-
Cancer Research Communications Feb 2024We report a deep next-generation sequencing analysis of 13 sequentially obtained tumor samples, eight sequentially obtained circulating tumor DNA (ctDNA) samples and...
UNLABELLED
We report a deep next-generation sequencing analysis of 13 sequentially obtained tumor samples, eight sequentially obtained circulating tumor DNA (ctDNA) samples and three germline DNA samples over the life history of 3 patients with triple-negative breast cancer (TNBC), 2 of whom had germline pathogenic BRCA1 mutation, to unravel tumor evolution. Tumor tissue from all timepoints and germline DNA was subjected to whole-exome sequencing (WES), custom amplicon deep sequencing (30,000X) of a WES-derived somatic mutation panel, and SNP arrays for copy-number variation (CNV), while whole transcriptome sequencing (RNA-seq) was performed only on somatic tumor.There was enrichment of homologous recombination deficiency signature in all tumors and widespread CNV, which remained largely stable over time. Somatic tumor mutation numbers varied between patients and within each patient (range: 70-216, one outlier). There was minimal mutational overlap between patients with TP53 being the sole commonly mutated gene, but there was substantial overlap in sequential samples in each patient. Each patient's tumor contained a founding ("stem") clone at diagnosis, which persisted over time, from which all other clones ("subclone") were derived ("branching evolution"), which contained mutations in well-characterized cancer-related genes like PDGFRB, ARID2, TP53 (Patient_02), TP53, BRAF, BRIP1, CSF3R (Patient_04), and TP53, APC, EZH2 (Patient_07). Including stem and subclones, tumors from all patients were polyclonal at diagnosis and during disease progression. ctDNA recapitulated most tissue-derived stem clonal and subclonal mutations while detecting some additional subclonal mutations. RNA-seq revealed a stable basal-like pattern, with most highly expressed variants belonging to stem clone.
SIGNIFICANCE
In germline BRCA1 mutated and BRCA wild-type patients, TNBC shows a branching evolutionary pattern of mutations with a single founding clone, are polyclonal throughout their disease course, and have widespread copy-number aberrations. This evolutionary pattern may be associated with treatment resistance or sensitivity and could be therapeutically exploited.
Topics: Humans; BRCA1 Protein; Disease Progression; DNA; Exome Sequencing; Triple Negative Breast Neoplasms; Germ-Line Mutation
PubMed: 38315150
DOI: 10.1158/2767-9764.CRC-23-0277 -
The British Journal of Surgery May 2024Clinical auditing is a powerful tool to evaluate and improve healthcare. Deviations from the expected quality of care are identified by benchmarking the results of...
BACKGROUND
Clinical auditing is a powerful tool to evaluate and improve healthcare. Deviations from the expected quality of care are identified by benchmarking the results of individual hospitals using national averages. This study aimed to evaluate the use of quality indicators for benchmarking hepato-pancreato-biliary (HPB) surgery and when outlier hospitals could be identified.
METHODS
A population-based study used data from two nationwide Dutch HPB audits (DHBA and DPCA) from 2014 to 2021. Sample size calculations determined the threshold (in percentage points) to identify centres as statistical outliers, based on current volume requirements (annual minimum of 20 resections) on a two-year period (2020-2021), covering mortality rate, failure to rescue (FTR), major morbidity rate and textbook/ideal outcome (TO) for minor liver resection (LR), major LR, pancreaticoduodenectomy (PD) and distal pancreatectomy (DP).
RESULTS
In total, 10 963 and 7365 patients who underwent liver and pancreatic resection respectively were included. Benchmark and corresponding range of mortality rates were 0.6% (0 -3.2%) and 3.3% (0-16.7%) for minor and major LR, and 2.7% (0-7.0%) and 0.6% (0-4.2%) for PD and DP respectively. FTR rates were 5.4% (0-33.3%), 14.2% (0-100%), 7.5% (1.6%-28.5%) and 3.1% (0-14.9%). For major morbidity rate, corresponding rates were 9.8% (0-20.5%), 28.1% (0-47.1%), 36% (15.8%-58.3%) and 22.3% (5.2%-46.1%). For TO, corresponding rates were 73.6% (61.3%-94.4%), 54.1% (35.3-100), 46.8% (25.3%-59.4%) and 63.3% (30.7%-84.6%). Mortality rate thresholds indicating a significant outlier were 8.6% and 15.4% for minor and major LR and 14.2% and 8.6% for PD and DP. For FTR, these thresholds were 17.9%, 31.6%, 22.9% and 15.0%. For major morbidity rate, these thresholds were 26.1%, 49.7%, 57.9% and 52.9% respectively. For TO, lower thresholds were 52.5%, 32.5%, 25.8% and 41.4% respectively. Higher hospital volumes decrease thresholds to detect outliers.
CONCLUSION
Current event rates and minimum volume requirements per hospital are too low to detect any meaningful between hospital differences in mortality rate and FTR. Major morbidity rate and TO are better candidates to use for benchmarking.
Topics: Humans; Benchmarking; Quality Indicators, Health Care; Netherlands; Pancreatectomy; Male; Pancreaticoduodenectomy; Hepatectomy; Female; Middle Aged; Aged; Hospital Mortality
PubMed: 38747683
DOI: 10.1093/bjs/znae119 -
Genes & Diseases May 2024Metabolomics as a research field and a set of techniques is to study the entire small molecules in biological samples. Metabolomics is emerging as a powerful tool... (Review)
Review
Metabolomics as a research field and a set of techniques is to study the entire small molecules in biological samples. Metabolomics is emerging as a powerful tool generally for precision medicine. Particularly, integration of microbiome and metabolome has revealed the mechanism and functionality of microbiome in human health and disease. However, metabolomics data are very complicated. Preprocessing/pretreating and normalizing procedures on metabolomics data are usually required before statistical analysis. In this review article, we comprehensively review various methods that are used to preprocess and pretreat metabolomics data, including MS-based data and NMR -based data preprocessing, dealing with zero and/or missing values and detecting outliers, data normalization, data centering and scaling, data transformation. We discuss the advantages and limitations of each method. The choice for a suitable preprocessing method is determined by the biological hypothesis, the characteristics of the data set, and the selected statistical data analysis method. We then provide the perspective of their applications in the microbiome and metabolome research.
PubMed: 38299197
DOI: 10.1016/j.gendis.2023.04.018 -
Sexual Medicine Feb 2024The causal relationship between certain lifestyle factors and erectile dysfunction (ED) is still uncertain.
BACKGROUND
The causal relationship between certain lifestyle factors and erectile dysfunction (ED) is still uncertain.
AIM
The study sought to investigate the causal effect of 9 life factors on ED through 2-sample single-variable Mendelian randomization (SVMR) and multivariable Mendelian randomization (MVMR).
METHODS
Genetic instruments to proxy 9 risk factors were identified by genome-wide association studies. The genome-wide association studies estimated the connection of these genetic variants with ED risk (n = 223 805). We conducted SVMR, inverse variance-weighting, Cochran's Q, weighted median, MR-Egger, MR-PRESSO (Mendelian Randomization Pleiotropy RESidual Sum and Outlier), and MVMR analyses to explore the total and direct relationship between life factors and ED.
OUTCOMES
The primary outcome was defined as self or physician-reported ED, or using oral ED medication, or a history of surgery related to ED.
RESULTS
In SVMR analyses, suggestive associations with increased the risk of ED were noted for ever smoked (odds ratio [OR], 5.894; 95% confidence interval [CI], 0.469 to 3.079; = .008), alcohol consumption (OR, 1.495; 95% CI, 0.044 to 0.760; = .028) and body mass index (BMI) (OR, 1.177; 95% CI, 0.057 to 0.268; = .003). Earlier age at first intercourse was significantly related to reduced ED risk (OR, 0.659; 95% CI, -0.592 to -0.244; = 2.5 × 10). No strong evidence was found for the effect of coffee intake, time spent driving, physical activity, and leisure sedentary behaviors on the incidence of ED (All > .05). The result of MVMR analysis for BMI (OR, 1.13; 95% CI, 1.01 to 1.25; = .045) and earlier age at first intercourse (OR, 0.77; 95% CI, 0.56 to 0.99; = .018) provided suggestive evidence for the direct impact on ED, while no causal factor was detected for alcoholic drinks per week and ever smoked.
CLINICAL IMPLICATIONS
This study provides evidence for the impact of certain modifiable lifestyle factors on the development of ED.
STRENGTHS AND LIMITATIONS
We performed both SVMR and MVMR to strengthen the causal relationship between exposures and outcomes. However, the population in this study was limited to European ancestry.
CONCLUSION
Ever smoked, alcoholic drinks per week, BMI, and age first had sexual intercourse were causally related to ED, while the potential connection between coffee intake, physical activity, recreational sedentary habits, and increased risk of ED needs to be further confirmed.
PubMed: 38505341
DOI: 10.1093/sexmed/qfae010 -
Frontiers in Microbiology 2024Increasing evidence indicates that gut microbiota dysbiosis is related to synovitis and tenosynovitis. Nonetheless, whether these associations are causal is currently...
BACKGROUND
Increasing evidence indicates that gut microbiota dysbiosis is related to synovitis and tenosynovitis. Nonetheless, whether these associations are causal is currently unknown.
OBJECTIVES
A two-sample Mendelian randomization (MR) study was performed to reveal the causality of gut microbiota with synovitis and tenosynovitis.
METHODS
The summary statistical data from a large-scale genome-wide association study (GWAS) were applied as the basis for a two-sample MR analysis. The causal effect was estimated using inverse variance weighted (IVW), weighted median, simple mode, MR-Egger, and weighted mode methods, of which IVW was the important method. Meanwhile, the pleiotropy and heterogeneity were detected and measured using MR-Egger regression, Cochran's Q statistics, funnel plots, and MR pleiotropy residual sum and outlier (MR-PRESSO) methods.
RESULTS
The IVW technique demonstrated that genetically predicted five genera, namely [odds ratio (OR) = 0.999, 95% confidence interval (CI): (0.9977, 0.9998), = 0.019], [OR = 0.999, 95% CI: (0.9971, 0.9999), = 0.036], [OR = 0.998, 95% CI: (0.9954, 0.9999), = 0.041], [OR = 0.997, 95% CI: (0.9955, 0.9994), = 0.011], and [OR = 0.997, 95% CI: (0.9954, 0.9992), = 0.006] were negatively correlated with the risk of synovitis and tenosynovitis, while two other genera, namely [OR = 1.003, 95% CI: (1.0004, 1.0049), = 0.019] and [OR = 1.003, 95% CI: (1.0002, 1.0052), = 0.035] were positively associated with synovitis and tenosynovitis risk. In addition, the data of sensitivity analyses demonstrated that there were no outliers, horizontal pleiotropy, or heterogeneity in the causal relationship of the above-mentioned gut microbiota on synovitis and tenosynovitis ( > 0.05).
CONCLUSION
The results of the study suggested that the gut microbiota was causally involved in synovitis and tenosynovitis and identified specific bacterial taxa that affect synovitis and tenosynovitis, which provide new insights into the pathogenesis underlying the development of synovitis and tenosynovitis mediated by gut microbiota.
PubMed: 38746746
DOI: 10.3389/fmicb.2024.1355725 -
Thrombosis and Haemostasis May 2024Despite previous observational studies linking obstructive sleep apnea (OSA) to venous thromboembolism (VTE), these findings remain controversial. This study aimed to...
BACKGROUND
Despite previous observational studies linking obstructive sleep apnea (OSA) to venous thromboembolism (VTE), these findings remain controversial. This study aimed to explore the association between OSA and VTE, including pulmonary embolism (PE) and deep vein thrombosis (DVT), at a genetic level using a bidirectional two-sample Mendelian randomization (MR) analysis.
METHODS
Utilizing summary-level data from large-scale genome-wide association studies in European individuals, we designed a bidirectional two-sample MR analysis to comprehensively assess the genetic association between OSA and VTE. The inverse variance weighted was used as the primary method for MR analysis. In addition, MR-Egger, weighted median, and MR pleiotropy residual sum and outlier (MR-PRESSO) were used for complementary analyses. Furthermore, a series of sensitivity analyses were performed to ensure the validity and robustness of the results.
RESULTS
The initial and validation MR analyses indicated that genetically predicted OSA had no effects on the risk of VTE (including PE and DVT). Likewise, the reverse MR analysis did not find substantial support for a significant association between VTE (including PE and DVT) and OSA. Supplementary MR methods and sensitivity analyses provided additional confirmation of the reliability of the MR results.
CONCLUSION
Our bidirectional two-sample MR analysis did not find genetic evidence supporting a significant association between OSA and VTE in either direction.
PubMed: 38631385
DOI: 10.1055/a-2308-2290 -
Scientific Reports Sep 2023Subspace outlier detection has emerged as a practical approach for outlier detection. Classical full space outlier detection methods become ineffective in high...
Subspace outlier detection has emerged as a practical approach for outlier detection. Classical full space outlier detection methods become ineffective in high dimensional data due to the "curse of dimensionality". Subspace outlier detection methods have great potential to overcome the problem. However, the challenge becomes how to determine which subspaces to be used for outlier detection among a huge number of all subspaces. In this paper, firstly, we propose an intuitive definition of outliers in subspaces. We study the desirable properties of subspaces for outlier detection and investigate the metrics for those properties. Then, a novel subspace outlier detection algorithm with a statistical foundation is proposed. Our method selectively leverages a limited set of the most interesting subspaces for outlier detection. Through experimental validation, we demonstrate that identifying outliers within this reduced set of highly interesting subspaces yields significantly higher accuracy compared to analyzing the entire feature space. We show by experiments that the proposed method outperforms competing subspace outlier detection approaches on real world data sets.
PubMed: 37714878
DOI: 10.1038/s41598-023-42261-4 -
Mammalian Genome : Official Journal of... Dec 2023The Mouse Phenome Database continues to serve as a curated repository and analysis suite for measured attributes of members of diverse mouse populations. The repository... (Meta-Analysis)
Meta-Analysis Review
The Mouse Phenome Database continues to serve as a curated repository and analysis suite for measured attributes of members of diverse mouse populations. The repository includes annotation to community standard ontologies and guidelines, a database of allelic states for 657 mouse strains, a collection of protocols, and analysis tools for flexible, interactive, user directed analyses that increasingly integrates data across traits and populations. The database has grown from its initial focus on a standard set of inbred strains to include heterogeneous mouse populations such as the Diversity Outbred and mapping crosses and well as Collaborative Cross, Hybrid Mouse Diversity Panel, and recombinant inbred strains. Most recently the system has expanded to include data from the International Mouse Phenotyping Consortium. Collectively these data are accessible by API and provided with an interactive tool suite that enables users' persistent selection, storage, and operation on collections of measures. The tool suite allows basic analyses, advanced functions with dynamic visualization including multi-population meta-analysis, multivariate outlier detection, trait pattern matching, correlation analyses and other functions. The data resources and analysis suite provide users a flexible environment in which to explore the basis of phenotypic variation in health and disease across the lifespan.
Topics: Mice; Animals; Mice, Inbred Strains; Phenotype; Phenomics
PubMed: 37581698
DOI: 10.1007/s00335-023-10014-3 -
American Journal of Speech-language... Aug 2023Few studies have reported on the vowel space area (VSA) in both acoustic and kinematic domains. This study examined acoustic and kinematic VSAs for speakers with and...
PURPOSE
Few studies have reported on the vowel space area (VSA) in both acoustic and kinematic domains. This study examined acoustic and kinematic VSAs for speakers with and without dysarthria and evaluated effects of normalization on acoustic and kinematic VSAs and the relationship between these measures.
METHOD
Vowel data from 12 speakers with and without dysarthria, presenting with a range of speech abilities, were examined. The speakers included four speakers with Parkinson's disease (PD), four speakers with brain injury (BI), and four neurotypical (NT) speakers. Speech acoustic and kinematic data were acquired simultaneously using electromagnetic articulography during a passage reading task. Raw and normalized VSAs calculated from corner vowels /i/, /æ/, /ɑ/, and /u/ were evaluated. Normalization was achieved through score transformations to the acoustic and kinematic data. The effect of normalization on variability within and across groups was evaluated. Regression analysis was used across speakers to assess the association between acoustic and kinematic VSAs for both raw and normalized data.
RESULTS
When evaluating the speakers as three different groups (i.e., PD, BI, and NT), normalization reduced the standard deviations within each group and changed the relative differences in average magnitude between groups. Regression analysis revealed a significant relationship between normalized, but not raw, acoustic and kinematic VSAs, after the exclusion of an outlier speaker.
CONCLUSIONS
Normalization reduces the variability across speakers, within groups, and changes average magnitudes affecting speaker group comparisons. Normalization also influences the correlation between acoustic and kinematic measures. Further investigation of the impact of normalization techniques upon acoustic and kinematic measures is warranted.
SUPPLEMENTAL MATERIAL
https://doi.org/10.23641/asha.22669747.
Topics: Humans; Speech Intelligibility; Speech Production Measurement; Speech Acoustics; Dysarthria; Biomechanical Phenomena; Acoustics; Parkinson Disease; Phonetics
PubMed: 37105919
DOI: 10.1044/2023_AJSLP-22-00158 -
NeuroImage Dec 2023Diffusion-weighted MRI (dMRI) is a medical imaging method that can be used to investigate the brain microstructure and structural connections between different brain...
Diffusion-weighted MRI (dMRI) is a medical imaging method that can be used to investigate the brain microstructure and structural connections between different brain regions. The method, however, requires relatively complex data processing frameworks and analysis pipelines. Many of these approaches are vulnerable to signal dropout artefacts that can originate from subjects moving their head during the scan. To combat these artefacts and eliminate such outliers, researchers have proposed two approaches: to replace outliers or to downweight outliers during modelling and analysis. With the rising interest in dMRI for clinical research, these types of corrections are increasingly important. Therefore, we set out to investigate the differences between outlier replacement and weighting approaches to help the dMRI community to select the best tool for their data processing pipelines. We evaluated dMRI motion correction registration and single tensor model fit pipelines using Gaussian Process and Spherical Harmonic based replacement approaches and outlier downweighting using highly realistic whole-brain simulations. As a proof of concept, we applied these approaches to dMRI infant data sets that contained varying numbers of dropout artefacts. Based on our results, we concluded that the Gaussian Process based outlier replacement provided similar tensor fit results to Gaussian Process based outlier detection and downweighting. Therefore, if only the least-squares estimate of the single tensor model is of interest, our recommendation is to use outlier replacement. However, outlier downweighting can potentially provide a more accurate estimate of the model precision which could be relevant for applications such as probabilistic tractoraphy.
Topics: Humans; Algorithms; Diffusion Magnetic Resonance Imaging; Brain; Artifacts; Least-Squares Analysis
PubMed: 37820862
DOI: 10.1016/j.neuroimage.2023.120397