Association of a 4-Locus Gene Model Including IL13, IL4, FCER1B, and ADRB2 With the Asthma Predictive Index and Atopy in Chinese Han Children

Bai, Shaochun; Li, Hua; Wang, X; Liu, Q; Bao, Yuqian

doi:10.18176/jiaci.0272

Cited by 11 publications

(13 citation statements)

References 30 publications

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“…Also, the original API was used to explore the effect of a smart nebulizing device on the rate of adherence to ICS in Chinese preschoolers with positive API ( n = 65), showing a significant improve in the rate of adherence, and reducing the frequency of emergency visits and respiratory infections, as well as the usage of antibiotics or systemic steroids (34). A recent study (35) in Chinese Han preschoolers ( n = 385) reported association of four-gene model consisting of IL13 rs20541, IL4 rs2243250, ADRB2 rs1042713, and FCER1B rs569108 with the original API [OR = 4.08, p < 0.0001; and OR = 2.36, p < 0.0001, for stringent and loose API, respectively].…”

Section: Predictive Models For Prognostic or Diagnostic Toolsmentioning

confidence: 99%

Predicting Asthma Using Clinical Indexes

2019

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Asthma is no longer considered a single disease, but a common label for a set of heterogeneous conditions with shared clinical symptoms but associated with different cellular and molecular mechanisms. Several wheezing phenotypes coexist at preschool age but not all preschoolers with recurrent wheezing develop asthma at school-age; and since at the present no accurate single screening test using genetic or biochemical markers has been developed to determine which preschooler with recurrent wheezing will have asthma at school age, the asthma diagnosis still needs to be based on clinical predicted models or scores. The purpose of this review is to summarize the existing and most frequently used asthma predicting models, to discuss their advantages/disadvantages, and their accomplishment on all the necessary consecutive steps for any predictive model. Seven most popular asthma predictive models were reviewed (original API, Isle of Wight, PIAMA, modified API, ucAPI, APT Leicestersher, and ademAPI). Among these, the original API has a good positive LR~7.4 (increases the probability of a prediction of asthma by 2–7 times), and it is also simple: it only requires four clinical parameters and a peripheral blood sample for eosinophil count. It is thus an easy model to use in any rural or urban health care system. However, because its negative LR is not good, it cannot be used to rule out the development of asthma.

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Section: Predictive Models For Prognostic or Diagnostic Toolsmentioning

confidence: 99%

Predicting Asthma Using Clinical Indexes

2019

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“…Its pathogenesis is extremely complex. The genes encoding these cytokines determine the occurrence and development of asthma 17 . Therefore, exploring immunological mechanisms underlying childhood asthma as well as identifying biological markers that predict asthma progression is vital for reducing the incidence of childhood asthma and implementing bilevel preventive measures.…”

Section: Discussionmentioning

confidence: 99%

Significance of Immune-related Genes in the Diagnosis and Subtype Classification of Childhood Asthma

Dai

Sun

Cai

et al. 2020

Preprint

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Background Childhood asthma is one of the most common causes of hospitalization in children, causing huge economic losses worldwide. The immune system was closely linked to the occurrence and development of childhood asthma. The main purpose of this research is to explore the role of immune-related genes in the occurrence and treatment of childhood asthma.Methods GSE40732 dataset and GSE40888 dataset were respectively regarded as training dataset and texting dataset in this article. We performed weighted gene co-expression network analysis (WGCNA) to select immune-related genes associated with the occurrence of childhood asthma based on the training dataset. Random forest (RF) model was established to screen the optimal variables to predict the occurrence of childhood asthma among these significant immune-related genes. Childhood asthma patients were grouped by the consensus clustering method based on the optimal variables. The grouping results were validated in the texting dataset. Results 69 significant immune-related genes associated with the occurrence of childhood asthma were screened through WGCNA. RF model indicated that 10 optimal variables among these significant immune-related genes can reasonably distinguish normal children and childhood asthma. Childhood asthma patients were classified into two molecular subtypes (Sub1 and Sub2) based on the 10 optimal variables using consensus clustering analysis. More interestingly, childhood asthma patients in Sub1 have higher inflammatory response than Sub2.Conclusions Our research selected 10 significant immune-related genes related to the occurrence of childhood asthma. We classified childhood asthma patients into two molecular subtypes with different immune cell infiltration based on the 10 significant immune-related genes, which may provide the basis for individualized treatment.

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“…More risk homozygotes of the four SNPs, higher risk for asthma and atopy 7 . As described in our previous study, the genotype combinations with no risk homozygotes (i.e., rs20541 AA or GA, rs2243250 CC or TC, rs1042713 GG or AG, and rs569108 AA or AG) were considered as the control, and those genotype combinations with a significantly higher risk for asthma and atopy ( p < .05 and odds ratio [OR] > 1) compared with the control were categorized as high risk, otherwise as low risk 8 . Genetic risk grouping was shown in Table 2.…”

Section: Methodsmentioning

confidence: 99%

“…Each of the four SNPs had an independent effect on asthma, with rs20541 G, rs2243250 T, rs1042713 A, and rs569108 G as the risk alleles, and more risk homozygotes of the four SNPs, higher risk for asthma 7 . Then we applied the four‐gene model among Chinese Han wheezing children and found that the high‐risk genotypes were associated with a positive Asthma Predictive Index and atopy 8 . In a word, the four‐locus gene model has been confirmed associated with asthma and atopy in Chinese Han children 7,8 .…”

Section: Introductionmentioning

confidence: 99%

“…Then we applied the four‐gene model among Chinese Han wheezing children and found that the high‐risk genotypes were associated with a positive Asthma Predictive Index and atopy 8 . In a word, the four‐locus gene model has been confirmed associated with asthma and atopy in Chinese Han children 7,8 . However, whether the gene model is associated with allergies in early life has yet to be determined.…”

Section: Introductionmentioning

confidence: 99%

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Association of a four‐gene model with allergic diseases: Two‐year follow‐up of a birth cohort study

Yang

Chen

et al. 2020

Immunity Inflam & Disease

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Background Our previous study has developed a four‐gene model involving IL13 rs20541, IL4 rs2243250, ADRB2 rs1042713, and FCER1B rs569108 associated with asthma and atopy in Chinese Han children. However, whether the gene model is associated with allergies in early life has yet to be determined. This study aimed to apply the gene model in a birth cohort to investigate its associations with the development of allergic diseases in Chinese Han toddlers. Methods Five hundred and ninety‐seven children from a birth cohort completing 2‐year follow‐up were included. Epidemiologic information and cord blood were collected. Children were genotyped for the above polymorphisms and divided into high or low genetic risk groups based on the genotypes. Subjects were followed at 6, 12, and 24 months, with information on allergic diseases collected via standard questionnaires and assessed by specialists. Results Two hundred and eighty‐four children were divided into a high‐risk group and 313 into a low‐risk group. Between the two groups, a significant difference was only found in delivery mode among all the subject characteristics (p = .025). After stratification for delivery mode, children at high risk were more likely to develop eczema (relative risk [RR] = 1.46, p = .040) over 2 years of follow‐up compared with those at low risk. No significant associations were found between genetic risk and food allergy, wheezing and allergic rhinitis (p > .05). Conclusion The gene model was significantly associated with the development of eczema in Chinese Han toddlers. Long‐term follow‐up along with functional and replication studies on the gene model are still needed in future.

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Association of a 4-Locus Gene Model Including IL13, IL4, FCER1B, and ADRB2 With the Asthma Predictive Index and Atopy in Chinese Han Children

Cited by 11 publications

References 30 publications

Predicting Asthma Using Clinical Indexes

Predicting Asthma Using Clinical Indexes

Significance of Immune-related Genes in the Diagnosis and Subtype Classification of Childhood Asthma

Association of a four‐gene model with allergic diseases: Two‐year follow‐up of a birth cohort study

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