rs10514804 (EPCAM-DT): Human Height Variant

Key takeaways

  • rs10514804 near EPCAM-DT is one of 12,111 common variants linked to adult height in a study of 5.4 million people.
  • Together these height variants explain about 40% of height differences in European-ancestry populations.
  • Genetic prediction of height is substantially less accurate in non-European populations.
  • Height-associated variants cluster in regions covering about 21% of the genome, pointing to specific biological pathways.

Key takeaways

  • rs10514804 near EPCAM-DT is one of 12,111 common variants linked to adult height in a study of 5.4 million people.
  • Together these height variants explain about 40% of height differences in European-ancestry populations.
  • Genetic prediction of height is substantially less accurate in non-European populations.
  • Height-associated variants cluster in regions covering about 21% of the genome, pointing to specific biological pathways.

What the research says rs10514804 lies near EPCAM-DT (the divergent transcript at the EPCAM gene locus), a genomic region flagged in a genome-wide association study (GWAS - a method that scans millions of genetic variants across many people to find those statistically linked to a trait) of adult human height using data from 5.4 million participants across 281 contributing studies. That study identified 12,111 independent single-nucleotide polymorphisms (SNPs - single-letter changes in the DNA code) associated with height, clustered in approximately 7,209 non-overlapping genomic segments covering about 21% of the genome. The full set of 12,111 variants accounts for nearly all common SNP-based heritability of height, explaining roughly 40% of height variance in European-ancestry populations and approximately 10-24% in other ancestry groups.

Reported associations

  • Adult human height: rs10514804 falls within a region implicated among 12,111 independent height-associated SNPs identified in a multi-ancestry GWAS of 5.4 million individuals; collectively these SNPs account for approximately 40% of height variance in European-ancestry populations and roughly 10-24% in populations of other ancestries.

Evidence quality The study contextualizing rs10514804 is among the largest genetic studies conducted for any human trait, with more than 5.4 million participants drawn from populations of European (approximately 76%), East Asian (approximately 9%), Hispanic admixed (approximately 8.5%), African (approximately 5.5%), and South Asian (approximately 1.4%) ancestry. The 12,111 SNPs identified are described as representing a near-complete map of common height-associated variation for European-ancestry populations, capturing nearly all of the estimated 40-50% common-SNP heritability of height. Prediction accuracy is substantially lower in non-European populations - the authors attribute this to differences in linkage disequilibrium (the tendency for nearby DNA variants to be inherited together) and allele frequencies across populations rather than fundamentally different underlying biology. The source study metadata did not include a PMID, so inline citation links cannot be provided for this entry.

Lifestyle considerations No lifestyle considerations on file for this variant.

Frequently asked questions

What is EPCAM-DT?

EPCAM-DT refers to a divergent transcript at the EPCAM gene locus. rs10514804 is a common genetic variant located in this genomic region, flagged in a large study of the genetics of human height.

Is rs10514804 linked to height?

This variant falls in a region implicated in a large genome-wide study of adult height involving more than 5.4 million participants. The study identified 12,111 height-associated variants overall, and this locus was among those flagged.

How much of height does genetics explain?

The 12,111 common variants identified in this study account for about 40% of height variation in people of European ancestry, and roughly 10-24% in people from other ancestry groups. Common variants are estimated to explain 40-50% of height heritability in total.

What is a genome-wide association study (GWAS)?

A GWAS scans millions of genetic variants across the entire genome in large numbers of people to find which variants are statistically associated with a trait such as height. The study contextualizing rs10514804 is one of the largest GWASs ever conducted, covering 5.4 million individuals.

Why is height prediction less accurate in non-European populations?

The study suggests this is likely due to differences in linkage disequilibrium - the tendency for nearby DNA variants to be inherited together - and differences in allele frequencies across populations, rather than different underlying biology driving height.