BACKGROUND:Early identification of children at risk of asthma attacks is important for optimizing treatment strategies. We aimed to integrate salivary microbiome and serum inflammatory mediator profiles with asthma attacks history to develop a comprehensive predictive model for future attacks. METHODS:This study contained a discovery (SysPharmPediA) and a replication phase (U-BIOPRED). School-aged children with asthma were classified into at risk and no-risk groups, based on the presence or absence of one or more severe attacks during one-year follow-up. Prediction models were developed using random forest on the training set (70%) with data on past asthma attacks, microbiome composition, serum inflammatory mediator levels, and their combinations and then tested on the rest of the population (30%). Outcomes were replicated in a subset of children with severe asthma from U-BIOPRED. RESULTS:Complete data were available for 154 children (SysPharmPediA = 121, U-BIOPRED = 33). In discovery, the model based on past attacks resulted in an area under the receiving characteristic curve (AUROCC) ~ 0.7. Models including six salivary bacteria or six inflammatory mediators achieved similar results. The combined model incorporating seven features, past asthma attacks, Capnocytophaga, Corynebacterium, and Cardiobacterium, TIMP-4, VEGF, and MIP-3β achieved the highest accuracy with AUROCC ~0.87. The combined model in the U-BIOPRED limited to available inflammatory mediators (VEGF), and incorporating past asthma attacks, Capnocytophaga, Corynebacterium, and Cardiobacterium, resulted in an AUROCC of 0.84. CONCLUSION:Serum inflammatory mediators and salivary microbiome complement asthma attacks history for predicting future attacks. These results highlight the imperative for continued investigation into oral microbiota and its interaction with the immune system.

BACKGROUND:Vascular alterations contribute significantly to the chronic obstructive pulmonary disease (COPD) pathophysiology. Thirty-nine percent of patients with COPD develop pulmonary hypertension, especially patients with the severe form of the disease. Cigarette-induced endothelial dysfunction is important in the pathogenesis of vascular alterations, even in the mild forms of the disease. This study investigates extracellular matrix (ECM) remodelling and endothelial activation in pulmonary (PMA) and bronchial muscular arteries (BMA) from non-smokers (NS), nonobstructed smokers (NOS) and patients with mild/moderate COPD. METHODS:Lung tissue samples from 44 patients undergoing lung resection were analysed. Morphometric parameters, ECM components (collagens, fibronectin, elastic fibres, tenascin-C and versican) and endothelial markers (VCAM-1, ICAM-1 and endothelin-1) were quantified in BMA and PMA using immunohistochemistry and morphometric analysis. Group differences and correlations with clinical parameters were assessed. RESULTS:COPD patients showed increased intimal thickness and fibronectin deposition in PMA, and larger adventitial areas in BMA compared to NS. NOS exhibited higher VCAM-1 expression in BMA and increased elastic fibre content in PMA. In COPD, elastic fibres and type-III collagen negatively correlated with smoking history (pack-years), while fibronectin positively correlated with age. VCAM-1 expression in BMA correlated negatively with lung function (FEV1 and FEV1/FVC). CONCLUSIONS:This study demonstrates for the first time ECM remodelling and endothelial activation in bronchial arteries of smokers and patients with COPD. Fibronectin emerges as a key ECM component in arterial remodelling in mild-moderate COPD. Understanding vascular changes may provide new insights into the regulation of bronchial circulation and the development of pulmonary hypertension in COPD.

Rationale Biological processes continuously fluctuate due to non-linear interactions with other biological processes and external perturbations. A previous analysis showed that in patients with asthma physiological and inflammatory processes are regulated differently compared to healthy individuals, which leads to a loss of adaptive capacity in response to e.g. a viral challenge (PMID: 31687927). In this study we aimed to determine fluctuation patterns of metabolic pathways in patient with asthma and healthy individuals by analysis of the urine metabolome, both in stable phase and after a viral challenge. Methods Urine samples of 11 patients with asthma and 12 healthy individuals were collected 3 times a week for a duration of 7 weeks. Samples were analysed by ultra-high-performance liquid chromatography combined with tandem mass spectrometry, both in the positive and negative ion mode. The average fluctuation per metabolite was calculated as the mean squared difference in abundance between two consecutive measurements adjusted for the time interval. The difference between asthma and healthy were normalized based on the average abundance and the metabolites with the greatest difference were further analysed using metaboanalyst.ca to determine the most dominant metabolic pathways. Results As a first approach we selected the metabolites from the positive ion analysis that showed the largest fluctuations in urine from both asthma patients and healthy individuals. After that we determined which pathways were implicated most, thus being discriminatory between asthma and health. Table 1 shows the most discriminative metabolites and its pathways (mean A-H difference in all metabolites is -0.36). The fluctuations of the lysine degradation were the highest in patients with asthma. In healthy subject the fluctuations of the glyoxylate and dicarboxylate metabolism and tryptophan metabolism, glycine, serine and threonine metabolism and purine metabolism (all KEGG pathways) were highest. We have previously studied the tryptophan metabolism in asthma and healthy subjects in conjunction with a rhinovirus challenge (PMID: 23882022), showing that in asthma there was an enhanced systemic tryptophan metabolism, but a reduced metabolism in the airways. In the current analysis we found a larger fluctuation pattern for tryptophan in healthy individuals compared to patients with asthma. Conclusion Our fluctuation analysis of urine metabolites from asthma patients and healthy individuals showed marked differences in the fluctuation of metabolic pathways involving a number of amino acids and purines. The smaller fluctuation in tryptophan metabolism in asthma is consistent with the reduced capacity in controlling inflammation in response to a viral challenge.

Abstract Rationale Knowledge about the clinical importance of patient-reported outcome measures (PROMs) in severe asthma is limited. Objectives To assess whether and to what extent asthma exacerbations affect changes in PROMS over time and asthma-specific PROMs can predict exacerbations in adult patients with severe asthma in usual care. Methods Data of 421 patients with severe asthma (62% female; mean age 51.9 ± 13.4 years; mean FEV1 67.5 ± 21.3%pred) from the U-BIOPRED cohort were analyzed. The included PROMs were: Asthma Control Questionnaire (ACQ5); Asthma Quality of Life Questionnaire (AQLQ); Hospital Anxiety and Depression scale (HADS); Epworth Sleepiness Scale (ESS); Medication Adherence Report Scale (MARS); Sino-Nasal Outcomes Test (SNOT20). Participants were assessed at baseline and after 12–18 months of usual care. Results PROMs showed very weak to weak correlations with clinical characteristics such as age, body mass index, FEV1, FeNO and eosinophilic cell count. Patients presenting no exacerbations during follow-up showed a statistically significant improvement in all PROMs (except for MARS), whereas individuals experiencing > 2 exacerbations showed a deterioration. Baseline ACQ5 was a predictor of exacerbations with an AUC of 0.590 (95%CI 0.514–0.666). Conclusions The association of PROMs with clinical measures was poor in severe asthmatics. Moreover, PROMs were prone to changes in usual care, with exacerbations playing a key role. PROMs need to be systematically evaluated in severe asthma to improve clinical care based on specific patient’s needs.

BACKGROUND:Lung quantitative computed tomography (qCT) severe asthma clusters have been reported, but their replication and underlying disease mechanisms are unknown. We identified and replicated qCT clusters of severe asthma in two independent asthma cohorts and determined their association with molecular pathways, using radiomultiomics, integrating qCT, multiomics and machine learning/artificial intelligence. METHODS:We used consensus clustering on qCT measurements of airway and lung CT scans, performed in 105 severe asthmatic adults from the U-BIOPRED cohort. The same qCT measurements were used to replicate qCT clusters in a subsample of the ATLANTIS asthma cohort (n=97). We performed integrated enrichment analysis using blood, sputum, bronchial biopsies, bronchial brushings and nasal brushings transcriptomics and blood and sputum proteomics to characterise radiomultiomic-associated clusters (RACs). RESULTS:qCT clusters and clinical features in U-BIOPRED were replicated in the matched ATLANTIS cohort. In the U-BIOPRED cohort, RAC1 (n=30) was predominantly female with elevated body mass index, mild airflow limitation, decreased CT lung volume and increased lung density and upregulation of the complement pathway. RAC2 (n=34) subjects had airway wall thickness and a mild degree of airflow limitation, with upregulation of proliferative pathways including neurotrophic receptor tyrosine kinase 2/tyrosine kinase receptor B, and downregulation of semaphorin pathways. RAC3 (n=41) showed increased lung attenuation area and air trapping, severe airflow limitation, hyperinflation, and upregulation of cytokine signalling and signalling by interleukin pathways, and matrix metallopeptidase 1, 2 and 9. CONCLUSIONS:U-BIOPRED severe asthma qCT clusters were replicated in a matched independent asthmatic cohort and associated with specific molecular pathways. Radiomultiomics might represent a novel strategy to identify new molecular pathways in asthma pathobiology.

Background: The anti-IgE monoclonal antibody omalizumab is widely used for severe asthma. This study aimed to identify biomarkers that predict clinical improvement during 1 year of omalizumab treatment. Methods: One-year open-label Study of Mechanisms of action of Omalizumab in Severe Asthma (SoMOSA) involving 216 patients with severe (Global Initiative for Asthma step 4/5) uncontrolled atopic asthma (at least two severe exacerbations in the previous year) taking high-dose inhaled corticosteroids and long-acting β-agonists with or without maintenance oral corticosteroids. It had two phases: 0-16 weeks, to assess early clinical improvement by Global Evaluation of Therapeutic Effectiveness (GETE); and 16-52 weeks, to assess late responses based on ⩾50% reduction in exacerbations or mOCS dose. All participants provided samples (exhaled breath, blood, sputum, urine) before and after 16 weeks of omalizumab treatment. Measurements and Main Results: A total of 191 patients completed phase 1; 63% had early improvement. Of 173 who completed phase 2, 69% had reduced exacerbations by ⩾50% and 57% (37 of 65) taking mOCSs had reduced their dose by ⩾50%. The primary outcomes 2,3-dinor-11-β-PGF2α, GETE score, and standard clinical biomarkers (blood and sputum eosinophils, exhaled nitric oxide, serum IgE) did not predict either clinical response. Five volatile organic compounds and five plasma lipid biomarkers strongly predicted the ⩾50% reduction in exacerbations (receiver operating characteristic areas under the curve of 0.780 and 0.922, respectively) and early responses (areas under the curve of 0.835 and 0.949, respectively). In an independent cohort, gas chromatography/mass spectrometry biomarkers differentiated between severe and mild asthma. Conclusions: This is the first discovery of omics biomarkers that predict improvement in asthma with biologic agent treatment. Prospective validation and development for clinical use is justified.

PURPOSE:Asthma is a clinical syndrome with various underlying pathomechanisms and clinical phenotypes. Genetic, ethnic, and geographic factors may influence the differences in clinical presentation, severity, and prognosis. We compared the characteristics of asthma based on the geographical background by analyzing representative cohorts from the United States, Europe, South America, and Asia using the Severe Asthma Research Program (SARP), Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes (U-BIOPRED), Program for Control of Asthma in Bahia (ProAR), and Cohort for Reality and Evolution of Adult Asthma in Korea (COREA), respectively. METHODS:The clinical characteristics and medications for the SARP (n = 669), U-BIOPRED (n = 509), ProAR (n = 996), and COREA (n = 3,748) were analyzed. Subgroup analysis was performed for severe asthma. RESULTS:The mean age was highest and lowest in the COREA and SARP, respectively. The asthma onset age was lowest in the ProAR. The mean body mass index was highest and lowest in the SARP and COREA, respectively. Baseline pulmonary function was lowest and highest in the U-BIOPRED and COREA, respectively. The number of patients with acute exacerbation in the previous year was highest in U-BIOPRED. The mean blood eosinophil count was highest in COREA. The total immunoglobulin E was highest in the ProAR. The frequency of atopy was highest in the SARP. The principal component analysis plot revealed differences among all cohorts. CONCLUSIONS:The cohorts from 4 different continents exhibited different clinical and physiological characteristics, probably resulting from the interplay between genetic susceptibility and geographical factors.

Rationale Patients with severe asthma are dependent upon treatment with high doses of inhaled corticosteroids (ICS) and often also oral corticosteroids (OCS). The extent of endogenous androgenic anabolic steroid (EAAS) suppression in asthma has not previously been described in detail. The objective of the present study was to measure urinary concentrations of EAAS in relation to exogenous corticosteroid exposure. Methods Urine collected at baseline in the U-BIOPRED (Unbiased Biomarkers for the Prediction of Respiratory Disease outcomes) study of severe adult asthmatics (SA, n=408) was analysed by quantitative mass spectrometry. Data were compared to that of mild-to-moderate asthmatics (MMA, n=70) and healthy subjects (HC, n=98) from the same study. Measurements and main results The concentrations of urinary endogenous steroid metabolites were substantially lower in SA than in MMA or HC. These differences were more pronounced in SA patients with detectable urinary OCS metabolites. Their dehydroepiandrosterone sulfate (DHEA-S) concentrations were <5% of those in HC, and cortisol concentrations were below the detection limit in 75% of females and 82% of males. The concentrations of EAAS in OCS-positive patients, as well as patients on high-dose ICS only, were more suppressed in females than males (p<0.05). Low levels of DHEA were associated with features of more severe disease and were more prevalent in females (p<0.05). The association between low EAAS and corticosteroid treatment was replicated in 289 of the SA patients at follow-up after 12–18 months. Conclusion The pronounced suppression of endogenous anabolic androgens in females might contribute to sex differences regarding the prevalence of severe asthma.

Background: Because of altered airway microbiome in asthma, we analysed the bacterial species in sputum of patients with severe asthma. Methods: Whole genome sequencing was performed on induced sputum from non-smoking (SAn) and current or ex-smoker (SAs/ex) severe asthma patients, mild/moderate asthma (MMA) and healthy controls (HC). Data were analysed by asthma severity, inflammatory status and transcriptome-associated clusters (TACs). Results: alpha-diversity at the species level was lower in SAn and SAs/ex, with an increase in Haemophilus influenzae and Moraxella catarrhalis, and Haemophilus influenzae and Tropheryma whipplei, respectively, compared to HC. In neutrophilic asthma, there was greater abundance of Haemophilus influenzae and Moraxella catarrhalis and in eosinophilic asthma, Tropheryma whipplei was increased. There was a reduction in a-diversity in TAC1 and TAC2 that expressed high levels of Haemophilus influenzae and Tropheryma whipplei, and Haemophilus influenzae and Moraxella catarrhalis, respectively, compared to HC. Sputum neutrophils correlated positively with Moraxella catarrhalis and negatively with Prevotella, Neisseria and Veillonella species and Haemophilus parainfluenzae. Sputum eosinophils correlated positively with Tropheryma whipplei which correlated with pack-years of smoking. alpha-and beta-diversities were stable at one year. Conclusions: Haemophilus influenzae and Moraxella catarrhalis were more abundant in severe neutrophilic asthma and TAC2 linked to inflammasome and neutrophil activation, while Haemophilus influenzae and Tropheryma whipplei were highest in SAs/ex and in TAC1 associated with highest expression of IL-13 type 2 and ILC2 signatures with the abundance of Tropheryma whipplei correlating positively with sputum eosinophils. Whether these bacterial species drive the inflammatory response in asthma needs evaluation.

Rationale: Children with preschool wheezing or school-age asthma are reported to have airway microbial imbalances. Objectives: To identify clusters in children with asthma or wheezing using oropharyngeal microbiota profiles. Methods: Oropharyngeal swabs from the U-BIOPRED (Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes) pediatric asthma or wheezing cohort were characterized using 16S ribosomal RNA gene sequencing, and unsupervised hierarchical clustering was performed on the Bray-Curtis b-diversity. Enrichment scores of the Molecular Signatures Database hallmark gene sets were computed from the blood transcriptome using gene set variation analysis. Children with severe asthma or severe wheezing were followed up for 12-18 months, with assessment of the frequency of exacerbations. Measurements and Main Results: Oropharyngeal samples from 241 children (age range, 1-17 years; 40% female) revealed four taxa-driven clusters dominated by Streptococcus, Veillonella, Rothia, and Haemophilus. The clusters showed significant differences in atopic dermatitis, grass pollen sensitization, FEV1% predicted after salbutamol, and annual asthma exacerbation frequency during follow-up. The Veillonella cluster was the most allergic and included the highest percentage of children with two or more exacerbations per year during follow-up. The oropharyngeal clusters were different in the enrichment scores of TGF-b (transforming growth factor-b) (highest in the Veillonella cluster) and Wnt/b-catenin signaling (highest in the Haemophilus cluster) transcriptomic pathways in blood (all q values,0.05). Conclusions: Analysis of the oropharyngeal microbiota of children with asthma or wheezing identified four clusters with distinct clinical characteristics (phenotypes) that associate with risk for exacerbation and transcriptomic pathways involved in airway remodeling. This suggests that further exploration of the oropharyngeal microbiota may lead to novel pathophysiologic insights and potentially new treatment approaches.

Background: The obese-asthma phenotype can be difficult-to-treat and severe in children; however, underlying mechanisms are unknown. Objective: Explore if gene expression patterns in children with mild/moderate vs severe (MMA vs SA) asthma differ by age and sex-adjusted BMI z-scores (BMIz), and if these differentially expressed patterns have functional significance. Methods: We performed a cross-sectional analysis of baseline clinical and blood transcriptome data from the U-BIOPRED cohort, including children aged 5-17 years with MMA (N=37) or SA (N=74). We ran gene-specific regression models for the outcome, asthma status (MMA vs SA), including age, sex, gene expression, BMIz, and a gene expression*BMIz interaction term. We then identified a list of top candidate genes (raw p<0.05) with differential expression by BMIz and assessed their functional significance using a pathway-centric approach. Results: We identified 157 down- and 258 up-regulated differentially expressed genes by BMIz. Pathway enrichment in severe asthma showed down-regulation of purinergic receptor pathways in children with lower BMIz, while DNA damage pathways were up-regulated in the higher BMIz group (Fig. 1). Conclusion: We found differential gene expression and implicated pathways for children with lower vs higher BMIz by asthma severity group, which could provide possible mechanisms underlying the obese-asthma phenotype. Larger studies are needed to validate this.

Background: Growing evidence indicates high comorbid anxiety and depression in patients with asthma. How-ever, the mechanisms underlying this comorbid condition remain unclear. The aim of this study was to inves-tigate the role of inflammation in comorbid anxiety and depression in three asthma patient cohorts of the Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes (U-BIOPRED) project.Methods: U-BIOPRED was conducted by a European Union consortium of 16 academic institutions in 11 European countries. A subset dataset from subjects with valid anxiety and depression measures and a large blood biomarker dataset were analysed, including 198 non-smoking patients with severe asthma (SAn), 65 smoking patients with severe asthma (SAs), 61 non-smoking patients with mild-to-moderate asthma (MMA), and 20 healthy non-smokers (HC). The Hospital Anxiety and Depression Scale was used to measure anxiety and depression and a series of inflammatory markers were analysed by the SomaScan v3 platform (SomaLogic, Boulder, Colo). ANOVA and the Kruskal-Wallis test were used for multiple-group comparisons as appropriate.Results: There were significant group effects on anxiety and depression among the four cohort groups (p < 0.05). Anxiety and depression of SAn and SAs groups were significantly higher than that of MMA and HC groups (p < 0.05. There were significant differences in serum IL6, MCP1, CCL18, CCL17, IL8, and Eotaxin among the four groups (p < 0.05). Depression was significantly associated with IL6, MCP1, CCL18 level, and CCL17; whereas anxiety was associated with CCL17 only (p < 0.05).Conclusions: The current study suggests that severe asthma patients are associated with higher levels of anxiety and depression, and inflammatory responses may underlie this comorbid condition.

Background: Asthma is a chronic respiratory disease with significant heterogeneity in its clinical presentation and pathobiology. There is need for improved understanding of respiratory lipid metabolism in asthma patients and its relation to observable clinical features.Objective: We performed a comprehensive, prospective, cross-sectional analysis of the lipid composition of induced sputum supernatant obtained from asthma patients with a range of disease severities, as well as from healthy controls.Methods: Induced sputum supernatant was collected from 211 adults with asthma and 41 healthy individuals enrolled onto the U-BIOPRED (Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes) study. Sputum lipidomes were characterized by semiquantitative shotgun mass spectrometry and clustered using topologic data analysis to identify lipid phenotypes.Results: Shotgun lipidomics of induced sputum supernatant revealed a spectrum of 9 molecular phenotypes, highlighting not just significant differences between the sputum lipidomes of asthma patients and healthy controls, but also within the asthma patient population. Matching clinical, pathobiologic, proteomic, and transcriptomic data helped inform the underlying disease processes. Sputum lipid phenotypes with higher levels of nonendogenous, cell-derived lipids were associated with significantly worse asthma severity, worse lung function, and elevated granulocyte counts.Conclusion: We propose a novel mechanism of increased lipid loading in the epithelial lining fluid of asthma patients resulting from the secretion of extracellular vesicles by granulocytic inflammatory cells, which could reduce the ability of pulmonary surfactant to lower surface tension in asthmatic small airways, as well as compromise its role as an immune regulator. (J Allergy Clin Immunol 2023;152:117-25.)

Asthma symptoms are often exacerbated by the common-cold-causing rhinovirus (RV). In this study, we characterized the temporal behavior of circulating exosomal microRNAs (ExoMiRNAs) in a longitudinal bi-phasic case-control study of mild asthmatics (n = 12) and matched non-atopic healthy controls (n = 12) inoculated with rhinovirus. We aimed to define clinical and immunologic characteristics associated with differentially expressed (DE) miRNAs. In total, 26 DE ExoMiRNAs, including hsa-let-7f-5p, hsa-let-7a-5p, hsa-miR-122-5p, hsa-miR-101-3p, and hsa-miR-126-3p, were identified between asthmatic and healthy subjects after inoculation with RV. Time series clustering identified a unique Cluster of Upregulated DE ExoMiRNAs with augmenting mean expression and a distinct Cluster of Downregulated DE ExoMiRNAs with mean expression decline in asthmatic subjects upon RV challenge. Notably, the Upregulated Cluster correlated with Th1 and interferon-induced cytokines/chemokines (IFN-γ and IFN-γ-inducible protein-10) and interleukin-10 (IL-10). Conversely, the Downregulated Cluster correlated with IL-13, a Th2 cytokine, pulmonary function measurements (FVC%, FEV1%, and PEF%), and inflammatory biomarkers (FeNO, eosinophil%, and neutrophil%). Key ExoMiRNA–target gene and anti-viral defense mechanisms of the Upregulated and Downregulated Clusters were identified by network and gene enrichment analyses. Our findings provide insight into the regulatory role of ExoMiRNAs in RV-induced asthma.

Rationale: There is a major unmet need for improving the care of children and adolescents with severe asthma and wheeze. Identifying factors contributing to disease severity may lead to improved diagnostics, biomarkers, or therapies. The airway microbiota may be such a key factor. Objectives: To compare the oropharyngeal airway microbiota of children and adolescents with severe and mild/moderate asthma/ wheeze. Methods: Oropharyngeal swab samples from school-age and preschool children in the European U-BIOPRED (Unbiased BIOmarkers in the PREDiction of respiratory disease outcomes) multicenter study of severe asthma, all receiving severityappropriate treatment, were examined using 16S ribosomal RNA gene sequencing. Bacterial taxa were defined as amplicon sequence variants. Results: We analyzed 241 samples from four cohorts: A) 86 school-age children with severe asthma; B) 39 school-age children with mild/moderate asthma; C) 65 preschool children with severe wheeze; and D) 51 preschool children with mild/moderate wheeze. The most common bacteria were Streptococcus (mean relative abundance, 33.5%), Veillonella (10.3%), Haemophilus (7.0%), Prevotella (5.9%), and Rothia (5.5%). Age group (school-age vs. preschool) was associated with the microbiota in b-diversity analysis (F = 3.32, P = 0.011) and in a differential abundance analysis (28 significant amplicon sequence variants). Among all children, we found no significant difference in the microbiota between children with severe and mild/moderate asthma/wheeze in univariable b-diversity analysis (F= 1.99, P = 0.08, N= 241), but a significant difference in amultivariable model (F = 2.66, P = 0.035), including the number of exacerbations in the previous year. Age was also significant when expressed as a microbial maturity score (Spearman Rho, 0.39; P= 4.6310210); however, this score was not associated with asthma/wheeze severity. Conclusions: There was a modest difference in the oropharyngeal airway microbiota between children with severe and mild/moderate asthma/wheeze across all children but not in individual age groups, and a strong association between the microbiota and age. This suggests the oropharyngeal airway microbiota as an interesting entity in studying asthma severity, but probably without the strength to serve as a biomarker for targeted intervention.