PCaLiStDB

PCaLiStDB catalogs interactions among lifestyle factors, environmental influences, genetic predispositions, and prostate cancer and supports Lifestyle-Wide Association Studies (PCa_LWAS) to discover associations and mechanistic links.

Key Features:

• Standardized data format: Data are organized in a standardized format to support systematic Lifestyle-Wide Association Studies (PCa_LWAS).
• Content scope: Contains 2,290 single-factor lifestyle entries and 856 joint-effect entries involving two or more factors.
• Categorization of evidence: Factors are classified as 394 protective, 556 risk, 45 no-influencing, 52 with contradictory evidence, and 1,977 lacking sufficient evidence.
• Multimodal data types: Integrates data on foods, nutrients, habits, social elements, environmental conditions, associated genes, physiological and biochemical indices, disease phenotypes, and drug information.
• Support for mechanistic analysis: Enables integration of diverse datasets for mechanistic studies relating lifestyle factors to prostate cancer development.

Scientific Applications:

• Lifestyle-Wide Association Studies (PCa_LWAS): Identify statistical associations between individual or joint lifestyle factors and prostate cancer onset or progression.
• Mechanistic investigations: Correlate lifestyle exposures with associated genes, physiological and biochemical indices, and disease phenotypes to explore potential mechanisms.
• Risk and prevention modeling: Provide evidence and structured data for development of predictive models and preventive strategies based on lifestyle factors.
• Evidence synthesis: Aggregate and categorize single-factor and joint-effect evidence to inform research priorities and hypothesis generation.

Methodology:

Data are integrated across lifestyle factors, genetic data, physiological/biochemical indices, disease phenotypes, and drug information and stored in a standardized format to support Lifestyle-Wide Association Studies (PCa_LWAS).