843 research outputs found

    Power calculations using exact data simulation: A useful tool for genetic study designs.

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    Statistical power calculations constitute an essential first step in the planning of scientific studies. If sufficient summary statistics are available, power calculations are in principle straightforward and computationally light. In designs, which comprise distinct groups (e.g., MZ & DZ twins), sufficient statistics can be calculated within each group, and analyzed in a multi-group model. However, when the number of possible groups is prohibitively large (say, in the hundreds), power calculations on the basis of the summary statistics become impractical. In that case, researchers may resort to Monte Carlo based power studies, which involve the simulation of hundreds or thousands of replicate samples for each specified set of population parameters. Here we present exact data simulation as a third method of power calculation. Exact data simulation involves a transformation of raw data so that the data fit the hypothesized model exactly. As in power calculation with summary statistics, exact data simulation is computationally light, while the number of groups in the analysis has little bearing on the practicality of the method. The method is applied to three genetic designs for illustrative purposes

    Plasmodium knowlesi Genome Sequences from Clinical Isolates Reveal Extensive Genomic Dimorphism.

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    Plasmodium knowlesi is a newly described zoonosis that causes malaria in the human population that can be severe and fatal. The study of P. knowlesi parasites from human clinical isolates is relatively new and, in order to obtain maximum information from patient sample collections, we explored the possibility of generating P. knowlesi genome sequences from archived clinical isolates. Our patient sample collection consisted of frozen whole blood samples that contained excessive human DNA contamination and, in that form, were not suitable for parasite genome sequencing. We developed a method to reduce the amount of human DNA in the thawed blood samples in preparation for high throughput parasite genome sequencing using Illumina HiSeq and MiSeq sequencing platforms. Seven of fifteen samples processed had sufficiently pure P. knowlesi DNA for whole genome sequencing. The reads were mapped to the P. knowlesi H strain reference genome and an average mapping of 90% was obtained. Genes with low coverage were removed leaving 4623 genes for subsequent analyses. Previously we identified a DNA sequence dimorphism on a small fragment of the P. knowlesi normocyte binding protein xa gene on chromosome 14. We used the genome data to assemble full-length Pknbpxa sequences and discovered that the dimorphism extended along the gene. An in-house algorithm was developed to detect SNP sites co-associating with the dimorphism. More than half of the P. knowlesi genome was dimorphic, involving genes on all chromosomes and suggesting that two distinct types of P. knowlesi infect the human population in Sarawak, Malaysian Borneo. We use P. knowlesi clinical samples to demonstrate that Plasmodium DNA from archived patient samples can produce high quality genome data. We show that analyses, of even small numbers of difficult clinical malaria isolates, can generate comprehensive genomic information that will improve our understanding of malaria parasite diversity and pathobiology

    Rare germline variants in DNA repair genes and the angiogenesis pathway predispose prostate cancer patients to develop metastatic disease

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    Background Prostate cancer (PrCa) demonstrates a heterogeneous clinical presentation ranging from largely indolent to lethal. We sought to identify a signature of rare inherited variants that distinguishes between these two extreme phenotypes. Methods We sequenced germline whole exomes from 139 aggressive (metastatic, age of diagnosis < 60) and 141 non-aggressive (low clinical grade, age of diagnosis β‰₯60) PrCa cases. We conducted rare variant association analyses at gene and gene set levels using SKAT and Bayesian risk index techniques. GO term enrichment analysis was performed for genes with the highest differential burden of rare disruptive variants. Results Protein truncating variants (PTVs) in specific DNA repair genes were significantly overrepresented among patients with the aggressive phenotype, with BRCA2, ATM and NBN the most frequently mutated genes. Differential burden of rare variants was identified between metastatic and non-aggressive cases for several genes implicated in angiogenesis, conferring both deleterious and protective effects. Conclusions Inherited PTVs in several DNA repair genes distinguish aggressive from non-aggressive PrCa cases. Furthermore, inherited variants in genes with roles in angiogenesis may be potential predictors for risk of metastases. If validated in a larger dataset, these findings have potential for future clinical application

    Novel genetic analysis for case-control genome-wide association studies: quantification of power and genomic prediction accuracy

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    Genome-wide association studies (GWAS) are routinely conducted for both quantitative and binary (disease) traits. We present two analytical tools for use in the experimental design of GWAS. Firstly, we present power calculations quantifying power in a unified framework for a range of scenarios. In this context we consider the utility of quantitative scores (e.g. endophenotypes) that may be available on cases only or both cases and controls. Secondly, we consider, the accuracy of prediction of genetic risk from genome-wide SNPs and derive an expression for genomic prediction accuracy using a liability threshold model for disease traits in a case-control design. The expected values based on our derived equations for both power and prediction accuracy agree well with observed estimates from simulations

    Dissociation of accumulated genetic risk and disease severity in patients with schizophrenia

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    Genotype–phenotype correlations of common monogenic diseases revealed that the degree of deviation of mutant genes from wild-type structure and function often predicts disease onset and severity. In complex disorders such as schizophrenia, the overall genetic risk is still often >50% but genotype–phenotype relationships are unclear. Recent genome-wide association studies (GWAS) replicated a risk for several single-nucleotide polymorphisms (SNPs) regarding the endpoint diagnosis of schizophrenia. The biological relevance of these SNPs, however, for phenotypes or severity of schizophrenia has remained obscure. We hypothesized that the GWAS β€˜top-10' should as single markers, but even more so upon their accumulation, display associations with lead features of schizophrenia, namely positive and negative symptoms, cognitive deficits and neurological signs (including catatonia), and/or with age of onset of the disease prodrome as developmental readout and predictor of disease severity. For testing this hypothesis, we took an approach complementary to GWAS, and performed a phenotype-based genetic association study (PGAS). We utilized the to our knowledge worldwide largest phenotypical database of schizophrenic patients (n>1000), the GRAS (GΓΆttingen Research Association for Schizophrenia) Data Collection. We found that the β€˜top-10' GWAS-identified risk SNPs neither as single markers nor when explored in the sense of a cumulative genetic risk, have any predictive value for disease onset or severity in the schizophrenic patients, as demonstrated across all core symptoms. We conclude that GWAS does not extract disease genes of general significance in schizophrenia, but may yield, on a hypothesis-free basis, candidate genes relevant for defining disease subgroups

    Evolution of High Trophic Diversity Based on Limited Functional Disparity in the Feeding Apparatus of Marine Angelfishes (f. Pomacanthidae)

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    The use of biting to obtain food items attached to the substratum is an ecologically widespread and important mode of feeding among aquatic vertebrates, which rarely has been studied. We did the first evolutionary analyses of morphology and motion kinematics of the feeding apparatus in Indo-Pacific members of an iconic family of biters, the marine angelfishes (f. Pomacanthidae). We found clear interspecific differences in gut morphology that clearly reflected a wide range of trophic niches. In contrast, feeding apparatus morphology appeared to be conserved. A few unusual structural innovations enabled angelfishes to protrude their jaws, close them in the protruded state, and tear food items from the substratum at a high velocity. Only one clade, the speciose pygmy angelfishes, showed functional departure from the generalized and clade-defining grab-and-tearing feeding pattern. By comparing the feeding kinematics of angelfishes with wrasses and parrotfishes (f. Labridae) we showed that grab-and-tearing is based on low kinematics disparity. Regardless of its restricted disparity, the grab-and-tearing feeding apparatus has enabled angelfishes to negotiate ecological thresholds: Given their widely different body sizes, angelfishes can access many structurally complex benthic surfaces that other biters likely are unable to exploit. From these surfaces, angelfishes can dislodge sturdy food items from their tough attachments. Angelfishes thus provide an intriguing example of a successful group that appears to have evolved considerable trophic diversity based on an unusual yet conserved feeding apparatus configuration that is characterized by limited functional disparity

    Improved Statistics for Genome-Wide Interaction Analysis

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    Recently, Wu and colleagues [1] proposed two novel statistics for genome-wide interaction analysis using case/control or case-only data. In computer simulations, their proposed case/control statistic outperformed competing approaches, including the fast-epistasis option in PLINK and logistic regression analysis under the correct model; however, reasons for its superior performance were not fully explored. Here we investigate the theoretical properties and performance of Wu et al.'s proposed statistics and explain why, in some circumstances, they outperform competing approaches. Unfortunately, we find minor errors in the formulae for their statistics, resulting in tests that have higher than nominal type 1 error. We also find minor errors in PLINK's fast-epistasis and case-only statistics, although theory and simulations suggest that these errors have only negligible effect on type 1 error. We propose adjusted versions of all four statistics that, both theoretically and in computer simulations, maintain correct type 1 error rates under the null hypothesis. We also investigate statistics based on correlation coefficients that maintain similar control of type 1 error. Although designed to test specifically for interaction, we show that some of these previously-proposed statistics can, in fact, be sensitive to main effects at one or both loci, particularly in the presence of linkage disequilibrium. We propose two new β€œjoint effects” statistics that, provided the disease is rare, are sensitive only to genuine interaction effects. In computer simulations we find, in most situations considered, that highest power is achieved by analysis under the correct genetic model. Such an analysis is unachievable in practice, as we do not know this model. However, generally high power over a wide range of scenarios is exhibited by our joint effects and adjusted Wu statistics. We recommend use of these alternative or adjusted statistics and urge caution when using Wu et al.'s originally-proposed statistics, on account of the inflated error rate that can result

    Surgeon-Performed Ultrasound as Preoperative Localization Study in Patients with Primary Hyperparathyroidism

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    Background: Minimally invasive parathyroidectomy is the treatment of choice for single-gland primary hyperparathyroidism. However, the exact location of the abnormal gland has to be established. Sestamibi scintigraphy, computed tomography and ultrasound (US) are commonly used modalities. We describe our experience in a non-academic center with surgeon-performed US (S-US) of the neck as preoperative localization study in patients with primary hyperparathyroidism (PHPT). Methods: Patients with a biochemically proven diagnosis of PHPT and preoperative S-US were included. Data were recorded prospectively. Perioperative gland location was compared to the preoperative S-US to determine sensitivity, specificity and accuracy rates. Results: Two of the 50 patients who underwent S-US were not subjected to surgery. In 85% of the patients analyzed by S-US, the appropriate abnormal gland(s) were identified. In 11%, no gland was identified, but abnormal glands were found during surgery. Sensitivity of S-US in our hospital is 85%, with a positive predictive value of 97%. Conclusions: We achieved a satisfactory sensitivity rate. S-US provides anatomic information to the surgeon which enables a more detailed operation planning, and it is a valuable diagnostic modality for patients with PHPT in our opinion. We hope that our data encourage other centers to implement this technique as well. Copyrigh

    Sphingomyelin phosphodiesterase-1 (SMPD1) coding variants do not contribute to low levels of high-density lipoprotein cholesterol

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    <p>Abstract</p> <p>Background</p> <p>Niemann-Pick disease type A and B is caused by a deficiency of acid sphingomyelinase due to mutations in the sphingomyelin phosphodiesterase-1 (<it>SMPD1</it>) gene. In Niemann-Pick patients, <it>SMPD1 </it>gene defects are reported to be associated with a severe reduction in plasma high-density lipoprotein (HDL) cholesterol.</p> <p>Methods</p> <p>Two common coding polymorphisms in the <it>SMPD1 </it>gene, the G1522A (G508R) and a hexanucleotide repeat sequence within the signal peptide region, were investigated in 118 unrelated subjects of French Canadian descent with low plasma levels of HDL-cholesterol (< 5<sup>th </sup>percentile for age and gender-matched subjects). Control subjects (n = 230) had an HDL-cholesterol level > the 25<sup>th </sup>percentile.</p> <p>Results</p> <p>For G1522A the frequency of the G and A alleles were 75.2% and 24.8% respectively in controls, compared to 78.6% and 21.4% in subjects with low HDL-cholesterol (<it>p </it>= 0.317). The frequency of 6 and 7 hexanucleotide repeats was 46.2% and 46.6% respectively in controls, compared to 45.6% and 49.1% in subjects with low HDL-cholesterol (<it>p </it>= 0.619). Ten different haplotypes were observed in cases and controls. Overall haplotype frequencies in cases and controls were not significantly different.</p> <p>Conclusion</p> <p>These results suggest that the two common coding variants at the <it>SMPD1 </it>gene locus are not associated with low HDL-cholesterol levels in the French Canadian population.</p
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