Multidimensional assessment of ocular phenotypes across distinct subtypes of type 2 diabetes mellitus in a Chinese cohort
| ISRCTN | ISRCTN15557580 |
|---|---|
| DOI | https://doi.org/10.1186/ISRCTN15557580 |
- Submission date
- 19/02/2025
- Registration date
- 21/02/2025
- Last edited
- 21/02/2025
- Recruitment status
- No longer recruiting
- Overall study status
- Ongoing
- Condition category
- Nutritional, Metabolic, Endocrine
Plain English summary of protocol
Background and study aims
The incidence of diabetes mellitus is rapidly increasing, and this condition often results in significant metabolic disease and severe complications. At the same time, diabetes mellitus is a highly heterogeneous disease in which the eye serves not only as an end-organ target but also as a window to systemic damage. Recent advancements in oculomics have provided novel tools for systemic disease stratification. This research aims to assess the 5- and 10-year risks of diabetic retinal and systemic complications (e.g., cardiovascular events, nephropathy) using oculomics and to identify distinct subtypes of diabetes in Chinese patients, which is helpful in understanding how these subtypes differ in long-term risks of eye damage and other health complications. The results could help doctors personalize diabetes care by using eye scans to catch complications earlier and tailor treatments to individual risks.
Who can participate?
Adults with type 2 diabetes mellitus were enrolled based on primary care-based diabetes management plans in township health centers, Shaoguan City (the part of a nationwide community screening program under China's Basic Public Health Service frame work). For external validation, a parallel rural cohort from Yangxi County was included.
What does the study involve?
Eligible participants were those who completed 3 consecutive annual screenings and undergo standardized diabetic retinal examinations (e.g., administered structured face-to-face questionnaires, slit-lamp biomicroscopy and digital fundus photography). All the exams follow the normal clinical operation.
What are the possible benefits and risks of participating?
Participants benefit from receiving ocular and general tests for 3 consecutive annual screenings. No additional risks are anticipated as all the exams follow the normal clinical operation.
Where is the study run from?
Shaoguan City, Guangdong Province, China
When is the study starting and how long is it expected to run for?
January 2020 to March 2030
Who is funding the study?
National Natural Science Foundation of China
Who is the main contact?
Dr Wei Wang, wangwei@gzzoc.com
Contact information
Public, Scientific, Principal Investigator
No. 7 Jinsui Rd
No. 54 Xianlie South Rd
Guangzhou
510060
China
 ORCID ID |
0000-0002-5273-3332 |
|---|---|
| Phone | +86 15915719579 |
| wangwei@gzzoc.com |
Study information
| Study design | Observational cohort study |
|---|---|
| Primary study design | Observational |
| Secondary study design | Cohort study |
| Study setting(s) | Community |
| Study type | Other |
| Participant information sheet | No participant information sheet available |
| Scientific title | Oculomics-Driven Identification of Diabetes Subgroups in Chinese Cohorts (ODISC) |
| Study acronym | ODISC |
| Study objectives | Diabetes mellitus is a highly heterogeneous disease in which the eye serves not only as an end-organ target but also as a window to systemic damage. Recent advancements in oculomics have provided novel tools for systemic disease stratification. Distinct diabetic subtypes exhibit different ocular manifestations, and we hypothesize that oculomics can capture these subtype-specific differences. |
| Ethics approval(s) |
Approved 08/03/2021, Ethics Committee of Zhongshan Ophthalmic Center (No. 7 Jinsui Rd, Guangzhou, 510060, China; +86 20-66610729; zoccrc@gzzoc.com), ref: 2020KYPJ160 |
| Health condition(s) or problem(s) studied | Individuals with diabetes |
| Intervention | The ODISC study is a observational cohort study that includes type 2 diabetes mellitus (T2DM) patients from a part of a nationwide community screening program under China’s Basic Public Health Service framework enrolled in primary care-based diabetes management plans in Shaoguan City. Eligible participants were those who undergo standardized diabetic retinal examinations and completed three consecutive annual screenings. For external validation, a parallel rural cohort from Yangxi County was included. The examinations include: face-to-face questionnaire surveys (e.g., sociodemographic data such as age, sex, income, education; lifestyle factors such as smoking, alcohol use, physical activity; medical history and medication adherence) , health data such as blood sugar levels, kidney function, and heart health; and ophthalmic evaluation (slit-lamp biomicroscopy and digital fundus photography). The study leverages artificial intelligence (AI)-driven computational methods to extract quantitative features from digital fundus photography, forming the basis of oculomics profiling. A deep learning framework, utilizing a pre-trained convolutional neural network (CNN) architecture (e.g., ResNet-50), was employed to automatically segment retinal vasculature, detect microaneurysms, and quantify optic disc morphology, generating 512-dimensional feature vectors for each participant. These oculomics parameters were then integrated into a multimodal dimensionality reduction pipeline. |
| Intervention type | Other |
| Primary outcome measure | The 5- and 10-year risks of diabetic retinal and systemic complications (e.g., cardiovascular events, nephropathy) are predicted using oculomics mainly extracted by digital fundus photography and other clinical data (at baseline, 1-year visit, 2 year-visit, 3-year visit). |
| Secondary outcome measures | The distinct diabetic subtypes were identified based on retinal phenotypic patterns. DDRTree (Discriminative Dimensionality Reduction via Learning a Tree) will be applied to project high-dimensional oculomics data into a low-dimensional latent space while preserving pseudotemporal trajectory patterns. Unsupervised clustering algorithms—including k-means (hard clustering) and Gaussian mixture models (soft clustering) are also applied. |
| Overall study start date | 01/01/2020 |
| Completion date | 08/03/2030 |
Eligibility
| Participant type(s) | Resident |
|---|---|
| Age group | Adult |
| Lower age limit | 18 Years |
| Sex | Both |
| Target number of participants | 1500 |
| Key inclusion criteria | 1. Individuals aged over 18 years. 2. T2DM diagnosis was confirmed by primary care physicians using internationally accepted thresholds: fasting plasma glucose (FPG) ≥7.0 mmol/L, 2-hour postprandial glucose (2h-PG) ≥11.1 mmol/L during a 75-g oral glucose tolerance test (OGTT), or hemoglobin A1c (HbA1c) ≥6.5%. |
| Key exclusion criteria | 1. Patients with type 1 diabetes, gestational diabetes, severe comorbidities (e.g., advanced cardiovascular disease like stage III-IV cardiovascular disease, chronic kidney disease with eGFR <30 mL/min/1.73 m², or active malignancy, etc. 2. Inability to complete ophthalmic assessments. 3. Unable to give their own informed consent. |
| Date of first enrolment | 09/03/2021 |
| Date of final enrolment | 08/09/2021 |
Locations
Countries of recruitment
- China
Study participating centre
512000
China
Sponsor information
Research organisation
No. 7 Jinsui Rd
No. 54 Xianlie South Rd
Guangzhou
510060
China
| Phone | +86 15915719579 |
|---|---|
| zocky@gzzoc.com | |
| Website | https://www.gzzoc.com/ |
Funders
Funder type
Government
Government organisation / National government
- Alternative name(s)
- Chinese National Science Foundation, Natural Science Foundation of China, National Science Foundation of China, NNSF of China, NSF of China, 国家自然科学基金委员会, National Nature Science Foundation of China, Guójiā Zìrán Kēxué Jījīn Wěiyuánhuì, NSFC, NNSF, NNSFC
- Location
- China
Results and Publications
| Intention to publish date | 30/12/2030 |
|---|---|
| Individual participant data (IPD) Intention to share | No |
| IPD sharing plan summary | Not expected to be made available |
| Publication and dissemination plan | The results will be published in peer-reviewed journals. |
| IPD sharing plan | Not be shared according to legislation. |
Editorial Notes
21/02/2025: Trial's existence confirmed by Ethics Committee of Zhongshan Ophthalmic Center.
