Biomedical subjects

D C Rao

Publications and source records attributed to D C Rao.

At least 127 records · Page 7Linked to original sources

PubMed2001

Tree-based recursive partitioning methods for subdividing sibpairs into relatively more homogeneous subgroups.

We propose a new splitting rule for recursively partitioning sibpair data into relatively more homogeneous subgroups. This strategy is designed to identify subgroups of sibpairs such that within-subgroup analyses result in increased power to detect linkage using Haseman-Elston regression. We assume that the subgroups can be defined by patterns of non-genetic binary covariates measured on each sibpair. The data we consider consists of the squared difference of a quantitative trait measurement on each sibpair, estimates of identity-by-descent (IBD) values at each genetic marker, and binary covariate data describing characteristics of the sibpair (e.g., race, sex, family history of disease). To test the efficacy of this method in linkage analysis, we performed two simulation experiments. In the first, we simulated a mixture consisting of 66.6% of the sibpairs with no linkage and 33.3% of the sibpairs with genetic linkage to one marker. The two groups were distinguished by the value of a single binary covariate. We also simulated one unlinked marker and one random covariate to include as noise in the data. In the second experiment, we simulated a mixture consisting of 55% of the sibpairs with no genetic linkage, 22.5% of the sibpairs with genetic linkage to one marker, and 22.5% of the sibpairs with linkage to a different marker. Each subgroup was defined by a distinct pattern of two binary covariates. We also simulated one unlinked marker and two random covariates to include as noise in the data. Our simulation studies found that we can significantly increase the overall power to detect linkage by fitting Haseman-Elston regression models to homogeneous subgroups with only a small increase in the false-positive rate. Second, the splitting rule can correctly identify important covariates and linked markers. Third, recursive partitioning of sibpair data using this splitting rule can correctly identify sibpair subgroups. These results indicate that partitioning sibpairs into homogeneous subgroups is feasible and significantly increases the power to detect linkage, thus demonstrating the practical utility and potential this new methodology holds.

Chromosome Mapping↗

PubMed2001

Genetic variation at the lipoprotein lipase locus and plasma lipoprotein and insulin levels in the Québec Family Study.

The associations between the S447X, BamHI, HindIII and PvuII DNA variants of the lipoprotein lipase (LPL) gene and indicators of body fat, fat distribution and plasma lipids and insulin were studied in the Québec Family Study cohort. Strong linkage disequilibrium among all the markers was observed. For the S447X polymorphism, plasma very low density lipoprotein (VLDL)-cholesterol (chol) (P<0.001), total triglyceride (TG) (P=0.033) and VLDL-TG (P<0.001) levels were lower and high density lipoprotein (HDL)-chol level higher (P<0.001) in the subjects homozygous or heterozygous for X447 (X447+, n=160) compared to the homozygotes for the S447 allele (X447-, n=576). The BamHI, PvuII and HindIII polymorphisms were not associated with the plasma lipid values when all X447 allele carriers were removed. In addition, the HindIII polymorphism as well as the HindIII and S447X markers combination influenced the insulin area under the curve during an oral glucose tolerance test. We conclude that DNA sequence variation in the LPL gene contributes significantly to the variability in the levels of VLDL-chol, total- and VLDL-TG as well as HDL-chol. The effects of the other polymorphisms considered here are most likely mediated by their linkage disequilibrium with the S447X mutation. In addition, genetic variation at the LPL locus may, by an unknown mechanism, influence insulin metabolism but not body fat variability.

Adult↗

PubMed2001

Race differences in the response of postheparin plasma lipoprotein lipase and hepatic lipase activities to endurance exercise training in men: results from the HERITAGE Family Study.

Endurance exercise training is known to produce favorable changes in the metabolic profile including reduced plasma triglyceride (TG) and increased high-density lipoprotein (HDL) cholesterol concentrations. These metabolic improvements are likely to contribute to the reduced coronary heart disease (CHD) risk often observed in physically active individuals. However, the physiological mechanisms responsible for such improvements in TG and HDL cholesterol concentrations with endurance exercise are not fully understood. The effect of a 20-week endurance exercise training program on plasma lipoproteins as well as on post-heparin plasma lipoprotein lipase (PH-LPL) and hepatic lipase (PH-HL) activities were therefore examined in a sample of 200 White and 69 Black men who were part of the HERITAGE Family Study. As expected, there were decreases in adiposity and in abdominal fat accumulation following training in both White and Black men. We also found that exercise training was associated with decreases in plasma cholesterol, TG and apolipoprotein B levels, as well as with an increase in HDL cholesterol concentrations in White men. In contrast, Black men showed an increase only in HDL(2) cholesterol over the 20-week period. Higher PH-LPL and lower PH-HL activities were noted in both ethnic groups at follow-up. Whereas in White men improvement of the lipoprotein-lipid profile was related to increased PH-LPL activity, no association between PH-LPL (or PH-HL) and lipoprotein-lipid variables was observed in Black men. Results of the present study suggest that in Whites, the increase in PH-LPL activity in response to endurance exercise training is associated with a better lipoprotein-lipid profile, therefore reducing CHD risk. However, the generally better metabolic profile of Black individuals may minimize further improvement of lipoprotein-lipid concentrations by exercise training.

Adipose Tissue↗

PubMed2001

Genetic dissection of complex traits: an overview.

Genetic dissection of even simple Mendelian traits has been sufficiently challenging. Complex traits are proving to be much more challenging and frustrating than previously thought. The concepts, methods, and strategies discussed in this volume emphasize the critical importance of study design, appropriate methods of analysis, including relatively newer and emerging methods, and issues relating to the interpretation of results from genome scans; some thoughts on the future the new millennium holds are offered, as well. This chapter overviews the key steps involved in the study of complex traits, which are discussed in detail in subsequent chapters. It is suggested that a combination of lumping and splitting strategies is more appropriate for the analysis of complex traits, and large-scale collaborations should make this possible. For example, by pooling data and/or results from multiple studies on a given disease/trait, one may attain a sample size large enough to permit the division of the data into multiple relatively more homogeneous subgroups. The sample size of the subgroups may still be sufficiently large sample, but the genetic dissection within each subgroup should be much less daunting. The expectation is that analyses within subgroups will enhance gene finding, especially when any interacting determinants are taken into account at the time of dividing the data into subgroups. Perhaps the methods are not yet optimum, but the future holds much promise. In the meantime, the cutting-edge methods discussed in this volume by leading experts should help. There is an increasing healthy tendency for investigators to collaborate by pooling materials and results across studies, with the goal of increasing the sample size and thus the power. We believe that such efforts are essential for the genetic dissection of complex traits and should contribute to greater success, especially if there is a real commitment to meaningful collaboration. After all, for most complex traits, the question is not whether there are genes, only when and how they might be found.

Genetic Variation↗

PubMed2001

Meta-analysis for model-free methods.

The intricate nature of complex genetic traits dictates that novel methodologies be developed and utilized to achieve better power, better accuracy, and more favorable balance between type I and type II errors than could be achieved by the traditional methods as they are used in mapping Mendelian traits. Meta-analysis provides one such method for synthesizing information from multiple studies. This has the advantage of being able to pool relatively weak signals from individual studies into a collectively stronger evidence of genetic effects, while at the same time providing a quantitative framework for modeling variability among studies. The traditional lod score measures significance level of a linkage effect in an individual study, and its additive property make it a natural candidate for combining results across independent studies. To incorporate the within-study variation of the linkage effect into the pooled overall measure of genetic effect, the effect sizes (such as the proportion of genes shared identical-by-descent, IBD) should be pooled directly across studies. Traditional regression models and mixed effects models can be used to estimate the overall genetic effect size and its variance, and to test heterogeneity among studies. Our simulation studies show that designing studies with moderate power and pooling their results via meta-analysis may be more cost-effective than large dedicated studies. We believe that, as a newly emerging methodology, the meta-analysis approach has the potential to become an integral part of our toolbox that will expedite the search for complex human disease genes.

Alleles↗

PubMed2001

Classification methods for confronting heterogeneity.

Recursive partitioning/tree models are discussed as a method of dissecting the complex nature of traits with different causal mechanisms operating in different subsets of the data (e.g., different genes operating in different subsets of families). In addition to the straightforward application of classification and regression trees to define more homogeneous subsets of the data on which to conduct further analysis, developments incorporating linkage analysis into the definition of the regression trees (Shannon et al., 2000) are discussed. The pros and cons of recursive partitioning vs. the related approach of context-dependent analysis (Turner et al., 1999) are also reviewed as two promising analysis strategies that may be useful for genetic dissection of complex traits.

Genetic Diseases, Inborn↗

PubMed2001

Optimum study designs.

Because simplistic designs will lead to prohibitively large sample sizes, the optimization of genetic study designs is critical for successfully mapping genes for complex diseases. Creative designs are necessary for detecting and amplifying the usually weak signals for complex traits. Two important outcomes of a study design--power and resolution--are implicitly tied together by the principle of uncertainty. Overemphasis on either one may lead to suboptimal designs. To achieve optimality for a particular study, therefore, practical measures such as cost-effectiveness must be used to strike a balance between power and resolution. In this light, the myriad of factors involved in study design can be checked for their effects on the ultimate outcomes, and the popular existing designs can be sorted into building blocks that may be useful for particular situations. It is hoped that imaginative construction of novel designs using such building blocks will lead to enhanced efficiency in finding genes for complex human traits.

Case-Control Studies↗

PubMed2001

False positives and false negatives in genome scans.

It is emphasized that two types of errors are made in the testing of a hypothesis, false positive (type I) and false negative (type II). Genome-wide scans involving many markers give rise to the problem of multiple testing, which results in an increased number of false positives, thus necessitating a correction in the nominal significance level. While the literature has concentrated reasonably heavily on controlling false positives in genomic scans, the need to control false negatives has been largely neglected. This chapter highlights this need and attempts to strike a balance between the two error types. The need to develop alternative methods for discriminating between false positives and true positives is also stressed.

Chromosome Mapping↗

PubMed2001

Sibling correlation of left ventricular mass and geometry in hypertensive African Americans and whites: the HyperGEN study. Hypertension Genetic Epidemiology Network.

BACKGROUND: Evidence suggests that left ventricular (LV) mass is under genetic control, independently of risk factors known to influence LV size and geometry. METHODS: As part of the HyperGEN study, four field centers recruited African American and white hypertensive siblings (n = 1,664), aged 23 to 87 years. Two-dimensionally guided M-mode echocardiography was performed, and LV mass and relative wall thickness (RWT) were measured at a central reading center. Familial correlations were calculated separately for each ethnic group using maximum likelihood methods, adjusted for the potential confounding influences of age, gender, systolic blood pressure, and obesity. RESULTS: In African Americans, brother-sister, brother-brother, and sister-sister correlation coefficients and standard errors for LV mass were 0.29 (0.08), 0.44 (0.10), and 0.33 (0.05). In whites, the corresponding correlations were lower than in African Americans at 0.05 (0.08), 0.12 (0.11), and 0.22 (0.09), respectively. Sibling correlation of LV geometry, assessed by RWT, was less in African Americans than in whites: brother-sister, 0.04 (0.10) v 0.21 (0.10), brother-brother, 0.12 (0.22) v 0.28 (0.09), and sister-sister, 0.11 (0.07) v 0.19 (0.11). CONCLUSIONS: LV mass is strongly correlated in hypertensive African American siblings, and modestly correlated in their white counterparts, whereas RWT has stronger sibling correlation in whites. The patterns of familial correlation of echocardiographic LV mass and RWT suggest that the genetic underpinnings of LV hypertrophy and geometric remodeling may differ among ethnic groups.

Adult↗

PubMed2001

Familial aggregation of QT-interval variability in a general population: results from the NHLBI Family Heart Study.

QT-interval prolongation is associated with increased risk of cardiac death. Although information on genetics and molecular mechanisms of the congenital long QT syndrome is mounting, limited data are available on the genetics of QT interval in the general population. Heart rate adjusted QT intervals (Bazett's QTc, and QT index (QTI)) were assessed by electrocardiography in 2399 members aged 25-91 years of 468 randomly selected families participating in the NHLBI Family Heart Study. Familial correlation and segregation analyses were performed to evaluate the genetics of the variability of QT interval in this population. The parent-offspring (0.14+/-0.03) and sibling (0.18+/-0.03) correlations for age and sex-adjusted QTc were moderate, while the spouse correlation was close to zero (0.09+/-0.06). This suggests that there are familial/genetic influences on QT-interval variability. Segregation analysis results suggest that there is a major effect in addition to heritable multifactorial effects (h2=0.34), but the major effect did not follow Mendelian inheritance. Further adjustments of QTc for other major cardiovascular risk factors did not significantly change the results. Similar results were found for QTI. The QT-interval variation in the general population is influenced by moderate heritable multifactorial effects in addition to a major effect. A major gene effect is not directly supported.

Adult↗

PubMed2001

Familial resemblance for glucose and insulin metabolism indices derived from an intravenous glucose tolerance test in Blacks and Whites of the HERITAGE Family Study.

Type 2 diabetes mellitus (T2DM), characterized by hyperglycemia, is a complex disease primarily caused by impairment in insulin sensitivity (SI) and insulin secretion. While a strong genetic component for T2DM is well established, there are few reports on racial differences in the magnitude of the genetic effects of T2DM and indices of glucose and insulin metabolism. We report here on the familial resemblance for traits related to glucose metabolism at pre-exercise training levels in 492 members from 99 sedentary White families and 259 members from 108 Black families participating in the multicenter HERITAGE Family Study. All these traits were obtained from the frequently sampled intravenous glucose tolerance test (IVGTT). They include glucose disappearance index (Kg), an overall index for glucose tolerance, acute insulin response to glucose (AIR(Glucose)) which is an index for insulin secretion, and those derived from the minimal model including SI and the disposition index (DI). DI, derived as the product of SI and AIR(Glucose), is a measure of the activity of the B-cells adjusted for insulin resistance. After adjustment for age, sex, and body mass index, the maximal heritability estimates in Blacks (Whites) are 48+/-14% (25+/-8%) for Kg, 44+/-14% (46+/-8%) for AIR(Glucose), 38+/-12% (44+/-8%) for SI and 32+/-14% (24+/-8%) for DI. Interestingly, Blacks have higher heritability for overall glucose tolerance than Whites but there is no race difference in heritability estimates for insulin sensitivity or insulin secretion.

Adult↗

PubMed2001

The Trp64Arg polymorphism of the beta3-adrenergic receptor gene is not associated with training-induced changes in body composition: The HERITAGE Family Study.

OBJECTIVE: To investigate the association between the Trp64Arg polymorphism of the beta3-adrenergic receptor gene and changes in body composition in response to endurance training. RESEARCH METHODS AND PROCEDURES: Adult sedentary white and black subjects participating in the HERITAGE Family Study were measured before and after 20 weeks on endurance training for the body mass index, fat mass, percentage of body fat, fat-free mass, sum of eight skinfolds, and subcutaneous, visceral, and total abdominal fat areas. The association between the Trp64Arg polymorphism and the response phenotypes, computed as the difference between pre- and post-training values, was tested by analysis of covariance separately in men and women. The gene by race interaction term was also tested. RESULTS: No race differences were observed for allelic and genotype frequencies. Training resulted in significant reduction of body fat in both men and women. No association of the Trp64Arg polymorphism was observed with training-induced changes for any of the body composition phenotypes in both men and women. DISCUSSION: These results suggest that the Trp64Arg polymorphism of the beta3-adrenergic receptor gene is not related to changes in body composition in response to exercise training.

Adipose Tissue↗

PubMed2001

Stability of adiposity phenotypes from childhood and adolescence into young adulthood with contribution of parental measures.

OBJECTIVE: The stability of several indicators of body composition and adipose tissue distribution over 12 years was quantified. RESEARCH METHODS AND PROCEDURES: The participants were 77 boys and 76 girls who were evaluated along with their parents at baseline as children and adolescents (8 to 18 years of age) and remeasured as young adults 12 years later. Indicators of body composition included the body mass index, fat mass, fat free mass, percentage of body fat, sum of six skinfolds (SF6), and the first principal component of six age-adjusted skinfold residuals. Relative adipose tissue distribution was represented by the second principal component of skinfold residuals and a trunk-to-extremity skinfold ratio, adjusted for SF6. RESULTS: Partial interage correlations, controlling for initial age and length of follow-up, were 0.65 and 0.59 for the body mass index, 0.59 and 0.64 for fat mass, 0.65 and 0.57 for fat free mass, 0.50 and 0.57 for percentage of body fat, 0.66 and 0.44 for SF6, 0.64 and 0.42 for the first principal component of six age-adjusted skinfold residuals, 0.19 and 0.31 for the second principal component of skinfold residuals, and 0.41 and 0.47 for trunk-to-extremity skinfold ratio, adjusted for SF6, in men and women, respectively. Multiple regression analyses indicated that the significant partial R(2) values of parental measurements on the prediction of their offspring in young adulthood ranged from 2% to 9%. DISCUSSION: The results indicate moderately high stability of indicators of body composition and somewhat lower stability of measures of adipose tissue distribution. Overall, parental measures offer less predictive value than do measures of childhood and adolescent body composition and adipose tissue distribution.

Adipose Tissue↗

PubMed2001

Interactions among the glucocorticoid receptor, lipoprotein lipase, and adrenergic receptor genes and plasma insulin and lipid levels in the Quebec Family Study.

The aim of the study was to investigate the possible interactions among the glucocorticoid receptor (GRL), lipoprotein lipase (LPL), and adrenergic receptor (ADR) genes on plasma insulin and lipid levels. The study was cross-sectional and based on 742 individuals from phase 2 of the Quebec Family Study (QFS) cohort. Gene markers were identified by Southern blot analysis or polymerase chain reaction (PCR). Plasma glucose and insulin in the fasted state and during an oral glucose tolerance test (OGTT) were determined and insulin and glucose areas were computed. Triglyceride (TG) and cholesterol concentrations in plasma and lipoprotein fractions were determined enzymatically. The results show that GRL and LPL variants had independent effects on plasma high-density lipoprotein cholesterol (HDL-C) and two beta2-ADR variants were related to total cholesterol concentrations. The alpha2-ADR gene Dral polymorphism was the only variant that had an independent effect on the plasma insulin area. Gene-gene interaction effects were found between GRL and alpha2-ADR genes for low-density lipoprotein cholesterol ([LDL-C] P = .013) and between GRL and LPL genes for HDL-C (P = .045). Higher-order interaction effects involving GRL, LPL, and ADR markers were observed for the plasma insulin area (P = .001 to .025) but not the glucose area. After correction for multiple tests, the findings remained essentially unchanged for the insulin area but became nonsignificant for the lipid phenotypes. In conclusion, multiple interactions among GRL, LPL, and ADR gene markers contribute to insulin metabolism and perhaps to lipid levels, while no significant effect is found for each gene separately. The LPL locus appears to determine the pattern of interactions with ADR and GRL loci. These results suggest that gene-gene interaction effects could play a role in the etiology of risk factors for common chronic diseases.

Area Under Curve↗

PubMed2001

Changes in blood lipids consequent to aerobic exercise training related to changes in body fatness and aerobic fitness.

The contribution of changes in body fatness and aerobic fitness to changes in blood lipids after aerobic exercise training was investigated. The sample included 295 men (77 black, 218 white) and 355 women (131 black, 224 white), aged 17 to 65 years, from the HERITAGE Family Study. Participants underwent measurements at baseline and after 20 weeks of supervised exercise training on a cycle ergometer. Body fat mass (FM, in kilograms) was determined by underwater weighing, and aerobic fitness (maximal oxygen uptake, VO(2max), in milliliters per minute) was assessed by cycle ergometry. Blood lipid measurements included fasting plasma levels of high-density lipoprotein cholesterol (HDL-C), HDL(2)-C, HDL(3)-C, low-density lipoprotein cholesterol (LDL-C), total cholesterol (CHOL), CHOL/HDL, and triglycerides (TG). A composite lipid change index (LCI) was derived by subjecting the Delta scores for the individual blood lipids to principal components analysis. The exercise training was accompanied by a mean increase of 17.5% in VO(2max) and a mean decrease of 3.3% in FM. Partial correlations, controlled for age, between absolute changes in VO(2max) and changes in the blood lipids were consistently low and nonsignificant. On the other hand, absolute changes in FM were significantly (P <.05) associated with changes in HDL-C (r = -.23), HDL(2)-C (r = -.17), and CHOL/HDL (r =.24) and the LCI (r = -.27) in men and with changes in LDL-C (r =.22), CHOL (r =.19), and CHOL/HDL (r =.15) and the LCI (r = -.19) in women. Forward stepwise regression confirmed that the change in FM was a better predictor of changes in blood lipids than the change in VO(2max), entering as a predictor in 4 of 8 regressions in both men and women. Change in VO(2max) did not enter as a significant predictor in any regression. Further, there were no differences in LCI between the upper and lower quartiles of VO(2max) change. On the other hand, there were significant differences between the low and high quartiles of FM change. No race effects were observed in any of the relationships, except that race was a significant predictor of changes in TG in both men and women. In conclusion, changes in blood lipids associated with aerobic exercise training do not appear to be related to changes in aerobic fitness per se; rather, they are weakly to moderately associated with changes in body fatness.

Adipose Tissue↗

PubMed2001

Race differences in the pattern of familial aggregation for dehydroepiandrosterone sulfate and its responsiveness to training in the HERITAGE Family Study.

Using a familial correlation model to assess familial influences, baseline dehydroepiandrosterone sulfate (DHEAS) and its change (post-training minus baseline) in response to a 20-week endurance exercise training program were analyzed in 85 black families who participated in the HERITAGE Family Study (HERITAGE). Baseline levels were adjusted for a polynomial in age, and the training response was adjusted for a polynomial in age, as well as the baseline values, within 4 sex-by-generation groups before genetic analysis. We found that the maximal heritability for baseline DHEAS reached 66% (with no sex and generation differences) in black families, which is slightly (but not significantly) higher than the estimate (58%) reported previously in 99 white families in HERITAGE. Whereas weak, but significant, familial effects (26%) for the training response were previously reported for whites in HERITAGE, they were undetectable in the present study. Furthermore, we found heterogeneity in the pattern of familial aggregation (primarily due to different spouse and parent-offspring correlations) for both the baseline and its training response between blacks and whites. In conclusion, baseline DHEAS levels in blacks were also determined by substantial familial factors (just as for whites), independent of the effects of age and sex. Genetic and nongenetic familial components influencing baseline DHEAS levels in both races may be different.

Adolescent↗

PubMed2001

Relationship of changes in maximal and submaximal aerobic fitness to changes in cardiovascular disease and non-insulin-dependent diabetes mellitus risk factors with endurance training: the HERITAGE Family Study.

The purpose of this study was to determine the relationship between changes in maximal oxygen uptake (VO2 max) and submaximal markers of aerobic fitness and changes in risk factors for cardiovascular disease (CVD) and non-insulin-dependent diabetes mellitus (NIDDM) consequent to a 20-week endurance training program. The 502 participants in this study were healthy and previously sedentary men (n = 250) and women (n = 252) of varying age (17 to 65 years) and race (blacks n = 142; whites n = 360) who had completed the HERITAGE Family Study testing and training protocol. Following baseline measurements, participants trained on cycle ergometers 3 days/week for a total of 60 exercise sessions starting at the heart rate (HR) associated with 55% of VO2 max for 30 minutes/session. This was progressively increased to the HR associated with 75% of VO2 max for 50 minutes/session, which was maintained during the last 6 weeks. VO2 max, heart rate at 50 W, power output at 60% of VO2 max, lipids and lipoproteins, resting blood pressure, body composition including abdominal fat (computed tomography [CT] scan), and blood glucose and insulin at rest and at peak following an intravenous glucose tolerance test (IVGTT) were determined both before and after training. Following training, there were significant increases in VO2 max (16%) and the power output at 60% of VO2 max and a significant decrease in HR at 50 W. These changes in markers of aerobic fitness were significantly correlated only to the changes in the body composition variables and the lipids and lipoproteins. Further, there was considerable individual variation in response for all variables studied. Finally, when risk factor data were analyzed by quartile of change in VO2 max, there were few significant relationships. It is concluded that there is a significant relationship between changes in markers of aerobic fitness and changes in several risk factors for CVD and NIDDM. However, the magnitude of these relationships is small.

Adolescent↗

PubMed2001

Genome-wide linkage scan to detect loci influencing levels of dehydroepiandrosterones in the HERITAGE Family Study.

A genome-wide linkage scan was performed to identify genomic regions that influence levels of dehydroepiandrosterone (DHEA), DHEA sulfate (DHEAS), and DHEA fatty acid esters (DHEA-FA) at baseline and in response to 20 weeks of endurance exercise training in sedentary white and black participants in the HERITAGE Family Study. The baseline levels were log-transformed and adjusted for the effects of age and sex prior to genetic analysis. The training responses were adjusted for the effects of age, sex, and the baseline values. A total of 509 autosomal component polymorphic markers were used for the genome scan with an average spacing of 6.0 Mb. Multipoint variance components linkage analyses were performed in nuclear families containing 360 white and 106 black sibling pairs. We found 5 genomic regions with significant linkages for baseline DHEA-FA in whites, with log odd (LOD) scores over 3.6 (P < 2 x 10(-5)). They include (1) D1S468 (LOD 4.56, 2.533 Mb, 1p36.22); (2) D2S177 (LOD 5.65, 52.663 Mb, 2p16.3); (3) D4S2397 (LOD 3.98, 32.246 Mb, 4p15.2); (4) the paraoxonase loci (LOD 3.93 approximately 3.99, 101.544 approximately 102.933 Mb, 7q21.3), and D7S821 (LOD 3.88, 104.497 Mb, 7q22.1); and (5) D12S372 (LOD 4.66, 2.129 Mb, 12q13.33). In addition, we obtained evidence of suggestive linkages (2.2 < LOD < 3.6; 2 x 10(-5) < P < 7 x 10(-4)) on chromosomes 3p, 6q, and 8q for baseline DHEAS; on chromosomes 2q, 3p, 9q, 10p, 16q, and 17p for baseline DHEA-FA in whites; and on chromosomes 9q and 11p for baseline DHEA in blacks. This is the first genome-wide linkage scan searching for genomic regions influencing human DHEA levels. Several potential candidate genes are located in these genomic regions, which warrant further studies in HERITAGE and other cohorts.

Adult↗