Biomedical subjects

R Duggirala

Publications and source records attributed to R Duggirala.

25 records · Page 2Linked to original sources

PubMed1996

Genetic basis of variation in carotid artery wall thickness.

BACKGROUND AND PURPOSE: Other than the documented associations of risk factors and carotid artery wall thickness, the genetic basis of variation in carotid artery intimal-medial thickness (IMT) is unknown. The purpose of this study was to examine the extent to which variation in common carotid artery (CCA) IMT and internal carotid artery (ICA) IMT are under genetic control. METHODS: The sibship data used for this analysis were part of an epidemiological survey in Mexico City. The CCA and ICA analyses were based on 46 and 44 sibships of various sizes, respectively. The CCA and ICA IMTs were measured with carotid ultrasonography. Using a robust variance decomposition method, we performed genetic analyses of CCA IMT and ICA IMT measurements with models incorporating several cardiovascular risk factors (eg, lipids, diabetes, blood pressure, and smoking) as covariates. RESULTS: After accounting for the effects of covariates, we detected high heritabilities for CCA IMT (h2 = 0.92 +/- 0.05, P = .001) and ICA IMT (h2 = 0.86 +/- 0.13, P = .029). Genes accounted for 66.0% of the total variation in CCA IMT, whereas 27.7% of variation was attributable to covariates. For ICA IMT, genes explained a high proportion (74.9%) of total phenotypic variation. The covariates accounted for 11.5% of variation in ICA IMT. CONCLUSIONS: Our results suggest that substantial proportions of phenotypic variance in CCA IMT and ICA IMT are attributable to shared genetic factors.

Cardiovascular Diseases↗

PubMed1996

Quantitative variation in obesity-related traits and insulin precursors linked to the OB gene region on human chromosome 7.

Despite the evidence that human obesity has strong genetic determinants, efforts at identifying specific genes that influence human obesity have largely been unsuccessful. Using the sibship data obtained from 32 low income Mexican American pedigrees ascertained on a type II diabetic proband and a multipoint variance-components method, we tested for linkage between various obesity-related traits plus associated metabolic traits and 15 markers on human chromosome 7. We found evidence for linkage between markers in the OB gene region and various traits, as follows: D7S514 and extremity skinfolds (LOD = 3.1), human carboxypeptidase A1 (HCPA1) and 32,33-split proinsulin level (LOD = 4.2), and HCPA1 and proinsulin level (LOD = 3.2). A putative susceptibility locus linked to the marker D7S514 explained 56% of the total phenotypic variation in extremity skinfolds. Variation at the HCPA1 locus explained 64% of phenotypic variation in proinsulin level and approximately 73% of phenotypic variation in split proinsulin concentration, respectively. Weaker evidence for linkage to several other obesity-related traits (e.g., waist circumference, body-mass index, fat mass by bioimpedance, etc.) was observed for a genetic location, which is approximately 15 cM telomeric to OB. In conclusion, our study reveals that the OB region plays a significant role in determining the phenotypic variation of both insulin precursors and obesity-related traits, at least in Mexican Americans.

Adult↗

PubMed1995

Population relationships among historical and modern indigenous Siberians based on anthropometric characters.

A comparison of anthropometric data recently collected from a modern population of Evenki and data collected from a group of Evenki at the turn of the century by the Jesup expedition (Boas 1903) reveals a pattern of significant changes over this time period. The modern Evenki exhibit larger sitting height and biacromial breadth but smaller bizygomatic and nasal breadth and a shorter face. Although the differences in the postcranial characters might be attributable to improvements in health and nutrition over time, those of the head and face might also indicate increased gene flow, perhaps from European populations. The comparative analysis of the anthropometric data was expanded to a multivariate approach by use of canonical variate analysis. This analysis was performed using data from the 10 populations sampled during the Jesup expedition along with the data from a sample of modern Evenki. In general, a pattern of relationships emerged, reflecting known population interactions and linguistic affiliations to a certain extent. However, the sample of modern Evenki differed substantially from all the other samples in the analysis. Although such a separation of the modern Evenki from this set of historical Siberian populations may be the result of a secular trend; it is also highly probable that it reflects new patterns of gene flow resulting from interactions and events associated with Russian colonial expansion and in this century the establishment of the Soviet state.

Adolescent↗

PubMed1994

Population structure of the Chenchu and other south Indian tribal groups: relationships between genetic, anthropometric, dermatoglyphic, geographic, and linguistic distances.

We describe the genetic structure and interrelationships of nine south Indian tribal groups (seven from Andhra Pradesh and two from the adjoining states of Tamil Nadu and Kerala) using seven polymorphic loci (ABO, MN, RH, PGM, ACP, PGD, and LDH). R matrix analysis indicates that the Andhra Pradesh tribes are clustered and that the Kadar and Irula are genetically isolated from them. This dispersion of populations has been explained by the combination of relatively high frequencies of the alleles RH D and MN M in the Kadar and the relatively high proportions of the allele PGM*2 in the Irula. The Mahaboobnagar Chenchu subgroup is isolated from other Telugu-speaking groups because of high frequencies of the PGM*1 and ACP*A alleles. The regression of mean per locus heterozygosity (H) on distance from the gene frequency centroid (rii) reveals considerable levels of external gene flow among the Lambadi, the Yerukula, and the two Chenchu subgroups and more homogeneity in the Kolam, Koya, Yanadi, Irula, and Kadar. Mantel statistics were used to assess the relative effects of nonbiological processes (i.e., language and geography) on the morphological and genetic patterns of these subdivided populations. The significance of correlations was determined between different data sets (genetic, dermatoglyphic, anthropometric, geographic, and linguistic) at three levels involving nine, six, and five populations. Although multiple correlation analysis reveals significant combined effects of geography and language on genetics, anthropometrics, and dermatoglyphics, highly significant partial correlations suggest strong effects of geography on both anthropometry and genetics. Our analysis indicates that geographic factors have an overwhelming effect on the genetic differentiation of the south Indian tribal groups.

Alleles↗

PubMed1993

Population genetics and structure of Buryats from the Lake Baikal Region of Siberia.

Genetic polymorphisms of blood groups, serum proteins, red cell enzymes, PTC tasting, and cerumen types are reported for five Mongoloid populations of Buryats from the Lake Baikal region of Siberia (Russia). These groups are characterized by relatively high frequencies of alleles ABO*B, RH*D, cerumen D, GC*1F, ACP1*B, ESD*2, and PGD*C. Significant genetic heterogeneity between populations was demonstrated for the loci RH, MN, cerumen, PGD, ABO, GC, GLO, TF, and PGM1. Genetic distance analyses using five loci revealed a lower level of genetic microdifferentiation within the Buryat populations compared with other native Siberian groups. The distribution of gene markers in Buryats is similar to that found in neighboring Central Asian groups, such as the Yakuts and the Mongols. Intrapopulational analyses of the five Buryat subdivisions, based on R matrix and rii, indicate that one of the subdivisions is reproductively more isolated than the others and that two of the communities have received considerable gene flow. A nonlinear relationship was demonstrated between geographic and genetic distances of Buryat population subdivisions.

Adolescent↗

PubMed1992

Digital dermatoglyphic patterns of Eskimo and Amerindian populations: relationships between geographic, dermatoglyphic, genetic, and linguistic distances.

Dermatoglyphic traits have been used to assess population affinities and structure. Here, we describe the digital patterns of four Eskimo populations from Alaska: two Yupik-speaking villages from St. Lawrence Island and two Inupik groups presently residing on mainland Alaska. For a broader evolutionary perspective, these four Eskimo populations are compared to other Inuit groups, to North American Indian populations, and to Siberian aggregates. The genetic structures of 18 New and Old World populations were explored using R-matrix plots and Wright's FST values. The relationships between dermatoglyphic, blood genetic, geographic, and linguistic distances were assessed by comparing matrices through Mantel correlations and through partial and multiple correlations. Statistically significant relationships between dermatoglyphics and genetics, genetics and geography, and geography and language were revealed. In addition, significant correlations between dermatoglyphics and geography, with linguistic variation constant, were noted for females but not for males. These results attest to the usefulness of dermatoglyphics in resolving various evolutionary questions concerning normal human variation.

Alaska↗

PubMedDate not supplied

Birth weight and the metabolic syndrome: thrifty phenotype or thrifty genotype?

BACKGROUND: Inverse correlations have been reported between birth weight and the Metabolic Syndrome (abdominal obesity, insulin resistance, hyperinsulinemia, glucose intolerance, dyslipidemia, and hypertension). These correlations are thought to reflect primarily nutritional inadequacies during fetal and early life. We explored familial influences on these correlations. METHODS: Using birth weight data on 602 subjects from 65 pedigrees, we partitioned phenotypic correlations into familial and non-familial. The former are usually regarded as reflecting primarily genetic influences, although they may also reflect environmental influences that are shared by family members, and the latter reflect random environmental influences. RESULTS: A consistent pattern of positive familial and inverse non-familial correlations were observed. The strongest familial correlations were between birth weight and fasting insulin (r = 0.58, p = 0.002), leptin (r = 0.48, p = 0.021), split proinsulin (r=0.51, p = 0.090), and heart rate (r = 0.39, p = 0.037). An inverse familial correlation was observed with HDL cholesterol (r = -0.28, p = 0.018). Non-familial correlations were weaker and only two-- subscapular-to-triceps skinfold ratio and fasting insulin--were statistically significant. CONCLUSION: Since the familial and non-familial correlations were in opposite directions, we attribute the former to the pleiotropic effects of genes. Specifically, we conclude that genes that increase birth weight also worsen the Metabolic Syndrome in adult life. Since the inverse correlations reported in the literature reflect mainly cohorts born in the early part of the 20th century, improved maternal nutrition since then may have allowed the expression of genetic influences in our participants, all of whom were born after 1950.

Adult↗