Category: Statistics

Pediatr Allergy Immunol. 2021 Jun 4. doi: 10.1111/pai.13569. Online ahead of print.

ABSTRACT

BACKGROUND: Subcutaneous immunotherapy (SCIT) is an effective, safe, preventative treatment for allergic asthma; however, potential biomarkers for monitoring SCIT have rarely been reported.

OBJECTIVE: Metabolomics was utilized for the discovery of new biomarkers and analyzing disease pathophysiology of allergic asthma, it was also applied to determine the metabolomic profiles of serum samples from children with asthma undergoing SCIT and identify potential biomarkers for allergic asthma and its therapeutic monitoring.

METHODS: Untargeted metabolomics using ultra-high-performance liquid chromatography-quadrupole-time-of-flight mass spectrometry, was performed on 15 asthmatic and 15 healthy pediatric sera to profile carboxylic acids. Statistical analysis combined with pathway enrichment analysis were applied to identify potential biomarkers. Then, targeted metabolomics was performed to study longitudinal changes of eicosanoid profiles on sera from 20 participants with asthma who received SCIT at baseline, 6 months, one, two and three years (ChiCTR-DDT-13003728).

RESULTS: Metabolomic analysis revealed that levels of eicosanoids, particularly 12(S)-hydroxyeicosatetraenoic acid (HETE; AUC = 0.94, P < 0.0001) and 15(S)-HETE (AUC = 0.89, P = 0.0028), metabolized from arachidonic acid by lipoxygenase and glutathione peroxidase enzymes, were significantly higher in asthma group than in healthy individuals. Furthermore, levels of these important metabolites increased in the first year of SCIT treatment and then decreased from years one to three, being significantly lower after three years of treatment than baseline levels.

CONCLUSION: 12(S)- and 15(S)-HETEs are potential biomarkers to participate in the pathogenesis and treatment of allergic asthma. Moreover, these metabolites may be a new target for biological indicators to monitor the therapeutic effect of SCIT, particularly in the setting of allergic asthma.

PMID:34087025 | DOI:10.1111/pai.13569

Oper Dent. 2021 Jun 4. doi: 10.2341/20-099-L. Online ahead of print.

ABSTRACT

The aim of this study was to compare the effects of accelerated aging on the overall color stability of potentially color adjusting commercial resin-based composite resins. Thirty specimens (10 mm diameter and 2.5 mm thick; n=6) were fabricated using five different materials: Estelite Omega, GC Kalore, Venus Pearl, Harmonize, and Omnichroma. Color measurements were taken for each sample using a spectrophotometer before and after submitting samples through the artificial aging process (Q-sun Xenon Test Chamber, 102 min light at 63°C black panel temperature; 18 min light and water spray per ASTM G155) for a total of 300 hours (12.5 days). The total color difference (ΔE*ab) was calculated using SpectraMagic NX software and analyzed using one-way analysis of variance and Tukey test. The results for color change (ΔE*ab) were statistically significant. Omnichroma and Venus Pearl presented superior color stability and the lowest overall color change, whereas GC Kalore and Harmonize presented significant color change that would be considered clinically unacceptable (ΔE*ab > 3.3).

PMID:34086953 | DOI:10.2341/20-099-L

J Infect Dis. 2021 Jun 4:jiab300. doi: 10.1093/infdis/jiab300. Online ahead of print.

ABSTRACT

The kinetics of IgG avidity maturation during severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection obtained from 217 participants of the Ischgl cohort, Austria, was studied 0.5-1.5 (baseline) and 7-8 months (follow up) after infection. The IgG avidity assay, using a modified IgG ELISA and 5.5 M urea, revealed that old age does not diminish the increase in avidity, detected in all participants positive at both time points, from 18% to 42%. High avidity was associated with a marked residual neutralization capacity in 97.2.% of participants (211/217), which was even higher in the older age group, revealing an important role of avidity assays as easy and cheap surrogate tests for assessing the maturation of the immune system conveying potential protection against further SARS-CoV-2 infections without necessitating expensive and laborious neutralization assays.

PMID:34086960 | DOI:10.1093/infdis/jiab300

J Infect Dis. 2021 Jun 4:jiab296. doi: 10.1093/infdis/jiab296. Online ahead of print.

ABSTRACT

BACKGROUND: Serosurveys are important to ascertain burden of infection. Prior SARS-CoV-2 serosurveys in New York City (NYC) have used nonrandom samples. During June-October 2020, the NYC Health Department conducted a population-based survey to estimate SARS-CoV-2 antibody prevalence in NYC adults.

METHODS: Participants were recruited from the NYC 2020 Community Health Survey. We estimated citywide and stratified antibody prevalence using a hybrid design: serum tested at the NYC Health Department using the DiaSorin LIAISON ® SARS-CoV-2 S1/S2 IgG assay and self-reported antibody test results were used together. Prevalence was estimated using univariate frequencies and 95% confidence intervals (CI), accounting for complex survey design. Two-sided P-values ≤0.05 were statistically significant.

RESULTS: There were 1074 respondents overall; 497 provided blood and 577 provided only a self-reported antibody test result. Weighted prevalence was 24.3% overall (95% CI: 20.7-28.3). Latino (30.7%, 95% CI: 24.1-38.2, p<0.01) and Black (30.7%, 95% CI: 21.9-41.2, p=0.02) respondents had a higher weighted prevalence compared with White respondents (17.4%, 95% CI: 12.5-23.7).

CONCLUSIONS: By October 2020, nearly 1 in 3 Black and 1 in 3 Latino NYC adults had SARS-CoV-2 antibodies, highlighting unequal impacts of the COVID-19 pandemic on Black and Latino adults in NYC.

PMID:34086923 | DOI:10.1093/infdis/jiab296

Nicotine Tob Res. 2021 Jun 4:ntab120. doi: 10.1093/ntr/ntab120. Online ahead of print.

ABSTRACT

INTRODUCTION: Menthol has been shown to target similar brain regions and neural receptors as nicotine, yet the association between menthol cigarette use and cognitive performance remains unknown.

METHODS: This study examined differences in cognitive task performance between menthol (MS) and non-menthol (NMS) cigarette smokers after acute cigarette consumption. Sixty White and Black/African American, non-abstinent, MS (n=30) and NMS (n=30) were assessed pre- and post-smoking their preferred cigarette on four computerized tasks: Continuous Performance Task (CPT; alerting attention), N-Back Task (working memory), Finger Tapping Task (motor control), and Apple Picker Task (reinforcement enhancement). Self-reported nicotine dependence and objective smoking topography measures were also compared between groups.

RESULTS: Initial unadjusted analyses showed a significant effect of cigarette type x time on CPT speed (p=.042), where MS improved while NMS group worsened in CPT speed after smoking. After controlling for baseline cigarette craving and cigarette nicotine levels, the effect of cigarette type x time for all cognitive outcomes was statistically non-significant (ps>.05). However, there remained a significant effect of cigarette type, where MS vs. NMS had poorer CPT (p=.046) and N-Back Task accuracy (p=.006) but faster N-Back speed (p=.039). There were no statistically significant differences between groups on reinforcement enhancement, nicotine dependence, or smoking behavior outcomes (ps>.05).

CONCLUSIONS: Contrary to our hypotheses, results did not find a significant effect of cigarette type on the change in cognitive performance after acute smoking in non-abstinent smokers. Further studies are needed to clarify the specific pharmacological effects of nicotine and menthol on cognitive functioning.

PMID:34086950 | DOI:10.1093/ntr/ntab120

Bioinformatics. 2021 Jun 4:btab428. doi: 10.1093/bioinformatics/btab428. Online ahead of print.

ABSTRACT

MOTIVATION: Species tree estimation from genes sampled from throughout the whole genome is complicated due to the gene tree-species tree discordance. Incomplete lineage sorting (ILS) is one of the most frequent causes for this discordance, where alleles can coexist in populations for periods that may span several speciation events. Quartet-based summary methods for estimating species trees from a collection of gene trees are becoming popular due to their high accuracy and statistical guarantee under ILS. Generating quartets with appropriate weights, where weights correspond to the relative importance of quartets, and subsequently amalgamating the weighted quartets to infer a single coherent species tree can allow for a statistically consistent way of estimating species trees. However, handling weighted quartets is challenging.

RESULTS: We propose wQFM, a highly accurate method for species tree estimation from multi-locus data, by extending the quartet FM (QFM) algorithm to a weighted setting. wQFM was assessed on a collection of simulated and real biological datasets, including the avian phylogenomic dataset which is one of the largest phylogenomic datasets to date. We compared wQFM with wQMC, which is the best alternate method for weighted quartet amalgamation, and with ASTRAL, which is one of the most accurate and widely used coalescent-based species tree estimation methods. Our results suggest that wQFM matches or improves upon the accuracy of wQMC and ASTRAL.

AVAILABILITY: wQFM is available in open source form at https://github.com/Mahim1997/wQFM-2020.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID:34086858 | DOI:10.1093/bioinformatics/btab428

J Exp Biol. 2021 Jun 1;224(11):jeb241059. doi: 10.1242/jeb.241059. Epub 2021 Jun 4.

ABSTRACT

The magnitude of many biological traits relates strongly and regularly to body size. Consequently, a major goal of comparative biology is to understand and apply these ‘size-scaling’ relationships, traditionally quantified by using linear regression analyses based on log-transformed data. However, recently some investigators have questioned this traditional method, arguing that linear or non-linear regression based on untransformed arithmetic data may provide better statistical fits than log-linear analyses. Furthermore, they advocate the replacement of the traditional method by alternative specific methods on a case-by-case basis, based simply on best-fit criteria. Here, I argue that the use of logarithms in scaling analyses presents multiple valuable advantages, both statistical and conceptual. Most importantly, log-transformation allows biologically meaningful, properly scaled (scale-independent) comparisons of organisms of different size, whereas non-scaled (scale-dependent) analyses based on untransformed arithmetic data do not. Additionally, log-based analyses can readily reveal biologically and theoretically relevant discontinuities in scale invariance during developmental or evolutionary increases in body size that are not shown by linear or non-linear arithmetic analyses. In this way, log-transformation advances our understanding of biological scaling conceptually, not just statistically. I hope that my Commentary helps students, non-specialists and other interested readers to understand the general benefits of using log-transformed data in size-scaling analyses, and stimulates advocates of arithmetic analyses to show how they may improve our understanding of scaling conceptually, not just statistically.

PMID:34086905 | DOI:10.1242/jeb.241059

J Appl Lab Med. 2021 Jun 4:jfab044. doi: 10.1093/jalm/jfab044. Online ahead of print.

ABSTRACT

BACKGROUND: Serum protein electrophoresis is one of the core investigations for screening for monoclonal proteins. Among the available capillary systems, the Helena V8 system has been evaluated in a limited number of studies.

METHODS: In total, 310 sera samples were assessed on the Helena V8 system and compared with the Sebia Capillarys instrument. Abnormalities suggestive of monoclonal proteins were confirmed by immunofixation. Imprecision studies and reference intervals were determined.

RESULTS: The imprecision of the Helena V8 was inferior or equal to 5.8%. The mean bias of Helena V8 vs Sebia Capillarys was about -0.9 g/L for albumin; -0.2 g/L foralpha-1; 1.1 g/L for alpha-2; -0.2 g/L for beta; 0.3 g/L for gamma; -0.5 g/L for monoclonal protein in beta; and 0.3 g/L for monoclonal protein in gamma. Among the 56 samples with monoclonal proteins confirmed by immunofixation, all were seen on both methods, with only 1 discordant result at a cutoff of 5.0 g/L. Reference intervals were statistically different between the 2 analyzers, except for the beta fraction.

CONCLUSIONS: Our evaluation confirms the good analytical performance of the Helena V8 analyzer as a suitable alternative to the Sebia Capillarys instrument.

PMID:34086920 | DOI:10.1093/jalm/jfab044

Bioinformatics. 2021 Jun 4:btab427. doi: 10.1093/bioinformatics/btab427. Online ahead of print.

ABSTRACT

MOTIVATION: Genome wide association studies (GWAS) can reveal important genotype-phenotype associations, however, data quality and interpretability issues must be addressed. For drug discovery scientists seeking to prioritize targets based on the available evidence, these issues go beyond the single study.

METHODS: Here, we describe rational ranking, filtering and interpretation of inferred gene-trait associations and data aggregation across studies by leveraging existing curation and harmonization efforts. Each gene-trait association is evaluated for confidence, with scores derived solely from aggregated statistics, linking a protein-coding gene and phenotype. We propose a method for assessing confidence in gene-trait associations from evidence aggregated across studies, including a bibliometric assessment of scientific consensus based on the iCite Relative Citation Ratio, and meanRank scores, to aggregate multivariate evidence.

RESULTS: This method, intended for drug target hypothesis generation, scoring and ranking, has been implemented as an analytical pipeline, available as open source, with public datasets of results, and a web application designed for usability by drug discovery scientists.

AVAILABILITY: Web application, datasets, and source code via: https://unmtid-shinyapps.net/tiga/.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID:34086846 | DOI:10.1093/bioinformatics/btab427

Bioinformatics. 2021 Jun 4:btab426. doi: 10.1093/bioinformatics/btab426. Online ahead of print.

ABSTRACT

MOTIVATION: The advancement in technologies and the growth of available single-cell datasets motivate integrative analysis of multiple single-cell genomic datasets. Integrative analysis of multimodal single-cell datasets combines complementary information offered by single-omic datasets and can offer deeper insights on complex biological process. Clustering methods that identify the unknown cell types are among the first few steps in the analysis of single-cell datasets, and they are important for downstream analysis built upon the identified cell types.

RESULTS: We propose scAMACE for the integrative analysis and clustering of single-cell data on chromatin accessibility, gene expression and methylation. We demonstrate that cell types are better identified and characterized through analyzing the three data types jointly. We develop an efficient expectationmaximization (EM) algorithm to perform statistical inference, and evaluate our methods on both simulation study and real data applications. We also provide the GPU implementation of scAMACE, making it scalable to large datasets.

AVAILABILITY: The software and datasets are available at https://github.com/cuhklinlab/scAMACE_py (python implementation) and https://github.com/cuhklinlab/scAMACE (R implementation).

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID:34086847 | DOI:10.1093/bioinformatics/btab426