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Annual Review of Medicine

Volume 72, 2021

Defining and Classifying New Subgroups of Diabetes

Abstract

An etiologically based classification of diabetes is needed to account for the heterogeneity of type 1 and type 2 diabetes (T1D and T2D) and emerging forms of diabetes worldwide. It may be productive for both classification and clinical discovery to consider variant forms of diabetes as a spectrum. Maturity onset diabetes of youth and neonatal diabetes serve as models for etiologically defined, rare forms of diabetes in the spectrum. Ketosis-prone diabetes is a model for more complex forms, amenable to phenotypic dissection. Bioinformatic approaches such as clustering analyses of large datasets and multi-omics investigations of rare and atypical phenotypes are promising avenues to explore and define new subgroups of diabetes.

Keyword(s): atypical diabetes, beta cell, clustering, insulin resistance, ketosis-prone diabetes, monogenic diabetes
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2021-01-27
2024-04-19
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Literature Cited

  1. 1. 
    Balasubramanyam A, Nalini R, Hampe CS et al. 2008. Syndromes of ketosis-prone diabetes mellitus. Endocr. Rev. 29:292–302
     [Google Scholar]
  2. 2. 
    Balasubramanyam A, Tandon N, Yajnik CS 2011. Non-traditional forms of diabetes worldwide: implications for translational investigation. Translational Endocrinology & Metabolism: Type 2 Diabetes Update AC Powers 43–67 Washington, DC: Endocr. Soc.
     [Google Scholar]
  3. 3. 
    Am. Diabetes Assoc 2020. 2. Classification and diagnosis of diabetes: standards of medical care in diabetes—2020. Diabetes Care 43:S14–S31
     [Google Scholar]
  4. 4. 
    Hattersley AT, Patel KA. 2017. Precision diabetes: learning from monogenic diabetes. Diabetologia 60:769–77
     [Google Scholar]
  5. 5. 
    Pieralice S, Pozzilli P. 2018. Latent autoimmune diabetes in adults: a review on clinical implications and management. Diabetes Metab. J. 42:451–64
     [Google Scholar]
  6. 6. 
    Andersen MK, Hansen T. 2019. Genetic aspects of latent autoimmune diabetes in adults: a mini-review. Curr. Diabetes Rev. 15:194–98
     [Google Scholar]
  7. 7. 
    Turner R, Stratton I, Horton V et al. 1997. UKPDS 25: autoantibodies to islet-cell cytoplasm and glutamic acid decarboxylase for prediction of insulin requirement in type 2 diabetes. UK Prospective Diabetes Study Group. Lancet 350:1288–93
     [Google Scholar]
  8. 8. 
    Davis TM, Wright AD, Mehta ZM et al. 2005. Islet autoantibodies in clinically diagnosed type 2 diabetes: prevalence and relationship with metabolic control (UKPDS 70). Diabetologia 48:695–702
     [Google Scholar]
  9. 9. 
    Zinman B, Kahn SE, Haffner SM et al. 2004. Phenotypic characteristics of GAD antibody-positive recently diagnosed patients with type 2 diabetes in North America and Europe. Diabetes 53:3193–200
     [Google Scholar]
  10. 10. 
    Pilla SJ, Balasubramanyam A, Knowler WC et al. 2018. Islet autoantibody positivity in overweight and obese adults with type 2 diabetes. Autoimmunity 51:408–16
     [Google Scholar]
  11. 11. 
    van Deutekom AW, Heine RJ, Simsek S 2008. The islet autoantibody titres: their clinical relevance in latent autoimmune diabetes in adults (LADA) and the classification of diabetes mellitus. Diabet. Med 25:117–25
     [Google Scholar]
  12. 12. 
    Monge L, Bruno G, Pinach S et al. 2004. A clinically orientated approach increases the efficiency of screening for latent autoimmune diabetes in adults (LADA) in a large clinic-based cohort of patients with diabetes onset over 50 years. Diabet. Med. 21:456–59
     [Google Scholar]
  13. 13. 
    Liu L, Li X, Xiang Y et al. 2015. Latent autoimmune diabetes in adults with low-titer GAD antibodies: similar disease progression with type 2 diabetes: a nationwide, multicenter prospective study (LADA China Study 3). Diabetes Care 38:16–21
     [Google Scholar]
  14. 14. 
    Herold KC, Brooks-Worrell B, Palmer J et al. 2009. Validity and reproducibility of measurement of islet autoreactivity by T-cell assays in subjects with early type 1 diabetes. Diabetes 58:2588–95
     [Google Scholar]
  15. 15. 
    Brooks-Worrell BM, Reichow JL, Goel A et al. 2011. Identification of autoantibody-negative autoimmune type 2 diabetic patients. Diabetes Care 34:168–73
     [Google Scholar]
  16. 16. 
    Brooks-Worrell B, Hampe CS, Hattery EG et al. 2020. Islet autoimmunity is highly prevalent and associated with diminished beta cell function in type 2 diabetes patients in the GRADE Study Paper presented at the 80th American Diabetes Association Annual Science Sessions, online, June 12–16. Abstr. 254-OR
  17. 17. 
    Rostambeigi N, Shaw JE, Atkins RC et al. 2010. Waist circumference has heterogeneous impact on development of diabetes in different populations: longitudinal comparative study between Australia and Iran. Diabetes Res. Clin. Pract. 88:117–24
     [Google Scholar]
  18. 18. 
    Birkeland KI, Kilhovd B, Thorsby P et al. 2003. Heterogeneity of non-insulin-dependent diabetes expressed as variability in insulin sensitivity, beta-cell function and cardiovascular risk profile. Diabet. Med. 20:37–45
     [Google Scholar]
  19. 19. 
    Cho SB, Kim SC, Chung MG 2019. Identification of novel population clusters with different susceptibilities to type 2 diabetes and their impact on the prediction of diabetes. Sci. Rep. 9:3329
     [Google Scholar]
  20. 20. 
    Ryoo H, Woo J, Kim Y et al. 2011. Heterogeneity of genetic associations of CDKAL1 and HHEX with susceptibility of type 2 diabetes mellitus by gender. Eur. J. Hum. Genet. 19:672–75
     [Google Scholar]
  21. 21. 
    Timpson NJ, Lindgren CM, Weedon MN et al. 2009. Adiposity-related heterogeneity in patterns of type 2 diabetes susceptibility observed in genome-wide association data. Diabetes 58:505–10
     [Google Scholar]
  22. 22. 
    Kong X, Xing X, Hong J et al. 2016. Genetic variants associated with lean and obese type 2 diabetes in a Han Chinese population: a case-control study. Medicine 95:e3841
     [Google Scholar]
  23. 23. 
    Ng MC, Park KS, Oh B et al. 2008. Implication of genetic variants near TCF7L2, SLC30A8, HHEX, CDKAL1, CDKN2A/B, IGF2BP2, and FTO in type 2 diabetes and obesity in 6,719 Asians. Diabetes 57:2226–33
     [Google Scholar]
  24. 24. 
    Perry JR, Voight BF, Yengo L et al. 2012. Stratifying type 2 diabetes cases by BMI identifies genetic risk variants in LAMA1 and enrichment for risk variants in lean compared to obese cases. PLOS Genet 8:e1002741
     [Google Scholar]
  25. 25. 
    Wium C, Eggesbø HB, Ueland T et al. 2014. Adipose tissue distribution in relation to insulin sensitivity and inflammation in Pakistani and Norwegian subjects with type 2 diabetes. Scand. J. Clin. Lab. Investig. 74:700–7
     [Google Scholar]
  26. 26. 
    Møller JB, Pedersen M, Tanaka H et al. 2014. Body composition is the main determinant for the difference in type 2 diabetes pathophysiology between Japanese and Caucasians. Diabetes Care 37:796–804
     [Google Scholar]
  27. 27. 
    Møller JB, Dalla Man C, Overgaard RV et al. 2014. Ethnic differences in insulin sensitivity, β-cell function, and hepatic extraction between Japanese and Caucasians: a minimal model analysis. J. Clin. Endocrinol. Metab. 99:4273–80
     [Google Scholar]
  28. 28. 
    Hasson BR, Apovian C, Istfan N 2015. Racial/ethnic differences in insulin resistance and beta cell function: relationship to racial disparities in type 2 diabetes among African Americans versus Caucasians. Curr. Obes. Rep. 4:241–49
     [Google Scholar]
  29. 29. 
    Nadeau KJ, Anderson BJ, Berg EG et al. 2016. Youth-onset type 2 diabetes consensus report: current status, challenges, and priorities. Diabetes Care 39:1635–42
     [Google Scholar]
  30. 30. 
    Edelstein SL 2019. Effects of treatment of impaired glucose tolerance or recently diagnosed type 2 diabetes with metformin alone or in combination with insulin glargine on β-cell function: comparison of responses in youth and adults. Diabetes 68:1670–80
     [Google Scholar]
  31. 31. 
    Shiga K, Kikuchi N. 2009. Children with type 2 diabetes mellitus are at greater risk of macrovascular complications. Pediatr. Int. 51:563–67
     [Google Scholar]
  32. 32. 
    Mayer-Davis EJ, Lawrence JM, Dabelea D et al. 2017. Incidence trends of type 1 and type 2 diabetes among youths, 2002–2012. N. Engl. J. Med. 376:1419–29
     [Google Scholar]
  33. 33. 
    Yang Y, Chan L. 2016. Monogenic diabetes: what it teaches us on the common forms of type 1 and type 2 diabetes. Endocr. Rev. 37:190–222
     [Google Scholar]
  34. 34. 
    Chung WK, Erion K, Florez JC et al. 2020. Precision medicine in diabetes: a consensus report from the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD). Diabetes Care 43:1617–35
     [Google Scholar]
  35. 35. 
    Shields BM, McDonald TJ, Ellard S et al. 2012. The development and validation of a clinical prediction model to determine the probability of MODY in patients with young-onset diabetes. Diabetologia 55:1265–72
     [Google Scholar]
  36. 36. 
    Dodu SR. 1967. Diabetes in the tropics. Br. Med. J. 2:747–50
     [Google Scholar]
  37. 37. 
    Kwaku Adadevoh B. 1968. “Temporary diabetes” in adult Nigerians. Trans. R. Soc. Trop. Med. Hygiene 62:528–30
     [Google Scholar]
  38. 38. 
    Oli J. 1978. Remittent diabetes mellitus in Nigeria. Trop. Geogr. Med. 30:57–62
     [Google Scholar]
  39. 39. 
    Winter WE, Maclaren NK, Riley WJ et al. 1987. Maturity-onset diabetes of youth in black Americans. N. Engl. J. Med. 316:285–91
     [Google Scholar]
  40. 40. 
    Banerji MA, Chaiken RL, Huey H et al. 1994. GAD antibody negative NIDDM in adult black subjects with diabetic ketoacidosis and increased frequency of human leukocyte antigen DR3 and DR4. Flatbush diabetes. Diabetes 43:741–45
     [Google Scholar]
  41. 41. 
    Umpierrez GE, Casals MM, Gebhart SP et al. 1995. Diabetic ketoacidosis in obese African-Americans. Diabetes 44:790–95
     [Google Scholar]
  42. 42. 
    Maldonado M, Hampe CS, Gaur LK et al. 2003. Ketosis-prone diabetes: dissection of a heterogeneous syndrome using an immunogenetic and beta-cell functional classification, prospective analysis, and clinical outcomes. J. Clin. Endocrinol. Metab. 88:5090–98
     [Google Scholar]
  43. 43. 
    Mauvais-Jarvis F, Sobngwi E, Porcher R et al. 2004. Ketosis-prone type 2 diabetes in patients of sub-Saharan African origin: clinical pathophysiology and natural history of beta-cell dysfunction and insulin resistance. Diabetes 53:645–53
     [Google Scholar]
  44. 44. 
    Ramos-Román MA, Piñero-Piloña A, Adams-Huet B et al. 2006. Comparison of type 1, type 2, and atypical ketosis-prone diabetes at 4 years of diabetes duration. J. Diabetes Complications 20:137–44
     [Google Scholar]
  45. 45. 
    Aizawa T, Katakura M, Taguchi N et al. 1995. Ketoacidosis-onset noninsulin dependent diabetes in Japanese subjects. Am. J. Med. Sci. 310:198–201
     [Google Scholar]
  46. 46. 
    Wilson C, Krakoff J, Gohdes D 1997. Ketoacidosis in Apache Indians with non-insulin-dependent diabetes mellitus. Arch. Intern. Med. 157:2098–100
     [Google Scholar]
  47. 47. 
    Balasubramanyam A, Zern JW, Hyman DJ et al. 1999. New profiles of diabetic ketoacidosis: type 1 versus type 2 diabetes and the effect of ethnicity. Arch. Intern. Med. 159:2317–22
     [Google Scholar]
  48. 48. 
    Westphal SA. 1996. The occurrence of diabetic ketoacidosis in non-insulin-dependent diabetes and newly diagnosed diabetic adults. Am. J. Med. 101:19–24
     [Google Scholar]
  49. 49. 
    Pinto ME, Villena JE, Villena AE 2008. Diabetic ketoacidosis in Peruvian patients with type 2 diabetes mellitus. Endocr. Pract. 14:442–46
     [Google Scholar]
  50. 50. 
    Pitteloud N, Philippe J. 2000. Characteristics of Caucasian type 2 diabetic patients during ketoacidosis and at follow-up. Schweiz. Med. Wochenschr. 130:576–82
     [Google Scholar]
  51. 51. 
    Jabbar A, Farooqui K, Habib A et al. 2004. Clinical characteristics and outcomes of diabetic ketoacidosis in Pakistani adults with type 2 diabetes mellitus. Diabet. Med. 21:920–23
     [Google Scholar]
  52. 52. 
    Gupta RD, Ramachandran R, Gangadhara P et al. 2017. Clinical characteristics, beta-cell dysfunction and treatment outcomes in patients with A–β+ ketosis-prone diabetes (KPD): the first identified cohort amongst Asian Indians. J. Diabetes Complications 31:1401–7
     [Google Scholar]
  53. 53. 
    Tan KC, Mackay IR, Zimmet PZ et al. 2000. Metabolic and immunologic features of Chinese patients with atypical diabetes mellitus. Diabetes Care 23:335–38
     [Google Scholar]
  54. 54. 
    Kim MK, Lee SH, Kim JH et al. 2009. Clinical characteristics of Korean patients with new-onset diabetes presenting with diabetic ketoacidosis. Diabetes Res. Clin. Pract. 85:e8–e11
     [Google Scholar]
  55. 55. 
    Balasubramanyam A, Garza G, Rodriguez L et al. 2006. Accuracy and predictive value of classification schemes for ketosis-prone diabetes. Diabetes Care 29:2575–79
     [Google Scholar]
  56. 56. 
    Haaland WC, Scaduto DI, Maldonado MR et al. 2009. A–β– subtype of ketosis-prone diabetes is not predominantly a monogenic diabetic syndrome. Diabetes Care 32:873–77
     [Google Scholar]
  57. 57. 
    Brooks-Worrell BM, Iyer D, Coraza I et al. 2013. Islet-specific T-cell responses and proinflammatory monocytes define subtypes of autoantibody-negative ketosis-prone diabetes. Diabetes Care 36:4098–103
     [Google Scholar]
  58. 58. 
    Redondo MJ, Rodriguez LM, Escalante M et al. 2013. Types of pediatric diabetes mellitus defined by anti-islet autoimmunity and random C-peptide at diagnosis. Pediatr. Diabetes 14:333–40
     [Google Scholar]
  59. 59. 
    Nalini R, Ozer K, Maldonado M et al. 2010. Presence or absence of a known diabetic ketoacidosis precipitant defines distinct syndromes of “A–β+” ketosis-prone diabetes based on long-term β-cell function, human leukocyte antigen class II alleles, and sex predilection. Metabolism 59:1448–55
     [Google Scholar]
  60. 60. 
    Patel SG, Hsu JW, Jahoor F et al. 2013. Pathogenesis of A–β+ ketosis-prone diabetes. Diabetes 62:912–22
     [Google Scholar]
  61. 61. 
    Mulukutla SN, Hsu JW, Gaba R et al. 2018. Arginine metabolism is altered in adults with A–β+ ketosis-prone diabetes. J. Nutr. 148:185–93
     [Google Scholar]
  62. 62. 
    Hampe CS, Nalini R, Maldonado MR et al. 2007. Association of amino-terminal-specific antiglutamate decarboxylase (GAD65) autoantibodies with β-cell functional reserve and a milder clinical phenotype in patients with GAD65 antibodies and ketosis-prone diabetes mellitus. J. Clin. Endocrinol. Metab. 92:462–67
     [Google Scholar]
  63. 63. 
    Ahlqvist E, Storm P, Käräjämäki A et al. 2018. Novel subgroups of adult-onset diabetes and their association with outcomes: a data-driven cluster analysis of six variables. Lancet Diabetes Endocrinol 6:361–69
     [Google Scholar]
  64. 64. 
    Udler MS, Kim J, von Grotthuss M et al. 2018. Type 2 diabetes genetic loci informed by multi-trait associations point to disease mechanisms and subtypes: a soft clustering analysis. PLOS Med 15:e1002654
     [Google Scholar]
  65. 65. 
    Xu P, Krischer JP. 2016. Prognostic classification factors associated with development of multiple autoantibodies, dysglycemia, and type 1 diabetes—a recursive partitioning analysis. Diabetes Care 39:1036–44
     [Google Scholar]
  66. 66. 
    Krischer JP, Liu X, Vehik K et al. 2019. Predicting islet cell autoimmunity and type 1 diabetes: an 8-year TEDDY Study progress report. Diabetes Care 42:1051–60
     [Google Scholar]
  67. 67. 
    McDonald TJ, Ellard S. 2013. Maturity onset diabetes of the young: identification and diagnosis. Ann. Clin. Biochem. 50:403–15
     [Google Scholar]
  68. 68. 
    Stenström G, Gottsäter A, Bakhtadze E et al. 2005. Latent autoimmune diabetes in adults: definition, prevalence, beta-cell function, and treatment. Diabetes 54:Suppl. 2S68–72
     [Google Scholar]
  69. 69. 
    Andersen MK, Lundgren V, Turunen JA et al. 2010. Latent autoimmune diabetes in adults differs genetically from classical type 1 diabetes diagnosed after the age of 35 years. Diabetes Care 33:2062–64
     [Google Scholar]
  70. 70. 
    Sidhu SS, Shah P, Srikant S et al. 1994. Ketosis resistant diabetes of the young: a profile of its exocrine and endocrine pancreatic dysfunction. Indian J. Physiol. Pharmacol. 38:289–93
     [Google Scholar]
  71. 71. 
    Oram RA, Patel K, Hill A et al. 2016. A type 1 diabetes genetic risk score can aid discrimination between type 1 and type 2 diabetes in young adults. Diabetes Care 39:337–44
     [Google Scholar]
  72. 72. 
    Patel KA, Oram RA, Flanagan SE et al. 2016. Type 1 diabetes genetic risk score: a novel tool to discriminate monogenic and type 1 diabetes. Diabetes 65:2094–99
     [Google Scholar]
  73. 73. 
    Sharp SA, Rich SS, Wood AR et al. 2019. Development and standardization of an improved type 1 diabetes genetic risk score for use in newborn screening and incident diagnosis. Diabetes Care 42:200–7
     [Google Scholar]
  74. 74. 
    Onengut-Gumuscu S, Chen WM, Robertson CC et al. 2019. Type 1 diabetes risk in African-ancestry participants and utility of an ancestry-specific genetic risk score. Diabetes Care 42:406–15
     [Google Scholar]
  75. 75. 
    Redondo MJ, Geyer S, Steck AK et al. 2018. A type 1 diabetes genetic risk score predicts progression of islet autoimmunity and development of type 1 diabetes in individuals at risk. Diabetes Care 41:1887–94
     [Google Scholar]
  76. 76. 
    Luo S, Ma X, Li X et al. 2020. Fulminant type 1 diabetes: a comprehensive review of an autoimmune condition. Diabetes Metab. Res. Rev. 36:e3317
     [Google Scholar]
/content/journals/10.1146/annurev-med-050219-034524
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Defining and Classifying New Subgroups of Diabetes
Annual Review of Medicine 72, 63 (2021); https://doi.org/10.1146/annurev-med-050219-034524
/content/journals/10.1146/annurev-med-050219-034524
/content/journals/10.1146/annurev-med-050219-034524
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