Background: Genomic regions of autozygosity (ROA) arise when an individual is homozygous for haplotypes inherited identical-by-descent from ancestors shared by both parents. Over the past decade, they have gained importance for understanding evolutionary history and the genetic basis of complex diseases and traits. However, methods to infer ROA in dense genotype data have not evolved in step with advances in genome technology that now enable us to rapidly create large high-resolution genotype datasets, limiting our ability to investigate their constituent ROA patterns. Methods: We report a weighted likelihood approach for inferring ROA in dense genotype data that accounts for autocorrelation among genotyped positions and the possibilities of unobserved mutation and recombination events, and variability in the confidence of individual genotype calls in whole genome sequence (WGS) data. Results: Forward-time genetic simulations under two demographic scenarios that reflect situations where inbreeding and its effect on fitness are of interest suggest this approach is better powered than existing state-of-the-art methods to infer ROA at marker densities consistent with WGS and popular microarray genotyping platforms used in human and non-human studies. Moreover, we present evidence that suggests this approach is able to distinguish ROA arising via consanguinity from ROA arising via endogamy. Using subsets of The 1000 Genomes Project Phase 3 data we show that, relative to WGS, intermediate and long ROA are captured robustly with popular microarray platforms, while detection of short ROA is more variable and improves with marker density. Worldwide ROA patterns inferred from WGS data are found to accord well with those previously reported on the basis of microarray genotype data. Finally, we highlight the potential of this approach to detect genomic regions enriched for autozygosity signals in one group relative to another based upon comparisons of per-individual autozygosity likelihoods instead of inferred ROA frequencies. Conclusions: This weighted likelihood ROA inference approach can assist population-and disease-geneticists working with a wide variety of data types and species to explore ROA patterns and to identify genomic regions with differential ROA signals among groups, thereby advancing our understanding of evolutionary history and the role of recessive variation in phenotypic variation and disease.

BackgroundGenomic regions of autozygosity (ROA) arise when an individual is homozygous for haplotypes inherited identical-by-descent from ancestors shared by both parents. Over the past decade, they have gained importance for understanding evolutionary history and the genetic basis of complex diseases and traits. However, methods to infer ROA in dense genotype data have not evolved in step with advances in genome technology that now enable us to rapidly create large high-resolution genotype datasets, limiting our ability to investigate their constituent ROA patterns.MethodsWe report a weighted likelihood approach for inferring ROA in dense genotype data that accounts for autocorrelation among genotyped positions and the possibilities of unobserved mutation and recombination events, and variability in the confidence of individual genotype calls in whole genome sequence (WGS) data.ResultsForward-time genetic simulations under two demographic scenarios that reflect situations where inbreeding and its effect on fitness are of interest suggest this approach is better powered than existing state-of-the-art methods to infer ROA at marker densities consistent with WGS and popular microarray genotyping platforms used in human and non-human studies. Moreover, we present evidence that suggests this approach is able to distinguish ROA arising via consanguinity from ROA arising via endogamy. Using subsets of The 1000 Genomes Project Phase 3 data we show that, relative to WGS, intermediate and long ROA are captured robustly with popular microarray platforms, while detection of short ROA is more variable and improves with marker density. Worldwide ROA patterns inferred from WGS data are found to accord well with those previously reported on the basis of microarray genotype data. Finally, we highlight the potential of this approach to detect genomic regions enriched for autozygosity signals in one group relative to another based upon comparisons of per-individual autozygosity likelihoods instead of inferred ROA frequencies.ConclusionsThis weighted likelihood ROA inference approach can assist population- and disease-geneticists working with a wide variety of data types and species to explore ROA patterns and to identify genomic regions with differential ROA signals among groups, thereby advancing our understanding of evolutionary history and the role of recessive variation in phenotypic variation and disease.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-017-4312-3) contains supplementary material, which is available to authorized users.

BackgroundMicrosatellites---contiguous arrays of 2–6 base-pair motifs---have formed the cornerstone of population-genetic studies for over two decades. Their genotype data typically takes the form of PCR fragment lengths obtained using locus-specific primer pairs to amplify the genomic region encompassing the microsatellite. Recently, we reported a dataset of 5,795 human and 84 chimpanzee individuals with genotypes at 246 human-derived autosomal microsatellites as a resource to facilitate interspecies comparisons. A major assumption underlying this dataset is that PCR amplicons at orthologous microsatellites are commensurable between species.ResultsWe find this assumption to be frequently incorrect owing to discordance in microsatellite organization and variability, as well as nontrivial length imbalances caused by small species-specific indels in microsatellite flanking sequences. Converting PCR fragment lengths into the repeat numbers they represent at 138 microsatellites whose organization and variability was found to be highly similar in both species, we show that interspecies incommensurability among PCR amplicons can inflate FST and DPS estimates by up to 10.6%. Separate investigations of determinants of microsatellite variability in humans and chimpanzees uncover similar patterns with mean and maximum numbers of repeats, as well as numbers and ranges of distinct alleles, all important factors in predicting heterozygosity. In contrast, across microsatellites, numbers of repeats were significantly smaller in chimpanzees than in humans, while numbers and ranges of distinct alleles were instead larger.ConclusionsOur findings have fundamental implications for interspecies comparisons using microsatellites and offer new opportunities for more accurate comparisons of patterns of human and chimpanzee genetic variation in numerous areas of application.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2164-15-990) contains supplementary material, which is available to authorized users.

BACKGROUND: Sepsis is a leading cause of mortality among critically ill patients and is associated with both systemic inflammation and up-regulation of coagulation. In the translational sub-study of the HALO (Heparin AnticoaguLation to improve Outcomes in septic shock) pilot trial, we evaluated the mechanisms by which unfractionated heparin (UFH) may reduce inflammation and coagulation in patients with septic shock. METHODS: In this multicenter pilot randomized trial of 69 patients diagnosed with septic shock, we evaluated the feasibility of administering therapeutic dose intravenous UFH (18 IU/kg/hr) compared to thromboprophylactic subcutaneous dalteparin (5000 IU daily). Blood samples were collected on days 1 (baseline prior to study infusion), 2, 3, 5, and 7. We evaluated coagulation using assays for protein C, activated protein C, thrombin-antithrombin (TAT), thrombin generation, clot lysis, plasminogen activator inhibitor-1 (PAI-1) and cell-free DNA (cf-DNA). Systematic inflammation was evaluated by measuring inflammatory cytokines (interleukin (IL)-6, IL-8, IL-10, and IL-17). RESULTS: The mean age of the study population was 61 years, of whom 43% were male. Thirty two patients (46%) were randomized to receive unfractionated heparin while 37 (54%) received dalteparin. The baseline mean aggregate Acute Physiology and Chronic Health Evaluation II (APACHE II) score was 25 ± 7.8, and Multiple Organ Dysfunction Score (MODS) 5.6 ± 2.38. Baseline laboratory testing (coagulation assays and inflammatory cytokines) was not statistically different between UFH vs. LMWH treated patients. On day 2, the median clot lysis time in UFH-treated patients compared to those receiving dalteparin was significantly decreased [6630 (IQR 0 - 14156) seconds vs. 9615 (IQR 8209 - 11018) seconds; p = 0.008] (Figure 1). UFH administration was associated with increased protein C levels [66.4% of normal (IQR 9.9 - 122.9) vs. 41.1% of normal (IQR 4.8 - 77.4); p = 0.02], and reduced thrombin generation of 0 (IQR 0 - 1725) units/min vs. 3393 (IQR 0 - 8519) units/min; p<0.001]. On day 2, we observed no differences between thrombin-antithrombin complex (TAT), activated protein C, plasminogen activator inhibitor-1 (PAI-1) or cell-free DNA (cf-DNA). Similarly, there were no differences between treatment groups in inflammatory markers, including IL-6, IL-8, IL-10 or IL-17. Analysis thus far is limited to samples collected on days 1 and 2; day 3-7 analyses are ongoing. CONCLUSION: In patients diagnosed with septic shock, IV UFH reduces thrombin generation, shortens clot lysis time and improves endogenous protein C levels compared to dalteparin administered for thromboprophylaxis. Analyses for samples obtained on days 3, 5 and 7 are ongoing. These preliminary data provide a biologic rational for the use of heparin in sepsis. Figure 1. Differences in clot lysis, protein C and thrombin generation in patients treated with UFH vs. LMWH. UFH is associated with reduced thrombin generation, improved Protein C levels, and reduced clot lysis time. Figure 1. Differences in clot lysis, protein C and thrombin generation in patients treated with UFH vs. LMWH. UFH is associated with reduced thrombin generation, improved Protein C levels, and reduced clot lysis time. Disclosures No relevant conflicts of interest to declare.

Early warning scores (EWS) and similar decision aids that rely on patient vital signs to predict patient risk of deterioration may play an important role in mitigating costs incurred as a result of the need to escalate care. Their use on medical and surgical wards as well as in emergency departments has become increasingly common. In these settings EWSs show potential in being able to alert medical staff to patients at high risk allowing for early intervention and increased monitoring in their care. Beyond the predictive ability of EWSs, factors such as institutional capacity, patient characteristics, and staff training on EWS protocols may also play an important role in determining the effectiveness, and consequently the cost effectiveness, of EWSs. If executed appropriately, the preventive opportunities created by EWSs may have substantial benefits for both patients and the healthcare system as a whole. Prudent implementation is therefore essential when introducing new EWSs and future assessments should evaluate these components as well.

Due to a steady rise in the number of refugees accepted by Canada in recent years, the need for government funding to cover the health care needs of this population has similarly increased. Despite this increased need, government funding via the Interim Federal Health Program (IFHP) was cut dramatically in 2012 by the Conservative government. In 2016, the Liberal government restored full refugee health care coverage. This article provides an overview of refugee health care funding decisions in Canada over the past decade, and explores the impact that such decisions have on the health outcomes of this population. Furthermore, this article compares and contrasts refugee health care funding in Canada with that in other world regions with high refugee influx. Key potential areas for funding improvement are identified.

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