Genome Modeling System: A Knowledge Management Platform for Genomics.

In this work, we present the Genome Modeling System (GMS), an analysis information management system capable of executing automated genome analysis pipelines at a massive scale. The GMS framework provides detailed tracking of samples and data coupled with reliable and repeatable analysis pipelines. The GMS also serves as a platform for bioinformatics development, allowing a large team to collaborate on data analysis, or an individual researcher to leverage the work of others effectively within its data management system. Rather than separating ad-hoc analysis from rigorous, reproducible pipelines, the GMS promotes systematic integration between the two. As a demonstration of the GMS, we performed an integrated analysis of whole genome, exome and transcriptome sequencing data from a breast cancer cell line (HCC1395) and matched lymphoblastoid line (HCC1395BL). These data are available for users to test the software, complete tutorials and develop novel GMS pipeline configurations. The GMS is available at https://github.com/genome/gms.

Higher-protein intake and physical activity are associated with healthier body composition and cardiometabolic health in Hispanic adults.

BACKGROUND: Higher protein (HP) intake and physical activity (PA) have been associated with improved lean soft tissue (LST) and reduced fat mass (FM). Puerto Ricans have among the highest age-adjusted prevalence (42.5%) of obesity, which may be associated with inadequate protein consumption and PA. We examined the relationship between protein intake and PA with body composition and biomarkers of cardiometabolic health in Puerto Rican adults. METHODS: Participants included 959 Puerto Rican adults (71.4% women, 28.6% men) from the Boston Puerto Rican Health Study (BPRHS), aged 46-79 y (Women: age, 60.4 ± 7.6 y, BMI, 32.9 ± 6.8 kg/m2; Men: age, 59.8 ± 7.9 y, BMI, 30.1 ± 5.2 kg/m2). Protein intake was assessed using a food frequency questionnaire and expressed as g/kg body weight/day in energy intake-adjusted equal cut point tertile categories (lower, moderate, higher: LP < 0.91 g/kg/d, MP ≥ 0.91 ≤ 1.11 g/kg/d, and HP > 1.11 g/kg/d). PA was assessed by questionnaire and expressed in tertile categories (low, moderate and high; PA1: <0.8 km/d, PA2: ≥0.8  ≤ 3.2 km/d, PA3: >3.2 km/d). RESULTS: Participants with energy-adjusted HP had lower appendicular LST (ALST: 16.2 ± 3.8 kg), LST (39.7 ± 8.0 kg) and FM (25.6 ± 8.1 kg) when compared to LP (ALST: 20.1 ± 4.5 kg; LST: 49.5 ± 10.0 kg; FM: 40.8 ± 12.3 kg; P < 0.001) and MP (ALST: 18.2 ± 4.3 kg; LST: 44.1 ± 8.8 kg; FM: 32.2 ± 9.8 kg; P < 0.001). However, when adjusted for total body weight (kg), relative LST was significantly greater in HP (58 ± 9%) when compared to LP (53 ± 9%; P < 0.001) and MP (56 ± 9%; P < 0.001). Participants in PA3 had greater ALST (19.5 ± 5.4 kg), and LST (58 ± 10%), compared to PA1 (ALST: 17.2 ± 4.3 kg; LST: 53 ± 9%; P < 0.001) or PA2 (ALST: 17.7 ± 4.7 kg; LST: 56 ± 9%; P < 0.05). Those in HP + PA3 or MP + PA2 had lower c-reactive protein (CRP; HP + PA3: 5.1 ± 6.8 mg/L; MP + PA2: 6.4 ± 10.0 mg/L), when compared to LP + PA1 (8.7 ± 8.8 mg/L; P < 0.05). Insulin concentration was lower for those in both the HP and PA3 (HP + PA3; 11.4 ± 7.9 IU/mL) compared to those in both the LP and PA1 (LP + PA1; 20.7 ± 16.3 UI/mL) (P < 0.001). CONCLUSIONS: The highest tertiles of energy-adjusted protein intake (≥1.11 g/kg/d) and PA (>3.2 km/d) were associated with more desirable indicators of overall body composition and cardiometabolic health, when adjusted for body weight, than those in the lower protein intake and PA in Puerto Rican adults.