Association of asthma with the risk of acute leukemia and non-Hodgkin lymphoma

Shared genetic architecture between autoimmune disorders and B-cell acute lymphoblastic leukemia: insights from large-scale genome-wide cross-trait analysis

BACKGROUND

To study the shared genetic structure between autoimmune diseases and B-cell acute lymphoblastic leukemia (B-ALL) and identify the shared risk loci and genes and genetic mechanisms involved.

METHODS

Based on large-scale genome-wide association study (GWAS) summary-level data sets, we observed genetic overlaps between autoimmune diseases and B-ALL, and cross-trait pleiotropic analysis was performed to detect shared pleiotropic loci and genes. A series of functional annotation and tissue-specific analysis were performed to determine the influence of pleiotropic genes. The heritability enrichment analysis was used to detect crucial immune cells and tissues. Finally, bidirectional Mendelian randomization (MR) methods were utilized to investigate the casual associations.

RESULTS

Our research highlighted shared genetic mechanisms between seven autoimmune disorders and B-ALL. A total of 73 pleiotropic loci were identified at the genome-wide significance level (P < 5 × 10-8), 16 of which had strong evidence of colocalization. We demonstrated that several loci have been previously reported (e.g., 17q21) and discovered some novel loci (e.g., 10p12, 5p13). Further gene-level identified 194 unique pleiotropic genes, for example IKZF1, GATA3, IKZF3, GSDMB, and ORMDL3. Pathway analysis determined the key role of cellular response to cytokine stimulus, B cell activation, and JAK-STAT signaling pathways. SNP-level and gene-level tissue enrichment suggested that crucial role pleiotropic mechanisms involved in the spleen, whole blood, and EBV-transformed lymphocytes. Also, hyprcoloc and stratified LD score regression analyses revealed that B cells at different developmental stages may be involved in mechanisms shared between two different diseases. Finally, two-sample MR analysis determined causal effects of asthma and rheumatoid arthritis on B-ALL.

CONCLUSIONS

Our research proved shared genetic architecture between autoimmune disorders and B-ALL and shed light on the potential mechanism that might involve in.

Early immune stimulation and childhood acute lymphoblastic leukemia in Costa Rica: A comparison of statistical approaches

BACKGROUND

Although epidemiologic studies suggest that early immune stimulation is protective against childhood leukemia, evidence for this relationship is equivocal for Hispanic children, who are disproportionately affected by this disease. The complex biological processes underlying immune stimulation and leukemogenesis may benefit from novel statistical approaches that account for mixed exposures and their nonlinear interactions. In this study, we utilized targeted machine learning and traditional statistical methods to investigate the association of multiple measures of early immune stimulation with acute lymphoblastic leukemia (ALL) in Costa Rican children.

MATERIALS AND METHODS

We used data from a population-based case-control study conducted in Costa Rica (2001-2003). Cases of ALL (n = 240) were diagnosed in 1995-2000 (age >1 year and <15 years at diagnosis) and were identified through the National Cancer Registry and National Children's Hospital. Population controls (n = 578) were frequency-matched to cases by birth year and drawn from the National Birth Registry. Data on surrogate measures of early immune stimulation were collected through in-home interviews. We fitted multivariable models, utilizing targeted causal inference (varimpact), unconditional logistic regression, and latent class analysis (LCA).

RESULTS

In varimpact analysis, contact with any pet [risk difference (RD) = -0.17, 95% CI: -0.25, -0.10)] or any farm animal (RD = -0.07, 95% CI: -0.13, 0.00) and allergies (RD = -0.08, 95% CI: -0.17, 0.01) were associated with a reduced risk of ALL, whereas experiencing a fever longer than one week was associated with an increased risk (RD = 0.23, 95% CI: 0.12, 0.33). In unconditional logistic regression models, contact with any pet or farm animal and a complete vaccination scheme were inversely associated with odds of ALL (OR = 0.44, 95% CI: 0.31, 0.62; OR = 0.66, 95% CI: 0.49, 0.90; OR = 0.45, 95% CI: 0.24, 0.83; respectively), whereas experiencing a fever longer than one week was positively associated with ALL (OR = 2.44, 95% CI: 1.61, 3.70). Two-class and three-class LCA revealed a group with elevated risk for ALL whose exposure profile was mainly characterized by reduced exposure to pets and farm animals.

CONCLUSIONS

Using distinct statistical approaches, we observed that exposure to pets and farm animals was inversely associated with ALL risk, whereas having a fever longer than one week (a putative proxy of severe infection) was associated with an increased risk. For multifactorial diseases such as childhood leukemia, we recommend estimating the joint effects of multiple exposures by applying diverse statistical methods and interpreting their results together. Overall, we found support for the hypothesis that early immune stimulation offers protection against childhood ALL.

A review on the pathophysiology of asthma remission

Asthma is a chronic respiratory condition, which is highly prevalent worldwide. Although no cure is currently available, it is well recognized that some asthma patients can spontaneously enter remission of the disease later in life. Asthma remission is characterized by absence of symptoms and lack of asthma-medication use. Subjects in asthma remission can be divided into two groups: those in clinical remission and those in complete remission. In clinical asthma remission, subjects still have a degree of lung functional impairment or bronchial hyperresponsiveness, while in complete asthma remission, these features are no longer present. Over longer periods, the latter group is less likely to relapse. This remission group is of great scientific interest due to the higher potential to find biomarkers or biological pathways that elicit or are associated with asthma remission. Despite the fact that the definition of asthma remission varies between studies, some factors are reproducibly observed to be associated with remitted asthma. Among these are lower levels of inflammatory markers, which are lowest in complete remission. Additionally, in both groups some degree of airway remodeling is present. Still, the pathological disease state of asthma remission has been poorly investigated. Future research should focus on at least two aspects: further characterisation of the small airways and airway walls in order to determine histologically true remission, and more thorough biological pathway analyses to explore triggers that elicit this phenomenon. Ultimately, this will result in pharmacological targets that provide the potential to steer the course of asthma towards remission.

Systematic identification of latent disease-gene associations from PubMed articles

Recent scientific advances have accumulated a tremendous amount of biomedical knowledge providing novel insights into the relationship between molecular and cellular processes and diseases. Literature mining is one of the commonly used methods to retrieve and extract information from scientific publications for understanding these associations. However, due to large data volume and complicated associations with noises, the interpretability of such association data for semantic knowledge discovery is challenging. In this study, we describe an integrative computational framework aiming to expedite the discovery of latent disease mechanisms by dissecting 146,245 disease-gene associations from over 25 million of PubMed indexed articles. We take advantage of both Latent Dirichlet Allocation (LDA) modeling and network-based analysis for their capabilities of detecting latent associations and reducing noises for large volume data respectively. Our results demonstrate that (1) the LDA-based modeling is able to group similar diseases into disease topics; (2) the disease-specific association networks follow the scale-free network property; (3) certain subnetwork patterns were enriched in the disease-specific association networks; and (4) genes were enriched in topic-specific biological processes. Our approach offers promising opportunities for latent disease-gene knowledge discovery in biomedical research.

Association between allergic conditions and risk of prostate cancer: A Prisma-Compliant Systematic Review and Meta-Analysis

Association between allergic conditions and prostate cancer risk has been investigated for many years. However, the results from available evidence for the association are inconsistent. We conducted a meta-analysis to evaluate the relationship between allergic conditions (asthma, atopy, hay fever and “any allergy”) and risk of prostate cancer. The PubMed and Embase databases were searched to screen observational studies meeting our meta-analysis criteria. Study selection and data extraction from included studies were independently performed by two authors. Twenty studies were considered eligible involving 5 case-control studies and 15 cohort studies. The summary relative risk (RR) for developing prostate cancer risk was 1.04 (95%CI: 0.92–1.17) for asthma, and 1.25 (95%CI: 0.74–2.10) for atopy, 1.04 (95%CI: 0.99–1.09) for hay fever, 0.96 (95%CI: 0.86–1.06) for any allergy. In the Subgroup and sensitivity analysis, similar results were produced. Little evidence of publication bias was observed. The present meta-analysis of observational studies indicates that no indication of an association between allergic conditions and risk of prostate cancer was found, and the meta-analysis does not support neither the original hypothesis of an overall cancer protective effect of allergic conditions, nor that of an opposite effect in the development of prostate cancer.

Decreased Level of IgE is Associated with Breast Cancer and Allergic Diseases

Background

The aim of this study was to explore the prevalence of type I allergic diseases in patients with breast cancer by carrying out a questionnaire survey and IgE detection in a healthy population and in patients with breast cancer.

Material/Method

There were 309 patients enrolled and they were further divided into the type I allergic disease group, the newly diagnosed breast cancer with type I allergic disease group, the re-visit breast cancer with type I allergic disease group, and the re-visit breast cancer without type I allergic disease group, as well as a healthy control group. Serum total IgE level was detected by immunoassay.

Results

The IgE value in the healthy population with type I allergic diseases (89.3±51.4 IU/ml) was significantly higher than in those without type I allergic diseases (45.6±65.1 IU/ml). There was no significant difference between IgE values in the re-visit breast cancer patients with type I allergic disease (25.1±65.1 IU/ml) and those without type I allergic disease (23.0±45.9 IU/ml). The area under the ROC curve was 0.618±0.04, sensitivity was 78%, specificity was 47.1%, Youden index was 0.251, and IgE threshold was 32.6 IU/ml.

Conclusions

The patients with newly diagnosed breast cancer were susceptible to type I allergic disease at about the same levels as in the healthy population. There was no correlation between breast cancer and type I allergic disease.