Abstract
Objective:Body mass index (BMI) is commonly used to assess obesity, which is associated with numerous diseases and negative health outcomes. BMI has been shown to be a heritable, polygenic trait, with close to 100 loci previously identified and replicated in multiple populations. We aim to replicate known BMI loci and identify novel associations in a trans-ethnic study population.Subjects:Using eligible participants from the Population Architecture using Genomics and Epidemiology consortium, we conducted a trans-ethnic meta-analysis of 102 514 African Americans, Hispanics, Asian/Native Hawaiian, Native Americans and European Americans. Participants were genotyped on over 200 000 SNPs on the Illumina Metabochip custom array, or imputed into the 1000 Genomes Project (Phase I). Linear regression of the natural log of BMI, adjusting for age, sex, study site (if applicable), and ancestry principal components, was conducted for each race/ethnicity within each study cohort. Race/ethnicity-specific, and combined meta-analyses used fixed-effects models.Results:We replicated 15 of 21 BMI loci included on the Metabochip, and identified two novel BMI loci at 1q41 (rs2820436) and 2q31.1 (rs10930502) at the Metabochip-wide significance threshold (P<2.5 × 10 ' 7). Bioinformatic functional investigation of SNPs at these loci suggests a possible impact on pathways that regulate metabolism and adipose tissue.Conclusion:Conducting studies in genetically diverse populations continues to be a valuable strategy for replicating known loci and uncovering novel BMI associations.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 384-390 |
| Number of pages | 7 |
| Journal | International Journal of Obesity |
| Volume | 42 |
| Issue number | 3 |
| DOIs | |
| State | Published - Mar 1 2018 |
ASJC Scopus subject areas
- Medicine (miscellaneous)
- Endocrinology, Diabetes and Metabolism
- Nutrition and Dietetics
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Trans-ethnic analysis of metabochip data identifies two new loci associated with BMI. / Gong, J.; Nishimura, K. K.; Fernandez-Rhodes, L.; Haessler, J.; Bien, S.; Graff, M.; Lim, U.; Lu, Y.; Gross, M.; Fornage, M.; Yoneyama, S.; Isasi, C. R.; Buzkova, P.; Daviglus, M.; Lin, D. Y.; Tao, R.; Goodloe, R.; Bush, W. S.; Farber-Eger, E.; Boston, J.; Dilks, H. H.; Ehret, G.; Gu, C. C.; Lewis, C. E.; Nguyen, K. D.H.; Cooper, R.; Leppert, M.; Irvin, M. R.; Bottinger, E. P.; Wilkens, L. R.; Haiman, C. A.; Park, L.; Monroe, K. R.; Cheng, I.; Stram, D. O.; Carlson, C. S.; Jackson, R.; Kuller, L.; Houston, D.; Kooperberg, C.; Buyske, S.; Hindorff, L. A.; Crawford, D. C.; Loos, R. J.F.; Le Marchand, L.; Matise, T. C.; North, K. E.; Peters, U.
In: International Journal of Obesity, Vol. 42, No. 3, 01.03.2018, p. 384-390.Research output: Contribution to journal › Article › peer-review
}
TY - JOUR
T1 - Trans-ethnic analysis of metabochip data identifies two new loci associated with BMI
AU - Gong, J.
AU - Nishimura, K. K.
AU - Fernandez-Rhodes, L.
AU - Haessler, J.
AU - Bien, S.
AU - Graff, M.
AU - Lim, U.
AU - Lu, Y.
AU - Gross, M.
AU - Fornage, M.
AU - Yoneyama, S.
AU - Isasi, C. R.
AU - Buzkova, P.
AU - Daviglus, M.
AU - Lin, D. Y.
AU - Tao, R.
AU - Goodloe, R.
AU - Bush, W. S.
AU - Farber-Eger, E.
AU - Boston, J.
AU - Dilks, H. H.
AU - Ehret, G.
AU - Gu, C. C.
AU - Lewis, C. E.
AU - Nguyen, K. D.H.
AU - Cooper, R.
AU - Leppert, M.
AU - Irvin, M. R.
AU - Bottinger, E. P.
AU - Wilkens, L. R.
AU - Haiman, C. A.
AU - Park, L.
AU - Monroe, K. R.
AU - Cheng, I.
AU - Stram, D. O.
AU - Carlson, C. S.
AU - Jackson, R.
AU - Kuller, L.
AU - Houston, D.
AU - Kooperberg, C.
AU - Buyske, S.
AU - Hindorff, L. A.
AU - Crawford, D. C.
AU - Loos, R. J.F.
AU - Le Marchand, L.
AU - Matise, T. C.
AU - North, K. E.
AU - Peters, U.
N1 - Funding Information: 384 390 10.1038/ijo.2017.304 EN J Gong Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA K K Nishimura Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA L Fernandez-Rhodes Department of Epidemiology, School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA J Haessler Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA S Bien Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA M Graff Department of Epidemiology, School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA U Lim Cancer Research Center, University of Hawaii, Honolulu, HI, USA Y Lu The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA The Genetics of Obesity and Related Metabolic Traits Program, Icahn School of Medicine at Mount Sinai, New York, NY, USA Division of Epidemiology, Department of Medicine, Vanderbilt-Ingram Cancer Center, Vanderbilt Epidemiology Center, Vanderbilt University School of Medicine, Nashville, TN, USA M Gross Masonic Cancer Center, University of Minnesota, Minneapolis, MN, USA M Fornage Health Science Center, University of Texas, Austin, TX, USA S Yoneyama Department of Epidemiology, School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA C R Isasi Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA P Buzkova Department of Biostatistics, University of Washington, Seattle, WA, USA M Daviglus Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA D-Y Lin Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA R Tao Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA R Goodloe Center for Human Genetics Research, Vanderbilt University Medical Center, Nashville, TN, USA W S Bush Department of Epidemiology and Biostatistics, Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, USA E Farber-Eger Center for Human Genetics Research, Vanderbilt University Medical Center, Nashville, TN, USA J Boston Center for Human Genetics Research, Vanderbilt University Medical Center, Nashville, TN, USA H H Dilks Sarah Cannon Research Institute, Nashville, TN, USA G Ehret Center for Complex Disease Genomics, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA Division of Cardiology, Geneva University Hospital, Geneva, Switzerland C C Gu Department of Biostatistics, Washington University, St Louis, MO, USA C E Lewis Department of Medicine, University of Alabama, Birmingham, AL, USA K-D H Nguyen Center for Complex Disease Genomics, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA R Cooper Preventive Medicine and Epidemiology, Loyola University, Chicago, IL, USA M Leppert Department of Human Genetics, University of Utah, Salt Lake City, UT, USA M R Irvin Department of Epidemiology, University of Alabama, Birmingham, AL, USA E P Bottinger The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA L R Wilkens Cancer Research Center, University of Hawaii, Honolulu, HI, USA C A Haiman Keck School of Medicine, University of Southern California, Los Angeles, CA, USA L Park Cancer Research Center, University of Hawaii, Honolulu, HI, USA K R Monroe Keck School of Medicine, University of Southern California, Los Angeles, CA, USA I Cheng Cancer Prevention Institute of California, Fremont, CA, USA D O Stram Keck School of Medicine, University of Southern California, Los Angeles, CA, USA C S Carlson Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA R Jackson Department of Internal Medicine, Ohio State Medical Center, Columbus, OH, USA L Kuller Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA D Houston Wake Forest University School of Medicine, Winston-Salem, NC, USA C Kooperberg Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA S Buyske Department of Genetics, Rutgers University, Piscataway, NJ, USA Department of Statistics and Biostatistics, Rutgers University, Piscataway, NJ, USA http://orcid.org/0000-0001-8539-5416 L A Hindorff Division of Genomic Medicine, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA D C Crawford Center for Human Genetics Research, Vanderbilt University Medical Center, Nashville, TN, USA R J F Loos The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA The Genetics of Obesity and Related Metabolic Traits Program, Icahn School of Medicine at Mount Sinai, New York, NY, USA The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA L Le Marchand Cancer Research Center, University of Hawaii, Honolulu, HI, USA T C Matise Department of Genetics, Rutgers University, Piscataway, NJ, USA K E North Department of Epidemiology, School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA U Peters Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA ijo2017304 10.1038/ijo.2017.304 2016 11 30 2017 11 3 2017 11 21 2017 12 21 Objective:Body mass index (BMI) is commonly used to assess obesity, which is associated with numerous diseases and negative health outcomes. BMI has been shown to be a heritable, polygenic trait, with close to 100 loci previously identified and replicated in multiple populations. We aim to replicate known BMI loci and identify novel associations in a trans-ethnic study population.Subjects:Using eligible participants from the Population Architecture using Genomics and Epidemiology consortium, we conducted a trans-ethnic meta-analysis of 102 514 African Americans, Hispanics, Asian/Native Hawaiian, Native Americans and European Americans. Participants were genotyped on over 200 000 SNPs on the Illumina Metabochip custom array, or imputed into the 1000 Genomes Project (Phase I). Linear regression of the natural log of BMI, adjusting for age, sex, study site (if applicable), and ancestry principal components, was conducted for each race/ethnicity within each study cohort. Race/ethnicity-specific, and combined meta-analyses used fixed-effects models.Results:We replicated 15 of 21 BMI loci included on the Metabochip, and identified two novel BMI loci at 1q41 (rs2820436) and 2q31.1 (rs10930502) at the Metabochip-wide significance threshold (P<2.5 × 10 − 7 ). Bioinformatic functional investigation of SNPs at these loci suggests a possible impact on pathways that regulate metabolism and adipose tissue.Conclusion:Conducting studies in genetically diverse populations continues to be a valuable strategy for replicating known loci and uncovering novel BMI associations.
PY - 2018/3/1
Y1 - 2018/3/1
N2 - Objective:Body mass index (BMI) is commonly used to assess obesity, which is associated with numerous diseases and negative health outcomes. BMI has been shown to be a heritable, polygenic trait, with close to 100 loci previously identified and replicated in multiple populations. We aim to replicate known BMI loci and identify novel associations in a trans-ethnic study population.Subjects:Using eligible participants from the Population Architecture using Genomics and Epidemiology consortium, we conducted a trans-ethnic meta-analysis of 102 514 African Americans, Hispanics, Asian/Native Hawaiian, Native Americans and European Americans. Participants were genotyped on over 200 000 SNPs on the Illumina Metabochip custom array, or imputed into the 1000 Genomes Project (Phase I). Linear regression of the natural log of BMI, adjusting for age, sex, study site (if applicable), and ancestry principal components, was conducted for each race/ethnicity within each study cohort. Race/ethnicity-specific, and combined meta-analyses used fixed-effects models.Results:We replicated 15 of 21 BMI loci included on the Metabochip, and identified two novel BMI loci at 1q41 (rs2820436) and 2q31.1 (rs10930502) at the Metabochip-wide significance threshold (P<2.5 × 10 ' 7). Bioinformatic functional investigation of SNPs at these loci suggests a possible impact on pathways that regulate metabolism and adipose tissue.Conclusion:Conducting studies in genetically diverse populations continues to be a valuable strategy for replicating known loci and uncovering novel BMI associations.
AB - Objective:Body mass index (BMI) is commonly used to assess obesity, which is associated with numerous diseases and negative health outcomes. BMI has been shown to be a heritable, polygenic trait, with close to 100 loci previously identified and replicated in multiple populations. We aim to replicate known BMI loci and identify novel associations in a trans-ethnic study population.Subjects:Using eligible participants from the Population Architecture using Genomics and Epidemiology consortium, we conducted a trans-ethnic meta-analysis of 102 514 African Americans, Hispanics, Asian/Native Hawaiian, Native Americans and European Americans. Participants were genotyped on over 200 000 SNPs on the Illumina Metabochip custom array, or imputed into the 1000 Genomes Project (Phase I). Linear regression of the natural log of BMI, adjusting for age, sex, study site (if applicable), and ancestry principal components, was conducted for each race/ethnicity within each study cohort. Race/ethnicity-specific, and combined meta-analyses used fixed-effects models.Results:We replicated 15 of 21 BMI loci included on the Metabochip, and identified two novel BMI loci at 1q41 (rs2820436) and 2q31.1 (rs10930502) at the Metabochip-wide significance threshold (P<2.5 × 10 ' 7). Bioinformatic functional investigation of SNPs at these loci suggests a possible impact on pathways that regulate metabolism and adipose tissue.Conclusion:Conducting studies in genetically diverse populations continues to be a valuable strategy for replicating known loci and uncovering novel BMI associations.
UR - http://www.scopus.com/inward/record.url?scp=85044574499&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85044574499&partnerID=8YFLogxK
U2 - 10.1038/ijo.2017.304
DO - 10.1038/ijo.2017.304
M3 - Article
C2 - 29381148
AN - SCOPUS:85044574499
VL - 42
SP - 384
EP - 390
JO - International Journal of Obesity
JF - International Journal of Obesity
SN - 0307-0565
IS - 3
ER -