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- Skwark, Marcin J., et al.
(författare)
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Interacting networks of resistance, virulence and core machinery genes identified by genome-wide epistasis analysis
- 2017
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Ingår i: PLOS Genetics. - : PUBLIC LIBRARY SCIENCE. - 1553-7390 .- 1553-7404. ; 13:2
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Tidskriftsartikel (refereegranskat)abstract
- Recent advances in the scale and diversity of population genomic datasets for bacteria now provide the potential for genome-wide patterns of co-evolution to be studied at the resolution of individual bases. Here we describe a new statistical method, genomeDCA, which uses recent advances in computational structural biology to identify the polymorphic loci under the strongest co-evolutionary pressures. We apply genomeDCA to two large population data sets representing the major human pathogens Streptococcus pneumoniae (pneumococcus) and Streptococcus pyogenes (group A Streptococcus). For pneumococcus we identified 5,199 putative epistatic interactions between 1,936 sites. Over three-quarters of the links were between sites within the pbp2x, pbp1a and pbp2b genes, the sequences of which are critical in determining non-susceptibility to beta-lactam antibiotics. A network-based analysis found these genes were also coupled to that encoding dihydrofolate reductase, changes to which underlie trimethoprim resistance. Distinct from these antibiotic resistance genes, a large network component of 384 protein coding sequences encompassed many genes critical in basic cellular functions, while another distinct component included genes associated with virulence. The group A Streptococcus (GAS) data set population represents a clonal population with relatively little genetic variation and a high level of linkage disequilibrium across the genome. Despite this, we were able to pinpoint two RNA pseudouridine synthases, which were each strongly linked to a separate set of loci across the chromosome, representing biologically plausible targets of co-selection. The population genomic analysis method applied here identifies statistically significantly co-evolving locus pairs, potentially arising from fitness selection interdependence reflecting underlying protein- protein interactions, or genes whose product activities contribute to the same phenotype. This discovery approach greatly enhances the future potential of epistasis analysis for systems biology, and can complement genome-wide association studies as a means of formulating hypotheses for targeted experimental work.
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| 2. |
- Tancin Lambert, Anna, et al.
(författare)
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Biomarkers Predictive of Atrial Fibrillation in Patients with Cryptogenic Stroke. Insights from The Nordic Atrial Fibrillation and Stroke (NOR-FIB) Study
- 2023
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Ingår i: European Journal of Neurology. - : Wiley. - 1351-5101 .- 1468-1331. ; 30:5, s. 1352-1363
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: There are currently no biomarkers used to select cryptogenic stroke (CS) patients for monitoring with insertable cardiac monitors (ICMs), the most effective tool for diagnosing atrial fibrillation (AF) in CS. The purpose of this study was to assess clinically available biomarkers as predictors of AF.METHODS: Eligible CS and cryptogenic transient ischemic attack (TIA) patients underwent 12-month monitoring with ICMs, clinical follow-up, and biomarker sampling. Levels of cardiac and thromboembolic biomarkers, taken within 14 days from symptom onset, were compared between patients diagnosed with AF (n=74) during monitoring and those without AF (n=185). Receiver operating characteristic (ROC) curves were created. Biomarkers reaching area under ROC curve (AUC) ≥ 0.7 were dichotomized by finding optimal cut-off values and used in logistic regression establishing their predictive value for increased risk of AF in unadjusted and adjusted models.RESULTS: B-type natriuretic peptide (BNP), N-terminal pro-brain natriuretic peptide (NT-proBNP), creatine kinase, D-dimer, high-sensitivity cardiac Troponin I and T were significantly higher in the AF than non-AF group. BNP and NT-proBNP reached predefined AUC level, 0.755 and 0.725 respectively. Optimal cut-off values were 33.5 ng/L for BNP, and 87 ng/L for NT-proBNP. Regression analysis showed that NT-proBNP was a predictor of AF in both unadjusted, odds ratio (OR) 7.72 (95% confidence interval [CI] 3.16-18.87), and age and sex adjusted models, OR 4.82 (95% CI 1.79-12.96).CONCLUSION: Several clinically established biomarkers were associated with AF. NT-proBNP performed best as AF predictor and could be used for selecting patients for long-term monitoring with ICMs.
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| 3. |
- Zivadinovic, Nikola, et al.
(författare)
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Loss to 5-year follow-up in the population-based Telemark Study: risk factors and potential for bias
- 2023
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Ingår i: BMJ OPEN. - : BMJ. - 2044-6055. ; 13:3
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Tidskriftsartikel (refereegranskat)abstract
- ObjectivesThis study aimed to characterise participants lost to follow-up and identify possible factors associated with non-participation in a prospective population-based study of respiratory health in Norway. We also aimed to analyse the impact of potentially biased risk estimates associated with a high proportion of non-responders.DesignProspective 5-year follow-up study.SettingRandomly selected inhabitants from the general population of Telemark County in south-eastern Norway were invited to fill in a postal questionnaire in 2013. Responders in 2013 were followed-up in 2018.Participants16 099 participants aged 16-50 years completed the baseline study. 7958 responded at the 5-year follow-up, while 7723 did not.Main outcome measures chi(2) test was performed to compare demographic and respiratory health-related characteristics between those who participated in 2018 and those who were lost to follow-up. Adjusted multivariable logistic regression models were used to assess the relationship between loss to follow-up, background variables, respiratory symptoms, occupational exposure and interactions, and to analyse whether loss to follow-up leads to biased risk estimates.Results7723 (49%) participants were lost to follow-up. Loss to follow-up was significantly higher for male participants, those in the youngest age group (16-30 years), those in lowest education level category and among current smokers (all p<0.001). In multivariable logistic regression analysis, loss to follow-up was significantly associated with unemployment (OR 1.34, 95%CI 1.22 to 1.46), reduced work ability (1.48, 1.35 to 1.60), asthma (1.22, 1.10 to 1.35), being woken by chest tightness (1.22, 1.11 to 1.34) and chronic obstructive pulmonary disease (1.81, 1.30 to 2.52). Participants with more respiratory symptoms and exposure to vapour, gas, dust and fumes (VGDF) (1.07 to 1.00-1.15), low-molecular weight (LMW) agents (1.19, 1.00 to 1.41) and irritating agents (1.15, 1.05 to 1.26) were more likely to be lost to follow-up. We found no statistically significant association of wheezing and exposure to LMW agents for all participants at baseline (1.11, 0.90 to 1.36), responders in 2018 (1.12, 0.83 to 1.53) and those lost to follow-up (1.07, 0.81 to 1.42).ConclusionThe risk factors for loss to 5-year follow-up were comparable to those reported in other population-based studies and included younger age, male gender, current smoking, lower educational level and higher symptom prevalence and morbidity. We found that exposure to VGDF, irritating and LMW agents can be risk factors associated with loss to follow-up. Results suggest that loss to follow-up did not affect estimates of occupational exposure as a risk factor for respiratory symptoms.
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