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Ranjan Deka

Bio: Ranjan Deka is an academic researcher from University of Cincinnati. The author has contributed to research in topics: Population & Allele. The author has an hindex of 52, co-authored 178 publications receiving 9856 citations. Previous affiliations of Ranjan Deka include University of Texas Health Science Center at Houston & Boston Children's Hospital.


Papers
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Journal ArticleDOI
TL;DR: Significant nonrandom association between two markers located 22 cM apart (FY-null and AT3) is detected, most likely due to admixture linkage disequilibrium created in the interbreeding of the two parental populations, emphasize the importance of admixed populations as a useful resource for mapping traits with different prevalence in two parental population.
Abstract: We analyzed the European genetic contribution to 10 populations of African descent in the United States (Maywood, Illinois; Detroit; New York; Philadelphia; Pittsburgh; Baltimore; Charleston, South Carolina; New Orleans; and Houston) and in Jamaica, using nine autosomal DNA markers. These markers either are population-specific or show frequency differences >45% between the parental populations and are thus especially informative for admixture. European genetic ancestry ranged from 6.8% (Jamaica) to 22.5% (New Orleans). The unique utility of these markers is reflected in the low variance associated with these admixture estimates (SEM 1.3%-2.7%). We also estimated the male and female European contribution to African Americans, on the basis of informative mtDNA (haplogroups H and L) and Y Alu polymorphic markers. Results indicate a sex-biased gene flow from Europeans, the male contribution being substantially greater than the female contribution. mtDNA haplogroups analysis shows no evidence of a significant maternal Amerindian contribution to any of the 10 populations. We detected significant nonrandom association between two markers located 22 cM apart (FY-null and AT3), most likely due to admixture linkage disequilibrium created in the interbreeding of the two parental populations. The strength of this association and the substantial genetic distance between FY and AT3 emphasize the importance of admixed populations as a useful resource for mapping traits with different prevalence in two parental populations.

769 citations

Journal ArticleDOI
TL;DR: Applying ANOVA to the distributions of the allele sizes at microsatellite loci from a set of populations, grouped by repeat motif types, provides an estimate of motif-type-specific mutation rates up to a multiplicative constant, indicating that the earlier suggestion of higher mutation rates of tetranucleotides in comparison with the din nucleotides may stem from a nonrandom sampling of tetanucleotide loci in direct mutation assays.
Abstract: Using the generalized stepwise mutation model, we propose a method of estimating the relative mutation rates of microsatellite loci, grouped by the repeat motif. Applying ANOVA to the distributions of the allele sizes at microsatellite loci from a set of populations, grouped by repeat motif types, we estimated the effect of population size differences and mutation rate differences among loci. This provides an estimate of motif-type-specific mutation rates up to a multiplicative constant. Applications to four different sets of di-, tri-, and tetranucleotide loci from a number of human populations reveal that, on average, the non-disease-causing microsatellite loci have mutation rates inversely related to their motif sizes. The dinucleotides appear to have mutation rates 1.5–2 times higher than the tetranucleotides, and the non-disease-causing trinucleotides have mutation rates intermediate between the di- and tetranucleotides. In contrast, the disease-causing trinucleotides have mutation rates 3.9–6.9 times larger than the tetranucleotides. Comparison of these estimates with the direct observations of mutation rates at microsatellites indicates that the earlier suggestion of higher mutation rates of tetranucleotides in comparison with the dinucleotides may stem from a nonrandom sampling of tetranucleotide loci in direct mutation assays.

427 citations

Journal ArticleDOI
01 May 2002-Stroke
TL;DR: In this paper, the authors report a preplanned, midpoint analysis of the first population-based, case-control study that examines both genetic and environmental risk factors of ICH.
Abstract: Background and Purpose— Intracerebral hemorrhage (ICH) has a 30-day mortality rate of 40% to 50% and lacks a proven treatment. We report a preplanned, midpoint analysis of the first population-based, case-control study that examines both genetic and environmental risk factors of ICH. Methods— We prospectively identified cases of hemorrhagic stroke at all 16 hospitals in the Greater Cincinnati/Northern Kentucky region. All cases underwent medical record and neuroimaging review. Cases enrolled in the direct interview and genetic sampling arm of the study were matched to population-based control subjects by age, race, and sex. Multivariable logistic regression was performed to identify significant independent risk factors. Results— We enrolled 188 cases of ICH (67 lobar, 121 nonlobar) and 366 control subjects in the direct interview arm of the study. Significant independent risk factors for lobar ICH included the presence of an apolipoprotein E2 or E4 allele, frequent alcohol use, prior stroke, and first-deg...

410 citations

Journal ArticleDOI
TL;DR: This pattern indicates that the first settlement of modern humans in eastern Asia occurred in mainland Southeast Asia during the last Ice Age, coinciding with the absence of human fossils in easternAsia, 50,000-100,000 years ago.
Abstract: Summary The timing and nature of the arrival and the subsequent expansion of modern humans into eastern Asia remains controversial. Using Y-chromosome biallelic markers, we investigated the ancient human-migration patterns in eastern Asia. Our data indicate that southern populations in eastern Asia are much more polymorphic than northern populations, which have only a subset of the southern haplotypes. This pattern indicates that the first settlement of modern humans in eastern Asia occurred in mainland Southeast Asia during the last Ice Age, coinciding with the absence of human fossils in eastern Asia, 50,000–100,000 years ago. After the initial peopling, a great northward migration extended into northern China and Siberia.

404 citations

Journal Article
TL;DR: Through a search of the literature and of unpublished data on allele frequencies, a panel of population-specific genetic markers are identified that enable robust ethnic-affiliation estimation for major U.S. resident populations and it is demonstrated that this panel of markers provides significant statistical power for ethnic-Affiliation estimation.
Abstract: During the past 10 years, DNA analysis has revolutionized the determination of identity in a forensic context Statements about the biological identity of two human DNA samples now can be made with complete confidence Although DNA markers are very powerful for distinguishing among individuals, most offer little power to distinguish ethnicity or to support any statement about the physical characteristics of an individual Through a search of the literature and of unpublished data on allele frequencies we have identified a panel of population-specific genetic markers that enable robust ethnic-affiliation estimation for major US resident populations In this report, we identify these loci and present their levels of allele-frequency differential between ethnically defined samples, and we demonstrate, using log-likelihood analysis, that this panel of markers provides significant statistical power for ethnic-affiliation estimation In addition to their use in forensic ethnic-affiliation estimation, population-specific genetic markers are very useful in both population- and individual-level admixture estimation and in mapping genes by use of the linkage disequilibrium created when populations hybridize

387 citations


Cited by
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Journal ArticleDOI
01 Jun 2000-Genetics
TL;DR: Pritch et al. as discussed by the authors proposed a model-based clustering method for using multilocus genotype data to infer population structure and assign individuals to populations, which can be applied to most of the commonly used genetic markers, provided that they are not closely linked.
Abstract: We describe a model-based clustering method for using multilocus genotype data to infer population structure and assign individuals to populations. We assume a model in which there are K populations (where K may be unknown), each of which is characterized by a set of allele frequencies at each locus. Individuals in the sample are assigned (probabilistically) to populations, or jointly to two or more populations if their genotypes indicate that they are admixed. Our model does not assume a particular mutation process, and it can be applied to most of the commonly used genetic markers, provided that they are not closely linked. Applications of our method include demonstrating the presence of population structure, assigning individuals to populations, studying hybrid zones, and identifying migrants and admixed individuals. We show that the method can produce highly accurate assignments using modest numbers of loci— e.g. , seven microsatellite loci in an example using genotype data from an endangered bird species. The software used for this article is available from http://www.stats.ox.ac.uk/~pritch/home.html.

27,454 citations

Journal Article
Fumio Tajima1
30 Oct 1989-Genomics
TL;DR: It is suggested that the natural selection against large insertion/deletion is so weak that a large amount of variation is maintained in a population.

11,521 citations

01 Jan 2014
TL;DR: These standards of care are intended to provide clinicians, patients, researchers, payors, and other interested individuals with the components of diabetes care, treatment goals, and tools to evaluate the quality of care.
Abstract: XI. STRATEGIES FOR IMPROVING DIABETES CARE D iabetes is a chronic illness that requires continuing medical care and patient self-management education to prevent acute complications and to reduce the risk of long-term complications. Diabetes care is complex and requires that many issues, beyond glycemic control, be addressed. A large body of evidence exists that supports a range of interventions to improve diabetes outcomes. These standards of care are intended to provide clinicians, patients, researchers, payors, and other interested individuals with the components of diabetes care, treatment goals, and tools to evaluate the quality of care. While individual preferences, comorbidities, and other patient factors may require modification of goals, targets that are desirable for most patients with diabetes are provided. These standards are not intended to preclude more extensive evaluation and management of the patient by other specialists as needed. For more detailed information, refer to Bode (Ed.): Medical Management of Type 1 Diabetes (1), Burant (Ed): Medical Management of Type 2 Diabetes (2), and Klingensmith (Ed): Intensive Diabetes Management (3). The recommendations included are diagnostic and therapeutic actions that are known or believed to favorably affect health outcomes of patients with diabetes. A grading system (Table 1), developed by the American Diabetes Association (ADA) and modeled after existing methods, was utilized to clarify and codify the evidence that forms the basis for the recommendations. The level of evidence that supports each recommendation is listed after each recommendation using the letters A, B, C, or E.

9,618 citations

Journal ArticleDOI
01 Aug 2003-Genetics
TL;DR: Extensions to the method of Pritchard et al. for inferring population structure from multilocus genotype data are described and methods that allow for linkage between loci are developed, which allows identification of subtle population subdivisions that were not detectable using the existing method.
Abstract: We describe extensions to the method of Pritchard et al. for inferring population structure from multilocus genotype data. Most importantly, we develop methods that allow for linkage between loci. The new model accounts for the correlations between linked loci that arise in admixed populations (“admixture linkage disequilibium”). This modification has several advantages, allowing (1) detection of admixture events farther back into the past, (2) inference of the population of origin of chromosomal regions, and (3) more accurate estimates of statistical uncertainty when linked loci are used. It is also of potential use for admixture mapping. In addition, we describe a new prior model for the allele frequencies within each population, which allows identification of subtle population subdivisions that were not detectable using the existing method. We present results applying the new methods to study admixture in African-Americans, recombination in Helicobacter pylori , and drift in populations of Drosophila melanogaster . The methods are implemented in a program, structure , version 2.0, which is available at http://pritch.bsd.uchicago.edu.

7,615 citations

Journal ArticleDOI
TL;DR: WRITING GROUP MEMBERS Emelia J. Benjamin, MD, SCM, FAHA Michael J. Reeves, PhD Matthew Ritchey, PT, DPT, OCS, MPH Carlos J. Jiménez, ScD, SM Lori Chaffin Jordan,MD, PhD Suzanne E. Judd, PhD
Abstract: WRITING GROUP MEMBERS Emelia J. Benjamin, MD, SCM, FAHA Michael J. Blaha, MD, MPH Stephanie E. Chiuve, ScD Mary Cushman, MD, MSc, FAHA Sandeep R. Das, MD, MPH, FAHA Rajat Deo, MD, MTR Sarah D. de Ferranti, MD, MPH James Floyd, MD, MS Myriam Fornage, PhD, FAHA Cathleen Gillespie, MS Carmen R. Isasi, MD, PhD, FAHA Monik C. Jiménez, ScD, SM Lori Chaffin Jordan, MD, PhD Suzanne E. Judd, PhD Daniel Lackland, DrPH, FAHA Judith H. Lichtman, PhD, MPH, FAHA Lynda Lisabeth, PhD, MPH, FAHA Simin Liu, MD, ScD, FAHA Chris T. Longenecker, MD Rachel H. Mackey, PhD, MPH, FAHA Kunihiro Matsushita, MD, PhD, FAHA Dariush Mozaffarian, MD, DrPH, FAHA Michael E. Mussolino, PhD, FAHA Khurram Nasir, MD, MPH, FAHA Robert W. Neumar, MD, PhD, FAHA Latha Palaniappan, MD, MS, FAHA Dilip K. Pandey, MBBS, MS, PhD, FAHA Ravi R. Thiagarajan, MD, MPH Mathew J. Reeves, PhD Matthew Ritchey, PT, DPT, OCS, MPH Carlos J. Rodriguez, MD, MPH, FAHA Gregory A. Roth, MD, MPH Wayne D. Rosamond, PhD, FAHA Comilla Sasson, MD, PhD, FAHA Amytis Towfighi, MD Connie W. Tsao, MD, MPH Melanie B. Turner, MPH Salim S. Virani, MD, PhD, FAHA Jenifer H. Voeks, PhD Joshua Z. Willey, MD, MS John T. Wilkins, MD Jason HY. Wu, MSc, PhD, FAHA Heather M. Alger, PhD Sally S. Wong, PhD, RD, CDN, FAHA Paul Muntner, PhD, MHSc On behalf of the American Heart Association Statistics Committee and Stroke Statistics Subcommittee Heart Disease and Stroke Statistics—2017 Update

7,190 citations