Search

Physical modelling of atmospheric processes, such as rainfall events, is often difficult due to the complexity of the atmosphere and the large number of variables involved. At the same time, it is necessary to know, as carefully as possible, some characteristics of precipitation processes, such as rainfall magnitude and frequency, in order to better understand their impacts on the territory. For this reason, statistical frameworks able to use external covariates to explain the physical process could be a central point in research.Starting from the rainfall events identified from continuous data series from about 40 rain gauges located in Sicily, this paper aims at assessing the occurrence of rainfall events in a fixed interval of time according to a temporal contagion model (branching process) with external covariates, within a regression-like framework (Adelfio and Chiodi, 2021).In detail, we extend the model formulation proposed by Meyer et al. (2012) in the context of infectious disease transmission, suggesting the use of a specific branching-type model, born in seismic context (the ETAS model, (Ogata 1988, 1998)), in a regression-oriented version modelling. In the temporal ETAS model, the expected frequency of events in a time unit can be defined as the sum of a term that describes the long-term variation and a term that describes the short-term variation.Accounting for further potential covariates in the model specification of the short-term variation component, may both explain some of the overall variability of the studied phenomenon (i.e., for decreasing the unpredictable variability) and provide a more realistic description of the observed activity. The Forward Likelihood for prediction (FLP) method (Chiodi and Adelfio 2011) is used for estimating the ETAS model components with the covariates.In this application the mean rainfall intensity, the duration and the anomalies in temperature and relative humidity of the events have been considered as external covariates of the model in order to explain the events frequency. The first results of the model appear to be interesting, and special attention will be paid to the sample of convective precipitation events identified using the same dataset (Sottile et al. 2021).

Students’ migration mobility is the new form of migration: students migrate to improve their skills and become more valued for the job market. The data regard the migration of Italian Bachelors who enrolled at Master Degree level, moving typically from poor to rich areas. This paper investigates the migration and other possible determinants on the Master Degree students’ performance. The Clustering of Effects approach for Quantile Regression Coefficients Modelling has been used to cluster the effects of some variables on the students’ performance for three Italian macro-areas. Results show evidence of similarity between Southern and Centre students, with respect to the Northern ones.

The Gaussian graphical model is one of the most used tools for inferring genetic networks. Nowadays, the data are often collected from different sources or under different biological conditions, resulting in heterogeneous datasets that exhibit a dependency structure that varies across groups. The complex structure of these data is typically recovered using regularized inferential procedures that use two penalties, one that encourages sparsity within each graph and the other that encourages common structures among the different groups. To this date, these approaches have not been developed for handling the case of censored data. However, these data are often generated by gene expression technologies such as RT-qPCR experiments. In this paper, we fill this gap and propose an extension of joint Gaussian graphical modelling to account for censored, or more generally missing, data.

The covariate adjusted glasso is one of the most used estimators for in- ferring genetic networks. Despite its diffusion, there are several fields in applied research where the limits of detection of modern measurement technologies make the use of this estimator theoretically unfounded, even when the assumption of a multivariate Gaussian distribution is satisfied. In this paper we propose an extension to censored data.

A new, broad family of quantile-based estimators is described, and theoretical and empirical evidence is provided for their robustness to outliers in the response. The proposed method can be used to estimate all types of parameters, including location, scale, rate and shape parameters, extremes, regression coefficients and hazard ratios, and can be extended to censored and truncated data. The described estimator can be utilized to construct robust versions of common parametric and semiparametric methods, such as linear (Normal) regression, generalized linear models, and proportional hazards models. A variety of significant results and applications is presented to show the flexibility of the proposed approach. The R package Qest implements the estimator and provides the necessary functions for model building, prediction, and inference.

The covariate adjusted glasso is one of the most used estimators for inferring genetic networks. Despite its diffusion, there are several fields in applied research where the limits of detection of modern measurement technologies make the use of this estimator theoretically unfounded, even when the assumption of a multivariate Gaussian distribution is satisfied. In this paper we propose an extension to censored data.

Coat color is one of the most important phenotypic features in livestock breeds. Cinisara is a local cattle breed generally of uniform black color which occasionally presents a particular phenotype, with animals typically display a white band along their spine, from the head to the tail, and on the ventral line (color sidedness). Therefore, this breed provides an ideal model to study the genetic components underlying phenotypic variation in coat color. A total of 63 animals, ten with sidedness phenotype and 53 with uniform black color were genotyped with Illumina Bovine 50 K. The comparison among genome-wide association study and FST analysis revealed a single nucleotide polymorphism (SNP), ARS-BFGL-NGS-55928, significantly associated with the trait. Only one gene (PLK2) was annotated near the associated SNP in a window of ±200 kb. The protein encoded by this gene is a member of the polo-like kinases, the same family of several known coat-color candidate genes. Based on the reported results, we draw the possible conclusion that the identified marker is potentially associated with the coat color sidedness in Cinisara. The local breeds with their genetic variability represent an important resource and model to study the genetic basis affecting peculiar traits. Future studies would be particularly relevant to refine these results and to better understand the genetic basis for this phenotype.

Background:To assess the prevalence of three nociceptive primitive reflexes (nPR), i.e., glabellar tap, snout reflex, and palmomental reflex, in neurologically and cognitively healthy (NCH) aging subjects.Objective:To investigate whether nPR are cross-sectionally associated with white matter hyperintensities (WMH), lacunes, atrophy of the caudate nuclei, and global brain atrophy.Methods:A total of 1246 NCH subjects aged 45–91 years were included in the study and underwent standard brain MRI. Atrophy of the caudate nuclei and global brain atrophy were assessed through the bicaudate ratio (BCr) and lateral ventricles to brain ratio (LVBr), respectively. WMH were assessed through visual rating scales. Lacunes were also rated. Association of nPR with vascular risk factors/diseases and imaging findings was evaluated using logistic regression analysis.Results:nPR were exhibited by 33.1% of subjects and increased with age. Subjects with nPR performed less than subjects without nPR in tests evaluating global cognition, executive functions, attention, and language. Snout reflex was the most common nPR, followed by glabellar tap and palmomental reflex. Glabellar tap was associated with parieto-temporal WMH, BCr, and LVBr; snout reflex was associated with frontal lacunes, temporal WMH, BCr, and LVBr; palmomental reflex was associated with parieto-occipital WMH, basal ganglia lacunes, BCr, and LVBr.Conclusions:This study demonstrates that in NCH aging individuals, nPR are associated with WMH, lacunes, BCr, and LVBr and are probably a warning sign of incipient cognitive decline. Therefore, NCH subjects presenting nPR should manage their vascular risk factors/vascular diseases rigorously in order to prevent or delay progression of small vessel disease, and future neurological and cognitive disabilities.

Understanding the structure of precipitation and its separation into stratiform and convective components is still today one of the important and interesting challenges for the scientific community. Despite this interest and the advances made in this field, the classification of rainfall into convective and stratiform components is still today not trivial. This study applies a novel criterion based on a clustering approach to analyze a high temporal resolution precipitation dataset collected for the period 2002–2018 over the Sicily (Italy). Starting from the rainfall events obtained from this dataset, the developed methodology makes it possible to classify the rainfall events into four different classes, which can be related to the convective and stratiform components of the events on the basis of their hyetograph shapes and average intensities. The results show that the occurrence of stratiform events is always much higher than the convective ones, especially in the winter and spring seasons, while from the summer to the mid-autumn the rainfall depth due to convective events results to be higher than that due to the stratiform events. Moreover, the comparison with a more widely accepted separation methodology demonstrates the physical consistency of the proposed methodology.

Background: Rigidity is a key clinical feature of Parkinson’s disease (PD), but in a very early phase of the disease it may be absent and can be enhanced through active movements of the arm contralateral to the one being tested. Objective: To evaluate in a large cohort of neurologically and cognitively healthy (NCH) subjects aged 18–90 years if activation-induced rigidity (AR) is present in all age classes, and if there are biological differences between subjects showing AR (AR+) and not showing AR (AR-). Methods: 2,228 NCH subjects categorized as young adult (18–44 years), adult (45–64 years), elderly (65–74 years), and old/oldest-old (75–90 years) were included in the analysis, and underwent brain MRI. White matter hyperintensities were assessed through two visual rating scales. Lacunes were also rated. Atrophy of the caudate nuclei and ventricular enlargement were assessed through the bicaudate ratio and the lateral ventricles to brain ratio. To elicit AR, the Froment’s maneuver (FM) and the instructions of the UPDRS-ME were used. Results: Among the sample, 1,689 (75.81%) subjects showed AR, of which 1,270 (57.00%) subjects showed AR by using FM, and 419 (18.81%) showed AR by using UPDRS-ME instructions. The latter subjects also showed AR by using FM. The number of AR+ subjects significantly increased with increasing age, regardless of the activation maneuver used. In each age class, the number of AR+ subjects was significantly higher by using the FM than the UPDRS-ME instructions. Conclusion: Our findings suggest that AR is likely to be one of the signs of the prodromal phase of PD.

Quantile regression (QR) has gained popularity during the last decades, and is now considered a standard method by applied statisticians and practitioners in various fields. In this work, we applied QR to investigate climate change by analysing historical temperatures in the Arctic Circle. This approach proved very flexible and allowed to investigate the tails of the distribution, that correspond to extreme events. The presence of quantile crossing, however, prevented using the fitted model for prediction and extrapolation. In search of a possible solution, we first considered a different version of QR, in which the QR coefficients were described by parametric functions. This alleviated the crossing problem, but did not eliminate it completely. Finally, we exploited the imposed parametric structure to formulate a constrained optimization algorithm that enforced monotonicity. The proposed example showed how the relatively unexplored field of parametric quantile functions could offer new solutions to the long-standing problem of quantile crossing. Our approach is particularly convenient in situations, like the analysis of time series, in which the fitted model may be used to predict extreme quantiles or to perform extrapolation. The described estimator has been implemented in the R package qrcm.

© 2020, Springer Science+Business Media, LLC, part of Springer Nature. In many applied fields, such as genomics, different types of data are collected on the same system, and it is not uncommon that some of these datasets are subject to censoring as a result of the measurement technologies used, such as data generated by polymerase chain reactions and flow cytometer. When the overall objective is that of network inference, at possibly different levels of a system, information coming from different sources and/or different steps of the analysis can be integrated into one model with the use of conditional graphical models. In this paper, we develop a doubly penalized inferential procedure for a conditional Gaussian graphical model when data can be subject to censoring. The computational challenges of handling censored data in high dimensionality are met with the development of an efficient expectation-maximization algorithm, based on approximate calculations of the moments of truncated Gaussian distributions and on a suitably derived two-step procedure alternating graphical lasso with a novel block-coordinate multivariate lasso approach. We evaluate the performance of this approach on an extensive simulation study and on gene expression data generated by RT-qPCR technologies, where we are able to integrate network inference, differential expression detection and data normalization into one model. European Cooperation in Science and Technology (COST) [COST Action CA15109EuropeanCooperationforStatisticsofNetworkDataScience (COSTNET)].

The conditional glasso is one of the most used estimators for inferring genetic networks. Despite its diffusion, there are several fields in applied research where the limits of detection of modern measurement technologies make the use of this estimator theoretically unfounded, even when the assumption of a multivariate Gaussian distribution is satisfied. In this paper we propose an extension to censored data.

Asthma and rhino-conjunctivitis are common chronic diseases in childhood. In this cross-sectional study, we performed a gene association analysis with current asthma and rhino-conjunctivitis in a cohort of Sicilian children aged 10–15 years. Overall, our findings reveal the importance of different genetic variants at 4p14, 16p12.1, 17q12, 6p12.2 and 17q21.1, identifying possible candidate genes responsible for susceptibility to asthma and rhino-conjunctivitis.

The availability of genotyping assays has allowed the detailed evaluation of cattle genetic diversity worldwide. However, these comprehensive studies did not include some local European populations, including autochthonous Italian cattle. In this study, we assembled a large-scale, genome-wide dataset of single nucleotide polymorphisms scored in 3,283 individuals from 205 cattle populations worldwide to assess genome-wide autozygosity and understand better the genetic relationships among these populations. We prioritized European cattle, with a special focus on Italian breeds. Moderate differences in estimates of molecular inbreeding calculated from runs of homozygosity (FROH) were observed among domesticated bovid populations from different geographic areas, except for Bali cattle. Our findings indicated that some Italian breeds show the highest estimates of levels of molecular inbreeding among the cattle populations assessed in this study. Patterns of genetic differentiation, shared ancestry, and phylogenetic analysis all suggested the occurrence of gene flow, particularly among populations originating from the same geographical area. For European cattle, we observed a distribution along three main directions, reflecting the known history and formation of the analyzed breeds. The Italian breeds are split into two main groups, based on their historical origin and degree of conservation of ancestral genomic components. The results pinpointed that also Sicilian breeds, much alike Podolian derived-breeds, in the past experienced a similar non-European influence, with African and indicine introgression.

The increasing occurrence of flood events in some areas of the Southern Mediterranean area (e.g., Sicily), over the last few years, has contributed to raising the importance of characterizing such events and identifying their causes. Since most of these events can be related to high-intensity rainfalls, which, in turn, are usually due to convective rainfall, it is very important to understand which factors could be recognized as drivers of such extreme events. Nevertheless, the way to distinguish between convective and stratiform rainfall is still an open issue and not easy to solve.With this regard, starting from precipitation time series recorded at different rain gauge stations of Sicily, which is the greatest Mediterranean island, we propose an algorithm capable to classify precipitation distinguishing between their convective and stratiform components.In order to do that, a dataset from the regional agency SIAS (Servizio Informativo Agrometeorologico Siciliano - Agro-meteorological Information Service of Sicily) has been used because of its high temporal resolution, quality, and availability of up-to-date data. Specifically, data from rain gauge stations spread over the entire island have been collected for the period 2003 - 2018 and with a temporal resolution of 10 minutes.In order to classify the precipitation in convective and stratiform components, the functional PCA-based clustering approach (denoted by FPCAC) has been applied, which can be considered as a variant of a k-means algorithm based on the principal component rotation of data. In order to evaluate the validity of the proposed algorithm, finally, the results have been compared to some ERA5 reanalysis products.

The coefficients of a quantile regression model are one-to-one functions of the order of the quantile. In standard quantile regression (QR), different quantiles are estimated one at a time. Another possibility is to model the coefficient functions parametrically, an approach that is referred to as quantile regression coefficients modeling (QRCM). Compared with standard QR, the QRCM approach facilitates estimation, inference and interpretation of the results, and generates more efficient estimators. We designed a penalized method that can address the selection of covariates in this particular modelling framework. Unlike standard penalized quantile regression estimators, in which model selection is quantile-specific, our approach permits using information on all quantiles simultaneously. We describe the estimator, provide simulation results and analyse the data that motivated the present article. The proposed approach is implemented in the qrcmNP package in R.

An increase in FEV1 >=12% has been proposed in international guidelines as a clue to airway reversibility for diagnosing asthma in both adults and children. However, the validity of this cut-off has been questioned in the pediatric population. The aim of this study was to provide evidence that different cut-off values in BDR may be associated with better performance in discriminating among outpatient children with naïve asthma (A) and without asthma (NA). We compared three approaches: i) the conventional cutoff (12%); ii) the cut-off estimated by Youden's criteria; and iii) the cut-off based on a model-driven approach. we found that the conventional cut-off of 12% showed poor sensitivity in discriminating A and NA. The cut-off of 6.5% obtained maximizing Youden's J statistic showed higher sensitivity than the conventional one; however, the average correct classification rates obtained using the two criteria mentioned were less than 63%, highlighting poor discriminating performance. A model-based approach identifying three different categories of BDR - low (=14.7%) - yielded correct classification rates higher than 80%. The model-based approach made it possible to develop a dynamic nomogram, which graphically returns the prediction probability of asthma, overcoming the elevated risk of misclassification associated with the use of the conventional cut-off of 12%.

Objective: To evaluate in 419 stroke-free cognitively normal subjects (CN) aged 45-82 years covering during a long prospective study (11.54 ± 1.47 years) the preclinical to dementia spectrum: 1) the distribution of small vessel disease (V) and brain atrophy (A) aggregated as following: V−/A−, V−/A+, V+/A−, V+/A+; 2) the relationship of these imaging classes with individual apolipoprotein E (APOE) genotypes; 3) the risk of progression to Alzheimer Disease (AD) of the individual APOE genotypes. Methods: Participants underwent one baseline (t0), and 4 clinical and neuropsychological assessments (t1,t2,t3, and t4). Brain MRI was performed in all subjects at t0, t2, t3 and t4.. White matter hyperintensities were assessed through two visual rating scales. Lacunes were also rated. Subcortical and global brain atrophy were determined through the bicaudate ratio and the lateral ventricle to brain ratio, respectively. APOE genotypes were determined at t0 in all subjects. Cox proportional hazard model was used to evaluate the risk of progression to AD. Results: The imaging class of mixed type was very common in AD, and in non amnestic mild cognitive impaired APOE ε4 non carriers. In these subjects, frontal and parieto-occipital regions were most affected by small vessel disease. Conclusion: Our findings suggest that the APOE ε3 allele is probably linked to the brain vascular pathology.

Background: Mild Parkinsonian signs (MPS) are commonly seen in aging, and have been related to cerebral Small Vessel Diseases (SVD) with no univocal results. Objective: The aim of this study was to investigate the cross-sectional relation between MPS and White Matter Hyperintensities (WMH), lacunes, caudate atrophy, and global cerebral atrophy in a large cohort of Neurologically and Cognitively Healthy (NCH) aging individuals. Method: 1,219 NCH individuals were included in the analysis, and underwent standard brain MRI. The items of the motor section of the Unified Parkinson’s Disease Rating Scale were used to evaluate tremor, rigidity, bradykinesia, and gait/balance/axial dysfunction. Caudate atrophy and global cerebral atrophy were assessed through the bicaudate ratio and the lateral ventricles to brain ratio, respectively. WMH were assessed through two visual rating scales. Lacunes were also rated. Associations of MPS with vascular risk factors/diseases and imaging findings were determined through the logistic regression analysis. Results: Frontal and basal ganglia lacunes, frontal WMH, caudate atrophy, and global cerebral atrophy were associated with bradykinesia. Basal ganglia lacunes, caudate atrophy, and global cerebral atrophy were associated with gait/balance/axial dysfunction. Rigidity was associated with frontal WMH, and tremor with caudate atrophy and global cerebral atrophy. NCH subjects with MPS, performed less than subjects without MPS in tests evaluating global cognition and language. Conclusion: This study demonstrates that in NCH aging individuals, MPS are associated with cortical and subcortical vascular and atrophic changes, and are probably, a warning sign of incipient cognitive decline. Subjects with MPS should manage rigorously cerebral SVD to prevent future physical and cognitive disabilities.

The availability of dense single nucleotide polymorphism (SNP) assays allows for the determination of autozygous segments based on runs of consecutive homozygous genotypes (ROH). The aim of the present study was to investigate the occurrence and distribution of ROH in 21 Italian sheep breeds using medium-density SNP genotypes in order to characterize autozygosity and identify genomic regions that frequently appeared in ROH within individuals, namely ROH islands. After filtering, the final number of animals and SNPs retained for analyses were 502 and 46 277 respectively. A total of 12 302 ROH were identified. The mean number of ROH per breed ranged from 10.58 (Comisana) to 44.54 (Valle del Belice). The average length of ROH across breeds was 4.55 Mb and ranged from 3.85 Mb (Biellese) to 5.51 Mb (Leccese). Valle del Belice showed the highest value of inbreeding on the basis of ROH (FROH= 0.099), whereas Comisana showed the lowest (FROH= 0.016), and high standard deviation values revealed high variability in autozygosity levels within each breed. Differences also existed in the length of ROH. Analysis of the distribution of ROH according to their size showed that, for all breeds, the majority of the detected ROH were 25 Mb. The levels of ROH that we estimated here reflect the inbreeding history of the investigated sheep breeds. These results also highlight that ancient and recent inbreeding have had an impact on the genome of the Italian sheep breeds and suggest that several animals have experienced recent autozygosity events. Comisana and Bergamasca appeared as the less consanguineous breeds, whereas Barbaresca, Leccese and Valle del Belice showed ROH patterns typically produced by recent inbreeding. Moreover, within the genomic regions most commonly associated with ROH, several candidate genes were detected.

Nero Siciliano (Sicilian Black, SB) is a local pig breed generally of uniform black color. In addition to this officially recognized breed, there are animals showing morphological characteristics resembling the SB but with gray hair (Sicilian Grey, SG). The SG, compared with the SB, also shows a more compact structure with greater transverse diameters, higher average daily gains and lower thickness of the back fat. In this study, using the Illumina PorcineSNP60 BeadChip, we run genome-wide analyses to identify regions that may explain the phenotypic differences between SB (n=21) and SG (n=27) individuals. Combining the results of the two case–control approaches (GWAS and FST), we identified two significant regions, one on SSC5 (95 401 083 bp) and one on SSC15 (55 051 435 bp), which contains several candidate genes related to growth traits in pig. The results of the Bayesian population differentiation approach identified a marker near the MGAT4C, a gene associated with average daily gain in pigs. Finally, scanning the genome for runs of homozygosity islands, we found that the two groups have different runs of homozygosity islands, with several candidate genes involved in coat color (in SG) or related to different pig performance traits (in SB). In summary, the two analyzed groups differed for several phenotypic traits, and genes involved in these traits (growth, meat traits and coat color) were detected. This study provided another contribution to the identification of genomic regions involved in phenotypic variability in local pig populations.

Isolated, subtle neurological abnormalities (ISNA) are commonly seen in aging and have been related to cerebral small vessel disease (SVD) and subcortical atrophy in neurologically and cognitively healthy aging subjects.To investigate the frequency of ISNA in different mild cognitive impairment (MCI) types and to evaluate for each MCI type, the cross-sectional relation between ISNA and white matter hyperintensities (WMH), lacunes, caudate atrophy, and ventricular enlargement.One thousand two hundred fifty subjects with different MCI types were included in the analysis and underwent brain magnetic resonance imaging. WMHs were assessed through two visual rating scales. Lacunes were also rated. Atrophy of the caudate nuclei and ventricular enlargement were assessed through the bicaudate ratio (BCr) and the lateral ventricles to brain ratio (LVBr), respectively. Apolipoprotein E (APOE) genotypes were also assessed. The routine neurological examination was used to evaluate ISNAs that were clustered as central-based signs, cerebellar-based signs, and primitive reflexes. The items of Part-III of the Unified Parkinson's Disease Rating Scale were used to evaluate ISNAs that were clustered as mild parkinsonian signs. Associations of ISNAs with imaging findings were determined through logistic regression analysis.The ISNAs increase with the age and are present in all MCI types, particularly in those multiple domains, and carrying the APOE ϵ4 allele, and are associated with WMH, lacunes, BCr, and LVBr.This study demonstrates that cortical and subcortical vascular and atrophic processes contribute to ISNAs. Long prospective population-based studies are needed to disentangle the role of ISNAs in the conversion from MCI to dementia.Des anomalies neurologiques subtiles et isolées associées à différents types de déficience cognitive légère. Contexte: Des anomalies neurologiques à la fois subtiles et isolées sont fréquemment observées chez les personnes vieillissantes. Elles ont été associées à la maladie des petits vaisseaux du cerveau (cerebral small vessel disease) et à une atrophie des structures sous-corticales chez des sujets âgés en santé sur les plans neurologique et cognitif. Objectif: Étudier la fréquence de ces anomalies dans le cas de différents types de déficience cognitive légère ; évaluer, pour chaque type de déficience, la relation transversale entre ces anomalies et des hyper-signaux de la substance blanche, des lacunes cérébrales, l’atrophie du noyau caudé et l’élargissement des ventricules. Méthodes: Au total, 1250 sujets atteints de différents types de déficience cognitive légère ont été inclus dans notre analyse et ont passé un examen d’IRM du cerveau. On a évalué les hyper-signaux de la substance blanche à l’aide de deux échelles d’évaluation visuelle. À noter que les lacunes cérébrales ont également été évaluées. Du côté de l’atrophie du noyau caudé et de l’élargissement des ventricules, ces anomalies ont été mesurées respectivement au moyen de l’index bicaudé (bicaudate ratio) et du ratio volumique ventricule-cerveau (lateral ventricles to brain ratio). Enfin, les génotypes associés à l’apolipoprotéine E (ApoE) ont été examinés. Fait à souligner, des examens neurologiques de routine portant sur les signes du système nerveux central, sur les signes du cervelet et sur les réflexes archaïques ont été utilisés pour tenter de cerner les anomalies évoquées ci-dessus. Des éléments de la partie III de l’échelle UPDRS (Unified Parkinson’s Disease Rating Scale) ont été par ailleurs mis à profit pour évaluer les anomalies regroupées au sein de la catégorie des signes bénins de la maladie de Parkinson. Les liens entre ces anomalies et les résultats aux examens d’IRM ont été déterminés à l’aide d’une analyse de régression logistique. Résultats: Ces anomalies neurologiques à la fois subtiles et isolées augmentent en fonction de l’âge et sont présentes parmi tous les types de déficience cognitive légère, en particulier dans ces domaines multiples et chez les sujets porteurs de l’allèle ϵ4 du gène de l’ApoE. On a vu également qu’elles sont associées à des hyper-signaux de la substance blanche, à des lacunes cérébrales, à l’atrophie du noyau caudé et à l’élargissement des ventricules. Conclusion: Cette étude démontre que les processus vasculaires et atrophiques des structures corticales et sous-corticales contribuent à l’apparition d’anomalies neurologiques à la fois subtiles et isolées. Des études prospectives de longue haleine basées sur la population sont toutefois nécessaires pour mieux comprendre le rôle de ces anomalies dans l’évolution des cas de déficience cognitive légère vers la démence.

This paper focuses on hypothesis testing in lasso regression, when one is interested in judging statistical significance for the regression coefficients in the regression equation involving a lot of covariates. To get reliable p-values, we propose a new lasso-type estimator relying on the idea of induced smoothing which allows to obtain appropriate covariance matrix and Wald statistic relatively easily. Some simulation experiments reveal that our approach exhibits good performance when contrasted with the recent inferential tools in the lasso framework. Two real data analyses are presented to illustrate the proposed framework in practice.

Selective breeding has led to modifications in the genome of many livestock breeds. In this study, we identified the genomic regions that may explain some of the phenotypic differences between two closely related breeds from Sardinia. A total of 44 animals, 20 Sardinian Ancestral Black (SAB) and 24 Sardinian White (SW), were genotyped using the Illumina Ovine 50K array. A total of 68, 38 and 15 significant markers were identified using the case–control genome-wide association study (GWAS), the Bayesian population differentiation analysis (FST) and the Rsb metric, respectively. Comparisons among the approaches revealed a total of 22 overlapping markers between GWAS and FST and one marker between GWAS and Rsb. Three markers detected by Rsb were also located near (

Background:Mild Parkinsonian Signs (MPS) have been associated with Mild Cognitive Impairment (MCI) types with conflicting results.Objective:To investigate the association of individual MPS with different MCI types using logistic ridge regression analysis, and to evaluate for each MCI type, the association of MPS with caudate atrophy, global cerebral atrophy, and the topographical location of White Matter Hyperintensities (WMH), and lacunes.Methods:A cross-sectional study was performed among 1,168 subjects with different types of MCI aged 45-97 (70,52 ± 9,41) years, who underwent brain MRI. WMH were assessed through two visual rating scales. The number and location of lacunes were also rated. Atrophy of the caudate nuclei and global cerebral atrophy were assessed through the bicaudate ratio, and the lateral ventricles to brain ratio, respectively. Apolipoprotein E (APOE) genotypes were also assessed. Using the items of the motor section of the Unified Parkinson’s Disease Rating Scale, tremor, rigidity, bradykinesia, and gait/balance/axial dysfunction were evaluated.Results:Bradykinesia, and gait/balance/axial dysfunction were the MPS more frequently encountered followed by rigidity, and tremor. MPS were present in both amnestic and non-amnestic MCI types, and were associated with WMH, lacunes, bicaudate ratio, and lateral ventricles to brain ratio.Conclusion:MPS are present in both amnestic and non-amnestic MCI types, particularly in those multiple domain, and carrying the APOE ε4 allele. Cortical and subcortical vascular and atrophic processes contribute to MPS. Long prospective studies are needed to disentangle the contribution of MPS to the conversion from MCI to dementia.

Copy number variation (CNV) is a major source of genomic structural variation. The aim of this study was to detect genomic CNV regions (CNVR) in Valle del Belice dairy sheep population and to identify those affecting milk production traits. The GO analysis identified possible candidate genes and pathways related to the selected traits. We identified CNVs in 416 individuals genotyped using the Illumina OvineSNP50 BeadChip array. The CNV association using a correlation-trend test model was examined with the Golden Helix SVS 8.7.0 tool. Significant CNVs were detected when their adjusted p-value was

Genome-wide analysis identifies potentially causative genes explaining the phenotypic variability in Pinzirita sheep

Simple Summary In order to assess sources of variation related to Polverara breed plumage color (black vs. white), we carried out genome-wide analyses to identify the genomic regions involved in this trait. The present work has revealed new candidate genes involved in the phenotypic variability in local chicken populations. These results also contribute insights into the genetic basis for plumage color in poultry, and confirm the great complexity of the mechanisms that control this trait. Abstract Through the development of the high-throughput genotyping arrays, molecular markers and genes related to phenotypic traits have been identified in livestock species. In poultry, plumage color is an important qualitative trait that can be used as phenotypic marker for breed identification. In order to assess sources of genetic variation related to the Polverara chicken breed plumage colour (black vs. white), we carried out a genome-wide association study (GWAS) and a genome-wide fixation index (FST) scan to uncover the genomic regions involved. A total of 37 animals (17 white and 20 black) were genotyped with the Affymetrix 600 K Chicken single nucleotide polymorphism (SNP) Array. The combination of results from GWAS and FST revealed a total of 40 significant markers distributed on GGA 01, 03, 08, 12 and 21, and located within or near known genes. In addition to the well-known TYR, other candidate genes have been identified in this study, such as GRM5, RAB38 and NOTCH2. All these genes could explain the difference between the two Polverara breeds. Therefore, this study provides the basis for further investigation of the genetic mechanisms involved in plumage color in chicken.

Microtia is a congenital deformity of the outer ear with phenotypes varying from a small auricle to total absence (anotia). The genetic basis is still poorly understood, and very few studies have been performed in sheep. Valle del Belice sheep is a breed showing microtia. The aim of this study was to identify the potential genomic regions involved in microtia in sheep. A total of 40 individuals, 20 with microtia and 20 normal, were genotyped with the Illumina OvineSNP50 BeadChip. The comparison among the results from a genome-wide association study, Fisher's exact test and FST analysis revealed a single strong association signal: rs419889303 on chromosome 1, located within intron 3 of the CLRN1 gene. Our study suggests for the first time that this novel candidate gene is responsible for microtia in sheep. Additional analysis based on the sequencing would help confirm our findings and allow for the proposal of a precise genetic basis for microtia in sheep.

In this paper, we propose a new method for finding similarity of effects based on quantile regression models. Clustering of effects curves (CEC) techniques are applied to quantile regression coefficients, which are one-to-one functions of the order of the quantile. We adopt the quantile regression coefficients modeling (QRCM) framework to describe the functional form of the coefficient functions by means of parametric models. The proposed method can be utilized to cluster the effect of covariates with a univariate response variable, or to cluster a multivariate outcome. We report simulation results, comparing our approach with the existing techniques. The idea of combining CEC with QRCM permits simplifying computation and interpretation of the results, and may improve the ability to identify clusters. We illustrate a variety of applications, highlighting the advantages and the usefulness of the described method.

The identification of individuals’ breed of origin has several practical applications in livestock and is useful in different biological contexts such as conservation genetics, breeding and authentication of animal products. In this paper, penalized multinomial regression was applied to identify the minimum number of single nucleotide polymorphisms (SNPs) from high-throughput genotyping data for individual assignment to dairy sheep breeds reared in Sicily. The combined use of penalized multinomial regression and stability selection reduced the number of SNPs required to 48. A final validation step on an independent population was carried out obtaining 100% correctly classified individuals. The results using independent analysis, such as admixture, F st, principal component analysis and random forest, confirmed the ability of these methods in selecting distinctive markers. The identified SNPs may constitute a starting point for the development of a SNP based identification test as a tool for breed assignment and traceability of animal products.

Background Because very large numbers of single nucleotide polymorphisms (SNPs) are now available throughout the genome, they are particularly suitable for the detection of genomic regions where a reduction in heterozygosity has occurred and they offer new opportunities to improve the accuracy of inbreeding (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$F$$\end{document}F) estimates. Runs of homozygosity (ROH) are contiguous lengths of homozygous segments of the genome where the two haplotypes inherited from the parents are identical. Here, we investigated the occurrence and distribution of ROH using a medium-dense SNP panel to characterize autozygosity in 516 Valle del Belice sheep and to identify the genomic regions with high ROH frequencies. Results We identified 11,629 ROH and all individuals displayed at least one ROH longer than 1 Mb. The mean value of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$F$$\end{document}F estimated from ROH longer than1 Mb was 0.084 ± 0.061. ROH that were shorter than 10 Mb predominated. The highest and lowest coverages of Ovis aries chromosomes (OAR) by ROH were on OAR24 and OAR1, respectively. The number of ROH per chromosome length displayed a specific pattern, with higher values for the first three chromosomes. Both number of ROH and length of the genome covered by ROH varied considerably between animals. Two hundred and thirty-nine SNPs were considered as candidate markers that may be under directional selection and we identified 107 potential candidate genes. Six genomic regions located on six chromosomes, corresponding to ROH islands, are presented as hotspots of autozygosity, which frequently coincided with regions of medium recombination rate. According to the KEGG database, most of these genes were involved in multiple signaling and signal transduction pathways in a wide variety of cellular and biochemical processes. A genome scan revealed the presence of ROH islands in genomic regions that harbor candidate genes for selection in response to environmental stress and which underlie local adaptation. Conclusions These results suggest that natural selection has, at least partially, a role in shaping the genome of Valle del Belice sheep and that ROH in the ovine genome may help to detect genomic regions involved in the determinism of traits under selection. Electronic supplementary material The online version of this article (10.1186/s12711-017-0360-z) contains supplementary material, which is available to authorized users.