Genetic determinants of obesity-related lipid traits

In our ongoing effort to identify genes influencing the biological pathways that underlie the metabolic disturbances associated with obesity, we performed genome-wide scanning in 2,209 individuals distributed over 507 Caucasian families to localize quantitative trait loci (QTLs), which affect variation of plasma lipids. Pedigree-based analysis using a quantitative trait variance component linkage method that localized a QTL on chromosome 7q35-q36, which linked to variation in levels of plasma triglyceride [TG, logarithm of odds (LOD) score = 3.7] and was suggestive of linkage to LDL-cholesterol (LDL-C, LOD = 2.2). Covariates of the TG linkage included waist circumference, fasting insulin, and insulin:glucose, but not body mass index or hip circumference. Plasma HDL-cholesterol (HDL-C) levels were suggestively linked to a second QTL on chromosome 12p12.3 (LOD = 2.6). Five other QTLs with lower LOD scores were identified for plasma levels of LDL-C, HDL-C, and total cholesterol. These newly identified loci likely harbor genetic elements that influence traits underlying lipid adversities associated with obesity.     

Evidence of QTLs on chromosomes 1q42 and 8q24 for LDL-cholesterol and apoB levels in the HERITAGE family study

Genome-wide multipoint linkage analyses were performed to identify chromosomal regions harboring genes influencing LDL-cholesterol, total apolipoprotein B (apoB), and LDL-apoB levels using 654 markers. They were assessed in a sedentary state (baseline) and after a 20 week endurance training program. Strong evidence for two quantitative trait loci (QTLs) for baseline levels was found. There is linkage evidence in black families on chromosomes 1q41-q44 [at marker D1S2860, 238 centimorgan (cM), with a maximum log of the odds (LOD) score of 3.7 for LDL-apoB] and in white families on chromosome 8q24 (at marker D8S1774, 142 cM, with LOD scores of 3.6, 3.3, and 2.5 for baseline LDL-cholesterol, LDL-apoB, and apoB, respectively). There were no strong signals for the lipoprotein training responses (as computed as the difference in posttraining minus baseline levels). In conclusion, QTLs for baseline apoB and LDL-cholesterol levels on chromosomes 1q41-q44 (in blacks) and 8q24 (in whites) were found. As there are no known strong candidate genes in these regions for lipids, follow-up studies to determine the source of those signals are needed.     

Variance‐Component Analysis of Obesity in Type 2 Diabetes Confirms Loci on Chromosomes 1q and 11q

To study genetic loci influencing obesity in nuclear families with type 2 diabetes, we performed a genome‐wide screen with 325 microsatellite markers that had an average spacing of 11 cM and a mean heterozygosity of ～75% covering all 22 autosomes. Genotype data were obtained from 562 individuals from 178 families from the Breda Study Cohort. These families were determined to have at least two members with type 2 diabetes. As a measure of obesity, the BMI of each diabetes patient was determined. The genotypes were analyzed using variance components (VCs) analysis implemented in GENEHUNTER 2 to determine quantitative trait loci influencing BMI. The VC analysis revealed two genomic regions showing VC logarithm of odds (LOD) scores ≥1.0 on chromosome 1 and chromosome 11. The regions of interest on both chromosomes were further investigated by fine‐mapping with additional markers, resulting in a VC LOD score of 1.5 on chromosome 1q and a VC LOD of 2.4 on chromosome 11q. The locus on chromosome 1 has been implicated previously in diabetes. The locus on chromosome 11 has been implicated previously in diabetes and obesity. Our study to determine linkage for BMI confirms the presence of quantitative trait loci influencing obesity in subjects with type 2 diabetes on chromosomes 1q31‐q42 and 11q14‐q24.     

A genome-wide linkage scan for quantitative trait loci underlying obesity related phenotypes in 434 Caucasian families

To identify quantitative trait loci (QTLs) that contribute to obesity, we performed a large-scale whole genome linkage scan (WGS) involving 4,102 individuals from 434 Caucasian families. The most pronounced linkage evidence was found at the genomic region 20p11-12 for fat mass (LOD = 3.31) and percentage fat mass (PFM) (LOD = 2.92). We also identified several regions showing suggestive linkage signals (threshold LOD = 1.9) for obesity phenotypes, including 5q35, 8q13, 10p12, and 17q11.     

The Human Obesity Gene Map: The 1997 Update

An update of the human obesity gene map incorporating published results up to October 1997 is presented. Evidence from Mendelian disorders exhibiting obesity as a clinical feature; single-gene mutation rodent models; quantitative trait loci uncovered in human genome-wide scans and in crossbreeding experiments with mouse, rat, and pig models; association and case-control studies with candidate genes; and linkage studies with genes and other markers is reviewed. All chromosomal locations of the animal loci are converted into human genome locations based on syntenic relationships between the genomes. A complete listing of all of these loci reveals that all but chromosome Y of the 24 human chromosomes are represented. Some chromosomes show at least three putative loci related to obesity on both arms (1, 2, 6, 8, 11, and 20) and several on one chromosome arm only (3p, 4q, 5q, 7q, 12q, 13q, 15q, 15p, 22q, and Xq). Studies reporting negative association and linkage results are also listed, with the exception of the unlinked markers from genome-wide scans.     

Multiple QTLs influencing triglyceride and HDL and total cholesterol levels identified in families with atherogenic dyslipidemia

We conducted a genome-wide scan using variance components linkage analysis to localize quantitative-trait loci (QTLs) influencing triglyceride (TG), high density lipoprotein-cholesterol (HDL-C), low density lipoprotein-cholesterol, and total cholesterol (TC) levels in 3,071 subjects from 459 families with atherogenic dyslipidemia. The most significant evidence for linkage to TG levels was found in a subset of Turkish families at 11q22 [logarithm of the odds ratio (LOD)=3.34] and at 17q12 (LOD=3.44). We performed sequential oligogenic linkage analysis to examine whether multiple QTLs jointly influence TG levels in the Turkish families. These analyses revealed loci at 20q13 that showed strong epistatic effects with 11q22 (conditional LOD=3.15) and at 7q36 that showed strong epistatic effects with 17q12 (conditional LOD=3.21). We also found linkage on the 8p21 region for TG in the entire group of families (LOD=3.08). For HDL-C levels, evidence of linkage was identified on chromosome 15 in the Turkish families (LOD=3.05) and on chromosome 5 in the entire group of families (LOD=2.83). Linkage to QTLs for TC was found at 8p23 in the entire group of families (LOD=4.05) and at 5q13 in a subset of Turkish and Mediterranean families (LOD=3.72). These QTLs provide important clues for the further investigation of genes responsible for these complex lipid phenotypes. These data also indicate that a large proportion of the variance of TG levels in the Turkish population is explained by the interaction of multiple genetic loci.     

Linkage Analysis of Factors Underlying Insulin Resistance: Strong Heart Family Study

In previous work in non‐diabetic participants of the Strong Heart Family Study, we identified three heritable principal components of nine insulin resistance (IR) phenotypes: 1) a glucose/insulin/obesity factor, 2) a blood pressure factor, and 3) a dyslipidemia factor. To localize quantitative trait loci (QTL) potentially influencing these factors, we conducted a genome scan of factor scores in Strong Heart Family Study participants. Approximately 599 men and women, ≥18 years of age, in 32 extended families at three centers (in Arizona, Oklahoma, and North and South Dakota), were examined between 1997 and 1999. We used variance components linkage analysis to identify QTLs for the IR factors. With age, sex, and study center as covariates, we detected linkage of the glucose/insulin/obesity factor to chromosome 4 (robust logarithm of the odds (LOD) = 2.2), the dyslipidemia factor to chromosome 12 (robust LOD = 2.7), and the blood pressure factor to chromosome 1 (robust LOD = 1.6). The peak linkage signals identified for these IR factors support several positive findings from other studies and occur in regions harboring interesting candidate genes. The corroboration of existing QTLs will bring us closer to the identification of the functional genes that predispose to IR.     

Genome-wide linkage scan reveals multiple susceptibility loci influencing lipid and lipoprotein levels in the Quebec Family Study

A genome-wide linkage study was performed to identify chromosomal regions harboring genes influencing lipid and lipoprotein levels. Linkage analyses were conducted for four quantitative lipoprotein/lipid traits, i.e., total cholesterol, triglyceride, HDL-cholesterol (HDL-C), and LDL-C concentrations, in 930 subjects enrolled in the Québec Family Study. A maximum of 534 pairs of siblings from 292 nuclear families were available. Linkage was tested using both allele-sharing and variance-component linkage methods. The strongest evidence of linkage was found on chromosome 12q14.1 at marker D12S334 for HDL-C, with a logarithm of the odds (LOD) score of 4.06. Chromosomal regions harboring quantitative trait loci (QTLs) for LDL-C included 1q43 (LOD = 2.50), 11q23.2 (LOD = 3.22), 15q26.1 (LOD = 3.11), and 19q13.32 (LOD = 3.59). In the case of triglycerides, three markers located on 2p14, 11p13, and 11q24.1 provided suggestive evidence of linkage (LOD > 1.75). Tests for total cholesterol levels yielded significant evidence of linkage at 15q26.1 and 18q22.3 with the allele-sharing linkage method, but the results were nonsignificant with the variance-component method. In conclusion, this genome scan provides evidence for several QTLs influencing lipid and lipoprotein levels. Promising candidate genes were located in the vicinity of the genomic regions showing evidence of linkage.     

Genome-wide linkage scan for the metabolic syndrome: the GENNID study

In the United States, the metabolic syndrome (MetS) constitutes a major public health problem with over 47 million persons meeting clinical criteria for MetS. Numerous studies have suggested genetic susceptibility to MetS. The goals of this study were (i) to identify susceptibility loci for MetS in well-characterized families with type 2 diabetes (T2D) in four ethnic groups and (ii) to determine whether evidence for linkage varies across the four groups. The GENNID study (Genetics of NIDDM) is a multicenter study established by the American Diabetes Association in 1993 and comprises a comprehensive, well-characterized resource of T2D families from four ethnic groups (whites, Mexican Americans, African Americans, and Japanese Americans). Principal component factor analysis (PCFA) was used to define quantitative phenotypes of the MetS. Variance components linkage analysis was conducted using microsatellite markers from a 10-cM genome-wide linkage scan, separately in each of the four ethnic groups. Three quantitative MetS factors were identified by PCFA and used as phenotypes for MetS: (i) a weight/waist factor, (ii) a blood pressure factor, and (iii) a lipid factor. Evidence for linkage to each of these factors was observed. For each ethnic group, our results suggest that several regions harbor susceptibility genes for the MetS. The strongest evidence for linkage for MetS phenotypes was observed on chromosome 2 (2q12.1-2q13) in the white sample and on chromosome 3 (3q26.1-3q29) in the Mexican-American sample. In conclusion, the results suggest that several regions harbor MetS susceptibility genes and that heterogeneity may exist across groups.     

Quantitative trait loci that regulate plasma lipid concentration in hereditary obese KK and KK-Ay mice

To identify quantitative trait loci (QTLs) responsible for regulating plasma lipid concentration associated with obesity, linkage analysis was carried out on the 190 F2 progeny of a cross between C57BL/6J female and KK-Ay (Ay allele at the agouti locus congenic) male. In F2 a/a (agouti locus genotype) mice, two QTLs were identified on chromosome 1 and a QTL on chromosome 3 for total-cholesterol. A QTL for HDL-cholesterol was identified on chromosome 1 and a QTL for NEFA on chromosome 9. In F2 Ay/a mice, two QTLs for HDL-cholesterol were found on chromosome 1. Loci for other lipids with suggestive linkage were also identified. In both F2 mice, one QTL on chromosome 1 for total- and HDL-cholesterol was mapped near D1Mit150, in the vicinity of the apolipoprotein A-II (Apoa2) locus. Seven nucleotide substitutions out of 309 nucleotide apolipoprotein A-II cDNA sequences were identified between KK and C57BL/6J. The Ay allele may be an indication of the plasma lipid levels, but its influence was less apparent than in the case of weight control. The loci for lipids were not on identical chromosomes with those previously identified for obesity, suggesting that hyperlipidemia in KK does not coincidentally occur with obesity.     

Genome-wide linkage scan for submaximal exercise heart rate in the HERITAGE family study

The purpose of this study was to identify regions of the human genome linked to submaximal exercise heart rates in the sedentary state and in response to a standardized 20-wk endurance training program in blacks and whites of the HERITAGE Family Study. A total of 701 polymorphic markers covering the 22 autosomes were used in the genome-wide linkage scan, with 328 sibling pairs from 99 white nuclear families and 102 pairs from 115 black family units. Steady-state heart rates were measured at the relative intensity of 60% maximal oxygen uptake (HR60) and at the absolute intensity of 50 W (HR50). Baseline phenotypes were adjusted for age, sex, and baseline body mass index (BMI) and training responses (posttraining minus baseline, Delta) were adjusted for age, sex, baseline BMI, and baseline value of the phenotype. Two analytic strategies were used, a multipoint variance components and a regression-based multipoint linkage analysis. In whites, promising linkages (LOD > 1.75) were identified on 18q21-q22 for baseline HR50 (LOD = 2.64; P = 0.0002) and DeltaHR60 (LOD = 2.10; P = 0.0009) and on chromosome 2q33.3 for DeltaHR50 (LOD = 2.13; P = 0.0009). In blacks, evidence of promising linkage for baseline HR50 was detected with several markers within the chromosomal region 10q24-q25.3 (peak LOD = 2.43, P = 0.0004 with D10S597). The most promising regions for fine mapping in the HERITAGE Family Study were found on 2q33 for HR50 training response in whites, on 10q25-26 for baseline HR60 in blacks, and on 18q21-22 for both baseline HR50 and DeltaHR60 in whites.     

The Human Obesity Gene Map: The 2004 Update

This paper presents the eleventh update of the human obesity gene map, which incorporates published results up to the end of October 2004. Evidence from single‐gene mutation obesity cases, Mendelian disorders exhibiting obesity as a clinical feature, transgenic and knockout murine models relevant to obesity, quantitative trait loci (QTLs) from animal cross‐breeding experiments, association studies with candidate genes, and linkages from genome scans is reviewed. As of October 2004, 173 human obesity cases due to single‐gene mutations in 10 different genes have been reported, and 49 loci related to Mendelian syndromes relevant to human obesity have been mapped to a genomic region, and causal genes or strong candidates have been identified for most of these syndromes. There are 166 genes which, when mutated or expressed as transgenes in the mouse, result in phenotypes that affect body weight and adiposity. The number of QTLs reported from animal models currently reaches 221. The number of human obesity QTLs derived from genome scans continues to grow, and we have now 204 QTLs for obesity‐related phenotypes from 50 genome‐wide scans. A total of 38 genomic regions harbor QTLs replicated among two to four studies. The number of studies reporting associations between DNA sequence variation in specific genes and obesity phenotypes has also increased considerably with 358 findings of positive associations with 113 candidate genes. Among them, 18 genes are supported by at least five positive studies. The obesity gene map shows putative loci on all chromosomes except Y. Overall, >600 genes, markers, and chromosomal regions have been associated or linked with human obesity phenotypes. The electronic version of the map with links to useful publications and genomic and other relevant sites can be found at http:obesitygene.pbrc.edu .     

Identification of diabetes susceptibility loci in db mice by combined quantitative trait loci analysis and haplotype mapping

To identify the disease-susceptibility genes of type 2 diabetes, we performed quantitative trait loci (QTL) analysis in F(2) populations generated from a BKS.Cg-m+/+Lepr(db) and C3H/HeJ intercross, taking advantage of genetically determined obesity and diabetes traits associated with the db gene. A genome-wide scan in the F(2) populations divided by sex and db genotypes identified 14 QTLs in total and 3 major QTLs on chromosome (Chr) 3 (LOD 5.78) for fat pad weight, Chr 15 (LOD 6.64) for body weight, and Chr 16 (LOD 8.15) for blood glucose concentrations. A linear-model-based genome scan using interactive covariates allowed us to consider sex- or sex-by db-specific effects of each locus. For the most significant QTL on Chr 16, the high-resolution haplotype comparison between BKS and C3H strains reduced the critical QTL interval from 20 to 4.6 Mb by excluding shared haplotype regions and identified 11 nonsynonymous single-nucleotide polymorphisms in six candidate genes.     

A genomewide scan for loci predisposing to type 2 diabetes in a U.K. population (the Diabetes UK Warren 2 Repository): analysis of 573 pedigrees provides independent replication of a susceptibility locus on chromosome 1q

Improved molecular understanding of the pathogenesis of type 2 diabetes is essential if current therapeutic and preventative options are to be extended. To identify diabetes-susceptibility genes, we have completed a primary (418-marker, 9-cM) autosomal-genome scan of 743 sib pairs (573 pedigrees) with type 2 diabetes who are from the Diabetes UK Warren 2 repository. Nonparametric linkage analysis of the entire data set identified seven regions showing evidence for linkage, with allele-sharing LOD scores > or =1.18 (P< or =.01). The strongest evidence was seen on chromosomes 8p21-22 (near D8S258 [LOD score 2.55]) and 10q23.3 (near D10S1765 [LOD score 1.99]), both coinciding with regions identified in previous scans in European subjects. This was also true of two lesser regions identified, on chromosomes 5q13 (D5S647 [LOD score 1.22] and 5q32 (D5S436 [LOD score 1.22]). Loci on 7p15.3 (LOD score 1.31) and 8q24.2 (LOD score 1.41) are novel. The final region showing evidence for linkage, on chromosome 1q24-25 (near D1S218 [LOD score 1.50]), colocalizes with evidence for linkage to diabetes found in Utah, French, and Pima families and in the GK rat. After dense-map genotyping (mean marker spacing 4.4 cM), evidence for linkage to this region increased to a LOD score of 1.98. Conditional analyses revealed nominally significant interactions between this locus and the regions on chromosomes 10q23.3 (P=.01) and 5q32 (P=.02). These data, derived from one of the largest genome scans undertaken in this condition, confirm that individual susceptibility-gene effects for type 2 diabetes are likely to be modest in size. Taken with genome scans in other populations, they provide both replication of previous evidence indicating the presence of a diabetes-susceptibility locus on chromosome 1q24-25 and support for the existence of additional loci on chromosomes 5, 8, and 10. These data should accelerate positional cloning efforts in these regions of interest.     

Genome scan for quantitative trait loci influencing HDL levels: evidence for multilocus inheritance in familial combined hyperlipidemia

Several genome scans in search of high-density lipoprotein (HDL) quantitative trait loci (QTLs) have been performed. However, to date the actual identification of genes implicated in the regulation of common forms of HDL abnormalities remains unsuccessful. This may be due, in part, to the oligogenic and multivariate nature of HDL regulation, and potentially, pleiotropy affecting HDL and other lipid-related traits. Using a Bayesian Markov Chain Monte Carlo (MCMC) approach, we recently provided evidence of linkage of HDL level variation to the APOA1–C3–A4–A5 gene complex, in familial combined hyperlipidemia pedigrees, with an estimated number of two to three large QTLs remaining to be identified. We also presented results consistent with pleiotropy affecting HDL and triglycerides at the APOA1–C3–A4–A5 gene complex. Here we use the same MCMC analytic strategy, which allows for oligogenic trait models, as well as simultaneous incorporation of covariates, in the context of multipoint analysis. We now present results from a genome scan in search for the additional HDL QTLs in these pedigrees. We provide evidence of linkage for additional HDL QTLs on chromosomes 3p14 and 13q32, with results on chromosome 3 further supported by maximum parametric and variance component LOD scores of 3.0 and 2.6, respectively. Weaker evidence of linkage was also obtained for 7q32, 12q12, 14q31–32 and 16q23–24.     

Quantitative-Trait-Locus Analysis of Body-Mass Index and of Stature, by Combined Analysis of Genome Scans of Five Finnish Study Groups

In recent years, many genomewide screens have been performed, to identify novel loci predisposing to various complex diseases. Often, only a portion of the collected clinical data from the study subjects is used in the actual analysis of the trait, and much of the phenotypic data is ignored. With proper consent, these data could subsequently be used in studies of common quantitative traits influencing human biology, and such a reanalysis method would be further justified by the nonbiased ascertainment of study individuals. To make our point, we report here a quantitative-trait-locus (QTL) analysis of body-mass index (BMI) and stature (i.e., height), with genotypic data from genome scans of five Finnish study groups. The combined study group was composed of 614 individuals from 247 families. Five study groups were originally ascertained in genetic studies on hypertension, obesity, osteoarthritis, migraine, and familial combined hyperlipidemia. Most of the families are from the Finnish Twin Cohort, which represents a population-wide sample. In each of the five genome scans, approximately 350 evenly spaced markers were genotyped on 22 autosomes. In analyzing the genotype data by a variance-component method, we found, on chromosome 7pter (maximum multipoint LOD score of 2.91), evidence for QTLs affecting stature, and a second locus, with suggestive evidence for linkage to stature, was detected on chromosome 9q (maximum multipoint LOD score of 2.61). Encouragingly, the locus on chromosome 7 is supported by the data reported by Hirschhorn et al. (in this issue), who used a similar method. We found no evidence for QTLs affecting BMI.     

Genetic dissection of "OLETF," a rat model for non-insulin-dependent diabetes mellitus: quantitative trait locus analysis of (OLETF x BN) x OLETF.

To identify genetic determinants relevant to non-insulin-dependent diabetes mellitus (NIDDM), we performed a genome-wide analysis for quantitative trait loci (QTLs) using 359 backcross progeny of the Otsuka Long-Evans Tokushima Fatty (OLETF) rat. The OLETF strain is a well-studied animal model of obese NIDDM, with features of hyperinsulinemia, hyperglycemia, insulin resistance, and abundant abdominal fat. Our extensive genomic scanning with 218 markers revealed nine significant QTLs, including a strong determinant of obesity on chromosome 1 (Dmo1: LOD = 13.99, for body weight). Two highly significant QTLs for glucose homeostasis were found, one on chromosome 1 (Dmo4 LOD = 7.16, for postprandial glucose level) and the other on chromosome X (Dmo11/Odb1: LOD = 7.81, for postprandial glucose level). These data are comparable to results of our previous studies of the OLETF rat.     

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.