Biomedical chimeras

The UK Department of Health and Social Care has funded King’s College, London, to develop a ‘bioresource’ of 40,000 people who have (or have been in the past) diagnosed with an anxiety or depressive disorder (1). These diagnoses apparently apply to one quarter to one third of the entire population. One purpose of the project is genetic profiling, presumably to help discover neuro pathways in the brain that could be modified by medication.

The sample of volunteers they wish to recruit, however large, is bound to be arbitrary and heterogeneous. There must be numerous people who could be or could have been given an anxiety or depression diagnosis who, for local and idiosyncratic reasons, were not, and a large number who should not have been so diagnosed due to the unreliability of diagnostic criteria. The sample is also biased by consisting only of volunteers. One previous attempt to find genetic characteristics associated with ‘major depression’ was unsuccessful (2). The authors stated that only a large sample comprising more than 50,000 subjects may be sufficiently powered to detect genes for depressive sumptoms. One reason for this negative result may be the fact that a questionnaire assessing ‘major depression’ is a hodgepodge of unrelated phenotypic behaviours. Another is that fact that ‘major depression’ (if it has any meaning at all) is almost certainly polygenic. If each gene contributes only a very small amount to ‘risk’, then it is only when a large number of randomly varying characteristics converge in a single individual that a genetic determination becomes evident.

The enthusiasm for investing in biomedical research into mental health seems unbounded. This project seems to be a fishing exercise, and seems entirely unjustifed when the target sample is one third of the entire ‘normal population’ who happen to have been subjected to an arbitrary diagnostic assessment.

1. Eley, T. (2018) Major new study to ‘serve the mental health community’. Interview with Professor Eley. The Psychologist, October, 2018, pp. 18-19.

2. Hek, K., Demirkan, A., Lahti, J. et al., (2013) A genome-wide association study of depressive symptoms. Biological Psychiatry. 73(7), 667-668.

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