Other entities represented in this entry:
Cytogenetic location: 6q24-q25 Genomic coordinates (GRCh38) : 6:138,300,001-160,600,000
| Location | Phenotype |
Phenotype MIM number |
Inheritance |
Phenotype mapping key |
|---|---|---|---|---|
| 6q24-q25 | {Stature QTL 1} | 606255 | 2 |
Stature (adult height) is an example of a complex genetic trait involving multiple genetic loci. Although complex traits are often difficult to study by linkage analysis, Hirschhorn et al. (2001) suggested that stature is a suitable complex trait for study because of the high heritability and the relatively limited contribution of environmental factors. Thus, linkage analysis has been used to identify quantitative trait loci for stature (STQTL) including STQTL1 on chromosome 6q24, STQTL2 (606256) on chromosome 7q31-q36, STQTL3 (606257) on chromosome 12p11-q14, STQTL4 (606258) on chromosome 13q32-q33, STQTL5 (608982) on chromosome 3p26, STQTL6 (300591) on chromosome Xq24, STQTL7 (609822) on chromosome 1p21, STQTL8 (610114) on chromosome 9q22, STQTL9 (611547) on chromosome 12q14.3, STQTL10 (612221) on chromosome 3q23, STQTL11 (612223) on chromosome 7q21-q22, STQTL12 (612224) on chromosome 4q28-q32, STQTL13 (612226) on chromosome 4p13.3, STQTL14 (612228) on chromosome 20q11.22, STQTL15 (612578) on chromosome 8q21.13, STQTL16 (612579) on chromosome 15q22.31, STQTL17 (612737) on chromosome 7p15, STQTL18 (612892) on chromosome 6p22.1, STQTL19 (612893) on chromosome 6p21.31, STQTL20 (612894) on chromosome 13q14.3, STQTL21 (613440) on chromosome 2q37.1, STQTL22 (613547) on chromosome 16q24, STQTL23 (613548) on chromosome 1p32, and STQTL24 (613549) on chromosome 2p16.
See also X-linked short stature (300582) associated with mutations in the SHOX gene (312865).
Associations Pending Confirmation
For discussion of a possible association between short stature and variation in the CYP26C1 gene, see 608428.
The genetics of stature has been studied at least since 1903, when measurements of height in families suggested a high heritability (Pearson and Lee, 1903). The studies also demonstrated that adult height follows a normal distribution, suggesting that multiple factors interact to affect stature, perhaps in an additive fashion. Estimates of heritability range from 76 to 90%.
Yang et al. (2010) estimated the proportion of variance for human height explained by 294,831 SNPs genotyped on 3,925 unrelated individuals using a linear model analysis, and validated the estimation method with simulations based on the observed genotype data. They showed that 45% of variance could be explained by considering all SNPs simultaneously. Thus, most of the heritability was not missing but had not previously been detected because the individual effects were too small to pass stringent significance tests. Yang et al. (2010) provided evidence that the remaining heritability is due to incomplete linkage disequilibrium between causal variants and genotyped SNPs, exacerbated by causal variants having lower minor allele frequency than the SNPs explored to that time.
Stature Quantitative Trait Locus 1 (STQTL1)
Hirschhorn et al. (2001) reanalyzed genomewide scans from 4 populations: the Botnia region of Finland, other parts of Finland, southern Sweden, and a region of Quebec. The 6q24-q25 region showed significant evidence for linkage to stature in the Botnian population (maximum lod = 3.85 at D6S1007, genomewide p less than 0.06).
Xu et al. (2002) performed segregation and linkage analyses for adult height in a population of 200 Dutch families, each of which was ascertained through a proband with asthma. The best-fit model from the segregation analysis was a major recessive gene with a significant residual polygenic background. A genomewide scan confirmed previous linkage results for 6q25 (lod = 3.06 at D6S2436), 9p1 (lod = 2.09 at D9S301), and 12q1 (lod = 1.86 at D12S375).
In 513 sib pairs from 174 Dutch families for whom complete genome scans and adult height data were available, Willemsen et al. (2004) found the strongest evidence for linkage on chromosome 6, near markers D6S1053 and D6S1031 (lod = 2.32).
In a metaanalysis of genomewide association study data of height for 15,821 individuals at 2.2 million SNPs, in which the strongest findings were followed up in greater than 10,000 subjects, Lettre et al. (2008) found association of a SNP, rs4896582, in the GPR126 gene (612243) on chromosome 6q24.1, with adult stature (combined p = 2.4 x 10(-18)). Independently, in a genomewide association study of height involving approximately 34,000 individuals in the discovery phase and followed by typing of the 40 most significant SNPs in a further 5,517 individuals, Gudbjartsson et al. (2008) found association with a SNP in the GPR126 gene, rs3748069 (combined p = 4.5 x 10(-14)).
To identify loci associated with stature, Soranzo et al. (2009) performed a genomewide scan of 12,611 participants followed by replication in an additional 7,187 individuals. They confirmed linkage of the GPR126 gene region, finding strong association with rs12189801 (combined p = 1.2 x 10(-10)) and rs6570507 (combined p = 4.4 x 10(-11)).
Associations Pending Confirmation
Mukhopadhyay et al. (2003) attempted to map loci influencing normal adult height in 335 families from the Framingham (Massachusetts) Heart Study. They observed a peak on chromosome 9p21 near D9S319 with a maximum lod score of 1.65 when only male height phenotypes were used. When only female phenotypes were used, a peak with a maximum lod score of 1.85 was observed on chromosome 11q25-qter near D11S2359. The region of interest on chromosome 9 had been implicated by 2 previous studies (Hirschhorn et al., 2001; Xu et al., 2002).
Population Stratification
Campbell et al. (2005) studied a European American panel discordant for height, a heritable trait that varies widely across Europe. Genotyping 178 SNPs and applying standard analytical methods yielded no evidence of stratification. However, they found that the -13910C-T polymorphism in the MCM6 gene (601806.0001) (which they designated LCT -13910C-T) was strongly associated with height (p less than 10(-6)). The T allele was strongly associated with tall stature. However, this apparent association was largely or completely due to stratification; rematching individuals on the basis of European ancestry greatly reduced the apparent association, and no association was observed in Polish or Scandinavian individuals. Campbell et al. (2005) concluded that the failure of standard methods to detect this stratification indicates that new methods may be required.
Associations Pending Confirmation
Chaves et al. (2004) analyzed the influence of SNPs in components of the renin-angiotensin system (RAS) on height in 370 (194 women) healthy normotensive Caucasian subjects aged 25 to 50 years who were selected from the general population. They found that a 573C-T polymorphism of the AGTR1 gene (106165) on chromosome 3q21-q25 and the I/D polymorphism of the ACE gene (106180.0001) on chromosome 17q23 were associated with final height in women, but not men. These genetic variants showed a clear gene dosage, independent, and additive effect on height.
To identify specific genes underlying human stature, Lei et al. (2009) performed genomewide association study in 1,000 unrelated homogeneous Caucasian subjects using a microarray. Seven contiguous markers in the region of the SBF2 gene (607697) on chromosome 11p15 were associated with stature. Three SNPs in the filamin B gene (FLNB; 603381) on chromosome 3p14 were also associated with stature. In independent replication studies, rs10734652 in SBF2 was significantly (p = 0.036) and suggestively (p = 0.07) associated with stature in Caucasian families and 1,306 unrelated Caucasian subjects, respectively, and rs9834312 in FLNB was also associated with stature in 2 such independent Caucasian populations (p = 0.008 in unrelated sample and p = 0.049 in family sample). Additional significant replication association signals were detected between rs9834312 and stature in 619 unrelated northern Chinese subjects (p = 0.017), as well as between rs10734652 and stature in 2,953 unrelated southern Chinese subjects (p = 0.048).
Estrada et al. (2009) performed a genomewide association study (GWAS) of body height using 2.2 million markers in 10,074 individuals from 3 Dutch and 1 German population-based cohorts. Upon genotyping the 12 most significantly height-associated single-nucleotide polymorphisms (SNPs) in 6,912 additional individuals of Dutch and Swedish origin, Estrada et al. (2009) found that a single-nucleotide polymorphism (SNP), rs10472828, located on 5p14 showed suggestive evidence for association with height in the combined data set (combined p = 2.1 x 10(-7)). The SNP rs10472828 is located only 100 kb upstream of the natriuretic peptide receptor-3 gene (NPR3; 108962), which encodes a receptor for NPPC (600296), a candidate for influencing height variation linked to chromosome 2q37 (STQTL21; 613440).
Tonjes et al. (2009) performed a genomewide association study of adult height in 929 individuals from the self-contained Sorbian population of eastern Germany. Metaanalysis of the strongest SNPs in the Sorbian sample combined with 2 independent European cohorts identified a significant association between adult height and 2 variants, rs1569019 (p = 1.02 x 10(-6)) and rs1976930 (p = 3.37 x 10(-7)), in the GPR133 gene (613639) that are in linkage disequilibrium. The 2 SNPs were also associated with height in the 2 independent European cohorts individually. Replication of the findings in 2 non-Sorbian German cohorts for rs1569019 showed significant effects on height in the Leipzig cohort in men and women and in 577 men of the Berlin cohort, though not in 1,151 women. The combined analysis of all 5 cohorts, which consisted of 6,687 individuals, resulted in an effect size of 0.949 cm (p = 4.7 x 10(-8)). Tonjes et al. (2009) proposed GPR133 to be a novel gene associated with adult height.
Widen et al. (2010) performed a genomewide scan for genes influencing pubertal height growth in 5,038 Finnish individuals and identified strong association between variants near the LIN28B gene (611044) on chromosome 6q21 and pubertal growth (female p = 4 x 10(-9), male p = 1.5 x 10(-4), and combined p - 5 x 10(-11) for the 5-prime LIN28B SNP rs7759938). Noting that correlated SNPs have been associated with age at menarche (see MENAQ2, 612882), Widen et al. (2010) performed multiple regression analysis, which suggested that the timing of pubertal growth and age of menarche may be mediated through a common underlying mechanism. In addition, because a partially correlated intronic LIN28B SNP, rs314277, was previously associated with final height (Lettre et al., 2008), Widen et al. (2010) tested both rs7759938 and rs314277 for independent effects on postnatal growth in 8,903 individuals. They found that the pubertal timing-associated marker rs7759938 affected prepubertal growth in females (p = 7 x 10(-5)) and final height in males (p = 5 x 10(-4)), whereas rs314277 had sex-specific effects on growth (p for interaction = 0.005) that were distinct from those observed at rs7759938. Widen et al. (2010) concluded that partially correlated variants in the LIN28B region tag distinctive, complex, and sex-specific height- and growth-regulating effects, influencing the entire period of postnatal growth, thus implying a critical role for LIN28B in the regulation of human growth.
Lango Allen et al. (2010) used 183,727 individuals to demonstrate that hundreds of genetic variants, in at least 180 loci, influence adult height. The large number of loci revealed patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci were not random, but instead were enriched for genes that are connected in biologic pathways (p = 0.016) and that underlie skeletal growth defects (p less than 0.001). Second, the likely causal gene was often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci had multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants, and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants were enriched for likely functional effects on genes, being overrepresented among variants that alter amino acid structure of proteins and expression levels of nearby genes. Lango Allen et al. (2010) concluded that their data explained approximately 10% of the phenotypic variation in height, and they estimated that unidentified common variants of similar effect sizes would increase the figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation).
Okada et al. (2010) performed a genomewide association study (GWAS) for adult height in 19,633 Japanese subjects. Of 8 significantly associated loci, the association to the LHX3 (600577)-QSOX2 (612860) locus was entirely novel (rs12338076, p = 2.2 x 10(-8)). Association to the IGF1 (147440) locus was also established; conditional analysis of this locus with the most significantly associated SNP suggested the existence of an additional independent association with height to this locus. There were large differences in IGF1 allele frequencies between Japanese and Caucasian populations, thereby suggesting weak statistical powers for the IGF1 locus in previous Caucasian GWASs for height. The combination of the height-associated loci identified in the study of Okada et al. (2010) and previous GWAS demonstrated an effect size of 1.26 cm (95% confidence interval: 1.18-1.34) per 1.0 increase of the normalized Z score for height-increasing alleles, explaining 4.6% of the total variance of adult height.
Nelson et al. (2015) used a genetic approach to investigate the association between height and coronary artery disease (CAD), using 180 height-associated genetic variants. The authors tested the association between a change in genetically determined height of 1 SD (6.5 cm) with the risk of CAD in 65,066 cases and 128,383 controls. Using individual-level genotype data from 18,249 persons, they also examined the risk of CAD associated with the presence of various numbers of height-associated alleles. Nelson et al. (2015) observed a relative increase of 13.5% (95% CI, 5.4-22.1; p less than 0.001) in the risk of CAD per 1-SD decrease in genetically determined height. There was a graded relationship between the presence of an increased number of height-raising variants and a reduced risk of CAD (OR for height quartile 4 vs quartile 1, 0.74; 95% CI, 0.68-0.84; p less than 0.001). Of the 12 risk factors studied, significant associations were observed only with levels of low-density lipoprotein cholesterol and triglycerides (accounting for approximately 30% of the association). Nelson et al. (2015) identified several overlapping pathways involving genes associated with both development and atherosclerosis. Signaling pathways involving NKX2-5 (600584), STAT3 (102582), BMP (see 112264), growth hormone (see 139250), TGFB (190180), and IGF1 (147440) were implicated.
To test the association between 241,453 variants and adult height variation, Marouli et al. (2017) conducted single-variant metaanalyses in a discovery sample of 458,927 individuals, of whom 381,625 were of European ancestry, and validated the association results in an independent set of 252,501 participants. Marouli et al. (2017) reported 83 height-associated coding variants with lower minor allele frequencies (in the range of 0.1 to 4.8%) and effects of up to 2 centimeters per allele (such as those in IHH (600726), STC2 (603665), AR (313700), and CRISPLD2 (612434)), greater than 10 times the average effect of common variants. In functional follow-up studies, rare height-increasing alleles of STC2 giving an increase of 1 to 2 centimeters per allele compromised proteolytic inhibition of PAPPA (176385) and increased cleavage of IGFBP4 (146733) in vitro, resulting in higher bioavailability of insulin-like growth factors. These 83 height-associated variants overlapped genes that are mutated in monogenic growth disorders and highlighted novel biological candidates, such as ADAMTS3 (605011), IL11RA (600939), and NOX4 (605261), and pathways, such as proteoglycan and glycosaminoglycan synthesis, involved in growth.
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