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Implementation of genome-wide complex trait analysis to quantify the heritability in multiple myeloma.

Mitchell JS, Johnson DC, Litchfield K, Broderick P, Weinhold N, Davies FE, Gregory WA, Jackson GH, Kaiser M, Morgan GJ, Houlston RS - Sci Rep (2015)

Bottom Line: Genome-wide association studies (GWAS) have successfully identified a number of common single-nucleotide polymorphisms (SNPs) influencing MM risk.We estimated that the heritability explained by known common MM risk SNPs identified in GWAS was 2.9% (± 2.4%), whereas the heritability explained by all common SNPs was 15.2% (± 2.8%).In summary, our results suggest that known MM SNPs only explain a small proportion of the heritability and more common SNPs remain to be identified.

View Article: PubMed Central - PubMed

Affiliation: Molecular and Population Genetics, Division of Genetics and Epidemiology, The Institute of Cancer Research, Surrey, UK.

ABSTRACT
A sizeable fraction of multiple myeloma (MM) is expected to be explained by heritable factors. Genome-wide association studies (GWAS) have successfully identified a number of common single-nucleotide polymorphisms (SNPs) influencing MM risk. While these SNPs only explain a small proportion of the genetic risk it is unclear how much is left to be detected by other, yet to be identified, common SNPs. Therefore, we applied Genome-Wide Complex Trait Analysis (GCTA) to 2,282 cases and 5,197 controls individuals to estimate the heritability of MM. We estimated that the heritability explained by known common MM risk SNPs identified in GWAS was 2.9% (± 2.4%), whereas the heritability explained by all common SNPs was 15.2% (± 2.8%). Comparing the heritability explained by the common variants with that from family studies, a fraction of the heritability may be explained by other genetic variants, such as rare variants. In summary, our results suggest that known MM SNPs only explain a small proportion of the heritability and more common SNPs remain to be identified.

No MeSH data available.


Related in: MedlinePlus

Variance explained by each chromosome as a function of chromosome length.
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f1: Variance explained by each chromosome as a function of chromosome length.

Mentions: To gain insight into the underlying basis of the heritability associated with common variation we investigated the relative contribution of individual chromosomes (Supplementary Table 1). In contrast to a trait such as height where there is a strong linear relationship between chromosome length and the variance explained by the chromosome10 we found no such relationship (R2 = 0.0063 from GCTA and R2 = 0.0016 from PCGC analysis) (Fig. 1).


Implementation of genome-wide complex trait analysis to quantify the heritability in multiple myeloma.

Mitchell JS, Johnson DC, Litchfield K, Broderick P, Weinhold N, Davies FE, Gregory WA, Jackson GH, Kaiser M, Morgan GJ, Houlston RS - Sci Rep (2015)

Variance explained by each chromosome as a function of chromosome length.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4513545&req=5

f1: Variance explained by each chromosome as a function of chromosome length.
Mentions: To gain insight into the underlying basis of the heritability associated with common variation we investigated the relative contribution of individual chromosomes (Supplementary Table 1). In contrast to a trait such as height where there is a strong linear relationship between chromosome length and the variance explained by the chromosome10 we found no such relationship (R2 = 0.0063 from GCTA and R2 = 0.0016 from PCGC analysis) (Fig. 1).

Bottom Line: Genome-wide association studies (GWAS) have successfully identified a number of common single-nucleotide polymorphisms (SNPs) influencing MM risk.We estimated that the heritability explained by known common MM risk SNPs identified in GWAS was 2.9% (± 2.4%), whereas the heritability explained by all common SNPs was 15.2% (± 2.8%).In summary, our results suggest that known MM SNPs only explain a small proportion of the heritability and more common SNPs remain to be identified.

View Article: PubMed Central - PubMed

Affiliation: Molecular and Population Genetics, Division of Genetics and Epidemiology, The Institute of Cancer Research, Surrey, UK.

ABSTRACT
A sizeable fraction of multiple myeloma (MM) is expected to be explained by heritable factors. Genome-wide association studies (GWAS) have successfully identified a number of common single-nucleotide polymorphisms (SNPs) influencing MM risk. While these SNPs only explain a small proportion of the genetic risk it is unclear how much is left to be detected by other, yet to be identified, common SNPs. Therefore, we applied Genome-Wide Complex Trait Analysis (GCTA) to 2,282 cases and 5,197 controls individuals to estimate the heritability of MM. We estimated that the heritability explained by known common MM risk SNPs identified in GWAS was 2.9% (± 2.4%), whereas the heritability explained by all common SNPs was 15.2% (± 2.8%). Comparing the heritability explained by the common variants with that from family studies, a fraction of the heritability may be explained by other genetic variants, such as rare variants. In summary, our results suggest that known MM SNPs only explain a small proportion of the heritability and more common SNPs remain to be identified.

No MeSH data available.


Related in: MedlinePlus