31 research outputs found

    Neuropathology of 16p13.11 Deletion in Epilepsy

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    16p13.11 genomic copy number variants are implicated in several neuropsychiatric disorders, such as schizophrenia, autism, mental retardation, ADHD and epilepsy. The mechanisms leading to the diverse clinical manifestations of deletions and duplications at this locus are unknown. Most studies favour NDE1 as the leading disease-causing candidate gene at 16p13.11. In epilepsy at least, the deletion does not appear to unmask recessive-acting mutations in NDE1, with haploinsufficiency and genetic modifiers being prime candidate disease mechanisms. NDE1 encodes a protein critical to cell positioning during cortical development. As a first step, it is important to determine whether 16p13.11 copy number change translates to detectable brain structural alteration. We undertook detailed neuropathology on surgically resected brain tissue of two patients with intractable mesial temporal lobe epilepsy (MTLE), who had the same heterozygous NDE1-containing 800 kb 16p13.11 deletion, using routine histological stains and immunohistochemical markers against a range of layer-specific, white matter, neural precursor and migratory cell proteins, and NDE1 itself. Surgical temporal lobectomy samples from a MTLE case known not to have a deletion in NDE1 and three non-epilepsy cases were included as disease controls. We found that apart from a 3 mm hamartia in the temporal cortex of one MTLE case with NDE1 deletion and known hippocampal sclerosis in the other case, cortical lamination and cytoarchitecture were normal, with no differences between cases with deletion and disease controls. How 16p13.11 copy changes lead to a variety of brain diseases remains unclear, but at least in epilepsy, it would not seem to be through structural abnormality or dyslamination as judged by microscopy or immunohistochemistry. The need to integrate additional data with genetic findings to determine their significance will become more pressing as genetic technologies generate increasingly rich datasets. Detailed examination of brain tissue, where available, will be an important part of this process in neurogenetic disease specifically

    Vitamin D supplementation for the prevention of type 2 diabetes in overweight adults: study protocol for a randomized controlled trial

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    Despite Australia's sunny climate, low vitamin D levels are increasingly prevalent. Sun exposure is limited by long working hours, an increase in time spent indoors, and sun protection practices, and there is limited dietary vitamin D fortification. While the importance of vitamin D for bone mineralization is well known, its role as a protective agent against chronic diseases, such as type 2 diabetes and cardiovascular disease, is less understood. Observational and limited intervention studies suggest that vitamin D might improve insulin sensitivity and secretion, mainly via its anti-inflammatory properties, thereby decreasing the risk of development and progression of type 2 diabetes. The primary aim of this trial is to investigate whether improved plasma concentrations of 25-hydroxyvitamin D (25(OH)D), obtained through vitamin D supplementation, will increase insulin sensitivity and insulin secretion. A secondary aim is to determine whether these relationships are mediated by a reduction in underlying subclinical inflammation associated with obesity.Fifty overweight but otherwise healthy nondiabetic adults between 18 and 60 years old, with low vitamin D levels (25(OH)D < 50 nmol/l), will be randomly assigned to intervention or placebo. At baseline, participants will undergo a medical review and anthropometric measurements, including dual X-ray absorptiometry, an intravenous glucose tolerance test, muscle and fat biopsies, a hyperinsulinemic euglycemic clamp, and questionnaires assessing diet, physical activity, sun exposure, back and knee pain, and depression. The intervention group will receive a first dose of 100,000 IU followed by 4,000 IU vitamin D (cholecalciferol) daily, while the placebo group will receive apparently identical capsules, both for a period of 16 weeks. All measurements will be repeated at follow-up, with the primary outcome measure expressed as a change from baseline in insulin sensitivity and secretion for the intervention group compared with the placebo group. Secondary outcome measures will compare changes in anthropometry, cardiovascular risk factors, and inflammatory markers.The trial will provide much needed clinical evidence on the impact of vitamin D supplementation on insulin resistance and secretion and its underlying mechanisms, which are relevant for the prevention and management of type 2 diabetes.Clinicaltrials.gov ID: NCT02112721 .Barbora de Courten, Aya Mousa, Negar Naderpoor, Helena Teede, Maximilian P J de Courten and Robert Scrag

    Comparative Linkage Meta-Analysis Reveals Regionally-Distinct, Disparate Genetic Architectures: Application to Bipolar Disorder and Schizophrenia

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    New high-throughput, population-based methods and next-generation sequencing capabilities hold great promise in the quest for common and rare variant discovery and in the search for ”missing heritability.” However, the optimal analytic strategies for approaching such data are still actively debated, representing the latest rate-limiting step in genetic progress. Since it is likely a majority of common variants of modest effect have been identified through the application of tagSNP-based microarray platforms (i.e., GWAS), alternative approaches robust to detection of low-frequency (1–5% MAF) and rare (<1%) variants are of great importance. Of direct relevance, we have available an accumulated wealth of linkage data collected through traditional genetic methods over several decades, the full value of which has not been exhausted. To that end, we compare results from two different linkage meta-analysis methods—GSMA and MSP—applied to the same set of 13 bipolar disorder and 16 schizophrenia GWLS datasets. Interestingly, we find that the two methods implicate distinct, largely non-overlapping, genomic regions. Furthermore, based on the statistical methods themselves and our contextualization of these results within the larger genetic literatures, our findings suggest, for each disorder, distinct genetic architectures may reside within disparate genomic regions. Thus, comparative linkage meta-analysis (CLMA) may be used to optimize low-frequency and rare variant discovery in the modern genomic era

    Genetic Signatures of Exceptional Longevity in Humans

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    Like most complex phenotypes, exceptional longevity is thought to reflect a combined influence of environmental (e.g., lifestyle choices, where we live) and genetic factors. To explore the genetic contribution, we undertook a genome-wide association study of exceptional longevity in 801 centenarians (median age at death 104 years) and 914 genetically matched healthy controls. Using these data, we built a genetic model that includes 281 single nucleotide polymorphisms (SNPs) and discriminated between cases and controls of the discovery set with 89% sensitivity and specificity, and with 58% specificity and 60% sensitivity in an independent cohort of 341 controls and 253 genetically matched nonagenarians and centenarians (median age 100 years). Consistent with the hypothesis that the genetic contribution is largest with the oldest ages, the sensitivity of the model increased in the independent cohort with older and older ages (71% to classify subjects with an age at death>102 and 85% to classify subjects with an age at death>105). For further validation, we applied the model to an additional, unmatched 60 centenarians (median age 107 years) resulting in 78% sensitivity, and 2863 unmatched controls with 61% specificity. The 281 SNPs include the SNP rs2075650 in TOMM40/APOE that reached irrefutable genome wide significance (posterior probability of association = 1) and replicated in the independent cohort. Removal of this SNP from the model reduced the accuracy by only 1%. Further in-silico analysis suggests that 90% of centenarians can be grouped into clusters characterized by different “genetic signatures” of varying predictive values for exceptional longevity. The correlation between 3 signatures and 3 different life spans was replicated in the combined replication sets. The different signatures may help dissect this complex phenotype into sub-phenotypes of exceptional longevity

    Individualized medicine enabled by genomics in Saudi Arabia

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    Design of exceptionally strong and conductive Cu alloys beyond the conventional speculation via the interfacial energy-controlled dispersion of γ-Al2O3 nanoparticles

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    The development of Cu-based alloys with high-mechanical properties (strength, ductility) and electrical conductivity plays a key role over a wide range of industrial applications. Successful design of the materials, however, has been rare due to the improvement of mutually exclusive properties as conventionally speculated. In this paper, we demonstrate that these contradictory material properties can be improved simultaneously if the interfacial energies of heterogeneous interfaces are carefully controlled. We uniformly disperse γ-Al(2)O(3) nanoparticles over Cu matrix, and then we controlled atomic level morphology of the interface γ-Al(2)O(3)//Cu by adding Ti solutes. It is shown that the Ti dramatically drives the interfacial phase transformation from very irregular to homogeneous spherical morphologies resulting in substantial enhancement of the mechanical property of Cu matrix. Furthermore, the Ti removes impurities (O and Al) in the Cu matrix by forming oxides leading to recovery of the electrical conductivity of pure Cu. We validate experimental results using TEM and EDX combined with first-principles density functional theory (DFT) calculations, which all consistently poise that our materials are suitable for industrial applications
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