Borwin Bandelow, David Baldwin, Marianna Abelli, Blanca Bolea-Alamanac, Michel Bourin, Samuel R Chamberlain, Eduardo Cinosi, Simon Davies, Katharina Domschke, Naomi Fineberg, Edna Grünblatt, Marek Jarema, Yong-Ku Kim, Eduard Maron, Vasileios Masdrakis, Olya Mikova, David Nutt, Stefano Pallanti, Stefano Pini, Andreas Ströhle, Florence Thibaut, Matilde M Vaghix, Eunsoo Won, Dirk Wedekind, Adam Wichniak, Jade Woolley, Peter Zwanzger, Peter Riederer
5 min
This paper serves as a consensus statement from the World Federation of Societies for Biological Psychiatry (WFSBP) and the European College of Neuropsychopharmacology (ECNP). It synthesizes current knowledge regarding potential biomarkers for anxiety disorders, obsessive-compulsive disorder (OCD), and post-traumatic stress disorder (PTSD). The review focuses on three primary domains: neurochemistry (including neurotransmitters, neuropeptides, and the HPA axis), neurophysiology (EEG and heart rate variability), and neurocognition.
The authors examine the role of monoaminergic systems, noting that serotonin, dopamine, and norepinephrine are heavily implicated in the pathophysiology of these disorders. For instance, serotonin dysregulation is linked to panic disorder (PDA) and social anxiety disorder (SAD), while the noradrenergic system shows hyperfunction in panic-related conditions. The paper also explores the GABAergic system, highlighting the role of neuroactive steroids and translocator protein (TSPO) as potential markers. Furthermore, the HPA axis is discussed as a central stress-response system; while findings are often inconsistent, there is evidence of altered cortisol regulation in PTSD and GAD, with hair cortisol analysis emerging as a promising technique for measuring long-term stress.
Neurophysiological markers, such as EEG patterns and heart rate variability (HRV), are highlighted as sensitive but non-specific indicators of autonomic and cortical arousal. The review notes that reduced HRV is a consistent finding across several anxiety disorders, reflecting autonomic nervous system dysfunction. Additionally, the paper addresses the growing evidence for a low-grade systemic inflammatory state in these disorders, characterized by altered cytokine levels (e.g., TNF, IL-6). The authors also discuss the autoimmune hypothesis for specific OCD subtypes, particularly those triggered by streptococcal infections (PANDAS/PANS).
While the authors emphasize that no current biomarker meets the criteria for a standalone diagnostic tool, they argue that the accumulation of high-quality research is essential for moving toward a more neurobiologically informed classification of psychiatric disorders. The findings underscore the importance of standardized protocols in future research to resolve current inconsistencies and improve clinical outcomes.
Objective: Biomarkers are defined as anatomical, biochemical or physiological traits that are specific to certain disorders or syndromes. The objective of this paper is to summarise the current knowledge of biomarkers for anxiety disorders, obsessive-compulsive disorder (OCD) and posttraumatic stress disorder (PTSD).Methods: Findings in biomarker research were reviewed by a task force of international experts in the field, consisting of members of the World Federation of Societies for Biological Psychiatry Task Force on Biological Markers and of the European College of Neuropsychopharmacology Anxiety Disorders Research Network.Results: The present article (Part II) summarises findings on potential biomarkers in neurochemistry (neurotransmitters such as serotonin, norepinephrine, dopamine or GABA, neuropeptides such as cholecystokinin, neurokinins, atrial natriuretic peptide, or oxytocin, the HPA axis, neurotrophic factors such as NGF and BDNF, immunology and CO2 hypersensitivity), neurophysiology (EEG, heart rate variability) and neurocognition. The accompanying paper (Part I) focuses on neuroimaging and genetics.Conclusions: Although at present, none of the putative biomarkers is sufficient and specific as a diagnostic tool, an abundance of high quality research has accumulated that should improve our understanding of the neurobiological causes of anxiety disorders, OCD and PTSD.
Alex: That's a meaningful reframe. It shifts the question from "what is the level?" to "what is the function of the regulatory circuit?"
Sam: Right, and that reframe has real implications for study design. The CO2 challenge paradigm is a good example—rather than sampling at rest, you perturb the system and watch how it responds. That approach gets you closer to the underlying dysregulation. The problem is that challenge paradigms are difficult to standardize across sites, they're time-consuming, and they don't translate easily into a busy clinic. So the field is in what the review essentially calls a map-making phase. We're identifying which circuits are involved and how they fail, but we're not yet at the point where a clinician can operationalize that in an afternoon.
Alex: Is the review pessimistic about the path forward, or does it point somewhere useful?
Sam: Not pessimistic—but clear-eyed. The task force is explicit that no single diagnostic biomarker exists for these disorders. Where they see traction is in multi-modal, dynamic monitoring: integrating neurophysiology, genetics, and cognitive performance rather than chasing a single molecule. The biomarker, if we get there, won't be a level. It'll be a pattern of system-wide activity across multiple measurement domains.
Alex: Which is a much harder thing to build a clinical test around, but probably the right problem to be solving.
Sam: Precisely. And it requires a precision-psychiatry framing rather than a categorical one. The implication for study design going forward is cohorts stratified by phenotype, challenge paradigms rather than resting baselines, and longitudinal sampling to capture system dynamics rather than snapshots. The review is essentially a call to restructure how the field collects evidence—not just which molecules it looks at.
Alex: So the field isn't stuck because the biology isn't there. It's stuck because the measurement framework hasn't caught up to the complexity of what's being measured. Thanks for walking us through this, Sam. And thanks to everyone listening to ResearchPod.