Opportunities offered by latent-based multiblock strategies to integrate biomarkers of chemical exposure and biomarkers of effect in environmental health studies.

Modern environmental epidemiology benefits from a new generation of technologies that enable comprehensive profiling of biomarkers, including environmental chemical exposure and omic datasets. The integration and analysis of large and structured datasets to identify functional associations is constrained by computational challenges that cannot be overcome using conventional regression methods. Some extensions of Partial Least Squares (PLS) regression have been developed to efficently integrate multiple datasets, including Multiblock PLS (MB-PLS) and Sequential and Orthogonalized PLS; however, these approaches remain seldom applied in environmental epidemiology. To address that research gap, this study aimed to assess and compare the applicability of PLS-based multiblock models in an observational case study, where biomarkers of exposure to environmental chemicals and endogenous biomarkers of effect were simultaneously integrated to highlight biological links related to a health outcome. The methods were compared with and without sparsity coupling two metrics to support the variable selection: Variable Importance in Projection (VIP) and Selectivity Ratio (SR). The framework was applied to a case-study dataset mimicking the structure of 36 environmental exposure biomarkers (E-block), 61 inflammation biomarkers (M-block), and their relationships with the gestational age at delivery of 161 mother-infant pairs. The results showed an overall consistency in the selected variables across models, although some specific selection patterns were identified. The block-scaled concatenation-based approaches (e.g. MB-PLS) tended to select more variables from the E-block, while these methods were unable to identify certain variables in the M-block. Overall, the number of variables selected using the SR criterion was higher than using the VIP criterion, with lower predictive performances. The multiblock models coupled to VIP, appeared to be the methods of choice for identifying relevant variables with similar statistical performances. Overall, the use of multiblock PLS-based methods appears to be a good strategy to efficiently support the variable selection process in modern environmental epidemiology.

A review of statistical strategies to integrate biomarkers of chemical exposure with biomarkers of effect applied in omic-scale environmental epidemiology.

Humans are exposed to a growing list of synthetic chemicals, some of them becoming a major public health concern due to their capacity to impact multiple biological endpoints and contribute to a range of chronic diseases. The integration of endogenous (omic) biomarkers of effect in environmental health studies has been growing during the last decade, aiming to gain insight into potential mechanisms linking the exposures and the clinical conditions. The emergence of high-throughput omic platforms has raised a list of statistical challenges posed by the large dimension and complexity of data generated. Thus, the aim of the present study was to critically review the current state-of-the-science about statistical approaches used to integrate endogenous biomarkers in environmental-health studies linking chemical exposures with health outcomes. The present review specifically focused on internal exposure to environmental chemical pollutants, involving both persistent organic pollutants (POPs) and non-persistent pollutants like phthalates or bisphenols, and metals. We identified 42 eligible articles published since 2016, reporting 48 different statistical workflows, mostly focused on POPs and using metabolomic profiling in the intermediate layer. The outcomes were mainly binary and focused on metabolic disorders. A large diversity of statistical strategies were reported to integrate chemical mixtures and endogenous biomarkers to characterize their associations with health conditions. Multivariate regression models were the most predominant statistical method reported in the published workflows, however some studies applied latent based methods or multipollutant models to overcome the specific constraints of omic or exposure data. A minority of studies used formal mediation analysis to characterize the indirect effects mediated by the endogenous biomarkers. The principles of each specific statistical method and overall workflow set-up are summarized in the light of highlighting their applicability, strengths and weaknesses or interpretability to gain insight into the causal structures underlying the triad: exposure, effect-biomarker and outcome.

Evaluation of External Trigeminal Nerve Stimulation to Prevent Cerebral Vasospasm after Subarachnoid Hemorrhage Due to Aneurysmal Rupture: A Randomized, Double-Blind Proof-of-Concept Pilot Trial (TRIVASOSTIM Study).

Cerebral vasospasm remains the most frequent and devastating complication after subarachnoid aneurysmal hemorrhage because of secondary cerebral ischemia and its sequelae. The underlying pathophysiology involves vasodilator peptide release (such as CGRP) and nitric oxide depletion at the level of the precapillary sphincters of the cerebral (internal carotid artery network) and dural (external carotid artery network) arteries, which are both innervated by craniofacial autonomic afferents and tightly connected to the trigeminal nerve and trigemino-cervical nucleus complex. We hypothesized that trigeminal nerve modulation could influence the cerebral flow of this vascular network through a sympatholytic effect and decrease the occurrence of vasospasm and its consequences. We conducted a prospective double-blind, randomized controlled pilot trial to compare the effect of 10 days of transcutaneous electrical trigeminal nerve stimulation vs. sham stimulation on cerebral infarction occurrence at 3 months. Sixty patients treated for aneurysmal SAH (World Federation of Neurosurgical Societies scale between 1 and 4) were included. We compared the radiological incidence of delayed cerebral ischemia (DCI) on magnetic resonance imaging (MRI) at 3 months in moderate and severe vasospasm patients receiving trigeminal nerve stimulation (TNS group) vs. sham stimulation (sham group). Our primary endpoint (the infarction rate at the 3-month follow-up) did not significantly differ between the two groups (p = 0.99). Vasospasm-related infarctions were present in seven patients (23%) in the TNS group and eight patients (27%) in the sham group. Ultimately, we were not able to show that TNS can decrease the rate of cerebral infarction secondary to vasospasm occurrence. As a result, it would be premature to promote trigeminal system neurostimulation in this context. This concept should be the subject of further research.

The Challenge of Converting "Failed Spinal Cord Stimulation Syndrome" Back to Clinical Success, Using SCS Reprogramming as Salvage Therapy, through Neurostimulation Adapters Combined with 3D-Computerized Pain Mapping Assessment: A Real Life Retrospective Study.

While paresthesia-based Spinal Cord Stimulation (SCS) has been proven effective as treatment for chronic neuropathic pain, its initial benefits may lead to the development of "Failed SCS Syndrome' (FSCSS) defined as decrease over time related to Loss of Efficacy (LoE) with or without Loss of Coverage (LoC). Development of technologies associating new paresthesia-free stimulation waveforms and implanted pulse generator adapters provide opportunities to manage patients with LoE. The main goal of our study was to investigate salvage procedures, through neurostimulation adapters, in patients already implanted with SCS and experiencing LoE. We retrospectively analyzed a cohort of patients who were offered new SCS programs/waveforms through an implanted adapter between 2018 and 2021. Patients were evaluated before and at 1-, 3-, 6- and 12-month follow-ups. Outcomes included pain intensity rating with a Visual Analog Scale (VAS), pain/coverage mappings and stimulation preferences. Last follow-up evaluations (N = 27) showed significant improvement in VAS (p = 0.0001), ODI (p = 0.021) and quality of life (p = 0.023). In the 11/27 patients with LoC, SCS efficacy on pain intensity (36.89%) was accompanied via paresthesia coverage recovery (55.57%) and pain surface decrease (47.01%). At 12-month follow-up, 81.3% preferred to keep tonic stimulation in their waveform portfolio. SCS conversion using adapters appears promising as a salvage solution, with an emphasis on paresthesia recapturing enabled via spatial retargeting. In light of these results, adapters could be integrated in SCS rescue algorithms or should be considered in SCS rescue.