The Vietnam Osteoporosis Study (VOS)

Goals and Objectives

The Vietnam Osteoporosis Study (VOS) (1) has been primarily aimed at investigating the extent and determinants of osteoporosis and osteoporotic fractures in the Vietnamese population. It also examines the relationship between osteoporosis and other non-communicable diseases such as osteoarthritis, sarcopenia, obesity, diabetes, metabolic syndrome, and cardiovascular disease. The overall goal is to identify genetic and environmental factors contributing to osteoporosis and associated chronic conditions. Additionally, VOS seeks to build capacity for high-quality population-based research and bioinformatics among Vietnamese scientists.

Study Design

VOS is a family-based cohort study involving 4500 participants from 817 families in Ho Chi Minh City and rural areas. Individuals aged 18 years and older (average age 51) were followed for 10 years to document fracture incidence and chronic disease development.

At baseline, extensive data collection was conducted, including:

• Anthropometric measurements (height, weight, BMI, waist-to-hip ratio);
• Two questionnaires covering demographics, medical history, medication use, physical activity, diet, and lifestyle factors;
• Skeletal assessments (digital X-ray, DXA, pQCT, TBS analysis);
• Muscle strength assessments (handgrip, back, and foot strength, performance analysis, and fitness tests);
• Carotid intima-media thickness measurement via ultrasound;
• Blood sample collection for glucose, HbA1c, lipid analysis, and genetic studies;
• DNA extraction for genomic and exposome analyses.

Plans include conducting genome-wide association studies (GWAS) and metabolomic analyses on all participants. The study aims to create a publicly available genetic reference for the Vietnamese population.

Key Findings

Osteoporosis Prevalence and Risk Factors

• The study developed a peak bone density reference for Vietnamese men and women, addressing overdiagnosis concerns (2).
• Estimated osteoporosis prevalence: 27% in women and 10% in men aged 50+ (3).
• Among individuals with osteopenia, 18% of women and 12% of men are at high risk for hip fractures (3).
• Approximately 12% of individuals have vertebral fractures, with an annual fracture incidence of 1% (4).
• Fracture risk is associated with male gender and low femoral neck bone mineral density (4).
• Bone loss begins before menopause and accelerates within five years post-menopause, highlighting the need for screening at age 45 (5).
• Greater fat mass correlates with higher bone mineral density, though this relationship is not mediated by leptin (6).
• Peak bone mass is primarily determined by lean mass, reinforcing the importance of physical activity in young adulthood (7).
• Bone fragility in aging is mainly due to trabecular bone loss and reduced cortical mass, with sex differences in trabecular density forming early and cortical differences emerging from age-related bone loss (8).

Osteoporosis and Chronic Diseases

• Diabetes: The prevalence of diabetes tripled from 3.8% (2004) to 11% (2010), with 40% of adults classified as prediabetic (9). FPG testing can miss a substantial proportion of diabetes and prediabetes (10). Diabetes is associated with lower cortical bone density and higher trabecular density, resulting in a lower bone strength and may be increase fracture risk (11). Patients with diabetes also have a lower trabecular bone score that was more pronounced in women than in men (12) and appear even in women prediabetes (13).
• Cardiovascular Disease: A weak but statistically significant association between carotid intima-media thickness and bone mineral density was found in men, but not in women, suggesting minimal osteoporosis impact on atherosclerosis (14).
• Sarcopenia: The prevalence of sarcopenia in individuals aged 50+ was 14%, with risk factors including advanced age, underweight status, and low physical activity, suggesting that this disease is preventable in the general population (15). Ethnic-specific muscle strength thresholds were developed for improved diagnosis (16).

Genetic Findings

• Thirteen independent genetic association signals were identified, including variants linked to osteoarthritis and hip fracture risk (17).
• Genetic factors account for approximately 45% of trabecular bone score variation. The co-variation between TBS and bone density is partially determined by genetic factors (18).

Predictive Models and Reference Ranges

• Normative reference values in body composition parameters were developed for the Vietnamese population (19).
• Ethnic-specific reference values for body composition, handgrip strength, and muscle strength with percentile charts were established (16).
• A validated osteoporosis risk prediction model was developed for use in settings without DXA (20).
• A shape-based algorithm (SBA) for vertebral fracture identification was created to aid in systematic screening fractures (21).
• An AI-based system utilizing deep convolutional neural networks was developed to predict bone mineral density from X-ray images.
• The study found that QUS is not a reliable alternative to DXA for osteoporosis screening (22).
• The annual incidence of falls in individuals aged 50+ was 15%, with jumping mechanography identified as a useful fall risk assessment tool (23).

Future Directions

VOS continues to expand its scope by integrating precision medicine approaches for musculoskeletal and metabolic disorders. Ongoing collaborations with domestic and international research centers involve GWAS, whole-genome sequencing, metabolomics, and transcriptomics. These efforts aim to develop new tools for early risk identification, intervention, and promoting healthy aging. An innovative aspect of VOS is the creation of a "diseasome" and exposome framework to enhance the understanding of disease interrelations and environmental influences.

To further advance precision medicine, VOS aims to:

• Develop a comprehensive genetic risk score integrating multi-omics data to predict osteoporosis and fracture risk such as other musculoskeletal and metabolic disorders.
• Use artificial intelligence and machine learning to refine predictive models for personalized treatment strategies.
• Identify gene-environment interactions that contribute to musculoskeletal and metabolic disorders, facilitating targeted prevention programs.
• Continue to conduct longitudinal studies to explore the impact of aging on bone health and associated comorbidities.
• Implement real-world applications of precision medicine in Vietnamese healthcare settings, ensuring accessibility and feasibility in low-resource environments.

By establishing a robust foundation for precision medicine in Vietnam, VOS aims to provide actionable insights for osteoporosis prevention, early detection, and management, ultimately improving public health outcomes. The integration of advanced genomic technologies and machine learning approaches will position VOS at the forefront of musculoskeletal and metabolic disorder research, contributing to global knowledge and healthcare advancements.

Saigonmec promotes open research and international collaboration in precision medicine by encouraging data sharing and collaborative research. We believe open access to our well-curated datasets can accelerate research and enable breakthroughs. If you have research ideas that could benefit from our datasets, please contact us at contact@saigonmec.org

Article date: Feb 14, 2025. Author: Dr. Lan T. Ho Pham