298 research outputs found

    Heritability estimates of the Big Five personality traits based on common genetic variants

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    According to twin studies, the Big Five personality traits have substantial heritable components explaining 40–60% of the variance, but identification of associated genetic variants has remained elusive. Consequently, knowledge regarding the molecular genetic architecture of personality and to what extent it is shared across the different personality traits is limited. Using genomic-relatedness-matrix residual maximum likelihood analysis (GREML), we here estimated the heritability of the Big Five personality factors (extraversion, agreeableness, conscientiousness, neuroticism and openness for experience) in a sample of 5011 European adults from 527 469 single-nucleotide polymorphisms across the genome. We tested for the heritability of each personality trait, as well as for the genetic overlap between the personality factors. We found significant and substantial heritability estimates for neuroticism (15%, s.e.=0.08, P=0.04) and openness (21%, s.e.=0.08, P<0.01), but not for extraversion, agreeableness and conscientiousness. The bivariate analyses showed that the variance explained by common variants entirely overlapped between neuroticism and openness (rG=1.00, P <0.001), despite low phenotypic correlation (r=−0.09, P <0.001), suggesting that the remaining unique heritability may be determined by rare or structural variants. As far as we are aware of, this is the first study estimating the shared and unique heritability of all Big Five personality traits using the GREML approach. Findings should be considered exploratory and suggest that detectable heritability estimates based on common variants is shared between neuroticism and openness to experiences

    Сетевая система контроля технологического процесса выращивания полупроводниковых кристаллов и тонких пленок

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    Экспериментальное моделирование аппаратно-программного обеспечения показало достаточную надежность работы системы и значительное уменьшение трудоемкости контроля и управления параметрами технологического процесса

    How can schistosome circulating antigen assays be best applied for diagnosing male genital schistosomiasis (MGS): an appraisal using exemplar MGS cases from a longitudinal cohort study among fishermen on the south shoreline of Lake Malawi

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    We provide an update on diagnostic methods for the detection of urogenital schistosomiasis (UGS) in men and highlight that satisfactory urine-antigen diagnostics for UGS lag much behind that for intestinal schistosomiasis, where application of a urine-based point-of-care strip assay, the circulating cathodic antigen (CCA) test, is now advocated. Making specific reference to male genital schistosomiasis (MGS), we place greater emphasis on parasitological detection methods and clinical assessment of internal genitalia with ultrasonography. Unlike the advances made in defining a clinical standard protocol for female genital schistosomiasis, MGS remains inadequately defined. Whilst urine filtration with microscopic examination for ova of Schistosoma haematobium is a convenient but error-prone proxy of MGS, we describe a novel low-cost sampling and direct visualization method for the enumeration of ova in semen. Using exemplar clinical cases of MGS from our longitudinal cohort study among fishermen along the shoreline of Lake Malawi, the portfolio of diagnostic needs is appraised including: the use of symptomatology questionnaires, urine analysis (egg count and CCA measurement), semen analysis (egg count, circulating anodic antigen measurement and real-time polymerase chain reaction analysis) alongside clinical assessment with portable ultrasonography

    Exploitation of Herpesvirus Immune Evasion Strategies to Modify the Immunogenicity of Human Mesenchymal Stem Cell Transplants

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    BACKGROUND: Mesenchymal stem cells (MSCs) are multipotent cells residing in the connective tissue of many organs and holding great potential for tissue repair. In culture, human MSCs (hMSCs) are capable of extensive proliferation without showing chromosomal aberrations. Large numbers of hMSCs can thus be acquired from small samples of easily obtainable tissues like fat and bone marrow. MSCs can contribute to regeneration indirectly by secretion of cytokines or directly by differentiation into specialized cell types. The latter mechanism requires their long-term acceptance by the recipient. Although MSCs do not elicit immune responses in vitro, animal studies have revealed that allogeneic and xenogeneic MSCs are rejected. METHODOLOGY/PRINCIPAL FINDINGS: We aim to overcome MSC immune rejection through permanent down-regulation of major histocompatibility complex (MHC) class I proteins on the surface of these MHC class II-negative cells through the use of viral immune evasion proteins. Transduction of hMSCs with a retroviral vector encoding the human cytomegalovirus US11 protein resulted in strong inhibition of MHC class I surface expression. When transplanted into immunocompetent mice, persistence of the US11-expressing and HLA-ABC-negative hMSCs at levels resembling those found in immunodeficient (i.e., NOD/SCID) mice could be attained provided that recipients' natural killer (NK) cells were depleted prior to cell transplantation. CONCLUSIONS/SIGNIFICANCE: Our findings demonstrate the potential utility of herpesviral immunoevasins to prevent rejection of xenogeneic MSCs. The observation that down-regulation of MHC class I surface expression renders hMSCs vulnerable to NK cell recognition and cytolysis implies that multiple viral immune evasion proteins are likely required to make hMSCs non-immunogenic and thereby universally transplantable

    Genetic Determinants of Electrocardiographic P-Wave Duration and Relation to Atrial Fibrillation.

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    BACKGROUND: The P-wave duration (PWD) is an electrocardiographic measurement that represents cardiac conduction in the atria. Shortened or prolonged PWD is associated with atrial fibrillation (AF). We used exome-chip data to examine the associations between common and rare variants with PWD. METHODS: Fifteen studies comprising 64 440 individuals (56 943 European, 5681 African, 1186 Hispanic, 630 Asian) and ≈230 000 variants were used to examine associations with maximum PWD across the 12-lead ECG. Meta-analyses summarized association results for common variants; gene-based burden and sequence kernel association tests examined low-frequency variant-PWD associations. Additionally, we examined the associations between PWD loci and AF using previous AF genome-wide association studies. RESULTS: We identified 21 common and low-frequency genetic loci (14 novel) associated with maximum PWD, including several AF loci (TTN, CAND2, SCN10A, PITX2, CAV1, SYNPO2L, SOX5, TBX5, MYH6, RPL3L). The top variants at known sarcomere genes (TTN, MYH6) were associated with longer PWD and increased AF risk. However, top variants at other loci (eg, PITX2 and SCN10A) were associated with longer PWD but lower AF risk. CONCLUSIONS: Our results highlight multiple novel genetic loci associated with PWD, and underscore the shared mechanisms of atrial conduction and AF. Prolonged PWD may be an endophenotype for several different genetic mechanisms of AF

    Genetic Determinants of Electrocardiographic P-Wave Duration and Relation to Atrial Fibrillation

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    Background: The P-wave duration (PWD) is an electrocardiographic measurement that represents cardiac conduction in the atria. Shortened or prolonged PWD is associated with atrial fibrillation (AF). We used exome-chip data to examine the associations between common and rare variants with PWD. / Methods: Fifteen studies comprising 64 440 individuals (56 943 European, 5681 African, 1186 Hispanic, 630 Asian) and ≈230 000 variants were used to examine associations with maximum PWD across the 12-lead ECG. Meta-analyses summarized association results for common variants; gene-based burden and sequence kernel association tests examined low-frequency variant-PWD associations. Additionally, we examined the associations between PWD loci and AF using previous AF genome-wide association studies. / Results: We identified 21 common and low-frequency genetic loci (14 novel) associated with maximum PWD, including several AF loci (TTN, CAND2, SCN10A, PITX2, CAV1, SYNPO2L, SOX5, TBX5, MYH6, RPL3L). The top variants at known sarcomere genes (TTN, MYH6) were associated with longer PWD and increased AF risk. However, top variants at other loci (eg, PITX2 and SCN10A) were associated with longer PWD but lower AF risk. / Conclusions: Our results highlight multiple novel genetic loci associated with PWD, and underscore the shared mechanisms of atrial conduction and AF. Prolonged PWD may be an endophenotype for several different genetic mechanisms of AF

    Common SNPs explain some of the variation in the personality dimensions of neuroticism and extraversion

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    The personality traits of neuroticism and extraversion are predictive of a number of social and behavioural outcomes and psychiatric disorders. Twin and family studies have reported moderate heritability estimates for both traits. Few associations have been reported between genetic variants and neuroticism/extraversion, but hardly any have been replicated. Moreover, the ones that have been replicated explain only a small proportion of the heritability (<∼2%). Using genome-wide single-nucleotide polymorphism (SNP) data from ∼12 000 unrelated individuals we estimated the proportion of phenotypic variance explained by variants in linkage disequilibrium with common SNPs as 0.06 (s.e.=0.03) for neuroticism and 0.12 (s.e.=0.03) for extraversion. In an additional series of analyses in a family-based sample, we show that while for both traits ∼45% of the phenotypic variance can be explained by pedigree data (that is, expected genetic similarity) one third of this can be explained by SNP data (that is, realized genetic similarity). A part of the so-called ‘missing heritability' has now been accounted for, but some of the reported heritability is still unexplained. Possible explanations for the remaining missing heritability are that: (i) rare variants that are not captured by common SNPs on current genotype platforms make a major contribution; and/ or (ii) the estimates of narrow sense heritability from twin and family studies are biased upwards, for example, by not properly accounting for nonadditive genetic factors and/or (common) environmental factors

    Common and Rare Coding Genetic Variation Underlying the Electrocardiographic PR Interval

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    Background: Electrical conduction from the cardiac sinoatrial node to the ventricles is critical for normal heart function. Genome-wide association studies have identified more than a dozen common genetic loci that are associated with PR interval. However, it is unclear whether rare and low-frequency variants also contribute to PR interval heritability. Methods: We performed large-scale meta-analyses of the PR interval that included 83 367 participants of European ancestry and 9436 of African ancestry. We examined both common and rare variants associated with the PR interval. Results: We identified 31 genetic loci that were significantly associated with PR interval after Bonferroni correction (P<1.2×10−6), including 11 novel loci that have not been reported previously. Many of these loci are involved in heart morphogenesis. In gene-based analysis, we found that multiple rare variants at MYH6 (P=5.9×10−11) and SCN5A (P=1.1×10−7) were associated with PR interval. SCN5A locus also was implicated in the common variant analysis, whereas MYH6 was a novel locus. Conclusions: We identified common variants at 11 novel loci and rare variants within 2 gene regions that were significantly associated with PR interval. Our findings provide novel insights to the current understanding of atrioventricular conduction, which is critical for cardiac activity and an important determinant of health

    Indicators of "Healthy Aging" in older women (65-69 years of age). A data-mining approach based on prediction of long-term survival

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    <p>Abstract</p> <p>Background</p> <p>Prediction of long-term survival in healthy adults requires recognition of features that serve as early indicators of successful aging. The aims of this study were to identify predictors of long-term survival in older women and to develop a multivariable model based upon longitudinal data from the Study of Osteoporotic Fractures (SOF).</p> <p>Methods</p> <p>We considered only the youngest subjects (<it>n </it>= 4,097) enrolled in the SOF cohort (65 to 69 years of age) and excluded older SOF subjects more likely to exhibit a "frail" phenotype. A total of 377 phenotypic measures were screened to determine which were of most value for prediction of long-term (19-year) survival. Prognostic capacity of individual predictors, and combinations of predictors, was evaluated using a cross-validation criterion with prediction accuracy assessed according to time-specific AUC statistics.</p> <p>Results</p> <p>Visual contrast sensitivity score was among the top 5 individual predictors relative to all 377 variables evaluated (mean AUC = 0.570). A 13-variable model with strong predictive performance was generated using a forward search strategy (mean AUC = 0.673). Variables within this model included a measure of physical function, smoking and diabetes status, self-reported health, contrast sensitivity, and functional status indices reflecting cumulative number of daily living impairments (HR ≥ 0.879 or RH ≤ 1.131; P < 0.001). We evaluated this model and show that it predicts long-term survival among subjects assigned differing causes of death (e.g., cancer, cardiovascular disease; P < 0.01). For an average follow-up time of 20 years, output from the model was associated with multiple outcomes among survivors, such as tests of cognitive function, geriatric depression, number of daily living impairments and grip strength (P < 0.03).</p> <p>Conclusions</p> <p>The multivariate model we developed characterizes a "healthy aging" phenotype based upon an integration of measures that together reflect multiple dimensions of an aging adult (65-69 years of age). Age-sensitive components of this model may be of value as biomarkers in human studies that evaluate anti-aging interventions. Our methodology could be applied to data from other longitudinal cohorts to generalize these findings, identify additional predictors of long-term survival, and to further develop the "healthy aging" concept.</p
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