Wolf, V. | Search bioRxiv

bioRxiv2021

Does non-invasive vagus nerve stimulation affect heart rate variability? A living and interactive Bayesian meta-analysis

Non-invasive brain stimulation techniques, such as transcutaneous auricular vagus nerve stimulation (taVNS), have considerable potential for clinical use. Beneficial effects of taVNS have been demonstrated on symptoms in patients with mental or neurological disorders as well as transdiagnostic dimensions, including mood and motivation. However, since taVNS research is still an emerging field, the underlying neurophysiological processes are not yet fully understood, and the replicability of findings on biomarkers of taVNS effects has been questioned. Here, we perform a living Bayesian random effects meta-analysis to synthesize the current evidence concerning the effects of taVNS on heart rate variability (HRV), a candidate biomarker that has, so far, received most attention in the field. To keep the synthesis of evidence transparent and up to date as new studies are being published, we developed a Shiny web app that regularly incorporates new results and enables users to modify study selection criteria to evaluate the robustness of the inference across potential confounds. Our analysis focuses on 17 single-blind studies comparing taVNS versus sham in healthy participants. These newly synthesized results provide strong evidence for the null hypothesis (g = 0.011, CIshortest = [-0.103, 0.125], BF01 = 25.587), indicating that acute taVNS does not alter HRV compared to sham. To conclude, based on a synthesis of the available evidence to date, there is no support for the hypothesis that HRV is a robust biomarker for acute taVNS. By increasing transparency and timeliness, we believe that the concept of living meta-analyses can lead to transformational benefits in emerging fields such as non-invasive brain stimulation.

physiology↗

bioRxiv2020

Genome wide efficiency profiling reveals modulation of maintenance and de novo methylation by Tets

A precise understanding of DNA methylation dynamics on a genome wide scale is of great importance for the comprehensive investigation of a variety of biological processes such as reprogramming of somatic cells to iPSCs, cell differentiation and also cancer development. To date, a complex integration of multiple and distinct genome wide data sets is required to derive the global activity of DNA modifying enzymes. We present GwEEP - Genome-wide Epigenetic Efficiency Profiling as a versatile approach to infer dynamic efficiency changes of DNA modifying enzymes at base pair resolution on a genome wide scale. GwEEP relies on genome wide oxidative Hairpin Bisulfite sequencing (HPoxBS) data sets, which are translated by a sophisticated hidden Markov model into quantitative enzyme efficiencies with reported confidence around the estimates. GwEEP in its present form predicts de novo and maintenance methylation efficiencies of Dnmts, as well as the hydroxylation efficiency of Tets but its purposefully flexible design allows to capture further oxidation processes such as formylation and carboxylation given available data in the future. Applied to a well characterized ES cell model, GwEEP precisely predicts the complex epigenetic changes following a Serum-to-2i shift i.e., (i) instant reduction in maintenance efficiency (ii) gradually decreasing de novo methylation efficiency and (iii) increasing Tet efficiencies. In addition, a complementary analysis of Tet triple knock-out ES cells confirms the previous hypothesized mutual interference of Dnmts and Tets. GwEEP is applicable to a wide range of biological samples including cell lines, but also tissues and primary cell types. MOTIVATIONDynamic changes of DNA methylation patterns are a common phenomenon in epigenetics. Although a stable DNA methylation profile is essential for cell identity, developmental processes require the rearrangement of 5-methylcytosine in the genome. Stable methylation patterns are the result of balanced Dnmts and Tets activities, while methylome transformation results from a coordinated change in Dnmt and Tet efficiencies. Such transformations occur on a global scale, for example during the reprogramming of maternal and paternal methylation patterns and the establishment of novel cell type specific methylomes during embryonic development in vivo, but also in vitro during (re)programming of induced pluripotent stem cells, as well as somatic cells. In addition, local (de)methylation events are key for gene regulation during cell differentiation. A detailed understanding of Dnmt and Tet cooperation is essential for understanding natural epigenetic adaptation as well as optimization of in vitro (re)programming protocols. For this purpose, we developed a pipeline for quantitative and precise estimation of Dnmt and Tet activity. Using only double strand methylation information, GwEEP infers accurate maintenance and de novo methylation efficiency of Dnmts, as well as hydroxylation efficiency of Tets at single base resolution. Thus, we believe GwEEP provides a powerful tool for the investigation of methylome rearrangements in various systems.

genomics↗