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World Health Organization has asserted that mental illness is the greatest overriding burden of disease in the majority of developed countries, and that the socioeconomic burden of mental disease will exceed that of cancer and cardiovascular disorders in the future. The life-time prevalence rate for mental disorders in Korea is reported at 27.6 %, which means three out of 10 adults experience mental disorders more than once throughout their lifetime. Korea's suicide rate has remained the highest among Organization for Economic Cooperation and Development (OECD) nations for 10 consecutive years, with 29.1 people out of every 100,000 having committed suicide. Nevertheless, a comprehensive study on the mental health services and the Research and Development (R&D) status in Korea is hard to find. Against this backdrop, this paper examines the mental health services and the R&D status in Korea, and examines their shortcomings and future direction. The paper discusses the mental health service system, budget and human resources, followed by the mental health R&D system and budget. And, by a comparison with other OECD countries, the areas for improvement are discussed and based on that, a future direction is suggested. This paper proposes three measures to realize mid and long-term mental health promotion services and to realize improvements in mental health R&D at the national level: first, establish a national mental health system; second, forecast demand for mental health; and third, secure and develop mental health professionals. [ABSTRACT FROM AUTHOR]

Background: Because common complex diseases are affected by multiple genes and environmental factors, it is essential to investigate gene-gene and/or gene-environment interactions to understand genetic architecture of complex diseases. After the great success of large scale genome-wide association (GWA) studies using the high density single nucleotide polymorphism (SNP) chips, the study of gene-gene interaction becomes a next challenge. Multifactor dimensionality reduction (MDR) analysis has been widely used for the gene-gene interaction analysis. In practice, however, it is not easy to perform high order gene-gene interaction analyses via MDR in genome-wide level because it requires exploring a huge search space and suffers from a computational burden due to high dimensionality. Results: We propose dimensional reduction analysis, Gene-MDR analysis for the fast and efficient high order genegene interaction analysis. The proposed Gene-MDR method is composed of two-step applications of MDR: withinand between-gene MDR analyses. First, within-gene MDR analysis summarizes each gene effect via MDR analysis by combining multiple SNPs from the same gene. Second, between-gene MDR analysis then performs interaction analysis using the summarized gene effects from within-gene MDR analysis. We apply the Gene-MDR method to bipolar disorder (BD) GWA data from Wellcome Trust Case Control Consortium (WTCCC). The results demonstrate that Gene-MDR is capable of detecting high order gene-gene interactions associated with BD. Conclusion: By reducing the dimension of genome-wide data from SNP level to gene level, Gene-MDR efficiently identifies high order gene-gene interactions. Therefore, Gene-MDR can provide the key to understand complex disease etiology. [ABSTRACT FROM AUTHOR]