Evidence for Three Novel QTLs for Adiposity on Chromosome 2 With Epistatic Interactions: The NHLBI Family Heart Study

We sought to identify quantitative trait loci (QTLs) by genome‐wide linkage analysis for BMI and waist circumference (WC) exploring various strategies to address heterogeneity including covariate adjustments and complex models based on epistatic components of variance. Because cholesterol‐lowering drugs and diabetes medications may affect adiposity and risk of coronary heart disease, we excluded subjects medicated for hypercholesterolemia and hyperglycemia. The evidence of linkage increased on 2p25 (BMI: lod = 1.59 vs. 2.43, WC: lod = 1.32 vs. 2.26). Because environmental and/or genetic components could mask the effect of a specific locus, we investigated further whether a QTL could influence adiposity independently of lipid pathway and dietary habits. Strong evidence of linkage on 2p25 (BMI: lod = 4.31; WC: lod = 4.23) was found using Willet's dietary factors and lipid profile together with age and sex in adjustment. It suggests that lipid profile and dietary habits are confounding factors for detecting a 2p25 QTL for adiposity. Because evidence of linkage has been previously detected for BMI on 7q34 and 13q14 in National Heart, Lung, and Blood Institute Family Heart Study (NHLBI FHS), and for diabetes on 15q13, we investigated epistasis between chromosome 2 and these loci. Significant epistatic interactions were found between QTLs 2p25 and 7q34, 2q37 and 7q34, 2q31 and 13q14, and 2q31–q36 and 15q13. These results suggest multiple pathways and factors involving genetic and environmental effects influencing adiposity. By taking some of these known factors into account, we clarified our linkage evidence of a QTL on 2p25 influencing BMI and WC. The 2p25, 2q24–q31, and 2q36–q37 showed evidence of epistatic interaction with 7q34, 13q14, and 15q13.     

A QTL for genotype by sex interaction for anthropometric measurements in Alaskan Eskimos (GOCADAN Study) on chromosome 19q12-13

Variation in anthropometric measurements due to sexual dimorphism can be the result of genotype by sex interactions (G×S). The purpose of this study was to examine the sex-specific genetic architecture in anthropometric measurements in Alaskan Eskimos from the Genetics of Coronary Artery Disease in Alaska Natives (GOCADAN) study. Maximum likelihood-based variance components decomposition methods, implemented in SOLAR, were used for G×S analyses. Anthropometric measurements included BMI, waist circumference (WC), waist/height ratio, percent body fat (%BF), and subscapular and triceps skinfolds. Except for WC, mean values of all phenotypes were significantly different in men and women (P < 0.05). All anthropometric measures were significantly heritable (P < 0.001). In a preliminary analysis not allowing for G×S interaction, evidence of linkage was detected between markers D19S414 and D19S220 on chromosome 19 for WC (logarithm of odds (lod) = 3.5), %BF (lod = 1.7), BMI (lod = 2.4), waist/height ratio (lod = 2.5), subscapular (lod = 2.1), and triceps skinfolds (lod = 1.9). In subsequent analyses which allowed for G×S interaction, linkage was again found between these traits and the same two markers on chromosome 19 with significantly improved lod scores for: WC (lod = 4.5), %BF (lod = 3.8), BMI (lod = 3.5), waist/height ratio (lod = 3.2), subscapular (lod = 3.0), and triceps skinfolds (lod = 2.9). These results support the evidence of a G×S interaction in the expression of genetic effects resulting in sexual dimorphism in anthropometric phenotypes and identify the chromosome 19q12-13 region as important for adiposity-related traits in Alaskan Eskimos.     

A genome-wide linkage scan identifies multiple chromosomal regions influencing serum lipid levels in the population on the Samoan islands

Abnormal lipid levels are important risk factors for cardiovascular diseases. We conducted genome-wide variance component linkage analyses to search for loci influencing total cholesterol (TC), LDL, HDL and triglyceride in families residing in American Samoa and Samoa as well as in a combined sample from the two polities. We adjusted the traits for a number of environmental covariates, such as smoking, alcohol consumption, physical activity, and material lifestyle. We found suggestive univariate linkage with log of the odds (LOD) scores > 3 for LDL on 6p21-p12 (LOD 3.13) in Samoa and on 12q21-q23 (LOD 3.07) in American Samoa. Furthermore, in American Samoa on 12q21, we detected genome-wide linkage (LOD(eq) 3.38) to the bivariate trait TC-LDL. Telomeric of this region, on 12q24, we found suggestive bivariate linkage to TC-HDL (LOD(eq) 3.22) in the combined study sample. In addition, we detected suggestive univariate linkage (LOD 1.9-2.93) on chromosomes 4p-q, 6p, 7q, 9q, 11q, 12q 13q, 15q, 16p, 18q, 19p, 19q and Xq23 and suggestive bivariate linkage (LOD(eq) 2.05-2.62) on chromosomes 6p, 7q, 12p, 12q, and 19p-q. In conclusion, chromosome 6p and 12q may host promising susceptibility loci influencing lipid levels; however, the low degree of overlap between the three study samples strongly encourages further studies of the lipid-related traits.     

Genome‐wide Linkage and Association Analyses to Identify Genes Influencing Adiponectin Levels: The GEMS Stud

Adiponectin has a variety of metabolic effects on obesity, insulin sensitivity, and atherosclerosis. To identify genes influencing variation in plasma adiponectin levels, we performed genome‐wide linkage and association scans of adiponectin in two cohorts of subjects recruited in the Genetic Epidemiology of Metabolic Syndrome Study. The genome‐wide linkage scan was conducted in families of Turkish and southern European (TSE, n = 789) and Northern and Western European (NWE, N = 2,280) origin. A whole genome association (WGA) analysis (500K Affymetrix platform) was carried out in a set of unrelated NWE subjects consisting of approximately 1,000 subjects with dyslipidemia and 1,000 overweight subjects with normal lipids. Peak evidence for linkage occurred at chromosome 8p23 in NWE subjects (lod = 3.10) and at chromosome 3q28 near ADIPOQ, the adiponectin structural gene, in TSE subjects (lod = 1.70). In the WGA analysis, the single‐nucleotide polymorphisms (SNPs) most strongly associated with adiponectin were rs3774261 and rs6773957 (P < 10^?7). These two SNPs were in high linkage disequilibrium (r² = 0.98) and located within ADIPOQ. Interestingly, our fourth strongest region of association (P < 2 × 10^?5) was to an SNP within CDH13, whose protein product is a newly identified receptor for high‐molecular‐weight species of adiponectin. Through WGA analysis, we confirmed previous studies showing SNPs within ADIPOQ to be strongly associated with variation in adiponectin levels and further observed these to have the strongest effects on adiponectin levels throughout the genome. We additionally identified a second gene (CDH13) possibly influencing variation in adiponectin levels. The impact of these SNPs on health and disease has yet to be determined.     

High-resolution genome-wide linkage mapping identifies susceptibility loci for BMI in the Chinese population

The genetic loci affecting the commonly used BMI have been intensively investigated using linkage approaches in multiple populations. This study aims at performing the first genome‐wide linkage scan on BMI in the Chinese population in mainland China with hypothesis that heterogeneity in genetic linkage could exist in different ethnic populations. BMI was measured from 126 dizygotic twins in Qingdao municipality who were genotyped using high‐resolution Affymetrix Genome‐Wide Human SNP arrays containing about 1 million single‐nucleotide polymorphisms (SNPs). Nonparametric linkage analysis was performed with Merlin software package for linkage analysis using variance components approach for quantitative trait loci mapping. We identified a strong linkage peak at the end of chromosome 7 (7q36 at 186 cM) with a lod score of 4.06 which overlaps with that reported by a large multicenter study in western countries. Multiple loci showing suggestive linkage were found on chromosome 1 (lod score 2.38 at 242 cM), chromosome 8 (2.48 at 95 cM), and chromosome 14 (2.2 at 89.4 cM). The strong linkage identified in the Chinese subjects that is consistent with that found in populations of European origin could suggest the existence of evolutionarily preserved genetic mechanisms for BMI whereas the multiple suggestive loci could represent genetic effect from gene—environment interaction as a result of population‐specific environmental adaptation.     

Genetic effects on obesity assessed by bivariate genome scan: the Mexican-American coronary artery disease study

Objective: To identify the genetic determinants of obesity using univariate and bivariate models in a genome scan. Research Methods and Procedures: We evaluated the genetic and environmental effects and performed a genome‐wide linkage analysis of obesity‐related traits in 478 subjects from 105 Mexican‐American nuclear families ascertained through a proband with documented coronary artery disease. The available obesity traits include BMI, body surface area (BSA), waist‐to‐hip ratio (WHR), and trunk fat mass as percentage of body weight. Heritability estimates and multipoint linkage analysis were performed using a variance components procedure implemented in SOLAR software. Results: The heritability estimates were 0.62 for BMI, 0.73 for BSA, 0.40 for WHR, and 0.38 for trunk fat mass as percentage of body weight. Using a bivariate genetic model, we observed significant genetic correlations between BMI and other obesity‐related traits (all p < 0.01). Evidence for univariate linkage was observed at 252 to approximately 267 cM on chromosome 2 for three obesity‐related traits (except for WHR) and at 163 to approximately 167 cM on chromosome 5 for BMI and BSA, with the maximum logarithm of the odds ratio score of 3.12 (empirical p value, 0.002) for BSA on chromosome 2. Use of the bivariate linkage model yielded an additional peak (logarithm of the odds ratio = 3.25, empirical p value, 0.002) at 25 cM on chromosome 7 for the pair of BMI and BSA. Discussion: The evidence for linkage on chromosomes 2q36‐37 and 5q36 is supported both by univariate and bivariate analysis, and an additional linkage peak at 7p15 was identified by the bivariate model. This suggests that use of the bivariate model provides additional information to identify linkage of genes responsible for obesity‐related traits.     

Short-Term Overfeeding Increases Circulating Adiponectin Independent of Obesity Status

Background

Adiponectin is an adipose tissue derived hormone which strengthens insulin sensitivity. However, there is little data available regarding the influence of a positive energy challenge (PEC) on circulating adiponectin and the role of obesity status on this response.

Objective

The purpose of this study was to investigate how circulating adiponectin will respond to a short-term PEC and whether or not this response will differ among normal-weight(NW), overweight(OW) and obese(OB).

Design

We examined adiponectin among 64 young men (19-29 yr) before and after a 7-day overfeeding (70% above normal energy requirements). The relationship between adiponectin and obesity related phenotypes including; weight, percent body fat (%BF), percent trunk fat (%TF), percent android fat (%AF), body mass index (BMI), total cholesterol, HDLc, LDLc, glucose, insulin, homeostatic model assessment insulin resistance (HOMA-IR) and β-cell function (HOMA-β) were analyzed before and after overfeeding.

Results

Analysis of variance (ANOVA) and partial correlations were used to compute the effect of overfeeding on adiponectin and its association with adiposity measurements, respectively. Circulating Adiponectin levels significantly increased after the 7-day overfeeding in all three adiposity groups. Moreover, adiponectin at baseline was not significantly different among NW, OW and OB subjects defined by either %BF or BMI. Baseline adiponectin was negatively correlated with weight and BMI for the entire cohort and %TF, glucose, insulin and HOMA-IR in OB. However, after controlling for insulin resistance the correlation of adiponectin with weight, BMI and %TF were nullified.

Conclusion

Our study provides evidence that the protective response of adiponectin is preserved during a PEC regardless of adiposity. Baseline adiponectin level is not directly associated with obesity status and weight gain in response to short-term overfeeding. However, the significant increase of adiponectin in response to overfeeding indicates the physiological potential for adiponectin to attenuate insulin resistance during the development of obesity.     

Concordance of BAI and BMI with DXA in the Newfoundland Population

Background:

Body adiposity index (BAI), indirect method proposed to predict adiposity, was developed using Mexican Americans and very little data are available regarding its validation in Caucasian populations to date.

Objective:

The study objectives were to validate the BAI with dual‐energy X‐ray absorptiometry (DXA) body fat percentage (%BF), taking into consideration the gender and adiposity status.

Design and Methods:

A total of 2,601 subjects (Male 662, Female 1939) from our Complex Diseases in the Newfoundland population: Environment and Genetics (CODING) study participated in this investigation. Pearson correlations, with the entire cohort along with men and women separately, were used to compare the correlation of both BAI and BMI with %BF. Additionally, the concordance between BAI and BMI with %BF were also performed among normal‐weight (NW), overweight (OW), and obese (OB) groups. Adiposity status was determined by the Bray Criteria according to DXA %BF.

Results:

BAI performs better than BMI in our Caucasian population by: (1) reflecting the gender difference in total %BF between women and men, (2) correlating better with DXA %BF than BMI when women and men are combined, and (3) performing better in NW and OW subjects for both the sexes. However, BAI performs less effectively than BMI in OB men and women.

Conclusion:

In summary, the BAI method is a better estimate of adiposity than BMI in non‐OB subjects in our Caucasian population. A measurement sensitive to the changes in adiposity for both men and women is suggested to be incorporated into the present BAI equation to increase accuracy.     

Linkage and Genome‐wide Association Analysis of Obesity‐related Phenotypes: Association of Weight With the MGAT1 Gene

As major risk‐factors for diabetes and cardiovascular diseases, the genetic contribution to obesity‐related traits has been of interest for decades. Recently, a limited number of common genetic variants, which have replicated in different populations, have been identified. One approach to increase the statistical power in genetic mapping studies is to focus on populations with increased levels of linkage disequilibrium (LD) and reduced genetic diversity. We have performed joint linkage and genome‐wide association analyses for weight and BMI in 3,448 (linkage) and 3,925 (association) partly overlapping healthy individuals from five European populations. A total of four chromosomal regions (two for weight and two for BMI) showed suggestive linkage (lod >2.69) either in one of the populations or in the joint data. At the genome‐wide level (nominal P < 1.6 × 10^?7, Bonferroni‐adjusted P < 0.05) one single‐nucleotide polymorphism (SNP) (rs12517906) (nominal P = 7.3 × 10^?8) was associated with weight, whereas none with BMI. The SNP associated with weight is located close to MGAT1. The monoacylglycerol acyltransferase (MGAT) enzyme family is known to be involved in dietary fat absorption. There was no overlap between the linkage regions and the associated SNPs. Our results show that genetic effects influencing weight and BMI are shared across diverse European populations, even though some of these populations have experienced recent population bottlenecks and/or been affected by genetic drift. The analysis enabled us to identify a new candidate gene, MGAT1, associated with weight in women.     

A genetic contribution to circulating cytokines and obesity in children

Cytokines are considered to be involved in obesity-related metabolic diseases. Study objectives are to determine the heritability of circulating cytokine levels, to investigate pleiotropy between cytokines and obesity traits, and to present genome scan results for cytokines in 1030 Hispanic children enrolled in VIVA LA FAMILIA Study. Cytokine phenotypes included monocyte chemoattractant protein-1 (MCP-1), tumor necrosis factor-alpha (TNF-alpha), leptin, adiponectin, soluble intercellular adhesion molecule-1 (sICAM-1), transforming growth factor beta 1 (TGF-beta1), C-reactive protein (CRP), regulated upon activation, normal T-cell expressed and secreted (RANTES) and eotaxin. Obesity-related phenotypes included body mass index (BMI), fat mass (FM), truncal FM and fasting serum insulin. Heritabilities ranged from 0.33 to 0.97. Pleiotropy was observed between cytokines and obesity traits. Positive genetic correlations were seen between CRP, leptin, MCP-1 and obesity traits, and negative genetic correlations with adiponectin, ICAM-1 and TGF-beta1. Genome-wide scan of sICAM-1 mapped to chromosome 3 (LOD=3.74) between markers D3S1580 and D3S1601, which flanks the adiponectin gene (ADIPOQ). Suggestive linkage signals were found in other chromosomal regions for other cytokines. In summary, significant heritabilities for circulating cytokines, pleiotropy between cytokines and obesity traits, and linkage for sICAM-1 on chromosome 3q substantiate a genetic contribution to circulating cytokine levels in Hispanic children.     

A QTL on 12q Influencing an Inflammation Marker and Obesity in White Women: The NHLBI Family Heart Study

It has been recognized that obese individuals are intrinsically in a state of chronic inflammation, as indicated by positive correlations between serum levels of C‐reactive protein (CRP) and various anthropometric measures of obesity. To explore the hypothesis that a gene(s) may underlie this relationship, we conducted bivariate linkage analyses of BMI and CRP in white and African‐American (AA) families of the National Heart, Lung, and Blood Institute (NHLBI) Family Heart Study (FHS). Variance components linkage analysis as implemented in SOLAR was performed in 1,825 whites (840 men and 985 women) and 548 AAs (199 men and 351 women). CRP exhibited significant genetic correlations with BMI in women (0.54 ± 0.10 for white and 0.53 ± 0.14 for AA) and the combined samples (0.37 ± 0.09 for white and 0.56 ± 0.13 for AA), but not in men. We detected a maximum bivariate lod score of 3.86 on chromosome 12q24.2–24.3 at 139 cM and a suggestive linkage signal (lod = 2.19) on chromosome 19p13.1 (44 cM) in white women. Both bivariate peaks were substantially higher than their respective univariate lods at the same locus for each trait. No significant lod scores were detected in AAs. Our results indicate that chromosome 12q may harbor quantitative trait loci (QTLs) jointly regulating BMI and CRP in white women.     

Leptin,Insulin, and Obesity‐related Phenotypes: Genetic Influences on Levels and Longitudinal Changes

This study estimated the genetic and environmental determinants of plasma leptin and insulin levels and of obesity‐related phenotypes. Included in this analysis were family members from 80 families living in kibbutz settlements, who participated in two examinations 8–10 years apart. We estimated that polygenes explained 30–50% of the adjusted leptin and insulin levels and 30–70% of the anthropometric phenotypes. This study demonstrated a significant genetic influence on longitudinal changes in leptin and BMI (h² = 0.45) and small‐to‐moderate heritability estimates for changes in insulin and other obesity‐related phenotypes. In bivariate genetic analyses, we observed positive genetic correlations between leptin and anthropometric phenotypes, suggesting that shared effects of the same sets of loci account for 20–30% of the additive genetic variance in these pairs of variables. Shared genetic factors also account for 20–25% of the additive genetic variance in insulin—anthropometric pairs of variables.     

Comparison of the Classification of Obesity by BMI vs. Dual‐energy X‐ray Absorptiometry in the Newfoundland Population

Although BMI is the most widely used measure of obesity, debate still exists on how accurately BMI defines obesity. In this study, adiposity status defined by BMI and dual‐energy X‐ray absorptiometry (DXA) was compared in a large population to evaluate the accuracy of BMI. A total of 1,691 adult volunteers from Newfoundland and Labrador participated in the study. BMI and body fat percentage (%BF) were measured for all subjects following a 12‐h fasting period. Subjects were categorized as underweight (UW), normal weight (NW), overweight (OW), or obese (OB) based on BMI and %BF criteria. Differences between the two methods were compared within gender and by age‐groups. According to BMI criteria, 1.2% of women were classified as UW, 44.2% as NW, 34.2% as OW, and 20.3% as OB. When women were classified according to %BF criteria, 2.2% were UW, 29.6% were NW, 30.9% were OW, and 37.1% were OB. The overall discrepancy between the two methods for women was substantial at 34.7% (14.6% for NW and 16.8% for OB, P < 0.001). In men, the overall discrepancy was 35.2% between BMI and DXA (17.6% for OW and 13.5% for OB, P < 0.001). Misclassification by BMI was dependent on age, gender, and adiposity status. In conclusion, BMI misclassified adiposity status in approximately one‐third of women and men compared with DXA. Caution should be taken when BMI is used in clinical and scientific research as well as clinical practice.     

The Prevalence of Metabolically Healthy Obese Subjects Defined by BMI and Dual‐Energy X‐Ray Absorptiometry

Nearly one‐third of obese (OB) people are reported to be metabolically healthy based on BMI criteria. It is unknown whether this holds true when more accurate adiposity measurements are applied such as dual‐energy X‐ray absorptiometry (DXA). We compared differences in the prevalence of cardiometabolic abnormalities among adiposity groups classified using BMI vs. DXA criteria. A total of 1,907 adult volunteers from Newfoundland and Labrador participated. BMI and body fat percentage (%BF; measured using DXA) were measured following a 12‐h fasting period. Subjects were categorized as normal weight (NW), overweight (OW), or OB based on BMI and %BF criteria. Cardiometabolic abnormalities considered included elevated triglyceride, glucose, and high‐sensitivity C‐reactive protein (hsCRP) levels, decreased high‐density lipoprotein (HDL) cholesterol levels, insulin resistance, and hypertension. Subjects were classified as metabolically healthy (0 or 1 cardiometabolic abnormality) or abnormal (≥2 cardiometabolic abnormalities). We found low agreement in the prevalence of cardiometabolic abnormalities between BMI and %BF classifications (κ = 0.373, P < 0.001). Among NW and OW subjects, the prevalence of metabolically healthy individuals was similar between BMI and %BF (77.6 vs. 75.7% and 58.8 vs. 62.5%, respectively) however, there was a pronounced difference among OB subjects (34.0 vs. 47.7%, P < 0.05). Similar trends were evident using three additional definitions to characterize metabolically healthy individuals. Our findings indicate that approximately one‐half of OB people are metabolically healthy when classified using %BF criteria which is significantly higher than previously reported using BMI. Caution should therefore be taken when making inferences about the metabolic health of an OB population depending on the method used to measure adiposity.     

Meta-analysis of genome-wide linkage studies in BMI and obesity

Objective: The objective was to provide an overall assessment of genetic linkage data of BMI and BMI‐defined obesity using a nonparametric genome scan meta‐analysis. Research Methods and Procedures: We identified 37 published studies containing data on over 31,000 individuals from more than >10,000 families and obtained genome‐wide logarithm of the odds (LOD) scores, non‐parametric linkage (NPL) scores, or maximum likelihood scores (MLS). BMI was analyzed in a pooled set of all studies, as a subgroup of 10 studies that used BMI‐defined obesity, and for subgroups ascertained through type 2 diabetes, hypertension, or subjects of European ancestry. Results: Bins at chromosome 13q13.2‐ q33.1, 12q23‐q24.3 achieved suggestive evidence of linkage to BMI in the pooled analysis and samples ascertained for hypertension. Nominal evidence of linkage to these regions and suggestive evidence for 11q13.3‐22.3 were also observed for BMI‐defined obesity. The FTO obesity gene locus at 16q12.2 also showed nominal evidence for linkage. However, overall distribution of summed rank p values <0.05 is not different from that expected by chance. The strongest evidence was obtained in the families ascertained for hypertension at 9q31.1‐qter and 12p11.21‐q23 (p < 0.01). Conclusion: Despite having substantial statistical power, we did not unequivocally implicate specific loci for BMI or obesity. This may be because genes influencing adiposity are of very small effect, with substantial genetic heterogeneity and variable dependence on environmental factors. However, the observation that the FTO gene maps to one of the highest ranking bins for obesity is interesting and, while not a validation of this approach, indicates that other potential loci identified in this study should be investigated further.     

Multiple Genes Influence BMI on Chromosome 7q31–34: The NHLBI Family Heart Study

The National Heart, Lung, and Blood Institute Family Heart Study (FHS) genome‐wide linkage scan identified a region of chromosome 7q31–34 with a lod score of 4.9 for BMI at D7S1804 (131.9 Mb). We report the results of linkage and association to BMI in this region for two independent FHS samples. The first sample includes 225 FHS pedigrees with evidence of linkage to 7q31–34, using 1,132 single‐nucleotide polymorphisms (SNPs) and 7 microsatellites. The second represents a case–control sample (318 cases; BMI >25 and 325 controls; BMI <25) derived from unrelated FHS participants who were not part of the genome scan. The latter set was genotyped for 606 SNPs, including 37 SNPs with prior evidence for association in the linked families. Although variance components linkage analysis using only SNPs generated a peak lod score that coincided with the original linkage scan at 131.9 Mb, a conditional linkage analysis showed evidence of a second quantitative trait locus (QTL) near 143 cM influencing BMI. Three SNPs (rs161339, rs12673281, and rs1993068) located near the three genes pleiotrophin (PTN), diacylglycerol (DAG) kinase iota (DGKι), and cholinergic receptor, muscarinic 2 (CHRM2) demonstrated significant association in both linked families (P = 0.0005, 0.002, and 0.03, respectively) and the case–control sample (P = 0.01, 0.0003, and 0.03, respectively), regardless of the genetic model tested. These findings suggest that several genes may be associated with BMI in the 7q31–34 region.     

Possible heterogeneity in the phosphoglycolate phosphatase (PGP)-haptoglobin alpha (HPA) linkage.

Previous investigators have reported loose linkage in both sexes for phosphoglycolate phosphatase (PGP) and haptoglobin alpha (HPA). We present results of linkage studies between PGP and HPA in two data sets, one from Houston and the other an update of an earlier report from Los Angeles. Using quadratic interpolation to estimate the male (theta m) and female (theta f) recombination values from bivariate lod tables, we found for the Houston data that theta m = 0.43 and theta f = 0.03 at the maximum lod score of z = 2.23. For the Los Angeles series, we found that theta m = 0.31, theta f = 0.48, and z = 0.27. We invoke heterogeneity in the recombination value in different families as an explanation of our findings. We also recommend that bivariate lod tables should always be generated, even though not reported. This is because the usual assumption of theta m = theta f (and, rarely, theta f = 1.8 theta f) under which lod scores are computed may be invalid in many cases.     

Relationship of visceral adiposity to cardiovascular disease risk factors in black and white teens

Objective: We tested the hypothesis that visceral adiposity, compared with general adiposity, would explain more of the variance in cardiovascular disease (CVD) risk factors. Research Method and Procedures: Subjects were 464 adolescents (238 black and 205 girls). Adiposity measures included visceral adipose tissue (VAT; magnetic resonance imaging), percent body fat (%BF; DXA), BMI, and waist girth (anthropometry). CVD risk factors were fasting insulin, fibrinogen, total to high‐density lipoprotein‐cholesterol ratio, triglycerides (TGs), systolic blood pressure, and left ventricular mass indexed to height^2.7. Results: After adjustment for age, race, and sex, all adiposity indices explained significant proportions of the variance in all of the CVD risk factors; %BF tended to explain more variance than VAT. Regression models that included both %BF and VAT found that both indices explained independent proportions of the variance only for total to high‐density lipoprotein‐cholesterol ratio. For TGs, the model that included both %BF and VAT found that only VAT was significant. For systolic blood pressure and left ventricular mass indexed to height^2.7, anthropometric measures explained more of the variance than VAT and %BF. Discussion: The hypothesis that visceral adiposity would explain more variance in CVD risk than general adiposity was not supported in this relatively large sample of black and white adolescents. Only for TGs did it seem that VAT was more influential than %BF. Perhaps the deleterious effect of visceral adiposity becomes greater later in life as it increases in proportion to general adiposity.