Multimodal image fusion-assisted endoscopic evacuation of spontaneous intracerebral hemorrhage.

PURPOSE: Although traditional craniotomy (TC) surgery has failed to show benefits for the functional outcome of intracerebral hemorrhage (ICH). However, a minimally invasive hematoma removal plan to avoid white matter fiber damage may be a safer and more feasible surgical approach, which may improve the prognosis of ICH. We conducted a historical cohort study on the use of multimodal image fusion-assisted neuroendoscopic surgery (MINS) for the treatment of ICH, and compared its safety and effectiveness with traditional methods. METHODS: This is a historical cohort study involving 241 patients with cerebral hemorrhage. Divided into MINS group and TC group based on surgical methods. Multimodal images (CT skull, CT angiography, and white matter fiber of MRI diffusion-tensor imaging) were fused into 3 dimensional images for preoperative planning and intraoperative guidance of endoscopic hematoma removal in the MINS group. Clinical features, operative efficiency, perioperative complications, and prognoses between 2 groups were compared. Normally distributed data were analyzed using t-test of 2 independent samples, Non-normally distributed data were compared using the Kruskal-Wallis test. Meanwhile categorical data were analyzed via the Chi-square test or Fisher's exact test. All statistical tests were two-sided, and p < 0.05 was considered statistically significant. RESULTS: A total of 42 patients with ICH were enrolled, who underwent TC surgery or MINS. Patients who underwent MINS had shorter operative time (p < 0.001), less blood loss (p < 0.001), better hematoma evacuation (p = 0.003), and a shorter stay in the intensive care unit (p = 0.002) than patients who underwent TC. Based on clinical characteristics and analysis of perioperative complications, there is no significant difference between the 2 surgical methods. Modified Rankin scale scores at 180 days were better in the MINS than in the TC group (p = 0.014). CONCLUSIONS: Compared with TC for the treatment of ICH, MINS is safer and more efficient in cleaning ICH, which improved the prognosis of the patients. In the future, a larger sample size clinical trial will be needed to evaluate its efficacy.

Metallic air pollutants and breast cancer heterogeneity.

BACKGROUND: Emerging evidence suggests airborne metals may be associated with breast cancer risk. However, breast cancer is heterogenous and associations with heavy metals vary by subtype. Heavy metals possess both carcinogenic and xenoestrogenic properties which may be related to different tumor etiologies. Therefore, we tested for etiologic heterogeneity, using a case-series approach, to determine whether associations between residential airborne metal concentrations and breast cancer differed by tumor subtype. METHODS: Between 2005 and 2008, we enrolled incident breast cancer cases into the Breast Cancer Care in Chicago study. Tumor estrogen and progesterone receptors status was determined by medical record abstraction and confirmed immunohistochemically (N = 696; 147 ER/PR-negative). The 2002 USEPA's National Air Toxics Assessment census-tract estimates of metal concentrations (antimony, arsenic, beryllium, cadmium, chromium, cobalt, lead, manganese, mercury, nickel and selenium) were matched to participants' residences of the same year. Adjusted logistic regression models were used to examine whether the airborne heavy metal associations differed by tumor ER/PR status. Principal component analysis was performed to assess associations by metal co-exposures. RESULTS: Comparing the highest and lowest quintiles, higher concentrations of antimony (odds ratio[OR]: 1.8, 95% confidence interval[CI]: 0.9, 3.7, P-trend: 0.05), cadmium (OR: 2.3, 95% CI: 1.2, 4.4, P-trend: 0.04) and cobalt (OR: 2.0, 95% CI: 0.9, 4.4, P-trend: 0.04) were associated with ER/PR-negative breast cancer. Mixture analysis using principal components suggested co-exposures to multiple airborne heavy metals may drive associations with tumor receptor status. CONCLUSIONS: Among women diagnosed with breast cancer, metallic air pollutants were associated with increased odds of developing ER/PR-negative breast cancer.

Endoscopic surgery for thalamic hemorrhage breaking into ventricles: Comparison of endoscopic surgery, minimally invasive hematoma puncture, and external ventricular drainage.

PURPOSE: Thalamic hemorrhage breaking into ventricles (THBIV) is a devastating disease with high morbidity and mortality rates. Endoscopic surgery (ES) may improve outcomes, although there is no consensus on its superiority. We investigated the efficacy and safety of ES and compared the outcomes of different management strategies by ES, hematoma puncture and drainage (HPD), and external ventricular drainage (EVD) in patients with THBIV. METHODS: We retrospectively analyzed patients with THBIV treated by ES, HPD, or EVD at our hospital from June 2015 to June 2018. Patients were categorized into anteromedial and posterolateral groups based on THBIV location, and then the two groups were further divided into ES, HPD, and EVD subgroups. Individualized surgical approach was adopted according to the location of the hematoma in the ES subgroups. Patient characteristics and surgical outcomes were investigated. RESULTS: We analyzed 211 consecutive patients. There were no significant differences in clinical characteristics or incidence of perioperative procedure-related complications (postoperative rebleeding and intracranial infection) in either anteromedial or posterolateral groups. Compared with other therapeutic methods, the ES subgroups had the highest hematoma evacuation rate, shortest drainage time, and lowest incidence of chronic ventricular dilatation (all p < 0.05). Among the three anteromedial subgroups, ES subgroup had the best clinical outcomes which was assessed by the modified Rankin Scale, followed by HPD and EVD subgroups (p < 0.01); while in the posterolateral subgroups, clinical outcomes in the ES and HPD subgroups were similar and better than that in the EVD subgroup (p = 0.037). CONCLUSION: Individualized surgical ES approach for removal of thalamic and ventricular hematomas is a minimally invasive, safe, and effective strategy for the treatment of THBIV with a thalamic hematoma volume of 10-30 mL.

Common vitamin D pathway gene variants reveal contrasting effects on serum vitamin D levels in African Americans and European Americans.

Vitamin D deficiency is more common among African Americans (AAs) than among European Americans (EAs), and epidemiologic evidence links vitamin D status to many health outcomes. Two genome-wide association studies (GWAS) in European populations identified vitamin D pathway gene single-nucleotide polymorphisms (SNPs) associated with serum vitamin D [25(OH)D] levels, but a few of these SNPs have been replicated in AAs. Here, we investigated the associations of 39 SNPs in vitamin D pathway genes, including 19 GWAS-identified SNPs, with serum 25(OH)D concentrations in 652 AAs and 405 EAs. Linear and logistic regression analyses were performed adjusting for relevant environmental and biological factors. The pattern of SNP associations was distinct between AAs and EAs. In AAs, six GWAS-identified SNPs in GC, CYP2R1, and DHCR7/NADSYN1 were replicated, while nine GWAS SNPs in GC and CYP2R1 were replicated in EAs. A CYP2R1 SNP, rs12794714, exhibited the strongest signal of association in AAs. In EAs, however, a different CYP2R1 SNP, rs1993116, was the most strongly associated. Our models, which take into account genetic and environmental variables, accounted for 20 and 28 % of the variance in serum vitamin D levels in AAs and EAs, respectively.

Correlation between DNA methylation and gene expression in the brains of patients with bipolar disorder and schizophrenia.

OBJECTIVES: Aberrant DNA methylation and gene expression have been reported in postmortem brain tissues of psychotic patients, but until now there has been no systematic evaluation of synergistic changes in methylation and expression on a genome-wide scale in brain tissue. METHODS: In this study, genome-wide methylation and expression analyses were performed on cerebellum samples from 39 patients with schizophrenia, 36 patients with bipolar disorder, and 43 unaffected controls, to screen for a correlation between gene expression and CpG methylation. RESULTS: Out of 71,753 CpG gene pairs (CGPs) tested across the genome, 204 were found to significantly correlate with gene expression after correction for multiple testing [p < 0.05, false discovery rate (FDR) q < 0.05]. The correlated CGPs were tested for disease-associated expression and methylation by comparing psychotic patients with bipolar disorder and schizophrenia to healthy controls. Four of the identified CGPs were found to significantly correlate with the differential expression and methylation of genes encoding phosphoinositide-3-kinase, regulatory subunit 1 (PIK3R1), butyrophilin, subfamily 3, member A3 (BTN3A3), nescient helix-loop-helix 1 (NHLH1), and solute carrier family 16, member 7 (SLC16A7) in psychotic patients (p < 0.05, FDR q < 0.2). Additional expression and methylation datasets were used to validate the relationship between DNA methylation, gene expression, and neuropsychiatric diseases. CONCLUSIONS: These results suggest that the identified differentially expressed genes with an aberrant methylation pattern may represent novel candidate factors in the etiology and pathology of neuropsychiatric disorders.

Semiparametric odds ratio model for case-control and matched case-control designs.

We propose a semiparametric odds ratio model that extends Umbach and Weinberg's approach to exploiting gene-environment association model for efficiency gains in case-control designs to both discrete and continuous data. We directly model the gene-environment association in the control population to avoid estimating the intercept in the disease risk model, which is inherently difficult because of the scarcity of information on the parameter with the sampling designs. We propose a novel permutation-based approach to eliminate the high-dimensional nuisance parameters in the matched case-control design. The proposed approach reduces to the conditional logistic regression when the model for the gene-environment association is unrestricted. Simulation studies demonstrate good performance of the proposed approach. We apply the proposed approach to a study of gene-environment interaction on coronary artery disease.

Bias correction to secondary trait analysis with case-control design.

In genetic association studies with densely typed genetic markers, it is often of substantial interest to examine not only the primary phenotype but also the secondary traits for their association with the genetic markers. For more efficient sample ascertainment of the primary phenotype, a case-control design or its variants, such as the extreme-value sampling design for a quantitative trait, are often adopted. The secondary trait analysis without correcting for the sample ascertainment may yield a biased association estimator. We propose a new method aiming at correcting the potential bias due to the inadequate adjustment of the sample ascertainment. The method yields explicit correction formulas that can be used to both screen the genetic markers and rapidly evaluate the sensitivity of the results to the assumed baseline case-prevalence rate in the population. Simulation studies demonstrate good performance of the proposed approach in comparison with the more computationally intensive approaches, such as the compensator approaches and the maximum prospective likelihood approach. We illustrate the application of the approach by analysis of the genetic association of prostate specific antigen in a case-control study of prostate cancer in the African American population.

Sample size determination for adaptive crossover trial in detecting gene-drug interactions.

Parallel design and crossover design are two of the most frequently used designs for studying drug-gene interactions. Due to the concerns of statistical power and ethics, it is often more prudent to use the crossover design while allowing the patients to have choices of not switching the treatment if the first stage treatment is effective. This complicates the calculation of the required sample size to achieve pre-specified statistical power. We propose a method to determine the required sample size with a closed-form formula. The proposed approach is applied to determine the sample size of an adaptive crossover trial in studying gene-drug interaction in treating atrial fibrillation, the most common cardiac arrhythmia in clinical practice. Our simulation study confirms the power achieved by the sample size determined using the proposed approach. Issues related to the adaptive crossover trial are also discussed and practical guidelines are provided.

Testing generalized linear models with high-dimensional nuisance parameter.

Generalized linear models often have a high-dimensional nuisance parameters, as seen in applications such as testing gene-environment interactions or gene-gene interactions. In these scenarios, it is essential to test the significance of a high-dimensional sub-vector of the model's coefficients. Although some existing methods can tackle this problem, they often rely on the bootstrap to approximate the asymptotic distribution of the test statistic, and thus are computationally expensive. Here, we propose a computationally efficient test with a closed-form limiting distribution, which allows the parameter being tested to be either sparse or dense. We show that under certain regularity conditions, the type I error of the proposed method is asymptotically correct, and we establish its power under high-dimensional alternatives. Extensive simulations demonstrate the good performance of the proposed test and its robustness when certain sparsity assumptions are violated. We also apply the proposed method to Chinese famine sample data in order to show its performance when testing the significance of gene-environment interactions.

Improving power and robustness for detecting genetic association with extreme-value sampling design.

Extreme-value sampling design that samples subjects with extremely large or small quantitative trait values is commonly used in genetic association studies. Samples in such designs are often treated as "cases" and "controls" and analyzed using logistic regression. Such a case-control analysis ignores the potential dose-response relationship between the quantitative trait and the underlying trait locus and thus may lead to loss of power in detecting genetic association. An alternative approach to analyzing such data is to model the dose-response relationship by a linear regression model. However, parameter estimation from this model can be biased, which may lead to inflated type I errors. We propose a robust and efficient approach that takes into consideration of both the biased sampling design and the potential dose-response relationship. Extensive simulations demonstrate that the proposed method is more powerful than the traditional logistic regression analysis and is more robust than the linear regression analysis. We applied our method to the analysis of a candidate gene association study on high-density lipoprotein cholesterol (HDL-C) which includes study subjects with extremely high or low HDL-C levels. Using our method, we identified several SNPs showing a stronger evidence of association with HDL-C than the traditional case-control logistic regression analysis. Our results suggest that it is important to appropriately model the quantitative traits and to adjust for the biased sampling when dose-response relationship exists in extreme-value sampling designs.

High CpG island methylator phenotype is associated with lymph node metastasis and prognosis in gastric cancer.

Several studies have found that the promoter CpG island is frequently methylated in gastric cancer. The CpG island methylator phenotype (CIMP) defines concordant methylation of multiple promoter CpG island loci in a subset of gastric cancer. However, the relationship between CIMP and lymph node metastasis in gastric cancer is unknown. Our study aimed to characterize the role of CIMP in lymph node metastasis. Clinical specimens from 120 patients were analyzed and PCR was used to detect the methylation status of five genes (ALX4, TMEFF2, CHCHD10, IGFBP3, and NPR1). We measured the level of mRNA for the five genes by real-time RT-PCR. Microsatellite instability and Helicobacter pylori infection status were assayed by capillary electrophoresis and real-time PCR, respectively. DNA methylation in the five genes was correlated with low expression of the respective mRNA. With CIMP as the dependent variable, CIMP-high gastric cancer tended to show more distant lymph node metastasis, higher pathologic tumor classification, more pathologic metastasis, and higher pathologic TNM status. Microsatellite instability and H. pylori status were not significant predictors of prognosis. CIMP-high gastric cancer showed significantly worse survival compared with that of CIMP-low/CIMP-negative gastric cancer (P < 0.001). Our results show that there is an association between CIMP status and lymph node metastasis in gastric cancer and CIMP-high was an independent prognostic factor.

[Fast track surgery accelerates the postoperative rehabilitation and recovery of insulin sensitivity in elective operation for colorectal carcinoma: a randomized controlled clinical trial].

OBJECTIVE: To investigate the effects of fast track surgery on postoperative insulin sensitivity on the basis of clinical benefits in patients undergoing elective open colorectal resection. METHODS: During May 2008 to December 2008, Seventy patients with colorectal carcinoma requiring colorectal resection were randomized into two groups: a fast track group (35 cases) and a conventional care group (35 cases). All included patients received elective open colorectal resection with combined tracheal intubation and general anesthesia. Clinical parameters, stress markers and insulin sensitivity were evaluated in both groups. RESULTS: The 62 patients finally completed the study, 32 cases in the fast-track group and 30 cases in the conventional care group. The speed of recovery of postoperative insulin sensitivity on 7 days postoperative in the fast-track group (97% ± 9%) was significantly faster than the conventional care group (88.5% ± 9.0%, t = 2.552, P = 0.016). The hospitalization days in the fast-track group was 6 days (M(50)), and it was significantly shorter than the conventional care group ((11.7 ± 3.8) days, Z = 4.360, P = 0.000). The time of recovery of bowel function were faster in the fast-track group (time to pass flatus was 2 days (M(50))) than the conventional care group (4 days, Z = 3.976, P = 0.000). The Infectious complication rate in the fast-track group (2/32) is lower than the other group (8/30, P = 0.040). CONCLUSION: Fast track surgery accelerates recovery of postoperative insulin sensitivity in elective surgery for colorectal carcinoma with a lower rate of postoperative infectious complications and a shorter length of postoperative hospital stay.

Statistical Methods for Assessing the Explained Variation of a Health Outcome by a Mixture of Exposures.

Exposures to environmental pollutants are often composed of mixtures of chemicals that can be highly correlated because of similar sources and/or chemical structures. The effect of an individual chemical on a health outcome can be weak and difficult to detect because of the relatively low level of exposures to many environmental pollutants. To tackle the challenging problem of assessing the health risk of exposure to a mixture of environmental pollutants, we propose a statistical approach to assessing the proportion of the variation of an outcome explained by a mixture of pollutants. The proposed approach avoids the difficult task of identifying specific pollutants that are responsible for the effects and may also be used to assess interactions among exposures. Extensive simulation results demonstrate that the proposed approach has very good performance. Application of the proposed approach is illustrated by investigating the main and interaction effects of the chemical pollutants on systolic and diastolic blood pressure in participants from the National Health and Nutrition Examination Survey.

Powering Research through Innovative Methods for Mixtures in Epidemiology (PRIME) Program: Novel and Expanded Statistical Methods.

Humans are exposed to a diverse mixture of chemical and non-chemical exposures across their lifetimes. Well-designed epidemiology studies as well as sophisticated exposure science and related technologies enable the investigation of the health impacts of mixtures. While existing statistical methods can address the most basic questions related to the association between environmental mixtures and health endpoints, there were gaps in our ability to learn from mixtures data in several common epidemiologic scenarios, including high correlation among health and exposure measures in space and/or time, the presence of missing observations, the violation of important modeling assumptions, and the presence of computational challenges incurred by current implementations. To address these and other challenges, NIEHS initiated the Powering Research through Innovative methods for Mixtures in Epidemiology (PRIME) program, to support work on the development and expansion of statistical methods for mixtures. Six independent projects supported by PRIME have been highly productive but their methods have not yet been described collectively in a way that would inform application. We review 37 new methods from PRIME projects and summarize the work across previously published research questions, to inform methods selection and increase awareness of these new methods. We highlight important statistical advancements considering data science strategies, exposure-response estimation, timing of exposures, epidemiological methods, the incorporation of toxicity/chemical information, spatiotemporal data, risk assessment, and model performance, efficiency, and interpretation. Importantly, we link to software to encourage application and testing on other datasets. This review can enable more informed analyses of environmental mixtures. We stress training for early career scientists as well as innovation in statistical methodology as an ongoing need. Ultimately, we direct efforts to the common goal of reducing harmful exposures to improve public health.

On information coded in gene-environment independence in case-control studies.

For analysis of case-control genetic association studies, it has recently been shown that gene-environment independence in the population can be leveraged to increase efficiency for estimating gene-environment interaction effects in comparison with the standard prospective analysis. However, for the special case in which data on the binary phenotype and genetic and environmental risk factors can be summarized in a 2 × 2 × 2 table, the authors show here that there is no efficiency gain for estimating interaction effects, nor is there an efficiency gain for estimating the genetic and environmental main effects. This contrasts with the well-known result assuming that rare phenotype prevalence and gene-environment independence in the control population for the same data can lead to efficiency gain. This discrepancy is counterintuitive, since the 2 likelihoods are also approximately equal when the phenotype is rare. An explanation for the paradox based on a theoretical analysis is provided. Implications of these results for data analyses are also examined, and practical guidance on analyzing such case-control studies is offered.

Multiple imputation for missing values through conditional Semiparametric odds ratio models.

Multiple imputation is a practically useful approach to handling incompletely observed data in statistical analysis. Parameter estimation and inference based on imputed full data have been made easy by Rubin's rule for result combination. However, creating proper imputation that accommodates flexible models for statistical analysis in practice can be very challenging. We propose an imputation framework that uses conditional semiparametric odds ratio models to impute the missing values. The proposed imputation framework is more flexible and robust than the imputation approach based on the normal model. It is a compatible framework in comparison to the approach based on fully conditionally specified models. The proposed algorithms for multiple imputation through the Markov chain Monte Carlo sampling approach can be straightforwardly carried out. Simulation studies demonstrate that the proposed approach performs better than existing, commonly used imputation approaches. The proposed approach is applied to imputing missing values in bone fracture data.

Non-invasive prenatal diagnosis of trisomy 21 by reverse transcriptase multiplex ligation-dependent probe amplification.

BACKGROUND: Obtaining fetal DNA or RNA by either chorionic villus sampling (CVS) or amniocentesis is currently, the gold standard prenatal diagnosis. However, these invasive procedures carry risk of miscarriage. A reliable method for non-invasive prenatal diagnosis (NIPD) has long been sought to reduce the risk of miscarriage. METHODS: Cell-free fetal RNA was extracted from the plasma of peripheral blood from 121 women 9-20 weeks of pregnancy. Five single nucleotide polymorphism (SNP) loci in PLAC4 gene were analyzed by reverse transcriptase multiplex ligation-dependent probe amplification (RT-MLPA), followed by capillary electrophoresis. Karyotype analysis was used for confirmation of prenatal diagnosis of trisomy 21. RESULTS: Of 121 samples, 23 were diagnosed with trisomy 21, 87 with normal ploidy, nine had all five SNP loci homozygous and two had one heterozygous SNP locus. Comparing with karyotype analysis, the diagnostic sensitivity and specificity of RT-MLPA were 92% and 100%, respectively. CONCLUSIONS: RT-MLPA is a convenient and reliable method for the diagnosis of trisomy 21. We have shown that this method has good specificity, high sensitivity, and high throughput, making this technique applicable for NIPD in clinical practice.

[Genotyping for CYP2C19 with multiplex PCR point mutation screening technology].

OBJECTIVE: To establish a multiplex PCR point mutation screening technique for the genotyping of CYP2C19. METHODS: Deoxyinosine multiplex-polymerase chain reaction (PCR) primers (DMPs) were designed to detect simultaneously CYP2C19*1,*2,*3 alleles in one PCR tube. RESULTS: The above technique could detect the genotypes of CYP2C19*1, CYP2C19*2 and CYP2C19*3 successfully. And the results were completely consistent with those of DNA sequencing. CONCLUSION: A novel screening technique of multiplex PCR point mutation is successfully established. With the advantages of high specificity, convenient handling, fast completion and low cost, it provides a reasonable and reliable detection method for basic researches and personalized medicine.

Representations of efficient score for coarse data problems based on Neumann series expansion.

We derive new representations of the efficient score for coarse data problems based on Neumann series expansion. The representations can be applied to both ignorable and nonignorable coarse data. An approximation to the new representation may be used for computing locally efficient scores in such problems. We show that many of the successive approximation approaches to the computation of the locally efficient score proposed in the literature for coarse data problems can be derived as special cases of the representations. In addition, the representations lead to new algorithms for computing the locally efficient scores for the coarse data problems.

Prenatal exposure to multiple metals and birth outcomes: An observational study within the National Children's Study cohort.

BACKGROUND: Prenatal exposure to metals may play an important role in fetal growth. However, the epidemiologic evidence for certain metals is sparse, and most of the existing research has focused on evaluating single metals in highly exposed target populations. OBJECTIVES: We evaluated associations of cadmium, lead, manganese, selenium, and total mercury exposures during pregnancy with fetal growth using data from mother-infant pairs participating in the National Children's Study. METHODS: Prenatal metal exposures were measured using maternal blood collected from 6 to 32 weeks of gestation. Birth outcomes, including gestational age, birthweight, birth length, head circumference, and ponderal index, were ascertained through physical measurement at birth or abstraction from medical records. Regression coefficients and their 95% confidence intervals were estimated from multivariable linear regression models in the overall study population as well as among male and female infants. We further evaluated pairwise metal-metal interactions. RESULTS: Sex-specific associations were observed for lead, with inverse associations for birthweight, birth length, head circumference, and gestational age observed only among female infants. Sex-specific associations were also observed for selenium, with a positive association for birthweight observed among male infants; selenium was also positively associated with ponderal index and inversely associated with birth length among female infants. Overall, total mercury was inversely associated with birthweight and ponderal index, and the association with birthweight was stronger among female infants. No significant associations were observed with cadmium and manganese. In the metal-metal interaction analyses, we found evidence of a synergistic interaction between lead and total mercury and antagonistic interaction between selenium and total mercury with selected birth outcomes. CONCLUSIONS: Our findings suggest that prenatal exposure to metals may be related to birth outcomes, and infant sex may modify these associations.