GENES & DIABETES
Our genetic codes are our ‘script of life’ and resemble a huge dictionary containing billions of codes, similar to the design of a car which consists of many different parts that collectively function to make the car move.
These codes come from mother and father and reshuffle during mating to form the script of their offspring which determine their appearances, bodily function, disease traits etc.
Genetic profiles amongst family members are similar but not identical and the ways how these genes express themselves, can also be influenced by external factors like nutrition, education, lifestyle and medical treatment.
By identifying high risk subjects with genetic predisposition, we can empower these subjects to manage their risk and seek advice from health care professionals to reduce future risk of diabetes and its complications.
We provide tests related to diabetes including tests measuring beta cell sufficiency (C-peptide, Anti-GAD, Anti-IA2), screening for monogenetic diabetes as well as two genetic tests predicting probability of having diabetes and development of diabetes related complications.
APeople at risk or with diabetes who need regular monitoring and early intervention
DIABETES AND ITS COMPLICATIONS
DForesee™ and DProtect™ are tests based on combining patented genetic markers, non-modifiable (e.g. age and sex) and modifiable risk factors (e.g. smoking and body weight) to calculate the future risk of developing diabetes or its complications at a very early stage before these conditions appear.
Genetic markers related to developing diabetes or its complications will be tested and results will show the high and low risk DNA carried by users. By using proprietary risk algorithms, probability of having diabetes or developing of complications will be predicted from current age to age of 65 in DForesee™ or age of 75 in DProtect™.
This panel includes common variants implicated in development, structure and function of insulin-secreting cells. These genetic variants interact with one another and their effects are amplified by risk factors such as obesity and smoking. Carriers of these genetic variants may develop diabetes at an earlier age and some may need early drug use for control. Family members of people with diabetes are advised to learn about their genetic risk for having diabetes in order to take early preventive actions.
Please refer to www.mygemcode.com for details.
This panel includes common variants implicated in beta cell biology and interacting pathways which can be activated by high blood glucose, blood pressure and lipids levels to cause cardiovascular-renal disease. People with diabetes are advised to learn about their genetic risk for diabetic complications in order to intensify their control of risk factors (A1c, BP and LDL-C) including use of organ protective drugs for early prevention.
BPeople with young-onset and/or non-obese diabetes at high risk of beta cell insufficiency
- C PEPTIDE
- These biomarkers include precursors of insulin (C peptide) and autoimmune antibodies (anti-GAD and anti-IA-2) which indicate reserve of insulin-secreting cells. Non-obese patients especially those diagnosed before age of 40 with or without affected parents and/or siblings may have low C peptide and/or positive antibodies, which call for early drug treatment including insulin.
BETA CELL INSUFFICIENCY
CPeople with young-onset diabetes, especially having multiple generations affected, who may need extended family screening.
- MD PANEL (GK, HNF 1-alpha, HNF 1-beta)
- IAPP S20G
- The MD panel detects genetic mutations, unique to a family pedigree, which requires re-sequencing of all coding regions of known MODY (Maturity Onset Diabetes of the Young) genes in Chinese. These genetic mutations may be found in patients with multiple generations affected by diabetes with increasingly young age of diagnosis (e.g. less than 25 years old). Defining different types of MODY have treatment implications with some requiring insulin while others may benefit from sulphonylureas. The other genetic variants code for mitochondrial protein (MtA3243G) and islet amyloid polypeptide (IAPP S20G) and are found in less than 5% of people with diabetes. These patients often have reduced insulin secretion who may need early insulin treatment.
MONOGENIC DIABETES (MD PANEL)
TESTING PROCEDURES & USER INSTRUCTIONS
- Our test is simple and safe. Only trace amount of buccal cells (Buccal swab or spit kit) or blood (1-2mL) is needed. No prior procedures e.g. fasting or stop medication is required.
- A simple questionnaire about patients’ non-modifiable (e.g. age and sex) and modifiable risk factors (e.g. smoking and body weight) will need to be completed for analysis for providing individualized recommendations.
- Contact us at 2809 2893 to collect the specimen. The samples will be sent directly to our testing centre for genetic testing.
Report will be sent to you after several working days.
You may then explain and discuss the health plan with your patients or clients. Users of our services may also use our mobile app "MyGem" to review and update their reports and health status for tracking.
The result is divided into 2 main parts:
AResult of Genetic Risk
- If the DNA sequence is changed, the production, structure or function of the protein will be affected. For most genes, there are two copies, one inherited from the father and the other, from mother.
- If DNA changes occur in the genes involved in insulin production or regulation of blood glucose and cellular functions, the risk of developing diabetes or its complications will be increased. In general, more than one gene is implicated with the risk and this risk increases with increasing number of affected genes.
A high risk gene inherited from either your father or mother will give you 1 genetic risk score. Depending on your total genetic risk score, you may be categorized as high (6% in population), moderate-to-high (25% in population), moderate (49% in population), low-to-moderate (15% in population) and low (5% in population) risk groups.
There are a total of 5 genetic markers for DForesee™ and 8 genetic markers for DProtect™ tests.
- Involved with maturation of structure and function of insulin protein
- Involved in manufacturing process of insulin protein
- Involved in degradation of intracellular insulin and thereby terminate its activity
- Involved with the maturation of bodily organs including pancreas
- Involved in pancreatic islet development and differentiation of insulin-producing beta cells
- Conversion of blood glucose inside the cells to form other products accompanied by generation of oxidizing substances which can cause diabetic complications
- The protein encoded by this gene is involved in activating the transmission of signals within the cells to influence the cellular structure and functions. High blood glucose can increase the activity of this protein to cause cellular and organ damage resulting in diabetic complications
- The protein encoded by this gene is involved in the control of blood pressure and cellular functions. People with diabetes often have high level of this protein which can be inhibited by drugs to reduce the risk of complications
- These genes are implicated in the development, the structure and the function of insulin-secreting cells which regulate blood glucose level in the body. Hyperglycemia mediated by these genetic variants triggers a series of pathogenic pathways associated with vascular dysfunction.
BYour Probability Of Getting Diabetes / Diabetic Complications
In addition to genetic factors, there are other factors contributing to the risk. Diabetes is a disease of aging. Most young to middle aged people have low risk for diabetes but this can rapidly increase after the age of 50, especially in those with high genetic risk. In people who are obese or smoke, the risk of diabetes over time can be further increased. Our calculation algorithm can estimate your risk of having diabetes at current age as well as predicting your risk in later years. It can also estimate your risks after changing your lifestyle such as weight and smoking status.
Age and disease duration are two major factors in determining risk of diabetic complications (heart and kidney disease) which can be modified by good control of blood glucose (indicated by A1c level which is the average blood glucose in last 8-12 weeks), Blood pressure and Cholesterol (ABC) and use of medications. Due to long disease duration, for the same age and sex, people with young onset diabetes have higher risk than those with late onset disease. On average, 5 years after diagnosis, 10-50% of people with diabetes may develop these complications especially in people with high genetic risk. In these high risk subjects, the benefit of optimal control of modifiable risk factors is particularly evident.
USE OF REPORT
This report is useful for medical professionals to understand the health status of your patients. With a precise probability of current and other conditions, you will be able to have a better approach on your patient’s health plan by providing a target and motivation. Amongst diabetic subjects who use DProtect™ test, those with well-controlled blood glucose, blood pressure and blood lipids have reduced risk of developing these complications.
Since patients with high genetic risk are more likely to develop complications, good control of other risk factors which can be controlled through careful management is particularly important in such subjects. The importance of treatment adherence 1 and early use of organ-protective drugs, notably statins and renin angiotensin system inhibitors 2-5 to prevent life-threatening diseases can be informed by the test.
Report will also highlight the amplifying effects of age and disease duration on future risk of complications and the importance of act early to save life and money. In those subjects without diabetes, the report can inform their inherent risks of diabetes based on genetic risk score and family history and the impacts of weight reduction and cessation of smoking on their overall diabetes risk.
DNA markers discovery
Our Gemomic® Technology is based on decades of university research in our local population. Since 1995, we have established multiple prospective cohorts with ongoing evaluation to discover, evaluate and validate biomarkers for predicting diabetes and its complications including but not limited to heart disease, kidney failure, cancer, stroke and all-cause death.
These cohorts, databases and biobanks included 20,000 patients enrolled into the Hong Kong Diabetes Registry 6, 4500 adults and adolescents as control subjects 7-8 and 1000 first degree relatives of families of young onset diabetes 9.
We are also part of the Asian Genetic Epidemiology Network 10-11 and Global Diabetes Consortium 12, the latter supported by the United States National Institute of Health, which are our key collaborators for validating our discoveries, along with other universities in China, Europe, Australia, Singapore, Korea, Japan and USA.
Using family-based linkage analysis 9,13-15, investigations of candidate genes 16-20 and genome wide association studies 21-23, we have discovered rare and common genetic variants predictive of diabetes and its complications 24-26 with replication in other cohorts or supported by independent meta-analysis 27.
Based on the genetic markers discovered in our Chinese cohorts with validation in other Asian populations or independent analysis, we have developed proprietary risk algorithms combining these genetic markers with highly modifiable risk factors to predict probabilities of diabetes or its complications over time.
Given the subtle inter-ethnic differences in genomic architectures as well as distribution, frequency and effect size of these genetic variants within the same loci 21,28, these genetic markers and algorithms are highly applicable to Asian populations which account for 60% of the global population with diabetes 29. Despite the modest effect size of these individual risk factors, whether genetic 21 or non-genetic 30, their joint effects can be amplified to increase the odds to 3-10 folds in complex diseases due to multiple causes 31.
Based on these premises, we have used similar strategies to develop a large number of risk equations for predicting multiple diabetic complications with personalized reports and decision support which were proven to change practice and health care behaviors with positive clinical outcomes 32-34.
The tests are operated by qualified and well experienced registered medical laboratory technologists in a registered medical laboratory under the Hong Kong Supplementary Medical Professions Ordinance (Chapter 359).
- Wu JY, Leung WY, Chang S, Lee B, Zee B, Tong PC, et al. Effectiveness of telephone counselling by a pharmacist in reducing mortality in patients receiving polypharmacy: randomised controlled trial. Bmj. 2006 Sep 9;333(7567):522.
- Ting RZ, Yang X, Yu LW, Luk AO, Kong AP, Tong PC, et al. Lipid control and use of lipid-regulating drugs for prevention of cardiovascular events in Chinese type 2 diabetic patients: a prospective cohort study. Cardiovascular diabetology. 2011 Nov 22;9(1):77 doi: 10.1186/475-2840-9-77.
- Luk AO, Yang X, Ma RC, Ng VW, Yu LW, Lau WW, et al. Association of statin use and development of renal dysfunction in type 2 diabetes--the Hong Kong Diabetes Registry. Diabetes Res Clin Pract. 2010 Jun;88(3):227-33.
- Kong AP, Yang X, So WY, Luk A, Ma RC, Ozaki R, et al. Additive effects of blood glucose lowering drugs, statins and renin-angiotensin system blockers on all-site cancer risk in patients with type 2 diabetes. BMC Med. 2014;12:76.
- So WY, Chan N, Tong PCY, Chow CC, Chan WB, Ng MCY, et al. Effect of RAAS inhibition on survival and renal outcomes in 3737 Chinese Type 2 diabetic patients. Hypertension. 2004;44:294-9.
- Chan JC, So WY, Ma RCW, Tong P, Wong R, Yang XL. The complexity of both vascular and non-vascular complications of diabetes: The Hong Kong Diabetes Registry. Curr Cardiovasc Risk Rep. 2011;5(3):230-9.
- Ozaki R, Qiao Q, Wong GW, Chan MH, So WY, Tong PC, et al. Overweight, family history of diabetes and attending schools of lower academic grading are independent predictors for metabolic syndrome in Hong Kong Chinese adolescents. Archives of disease in childhood. 2007 Mar;92(3):224-8.
- Liu KH, Chan YL, Chan WB, Chan JC, Chu CW. Mesenteric fat thickness is an independent determinant of metabolic syndrome and identifies subjects with increased carotid intima-media thickness. Diabetes care. 2006 Feb;29(2):379-84.
- Li JKY, Ng MCY, So WY, Chiu C, Ozaki R, Tong PCY, et al. Phenotypic and genetic clustering of diabetes and metabolic syndrome in Chinese families with type 2 diabetes mellitus. Diabetes/metabolism research and reviews. 2006;22:46-52.
- Cho YS, Chen CH, Hu C, Long J, Hee Ong RT, Sim X, et al. Meta-analysis of genome-wide association studies identifies eight new loci for type 2 diabetes in east Asians. Nature genetics. 2011 Dec 11;44(1):67-72.
- Yamauchi T, Hara K, Maeda S, Yasuda K, Takahashi A, Horikoshi M, et al. A genome-wide association study in the Japanese population identifies susceptibility loci for type 2 diabetes at UBE2E2 and C2CD4A-C2CD4B. Nature genetics. 2010 Oct;42(10):864-8.
- Fuchsberger C, Flannick J, Teslovich TM, Mahajan A, Agarwala V, Gaulton KJ, et al. The genetic architecture of type 2 diabetes. Nature. 2016 Jul 11;536(7614):41-7. PubMed PMID: 27398621.
- Ng MCY, So WY, Cox NJ, Lam VKL, Cockram CS, Critchley JAJH, et al. Genome wide scan for type 2 diabetes loci in Hong Kong Chinese and confirmation of a susceptibility locus on chromosome 1q21-q25. Diabetes. 2004;53:1609-13.
- Ng MCY, So WY, Cox NJ, Lam VKL, Cockram CS, Bell GI, et al. Genome wide scan for metabolic syndrome and related quantitative traits in Hong Kong Chinese and confirmation of a susceptibility locus on chromosome 1q21-25. Diabetes. 2004;53:2676-83.
- Ng MCY, Miyake K, So WY, Poon EW, Lam VK, Li JKY, et al. The linkage and association of the gene encoding upstream stimulatory factor 1 with type 2 diabetes and metabolic syndrome in the Chinese population. Diabetologia. 2005;48:2018-24.
- Ng MCY, Cockburn BN, Yeung VTF, Chow CC, Cockram CS, Critchley JAJH, et al. Molecular genetics of diabetes mellitus in Chinese subjects: identification of mutations in glucokinase and HNF-1alpha in patients with early onset type 2 diabetes mellitus/MODY. Diabetic Medicine. 1999;16:956-63.
- Ng MCY, Yeung VTF, Chow CC, Li JKY, Smith PR, Mijovic CH, et al. Mitochondrial DNA A3243G mutation in patients with early or late onset Type 2 diabetes mellitus in Hong Kong Chinese. Journal of Endocrinology. 2000;52:557-64.
- Lee SC, Hashim Y, Li JKY, Ko GTC, Critchley JAJH, Cockram CS, et al. The islet amyloid polypeptide (amylin) gene S20G mutation in Chinese subjects: Evidence for associations with type 2 diabetes and cholesterol levels. Journal of Endocrinology. 2001;54:541-6.
- Ng MCY, Li JKY, So WY, Critchley JAJH, Cockram CS, Bell GI, et al. Nature or nurture - an insightful illustration from a Chinese family with hepatocyte nuclear factor 1-alpha diabetes (MODY3). Diabetologia. 2000;43:816-8.
- Lam VK, Ma RC, Lee HM, Hu C, Park KS, Furuta H, et al. Genetic associations of type 2 diabetes with islet amyloid polypeptide processing and degrading pathways in asian populations. PLoS One. 2013;8(6):e62378.
- Ng MCY, Park KS, Oh B, Tam CH, Cho YM, Shin HD, et al. Implication of genetic variants near TCF7L2, SLC30A8, HHEX, CDKAL1, CDKN2A/B, IGF2BP2, and FTO in type 2 diabetes and obesity in 6,719 Asians. Diabetes. 2008 Aug;57(8):2226-33.
- Ma RC, Hu C, Tam CH, Zhang R, Kwan P, Leung TF, et al. Genome-wide association study in a Chinese population identifies a susceptibility locus for type 2 diabetes at 7q32 near PAX4. Diabetologia. 2013 Jun;56(6):1291-305.
- Ma RC, Lee HM, Lam VK, Tam CH, Ho JS, Zhao HL, et al. Familial young-onset diabetes, pre-diabetes and cardiovascular disease are associated with genetic variants of DACH1 in Chinese. PLoS One. 2014;9(1):e84770.
- So WY, Wang Y, Ng MC, Yang X, Ma RC, Lam V, et al. Aldose reductase genotypes and cardio-renal complications - a 8-year prospective analysis of 1074 type 2 diabetic patients. Diabetes care. 2008 Aug 20;31(11):2148-53.
- Wang Y, Ng MCY, So WY, Tong PCY, Ma RCW, Chow CC, et al. Prognostic effect of insertion/deletion polymorphism of the ACE gene on renal and cardiovascular clinical outcomes in Chinese patients with type 2 diabetes. Diabetes care. 2004;28:348-54.
- Ma RC, Tam CH, Wang Y, Luk AO, Hu C, Yang X, et al. Genetic variants of the protein kinase C-beta 1 gene and development of end-stage renal disease in patients with type 2 diabetes. JAMA. 2010 Aug 25;304(8):881-9.
- Mooyaart AL, Valk EJ, van Es LA, Bruijn JA, de Heer E, Freedman BI, et al. Genetic associations in diabetic nephropathy: a meta-analysis. Diabetologia. 2011 Mar;54(3):544-53.
- Ng MC, Wang Y, So WY, Cheng S, Visvikis S, Zee RY, et al. Ethnic differences in the linkage disequilibrium and distribution of single-nucleotide polymorphisms in 35 candidate genes for cardiovascular diseases. Genomics. 2004 Apr;83(4):559-65.
- Ramachandran A, Ma RC, Snehalatha C. Diabetes in Asia. Lancet. 2010 Jan 30;375(9712):408-18.
- Ko G, So W, Tong P, Ma R, Kong A, Ozaki R, et al. A simple risk score to identify Southern Chinese at high risk for diabetes. Diabetic medicine. 2011 Jun;27(6):644-9.
- Rothman KJ, Greenland S. Causation and causal inference in epidemiology. American journal of public health. 2005;95 Suppl 1:S144-50.
- Ko GT, So WY, Tong PC, Le Coguiec F, Kerr D, Lyubomirsky G, et al. From design to implementation--the Joint Asia Diabetes Evaluation (JADE) program: a descriptive report of an electronic web-based diabetes management program. BMC medical informatics and decision making. 2010;10:26.
- Chan JCN, So WY, Ko G, Tong PCT, Yang XL, Ma RCW, et al. The Joint Asia Diabetes Evaluation (JADE) Program: A Web-based Program To Translate Evidence To Clinical Practice in Type 2 Diabetes. Diabetic Medicine. 2009;26:693-9.
- Chan JC, Ozaki R, Luk A, Kong AP, Ma RC, Chow FC, et al. Delivery of integrated diabetes care using logistics and information technology - The Joint Asia Diabetes Evaluation (JADE) program. Diabetes Res Clin Pract. 2014 Dec;106 Suppl 2:S295-304.