Although precision psychiatry remains a future aspiration, clinical stratification is a reality, and progress is being made in biomarker identification and pharmacogenetics, Professor Vieta explained.
No individual patient with bipolar disorder is the “average” patient
No individual patient with bipolar disorder is the “average” patient, Professor Vieta said. Clinical trial results are very different to those in real-life because clinical trials show mean values rather than individual data. Real-life patients may be pregnant, old, have comorbidities and/or abuse alcohol or other recreational drugs. In other words, patients in clinical trials often do not reflect those in real life.
In addition, remission is commonly defined using scales that do not measure functional outcome. Reality is more complex. What matters to patients is whether they will respond to treatment so they can be as they were before. They do not want to just feel well. They also want to do well and contribute successfully to society: that is, they want a full functional recovery.
Patients don’t just want to feel well. They also want to do well
While precision psychiatry will enable psychiatrists to decide upon the best treatment for each individual patient based on a number of factors (including family history, genetics, etc), it remains an aspiration. However, through technological advancements, we see that personalised medicine is emerging and may have great clinical benefit. An example of this is using genetics to predict treatment response, Professor Vieta said. Indeed, pharmacogenetics can be used to identify fast and slow metabolisers and predict treatment response or possibly even adverse events, though in Professor Vieta’s practice these tests are restricted to selected patients because they are expensive and the information they provide needs replication.
Professor Vieta highlighted the importance of measuring and monitoring variables within the mental health environment to inform the provision of psychiatric care, and added that this need not be too onerous if short scales and e-mental health tools are used.
Early detection of bipolar disorder enables early intervention to prevent progression to late expressions of bipolar disorder, which are more difficult to treat.
Evolving understanding about the pathophysiology of bipolar disorder — from genetic vulnerability through neural connectivity and anatomic and functional changes in the brain, to emotional, behaviour and cognitive changes, and thence to patient function and efficiency within society — will enable earlier identification of bipolar disorder, explained Professor Vieta.
Symptoms are late manifestations of the underlying illness
At present, a diagnosis is based on symptoms and has been defined by consensus. However, symptoms are late manifestations of the underlying illness.
Neuroanatomical changes are also late manifestations of bipolar disorder and correlate with chronicity. These changes in the limbic system, cingulate, amygdala, brainstem, hypothalamus, ventromedial precentral cortex, striatum, nucleus accumbens, thalamus and cerebellum and coincide with the serotonergic, noradrenergic and dopaminergic networks.
The at-risk phase of bipolar disorder is difficult to identify
The at-risk phase of bipolar disorder is difficult to identify, Professor Vieta said. Biological indicators include experience of early adversity, low cognitive reserve, genetic predisposition and the use of recreational drugs. Most biomarkers, however, such as increased cytokines, are not specific and correlate with brain stress.
If the patients agree, he suggested using e-mental health tools such as smartphone apps and wearables to help capture behaviour such as social media interactions that can be used to reveal a change indicating a deterioration in the illness. Families are also increasingly involved in the treatment process and often help in alerting the psychiatric services to functional and behavioral changes.