Genetics of diabetes
From Ganfyd
Contents |
Polygenetic diabetes mellitus
There are multiple associations of Type 1 and Type 2 diabetes mellitus with particular genotypes. These associations only predispose to the respective condition and are not predictive nor have any known therapeutic implications. They are consistent with Type 1 diabetes being an autoimmune disease and Type 2 diabetes being a polygenetic condition like essential hypertension.
Type 1 diabetes associations
- A diagram of the known relevant human gene signals and processes for Type 1 Diabetes exists.
- A database on the genes implicated in type 1 diabetes is at T1DBase
- HLA DQ haplotypes show strongest association.
- Other major histocompatibility complex (MHC)associations
- HLA DR haplotypes
- Major histocompatibility complex I related gene A (MIC-A) gene
- Genes outside MHC
- Lymphoid protein tyrosine phosphatase (PTPN22) gene
- Cytotoxic T lymphocyte-associated antigen-4 CTLA4 gene
- Insulin INS gene.
Type 2 diabetes associations
There are multiple weak but proven associations[1].Attempts to use the multiple known genetic loci associated with risk of type 2 diabetes to predict diabetes are little more successful than using classic clinical risk factors[2].
The reproducible associations to date include:
- KCNJ11 E23K polymorphism[3]
- Present in 40% of population increases risk of diabetes by a fifth.
- TCF7L2[3] [4]
- PPARG[3]
- CDKAL1[4]
- IGF2BP2[4]
- JAZF1[5] [4]
- CDC123[5]
- CAMK1D[5]
- TSPAN8/lGR5[5]
- THADA[5]
- ADAMTS9[5][4]
- NOTCH2[5]
- Region on chromosome 9
Monogenetic diabetes mellitus
Up to two per cent (probably less, but the papers will be biased towards tertiary centres) of those with diabetes mellitus actually have monogenetic diabetes. This can have very important therapeutic and prognostic implications if diagnosed. To date 6 different genes have been associated with maturity-onset diabetes of the young (MODY)[6].
Maturity-onset Diabetes of the Young (MODY)
- Glycolytic enzyme glucokinase
- Onset at birth
- Stable hyperglycaemia
- Complications rare
- Treat by diet
- Beta cell transcription factors (complications frequent)
- HNF1α MODY (hepatic nuclear factor-1α maturity-onset diabetes of the young) is most common
- Incidence 1:20,000 in Uk
- Age of onset results in misdiagnosis typically as Type 1 (younger patients) or Type 2 (older patients)
- Autosomial dominant
- Little risk microvascular complications
- Extremely sensitive to sulphonylureas(four times as sensitive as type 2 diabetics)
- HNF4α monogenetic diabetes
- Also respond to sulphonylureas
- HNF1β monogenetic diabetes
- Insulin promoter factor 1 monogenetic diabetes
- NeuroD1 monogenetic diabetes
- HNF1α MODY (hepatic nuclear factor-1α maturity-onset diabetes of the young) is most common
Neonatal Diabetes Mellitus
- Multiple rare genetic causes
- Commonest is of Kir6.2 subunit of beta cell K+ATP channel
- Often a spontaneous mutation
- Half of permanent neonatal diabetes mellitus (PNDM)
- Beta cell remains in hyperpolarised state so can not secrete insulin
- Many mutations respond to high dose sulphonylureas ( Act on the sulphonylurea receptor 1 (SUR1) subunit of K+ATP channel)[7]
- Presentation
- Low birth weight
- At diagnosis (can be up to 6 months) marked hyperglycaemia or even ketoacidosis
- No pancreatic autoantibodies
- Rarely in context of DEND syndrome
- Developmental delay
- Epilepsy
- Neonatal Diabetes
- One variety, the V59M mutation responds specifically to glibenclamide with improved muscle strength and concentration as predicted by glibenclamide actions on the SUR2 receptor on nerve and muscle cells)
References
- ↑ Lango H, Palmer CN, Morris AD, Zeggini E, Hattersley AT, McCarthy MI, Frayling TM, Weedon MN. Assessing the combined impact of 18 common genetic variants of modest effect sizes on type 2 diabetes risk. Diabetes. 2008 Nov; 57(11):3129-35.(Link to article – subscription may be required.)
- ↑ Meigs JB, Shrader P, Sullivan LM, McAteer JB, Fox CS, Dupuis J, Manning AK, Florez JC, Wilson PW, D'Agostino RB, Cupples LA. Genotype score in addition to common risk factors for prediction of type 2 diabetes. The New England journal of medicine. 2008 Nov 20; 359(21):2208-19.(Link to article – subscription may be required.)
- ↑ a b c Thorsby PM, Midthjell K, Gjerlaugsen N, Holmen J, Hanssen KF, Birkeland KI, Berg JP. Comparison of genetic risk in three candidate genes (TCF7L2, PPARG, KCNJ11) with traditional risk factors for type 2 diabetes in a population-based study - the HUNT study. Scandinavian journal of clinical and laboratory investigation. 2008 Oct 29; :1-6.(Epub ahead of print) (Link to article – subscription may be required.)
- ↑ a b c d e van Hoek M, Dehghan A, Witteman JC, van Duijn CM, Uitterlinden AG, Oostra BA, Hofman A, Sijbrands EJ, Janssens AC. Predicting type 2 diabetes based on polymorphisms from genome-wide association studies: a population-based study. Diabetes. 2008 Nov; 57(11):3122-8.(Link to article – subscription may be required.)
- ↑ a b c d e f g Zeggini E, Scott LJ, Saxena R, Voight BF, Marchini JL, Hu T, de Bakker PI, Abecasis GR, Almgren P, Andersen G, Ardlie K, Boström KB, Bergman RN, Bonnycastle LL, Borch-Johnsen K, Burtt NP, Chen H, Chines PS, Daly MJ, Deodhar P, Ding CJ, Doney AS, Duren WL, Elliott KS, Erdos MR, Frayling TM, Freathy RM, Gianniny L, Grallert H, Grarup N, Groves CJ, Guiducci C, Hansen T, Herder C, Hitman GA, Hughes TE, Isomaa B, Jackson AU, Jørgensen T, Kong A, Kubalanza K, Kuruvilla FG, Kuusisto J, Langenberg C, Lango H, Lauritzen T, Li Y, Lindgren CM, Lyssenko V, Marvelle AF, Meisinger C, Midthjell K, Mohlke KL, Morken MA, Morris AD, Narisu N, Nilsson P, Owen KR, Palmer CN, Payne F, Perry JR, Pettersen E, Platou C, Prokopenko I, Qi L, Qin L, Rayner NW, Rees M, Roix JJ, Sandbaek A, Shields B, Sjögren M, Steinthorsdottir V, Stringham HM, Swift AJ, Thorleifsson G, Thorsteinsdottir U, Timpson NJ, Tuomi T, Tuomilehto J, Walker M, Watanabe RM, Weedon MN, Willer CJ, Illig T, Hveem K, Hu FB, Laakso M, Stefansson K, Pedersen O, Wareham NJ, Barroso I, Hattersley AT, Collins FS, Groop L, McCarthy MI, Boehnke M, Altshuler D. Meta-analysis of genome-wide association data and large-scale replication identifies additional susceptibility loci for type 2 diabetes. Nature genetics. 2008 May; 40(5):638-45.(Link to article – subscription may be required.)
- ↑ Hattersley AT. Molecular genetics goes to the diabetes clinic. Clin Med 2005;5;476-81
- ↑ Koster JC, Remedi MS, Dao C, Nichols CG. ATP and sulfonylurea sensitivity of mutant ATP-sensitive K+ channels in neonatal diabetes: implications for pharmacogenomic therapy. Diabetes. 2005; 54(9):2645-54