Genome-Wide Association Study Identifies ALDH7A1 as a Novel Susceptibility Gene for Osteoporosis
et al. (2010) Genome-Wide Association Study Identifies ALDH7A1 as a Novel Susceptibility Gene for
Osteoporosis. PLoS Genet 6(1): e1000806. doi:10.1371/journal.pgen.1000806
Genome-Wide Association Study Identifies ALDH7A1 as a Novel Susceptibility Gene for Osteoporosis
Christopher J. Papasian
Robert R. Recker
Michel Georges, University of Lie`ge, Belgium
Osteoporosis is a major public health problem. It is mainly characterized by low bone mineral density (BMD) and/or lowtrauma osteoporotic fractures (OF), both of which have strong genetic determination. The specific genes influencing these phenotypic traits, however, are largely unknown. Using the Affymetrix 500K array set, we performed a case-control genomewide association study (GWAS) in 700 elderly Chinese Han subjects (350 with hip OF and 350 healthy matched controls). A follow-up replication study was conducted to validate our major GWAS findings in an independent Chinese sample containing 390 cases with hip OF and 516 controls. We found that a SNP, rs13182402 within the ALDH7A1 gene on chromosome 5q31, was strongly associated with OF with evidence combined GWAS and replication studies (P = 2.0861029, odds ratio = 2.25). In order to explore the target risk factors and potential mechanism underlying hip OF risk, we further examined this candidate SNP's relevance to hip BMD both in Chinese and Caucasian populations involving 9,962 additional subjects. This SNP was confirmed as consistently associated with hip BMD even across ethnic boundaries, in both Chinese and Caucasians (combined P = 6.3961026), further attesting to its potential effect on osteoporosis. ALDH7A1 degrades and detoxifies acetaldehyde, which inhibits osteoblast proliferation and results in decreased bone formation. Our findings may provide new insights into the pathogenesis of osteoporosis.
Funding: This work was supported by the National Institute of Health (R01 AR050496, R21 AG027110, R01 AG026564, P50 AR055081, and R21 AA015973). The
study was also funded partially by from the National Natural Science Foundation of China (30570875), Xian Jiaotong University, and the Ministry of Education of
China; Huo Ying Dong Education Foundation, HuNan Province, and Hunan Normal University. The funders had no role in study design, data collection and
analysis, decision to publish, or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
. These authors contributed equally to this work.
Osteoporosis, characterized primarily by low bone mineral
density (BMD), is a major public health problem because it
increases susceptibility to low-trauma osteoporotic fractures (OF).
Hip fractures, which are the most common and severe form of OF,
are associated with high morbidity and mortality, as well as
tremendous health care expenditures . Due to an aging
population, the annual incidence of hip fractures worldwide is
predicted to be ,6.27 million by the year 2050, with an estimated
cost of ,$131.5 billion . The ultimate goal of osteoporosis
research is to reduce the incidence and prevalence of OF.
Genetic factors play an important role in susceptibility to
osteoporosis. Both BMD and OF have high genetic determinations
[2,3,4,5]. BMD has been identified as the major risk factor for
susceptibility to OF and is currently the predominant study
phenotype for osteoporosis. Variations in BMD account for
,5070% of the variation in total bone strength  and risk of
OF . Additional risk factors, including those not readily
quantifiable (e.g. bone microstructure  and cartilage
organization ), also contribute to the risk of OF. Most of genetic studies
of osteoporosis have focused primarily on the surrogate phenotype
BMD, whereas little effort has been expended on the study of OF
per se as a focal phenotype or on the relevance of genes associated
with BMD on OF . The major obstacle to this approach has
been assembling a homogeneous sample with a homogenously
defined OF type. Genetic factors associated with variations in
BMD and risk of OF overlap, to some extent, but are not all
Osteoporosis is a major health concern worldwide. It is a
highly heritable disease characterized mainly by low bone
mineral density (BMD) and/or osteoporotic fractures.
However, the specific genetic variants determining risk
for low BMD or OF are largely unknown. Here, taking
advantage of recent technological advances in human
genetics, we performed a genome-wide association study
and follow-up validation studies to identify genetic
variants for osteoporosis. By examining a total of 11,568
individuals from Chinese and Caucasian populations, we
discovered a susceptibility gene, ALDH7A1, which is
associated with hip osteoporotic fracture and BMD.
ALDH7A1 might inhibit osteoblast proliferation and
decrease bone formation. Our finding opens a new avenue
for exploring the pathophysiology of osteoporosis.
identical . The ultimate goal of osteoporosis research is to
reduce the incidence and prevalence of OF. Therefore, it is useful
to conduct genetic studies of OF per se, in conjunction with other
intermediate phenotypes (e.g. BMD) that influence the risk of OF.
This approach can be used to identify quantifiable measures for
early prevention and intervention before the adverse clinical
outcome, OF, actually occurs.
So far, several specific genes contributing to osteoporosis (i.e.
those impacting BMD or risk of OF) have been identified, such as
ESR1 with OF risk, COL1A1 and VDR with BMD and vertebral
fracture risk, OPG and LRP5 with BMD [10,11,12,13,14,15].
However, the majority of genetic variants that influence
osteoporosis remain unknown. With current high throughput SNP
genotyping platforms and our knowledge about the distribution
and correlation of SNPs in the human genome (e.g., haplotype
structure), genome-wide association study (GWAS) has proven
itself to be a feasible, powerful and effective approach for
identifying novel genes associated with complex phenotypes. Four
recent GWASs [12,13,16,17] have identified several specific genes
for osteoporosis. In the current investigation, based on significant
heritability of ,50% for OF [2,4], we utilized a GWAS to identify
genetic variants underlying susceptibility to osteoporosis that are
directly relevant to the risk of OF. Using the Affymetrix 500K
array set, we successfully genotyped a study population of 700
elderly Chinese Han subjects consisting of 350 cases with
homogeneous hip OF and 350 healthy matched controls. A
follow-up replication study was performed in an independent
Chinese sample consisting of 390 cases with hip OF and 516
controls. For SNPs that were identified for OF, we further
examined their relationships with hip BMD in two ethnic groups
(Chinese and Caucasians), involving additional 9,962 subjects, in
order to determine whether the genetic basis for their contribution
to the risk of OF might also be, at least partially, attributable to
their effects on variation in BMD.
GWAS Discovery Study
The study design included an initial exploratory stage in a
Chinese Han sample of moderate size and follow-up replication
and validation studies with much larger sample sizes in
independent Chinese Han and Caucasian samples. Table 1 details
the basic characteristics of the respective samples. In the GWAS
discovery stage, a total of 281,533 SNPs passed our quality control
criteria for GWAS analyses. A quantile-quantile (QQ) plot is
presented in Figure 1. The x2 distributions for the association tests
across the SNPs tested showed little evidence of overall systematic
bias (genomic inflation factor l = 1.02). The highest x2 was
consistent with the presence of true association. We further
performed the principal component analysis implemented in
EIGENSTRAT to guard against possible population stratification.
The first two principal components were not associated with case
status (P values.0.05), further indicating that it is very unlikely
that positive associations in this study would be attributable to
confounding due to population structure. The association analyses
by EIGENSTRAT confirmed, qualitatively, our main results and
consequently, the results of the EIGENSTRAT analyses are not
Table 2 lists the most promising results from GWAS analyses.
We identified five SNPs with P values,561026 by allelic
association analyses. After applying the Bonferroni correction for
multiple testing, a single SNP, rs13182402, reached a
genomewide significance level (P,1.7861027). SNP rs13182402 achieved
a P value of 8.5361029 in the allelic test (Bonferroni corrected
P = 2.4061023). The odds ratio (OR) was 2.94 (95% confidence
interval (CI): 2.024.30) for minor allele G. The frequency of the
G allele was 0.162 in cases, and 0.061 in controls. When all
covariates were considered simultaneously in a multivariate logistic
regression model, this SNP remained a significant predictor of OF
risk, independent of age, sex, height, and weight (P = 2.2161028).
Assessment of Genome-Wide Findings
Replication in Chinese. Replication analyses were
performed in an independent Chinese sample containing 390 cases
with hip OF and 516 controls. Of the ten genotyped SNPs in the
OF replication sample, two SNPs (rs13182402 and rs16894980)
Chinese replication sample
Abbreviations: M: male; F: female.
Data are shown as mean (standard deviation, SD).
were nominally significant (Table 2). However, considering the
effect direction, only SNP rs13182402 was successfully replicated
(P = 1.1061022) and the effect was in the same direction as in the
initial GWAS sample (OR: 1.66 for allele G, 95% CI: 1.12,2.43).
Combining the GWAS discovery and replication samples by
metaanalyses, rs13182402 achieved a P value of 2.0861029 with an
estimated OR of 2.25 (95% CI: 1.72,2.94).
BMD validation in Chinese and Caucasians. To further
explore the relationship between rs13182402 and osteoporosis risk,
we performed association analyses with hip BMD in Chinese and
Caucasian samples (Table 3). In the Chinese BMD sample,
rs13182402 was associated with reduced hip BMD values
(P = 2.3561022) and the effect size (b) was estimated to be
,0.04 for each copy of the minor allele. This was consistent with
its association with an increased risk of hip OF. The contribution
of rs13182402 to BMD variation was estimated to be ,0.68%.
Statistical significance of rs13182402 was consistently achieved
in the US-MidWest Caucasian samples (unrelated sample:
P = 1.9261022; related sample: P = 1.6061023), and the effect is
in the same direction as in the Chinese BMD sample. The b was
estimated to be 0.043 for each copy of the minor allele in the
unrelated sample. The contribution of this SNP to BMD variation
in the unrelated sample was estimated to be ,0.75%.
We further examined the association signal in the
USFramingham Caucasian sample. SNP rs13182402 was consistently
significantly associated with hip BMD in the US-Framingham
sample (P = 3.3861022).
We also examined the associations between rs13182402 and
spine BMD in the Chinese and Caucasian BMD samples.
However, no significant results were found (data not shown),
which might be due to the heterogeneity of BMD across different
skeletal sites .
Finally, using meta-analysis, we combined all of the BMD
validation results (one Chinese sample and three Caucasian
US-MidWest-unrelated sample 1,725
Number Allelesa MAF P valueb
0.062 2.3561022 20.040
0.098 1.9261022 20.043
Abbreviations: MAF, minor allele frequency.
aThe former allele represents the minor allele.
bP values were one tailed.
cThe estimation for SNP effect size was performed under additive model.
dThe P value from each sample set was combined based on the Stouffer
method to quantify the overall association significance.
samples) to yield a commonly used probability measure. The
statistical significance for rs13182402 was significantly improved
(P = 6.3961026). These findings, combined with the results of our
GWAS studies, lend strong support for the conclusion that
rs13182402 is associated with low hip BMD and increased risk
Fine Mapping for Gene Identification
Given the significant evidence for rs13182402, we imputed the
genotypes of SNPs located surrounding this SNP based on our
GWAS data and Asian HapMap data, and presented a regional
association plot in Figure 2. The most significantly associated SNP,
rs13182402 (GWAS: P = 8.5361029), is located 394 bp
downstream from exon 5 of the ALDH7A1 gene (aldehyde
dehydrogenase 7 family, member A1) on chromosome 5q31. According to
the FASTSNP program (http://fastsnp.ibms.sinica.edu.tw), a
change of ARG at rs13182402 may lead to removal of binding
sites for transcription factors RORalp and CdxA.
In this study, we first performed a GWAS and follow-up
replication on OF and identified a novel susceptibility gene
(ALDH7A1) that significantly impacts the risk for OF per se. Next,
we examined this genes relationship with hip BMD both in
Chinese and Caucasian populations, and this gene was consistently
associated with hip BMD even across ethnic boundaries. The
effect size on BMD was modest and lower than the effect size on
OF risk. One interpretation of this differential effect would be that
BMD is not the only risk factor for OF; other risk factors also
contribute to the risk of OF. It is consistent with and supports our
statement in the introduction. It might also be caused by the
differences in power between the relatively small hip OF samples
compared to the large BMD samples. In addition, because we
didnt have BMD measurements for the hip OF cases, we couldnt
adjust the OR for BMD to see if the risk would be attenuated by
the adjustment. However, regardless of this differential effect, the
significant association results we identified both for BMD and OF
risk strongly support the potential contribution of ALDH7A1 to the
pathogenesis of osteoporosis.
The ALDH7A1 gene encodes an enzyme of the acetaldehyde
dehydrogenase superfamily, which degrades and detoxifies
acetaldehyde generated by alcohol metabolism. Acetaldehyde
has been shown to inhibit osteoblast proliferation and to decrease
bone formation . In addition, previous studies have identified
that polymorphisms of the ALDH2 gene, another member of the
acetaldehyde dehydrogenase family, are significantly associated
with osteoporosis . Our findings, combined with the above
lines of evidence, suggest that ALDH7A1 might be a novel and
potential candidate gene contributing to the risk of osteoporosis.
Using the genotyped and imputed genotypes in our GWAS
sample of 700 Chinese, we examined the associations between hip
OF and the key SNPs identified in previous GWAS on
osteoporosis [12,13,16]. Table 4 summarizes the major results.
Only two SNPs in RANKL were confirmed to be associated with
hip OF in our sample, including rs9594759 (P = 0.020) and
rs9594738 (P = 0.045). The data provided may serve as a reference
for other investigators searching for replication for their GWAS
An apparent advantage of this study is that our GWAS sample
came from a homogenous population with well defined
homogeneous phenotype. The genomic control factor was quite close to
1.0 (l = 1.02) (expected under no population stratification) and,
analyses by EIGENSTRAT showed qualitatively supportive
results. Thus, our association results are unlikely to be plagued
by spurious associations due to population stratification. In
particular, since the significant associations with BMD are shown
in both Caucasian and Chinese samples, the results are even less
likely to be due to population stratification/admixture.
A potential limitation of our study is the relatively small size of
the GWAS sample and the replication sample, which might lead to
over estimation of the effect size for the significant SNPs identified.
However, hip fractures are the most severe OFs followed by high
mortality rates, making subjects recruitment difficult. It took us
several years to accumulate such a homogeneous hip OF sample.
This study represents the best we can do under current conditions
to identify genes for OF. Meanwhile, we are keeping the
recruitment of hip OF subjects. As a future direction, a new
GWAS needs to be implemented on a larger sample to identify
more comprehensively novel genes for OF. In addition, since
genetic and environmental backgrounds vary for different
populations, replication across a wide range of populations is
necessary to determine the generality of our findings to the
broader population, or to specific ethnic groups or populations
In summary, using data from over 11,500 individuals, we have
identified and validated ALDH7A1 as a novel susceptibility
candidate gene for osteoporosis. Further studies are warranted to
explore the generality of our findings for ALDH7A1 identified by
GWAS to other populations, and to determine the mechanisms by
which this gene and its products contribute to the pathogenesis of
Materials and Methods
The study was approved by the local institutional review boards
or the office of research administration of all participating
institutions. After signing an informed consent, all subjects
received assistance completing a structured questionnaire
including anthropometric variables, lifestyles, and medical history.
The study was initially performed with a GWAS discovery stage
for SNPs of potential significance for OF in a Chinese Han,
casecontrol sample. The significance of the SNPs identified in the
discovery stage was subsequently confirmed through replication
study in another independent Chinese case-control sample. For
SNPs identified for OF, we further examined their relationships
with hip BMD within/across ethnic groups in a Chinese unrelated
BMD sample and three independent Caucasian samples. Table 1
details the basic characteristics of the respective samples, with
additional descriptions below.
GWAS Discovery Sample
The sample for the initial GWAS consisted of 350 patients with
osteoporotic (low trauma) hip fractures (including 124 males and
226 females) and 350 elderly controls (including 173 males and
Current GWAS P value
Published GWAS P valuea
aP value reported here was the original P value in the discovery sample in each GWAS.
bhipBMD is the combined BMD at the femoral neck, trochanter and intertrochanter region.
cSPBMD: Spine BMD.
177 females). Since fractures at different skeletal sites may have
different underlying pathological mechanisms, we focused
exclusively on hip fractures in order to minimize potential clinical and
genetic heterogeneity of the study phenotype. All the subjects were
unrelated northern Chinese Han adults living in the city of Xian
and its neighboring areas. Affected individuals with low trauma
hip fractures were recruited from the affiliated hospitals and their
associated clinics of Xian Jiaotong University. Inclusion criteria
for cases were (i) onset age of hip OF.55 years, to make sure all
female subjects were postmenopausal, and the onset of OF was
largely due to decreased BMD; (ii) age,80 years to minimize the
effect due to age, since previous studies showed that approximately
half of females aged 80 years or older have fractures ; (iii)
fractures occurred with minimal or no trauma, usually due to falls
from standing height or less; (iv) the fracture sites were at the
femoral neck or inter-trochanter regions; (v) hip fracture was
identified/confirmed through diagnosis of orthopedic surgeons/
radiologists according to radiological reports and x-rays. Patients
with pathological fractures and high-impact fractures (such as due
to motor vehicle accidents) were excluded. Patients with chronic
diseases before the onset of HF were also excluded.
Healthy control subjects were enrolled by use of local
advertisements. They were geography- and age-matched to the
cases. Inclusion/exclusion criteria for controls were: (i) age at
exam must be .55 years, without any fracture histories (all female
controls were postmenopausal); (ii) subjects with chronic diseases
and conditions that might potentially affect bone mass, structure,
or metabolism were excluded. Diseases/conditions resulting in
exclusion included chronic disorders involving vital organs (heart,
lung, liver, kidney, brain), serious metabolic diseases (diabetes,
hypo- and hyper-parathyroidism, hyperthyroidism, etc.), other
skeletal diseases (Pagets disease, osteogenesis imperfecta,
rheumatoid arthritis, etc.), chronic use of drugs affecting bone metabolism
(e.g., hormone replacement therapy, corticosteroid therapy,
anticonvulsant drugs), and malnutrition conditions (such as chronic
diarrhea, chronic ulcerative colitis); (iii) subjects taking
anti-boneresorptive or bone anabolic agents/drugs, such as bisphosphonates
Chinese Replication Sample
For replication of our GWAS findings for hip OF, we used an
independent Chinese sample containing 906 unrelated Han
subjects (390 cases with hip OF and 516 controls). All subjects
were drawn from the same geographic area as the above GWAS
discovery sample, and the sample inclusion and exclusion criteria
for cases and controls were the same as those adopted in the
recruitment of the above GWAS sample.
For SNPs that were identified for OF, we further performed
validation analyses to evaluate their relevance with hip BMD (with
targeted experimental genotyping of candidate SNPs discovered in
the initial GWAS) in two ethnic groups, including a Chinese
sample and two US Mid-West Caucasian samples. We finally
performed in silico validation to compare the association signals of
our most promising GWAS results with those achieved in the
Framingham Heart Study (FHS) .
Chinese BMD Sample
The Chinese BMD sample contained 2,955 unrelated ethnic
Han adults. This sample came from Changsha, Hunan province,
which is more than 1,000 km from Xian where the sample for the
GWAS was recruited. The subjects were randomly selected from
an established and expanding database with BMD measurements.
The exclusion criteria were the same as those adopted in the
recruitment of healthy control subjects in the GWAS sample, and
have been detailed in our earlier publication .
USMidWest Caucasian BMD Samples
The US-MidWest BMD samples with a total of 4,054 subjects
consisted of two independent sample sets, including one sample of
unrelated subjects and the other sample of nuclear families, which
were all US Caucasians of Northern European origin living in
Omaha, Nebraska, and its surrounding regions in Midwestern
USA. They were normal healthy subjects defined by the same
exclusion criteria as above in Chinese samples. The unrelated
sample contained 1,725 subjects. The related sample contained
2,329 subjects from 593 nuclear families.
All hip BMD measurements for the above BMD samples were
obtained with dual-energy X-ray absorptiometry using the same
type of machine (Hologic 4500) under the same protocol defined
by the manufacturer (Hologic Inc., Bedford, MA, USA). The
machines were calibrated daily. The coefficients of variation (CV)
of the hip BMD measurements were 1.33% for Chinese and
1.40% for Caucasians, respectively.
US-Framingham BMD Sample
The US-Framingham BMD sample is from the Framingham
Osteoporosis Study, an ancillary study of the Framingham SNP
Health Association Resource (SHARe) data sets . Details and
descriptions about the Framingham Osteoporosis Study have been
previously reported . Both genotype and phenotype data were
downloaded from dbGaP database (http://www.ncbi.nlm.nih.
gov/sites/entrez?db = gap). Data download and usage was
authorized by SHARe data access committee (phs000007.v3.p2,
phs000078.v3.p2). We have the data on 2,953 phenotyped
Caucasian subjects, 448 from the Original cohort (160 men and
288 women) and 2,505 from the Offspring cohort (1,114 men and
1,391 women). The Original Cohort participants had BMD
measures by dual x-ray absorptiometry machine (Lunar DPX-L) at
the hip performed at exam 24. The Offspring Cohort participants
were scanned with the same machine at exam 6/7. As reported
before , the CV was 1.7% for femoral neck.
Genotyping and Quality Control
Genomic DNA was extracted from peripheral blood leukocytes
using standard protocols. The genome-wide scan was performed
using the Affymetrix Human Mapping 500K array set (Affymetrix,
Santa Clara, CA, USA) according to the Affymetrix protocol.
Data management and analyses were conducted using the
Affymetrix GeneChip Operating System. Genotyping calls were
determined from the fluorescent intensities using the DM
algorithm with a 0.33 P-value setting  as well as the
BRLMM algorithm .
Quality control procedures were as follows. First, only samples
with a minimum call rate of 95% were included. Due to efforts of
repeat experiments, all samples (n = 700) met this criteria and the
final mean BRLMM call rate reached a high level of 99.02%.
Second, out of the initial full-set of 500,568 SNPs, we discarded: 1)
SNPs with a call rate ,90% in the total sample (n = 54,845); 2)
those deviating from Hardy-Weinberg equilibrium (HWE) in
controls (P,0.001, n = 22,002); 3) those having a minor allele
frequency (MAF),0.05 in the total sample (n = 142,188).
Therefore, 281,533 SNPs were available for subsequent analyses.
Based on the initial GWAS results, we selected the 10 most
promising SNPs for subsequent genotyping in the Chinese hip OF
replication sample based on the following inclusion criteria: (i) P
values#561026 in the GWAS allelic association analyses (5
SNPs); (ii) P values between 561026 and 561025, with
neighboring SNPs having P values#1024 showing a consistent
trend of association (5 SNPs). Genotypes were obtained using
MALDI-TOF mass spectrometry on a Sequenom system
(Sequenom, Inc., San Diego, CA) with iPLEX assay . Primers were
designed using MassARRAY Assay Design 3.1 software.
Genotyping quality control procedures leading to SNP exclusion were
call rate ,90%, MAF,0.05 in the total sample and P,0.001 for
deviations from HWE in controls. The average call rate was
98.7% for the Sequenom system and the corresponding
consistency of genotyping (replication or concordance rates), as obtained
by duplication samples, was 99.8%. Nine of the ten genotyped
SNPs were qualified for subsequent association analyses.
The Chinese BMD sample was also genotyped using the
Sequenom system, which was the same as that used for the OF
replication sample. Genotyping of the two US-MidWest samples
was performed by a service company KBioscience (Herts, UK)
using a technology of competitive allele specific PCR (KASPar),
which is detailed at the website (www.kbioscience.co.uk). The
USFramingham sample was genotyped using approximately 550,000
SNPs (Affymetrix 500K mapping array plus Affymetrix 50K
For the GWAS analyses for OF risk, single-marker allelic
association analysis was performed by comparing SNP allele counts
among cases and controls with a x2 test. ORs with the corresponding
95% CIs were also computed. For the interesting SNPs identified by
allelic tests, we also used a multivariate logistic regression model to
examine associations with OF risk, taking into account potential
covariates such as age, sex, height, and weight. For the sex
chromosome analyses, the affymetrix platform does not assay the Y
chromosome. The X chromosome needs to be treated differently
from the autosomes since males have only one copy of the X
chromosome. As most loci on the X chromosome are subject to X
chromosome inactivation, it is reasonable to treat males as if they
were homozygous females, and then the assumption was the same as
tests for autosomes. All association statistical analyses were carried
out using HelixTree 5.3.1 software (Golden Helix, Bozeman, MT,
USA). We adjusted for multiple testing by adopting the conservative
Bonferroni correction. The genome-wide significance threshold was
set at a P value of less than 1.7861027 (0.05/281,533 SNPs that
passed our quality control check).
To correct for potential population stratification that may lead
to spurious association results, we estimated the inflation factor (l)
for the GWAS sample using a method of genomic control . l
was calculated as the median of the observed x2 statistics divided
by the median of the expected x2 statistics for the genome-wide
SNP set. This led to an l of 1.02. Results presented in this study
were based on adjusting x2 statistics by dividing each of them by
1.02. The data were also analyzed by the principal component
analyses implemented in EIGENSTRAT  for cross-checking
the association results while controlling for admixture.
For OF replication analyses, the same allelic association analysis
was performed by x2 tests. For BMD validation analyses,
significant parameters (P,0.05) such as age, sex, height and
weight were used as covariates to adjust for the raw BMD values.
For the unrelated samples, ANOVA was conducted to achieve the
association tests. ANOVA is a model free test and more robust
than assuming any genetic models. The independent variable was
the genotype, which was divided into three levels corresponding to
the three genotypes observed for each SNP (1,1; 1,2; 2,2). Since
ANOVA cant give the effect size, we estimated the effect size of
significant SNPs using the linear regression assuming the additive
model in SAS (SAS Institute Inc., Cary, NC). For the related
samples, we used the BMD residuals after adjustment to conduct
family-based association tests under an additive model using
FBAT program . FBAT is a powerful approach to handle
family sample, which tests for differences in probability of
transmission of a genotype from parents to offspring based on
phenotype. FBAT examines association within families, which is
not affected by population stratification bias. To quantify the
overall evidence of associations, we performed meta-analyses by
using the Mantel-Haenszel method to calculate the P values and
OR for the combined OF samples. For the BMD samples, we used
a weighted Z-score method to calculate the combined P values.
The individual Z-score (a standard normal deviate, the statistic
associated with a P value) was weighted by the square root of the
sample size of each sample. We added the individual weighted
Z-score together and divided by the square root of the total sample
size to obtain a combined Z-score and an associated combined
P value (Stouffer method) . If an individual result was
nonsignificant and gave no other useful data for calculation of a
Z-score, we set it as 0 to calculate the combined probability.
For the interested genomic regions, IMPUTE program  was
utilized to impute the genotypes of all SNPs located in the regions
based on Asian HapMap data. SNPTEST  was used to test for
associations between the imputed SNPs and OF. SNAP was used
to depict the regional association plot .
We thank the Framingham Heart Study and the Framingham SHARe
project, which are conducted and supported by the National Heart, Lung,
and Blood Institute (NHLBI) in collaboration with Boston University. The
Framingham SHARe data used for the analyses described in this
manuscript were obtained through dbGaP (phs000007.v3.p2,
phs000078.v3.p2). This manuscript was not prepared in collaboration
with investigators of the Framingham Heart Study and does not necessarily
reflect the opinions or views of the Framingham Heart Study, Boston
University, or the NHLBI.
Conceived and designed the experiments: HWD. Performed the
experiments: YG LJT SFL TLY XDC FZ YC FP HY ZXZ QZ CQ
SSD XHX SLL XLW XL YL. Analyzed the data: TLY XL YFG.
Contributed reagents/materials/analysis tools: QT XZZ LSZ ML JTW
TW RRR XPS JC. Wrote the paper: YG. Manuscript writing revision:
BD, CJP, JH.
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