Georgia M Dunston

Howard University, Вашингтон, West Virginia, United States

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Publications (86)499.64 Total impact

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    ABSTRACT: Genome wide association studies (GWAS) for type 2 diabetes (T2D) undertaken in European and Asian ancestry populations have yielded dozens of robustly associated loci. However, the genomics of T2D remains largely understudied in sub-Saharan Africa (SSA), where rates of T2D are increasing dramatically and where the environmental background is quite different than in these previous studies. Here, we evaluate 106 reported T2D GWAS loci in continental Africans. We tested each of these SNPs, and SNPs in linkage disequilibrium (LD) with these index SNPs, for an association with T2D in order to assess transferability and to fine map the loci leveraging the generally reduced LD of African genomes. The study included 1775 unrelated Africans (1035 T2D cases, 740 controls; mean age 54 years; 59% female) enrolled in Nigeria, Ghana, and Kenya as part of the Africa America Diabetes Mellitus (AADM) study. All samples were genotyped on the Affymetrix Axiom PanAFR SNP array. Forty-one of the tested loci showed transferability to this African sample (p < 0.05, same direction of effect), 11 at the exact reported SNP and 30 others at SNPs in LD with the reported SNP (after adjustment for the number of tested SNPs). TCF7L2 SNP rs7903146 was the most significant locus in this study (p = 1.61 × 10−8). Most of the loci that showed transferability were successfully fine-mapped, i.e., localized to smaller haplotypes than in the original reports. The findings indicate that the genetic architecture of T2D in SSA is characterized by several risk loci shared with non-African ancestral populations and that data from African populations may facilitate fine mapping of risk loci. The study provides an important resource for meta-analysis of African ancestry populations and transferability of novel loci.
    Frontiers in Genetics 11/2015; 6. DOI:10.3389/fgene.2015.00335
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    ABSTRACT: Several studies reported that patients with benign prostatic hyperplasia (BPH) experienced a 10% increased incidence of prostate cancer (PCa) after the first 5 years of diagnosis. We investigated the association between single nucleotide polymorphisms (SNPs) in the promoter of Serine Protease Inhibitor Kazal Type 1 (SPINK1) and the increased risk of BPH and PCa. We genotyped three SNPs in a cases-control study, including BPH and PCa cases. Multiple logistic regression models were applied to analyze clinical and genotypic data. We found an inverse association between SNP rs10035432 and BPH under the log-additive (p=0.007) model. No association was found between these SNPs and PCa risk. However, we observed a possible association between rs1432982 and lower-grade PCa (p=0.05) under the recessive model. SPINK1 promoter variants are likely to be associated with the risk of BPH. Copyright© 2015 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.
    Anticancer research 07/2015; 35(7):3811-9. · 1.83 Impact Factor
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    ABSTRACT: Prostate cancer (PCa) shows disproportionately higher incidence and disease-associated mortality in African Americans. The human crystallin beta B2 (CRYBB2) gene has been reported as one tumor signature gene differentially expressed between African American and European American cancer patients. We investigated the role of CRYBB2 genetic variants in PCa in African Americans. Subjects comprised of 233 PCa cases and 294 controls. Nine haplotype-tagged single nucleotide polymorphisms (SNPs) in and around the CRYBB2 gene were genotyped by pyrosequencing. Association analyses were performed for PCa with adjustment for age and prostate-specific antigen (PSA), under an additive genetic model. Out of the nine SNPs examined, rs9608380 was found to be nominally associated with PCa (odds ratio (OR)=2.619 (95% confidence interval (CI)=1.156-5.935), p=0.021). rs9306412 was in strong linkage disequilibrium with rs9608380 that showed an association p-value of 0.077. Using ENCODE data, we found rs9608380 mapped to a region annotated with regulatory motifs, such as DNase hypersensitive sites and histone modifications. This is the first study to analyze the association between genetic variations in the CRYBB2 gene with PCa. rs9608380, associated with PCa, is a potentially functional variant. Copyright© 2015 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.
    Anticancer research 05/2015; 35(5):2565-70. · 1.83 Impact Factor
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    ABSTRACT: Several studies have revealed an association between single nucleotide polymorphisms (SNPs) in the VDR gene and prostate cancer (PCa) risk in European and Asian populations. To investigate whether VDR SNPs are associated with PCa risk in African-American (AA) men, nine VDR SNPs were analyzed in a case-control study. Multiple and binary logistic regression models were applied to analyze the clinical and genotypic data. rs731236 and rs7975232 were significantly associated with PCa risk (p<0.05). In the analysis of clinical phenotypes, rs731236, rs1544410 and rs3782905 were strongly associated with high PSA level (p<0.05), whereas rs1544410 and rs2239185 showed a statistically significant association with high Gleason score (p<0.05). Haplotype analysis revealed several VDR haplotypes associated with PCa risk. Additionally, a trend existed, where as the number of risk alleles increased in the haplotype, the greater was the association with risk (p-trend=0.01). These results suggest that the VDR SNPs may be associated with PCa risk and other clinical phenotypes of PCa in AA men. Copyright© 2015 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.
    Anticancer research 03/2015; 35(3):1549-58. · 1.83 Impact Factor

  • Journal of Allergy and Clinical Immunology 02/2015; 135(2):AB162. DOI:10.1016/j.jaci.2014.12.1469 · 11.48 Impact Factor
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    James Lindesay · Tshela E Mason · William Hercules · Georgia M Dunston ·
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    ABSTRACT: Single nucleotide polymorphisms (SNPs) represent an important type of dynamic sites within the human genome. These common variants often locally correlate within more complex multi-SNP haploblocks that are maintained throughout generations in a stable population. Information encoded in the structure of SNPs and SNP haploblock variation can be characterized through a normalized information content metric. Genodynamics is being developed as the analogous "thermodynamics" characterizing the state variables for genomic populations that are stable under stochastic environmental stresses. Since living systems have not been found to develop in the absence of environmental influences, this paper describes the analogous genomic free energy metrics in a given environment. SNP haploblocks were constructed by Haploview v4.2 for five chromosomes from phase III HapMap data, and the genomic state variables for each chromosome were calculated. An in silico analysis was performed on SNP haploblocks with the lowest genomic energy measures. Highly favorable genomic energy measures were found to correlate with highly conserved SNP haploblocks. Moreover, the most conserved haploblocks were associated with an evolutionarily conserved regulatory element and domain.
    11/2014; 6(1).
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    William Hercules · James Lindesay · Tshela E Mason · Georgia M Dunston ·
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    ABSTRACT: The human genome is a complex, dynamic information system that encodes principles of life and living systems. These principles are incorporated in the structure of human genome sequence variation and are foundational for the continuity of life and human survival. Using first principles of thermodynamics and statistical physics, we have developed analogous "genodynamic tools" for population genomic studies. Characterizing genomic information through the lens of physics has allowed us to develop energy measures for modeling genome-environment interactions. In developing biophysical parameters for genome-environment homeostasis, we found that stable genomic free energy trades off low genomic energy (genomic conservation and increased order) and high genomic entropy (genomic variation) with an environmental potential that drives the variation. In our approach, we assert that common variants are dynamic sites in the genome of a population and that the stability of whole genome adaptation is reflected in the frequencies of maintained diversity in common variants for the population in its environment. In this paper, we address the relativity of whole genome adaptation towards homeostasis. By this we mean that adaptive forces are directly reflected in the frequency distribution of alleles and/or haplotypes of the population relative to its environment, with adaptive forces driving the genome towards homeostasis. The use of genomic energy units as a biophysical metric in DNA sequence variation analyses provides new insights into the foundations of population biology and diversity. Using our biophysical tools, population differences directly reflect the adaptive influences of the environment on populations.
    Natural Science 10/2014; 6(15):1228-1231. DOI:10.4236/ns.2014.615110
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    Georgia M Dunston · Tshela E Mason · William Hercules · James Lindesay ·
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    ABSTRACT: Nested in the environment of the nucleus of the cell, the 23 sets of chromosomes that comprise the human genome function as one integrated whole system, orchestrating the expression of thousands of genes underlying the biological characteristics of the cell, individual and the species. The extraction of meaningful information from this complex data set depends crucially upon the lens through which the data are examined. We present a biophysical perspective on genomic information encoded in single nucleotide polymorphisms (SNPs), and introduce metrics for modeling information encoded in the genome. Information, like energy, is considered to be a conserved physical property of the universe. The information structured in SNPs describes the adaptation of a human population to a given environment. The maintained order measured by the information content is associated with entropies, energies, and other state variables for a dynamic system in homeostasis. "Genodynamics" characterizes the state variables for genomic populations that are stable under stochastic environmental stresses. The determination of allelic energies allows the parameterization of specific environmental influences upon individual alleles across populations. The environment drives population-based genome variation. From this vantage point, the genome is modeled as a complex, dynamic information system defined by patterns of SNP alleles and SNP haplotypes.
    Advances in Bioscience and Biotechnology 06/2014; 5(7):623-626. DOI:10.4236/abb.2014.57073
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    James Lindesay · Tshela E. Mason · William Hercules · Georgia M. Dunston ·
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    ABSTRACT: Single nucleotide polymorphisms (SNPs) represent an important type of dynamic sites within the human genome. These common variants often locally correlate into more complex multi-SNP haploblocks that are maintained throughout generations in a stable population. The information encoded in the structure of common SNPs and SNP haploblock variation can be characterized through a normalized information content (NIC) metric. Such an intrinsic measure allows disparate regions of individual genomes and the genomes of various populations to be quantitatively compared in a meaningful way. Using our defined measures of genomic information, the interplay of maintained statistical variations due to the environmental baths within which stable populations exist can be interrogated. We develop the analogous "thermodynamics" characterizing the state variables for genomic populations that are stable under stochastic environmental stresses. Since living systems have not been found to develop in the absence of environmental influences, we focus on describing the analogous genomic free energy measures in this development. The intensive parameter describing how an environment drives genomic diversity is found to depend inversely upon the NIC of the genome of a stable population within that environment. Once this environmental potential has been determined from the whole genome of a population, additive state variables can be directly related to the probabilities of the occurrence of given viable SNP based units (alleles) within that genome. This formulation allows the determination of both population averaged state variables as well as the genomic energies of individual alleles and their combinations. The determination of individual allelic potentials then should allow the parameterization of specific environmental influences upon shared alleles across populations in varying environments.
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    ABSTRACT: Multiple Sclerosis (MS) is a complex disease where genetic and environmental factors have been implicated. The onset of symptoms occurs in individuals from twenty to fifty years of age, producing a progressive impairment of motor, sensory and cognitive functions. MS is more frequent in females than in males with a ratio of 4:1. The prevalence of the MS varies among ethnics groups such as Europeans, Africans and Caucasians. The estimated prevalence of MS in Puerto Rico is 42 for each 100,000 habitants, which is more than the prevalence reported for Central America and the Caribbean. In spite of this prevalence, the genetic component of MS has not been explored in order to know the alleles' expression of Puerto Rican MS patients and compare it with the allele expression in other ethnic groups. Thirty-five patients and 31 control subjects were genotyped. The allele frequencies expressed in this sample were similar to those expressed for Puerto Ricans in the National Marrow Donor Program Registry (n = 3,149). The most prevalent alleles for MS patients were HLA-DRB1*01 and *03. HLA-DQB1*04 was the most frequent in the control group and HLA-A*30, in MS patients. These findings are in agreement with published data. HLA-DQB1*04 was a marginal protector in this sample and this role has not been described before. The accuracy of the results is limited due to the sample size. After performing a statistical power analysis it showed that by increasing the sample the values would be significant.
    Boletín de la Asociación Médica de Puerto Rico 06/2013; 105(1):18-23.
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    ABSTRACT: Characterization of genetic admixture of populations in the Americas and the Caribbean is of interest for anthropological, epidemiological, and historical reasons. Asthma has a higher prevalence and is more severe in populations with a high African component. Association of African ancestry with asthma has been demonstrated. We estimated admixture proportions of samples from six trihybrid populations of African descent and determined the relationship between African ancestry and asthma and total serum IgE levels (tIgE). We genotyped 237 ancestry informative markers in asthmatics and nonasthmatic controls from Barbados (190/277), Jamaica (177/529), Brazil (40/220), Colombia (508/625), African Americans from New York (207/171), and African Americans from Baltimore/Washington, D.C. (625/757). We estimated individual ancestries and evaluated genetic stratification using Structure and principal component analysis. Association of African ancestry and asthma and tIgE was evaluated by regression analysis. Mean ± SD African ancestry ranged from 0.76 ± 0.10 among Barbadians to 0.33 ± 0.13 in Colombians. The European component varied from 0.14 ± 0.05 among Jamaicans and Barbadians to 0.26 ± 0.08 among Colombians. African ancestry was associated with risk for asthma in Colombians (odds ratio (OR) = 4.5, P = 0.001) Brazilians (OR = 136.5, P = 0.003), and African Americans of New York (OR: 4.7; P = 0.040). African ancestry was also associated with higher tIgE levels among Colombians (β = 1.3, P = 0.04), Barbadians (β = 3.8, P = 0.03), and Brazilians (β = 1.6, P = 0.03). Our findings indicate that African ancestry can account for, at least in part, the association between asthma and its associated trait, tIgE levels.
    Genetic Epidemiology 05/2013; 37(4). DOI:10.1002/gepi.21702 · 2.60 Impact Factor
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    Georgia M Dunston ·
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    ABSTRACT: The complete sequencing of the human genome introduced a new knowledge base for decoding information structured in DNA sequence variation. My research is predicated on the supposition that the genome is the most sophisticated knowledge system known, as evidenced by the exquisite information it encodes on biochemical pathways and molecular processes underlying the biology of health and disease. Also, as a living legacy of human origins, migrations, adaptations, and identity, the genome communicates through the complexity of sequence variation expressed in population diversity. As a biomedical research scientist and academician, a question I am often asked is: "How is it that a black woman like you went to the University of Michigan for a PhD in Human Genetics?" As the ASCB 2012 E. E. Just Lecturer, I am honored and privileged to respond to this question in this essay on the science of the human genome and my career perspectives.
    Molecular biology of the cell 11/2012; 23(21):4154-6. DOI:10.1091/mbc.E12-05-0342 · 4.47 Impact Factor
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    ABSTRACT: Background: Prostate cancer (PCa) is a common malignancy and a leading cause of cancer death among men in the United States with African-American (AA) men having the highest incidence and mortality rates. Given recent results from admixture mapping and genome-wide association studies for PCa in AA men, it is clear that many risk alleles are enriched in men with West African genetic ancestry. Methods: A total of 77 ancestry informative markers (AIMs) within surrounding candidate gene regions were genotyped and haplotyped using Pyrosequencing in 358 unrelated men enrolled in a PCa genetic association study at the Howard University Hospital between 2000 and 2004. Sequence analysis of promoter region single-nucleotide polymorphisms (SNPs) to evaluate disruption of transcription factor-binding sites was conducted using in silico methods. Results: Eight AIMs were significantly associated with PCa risk after adjusting for age and West African ancestry. SNP rs1993973 (intervening sequences) had the strongest association with PCa using the log-additive genetic model (P=0.002). SNPs rs1561131 (genotypic, P=0.007), rs1963562 (dominant, P=0.01) and rs615382 (recessive, P=0.009) remained highly significant after adjusting for both age and ancestry. We also tested the independent effect of each significantly associated SNP and rs1561131 (P=0.04) and rs1963562 (P=0.04) remained significantly associated with PCa development. After multiple comparisons testing using the false discovery rate, rs1993973 remained significant. Analysis of the rs156113-, rs1963562-rs615382l and rs1993973-rs585224 haplotypes revealed that the least frequently found haplotypes in this population were significantly associated with a decreased risk of PCa (P=0.032 and 0.0017, respectively). Conclusions: The approach for SNP selection utilized herein showed that AIMs may not only leverage increased linkage disequilibrium in populations to identify risk and protective alleles, but may also be informative in dissecting the biology of PCa and other health disparities.
    Prostate cancer and prostatic diseases 07/2012; 15(4). DOI:10.1038/pcan.2012.19 · 3.43 Impact Factor

  • Cancer Research 06/2012; 72(8 Supplement):692-692. DOI:10.1158/1538-7445.AM2012-692 · 9.33 Impact Factor
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    ABSTRACT: The 21(st) century emergence of genomic medicine is shifting the paradigm in biomedical science from the population phenotype to the individual genotype. In characterizing the biology of disease and health disparities in population genetics, human populations are often defined by the most common alleles in the group. This definition poses difficulties when categorizing individuals in the population who do not have the most common allele(s). Various epidemiological studies have shown an association between common genomic variation, such as single nucleotide polymorphisms (SNPs), and common diseases. We hypothesize that information encoded in the structure of SNP haploblock variation in the human leukocyte antigen-disease related (HLA-DR) region of the genome illumines molecular pathways and cellular mechanisms involved in the regulation of host adaptation to the environment. In this paper we describe the development and application of the normalized information content (NIC) as a novel metric based on SNP haploblock variation. The NIC facilitates translation of biochemical DNA sequence variation into a biophysical quantity derived from Boltzmann's canonical ensemble in statistical physics and used widely in information theory. Our normalization of this information metric allows for comparisons of unlike, or even unrelated, regions of the genome. We report here NIC values calculated for HLA-DR SNP haploblocks constructed by Haploview, a product of the International Haplotype Map Project. These haploblocks were scanned for potential regulatory elements using ConSite and miRBase, publicly available bioinformatics tools. We found that all of the haploblocks with statistically low NIC values contained putative transcription factor binding sites and microRNA motifs, suggesting correlation with genomic regulation. Thus, we were able to relate a mathematical measure of information content in HLA-DR SNP haploblocks to biologically relevant functional knowledge embedded in the structure of DNA sequence variation. We submit that NIC may be useful in analyzing the regulation of molecular pathways involved in host adaptation to environmental pathogens and in decoding the functional significance of common variation in the human genome.
    02/2012; 4(2):15-22.

  • Cancer Epidemiology Biomarkers & Prevention 09/2011; 20(Supplement 1):A88-A88. DOI:10.1158/1055-9965.DISP-11-A88 · 4.13 Impact Factor

  • Cancer Epidemiology Biomarkers & Prevention 09/2011; 20(Supplement 1):A69-A69. DOI:10.1158/1055-9965.DISP-11-A69 · 4.13 Impact Factor
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    ABSTRACT: Although an increasing number of hypertension-associated genetic variants is being reported, replication of these findings in independent studies has been challenging. Several genes in a human chromosome 1q linkage region have been reported to be associated with hypertension. We examined polymorphisms in three of these genes (ATP1B1, RGS5 and SELE) in relation to hypertension and blood pressure in a cohort of African-Americans. We genotyped 87 single nucleotide polymorphisms (SNPs) from the ATP1B1, RGS5 and SELE genes in a well characterized cohort of 968 African-Americans and performed a case-control study to identify susceptibility alleles for hypertension and blood pressure regulation. Single SNP and haplotype association testing was done under an additive genetic model with adjustment for age, sex, BMI and ancestry-by-genotype (principal components). A total of 12 SNPs showed nominal association with hypertension and/or blood pressure. The strongest signal for hypertension was for rs2815272 in the RGS5 gene (P = 9.3 × 10). For SBP, rs3917420 in the SELE gene (P = 9.0 × 10) and rs4657251 in the RGS5 gene (P = 9.7 × 10) were the top hits. Effect size for each of these variants was approximately 2-3 mmHg. A five-SNP haplotype in the SELE gene also showed significant association with SBP after correction for multiple testing (P < 0.01). These findings provide additional support for the genetic role of ATP1B1, RGS5 and SELE in hypertension and blood pressure regulation.
    Journal of Hypertension 08/2011; 29(10):1906-12. DOI:10.1097/HJH.0b013e32834b000d · 4.72 Impact Factor

Publication Stats

5k Citations
499.64 Total Impact Points


  • 1986-2015
    • Howard University
      • • Department of Microbiology
      • • College of Medicine
      Вашингтон, West Virginia, United States
    • Washington Hospital Center
      Washington, Washington, D.C., United States
  • 2013
    • Inter American University of Puerto Rico
      Fajardo, Fajardo, Puerto Rico
  • 2010
    • Ulsan University Hospital
      Urusan, Ulsan, South Korea
    • University of the District of Columbia
      Washington, Washington, D.C., United States
  • 2009
    • Harvard University
      Cambridge, Massachusetts, United States
  • 2007
    • Johns Hopkins University
      • Department of Medicine
      Baltimore, MD, United States
  • 2000-2006
    • Howard University Hospital
      Washington, Washington, D.C., United States
  • 2002
    • University of Louisville
      • School of Nursing
      Louisville, Kentucky, United States
    • American University Washington D.C.
      Washington, Washington, D.C., United States