Common DNA variants predict tall stature in Europeans

Genomic prediction of the extreme forms of adult body height or stature is of practical relevance in several areas such as pediatric endocrinology and forensic investigations. Here, we examine 770 extremely tall cases and 9,591 normal height controls in a population-based Dutch European sample to ev...

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Vydáno v:	Human genetics Ročník 133; číslo 5; s. 587 - 597
Hlavní autoři:	Liu, Fan, Hendriks, A. Emile J., Ralf, Arwin, Boot, Annemieke M., Benyi, Emelie, Sävendahl, Lars, Oostra, Ben A., van Duijn, Cornelia, Hofman, Albert, Rivadeneira, Fernando, Uitterlinden, André G., Drop, Stenvert L. S., Kayser, Manfred
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Berlin/Heidelberg Springer Berlin Heidelberg 01.05.2014 Springer Springer Nature B.V
Témata:	Analysis Anthropocentrism Biomedical and Life Sciences Biomedicine Body Height - genetics Cell cycle Chromosomes Cohort Studies Criminal investigation DNA DNA - genetics Endocrinology European Continental Ancestry Group Female Gene Function Gene loci Genetic polymorphisms Genome-Wide Association Study Genomes Genomics Height Human Genetics Humans Male Metabolic Diseases Molecular Medicine Netherlands Original Investigation Pediatrics Polymorphism, Single Nucleotide Netherlands Tall Individual Allelic Heterogeneity Genomic Prediction Tall Stature Genomic Prediction Accuracy
ISSN:	0340-6717, 1432-1203, 1432-1203
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Abstract	Genomic prediction of the extreme forms of adult body height or stature is of practical relevance in several areas such as pediatric endocrinology and forensic investigations. Here, we examine 770 extremely tall cases and 9,591 normal height controls in a population-based Dutch European sample to evaluate the capability of known height-associated DNA variants in predicting tall stature. Among the 180 normal height-associated single nucleotide polymorphisms (SNPs) previously reported by the Genetic Investigation of ANthropocentric Traits (GIANT) genome-wide association study on normal stature, in our data 166 (92.2 %) showed directionally consistent effects and 75 (41.7 %) showed nominally significant association with tall stature, indicating that the 180 GIANT SNPs are informative for tall stature in our Dutch sample. A prediction analysis based on the weighted allele sums method demonstrated a substantially improved potential for predicting tall stature (AUC = 0.75; 95 % CI 0.72–0.79) compared to a previous attempt using 54 height-associated SNPs (AUC = 0.65). The achieved accuracy is approaching practical relevance such as in pediatrics and forensics. Furthermore, a reanalysis of all SNPs at the 180 GIANT loci in our data identified novel secondary association signals for extreme tall stature at TGFB2 ( P = 1.8 × 10 −13 ) and PCSK5 ( P = 7.8 × 10 −11 ) suggesting the existence of allelic heterogeneity and underlining the importance of fine analysis of already discovered loci. Extrapolating from our results suggests that the genomic prediction of at least the extreme forms of common complex traits in humans including common diseases are likely to be informative if large numbers of trait-associated common DNA variants are available.
AbstractList	Genomic prediction of the extreme forms of adult body height or stature is of practical relevance in several areas such as pediatric endocrinology and forensic investigations. Here, we examine 770 extremely tall cases and 9,591 normal height controls in a population-based Dutch European sample to evaluate the capability of known height-associated DNA variants in predicting tall stature. Among the 180 normal height-associated single nucleotide polymorphisms (SNPs) previously reported by the Genetic Investigation of ANthropocentric Traits (GIANT) genome-wide association study on normal stature, in our data 166 (92.2 %) showed directionally consistent effects and 75 (41.7 %) showed nominally significant association with tall stature, indicating that the 180 GIANT SNPs are informative for tall stature in our Dutch sample. A prediction analysis based on the weighted allele sums method demonstrated a substantially improved potential for predicting tall stature (AUC = 0.75; 95 % CI 0.72-0.79) compared to a previous attempt using 54 height-associated SNPs (AUC = 0.65). The achieved accuracy is approaching practical relevance such as in pediatrics and forensics. Furthermore, a reanalysis of all SNPs at the 180 GIANT loci in our data identified novel secondary association signals for extreme tall stature at TGFB2 (P = 1.8 × 10^sup -13^) and PCSK5 (P = 7.8 × 10^sup -11^) suggesting the existence of allelic heterogeneity and underlining the importance of fine analysis of already discovered loci. Extrapolating from our results suggests that the genomic prediction of at least the extreme forms of common complex traits in humans including common diseases are likely to be informative if large numbers of trait-associated common DNA variants are available.[PUBLICATION ABSTRACT] Genomic prediction of the extreme forms of adult body height or stature is of practical relevance in several areas such as pediatric endocrinology and forensic investigations. Here, we examine 770 extremely tall cases and 9,591 normal height controls in a population-based Dutch European sample to evaluate the capability of known height-associated DNA variants in predicting tall stature. Among the 180 normal height-associated single nucleotide polymorphisms (SNPs) previously reported by the Genetic Investigation of ANthropocentric Traits (GIANT) genome-wide association study on normal stature, in our data 166 (92.2 %) showed directionally consistent effects and 75 (41.7 %) showed nominally significant association with tall stature, indicating that the 180 GIANT SNPs are informative for tall stature in our Dutch sample. A prediction analysis based on the weighted allele sums method demonstrated a substantially improved potential for predicting tall stature (AUC = 0.75; 95 % CI 0.72-0.79) compared to a previous attempt using 54 height-associated SNPs (AUC = 0.65). The achieved accuracy is approaching practical relevance such as in pediatrics and forensics. Furthermore, a reanalysis of all SNPs at the 180 GIANT loci in our data identified novel secondary association signals for extreme tall stature at TGFB2 (P = 1.8 × 10(-13)) and PCSK5 (P = 7.8 × 10(-11)) suggesting the existence of allelic heterogeneity and underlining the importance of fine analysis of already discovered loci. Extrapolating from our results suggests that the genomic prediction of at least the extreme forms of common complex traits in humans including common diseases are likely to be informative if large numbers of trait-associated common DNA variants are available. Genomic prediction of the extreme forms of adult body height or stature is of practical relevance in several areas such as pediatric endocrinology and forensic investigations. Here, we examine 770 extremely tall cases and 9,591 normal height controls in a population-based Dutch European sample to evaluate the capability of known height-associated DNA variants in predicting tall stature. Among the 180 normal height-associated single nucleotide polymorphisms (SNPs) previously reported by the Genetic Investigation of ANthropocentric Traits (GIANT) genome-wide association study on normal stature, in our data 166 (92.2 %) showed directionally consistent effects and 75 (41.7 %) showed nominally significant association with tall stature, indicating that the 180 GIANT SNPs are informative for tall stature in our Dutch sample. A prediction analysis based on the weighted allele sums method demonstrated a substantially improved potential for predicting tall stature (AUC = 0.75; 95 % CI 0.72-0.79) compared to a previous attempt using 54 height-associated SNPs (AUC = 0.65). The achieved accuracy is approaching practical relevance such as in pediatrics and forensics. Furthermore, a reanalysis of all SNPs at the 180 GIANT loci in our data identified novel secondary association signals for extreme tall stature at TGFB2 (P = 1.8 × 10(-13)) and PCSK5 (P = 7.8 × 10(-11)) suggesting the existence of allelic heterogeneity and underlining the importance of fine analysis of already discovered loci. Extrapolating from our results suggests that the genomic prediction of at least the extreme forms of common complex traits in humans including common diseases are likely to be informative if large numbers of trait-associated common DNA variants are available.Genomic prediction of the extreme forms of adult body height or stature is of practical relevance in several areas such as pediatric endocrinology and forensic investigations. Here, we examine 770 extremely tall cases and 9,591 normal height controls in a population-based Dutch European sample to evaluate the capability of known height-associated DNA variants in predicting tall stature. Among the 180 normal height-associated single nucleotide polymorphisms (SNPs) previously reported by the Genetic Investigation of ANthropocentric Traits (GIANT) genome-wide association study on normal stature, in our data 166 (92.2 %) showed directionally consistent effects and 75 (41.7 %) showed nominally significant association with tall stature, indicating that the 180 GIANT SNPs are informative for tall stature in our Dutch sample. A prediction analysis based on the weighted allele sums method demonstrated a substantially improved potential for predicting tall stature (AUC = 0.75; 95 % CI 0.72-0.79) compared to a previous attempt using 54 height-associated SNPs (AUC = 0.65). The achieved accuracy is approaching practical relevance such as in pediatrics and forensics. Furthermore, a reanalysis of all SNPs at the 180 GIANT loci in our data identified novel secondary association signals for extreme tall stature at TGFB2 (P = 1.8 × 10(-13)) and PCSK5 (P = 7.8 × 10(-11)) suggesting the existence of allelic heterogeneity and underlining the importance of fine analysis of already discovered loci. Extrapolating from our results suggests that the genomic prediction of at least the extreme forms of common complex traits in humans including common diseases are likely to be informative if large numbers of trait-associated common DNA variants are available. Genomic prediction of the extreme forms of adult body height or stature is of practical relevance in several areas such as pediatric endocrinology and forensic investigations. Here, we examine 770 extremely tall cases and 9,591 normal height controls in a population-based Dutch European sample to evaluate the capability of known height-associated DNA variants in predicting tall stature. among the 180 normal height-associated single nucleotide polymorphisms (SNPs) previously reported by the Genetic Investigation of ANthropocentric Traits (Giant) genome-wide association study on normal stature, in our data 166 (92.2 %) showed directionally consistent effects and 75 (41.7 %) showed nominally significant association with tall stature, indicating that the 180 GIANT SNPs are informative for tall stature in our Dutch sample. A prediction analysis based on the weighted allele sums method demonstrated a substantially improved potential for predicting tall stature (AUC = 0.75; 95 % CI 0.72-0.79) compared to a previous attempt using 54 height-associated SNPs (AUC = 0.65). The achieved accuracy is approaching practical relevance such as in pediatrics and forensics. Furthermore, a reanalysis of all SNPs at the 180 GIANT loci in our data identified novel secondary association signals for extreme tall stature at TGFB2 (P = 1.8 x [10.sup.-13]) and PCSK5 (P = 7.8 x [10.sup.-11]) suggesting the existence of allelic heterogeneity and underlining the importance of fine analysis of already discovered loci. Extrapolating from our results suggests that the genomic prediction of at least the extreme forms of common complex traits in humans including common diseases are likely to be informative if large numbers of trait-associated common DNA variants are available. Genomic prediction of the extreme forms of adult body height or stature is of practical relevance in several areas such as pediatric endocrinology and forensic investigations. Here, we examine 770 extremely tall cases and 9,591 normal height controls in a population-based Dutch European sample to evaluate the capability of known height-associated DNA variants in predicting tall stature. Among the 180 normal height-associated single nucleotide polymorphisms (SNPs) previously reported by the Genetic Investigation of ANthropocentric Traits (GIANT) genome-wide association study on normal stature, in our data 166 (92.2 %) showed directionally consistent effects and 75 (41.7 %) showed nominally significant association with tall stature, indicating that the 180 GIANT SNPs are informative for tall stature in our Dutch sample. A prediction analysis based on the weighted allele sums method demonstrated a substantially improved potential for predicting tall stature (AUC = 0.75; 95 % CI 0.72-0.79) compared to a previous attempt using 54 height-associated SNPs (AUC = 0.65). The achieved accuracy is approaching practical relevance such as in pediatrics and forensics. Furthermore, a reanalysis of all SNPs at the 180 GIANT loci in our data identified novel secondary association signals for extreme tall stature at TGFB2 (P = 1.8 x 10 super(-13)) and PCSK5 (P = 7.8 x 10 super(-11)) suggesting the existence of allelic heterogeneity and underlining the importance of fine analysis of already discovered loci. Extrapolating from our results suggests that the genomic prediction of at least the extreme forms of common complex traits in humans including common diseases are likely to be informative if large numbers of trait-associated common DNA variants are available. Genomic prediction of the extreme forms of adult body height or stature is of practical relevance in several areas such as pediatric endocrinology and forensic investigations. Here, we examine 770 extremely tall cases and 9,591 normal height controls in a population-based Dutch European sample to evaluate the capability of known height-associated DNA variants in predicting tall stature. Among the 180 normal height-associated single nucleotide polymorphisms (SNPs) previously reported by the Genetic Investigation of ANthropocentric Traits (GIANT) genome-wide association study on normal stature, in our data 166 (92.2 %) showed directionally consistent effects and 75 (41.7 %) showed nominally significant association with tall stature, indicating that the 180 GIANT SNPs are informative for tall stature in our Dutch sample. A prediction analysis based on the weighted allele sums method demonstrated a substantially improved potential for predicting tall stature (AUC = 0.75; 95 % CI 0.72–0.79) compared to a previous attempt using 54 height-associated SNPs (AUC = 0.65). The achieved accuracy is approaching practical relevance such as in pediatrics and forensics. Furthermore, a reanalysis of all SNPs at the 180 GIANT loci in our data identified novel secondary association signals for extreme tall stature at TGFB2 ( P = 1.8 × 10 −13 ) and PCSK5 ( P = 7.8 × 10 −11 ) suggesting the existence of allelic heterogeneity and underlining the importance of fine analysis of already discovered loci. Extrapolating from our results suggests that the genomic prediction of at least the extreme forms of common complex traits in humans including common diseases are likely to be informative if large numbers of trait-associated common DNA variants are available.
Audience	Academic
Author	Hofman, Albert Hendriks, A. Emile J. Oostra, Ben A. Benyi, Emelie Ralf, Arwin Liu, Fan van Duijn, Cornelia Uitterlinden, André G. Drop, Stenvert L. S. Sävendahl, Lars Rivadeneira, Fernando Kayser, Manfred Boot, Annemieke M.
Author_xml	– sequence: 1 givenname: Fan surname: Liu fullname: Liu, Fan organization: Department of Forensic Molecular Biology, Erasmus MC University Medical Center Rotterdam – sequence: 2 givenname: A. Emile J. surname: Hendriks fullname: Hendriks, A. Emile J. organization: Division of Endocrinology, Department of Pediatrics, Sophia Children’s Hospital, Erasmus MC University Medical Center Rotterdam – sequence: 3 givenname: Arwin surname: Ralf fullname: Ralf, Arwin organization: Department of Forensic Molecular Biology, Erasmus MC University Medical Center Rotterdam – sequence: 4 givenname: Annemieke M. surname: Boot fullname: Boot, Annemieke M. organization: Division of Endocrinology, Department of Pediatrics, University Medical Center Groningen – sequence: 5 givenname: Emelie surname: Benyi fullname: Benyi, Emelie organization: Department of Women’s and Children’s Health, Karolinska Institute – sequence: 6 givenname: Lars surname: Sävendahl fullname: Sävendahl, Lars organization: Department of Women’s and Children’s Health, Karolinska Institute – sequence: 7 givenname: Ben A. surname: Oostra fullname: Oostra, Ben A. organization: Department of Clinical Genetics, Erasmus MC University Medical Center Rotterdam – sequence: 8 givenname: Cornelia surname: van Duijn fullname: van Duijn, Cornelia organization: Department of Epidemiology, Erasmus MC University Medical Center Rotterdam – sequence: 9 givenname: Albert surname: Hofman fullname: Hofman, Albert organization: Department of Epidemiology, Erasmus MC University Medical Center Rotterdam – sequence: 10 givenname: Fernando surname: Rivadeneira fullname: Rivadeneira, Fernando organization: Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Department of Internal Medicine, Erasmus MC University Medical Center Rotterdam – sequence: 11 givenname: André G. surname: Uitterlinden fullname: Uitterlinden, André G. organization: Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Department of Internal Medicine, Erasmus MC University Medical Center Rotterdam – sequence: 12 givenname: Stenvert L. S. surname: Drop fullname: Drop, Stenvert L. S. organization: Division of Endocrinology, Department of Pediatrics, Sophia Children’s Hospital, Erasmus MC University Medical Center Rotterdam – sequence: 13 givenname: Manfred surname: Kayser fullname: Kayser, Manfred email: m.kayser@erasmusmc.nl organization: Department of Forensic Molecular Biology, Erasmus MC University Medical Center Rotterdam
BackLink	https://www.ncbi.nlm.nih.gov/pubmed/24253421$$D View this record in MEDLINE/PubMed http://kipublications.ki.se/Default.aspx?queryparsed=id:128745328$$DView record from Swedish Publication Index (Karolinska Institutet)
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SubjectTerms	Analysis Anthropocentrism Biomedical and Life Sciences Biomedicine Body Height - genetics Cell cycle Chromosomes Cohort Studies Criminal investigation DNA DNA - genetics Endocrinology European Continental Ancestry Group Female Gene Function Gene loci Genetic polymorphisms Genome-Wide Association Study Genomes Genomics Height Human Genetics Humans Male Metabolic Diseases Molecular Medicine Netherlands Original Investigation Pediatrics Polymorphism, Single Nucleotide
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Title	Common DNA variants predict tall stature in Europeans
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