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Your search keyword '"Andreas R. Pfenning"' showing total 2 results
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2 results on '"Andreas R. Pfenning"'

1. Molecular rhythm alterations in prefrontal cortex and nucleus accumbens associated with opioid use disorder

Author

Xiangning Xue, Wei Zong, Jill R. Glausier, Sam-Moon Kim, Micah A. Shelton, BaDoi N. Phan, Chaitanya Srinivasan, Andreas R. Pfenning, George C. Tseng, David A. Lewis, Marianne L. Seney, and Ryan W. Logan

Subjects
Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

Abstract Severe and persistent disruptions to sleep and circadian rhythms are common in people with opioid use disorder (OUD). Preclinical evidence suggests altered molecular rhythms in the brain modulate opioid reward and relapse. However, whether molecular rhythms are disrupted in the brains of people with OUD remained an open question, critical to understanding the role of circadian rhythms in opioid addiction. Using subjects’ times of death as a marker of time of day, we investigated transcriptional rhythms in the brains of subjects with OUD compared to unaffected comparison subjects. We discovered rhythmic transcripts in both the dorsolateral prefrontal cortex (DLPFC) and nucleus accumbens (NAc), key brain areas involved in OUD, that were largely distinct between OUD and unaffected subjects. Fewer rhythmic transcripts were identified in DLPFC of subjects with OUD compared to unaffected subjects, whereas in the NAc, nearly double the number of rhythmic transcripts was identified in subjects with OUD. In NAc of subjects with OUD, rhythmic transcripts peaked either in the evening or near sunrise, and were associated with an opioid, dopamine, and GABAergic neurotransmission. Associations with altered neurotransmission in NAc were further supported by co-expression network analysis which identified OUD-specific modules enriched for transcripts involved in dopamine, GABA, and glutamatergic synaptic functions. Additionally, rhythmic transcripts in DLPFC and NAc of subjects with OUD were enriched for genomic loci associated with sleep-related GWAS traits, including sleep duration and insomnia. Collectively, our findings connect transcriptional rhythm changes in opioidergic, dopaminergic, GABAergic signaling in the human brain to sleep-related traits in opioid addiction.

Published
2022
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2. Integrative analysis of 111 reference human epigenomes

Author

Daofeng Li, Tim R. Mercer, Wei Li, Lisa Helbling Chadwick, Jesse R. Dixon, Pouya Kheradpour, Joseph F. Costello, Pradipta R. Ray, John W. Whitaker, Peggy J. Farnham, Angela Tam, Vitor Onuchic, Robert A. Waterland, Misha Bilenky, James A. Thomson, Zhizhuo Zhang, Yaping Liu, Gerald Quon, Andrew J. Mungall, Steven J.M. Jones, Bradley E. Bernstein, Alexander Meissner, Melina Claussnitzer, Charles B. Epstein, Andreas R. Pfenning, Li-Huei Tsai, Laurie A. Boyer, Angela Yen, Ting Wang, Rajinder Kaul, Alireza Heravi-Moussavi, Danny Leung, Noam Shoresh, Michael T. McManus, Michael Stevens, John A. Stamatoyannopoulos, Mukul S. Bansal, Thea D. Tlsty, Susan J. Fisher, Manolis Kellis, Michael Q. Zhang, Aleksandar Milosavljevic, Viren Amin, Martin Hirst, Matthew D. Schultz, Joseph R. Ecker, Xinchen Wang, Jie Wu, Marco A. Marra, Kyle Siebenthall, Wei Wang, Ashwinikumar Kulkarni, Peter J. Sabo, R. Scott Hansen, Jianrong Wang, Michael J. Ziller, Richard A. Moore, Shane Neph, Richard C Sallari, Robert E. Thurman, Paz Polak, Wei Xie, Eric Chuah, Jason Ernst, Bing Ren, Nisha Rajagopal, Anshul Kundaje, Xin Zhou, Yi-Chieh Wu, Shamil R. Sunyaev, Ginell Elliott, Philippe Gascard, Soheil Feizi, Chibo Hong, R. Alan Harris, Ah Ram Kim, Philip L. De Jager, Rosa Karlic, R. David Hawkins, Matthew L. Eaton, Ryan Lister, Rebecca F. Lowdon, Annaick Carles, Elizabeta Gjoneska, David Haussler, Abhishek Sarkar, Nicholas A Sinnott-Armstrong, Wouter Meuleman, Lucas D. Ward, Kai How Farh, Richard Sandstrom, Arthur E. Beaudet, Theresa K. Canfield, Cristian Coarfa, Bo Zhang, Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology. Department of Biology, Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science, Picower Institute for Learning and Memory, Kundaje, Anshul, Meuleman, Wouter, Ernst, Jason, Yen, Angela, Kheradpour, Pouya, Zhang, Zhizhuo, Wang, Jianrong, Ward, Lucas D., Sarkar, Abhishek Kulshreshtha, Quon, Gerald, Eaton, Matthew Lucas, Wu, Yi-Chieh, Pfenning, Andreas R., Wang, Xinchen, Claussnitzer, Melina, Liu, Yaping, Bansal, Mukul S., Feizi-Khankandi, Soheil, Kim, Ah Ram, Cowper Sal-lari, Richard, Sinnott-Armstrong, Nicholas A., Kellis, Manolis, Boyer, Laurie, Gjoneska, Elizabeta, and Tsai, Li-Huei

Subjects
Epigenomics, Datasets as Topic, ATAC-seq, Computational biology, Biology, Article, Epigenesis, Genetic, Histones, Reference Values, Computational epigenetics, Chromosomes, Human, Humans, Cell Lineage, Epigenetics, Cells, Cultured, Genetics, Regulation of gene expression, Multidisciplinary, Base Sequence, Genome, Human, Genetic Variation, DNA, Epigenome, DNA Methylation, Chromatin, Human genetics, Enhancer Elements, Genetic, Organ Specificity, RNA, Human genome, chromatin, histone, epigenome, tissue specificity, Genome-Wide Association Study
Abstract

The reference human genome sequence set the stage for studies of genetic variation and its association with human disease, but epigenomic studies lack a similar reference. To address this need, the NIH Roadmap Epigenomics Consortium generated the largest collection so far of human epigenomes for primary cells and tissues. Here we describe the integrative analysis of 111 reference human epigenomes generated as part of the programme, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression. We establish global maps of regulatory elements, define regulatory modules of coordinated activity, and their likely activators and repressors. We show that disease- and trait-associated genetic variants are enriched in tissue-specific epigenomic marks, revealing biologically relevant cell types for diverse human traits, and providing a resource for interpreting the molecular basis of human disease. Our results demonstrate the central role of epigenomic information for understanding gene regulation, cellular differentiation and human disease., National Human Genome Research Institute (U.S.) (RC1HG005334), National Human Genome Research Institute (U.S.) (R01HG004037), National Human Genome Research Institute (U.S.) (R01HG004037-S1), National Human Genome Research Institute (U.S.) (RO1NS078839), National Science Foundation (U.S.) (CAREER Award 1254200)

Published
2014

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