Patricia Braun and Alyssa Hahn to Present at Genetics Student Seminar on 1/23/17

Genome-wide DNA methylation analysis of high-dose synthetic glucocorticoid administration within buccal samples of oral surgery patients

Patricia Braun1, Aubrey Chan1, Kumi Yuki1, Benjamin Hing1, Lindsey Gaul1, Jonathan Heinzman1, Nick Sparr1, Julian Robles1, Theodosis Chronis1, Mai Tanaka-Sahker1, Kyle Stein2, James Potash1, Gen Shinozaki1

1Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, IA

2Department of Oral and Maxillofacial Surgery, University of Iowa College of Dentistry, Iowa City, Iowa\

Background: Glucocorticoids play a major role in regulating the stress response, and an imbalance of glucocorticoids has been implicated in stress-related disorders. Within mouse models, candidate genes have been shown to be differentially methylated in response to glucocorticoid treatment. However, within humans the extent to which glucocorticoids affect DNA methylation (DNAm) across the genome is unknown.

Method: Buccal samples were collected before and after synthetic glucocorticoid treatment in the context of oral surgery. This included 30 minor tooth extraction surgery patients who received 10 mg of dexamethasone, and 12 major jaw surgery patients who received 750-1,000 mg of methylprednisolone. Genome-wide DNAm was assessed with the Infinium HumanMethylationEPIC array. Data were processed and analyzed with the R package RnBeads. Statistical significance was determined using the limma method. The genome-wide significance threshold for this experiment is p<6.03 x 10-8.

Results: Within the minor surgery samples, 10 CpG sites surpassed the genome-wide significance threshold. The most significantly different CpG in the before vs. after treatment comparison was within the insulin-like growth factor 1 receptor (IGF1R; average DNAm: pre-steroid 7%, post-steroid 15%; p=2.72 x 10-10). Within major surgery subjects, no sites attained genome-wide level of significance. The top differentially methylated CpG was within the small nucleolar RNA host gene 16 (SNHG16; average DNAm: pre-steroid 20%, post-steroid 11%; p=4.49 x 10-5).

Conclusion: High-dose synthetic glucocorticoid administration in the setting of oral surgery is significantly associated with DNAm changes within buccal samples. These findings provide initial evidence for an influence of glucocorticoids on DNAm within humans.

 

INVESTIGATING SIMILAR GENETIC BURDEN AMONG CLUSTERED PRIMARY AND SECONDARY CNVS

Hahn1,2, M. Parida3, H. Major1, & B. Darbro1,2

1 Stead Family Department of Pediatrics, Carver College of Medicine; 2 Interdisciplinary Graduate Program in Genetics, University of Iowa; 3 Department of Biology, University of Iowa

According to a survey conducted by National Institute of Health, nearly 15% of the US population aged 3-18 are affected by developmental disabilities. While a variety of genetic and environmental factors have been implicated as causative factors, approximately 10-20% of cases can be attributed to copy number variations (CNVs). While chromosomal microarray data has provided insight into the genes which are directly affected by CNVs, and led to the identification of a number of unique genomic disorders, the contribution of individual genes within the pathogenic CNV interval to the clinical phenotype is still under investigation. Our lab has taken a novel approach to identify genotype-phenotype associations for CNVs by utilizing protein-protein interaction networks to better ascertain and model the total genetic burden caused by non-benign CNVs.

Preliminary data demonstrated that our method of network smoothing and non-negative matrix factorization clustering leads to robust segregation of patients with known CNV disorders into unique clusters. Several patient clusters contained individuals with one or more CNVs of unclear clinical significance (secondary CNVs) in absentia of the (primary) pathogenic CNV characteristic of the cluster, suggesting that one or more secondary CNVs can cause the same genetic burden as a primary CNV. We are currently in the process of quality controlling our analysis pipeline and performing more granular phenotypic characterization of our patient cohort. Future work in the lab will utilize bioinformatics techniques and programs to identify the underlying gene networks and genetic burden that inform and underlie each chosen patient cluster. Directed examination of the medical records for patients within each of the chosen clusters will be used to evaluate phenotypic consistency between the individuals with primary and secondary CNVs. Together, the gene network, genic burden, and phenotypic information will be used to develop genotype-phenotype associations.

 

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Posted on January 19, 2017, in Uncategorized. Bookmark the permalink. Leave a comment.

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