Multiomics and blood-based biomarkers of electroconvulsive therapy in severe and treatment-resistant depression: study protocol of the DetECT study.

Electroconvulsive therapy (ECT) is commonly used to treat treatment-resistant depression (TRD). However, our knowledge of the ECT-induced molecular mechanisms causing clinical improvement is limited. To address this issue, we developed the single-center, prospective observational DetECT study ("Multimodal Biomarkers of ECT in TRD"; registered 18/07/2022, www.clinicalTrials.gov , NCT05463562). Its objective is to identify molecular, psychological, socioeconomic, and clinical biomarkers of ECT response in TRD. We aim to recruit n = 134 patients in 3 years. Over the course of 12 biweekly ECT sessions (± 7 weeks), participant blood is collected before and 1 h after the first and seventh ECT and within 1 week after the twelfth session. In pilot subjects (first n = 10), additional blood draws are performed 3 and 6 h after the first ECT session to determine the optimal post-ECT blood draw interval. In blood samples, multiomic analyses are performed focusing on genotyping, epigenetics, RNA sequencing, neuron-derived exosomes, purines, and immunometabolics. To determine clinical response and side effects, participants are asked weekly to complete four standardized self-rating questionnaires on depressive and somatic symptoms. Additionally, clinician ratings are obtained three times (weeks 1, 4, and 7) within structured clinical interviews. Medical and sociodemographic data are extracted from patient records. The multimodal data collected are used to perform the conventional statistics as well as mixed linear modeling to identify clusters that link biobehavioural measures to ECT response. The DetECT study can provide important insight into the complex mechanisms of ECT in TRD and a step toward biologically informed and data-driven-based ECT biomarkers.

The biological classification of mental disorders (BeCOME) study: a protocol for an observational deep-phenotyping study for the identification of biological subtypes.

BACKGROUND: A major research finding in the field of Biological Psychiatry is that symptom-based categories of mental disorders map poorly onto dysfunctions in brain circuits or neurobiological pathways. Many of the identified (neuro) biological dysfunctions are "transdiagnostic", meaning that they do not reflect diagnostic boundaries but are shared by different ICD/DSM diagnoses. The compromised biological validity of the current classification system for mental disorders impedes rather than supports the development of treatments that not only target symptoms but also the underlying pathophysiological mechanisms. The Biological Classification of Mental Disorders (BeCOME) study aims to identify biology-based classes of mental disorders that improve the translation of novel biomedical findings into tailored clinical applications. METHODS: BeCOME intends to include at least 1000 individuals with a broad spectrum of affective, anxiety and stress-related mental disorders as well as 500 individuals unaffected by mental disorders. After a screening visit, all participants undergo in-depth phenotyping procedures and omics assessments on two consecutive days. Several validated paradigms (e.g., fear conditioning, reward anticipation, imaging stress test, social reward learning task) are applied to stimulate a response in a basic system of human functioning (e.g., acute threat response, reward processing, stress response or social reward learning) that plays a key role in the development of affective, anxiety and stress-related mental disorders. The response to this stimulation is then read out across multiple levels. Assessments comprise genetic, molecular, cellular, physiological, neuroimaging, neurocognitive, psychophysiological and psychometric measurements. The multilevel information collected in BeCOME will be used to identify data-driven biologically-informed categories of mental disorders using cluster analytical techniques. DISCUSSION: The novelty of BeCOME lies in the dynamic in-depth phenotyping and omics characterization of individuals with mental disorders from the depression and anxiety spectrum of varying severity. We believe that such biology-based subclasses of mental disorders will serve as better treatment targets than purely symptom-based disease entities, and help in tailoring the right treatment to the individual patient suffering from a mental disorder. BeCOME has the potential to contribute to a novel taxonomy of mental disorders that integrates the underlying pathomechanisms into diagnoses. TRIAL REGISTRATION: Retrospectively registered on June 12, 2019 on ClinicalTrials.gov (TRN: NCT03984084).

Vitamin D and cardiovascular disease: systematic review and meta-analysis of prospective studies.

BACKGROUND: Low serum 25-hydroxyvitamin D (25-OH-D) has recently been linked to cardiovascular diseases. This review summarizes evidence from prospective studies evaluating the prognostic value of 25-OH-D for cardiovascular disease incidence and mortality. METHOD: A systematic literature search in EMBASE and Pubmed-Medline databases was performed until November 2009. Prospective studies published in English were selected reporting estimates for the association of 25-OH-D with primary or secondary cardiovascular event incidence or mortality in the general population or subjects with prevalent cardiovascular disease. Pooled risk estimators were derived by meta-analysis using a random effects model approach. RESULTS: Four incidence and five independent mortality studies were included. Two incidence and three mortality studies reported a two- to five-fold risk increase for both outcomes in subjects with lower 25-OH-D, while the others did not detect a significant association. Meta-analysis supported the existence of an inverse association. CONCLUSION: Data from prospective investigations suggest an inverse association between 25-OH-D and cardiovascular risk. However, given the heterogeneity and small number of longitudinal studies, more research is needed to corroborate a potential prognostic value of 25-OH-D for cardiovascular disease incidence and mortality.

Prognostic usefulness of free fatty acids in patients with stable coronary heart disease.

Circulating nonesterified or free fatty acids (FFAs) may contribute to the development of cardiovascular pathology and correlate with ischemia in acute cardiovascular conditions. The aim of this study was to assess whether serum levels of FFAs are associated with long-term prognosis in subjects with stable coronary heart disease. This observational prospective cohort study included 1,206 participants in 3-weeks inpatient rehabilitation programs after acute myocardial infarction, coronary syndromes, or coronary intervention at 2 rehabilitation clinics in Germany (1999 to 2000). Eight-year prognosis (time to a secondary fatal or nonfatal cardiovascular disease event including myocardial infarction and stroke [n = 153] and time to death from any cause [n = 124]) was examined according to FFA quartiles and in spline regression. FFAs were correlated with established serum markers of cardiovascular risk and strongly related to secondary cardiovascular events and all-cause mortality in age- and gender-adjusted analysis. When additionally controlling for multiple established risk factors and risk markers, the hazard ratio in the fourth versus first quartile was 1.34 (95% confidence interval 0.79 to 2.24) for secondary cardiovascular events and 1.09 (95% confidence interval 0.62 to 1.91) for all-cause mortality. Dose-response modeling suggested that very high FFAs might predict an increased risk for mortality (hazard ratio 1.98, 95% confidence interval 0.98 to 4.02, for 95th percentile vs first quartile). In conclusion, FFAs are closely correlated with cardiovascular risk markers, and in particular, very high FFA might identify patients with stable coronary heart disease with worse prognoses.