Association of bone fracture with 30-year body mass index (BMI) trajectories: findings from the Framingham Heart Study : Bone fracture and 30-year BMI trajectories.

A knowledge gap exists in associating later life's osteoporotic fracture and middle adulthood's BMI trajectories. We observed an association showing those transitioning from overweight to normal weight face a higher fracture risk in late adulthood, emphasizing the potential benefits of maintaining a stable BMI to reduce late-life fractures. PURPOSE: Numerous studies on the relationship between obesity and fractures have relied on body mass index (BMI) at a single time point, yielding inconclusive results. This study investigated the association of BMI trajectories over middle adulthood with fracture risk in late adulthood. METHODS: This prospective cohort study analyzed 1772 qualified participants from the Framingham Original Cohort Study, with 292 (16.5%) incident fractures during an average of 17.1-year follow-up. We constructed BMI trajectories of age 35-64 years based on latent class mixed modeling and explored their association with the risk of fracture after 65 years using the Cox regression. RESULTS: The result showed that compared to the BMI trajectory Group 4 (normal to slightly overweight; see "Methods" for detailed description), Group 1 (overweight declined to normal weight) had a higher all-fracture risk after age 65 (hazard ratio [HR], 2.22, 95% CI, 1.13-4.39). The secondary analysis focusing on lower extremity fractures (pelvis, hip, leg, and foot) showed a similar association pattern. CONCLUSIONS: This study suggested that people whose BMI slightly increased from normal weight to low-level overweight during 30 years of middle adulthood confer a significantly lower risk of fracture in later life than those whose BMI declined from overweight to normal weight. This result implies the potentially beneficial effects of avoiding weight loss to normal weight during middle adulthood for overweight persons, with reduced fracture risk in late life.

Identifying BMI-associated genes via a genome-wide multi-omics integrative approach using summary data.

OBJECTIVE: This study aims to identify BMI-associated genes by integrating aggregated summary information from different omics data. METHODS: We conducted a meta-analysis to leverage information from a genome-wide association study (n = 339 224), a transcriptome-wide association study (n = 5619), and an epigenome-wide association study (n = 3743). We prioritized the significant genes with a machine learning-based method, netWAS, which borrows information from adipose tissue-specific interaction networks. We also used the brain-specific network in netWAS to investigate genes potentially involved in brain-adipose interaction. RESULTS: We identified 195 genes that were significantly associated with BMI through meta-analysis. The netWAS analysis narrowed down the list to 21 genes in adipose tissue. Among these 21 genes, six genes, including FUS, STX4, CCNT2, FUBP1, NDUFS3, and RAPSN, were not reported to be BMI-associated in PubMed or GWAS Catalog. We also identified 11 genes that were significantly associated with BMI in both adipose and whole brain tissues. CONCLUSION: This study integrated three types of omics data and identified a group of genes that have not previously been reported to be associated with BMI. This strategy could provide new insights for future studies to identify molecular mechanisms contributing to BMI regulation.