Genome-wide linkage scan to identify loci associated with type 2 diabetes and blood lipid phenotypes in the Sikh Diabetes Study

In this investigation, we have carried out an autosomal genome-wide linkage analysis to map genes associated with type 2 diabetes (T2D) and five quantitative traits of blood lipids including total cholesterol, high-density lipoprotein (HDL) cholesterol, low-density lipoprotein (LDL) cholesterol, very low-density lipoprotein (VLDL) cholesterol, and triglycerides in a unique family-based cohort from the Sikh Diabetes Study (SDS). A total of 870 individuals (526 male/344 female) from 321 families were successfully genotyped using 398 polymorphic microsatellite markers with an average spacing of 9.26 cM on the autosomes. Results of non-parametric multipoint linkage analysis using S_all statistics (implemented in Merlin) did not reveal any chromosomal region to be significantly associated with T2D in this Sikh cohort. However, linkage analysis for lipid traits using QTL-ALL analysis revealed promising linkage signals with p≤0.005 for total cholesterol, LDL cholesterol, and HDL cholesterol at chromosomes 5p15, 9q21, 10p11, 10q21, and 22q13. The most significant signal (p = 0.0011) occurred at 10q21.2 for HDL cholesterol. We also observed linkage signals for total cholesterol at 22q13.32 (p = 0.0016) and 5p15.33 (p = 0.0031) and for LDL cholesterol at 10p11.23 (p = 0.0045). Interestingly, some of linkage regions identified in this Sikh population coincide with plausible candidate genes reported in recent genome-wide association and meta-analysis studies for lipid traits. Our study provides the first evidence of linkage for loci associated with quantitative lipid traits at four chromosomal regions in this Asian Indian population from Punjab. More detailed examination of these regions with more informative genotyping, sequencing, and functional studies should lead to rapid detection of novel targets of therapeutic importance.     

Quantitative Trait Loci for Metabolic Syndrome in the Hypertension Genetic Epidemiology Network Study

As part of the Hypertension Genetic Epidemiology Network study, genome scans were performed in two ethnicities on the categorical metabolic syndrome (MetS). Genome scans were performed also on the factor scores produced by factor analysis (quantitative MetS). Heritabilities were highest for the obesity‐insulin (INS) factor and lowest for blood pressure (BP) and central obesity. Seventeen unique putative quantitative trait loci (QTLs) yielded logarithm of the odds ratio (LOD) scores in excess of 1.7, 8 for blacks and 9 for whites. Important QTL findings in whites included an LOD score of 3.19 on chromosome 15q15 for the BP factor, 3.08 on chromosome 8p23 for the lipids‐INS factor, and 3.07 on chromosome 3p26 for the obesity‐INS factor. In blacks, after excluding type 2 diabetics, important QTLs were identified, including an LOD score of 2.77 on 13p12 for the obesity‐INS factor and 2.63 on chromosome 11q24 for the lipids‐INS factor. Categorical MetS had lower results than quantitative MetS. Notably, several loci identified overlap with those identified in other studies for a single or group of traits. The most promising candidate loci on 11q24 for lipids‐INS and 13p12 for obesity‐INS in blacks, 8p23 for lipids‐INS, 14q24 for obesity‐INS, and 15q15 for BP in whites warrant further investigation.     

Neuropsychological endophenotype approach to genome-wide linkage analysis identifies susceptibility loci for ADHD on 2q21.1 and 13q12.11

ADHD linkage findings have not all been consistently replicated, suggesting that other approaches to linkage analysis in ADHD might be necessary, such as the use of (quantitative) endophenotypes (heritable traits associated with an increased risk for ADHD). Genome-wide linkage analyses were performed in the Dutch subsample of the International Multi-Center ADHD Genetics (IMAGE) study comprising 238 DSM-IV combined-type ADHD probands and their 112 affected and 195 nonaffected siblings. Eight candidate neuropsychological ADHD endophenotypes with heritabilities > 0.2 were used as quantitative traits. In addition, an overall component score of neuropsychological functioning was used. A total of 5407 autosomal single-nucleotide polymorphisms (SNPs) were used to run multipoint regression-based linkage analyses. Two significant genome-wide linkage signals were found, one for Motor Timing on chromosome 2q21.1 (LOD score: 3.944) and one for Digit Span on 13q12.11 (LOD score: 3.959). Ten suggestive linkage signals were found (LOD scores > or = 2) on chromosomes 2p, 2q, 3p, 4q, 8q, 12p, 12q, 14q, and 17q. The suggestive linkage signal for the component score that was found at 2q14.3 (LOD score: 2.878) overlapped with the region significantly linked to Motor Timing. Endophenotype approaches may increase power to detect susceptibility loci in ADHD and possibly in other complex disorders.     

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.     

Genetic loci for blood lipid levels identified by linkage and association analyses in Caribbean Hispanics

To identify genetic loci influencing blood lipid levels in Caribbean Hispanics, we first conducted a genome-wide linkage scan in 1,211 subjects from 100 Dominican families on five lipid quantitative traits: total cholesterol (TC), low density lipoprotein cholesterol (LDL-C), high density lipoprotein cholesterol (HDL-C), triglycerides (TG), and LDL-C/HDL-C ratio. We then investigated the association between blood lipid levels and 21,361 single nucleotide polymorphisms (SNP) under the 1-logarithm of odds (LOD) unit down regions of linkage peaks in an independent community-based subcohort (N = 814, 42% Dominican) from the Northern Manhattan Study (NOMAS). We found significant linkage evidence for LDL-C/HDL-C on 7p12 (multipoint LOD = 3.91) and for TC on 16q23 (LOD = 3.35). In addition, we identified suggestive linkage evidence of LOD > 2.0 on 15q23 for TG, 16q23 for LDL-C, 19q12 for TC and LDL-C, and 20p12 for LDL-C. In the association analysis of the linkage peaks, we found that seven SNPs near FLJ45974 were associated with LDL-C/HDL-C with a nominal P < 3.5 × 10(-5), in addition to associations (P < 0.0001) for other lipid traits with SNPs in or near CDH13, SUMF2, TLE3, FAH, ARNT2, TSHZ3, ZNF343, RPL7AL2, and TMC3. Further studies are warranted to perform in-depth investigations of functional genetic variants in these regions.     

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.     

Genome‐wide Linkage Analysis of Multiple Metabolic Factors: Evidence of Genetic Heterogeneity

The metabolic syndrome is a highly complex disease and has become one of the major public‐health challenges worldwide. We sought to identify genetic loci with potential influence on multiple metabolic factors in a white population in Beaver Dam, Wisconsin, and to explore the possibility of genetic heterogeneity by family history of diabetes (FHD). Three metabolic factors were generated using principal‐component factor analysis, and they represented: (i) glycemia, (ii) blood pressure, and (iii) combined (BMI, high‐density lipoprotein (HDL) cholesterol, and serum uric acid) factors. Multipoint model‐free linkage analysis of these factors with 385 microsatellite markers was performed on 1,055 sib‐pairs, using Haseman–Elston regression. Genome‐wide suggestive evidence of linkage was found at 30 cM on chromosome 22q (empirical P (P_e) = 0.0002) for the glycemia factor, at 188–191 cM on chromosome 1q (P_e = 0.0007) for the blood pressure factor, and at 82 cM on chromosome 17q (P_e = 0.0007) for the combined factor. Subset analyses of the families by FHD showed evidence of genetic heterogeneity, with divergent linkage signals in the subsets on at least four chromosomes. We found evidence of genetic heterogeneity by FHD for the three metabolic factors. The results also confirmed findings of previous studies that mapped components of the metabolic syndrome to a chromosome 1q region.     

The inverse relation of HDL anti‐oxidative functionality with serum amyloid a is lost in metabolic syndrome subjects

Objective:

Anti‐oxidative properties of high density lipoproteins (HDL) are relevant for atheroprotection. HDL carry serum amyloid A (SAA), which may impair HDL functionality. We questioned whether HDL anti‐oxidative capacity is determined by SAA.

Design and Methods:

Relationships of HDL anti‐oxidative capacity (% inhibition of low density lipoprotein oxidation in vitro) with SAA were determined in 54 non‐diabetic subjects without metabolic syndrome (MetS) and 68 subjects with MetS (including 51 subjects with Type 2 diabetes mellitus).

Results:

SAA levels were higher in MetS subjects, coinciding higher high sensitive C‐reactive protein (hs‐CRP) and lower HDL cholesterol and apolipoprotein (apo) A‐I levels (P<0.001 for all). HDL anti‐oxidative capacity was not different between subjects with and without MetS (P=0.76), but the HDL anti‐oxidation index (HDL anti‐oxidative capacity multiplied by individual HDL cholesterol concentrations), as a measure of global anti‐oxidative functionality of HDL, was lower in Mets subjects (P<0.001). HDL anti‐oxidative capacity was correlated inversely with SAA levels in subjects without MetS (r=‐0.286, P=0.036). Notably, this relationship was independent of HDL cholesterol or apoA‐I (P<0.05 for both). In contrast, no relation of HDL anti‐oxidative capacity with SAA was observed in MetS subjects (r=0.032, P=0.80). The relationship of SAA with HDL anti‐oxidative capacity was different in subjects with MetS compared to subjects without MetS (P=0.039 for the interaction between the presence of MetS and SAA on HDL anti‐oxidative capacity) taking age and diabetes status into account.

Conclusion:

Higher SAA levels may impair HDL anti‐oxidative functionality. The relationship of this physiologically relevant HDL functionality measure with circulating SAA levels is apparently disturbed in metabolic syndrome.     

Pleiotropic QTL on chromosome 12q23-q24 influences triglyceride and high-density lipoprotein cholesterol levels: the HERITAGE family study

To determine whether a common quantitative trait locus (QTL) influences the variation of fasting triglyceride (TG) and high-density lipoprotein cholesterol (HDL-C) levels, we used a bivariate multipoint linkage analysis with 654 polymorphic markers in 99 white and 101 black families. The phenotypes were investigated under two conditions: at baseline and after a 20-week exercise training intervention. A maximum genome-wide bivariate LOD score of 3.0 (p = 0.00010) was found on chromosome 12q23-q24, located within the IGF1 gene (insulin-like growth factor 1, at 107 cM) for TG and HDL-C at baseline in whites. This bivariate linkage peak is considerably higher than the univariate linkage results at the same chromosome location for either trait (for TG, LOD = 2.07, p = 0.00108; for HDL-C, LOD = 2.04, p = 0.00101). The genetic correlations between baseline TG and HDL-C levels were -0.14 for the residual and -0.33 for the QTL components. Moreover, association analysis showed that TG, HDL-C, and IGF1 are significantly associated (p = 0.04). In conclusion, these results suggest that a QTL on chromosome 12q23-q24 influences the variation of plasma TG and HDL-C levels. Further investigation should confirm whether IGF1 or another nearby gene is responsible for the concomitant variation in TG and HDL-C levels.     

Meta-analysis of genome-wide linkage studies of asthma and related traits

Background

Asthma and allergy are complex multifactorial disorders, with both genetic and environmental components determining disease expression. The use of molecular genetics holds great promise for the identification of novel drug targets for the treatment of asthma and allergy. Genome-wide linkage studies have identified a number of potential disease susceptibility loci but replication remains inconsistent. The aim of the current study was to complete a meta-analysis of data from genome-wide linkage studies of asthma and related phenotypes and provide inferences about the consistency of results and to identify novel regions for future gene discovery.

Methods

The rank based genome-scan meta-analysis (GSMA) method was used to combine linkage data for asthma and related traits; bronchial hyper-responsiveness (BHR), allergen positive skin prick test (SPT) and total serum Immunoglobulin E (IgE) from nine Caucasian asthma populations.

Results

Significant evidence for susceptibility loci was identified for quantitative traits including; BHR (989 pedigrees, n = 4,294) 2p12-q22.1, 6p22.3-p21.1 and 11q24.1-qter, allergen SPT (1,093 pedigrees, n = 4,746) 3p22.1-q22.1, 17p12-q24.3 and total IgE (729 pedigrees, n = 3,224) 5q11.2-q14.3 and 6pter-p22.3. Analysis of the asthma phenotype (1,267 pedigrees, n = 5,832) did not identify any region showing genome-wide significance.

Conclusion

This study represents the first linkage meta-analysis to determine the relative contribution of chromosomal regions to the risk of developing asthma and atopy. Several significant results were obtained for quantitative traits but not for asthma confirming the increased phenotype and genetic heterogeneity in asthma. These analyses support the contribution of regions that contain previously identified asthma susceptibility genes and provide the first evidence for susceptibility loci on 5q11.2-q14.3 and 11q24.1-qter.     

Genetic determination of osteoporosis: lessons learned from a large genome-wide linkage study

Osteoporosis is a common disease with strong genetic control. We performed an autosomal linkage scan in a large pedigree-based sample of 4,498 subjects for a composite osteoporosis phenotype that combines osteoporotic fracture (OF) and low bone mineral density (BMD). All of the subjects were U.S. Caucasians recruited in the Omaha area of Nebraska. Sex-specific linkage analyses and autosomal imprinting analyses were also conducted. For conventional linkage analyses in the total sample, we identified suggestive linkage on chromosomes 14q32 (LOD = 2.61), 7p14 (LOD = 2.42), and 11q25 (LOD = 2.09). In female subjects a significant linkage signal was detected on chromosome 14q22 (LOD = 3.53) and another two peaks were detected on chromosomes 7p14 (LOD = 3.07) and 9p21 (LOD = 2.29). Suggestive evidence of imprinted loci was found with paternally derived alleles on chromosomes 1q42 (LOD = 2.12) and 9q34 (LOD = 1.88). Some evidence of linkage to maternally derived alleles was found on chromosome 7q22 (LOD = 1.67). Our study provides new clues to osteoporosis genetic research and for the first time suggests that genomic imprinting effects may play a role in the etiology of osteoporosis.     

Genome-wide linkage and peak-wide association study of obesity-related quantitative traits in Caribbean Hispanics

Although obesity is more prevalent in Hispanics than non-Hispanic whites in the United States, little is known about the genetic etiology of the related traits in this population. To identify genetic loci influencing obesity in non-Mexican Hispanics, we performed a genome-wide linkage scan in 1,390 subjects from 100 Caribbean Hispanic families on six obesity-related quantitative traits: body mass index (BMI), body weight, waist circumference, waist-to-hip ratio, abdominal and average triceps skinfold thickness after adjusting for significant demographic and lifestyle factors. We then carried out an association analysis of the linkage peaks and the FTO gene in an independent community-based Hispanic subcohort (N = 652, 64% Caribbean Hispanics) from the Northern Manhattan Study. Evidence of linkage was strongest on 1q43 with multipoint LOD score of 2.45 (p = 0.0004) for body weight. Suggestive linkage evidence of LOD > 2.0 was also identified on 1q43 for BMI (LOD = 2.03), 14q32 for abdominal skinfold thickness (LOD = 2.17), 16p12 for BMI (LOD = 2.27) and weight (LOD = 2.26), and 16q23–24 for average triceps skinfold thickness (LOD = 2.32). In the association analysis of 6,440 single nucleotide polymorphisms (SNPs) under 1-LOD unit down regions of our linkage peaks on chromosome 1q43 and 16p12 as well as in the FTO gene, we found that two SNPs (rs6665519 and rs669231) on 1q43 and one FTO SNP (rs12447427) were significantly associated with BMI or body weight after adjustment for multiple testing. Our results suggest that in addition to FTO, multiple genetic loci, particularly those on 1q43 region, may contribute to the variations in obesity-related quantitative traits in Caribbean Hispanics.     

Heritability and genetic correlations explained by common SNPs for metabolic syndrome traits

We used a bivariate (multivariate) linear mixed-effects model to estimate the narrow-sense heritability (h(2)) and heritability explained by the common SNPs (h(g)(2)) for several metabolic syndrome (MetS) traits and the genetic correlation between pairs of traits for the Atherosclerosis Risk in Communities (ARIC) genome-wide association study (GWAS) population. MetS traits included body-mass index (BMI), waist-to-hip ratio (WHR), systolic blood pressure (SBP), fasting glucose (GLU), fasting insulin (INS), fasting trigylcerides (TG), and fasting high-density lipoprotein (HDL). We found the percentage of h(2) accounted for by common SNPs to be 58% of h(2) for height, 41% for BMI, 46% for WHR, 30% for GLU, 39% for INS, 34% for TG, 25% for HDL, and 80% for SBP. We confirmed prior reports for height and BMI using the ARIC population and independently in the Framingham Heart Study (FHS) population. We demonstrated that the multivariate model supported large genetic correlations between BMI and WHR and between TG and HDL. We also showed that the genetic correlations between the MetS traits are directly proportional to the phenotypic correlations.     

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.     

Age-stratified QTL genome scan analyses for anthropometric measures

With the availability of longitudinal data, age-specific (stratified) or age-adjusted genetic analyses have the potential to localize different putative trait influencing loci. If age does not influence the locus-specific penetrance function within the range examined, age-stratified analyses will tend to yield comparable results for an individual trait. However, age-stratified results should vary across age strata when the locus-specific penetrance function is age dependent. In this paper, age-stratified and age-adjusted quantitative trait loci (QTL) linkage analyses were contrasted for height, weight, body mass index (BMI), and systolic blood pressure on a subset of the Framingham Heart Study. The strata comprised individuals with data present in each of three age groups: 31-49, 50-60, 61-79. Genome-wide QTL analyses were performed using SOLAR. Over all ages, a linkage signal for height was detected on chromosome 14q11.2 near marker GATA74E02A (LOD for ages 31-49 = 2.38, LOD for ages 50-60 = 1.84, LOD for ages 61-79 = 2.45). Evidence of linkage to BMI in the 31-49 age group was found on chromosome 3q22 (GATA3C02, LOD = 2.89, p = 0.0003) at the same location as the signal for weight (LOD = 3.10, p = 0.0002). Linkage was also supported on chromosome 1p22.1 for BMI (LOD = 2.21, p = 0.0014) and weight (LOD = 2.47, p = 0.0007) in the 31-49 age group. Our age-stratified results suggest that QTL that are expressed over long periods of time and affecting multiple, correlated traits may be identified using genome scan and variance-component methodology to help detect early and/or late gene expression.     

Genome‐wide linkage analysis for human longevity: Genetics of Healthy Aging Study

Clear evidence exists for heritability of human longevity, and much interest is focused on identifying genes associated with longer lives. To identify such longevity alleles, we performed the largest genome‐wide linkage scan thus far reported. Linkage analyses included 2118 nonagenarian Caucasian sibling pairs that have been enrolled in 15 study centers of 11 European countries as part of the Genetics of Healthy Aging (GEHA) project. In the joint linkage analyses, we observed four regions that show linkage with longevity; chromosome 14q11.2 (LOD = 3.47), chromosome 17q12‐q22 (LOD = 2.95), chromosome 19p13.3‐p13.11 (LOD = 3.76), and chromosome 19q13.11‐q13.32 (LOD = 3.57). To fine map these regions linked to longevity, we performed association analysis using GWAS data in a subgroup of 1228 unrelated nonagenarian and 1907 geographically matched controls. Using a fixed‐effect meta‐analysis approach, rs4420638 at the TOMM40/APOE/APOC1 gene locus showed significant association with longevity (P‐value = 9.6 × 10^?8). By combined modeling of linkage and association, we showed that association of longevity with APOEε4 and APOEε2 alleles explain the linkage at 19q13.11‐q13.32 with P‐value = 0.02 and P‐value = 1.0 × 10^?5, respectively. In the largest linkage scan thus far performed for human familial longevity, we confirm that the APOE locus is a longevity gene and that additional longevity loci may be identified at 14q11.2, 17q12‐q22, and 19p13.3‐p13.11. As the latter linkage results are not explained by common variants, we suggest that rare variants play an important role in human familial longevity.     

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.     

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.     

HDL Subspecies in Young Adult Twins: Heritability and Impact of Overweight

The association between abdominal obesity and atherogenic lipid profile emerges from complex interactions of genes and environment. We aimed to explore the heritability and effects of overweight on serum lipid profile (high‐density lipoprotein‐cholesterol (HDL‐C), HDL mean particle size, percentages of HDL_{2b, 2a, 3a, 3b, and 3c}, low‐density lipoprotein‐cholesterol (LDL‐C), LDL peak particle size and triglycerides (TGs)) in healthy, young adults. HDL‐C, LDL‐C, and TG were measured in 52 monozygotic (MZ) and 89 dizygotic (DZ) twin pairs, aged 23–32 years, chosen to represent a wide range of BMIs (17.6–42.9 kg/m²). Of them, 24 MZ and 26 DZ pairs were chosen at random for measurements of HDL mean and LDL peak particle sizes and percentages of HDL subspecies. The heritabilities of the lipid parameters adjusted for BMI were HDL‐C 73%, HDL mean particle size 56%, HDL subspecies 46–63%, LDL‐C 79%, LDL peak particle size 49%, and TG 64%. Genetic and environmental correlations between BMI and HDL‐C, LDL‐C, and TG were modest (0.3–0.4). Abdominal overweight (waist circumference ≥94 cm for males and ≥80 cm for females) associated with decreased HDL‐C, increased LDL‐C, and TG concentrations, smaller HDL mean particle size, lower HDL_2b, and higher HDL_3c percentages in both genders. Within MZ twins, controlling for genetic influences, within‐pair differences in HDL_3c percentage were associated with those in waist (r = 0.46, P = 0.032) and BMI (r = 0.51, P = 0.013). In conclusion, serum lipid parameters, including LDL peak and HDL mean particle sizes and HDL subspecies distribution are under strong genetic control. Overweight associated with significant lipid profile changes, particularly, small HDL_3c increased in overweight independent of genetic influences.