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1.  Multiple Measures of Adiposity Are Associated with Mean Leukocyte Telomere Length in the Northern Finland Birth Cohort 1966 
PLoS ONE  2014;9(6):e99133.
Studies of leukocyte telomere length (LTL) and adiposity have produced conflicting results, and the relationship between body mass index (BMI) and telomere length throughout life remains unclear. We therefore tested association of adult LTL measured in 5,598 participants with: i) childhood growth measures (BMI and age at adiposity rebound (AR)); ii) change in BMI from childhood to adulthood and iii) adult BMI, waist-to-hip ratio (WHR), body adiposity index (BAI). Childhood BMI at AR was positively associated with LTL at 31 years in women (P = 0.041). Adult BMI and WHR in both men (P = 0.025 and P = 0.049, respectively) and women (P = 0.029 and P = 0.008, respectively), and BAI in women (P = 0.021) were inversely associated with LTL at 31 years. An increase in standardised BMI between early childhood and adulthood was associated with shorter adult LTL in women (P = 0.008). We show that LTL is inversely associated with multiple measures of adiposity in both men and women. Additionally, BMI increase in women from childhood to adulthood is associated with shorter telomeres at age 31, potentially indicating accelerated biological ageing.
doi:10.1371/journal.pone.0099133
PMCID: PMC4053385  PMID: 24919187
2.  Discovery and Refinement of Loci Associated with Lipid Levels 
Willer, Cristen J. | Schmidt, Ellen M. | Sengupta, Sebanti | Peloso, Gina M. | Gustafsson, Stefan | Kanoni, Stavroula | Ganna, Andrea | Chen, Jin | Buchkovich, Martin L. | Mora, Samia | Beckmann, Jacques S. | Bragg-Gresham, Jennifer L. | Chang, Hsing-Yi | Demirkan, Ayşe | Den Hertog, Heleen M. | Do, Ron | Donnelly, Louise A. | Ehret, Georg B. | Esko, Tõnu | Feitosa, Mary F. | Ferreira, Teresa | Fischer, Krista | Fontanillas, Pierre | Fraser, Ross M. | Freitag, Daniel F. | Gurdasani, Deepti | Heikkilä, Kauko | Hyppönen, Elina | Isaacs, Aaron | Jackson, Anne U. | Johansson, Åsa | Johnson, Toby | Kaakinen, Marika | Kettunen, Johannes | Kleber, Marcus E. | Li, Xiaohui | Luan, Jian’an | Lyytikäinen, Leo-Pekka | Magnusson, Patrik K.E. | Mangino, Massimo | Mihailov, Evelin | Montasser, May E. | Müller-Nurasyid, Martina | Nolte, Ilja M. | O’Connell, Jeffrey R. | Palmer, Cameron D. | Perola, Markus | Petersen, Ann-Kristin | Sanna, Serena | Saxena, Richa | Service, Susan K. | Shah, Sonia | Shungin, Dmitry | Sidore, Carlo | Song, Ci | Strawbridge, Rona J. | Surakka, Ida | Tanaka, Toshiko | Teslovich, Tanya M. | Thorleifsson, Gudmar | Van den Herik, Evita G. | Voight, Benjamin F. | Volcik, Kelly A. | Waite, Lindsay L. | Wong, Andrew | Wu, Ying | Zhang, Weihua | Absher, Devin | Asiki, Gershim | Barroso, Inês | Been, Latonya F. | Bolton, Jennifer L. | Bonnycastle, Lori L | Brambilla, Paolo | Burnett, Mary S. | Cesana, Giancarlo | Dimitriou, Maria | Doney, Alex S.F. | Döring, Angela | Elliott, Paul | Epstein, Stephen E. | Ingi Eyjolfsson, Gudmundur | Gigante, Bruna | Goodarzi, Mark O. | Grallert, Harald | Gravito, Martha L. | Groves, Christopher J. | Hallmans, Göran | Hartikainen, Anna-Liisa | Hayward, Caroline | Hernandez, Dena | Hicks, Andrew A. | Holm, Hilma | Hung, Yi-Jen | Illig, Thomas | Jones, Michelle R. | Kaleebu, Pontiano | Kastelein, John J.P. | Khaw, Kay-Tee | Kim, Eric | Klopp, Norman | Komulainen, Pirjo | Kumari, Meena | Langenberg, Claudia | Lehtimäki, Terho | Lin, Shih-Yi | Lindström, Jaana | Loos, Ruth J.F. | Mach, François | McArdle, Wendy L | Meisinger, Christa | Mitchell, Braxton D. | Müller, Gabrielle | Nagaraja, Ramaiah | Narisu, Narisu | Nieminen, Tuomo V.M. | Nsubuga, Rebecca N. | Olafsson, Isleifur | Ong, Ken K. | Palotie, Aarno | Papamarkou, Theodore | Pomilla, Cristina | Pouta, Anneli | Rader, Daniel J. | Reilly, Muredach P. | Ridker, Paul M. | Rivadeneira, Fernando | Rudan, Igor | Ruokonen, Aimo | Samani, Nilesh | Scharnagl, Hubert | Seeley, Janet | Silander, Kaisa | Stančáková, Alena | Stirrups, Kathleen | Swift, Amy J. | Tiret, Laurence | Uitterlinden, Andre G. | van Pelt, L. Joost | Vedantam, Sailaja | Wainwright, Nicholas | Wijmenga, Cisca | Wild, Sarah H. | Willemsen, Gonneke | Wilsgaard, Tom | Wilson, James F. | Young, Elizabeth H. | Zhao, Jing Hua | Adair, Linda S. | Arveiler, Dominique | Assimes, Themistocles L. | Bandinelli, Stefania | Bennett, Franklyn | Bochud, Murielle | Boehm, Bernhard O. | Boomsma, Dorret I. | Borecki, Ingrid B. | Bornstein, Stefan R. | Bovet, Pascal | Burnier, Michel | Campbell, Harry | Chakravarti, Aravinda | Chambers, John C. | Chen, Yii-Der Ida | Collins, Francis S. | Cooper, Richard S. | Danesh, John | Dedoussis, George | de Faire, Ulf | Feranil, Alan B. | Ferrières, Jean | Ferrucci, Luigi | Freimer, Nelson B. | Gieger, Christian | Groop, Leif C. | Gudnason, Vilmundur | Gyllensten, Ulf | Hamsten, Anders | Harris, Tamara B. | Hingorani, Aroon | Hirschhorn, Joel N. | Hofman, Albert | Hovingh, G. Kees | Hsiung, Chao Agnes | Humphries, Steve E. | Hunt, Steven C. | Hveem, Kristian | Iribarren, Carlos | Järvelin, Marjo-Riitta | Jula, Antti | Kähönen, Mika | Kaprio, Jaakko | Kesäniemi, Antero | Kivimaki, Mika | Kooner, Jaspal S. | Koudstaal, Peter J. | Krauss, Ronald M. | Kuh, Diana | Kuusisto, Johanna | Kyvik, Kirsten O. | Laakso, Markku | Lakka, Timo A. | Lind, Lars | Lindgren, Cecilia M. | Martin, Nicholas G. | März, Winfried | McCarthy, Mark I. | McKenzie, Colin A. | Meneton, Pierre | Metspalu, Andres | Moilanen, Leena | Morris, Andrew D. | Munroe, Patricia B. | Njølstad, Inger | Pedersen, Nancy L. | Power, Chris | Pramstaller, Peter P. | Price, Jackie F. | Psaty, Bruce M. | Quertermous, Thomas | Rauramaa, Rainer | Saleheen, Danish | Salomaa, Veikko | Sanghera, Dharambir K. | Saramies, Jouko | Schwarz, Peter E.H. | Sheu, Wayne H-H | Shuldiner, Alan R. | Siegbahn, Agneta | Spector, Tim D. | Stefansson, Kari | Strachan, David P. | Tayo, Bamidele O. | Tremoli, Elena | Tuomilehto, Jaakko | Uusitupa, Matti | van Duijn, Cornelia M. | Vollenweider, Peter | Wallentin, Lars | Wareham, Nicholas J. | Whitfield, John B. | Wolffenbuttel, Bruce H.R. | Ordovas, Jose M. | Boerwinkle, Eric | Palmer, Colin N.A. | Thorsteinsdottir, Unnur | Chasman, Daniel I. | Rotter, Jerome I. | Franks, Paul W. | Ripatti, Samuli | Cupples, L. Adrienne | Sandhu, Manjinder S. | Rich, Stephen S. | Boehnke, Michael | Deloukas, Panos | Kathiresan, Sekar | Mohlke, Karen L. | Ingelsson, Erik | Abecasis, Gonçalo R.
Nature genetics  2013;45(11):10.1038/ng.2797.
Low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, triglycerides, and total cholesterol are heritable, modifiable, risk factors for coronary artery disease. To identify new loci and refine known loci influencing these lipids, we examined 188,578 individuals using genome-wide and custom genotyping arrays. We identify and annotate 157 loci associated with lipid levels at P < 5×10−8, including 62 loci not previously associated with lipid levels in humans. Using dense genotyping in individuals of European, East Asian, South Asian, and African ancestry, we narrow association signals in 12 loci. We find that loci associated with blood lipids are often associated with cardiovascular and metabolic traits including coronary artery disease, type 2 diabetes, blood pressure, waist-hip ratio, and body mass index. Our results illustrate the value of genetic data from individuals of diverse ancestries and provide insights into biological mechanisms regulating blood lipids to guide future genetic, biological, and therapeutic research.
doi:10.1038/ng.2797
PMCID: PMC3838666  PMID: 24097068
3.  Common variants associated with plasma triglycerides and risk for coronary artery disease 
Do, Ron | Willer, Cristen J. | Schmidt, Ellen M. | Sengupta, Sebanti | Gao, Chi | Peloso, Gina M. | Gustafsson, Stefan | Kanoni, Stavroula | Ganna, Andrea | Chen, Jin | Buchkovich, Martin L. | Mora, Samia | Beckmann, Jacques S. | Bragg-Gresham, Jennifer L. | Chang, Hsing-Yi | Demirkan, Ayşe | Den Hertog, Heleen M. | Donnelly, Louise A. | Ehret, Georg B. | Esko, Tõnu | Feitosa, Mary F. | Ferreira, Teresa | Fischer, Krista | Fontanillas, Pierre | Fraser, Ross M. | Freitag, Daniel F. | Gurdasani, Deepti | Heikkilä, Kauko | Hyppönen, Elina | Isaacs, Aaron | Jackson, Anne U. | Johansson, Åsa | Johnson, Toby | Kaakinen, Marika | Kettunen, Johannes | Kleber, Marcus E. | Li, Xiaohui | Luan, Jian'an | Lyytikäinen, Leo-Pekka | Magnusson, Patrik K.E. | Mangino, Massimo | Mihailov, Evelin | Montasser, May E. | Müller-Nurasyid, Martina | Nolte, Ilja M. | O'Connell, Jeffrey R. | Palmer, Cameron D. | Perola, Markus | Petersen, Ann-Kristin | Sanna, Serena | Saxena, Richa | Service, Susan K. | Shah, Sonia | Shungin, Dmitry | Sidore, Carlo | Song, Ci | Strawbridge, Rona J. | Surakka, Ida | Tanaka, Toshiko | Teslovich, Tanya M. | Thorleifsson, Gudmar | Van den Herik, Evita G. | Voight, Benjamin F. | Volcik, Kelly A. | Waite, Lindsay L. | Wong, Andrew | Wu, Ying | Zhang, Weihua | Absher, Devin | Asiki, Gershim | Barroso, Inês | Been, Latonya F. | Bolton, Jennifer L. | Bonnycastle, Lori L | Brambilla, Paolo | Burnett, Mary S. | Cesana, Giancarlo | Dimitriou, Maria | Doney, Alex S.F. | Döring, Angela | Elliott, Paul | Epstein, Stephen E. | Eyjolfsson, Gudmundur Ingi | Gigante, Bruna | Goodarzi, Mark O. | Grallert, Harald | Gravito, Martha L. | Groves, Christopher J. | Hallmans, Göran | Hartikainen, Anna-Liisa | Hayward, Caroline | Hernandez, Dena | Hicks, Andrew A. | Holm, Hilma | Hung, Yi-Jen | Illig, Thomas | Jones, Michelle R. | Kaleebu, Pontiano | Kastelein, John J.P. | Khaw, Kay-Tee | Kim, Eric | Klopp, Norman | Komulainen, Pirjo | Kumari, Meena | Langenberg, Claudia | Lehtimäki, Terho | Lin, Shih-Yi | Lindström, Jaana | Loos, Ruth J.F. | Mach, François | McArdle, Wendy L | Meisinger, Christa | Mitchell, Braxton D. | Müller, Gabrielle | Nagaraja, Ramaiah | Narisu, Narisu | Nieminen, Tuomo V.M. | Nsubuga, Rebecca N. | Olafsson, Isleifur | Ong, Ken K. | Palotie, Aarno | Papamarkou, Theodore | Pomilla, Cristina | Pouta, Anneli | Rader, Daniel J. | Reilly, Muredach P. | Ridker, Paul M. | Rivadeneira, Fernando | Rudan, Igor | Ruokonen, Aimo | Samani, Nilesh | Scharnagl, Hubert | Seeley, Janet | Silander, Kaisa | Stančáková, Alena | Stirrups, Kathleen | Swift, Amy J. | Tiret, Laurence | Uitterlinden, Andre G. | van Pelt, L. Joost | Vedantam, Sailaja | Wainwright, Nicholas | Wijmenga, Cisca | Wild, Sarah H. | Willemsen, Gonneke | Wilsgaard, Tom | Wilson, James F. | Young, Elizabeth H. | Zhao, Jing Hua | Adair, Linda S. | Arveiler, Dominique | Assimes, Themistocles L. | Bandinelli, Stefania | Bennett, Franklyn | Bochud, Murielle | Boehm, Bernhard O. | Boomsma, Dorret I. | Borecki, Ingrid B. | Bornstein, Stefan R. | Bovet, Pascal | Burnier, Michel | Campbell, Harry | Chakravarti, Aravinda | Chambers, John C. | Chen, Yii-Der Ida | Collins, Francis S. | Cooper, Richard S. | Danesh, John | Dedoussis, George | de Faire, Ulf | Feranil, Alan B. | Ferrières, Jean | Ferrucci, Luigi | Freimer, Nelson B. | Gieger, Christian | Groop, Leif C. | Gudnason, Vilmundur | Gyllensten, Ulf | Hamsten, Anders | Harris, Tamara B. | Hingorani, Aroon | Hirschhorn, Joel N. | Hofman, Albert | Hovingh, G. Kees | Hsiung, Chao Agnes | Humphries, Steve E. | Hunt, Steven C. | Hveem, Kristian | Iribarren, Carlos | Järvelin, Marjo-Riitta | Jula, Antti | Kähönen, Mika | Kaprio, Jaakko | Kesäniemi, Antero | Kivimaki, Mika | Kooner, Jaspal S. | Koudstaal, Peter J. | Krauss, Ronald M. | Kuh, Diana | Kuusisto, Johanna | Kyvik, Kirsten O. | Laakso, Markku | Lakka, Timo A. | Lind, Lars | Lindgren, Cecilia M. | Martin, Nicholas G. | März, Winfried | McCarthy, Mark I. | McKenzie, Colin A. | Meneton, Pierre | Metspalu, Andres | Moilanen, Leena | Morris, Andrew D. | Munroe, Patricia B. | Njølstad, Inger | Pedersen, Nancy L. | Power, Chris | Pramstaller, Peter P. | Price, Jackie F. | Psaty, Bruce M. | Quertermous, Thomas | Rauramaa, Rainer | Saleheen, Danish | Salomaa, Veikko | Sanghera, Dharambir K. | Saramies, Jouko | Schwarz, Peter E.H. | Sheu, Wayne H-H | Shuldiner, Alan R. | Siegbahn, Agneta | Spector, Tim D. | Stefansson, Kari | Strachan, David P. | Tayo, Bamidele O. | Tremoli, Elena | Tuomilehto, Jaakko | Uusitupa, Matti | van Duijn, Cornelia M. | Vollenweider, Peter | Wallentin, Lars | Wareham, Nicholas J. | Whitfield, John B. | Wolffenbuttel, Bruce H.R. | Altshuler, David | Ordovas, Jose M. | Boerwinkle, Eric | Palmer, Colin N.A. | Thorsteinsdottir, Unnur | Chasman, Daniel I. | Rotter, Jerome I. | Franks, Paul W. | Ripatti, Samuli | Cupples, L. Adrienne | Sandhu, Manjinder S. | Rich, Stephen S. | Boehnke, Michael | Deloukas, Panos | Mohlke, Karen L. | Ingelsson, Erik | Abecasis, Goncalo R. | Daly, Mark J. | Neale, Benjamin M. | Kathiresan, Sekar
Nature genetics  2013;45(11):1345-1352.
Triglycerides are transported in plasma by specific triglyceride-rich lipoproteins; in epidemiologic studies, increased triglyceride levels correlate with higher risk for coronary artery disease (CAD). However, it is unclear whether this association reflects causal processes. We used 185 common variants recently mapped for plasma lipids (P<5×10−8 for each) to examine the role of triglycerides on risk for CAD. First, we highlight loci associated with both low-density lipoprotein cholesterol (LDL-C) and triglycerides, and show that the direction and magnitude of both are factors in determining CAD risk. Second, we consider loci with only a strong magnitude of association with triglycerides and show that these loci are also associated with CAD. Finally, in a model accounting for effects on LDL-C and/or high-density lipoprotein cholesterol, a polymorphism's strength of effect on triglycerides is correlated with the magnitude of its effect on CAD risk. These results suggest that triglyceride-rich lipoproteins causally influence risk for CAD.
doi:10.1038/ng.2795
PMCID: PMC3904346  PMID: 24097064
4.  Stability of the Associations between Early Life Risk Indicators and Adolescent Overweight over the Evolving Obesity Epidemic 
PLoS ONE  2014;9(4):e95314.
Background
Pre- and perinatal factors and preschool body size may help identify children developing overweight, but these factors might have changed during the development of the obesity epidemic.
Objective
We aimed to assess the associations between early life risk indicators and overweight at the age of 9 and 15 years at different stages of the obesity epidemic.
Methods
We used two population-based Northern Finland Birth Cohorts including 4111 children born in 1966 (NFBC1966) and 5414 children born in 1985–1986 (NFBC1986). In both cohorts, we used the same a priori defined prenatal factors, maternal body mass index (BMI), birth weight, infant weight (age 5 months and 1 year), and preschool BMI (age 2–5 years). We used internal references in early childhood to define percentiles of body size (<50, 50–75, 75–90 and >90) and generalized linear models to study the association with overweight, according to the International Obesity Taskforce (IOTF) definitions, at the ages of 9 and 15 years.
Results
The prevalence of overweight at the age of 15 was 9% for children born in 1966 and 16% for children born in 1986. However, medians of infant weight and preschool BMI changed little between the cohorts, and we found similar associations between maternal BMI, infant weight, preschool BMI, and later overweight in the two cohorts. At 5 years, children above the 90th percentile had approximately a 12 times higher risk of being overweight at the age of 15 years compared to children below the 50th percentile in both cohorts.
Conclusions
The associations between early body size and adolescent overweight showed remarkable stability, despite the increase in prevalence of overweight over the 20 years between the cohorts. Using consequently defined internal percentiles may be a valuable tool in clinical practice.
doi:10.1371/journal.pone.0095314
PMCID: PMC3991687  PMID: 24748033
5.  Distinct Loci in the CHRNA5/CHRNA3/CHRNB4 Gene Cluster Are Associated With Onset of Regular Smoking 
Stephens, Sarah H. | Hartz, Sarah M. | Hoft, Nicole R. | Saccone, Nancy L. | Corley, Robin C. | Hewitt, John K. | Hopfer, Christian J. | Breslau, Naomi | Coon, Hilary | Chen, Xiangning | Ducci, Francesca | Dueker, Nicole | Franceschini, Nora | Frank, Josef | Han, Younghun | Hansel, Nadia N. | Jiang, Chenhui | Korhonen, Tellervo | Lind, Penelope A. | Liu, Jason | Lyytikäinen, Leo-Pekka | Michel, Martha | Shaffer, John R. | Short, Susan E. | Sun, Juzhong | Teumer, Alexander | Thompson, John R. | Vogelzangs, Nicole | Vink, Jacqueline M. | Wenzlaff, Angela | Wheeler, William | Yang, Bao-Zhu | Aggen, Steven H. | Balmforth, Anthony J. | Baumeister, Sebastian E. | Beaty, Terri H. | Benjamin, Daniel J. | Bergen, Andrew W. | Broms, Ulla | Cesarini, David | Chatterjee, Nilanjan | Chen, Jingchun | Cheng, Yu-Ching | Cichon, Sven | Couper, David | Cucca, Francesco | Dick, Danielle | Foroud, Tatiana | Furberg, Helena | Giegling, Ina | Gillespie, Nathan A. | Gu, Fangyi | Hall, Alistair S. | Hällfors, Jenni | Han, Shizhong | Hartmann, Annette M. | Heikkilä, Kauko | Hickie, Ian B. | Hottenga, Jouke Jan | Jousilahti, Pekka | Kaakinen, Marika | Kähönen, Mika | Koellinger, Philipp D. | Kittner, Stephen | Konte, Bettina | Landi, Maria-Teresa | Laatikainen, Tiina | Leppert, Mark | Levy, Steven M. | Mathias, Rasika A. | McNeil, Daniel W. | Medland, Sarah E. | Montgomery, Grant W. | Murray, Tanda | Nauck, Matthias | North, Kari E. | Paré, Peter D. | Pergadia, Michele | Ruczinski, Ingo | Salomaa, Veikko | Viikari, Jorma | Willemsen, Gonneke | Barnes, Kathleen C. | Boerwinkle, Eric | Boomsma, Dorret I. | Caporaso, Neil | Edenberg, Howard J. | Francks, Clyde | Gelernter, Joel | Grabe, Hans Jörgen | Hops, Hyman | Jarvelin, Marjo-Riitta | Johannesson, Magnus | Kendler, Kenneth S. | Lehtimäki, Terho | Magnusson, Patrik K.E. | Marazita, Mary L. | Marchini, Jonathan | Mitchell, Braxton D. | Nöthen, Markus M. | Penninx, Brenda W. | Raitakari, Olli | Rietschel, Marcella | Rujescu, Dan | Samani, Nilesh J. | Schwartz, Ann G. | Shete, Sanjay | Spitz, Margaret | Swan, Gary E. | Völzke, Henry | Veijola, Juha | Wei, Qingyi | Amos, Chris | Cannon, Dale S. | Grucza, Richard | Hatsukami, Dorothy | Heath, Andrew | Johnson, Eric O. | Kaprio, Jaakko | Madden, Pamela | Martin, Nicholas G. | Stevens, Victoria L. | Weiss, Robert B. | Kraft, Peter | Bierut, Laura J. | Ehringer, Marissa A.
Genetic epidemiology  2013;37(8):846-859.
Neuronal nicotinic acetylcholine receptor (nAChR) genes (CHRNA5/CHRNA3/CHRNB4) have been reproducibly associated with nicotine dependence, smoking behaviors, and lung cancer risk. Of the few reports that have focused on early smoking behaviors, association results have been mixed. This meta-analysis examines early smoking phenotypes and SNPs in the gene cluster to determine: (1) whether the most robust association signal in this region (rs16969968) for other smoking behaviors is also associated with early behaviors, and/or (2) if additional statistically independent signals are important in early smoking. We focused on two phenotypes: age of tobacco initiation (AOI) and age of first regular tobacco use (AOS). This study included 56,034 subjects (41 groups) spanning nine countries and evaluated five SNPs including rs1948, rs16969968, rs578776, rs588765, and rs684513. Each dataset was analyzed using a centrally generated script. Meta-analyses were conducted from summary statistics. AOS yielded significant associations with SNPs rs578776 (beta = 0.02, P = 0.004), rs1948 (beta = 0.023, P = 0.018), and rs684513 (beta = 0.032, P = 0.017), indicating protective effects. There were no significant associations for the AOI phenotype. Importantly, rs16969968, the most replicated signal in this region for nicotine dependence, cigarettes per day, and cotinine levels, was not associated with AOI (P = 0.59) or AOS (P = 0.92). These results provide important insight into the complexity of smoking behavior phenotypes, and suggest that association signals in the CHRNA5/A3/B4 gene cluster affecting early smoking behaviors may be different from those affecting the mature nicotine dependence phenotype.
doi:10.1002/gepi.21760
PMCID: PMC3947535  PMID: 24186853
CHRNA5; CHRNA3; CHRNB4; meta-analysis; nicotine; smoke
6.  Preschool Weight and Body Mass Index in Relation to Central Obesity and Metabolic Syndrome in Adulthood 
PLoS ONE  2014;9(3):e89986.
Background
If preschool measures of body size routinely collected at preventive health examinations are associated with adult central obesity and metabolic syndrome, a focused use of these data for the identification of high risk children is possible. The aim of this study was to test the associations between preschool weight and body mass index (BMI) and adult BMI, central obesity and metabolic alterations.
Methods
The Northern Finland Birth Cohort 1966 (NFBC1966) (N = 4111) is a population-based cohort. Preschool weight (age 5 months and 1 year) and BMI (age 2–5 years) were studied in relation to metabolic syndrome as well as BMI, waist circumference, lipoproteins, blood pressure, and fasting glucose at the age of 31 years. Linear regression models and generalized linear regression models with log link were used.
Results
Throughout preschool ages, weight and BMI were significantly linearly associated with adult BMI and waist circumference. Preschool BMI was inversely associated with high-density lipoprotein levels from the age of 3 years. Compared with children in the lower half of the BMI range, the group of children with the 5% highest BMI at the age of 5 years had a relative risk of adult obesity of 6.2(95% CI:4.2–9.3), of adult central obesity of 2.4(95% CI:2.0–2.9), and of early onset adult metabolic syndrome of 2.5(95% CI:1.7–3.8).
Conclusions
High preschool BMI is consistently associated with adult obesity, central obesity and early onset metabolic syndrome. Routinely collected measures of body size in preschool ages can help to identify children in need of focused prevention due to their increased risk of adverse metabolic alterations in adulthood.
doi:10.1371/journal.pone.0089986
PMCID: PMC3940896  PMID: 24595022
7.  Re-sequencing Expands Our Understanding of the Phenotypic Impact of Variants at GWAS Loci 
PLoS Genetics  2014;10(1):e1004147.
Genome-wide association studies (GWAS) have identified >500 common variants associated with quantitative metabolic traits, but in aggregate such variants explain at most 20–30% of the heritable component of population variation in these traits. To further investigate the impact of genotypic variation on metabolic traits, we conducted re-sequencing studies in >6,000 members of a Finnish population cohort (The Northern Finland Birth Cohort of 1966 [NFBC]) and a type 2 diabetes case-control sample (The Finland-United States Investigation of NIDDM Genetics [FUSION] study). By sequencing the coding sequence and 5′ and 3′ untranslated regions of 78 genes at 17 GWAS loci associated with one or more of six metabolic traits (serum levels of fasting HDL-C, LDL-C, total cholesterol, triglycerides, plasma glucose, and insulin), and conducting both single-variant and gene-level association tests, we obtained a more complete understanding of phenotype-genotype associations at eight of these loci. At all eight of these loci, the identification of new associations provides significant evidence for multiple genetic signals to one or more phenotypes, and at two loci, in the genes ABCA1 and CETP, we found significant gene-level evidence of association to non-synonymous variants with MAF<1%. Additionally, two potentially deleterious variants that demonstrated significant associations (rs138726309, a missense variant in G6PC2, and rs28933094, a missense variant in LIPC) were considerably more common in these Finnish samples than in European reference populations, supporting our prior hypothesis that deleterious variants could attain high frequencies in this isolated population, likely due to the effects of population bottlenecks. Our results highlight the value of large, well-phenotyped samples for rare-variant association analysis, and the challenge of evaluating the phenotypic impact of such variants.
Author Summary
Abnormal serum levels of various metabolites, including measures relevant to cholesterol, other fats, and sugars, are known to be risk factors for cardiovascular disease and type 2 diabetes. Identification of the genes that play a role in generating such abnormalities could advance the development of new treatment and prevention strategies for these disorders. Investigations of common genetic variants carried out in large sets of research subjects have successfully pinpointed such genes within many regions of the human genome. However, these studies often have not led to the identification of the specific genetic variations affecting metabolic traits. To attempt to detect such causal variations, we sequenced genes in 17 genomic regions implicated in metabolic traits in >6,000 people from Finland. By conducting statistical analyses relating specific variations (individually and grouped by gene) to the measures for these metabolic traits observed in the study subjects, we added to our understanding of how genotypes affect these traits. Our findings support a long-held hypothesis that the unique history of the Finnish population provides important advantages for analyzing the relationship between genetic variations and biomedically important traits.
doi:10.1371/journal.pgen.1004147
PMCID: PMC3907339  PMID: 24497850
8.  Common variants at 12q15 and 12q24 are associated with infant head circumference 
Taal, H Rob | Pourcain, Beate St | Thiering, Elisabeth | Das, Shikta | Mook-Kanamori, Dennis O | Warrington, Nicole M | Kaakinen, Marika | Kreiner-Møller, Eskil | Bradfield, Jonathan P | Freathy, Rachel M | Geller, Frank | Guxens, Mònica | Cousminer, Diana L | Kerkhof, Marjan | Timpson, Nicholas J | Ikram, M Arfan | Beilin, Lawrence J | Bønnelykke, Klaus | Buxton, Jessica L | Charoen, Pimphen | Chawes, Bo Lund Krogsgaard | Eriksson, Johan | Evans, David M | Hofman, Albert | Kemp, John P | Kim, Cecilia E | Klopp, Norman | Lahti, Jari | Lye, Stephen J | McMahon, George | Mentch, Frank D | Müller, Martina | O’Reilly, Paul F | Prokopenko, Inga | Rivadeneira, Fernando | Steegers, Eric A P | Sunyer, Jordi | Tiesler, Carla | Yaghootkar, Hanieh | Breteler, Monique M B | Debette, Stephanie | Fornage, Myriam | Gudnason, Vilmundur | Launer, Lenore J | van der Lugt, Aad | Mosley, Thomas H | Seshadri, Sudha | Smith, Albert V | Vernooij, Meike W | Blakemore, Alexandra IF | Chiavacci, Rosetta M | Feenstra, Bjarke | Fernandez-Benet, Julio | Grant, Struan F A | Hartikainen, Anna-Liisa | van der Heijden, Albert J | Iñiguez, Carmen | Lathrop, Mark | McArdle, Wendy L | Mølgaard, Anne | Newnham, John P | Palmer, Lyle J | Palotie, Aarno | Pouta, Annneli | Ring, Susan M | Sovio, Ulla | Standl, Marie | Uitterlinden, Andre G | Wichmann, H-Erich | Vissing, Nadja Hawwa | DeCarli, Charles | van Duijn, Cornelia M | McCarthy, Mark I | Koppelman, Gerard H. | Estivill, Xavier | Hattersley, Andrew T | Melbye, Mads | Bisgaard, Hans | Pennell, Craig E | Widen, Elisabeth | Hakonarson, Hakon | Smith, George Davey | Heinrich, Joachim | Jarvelin, Marjo-Riitta | Jaddoe, Vincent W V
Nature genetics  2012;44(5):532-538.
To identify genetic variants associated with head circumference in infancy, we performed a meta-analysis of seven genome-wide association (GWA) studies (N=10,768 from European ancestry enrolled in pregnancy/birth cohorts) and followed up three lead signals in six replication studies (combined N=19,089). Rs7980687 on chromosome 12q24 (P=8.1×10−9), and rs1042725 on chromosome 12q15 (P=2.8×10−10) were robustly associated with head circumference in infancy. Although these loci have previously been associated with adult height1, their effects on infant head circumference were largely independent of height (P=3.8×10−7 for rs7980687, P=1.3×10−7 for rs1042725 after adjustment for infant height). A third signal, rs11655470 on chromosome 17q21, showed suggestive evidence of association with head circumference (P=3.9×10−6). SNPs correlated to the 17q21 signal show genome-wide association with adult intra cranial volume2, Parkinson’s disease and other neurodegenerative diseases3-5, indicating that a common genetic variant in this region might link early brain growth with neurological disease in later life.
doi:10.1038/ng.2238
PMCID: PMC3773913  PMID: 22504419
9.  Meal Frequencies Modify the Effect of Common Genetic Variants on Body Mass Index in Adolescents of the Northern Finland Birth Cohort 1986 
PLoS ONE  2013;8(9):e73802.
Recent studies suggest that meal frequencies influence the risk of obesity in children and adolescents. It has also been shown that multiple genetic loci predispose to obesity already in youth. However, it is unknown whether meal frequencies could modulate the association between single nucleotide polymorphisms (SNPs) and the risk of obesity. We examined the effect of two meal patterns on weekdays –5 meals including breakfast (regular) and ≤4 meals with or without breakfast (meal skipping) – on the genetic susceptibility to increased body mass index (BMI) in Finnish adolescents. Eight variants representing 8 early-life obesity-susceptibility loci, including FTO and MC4R, were genotyped in 2215 boys and 2449 girls aged 16 years from the population-based Northern Finland Birth Cohort 1986. A genetic risk score (GRS) was calculated for each individual by summing the number of BMI-increasing alleles across the 8 loci. Weight and height were measured and dietary data were collected using self-administered questionnaires. Among meal skippers, the difference in BMI between high-GRS and low-GRS (<8 and ≥8 BMI-increasing alleles) groups was 0.90 (95% CI 0.63,1.17) kg/m2, whereas in regular eaters, this difference was 0.32 (95% CI 0.06,0.57) kg/m2 (pinteraction  = 0.003). The effect of each MC4R rs17782313 risk allele on BMI in meal skippers (0.47 [95% CI 0.22,0.73] kg/m2) was nearly three-fold compared with regular eaters (0.18 [95% CI -0.06,0.41] kg/m2) (pinteraction  = 0.016). Further, the per-allele effect of the FTO rs1421085 was 0.24 (95% CI 0.05,0.42) kg/m2 in regular eaters and 0.46 (95% CI 0.27,0.66) kg/m2 in meal skippers but the interaction between FTO genotype and meal frequencies on BMI was significant only in boys (pinteraction  = 0.015). In summary, the regular five-meal pattern attenuated the increasing effect of common SNPs on BMI in adolescents. Considering the epidemic of obesity in youth, the promotion of regular eating may have substantial public health implications.
doi:10.1371/journal.pone.0073802
PMCID: PMC3769374  PMID: 24040077
10.  GWAS of 126,559 Individuals Identifies Genetic Variants Associated with Educational Attainment 
Rietveld, Cornelius A. | Medland, Sarah E. | Derringer, Jaime | Yang, Jian | Esko, Tõnu | Martin, Nicolas W. | Westra, Harm-Jan | Shakhbazov, Konstantin | Abdellaoui, Abdel | Agrawal, Arpana | Albrecht, Eva | Alizadeh, Behrooz Z. | Amin, Najaf | Barnard, John | Baumeister, Sebastian E. | Benke, Kelly S. | Bielak, Lawrence F. | Boatman, Jeffrey A. | Boyle, Patricia A. | Davies, Gail | de Leeuw, Christiaan | Eklund, Niina | Evans, Daniel S. | Ferhmann, Rudolf | Fischer, Krista | Gieger, Christian | Gjessing, Håkon K. | Hägg, Sara | Harris, Jennifer R. | Hayward, Caroline | Holzapfel, Christina | Ibrahim-Verbaas, Carla A. | Ingelsson, Erik | Jacobsson, Bo | Joshi, Peter K. | Jugessur, Astanand | Kaakinen, Marika | Kanoni, Stavroula | Karjalainen, Juha | Kolcic, Ivana | Kristiansson, Kati | Kutalik, Zoltán | Lahti, Jari | Lee, Sang H. | Lin, Peng | Lind, Penelope A. | Liu, Yongmei | Lohman, Kurt | Loitfelder, Marisa | McMahon, George | Vidal, Pedro Marques | Meirelles, Osorio | Milani, Lili | Myhre, Ronny | Nuotio, Marja-Liisa | Oldmeadow, Christopher J. | Petrovic, Katja E. | Peyrot, Wouter J. | Polašek, Ozren | Quaye, Lydia | Reinmaa, Eva | Rice, John P. | Rizzi, Thais S. | Schmidt, Helena | Schmidt, Reinhold | Smith, Albert V. | Smith, Jennifer A. | Tanaka, Toshiko | Terracciano, Antonio | van der Loos, Matthijs J.H.M. | Vitart, Veronique | Völzke, Henry | Wellmann, Jürgen | Yu, Lei | Zhao, Wei | Allik, Jüri | Attia, John R. | Bandinelli, Stefania | Bastardot, François | Beauchamp, Jonathan | Bennett, David A. | Berger, Klaus | Bierut, Laura J. | Boomsma, Dorret I. | Bültmann, Ute | Campbell, Harry | Chabris, Christopher F. | Cherkas, Lynn | Chung, Mina K. | Cucca, Francesco | de Andrade, Mariza | De Jager, Philip L. | De Neve, Jan-Emmanuel | Deary, Ian J. | Dedoussis, George V. | Deloukas, Panos | Dimitriou, Maria | Eiriksdottir, Gudny | Elderson, Martin F. | Eriksson, Johan G. | Evans, David M. | Faul, Jessica D. | Ferrucci, Luigi | Garcia, Melissa E. | Grönberg, Henrik | Gudnason, Vilmundur | Hall, Per | Harris, Juliette M. | Harris, Tamara B. | Hastie, Nicholas D. | Heath, Andrew C. | Hernandez, Dena G. | Hoffmann, Wolfgang | Hofman, Adriaan | Holle, Rolf | Holliday, Elizabeth G. | Hottenga, Jouke-Jan | Iacono, William G. | Illig, Thomas | Järvelin, Marjo-Riitta | Kähönen, Mika | Kaprio, Jaakko | Kirkpatrick, Robert M. | Kowgier, Matthew | Latvala, Antti | Launer, Lenore J. | Lawlor, Debbie A. | Lehtimäki, Terho | Li, Jingmei | Lichtenstein, Paul | Lichtner, Peter | Liewald, David C. | Madden, Pamela A. | Magnusson, Patrik K. E. | Mäkinen, Tomi E. | Masala, Marco | McGue, Matt | Metspalu, Andres | Mielck, Andreas | Miller, Michael B. | Montgomery, Grant W. | Mukherjee, Sutapa | Nyholt, Dale R. | Oostra, Ben A. | Palmer, Lyle J. | Palotie, Aarno | Penninx, Brenda | Perola, Markus | Peyser, Patricia A. | Preisig, Martin | Räikkönen, Katri | Raitakari, Olli T. | Realo, Anu | Ring, Susan M. | Ripatti, Samuli | Rivadeneira, Fernando | Rudan, Igor | Rustichini, Aldo | Salomaa, Veikko | Sarin, Antti-Pekka | Schlessinger, David | Scott, Rodney J. | Snieder, Harold | Pourcain, Beate St | Starr, John M. | Sul, Jae Hoon | Surakka, Ida | Svento, Rauli | Teumer, Alexander | Tiemeier, Henning | Rooij, Frank JAan | Van Wagoner, David R. | Vartiainen, Erkki | Viikari, Jorma | Vollenweider, Peter | Vonk, Judith M. | Waeber, Gérard | Weir, David R. | Wichmann, H.-Erich | Widen, Elisabeth | Willemsen, Gonneke | Wilson, James F. | Wright, Alan F. | Conley, Dalton | Davey-Smith, George | Franke, Lude | Groenen, Patrick J. F. | Hofman, Albert | Johannesson, Magnus | Kardia, Sharon L.R. | Krueger, Robert F. | Laibson, David | Martin, Nicholas G. | Meyer, Michelle N. | Posthuma, Danielle | Thurik, A. Roy | Timpson, Nicholas J. | Uitterlinden, André G. | van Duijn, Cornelia M. | Visscher, Peter M. | Benjamin, Daniel J. | Cesarini, David | Koellinger, Philipp D.
Science (New York, N.Y.)  2013;340(6139):1467-1471.
A genome-wide association study of educational attainment was conducted in a discovery sample of 101,069 individuals and a replication sample of 25,490. Three independent SNPs are genome-wide significant (rs9320913, rs11584700, rs4851266), and all three replicate. Estimated effects sizes are small (R2 ≈ 0.02%), approximately 1 month of schooling per allele. A linear polygenic score from all measured SNPs accounts for ≈ 2% of the variance in both educational attainment and cognitive function. Genes in the region of the loci have previously been associated with health, cognitive, and central nervous system phenotypes, and bioinformatics analyses suggest the involvement of the anterior caudate nucleus. These findings provide promising candidate SNPs for follow-up work, and our effect size estimates can anchor power analyses in social-science genetics.
doi:10.1126/science.1235488
PMCID: PMC3751588  PMID: 23722424
11.  Increased Genetic Vulnerability to Smoking at CHRNA5 in Early-Onset Smokers 
Hartz, Sarah M. | Short, Susan E. | Saccone, Nancy L. | Culverhouse, Robert | Chen, LiShiun | Schwantes-An, Tae-Hwi | Coon, Hilary | Han, Younghun | Stephens, Sarah H. | Sun, Juzhong | Chen, Xiangning | Ducci, Francesca | Dueker, Nicole | Franceschini, Nora | Frank, Josef | Geller, Frank | Guđbjartsson, Daniel | Hansel, Nadia N. | Jiang, Chenhui | Keskitalo-Vuokko, Kaisu | Liu, Zhen | Lyytikäinen, Leo-Pekka | Michel, Martha | Rawal, Rajesh | Hum, Sc | Rosenberger, Albert | Scheet, Paul | Shaffer, John R. | Teumer, Alexander | Thompson, John R. | Vink, Jacqueline M. | Vogelzangs, Nicole | Wenzlaff, Angela S. | Wheeler, William | Xiao, Xiangjun | Yang, Bao-Zhu | Aggen, Steven H. | Balmforth, Anthony J. | Baumeister, Sebastian E. | Beaty, Terri | Bennett, Siiri | Bergen, Andrew W. | Boyd, Heather A. | Broms, Ulla | Campbell, Harry | Chatterjee, Nilanjan | Chen, Jingchun | Cheng, Yu-Ching | Cichon, Sven | Couper, David | Cucca, Francesco | Dick, Danielle M. | Foroud, Tatiana | Furberg, Helena | Giegling, Ina | Gu, Fangyi | Hall, Alistair S. | Hällfors, Jenni | Han, Shizhong | Hartmann, Annette M. | Hayward, Caroline | Heikkilä, Kauko | Lic, Phil | Hewitt, John K. | Hottenga, Jouke Jan | Jensen, Majken K. | Jousilahti, Pekka | Kaakinen, Marika | Kittner, Steven J. | Konte, Bettina | Korhonen, Tellervo | Landi, Maria-Teresa | Laatikainen, Tiina | Leppert, Mark | Levy, Steven M. | Mathias, Rasika A. | McNeil, Daniel W. | Medland, Sarah E. | Montgomery, Grant W. | Muley, Thomas | Murray, Tanda | Nauck, Matthias | North, Kari | Pergadia, Michele | Polasek, Ozren | Ramos, Erin M. | Ripatti, Samuli | Risch, Angela | Ruczinski, Ingo | Rudan, Igor | Salomaa, Veikko | Schlessinger, David | Styrkársdóttir, Unnur | Terracciano, Antonio | Uda, Manuela | Willemsen, Gonneke | Wu, Xifeng | Abecasis, Goncalo | Barnes, Kathleen | Bickeböller, Heike | Boerwinkle, Eric | Boomsma, Dorret I. | Caporaso, Neil | Duan, Jubao | Edenberg, Howard J. | Francks, Clyde | Gejman, Pablo V. | Gelernter, Joel | Grabe, Hans Jörgen | Hops, Hyman | Jarvelin, Marjo-Riitta | Viikari, Jorma | Kähönen, Mika | Kendler, Kenneth S. | Lehtimäki, Terho | Levinson, Douglas F. | Marazita, Mary L. | Marchini, Jonathan | Melbye, Mads | Mitchell, Braxton D. | Murray, Jeffrey C. | Nöthen, Markus M. | Penninx, Brenda W. | Raitakari, Olli | Rietschel, Marcella | Rujescu, Dan | Samani, Nilesh J. | Sanders, Alan R. | Schwartz, Ann G. | Shete, Sanjay | Shi, Jianxin | Spitz, Margaret | Stefansson, Kari | Swan, Gary E. | Thorgeirsson, Thorgeir | Völzke, Henry | Wei, Qingyi | Wichmann, H.-Erich | Amos, Christopher I. | Breslau, Naomi | Cannon, Dale S. | Ehringer, Marissa | Grucza, Richard | Hatsukami, Dorothy | Heath, Andrew | Johnson, Eric O. | Kaprio, Jaakko | Madden, Pamela | Martin, Nicholas G. | Stevens, Victoria L. | Stitzel, Jerry A. | Weiss, Robert B. | Kraft, Peter | Bierut, Laura J.
Archives of general psychiatry  2012;69(8):854-860.
Context
Recent studies have shown an association between cigarettes per day (CPD) and a nonsynonymous single-nucleotide polymorphism in CHRNA5, rs16969968.
Objective
To determine whether the association between rs16969968 and smoking is modified by age at onset of regular smoking.
Data Sources
Primary data.
Study Selection
Available genetic studies containing measures of CPD and the genotype of rs16969968 or its proxy.
Data Extraction
Uniform statistical analysis scripts were run locally. Starting with 94 050 ever-smokers from 43 studies, we extracted the heavy smokers (CPD >20) and light smokers (CPD ≤10) with age-at-onset information, reducing the sample size to 33 348. Each study was stratified into early-onset smokers (age at onset ≤16 years) and late-onset smokers (age at onset >16 years), and a logistic regression of heavy vs light smoking with the rs16969968 genotype was computed for each stratum. Meta-analysis was performed within each age-at-onset stratum.
Data Synthesis
Individuals with 1 risk allele at rs16969968 who were early-onset smokers were significantly more likely to be heavy smokers in adulthood (odds ratio [OR]=1.45; 95% CI, 1.36–1.55; n=13 843) than were carriers of the risk allele who were late-onset smokers (OR = 1.27; 95% CI, 1.21–1.33, n = 19 505) (P = .01).
Conclusion
These results highlight an increased genetic vulnerability to smoking in early-onset smokers.
doi:10.1001/archgenpsychiatry.2012.124
PMCID: PMC3482121  PMID: 22868939
12.  New loci associated with birth weight identify genetic links between intrauterine growth and adult height and metabolism 
Horikoshi, Momoko | Yaghootkar, Hanieh | Mook-Kanamori, Dennis O. | Sovio, Ulla | Taal, H. Rob | Hennig, Branwen J. | Bradfield, Jonathan P. | St. Pourcain, Beate | Evans, David M. | Charoen, Pimphen | Kaakinen, Marika | Cousminer, Diana L. | Lehtimäki, Terho | Kreiner-Møller, Eskil | Warrington, Nicole M. | Bustamante, Mariona | Feenstra, Bjarke | Berry, Diane J. | Thiering, Elisabeth | Pfab, Thiemo | Barton, Sheila J. | Shields, Beverley M. | Kerkhof, Marjan | van Leeuwen, Elisabeth M. | Fulford, Anthony J. | Kutalik, Zoltán | Zhao, Jing Hua | den Hoed, Marcel | Mahajan, Anubha | Lindi, Virpi | Goh, Liang-Kee | Hottenga, Jouke-Jan | Wu, Ying | Raitakari, Olli T. | Harder, Marie N. | Meirhaeghe, Aline | Ntalla, Ioanna | Salem, Rany M. | Jameson, Karen A. | Zhou, Kaixin | Monies, Dorota M. | Lagou, Vasiliki | Kirin, Mirna | Heikkinen, Jani | Adair, Linda S. | Alkuraya, Fowzan S. | Al-Odaib, Ali | Amouyel, Philippe | Andersson, Ehm Astrid | Bennett, Amanda J. | Blakemore, Alexandra I.F. | Buxton, Jessica L. | Dallongeville, Jean | Das, Shikta | de Geus, Eco J. C. | Estivill, Xavier | Flexeder, Claudia | Froguel, Philippe | Geller, Frank | Godfrey, Keith M. | Gottrand, Frédéric | Groves, Christopher J. | Hansen, Torben | Hirschhorn, Joel N. | Hofman, Albert | Hollegaard, Mads V. | Hougaard, David M. | Hyppönen, Elina | Inskip, Hazel M. | Isaacs, Aaron | Jørgensen, Torben | Kanaka-Gantenbein, Christina | Kemp, John P. | Kiess, Wieland | Kilpeläinen, Tuomas O. | Klopp, Norman | Knight, Bridget A. | Kuzawa, Christopher W. | McMahon, George | Newnham, John P. | Niinikoski, Harri | Oostra, Ben A. | Pedersen, Louise | Postma, Dirkje S. | Ring, Susan M. | Rivadeneira, Fernando | Robertson, Neil R. | Sebert, Sylvain | Simell, Olli | Slowinski, Torsten | Tiesler, Carla M.T. | Tönjes, Anke | Vaag, Allan | Viikari, Jorma S. | Vink, Jacqueline M. | Vissing, Nadja Hawwa | Wareham, Nicholas J. | Willemsen, Gonneke | Witte, Daniel R. | Zhang, Haitao | Zhao, Jianhua | Wilson, James F. | Stumvoll, Michael | Prentice, Andrew M. | Meyer, Brian F. | Pearson, Ewan R. | Boreham, Colin A.G. | Cooper, Cyrus | Gillman, Matthew W. | Dedoussis, George V. | Moreno, Luis A | Pedersen, Oluf | Saarinen, Maiju | Mohlke, Karen L. | Boomsma, Dorret I. | Saw, Seang-Mei | Lakka, Timo A. | Körner, Antje | Loos, Ruth J.F. | Ong, Ken K. | Vollenweider, Peter | van Duijn, Cornelia M. | Koppelman, Gerard H. | Hattersley, Andrew T. | Holloway, John W. | Hocher, Berthold | Heinrich, Joachim | Power, Chris | Melbye, Mads | Guxens, Mònica | Pennell, Craig E. | Bønnelykke, Klaus | Bisgaard, Hans | Eriksson, Johan G. | Widén, Elisabeth | Hakonarson, Hakon | Uitterlinden, André G. | Pouta, Anneli | Lawlor, Debbie A. | Smith, George Davey | Frayling, Timothy M. | McCarthy, Mark I. | Grant, Struan F.A. | Jaddoe, Vincent W.V. | Jarvelin, Marjo-Riitta | Timpson, Nicholas J. | Prokopenko, Inga | Freathy, Rachel M.
Nature genetics  2012;45(1):76-82.
Birth weight within the normal range is associated with a variety of adult-onset diseases, but the mechanisms behind these associations are poorly understood1. Previous genome-wide association studies identified a variant in the ADCY5 gene associated both with birth weight and type 2 diabetes, and a second variant, near CCNL1, with no obvious link to adult traits2. In an expanded genome-wide association meta-analysis and follow-up study (up to 69,308 individuals of European descent from 43 studies), we have now extended the number of genome-wide significant loci to seven, accounting for a similar proportion of variance to maternal smoking. Five of the loci are known to be associated with other phenotypes: ADCY5 and CDKAL1 with type 2 diabetes; ADRB1 with adult blood pressure; and HMGA2 and LCORL with adult height. Our findings highlight genetic links between fetal growth and postnatal growth and metabolism.
doi:10.1038/ng.2477
PMCID: PMC3605762  PMID: 23202124
13.  The Role of Adiposity in Cardiometabolic Traits: A Mendelian Randomization Analysis 
Fall, Tove | Hägg, Sara | Mägi, Reedik | Ploner, Alexander | Fischer, Krista | Horikoshi, Momoko | Sarin, Antti-Pekka | Thorleifsson, Gudmar | Ladenvall, Claes | Kals, Mart | Kuningas, Maris | Draisma, Harmen H. M. | Ried, Janina S. | van Zuydam, Natalie R. | Huikari, Ville | Mangino, Massimo | Sonestedt, Emily | Benyamin, Beben | Nelson, Christopher P. | Rivera, Natalia V. | Kristiansson, Kati | Shen, Huei-yi | Havulinna, Aki S. | Dehghan, Abbas | Donnelly, Louise A. | Kaakinen, Marika | Nuotio, Marja-Liisa | Robertson, Neil | de Bruijn, Renée F. A. G. | Ikram, M. Arfan | Amin, Najaf | Balmforth, Anthony J. | Braund, Peter S. | Doney, Alexander S. F. | Döring, Angela | Elliott, Paul | Esko, Tõnu | Franco, Oscar H. | Gretarsdottir, Solveig | Hartikainen, Anna-Liisa | Heikkilä, Kauko | Herzig, Karl-Heinz | Holm, Hilma | Hottenga, Jouke Jan | Hyppönen, Elina | Illig, Thomas | Isaacs, Aaron | Isomaa, Bo | Karssen, Lennart C. | Kettunen, Johannes | Koenig, Wolfgang | Kuulasmaa, Kari | Laatikainen, Tiina | Laitinen, Jaana | Lindgren, Cecilia | Lyssenko, Valeriya | Läärä, Esa | Rayner, Nigel W. | Männistö, Satu | Pouta, Anneli | Rathmann, Wolfgang | Rivadeneira, Fernando | Ruokonen, Aimo | Savolainen, Markku J. | Sijbrands, Eric J. G. | Small, Kerrin S. | Smit, Jan H. | Steinthorsdottir, Valgerdur | Syvänen, Ann-Christine | Taanila, Anja | Tobin, Martin D. | Uitterlinden, Andre G. | Willems, Sara M. | Willemsen, Gonneke | Witteman, Jacqueline | Perola, Markus | Evans, Alun | Ferrières, Jean | Virtamo, Jarmo | Kee, Frank | Tregouet, David-Alexandre | Arveiler, Dominique | Amouyel, Philippe | Ferrario, Marco M. | Brambilla, Paolo | Hall, Alistair S. | Heath, Andrew C. | Madden, Pamela A. F. | Martin, Nicholas G. | Montgomery, Grant W. | Whitfield, John B. | Jula, Antti | Knekt, Paul | Oostra, Ben | van Duijn, Cornelia M. | Penninx, Brenda W. J. H. | Davey Smith, George | Kaprio, Jaakko | Samani, Nilesh J. | Gieger, Christian | Peters, Annette | Wichmann, H.-Erich | Boomsma, Dorret I. | de Geus, Eco J. C. | Tuomi, TiinaMaija | Power, Chris | Hammond, Christopher J. | Spector, Tim D. | Lind, Lars | Orho-Melander, Marju | Palmer, Colin Neil Alexander | Morris, Andrew D. | Groop, Leif | Järvelin, Marjo-Riitta | Salomaa, Veikko | Vartiainen, Erkki | Hofman, Albert | Ripatti, Samuli | Metspalu, Andres | Thorsteinsdottir, Unnur | Stefansson, Kari | Pedersen, Nancy L. | McCarthy, Mark I. | Ingelsson, Erik | Prokopenko, Inga
PLoS Medicine  2013;10(6):e1001474.
In this study, Prokopenko and colleagues provide novel evidence for causal relationship between adiposity and heart failure and increased liver enzymes using a Mendelian randomization study design.
Please see later in the article for the Editors' Summary
Background
The association between adiposity and cardiometabolic traits is well known from epidemiological studies. Whilst the causal relationship is clear for some of these traits, for others it is not. We aimed to determine whether adiposity is causally related to various cardiometabolic traits using the Mendelian randomization approach.
Methods and Findings
We used the adiposity-associated variant rs9939609 at the FTO locus as an instrumental variable (IV) for body mass index (BMI) in a Mendelian randomization design. Thirty-six population-based studies of individuals of European descent contributed to the analyses.
Age- and sex-adjusted regression models were fitted to test for association between (i) rs9939609 and BMI (n = 198,502), (ii) rs9939609 and 24 traits, and (iii) BMI and 24 traits. The causal effect of BMI on the outcome measures was quantified by IV estimators. The estimators were compared to the BMI–trait associations derived from the same individuals. In the IV analysis, we demonstrated novel evidence for a causal relationship between adiposity and incident heart failure (hazard ratio, 1.19 per BMI-unit increase; 95% CI, 1.03–1.39) and replicated earlier reports of a causal association with type 2 diabetes, metabolic syndrome, dyslipidemia, and hypertension (odds ratio for IV estimator, 1.1–1.4; all p<0.05). For quantitative traits, our results provide novel evidence for a causal effect of adiposity on the liver enzymes alanine aminotransferase and gamma-glutamyl transferase and confirm previous reports of a causal effect of adiposity on systolic and diastolic blood pressure, fasting insulin, 2-h post-load glucose from the oral glucose tolerance test, C-reactive protein, triglycerides, and high-density lipoprotein cholesterol levels (all p<0.05). The estimated causal effects were in agreement with traditional observational measures in all instances except for type 2 diabetes, where the causal estimate was larger than the observational estimate (p = 0.001).
Conclusions
We provide novel evidence for a causal relationship between adiposity and heart failure as well as between adiposity and increased liver enzymes.
Please see later in the article for the Editors' Summary
Editors' Summary
Cardiovascular disease (CVD)—disease that affects the heart and/or the blood vessels—is a major cause of illness and death worldwide. In the US, for example, coronary heart disease—a CVD in which narrowing of the heart's blood vessels by fatty deposits slows the blood supply to the heart and may eventually cause a heart attack—is the leading cause of death, and stroke—a CVD in which the brain's blood supply is interrupted—is the fourth leading cause of death. Globally, both the incidence of CVD (the number of new cases in a population every year) and its prevalence (the proportion of the population with CVD) are increasing, particularly in low- and middle-income countries. This increasing burden of CVD is occurring in parallel with a global increase in the incidence and prevalence of obesity—having an unhealthy amount of body fat (adiposity)—and of metabolic diseases—conditions such as diabetes in which metabolism (the processes that the body uses to make energy from food) is disrupted, with resulting high blood sugar and damage to the blood vessels.
Why Was This Study Done?
Epidemiological studies—investigations that record the patterns and causes of disease in populations—have reported an association between adiposity (indicated by an increased body mass index [BMI], which is calculated by dividing body weight in kilograms by height in meters squared) and cardiometabolic traits such as coronary heart disease, stroke, heart failure (a condition in which the heart is incapable of pumping sufficient amounts of blood around the body), diabetes, high blood pressure (hypertension), and high blood cholesterol (dyslipidemia). However, observational studies cannot prove that adiposity causes any particular cardiometabolic trait because overweight individuals may share other characteristics (confounding factors) that are the real causes of both obesity and the cardiometabolic disease. Moreover, it is possible that having CVD or a metabolic disease causes obesity (reverse causation). For example, individuals with heart failure cannot do much exercise, so heart failure may cause obesity rather than vice versa. Here, the researchers use “Mendelian randomization” to examine whether adiposity is causally related to various cardiometabolic traits. Because gene variants are inherited randomly, they are not prone to confounding and are free from reverse causation. It is known that a genetic variant (rs9939609) within the genome region that encodes the fat-mass- and obesity-associated gene (FTO) is associated with increased BMI. Thus, an investigation of the associations between rs9939609 and cardiometabolic traits can indicate whether obesity is causally related to these traits.
What Did the Researchers Do and Find?
The researchers analyzed the association between rs9939609 (the “instrumental variable,” or IV) and BMI, between rs9939609 and 24 cardiometabolic traits, and between BMI and the same traits using genetic and health data collected in 36 population-based studies of nearly 200,000 individuals of European descent. They then quantified the strength of the causal association between BMI and the cardiometabolic traits by calculating “IV estimators.” Higher BMI showed a causal relationship with heart failure, metabolic syndrome (a combination of medical disorders that increases the risk of developing CVD), type 2 diabetes, dyslipidemia, hypertension, increased blood levels of liver enzymes (an indicator of liver damage; some metabolic disorders involve liver damage), and several other cardiometabolic traits. All the IV estimators were similar to the BMI–cardiovascular trait associations (observational estimates) derived from the same individuals, with the exception of diabetes, where the causal estimate was higher than the observational estimate, probably because the observational estimate is based on a single BMI measurement, whereas the causal estimate considers lifetime changes in BMI.
What Do These Findings Mean?
Like all Mendelian randomization studies, the reliability of the causal associations reported here depends on several assumptions made by the researchers. Nevertheless, these findings provide support for many previously suspected and biologically plausible causal relationships, such as that between adiposity and hypertension. They also provide new insights into the causal effect of obesity on liver enzyme levels and on heart failure. In the latter case, these findings suggest that a one-unit increase in BMI might increase the incidence of heart failure by 17%. In the US, this corresponds to 113,000 additional cases of heart failure for every unit increase in BMI at the population level. Although additional studies are needed to confirm and extend these findings, these results suggest that global efforts to reduce the burden of obesity will likely also reduce the occurrence of CVD and metabolic disorders.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001474.
The American Heart Association provides information on all aspects of cardiovascular disease and tips on keeping the heart healthy, including weight management (in several languages); its website includes personal stories about stroke and heart attacks
The US Centers for Disease Control and Prevention has information on heart disease, stroke, and all aspects of overweight and obesity (in English and Spanish)
The UK National Health Service Choices website provides information about cardiovascular disease and obesity, including a personal story about losing weight
The World Health Organization provides information on obesity (in several languages)
The International Obesity Taskforce provides information about the global obesity epidemic
Wikipedia has a page on Mendelian randomization (note: Wikipedia is a free online encyclopedia that anyone can edit; available in several languages)
MedlinePlus provides links to other sources of information on heart disease, on vascular disease, on obesity, and on metabolic disorders (in English and Spanish)
The International Association for the Study of Obesity provides maps and information about obesity worldwide
The International Diabetes Federation has a web page that describes types, complications, and risk factors of diabetes
doi:10.1371/journal.pmed.1001474
PMCID: PMC3692470  PMID: 23824655
14.  FTO genotype is associated with phenotypic variability of body mass index 
Yang, Jian | Loos, Ruth J. F. | Powell, Joseph E. | Medland, Sarah E. | Speliotes, Elizabeth K. | Chasman, Daniel I. | Rose, Lynda M. | Thorleifsson, Gudmar | Steinthorsdottir, Valgerdur | Mägi, Reedik | Waite, Lindsay | Smith, Albert Vernon | Yerges-Armstrong, Laura M. | Monda, Keri L. | Hadley, David | Mahajan, Anubha | Li, Guo | Kapur, Karen | Vitart, Veronique | Huffman, Jennifer E. | Wang, Sophie R. | Palmer, Cameron | Esko, Tõnu | Fischer, Krista | Zhao, Jing Hua | Demirkan, Ayşe | Isaacs, Aaron | Feitosa, Mary F. | Luan, Jian’an | Heard-Costa, Nancy L. | White, Charles | Jackson, Anne U. | Preuss, Michael | Ziegler, Andreas | Eriksson, Joel | Kutalik, Zoltán | Frau, Francesca | Nolte, Ilja M. | Van Vliet-Ostaptchouk, Jana V. | Hottenga, Jouke-Jan | Jacobs, Kevin B. | Verweij, Niek | Goel, Anuj | Medina-Gomez, Carolina | Estrada, Karol | Bragg-Gresham, Jennifer Lynn | Sanna, Serena | Sidore, Carlo | Tyrer, Jonathan | Teumer, Alexander | Prokopenko, Inga | Mangino, Massimo | Lindgren, Cecilia M. | Assimes, Themistocles L. | Shuldiner, Alan R. | Hui, Jennie | Beilby, John P. | McArdle, Wendy L. | Hall, Per | Haritunians, Talin | Zgaga, Lina | Kolcic, Ivana | Polasek, Ozren | Zemunik, Tatijana | Oostra, Ben A. | Junttila, M. Juhani | Grönberg, Henrik | Schreiber, Stefan | Peters, Annette | Hicks, Andrew A. | Stephens, Jonathan | Foad, Nicola S. | Laitinen, Jaana | Pouta, Anneli | Kaakinen, Marika | Willemsen, Gonneke | Vink, Jacqueline M. | Wild, Sarah H. | Navis, Gerjan | Asselbergs, Folkert W. | Homuth, Georg | John, Ulrich | Iribarren, Carlos | Harris, Tamara | Launer, Lenore | Gudnason, Vilmundur | O’Connell, Jeffrey R. | Boerwinkle, Eric | Cadby, Gemma | Palmer, Lyle J. | James, Alan L. | Musk, Arthur W. | Ingelsson, Erik | Psaty, Bruce M. | Beckmann, Jacques S. | Waeber, Gerard | Vollenweider, Peter | Hayward, Caroline | Wright, Alan F. | Rudan, Igor | Groop, Leif C. | Metspalu, Andres | Khaw, Kay Tee | van Duijn, Cornelia M. | Borecki, Ingrid B. | Province, Michael A. | Wareham, Nicholas J. | Tardif, Jean-Claude | Huikuri, Heikki V. | Cupples, L. Adrienne | Atwood, Larry D. | Fox, Caroline S. | Boehnke, Michael | Collins, Francis S. | Mohlke, Karen L. | Erdmann, Jeanette | Schunkert, Heribert | Hengstenberg, Christian | Stark, Klaus | Lorentzon, Mattias | Ohlsson, Claes | Cusi, Daniele | Staessen, Jan A. | Van der Klauw, Melanie M. | Pramstaller, Peter P. | Kathiresan, Sekar | Jolley, Jennifer D. | Ripatti, Samuli | Jarvelin, Marjo-Riitta | de Geus, Eco J. C. | Boomsma, Dorret I. | Penninx, Brenda | Wilson, James F. | Campbell, Harry | Chanock, Stephen J. | van der Harst, Pim | Hamsten, Anders | Watkins, Hugh | Hofman, Albert | Witteman, Jacqueline C. | Zillikens, M. Carola | Uitterlinden, André G. | Rivadeneira, Fernando | Zillikens, M. Carola | Kiemeney, Lambertus A. | Vermeulen, Sita H. | Abecasis, Goncalo R. | Schlessinger, David | Schipf, Sabine | Stumvoll, Michael | Tönjes, Anke | Spector, Tim D. | North, Kari E. | Lettre, Guillaume | McCarthy, Mark I. | Berndt, Sonja I. | Heath, Andrew C. | Madden, Pamela A. F. | Nyholt, Dale R. | Montgomery, Grant W. | Martin, Nicholas G. | McKnight, Barbara | Strachan, David P. | Hill, William G. | Snieder, Harold | Ridker, Paul M. | Thorsteinsdottir, Unnur | Stefansson, Kari | Frayling, Timothy M. | Hirschhorn, Joel N. | Goddard, Michael E. | Visscher, Peter M.
Nature  2012;490(7419):267-272.
There is evidence across several species for genetic control of phenotypic variation of complex traits1–4, such that the variance among phenotypes is genotype dependent. Understanding genetic control of variability is important in evolutionary biology, agricultural selection programmes and human medicine, yet for complex traits, no individual genetic variants associated with variance, as opposed to the mean, have been identified. Here we perform a meta-analysis of genome-wide association studies of phenotypic variation using 170,000 samples on height and body mass index (BMI) in human populations. We report evidence that the single nucleotide polymorphism (SNP) rs7202116 at the FTO gene locus, which is known to be associated with obesity (as measured by mean BMI for each rs7202116 genotype)5–7, is also associated with phenotypic variability. We show that the results are not due to scale effects or other artefacts, and find no other experiment-wise significant evidence for effects on variability, either at loci other than FTO for BMI or at any locus for height. The difference in variance for BMI among individuals with opposite homozygous genotypes at the FTO locus is approximately 7%, corresponding to a difference of 0.5 kilograms in the standard deviation of weight. Our results indicate that genetic variants can be discovered that are associated with variability, and that between-person variability in obesity can partly be explained by the genotype at the FTO locus. The results are consistent with reported FTO by environment interactions for BMI8, possibly mediated by DNA methylation9,10. Our BMI results for other SNPs and our height results for all SNPs suggest that most genetic variants, including those that influence mean height or mean BMI, are not associated with phenotypic variance, or that their effects on variability are too small to detect even with samples sizes greater than 100,000.
doi:10.1038/nature11401
PMCID: PMC3564953  PMID: 22982992
15.  The Molecular Genetic Architecture of Self-Employment 
van der Loos, Matthijs J. H. M. | Rietveld, Cornelius A. | Eklund, Niina | Koellinger, Philipp D. | Rivadeneira, Fernando | Abecasis, Gonçalo R. | Ankra-Badu, Georgina A. | Baumeister, Sebastian E. | Benjamin, Daniel J. | Biffar, Reiner | Blankenberg, Stefan | Boomsma, Dorret I. | Cesarini, David | Cucca, Francesco | de Geus, Eco J. C. | Dedoussis, George | Deloukas, Panos | Dimitriou, Maria | Eiriksdottir, Guðny | Eriksson, Johan | Gieger, Christian | Gudnason, Vilmundur | Höhne, Birgit | Holle, Rolf | Hottenga, Jouke-Jan | Isaacs, Aaron | Järvelin, Marjo-Riitta | Johannesson, Magnus | Kaakinen, Marika | Kähönen, Mika | Kanoni, Stavroula | Laaksonen, Maarit A. | Lahti, Jari | Launer, Lenore J. | Lehtimäki, Terho | Loitfelder, Marisa | Magnusson, Patrik K. E. | Naitza, Silvia | Oostra, Ben A. | Perola, Markus | Petrovic, Katja | Quaye, Lydia | Raitakari, Olli | Ripatti, Samuli | Scheet, Paul | Schlessinger, David | Schmidt, Carsten O. | Schmidt, Helena | Schmidt, Reinhold | Senft, Andrea | Smith, Albert V. | Spector, Timothy D. | Surakka, Ida | Svento, Rauli | Terracciano, Antonio | Tikkanen, Emmi | van Duijn, Cornelia M. | Viikari, Jorma | Völzke, Henry | Wichmann, H. -Erich | Wild, Philipp S. | Willems, Sara M. | Willemsen, Gonneke | van Rooij, Frank J. A. | Groenen, Patrick J. F. | Uitterlinden, André G. | Hofman, Albert | Thurik, A. Roy
PLoS ONE  2013;8(4):e60542.
Economic variables such as income, education, and occupation are known to affect mortality and morbidity, such as cardiovascular disease, and have also been shown to be partly heritable. However, very little is known about which genes influence economic variables, although these genes may have both a direct and an indirect effect on health. We report results from the first large-scale collaboration that studies the molecular genetic architecture of an economic variable–entrepreneurship–that was operationalized using self-employment, a widely-available proxy. Our results suggest that common SNPs when considered jointly explain about half of the narrow-sense heritability of self-employment estimated in twin data (σg2/σP2 = 25%, h2 = 55%). However, a meta-analysis of genome-wide association studies across sixteen studies comprising 50,627 participants did not identify genome-wide significant SNPs. 58 SNPs with p<10−5 were tested in a replication sample (n = 3,271), but none replicated. Furthermore, a gene-based test shows that none of the genes that were previously suggested in the literature to influence entrepreneurship reveal significant associations. Finally, SNP-based genetic scores that use results from the meta-analysis capture less than 0.2% of the variance in self-employment in an independent sample (p≥0.039). Our results are consistent with a highly polygenic molecular genetic architecture of self-employment, with many genetic variants of small effect. Although self-employment is a multi-faceted, heavily environmentally influenced, and biologically distal trait, our results are similar to those for other genetically complex and biologically more proximate outcomes, such as height, intelligence, personality, and several diseases.
doi:10.1371/journal.pone.0060542
PMCID: PMC3617140  PMID: 23593239
16.  Causal Relationship between Obesity and Vitamin D Status: Bi-Directional Mendelian Randomization Analysis of Multiple Cohorts 
PLoS Medicine  2013;10(2):e1001383.
A mendelian randomization study based on data from multiple cohorts conducted by Karani Santhanakrishnan Vimaleswaran and colleagues re-examines the causal nature of the relationship between vitamin D levels and obesity.
Background
Obesity is associated with vitamin D deficiency, and both are areas of active public health concern. We explored the causality and direction of the relationship between body mass index (BMI) and 25-hydroxyvitamin D [25(OH)D] using genetic markers as instrumental variables (IVs) in bi-directional Mendelian randomization (MR) analysis.
Methods and Findings
We used information from 21 adult cohorts (up to 42,024 participants) with 12 BMI-related SNPs (combined in an allelic score) to produce an instrument for BMI and four SNPs associated with 25(OH)D (combined in two allelic scores, separately for genes encoding its synthesis or metabolism) as an instrument for vitamin D. Regression estimates for the IVs (allele scores) were generated within-study and pooled by meta-analysis to generate summary effects.
Associations between vitamin D scores and BMI were confirmed in the Genetic Investigation of Anthropometric Traits (GIANT) consortium (n = 123,864). Each 1 kg/m2 higher BMI was associated with 1.15% lower 25(OH)D (p = 6.52×10−27). The BMI allele score was associated both with BMI (p = 6.30×10−62) and 25(OH)D (−0.06% [95% CI −0.10 to −0.02], p = 0.004) in the cohorts that underwent meta-analysis. The two vitamin D allele scores were strongly associated with 25(OH)D (p≤8.07×10−57 for both scores) but not with BMI (synthesis score, p = 0.88; metabolism score, p = 0.08) in the meta-analysis. A 10% higher genetically instrumented BMI was associated with 4.2% lower 25(OH)D concentrations (IV ratio: −4.2 [95% CI −7.1 to −1.3], p = 0.005). No association was seen for genetically instrumented 25(OH)D with BMI, a finding that was confirmed using data from the GIANT consortium (p≥0.57 for both vitamin D scores).
Conclusions
On the basis of a bi-directional genetic approach that limits confounding, our study suggests that a higher BMI leads to lower 25(OH)D, while any effects of lower 25(OH)D increasing BMI are likely to be small. Population level interventions to reduce BMI are expected to decrease the prevalence of vitamin D deficiency.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Obesity—having an unhealthy amount of body fat—is increasing worldwide. In the US, for example, a third of the adult population is now obese. Obesity is defined as having a body mass index (BMI, an indicator of body fat calculated by dividing a person's weight in kilograms by their height in meters squared) of more than 30.0 kg/m2. Although there is a genetic contribution to obesity, people generally become obese by consuming food and drink that contains more energy than they need for their daily activities. Thus, obesity can be prevented by having a healthy diet and exercising regularly. Compared to people with a healthy weight, obese individuals have an increased risk of developing diabetes, heart disease and stroke, and tend to die younger. They also have a higher risk of vitamin D deficiency, another increasingly common public health concern. Vitamin D, which is essential for healthy bones as well as other functions, is made in the skin after exposure to sunlight but can also be obtained through the diet and through supplements.
Why Was This Study Done?
Observational studies cannot prove that obesity causes vitamin D deficiency because obese individuals may share other characteristics that reduce their circulating 25-hydroxy vitamin D [25(OH)D] levels (referred to as confounding). Moreover, observational studies cannot indicate whether the larger vitamin D storage capacity of obese individuals (vitamin D is stored in fatty tissues) lowers their 25(OH)D levels or whether 25(OH)D levels influence fat accumulation (reverse causation). If obesity causes vitamin D deficiency, monitoring and treating vitamin D deficiency might alleviate some of the adverse health effects of obesity. Conversely, if low vitamin D levels cause obesity, encouraging people to take vitamin D supplements might help to control the obesity epidemic. Here, the researchers use bi-directional “Mendelian randomization” to examine the direction and causality of the relationship between BMI and 25(OH)D. In Mendelian randomization, causality is inferred from associations between genetic variants that mimic the influence of a modifiable environmental exposure and the outcome of interest. Because gene variants do not change over time and are inherited randomly, they are not prone to confounding and are free from reverse causation. Thus, if a lower vitamin D status leads to obesity, genetic variants associated with lower 25(OH)D concentrations should be associated with higher BMI, and if obesity leads to a lower vitamin D status, then genetic variants associated with higher BMI should be associated with lower 25(OH)D concentrations.
What Did the Researchers Do and Find?
The researchers created a “BMI allele score” based on 12 BMI-related gene variants and two “25(OH)D allele scores,” which are based on gene variants that affect either 25(OH)D synthesis or breakdown. Using information on up to 42,024 participants from 21 studies, the researchers showed that the BMI allele score was associated with both BMI and with 25(OH)D levels among the study participants. Based on this information, they calculated that each 10% increase in BMI will lead to a 4.2% decrease in 25(OH)D concentrations. By contrast, although both 25(OH)D allele scores were strongly associated with 25(OH)D levels, neither score was associated with BMI. This lack of an association between 25(OH)D allele scores and obesity was confirmed using data from more than 100,000 individuals involved in 46 studies that has been collected by the GIANT (Genetic Investigation of Anthropometric Traits) consortium.
What Do These Findings Mean?
These findings suggest that a higher BMI leads to a lower vitamin D status whereas any effects of low vitamin D status on BMI are likely to be small. That is, these findings provide evidence for obesity as a causal factor in the development of vitamin D deficiency but not for vitamin D deficiency as a causal factor in the development of obesity. These findings suggest that population-level interventions to reduce obesity should lead to a reduction in the prevalence of vitamin D deficiency and highlight the importance of monitoring and treating vitamin D deficiency as a means of alleviating the adverse influences of obesity on health.
Additional Information
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001383.
The US Centers for Disease Control and Prevention provides information on all aspects of overweight and obesity (in English and Spanish); a data brief provides information about the vitamin D status of the US population
The World Health Organization provides information on obesity (in several languages)
The UK National Health Service Choices website provides detailed information about obesity and a link to a personal story about losing weight; it also provides information about vitamin D
The International Obesity Taskforce provides information about the global obesity epidemic
The US Department of Agriculture's ChooseMyPlate.gov website provides a personal healthy eating plan; the Weight-control Information Network is an information service provided for the general public and health professionals by the US National Institute of Diabetes and Digestive and Kidney Diseases (in English and Spanish)
The US Office of Dietary Supplements provides information about vitamin D (in English and Spanish)
MedlinePlus has links to further information about obesity and about vitamin D (in English and Spanish)
Wikipedia has a page on Mendelian randomization (note: Wikipedia is a free online encyclopedia that anyone can edit; available in several languages)
Overview and details of the collaborative large-scale genetic association study (D-CarDia) provide information about vitamin D and the risk of cardiovascular disease, diabetes and related traits
doi:10.1371/journal.pmed.1001383
PMCID: PMC3564800  PMID: 23393431
17.  Variants in MTNR1B influence fasting glucose levels 
Prokopenko, Inga | Langenberg, Claudia | Florez, Jose C | Saxena, Richa | Soranzo, Nicole | Thorleifsson, Gudmar | Loos, Ruth J F | Manning, Alisa K | Jackson, Anne U | Aulchenko, Yurii | Potter, Simon C | Erdos, Michael R | Sanna, Serena | Hottenga, Jouke-Jan | Wheeler, Eleanor | Kaakinen, Marika | Lyssenko, Valeriya | Chen, Wei-Min | Ahmadi, Kourosh | Beckmann, Jacques S | Bergman, Richard N | Bochud, Murielle | Bonnycastle, Lori L | Buchanan, Thomas A | Cao, Antonio | Cervino, Alessandra | Coin, Lachlan | Collins, Francis S | Crisponi, Laura | de Geus, Eco J C | Dehghan, Abbas | Deloukas, Panos | Doney, Alex S F | Elliott, Paul | Freimer, Nelson | Gateva, Vesela | Herder, Christian | Hofman, Albert | Hughes, Thomas E | Hunt, Sarah | Illig, Thomas | Inouye, Michael | Isomaa, Bo | Johnson, Toby | Kong, Augustine | Krestyaninova, Maria | Kuusisto, Johanna | Laakso, Markku | Lim, Noha | Lindblad, Ulf | Lindgren, Cecilia M | McCann, Owen T | Mohlke, Karen L | Morris, Andrew D | Naitza, Silvia | Orrù, Marco | Palmer, Colin N A | Pouta, Anneli | Randall, Joshua | Rathmann, Wolfgang | Saramies, Jouko | Scheet, Paul | Scott, Laura J | Scuteri, Angelo | Sharp, Stephen | Sijbrands, Eric | Smit, Jan H | Song, Kijoung | Steinthorsdottir, Valgerdur | Stringham, Heather M | Tuomi, Tiinamaija | Tuomilehto, Jaakko | Uitterlinden, André G | Voight, Benjamin F | Waterworth, Dawn | Wichmann, H-Erich | Willemsen, Gonneke | Witteman, Jacqueline C M | Yuan, Xin | Zhao, Jing Hua | Zeggini, Eleftheria | Schlessinger, David | Sandhu, Manjinder | Boomsma, Dorret I | Uda, Manuela | Spector, Tim D | Penninx, Brenda WJH | Altshuler, David | Vollenweider, Peter | Jarvelin, Marjo Riitta | Lakatta, Edward | Waeber, Gerard | Fox, Caroline S | Peltonen, Leena | Groop, Leif C | Mooser, Vincent | Cupples, L Adrienne | Thorsteinsdottir, Unnur | Boehnke, Michael | Barroso, Inês | Van Duijn, Cornelia | Dupuis, Josée | Watanabe, Richard M | Stefansson, Kari | McCarthy, Mark I | Wareham, Nicholas J | Meigs, James B | Abecasis, Gonçalo R
Nature genetics  2008;41(1):77-81.
To identify previously unknown genetic loci associated with fasting glucose concentrations, we examined the leading association signals in ten genome-wide association scans involving a total of 36,610 individuals of European descent. Variants in the gene encoding melatonin receptor 1B (MTNR1B) were consistently associated with fasting glucose across all ten studies. The strongest signal was observed at rs10830963, where each G allele (frequency 0.30 in HapMap CEU) was associated with an increase of 0.07 (95% CI = 0.06-0.08) mmol/l in fasting glucose levels (P = 3.2 = × 10−50) and reduced beta-cell function as measured by homeostasis model assessment (HOMA-B, P = 1.1 × 10−15). The same allele was associated with an increased risk of type 2 diabetes (odds ratio = 1.09 (1.05-1.12), per G allele P = 3.3 × 10−7) in a meta-analysis of 13 case-control studies totaling 18,236 cases and 64,453 controls. Our analyses also confirm previous associations of fasting glucose with variants at the G6PC2 (rs560887, P = 1.1 × 10−57) and GCK (rs4607517, P = 1.0 × 10−25) loci.
doi:10.1038/ng.290
PMCID: PMC2682768  PMID: 19060907
18.  Estimation of Newborn Risk for Child or Adolescent Obesity: Lessons from Longitudinal Birth Cohorts 
PLoS ONE  2012;7(11):e49919.
Objectives
Prevention of obesity should start as early as possible after birth. We aimed to build clinically useful equations estimating the risk of later obesity in newborns, as a first step towards focused early prevention against the global obesity epidemic.
Methods
We analyzed the lifetime Northern Finland Birth Cohort 1986 (NFBC1986) (N = 4,032) to draw predictive equations for childhood and adolescent obesity from traditional risk factors (parental BMI, birth weight, maternal gestational weight gain, behaviour and social indicators), and a genetic score built from 39 BMI/obesity-associated polymorphisms. We performed validation analyses in a retrospective cohort of 1,503 Italian children and in a prospective cohort of 1,032 U.S. children.
Results
In the NFBC1986, the cumulative accuracy of traditional risk factors predicting childhood obesity, adolescent obesity, and childhood obesity persistent into adolescence was good: AUROC = 0·78[0·74–0.82], 0·75[0·71–0·79] and 0·85[0·80–0·90] respectively (all p<0·001). Adding the genetic score produced discrimination improvements ≤1%. The NFBC1986 equation for childhood obesity remained acceptably accurate when applied to the Italian and the U.S. cohort (AUROC = 0·70[0·63–0·77] and 0·73[0·67–0·80] respectively) and the two additional equations for childhood obesity newly drawn from the Italian and the U.S. datasets showed good accuracy in respective cohorts (AUROC = 0·74[0·69–0·79] and 0·79[0·73–0·84]) (all p<0·001). The three equations for childhood obesity were converted into simple Excel risk calculators for potential clinical use.
Conclusion
This study provides the first example of handy tools for predicting childhood obesity in newborns by means of easily recorded information, while it shows that currently known genetic variants have very little usefulness for such prediction.
doi:10.1371/journal.pone.0049919
PMCID: PMC3509134  PMID: 23209618
19.  Associations between Variation in CHRNA5-CHRNA3-CHRNB4, Body Mass Index and Blood Pressure in the Northern Finland Birth Cohort 1966 
PLoS ONE  2012;7(9):e46557.
Background
The CHRNA5-CHRNA3-CHRNB4 gene cluster on 15q25 has consistently been associated with smoking quantity, nicotine dependence and lung cancer. Recent research also points towards its involvement in cardiovascular homeostasis, but studies in large human samples are lacking, especially on the role of the gene cluster in blood pressure regulation.
Methodology/Principal Findings
We studied the associations between 18 single nucleotide polymorphisms (SNPs) in CHRNA5-CHRNA3-CHRNB4 and systolic blood pressure (SBP), diastolic blood pressure (DBP), and body mass index (BMI) in 5402 young adults from the Northern Finland Birth Cohort 1966. We observed some evidence for associations between two SNPs and SBP and between six SNPs and BMI; the evidence for associations with DBP was weaker. The associations with the three phenotypes were driven by different loci with low linkage disequilibrium with each other. The associations appeared more pronounced in smokers, such that the smoking-increasing alleles would predict lower SBP and BMI. Each additional copy of the rs1948 G-allele and the rs950776 A-allele reduced SBP on average by −1.21 (95% CI −2.01, −0.40) mmHg in smokers. The variants associated with BMI included rs2036534, rs6495309, rs1996371, rs6495314, rs4887077 and rs11638372 and had an average effect size of −0.38 (−0.68, −0.08) kg/m2 per an additional copy of the risk allele in smokers. Formal assessments of interactions provided weaker support for these findings, especially after adjustment for multiple testing.
Conclusions
Variation at 15q25 appears to interact with smoking status in influencing SBP and BMI. The genetic loci associated with SBP were in low linkage disequilibrium with those associated with BMI suggesting that the gene cluster might regulate SBP through biological mechanisms that partly differ from those regulating BMI. Further studies in larger samples are needed for more precise evaluation of the possible interactions, and to understand the mechanisms behind.
doi:10.1371/journal.pone.0046557
PMCID: PMC3459914  PMID: 23029550
20.  Genetic variation in the 15q25 nicotinic acetylcholine receptor gene cluster (CHRNA5–CHRNA3–CHRNB4) interacts with maternal self-reported smoking status during pregnancy to influence birth weight 
Human Molecular Genetics  2012;21(24):5344-5358.
Maternal smoking during pregnancy is associated with low birth weight. Common variation at rs1051730 is robustly associated with smoking quantity and was recently shown to influence smoking cessation during pregnancy, but its influence on birth weight is not clear. We aimed to investigate the association between this variant and birth weight of term, singleton offspring in a well-powered meta-analysis. We stratified 26 241 European origin study participants by smoking status (women who smoked during pregnancy versus women who did not smoke during pregnancy) and, in each stratum, analysed the association between maternal rs1051730 genotype and offspring birth weight. There was evidence of interaction between genotype and smoking (P = 0.007). In women who smoked during pregnancy, each additional smoking-related T-allele was associated with a 20 g [95% confidence interval (95% CI): 4–36 g] lower birth weight (P = 0.014). However, in women who did not smoke during pregnancy, the effect size estimate was 5 g per T-allele (95% CI: −4 to 14 g; P = 0.268). To conclude, smoking status during pregnancy modifies the association between maternal rs1051730 genotype and offspring birth weight. This strengthens the evidence that smoking during pregnancy is causally related to lower offspring birth weight and suggests that population interventions that effectively reduce smoking in pregnant women would result in a reduced prevalence of low birth weight.
doi:10.1093/hmg/dds372
PMCID: PMC3516066  PMID: 22956269
21.  Glucocorticoid receptor (NR3C1) gene polymorphisms and onset of alcohol abuse in adolescents 
Addiction biology  2010;16(3):510-513.
Onset of alcohol use at an early age increases the risk for later alcohol dependence. We investigated the role of the glucocorticoid receptor (GR) gene (NR3C1) in onset of alcohol use and abuse in 14-year-old adolescents (n = 4534). Several NR3C1 polymorphisms were associated with onset of alcohol drinking or drunkenness at this age. Strongest associations were observed in females, with one marker (rs244465) remaining significant after correction for multiple testing (Padj = 0.0067; odds ratio = 1.7, for drunkenness). Our data provide the first evidence that GR modulates initiation of alcohol abuse and reveal a polymorphism that might contribute to susceptibility to addiction.
doi:10.1111/j.1369-1600.2010.00239.x
PMCID: PMC3428936  PMID: 20731635
Addiction; adolescent; alcohol; glucocorticoid receptor; NR3C1; polymorphism
22.  META-ANALYSIS OF GENOME-WIDE ASSOCIATION STUDIES IDENTIFIES THREE NEW RISK LOCI FOR ATOPIC DERMATITIS 
Paternoster, Lavinia | Standl, Marie | Chen, Chih-Mei | Ramasamy, Adaikalavan | Bønnelykke, Klaus | Duijts, Liesbeth | Ferreira, Manuel A | Alves, Alexessander Couto | Thyssen, Jacob P | Albrecht, Eva | Baurecht, Hansjörg | Feenstra, Bjarke | Sleiman, Patrick MA | Hysi, Pirro | Warrington, Nicole M | Curjuric, Ivan | Myhre, Ronny | Curtin, John A | Groen-Blokhuis, Maria M | Kerkhof, Marjan | Sääf, Annika | Franke, Andre | Ellinghaus, David | Fölster-Holst, Regina | Dermitzakis, Emmanouil | Montgomery, Stephen B | Prokisch, Holger | Heim, Katharina | Hartikainen, Anna-Liisa | Pouta, Anneli | Pekkanen, Juha | Blakemore, Alexandra IF | Buxton, Jessica L | Kaakinen, Marika | Duffy, David L | Madden, Pamela A | Heath, Andrew C | Montgomery, Grant W | Thompson, Philip J | Matheson, Melanie C | Le Souëf, Peter | Pourcain, Beate St | Smith, George Davey | Henderson, John | Kemp, John P | Timpson, Nicholas J | Deloukas, Panos | Ring, Susan M | Wichmann, H-Erich | Müller-Nurasyid, Martina | Novak, Natalija | Klopp, Norman | Rodríguez, Elke | McArdle, Wendy | Linneberg, Allan | Menné, Torkil | Nohr, Ellen A | Hofman, Albert | Uitterlinden, André G | van Duijn, Cornélia M | Rivadeneira, Fernando | de Jongste, Johan C | van der Valk, Ralf JP | Wjst, Matthias | Jogi, Rain | Geller, Frank | Boyd, Heather A | Murray, Jeffrey C | Kim, Cecilia | Mentch, Frank | March, Michael | Mangino, Massimo | Spector, Tim D | Bataille, Veronique | Pennell, Craig E | Holt, Patrick G | Sly, Peter | Tiesler, Carla MT | Thiering, Elisabeth | Illig, Thomas | Imboden, Medea | Nystad, Wenche | Simpson, Angela | Hottenga, Jouke-Jan | Postma, Dirkje | Koppelman, Gerard H | Smit, Henriette A | Söderhäll, Cilla | Chawes, Bo | Kreiner-Møller, Eskil | Bisgaard, Hans | Melén, Erik | Boomsma, Dorret I | Custovic, Adnan | Jacobsson, Bo | Probst-Hensch, Nicole M | Palmer, Lyle J | Glass, Daniel | Hakonarson, Hakon | Melbye, Mads | Jarvis, Deborah L | Jaddoe, Vincent WV | Gieger, Christian | Strachan, David P | Martin, Nicholas G | Jarvelin, Marjo-Riitta | Heinrich, Joachim | Evans, David M | Weidinger, Stephan
Nature genetics  2011;44(2):187-192.
Atopic dermatitis (AD) is a common chronic skin disease with high heritability. Apart from filaggrin (FLG), the genes influencing AD are largely unknown. We conducted a genome-wide association meta-analysis of 5,606 cases and 20,565 controls from 16 population-based cohorts and followed up the ten most strongly associated novel markers in a further 5,419 cases and 19,833 controls from 14 studies. Three SNPs met genome-wide significance in the discovery and replication cohorts combined: rs479844 upstream of OVOL1 (OR=0.88, p=1.1×10−13) and rs2164983 near ACTL9 (OR=1.16, p=7.1×10−9), genes which have been implicated in epidermal proliferation and differentiation, as well as rs2897442 in KIF3A within the cytokine cluster on 5q31.1 (OR=1.11, p=3.8×10−8). We also replicated the FLG locus and two recently identified association signals at 11q13.5 (rs7927894, p=0.008) and 20q13.3 (rs6010620, p=0.002). Our results underline the importance of both epidermal barrier function and immune dysregulation in AD pathogenesis.
doi:10.1038/ng.1017
PMCID: PMC3272375  PMID: 22197932
23.  Evidence of Inbreeding Depression on Human Height 
McQuillan, Ruth | Eklund, Niina | Pirastu, Nicola | Kuningas, Maris | McEvoy, Brian P. | Esko, Tõnu | Corre, Tanguy | Davies, Gail | Kaakinen, Marika | Lyytikäinen, Leo-Pekka | Kristiansson, Kati | Havulinna, Aki S. | Gögele, Martin | Vitart, Veronique | Tenesa, Albert | Aulchenko, Yurii | Hayward, Caroline | Johansson, Åsa | Boban, Mladen | Ulivi, Sheila | Robino, Antonietta | Boraska, Vesna | Igl, Wilmar | Wild, Sarah H. | Zgaga, Lina | Amin, Najaf | Theodoratou, Evropi | Polašek, Ozren | Girotto, Giorgia | Lopez, Lorna M. | Sala, Cinzia | Lahti, Jari | Laatikainen, Tiina | Prokopenko, Inga | Kals, Mart | Viikari, Jorma | Yang, Jian | Pouta, Anneli | Estrada, Karol | Hofman, Albert | Freimer, Nelson | Martin, Nicholas G. | Kähönen, Mika | Milani, Lili | Heliövaara, Markku | Vartiainen, Erkki | Räikkönen, Katri | Masciullo, Corrado | Starr, John M. | Hicks, Andrew A. | Esposito, Laura | Kolčić, Ivana | Farrington, Susan M. | Oostra, Ben | Zemunik, Tatijana | Campbell, Harry | Kirin, Mirna | Pehlic, Marina | Faletra, Flavio | Porteous, David | Pistis, Giorgio | Widén, Elisabeth | Salomaa, Veikko | Koskinen, Seppo | Fischer, Krista | Lehtimäki, Terho | Heath, Andrew | McCarthy, Mark I. | Rivadeneira, Fernando | Montgomery, Grant W. | Tiemeier, Henning | Hartikainen, Anna-Liisa | Madden, Pamela A. F. | d'Adamo, Pio | Hastie, Nicholas D. | Gyllensten, Ulf | Wright, Alan F. | van Duijn, Cornelia M. | Dunlop, Malcolm | Rudan, Igor | Gasparini, Paolo | Pramstaller, Peter P. | Deary, Ian J. | Toniolo, Daniela | Eriksson, Johan G. | Jula, Antti | Raitakari, Olli T. | Metspalu, Andres | Perola, Markus | Järvelin, Marjo-Riitta | Uitterlinden, André | Visscher, Peter M. | Wilson, James F.
PLoS Genetics  2012;8(7):e1002655.
Stature is a classical and highly heritable complex trait, with 80%–90% of variation explained by genetic factors. In recent years, genome-wide association studies (GWAS) have successfully identified many common additive variants influencing human height; however, little attention has been given to the potential role of recessive genetic effects. Here, we investigated genome-wide recessive effects by an analysis of inbreeding depression on adult height in over 35,000 people from 21 different population samples. We found a highly significant inverse association between height and genome-wide homozygosity, equivalent to a height reduction of up to 3 cm in the offspring of first cousins compared with the offspring of unrelated individuals, an effect which remained after controlling for the effects of socio-economic status, an important confounder (χ2 = 83.89, df = 1; p = 5.2×10−20). There was, however, a high degree of heterogeneity among populations: whereas the direction of the effect was consistent across most population samples, the effect size differed significantly among populations. It is likely that this reflects true biological heterogeneity: whether or not an effect can be observed will depend on both the variance in homozygosity in the population and the chance inheritance of individual recessive genotypes. These results predict that multiple, rare, recessive variants influence human height. Although this exploratory work focuses on height alone, the methodology developed is generally applicable to heritable quantitative traits (QT), paving the way for an investigation into inbreeding effects, and therefore genetic architecture, on a range of QT of biomedical importance.
Author Summary
Studies investigating the extent to which genetics influences human characteristics such as height have concentrated mainly on common variants of genes, where having one or two copies of a given variant influences the trait or risk of disease. This study explores whether a different type of genetic variant might also be important. We investigate the role of recessive genetic variants, where two identical copies of a variant are required to have an effect. By measuring genome-wide homozygosity—the phenomenon of inheriting two identical copies at a given point of the genome—in 35,000 individuals from 21 European populations, and by comparing this to individual height, we found that the more homozygous the genome, the shorter the individual. The offspring of first cousins (who have increased homozygosity) were predicted to be up to 3 cm shorter on average than the offspring of unrelated parents. Height is influenced by the combined effect of many recessive variants dispersed across the genome. This may also be true for other human characteristics and diseases, opening up a new way to understand how genetic variation influences our health.
doi:10.1371/journal.pgen.1002655
PMCID: PMC3400549  PMID: 22829771
24.  The Interplay of Variants Near LEKR and CCNL1 and Social Stress in Relation to Birth Size 
PLoS ONE  2012;7(6):e38216.
Background
We previously identified via a genome wide association study variants near LEKR and CCNL1 and in the ADCY5 genes lead to lower birthweight. Here, we study the impact of these variants and social stress during pregnancy, defined as social adversity and neighborhood disparity, on infant birth size. We aimed to determine whether the addition of genetic variance magnified the observed associations.
Methodology/Principal Findings
We analyzed data from the Northern Finland Birth Cohort 1986 (n = 5369). Social adversity was defined by young maternal age (<20 years), low maternal education (<11 years), and/or single marital status. Neighborhood social disparity was assessed by discrepancy between neighborhoods relative to personal socio-economic status. These variables are indicative of social and socioeconomic stress, but also of biological risk. The adjusted multiple regression analysis showed smaller birth size in both infants of mothers who experienced social adversity (birthweight by −40.4 g, 95%CI −61.4, −19.5; birth length −0.14 cm, 95%CI −0.23, −0.05; head circumference −0.09 cm 95%CI −0.15, −0.02) and neighborhood disparity (birthweight −28.8 g, 95%CI −47.7, −10.0; birth length −0.12 cm, 95%CI −0.20, −0.05). The birthweight-lowering risk allele (SNP rs900400 near LEKR and CCNL1) magnified this association in an additive manner. However, likely due to sample size restriction, this association was not significant for the SNP rs9883204 in ADCY5. Birth size difference due to social stress was greater in the presence of birthweight-lowering alleles.
Conclusions/Significance
Social adversity, neighborhood disparity, and genetic variants have independent associations with infant birth size in the mutually adjusted analyses. If the newborn carried a risk allele rs900400 near LEKR/CCNL1, the impact of stress on birth size was stronger. These observations give support to the hypothesis that individuals with genetic or other biological risk are more vulnerable to environmental influences. Our study indicates the need for further research to understand the mechanisms by which genes impact individual vulnerability to environmental insults.
doi:10.1371/journal.pone.0038216
PMCID: PMC3369922  PMID: 22685556
25.  TTC12-ANKK1-DRD2 and CHRNA5-CHRNA3-CHRNB4 influence different pathways leading to smoking behaviour from adolescence to mid-adulthood 
Biological psychiatry  2010;69(7):650-660.
Background
CHRNA5-CHRNA3-CHRNB4 and TTC12-ANKK1-DRD2 gene-clusters influence smoking behavior. Our aim was to test developmental changes in their effects as well as the interplays between them and with non-genetic factors.
Methods
Participants included 4,762 subjects from a general population based prospective Northern Finland 1966 Birth Cohort (NFBC 1966). Smoking behavior was collected at age 14 and 31 years(y). Information on maternal smoking, socio-economic status, and novelty seeking were also collected. Structural equation modeling was used to construct an integrative etiological model including genetic and non-genetic factors.
Results
Several SNPs in both gene-clusters were significantly associated with smoking. The most significant were in CHRNA3 (rs1051730, P=1.1×10−5) and in TTC12 (rs10502172, P=9.1×10−6). CHRNA3-rs1051730[A] was more common among heavy/regular smokers than non-smokers with similar effect-sizes at age 14y [OR(95%CI):1.27(1.06–1.52)] and 31y [1.28(1.13–1.44)]. TTC12-rs10502172[G] was more common among smokers than non-smokers with stronger association at 14y [1.33(1.11–1.60)] than 31y [1.14(1.02–1.28)]. In adolescence, carriers of three-four risk alleles at either CHRNA3-rs1051730 or TTC12-rs10502172 had almost 3-fold odds of smoking regularly than subjects with no risk alleles. TTC12-rs10502172 effect on smoking in adulthood was mediated by its effect on smoking in adolescence and via novelty seeking. Effect of CHRNA3-rs1051730 on smoking in adulthood was direct.
Conclusions
TTC12-ANKK1-DRD2s seemed to influence smoking behavior mainly in adolescence and its effect is partially mediated by personality characteristics promoting drug-seeking behavior. In contrast, CHRNA5-CHRNA3-CHRNB4 is involved in the transition towards heavy smoking in mid-adulthood and in smoking persistence. Factors related to familial and social disadvantages were strong independent predictors of smoking.
doi:10.1016/j.biopsych.2010.09.055
PMCID: PMC3058144  PMID: 21168125
TTC12; ANKK1; DRD2; CHRNA5; CHRNA3; CHRNB4; nicotine; gene; adolescence; smoking

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