Clarifying the risk of lung disease in SZ alpha-1 antitrypsin deficiency

Rationale: The ZZ genotype of alpha-1 antitrypsin deficiency (AATD) is associated with chronic obstructive pulmonary disease (COPD), even among never-smokers. The SZ genotype is also considered severe; yet, its effect on lung health remains unclear. Objectives: To determine the effect of SZ-AATD on spirometry compared with a normal-risk population and to determine the effect of smoking cessation in this genotype. Methods: We prospectively enrolled 166 related individuals, removing lung index cases to reduce bias, and compared spirometry between 70 SZ and 46 MM/MS individuals (control subjects). The effect of AAT concentrations on outcomes was assessed in 82 SZ individuals (including lung index cases). Subsequently, we analyzed retrospective SZ registry data to determine the effect of smoking cessation on spirometry decline (n = 60) and plasma anti–neutrophil elastase capacity (n = 20). Measurements and Main Results: No difference between SZ and control never-smokers was seen. Ever smoking was associated with a lower FEV1% predicted (−14.3%; P = 0.0092) and a lower FEV1/FVC ratio (−0.075; P = 0.0041) in SZ-AATD. No association was found between AAT concentration and outcomes for SZ-AATD. Longitudinal analysis of 60 SZ individuals demonstrated that COPD at baseline, but not former smoking or AAT concentrations, predicted greater spirometry decline. Finally, anti–neutrophil elastase capacity did not differ between former smokers and never-smokers (P = 0.67). Conclusions: SZ never-smokers demonstrated no increased risk of COPD, regardless of AAT concentration. Smoking interacts with SZ-AATD to significantly increase airflow obstruction. Former smoking alone is not associated with greater spirometry decline in SZ-AATD, suggesting that cessation attenuates the obstructive process. We found no evidence that the putative protective threshold or AAT concentrations predict risk within the SZ genotype, raising further doubts over the need for intravenous AAT augmentation in this cohort.</p

A linear prognostic score based on the ratio of interleukin-6 to interleukin-10 predicts outcomes in COVID-19

Background: Prognostic tools are required to guide clinical decision-making in COVID-19.Methods: We studied the relationship between the ratio of interleukin (IL)-6 to IL-10 and clinical outcome in 80 patients hospitalized for COVID-19, and created a simple 5-point linear score predictor of clinical outcome, the Dublin-Boston score. Clinical outcome was analysed as a three-level ordinal variable ("Improved", "Unchanged", or "Declined"). For both IL-6:IL-10 ratio and IL-6 alone, we associated clinical outcome with a) baseline biomarker levels, b) change in biomarker level from day 0 to day 2, c) change in biomarker from day 0 to day 4, and d) slope of biomarker change throughout the study. The associations between ordinal clinical outcome and each of the different predictors were performed with proportional odds logistic regression. Associations were run both "unadjusted" and adjusted for age and sex. Nested cross-validation was used to identify the model for incorporation into the Dublin-Boston score.Findings: The 4-day change in IL-6:IL-10 ratio was chosen to derive the Dublin-Boston score. Each 1 point increase in the score was associated with a 5.6 times increased odds for a more severe outcome (OR 5.62, 95% CI -3.22-9.81, P = 1.2 × 10-9). Both the Dublin-Boston score and the 4-day change in IL-6:IL-10 significantly outperformed IL-6 alone in predicting clinical outcome at day 7.Interpretation: The Dublin-Boston score is easily calculated and can be applied to a spectrum of hospitalized COVID-19 patients. More informed prognosis could help determine when to escalate care, institute or remove mechanical ventilation, or drive considerations for therapies.</p

Corrigendum to 'A linear prognostic score based on the ratio of interleukin-6 to interleukin-10 predicts outcomes in COVID-19'

The authors wish to correct a typographical error in the manuscript. In both the abstract and Section 3.4 of the original manuscript, a 1-point increase in the Dublin-Boston score was described as being associated with a 5.6 times increased odds (OR 5.62, 95% CI = 3.229.81, P = 1.2 £ 109 ) for a more severe outcome. While the OR and P-value stated are correct, the CI should instead have read “3.229.81”. The CI listed in Table 3 of the original manuscript, which accompanied Section 3.4, is correct. The authors regret any confusion caused, and appreciate the opportunity to correct this mistake.</div

A systematic analysis of protein-altering exonic variants in chronic obstructive pulmonary disease

Genome-wide association studies (GWASs) have identified regions associated with chronic obstructive pulmonary disease (COPD). GWASs of other diseases have shown an approximately 10-fold overrepresentation of nonsynonymous variants, despite limited exonic coverage on genotyping arrays. We hypothesized that a large-scale analysis of coding variants could discover novel genetic associations with COPD, including rare variants with large effect sizes. We performed a meta-analysis of exome arrays from 218,399 controls and 33,851 moderate-to-severe COPD cases. All exome-wide significant associations were present in regions previously identified by GWAS. We did not identify any novel rare coding variants with large effect sizes. Within GWAS regions on chromosomes 5q, 6p, and 15q, four coding variants were conditionally significant (P < 0.00015) when adjusting for lead GWAS single-nucleotide polymorphisms A common gasdermin B (GSDMB) splice variant (rs11078928) previously associated with a decreased risk for asthma was nominally associated with a decreased risk for COPD [minor allele frequency (MAF)=0.46, P = 1.8e-4]. Two stop variants in coiled-coil a-helical rod protein 1 (CCHCR1), a gene involved in regulating cell proliferation, were associated with COPD (both P < 0.0001). The SERPINA1 Z allele was associated with a random-effects odds ratio of 1.43 for COPD (95% confidence interval = 1.17–1.74), though with marked heterogeneity across studies. Overall, COPD-associated exonic variants were identified in genes involved in DNA methylation, cell-matrix interactions, cell proliferation, and cell death. In conclusion, we performed the largest exome array meta-analysis of COPD to date and identified potential functional coding variants. Future studies are needed to identify rarer variants and further define the role of coding variants in COPD pathogenesis