This report describes the association between birth weight (BW) and obesity. Screening of 478 citations from five electronic databases resulted in the inclusion of 33 studies, most of medium quality. The meta-analysis included 20 of these published studies. The 13 remaining articles did not provide sufficient dichotomous data and were systematically reviewed, revealing results consistent with the meta-analysis. Our results revealed that high BW (>4000 g) was associated with increased risk of obesity (odds ratio [OR], 2.07; 95% confidence interval [CI], 1.91-2.24) compared with subjects with BW ≤ 4000 g. Low BW (<2500 g) was associated with decreased risk of obesity (OR, 0.61; 95% CI, 0.46-0.80) compared with subjects with BW ≥ 2500 g. However, when two studies exhibited selection bias were removed, the results indicated no significant association between low BW and obesity (OR, 0.77; 95% CI, 0.58-1.04). Sensitivity analyses showed that differences in the study design, sample size and quality grade of the study had an effect on the low BW/obesity association, which low BW was not associated with the risk of obesity in cohort studies, studies with large sample sizes and studies with high quality grades. Pooled results were similar when normal birth weight (2500-4000 g) was used as the reference category. Subgroup analyses based on different growth and developmental stages (pre-school children, school children and adolescents) also revealed that high BW was associated with increased risk of obesity from childhood to early adulthood. No significant evidence of publication bias was present. These results suggest that high BW is associated with increased risk of obesity and may serve as a mediator between prenatal influences and later disease risk.

CRISPR/Cas9 has been used to genetically modify genomes in a variety of species, including non-human primates. Unfortunately, this new technology does cause mosaic mutations, and we do not yet know whether such mutations can functionally disrupt the targeted gene or cause the pathology seen in human disease. Addressing these issues is necessary if we are to generate large animal models of human diseases using CRISPR/Cas9. Here we used CRISPR/Cas9 to target the monkey dystrophin gene to create mutations that lead to Duchenne muscular dystrophy (DMD), a recessive X-linked form of muscular dystrophy. Examination of the relative targeting rate revealed that Crispr/Cas9 targeting could lead to mosaic mutations in up to 87% of the dystrophin alleles in monkey muscle. Moreover, CRISPR/Cas9 induced mutations in both male and female monkeys, with the markedly depleted dystrophin and muscle degeneration seen in early DMD. Our findings indicate that CRISPR/Cas9 can efficiently generate monkey models of human diseases, regardless of inheritance patterns. The presence of degenerated muscle cells in newborn Cas9-targeted monkeys suggests that therapeutic interventions at the early disease stage may be effective at alleviating the myopathy.

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