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Rare and low-frequency coding variants alter human adult height.
Marouli E, Graff M, Medina-Gomez C, Lo KS, Wood AR, Kjaer TR, Fine RS, Lu Y, Schurmann C, Highland HM, Rüeger S, Thorleifsson G, Justice AE, Lamparter D, Stirrups KE, Turcot V, Young KL, Winkler TW, Esko T, Karaderi T, Locke AE, Masca NG, Ng MC, Mudgal P, Rivas MA, Vedantam S, Mahajan A, Guo X, Abecasis G, Aben KK, Adair LS, Alam DS, Albrecht E, Allin KH, Allison M, Amouyel P, Appel EV, Arveiler D, Asselbergs FW, Auer PL, Balkau B, Banas B, Bang LE, Benn M, Bergmann S, Bielak LF, Blüher M, Boeing H, Boerwinkle E, Böger CA, Bonnycastle LL, Bork-Jensen J, Bots ML, Bottinger EP, Bowden DW, Brandslund I, Breen G, Brilliant MH, Broer L, Burt AA, Butterworth AS, Carey DJ, Caulfield MJ, Chambers JC, Chasman DI, Chen YI, Chowdhury R, Christensen C, Chu AY, Cocca M, Collins FS, Cook JP, Corley J, Galbany JC, Cox AJ, Cuellar-Partida G, Danesh J, Davies G, de Bakker PI, de Borst GJ, de Denus S, de Groot MC, de Mutsert R, Deary IJ, Dedoussis G, Demerath EW, den Hollander AI, Dennis JG, Di Angelantonio E, Drenos F, Du M, Dunning AM, Easton DF, Ebeling T, Edwards TL, Ellinor PT, Elliott P, Evangelou E, Farmaki AE, Faul JD, Feitosa MF, Feng S, Ferrannini E, Ferrario MM, Ferrieres J, Florez JC, Ford I, Fornage M, Franks PW, Frikke-Schmidt R, Galesloot TE, Gan W, Gandin I, Gasparini P, Giedraitis V, Giri A, Girotto G, Gordon SD, Gordon-Larsen P, Gorski M, Grarup N, Grove ML, Gudnason V, Gustafsson S, Hansen T, Harris KM, Harris TB, Hattersley AT, Hayward C, He L, Heid IM, Heikkilä K, Helgeland Ø, Hernesniemi J, Hewitt AW, Hocking LJ, Hollensted M, Holmen OL, Hovingh GK, Howson JM, Hoyng CB, Huang PL, Hveem K, Ikram MA, Ingelsson E, Jackson AU, Jansson JH, Jarvik GP, Jensen GB, Jhun MA, Jia Y, Jiang X, Johansson S, Jørgensen ME, Jørgensen T, Jousilahti P, Jukema JW, Kahali B, Kahn RS, Kähönen M, Kamstrup PR, Kanoni S, Kaprio J, Karaleftheri M, Kardia SL, Karpe F, Kee F, Keeman R, Kiemeney LA, Kitajima H, Kluivers KB, Kocher T, Komulainen P, Kontto J, Kooner JS, Kooperberg C, Kovacs P, Kriebel J, Kuivaniemi H, Küry S, Kuusisto J, La Bianca M, Laakso M, Lakka TA, Lange EM, Lange LA, Langefeld CD, Langenberg C, Larson EB, Lee IT, Lehtimäki T, Lewis CE, Li H, Li J, Li-Gao R, Lin H, Lin LA, Lin X, Lind L, Lindström J, Linneberg A, Liu Y, Liu Y, Lophatananon A, Luan J, Lubitz SA, Lyytikäinen LP, Mackey DA, Madden PA, Manning AK, Männistö S, Marenne G, Marten J, Martin NG, Mazul AL, Meidtner K, Metspalu A, Mitchell P, Mohlke KL, Mook-Kanamori DO, Morgan A, Morris AD, Morris AP, Müller-Nurasyid M, Munroe PB, Nalls MA, Nauck M, Nelson CP, Neville M, Nielsen SF, Nikus K, Njølstad PR, Nordestgaard BG, Ntalla I, O'Connel JR, Oksa H, Loohuis LM, Ophoff RA, Owen KR, Packard CJ, Padmanabhan S, Palmer CN, Pasterkamp G, Patel AP, Pattie A, Pedersen O, Peissig PL, Peloso GM, Pennell CE, Perola M, Perry JA, Perry JR, Person TN, Pirie A, Polasek O, Posthuma D, Raitakari OT, Rasheed A, Rauramaa R, Reilly DF, Reiner AP, Renström F, Ridker PM, Rioux JD, Robertson N, Robino A, Rolandsson O, Rudan I, Ruth KS, Saleheen D, Salomaa V, Samani NJ, Sandow K, Sapkota Y, Sattar N, Schmidt MK, Schreiner PJ, Schulze MB, Scott RA, Segura-Lepe MP, Shah S, Sim X, Sivapalaratnam S, Small KS, Smith AV, Smith JA, Southam L, Spector TD, Speliotes EK, Starr JM, Steinthorsdottir V, Stringham HM, Stumvoll M, Surendran P, 't Hart LM, Tansey KE, Tardif JC, Taylor KD, Teumer A, Thompson DJ, Thorsteinsdottir U, Thuesen BH, Tönjes A, Tromp G, Trompet S, Tsafantakis E, Tuomilehto J, Tybjaerg-Hansen A, Tyrer JP, Uher R, Uitterlinden AG, Ulivi S, van der Laan SW, Van Der Leij AR, van Duijn CM, van Schoor NM, van Setten J, Varbo A, Varga TV, Varma R, Edwards DR, Vermeulen SH, Vestergaard H, Vitart V, Vogt TF, Vozzi D, Walker M, Wang F, Wang CA, Wang S, Wang Y, Wareham NJ, Warren HR, Wessel J, Willems SM, Wilson JG, Witte DR, Woods MO, Wu Y, Yaghootkar H, Yao J, Yao P, Yerges-Armstrong LM, Young R, Zeggini E, Zhan X, Zhang W, Zhao JH, Zhao W, Zhao W, Zheng H, Zhou W, EPIC-InterAct Consortium, CHD Exome+ Consortium, ExomeBP Consortium, T2D-Genes Consortium, GoT2D Genes Consortium, Global Lipids Genetics Consortium, ReproGen Consortium, MAGIC Investigators, Rotter JI, Boehnke M, Kathiresan S, McCarthy MI, Willer CJ, Stefansson K, Borecki IB, Liu DJ, North KE, Heard-Costa NL, Pers TH, Lindgren CM, Oxvig C, Kutalik Z, Rivadeneira F, Loos RJ, Frayling TM, Hirschhorn JN, Deloukas P, Lettre G
(2017) Nature 542: 186-190
MeSH Terms: ADAMTS Proteins, Adult, Alleles, Body Height, Cell Adhesion Molecules, Female, Gene Frequency, Genetic Variation, Genome, Human, Glycoproteins, Glycosaminoglycans, Hedgehog Proteins, Humans, Intercellular Signaling Peptides and Proteins, Interferon Regulatory Factors, Interleukin-11 Receptor alpha Subunit, Male, Multifactorial Inheritance, NADPH Oxidase 4, NADPH Oxidases, Phenotype, Pregnancy-Associated Plasma Protein-A, Procollagen N-Endopeptidase, Proteoglycans, Proteolysis, Receptors, Androgen, Somatomedins
Show Abstract · Added April 26, 2017
Height is a highly heritable, classic polygenic trait with approximately 700 common associated variants identified through genome-wide association studies so far. Here, we report 83 height-associated coding variants with lower minor-allele frequencies (in the range of 0.1-4.8%) and effects of up to 2 centimetres per allele (such as those in IHH, STC2, AR and CRISPLD2), greater than ten times the average effect of common variants. In functional follow-up studies, rare height-increasing alleles of STC2 (giving an increase of 1-2 centimetres per allele) compromised proteolytic inhibition of PAPP-A and increased cleavage of IGFBP-4 in vitro, resulting in higher bioavailability of insulin-like growth factors. These 83 height-associated variants overlap genes that are mutated in monogenic growth disorders and highlight new biological candidates (such as ADAMTS3, IL11RA and NOX4) and pathways (such as proteoglycan and glycosaminoglycan synthesis) involved in growth. Our results demonstrate that sufficiently large sample sizes can uncover rare and low-frequency variants of moderate-to-large effect associated with polygenic human phenotypes, and that these variants implicate relevant genes and pathways.
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27 MeSH Terms
Association between Adult Height and Risk of Colorectal, Lung, and Prostate Cancer: Results from Meta-analyses of Prospective Studies and Mendelian Randomization Analyses.
Khankari NK, Shu XO, Wen W, Kraft P, Lindström S, Peters U, Schildkraut J, Schumacher F, Bofetta P, Risch A, Bickeböller H, Amos CI, Easton D, Eeles RA, Gruber SB, Haiman CA, Hunter DJ, Chanock SJ, Pierce BL, Zheng W, Colorectal Transdisciplinary Study (CORECT), Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE), Elucidating Loci Involved in Prostate Cancer Susceptibility (ELLIPSE), Transdisciplinary Research in Cancer of the Lung (TRICL)
(2016) PLoS Med 13: e1002118
MeSH Terms: Adult, Aged, Aged, 80 and over, Body Height, Colorectal Neoplasms, Female, Genetic Variation, Genome-Wide Association Study, Humans, Lung Neoplasms, Male, Mendelian Randomization Analysis, Middle Aged, Odds Ratio, Prospective Studies, Prostatic Neoplasms, Risk Factors, Young Adult
Show Abstract · Added April 10, 2018
BACKGROUND - Observational studies examining associations between adult height and risk of colorectal, prostate, and lung cancers have generated mixed results. We conducted meta-analyses using data from prospective cohort studies and further carried out Mendelian randomization analyses, using height-associated genetic variants identified in a genome-wide association study (GWAS), to evaluate the association of adult height with these cancers.
METHODS AND FINDINGS - A systematic review of prospective studies was conducted using the PubMed, Embase, and Web of Science databases. Using meta-analyses, results obtained from 62 studies were summarized for the association of a 10-cm increase in height with cancer risk. Mendelian randomization analyses were conducted using summary statistics obtained for 423 genetic variants identified from a recent GWAS of adult height and from a cancer genetics consortium study of multiple cancers that included 47,800 cases and 81,353 controls. For a 10-cm increase in height, the summary relative risks derived from the meta-analyses of prospective studies were 1.12 (95% CI 1.10, 1.15), 1.07 (95% CI 1.05, 1.10), and 1.06 (95% CI 1.02, 1.11) for colorectal, prostate, and lung cancers, respectively. Mendelian randomization analyses showed increased risks of colorectal (odds ratio [OR] = 1.58, 95% CI 1.14, 2.18) and lung cancer (OR = 1.10, 95% CI 1.00, 1.22) associated with each 10-cm increase in genetically predicted height. No association was observed for prostate cancer (OR = 1.03, 95% CI 0.92, 1.15). Our meta-analysis was limited to published studies. The sample size for the Mendelian randomization analysis of colorectal cancer was relatively small, thus affecting the precision of the point estimate.
CONCLUSIONS - Our study provides evidence for a potential causal association of adult height with the risk of colorectal and lung cancers and suggests that certain genetic factors and biological pathways affecting adult height may also affect the risk of these cancers.
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MeSH Terms
Heterozygosity Ratio, a Robust Global Genomic Measure of Autozygosity and Its Association with Height and Disease Risk.
Samuels DC, Wang J, Ye F, He J, Levinson RT, Sheng Q, Zhao S, Capra JA, Shyr Y, Zheng W, Guo Y
(2016) Genetics 204: 893-904
MeSH Terms: Body Height, Gene Frequency, Genetic Predisposition to Disease, Genome, Human, Heterozygote, Humans, Polymorphism, Genetic
Show Abstract · Added April 18, 2017
Greater genetic variability in an individual is protective against recessive disease. However, existing quantifications of autozygosity, such as runs of homozygosity (ROH), have proved highly sensitive to genotyping density and have yielded inconclusive results about the relationship of diversity and disease risk. Using genotyping data from three data sets with >43,000 subjects, we demonstrated that an alternative approach to quantifying genetic variability, the heterozygosity ratio, is a robust measure of diversity and is positively associated with the nondisease trait height and several disease phenotypes in subjects of European ancestry. The heterozygosity ratio is the number of heterozygous sites in an individual divided by the number of nonreference homozygous sites and is strongly affected by the degree of genetic admixture of the population and varies across human populations. Unlike quantifications of ROH, the heterozygosity ratio is not sensitive to the density of genotyping performed. Our results establish the heterozygosity ratio as a powerful new statistic for exploring the patterns and phenotypic effects of different levels of genetic variation in populations.
Copyright © 2016 by the Genetics Society of America.
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7 MeSH Terms
Testing the role of predicted gene knockouts in human anthropometric trait variation.
Lessard S, Manning AK, Low-Kam C, Auer PL, Giri A, Graff M, Schurmann C, Yaghootkar H, Luan J, Esko T, Karaderi T, NHLBI GO Exome Sequence Project, GOT2D, T2D-GENES, GIANT Consortium, Bottinger EP, Lu Y, Carlson C, Caulfield M, Dubé MP, Jackson RD, Kooperberg C, McKnight B, Mongrain I, Peters U, Reiner AP, Rhainds D, Sotoodehnia N, Hirschhorn JN, Scott RA, Munroe PB, Frayling TM, Loos RJ, North KE, Edwards TL, Tardif JC, Lindgren CM, Lettre G
(2016) Hum Mol Genet 25: 2082-2092
MeSH Terms: Anthropometry, Body Height, Body Mass Index, Canada, Exome, Female, Gene Knockout Techniques, Genotype, Humans, Male, Mutation, Phenotype, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Waist-Hip Ratio
Show Abstract · Added April 26, 2017
Although the role of complete gene inactivation by two loss-of-function mutations inherited in trans is well-established in recessive Mendelian diseases, we have not yet explored how such gene knockouts (KOs) could influence complex human phenotypes. Here, we developed a statistical framework to test the association between gene KOs and quantitative human traits. Our method is flexible, publicly available, and compatible with common genotype format files (e.g. PLINK and vcf). We characterized gene KOs in 4498 participants from the NHLBI Exome Sequence Project (ESP) sequenced at high coverage (>100×), 1976 French Canadians from the Montreal Heart Institute Biobank sequenced at low coverage (5.7×), and >100 000 participants from the Genetic Investigation of ANthropometric Traits (GIANT) Consortium genotyped on an exome array. We tested associations between gene KOs and three anthropometric traits: body mass index (BMI), height and BMI-adjusted waist-to-hip ratio (WHR). Despite our large sample size and multiple datasets available, we could not detect robust associations between specific gene KOs and quantitative anthropometric traits. Our results highlight several limitations and challenges for future gene KO studies in humans, in particular when there is no prior knowledge on the phenotypes that might be affected by the tested gene KOs. They also suggest that gene KOs identified with current DNA sequencing methodologies probably do not strongly influence normal variation in BMI, height, and WHR in the general human population.
© The Author 2016. Published by Oxford University Press.
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15 MeSH Terms
Height and Breast Cancer Risk: Evidence From Prospective Studies and Mendelian Randomization.
Zhang B, Shu XO, Delahanty RJ, Zeng C, Michailidou K, Bolla MK, Wang Q, Dennis J, Wen W, Long J, Li C, Dunning AM, Chang-Claude J, Shah M, Perkins BJ, Czene K, Darabi H, Eriksson M, Bojesen SE, Nordestgaard BG, Nielsen SF, Flyger H, Lambrechts D, Neven P, Wildiers H, Floris G, Schmidt MK, Rookus MA, van den Hurk K, de Kort WL, Couch FJ, Olson JE, Hallberg E, Vachon C, Rudolph A, Seibold P, Flesch-Janys D, Peto J, Dos-Santos-Silva I, Fletcher O, Johnson N, Nevanlinna H, Muranen TA, Aittomäki K, Blomqvist C, Li J, Humphreys K, Brand J, Guénel P, Truong T, Cordina-Duverger E, Menegaux F, Burwinkel B, Marme F, Yang R, Surowy H, Benitez J, Zamora MP, Perez JI, Cox A, Cross SS, Reed MW, Andrulis IL, Knight JA, Glendon G, Tchatchou S, Sawyer EJ, Tomlinson I, Kerin MJ, Miller N, Chenevix-Trench G, kConFab Investigators, Australian Ovarian Study Group, Haiman CA, Henderson BE, Schumacher F, Marchand LL, Lindblom A, Margolin S, Hooning MJ, Martens JW, Tilanus-Linthorst MM, Collée JM, Hopper JL, Southey MC, Tsimiklis H, Apicella C, Slager S, Toland AE, Ambrosone CB, Yannoukakos D, Giles GG, Milne RL, McLean C, Fasching PA, Haeberle L, Ekici AB, Beckmann MW, Brenner H, Dieffenbach AK, Arndt V, Stegmaier C, Swerdlow AJ, Ashworth A, Orr N, Jones M, Figueroa J, Garcia-Closas M, Brinton L, Lissowska J, Dumont M, Winqvist R, Pylkäs K, Jukkola-Vuorinen A, Grip M, Brauch H, Brüning T, Ko YD, Peterlongo P, Manoukian S, Bonanni B, Radice P, Bogdanova N, Antonenkova N, Dörk T, Mannermaa A, Kataja V, Kosma VM, Hartikainen JM, Devilee P, Seynaeve C, Van Asperen CJ, Jakubowska A, Lubiński J, Jaworska-Bieniek K, Durda K, Hamann U, Torres D, Schmutzler RK, Neuhausen SL, Anton-Culver H, Kristensen VN, Grenaker Alnæs GI, DRIVE Project, Pierce BL, Kraft P, Peters U, Lindstrom S, Seminara D, Burgess S, Ahsan H, Whittemore AS, John EM, Gammon MD, Malone KE, Tessier DC, Vincent D, Bacot F, Luccarini C, Baynes C, Ahmed S, Maranian M, Healey CS, González-Neira A, Pita G, Alonso MR, Álvarez N, Herrero D, Pharoah PD, Simard J, Hall P, Hunter DJ, Easton DF, Zheng W
(2015) J Natl Cancer Inst 107:
MeSH Terms: Body Height, Breast Neoplasms, Evidence-Based Medicine, Female, Humans, Mendelian Randomization Analysis, Odds Ratio, Prospective Studies, Risk Factors
Show Abstract · Added February 22, 2016
BACKGROUND - Epidemiological studies have linked adult height with breast cancer risk in women. However, the magnitude of the association, particularly by subtypes of breast cancer, has not been established. Furthermore, the mechanisms of the association remain unclear.
METHODS - We performed a meta-analysis to investigate associations between height and breast cancer risk using data from 159 prospective cohorts totaling 5216302 women, including 113178 events. In a consortium with individual-level data from 46325 case patients and 42482 control patients, we conducted a Mendelian randomization analysis using a genetic score that comprised 168 height-associated variants as an instrument. This association was further evaluated in a second consortium using summary statistics data from 16003 case patients and 41335 control patients.
RESULTS - The pooled relative risk of breast cancer was 1.17 (95% confidence interval [CI] = 1.15 to 1.19) per 10cm increase in height in the meta-analysis of prospective studies. In Mendelian randomization analysis, the odds ratio of breast cancer per 10cm increase in genetically predicted height was 1.22 (95% CI = 1.13 to 1.32) in the first consortium and 1.21 (95% CI = 1.05 to 1.39) in the second consortium. The association was found in both premenopausal and postmenopausal women but restricted to hormone receptor-positive breast cancer. Analyses of height-associated variants identified eight new loci associated with breast cancer risk after adjusting for multiple comparisons, including three loci at 1q21.2, DNAJC27, and CCDC91 at genome-wide significance level P < 5×10(-8).
CONCLUSIONS - Our study provides strong evidence that adult height is a risk factor for breast cancer in women and certain genetic factors and biological pathways affecting adult height have an important role in the etiology of breast cancer.
© The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
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9 MeSH Terms
Methodological Considerations in Estimation of Phenotype Heritability Using Genome-Wide SNP Data, Illustrated by an Analysis of the Heritability of Height in a Large Sample of African Ancestry Adults.
Chen F, He J, Zhang J, Chen GK, Thomas V, Ambrosone CB, Bandera EV, Berndt SI, Bernstein L, Blot WJ, Cai Q, Carpten J, Casey G, Chanock SJ, Cheng I, Chu L, Deming SL, Driver WR, Goodman P, Hayes RB, Hennis AJ, Hsing AW, Hu JJ, Ingles SA, John EM, Kittles RA, Kolb S, Leske MC, Millikan RC, Monroe KR, Murphy A, Nemesure B, Neslund-Dudas C, Nyante S, Ostrander EA, Press MF, Rodriguez-Gil JL, Rybicki BA, Schumacher F, Stanford JL, Signorello LB, Strom SS, Stevens V, Van Den Berg D, Wang Z, Witte JS, Wu SY, Yamamura Y, Zheng W, Ziegler RG, Stram AH, Kolonel LN, Le Marchand L, Henderson BE, Haiman CA, Stram DO
(2015) PLoS One 10: e0131106
MeSH Terms: African Continental Ancestry Group, Body Height, Female, Genome-Wide Association Study, Genotype, Humans, Linear Models, Male, Models, Genetic, Phenotype, Polymorphism, Single Nucleotide, Regression Analysis
Show Abstract · Added April 3, 2018
Height has an extremely polygenic pattern of inheritance. Genome-wide association studies (GWAS) have revealed hundreds of common variants that are associated with human height at genome-wide levels of significance. However, only a small fraction of phenotypic variation can be explained by the aggregate of these common variants. In a large study of African-American men and women (n = 14,419), we genotyped and analyzed 966,578 autosomal SNPs across the entire genome using a linear mixed model variance components approach implemented in the program GCTA (Yang et al Nat Genet 2010), and estimated an additive heritability of 44.7% (se: 3.7%) for this phenotype in a sample of evidently unrelated individuals. While this estimated value is similar to that given by Yang et al in their analyses, we remain concerned about two related issues: (1) whether in the complete absence of hidden relatedness, variance components methods have adequate power to estimate heritability when a very large number of SNPs are used in the analysis; and (2) whether estimation of heritability may be biased, in real studies, by low levels of residual hidden relatedness. We addressed the first question in a semi-analytic fashion by directly simulating the distribution of the score statistic for a test of zero heritability with and without low levels of relatedness. The second question was addressed by a very careful comparison of the behavior of estimated heritability for both observed (self-reported) height and simulated phenotypes compared to imputation R2 as a function of the number of SNPs used in the analysis. These simulations help to address the important question about whether today's GWAS SNPs will remain useful for imputing causal variants that are discovered using very large sample sizes in future studies of height, or whether the causal variants themselves will need to be genotyped de novo in order to build a prediction model that ultimately captures a large fraction of the variability of height, and by implication other complex phenotypes. Our overall conclusions are that when study sizes are quite large (5,000 or so) the additive heritability estimate for height is not apparently biased upwards using the linear mixed model; however there is evidence in our simulation that a very large number of causal variants (many thousands) each with very small effect on phenotypic variance will need to be discovered to fill the gap between the heritability explained by known versus unknown causal variants. We conclude that today's GWAS data will remain useful in the future for causal variant prediction, but that finding the causal variants that need to be predicted may be extremely laborious.
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Anthropometry and head and neck cancer:a pooled analysis of cohort data.
Gaudet MM, Kitahara CM, Newton CC, Bernstein L, Reynolds P, Weiderpass E, Kreimer AR, Yang G, Adami HO, Alavanja MC, Beane Freeman LE, Boeing H, Buring J, Chaturvedi A, Chen Y, D'Aloisio AA, Freedman M, Gao YT, Gaziano JM, Giles GG, Håkansson N, Huang WY, Lee IM, Linet MS, MacInnis RJ, Park Y, Prizment A, Purdue MP, Riboli E, Robien K, Sandler DP, Schairer C, Sesso HD, Ou Shu X, White E, Wolk A, Xiang YB, Zelenuich-Jacquotte A, Zheng W, Patel AV, Hartge P, Berrington de González A, Gapstur SM
(2015) Int J Epidemiol 44: 673-81
MeSH Terms: Adult, Aged, Aged, 80 and over, Anthropometry, Body Height, Body Mass Index, Cohort Studies, Female, Head and Neck Neoplasms, Humans, Male, Middle Aged, Smoking, Waist Circumference, Waist-Hip Ratio, Young Adult
Show Abstract · Added May 4, 2017
BACKGROUND - Associations between anthropometry and head and neck cancer (HNC) risk are inconsistent. We aimed to evaluate these associations while minimizing biases found in previous studies.
METHODS - We pooled data from 1,941,300 participants, including 3760 cases, in 20 cohort studies and used multivariable-adjusted Cox proportional hazard regression models to estimate hazard ratios (HR) and 95% confidence intervals (CI) for the association of anthropometric measures with HNC risk overall and stratified by smoking status.
RESULTS - Greater waist circumference (per 5 cm: HR = 1.04, 95% CI 1.03-1.05, P-value for trend = <0.0001) and waist-to-hip ratio (per 0.1 unit: HR = 1.07, 95% CI 1.05-1.09, P-value for trend = <0.0001), adjusted for body mass index (BMI), were associated with higher risk and did not vary by smoking status (P-value for heterogeneity = 0.85 and 0.44, respectively). Associations with BMI (P-value for interaction = <0.0001) varied by smoking status. Larger BMI was associated with higher HNC risk in never smokers (per 5 kg/m(2): HR = 1.15, 95% CI 1.06-1.24, P-value for trend = 0.0006), but not in former smokers (per 5 kg/m(2): HR = 0.99, 95% CI 0.93-1.06, P-value for trend = 0.79) or current smokers (per 5 kg/m(2): HR = 0.76, 95% CI 0.71-0.82, P-value for trend = <0.0001). Larger hip circumference was not associated with a higher HNC risk. Greater height (per 5 cm) was associated with higher risk of HNC in never and former smokers, but not in current smokers.
CONCLUSIONS - Waist circumference and waist-to-hip ratio were associated positively with HNC risk regardless of smoking status, whereas a positive association with BMI was only found in never smokers.
© The Author 2015; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association.
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16 MeSH Terms
Meta-analysis of genome-wide association studies of adult height in East Asians identifies 17 novel loci.
He M, Xu M, Zhang B, Liang J, Chen P, Lee JY, Johnson TA, Li H, Yang X, Dai J, Liang L, Gui L, Qi Q, Huang J, Li Y, Adair LS, Aung T, Cai Q, Cheng CY, Cho MC, Cho YS, Chu M, Cui B, Gao YT, Go MJ, Gu D, Gu W, Guo H, Hao Y, Hong J, Hu Z, Hu Y, Huang J, Hwang JY, Ikram MK, Jin G, Kang DH, Khor CC, Kim BJ, Kim HT, Kubo M, Lee J, Lee J, Lee NR, Li R, Li J, Liu J, Longe J, Lu W, Lu X, Miao X, Okada Y, Ong RT, Qiu G, Seielstad M, Sim X, Song H, Takeuchi F, Tanaka T, Taylor PR, Wang L, Wang W, Wang Y, Wu C, Wu Y, Xiang YB, Yamamoto K, Yang H, Liao M, Yokota M, Young T, Zhang X, Kato N, Wang QK, Zheng W, Hu FB, Lin D, Shen H, Teo YY, Mo Z, Wong TY, Lin X, Mohlke KL, Ning G, Tsunoda T, Han BG, Shu XO, Tai ES, Wu T, Qi L
(2015) Hum Mol Genet 24: 1791-800
MeSH Terms: Adolescent, Adult, Aged, Aged, 80 and over, Asian Continental Ancestry Group, Body Height, European Continental Ancestry Group, Far East, Female, Gene Frequency, Genetic Loci, Genome-Wide Association Study, Humans, Male, Metabolic Networks and Pathways, Middle Aged, Polymorphism, Single Nucleotide, Protein Tyrosine Phosphatases, Young Adult
Show Abstract · Added February 16, 2015
Human height is associated with risk of multiple diseases and is profoundly determined by an individual's genetic makeup and shows a high degree of ethnic heterogeneity. Large-scale genome-wide association (GWA) analyses of adult height in Europeans have identified nearly 180 genetic loci. A recent study showed high replicability of results from Europeans-based GWA studies in Asians; however, population-specific loci may exist due to distinct linkage disequilibrium patterns. We carried out a GWA meta-analysis in 93 926 individuals from East Asia. We identified 98 loci, including 17 novel and 81 previously reported loci, associated with height at P < 5 × 10(-8), together explaining 8.89% of phenotypic variance. Among the newly identified variants, 10 are commonly distributed (minor allele frequency, MAF > 5%) in Europeans, with comparable frequencies with in Asians, and 7 single-nucleotide polymorphisms are with low frequency (MAF < 5%) in Europeans. In addition, our data suggest that novel biological pathway such as the protein tyrosine phosphatase family is involved in regulation of height. The findings from this study considerably expand our knowledge of the genetic architecture of human height in Asians.
© The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
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19 MeSH Terms
Defining the role of common variation in the genomic and biological architecture of adult human height.
Wood AR, Esko T, Yang J, Vedantam S, Pers TH, Gustafsson S, Chu AY, Estrada K, Luan J, Kutalik Z, Amin N, Buchkovich ML, Croteau-Chonka DC, Day FR, Duan Y, Fall T, Fehrmann R, Ferreira T, Jackson AU, Karjalainen J, Lo KS, Locke AE, Mägi R, Mihailov E, Porcu E, Randall JC, Scherag A, Vinkhuyzen AA, Westra HJ, Winkler TW, Workalemahu T, Zhao JH, Absher D, Albrecht E, Anderson D, Baron J, Beekman M, Demirkan A, Ehret GB, Feenstra B, Feitosa MF, Fischer K, Fraser RM, Goel A, Gong J, Justice AE, Kanoni S, Kleber ME, Kristiansson K, Lim U, Lotay V, Lui JC, Mangino M, Mateo Leach I, Medina-Gomez C, Nalls MA, Nyholt DR, Palmer CD, Pasko D, Pechlivanis S, Prokopenko I, Ried JS, Ripke S, Shungin D, Stancáková A, Strawbridge RJ, Sung YJ, Tanaka T, Teumer A, Trompet S, van der Laan SW, van Setten J, Van Vliet-Ostaptchouk JV, Wang Z, Yengo L, Zhang W, Afzal U, Arnlöv J, Arscott GM, Bandinelli S, Barrett A, Bellis C, Bennett AJ, Berne C, Blüher M, Bolton JL, Böttcher Y, Boyd HA, Bruinenberg M, Buckley BM, Buyske S, Caspersen IH, Chines PS, Clarke R, Claudi-Boehm S, Cooper M, Daw EW, De Jong PA, Deelen J, Delgado G, Denny JC, Dhonukshe-Rutten R, Dimitriou M, Doney AS, Dörr M, Eklund N, Eury E, Folkersen L, Garcia ME, Geller F, Giedraitis V, Go AS, Grallert H, Grammer TB, Gräßler J, Grönberg H, de Groot LC, Groves CJ, Haessler J, Hall P, Haller T, Hallmans G, Hannemann A, Hartman CA, Hassinen M, Hayward C, Heard-Costa NL, Helmer Q, Hemani G, Henders AK, Hillege HL, Hlatky MA, Hoffmann W, Hoffmann P, Holmen O, Houwing-Duistermaat JJ, Illig T, Isaacs A, James AL, Jeff J, Johansen B, Johansson Å, Jolley J, Juliusdottir T, Junttila J, Kho AN, Kinnunen L, Klopp N, Kocher T, Kratzer W, Lichtner P, Lind L, Lindström J, Lobbens S, Lorentzon M, Lu Y, Lyssenko V, Magnusson PK, Mahajan A, Maillard M, McArdle WL, McKenzie CA, McLachlan S, McLaren PJ, Menni C, Merger S, Milani L, Moayyeri A, Monda KL, Morken MA, Müller G, Müller-Nurasyid M, Musk AW, Narisu N, Nauck M, Nolte IM, Nöthen MM, Oozageer L, Pilz S, Rayner NW, Renstrom F, Robertson NR, Rose LM, Roussel R, Sanna S, Scharnagl H, Scholtens S, Schumacher FR, Schunkert H, Scott RA, Sehmi J, Seufferlein T, Shi J, Silventoinen K, Smit JH, Smith AV, Smolonska J, Stanton AV, Stirrups K, Stott DJ, Stringham HM, Sundström J, Swertz MA, Syvänen AC, Tayo BO, Thorleifsson G, Tyrer JP, van Dijk S, van Schoor NM, van der Velde N, van Heemst D, van Oort FV, Vermeulen SH, Verweij N, Vonk JM, Waite LL, Waldenberger M, Wennauer R, Wilkens LR, Willenborg C, Wilsgaard T, Wojczynski MK, Wong A, Wright AF, Zhang Q, Arveiler D, Bakker SJ, Beilby J, Bergman RN, Bergmann S, Biffar R, Blangero J, Boomsma DI, Bornstein SR, Bovet P, Brambilla P, Brown MJ, Campbell H, Caulfield MJ, Chakravarti A, Collins R, Collins FS, Crawford DC, Cupples LA, Danesh J, de Faire U, den Ruijter HM, Erbel R, Erdmann J, Eriksson JG, Farrall M, Ferrannini E, Ferrières J, Ford I, Forouhi NG, Forrester T, Gansevoort RT, Gejman PV, Gieger C, Golay A, Gottesman O, Gudnason V, Gyllensten U, Haas DW, Hall AS, Harris TB, Hattersley AT, Heath AC, Hengstenberg C, Hicks AA, Hindorff LA, Hingorani AD, Hofman A, Hovingh GK, Humphries SE, Hunt SC, Hypponen E, Jacobs KB, Jarvelin MR, Jousilahti P, Jula AM, Kaprio J, Kastelein JJ, Kayser M, Kee F, Keinanen-Kiukaanniemi SM, Kiemeney LA, Kooner JS, Kooperberg C, Koskinen S, Kovacs P, Kraja AT, Kumari M, Kuusisto J, Lakka TA, Langenberg C, Le Marchand L, Lehtimäki T, Lupoli S, Madden PA, Männistö S, Manunta P, Marette A, Matise TC, McKnight B, Meitinger T, Moll FL, Montgomery GW, Morris AD, Morris AP, Murray JC, Nelis M, Ohlsson C, Oldehinkel AJ, Ong KK, Ouwehand WH, Pasterkamp G, Peters A, Pramstaller PP, Price JF, Qi L, Raitakari OT, Rankinen T, Rao DC, Rice TK, Ritchie M, Rudan I, Salomaa V, Samani NJ, Saramies J, Sarzynski MA, Schwarz PE, Sebert S, Sever P, Shuldiner AR, Sinisalo J, Steinthorsdottir V, Stolk RP, Tardif JC, Tönjes A, Tremblay A, Tremoli E, Virtamo J, Vohl MC, Electronic Medical Records and Genomics (eMEMERGEGE) Consortium, MIGen Consortium, PAGEGE Consortium, LifeLines Cohort Study, Amouyel P, Asselbergs FW, Assimes TL, Bochud M, Boehm BO, Boerwinkle E, Bottinger EP, Bouchard C, Cauchi S, Chambers JC, Chanock SJ, Cooper RS, de Bakker PI, Dedoussis G, Ferrucci L, Franks PW, Froguel P, Groop LC, Haiman CA, Hamsten A, Hayes MG, Hui J, Hunter DJ, Hveem K, Jukema JW, Kaplan RC, Kivimaki M, Kuh D, Laakso M, Liu Y, Martin NG, März W, Melbye M, Moebus S, Munroe PB, Njølstad I, Oostra BA, Palmer CN, Pedersen NL, Perola M, Pérusse L, Peters U, Powell JE, Power C, Quertermous T, Rauramaa R, Reinmaa E, Ridker PM, Rivadeneira F, Rotter JI, Saaristo TE, Saleheen D, Schlessinger D, Slagboom PE, Snieder H, Spector TD, Strauch K, Stumvoll M, Tuomilehto J, Uusitupa M, van der Harst P, Völzke H, Walker M, Wareham NJ, Watkins H, Wichmann HE, Wilson JF, Zanen P, Deloukas P, Heid IM, Lindgren CM, Mohlke KL, Speliotes EK, Thorsteinsdottir U, Barroso I, Fox CS, North KE, Strachan DP, Beckmann JS, Berndt SI, Boehnke M, Borecki IB, McCarthy MI, Metspalu A, Stefansson K, Uitterlinden AG, van Duijn CM, Franke L, Willer CJ, Price AL, Lettre G, Loos RJ, Weedon MN, Ingelsson E, O'Connell JR, Abecasis GR, Chasman DI, Goddard ME, Visscher PM, Hirschhorn JN, Frayling TM
(2014) Nat Genet 46: 1173-86
MeSH Terms: Adult, Analysis of Variance, Body Height, European Continental Ancestry Group, Genetic Variation, Genetics, Population, Genome-Wide Association Study, Humans, Oligonucleotide Array Sequence Analysis, Polymorphism, Single Nucleotide
Show Abstract · Added March 13, 2015
Using genome-wide data from 253,288 individuals, we identified 697 variants at genome-wide significance that together explained one-fifth of the heritability for adult height. By testing different numbers of variants in independent studies, we show that the most strongly associated ∼2,000, ∼3,700 and ∼9,500 SNPs explained ∼21%, ∼24% and ∼29% of phenotypic variance. Furthermore, all common variants together captured 60% of heritability. The 697 variants clustered in 423 loci were enriched for genes, pathways and tissue types known to be involved in growth and together implicated genes and pathways not highlighted in earlier efforts, such as signaling by fibroblast growth factors, WNT/β-catenin and chondroitin sulfate-related genes. We identified several genes and pathways not previously connected with human skeletal growth, including mTOR, osteoglycin and binding of hyaluronic acid. Our results indicate a genetic architecture for human height that is characterized by a very large but finite number (thousands) of causal variants.
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10 MeSH Terms
Factors associated with growth and blood pressure patterns in children with sickle cell anemia: Silent Cerebral Infarct Multi-Center Clinical Trial cohort.
Wolf RB, Saville BR, Roberts DO, Fissell RB, Kassim AA, Airewele G, DeBaun MR
(2015) Am J Hematol 90: 2-7
MeSH Terms: Adolescent, Anemia, Sickle Cell, Anthropometry, Blood Pressure, Body Height, Body Weight, Child, Child, Preschool, Hemoglobins, Humans, Multicenter Studies as Topic, Randomized Controlled Trials as Topic, Severity of Illness Index
Show Abstract · Added October 7, 2014
Individuals with sickle cell anemia (SCA) exhibit delayed growth trajectories and lower blood pressure (BP) measurements than individuals without SCA. We evaluated factors associated with height, weight, and BP and established reference growth curves and BP tables using data from the Silent Cerebral Infarct Multi-Center Clinical (SIT) Trial (NCT00072761). Quantile regression models were used to determine the percentiles of growth and BP measurements. Multivariable quantile regression was used to test associations of baseline variables with height, weight, and BP measurements. Height and weight measurements were collected from a total of 949 participants with median age of 10.5 years [Interquartile range (IQR) 8.2-12.9] and median follow-up time of 3.2 years (IQR 1.8-4.7, range 0-12.9). Serial BP measurements were collected from a total of 944 and 943 participants, respectively, with median age of 10.6 years (IQR = 8.3-12.9 years), and median follow-up time of 3.3 years (IQR = 1.7-4.8). Multivariable quantile regression analysis revealed that higher hemoglobin measurements at baseline were associated with greater height (P < 0.001), weight (P = 0.000), systolic BP (P < 0.001), and diastolic BP (P = 0.003) measurements. We now provide new reference values for height, weight, and BP measurements that are now readily available for medical management.
© 2014 Wiley Periodicals, Inc.
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13 MeSH Terms