Melanocortin 4 receptor (MC4R) deficiency, caused by mutations in MC4R, is the most common cause of monogenic forms of obesity. However, these mutations have often been identified in small-scale, ...case-focused studies. Here, we assess the penetrance of previously reported MC4R mutations at a population level. Furthermore, we examine why some carriers of pathogenic mutations remain of normal weight, to gain insight into the mechanisms that control body weight.
We identified 59 known obesity-increasing mutations in MC4R from the Human Gene Mutation Database (HGMD) and Clinvar. We assessed their penetrance and effect on obesity (body mass index BMI ≥ 30 kg/m2) in >450,000 individuals (age 40-69 years) of the UK Biobank, a population-based cohort study. Of these 59 mutations, only 11 had moderate-to-high penetrance and increased the odds of obesity by more than 2-fold. We subsequently focused on these 11 mutations and examined differences between carriers of normal weight and carriers with obesity. Twenty-eight of the 182 carriers of these 11 mutations were of normal weight. Body composition of carriers of normal weight was similar to noncarriers of normal weight, whereas among individuals with obesity, carriers had a somewhat higher BMI than noncarriers (1.44 ± 0.07 standard deviation scores SDSs ± standard error SE versus 1.29 ± 0.001, P = 0.03), because of greater lean mass (1.44 ± 0.09 versus 1.15 ± 0.002, P = 0.002). Carriers of normal weight more often reported that, already at age 10 years, their body size was below average or average (72%) compared with carriers with obesity (48%) (P = 0.01). To assess the polygenic contribution to body weight in carriers of normal weight and carriers with obesity, we calculated a genome-wide polygenic risk score for BMI (PRSBMI). The PRSBMI of carriers of normal weight (PRSBMI = -0.64 ± 0.18) was significantly lower than of carriers with obesity (0.40 ± 0.11; P = 1.7 × 10-6), and tended to be lower than that of noncarriers of normal weight (-0.29 ± 0.003; P = 0.05). Among carriers, those with a low PRSBMI (bottom quartile) have an approximately 5-kg/m2 lower BMI (approximately 14 kg of body weight for a 1.7-m-tall person) than those with a high PRS (top quartile). Because the UK Biobank population is healthier than the general population in the United Kingdom, penetrance may have been somewhat underestimated.
We showed that large-scale data are needed to validate the impact of mutations observed in small-scale and case-focused studies. Furthermore, we observed that despite the key role of MC4R in obesity, the effects of pathogenic MC4R mutations may be countered, at least in part, by a low polygenic risk potentially representing other innate mechanisms implicated in body weight regulation.
Abstract Objective Excess fructose consumption is hypothesized to be associated with risk for metabolic disease. Actual fructose consumption levels are difficult to estimate because of the unlabeled ...quantity of fructose in beverages. The aims of this study were threefold: 1) re-examine the fructose content in previously tested beverages using two additional assay methods capable of detecting other sugars, especially maltose, 2) compare data across all methods to determine the actual free fructose-to-glucose ratio in beverages made either with or without high-fructose corn syrup (HFCS), and 3) expand the analysis to determine fructose content in commonly consumed juice products. Methods Sugar-sweetened beverages (SSBs) and fruit juice drinks that were either made with or without HFCS were analyzed in separate, independent laboratories via three different methods to determine sugar profiles. Results For SSBs, the three independent laboratory methods showed consistent and reproducible results. In SSBs made with HFCS, fructose constituted 60.6% ± 2.7% of sugar content. In juices sweetened with HFCS, fructose accounted for 52.1% ± 5.9% of sugar content, although in some juices made from 100% fruit, fructose concentration reached 65.35 g/L accounting for 67% of sugars. Conclusion Our results provide evidence of higher than expected amounts of free fructose in some beverages. Popular beverages made with HFCS have a fructose-to-glucose ratio of approximately 60:40, and thus contain 50% more fructose than glucose. Some pure fruit juices have twice as much fructose as glucose. These findings suggest that beverages made with HFCS and some juices have a sugar profile very different than sucrose, in which amounts of fructose and glucose are equivalent. Current dietary analyses may underestimate actual fructose consumption.
Exposure to ambient fine particulate matter (PM2.5) is a major global health concern. Quantitative estimates of attributable mortality are based on disease-specific hazard ratio models that ...incorporate risk information from multiple PM2.5 sources (outdoor and indoor air pollution from use of solid fuels and secondhand and active smoking), requiring assumptions about equivalent exposure and toxicity. We relax these contentious assumptions by constructing a PM2.5-mortality hazard ratio function based only on cohort studies of outdoor air pollution that covers the global exposure range. We modeled the shape of the association between PM2.5 and nonaccidental mortality using data from 41 cohorts from 16 countries—the Global Exposure Mortality Model (GEMM). We then constructed GEMMs for five specific causes of death examined by the global burden of disease (GBD). The GEMM predicts 8.9 million 95% confidence interval (CI): 7.5–10.3 deaths in 2015, a figure 30% larger than that predicted by the sum of deaths among the five specific causes (6.9; 95% CI: 4.9–8.5) and 120% larger than the risk function used in the GBD (4.0; 95% CI: 3.3–4.8). Differences between the GEMM and GBD risk functions are larger for a 20% reduction in concentrations, with the GEMM predicting 220% higher excess deaths. These results suggest that PM2.5 exposure may be related to additional causes of death than the five considered by the GBD and that incorporation of risk information from other, nonoutdoor, particle sources leads to underestimation of disease burden, especially at higher concentrations.
Children who are hard of hearing (CHH) experience delays in spoken language and executive function, but the mechanisms for these deficits remain unresolved. Differences in auditory experience and ...language skills have been examined as contributing factors to deficits in executive function, primarily with children who are deaf and children with cochlear implants. The theoretical model of cumulative auditory experience quantifies auditory dosage as how much speech is audible and how often children wear their hearing aids. CHH with higher auditory dosage have better language outcomes than peers with less auditory dosage. However, the effects of auditory experience on executive function have not been studied in CHH. The goal of this study was to examine the influences of auditory experience and language skills on the development of executive function in CHH.
We collected measures of aided speech audibility, hearing aid use, executive function, and receptive vocabulary in 177 CHH and 86 children with typical hearing who were 5- to 10 years old and matched for socioeconomic status and nonverbal intelligence. Auditory dosage was calculated by combining each child's average hours of hearing aid use with their audibility for speech to create a variable that quantifies individual differences in auditory access.
CHH had lower receptive vocabulary and deficits in executive function related to working memory and selective attention compared to peers with typical hearing. CHH with greater auditory dosage had higher receptive vocabulary than CHH with lower auditory dosage. Better receptive vocabulary was associated with better scores on executive function measures related to working memory and attention. Auditory dosage was also directly associated with measures of verbal working memory.
CHH have deficits in language and some, but not all, areas of executive function related to working memory and attention. Auditory dosage was associated with language abilities and verbal working memory. Language was associated with individual differences in executive function skills related to attention and working memory. These results provide support for systems theories regarding the development of executive function in CHH. Interventions that improve auditory access and language may be effective for improving executive function related to working memory and attention in CHH.
Children with hearing loss listen and learn in environments with noise and reverberation, but perform more poorly in noise and reverberation than children with normal hearing. Even with ...amplification, individual differences in speech recognition are observed among children with hearing loss. Few studies have examined the factors that support speech understanding in noise and reverberation for this population. This study applied the theoretical framework of the Ease of Language Understanding (ELU) model to examine the influence of auditory, cognitive, and linguistic factors on speech recognition in noise and reverberation for children with hearing loss.
Fifty-six children with hearing loss and 50 age-matched children with normal hearing who were 7-10 years-old participated in this study. Aided sentence recognition was measured using an adaptive procedure to determine the signal-to-noise ratio for 50% correct (SNR50) recognition in steady-state speech-shaped noise. SNR50 was also measured with noise plus a simulation of 600 ms reverberation time. Receptive vocabulary, auditory attention, and visuospatial working memory were measured. Aided speech audibility indexed by the Speech Intelligibility Index was measured through the hearing aids of children with hearing loss.
Children with hearing loss had poorer aided speech recognition in noise and reverberation than children with typical hearing. Children with higher receptive vocabulary and working memory skills had better speech recognition in noise and noise plus reverberation than peers with poorer skills in these domains. Children with hearing loss with higher aided audibility had better speech recognition in noise and reverberation than peers with poorer audibility. Better audibility was also associated with stronger language skills.
Children with hearing loss are at considerable risk for poor speech understanding in noise and in conditions with noise and reverberation. Consistent with the predictions of the ELU model, children with stronger vocabulary and working memory abilities performed better than peers with poorer skills in these domains. Better aided speech audibility was associated with better recognition in noise and noise plus reverberation conditions for children with hearing loss. Speech audibility had direct effects on speech recognition in noise and reverberation and cumulative effects on speech recognition in noise through a positive association with language development over time.
Purpose: This study examined the effects of consistent hearing aid (HA) use on outcomes in children with mild hearing loss (HL). Method: Five- or 7-year-old children with mild HL were separated into ...3 groups on the basis of patterns of daily HA use. Using analyses of variance, we compared outcomes between groups on speech and language tests and a speech perception in noise task. Regression models were used to investigate the influence of cumulative auditory experience (audibility, early intervention, HA use) on outcomes. Results: Full-time HA users demonstrated significantly higher scores on vocabulary and grammar measures compared with nonusers. There were no significant differences between the 3 groups on articulation or speech perception measures. After controlling for the variance in age at confirmation of HL, level of audibility, and enrollment in early intervention, only amount of daily HA use was a significant predictor of grammar and vocabulary. Conclusions: The current results provide evidence that children's language development benefits from consistent HA use. Nonusers are at risk in areas such as vocabulary and grammar compared with other children with mild HL who wear HAs regularly. Service providers should work collaboratively to encourage consistent HA use.
The purpose of this study was to determine if traditional audiologic measures (e.g., pure-tone average, speech recognition) and audibility-based measures predict risk for spoken language delay in ...children who are hard of hearing (CHH) who use hearing aids (HAs). Audibility-based measures included the Speech Intelligibility Index (SII), HA use, and auditory dosage, a measure of auditory access that weighs each child's unaided and aided audibility by the average hours of HA use per day. The authors also sought to estimate values of these measures at which CHH would be at greater risk for delayed outcomes compared with a group of children with typical hearing (CTH) matched for age and socioeconomic status, potentially signaling a need to make changes to a child's hearing technology or intervention plan.
The authors compared spoken language outcomes of 182 CHH and 78 CTH and evaluated relationships between language and audiologic measures (e.g., aided SII) in CHH using generalized additive models. They used these models to identify values associated with falling below CTH (by > 1.5 SDs from the mean) on language assessments, putting CHH at risk for language delay.
Risk for language delay was associated with aided speech recognition in noise performance (<59% phonemes correct, 95% confidence interval 55%, 62%), aided Speech Intelligibility Index (SII < 0.61, 95% confidence internal .53,.68), and auditory dosage (dosage < 6.0, 95% confidence internal 5.3, 6.7) in CHH. The level of speech recognition in quiet, unaided pure-tone average, and unaided SII that placed children at risk for language delay could not be determined due to imprecise estimates with broad confidence intervals.
Results support using aided SII, aided speech recognition in noise measures, and auditory dosage as tools to facilitate clinical decision-making, such as deciding whether changes to a child's hearing technology are warranted. Values identified in this article can complement other metrics (e.g., unaided hearing thresholds, aided speech recognition testing, language assessment) when considering changes to intervention, such as adding language supports, making HA adjustments, or referring for cochlear implant candidacy evaluation.
The purpose of this study was to evaluate effects of masker type and hearing group on the relationship between school-age children's speech recognition and age, vocabulary, working memory, and ...selective attention. This study also explored effects of masker type and hearing group on the time course of maturation of masked speech recognition.
Participants included 31 children with normal hearing (CNH) and 41 children with mild to severe bilateral sensorineural hearing loss (CHL), between 6.7 and 13 years of age. Children with hearing aids used their personal hearing aids throughout testing. Audiometric thresholds and standardized measures of vocabulary, working memory, and selective attention were obtained from each child, along with masked sentence recognition thresholds in a steady state, speech-spectrum noise (SSN) and in a two-talker speech masker (TTS). Aided audibility through children's hearing aids was calculated based on the Speech Intelligibility Index (SII) for all children wearing hearing aids. Linear mixed effects models were used to examine the contribution of group, age, vocabulary, working memory, and attention to individual differences in speech recognition thresholds in each masker. Additional models were constructed to examine the role of aided audibility on masked speech recognition in CHL. Finally, to explore the time course of maturation of masked speech perception, linear mixed effects models were used to examine interactions between age, masker type, and hearing group as predictors of masked speech recognition.
Children's thresholds were higher in TTS than in SSN. There was no interaction of hearing group and masker type. CHL had higher thresholds than CNH in both maskers. In both hearing groups and masker types, children with better vocabularies had lower thresholds. An interaction of hearing group and attention was observed only in the TTS. Among CNH, attention predicted thresholds in TTS. Among CHL, vocabulary and aided audibility predicted thresholds in TTS. In both maskers, thresholds decreased as a function of age at a similar rate in CNH and CHL.
The factors contributing to individual differences in speech recognition differed as a function of masker type. In TTS, the factors contributing to individual difference in speech recognition further differed as a function of hearing group. Whereas attention predicted variance for CNH in TTS, vocabulary and aided audibility predicted variance in CHL. CHL required a more favorable signal to noise ratio (SNR) to recognize speech in TTS than in SSN (mean = +1 dB in TTS, -3 dB in SSN). We posit that failures in auditory stream segregation limit the extent to which CHL can recognize speech in a speech masker. Larger sample sizes or longitudinal data are needed to characterize the time course of maturation of masked speech perception in CHL.