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.

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.

Examining the Association between Medical Marijuana Legalization and Criminal Behaviors: Evidence from a U.S. Representative Sample.

Background: Medical marijuana legalization (MML) has been widely implemented in the past decade. However, the debates regarding the consequences of MML persist, especially criminal behaviors. Objectives: We examined the association between MML and criminal behaviors among adults in the United States. The criminal behaviors measured three past-year offenses: whether the adult (1) have sold illegal drugs, (2) have stolen anything worth > $50 USD, or (3) have attacked someone. Methods: Using the 2015-2020 National Survey of Drug Use and Health, we included 214,505 adults in our primary analysis for 2015-2019 and 27,170 adults in 2020 for supplemental analysis (age > = 18). Weighted multivariable logistic regression models were used to examine the association between MML and three criminal behaviors. Results: In our primary analysis, we observed no statistically significant association between MML and the three outcomes of criminal behavior. Nevertheless, our supplemental analysis of the 2020 data showed MML was associated with increasing odds of the three criminal behaviors (have sold illegal drugs: AOR [adjusted odds ratio] = 1.7; have stolen anything worth > $50 USD: AOR = 1.9; have attacked someone: AOR = 1.8; all p < 0.05). Conclusion: Surveys from 2015 to 2019 did not suggest MML as a risk factor for higher incidence of criminal behaviors. However, 2020 data showed statistically significant association between MML and selected criminal behaviors. Issues related to the COVID-19 pandemic, such as the U.S. economic downturn, could potentially explain this discrepancy. Further research efforts may be warranted.

Learning Gaussian Graphical Models from Correlated Data.

Gaussian Graphical Models (GGM) have been widely used in biomedical research to explore complex relationships between many variables. There are well established procedures to build GGMs from a sample of independent and identical distributed observations. However, many studies include clustered and longitudinal data that result in correlated observations and ignoring this correlation among observations can lead to inflated Type I error. In this paper, we propose a Bootstrap algorithm to infer GGM from correlated data. We use extensive simulations of correlated data from family-based studies to show that the Bootstrap method does not inflate the Type I error while retaining statistical power compared to alternative solutions. We apply our method to learn the GGM that represents complex relations between 47 Polygenic Risk Scores generated using genome-wide genotype data from a family-based study known as the Long Life Family Study. By comparing it to the conventional methods that ignore within-cluster correlation, we show that our method controls the Type I error well in this real example.

Vascular function and skeletal fragility: a study of tonometry, brachial hemodynamics, and bone microarchitecture.

Osteoporosis and cardiovascular disease frequently occur together in older adults; however, a causal relationship between these 2 common conditions has not been established. By the time clinical cardiovascular disease develops, it is often too late to test whether vascular dysfunction developed before or after the onset of osteoporosis. Therefore, we assessed the association of vascular function, measured by tonometry and brachial hemodynamic testing, with bone density, microarchitecture, and strength, measured by HR-pQCT, in 1391 individuals in the Framingham Heart Study. We hypothesized that decreased vascular function (pulse wave velocity, primary pressure wave, brachial pulse pressure, baseline flow amplitude, and brachial flow velocity) contributes to deficits in bone density, microarchitecture and strength, particularly in cortical bone, which is less protected from excessive blood flow pulsatility than the trabecular compartment. We found that individuals with increased carotid-femoral pulse wave velocity had lower cortical volumetric bone mineral density (tibia: -0.21 [-0.26, -0.15] standardized beta [95% CI], radius: -0.20 [-0.26, -0.15]), lower cortical thickness (tibia: -0.09 [-0.15, -0.04], radius: -0.07 [-0.12, -0.01]) and increased cortical porosity (tibia: 0.20 [0.15, 0.25], radius: 0.21 [0.15, 0.27]). However, these associations did not persist after adjustment for age, sex, height, and weight. These results suggest that vascular dysfunction with aging may not be an etiologic mechanism that contributes to the co-occurrence of osteoporosis and cardiovascular disease in older adults. Further study employing longitudinal measures of HR-pQCT parameters is needed to fully elucidate the link between vascular function and bone health.

Osteoporosis and heart disease are both medical conditions that commonly develop in older age. It is not known whether abnormal functioning of blood vessels contributes to the development of bone fragility with aging. In this study, we investigated the relationship between impaired blood vessel function and bone density and micro-structure in a group of 1391 people enrolled in the Framingham Heart Study. Blood vessel function was measured using specialized tools to assess blood flow and pressure. Bone density and micro-structure were measured using advanced imaging called HR-pQCT. We found that people with impaired blood vessel function tended to have lower bone density and worse deterioration in bone micro-structure. However, once we statistically controlled for age and sex and other confounders, we did not find any association between blood vessel function and bone measures. Overall, our results showed that older adults with impaired blood vessel function do not exhibit greater deterioration in the skeleton.

CKLF instigates a "cold" microenvironment to promote MYCN-mediated tumor aggressiveness.

Solid tumors, especially those with aberrant MYCN activation, often harbor an immunosuppressive microenvironment to fuel malignant growth and trigger treatment resistance. Despite this knowledge, there are no effective strategies to tackle this problem. We found that chemokine-like factor (CKLF) is highly expressed by various solid tumor cells and transcriptionally up-regulated by MYCN. Using the MYCN-driven high-risk neuroblastoma as a model system, we demonstrated that as early as the premalignant stage, tumor cells secrete CKLF to attract CCR4-expressing CD4+ cells, inducing immunosuppression and tumor aggression. Genetic depletion of CD4+ T regulatory cells abolishes the immunorestrictive and protumorigenic effects of CKLF. Our work supports that disrupting CKLF-mediated cross-talk between tumor and CD4+ suppressor cells represents a promising immunotherapeutic approach to battling MYCN-driven tumors.

Integrating Genetic and Transcriptomic Data to Identify Genes Underlying Obesity Risk Loci.

Genome-wide association studies (GWAS) have identified numerous body mass index (BMI) loci. However, most underlying mechanisms from risk locus to BMI remain unknown. Leveraging omics data through integrative analyses could provide more comprehensive views of biological pathways on BMI. We analyzed genotype and blood gene expression data in up to 5,619 samples from the Framingham Heart Study (FHS). Using 3,992 single nucleotide polymorphisms (SNPs) at 97 BMI loci and 20,692 transcripts within 1 Mb, we performed separate association analyses of transcript with BMI and SNP with transcript (PBMI and PSNP, respectively) and then a correlated meta-analysis between the full summary data sets (PMETA). We identified transcripts that met Bonferroni-corrected significance for each omic, were more significant in the correlated meta-analysis than each omic, and were at least nominally associated with BMI in FHS data. Among 308 significant SNP-transcript-BMI associations, we identified seven genes (NT5C2, GSTM3, SNAPC3, SPNS1, TMEM245, YPEL3, and ZNF646) in five association regions. Using an independent sample of blood gene expression data, we validated results for SNAPC3 and YPEL3. We tested for generalization of these associations in hypothalamus, nucleus accumbens, and liver and observed significant (PMETA<0.05 & PMETA

Genome-Wide Interaction Analysis With DASH Diet Score Identified Novel Loci for Systolic Blood Pressure.

BACKGROUND: The Dietary Approaches to Stop Hypertension (DASH) diet score lowers blood pressure (BP). We examined interactions between genotype and the DASH diet score in relation to systolic BP. METHODS: We analyzed up to 9 420 585 single nucleotide polymorphisms in up to 127 282 individuals of 6 population groups (91% of European population) from the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium (n=35 660) and UK Biobank (n=91 622) and performed European population-specific and cross-population meta-analyses. RESULTS: We identified 3 loci in European-specific analyses and an additional 4 loci in cross-population analyses at Pinteraction<5e-8. We observed a consistent interaction between rs117878928 at 15q25.1 (minor allele frequency, 0.03) and the DASH diet score (Pinteraction=4e-8; P for heterogeneity, 0.35) in European population, where the interaction effect size was 0.42±0.09 mm Hg (Pinteraction=9.4e-7) and 0.20±0.06 mm Hg (Pinteraction=0.001) in Cohorts for Heart and Aging Research in Genomic Epidemiology and the UK Biobank, respectively. The 1 Mb region surrounding rs117878928 was enriched with cis-expression quantitative trait loci (eQTL) variants (P=4e-273) and cis-DNA methylation quantitative trait loci variants (P=1e-300). Although the closest gene for rs117878928 is MTHFS, the highest narrow sense heritability accounted by single nucleotide polymorphisms potentially interacting with the DASH diet score in this locus was for gene ST20 at 15q25.1. CONCLUSIONS: We demonstrated gene-DASH diet score interaction effects on systolic BP in several loci. Studies with larger diverse populations are needed to validate our findings.