VIENNA — When combined with clinical parameters, a panel of serum biomarkers predicts the onset of depression in patients with social anxiety disorder (SAD) better than either set of measures alone, new research shows.
On the basis of findings of the study, Michael Gottschalk, of the Cambridge Center for Neuropsychiatric Research at the University of Cambridge, United Kingdom, said that there is "converging evidence for the potential of combining biomarkers and clinical readouts for the prediction of depressive episodes in social phobia."
The findings were presented here at the European Psychiatric Association (EPA) 23rd Congress.
Researchers tested serum samples from 143 patients enrolled in the Netherlands Study of Depression and Anxiety (NESDA) for 250 analytes to find ones common to people who went on to develop depression. Patients had experienced SAD within 6 months but had no depressive disorders at baseline. Multiplexed immunoassays were used to test for the analytes.
Among the demographic, psychiatric diagnostic, physical disease, or psychiatric or nonpsychiatric medication variables investigated, only results of the Inventory of Depressive Symptomatology (IDS) at baseline and at 2-year follow-up distinguished SAD nonconverters from SAD convertors (both P < .001) among SAD patients with or without comorbid anxiety disorders.
For patients without comorbid anxiety disorders, IDS results at baseline and at 2 years also distinguished nonconvertors from converters (P = .012 at baseline; P = .0085 at 2 years).
The researchers used stepwise logistic regression to determine an optimal set of serum biomarkers and clinical variables to predict depressive episodes during a 2-year follow-up period.
The serum biomarkers that emerged were receptor tyrosine kinase AXL (AXL), vascular cell adhesion molecule-1 (VCAM1), insulinlike growth factor binding protein 3, collagen IV, and vitronectin. The clinical variables of interest were the results on the Beck Anxiety Inventory (BAI), the BAI somatic (BAIsom) scale, and the BAI subjective scale, as well as the presence of chronic respiratory diseases and IDS results.
For patients with SAD who were without comorbid anxiety disorders, the combination of the clinical parameters of IDS and BAI had low predictive sensitivity (55%) and higher specificity (82%), and AXL alone had 100% sensitivity but only 56% specificity. However, when these clinical parameters were combined with AXL, sensitivity was 95% with specificity was 70%, which Gottschalk described as acceptable levels for a predictive test.
An analysis for SAD patients with or without comorbid anxiety disorders showed similar results using the clinical variables of IDS, BAIsom, depressive disorder lifetime history, and body mass index or the serum analytes AXL, VCAM1, vitronectin, and collagen IV. Neither the combination of clinical variables nor of serum markers had sufficient sensitivity and specificity to be a useful predictor.
But when the clinical variables and biomarkers were combined, sensitivity was 77% with specificity of 81% to predict the onset of a depressive disorder during the 2-year follow-up period.
Gottschalk concluded that the "biomarker panels yielded superior discriminative performance compared to clinical variables alone."
He noted that some of the limitations of the study are that there is no way to validate the findings externally because no other study has been done the same way. It is also unclear how the biomarkers relate to the pathophysiology of the disease, especially considering the multigenic nature of depression.
At this point, they just correlate with risk of the outcome. Finally, although they could possibly be useful for early detection, there is a question of the clinical utility of early detection in altering the course of the disease.
Session moderators Jean-Marie Sengelen, MD, of the psychiatric hospital in Rouffach, France, and Benjamin Lavigne, who is in his final year of medical training at the University of Limoges, France, spoke with Medscape Medical News after the session. Dr Sengelen commented that in the coming years, psychiatry will have to count on techniques such biology, genetics, and imaging.
"I think combinations of these kinds of techniques will help us to have a better diagnostic [ability] and healthcare for patients," he said. Although there are not yet enough results to act upon, he said he believes this is the direction in which healthcare will move.
"For the moment, we have some results, but we don't know what to do with them," Lavigne said.
"We don't understand why these particular molecules are in the social anxiety disorders and why another one is not."
Therefore, he added, more studies will be required before such biomarkers may shed light on mechanisms of pathogenesis and become relevant for practice as well as potential targets for drug development.
There was no commercial funding for the study. Michael Gottschalk, Dr Sengelen, and Benjamin Lavigne report no relevant financial relationships.
European Psychiatric Association (EPA) 23rd Congress. Abstract 0171. Presented March 29, 2015.
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Cite this: Serum, Clinical Measures Predict Depression in Social Phobia - Medscape - Apr 13, 2015.