Key Points
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Infectious pathogens are among the strongest selective forces that shape the human genome. Migrations and cultural changes in the past 100,000 years exposed populations to dangerous new pathogens.
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Host genetics influences susceptibility to infectious disease. Evolutionary adaptations for resistance and symbiosis may underlie common immune-mediated diseases.
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Signatures of selection and methods to detect them vary with the age, geographical spread and virulence of the pathogen.
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A history of selection on a trait adds power to association studies by driving the emergence of common alleles of strong effect. Combining selection and association metrics can further increase power.
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Genome-wide association studies (GWASs) of susceptibility to pathogens that are moderately old (1,000–50,000 years ago), geographically limited in history and exerted strong positive selective pressure will have the most power if GWASs can be done in the historically affected population.
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An understanding of host–pathogen interactions can inform the development of new therapies for both infectious diseases and common immune-mediated diseases.
Abstract
The ancient biological 'arms race' between microbial pathogens and humans has shaped genetic variation in modern populations, and this has important implications for the growing field of medical genomics. As humans migrated throughout the world, populations encountered distinct pathogens, and natural selection increased the prevalence of alleles that are advantageous in the new ecosystems in both host and pathogens. This ancient history now influences human infectious disease susceptibility and microbiome homeostasis, and contributes to common diseases that show geographical disparities, such as autoimmune and metabolic disorders. Using new high-throughput technologies, analytical methods and expanding public data resources, the investigation of natural selection is leading to new insights into the function and dysfunction of human biology.
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References
Fumagalli, M. et al. Signatures of environmental genetic adaptation pinpoint pathogens as the main selective pressure through human evolution. PLoS Genet. 7, e1002355 (2011). This study of genetic variation in 50 worldwide populations reveals that pathogens are primary drivers of local adaptation.
Polgar, S. in Horizons of Anthropology (ed. Tax, S. ) (Aldine, 1964).
Armelagos, G. J., Barnes, K. C. & Lin, J. Disease in human evolution: the re-emergence of infectious disease in the third epidemiological transition. AnthroNotes 18, 1–7 (1996).
Bocquet-Appel, J. P. When the world's population took off: the springboard of the Neolithic demographic transition. Science 333, 560–561 (2011).
Vannberg, F. O., Chapman, S. J. & Hill, A. V. Human genetic susceptibility to intracellular pathogens. Immunol. Rev. 240, 105–116 (2011).
Chapman, S. J. & Hill, A. V. Human genetic susceptibility to infectious disease. Nature Rev. Genet. 13, 175–188 (2012).
Anderson, R. M. & May, R. M. Co-evolution of hosts and parasites. Parasitology 85, 411–426 (1982).
Cohen, M. L. Changing patterns of infectious disease. Nature 406, 762–767 (2000).
Cagliani, R. et al. Crohn's disease loci are common targets of protozoa-driven selection. Mol. Biol. Evol. 30, 1077–1087 (2013).
Okada, H., Kuhn, C., Feillet, H. & Bach, J. F. The 'hygiene hypothesis' for autoimmune and allergic diseases: an update. Clin. Exp. Immunol. 160, 1–9 (2010).
Jostins, L. et al. Host–microorganism interactions have shaped the genetic architecture of inflammatory bowel disease. Nature 491, 119–124 (2012). This paper presents selection for pathogen resistance in IBD.
Sironi, M. & Clerici, M. The hygiene hypothesis: an evolutionary perspective. Microbes. Infect. 12, 421–427 (2010).
Lin, A. et al. Distinct distal gut microbiome diversity and composition in healthy children from Bangladesh and the United States. PLoS ONE 8, e53838 (2013).
Honda, K. & Littman, D. R. The microbiome in infectious disease and inflammation. Annu. Rev. Immunol. 30, 759–795 (2012).
Segal, S. & Hill, A. V. Genetic susceptibility to infectious disease. Trends Microbiol. 11, 445–448 (2003).
Akey, J. M. Constructing genomic maps of positive selection in humans: where do we go from here? Genome Res. 19, 711–722 (2009).
Koboldt, D. C., Steinberg, K. M., Larson, D. E., Wilson, R. K. & Mardis, E. R. The next-generation sequencing revolution and its impact on genomics. Cell 155, 27–38 (2013).
Marx, V. Biology: the big challenges of big data. Nature 498, 255–260 (2013).
Hellmann, I., Ebersberger, I., Ptak, S. E., Paabo, S. & Przeworski, M. A neutral explanation for the correlation of diversity with recombination rates in humans. Am. J. Hum. Genet. 72, 1527–1535 (2003).
Albrechtsen, A., Nielsen, F. C. & Nielsen, R. Ascertainment biases in SNP chips affect measures of population divergence. Mol. Biol. Evol. 27, 2534–2547 (2010).
Jallow, M. et al. Genome-wide and fine-resolution association analysis of malaria in West Africa. Nature Genet. 41, 657–665 (2009).
Nielsen, R. Molecular signatures of natural selection. Annu. Rev. Genet. 39, 197–218 (2005).
Ronald, J. & Akey, J. M. Genome-wide scans for loci under selection in humans. Hum. Genom. 2, 113–125 (2005).
Bamshad, M. & Wooding, S. P. Signatures of natural selection in the human genome. Nature Rev. Genet. 4, 99–111 (2003).
Fu, W. & Akey, J. M. Selection and adaptation in the human genome. Annu. Rev. Genom. Hum. Genet. 14, 467–489 (2013).
Vitti, J. J., Grossman, S. R. & Sabeti, P. C. Detecting natural selection in genomic data. Annu. Rev. Genet. 47, 97–120 (2013).
Kwiatkowski, D. P. How malaria has affected the human genome and what human genetics can teach us about malaria. Am. J. Hum. Genet. 77, 171–192 (2005). This study shows that investigating targets of pathogen-driven selection leads to immunological discoveries and possible new therapies.
Sabeti, P. C. et al. Positive natural selection in the human lineage. Science 312, 1614–1620 (2006).
Deagle, B. E. et al. Population genomics of parallel phenotypic evolution in stickleback across stream–lake ecological transitions. Proc. Biol. Sci. 279, 1277–1286 (2012).
Sabeti, P. C. et al. Genome-wide detection and characterization of positive selection in human populations. Nature 449, 913–918 (2007).
Hernandez, R. D. et al. Classic selective sweeps were rare in recent human evolution. Science 331, 920–924 (2011).
Pritchard, J. K., Pickrell, J. K. & Coop, G. The genetics of human adaptation: hard sweeps, soft sweeps, and polygenic adaptation. Curr. Biol. 20, R208–R215 (2010).
Grossman, S. R. et al. Identifying recent adaptations in large-scale genomic data. Cell 152, 703–713 (2013).
Granka, J. M. et al. Limited evidence for classic selective sweeps in African populations. Genetics 192, 1049–1064 (2012).
Akey, J. M., Zhang, G., Zhang, K., Jin, L. & Shriver, M. D. Interrogating a high-density SNP map for signatures of natural selection. Genome Res. 12, 1805–1814 (2002).
Bustamante, C. D. et al. Natural selection on protein-coding genes in the human genome. Nature 437, 1153–1157 (2005).
Frazer, K. A. et al. A second generation human haplotype map of over 3.1 million SNPs. Nature 449, 851–861 (2007).
Pickrell, J. K. et al. Signals of recent positive selection in a worldwide sample of human populations. Genome Res. 19, 826–837 (2009).
Voight, B. F., Kudaravalli, S., Wen, X. & Pritchard, J. K. A map of recent positive selection in the human genome. PLoS Biol. 4, e72 (2006).
Williamson, S. H. et al. Localizing recent adaptive evolution in the human genome. PLoS Genet. 3, e90 (2007).
Barreiro, L. B., Laval, G., Quach, H., Patin, E. & Quintana-Murci, L. Natural selection has driven population differentiation in modern humans. Nature Genet. 40, 340–345 (2008).
Bhatia, G. et al. Genome-wide comparison of African-ancestry populations from CARe and other cohorts reveals signals of natural selection. Am. J. Hum. Genet. 89, 368–381 (2011).
Grossman, S. R. et al. A composite of multiple signals distinguishes causal variants in regions of positive selection. Science 327, 883–886 (2010).
McClelland, E. E., Penn, D. J. & Potts, W. K. Major histocompatibility complex heterozygote superiority during co-infection. Infect. Immun. 71, 2079–2086 (2003).
Aguilar, A. et al. High MHC diversity maintained by balancing selection in an otherwise genetically monomorphic mammal. Proc. Natl. Acad. Sci. USA 101, 3490–3494 (2004).
Prugnolle, F. et al. Pathogen-driven selection and worldwide HLA class I diversity. Curr. Biol. 15, 1022–1027 (2005).
de Bakker, P. I. & Raychaudhuri, S. Interrogating the major histocompatibility complex with high-throughput genomics. Hum. Mol. Genet. 21, R29–R36 (2012).
Hindorff, L. A. et al. Potential aetiologic and functional implications of genome-wide association loci for human diseases and traits. Proc. Natl Acad. Sci. USA 106, 9362–9367 (2009).
Pereyra, F. et al. The major genetic determinants of HIV-1 control affect HLA class I peptide presentation. Science 330, 1551–1557 (2010).
Fellay, J. et al. Common genetic variation and the control of HIV-1 in humans. PLoS Genet. 5, e1000791 (2009).
Limou, S. et al. Genomewide association study of an AIDS-nonprogression cohort emphasizes the role played by HLA genes (ANRS Genomewide Association Study 02). J. Infect. Dis. 199, 419–426 (2009).
Zhang, F. R. et al. Genomewide association study of leprosy. N. Engl. J. Med. 361, 2609–2618 (2009).
LeishGEN Consortium et al. Common variants in the HLA-DRB1–HLA-DQA1 HLA class II region are associated with susceptibility to visceral leishmaniasis. Nature Genet. 45, 208–213 (2013).
Kamatani, Y. et al. A genome-wide association study identifies variants in the HLA-DP locus associated with chronic hepatitis B in Asians. Nature Genet. 41, 591–595 (2009).
Mbarek, H. et al. A genome-wide association study of chronic hepatitis B identified novel risk locus in a Japanese population. Hum. Mol. Genet. 20, 3884–3892 (2011).
Nishida, N. et al. Genome-wide association study confirming association of HLA-DP with protection against chronic hepatitis B and viral clearance in Japanese and Korean. PLoS ONE 7, e39175 (2012).
Duggal, P. et al. Genome-wide association study of spontaneous resolution of hepatitis C virus infection: data from multiple cohorts. Ann. Intern. Med. 158, 235–245 (2013).
Chen, D. et al. Genome-wide association study of HPV seropositivity. Hum. Mol. Genet. 20, 4714–4723 (2011).
Hanchard, N. A. et al. Screening for recently selected alleles by analysis of human haplotype similarity. Am. J. Hum. Genet. 78, 153–159 (2006).
Hanchard, N. et al. Classical sickle β-globin haplotypes exhibit a high degree of long-range haplotype similarity in African and Afro-Caribbean populations. BMC Genet. 8, 52 (2007).
Andres, A. M. et al. Targets of balancing selection in the human genome. Mol. Biol. Evol. 26, 2755–2764 (2009).
Klein, J., Satta, Y., O'hUigin, C. & Takahata, N. The molecular descent of the major histocompatibility complex. Annu. Rev. Immunol. 11, 269–295 (1993).
Segurel, L. et al. The ABO blood group is a trans-species polymorphism in primates. Proc. Natl. Acad. Sci. USA 109, 18493–18498 (2012).
Leffler, E. M. et al. Multiple instances of ancient balancing selection shared between humans and chimpanzees. Science 339, 1578–1582 (2013).
Olofsson, S. & Bergstrom, T. Glycoconjugate glycans as viral receptors. Ann. Med. 37, 154–172 (2005).
Day, C. J., Semchenko, E. A. & Korolik, V. Glycoconjugates play a key role in Campylobacter jejuni infection: interactions between host and pathogen. Front. Cell. Infect. Microbiol. 2, 9 (2012).
Ko, W.-Y. et al. Effects of natural selection and gene conversion on the evolution of human glycophorins coding for MNS blood polymorphisms in malaria-endemic African populations. Am. J. Hum. Genet. 88, 741–754 (2011).
Charlesworth, B., Morgan, M. T. & Charlesworth, D. The effect of deleterious mutations on neutral molecular variation. Genetics 134, 1289–1303 (1993).
Barua, D. & Paguio, A. S. ABO blood groups and cholera. Ann. Hum. Biol. 4, 489–492 (1977).
Harris, J. B. et al. Susceptibility to Vibrio cholerae Infection in a cohort of household contacts of patients with cholera in Bangladesh. PLoS Negl. Trop. Dis. 2, e221 (2008).
Lindblad-Toh, K. et al. A high-resolution map of human evolutionary constraint using 29 mammals. Nature 478, 476–482 (2011).
Hong, E. P. & Park, J. W. Sample size and statistical power calculation in genetic association studies. Genom. Inform 10, 117–122 (2012).
McCarthy, M. I. et al. Genome-wide association studies for complex traits: consensus, uncertainty and challenges. Nature Rev. Genet. 9, 356–369 (2008).
Hill, A. V. Evolution, revolution and heresy in the genetics of infectious disease susceptibility. Phil. Trans. R. Soc. B 367, 840–849 (2012).
Siontis, K. C., Patsopoulos, N. A. & Ioannidis, J. P. Replication of past candidate loci for common diseases and phenotypes in 100 genome-wide association studies. Eur. J. Hum. Genet. 18, 832–837 (2010).
Thye, T. et al. Genome-wide association analyses identifies a susceptibility locus for tuberculosis on chromosome 18q11.2. Nature Genet. 42, 739–741 (2010).
Qu, H. Q., Li, Q., McCormick, J. B. & Fisher-Hoch, S. P. What did we learn from the genome-wide association study for tuberculosis susceptibility? J. Med. Genet. 48, 217–218 (2011).
Qu, H. Q., Fisher-Hoch, S. P. & McCormick, J. B. Knowledge gaining by human genetic studies on tuberculosis susceptibility. J. Hum. Genet. 56, 177–182 (2011).
Kaslow, R. A., McNicholl, J. & Hill, A. V. S. Genetic Susceptibility to Infectious Diseases (Oxford Univ. Press, 2008).
Roeder, K., Bacanu, S. A., Wasserman, L. & Devlin, B. Using linkage genome scans to improve power of association in genome scans. Am. J. Hum. Genet. 78, 243–252 (2006).
Ayodo, G. et al. Combining evidence of natural selection with association analysis increases power to detect malaria-resistance variants. Am. J. Hum. Genet. 81, 234–242 (2007). This paper shows that signals of positive selection can increase power to detect associations.
Park, D. J. et al. Sequence-based association and selection scans identify drug resistance loci in the Plasmodium falciparum malaria parasite. Proc. Natl. Acad. Sci. USA 109, 13052–13057 (2012).
Daub, J. T. et al. Evidence for polygenic adaptation to pathogens in the human genome. Mol. Biol. Evol. 30, 1544–1558 (2013).
Lee, P. H. et al. Multi-locus genome-wide association analysis supports the role of glutamatergic synaptic transmission in the aetiology of major depressive disorder. Transl. Psychiatry 2, e184 (2012).
Wang, K., Li, M. & Hakonarson, H. Analysing biological pathways in genome-wide association studies. Nature Rev. Genet. 11, 843–854 (2010).
Genovese, G. et al. Association of trypanolytic ApoL1 variants with kidney disease in African Americans. Science 329, 841–845 (2010).
Dunham, I. et al. An integrated encyclopedia of DNA elements in the human genome. Nature 489, 57–74 (2012).
Kudaravalli, S., Veyrieras, J. B., Stranger, B. E., Dermitzakis, E. T. & Pritchard, J. K. Gene expression levels are a target of recent natural selection in the human genome. Mol. Biol. Evol. 26, 649–658 (2009).
Raj, T. et al. Common risk alleles for inflammatory diseases are targets of recent positive selection. Am. J. Hum. Genet. 92, 517–529 (2013). This paper presents a systems-based analysis that integrates GWAS, selection, functional data and eQTL mapping.
Altshuler, D. M. et al. Integrating common and rare genetic variation in diverse human populations. Nature 467, 52–58 (2010).
Rosenbloom, K. R. et al. ENCODE data in the UCSC Genome Browser: year 5 update. Nucleic Acids Res. 41, D56–D63 (2013).
Melnikov, A. et al. Systematic dissection and optimization of inducible enhancers in human cells using a massively parallel reporter assay. Nature Biotech. 30, 271–277 (2012).
Cong, L. et al. Multiplex genome engineering using CRISPR/Cas systems. Science 339, 819–823 (2013).
Edwards, S. L., Beesley, J., French, J. D. & Dunning, A. M. Beyond GWASs: illuminating the dark road from association to function. Am. J. Hum. Genet. 93, 779–797 (2013).
de Wit, E. & de Laat, W. A decade of 3C technologies: insights into nuclear organization. Genes Dev. 26, 11–24 (2012).
Shapiro, E., Biezuner, T. & Linnarsson, S. Single-cell sequencing-based technologies will revolutionize whole-organism science. Nature Rev. Genet. 14, 618–630 (2013).
Schneider, T., Kreutz, J. & Chiu, D. T. The potential impact of droplet microfluidics in biology. Anal. Chem. 85, 3476–3482 (2013).
Shalem, O. et al. Genome-scale CRISPR–Cas9 knockout screening in human cells. Science 343, 84–87 (2014).
Wang, T., Wei, J. J., Sabatini, D. M. & Lander, E. S. Genetic screens in human cells using the CRISPR–Cas9 system. Science 343, 80–84 (2014).
Hindorff, L. A. et al. Potential aetiologic and functional implications of genome-wide association loci for human diseases and traits. Proc. Natl. Acad. Sci. USA 106, 9362–9367 (2009).
Wang, Y. et al. The lactase persistence/non-persistence polymorphism is controlled by a cis-acting element. Hum. Mol. Genet. 4, 657–662 (1995).
Coop, G. et al. The role of geography in human adaptation. PLoS Genet. 5, e1000500 (2009).
World Health Organization. World Malaria Report 2011. WHO [online], (2011).
Hartl, D. L. The origin of malaria: mixed messages from genetic diversity. Nature Rev. Microbiol. 2, 15–22 (2004).
Miller, L. H., Mason, S. J., Clyde, D. F. & McGinniss, M. H. The resistance factor to Plasmodium vivax in blacks. The Duffy-blood-group genotype, FyFy. N. Engl. J. Med. 295, 302–304 (1976).
Tournamille, C., Colin, Y., Cartron, J. P. & Le Van Kim, C. Disruption of a GATA motif in the Duffy gene promoter abolishes erythroid gene expression in Duffy-negative individuals. Nature Genet. 10, 224–228 (1995).
Shimizu, Y. et al. Sero- and molecular typing of Duffy blood group in Southeast Asians and Oceanians. Hum. Biol. 72, 511–518 (2000).
Menard, D. et al. Plasmodium vivax clinical malaria is commonly observed in Duffy-negative Malagasy people. Proc. Natl. Acad. Sci. USA 107, 5967–5971 (2010).
Menard, D. et al. Whole genome sequencing of field isolates reveals a common duplication of the Duffy binding protein gene in Malagasy Plasmodium vivax strains. PLoS Negl. Trop. Dis. 7, e2489 (2013).
Teo, Y.-Y., Small, K. S. & Kwiatkowski, D. P. Methodological challenges of genome-wide association analysis in Africa. Nature Rev. Genet. 11, 149–160 (2010).
Timmann, C. et al. Genome-wide association study indicates two novel resistance loci for severe malaria. Nature 489, 443–446 (2012).
Band, G. et al. Imputation-based meta-analysis of severe malaria in three African populations. PLoS Genet. 9, e1003509 (2013). This study presents new methods for tackling complex GWASs.
Achidi, E. A. et al. A global network for investigating the genomic epidemiology of malaria. Nature 456, 732–737 (2008).
van Brakel, W. H. Measuring leprosy stigma — a preliminary review of the leprosy literature. Int. J. Lepr. Other Mycobact. Dis. 71, 190–197 (2003).
Rao, P. S. et al. Disability adjusted working life years (DAWLYs) of leprosy affected persons in India. Indian J. Med. Res. 137, 907–910 (2013).
Guinto, R. S., Doull, J. A. & De Guia, L. Mortality of persons with leprosy before sulphone therapy, Cordova and Talisay, Cebu, Philippines. Int. J. Lepr 22, 273–284 (1954).
Saporta, L. & Yuksel, A. Androgenic status in patients with lepromatous leprosy. Br. J. Urol. 74, 221–224 (1994).
Leal, A. M. & Foss, N. T. Endocrine dysfunction in leprosy. Eur. J. Clin. Microbiol. Infect. Dis. 28, 1–7 (2009).
Monot, M. et al. Comparative genomic and phylogeographic analysis of Mycobacterium leprae. Nature Genet. 41, 1282–1289 (2009).
Smith, D. G. & Guinto, R. S. Leprosy and fertility. Hum. Biol. 50, 451–460 (1978).
Jacobson, R. R. & Krahenbuhl, J. L. Leprosy. Lancet 353, 655–660 (1999).
Alter, A., Alcais, A., Abel, L. & Schurr, E. Leprosy as a genetic model for susceptibility to common infectious diseases. Hum. Genet. 123, 227–235 (2008).
Shields, E. D., Russell, D. A. & Pericak-Vance, M. A. Genetic epidemiology of the susceptibility to leprosy. J. Clin. Invest. 79, 1139–1143 (1987).
Boldsen, J. L. Leprosy in mediaeval Denmark — osteological and epidemiological analyses. Anthropol. Anz. 67, 407–425 (2009).
World Health Organization. Global leprosy situation. Weekly Epidemiol. Record 87, 317–328 [online], (2012).
Zhang, F. et al. Identification of two new loci at IL23R and RAB32 that influence susceptibility to leprosy. Nature Genet. 43, 1247–1251 (2011).
Wong, S. H., Hill, A. V., Vannberg, F. O. Genomewide association study of leprosy. N. Engl. J. Med. 362, 1446–1447; author reply 1447–1448 (2010).
Johnson, C. M. et al. Cutting edge: a common polymorphism impairs cell surface trafficking and functional responses of TLR1 but protects against leprosy. J. Immunol. 178, 7520–7524 (2007).
Wong, S. H. et al. Leprosy and the adaptation of human Toll-like receptor 1. PLoS Pathog. 6, e1000979 (2010). This paper shows selection for a leprosy protective variant in TLR1 in Europeans, which suggests a long host–pathogen relationship.
Barreiro, L. B. et al. Evolutionary dynamics of human Toll-like receptors and their different contributions to host defense. PLoS Genet. 5, e1000562 (2009).
Reiley, W. W. et al. Regulation of T cell development by the deubiquitylating enzyme CYLD. Nature Immunol. 7, 411–417 (2006).
Brummelkamp, T. R., Nijman, S. M., Dirac, A. M. & Bernards, R. Loss of the cylindromatosis tumour suppressor inhibits apoptosis by activating NF-κB. Nature 424, 797–801 (2003).
Wirth, T. et al. Origin, spread and demography of the Mycobacterium tuberculosis complex. PLoS Pathog. 4, e1000160 (2008).
Hershberg, R. et al. High functional diversity in Mycobacterium tuberculosis driven by genetic drift and human demography. PLoS Biol. 6, e311 (2008).
Moller, M. & Hoal, E. G. Current findings, challenges and novel approaches in human genetic susceptibility to tuberculosis. Tuberculosis 90, 71–83 (2010).
Thye, T. et al. Common variants at 11p13 are associated with susceptibility to tuberculosis. Nature Genet. 44, 257–259 (2012).
Gagneux, S. et al. Variable host–pathogen compatibility in Mycobacterium tuberculosis. Proc. Natl. Acad. Sci. USA 103, 2869–2873 (2006).
World Health Organization. Global Tuberculosis Control 2011. WHO [online], (2011).
Stein, C. M. Genetic epidemiology of tuberculosis susceptibility: impact of study design. PLoS Pathog. 7, e1001189 (2011).
Global AIDS epidemic facts and figures. UNAIDS [online], (2013).
Worobey, M. et al. Direct evidence of extensive diversity of HIV-1 in Kinshasa by 1960. Nature 455, 661–664 (2008).
VandeWoude, S. & Apetrei, C. Going wild: lessons from naturally occurring T lymphotropic lentiviruses. Clin. Microbiol. Rev. 19, 728–762 (2006).
Worobey, M. et al. Island biogeography reveals the deep history of SIV. Science 329, 1487 (2010).
Liu, R. et al. Homozygous defect in HIV-1 co-receptor accounts for resistance of some multiply-exposed individuals to HIV-1 infection. Cell 86, 367–377 (1996).
Dean, M. et al. Genetic restriction of HIV-1 infection and progression to AIDS by a deletion allele of the CKR5 structural gene. Science 273, 1856–1862 (1996).
Stephens, J. C. et al. Dating the origin of the CCR5–Δ32 AIDS-resistance allele by the coalescence of haplotypes. Am. J. Hum. Genet. 62, 1507–1515 (1998).
Sabeti, P. C. et al. The case for selection at CCR5- Δ 32. PLoS Biol. 3, e378 (2005).
Tebas, P. et al. Gene editing of CCR5 in autologous CD4 T cells of persons infected with HIV. N. Engl. J. Med. 370, 901–910 (2014).
Thomas, R. et al. HLA-C cell surface expression and control of HIV/AIDS correlate with a variant upstream of HLA-C. Nature Genet. 41, 1290–1294 (2009).
Apps, R. et al. Influence of HLA-C expression level on HIV control. Science 340, 87–91 (2013).
Harris, J. B., LaRocque, R. C., Qadri, F., Ryan, E. T. & Calderwood, S. B. Cholera. Lancet 379, 2466–2476 (2012).
Sack, D. A., Sack, R. B., Nair, G. B. & Siddique, A. K. Cholera. Lancet 363, 223–233 (2004).
Harris, J. B. et al. Cholera's western front. Lancet 376, 1961–1965 (2010).
Lee, K. The global dimensions of cholera. Global Change Hum. Health 2, 6–17 (2001).
Chowdhury, F. et al. Impact of rapid urbanization on the rates of infection by Vibrio cholerae O1 and enterotoxigenic Escherichia coli in Dhaka, Bangladesh. PLoS Negl. Trop. Dis 5, e999 (2011).
Mosley, W. H., McCormack, W. M., Ahmed, A., Chowdhury, A. K. & Barui, R. K. Report of the 1966–1967 cholera vaccine field trial in rural East Pakistan. 2. Results of the serological surveys in the study population — the relationship of case rate to antibody titre and an estimate of the inapparent infection rate with Vibrio cholerae. Bull. World Health Organ. 40, 187–197 (1969).
Glass, R. I. et al. Seroepidemiological studies of El Tor cholera in Bangladesh: association of serum antibody levels with protection. J. Infect. Dis. 151, 236–242 (1985).
Karlsson, E. K. et al. Natural selection in a Bangladeshi population from the cholera-endemic Ganges River Delta. Sci. Transl. Med. 5, 192ra86 (2013). This study uses selection for host resistance to historically localized pathogen to investigate immune response pathways.
Lee, P. H., O'Dushlaine, C., Thomas, B. & Purcell, S. M. INRICH: interval-based enrichment analysis for genome-wide association studies. Bioinformatics 28, 1797–1799 (2012).
Hall, A. J. Noroviruses: the perfect human pathogens? J. Infect. Dis. 205, 1622–1624 (2012).
Patel, M. M. et al. Systematic literature review of role of noroviruses in sporadic gastroenteritis. Emerg. Infect. Dis. 14, 1224–1231 (2008).
Wertheim, J. O. & Kosakovsky Pond, S. L. Purifying selection can obscure the ancient age of viral lineages. Mol. Biol. Evol. 28, 3355–3365 (2011).
Worobey, M., Bjork, A. & Wertheim, J. O. Point, counterpoint: the evolution of pathogenic viruses and their human hosts. Annu. Rev. Ecol. Evol. Syst. 38, 515–540 (2007).
Emerman, M. & Malik, H. S. Paleovirology — modern consequences of ancient viruses. PLoS Biol. 8, e1000301 (2010).
Lindesmith, L. et al. Human susceptibility and resistance to Norwalk virus infection. Nature Med. 9, 548–553 (2003).
Carlsson, B. et al. The G428A nonsense mutation in FUT2 provides strong but not absolute protection against symptomatic GII.4 Norovirus infection. PLoS ONE 4, e5593 (2009).
Nordgren, J., Kindberg, E., Lindgren, P.-E., Matussek, A. & Svensson, L. Norovirus gastroenteritis outbreak with a secretor-independent susceptibility pattern, Sweden. Emerg. Infecti. Diseases 16, 81 (2010).
Ferrer-Admetlla, A. et al. A natural history of FUT2 polymorphism in humans. Mol. Biol. Evol. 26, 1993–2003 (2009).
Taubenberger, J. K. & Morens, D. M. Influenza revisited. Emerg. Infecti. Diseases 12, 1 (2006).
Johnson, N. P. & Mueller, J. Updating the accounts: global mortality of the 1918–1920 “Spanish†influenza pandemic. Bull. Hist. Med. 76, 105–115 (2002).
Martin, P. M. & Martin-Granel, E. 2,500 year evolution of the term epidemic. Emerg. Infect. Dis. 12, 976–980 (2006).
Albright, F. S., Orlando, P., Pavia, A. T., Jackson, G. G. & Cannon Albright, L. A. Evidence for a heritable predisposition to death due to influenza. J. Infect. Dis. 197, 18–24 (2008).
Horby, P., Nguyen, N. Y., Dunstan, S. J. & Baillie, J. K. The role of host genetics in susceptibility to influenza: a systematic review. PLoS ONE 7, e33180 (2012).
Brass, A. L. et al. The IFITM proteins mediate cellular resistance to influenza A H1N1 virus, West Nile virus, and dengue virus. Cell 139, 1243–1254 (2009).
Everitt, A. R. et al. IFITM3 restricts the morbidity and mortality associated with influenza. Nature 484, 519–523 (2012).
Li, Y. et al. On the origin of smallpox: correlating variola phylogenics with historical smallpox records. Proc. Natl. Acad. Sci. USA 104, 15787–15792 (2007).
Babkin, I. V. & Shelkunov, S. N. [Molecular evolution of poxviruses]. Genetika 44, 1029–1044 (in Russian) (2008).
Esposito, J. J. et al. Genome sequence diversity and clues to the evolution of variola (smallpox) virus. Science 313, 807–812 (2006).
Ovsyannikova, I. G. et al. Genome-wide association study of antibody response to smallpox vaccine. Vaccine 30, 4182–4189 (2012).
Kennedy, R. B. et al. Genome-wide analysis of polymorphisms associated with cytokine responses in smallpox vaccine recipients. Hum. Genet. 131, 1403–1421 (2012).
Barreiro, L. B. & Quintana-Murci, L. From evolutionary genetics to human immunology: how selection shapes host defence genes. Nature Rev. Genet. 11, 17–30 (2010). This paper shows that pathogen-driven selection shaped the human genome.
Casto, A. M. & Feldman, M. W. Genome-wide association study SNPs in the human genome diversity project populations: does selection affect unlinked SNPs with shared trait associations? PLoS Genet. 7, e1001266 (2011).
Hancock, A. M. et al. Adaptations to climate-mediated selective pressures in humans. PLoS Genet. 7, e1001375 (2011).
Hu, X. & Daly, M. What have we learned from six years of GWAS in autoimmune diseases, and what is next? Curr. Opin. Immunol. 24, 571–575 (2012).
Fumagalli, M. et al. Parasites represent a major selective force for interleukin genes and shape the genetic predisposition to autoimmune conditions. J. Exp. Med. 206, 1395–1408 (2009).
Sirota, M., Schaub, M. A., Batzoglou, S., Robinson, W. H. & Butte, A. J. Autoimmune disease classification by inverse association with SNP alleles. PLoS Genet. 5, e1000792 (2009).
Schenk, M. et al. NOD2 triggers an interleukin-32 dependent human dendritic cell program in leprosy. Nature Med. 18, 555–563 (2012).
Greco, L. et al. The first large population based twin study of coeliac disease. Gut 50, 624–628 (2002).
Dube, C. et al. The prevalence of coeliac disease in average-risk and at risk western European populations: a systematic review. Gastroenterology 128, S57–S67 (2005).
Catassi, C. et al. Why is coeliac disease endemic in the people of the Sahara? Lancet 354, 647–648 (1999).
Zhernakova, A. et al. Evolutionary and functional analysis of coeliac risk loci reveals SH2B3 as a protective factor against bacterial infection. Am. J. Hum. Genet. 86, 970–977 (2010).
Pinhasi, R., Fort, J. & Ammerman, A. J. Tracing the origin and spread of agriculture in Europe. PLoS Biol. 3, e410 (2005).
Itan, Y., Powell, A., Beaumont, M. A., Burger, J. & Thomas, M. G. The origins of lactase persistence in Europe. PLoS Comput. Biol. 5, e1000491 (2009).
Kao, W. H. et al. MYH9 is associated with nondiabetic end-stage renal disease in African Americans. Nature Genet. 40, 1185–1192 (2008).
Kopp, J. B. et al. MYH9 is a major-effect risk gene for focal segmental glomerulosclerosis. Nature Genet. 40, 1175–1184 (2008).
Sainz, J. et al. Inflammatory and immune response genes have significantly altered expression in schizophrenia. Mol. Psychiatry 18, 1056–1057 (2013).
Onore, C., Careaga, M. & Ashwood, P. The role of immune dysfunction in the pathophysiology of autism. Brain Behav. Immun. 26, 383–392 (2012).
Spencer, C. C., Su, Z., Donnelly, P. & Marchini, J. Designing genome-wide association studies: sample size, power, imputation, and the choice of genotyping chip. PLoS Genet. 5, e1000477 (2009).
Png, E. et al. A genome wide association study of pulmonary tuberculosis susceptibility in Indonesians. BMC Med. Genet. 13, 5 (2012).
Mahasirimongkol, S. et al. Genome-wide association studies of tuberculosis in Asians identify distinct at risk locus for young tuberculosis. J. Hum. Genet. 57, 363–367 (2012).
Petrovski, S. et al. Common human genetic variants and HIV-1 susceptibility: a genome-wide survey in a homogeneous African population. AIDS 25, 513–518 (2011).
Pelak, K. et al. Host determinants of HIV-1 control in African Americans. J. Infect. Dis. 201, 1141–1149 (2010).
Acknowledgements
The authors thank S. Schaffner, E. Brown, D. Park, D. Neafsey, R. LaRocque and J. Harris for discussions.
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FURTHER INFORMATION
Supplementary information
Supplementary information S1 (table)
Pathogen GWASs in NHGRI GWAS catalog (https://www.genome.gov/26525384) as of April 15, 2014 (PDF 191 kb)
Glossary
- Pathogens
-
Viruses, bacteria or other microorganisms that can cause disease.
- Signatures of selection
-
An unusual pattern of allele frequencies that marks a selected locus.
- Frequency
-
Prevalence of an allele in a population.
- Genome-wide association studies
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(GWASs). Examination of variants that are distributed across the entire genome for correlation with particular traits.
- Next-generation sequencing
-
New high-throughput, parallelized, low-cost sequencing technologies that do not use the chain termination Sanger method.
- Genetic diversity
-
Total amount of genetic variation in a population.
- Bottlenecks
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Sharp decreases in the effective sizes of populations.
- Admixture
-
Interbreeding between two genetically separated populations.
- Ascertainment bias
-
Nonrandom selection of variants for genotyping.
- Neutral variation
-
Genetic variation that confers no selective advantage or disadvantage and that varies in frequency by random drift.
- Linkage disequilibrium
-
(LD). The nonrandom association of alleles at different genomic loci.
- Fixation
-
The increase in frequency of an allele to 100% in a population.
- Standing variation
-
Existing genetic variation within a population.
- Selective sweeps
-
Reductions in genetic variation caused by positive selection at particular loci.
- Incomplete sweeps
-
Partial or ongoing selective sweeps of advantageous alleles to <100% prevalence.
- Complete sweeps
-
Selective sweeps of advantageous alleles to 100% prevalence.
- Candidate gene approach
-
Association study that tests only variants in a pre-specified set of genes.
- Pathway-based approaches
-
Methods that test for joint association of genes in the same functional pathway.
- Expression quantitative trait loci
-
(eQTLs). Genomic loci that regulate gene expression.
- Imputation
-
Statistical prediction of missing genetic data.
- Gene set enrichment
-
Overrepresentation of an a priori defined group of genes.
- Pleiotropic effects
-
Effects on multiple unrelated phenotypes.
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Karlsson, E., Kwiatkowski, D. & Sabeti, P. Natural selection and infectious disease in human populations. Nat Rev Genet 15, 379–393 (2014). https://doi.org/10.1038/nrg3734
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DOI: https://doi.org/10.1038/nrg3734
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