Background: Protein intake from cow milk-based infant formula has been associated with rapid weight gain and increased adiposity, but the effect of protein from complementary foods has not been prospectively evaluated, and the effect of protein from sources other than formula during complementary feeding is not clear. Objective: The aim of this study was to directly compare the effect of protein from 2 common complementary food sources, meat and dairy, on infant growth and weight trajectory. Design: Healthy term, formula-fed infants were recruited from the metro Denver area, matched by sex and race/ethnicity and randomly assigned to a meat or a dairy complementary food group from 5 to 12 mo of age. Total protein intake during this 7-mo intervention was ∼3 g kg −1 d −1 for both groups. Intakes of infant formula, cereal, fruit, and vegetables were ad libitum. Caregivers also completed 3-d diet records at 5, 10, and 12 mo of age. Anthropometric measures were obtained during monthly home visits, and blood samples were collected at 5 and 12 mo of age. Results: Sixty-four infants completed the intervention (meat: n = 32; dairy: n = 32). The average total protein intake (mean ± SD) increased from 2.01 ± 0.06 g kg −1 d −1 at 5 mo to 3.35 ± 0.12 g kg −1 d −1 at 12 mo and did not differ between groups. Over time, weight and weight-for-age z score increased by 0.48 ± 0.07. However, there was a significant group-by-time interaction for both length-for-age z score (LAZ) and weight-for-length z score (WLZ). Post hoc analysis showed that LAZ increased in the meat group (+0.33 ± 0.09; P = 0.001 over time) and decreased in the dairy group (−0.30 ± 0.10; P = 0.0002 over time); WLZ significantly increased in the dairy group (0.76 ± 0.21; P = 0.000002 over time) compared with the meat group (0.30 ± 0.17; P = 0.55 over time). Insulin-like growth factor I and insulin-like growth factor-binding protein 3 both increased over time without group differences. Conclusions: Protein source may have an important role in regulating growth. In these formula-fed older infants, meat-and dairybased complementary foods led to distinct growth patterns, especially for length. This trial was registered at www.clinicaltrials.gov as NCT02142647.

Identification of rare variant associations is crucial to fully characterize the genetic architecture of complex traits and diseases. Essential in this process is the evaluation of novel methods in simulated data that mirrors the distribution of rare variants and haplotype structure in real data. Additionally, importing real variant annotation enables in silico comparison of methods that focus on putative causal variants, such as rare variant association tests, and polygenic scoring methods. Existing simulation methods are either unable to employ real variant annotation or severely under- or over-estimate the number of singletons and doubletons reducing the ability to generalize simulation results to real studies. We present RAREsim, a flexible and accurate rare variant simulation algorithm. Using parameters and haplotypes derived from real sequencing data, RAREsim efficiently simulates the expected variant distribution and enables real variant annotations. We highlight RAREsim's utility across various genetic regions, sample sizes, ancestries, and variant classes.