2011 University Of New England College Of Osteopathic Medicine Fellowship Recipients

2011 recipients of the University of New England College of Osteopathic Medicine\u27s Peter Morgane Research Fellowship (known then as the Dean’s Research Fellowship)

A panel of DNA methylation markers for the detection of prostate cancer from FV and DRE urine DNA

Abstract Background Early screening for prostate cancer (PCA) remains controversial because of overdiagnosis and overtreatment of clinically insignificant cancers. Even though a number of diagnostic tests have been developed to improve on PSA testing, there remains a need for a more informative non-invasive test for PCA. The objective of this study is to identify a panel of DNA methylation markers suitable for a non-invasive diagnostic test from urine DNA collected following a digital rectal exam (DRE) and/or from first morning void (FV). A secondary objective is to determine if the cumulative methylation is indicative of biopsy findings. Methods DRE and FV urine samples were prospectively collected from 94 patients and analyzed using 24 methylation-specific quantitative PCR assays derived from 19 CpG islands. The methylation of individual markers and various combinations of markers was compared to biopsy results. A methylation threshold for cancer classification was determined using a target specificity of 70%. The average methylation and the number of positive markers were also compared to the result of the biopsy, and the area under the receiver operating characteristic curves (AUCs) were calculated. Results Methylation of all 19 markers was detected in FV and DRE DNAs. Combining the methylation of two or more markers improved on individual marker results. Using 6of19 methylated markers as the threshold for cancer classification yielded a specificity of 71% (95% CI, 0.57–0.86) from both DRE and FV and a sensitivity of 89% (95% CI, 0.79–0.97) from DRE and 94% (95% CI, 0.84–1.0) from FV. The negative predictive value at the 6of19 threshold was ≥ 90 for both DNA types. Conclusions PCA-specific methylation was detected in both FV and DRE DNA. There was no significant difference in diagnostic accuracy at the 6of19 threshold between DRE and FV urine DNA. The results support the development of a non-invasive diagnostic test to reduce unnecessary biopsies in men with elevated PSA. The test can also provide patients with personalized recommendations based on their own methylation profile

Additional file 4: of A panel of DNA methylation markers for the detection of prostate cancer from FV and DRE urine DNA

The file contains the marker data. The patients were sorted and assigned new numbers that are unrelated to the alphanumeric code used as the identifier when the clinical samples were collected. (XLSX 35 kb

Use of a dense single nucleotide polymorphism map for in silico mapping in the mouse

Rapid expansion of available data, both phenotypic and genotypic, for multiple strains of mice has enabled the development of new methods to interrogate the mouse genome for functional genetic perturbations. In silico mapping provides an expedient way to associate the natural diversity of phenotypic traits with ancestrally inherited polymorphisms for the purpose of dissecting genetic traits. In mouse, the current single nucleotide polymorphism (SNP) data have lacked the density across the genome and coverage of enough strains to properly achieve this goal. To remedy this, 470,407 allele calls were produced for 10,990 evenly spaced SNP loci across 48 inbred mouse strains. Use of the SNP set with statistical models that considered unique patterns within blocks of three SNPs as an inferred haplotype could successfully map known single gene traits and a cloned quantitative trait gene. Application of this method to high-density lipoprotein and gallstone phenotypes reproduced previously characterized quantitative trait loci (QTL). The inferred haplotype data also facilitates the refinement of QTL regions such that candidate genes can be more easily identified and characterized as shown for adenylate cyclase 7

Use of a Dense Single Nucleotide Polymorphism Map for In Silico Mapping in the Mouse

<div><p>Rapid expansion of available data, both phenotypic and genotypic, for multiple strains of mice has enabled the development of new methods to interrogate the mouse genome for functional genetic perturbations. In silico mapping provides an expedient way to associate the natural diversity of phenotypic traits with ancestrally inherited polymorphisms for the purpose of dissecting genetic traits. In mouse, the current single nucleotide polymorphism (SNP) data have lacked the density across the genome and coverage of enough strains to properly achieve this goal. To remedy this, 470,407 allele calls were produced for 10,990 evenly spaced SNP loci across 48 inbred mouse strains. Use of the SNP set with statistical models that considered unique patterns within blocks of three SNPs as an inferred haplotype could successfully map known single gene traits and a cloned quantitative trait gene. Application of this method to high-density lipoprotein and gallstone phenotypes reproduced previously characterized quantitative trait loci (QTL). The inferred haplotype data also facilitates the refinement of QTL regions such that candidate genes can be more easily identified and characterized as shown for <em>adenylate cyclase 7.</em></p> </div

Analysis of <i>Adcy7</i> Haplotypes Reveals Amino Acid Change Associated with HDL Phenotype

<div><p>(A) Sequencing of <i>Adcy7</i> in multiple strains revealed 28 SNPs distinguishing three distinct haplotype patterns. All strains were typed with markers selected to represent the three haplotypes. The strain distribution pattern predicted by the SNP data and the sample sequencing for this region was confirmed with NZB/BlNJ and BTBR T+ tf/J, I/LnJ and MA/MyJ, and C3H/HeJ, C57BL6/J, and C57L/J, each separating into unique haplotypes.</p> <p>(B) The SNP represented by marker 08.089.597 resulted in a change from a cysteine to a tyrosine in the resulting protein (asterisk). This cysteine is conserved in orthologs of the gene in human, rat, and cow. It is also found at the beginning of a stretch of ten amino acids (indicated by black line) predicted to be one of the protein's ten transmembrane domains. Identical amino acids are black and conserved amino acid changes are gray.</p></div

Visualization of the SNP Sets Allows for Mapping in Crosses That Minimize the Number of Potential Modifiers

<p>When the distribution of the SNPs is plotted out genome-wide, the expected irregular clustering of SNPs mark regions where heterozygosity was continuing to segregate during the inbreeding of the C57 family. Likewise, there are regions that were successfully homozygosed before the split of C58/J from the rest of the family members. In all five strain comparisons, no SNPs were found in the distal 25 Mb of MMU19.</p

Comparative genome and proteome analysis of Anopheles gambiae and Drosophila melanogaster

Comparison of the genomes and proteomes of the two diptera Anopheles gambiae and Drosophila melanogaster, which diverged about 250 million years ago, reveals considerable similarities. However, numerous differences are also observed; some of these must reflect the selection and subsequent adaptation associated with different ecologies and life strategies. Almost half of the genes in both genomes are interpreted as orthologs and show an average sequence identity of about 56%, which is slightly lower than that observed between the orthologs of the pufferfish and human (diverged about 450 million years ago). This indicates that these two insects diverged considerably faster than vertebrates. Aligned sequences reveal that orthologous genes have retained only half of their intron/exon structure, indicating that intron gains or losses have occurred at a rate of about one per gene per 125 million years. Chromosomal arms exhibit significant remnants of homology between the two species, although only 34% of the genes colocalize in small "microsyntenic" clusters, and major interarm transfers as well as intra-arm shuffling of gene order are detected