Browsing by Subject "Functional annotation"

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    Efficient region-based test strategy uncovers genetic risk factors for functional outcome in bipolar disorder
    (Elsevier, 2019-01-01) Budde, Monika; Friedrichs, Stefanie; Alliey-Rodriguez, Ney; Ament, Seth; Badner, Judith A.; Berrettini, Wade H.; Bloss, Cinnamon S.; Byerley, William; Cichon, Sven; Comes, Ashley L.; Coryell, William; Craig, David W.; Degenhardt, Franziska; Edenberg, Howard J.; Foroud, Tatiana; Forstner, Andreas J.; Frank, Josef; Gershon, Elliot S.; Goes, Fernando S.; Greenwood, Tiffany A.; Guo, Yiran; Hipolito, Maria; Hood, Leroy; Keating, Brendan J.; Koller, Daniel L.; Lawson, William B.; Liu, Chunyu; Mahon, Pamela B.; McInnis, Melvin G.; McMahon, Francis J.; Meier, Sandra M.; Mühleisen, Thomas W.; Murray, Sarah S.; Nievergelt, Caroline M.; Nurnberger, John I.; Nwulia, Evaristus A.; Potash, James B.; Quarless, Danjuma; Rice, John; Roach, Jared C.; Scheftner, William A.; Schork, Nicholas J.; Shekhtman, Tatyana; Shilling, Paul D.; Smith, Erin N.; Streit, Fabian; Strohmaier, Jana; Szelinger, Szabolcs; Treutlein, Jens; Witt, Stephanie H.; Zandi, Peter P.; Zhang, Peng; Zöllner, Sebastian; Bickeböller, Heike; Falkai, Peter G.; Kelsoe, John R.; Nöthen, Markus M.; Rietschel, Marcella; Schulze, Thomas G.; Malzahn, Dörthe; Biochemistry and Molecular Biology, School of Medicine
    Genome-wide association studies of case-control status have advanced the understanding of the genetic basis of psychiatric disorders. Further progress may be gained by increasing sample size but also by new analysis strategies that advance the exploitation of existing data, especially for clinically important quantitative phenotypes. The functionally-informed efficient region-based test strategy (FIERS) introduced herein uses prior knowledge on biological function and dependence of genotypes within a powerful statistical framework with improved sensitivity and specificity for detecting consistent genetic effects across studies. As proof of concept, FIERS was used for the first genome-wide single nucleotide polymorphism (SNP)-based investigation on bipolar disorder (BD) that focuses on an important aspect of disease course, the functional outcome. FIERS identified a significantly associated locus on chromosome 15 (hg38: chr15:48965004 – 49464789 bp) with consistent effect strength between two independent studies (GAIN/TGen: European Americans, BOMA: Germans; n = 1592 BD patients in total). Protective and risk haplotypes were found on the most strongly associated SNPs. They contain a CTCF binding site (rs586758); CTCF sites are known to regulate sets of genes within a chromatin domain. The rs586758 – rs2086256 – rs1904317 haplotype is located in the promoter flanking region of the COPS2 gene, close to microRNA4716, and the EID1, SHC4, DTWD1 genes as plausible biological candidates. While implication with BD is novel, COPS2, EID1, and SHC4 are known to be relevant for neuronal differentiation and function and DTWD1 for psychopharmacological side effects. The test strategy FIERS that enabled this discovery is equally applicable for tag SNPs and sequence data.
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    Pathway analysis of genomic data: concepts, methods, and prospects for future development
    (Elsevier, 2012) Ramanan, Vijay K.; Shen, Li; Moore, Jason H.; Saykin, Andrew J.; Medical and Molecular Genetics, School of Medicine
    Genome-wide data sets are increasingly being used to identify biological pathways and networks underlying complex diseases. In particular, analyzing genomic data through sets defined by functional pathways offers the potential of greater power for discovery and natural connections to biological mechanisms. With the burgeoning availability of next-generation sequencing, this is an opportune moment to revisit strategies for pathway-based analysis of genomic data. Here, we synthesize relevant concepts and extant methodologies to guide investigators in study design and execution. We also highlight ongoing challenges and proposed solutions. As relevant analytical strategies mature, pathways and networks will be ideally placed to integrate data from diverse -omics sources to harness the extensive, rich information related to disease and treatment mechanisms.