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Nickle, D.

Publications and source records attributed to Nickle, D..

3 recordsLinked to original sources
bioRxiv2022

Age-associated Differences in the Human Lung Extracellular Matrix

IntroductionExtracellular matrix (ECM) remodelling has been associated with chronic lung diseases. However, information about specific age-associated differences in lung ECM is currently limited. In this study we aimed to identify and localize age-associated ECM differences in human lung using comprehensive transcriptomic, proteomic and immunohistochemical analyses. MethodsOur previously identified age-associated gene expression signature of the lung was re-analysed limiting it to an aging signature based on 270 control patients (37-80 years) and focused on the Matrisome core geneset using geneset enrichment analysis. To validate the age-associated transcriptomic differences on protein level, we compared the age-associated ECM genes (F <0.05) with a profile of age-associated proteins identified from a lung tissue proteomics dataset from 9 control patients (49-76 years) (FDR<0.05). Extensive immunohistochemical analysis was used to localize the age-associated ECM differences in lung tissues from control patients (9-82 years). ResultsComparative analysis of transcriptomic and proteomic data identified 7 ECM proteins with higher expression with age at both gene and protein level: COL1A1, COL6A1, COL6A2, COL14A1, FBLN2, LTBP4 and LUM. With immunohistochemistry we demonstrated higher protein expression with age for COL6A2 in whole tissue, parenchyma, airway wall and blood vessel, for COL14A1 in bronchial epithelium and blood vessel, and for FBLN2 and COL1A1 in lung parenchyma. ConclusionOur study revealed that higher age is associated with lung ECM remodelling, with specific differences occurring in defined regions within the lung. These differences may affect lung structure and physiology with aging and as such may increase susceptibility for developing chronic lung diseases. Key messagesO_ST_ABSWhat is already known on this topicC_ST_ABSsummarise the state of scientific knowledge on this subject before you did your study and why this study needed to be done. In animal models, it has been demonstrated that aging alters the composition of the lung ECM, with more deposition of collagen and degradation of elastin. Similar ECM differences have been observed in age-associated chronic lung diseases, including COPD; moreover, we observed in lung tissue that several ECM genes associate differently with age in COPD patients compared to non-COPD controls(1). Detailed knowledge on age-associated changes in specific ECM proteins as well as regional differences within the lung is lacking. What this study addssummarise what we now know as a result of this study that we did not know before. We identified 7 age-associated ECM proteins i.e. COL1A1, COL6A1, COL6A2 COL14A1, FBLN2, LTBP4 and LUM with higher transcript and protein levels in human lung tissue with age. Extensive immunohistochemical analysis revealed significant age-associated differences for 3 of these ECM proteins in specific compartments of the lung, with the most notable differences in the blood vessels and parenchyma. How this study might affect research, practice, or policysummarise the implications of this study. The identification of age-associated differences in specific human lung ECM proteins lays a new foundation for the investigation of ECM differences in age-associated chronic lung diseases. Additionally, examining the function of these age-associated ECM proteins and their cellular interactions in lung injury and repair responses may provide novel insight in mechanisms underlying chronic lung diseases.

molecular biology↗
bioRxiv2020

Gene Expression Network Analysis Provides Potential Targets Against SARS-CoV-2

ABSTRACTBACKGROUND Cell entry of SARS-CoV-2, the novel coronavirus causing COVID-19, is facilitated by host cell angiotensin-converting enzyme 2 (ACE2) and transmembrane serine protease 2 (TMPRSS2). We aimed to identify and characterize genes that are co-expressed with ACE2 and TMPRSS2, and to further explore their biological functions and potential as druggable targets.METHODS Using the gene expression profiles of 1,038 lung tissue samples, we performed a weighted gene correlation network analysis (WGCNA) to identify modules of co-expressed genes. We explored the biology of co-expressed genes using bioinformatics databases, and identified known drug-gene interactions.RESULTS ACE2 was in a module of 681 co-expressed genes; 12 genes with moderate-high correlation with ACE2 (r>0.3, FDR<0.05) had known interactions with existing drug compounds. TMPRSS2 was in a module of 1,086 co-expressed genes; 15 of these genes were enriched in the gene ontology biologic process ‘Entry into host cell’, and 53 TMPRSS2-correlated genes had known interactions with drug compounds.CONCLUSION Dozens of genes are co-expressed with ACE2 and TMPRSS2, many of which have plausible links to COVID-19 pathophysiology. Many of the co-expressed genes are potentially targetable with existing drugs, which may help to fast-track the development of COVID-19 therapeutics.Competing Interest StatementS.M. reports personal fees from Novartis and Boehringer-Ingelheim, outside the submitted work. W.T. reports fees to Institution from Roche-Ventana, AbbVie, Merck-Sharp-Dohme and Bristol-Myers-Squibb, outside the submitted work. M.B. reports research grants paid to University from Astra Zeneca, Novartis, outside the submitted work. D.D.S. reports research funding from AstraZeneca and received honoraria for speaking engagements from Boehringer Ingelheim and AstraZeneca over the past 36 months, outside of the submitted work.View Full Text

genomics↗
bioRxiv2017

Leveraging lung tissue transcriptome to uncover candidate causal genes in COPD genetic associations

We collated 129 non-overlapping risk loci for chronic obstructive pulmonary disease (COPD) from the GWAS literature. Using recent and complementary integrative genomics approaches, combining GWAS and lung eQTL results, we identified 12 novel COPD loci and corresponding causal genes. In addition, we mapped candidate causal genes for 60 out of the 129 GWAS-nominated loci as well as for four sub-genome-wide significant COPD risk loci derived from the largest GWAS on COPD. Mapping causal genes in lung tissue represents an important contribution on the genetics of COPD, enriches our biological interpretation of GWAS findings, and brings us closer to clinical translation of genetic associations.

genomics↗