Skip to main content
Top
Published in: Current Diabetes Reports 12/2018

Open Access 01-12-2018 | Genetics (AP Morris, Section Editor)

Genetics of Monogenic Diabetes: Present Clinical Challenges

Authors: Shivani Misra, Katharine R. Owen

Published in: Current Diabetes Reports | Issue 12/2018

Login to get access

Abstract

Purpose of Review

Monogenic forms of diabetes have specific treatments that differ from the standard care provided for type 1 and type 2 diabetes, making the appropriate diagnosis essential. In this review, we discuss current clinical challenges that remain, including improving case-finding strategies, particularly those that have transethnic applicability, and understanding the interpretation of genetic variants as pathogenic, with clinically meaningful impacts.

Recent Findings

Biomarker approaches to the stratification for genetic testing now appear to be most effective in identifying cases of monogenic diabetes, and use of genetic risk scores may also prove useful. However, applicability in all ethnic groups is lacking. Challenges remain in the classification of genes as diabetes-causing and the interpretation of genetic variants at the clinical interface.

Summary

Since the discovery that genetic defects can cause neonatal or young-onset diabetes, multiple causal genes have been identified and there have been many advances in strategies to detect genetic forms of diabetes and their treatments. Approaches learnt from monogenic diabetes are now being translated to polygenic diabetes.
Literature
1.
go back to reference De Franco E, Flanagan SE, Houghton JAL, Allen HL, Mackay DJG, Temple IK, et al. The effect of early, comprehensive genomic testing on clinical care in neonatal diabetes: an international cohort study. Lancet Elsevier. 2015;386(9997):957–63.CrossRef De Franco E, Flanagan SE, Houghton JAL, Allen HL, Mackay DJG, Temple IK, et al. The effect of early, comprehensive genomic testing on clinical care in neonatal diabetes: an international cohort study. Lancet Elsevier. 2015;386(9997):957–63.CrossRef
2.
go back to reference • Shields BM, Shepherd M, Hudson M, McDonald TJ, Colclough K, Peters J, et al. Population-based assessment of a biomarker-based screening pathway to aid diagnosis of monogenic diabetes in young-onset patients. Diabetes Care. 2017;40(8):1017–25. This article highlights the benefits of the biomarker approach to MODY testing over clinical and probability calculator approaches.CrossRefPubMedCentral • Shields BM, Shepherd M, Hudson M, McDonald TJ, Colclough K, Peters J, et al. Population-based assessment of a biomarker-based screening pathway to aid diagnosis of monogenic diabetes in young-onset patients. Diabetes Care. 2017;40(8):1017–25. This article highlights the benefits of the biomarker approach to MODY testing over clinical and probability calculator approaches.CrossRefPubMedCentral
3.
go back to reference Johansson BB, Irgens HU, Molnes J, Sztromwasser P, Aukrust I, Juliusson PB, et al. Targeted next-generation sequencing reveals MODY in up to 6.5% of antibody-negative diabetes cases listed in the Norwegian Childhood Diabetes Registry. Diabetologia. Germany. 2017;60(4):625–35.CrossRef Johansson BB, Irgens HU, Molnes J, Sztromwasser P, Aukrust I, Juliusson PB, et al. Targeted next-generation sequencing reveals MODY in up to 6.5% of antibody-negative diabetes cases listed in the Norwegian Childhood Diabetes Registry. Diabetologia. Germany. 2017;60(4):625–35.CrossRef
4.
go back to reference Misra S, Hattersley AT. Chapter 18 monogenic causes of diabetes. In: Holt R, Cockram C, Flyvbjerg A, Godlstein B, editors. Textbook of diabetes, 5th edition. 5th ed. Wiley; 2017. p. 243. Misra S, Hattersley AT. Chapter 18 monogenic causes of diabetes. In: Holt R, Cockram C, Flyvbjerg A, Godlstein B, editors. Textbook of diabetes, 5th edition. 5th ed. Wiley; 2017. p. 243.
6.
go back to reference Pearson ER, Flechtner I, Njolstad PR, Malecki MT, Flanagan SE, Larkin B, et al. Switching from insulin to oral sulfonylureas in patients with diabetes due to Kir6.2 mutations. N Engl J Med. 2006;355(5):467–77.CrossRef Pearson ER, Flechtner I, Njolstad PR, Malecki MT, Flanagan SE, Larkin B, et al. Switching from insulin to oral sulfonylureas in patients with diabetes due to Kir6.2 mutations. N Engl J Med. 2006;355(5):467–77.CrossRef
7.
go back to reference Gloyn AL, Pearson ER, Antcliff JF, Proks P, Bruining GJ, Slingerland AS, et al. Activating mutations in the gene encoding the ATP-sensitive potassium-channel subunit Kir6.2 and permanent neonatal diabetes. N Engl J Med. 2004;350(18):1838–49.CrossRef Gloyn AL, Pearson ER, Antcliff JF, Proks P, Bruining GJ, Slingerland AS, et al. Activating mutations in the gene encoding the ATP-sensitive potassium-channel subunit Kir6.2 and permanent neonatal diabetes. N Engl J Med. 2004;350(18):1838–49.CrossRef
8.
go back to reference Shepherd M, Pearson ER, Houghton J, Salt G, Ellard S, Hattersley AT. No deterioration in glycemic control in HNF-1alpha maturity-onset diabetes of the young following transfer from long-term insulin to sulphonylureas. Diabetes Care. 2003;26(11):3191–2.CrossRef Shepherd M, Pearson ER, Houghton J, Salt G, Ellard S, Hattersley AT. No deterioration in glycemic control in HNF-1alpha maturity-onset diabetes of the young following transfer from long-term insulin to sulphonylureas. Diabetes Care. 2003;26(11):3191–2.CrossRef
9.
go back to reference Shields BM, Hicks S, Shepherd MH, Colclough K, Hattersley AT, Ellard S. Maturity-onset diabetes of the young (MODY): how many cases are we missing? Diabetologia. 2010;53(12):2504–8.CrossRef Shields BM, Hicks S, Shepherd MH, Colclough K, Hattersley AT, Ellard S. Maturity-onset diabetes of the young (MODY): how many cases are we missing? Diabetologia. 2010;53(12):2504–8.CrossRef
10.
go back to reference Tattersall RB. Mild familial diabetes with dominant inheritance. Q J Med. 1974;43(170):339–57.PubMed Tattersall RB. Mild familial diabetes with dominant inheritance. Q J Med. 1974;43(170):339–57.PubMed
11.
go back to reference DiMeglio LA, Evans-Molina C, Oram RA. Type 1 diabetes. Lancet (London, England) England. 2018;391(10138):2449–62.CrossRef DiMeglio LA, Evans-Molina C, Oram RA. Type 1 diabetes. Lancet (London, England) England. 2018;391(10138):2449–62.CrossRef
12.
go back to reference Parkkola A, Härkönen T, Ryhänen SJ, Ilonen J, Knip M. Extended family history of type 1 diabetes and phenotype and genotype of newly diagnosed children. Diabetes Care. 2013;36(2):348 LP–354.CrossRef Parkkola A, Härkönen T, Ryhänen SJ, Ilonen J, Knip M. Extended family history of type 1 diabetes and phenotype and genotype of newly diagnosed children. Diabetes Care. 2013;36(2):348 LP–354.CrossRef
13.
go back to reference Thanabalasingham G, Owen KR. Diagnosis and management of maturity onset diabetes of the young (MODY). BMJ. 2011;343:d6044.CrossRef Thanabalasingham G, Owen KR. Diagnosis and management of maturity onset diabetes of the young (MODY). BMJ. 2011;343:d6044.CrossRef
14.
go back to reference • Misra S, Shields B, Colclough K, Johnston DG, Oliver NS, Ellard S, et al. South Asian individuals with diabetes who are referred for MODY testing in the UK have a lower mutation pick-up rate than white European people. Diabetologia. 2016;59(10):2262–5. This article demonstrates the lower detection rate of MODY in people of south Asian ethnicity and highlights the inadequcy of clinical criteria in these populations. CrossRefPubMedCentral • Misra S, Shields B, Colclough K, Johnston DG, Oliver NS, Ellard S, et al. South Asian individuals with diabetes who are referred for MODY testing in the UK have a lower mutation pick-up rate than white European people. Diabetologia. 2016;59(10):2262–5. This article demonstrates the lower detection rate of MODY in people of south Asian ethnicity and highlights the inadequcy of clinical criteria in these populations. CrossRefPubMedCentral
15.
go back to reference Shields BM, McDonald TJ, Ellard S, Campbell MJ, Hyde C, Hattersley AT. The development and validation of a clinical prediction model to determine the probability of MODY in patients with young-onset diabetes. Diabetologia. 2012;55(5):1265–72.CrossRefPubMedCentral Shields BM, McDonald TJ, Ellard S, Campbell MJ, Hyde C, Hattersley AT. The development and validation of a clinical prediction model to determine the probability of MODY in patients with young-onset diabetes. Diabetologia. 2012;55(5):1265–72.CrossRefPubMedCentral
16.
go back to reference Ang SF, Lim SC, Tan CSH, Fong JCW, Kon WYC, Lian JX, et al. A preliminary study to evaluate the strategy of combining clinical criteria and next generation sequencing (NGS) for the identification of monogenic diabetes among multi-ethnic Asians. Diabetes Res Clin Pract Elsevier. 2016;119:13–22.CrossRef Ang SF, Lim SC, Tan CSH, Fong JCW, Kon WYC, Lian JX, et al. A preliminary study to evaluate the strategy of combining clinical criteria and next generation sequencing (NGS) for the identification of monogenic diabetes among multi-ethnic Asians. Diabetes Res Clin Pract Elsevier. 2016;119:13–22.CrossRef
17.
go back to reference Jones AG, Hattersley AT. The clinical utility of C-peptide measurement in the care of patients with diabetes. Diabet Med. 2013;30:803–17.CrossRefPubMedCentral Jones AG, Hattersley AT. The clinical utility of C-peptide measurement in the care of patients with diabetes. Diabet Med. 2013;30:803–17.CrossRefPubMedCentral
18.
go back to reference Besser REJ, Shepherd MH, McDonald TJ, Shields BM, Knight BA, Ellard S, et al. Urinary C-peptide creatinine ratio is a practical outpatient tool for identifying hepatocyte nuclear factor 1-{alpha}/hepatocyte nuclear factor 4-{alpha} maturity-onset diabetes of the young from long-duration type 1 diabetes. Diabetes Care. 2011;34:286–91.CrossRefPubMedCentral Besser REJ, Shepherd MH, McDonald TJ, Shields BM, Knight BA, Ellard S, et al. Urinary C-peptide creatinine ratio is a practical outpatient tool for identifying hepatocyte nuclear factor 1-{alpha}/hepatocyte nuclear factor 4-{alpha} maturity-onset diabetes of the young from long-duration type 1 diabetes. Diabetes Care. 2011;34:286–91.CrossRefPubMedCentral
19.
go back to reference Mcdonald TJ, Colclough K, Brown R, Shields B, Shepherd M, Bingley P, et al. Islet autoantibodies can discriminate maturity-onset diabetes of the young (MODY) from Type1 diabetes. Diabet Med. 2011;28(9):1028–33.CrossRef Mcdonald TJ, Colclough K, Brown R, Shields B, Shepherd M, Bingley P, et al. Islet autoantibodies can discriminate maturity-onset diabetes of the young (MODY) from Type1 diabetes. Diabet Med. 2011;28(9):1028–33.CrossRef
20.
go back to reference Thanabalasingham G, Shah N, Vaxillaire M, Hansen T, Tuomi T, Gašperíková D, et al. A large multi-centre European study validates high-sensitivity C-reactive protein (hsCRP) as a clinical biomarker for the diagnosis of diabetes subtypes. Diabetologia. 2011;54(11):2801–10.CrossRef Thanabalasingham G, Shah N, Vaxillaire M, Hansen T, Tuomi T, Gašperíková D, et al. A large multi-centre European study validates high-sensitivity C-reactive protein (hsCRP) as a clinical biomarker for the diagnosis of diabetes subtypes. Diabetologia. 2011;54(11):2801–10.CrossRef
21.
go back to reference Mcdonald TJ, Shields BM, Lawry J, Owen KR, Gloyn AL, Ellard S, et al. High-sensitivity CRP discriminates HNF1A-MODY from other subtypes of diabetes. Diabetes Care. 2011;34(8):1860–2.CrossRefPubMedCentral Mcdonald TJ, Shields BM, Lawry J, Owen KR, Gloyn AL, Ellard S, et al. High-sensitivity CRP discriminates HNF1A-MODY from other subtypes of diabetes. Diabetes Care. 2011;34(8):1860–2.CrossRefPubMedCentral
22.
go back to reference Shields BM, McDonald TJ, Owen KR, Malecki M, Besser REJ, Jones A, et al. Integration of biomarkers and clinical characteristics provides the best method of identifying patients with MODY. Diabet Med. 2012;29:11. Shields BM, McDonald TJ, Owen KR, Malecki M, Besser REJ, Jones A, et al. Integration of biomarkers and clinical characteristics provides the best method of identifying patients with MODY. Diabet Med. 2012;29:11.
23.
go back to reference Oram RA, Jones AG, Besser REJ, Knight BA, Shields BM, Brown RJ, et al. The majority of patients with long-duration type 1 diabetes are insulin microsecretors and have functioning beta cells. Diabetologia. 2014;57(1):187–91.CrossRef Oram RA, Jones AG, Besser REJ, Knight BA, Shields BM, Brown RJ, et al. The majority of patients with long-duration type 1 diabetes are insulin microsecretors and have functioning beta cells. Diabetologia. 2014;57(1):187–91.CrossRef
24.
go back to reference Thanabalasingham G, Pal A, Selwood MP, Dudley C, Fisher K, Bingley PJ, et al. Systematic assessment of etiology in adults with a clinical diagnosis of young-onset type 2 diabetes is a successful strategy for identifying maturity-onset diabetes of the young. Diabetes Care. 2012;35(6):1206–12.CrossRefPubMedCentral Thanabalasingham G, Pal A, Selwood MP, Dudley C, Fisher K, Bingley PJ, et al. Systematic assessment of etiology in adults with a clinical diagnosis of young-onset type 2 diabetes is a successful strategy for identifying maturity-onset diabetes of the young. Diabetes Care. 2012;35(6):1206–12.CrossRefPubMedCentral
25.
go back to reference Shepherd M, Shields B, Hammersley S, Hudson M, McDonald TJ, Colclough K, et al. Systematic population screening, using biomarkers and genetic testing, identifies 2.5% of the U.K. pediatric diabetes population with monogenic diabetes. Diabetes Care. 2016:6. Shepherd M, Shields B, Hammersley S, Hudson M, McDonald TJ, Colclough K, et al. Systematic population screening, using biomarkers and genetic testing, identifies 2.5% of the U.K. pediatric diabetes population with monogenic diabetes. Diabetes Care. 2016:6.
26.
go back to reference Concannon P, Rich SS, Nepom GT. Genetics of type 1A diabetes. N Engl J Med United States. 2009;360(16):1646–54.CrossRef Concannon P, Rich SS, Nepom GT. Genetics of type 1A diabetes. N Engl J Med United States. 2009;360(16):1646–54.CrossRef
27.
go back to reference Patel KA, Oram RA, Flanagan SE, De Franco E, Colclough K, Shepherd M, et al. Type 1 diabetes genetic risk score: a novel tool to discriminate monogenic and type 1 diabetes. Diabetes 2016 5; Patel KA, Oram RA, Flanagan SE, De Franco E, Colclough K, Shepherd M, et al. Type 1 diabetes genetic risk score: a novel tool to discriminate monogenic and type 1 diabetes. Diabetes 2016 5;
28.
go back to reference Oram RA, Patel K, Hill A, Shields B, McDonald TJ, Jones A, et al. A type 1 diabetes genetic risk score can aid discrimination between type 1 and type 2 diabetes in young adults. Diabetes Care. 2016;39(3):337 LP–344.CrossRef Oram RA, Patel K, Hill A, Shields B, McDonald TJ, Jones A, et al. A type 1 diabetes genetic risk score can aid discrimination between type 1 and type 2 diabetes in young adults. Diabetes Care. 2016;39(3):337 LP–344.CrossRef
29.
go back to reference Perry DJ, Wasserfall CH, Oram RA, Williams MD, Posgai A, Muir AB, et al. Application of a genetic risk score to racially diverse type 1 diabetes populations demonstrates the need for diversity in risk-modeling. Sci rep. England. 2018;8(1):4529.CrossRef Perry DJ, Wasserfall CH, Oram RA, Williams MD, Posgai A, Muir AB, et al. Application of a genetic risk score to racially diverse type 1 diabetes populations demonstrates the need for diversity in risk-modeling. Sci rep. England. 2018;8(1):4529.CrossRef
30.
go back to reference Hope S V, Wienand-Barnett S, Shepherd M, King SM, Fox C, Khunti K, et al. Practical classification guidelines for diabetes in patients treated with insulin: a cross-sectional study of the accuracy of diabetes diagnosis. Br J Gen Pract 2016 14; Hope S V, Wienand-Barnett S, Shepherd M, King SM, Fox C, Khunti K, et al. Practical classification guidelines for diabetes in patients treated with insulin: a cross-sectional study of the accuracy of diabetes diagnosis. Br J Gen Pract 2016 14;
31.
go back to reference Royal College of General Practioners. Coding, Classification & Diagnosis of Diabetes 2011. p. 1–56. Royal College of General Practioners. Coding, Classification & Diagnosis of Diabetes 2011. p. 1–56.
32.
go back to reference Ehtisham S, Hattersley AT, Dunger DB, Barrett TG. First UK survey of paediatric type 2 diabetes and MODY. Arch Dis Child. 2004;89(6):526–9.CrossRefPubMedCentral Ehtisham S, Hattersley AT, Dunger DB, Barrett TG. First UK survey of paediatric type 2 diabetes and MODY. Arch Dis Child. 2004;89(6):526–9.CrossRefPubMedCentral
33.
go back to reference Porter JR, Rangasami JJ, Ellard S, Gloyn AL, Shields BM, Edwards J, et al. Asian MODY: are we missing an important diagnosis? Diabet Med. 2006;23(11):1257–60.CrossRef Porter JR, Rangasami JJ, Ellard S, Gloyn AL, Shields BM, Edwards J, et al. Asian MODY: are we missing an important diagnosis? Diabet Med. 2006;23(11):1257–60.CrossRef
34.
go back to reference Pihoker C, Gilliam LK, Ellard S, Dabelea D, Davis C, Dolan LM, et al. Prevalence, characteristics and clinical diagnosis of maturity onset diabetes of the young due to mutations in HNF1A, HNF4A, and glucokinase: results from the SEARCH for diabetes in youth. J Clin Endocrinol Metab. 2013;98(10):4055–62.CrossRefPubMedCentral Pihoker C, Gilliam LK, Ellard S, Dabelea D, Davis C, Dolan LM, et al. Prevalence, characteristics and clinical diagnosis of maturity onset diabetes of the young due to mutations in HNF1A, HNF4A, and glucokinase: results from the SEARCH for diabetes in youth. J Clin Endocrinol Metab. 2013;98(10):4055–62.CrossRefPubMedCentral
35.
go back to reference Radha V, Ek J, Anuradha S, Hansen T, Pedersen O, Mohan V. Identification of novel variants in the hepatocyte nuclear factor-1alpha gene in South Indian patients with maturity onset diabetes of young. J Clin Endocrinol Metab. 2009;94(6):1959–65.CrossRef Radha V, Ek J, Anuradha S, Hansen T, Pedersen O, Mohan V. Identification of novel variants in the hepatocyte nuclear factor-1alpha gene in South Indian patients with maturity onset diabetes of young. J Clin Endocrinol Metab. 2009;94(6):1959–65.CrossRef
36.
go back to reference Anuradha S, Radha V, Mohan V. Association of novel variants in the hepatocyte nuclear factor 4A gene with maturity onset diabetes of the young and early onset type 2 diabetes. Clin Genet. 2011;80(6):541–9.CrossRef Anuradha S, Radha V, Mohan V. Association of novel variants in the hepatocyte nuclear factor 4A gene with maturity onset diabetes of the young and early onset type 2 diabetes. Clin Genet. 2011;80(6):541–9.CrossRef
37.
go back to reference Kanthimathi S, Jahnavi S, Balamurugan K, Ranjani H, Sonya J, Goswami S, et al. Glucokinase gene mutations (MODY 2) in Asian Indians. Diabetes Technol Ther. 2014;16:180–5.CrossRef Kanthimathi S, Jahnavi S, Balamurugan K, Ranjani H, Sonya J, Goswami S, et al. Glucokinase gene mutations (MODY 2) in Asian Indians. Diabetes Technol Ther. 2014;16:180–5.CrossRef
38.
go back to reference Doddabelavangala Mruthyunjaya M, Chapla A, Hesarghatta Shyamasunder A, Varghese D, Varshney M, Paul J, et al. Comprehensive maturity onset diabetes of the young (MODY) gene screening in pregnant women with diabetes in India. PLoS one. Public Libr Sci. 2017;12(1):1–15. Doddabelavangala Mruthyunjaya M, Chapla A, Hesarghatta Shyamasunder A, Varghese D, Varshney M, Paul J, et al. Comprehensive maturity onset diabetes of the young (MODY) gene screening in pregnant women with diabetes in India. PLoS one. Public Libr Sci. 2017;12(1):1–15.
39.
go back to reference Xu JY, Dan QH, Chan V, Wat NM, Tam S, Tiu SC, et al. Genetic and clinical characteristics of maturity-onset diabetes of the young in Chinese patients. Eur J Hum Genet. 2005;13(4):422–7.CrossRef Xu JY, Dan QH, Chan V, Wat NM, Tam S, Tiu SC, et al. Genetic and clinical characteristics of maturity-onset diabetes of the young in Chinese patients. Eur J Hum Genet. 2005;13(4):422–7.CrossRef
40.
go back to reference Iwasaki N, Ohgawara H, Nagahara H, Kawamura M, Bell GI, Omori Y. Characterization of Japanese families with early-onset type 2 (non-insulin dependent) diabetes mellitus and screening for mutations in the glucokinase and mitochondrial tRNALeu(UUR) genes. Acta Diabetol. 1995;32(1):17–22.CrossRef Iwasaki N, Ohgawara H, Nagahara H, Kawamura M, Bell GI, Omori Y. Characterization of Japanese families with early-onset type 2 (non-insulin dependent) diabetes mellitus and screening for mutations in the glucokinase and mitochondrial tRNALeu(UUR) genes. Acta Diabetol. 1995;32(1):17–22.CrossRef
41.
go back to reference Al Senani A, Hamza N, Al Azkawi H, Al Kharusi M, Al Sukaiti N, Al Badi M, et al. Genetic mutations associated with neonatal diabetes mellitus in Omani patients. J Pediatr Endocrinol Metab Germany. 2018;31(2):195–204.CrossRef Al Senani A, Hamza N, Al Azkawi H, Al Kharusi M, Al Sukaiti N, Al Badi M, et al. Genetic mutations associated with neonatal diabetes mellitus in Omani patients. J Pediatr Endocrinol Metab Germany. 2018;31(2):195–204.CrossRef
42.
go back to reference Sattar N, Gill JMR. Type 2 diabetes in migrant south Asians: mechanisms, mitigation, and management. Lancet Diabetes Endocrinol Elsevier. 2017;3(12):1004–16.CrossRef Sattar N, Gill JMR. Type 2 diabetes in migrant south Asians: mechanisms, mitigation, and management. Lancet Diabetes Endocrinol Elsevier. 2017;3(12):1004–16.CrossRef
43.
go back to reference Lutale JJK, Thordarson H, Holm PI, Eide GE, Vetvik K. Islet cell autoantibodies in African patients with type 1 and type 2 diabetes in Dar es Salaam Tanzania: a cross sectional study. J Autoimmune Dis. 2007;4(1):4.CrossRefPubMedCentral Lutale JJK, Thordarson H, Holm PI, Eide GE, Vetvik K. Islet cell autoantibodies in African patients with type 1 and type 2 diabetes in Dar es Salaam Tanzania: a cross sectional study. J Autoimmune Dis. 2007;4(1):4.CrossRefPubMedCentral
44.
go back to reference Misra S, Sebastian A, Groom O, Colclough K, Johnston D, Ellard S, et al. Systematic screening for monogenic diabetes in people of south Asian and African-Caribbean ethnicity: preliminary results from the MY DIABETES study. Diabet Med. 2018;35(S1):159–60. Misra S, Sebastian A, Groom O, Colclough K, Johnston D, Ellard S, et al. Systematic screening for monogenic diabetes in people of south Asian and African-Caribbean ethnicity: preliminary results from the MY DIABETES study. Diabet Med. 2018;35(S1):159–60.
45.
go back to reference Ellard S, Lango Allen H, De Franco E, Flanagan SE, Hysenaj G, Colclough K, et al. Improved genetic testing for monogenic diabetes using targeted next-generation sequencing. Diabetologia. Berlin/Heidelberg: Springer Berlin Heidelberg. 2013;56(9):1958–63.CrossRef Ellard S, Lango Allen H, De Franco E, Flanagan SE, Hysenaj G, Colclough K, et al. Improved genetic testing for monogenic diabetes using targeted next-generation sequencing. Diabetologia. Berlin/Heidelberg: Springer Berlin Heidelberg. 2013;56(9):1958–63.CrossRef
46.
go back to reference Sanger F, Coulson AR. A rapid method for determining sequences in DNA by primed synthesis with DNA polymerase. J Mol Biol England. 1975;94(3):441–8.CrossRef Sanger F, Coulson AR. A rapid method for determining sequences in DNA by primed synthesis with DNA polymerase. J Mol Biol England. 1975;94(3):441–8.CrossRef
47.
go back to reference MacArthur DG, Manolio TA, Dimmock DP, Rehm HL, Shendure J, Abecasis GR, et al. Guidelines for investigating causality of sequence variants in human disease. Nature. Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved. 2014;508(7497):469–76. MacArthur DG, Manolio TA, Dimmock DP, Rehm HL, Shendure J, Abecasis GR, et al. Guidelines for investigating causality of sequence variants in human disease. Nature. Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved. 2014;508(7497):469–76.
48.
go back to reference Althari S, Gloyn AL. When is it MODY? Challenges in the interpretation of sequence variants in MODY genes. Rev Diabet Stud Germany. 2015;12(3–4):330–48.CrossRef Althari S, Gloyn AL. When is it MODY? Challenges in the interpretation of sequence variants in MODY genes. Rev Diabet Stud Germany. 2015;12(3–4):330–48.CrossRef
49.
go back to reference Stanik J, Dusatkova P, Cinek O, Valentinova L, Huckova M, Skopkova M, et al. De novo mutations of GCK, HNF1A and HNF4A may be more frequent in MODY than previously assumed. Diabetologia. 2014;57(3):480–4.CrossRef Stanik J, Dusatkova P, Cinek O, Valentinova L, Huckova M, Skopkova M, et al. De novo mutations of GCK, HNF1A and HNF4A may be more frequent in MODY than previously assumed. Diabetologia. 2014;57(3):480–4.CrossRef
50.
go back to reference Richards S, Aziz N, Bale S, Bick D, Das S, Gastier-Foster J, et al. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet Med. 2015;17(5):405–23.CrossRefPubMedCentral Richards S, Aziz N, Bale S, Bick D, Das S, Gastier-Foster J, et al. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet Med. 2015;17(5):405–23.CrossRefPubMedCentral
52.
go back to reference Walsh R, Thomson KL, Ware JS, Funke BH, Woodley J, McGuire KJ, et al. Reassessment of Mendelian gene pathogenicity using 7,855 cardiomyopathy cases and 60,706 reference samples. Genet Med United States. 2017;19(2):192–203. Walsh R, Thomson KL, Ware JS, Funke BH, Woodley J, McGuire KJ, et al. Reassessment of Mendelian gene pathogenicity using 7,855 cardiomyopathy cases and 60,706 reference samples. Genet Med United States. 2017;19(2):192–203.
53.
go back to reference • Flannick J, Johansson S, Njølstad PR. Common and rare forms of diabetes mellitus: towards a continuum of diabetes subtypes. Nat Rev Endocrinol. 2016;12(7). This article highlights the importance of correctly classifying varaints in dominant diabetes genes. • Flannick J, Johansson S, Njølstad PR. Common and rare forms of diabetes mellitus: towards a continuum of diabetes subtypes. Nat Rev Endocrinol. 2016;12(7). This article highlights the importance of correctly classifying varaints in dominant diabetes genes.
54.
go back to reference Tavtigian SV, Greenblatt MS, Lesueur F, Byrnes GB. In silico analysis of missense substitutions using sequence-alignment based methods. Hum Mutat. 2008;29(11):1327–36.CrossRefPubMedCentral Tavtigian SV, Greenblatt MS, Lesueur F, Byrnes GB. In silico analysis of missense substitutions using sequence-alignment based methods. Hum Mutat. 2008;29(11):1327–36.CrossRefPubMedCentral
55.
go back to reference Ashkenazy H, Erez E, Martz E, Pupko T, Ben-Tal N. ConSurf 2010: calculating evolutionary conservation in sequence and structure of proteins and nucleic acids. Nucleic Acids Res England. 2010;38(Web Server issue):W529–33.CrossRef Ashkenazy H, Erez E, Martz E, Pupko T, Ben-Tal N. ConSurf 2010: calculating evolutionary conservation in sequence and structure of proteins and nucleic acids. Nucleic Acids Res England. 2010;38(Web Server issue):W529–33.CrossRef
56.
go back to reference Celniker G, Nimrod G, Ashkenazy H, Glaser F, Martz E, Mayrose I, et al. ConSurf: using evolutionary data to raise testable hypotheses about protein function. Isr J Chem WILEY-VCH Verlag. 2013;53(3–4):199–206.CrossRef Celniker G, Nimrod G, Ashkenazy H, Glaser F, Martz E, Mayrose I, et al. ConSurf: using evolutionary data to raise testable hypotheses about protein function. Isr J Chem WILEY-VCH Verlag. 2013;53(3–4):199–206.CrossRef
60.
go back to reference Kumar P, Henikoff S, Ng PC. Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm. Nat Protoc England. 2009;4(7):1073–81.CrossRef Kumar P, Henikoff S, Ng PC. Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm. Nat Protoc England. 2009;4(7):1073–81.CrossRef
62.
go back to reference Tavtigian SV, Deffenbaugh AM, Yin L, Judkins T, Scholl T, Samollow PB, et al. Comprehensive statistical study of 452 BRCA1 missense substitutions with classification of eight recurrent substitutions as neutral. J Med Genet England. 2006;43(4):295–305.CrossRef Tavtigian SV, Deffenbaugh AM, Yin L, Judkins T, Scholl T, Samollow PB, et al. Comprehensive statistical study of 452 BRCA1 missense substitutions with classification of eight recurrent substitutions as neutral. J Med Genet England. 2006;43(4):295–305.CrossRef
64.
go back to reference Adzhubei IA, Schmidt S, Peshkin L, Ramensky VE, Gerasimova A, Bork P, et al. A method and server for predicting damaging missense mutations. Vol. 7, Nature methods. United States; 2010. p. 248–9. Adzhubei IA, Schmidt S, Peshkin L, Ramensky VE, Gerasimova A, Bork P, et al. A method and server for predicting damaging missense mutations. Vol. 7, Nature methods. United States; 2010. p. 248–9.
65.
go back to reference Galan M, Garcia-Herrero C-M, Azriel S, Gargallo M, Duran M, Gorgojo J-J, et al. Differential effects of HNF-1alpha mutations associated with familial young-onset diabetes on target gene regulation. Mol Med United States. 2011;17(3–4):256–65. Galan M, Garcia-Herrero C-M, Azriel S, Gargallo M, Duran M, Gorgojo J-J, et al. Differential effects of HNF-1alpha mutations associated with familial young-onset diabetes on target gene regulation. Mol Med United States. 2011;17(3–4):256–65.
66.
go back to reference Bjorkhaug L, Sagen JV, Thorsby P, Sovik O, Molven A, Njolstad PR. Hepatocyte nuclear factor-1 alpha gene mutations and diabetes in Norway. J Clin Endocrinol Metab. 2003;88(2):920–31.CrossRef Bjorkhaug L, Sagen JV, Thorsby P, Sovik O, Molven A, Njolstad PR. Hepatocyte nuclear factor-1 alpha gene mutations and diabetes in Norway. J Clin Endocrinol Metab. 2003;88(2):920–31.CrossRef
67.
go back to reference Najmi LA, Aukrust I, Flannick J, Molnes J, Burtt N, Molven A, et al. Functional investigations of HNF1A identify rare variants as risk factors for type 2 diabetes in the general population. Diabetes 2016 29; Najmi LA, Aukrust I, Flannick J, Molnes J, Burtt N, Molven A, et al. Functional investigations of HNF1A identify rare variants as risk factors for type 2 diabetes in the general population. Diabetes 2016 29;
68.
go back to reference Babiker T, Vedovato N, Patel K, Thomas N, Finn R, Männikkö R, et al. Successful transfer to sulfonylureas in KCNJ11 neonatal diabetes is determined by the mutation and duration of diabetes. Diabetologia. 2016;59:1162–6.CrossRefPubMedCentral Babiker T, Vedovato N, Patel K, Thomas N, Finn R, Männikkö R, et al. Successful transfer to sulfonylureas in KCNJ11 neonatal diabetes is determined by the mutation and duration of diabetes. Diabetologia. 2016;59:1162–6.CrossRefPubMedCentral
69.
go back to reference Misra S, Vedovato N, Cliff E, De Franco E, Hattersley AT, Ashcroft FM, et al. Permanent neonatal diabetes: combining sulfonylureas with insulin may be an effective treatment. Diabetic medicine: a journal of the British Diabetic Association. England; 2018. Misra S, Vedovato N, Cliff E, De Franco E, Hattersley AT, Ashcroft FM, et al. Permanent neonatal diabetes: combining sulfonylureas with insulin may be an effective treatment. Diabetic medicine: a journal of the British Diabetic Association. England; 2018.
70.
go back to reference Raeder H, Johansson S, Holm PI, Haldorsen IS, Mas E, Sbarra V, et al. Mutations in the CEL VNTR cause a syndrome of diabetes and pancreatic exocrine dysfunction. Nat Genet. 2006;38(1):54–62.CrossRef Raeder H, Johansson S, Holm PI, Haldorsen IS, Mas E, Sbarra V, et al. Mutations in the CEL VNTR cause a syndrome of diabetes and pancreatic exocrine dysfunction. Nat Genet. 2006;38(1):54–62.CrossRef
71.
go back to reference Weedon MN, Ellard S, Prindle MJ, Caswell R, Allen HL, Oram R, et al. An in-frame deletion at the polymerase active site of POLD1 causes a multisystem disorder with lipodystrophy. Nat Genet. 2013;45(8):947–50.CrossRefPubMedCentral Weedon MN, Ellard S, Prindle MJ, Caswell R, Allen HL, Oram R, et al. An in-frame deletion at the polymerase active site of POLD1 causes a multisystem disorder with lipodystrophy. Nat Genet. 2013;45(8):947–50.CrossRefPubMedCentral
72.
go back to reference Prudente S, Jungtrakoon P, Marucci A, Ludovico O, Buranasupkajorn P, Mazza T, et al. Loss-of-function mutations in APPL1 in familial diabetes mellitus. Am J Hum Genet United States. 2015;97(1):177–85.CrossRef Prudente S, Jungtrakoon P, Marucci A, Ludovico O, Buranasupkajorn P, Mazza T, et al. Loss-of-function mutations in APPL1 in familial diabetes mellitus. Am J Hum Genet United States. 2015;97(1):177–85.CrossRef
73.
go back to reference Consortium ST. 2 D. ASsociation of a low-frequency variant in hnf1a with type 2 diabetes in a latino population. JAMA. 2014;311(22):2305–14.CrossRef Consortium ST. 2 D. ASsociation of a low-frequency variant in hnf1a with type 2 diabetes in a latino population. JAMA. 2014;311(22):2305–14.CrossRef
74.
go back to reference Bonnycastle LL, Chines PS, Hara T, Huyghe JR, Swift AJ, Heikinheimo P, et al. Autosomal dominant diabetes arising from a Wolfram syndrome 1 mutation. Diabetes United States. 2013;62(11):3943–50.CrossRef Bonnycastle LL, Chines PS, Hara T, Huyghe JR, Swift AJ, Heikinheimo P, et al. Autosomal dominant diabetes arising from a Wolfram syndrome 1 mutation. Diabetes United States. 2013;62(11):3943–50.CrossRef
75.
go back to reference Patel KA, Kettunen J, Laakso M, Stančáková A, Laver TW, Colclough K, et al. Heterozygous RFX6 protein truncating variants are associated with MODY with reduced penetrance. Nat Commun. 2017;8(1):888.CrossRefPubMedCentral Patel KA, Kettunen J, Laakso M, Stančáková A, Laver TW, Colclough K, et al. Heterozygous RFX6 protein truncating variants are associated with MODY with reduced penetrance. Nat Commun. 2017;8(1):888.CrossRefPubMedCentral
76.
go back to reference Smith SB, Qu H-Q, Taleb N, Kishimoto NY, Scheel DW, Lu Y, et al. Rfx6 directs islet formation and insulin production in mice and humans. Nature England. 2010;463(7282):775–80.CrossRef Smith SB, Qu H-Q, Taleb N, Kishimoto NY, Scheel DW, Lu Y, et al. Rfx6 directs islet formation and insulin production in mice and humans. Nature England. 2010;463(7282):775–80.CrossRef
77.
go back to reference Pearson ER, Starkey BJ, Powell RJ, Gribble FM, Clark PM, Hattersley AT. Genetic aetiology of hyperglycaemia determines response to treatment in diabetes. Lancet. 2003;362(9392):1275–81.CrossRef Pearson ER, Starkey BJ, Powell RJ, Gribble FM, Clark PM, Hattersley AT. Genetic aetiology of hyperglycaemia determines response to treatment in diabetes. Lancet. 2003;362(9392):1275–81.CrossRef
78.
go back to reference Shepherd MH, Shields BM, Hudson M et al. A UK nationwide prospective study of treatment change in MODY: genetic subtype and clinical characterstics predict optimal glycaemic control after discontinuing insulin and metformin. Diabetologia. 2018. https://doi.org/10.1007/s00125=018-4728-6. Shepherd MH, Shields BM, Hudson M et al. A UK nationwide prospective study of treatment change in MODY: genetic subtype and clinical characterstics predict optimal glycaemic control after discontinuing insulin and metformin. Diabetologia. 2018. https://​doi.​org/​10.​1007/​s00125=​018-4728-6.
79.
go back to reference Østoft SH, Bagger JI, Hansen T, Pedersen O, Faber J, Holst JJ, et al. Glucose-lowering effects and low risk of hypoglycemia in patients with maturity-onset diabetes of the young when treated with a GLP-1 receptor agonist: a double-blind, randomized. Crossover Trial. Diabetes Care. 2014;37(7):1797–805.PubMed Østoft SH, Bagger JI, Hansen T, Pedersen O, Faber J, Holst JJ, et al. Glucose-lowering effects and low risk of hypoglycemia in patients with maturity-onset diabetes of the young when treated with a GLP-1 receptor agonist: a double-blind, randomized. Crossover Trial. Diabetes Care. 2014;37(7):1797–805.PubMed
80.
go back to reference Hohendorff J, Szopa M, Skupien J, Kapusta M, Zapala B, Platek T, et al. A single dose of dapagliflozin, an SGLT-2 inhibitor, induces higher glycosuria in GCK- and HNF1A-MODY than in type 2 diabetes mellitus. Endocrine United States. 2017;57(2):272–9.CrossRef Hohendorff J, Szopa M, Skupien J, Kapusta M, Zapala B, Platek T, et al. A single dose of dapagliflozin, an SGLT-2 inhibitor, induces higher glycosuria in GCK- and HNF1A-MODY than in type 2 diabetes mellitus. Endocrine United States. 2017;57(2):272–9.CrossRef
81.
go back to reference Bowman P, Sulen A, Barbetti F, Beltrand J, Svalastoga P, Codner E, et al. Effectiveness and safety of long-term treatment with sulfonylureas in patients with neonatal diabetes due to KCNJ11 mutations: an international cohort study. Lancet Diabetes Endocrinol. England. 2018;6(8):637–46.CrossRef Bowman P, Sulen A, Barbetti F, Beltrand J, Svalastoga P, Codner E, et al. Effectiveness and safety of long-term treatment with sulfonylureas in patients with neonatal diabetes due to KCNJ11 mutations: an international cohort study. Lancet Diabetes Endocrinol. England. 2018;6(8):637–46.CrossRef
82.
go back to reference Steele AM, Shields BM, Wensley KJ, Colclough K, Ellard S, Hattersley AT. Prevalence of vascular complications among patients with glucokinase mutations and prolonged, mild hyperglycemia. JAMA. 2014;311(3):279–86.CrossRef Steele AM, Shields BM, Wensley KJ, Colclough K, Ellard S, Hattersley AT. Prevalence of vascular complications among patients with glucokinase mutations and prolonged, mild hyperglycemia. JAMA. 2014;311(3):279–86.CrossRef
83.
go back to reference Murphy R, Ellard S, Hattersley AT. Clinical implications of a molecular genetic classification of monogenic beta-cell diabetes. Nat Clin Pract Endocrinol Metab. 2008;4(4):200–13.CrossRef Murphy R, Ellard S, Hattersley AT. Clinical implications of a molecular genetic classification of monogenic beta-cell diabetes. Nat Clin Pract Endocrinol Metab. 2008;4(4):200–13.CrossRef
84.
go back to reference Walford GA, Colomo N, Todd JN, Billings LK, Fernandez M, Chamarthi B, et al. The study to understand the genetics of the acute response to metformin and glipizide in humans (SUGAR-MGH): design of a pharmacogenetic resource for type 2 diabetes. PLoS One Public Library of Science. 2015;10(3):e0121553.CrossRef Walford GA, Colomo N, Todd JN, Billings LK, Fernandez M, Chamarthi B, et al. The study to understand the genetics of the acute response to metformin and glipizide in humans (SUGAR-MGH): design of a pharmacogenetic resource for type 2 diabetes. PLoS One Public Library of Science. 2015;10(3):e0121553.CrossRef
Metadata
Title
Genetics of Monogenic Diabetes: Present Clinical Challenges
Authors
Shivani Misra
Katharine R. Owen
Publication date
01-12-2018
Publisher
Springer US
Published in
Current Diabetes Reports / Issue 12/2018
Print ISSN: 1534-4827
Electronic ISSN: 1539-0829
DOI
https://doi.org/10.1007/s11892-018-1111-4

Other articles of this Issue 12/2018

Current Diabetes Reports 12/2018 Go to the issue

Immunology, Transplantation, and Regenerative Medicine (L Piemonti and V Sordi, Section Editors)

Who Will Win: Induced Pluripotent Stem Cells Versus Embryonic Stem Cells for β Cell Replacement and Diabetes Disease Modeling?

Microvascular Complications—Neuropathy (R Pop-Busui, Section Editor)

Blood Pressure Variability and Autonomic Dysfunction

Macrovascular Complications in Diabetes (VR Aroda and A Getaneh, Section Editors)

Revisiting the Diabetes-Heart Failure Connection

Therapies and New Technologies in the Treatment of Diabetes (M Pietropaolo, Section Editor)

Gut Microbiome in Obesity, Metabolic Syndrome, and Diabetes

Pediatric Type 2 and Monogenic Diabetes (PS Zeitler and O Pinhas-Hamiel, Section Editors)

Non-Diabetic Hyperglycemia in the Pediatric Age: Why, How, and When to Treat?

Macrovascular Complications in Diabetes (VR Aroda and A Getaneh, Section Editors)

Comparison of Lipid-Lowering Medications and Risk for Cardiovascular Disease in Diabetes