Parental experiences of rapid exome sequencing in cases with major ultrasound anomalies during pregnancy

BACKGROUND: Adding rapid Exome Sequencing (rES) to conventional genetic tests improves the diagnostic yield of pregnancies showing ultrasound abnormalities but also carries a higher chance of unsolicited findings. We evaluated how rES, including pre- and post-test counseling, was experienced by parents investigating its impact on decision-making and experienced levels of anxiety. METHODS: A mixed-methods approach was adopted. Participating couples (n=46) were asked to fill in two surveys (pre-test and post-test counseling) and 11 couples were approached for an additional interview. RESULTS: All couples accepted the rES test-offer with the most important reason for testing emphasizing their hope of finding an underlying diagnosis that would aid decision-making. The actual impact on decision-making was low, however, since most parents decided to terminate the pregnancy based on the major and multiple fetal ultrasound anomalies and did not wait for their rES results. Anxiety was elevated for most participants and decreased over time. CONCLUSION: Major congenital anomalies detected on ultrasound seem to have more impact on prenatal parental decision-making and anxiety then the offer and results of rES. However, the impact of rES on reproductive decision-making and experienced anxiety requires further investigation, especially in pregnancies where less (severe) fetal anomalies are detected on ultrasound. This article is protected by copyright. All rights reserved

Target engagement and brain state dependence of transcranial magnetic stimulation:implications for clinical practice

Transcranial Magnetic Stimulation (TMS) is capable of noninvasively inducing lasting neuroplastic changes when applied repetitively across multiple treatment sessions. In recent years, repetitive TMS has developed into an established evidence-based treatment for various neuropsychiatric disorders such as depression. Despite significant advancements in our understanding of the mechanisms of action of TMS, there is still much to learn about how these mechanisms relate to the clinical effects observed in patients. If there is one thing about TMS that we know for sure, it is that TMS effects are state-dependent. In this review, we will describe how the effects of TMS on brain networks depend on various factors, including cognitive brain state, oscillatory brain state, and recent brain state history. These states play a crucial role in determining the effects of TMS at the moment of stimulation and are therefore directly linked to what is referred to as target engagement in TMS therapy. There is no control over target engagement without considering the different brain state dependencies of our TMS intervention. Clinical TMS protocols are largely ignoring this fundamental principle, which may explain the large variability and often still limited efficacy of TMS treatments. We propose that after almost 30 years of research on state-dependency of TMS, it is time to change standard clinical practice by taking advantage of this fundamental principle. Rather than ignoring TMS state-dependency, we can use it to our clinical advantage to improve the effectiveness of TMS treatments

Heartbeat evoked potential in major depressive disorder:A biomarker for differential treatment prediction between venlafaxine and rTMS?

Introduction: Currently, major depressive disorder (MDD) treatment plans are based on trial-and-error, and remission rates remain low. A strategy to replace trial-and-error and increase remission rates could be treatment stratification. We explored the heartbeat-evoked potential (HEP) as a biomarker for treatment stratification to either antidepressant medication or rTMS treatment. Methods: Two datasets were analyzed: (1) the International Study to Predict Optimized Treatment in Depression (iSPOT-D; n = 1,008 MDD patients, randomized to escitalopram, sertraline, or venlafaxine, and n = 336 healthy controls) and (2) a multi-site, open-label rTMS study (n = 196). The primary outcome measure was remission. Cardiac field artifacts were removed from the baseline EEG using independent component analysis (ICA). The HEP-peak was detected in a bandwidth of 20 ms around 8 ms and 270 ms (N8, N270) after the R-peak of the electrocardiogram signal. Differences between remitters and non-remitters were statistically assessed by repeated-measures ANOVAs for electrodes Fp1, Cz, and Oz. Results: In the venlafaxine subgroup, remitters showed a lower HEP around the N8 peak than non-remitters on electrode site Cz (p = 0.004; d = 0.497). The rTMS group showed a non-significant difference in the opposite direction (d = -0.051). Retrospective stratification to one of the treatments based on the HEP resulted in enhanced treatment outcome prediction for venlafaxine (+22.98%) and rTMS (+10.66%). Conclusion: These data suggest that the HEP could be used as a stratification biomarker between venlafaxine and rTMS; however, future out-of-sample replication is warranted