Finding the genetic markers that influence complex, multigenic substance addiction phenotypes has been an area of significant medical study. Understanding complex disease traits like addiction has been hampered by the lack of functional insights into novel variants to the human genome. We hypothesized that gene location plays a role in functional genomic neighborhoods.
To test whether there is a relationship between opiate, dopamine, and GABA disease and population allele frequencies, we used genes obtained from addiction literature curated by the National Center for Biotechnology Information (NCBI). These addiction and metabolism focused search terms generated opiate, dopamine, and GABA addiction results (N=587 genes). These genes were then projected onto the genome to identify cluster regions of genetic importance for substance addiction. Clusters were defined as regions of the genome with more than six genes within a 1.5Mb linear genomic window. We identified seven hotspots located on chromosomes 4, 6 (2 clusters), 10, 11, and 19. Human polymorphism data was surveyed from the 1148 individuals comprising the 11 sample populations of the HapMap Project dataset. Our analyses demonstrate that when human populations are assessed, ten candidate addiction alleles were identified. Finally assessments of public genome wide association studies show long range linkages to canonical addiction genes. This study delineates a novel method to identify novel candidate addiction variants using a systems biology approach that relies on an interdisciplinary set of data, including genomic, pathway data, and population variation. Important connections to sociological and environmental data are discussed to contextualize addiction data.
Key Take Away Points
- These results identify for the first time the presence of seven opiate, dopamine, and GABA hotspots located across the genome, three of which are GABA specific with the balance being mixed addiction hotspots.
- All but two of these hotspots share functional annotation between those genes previously identified from the addiction literature as participating in addiction phenotypes and their co-located gene neighbors.
- When all genes within a hotspot window are mapped onto KEGG pathways, they identify both canonical pathways such as acute alcohol intoxication as well as more unconventional pathways such as those involved in systemic lupus.
- Three striking ethnicity based signatures arose: Yoruba (YRI) , a tropical living Africans show differences from all other ethnic populations at two hotspots which East Asian populations (CHB,CHD, and JPT) showed differences to all other surveyed populations at another hotspot.
Dr. Jackson received her Bachelor’s degrees in Cell/Molecular Biology and Genetics (B.S.) and French Language and Literature (B.A.) from the University of Maryland at College Park. in 2011, She received my Master’s degree in Ecology & Evolutionary Biology from the University of Arizona. She completed her Ph.D. in Biomedical Science in 2014 from the School of Biomedical Engineering, Science and Health Systems at Drexel University. Her dissertation research investigated the use of gene locality in identifying genomic regions of interest for chronic and infectious disease and how disease risk and resistance alleles segregate in human populations. She uses bioinformatics, functional genomics and evolutionary biology approaches to study genetic patterns that contribute to disease phenotypes within a biological anthropology framework. Her postdoctoral research seeks to explore how genetic variants and environmental factors contribute to the complex phenotypes associated with resilience to social adversity.
LFJ would like to acknowledge Dr. Ceylan Tanes, Maksim Shestov and Dr. Aydin Tozeren for important conversation on the bioinformatics implemented in this project.
Jackson, Latifa F.
"A Novel Bioinformatic Approach to Understanding Addiction,"
Journal of Family Strengths: Vol. 17:
1, Article 4.
Available at: https://digitalcommons.library.tmc.edu/jfs/vol17/iss1/4