Armed with weapons provided by cutting-edge science and technology, modern psychiatry is off to a blazing start.
Mental disorders have been poorly understood for centuries.
Modern psychiatry, however, is now trying to identify biological indicators of mental illnesses by exploring the genetic, cellular and neural-network perturbations that underlie many of these conditions.
Genome-wide association studies have uncovered multiple gene variants underpinning many psychiatric disorders. It is increasingly becoming clear that some of the mental illnesses are no different from complex physical diseases that involve many genes.
Heritability marks many psychiatric conditions. In bipolar disorder, for example, if one of a pair of monozygotic twins has the disorder, the chance that the other too will have it is around 60%. In dizygotic twins, the figure is 10%. When one identical twin has autism, the likelihood that the other too has it is about 90%. With schizophrenia, the figure is about 50%, even for twins raised apart.
GWAS has pointed to many common gene candidates with small, but significant influences on mental disorders.
A single mutation on chromosome 7 increases the chances of developing autism and schizophrenia.
A recent collaborative research project carried out by The University of Queensland and Vrije Universiteit in Amsterdam, which analysed more than 400,000 individuals, uncovered the genes that contribute to the development of ADHD, autism spectrum disorder, bipolar disorder, major depression and schizophrenia.
Investigating specific sets of genes involved in the development of multiple disorders, these researchers found that genes that are highly expressed in the brain affect different disorders and that some genes were related to all the illnesses studied.
Evidently, there is a common set of genes that increase the risk for all five disorders due to the biological pathways shared by the genes in the brain.
This knowledge will help in the development of more effective personalised medicines with new pharmaceutical drugs that target these shared pathways, the researchers said.
Similarly, studies have also identified rare genetic variants having a strong association with conditions such as autism.
Critics, however, posit that the lack of strong ‘acting’ variants suggests that the approach had missed important heritable factors, or that the polygenic patterns were artefacts.
Moreover, genetic strategies are of limited use in conditions such as mood and anxiety disorders, which have significant environmental triggers.
Psychiatric disorders are complex and often present with diverse clinical features. The identification of genetic variants and influences is often a starting point. Genetic data must be complemented by analyses of epigenetic effects, gene-expression profiles, the proteome, metabolic profiles and neuroendocrinology and imaging data to yield definitive insights, studies indicate.
Many technologies need further refinement to determine the molecular differences between healthy and diseased individuals.
Transcriptomics: Methods such as DNA microarrays lack reproducibility and adequate signal intensity. More sensitive and accurate technologies will help researchers to better identify disease modified regions of the genome.
Proteomics: A comprehensive analysis of protein biomarkers of psychiatric disorders has been a challenge. New developments in analysis and mass-spectrometry techniques are likely to resolve many of them.
Metabolomics: The metabolome of an
individual is heterogeneous in its molecular composition. The metabolic profile of a patient reflects the interplay of ongoing gene–environment interactions. Such profiles can signal pathophysiological changes or reactions to a drug.
Brain imaging: Morphological changes in specific brain areas can be used as predictors of responses to therapy, shows evidence from nuclear magnetic resonance (NMR)-based neuroimaging. Electroencephalography (EEG) readings taken during sleep have already yielded information on biomarker candidates.
Neuroendocrinology: Measurements of certain hormones, especially stress hormones, have important clinical prognostic value in patients.