TY  - JOUR
A1  - Kress, Michaela
A1  - Hüttenhofer, Alexander
A1  - Landry, Marc
A1  - Kuner, Rohini
A1  - Favereaux, Alexandre
A1  - Greenberg, David
A1  - Bednarik, Josef
A1  - Heppenstall, Paul
A1  - Kronenberg, Florian
A1  - Malcangio, Marzia
A1  - Rittner, Heike
A1  - Üçeyler, Nurcan
A1  - Trajanoski, Zlatko
A1  - Mouritzen, Peter
A1  - Birklein, Frank
A1  - Sommer, Claudia
A1  - Soreq, Hermona
T1  - microRNAs in nociceptive circuits as predictors of future clinical applications
JF  - Frontiers in Molecular Neuroscience
N2  - Neuro-immune alterations in the peripheral and central nervous system play a role in the pathophysiology of chronic pain, and non-coding RNAs – and microRNAs (miRNAs) in particular – regulate both immune and neuronal processes. Specifically, miRNAs control macromolecular complexes in neurons, glia and immune cells and regulate signals used for neuro-immune communication in the pain pathway. Therefore, miRNAs may be hypothesized as critically important master switches modulating chronic pain. In particular, understanding the concerted function of miRNA in the regulation of nociception and endogenous analgesia and defining the importance of miRNAs in the circuitries and cognitive, emotional and behavioral components involved in pain is expected to shed new light on the enigmatic pathophysiology of neuropathic pain, migraine and complex regional pain syndrome. Specific miRNAs may evolve as new druggable molecular targets for pain prevention and relief. Furthermore, predisposing miRNA expression patterns and inter-individual variations and polymorphisms in miRNAs and/or their binding sites may serve as biomarkers for pain and help to predict individual risks for certain types of pain and responsiveness to analgesic drugs. miRNA-based diagnostics are expected to develop into hands-on tools that allow better patient stratification, improved mechanism-based treatment, and targeted prevention strategies for high risk individuals.
KW  - chronic pain
KW  - biomarker
KW  - polymorphism
KW  - miRNA-based diagnostics
KW  - miRNA expression patterns
KW  - miRNA polymorphisms
KW  - antagomir
KW  - miRNA-based analgesic
Y1  - 2013
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-154597
VL  - 6
IS  - 33
ER  - 
TY  - JOUR
A1  - Breuer, René
A1  - Mattheisen, Manuel
A1  - Frank, Josef
A1  - Krumm, Bertram
A1  - Treutlein, Jens
A1  - Kassem, Layla
A1  - Strohmaier, Jana
A1  - Herms, Stefan
A1  - Mühleisen, Thomas W.
A1  - Degenhardt, Franziska
A1  - Cichon, Sven
A1  - Nöthen, Markus M.
A1  - Karypis, George
A1  - Kelsoe, John
A1  - Greenwood, Tiffany
A1  - Nievergelt, Caroline
A1  - Shilling, Paul
A1  - Shekhtman, Tatyana
A1  - Edenberg, Howard
A1  - Craig, David
A1  - Szelinger, Szabolcs
A1  - Nurnberger, John
A1  - Gershon, Elliot
A1  - Alliey-Rodriguez, Ney
A1  - Zandi, Peter
A1  - Goes, Fernando
A1  - Schork, Nicholas
A1  - Smith, Erin
A1  - Koller, Daniel
A1  - Zhang, Peng
A1  - Badner, Judith
A1  - Berrettini, Wade
A1  - Bloss, Cinnamon
A1  - Byerley, William
A1  - Coryell, William
A1  - Foroud, Tatiana
A1  - Guo, Yirin
A1  - Hipolito, Maria
A1  - Keating, Brendan
A1  - Lawson, William
A1  - Liu, Chunyu
A1  - Mahon, Pamela
A1  - McInnis, Melvin
A1  - Murray, Sarah
A1  - Nwulia, Evaristus
A1  - Potash, James
A1  - Rice, John
A1  - Scheftner, William
A1  - Zöllner, Sebastian
A1  - McMahon, Francis J.
A1  - Rietschel, Marcella
A1  - Schulze, Thomas G.
T1  - Detecting significant genotype–phenotype association rules in bipolar disorder: market research meets complex genetics
JF  - International Journal of Bipolar Disorders
N2  - Background
Disentangling the etiology of common, complex diseases is a major challenge in genetic research. For bipolar disorder (BD), several genome-wide association studies (GWAS) have been performed. Similar to other complex disorders, major breakthroughs in explaining the high heritability of BD through GWAS have remained elusive. To overcome this dilemma, genetic research into BD, has embraced a variety of strategies such as the formation of large consortia to increase sample size and sequencing approaches. Here we advocate a complementary approach making use of already existing GWAS data: a novel data mining procedure to identify yet undetected genotype–phenotype relationships. We adapted association rule mining, a data mining technique traditionally used in retail market research, to identify frequent and characteristic genotype patterns showing strong associations to phenotype clusters. We applied this strategy to three independent GWAS datasets from 2835 phenotypically characterized patients with BD. In a discovery step, 20,882 candidate association rules were extracted.

Results
Two of these rules—one associated with eating disorder and the other with anxiety—remained significant in an independent dataset after robust correction for multiple testing. Both showed considerable effect sizes (odds ratio ~ 3.4 and 3.0, respectively) and support previously reported molecular biological findings.

Conclusion
Our approach detected novel specific genotype–phenotype relationships in BD that were missed by standard analyses like GWAS. While we developed and applied our method within the context of BD gene discovery, it may facilitate identifying highly specific genotype–phenotype relationships in subsets of genome-wide data sets of other complex phenotype with similar epidemiological properties and challenges to gene discovery efforts.
KW  - bipolar disorder
KW  - subphenotypes
KW  - rule discovery
KW  - data mining
KW  - genotype-phenotype patterns
Y1  - 2018
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-220509
VL  - 6
ER  -