Modern psychiatry

Genome wide association studies have uncovered the importance of multiple gene variants in psychiatric disorders. Genotypes and biomarkers in combination with clinical features will help to address heterogeneity in patient phenotypes. New biomarkers will help to identify the onset of pathology long before clinical symptoms emerge, thus allowing early intervention and prediction of outcome.


Hundreds of millions of people around the world are affected by mental disorders. These conditions have been poorly understood for centuries; however, modern psychiatry is now starting to explore the genetic, cellular and neural-
network perturbations that underpin mental illness, with the aim of identifying biological indicators — or biomarkers — that can be used for diagnosis, prognosis and therapeutic intervention.


Genetics has been one of the main driving forces in psychiatric research, as it has been clear for decades that there is heritability in many — if not all — psychiatric conditions. Two research strategies dominate the field of psychiatric genetics today. The first involves the genome-wide association study (GWAS), in which researchers scan and compare entire genomes of people with and without a particular disorder (Fig. 1); this approach has pointed to many common gene candidates with small but significant influences on disorders such as schizophrenia1. The second involves a search for rare genetic variants that have a strong association with a condition; in autism research, such studies have pinpointed genes that affect how neurons connect to one another2.

Genetic strategies come with some caveats. For instance, they are of limited use in conditions, such as mood and anxiety disorders, that have large environmental influences. Furthermore, the identification of genetic variants is often merely a starting point, and 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.

Consequently, the fields of transcriptomics, proteomics, metabolomics and functional imaging are developing rapidly. Despite the limitations, genetic studies have revealed important information on putative disease genes and, in some cases, have led to the development of important animal models of psychiatric diseases3,4.


Psychiatric disorders are complex and give rise to patient groups with diverse clinical features. For example, two patients with similar symptoms can have different underlying pathologies, while identical twins can have different symptoms. To unravel the causes of this heterogeneity, it is important to develop better clinical definitions based on detailed clinical data sets and quantifiable biological information on a given disorder, rather than a diagnosis based on comparison with healthy controls.

New biomarkers of psychiatric disorders will prove important, not only for diagnosis and determining therapy, but also for the identification of disease onset, progression, remission and relapse5. Many of the technologies needed to determine molecular differences between healthy and diseased individuals are complex and thus problematic to use in large patient cohorts. Advances in instrumentation, in addition to strong bioinformatics support, are needed in several disciplines.

The first is genetics. Faster and more accurate gene-sequencing technologies will continue to drive advances in the field. These technologies will eventually allow more affordable, in-depth genome scans.

The second is transcriptomics. It has been challenging to determine differences in gene-expression patterns between diseased and healthy states, because DNA microarrays and other methods lack reproducibility and adequate signal intensity. With more sensitive and accurate technologies, researchers will be better able to identify disease modified regions of the genome.

The third is proteomics. Proteins are key players in physiology and pathophysiology; however, realizing comprehensive analyses of protein biomarkers of psychiatric disorders has been a daunting task. New developments in detection, analysis and mass-spectrometry techniques are likely to resolve many of the current challenges. The fourth is metabolomics. The metabolic profile of a patient reflects the interplay of ongoing gene–environment interactions6. Such profiles can serve as key indicators of possible pathophysiological perturbations or reactions to a drug. The metabolome of an individual is complex and heterogeneous with regard to its molecular composition.

The fifth is brain imaging. Evidence from nuclear magnetic resonance (NMR)-based neuroimaging indicates that morphological changes in specific brain areas can be used as predictors of responses to therapy. Electroencephalography (EEG) readings taken during sleep have already yielded information on biomarker candidates. To realize their benefits, imaging technologies must be made available to more patients, which will require major investments in instrumentation and training.

The sixth is neuroendocrinology. For example, measurements of stress hormones in patients with depression, have important clinical prognostic value. However, progress will depend on the application of new proteomic and metabolomic approaches.

Another major goal in the search for biomarkers is to discover signalling pathways that can be targeted by drugs. For this, scientists need direct access to small-molecule libraries and high-throughput analysis resources so that they can screen their targets under ideal conditions.


Genetic studies have pointed to many gene candidates that are involved in psychiatric disorders; however, researchers also need to determine the neurobiological consequences of a given genetic variation. This requires knowledge of the mechanisms by which environmental and other non-genetic factors influence the expression of genes, and how they vary to adapt to changing demands. Of particular interest is how early-childhood experiences shape disease susceptibility or resilience. Animal experiments that mimic adversities in different periods of life will be indispensable. Researchers have shown, for example, that separating mouse pups from their mothers can lead to behavioural traits reminiscent of depression7.

Mouse models provide unique insights into behavioural deficits because they have good face validity — meaning that their symptoms mimic those in humans. Development of genetic mouse models for psychiatric diseases will become increasingly important as researchers aim to tease apart the genetic and environmental influences on psychiatric diseases. Such models will need to include complex genetic variants, and be tested in conjunction with environmental factors such as stress, infection and physical trauma. Many behavioural traits that characterize psychiatric disorders cannot be replicated in mice, so it will be necessary to use other animal species as models.

Psychiatric genomics has the potential to lead to new diagnostic strategies that will help the detection of mental illnesses before the clinical symptoms manifest, and the determination of their subsequent trajectory. Moreover, this field will help the development of new evidence-based (and, ideally, personalized) treatments for psychiatric disorders. Given the prevalence of psychiatric disorders, this will have important consequences for society.

Key experiments interrogating how environmental factors may result in epigenetic signals were conducted at the Max Planck Institute of Psychiatry where mice were postnatally exposed to trauma. This resulted in persistent behavioral depression-like changes caused by altered DNA-methylation and upregulation of vasopressin gene activity a known causal factor of depression (Murgatroyd, C. et al. Nature Neurosci. 12, 1559–1566, 2009).

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