Bacteria are highly diverse, even within a species; thus, there have been many studies which classify a single species into multiple types and analyze the genetic differences between them. Recently, the use of whole-genome sequencing (WGS) has been popular for these analyses, and the identification of single-nucleotide polymorphisms (SNPs) between isolates is the most basic analysis performed following WGS. The performance of SNP-calling methods therefore has a significant effect on the accuracy of downstream analyses, such as phylogenetic tree inference. In particular, when closely related isolates are analyzed, e.g. in outbreak investigations, some SNP callers tend to detect a high number of false-positive SNPs compared with the limited number of true SNPs among isolates. However, the performances of various SNP callers in such a situation have not been validated sufficiently. Here, we show the results of realistic benchmarks of commonly used SNP callers, revealing that some of them exhibit markedly low accuracy when target isolates are closely related. As an alternative, we developed a novel pipeline BactSNP, which utilizes both assembly and mapping information and is capable of highly accurate and sensitive SNP calling in a single step. BactSNP is also able to call SNPs among isolates when the reference genome is a draft one or even when the user does not input the reference genome. BactSNP is available at https://github.com/IEkAdN/BactSNP .

Background Clarification of the risk factors for coronavirus disease 2019 (COVID-19) severity is strongly warranted for global health. Recent studies have indicated that elevated body mass index (BMI) is associated with unfavorable progression of COVID-19. This is assumed to be due to excessive deposition of visceral adipose tissue (VAT); however, the evidence investigating the association between intra-abdominal fat and COVID-19 prognosis is sparse. We therefore investigated whether measuring the amount of intra-abdominal fat is useful to predict the prognosis of COVID-19. Methods The present study enrolled 53 consecutive cases of COVID-19 patients aged ≥ 20 years with chest computed tomography (CT) scans. The VAT area, total adipose tissue (TAT) area, and VAT/TAT ratio were estimated using axial CT images at the level of the upper pole of the right kidney. Severe COVID-19 was defined as death or acute respiratory failure demanding oxygen at ≥ 6 L per minute, a high-flow nasal cannula, or mechanical ventilation. The association of VAT/TAT with the incidence of progression to a severe state was estimated as a hazard ratio (HR) using Cox regression analysis. To compare the prediction ability for COVID-19 disease progression between BMI and VAT/TAT, the area under the receiver operating characteristic curve (AUC) of each was assessed. Results A total of 15 cases (28.3% of the whole study subjects) progressed to severe stages. The incidence of developing severe COVID-19 increased significantly with VAT/TAT (HR per 1% increase = 1.040 (95% CI 1.008–1.074), P = 0.01). After adjustment for potential confounders, the positive association of VAT/TAT with COVID-19 aggravation remained significant (multivariable-adjusted HR = 1.055 (95% CI 1.000–1.112) per 1% increase, P = 0.049). The predictive ability of VAT/TAT for COVID-19 becoming severe was significantly better than that of BMI (AUC of 0.73 for VAT/TAT and 0.50 for BMI; P = 0.0495 for the difference). Conclusions A higher ratio of VAT/TAT was an independent risk factor for disease progression among COVID-19 patients. VAT/TAT was superior to BMI in predicting COVID-19 morbidity. COVID-19 patients with high VAT/TAT levels should be carefully observed as high-risk individuals for morbidity and mortality.

Purpose Similar to chronic obstructive pulmonary disease (COPD), the diffusing capacity of the lung (D LCO ) might be decreased and associated with poor prognosis in preserved ratio impaired spirometry (PRISm), a clinical entity as a prodromal phase of COPD. The aims of the present study were to evaluate the distributions of D LCO and to assess the association between D LCO and mortality among subjects with PRISm. Patients and Methods We conducted an observational cohort study at the National Hospital Organization Fukuoka National Hospital. We classified the 899 patients ≥ 40 years of age with an assessment of D LCO into five groups based on spirometry: preserved spirometry, PRISm, mild COPD, moderate COPD, and severe/very severe COPD. The prevalence of low D LCO (< 80% per predicted) was compared among the five groups. Using PRISm patients with follow-up data, we further investigated the association of low D LCO with all-cause mortality. Results The prevalence of low D LCO in the PRISm group (58.8%) was significantly higher than that in the preserved-spirometry group (21.8%), the mild-COPD group (23.5%), and the moderate-COPD group (36.0%) (all P < 0.01), and it was comparable to that in the severe/very severe-COPD group (63.2%). The results remained unchanged after adjusting for potential confounders. Among the PRISm subjects, the overall survival rate was significantly lower in the low-D LCO group than in the preserved-D LCO group ( P < 0.01). The multivariable-adjusted hazard ratio (HR) for all-cause mortality was significantly higher in the low-D LCO group than in the preserved-D LCO group (HR = 10.10 (95% confidence interval 2.33–43.89)). Conclusion Diffusing capacity was more impaired in PRISm subjects than in those with preserved spirometry or mild to moderate COPD. Regarding PRISm, low D LCO was a significant risk factor for all-cause mortality. Clinicians should assess D LCO in the management of PRISm to predict the future risk of overall death.

Background Asthma–chronic obstructive pulmonary disease (COPD) overlap (ACO) patients experience exacerbations more frequently than those with asthma or COPD alone. Since low diffusing capacity of the lung for carbon monoxide (DLCO) is known as a strong risk factor for severe exacerbation in COPD, DLCO or a transfer coefficient of the lung for carbon monoxide (KCO) is speculated to also be associated with the risk of exacerbations in ACO. Methods This study was conducted as an observational cohort survey at the National Hospital Organization Fukuoka National Hospital. DLCO and KCO were measured in 94 patients aged ≥ 40 years with a confirmed diagnosis of ACO. Multivariable-adjusted hazard ratios (HRs) for the exacerbation-free rate over one year were estimated and compared across the levels of DLCO and KCO. Results Within one year, 33.3% of the cohort experienced exacerbations. After adjustment for potential confounders, low KCO (< 80% per predicted) was positively associated with the incidence of exacerbation (multivariable-adjusted HR = 3.71 (95% confidence interval 1.32–10.4)). The association between low DLCO (< 80% per predicted) and exacerbations showed similar trends, although it failed to reach statistical significance (multivariable-adjusted HR = 1.31 (95% confidence interval 0.55–3.11)). Conclusions Low KCO was a significant risk factor for exacerbations among patients with ACO. Clinicians should be aware that ACO patients with impaired KCO are at increased risk of exacerbations and that careful management in such a population is mandatory.

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