Body mass index and risk of inflammatory breast disease: a Mendelian randomization study.
Аннотация
Introduction
in previous studies, obesity was identified as a risk factor for inflammatory breast disease, but its causality is uncertain. In the present study, we performed a two-sample Mendelian randomization (TSMR) analysis to investigate the causal relationship between obesity and inflammatory breast disease.
Methods
we use body mass index (BMI) as a measure of obesity. Data for single nucleotide polymorphisms (SNPs) associated with BMI were obtained from UK Biobank. Data for single nucleotide polymorphisms (SNPs) associated with mastitis were obtained from FinnGen Biobank. We used several MR analysis methods, such as inverse-variance weighting (IVW), MR-Egger, weighted median, simple mode and weighted mode to make our results more convincing. We also performed MR-PRESSO test, MR-Egger test, heterogeneity test, pleiotropy test and leave-one-out analysis to make our analysis results more robust and credible. We used odds ratio (OR) to evaluate the causal relationship between BMI and mastitis.
Results
based on the IVW random effects model, we found that a one-standard deviation (SD) increase in BMI increased the risk of mastitis by 62.1 % (OR = 1.621, 95 % CI: 1.262-2.083, p = 1.59E-4), which is almost consistent with the results of several other methods.
Conclusions
in European individuals, an increase in the number of BMI increases the risk of inflammatory breast disease. People with high BMI need to control their weight to reduce the incidence of inflammatory breast disease.
Предметные рубрики MeSH
Подготовка и перевод публикации
Обработка статьи · этапы, ошибки и управление
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Тип публикации указан по данным источника. Уровень доказательности автоматически не присваивается.