Correction: Digital Phenotyping for Differential Diagnosis of Major Depressive Episode: Narrative Review.

[This corrects the article DOI: 10.2196/37225.].

Digital Phenotyping for Differential Diagnosis of Major Depressive Episode: Narrative Review.

BACKGROUND: Major depressive episode (MDE) is a common clinical syndrome. It can be found in different pathologies such as major depressive disorder (MDD), bipolar disorder (BD), posttraumatic stress disorder (PTSD), or even occur in the context of psychological trauma. However, only 1 syndrome is described in international classifications (Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition [DSM-5]/International Classification of Diseases 11th Revision [ICD-11]), which do not take into account the underlying pathology at the origin of the MDE. Clinical interviews are currently the best source of information to obtain the etiological diagnosis of MDE. Nevertheless, it does not allow an early diagnosis and there are no objective measures of extracted clinical information. To remedy this, the use of digital tools and their correlation with clinical symptomatology could be useful. OBJECTIVE: We aimed to review the current application of digital tools for MDE diagnosis while highlighting shortcomings for further research. In addition, our work was focused on digital devices easy to use during clinical interview and mental health issues where depression is common. METHODS: We conducted a narrative review of the use of digital tools during clinical interviews for MDE by searching papers published in PubMed/MEDLINE, Web of Science, and Google Scholar databases since February 2010. The search was conducted from June to September 2021. Potentially relevant papers were then compared against a checklist for relevance and reviewed independently for inclusion, with focus on 4 allocated topics of (1) automated voice analysis, behavior analysis by (2) video and physiological measures, (3) heart rate variability (HRV), and (4) electrodermal activity (EDA). For this purpose, we were interested in 4 frequently found clinical conditions in which MDE can occur: (1) MDD, (2) BD, (3) PTSD, and (4) psychological trauma. RESULTS: A total of 74 relevant papers on the subject were qualitatively analyzed and the information was synthesized. Thus, a digital phenotype of MDE seems to emerge consisting of modifications in speech features (namely, temporal, prosodic, spectral, source, and formants) and in speech content, modifications in nonverbal behavior (head, hand, body and eyes movement, facial expressivity, and gaze), and a decrease in physiological measurements (HRV and EDA). We not only found similarities but also differences when MDE occurs in MDD, BD, PTSD, or psychological trauma. However, comparative studies were rare in BD or PTSD conditions, which does not allow us to identify clear and distinct digital phenotypes. CONCLUSIONS: Our search identified markers from several modalities that hold promise for helping with a more objective diagnosis of MDE. To validate their potential, further longitudinal and prospective studies are needed.

Comparison of Environmental and Culture-Derived Bacterial Communities through 16S Metabarcoding: A Powerful Tool to Assess Media Selectivity and Detect Rare Taxa.

To compare environmental and culture-derived microbial communities, we performed 16S metabarcoding of uncultured samples and their culture-derived bacterial lawns. Microbial communities were obtained from freshwater river samples representative of an anthropization gradient along a river stream. Their culture-derived bacterial lawns were obtained by growing aliquots of the samples on a broad range medium and on two different semi-selective media. The V3-V4 16S rRNA region was amplified and sequenced. The bacterial diversity of water samples decreased from the upper to lower stream sampling sites and, as expected, these differences were mostly suppressed by the culture step. Overall, the diversity of cultured-derived bacterial communities reflected selectivity of each tested medium. Comparison of treatments indicated that the culture selected both detected and rare undetected environmental species. Accurate detection of rare environmental bacteria of the Pectobacterium genus by 16S metabarcoding of the culture lawn was demonstrated. Interestingly, for abundant taxa, such as those of the Pseudomonas genus, the culture/environment ratio varied between sampled sites, indicating the difficulty of comparing cultured-derived taxa abundance between environmental sites. Finally, our study also highlighted media specificity and complementarity: bacterial communities grown on the two selective media, while selecting a small set of specific species, were mostly a subset of the bacterial community observed on the broad range medium.