Publications by authors named "Hailing Xie"

3 Publications

  • Page 1 of 1

MAD1L1 and TSNARE gene polymorphisms are associated with schizophrenia susceptibility in the Han Chinese population.

BMC Med Genomics 2021 Sep 4;14(1):218. Epub 2021 Sep 4.

Institute of Mental Health, Hainan Provincial Anning Hospital, No 10, Nanhai Avenue East, Haikou, 571100, Hainan, China.

Background: Schizophrenia (SCZ) is a severe mental illness with high heritability. This study aimed to explore the correlation between MAD1L1, TSNARE polymorphisms and SCZ susceptibility.

Methods: A total of 493 SCZ patients and 493 healthy controls were included. The genotypes of MAD1L1 and TSNARE polymorphisms were identified by Agena MassARRAY platform. Odds ratio (OR) and 95% confidence intervals (CIs) were tested via logistic regression analysis in multiple genetic models and different subgroups.

Results: We observed that AG genotype of rs1107592, AG genotype of rs4976976, and CA genotype of rs67756423 decreased the susceptibility to SCZ (p < 0.05). Age stratification analysis showed that the TC genotype of rs12666575, AG genotype of rs1107592, and AG genotype of rs4976976 decreased the risk of SCZ individuals older than 36 years (p < 0.05). In addition, the AG and AA genotype of rs4976976, the CA genotype of rs67756423 were associated with a lower risk of SCZ in males (p < 0.05). In females, the TT genotype of rs12666575 in recessive model, the AG and AA-AG genotype of rs1107592 in heterozygote and dominant model, could reduce the susceptibility to SCZ (p < 0.05). However, no significant association was found after Bonferroni correction.

Conclusions: Our results suggest that MAD1L1 and TSNARE genetic polymorphisms exert a protective role in the risk of SCZ. These findings provide evidence that MAD1L1 and TSNARE may serve as potential biomarkers of SCZ. However, a replication experiment in a cohort with large sample size are required to confirm our findings. Trial registration Not applicable.
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http://dx.doi.org/10.1186/s12920-021-01070-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8418747PMC
September 2021

Evaluation of the relationship between VRK2, rs4380187 polymorphisms, and genetic susceptibility to schizophrenia in the Chinese Han population.

J Gene Med 2021 03 31;23(3):e3313. Epub 2021 Jan 31.

Institute of Mental Health, Anning Hospital, Hainan Province, China.

Background: Schizophrenia (SZ) is a serious hereditary mental disease with a low recovery rate, especially due to the lack of understanding about the cause of the disease. VRK2 is considered to be related to the pathogenesis of schizophrenia. In this study, we analyzed the correlation between VRK2, rs4380187 single-nucleotide polymorphism (SNP), and schizophrenia.

Methods: Peripheral blood DNA was extracted using a genomic DNA extraction kit. The DNA samples were genotyped using the Agena MassARRAY platform, and four genetic models were applied to compute the odds ratios (ORs) and 95% confidence intervals (CIs) using unconditional logistic regression. The p value was obtained by the chi-square and t test for independent samples.

Results: The C allele of rs4380187 SNP was significantly (p = 0.008) associated with decreased risk of SZ. The AA genotype of rs4380187 showed significantly (p = 0.009) lower frequency in cases with SZ than in controls and was associated with decreased risk of the disease. The frequency of the CA genotype of rs4380187 correlated with a 0.73-fold decreased risk of SZ (p = 0.033). In the co-dominant genetic model, the genotype of rs4380187 was associated with a decreased risk of SZ (p = 0.010). We also found that the log-additive model of rs4380187 significantly reduced the risk of SZ disease (p = 0.007).

Conclusion: This study provides further evidence that rs4380187 SNP is associated with SZ. This genotype variation could be associated with the psychopathology and cognitive function in SZ.
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http://dx.doi.org/10.1002/jgm.3313DOI Listing
March 2021

Automated detection of cloud and aerosol features with SACOL micro-pulse lidar in northwest China.

Opt Express 2017 Nov;25(24):30732-30753

The detection of cloud and aerosols using a modified retrieval algorithm solely for a ground-based micropulse lidar (MPL) is presented, based on one-year data at the Semi-Arid Climate Observatory and Laboratory (SACOL) site (35.57°N, 104.08°E, 1965.8 m), northwest of China, from March 2011 to February 2012. The work not only identifies atmosphere particle layers by means of the range-dependent thresholds based on elastic scattering ratio and depolarization ratio, but also discriminates the detected layers by combining empirical thresholds of the atmosphere's thermodynamics states and scattering properties and continuous wavelet transform (CWT) analyses. Two cases were first presented in detail that demonstrated that the modified algorithm can capture atmosphere layers well. The cloud macro-physical properties including cloud base height (CBH), cloud geometrical thickness (CGT), and cloud fraction (CF) were then analyzed in terms of their monthly and seasonal variations. It is shown that the maximum/minimum CBHs were found in summer (4.66 ± 1.95km)/autumn (3.34 ± 1.84km). The CGT in winter (1.05 ± 0.43km) is slightly greater than in summer (0.99 ± 0.44km). CF varies significantly throughout year, with the maximum value in autumn (0.68), and a minimum (0.58) in winter, which is dominated by single-layered clouds (81%). The vertical distribution of CF shows a bimodal distribution, with a lower peak between 1 and 4km and a higher one between 6and 9km. The seasonal and vertical variations in CF are important for the local radiative energy budget.
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http://dx.doi.org/10.1364/OE.25.030732DOI Listing
November 2017
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