Zinc finger protein 33B demonstrates sex interaction with atopy-related markers in childhood asthma

Associations of APOE variants with sphingomyelin and cholesterol metabolites across the life-course in diverse populations

INTRODUCTION

Two alleles (ε2 and ε4) in the APOE gene are known to be strongly associated with lipid metabolism disorders, such as dyslipidemia, which are important risk factors for the development of cardiovascular diseases. While prior research has largely centered on adult populations, establishing APOE-lipid associations in infants, children, and adolescents-especially those from historically understudied groups-could inform earlier interventions and treatments.

OBJECTIVES

This study aimed to evaluate the dependence of the metabolome on the APOE variants using five diverse cohorts that span infancy through adulthood, comprising a total of over 190,000 individuals.

METHODS

We extracted the APOE variants (rs7412 and rs429358) from all cohorts-testing both the ε2 allele (rs7412-T and rs429358-T) and the ε4 allele (rs7412-C and rs429358-C)-and evaluated their associations with the global plasma metabolome which was measured by mass spectrometry-based (Metabolon or Broad Institute) or NMR-based (Nightingale) assays depending on the cohort, using a Bonferroni-corrected significance threshold.

RESULTS

Among 589 metabolites tested in our discovery population, only six including sphingomyelins and cholesterol were significantly associated with the rs7412/ε2 allele. Sphingomyelin (d18:1/22:0) and cholesterol were negatively associated with ε2 allele (β-value = -0.54 [-0.76, -0.32] p-value = 1.39 × 10-6 and - 0.55 [-0.77, -0.33]; p-value = 1.49 × 10-6, respectively). These relationships were replicated in the four additional cohorts without heterogeneity.

CONCLUSION

Our findings support the need for early intervention in lipid levels regardless of age, sex, and ethnicity and further investigations of the APOE variants on risk of various diseases in later life.

On the analysis of metabolite quantitative trait loci: Impact of different data transformations and study designs

Metabolomic genome-wide association studies (mGWASs), or metabolomic quantitative trait locus (metQTL) analyses, are gaining growing attention. However, robust methods and analysis guidelines, vital to address the complexity of metabolomic data, remain to be established. Here, we use whole-genome sequencing and metabolomic data from two independent studies to compare different approaches. We adopted three popular data transformation methods for metabolite levels-(i) log10 transformation, (ii) rank inverse normal transformation, and (iii) a fully adjusted two-step procedure-and compared population-based versus family-based analysis approaches. For validation, we performed permutation-based testing, Huber regression, and independent replication analysis. Simulation studies were used to illustrate the observed differences between data transformations. We demonstrate the advantages and limitations of popular analytic strategies used in mGWASs where especially low-frequency variants in combination with a skewed metabolite measurement distribution can lead to potentially false-positive metQTL findings. We recommend the rank inverse normal transformation or robust test statistics such as in family-based association tests as reliable approaches for mGWASs.

Sex differences in asthma: omics evidence and future directions

Asthma is a common and complex heterogeneous disease, with prevalence and severity varying across different age groups and sexes. Over the past few decades, with the development of high-throughput technologies, various "omics" analyses have emerged and been applied to asthma research, providing us with significant opportunities to study the genetic mechanisms underlying asthma. However, despite these advancements, the differences and specificities in the genetic mechanisms of asthma between sexes remain to be fully explored. Moreover, clinical guidelines have yet to incorporate or recommend sex-specific asthma management based on high-quality omics evidence. In this article, we review recent omics-level findings on sex differ-ences in asthma and discuss how to better integrate these multidimensional findings to generate further insights and advance the precision and effectiveness of asthma treatment.