Genetic Testing and Counseling to Reduce Diabetic Complications

Diabetic Complication Clinical Trial

Official title: A Randomized Clinical Trial to Compare a Strategy Utilizing Genetic Testing and Personalized Risk Counseling With Standard Care on Patient Empowerment, Risk Factors Control and the Risk of Diabetic Complications

Status Completed

Clinical Trial Summary

The risk of diabetic kidney complications includes non-modifiable risk factors such as genetic predictors, as well as modifiable risk factors such as hyperglycaemia, hypertension, hyperlipidaemia and proteinuria. Genetic testing for personalized medicine is increasing in popularity, though evidence that genetic testing can empower patients to modify behaviour and reduce clinical risk remains lacking. In this project, the investigators aim to utilize a personalized risk counseling with genetic testing to evaluate its impact on risk factor control in diabetic patients. The investigators hypothesize that knowledge of genetic +/- clinical risk will empower patients and lead to improvement in the number of treatment targets achieved. The investigators will recruit 400 patients with diabetes. All subjects will undergo a comprehensive assessment of the risk of diabetic complications based on clinical risk factors. Half of the patients will be randomized to receive additional genetic testing of a panel of genetic markers proven to predict renal complications in our population: ACE I/D, aldose reductase (CA)n and PRKCB1 gene polymorphisms. The results of personalized risk assessment will be communicated by a health counsellor in the intervention arm. The impact of testing and patient knowledge of the result of genetic testing on achievement of treatment targets (A1c, BP, LDL-cholesterol, TG, use of ACEI/ARB) and patient behavior will be evaluated after 12 months. The other arm will receive results of the genetic testing at the completion of the study period. The study will help towards developing a strategy to empower patients through structured and personalized risk assessment will provide a novel approach to identify high-risk subjects for early intensive management, and may lead to reduction in long-term complications.

Clinical Trial Description

Asia is in the midst of an epidemic of diabetes. Approximately 1 in 10 people in China has diabetes [1]. Asian patients with diabetes are characterized by early age of onset and increased risk of kidney complications. Young age of onset and long disease duration will place Chinese diabetic patients at high risk for complications. In the Hong Kong Diabetes Registry, which includes more than 7000 patients with type 2 diabetes, we have reported a high risk of diabetic complications, with 30% having died or sustained a major clinical event within 10years after diagnosis, including 10% developing cardiovascular complications, and 10% developing end-stage renal disease [2] [3]. The medical costs for the diabetic patient with complication is 2.2-3.8 fold that of patients without complications, and patients with cardiorenal complications are the most costly to manage [4]. Using our registry, we have identified clinical risk predictors for developing renal complications as glycaemic control, elevated blood pressure, hyperlipidaemia, and albuminuria [2] [3, 5], and have derived clinical risk prediction algorithms and incorporated them into a patient management portal, which can generate a standardized report for risk counseling based on clinical risk factors [6, 7]. Furthermore, in a multi-centre study utilizing a multidisciplinary team, we found that intensive management aiming to achieve targets of A1c, lipids, BP can significantly reduce the risk of developing kidney complication [8]. Therefore, the ability to identify subjects at risk of complications, and to target and motivate them to optimize modifiable risk factors for diabetic complications will be of clinical benefit and potentially cost-saving.

There has been much recent interest in the use of genetic testing for personalized medicine [9]. Diabetic kidney complications has high heritability of around 40% and several genetic factors have been found to be associated with diabetic renal complications. Using candidate-gene approach, our group has identified several genetic markers for diabetic kidney complications [10, 11] [12]. These include the angiotensin converting enzyme deletion/ insertion (ACE D/I) polymorphism and the aldose reductase (ALR2) 5'-(CA) n microsatellite polymorphism, each being associated with 2-3 fold increased risk of diabetic cardio-renal complications in Chinese [10, 13]. More recently, we have found that carriers of risk alleles at the protein kinase C-β1 (PRKCB1) locus can have up to 6-fold increased risk of developing end-stage renal disease during follow-up, after adjusting for the effect of clinical risk predictors [12].

The recent increase in consumer-initiated genetic testing has been driven by direct-to-consumer genetic testing, which assumes that personal genetic information can motivate positive behavioural change in patients [14]. Interestingly, a recent survey of patients without type 2 diabetes suggests that genetic testing may be able to motivate patients, with 71% of respondents reporting that they would be "much more motivated" to make behavioural changes if they were informed to be of high genetic risk for diabetes [15]. Although evidence that genetic testing can lead to behavioural changes is still lacking, several randomized clinical trials are currently underway to examine the impact of genetic testing on behaviour to reduce risk of diabetes. Given the disabling consequences of diabetic complications, and the ability to predict those at risk of developing complications, we plan to examine the role of personalized risk counseling incorporating genetic markers, and to examine its role in patient empowerment and risk factor control, which may help to reduce the risk of developing complications. ;

Related Conditions & MeSH terms

• Diabetes Complications
• Diabetic Complication

• NCT number: NCT02364323
• Study type: Interventional
• Source: Chinese University of Hong Kong
• Status: Completed
• Phase: N/A
• Start date: February 17, 2015
• Completion date: December 31, 2018