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Psoriasis Risk In Children With High BMI

Psoriasis Risk In Children With High BMI

Overview

This study aimed to investigate the potential association between childhood body mass index (BMI) and the risk of psoriasis. Using publicly available summary statistics from genome-wide association studies (GWAS) that focused on childhood BMI in individuals of European descent (n=39,620), the researchers conducted a Mendelian randomization (MR) analysis employing three different techniques: inverse variance weighting (IVW), MR-Egger regression, and the weighted median method. The outcome variable was a GWAS for psoriasis, based on self-reported non-cancer disease classification within the UK Biobank population (total n=337,159; cases=3,871; controls=333,288).

The study identified 16 single nucleotide polymorphisms (SNPs) as instrumental variables, all of which had achieved genome-wide significance in childhood BMI GWAS. Using the IVW method, the results indicated a positive and statistically significant causal relationship between childhood BMI and psoriasis (beta=0.003, standard error [SE]=0.001, p=0.006). In contrast, the MR-Egger regression analysis, designed to assess potential directional pleiotropy, showed no evidence of a causal link between childhood BMI and psoriasis (beta=-0.002, SE=0.004, p=0.625).

However, the weighted median method provided evidence supporting a causal relationship between childhood BMI and psoriasis (beta=0.003, SE=0.001, p=0.029). Further assessments, including Cochran’s Q test and the funnel plot, did not reveal significant heterogeneity or asymmetry, suggesting a lack of directional pleiotropy in the dataset.

In summary, this study explored the relationship between childhood BMI and psoriasis. The IVW method suggested a positive causal link, while MR-Egger regression found no evidence of causality. The weighted median method supported a causal relationship, with additional analyses indicating minimal heterogeneity and directional pleiotropy.

Introduction

Psoriasis is a chronic inflammatory skin condition characterized by symptoms like erythema, scaly papules, and plaques, often causing discomfort and sensations of stinging, irritation, burning, and tingling. The development of psoriasis is considered to result from the interplay of genetic and environmental factors, with environmental influences playing a significant role in genetically predisposed individuals. In children, psoriasis has a prevalence of about 0.5%, with a steady rise from 1 to 18 years of age. Notably, a substantial proportion of adults with psoriasis experienced their first onset during childhood. The peak age for psoriasis onset inchildren is generally reported between 2 and 8 years, although there is some debate on whether this varies by gender. Family history plays a substantial role in pediatric psoriasis, with approximately one-third of children having relatives with the condition, and 30% to 50% of first-degree relatives also affected.

 

In children, psoriasis lesions frequently occur on the extremities, while in adults, the scalp is a common site of involvement. Furthermore, Koebner’s phenomenon, the development of skin lesions following trauma or irritation, is more prevalent in children with psoriasis than in adults.

 

The role of adipose tissue in inflammation and immunity is well-recognized. It produces hormone-active substances and chemokines. There is evidence linking excess weight or obesity to an increased risk of psoriasis, with a high body mass index (BMI) being associated with a greater likelihood of the condition. Nevertheless, it remains uncertain whether adolescent obesity causally contributes to the elevated risk of psoriasis.

 

Mendelian randomization (MR) is a research approach that employs genetic variants as instrumental variables (IVs) to determine if a statistical association between a risk factor and an outcome is indicative of a causal relationship. Two-sample MR is used to assess causal links when data on outcomes and exposures are derived from different datasets. Thus far, no MR studies have examined the causative relationship between BMI and psoriasis incidence in children. This study employs MR analysis to explore whether there is a causal connection between BMI and the onset of psoriasis in children.

Method

To investigate the potential causal relationship between childhood BMI and the onset of psoriasis, a search was conducted in the MR Base database. This database aggregates statistical data from a wide array of genome-wide association studies (GWAS). The exposure data used in this analysis were obtained from openly accessible summary statistics datasets derived from GWAS systematic reviews focused on childhood BMI in individuals of European descent, with a total sample size of 39,620.

 

In order to ensure robust inference, a two-sample Mendelian randomization (MR) study design was employed. This approach utilized genetic variants that are associated with childhood BMI as instrumental variables (IVs) for assessing causality. The selection of these genetic variants was based on their reaching a genome-wide significance p-value threshold of 5.00E-08. In total, 16 single-nucleotide polymorphisms (SNPs) linked to childhood BMI were extracted from the GWAS data and used as instrumental variables.

 

The study sample comprised a total of 337,159 individuals, including 3,871 cases with psoriasis and 333,288 controls without the condition. This comprehensive dataset allowed for a rigorous investigation into the potential causal relationship between childhood BMI and the risk of developing psoriasis.

Statistical Analysis

In this Mendelian randomization (MR) analysis, genetic variants functioned as proxies for the exposure variables, and they were not considered potential confounding factors. The study followed a three-step methodology:

 

  1. First, the study examined the individual relationship between each single-nucleotide polymorphism (SNP) and childhood BMI. This step aimed to understand how these genetic variants were associated with childhood BMI.

 

  1. Next, the study explored the relationship between each of these SNPs and the likelihood of developing psoriasis. This step helped establish the link between genetic variations and psoriasis risk.

 

  1. Finally, the study combined the findings from the previous two steps to assess the causal relationship between childhood BMI and psoriasis using MR analysis. Sixteen SNPs were used as instrumental variables (IVs) in the two-sample MR analysis.

 

The MR analysis employed various statistical methods:

 

  • Inverse Variance Weighting (IVW): This method integrated predicted Wald percentages of attributable effects obtained from different SNPs to estimate the correlated impact of childhood BMI on psoriasis risk. It is a systematic review approach that relies on the assumption that all genetic mutations used as IVs meet the required criteria.

 

  • Weighted Median and MR-Egger Regression: These methods were used to account for pleiotropy, which is the phenomenon where a single genetic variant influence multiple traits. MR-Egger can detect and adjust for asymmetrical pleiotropy by considering data summary statistics from various genetic variants.
  • “Leave-One-Out” Approach: To examine the potential influence of individual SNPs on the causal association, the study implemented a “leave-one-out” approach. This involved assessing the impact of each SNP individually on the causal relationship.

 

  • Heterogeneity Evaluation: Cochran’s Q-statistics and I² statistics were used to evaluate heterogeneity among the SNPs. This helped assess the consistency of results across the different genetic variants.

 

All MR analyses were conducted on MR Base, using specific software and versions. A significance level of p<0.05 was considered to indicate statistically significant results. The study rigorously examined the causal relationship between childhood BMI and the incidence of psoriasis, considering various statistical approaches and methods to ensure reliable and robust findings.

Result

The study identified 16 single-nucleotide polymorphisms (SNPs) from genome-wide association studies (GWAS) on childhood BMI that met the criteria for being independently and causally related to childhood BMI at the genome-wide significance level. None of the nine positive associations between these SNPs and psoriasis reached statistical significance. The selected genetic variants, used as instrumental variables (IVs), collectively explained 1.4% of the variation in childhood BMI and exhibited F-statistics greater than 30, indicating their strong relevance and meeting the “weak IV” threshold set at F< 10.

 

Mendelian randomization (MR) analysis was conducted using multiple methods to evaluate the causal relationship between childhood BMI and psoriasis:

 

  1. IVW Method: The IVW method provided support for a causal link between childhood BMI and psoriasis, with a calculated effect size (β) of 0.003 (standard error [SE] = 0.001), and a statistically significant p-value of 0.006.

 

  1. MR-Egger Analysis: This analysis confirmed that directional pleiotropy was unlikely to bias the results, with an intercept value of 0.00039 and a non-significant p-value of 0.247. However, the MR-Egger method indicated no evidence of causation between childhood BMI and psoriasis in children (β = -0.002, SE = 0.004, p = 0.625).

 

  1. Weighted Median Method: The weighted median estimator method provided further evidence supporting a causal relationship (β = 0.003, SE = 0.001, p = 0.029). Although MR-Egger and weighted median methods produced inconsistent estimates, the weighted median method was considered to be more precise, suggesting a potential causal link between childhood BMI and psoriasis.

 

The study also conducted tests for heterogeneity and sensitivity:

 

  • No heterogeneity was detected in the causal effect estimates for each SNP, as indicated by Cochran’s Q test and I² values, suggesting that the MR estimations were consistent and robust.
  • The stability of the IVW estimation was confirmed, even after the removal of individual SNPs, further supporting the reliability of the findings.
  • Funnel plots and MR-Egger regression indicated no evidence of asymmetry, suggesting that directional pleiotropy did not bias the MR results.
  • The “Leave-one-out” approach demonstrated that none of the SNPs significantly influenced the causal inferences, further reinforcing the findings.

 

Overall, the results from Mendelian randomization analyses provide support for a potential causal relationship between childhood BMI and psoriasis, though some inconsistencies were observed between different analytical methods. The study employed rigorous testing and sensitivity analyses to ensure the robustness and reliability of the findings.

Conclusion

The study investigated the relationship between childhood obesity, specifically measured by BMI, and the risk of developing psoriasis. Using three Mendelian randomization (MR) statistical techniques, namely Inverse Variance Weighting (IVW), weighted median, and MR-Egger regression, the study aimed to elucidate a potential causal link between childhood BMI and psoriasis.

The findings from the MR analysis suggest a potential causal relationship between childhood BMI and the risk of developing psoriasis. Although the results obtained from the different MR methods were not entirely consistent, both the IVW and weighted median methods provided evidence supporting this association. The MR-Egger regression, while not conclusive, indicated no evidence of a causal link between BMI in childhood and psoriasis in children.

These results align with previous observational studies that have associated a higher BMI with an increased risk of psoriasis in adults. The study cited research indicating that individuals with higher BMIs faced a significantly higher risk of psoriasis compared to those with lower BMIs. Genetic alterations in genes related to obesity, such as the leptin receptor and brain-derived neurotrophic factor, were also linked to psoriasis, suggesting a common genetic background. Leptin, produced in fat tissue, plays a role in obesity-associated inflammation and may contribute to the development of psoriasis.

Additionally, the study highlighted the association between obesity and metabolic syndrome, which can significantly impact the physical and mental health of children with psoriasis. While treatment for psoriasis in children primarily relies on topical medications, advanced treatments like biologics have emerged as effective options, albeit with potential clinical challenges. Furthermore, low levels of lipocalin in psoriasis patients are associated with obesity and metabolic syndrome, making it a potential target for innovative drug development.

The study acknowledged its limitations, such as the small effect of genetic variants on BMI and classification biases among psoriasis patients. The research was conducted on individuals of European ancestry, emphasizing the need for further MR studies on different populations to establish causality.

In conclusion, this MR analysis indicates a potential causal relationship between childhood BMI and an increased risk of psoriasis. This finding suggests that managing childhood weight may have implications for the prevention and treatment of psoriasis. Further research is needed to delve into the underlying mechanisms of this causal relationship, providing valuable insights for future studies.

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