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Lo YC, Tian H, Chan TF, Jeon S, Alatorre K, Dinh BL, Maskarinec G, Taparra K, Nakatsuka N, Yu M, Chen CY, Lin YF, Wilkens LR, Le Marchand L, Haiman CA, Chiang CWK. The accuracy of polygenic score models for BMI and Type II diabetes in the Native Hawaiian population. Commun Biol 2025; 8:651. [PMID: 40269120 PMCID: PMC12018950 DOI: 10.1038/s42003-025-08050-7] [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: 08/23/2024] [Accepted: 04/07/2025] [Indexed: 04/25/2025] Open
Abstract
Polygenic scores (PGS) are promising in stratifying individuals based on the genetic susceptibility to complex diseases or traits. However, the accuracy of PGS models, typically trained in European- or East Asian-ancestry populations, tend to perform poorly in other ethnic minority populations and their accuracies have not been evaluated for Native Hawaiians. In particular, for body mass index (BMI) and type-2 diabetes (T2D), Polynesian-ancestry individuals such as Native Hawaiians or Samoans exhibit varied distribution from other continental populations, but are understudied, particularly in the context of PGS. Using BMI and T2D as examples of metabolic traits of importance to Polynesian populations (along with height as a comparison of a similarly highly polygenic trait), here we examine the prediction accuracies of PGS models in a large Native Hawaiian sample from the Multiethnic Cohort with up to 5300 individuals. We find evidence of lowered prediction accuracies for the PGS models in some cases, particularly for height. We also find that using the Native Hawaiian samples as an optimization cohort during training does not consistently improve PGS performance. Moreover, even the best-performing PGS models among Native Hawaiians have lowered prediction accuracy among the subset of individuals most enriched with Polynesian ancestry. Our findings indicate that factors such as admixture histories, sample size, and diversity in GWAS can influence PGS performance for complex traits among Native Hawaiian samples. This study provides an initial survey of PGS performance among Native Hawaiians and exposes the current gaps and challenges associated with improving polygenic prediction models for underrepresented minority populations.
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Affiliation(s)
- Ying-Chu Lo
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - He Tian
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Tsz Fung Chan
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Soyoung Jeon
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Kimberli Alatorre
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Bryan L Dinh
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Gertraud Maskarinec
- Epidemiology Program, University of Hawai'i Cancer Center, University of Hawai'i, Manoa, Honolulu, HI, USA
| | - Kekoa Taparra
- Standard Health Care, Department of Radiation Oncology, Palo Alto, CA, USA
| | | | - Mingrui Yu
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | | | - Yen-Feng Lin
- Center for Neuropsychiatric Research, National Health Research Institutes, Miaoli, Taiwan
- Department of Public Health & Medical Humanities, School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
- Institute of Behavioral Medicine, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Lynne R Wilkens
- Epidemiology Program, University of Hawai'i Cancer Center, University of Hawai'i, Manoa, Honolulu, HI, USA
| | - Loic Le Marchand
- Epidemiology Program, University of Hawai'i Cancer Center, University of Hawai'i, Manoa, Honolulu, HI, USA
| | - Christopher A Haiman
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Cancer Epidemiology Program, Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, USA
| | - Charleston W K Chiang
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
- Cancer Epidemiology Program, Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, USA.
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA.
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2
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Harries V, Abraham J, Vesi L, Reupena A, Faaselele-Savusa K, Duckham RL, Bribiescas R, Hawley N. The milk study protocol: A longitudinal, prospective cohort study of the relationship between human milk metabolic hormone concentration, maternal body composition, and early growth and satiety development in Samoan infants aged 1-4 months. PLoS One 2024; 19:e0292997. [PMID: 38728264 PMCID: PMC11086876 DOI: 10.1371/journal.pone.0292997] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Accepted: 10/03/2023] [Indexed: 05/12/2024] Open
Abstract
BACKGROUND Current research suggests that energy transfer through human milk influences infant nutritional development and initiates metabolic programming, influencing eating patterns into adulthood. To date, this research has predominantly been conducted among women in high income settings and/or among undernourished women. We will investigate the relationship between maternal body composition, metabolic hormones in human milk, and infant satiety to explore mechanisms of developmental satiety programming and implications for early infant growth and body composition in Samoans; a population at high risk and prevalence for overweight and obesity. Our aims are (1) to examine how maternal body composition influences metabolic hormone transfer from mother to infant through human milk, and (2) to examine the influences of maternal metabolic hormone transfer and infant feeding patterns on early infant growth and satiety. METHODS We will examine temporal changes in hormone transfers to infants through human milk in a prospective longitudinal cohort of n = 80 Samoan mother-infant dyads. Data will be collected at three time points (1, 3, & 4 months postpartum). At each study visit we will collect human milk and fingerpick blood samples from breastfeeding mother-infant dyads to measure the hormones leptin, ghrelin, and adiponectin. Additionally, we will obtain body composition measurements from the dyad, observe breastfeeding behavior, conduct semi-structured interviews, and use questionnaires to document infant hunger and feeding cues and satiety responsiveness. Descriptive statistics, univariate and multivariate analyses will be conducted to address each aim. DISCUSSION This research is designed to advance our understanding of variation in the developmental programming of satiety and implications for early infant growth and body composition. The use of a prospective longitudinal cohort alongside data collection that utilizes a mixed methods approach will allow us to capture a more accurate representation on both biological and cultural variables at play in a population at high risk of overweight and obesity.
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Affiliation(s)
- Victoria Harries
- Department of Anthropology, Yale University, New Haven, Connecticut, United States of America
| | - Jyothi Abraham
- School of Nursing, National University of Samoa, Apia, Samoa
| | - Lupesina Vesi
- Obesity, Lifestyle, and Genetic Adaptations Study Group, Apia, Samoa
| | - Aniva Reupena
- Obesity, Lifestyle, and Genetic Adaptations Study Group, Apia, Samoa
| | | | - Rachel L. Duckham
- Institute of Physical Activity and Nutrition, Deakin University, Geelong, Australia
- Australian Institute for Musculoskeletal Sciences, The University of Melbourne and Western Health, St Albans, Australia
| | - Richard Bribiescas
- Department of Anthropology, Yale University, New Haven, Connecticut, United States of America
| | - Nicola Hawley
- Department of Chronic Disease Epidemiology, Yale School of Public Health, New Haven, Connecticut, United States of America
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3
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Amitrano F, Krishnan M, Murphy R, Okesene-Gafa KAM, Ji M, Thompson JMD, Taylor RS, Merriman TR, Rush E, McCowan M, McCowan LME, McKinlay CJD. The impact of CREBRF rs373863828 Pacific-variant on infant body composition. Sci Rep 2024; 14:8825. [PMID: 38627436 PMCID: PMC11021527 DOI: 10.1038/s41598-024-59417-5] [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: 12/21/2023] [Accepted: 04/10/2024] [Indexed: 04/19/2024] Open
Abstract
In Māori and Pacific adults, the CREBRF rs373863828 minor (A) allele is associated with increased body mass index (BMI) but reduced incidence of type-2 and gestational diabetes mellitus. In this prospective cohort study of Māori and Pacific infants, nested within a nutritional intervention trial for pregnant women with obesity and without pregestational diabetes, we investigated whether the rs373863828 A allele is associated with differences in growth and body composition from birth to 12-18 months' corrected age. Infants with and without the variant allele were compared using generalised linear models adjusted for potential confounding by gestation length, sex, ethnicity and parity, and in a secondary analysis, additionally adjusted for gestational diabetes. Carriage of the rs373863828 A allele was not associated with altered growth and body composition from birth to 6 months. At 12-18 months, infants with the rs373863828 A allele had lower whole-body fat mass [FM 1.4 (0.7) vs. 1.7 (0.7) kg, aMD -0.4, 95% CI -0.7, 0.0, P = 0.05; FM index 2.2 (1.1) vs. 2.6 (1.0) kg/m2 aMD -0.6, 95% CI -1.2,0.0, P = 0.04]. However, this association was not significant after adjustment for gestational diabetes, suggesting that it may be mediated, at least in part, by the beneficial effect of CREBRF rs373863828 A allele on maternal glycemic status.
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Affiliation(s)
| | - Mohanraj Krishnan
- Department of Obstetrics and Gynaecology, University of Auckland, Auckland, New Zealand
- Department of Medicine, University of Auckland, Auckland, New Zealand
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Rinki Murphy
- Department of Medicine, University of Auckland, Auckland, New Zealand
- Te Whatu Ora, Counties Manukau, Auckland, New Zealand
- Maurice Wilkins Centre for Molecular Biodiscovery, University of Auckland, Auckland, New Zealand
| | - Karaponi A M Okesene-Gafa
- Department of Obstetrics and Gynaecology, University of Auckland, Auckland, New Zealand
- Te Whatu Ora, Counties Manukau, Auckland, New Zealand
| | - Maria Ji
- Department of Obstetrics and Gynaecology, University of Auckland, Auckland, New Zealand
| | - John M D Thompson
- Department of Obstetrics and Gynaecology, University of Auckland, Auckland, New Zealand
- Department of Paediatrics: Child and Youth Health, University of Auckland, Auckland, New Zealand
| | - Rennae S Taylor
- Department of Obstetrics and Gynaecology, University of Auckland, Auckland, New Zealand
| | - Tony R Merriman
- Department of Microbiology and Immunology, University of Otago, Dunedin, New Zealand
- Division of Clinical Immunology and Rheumatology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Elaine Rush
- Faculty of Health and Environmental Science, Auckland University of Technology, Auckland, New Zealand
| | - Megan McCowan
- Te Whatu Ora, Counties Manukau, Auckland, New Zealand
| | - Lesley M E McCowan
- Department of Obstetrics and Gynaecology, University of Auckland, Auckland, New Zealand
- Te Whatu Ora, Counties Manukau, Auckland, New Zealand
| | - Christopher J D McKinlay
- Te Whatu Ora, Counties Manukau, Auckland, New Zealand.
- Department of Paediatrics: Child and Youth Health, University of Auckland, Auckland, New Zealand.
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Zhang JZ, Heinsberg LW, Krishnan M, Hawley NL, Major TJ, Carlson JC, Hindmarsh JH, Watson H, Qasim M, Stamp LK, Dalbeth N, Murphy R, Sun G, Cheng H, Naseri T, Reupena MS, Kershaw EE, Deka R, McGarvey ST, Minster RL, Merriman TR, Weeks DE. Multivariate analysis of a missense variant in CREBRF reveals associations with measures of adiposity in people of Polynesian ancestries. Genet Epidemiol 2023; 47:105-118. [PMID: 36352773 PMCID: PMC9892232 DOI: 10.1002/gepi.22508] [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: 06/14/2022] [Revised: 09/02/2022] [Accepted: 10/05/2022] [Indexed: 11/11/2022]
Abstract
The minor allele of rs373863828, a missense variant in CREB3 Regulatory Factor, is associated with several cardiometabolic phenotypes in Polynesian peoples. To better understand the variant, we tested the association of rs373863828 with a panel of correlated phenotypes (body mass index [BMI], weight, height, HDL cholesterol, triglycerides, and total cholesterol) using multivariate Bayesian association and network analyses in a Samoa cohort (n = 1632), Aotearoa New Zealand cohort (n = 1419), and combined cohort (n = 2976). An expanded set of phenotypes (adding estimated fat and fat-free mass, abdominal circumference, hip circumference, and abdominal-hip ratio) was tested in the Samoa cohort (n = 1496). In the Samoa cohort, we observed significant associations (log10 Bayes Factor [BF] ≥ 5.0) between rs373863828 and the overall phenotype panel (8.81), weight (8.30), and BMI (6.42). In the Aotearoa New Zealand cohort, we observed suggestive associations (1.5 < log10 BF < 5) between rs373863828 and the overall phenotype panel (4.60), weight (3.27), and BMI (1.80). In the combined cohort, we observed concordant signals with larger log10 BFs. In the Samoa-specific expanded phenotype analyses, we also observed significant associations between rs373863828 and fat mass (5.65), abdominal circumference (5.34), and hip circumference (5.09). Bayesian networks provided evidence for a direct association of rs373863828 with weight and indirect associations with height and BMI.
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Affiliation(s)
- Jerry Z. Zhang
- Department of Biostatistics, School of Public Health, University of Pittsburgh, Pittsburgh, PA
| | - Lacey W. Heinsberg
- Department of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, PA
| | - Mohanraj Krishnan
- Department of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, PA
| | - Nicola L. Hawley
- Department of Chronic Disease Epidemiology, Yale University School of Public Health, New Haven, CT
| | - Tanya J. Major
- Department of Biochemistry, University of Otago, Dunedin, New Zealand
| | - Jenna C. Carlson
- Department of Biostatistics, School of Public Health, University of Pittsburgh, Pittsburgh, PA
- Department of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, PA
| | | | - Huti Watson
- Ngāti Porou Hauora Charitable Trust, Te Puia Springs, Tairāwhiti, New Zealand
| | - Muhammad Qasim
- Ngāti Porou Hauora Charitable Trust, Te Puia Springs, Tairāwhiti, New Zealand
| | - Lisa K. Stamp
- Department of Medicine, University of Otago, Christchurch, New Zealand
| | - Nicola Dalbeth
- Department of Medicine, University of Auckland, Auckland, New Zealand
| | - Rinki Murphy
- Department of Medicine, University of Auckland, Auckland, New Zealand
- Maurice Wilkins Centre for Molecular Biodiscovery, Auckland, New Zealand
| | - Guangyun Sun
- Department of Environmental and Public Health Sciences, College of Medicine, University of Cincinnati, Cincinnati, OH
| | - Hong Cheng
- Department of Environmental and Public Health Sciences, College of Medicine, University of Cincinnati, Cincinnati, OH
| | - Take Naseri
- Ministry of Health, Government of Samoa, Apia, Samoa
| | | | - Erin E. Kershaw
- Division of Endocrinology and Metabolism, Department of Medicine, University of Pittsburgh, Pittsburgh, PA
| | - Ranjan Deka
- Department of Environmental and Public Health Sciences, College of Medicine, University of Cincinnati, Cincinnati, OH
| | - Stephen T. McGarvey
- International Health Institute, Department of Epidemiology, School of Public Health, Brown University, Providence, RI
- Department of Anthropology, Brown University, Providence, RI
| | - Ryan L. Minster
- Department of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, PA
| | - Tony R. Merriman
- Department of Biochemistry, University of Otago, Dunedin, New Zealand
- Maurice Wilkins Centre for Molecular Biodiscovery, Auckland, New Zealand
- Division of Clinical Immunology and Rheumatology, University of Alabama Birmingham, Birmingham, AL
| | - Daniel E. Weeks
- Department of Biostatistics, School of Public Health, University of Pittsburgh, Pittsburgh, PA
- Department of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, PA
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5
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Carlson JC, Krishnan M, Rosenthal SL, Russell EM, Zhang JZ, Hawley NL, Moors J, Cheng H, Dalbeth N, de Zoysa JR, Watson H, Qasim M, Murphy R, Naseri T, Reupena MS, Viali S, Stamp LK, Tuitele J, Kershaw EE, Deka R, McGarvey ST, Merriman TR, Weeks DE, Minster RL. A stop-gain variant in BTNL9 is associated with atherogenic lipid profiles. HGG ADVANCES 2023; 4:100155. [PMID: 36340932 PMCID: PMC9630829 DOI: 10.1016/j.xhgg.2022.100155] [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: 06/22/2022] [Accepted: 10/10/2022] [Indexed: 11/12/2022] Open
Abstract
Current understanding of lipid genetics has come mainly from studies in European-ancestry populations; limited effort has focused on Polynesian populations, whose unique population history and high prevalence of dyslipidemia may provide insight into the biological foundations of variation in lipid levels. Here, we performed an association study to fine map a suggestive association on 5q35 with high-density lipoprotein cholesterol (HDL-C) seen in Micronesian and Polynesian populations. Fine-mapping analyses in a cohort of 2,851 Samoan adults highlighted an association between a stop-gain variant (rs200884524; c.652C>T, p.R218∗; posterior probability = 0.9987) in BTNL9 and both lower HDL-C and greater triglycerides (TGs). Meta-analysis across this and several other cohorts of Polynesian ancestry from Samoa, American Samoa, and Aotearoa New Zealand confirmed the presence of this association (βHDL-C = -1.60 mg/dL, p HDL-C = 7.63 × 10-10; βTG = 12.00 mg/dL, p TG = 3.82 × 10-7). While this variant appears to be Polynesian specific, there is also evidence of association from other multiancestry analyses in this region. This work provides evidence of a previously unexplored contributor to the genetic architecture of lipid levels and underscores the importance of genetic analyses in understudied populations.
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Affiliation(s)
- Jenna C. Carlson
- Department of Biostatistics, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, USA
| | - Mohanraj Krishnan
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, USA
| | - Samantha L. Rosenthal
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, USA
- Center for Craniofacial and Dental Genetics, Department of Oral Biology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Emily M. Russell
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, USA
| | - Jerry Z. Zhang
- Department of Biostatistics, University of Pittsburgh, Pittsburgh, PA, USA
| | - Nicola L. Hawley
- Department of Chronic Disease Epidemiology, Yale School of Public Health, New Haven, CT, USA
| | - Jaye Moors
- Department of Biochemistry, University of Otago, Dunedin, New Zealand
| | - Hong Cheng
- Department of Environmental Health, College of Medicine, University of Cincinnati, Cincinnati, OH, USA
| | - Nicola Dalbeth
- Department of Medicine, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand
| | - Janak R. de Zoysa
- Department of Medicine, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand
| | - Huti Watson
- Ngāti Porou Hauora Charitable Trust, Te Puia Springs, Tairāwhiti East Coast, New Zealand
| | - Muhammad Qasim
- Ngāti Porou Hauora Charitable Trust, Te Puia Springs, Tairāwhiti East Coast, New Zealand
| | - Rinki Murphy
- Department of Medicine, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand
- Maurice Wilkins Centre for Molecular Biodiscovery, University of Auckland, Auckland, New Zealand
| | - Take Naseri
- Ministry of Health, Government of Samoa, Apia, Samoa
| | | | | | - Lisa K. Stamp
- Department of Medicine, University of Otago Christchurch, Christchurch, New Zealand
| | - John Tuitele
- Department of Public Health, Government of American Samoa, Pago Pago, American Samoa
| | - Erin E. Kershaw
- Division of Endocrinology, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Ranjan Deka
- Department of Environmental Health, College of Medicine, University of Cincinnati, Cincinnati, OH, USA
| | - Stephen T. McGarvey
- International Health Institute, Department of Epidemiology, Brown University, Providence, RI, USA
- Department of Anthropology, Brown University, Providence, RI, USA
| | - Tony R. Merriman
- Department of Biochemistry, University of Otago, Dunedin, New Zealand
- Maurice Wilkins Centre for Molecular Biodiscovery, University of Auckland, Auckland, New Zealand
| | - Daniel E. Weeks
- Department of Biostatistics, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, USA
| | - Ryan L. Minster
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, USA
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6
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Hawley NL, Duckham RL, Carlson JC, Naseri T, Reupena MS, Lameko V, Pomer A, Wetzel A, Selu M, Lupematisila V, Unasa F, Vesi L, Fatu T, Unasa S, Faasalele-Savusa K, Rivara AC, Russell E, Delany JP, Viali S, Kershaw EE, Minster RL, Weeks DE, McGarvey ST. The protective effect of rs373863828 on type 2 diabetes does not operate through a body composition pathway in adult Samoans. Obesity (Silver Spring) 2022; 30:2468-2476. [PMID: 36284436 PMCID: PMC10111239 DOI: 10.1002/oby.23559] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Revised: 04/01/2022] [Accepted: 05/09/2022] [Indexed: 01/04/2023]
Abstract
OBJECTIVE The aim of this study was to understand whether the paradoxical association of missense variant rs373863828 in CREB3 regulatory factor (CREBRF) with higher BMI but lower odds of diabetes is explained by either metabolically favorable body fat distribution or greater fat-free mass. METHODS This study explored the association of the minor allele with dual-energy x-ray absorptiometry-derived body composition in n = 421 Samoans and used path analysis to examine the mediating role of fat and fat-free mass on the relationship between rs373863828 and fasting glucose. RESULTS Among females, the rs373863828 minor A allele was associated with greater BMI. There was no association of genotype with percent body fat, visceral adiposity, or fat distribution in either sex. In both females and males, lean mass was greater with each A allele: 2.16 kg/copy (p = 0.0001) and 1.73 kg/copy (p = 0.02), respectively. Path analysis showed a direct negative effect of rs373863828 genotype on fasting glucose (p = 0.004) consistent with previous findings, but also an indirect positive effect on fasting glucose operating through fat-free mass (p = 0.027). CONCLUSIONS The protective effect of rs373863828 in CREBRF, common among Pacific Islanders, on type 2 diabetes does not operate through body composition. Rather, the variant's effects on body size/composition and fasting glucose likely operate via different, tissue-specific mechanisms.
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Affiliation(s)
- Nicola L. Hawley
- Department of Chronic Disease Epidemiology, Yale School of Public Health, New Haven, CT, USA
| | - Rachel L. Duckham
- Institute of Physical Activity and Nutrition, Deakin University, Melbourne, VIC, Australia
- Australian Institute for Musculoskeletal Science (AIMSS), The University of Melbourne and Western Health, St Albans, Victoria, Australia
| | - Jenna C. Carlson
- Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | | | | | | | - Alysa Pomer
- Department of Chronic Disease Epidemiology, Yale School of Public Health, New Haven, CT, USA
| | - Abigail Wetzel
- International Health Institute, Department of Epidemiology, School of Public Health, Brown University, Providence, RI, USA
| | - Melania Selu
- Obesity, Lifestyle and Genetic Adaptations Study Group, Apia, Samoa
| | | | - Folla Unasa
- Obesity, Lifestyle and Genetic Adaptations Study Group, Apia, Samoa
| | - Lupesina Vesi
- Obesity, Lifestyle and Genetic Adaptations Study Group, Apia, Samoa
| | - Tracy Fatu
- Obesity, Lifestyle and Genetic Adaptations Study Group, Apia, Samoa
| | - Seipepa Unasa
- Obesity, Lifestyle and Genetic Adaptations Study Group, Apia, Samoa
| | | | - Anna C. Rivara
- Department of Chronic Disease Epidemiology, Yale School of Public Health, New Haven, CT, USA
| | - Emily Russell
- Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - James P. Delany
- AdventHealth, Translational Research Institute, Orlando, FL, USA
| | | | - Erin E. Kershaw
- Division of Endocrinology, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Ryan L. Minster
- Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Daniel E. Weeks
- Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Stephen T. McGarvey
- International Health Institute, Department of Epidemiology, School of Public Health, Brown University, Providence, RI, USA
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7
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Li Y, Wang H, Chen H, Liao Y, Gou S, Yan Q, Zhuang Z, Li H, Wang J, Suo Y, Lan T, Liu Y, Zhao Y, Zou Q, Nie T, Hui X, Lai L, Wu D, Fan N. Generation of a genetically modified pig model with CREBRF R457Q variant. FASEB J 2022; 36:e22611. [PMID: 36250915 DOI: 10.1096/fj.202201117] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Accepted: 10/03/2022] [Indexed: 11/11/2022]
Abstract
Obesity is among the strongest risk factors for type 2 diabetes (T2D). The CREBRF missense allele rs373863828 (p. Arg457Gln, p. R457Q) is associated with increased body mass index but reduced risk of T2D in people of Pacific ancestry. To investigate the functional consequences of the CREBRF variant, we introduced the corresponding human mutation R457Q into the porcine genome. The CREBRFR457Q pigs displayed dramatically increased fat deposition, which was mainly distributed in subcutaneous adipose tissue other than visceral adipose tissue. The CREBRFR457Q variant promoted preadipocyte differentiation. The increased differentiation capacity of precursor adipocytes conferred pigs the unique histological phenotype that adipocytes had a smaller size but a greater number in subcutaneous adipose tissue (SAT) of CREBRFR457Q variant pigs. In addition, in SAT of CREBRFR457Q pigs, the contents of the peroxidative metabolites 4-hydroxy-nonenal and malondialdehyde were significantly decreased, while the activity of antioxidant enzymes, such as glutathione peroxidase, superoxide dismutase, and catalase, was increased, which was in accordance with the declined level of the reactive oxygen species (ROS) in CREBRFR457Q pigs. Together, these data supported a causal role of the CREBRFR457Q variant in the pathogenesis of obesity, partly via adipocyte hyperplasia, and further suggested that reduced oxidative stress in adipose tissue may mediate the relative metabolic protection afforded by this variant despite the related obesity.
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Affiliation(s)
- Yingying Li
- CAS Key Laboratory of Regenerative Biology, GIBH-HKU Guangdong-Hong Kong Stem Cell and Regenerative Medicine Research Centre, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China.,University of Chinese Academy of Sciences, Beijing, China.,Sanya Institute of Swine Resource, Hainan Provincial Research Centre of Laboratory Animals, Sanya, China.,Research Unit of Generation of Large Animal Disease Models, Chinese Academy of Medical Sciences (2019RU015), Guangzhou, China.,Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, China
| | - Hai Wang
- CAS Key Laboratory of Regenerative Biology, GIBH-HKU Guangdong-Hong Kong Stem Cell and Regenerative Medicine Research Centre, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China.,Sanya Institute of Swine Resource, Hainan Provincial Research Centre of Laboratory Animals, Sanya, China.,Research Unit of Generation of Large Animal Disease Models, Chinese Academy of Medical Sciences (2019RU015), Guangzhou, China.,Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, China
| | - Huangyao Chen
- CAS Key Laboratory of Regenerative Biology, GIBH-HKU Guangdong-Hong Kong Stem Cell and Regenerative Medicine Research Centre, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China.,Sanya Institute of Swine Resource, Hainan Provincial Research Centre of Laboratory Animals, Sanya, China.,Research Unit of Generation of Large Animal Disease Models, Chinese Academy of Medical Sciences (2019RU015), Guangzhou, China.,Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, China
| | - Yuan Liao
- CAS Key Laboratory of Regenerative Biology, GIBH-HKU Guangdong-Hong Kong Stem Cell and Regenerative Medicine Research Centre, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China.,Institute of Physical Science and Information Technology, Anhui University, Hefei, China
| | - Shixue Gou
- CAS Key Laboratory of Regenerative Biology, GIBH-HKU Guangdong-Hong Kong Stem Cell and Regenerative Medicine Research Centre, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China.,Sanya Institute of Swine Resource, Hainan Provincial Research Centre of Laboratory Animals, Sanya, China.,Research Unit of Generation of Large Animal Disease Models, Chinese Academy of Medical Sciences (2019RU015), Guangzhou, China.,Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, China
| | - Quanmei Yan
- CAS Key Laboratory of Regenerative Biology, GIBH-HKU Guangdong-Hong Kong Stem Cell and Regenerative Medicine Research Centre, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China
| | - Zhenpeng Zhuang
- CAS Key Laboratory of Regenerative Biology, GIBH-HKU Guangdong-Hong Kong Stem Cell and Regenerative Medicine Research Centre, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China.,Sanya Institute of Swine Resource, Hainan Provincial Research Centre of Laboratory Animals, Sanya, China.,Research Unit of Generation of Large Animal Disease Models, Chinese Academy of Medical Sciences (2019RU015), Guangzhou, China.,Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, China
| | - Hao Li
- CAS Key Laboratory of Regenerative Biology, GIBH-HKU Guangdong-Hong Kong Stem Cell and Regenerative Medicine Research Centre, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China.,Sanya Institute of Swine Resource, Hainan Provincial Research Centre of Laboratory Animals, Sanya, China.,Research Unit of Generation of Large Animal Disease Models, Chinese Academy of Medical Sciences (2019RU015), Guangzhou, China.,Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, China
| | - Jiaowei Wang
- CAS Key Laboratory of Regenerative Biology, GIBH-HKU Guangdong-Hong Kong Stem Cell and Regenerative Medicine Research Centre, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China.,Sanya Institute of Swine Resource, Hainan Provincial Research Centre of Laboratory Animals, Sanya, China.,Research Unit of Generation of Large Animal Disease Models, Chinese Academy of Medical Sciences (2019RU015), Guangzhou, China.,Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, China
| | - Yangyang Suo
- CAS Key Laboratory of Regenerative Biology, GIBH-HKU Guangdong-Hong Kong Stem Cell and Regenerative Medicine Research Centre, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China.,Sanya Institute of Swine Resource, Hainan Provincial Research Centre of Laboratory Animals, Sanya, China.,Research Unit of Generation of Large Animal Disease Models, Chinese Academy of Medical Sciences (2019RU015), Guangzhou, China.,Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, China
| | - Ting Lan
- CAS Key Laboratory of Regenerative Biology, GIBH-HKU Guangdong-Hong Kong Stem Cell and Regenerative Medicine Research Centre, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China.,Sanya Institute of Swine Resource, Hainan Provincial Research Centre of Laboratory Animals, Sanya, China.,Research Unit of Generation of Large Animal Disease Models, Chinese Academy of Medical Sciences (2019RU015), Guangzhou, China.,Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, China
| | - Yang Liu
- CAS Key Laboratory of Regenerative Biology, GIBH-HKU Guangdong-Hong Kong Stem Cell and Regenerative Medicine Research Centre, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China.,Sanya Institute of Swine Resource, Hainan Provincial Research Centre of Laboratory Animals, Sanya, China.,Research Unit of Generation of Large Animal Disease Models, Chinese Academy of Medical Sciences (2019RU015), Guangzhou, China.,Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, China
| | - Yu Zhao
- CAS Key Laboratory of Regenerative Biology, GIBH-HKU Guangdong-Hong Kong Stem Cell and Regenerative Medicine Research Centre, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China.,Sanya Institute of Swine Resource, Hainan Provincial Research Centre of Laboratory Animals, Sanya, China.,Research Unit of Generation of Large Animal Disease Models, Chinese Academy of Medical Sciences (2019RU015), Guangzhou, China.,Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, China
| | - Qingjian Zou
- Guangdong Provincial Key Laboratory of Large Animal Models for Biomedicine, Wuyi University, Jiangmen, China
| | - Tao Nie
- CAS Key Laboratory of Regenerative Biology, GIBH-HKU Guangdong-Hong Kong Stem Cell and Regenerative Medicine Research Centre, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China
| | - Xiaoyan Hui
- School of Biomedical Sciences, the Chinese University of Hong Kong, Hong Kong SAR
| | - Liangxue Lai
- CAS Key Laboratory of Regenerative Biology, GIBH-HKU Guangdong-Hong Kong Stem Cell and Regenerative Medicine Research Centre, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China.,Sanya Institute of Swine Resource, Hainan Provincial Research Centre of Laboratory Animals, Sanya, China.,Research Unit of Generation of Large Animal Disease Models, Chinese Academy of Medical Sciences (2019RU015), Guangzhou, China.,Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, China.,Guangdong Provincial Key Laboratory of Large Animal Models for Biomedicine, Wuyi University, Jiangmen, China
| | - Donghai Wu
- CAS Key Laboratory of Regenerative Biology, GIBH-HKU Guangdong-Hong Kong Stem Cell and Regenerative Medicine Research Centre, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China.,Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, China
| | - Nana Fan
- CAS Key Laboratory of Regenerative Biology, GIBH-HKU Guangdong-Hong Kong Stem Cell and Regenerative Medicine Research Centre, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China.,Sanya Institute of Swine Resource, Hainan Provincial Research Centre of Laboratory Animals, Sanya, China.,Research Unit of Generation of Large Animal Disease Models, Chinese Academy of Medical Sciences (2019RU015), Guangzhou, China.,Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, China
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8
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Fu H, Hawley NL, Carlson JC, Russell EM, Pomer A, Cheng H, Naseri T, Reupena MS, Deka R, Choy CC, McGarvey ST, Minster RL, Weeks DE. The missense variant, rs373863828, in CREBRF plays a role in longitudinal changes in body mass index in Samoans. Obes Res Clin Pract 2022; 16:220-227. [PMID: 35606300 DOI: 10.1016/j.orcp.2022.04.004] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/17/2022] [Revised: 04/27/2022] [Accepted: 04/30/2022] [Indexed: 11/30/2022]
Abstract
OBJECTIVE A missense variant, rs373863828, in CREBRF is associated with obesity in Polynesians. We investigate whether rs373863828 and other factors are associated with body mass index (BMI) rate-of-change between 2010 and 2017-19 in Samoans. METHODS We used sex-stratified models to test whether BMI rate-of-change was associated with rs373863828, baseline BMI, age, residence, physical activity, and household asset score in a cohort study of 480 Samoan adults measured in both 2010 (mean age 43.8 years) and 2017-19. RESULTS Mean BMI increased from 32.1 to 33.5 kg/m2 in males (n = 220, p = 1.3 ×10-8) and from 35.9 to 37.8 kg/m2 in females (n = 260, p = 1.2 ×10-13). In females, the A allele was associated with a higher rate-of-change (0.150 kg/m2/year/allele, p = 1.7 ×10-4). Across 10-year age groups, mean BMI rate-of-change was lower in older participants. The BMI rate of change differed by genotype: it was, in females with AA genotype, approximately half that seen in GG and AG participants. In females lower baseline household asset scores were associated with a higher rate-of-change (p = 0.002). CONCLUSIONS In Samoans, the minor A allele of rs373863828 is associated with an increased rate-of-change in BMI in females. On average, BMI of females with the AA genotype increased 0.30 kg/m2/year more than of those with the GG genotype.
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Affiliation(s)
- Haoyi Fu
- Department of Biostatistics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Nicola L Hawley
- International Health Institute, Department of Epidemiology, School of Public Health, Brown University, Providence, RI, USA; Department of Epidemiology (Chronic Disease), School of Public Health, Yale University, New Haven, CT, USA
| | - Jenna C Carlson
- Department of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA; Department of Biostatistics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Emily M Russell
- Department of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Alysa Pomer
- Department of Anthropology, Yale University, New Haven, CT, USA
| | - Hong Cheng
- Department of Environmental & Public Health Sciences, College of Medicine, University of Cincinnati, Cincinnati, OH, USA
| | - Take Naseri
- International Health Institute, Department of Epidemiology, School of Public Health, Brown University, Providence, RI, USA; Ministry of Health, Apia, Samoa
| | | | - Ranjan Deka
- Department of Environmental & Public Health Sciences, College of Medicine, University of Cincinnati, Cincinnati, OH, USA
| | - Courtney C Choy
- International Health Institute, Department of Epidemiology, School of Public Health, Brown University, Providence, RI, USA; Department of Epidemiology (Chronic Disease), School of Public Health, Yale University, New Haven, CT, USA
| | - Stephen T McGarvey
- International Health Institute, Department of Epidemiology, School of Public Health, Brown University, Providence, RI, USA; Department of Anthropology, Brown University, Providence, RI, USA
| | - Ryan L Minster
- Department of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Daniel E Weeks
- Department of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA; Department of Biostatistics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA.
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9
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Lee K, Vakili S, Burden HJ, Adams S, Smith GC, Kulatea B, Wright-McNaughton M, Sword D, Watene-O'Sullivan C, Atiola RD, Paul RG, Plank LD, Kallingappa P, King F, Wilcox P, Merriman TR, Krebs JD, Hall RM, Murphy R, Merry TL, Shepherd PR. The minor allele of the CREBRF rs373863828 p.R457Q coding variant is associated with reduced levels of myostatin in males: Implications for body composition. Mol Metab 2022; 59:101464. [PMID: 35218947 PMCID: PMC8927835 DOI: 10.1016/j.molmet.2022.101464] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Revised: 02/16/2022] [Accepted: 02/16/2022] [Indexed: 12/04/2022] Open
Abstract
OBJECTIVE The minor allele (A) of the rs373863828 variant (p.Arg457Gln) in CREBRF is restricted to indigenous peoples of the Pacific islands (including New Zealand Māori and peoples of Polynesia), with a frequency of up to 25% in these populations. This allele associates with a large increase in body mass index (BMI) but with significantly lower risk of type-2 diabetes (T2D). It remains unclear whether the increased BMI is driven by increased adiposity or by increased lean mass. METHODS We undertook body composition analysis using DXA in 189 young men of Māori and Pacific descent living in Aotearoa New Zealand. Further investigation was carried out in two orthologous Arg458Gln knockin mouse models on FVB/NJ and C57BL/6j backgrounds. RESULTS The rs373863828 A allele was associated with lower fat mass when adjusted for BMI (p < 0.05) and was associated with significantly lower circulating levels of the muscle inhibitory hormone myostatin (p < 0.05). Supporting the human data, significant reductions in adipose tissue mass were observed in the knockin mice. This was more significant in older mice in both backgrounds and appeared to be the result of reduced age-associated increases in fat mass. The older male knockin mice on C57BL/6j background also had increased grip strength (p < 0.01) and lower levels of myostatin (p < 0.05). CONCLUSION Overall, these results prove that the rs373863828 A-allele is associated with a reduction of myostatin levels which likely contribute to an age-dependent lowering of fat mass, at least in males.
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Affiliation(s)
- Kate Lee
- Maurice Wilkins Centre for Molecular Biodiscovery, The University of Auckland, Auckland, New Zealand; Department of Molecular Medicine and Pathology, School of Medical Sciences, The University of Auckland, Auckland, New Zealand
| | - Sanaz Vakili
- Maurice Wilkins Centre for Molecular Biodiscovery, The University of Auckland, Auckland, New Zealand; Department of Molecular Medicine and Pathology, School of Medical Sciences, The University of Auckland, Auckland, New Zealand
| | - Hannah J Burden
- Maurice Wilkins Centre for Molecular Biodiscovery, The University of Auckland, Auckland, New Zealand; Department of Molecular Medicine and Pathology, School of Medical Sciences, The University of Auckland, Auckland, New Zealand
| | - Shannon Adams
- Discipline of Nutrition, School of Medical Sciences, The University of Auckland, Auckland, New Zealand
| | - Greg C Smith
- Department of Pharmacology, School of Medical Sciences, UNSW Australia, Kensington, Australia
| | - Braydon Kulatea
- Discipline of Nutrition, School of Medical Sciences, The University of Auckland, Auckland, New Zealand
| | | | - Danielle Sword
- Department of Medicine, University of Otago Wellington, Wellington, New Zealand
| | | | - Robert D Atiola
- Discipline of Nutrition, School of Medical Sciences, The University of Auckland, Auckland, New Zealand
| | - Ryan G Paul
- Waikato Medical Research Centre, University of Waikato, Hamilton, New Zealand
| | - Lindsay D Plank
- Department of Surgery, School of Medicine, The University of Auckland, Auckland, New Zealand
| | - Prasanna Kallingappa
- Department of Molecular Medicine and Pathology, School of Medical Sciences, The University of Auckland, Auckland, New Zealand
| | - Frances King
- Ngati Porou Hauora, Te Puia Springs, New Zealand
| | - Phillip Wilcox
- Department of Mathematics and Statistics, University of Otago, New Zealand
| | - Tony R Merriman
- Maurice Wilkins Centre for Molecular Biodiscovery, The University of Auckland, Auckland, New Zealand; Department of Biochemistry, School of Biomedical Sciences, University of Otago, New Zealand; Division of Clinical Immunology and Rheumatology, University of Alabama at Birmingham, Alabama, United States
| | - Jeremy D Krebs
- Maurice Wilkins Centre for Molecular Biodiscovery, The University of Auckland, Auckland, New Zealand; Department of Medicine, University of Otago Wellington, Wellington, New Zealand
| | - Rosemary M Hall
- Maurice Wilkins Centre for Molecular Biodiscovery, The University of Auckland, Auckland, New Zealand; Department of Medicine, University of Otago Wellington, Wellington, New Zealand
| | - Rinki Murphy
- Maurice Wilkins Centre for Molecular Biodiscovery, The University of Auckland, Auckland, New Zealand; Department of Medicine, Faculty of Medical and Health Sciences, The University of Auckland, Auckland, New Zealand
| | - Troy L Merry
- Discipline of Nutrition, School of Medical Sciences, The University of Auckland, Auckland, New Zealand; Maurice Wilkins Centre for Molecular Biodiscovery, The University of Auckland, Auckland, New Zealand
| | - Peter R Shepherd
- Maurice Wilkins Centre for Molecular Biodiscovery, The University of Auckland, Auckland, New Zealand; Department of Molecular Medicine and Pathology, School of Medical Sciences, The University of Auckland, Auckland, New Zealand.
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10
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Limited Metabolic Effect of the CREBRF R457Q Obesity Variant in Mice. Cells 2022; 11:cells11030497. [PMID: 35159305 PMCID: PMC8833978 DOI: 10.3390/cells11030497] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 01/21/2022] [Accepted: 01/25/2022] [Indexed: 11/17/2022] Open
Abstract
The Arg457Gln missense variant in the CREBRF gene has previously been identified as driving excess body weight in Pacific/Oceanic populations. Intriguingly, Arg457Gln variant carriers also demonstrate paradoxical reductions in diabetes risk, indicating that the gene has a critical role in whole-body metabolism. To study the function of this variant in more detail, we generated mice on an FVB/N background with the Crebrf Arg458Gln variant knocked in to replace the endogenous Crebrf. The whole-body metabolic phenotype was characterized for male and female mice on a regular chow diet or an 8-week high-fat challenge. Regular assessment of body composition found that the Crebrf variant had no influence on total body weight or fat mass at any time point. Glucose tolerance tests demonstrated no obvious genotype effect on glucose homeostasis, with indirect calorimetry measures of whole-body energy expenditure likewise unaffected. Male chow-fed variant carriers displayed a trend towards increased lean mass and significantly reduced sensitivity to insulin administration. Overall, this novel mouse model showed only limited phenotypic effects associated with the Crebrf missense variant. The inability to recapitulate results of human association studies may invite reconsideration of the precise mechanistic link between CREBRF function and the risks of obesity and diabetes in variant allele carriers.
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11
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Kanshana JS, Mattila PE, Ewing MC, Wood AN, Schoiswohl G, Meyer AC, Kowalski A, Rosenthal SL, Gingras S, Kaufman BA, Lu R, Weeks DE, McGarvey ST, Minster RL, Hawley NL, Kershaw EE. A murine model of the human CREBRFR457Q obesity-risk variant does not influence energy or glucose homeostasis in response to nutritional stress. PLoS One 2021; 16:e0251895. [PMID: 34520472 PMCID: PMC8439463 DOI: 10.1371/journal.pone.0251895] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2021] [Accepted: 08/09/2021] [Indexed: 01/02/2023] Open
Abstract
Obesity and diabetes have strong heritable components, yet the genetic contributions to these diseases remain largely unexplained. In humans, a missense variant in Creb3 regulatory factor (CREBRF) [rs373863828 (p.Arg457Gln); CREBRFR457Q] is strongly associated with increased odds of obesity but decreased odds of diabetes. Although virtually nothing is known about CREBRF's mechanism of action, emerging evidence implicates it in the adaptive transcriptional response to nutritional stress downstream of TORC1. The objectives of this study were to generate a murine model with knockin of the orthologous variant in mice (CREBRFR458Q) and to test the hypothesis that this CREBRF variant promotes obesity and protects against diabetes by regulating energy and glucose homeostasis downstream of TORC1. To test this hypothesis, we performed extensive phenotypic analysis of CREBRFR458Q knockin mice at baseline and in response to acute (fasting/refeeding), chronic (low- and high-fat diet feeding), and extreme (prolonged fasting) nutritional stress as well as with pharmacological TORC1 inhibition, and aging to 52 weeks. The results demonstrate that the murine CREBRFR458Q model of the human CREBRFR457Q variant does not influence energy/glucose homeostasis in response to these interventions, with the exception of possible greater loss of fat relative to lean mass with age. Alternative preclinical models and/or studies in humans will be required to decipher the mechanisms linking this variant to human health and disease.
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Affiliation(s)
- Jitendra S. Kanshana
- Division of Endocrinology and Metabolism, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, United States of America
| | - Polly E. Mattila
- Division of Endocrinology and Metabolism, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, United States of America
| | - Michael C. Ewing
- Division of Endocrinology and Metabolism, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, United States of America
| | - Ashlee N. Wood
- Division of Endocrinology and Metabolism, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, United States of America
| | - Gabriele Schoiswohl
- Department of Pharmacology and Toxicology, University of Graz, Graz, Austria
| | - Anna C. Meyer
- Division of Endocrinology and Metabolism, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, United States of America
| | - Aneta Kowalski
- Division of Endocrinology and Metabolism, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, United States of America
| | - Samantha L. Rosenthal
- Center for Craniofacial and Dental Genetics, Department of Oral and Craniofacial Sciences, University of Pittsburgh, Pittsburgh, PA, United States of America
| | - Sebastien Gingras
- Department of Immunology, University of Pittsburgh, Pittsburgh, PA, United States of America
| | - Brett A. Kaufman
- Division of Cardiology, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, United States of America
| | - Ray Lu
- Department of Molecular and Cellular Biology, College of Biological Science, University of Guelph, Guelph, ON, Canada
| | - Daniel E. Weeks
- Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
- Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Stephen T. McGarvey
- International Health Institute, Department of Epidemiology, Brown University School of Public Health, Providence, Rhode Island, United States of America
- Department of Anthropology, Brown University, Providence, Rhode Island, United States of America
| | - Ryan L. Minster
- Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Nicola L. Hawley
- Department of Chronic Disease Epidemiology, Yale School of Public Health, New Haven, Connecticut, United States of America
| | - Erin E. Kershaw
- Division of Endocrinology and Metabolism, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, United States of America
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12
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Lin M, Caberto C, Wan P, Li Y, Lum-Jones A, Tiirikainen M, Pooler L, Nakamura B, Sheng X, Porcel J, Lim U, Setiawan VW, Le Marchand L, Wilkens LR, Haiman CA, Cheng I, Chiang CWK. Population-specific reference panels are crucial for genetic analyses: an example of the CREBRF locus in Native Hawaiians. Hum Mol Genet 2021; 29:2275-2284. [PMID: 32491157 DOI: 10.1093/hmg/ddaa083] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2019] [Revised: 03/16/2020] [Accepted: 03/17/2020] [Indexed: 01/10/2023] Open
Abstract
Statistical imputation applied to genome-wide array data is the most cost-effective approach to complete the catalog of genetic variation in a study population. However, imputed genotypes in underrepresented populations incur greater inaccuracies due to ascertainment bias and a lack of representation among reference individuals, further contributing to the obstacles to study these populations. Here we examined the consequences due to the lack of representation by genotyping in a large number of self-reported Native Hawaiians (N = 3693) a functionally important, Polynesian-specific variant in the CREBRF gene, rs373863828. We found the derived allele was significantly associated with several adiposity traits with large effects (e.g. ~ 1.28 kg/m2 per allele in body mass index as the most significant; P = 7.5 × 10-5), consistent with the original findings in Samoans. Due to the current absence of Polynesian representation in publicly accessible reference sequences, rs373863828 or its proxies could not be tested through imputation using these existing resources. Moreover, the association signals at the entire CREBRF locus could not be captured by alternative approaches, such as admixture mapping. In contrast, highly accurate imputation can be achieved even if a small number (<200) of internally constructed Polynesian reference individuals were available; this would increase sample size and improve the statistical evidence of associations. Taken together, our results suggest the alarming possibility that lack of representation in reference panels could inhibit discovery of functionally important loci such as CREBRF. Yet, they could be easily detected and prioritized with improved representation of diverse populations in sequencing studies.
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Affiliation(s)
- Meng Lin
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Christian Caberto
- Epidemiology Program, University of Hawai'i Cancer Center, University of Hawai'i at Mānoa, Honolulu, HI 96813, USA
| | - Peggy Wan
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Yuqing Li
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA 94518, USA
| | - Annette Lum-Jones
- Epidemiology Program, University of Hawai'i Cancer Center, University of Hawai'i at Mānoa, Honolulu, HI 96813, USA
| | - Maarit Tiirikainen
- Epidemiology Program, University of Hawai'i Cancer Center, University of Hawai'i at Mānoa, Honolulu, HI 96813, USA
| | - Loreall Pooler
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Brooke Nakamura
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Xin Sheng
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Jacqueline Porcel
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Unhee Lim
- Epidemiology Program, University of Hawai'i Cancer Center, University of Hawai'i at Mānoa, Honolulu, HI 96813, USA
| | - Veronica Wendy Setiawan
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Loïc Le Marchand
- Epidemiology Program, University of Hawai'i Cancer Center, University of Hawai'i at Mānoa, Honolulu, HI 96813, USA
| | - Lynne R Wilkens
- Epidemiology Program, University of Hawai'i Cancer Center, University of Hawai'i at Mānoa, Honolulu, HI 96813, USA
| | - Christopher A Haiman
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Iona Cheng
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA 94518, USA
| | - Charleston W K Chiang
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA.,Quantitative Computational Biology Section, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089, USA
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13
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Oyama S, Duckham RL, Arslanian KJ, Kershaw EE, Strayer JA, Fidow UT, Naseri T, Hawley NL. Body size and composition of Samoan toddlers aged 18-25 months in 2019. Ann Hum Biol 2021; 48:346-349. [PMID: 34340601 PMCID: PMC9912174 DOI: 10.1080/03014460.2021.1951351] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
BACKGROUND The "Foafoaga O le Ola (Beginning of Life)" study is a prospective birth cohort of n = 160 Samoan mother-infant dyads established in 2017-2018. A primary study aim is to explore how a missense variant at CREBRF rs373863828 impacts growth in early life, given its association with increased body size but lower risk of diabetes in adult Samoans. Here, we examine body size and composition by genotype among toddlers aged 18.7-24.5 months. METHODS Height, weight, head circumference, mid-upper-arm circumference, and abdominal circumference, as well as subscapular, triceps, iliac crest and thigh skinfold thickness were measured among 107 toddlers with known rs373863828 genotype; 42 of these toddlers completed dual-energy X-ray absorptiometry (DXA) scans from which body composition (total body less head fat mass, lean mass, bone mass, % fat mass and % fat-free mass) was estimated. RESULTS After controlling for sex and age, toddlers with at least one copy of the CREBRF minor allele (AA/AG) were 1.31 cm taller (SE = 0.64, p = 0.045) than toddlers with the GG genotype. CONCLUSION Whether greater linear growth in early childhood could contribute to the metabolically protective effects associated with the CREBRF variant in adulthood should be explored in future studies.
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Affiliation(s)
- Sakurako Oyama
- Department of Anthropology, Yale University, New Haven, CT,Yale School of Medicine, Yale University, New Haven, CT
| | - Rachel L. Duckham
- Institute of Physical Activity and Nutrition, Deakin University, Geelong, Australia,Australian Institute for Musculoskeletal Science (AIMSS), The University of Melbourne and Western Health, St Albans, Victoria,Department of General Practice, Monash University, Melbourne, AUS
| | - Kendall J. Arslanian
- Department of Chronic Disease Epidemiology, Yale School of Public Health, New Haven, CT
| | - Erin E. Kershaw
- Division of Endocrinology, Department of Medicine, University of Pittsburgh, Pittsburgh, PA
| | - Joshua A. Strayer
- Division of Endocrinology, Department of Medicine, University of Pittsburgh, Pittsburgh, PA
| | - Ulai T. Fidow
- Department of Obstetrics & Gynecology, Tupua Tamasese Meaole Hospital, Samoa National Health Services, Apia, Samoa
| | | | - Nicola L. Hawley
- Department of Chronic Disease Epidemiology, Yale School of Public Health, New Haven, CT
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14
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Krishnan M, Murphy R, Okesene-Gafa KAM, Ji M, Thompson JMD, Taylor RS, Merriman TR, McCowan LME, McKinlay CJD. The Pacific-specific CREBRF rs373863828 allele protects against gestational diabetes mellitus in Māori and Pacific women with obesity. Diabetologia 2020; 63:2169-2176. [PMID: 32654027 DOI: 10.1007/s00125-020-05202-8] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/29/2019] [Accepted: 05/06/2020] [Indexed: 01/13/2023]
Abstract
AIMS/HYPOTHESIS The CREBRF rs373863828 minor (A) allele is associated with increased BMI but reduced prevalence of type 2 diabetes in Māori and Pacific people. Given the shared aetiology of type 2 diabetes and gestational diabetes mellitus (GDM), we tested for an association between the CREBRF rs373863828 variant and GDM. METHODS We conducted a prospective cohort study of Māori and Pacific women nested within a nutritional intervention study for pregnant women with obesity. Women were enrolled at 12-17 weeks' gestation and underwent anthropometry and collection of buffy coats for later genetic testing. GDM was diagnosed by 75 g OGTT at 24-28 weeks' gestation using the International Association of Diabetes and Pregnancy Study Groups criteria. Genotyping was performed by real-time PCR with a custom CREBRF rs373863828 probe-set. The association between CREBRF rs373863828 and GDM was analysed separately by ethnic group using logistic regression, with effect estimates combined in a meta-analysis. RESULTS Of 112 Māori and Pacific pregnant women with obesity, 31 (28%) carried the CREBRF rs373863828 A allele (A/G or A/A) and 35 (31%) developed GDM. Women who carried the CREBRF rs373863828 A allele did not differ in BMI when compared with non-carriers (G/G). There was a fivefold reduction in the likelihood of GDM per CREBRF rs373863828 A allele (OR 0.19 [95% CI 0.05, 0.69], p = 0.01), independent of age, BMI and family history of diabetes (adjusted OR 0.13 [95% CI 0.03, 0.53], p = 0.004). GDM was diagnosed in 10% and 40% of women with and without the CREBRF rs373863828 A allele, respectively (no woman with the A/A genotype developed GDM). CONCLUSIONS/INTERPRETATION The CREBRF rs373863828 (A) allele is associated with reduced likelihood of GDM in Māori and Pacific women with obesity and may improve GDM risk prediction. Graphical abstract.
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Affiliation(s)
- Mohanraj Krishnan
- Department of Obstetrics and Gynaecology, University of Auckland, Auckland, New Zealand
- Department of Medicine, University of Auckland, Private Bag 92019, Auckland, 1142, New Zealand
| | - Rinki Murphy
- Department of Medicine, University of Auckland, Private Bag 92019, Auckland, 1142, New Zealand.
- Counties Manukau Health, Auckland, New Zealand.
- Maurice Wilkins Centre for Molecular Biodiscovery, University of Auckland, Auckland, New Zealand.
| | - Karaponi A M Okesene-Gafa
- Department of Obstetrics and Gynaecology, University of Auckland, Auckland, New Zealand
- Counties Manukau Health, Auckland, New Zealand
| | - Maria Ji
- Department of Obstetrics and Gynaecology, University of Auckland, Auckland, New Zealand
| | - John M D Thompson
- Department of Obstetrics and Gynaecology, University of Auckland, Auckland, New Zealand
- Department of Paediatrics, University of Auckland, Auckland, New Zealand
| | - Rennae S Taylor
- Department of Obstetrics and Gynaecology, University of Auckland, Auckland, New Zealand
| | - Tony R Merriman
- Maurice Wilkins Centre for Molecular Biodiscovery, University of Auckland, Auckland, New Zealand
- Department of Biochemistry, University of Otago, Dunedin, New Zealand
| | - Lesley M E McCowan
- Department of Obstetrics and Gynaecology, University of Auckland, Auckland, New Zealand
- Counties Manukau Health, Auckland, New Zealand
| | - Christopher J D McKinlay
- Counties Manukau Health, Auckland, New Zealand.
- Liggins Institute, University of Auckland, Private Bag 92019, Auckland, 1142, New Zealand.
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