2. Diabetes mellitus classification
1 Type 1 diabetes
2 Type 2 diabetes
3 Gestational diabetes mellitus (GDM)
4 Specific types of diabetes due to other causes, e.g., monogenic
diabetes syndromes
(such as neonatal diabetes and maturity-onset diabetes of the young
[MODY]), diseases of the exocrine pancreas (such as cystic fibrosis),
and drug-induced diabetes American Diabetes Association. Classification and diagnosis of diabetes. Sec. 2. In Standards of Medical Carein Diabetes—2015.
Diabetes Care 2015;38(Suppl.1):S8–S16
3. Monogenic diabetes mellitus
• rare forms of diabetes result from mutations in a single gene
• reduce the body's ability to produce insulin
• account for about 1 to 5 percent of all cases of diabetes in young people.
• In most cases, the gene mutation is inherited
4. • Heterogeneous clinical characteristics
• Important implications for management
• Allows appropriate counseling of other family members
Monogenic diabetes mellitus
5. Problems in detection
• Clinical features, probability calculator still has limitation
• Molecular genetic testing is not feasible
6. • GAD, Islet autoantibodies, C-peptide has been shown to be a
highly sensitive and specific biomarker for discriminating
between type 1 and type 2 diabetes and MODY
• Combined diagnostic performance of the two biomarkers as a
screening pathway has not been assessed
Problems in detection
8. Subject
• Diagnosed at age 30 years or younger
• Currently aged younger than 50 years
• In the catchment areas of the Royal Devon and Exeter NHS
Foundation Trust (Exeter, U.K.) and Ninewells Hospital (Dundee,
U.K.)
9. Dia
Non-insulin
treated
T2DM or
atypical T1DM
DiaDiagnosed < 30 yr oldDiagnosed < 30 yr old
Dia
Diagnosed < 30 yr
old
Insulin treated
DiaDiagnosed < 30 yr oldC-peptide (UCPCR)
DiaDiagnosed < 30 yr oldGAD & IA2 Antibodies
DiaDiagnosed < 30 yr old
Genetic testing:
All monogenic subtypes
-
-
+
+ Monogenic
diabetes
T1DM
T1DM
+
-
Non-insulin treated
11. Urinary C-peptide/creatinine ratio
(UCPCR)
• Spot urine
• 2 h after the largest carbohydrate-containing meal of the day
• Post to the laboratory within 72 h
• Electrochemiluminescence immunoassay (lower limit of the C-peptide assay was 0.03 nmol/L)
12. Glutamic Acid Decarboxylase, Islet Autoantibody Measurement
• Checked for previous GAD and IA2 results
• Commercial ELISA assays (RSR Ltd., Cardiff, U.K.)
• Considered positive for antibodies if their results were >99th percentile
• were considered positive for an- tibodies if their results were .99th centile (64 World Health
Organization units/mL for GAD and 15 World Health Organiza- tion units/mL for IA2)
13. Molecular Genetic Testing
• DNA sequencing of HNF1A, HNF4A, and GCK was performed by
PCR amplification of purified genomic DNA, followed by Sanger
DNA sequencing of each gene’s exons and flanking intronic regions.
• Targeted Next-Generation Sequencing for 35 Genes in Which
Mutations Are Known to Cause Monogenic Diabetes.
15. Flow chart of patients recruited as part of UNITED. Biomarker screening pathway in 1,376 patients with no
known genetic cause for their diabetes in Exeter and Tayside.
Beverley M. Shields et al. Dia Care 2017;40:1017-1025
16. Baseline characteristics of the 1365 patients who completed the biomarker screening pathway with no existing known cause for their diabetes: Data
shown as median (IQR)
Characteristics Median(IQR1,IQR3)
Male (n (%)) 706 (52%)
Age at diagnosis (y) 13 (8,21)
Age at recruitment (y) 29 (19,40)
Duration of diabetes (y) 13.6 (5.6, 22.7)
BMI* (kg/m2
) 25.7 (23.2, 29.0)
HbA1c 8.7 (7.8, 9.9)
Current treatment (n (%)): Diet OHA Insulin
+/- OHA
15 (1%) 69 (5%) 1281 (94%)
White Caucasian (n(%)) 1389 (98%)
Pediatric (<20years) (n(%)) 351 (26%)
17. Distribution of genetic causes of 54 confirmed cases of monogenic diabetes in Exeter and Dundee. Data presented as
number of cases caused by mutations in each gene - grey bars indicate cases where the diagnosis was made prior to this
study, black bars are those diagnosed as a result of the biomarker pathway.
19. Conclusion
• biomarker screening pathway is a systematic, cheap and easily
implemented approach to screening
• picked up new cases of monogenic diabetes, even in areas of
existing high detection
• high NPV of 99.9% indicates it is an extremely effective approach
for ruling out monogenic diabetes.
20. Discussion
• Health economic evaluation of the pathway for detecting the
common forms of MODY (GCK, HNF1A, and HNF4A) has
shown cost-saving
• Help with management, prognosis, and advice on risk to other
family members
21. Discussion• Only 8 out of 51 (16%) of patients with a genetic diagnosis of
monogenic diabetes in our cohort were in the pediatric age range
(younger than 20 years) at the time of recruitment
• We showed that by using clinical features alone, over half of the
cases of monogenic diabetes would be missed.
22. limitation
• Small numbers of patients to evaluate the sensitivity of the pathway
• Coincidental Type 1 diabetes with MODY
• Screening using C-peptide and antibody testing, the PPV is still fairly low at 20%
• Further studies are integrating the pathway with clinical features, such as the MODY
calculator
• this study comprised a 98% white population and assesses patients at a median of 14 years
after diagnosis.
25. • Common MODY gene, mechanism
• Benefit for pt
https://www.ncbi.nlm.nih.gov/pubmed/22218698?access_num=22218698&li
nk_type=MED&dopt=Abstract
Calculator.
weaker for detect-
ing MODY in insulin-treated patients
compared with non–insulin-treated
patients
26.
27. Type OMIM Gene/protein Description
MODY 1 125850
hepatocyte nuclear
factor 4α
Due to a loss-of-function mutation in the HNF4α gene. 5%–10% cases.
MODY 2 125851 glucokinase
Due to any of several mutations in the GCK gene. 30%–70% cases. Mild fasting hyperglycemia throughout life.
Small rise on glucose loading. Patients do not tend to get diabetes complications and do not require treatment.[17]
MODY 3 600496
hepatocyte nuclear
factor 1α
Mutations of the HNF1α gene (a homeobox gene). 30%–70% cases. Tend to be responsive to sulfonylureas. Low
renal threshold for glucose.
MODY 4 606392
insulin promoter
factor-1
Mutations of the IPF1 homeobox (Pdx1) gene. < 1% cases. Associated with pancreatic agensis in homozygotes a
occasionally in heterozygotes.
MODY 5 137920
hepatocyte nuclear
factor 1β
One of the less common forms of MODY, with some distinctive clinical features, including atrophy of the pancreas
and several forms of renal disease. Defect in HNF-1 beta gene. 5%–10% cases.
MODY 6 606394
neurogenic
differentiation 1
Mutations of the gene for the transcription factor referred to as neurogenic differentiation 1. Very rare: 5 families
reported to date.
MODY 7 610508 Kruppel-like factor 11 KLF11 has been associated with a form of diabetes[18] that has been characterized as "MODY7" by OMIM.[19]
MODY 8 609812
Bile salt dependent
lipase
CEL has been associated with a form of diabetes[20] that has been characterized as "MODY8" by OMIM.[21] It is ver
rare with five families reported to date. It is associated with exocrine pancreatic dysfunction.
MODY 9 612225 PAX4 Pax4 is a transcription factor. MODY 9 is a very rare medical condition.
MODY 10 613370 INS Mutations in the insulin gene. Usually associated with neonatal diabetes. Rare < 1% cases.
MODY 11 613375 BLK Mutated B-lymphocyte tyrosin kinase, which is also present in pancreatic islet cells. Very rare.
Permanent
neonatal
diabetes
mellitus
606176 KCNJ11 and ABCC8
A newly identified and potentially treatable form of monogenic diabetes is the neonatal diabetes caused by activat
mutations of the ABCC8 or KCNJ11 genes which encode subunits of the KATP channel. < 1% cases. Tend to respo
to sulfonylureas.
Transient
neonatal
diabetes
601410
610374 ABCC8 Some forms of neonatal-onset diabetes are not permanent. < 1% cases. Tend to respond to sulfonylureas.
Editor's Notes
1 Type 1 diabetes (due to β-cell destruction, usually leading to absolute insulin deficiency)
2 Type 2 diabetes (due to a progressive insulin secretory defect on the background of insulin resistance)
3 Gestational diabetes mellitus (GDM) (diabetes diagnosed in the second or third trimester of pregnancy that is not clearly overt diabetes)
4 Specific types of diabetes due to other causes, e.g., monogenic diabetes syndromes (such as neonatal diabetes and maturity-onset diabetes of the young [MODY]), diseases of the exocrine pancreas (such as cystic fibrosis), and drug- or chemical-induced diabetes (such as in the treatment of HIV/AIDS or after organ transplantation)
heterogeneous clinical characteristics may not be reliable in predicting the underlying pathogenesis
Many patients are misclassified as having either type 1 or 2 diabetes
It is estimated that at least 80% of patients with Maturity Onset Diabetes of the Young (MODY) are misdiagnosed
Important implications for management of an individual’s diabetes, a prognosis, and recognition of associated clinical features;
The most common form of diabetes in children and young adults is type 1 diabetes, accounting for 90% of cases.
Patients with MODY misclassified as type 1 diabetes will be treated with insulin.
mutations in the HNF1A or HNF4A genes respond well to low-dose sulphonylureas and those with MODY because of mutations in the GCK gene require no pharmacological treatment
weaker for detect-
ing MODY in insulin-treated patients
compared with non–insulin-treated
patients.
GAD and IA2 islet autoanti- bodies with cross-sectional studies showing they are present in 80% of patients with type 1 diabetes and in ,1% of patients with MODY
Furthermore, the combined diag- nostic performance of the two bio- markers as a screening pathway has not been formally assessed.
screening pathway using both C-peptide and islet autoanti- bodies to exclude type 1 diabetes in two populations with previously high pickup rates of MODY (3)
The UNITED biomarker screening pathway to investigate etiology of diabetes in patients diagnosed at age 30 years or younger.
Genetic testing is carried out on all patients who have endogenous insulin (UCPCR ≥0.2 nmol/mmol) and do not have either GAD or IA2 islet autoantibodies. Patients without endogenous insulin or with GAD and/or IA2 islet autoantibodies are classed as having type 1 diabetes.
(
Recruitment bias
To determine whether there was any potential bias in recruitment of MODY patients that may affect our prevalence estimate, we also obtained summary data on the number of patients with pre- viously confirmed monogenic diabetes in each study area who had not been re- cruited into this study)
+
UCPCR >=0.2 nmol/mmol were considered to have significant en- dogenous insulin secretion (10).
(UCPCR
-The total quantity of C-peptide excreted in the urine per day represents 5%–10% of pancreatic secretion, compared with only 0.1% of secreted insulin
-24h UCPCR to glucagon test : Two-hour postprandial urinary C-peptide/creatinine quotient turned out to be slightly less sensitive (89%) than the glucagon test (94%) and of equal specificity (96%). Glucagon-stimulated plasma C-peptide and postprandial urinary C-peptide excretion correlated significantly among insulin-requiring diabetics (r = 0.73), but not among non-insulin-requiring diabetics (r = 0.23))
(Dynex DSX automated ELISA system (Launch Diag- nostics, Longfield, U.K.)
Patients were considered positive for antibodies if their results were >99th centile (64 World Health Organization units/mL for GAD and 15 World Health Organization units/mL for IA2)
(Both meth- ods are highly specific and sensitive (GAD antibodies, 98 and 84%, and IA-2 anti- bodies, 99 and 74%, respectively).
The prevalence of GAD and IA-2 antibodies in maturity-onset diabetes of the young is the same as in control subjects (< 1%). )
Significant Endogenous Insulin and Negative Antibody Results
(Dosage analysis of HNF1A, HNF4A, and GCK for partial- and whole- gene deletions was also performed by multiplex ligation-dependent probe am- plification using the MRC-Holland MODY multiplex ligation-dependent probe am- plification kit (P241-B1). )
If no patho- genic mutation was identified in HNF1A, HNF4A, or GCK, further targeted next- generation sequencing 35 monogenic diabetes genes
(all genes in which mutations are known to cause MODY, neonatal dia- betes, and other genetic diabetic syn- dromes) using a custom SureSelect exon-capture assay (Agilent Technolo- gies, Santa Clara, CA) (17) (see Supple- mentary Data and Supplementary Table 1 for methodology, sensitivity, and details of genes tested).
Flow chart of patients recruited as part of UNITED. Biomarker screening pathway in 1,376 patients with no known genetic cause for their diabetes in Exeter and Tayside.11 dropped out. Seventeen new cases of monogenic diabetes detected (*one case identified through exome sequencing).
A total of 2,288 patients were eligible in area, and 1,418 subjects (62%) in total consented to the study and were recruited: 716 from the Exeter area and 702 from Dundee. A total of 11 pa- tients dropped out (9 did not provide blood samples for antibody testing, and 2 did not provide samples for DNA testing).
Of the 1,407 remaining patients, 1,365 had no known genetic cause for their diabetes.
subse- quent results on the screening pathway are based on these patients. A total of 42 patients had a known genetic cause for their diabetes prior to participating in this pathway: 34 patients had con- firmed monogenic diabetes (Table 1), and 8 patients had cystic fibrosis–related diabetes.
Identifies 17 New Cases of Monogenic Diabetes
2 pa- tients were anuric because of renal failure and therefore went straight on to antibody testing.
those diagnosed with monogenic diabetes as part of the study were less likely to have a parent known to be affected than those with a previous known monogenic diagnosis (8 out of 17 [47%] vs. 29 out of 34 [85%];
the proportion of known monogenic diabetes prior to the study in the recruited population (34 out of 1,407 [2.4%]) was similar to the proportion in the nonrecruited pop- ulation (26 out of 870 [3.0%]) (P = 0.4), suggesting no overall bias in recruitment.
There was no difference in terms of age at diagnosis (mean 18 vs. 19 years; P = 0.5), age at time of recruitment (using 2011 for nonrecruited patients) (32 vs. 32 years; P = 0.98), or sex (35 female vs. 45% male; P = 0.4).
standard clinical criteria for MODY (age at diagnosis younger than 25 years, non– insulin-requiring, and a parent known to be affected with diabetes)
higher pickup rate and PPV (57.6%) than the biomarker pathway, but the majority of monogenic cases would have been missed (63% compared with 0% for the biomarker pathway)
MODY probability calculator also had a higher PPV (40.4%), but missed more cases (55%)
Prevalence performance
(U.K. UCPCR cost of £10.80 and antibodies cost of £20),
The cost-effectiveness of additional testing for other forms of monogenic diabetes has not been assessed. change from insulin to sulphonylur- eas is still possible in cases diagnosed with ABCC8 and KCNJ11
(Cost saving ADA 2013: The testing policy yielded an average gain of 0.012 QALYs and resulted in an ICER of 205,000 USD. Sensitivity analysis showed that if the MODY prevalence was 6%, the ICER would be ∼50,000 USD. If MODY prevalence was >30%, the testing policy was cost saving. Reducing genetic testing costs to 700 USD also resulted in an ICER of ∼50,000 USD.) type 2 diabetic patients 25–40 years old with a MODY prevalence of 2%.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3867988/
few studies that have systematically screened whole populations for monogenic diabetes.
The majority of studies have been in pediatric populations only, with only two studies that have screened adults
การศึกษานี้พบว่าการใช้biomarker based pathway สามารถinclude คนไข้เพิ่มขึ้นได้
, or whether this would result in more missed patients because of reduced testing.
clinically defined, rather than ge- netically confirmed, MODY (31) or use low cutoffs for antibody positivity,
To determine whether there was any potential bias in recruitment
26 patients with a diagnosis of monogenic diabetes in the Exeter and Tayside regions who met study inclusion criteria but were not recruited to the UNITED study. Therefore, the proportion of known monogenic diabetes prior to the study in the recruited population (34 out of 1,407 [2.4%]) was similar to the proportion in the nonrecruited pop- ulation (26 out of 870 [3.0%]) (P = 0.4)
(e.g., renal cysts associated with HNF1B) >>. Bad prognosis?
![Diabetes mellitus classification
1 Type 1 diabetes
2 Type 2 diabetes
3 Gestational diabetes mellitus (GDM)
4 Specific types of diabetes due to other causes, e.g., monogenic
diabetes syndromes
(such as neonatal diabetes and maturity-onset diabetes of the young
[MODY]), diseases of the exocrine pancreas (such as cystic fibrosis),
and drug-induced diabetes American Diabetes Association. Classification and diagnosis of diabetes. Sec. 2. In Standards of Medical Carein Diabetes—2015.
Diabetes Care 2015;38(Suppl.1):S8–S16](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)