The association between nonsteroidal anti-inflammatory drugs and skin cancer: Different responses in American and European populations.

OBJECTIVE: To conduct a comprehensive systematic meta-analysis investigating the association of nonsteroidal anti-inflammatory drugs (NSAIDs) and their subtypes with skin cancer (SC) and its subclasses (basal cell carcinoma BCC; squamous cell carcinoma SCC; melanoma; nonmelanoma skin cancer NMSC) in general, American and European populations. METHODS: PubMed, Embase, the Cochrane Library, the China National Knowledge Infrastructure and ClinicalTrials.gov were searched up to 24 February 2019. Pooled effect sizes and 95% confidence intervals were used to estimate associations. RESULTS: Results based on 26 original studies including 223,619 cases and 1,398,507 controls showed both NSAIDs and nonselective Cyclooxygenase (COX) inhibitors to be statistically significantly associated with a reduced risk of SC, BCC, SCC and NMSC but not with melanoma. Conversely, no association was observed between selective Cyclooxygenase 2 (COX-2) inhibitors and SC or its subclasses. Further subgroup analysis showed that the results analyzed for American populations were almost the same as those for the general population. For European populations, neither NSAIDs nor its subtypes correlated significantly with susceptibility to SC or its subclasses. CONCLUSIONS: The use of NSAIDs might reduce the risk of SC, but many factors including study population, drug subtype, and disease subclass affect the significance of the association.

Advanced stratification analyses in molecular association meta-analysis: methodology and application.

BACKGROUND: Stratification analyses have been widely utilized in molecular association meta-analyses to estimate the interaction between genetic and environmental factors or to control for the confounding variables linked to a disease. Two calculation methods utilized in practical research, which are known as the variants of factorial stratification analysis and confounder-controlling stratification analysis in our nomenclature, have been applied in previous studies, but none of which have presented a methodology and application for these analyses. METHODS: In this paper, these two approaches are integrated and further developed into a standard procedure for stratification analysis. We first propose the advanced statistical methodology and theoretical algorithm of these three types of stratification analysis and then provide two example applications in meta-analyses of molecular association to illustrate the computing processes and interpretation of the results. RESULTS: The standard stratification analysis synthesizes the advantages of the first two practical methods, including identifying and controlling confounding moderators or revealing and calculating gene-environment interactions, to efficiently classify the real influence of various investigated factors on a disease in the general population. Additional challenges concerning this method and their potential solutions are also discussed, such as the approach to utilizing only the partially stratified data available in meta-research practice. CONCLUSIONS: The standard stratification method will be extensively applicable to rapidly expanding future research on the complex relationships among genetics, environment, disease, and other variables.

Association of Dopamine Beta-Hydroxylase Polymorphisms with Alzheimer's Disease, Parkinson's Disease and Schizophrenia: Evidence Based on Currently Available Loci.

BACKGROUND/AIMS: The neuropathies Alzheimer's disease (AD), Parkinson's disease (PD), and schizophrenia (SCZ) have different pathological mechanisms but share some common neurodegenerative features, such as gradual loss of neuronal structure and function. Dopamine beta-hydroxylase (DBH), a gene located in the chromosomal region 9q34, plays a crucial role in the process of converting dopamine into norepinephrine (NE). Several case-control studies have reported this pathway in the pathogenesis of AD, PD and SCZ. However, the results are controversial. METHODS: We conducted a meta-analysis to estimate the associations between polymorphisms in this gene and AD, PD and SCZ. Seven databases (PubMed, Embase, Web of Science, China National Knowledge Infrastructure (CNKI), Wan Fang, SZ Gene and AD Gene) were searched to identify eligible studies. Odds ratios (ORs) with 95% confidence intervals (CIs) were calculated to evaluate the associations of DBH variants with AD, PD and SCZ susceptibility. RESULTS: A total of 41 studies involving 10506 cases and 15083 controls were included in our meta-analysis. The analysis results indicated that a lack of association (P > 0.05) was observed between most of the currently available DBH polymorphisms and the neurological diseases AD, PD and SCZ; however, the DBH rs1611131 (allelic model: OR = 0.889, 95% CI: 0.815 - 0.969; dominant model: OR = 0.868, 95% CI: 0.778 - 0.968), rs2283123 (allelic model: OR = 0.285, 95% CI: 0.095 - 0.862; dominant model: OR = 0.290, 95% CI: 0.094 -0.897) and rs2007153 (allelic model: OR = 2.196, 95% CI: 1.506 - 3.200; dominant model: OR = 2.985, 95% CI: 1.465 - 6.084; recessive model: OR = 2.729, 95% CI: 1.548 - 4.812) variants were shown to be significantly associated with the risk of AD (the former variant) and SCZ (the latter two variants). CONCLUSION: On the one hand, most DBH polymorphisms from the currently available loci showed no linkage to AD, PD or SCZ, indicating the lower possibility of these loci serving as genetic markers of the risks of diseases with neurodegenerative characteristics. On the other hand, the DBH rs2283123 and rs2007153 polymorphisms could have opposite effects on SCZ development in Caucasians and be more specific in Croatians, while the DBH rs1611131 minor variant might have a protective effect on AD risk in Caucasians; however, these results require further study.

Association Between a History of Breast Cancer and Decreased Thyroid Cancer-specific Mortality.

CONTEXT: The clinical relevance of the well-known association between thyroid cancer (TC) and breast cancer (BC) remains to be further defined. OBJECTIVE: This work aimed to investigate the effect of history of BC on the prognosis of TC. METHODS: This was a comparative cohort study of tumor behaviors and TC-specific mortality in 5598 patients with papillary thyroid cancer (PTC) and 604 patients with follicular thyroid cancer (FTC), all with a history of BC (TC-BC patients), and their propensity score-matched TC patients without a history of BC (TCnoBC patients) in Surveillance, Epidemiology and End Results (SEER) 18. The main outcome measure was TC-specific mortality. RESULTS: Lower TC distant metastasis rates of 2.4% vs 3.0% in PTC and 6.1% vs 9.1% in FTC and TC-specific mortality rates of 1.3% vs 2.6% in PTC and 5.8% vs 8.4% in FTC were found in TC-BC patients vs matched TCnoBC patients (all P < .05). Comparing TC-BC patients with matched TCnoBC patients, hazard ratios (HRs) for mortality were 0.472 (95% CI, 0.370-0.601) in PTC and 0.656 (95% CI, 0.461-0.934) in FTC (all P < .05). Such HRs for mortality in PTC were 0.397 (95% CI, 0.268-0.588; P < .001) when TC occurred before BC vs 0.607 (95% CI, 0.445-0.827; P = .002) when BC occurred before TC. CONCLUSION: This study demonstrates a robust protective effect of a history of BC on TC-specific patient survival, which has strong implications for more precise prognostication of TC in such patients.

Coexisting RET/PTC and TERT Promoter Mutation Predict Poor Prognosis but Effective RET and MEK Targets in Thyroid Cancer.

PURPOSE: To investigate the role of coexisting RET/PTC rearrangement and TERT promoter mutation in the prognosis and therapeutic targeting in papillary thyroid cancer (PTC). METHODS: A total of 669 PTC patients with complete clinical follow-up and genetic data were pooled from thyroid cancer datasets TCGA, MSK MetTropism, and MSK-IMPACT, from whom 163 patients (112 women and 47 men, 4 unknown) with wild-type BRAF/RAS were identified, with median age (IQR) of 46.00 (33.00, 61.00) years and median follow-up time (IQR) of 16.13 (8.09, 27.91) months for comparative genotype cohort analysis of mortality. RESULTS: There was a significant concurrence index between RET/PTC and TERT promoter mutations, being 2.040 (95% CI 1.110-3.747, P = 0.023). Mortality occurred in 5/100 (5%) patients harboring neither mutation, 2/18 (11.1%) patients harboring TERT promoter mutation alone, 0/31 (0%) patients harboring RET/PTC alone, and 7/14 (50%) patients harboring both genetic alterations, corresponding to HRs (95% CI) of 1 (Reference), 2.469 (0.405-14.02), 3.296e-09 (0-inf), and 9.019 (2.635-30.87), respectively, which remained essentially unchanged after adjustment for patient race, sex, and age. Similar results were observed with BRAF/RAS and TERT promoter mutations. Mechanistically, RET/PTC used the MAP kinase pathway to upregulate the mutated TERT, but not the wild-type TERT, and, correspondingly, targeting RET and MEK could suppress mutated TERT but not the wild-type TERT. CONCLUSION: Coexisting RET/PTC and TERT promoter mutation identify PTC as a unique clinical entity with high mortality, providing new implications for genetic-based prognostication and potential therapeutic targeting of RET and MEK guided by RET/PTC and TERT status.

HLA-DQB1 and HLA-DRB1 Variants Confer Susceptibility to Latent Autoimmune Diabetes in Adults: Relative Predispositional Effects among Allele Groups.

Latent autoimmune diabetes in adults (LADA) was recently demonstrated to be the most frequent form of adult-onset autoimmune diabetes mellitus. Case-control studies have investigated the relationship between human leukocyte antigen (HLA)-DQB1 and HLA-DRB1 polymorphisms and LADA risk, but their conclusions are inconsistent. This study aimed to more precisely explore the correlation between these HLA gene variants and LADA development. Eight databases, including PubMed, Embase, and Medline, were systematically searched for relevant studies up to September 15, 2018. We performed this retrospective study using meta-analysis and relative predispositional effect (RPE) methods. The meta-analysis results indicated that DQB1*02 (odds ratio (OR) = 1.685, pc < 0.005) and DQB1*06 (OR = 0.604, pc = 0.010) have opposite effects on susceptibility to LADA, while a significant decrease in LADA risk caused by DQB1*05 (OR = 0.764, pc = 0.100) disappeared upon Bonferroni correction. The RPE method confirmed the roles of DQB1*02 (χ² = 46.475, p < 0.001) and DQB1*06 (χ² = 17.883, p < 0.001) and further suggested protective effects of DQB1*05 (χ² = 16.496, p < 0.001). Additionally, the meta-analysis results showed that DRB1*03 (OR = 2.685, pc < 0.013), DRB1*04 (OR = 1.954, pc < 0.013), and DRB1*09 (OR = 1.346, pc < 0.013) are associated with increased LADA risk, while DRB1*12 (OR = 0.600, pc < 0.013) and DRB1*13 (OR = 0.583, pc < 0.013) carriers have a decreased risk of developing LADA. Furthermore, the RPE method revealed that DRB1*03 (χ² = 98.754, p < 0.001), DRB1*04 (χ² = 94.685, p < 0.001), DRB1*09 (χ² = 40.489, p < 0.001), DRB1*01 (χ² = 12.181, p < 0.001), DRB1*07 (χ² = 10.882, p = 0.001), and DRB1*08 (χ² = 5.000, p = 0.025) play protective roles against LADA. LADA showed a close relationship with genetic polymorphisms of HLA-DQB1 and WHLA-DRB1, which could contribute to a better understanding of disease pathogenesis and the identification of predisposing loci in the diagnosis and treatment of LADA.

Prognostic Impact of Tissue Inhibitor of Metalloproteinase-1 in Non- Small Cell Lung Cancer: Systematic Review and Meta-Analysis.

BACKGROUND AND OBJECTIVES: Tissue Inhibitor of Metalloproteinase-1 (TIMP-1) is a multifunctional natural matrixin inhibitor that is generally considered a negative regulator of cancer metastasis. Clinical studies reporting the prognostic value of TIMP-1 in Non-small Cell Lung Cancer (NSCLC) are inconsistent. Therefore, the present study aimed to determine the prognostic impact of TIMP-1 expression in NSCLC. METHODS: Appropriate studies with full-text articles were identified in searches of the China National Knowledge Infrastructure (CNKI), Cochrane Library, PubMed, and Web of Science databases up to March 7, 2018. The pooled Hazard Ratio (HR) of overall survival with a 95% confidence interval (95% CI) was employed to assess the relationship between the expression of TIMP-1 and NSCLC patient survival. RESULTS: The meta-analysis comprised 40 studies including 3,194 patients. Study outcomes indicated that high TIMP-1 expression is independently associated with poor overall survival (HR: 1.60; 95% CI: 1.50, 1.69; P < 0.00001) with 61% of heterogeneity. In addition, we analyzed subgroups, including ethnicities, histological types, percentage of TIMP-1 expression levels, specimens, and tumor stage. All results were statistically significant. The outcome of our meta-analysis indicates that high expression levels of TIMP-1 are correlated with poor prognosis in patients with NSCLC. CONCLUSION: Expression levels of TIMP-1 represent a potential prognostic biomarker in NSCLC patients in addition to being a possible therapeutic target.

Controlling for confounding factors and revealing their interactions in genetic association meta-analyses: a computing method and application for stratification analyses.

Subgroup and stratification analyses have been widely applied in genetic association studies to compare the effects of different factors or control for the effects of the confounding variables associated with a disease. However, studies have not systematically provided application standards and computing methods for stratification analyses. Based on the Mantel-Haenszel and Inverse-Variant approaches and two practical computing methods described in previous studies, we propose a standard stratification method for meta-analyses that contains two sequential steps: factorial stratification analysis and confounder-controlling stratification analysis. Examples of genetic association meta-analyses are used to illustrate these points. The standard stratification analysis method identifies interacting effects on investigated factors and controls for confounding variables, and this method effectively reveals the real effects of these factors and confounding variables on a disease in an overall study population. We also discuss important issues concerning stratification for meta-analyses, such as conceptual confusion between subgroup and stratification analyses, and incorrect calculations previously used for factorial stratification analyses. This standard stratification method will have extensive applications in future research for increasing studies on the complicated relationships between genetics and disease.