Diagnosis of autistic spectrum disorders in Queensland: Variations in practice

Objective: For both paediatricians and child psychiatrists, referrals to assess possible autistic spectrum disorders (ASD) are increasing. This study examines current practices of medical specialists in the assessment of these disorders. Methods: An anonymous, self-report questionnaire was sent to all Queensland paediatricians and child psychiatrists. The survey elicited frequencies of consultation for ASD, diagnostic method, advice provided and perceived adequacy of training for this work. Results: Responses were received from 79 (85%) eligible paediatricians and 26 (58%) eligible child psychiatrists. For one-third of all clinicians, new consultations for possible ASD occurred as often as 2-3 times per week. Most specialists approached the clinical diagnosis of ASD by considering history from different sources and professional assessments. Paediatricians (86%) were more likely than child psychiatrists (62%) to request genetic studies for children with severe autism (P = 0.01). Both general paediatricians and developmental paediatricians perceived level of training for possible ASD consultations was significantly worse than child psychiatrists (P < 0.001 and P = 0.02, respectively), but no difference was found between paediatric groups (P = 0.27). Perceived adequacy of specialist training was not associated with length of experience in clinical practice. Conclusion: Medical practice in Queensland around diagnosis of ASD is characterized by considerable variability. There is still a long way to go if we are to achieve consistency around medical issues of organic diagnosis and practices impacting on health as well as consideration of differential developmental diagnoses. The finding that recently trained paediatricians felt just as unprepared for this work as their older colleagues suggests that the graduate training response to this 'new morbidity' has not been adequate.

Optimal design of a regenerative dynamic dynamometer using genetic algorithms

This paper presents an approach for optimal design of a fully regenerative dynamic dynamometer using genetic algorithms. The proposed dynamometer system includes an energy storage mechanism to adaptively absorb the energy variations following the dynamometer transients. This allows the minimum power electronics requirement at the mains power supply grid to compensate for the losses. The overall dynamometer system is a dynamic complex system and design of the system is a multi-objective problem, which requires advanced optimisation techniques such as genetic algorithms. The case study of designing and simulation of the dynamometer system indicates that the genetic algorithm based approach is able to locate a best available solution in view of system performance and computational costs.

Self Evolving Character Recognition Using Genetic Operators

In this paper, a novel approach for character recognition has been presented with the help of genetic operators which have evolved from biological genetics and help us to achieve highly accurate results. A genetic algorithm approach has been described in which the biological haploid chromosomes have been implemented using a single row bit pattern of 315 values which have been operated upon by various genetic operators. A set of characters are taken as an initial population from which various new generations of characters are generated with the help of selection, crossover and mutation. Variations of population of characters are evolved from which the fittest solution is found by subjecting the various populations to a new fitness function developed. The methodology works and reduces the dissimilarity coefficient found by the fitness function between the character to be recognized and members of the populations and on reaching threshold limit of the error found from dissimilarity, it recognizes the character. As the new population is being generated from the older population, traits are passed on from one generation to another. We present a methodology with the help of which we are able to achieve highly efficient character recognition.

Theoretical model simulations for variations in thermal reaction norms

Thermal reaction norms for growth rates of six Emiliania huxleyi isolates originating from the central Atlantic (Azores, Portugal) and five isolates from the coastal North Atlantic (Bergen, Norway) were assessed. We used the template mode of variation model to decompose variations in growth rates into modes of biological interest: vertical shift, horizontal shift, and generalist-specialist variation. In line with the actual habitat conditions, isolates from Bergen (Bergen population) grew well at lower temperatures, and isolates from the Azores (Azores population) performed better at higher temperatures. The optimum growth temperature of the Azores population was significantly higher than that of the Bergen population. Neutral genetic differentiation was found between populations by microsatellite analysis. These findings indicate that E. huxleyi populations are adapted to local temperature regimes. Next to between-population variation, we also found variation within populations. Genotype-by-environment interactions resulted in the most pronounced phenotypic differences when isolates were exposed to temperatures outside the range they naturally encounter. Variation in thermal reaction norms between and within populations emphasizes the importance of using more than one isolate when studying the consequences of global change on marine phytoplankton. Phenotypic plasticity and standing genetic variation will be important in determining the potential of natural E. huxleyi populations to cope with global climate change.

Interpreting Human Genetic Variation through Genomics and In Vivo Models

Improvements in genomic technology, both in the increased speed and reduced cost of sequencing, have expanded the appreciation of the abundance of human genetic variation. However the sheer amount of variation, as well as the varying type and genomic content of variation, poses a challenge in understanding the clinical consequence of a single mutation. This work uses several methodologies to interpret the observed variation in the human genome, and presents novel strategies for the prediction of allele pathogenicity.

Using the zebrafish model system as an in vivo assay of allele function, we identified a novel driver of Bardet-Biedl Syndrome (BBS) in CEP76. A combination of targeted sequencing of 785 cilia-associated genes in a cohort of BBS patients and subsequent in vivo functional assays recapitulating the human phenotype gave strong evidence for the role of CEP76 mutations in the pathology of an affected family. This portion of the work demonstrated the necessity of functional testing in validating disease-associated mutations, and added to the catalogue of known BBS disease genes.

Further study into the role of copy-number variations (CNVs) in a cohort of BBS patients showed the significant contribution of CNVs to disease pathology. Using high-density array comparative genomic hybridization (aCGH) we were able to identify pathogenic CNVs as small as several hundred bp. Dissection of constituent gene and in vivo experiments investigating epistatic interactions between affected genes allowed for an appreciation of several paradigms by which CNVs can contribute to disease. This study revealed that the contribution of CNVs to disease in BBS patients is much higher than previously expected, and demonstrated the necessity of consideration of CNV contribution in future (and retrospective) investigations of human genetic disease.

Finally, we used a combination of comparative genomics and in vivo complementation assays to identify second-site compensatory modification of pathogenic alleles. These pathogenic alleles, which are found compensated in other species (termed compensated pathogenic deviations [CPDs]), represent a significant fraction (from 3 – 10%) of human disease-associated alleles. In silico pathogenicity prediction algorithms, a valuable method of allele prioritization, often misrepresent these alleles as benign, leading to omission of possibly informative variants in studies of human genetic disease. We created a mathematical model that was able to predict CPDs and putative compensatory sites, and functionally showed in vivo that second-site mutation can mitigate the pathogenicity of disease alleles. Additionally, we made publically available an in silico module for the prediction of CPDs and modifier sites.

These studies have advanced the ability to interpret the pathogenicity of multiple types of human variation, as well as made available tools for others to do so as well.

Peroxisome Proliferator-Activated Receptor-γ Coactivator 1-α (PPARGC1A) Genetic Associations with Type 2 Diabetes in Three Ethnicities

Genetic heterogeneity, lifestyle factors, gene-gene or gene-environment interactions are the determinants of T2D which puts Hispanics and populations with African ancestry at higher risk of developing T2D. In this dissertation, the genetic associations of PPARGC1A polymorphisms with T2D and its related phenotypes (metabolic markers) in Haitian Americans (cases=110, controls=116), African Americans (cases=120, controls=124) and Cuban Americans (cases=160, controls=181) of South Florida were explored. Five single nucleotide polymorphisms of gene PPARGC1A were evaluated in each ethnicity for their disease association. In Haitian Americans, rs7656250 (OR= 0.22, pp=0.03) had significant protective association with T2D but had risk association in African Americans for rs7656250 (OR=1.02, p=0.96) and rs4235308 (OR=2.53, p=0.03). We found that in Haitian American females, both rs7656250 (OR=0.23, pp=0.03) had protective association with T2D. In African American females, rs7656250 (OR=1.14, p=0.78) had risk association whereas in males, it had significant protective effect (OR=0.37, p=0.04). However, the risk association exhibited by rs4235308 was stronger in African American females (OR=2.69, p=0.03) than males (OR=1.16, p=0.72). In Cuban Americans, only rs7656250 showed significant risk association with T2D (OR=6.87, p=0.02) which was stronger in females alone (OR=7.67, p=0.01). We also observed significant differences among correlations of PPARGC1A SNPs and T2D phenotypes. Positive correlation was observed for log Hs-CRP with rs3774907 (pp=0.03) in Cuban Americans respectively. Correlation of log A1C with rs7656250 (p=0.02) was positive in Cuban Americans while it was negative for rs3774907 in Haitian Americans (ppPPARGC1A correlations with T2D and its phenotypes among the three ethnicities studied (ii) the associations of PPARGC1A SNPs showed significant effect modification by sex. The findings suggest that variations in effects of PPARGC1A gene polymorphisms among three ethnicities and between sexes may have biomedical implications for the development of T2D as well as the phenotypes related to T2D.

Étude de variations génétiques et épigénétiques de gènes candidats des complications métaboliques de l'obésité

L’obésité est de nos jours un problème croissant à travers le monde. La morbidité qui y est associée est surtout reliée au développement des différentes composantes du syndrome métabolique (SMet), une constellation de facteurs de risque regroupant l’hypertension, la dyslipidémie (concentration faible de cholestérol des lipoprotéines à haute densité (C-HDL) et élevée de triglycérides (TG)), l’hyperglycémie et l’obésité. Cependant, certains sujets obèses demeurent métaboliquement sains. Les facteurs génétiques joueraient donc un rôle important dans le développement de l’obésité et de ses complications. Les facteurs épigénétiques semblent également y avoir des effets. L’analyse de tissu adipeux viscéral (TAV) a donc été réalisée pour mener à la découverte de plusieurs gènes différentiellement exprimés et méthylés entre les obèses atteints et non atteints par le SMet. Les deux gènes candidats NMT1 et DGKZ font partie de ce groupe et leurs associations avec les composantes du SMet ont été testées. Leurs niveaux de méthylation et d’expression génique ont aussi été analysés.

Development, characterization and use of genomic SSR markers for assessment of genetic diversity in some Saudi date palm ( Phoenix dactylifera L.) cultivars

Background: The present study was undertaken towards the development of SSR markers and assessing genetic relationships among 32 date palm ( Phoenix dactylifera L.) representing common cultivars grown in different geographical regions in Saudi Arabia. Results: Ninety-three novel simple sequence repeat markers were developed and screened for their ability to detect polymorphism in date palm. Around 71% of genomic SSRs were dinucleotide, 25% tri, 3% tetra and 1% penta nucleotide motives. Twenty-two primers generated a total of 91 alleles with a mean of 4.14 alleles per locus and 100% polymorphism percentage. A 0.595 average polymorphic information content and 0.662 primer discrimination power values were recorded. The expected and observed heterozygosities were 0.676 and 0.763 respectively. Pair-wise similarity values ranged from 0.06 to 0.89 and the overall cultivars averaged 0.41. The UPGMA cluster analysis recovered by principal coordinate analysis illustrated that cultivars tend to group according to their class of maturity, region of cultivation, and fruit color. Analysis of molecular variations (AMOVA) revealed that genetic variation among and within cultivars were 27% and 73%, respectively according to geographical distribution of cultivars. Conclusions: The developed microsatellite markers are additional values to date palm characterization tools that can be used by researchers in population genetics, cultivar identification as well as genetic resource exploration and management. The tested cultivars exhibited a significant amount of genetic diversity and could be suitable for successful breeding program. Genomic sequences generated from this study are available at the National Center for Biotechnology Information (NCBI), Sequence Read Archive (Accession numbers. LIBGSS_039019).

A genetic variant of the CAPN10 gene in Mexican subjects with dyslipidemia is associated with increased HDL-cholesterol concentrations after the consumption of a soy protein and soluble fiber dietary portfolio

Dyslipidemia is a major public health problem, and therefore, it is important to develop dietary strategies to diminish the prevalence of this disorder. It was recently reported that diet may play an important role in triggering insulin resistance by interacting with genetic variants at the CAPN10 gene locus in patients with metabolic syndrome. Nonetheless, it remains unknown whether genetic variants of genes involved in the development of type 2 diabetes are associated with variations in high-density lipoprotein cholesterol (HDL-C). The study used a single-center, prospective, cohort design. Here, we assessed the effect of four variants of the CAPN10 gene on HDL-C levels in response to a soy protein and soluble fiber dietary portfolio in subjects with dyslipidemia. In 31 Mexican dyslipidemic individuals, we analyzed four CAPN10 gene variants (rs5030952, rs2975762, rs3792267, and rs2975760) associated with type 2 diabetes. Subjects with the GG genotype of the rs2975762 variant of the CAPN10 gene were better responders to dietary intervention, showing increased HDL-C concentrations from the first month of treatment. HDL-C concentrations in participants with the wild type genotype increased by 17.0%, whereas the HDL-C concentration in subjects with the variant genotypes increased by only 3.22% (p = 0.03); the low-density lipoprotein cholesterol levels of GG carriers tended to decrease (-12.6%). These results indicate that Mexican dyslipidemic carriers of the rs2975762-GG genotype are better responders to this dietary intervention.

Genetic diversity across geographical scales in marine coastal ecosystems: Holothuria arguinensis a model species

Coastal lagoons are considered one of the most productive areas of our planet harboring a large variety of habitats. Their transitional character, between terrestrial and marine environments, creates a very particular ecosystem with important variations of its environmental conditions. The organisms that are able to survive on these ecosystems frequently experience strong selective pressures and constrictions to gene flowwith marine populations, which could contribute to genetic divergence among populations inhabiting coastal lagoon and marine environments. Therefore, the main aims of this study are to asses the genetic diversity and population structure of Holothuria arguinensis across geographical ranges, to test the hypothesis of coastal lagoons as hotspots of genetic diversity in the Ria Formosa lagoon, and to determine the role of exporting standing genetic variation from the lagoon to open sea and their implications to recent geographical expansion events. To reach these objectives, we investigate the genetic structure of H. arguinensis using two mitochondrial DNA markers (COI and 16S) at different spatial scales: i) small, inside Ria Formosa coastal lagoon, South Portugal; 2) large, including most of the geographical distribution of this species (South and Western Portuguese coast and Canary islands); these results will allow us to compare the genetic diversity of lagoonal and marine populations of H. arguinensis. On this framework, its recent geographical expansion events, recorded by Rodrigues (2012) and González-Wangüemert and Borrero-Pérez (2012), will be analyzed considering the potential contribution from lagoonal genetic pool. Non-significant genetic structure and high haplotypic diversity were found inside the Ria Formosa coastal lagoon. Both genes were unable to detect significant genetic differentiation among lagoonal and marine localities, suggesting a high rate of gene flow. The results supported our hypotheses that coastal lagoons are not only acting as hotspots of genetic diversity, but also contributing for the genetic variability of the species, working as a source of new haplotypes and enhancing adaptation to the high variable conditions. Different genetic patterns of colonization were found on H. arguinensis, but they must be studied more deeply.

Genetic parameters for carcass traits and body weight using a Bayesian approach in the Canchim cattle.

Correlation between genetic parameters and factors such as backfat thickness (BFT), rib eye area (REA), and body weight (BW) were estimated for Canchim beef cattle raised in natural pastures of Brazil. Data from 1648 animals were analyzed using multi-trait (BFT, REA, and BW) animal models by the Bayesian approach. This model included the effects of contemporary group, age, and individual heterozygosity as covariates. In addition, direct additive genetic and random residual effects were also analyzed. Heritability estimated for BFT (0.16), REA (0.50), and BW (0.44) indicated their potential for genetic improvements and response to selection processes. Furthermore, genetic correlations between BW and the remaining traits were high (P > 0.50), suggesting that selection for BW could improve REA and BFT. On the other hand, genetic correlation between BFT and REA was low (P = 0.39 ± 0.17), and included considerable variations, suggesting that these traits can be jointly included as selection criteria without influencing each other. We found that REA and BFT responded to the selection processes, as measured by ultrasound. Therefore, selection for yearling weight results in changes in REA and BFT.