wide genotyping data at this locus. SUBJECTS/ METHODS: The sequencing data were obtained from the eMERGE phase III study, in which multisample variant call format calls have been generated, curated, and annotated. In addition to penetrance estimation using body mass index (BMI) as a binary outcome, GWAS and PheWAS were performed using median BMI in linear regression analyses. All results were adjusted for principal components, age, sex, and sites of genotyping. RESULTS: Targeted sequencing data of MC4R revealed 125 coding variants in 1839 eMERGE participants including 30 unreported coding variants that were predicted to be functionally damaging. Highly penetrant unreported variants included (L325I, E308K, D298N, S270F, F261L, T248A, D111V, and Y80F) in which seven participants had obesity class III defined as BMI ≥ 40 kg/m2. In GWAS analysis, in addition to known risk haplotype upstream of MC4R (best variant rs6567160 (P = 5.36 × 10-25, Beta = 0.37), a novel rare haplotype was detected which was protective against obesity and encompassed the V103I variant with known gain-of-function properties (P = 6.23 × 10-08, Beta = -0.62). PheWAS analyses extended this protective effect of V103I to type 2 diabetes, diabetic nephropathy, and chronic renal failure independent of BMI. CONCLUSIONS: MC4R screening in a large eMERGE cohort confirmed many previous findings, extend the MC4R pleotropic effects, and discovered additional MC4R rare alleles that probably contribute to obesity.
BACKGROUND/ OBJECTIVES: Melanocortin-4 receptor (MC4R) plays an essential role in food intake and energy homeostasis. More than 170 MC4R variants have been described over the past two decades, with conflicting reports regarding the prevalence and phenotypic effects of these variants in diverse cohorts. To determine the frequency of MC4R variants in large cohort of different ancestries, we evaluated the MC4R coding region for 20,537 eMERGE participants with sequencing data plus additional 77,454 independent individuals with genome-wide genotyping data at this locus. SUBJECTS/ METHODS: The sequencing data were obtained from the eMERGE phase III study, in which multisample variant call format calls have been generated, curated, and annotated. In addition to penetrance estimation using body mass index (BMI) as a binary outcome, GWAS and PheWAS were performed using median BMI in linear regression analyses. All results were adjusted for principal components, age, sex, and sites of genotyping. RESULTS: Targeted sequencing data of MC4R revealed 125 coding variants in 1839 eMERGE participants including 30 unreported coding variants that were predicted to be functionally damaging. Highly penetrant unreported variants included (L325I, E308K, D298N, S270F, F261L, T248A, D111V, and Y80F) in which seven participants had obesity class III defined as BMI ≥ 40 kg/m2. In GWAS analysis, in addition to known risk haplotype upstream of MC4R (best variant rs6567160 (P = 5.36 × 10-25, Beta = 0.37), a novel rare haplotype was detected which was protective against obesity and encompassed the V103I variant with known gain-of-function properties (P = 6.23 × 10-08, Beta = -0.62). PheWAS analyses extended this protective effect of V103I to type 2 diabetes, diabetic nephropathy, and chronic renal failure independent of BMI. CONCLUSIONS: MC4R screening in a large eMERGE cohort confirmed many previous findings, extend the MC4R pleotropic effects, and discovered additional MC4R rare alleles that probably contribute to obesity.
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