New loci for body fat percentage reveal link between adiposity and cardiometabolic disease risk

Lu, Yingchang; Day, Felix R.; Gustafsson, Stefan; Buchkovich, Martin L.; Na, Jianbo; Bataille, Véronique; Cousminer, Diana L.; Dastani, Zari; Drong, Alexander W.; Esko, Tõnu; Evans, David M.; Falchi, Mario; Feitosa, Mary F.; Ferreira, Teresa; Hedman, Åsa K.; Häring, R.; Hysi, Pirro G.; Iles, Mark M.; Justice, Anne E.; Kanoni, Stavroula; Lagou, Vasiliki; Li, Rui; Li, Xin; Locke, Adam E.; Lu, Ciyong; Mägi, Reedik; Perry, John R. B.; Pers, Tune H.; Qi, Qibin; Sanna, Marianna; Schmidt, Ellen M.; Scott, William R.; Shungin, Dmitry; Teumer, Alexander; Vinkhuyzen, Anna A. E.; Walker, Ryan W.; Westra, Harm-Jan; Zhang, Mingfeng; Zhang, Weihua; Zhao, Jing Hua; Zhu, Zhihong; Afzal, Uzma; Ahluwalia, Tarunveer S.; Bakker, Stephan J. L.; Bellis, Claire; Bonnefond, Amélie; Borodulin, Katja; Buchman, Aron S.; Cederholm, Tommy; Choh, Audrey C.; Choi, Hyung Jin; Curran, Joanne E.; Groot, Lisette C. P. G. M. de; Jager, Philip L. De; Dhonukshe-Rutten, R.A.M.; Enneman, Anke W.; Eury, Elodie; Evans, Daniel S.; Forsén, Tom; Friedrich, Nele; Fumeron, Frédéric; García, Melissa; Gärtner, Simone; Han, Bok‐Ghee; Havulinna, Aki S.; Hayward, Caroline; Hernandez, Dena G.; Hillege, Hans L.; Ittermann, Till; Kent, Jack W.; Kolčić, Ivana; Laatikainen, Tiina; Lahti, Jari; Leach, Irene Mateo; Lee, Christine G.; Lee, Jong‐Young; Tian, Li; Liu, Youfang; Lobbens, Stéphane; Loh, Marie; Lyytikäinen, Leo-Pekka; Medina‐Gomez, Carolina; Michaëlsson, Karl; Nalls, Mike A.; Nielson, Carrie M.; Oozageer, Laticia; Pascoe, Laura; Paternoster, Lavinia; Polašek, Ozren; Ripatti, Samuli; Sarzynski, Mark A.; Shin, Chan Soo; Narančić, Nina Smolej; Spira, Dominik; Srikanth, Priya; Steinhagen‐Thiessen, Elisabeth; Sung, Yun Ju; Swart, Karin M. A.; Taittonen, Leena; Tanaka, Toshiko; Tikkanen, Emmi; Velde, Nathalie van der; Schoor, Natasja M. van; Verweij, Niek; Wright, Alan F.; Yu, Lei; Zmuda, Joseph M.; Eklund, Niina; Forrester, Terrence; Grarup, Niels; Jackson, Anne; Kristiansson, Kati; Kuulasmaa, Teemu; Kuusisto, Johanna; Lichtner, Peter; Luan, Jian’an; Mahajan, Anubha; Männistö, Satu; Palmer, Cameron D.; Ried, Janina S.; Scott, Robert A.; Stančáková, Alena; Wagner, Peter J.; Demirkan, Ayşe; Döring, Angela; Gudnason, Vilmundur; Kiel, Douglas P.; Kühnel, Brigitte; Mangino, Massimo; McKnight, Barbara; Menni, Cristina; O’Connell, Jeffrey R.; Oostra, Ben A.; Shuldiner, Alan R.; Song, Kijoung; Vandenput, Liesbeth; Duijn, Cornelia M. van; Vollenweider, Péter; White, Charles C.; Boehnke, Michael; Boettcher, Yvonne; Cooper, Richard S.; Forouhi, Nita G.; Gieger, Christian; Grallert, Harald; Hingorani, Aroon D.; Jørgensen, Torben; Jousilahti, Pekka; Kivimäki, Mika; Kumari, Meena; Laakso, Markku; Langenberg, Claudia; Linneberg, Allan; Luke, Amy; McKenzie, Colin A.; Palotie, Aarno; Pedersen, Oluf; Peters, Annette; Strauch, Konstantin; Tayo, Bamidele O.; Wareham, Nicholas J.; Bennett, David A.; Bertram, Lars; Blangero, John; Blüher, Matthias; Bouchard, Claude; Campbell, Harry; Cho, Nam H.; Cummings, Steven R.; Czerwinski, Stefan A.; Demuth, Ilja; Eckardt, Rahel; Eriksson, Johan G.; Ferrucci, Luigi; Franco, Oscar H.; Froguel, Philippe; Gansevoort, Ron T.; Hansen, Torben; Harris, Tamara B.; Hastie, Nicholas D.; Heliövaara, Markku; Hofman, Albert; Jordan, Joanne M.; Jula, Antti; Kähönen, Mika; Kajantie, Eero; Knekt, Paul; Koskinen, Seppo; Kovacs, Peter; Lehtimäki, Terho; Lind, Lars; Liu, Yongmei; Orwoll, Eric S.; Osmond, Clive; Perola, Markus; Pérusse, Louis; Raitakari, Olli T.; Rankinen, Tuomo; Rao, D. C.; Rice, Treva; Rivadeneira, Fernando; Rudan, Igor; Salomaa, Veikko; Sørensen, Thorkild I. A.; Stümvoll, Michael; Tönjes, Anke; Towne, Bradford; Tranah, Gregory J.; Tremblay, Angelo; Uitterlinden, André G.; Harst, Pim van der; Vartiainen, Erkki; Viikari, Jorma; Vitart, Véronique; Vohl, Marie‐Claude; Völzke, Henry; Walker, Mark; Wallaschofski, Henri; Wild, Sarah H.; Wilson, James F.; Yengo, Loïc; Bishop, D. Timothy; Borecki, Ingrid B.; Chambers, John C.; Cupples, L. Adrienne; Dehghan, Abbas; Deloukas, Panos; Fatemifar, Ghazaleh; Fox, Caroline S.; Furey, Terrence S.; Franke, Lude; Han, Jiali; Hunter, David J.; Karjalainen, Juha; Karpe, Fredrik; Kaplan, Robert C.; Kooner, Jaspal S.; McCarthy, Mark I.; Murabito, Joanne M.; Morris, Andrew P.; Bishop, Julia A. Newton; North, Kari E.; Ohlsson, Claes; Ong, Ken K.; Prokopenko, Inga; Richards, J. Brent; Schadt, Eric E.; Spector, Tim D.; Widén, Elisabeth; Willer, Cristen J.; Yang, Jian; Ingelsson, Erik; Mohlke, Karen L.; Hirschhorn, Joel N.; Pospisilik, J. Andrew; Zillikens, M. Carola; Lindgren, Cecilia M.; Kilpeläinen, Tuomas O.; Loos, Ruth J.F.

doi:10.1038/ncomms10495

Cited by 254 publications

(280 citation statements)

References 74 publications

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“…The METSIM study has participated as a replication cohort for meta-analyses for adiposity and fat distribution (67)(68)(69)(70)(71). Interestingly, we found that the body-fat-decreasing allele near IRS1 was paradoxically associated with insulin resistance, dyslipidemia, and decreased adiponectin levels.…”

Section: Adipositymentioning

confidence: 80%

The Metabolic Syndrome in Men study: a resource for studies of metabolic and cardiovascular diseases

Laakso

Kuusisto

Stančáková

et al. 2017

Journal of Lipid Research

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156

140

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The Metabolic Syndrome in Men (METSIM) study is a population-based study including 10,197 Finnish men examined in 2005-2010. The aim of the study is to investigate nongenetic and genetic factors associated with the risk of T2D and CVD, and with cardiovascular risk factors. The protocol includes a detailed phenotyping of the participants, an oral glucose tolerance test, fasting laboratory measurements including proton NMR measurements, mass spectometry metabolomics, adipose tissue biopsies from 1,400 participants, and a stool sample. In our ongoing follow-up study, we have, to date, reexamined 6,496 participants. Extensive genotyping and exome sequencing have been performed for essentially all METSIM participants, and >2,000 METSIM participants have been whole-genome sequenced. We have identified several nongenetic markers associated with the development of diabetes and cardiovascular events, and participated in several genetic association studies to identify gene variants associated with diabetes, hyperglycemia, and cardiovascular risk factors. The generation of a phenotype and genotype resource in the METSIM study allows us to proceed toward a "systems genetics" approach, which includes statistical methods to quantitate and integrate intermediate phenotypes, such as transcript, protein, or metabolite levels, to provide a global view of the molecular architecture of complex traits.

show abstract

Section: Adipositymentioning

confidence: 80%

The Metabolic Syndrome in Men study: a resource for studies of metabolic and cardiovascular diseases

Laakso

Kuusisto

Stančáková

et al. 2017

Journal of Lipid Research

Self Cite

156

140

View full text Add to dashboard Cite

show abstract

“…Since these two studies, there has been a boom in GWAS studies and subsequent obesity susceptibility loci identified. To date, ~200 variants associated with obesity-related phenotypes have been identified; however, it is postulated that these loci only account for <10% of the variance [10][11][12][13][14][15]. Although this is quite low, and means that 90% of variance remains to be explained, they have provided us with an emerging wealth of knowledge of the genomic localisation, frequency and effect sizes, and potential functional implications that these loci may have.…”

Section: Genome-wide Association Studies In Obesitymentioning

confidence: 99%

The Omics of Obesity

Henstridge¹,

Bozaoglu²

2017

Adiposity - Omics and Molecular Understanding

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Obesity is a complex multi-faceted disease affecting billions of people worldwide. Traditionally, obesity was thought to be a consequence of having access to energy dense food and busy lifestyles that do not factor in sufficient physical activity. Although diet and exercise play a major role in obesity development, these are not the only contributors. It is widely accepted that genetic and epigenetic factors also play a major role in obesity development and these in turn affect the lipidome, metabolome and proteome. With new technological advances, it is now possible to delve into these specific areas to further understand the mechanisms involved in obesity development. These technologies are collectively termed "omics" technologies, and this chapter will summarise the recent advances in obesity and metabolism research and describe new technologies that have been used to identify mechanisms that play a major role in the development of obesity. In particular, we will examine the different omics platforms that are available and have been used to study obesity. Collectively, these studies will be fundamental in identifying new and effective treatment strategies.

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“…Recent genome-wide association studies (GWAS) have identified different sets of single nucleotide polymorphisms (SNPs) that are associated with BMI and BF% (5,6). Earlier studies on the association between BMI-associated genetic variants and weight change have revealed contradictory results (7–9).…”

Section: Introductionmentioning

confidence: 99%

“…In the current study, we analyzed the associations of the genetic variations of BMI and BF%, assessed by two genetic risk scores (GRSs) based on 77 BMI-associated SNPs and 12 BF%-associated SNPs recently identified through GWAS (5,6), respectively, with long-term BMI change. In addition, we particularly examined the interaction between each GRS and change in physical activity on long-term BMI change in two independent cohorts: the Nurses’ Health Study (NHS) and the Health Professionals Follow-Up Study (HPFS).…”

Section: Introductionmentioning

confidence: 99%

Genetic Susceptibility, Change in Physical Activity, and Long-term Weight Gain

et al. 2017

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Whether change in physical activity over time modifies the genetic susceptibility to long-term weight gain is unknown. We calculated a BMI–genetic risk score (GRS) based on 77 BMI-associated single nucleotide polymorphisms (SNPs) and a body fat percentage (BF%)-GRS based on 12 BF%-associated SNPs in 9,390 women from the Nurses’ Health Study (NHS) and 5,291 men from the Health Professionals Follow-Up Study (HPFS). We analyzed the interactions between each GRS and change in physical activity on BMI/body weight change within five 4-year intervals from 1986 to 2006 using multivariable generalized linear models with repeated-measures analyses. Both the BMI-GRS and the BF%-GRS were associated with long-term increases in BMI/weight, and change in physical activity consistently interacted with the BF%-GRS on BMI change in the NHS (P for interaction = 0.025) and HPFS (P for interaction = 0.001). In the combined cohorts, 4-year BMI change per 10-risk allele increment was −0.02 kg/m2 among participants with greatest increase in physical activity and 0.24 kg/m2 among those with greatest decrease in physical activity (P for interaction < 0.001), corresponding to 0.01 kg versus 0.63 kg weight changes every 4 years (P for interaction = 0.001). Similar but marginal interactions were observed for the BMI-GRS (P for interaction = 0.045). Our data indicate that the genetic susceptibility to weight gain may be diminished by increasing physical activity.

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New loci for body fat percentage reveal link between adiposity and cardiometabolic disease risk

Cited by 254 publications

References 74 publications

The Metabolic Syndrome in Men study: a resource for studies of metabolic and cardiovascular diseases

The Metabolic Syndrome in Men study: a resource for studies of metabolic and cardiovascular diseases

The Omics of Obesity

Genetic Susceptibility, Change in Physical Activity, and Long-term Weight Gain

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