中国汉族人群身高和体重指数的全基因组关联研究
摘要
第一部分中国汉族人群身高的全基因组关联研究
背景和目的
身高主要受遗传因素控制,其遗传度约为80%。研究身高的遗传机制将有助于深入理解人类生长发育过程。到目前为止,大部分身高的全基因组关联研究是在欧洲人群开展的。因此,我们在中国汉族人群中开展了这项全基因组关联研究并进行重复验证,来探讨中国汉族人群身高的遗传因素。
研究对象和方法
本研究的芯片阶段纳入了来自北京动脉粥样硬化研究和中国动脉粥样硬化研究的6534名研究对象。北京动脉粥样硬化研究和中国动脉粥样硬化研究分别使用Affymetrix的GeneChip(?)500K和AxiomTM全基因组CHB1阵列芯片进行基因分型。挑选芯片阶段达到全基因组显著性(P<5.0×10-8)或潜在关联(5.0×10-8 结果
通过芯片阶段的meta分析,我们发现了两个位点达到全基因组显著水平。这两个位点分别是欧洲人群中已报道的CYP19A1位点(rs3751599, P=1.86×10-9)和从未报道过的ZNF638位点(rs12612930,P=1.07×10-8)。我们从芯片阶段选择了17个位点在GenSalt研究中进行了重复验证。将芯片阶段和重复验证阶段结果合并后,CYP19A1和ZNF638与身高的关联变得更为显著(rs3751599,P＝4.80×10-10；rs12612930,P=2.02x10-10)。除这两个位点外,还有其它3个位点达到了全基因组显著性。其中,11q21的MAML2(rs11021504,P=7.81×10-9)和18q21.1的C18orf12(rs11082671,P=1.87×10-8)为新发现的位点,12q13.3的CS(rs3816804,P=2.63×10-9)为已报道过的位点。因此,在将芯片阶段和重复验证阶段合并共计8415研究对象中,我们发现了三个新的身高位点(ZNF638、MAML2和C18orf12)并验证了两个已报道的位点(CS和CYP19A1)。
我们分析了亚洲人群中已报道的8个身高位点在本研究芯片阶段的关联结果。所有8个位点在本研究中的效应方向均与以往亚洲人群研究报道的方向相同并且4个位点显示显著关联(P<0.05)。这4个位点的SNP分别为rs3791675(EFEMP1,P=432×10-4), rs7571816(DIS3L2, P=9.50×10-4), rs7678436(NCAPG-LCORL, P=5.52×10-4)和rs12338076(LHX3-QSOX2,P=3.42×10-2)。同样,我们也评估了其他人群中报道的身高位点在本研究中与身高的关联情况,共有35个位点在本研究中提示有显著关联的证据(P<0.05)。
结论
本研究在汉族人群中发现了三个新的身高相关位点,分别为ZNF638、MAML2和C18orfl2。此外还验证了两个以往报道的位点,分别为CS和CYP19A1。这些研究结果表明,身高的遗传机制在不同人种之间既有共同又有不同之处。应当开展进一步研究对这些位点在不同人群中进行验证并解释其潜在的生物学机制。
第二部分中国汉族人群体重指数的全基因组关联研究
背景和目的
肥胖是全球重要的公共卫生问题。目前为止,全基因组关联研究已经发现50多个与肥胖和体重指数相关联的位点。这些位点大多是在欧洲人群中发现的,仅有部分在亚洲人群中得到验证。这提示体重指数这一复杂性状的遗传机制在不同种族之间有一定的差异,需要在不同种族中开展体重指数的全基因组关联研究并相互验证。因此,本研究在中国汉族人群中开展体重指数全基因组关联研究并在独立样本中进行重复验证,来探讨中国汉族人群体重指数的遗传因素。
研究对象和方法
本研究芯片阶段纳入的6534名研究对象分别来自北京动脉粥样硬化研究和中国动脉粥样硬化研究。北京动脉粥样硬化研究使用Affymetrix的GeneChip(？)500K,中国动脉粥样硬化研究使用AxiomTM全基因组CHB1阵列芯片进行全基因组基因分型。芯片阶段达到潜在关联(P<1.0×10-5)的位点进入重复验证分析阶段。重复验证采用盐敏感性遗传流行病学网络(GenSalt)研究,1881名研究对象已使用Afymetrix(?)6.0芯片进行基因分型。
结果
通过对6534名研究对象的芯片阶段分析,我们发现7个位点的P值小于1×10-5。这7个位点包括两个已报道的体重指数相关位点分别为FTO(rs17817712,P=3.21×10-6)和MC4R (rs975918, P=9.80×10-6),还有5个新位点CMTM7(rs347134, P=2.56×10-6)、VEPH1(rs16827528, P=3.97×10-6)、 RPL18P9(rs12818806,P=2.98×10-6)、GJA3(rs4769965,P=1.17R10-6)和C14orf177(rs17097110, P=5.92×10-6)。我们将从芯片阶段筛选出的这7个位点关联信号最强的SNP在GenSalt研究中进行了重复验证,其中3个在重复验证阶段提示有显著关联证据(P<0.05)。这3个SNP分别位于3号染色体的CMTM7(rs347134, P=3.39×10-2)、3号染色体的VEPH1(rs16827528, P=3.47×10-3)和18号染色体的MC4R (rs975918, P=2.79×102).在芯片阶段和重复验证阶段合并后的共计8415名研究对象中,一个位点到达全基因组显著水平CVEPH1, rs16827528,P=4.85×10-8)。对于已报道的两个位点FTO和MC4R,两阶段合并后均没有达到全基因组显著性水平(FTO, rsl7817712, P=1.05×10-5; MC4R, rs975918,P=8.72×10-7)。
此外,我们还分析了以往报道的51个肥胖和体重指数位点在本研究芯片阶段的关联情况。除了前面提到的FTO和MC4R(?),还有8个位点与体重指数存在关联(P<0.05)：TMEM18、SEC16B、GNPDA2、PCSK1、CDKAL1、MTCH2、GP2和NPC1、在其余41个位点中,有6个位点在汉族人群中为单态,35个位点未在本研究中发现与体重指数存在关联(P>0.05)。
结论
本研究在中国汉族人群中发现1个新的体重指数位点(VEPH1)和4个潜在关联的位点(CMTM7, RPL18P9, GJA3和C14orfl77),此外还不同程度验证了10个以往研究报道的位点,包括FTO、MC4R、TMEM18、SEC16B、GNPDA2、 PCSK1、CDKAL1、MTCH2、GP2和NPC1(P值从4.42×10-2到8.72×10-7)。本研究发现的新位点需要进一步在不同人群中进行大规模重复验证,以验证关联结果的可靠性。对这些新位点进行精细定位和功能研究将有助于阐明体重指数和肥胖的遗传机制。
Part One:Genome-wide association study of human height in Han Chinese
Background and objective
Human height is mainly determined by genetic factors with heritability estimates of80%. Insights into the genetic determination of height will provide a better understanding of human development and growth. Up to now, most genome-wide association studies (GWAS) of height were conducted in European populations. So we conduct a meta-analysis of GWAS for human height in Chinese Han population with replication to identify genetic underpinnings in Chinese.
Subjects and methods
This study included GWAS discovery studies of6534Han Chinese subjects from Beijing Atherosclerosis Study (BAS) and China Atherosclerosis Study (CAS). The BAS subjects were genotyped with the Affymetrix GeneChip(?) Human Mapping500K Array Set and CAS subjects were genotyped with the AxiomTM Genome-Wide CHB1Array. Top SNPs in loci that achieved genome-wide significance (P<5.0×10-8) or suggestive evidence (5.0×10-8 Results
Through meta-analysis of discovery studies, we identified two loci that reached the genome-wide significance level of P<5×10-8. These included one locus at CYP19A1(rs3751599, P=1.86×10-9) reported in populations of European descent and one unreported locus at ZNF638(rs12612930, P=1.07×10-8). We selected17top SNPs in17loci (P<1×10-5) from the discovery study for replication in the GenSalt study. Combined analysis of discovery and replication studies strengthened the original associations of the CYP19A1and ZNF638loci with height (rs3751599, P=4.80×10-10; rs12612930, P=2.02×10-10) in a total of8415subjects. We also observed another three loci reached genome-wide significance in combined analysis. rs11021504on11q21(MAML2, P=7.81×10-9) and rs11082671on18q21.1(C18orf12, P=1.87×10-8) were newly identified. Another locus on12q13.3(rs3816804, P=2.63×10-9) had been reported previously. Finally, we identified three novel loci (ZNF638, MAML2and C18orf12) and confirmed two loci (CS and CYP19A1) previously reported in European populations.
We evaluated the associations of eight SNPs that achieved genome-wide significance in GWAS of other Asian populations in our discovery study. All these SNPs were in the same effect directions of previous studies and four showed nominal significance (P<0.05) including rs3791675(EFEMP1, P=4.32×10-4),rs7571816(DIS3L2, P=9.50×10-4), rs7678436(NCAPG-LCORL, P=5.52×10-4) and rs12338076(LHX3-QSOX2, P=3.42×10-2). We also investigated whether the height-associated SNPs identified by non-Asian GWAS were associated in our sample. We found35SNPs showed directionally consistent and nominally significant associations in the discovery study (P<0.05).
Conclusion
We identified three novel loci reaching the genome-wide significance threshold (P<5×10-8) including ZNF638, MAML2and C18orf12. We also confirmed two loci previously reported in European populations including CS and CYP19A1. Our data suggest that both shared and unique genetic backgrounds of human height are present in different ancestry groups. Further studies are required to confirm associations of loci identified in this study across different populations and elucidate the underlying molecular mechanisms of growth in the future.
Part Two:Genome-wide association study of body mass index in Han Chinese
Background and objective
Obesity is a global public health problem. Up to now, genome-wide association studies (GWAS) have identified more than fifty loci that influence body mass index (BMI) and obesity. Most of these loci were identified in samples of European origin, and only several of them were replicated in Asian populations. It implied that there might be substantial genetic differences for BMI among different populations. Therefore, we carried out this GWAS of BMI in Han Chinese with replication study to investigate the genetic basis of BMI.in Chinese.
Subjects and methods
This study included GWAS discovery studies of6534Han Chinese subjects from Beijing Atherosclerosis Study (BAS) and China Atherosclerosis Study (CAS). Subjects from BAS and CAS were genotyped with the Affymetrix GeneChip(?) Human Mapping500K Array Set and the AxiomTM Genome-Wide CHB1Array, respectively. Top SNPs in loci that achieved suggestive evidence (P<1.0×10-5) were replicated in the Genetic Epidemiology Network of Salt Sensitivity (GenSalt) study. The1881subjects of GenSalt study were genotyped using Affymetrix(?) Genome-Wide Human Array6.0.
Results
In the meta-analysis of6534participants from discovery stage, seven loci showed suggestive association with P less than1×10-5. These included two previously reported BMI loci (FTO, rs17817712, P=3.21×10-6and MC4R, rs975918, P=9.80×10-6) and five new loci (CMTM7, rs347134, P=2.56×10-6; VEPH1, rs16827528, P=3.97×10-6; RPL18P9, rs12818806, P=2.98×10-6; GJA3, rs4769965, P=1.17×10-6and C14orf177, rs17097110, P=5.92×10-6). We selected tops SNPs of these seven loci for replication in the GenSalt study. Three SNPs showed nominal significance(P<0.05) in replication study including two SNPs on chromosome3(rs347134, CMTM7, P=3.39×10-2; rs16827528, VEPH1, P=3.47×10-3) and one SNP on chromosome18(rs975918, MC4R, P=2.79×10-2). In the combined analysis of discovery and replication studies with8415subjects, one locus (VEPH1, rsl6827528, P=4.85×10-8) on chromosome3reached genome-wide significance. Two loci previously reported did not reached genome-wide significance in the combined analysis (FTO, rs17817712, P=1.05×105; MC4R, rs975918, P=8.72×10-7).
We evaluated whether the51BMI-related loci identified in previous studies were associated with BMI in our discovery study. Besides FTO and MC4R, another eight loci showed nominal association with BMI (P<0.05) including TMEM18, SEC16B, GNPDA2, PCSK1, CDKAL1, MTCH2, GP2and NPC1. For the other41loci, six were monomorphic in Chinese Han population and35did not show significant association with BMI (P>0.05).
Conclusion
In this GWAS of BMI in Han Chinese, we newly identified one locus (VEPH1) associated with BMI and four loci (CMTM7, RPL18P9, GJA3and C14orf177) potentially associated with BMI. We also replicated10previously reported BMI loci including FTO, MC4R, TMEM18, SEC16B, GNPDA2, PCSK1, CDKAL1, MTCH2, GP2and NPC1, with P values ranging from4.42×10-2to8.72×10-7. New loci from this study need validation in studies of large sample sizes across different population. Fine mapping and functional studies may help to explain the genetic mechanism of these loci.
背景和目的
身高主要受遗传因素控制,其遗传度约为80%。研究身高的遗传机制将有助于深入理解人类生长发育过程。到目前为止,大部分身高的全基因组关联研究是在欧洲人群开展的。因此,我们在中国汉族人群中开展了这项全基因组关联研究并进行重复验证,来探讨中国汉族人群身高的遗传因素。
研究对象和方法
本研究的芯片阶段纳入了来自北京动脉粥样硬化研究和中国动脉粥样硬化研究的6534名研究对象。北京动脉粥样硬化研究和中国动脉粥样硬化研究分别使用Affymetrix的GeneChip(?)500K和AxiomTM全基因组CHB1阵列芯片进行基因分型。挑选芯片阶段达到全基因组显著性(P<5.0×10-8)或潜在关联(5.0×10-8
通过芯片阶段的meta分析,我们发现了两个位点达到全基因组显著水平。这两个位点分别是欧洲人群中已报道的CYP19A1位点(rs3751599, P=1.86×10-9)和从未报道过的ZNF638位点(rs12612930,P=1.07×10-8)。我们从芯片阶段选择了17个位点在GenSalt研究中进行了重复验证。将芯片阶段和重复验证阶段结果合并后,CYP19A1和ZNF638与身高的关联变得更为显著(rs3751599,P＝4.80×10-10；rs12612930,P=2.02x10-10)。除这两个位点外,还有其它3个位点达到了全基因组显著性。其中,11q21的MAML2(rs11021504,P=7.81×10-9)和18q21.1的C18orf12(rs11082671,P=1.87×10-8)为新发现的位点,12q13.3的CS(rs3816804,P=2.63×10-9)为已报道过的位点。因此,在将芯片阶段和重复验证阶段合并共计8415研究对象中,我们发现了三个新的身高位点(ZNF638、MAML2和C18orf12)并验证了两个已报道的位点(CS和CYP19A1)。
我们分析了亚洲人群中已报道的8个身高位点在本研究芯片阶段的关联结果。所有8个位点在本研究中的效应方向均与以往亚洲人群研究报道的方向相同并且4个位点显示显著关联(P<0.05)。这4个位点的SNP分别为rs3791675(EFEMP1,P=432×10-4), rs7571816(DIS3L2, P=9.50×10-4), rs7678436(NCAPG-LCORL, P=5.52×10-4)和rs12338076(LHX3-QSOX2,P=3.42×10-2)。同样,我们也评估了其他人群中报道的身高位点在本研究中与身高的关联情况,共有35个位点在本研究中提示有显著关联的证据(P<0.05)。
结论
本研究在汉族人群中发现了三个新的身高相关位点,分别为ZNF638、MAML2和C18orfl2。此外还验证了两个以往报道的位点,分别为CS和CYP19A1。这些研究结果表明,身高的遗传机制在不同人种之间既有共同又有不同之处。应当开展进一步研究对这些位点在不同人群中进行验证并解释其潜在的生物学机制。
第二部分中国汉族人群体重指数的全基因组关联研究
背景和目的
肥胖是全球重要的公共卫生问题。目前为止,全基因组关联研究已经发现50多个与肥胖和体重指数相关联的位点。这些位点大多是在欧洲人群中发现的,仅有部分在亚洲人群中得到验证。这提示体重指数这一复杂性状的遗传机制在不同种族之间有一定的差异,需要在不同种族中开展体重指数的全基因组关联研究并相互验证。因此,本研究在中国汉族人群中开展体重指数全基因组关联研究并在独立样本中进行重复验证,来探讨中国汉族人群体重指数的遗传因素。
研究对象和方法
本研究芯片阶段纳入的6534名研究对象分别来自北京动脉粥样硬化研究和中国动脉粥样硬化研究。北京动脉粥样硬化研究使用Affymetrix的GeneChip(？)500K,中国动脉粥样硬化研究使用AxiomTM全基因组CHB1阵列芯片进行全基因组基因分型。芯片阶段达到潜在关联(P<1.0×10-5)的位点进入重复验证分析阶段。重复验证采用盐敏感性遗传流行病学网络(GenSalt)研究,1881名研究对象已使用Afymetrix(?)6.0芯片进行基因分型。
结果
通过对6534名研究对象的芯片阶段分析,我们发现7个位点的P值小于1×10-5。这7个位点包括两个已报道的体重指数相关位点分别为FTO(rs17817712,P=3.21×10-6)和MC4R (rs975918, P=9.80×10-6),还有5个新位点CMTM7(rs347134, P=2.56×10-6)、VEPH1(rs16827528, P=3.97×10-6)、 RPL18P9(rs12818806,P=2.98×10-6)、GJA3(rs4769965,P=1.17R10-6)和C14orf177(rs17097110, P=5.92×10-6)。我们将从芯片阶段筛选出的这7个位点关联信号最强的SNP在GenSalt研究中进行了重复验证,其中3个在重复验证阶段提示有显著关联证据(P<0.05)。这3个SNP分别位于3号染色体的CMTM7(rs347134, P=3.39×10-2)、3号染色体的VEPH1(rs16827528, P=3.47×10-3)和18号染色体的MC4R (rs975918, P=2.79×102).在芯片阶段和重复验证阶段合并后的共计8415名研究对象中,一个位点到达全基因组显著水平CVEPH1, rs16827528,P=4.85×10-8)。对于已报道的两个位点FTO和MC4R,两阶段合并后均没有达到全基因组显著性水平(FTO, rsl7817712, P=1.05×10-5; MC4R, rs975918,P=8.72×10-7)。
此外,我们还分析了以往报道的51个肥胖和体重指数位点在本研究芯片阶段的关联情况。除了前面提到的FTO和MC4R(?),还有8个位点与体重指数存在关联(P<0.05)：TMEM18、SEC16B、GNPDA2、PCSK1、CDKAL1、MTCH2、GP2和NPC1、在其余41个位点中,有6个位点在汉族人群中为单态,35个位点未在本研究中发现与体重指数存在关联(P>0.05)。
结论
本研究在中国汉族人群中发现1个新的体重指数位点(VEPH1)和4个潜在关联的位点(CMTM7, RPL18P9, GJA3和C14orfl77),此外还不同程度验证了10个以往研究报道的位点,包括FTO、MC4R、TMEM18、SEC16B、GNPDA2、 PCSK1、CDKAL1、MTCH2、GP2和NPC1(P值从4.42×10-2到8.72×10-7)。本研究发现的新位点需要进一步在不同人群中进行大规模重复验证,以验证关联结果的可靠性。对这些新位点进行精细定位和功能研究将有助于阐明体重指数和肥胖的遗传机制。
Part One:Genome-wide association study of human height in Han Chinese
Background and objective
Human height is mainly determined by genetic factors with heritability estimates of80%. Insights into the genetic determination of height will provide a better understanding of human development and growth. Up to now, most genome-wide association studies (GWAS) of height were conducted in European populations. So we conduct a meta-analysis of GWAS for human height in Chinese Han population with replication to identify genetic underpinnings in Chinese.
Subjects and methods
This study included GWAS discovery studies of6534Han Chinese subjects from Beijing Atherosclerosis Study (BAS) and China Atherosclerosis Study (CAS). The BAS subjects were genotyped with the Affymetrix GeneChip(?) Human Mapping500K Array Set and CAS subjects were genotyped with the AxiomTM Genome-Wide CHB1Array. Top SNPs in loci that achieved genome-wide significance (P<5.0×10-8) or suggestive evidence (5.0×10-8
Through meta-analysis of discovery studies, we identified two loci that reached the genome-wide significance level of P<5×10-8. These included one locus at CYP19A1(rs3751599, P=1.86×10-9) reported in populations of European descent and one unreported locus at ZNF638(rs12612930, P=1.07×10-8). We selected17top SNPs in17loci (P<1×10-5) from the discovery study for replication in the GenSalt study. Combined analysis of discovery and replication studies strengthened the original associations of the CYP19A1and ZNF638loci with height (rs3751599, P=4.80×10-10; rs12612930, P=2.02×10-10) in a total of8415subjects. We also observed another three loci reached genome-wide significance in combined analysis. rs11021504on11q21(MAML2, P=7.81×10-9) and rs11082671on18q21.1(C18orf12, P=1.87×10-8) were newly identified. Another locus on12q13.3(rs3816804, P=2.63×10-9) had been reported previously. Finally, we identified three novel loci (ZNF638, MAML2and C18orf12) and confirmed two loci (CS and CYP19A1) previously reported in European populations.
We evaluated the associations of eight SNPs that achieved genome-wide significance in GWAS of other Asian populations in our discovery study. All these SNPs were in the same effect directions of previous studies and four showed nominal significance (P<0.05) including rs3791675(EFEMP1, P=4.32×10-4),rs7571816(DIS3L2, P=9.50×10-4), rs7678436(NCAPG-LCORL, P=5.52×10-4) and rs12338076(LHX3-QSOX2, P=3.42×10-2). We also investigated whether the height-associated SNPs identified by non-Asian GWAS were associated in our sample. We found35SNPs showed directionally consistent and nominally significant associations in the discovery study (P<0.05).
Conclusion
We identified three novel loci reaching the genome-wide significance threshold (P<5×10-8) including ZNF638, MAML2and C18orf12. We also confirmed two loci previously reported in European populations including CS and CYP19A1. Our data suggest that both shared and unique genetic backgrounds of human height are present in different ancestry groups. Further studies are required to confirm associations of loci identified in this study across different populations and elucidate the underlying molecular mechanisms of growth in the future.
Part Two:Genome-wide association study of body mass index in Han Chinese
Background and objective
Obesity is a global public health problem. Up to now, genome-wide association studies (GWAS) have identified more than fifty loci that influence body mass index (BMI) and obesity. Most of these loci were identified in samples of European origin, and only several of them were replicated in Asian populations. It implied that there might be substantial genetic differences for BMI among different populations. Therefore, we carried out this GWAS of BMI in Han Chinese with replication study to investigate the genetic basis of BMI.in Chinese.
Subjects and methods
This study included GWAS discovery studies of6534Han Chinese subjects from Beijing Atherosclerosis Study (BAS) and China Atherosclerosis Study (CAS). Subjects from BAS and CAS were genotyped with the Affymetrix GeneChip(?) Human Mapping500K Array Set and the AxiomTM Genome-Wide CHB1Array, respectively. Top SNPs in loci that achieved suggestive evidence (P<1.0×10-5) were replicated in the Genetic Epidemiology Network of Salt Sensitivity (GenSalt) study. The1881subjects of GenSalt study were genotyped using Affymetrix(?) Genome-Wide Human Array6.0.
Results
In the meta-analysis of6534participants from discovery stage, seven loci showed suggestive association with P less than1×10-5. These included two previously reported BMI loci (FTO, rs17817712, P=3.21×10-6and MC4R, rs975918, P=9.80×10-6) and five new loci (CMTM7, rs347134, P=2.56×10-6; VEPH1, rs16827528, P=3.97×10-6; RPL18P9, rs12818806, P=2.98×10-6; GJA3, rs4769965, P=1.17×10-6and C14orf177, rs17097110, P=5.92×10-6). We selected tops SNPs of these seven loci for replication in the GenSalt study. Three SNPs showed nominal significance(P<0.05) in replication study including two SNPs on chromosome3(rs347134, CMTM7, P=3.39×10-2; rs16827528, VEPH1, P=3.47×10-3) and one SNP on chromosome18(rs975918, MC4R, P=2.79×10-2). In the combined analysis of discovery and replication studies with8415subjects, one locus (VEPH1, rsl6827528, P=4.85×10-8) on chromosome3reached genome-wide significance. Two loci previously reported did not reached genome-wide significance in the combined analysis (FTO, rs17817712, P=1.05×105; MC4R, rs975918, P=8.72×10-7).
We evaluated whether the51BMI-related loci identified in previous studies were associated with BMI in our discovery study. Besides FTO and MC4R, another eight loci showed nominal association with BMI (P<0.05) including TMEM18, SEC16B, GNPDA2, PCSK1, CDKAL1, MTCH2, GP2and NPC1. For the other41loci, six were monomorphic in Chinese Han population and35did not show significant association with BMI (P>0.05).
Conclusion
In this GWAS of BMI in Han Chinese, we newly identified one locus (VEPH1) associated with BMI and four loci (CMTM7, RPL18P9, GJA3and C14orf177) potentially associated with BMI. We also replicated10previously reported BMI loci including FTO, MC4R, TMEM18, SEC16B, GNPDA2, PCSK1, CDKAL1, MTCH2, GP2and NPC1, with P values ranging from4.42×10-2to8.72×10-7. New loci from this study need validation in studies of large sample sizes across different population. Fine mapping and functional studies may help to explain the genetic mechanism of these loci.
引文
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