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Human genetic variation and its contribution to complex traits

Nature Reviews Genetics volume 10, pages 241251 (2009) | Download Citation

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Abstract

The last few years have seen extensive efforts to catalogue human genetic variation and correlate it with phenotypic differences. Most common SNPs have now been assessed in genome-wide studies for statistical associations with many complex traits, including many important common diseases. Although these studies have provided new biological insights, only a limited amount of the heritable component of any complex trait has been identified and it remains a challenge to elucidate the functional link between associated variants and phenotypic traits. Technological advances, such as the ability to detect rare and structural variants, and a clear understanding of the challenges in linking different types of variation with phenotype, will be essential for future progress.

Key points

  • Human genetic variants are typically referred to as either common or rare, to denote the frequency of the minor allele in the human population. Genetic variants can also be divided into two different nucleotide composition classes — single nucleotide variants and structural variants.

  • The alleles of SNPs located in the same genomic interval are often correlated with one another. This correlation structure, or linkage disequilibrium (LD), varies in a complex and unpredictable manner across the genome and between different populations.

  • Structural variants seem to behave similarly to SNPs in terms of both genomic and population distribution, indicating a similar evolutionary history: both types of variants are 'ancestral' having arisen once in human history and then shared among individuals by descent rather than being the result of recurrent mutations.

  • Full sequencing of human genomes has shown that in any given individual there are, on average, 4 million genetic variants encompassing 12 Mb of sequence. The challenge is to determine which of these variants underlie or are responsible for the inherited components of phenotypes.

  • Over the last decade or so the human genetics field has debated the common disease–common variant hypothesis, which posits that common complex traits are largely due to common variants with small-to-modest affect sizes. The opposing theory, the rare variant hypothesis, posits that common complex traits are the summation of low-frequency, high-penetrance variants.

  • Genome-wide association (GWA) studies are the most widely used contemporary approach to relate genetic variation to phenotypic diversity. Over the past 2 years these studies have identified statistical association between hundreds of loci across the genome and common complex traits.

  • Most of the genes or genomic loci that have been identified by GWA studies have not previously been known to be related to the complex trait under investigation. Surprisingly, there have been several instances in which one genomic interval has been associated with two or more seemingly distinct diseases.

  • An unforeseen limitation of GWA studies is that the genomic markers that are found to be associated with any given complex trait each have less impact on susceptibility than was anticipated. Most of the odds ratios for the heterozygote genotypes of the associated variants that have been identified so far are approximately 1.1, a figure that can increase to 1.5–1.6 for homozygote genotypes.

  • At this point, there are almost no complex traits for which more than 10% of the genetic variance is explained, and many are far below that threshold, leaving the bulk of heritability unexplained by the common variants identified so far.

  • One possibility is that the missing variation is accounted for by common genetic variants with small effect sizes that have not yet been identified. Some of the missing heritability is probably accounted for by rare and novel variants. Additionally, there are statistical limitations of the GWA approach in identifying gene–gene and gene–environment interactions, which are likely to be profoundly important.

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Acknowledgements

The authors are supported by a National Institutes of Health grant (NIH 1U54RR025204-01).

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  1. Scripps Genomic Medicine, Scripps Translational Science Institute and The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, California 92037, USA.

    • Kelly A. Frazer
    • , Sarah S. Murray
    • , Nicholas J. Schork
    •  & Eric J. Topol

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Glossary

Structural variants

Broadly defined, these are all variants that are not single nucleotide variants. They include insertion–deletions, block substitutions, inversions of DNA sequences and copy number differences.

Genome-wide association (GWA) study

An investigation of the association between common genetic variation and disease. This type of analysis requires a dense set of markers (for example, SNPs) that capture a substantial proportion of common variation across the genome, and large numbers of study subjects.

Complex traits

Continuously distributed phenotypes that are classically believed to result from the independent action of many genes, environmental factors and gene-by-environment interactions.

Minor allele

The less common allele of a polymorphism.

Linkage disequilibrium

(LD). In population genetics, LD is the nonrandom association of alleles. For example, alleles of SNPs that reside near one another on a chromosome often occur in nonrandom combinations owing to infrequent recombination.

Population stratification

Subdivision of a population into different ethnic groups with potentially different marker allele frequencies and different disease prevalences.

Odds ratio

A measurement of association that is commonly used in case–control studies. It is defined as the odds of exposure to the susceptible genetic variant in cases compared with that in controls. If the odds ratio is significantly greater than one, then the genetic variant is associated with the disease.

Epistasis

In statistical genetics, this term refers to an interaction of multiple genetic variants (usually at different loci) such that the net phenotypic effect of carrying more than one variant is different than would be predicted by simply combining the effects of each individual variant.

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