Background: Currently, diabetes has become one of the leading causes of death worldwide. Fasting plasma glucose (FPG) levels that are higher than optimal, even if below the diagnostic threshold of diabetes, can also lead to increased morbidity and mortality. Here we intend to study the magnitude of the genetic influence on FPG variation by conducting structural equation modelling analysis and to further identify specific genetic variants potentially related to FPG levels by performing a genome-wide association study (GWAS) in Chinese twins. Results: The final sample included 382 twin pairs: 139 dizygotic (DZ) pairs and 243 monozygotic (MZ) pairs. The DZ twin correlation for the FPG level (r DZ = 0.20, 95% CI: 0.04-0.36) was much lower than half that of the MZ twin correlation (r MZ = 0.68, 95% CI: 0.62-0.74). For the variation in FPG level, the AE model was the better fitting model, with additive genetic parameters (A) accounting for 67.66% (95% CI: 60.50-73.62%) and unique environmental or residual parameters (E) accounting for 32.34% (95% CI: 26.38-39.55%), respectively. In the GWAS, although no genetic variants reached the genome-wide significance level (P < 5 × 10 − 8), 28 SNPs exceeded the level of a suggestive association (P < 1 × 10 − 5). One promising genetic region (2q33.1) around rs10931893 (P = 1.53 × 10 − 7) was found. After imputing untyped SNPs, we found that rs60106404 (P = 2.38 × 10 − 8) located at SPATS2L reached the genome-wide significance level, and 216 SNPs exceeded the level of a suggestive association. We found 1007 genes nominally associated with the FPG level (P < 0.05), including SPATS2L, KCNK5, ADCY5, PCSK1, PTPRA, and SLC26A11. Moreover, C1orf74 (P = 0.014) and SLC26A11 (P = 0.021) were differentially expressed between patients with impaired fasting glucose and healthy controls. Some important enriched biological pathways, such as βalanine metabolism, regulation of insulin secretion, glucagon signaling in metabolic regulation, IL-1 receptor pathway, signaling by platelet derived growth factor, cysteine and methionine metabolism pathway, were identified.