Precision Medicine in Chinese Patients With Young Onset Diabetes

Precision Medicine to Redefine Insulin Secretion and Monogenic Diabetes (PRISM) in Chinese Patients With Young Onset Diabetes

Patients with young onset diabetes (YOD) are one of the most challenging groups of patients due to their long disease duration, complex causes, delayed interventions, psychosocial stress, poor adherence and frequent default. The investigator's previous studies indicate that provision of biogenetic information improved satisfaction, reduced ambiguity and improved self-efficacy in patients with T2D. Provision of personalized information using the web-based Joint Asia Diabetes Evaluation (JADE) Technology with risk stratification and decision support empowers better self care and medical intervention with improved control of risk factors. To further improve the precision of diagnosis for individualizing care, the use of CP, GADA, genetic risk scores (GRS) or rare genetic variants of maturity onset of diabetes (MODY) can help doctors select the most appropriate therapy in a timely manner. While patients with low CP, GADA and high GRS will benefit from early insulin therapy, some MODY variants are associated with good response to insulin-releasing oral drugs (e.g. sulphonylurea) which may spare the use of insulin with reduced patient distress and over-insulinization. By contrast, patients with high CP often due to obesity-associated insulin resistance should undergo intensive lifestyle modification and use of drugs with weight-reducing or neutral effects to avoid weight gain due to excessive dose of insulin.

Study Overview

• Status: Active, not recruiting
• Conditions: Type 2 Diabetes
• Intervention / Treatment: Other: Biogenetic explanation and endocrinologist intensive managment; Other: Usual care management

Detailed Description

Patients with young onset diabetes (YOD) are one of the most challenging groups of patients due to their long disease duration, complex causes, delayed interventions, psychosocial stress, poor adherence and frequent default. The investigator's previous studies indicate that provision of biogenetic information improved satisfaction, reduced ambiguity and improved self-efficacy in patients with T2D. Provision of personalized information using the web-based Joint Asia Diabetes Evaluation (JADE) Technology with risk stratification and decision support empowers better self care and medical intervention with improved control of risk factors. To further improve the precision of diagnosis for individualizing care, the use of CP, GADA, genetic risk scores (GRS) or rare genetic variants of maturity onset of diabetes (MODY) can help doctors select the most appropriate therapy in a timely manner. While patients with low CP, GADA and high GRS will benefit from early insulin therapy, some MODY variants are associated with good response to insulin-releasing oral drugs (e.g. sulphonylurea) which may spare the use of insulin with reduced patient distress and over-insulinization. By contrast, patients with high CP often due to obesity-associated insulin resistance should undergo intensive lifestyle modification and use of drugs with weight-reducing or neutral effects to avoid weight gain due to excessive dose of insulin.

PART 1:

Objective: To characterize Chinese patients diabetes classified by fasting CP and GADA positivity and their prognostic significance.

Methods: Fasting CP levels and GADA in stored biosamples of 4000 patients in the Hong Kong Diabetes Register (HKDR) followed up since 1995.

PART 2:

Objective: To uncover genetic variants/sequences associated with familial YOD. Methods: Whole genome sequencing (WGS) in stored DNA of 100-120 sibpairs of YOD after 13 years of follow-up for imputation with exome data of case-control cohort of YOD and genome wide association studies (GWAS) data of 200 YOD families and 6000 T2D patients.

PART 3:

Objectives: To examine the impacts of precision medicine augmented by information technology and biogenetic markers (JADEPRISM) on attainment of cardiometabolic targets at 1 year and clinical outcomes at 3 year (n=440), compared with JADE-augmented care (n=440) in YOD.

Deliverables A catalogue of biogenetic markers to guide precision medicine augmented by the JADE-Technology to optimize clinical outcomes in YOD.

• Study Type: Interventional
• Enrollment (Actual): 884
• Phase: Not Applicable

Contacts and Locations

Study Locations

• Hong Kong
  • Sha Tin, Hong Kong
    • The Chinese University of Hong Kong

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years to 50 years (Adult)
• Accepts Healthy Volunteers: No
• Genders Eligible for Study: All

Description

Inclusion Criteria:

Part 1: Prospective cohort of Chinese with type 2 diabetes

Between 1995 and December 2004, 10,129 patients were assessed using structured protocol to esetablish the HKDR and of them, we have measured GADA and CP in 1400 patients with YOD. In this study, we shall measure CP and GADA in 4000 subjects from the HKDR with available GWAS data irrespective of their age of diagnosis. These samples were linked to our various databases by a unique identification code which will enable us to track the clinical outcomes including development of complications.

Part 2: Family-based cohort of first-degree relatives of diabetic probands

We shall utilize the resource of the HKDFS and control subjects to discover novel genetic variants of YOD. Subjects will be selected based on their status with or without diabetes. In 2012-2013, we ascertained the glycemic status of 365 siblings in the HKDFS and 452 participants of the community-based LKS cohort (aged 18-55 years) without diabetes at baseline (1998-2002).

In this cohort, 167 participants (53.7%) with a family history of YOD, 68 participants (30.1%) with a family history of late onset diabetes and 40 (14.4%) participants without family history of diabetes developed diabetes. Amongst the 313 siblings with family history of YOD, 167 had diabetes at baseline or developed diabetes during follow up and 146 did not develop diabetes after 13 years giving 100-120 sibpairs for linkage analysis. These sequence data will be imputed with 500 YOD patients and 500 control subjects with exome data as well as 6000 patients in the HKDR with GWAS data for analysis for validation purpose.

Part 3: RCT (PRISM)

• Non-type 1 diabetes (T1D)
• Chinese ethnicity
• Age between 18-50 years inclusive
• Age at diabetes diagnosis 40 years
• Able to understand study requirements and voluntarily agree to participate by providing written informed consent

Exclusion Criteria:

Part 1/2:

Subjects in the HKDR, HKFDS and LKS cohorts without or insuffiicent amount of biosamples for assays or sequencing.

Part 3:

• T1D, defined by presentation with diabetic ketoacidosis or insulin requirement within 6 months of diagnosis.
• Reduced life expectancy due to terminal illness or otherwise deemed not appropriate per discretion of the investigator

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Health Services Research
• Allocation: Randomized
• Interventional Model: Parallel Assignment
• Masking: None (Open Label)

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Other: JADE-PRISM group; Only applicable in part 3 which is a randomized controlled trial. Part 1 and part 2 are the prospective cohort studies.	Other: Biogenetic explanation and endocrinologist intensive managment; JADE report and JADE APP; Biogenetic explanation; First-year intensive management by endocrinologists; Follow up by their usual care doctors for continue treatment regimen maintenance.; Yearly DM nurses follow up for blood taking and questionnaires
Other: JADE group; Only applicable in part 3 which is a randomized controlled trial. Part 1 and part 2 are the prospective cohort studies.	Other: Usual care management; JADE report and JADE APP; Attend their usual care clinic for ongoing treatment; Yearly DM nurses follow up for blood taking and questionnaires

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Prevalence of C-Peptide (CP) and Glutamic Acid Decarboxylase Antibody (GADA) in Chinese adult patients with T2D (Part 1 of study)	Between 1995 to 2004, all patients in the HKDR had structured assessment with storage of blood samples (collected at registration) for future research purpose. We shall measure CP and GADA in 4000-5000 patients.	through study completion, an average of 4 years
The correlation of C-Peptide (CP) and Glutamic Acid Decarboxylase Antibody (GADA) on clinical outcomes (Part 1 of study)	Between 1995 to 2004, all patients in the HKDR had structured assessment with storage of blood samples (collected at registration) for future research purpose.	through study completion, an average of 4 years
Incidence of young-onset type 2 diabetes and its genetic susceptibility (Part 2 of study)	Between 1998 to 2013, subjects from the HKFDS and the community-based LKS cohort had storage of blood samples at registration.	through study completion, an average of 4 years
Incidence of any diabetes-related micro/macrovascular endpoints (Part 3 of study)	Incident including cardiovascular disease (coronary heart disease, congestive heart failure, stroke, peripheral artery disease), chronic kidney disease, all-cause death and/or incident/progression/remission of albuminuria, estimated glomerular filtration rate, retinopathy, visual acuity and sensory neuropathy	through study completion, an average of 4 year

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
The levels of CP and GADA and the number of genetic variants for disease prognositication and classification to guide precision medicine in YOD (Part 1 and 2 of study)		through study completion, an average of 4 years
The number of genetic variants for disease prognositication and classification to guide precision medicine in YOD (Part 1 and 2 of study)		through study completion, an average of 4 years
The number of novel targets and pathways for discovery of drug targets with companian diagnostics (Part 1 and 2 of study)		through study completion, an average of 4 years
The number of patients attaining ≥3 cardiometabolic risk factors (Part 3 of study)	Defined as A1c<6,2%, blood pressure<120/80 mmHg, LDL-C<1.8 mmol/L , triglyceride<1.2 mmol/L, waist circumference<80 cm in women <85 cm in men which has been shown to reduce cardiovascular-renal endpoint in the JDOIT- 3 Study compared to conventional targets (A1c<7%, BP<130/80, LDL-C<1.8 mmol/L, triglyceride <1.7 mmol/L)	through study completion, an average of 4 years
Incidence of severe hypoglycaemia (Part 3 of study)	Defined as hospitalization due to hypoglycaemia	through study completion, an average of 4 year
Rate of changes in glycaemic control (Part 3 of study)	changes in HbA1c	through study completion, an average of 4 year
On-treatment changes in blood pressure (Part 3 of study)	measure both systolic and diastolic blood pressure in mmHg	through study completion, an average of 4 year
On-treatment changes in lipid profiles (Part 3 of study)	measure the changes in Total cholesterol, Triglyceride, High-density lipo-protein cholesterol, Low-density lipo-protein cholesterol	through study completion, an average of 4 year
On-treatment changes in Body Mass Index (Part 3 of study)	Measure by BW in kg	through study completion, an average of 4 year
On-treatment changes in CP (Part 3 of study)	Measure by changes in C-peptide	through study completion, an average of 4 year
Rate of changes in use of medications (Part 3 of study)		through study completion, an average of 4 year
Changes in patient's Quality of life (Part 3 of study)	Measure by questionnaire: EQ-5D For Quality of life (Total 5 questions with total score 1-15, highest score indicates the worst outcome)	through study completion, an average of 4 year
Changes in patient's reported outcomes : Depression (Part 3 of study)	Measure by questionnaire: PHQ-9 For Depression (Total 9 questions with total score 0-27, highest score indicates the worst outcome)	through study completion, an average of 4 year
Changes in patient's compliance (Part 3 of study)	Measure by questionnaire: CQ-4 For Compliance (Total 4 questions with total score 0-4, highest score indicates the worst outcome)	through study completion, an average of 4 year
Changes in patient's diabetes empowerment (Part 3 of study)	Measure by Diabetes Empowerment Scale (DES-20 for efficacy) (Total 20 questions with total score 0-80, highest score indicates better outcome)	through study completion, an average of 4 year
Changes in patient's diabetes self care activities (Part 3 of study)	Measure by questionnaire: Summary of diabetes self care activities (SDSCA-15 For self care) (Total 15 questions with total score 0-105, highest score indicates better outcome)	through study completion, an average of 4 year
Changes in patient's perceived personal control (Part 3 of study)	Measure by Perceived personal control (PPC) questionnaire (Total 9 questions with total score 0-18, highest score indicates better outcome)	through study completion, an average of 4 year
Changes in patient's genetic counseling satisfaction (Part 3 of study)	Measure by Genetic counseling satisfaction scale (GCSS) (Total 6 questions with total score 1-30, highest score indicates better outcome)	through study completion, an average of 4 year
Changes in patient's diabetes related distress (Part 3 of study)	Measures by questionnaire: Diabetes Distress Scale (DDS; total score from 17-102), comprising 3 subscales namely emotional, physician, regimen / social support. A lower score indicates better outcome	through study completion, an average of 4 year
Changes in patient's Depression Anxiety Stress (Part 3 of study)	Measure by Depression Anxiety Stress Scale (DASS-21) (Total 21 questions with total score 0-63, lowest score indicates better outcome)	through study completion, an average of 4 year

Collaborators and Investigators

• Sponsor: Chinese University of Hong Kong
• Investigators: Principal Investigator: Juliana Chan, MD, Chinese University of Hong Kong

Study record dates

Study Major Dates

• Study Start (Actual): January 14, 2020
• Primary Completion (Anticipated): December 31, 2024
• Study Completion (Anticipated): December 31, 2024

Study Registration Dates

• First Submitted: July 22, 2019
• First Submitted That Met QC Criteria: August 6, 2019
• First Posted (Actual): August 7, 2019

Study Record Updates

• Last Update Posted (Actual): July 20, 2022
• Last Update Submitted That Met QC Criteria: July 19, 2022
• Last Verified: July 1, 2022

More Information

Terms related to this study

• Keywords: Young-onset type 2 diabetes
• Additional Relevant MeSH Terms: Glucose Metabolism Disorders; Metabolic Diseases; Endocrine System Diseases; Diabetes Mellitus; Diabetes Mellitus, Type 2
• Other Study ID Numbers: CRE-2019.080

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No