Browsing by Author "Malinovschi, Andrei"
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- Comparison of hypothesis- and data-driven asthma phenotypes in NHANES 2007–2012: the importance of comprehensive data availabilityPublication . Amaral, Rita; Pereira, Ana M.; Jacinto, Tiago; Malinovschi, Andrei; Janson, Christer; Alving, Kjell; Fonseca, João A.Half of the adults with current asthma among the US National Health and Nutrition Examination Survey (NHANES) participants could be classified in more than one hypothesis-driven phenotype. A data-driven approach applied to the same subjects may allow a more useful classification compared to the hypothesis-driven one. To compare previously defined hypothesis-driven with newly derived data-driven asthma phenotypes, identified by latent class analysis (LCA), in adults with current asthma from NHANES 2007–2012. Adults (≥ 18 years) with current asthma from the NHANES were included (n = 1059). LCA included variables commonly used to subdivide asthma. LCA models were derived independently according to age groups: < 40 and ≥ 40 years old. Two data-driven phenotypes were identified among adults with current asthma, for both age groups. The proportions of the hypothesis-driven phenotypes were similar among the two data-driven phenotypes (p > 0.05). Class A < 40 years (n = 285; 75%) and Class A ≥ 40 years (n = 462; 73%), respectively, were characterized by a predominance of highly symptomatic asthma subjects with poor lung function, compared to Class B < 40 years (n = 94; 25%) and Class B ≥ 40 years (n = 170; 27%). Inflammatory biomarkers, smoking status, presence of obesity and hay fever did not markedly differ between the phenotypes. Both data- and hypothesis-driven approaches using clinical and physiological variables commonly used to characterize asthma are suboptimal to identify asthma phenotypes among adults from the general population. Further studies based on more comprehensive disease features are required to identify asthma phenotypes in population-based studies.
- Differential effect of cigarette smoke exposure on exhaled nitric oxide and blood eosinophils in healthy and asthmatic individualsPublication . Jacinto, Tiago; Malinovschi, Andrei; Janson, Christer; Fonseca, João; Alving, KjellTobacco smoking affects both the fraction of exhaled nitric oxide (FeNO) and blood eosinophil (B-Eos) count, two clinically useful biomarkers in respiratory disease that represent local and systemic type-2 inflammation, respectively. We aimed to study the influence of objectively measured smoke exposure on FeNO and B-Eos in a large population of subjects with and without asthma. Methods: We utilized the US National Health and Nutrition Examination Surveys 2007–2012 and included 10 669 subjects aged 6–80 years: 9869 controls and 800 asthmatics. Controls were defined as having no respiratory disease, no hay fever in the past year, and B-Eos count ≤0.3 × 109 l−1. Asthma was defined as self-reported current asthma and at least one episode of wheezing or an asthma attack in the past year, but no emphysema or chronic bronchitis. Tobacco use was collected via questionnaires and serum cotinine was measured with mass spectrometry. Increasing cotinine levels were associated with a progressive reduction in FeNO in both controls and asthmatics. FeNO remained significantly higher in asthmatics than controls except in the highest cotinine decile, equivalent to an average reported consumption of 13 cigarettes/day. B-Eos count increased with cotinine in controls, but was unchanging in asthmatics. Interestingly, B-Eos count was significantly higher in presently non-exposed (cotinine below detection limit) former smokers than never smokers. Smoke exposure decreases FeNO and increases B-Eos count. These effects should be considered in the development of normalized values and their interpretation in clinical practice. The persistence of elevated B-Eos in former smokers warrants further studies.
- Exhaled NO reference limits in a large population-based sample using the Lambda-Mu-Sigma methodPublication . Jacinto, Tiago; Amaral, Rita; Malinovschi, Andrei; Janson, Christer; Fonseca, João; Alving, KjellAbsolute values are used in the interpretation of the fraction of exhaled nitric oxide (FeNO), but it has been suggested that equations to calculate reference values may be a practical and clinically useful approach. We hypothesize that the application of the Lambda-Mu-Sigma (LMS) method may improve FeNO reference equations and their interpretation. Our aims were to develop FeNO reference equations with the LMS method and to describe the difference between this method and the absolute fixed cut-offs of the current recommendations. We utilized the United States National Health and Nutrition Examination Surveys 2007-2012 and included healthy individuals with no respiratory diseases and blood eosinophils <300/mm3 ( n = 8,340). Natural log-transformed FeNO was modeled using the LMS method, imbedded in the generalized additive models for location, scale, and shape models. A set of FeNO reference equations was developed. The explanatory variables were sex, age, height, smoking habits, and race/ethnicity. A significant proportion of individuals with normal FeNO given by the equations were classified as having intermediate levels by the current recommendations. Further lower predicted FeNO compared with previous linear models was seen. In conclusion, we suggest a novel model for the prediction of reference FeNO values that can contribute to the interpretation of FeNO in clinical practice. This approach should be further validated in large samples with an objective measurement of atopy and a medical diagnosis of asthma and rhinitis. NEW & NOTEWORTHY Novel reference equations and fraction of exhaled nitric oxide (FeNO)-predicted values to improve interpretation of FeNO in clinical practice are presented. These may increase the accuracy of ruling out airway inflammation in patients with asthma or suspected asthma.
- Having concomitant asthma phenotypes is common and independently relates to poor lung function in NHANES 2007–2012Publication . Amaral, Rita; Fonseca, João A.; Jacinto, Tiago; Pereira, Ana M.; Malinovschi, Andrei; Janson, Christer; Alving, KjellEvidence for distinct asthma phenotypes and their overlap is becoming increasingly relevant to identify personalized and targeted therapeutic strategies. In this study, we aimed to describe the overlap of five commonly reported asthma phenotypes in US adults with current asthma and assess its association with asthma outcomes. Data from the National Health and Nutrition Examination Surveys (NHANES) 2007–2012 were used (n = 30,442). Adults with current asthma were selected. Asthma phenotypes were: B-Eos-high [if blood eosinophils (B-Eos) ≥ 300/mm3]; FeNO-high (FeNO ≥ 35 ppb); B-Eos&FeNO-low (B-Eos < 150/mm3 and FeNO < 20 ppb); asthma with obesity (AwObesity) (BMI ≥ 30 kg/m2); and asthma with concurrent COPD. Data were weighted for the US population and analyses were stratified by age (< 40 and ≥ 40 years old). Of the 18,619 adults included, 1059 (5.6% [95% CI 5.1–5.9]) had current asthma. A substantial overlap was observed both in subjects aged < 40 years (44%) and ≥ 40 years (54%). The more prevalent specific overlaps in both age groups were AwObesity associated with either B-Eos-high (15 and 12%, respectively) or B-Eos&FeNO-low asthma (13 and 11%, respectively). About 14% of the current asthma patients were “non-classified”. Regardless of phenotype classification, having concomitant phenotypes was significantly associated with (adjusted OR, 95% CI) ≥ 2 controller medications (2.03, 1.16–3.57), and FEV1 < LLN (3.21, 1.74–5.94), adjusted for confounding variables. A prevalent overlap of commonly reported asthma phenotypes was observed among asthma patients from the general population, with implications for objective asthma outcomes. A broader approach may be required to better characterize asthma patients and prevent poor asthma outcomes.
- Having concomitant asthma phenotypes is common and independently relates to poor lung function in NHANES 2007-2012Publication . Amaral, Rita; Fonseca, João A; Jacinto, Tiago; Pereira, Ana M; Malinovschi, Andrei; Janson, Christer; Alving, KjellEvidence for distinct asthma phenotypes and their overlap is becoming increasingly relevant to identify personalized and targeted therapeutic strategies. In this study, we aimed to describe the overlap of five commonly reported asthma phenotypes in US adults with current asthma and assess its association with asthma outcomes. Data from the National Health and Nutrition Examination Surveys (NHANES) 2007–2012 were used (n = 30,442). Adults with current asthma were selected. Asthma phenotypes were: B-Eos-high [if blood eosinophils (B-Eos) ≥ 300/mm3]; FeNO-high (FeNO ≥ 35 ppb); B-Eos&FeNO-low (B-Eos < 150/mm3 and FeNO < 20 ppb); asthma with obesity (AwObesity) (BMI ≥ 30 kg/m2); and asthma with concurrent COPD. Data were weighted for the US population and analyses were stratified by age (< 40 and ≥ 40 years old). Of the 18,619 adults included, 1059 (5.6% [95% CI 5.1–5.9]) had current asthma. A substantial overlap was observed both in subjects aged < 40 years (44%) and ≥ 40 years (54%). The more prevalent specific overlaps in both age groups were AwObesity associated with either B-Eos-high (15 and 12%, respectively) or B-Eos&FeNO-low asthma (13 and 11%, respectively). About 14% of the current asthma patients were “non-classified”. Regardless of phenotype classification, having concomitant phenotypes was significantly associated with (adjusted OR, 95% CI) ≥ 2 controller medications (2.03, 1.16–3.57), and FEV1 < LLN (3.21, 1.74–5.94), adjusted for confounding variables. A prevalent overlap of commonly reported asthma phenotypes was observed among asthma patients from the general population, with implications for objective asthma outcomes. A broader approach may be required to better characterize asthma patients and prevent poor asthma outcomes.
- The influence of individual characteristics and non-respiratory diseases on blood eosinophil countPublication . Amaral, Rita; Jacinto, Tiago; Malinovschi, Andrei; Janson, Christer; Price, David; Fonseca, João A.; Alving, KjellBlood eosinophil (B-Eos) count is an emerging biomarker in the management of respiratory disease but determinants of B-Eos count besides respiratory disease are poorly described. Therefore, we aimed to evaluate the influence of non-respiratory diseases on B-Eos count, in comparison to the effect on two other biomarkers: fraction of exhaled nitric oxide (FeNO) and C-reactive protein (CRP), and to identify individual characteristics associated with B-Eos count in healthy controls.