SELDI-TOF biomarker signatures for cystic fibrosis, asthma and chronic obstructive pulmonary disease

Gomes‐Alves, Patrícia; Imrie, M.; Gray, Robert D.; Nogueira, Paulo; Ciordia, Sergio; Pacheco, Paula; Azevedo, Pilar; Lopes, Carlos; Almeida, Álvaro; Guardiano, Micaela; Porteous, David J.; Albar, Juan Pablo; Boyd, Alan; Penque, Deborah

doi:10.1016/j.clinbiochem.2009.10.006

Cited by 28 publications

(24 citation statements)

References 29 publications

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“…To separate lipids containing one fatty acyl group, a reversed-phase exacerbation in CF ( 14 ). In a recent report, a SELDI-based screening of serum and nasal cells from patients with CF and other respiratory diseases suggested that combinations of peptide ions studied by multivariate analysis have a better predictive value than individual species ( 15 ).…”

Section: Lc-msmentioning

confidence: 99%

Plasma lipidomics reveals potential prognostic signatures within a cohort of cystic fibrosis patients

Ollero

Astarita

Guerrera

et al. 2011

Journal of Lipid Research

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Cystic fi brosis (CF) is associated with abnormal lipid metabolism. We have recently shown variations in plasma levels of several phosphatidylcholine (PC) and lysophopshatidylcholine (LPC) species related to disease severity in CF patients. Here our goal was to search for blood plasma lipid signatures characteristic of CF patients bearing the same mutation (F508del) and different phenotypes, and to study their correlation with forced expiratory volume in 1 s (FEV1) and Pseudomonas aeruginosa chronic infection, evaluated at the time of testing (t = 0) and three years later (t = 3). Samples from 44 F508del homozygotes were subjected to a lipidomic approach based on LC-ESI-MS. Twelve free fatty acids were positively correlated with FEV1 at t = 0 (n = 29). Four of them (C20:3n-9, C20:5n-3, C22:5n-3, and C22:6n-3) were also positively correlated with FEV1 three years later, along with PC(32:2) and PC(36:4) (n = 31). Oleoylethanolamide (OEA) was negatively correlated with FEV1 progression (n = 17). Chronically infected patients at t = 0 showed lower PC(32:2), PC(38:5), and C18:3n-3 and higher cholesterol, cholesterol esters, and triacylglycerols (TAG). Chronically infected patients at t = 3 showed significantly lower levels of LPC(18:0). These results suggest a potential prognostic value for some lipid signatures in, to our knowledge, the fi rst longitudinal study aimed at identifying lipid biomarkers for CF. -Ollero, M., G. Astarita, I. C. Guerrera, I. Sermet-Gaudelus, S.

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Section: Lc-msmentioning

confidence: 99%

Plasma lipidomics reveals potential prognostic signatures within a cohort of cystic fibrosis patients

Ollero

Astarita

Guerrera

et al. 2011

Journal of Lipid Research

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“…However, lack of resolution and mass accuracy hinders unambiguous identification of protein peaks [19,20]. Accordingly, identification of candidate biomarkers of pulmonary disease has had only limited success [21][22][23]. The majority of 'omics efforts have therefore moved towards high-resolution instruments that provide increased mass accuracy to facilitate molecular species identification.…”

Section: Mass Spectrometry Overviewmentioning

confidence: 99%

Application of ’omics technologies to biomarker discovery in inflammatory lung diseases

et al. 2013

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Inflammatory lung diseases are highly complex in respect of pathogenesis and relationships between inflammation, clinical disease and response to treatment. Sophisticated large-scale analytical methods to quantify gene expression (transcriptomics), proteins (proteomics), lipids (lipidomics) and metabolites (metabolomics) in the lungs, blood and urine are now available to identify biomarkers that define disease in terms of combined clinical, physiological and patho-biological abnormalities. The aspiration is that these approaches will improve diagnosis, i.e. define pathological phenotypes, and facilitate the monitoring of disease and therapy, and also, unravel underlying molecular pathways. Biomarker studies can either select predefined biomarker(s) measured by specific methods or apply an ''unbiased'' approach involving detection platforms that are indiscriminate in focus. This article reviews the technologies presently available to study biomarkers of lung disease within the 'omics field. The contributions of the individual 'omics analytical platforms to the field of respiratory diseases are summarised, with the goal of providing background on their respective abilities to contribute to systems medicine-based studies of lung disease. @ERSpublications Summary of the application of 'omics-based analytical platforms for biomarker discovery in inflammatory lung diseases

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“…The required high-throughput ''omics'' tools are now available for use in blood, secretions and tissue [4], and these have already shown their value in discriminating various chronic respiratory diseases and different phenotypes within a disease [5,6]. The advantage of respiratory medicine is that our organ of interest is continuously exchanging molecular constituents with the environment.…”

mentioning

confidence: 99%

“…The problem in chronic respiratory medicine has been that each of the disease domains by itself is characterised by multiple perturbed mechanisms in parallel or in series, so that adequately describing various disease states requires capturing this seeming ''chaos'' by: 1) high-throughput measurements in each of these disease domains; 2) sophisticated multi-scale mathematical integration of these data [3] to come to; 3) unbiased discovery of (changes in) mechanistic pathways. ''Omics'' techniques follow this approach [4][5][6].…”

mentioning

confidence: 99%

Wake-up call by breathomics in sleep apnoea

2013

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SELDI-TOF biomarker signatures for cystic fibrosis, asthma and chronic obstructive pulmonary disease

Cited by 28 publications

References 29 publications

Plasma lipidomics reveals potential prognostic signatures within a cohort of cystic fibrosis patients

Plasma lipidomics reveals potential prognostic signatures within a cohort of cystic fibrosis patients

Application of ’omics technologies to biomarker discovery in inflammatory lung diseases

Wake-up call by breathomics in sleep apnoea

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