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The legacy of human-Neandertal interbreeding

Non-African humans are estimated to have inherited on average 1.5 to 4% of their genomes from Neandertals. However, how this genetic legacy affects human traits is unknown. Simonti et al. combined genotyping data with electronic health records. Individual Neandertal alleles were correlated with clinically relevant phenotypes in individuals of European descent. These archaic genetic variants were associated with medical conditions affecting the skin, the blood, and the risk of depression.
Science, this issue p. 737

Abstract

Many modern human genomes retain DNA inherited from interbreeding with archaic hominins, such as Neandertals, yet the influence of this admixture on human traits is largely unknown. We analyzed the contribution of common Neandertal variants to over 1000 electronic health record (EHR)–derived phenotypes in ~28,000 adults of European ancestry. We discovered and replicated associations of Neandertal alleles with neurological, psychiatric, immunological, and dermatological phenotypes. Neandertal alleles together explained a significant fraction of the variation in risk for depression and skin lesions resulting from sun exposure (actinic keratosis), and individual Neandertal alleles were significantly associated with specific human phenotypes, including hypercoagulation and tobacco use. Our results establish that archaic admixture influences disease risk in modern humans, provide hypotheses about the effects of hundreds of Neandertal haplotypes, and demonstrate the utility of EHR data in evolutionary analyses.
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Tables S1 to S5
References (2651)

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REFERENCES AND NOTES

1
Higham T., Douka K., Wood R., Ramsey C. B., Brock F., Basell L., Camps M., Arrizabalaga A., Baena J., Barroso-Ruíz C., Bergman C., Boitard C., Boscato P., Caparrós M., Conard N. J., Draily C., Froment A., Galván B., Gambassini P., Garcia-Moreno A., Grimaldi S., Haesaerts P., Holt B., Iriarte-Chiapusso M. J., Jelinek A., Jordá Pardo J. F., Maíllo-Fernández J. M., Marom A., Maroto J., Menéndez M., Metz L., Morin E., Moroni A., Negrino F., Panagopoulou E., Peresani M., Pirson S., de la Rasilla M., Riel-Salvatore J., Ronchitelli A., Santamaria D., Semal P., Slimak L., Soler J., Soler N., Villaluenga A., Pinhasi R., and Jacobi R., The timing and spatiotemporal patterning of Neandertal disappearance. Nature 512, 306–309 (2014).
2
Green R. E., Krause J., Briggs A. W., Maricic T., Stenzel U., Kircher M., Patterson N., Li H., Zhai W., Fritz M. H., Hansen N. F., Durand E. Y., Malaspinas A. S., Jensen J. D., Marques-Bonet T., Alkan C., Prüfer K., Meyer M., Burbano H. A., Good J. M., Schultz R., Aximu-Petri A., Butthof A., Höber B., Höffner B., Siegemund M., Weihmann A., Nusbaum C., Lander E. S., Russ C., Novod N., Affourtit J., Egholm M., Verna C., Rudan P., Brajkovic D., Kucan Z., Gusic I., Doronichev V. B., Golovanova L. V., Lalueza-Fox C., de la Rasilla M., Fortea J., Rosas A., Schmitz R. W., Johnson P. L., Eichler E. E., Falush D., Birney E., Mullikin J. C., Slatkin M., Nielsen R., Kelso J., Lachmann M., Reich D., and Pääbo S., A draft sequence of the Neandertal genome. Science 328, 710–722 (2010).
3
Prüfer K., Racimo F., Patterson N., Jay F., Sankararaman S., Sawyer S., Heinze A., Renaud G., Sudmant P. H., de Filippo C., Li H., Mallick S., Dannemann M., Fu Q., Kircher M., Kuhlwilm M., Lachmann M., Meyer M., Ongyerth M., Siebauer M., Theunert C., Tandon A., Moorjani P., Pickrell J., Mullikin J. C., Vohr S. H., Green R. E., Hellmann I., Johnson P. L., Blanche H., Cann H., Kitzman J. O., Shendure J., Eichler E. E., Lein E. S., Bakken T. E., Golovanova L. V., Doronichev V. B., Shunkov M. V., Derevianko A. P., Viola B., Slatkin M., Reich D., Kelso J., and Pääbo S., The complete genome sequence of a Neandertal from the Altai Mountains. Nature 505, 43–49 (2014).
4
Wall J. D., Yang M. A., Jay F., Kim S. K., Durand E. Y., Stevison L. S., Gignoux C., Woerner A., Hammer M. F., and Slatkin M., Higher levels of neanderthal ancestry in East Asians than in Europeans. Genetics 194, 199–209 (2013).
5
Sankararaman S., Mallick S., Dannemann M., Prüfer K., Kelso J., Pääbo S., Patterson N., and Reich D., The genomic landscape of Neandertal ancestry in present-day humans. Nature 507, 354–357 (2014).
6
Vernot B. and Akey J. M., Resurrecting surviving Neandertal lineages from modern human genomes. Science 343, 1017–1021 (2014).
7
Abi-Rached L., Jobin M. J., Kulkarni S., McWhinnie A., Dalva K., Gragert L., Babrzadeh F., Gharizadeh B., Luo M., Plummer F. A., Kimani J., Carrington M., Middleton D., Rajalingam R., Beksac M., Marsh S. G., Maiers M., Guethlein L. A., Tavoularis S., Little A. M., Green R. E., Norman P. J., and Parham P., The shaping of modern human immune systems by multiregional admixture with archaic humans. Science 334, 89–94 (2011).
8
Huerta-Sánchez E., Jin X., Asan Z., Bianba B. M., Peter N., Vinckenbosch Y., Liang X., Yi M., He M., Somel P., Ni B., Wang X., Ou J., Huasang Z. X., Luosang K., Cuo G., Li Y., Gao W., Yin X., Wang X., Zhang H., Xu Y., Yang J., Li J., Wang R., Wang, and Nielsen, Altitude adaptation in Tibetans caused by introgression of Denisovan-like DNA. Nature 512, 194–197 (2014).
9
Khrameeva E. E., Bozek K., He L., Yan Z., Jiang X., Wei Y., Tang K., Gelfand M. S., Prufer K., Kelso J., Paabo S., Giavalisco P., Lachmann M., and Khaitovich P., Neandertal ancestry drives evolution of lipid catabolism in contemporary Europeans. Nat. Commun. 5, 3584 (2014).
10
Kho A. N., Pacheco J. A., Peissig P. L., Rasmussen L., Newton K. M., Weston N., Crane P. K., Pathak J., Chute C. G., Bielinski S. J., Kullo I. J., Li R., Manolio T. A., Chisholm R. L., and Denny J. C., Electronic medical records for genetic research: Results of the eMERGE consortium. Sci. Transl. Med. 3, 79re1 (2011).
11
Schroeder L. F., Robilotti E., Peterson L. R., Banaei N., and Dowdy D. W., Economic evaluation of laboratory testing strategies for hospital-associated Clostridium difficile infection. J. Clin. Microbiol. 52, 489–496 (2014).
12
Gottesman O., Kuivaniemi H., Tromp G., Faucett W. A., Li R., Manolio T. A., Sanderson S. C., Kannry J., Zinberg R., Basford M. A., Brilliant M., Carey D. J., Chisholm R. L., Chute C. G., Connolly J. J., Crosslin D., Denny J. C., Gallego C. J., Haines J. L., Hakonarson H., Harley J., Jarvik G. P., Kohane I., Kullo I. J., Larson E. B., McCarty C., Ritchie M. D., Roden D. M., Smith M. E., Böttinger E. P., and Williams M. S., The Electronic Medical Records and Genomics (eMERGE) Network: Past, present, and future. Genet. Med. 15, 761–771 (2013).
13
Plagnol V. and Wall J. D., Possible ancestral structure in human populations. PLOS Genet. 2, e105 (2006).
14
Abecasis G. R., Auton A., Brooks L. D., DePristo M. A., Durbin R. M., Handsaker R. E., Kang H. M., Marth G. T., and McVean G. A., An integrated map of genetic variation from 1,092 human genomes. Nature 491, 56–65 (2012).
15
Yang J., Lee S. H., Goddard M. E., and Visscher P. M., GCTA: A tool for genome-wide complex trait analysis. Am. J. Hum. Genet. 88, 76–82 (2011).
16
Gokhman D., Lavi E., Prüfer K., Fraga M. F., Riancho J. A., Kelso J., Pääbo S., Meshorer E., and Carmel L., Reconstructing the DNA methylation maps of the Neandertal and the Denisovan. Science 344, 523–527 (2014).
17
Oksenberg N., Stevison L., Wall J. D., and Ahituv N., Function and regulation of AUTS2, a gene implicated in autism and human evolution. PLOS Genet. 9, e1003221 (2013).
18
Golden R. N., Gaynes B. N., Ekstrom R. D., Hamer R. M., Jacobsen F. M., Suppes T., Wisner K. L., and Nemeroff C. B., The efficacy of light therapy in the treatment of mood disorders: A review and meta-analysis of the evidence. Am. J. Psychiatry 162, 656–662 (2005).
19
Denny J. C., Bastarache L., Ritchie M. D., Carroll R. J., Zink R., Mosley J. D., Field J. R., Pulley J. M., Ramirez A. H., Bowton E., Basford M. A., Carrell D. S., Peissig P. L., Kho A. N., Pacheco J. A., Rasmussen L. V., Crosslin D. R., Crane P. K., Pathak J., Bielinski S. J., Pendergrass S. A., Xu H., Hindorff L. A., Li R., Manolio T. A., Chute C. G., Chisholm R. L., Larson E. B., Jarvik G. P., Brilliant M. H., McCarty C. A., Kullo I. J., Haines J. L., Crawford D. C., Masys D. R., and Roden D. M., Systematic comparison of phenome-wide association study of electronic medical record data and genome-wide association study data. Nat. Biotechnol. 31, 1102–1110 (2013).
20
The GTEx Consortium, The Genotype-Tissue Expression (GTEx) pilot analysis: Multitissue gene regulation in humans. Science 348, 648–660 (2015).
21
Heit J. A., Armasu S. M., Asmann Y. W., Cunningham J. M., Matsumoto M. E., Petterson T. M., and De Andrade M., A genome-wide association study of venous thromboembolism identifies risk variants in chromosomes 1q24.2 and 9q. J. Thromb. Haemost. 10, 1521–1531 (2012).
22
Rallapalli P. M., Orengo C. A., Studer R. A., and Perkins S. J., Positive selection during the evolution of the blood coagulation factors in the context of their disease-causing mutations. Mol. Biol. Evol. 31, 3040–3056 (2014).
23
Martin P. R., Singleton C. K., and Hiller-Sturmhöfel S., The role of thiamine deficiency in alcoholic brain disease. Alcohol Res. Health 27, 134–142 (2003).
24
Pazo J. H. and Belforte J. E., Basal ganglia and functions of the autonomic nervous system. Cell. Mol. Neurobiol. 22, 645–654 (2002).
25
Pickering C., Bergenheim V., Schiöth H. B., and Ericson M., Sensitization to nicotine significantly decreases expression of GABA transporter GAT-1 in the medial prefrontal cortex. Prog. Neuropsychopharmacol. Biol. Psychiatry 32, 1521–1526 (2008).
26
O’Connell J., Gurdasani D., Delaneau O., Pirastu N., Ulivi S., Cocca M., Traglia M., Huang J., Huffman J. E., Rudan I., McQuillan R., Fraser R. M., Campbell H., Polasek O., Asiki G., Ekoru K., Hayward C., Wright A. F., Vitart V., Navarro P., Zagury J. F., Wilson J. F., Toniolo D., Gasparini P., Soranzo N., Sandhu M. S., and Marchini J., A general approach for haplotype phasing across the full spectrum of relatedness. PLOS Genet. 10, e1004234 (2014).
27
Howie B. N., Donnelly P., and Marchini J., A flexible and accurate genotype imputation method for the next generation of genome-wide association studies. PLOS Genet. 5, e1000529 (2009).
28
Price A. L., Patterson N. J., Plenge R. M., Weinblatt M. E., Shadick N. A., and Reich D., Principal components analysis corrects for stratification in genome-wide association studies. Nat. Genet. 38, 904–909 (2006).
29
Crosslin D. R., Tromp G., Burt A., Kim D. S., Verma S. S., Lucas A. M., Bradford Y., Crawford D. C., Armasu S. M., Heit J. A., Hayes M. G., Kuivaniemi H., Ritchie M. D., Jarvik G. P., de Andrade M., and electronic Medical Records and Genomics (eMERGE) Network, Controlling for population structure and genotyping platform bias in the eMERGE multi-institutional biobank linked to electronic health records. Front. Genet. 5, 352 (2014).
30
Verma S. S., de Andrade M., Tromp G., Kuivaniemi H., Pugh E., Namjou-Khales B., Mukherjee S., Jarvik G. P., Kottyan L. C., Burt A., Bradford Y., Armstrong G. D., Derr K., Crawford D. C., Haines J. L., Li R., Crosslin D., and Ritchie M. D., Imputation and quality control steps for combining multiple genome-wide datasets. Front. Genet. 5, 370 (2014).
31
Carroll R. J., Bastarache L., and Denny J. C., R PheWAS: Data analysis and plotting tools for phenome-wide association studies in the R environment. Bioinformatics 30, 2375–2376 (2014).
32
Denny J. C., Ritchie M. D., Basford M. A., Pulley J. M., Bastarache L., Brown-Gentry K., Wang D., Masys D. R., Roden D. M., and Crawford D. C., PheWAS: Demonstrating the feasibility of a phenome-wide scan to discover gene-disease associations. Bioinformatics 26, 1205–1210 (2010).
33
Hebbring S. J., Schrodi S. J., Ye Z., Zhou Z., Page D., and Brilliant M. H., A PheWAS approach in studying HLA-DRB1*1501. Genes Immun. 14, 187–191 (2013).
34
M. D. Ritchie, J. C. Denny, R. L. Zuvich, D. C. Crawford, J. S. Schildcrout, L. Bastarache, A. H. Ramirez, J. D. Mosley, J. M. Pulley, M. A. Basford, Y. Bradford, L. V. Rasmussen, J. Pathak, C. G. Chute, I. J. Kullo, C. A. McCarty, R. L. Chisholm, A. N. Kho, C. S. Carlson, E. B. Larson, G. P. Jarvik, N. Sotoodehnia, T. A. Manolio, R. Li, D. R. Masys, J. L. Haines, D. M. Roden, Genome-and phenome-wide analysis of cardiac conduction identifies markers of arrhythmia risk. Circulation 127, 1377–1385 (2013).
35
Yang J., Manolio T. A., Pasquale L. R., Boerwinkle E., Caporaso N., Cunningham J. M., de Andrade M., Feenstra B., Feingold E., Hayes M. G., Hill W. G., Landi M. T., Alonso A., Lettre G., Lin P., Ling H., Lowe W., Mathias R. A., Melbye M., Pugh E., Cornelis M. C., Weir B. S., Goddard M. E., and Visscher P. M., Genome partitioning of genetic variation for complex traits using common SNPs. Nat. Genet. 43, 519–525 (2011).
36
L. A. Pratt, D. J. Brody, Q. Gu, Antidepressant use in persons aged 12 and over: United States, 2005-2008. NCHS Data Brief 76, 1–8 (2011)
37
Flohil S. C., van der Leest R. J., Dowlatshahi E. A., Hofman A., de Vries E., and Nijsten T., Prevalence of actinic keratosis and its risk factors in the general population: The Rotterdam Study. J. Invest. Dermatol. 133, 1971–1978 (2013).
38
C. L. Ogden, M. M. Lamb, M. D. Carroll, K. M. Flegal, Obesity and socioeconomic status in adults: United States, 2005-2008. NCHS Data Brief 50, 1–8 (2010).
39
C. D. Fryar, R. Hirsch, M. S. Eberhardt, S. S. Yoon, J. D. Wright, Hypertension, high serum total cholesterol, and diabetes: Racial and ethnic prevalence differences in U.S. adults, 1999-2006. NCHS Data Brief 36, 1–8 (2010).
40
Kessler R. C., Chiu W. T., Demler O., Merikangas K. R., and Walters E. E., Prevalence, severity, and comorbidity of 12-month DSM-IV disorders in the National Comorbidity Survey Replication. Arch. Gen. Psychiatry 62, 617–627 (2005).
41
McLean C. Y., Bristor D., Hiller M., Clarke S. L., Schaar B. T., Lowe C. B., Wenger A. M., and Bejerano G., GREAT improves functional interpretation of cis-regulatory regions. Nat. Biotechnol. 28, 495–501 (2010).
42
Heller R., Bogomolov M., and Benjamini Y., Deciding whether follow-up studies have replicated findings in a preliminary large-scale omics study. Proc. Natl. Acad. Sci. U.S.A. 111, 16262–16267 (2014).
43
Hadley G., Derry S., and Moore R. A., Imiquimod for actinic keratosis: Systematic review and meta-analysis. J. Invest. Dermatol. 126, 1251–1255 (2006).
44
F. Zou, H. S. Chai, C. S. Younkin, M. Allen, J. Crook, V. S. Pankratz, M. M. Carrasquillo, C. N. Rowley, A. A. Nair, S. Middha, S. Maharjan, Brain expression genome-wide association study (eGWAS) identifies human disease-associated variants. PLOS Genet. 8e1002707(2012).
45
Gamazon E. R., Zhang W., Konkashbaev A., Duan S., Kistner E. O., Nicolae D. L., Dolan M. E., and Cox N. J., SCAN: SNP and copy number annotation. Bioinformatics 26, 259–262 (2010).
46
Storey J. D. and Tibshirani R., Statistical significance for genomewide studies. Proc. Natl. Acad. Sci. U.S.A. 100, 9440–9445 (2003).
47
Chen C., Cheng L., Grennan K., Pibiri F., Zhang C., Badner J. A., Gershon E. S., Liu C., and Members of the Bipolar Disorder Genome Study (BiGS) Consortium, Two gene co-expression modules differentiate psychotics and controls. Mol. Psychiatry 18, 1308–1314 (2013).
48
Gachet C., Regulation of platelet functions by P2 receptors. Annu. Rev. Pharmacol. Toxicol. 46, 277–300 (2006).
49
Kujovich J. L., Factor V Leiden thrombophilia. Genet. Med. 13, 1–16 (2011).
50
Heit J. A., Cunningham J. M., Petterson T. M., Armasu S. M., Rider D. N., and DE Andrade M., Genetic variation within the anticoagulant, procoagulant, fibrinolytic and innate immunity pathways as risk factors for venous thromboembolism. J. Thromb. Haemost. 9, 1133–1142 (2011).
51
Purcell S., Cherny S. S., and Sham P. C., Genetic Power Calculator: Design of linkage and association genetic mapping studies of complex traits. Bioinformatics 19, 149–150 (2003).

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Science
Volume 351Issue 627412 February 2016
Pages: 737 - 741

History

Received: 10 August 2015
Accepted: 8 January 2016

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Corinne N. Simonti
Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN, USA.
Benjamin Vernot
Department of Genome Sciences, University of Washington, Seattle, WA, USA.
Lisa Bastarache
Department of Biomedical Informatics, Vanderbilt University, Nashville, TN, USA.
Erwin Bottinger
Mount Sinai School of Medicine, New York, NY, USA.
David S. Carrell
Department of Medicine (Medical Genetics), University of Washington Medical Center, Seattle, WA, USA.
Rex L. Chisholm
Center for Genetic Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
David R. Crosslin
Department of Genome Sciences, University of Washington, Seattle, WA, USA.
Department of Medicine (Medical Genetics), University of Washington Medical Center, Seattle, WA, USA.
Scott J. Hebbring
Center for Human Genetics, Marshfield Clinic, Marshfield, WI, USA.
Gail P. Jarvik
Department of Genome Sciences, University of Washington, Seattle, WA, USA.
Department of Medicine (Medical Genetics), University of Washington Medical Center, Seattle, WA, USA.
Iftikhar J. Kullo
Division of Cardiovascular Diseases, Mayo Clinic, Rochester, MN, USA.
Rongling Li
Division of Genomic Medicine, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA.
Jyotishman Pathak*
Division of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.
Marylyn D. Ritchie
Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, PA, USA.
Biomedical and Translational Informatics, Geisinger Health System, Danville, PA, USA.
Dan M. Roden
Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN, USA.
Department of Biomedical Informatics, Vanderbilt University, Nashville, TN, USA.
Department of Medicine, Vanderbilt University, Nashville, TN, USA.
Department of Pharmacology, Vanderbilt University, Nashville, TN, USA.
Shefali S. Verma
Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, PA, USA.
Gerard Tromp
Weis Center for Research, Geisinger Health System, Danville, PA, USA.
Division of Molecular Biology and Human Genetics, Department of Biomedical Sciences, Faculty of Health Science, Stellenbosch University, Tygerberg, South Africa.
Jeffrey D. Prato
Department of Biomedical Informatics, Vanderbilt University, Nashville, TN, USA.
William S. Bush
Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA.
Joshua M. Akey
Department of Genome Sciences, University of Washington, Seattle, WA, USA.
Joshua C. Denny
Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN, USA.
Department of Biomedical Informatics, Vanderbilt University, Nashville, TN, USA.
Department of Medicine, Vanderbilt University, Nashville, TN, USA.
John A. Capra
Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN, USA.
Department of Biomedical Informatics, Vanderbilt University, Nashville, TN, USA.
Department of Biological Sciences, Vanderbilt University, Nashville, TN, USA.
Center for Quantitative Sciences, Vanderbilt University, Nashville, TN, USA.

Notes

*
These authors contributed equally to this work.
Department of Healthcare Policy and Research, Weill Cornell Medical College, New York, NY, USA.
Corresponding author. E-mail: [email protected]

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Volume 351|Issue 6274
12 February 2016
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