Psychology and Neuroscience of Affective Disorders PDF - King's College London

Module: Psychology and Neuroscience of Affective Disorders Week 1: Introduction to affective disorders Topic 3: Emerging focuses in affective disorders (Part 4 of 4) Lecture transcript Dr Rebecca Strawbridge Department: Centre for Affective Disorders Slide 4 The final part of this lecture focuses on...

Module: Psychology and Neuroscience of Affective Disorders Week 1: Introduction to affective disorders Topic 3: Emerging focuses in affective disorders (Part 4 of 4) Lecture transcript Dr Rebecca Strawbridge Department: Centre for Affective Disorders Slide 4 The final part of this lecture focuses on ways to improve treatment response other than just the development of new therapies to treat people with a disorder. Firstly, there are many recent calls for preventative interventions for affective disorders. In one sense, this makes a lot of sense because if you can prevent illness, there is essentially no disability burden. But the flip side to that is that firstly, preventative strategies have traditionally not been successful, and secondly, that it could be considered costly and even unethical to administer treatments to people who are not currently ill. For the latter reason, preventative interventions are often low intensity, with low risk of side effects and or low cost to deliver, and generally did not include pharmacological therapies. Some examples are IPSRT which we talked about in the last section or psychoeducation which was mentioned earlier, and these online anti-suicide interventions, which have also been mentioned previously. But these tend to be less focused on a general population and more focused on people considered at risk of illness. For example, those with a family history or with potential current signs of an affective disorder or with suicide ideation. © King’s College London 1 Slide 5 Preventative measures that are not specifically thought to be therapeutic themselves include detection of relapse or prelapse or prodrome i.e, a state that signifies a possible impending relapse. Detection of these can then act as signals for increased monitoring or active intervention. More broadly, interventions to prevent an initial illness onset can include again, usually for people at risk in one way or another, psychological interventions which are often family-focused and targeted at young people. This is an area we can expect to grow in upcoming years. Slide 6 An alternative to total prevention is intervening at the earliest possible point where illness is evident. This may seem like an obvious idea or it may be surprising that this is not already usual practice but as mentioned earlier, affective disorders are often poorly recognised, and there are long delays to accurate diagnosis and therefore long delays to initial treatment. Two reasons why early intervention is becoming a priority are, firstly, that we now know that delays to appropriate intervention are reliably associated with poorer long term illness outcomes, and secondly that the introduction of early intervention for psychosis services in the UK but also other areas globally have proved highly successful in terms of improving outcomes and reducing health care costs in the long term. Slide 7 Given the importance of intervening early, this is an area which is now just starting to grow. Two examples of early evidence in this area are noted here. The first, by Michael Berk, was a trial looking at which of two first-line medications for people with bipolar disorder is best for people after their first episode of mania, and they found lithium to be superior to quetiapine. The second is an ongoing trial, which is the first examining the effects of group psychotherapy early in the course of bipolar disorder, in this case early being based on age. However, the poor detection rates make it difficult to identify sufficient sample sizes of people who are early in the course of illness in order to conduct trials. Also, the need to assess long-term outcomes makes trials difficult and costly to conduct. So this is something that needs a lot of investment, especially because in the absence of evidence, there isn't considered a sufficient case to invest in early intervention services for affective disorders. Slide 8 Finally, a lot of research is focusing on personalising treatments for people with affective disorders. Given the number and variety of treatments that are recommended for these illnesses, it surprises many that treatment selection is still done using a trial and error approach. Many attempts have been made to identify factors before treatment that predict response versus nonresponse to various subsequent interventions. This has been looked at for a wide variety of biological markers. Some examples here include meta-analysis showing that people with biomarker levels that it's suggests an over activity of inflammatory responses respond less well when they're given standard antidepressant medications for depression compared to people with more normal levels of inflammation. And secondly, that people with higher cortisol secretion suggesting a dysregulated HPA axis respond less well to 2 © King’s College London psychological therapies. Of course, it might be that both cortisol and inflammation predict a generalised non-response to initial treatments for depression. And indeed, there is both evidence that inflammation predicts non-response to psychological therapy and that high cortisol is found in antidepressant-resistant patients. Slide 9 Others have for a long time looked at whether non-biological factors predict response to treatments. The Taylor et al. reference here refers to a systematic review of all studies looking at predicting response to augmentation therapies in people with at least early-stage treatment-resistant depression. A consistent effect was found where the severity of depressive symptoms before treatment and the number of previously unsuccessful treatments taken before treatment seemed to predict a worse outcome later to these TRD therapies. But the majority of predictors did find inconsistent results between studies, and this is the case also for the biological work. So new studies are increasingly examining multimodal predictors, that is a combination of biological and non-biological predictors. Slide 10 These models predicting response, need to be done across the different treatment strategies and populations of people with affective disorders. Any model that is found to successfully predict response has to then be replicated sufficiently in other studies i.e, retrospectively and this is where we have been stuck in the field so far. When a model or models do pass this hurdle, they then need to be replicated in prospective studies. One way of doing this is in naturalistic studies of treatment, where the predictive markers are set out a priori and then tested as people are treated. But this is also needed in controlled trials to ensure that other factors do not account for any benefits to a clinical outcome that are observed from employing a precision medicine model. Slide 11 In a fully personalised medicine approach, an individual person's characteristics would be assessed and then analysed, and an intervention strategy would be indicated as likely to be successful for that particular person. Stratified medicine may be a more feasible alternative. One example of this might be categorising people dichotomously as either having high or low levels of, for example, cortisol or inflammation and targeting those with aberrant biology to medication antidepressants and those without biological abnormalities to a psychological intervention. A stratified randomised trial would need to test this by randomising participants to usual strategies compared with treatment selection being guided using a predictive model to direct patients to a treatment estimated to be more likely to improve outcomes and then to compare clinical response between the two conditions. Slide 12 Before I move on to the final thoughts from the lecture, I want to make one final point. You might have noticed that both in this lecture and in other content covered in this course that there is a prominent focus on depression and less on bipolar disorder. There are a few reasons for this, one is that depression is a common feature across all affective disorders, 3 © King’s College London with one exception which is unipolar mania. This is an extremely rare condition and is largely not well understood. So depression is the most prevalent state in these affective disorders and has resultantly received by far the most attention in the literature. Even in the context of bipolar disorders, depression also tends to carry a higher burden and have poorer response to treatment compared to manic states. Secondly, there are practical challenges with researching people who are experiencing mania. In acute manic states, participants will often be unable to complete measures and tasks. For example, prominent symptoms of mania include distractibility, highly goal-directed activity, but according to the patient's own goals rather than others. Flight of ideas, racing thoughts, pressured speech, and engaging in risky behaviours. This also means challenges in participants turning up to research visits and even issues with having the capacity to provide fully informed consent to research. The most notable example of this is in brain scans, where a participant's head needs to remain still for an extended period of time. But this difficulty is common to all research on current mania. Slide 13 In summary then, there is a lot happening in scientific endeavours related to affective disorders, and there is a lot that needs to happen. Large-scale research drives of many participants and many data types over long periods of time can be facilitated via technological and social progress. Powerful computational models alongside clinical expertise in addition, can help us disentangle affective disorders into homogeneous subgroups, which should allow a more comprehensive, multifaceted understanding of pathogenesis, mechanisms and treatment. These will themselves facilitate a move towards optimised treatment in the real world through new compounds, preventative, early, personalised, and evidence-based intervention. Slide 14 As a final note, thank you very much for listening to all of this lecture on emerging topics in affective disorders. I realised that a lot has been covered and therefore not at incredible depth. If you wish to ask any questions, please feel free to contact me on my email address which is here on the slide, [email protected]. Thank you once again, I hope it was of interest, and all the best with the rest of the module. 4 © King’s College London