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Genomics of disease risk in globally diverse populations

An Author Correction to this article was published on 03 July 2019

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Abstract

Risk of disease is multifactorial and can be shaped by socio-economic, demographic, cultural, environmental and genetic factors. Our understanding of the genetic determinants of disease risk has greatly advanced with the advent of genome-wide association studies (GWAS), which detect associations between genetic variants and complex traits or diseases by comparing populations of cases and controls. However, much of this discovery has occurred through GWAS of individuals of European ancestry, with limited representation of other populations, including from Africa, The Americas, Asia and Oceania. Population demography, genetic drift and adaptation to environments over thousands of years have led globally to the diversification of populations. This global genomic diversity can provide new opportunities for discovery and translation into therapies, as well as a better understanding of population disease risk. Large-scale multi-ethnic and representative biobanks and population health resources provide unprecedented opportunities to understand the genetic determinants of disease on a global scale.

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Fig. 1: Representation of different ethnic groups in genome-wide association studies.
Fig. 2: Genetic drift and changes in allele frequency as a function of population size.
Fig. 3: Mechanisms for observed heterogeneity of effect size between populations.

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  • 03 July 2019

    An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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Acknowledgements

D.G. is funded by a UKRI HDR-UK Innovation Fellowship (reference number MR/S003711/1). I.B. acknowledges funding from Wellcome (WT206194). M.S. acknowledges funding from the Wellcome Sanger Institute (WT098051), the UK Medical Research Council (G0901213-92157, G0801566 and MR/K013491/1) and the National Institute for Health Research Cambridge Biomedical Research Centre.

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Nature Reviews Genetics thanks H. Hakonarson, T. Manolio and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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D.G. and M.S.S. researched the literature and wrote the manuscript. All authors substantially contributed to discussions of the content, and reviewed and/or edited the manuscript before submission.

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Correspondence to Manjinder S. Sandhu.

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Related links

China Kadoorie Biobank: http://www.ckbiobank.org/

East London Genes and Health Study: http://www.genesandhealth.org/

Finnish Biobanks: https://www.biopankki.fi/en/finnish-biobanks

gnomAD: https://gnomad.broadinstitute.org/

H3Africa: https://h3africa.org/

Million Veteran Program: https://www.research.va.gov/mvp

NIH All of Us: https://allofus.nih.gov/

Qatar Genomes Project: https://qatargenome.org.qa/

TOPMed Programme: https://www.nhlbi.nih.gov/science/trans-omics-precision-medicine-topmed-program

Web PopGen simulator: https://www.radford.edu/~rsheehy/Gen_flash/popgen

Glossary

Genome-wide association studies

Hypothesis-free studies of association between genetic variants and quantitative traits or diseases; typically, associations are examined across the whole genome using genotype array or sequencing approaches.

Imputation

Statistical inference of unobserved genotypes in individuals based on a collection of observed haplotypes among another set of individuals (usually referred to as the reference panel).

Minor allele frequency

The frequency of the less common allele at a site of genetic variation across a sample of individuals or a population.

Genetic variance

The contribution of genetic variation among individuals to phenotypic variation.

Linkage disequilibrium

The non-random association of alleles at loci along the genome in a given population.

Heterogeneity of effect

Statistically significant differences in effect size observed for associations between genetic variants and traits or disease among different studies or populations.

Allelic heterogeneity

The phenomenon whereby multiple causal variants within a given gene can be associated with the same trait or disease.

Genetic drift

A process by which frequencies of alleles in a given population change over time due to random sampling of individuals who may reproduce at every generation.

Selection

A process in which environmental or genetic influences determine which types of organism thrive better than others. Regarded as a factor in evolution.

Population bottleneck

An event that drastically reduces the size of a population. Such events can greatly reduce the genetic diversity of a population and make the population more susceptible to the influence of genetic drift.

Non-reference alleles

An allele that is different from the allele in the human reference genome at a given position. The human reference genome is a curated human genome assembly that is based on existing knowledge about the human genome at a given time.

Adaptive selection

Evolutionary changes to the genome that occur due to selection and are adaptive to the given environment.

Fixation

The change in the genetic pool of a population from the presence of two alleles at a given locus to only one allele being present; this allele is said to be fixed.

Admixture

Interbreeding or mixing of two or more populations that were previously isolated.

Consanguinity

The state of being closely related to someone by sharing a recent ancestor; in genetics, commonly used to refer to mating with close relatives.

Endogamy

The practice of marrying only within the limits of a local community, clan or tribe.

Autozygosity

Stretches of the two homologous chromosomes within the same individual that are identical by descent; occurs when there is non-random mating.

Inbreeding coefficient

The probability that two alleles at a locus in an individual are identical by descent from a common ancestor, that is, the chance that an individual is homozygous for an ancestral allele by inheritance (not by mutation).

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Gurdasani, D., Barroso, I., Zeggini, E. et al. Genomics of disease risk in globally diverse populations. Nat Rev Genet 20, 520–535 (2019). https://doi.org/10.1038/s41576-019-0144-0

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