57 research outputs found
Clinical Heterogeneity in Patients With FOXP3 Mutations Presenting With Permanent Neonatal Diabetes
OBJECTIVE—Immune dysregulation, polyendocrinopathy, enteropathy, X-linked (IPEX) syndrome is caused by FOXP3 mutations. We aimed to determine the prevalence, genetics, and clinical phenotype of FOXP3 mutations in a large cohort with permanent neonatal diabetes (PNDM)
Responses of Southern Ocean seafloor habitats and communities to global and local drivers of change
Knowledge of life on the Southern Ocean seafloor has substantially grown since the beginning of this century with increasing ship-based surveys and regular monitoring sites, new technologies and greatly enhanced data sharing. However, seafloor habitats and their communities exhibit high spatial variability and heterogeneity that challenges the way in which we assess the state of the Southern Ocean benthos on larger scales. The Antarctic shelf is rich in diversity compared with deeper water areas, important for storing carbon (“blue carbon”) and provides habitat for commercial fish species. In this paper, we focus on the seafloor habitats of the Antarctic shelf, which are vulnerable to drivers of change including increasing ocean temperatures, iceberg scour, sea ice melt, ocean acidification, fishing pressures, pollution and non-indigenous species. Some of the most vulnerable areas include the West Antarctic Peninsula, which is experiencing rapid regional warming and increased iceberg-scouring, subantarctic islands and tourist destinations where human activities and environmental conditions increase the potential for the establishment of non-indigenous species and active fishing areas around South Georgia, Heard and MacDonald Islands. Vulnerable species include those in areas of regional warming with low thermal tolerance, calcifying species susceptible to increasing ocean acidity as well as slow-growing habitat-forming species that can be damaged by fishing gears e.g., sponges, bryozoan, and coral species. Management regimes can protect seafloor habitats and key species from fishing activities; some areas will need more protection than others, accounting for specific traits that make species vulnerable, slow growing and long-lived species, restricted locations with optimum physiological conditions and available food, and restricted distributions of rare species. Ecosystem-based management practices and long-term, highly protected areas may be the most effective tools in the preservation of vulnerable seafloor habitats. Here, we focus on outlining seafloor responses to drivers of change observed to date and projections for the future. We discuss the need for action to preserve seafloor habitats under climate change, fishing pressures and other anthropogenic impacts
Spin fluctuations in nearly magnetic metals from ab-initio dynamical spin susceptibility calculations:application to Pd and Cr95V5
We describe our theoretical formalism and computational scheme for making
ab-initio calculations of the dynamic paramagnetic spin susceptibilities of
metals and alloys at finite temperatures. Its basis is Time-Dependent Density
Functional Theory within an electronic multiple scattering, imaginary time
Green function formalism. Results receive a natural interpretation in terms of
overdamped oscillator systems making them suitable for incorporation into spin
fluctuation theories. For illustration we apply our method to the nearly
ferromagnetic metal Pd and the nearly antiferromagnetic chromium alloy Cr95V5.
We compare and contrast the spin dynamics of these two metals and in each case
identify those fluctuations with relaxation times much longer than typical
electronic `hopping times'Comment: 21 pages, 9 figures. To appear in Physical Review B (July 2000
Practical Indicators for Risk of Airborne Transmission in Shared Indoor Environments and Their Application to COVID-19 Outbreaks
Some infectious diseases, including COVID-19, can undergo airborne transmission. This may happen at close proximity, but as time indoors increases, infections can occur in shared room air despite distancing. We propose two indicators of infection risk for this situation, that is, relative risk parameter (Hr) and risk parameter (H). They combine the key factors that control airborne disease transmission indoors: viruscontaining aerosol generation rate, breathing flow rate, masking and its quality, ventilation and aerosol-removal rates, number of occupants, and duration of exposure. COVID-19 outbreaks show a clear trend that is consistent with airborne infection and enable recommendations to minimize transmission risk. Transmission in typical prepandemic indoor spaces is highly sensitive to mitigation efforts. Previous outbreaks of measles, influenza, and tuberculosis were also assessed. Measles outbreaks occur at much lower risk parameter values than COVID-19, while tuberculosis outbreaks are observed at higher risk parameter values. Because both diseases are accepted as airborne, the fact that COVID-19 is less contagious than measles does not rule out airborne transmission. It is important that future outbreak reports include information on masking, ventilation and aerosol-removal rates, number of occupants, and duration of exposure, to investigate airborne transmission
Evaluation of models of sequestration flow in coronary arteries—Physiology versus anatomy?
Background:
Myocardial ischaemia results from insufficient coronary blood flow. Computed virtual fractional flow reserve (vFFR) allows quantification of proportional flow loss without the need for invasive pressure-wire testing. In the current study, we describe a novel, conductivity model of side branch flow, referred to as ‘leak’. This leak model is a function of taper and local pressure, the latter of which may change radically when focal disease is present. This builds upon previous techniques, which either ignore side branch flow, or rely purely on anatomical factors. This study aimed to describe a new, conductivity model of side branch flow and compare this with established anatomical models.
Methods and results:
The novel technique was used to quantify vFFR, distal absolute flow (Qd) and microvascular resistance (CMVR) in 325 idealised 1D models of coronary arteries, modelled from invasive clinical data. Outputs were compared to an established anatomical model of flow. The conductivity model correlated and agreed with the reference model for vFFR (r = 0.895, p
<
0.0001; +0.02, 95% CI 0.00 to + 0.22), Qd (r = 0.959, p
<
0.0001; −5.2 mL/min, 95% CI −52.2 to +13.0) and CMVR (r = 0.624, p
<
0.0001; +50 Woods Units, 95% CI −325 to +2549).
Conclusion:
Agreement between the two techniques was closest for vFFR, with greater proportional differences seen for Qd and CMVR. The conductivity function assumes vessel taper was optimised for the healthy state and that CMVR was not affected by local disease. The latter may be addressed with further refinement of the technique or inferred from complementary image data.The conductivity technique may represent a refinement of current techniques for modelling coronary side-branch flow. Further work is needed to validate the technique against invasive clinical data
A new strategy for enhancing imputation quality of rare variants from next-generation sequencing data via combining SNP and exome chip data
Background: Rare variants have gathered increasing attention as a possible alternative source of missing heritability. Since next generation sequencing technology is not yet cost-effective for large-scale genomic studies, a widely used alternative approach is imputation. However, the imputation approach may be limited by the low accuracy of the imputed rare variants. To improve imputation accuracy of rare variants, various approaches have been suggested, including increasing the sample size of the reference panel, using sequencing data from study-specific samples (i.e., specific populations), and using local reference panels by genotyping or sequencing a subset of study samples. While these approaches mainly utilize reference panels, imputation accuracy of rare variants can also be increased by using exome chips containing rare variants. The exome chip contains 250 K rare variants selected from the discovered variants of about 12,000 sequenced samples. If exome chip data are available for previously genotyped samples, the combined approach using a genotype panel of merged data, including exome chips and SNP chips, should increase the imputation accuracy of rare variants. Results: In this study, we describe a combined imputation which uses both exome chip and SNP chip data simultaneously as a genotype panel. The effectiveness and performance of the combined approach was demonstrated using a reference panel of 848 samples constructed using exome sequencing data from the T2D-GENES consortium and 5,349 sample genotype panels consisting of an exome chip and SNP chip. As a result, the combined approach increased imputation quality up to 11 %, and genomic coverage for rare variants up to 117.7 % (MAF < 1 %), compared to imputation using the SNP chip alone. Also, we investigated the systematic effect of reference panels on imputation quality using five reference panels and three genotype panels. The best performing approach was the combination of the study specific reference panel and the genotype panel of combined data. Conclusions: Our study demonstrates that combined datasets, including SNP chips and exome chips, enhances both the imputation quality and genomic coverage of rare variants
Refined histopathological predictors of BRCA1 and BRCA2 mutation status: A large-scale analysis of breast cancer characteristics from the BCAC, CIMBA, and ENIGMA consortia
Introduction: The distribution of histopathological features of invasive breast tumors in BRCA1 or BRCA2 germline mutation carriers differs from that of individuals with no known mutation. Histopathological features thus have utility for mutation prediction, including statistical modeling to assess pathogenicity of BRCA1 or BRCA2 variants of uncertain clinical significance. We analyzed large pathology datasets accrued by the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA) and the Breast Cancer Association Consortium (BCAC) to reassess histopathological predictors of BRCA1 and BRCA2 mutation status, and provide robust likelihood ratio (LR) estimates for statistical modeling. Methods: Selection criteria for study/center inclusion were estrogen receptor (ER) status or grade data available for invasive breast cancer diagnosed younger than 70 years. The dataset included 4,477 BRCA1 mutation carriers, 2,565 BRCA2 mutation carriers, and 47,565 BCAC breast cancer cases. Country-stratified estimates of the
A Solve-RD ClinVar-based reanalysis of 1522 index cases from ERN-ITHACA reveals common pitfalls and misinterpretations in exome sequencing
Purpose
Within the Solve-RD project (https://solve-rd.eu/), the European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies aimed to investigate whether a reanalysis of exomes from unsolved cases based on ClinVar annotations could establish additional diagnoses. We present the results of the “ClinVar low-hanging fruit” reanalysis, reasons for the failure of previous analyses, and lessons learned.
Methods
Data from the first 3576 exomes (1522 probands and 2054 relatives) collected from European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies was reanalyzed by the Solve-RD consortium by evaluating for the presence of single-nucleotide variant, and small insertions and deletions already reported as (likely) pathogenic in ClinVar. Variants were filtered according to frequency, genotype, and mode of inheritance and reinterpreted.
Results
We identified causal variants in 59 cases (3.9%), 50 of them also raised by other approaches and 9 leading to new diagnoses, highlighting interpretation challenges: variants in genes not known to be involved in human disease at the time of the first analysis, misleading genotypes, or variants undetected by local pipelines (variants in off-target regions, low quality filters, low allelic balance, or high frequency).
Conclusion
The “ClinVar low-hanging fruit” analysis represents an effective, fast, and easy approach to recover causal variants from exome sequencing data, herewith contributing to the reduction of the diagnostic deadlock
The global burden of cancer attributable to risk factors, 2010–19: a systematic analysis for the Global Burden of Disease Study 2019
BACKGROUND: Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. METHODS: The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk–outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented. FINDINGS: Globally, in 2019, the risk factors included in this analysis accounted for 4·45 million (95% uncertainty interval 4·01–4·94) deaths and 105 million (95·0–116) DALYs for both sexes combined, representing 44·4% (41·3–48·4) of all cancer deaths and 42·0% (39·1–45·6) of all DALYs. There were 2·88 million (2·60–3·18) risk-attributable cancer deaths in males (50·6% [47·8–54·1] of all male cancer deaths) and 1·58 million (1·36–1·84) risk-attributable cancer deaths in females (36·3% [32·5–41·3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20·4% (12·6–28·4) and DALYs by 16·8% (8·8–25·0), with the greatest percentage increase in metabolic risks (34·7% [27·9–42·8] and 33·3% [25·8–42·0]). INTERPRETATION: The leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden
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