Association of Common Genetic Variants with Lipid Traits in the Indian Population
et al. (2014) Association of Common Genetic Variants with Lipid Traits in the Indian
Population. PLoS ONE 9(7): e101688. doi:10.1371/journal.pone.0101688
Association of Common Genetic Variants with Lipid Traits in the Indian Population
Gagandeep Kaur Walia 0
Vipin Gupta 0
Aastha Aggarwal 0
Mohammad Asghar 0
Frank Dudbridge 0
Nicholas Timpson 0
Nongmaithem Suraj Singh 0
M. Ravi Kumar 0
Sanjay Kinra 0
Dorairaj Prabhakaran 0
K. Srinath Reddy 0
Giriraj Ratan Chandak 0
George Davey Smith 0
Shah Ebrahim 0
Ludmila Prokunina-Olsson, National Cancer Institute, National Institutes of Health, United States of America
0 1 South Asia Network for Chronic Disease (SANCD), Public Health Foundation of India (PHFI) , New Delhi , India , 2 Department of Anthropology, University of Delhi , Delhi , India , 3 Department of Anthropology, Rajiv Gandhi University , Itanagar, Arunachal Pradesh , India , 4 Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine , London , United Kingdom , 5 School of Social and Community Medicine, University of Bristol , Bristol , United Kingdom , 6 Centre for Cellular and Molecular Biology , Hyderabad, Telangana , India , 7 Centre for Chronic Disease Control , New Delhi , India , 8 Public Health Foundation of India , New Delhi , India
Genome-wide association studies (GWAS) have been instrumental in identifying novel genetic variants associated with altered plasma lipid levels. However, these quantitative trait loci have not been tested in the Indian population, where there is a poorly understood and growing burden of cardiometabolic disorders. We present the association of six single nucleotide polymorphisms in 1671 sib pairs (3342 subjects) with four lipid traits: total cholesterol, triglycerides, high density lipoprotein cholesterol (HDL-C) and low density lipoprotein cholesterol (LDL-C). We also investigated the interaction effects of gender, location, fat intake and physical activity. Each copy of the risk allele of rs964184 at APOA1 was associated with 1.06 mmol/l increase in triglycerides (SE = 0.049; p = 0.006), rs3764261 at CETP with 1.02 mmol/l increase in both total cholesterol (SE = 0.042; p = 0.017) and HDL-C (SE = 0.041; p = 0.008), rs646776 at CELSR2-PSRC1-SORT1 with 0.96 mmol/l decrease in cholesterol (SE = 0.043; p = 0.0003) and 0.15 mmol/l decrease in LDL-C levels (SE = 0.043; p = 0.0003) and rs2954029 at TRIB1 with 1.02 mmol/l increase in HDL-C (SE = 0.039; p = 0.047). A combined risk score of APOA1 and CETP loci predicted an increase of 1.25 mmol/l in HDL-C level (SE = 0.312; p = 0.0007). Urban location and sex had strong interaction effects on the genetic association of most of the studied loci with lipid traits. To conclude, we validated four genetic variants (identified by GWAS in western populations) associated with lipid traits in the Indian population. The interaction effects found here may explain the sex-specific differences in lipid levels and their heritability. Urbanization appears to influence the nature of the association with GWAS lipid loci in this population. However, these findings will require replication in other Indian populations.
Competing Interests: The authors have declared that no competing interests exist.
Coronary heart disease is projected to be the leading cause of
death for adult Indians by 2020  due to rising prevalence of
cardiometabolic disorders [2,3]. Plasma lipid concentrations are
established risk factors for coronary artery disease (CAD)  and
are also targets for therapeutic interventions . While
genomewide association studies (GWAS) have been instrumental in
identifying the quantitative trait loci (QTL) associated with altered
levels of plasma lipids , these new discoveries require
validation in different population groups in order to understand
their wider potential for application and clinical benefits.
Only two previous validations of a limited sub-set of GWAS
lipid findings have been reported for Indian populations [10,11].
During the discovery and replication phases, samples from the
LOLIPOP cohort have been widely used to validate GWAS loci
for Indian populations, but this cohort comprises Indians residing
in the UK and demonstrated a replication rate of 35% .
Further, considerable Asian/European differences in lipid profiles
have been reported for Asian Indians exhibiting an adverse lipid
pattern consisting of low high density lipoprotein cholesterol
(HDL-C) and high triglycerides irrespective of diabetic status .
Moreover, none of the published reports addressed the complexity
of numerous endogamous groups where the average allele
frequency differentiation across different groups is known to be
3-fold greater than that observed in European population groups
. This indicates a gap in the understanding of the aetiology of
lipid traits in Indian populations.
In addition to plasma lipids, other risk factors (e.g. obesity,
diabetes and hypertension) are independently and interactively
associated with increased risk of cardiovascular diseases 
which are further associated with dyslipidemia . Gottesman
and colleagues  investigated the overlap of genetic variants
related to cardiometabolic traits and reported 44 positional genes
that have pleiotropic effects. With these findings in mind, we
hypothesize that dyslipidemia and metabolic phenotypes such as
hyperglycemia, hypertension and anthropometric traits have a
common genetic basis.
In our previous study, we had reported on association analysis
of five lipid-related QTLs in the Indian population . Since our
earlier report, a genome-wide meta-analysis  has reported 95
loci associated with lipid levels with an impact in three
nonEuropean populations including South Asians. Simultaneously, a
non coding genetic variant in the SORT1 gene was observed that
lead to clinical phenotypes, thus suggesting a novel regulatory
pathway . Further, a genome-wide meta-analysis found five
new loci associated with CAD in European and South Asian
populations . In the present study, we raise the following
questions: (i) are lipid-related QTLs discovered since our earlier
study also associated with altered plasma lipid levels in Indian
populations? and (ii) are these genetic loci associated with other
cardiometabolic traits in Indians? Answering these questions will
help in determining whether cardiometabolic traits have a
common pathophysiology across different population groups.
The ethical approval for the Indian Migration Study (IMS) was
attained from All India Institute of Medical Sciences (AIIMS),
New Delhi, India (reference number A-60/4/8/2004).
Preinformed written consent was obtained from each participant
before beginning the data collection.
The present study was carried out using trait data and DNA
from the IMS where migrant and non-migrant factory workers
and their co-resident spouses were recruited along with their
ruraldwelling sibs [20,21]. The fieldwork for the IMS took place from
20052007 in four factories located in different cities of India
(Lucknow, Nagpur, Hyderabad and Bangalore).
Age (in years)
Total cholesterol (mmol/l)
High Density Lipoprotein- Cholesterol (mmol/l)
Low Density Lipoprotein- Cholesterol (mmol/l)
Systolic Blood Pressure (mmHg)
Diastolic Blood Pressure (mmHg)
Fasting Glucose (mmol/l)
Fasting Insulin (mU/l)
Body mass Index (Kg/m2)
Waist Circumference (cm)
% Body Fat
Average Daily Fat Intake (g/day)
Total Physical Activity per day (MET hrs/day)
All values are Mean 6 SD; P represents p values on comparison of males and females by T-test.
Phenotyping details are described in File S1. Briefly, blood
pressure, height, weight, waist and hip girth and skin folds were
measured on the sib-pairs in the same clinic by trained clinicians
and the % body fat was derived from the skin folds. Data on diet
and physical activity were recorded on interviewer-administered
questionnaires. Fasting blood samples were collected from the
participants and the time of the last meal was recorded. Serum and
plasma samples were used for generating data on glycemic and
Genotyping and quality control
Genotyping was performed during 20112012 using the
Fluidigm platform with single-plex 96.96 chips wherein 96
established GWAS single nucleotide polymorphisms (SNPs)
related to cardiometabolic traits were analyzed. Two pairs of
duplicates and negative controls (water) were run with every 96
samples for quality control purposes. The genotyping success rate
was .95% and duplicate samples had .99% concordance. Out of
96 SNPs, fourteen loci were selected from three major studies on
lipid levels [8,9] and CAD . The limited loci were selected
from these studies based on their biological importance and
pvalues (#1610240 for lipid loci and ,161028 for CAD loci). Out
of the 14 SNPs genotyped, nine passed the quality control during
data cleaning process and finally six loci were found to be in
Hardy-Weinberg equilibrium (HWE) (Table S1 in File S1) for
which the results are presented.
Sample Size and power calculation
We analyzed 1671 sib pairs (3342 individuals) after excluding: (i)
singletons (ii) cousin/friend pairs (iii) pairs with one or both sibs
having missing phenotypes (iv) pairs with one or both sibs having
missing genotyping data on .7 SNPs (v) pairs where one or both
sibs self-reported cardiovascular diseases to avoid phenotypic
heterogeneity that could cause distorted relationships with lipid
A C EC ILP P T
traits. Power estimates were derived using the genetic power
calculator using option QTL association for sibships and
singletons . Given the minor allele frequency (MAF) of
21% (minimum MAF in IMS) and the sample size of 1671
sibpairs, this study had 80% power at a = 0.05 to detect a QTL
explaining 1% variation of a trait. Sex-specific associations were
estimated among 632 male and 364 female sib-pairs.
After log transformation of skewly distributed variables (see File
S1), the association analysis was done using an orthogonal
familybased model described by Fulker et al.  assuming an additive
model of inheritance and considering a sib-pair as the unit of
analysis (described in File S1). We applied multi-level models
adjusted for age, sex, site (i.e. city) and location (i.e. rural/urban)
for analyses on all quantitative traits because these covariates were
associated with various outcomes in the study population and
differences were found across the sites and locations . Since
physical activity and fat intake are important determinants of the
lipid profile , we also adjusted for these two variables when
estimating the associations. Association of the six selected loci was
estimated for four lipid traits [total cholesterol, triglycerides,
HDLC and low density lipoprotein cholesterol (LDL-C)] and also for
other metabolic traits related to obesity [body mass index (BMI),
waist-hip ratio (WHR), waist circumference (WC) and %body fat],
hypertension [systolic blood pressure (SBP) and diastolic blood
pressure (DBP)] and diabetes (fasting glucose and fasting insulin)
after adjusting for lipid traits and also for WHR in the case of
BMI, to detect the independent associations. Correction for
multiple testing was not applied for lipid traits as the studied SNPs
are established loci [8,9,19], whereas for all other metabolic traits
inferences were made on the basis of corrected a (value = 0.0083)
based on a Bonferroni correction  for six tests.
Sex-specific associations were also examined given prior
evidence for dimorphic patterns of association [8,28]. We also
tested for interaction effects by sex, location, fat intake and
physical activity by including interaction terms within the fixed
effect component of the Fulker association model (see details in
File S1). Stratified analysis by location, fat intake and physical
activity could not be performed due to limited sample size
available in these groups.
To estimate the combined effect of loci on lipid levels, risk scores
were calculated using loci associated with each of the lipid traits
examined in the present study. Weighted risk scores (trait specific b
coefficients as weights) based on associated loci observed  were
fitted into the Fulker model for estimating within sib-pair effects.
Since additional samples for estimating the effect of risk score were
not available, the present data set was divided into two random
halves representing the discovery and validation samples to
validate the weighted risk scores.
Results and Discussion
Over 100 SNPs associated with altered plasma lipid levels have
been discovered using GWAS . Considering that these
studies were mostly conducted in populations of European descent
and that the minor alleles and their frequency, haplotype
background and environmental influences vary across ethnic
groups , we investigated the role of these loci on four lipid and
other traits that predict cardiovascular disease risk in Indian
population. Validation of the effects of GWAS loci will likely be
more valuable in populations such as Asian Indians  that have
high disease burden and where conducting GWAS is a difficult
task. Table S2 in File S1 shows the comparison between the effect
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alleles and their frequency observed in European populations and
that observed in our study samples and highlights the considerable
variation between them. However, the allele frequencies we
observed were consistent with those reported for Gujarati Indians
living in the Houston (GIH) HapMap database.
The general characteristics of the study population and outcome
variables are summarized in Table 1. Significant differences were
found between males and females for various cardiometabolic
traits, except for total cholesterol and fasting glucose (Table 1).
Association of six loci with lipid levels
In an earlier report, rs662799 at APOA5, rs10503669 at LPL,
rs780094 in GCKR, rs562338 in APOB and rs4775041 in LIPC
were validated in the present study population10. In the current
analyses, we found associations between genetic variants on/near
four loci (APOA1, CETP, CELSR2-PSRC1-SORT1 and TRIB1) and
the four lipid traits in the Indian population (Table 2). Although
the directions of associations were consistent with that reported
worldwide, the effect sizes in the Indian population were larger
than that observed for European populations but consistent with
other Asian populations (Table S3 in File S1). Of these, rs964184
at APOA1 locus was associated with 1.06 mmol/l higher
triglycerides (SE = 0.049; p = 0.006); rs3764261 at CETP with
1.02 mmol/l higher total cholesterol (SE = 0.042; p = 0.017) and
1.02 mmol/l higher HDL-C (SE = 0.041; p = 0.008); rs646776 at
CELSR2-PSRC1-SORT1 with 0.96 mmol/l lower total cholesterol
(SE = 0.043; p = 0.0003) and 0.15 mmol/l lower LDL-C
(SE = 0.043; p = 0.0003) and rs2954029 at TRIB1 with
1.02 mmol/l higher HDL-C (SE = 0.039; p = 0.047) levels.
Apolipoprotein A-1 is the major protein component of HDL
and promotes cholesterol efflux from tissues to the liver for
excretion. The APOA1 locus was reported to be associated with
increased triglycerides and lower HDL-C in the discovery phase of
various studies . In subsequent GWAS and meta-analyses, the
APOA1 locus was confirmed to be associated with higher
triglycerides, total cholesterol, LDL-C and lower HDL-C levels
in Europeans . The association of APOA1 variants with higher
triglyceride levels has also been established in Tibetans  as well
as in Punjabi and US cohorts . We have also observed
significant association of this locus with higher triglyceride levels in
the present analyses.
The CETP locus codes for cholesteryl ester transfer protein that
facilitates the transfer of cholesteryl esters and triglycerides
between lipoproteins. CETP was found to be associated with high
HDL-C in GWAS discovery , which was further replicated
among Europeans , Americans  and Punjabi cohorts
[11,35] and with higher total cholesterol levels among Caucasians
. Lower triglycerides and LDL-C in a European GWAS
metaanalysis were also observed to be associated with CETP . In the
present study, we validated its association with higher total
cholesterol and HDL-C levels.
The third locus is mapped near the CELSR2-PSRC1-SORT1
gene cluster and emerged from a GWAS of LDL-C conducted
among British population . Its association with lower LDL-C
levels was also replicated in Austrians  and Pakistanis ; and
with high total cholesterol in Netherland population . In the
present study, CELSR2-PSRC1-SORT1 was associated with lower
levels of total cholesterol and LDL-C.
The TRIB1 locus codes for tribbles homologue 1 protein that
regulates the activation of mitogen activated protein kinases. The
association of this locus was first reported to be associated with
triglycerides  and subsequently with low total cholesterol,
LDL-C and high HDL-C in European population [8,41]. Here,
we observed its association with higher HDL-C levels, which is in
agreement with that seen for Europeans. In contrast, the TRIB1
locus was associated with lower HDL-C levels in a Danish
Since lifestyle factors, especially diet and physical activity, are
strongly associated with individual serum lipid profiles ,
dietary daily fat intake and physical activity (total MET score)
were included as additional covariates to explore the possible
associations of studied QTLs. In the studied population, these
adjusted analyses did not alter the direction or effect size
compared with the unadjusted analyses of these two covariates
(Table S4 in File S1).
The cumulative effect of genetic variants for lipids is known to
be associated with subclinical and clinical cardiovascular outcomes
. In the present study, multiple loci were associated with
HDLC and total cholesterol, but the directions of the effects were same
only for SNPs associated with HDL-C (Table 2). Thus, an attempt
was made to estimate the combined effect of the two significant
loci (rs2954029 at TRIB1 and rs3764261 at CETP) on HDL-C
levels. The weighted risk score was associated with a 1.25 mmol/l
higher HDL-C level per risk alleles at both variants (SE = 0.312;
p = 0.0007) as opposed to a 1.02 mmol/l increase that could be
explained by independent SNPs.
Association of six loci with related metabolic traits
We further investigated these GWAS loci related to lipids for
their association(s) with other metabolic traits which would help in
identifying the causal pathways that are common to these
outcomes. While there are sufficient epidemiological and clinical
evidence that support the relationship among dyslipidemia,
cardiovascular disease, diabetes, obesity and hypertension; the
common genetic mechanisms underlying these diseases are not
well established . Evidence of weak associations between lipid
related genetic variants in LPL and GCKR have been reported
earlier with hypertension and variants in LPL with fasting glucose,
fasting insulin and systolic blood pressure . In the present
study, three out of the six investigated loci were associated with
metabolic disorders (Tables S5S7 in File S1). While performing
association analyses, adjustments were made for lipid traits (in
addition to age, sex, site and location) to avoid bias that could
occur due to phenotypic heterogeneity.
Of interest was that the two loci APOA1 and TRIB1 that affected
HDL-C levels also influenced waist circumference. We noted an
overlapping association between lipid levels and waist
circumference, which would point towards a common pathophysiology
between lipids and obesity traits. In addition, we found a weak
association between the PDGFD locus and diastolic blood pressure,
which echoes the pattern of association with other traits in a
previous study  that found that PDGFD was implicated in
variety of functions, especially angiogenesis. Recently, Schierer
and colleagues  in a similar attempt reported that CETP was
associated with a decrease in systolic blood pressure (b = 20.08,
p = 0.002) among Asian normoglycemic controls.
However, these loci need to be assessed in a larger set of samples
in order to draw more meaningful inferences, as none of the
genetic variants retained the association after correction for
Sex-specific association of six loci related to lipid levels
There is evidence that point towards sex heterogeneity in the
association of lipid-related loci with lipid parameters . We
found sex-specific associations with various lipid traits (Table 3).
Out of the four loci that were associated in the combined analyses,
CETP was associated with 1.05 mmol/l higher HDL-C
(SE = 0.071; p = 0.001) and CELSR2-PSRC1-SORT1 was
associated with 0.94 mmol/l lower triglycerides (SE = 0.081; p = 0.074),
0.95 mmol/l lower total cholesterol (SE = 0.076; p = 0.007) and
0.15 mmol/l lower LDL-C (SE = 0.072; p = 0.033) among male
sib-pairs only. On the other hand, APOPA1 was associated with
1.05 mmol/l higher triglycerides (SE = 0.089; p = 0.015) and
TRIB1 with 1.04 mmol/l higher HDL-C (SE = 0.077; p = 0.007)
among female sib-pairs only. In addition, LIPA was associated with
1.03 mmol/l higher HDL-C (SE = 0.078; p = 0.041) only in
female sib-pairs which did not emerge in the combined analyses.
We previously also reported sex-specific associations for lipid traits
 and now postulate that these findings might explain the sex
differences in lipid levels and their heritability.
The exploratory interaction analyses provide evidence that the
genetic effects of all six loci were influenced by gender and these
associations were consistent even after adjustments for fat intake
and physical activity (Table 3). Modifications in the genetic effects
of two loci was seen where the effects were stronger among males
in the case of APOA1 with triglycerides (b = 0.168, SE = 0.051,
p = 0.001) and CELSR2-PSRC1-SORT1I with total cholesterol
(b = 20.135, SE = 0.045, p = 0.003) and LDL-C (b = 20.099,
SE = 0.046, p = 0.030). In addition, a few conditional associations
with sex were found, such as association of LIPA with HDL-C
(b = 20.100, SE = 0.033, p = 0.002) (Table 3) that did not
originate in main effects.
Effects of environmental factors on lipid loci
Rural to urban migration has been suggested to be associated
with increased fat intake and reduced physical activity . Thus,
we tested for effect modification by location, fat intake and
physical activity while allowing for the main effects of four loci that
were associated with the lipid traits. Genetic associations of four
loci with lipids was found in urban dwellers compared to their
rural sibs after adjusting for daily fat intake and physical activity
(Table 4), suggesting interaction. The genetic effect of APOA1 on
triglycerides (b = 0.147, SE = 0.044, p = 0.001) and CETP on total
cholesterol (b = 0.110, SE = 0.035, p = 0.002) increased while
interacting with location when compared to the main effects (see
Table 2). Further, conditional associations with urban location
were found, such as the association of LIPA with total cholesterol
(b = 0.082, SE = 0.030, p = 0.006) which was not evident in the
Similarly, in comparison to the main effects (Table 2), reduction
in the genetic effects of AOPA1 on triglycerides (b = 0.107,
SE = 0.052, p = 0.040) and CETP on total cholesterol (b = 0.097,
SE = 0.041, p = 0.018) were seen in people consuming high dietary
fat after adjusting for physical activity (Table 4). Further,
conditional associations with dietary fat was seen for CETP on
LDL-C (b = 0.085, SE = 0.041, p = 0.042) and TRIB1 on total
cholesterol (b = 0.114, SE = 0.038, p = 0.003) and LDL-C
(b = 0.111, SE = 0.039, p = 0.004) which were absent in the main
The genetic effect of TRIB1 on HDL-C (b = 0.087, SE = 0.038;
p = 0.021) was found to be stronger among physically active
participants (Talbe 4) than the main effects (Table 2) after
adjusting for fat intake. A conditional association of LIPA on
triglycerides (b = 20.077, SE = 0.033; p = 0.021) was also seen
among physically active individuals (Table 4).
To conclude, we confirm that four previously discovered QTLs
in Europeans also influence lipid levels in the Indian population.
Two of these loci (TRIB1 and CELSR2-PSRC1-SORT1) have been
validated in the Indian population for the first time. However, the
present findings will need to be replicated in larger samples.
Sexspecific associations were also observed in the studied population
along with strong interaction effects for all six loci studied. Genetic
associations with lipid traits were stronger in urban dwellers
compared to their rural sibs, suggesting interaction. Some
evidence was also seen for interaction by dietary fat intake and
physical activity on the genetic association of lipid traits.
File S1 Supporting Information containing details of
methodology and Tables S1S7.
We are highly grateful to Indian Migration Study group, study participants
and field staff for conducting the migration study.
Conceived and designed the experiments: GKW VG SE GDS SK DP
KSR GRC. Performed the experiments: GKW VG AA MA NSS MRK.
Analyzed the data: GKW VG FD. Wrote the paper: GKW VG FD NT SK
GRC GDS SE.
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