X chromosome-wide association study of quantitative biomarkers from the Alzheimer's Disease Neuroimaging Initiative study.

Introduction: Alzheimer's disease (AD) is a complex neurodegenerative disease with high heritability. Compared to autosomes, a higher proportion of disorder-associated genes on X chromosome are expressed in the brain. However, only a few studies focused on the identification of the susceptibility loci for AD on X chromosome. Methods: Using the data from the Alzheimer's Disease Neuroimaging Initiative Study, we conducted an X chromosome-wide association study between 16 AD quantitative biomarkers and 19,692 single nucleotide polymorphisms (SNPs) based on both the cross-sectional and longitudinal studies. Results: We identified 15 SNPs statistically significantly associated with different quantitative biomarkers of the AD. For the cross-sectional study, six SNPs (rs5927116, rs4596772, rs5929538, rs2213488, rs5920524, and rs5945306) are located in or near to six genes DMD, TBX22, LOC101928437, TENM1, SPANXN1, and ZFP92, which have been reported to be associated with schizophrenia or neuropsychiatric diseases in literature. For the longitudinal study, four SNPs (rs4829868, rs5931111, rs6540385, and rs763320) are included in or near to two genes RAC1P4 and AFF2, which have been demonstrated to be associated with brain development or intellectual disability in literature, while the functional annotations of other five novel SNPs (rs12157031, rs428303, rs5953487, rs10284107, and rs5955016) have not been found. Discussion: 15 SNPs were found statistically significantly associated with the quantitative biomarkers of the AD. Follow-up study in molecular genetics is needed to verify whether they are indeed related to AD. The findings in this article expand our understanding of the role of the X chromosome in exploring disease susceptibility, introduce new insights into the molecular genetics behind the AD, and may provide a mechanistic clue to further AD-related studies.

An Efficient Bayesian Method for Estimating the Degree of the Skewness of X Chromosome Inactivation Based on the Mixture of General Pedigrees and Unrelated Females.

Skewed X chromosome inactivation (XCI-S) has been reported to be associated with some X-linked diseases. Several methods have been proposed to estimate the degree of XCI-S (denoted as γ) for quantitative and qualitative traits based on unrelated females. However, there is no method available for estimating γ based on general pedigrees. Therefore, in this paper, we propose a Bayesian method to obtain the point estimate and the credible interval of γ based on the mixture of general pedigrees and unrelated females (called mixed data for brevity), which is also suitable for only general pedigrees. We consider the truncated normal prior and the uniform prior for γ. Further, we apply the eigenvalue decomposition and Cholesky decomposition to our proposed methods to accelerate the computation speed. We conduct extensive simulation studies to compare the performances of our proposed methods and two existing Bayesian methods which are only applicable to unrelated females. The simulation results show that the incorporation of general pedigrees can improve the efficiency of the point estimation and the precision and the accuracy of the interval estimation of γ. Finally, we apply the proposed methods to the Minnesota Center for Twin and Family Research data for their practical use.

Robust association tests for quantitative traits on the X chromosome.

The genome-wide association study is an elementary tool to assess the genetic contribution to complex human traits. However, such association tests are mainly proposed for autosomes, and less attention has been given to methods for identifying loci on the X chromosome due to their distinct biological features. In addition, the existing association tests for quantitative traits on the X chromosome either fail to incorporate the information of males or only detect variance heterogeneity. Therefore, we propose four novel methods, which are denoted as QXcat, QZmax, QMVXcat and QMVZmax. When using these methods, it is assumed that the risk alleles for females and males are the same and that the locus being studied satisfies the generalized genetic model for females. The first two methods are based on comparing the means of the trait value across different genotypes, while the latter two methods test for the difference of both means and variances. All four methods effectively incorporate the information of X chromosome inactivation. Simulation studies demonstrate that the proposed methods control the type I error rates well. Under the simulated scenarios, the proposed methods are generally more powerful than the existing methods. We also apply our proposed methods to data from the Minnesota Center for Twin and Family Research and find 10 single nucleotide polymorphisms that are statistically significantly associated with at least two traits at the significance level of 1 × 10-3.

Detection of Parent-of-Origin Effects for the Variants Associated With Behavioral Disinhibition in the MCTFR Data.

Behavioral disinhibition is one of the important characteristics of many mental diseases. It has been reported in literature that serious behavioral disinhibition will affect people's health and greatly reduce people's quality of life. Meanwhile, behavioral disinhibition can easily lead to illegal drug abuse and violent crimes, etc., which will bring great harm to the society. At present, large-scale genome-wide association analysis has identified many loci associated with behavioral disinhibition. However, these studies have not incorporated the parent-of-origin effects (POE) into analysis, which may ignore or underestimate the genetic effects of loci on behavioral disinhibition. Therefore, in this article, we analyzed the five phenotypes related to behavioral disinhibition in the Minnesota Center for Twin and Family Research data (nicotine, alcohol consumption, alcohol dependence, illicit drugs, and non-substance use related behavioral disinhibition), to further explore the POE of variants on behavioral disinhibition. We applied a linear mixed model to test for the POE at a genome-wide scale on five transformed phenotypes, and found nine SNPs with statistically significant POE at the significance level of 5 × 10-8. Among them, SNPs rs4141854, rs9394515, and rs4711553 have been reported to be associated with two neurological disorders (restless legs syndrome and Tourette's syndrome) which are related to behavioral disinhibition; SNPs rs12960235 and rs715351 have been found to be associated with head and neck squamous cell carcinoma, skin cancer and type I diabetes, while both SNPs have not been identified to be related to behavioral disinhibition in literature; SNPs rs704833, rs6837925, rs1863548, and rs11067062 are novel loci identified in this article, and their function annotations have not been reported in literature. Follow-up study in molecular genetics is needed to verify whether they are surely related to behavioral disinhibition.

Gene-Based Methods for Estimating the Degree of the Skewness of X Chromosome Inactivation.

Skewed X chromosome inactivation (XCI-S) has been reported to be associated with some X-linked diseases, and currently several methods have been proposed to estimate the degree of the XCI-S (denoted as γ) for a single locus. However, no method has been available to estimate γ for genes. Therefore, in this paper, we first propose the point estimate and the penalized point estimate of γ for genes, and then derive its confidence intervals based on the Fieller's and penalized Fieller's methods, respectively. Further, we consider the constraint condition of γ∈[0, 2] and propose the Bayesian methods to obtain the point estimates and the credible intervals of γ, where a truncated normal prior and a uniform prior are respectively used (denoted as GBN and GBU). The simulation results show that the Bayesian methods can avoid the extreme point estimates (0 or 2), the empty sets, the noninformative intervals ([0, 2]) and the discontinuous intervals to occur. GBN performs best in both the point estimation and the interval estimation. Finally, we apply the proposed methods to the Minnesota Center for Twin and Family Research data for their practical use. In summary, in practical applications, we recommend using GBN to estimate γ of genes.

BEXCIS: Bayesian methods for estimating the degree of the skewness of X chromosome inactivation.

BACKGROUND: X chromosome inactivation (XCI) is an epigenetic phenomenon that one of two X chromosomes in females is transcriptionally silenced during early embryonic development. Skewed XCI has been reported to be associated with some X-linked diseases. There have been several methods measuring the degree of the skewness of XCI. However, these methods may still have several limitations. RESULTS: We propose a Bayesian method to obtain the point estimate and the credible interval of the degree of XCI skewing by incorporating its prior information of being between 0 and 2. We consider a normal prior and a uniform prior for it (respectively denoted by BN and BU). We also propose a penalized point estimate based on the penalized Fieller's method and derive the corresponding confidence interval. Simulation results demonstrate that the BN and BU methods can solve the problems of extreme point estimates, noninformative intervals, empty sets and discontinuous intervals. The BN method generally outperforms other methods with the lowest mean squared error in the point estimation, and well controls the coverage probability with the smallest median and the least variation of the interval width in the interval estimation. We apply all the methods to the Graves' disease data and the Minnesota Center for Twin and Family Research data, and find that SNP rs3827440 in the Graves' disease data may undergo skewed XCI towards the allele C. CONCLUSIONS: We recommend the BN method for measuring the degree of the skewness of XCI in practice. The R package BEXCIS is publicly available at https://github.com/Wen-YiYu/BEXCIS .

A statistical measure for the skewness of X chromosome inactivation for quantitative traits and its application to the MCTFR data.

BACKGROUND: X chromosome inactivation (XCI) is that one of two chromosomes in mammalian females is silenced during early development of embryos. There has been a statistical measure for the degree of the skewness of XCI for qualitative traits. However, no method is available for such task at quantitative trait loci. RESULTS: In this article, we extend the existing statistical measure for the skewness of XCI for qualitative traits, and the likelihood ratio, Fieller's and delta methods for constructing the corresponding confidence intervals, and make them accommodate quantitative traits. The proposed measure is a ratio of two linear regression coefficients when association exists. Noting that XCI may cause variance heterogeneity of the traits across different genotypes in females, we obtain the point estimate and confidence intervals of the measure by incorporating such information. The hypothesis testing of the proposed methods is also investigated. We conduct extensive simulation studies to assess the performance of the proposed methods. Simulation results demonstrate that the median of the point estimates of the measure is very close to the pre-specified true value. The likelihood ratio and Fieller's methods control the size well, and have the similar test power and accurate coverage probability, which perform better than the delta method. So far, we are not aware of any association study for the X-chromosomal loci in the Minnesota Center for Twin and Family Research data. So, we apply our proposed methods to these data for their practical use and find that only the rs792959 locus, which is simultaneously associated with the illicit drug composite score and behavioral disinhibition composite score, may undergo XCI skewing. However, this needs to be confirmed by molecular genetics. CONCLUSIONS: We recommend the Fieller's method in practical use because it is a non-iterative procedure and has the similar performance to the likelihood ratio method.

Uptake and correlates of chlamydia and gonorrhea testing among female sex workers in Southern China: a cross-sectional study.

BACKGROUND: Female sex workers (FSW) are highly susceptible to chlamydia and gonorrhea infection. However, there is limited literature examining their testing uptake to date. This study aimed to assess the uptake and determinants of chlamydia and gonorrhea testing among FSW in Southern China. METHODS: A cross-sectional study with convenience sampling was performed in five cities in Southern China. Data on socio-demographic characteristics, sexual behaviors, chlamydia and gonorrhea testing, and the utilization of health care services from participants were collected through face-to-face interviews. Univariate and multivariable logistic regressions were used to determine factors associated with chlamydia and gonorrhea testing, respectively. RESULTS: Overall, 1207 FSWs were recruited, with the mean age of 30.7 ± 6.8 years and an average number of clients of 7.0 (4.0-10.0) per week. 65.4% participants constantly used condoms with clients during the past month. Only 7.5 and 10.4% had been tested for chlamydia and gonorrhea in the last year, respectively. Multivariable analysis indicated that FSW who worked at low tiers (adjusted Odds Ratio (aOR) = 2.36, 95%CI:1.23-10.14), had more clients in the last month (aOR = 1.03, 95%CI:1.01-1.05), used condoms consistently (aOR = 1.79, 95%CI:1.12-2.86), had STD symptoms (aOR = 4.09,95%CI:2.62-6.40), had been tested for HIV (aOR = 5.16, 95%CI:3.21-8.30) or syphilis (aOR = 6.90, 95%CI:4.21-11.22) in the last year were more likely to have chlamydia testing. In addition, FSW who had more clients in the past month (aOR = 1.02,95%CI:1.00-1.04), had STD symptoms (aOR = 3.33, 95%CI:2.03-5.46), had been tested for HIV (aOR = 3.94, 95%CI:2.34-6.65) and syphilis (aOR = 3.27, 95%CI:1.96-5.46) in the last year were more likely to have gonorrhea testing. CONCLUSIONS: The testing rates of chlamydia and gonorrhea are low among Chinese FSW. Integrating chlamydia and gonorrhea testing into HIV testing promotion programs may help bridge the gap among FSW.

Prediction of hepatic inflammation in chronic hepatitis B patients with a random forest-backward feature elimination algorithm.

BACKGROUND: Persistent liver inflammatory damage is the main risk factor for developing liver fibrosis, cirrhosis, and even hepatocellular carcinoma in chronic hepatitis B (CHB) patients. Thus, accurate prediction of the degree of liver inflammation is a high priority and a growing medical need. AIM: To build an effective and robust non-invasive model for predicting hepatitis B-related hepatic inflammation. METHODS: A total of 650 treatment-naïve CHB (402 HBeAg-positive and 248 HBeAg-negative) patients who underwent liver biopsy were enrolled in this study. Histological inflammation grading was assessed by the Ishak scoring system. Serum quantitative hepatitis B core antibody (qAnti-HBc) levels and 21 immune-related inflammatory factors were measured quantitatively using a chemiluminescent microparticle immunoassay. A backward feature elimination (BFE) algorithm utilizing random forest (RF) was used to select optional features and construct a combined model. The diagnostic abilities of the model or variables were evaluated based on the estimated area under the receiver operating characteristics curve (AUROC) and compared using the DeLong test. RESULTS: Four features were selected to predict moderate-to-severe inflammation in CHB patients using the RF-BFE method. These predictive features included qAnti-HBc, ALT, AST, and CXCL11. Spearman's correlation analysis indicated that serum qAnti-HBc, ALT, AST, and CXCL11 levels were positively correlated with the histology activity index (HAI) score. These selected features were incorporated into the model to establish a novel model named I-3A index. The AUROC [0.822; 95% confidence interval (CI): 0.790-0.851] of the I-3A index was significantly increased compared with qAnti-HBc alone (0.760, 95%CI: 0.724-0.792, P < 0.0001) in all CHB patients. The use of an I-3A index cutoff value of 0.41 produced a sensitivity of 69.17%, specificity of 81.44%, and accuracy of 73.8%. Additionally, the I-3A index showed significantly improved diagnostic performance for predicting moderate-to-severe inflammation in HBeAg-positive and HBeAg-negative CHB patients (0.829, 95%CI: 0.789-0.865 and 0.810, 95%CI: 0.755-0.857, respectively). CONCLUSION: The selected features of the I-3A index constructed using the RF-BFE algorithm can effectively predict moderate-to-severe liver inflammation in CHB patients.

A robust test for X-chromosome genetic association accounting for X-chromosome inactivation and imprinting.

The X chromosome is known to play an important role in many sex-specific diseases. However, only a few single-nucleotide polymorphisms on the X chromosome have been found to be associated with diseases. Compared to the autosomes, conducting association tests on the X chromosome is more intractable due to the difference in the number of X chromosomes between females and males. On the other hand, X-chromosome inactivation takes place in female mammals, which is a phenomenon in which the expression of one copy of two X chromosomes in females is silenced in order to achieve the same gene expression level as that in males. In addition, imprinting effects may be related to certain diseases. Currently, there are some existing approaches taking X-chromosome inactivation into account when testing for associations on the X chromosome. However, none of them allows for imprinting effects. Therefore, in this paper, we propose a robust test, ZXCII, which accounts for both X-chromosome inactivation and imprinting effects without requiring specifying the genetic models in advance. Simulation studies are conducted in order to investigate the validity and performance of ZXCII under various scenarios of different parameter values. The simulation results show that ZXCII controls the type I error rate well when there is no association. Furthermore, with regards to power, ZXCII is robust in all of the situations considered and generally outperforms most of the existing methods in the presence of imprinting effects, especially under complete imprinting effects.

Single-nucleotide polymorphisms of HLA and Polygonum multiflorum-induced liver injury in the Han Chinese population.

BACKGROUND: Polygonum multiflorum is one of the leading causes of herb-induced liver injury in China. HLA-B*35:01 is reported to be a potential biomarker of Polygonum multiflorum-induced liver injury (PM-DILI). However, little is known about the relationship between single-nucleotide polymorphisms (SNPs) and PM-DILI. AIM: To identify SNPs that indicate susceptibility to PM-DILI. METHODS: We conducted a systematic study enrolling 382 participants from four independent hospitals, including 73 PM-DILI patients, 118 patients with other drug-induced liver injury (other-DILI) and 191 healthy controls. Whole-exome sequencing was performed for 8 PM-DILI patients and 8 healthy controls who were randomly selected from the above subjects. Nineteen SNPs that showed high frequencies in the 8 PM-DILI patients were selected as candidate SNPs and then screened in 65 PM-DILI patients, 118 other-DILI patients and 183 healthy controls using the MassARRAY system. HLA-B high-resolution genotyping was performed for the 73 PM-DILI and 118 other-DILI patients. The Han-MHC database was selected as a population control for HLA-B analysis. P < 6.25 × 10-3 after Bonferroni correction was considered significant. RESULTS: The frequencies of rs111686806 in the HLA-A gene, rs1055348 in the HLA-B gene, and rs202047044 in the HLA-DRB1 gene were significantly higher in the PM-DILI group than in the control group [27.2% vs 11.6%, P = 1.72 × 10-5, odds ratio (OR) = 3.96, 95% confidence interval (CI): 2.21-7.14; 42.5% vs 8.6%, P = 1.72 × 10-19, OR = 13.62, 95%CI: 7.16-25.9; 22.9% vs 8.1%, P = 4.64 × 10-6, OR = 4.1, 95%CI: 2.25-7.47]. Only rs1055348 showed a significantly higher frequency in the PM-DILI group than in the other-DILI group (42.5% vs 13.6%, P = 1.84 × 10-10, OR = 10.06, 95%CI: 5.06-20.0), which suggested that it is a specific risk factor for PM-DILI. rs1055348 may become a tag for HLA-B*35:01 with 100% sensitivity and 97.7% specificity in the PM-DILI group and 100% sensitivity and 98.1% specificity in the other-DILI group. Furthermore, HLA-B*35:01 was confirmed to be associated with PM-DILI with a frequency of 41.1% in the PM-DILI group compared with 11.9% (P = 4.30 × 10-11, OR = 11.11, 95%CI: 5.57-22.19) in the other-DILI group and 2.7% (P = 6.22 × 10-166, OR = 62.62, 95%CI: 35.91-109.20) in the Han-MHC database. CONCLUSION: rs111686806, rs1055348, and rs202047044 are associated with PM-DILI, of which, rs1055348 is specific to PM-DILI. As a tag for HLA-B*35:01, rs1055348 may become an alternative predictive biomarker of PM-DILI.

X-chromosome genetic association test incorporating X-chromosome inactivation and imprinting effects.

Studies have shown that many complex diseases are sex-determined. When conducting genetic association studies on X-chromosome, there are two important epigenetic factors which should be considered simultaneously: X-chromosome inactivation and genomic imprinting. Currently, there have been several association tests accounting for the information on X-chromosome inactivation. However, these tests do not take the imprinting effects into account. In this paper, we propose a novel association test simultaneously incorporating X-chromosome inactivation and imprinting effects based on case-parent trios and control-parent trios for female offspring and case-control data for male offspring, denoted by MLRXCII. Extensive simulation studies are carried out to investigate the type I error rate and the test power of the proposed MLRXCII . Simulation results demonstrate that the proposed test controls the type I error rate well andis more powerful than the existing method when imprinting effects exist. The proposed MLRXCII test is valid and powerful in genetic association studies on X-chromosome for qualitative traits and thus is recommended in practice.

Migrant population is more vulnerable to the effect of air pollution on preterm birth: Results from a birth cohort study in seven Chinese cities.

BACKGROUND: Studies have reported that exposure to air pollution during pregnancy was associated with preterm birth (PTB). However, it remains unknown whether this association differs between local residents and migrants. OBJECTIVE: This study aimed to differentiate the associations between maternal air pollution exposure and PTB between local residents and migrants. METHODS: We established a retrospective birth cohort in seven Chinese cities in Pearl River Delta (PRD) region during 2015-2017. The mothers were included in the cohort at their first time of hospital visit for pregnancy, and the endpoint events were identified using the birth registry. The air pollution exposure was estimated based on the daily air pollution concentrations in the nearby air monitoring stations during different pregnancy periods. Cox proportional hazards models were utilized to estimate the associations between each air pollutant and PTB for different pregnancy periods. RESULTS: Our cohort included a total of 628,439 mother-and-live-birth pairs. Among them, 308,201 women were local residents, and 320,238 were migrants. We observed stronger effects of air pollutants among the migrants than the local residents. For the exposure during the entire pregnancy, the hazard ratio (HR) among the migrants and local residents were 1.56 (95% CI: 1.50, 1.63) and 0.98 (95% CI: 0.93, 1.02) for each 10 µg/m3 increase in PM2.5, 1.32 (95% CI: 1.27, 1.39) and 1.18 (95% CI: 1.12, 1.23) for each 10 ppb increase in O3, and 1.48 (95% CI: 1.40, 1.57) and 0.99 (95% CI: 0.93, 1.05) for each 10 µg/m3 increase in SO2, respectively. Similarly higher effects were observed among the migrants for the exposures in different trimesters of pregnancy. However, the effects of NO2 were comparable between the two groups. CONCLUSION: Our study suggests that maternal PM2.5, O3 and SO2 exposures might be important risk factors of preterm birth, particularly among the migrants. More specific protective and education measures should be considered for the migrant pregnant women.

A statistical measure for the skewness of X chromosome inactivation based on case-control design.

BACKGROUND: Skewed X chromosome inactivation (XCI), which is a non-random process, is frequently observed in both healthy and affected females. Furthermore, skewed XCI has been reported to be related to many X-linked diseases. However, no statistical method is available in the literature to measure the degree of the skewness of XCI for case-control design. Therefore, it is necessary to develop methods for such a task. RESULTS: In this article, we first proposed a statistical measure for the degree of XCI skewing by using a case-control design, which is a ratio of two logistic regression coefficients after a simple reparameterization. Based on the point estimate of the ratio, we further developed three types of confidence intervals (the likelihood ratio, Fieller's and delta methods) to evaluate its variation. Simulation results demonstrated that the likelihood ratio method and the Fieller's method have more accurate coverage probability and more balanced tail errors than the delta method. We also applied these proposed methods to analyze the Graves' disease data for their practical use and found that rs3827440 probably undergoes a skewed XCI pattern with 68.7% of cells in heterozygous females having the risk allele T active, while the other 31.3% of cells keeping the normal allele C active. CONCLUSIONS: For practical application, we suggest using the Fieller's method in large samples due to the non-iterative computation procedure and using the LR method otherwise for its robustness despite its slightly heavy computational burden.

A robust and powerful test for case-control genetic association study on X chromosome.

Hundreds of genome-wide association studies were conducted to map the disease genes on autosomes in human beings. It is known that many complex diseases are sex-determined and X chromosome is expected to play an important role. However, only a few single-nucleotide polymorphisms on X chromosome were found to be significantly associated with the diseases under study. On the other hand, to balance the genetic effect between two sexes, X chromosome inactivation occurs in most of X-linked genes by silencing one copy of two X chromosomes in females and dosage compensation is achieved. A few association studies on X chromosome incorporated the information on dosage compensation. However, some of them require the assumption of Hardy-Weinberg equilibrium and some need to specify the underlying genetic model. Therefore, in this article, we propose a novel method for association by taking account of different dosage compensation patterns. The proposed test is a robust approach because it requires neither specifying the underlying genetic models nor the assumption of Hardy-Weinberg equilibrium. Further, the proposed method allows for different deviations from Hardy-Weinberg equilibrium between cases and controls. Simulation results demonstrate that our proposed method generally outperforms the existing methods in terms of controlling the size and the test power. Finally, we apply the proposed test to the meta-analysis of the Graves' disease data for its practical use.

A statistical measure for the skewness of X chromosome inactivation based on family trios.

BACKGROUND: X chromosome inactivation (XCI) is an important gene regulation mechanism in females to equalize the expression levels of X chromosome between two sexes. Generally, one of two X chromosomes in females is randomly chosen to be inactivated. Nonrandom XCI (XCI skewing) is also observed in females, which has been reported to play an important role in many X-linked diseases. However, there is no statistical measure available for the degree of the XCI skewing based on family data in population genetics. RESULTS: In this article, we propose a statistical approach to measure the degree of the XCI skewing based on family trios, which is represented by a ratio of two genotypic relative risks in females. The point estimate of the ratio is obtained from the maximum likelihood estimates of two genotypic relative risks. When parental genotypes are missing in some family trios, the expectation-conditional-maximization algorithm is adopted to obtain the corresponding maximum likelihood estimates. Further, the confidence interval of the ratio is derived based on the likelihood ratio test. Simulation results show that the likelihood-based confidence interval has an accurate coverage probability under the situations considered. Also, we apply our proposed method to the rheumatoid arthritis data from USA for its practical use, and find out that a locus, rs2238907, may undergo the XCI skewing against the at-risk allele. But this needs to be further confirmed by molecular genetics. CONCLUSIONS: The proposed statistical measure for the skewness of XCI is applicable to complete family trio data or family trio data with some paternal genotypes missing. The likelihood-based confidence interval has an accurate coverage probability under the situations considered. Therefore, our proposed statistical measure is generally recommended in practice for discovering the potential loci which undergo the XCI skewing.

Effect of the 2008 cold spell on preterm births in two subtropical cities of Guangdong Province, Southern China.

BACKGROUND: A few studies have reported that low temperatures were associated with an increased risk of preterm birth. However, the effect of extreme weather events, such as cold spell, on preterm birth has not been studied in China. OBJECTIVE: This study was conducted to evaluate the impact of the 2008 cold spell on preterm birth in two subtropical cities of Guangdong Province. METHODS: Data of daily preterm birth, air pollution and meteorological variables from 2006 to 2010 were collected in Dongguan and Shenzhen. A Poisson regression with a distributed lag nonlinear model was used to investigate the association between the 2008 cold spell and daily rate of preterm birth for each city. RESULTS: During the 2008 cold spell, total vaginal preterm births were increased by 22.44% and 21.25% in Dongguan and Shenzhen, respectively. The effect of the cold spell on preterm births lasted for more than 1 week, the lag0-6 days cumulative relative risk (RR) is 1.32 (95% CI: 1.10-1.58) and 1.40 (95% CI: 1.18-1.68) in Dongguan and Shenzhen, respectively. The effects were found to be more pronounced for the pregnant women with 34-36 gestation weeks, maternal age < 35 years group. CONCLUSION: This study demonstrates that cold spell could increase the risk of preterm births in Dongguan and Shenzhen, and the effect lasts for more than 1 week. Specific measures should be considered to protect the pregnant women, especially the vulnerable subgroups.

A powerful parent-of-origin effects test for qualitative traits on X chromosome in general pedigrees.

BACKGROUND: Genomic imprinting is one of the well-known epigenetic factors causing the association between traits and genes, and has generally been examined by detecting parent-of-origin effects of alleles. A lot of methods have been proposed to test for parent-of-origin effects on autosomes based on nuclear families and general pedigrees. Although these parent-of-origin effects tests on autosomes have been available for more than 15 years, there has been no statistical test developed to test for parent-of-origin effects on X chromosome, until the parental-asymmetry test on X chromosome (XPAT) and its extensions were recently proposed. However, these methods on X chromosome are only applicable to nuclear families and thus are not suitable for general pedigrees. RESULTS: In this article, we propose the pedigree parental-asymmetry test on X chromosome (XPPAT) statistic to test for parent-of-origin effects in the presence of association, which can accommodate general pedigrees. When there are missing genotypes in some pedigrees, we further develop the Monte Carlo pedigree parental-asymmetry test on X chromosome (XMCPPAT) to test for parent-of-origin effects, by inferring the missing genotypes given the observed genotypes based on a Monte Carlo estimation. An extensive simulation study has been carried out to investigate the type I error rates and the powers of the proposed tests. Our simulation results show that the proposed methods control the size well under the null hypothesis of no parent-of-origin effects. Moreover, XMCPPAT substantially outperforms the existing tests and has a much higher power than XPPAT which only uses complete nuclear families (with both parents) from pedigrees. We also apply the proposed methods to analyze rheumatoid arthritis data for their practical use. CONCLUSIONS: The proposed XPPAT and XMCPPAT test statistics are valid and powerful in detecting parent-of-origin effects on X chromosome for qualitative traits based on general pedigrees and thus are recommended.

Two Powerful Tests for Parent-of-Origin Effects at Quantitative Trait Loci on the X Chromosome.

Parent-of-origin effects, which describe an occurrence where the expression of a gene depends on its parental origin, are an important phenomenon in epigenetics. Statistical methods for detecting parent-of-origin effects on autosomes have been investigated for 20 years, but the development of statistical methods for detecting parent-of-origin effects on the X chromosome is relatively new. In the literature, a class of Q-XPAT-type tests are the only tests for the parent-of-origin effects for quantitative traits on the X chromosome. In this paper, we propose two simple and powerful classes of tests to detect parent-of-origin effects for quantitative trait values on the X chromosome. The proposed tests can accommodate complete and incomplete nuclear families with any number of daughters. The simulation study shows that our proposed tests produce empirical type I error rates that are close to their respective nominal levels, as well as powers that are larger than those of the Q-XPAT-type tests. The proposed tests are applied to a real data set on Turner's syndrome, and the proposed tests give a more significant finding than the Q-C-XPAT test.

Detection of imprinting effects for qualitative traits on X chromosome based on nuclear families.

Methods for detecting imprinting effects have been developed primarily for autosomal markers. However, no method is available in the literature to test for imprinting effects on X chromosome. Therefore, it is necessary to suggest methods for detecting such imprinting effects. In this article, the parental-asymmetry test on X chromosome (XPAT) is first developed to test for imprinting for qualitative traits in the presence of association, based on family trios each with both parents and their affected daughter. Then, we propose 1-XPAT to deal with parent-daughter pairs, each with one parent and his/her affected daughter. By simultaneously considering family trios and parent-daughter pairs, C-XPAT (the combined test statistic of XPAT and 1-XPAT) is constructed to test for imprinting. Further, we extend the proposed methods to accommodate complete (with both parents) and incomplete (with one parent) nuclear families having multiple daughters of which at least one is affected. Simulation results demonstrate that the proposed methods control the size well, irrespective of the inbreeding coefficient in females being zero or non-zero. By incorporating incomplete nuclear families, C-XPAT is more powerful than XPAT using only complete nuclear families. For practical use, these proposed methods are applied to analyse the rheumatoid arthritis data and Turner's syndrome data.