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This study aims to enhance personalized and preventive care for non-communicable diseases (NCDs) in Kazakhstan by examining epigenetic factors, predicting biological age and reproductive function using machine learning, and developing health improvement recommendations.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| The study includes 1 cohort divided into 4 age subgroups. | The study follows a multistage cluster sampling design with age and gender stratification. A total of 1 cohorts have been identified, further divided into 4 age subgroups:
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Genetic: DNA analysis | Other | Investigation of telomere length (TL) and DNA methylation level analysis |
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| Measure | Description | Time Frame |
|---|---|---|
| Accuracy of Machine Learning Model for Predicting Biological Age | Evaluation of the model's performance (based on telomere length and DNA methylation) using Mean Absolute Error (MAE), Mean Squared Error (MSE), and R². | Within 10 months from start of data collection |
| Accuracy of Reproductive Function Prediction Model | Development and validation of machine learning model to predict reproductive function using biomarkers. Model performance evaluated via MAE, MSE, and R². | Within 10 months from start of data collection |
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Inclusion Criteria:
Exclusion Criteria:
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The study population consists of 6,720 adult volunteers aged 18 to 69 years, residing across 17 regions of Kazakhstan. Participants are stratified by age and gender to ensure balanced representation within the following age groups:
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Ildar Fakhradiyev, Ph.D | Contact | +7 (727) 338 7090 | fakhradiyev.i@kaznmu.kz |
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Asfendiyarov Kazakh National Medical University | Recruiting | Almaty | Kazakhstan | 050000 | Kazakhstan |
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Venous blood samples and peripheral blood mononuclear cells (PBMCs) will be collected. DNA will be extracted and analyzed for telomere length (via quantitative real-time polymerase chain reaction (qPCR)) and methylation patterns (using methylation-sensitive high-resolution melting (MS-HRM)). Only high-quality DNA (assessed by spectrophotometry and fluorometry) will be retained. Samples will be stored at -80°C.
| ID | Term |
|---|---|
| D002318 | Cardiovascular Diseases |
| D003924 | Diabetes Mellitus, Type 2 |
| D009765 | Obesity |
| D051436 | Renal Insufficiency, Chronic |
| ID | Term |
|---|---|
| D003920 | Diabetes Mellitus |
| D044882 | Glucose Metabolism Disorders |
| D008659 | Metabolic Diseases |
| D009750 | Nutritional and Metabolic Diseases |
| D004700 | Endocrine System Diseases |
| D050177 | Overweight |
| D044343 | Overnutrition |
| D009748 | Nutrition Disorders |
| D001835 | Body Weight |
| D012816 | Signs and Symptoms |
| D013568 | Pathological Conditions, Signs and Symptoms |
| D051437 | Renal Insufficiency |
| D007674 | Kidney Diseases |
| D014570 | Urologic Diseases |
| D052776 | Female Urogenital Diseases |
| D005261 | Female Urogenital Diseases and Pregnancy Complications |
| D000091642 | Urogenital Diseases |
| D052801 | Male Urogenital Diseases |
| D002908 | Chronic Disease |
| D020969 | Disease Attributes |
| D010335 | Pathologic Processes |
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