Genome-Wide Prediction Methods in Highly Diverse and Heterozygous Species: Proof-of-Concept through Simulation in Grapevine.

Nowadays, genome-wide association studies (GWAS) and genomic selection (GS) methods which use genome-wide marker data for phenotype prediction are of much potential interest in plant breeding. However, to our knowledge, no studies have been performed yet on the predictive ability of these methods for structured traits when using training populations with high levels of genetic diversity. Such an example of a highly heterozygous, perennial species is grapevine. The present study compares the accuracy of models based on GWAS or GS alone, or in combination, for predicting simple or complex traits, linked or not with population structure. In order to explore the relevance of these methods in this context, we performed simulations using approx 90,000 SNPs on a population of 3,000 individuals structured into three groups and corresponding to published diversity grapevine data. To estimate the parameters of the prediction models, we defined four training populations of 1,000 individuals, corresponding to these three groups and a core collection. Finally, to estimate the accuracy of the models, we also simulated four breeding populations of 200 individuals. Although prediction accuracy was low when breeding populations were too distant from the training populations, high accuracy levels were obtained using the sole core-collection as training population. The highest prediction accuracy was obtained (up to 0.9) using the combined GWAS-GS model. We thus recommend using the combined prediction model and a core-collection as training population for grapevine breeding or for other important economic crops with the same characteristics.

Renal hemodynamic and natriuretic effects of concomitant Angiotensin-converting enzyme and neutral endopeptidase inhibition in men.

This double-blind placebo-controlled study was designed to investigate the acute and sustained hormonal, renal hemodynamic, and tubular effects of concomitant ACE and neutral endopeptidase (NEP) inhibition by omapatrilat, a vasopeptidase inhibitor, in men. Thirty-two normotensive subjects were randomized to receive a placebo, omapatrilat (40 or 80 mg), or the fosinopril/hydrochlorothiazide (FOS/HCTZ; 20 and 12.5 mg, respectively) fixed combination for 1 week. Blood pressure, renal hemodynamics, urinary electrolytes and atrial natriuretic peptide excretion, and several components of the renin-angiotensin system were measured for 6 hours on days 1 and 7 of drug administration. When compared with the placebo and the FOS/HCTZ combination, omapatrilat induced a significant decrease in plasma angiotensin II levels (P<0.001 versus placebo; P<0.05 versus FOS/HCTZ) and an increase in urinary atrial natriuretic peptide excretion (P<0.01). These hormonal effects were associated with a significant fall in blood pressure (P<0.01) and a marked renal vasodilatation, but with no significant changes in glomerular filtration rate. The FOS/HCTZ markedly increased urinary sodium excretion (P<0.001). The acute natriuretic response to FOS/HCTZ was significantly greater than that observed with omapatrilat (P<0.01). Over 1 week, however, the cumulative sodium excretion induced by both doses of omapatrilat (P<0.01 versus placebo) was at least as great as that induced by the dose of FOS/HCTZ (P=NS versus FOS/HCTZ). In conclusion, the results of the present study in normal subjects demonstrate that omapatrilat has favorable renal hemodynamic effects. Omapatrilat combines potent ACE inhibition with a sustained natriuresis, which explains its well-documented potent antihypertensive efficacy.

Prediction of functional outcome 18 months after a first psychotic episode: a proton magnetic resonance spectroscopy study.

CONTEXT: Recent magnetic resonance imaging studies have attempted to relate volumetric brain measurements in early schizophrenia to clinical and functional outcome some years later. These studies have generally been negative, perhaps because gray and white matter volumes inaccurately assess the underlying dysfunction that might be predictive of outcome. OBJECTIVE: To investigate the predictive value of frontal and temporal spectroscopy measures for outcome in patients with first-episode psychoses. DESIGN: Left prefrontal cortex and left mediotemporal lobe voxels were assessed using proton magnetic resonance spectroscopy to provide the ratio of N-acetylaspartate (NAA) and choline-containing compounds to creatine and phosphocreatine (Cr) (NAA/Cr ratio). These data were used to predict outcome at 18 months after admission, as assessed by a systematic medical record audit. SETTING: Early psychosis clinic. PARTICIPANTS: Forty-six patients with first-episode psychosis. MAIN OUTCOME MEASURES: We used regression models that included age at imaging and duration of untreated psychosis to predict outcome scores on the Global Assessment of Functioning Scale, Clinical Global Impression scales, and Social and Occupational Functional Assessment Scale, as well as the number of admissions during the treatment period. We then further considered the contributions of premorbid function and baseline level of negative symptoms. RESULTS: The only spectroscopic predictor of outcome was the NAA/Cr ratio in the prefrontal cortex. Low scores on this variable were related to poorer outcome on all measures. In addition, the frontal NAA/Cr ratio explained 17% to 30% of the variance in outcome. CONCLUSIONS: Prefrontal neuronal dysfunction is an inconsistent feature of early psychosis; rather, it is an early marker of poor prognosis across the first years of illness. The extent to which this can be used to guide treatment and whether it predicts outcome some years after first presentation are questions for further research.

Ruling out coronary heart disease in primary care patients with chest pain: a clinical prediction score.

ABSTRACT: BACKGROUND: Chest pain raises concern for the possibility of coronary heart disease. Scoring methods have been developed to identify coronary heart disease in emergency settings, but not in primary care. METHODS: Data were collected from a multicenter Swiss clinical cohort study including 672 consecutive patients with chest pain, who had visited one of 59 family practitioners' offices. Using delayed diagnosis we derived a prediction rule to rule out coronary heart disease by means of a logistic regression model. Known cardiovascular risk factors, pain characteristics, and physical signs associated with coronary heart disease were explored to develop a clinical score. Patients diagnosed with angina or acute myocardial infarction within the year following their initial visit comprised the coronary heart disease group. RESULTS: The coronary heart disease score was derived from eight variables: age, gender, duration of chest pain from 1 to 60 minutes, substernal chest pain location, pain increases with exertion, absence of tenderness point at palpation, cardiovascular risks factors, and personal history of cardiovascular disease. Area under the receiver operating characteristics curve was of 0.95 with a 95% confidence interval of 0.92; 0.97. From this score, 413 patients were considered as low risk for values of percentile 5 of the coronary heart disease patients. Internal validity was confirmed by bootstrapping. External validation using data from a German cohort (Marburg, n = 774) revealed a receiver operating characteristics curve of 0.75 (95% confidence interval, 0.72; 0.81) with a sensitivity of 85.6% and a specificity of 47.2%. CONCLUSIONS: This score, based only on history and physical examination, is a complementary tool for ruling out coronary heart disease in primary care patients complaining of chest pain.

Hemodynamic and biochemical consequences of renin inhibition by infusion of CGP 38560A in normal volunteers.

Hemodynamic and biochemical effects of the new renin inhibitor CGP 38560A (molecular weight 826) were tested in 15 healthy volunteers after a single-blind, randomized, placebo-controlled protocol. At a 2-week interval, groups of five subjects received a 30-minute infusion of either 5% dextrose or CGP 38560A 50, 125, or 250 micrograms/kg. Blood pressure, heart rate, plasma renin activity, active and total renin, angiotensin-(1-8)octapeptide (angiotensin II), and aldosterone were sequentially measured up to 3 hours from the onset of the infusion. There was no consistent change in blood pressure or heart rate. Plasma renin activity and angiotensin II decreased dose dependently, and peak suppression was observed at the end of the infusion of CGP 38560A and after the 250-micrograms/kg dose. Plasma renin activity fell from 1.0 +/- 0.19 (mean +/- SEM) to less than 0.05 ng/ml/hr in all five subjects (p less than 0.001), and angiotensin II fell from 7.7 +/- 1.2 to 2.6 +/- 0.9 femtomole/ml (p less than 0.01). Active renin rose fourfold from 24 +/- 1.9 to 98 +/- 14 pg/ml (p less than 0.001) at the end of the infusion of the high dose. Plasma angiotensin II returned toward its initial values much faster than plasma renin activity and active renin. In conclusion, CGP 38560A was well tolerated. It induced a dose-dependent decrease in angiotensin II and plasma renin activity and a long-lasting and dose-dependent rise in active renin. The doses used did not reduce plasma angiotensin II maximally despite reduction of plasma renin activity to unmeasurable levels.(ABSTRACT TRUNCATED AT 250 WORDS)

Early multimodal outcome prediction after cardiac arrest in patients treated with hypothermia.

OBJECTIVES: Therapeutic hypothermia and pharmacological sedation may influence outcome prediction after cardiac arrest. The use of a multimodal approach, including clinical examination, electroencephalography, somatosensory-evoked potentials, and serum neuron-specific enolase, is recommended; however, no study examined the comparative performance of these predictors or addressed their optimal combination. DESIGN: Prospective cohort study. SETTING: Adult ICU of an academic hospital. PATIENTS: One hundred thirty-four consecutive adults treated with therapeutic hypothermia after cardiac arrest. MEASUREMENTS AND MAIN RESULTS: Variables related to the cardiac arrest (cardiac rhythm, time to return of spontaneous circulation), clinical examination (brainstem reflexes and myoclonus), electroencephalography reactivity during therapeutic hypothermia, somatosensory-evoked potentials, and serum neuron-specific enolase. Models to predict clinical outcome at 3 months (assessed using the Cerebral Performance Categories: 5 = death; 3-5 = poor recovery) were evaluated using ordinal logistic regressions and receiving operator characteristic curves. Seventy-two patients (54%) had a poor outcome (of whom, 62 died), and 62 had a good outcome. Multivariable ordinal logistic regression identified absence of electroencephalography reactivity (p < 0.001), incomplete recovery of brainstem reflexes in normothermia (p = 0.013), and neuron-specific enolase higher than 33 μg/L (p = 0.029), but not somatosensory-evoked potentials, as independent predictors of poor outcome. The combination of clinical examination, electroencephalography reactivity, and neuron-specific enolase yielded the best predictive performance (receiving operator characteristic areas: 0.89 for mortality and 0.88 for poor outcome), with 100% positive predictive value. Addition of somatosensory-evoked potentials to this model did not improve prognostic accuracy. CONCLUSIONS: Combination of clinical examination, electroencephalography reactivity, and serum neuron-specific enolase offers the best outcome predictive performance for prognostication of early postanoxic coma, whereas somatosensory-evoked potentials do not add any complementary information. Although prognostication of poor outcome seems excellent, future studies are needed to further improve prediction of good prognosis, which still remains inaccurate.

Correlates of frailty, prediction of functional decline and preventative approaches - selected results from the lausanne cohort 65+ (lc65+) study (Switzerland) (Lausanne) and the longitudinal urban cohort ageing study (Lucas) (Germany)

Overall introduction.- Longitudinal studies have been designed to investigate prospectively, from their beginning, the pathway leading from health to frailty and to disability. Knowledge about determinants of healthy ageing and health behaviour (resources) as well as risks of functional decline is required to propose appropriate preventative interventions. The functional status in older people is important considering clinical outcome in general, healthcare need and mortality. Part I.- Results and interventions from lucas (longitudinal urban cohort ageing study). Authors.- J. Anders, U. Dapp, L. Neumann, F. Pröfener, C. Minder, S. Golgert, A. Daubmann, K. Wegscheider,. W. von Renteln-Kruse Methods.- The LUCAS core project is a longitudinal cohort of urban community-dwelling people 60 years and older, recruited in 2000/2001. Further LUCAS projects are cross-sectional comparative and interventional studies (RCT). Results.- The emphasis will be on geriatric medical care in a population-based approach, discussing different forms of access, too. (Dapp et al. BMC Geriatrics 2012, 12:35; http://www.biomedcentral.com/1471-2318/12/35): - longitudinal data from the LUCAS urban cohort (n = 3.326) will be presented covering 10 years of observation, including the prediction of functional decline, need of nursing care, and mortality by using a self-filling screening tool; - interventions to prevent functional decline do focus on first (pre-clinical) signs of pre-frailty before entering the frailty-cascade ("Active Health Promotion in Old Age", "geriatric mobility centre") or disability ("home visits"). Conclusions.- The LUCAS research consortium was established to study particular aspects of functional competence, its changes with ageing, to detect pre-clinical signs of functional decline, and to address questions on how to maintain functional competence and to prevent adverse outcome in different settings. The multidimensional data base allows the exploration of several further questions. Gait performance was exmined by GAITRite®-System. Supported by the Federal Ministry for Education and Research (BMBF Funding No. 01ET1002A). Part II.- Selected results from the lausanne cohort 65+ (Lc65 + ) Study (Switzerland). Authors.- Prof Santos-Eggimann Brigitte, Dr Seematter-Bagnoud Laurence, Prof Büla Christophe, Dr Rochat Stéphane. Methods.- The Lc65+ cohort was launched in 2004 with the random selection of 3054 eligible individuals aged 65 to 70 (birth year 1934-1938) in the non-institutionalized population of Lausanne (Switzerland). Results.- Information is collected about life course social and health-related events, socio-economics, medical and psychosocial dimensions, lifestyle habits, limitations in activities of daily living, mobility impairments, and falls. Gait performance are objectively measured using body-fixed sensors. Frailty is assessed using Fried's frailty phenotype. Follow-up consists in annual self-completed questionnaires, as well as physical examination and physical and mental performance tests every three years. - Lausanne cohort 65+ (Lc65 + ): design and longitudinal outcomes. The baseline data collection was completed among 1422 participants in 2004-2005 through self-completed questionnaires, face-to-face interviews, physical examination and tests of mental and physical performances. Information about institutionalization, self-reported health services utilization, and death is also assessed. An additional random sample (n = 1525) of 65-70 years old subjects was recruited in 2009 (birth year 1939-1943). - lecture no 4: alcohol intake and gait parameters: prevalent and longitudinal association in the Lc65+ study. The association between alcohol intake and gait performance was investigated.

Prediction of 18-month survival in patients with primary myelodysplastic syndrome. A regression model and scoring system based on the combination of chromosome findings and the Bournemouth score.

The predictive potential of six selected factors was assessed in 72 patients with primary myelodysplastic syndrome using univariate and multivariate logistic regression analysis of survival at 18 months. Factors were age (above median of 69 years), dysplastic features in the three myeloid bone marrow cell lineages, presence of chromosome defects, all metaphases abnormal, double or complex chromosome defects (C23), and a Bournemouth score of 2, 3, or 4 (B234). In the multivariate approach, B234 and C23 proved to be significantly associated with a reduction in the survival probability. The similarity of the regression coefficients associated with these two factors means that they have about the same weight. Consequently, the model was simplified by counting the number of factors (0, 1, or 2) present in each patient, thus generating a scoring system called the Lausanne-Bournemouth score (LB score). The LB score combines the well-recognized and easy-to-use Bournemouth score (B score) with the chromosome defect complexity, C23 constituting an additional indicator of patient outcome. The predicted risk of death within 18 months calculated from the model is as follows: 7.1% (confidence interval: 1.7-24.8) for patients with an LB score of 0, 60.1% (44.7-73.8) for an LB score of 1, and 96.8% (84.5-99.4) for an LB score of 2. The scoring system presented here has several interesting features. The LB score may improve the predictive value of the B score, as it is able to recognize two prognostic groups in the intermediate risk category of patients with B scores of 2 or 3. It has also the ability to identify two distinct prognostic subclasses among RAEB and possibly CMML patients. In addition to its above-described usefulness in the prognostic evaluation, the LB score may bring new insights into the understanding of evolution patterns in MDS. We used the combination of the B score and chromosome complexity to define four classes which may be considered four possible states of myelodysplasia and which describe two distinct evolutional pathways.

ET-1 and NOS III gene expression regulation by plaque-free and plaque-prone hemodynamic conditions

Résumé: Les environnements hémodynamiques, favorisant ou protégeant contre la formation de la plaque, induisent tout deux une augmentation de la production d'anion superoxide dans les cellules endothéliales (ECs). Par ailleurs, une régulation différente de l'expression des gènes a été décrite dans les cellules exposées à ces différentes conditions. Dans le but d'investiguer le rôle de l'augmentation du stress oxydatif dans l'expression des gènes régulée par le flux, nous avons d'abord exposé les EC à un flux unidirectionnel, non pulsé. Dans ces conditions, l'état oxydatif des cellules endothéliales est augmenté de façon transitoire. L'expression du gène de l'endothéline 1 (ET-1) est aussi induite de façon transitoire par un tel flux, alors que l'expression du gène de la nitiric oxyde synthase endothéliale (NOS III) est stimulé de façon durable. Au contraire, un flux unidirectionnel pulsé, qui induit une augmentation durable de la production d'anion superoxide, augmente aussi de façon durable l'expression des gènes de ET-1 comme de NOS III. Un flux oscillatoire (favorisant la plaque), qui lui aussi ,a des effets à long terme sur la production d'anion superoxide, a uniquement augmenté l'expression de ET-1. De plus, l'utilisation d'un antioxydant, a seulement partiellement inhibé la stimulation de l'expression du gène NOS III par le flux unidirectionnel pulsé, alors qu'il a complètement abrogé la stimulation de l'expression du gène ET-1 par le flux unidirectionnel pulsé et oscillatoire. Ceci suggère que les forces mécaniques régulent l'expression des gènes dans les EC par un double mécanisme dépendant et indépendant du stress oxidatif des cellules. Par ailleurs, ces résultats supportent ultérieurement l'hypothèse que la balance entre la réponse oxidative et anti-oxidante dans les cellules endothéliales exposées à un environnement hémodynamique est une des clés de la prédisposition à un dysfonctionnement endothélial observé dans des régions exposées à des flux perturbés. Abstract: Both plaque-free and plaque-prone hemodynamic environments induce an increase in the oxidative state of endothelial cells (ECs), whereas differential gene expression regulation was described in cells exposed to these conditions. In order to investigate the role of the increased oxidative state in flow-regulation of gene expression, we first exposed EC to non-pulsed unidirectional shear stress. These conditions only slightly increases ECs oxidative state and endothelin-1 (ET-1) mRNA expression, whereas endothelial nitric oxide synthase (NOS III) mRNA level were significantly up-regulated. On the contrary, both ET-1 and NOS III gene expression were significantly induced in EC exposed to pulsed-unidirectional flow (plaque-free). Only ET-1 gene expression was up-regulated by oscillatory flow (plaque-prone). Moreover, use of an antioxidant only partially inhibited NOS III gene up-regulation by unidirectional flow, whereas it completely abrogated ET-1 gene up-regulation by unidirectional and oscillatory flows. Thus suggesting that mechanical forces regulate gene expression in ECs both via oxidative stress-dependent and -independent mechanisms.

Uncertainty Quantification with Support Vector Regression Prediction Models

Uncertainty quantification of petroleum reservoir models is one of the present challenges, which is usually approached with a wide range of geostatistical tools linked with statistical optimisation or/and inference algorithms. The paper considers a data driven approach in modelling uncertainty in spatial predictions. Proposed semi-supervised Support Vector Regression (SVR) model has demonstrated its capability to represent realistic features and describe stochastic variability and non-uniqueness of spatial properties. It is able to capture and preserve key spatial dependencies such as connectivity, which is often difficult to achieve with two-point geostatistical models. Semi-supervised SVR is designed to integrate various kinds of conditioning data and learn dependences from them. A stochastic semi-supervised SVR model is integrated into a Bayesian framework to quantify uncertainty with multiple models fitted to dynamic observations. The developed approach is illustrated with a reservoir case study. The resulting probabilistic production forecasts are described by uncertainty envelopes.

The prediction of speed and incline in outdoor running in humans using accelerometry.

PURPOSE: To explore whether triaxial accelerometric measurements can be utilized to accurately assess speed and incline of running in free-living conditions. METHODS: Body accelerations during running were recorded at the lower back and at the heel by a portable data logger in 20 human subjects, 10 men, and 10 women. After parameterizing body accelerations, two neural networks were designed to recognize each running pattern and calculate speed and incline. Each subject ran 18 times on outdoor roads at various speeds and inclines; 12 runs were used to calibrate the neural networks whereas the 6 other runs were used to validate the model. RESULTS: A small difference between the estimated and the actual values was observed: the square root of the mean square error (RMSE) was 0.12 m x s(-1) for speed and 0.014 radiant (rad) (or 1.4% in absolute value) for incline. Multiple regression analysis allowed accurate prediction of speed (RMSE = 0.14 m x s(-1)) but not of incline (RMSE = 0.026 rad or 2.6% slope). CONCLUSION: Triaxial accelerometric measurements allows an accurate estimation of speed of running and incline of terrain (the latter with more uncertainty). This will permit the validation of the energetic results generated on the treadmill as applied to more physiological unconstrained running conditions.

Validated prediction of clinical outcome in sarcomas and multiple types of cancer on the basis of a gene expression signature related to genome complexity.

Sarcomas are heterogeneous and aggressive mesenchymal tumors. Histological grading has so far been the best predictor for metastasis-free survival, but it has several limitations, such as moderate reproducibility and poor prognostic value for some histological types. To improve patient grading, we performed genomic and expression profiling in a training set of 183 sarcomas and established a prognostic gene expression signature, complexity index in sarcomas (CINSARC), composed of 67 genes related to mitosis and chromosome management. In a multivariate analysis, CINSARC predicts metastasis outcome in the training set and in an independent 127 sarcomas validation set. It is superior to the Fédération Francaise des Centres de Lutte Contre le Cancer grading system in determining metastatic outcome for sarcoma patients. Furthermore, it also predicts outcome for gastrointestinal stromal tumors (GISTs), breast carcinomas and lymphomas. Application of the signature will permit more selective use of adjuvant therapies for people with sarcomas, leading to decreased iatrogenic morbidity and improved outcomes for such individuals.

Novel methods improve prediction of species' distributions from occurrence data

Prediction of species' distributions is central to diverse applications in ecology, evolution and conservation science. There is increasing electronic access to vast sets of occurrence records in museums and herbaria, yet little effective guidance on how best to use this information in the context of numerous approaches for modelling distributions. To meet this need, we compared 16 modelling methods over 226 species from 6 regions of the world, creating the most comprehensive set of model comparisons to date. We used presence-only data to fit models, and independent presence-absence data to evaluate the predictions. Along with well-established modelling methods such as generalised additive models and GARP and BIOCLIM, we explored methods that either have been developed recently or have rarely been applied to modelling species' distributions. These include machine-learning methods and community models, both of which have features that may make them particularly well suited to noisy or sparse information, as is typical of species' occurrence data. Presence-only data were effective for modelling species' distributions for many species and regions. The novel methods consistently outperformed more established methods. The results of our analysis are promising for the use of data from museums and herbaria, especially as methods suited to the noise inherent in such data improve.