Association between circulating fatty acid metabolites and asthma risk: a two-sample bidirectional Mendelian randomization study

Abstract

Background Fatty acids are involved in a wide range of immunological responses in humans. Supplementation of polyunsaturated fatty acids has been reported to help alleviate symptoms and airway inflammation in asthma patients, whereas the effects of fatty acids on the actual risk of asthma remain controversial. This study comprehensively investigated the causal effects of serum fatty acids on asthma risk using two-sample bidirectional Mendelian Randomization (MR) analysis. Methods Genetic variants strongly associated with 123 circulating fatty acid metabolites were extracted as instrumental variables, and a large GWAS data of asthma was used to test effects of the metabolites on this outcome. The inverse-variance weighted method was used for primary MR analysis. The weighted median, MR-Egger regression, MR-PRESSO, and leave-one-out analyses were utilized to evaluate heterogeneity and pleiotropy. Potential confounders were adjusted by performing multivariable MR analyses. Reverse MR analysis was also conducted to estimate the causal effect of asthma on candidate fatty acid metabolites. Further, we performed colocalization analysis to examine the pleiotropy of variants within the fatty acid desaturase 1 (FADS1) locus between the significant metabolite traits and the risk of asthma. Cis-eQTL-MR and colocalization analysis were also performed to determine the association between RNA expression of FADS1 and asthma. Results Genetically instrumented higher average number of methylene groups was causally associated with a lower risk of asthma in primary MR analysis, while inversely, the higher ratio of bis-allylic groups to double bonds and the higher ratio of bis-allylic groups to total fatty acids, were associated with higher probabilities of asthma. Consistent results were obtained in multivariable MR when adjusted for potential confounders. However, these effects were completely eliminated after SNPs correlated with the FADS1 gene were excluded. The reverse MR also found no causal association. The colocalization analysis suggested that the three candidate metabolite traits and asthma likely share causal variants within the FADS1 locus. In addition, the cis-eQTL-MR and colocalization analyses demonstrated a causal association and shared causal variants between FADS1 expression and asthma. Conclusions Our study supports a negative association between several PUFA traits and the risk of asthma. However, this association is largely attributed to the influence of FADS1 polymorphisms. The results of this MR study should be carefully interpreted given the pleiotropy of SNPs associated with FADS1.

Integrated mendelian randomization analyses highlight AFF3 as a novel eQTL-mediated susceptibility gene in renal cancer and its potential mechanisms

“…Although the exact identity and functions of X-11,315 remain unclear at the current stage, this finding undoubtedly provides clues guiding future developments of metabolic biomarker-based diagnostic tests and therapies for RC. Similar mechanisms could be found in other diseases, such as asthma [ 48 ], multiple sclerosis [ 49 ], and so on. Deeper investigations into the interplay between AFF3 and metabolic networks could yield more fruitful outcomes moving forward.…”

The causal relationship between genetically predicted blood metabolites and idiopathic pulmonary fibrosis: A bidirectional two-sample Mendelian randomization study

“…For each metabolite assessed, SNPs that exhibited significant associations at a threshold of P < 1 × 10 −5 were selected primarily to maintain an optimal balance between the strength and quantity of IVs [ 26 , 27 ]. Next, SNPs were clustered by eliminating linkage disequilibrium with R 2 > 0.001 within 10000 kb in the Phase 3 reference panel of the European 1000 Genomes Project.…”

“…The genetic variant used as an instrumental variable (IV) should fulfill the following three assumptions [25]: (1) the variant is robustly associated with exposures; (2) the variant is independent of potential confounders; (3) the variant may only affect the outcome through exposures without any direct correlation with the outcome. For each metabolite assessed, SNPs that exhibited significant associations at a threshold of P < 1 × 10 −5 were selected primarily to maintain an optimal balance between the strength and quantity of IVs [26,27]. Next, SNPs were clustered by eliminating linkage disequilibrium with R 2 > 0.001 within 10000 kb in the Phase 3 reference panel of the European 1000 Genomes Project.…”