A region-based method for causal mediation analysis of DNA methylation data

Analytical challenges in omics research on asthma and allergy: A National Institute of Allergy and Infectious Diseases workshop

Studies of asthma and allergy are generating increasing volumes of omics data for analysis and interpretation. The National Institute of Allergy and Infectious Diseases (NIAID) assembled a workshop comprising investigators studying asthma and allergic diseases using omics approaches, omics investigators from outside the field, and NIAID medical and scientific officers to discuss the following areas in asthma and allergy research: genomics, epigenomics, transcriptomics, microbiomics, metabolomics, proteomics, lipidomics, integrative omics, systems biology, and causal inference. Current states of the art, present challenges, novel and emerging strategies, and priorities for progress were presented and discussed for each area. This workshop report summarizes the major points and conclusions from this NIAID workshop. As a group, the investigators underscored the imperatives for rigorous analytic frameworks, integration of different omics data types, cross-disciplinary interaction, strategies for overcoming current limitations, and the overarching goal to improve scientific understanding and care of asthma and allergic diseases.

A mediation analysis framework based on variance component to remove genetic confounding effect

Identification of pleiotropy at the single nucleotide polymorphism (SNP) level provides valuable insights into shared genetic signals among phenotypes. One approach to study these signals is through mediation analysis, which dissects the total effect of a SNP on the outcome into a direct effect and an indirect effect through a mediator. However, estimated effects from mediation analysis can be confounded by the genetic correlation between phenotypes, leading to inaccurate results. To address this confounding effect in the context of genetic mediation analysis, we propose a restricted-maximum-likelihood (REML)-based mediation analysis framework called REML-mediation, which can be applied to either individual-level or summary statistics data. Simulations demonstrated that REML-mediation provides unbiased estimates of the true cross-trait causal effect, assuming certain assumptions, albeit with a slightly inflated standard error compared to traditional linear regression. To validate the effectiveness of REML-mediation, we applied it to UK Biobank data and analyzed several mediator-outcome trait pairs along with their corresponding sets of pleiotropic SNPs. REML-mediation successfully identified and corrected for genetic confounding effects in these trait pairs, with correction magnitudes ranging from 7% to 39%. These findings highlight the presence of genetic confounding effects in cross-trait epidemiological studies and underscore the importance of accounting for them in data analysis.

Airway Wall Remodeling in Childhood Asthma-A Personalized Perspective from Cell Type-Specific Biology

Airway wall remodeling is a pathology occurring in chronic inflammatory lung diseases including asthma, chronic obstructive pulmonary disease, and fibrosis. In 2017, the American Thoracic Society released a research statement highlighting the gaps in knowledge and understanding of airway wall remodeling. The four major challenges addressed in this statement were: (i) the lack of consensus to define “airway wall remodeling” in different diseases, (ii) methodologic limitations and inappropriate models, (iii) the lack of anti-remodeling therapies, and (iv) the difficulty to define endpoints and outcomes in relevant studies. This review focuses on the importance of cell-cell interaction, especially the bronchial epithelium, in asthma-associated airway wall remodeling. The pathology of “airway wall remodeling” summarizes all structural changes of the airway wall without differentiating between different pheno- or endo-types of asthma. Indicators of airway wall remodeling have been reported in childhood asthma in the absence of any sign of inflammation; thus, the initiation event remains unknown. Recent studies have implied that the interaction between the epithelium with immune cells and sub-epithelial mesenchymal cells is modified in asthma by a yet unknown epigenetic mechanism during early childhood.