Association between pre-biologic T2-biomarker combinations and response to biologics in patients with severe asthma

Background

To date, studies investigating the association between pre-biologic biomarker levels and post-biologic outcomes have been limited to single biomarkers and assessment of biologic efficacy from structured clinical trials.

Aim

To elucidate the associations of pre-biologic individual biomarker levels or their combinations with pre-to-post biologic changes in asthma outcomes in real-life.

Methods

This was a registry-based, cohort study using data from 23 countries, which shared data with the International Severe Asthma Registry (May 2017-February 2023). The investigated biomarkers (highest pre-biologic levels) were immunoglobulin E (IgE), blood eosinophil count (BEC) and fractional exhaled nitric oxide (FeNO). Pre- to approximately 12-month post-biologic change for each of three asthma outcome domains (i.e. exacerbation rate, symptom control and lung function), and the association of this change with pre-biologic biomarkers was investigated for individual and combined biomarkers.

Results

Overall, 3751 patients initiated biologics and were included in the analysis. No association was found between pre-biologic BEC and pre-to-post biologic change in exacerbation rate for any biologic class. However, higher pre-biologic BEC and FeNO were both associated with greater post-biologic improvement in FEV1 for both anti-IgE and anti-IL5/5R, with a trend for anti-IL4Rα. Mean FEV1 improved by 27-178 mL post-anti-IgE as pre-biologic BEC increased (250 to 1000 cells/µL), and by 43-216 mL and 129-250 mL post-anti-IL5/5R and -anti-IL4Rα, respectively along the same BEC gradient. Corresponding improvements along a FeNO gradient (25-100 ppb) were 41-274 mL, 69-207 mL and 148-224 mL for anti-IgE, anti-IL5/5R, and anti-IL4Rα, respectively. Higher baseline BEC was also associated with lower probability of uncontrolled asthma (OR 0.392; p=0.001) post-biologic for anti-IL5/5R. Pre-biologic IgE was a poor predictor of subsequent pre-to-post-biologic change for all outcomes assessed for all biologics. The combination of BEC + FeNO marginally improved the prediction of post-biologic FEV1 increase (adjusted R2: 0.751), compared to BEC (adjusted R2: 0.747) or FeNO alone (adjusted R2: 0.743) (p=0.005 and <0.001, respectively); however, this prediction was not improved by the addition of IgE.

Conclusions

The ability of higher baseline BEC, FeNO and their combination to predict biologic-associated lung function improvement may encourage earlier intervention in patients with impaired lung function or at risk of accelerated lung function decline.

Advances in neuroproteomics for neurotrauma: unraveling insights for personalized medicine and future prospects

Neuroproteomics, an emerging field at the intersection of neuroscience and proteomics, has garnered significant attention in the context of neurotrauma research. Neuroproteomics involves the quantitative and qualitative analysis of nervous system components, essential for understanding the dynamic events involved in the vast areas of neuroscience, including, but not limited to, neuropsychiatric disorders, neurodegenerative disorders, mental illness, traumatic brain injury, chronic traumatic encephalopathy, and other neurodegenerative diseases. With advancements in mass spectrometry coupled with bioinformatics and systems biology, neuroproteomics has led to the development of innovative techniques such as microproteomics, single-cell proteomics, and imaging mass spectrometry, which have significantly impacted neuronal biomarker research. By analyzing the complex protein interactions and alterations that occur in the injured brain, neuroproteomics provides valuable insights into the pathophysiological mechanisms underlying neurotrauma. This review explores how such insights can be harnessed to advance personalized medicine (PM) approaches, tailoring treatments based on individual patient profiles. Additionally, we highlight the potential future prospects of neuroproteomics, such as identifying novel biomarkers and developing targeted therapies by employing artificial intelligence (AI) and machine learning (ML). By shedding light on neurotrauma's current state and future directions, this review aims to stimulate further research and collaboration in this promising and transformative field.

An innovative framework to determine the implementation level of personalized medicine: A systematic review

Background

Personalized medicine (PM) is now the new frontier in patient care. The application of this new paradigm extends to various pathologies and different patient care phases, such as diagnosis and treatment. Translating biotechnological advances to clinical routine means adapting health services at all levels is necessary.

Purpose

This article aims to identify the elements for devising a framework that will allow the level of PM implementation in the country under study to be quantitatively and qualitatively assessed and that can be used as a guideline for future implementation plans.

Methods

A systematic review was conducted per the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. The research question was: What are the domains for determining the level of implementation of PM at the national level? The domains for assessing the degree of PM implementation, which would form the framework, were established.

Results

19 full-text studies that met the inclusion criteria were peer-selected in the systematic review. From all the studies that were included, 37 elements-encompassed in 11 domains-were extracted for determining the degree of PM implementation. These domains and their constituent elements comprise the qualitative and quantitative assessment framework presented herein. Each of the elements can be assessed individually. On the other hand, the domains were standardized to all have the same weight in an overall assessment.

Conclusions

A framework has been developed that takes a multi-factorial approach to determine the degree of implementation of PM at the national level. This framework could also be used to rank countries and their implementation strategies according to the score they receive in the application of the latter. It could also be used as a guide for developing future national PM implementation strategies.

Systematic review registration

https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022338611, Identifier: CRD42022338611.

Personalized-medicine on carotid endarterectomy and stenting

Evidence based medicine (EBM) is the core of current clinical guidelines and is considered as the gold standard of clinical practice. Despite this, a number of limitations and criticisms are moved to EBM. The major one is that this method privileges randomized controlled trials (RCTs), in which the selection of patients is often based on rigid inclusion criteria. The lack of “pragmatism” of some RCTs sometimes makes it difficult to apply guidelines that derive from them to patients observed in clinical practice, who are often affected by comorbidities and disabilities. The new paradigm to overcome this limitation is personalized medicine (PM), which aims to take into account the particular characteristics displayed by the individual. In order to tailor the best treatment for the patient, PM uses EBM but emphasizes the person's specific information from the assessment of the clinic, lifestyle and risk/benefit scores. This narrative review tries to find the best evidence by analysing subgroups and risk scores of patients from meta-analysis and RCTs in order to try to apply PM and to provide good practice points (GPP) on grey aspects and open questions not fully covered by current guidelines on carotid endarterectomy (CEA) and stenting for stroke prevention.