Reviews in Endocrine and Metabolic Disorders

, Volume 20, Issue 3, pp 321–332 | Cite as

Genetics, adaptation to environmental changes and archaic admixture in the pathogenesis of diabetes mellitus in Indigenous Australians

  • Malgorzata Monika BrzozowskaEmail author
  • Essi Havula
  • Richard Benjamin Allen
  • Murray P. Cox


Indigenous Australians are particularly affected by type 2 diabetes mellitus (T2D) due to both their genetic susceptibility and a range of environmental and lifestyle risk factors. Recent genetic studies link predisposition to some diseases, including T2D, to alleles acquired from archaic hominins, such as Neanderthals and Denisovans, which persist in the genomes of modern humans today. Indo-Pacific human populations, including Indigenous Australians, remain extremely underrepresented in genomic research with a paucity of data examining the impact of Denisovan or Neanderthal lineages on human phenotypes in Oceania. The few genetic studies undertaken emphasize the uniqueness and antiquity of Indigenous Australian genomes, with possibly the largest proportion of Denisovan ancestry of any population in the world. In this review, we focus on the potential contributions of ancient genes/pathways to modern human phenotypes, while also highlighting the evolutionary roles of genetic adaptation to dietary and environmental changes associated with an adopted Western lifestyle. We discuss the role of genetic and epigenetic factors in the pathogenesis of T2D in understudied Indigenous Australians, including the potential impact of archaic gene lineages on this disease. Finally, we propose that greater understanding of the underlying genetic predisposition may contribute to the clinical efficacy of diabetes management in Indigenous Australians. We suggest that improved identification of T2D risk variants in Oceania is needed. Such studies promise to clarify how genetic and phenotypic differences vary between populations and, crucially, provide novel targets for personalised medical therapies in currently marginalized groups.


Archaic human genes Genome-wide association studies Obesity Diabetes mellitus Indigenous Australians 



We acknowledge the Bedegal and Gadigal peoples, the Traditional Custodians of the lands of the University of New South Wales and the University of Sydney, and we pay our respects to Elders past, present and future, both Bedegal, Gadigal and all Indigenous groups across Australia. We acknowledge the “structural nature of our problem”, as put forth in the Statement from the Heart. Just as Indigenous lands have always been a learning space for Aboriginal nations, one of the oldest knowledge systems in the world, we offer our knowledge from a western science perspective as a shared path to redressing past and ongoing healthcare wrongs.

Compliance with ethical standards

Conflict of interest

There are no supporting grants or conflicts of interest to declare.


  1. 1.
    Bommer C, Sagalova V, Heesemann E, Manne-Goehler J, Atun R, Barnighausen T, et al. Global Economic Burden of Diabetes in Adults: Projections From 2015 to 2030. Diabetes Care. 2018;41(5):963–70.PubMedPubMedCentralGoogle Scholar
  2. 2.
    Zimmet PZ, Magliano DJ, Herman WH, Shaw JE. Diabetes: a 21st century challenge. Lancet Diabetes Endocrinol. 2014;2(1):56–64.PubMedPubMedCentralGoogle Scholar
  3. 3.
    Hoy WE, Kondalsamy-Chennakesavan S, Wang Z, Briganti E, Shaw J, Polkinghorne K, et al. Quantifying the excess risk for proteinuria, hypertension and diabetes in Australian Aborigines: comparison of profiles in three remote communities in the Northern Territory with those in the AusDiab study. Aust N Z J Public Health. 2007;31(2):177–83.PubMedPubMedCentralGoogle Scholar
  4. 4.
    Davis TM, McAullay D, Davis WA, Bruce DG. Characteristics and outcome of type 2 diabetes in urban Aboriginal people: the Fremantle Diabetes Study. Intern Med J. 2007;37(1):59–63.PubMedPubMedCentralGoogle Scholar
  5. 5.
    Demaio A, Drysdale M, de Courten M. Appropriate health promotion for Australian Aboriginal and Torres Strait Islander communities: crucial for closing the gap. Glob Health Promot. 2012;19(2):58–62.PubMedPubMedCentralGoogle Scholar
  6. 6.
    Reich D, Green RE, Kircher M, Krause J, Patterson N, Durand EY, et al. Genetic history of an archaic hominin group from Denisova Cave in Siberia. Nature. 2010;468(7327):1053–60.PubMedPubMedCentralGoogle Scholar
  7. 7.
    Reich D, Patterson N, Kircher M, Delfin F, Nandineni MR, Pugach I, et al. Denisova admixture and the first modern human dispersals into Southeast Asia and Oceania. Am J Hum Genet. 2011;89(4):516–28.PubMedPubMedCentralGoogle Scholar
  8. 8.
    Sankararaman S, Patterson N, Li H, Paabo S, Reich D. The date of interbreeding between Neandertals and modern humans. PLoS Genet. 2012;8(10):e1002947.PubMedPubMedCentralGoogle Scholar
  9. 9.
    Sankararaman S, Mallick S, Dannemann M, Prufer K, Kelso J, Paabo S, et al. The genomic landscape of Neanderthal ancestry in present-day humans. Nature. 2014;507(7492):354–7.PubMedPubMedCentralGoogle Scholar
  10. 10.
    Popejoy AB, Fullerton SM. Genomics is failing on diversity. Nature. 2016;538(7624):161–4.PubMedPubMedCentralGoogle Scholar
  11. 11.
    Sankararaman S, Mallick S, Patterson N, Reich D. The Combined Landscape of Denisovan and Neanderthal Ancestry in Present-Day Humans. Curr Biol. 2016;26(9):1241–7.PubMedPubMedCentralGoogle Scholar
  12. 12.
    Simonti CN, Vernot B, Bastarache L, Bottinger E, Carrell DS, Chisholm RL, et al. The phenotypic legacy of admixture between modern humans and Neandertals. Science. 2016;351(6274):737–41.PubMedPubMedCentralGoogle Scholar
  13. 13.
    Tobler R, Rohrlach A, Soubrier J, Bover P, Llamas B, Tuke J, et al. Aboriginal mitogenomes reveal 50,000 years of regionalism in Australia. Nature. 2017;544(7649):180–4.Google Scholar
  14. 14.
    Jacobs GS, Hudjashov G, Saag L, Kusuma P, Darusallam CC, Lawson DJ, et al. Multiple Deeply Divergent Denisovan Ancestries in Papuans. Cell. 2019;177(4):1010–21e32.Google Scholar
  15. 15.
    Consortium STD, Williams AL, Jacobs SB, Moreno-Macias H, Huerta-Chagoya A, Churchhouse C, et al. Sequence variants in SLC16A11 are a common risk factor for type 2 diabetes in Mexico. Nature. 2014;506(7486):97–101.Google Scholar
  16. 16.
    Vernot B, Akey JM. Resurrecting surviving Neandertal lineages from modern human genomes. Science. 2014;343(6174):1017–21.Google Scholar
  17. 17.
    Gibbons A. Human Evolution Neandertal genes linked to modern diseases. Science. 2016;351(6274):648–9.PubMedPubMedCentralGoogle Scholar
  18. 18.
    Busfield F, Duffy DL, Kesting JB, Walker SM, Lovelock PK, Good D, et al. A genomewide search for type 2 diabetes-susceptibility genes in indigenous Australians. Am J Hum Genet. 2002;70(2):349–57.PubMedPubMedCentralGoogle Scholar
  19. 19.
    Daniel M, Rowley KG, McDermott R, O'Dea K. Diabetes and impaired glucose tolerance in Aboriginal Australians: prevalence and risk. Diabetes Res Clin Pract. 2002;57(1):23–33.PubMedPubMedCentralGoogle Scholar
  20. 20.
    O'Dea K, Rowley KG, Brown A. Diabetes in Indigenous Australians: possible ways forward. The MJA. 2007;186(10):494–5.PubMedPubMedCentralGoogle Scholar
  21. 21.
    Anderson D, Cordell HJ, Fakiola M, Francis RW, Syn G, Scaman ES, et al. First genome-wide association study in an Australian aboriginal population provides insights into genetic risk factors for body mass index and type 2 diabetes. PLoS One. 2015;10(3):e0119333.PubMedPubMedCentralGoogle Scholar
  22. 22.
    McCoy RC, Wakefield J, Akey JM. Impacts of Neanderthal-Introgressed Sequences on the Landscape of Human Gene Expression. Cell. 2017;168(5):916–27 e12.PubMedPubMedCentralGoogle Scholar
  23. 23.
    Williams DR, Moffitt PS, Fisher JS, Bashir HV. Diabetes and glucose tolerance in New South Wales coastal Aborigines: possible effects of non-Aboriginal genetic admixture. Diabetologia. 1987;30(2):72–7.PubMedPubMedCentralGoogle Scholar
  24. 24.
    Neel JV. The "thrifty genotype" in 1998. Nutr Rev. 1999;57(5 Pt 2):S2–9.PubMedPubMedCentralGoogle Scholar
  25. 25.
    Cordain L, Miller JB, Eaton SB, Mann N, Holt SH, Speth JD. Plant-animal subsistence ratios and macronutrient energy estimations in worldwide hunter-gatherer diets. Am J Clin Nutr. 2000;71(3):682–92.PubMedPubMedCentralGoogle Scholar
  26. 26.
    Xu B, Goulding EH, Zang K, Cepoi D, Cone RD, Jones KR, et al. Brain-derived neurotrophic factor regulates energy balance downstream of melanocortin-4 receptor. Nat Neurosci. 2003;6(7):736–42.PubMedPubMedCentralGoogle Scholar
  27. 27.
    Prentice AM. Early influences on human energy regulation: thrifty genotypes and thrifty phenotypes. Physiol Behav. 2005;86(5):640–5.PubMedPubMedCentralGoogle Scholar
  28. 28.
    Dabelea D, Mayer-Davis EJ, Lamichhane AP, D'Agostino RB Jr, Liese AD, Vehik KS, et al. Association of intrauterine exposure to maternal diabetes and obesity with type 2 diabetes in youth: the SEARCH Case-Control Study. Diabetes Care. 2008;31(7):1422–6.PubMedPubMedCentralGoogle Scholar
  29. 29.
    Heijmans BT, Tobi EW, Stein AD, Putter H, Blauw GJ, Susser ES, et al. Persistent epigenetic differences associated with prenatal exposure to famine in humans. Proc Natl Acad Sci U S A. 2008;105(44):17046–9.PubMedPubMedCentralGoogle Scholar
  30. 30.
    Prentice AM, Hennig BJ, Fulford AJ. Evolutionary origins of the obesity epidemic: natural selection of thrifty genes or genetic drift following predation release? Int J Obes. 2008;32(11):1607–10.Google Scholar
  31. 31.
    Speakman JR. Thrifty genes for obesity, an attractive but flawed idea, and an alternative perspective: the 'drifty gene' hypothesis. Int J Obes. 2008;32(11):1611–7.Google Scholar
  32. 32.
    Ayub Q, Moutsianas L, Chen Y, Panoutsopoulou K, Colonna V, Pagani L, et al. Revisiting the thrifty gene hypothesis via 65 loci associated with susceptibility to type 2 diabetes. Am J Hum Genet. 2014;94(2):176–85.PubMedPubMedCentralGoogle Scholar
  33. 33.
    Chamberlain C, Banks E, Joshy G, Diouf I, Oats JJ, Gubhaju L, et al. Prevalence of gestational diabetes mellitus among Indigenous women and comparison with non-Indigenous Australian women: 1990–2009. Aust N Z J Obstet Gynaecol. 2014;54(5):433–40.Google Scholar
  34. 34.
    Chamberlain CR, Oldenburg B, Wilson AN, Eades SJ, O'Dea K, Oats JJ, et al. Type 2 diabetes after gestational diabetes: greater than fourfold risk among Indigenous compared with non-Indigenous Australian women. Diabetes Metab Res Rev. 2016;32(2):217–27.Google Scholar
  35. 35.
    Ruhli F, van Schaik K, Henneberg M. Evolutionary Medicine: The Ongoing Evolution of Human Physiology and Metabolism. Physiology (Bethesda). 2016;31(6):392–7.Google Scholar
  36. 36.
    Wang G, Speakman JR. Analysis of Positive Selection at Single Nucleotide Polymorphisms Associated with Body Mass Index Does Not Support the "Thrifty Gene" Hypothesis. Cell Metab. 2016;24(4):531–41.Google Scholar
  37. 37.
    Xue A, Wu Y, Zhu Z, Zhang F, Kemper KE, Zheng Z, et al. Genome-wide association analyses identify 143 risk variants and putative regulatory mechanisms for type 2 diabetes. Nat Commun. 2018;9(1):2941.PubMedPubMedCentralGoogle Scholar
  38. 38.
    Titmuss A, Davis EA, Brown A, Maple-Brown LJ. Emerging diabetes and metabolic conditions among Aboriginal and Torres Strait Islander young people. MJA. 2019;210(3):111–3 e1.Google Scholar
  39. 39.
    Rogers AR, Bohlender RJ, Huff CD. Early history of Neanderthals and Denisovans. Proc Natl Acad Sci U S A. 2017;114(37):9859–63.PubMedPubMedCentralGoogle Scholar
  40. 40.
    Pennisi E. Human evolution. More genomes from Denisova Cave show mixing of early human groups. Science. 2013;340(6134):799.Google Scholar
  41. 41.
    Juric I, Aeschbacher S, Coop G. The Strength of Selection against Neanderthal Introgression. PLoS Genet. 2016;12(11):e1006340.PubMedPubMedCentralGoogle Scholar
  42. 42.
    Green RE, Krause J, Briggs AW, Maricic T, Stenzel U, Kircher M, et al. A draft sequence of the Neandertal genome. Science. 2010;328(5979):710–22.PubMedPubMedCentralGoogle Scholar
  43. 43.
    Prufer K, Racimo F, Patterson N, Jay F, Sankararaman S, Sawyer S, et al. The complete genome sequence of a Neanderthal from the Altai Mountains. Nature. 2014;505(7481):43–9.Google Scholar
  44. 44.
    Martin SH, Jiggins CD. Interpreting the genomic landscape of introgression. Curr Opin Genet Dev. 2017;47:69–74.Google Scholar
  45. 45.
    Barton N, Bengtsson BO. The barrier to genetic exchange between hybridising populations. Heredity (Edinb). 1986;57 ( Pt 3:357–76.Google Scholar
  46. 46.
    Malaspinas AS, Westaway MC, Muller C, Sousa VC, Lao O, Alves I, et al. A genomic history of Aboriginal Australia. Nature. 2016;538(7624):207–14.Google Scholar
  47. 47.
    Meyer M, Kircher M, Gansauge MT, Li H, Racimo F, Mallick S, et al. A high-coverage genome sequence from an archaic Denisovan individual. Science. 2012;338(6104):222–6.PubMedPubMedCentralGoogle Scholar
  48. 48.
    Taskent RO, Alioglu ND, Fer E, Melike Donertas H, Somel M, Gokcumen O. Variation and Functional Impact of Neanderthal Ancestry in Western Asia. Genome Biol Evol. 2017;9(12):3516–24.PubMedPubMedCentralGoogle Scholar
  49. 49.
    Band G, Le QS, Jostins L, Pirinen M, Kivinen K, Jallow M, et al. Imputation-based meta-analysis of severe malaria in three African populations. PLoS Genet. 2013;9(5):e1003509.PubMedPubMedCentralGoogle Scholar
  50. 50.
    Dolgova O, Lao O. Evolutionary and Medical Consequences of Archaic Introgression into Modern Human Genomes. Genes (Basel). 2018;9(7).Google Scholar
  51. 51.
    Gianfrancesco F, Esposito T, Casu G, Maninchedda G, Roberto R, Pirastu M. Emergence of Talanin protein associated with human uric acid nephrolithiasis in the Hominidae lineage. Gene. 2004;339:131–8.PubMedPubMedCentralGoogle Scholar
  52. 52.
    Khrameeva EE, Bozek K, He L, Yan Z, Jiang X, Wei Y, et al. Neanderthal ancestry drives evolution of lipid catabolism in contemporary Europeans. Nat Commun. 2014;5:3584.PubMedPubMedCentralGoogle Scholar
  53. 53.
    Dannemann M, Andres AM, Kelso J. Introgression of Neandertal- and Denisovan-like Haplotypes Contributes to Adaptive Variation in Human Toll-like Receptors. Am J Hum Genet. 2016;98(1):22–33.PubMedPubMedCentralGoogle Scholar
  54. 54.
    Akira S, Uematsu S, Takeuchi O. Pathogen recognition and innate immunity. Cell. 2006;124(4):783–801.PubMedPubMedCentralGoogle Scholar
  55. 55.
    Westwell-Roper C, Nackiewicz D, Dan M, Ehses JA. Toll-like receptors and NLRP3 as central regulators of pancreatic islet inflammation in type 2 diabetes. Immunol Cell Biol. 2014;92(4):314–23.PubMedPubMedCentralGoogle Scholar
  56. 56.
    Sepehri Z, Kiani Z, Nasiri AA, Mashhadi MA, Javadian F, Haghighi A, et al. Human Toll like receptor 4 gene expression of PBMCs in diabetes mellitus type 2 patients. Cell Mol Biol (Noisy-le-grand). 2015;61(3):92–5.Google Scholar
  57. 57.
    Adegbija O, Hoy WE, Wang Z. Corresponding waist circumference and body mass index values based on 10-years absolute type 2 diabetes risk in an Australian Aboriginal community. BMJ Open Diabetes Res Care. 2015;3(1):e000127.PubMedPubMedCentralGoogle Scholar
  58. 58.
    Lyssenko V, Jonsson A, Almgren P, Pulizzi N, Isomaa B, Tuomi T, et al. Clinical risk factors, DNA variants, and the development of type 2 diabetes. N Engl J Med. 2008;359(21):2220–32.Google Scholar
  59. 59.
    McCarthy MI. Genomics, type 2 diabetes, and obesity. N Engl J Med. 2010;363(24):2339–50.PubMedPubMedCentralGoogle Scholar
  60. 60.
    Vionnet N, Hani EH, Lesage S, Philippi A, Hager J, Varret M, et al. Genetics of NIDDM in France: studies with 19 candidate genes in affected sib pairs. Diabetes. 1997;46(6):1062–8.PubMedPubMedCentralGoogle Scholar
  61. 61.
    Hemming R, Agatep R, Badiani K, Wyant K, Arthur G, Gietz RD, et al. Human growth factor receptor bound 14 binds the activated insulin receptor and alters the insulin-stimulated tyrosine phosphorylation levels of multiple proteins. Biochem Cell Biol. 2001;79(1):21–32.PubMedPubMedCentralGoogle Scholar
  62. 62.
    Khan A, Hong-Lie C, Landau BR. Glucose-6-phosphatase activity in islets from ob/ob and lean mice and the effect of dexamethasone. Endocrinology. 1995;136(5):1934–8.PubMedPubMedCentralGoogle Scholar
  63. 63.
    Goodarzi MO, Guo X, Taylor KD, Quinones MJ, Saad MF, Yang H, et al. Lipoprotein lipase is a gene for insulin resistance in Mexican Americans. Diabetes. 2004;53(1):214–20.PubMedPubMedCentralGoogle Scholar
  64. 64.
    Ragolia L, Begum N. Protein phosphatase-1 and insulin action. Mol Cell Biochem. 1998;182(1–2):49–58.PubMedPubMedCentralGoogle Scholar
  65. 65.
    Loos RJ, Lindgren CM, Li S, Wheeler E, Zhao JH, Prokopenko I, et al. Common variants near MC4R are associated with fat mass, weight and risk of obesity. Nat Genet. 2008;40(6):768–75.PubMedPubMedCentralGoogle Scholar
  66. 66.
    Willer CJ, Speliotes EK, Loos RJ, Li S, Lindgren CM, Heid IM, et al. Six new loci associated with body mass index highlight a neuronal influence on body weight regulation. Nat Genet. 2009;41(1):25–34.PubMedPubMedCentralGoogle Scholar
  67. 67.
    Chambers JC, Elliott P, Zabaneh D, Zhang W, Li Y, Froguel P, et al. Common genetic variation near MC4R is associated with waist circumference and insulin resistance. Nat Genet. 2008;40(6):716–8.PubMedPubMedCentralGoogle Scholar
  68. 68.
    Diabetes Genetics Initiative of Broad Institute of H, Mit LU, Novartis Institutes of BioMedical R, Saxena R, Voight BF, Lyssenko V, et al. Genome-wide association analysis identifies loci for type 2 diabetes and triglyceride levels. Science. 2007;316(5829):1331–6.Google Scholar
  69. 69.
    Scott LJ, Mohlke KL, Bonnycastle LL, Willer CJ, Li Y, Duren WL, et al. A genome-wide association study of type 2 diabetes in Finns detects multiple susceptibility variants. Science. 2007;316(5829):1341–5.PubMedPubMedCentralGoogle Scholar
  70. 70.
    Zeggini E, Weedon MN, Lindgren CM, Frayling TM, Elliott KS, Lango H, et al. Replication of genome-wide association signals in UK samples reveals risk loci for type 2 diabetes. Science. 2007;316(5829):1336–41.PubMedPubMedCentralGoogle Scholar
  71. 71.
    Daimon M, Sato H, Oizumi T, Toriyama S, Saito T, Karasawa S, et al. Association of the PIK3C2G gene polymorphisms with type 2 DM in a Japanese population. Biochem Biophys Res Commun. 2008;365(3):466–71.PubMedPubMedCentralGoogle Scholar
  72. 72.
    Poliak S, Gollan L, Martinez R, Custer A, Einheber S, Salzer JL, et al. Caspr2, a new member of the neurexin superfamily, is localized at the juxtaparanodes of myelinated axons and associates with K+ channels. Neuron. 1999;24(4):1037–47.PubMedPubMedCentralGoogle Scholar
  73. 73.
    Kramps T, Peter O, Brunner E, Nellen D, Froesch B, Chatterjee S, et al. Wnt/wingless signaling requires BCL9/legless-mediated recruitment of pygopus to the nuclear beta-catenin-TCF complex. Cell. 2002;109(1):47–60.PubMedPubMedCentralGoogle Scholar
  74. 74.
    Jin T. Current Understanding on Role of the Wnt Signaling Pathway Effector TCF7L2 in Glucose Homeostasis. Endocr Rev. 2016;37(3):254–77.PubMedPubMedCentralGoogle Scholar
  75. 75.
    Ilich JZ, Kelly OJ, Kim Y, Spicer MT. Low-grade chronic inflammation perpetuated by modern diet as a promoter of obesity and osteoporosis. Arhiv za higijenu rada i toksikologiju. 2014;65(2):139–48.PubMedPubMedCentralGoogle Scholar
  76. 76.
    Eaton SB, Konner M, Shostak M. Stone agers in the fast lane: chronic degenerative diseases in evolutionary perspective. Am J Med. 1988;84(4):739–49.PubMedPubMedCentralGoogle Scholar
  77. 77.
    Gracey M, Bridge E, Martin D, Jones T, Spargo RM, Shephard M, et al. An Aboriginal-driven program to prevent, control and manage nutrition-related "lifestyle" diseases including diabetes. Asia Pac J Clin Nutr. 2006;15(2):178–88.PubMedPubMedCentralGoogle Scholar
  78. 78.
    Genne-Bacon EA. Thinking evolutionarily about obesity. Yale J Biol Med. 2014;87(2):99–112.PubMedPubMedCentralGoogle Scholar
  79. 79.
    Frisch RE. Fatness, menarche, and female fertility. Perspect Biol Med. 1985;28(4):611–33.PubMedPubMedCentralGoogle Scholar
  80. 80.
    Aschard H, Chen J, Cornelis MC, Chibnik LB, Karlson EW, Kraft P. Inclusion of gene-gene and gene-environment interactions unlikely to dramatically improve risk prediction for complex diseases. Am J Hum Genet. 2012;90(6):962–72.PubMedPubMedCentralGoogle Scholar
  81. 81.
    Stenzel SL, Ahn J, Boonstra PS, Gruber SB, Mukherjee B. The impact of exposure-biased sampling designs on detection of gene-environment interactions in case-control studies with potential exposure misclassification. Eur J Epidemiol. 2015;30(5):413–23.PubMedPubMedCentralGoogle Scholar
  82. 82.
    Baschetti R. Diabetes epidemic in newly westernized populations: is it due to thrifty genes or to genetically unknown foods? J R Soc Med. 1998;91(12):622–5.PubMedPubMedCentralGoogle Scholar
  83. 83.
    O'Dea K. Marked improvement in carbohydrate and lipid metabolism in diabetic Australian aborigines after temporary reversion to traditional lifestyle. Diabetes. 1984;33(6):596–603.PubMedPubMedCentralGoogle Scholar
  84. 84.
    Vaag AA, Grunnet LG, Arora GP, Brons C. The thrifty phenotype hypothesis revisited. Diabetologia. 2012;55(8):2085–8.PubMedPubMedCentralGoogle Scholar
  85. 85.
    Fuchsberger C, Flannick J, Teslovich TM, Mahajan A, Agarwala V, Gaulton KJ, et al. The genetic architecture of type 2 diabetes. Nature. 2016;536(7614):41–7.PubMedPubMedCentralGoogle Scholar
  86. 86.
    Field Y, Boyle EA, Telis N, Gao Z, Gaulton KJ, Golan D, et al. Detection of human adaptation during the past 2000 years. Science. 2016;354(6313):760–4.PubMedPubMedCentralGoogle Scholar
  87. 87.
    Sebastio G, Villa M, Sartorio R, Guzzetta V, Poggi V, Auricchio S, et al. Control of lactase in human adult-type hypolactasia and in weaning rabbits and rats. Am J Hum Genet. 1989;45(4):489–97.PubMedPubMedCentralGoogle Scholar
  88. 88.
    Ingram CJ, Mulcare CA, Itan Y, Thomas MG, Swallow DM. Lactose digestion and the evolutionary genetics of lactase persistence. Hum Genet. 2009;124(6):579–91.PubMedPubMedCentralGoogle Scholar
  89. 89.
    Itan Y, Jones BL, Ingram CJ, Swallow DM, Thomas MG. A worldwide correlation of lactase persistence phenotype and genotypes. BMC Evol Biol. 2010;10:36.PubMedPubMedCentralGoogle Scholar
  90. 90.
    Bersaglieri T, Sabeti PC, Patterson N, Vanderploeg T, Schaffner SF, Drake JA, et al. Genetic signatures of strong recent positive selection at the lactase gene. Am J Hum Genet. 2004;74(6):1111–20.PubMedPubMedCentralGoogle Scholar
  91. 91.
    Enattah NS, Sahi T, Savilahti E, Terwilliger JD, Peltonen L, Jarvela I. Identification of a variant associated with adult-type hypolactasia. Nat Genet. 2002;30(2):233–7.Google Scholar
  92. 92.
    Evershed RP, Payne S, Sherratt AG, Copley MS, Coolidge J, Urem-Kotsu D, et al. Earliest date for milk use in the Near East and southeastern Europe linked to cattle herding. Nature. 2008;455(7212):528–31.Google Scholar
  93. 93.
    Tishkoff SA, Reed FA, Ranciaro A, Voight BF, Babbitt CC, Silverman JS, et al. Convergent adaptation of human lactase persistence in Africa and Europe. Nat Genet. 2007;39(1):31–40.Google Scholar
  94. 94.
    Perry GH, Dominy NJ, Claw KG, Lee AS, Fiegler H, Redon R, et al. Diet and the evolution of human amylase gene copy number variation. Nat Genet. 2007;39(10):1256–60.PubMedPubMedCentralGoogle Scholar
  95. 95.
    Santos JL, Saus E, Smalley SV, Cataldo LR, Alberti G, Parada J, et al. Copy number polymorphism of the salivary amylase gene: implications in human nutrition research. J Nutrigenet Nutrigenomics. 2012;5(3):117–31.Google Scholar
  96. 96.
    Luca F, Bubba G, Basile M, Brdicka R, Michalodimitrakis E, Rickards O, et al. Multiple advantageous amino acid variants in the NAT2 gene in human populations. PLoS One. 2008;3(9):e3136.PubMedPubMedCentralGoogle Scholar
  97. 97.
    Hancock AM, Witonsky DB, Ehler E, Alkorta-Aranburu G, Beall C, Gebremedhin A, et al. Colloquium paper: human adaptations to diet, subsistence, and ecoregion are due to subtle shifts in allele frequency. Proc Natl Acad Sci U S A. 2010;107(Suppl 2):8924–30.PubMedPubMedCentralGoogle Scholar
  98. 98.
    Kernie SG, Liebl DJ, Parada LF. BDNF regulates eating behavior and locomotor activity in mice. EMBO J. 2000;19(6):1290–300.PubMedPubMedCentralGoogle Scholar
  99. 99.
    Gray J, Yeo G, Hung C, Keogh J, Clayton P, Banerjee K, et al. Functional characterization of human NTRK2 mutations identified in patients with severe early-onset obesity. Int J Obes. 2007;31(2):359–64.Google Scholar
  100. 100.
    Yilmaz Z, Kaplan AS, Tiwari AK, Levitan RD, Piran S, Bergen AW, et al. The role of leptin, melanocortin, and neurotrophin system genes on body weight in anorexia nervosa and bulimia nervosa. J Psychiatr Res. 2014;55:77–86.PubMedPubMedCentralGoogle Scholar
  101. 101.
    Peyregne S, Boyle MJ, Dannemann M, Prufer K. Detecting ancient positive selection in humans using extended lineage sorting. Genome Res. 2017;27(9):1563–72.PubMedPubMedCentralGoogle Scholar
  102. 102.
    Ruhli FJ, Henneberg M. New perspectives on evolutionary medicine: the relevance of microevolution for human health and disease. BMC Med. 2013;11:115.PubMedPubMedCentralGoogle Scholar
  103. 103.
    Grafen A. Biological fitness and the fundamental theorem of natural selection. Am Nat. 2015;186(1):1–14.PubMedPubMedCentralGoogle Scholar
  104. 104.
    Piegorsch WW. Fisher's contributions to genetics and heredity, with special emphasis on the Gregor Mendel controversy. Biometrics. 1990;46(4):915–24.PubMedPubMedCentralGoogle Scholar
  105. 105.
    Henneberg MPJ. Biological state index of human groups. Przeglad Antropologiczny. 1975;41:191–201.Google Scholar
  106. 106.
    (AIHW) AIoHaW. National (insulin-treated) Diabetes Register (2016)Google Scholar
  107. 107.
    Marrack P, Kappler J, Kotzin BL. Autoimmune disease: why and where it occurs. Nat Med. 2001;7(8):899–905.Google Scholar
  108. 108.
    Pociot F. Type 1 diabetes genome-wide association studies: not to be lost in translation. Clin Transl Immunology. 2017;6(12):e162.PubMedPubMedCentralGoogle Scholar
  109. 109.
    Huo L, Harding JL, Peeters A, Shaw JE, Magliano DJ. Life expectancy of type 1 diabetic patients during 1997–2010: a national Australian registry-based cohort study. Diabetologia. 2016;59(6):1177–85.Google Scholar
  110. 110.
    Livingstone SJ, Levin D, Looker HC, Lindsay RS, Wild SH, Joss N, et al. Estimated life expectancy in a Scottish cohort with type 1 diabetes, 2008–2010. JAMA. 2015;313(1):37–44.PubMedPubMedCentralGoogle Scholar
  111. 111.
    Wiebe JC, Santana A, Medina-Rodriguez N, Hernandez M, Novoa J, Mauricio D, et al. Fertility is reduced in women and in men with type 1 diabetes: results from the Type 1 Diabetes Genetics Consortium (T1DGC). Diabetologia. 2014;57(12):2501–4.PubMedPubMedCentralGoogle Scholar
  112. 112.
    Elhamamsy AR. DNA methylation dynamics in plants and mammals: overview of regulation and dysregulation. Cell Biochem Funct. 2016;34(5):289–98.PubMedPubMedCentralGoogle Scholar
  113. 113.
    Ling C, Ronn T. Epigenetics in Human Obesity and Type 2 Diabetes. Cell Metab. 2019;29(5):1028–44.PubMedPubMedCentralGoogle Scholar
  114. 114.
    Dabelea D, Hanson RL, Lindsay RS, Pettitt DJ, Imperatore G, Gabir MM, et al. Intrauterine exposure to diabetes conveys risks for type 2 diabetes and obesity: a study of discordant sibships. Diabetes. 2000;49(12):2208–11.PubMedPubMedCentralGoogle Scholar
  115. 115.
    Roseboom T, de Rooij S, Painter R. The Dutch famine and its long-term consequences for adult health. Early Hum Dev. 2006;82(8):485–91.PubMedPubMedCentralGoogle Scholar
  116. 116.
    Chen P, Piaggi P, Traurig M, Bogardus C, Knowler WC, Baier LJ, et al. Differential methylation of genes in individuals exposed to maternal diabetes in utero. Diabetologia. 2017;60(4):645–55.PubMedPubMedCentralGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Endocrinology DepartmentSutherland HospitalSydneyAustralia
  2. 2.St George & Sutherland Hospital Clinical SchoolUniversity of New South WalesSydneyAustralia
  3. 3.School of Life and Environmental Sciences, Charles Perkins CentreUniversity of SydneySydneyAustralia
  4. 4.The Palaeogenomics and Bio-Archaeology Research Network, Research Laboratory for Archaeology and History of ArtUniversity of OxfordOxfordUK
  5. 5.Statistics and Bioinformatics Group, School of Fundamental SciencesMassey UniversityPalmerston NorthNew Zealand

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