Erratum

Area of Science:

• Genetics
• Obesity Research
• Biostatistics

Background:

• Body Mass Index (BMI) is a key indicator of obesity, influenced by complex genetic factors.
• Rare genetic variants, though individually infrequent, can collectively contribute significantly to phenotypic variation.
• Identifying genes associated with BMI is crucial for understanding obesity etiology and developing targeted interventions.

Purpose of the Study:

• To identify novel genes that influence Body Mass Index (BMI) through the analysis of rare genetic variants.
• To apply a weighted burden analysis approach to enhance the detection of gene effects on BMI.
• To contribute to the understanding of the genetic architecture of obesity.

Main Methods:

• Utilized a weighted burden analysis framework to aggregate the effects of rare genetic variants within genes.
• Analyzed genetic data to assess the association between gene-based rare variant burdens and BMI.
• Employed statistical methods to identify genes with significant effects on BMI, controlling for potential confounders.

Main Results:

• Identified several novel genes demonstrating a significant association with BMI through rare variant burden analysis.
• The weighted approach successfully highlighted genes that might be overlooked by traditional single-variant association studies.
• Specific genes implicated in metabolic pathways showed a notable effect on BMI.

Conclusions:

• Rare genetic variants, analyzed collectively, play a significant role in determining BMI.
• The identified novel genes represent potential targets for future research into obesity and metabolic disorders.
• Weighted burden analysis is a powerful tool for dissecting the genetic underpinnings of complex traits like BMI.