Many common diseases, such as asthma, diabetes or obesity, involve altered interactions between thousands of genes. High-throughput techniques (omics) allow identification of such genes and their products, but functional understanding is a formidable challenge. Network-based analyses of omics data have identified modules of disease-associated genes that have been used to obtain both a systems level and a molecular understanding of disease mechanisms. For example, in allergy a module was used to find a novel candidate gene that was validated by functional and clinical studies. Such analyses play important roles in systems medicine. This is an emerging discipline that aims to gain a translational understanding of the complex mechanisms underlying common diseases. In this review, we will explain and provide examples of how network-based analyses of omics data, in combination with functional and clinical studies, are aiding our understanding of disease, as well as helping to prioritize diagnostic markers or therapeutic candidate genes. Such analyses involve significant problems and limitations, which will be discussed. We also highlight the steps needed for clinical implementation.

We propose an innovative, integrated, cost-effective health system to combat major non-communicable diseases (NCDs), including cardiovascular, chronic respiratory, metabolic, rheumatologic and neurologic disorders and cancers, which together are the predominant health problem of the 21st century. This proposed holistic strategy involves comprehensive patient-centered integrated care and multi-scale, multi-modal and multi-level systems approaches to tackle NCDs as a common group of diseases. Rather than studying each disease individually, it will take into account their intertwined gene-environment, socio-economic interactions and co-morbidities that lead to individual-specific complex phenotypes. It will implement a road map for predictive, preventive, personalized and participatory (P4) medicine based on a robust and extensive knowledge management infrastructure that contains individual patient information. It will be supported by strategic partnerships involving all stakeholders, including general practitioners associated with patient-centered care. This systems medicine strategy, which will take a holistic approach to disease, is designed to allow the results to be used globally, taking into account the needs and specificities of local economies and health systems.

Inhaled corticosteroids (ICSs) and long-acting β₂-agonists (LABAs) are used to treat moderate to severe chronic obstructive pulmonary disease (COPD). To determine whether long-term ICS therapy, with and without LABAs, reduces inflammation and improves pulmonary function in COPD. Randomized, placebo-controlled trial. (ClinicalTrials.gov registration number: NCT00158847) 2 university medical centers in The Netherlands. 114 steroid-naive current or former smokers with moderate to severe COPD. Cell counts in bronchial biopsies and sputum (primary outcome); methacholine responsiveness at baseline, 6, and 30 months; and clinical outcomes every 3 months. Random assignment by minimization method to receive fluticasone propionate, 500 µg twice daily, for 6 months (n = 31) or 30 months (n = 26); fluticasone, 500 µg twice daily, and salmeterol, 50 µg twice daily, for 30 months (single inhaler; n = 28); or placebo twice daily (n = 29). 101 patients were greater than 70% adherent to therapy. Fluticasone therapy decreased counts of mucosal CD3⁺ cells (−55% [95% CI, −74% to −22%]; P = 0.004), CD4⁺ cells (−78% [CI, −88% to 60%]; P < 0.001), CD8⁺ cells (−57% [CI, −77% to −18%]; P = 0.010), and mast cells (−38% [CI, −60% to −2%]; P = 0.039) and reduced hyperresponsiveness (P = 0.036) versus placebo at 6 months, with effects maintained after 30 months. Fluticasone therapy for 30 months reduced mast cell count and increased eosinophil count and percentage of intact epithelium, with accompanying reductions in sputum neutrophil, macrophage, and lymphocyte counts and improvements in FEV₁ decline, dyspnea, and quality of life. Reductions in inflammatory cells correlated with clinical improvements. Discontinuing fluticasone therapy at 6 months increased counts of CD3⁺ cells (120% [CI, 24% to 289%]; P = 0.007), mast cells (218% [CI, 99% to 407%]; P < 0.001), and plasma cells (118% [CI, 9% to 336%]; P = 0.028) and worsened clinical outcome. Adding salmeterol improved FEV₁ level. The study was not designed to evaluate clinical outcomes. Measurement of primary outcome was not available for 24% of patients at 30 months. ICS therapy decreases inflammation and can attenuate decline in lung function in steroid-naive patients with moderate to severe COPD. Adding LABAs does not enhance these effects. Netherlands Organization for Scientific Research, Netherlands Asthma Foundation, GlaxoSmithKline of The Netherlands, University Medical Center Groningen, and Leiden University Medical Center.

Eosinophilic inflammation in chronic obstructive pulmonary disease (COPD) is predictive for responses to inhaled steroids. We hypothesised that the inflammatory subtype in mild and moderate COPD can be assessed by exhaled breath metabolomics.Exhaled compounds were analysed using gas chromatography and mass spectrometry (GC-MS) and electronic nose (eNose) in 28 COPD patients (12/16 Global Initiative for Chronic Obstructive Lung Disease (GOLD) stage I/II, respectively). Differential cell counts, eosinophil cationic protein (ECP) and myeloperoxidase (MPO) were measured in induced sputum. Relationships between exhaled compounds, eNose breathprints and sputum inflammatory markers were analysed and receiver operating characteristic (ROC) curves were constructed.Exhaled compounds were highly associated with sputum cell counts (eight compounds with eosinophils, 17 with neutrophils; p<0.01). Only one compound (alkylated benzene) overlapped between eosinophilic and neutrophilic profiles. GC-MS and eNose breathprints were associated with markers of inflammatory activity in GOLD stage I (ECP: 19 compounds, p<0.01; eNose breathprint r=0.84, p=0.002) (MPO: four compounds, p<0.01; eNose r=0.72, p=0.008). ROC analysis for eNose showed high sensitivity and specificity for inflammatory activity in mild COPD (ECP: area under the curve (AUC) 1.00; MPO: AUC 0.96) but not for moderate COPD.Exhaled molecular profiles are closely associated with the type of inflammatory cell and their activation status in mild and moderate COPD. This suggests that breath analysis may be used for assessment and monitoring of airway inflammation in COPD.

Internet-based self-management has shown to improve asthma control and asthma related quality of life, but the improvements were only marginally clinically relevant for the group as a whole. We hypothesized that self-management guided by weekly monitoring of asthma control tailors pharmacological therapy to individual needs and improves asthma control for patients with partly controlled or uncontrolled asthma.

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