Browsing by Author "Chen, Junfang"

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    Differential resting-state patterns across networks are spatially associated with Comt and Trmt2a gene expression patterns in a mouse model of 22q11.2 deletion
    (Elsevier, 2021) Gass, Natalia; Peterson, Zeru; Reinwald, Jonathan; Sartorius, Alexander; Weber-Fahr, Wolfgang; Sack, Markus; Chen, Junfang; Cao, Han; Didriksen, Michael; Stensbøl, Tine Bryan; Klemme, Gabriele; Schwarz, Adam J.; Schwarz, Emanuel; Meyer-Lindenberg, Andreas; Nickl-Jockschat, Thomas; Radiology and Imaging Sciences, School of Medicine
    Copy number variations (CNV) involving multiple genes are ideal models to study polygenic neuropsychiatric disorders. Since 22q11.2 deletion is regarded as the most important single genetic risk factor for developing schizophrenia, characterizing the effects of this CNV on neural networks offers a unique avenue towards delineating polygenic interactions conferring risk for the disorder. We used a Df(h22q11)/+ mouse model of human 22q11.2 deletion to dissect gene expression patterns that would spatially overlap with differential resting-state functional connectivity (FC) patterns in this model (N = 12 Df(h22q11)/+ mice, N = 10 littermate controls). To confirm the translational relevance of our findings, we analyzed tissue samples from schizophrenia patients and healthy controls using machine learning to explore whether identified genes were co-expressed in humans. Additionally, we employed the STRING protein-protein interaction database to identify potential interactions between genes spatially associated with hypo- or hyper-FC. We found significant associations between differential resting-state connectivity and spatial gene expression patterns for both hypo- and hyper-FC. Two genes, Comt and Trmt2a, were consistently over-expressed across all networks. An analysis of human datasets pointed to a disrupted co-expression of these two genes in the brain in schizophrenia patients, but not in healthy controls. Our findings suggest that COMT and TRMT2A form a core genetic component implicated in differential resting-state connectivity patterns in the 22q11.2 deletion. A disruption of their co-expression in schizophrenia patients points out a prospective cause for the aberrance of brain networks communication in 22q11.2 deletion syndrome on a molecular level.
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    Genome-wide Association Studies in Ancestrally Diverse Populations: Opportunities, Methods, Pitfalls, and Recommendations
    (Elsevier, 2019-10-10) Peterson, Roseann E.; Kuchenbaecker, Karoline; Walters, Raymond K.; Chen, Chia-Yen; Popejoy, Alice B.; Periyasamy, Sathish; Lam, Max; Iyegbe, Conrad; Strawbridge, Rona J.; Brick, Leslie; Carey, Caitlin E.; Martin, Alicia R.; Meyers, Jacquelyn L.; Su, Jinni; Chen, Junfang; Edwards, Alexis C.; Kalungi, Allan; Koen, Nastassja; Majara, Lerato; Schwarz, Emanuel; Smoller, Jordan W.; Stahl, Eli A.; Sullivan, Patrick F.; Vassos, Evangelos; Mowry, Bryan; Prieto, Miguel L.; Cuellar-Barboza, Alfredo; Bigdeli, Tim B.; Edenberg, Howard J.; Huang, Hailiang; Duncan, Laramie E.; Biochemistry and Molecular Biology, School of Medicine
    Genome-wide association studies (GWAS) have focused primarily on populations of European descent, but it is essential that diverse populations become better represented. Increasing diversity among study participants will advance our understanding of genetic architecture in all populations and ensure that genetic research is broadly applicable. To facilitate and promote research in multi-ancestry and admixed cohorts, we outline key methodological considerations and highlight opportunities, challenges, solutions, and areas in need of development. Despite the perception that analyzing genetic data from diverse populations is difficult, it is scientifically and ethically imperative, and there is an expanding analytical toolbox to do it well.