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High-probability grants
According to our matching algorithm, Silviu-Alin Bacanu is the likely recipient of the following grants.
Years |
Recipients |
Code |
Title / Keywords |
Matching score |
2014 — 2015 |
Bacanu, Silviu-Alin |
R21Activity Code Description: To encourage the development of new research activities in categorical program areas. (Support generally is restricted in level of support and in time.) |
Using Genetic Overlap to Dissect the Genetic Architecture of Psychiatric Diseases @ Virginia Commonwealth University
DESCRIPTION (provided by applicant): This project seeks to contribute to the understanding of the genetic basis for schizophrenia (SCZ) and bipolar disease (BD). To achieve this goal, we attempt to amplify genetic signals of modest effect in an SCZ/BD cohort, by analyzing such a cohort together with a well powered study of another (relevant) phenotype. The strategy relies on clarifying etiologic pathways to illness by looking at overlaps with a genetically well characterized correlated trait - in this case height (H). Large scale epidemiological studies suggest that increased H is associated with a decreased risk of SCZ. Given that BD is comorbid with SCZ, H might share (as suggested by our pilot analyses) causal pathways with each of these two psychiatric disorders. The genetic meta-analysis of H is probably the largest to be published, which ensures that it has good power to detect even modest genetic signals. Thus, H is a good candidate for a phenotype to be tested for genetic overlap with SCZ/BD, where by genetic overlap we mean the SNP/genes which significantly affect both phenotypes, not just one. Critically, this overlap can allow us to clarify etiologic pathways to SCZ/BD that might be quite difficult to detect in other ways. Furthermore, we suggest that our method can yield at least two classes of etiologic pathways. We provide preliminary evidence that pathways where the genetic effects on the two phenotypes are concordant (i.e., in the same direction) are very different from pathways where they are discordant. Thus, we suggest that, to avoid pathway heterogeneity, it is advisable for the concordant and discordant signals to be analyzed separately in pathway analyses. To uncover a part of the genetic architecture of SCZ/BD we employ a two steps process using only publicly available univariate summaries from relevant meta-analyses. In the first step we evaluate i) the genetic overlap of each disease with a) H and b) between SCZ and BD. In the second step, the most promising concordant and discordant overlap signals are used in separate gene set analyses to uncover whether these signals are enriched in certain molecular pathways. To assess the overlap between SCZ/BD and H, we develop novel statistical methods to i) increase the genetic data resolution by imputing summary statistics at unobserved SNPs based only on the summary statistics at observed SNPs and ii) obtain the genetic overlap between multiple phenotypes which is not overly influenced by a strong signal coming from just one phenotype.
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1 |
2014 — 2015 |
Bacanu, Silviu-Alin |
R21Activity Code Description: To encourage the development of new research activities in categorical program areas. (Support generally is restricted in level of support and in time.) |
Using Novel Eqtl-Based Methods to Find the Molecular Causes of Alcohol Dependency @ Virginia Commonwealth University
DESCRIPTION (provided by applicant): To contribute to the understanding of the molecular basis of alcohol dependence, we i) attempt to increase the power of detecting genetic signals by developing methods to analyze all functional variants in a gene jointly and ii) use such developed methods to discover and replicate genetic findings from available alcohol related data. In this proposal we focus on expression Quantitative Trait Loci (eQTLs). To achieve the goal of testing eQTLs jointly, we propose to i) construct a tissue specific data base of eQTLs found in dense genotype panels, e.g. 1000 Genomes Project (1KG), ii) develop two statistical methods which use this database information and implement them into fast user friendly software, iii) discover promising genes by applying the developed methods to publicly available alcohol use disorder (AUD) studies and iv) replicate discovered genes in a proprietary AUD study. In the database we include all 1KG genetic variants which are known or predicted to influence gene expression in tissues relevant for AUD, i.e. brain and liver. Both proposed methods have the major advantage of using only summary statistics, i.e. they do not require access to subject level genotypes. The first method directly imputes the univariate summary statistics at unobserved eQTLs based on 1) univariate summary statistics at measured variants nearby and 2) the correlation structure, as estimated from a relevant reference population. The second method uses the univariate statistic at measured and imputed eQTLs, to derive the test for the joint effect on phenotype of all eQTLs in a gene. These methods are subsequently used to discover and replicate findings using summary statistics from data sets which are both publicly available and proprietary. For the discovery phase, we use all the publicly available summary data sets, such as Collaborative Study on the Genetics of Alcoholism among others. We replicate the discovered genes using the internally available Irish Alcohol Study.
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1 |
2020 — 2021 |
Bacanu, Silviu-Alin |
P50Activity Code Description: To support any part of the full range of research and development from very basic to clinical; may involve ancillary supportive activities such as protracted patient care necessary to the primary research or R&D effort. The spectrum of activities comprises a multidisciplinary attack on a specific disease entity or biomedical problem area. These grants differ from program project grants in that they are usually developed in response to an announcement of the programmatic needs of an Institute or Division and subsequently receive continuous attention from its staff. Centers may also serve as regional or national resources for special research purposes. |
Core 3: Bioinformatics and Analysis Core @ Virginia Commonwealth University
Project Summary ? Core 3 The Bioinformatics and Analysis (BIA) Core serves as a support network for all VCU Alcohol Research Center (ARC) projects and will interact closely with each component to provide computational, statistical, and research design expertise. The core will play a central role in the data collection, curation, annotation, management, storage, and analysis. As such, we will first collect and curate project related data include those generated by the VCU-ARC and those that are available from other outside sources. Examples of these internal and external data include human association studies and expression and network analyses for mouse, worm and fly. The collected data will be integrated via a data management system. Many statistical and bioinformatics analyses will be performed for the identification of Alcohol Use Disorders (AUD) related genes, including within and across species gene network analysis. The core will also implement methods for prioritizing genes for additional study. The overall goal of facilitating data sharing and the application of emerging methods will be to accelerate the understanding of AUD and related traits. To this end, a wide range of experimental data and results related to alcohol will be used and generated by the proposed center. Collecting and integrating these data provides the opportunity to discover patterns that would be detected when considering a single organism or experimental design.
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1 |