Cluster Analyses From the Real-World NOVELTY Study: Six Clusters Across the Asthma-COPD Spectrum

BACKGROUND

Asthma and chronic obstructive pulmonary disease (COPD) are complex diseases, the definitions of which overlap.

OBJECTIVE

To investigate clustering of clinical/physiological features and readily available biomarkers in patients with physician-assigned diagnoses of asthma and/or COPD in the NOVEL observational longiTudinal studY (NOVELTY; NCT02760329).

METHODS

Two approaches were taken to variable selection using baseline data: approach A was data-driven, hypothesis-free and used the Pearson dissimilarity matrix; approach B used an unsupervised Random Forest guided by clinical input. Cluster analyses were conducted across 100 random resamples using partitioning around medoids, followed by consensus clustering.

RESULTS

Approach A included 3796 individuals (mean age, 59.5 years; 54% female); approach B included 2934 patients (mean age, 60.7 years; 53% female). Each identified 6 mathematically stable clusters, which had overlapping characteristics. Overall, 67% to 75% of patients with asthma were in 3 clusters, and approximately 90% of patients with COPD were in 3 clusters. Although traditional features such as allergies and current/ex-smoking (respectively) were higher in these clusters, there were differences between clusters and approaches in features such as sex, ethnicity, breathlessness, frequent productive cough, and blood cell counts. The strongest predictors of the approach A cluster membership were age, weight, childhood onset, prebronchodilator FEV1, duration of dust/fume exposure, and number of daily medications.

CONCLUSIONS

Cluster analyses in patients from NOVELTY with asthma and/or COPD yielded identifiable clusters, with several discriminatory features that differed from conventional diagnostic characteristics. The overlap between clusters suggests that they do not reflect discrete underlying mechanisms and points to the need for identification of molecular endotypes and potential treatment targets across asthma and/or COPD.

Oropharyngeal Microbiota Clusters in Children with Asthma or Wheeze Associate with Allergy, Blood Transcriptomic Immune Pathways, and Exacerbation Risk

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 β-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-β (transforming growth factor-β) (highest in the Veillonella cluster) and Wnt/β-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.

Stratification of asthma by lipidomic profiling of induced sputum supernatant

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.

What bothers severe asthma patients most? A paired patient-clinician study across seven European countries

Introduction

Severe asthma is a complex, multidimensional disease. Optimal treatment, adherence and outcomes require shared decision-making, rooted in mutual understanding between patient and clinician. This study used a novel, patient-centred approach to examine the most bothersome aspects of severe asthma to patients, as seen from both perspectives in asthma registries.

Methods

Across seven countries, 126 patients with severe asthma completed an open-ended survey regarding most the bothersome aspect(s) of their asthma. Patients' responses were linked with their treating clinician who also completed a free-text survey about each patient's most bothersome aspect(s). Responses were coded using content analysis, and patient and clinician responses were compared. Finally, asthma registries that are part of the SHARP (Severe Heterogeneous Asthma Research collaboration, Patient-centred) Clinical Research Collaboration were examined to see the extent to which they reflected the most bothersome aspects reported by patients.

Results

88 codes and 10 themes were identified. Clinicians were more focused on direct physical symptoms and were less focused on "holistic" aspects such as the effort required to self-manage the disease. Clinicians accurately identified a most bothersome symptom for 29% of patients. Agreement was particularly low with younger patients and those using oral corticosteroids infrequently. In asthma registries, patient aspects were predominantly represented in questionnaires.

Conclusions

Results demonstrated different perspectives and priorities between patients and clinicians, with clinicians more focused on physical aspects. These differences must be considered when treating individual patients, and within multidisciplinary treatment teams. The use of questionnaires that include multifaceted aspects of disease may result in improved asthma research.

Evaluation of Real-World Mepolizumab Use in Severe Asthma across Europe - the SHARP experience with privacy-preserving federated analysis

Background

An objective of the Severe Heterogeneous Asthma Registry, Patient-centered (SHARP) is to produce real-world evidence on a pan-European scale by linking non-standardized, patient-level registry-data. Mepolizumab has shown clinical efficacy in RCTs and prospective real-world studies and could therefore serve as a proof of principle for this novel approach.

Aim

To harmonize data from 10 national severe asthma registries and characterize patients receiving mepolizumab, assess its effectiveness on annual exacerbations and maintenance oral glucocorticoid (OCS) use, and evaluate treatment patterns.

Methods

In this observational cohort study, registry data (5871 patients) were extracted for harmonization. Where harmonization was possible, patients who initiated mepolizumab between 1-1-2016 and 31-12-2021 were examined. Changes of a 12 (range 11–18) months period in frequent (≥2) exacerbations, maintenance OCS use and dose were analyzed in a privacy-preserving manner using meta-analysis of generalized estimating equation parameters. Periods before and during the COVID-19 pandemic were analyzed separately.

Results

In 912 patients who fulfilled selection criteria mepolizumab significantly reduced frequent exacerbations (OR;95%CI: 0.18;0.13–0.25), maintenance OCS use (OR;95%CI: 0.75;0.61–0.92) and dose (mean; 95%CI: −3.93 mg·day−1; −5.24–2.62) in the Pre-Pandemic group, with similar trends in the Pandemic group. Marked heterogeneity was observed between registries in patient characteristics and mepolizumab treatment patterns.

Conclusions

By harmonizing patient-level registry data and applying federated analysis, SHARP demonstrated the real-wold effectiveness of mepolizumab on asthma exacerbations and maintenance OCS use in severe asthma patients across Europe, consistent with previous evidence. This paves the way for future pan-European real-world severe asthma studies using patient-level data in a privacy-proof manner.

Bayesian network analysis of panomic biological big data identifies the importance of triglyceride-rich LDL in atherosclerosis development

Introduction

We sought to explore biomarkers of coronary atherosclerosis in an unbiased fashion.

Methods

We analyzed 665 patients (mean ± SD age, 56 ± 11 years; 47% male) from the GLOBAL clinical study (NCT01738828). Cases were defined by the presence of any discernable atherosclerotic plaque based on comprehensive cardiac computed tomography (CT). De novo Bayesian networks built out of 37,000 molecular measurements and 99 conventional biomarkers per patient examined the potential causality of specific biomarkers.

Results

Most highly ranked biomarkers by gradient boosting were interleukin-6, symmetric dimethylarginine, LDL-triglycerides [LDL-TG], apolipoprotein B48, palmitoleic acid, small dense LDL, alkaline phosphatase, and asymmetric dimethylarginine. In Bayesian analysis, LDL-TG was directly linked to atherosclerosis in over 95% of the ensembles. Genetic variants in the genomic region encoding hepatic lipase (LIPC) were associated with LIPC gene expression, LDL-TG levels and with atherosclerosis.

Discussion

Triglyceride-rich LDL particles, which can now be routinely measured with a direct homogenous assay, may play an important role in atherosclerosis development.

Clinical trial registration

GLOBAL clinical study (Genetic Loci and the Burden of Atherosclerotic Lesions); [https://clinicaltrials.gov/ct2/show/NCT01738828?term=NCT01738828&rank=1], identifier [NCT01738828].

Blueprint for harmonizing non-standardized disease registries to allow federated data analysis – prepare for the future

Real-world evidence from multinational disease registries is becoming increasingly important not only for confirming the results of randomised controlled trials, but also for identifying phenotypes, monitoring disease progression, predicting response to new drugs and early detection of rare side-effects. With new open-access technologies, it has become feasible to harmonise patient data from different disease registries and use it for data analysis without compromising privacy rules. Here, we provide a blueprint for how a clinical research collaboration can successfully use real-world data from existing disease registries to perform federated analyses. We describe how the European severe asthma clinical research collaboration SHARP (Severe Heterogeneous Asthma Research collaboration, Patient-centred) fulfilled the harmonisation process from nonstandardised clinical registry data to the Observational Medical Outcomes Partnership Common Data Model and built a strong network of collaborators from multiple disciplines and countries. The blueprint covers organisational, financial, conceptual, technical, analytical and research aspects, and discusses both the challenges and the lessons learned. All in all, setting up a federated data network is a complex process that requires thorough preparation, but above all, it is a worthwhile investment for all clinical research collaborations, especially in view of the emerging applications of artificial intelligence and federated learning.

Harmonising real-world patient data from diverse registries to allow federated analyses is a complex process that requires thorough preparation but is above all a valuable investment, especially in view of emerging applications of artificial intelligencehttps://bit.ly/3NEKKnV

Clinical and transcriptomic features of persistent exacerbation-prone severe asthma in U-BIOPRED cohort

Background

Exacerbation‐prone asthma is a feature of severe disease. However, the basis for its persistency remains unclear.

Objectives

To determine the clinical and transcriptomic features of frequent exacerbators (FEs) and persistent FEs (PFEs) in the U‐BIOPRED cohort.

Methods

We compared features of FE (≥2 exacerbations in past year) to infrequent exacerbators (IE, <2 exacerbations) and of PFE with repeat ≥2 exacerbations during the following year to persistent IE (PIE). Transcriptomic data in blood, bronchial and nasal epithelial brushings, bronchial biopsies and sputum cells were analysed by gene set variation analysis for 103 gene signatures.

Results

Of 317 patients, 62.4% had FE, of whom 63.6% had PFE, while 37.6% had IE, of whom 61.3% had PIE. Using multivariate analysis, FE was associated with short‐acting beta‐agonist use, sinusitis and daily oral corticosteroid use, while PFE was associated with eczema, short‐acting beta‐agonist use and asthma control index. CEA cell adhesion molecule 5 (CEACAM5) was the only differentially expressed transcript in bronchial biopsies between PE and IE. There were no differentially expressed genes in the other four compartments. There were higher expression scores for type 2, T‐helper type‐17 and type 1 pathway signatures together with those associated with viral infections in bronchial biopsies from FE compared to IE, while there were higher expression scores of type 2, type 1 and steroid insensitivity pathway signatures in bronchial biopsies of PFE compared to PIE.

Conclusion

The FE group and its PFE subgroup are associated with poor asthma control while expressing higher type 1 and type 2 activation pathways compared to IE and PIE, respectively.

Transgelin: A New Gene Involved in LDL Endocytosis Identified by a Genome-wide CRISPR-Cas9 Screen

A significant proportion of patients with elevated LDL and a clinical presentation of familial hypercholesterolemia do not carry known genetic mutations associated with hypercholesterolemia, such as defects in the LDL receptor. To identify new genes involved in the cellular uptake of LDL, we developed a novel whole-genome clustered regularly interspaced short palindromic repeat-Cas9 KO screen in HepG2 cells. We identified transgelin (TAGLN), an actin-binding protein, as a potentially new gene involved in LDL endocytosis. In silico validation demonstrated that genetically predicted differences in expression of TAGLN in human populations were significantly associated with elevated plasma lipids (triglycerides, total cholesterol, and LDL-C) in the Global Lipids Genetics Consortium and lipid-related phenotypes in the UK Biobank. In biochemical studies, TAGLN-KO HepG2 cells showed a reduction in cellular LDL uptake, as measured by flow cytometry. In confocal microscopy imaging, TAGLN-KO cells had disrupted actin filaments as well as an accumulation of LDL receptor on their surface because of decreased receptor internalization. Furthermore, TAGLN-KO cells exhibited a reduction in total and free cholesterol content, activation of SREBP2, and a compensatory increase in cholesterol biosynthesis. TAGLN deficiency also disrupted the uptake of VLDL and transferrin, other known cargoes for receptors that depend upon clathrin-mediated endocytosis. Our data suggest that TAGLN is a novel factor involved in the actin-dependent phase of clathrin-mediated endocytosis of LDL. The identification of novel genes involved in the endocytic uptake of LDL may improve the diagnosis of hypercholesterolemia and provide future therapeutic targets for the prevention of cardiovascular disease.

Heterogeneity within and between physician-diagnosed asthma and/or COPD: NOVELTY cohort

BACKGROUND

Studies of asthma and chronic obstructive pulmonary disease (COPD) typically focus on these diagnoses separately, limiting understanding of disease mechanisms and treatment options. NOVELTY is a global, 3-year, prospective observational study of patients with asthma and/or COPD from real-world clinical practice. We investigated heterogeneity and overlap by diagnosis and severity in this cohort.

METHODS

Patients with physician-assigned asthma, COPD or both (asthma+COPD) were enrolled, and stratified by diagnosis and severity. Baseline characteristics were reported descriptively by physician-assigned diagnosis and/or severity. Factors associated with physician-assessed severity were evaluated using ordinal logistic regression analysis.

RESULTS

Of 11 243 patients, 5940 (52.8%) had physician-assigned asthma, 1396 (12.4%) had asthma+COPD and 3907 (34.8%) had COPD; almost half were from primary care. Symptoms, health-related quality of life and spirometry showed substantial heterogeneity and overlap between asthma, asthma+COPD and COPD, with 23%, 62% and 64% of patients, respectively, having a ratio of post-bronchodilator forced expiratory volume in 1 s to forced vital capacity below the lower limit of normal. Symptoms and exacerbations increased with greater physician-assessed severity and were higher in asthma+COPD. However, 24.3% with mild asthma and 20.4% with mild COPD had experienced ≥1 exacerbation in the past 12 months. Medication records suggested both under-treatment and over-treatment relative to severity. Blood eosinophil counts varied little across diagnosis and severity groups, but blood neutrophil counts increased with severity across all diagnoses.

CONCLUSION

This analysis demonstrates marked heterogeneity within, and overlap between, physician-assigned diagnosis and severity groups in patients with asthma and/or COPD. Current diagnostic and severity classifications in clinical practice poorly differentiate between clinical phenotypes that may have specific risks and treatment implications.

Medication Adherence in Patients With Severe Asthma Prescribed Oral Corticosteroids in the U-BIOPRED Cohort

BACKGROUND

Although estimates of suboptimal adherence to oral corticosteroids in asthma range from 30% to 50%, no ideal method for measurement exists; the impact of poor adherence in severe asthma is likely to be particularly high.

RESEARCH QUESTIONS

What is the prevalence of suboptimal adherence detected by self-reporting and direct measures? Is suboptimal adherence associated with disease activity?

STUDY DESIGN AND METHODS

Data were included from individuals with severe asthma taking part in the U-BIOPRED (Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes) study and prescribed daily oral corticosteroids. Participants completed the Medication Adherence Report Scale, a five-item questionnaire used to grade adherence on a scale from 1 to 5, and provided a urine sample for analysis of prednisolone and metabolites by liquid chromatography-mass spectrometry.

RESULTS

Data from 166 participants were included in this study: mean (SD) age, 54.2 (± 11.9) years; FEV₁, 65.1% (± 20.5%) predicted; female, 58%; 37% completing the Medication Adherence Report Scale reported suboptimal adherence; and 43% with urinary corticosteroid data did not have detectable prednisolone or metabolites in their urine. Good adherence by both methods was detected in 49 of the 142 (35%) of participants in whom both methods were performed; adherence detection did not match between methods in 53%. Self-reported high adherers had better asthma control and quality of life, whereas directly measured high adherers had lower blood eosinophil levels.

INTERPRETATION

Low adherence is a common problem in severe asthma, whether measured directly or self-reported. We report poor agreement between the two methods, suggesting some disassociation between self-assessment of medication adherence and regular oral corticosteroid use, which suggests that each approach may provide complementary information in clinical practice.

Asthma similarities across ProAR (Brazil) and U-BIOPRED (Europe) adult cohorts of contrasting locations, ethnicity and socioeconomic status

BACKGROUND

Asthma prevalence is 339 million globally. 'Severe asthma' (SA) comprises subjects with uncontrolled asthma despite proper management.

OBJECTIVES

To compare asthma from diverse ethnicities and environments.

METHODS

A cross-sectional analysis of two adult cohorts, a Brazilian (ProAR) and a European (U-BIOPRED). U-BIOPRED comprised of 311 non-smoking with Severe Asthma (SAn), 110 smokers or ex-smokers with SA (SAs) and 88 mild to moderate asthmatics (MMA) while ProAR included 544 SA and 452 MMA. Although these projects were independent, there were similarities in objectives and methodology, with ProAR adopting operating procedures of U-BIOPRED.

RESULTS

Among SA subjects, age, weight, proportion of former smokers and FEV₁ pre-bronchodilator were similar. The proportion of SA with a positive skin prick tests (SPT) to aeroallergens, the scores of sino-nasal symptoms and quality of life were comparable. In addition, blood eosinophil counts (EOS) and the % of subjects with EOS > 300 cells/μl were not different. The Europeans with SA however, were more severe with a greater proportion of continuous oral corticosteroids (OCS), worse symptoms and more frequent exacerbations. FEV₁/FVC pre- and post-bronchodilator were lower among the Europeans. The MMA cohorts were less comparable in control and treatment, but similar in the proportion of allergic rhinitis, gastroesophageal reflux disease and EOS >3%.

CONCLUSIONS

ProAR and U-BIOPRED cohorts, with varying severity, ethnicity and environment have similarities, which provide the basis for global external validation of asthma phenotypes. This should stimulate collaboration between asthma consortia with the aim of understanding SA, which will lead to better management.

Genetic variation in FCER1A predicts peginterferon alfa-2a-induced hepatitis B surface antigen clearance in East Asian patients with chronic hepatitis B

In a multicentre, genome-wide association study to identify host genetic factors associated with treatment response in adult chronic hepatitis B patients, genotype data were obtained by microarray analysis from 1669 patients who received peginterferon alfa-2a for ≥ 24 weeks with/without a nucleos(t)ide analog. Treatment response was assessed at least 24 weeks post-treatment, using serological and/or virological endpoints. Thirty-six single-marker analyses and a gene-by-gene analysis were conducted. No single nucleotide polymorphisms (SNPs) achieved genome-wide significance (P < 5 × 10^-8 ) in single-marker analyses, but suggestive associations (P < 1 × 10^-5 ) were identified for 116 SNPs. In gene-by-gene analyses, one gene, FCER1A (rs7549785), reached genome-wide significance (P = 2.65 × 10^-8 ) in East Asian patients for hepatitis B surface antigen (HBsAg) clearance, with a moderate effect size (odds ratio = 4.74). Eleven of 44 carriers (25%) of the A allele at rs7549785 achieved HBsAg clearance compared with 69/1051 (7%) noncarriers. FCER1A encodes the alpha subunit of the immunoglobulin E receptor. In a post hoc analysis of a homogenous patient subset, the strongest intragenic association was for rs7712322 (POLR3G, P = 7.21 × 10^-7 ). POLR3G encodes the G subunit of the polymerase (RNA) III enzyme, involved in sensing and limiting infection by intracellular bacteria and DNA viruses, and as a DNA sensor in innate immune responses. FCER1A (rs7549785) and possibly POLR3G (rs7712322) are shown to be associated with peginterferon alfa-2a response in adult patients with chronic hepatitis B. Independent confirmation of these findings is warranted (clinicaltrials.gov number NCT01855997).

Stratification of asthma phenotypes by airway proteomic signatures

BACKGROUND

Stratification by eosinophil and neutrophil counts increases our understanding of asthma and helps target therapy, but there is room for improvement in our accuracy in prediction of treatment responses and a need for better understanding of the underlying mechanisms.

OBJECTIVE

We sought to identify molecular subphenotypes of asthma defined by proteomic signatures for improved stratification.

METHODS

Unbiased label-free quantitative mass spectrometry and topological data analysis were used to analyze the proteomes of sputum supernatants from 246 participants (206 asthmatic patients) as a novel means of asthma stratification. Microarray analysis of sputum cells provided transcriptomics data additionally to inform on underlying mechanisms.

RESULTS

Analysis of the sputum proteome resulted in 10 clusters (ie, proteotypes) based on similarity in proteomic features, representing discrete molecular subphenotypes of asthma. Overlaying granulocyte counts onto the 10 clusters as metadata further defined 3 of these as highly eosinophilic, 3 as highly neutrophilic, and 2 as highly atopic with relatively low granulocytic inflammation. For each of these 3 phenotypes, logistic regression analysis identified candidate protein biomarkers, and matched transcriptomic data pointed to differentially activated underlying mechanisms.

CONCLUSION

This study provides further stratification of asthma currently classified based on quantification of granulocytic inflammation and provided additional insight into their underlying mechanisms, which could become targets for novel therapies.

Sputum proteomic signature of gastro-oesophageal reflux in patients with severe asthma

Gastro-oesophageal reflux disease (GORD) has long been associated with poor asthma control without an established cause-effect relationship. 610 asthmatics (421 severe/88 mild-moderate) and 101 healthy controls were assessed clinically and a subset of 154 severe asthmatics underwent proteomic analysis of induced sputum using untargeted mass spectrometry, LC-IMS-MS^E. Univariate and multiple logistic regression analyses (MLR) were conducted to identify proteins associated with GORD in this cohort. When compared to mild/moderate asthmatics and healthy individuals, respectively, GORD was three- and ten-fold more prevalent in severe asthmatics and was associated with increased asthma symptoms and oral corticosteroid use, poorer quality of life, depression/anxiety, obesity and symptoms of sino-nasal disease. Comparison of sputum proteomes in severe asthmatics with and without active GORD showed five differentially abundant proteins with described roles in anti-microbial defences, systemic inflammation and epithelial integrity. Three of these were associated with active GORD by multiple linear regression analysis: Ig lambda variable 1-47 (p = 0·017) and plasma protease C1 inhibitor (p = 0·043), both in lower concentrations, and lipocalin-1 (p = 0·034) in higher concentrations in active GORD. This study provides evidence which suggests that reflux can cause subtle perturbation of proteins detectable in the airways lining fluid and that severe asthmatics with GORD may represent a distinct phenotype of asthma.

Prospective observational study in patients with obstructive lung disease: NOVELTY design

Asthma and chronic obstructive pulmonary disease (COPD) have overlapping clinical features and share pathobiological mechanisms but are often considered distinct disorders. Prospective, observational studies across asthma, COPD and asthma–COPD overlap are limited. NOVELTY is a global, prospective observational 3-year study enrolling ∼12 000 patients ≥12 years of age from primary and specialist clinical practices in 19 countries (ClinicalTrials.gov identifier: NCT02760329).

NOVELTY's primary objectives are to describe patient characteristics, treatment patterns and disease burden over time, and to identify phenotypes and molecular endotypes associated with differential outcomes over time in patients with a diagnosis/suspected diagnosis of asthma and/or COPD. NOVELTY aims to recruit real-world patients, unlike clinical studies with restrictive inclusion/exclusion criteria.

Data collected at yearly intervals include clinical assessments, spirometry, biospecimens, patient-reported outcomes (PROs) and healthcare utilisation (HCU). PROs and HCU will also be collected 3-monthly via internet/telephone. Data will be used to identify phenotypes and endotypes associated with different trajectories for symptom burden, clinical progression or remission and HCU. Results may allow patient classification across obstructive lung disease by clinical outcomes and biomarker profile, rather than by conventional diagnostic labels and severity categories.

NOVELTY will provide a rich data source on obstructive lung disease, to help improve patient outcomes and aid novel drug development.

NOVELTY is a global study to characterise patients with asthma and/or COPD and identify novel phenotypes and endotypeshttp://ow.ly/QFiH30n3IBF

Identification and prospective stability of electronic nose (eNose)-derived inflammatory phenotypes in patients with severe asthma

BACKGROUND

Severe asthma is a heterogeneous condition, as shown by independent cluster analyses based on demographic, clinical, and inflammatory characteristics. A next step is to identify molecularly driven phenotypes using "omics" technologies. Molecular fingerprints of exhaled breath are associated with inflammation and can qualify as noninvasive assessment of severe asthma phenotypes.

OBJECTIVES

We aimed (1) to identify severe asthma phenotypes using exhaled metabolomic fingerprints obtained from a composite of electronic noses (eNoses) and (2) to assess the stability of eNose-derived phenotypes in relation to within-patient clinical and inflammatory changes.

METHODS

In this longitudinal multicenter study exhaled breath samples were taken from an unselected subset of adults with severe asthma from the U-BIOPRED cohort. Exhaled metabolites were analyzed centrally by using an assembly of eNoses. Unsupervised Ward clustering enhanced by similarity profile analysis together with K-means clustering was performed. For internal validation, partitioning around medoids and topological data analysis were applied. Samples at 12 to 18 months of prospective follow-up were used to assess longitudinal within-patient stability.

RESULTS

Data were available for 78 subjects (age, 55 years [interquartile range, 45-64 years]; 41% male). Three eNose-driven clusters (n = 26/33/19) were revealed, showing differences in circulating eosinophil (P = .045) and neutrophil (P = .017) percentages and ratios of patients using oral corticosteroids (P = .035). Longitudinal within-patient cluster stability was associated with changes in sputum eosinophil percentages (P = .045).

CONCLUSIONS

We have identified and followed up exhaled molecular phenotypes of severe asthma, which were associated with changing inflammatory profile and oral steroid use. This suggests that breath analysis can contribute to the management of severe asthma.

Enhanced oxidative stress in smoking and ex-smoking severe asthma in the U-BIOPRED cohort

Oxidative stress is believed to be a major driver of inflammation in smoking asthmatics. The U-BIOPRED project recruited a cohort of Severe Asthma smokers/ex-smokers (SAs/ex) and non-smokers (SAn) with extensive clinical and biomarker information enabling characterization of these subjects. We investigated oxidative stress in severe asthma subjects by analysing urinary 8-iso-PGF2α and the mRNA-expression of the main pro-oxidant (NOX2; NOSs) and anti-oxidant (SODs; CAT; GPX1) enzymes in the airways of SAs/ex and SAn. All the severe asthma U-BIOPRED subjects were further divided into current smokers with severe asthma (CSA), ex-smokers with severe asthma (ESA) and non-smokers with severe asthma (NSA) to deepen the effect of active smoking. Clinical data, urine and sputum were obtained from severe asthma subjects. A bronchoscopy to obtain bronchial biopsy and brushing was performed in a subset of subjects. The main clinical data were analysed for each subset of subjects (urine-8-iso-PGF2α; IS-transcriptomics; BB-transcriptomics; BBr-transcriptomics). Urinary 8-iso-PGF2α was quantified using mass spectrometry. Sputum, bronchial biopsy and bronchial brushing were processed for mRNA expression microarray analysis. Urinary 8-iso-PGF2α was increased in SAs/ex, median (IQR) = 31.7 (24.5-44.7) ng/mmol creatinine, compared to SAn, median (IQR) = 26.6 (19.6-36.6) ng/mmol creatinine (p< 0.001), and in CSA, median (IQR) = 34.25 (24.4-47.7), vs. ESA, median (IQR) = 29.4 (22.3-40.5), and NSA, median (IQR) = 26.5 (19.6-16.6) ng/mmol creatinine (p = 0.004). Sputum mRNA expression of NOX2 was increased in SAs/ex compared to SAn (probe sets 203922_PM_s_at fold-change = 1.05 p = 0.006; 203923_PM_s_at fold-change = 1.06, p = 0.003; 233538_PM_s_at fold-change = 1.06, p = 0.014). The mRNA expression of antioxidant enzymes were similar between the two severe asthma cohorts in all airway samples. NOS2 mRNA expression was decreased in bronchial brushing of SAs/ex compared to SAn (fold-change = -1.10; p = 0.029). NOS2 mRNA expression in bronchial brushing correlated with FeNO (Kendal's Tau = 0.535; p< 0.001). From clinical and inflammatory analysis, FeNO was lower in CSA than in ESA in all the analysed subject subsets (p< 0.01) indicating an effect of active smoking. Results about FeNO suggest its clinical limitation, as inflammation biomarker, in severe asthma active smokers. These data provide evidence of greater systemic oxidative stress in severe asthma smokers as reflected by a significant changes of NOX2 mRNA expression in the airways, together with elevated urinary 8-iso-PGF2α in the smokers/ex-smokers group. Trial registration ClinicalTrials.gov-Identifier: NCT01976767.

Lipid phenotyping of lung epithelial lining fluid in healthy human volunteers

BACKGROUND

Lung epithelial lining fluid (ELF)-sampled through sputum induction-is a medium rich in cells, proteins and lipids. However, despite its key role in maintaining lung function, homeostasis and defences, the composition and biology of ELF, especially in respect of lipids, remain incompletely understood.

OBJECTIVES

To characterise the induced sputum lipidome of healthy adult individuals, and to examine associations between different ELF lipid phenotypes and the demographic characteristics within the study cohort.

METHODS

Induced sputum samples were obtained from 41 healthy non-smoking adults, and their lipid compositions analysed using a combination of untargeted shotgun and liquid chromatography mass spectrometry methods. Topological data analysis (TDA) was used to group subjects with comparable sputum lipidomes in order to identify distinct ELF phenotypes.

RESULTS

The induced sputum lipidome was diverse, comprising a range of different molecular classes, including at least 75 glycerophospholipids, 13 sphingolipids, 5 sterol lipids and 12 neutral glycerolipids. TDA identified two distinct phenotypes differentiated by a higher total lipid content and specific enrichments of diacyl-glycerophosphocholines, -inositols and -glycerols in one group, with enrichments of sterols, glycolipids and sphingolipids in the other. Subjects presenting the lipid-rich ELF phenotype also had significantly higher BMI, but did not differ in respect of other demographic characteristics such as age or gender.

CONCLUSIONS

We provide the first evidence that the ELF lipidome varies significantly between healthy individuals and propose that such differences are related to weight status, highlighting the potential impact of (over)nutrition on lung lipid metabolism.

A computational framework for complex disease stratification from multiple large-scale datasets

BACKGROUND

Multilevel data integration is becoming a major area of research in systems biology. Within this area, multi-'omics datasets on complex diseases are becoming more readily available and there is a need to set standards and good practices for integrated analysis of biological, clinical and environmental data. We present a framework to plan and generate single and multi-'omics signatures of disease states.

METHODS

The framework is divided into four major steps: dataset subsetting, feature filtering, 'omics-based clustering and biomarker identification.

RESULTS

We illustrate the usefulness of this framework by identifying potential patient clusters based on integrated multi-'omics signatures in a publicly available ovarian cystadenocarcinoma dataset. The analysis generated a higher number of stable and clinically relevant clusters than previously reported, and enabled the generation of predictive models of patient outcomes.

CONCLUSIONS

This framework will help health researchers plan and perform multi-'omics big data analyses to generate hypotheses and make sense of their rich, diverse and ever growing datasets, to enable implementation of translational P4 medicine.

Transcriptomic gene signatures associated with persistent airflow limitation in patients with severe asthma

A proportion of severe asthma patients suffers from persistent airflow limitation (PAL), often associated with more symptoms and exacerbations. Little is known about the underlying mechanisms. Here, our aim was to discover unexplored potential mechanisms using Gene Set Variation Analysis (GSVA), a sensitive technique that can detect underlying pathways in heterogeneous samples.Severe asthma patients from the U-BIOPRED cohort with PAL (post-bronchodilator forced expiratory volume in 1 s/forced vital capacity ratio below the lower limit of normal) were compared with those without PAL. Gene expression was assessed on the total RNA of sputum cells, nasal brushings, and endobronchial brushings and biopsies. GSVA was applied to identify differentially enriched predefined gene signatures based on all available gene expression publications and data on airways disease.Differentially enriched gene signatures were identified in nasal brushings (n=1), sputum (n=9), bronchial brushings (n=1) and bronchial biopsies (n=4) that were associated with response to inhaled steroids, eosinophils, interleukin-13, interferon-α, specific CD4⁺ T-cells and airway remodelling.PAL in severe asthma has distinguishable underlying gene networks that are associated with treatment, inflammatory pathways and airway remodelling. These findings point towards targets for the therapy of PAL in severe asthma.

Severe asthma exists despite suppressed tissue inflammation: findings of the U-BIOPRED study

The U-BIOPRED study is a multicentre European study aimed at a better understanding of severe asthma. It included three steroid-treated adult asthma groups (severe nonsmokers (SAn group), severe current/ex-smokers (SAs/ex group) and those with mild-moderate disease (MMA group)) and healthy controls (HC group). The aim of this cross-sectional, bronchoscopy substudy was to compare bronchial immunopathology between these groups.In 158 participants, bronchial biopsies and bronchial epithelial brushings were collected for immunopathologic and transcriptomic analysis. Immunohistochemical analysis of glycol methacrylate resin-embedded biopsies showed there were more mast cells in submucosa of the HC group (33.6 mm^-2) compared with both severe asthma groups (SAn: 17.4 mm^-2, p<0.001; SAs/ex: 22.2 mm^-2, p=0.01) and with the MMA group (21.2 mm^-2, p=0.01). The number of CD4⁺ lymphocytes was decreased in the SAs/ex group (4.7 mm^-2) compared with the SAn (11.6 mm^-2, p=0.002), MMA (10.1 mm^-2, p=0.008) and HC (10.6 mm^-2, p<0.001) groups. No other differences were observed.Affymetrix microarray analysis identified seven probe sets in the bronchial brushing samples that had a positive relationship with submucosal eosinophils. These mapped to COX-2 (cyclo-oxygenase-2), ADAM-7 (disintegrin and metalloproteinase domain-containing protein 7), SLCO1A2 (solute carrier organic anion transporter family member 1A2), TMEFF2 (transmembrane protein with epidermal growth factor like and two follistatin like domains 2) and TRPM-1 (transient receptor potential cation channel subfamily M member 1); the remaining two are unnamed.We conclude that in nonsmoking and smoking patients on currently recommended therapy, severe asthma exists despite suppressed tissue inflammation within the proximal airway wall.

Raman Spectroscopic Analysis of Fingernail Clippings Can Help Differentiate Between Postmenopausal Women Who Have and Have Not Suffered a Fracture

Raman spectroscopy was applied to nail clippings from 633 postmenopausal British and Irish women, from six clinical sites, of whom 42% had experienced a fragility fracture. The objective was to build a prediction algorithm for fracture using data from four sites (known as the calibration set) and test its performance using data from the other two sites (known as the validation set). Results from the validation set showed that a novel algorithm, combining spectroscopy data with clinical data, provided area under the curve (AUC) of 74% compared to an AUC of 60% from a reduced QFracture score (a clinically accepted risk calculator) and 61% from the dual-energy X-ray absorptiometry T-score, which is in current use for the diagnosis of osteoporosis. Raman spectroscopy should be investigated further as a noninvasive tool for the early detection of enhanced risk of fragility fracture.

The burden of severe asthma in childhood and adolescence: results from the paediatric U-BIOPRED cohorts

U-BIOPRED aims to characterise paediatric and adult severe asthma using conventional and innovative systems biology approaches. A total of 99 school-age children with severe asthma and 81 preschoolers with severe wheeze were compared with 49 school-age children with mild/moderate asthma and 53 preschoolers with mild/moderate wheeze in a cross-sectional study. Despite high-dose treatment, the severe cohorts had more severe exacerbations compared with the mild/moderate ones (annual medians: school-aged 3.0 versus 1.1, preschool 3.9 versus 1.8; p<0.001). Exhaled tobacco exposure was common in the severe wheeze cohort. Almost all participants in each cohort were atopic and had a normal body mass index. Asthma-related quality of life, as assessed by the Paediatric Asthma Quality of Life Questionnaire (PAQLQ) and the Paediatric Asthma Caregiver's Quality of Life Questionnaire (PACQLQ), was worse in the severe cohorts (mean±se school-age PAQLQ: 4.77±0.15 versus 5.80±0.19; preschool PACQLQ: 4.27±0.18 versus 6.04±0.18; both p≤0.001); however, mild/moderate cohorts also had significant morbidity. Impaired quality of life was associated with poor control and airway obstruction. Otherwise, the severe and mild/moderate cohorts were clinically very similar. Children with severe preschool wheeze or severe asthma are usually atopic and have impaired quality of life that is associated with poor control and airflow limitation: a very different phenotype from adult severe asthma. In-depth phenotyping of these children, integrating clinical data with high-dimensional biomarkers, may help to improve and tailor their clinical management.

Clinical and inflammatory characteristics of the European U-BIOPRED adult severe asthma cohort

U-BIOPRED is a European Union consortium of 20 academic institutions, 11 pharmaceutical companies and six patient organisations with the objective of improving the understanding of asthma disease mechanisms using a systems biology approach.This cross-sectional assessment of adults with severe asthma, mild/moderate asthma and healthy controls from 11 European countries consisted of analyses of patient-reported outcomes, lung function, blood and airway inflammatory measurements.Patients with severe asthma (nonsmokers, n=311; smokers/ex-smokers, n=110) had more symptoms and exacerbations compared to patients with mild/moderate disease (n=88) (2.5 exacerbations versus 0.4 in the preceding 12 months; p<0.001), with worse quality of life, and higher levels of anxiety and depression. They also had a higher incidence of nasal polyps and gastro-oesophageal reflux with lower lung function. Sputum eosinophil count was higher in severe asthma compared to mild/moderate asthma (median count 2.99% versus 1.05%; p=0.004) despite treatment with higher doses of inhaled and/or oral corticosteroids.Consistent with other severe asthma cohorts, U-BIOPRED is characterised by poor symptom control, increased comorbidity and airway inflammation, despite high levels of treatment. It is well suited to identify asthma phenotypes using the array of "omic" datasets that are at the core of this systems medicine approach.

Precision phenotyping, panomics, and system-level bioinformatics to delineate complex biologies of atherosclerosis: rationale and design of the "Genetic Loci and the Burden of Atherosclerotic Lesions" study

BACKGROUND

Complex biological networks of atherosclerosis are largely unknown.

OBJECTIVE

The main objective of the Genetic Loci and the Burden of Atherosclerotic Lesions study is to assemble comprehensive biological networks of atherosclerosis using advanced cardiovascular imaging for phenotyping, a panomic approach to identify underlying genomic, proteomic, metabolomic, and lipidomic underpinnings, analyzed by systems biology-driven bioinformatics.

METHODS

By design, this is a hypothesis-free unbiased discovery study collecting a large number of biologically related factors to examine biological associations between genomic, proteomic, metabolomic, lipidomic, and phenotypic factors of atherosclerosis. The Genetic Loci and the Burden of Atherosclerotic Lesions study (NCT01738828) is a prospective, multicenter, international observational study of atherosclerotic coronary artery disease. Approximately 7500 patients are enrolled and undergo non-contrast-enhanced coronary calcium scanning by CT for the detection and quantification of coronary artery calcium, as well as coronary artery CT angiography for the detection and quantification of plaque, stenosis, and overall coronary artery disease burden. In addition, patients undergo whole genome sequencing, DNA methylation, whole blood-based transcriptome sequencing, unbiased proteomics based on mass spectrometry, as well as metabolomics and lipidomics on a mass spectrometry platform. The study is analyzed in 3 subsequent phases, and each phase consists of a discovery cohort and an independent validation cohort. For the primary analysis, the primary phenotype will be the presence of any atherosclerotic plaque, as detected by cardiac CT. Additional phenotypic analyses will include per patient maximal luminal stenosis defined as 50% and 70% diameter stenosis. Single-omic and multi-omic associations will be examined for each phenotype; putative biomarkers will be assessed for association, calibration, discrimination, and reclassification.

Genetic variability of VEGF pathway genes in six randomized phase III trials assessing the addition of bevacizumab to standard therapy

BACKGROUND

Despite extensive translational research, no validated biomarkers predictive of bevacizumab treatment outcome have been identified.

METHODS

We performed a meta-analysis of individual patient data from six randomized phase III trials in colorectal, pancreatic, lung, renal, breast, and gastric cancer to explore the potential relationships between 195 common genetic variants in the vascular endothelial growth factor (VEGF) pathway and bevacizumab treatment outcome.

RESULTS

The analysis included 1,402 patients (716 bevacizumab-treated and 686 placebo-treated). Twenty variants were associated (P < 0.05) with progression-free survival (PFS) in bevacizumab-treated patients. Of these, 4 variants in EPAS1 survived correction for multiple testing (q < 0.05). Genotype-by-treatment interaction tests revealed that, across these 20 variants, 3 variants in VEGF-C (rs12510099), EPAS1 (rs4953344), and IL8RA (rs2234671) were potentially predictive (P < 0.05), but not resistant to multiple testing (q > 0.05). A weak genotype-by-treatment interaction effect was also observed for rs699946 in VEGF-A, whereas Bayesian genewise analysis revealed that genetic variability in VHL was associated with PFS in the bevacizumab arm (q < 0.05). Variants in VEGF-A, EPAS1, and VHL were located in expression quantitative loci derived from lymphoblastoid cell lines, indicating that they affect the expression levels of their respective gene.

CONCLUSIONS

This large genetic analysis suggests that variants in VEGF-A, EPAS1, IL8RA, VHL, and VEGF-C have potential value in predicting bevacizumab treatment outcome across tumor types. Although these associations did not survive correction for multiple testing in a genotype-by-interaction analysis, they are among the strongest predictive effects reported to date for genetic variants and bevacizumab efficacy.

Inclusion of genotype with fundus phenotype improves accuracy of predicting choroidal neovascularization and geographic atrophy

PURPOSE

The accuracy of predicting conversion from early-stage age-related macular degeneration (AMD) to the advanced stages of choroidal neovascularization (CNV) or geographic atrophy (GA) was evaluated to determine whether inclusion of clinically relevant genetic markers improved accuracy beyond prediction using phenotypic risk factors alone.

DESIGN

Cohort study.

PARTICIPANTS

White, non-Hispanic subjects participating in the Age-Related Eye Disease Study (AREDS) sponsored by the National Eye Institute consented to provide a genetic specimen. Of 2415 DNA specimens available, 940 were from disease-free subjects and 1475 were from subjects with early or intermediate AMD.

METHODS

DNA specimens from study subjects were genotyped for 14 single nucleotide polymorphisms (SNPs) in genes shown previously to associate with CNV: ARMS2, CFH, C3, C2, FB, CFHR4, CFHR5, and F13B. Clinical demographics and established disease associations, including age, sex, smoking status, body mass index (BMI), AREDS treatment category, and educational level, were evaluated. Four multivariate logistic models (phenotype; genotype; phenotype + genotype; and phenotype + genotype + demographic + environmental factors) were tested using 2 end points (CNV, GA). Models were fitted using Cox proportional hazards regression to use time-to-disease onset data.

MAIN OUTCOME MEASURES

Brier score (measure of accuracy) was used to identify the model with the lowest prediction error in the training set. The most accurate model was subjected to independent statistical validation, and final model performance was described using area under the receiver operator curve (AUC) or C-statistic.

RESULTS

The CNV prediction models that combined genotype with phenotype with or without age and smoking revealed superior performance (C-statistic = 0.96) compared with the phenotype model based on the simplified severity scale and the presence of CNV in the nonstudy eye (C-statistic = 0.89; P<0.01). For GA, the model that combined genotype with phenotype demonstrated the highest performance (AUC = 0.94). Smoking status and ARMS2 genotype had less of an impact on the prediction of GA compared with CNV.

CONCLUSIONS

Inclusion of genotype assessment improves CNV prediction beyond that achievable with phenotype alone and may improve patient management. Separate assessments should be used to predict progression to CNV and GA because genetic markers and smoking status do not equally predict both end points.

FINANCIAL DISCLOSURE(S)

Proprietary or commercial disclosure may be found after the references.

First all-in-one diagnostic tool for DNA intelligence: genome-wide inference of biogeographic ancestry, appearance, relatedness, and sex with the Identitas v1 Forensic Chip

When a forensic DNA sample cannot be associated directly with a previously genotyped reference sample by standard short tandem repeat profiling, the investigation required for identifying perpetrators, victims, or missing persons can be both costly and time consuming. Here, we describe the outcome of a collaborative study using the Identitas Version 1 (v1) Forensic Chip, the first commercially available all-in-one tool dedicated to the concept of developing intelligence leads based on DNA. The chip allows parallel interrogation of 201,173 genome-wide autosomal, X-chromosomal, Y-chromosomal, and mitochondrial single nucleotide polymorphisms for inference of biogeographic ancestry, appearance, relatedness, and sex. The first assessment of the chip’s performance was carried out on 3,196 blinded DNA samples of varying quantities and qualities, covering a wide range of biogeographic origin and eye/hair coloration as well as variation in relatedness and sex. Overall, 95 % of the samples (N = 3,034) passed quality checks with an overall genotype call rate >90 % on variable numbers of available recorded trait information. Predictions of sex, direct match, and first to third degree relatedness were highly accurate. Chip-based predictions of biparental continental ancestry were on average ~94 % correct (further support provided by separately inferred patrilineal and matrilineal ancestry). Predictions of eye color were 85 % correct for brown and 70 % correct for blue eyes, and predictions of hair color were 72 % for brown, 63 % for blond, 58 % for black, and 48 % for red hair. From the 5 % of samples (N = 162) with <90 % call rate, 56 % yielded correct continental ancestry predictions while 7 % yielded sufficient genotypes to allow hair and eye color prediction. Our results demonstrate that the Identitas v1 Forensic Chip holds great promise for a wide range of applications including criminal investigations, missing person investigations, and for national security purposes.

Novel genetic variants associated with lumbar disc degeneration in northern Europeans: a meta-analysis of 4600 subjects

OBJECTIVE

Lumbar disc degeneration (LDD) is an important cause of low back pain, which is a common and costly problem. LDD is characterised by disc space narrowing and osteophyte growth at the circumference of the disc. To date, the agnostic search of the genome by genome-wide association (GWA) to identify common variants associated with LDD has not been fruitful. This study is the first GWA meta-analysis of LDD.

METHODS

We have developed a continuous trait based on disc space narrowing and osteophytes growth which is measurable on all forms of imaging (plain radiograph, CT scan and MRI) and performed a meta-analysis of five cohorts of Northern European extraction each having GWA data imputed to HapMap V.2.

RESULTS

This study of 4600 individuals identified four single nucleotide polymorphisms with p<5×10(-8), the threshold set for genome-wide significance. We identified a variant in the PARK2 gene (p=2.8×10(-8)) associated with LDD. Differential methylation at one CpG island of the PARK2 promoter was observed in a small subset of subjects (β=8.74×10(-4), p=0.006).

CONCLUSIONS

LDD accounts for a considerable proportion of low back pain and the pathogenesis of LDD is poorly understood. This work provides evidence of association of the PARK2 gene and suggests that methylation of the PARK2 promoter may influence degeneration of the intervertebral disc. This gene has not previously been considered a candidate in LDD and further functional work is needed on this hitherto unsuspected pathway.

Genetic association of the major histocompatibility complex with rheumatoid arthritis implicates two non-DRB1 loci

OBJECTIVE

The HLA-DRB1 locus within the major histocompatibility complex (MHC) at 6p21.3 has been identified as a susceptibility gene for rheumatoid arthritis (RA); however, there is increasing evidence of additional susceptibility genes in the MHC region. The aim of this study was to estimate their number and location.

METHODS

A case-control study was performed involving 977 control subjects and 855 RA patients. The HLA-DRB1 locus was genotyped together with 2,360 single-nucleotide polymorphisms in the MHC region. Logistic regression was used to detect DRB1-independent effects.

RESULTS

After adjusting for the effect of HLA-DRB1, 18 markers in 14 genes were strongly associated with RA (P<10(-4)). Multivariate logistic regression analysis of these markers and DRB1 led to a model containing DRB1 plus the following 3 markers: rs4678, a nonsynonymous change in the VARS2L locus, approximately 1.7 Mb telomeric of DRB1; rs2442728, upstream of HLA-B, approximately 1.2 Mb telomeric of DRB1; and rs17499655, located in the 5'-untranslated region of DQA2, only 0.1 Mb centromeric of DRB1. In-depth investigation of the DQA2 association, however, suggested that it arose through cryptic linkage disequilibrium with an allele of DRB1. Two non-shared epitope alleles were also strongly associated with RA (P<10(-4)): *0301 with anti- cyclic citrullinated peptide-negative RA and *0701 independently of autoantibody status.

CONCLUSION

These results confirm the polygenic contribution of the MHC to RA and implicate 2 additional non-DRB1 susceptibility loci. The role of the HLA-DQ locus in RA has been a subject of controversy, but in our data, it appears to be spurious.

Genomics in drug discovery: the best things come to those who wait

The year 2007 has been marked by the maturation of high-throughput technologies that combine automation and miniaturization to enable systematic surveys of genome sequence variation, gene expression and gene function. These technologies have the potential to affect drug discovery in many ways, from target identification and validation, to pinpointing the molecular variants that influence medicine response. In the current climate of declining pharmaceutical R&D productivity, these approaches offer hope, but a price tag is attached. This review covers exciting advances in the field of genomics, and discusses when to act on genomic data versus when to wait for further information.

Use of pairwise marker combination and recursive partitioning in a pharmacogenetic genome-wide scan

The objective of pharmacogenetic research is to identify a genetic marker, or a set of genetic markers, that can predict how a given person will respond to a given medicine. To search for such marker combinations that are predictive of adverse drug events, we have developed and applied two complementary methods to a pharmacogenetic study of the hypersensitivity reaction (HSR) associated with treatment with abacavir, a medicine that is used to treat HIV-infected patients. Our results show that both of these methods can be used to uncover potentially useful predictive marker combinations. The pairwise marker combination method yielded a collection of marker pairs that featured a spectrum of sensitivities and specificities. Recursive partitioning results led to the genetic delineation of multiple risk categories, including those with extremely high and extremely low risk of HSR. These methods can be readily applied in pharmacogenetic candidate gene studies as well as in genome-wide scans.

Association of genetic variations in HLA-B region with hypersensitivity to abacavir in some, but not all, populations

Abacavir is an effective antiretroviral drug used to treat HIV-1 infection. Approximately 5% of patients treated with abacavir develop a hypersensitivity reaction that requires discontinuation of the drug. In an initial pharmacogenetic study conducted in a predominantly White male population, multiple markers in the human leukocyte antigen (HLA)-B chromosomal region were associated with hypersensitivity to abacavir. The HLA-B*5701 association has now been confirmed in White males in a subsequent, larger study (n=293, p=4.7 x 10(-18)) and is also observed in White females (n=56, p=6.8 x 10(-6)) and Hispanics (n=104, p=2.1 x 10(-4)). HLA-B*5701 was not associated with hypersensitivity in Blacks (n=78, p=0.27). HLA-B*5701 alone lacks sufficient predictive value to identify patients at risk for hypersensitivity to abacavir across diverse patient populations. Efforts are ongoing to identify markers with sufficient sensitivity and specificity to be clinically useful. Even after a marker set is identified, appropriate clinical identification and management of hypersensitivity to abacavir must remain the cornerstone of clinical practice.