Meta-analysis of Dense Genecentric Association Studies Reveals Common and Uncommon Variants Associated with Height

Lanktree, Matthew B.; Guo, Yiran; Murtaza, Muhammed; Glessner, Joseph T.; Bailey, Swneke D.; Onland‐Moret, N. Charlotte; Lettre, Guillaume; Ongen, Halit; Rajagopalan, Ramakrishnan; Johnson, Toby; Shen, Haiqing; Nelson, Christopher P.; Klopp, Norman; Baumert, Jens; Padmanabhan, Sandosh; Pankratz, Nathan; Pankow, James S.; Shah, Sonia; Taylor, Kira C.; Barnard, John; Peters, Bas J M; Maloney, Cliona M.; Lobmeyer, Maximilian T.; Stanton, Alice; Zafarmand, Mohammad Hadi; Romaine, Simon P. R.; Mehta, Amar; Iperen, Erik P.A. van; Gong, Yan; Price, Thomas S.; Smith, Erin N.; Kim, Chong; Li, Yun R.; Asselbergs, Folkert W.; Atwood, Larry D.; Bailey, Kristian; Bhatt, Deepak L.; Bauer, Florianne; Behr, Elijah R.; Bhangale, Tushar; Boer, Jolanda M. A.; Boehm, Bernhard O.; Bradfield, Jonathan P.; Brown, M A; Braund, Peter S.; Burton, Paul R.; Carty, Cara L.; Chandrupatla, Hareesh R.; Chen, Wei; Connell, John; Dalgeorgou, Chrysoula; Boer, Anthonius de; Drenos, Fotios; Elbers, Clara C.; Fang, James C.; Fox, Caroline S.; Frackelton, Edward C.; Fuchs, Barry D.; Furlong, Clement E.; Gibson, Quince; Gieger, Christian; Goel, Anuj; Grobbee, D. E.; Hastie, Claire E.; Howard, Philip J.; Huang, Guan; Johnson, W. Craig; Li, Qing; Kleber, Marcus E.; Klein, Barbara E. K.; Klein, Ronald; Kooperberg, Charles; Ky, Bonnie; LaCroix, Andrea Z.; Lanken, Paul N.; Lathrop, Mark; Li, Mingyao; Marshall, Vanessa; Melander, Olle; Mentch, Frank; Meyer, Nuala J.; Monda, Keri L.; Montpetit, Alexandre; Murugesan, Gurunathan; Nakayama, Karen; Nondahl, Dave; Onipinla, Abiodun; Rafelt, Suzanne; Newhouse, Stephen; Otieno, F. George; Patel, Sanjay R.; Putt, Mary; Rodríguez, Santiago; Safa, Radwan; Sawyer, Douglas B.; Schreiner, Pamela J.; Simpson, Claire L.; Sivapalaratnam, Suthesh; Srinivasan, Sathanur R.; Suver, Christine; Swergold, Gary D.; Sweitzer, Nancy K.; Thomas, Kelly; Thorand, Barbara; Timpson, Nicholas J.; Tischfield, Sam E.; Tobin, Martin D.; Tomaszewski, Maciej; Verschuren, W M Monique; Wallace, Chris; Winkelmann, Bernhard R.; Zhang, Haitao; Zheng, Deyou; Zhang, Li; Zmuda, Joseph M.; Clarke, Robert; Balmforth, Anthony J.; Danesh, John; Day, Ian N. M.; Schork, Nicholas J.; Bakker, Paul I. W. de; Delles, Christian; Duggan, David; Hingorani, Aroon D.; Hirschhorn, Joel N.; Hofker, Marten H.; Humphries, Steve E.; Kivimäki, Mika; Lawlor, Debbie A.; Kottke‐Marchant, Kandice; Mega, Jessica L.; Mitchell, Braxton D.; Morrow, David A.; Palmen, Jutta; Redline, Susan; Shields, Denis C.; Shuldiner, Alan R.; Sleiman, Patrick; Smith, George Davey; Farrall, Martin; Jamshidi, Yalda; Christiani, David C.; Casas, Juan P.; Hall, Alistair S.; Doevendans, Pieter A.; Christie, Jason D.; Berenson, Gerald S.; Murray, Sarah; Illig, Thomas; Dorn, Gerald W.; Cappola, Thomas P.; Boerwinkle, Eric; Sever, Peter; Rader, Daniel J.; Reilly, Muredach P.; Caulfield, Mark; Talmud, Philippa J.; Topol, Eric J.; Engert, James C.; Wang, Kai; Dominiczak, Anna F.; Hamsten, Anders; Curtis, Sean; Silverstein, Roy L.; Lange, Leslie A.; Sabatine, Marc S.; Trip, Mieke D.; Saleheen, Danish; Peden, John F.; Cruickshanks, Karen J.; März, Winfried; O’Connell, Jeffrey R.; Klungel, Olaf H.; Wijmenga, Cisca; Zee, Anke‐Hilse Maitland‐van der; Schadt, Eric E.; Johnson, Julie A.; Jarvik, Gail P.; Papanicolaou, George; Grant, Struan F.A.; Munroe, Patricia B.; North, Kari E.; Samani, Nilesh J.; Köenig, Wolfgang; Gaunt, Tom R.; Anand, Sonia S.; Schouw, Yvonne T. van der; Soranzo, Nicole; FitzGerald, Garret A.; Reiner, Alex P.; Hegele, Robert A.; Hákonarson, Hákon; Keating, Brendan J.

doi:10.1016/j.ajhg.2012.05.017

Cited by 18 publications

(24 citation statements)

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“…In addition, a relationship between rs6180 and body height has been previously reported. 25 However, in the present study, the correlation between rs6180 and RCP-LCP was weakened on adding the covariate of A'-PTM' to the correction value. As craniofacial size is strongly correlated with body height, 26 we estimated a relationship between rs6180 and height by using A'-PTM' data as an indicator for the craniofacial size.…”

Section: Discussionmentioning

confidence: 65%

Growth hormone receptor gene variant and three-dimensional mandibular morphology

Nakawaki

Yamaguchi

Isa

et al. 2016

The Angle Orthodontist

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Objective: To examine the relationship between three-dimensional mandibular morphology and growth hormone receptor (GHR) gene variants in a healthy Japanese population. Materials and Methods: The subjects, who were unrelated Japanese orthodontic patients, consisted of 64 men and 114 women. Using the Taqman genotyping assay, GHR gene rs6184 and rs6180 variants were detected in genomic DNA extracted from saliva. Mandibular volume and length were measured from cone-beam computed tomography images that were analyzed using Analyze image-processing software. The relationship between GHR gene variants and threedimensional mandibular morphology was statistically examined. Results: Statistical significance for the relationship between the distance between the left and right coronoid processes and rs6180 was noted (P , .05). Conclusion: Our results indicate that the GHR variant rs6180 is associated with the distance between the left and right coronoid process in the Japanese subjects. (Angle Orthod. 2017;87:68-73)

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Section: Discussionmentioning

confidence: 65%

Growth hormone receptor gene variant and three-dimensional mandibular morphology

Nakawaki

Yamaguchi

Isa

et al. 2016

The Angle Orthodontist

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“…In addition to being highly redundant and finely tuned, blood pressure regulation is a coordinated effort of multiple pathways-the nervous system, the heart, the kidneys, and the hypothalamic-pituitary-adrenal axis, among others. We now have empirical evidence that height is likely to be influenced by 4-500 genetic loci (Lanktree et al 2011); it would be surprising if any fewer accounted for the distribution of blood pressure in the population. Large studies on blood pressure have failed to identify loci that have major effects, and although this may be in part owing to the difficulty in characterizing "average" blood pressure of an individual, it shows that genes with large effects are not common in human populations.…”

Section: Genomics and Studies Of Racial Factors In Diseasementioning

confidence: 99%

Race in Biological and Biomedical Research

Cooper

2013

Cold Spring Harbor Perspectives in Medicine

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“…The first example is based on a recent meta-analysis of three case-control studies in Paget's disease [4] . In the second example, we consider the effect of a planned study on a current meta-analysis of 25 studies in human height [5] , and illustrate the use of an additive genotype model as well as a quantitative phenotype.…”

Section: Examplesmentioning

confidence: 99%

“…To illustrate its particular strengths, the proposed algorithm is applied to two recent meta-analyses, one in Paget's disease [4] and a second in human height [5] . Appropriate R code to implement the sample size estimation algorithm is available in the software package metaSNPPER which is freely available from the R project [6] .…”

Section: Introductionmentioning

confidence: 99%

Cumulative Meta-Analysis for Genetic Association: When Is a New Study Worthwhile?

Rotondi

Bull²

2012

Hum Hered

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Objectives: In this paper, we address the questions: how large a sample size would be required to show genome-wide significance between a single nucleotide polymorphism (SNP) and a genetic trait in a meta-analysis of a newly planned study together with the existing ones? Or alternatively: will a planned study of size n be able to provide evidence of a genetic association when this study is combined with a current meta-analysis? Methods: We examine the potential impact of a newly planned genetic study on an existing meta-analysis through the use of a simulation-based algorithm. The proposed approach provides an empirical estimate of the power of the updated meta-analysis to detect genome-wide significance (p < 5.0 × 10^-8) of a complex trait and each of a set of specific SNPs of interest or the expected p value of the updated meta-analysis including the current and proposed studies. Results: This technique is illustrated in the context of an updated meta-analysis of case-control studies in Paget's disease. A second example illustrates the impact of adding a newly planned study to a large meta-analysis of SNP associations with human height. Conclusions: The proposed algorithm is particularly useful for the design of studies to assess a selected set of high-priority SNP associations that are ‘nearly' significant in meta-analysis of existing studies. The results may help investigators decide whether an updated meta-analysis is likely to achieve genome-wide significance.

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Meta-analysis of Dense Genecentric Association Studies Reveals Common and Uncommon Variants Associated with Height

Cited by 18 publications

References 0 publications

Growth hormone receptor gene variant and three-dimensional mandibular morphology

Growth hormone receptor gene variant and three-dimensional mandibular morphology

Race in Biological and Biomedical Research

Cumulative Meta-Analysis for Genetic Association: When Is a New Study Worthwhile?

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