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Find video protocols related to scientific articles indexed in Pubmed.
Increased CNV-region deletions in mild cognitive impairment (MCI) and Alzheimers disease (AD) subjects in the ADNI sample.
Genomics
PUBLISHED: 03-22-2013
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We investigated the genome-wide distribution of CNVs in the Alzheimers disease (AD) Neuroimaging Initiative (ADNI) sample (146 with AD, 313 with Mild Cognitive Impairment (MCI), and 181 controls). Comparison of single CNVs between cases (MCI and AD) and controls shows overrepresentation of large heterozygous deletions in cases (p-value<0.0001). The analysis of CNV-Regions identifies 44 copy number variable loci of heterozygous deletions, with more CNV-Regions among affected than controls (p=0.005). Seven of the 44 CNV-Regions are nominally significant for association with cognitive impairment. We validated and confirmed our main findings with genome re-sequencing of selected patients and controls. The functional pathway analysis of the genes putatively affected by deletions of CNV-Regions reveals enrichment of genes implicated in axonal guidance, cell-cell adhesion, neuronal morphogenesis and differentiation. Our findings support the role of CNVs in AD, and suggest an association between large deletions and the development of cognitive impairment.
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Analysis of miR-137 expression and rs1625579 in dorsolateral prefrontal cortex.
J Psychiatr Res
PUBLISHED: 03-05-2013
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MicroRNAs (miRNAs) are small non-coding RNAs that act as potent regulators of gene expression. A recent GWAS reported the rs1625579 SNP, located downstream of miR-137, as the strongest new association with schizophrenia [Ripke S, Sanders AR, Kendler KS, Levinson DF, Sklar P, Holmans PA, et al. Genome-wide association study identifies five new schizophrenia loci. Nat Genet 2011;43:969-76.]. Prior to this GWAS finding, a schizophrenia imaging-genetic study found miR-137 target genes significantly enriched for association with activation in the dorsolateral prefrontal cortex (DLPFC) [Potkin SG, Macciardi F, Guffanti G, Fallon JH, Wang Q, Turner JA, et al. Identifying gene regulatory networks in schizophrenia. Neuroimage 2010;53:839-47.]. We investigated the expression levels of miR-137 and three candidate target genes (ZNF804A, CACNA1C, TCF4) in the DLPFC of postmortem brain tissue from 2 independent cohorts: (1) 26 subjects (10 control (CTR), 7 schizophrenia (SZ), 9 bipolar disorder (BD)) collected at the UCI brain bank; and (2) 99 subjects (33 CTR, 35 SZ, 31 BD) obtained from the Stanley Medical Research Institute (SMRI). MiR-137 expression in the DLPFC did not differ between diagnoses. We also explored the relationship between rs1625579 genotypes and miR-137 expression. Significantly lower miR-137 expression levels were observed in the homozygous TT subjects compared to TG and GG subjects in the control group (30% decrease, p-value = 0.03). Moreover, reduced miR-137 levels in TT subjects corresponded to increased levels of the miR-137 target gene TCF4. The miR-137 expression pattern in 9 brain regions was significant for regional effect (ANOVA p-value = 1.83E-12), with amygdala and hippocampus having the highest miR-137 expression level. In conclusion, decreased miR-137 expression is associated with the SZ risk allele of rs1625579, and potential regulation of TCF4, another SZ candidate gene. This study offers additional support for involvement of miR-137 and downstream targets as mechanisms of risk for psychiatric disorders.
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Applications of the pipeline environment for visual informatics and genomics computations.
BMC Bioinformatics
PUBLISHED: 03-24-2011
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Contemporary informatics and genomics research require efficient, flexible and robust management of large heterogeneous data, advanced computational tools, powerful visualization, reliable hardware infrastructure, interoperability of computational resources, and detailed data and analysis-protocol provenance. The Pipeline is a client-server distributed computational environment that facilitates the visual graphical construction, execution, monitoring, validation and dissemination of advanced data analysis protocols.
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Fine mapping of AHI1 as a schizophrenia susceptibility gene: from association to evolutionary evidence.
FASEB J.
PUBLISHED: 04-06-2010
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In previous studies, we identified a locus for schizophrenia on 6q23.3 and proposed the Abelson helper integration site 1 (AHI1) as the candidate gene. AHI1 is expressed in the brain and plays a key role in neurodevelopment, is involved in Joubert syndrome, and has been recently associated with autism. The neurodevelopmental role of AHI1 fits with etiological hypotheses of schizophrenia. To definitively confirm our hypothesis, we searched for associations using a dense map of the region. Our strongest findings lay within the AHI1 gene: single-nucleotide polymorphisms rs11154801 and rs7759971 showed significant associations (P=6.23E-06; P=0.84E-06) and haplotypes gave P values in the 10E-8 to 10E-10 range. The second highest significant region maps close to AHI1 and includes the intergenic region between BC040979 and PDE7B (rs2038549 at P=9.70E-06 and rs1475069 at P=6.97E-06), and PDE7B and MAP7. Using a sample of Palestinian Arab families to confirm these findings, we found isolated signals. While these results did not retain their significance after correction for multiple testing, the joint analysis across the 2 samples supports the role of AHI1, despite the presence of heterogeneity. Given the hypothesis of positive selection of schizophrenia genes, we resequenced a 11 kb region within AHI1 in ethnically defined populations and found evidence for a selective sweep. Network analysis indicates 2 haplotype clades, with schizophrenia-susceptibility haplotypes clustering within the major clade. In conclusion, our data support the role of AHI1 as a susceptibility gene for schizophrenia and confirm it has been subjected to positive selection, also shedding light on new possible candidate genes, MAP7 and PDE7B.
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Loss of mismatched HLA in leukemia after stem-cell transplantation.
N. Engl. J. Med.
PUBLISHED: 07-31-2009
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Transplantation of hematopoietic stem cells from partially matched family donors is a promising therapy for patients who have a hematologic cancer and are at high risk for relapse. The donor T-cell infusions associated with such transplantation can promote post-transplantation immune reconstitution and control residual disease.
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Genome-wide strategies for discovering genetic influences on cognition and cognitive disorders: methodological considerations.
Cogn Neuropsychiatry
PUBLISHED: 07-28-2009
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Genes play a well-documented role in determining normal cognitive function. This paper focuses on reviewing strategies for the identification of common genetic variation in genes that modulate normal and abnormal cognition with a genome-wide association scan (GWAS). GWASs make it possible to survey the entire genome to discover important but unanticipated genetic influences.
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Diverse evolutionary histories for beta-adrenoreceptor genes in humans.
Am. J. Hum. Genet.
PUBLISHED: 03-31-2009
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In humans, three genes--ADRB1, ADRB2 and ADRB3--encode beta-adrenoreceptors (ADRB); these molecules mediate the action of catecholamines in multiple tissues and play pivotal roles in cardiovascular, respiratory, metabolic, and immunological functions. Genetic variants in ADRB genes have been associated with widespread diseases and conditions, but inconsistent results have often been obtained. Here, we addressed the recent evolutionary history of ADRB genes in human populations. Although ADRB1 is neutrally evolving, most tests rejected neutral evolution for ADRB2 in European, African, and Asian population samples. Analysis of inferred haplotypes for ADRB2 revealed three major clades with a coalescence time of 1-1.5 million years, suggesting that the gene is either subjected to balancing selection or undergoing a selective sweep. Haplotype analysis also revealed ethnicity-specific differences. Additionally, we observed significant deviations from Hardy-Weinberg equilibrium (HWE) for ADRB2 genotypes in distinct European cohorts; HWE deviation depends on sex (only females are in disequilibrium), and genotypes displaying maximum and minimum relative fitness differ across population samples, suggesting a complex situation possibly involving epistasis or maternal selection. Overall, our data indicate that future association studies involving ADRB2 will benefit from taking into account ethnicity-specific haplotype distributions and sex-based effects. With respect to ADRB3, our data indicate that the gene has been subjected to a selective sweep in African populations, the Trp64 variant possibly representing the selection target. Given the previous association of the ancestral ADRB3 Arg64 allele with obesity and type 2 diabetes, dietary adaptations might represent the underlying selective force.
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A two-stage genome-wide association study of sporadic amyotrophic lateral sclerosis.
Hum. Mol. Genet.
PUBLISHED: 02-04-2009
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The cause of sporadic amyotrophic lateral sclerosis (ALS) is largely unknown, but genetic factors are thought to play a significant role in determining susceptibility to motor neuron degeneration. To identify genetic variants altering risk of ALS, we undertook a two-stage genome-wide association study (GWAS): we followed our initial GWAS of 545 066 SNPs in 553 individuals with ALS and 2338 controls by testing the 7600 most associated SNPs from the first stage in three independent cohorts consisting of 2160 cases and 3008 controls. None of the SNPs selected for replication exceeded the Bonferroni threshold for significance. The two most significantly associated SNPs, rs2708909 and rs2708851 [odds ratio (OR) = 1.17 and 1.18, and P-values = 6.98 x 10(-7) and 1.16 x 10(-6)], were located on chromosome 7p13.3 within a 175 kb linkage disequilibrium block containing the SUNC1, HUS1 and C7orf57 genes. These associations did not achieve genome-wide significance in the original cohort and failed to replicate in an additional independent cohort of 989 US cases and 327 controls (OR = 1.18 and 1.19, P-values = 0.08 and 0.06, respectively). Thus, we chose to cautiously interpret our data as hypothesis-generating requiring additional confirmation, especially as all previously reported loci for ALS have failed to replicate successfully. Indeed, the three loci (FGGY, ITPR2 and DPP6) identified in previous GWAS of sporadic ALS were not significantly associated with disease in our study. Our findings suggest that ALS is more genetically and clinically heterogeneous than previously recognized. Genotype data from our study have been made available online to facilitate such future endeavors.
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Next Generation Sequence Analysis and Computational Genomics Using Graphical Pipeline Workflows.
Genes (Basel)
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Whole-genome and exome sequencing have already proven to be essential and powerful methods to identify genes responsible for simple Mendelian inherited disorders. These methods can be applied to complex disorders as well, and have been adopted as one of the current mainstream approaches in population genetics. These achievements have been made possible by next generation sequencing (NGS) technologies, which require substantial bioinformatics resources to analyze the dense and complex sequence data. The huge analytical burden of data from genome sequencing might be seen as a bottleneck slowing the publication of NGS papers at this time, especially in psychiatric genetics. We review the existing methods for processing NGS data, to place into context the rationale for the design of a computational resource. We describe our method, the Graphical Pipeline for Computational Genomics (GPCG), to perform the computational steps required to analyze NGS data. The GPCG implements flexible workflows for basic sequence alignment, sequence data quality control, single nucleotide polymorphism analysis, copy number variant identification, annotation, and visualization of results. These workflows cover all the analytical steps required for NGS data, from processing the raw reads to variant calling and annotation. The current version of the pipeline is freely available at http://pipeline.loni.ucla.edu. These applications of NGS analysis may gain clinical utility in the near future (e.g., identifying miRNA signatures in diseases) when the bioinformatics approach is made feasible. Taken together, the annotation tools and strategies that have been developed to retrieve information and test hypotheses about the functional role of variants present in the human genome will help to pinpoint the genetic risk factors for psychiatric disorders.
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Genomic profiling by whole-genome single nucleotide polymorphism arrays in Wilms tumor and association with relapse.
Genes Chromosomes Cancer
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Despite the excellent survival rate of Wilms tumor (WT) patients, only approximately one-half of children who suffer tumor recurrence reach second durable remission. This underlines the need for novel markers to optimize initial treatment. We investigated 77 tumors using Illumina 370CNV-QUAD genotyping BeadChip arrays and compared their genomic profiles to detect copy number (CN) abnormalities and allelic ratio anomalies associated with the following clinicopathological variables: relapse (yes vs. no), age at diagnosis (? 24 months vs. >24 months), and disease stage (low stage, I and II, vs. high stage, III and IV). We found that CN gains at chromosome region 1q21.1-q31.3 were significantly associated with relapse. Additional genetic events, including allelic imbalances at chromosome arms 1p, 1q, 3p, 3q, and 14q were also found to occur at higher frequency in relapsing tumors. Interestingly, allelic imbalances at 1p and 14q also showed a borderline association with higher tumor stages. No genetic events were found to be associated with age at diagnosis. This is the first genome wide analysis with single nucleotide polymorphism (SNP) arrays specifically investigating the role of genetic anomalies in predicting WT relapse on cases prospectively enrolled in the same clinical trial. Our study, besides confirming the role of 1q gains, identified a number of additional candidate genetic markers, warranting further molecular investigations.
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The perfect neuroimaging-genetics-computation storm: collision of petabytes of data, millions of hardware devices and thousands of software tools.
Brain Imaging Behav
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The volume, diversity and velocity of biomedical data are exponentially increasing providing petabytes of new neuroimaging and genetics data every year. At the same time, tens-of-thousands of computational algorithms are developed and reported in the literature along with thousands of software tools and services. Users demand intuitive, quick and platform-agnostic access to data, software tools, and infrastructure from millions of hardware devices. This explosion of information, scientific techniques, computational models, and technological advances leads to enormous challenges in data analysis, evidence-based biomedical inference and reproducibility of findings. The Pipeline workflow environment provides a crowd-based distributed solution for consistent management of these heterogeneous resources. The Pipeline allows multiple (local) clients and (remote) servers to connect, exchange protocols, control the execution, monitor the states of different tools or hardware, and share complete protocols as portable XML workflows. In this paper, we demonstrate several advanced computational neuroimaging and genetics case-studies, and end-to-end pipeline solutions. These are implemented as graphical workflow protocols in the context of analyzing imaging (sMRI, fMRI, DTI), phenotypic (demographic, clinical), and genetic (SNP) data.
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What is Visualize?

JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

How does it work?

We use abstracts found on PubMed and match them to JoVE videos to create a list of 10 to 30 related methods videos.

Video X seems to be unrelated to Abstract Y...

In developing our video relationships, we compare around 5 million PubMed articles to our library of over 4,500 methods videos. In some cases the language used in the PubMed abstracts makes matching that content to a JoVE video difficult. In other cases, there happens not to be any content in our video library that is relevant to the topic of a given abstract. In these cases, our algorithms are trying their best to display videos with relevant content, which can sometimes result in matched videos with only a slight relation.