The precision medicine approach of tailoring treatment to the individual characteristics of each patient or subgroup has been a great success in monogenic diabetes subtypes, MODY and neonatal ...diabetes. This review examines what has led to the success of a precision medicine approach in monogenic diabetes (precision diabetes) and outlines possible implications for type 2 diabetes. For monogenic diabetes, the molecular genetics can define discrete aetiological subtypes that have profound implications on diabetes treatment and can predict future development of associated clinical features, allowing early preventative or supportive treatment. In contrast, type 2 diabetes has overlapping polygenic susceptibility and underlying aetiologies, making it difficult to define discrete clinical subtypes with a dramatic implication for treatment. The implementation of precision medicine in neonatal diabetes was simple and rapid as it was based on single clinical criteria (diagnosed <6 months of age). In contrast, in MODY it was more complex and slow because of the lack of single criteria to identify patients, but it was greatly assisted by the development of a diagnostic probability calculator and associated smartphone app. Experience in monogenic diabetes suggests that successful adoption of a precision diabetes approach in type 2 diabetes will require simple, quick, easily accessible stratification that is based on a combination of routine clinical data, rather than relying on newer technologies. Analysing existing clinical data from routine clinical practice and trials may provide early success for precision medicine in type 2 diabetes.
To describe the relationship between type 2 diabetes and all-cause mortality among adults with coronavirus disease 2019 (COVID-19) in the critical care setting.
This was a nationwide retrospective ...cohort study in people admitted to hospital in England with COVID-19 requiring admission to a high dependency unit (HDU) or intensive care unit (ICU) between 1 March 2020 and 27 July 2020. Cox proportional hazards models were used to estimate 30-day in-hospital all-cause mortality associated with type 2 diabetes, with adjustment for age, sex, ethnicity, obesity, and other major comorbidities (chronic respiratory disease, asthma, chronic heart disease, hypertension, immunosuppression, chronic neurological disease, chronic renal disease, and chronic liver disease).
A total of 19,256 COVID-19-related HDU and ICU admissions were included in the primary analysis, including 13,809 HDU (mean age 70 years) and 5,447 ICU (mean age 58 years) admissions. Of those admitted, 3,524 (18.3%) had type 2 diabetes and 5,077 (26.4%) died during the study period. Patients with type 2 diabetes were at increased risk of death (adjusted hazard ratio aHR 1.23 95% CI 1.14, 1.32), and this result was consistent in HDU and ICU subsets. The relative mortality risk associated with type 2 diabetes decreased with higher age (age 18-49 years aHR 1.50 95% CI 1.05, 2.15, age 50-64 years 1.29 1.10, 1.51, and age ≥65 years 1.18 1.09, 1.29;
value for age-type 2 diabetes interaction = 0.002).
Type 2 diabetes may be an independent prognostic factor for survival in people with severe COVID-19 requiring critical care treatment, and in this setting the risk increase associated with type 2 diabetes is greatest in younger people.
Identifying copy number variants (CNVs) can provide diagnoses to patients and provide important biological insights into human health and disease. Current exome and targeted sequencing approaches ...cannot detect clinically and biologically-relevant CNVs outside their target area. We present SavvyCNV, a tool which uses off-target read data from exome and targeted sequencing data to call germline CNVs genome-wide. Up to 70% of sequencing reads from exome and targeted sequencing fall outside the targeted regions. We have developed a new tool, SavvyCNV, to exploit this 'free data' to call CNVs across the genome. We benchmarked SavvyCNV against five state-of-the-art CNV callers using truth sets generated from genome sequencing data and Multiplex Ligation-dependent Probe Amplification assays. SavvyCNV called CNVs with high precision and recall, outperforming the five other tools at calling CNVs genome-wide, using off-target or on-target reads from targeted panel and exome sequencing. We then applied SavvyCNV to clinical samples sequenced using a targeted panel and were able to call previously undetected clinically-relevant CNVs, highlighting the utility of this tool within the diagnostic setting. SavvyCNV outperforms existing tools for calling CNVs from off-target reads. It can call CNVs genome-wide from targeted panel and exome data, increasing the utility and diagnostic yield of these tests. SavvyCNV is freely available at https://github.com/rdemolgen/SavvySuite.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
•Ab-initio investigation of interstitial B doping in ordered phases of binary Fe-Pd alloys is performed.•Magnetic moments on Fe and Pd atoms are suppressed locally around the dopant atom.•For FePd ...systems, the MAE increases up to three times (0.215 to 0.636 meV/. f.u.) for 12.5 atomic % of B doping.•For Fe3Pd5 system, the MAE enhances drastically up to seven times (−0.161 to −1.136 meV/f.u.) for 12.5 atomic % of B.
Magnetic properties of L10-type tetragonal FePd, L12-type cubic FePd3, CuZr2-type tetragonal FePd2 and Pt5Ga3-type orthorhombic Fe3Pd5 binary alloys with interstitial boron doping are investigated using supercell approach within first principles density functional calculations for various doping concentrations. The magnetic moments around dopant sites are suppressed slightly both on Fe and Pd atoms whereas the per-unit magnetization almost remains unaffected in the supercell. Magnetocrystalline anisotropy energy enhances by a considerable amount and the Curie temperature decreases but remains well above room temperature. Overall, we report the magnetic properties of various Fe-Pd phases with boron doping with slight compromise in magnetization and considerable gain in magnetic anisotropy energy.
The increasing availability of DNA sequence data and access to sophisticated bioinformatic algorithms mean that an unbiased bioinformatics-based assessment of the predicted impact of a genomic ...variant is rapidly available. Here, Ellard et al argue that such bioinformatic assessments are not equivalent to an expert diagnostic interpretation and may be misleading in both research and clinical care.
Clinical exome sequencing routinely identifies missense variants in disease-related genes, but functional characterization is rarely undertaken, leading to diagnostic uncertainty. For example, ...mutations in PPARG cause Mendelian lipodystrophy and increase risk of type 2 diabetes (T2D). Although approximately 1 in 500 people harbor missense variants in PPARG, most are of unknown consequence. To prospectively characterize PPARγ variants, we used highly parallel oligonucleotide synthesis to construct a library encoding all 9,595 possible single-amino acid substitutions. We developed a pooled functional assay in human macrophages, experimentally evaluated all protein variants, and used the experimental data to train a variant classifier by supervised machine learning. When applied to 55 new missense variants identified in population-based and clinical sequencing, the classifier annotated 6 variants as pathogenic; these were subsequently validated by single-variant assays. Saturation mutagenesis and prospective experimental characterization can support immediate diagnostic interpretation of newly discovered missense variants in disease-related genes.
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