Abstract

This is an exploratory paper of the ethical implications for genomic research and mental illness with specific reference to Singapore. Singapore has a unique context due to its social and political systems, and although it is a relatively small country, its population is religiously and culturally diverse. The issues that we identify here, therefore, will offer new perspectives and will also shed light on the existing literature on psychiatric genomics in society. We contextualise issues such as risk and stigma in the identification and diagnosis of psychosis in the way they relate to Singaporean society, and use a current study as a case example. Genomic research has the potential to change significantly he practice of clinical medicine if, as expected, fast and inexpensive sequencing becomes a reality. It will likely also change how society thinks and acts in respect to multi-factorial diseases, conditions, traits, and syndromes that have a genetic component. Genomic research already raises a number of ethical concerns relating to the privacy of individuals, including the disclosure of research results and incidental findings, surreptitious tests, third party access to data, and the re-emergence of genetic determinism. These issues are potentially exacerbated when genomics - the study of whole genomes to understand complex illness and behavioural traits - is applied to psychiatric research, because of the stigma that is often attached to mental illness. In this paper, we discuss some of the issues that have arisen in the context of a study in Singapore that is currently investigating the genomics and biomarkers of psychosis. We argue that although a genomic study rarely creates data that is directly useful to the participant, it can have incidental benefits to the individual who is identified during the study as being at high risk of developing psychosis and its related states. Understanding these potential benefits requires us to examine the implications that this type of research may have on public understandings of genomic data and risk.