A Pilot Cross-Sectional Study of Immunological and Microbiome Profiling Reveals Distinct Inflammatory Profiles for Smokers, Electronic Cigarette Users, and Never-Smokers.

Smokers (SM) have increased lung immune cell counts and inflammatory gene expression compared to electronic cigarette (EC) users and never-smokers (NS). The objective of this study is to further assess associations for SM and EC lung microbiomes with immune cell subtypes and inflammatory gene expression in samples obtained by bronchoscopy and bronchoalveolar lavage (n = 28). RNASeq with the CIBERSORT computational algorithm were used to determine immune cell subtypes, along with inflammatory gene expression and microbiome metatranscriptomics. Macrophage subtypes revealed a two-fold increase in M0 (undifferentiated) macrophages for SM and EC users relative to NS, with a concordant decrease in M2 (anti-inflammatory) macrophages. There were 68, 19, and 1 significantly differentially expressed inflammatory genes (DEG) between SM/NS, SM/EC users, and EC users/NS, respectively. CSF-1 and GATA3 expression correlated positively and inversely with M0 and M2 macrophages, respectively. Correlation profiling for DEG showed distinct lung profiles for each participant group. There were three bacteria genera-DEG correlations and three bacteria genera-macrophage subtype correlations. In this pilot study, SM and EC use were associated with an increase in undifferentiated M0 macrophages, but SM differed from EC users and NS for inflammatory gene expression. The data support the hypothesis that SM and EC have toxic lung effects influencing inflammatory responses, but this may not be via changes in the microbiome.

Lung mitochondrial DNA copy number, inflammatory biomarkers, gene transcription and gene methylation in vapers and smokers.

BACKGROUND: Mitochondrial DNA copy number (mtCN) maintains cellular function and homeostasis, and is linked to nuclear DNA methylation and gene expression. Increased mtCN in the blood is associated with smoking and respiratory disease, but has received little attention for target organ effects for smoking or electronic cigarette (EC) use. METHODS: Bronchoscopy biospecimens from healthy EC users, smokers (SM), and never-smokers (NS) were assessed for associations of mtCN with mtDNA point mutations, immune responses, nuclear DNA methylation and gene expression using linear regression. Ingenuity pathway analysis was used for enriched pathways. GEO and TCGA respiratory disease datasets were used to explore the involvement of mtCN-associated signatures. FINDINGS: mtCN was higher in SM than NS, but EC was not statistically different from either. Overall there was a negative association of mtCN with a point mutation in the D-loop but no difference within groups. Positive associations of mtCN with IL-2 and IL-4 were found in EC only. mtCN was significantly associated with 71,487 CpGs and 321 transcripts. 263 CpGs were correlated with nearby transcripts for genes enriched in the immune system. EC-specific mtCN-associated-CpGs and genes were differentially expressed in respiratory diseases compared to controls, including genes involved in cellular movement, inflammation, metabolism, and airway hyperresponsiveness. INTERPRETATION: Smoking may elicit a lung toxic effect through mtCN. While the impact of EC is less clear, EC-specific associations of mtCN with nuclear biomarkers suggest exposure may not be harmless. Further research is needed to understand the role of smoking and EC-related mtCN on lung disease risks. FUNDING: The National Cancer Institute, the National Heart, Lung, and Blood Institute, the Food and Drug Administration Center for Tobacco Products, the National Center For Advancing Translational Sciences, and Pelotonia Intramural Research Funds.

Saliva and Lung Microbiome Associations with Electronic Cigarette Use and Smoking.

The microbiome has increasingly been linked to cancer. Little is known about the lung and oral cavity microbiomes in smokers, and even less for electronic cigarette (EC) users, compared with never-smokers. In a cross-sectional study (n = 28) of smokers, EC users, and never-smokers, bronchoalveolar lavage and saliva samples underwent metatranscriptome profiling to examine associations with lung and oral microbiomes. Pairwise comparisons assessed differentially abundant bacteria species. Total bacterial load was similar between groups, with no differences in bacterial diversity across lung microbiomes. In lungs, 44 bacteria species differed significantly (FDR < 0.1) between smokers/never-smokers, with most decreased in smokers. Twelve species differed between smokers/EC users, all decreased in smokers of which Neisseria sp. KEM232 and Curvibacter sp. AEP1-3 were observed. Among the top five decreased species in both comparisons, Neisseria elongata, Neisseria sicca, and Haemophilus parainfluenzae were observed. In the oral microbiome, 152 species were differentially abundant for smokers/never-smokers, and 17 between smokers/electronic cigarette users, but only 21 species were differentially abundant in both the lung and oral cavity. EC use is not associated with changes in the lung microbiome compared with never-smokers, indicating EC toxicity does not affect microbiota. Statistically different bacteria in smokers compared with EC users and never-smokers were almost all decreased, potentially due to toxic effects of cigarette smoke. The low numbers of overlapping oral and lung microbes suggest that the oral microbiome is not a surrogate for analyzing smoking-related effects in the lung. PREVENTION RELEVANCE: The microbiome affects cancer and other disease risk. The effects of e-cig usage on the lung microbiome are essentially unknown. Given the importance of lung microbiome dysbiosis populated by oral species which have been observed to drive lung cancer progression, it is important to study effects of e-cig use on microbiome.

Metabolomics and Multi-Omics Integration: A Survey of Computational Methods and Resources.

As researchers are increasingly able to collect data on a large scale from multiple clinical and omics modalities, multi-omics integration is becoming a critical component of metabolomics research. This introduces a need for increased understanding by the metabolomics researcher of computational and statistical analysis methods relevant to multi-omics studies. In this review, we discuss common types of analyses performed in multi-omics studies and the computational and statistical methods that can be used for each type of analysis. We pinpoint the caveats and considerations for analysis methods, including required parameters, sample size and data distribution requirements, sources of a priori knowledge, and techniques for the evaluation of model accuracy. Finally, for the types of analyses discussed, we provide examples of the applications of corresponding methods to clinical and basic research. We intend that our review may be used as a guide for metabolomics researchers to choose effective techniques for multi-omics analyses relevant to their field of study.

Biomarkers of Exposure and Effect in the Lungs of Smokers, Nonsmokers, and Electronic Cigarette Users.

BACKGROUND: Nicotine-containing electronic cigarette (e-cig) use has become widespread. However, understanding the biological impact of e-cigs compared with smoking on the lung is needed. There are major gaps in knowledge for chronic effects and for an etiology to recent acute lung toxicity leading to death among vapers. METHODS: We conducted bronchoscopies in a cross-sectional study of 73 subjects (42 never-smokers, 15 e-cig users, and 16 smokers). Using bronchoalveolar lavage and brushings, we examined lung inflammation by cell counts, cytokines, genome-wide gene expression, and DNA methylation. RESULTS: There were statistically significant differences among never-smokers, e-cig users, and smokers for inflammatory cell counts and cytokines (FDR q < 0.1). The e-cig users had values intermediate between smokers and never-smokers, with levels for most of the biomarkers more similar to never-smokers. For differential gene expression and DNA methylation, e-cig users also more like never-smokers; many of these genes corresponded to smoking-related pathways, including those for xenobiotic metabolism, aryl hydrocarbon receptor signaling, and oxidative stress. Differentially methylated genes were correlated with changes in gene expression, providing evidence for biological effects of the methylation associations. CONCLUSIONS: These data indicate that e-cigs are associated with less toxicity than cigarettes for smoking-related pathways. What is unknown may be unique effects for e-cigs not measured herein, and a comparison of smokers completely switching to e-cigs compared with former smokers. Clinical trials for smokers switching to e-cigs who undergo serial bronchoscopy and larger cross-sectional studies of former smokers with and without e-cig use, and for e-cigs who relapse back to smoking, are needed. IMPACT: These data can be used for product regulation and for informing tobacco users considering or using e-cigs. What is unknown may be unique effects for e-cigs not measured herein, and clinical trials with serial bronchoscopy underway can demonstrate a direct relationship for changes in lung biomarkers.

Development and validation of a targeted gene sequencing panel for application to disparate cancers.

Next generation sequencing has revolutionised genomic studies of cancer, having facilitated the development of precision oncology treatments based on a tumour's molecular profile. We aimed to develop a targeted gene sequencing panel for application to disparate cancer types with particular focus on tumours of the head and neck, plus test for utility in liquid biopsy. The final panel designed through Roche/Nimblegen combined 451 cancer-associated genes (2.01 Mb target region). 136 patient DNA samples were collected for performance and application testing. Panel sensitivity and precision were measured using well-characterised DNA controls (n = 47), and specificity by Sanger sequencing of the Aryl Hydrocarbon Receptor Interacting Protein (AIP) gene in 89 patients. Assessment of liquid biopsy application employed a pool of synthetic circulating tumour DNA (ctDNA). Library preparation and sequencing were conducted on Illumina-based platforms prior to analysis with our accredited (ISO15189) bioinformatics pipeline. We achieved a mean coverage of 395x, with sensitivity and specificity of >99% and precision of >97%. Liquid biopsy revealed detection to 1.25% variant allele frequency. Application to head and neck tumours/cancers resulted in detection of mutations aligned to published databases. In conclusion, we have developed an analytically-validated panel for application to cancers of disparate types with utility in liquid biopsy.

Pathogenic variants in PLOD3 result in a Stickler syndrome-like connective tissue disorder with vascular complications.

BACKGROUND: Pathogenic PLOD3 variants cause a connective tissue disorder (CTD) that has been described rarely. We further characterise this CTD and propose a clinical diagnostic label to improve recognition and diagnosis of PLOD3-related disease. METHODS: Reported PLOD3 phenotypes were compared with known CTDs utilising data from three further individuals from a consanguineous family with a homozygous PLOD3 c.809C>T; p.(Pro270Leu) variant. PLOD3 mRNA expression in the developing embryo was analysed for tissue-specific localisation. Mouse microarray expression data were assessed for phylogenetic gene expression similarities across CTDs with overlapping clinical features. RESULTS: Key clinical features included ocular abnormalities with risk for retinal detachment, sensorineural hearing loss, reduced palmar creases, finger contractures, prominent knees, scoliosis, low bone mineral density, recognisable craniofacial dysmorphisms, developmental delay and risk for vascular dissection. Collated clinical features showed most overlap with Stickler syndrome with variable features of Ehlers-Danlos syndrome (EDS) and epidermolysis bullosa (EB). Human lysyl hydroxylase 3/PLOD3 expression was localised to the developing cochlea, eyes, skin, forelimbs, heart and cartilage, mirroring the clinical phenotype of this disorder. CONCLUSION: These data are consistent with pathogenic variants in PLOD3 resulting in a clinically distinct Stickler-like syndrome with vascular complications and variable features of EDS and EB. Early identification of PLOD3 variants would improve monitoring for comorbidities and may avoid serious adverse ocular and vascular outcomes.

Whole-exome sequencing reanalysis at 12 months boosts diagnosis and is cost-effective when applied early in Mendelian disorders.

PURPOSE: Whole-exome sequencing (WES) has revolutionized Mendelian diagnostics, however, there is no consensus on the timing of data review in undiagnosed individuals and only preliminary data on the cost-effectiveness of this technology. We aimed to assess the utility of WES data reanalysis for diagnosis in Mendelian disorders and to analyze the cost-effectiveness of this technology compared with a traditional diagnostic pathway. METHODS: WES was applied to a cohort of 54 patients from 37 families with a variety of Mendelian disorders to identify the genetic etiology. Reanalysis was performed after 12 months with an improved WES diagnostic pipeline. A comparison was made between costs of a modeled WES pathway and a traditional diagnostic pathway in a cohort with intellectual disability (ID). RESULTS: Reanalysis of WES data at 12 months improved diagnostic success from 30 to 41% due to interim publication of disease genes, expanded phenotype data from referrer, and an improved bioinformatics pipeline. Cost analysis on the ID cohort showed average cost savings of US$586 (AU$782) for each additional diagnosis. CONCLUSION: Early application of WES in Mendelian disorders is cost-effective and reanalysis of an undiagnosed individual at a 12-month time point increases total diagnoses by 11%.

A Mild PUM1 Mutation Is Associated with Adult-Onset Ataxia, whereas Haploinsufficiency Causes Developmental Delay and Seizures.

Certain mutations can cause proteins to accumulate in neurons, leading to neurodegeneration. We recently showed, however, that upregulation of a wild-type protein, Ataxin1, caused by haploinsufficiency of its repressor, the RNA-binding protein Pumilio1 (PUM1), also causes neurodegeneration in mice. We therefore searched for human patients with PUM1 mutations. We identified eleven individuals with either PUM1 deletions or de novo missense variants who suffer a developmental syndrome (Pumilio1-associated developmental disability, ataxia, and seizure; PADDAS). We also identified a milder missense mutation in a family with adult-onset ataxia with incomplete penetrance (Pumilio1-related cerebellar ataxia, PRCA). Studies in patient-derived cells revealed that the missense mutations reduced PUM1 protein levels by ∼25% in the adult-onset cases and by ∼50% in the infantile-onset cases; levels of known PUM1 targets increased accordingly. Changes in protein levels thus track with phenotypic severity, and identifying posttranscriptional modulators of protein expression should identify new candidate disease genes.

Integrating exome sequencing into a diagnostic pathway for epileptic encephalopathy: Evidence of clinical utility and cost effectiveness.

BACKGROUND: Epileptic encephalopathies are a devastating group of neurological conditions in which etiological diagnosis can alter management and clinical outcome. Exome sequencing and gene panel testing can improve diagnostic yield but there is no cost-effectiveness analysis of their use or consensus on how to best integrate these tests into clinical diagnostic pathways. METHODS: We conducted a retrospective cost-effectiveness study comparing trio exome sequencing with a standard diagnostic approach, for a well-phenotyped cohort of 32 patients with epileptic encephalopathy, who remained undiagnosed after "first-tier" testing. Sensitivity analysis was included with a range of commercial exome and multigene panels. RESULTS: The diagnostic yield was higher for the exome sequencing (16/32; 50%) than the standard arm (2/32; 6.2%). The trio exome sequencing pathway was cost-effective compared to the standard diagnostic pathway with a cost saving of AU$5,236 (95% confidence intervals $2,482; $9,784) per additional diagnosis; the standard pathway cost approximately 10 times more per diagnosis. Sensitivity analysis demonstrated that the majority of commercial exome sequencing and multigene panels studied were also cost-effective. The clinical utility of all diagnoses was reported. CONCLUSION: Our study supports the integration of exome sequencing and gene panel testing into the diagnostic pathway for epileptic encephalopathy, both in terms of cost effectiveness and clinical utility. We propose a diagnostic pathway that integrates initial rapid screening for treatable causes and comprehensive genomic screening. This study has important implications for health policy and public funding for epileptic encephalopathy and other neurological conditions.

A De Novo Mutation in the Sodium-Activated Potassium Channel KCNT2 Alters Ion Selectivity and Causes Epileptic Encephalopathy.

Early infantile epileptic encephalopathies (EOEE) are a debilitating spectrum of disorders associated with cognitive impairments. We present a clinical report of a KCNT2 mutation in an EOEE patient. The de novo heterozygous variant Phe240Leu SLICK was identified by exome sequencing and confirmed by Sanger sequencing. Phe240Leu rSlick and hSLICK channels were electrophysiologically, heterologously characterized to reveal three significant alterations to channel function. First, [Cl-]i sensitivity was reversed in Phe240Leu channels. Second, predominantly K+-selective WT channels were made to favor Na+ over K+ by Phe240Leu. Third, and consequent to altered ion selectivity, Phe240Leu channels had larger inward conductance. Further, rSlick channels induced membrane hyperexcitability when expressed in primary neurons, resembling the cellular seizure phenotype. Taken together, our results confirm that Phe240Leu is a "change-of-function" KCNT2 mutation, demonstrating unusual altered selectivity in KNa channels. These findings establish pathogenicity of the Phe240Leu KCNT2 mutation in the reported EOEE patient.

Methylation-capture and Next-Generation Sequencing of free circulating DNA from human plasma.

BACKGROUND: Free circulating DNA (fcDNA) has many potential clinical applications, due to the non-invasive way in which it is collected. However, because of the low concentration of fcDNA in blood, genome-wide analysis carries many technical challenges that must be overcome before fcDNA studies can reach their full potential. There are currently no definitive standards for fcDNA collection, processing and whole-genome sequencing. We report novel detailed methodology for the capture of high-quality methylated fcDNA, library preparation and downstream genome-wide Next-Generation Sequencing. We also describe the effects of sample storage, processing and scaling on fcDNA recovery and quality. RESULTS: Use of serum versus plasma, and storage of blood prior to separation resulted in genomic DNA contamination, likely due to leukocyte lysis. Methylated fcDNA fragments were isolated from 5 donors using a methyl-binding protein-based protocol and appear as a discrete band of ~180 bases. This discrete band allows minimal sample loss at the size restriction step in library preparation for Next-Generation Sequencing, allowing for high-quality sequencing from minimal amounts of fcDNA. Following sequencing, we obtained 37 × 10(6)-86 × 10(6) unique mappable reads, representing more than 50% of total mappable reads. The methylation status of 9 genomic regions as determined by DNA capture and sequencing was independently validated by clonal bisulphite sequencing. CONCLUSIONS: Our optimized methods provide high-quality methylated fcDNA suitable for whole-genome sequencing, and allow good library complexity and accurate sequencing, despite using less than half of the recommended minimum input DNA.