Imaging and Genetic Approaches to Inform Biomarkers for Anxiety Disorders, Obsessive-Compulsive Disorders, and PSTD

Candidate biomarkers in psychiatric disorders: state of the field

The field of psychiatry is hampered by a lack of robust, reliable and valid biomarkers that can aid in objectively diagnosing patients and providing individualized treatment recommendations. Here we review and critically evaluate the evidence for the most promising biomarkers in the psychiatric neuroscience literature for autism spectrum disorder, schizophrenia, anxiety disorders and post-traumatic stress disorder, major depression and bipolar disorder, and substance use disorders. Candidate biomarkers reviewed include various neuroimaging, genetic, molecular and peripheral assays, for the purposes of determining susceptibility or presence of illness, and predicting treatment response or safety. This review highlights a critical gap in the biomarker validation process. An enormous societal investment over the past 50 years has identified numerous candidate biomarkers. However, to date, the overwhelming majority of these measures have not been proven sufficiently reliable, valid and useful to be adopted clinically. It is time to consider whether strategic investments might break this impasse, focusing on a limited number of promising candidates to advance through a process of definitive testing for a specific indication. Some promising candidates for definitive testing include the N170 signal, an event-related brain potential measured using electroencephalography, for subgroup identification within autism spectrum disorder; striatal resting-state functional magnetic resonance imaging (fMRI) measures, such as the striatal connectivity index (SCI) and the functional striatal abnormalities (FSA) index, for prediction of treatment response in schizophrenia; error-related negativity (ERN), an electrophysiological index, for prediction of first onset of generalized anxiety disorder, and resting-state and structural brain connectomic measures for prediction of treatment response in social anxiety disorder. Alternate forms of classification may be useful for conceptualizing and testing potential biomarkers. Collaborative efforts allowing the inclusion of biosystems beyond genetics and neuroimaging are needed, and online remote acquisition of selected measures in a naturalistic setting using mobile health tools may significantly advance the field. Setting specific benchmarks for well-defined target application, along with development of appropriate funding and partnership mechanisms, would also be crucial. Finally, it should never be forgotten that, for a biomarker to be actionable, it will need to be clinically predictive at the individual level and viable in clinical settings.

Shared genetic basis between reproductive behaviors and anxiety-related disorders

Reproductive behaviors are associated with risks for psychiatric disorders. Reproductive phenotypes are moderately heritable and have genetic overlaps with risks for psychiatric disorders. However, the genetic and causal relationships between anxiety-related disorders or specific anxiety disorders and reproductive phenotypes remain unknown. We utilized large-scale genome-wide association study (GWAS) results (n = 9537-542,901) for five reproductive phenotypes [age at menarche, age at first sexual intercourse (AFS), age at first birth (AFB), number of children ever born (NEB), and age at menopause] and five anxiety-related disorders [panic disorder, anxiety disorders from the ANGST and the UK biobank (UKBB), posttraumatic stress disorder (PTSD) and obsessive-compulsive disorder (OCD)]. To assess genetic correlations and causal associations, linkage disequilibrium score regression and Mendelian randomization analyses, respectively, were performed. We found that AFS and AFB were negatively correlated with anxiety disorders ANGST (AFS: r_g ± SE = -0.28 ± 0.08, p = 6.00 × 10^-4; AFB: -0.45 ± 0.11, p = 3.26 × 10^-5), anxiety disorders UKBB (AFS: -0.18 ± 0.03, p = 9.64 × 10^-9; AFB; -0.25 ± 0.03, p = 2.90 × 10^-13) and PTSD (AFS: -0.42 ± 0.12, p = 4.00 × 10^-4; AFB: -0.44 ± 0.12, p = 2.00 × 10^-4) and positively correlated with OCD (AFS: 0.25 ± 0.05, p = 2.46 × 10^-6; AFB: 0.25 ± 0.05, p = 3.92 × 10^-7). Conversely, NEB was negatively correlated with OCD (-0.28 ± 0.08, p = 6.00 × 10^-4). We revealed bidirectional effects between earlier AFS and AFB and anxiety disorders (odds ratios: OR_{earlier AFS→Anxiety} = 1.64, p = 2.27 × 10^-8; OR_{earlier AFB→Anxiety} = 1.15, p = 2.28 × 10^-3; OR_{Anxiety→earlier AFS} = 1.02, p = 6.62 × 10^-8; OR_{Anxiety→earlier AFB} = 1.08, p = 1.60 × 10^-4). In contrast, we observed unidirectional effects of later AFS and AFB on OCD (OR_{later AFS→OCD} = 2.18, p = 2.16 × 10^-6; OR_{later AFB→OCD} = 1.22, p = 0.016). We suggest that those who have earlier sexual debut and childbirth are prone to risk for anxiety disorders and vice versa, while those who have later sexual debut and childbirth are genetically prone to risk for OCD. Our findings further support revising the diagnostic criteria (DSM-5) such that OCD is independent from anxiety disorders.

Genetic contributions to anxiety disorders: where we are and where we are heading

Anxiety disorders are among the most common psychiatric disorders worldwide. They often onset early in life, with symptoms and consequences that can persist for decades. This makes anxiety disorders some of the most debilitating and costly disorders of our time. Although much is known about the synaptic and circuit mechanisms of fear and anxiety, research on the underlying genetics has lagged behind that of other psychiatric disorders. However, alongside the formation of the Psychiatric Genomic Consortium Anxiety workgroup, progress is rapidly advancing, offering opportunities for future research.Here we review current knowledge about the genetics of anxiety across the lifespan from genetically informative designs (i.e. twin studies and molecular genetics). We include studies of specific anxiety disorders (e.g. panic disorder, generalised anxiety disorder) as well as those using dimensional measures of trait anxiety. We particularly address findings from large-scale genome-wide association studies and show how such discoveries may provide opportunities for translation into improved or new therapeutics for affected individuals. Finally, we describe how discoveries in anxiety genetics open the door to numerous new research possibilities, such as the investigation of specific gene-environment interactions and the disentangling of causal associations with related traits and disorders.We discuss how the field of anxiety genetics is expected to move forward. In addition to the obvious need for larger sample sizes in genome-wide studies, we highlight the need for studies among young people, focusing on specific underlying dimensional traits or components of anxiety.

Shared genetic etiology between anxiety disorders and psychiatric and related intermediate phenotypes

BACKGROUND

Psychiatric disorders and related intermediate phenotypes are highly heritable and have a complex, overlapping polygenic architecture. A large-scale genome-wide association study (GWAS) of anxiety disorders identified genetic variants that are significant on a genome-wide. The current study investigated the genetic etiological overlaps between anxiety disorders and frequently cooccurring psychiatric disorders and intermediate phenotypes.

METHODS

Using case-control and factor score models, we investigated the genetic correlations of anxiety disorders with eight psychiatric disorders and intermediate phenotypes [the volumes of seven subcortical brain regions, childhood cognition, general cognitive ability and personality traits (subjective well-being, loneliness, neuroticism and extraversion)] from large-scale GWASs (n = 7556-298 420) by linkage disequilibrium score regression.

RESULTS

Among psychiatric disorders, the risk of anxiety disorders was positively genetically correlated with the risks of major depressive disorder (MDD) (rg ± standard error = 0.83 ± 0.16, p = 1.97 × 10-7), schizophrenia (SCZ) (0.28 ± 0.09, p = 1.10 × 10-3) and attention-deficit/hyperactivity disorder (ADHD) (0.34 ± 0.13, p = 8.40 × 10-3). Among intermediate phenotypes, significant genetic correlations existed between the risk of anxiety disorders and neuroticism (0.81 ± 0.17, p = 1.30 × 10-6), subjective well-being (-0.73 ± 0.18, p = 4.89 × 10-5), general cognitive ability (-0.23 ± 0.08, p = 4.70 × 10-3) and putamen volume (-0.50 ± 0.18, p = 5.00 × 10-3). No other significant genetic correlations between anxiety disorders and psychiatric or intermediate phenotypes were observed (p > 0.05). The case-control model yielded stronger genetic effect sizes than the factor score model.

CONCLUSIONS

Our findings suggest that common genetic variants underlying the risk of anxiety disorders contribute to elevated risks of MDD, SCZ, ADHD and neuroticism and reduced quality of life, putamen volume and cognitive performance. We suggest that the comorbidity of anxiety disorders is partly explained by common genetic variants.

Novel pharmacological targets in drug development for the treatment of anxiety and anxiety-related disorders

Current medication for anxiety disorders is suboptimal in terms of efficiency and tolerability, highlighting the need for improved drug treatments. In this review an overview of drugs being studied in different phases of clinical trials for their potential in the treatment of fear-, anxiety- and trauma-related disorders is presented. One strategy followed in drug development is refining and improving compounds interacting with existing anxiolytic drug targets, such as serotonergic and prototypical GABAergic benzodiazepines. A more innovative approach involves the search for compounds with novel mechanisms of anxiolytic action using the growing knowledge base concerning the relevant neurocircuitries and neurobiological mechanisms underlying pathological fear and anxiety. The target systems evaluated in clinical trials include glutamate, endocannabinoid and neuropeptide systems, as well as ion channels and targets derived from phytochemicals. Examples of promising novel candidates currently in clinical development for generalised anxiety disorder, social anxiety disorder, panic disorder, obsessive compulsive disorder or post-traumatic stress disorder include ketamine, riluzole, xenon with one common pharmacological action of modulation of glutamatergic neurotransmission, as well as the neurosteroid aloradine. Finally, compounds such as D-cycloserine, MDMA, L-DOPA and cannabinoids have shown efficacy in enhancing fear-extinction learning in humans. They are thus investigated in clinical trials as an augmentative strategy for speeding up and enhancing the long-term effectiveness of exposure-based psychotherapy, which could render chronic anxiolytic drug treatment dispensable for many patients. These efforts are indicative of a rekindled interest and renewed optimism in the anxiety drug discovery field, after decades of relative stagnation.

Biomarkers in Neuropsychiatry: A Prospect for the Twenty-First Century?

The search for biomarkers to aid in the diagnosis and prognosis of psychiatric conditions and predict response to treatment is a focus of twenty-first century medicine. The current lack of biomarkers in routine use is attributable in part to the existing way mental health conditions are diagnosed, being based upon descriptions of symptoms rather than causal biological evidence. New ways of conceptualizing mental health disorders together with the enormous advances in genetic, epidemiological, and neuroscience research are informing the brain circuits and physiological mechanisms underpinning behavioural constructs that cut across current diagnostic DSM-5 categories. Combining these advances with 'Big Data', analytical approaches offer new opportunities for biomarker development. Here we provide an introductory perspective to this volume, highlighting methodological strategies for biomarker identification; ranging from stem cells, immune mechanisms, genomics, imaging, network science to cognition. Thereafter we emphasize key points made by contributors on affective disorders, psychosis, schizophrenia, and autism spectrum disorder. An underlying theme is how preclinical and clinical research are informing biomarker development and the importance of forward and reverse translation approaches. In considering the exploitation of biomarkers we note that there is a timely opportunity to improve clinical trial design informed by patient 'biological' and 'psychological' phenotype. This has the potential to reinvigorate drug development and clinical trials in psychiatry. In conclusion, we are poised to move from the descriptive and discovery phase to one where biomarker panels can be evaluated in real-life cohorts. This will necessitate resources for large-scale collaborative efforts worldwide. Ultimately this will lead to new interventions and personalized medicines and transform our ability to prevent illness onset and treat complex psychiatric disorders more effectively.