© 2000 American Heart Association, Inc.
Atherosclerosis and Lipoproteins |
A Locus Influencing Total Serum Cholesterol on Chromosome 19p
Results From an Autosomal Genomic Scan of Serum Lipid Concentrations in Pima Indians
From the Diabetes and Arthritis Epidemiology Section, Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, Ariz. Dr Pettitt is now at Sansum Medical Research Institute, Santa Barbara, Calif. Dr Fuller is now at the Department of Epidemiology and Public Health, University College London, London, England. Dr Imperatore is now at the Division of Diabetes Translation, Centers for Disease Control, Atlanta, Ga.
Correspondence to Robert L. Hanson, MD, MPH, National Institute of Diabetes and Digestive and Kidney Diseases, 1550 E Indian School Rd, Phoenix AZ 85014. E-mail rhanson{at}phx.niddk.nih.gov
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Abstract |
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Abstract—A genome-wide linkage study was analyzed to identify loci that influence serum lipid concentrations in Pima Indians. Linkage analyses were conducted for total cholesterol measured in 998 siblings from 292 nuclear families, for total triglycerides in 547 siblings from 188 families, and for high density lipoprotein (HDL) cholesterol in 590 siblings from 201 families. Genotypes were generated for 516 autosomal microsatellite markers. Multipoint variance components methods were used to assess linkage. The strongest evidence for linkage with total cholesterol was on chromosome 19p (lod score 3.89), in the vicinity of the marker D19S1034, which is near the low density lipoprotein receptor gene. The strongest evidence for linkage with HDL cholesterol was on chromosome 3q (lod score 2.64) near D3S3053. For triglycerides, the strongest evidence for linkage was on chromosome 2p near D2S1788 (lod score 1.70) and on chromosome 3p near D3S2406 (lod score 1.77). This genomic scan provides evidence for a locus influencing total cholesterol concentration on chromosome 19p. It also suggests a locus influencing HDL cholesterol on chromosome 3q.
Key Words: cholesterol • HDL cholesterol • linkage • genetics • triglycerides
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Introduction |
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Elevated total cholesterol and low HDL cholesterol concentrations are well-established risk factors for coronary heart disease. Elevated triglyceride level may also be a risk factor for cardiovascular disease.1 Family and twin studies indicate that genetic factors account for a substantial proportion of interindividual variability in serum lipid concentrations.2 3 However, genetic factors involved in lipid disorders have been identified mainly for monogenic familial disorders, and these account only for a small proportion of coronary heart disease.4 For most lipid abnormalities, the genetic determinants remain unknown. Given the complexity of lipid metabolism, genome-wide linkage studies are an appealing strategy to localize genes influencing serum lipid levels. Such studies, in contrast to those of candidate genes, can potentially detect regions that contain genes that influence lipid metabolism but whose function is currently unknown.
In the present study, genome-wide linkage analyses to detect loci influencing total cholesterol, HDL cholesterol, and total triglyceride concentrations were conducted among Pima Indians. The prevalence of diabetes mellitus among Pimas is very high, with >50% of individuals aged >40 years affected.5 Because diabetic individuals tend to have higher total cholesterol and triglyceride concentrations and lower HDL cholesterol concentrations than do nondiabetic persons, linkage analysis of serum lipids in this population is complicated by the high prevalence of diabetes. If the same loci influence lipid levels in diabetic and nondiabetic individuals, then power would be maximized by pooling these individuals. On the other hand, if loci that are important in diabetic persons are different from those in nondiabetic individuals (eg, as a result of a genetically determined response to hyperglycemia), then separate linkage analyses should be conducted. To determine the extent to which potential genetic determinants of serum lipid levels in diabetic persons overlap those in nondiabetic persons, familial resemblance of lipid levels among diabetic siblings, nondiabetic siblings, and siblings discordant for diabetes was assessed before performing linkage analysis.
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Methods |
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Subjects and Phenotypes
Since 1965, the Pima Indians from the Gila River Indian Community have participated in a longitudinal survey in which each resident aged
5 years is asked biennially to participate in a
standardized medical
examination.5 The examination
has included a 75-g oral glucose tolerance test. Participants have been
asked to fast overnight before the examination, but the glucose
tolerance test has still been administered even if the individual did
not fast. Serum samples were centrifuged at
1440g for 10 minutes at room
temperature and stored at -20°C for 1 to 5 days before
measurements. Total serum cholesterol was determined with a
colorimetric
method6 from 1965 to March
1992 and with an enzymatic method
subsequently.7 Total
triglyceride and HDL cholesterol concentrations
have been measured since 1993 by enzymatic
methods.8 9 Accuracy
of the lipid assays has been monitored and verified by the Centers for
Disease Control Laboratory Program Office, the College of American
Pathologists Surveys Program, or the American Association of
Bioanalysts. Interassay coefficients of variation were 4.83% for HDL
cholesterol, 5.20% for triglycerides, and
1.97% for total cholesterol by the enzymatic method and
2.47% for total cholesterol by the
colorimetric method. Genealogical information has also been collected, allowing for construction of pedigrees for family studies. In recent years, blood samples for DNA analysis have been collected. The institutional review board of the National Institute of Diabetes and Digestive and Kidney Diseases approved the study, and subjects gave informed consent.
For the present analyses, measurements of total
serum cholesterol, triglycerides, and HDL
cholesterol were taken from the last available examination
for each individual. For statistical procedures, all variables were
logarithmically transformed to reduce skewness. The logarithmically
transformed values were adjusted for age,
age2, and sex and, among diabetic
individuals, for the duration of diabetes by multiple linear regression
analysis. These adjusted values were standardized to a mean of
0 and an SD of 1 before genetic analyses. Separate regression
and standardization analyses were conducted for diabetic and
nondiabetic individuals, thereby adjusting for diabetes. Only
individuals aged 20 years were included in the
analyses.
Quantitative Genetic Analyses
Before performing linkage analysis,
quantitative genetic analyses were conducted to estimate the
extent of overlap between familial determinants of total
cholesterol, HDL cholesterol, and
triglyceride concentrations in nondiabetic individuals and
in diabetic individuals. Familial resemblance for each
phenotype was assessed among diabetic siblings, nondiabetic
siblings, and siblings discordant for diabetes. These analyses
included all nuclear families from the population study in which 2
siblings had been examined. This resulted in 1232 sibships composed of
3900 participants, of whom 1667 individuals had diabetes and 2233 did
not. Because data for HDL cholesterol and
triglyceride concentrations were available from only more
recent examinations and because triglyceride concentrations
were measured only in individuals who were fasting, families
informative for HDL cholesterol were a subset of those
informative for total cholesterol, and families informative
for triglycerides were yet a further subset. There were
1552 siblings in 553 families in the analysis of HDL
cholesterol concentrations and 1454 siblings in 526
families in the analysis of triglyceride
concentrations.
Statistical analyses were based on the variance
components method for quantitative
traits.10 This method
involves fitting a linear "mixed" model in which the phenotypic
variance is partitioned into various components. Typically, one
estimates the trait mean (µ), and the variance is partitioned into a
"polygenic" component
(
2G), which
reflects overall familial effects (both genetic and shared
environment), and an "environmental" component
(2E), which
reflects effects unique to the individual. Under the assumption of
multivariate normality, the phenotypic
variance-covariance matrix (
) for individuals in a pedigree
is
=
2G+I2E,
where is a matrix of the expected proportion of alleles shared
that are identical by descent (IBD) for pairs of relatives, and I is an
identity matrix. Parameters are estimated by maximum
likelihood methods, and the ratio of
2G to the total
variance
(2G+2E)
provides an estimate of the proportion of phenotypic variance
potentially attributable to additive genetic factors.
To test whether familial determinants of lipid
concentrations were the same in diabetic and nondiabetic individuals,
this model was extended to incorporate components of
covariance.11 In
these analyses, separate mean and variance
parameters were estimated in diabetic
(µd,
2Gd, and
2Ed, with
subscript d indicating diabetic) and nondiabetic
(µnd,
2Gnd, and
2End, with
subscript nd indicating nondiabetic) siblings, and a "polygenic"
covariance component between siblings discordant for diabetes
(Gnd+d) was also estimated (all
parameters were estimated simultaneously among
all siblings). The Gnd+d
parameter reflects the correlation in the trait between
pairs of siblings discordant for diabetes; a high value reflects shared
familial determinants between diabetic and nondiabetic persons. Under
the assumption that familial resemblance among siblings is due to
additive effects of polygenes, degree of overlap can also be quantified
by calculating the "correlation" (RG)
between the familial determinants in diabetic and nondiabetic persons
as a function of the estimated variance components
[RG=Gnd+d/(2Gd · 2Gnd)1/2].12
The null hypothesis of no overlap in familial determinants of lipid
concentrations (Gnd+d=0) was assessed by the
likelihood ratio test.
Linkage Analyses
As previously described, an autosomal genomic scan to
detect loci linked to type 2 diabetes and related traits has been
conducted in 1338 individuals in 112 extended pedigrees from this
population.13 In all 1338
individuals, 516 autosomal microsatellite markers were typed; the
proportion of samples that failed to amplify was not >15% for any
marker (median 2.5%). Median heterozygosity was 68%, and median
distance between adjacent markers was 6.4 cM (range 0 to 25.6 cM).
Marker allele frequencies and genetic map locations were estimated
in these subjects as previously
described.13 The Pima map
agreed well with the Marshfield map; one exception was
ATA9A05, which was originally
(but no longer) placed at the p-terminus of chromosome 19 in the
Marshfield map, which could not be mapped to chromosome 19 in the
present sample. Among the 1232 families with 2 siblings with
lipid measurements, 292 families had 2 siblings with total
cholesterol and genotypic data, providing 998 siblings; 201
families had 2 siblings with HDL cholesterol and
genotypic data, containing 590 siblings; and 181 families had 2
siblings with triglyceride and genotypic data containing
548 siblings.
Linkage analyses were conducted by the variance
components method.14 In this
method, the mixed model, described above, is extended to include a
monogenic component of variance
(2M) influenced by
a locus linked to the region of interest, in addition to
"polygenic"
(2G) and
"environmental"
(2E) components.
The phenotypic variance-covariance matrix is
=2G+
2M+I2E,
where is a matrix of the proportion of IBD alleles shared,
estimated from genotypic data, and and I are defined as above.
Multipoint estimates of IBD were obtained as described by Fulker et
al.15 At any point on the
chromosome, this method estimates the proportion of IBD alleles
shared as a weighted average of IBD at each individual marker.
Estimates of IBD for individual markers were obtained by the method of
Curtis and Sham,16 which was
implemented by use of the FASTLINK
program.17 This method uses
genotypic information from all relatives to infer IBD for sibling
pairs. To avoid the need for a more complex model to account for
phenotypic correlations among extended relatives, analyses of
phenotypic data were restricted to sibships.
Parameters were estimated by use of the MIXED
procedure of SAS (SAS Institute). Linkage was assessed by the
likelihood ratio test comparing the full model to one in which
2M was constrained
to equal 0. The lod score was calculated by dividing the likelihood
ratio test for linkage by
2 · loge(10).
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Results |
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Table 1
shows results of covariance
components analyses in families from the population study. For
total cholesterol, for example, the estimated additive
genetic component accounted for 48% of the total variance among
nondiabetic siblings, for 32% of the variance among diabetic siblings,
and for 37% of the variance among siblings discordant for diabetes.
All 3 traits were significantly
(P<0.0001) correlated among
siblings discordant for diabetes. Estimated correlations between
familial determinants in diabetic and nondiabetic siblings
(RG) were 0.96 for each trait, suggesting that
familial determinants of total cholesterol, total
triglyceride, and HDL levels are largely the same in
diabetic and nondiabetic individuals. Therefore, linkage
analyses were performed jointly in diabetic and nondiabetic
persons.
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Characteristics of subjects in the genomic scan are reported
in
Table 2. In 
40% of sibling pairs, both siblings had
diabetes, whereas in 20% of sibling pairs, both siblings were
nondiabetic, and 40% of sibling pairs were discordant for
diabetes.
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In
Table 3, all chromosomal regions with a lod score >1.18
(P<0.01, which is of
sufficient magnitude to replicate strong linkage signals seen in other
populations18 ) with total
cholesterol, triglycerides, or HDL
cholesterol are reported. The only region that reached a
lod score >3 was on chromosome 19p at the location of the marker
D19S1034 in the
analyses of total cholesterol. Multipoint linkage
results for chromosome 19 are shown in
Figure 1. The 1-lod support interval for the location of the
putative gene influencing total cholesterol covers the
region from 0 to 20 cM and includes the gene for the LDL receptor
(LDLR). The highest lod score for HDL occurred on chromosome 3q near
D3S3053. For total
triglycerides, the strongest evidence for linkage was on
chromosome 2p near D2S1788 and
on chromosome 3p near D3S2406.
Figure 2 shows the results of multipoint linkage
analyses for chromosomes 2 and 3. The 1-lod support interval
for the HDL linkage on chromosome 3q encompasses a 23-cM region from
162 to 185 cM. The 1-lod support interval for triglycerides
on chromosome 2p extends for 23 cM from 35 to 58 cM; that on chromosome
3p covers 30 cM from 76 to 106 cM. Additional regions with some
evidence for linkage were seen on chromosome 5 with
triglycerides and on chromosomes 7 and 20 with HDL
cholesterol
(Table 2
). To assess whether the effects of these loci
differed according to the presence of diabetes, regions shown in
Table 2 were analyzed by using an extension of the
covariance components model that estimates separate monogenic
components for diabetic siblings, nondiabetic siblings, and siblings
discordant for diabetes. There was no significant difference among the
monogenic components for any region
(P>0.05).
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Discussion |
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An autosomal genome-wide linkage study was analyzed to detect loci influencing serum concentrations of total cholesterol, HDL cholesterol, and triglycerides in Pima Indians. The results provide strong evidence (lod score 3.89) that a gene on chromosome 19p influences total cholesterol levels and weaker but suggestive evidence (lod score 2.64) for a locus influencing HDL cholesterol concentration on chromosome 3q. For triglyceride levels, linkage evidence was weaker; the highest lod scores were seen on chromosomes 2p and 3p (lod scores 1.70 and 1.77, respectively).
The present study has also examined the extent to which genetic determinants of lipid concentrations in diabetic persons overlap those in nondiabetic persons. Because the prevalence of diabetes among the Pimas is high, it is important to examine this potential overlap to determine whether separate or joint linkage analyses are indicated. This was assessed by estimating familial resemblance for each phenotype among nondiabetic siblings, diabetic siblings, and siblings discordant for diabetes. For all 3 phenotypes, resemblance among siblings discordant for diabetes was similar to that among siblings concordant for diabetes. This is consistent with the hypothesis that genetic determinants of lipid levels in nondiabetic persons and in diabetic persons are largely shared. Thus, linkage analyses were conducted by pooling diabetic and nondiabetic individuals, but with adjustment for diabetes. The adjustment for diabetes will generally enhance power to detect loci influencing lipid levels, unless the major genes influencing lipid levels also influence susceptibility to diabetes. This is unlikely, inasmuch as none of the regions identified as potentially linked with lipid levels showed linkage with diabetes in these families.13
The variance components method is a powerful tool for assessing genetic linkage. The method does not require specification of mode of inheritance, which makes it useful for analyzing complex traits for which the mode of inheritance is usually unknown, but it is somewhat less powerful than correctly specified parametric analyses. In addition, sibships rather than sibling pairs are analyzed, relaxing the assumption of independence among pairs of siblings inherent in sib-pair methods of linkage analysis. However, the method is potentially sensitive to individuals with extreme phenotypic values. To determine whether a few such individuals accounted for the present results, chromosomes showing linkage were reanalyzed after the exclusion of individuals whose trait values were >3 SDs from the mean; in each case, substantial evidence for linkage remained.
The variance components method assumes
multivariate normality, and statistical evidence for
linkage may be inflated if the trait distribution deviates radically
from a normal distribution.19
To reduce skewness, a logarithmic transformation was applied to each of
the lipid variables. One can also impose a normal distribution by
ranking individuals according to the quantitative trait and applying an
inverse gaussian transformation; when this procedure was applied to the
present data, results similar to those presented above were
obtained. This suggests that the present lod scores are not
inflated because of violations of the assumption of
multivariate normality. In the absence of such
violations, probability values associated with lod scores are well
approximated by a 
2 distribution with 1
df (with use of a 2-tailed test
for a small sample and a 1-tailed test for a large
sample).20 With this
assumption, the 1-tailed P
value associated with linkage of the normalized total
cholesterol concentration to chromosome 19p is 0.00002,
that associated with HDL cholesterol on chromosome 3q is
0.0004, that associated with triglycerides on chromosome 2p
is 0.0023, and that associated with triglycerides on 3p is
0.0033.
Criteria for statistical significance in genetic linkage studies have been controversial. For mendelian traits, a lod score >3.0 has traditionally been considered to represent a high probability of linkage, whereas a lod score of 2.0 to 3.0 is suggestive of linkage but is associated with an unacceptably high type I error to be considered conclusive. Although some authors have proposed more stringent criteria for complex traits,18 the criteria originally proposed for mendelian traits appear to be applicable to complex inheritance.21 By these criteria, the lod score of 3.89 observed on chromosome 19 for total cholesterol represents significant evidence for linkage, whereas the lod score of 2.64 on chromosome 3 is suggestive of a locus influencing HDL cholesterol. However, regardless of the magnitude of the lod score, it is possible for a result from a single study to be spurious, and the present results need to be replicated in other subjects to distinguish a statistical artifact from a true linkage.
The chromosome 19p region identified as linked with total cholesterol concentrations contains the LDLR gene. Because LDL particles transport most of the cholesterol in the plasma, total cholesterol concentrations largely reflect LDL cholesterol. A large number of rare mutations in the LDLR gene are responsible for the autosomal-dominant disorder familial hypercholesterolemia (MIM 143890). This fact and the known role of LDLR in lipid metabolism give rise to the hypothesis that more common polymorphisms in this gene may influence lipid levels. Consequently, a number of candidate gene studies have examined linkage and association of polymorphisms in the vicinity of LDLR with lipid phenotypes. Polymorphisms in the LDLR gene are associated with total or LDL cholesterol levels in some populations,22 23 but not in others.24 25 Weak evidence for linkage in this region has been observed with LDL cholesterol concentrations in Hutterites (lod score 0.8).23 Linkage has also been observed with LDL size distributions, which reflect atherogenicity of the LDL particles, in families with coronary artery disease (lod score 1.3)26 and in families in which the proportion of LDL cholesterol contained in small dense particles segregates in a mendelian fashion (lod score 4.1).27 In contrast, this region of chromosome 19 was not linked to LDL particle size or triglyceride concentrations in dizygotic female twins.28 Recently, genome-wide linkage analysis in Mexican American families suggested a locus influencing cholesterol concentration in LDL-1, a fraction containing large LDL particles, 16 cM centromeric from LDLR (lod score 2.3).29 None of these studies assessed linkage with total cholesterol concentration; nonetheless, they lend support to the hypothesis of a locus influencing lipid metabolism on chromosome 19p.
Although the LDLR gene is a strong positional candidate to influence cholesterol levels, the present findings could reflect other genetic elements in the region. Additional potential candidate genes in this region include those coding for the insulin receptor and the third component of complement (C3). Acylation-stimulation protein is a fragment of C3 that promotes clearance of lipoproteins from the circulation by increasing uptake of free fatty acids into the adipose tissue.
In this genomic scan, no region reached the level of significant linkage for HDL cholesterol concentrations, but a region on chromosome 3q showed a lod score of 2.64, which is suggestive of linkage. Complex segregation analyses suggest that there may be strong genetic influences on HDL levels,30 31 but linkage studies with candidate genes have not identified these determinants.30 A genomic scan of Mexican Americans did not show linkage of chromosome 3 with concentrations of subfractions of HDL cholesterol but identified strong evidence for linkage with concentrations of the 2a subfraction to chromosomes 8 and 15,32 neither of which showed evidence for linkage with total HDL cholesterol in the present study. The chromosome 3q region identified in the present study as linked to HDL cholesterol was also modestly linked to fasting insulin concentrations in nondiabetic Pimas (lod score 1.2).33 Low HDL concentration and low insulin sensitivity are features of the insulin resistance syndrome, and alteration of a common genetic pathway may be responsible for this association.34 Potential candidate genes in this region of chromosome 3q include peroxisome bifunctional enzyme, which is involved in peroxisomal fatty acid oxidation, and liver glucose transport protein-2.
In the present analysis, only weak evidence of
linkage for total triglycerides was detected. Although
serum triglyceride levels are
heritable,2 3 it is
unknown whether the genetic component comes from a large number of
genes with small effects or from 1 gene with large effects. The
region on chromosome 2p that was linked to triglyceride
levels in the present analyses is near the gene for apoB,
which was modestly linked to triglyceride concentrations in
dizygotic female twins (lod score
1.0),28 and is near a region
linked with serum leptin levels in Mexican Americans (lod score
5.0).35 A recent genomic scan
of serum triglyceride levels in Mexican Americans did not
detect linkage in any of the regions that were tentatively linked in
the present study but showed significant evidence for linkage (lod
score 3.9) on chromosome 15q, where there was no evidence for linkage
in the Pimas.36 Loci with
small or moderate effects are difficult to detect with linkage
analysis, and detection of such loci requires a larger sample
size than is available in the present study.
Fine-mapping studies and studies of candidate genes in the chromosome 19p region are required to identify the genetic elements responsible for the observed linkage with total cholesterol levels. Identification of the genetic mechanisms influencing lipid concentrations will help investigators to better understand lipid metabolism. This will improve understanding of the pathophysiology of the atherosclerotic process and, ultimately, may lead to better treatment and prevention of cardiovascular disease.
Electronic Database Information
Online Mendelian Inheritance in Man (OMIM),
http://www.ncbi.nlm.nih.gov/Omim (familial
hypercholesterolemia [MIM
143890]).
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Acknowledgments |
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We thank the members of the Gila River Indian Community for participating in these studies. We also thank Vickie Andre, Sonja Antone, and Linda Phillips for technical assistance and Dr Clifton Bogardus for advice and assistance. Costs of genotyping performed by the Marshfield Clinic were funded by contract with GlaxoWellcome Inc.
Received August 10, 2000; accepted September 1, 2000.
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