Skip to main content
Top
Published in: Diabetologia 6/2017

Open Access 01-06-2017 | Review

Human genetics as a model for target validation: finding new therapies for diabetes

Authors: Soren K. Thomsen, Anna L. Gloyn

Published in: Diabetologia | Issue 6/2017

Login to get access

Abstract

Type 2 diabetes is a global epidemic with major effects on healthcare expenditure and quality of life. Currently available treatments are inadequate for the prevention of comorbidities, yet progress towards new therapies remains slow. A major barrier is the insufficiency of traditional preclinical models for predicting drug efficacy and safety. Human genetics offers a complementary model to assess causal mechanisms for target validation. Genetic perturbations are ‘experiments of nature’ that provide a uniquely relevant window into the long-term effects of modulating specific targets. Here, we show that genetic discoveries over the past decades have accurately predicted (now known) therapeutic mechanisms for type 2 diabetes. These findings highlight the potential for use of human genetic variation for prospective target validation, and establish a framework for future applications. Studies into rare, monogenic forms of diabetes have also provided proof-of-principle for precision medicine, and the applicability of this paradigm to complex disease is discussed. Finally, we highlight some of the limitations that are relevant to the use of genome-wide association studies (GWAS) in the search for new therapies for diabetes. A key outstanding challenge is the translation of GWAS signals into disease biology and we outline possible solutions for tackling this experimental bottleneck.
Appendix
Available only for authorised users
Literature
2.
go back to reference DiMasi JA, Feldman L, Seckler A, Wilson A (2010) Trends in risks associated with new drug development: success rates for investigational drugs. Clin Pharmacol Ther 87:272–277CrossRefPubMed DiMasi JA, Feldman L, Seckler A, Wilson A (2010) Trends in risks associated with new drug development: success rates for investigational drugs. Clin Pharmacol Ther 87:272–277CrossRefPubMed
3.
go back to reference DiMasi JA, Grabowski HG, Hansen RW (2016) Innovation in the pharmaceutical industry: new estimates of R&D costs. J Health Econ 47:20–33CrossRefPubMed DiMasi JA, Grabowski HG, Hansen RW (2016) Innovation in the pharmaceutical industry: new estimates of R&D costs. J Health Econ 47:20–33CrossRefPubMed
4.
go back to reference Arrowsmith J, Miller P (2013) Trial watch: phase II and phase III attrition rates 2011-2012. Nat Rev Drug Discov 12:569CrossRefPubMed Arrowsmith J, Miller P (2013) Trial watch: phase II and phase III attrition rates 2011-2012. Nat Rev Drug Discov 12:569CrossRefPubMed
5.
go back to reference Cook D, Brown D, Alexander R et al (2014) Lessons learned from the fate of AstraZeneca's drug pipeline: a five-dimensional framework. Nat Rev Drug Discov 13:419–431CrossRefPubMed Cook D, Brown D, Alexander R et al (2014) Lessons learned from the fate of AstraZeneca's drug pipeline: a five-dimensional framework. Nat Rev Drug Discov 13:419–431CrossRefPubMed
6.
go back to reference Wehling M (2009) Assessing the translatability of drug projects: what needs to be scored to predict success? Nat Rev Drug Discov 8:541–546CrossRefPubMed Wehling M (2009) Assessing the translatability of drug projects: what needs to be scored to predict success? Nat Rev Drug Discov 8:541–546CrossRefPubMed
7.
go back to reference Plenge RM, Scolnick EM, Altshuler D (2013) Validating therapeutic targets through human genetics. Nat Rev Drug Discov 12:581–594CrossRefPubMed Plenge RM, Scolnick EM, Altshuler D (2013) Validating therapeutic targets through human genetics. Nat Rev Drug Discov 12:581–594CrossRefPubMed
8.
go back to reference Barrett JC, Dunham I, Birney E (2015) Using human genetics to make new medicines. Nat Rev Genet 16:561–562CrossRefPubMed Barrett JC, Dunham I, Birney E (2015) Using human genetics to make new medicines. Nat Rev Genet 16:561–562CrossRefPubMed
9.
go back to reference Hindorff LA, Sethupathy P, Junkins HA et al (2009) Potential etiologic and functional implications of genome-wide association loci for human diseases and traits. Proc Natl Acad Sci U S A 106:9362–9367CrossRefPubMedPubMedCentral Hindorff LA, Sethupathy P, Junkins HA et al (2009) Potential etiologic and functional implications of genome-wide association loci for human diseases and traits. Proc Natl Acad Sci U S A 106:9362–9367CrossRefPubMedPubMedCentral
10.
11.
go back to reference Kryukov GV, Pennacchio LA, Sunyaev SR (2007) Most rare missense alleles are deleterious in humans: implications for complex disease and association studies. Am J Hum Genet 80:727–739CrossRefPubMedPubMedCentral Kryukov GV, Pennacchio LA, Sunyaev SR (2007) Most rare missense alleles are deleterious in humans: implications for complex disease and association studies. Am J Hum Genet 80:727–739CrossRefPubMedPubMedCentral
14.
go back to reference Zuk O, Schaffner SF, Samocha K et al (2014) Searching for missing heritability: designing rare variant association studies. Proc Natl Acad Sci U S A 111:E455–E464CrossRefPubMedPubMedCentral Zuk O, Schaffner SF, Samocha K et al (2014) Searching for missing heritability: designing rare variant association studies. Proc Natl Acad Sci U S A 111:E455–E464CrossRefPubMedPubMedCentral
15.
go back to reference Flannick J, Beer NL, Bick AG et al (2013) Assessing the phenotypic effects in the general population of rare variants in genes for a dominant Mendelian form of diabetes. Nat Genet 45:1380–1385CrossRefPubMedPubMedCentral Flannick J, Beer NL, Bick AG et al (2013) Assessing the phenotypic effects in the general population of rare variants in genes for a dominant Mendelian form of diabetes. Nat Genet 45:1380–1385CrossRefPubMedPubMedCentral
16.
go back to reference Begg CB (2002) On the use of familial aggregation in population-based case probands for calculating penetrance. J Natl Cancer Inst 94:1221–1226CrossRefPubMed Begg CB (2002) On the use of familial aggregation in population-based case probands for calculating penetrance. J Natl Cancer Inst 94:1221–1226CrossRefPubMed
17.
go back to reference Zhou K, Pedersen HK, Dawed AY, Pearson ER (2016) Pharmacogenomics in diabetes mellitus: insights into drug action and drug discovery. Nat Rev Endocrinol 12:337–346PubMed Zhou K, Pedersen HK, Dawed AY, Pearson ER (2016) Pharmacogenomics in diabetes mellitus: insights into drug action and drug discovery. Nat Rev Endocrinol 12:337–346PubMed
18.
19.
go back to reference Nelson MR, Tipney H, Painter JL et al (2015) The support of human genetic evidence for approved drug indications. Nat Genet 47:856–860CrossRefPubMed Nelson MR, Tipney H, Painter JL et al (2015) The support of human genetic evidence for approved drug indications. Nat Genet 47:856–860CrossRefPubMed
20.
go back to reference Hauner H (2002) The mode of action of thiazolidinediones. Diabetes Metab Res Rev 18(Suppl 2):S10–S15 Hauner H (2002) The mode of action of thiazolidinediones. Diabetes Metab Res Rev 18(Suppl 2):S10–S15
21.
go back to reference Altshuler D, Hirschhorn JN, Klannemark M et al (2000) The common PPARgamma Pro12Ala polymorphism is associated with decreased risk of type 2 diabetes. Nat Genet 26:76–80CrossRefPubMed Altshuler D, Hirschhorn JN, Klannemark M et al (2000) The common PPARgamma Pro12Ala polymorphism is associated with decreased risk of type 2 diabetes. Nat Genet 26:76–80CrossRefPubMed
22.
go back to reference Deeb SS, Fajas L, Nemoto M et al (1998) A Pro12Ala substitution in PPARgamma2 associated with decreased receptor activity, lower body mass index and improved insulin sensitivity. Nat Genet 20:284–287CrossRefPubMed Deeb SS, Fajas L, Nemoto M et al (1998) A Pro12Ala substitution in PPARgamma2 associated with decreased receptor activity, lower body mass index and improved insulin sensitivity. Nat Genet 20:284–287CrossRefPubMed
23.
go back to reference Yen CJ, Beamer BA, Negri C et al (1997) Molecular scanning of the human peroxisome proliferator activated receptor gamma (hPPAR gamma) gene in diabetic Caucasians: identification of a Pro12Ala PPAR gamma 2 missense mutation. Biochem Biophys Res Commun 241:270–274CrossRefPubMed Yen CJ, Beamer BA, Negri C et al (1997) Molecular scanning of the human peroxisome proliferator activated receptor gamma (hPPAR gamma) gene in diabetic Caucasians: identification of a Pro12Ala PPAR gamma 2 missense mutation. Biochem Biophys Res Commun 241:270–274CrossRefPubMed
24.
go back to reference Majithia AR, Flannick J, Shahinian P et al (2014) Rare variants in PPARG with decreased activity in adipocyte differentiation are associated with increased risk of type 2 diabetes. Proc Natl Acad Sci U S A 111:13127–13132CrossRefPubMedPubMedCentral Majithia AR, Flannick J, Shahinian P et al (2014) Rare variants in PPARG with decreased activity in adipocyte differentiation are associated with increased risk of type 2 diabetes. Proc Natl Acad Sci U S A 111:13127–13132CrossRefPubMedPubMedCentral
25.
go back to reference Mahajan A (2014) Genome-wide trans-ancestry meta-analysis provides insight into the genetic architecture of type 2 diabetes susceptibility. Nat Genet 46:234–244CrossRefPubMed Mahajan A (2014) Genome-wide trans-ancestry meta-analysis provides insight into the genetic architecture of type 2 diabetes susceptibility. Nat Genet 46:234–244CrossRefPubMed
26.
go back to reference Janbon M, Chaptal J, Vedel A, Schaap J (1942) Accidents hypoglycémiques graves par un sulfamidothiodiazol (le VK 57 ou 2254 RP). Montp Med 441:21–22 Janbon M, Chaptal J, Vedel A, Schaap J (1942) Accidents hypoglycémiques graves par un sulfamidothiodiazol (le VK 57 ou 2254 RP). Montp Med 441:21–22
27.
go back to reference Gloyn AL, Weedon MN, Owen KR et al (2003) Large-scale association studies of variants in genes encoding the pancreatic beta-cell KATP channel subunits Kir6.2 (KCNJ11) and SUR1 (ABCC8) confirm that the KCNJ11 E23K variant is associated with type 2 diabetes. Diabetes 52:568–572CrossRefPubMed Gloyn AL, Weedon MN, Owen KR et al (2003) Large-scale association studies of variants in genes encoding the pancreatic beta-cell KATP channel subunits Kir6.2 (KCNJ11) and SUR1 (ABCC8) confirm that the KCNJ11 E23K variant is associated with type 2 diabetes. Diabetes 52:568–572CrossRefPubMed
28.
go back to reference Hani EH, Boutin P, Durand E et al (1998) Missense mutations in the pancreatic islet beta cell inwardly rectifying K+ channel gene (KIR6.2/BIR): a meta-analysis suggests a role in the polygenic basis of type II diabetes mellitus in Caucasians. Diabetologia 41:1511–1515CrossRefPubMed Hani EH, Boutin P, Durand E et al (1998) Missense mutations in the pancreatic islet beta cell inwardly rectifying K+ channel gene (KIR6.2/BIR): a meta-analysis suggests a role in the polygenic basis of type II diabetes mellitus in Caucasians. Diabetologia 41:1511–1515CrossRefPubMed
29.
go back to reference Gloyn AL, Hashim Y, Ashcroft SJ, Ashfield R, Wiltshire S, Turner RC (2001) Association studies of variants in promoter and coding regions of beta-cell ATP-sensitive K-channel genes SUR1 and Kir6.2 with type 2 diabetes mellitus (UKPDS 53). Diabet Med 18:206–212CrossRefPubMed Gloyn AL, Hashim Y, Ashcroft SJ, Ashfield R, Wiltshire S, Turner RC (2001) Association studies of variants in promoter and coding regions of beta-cell ATP-sensitive K-channel genes SUR1 and Kir6.2 with type 2 diabetes mellitus (UKPDS 53). Diabet Med 18:206–212CrossRefPubMed
30.
go back to reference Hamming KS, Soliman D, Matemisz LC et al (2009) Coexpression of the type 2 diabetes susceptibility gene variants KCNJ11 E23K and ABCC8 S1369A alter the ATP and sulfonylurea sensitivities of the ATP-sensitive K(+) channel. Diabetes 58:2419–2424CrossRefPubMedPubMedCentral Hamming KS, Soliman D, Matemisz LC et al (2009) Coexpression of the type 2 diabetes susceptibility gene variants KCNJ11 E23K and ABCC8 S1369A alter the ATP and sulfonylurea sensitivities of the ATP-sensitive K(+) channel. Diabetes 58:2419–2424CrossRefPubMedPubMedCentral
31.
go back to reference Proks P, Reimann F, Green N, Gribble F, Ashcroft F (2002) Sulfonylurea stimulation of insulin secretion. Diabetes 51(Suppl 3):S368–S376 Proks P, Reimann F, Green N, Gribble F, Ashcroft F (2002) Sulfonylurea stimulation of insulin secretion. Diabetes 51(Suppl 3):S368–S376
32.
go back to reference Sladek R, Rocheleau G, Rung J et al (2007) A genome-wide association study identifies novel risk loci for type 2 diabetes. Nature 445:881–885CrossRefPubMed Sladek R, Rocheleau G, Rung J et al (2007) A genome-wide association study identifies novel risk loci for type 2 diabetes. Nature 445:881–885CrossRefPubMed
33.
34.
35.
go back to reference Bush WS, Oetjens MT, Crawford DC (2016) Unravelling the human genome-phenome relationship using phenome-wide association studies. Nat Rev Genet 17:129–145CrossRefPubMed Bush WS, Oetjens MT, Crawford DC (2016) Unravelling the human genome-phenome relationship using phenome-wide association studies. Nat Rev Genet 17:129–145CrossRefPubMed
36.
go back to reference Shiota C, Coffey J, Grimsby J, Grippo JF, Magnuson MA (1999) Nuclear import of hepatic glucokinase depends upon glucokinase regulatory protein, whereas export is due to a nuclear export signal sequence in glucokinase. J Biol Chem 274:37125–37130CrossRefPubMed Shiota C, Coffey J, Grimsby J, Grippo JF, Magnuson MA (1999) Nuclear import of hepatic glucokinase depends upon glucokinase regulatory protein, whereas export is due to a nuclear export signal sequence in glucokinase. J Biol Chem 274:37125–37130CrossRefPubMed
37.
go back to reference Dupuis J, Langenberg C, Prokopenko I et al (2010) New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk. Nat Genet 42:105–116CrossRefPubMedPubMedCentral Dupuis J, Langenberg C, Prokopenko I et al (2010) New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk. Nat Genet 42:105–116CrossRefPubMedPubMedCentral
38.
go back to reference Lloyd DJ, St Jean DJ Jr, Kurzeja RJ et al (2013) Antidiabetic effects of glucokinase regulatory protein small-molecule disruptors. Nature 504:437–440CrossRefPubMed Lloyd DJ, St Jean DJ Jr, Kurzeja RJ et al (2013) Antidiabetic effects of glucokinase regulatory protein small-molecule disruptors. Nature 504:437–440CrossRefPubMed
39.
go back to reference Matschinsky FM (2009) Assessing the potential of glucokinase activators in diabetes therapy. Nat Rev Drug Discov 8:399–416CrossRefPubMed Matschinsky FM (2009) Assessing the potential of glucokinase activators in diabetes therapy. Nat Rev Drug Discov 8:399–416CrossRefPubMed
40.
go back to reference Saxena R, Voight BF, Lyssenko V et al (2007) Genome-wide association analysis identifies loci for type 2 diabetes and triglyceride levels. Science 316:1331–1336CrossRefPubMed Saxena R, Voight BF, Lyssenko V et al (2007) Genome-wide association analysis identifies loci for type 2 diabetes and triglyceride levels. Science 316:1331–1336CrossRefPubMed
41.
go back to reference Orho-Melander M, Melander O, Guiducci C et al (2008) Common missense variant in the glucokinase regulatory protein gene is associated with increased plasma triglyceride and C-reactive protein but lower fasting glucose concentrations. Diabetes 57:3112–3121CrossRefPubMedPubMedCentral Orho-Melander M, Melander O, Guiducci C et al (2008) Common missense variant in the glucokinase regulatory protein gene is associated with increased plasma triglyceride and C-reactive protein but lower fasting glucose concentrations. Diabetes 57:3112–3121CrossRefPubMedPubMedCentral
42.
go back to reference Johansen CT, Wang J, Lanktree MB et al (2010) Excess of rare variants in genes identified by genome-wide association study of hypertriglyceridemia. Nat Genet 42:684–687CrossRefPubMedPubMedCentral Johansen CT, Wang J, Lanktree MB et al (2010) Excess of rare variants in genes identified by genome-wide association study of hypertriglyceridemia. Nat Genet 42:684–687CrossRefPubMedPubMedCentral
43.
go back to reference Beer NL, Tribble ND, McCulloch LJ et al (2009) The P446L variant in GCKR associated with fasting plasma glucose and triglyceride levels exerts its effect through increased glucokinase activity in liver. Hum Mol Genet 18:4081–4088CrossRefPubMedPubMedCentral Beer NL, Tribble ND, McCulloch LJ et al (2009) The P446L variant in GCKR associated with fasting plasma glucose and triglyceride levels exerts its effect through increased glucokinase activity in liver. Hum Mol Genet 18:4081–4088CrossRefPubMedPubMedCentral
44.
go back to reference Rees MG, Wincovitch S, Schultz J et al (2012) Cellular characterisation of the GCKR P446L variant associated with type 2 diabetes risk. Diabetologia 55:114–122CrossRefPubMed Rees MG, Wincovitch S, Schultz J et al (2012) Cellular characterisation of the GCKR P446L variant associated with type 2 diabetes risk. Diabetologia 55:114–122CrossRefPubMed
45.
go back to reference Rees MG, Ng D, Ruppert S et al (2012) Correlation of rare coding variants in the gene encoding human glucokinase regulatory protein with phenotypic, cellular, and kinetic outcomes. J Clin Invest 122:205–217CrossRefPubMed Rees MG, Ng D, Ruppert S et al (2012) Correlation of rare coding variants in the gene encoding human glucokinase regulatory protein with phenotypic, cellular, and kinetic outcomes. J Clin Invest 122:205–217CrossRefPubMed
46.
go back to reference Rees MG, Raimondo A, Wang J et al (2014) Inheritance of rare functional GCKR variants and their contribution to triglyceride levels in families. Hum Mol Genet 23:5570–5578CrossRefPubMedPubMedCentral Rees MG, Raimondo A, Wang J et al (2014) Inheritance of rare functional GCKR variants and their contribution to triglyceride levels in families. Hum Mol Genet 23:5570–5578CrossRefPubMedPubMedCentral
47.
go back to reference Meininger GE, Scott R, Alba M et al (2011) Effects of MK-0941, a novel glucokinase activator, on glycemic control in insulin-treated patients with type 2 diabetes. Diabetes Care 34:2560–2566CrossRefPubMedPubMedCentral Meininger GE, Scott R, Alba M et al (2011) Effects of MK-0941, a novel glucokinase activator, on glycemic control in insulin-treated patients with type 2 diabetes. Diabetes Care 34:2560–2566CrossRefPubMedPubMedCentral
48.
go back to reference De Ceuninck F, Kargar C, Ilic C et al (2013) Small molecule glucokinase activators disturb lipid homeostasis and induce fatty liver in rodents: a warning for therapeutic applications in humans. Br J Pharmacol 168:339–353CrossRefPubMed De Ceuninck F, Kargar C, Ilic C et al (2013) Small molecule glucokinase activators disturb lipid homeostasis and induce fatty liver in rodents: a warning for therapeutic applications in humans. Br J Pharmacol 168:339–353CrossRefPubMed
50.
go back to reference Ehrenkranz JR, Lewis NG, Kahn CR, Roth J (2005) Phlorizin: a review. Diabetes Metab Res Rev 21:31–38CrossRefPubMed Ehrenkranz JR, Lewis NG, Kahn CR, Roth J (2005) Phlorizin: a review. Diabetes Metab Res Rev 21:31–38CrossRefPubMed
51.
go back to reference Kanai Y, Lee WS, You G, Brown D, Hediger MA (1994) The human kidney low affinity Na+/glucose cotransporter SGLT2. Delineation of the major renal reabsorptive mechanism for D-glucose. J Clin Invest 93:397–404CrossRefPubMedPubMedCentral Kanai Y, Lee WS, You G, Brown D, Hediger MA (1994) The human kidney low affinity Na+/glucose cotransporter SGLT2. Delineation of the major renal reabsorptive mechanism for D-glucose. J Clin Invest 93:397–404CrossRefPubMedPubMedCentral
52.
go back to reference van den Heuvel LP, Assink K, Willemsen M, Monnens L (2002) Autosomal recessive renal glucosuria attributable to a mutation in the sodium glucose cotransporter (SGLT2). Hum Genet 111:544–547CrossRefPubMed van den Heuvel LP, Assink K, Willemsen M, Monnens L (2002) Autosomal recessive renal glucosuria attributable to a mutation in the sodium glucose cotransporter (SGLT2). Hum Genet 111:544–547CrossRefPubMed
53.
go back to reference Tancredi M, Rosengren A, Svensson AM et al (2015) Excess mortality among persons with type 2 diabetes. N Engl J Med 373:1720–1732CrossRefPubMed Tancredi M, Rosengren A, Svensson AM et al (2015) Excess mortality among persons with type 2 diabetes. N Engl J Med 373:1720–1732CrossRefPubMed
55.
56.
go back to reference Smith GD, Ebrahim S (2003) ‘Mendelian randomization’: can genetic epidemiology contribute to understanding environmental determinants of disease? Int J Epidemiol 32:1–22CrossRefPubMed Smith GD, Ebrahim S (2003) ‘Mendelian randomization’: can genetic epidemiology contribute to understanding environmental determinants of disease? Int J Epidemiol 32:1–22CrossRefPubMed
57.
go back to reference Smith GD, Ebrahim S (2004) Mendelian randomization: prospects, potentials, and limitations. Int J Epidemiol 33:30–42CrossRefPubMed Smith GD, Ebrahim S (2004) Mendelian randomization: prospects, potentials, and limitations. Int J Epidemiol 33:30–42CrossRefPubMed
58.
go back to reference Schmidt AF, Swerdlow DI, Holmes MV et al (2016) PCSK9 genetic variants and risk of type 2 diabetes: a mendelian randomisation study. Lancet Diabetes Endocrinol 5:97–105CrossRefPubMed Schmidt AF, Swerdlow DI, Holmes MV et al (2016) PCSK9 genetic variants and risk of type 2 diabetes: a mendelian randomisation study. Lancet Diabetes Endocrinol 5:97–105CrossRefPubMed
59.
go back to reference Ference BA, Robinson JG, Brook RD et al (2016) Variation in PCSK9 and HMGCR and risk of cardiovascular disease and diabetes. N Engl J Med 375:2144–2153CrossRefPubMed Ference BA, Robinson JG, Brook RD et al (2016) Variation in PCSK9 and HMGCR and risk of cardiovascular disease and diabetes. N Engl J Med 375:2144–2153CrossRefPubMed
60.
go back to reference Rastegar-Mojarad M, Ye Z, Kolesar JM, Hebbring SJ, Lin SM (2015) Opportunities for drug repositioning from phenome-wide association studies. Nat Biotechnol 33:342–345CrossRefPubMed Rastegar-Mojarad M, Ye Z, Kolesar JM, Hebbring SJ, Lin SM (2015) Opportunities for drug repositioning from phenome-wide association studies. Nat Biotechnol 33:342–345CrossRefPubMed
61.
go back to reference Sanseau P, Agarwal P, Barnes MR et al (2012) Use of genome-wide association studies for drug repositioning. Nat Biotechnol 30:317–320CrossRefPubMed Sanseau P, Agarwal P, Barnes MR et al (2012) Use of genome-wide association studies for drug repositioning. Nat Biotechnol 30:317–320CrossRefPubMed
62.
go back to reference Sanseau P, Agarwal P, Barnes MR et al (2013) Reply to rational drug repositioning by medical genetics. Nat Biotechnol 31:1082CrossRefPubMed Sanseau P, Agarwal P, Barnes MR et al (2013) Reply to rational drug repositioning by medical genetics. Nat Biotechnol 31:1082CrossRefPubMed
63.
go back to reference Wang ZY, Zhang HY (2013) Rational drug repositioning by medical genetics. Nat Biotechnol 31:1080–1082CrossRefPubMed Wang ZY, Zhang HY (2013) Rational drug repositioning by medical genetics. Nat Biotechnol 31:1080–1082CrossRefPubMed
64.
go back to reference Althari S, Gloyn AL (2015) When is it MODY? Challenges in the interpretation of sequence variants in MODY genes. Rev Diabet Stud 12:330–348CrossRefPubMed Althari S, Gloyn AL (2015) When is it MODY? Challenges in the interpretation of sequence variants in MODY genes. Rev Diabet Stud 12:330–348CrossRefPubMed
65.
go back to reference Gloyn AL, Pearson ER, Antcliff JF et al (2004) Activating mutations in the gene encoding the ATP-sensitive potassium-channel subunit Kir6.2 and permanent neonatal diabetes. N Engl J Med 350:1838–1849CrossRefPubMed Gloyn AL, Pearson ER, Antcliff JF et al (2004) Activating mutations in the gene encoding the ATP-sensitive potassium-channel subunit Kir6.2 and permanent neonatal diabetes. N Engl J Med 350:1838–1849CrossRefPubMed
66.
go back to reference Pearson ER, Flechtner I, Njolstad PR et al (2006) Switching from insulin to oral sulfonylureas in patients with diabetes due to Kir6.2 mutations. N Engl J Med 355:467–477CrossRefPubMed Pearson ER, Flechtner I, Njolstad PR et al (2006) Switching from insulin to oral sulfonylureas in patients with diabetes due to Kir6.2 mutations. N Engl J Med 355:467–477CrossRefPubMed
67.
go back to reference Sagen JV, Raeder H, Hathout E et al (2004) Permanent neonatal diabetes due to mutations in KCNJ11 encoding Kir6.2: patient characteristics and initial response to sulfonylurea therapy. Diabetes 53:2713–2718CrossRefPubMed Sagen JV, Raeder H, Hathout E et al (2004) Permanent neonatal diabetes due to mutations in KCNJ11 encoding Kir6.2: patient characteristics and initial response to sulfonylurea therapy. Diabetes 53:2713–2718CrossRefPubMed
68.
go back to reference Shepherd M, Pearson ER, Houghton J, Salt G, Ellard S, Hattersley AT (2003) No deterioration in glycemic control in HNF-1alpha maturity-onset diabetes of the young following transfer from long-term insulin to sulphonylureas. Diabetes Care 26:3191–3192CrossRefPubMed Shepherd M, Pearson ER, Houghton J, Salt G, Ellard S, Hattersley AT (2003) No deterioration in glycemic control in HNF-1alpha maturity-onset diabetes of the young following transfer from long-term insulin to sulphonylureas. Diabetes Care 26:3191–3192CrossRefPubMed
69.
go back to reference Pearson ER, Pruhova S, Tack CJ et al (2005) Molecular genetics and phenotypic characteristics of MODY caused by hepatocyte nuclear factor 4alpha mutations in a large European collection. Diabetologia 48:878–885CrossRefPubMed Pearson ER, Pruhova S, Tack CJ et al (2005) Molecular genetics and phenotypic characteristics of MODY caused by hepatocyte nuclear factor 4alpha mutations in a large European collection. Diabetologia 48:878–885CrossRefPubMed
70.
go back to reference Pearson ER, Starkey BJ, Powell RJ, Gribble FM, Clark PM, Hattersley AT (2003) Genetic cause of hyperglycaemia and response to treatment in diabetes. Lancet 362:1275–1281CrossRefPubMed Pearson ER, Starkey BJ, Powell RJ, Gribble FM, Clark PM, Hattersley AT (2003) Genetic cause of hyperglycaemia and response to treatment in diabetes. Lancet 362:1275–1281CrossRefPubMed
71.
go back to reference McCarthy MI (2017) Painting a new picture of personalised medicine for diabetes. Diabetologia 60:793–799 McCarthy MI (2017) Painting a new picture of personalised medicine for diabetes. Diabetologia 60:793–799
73.
go back to reference Franks PW, McCarthy MI (2016) Exposing the exposures responsible for type 2 diabetes and obesity. Science 354:69–73CrossRefPubMed Franks PW, McCarthy MI (2016) Exposing the exposures responsible for type 2 diabetes and obesity. Science 354:69–73CrossRefPubMed
75.
go back to reference Steinthorsdottir V, Thorleifsson G, Sulem P (2014) Identification of low-frequency and rare sequence variants associated with elevated or reduced risk of type 2 diabetes. Nat Genet 46:294–298CrossRefPubMed Steinthorsdottir V, Thorleifsson G, Sulem P (2014) Identification of low-frequency and rare sequence variants associated with elevated or reduced risk of type 2 diabetes. Nat Genet 46:294–298CrossRefPubMed
76.
go back to reference Bouatia-Naji N, Rocheleau G, Van Lommel L et al (2008) A polymorphism within the G6PC2 gene is associated with fasting plasma glucose levels. Science 320:1085–1088CrossRefPubMed Bouatia-Naji N, Rocheleau G, Van Lommel L et al (2008) A polymorphism within the G6PC2 gene is associated with fasting plasma glucose levels. Science 320:1085–1088CrossRefPubMed
77.
go back to reference Chen WM, Erdos MR, Jackson AU et al (2008) Variations in the G6PC2/ABCB11 genomic region are associated with fasting glucose levels. J Clin Invest 118:2620–2628PubMedPubMedCentral Chen WM, Erdos MR, Jackson AU et al (2008) Variations in the G6PC2/ABCB11 genomic region are associated with fasting glucose levels. J Clin Invest 118:2620–2628PubMedPubMedCentral
78.
go back to reference Mahajan A, Sim X, Ng HJ et al (2015) Identification and functional characterization of G6PC2 coding variants influencing glycemic traits define an effector transcript at the G6PC2-ABCB11 locus. PLoS Genet 11:e1004876CrossRefPubMedPubMedCentral Mahajan A, Sim X, Ng HJ et al (2015) Identification and functional characterization of G6PC2 coding variants influencing glycemic traits define an effector transcript at the G6PC2-ABCB11 locus. PLoS Genet 11:e1004876CrossRefPubMedPubMedCentral
79.
go back to reference Wessel J, Chu AY, Willems SM et al (2015) Low-frequency and rare exome chip variants associate with fasting glucose and type 2 diabetes susceptibility. Nat Commun 6:5897CrossRefPubMedPubMedCentral Wessel J, Chu AY, Willems SM et al (2015) Low-frequency and rare exome chip variants associate with fasting glucose and type 2 diabetes susceptibility. Nat Commun 6:5897CrossRefPubMedPubMedCentral
80.
go back to reference Thomsen SK, McCarthy MI, Gloyn AL (2016) The importance of context: uncovering species- and tissue-specific effects of genetic risk variants for type 2 diabetes. Front Endocrinol 7:112CrossRef Thomsen SK, McCarthy MI, Gloyn AL (2016) The importance of context: uncovering species- and tissue-specific effects of genetic risk variants for type 2 diabetes. Front Endocrinol 7:112CrossRef
81.
go back to reference Moltke I, Grarup N, Jorgensen ME et al (2014) A common Greenlandic TBC1D4 variant confers muscle insulin resistance and type 2 diabetes. Nature 512:190–193CrossRefPubMed Moltke I, Grarup N, Jorgensen ME et al (2014) A common Greenlandic TBC1D4 variant confers muscle insulin resistance and type 2 diabetes. Nature 512:190–193CrossRefPubMed
82.
go back to reference GTEx Consortium (2015) Human genomics. The genotype-tissue expression (GTEx) pilot analysis: multitissue gene regulation in humans. Science 348:648–660CrossRefPubMedCentral GTEx Consortium (2015) Human genomics. The genotype-tissue expression (GTEx) pilot analysis: multitissue gene regulation in humans. Science 348:648–660CrossRefPubMedCentral
83.
go back to reference Voight BF, Scott LJ, Steinthorsdottir V et al (2010) Twelve type 2 diabetes susceptibility loci identified through large-scale association analysis. Nat Genet 42:579–589CrossRefPubMedPubMedCentral Voight BF, Scott LJ, Steinthorsdottir V et al (2010) Twelve type 2 diabetes susceptibility loci identified through large-scale association analysis. Nat Genet 42:579–589CrossRefPubMedPubMedCentral
84.
go back to reference Dimas AS, Lagou V, Barker A et al (2014) Impact of type 2 diabetes susceptibility variants on quantitative glycemic traits reveals mechanistic heterogeneity. Diabetes 63:2158–2171CrossRefPubMedPubMedCentral Dimas AS, Lagou V, Barker A et al (2014) Impact of type 2 diabetes susceptibility variants on quantitative glycemic traits reveals mechanistic heterogeneity. Diabetes 63:2158–2171CrossRefPubMedPubMedCentral
85.
go back to reference Fadista J, Vikman P, Laakso EO et al (2014) Global genomic and transcriptomic analysis of human pancreatic islets reveals novel genes influencing glucose metabolism. Proc Natl Acad Sci U S A 111:13924–13929CrossRefPubMedPubMedCentral Fadista J, Vikman P, Laakso EO et al (2014) Global genomic and transcriptomic analysis of human pancreatic islets reveals novel genes influencing glucose metabolism. Proc Natl Acad Sci U S A 111:13924–13929CrossRefPubMedPubMedCentral
86.
go back to reference van de Bunt M, Manning Fox JE, Dai X et al (2015) Transcript expression data from human islets links regulatory signals from genome-wide association studies for type 2 diabetes and glycemic traits to their downstream effectors. PLoS Genet 11:e1005694CrossRefPubMedPubMedCentral van de Bunt M, Manning Fox JE, Dai X et al (2015) Transcript expression data from human islets links regulatory signals from genome-wide association studies for type 2 diabetes and glycemic traits to their downstream effectors. PLoS Genet 11:e1005694CrossRefPubMedPubMedCentral
87.
go back to reference Gaulton KJ, Ferreira T, Lee Y et al (2015) Genetic fine mapping and genomic annotation defines causal mechanisms at type 2 diabetes susceptibility loci. Nat Genet 47:1415–1425CrossRefPubMedPubMedCentral Gaulton KJ, Ferreira T, Lee Y et al (2015) Genetic fine mapping and genomic annotation defines causal mechanisms at type 2 diabetes susceptibility loci. Nat Genet 47:1415–1425CrossRefPubMedPubMedCentral
88.
go back to reference Tuomi T, Nagorny CL, Singh P et al (2016) Increased melatonin signaling is a risk factor for type 2 diabetes. Cell Metab 23:1067–1077CrossRefPubMed Tuomi T, Nagorny CL, Singh P et al (2016) Increased melatonin signaling is a risk factor for type 2 diabetes. Cell Metab 23:1067–1077CrossRefPubMed
89.
go back to reference Bonnefond A, Clement N, Fawcett K et al (2012) Rare MTNR1B variants impairing melatonin receptor 1B function contribute to type 2 diabetes. Nat Genet 44:297–301CrossRefPubMedPubMedCentral Bonnefond A, Clement N, Fawcett K et al (2012) Rare MTNR1B variants impairing melatonin receptor 1B function contribute to type 2 diabetes. Nat Genet 44:297–301CrossRefPubMedPubMedCentral
90.
go back to reference Thomsen SK, Ceroni A, van de Bunt M et al (2016) Systematic functional characterization of candidate causal genes for type 2 diabetes risk variants. Diabetes 65:3805–3811CrossRefPubMed Thomsen SK, Ceroni A, van de Bunt M et al (2016) Systematic functional characterization of candidate causal genes for type 2 diabetes risk variants. Diabetes 65:3805–3811CrossRefPubMed
Metadata
Title
Human genetics as a model for target validation: finding new therapies for diabetes
Authors
Soren K. Thomsen
Anna L. Gloyn
Publication date
01-06-2017
Publisher
Springer Berlin Heidelberg
Published in
Diabetologia / Issue 6/2017
Print ISSN: 0012-186X
Electronic ISSN: 1432-0428
DOI
https://doi.org/10.1007/s00125-017-4270-y

Other articles of this Issue 6/2017

Diabetologia 6/2017 Go to the issue