Medical
Communication
Biosci. Biotech. Res. Comm. 9(4): 850-855 (2016)
DAZL A386G gene mutation and male infertility: A
genetic association analysis of Asian population
Majid Nejati
1
and Mohammad Karimian
1,2
*
1
Anatomical Sciences Research Center, Kashan University of Medical Sciences, Kashan, Iran
2
Gametogenesis Research Center, Kashan University of Medical Sciences, Kashan, Iran
ABSTRACT
Genetic susceptibility has a prominent role in infertility. This study was proposed the association of Deleted in
Azoospermia-Like (DAZL) A386G gene transition with male infertility in an Iranian population which followed by a
meta-analysis in Asian population. In the case-control study we collected blood samples from 100 idiopathic infertile
and 100 healthy fertile men. After DNA extraction, DAZL A386G genotyping was performed by PCR-RFLP method.
In meta-analysis, we found eligible papers by searching in standard databases. Case-control study indicated that
there is no signi cant association between DAZL A386G and male infertility in study population. However in meta-
analysis, we found a signi cant association between DAZL A386G and male infertility in G vs. A (OR= 8.33, 95% CI=
3.56-19.46, P < 0.001), AG vs. AA (OR= 7.60, 95% CI= 3.24-17.82, P < 0.001), and AG+GG vs. AA (OR= 8.13, 95%
CI= 3.47-19.07, P < 0.001) genetic models within Asian population. Therefore, we concluded that DAZL A386G can
be considered as a possible risk factor for susceptibility to male infertility within Asian population. However, further
studies with larger sample sizes are required to obtain more accurate data.
KEY WORDS: MALE INFERTILITY; DAZL; GENETIC POLYMORPHISM; META-ANALYSIS
850
ARTICLE INFORMATION:
*Corresponding Author: mdkarimian@gmail.com (M. Karimian)
Received 26
th
Nov, 2016
Accepted after revision 28
th
Dec, 2016
BBRC Print ISSN: 0974-6455
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INTRODUCTION
Infertility refers to the inability to conceive after at least
12 months of regular unprotected intercourse. It is an
important health issue that affects 10-15% of couples,
worldwide. Almost half of infertility causes are related
to male factors (Agarwal et al., 2015). Environmental
factors, life style, and genetic background are involved
in male infertility. However, about half of male infer-
tility cases remain unknown which is called idiopathic
infertility (Neto et al., 2016). Numerous elements could
involve in idiopathic infertility such as DNA damage of
sperm and other genetic abnormalities. Recently, several
genetic association studies are developed for evalua-
Majid Nejati and Mohammad Karimian
tion of genetic polymorphisms effects on male infertility
risk In these genetic association studies, an abundant
attention has been focused on the Deleted in Azo-
ospermia-Like (DAZL) gene (Treulen et al 2015 and
Karimian and Colagar, 2016a).
This gene is autosomal homologue of DAZ, which is
deleted in approximately 10% of azoospermic or oli-
gozoospermic men (Nagafuchi et al., 1993; Reijo et al.,
1995), and nominated as a male infertility risk. This gene
is expressing during spermatogenesis in the germ cells
and localizing in spermatogonia and gonocytes (Reyn-
olds et al., 2005). Some evidences showed that DAZL
gene has an essential role in spermatogenesis process
and it is regulating mRNA expression as a translational
activator (Ruggiu et al., 2000).
There are two common single nucleotide polymor-
phisms (SNPs) in DAZL gene including SNP260 and
SNP386. The SNP260 (A260G) is located on exon 2 and
results in threonine to alanine substitution at codon 12
(Thr12Ala). Whereas, SNP386 (A386G) is located on
exon 3 and lead to substitution of threonine with ala-
nine at codon 54 (Thr54Ala) (Zhang et al., 2014). In this
study we investigated the association of SNP386 and
male infertility in an Iranian population and followed it
by a meta-analysis in Asian population.
MATERIALS AND METHODS
CASE-CONTROL STUDY
In the case-control study, we collected 100 idiopathic
infertile and 100 healthy fertile, age-matched men as a
case and a control groups, respectively. All subjects in
case group were classi ed in azoospermia. The healthy
controls were men with normal sperm parameters and
without infertility, who had at least one child. The sub-
jects were selected from IVF center (Kashan, Iran). The
inclusion and exclusion criteria were described in our
previous study, in detail (Nikzad et al., 2015).
After obtaining signed informed consent form, we got
2 ml blood sample from all subjects and collected it on
the EDTA. . The genomic DNA was isolated from blood
samples by DNGplus DNA extraction buffer (CinnaGen,
Iran). The PCR-RFLP method was used to SNP386 geno-
typing as detailed previously (Teng et al., 2002). After
digestion of PCR fragments by AluI restriction enzyme
(Fermentas, Germany), the enzymatic mixtures were
electrophoresed on 12% polyacrylamide gel and stained
by AgNO3. PCR products in wild samples were digested
to 115- and 66-bp fragments while in mutant samples
the 66-bp band was digested to 53- and 13-bp frag-
ments. Therefore, heterozygote samples were contained
four following fragments: 115-, 66-, 53-, and 13-bp.
META-ANALYSIS
We searched for all studies that investigated the correla-
tion of DAZL SNP386 mutation with male infertility in
Asian population. To nd these studies, we performed an
accurate search via Google Scholar, PubMed, and Scince-
Direct databases until October 2016. For search process,
we used the following words: “male infertility”, “DAZL”,
“polymorphism”, “SNP386”, “A386G”, and “Thr54Ala”.
Also, some studies were found by assessment of reference
list of articles which collected in electronic search. The
studies which met the following criteria were included
in meta-analysis: 1. relation of DAZL A386G and male
infertility risk. 2. case-control studies. 3. enough data for
calculation of odds ratio (OR) and its 95% con dence
interval (CI). Some information including the name of
authors, publication year, and genotype and allele fre-
quencies were extracted from included studies.
STATISTICAL ANALYSIS
In the case-control study, OR with 95% CI was calcu-
lated for each alleles and genotype. To compare the dif-
ferences in allele and genotype frequencies between case
and control groups, we employed a Chi-square test. The
P-value less than 0.05 (P< 0.05) has been considered as
statistically signi cant. These statistical analyzes were
performed by SPSS software version 19.
Meta-analysis was done in ve following genetic
models: 1- G vs. A (allelic), 2- GG vs. AA (co-dominant),
3- AG vs. AA (co-dominant), 4- AG+GG vs. AA (domi-
nant), and 5- GG vs. AA+AG (recessive). A Chi square
based ‘Q’ test and I
2
score
was employed to calculate the
heterogeneity (a P-value less than 0.1 was considered
as statistically signi cant) (Higgins et al., 2003). In the
presence of true heterogeneity, the random-effect model
was applied to pool data, but in the absence of signi -
cant heterogeneity, the xed-effect model was used (Der
Simonian et al., 1986; Huedo et al., 2006). For sensitivity
analysis, each study was eliminated from the meta-anal-
ysis at a time to evaluate the magnitude of impact on the
total estimate. Egger’s test and Begg’s funnel plot were
employed to evaluate the possible publication bias (Begg
and Mazumdar 1994; Egger et al., 1997). Two following
software including: Open Meta-analyst and Comprehen-
sive Meta-analysis were used for statistical meta-analysis.
RESULTS
DISTRIBUTION OF A386G IN OUR POPULATION
STUDY
The allele and genotype frequencies of DAZL A386G are
given in table 1. Our data revealed that A386G mutation
BIOSCIENCE BIOTECHNOLOGY RESEARCH COMMUNICATIONS DAZL A386G GENE POLYMORPHISM AND MALE INFERTILITY 851
Majid Nejati and Mohammad Karimian
Table 1: Genotype and allele frequencies of A386G in cases and controls.
Genotype/Allele Control (%) (n= 100) Cases (%) (n= 100) OR (95% CI) P-value
AA 100 (100%) 97 (97%) - -
AG 0 (0%) 2 (2%) 5.15 (0.24-108.76) 0.292
GG 0 (0%) 1 (1%) 3.09 (0.12-76.84) 0.491
AG+GG 0 (0%) 3 (3%) 7.22 (0.37-141.53) 0.193
A 200 (100%) 196 (98%) - -
G 0 (0%) 4 (2%) 9.18 (0.49-171.71) 0.138
OR, Odds Ratio; CI, Con dence Interval.
Table 2: Characteristics of included studies
Country
Genotype frequencies Allele frequencies
ReferenceControl Case Control Case
AA AG GG AA AG GG A G A G
China 114 2 0 121 21 0 230 2 263 21 Teng et al., 2002
Japan 131 0 0 234 0 0 262 0 468 0 Yang et al., 2005
India 349 1 0 656 4 0 699 1 1316 4 Thangaraj et al., 2006
China 189 2 0 205 25 1 380 2 435 27 Teng et al., 2006
China 53 0 0 144 0 0 106 0 288 0 Wen et al., 2007
India 140 0 0 147 0 0 280 0 294 0 Poongothai et al., 2008
China 40 0 0 192 0 4 80 0 384 8 Wang, 2009
India 199 1 0 165 0 0 399 1 330 0 Singh and Raman, 2009
China 175 0 0 173 0 0 350 0 346 0 Ye et al., 2013
Jordan 176 0 0 170 0 0 352 0 340 0 Khabour et al., 2013
Iran 100 0 0 97 2 1 200 0 196 4 This study
Table 3: Association results in the meta-analysis
A) Association results
G
vs.
A GG
vs.
AA AG
vs.
AA AG+GG
vs.
AA GG
vs.
AA+AG
OR (95% CI) P OR (95% CI) P OR (95% CI) P OR (95% CI) P OR (95% CI) P
8.33
(3.56-19.46)
< 0.001 1.26
(0.45-3.55)
0.659 7.60
(3.24-17.82)
< 0.001 8.13
(3.47-19.07)
< 0.001 1.23
(0.44-3.46)
0.695
B) Heterogeneity and publication bias results
G
vs.
A GG
vs.
AA AG
vs.
AA AG+GG
vs.
AA GG
vs.
AA+AG
Ph I
2
Pe Ph I
2
Pe Ph I
2
Pe Ph I
2
Pe Ph I
2
Pe
0.357 0% 0.096 0.999 0% 0.112 0.285 0% 0.078 0.296 0% 0.048 0.999 0% 0.246
OR: Odds ratio, CI: Con dence interval
Ph: Pheterogeneity (p< 0.1) was considered as a signi cant difference. Pe: PEgger (p< 0.05) was considered as a signi cant difference
is absent in control group. Although, we found 2 het-
erozygote and 1 mutant homozygote in case group, but,
statistical analysis revealed that there are no signi cant
associations between AG (OR: 5.15, 95%CI: 0.24-108.76,
P= 0.292) and GG (OR: 3.09, 95%CI: 0.12-76.84, P=
0.491) genotypes and male infertility. In addition, carri-
ers of G allele (AG+GG) were not at a high risk for male
infertility (OR: 7.22, 95%CI: 0.37-141.53, P= 0.193).
Also, allelic analysis revealed that G allele is not a risk
factor for male infertility (OR: 9.18, 95%CI: 0.49-171.71,
P= 0.138).
META-ANALYSIS
After search and screening of studies for meta-anal-
ysis, we found 10 eligible papers. From these 10 arti-
852 DAZL A386G GENE POLYMORPHISM AND MALE INFERTILITY BIOSCIENCE BIOTECHNOLOGY RESEARCH COMMUNICATIONS
Majid Nejati and Mohammad Karimian
FIGURE 1. Forest plot for the association of DAZL A386G
transition with male infertility.
FIGURE 2. Funnel plot for association of DAZL A386G transition with male
infertility.
cles, 5 studies are related to Chinese population (Table
2). Results of meta-analysis are presented in table 3.
Our data indicated that there is signi cant association
between DAZL A386G and male infertility in G vs. A
(OR= 8.33, 95%CI= 3.56-19.46, P< 0.001), AG vs. AA
(OR= 7.60, 95%CI= 3.24-17.82, P< 0.001), and AG+GG
vs. AA (OR= 8.13, 95%CI= 3.47-19.07, P < 0.001) genetic
models (Figure 1). But, association between GG vs. AA
and GG vs. AA+AG genetic models and male infertility
was not signi cant. Also, in the meta-analysis we did
not nd true heterogeneity in (G vs. A: P
heterogeneity
= 0.357,
I
2
= 0%; GG vs. AA: P
heterogeneity
= 0.999, I
2
= 0%; AG vs. AA:
P
heterogeneity
= 0.285, I
2
= 0%; AG+GG vs. AA: P
heterogeneity
=
0.296, I
2
= 0%; GG vs. AA+AG: P
heterogeneity
= 0.999; I
2
= 0%)
genetic models. Evaluation of meta-analysis regard to
possible publication bias revealed that there is no publi-
cation bias in G vs. A (P
Egger
= 0.096), GG vs. AA (P
Egger
=
0.112), AG vs. AA (P
Egger
= 0.078), and GG vs. AA+AG
(P
Egger
= 0.246) genetic models. But, we observed a mar-
ginal publication bias in AG+GG vs. AA (P
Egger
= 0.048)
genetic model (Figure 2). Sensitivity analysis revealed
that exclusion of each study has no signi cant effect on
overall meta-analysis (data not shown).
DISCUSSION
In this study we investigated the association of DAZL
A386G gene mutation with male infertility in a case-
control study and a meta-analysis approach in Asian
population. We found that there was no association
between DAZL A386G polymorphism and male infertil-
ity in study population. Nevertheless there were signi -
cant associations between DAZL A386G and male infer-
tility in G vs. A, AG vs. AA, and GG vs. AA+AG genetic
models within Asian population. The partial differences
between results of individual studies may arise from eth-
nic and geographical differences. Also, it may be due to
small population studied. In addition we did not observe
signi cant publication bias in meta-analysis except in
AG+GG vs. AA genetic model. A publication bias can
due to small sample sizes or low quality. In addition, the
bias may arise from greater luck of positive outcomes
for publication than negatives (Stanley, 2005).
BIOSCIENCE BIOTECHNOLOGY RESEARCH COMMUNICATIONS DAZL A386G GENE POLYMORPHISM AND MALE INFERTILITY 853
Majid Nejati and Mohammad Karimian
Some possible mechanism can explain the role of
Deleted in Azoospermia-Like gene in male reproductive
system. Dazlgene is crucial for germ cells differentia-
tion (Eberhart et al., 1996). For example knockout of
Dazl in mice models results in the lack of production
of gametes and loss of germ cells (Ruggiuet al., 1997).
Another matter which could explain the essential role
of DAZL gene in male fertility is the expression pro-
le of this gene in the testis. Lin et al (2001) reported
that DAZLtranscripts in men with spermatogenic fail-
ure were lower than normal. They obtained testis tissues
from obstructive azoosperma men with normal sper-
matogenesis and non-obstructive azoospermia men with
abnormal spermatogenesis. Their analysis from DAZL
expression revealed that there is a higher expression
level of DAZL in obstructive azoospermic men rather
than it in non-obstructive azoospermic men (Lin et al.,
2001). According to this nding, evaluation of polymor-
phisms and mutations in the promoter of DAZL gene in
azoospermic men can be considered in further studies,
because functional polymorphisms in promoter region
may affect gene expression (Jamali et al., 2016).
The coding SNPs, which located on exon region, could
change the function and structure of protein (Raygan et
al., 2016). It is predicted that about 25-30% of coding
SNPs may reduce protein function (Ng and Henikoff,
2002). Also, coding SNPs can alter some other molecular
aspects such as structure and function of mRNA, splicing
pattern, and post-translational modi cations (Karimian
et al., 2015; Karimian and Colagar, 2016b). On the other
hand, in silico analysis is a helpful approach to analyze
the damaging effects of SNPs on the several molecular
aspects (Karimian et al., 2015). Therefore this approach
will be helpful for evaluation of the effects of A386G
as an exonic SNP on the mRNA structure, RNA splic-
ing, protein function, and post translational modi ca-
tion of DAZL. There are two meta-analysis studies about
the association of A386G DAZL gene polymorphism and
male infertility (Zhang et al., 2014; Chen et al., 2016).
These studies showed that there was signi cant asso-
ciation between A386G and male infertility within Asian
population. But, there are some mistakes in these studies
that should be considered. Zhang et al. (2014) presented
the some genotypes frequencies of both of Thangaraj et
al. (2006) and Poongothai et al. (2008) studies as wrong.
In addition, the some genotypes frequencies of Wen et
al. (2007) and Poongothai et al. (2008) were reported by
Chen et al. (2016), incorrectly.
Finally there are some limitation in this study that
should be mentioned. In case-control study, we did not
considered the effects of gene-gene and gene-environ-
ment interactions, because these interactions may mod-
ulate the effects of A386G DAZL on male infertility. In
addition, in meta-analysis we did not access to original
data such as BMI and biochemical characteristics to jus-
tify the role of A386G DAZL in male infertility. Moreo-
ver, few studies are included in meta-analysis, therefore
more studies with larger sample size and by consider-
ing environmental factors are necessary to obtain more
accurate data.
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