Apolipoprotein M Gene (APOM) Polymorphism Modifies Metabolic and Disease Traits in Type 2 Diabetes
et al. (2011) Apolipoprotein M Gene (APOM) Polymorphism Modifies Metabolic and Disease Traits in Type 2
Diabetes. PLoS ONE 6(2): e17324. doi:10.1371/journal.pone.0017324
Apolipoprotein M Gene (APOM ) Polymorphism Modifies Metabolic and Disease Traits in Type 2 Diabetes
Jun-Wei Zhou 0 1
Stephen K. W. Tsui 0 1
Maggie C. Y. Ng 0 1
Hua Geng 0 1
Sai-Kam Li 0 1
Wing-Yee So 0 1
Ronald C. Ma 0 1
Ying Wang 0 1
Qian Tao 0 1
Zhen-Yu Chen 0 1
Juliana C. N. Chan 0 1
Yuan-Yuan Ho 0 1
Vincent Laudet, Ecole Normale Superieure de Lyon, France
0 Current address: The School of Biomedical Sciences, The Chinese University of Hong Kong , Hong Kong , China
1 1 Department of Biochemistry, The Chinese University of Hong Kong , Hong Kong , China , 2 Department of Pediatrics, Center for Diabetes Research, Wake Forest University Health Sciences , Winston-Salem , North Carolina, United States of America, 3 Cancer Epigenetics Laboratory, State Key Laboratory in Oncology in South China, Department of Clinical Oncology, Sir YK Pao Center for Cancer, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong , Hong Kong , China , 4 Department of Medicine and Therapeutics, The Chinese University of Hong Kong , Hong Kong , China , 5 Hong Kong Institute of Diabetes and Obesity , Hong Kong , China , 6 Institute of Human Nutrition, Columbia University , New York , New York, United States of America, 7 Departments of Biostatistics and Psychiatry, Columbia University , New York, New York , United States of America
This study aimed at substantiating the associations of the apolipoproein M gene (APOM) with type 2 diabetes (T2D) as well as with metabolic traits in Hong Kong Chinese. In addition, APOM gene function was further characterized to elucidate its activity in cholesterol metabolism. Seventeen APOM SNPs documented in the NCBI database were genotyped. Five SNPs were confirmed in our study cohort of 1234 T2D and 606 control participants. Three of the five SNPs rs707921(C+1871A), rs707922(G+1837T) and rs805264(G+203A) were in linkage disequilibrium (LD). We chose rs707922 to tag this LD region for down stream association analyses and characterized the function of this SNP at molecular level. No association between APOM and T2D susceptibility was detected in our Hong Kong Chinese cohort. Interestingly, the C allele of rs805297 was significantly associated with T2D duration of longer than 10 years (OR = 1.245, p = 0.015). The rs707922 TT genotype was significantly associated with elevated plasma total- and LDL- cholesterol levels (p = 0.006 and p = 0.009, respectively) in T2D patients. Molecular analyses of rs707922 lead to the discoveries of a novel transcript APOM5 as well as the cryptic nature of exon 5 of the gene. Ectopic expression of APOM5 transcript confirmed rs707922 allele-dependent activity of the transcript in modifying cholesterol homeostasis in vitro. In conclusion, the results here did not support APOM as a T2D susceptibility gene in Hong Kong Chinese. However, in T2D patients, a subset of APOM SNPs was associated with disease duration and metabolic traits. Further molecular analysis proved the functional activity of rs707922 in APOM expression and in regulation of cellular cholesterol content.
Funding: T32-MH-65213, National Institute of Mental Health, USA. 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.
The human apolipoprotein M gene (APOM, Gene ID: 55937) is
located on chromosome 6p21.33 and contains six exons spanning
a region of 2.3 kb in length with gene structure conserved across
species [1,2]. In human and mice, APOM mRNA is highly
expressed in liver and kidney . The human apoM protein (MIM
606907) of 188 amino acids is mainly associated with HDL and to
a minor degree with LDL, very low density lipoprotein, and
chylomicrons . Plasma apoM has been positively associated
with plasma total cholesterol (TC), LDL cholesterol (LDL-C), and
HDL cholesterol (HDL-C) . APOM knockdown in mice by
siRNA revealed its anti-atherosclerotic effect by participating in
pre-b HDL formation and reverse cholesterol transport .
Kruit et al., recently reported the effect of cellular cholesterol
accumulation on beta cell dysfunction in type 2 diabetes . Such
finding implies that factors (i.e., apoM) affecting the balance of
cellular cholesterol content are likely to modify beta cell function
and thus the susceptibility to or progression of type 2 diabetes.
Several additional lines of evidence also indicated the possible
involvement of APOM in the development of diabetes and
metabolic disturbances: 1) the human APOM gene is located
within a high susceptibility region (6q21q23) to type 2 diabetes
(T2D) in genome-wide linkage analyses . 2) SNP rs805296
(T778C) in APOM promoter has been associated with the levels of
plasma total cholesterol (TC) and fasting plasma glucose (FPG) in
non-diabetic participants, 3) SNP rs805296 has also been
associated with the susceptibility to T2D and coronary artery
disease among the Northern Chinese [7,8].
In 2010, China became the country with the largest diabetic
population in the world. The Northern and Southern Chinese
populations are distinct in genetic marker analyses , meaning
disease markers identified in northen populations may not be
shared by the Southern populations. The primary aim of the
current study is to establish the association between APOM and
T2D susceptibility in a Southern Chinese cohort in Hong Kong.
By assuming the same effect size (OR = 1.934) and disease allele
frequency as observed in the studies of Northern Chinese , the
power of the current case-control study is over 95% with 1234
cases and 606 controls. The secondary aims are to examine for
association between APOM and component metabolic traits as well
as to further assess the function of the gene.
Materials and Methods
1. Study population
The pilot cohort consisted of 103 male and 95 female controls
(average age = 43 yrs). They were Hong Kong Chinese adults
recruited from a community health screening program of
cardiovascular risk factors with normal response at a 75 g oral
glucose tolerance test .
The study cohort had 1234 unrelated T2D patients and 606
controls. All participants gave written informed consent at the time
of blood sampling. Ethics approval was obtained from the Clinical
Research Ethics Committee of Chinese University of Hong Kong,
Shatin, NT, Hong Kong. All T2D participants were selected from
the Hong Kong Diabetes Registry. Control participants were
recruited in a community health screening program for
cardiovascular risk factors and some were hospital staff (3.1%, n = 19).
No subdemographic differences were detected in control
participants. All control participants had no known history of diabetes
and had fasting plasma glucose (FPG) , 6.1 mmol/l.
Clinical assessments of participants had been described
elsewhere . Body mass index (BMI), blood pressure (BP) as
well as fasting blood biochemical and metabolic profiles were
measured. Among the 1234 T2D patients, 9.8% (n = 121) were on
diet treatment only, 41.3% (n = 510) were on oral anti-diabetic
drugs only, 12.5% (n = 154) were on insulin only, 9.5% (n = 117)
on both oral anti-diabetic drugs and insulin, and 7.3% (n = 90)
were treated for dyslipidemia.
2. Analysis and measurement
2.1. SNP selection and genotyping analyses. Genomic
DNA was prepared from whole blood as previously described .
Seventeen APOM SNPs including rs6921907, rs1266078,
rs9267528, rs805297, rs4947251, rs9404941, rs805296,
rs805264, rs3117581, rs34490746, rs11462733, rs2273612,
rs707922, rs707921, rs28432254, rs3132449, rs3178094 enlisted
in the NCBI database  were selected for genotyoping in the
pilot cohort of 198 controls by multiplex reactions using the Mass
ARRAY system (Sequenom, San Diego, CA, USA) at the Genome
Quebec Innovation Centre, McGill University (Montreal,
Quebec, Canada). Six of the seventeen SNPs were confirmed in
the pilot cohort: rs1266078(T-1628G), rs805297(C-1065A),
rs9404941(T-855C), rs805264(G+203A), rs707922(G+1837T)
and rs707921(C+1871A). These six SNPs were further
genotyped in the study cohort of 1840 participants (1234 cases
and 606 controls). Case and control DNA samples were genotyped
in parallel on the same plates. Two hundred ninety one duplicate
samples (15.8%) were used to assess intra-plate and inter-plate
genotype quality. No genotyping discrepancies were detected. The
overall call rate was 98.0%. Five out of the six SNPs (except for
rs1266078) were successfully genotyped in the study cohort.
2.2. Plasma lipids and apoM levels. Plasma apoM
concentration was estimated by dot-blot analysis using
monoclonal mouse anti-human apoM antibody (ABNOVA,
Taipei, Taiwan) following previously established protocols
[14,15]. Recombinant human apoM (ABNOVA, Taipei,
Taiwan) was used as protein standard after serial dilution. The
mean signal densities of each specimen and protein standards in
triplicate measures were determined by ImageJ 1.42q software
(http://rsbweb.nih.gov/ij/). ApoM concentration was derived
from the standard curves developed using the recombinant
2.3. Total cholesterol measures in cultured cells with
ectopic APOM1 and APOM5 expression. WRL-68 and
HepG2 hepatic cell lines were purchased from American Type
Culture Collection (Rockville, MD, USA) and maintained in
RPMI-1640 medium supplemented with 10% FBS and 100 units/
ml penicillin and 100 mg/ml streptomycin in a humidified
atmosphere containing 5% CO2 at 37uC. Prior to the
expreiments measuring cellular and medium cholesterol content,
cells were switched to serum free and phenol red free RPMI
medium (Invitrogen, Carlsbad, CA, USA).
Ectopic expression of APOM was achieved by transient
transfection of APOM1 or APOM5 cDNA (cloned into the
pCMV-Myc vectors) into cultured cells at 70% confluence using
LipofectamineTM 2000 reagent (Invitrogen, Carlsbad, CA, USA)
following the manufactorers protocols .
Cellular lipids were extracted as previously described .
Total cellular cholesterol was measured using the InfinityTM
Cholesterol Liquid Stable Reagent (Thermo Fisher Scientific Inc.,
Middletown, VA, USA) following the manufacturers instructions.
The measured amount of total cholesterol was normalized by cell
3. Bioinformatics and molecular anayses of APOM transcripts
3.1. Comparative genomic and protein sequence
analyses. APOM transcript and gene sequences were obtained
from the NCBI human Genome Browser , the Ensembl
Genome Browser  and the human Expressed Sequence Tags
(EST) databases. The Evolutionary Conserved Regions Browser
 and the Ensembl Genome Browser were used to identify
3.2. Rapid amplification of cDNA ends (RACE). The
Human Liver FirstChoice RACE-ready cDNA kit (Ambion,
Austin, Texas, USA) was used to amplify the 59 and 39 ends of
novel APOM transcripts (Supplementary Figure S1, and
Supplementary Table S1).
3.3. Semi-quantitative RTPCR analysis. Human normal
adult tissue RNA samples were purchased commercially
(Stratagene, La Jolla, CA, USA or Millipore Chemicon,
Billerica, MA, USA). cDNA was synthesized using the
GeneAmp RNA PCR kit (Applied Biosystems, Foster City, CA,
USA) in combination with RNase inhibitor (Roche Applied
Science, Indianapolis, IN, USA) and M-MuLV reverse
transcriptase. The subsequent PCR amplification of cDNA was
performed using the AmpliTaq Gold DNA Polymerase (Applied
Biosystems, Foster City, CA, USA) following standardized
protocols [21,22]. The vulgate transcript APOM1 (Ensembl:
ENST00000375916) and the novel transcript APOM5 were
amplified using primer RT-PCR-YY12 paired with
RT-PCRYY13 and RT-PCR-YY12 paired with RT-PCR-YY14,
respectively (Supplementary Table S4). GAPDH was amplified
as a house-keeping gene control for RNA integrity and equal
loading using the GAPDH primers, RT-PCR-Tao1 and
RTPCR-Tao2  (Supplementary Table S1).
Continuous variables were compared using Students t test or
one-way analysis of variance (ANOVA) for traits with normal
Genotype n (% frequencies)
Allele n (% frequencies)
distribution. Plasma triglycerides (TG) were skewed and
logarithmically transformed. Association tests between genotypes and
quantitative traits were performed in T2D patients and
nondiabetic controls separately. Categorical variables, including
genotype distributions were compared by x2 tests.
Genotype distributions were tested for Hardy-Weinberg
equilibrium using goodness-of-fit test (1 df). Informative missingness
was checked by coding successful genotypes into one group and
failed genotypes into another group followed by 262 Chi-square
test for T2D and t-test for the quantitative traits of interest. One
SNP (rs805264) with significant result (p,0.001) indicative of
informative missingness (IM) was excluded for further T2D
association analyses (Supplelmentary Table S2).
Pairwise LD of D and r2 analyses were performed using
Haploview (Broad Institute of MIT and Harvard, USA, version
4.0). 262 contingency tables were used for comparing the
differences of allele frequencies and 263 contingency tables were
used for detecting the differences of genotype frequencies between
cases and controls. Allelic, dominant, recessive and additive
genetic models were used to test the association between each
SNPs and T2D. Multivariate logistic regression analysis was used
to assess the significance of covariates and adjusted for
confounders in the association of genetic factors with T2D.
The independent contributions of all traits, covariates, SNPs, and
haplotypes were determined by multiple regression analysis.
Association between haplotypes and T2D or metabolic traits were
tested by Haploview (version 4.0, Broad Institute of MIT and
Harvard, USA) and PHASE software (version 2.1, UW
TechTransfer Digital Ventures, University of Washington, Seattle, WA,
USA) . When using PHASE software, the probability thresholds
were set at 90% for haplotype inference to deal with ambiguous
haplotypes. It was only used to infer the haplotype of each individual
and thus the case-control permutation test was not conducted. The
PHASE-imputed haplotypes were counted 20 times using different
seed numbers. No difference between runs was detected.
To account for multiple testing, we used the Bonferroni
correction and a statistical significance was considered only when
an SNP association with T2D/metabolic traits was p,0.017
(equivelent to 0.05/3), and a haplotype association with T2D/
metabolic traits was p,0.0125 (equivelent to 0.05/4). The human
plasma apoM concentrations determined by dot-blot assays were
compared by a nonparametric Kruskal-Wallis H test. A value of
p,0.05 was considered significant.
Results from functional analyses were analyzed by Students
ttest for two-group comparison, and one way ANOVA for multiple
group comparisons. A statistical significance is considered at
p,0.05 level. All statistical analyses were performed using the
SPSS program (SPSS version 15.0, Chicago, IL, USA) unless
1. APOM genotype analyses
Seventeen APOM SNPs enlisted in the public databases were
selected for genotyping in a pilot cohort of 198 control
participants. Six SNPs were confirmed polymorphic in this pilot
cohort of Hong Kong Chinese. These six SNPs were further
genotyped in the full study cohort of 1840 participants. Five of the
variants were successfully genotyped: rs805297(C-1065A),
rs9404941(T-855C), rs805264(G+203A), rs707922(G+1837T),
and rs707921(C+1871A) with genotype distributions fitting
Hardy-Weinberg equilibrium. Table 1 summarized the allele
and genotype frequencies of SNPs in non-diabetic controls and
T2D patients. SNP rs805264 was removed from further
association analysis for T2D due to informative missingness
(Supplementary Table S2).
2. Association analysis
2.1. APOM SNPs and T2D susceptibility. No significant
association was detected between individual SNPs and T2D
(Table 1). Further multiple logistic regression analysis adjusting for
age, BMI, SBP (systolic blood pressure), DBP (diastolic blood
pressure), TC and TG again detected no significant association
between individual SNPs and T2D (data not shown).
2.2. APOM SNPs and T2D duration. We next examine the
association between APOM SNPs and T2D disease duration. T2D
patients were subgrouped into disease duration of # 10 years
(n = 583) and disease duration of .10 years (n = 586). As shown in
Table 2, the C allele of rs805297 was associated with T2D
duration of longer than 10 years (odds ratio = 1.245, p = 0.015).
2.3. APOM SNPs and metabolic traits. We next analyzed
the association between SNPs and metabolic variables in patients
and controls separately. SNP rs805297(C-1065A) was not
associated with metabolic traits in either patients or controls.
Since rs707922(G+1837T) was in near perfect LD with
rs805264(G+203A) and rs707921(C+1871A) (Supplementary
Figure S2B), similar association results were expected and
observed. Table 3 showed the representative results using
rs707922 as the marker SNP. Under recessive model,
homozygous minor allele TT of rs707922 was associated with
significantly higher TC (p = 0.006), LDL-C (p = 0.009) in T2D
patients. In controls, no association between SNPs and metabolic
traits was detected. When plasma apoM concentration was
measured in T2D patients and controls subgrouped by their
rs707922 genotype, the TT genotype was found associated with
significantly higher apoM level as compared to the GT (and GG)
genotype(s) (p = 0.002).
3. APOM haplotype association with T2D and metabolic profiles
As mentioned above, rs805264, rs707922, and rs707921 are
located within the same LD block. Therefore, in the subsequent
haplotype analysis, rs707922 was used to tag the three SNPs.
Haplotype construction was conducted for rs707922(G+1837T)
with other independent SNPs rs805297(C-1065A) and
rs9404941(T-855C). Four haplotypes (A-T-G, C-C-G, C-T-G,
and C-T-T) accounting for 99.9% of all possible haplotypes were
detected in our Hong Kong Chinese population (Supplementary
Table S3). No significant association was found between these
haplotypes with T2D. Homozygous C-T-T was significantly
associatiated with elevated TC, LDL-C and HbA1c in T2D
patients (p,0.0125, Supplementary Table S4).
4. Bioinformatics and molecular analyses of APOM transcripts
4.1. Bioinformatics analyses of APOM
transcripts. Sequence alignment analysis revealed conserved
regions of the APOM gene in human, mouse, rat, cow, and dog
(Supplementary Figure S3). SNPs rs707922 (G+1837T) and
rs707921 (C+1871A) which associated with plasma levels of TC,
LDL-C and apoM in T2D patients fell within the evolutionary
conserved region. Figure 1 (top panel) illustrated the cross-species
sequence conservation of the rs707922- and rs707921- flanking
region. BLAST search using this conserved sequence as the
template returned unique human EST clones BI757556 (human
brain) and AA975560.1 (human kidney) which are likely other
APOM transcripts. The Ensembl Browser also displayed three
APOM transcripts (APOM1: Ensembl-ENST00000375916,
APOM2: Ensembl-ENST00000375920 and APOM3:
4.2. Molecular cloning of APOM transcripts. Since the
sequences of EST clones BI757556 and AA975560.1 were
different than the known APOM transcripts, we proceeded with
cloning alternative transcripts of APOM. A novel transcript,
designated APOM5, was identified by 59 RACE and 39 RACE.
As shown in Figure 1, the 39 end of APOM5 was identical to the 39
end of APOM3. The 59 end, however, was similar to that of the
vulgate APOM transcript (designated APOM1) except that the
transcription start site of APOM5 was 21 nucleotides downstream
that of the APOM1. The full-length sequence of APOM5 is
provided in Supplementary Figure S4. It is important to note that
the two SNPs rs707922(G+1837T) and rs707921(C+1871A)
associated with metabolic traits in T2D are located to the exon
5 of APOM5. On the contrary, when reference to the vulgate
APOM1 transcript, rs707921 and rs707922 are located to intron 5.
These observations support the cryptic nature of exon 5 of the
4.3. Tissue expression and function of APOM
transcripts. Tissue expression of APOM5 transcript was
determined by RT-PCR. As shown in Figure 2, APOM5 and the
vulgate transcript APOM1 shared similar tissue expression profiles:
relatively strong expression in liver and kidney and almost
undetectable in spleen, colon, lung, breast, testis, esophagus, and
trachea. Figrue 3 showed that the expression of two allelic forms of
APOM5 transcripts elicited distinct effects on cellular cholesterol
content relative to APOM1. Expression of the transcript in G-allelic
form (APOM5-G) resulted in slight accumulation of cholesterol in
the cells whereas cells expressing the T-allelic form (APOM5-T) of
the transcript had lower cholesterol content. Consistent results
were obtained in two human hepatic cell lines HepG2 and
The results of this study did not support an assoiation between
APOM and T2D suseptibility in Hong Kong Chinese. For a subset
of SNPs, we presented evidence of association between APOM and
disease duration as well as metabolic traits in T2D patients.
Further characterization of rs707922, one of the metabolic
traitassociated SNP at molecular level lead to the discoveries of a novel
transcript APOM5 and its SNP-dependent effect on cellular
The LD block formed among rs805264, rs707922, and
rs707921 in our cohort agreed with the LD structure reported in
the Northern Chinese . It is currently unknown whether this
subset of SNPs is also associated with metabolic traits in Northern
Chinese with T2D. Among the four common haplotypes
ballelic odds ratio (OR) of association.
Genotype n (%frequencies)
Allele n (% frequencies)
ltro T /1171 6.211 6.213 .2165 6.782 6.48 6.39 6.65 .09 6.49 6.60 and xaen
n G 7 4 - 2 1 7 - 4 4 1 0 2 0
-nod T /619 6.493 6.243 .5518 6.235 6.59 6.71 6.45 .11 6.30 6.60 ithw jsaud
N T 1 4 - 2 1 7 - 4 5 1 1 3 0
a ) irc PB G
h 8 t S G
c 9 .8 e , /
liilccannd TT /3711 6..02581370 6..3015130 6..7426388 6..73109267 6..95761208 6..568244 6..1017387 6..056141 6..371047 ..(4610742 6..853120 6..0600007 ,rSeoogDm irtsaaeeuond t/syeTTTopG
6 is n
ae 4 .)76 an ,Id feg . t030
tye2nogp 2TD lta2TToD /743005 6..30103571 6..126919 6..6254220 6..74032129 6..39611722 6..391857 6..593518 6..541255 6..720371 ..(2407312 6..913003 6..4090002 ,jtsceeubm ,,sxaeeBgM (sscaeno ,.()P0017 ..0017324
constructed from rs805297, rs9404941, and rs707922, only
homozygous haplotype C-T-T was significantly associated with
higher TC, LDL-C and HbA1c levels in T2D patients. Given the
established association between rs7070922 and plasma TC and
LDL-C levels, these association results did not support additional
effects of the haplotypes on serum cholesterol levels. Interestingly,
the association between the homozygous haplotype C-T-T with
HbA1c indicated the interaction among the three alleles to control
systemic glucose level in T2D patients.
It would have been ideal if the previously reported association
between SNP rs805296(T-778C) and T2D in Northern Chinese
were reproduced in this Hong Kong Chinese population.
Unfortunately, genotyping of this SNP failed to produce results
in this study, precluding it being used for discussions attempting to
reconcile the current findings with prior results. Although
rs805296 is physically close to rs9404941, the existing
information/data does not allow the relationship between SNP rs805296
and T2D/T2D metabolic traits to be predicted in our cohort.
It is noteworthy that the case-control study design adopted by
the current and other studies tend to be limited by the
heterogeneity of the prevalent cases with regards to T2D
ascertainment, i.e., both those have developed T2D and those
have survived in the setting of T2D were included as cases.
Therefore, those susceptible to the disease were not distinguished
from those survived the disease. One possibility to circumvent
such issue is to examine for similar duration of diabetes across
studies being compared and test for difference in duration of T2D
by SNP. Interestingly, while our results did not support an
association between APOM and T2D susceptibility, stratification of
our cases by disease duration allowed us to detect an association
between rs805297(C-1065A) and T2D duration. This result
implied the possibility that relative to the rs805297-A carriers,
the rs805297-C carriers better survived the diabetic condition over
the long term and such possibility can be further tested.
Interestingly, Zhao et al., recently reported a positive association
between rs805297-A and the risk of stroke in Norhtern Chinese
(OR = 1.38, p = 0.002) after adjusting for other risk factors
including history of diabetes . Whether such association is
present among the Southern Chinese requires further
investigation. Nevertheless, losing rs805297-A carriers with T2D to stroke
over time provides a plausible explanation for the observed higher
frequency of rs805297-C allele in the T2D duration .10 years
subgroup (relative to T2D duration #10 years subgroup).
Previous studies attempting to correlate plasma apoM and
cholesterol levels have generated inconsistent results [3,27]. In this
study, rs707922 homozygous minor allele (TT) was associated with
elevated TC and LDL-C as well as plasma apoM levels in diabetic
cases (average BMI of 25.26). These observations are consistent
with previously reported positive association between plasma
apoM and plasma TC and LDL-C in overweight-obese individuals
. Results presented by Han et al. from the study of a Northern
Chinese cohort showed significant association between rs707922 T
allele and increased risk of cerebral infraction (OR = 1.78,
p = 0.000). In parallel they also confirmed hypercholesterolemia
as an independent risk factor for cerebral infraction . These
results implied the possibility that rs707922 is also a modifier of
serum cholesterol in Northern Chinese. The association between
rs707922 TT genotype and elevated serum total-/LDL-
cholesterol levels in type 2 diabetes found in the current report deserves
to be further substantiated in strict replicate studies.
The mechanism underlying the effects of rs707922 on plasma
TC and LDL-C levels in diabetes remains elusive. Richter et al.,
reported HNF-1 alpha being a potent transcription activator of
APOM . The decreased serum apoM level in maturity-onset
diabetes of the young subjects as compared to the controls could
be explained by the HNF-1 alpha mutations in these patients .
Given the association between APOM and metabolic traits found
in this study, one may speculate that SNP rs707922 (G+1837T), in
the capacity of an intronic SNP (reference to the APOM1
transcript), may modify APOM expression through SNP-specific
recruitment of transcription factors (i.e., PAX 6 showed an
allelespecific interaction with rs707922 T by computer prediction as
presented in Supplementary Figure S5) and subsequently affect
cellular cholesterol homeostasis in liver and possibly other tissues.
More interestingly, we found that rs707922 can also assume the
capacity as an exonic SNP (i.e., reference to the APOM5
transcript). While the function of APOM5 requires further
elucidation, the high renal and hepatic expression levels of
APOM1 and APOM5 indicated the possibility of these transcripts
coordinate to regulate cholesterol homeostasis in these tissues.
Such possibility is further supported by the results showing the
activities of ectopically expressed APOM5 in modifying hepatic cell
cholesterol content. With regards to systematic cholesterol
homeostasis, we observed that homozygous rs707922-T allele
associated with elevated total- and LDL-cholesterol levels. One
possible mechanism of such elevation is through reducd hepatic
and/or pheripheral clearance of circulating cholesterol. Consistent
with this notion, our in vitro data showed that hepatic cells
overexpressing APOM5-T transcript had lower cholesterol content
relative to cells expressing the APOM5-G counterpart.
In conclusion, the APOM SNP frequencies and the LD structure
reported in this study of Hong Kong Chinese population will
facilitate future population genetics studies. While our results did
not support an association between APOM and T2D susceptibility
in Hong Kong Chinese, subgroup analyses found SNP as well as
haplotype associations between APOM and metabolic traits in
T2D. Bioinformatics/molecular analyses revealed the cryptic
nature of exon 5 responsible for the expression of a novel
transcript APOM5, predominantly in liver and kidney. The activity
of APOM5 on modifying cellular cholesterol content revealed
another layer of regulation underlying the expression and function
Figure S1 Positions of primers used for 59 and 39 RACE
experiments. The relative positions of primers were indicated
by pink arrowheads above or below the APOM5 transcripts with
the positions of coding exons (dark blue boxes), introns (fold lines),
untranslated exons (open boxes) and adaptors (red boxes)
indicated. The primer names corresponding to those in the
Supplemental Table S1 were indicated in parentheses. (A)
Positions of the primers used for 59 RACE experiment. (B)
Positions of the primers used for 39 RACE experiment. (C) A
schematic representation of the structure of APOM1 transcript in
the same length proportion to the APOM5 transcript. Since all 39
primers were targeted to APOM5-specific sequences, no
amplification APOM1 transcript was expected.
Figure S2 Linkage disequilibrium (LD) structure of five
SNPs in the full cohort (n = 1840). Images were taken from
HaploView 4.0. Blocks were defined using the solid spline of
linkage disequilibrium. A. The red squares without numbers
indicates the D value of 1.00. B. The shades of grey refer to the
strength of pairwise linkage disequilibrium based on r2, which was
also indicated within each square. White squares were very low
value of r2. Black squares indicate r2 close to or equal to 1. The
pilot cohort produced very similar LD structure results.
Figure S3 Conservation profiles and transcript patterns
of the APOM. The conservation profiles (percent identity cut-off
of 50% to 100%) of the human APOM1 (shown on the very top of
the figure) in comparison with the mouse (Mus musculus; chr17), rat
(Rattus norvegicus; chr20), cow (Bos Taurus; chr23) and dog (Canis
familiaris; chr12) genes are shown. Conserved sequences were
defined as coding exons (blue), The Evolutionary Conserved
Regions (ECRs) were indicated by pink lines (on top of the panel
for each species) with a default value of 70%. The human APOM
was depicted as a horizontal blue line above the graph, with
strand/transcriptional orientation indicated by arrows. APOM
coding exons were shown as blue boxes along the line, while
untranslated regions (UTR) were indicated as yellow boxes. Peaks
within the conservation profile which corresponded to these five
exons of APOM were similarly coloured within the plot. Peaks
within the conservation profile that did not correspond to
transcribed sequences were highlighted in red colour. Regions of
transposable elements and simple repeats were highlighted in
green color. Relative length was indicated by a line at the bottom
for human APOM (chr6: 31730492-31733971). The locations of
APOM SNPs, rs805297 (C-1065A), rs9404941 (T-855C), rs805264
(G+203A), rs707922 (G+1837T) and rs707921 (C+1871A) were
indicated by arrowheads on the top of the figure.
Figure S4 Sequencing result of APOM5 transcript from
59-RACE. Shown above is the reverse complementary sequence
with the location corresponding to the first nucleotide of the cDNA
sequence listed in Supplementary Figure S3 indicated by black
arrowhead. The nucleotides between the black arrowhead and the
red arrowhead are identical to the sequence shown in
Supplementary Figure S3 (from nucleotide position 1 to 655). The
forward sequence corresponding to the above chromatograph is
provided below for easy viewing. Q
Figure S5 Computer-predicted transcription factor
interaction sites in nucleotide sequences spanning SNPs
rs707922(G+1837T) and rs707921(C+1871A). This figure is
generated by the MATCH program. Top panel: The
transcription factors predicted to interact with the nucleotide sequences
spanning the major allele of SNPs rs707922 (G allele) and
rs707921 (the C allele). Bottom panel: The transcription factors
predicted to interact with the nucleotide sequences spanning the
minor allele of SNPs rs707922 (the T allele) and rs707921 (the A
allele). The predicted transcription factors are marked by blue text
with scores of matrix match indicated in parentheses. The
locations and orientations of the binding sites for these predicted
transcription factors are marked by black horizontal dashed lines
with arrows. Highlighted in pink boxes are allele-specific
transcription factors (PAX6 and AREB6 for rs707922-T; HNF4
and OCT1 for rs707921-A) and their corresponding binding sites.
The vertical dashed lines indicate the locations of SNPs rs707922
and rs707921. The precise nucleotide positions of SNP rs707922
and rs707921 are also highlighted with grey boxes in the DNA
sequences represented by red colored text.
Sequences of primers used in this study.
Table S2 Summary of data quality of the five
successfully genotyped APOM SNPs in the full cohort (n = 1840).
The clinical traits tested for IM include T2D, TG, HbA1c, FPG,
TC, HDL-C, and LDL-C.
Table S3 Frequencies of common haplotypes
constructed by APOM SNPs rs805297, rs904941, and rs707922.
Table S4 Haplotype C-T-T formed from SNPs
rs805297(C-1065A), rs9404941(T-855C), and rs707922
(G+1837T) and clinical characteristics of T2D patients.
Values are either number of subjects, mean 6 SD, or geometric
mean (95% confidence interval). p values here represent the
comparisons between subgroup of homozygotes of C-T-T
haplotype vs. subgroup with one C-T-T haplotype and without
C-T-T haplotype (a recessive model). p values are adjusted for age,
sex, BMI and disease duration in T2D. In non-diabetic controls,
the p values without parentheses are adjusted for age, sex and
BMI. +/+ represent the homozygote of haplotype C-T-T,
+/2 represent the heterozygote of haplotype C-T-T, 2/2
represent the subgroup who do not have the haplotype of C-T-T.
Individuals on lipid lowering medications (n = 90) were excluded
for association analysis with lipid traits. * statistical significance
We thank Dr. Tilla Worgall, Department of Pathology and Dr. Richard,
Deckelbaum, Institute of Human Nutrition, Columbia University, New
York for their generous technical support and scientific input.
Conceived and designed the experiments: Y-YH J-WZ JCC. Performed the
experiments: J-WZ HG. Analyzed the data: J-WZ Y-YH MCYN.
Contributed reagents/materials/analysis tools: J-WZ Y-YH SKWT
MCYN S-KL W-YS RCM YW Z-YC QT JCNC. Wrote the paper:
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