A New Mouse Model for Marfan Syndrome Presents Phenotypic Variability Associated with the Genetic Background and Overall Levels of Fbn1 Expression

Marfan syndrome is an autosomal dominant disease of connective tissue caused by mutations in the fibrillin-1 encoding gene FBN1. Patients present cardiovascular, ocular and skeletal manifestations, and although being fully penetrant, MFS is characterized by a wide clinical variability both within and between families. Here we describe a new mouse model of MFS that recapitulates the clinical heterogeneity of the syndrome in humans. Heterozygotes for the mutant Fbn1 allele mg Delta(loxPneo), carrying the same internal deletion of exons 19-24 as the mg Delta mouse model, present defective microfibrillar deposition, emphysema, deterioration of aortic wall and kyphosis. However, the onset of a clinical phenotypes is earlier in the 129/Sv than in C57BL/6 background, indicating the existence of genetic modifiers of MFS between these two mouse strains. In addition, we characterized a wide clinical variability within the 129/Sv congenic heterozygotes, suggesting involvement of epigenetic factors in disease severity. Finally, we show a strong negative correlation between overall levels of Fbn1 expression and the severity of the phenotypes, corroborating the suggested protective role of normal fibrillin-1 in MFS pathogenesis, and supporting the development of therapies based on increasing Fbn1 expression.

Additive genetic relationship of longevity with fertility and production traits in Nellore cattle based on bivariate models

Survival or longevity is an economically important trait in beef cattle. The main inconvenience for its inclusion in selection criteria is delayed recording of phenotypic data and the high computational demand for including survival in proportional hazard models. Thus, identification of a longevity-correlated trait that could be recorded early in life would be very useful for selection purposes. We estimated the genetic relationship of survival with productive and reproductive traits in Nellore cattle, including weaning weight (WW), post-weaning growth (PWG), muscularity (MUSC), scrotal circumference at 18 months (SC18), and heifer pregnancy (HP). Survival was measured in discrete time intervals and modeled through a sequential threshold model. Five independent bivariate Bayesian analyses were performed, accounting for cow survival and the five productive and reproductive traits. Posterior mean estimates for heritability (standard deviation in parentheses) were 0.55 (0.01) for WW, 0.25 (0.01) for PWG, 0.23 (0.01) for MUSC, and 0.48 (0.01) for SC18. The posterior mean estimates (95% confidence interval in parentheses) for the genetic correlation with survival were 0.16 (0.13-0.19), 0.30 (0.25-0.34), 0.31 (0.25-0.36), 0.07 (0.02-0.12), and 0.82 (0.78-0.86) for WW, PWG, MUSC, SC18, and HP, respectively. Based on the high genetic correlation and heritability (0.54) posterior mean estimates for HP, the expected progeny difference for HP can be used to select bulls for longevity, as well as for post-weaning gain and muscle score.

Dynamical estimates of chaotic systems from Poincare recurrences

We show a function that fits well the probability density of return times between two consecutive visits of a chaotic trajectory to finite size regions in phase space. It deviates from the exponential statistics by a small power-law term, a term that represents the deterministic manifestation of the dynamics. We also show how one can quickly and easily estimate the Kolmogorov-Sinai entropy and the short-term correlation function by realizing observations of high probable returns. Our analyses are performed numerically in the Henon map and experimentally in a Chua's circuit. Finally, we discuss how our approach can be used to treat the data coming from experimental complex systems and for technological applications. (C) 2009 American Institute of Physics. [doi: 10.1063/1.3263943]

Parametric correlation functions to model the structure of permanent environmental (co)variances in milk yield random regression models

The objective of the present study was to estimate milk yield genetic parameters applying random regression models and parametric correlation functions combined with a variance function to model animal permanent environmental effects. A total of 152,145 test-day milk yields from 7,317 first lactations of Holstein cows belonging to herds located in the southeastern region of Brazil were analyzed. Test-day milk yields were divided into 44 weekly classes of days in milk. Contemporary groups were defined by herd-test-day comprising a total of 2,539 classes. The model included direct additive genetic, permanent environmental, and residual random effects. The following fixed effects were considered: contemporary group, age of cow at calving (linear and quadratic regressions), and the population average lactation curve modeled by fourth-order orthogonal Legendre polynomial. Additive genetic effects were modeled by random regression on orthogonal Legendre polynomials of days in milk, whereas permanent environmental effects were estimated using a stationary or nonstationary parametric correlation function combined with a variance function of different orders. The structure of residual variances was modeled using a step function containing 6 variance classes. The genetic parameter estimates obtained with the model using a stationary correlation function associated with a variance function to model permanent environmental effects were similar to those obtained with models employing orthogonal Legendre polynomials for the same effect. A model using a sixth-order polynomial for additive effects and a stationary parametric correlation function associated with a seventh-order variance function to model permanent environmental effects would be sufficient for data fitting.

Genetic variation for anatomic traits and volume shrinkage and their correlation with wood basic density in an Eucalyptus camaldulensis Dehn base population

Eucalyptus camaldulensis has great importance in Brazil because of their phenotypic plasticity for different environmental conditions, as soils, altitudes and rainfall. This study is an investigation of a base population of E. camaldulensis from Australia through a progeny test implanted in Selviria, MS. The trial was established in a randomized block design, with 25 families and 60 replications of single tree plots. Genetic parameters for anatomic traits and volume shrinkage were estimated, as well as their correlations with wood basic density. No significant differences among progenies were observed for the traits studied. The additive genetic variation coefficient at individual and among progeny levels ranged from low (0.26%) to high (16.98%). The narrow sense heritability at individual and family means levels also ranged from low (0.01) to high (0.87). This indicates that some traits are under strong genetic control and can be improved by selection. In the present situation, in order to attain the highest genetic gains, the sequential selection among and within progeny would be recommended.

Principal components and generalized linear modeling in the correlation between hospital admissions and air pollution

OBJECTIVE To analyze the association between concentrations of air pollutants and admissions for respiratory causes in children. METHODS Ecological time series study. Daily figures for hospital admissions of children aged < 6, and daily concentrations of air pollutants (PM10, SO2, NO2, O3 and CO) were analyzed in the Região da Grande Vitória, ES, Southeastern Brazil, from January 2005 to December 2010. For statistical analysis, two techniques were combined: Poisson regression with generalized additive models and principal model component analysis. Those analysis techniques complemented each other and provided more significant estimates in the estimation of relative risk. The models were adjusted for temporal trend, seasonality, day of the week, meteorological factors and autocorrelation. In the final adjustment of the model, it was necessary to include models of the Autoregressive Moving Average Models (p, q) type in the residuals in order to eliminate the autocorrelation structures present in the components. RESULTS For every 10:49 μg/m3 increase (interquartile range) in levels of the pollutant PM10 there was a 3.0% increase in the relative risk estimated using the generalized additive model analysis of main components-seasonal autoregressive – while in the usual generalized additive model, the estimate was 2.0%. CONCLUSIONS Compared to the usual generalized additive model, in general, the proposed aspect of generalized additive model − principal component analysis, showed better results in estimating relative risk and quality of fit.

Exome sequencing extends the phenotypic spectrum for ABHD12 mutations: from syndromic to nonsyndromic retinal degeneration.

OBJECTIVE: To identify the genetic causes underlying autosomal recessive retinitis pigmentosa (arRP) and to describe the associated phenotype. DESIGN: Case series. PARTICIPANTS: Three hundred forty-seven unrelated families affected by arRP and 33 unrelated families affected by retinitis pigmentosa (RP) plus noncongenital and progressive hearing loss, ataxia, or both, respectively. METHODS: A whole exome sequencing (WES) analysis was performed in 2 families segregating arRP. A mutational screening was performed in 378 additional unrelated families for the exon-intron boundaries of the ABHD12 gene. To establish a genotype-phenotype correlation, individuals who were homozygous or compound heterozygotes of mutations in ABHD12 underwent exhaustive clinical examinations by ophthalmologists, neurologists, and otologists. MAIN OUTCOME MEASURES: DNA sequence variants, best-corrected visual acuity, visual field assessments, electroretinogram responses, magnetic resonance imaging, and audiography. RESULTS: After a WES analysis, we identified 4 new mutations (p.Arg107Glufs*8, p.Trp159*, p.Arg186Pro, and p.Thr202Ile) in ABHD12 in 2 families (RP-1292 and W08-1833) previously diagnosed with nonsyndromic arRP, which cosegregated with the disease among the family members. Another homozygous mutation (p.His372Gln) was detected in 1 affected individual (RP-1487) from a cohort of 378 unrelated arRP and syndromic RP patients. After exhaustive clinical examinations by neurologists and otologists, the 4 affected members of the RP-1292 had no polyneuropathy or ataxia, and the sensorineural hearing loss and cataract were attributed to age or the normal course of the RP, whereas the affected members of the families W08-1833 and RP-1487 showed clearly symptoms associated with polyneuropathy, hearing loss, cerebellar ataxia, RP, and early-onset cataract (PHARC) syndrome. CONCLUSIONS: Null mutations in the ABHD12 gene lead to PHARC syndrome, a neurodegenerative disease including polyneuropathy, hearing loss, cerebellar ataxia, RP, and early-onset cataract. Our study allowed us to report 5 new mutations in ABHD12. This is the first time missense mutations have been described for this gene. Furthermore, these findings are expanding the spectrum of phenotypes associated with ABHD12 mutations ranging from PHARC syndrome to a nonsyndromic form of retinal degeneration.

Estimation of the lateral correlation structure of subsurface water content from surface-based ground-penetrating radar reflection images

Over the past decade, significant interest has been expressed in relating the spatial statistics of surface-based reflection ground-penetrating radar (GPR) data to those of the imaged subsurface volume. A primary motivation for this work is that changes in the radar wave velocity, which largely control the character of the observed data, are expected to be related to corresponding changes in subsurface water content. Although previous work has indeed indicated that the spatial statistics of GPR images are linked to those of the water content distribution of the probed region, a viable method for quantitatively analyzing the GPR data and solving the corresponding inverse problem has not yet been presented. Here we address this issue by first deriving a relationship between the 2-D autocorrelation of a water content distribution and that of the corresponding GPR reflection image. We then show how a Bayesian inversion strategy based on Markov chain Monte Carlo sampling can be used to estimate the posterior distribution of subsurface correlation model parameters that are consistent with the GPR data. Our results indicate that if the underlying assumptions are valid and we possess adequate prior knowledge regarding the water content distribution, in particular its vertical variability, this methodology allows not only for the reliable recovery of lateral correlation model parameters but also for estimates of parameter uncertainties. In the case where prior knowledge regarding the vertical variability of water content is not available, the results show that the methodology still reliably recovers the aspect ratio of the heterogeneity.

When genetic load does not correlate with phenotypic spectrum: lessons from the GnRH receptor (GNRHR).

CONTEXT: A broad spectrum of GnRH-deficient phenotypes has been identified in individuals with both mono- and biallelic GNRHR mutations. OBJECTIVE: The objective of the study was to determine the correlation between the severity of the reproductive phenotype(s) and the number and functional severity of rare sequence variants in GNRHR. SUBJECTS: Eight hundred sixty-three probands with different forms of GnRH deficiency, 46 family members and 422 controls were screened for GNRHR mutations. The 70 subjects (32 patients and 38 family members) harboring mutations were divided into four groups (G1-G4) based on the functional severity of the mutations (complete or partial loss of function) and the number of affected alleles (monoallelic or biallelic) with mutations, and these classes were mapped on their clinical phenotypes. RESULTS: The prevalence of heterozygous rare sequence variants in GNRHR was significantly higher in probands vs. controls (P < 0.01). Among the G1-G3 groups (homozygous subjects with successively decreasing severity and number of mutations), the hypogonadotropic phenotype related to their genetic load. In contrast, subjects in G4, with only monoallelic mutations, demonstrated a greater diversity of clinical phenotypes. CONCLUSIONS: In patients with GnRH deficiency and biallelic mutations in GNRHR, genetic burden defined by severity and dose is associated with clinical phenotype. In contrast, for patients with monoallelic GNRHR mutations this correlation does not hold. Taken together, these data indicate that as-yet-unidentified genetic and/or environmental factors may combine with singly mutated GNRHR alleles to produce reproductive phenotypes.

Familiality and SNP heritability of age at onset and episodicity in major depressive disorder.

BACKGROUND: Strategies to dissect phenotypic and genetic heterogeneity of major depressive disorder (MDD) have mainly relied on subphenotypes, such as age at onset (AAO) and recurrence/episodicity. Yet, evidence on whether these subphenotypes are familial or heritable is scarce. The aims of this study are to investigate the familiality of AAO and episode frequency in MDD and to assess the proportion of their variance explained by common single nucleotide polymorphisms (SNP heritability). METHOD: For investigating familiality, we used 691 families with 2-5 full siblings with recurrent MDD from the DeNt study. We fitted (square root) AAO and episode count in a linear and a negative binomial mixed model, respectively, with family as random effect and adjusting for sex, age and center. The strength of familiality was assessed with intraclass correlation coefficients (ICC). For estimating SNP heritabilities, we used 3468 unrelated MDD cases from the RADIANT and GSK Munich studies. After similarly adjusting for covariates, derived residuals were used with the GREML method in GCTA (genome-wide complex trait analysis) software. RESULTS: Significant familial clustering was found for both AAO (ICC = 0.28) and episodicity (ICC = 0.07). We calculated from respective ICC estimates the maximal additive heritability of AAO (0.56) and episodicity (0.15). SNP heritability of AAO was 0.17 (p = 0.04); analysis was underpowered for calculating SNP heritability of episodicity. CONCLUSIONS: AAO and episodicity aggregate in families to a moderate and small degree, respectively. AAO is under stronger additive genetic control than episodicity. Larger samples are needed to calculate the SNP heritability of episodicity. The described statistical framework could be useful in future analyses.

Correlation of the IJK Roadmeter to the International Roughness Index, MLR-91-5, 1992

The Iowa Department of Transportation has been determining a present serviceability index (PSI) on the primary highway system since 1968. A CHLOE profilometer has been used as the standard for calibrating the Roadmeters that do the system survey. The current Roadmeter, an IJK Iowa DOT developed unit, is not considered an acceptable Roadmeter for determining the FHWA required International Roughness Index (IRI). Iowa purchased a commercial version of the South Dakota type profile (SD Unit) to obtain IRI. This study was undertaken to correlate the IRI to the IJK Roadmeter and retire the Roadmeter. One hundred forty-seven pavement management sections (IPMS) were tested in June and July 1991 with both units. Correlation coefficients and standard error of estimates were: r' Std. Error PCC pavements 0.81 0.15 Composite pavements 0.71 0.18 ACC pavements 0.77 0.17 The correlation equations developed from this work will allow use of the IRI to predict the IJK Roadmeter response with sufficient accuracy. Trend analysis should also not be affected.

Phenotypic stability and genetic gains in six-year girth growth of Hevea clones

Rubber tree [Hevea brasiliensis (Willd. ex Adr. de Juss.) Müell. Arg.] budgrafts of seven clones were evaluated on five contrasting sites in the plateau region of the São Paulo State, Brazil. The objective of this work was to study the phenotypic stability for girth growth. The experimental design was a randomized block design with three replications and seven treatments. Analysis of variance of girth at six-year plant growth indicated a highly significant clone x site interaction. Only linear sites and clone x site components of clone x year interaction were significant, indicating that the performance of clones over sites for this trait could be predicted. The clones GT 1 and PB 235 showed the greatest stability in relation to girth growth, with foreseen responses to change, introduced in the sites. The clones PB 235 and IAN 873 showed significative difference in relation to regression coefficient, representing clones with specific adaptability on favorable and unfavorable sites respectively. The clone GT 1 became the most promissory one in the study of stability and adaptability even showing low girth growth. Expected genetic gains from planting sites, along with estimates of clonal variance and repeatability of clonal means are generally greatest or close to the greatest when selection is done at the same site.

Correlation between microtensile bond strength data and clinical outcome of Class V restorations.

OBJECTIVE: To determine if the results of resin-dentin microtensile bond strength (µTBS) is correlated with the outcome parameters of clinical studies on non-retentive Class V restorations. METHODS: Resin-dentin µTBS data were obtained from one test center; the in vitro tests were all performed by the same operator. The µTBS testing was performed 8h after bonding and after 6 months of storing the specimens in water. Pre-test failures (PTFs) of specimens were included in the analysis, attributing them a value of 1MPa. Prospective clinical studies on cervical restorations (Class V) with an observation period of at least 18 months were searched in the literature. The clinical outcome variables were retention loss, marginal discoloration and marginal integrity. Furthermore, an index was formulated to be better able to compare the laboratory and clinical results. Estimates of adhesive effects in a linear mixed model were used to summarize the clinical performance of each adhesive between 12 and 36 months. Spearman correlations between these clinical performances and the µTBS values were calculated subsequently. RESULTS: Thirty-six clinical studies with 15 adhesive/restorative systems for which µTBS data were also available were included in the statistical analysis. In general 3-step and 2-step etch-and-rinse systems showed higher bond strength values than the 2-step/3-step self-etching systems, which, however, produced higher values than the 1-step self-etching and the resin modified glass ionomer systems. Prolonged water storage of specimens resulted in a significant decrease of the mean bond strength values in 5 adhesive systems (Wilcoxon, p<0.05). There was a significant correlation between µTBS values both after 8h and 6 months of storage and marginal discoloration (r=0.54 and r=0.67, respectively). However, the same correlation was not found between µTBS values and the retention rate, clinical index or marginal integrity. SIGNIFICANCE: As µTBS data of adhesive systems, especially after water storage for 6 months, showed a good correlation with marginal discoloration in short-term clinical Class V restorations, longitudinal clinical trials should explore whether early marginal staining is predictive for future retention loss in non-carious cervical restorations.

Assessing inter-rater reliability when the raters are fixed: two concepts and two estimates.

Intraclass correlation (ICC) is an established tool to assess inter-rater reliability. In a seminal paper published in 1979, Shrout and Fleiss considered three statistical models for inter-rater reliability data with a balanced design. In their first two models, an infinite population of raters was considered, whereas in their third model, the raters in the sample were considered to be the whole population of raters. In the present paper, we show that the two distinct estimates of ICC developed for the first two models can both be applied to the third model and we discuss their different interpretations in this context.

O6-Methylguanine-DNA methyltransferase protein expression by immunohistochemistry in brain and non-brain systemic tumours: systematic review and meta-analysis of correlation with methylation-specific polymerase chain reaction

Background: The DNA repair protein O6-Methylguanine-DNA methyltransferase (MGMT) confers resistance to alkylating agents. Several methods have been applied to its analysis, with methylation-specific polymerase chain reaction (MSP) the most commonly used for promoter methylation study, while immunohistochemistry (IHC) has become the most frequently used for the detection of MGMT protein expression. Agreement on the best and most reliable technique for evaluating MGMT status remains unsettled. The aim of this study was to perform a systematic review and meta-analysis of the correlation between IHC and MSP. Methods A computer-aided search of MEDLINE (1950-October 2009), EBSCO (1966-October 2009) and EMBASE (1974-October 2009) was performed for relevant publications. Studies meeting inclusion criteria were those comparing MGMT protein expression by IHC with MGMT promoter methylation by MSP in the same cohort of patients. Methodological quality was assessed by using the QUADAS and STARD instruments. Previously published guidelines were followed for meta-analysis performance. Results Of 254 studies identified as eligible for full-text review, 52 (20.5%) met the inclusion criteria. The review showed that results of MGMT protein expression by IHC are not in close agreement with those obtained with MSP. Moreover, type of tumour (primary brain tumour vs others) was an independent covariate of accuracy estimates in the meta-regression analysis beyond the cut-off value. Conclusions Protein expression assessed by IHC alone fails to reflect the promoter methylation status of MGMT. Thus, in attempts at clinical diagnosis the two methods seem to select different groups of patients and should not be used interchangeably.