Xiaowen Zhang

and 13 more

Background: Growing evidence from observational studies suggests a link between Allergic [rhinitis](https://www.sciencedirect.com/topics/neuroscience/rhinitis) (AR) and psychiatric disorders; whether these associations represent causal relationships remains uncertain. Methods: We performed bi-directional two-sample mendelian randomization (MR) using summary statistics from European genome-wide association studies to examine evidence of causality, specificity and direction of association of AR with 11 different psychiatric disorders or relevant traits. MR was conducted using the inverse-variance weighted method (IVW), MR-Egger and weighted median methods. Sensitivity analyses included the MR-Egger regression and MR pleiotropy residual sum and outlier test. Results: AR from 2 different GWAS data was positively associated with bipolar disorder (OR=1.649, 95% CI: 1.077-2.526; P=0.021; OR=1.599; 95%CI 1.058-2.417; P=0.026). AR was also associated with major depressive disorder (OR=1.539; 95%CI 1.007-2.353; P=0.047). There were no significant association between AR and other 9 psychiatric disorders. Bidirectional analyses showed that bipolar disorder is negatively associated with AR (OR=0.964; 95%CI: 0.936-0.993; P=0.015). There was no evidence for potential causal schizophrenia and effects of attention deficit/hyperactivity disorder on risk of AR by MR method, but, MR pleiotropy residual outlier test suggested that attention deficit/hyperactivity disorder is negatively associated with AR after outlier correction (OR=0.976, 95%CI: 0.958-0.995, P=0.012). Conclusions: This MR study indicated that AR was a causal risk factor for bipolar disorder and major depressive disorder, but not for other psychiatric disorders. Bipolar disorder and attention deficit/hyperactivity disorder may be a protective factor for AR. Further studies could be carried out to leverage these new found insight into better clinical and experimental research in AR and psychiatric disorders.

Xiaowen Zhang

and 10 more

Objectives: World-wide incidence and prevalence of both asthma and type 1 diabetes mellitus (T1DM) has been increasing in past decades. Association between the two diseases has been found in some but not other studies. We conducted a meta-analysis to verify such an association, and bidirectional Mendelian randomization analysis to examine the potential cause-effect relationships. Methods: Three databases(PubMed, Embase and Web of Science) were searched from their inception to February 1, 2021. Pooled hazard ratios (HR) or odds ratios (OR), and 95% confidence intervals, were calculated. Associations between single-nucleotide polymorphisms with childhood asthma and T1DM were selected based on genome-wide association studies. The outcome datasets were obtained from FinnGen study. We used the inverse variance-weighted, weighted median and MR-Egger methods to estimate causal effects. To assess robustness and horizontal pleiotropy, MR-Egger regression and MR pleiotropy residual sum and outlier test was conducted. Results: In meta-analysis, childhood asthma was associated with an increased risk of T1DM (HR=1.30, 95% CI 1.05–1.61, P=0.014), whereas T1DM was not associated with the risk of asthma (HR=0.98, 95% CI 0.64–1.51, P=0.941; OR=0.84, 95% CI 0.65–1.08, P=0.168). MR analysis indicated increased genetic risk of T1DM in children with asthma (OR=1.308; 95% CI 1.030-1.661; P =0.028). Analysis using the IVW method indicated decreased genetic risk of asthma in children with T1DM (OR = 0.937, 95%CI 0.881-0.996, P = 0.037). Conclusions: Childhood asthma is a risk factor for T1DM; T1DM is a possible protective factor for childhood asthma.

Junyang Xie

and 11 more

Background: World-wide incidence and prevalence of both asthma and type 1 diabetes mellitus (T1DM) in children has been increasing in past decades. Association between the two diseases has been found in some but not other studies. Objective: We conducted a meta-analysis to verify such an association, and bidirectional Mendelian randomization analysis to examine the potential cause-effect relationships. Methods: Three databases (PubMed, Embase and Web of Science) were searched from their inception to February 1, 2021. Pooled hazard ratios (HR) or odds ratios (OR), and 95% confidence intervals, were calculated. Associations between single-nucleotide polymorphisms with childhood asthma and T1DM were selected based on genome-wide association studies. The outcome datasets were obtained from FinnGen study. We used the inverse variance-weighted, weighted median and MR-Egger methods to estimate causal effects. To assess robustness and horizontal pleiotropy, MR-Egger regression and MR pleiotropy residual sum and outlier test was conducted. Results: In meta-analysis, childhood asthma was associated with an increased risk of T1DM (HR=1.30, 95% CI 1.05-1.61, P=0.014), whereas T1DM was not associated with the risk of asthma (HR=0.98, 95% CI 0.64-1.51, P=0.941; OR=0.84, 95% CI 0.65-1.08, P=0.168). MR analysis indicated increased genetic risk of T1DM in children with asthma (OR=1.308; 95% CI 1.030-1.661; P =0.028). Analysis using the IVW method indicated not associated between T1DM and genetic risk of asthma (OR=1.027, 95%CI 0.970-1.089, P=0.358). Conclusion: Both meta-analysis and MR study suggested that childhood asthma was a risk factor for T1DM. No epidemiological or genetic evidence for an association of T1DM with asthma incidence. Further studies could be carried out to leverage this newfound insight into better clinical and experimental research in asthma and T1DM. Further studies could be carried out to leverage this newfound insight into better clinical and experimental research in asthma and T1DM.