Search tips
Search criteria

Results 1-12 (12)

Clipboard (0)

Select a Filter Below

Year of Publication
Document Types
1.  Common variants near ATM are associated with glycemic response to metformin in type 2 diabetes 
Nature genetics  2010;43(2):117-120.
Metformin is the most commonly used pharmacological therapy for type 2 diabetes. We carried out a GWA study on glycaemic response to metformin in 1024 Scottish patients with type 2 diabetes. Replication was in two cohorts consisting of 1783 Scottish patients and 1113 patients from the UK Prospective Diabetes Study. In a meta-analysis (n=3920) we observed an association (P=2.9 *10−9) for a SNP rs11212617 at a locus containing the ataxia telangiectasia mutated (ATM) gene with an odds ratio of 1.35 (95% CI 1.22 to 1.49) for treatment success. In a rat hepatoma cell line, inhibition of ATM with KU-55933 attenuated the phosphorylation and activation of AMPK in response to metformin. We conclude that ATM, a gene known to be involved in DNA repair and cell cycle control, plays a role in the effect of metformin upstream of AMPK, and variation in this gene alters glycaemic response to metformin.
PMCID: PMC3030919  PMID: 21186350
2.  Reduced-Function SLC22A1 Polymorphisms Encoding Organic Cation Transporter 1 and Glycemic Response to Metformin: A GoDARTS Study 
Diabetes  2009;58(6):1434-1439.
Metformin is actively transported into the liver by the organic cation transporter (OCT)1 (encoded by SLC22A1). In 12 normoglycemic individuals, reduced-function variants in SLC22A1 were shown to decrease the ability of metformin to reduce glucose excursion in response to oral glucose. We assessed the effect of two common loss-of-function polymorphisms in SLC22A1 on metformin response in a large cohort of patients with type 2 diabetes.
The Diabetes Audit and Research in Tayside Scotland (DARTS) database includes prescribing and biochemistry information and clinical phenotypes of all patients with diabetes within Tayside, Scotland, from 1992 onwards. R61C and 420del variants of SLC22A1 were genotyped in 3,450 patients with type 2 diabetes who were incident users of metformin. We assessed metformin response by modeling the maximum A1C reduction in 18 months after starting metformin and investigated whether a treatment target of A1C <7% was achieved. Sustained metformin effect on A1C between 6 and 42 months was also assessed, as was the time to metformin monotherapy failure. Covariates were SLC22A1 genotype, BMI, average drug dose, adherence, and creatinine clearance.
A total of 1,531 patients were identified with a definable metformin response. R61C and 420del variants did not affect the initial A1C reduction (P = 0.47 and P = 0.92, respectively), the chance of achieving a treatment target (P = 0.83 and P = 0.36), the average A1C on monotherapy up to 42 months (P = 0.44 and P = 0.75), or the hazard of monotherapy failure (P = 0.85 and P = 0.56).
The SLC22A1 loss-of-function variants, R61C and 420del, do not attenuate the A1C reduction achieved by metformin in patients with type 2 diabetes.
PMCID: PMC2682689  PMID: 19336679
3.  Glycemic Exposure and Blood Pressure Influencing Progression and Remission of Diabetic Retinopathy 
Diabetes Care  2013;36(12):3979-3984.
This study sought to investigate the progression and regression of diabetic retinopathy (DR) and the effects of population risk factors on the rates of transition across retinopathy stages.
The study cohort consisted of 44,871 observed DR events between the calendar years 1990 and 2011 for 4,758 diabetic patients who were diagnosed at 35 years of age or older. The first retinal observation was recorded within a year from diagnosis, and the result was recorded as free of retinopathy. A multistate Markov model was applied for analyzing the development of DR and its relation to the patterns of changes in risk factors.
We observed a consistent risk effect of HbA1c on the progression (no retinopathy to mild background DR [BDR] hazard ratio per SD of HbA1c [HR] 1.42 [95% CI 1.32–1.52], mild BDR to observable BDR HR 1.32 [95% CI 1.08–1.60], and observable BDR to severe nonproliferative/proliferative DR HR 2.23 [95% CI 1.16–4.29]). Similarly, systolic blood pressure (SBP) and diastolic blood pressure increased the risk for the transition from the asymptomatic phase to mild BDR (HR 1.20 [95% CI 1.11–1.30]) and the mild BDR to observable BDR (HR 1.87 [95% CI 1.46–2.40]), respectively. Regression from mild BDR to no DR was associated with lower SBP (HR 0.79 [95% CI 0.64–0.97]) and lower HbA1c (HR 0.76 [95% CI 0.64–0.89]).
Progression and regression of DR were strongly associated with blood pressure and glycemic exposure.
PMCID: PMC3836116  PMID: 24170761
4.  The CTRB1/2 Locus Affects Diabetes Susceptibility and Treatment via the Incretin Pathway 
Diabetes  2013;62(9):3275-3281.
The incretin hormone glucagon-like peptide 1 (GLP-1) promotes glucose homeostasis and enhances β-cell function. GLP-1 receptor agonists (GLP-1 RAs) and dipeptidyl peptidase-4 (DPP-4) inhibitors, which inhibit the physiological inactivation of endogenous GLP-1, are used for the treatment of type 2 diabetes. Using the Metabochip, we identified three novel genetic loci with large effects (30–40%) on GLP-1–stimulated insulin secretion during hyperglycemic clamps in nondiabetic Caucasian individuals (TMEM114; CHST3 and CTRB1/2; n = 232; all P ≤ 8.8 × 10−7). rs7202877 near CTRB1/2, a known diabetes risk locus, also associated with an absolute 0.51 ± 0.16% (5.6 ± 1.7 mmol/mol) lower A1C response to DPP-4 inhibitor treatment in G-allele carriers, but there was no effect on GLP-1 RA treatment in type 2 diabetic patients (n = 527). Furthermore, in pancreatic tissue, we show that rs7202877 acts as expression quantitative trait locus for CTRB1 and CTRB2, encoding chymotrypsinogen, and increases fecal chymotrypsin activity in healthy carriers. Chymotrypsin is one of the most abundant digestive enzymes in the gut where it cleaves food proteins into smaller peptide fragments. Our data identify chymotrypsin in the regulation of the incretin pathway, development of diabetes, and response to DPP-4 inhibitor treatment.
PMCID: PMC3749354  PMID: 23674605
5.  Robust association of the LPA locus with LDLc lowering response to statin treatment in a meta-analysis of 30,467 individuals from both randomised control trials and observational studies and association with coronary artery disease outcome during statin treatment 
Pharmacogenetics and genomics  2013;23(10):518-525.
The LPA SNP rs10455872 has been associated with low density lipoprotein cholesterol (LDLc) lowering response to statins in several randomised control trials (RCTs) and is a known coronary artery disease (CAD) marker. However it is unclear what residual risk of CAD this marker may have during statin treatment.
Using electronic medical records linked to the GoDARTS genotyped population we identified over 8000 patients on statins in Tayside, Scotland.
We replicated the findings of the RCTs, with the G allele of rs10455872 being associated with a 0.10mmol/l per allele poorer reduction in LDLc in response to statin treatment, and conducted a meta-analysis with previously published RCTs (P=1.46×10−29, n=30,467). We demonstrate an association between rs10455872 and CAD in statin treated individuals and have replicated this finding in the Utrecht Cardiovascular Pharmacogenetics Study (combined odds ratio 1·41, 95% CI 1.17-1.68, P=4.5×10−5, n=8822) suggesting that statin treatment does not abrogate this well-established genetic risk for CAD. Furthermore in a Cox proportional hazards model with LDLc measured time dependently we demonstrated the relationship between CAD and rs10455872 was independent of LDLc during statin treatment.
Individuals with the G allele of rs10455872, which represents approximately 1 in 7 patients, have a higher risk of CAD than the majority of the population even after treatment with statins, and therefore represent a vulnerable group requiring an alternative medication in addition to statin treatment.
PMCID: PMC4110714  PMID: 23903772
Lipoproteins; drug response; pharmacogenetics; HMG CoA Reductase inhibitors; coronary artery disease
6.  Clinical and genetic determinants of progression of type 2 diabetes: A DIRECT Study 
Diabetes care  2013;37(3):718-724.
The rate at which diabetes progresses following diagnosis of type 2 diabetes is highly variable between individuals.
Research Design and Methods
We studied 5250 patients with type 2 diabetes using comprehensive electronic medical records on all patients in Tayside, Scotland from 1992 onwards. We investigated the association of clinical, biochemical and genetic factors with the risk of progression of type 2 diabetes from diagnosis to requirement for insulin treatment (defined as insulin treatment or HbA1c ≥8.5%/69 mmol/mol treated with two or more non-insulin diabetes therapies).
Risk of progression was associated with both low and high BMI. In an analysis stratified by BMI and HbA1c at diagnosis, faster progression was independently associated with younger age at diagnosis, higher log triacylglyceride concentrations (Hazard Ratio (HR) 1.28 per mmol/L (95% CI 1.15-1.42)) and lower HDL concentrations (HR 0.70 per mmol/L (95% CI 0.55-0.87)). A high genetic risk score derived from 61 diabetes risk variants was associated with a younger age of diagnosis, a younger age at starting insulin, but was not associated with the progression rate from diabetes to requirement for insulin treatment.
Increased triacylglyceride and low HDL are independently associated with increased rate of progression of diabetes. The genetic factors that predispose to diabetes are different from those that cause rapid progression of diabetes suggesting a difference in biological process that needs further investigation.
PMCID: PMC4038744  PMID: 24186880
7.  Heritability of variation in glycaemic response to metformin: a genome-wide complex trait analysis 
Metformin is a first-line oral agent used in the treatment of type 2 diabetes, but glycaemic response to this drug is highly variable. Understanding the genetic contribution to metformin response might increase the possibility of personalising metformin treatment. We aimed to establish the heritability of glycaemic response to metformin using the genome-wide complex trait analysis (GCTA) method.
In this GCTA study, we obtained data about HbA1c concentrations before and during metformin treatment from patients in the Genetics of Diabetes Audit and Research in Tayside Scotland (GoDARTS) study, which includes a cohort of patients with type 2 diabetes and is linked to comprehensive clinical databases and genome-wide association study data. We applied the GCTA method to estimate heritability for four definitions of glycaemic response to metformin: absolute reduction in HbA1c; proportional reduction in HbA1c; adjusted reduction in HbA1c; and whether or not the target on-treatment HbA1c of less than 7% (53 mmol/mol) was achieved, with adjustment for baseline HbA1c and known clinical covariates. Chromosome-wise heritability estimation was used to obtain further information about the genetic architecture.
5386 individuals were included in the final dataset, of whom 2085 had enough clinical data to define glycaemic response to metformin. The heritability of glycaemic response to metformin varied by response phenotype, with a heritability of 34% (95% CI 1–68; p=0·022) for the absolute reduction in HbA1c, adjusted for pretreatment HbA1c. Chromosome-wise heritability estimates suggest that the genetic contribution is probably from individual variants scattered across the genome, which each have a small to moderate effect, rather than from a few loci that each have a large effect.
Glycaemic response to metformin is heritable, thus glycaemic response to metformin is, in part, intrinsic to individual biological variation. Further genetic analysis might enable us to make better predictions for stratified medicine and to unravel new mechanisms of metformin action.
Wellcome Trust.
PMCID: PMC4038749  PMID: 24731673
8.  Pharmacogenetics of Oral Antidiabetic Drugs 
Oral antidiabetic drugs (OADs) are used for more than a half-century in the treatment of type 2 diabetes. Only in the last five years, intensive research has been conducted in the pharmacogenetics of these drugs based mainly on the retrospective register studies, but only a handful of associations detected in these studies were replicated. The gene variants in CYP2C9, ABCC8/KCNJ11, and TCF7L2 were associated with the effect of sulfonylureas. CYP2C9 encodes sulfonylurea metabolizing cytochrome P450 isoenzyme 2C9, ABCC8 and KCNJ11 genes encode proteins constituting ATP-sensitive K+ channel which is a therapeutic target for sulfonylureas, and TCF7L2 is a gene with the strongest association with type 2 diabetes. SLC22A1, SLC47A1, and ATM gene variants were repeatedly associated with the response to metformin. SLC22A1 and SLC47A1 encode metformin transporters OCT1 and MATE1, respectively. The function of a gene variant near ATM gene identified by a genome-wide association study is not elucidated so far. The first variant associated with the response to gliptins is a polymorphism in the proximity of CTRB1/2 gene which encodes chymotrypsinogen. Establishment of diabetes pharmacogenetics consortia and reduction in costs of genomics might lead to some significant clinical breakthroughs in this field in a near future.
PMCID: PMC3845331  PMID: 24324494
9.  Molecular mechanism of action of metformin: old or new insights? 
Diabetologia  2013;56(9):1898-1906.
Metformin is the first-line drug treatment for type 2 diabetes. Globally, over 100 million patients are prescribed this drug annually. Metformin was discovered before the era of target-based drug discovery and its molecular mechanism of action remains an area of vigorous diabetes research. An improvement in our understanding of metformin’s molecular targets is likely to enable target-based identification of second-generation drugs with similar properties, a development that has been impossible up to now. The notion that 5' AMP-activated protein kinase (AMPK) mediates the anti-hyperglycaemic action of metformin has recently been challenged by genetic loss-of-function studies, thrusting the AMPK-independent effects of the drug into the spotlight for the first time in more than a decade. Key AMPK-independent effects of the drug include the mitochondrial actions that have been known for many years and which are still thought to be the primary site of action of metformin. Coupled with recent evidence of AMPK-independent effects on the counter-regulatory hormone glucagon, new paradigms of AMPK-independent drug action are beginning to take shape. In this review we summarise the recent research developments on the molecular action of metformin.
PMCID: PMC3737434  PMID: 23835523
AMPK; Biguanide; Energy metabolism; Gluconeogenesis; LKB1; Mitochondrial respiration; Organic cation transporter; Review; Type 2 diabetes
10.  New loci associated with birth weight identify genetic links between intrauterine growth and adult height and metabolism 
Horikoshi, Momoko | Yaghootkar, Hanieh | Mook-Kanamori, Dennis O. | Sovio, Ulla | Taal, H. Rob | Hennig, Branwen J. | Bradfield, Jonathan P. | St. Pourcain, Beate | Evans, David M. | Charoen, Pimphen | Kaakinen, Marika | Cousminer, Diana L. | Lehtimäki, Terho | Kreiner-Møller, Eskil | Warrington, Nicole M. | Bustamante, Mariona | Feenstra, Bjarke | Berry, Diane J. | Thiering, Elisabeth | Pfab, Thiemo | Barton, Sheila J. | Shields, Beverley M. | Kerkhof, Marjan | van Leeuwen, Elisabeth M. | Fulford, Anthony J. | Kutalik, Zoltán | Zhao, Jing Hua | den Hoed, Marcel | Mahajan, Anubha | Lindi, Virpi | Goh, Liang-Kee | Hottenga, Jouke-Jan | Wu, Ying | Raitakari, Olli T. | Harder, Marie N. | Meirhaeghe, Aline | Ntalla, Ioanna | Salem, Rany M. | Jameson, Karen A. | Zhou, Kaixin | Monies, Dorota M. | Lagou, Vasiliki | Kirin, Mirna | Heikkinen, Jani | Adair, Linda S. | Alkuraya, Fowzan S. | Al-Odaib, Ali | Amouyel, Philippe | Andersson, Ehm Astrid | Bennett, Amanda J. | Blakemore, Alexandra I.F. | Buxton, Jessica L. | Dallongeville, Jean | Das, Shikta | de Geus, Eco J. C. | Estivill, Xavier | Flexeder, Claudia | Froguel, Philippe | Geller, Frank | Godfrey, Keith M. | Gottrand, Frédéric | Groves, Christopher J. | Hansen, Torben | Hirschhorn, Joel N. | Hofman, Albert | Hollegaard, Mads V. | Hougaard, David M. | Hyppönen, Elina | Inskip, Hazel M. | Isaacs, Aaron | Jørgensen, Torben | Kanaka-Gantenbein, Christina | Kemp, John P. | Kiess, Wieland | Kilpeläinen, Tuomas O. | Klopp, Norman | Knight, Bridget A. | Kuzawa, Christopher W. | McMahon, George | Newnham, John P. | Niinikoski, Harri | Oostra, Ben A. | Pedersen, Louise | Postma, Dirkje S. | Ring, Susan M. | Rivadeneira, Fernando | Robertson, Neil R. | Sebert, Sylvain | Simell, Olli | Slowinski, Torsten | Tiesler, Carla M.T. | Tönjes, Anke | Vaag, Allan | Viikari, Jorma S. | Vink, Jacqueline M. | Vissing, Nadja Hawwa | Wareham, Nicholas J. | Willemsen, Gonneke | Witte, Daniel R. | Zhang, Haitao | Zhao, Jianhua | Wilson, James F. | Stumvoll, Michael | Prentice, Andrew M. | Meyer, Brian F. | Pearson, Ewan R. | Boreham, Colin A.G. | Cooper, Cyrus | Gillman, Matthew W. | Dedoussis, George V. | Moreno, Luis A | Pedersen, Oluf | Saarinen, Maiju | Mohlke, Karen L. | Boomsma, Dorret I. | Saw, Seang-Mei | Lakka, Timo A. | Körner, Antje | Loos, Ruth J.F. | Ong, Ken K. | Vollenweider, Peter | van Duijn, Cornelia M. | Koppelman, Gerard H. | Hattersley, Andrew T. | Holloway, John W. | Hocher, Berthold | Heinrich, Joachim | Power, Chris | Melbye, Mads | Guxens, Mònica | Pennell, Craig E. | Bønnelykke, Klaus | Bisgaard, Hans | Eriksson, Johan G. | Widén, Elisabeth | Hakonarson, Hakon | Uitterlinden, André G. | Pouta, Anneli | Lawlor, Debbie A. | Smith, George Davey | Frayling, Timothy M. | McCarthy, Mark I. | Grant, Struan F.A. | Jaddoe, Vincent W.V. | Jarvelin, Marjo-Riitta | Timpson, Nicholas J. | Prokopenko, Inga | Freathy, Rachel M.
Nature genetics  2012;45(1):76-82.
Birth weight within the normal range is associated with a variety of adult-onset diseases, but the mechanisms behind these associations are poorly understood1. Previous genome-wide association studies identified a variant in the ADCY5 gene associated both with birth weight and type 2 diabetes, and a second variant, near CCNL1, with no obvious link to adult traits2. In an expanded genome-wide association meta-analysis and follow-up study (up to 69,308 individuals of European descent from 43 studies), we have now extended the number of genome-wide significant loci to seven, accounting for a similar proportion of variance to maternal smoking. Five of the loci are known to be associated with other phenotypes: ADCY5 and CDKAL1 with type 2 diabetes; ADRB1 with adult blood pressure; and HMGA2 and LCORL with adult height. Our findings highlight genetic links between fetal growth and postnatal growth and metabolism.
PMCID: PMC3605762  PMID: 23202124
11.  Paradoxical Lower Serum Triglyceride Levels and Higher Type 2 Diabetes Mellitus Susceptibility in Obese Individuals with the PNPLA3 148M Variant 
PLoS ONE  2012;7(6):e39362.
Obesity is highly associated with elevated serum triglycerides, hepatic steatosis and type 2 diabetes (T2D). The I148M (rs738409) genetic variant of patatin-like phospholipase domain-containing 3 gene (PNPLA3) is known to modulate hepatic triglyceride accumulation, leading to steatosis. No association between PNPLA3 I148M genotype and T2D in Europeans has been reported. Aim of this study is to examine the relationship between PNPLA3 I148M genotypes and serum triglycerides, insulin resistance and T2D susceptibility by testing a gene-environment interaction model with severe obesity.
Methods and Findings
PNPLA3 I148M was genotyped in a large obese cohort, the SOS study (n = 3,473) and in the Go-DARTS (n = 15,448), a T2D case-control study. Metabolic parameters were examined across the PNPLA3 I148M genotypes in participants of the SOS study at baseline and at 2- and 10-year follow up after bariatric surgery or conventional therapy. The associations with metabolic parameters were validated in the Go-DARTS study. Serum triglycerides were found to be lower in the PNPLA3 148M carriers from the SOS study at baseline and from the Go-DARTS T2D cohort. An increased risk for T2D conferred by the 148M allele was found in the SOS study (O.R. 1.09, 95% C.I. 1.01-1.39, P = 0.040) and in severely obese individuals in the Go-DARTS study (O.R. 1.37, 95% C.I. 1.13-1.66, P = 0.001). The 148M allele was no longer associated with insulin resistance or T2D after bariatric surgery in the SOS study and no association with the 148M allele was observed in the less obese (BMI<35) individuals in the Go-DARTS study (P for interaction  = 0.002). This provides evidence for the obesity interaction with I48M allele and T2D risk in a large-scale cross-sectional and a prospective interventional study.
Severely obese individuals carrying the PNPLA3 148M allele have lower serum triglyceride levels, are more insulin resistant and more susceptible to T2D. This study supports the hypothesis that obesity-driven hepatic lipid accumulation may contribute to T2D susceptibility.
PMCID: PMC3377675  PMID: 22724004
12.  Macrosomia and Hyperinsulinaemic Hypoglycaemia in Patients with Heterozygous Mutations in the HNF4A Gene 
PLoS Medicine  2007;4(4):e118.
Macrosomia is associated with considerable neonatal and maternal morbidity. Factors that predict macrosomia are poorly understood. The increased rate of macrosomia in the offspring of pregnant women with diabetes and in congenital hyperinsulinaemia is mediated by increased foetal insulin secretion. We assessed the in utero and neonatal role of two key regulators of pancreatic insulin secretion by studying birthweight and the incidence of neonatal hypoglycaemia in patients with heterozygous mutations in the maturity-onset diabetes of the young (MODY) genes HNF4A (encoding HNF-4α) and HNF1A/TCF1 (encoding HNF-1α), and the effect of pancreatic deletion of Hnf4a on foetal and neonatal insulin secretion in mice.
Methods and Findings
We examined birthweight and hypoglycaemia in 108 patients from families with diabetes due to HNF4A mutations, and 134 patients from families with HNF1A mutations. Birthweight was increased by a median of 790 g in HNF4A-mutation carriers compared to non-mutation family members (p < 0.001); 56% (30/54) of HNF4A-mutation carriers were macrosomic compared with 13% (7/54) of non-mutation family members (p < 0.001). Transient hypoglycaemia was reported in 8/54 infants with heterozygous HNF4A mutations, but was reported in none of 54 non-mutation carriers (p = 0.003). There was documented hyperinsulinaemia in three cases. Birthweight and prevalence of neonatal hypoglycaemia were not increased in HNF1A-mutation carriers. Mice with pancreatic β-cell deletion of Hnf4a had hyperinsulinaemia in utero and hyperinsulinaemic hypoglycaemia at birth.
HNF4A mutations are associated with a considerable increase in birthweight and macrosomia, and are a novel cause of neonatal hypoglycaemia. This study establishes a key role for HNF4A in determining foetal birthweight, and uncovers an unanticipated feature of the natural history of HNF4A-deficient diabetes, with hyperinsulinaemia at birth evolving to decreased insulin secretion and diabetes later in life.
HNF4A mutations were found to be associated with a considerable increase in birthweight and macrosomia, and were a cause of neonatal hypoglycaemia.
Editors' Summary
MODY, or maturity-onset diabetes of the young, is a particular subtype of diabetes; only a few percent of people with diabetes are thought to have this subtype. The condition comes about as a result of a mutation in one of six genes. Generally, people with MODY have high glucose (sugar) levels in the blood, and the typical symptoms of diabetes, such as increased thirst and urination, typically develop when the person is below the age of 25 y. Two of the genes that are known to cause MODY are mutant forms of HNF4A and HNF1A. The proteins that are encoded by these two genes control insulin levels produced by the pancreas; when these genes are mutated, not enough insulin is produced. Without enough insulin to control blood sugar, levels rise, leading to the symptoms of diabetes. However, MODY can be managed by many of the same interventions as other types of diabetes, such as diet, exercise, drug treatments, and insulin injections.
Why Was This Study Done?
Although the evidence shows that individuals who carry mutations in HNF4A and HNF1A do not produce enough insulin and therefore have higher glucose levels in their blood, there were some tantalizing suggestions from mouse experiments that this might not be the whole story. Specifically, the researchers suspected that during embryonic development, mutations in HNF4A or HNF1A might actually cause higher insulin levels. Too much insulin during development of a fetus is known to cause it to gain weight, resulting in a baby that is larger than the average size for its age. Larger babies are risky for both the baby and the mother. The researchers doing this study wanted to understand more precisely what the links were between the forms of MODY caused by HNF4A and HNF1A mutations, and birth-weight and blood-sugar levels.
What Did the Researchers Do and Find?
In this study, the researchers examined 15 families in which some family members had MODY caused by a mutation in HNF4A. They compared the birthweight for family members carrying the mutation (54 people) against the birthweight for those who did not (54 people). A similar comparison was done for 38 families in which some members had a different form of MODY, this time caused by a mutation in HNF1A. The results showed that the birthweight of family members who carried a mutation in HNF4A was, on average, 790 g higher than the birthweight of family members who didn't carry the mutation. Low blood-sugar levels at birth were also more common in people carrying the HNF4A mutation as compared to people who did not. However, the HNF1A mutation did not seem to be associated with greater birthweight or low blood-sugar levels at birth. Finally, in order to understand these findings further, the researchers created embryonic mice carrying mutations in the mouse equivalent of HNF4A. These embryos produced more insulin than normal mouse embryos and, after birth, were more likely to have low blood-sugar levels.
What Do These Findings Mean?
These findings show that there is a link between mutations in HNF4A, but not in HNF1A, and increased birthweight. The increase found in this study is quite substantial (a median weight of 4,660 g in the affected babies; a birthweight of more than 4,000 g is generally considered large). The results suggest that in human embryos with a mutated form of HNF4A, too much insulin is produced during development, causing faster growth and a higher chance of the baby being born with low blood-sugar levels. This is an unexpected finding, because later in life the HNF4A mutation causes lower insulin levels. Therefore, the biochemical pathways causing this type of MODY seem to be quite complicated, and further research will need to be done to fully understand them. Crucially, the research also suggests that pregnant women carrying HNF4A mutations should be closely followed to check their baby's growth and minimize the chance of complications. Doctors and families should also consider doing a genetic test for HNF4A if a baby has low blood-sugar levels and if there is a family history of diabetes; this would increase the chance of diagnosing MODY early.
Additional Information.
Please access these Web sites via the online version of this summary at 0040118.
In a related Perspective in PLoS Medicine, Benjamin Glaser discusses causes of type 2 diabetes mellitus in the context of this study's findings
The US National Institute of Diabetes and Digestive and Kidney Diseases has pages of information on different types of diabetes
Wikipedia has an entry on Maturity Onset Diabetes of the Young (MODY) (note that Wikipedia is an internet encyclopedia that anyone can edit)
Diabetes Research Department, Peninsula Medical School, Exeter, UK provides information for patients and doctors on genetic types of diabetes; the website is maintained by the research group carrying out this study
Information from the Centers for Disease Control and Prevention on diabetes and pregnancy
PMCID: PMC1845156  PMID: 17407387

Results 1-12 (12)