Non-disjunction of chromosome 13

We performed a molecular study with 21 microsatellites on a sample of 82 trisomy 13 conceptuses, the largest number of cases studied to date. The parental origin was determined in every case and in 89% the extra chromosome 13 was of maternal origin with an almost equal number of maternal MI and MII errors. The latter finding is unique among human autosomal trisomies, where maternal MI (trisomies 15, 16, 21, 22) or MII (trisomy 18) errors dominate. Of the nine paternally derived cases five were of MII origin but none arose from MI errors. There was some evidence for elevated maternal age in cases with maternal meiotic origin for liveborn infants. Maternal and paternal ages were elevated in cases with paternal meiotic origin. This is in contrast to results from a similar study of non-disjunction of trisomy 21 where paternal but not maternal age was elevated. We find clear evidence for reduced recombination in both maternal MI and MII errors and the former is associated with a significant number of tetrads (33%) that are nullichiasmate, which do not appear to be a feature of normal chromosome 13 meiosis. This study supports the evidence for subtle chromosome-specific influences on the mechanisms that determine non-disjunction of human chromosomes, consistent with the diversity of findings for other trisomie

EcoTILLING in Capsicum species: searching for new virus resistances

<p>Abstract</p> <p>Background</p> <p>The EcoTILLING technique allows polymorphisms in target genes of natural populations to be quickly analysed or identified and facilitates the screening of genebank collections for desired traits. We have developed an EcoTILLING platform to exploit <it>Capsicum </it>genetic resources. A perfect example of the utility of this EcoTILLING platform is its application in searching for new virus-resistant alleles in <it>Capsicum </it>genus. Mutations in translation initiation factors (eIF4E, eIF(iso)4E, eIF4G and eIF(iso)4G) break the cycle of several RNA viruses without affecting the plant life cycle, which makes these genes potential targets to screen for resistant germplasm.</p> <p>Results</p> <p>We developed and assayed a cDNA-based EcoTILLING platform with 233 cultivated accessions of the genus <it>Capsicum</it>. High variability in the coding sequences of the <it>eIF4E </it>and <it>eIF(iso)4E </it>genes was detected using the cDNA platform. After sequencing, 36 nucleotide changes were detected in the CDS of <it>eIF4E </it>and 26 in <it>eIF(iso)4E</it>. A total of 21 <it>eIF4E </it>haplotypes and 15 <it>eIF(iso)4E </it>haplotypes were identified. To evaluate the functional relevance of this variability, 31 possible eIF4E/eIF(iso)4E combinations were tested against <it>Potato virus Y</it>. The results showed that five new <it>eIF4E </it>variants (<it>pvr2¹⁰</it>, <it>pvr2¹¹</it>, <it>pvr2¹²</it>, <it>pvr2¹³</it>and <it>pvr2¹⁴</it>) were related to PVY-resistance responses.</p> <p>Conclusions</p> <p>EcoTILLING was optimised in different <it>Capsicum </it>species to detect allelic variants of target genes. This work is the first to use cDNA instead of genomic DNA in EcoTILLING. This approach avoids intronic sequence problems and reduces the number of reactions. A high level of polymorphism has been identified for initiation factors, showing the high genetic variability present in our collection and its potential use for other traits, such as genes related to biotic or abiotic stresses, quality or production. Moreover, the new <it>eIF4E </it>and <it>eIF(iso)4E </it>alleles are an excellent collection for searching for new resistance against other RNA viruses.</p

Suggestion for linkage of chromosome 1p35.2 and 3q28 to plasma adiponectin concentrations in the GOLDN Study

<p>Abstract</p> <p>Background</p> <p>Adiponectin is inversely associated with obesity, insulin resistance, and atherosclerosis, but little is known about the genetic pathways that regulate the plasma level of this protein. To find novel genes that influence circulating levels of adiponectin, a genome-wide linkage scan was performed on plasma adiponectin concentrations before and after 3 weeks of treatment with fenofibrate (160 mg daily) in the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) Study. We studied Caucasian individuals (n = 1121) from 190 families in Utah and Minnesota. Of these, 859 individuals from 175 families had both baseline and post-fenofibrate treatment measurements for adiponectin. Plasma adiponectin concentrations were measured with an ELISA assay. All participants were typed for microsatellite markers included in the Marshfield Mammalian Genotyping Service marker set 12, which includes 407 markers spaced at approximately 10 cM regions across the genome. Variance components analysis was used to estimate heritability and to perform genome-wide scans. Adiponectin was adjusted for age, sex, and field center. Additional models also included BMI adjustment.</p> <p>Results</p> <p>Baseline and post-fenofibrate adiponectin measurements were highly correlated (r = 0.95). Suggestive (LOD > 2) peaks were found on chromosomes 1p35.2 and 3q28 (near the location of the adiponectin gene).</p> <p>Conclusion</p> <p>Two candidate genes, <it>IL22RA1 </it>and <it>IL28RA</it>, lie under the chromosome 1 peak; further analyses are needed to identify the specific genetic variants in this region that influence circulating adiponectin concentrations.</p

Establishing a hepatitis C continuum of care among HIV/hepatitis C virus-coinfected individuals in EuroSIDA

Objectives The aim of the study was to establish a methodology for evaluating the hepatitis C continuum of care in HIV/hepatitis C virus (HCV)-coinfected individuals and to characterize the continuum in Europe on 1 January 2015, prior to widespread access to direct-acting antiviral (DAA) therapy. Methods Stages included in the continuum were as follows: anti-HCV antibody positive, HCV RNA tested, currently HCV RNA positive, ever HCV RNA positive, ever received HCV treatment, completed HCV treatment, follow-up HCV RNA test, and cure. Sustained virological response (SVR) could only be assessed for those with a follow-up HCV RNA test and was defined as a negative HCV RNA result measured > 12 or 24 weeks after stopping treatment. Results Numbers and percentages for the stages of the HCV continuum of care were as follows: anti-HCV positive (n = 5173), HCV RNA tested (4207 of 5173; 81.3%), currently HCV RNA positive (3179 of 5173; 61.5%), ever HCV RNA positive (n = 3876), initiated HCV treatment (1693 of 3876; 43.7%), completed HCV treatment (1598 of 3876; 41.2%), follow-up HCV RNA test to allow SVR assessment (1195 of 3876; 30.8%), and cure (629 of 3876; 16.2%). The proportion that achieved SVR was 52.6% (629 of 1195). There were significant differences between regions at each stage of the continuum (P <0.0001). Conclusions In the proposed HCV continuum of care for HIV/HCV-coinfected individuals, we found major gaps at all stages, with almost 20% of anti-HCV-positive individuals having no documented HCV RNA test and a low proportion achieving SVR, in the pre-DAA era.Peer reviewe

Why Are Outcomes Different for Registry Patients Enrolled Prospectively and Retrospectively? Insights from the Global Anticoagulant Registry in the FIELD-Atrial Fibrillation (GARFIELD-AF).

Background: Retrospective and prospective observational studies are designed to reflect real-world evidence on clinical practice, but can yield conflicting results. The GARFIELD-AF Registry includes both methods of enrolment and allows analysis of differences in patient characteristics and outcomes that may result. Methods and Results: Patients with atrial fibrillation (AF) and ≥1 risk factor for stroke at diagnosis of AF were recruited either retrospectively (n = 5069) or prospectively (n = 5501) from 19 countries and then followed prospectively. The retrospectively enrolled cohort comprised patients with established AF (for a least 6, and up to 24 months before enrolment), who were identified retrospectively (and baseline and partial follow-up data were collected from the emedical records) and then followed prospectively between 0-18 months (such that the total time of follow-up was 24 months; data collection Dec-2009 and Oct-2010). In the prospectively enrolled cohort, patients with newly diagnosed AF (≤6 weeks after diagnosis) were recruited between Mar-2010 and Oct-2011 and were followed for 24 months after enrolment. Differences between the cohorts were observed in clinical characteristics, including type of AF, stroke prevention strategies, and event rates. More patients in the retrospectively identified cohort received vitamin K antagonists (62.1% vs. 53.2%) and fewer received non-vitamin K oral anticoagulants (1.8% vs . 4.2%). All-cause mortality rates per 100 person-years during the prospective follow-up (starting the first study visit up to 1 year) were significantly lower in the retrospective than prospectively identified cohort (3.04 [95% CI 2.51 to 3.67] vs . 4.05 [95% CI 3.53 to 4.63]; p = 0.016). Conclusions: Interpretations of data from registries that aim to evaluate the characteristics and outcomes of patients with AF must take account of differences in registry design and the impact of recall bias and survivorship bias that is incurred with retrospective enrolment. Clinical Trial Registration: - URL: http://www.clinicaltrials.gov . Unique identifier for GARFIELD-AF (NCT01090362)

Improved risk stratification of patients with atrial fibrillation: an integrated GARFIELD-AF tool for the prediction of mortality, stroke and bleed in patients with and without anticoagulation.

OBJECTIVES: To provide an accurate, web-based tool for stratifying patients with atrial fibrillation to facilitate decisions on the potential benefits/risks of anticoagulation, based on mortality, stroke and bleeding risks. DESIGN: The new tool was developed, using stepwise regression, for all and then applied to lower risk patients. C-statistics were compared with CHA2DS2-VASc using 30-fold cross-validation to control for overfitting. External validation was undertaken in an independent dataset, Outcome Registry for Better Informed Treatment of Atrial Fibrillation (ORBIT-AF). PARTICIPANTS: Data from 39 898 patients enrolled in the prospective GARFIELD-AF registry provided the basis for deriving and validating an integrated risk tool to predict stroke risk, mortality and bleeding risk. RESULTS: The discriminatory value of the GARFIELD-AF risk model was superior to CHA2DS2-VASc for patients with or without anticoagulation. C-statistics (95% CI) for all-cause mortality, ischaemic stroke/systemic embolism and haemorrhagic stroke/major bleeding (treated patients) were: 0.77 (0.76 to 0.78), 0.69 (0.67 to 0.71) and 0.66 (0.62 to 0.69), respectively, for the GARFIELD-AF risk models, and 0.66 (0.64-0.67), 0.64 (0.61-0.66) and 0.64 (0.61-0.68), respectively, for CHA2DS2-VASc (or HAS-BLED for bleeding). In very low to low risk patients (CHA2DS2-VASc 0 or 1 (men) and 1 or 2 (women)), the CHA2DS2-VASc and HAS-BLED (for bleeding) scores offered weak discriminatory value for mortality, stroke/systemic embolism and major bleeding. C-statistics for the GARFIELD-AF risk tool were 0.69 (0.64 to 0.75), 0.65 (0.56 to 0.73) and 0.60 (0.47 to 0.73) for each end point, respectively, versus 0.50 (0.45 to 0.55), 0.59 (0.50 to 0.67) and 0.55 (0.53 to 0.56) for CHA2DS2-VASc (or HAS-BLED for bleeding). Upon validation in the ORBIT-AF population, C-statistics showed that the GARFIELD-AF risk tool was effective for predicting 1-year all-cause mortality using the full and simplified model for all-cause mortality: C-statistics 0.75 (0.73 to 0.77) and 0.75 (0.73 to 0.77), respectively, and for predicting for any stroke or systemic embolism over 1 year, C-statistics 0.68 (0.62 to 0.74). CONCLUSIONS: Performance of the GARFIELD-AF risk tool was superior to CHA2DS2-VASc in predicting stroke and mortality and superior to HAS-BLED for bleeding, overall and in lower risk patients. The GARFIELD-AF tool has the potential for incorporation in routine electronic systems, and for the first time, permits simultaneous evaluation of ischaemic stroke, mortality and bleeding risks. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifier for GARFIELD-AF (NCT01090362) and for ORBIT-AF (NCT01165710)