976 resultados para Christoffel pairs
Resumo:
We present a shape-space approach for analyzing genetic influences on the shapes of the sulcal folding patterns on the cortex. Sulci are represented as continuously parameterized functions in a shape space, and shape differences between sulci are obtained via geodesics between them. The resulting statistical shape analysis framework is used not only to construct populations averages, but also used to compute meaningful correlations within and across groups of sulcal shapes. More importantly, we present a new algorithm that extends the traditional Euclidean estimate of the intra-class correlation to the geometric shape space, thereby allowing us to study heritability of sulcal shape traits for a population of 193 twin pairs. This new methodology reveals strong genetic influences on the sulcal geometry of the cortex.
Resumo:
We used diffusion tensor magnetic resonance imaging (DTI) to reveal the extent of genetic effects on brain fiber microstructure, based on tensor-derived measures, in 22 pairs of monozygotic (MZ) twins and 23 pairs of dizygotic (DZ) twins (90 scans). After Log-Euclidean denoising to remove rank-deficient tensors, DTI volumes were fluidly registered by high-dimensional mapping of co-registered MP-RAGE scans to a geometrically-centered mean neuroanatomical template. After tensor reorientation using the strain of the 3D fluid transformation, we computed two widely used scalar measures of fiber integrity: fractional anisotropy (FA), and geodesic anisotropy (GA), which measures the geodesic distance between tensors in the symmetric positive-definite tensor manifold. Spatial maps of intraclass correlations (r) between MZ and DZ twins were compared to compute maps of Falconer's heritability statistics, i.e. the proportion of population variance explainable by genetic differences among individuals. Cumulative distribution plots (CDF) of effect sizes showed that the manifold measure, GA, comparably the Euclidean measure, FA, in detecting genetic correlations. While maps were relatively noisy, the CDFs showed promise for detecting genetic influences on brain fiber integrity as the current sample expands.
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Information from the full diffusion tensor (DT) was used to compute voxel-wise genetic contributions to brain fiber microstructure. First, we designed a new multivariate intraclass correlation formula in the log-Euclidean framework. We then analyzed used the full multivariate structure of the tensor in a multivariate version of a voxel-wise maximum-likelihood structural equation model (SEM) that computes the variance contributions in the DTs from genetic (A), common environmental (C) and unique environmental (E) factors. Our algorithm was tested on DT images from 25 identical and 25 fraternal twin pairs. After linear and fluid registration to a mean template, we computed the intraclass correlation and Falconer's heritability statistic for several scalar DT-derived measures and for the full multivariate tensors. Covariance matrices were found from the DTs, and inputted into SEM. Analyzing the full DT enhanced the detection of A and C effects. This approach should empower imaging genetics studies that use DTI.
Resumo:
We present a new algorithm to compute the voxel-wise genetic contribution to brain fiber microstructure using diffusion tensor imaging (DTI) in a dataset of 25 monozygotic (MZ) twins and 25 dizygotic (DZ) twin pairs (100 subjects total). First, the structural and DT scans were linearly co-registered. Structural MR scans were nonlinearly mapped via a 3D fluid transformation to a geometrically centered mean template, and the deformation fields were applied to the DTI volumes. After tensor re-orientation to realign them to the anatomy, we computed several scalar and multivariate DT-derived measures including the geodesic anisotropy (GA), the tensor eigenvalues and the full diffusion tensors. A covariance-weighted distance was measured between twins in the Log-Euclidean framework [2], and used as input to a maximum-likelihood based algorithm to compute the contributions from genetics (A), common environmental factors (C) and unique environmental ones (E) to fiber architecture. Quanititative genetic studies can take advantage of the full information in the diffusion tensor, using covariance weighted distances and statistics on the tensor manifold.
Resumo:
Twin studies are a major research direction in imaging genetics, a new field, which combines algorithms from quantitative genetics and neuroimaging to assess genetic effects on the brain. In twin imaging studies, it is common to estimate the intraclass correlation (ICC), which measures the resemblance between twin pairs for a given phenotype. In this paper, we extend the commonly used Pearson correlation to a more appropriate definition, which uses restricted maximum likelihood methods (REML). We computed proportion of phenotypic variance due to additive (A) genetic factors, common (C) and unique (E) environmental factors using a new definition of the variance components in the diffusion tensor-valued signals. We applied our analysis to a dataset of Diffusion Tensor Images (DTI) from 25 identical and 25 fraternal twin pairs. Differences between the REML and Pearson estimators were plotted for different sample sizes, showing that the REML approach avoids severe biases when samples are smaller. Measures of genetic effects were computed for scalar and multivariate diffusion tensor derived measures including the geodesic anisotropy (tGA) and the full diffusion tensors (DT), revealing voxel-wise genetic contributions to brain fiber microstructure.
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We study the influence of the choice of template in tensor-based morphometry. Using 3D brain MR images from 10 monozygotic twin pairs, we defined a tensor-based distance in the log-Euclidean framework [1] between each image pair in the study. Relative to this metric, twin pairs were found to be closer to each other on average than random pairings, consistent with evidence that brain structure is under strong genetic control. We also computed the intraclass correlation and associated permutation p-value at each voxel for the determinant of the Jacobian matrix of the transformation. The cumulative distribution function (cdf) of the p-values was found at each voxel for each of the templates and compared to the null distribution. Surprisingly, there was very little difference between CDFs of statistics computed from analyses using different templates. As the brain with least log-Euclidean deformation cost, the mean template defined here avoids the blurring caused by creating a synthetic image from a population, and when selected from a large population, avoids bias by being geometrically centered, in a metric that is sensitive enough to anatomical similarity that it can even detect genetic affinity among anatomies.
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Understanding the aetiology of patterns of variation within and covariation across brain regions is key to advancing our understanding of the functional, anatomical and developmental networks of the brain. Here we applied multivariate twin modelling and principal component analysis (PCA) to investigate the genetic architecture of the size of seven subcortical regions (caudate nucleus, thalamus, putamen, pallidum, hippocampus, amygdala and nucleus accumbens) in a genetically informative sample of adolescents and young adults (N=1038; mean age=21.6±3.2years; including 148 monozygotic and 202 dizygotic twin pairs) from the Queensland Twin IMaging (QTIM) study. Our multivariate twin modelling identified a common genetic factor that accounts for all the heritability of intracranial volume (0.88) and a substantial proportion of the heritability of all subcortical structures, particularly those of the thalamus (0.71 out of 0.88), pallidum (0.52 out of 0.75) and putamen (0.43 out of 0.89). In addition, we also found substantial region-specific genetic contributions to the heritability of the hippocampus (0.39 out of 0.79), caudate nucleus (0.46 out of 0.78), amygdala (0.25 out of 0.45) and nucleus accumbens (0.28 out of 0.52). This provides further insight into the extent and organization of subcortical genetic architecture, which includes developmental and general growth pathways, as well as the functional specialization and maturation trajectories that influence each subcortical region. This multivariate twin study identifies a common genetic factor that accounts for all the heritability of intracranial volume (0.88) and a substantial proportion of the heritability of all subcortical structures, particularly those of the thalamus (0.71 out of 0.88), pallidum (0.52 out of 0.75) and putamen (0.43 out of 0.89). In parallel, it also describes substantial region-specific genetic contributions to the heritability of the hippocampus (0.39 out of 0.79), caudate nucleus (0.46 out of 0.78), amygdala (0.25 out of 0.45) and nucleus accumbens (0.28 out of 0.52).
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The Older Australian Twins Study (OATS) was recently initiated to investigate genetic and environmental factors and their associations and interactions in healthy brain ageing and ageing-related neurocognitive disorders. The study extends the classic MZ-DZ design to include one or two equivalently aged siblings for each twin pair and utilizes the rich resources of the Australian Twin Registry. The study has a number of distinguishing features including comprehensive psychiatric, neuropsychological, cardiovascular, metabolic, and neuroimaging assessments, a longitudinal design and links with a brain donor program. The study measures many behavioral and environmental factors, but in particular lifetime physical and mental activity, physical and psychological trauma, loss of parent early in life, later losses and life events, early-life socioeconomic environment, alcohol and drug use, occupational exposure, and nutrition. It also includes comprehensive cardiovascular assessment, blood biochemistry, genetics and proteomics. The socio-demographic and health data on the first 172 pairs of twins participating in this study are presented. Prevalence of mild cognitive impairment is 12.8% and of dementia 1.5% in the sample. The target sample size is 1000, with at least 400 pairs of twins aged 65-90 years. The cohort will be assessed every two years, with in-depth assessments being repeated. OATS offers an excellent opportunity for collaboration with other similar studies as well as researchers who share the same interests.
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Aim: To examine the concordance rates of common medical conditions and neurocognitive performance in monozygotic (MZ) and dizygotic (DZ) older twins. Methods: Twins aged ≥65 years and living in the three Eastern states of Australia were recruited through the Australian Twin Registry and underwent detailed neuropsychological and medical assessment. Results: Assessments were conducted on 113 MZ and 96 DZ twin pairs, with a mean age of 70.5 years. MZ twins were more concordant than DZ twins for hypertension and asthma. MZ twins had higher correlations than DZ twins on most neuropsychological tests, with the exception of some tests related to processing speed. The concordance rate for mild cognitive impairment or dementia was 76.2% in MZ twins and 42.9% in DZ twins, a non-significant difference. Conclusions: Except for some aspects of processing speed, most cognitive functions in older individuals show significant heritability. The heritability of neurocognitive disorders is, however, low.
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Heritability of brain anatomical connectivity has been studied with diffusion-weighted imaging (DWI) mainly by modeling each voxel's diffusion pattern as a tensor (e.g., to compute fractional anisotropy), but this method cannot accurately represent the many crossing connections present in the brain. We hypothesized that different brain networks (i.e., their component fibers) might have different heritability and we investigated brain connectivity using High Angular Resolution Diffusion Imaging (HARDI) in a cohort of twins comprising 328 subjects that included 70 pairs of monozygotic and 91 pairs of dizygotic twins. Water diffusion was modeled in each voxel with a Fiber Orientation Distribution (FOD) function to study heritability for multiple fiber orientations in each voxel. Precision was estimated in a test-retest experiment on a sub-cohort of 39 subjects. This was taken into account when computing heritability of FOD peaks using an ACE model on the monozygotic and dizygotic twins. Our results confirmed the overall heritability of the major white matter tracts but also identified differences in heritability between connectivity networks. Inter-hemispheric connections tended to be more heritable than intra-hemispheric and cortico-spinal connections. The highly heritable tracts were found to connect particular cortical regions, such as medial frontal cortices, postcentral, paracentral gyri, and the right hippocampus.
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In 2014, the northern outlying population of carnivorous marsupial Dusky Antechinus (Antechinus swainsonii) was nominated a new species, A. arktos. Here, we describe a further new species in the dasyurid A. swainsonii complex, which now contains five taxa. We recognise two distinct species from Tasmania, formerly represented by A. swainsonii swainsonii (Waterhouse); one species (and 2 subspecies) from mainland south-eastern Australia, formerly known as A. swainsonii mimetes (Thomas) and A. swainsonii insulanus Davison; and one species from the Tweed Caldera in mid-eastern Australia, formerly known as A. s. mimetes but recently described as A. arktos Baker, Mutton, Hines and Van Dyck. Primacy of discovery dictates the Tasmanian Dusky Antechinus A. swainsonii (Waterhouse) is nominate; the Mainland Dusky Antechinus taxa, one raised from subspecies within A. swainsonii mimetes (Thomas) is elevated to species (now A. mimetes mimetes) and the other, A. swainsonii insulanus Davison is transferred as a subspecies of A. mimetes (now A. mimetes insulanus); a species from Tasmania, the Tasman Peninsula Dusky Antechinus, is named A. vandycki sp. nov. These taxa are strongly differentiated: geographically (in allopatry), morphologically (in coat colour and craniodental features) and genetically (in mtDNA, 7.5-12.5% between species pairs).
Resumo:
Nutrition plays an important role in the development of all organisms and in particular that of farmed aquatic species where costs associated with feed can often exceed 60% of total production costs. Crustacean species in addition, have the added metabolic requirement for regular moulting to allow normal growth and this requires large amounts of energy in the form of sugars (glucose). The current study explored the capacity of the giant freshwater prawn to produce endogenous cellulose-degrading enzymes capable of extracting nutrients (simple sugars) from plant sources in formulated feeds used in the prawn aquaculture industry. We identified a putative cellulase cDNA fragment in the target organism of 1576 base pairs in length of non-microbial origin that after protein modelling exhibited a TM-score of 0.916 with a described cellulase reported from another crustacean species. The functional role of cellulase enzymes is to hydrolyse cellulose to glucose and the fragment identified in GFP was highly expressed in the hepatopancreas, the site of primary food digestion and absorption in crustaceans. Hepatopancreatic tissue from Macrobrachium rosenbergii also showed active digestion of cellulose to glucose following an endoglucanase assay. Cellulase gene(s) are present in the genomes of many invertebrate taxa and play an active role in the conversion of cellulose to available energy. Identification and characterization of endogenous cellulase gene(s) in giant freshwater prawn can assist development of the culture industry because the findings confirm that potentially greater levels of low-cost plant-material could be included in artificial formulated diets in the future without necessarily compromising individual growth performance. Ultimately, this development may contribute to more efficient, cost-effective production systems for freshwater prawn culture stocks that meet the animal's basic nutritional requirements and that also support good individual growth rates.
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This cross-sectional study assessed intellect, cognition, academic function, behaviour, and emotional health of long-term survivors after childhood liver transplantation. Eligible children were >5 yr post-transplant, still attending school, and resident in Queensland. Hearing and neurocognitive testing were performed on 13 transplanted children and six siblings including two twin pairs where one was transplanted and the other not. Median age at testing was 13.08 (range 6.52-16.99) yr; time elapsed after transplant 10.89 (range 5.16-16.37) yr; and age at transplant 1.15 (range 0.38-10.00) yr. Mean full-scale IQ was 97 (81-117) for transplanted children and 105 (87-130) for siblings. No difficulties were identified in intellect, cognition, academic function, and memory and learning in transplanted children or their siblings, although both groups had reduced mathematical ability compared with normal. Transplanted patients had difficulties in executive functioning, particularly in self-regulation, planning and organization, problem-solving, and visual scanning. Thirty-one percent (4/13) of transplanted patients, and no siblings, scored in the clinical range for ADHD. Emotional difficulties were noted in transplanted patients but were not different from their siblings. Long-term liver transplant survivors exhibit difficulties in executive function and are more likely to have ADHD despite relatively intact intellect and cognition.
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Korean rose bitterling (Rhodeus uyekii) is a freshwater fish endemic to Korea. Natural populations of this species have experienced severe declines as a result of habitat fragmentation and water pollution. To conserve and restore R. uyekii, the genetic diversity of this species needs to be assessed at the population level. Eighteen novel polymorphic microsatellite loci for R. uyekii were developed using an enriched partial genomic library. Polymorphisms at these loci were studied in 150 individuals collected from three populations. The number of alleles at each locus ranged from 3 to 47 (mean = 17.1). Within the populations, the observed heterozygosity ranged from 0.032 to 1.000, expected heterozygosity from 0.082 to 0.967, and polymorphism information content from 0.078 to 0.950. Six loci showed significant deviation from Hardy-Weinberg equilibrium after Bonferroni’s correction, and no significant linkage disequilibrium was detected between most locus pairs, except in three cases. These highly informative microsatellite markers should be useful for genetic population structure analyses of R. uyekii.
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Ankylosing spondylitis (AS) is a common inflammatory arthritis predominantly affecting the axial skeleton. Susceptibility to the disease is thought to be oligogenic. To identify the genes involved, we have performed a genomewide scan in 185 families containing 255 affected sibling pairs. Two-point and multipoint nonparametric linkage analysis was performed. Regions were identified showing "suggestive" or stronger linkage with the disease on chromosomes 1p, 2q, 6p, 9q, 10q, 16q, and 19q. The MHC locus was identified as encoding the greatest component of susceptibility, with an overall LOD score of 15.6. The strongest non-MHC linkage lies on chromosome 16q (overall LOD score 4.7). These results strongly support the presence of non-MHC genetic-susceptibility factors in AS and point to their likely locations.