www.nature.com/scientificreports OPEN A Genome-Wide Association Study Identifies Genetic Variants Associated with Mathematics Received: 16 May 2016 Accepted: 06 December 2016 Ability Published: 03 February 2017 Huan Chen1,2,*, Xiao-hong Gu3,*, Yuxi Zhou4,5,*, Zeng Ge4,5,*, Bin Wang4,5, Wai Ting Siok6, Guoqing Wang4,5, Michael Huen7, Yuyang Jiang8, Li-Hai Tan1,9 & Yimin Sun4,5,8,10 Mathematics ability is a complex cognitive trait with polygenic heritability. Genome-wide association study (GWAS) has been an effective approach to investigate genetic components underlying mathematic ability. Although previous studies reported several candidate genetic variants, none of them exceeded genome-wide significant threshold in general populations. Herein, we performed GWAS in Chinese elementary school students to identify potential genetic variants associated with mathematics ability. The discovery stage included 494 and 504 individuals from two independent cohorts respectively. The replication stage included another cohort of 599 individuals. In total, 28 of 81 candidate SNPs that met validation criteria were further replicated. Combined meta-analysis of three cohorts identified four SNPs (rs1012694, rs11743006, rs17778739 and rs17777541) ofSPOCK1 gene showing association with mathematics ability (minimum p value 5.67 × 10−10, maximum β −2.43). The SPOCK1 gene is located on chromosome 5q31.2 and encodes a highly conserved glycoprotein testican-1 which was associated with tumor progression and prognosis as well as neurogenesis. This is the first study to report genome-wide significant association of individual SNPs with mathematics ability in general populations. Our preliminary results further supported the role of SPOCK1 during neurodevelopment. The genetic complexities underlying mathematics ability might contribute to explain the basis of human cognition and intelligence at genetic level. Mathematics serves as a fundamental instrument in modern society as it plays an important role in many fields including science, engineering, and economics. It also used as a key index of human intelligence. Exceptional mathematics ability was frequently observed among genius from many domains. Meanwhile, dyscalculia, char- acterized by impaired number processing skills, is a specific developmental disorder of mathematics ability that affects approximately 3 to 6% of children1. Childhood mathematics ability was associated with adult socioeco- nomic status and quality of life2. Understanding mathematics ability is an essential step to improve children’s numeracy skills and academic achievements and could also provide novel insights into human brain functions. Mathematics ability is a complex trait that involves neurological and cognitive development as well as postnatal education and training. In particular, it is estimated that considerable proportion of variation in mathematic ability could be explained by genetic factors. 1Center for Neurogenetics, Shenzhen Institute of Neuroscience, Shenzhen, 518057, China. 2State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine, Beijing, 102206, China. 3Department of Healthy Management, Research Institute of Surgery, DaPing Hospital, Third Military Medical University, Chongqing, 400042, China. 4CapitalBio eHealth Science & Technology (Beijing) Co., Ltd., Beijing, 102206, China. 5National Engineering Research Center for Beijing Biochip Technology, Beijing, 102206, China. 6Department of Linguistics, The University of Hong Kong, Hong Kong, China. 7Department of Anatomy, The University of Hong Kong, Hong Kong, China. 8The State Key Laboratory Breeding Base-Shenzhen Key Laboratory of Chemical Biology, The Graduate School at Shenzhen, Tsinghua University, Shenzhen, 518055, China. 9School of Biomedical Engineering, Shenzhen University Health Science Center, Shenzhen, 518060, China. 10Department of Biomedical Engineering, Medical Systems Biology Research Center, Tsinghua University School of Medicine, Beijing, 100084, China. *These authors contributed equally to this work. Correspondence and requests for materials should be addressed to L.H.T. (email: [email protected]) or Y.S. (email: [email protected]) SCIENTIFIC REPORTS | 7:40365 | DOI: 10.1038/srep40365 1 www.nature.com/scientificreports/ GWAS Liangshan Dongming Replication Cao Variables (n = 494) (n = 504) (n = 599) Grade 2 98 (19.84) 98 (19.44) 121 (20.20) 3 103 (20.85) 101 (20.04) 134 (22.37) 4 122 (24.70) 102 (20.24) 136 (22.70) 5 82 (16.60) 99 (19.64) 108 (18.03) 6 89 (18.02) 104 (20.63) 100 (16.69) Sex Male 213 (43.12) 202 (40.08) 283 (47.25) Female 281 (56.88) 302 (59.92) 316 (52.75) Age, year 9.79 ± 1.39 9.51 ± 1.44 9.40 ± 1.45 Math score* 97 (93,99) 91 (83, 95) 95 (89,98) Table 1. Basic characteristics of three populations. *Full score is 100. Data are expressed as number of participants (percentage), mean ±​ SD or median (Q1, Q3). Math score* <80 80–90 ≥90 P value Grade 2 12 (6.22) 35 (12.15) 275 (24.64) 3 38 (19.69) 91 (31.60) 221 (19.80) 4 44 (22.80) 47 (16.32) 261 (23.39) < 0.001 5 43 (22.28) 70 (24.31) 172 (15.41) 6 56 (29.02) 45 (15.63) 187 (16.76) Sex Male 77 (39.90) 125 (43.40) 506 (45.34) 0.28 Female 116 (60.10) 163 (56.60) 610 (54.66) Region Liangshan 16 (8.29) 49 (17.01) 429 (38.44) Dongming 92 (47.67) 149 (51.74) 263 (23.57) < 0.001 Cao 85 (44.04) 90 (31.25) 424 (37.99) Raven score** 45.76 ± 5.63 45.13 ± 5.75 46.69 ± 5.67 < 0.001 Table 2. Breakdown of math score in all participants. Data are expressed as number of participants (percentage) or mean ± SD. *Full math score is 100. **Full Raven score is 60. Recent years, genome-wide association study (GWAS) has been widely applied to investigate genetic com- ponents underlying complex traits3. The first GWAS of mathematics ability was performed among children with high and low mathematics ability respectively and nominated top-performing SNPs for subsequent validation in a large sample of individuals spanning the entire distribution of mathematical ability4. The study did not observe any SNPs alone showing genome-wide significant association with mathematic ability but hypothesized that genetic contribution to mathematics ability might be explained by multiple quantitative trait locus (QTLs) of small effect4. Indeed, the top 10 candidate SNPs only accounted for 2.9% of phenotypic variance in mathematics ability4. The second GWAS of mathematics ability used children’s verbal ability as control and then divided them into groups of high and low mathematic ability5. Candidate SNPs from the discovery stage were individually genotyped for validation but none of them exceeded threshold of genome-wide significance5. In the meantime, another GWAS in monozygotic and dizygotic twin pairs also observed a number of SNPs showing signals of asso- ciations with mathematic ability, but none of them achieved genome-wide significant level6. To date, none of studies has identified genome-wide significant association with mathematics ability in general populations due to small effects of common variants. However, research with specific populations might increase statistical power to detect significant association as it was reported that prevalence of mathematic disability was higher among children with neurodevelopmental disorders such as reading disability, attention-deficit/hyperac- tivity disorder (ADHD) and autism7,8. The GWAS performed in German dyslexic children identified rs133885 as a genome-wide significant SNP associated with mathematics ability9. This variant is a coding variant of MYO18B and is associated with intraparietal sulcus morphology9. However, a recent replication study of rs133885 failed to find its association with mathematics ability in either dyslexic or general populations10. Previous GWAS of mathematic ability is mainly performed in Western populations of which genetic back- grounds are substantially different to Chinese populations. In the present study, we performed GWAS of mathe- matic ability in the Han Chinese elementary school students through QTL-based approach. In total, we identified SCIENTIFIC REPORTS | 7:40365 | DOI: 10.1038/srep40365 2 www.nature.com/scientificreports/ Figure 1. Manhattan plot of –log10 (P values) of meta-analysis result from the additive model after adjustment for sex, age, school and nominal significant principal components in GWAS in Liangshan and Dongming population. The genome-wide threshold for significant (P =​ 5 ×​ 10−8) and suggestive (P =​ 1 ×​ 10−5) association are indicated by the horizontal blue and red lines, respectively. 81 SNPs in meta-analysis had P value <​ 1 ×​ 10−5, of which 28 met the criteria for further replication. The symbol for the gene where the significant SNPs are in combined meta-analysis is shown in italics. four SNPs exceeding genome-wide significant threshold which is the first time to report genome-wide significant association of individual SNPs with mathematics ability in general populations. Our results provide novel evi- dence to explain genetic complexities underlying mathematic ability and the basis of human intelligence at the genetic level. Results In the initial discovery phase, we performed a GWAS scan in two cohorts of Liangshan and Dongming (Supplementary Figure S1; Table 1). Breakdown of math scores according to grades, sex and regions of all par- ticipants were presented in Table 2. After quality control, about 1.1 million autosomal SNPs were analyzed (see Methods) in 998 samples (494 from the Liangshan cohort and 504 from the Dongming cohort). We per- formed linear regression in each cohort with adjustment for age, sex, school and top ten significant principal components of the corresponding cohort to test the additive effect of minor alleles of each SNP. In total, 13082 and 11170 SNPs with P-value less than 0.01 were identified in Liangshan and Dongming cohort respectively (Supplementary Figure S2). Results of the two discovery cohorts were combined by meta-analysis and 81 SNPs with P-value less than 1 ×​ 10−5 were identified (Fig. 1). Finally, 28 SNPs met the criteria selection for subsequent replication stage (see Methods; Table 3). The 28 SNPs met the replication criteria were evaluated in an independent cohort (Cao, Table 4).