Iron supplementation may have adverse health effects in infants, probably through manipulation of the gut microbiome. Previous research in low-resource settings have focused primarily on anemic ...infants. This was a double blind, randomized, controlled trial of home fortification comparing multiple micronutrient powder (MNP) with and without iron. Six-month-old, non- or mildly anemic, predominantly-breastfed Kenyan infants in a rural malaria-endemic area were randomized to consume: (1) MNP containing 12.5 mg iron (MNP+Fe,
= 13); (2) MNP containing no iron (MNP-Fe,
= 13); or (3) Placebo (CONTROL,
= 7), from 6-9 months of age. Fecal microbiota were profiled by high-throughput bacterial 16S rRNA gene sequencing. Markers of inflammation in serum and stool samples were also measured. At baseline, the most abundant phylum was Proteobacteria (37.6% of rRNA sequences). The proteobacterial genus
was the most abundant genus across all phyla (30.1% of sequences). At the end of the intervention, the relative abundance of
significantly decreased in MNP-Fe (-16.05 ± 6.9%,
= 0.05) and CONTROL (-19.75 ± 4.5%,
= 0.01), but not in the MNP+Fe group (-6.23 ± 9%,
= 0.41). The second most abundant genus at baseline was
(17.3%), the relative abundance of which significantly decreased in MNP+Fe (-6.38 ± 2.5%,
= 0.02) and CONTROL (-8.05 ± 1.46%,
= 0.01), but not in MNP-Fe (-4.27 ± 5%,
= 0.4445).
increased in MNP-Fe only (1.9 ± 0.5%,
= 0.02). No significant differences were observed in inflammation markers, except for IL-8, which decreased in CONTROL. MNP fortification over three months in non- or mildly anemic Kenyan infants can potentially alter the gut microbiome. Consistent with previous research, addition of iron to the MNP may adversely affect the colonization of potential beneficial microbes and attenuate the decrease of potential pathogens.
Obesity is genetically heterogeneous with monogenic and complex polygenic forms. Using exome and targeted sequencing in 2,737 severely obese cases and 6,704 controls, we identified three genes (PHIP, ...DGKI, and ZMYM4) with an excess burden of very rare predicted deleterious variants in cases. In cells, we found that nuclear PHIP (pleckstrin homology domain interacting protein) directly enhances transcription of pro-opiomelanocortin (POMC), a neuropeptide that suppresses appetite. Obesity-associated PHIP variants repressed POMC transcription. Our demonstration that PHIP is involved in human energy homeostasis through transcriptional regulation of central melanocortin signaling has potential diagnostic and therapeutic implications for patients with obesity and developmental delay. Additionally, we found an excess burden of predicted deleterious variants involving genes nearest to loci from obesity genome-wide association studies. Genes and gene sets influencing obesity with variable penetrance provide compelling evidence for a continuum of causality in the genetic architecture of obesity, and explain some of its missing heritability.
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•Three genes (PHIP, DGKI, and ZMYM4) are linked to severe childhood obesity•Wild-type PHIP enhances POMC transcription, but variants in PHIP repress POMC•Rare variants in BMI-associated loci from GWAS are enriched in severe obesity•Genetic architecture of severe childhood obesity reveals a continuum of causality
Childhood obesity can be caused by penetrant mutations in a number of genes controlling appetite and body weight. Marenne et al. identify three genes with mutations with variable penetrance in a continuum of causality in childhood obesity, and demonstrate that variants in PHIP repress POMC transcription.
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.
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.
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.
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.
Protein source may have an important role in regulating growth. In these formula-fed older infants, meat- and dairy-based complementary foods led to distinct growth patterns, especially for length. This trial was registered at www.clinicaltrials.gov as NCT02142647.
Hypothalamic melanocortin neurons play a pivotal role in weight regulation. Here, we examined the contribution of Semaphorin 3 (SEMA3) signaling to the development of these circuits. In genetic ...studies, we found 40 rare variants in SEMA3A-G and their receptors (PLXNA1-4; NRP1-2) in 573 severely obese individuals; variants disrupted secretion and/or signaling through multiple molecular mechanisms. Rare variants in this set of genes were significantly enriched in 982 severely obese cases compared to 4,449 controls. In a zebrafish mutagenesis screen, deletion of 7 genes in this pathway led to increased somatic growth and/or adiposity demonstrating that disruption of Semaphorin 3 signaling perturbs energy homeostasis. In mice, deletion of the Neuropilin-2 receptor in Pro-opiomelanocortin neurons disrupted their projections from the arcuate to the paraventricular nucleus, reduced energy expenditure, and caused weight gain. Cumulatively, these studies demonstrate that SEMA3-mediated signaling drives the development of hypothalamic melanocortin circuits involved in energy homeostasis.
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•Rare variants affecting Semaphorin 3 signaling are associated with human obesity•Disruption of Semaphorin 3 signaling leads to weight gain in zebrafish and mice•Semaphorin 3 signaling promotes the development of hypothalamic melanocortin circuits
Semaphorin 3 signaling promotes the development of hypothalamic circuits, and human variants are associated with obesity.
A primary goal of the recent investment in sequencing is to detect novel genetic associations in health and disease improving the development of treatments and playing a critical role in precision ...medicine. While this investment has resulted in an enormous total number of sequenced genomes, individual studies of complex traits and diseases are often smaller and underpowered to detect rare variant genetic associations. Existing genetic resources such as the Exome Aggregation Consortium (>60,000 exomes) and the Genome Aggregation Database (~140,000 sequenced samples) have the potential to be used as controls in these studies. Fully utilizing these and other existing sequencing resources may increase power and could be especially useful in studies where resources to sequence additional samples are limited. However, to date, these large, publicly available genetic resources remain underutilized, or even misused, in large part due to the lack of statistical methods that can appropriately use this summary level data. Here, we present a new method to incorporate external controls in case-control analysis called ProxECAT (Proxy External Controls Association Test). ProxECAT estimates enrichment of rare variants within a gene region using internally sequenced cases and external controls. We evaluated ProxECAT in simulations and empirical analyses of obesity cases using both low-depth of coverage (7x) whole-genome sequenced controls and ExAC as controls. We find that ProxECAT maintains the expected type I error rate with increased power as the number of external controls increases. With an accompanying R package, ProxECAT enables the use of publicly available allele frequencies as external controls in case-control analysis.
To test the long-term effect on growth status at 24 months of age in formula-fed infants who were randomized to consume a meat- or dairy-based complementary diet from 5 to 12 months of age.
...Observational assessments, including anthropometric, dietary, and blood biomarkers, were conducted at 24 months of age, 1 year after the intervention ended.
The retention rate at 24 months of age was 84% for the meat group and 81% for the dairy group. Mean (±SD) protein intakes at 24 months of age were 4.1 ± 1.2 and 4.0 ± 1.1 g/kmeat (n = 27) and dairy (n = 26) groups, respectively, and comparable with the estimates of US population intake. At 24 months of age, weight-for-age z score did not differ significantly between groups and was similar to that at 12 months. Length-for-age z score remained significantly higher in the meat group compared with the dairy group, and the average length was 1.9 cm greater in the meat group. Weight-for-length z score also did not differ significantly between groups. Insulin-like growth factor 1 significantly increased from 12 to 24 months of age in both groups, but insulin-like growth factor-binding protein 3 and blood urea nitrogen did not change significantly from 12 to 24 months of age and were comparable between groups.
The protein source-induced distinctive growth patterns observed during infancy persisted at 24 months of age, suggesting a potential long-term impact of early protein quality on growth trajectories in formula-fed infants.
ClinicalTrials.gov: NCT02142647.
The age of onset of Huntington's disease (HD) is determined primarily by the length of the HD CAG repeat mutation, but is also influenced by other modifying factors. Delineating these modifiers is a ...critical step towards developing validated therapeutic targets in HD patients. The HD CAG repeat is somatically unstable, undergoing progressive length increases over time, particularly in brain regions that are the targets of neurodegeneration. Here, we have explored the hypothesis that somatic instability of the HD CAG repeat is itself a modifier of disease. Using small-pool PCR, we quantified somatic instability in the cortex region of the brain from a cohort of HD individuals exhibiting phenotypic extremes of young and old disease onset as predicted by the length of their constitutive HD CAG repeat lengths. After accounting for constitutive repeat length, somatic instability was found to be a significant predictor of onset age, with larger repeat length gains associated with earlier disease onset. These data are consistent with the hypothesis that somatic HD CAG repeat length expansions in target tissues contribute to the HD pathogenic process, and support pursuing factors that modify somatic instability as viable therapeutic targets.
Identification of rare-variant associations is crucial to full characterization of the genetic architecture of complex traits and diseases. Essential in this process is the evaluation of novel ...methods in simulated data that mirror the distribution of rare variants and haplotype structure in real data. Additionally, importing real-variant annotation enables in silico comparison of methods, such as rare-variant association tests and polygenic scoring methods, that focus on putative causal variants. Existing simulation methods are either unable to employ real-variant annotation or severely under- or overestimate the number of singletons and doubletons, thereby 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.
The variation in weight within a shared environment is largely attributable to genetic factors. Whilst many genes/loci confer susceptibility to obesity, little is known about the genetic architecture ...of healthy thinness. Here, we characterise the heritability of thinness which we found was comparable to that of severe obesity (h2 = 28.07 vs 32.33% respectively), although with incomplete genetic overlap (r = -0.49, 95% CI -0.17, -0.82, p = 0.003). In a genome-wide association analysis of thinness (n = 1,471) vs severe obesity (n = 1,456), we identified 10 loci previously associated with obesity, and demonstrate enrichment for established BMI-associated loci (pbinomial = 3.05x10-5). Simulation analyses showed that different association results between the extremes were likely in agreement with additive effects across the BMI distribution, suggesting different effects on thinness and obesity could be due to their different degrees of extremeness. In further analyses, we detected a novel obesity and BMI-associated locus at PKHD1 (rs2784243, obese vs. thin p = 5.99x10-6, obese vs. controls p = 2.13x10-6 pBMI = 2.3x10-13), associations at loci recently discovered with much larger sample sizes (e.g. FAM150B and PRDM6-CEP120), and novel variants driving associations at previously established signals (e.g. rs205262 at the SNRPC/C6orf106 locus and rs112446794 at the PRDM6-CEP120 locus). Our ability to replicate loci found with much larger sample sizes demonstrates the value of clinical extremes and suggest that characterisation of the genetics of thinness may provide a more nuanced understanding of the genetic architecture of body weight regulation and may inform the identification of potential anti-obesity targets.
Longitudinal studies are commonly used to examine possible causal factors associated with human health and disease. However, the statistical models, such as two-way ANOVA, often applied in these ...studies do not appropriately model the experimental design, resulting in biased and imprecise results. Here, we describe the linear mixed effects (LME) model and how to use it for longitudinal studies. We re-analyze a dataset published by Blanton et al. in 2016 that modeled growth trajectories in mice after microbiome implantation from nourished or malnourished children. We compare the fit and stability of different parameterizations of ANOVA and LME models; most models found that the nourished versus malnourished growth trajectories differed significantly. We show through simulation that the results from the two-way ANOVA and LME models are not always consistent. Incorrectly modeling correlated data can result in increased rates of false positives or false negatives, supporting the need to model correlated data correctly. We provide an interactive Shiny App to enable accessible and appropriate analysis of longitudinal data using LME models.
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