Biological Aging, Healthy Aging, Lifestyle Factors
Conditions
Keywords
Aging, Biological Clocks, DNA methylation, Geroscience, Lifestyle
Brief summary
The Ageing BIOmarker Study in Singaporeans (ABIOS) aims to understand the biological aging processes and how they affect health among people in Singapore. As people grow older, their risk of developing chronic diseases increases. This study aims to better understand the biological changes that come with age, particularly in three major ethnic groups: Chinese, Malay, and Indian adults over 21 years old. By examining a range of health indicators such as DNA methylation, inflammation, metabolism, cardiovascular health, physical function, and physical activity (i.e., molecular, physiological, and digital biomarkers of ageing), the study seeks to identify how ethnicity, lifestyle, and socioeconomic factors influence ageing. This unique study focuses on an all-Asian population, aiming to enhance our understanding of healthy aging across different ethnic groups.
Detailed description
Biological ageing is the primary driver of age-associated chronic diseases in older adults. Asian populations have been underrepresented in studies developing biological age predictors and understanding age-related diseases. Thus, the Ageing BIOmarker Study in Singaporeans (ABIOS) aims to characterise the biomarkers of ageing in Singaporeans, exploring associations between molecular, physiological, and digital biomarkers of ageing. This is a single-centre, cross-sectional study that recruits healthy community-dwelling adults (≥ 21 years) from three different ethnic groups (Chinese, Malay, and Indian). Molecular biomarkers of ageing include a multi-omics approach, such as DNA methylation and metabolic and inflammatory parameters in blood, saliva, and stool. Physiological biomarkers of ageing include bone density, body composition, skin autofluorescence, arterial stiffness, physical performance (e.g., muscle strength and flexibility), cognition, and nutritional status. Digital biomarkers of ageing include three-dimensional facial morphology and objective physical activity. Additional factors such as habitual physical activity, dietary patterns, and medical history are also examined. The associations between the molecular, physiological, and digital phenotypes will be explored. By examining diverse age-related biomarkers, clinical indicators, and lifestyle factors, ABIOS will offer unique insights into the ageing process within these ethnic groups to develop health policies and interventions for promoting healthy ageing in an all-Asian population.
Interventions
None listed
Sponsors
National University of Singapore
Study design
Observational model
COHORT
Time perspective
CROSS_SECTIONAL
Eligibility
Sex/Gender
ALL
Age
21 Years to No maximum
Healthy volunteers
Yes
Inclusion criteria
* ≥21 years of age * Chinese, Malay, or Indian and has lived in Singapore for at least 5 consecutive years * Apparently healthy and non-smokers * Having only 1 condition (if ≥45 and \<65 years) or any condition (if ≥65 years), and all conditions were medication-controlled (if any): * Hypertension * Hyperlipidemia * Hyperglycemia * Osteopenia/osteoporosis * Osteoarthritis * Type 2 diabetes
Exclusion criteria
* Body mass index (BMI) ≥30 kg/m\^2 * Pre-existing or history of major cardiovascular disease (e.g., coronary artery disease, heart failure, stroke, peripheral vascular disease) * Any metal implants (excluding dental implants) in the body * Pre-existing or history of cancer or chronic obstructive pulmonary disease (COPD) * Pregnant women or planning pregnancy in the next 6-12 months
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| blood DNA methylation | Baseline | DNA methylation ageing clock, years |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Carotid-femoral Pulse Wave Velocity | Baseline | Arterial stiffness measured by pulse wave velocity, m/s |
| Handgrip strength | Baseline | Handgrip strength measured by dynamometer, kg |
| 8-repetition maximal strength | Baseline | Lower body strength measured by maximum weight for 8 leg extension repetitions, kg |
| Skin advanced glycation endproducts | Baseline | Skin advanced glycation endproducts measured by autofluorescence |
| Objective physical activity | Baseline | Objective physical activity measured by an activity tracking monitor |
| Facial age | Baseline | Facial ageing clock based on 3D face morphometry, years |
| Complete red blood cell (RBC) count | Baseline | Clinical blood parameters, RBC x 10\^12/L |
| Total white blood cell (WBC) count | Baseline | Clinical blood parameters, WBC x 10\^9/L |
| Total cholesterol | Baseline | Lipid profile panel, mmol/L |
| HDL cholesterol | Baseline | Lipid profile panel, mmol/L |
| LDL cholesterol | Baseline | Lipid profile panel, mmol/L |
| Triglycerides | Baseline | Lipid profile panel, mmol/L |
| Fasting blood glucose | Baseline | Clinical blood parameters, mmol/L |
| Total protein | Baseline | Liver profile panel, mmol/L |
| Total bilirubin | Baseline | Liver profile panel, umol/L |
| Alkaline phosphatase (ALP) | Baseline | Clinical blood parameters, U/L |
| Insulin | Baseline | Clinical blood parameters, Roche immunoassay, mU/L |
| HbA1c | Baseline | Clinical blood parameters, % |
Countries
Singapore
Contacts
PRINCIPAL_INVESTIGATORAndrea Maier, MD, PhD
National University of Singapore
Outcome results
None listed