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.

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.

Taking "Galton's problem" Seriously : Towards a Theory of Policy Diffusion

This article builds on the recent policy diffusion literature and attempts to overcome one of its major problems, namely the lack of a coherent theoretical framework. The literature defines policy diffusion as a process where policy choices are interdependent, and identifies several diffusion mechanisms that specify the link between the policy choices of the various actors. As these mechanisms are grounded in different theories, theoretical accounts of diffusion currently have little internal coherence. In this article we put forward an expected-utility model of policy change that is able to subsume all the diffusion mechanisms. We argue that the expected utility of a policy depends on both its effectiveness and the payoffs it yields, and we show that the various diffusion mechanisms operate by altering these two parameters. Each mechanism affects one of the two parameters, and does so in distinct ways. To account for aggregate patterns of diffusion, we embed our model in a simple threshold model of diffusion. Given the high complexity of the process that results, strong analytical conclusions on aggregate patterns cannot be drawn without more extensive analysis which is beyond the scope of this article. However, preliminary considerations indicate that a wide range of diffusion processes may exist and that convergence is only one possible outcome.

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.

Predicting species distribution: offering more than simple habitat models

n the last two decades, interest in species distribution models (SDMs) of plants and animals has grown dramatically. Recent advances in SDMs allow us to potentially forecast anthropogenic effects on patterns of biodiversity at different spatial scales. However, some limitations still preclude the use of SDMs in many theoretical and practical applications. Here, we provide an overview of recent advances in this field, discuss the ecological principles and assumptions underpinning SDMs, and highlight critical limitations and decisions inherent in the construction and evaluation of SDMs. Particular emphasis is given to the use of SDMs for the assessment of climate change impacts and conservation management issues. We suggest new avenues for incorporating species migration, population dynamics, biotic interactions and community ecology into SDMs at multiple spatial scales. Addressing all these issues requires a better integration of SDMs with ecological theory.

Statistical learning theory for geospatial data. Case study: Aral sea

In recent years there has been an explosive growth in the development of adaptive and data driven methods. One of the efficient and data-driven approaches is based on statistical learning theory (Vapnik 1998). The theory is based on Structural Risk Minimisation (SRM) principle and has a solid statistical background. When applying SRM we are trying not only to reduce training error ? to fit the available data with a model, but also to reduce the complexity of the model and to reduce generalisation error. Many nonlinear learning procedures recently developed in neural networks and statistics can be understood and interpreted in terms of the structural risk minimisation inductive principle. A recent methodology based on SRM is called Support Vector Machines (SVM). At present SLT is still under intensive development and SVM find new areas of application (www.kernel-machines.org). SVM develop robust and non linear data models with excellent generalisation abilities that is very important both for monitoring and forecasting. SVM are extremely good when input space is high dimensional and training data set i not big enough to develop corresponding nonlinear model. Moreover, SVM use only support vectors to derive decision boundaries. It opens a way to sampling optimization, estimation of noise in data, quantification of data redundancy etc. Presentation of SVM for spatially distributed data is given in (Kanevski and Maignan 2004).

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.

Corticosterone mediates the condition-dependent component of melanin-based coloration

The handicap principle of sexual selection theory states that colourful phenotypic traits signal aspects of individual quality because only individuals in prime condition can afford to produce and bear conspicuous traits. Melanin-based pigments participate in the elaboration of many secondary sexual characters and, given their role in sexual selection, melanin-based coloration may therefore honestly reject individual quality. Although the expression of melanism is usually under genetic control, in some species it is condition dependent. However, the underlying physiological mechanism is yet unknown. Based on the negative feedback link between corticosterone and melanogenesis ( melanocortins, tyrosinase) in response to stressful environmental factors, we hypothesize that corticosterone mediates the condition-dependent component of melanism. This hypothesis predicts that stressful factors induce a rise in circulating corticosterone which inhibits the secretion of melanocortins and tyrosinase and in turn melanin production. We tested this prediction by manipulating the level of corticosterone at the time of melanin production in nestling barn owls, Tyto alba, a species showing heritable variation in the degree of phaeomelanism from reddish-brown to white. The finding that corticosterone-implanted nestlings produced feathers with less phaeomelanic coloration than placebo-implanted nestlings is consistent with the hypothesis that the environment-mediated reduction in the degree of melanism is, at least in part, caused by a rise in corticosterone. In species in which the expression of melanin-based coloration is condition dependent, we now need a test showing that individuals with less corticosterone and more melanin-based signals are individuals in better condition.

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.

Inclusive fitness theory and eusociality.

Arising from M. A. Nowak, C. E. Tarnita & E. O. Wilson 466, 1057-1062 (2010); Nowak et al. reply. Nowak et al. argue that inclusive fitness theory has been of little value in explaining the natural world, and that it has led to negligible progress in explaining the evolution of eusociality. However, we believe that their arguments are based upon a misunderstanding of evolutionary theory and a misrepresentation of the empirical literature. We will focus our comments on three general issues.