Multi-Omics Profiling Approach to Asthma: An Evolving Paradigm

Gautam, Yadu; Johansson, Erika; Mersha, Tesfaye B.

doi:10.3390/jpm12010066

Cited by 40 publications

(36 citation statements)

References 210 publications

(244 reference statements)

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“…However, significant difficulties still exist in comparing data generated on differing technologies due to both data heterogeneity and inherent biases in the systems used to generate these datasets. With the continued development of new methods and tools for bioinformatics analysis, including machine learning and deep learning techniques, these will undoubtedly help to ease the bottlenecks associated with the integration of high dimensional data generated from multiple sources in multiple modalities ( 165 , 166 ).…”

Section: Current Application Of Multiomics Analysis To Asthma Studiesmentioning

confidence: 99%

Asthma and the Missing Heritability Problem: Necessity for Multiomics Approaches in Determining Accurate Risk Profiles

et al. 2022

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Asthma is ranked among the most common chronic conditions and has become a significant public health issue due to the recent and rapid increase in its prevalence. Investigations into the underlying genetic factors predict a heritable component for its incidence, estimated between 35% and 90% of causation. Despite the application of large-scale genome-wide association studies (GWAS) and admixture mapping approaches, the proportion of variants identified accounts for less than 15% of the observed heritability of the disease. The discrepancy between the predicted heritable component of disease and the proportion of heritability mapped to the currently identified susceptibility loci has been termed the ‘missing heritability problem.’ Here, we examine recent studies involving both the analysis of genetically encoded features that contribute to asthma and also the role of non-encoded heritable characteristics, including epigenetic, environmental, and developmental aspects of disease. The importance of vertical maternal microbiome transfer and the influence of maternal immune factors on fetal conditioning in the inheritance of disease are also discussed. In order to highlight the broad array of biological inputs that contribute to the sum of heritable risk factors associated with allergic disease incidence that, together, contribute to the induction of a pro-atopic state. Currently, there is a need to develop in-depth models of asthma risk factors to overcome the limitations encountered in the interpretation of GWAS results in isolation, which have resulted in the missing heritability problem. Hence, multiomics analyses need to be established considering genetic, epigenetic, and functional data to create a true systems biology-based approach for analyzing the regulatory pathways that underlie the inheritance of asthma and to develop accurate risk profiles for disease.

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Section: Current Application Of Multiomics Analysis To Asthma Studiesmentioning

confidence: 99%

Asthma and the Missing Heritability Problem: Necessity for Multiomics Approaches in Determining Accurate Risk Profiles

et al. 2022

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“…Other transcriptomic analysis sources are the sputum and other epithelial cells obtained from nasal epithelia and bronchial brushing. Bronchoalveolar lavage (BAL) was another source of cells as it might reflect the internal environment present in the lower respiratory tract [ 71 ].…”

Section: Systems Biology Findings and Applications In Asthmamentioning

confidence: 99%

The Role of Systems Biology in Deciphering Asthma Heterogeneity

Hachim

Alqutami

Hachim

et al. 2022

Life

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Asthma is one of the most common and lifelong and chronic inflammatory diseases characterized by inflammation, bronchial hyperresponsiveness, and airway obstruction episodes. It is a heterogeneous disease of varying and overlapping phenotypes with many confounding factors playing a role in disease susceptibility and management. Such multifactorial disorders will benefit from using systems biology as a strategy to elucidate molecular insights from complex, quantitative, massive clinical, and biological data that will help to understand the underlying disease mechanism, early detection, and treatment planning. Systems biology is an approach that uses the comprehensive understanding of living systems through bioinformatics, mathematical, and computational techniques to model diverse high-throughput molecular, cellular, and the physiologic profiling of healthy and diseased populations to define biological processes. The use of systems biology has helped understand and enrich our knowledge of asthma heterogeneity and molecular basis; however, such methods have their limitations. The translational benefits of these studies are few, and it is recommended to reanalyze the different studies and omics in conjugation with one another which may help understand the reasons for this variation and help overcome the limitations of understanding the heterogeneity in asthma pathology. In this review, we aim to show the different factors that play a role in asthma heterogeneity and how systems biology may aid in understanding and deciphering the molecular basis of asthma.

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“…The reproducibility of the results and the capacity to uncover marginal signals may both be improved by meta-analyses of several independent studies. Gene set enriched and network analysis may be used in the genes with differential expression (DEGs) to detect the pathways and gene networks that they are highly prone to influence [ 37 ].…”

Section: Reviewmentioning

confidence: 99%

A Multi-Point View of Genetic Factors Affecting Hereditary Transmissibility of Asthma

Kulkarni¹,

Kediya²

2022

Cureus

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Asthma is a respiratory illness characterized by episodes of bronchial spasm that make breathing difficult. It often has an association with an allergic response or any hypersensitivity followed by inflammation and hypersensitivity of the airways. Asthma is a sophisticated, complicated, and diverse respiratory condition. Even while heredity is a chief hazard factor for developing asthma, environmental and inner exposures, as well as how they interact with genetic variables, also have a substantial impact on the disease's pathogenesis. In recent years, the field of asthma research has seen the emergence and deployment of high throughput omics techniques for the unbiased screening of biomarkers such as genes, transcripts, proteins, and metabolites. Better asthma risk profile has been achieved by utilizing large-scale studies that are illustrative of various population-based data and merging with clinical data. This allergic airway illness has a wide range of phenotypes and endotypes, many of which have not yet been fully defined. The diversity of phenotypes is reflected in similarly complicated etiologies, and it is thought that a number of genetic and environmental variables interrelate to promote the danger of asthma in both children and adults. In order to achieve this objective, significant efforts are necessary to describe different phenotypes, uncover fundamental mechanisms, and find associated biomarkers. It is clear that the analysis, monitoring, and treatment of asthma require a tailored strategy. The risk of developing a multifactorial ailment is characterized by the grade of genetic relationship between the individual and affected relative. Additionally, the risk is typically larger if the relative has a severe illness or was afflicted when they were young. The asthma phenotype is highly varied and expressed non-linearly in contrast to single gene illnesses. This makes it challenging to predict whether someone with a certain gene or set of genotypes would have asthma.

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Multi-Omics Profiling Approach to Asthma: An Evolving Paradigm

Cited by 40 publications

References 210 publications

Asthma and the Missing Heritability Problem: Necessity for Multiomics Approaches in Determining Accurate Risk Profiles

Asthma and the Missing Heritability Problem: Necessity for Multiomics Approaches in Determining Accurate Risk Profiles

The Role of Systems Biology in Deciphering Asthma Heterogeneity

A Multi-Point View of Genetic Factors Affecting Hereditary Transmissibility of Asthma

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