The American Journal of Clinical Nutrition

Background: Obesity is becoming a global health crisis, and it leads to various metabolic disorders. Body mass index fails to differentiate fat mass from lean mass and systematically misclassifies adiposity risk - a limitation particularly pronounced in South Asian adults, who exhibit characteristically elevated visceral adiposity and reduced appendicular lean mass at a normal BMI. The 2025 Lancet Commission explicitly recommends direct adiposity measurement beyond BMI for obesity diagnosis. Weight loss interventions - whether dietary, behavioural, or pharmacological - are consistently associated with concurrent reductions in both fat mass and lean mass, making body composition monitoring essential beyond scale weight alone. Although DEXA is globally accepted as a gold standard for body composition analysis, the accessibility of DEXA is limited, particularly in resource-constrained low and middle-income countries such as India. BIA devices are a convenient low-cost option to DEXA and can be used for body composition analysis more frequently than a DEXA scan to provide longitudinal data. The aim of this study is to validate 8 electrode BIA devices as a viable alternative to DEXA scan for the South Asian population. Methods: A prospective cross-sectional validation study was conducted following ethics committee approval, with a priori sample size estimation ( = 0.05, power = 80%). Fifty-eight healthy adults (n=58) underwent three BIA measurements and one DEXA scan each. To ensure statistical independence, the three BIA readings per participant were averaged, yielding 58 final measurements for validation. Body fat percentage, lean mass and fat mass were evaluated using Python with statistical analyses like Bland Altman analysis, Pearson correlation, ICC and regression analysis. Results: In this BIA vs DEXA study, the Pearson correlation was strong across all three outcomes (fat%: r = 0.97; fat mass: r = 0.98; lean mass: r = 0.96), with ICC (2,1) values of 0.94, 0.97, and 0.91 confirming excellent absolute agreement. Mean absolute error was 3.40% for fat percentage, 1.96 kg for fat mass, and 3.37 kg for lean mass. BIA systematically underestimated body fat percentage (bias -1.96%, 95% CI: -2.91% to -1.01%; LoA: -9.04% to +5.12%) and fat mass (bias -0.72 kg, 95% CI: -1.38 to -0.07 kg; LoA: -5.59 to +4.14 kg), while overestimating lean mass by +3.08 kg (95% CI: +2.34 to +3.82 kg; LoA: -2.46 to +8.62 kg). Conclusions: The 8-electrode BIA device shows clinically acceptable agreement with DEXA for body composition assessment in healthy Indian adults. It offers a radiation-free, cost-effective, accessible, and portable alternative to DEXA, making it suitable for longitudinal monitoring and trend detection. The device is particularly valuable for obesity screening and for tracking body composition changes during weight loss interventions at the population level, addressing the critical need for accessible body composition assessment in resource-limited settings.

Background: Polygenic risk scores (PRS) for breast cancer are increasingly used for risk stratification to inform screening and prevention. However, for PRSs to be equitable and clinically useful, they need to perform well across diverse populations. While PRS performance is known to be ancestry-dependent, it is not well understood how environmental context, such as that of socioeconomic status (SES), affects PRS transferability. Here, we assess whether SES, measured via self-reported household income, modifies breast cancer PRS performance and, if so, whether socioeconomic context contributes predictive information beyond genetic risk alone. Methods: We used the US-based All of Us biobank to evaluate how SES impacts breast cancer PRS performance. First, we quantified changes in breast cancer PRS performance by modeling a commonly-cited polygenic score for breast cancer previously described by Mavaddat et al. with SES. We then reestimated the genetic effect sizes of the 3,820 variants from Mavaddat et al. in All of Us with and without income as a covariate. Because social determinants of health affect breast cancer detection and outcomes, we stratified analyses by socially defined populations on the basis of self-identified race and ethnicity. We further stratified individuals whose self-identified race is White (''White'') into three SES groups (high, middle, low) based on self-reported income and re-estimated genetic effect sizes to create SES-specific PRSs. We then applied these PRSs to White participants, the largest group in the study, and to Black or African American (''Black'') and Hispanic or Latino (''Hispanic'') participants, groups underrepresented in breast cancer research. Model discrimination between cases and controls was measured by area under the curve (AUC). Results: We analyzed 163,715 women from the All of Us biobank, which included 8,833 breast cancer cases (6,619 White, 1,178 Black, and 1,036 Hispanic), with relative income available for a subset of these cases (5,525 White, 848 Black, and 566 Hispanic). The ancestry-dependent performance of the breast cancer PRS described in Mavaddat et al. was replicated in All of Us. In Black individuals, this PRS (AUC and 95% CI: 0.576 [0.571, 0.582]) produced a similar increase in AUC as relative income (AUC: 0.573 [0.568, 0.577]) when added to an age-only model. Incorporating income with PRS, age, and genetic PCs 1-3 improved AUC by 0.007 in White Americans and 0.018 in Black Americans (both p < 10-11), while attenuating the contribution of PRS in the full model. PRS performance also varied among SES categories. Notably, PRSs with variant effect sizes that were recalibrated in low-SES White participants performed best in low-SES White participants (AUC: 0.605 [0.583, 0.628]) and Black Americans (AUC: 0.588 [0.586, 0.591]), both better than performance in high-SES White Americans (AUC: 0.579 [0.577, 0.580]) and middle-SES White Americans (AUC: 0.578 [0.569, 0.586]). Conclusion: Socioeconomic context, measured by income, significantly impacts the transferability of a PRS for breast cancer within and among groups defined by self-identified race and ethnicity. Accounting for SES improves PRS performance, most notably in Black Americans and low-SES White individuals.

Background: Obesity is globally recognized as a complex, multifactorial chronic disease, with biological, psychological, environmental and behavioural factors involved in both disease pathogenesis and maintenance. Although previous group-based studies demonstrated involvement of each of these factors, there is large inter-individual variability in the factors contributing to disease development as well as intervention outcomes, causing limited translatability to the individual level. This heterogeneity in treatment effectiveness might be due to differential causal and maintenance factors of obesity. To enable the transition from a one-size-fits-all approach to a more personalized approach for individuals with overweight or obesity, this study aims to investigate if and how the degree of weight loss and changes in daily life behaviour after a combined lifestyle intervention depend on individual baseline profiles comprising of person characteristics, biological, psychological, environmental and behavioural factors. Methods: This study will include 600 individuals varying in BMI, 200 participants with a healthy BMI (18.5-24.9kg/m2), 200 with overweight (BMI 25.0-29.9kg/m2), and 200 with obesity (BMI [&ge;]30.0kg/m2). For all participants, a comprehensive individual baseline profile is created, including person characteristics, biological, psychological, environmental and behavioural factors. A clustering method is applied to identify clusters of participants with similar characteristics. Next, we examine if and how these clusters are linked to bodyweight indicators measured at baseline, and how they relate to daily lifestyle behaviour, as measured by ecological momentary assessment (EMA) using a smartphone app and sensor technology (3-week measurements). Individuals with overweight or obesity will be randomized to the intensive lifestyle intervention or a lifestyle information condition, to determine if treatment response can be predicted based on cluster characteristics, how daily lifestyle behaviour changes after an intervention, and how changes in daily lifestyle behaviour relate to treatment response. Discussion: The End of Average study aims to characterize a large set of individuals varying in body weight to predict intervention effectiveness measured as changes in body weight indicators and in daily lifestyle behaviours. If reliable predictors of treatment success can be identified, these can be applied in personalized lifestyle interventions to improve lifestyle behaviour, body weight management and overall health.

Background: Pregnancy loss has important implications for womens health. Although maternal age is a well-established risk factor, the contribution of routinely measured cardiometabolic and behavioral markers at population-scale remains incompletely characterized. Objective: To examine associations between cardiometabolic, nutritional, and behavioral risk markers and pregnancy loss among U.S. women of reproductive age. Methods: We conducted a cross-sectional analysis of 4,842 U.S. women aged 20-44 years with [&ge;]1 pregnancy using the National Health and Nutrition Examination Survey data (2013-2023). Pregnancy loss was defined as [&ge;]1 prior miscarriages. Exposures included body mass index, smoking exposure (cotinine), lipid biomarkers, vitamin D and folate, and a composite cardiometabolic-nutritional risk score. Survey-weighted logistic regression estimated adjusted odds ratios (aORs) and 95% confidence intervals, with bootstrap resampling for predictor robustness. Results: The weighted prevalence of pregnancy loss was 23%. Higher odds of pregnancy loss were associated with increasing age (aOR per year=1.02; 95% CI: 1.00-1.04), Non-Hispanic Black race (aOR=1.32; 95% CI: 1.00-1.74), overweight (aOR=1.56; 95% CI: 1.16-2.11), obesity (aOR=2.06; 95% CI: 1.39-3.05), and smoking (aOR=1.58; 95% CI: 1.19-2.10). Adverse lipid profiles, particularly elevated triglycerides (aOR=1.83; 95% CI: 1.16-2.90) and high low-density lipoprotein (aOR=2.97; 95% CI: 1.45-6.61), were independently associated with pregnancy loss. Vitamin D/folate were not stable predictors. Higher composite cardiometabolic-nutritional risk scores were observed among women with pregnancy loss (P=0.026). Conclusion: Pregnancy loss clustered with adverse cardiometabolic and behavioral risk markers in a nationally representative population. These findings highlight pregnancy loss as a marker of broader metabolic vulnerability supporting the need for longitudinal studies and cardiometabolic profiling to inform preconception care and risk stratification.

Heterozygous carriers of autosomal recessive disease variants are conventionally considered unaffected, yet population-scale genomic datasets reveal subclinical carrier phenotypes. MMACHC encodes a cobalamin-processing protein whose biallelic loss causes cobalamin C deficiency, an inborn error of intracellular cobalamin metabolism. We performed an unbiased quantitative phenome-wide association screen in All of Us Research Program v8 to identify phenotypes associated with rare heterozygous MMACHC burden variants. Serum/plasma vitamin B12 was the top quantitative association. Carriers had higher circulating B12 than non-carriers in adjusted analyses, but also higher homocysteine, suggesting that elevated circulating B12 does not reflect improved intracellular cobalamin function. Carriers were less likely to fall below conventional B12 insufficiency thresholds, indicating a potential diagnostic blind spot. A pathway-wide rare-variant gene-burden (All-by-All) gene-burden analysis placed this finding in broader biological context. Burdens in genes related to circulating B12 binding or intestinal absorption were associated with lower circulating B12. In contrast, burdens in several genes involved in cellular delivery and intracellular cobalamin handling were associated with higher circulating B12. This step-specific directionality supports a model in which elevated circulating B12 can reflect impaired cellular handling and consequent systemic accumulation rather than improved cellular cobalamin availability. Because EHR-derived B12 is shaped by heterogeneous clinical and medication contexts, prospective carrier-enriched studies with standardized methylmalonic acid, homocysteine, diet, supplement, medication, comorbidity, and symptom ascertainment are needed to evaluate functional-marker-based screening.

Background and Aims: MASLD has become the most prevalent chronic liver disease globally. Although MVPA and plasma fatty acids have been individually studied in relation to metabolic health, their independent and combined associations with MASLD incidence remain unclear. We aimed to investigate these associations. Methods: This study included 51,717 UK Biobank participants free of liver disease at baseline, with MVPA measured using wrist-worn accelerometers and plasma fatty acids quantified via NMR. Multivariable-adjusted Cox models and restricted cubic splines were used. Results: Over a median follow-up of 7.8 years, 472 incident cases were identified. In fully adjusted models, meeting recommended MVPA levels together with higher n-6 PUFA concentrations was associated with a 71% lower risk (HR 0.29, 95% CI 0.18-0.45). The MVPA-MASLD association was nonlinear, with risk reduction plateauing at approximately 189 minutes per week. Higher n-6 PUFA was associated with reduced risk, whereas n-3 PUFA showed no significant association. Conclusions: These findings suggest that behavioral and metabolic factors may jointly influence MASLD risk. Further studies in diverse populations are needed to confirm these associations.

Background: Chronic diseases and symptom syndromes often develop after prolonged biological changes that may precede formal diagnosis. RNA-based metatranscriptomics captures active microbial and human gene expression and may provide a functional layer for disease risk evaluation. To address this translational gap, we developed and validated a Disease Risk Score (DRS) framework that integrates metatranscriptome-derived pathway activity scores from stool, saliva, and blood samples, and evaluated its potential clinical utility as an adjunct risk-evaluation tool. Methods: DRS uses disease-specific sets of pathway activity scores derived from stool and saliva microbial functions, stool and saliva microbial taxa, and blood human gene expression. For each disease, 'not optimal' pathway scores are aggregated into a normalized cumulative odds ratio, or cOR, using score-level odds ratios, statistical significance, and literature-supported biological relevance derived from a Development Cohort of 22,369 individuals. A cOR [&ge;] 5 is defined as high risk. Performance is evaluated in an independent Validation Cohort of 15,908 individuals using self-reported diseases as the reference. Disease support requires both significant cOR separation between self-reported and not-reported (Cohen's d [&ge;] 0.2) and risk ratio enrichment of self-reported disease among individuals classified as high risk (95% CI of Risk Ratio > 1). Results: Of 20 initially evaluated diseases, 15 meet the prespecified validation criteria on the independent validation cohort: ADHD, anxiety, chronic fatigue syndrome, depression, GERD, hypertension, inflammatory bowel disease, IBS-C, IBS-D, insomnia, MASLD, obesity, obstructive sleep apnea, Sjogren's syndrome, and type 2 diabetes. Five selected clinical scenarios illustrate how DRS can support clinician-mediated decision making, including IBS subtype reclassification, improved diagnostic acceptance in IBS-D, personalized lifestyle counseling in MASLD and early type 2 diabetes, and diagnostic uncertainty in atypical GERD. Conclusions: DRS is a metatranscriptomics-based risk-stratification framework that aggregates active microbial and human pathway signals into interpretable disease-specific risk estimates across a wide range of disease conditions. Validation against self-reported disease labels in an independent cohort shows significant risk enrichment for each of 15 diseases. DRS is intended as an adjunct to clinical evaluation: a decision support tool in situations where routine care encounters uncertainty, delay, or low patient engagement. Future prospective studies using clinically adjudicated endpoints are needed to assess calibration and clinical outcomes.

Abstract Objective: This study aimed to assess the magnitude of undernutrition and associated factors among pregnant women attending public health facilities in the Goba district, Bale zone, Oromia Region, Ethiopia, 2022. Design: Institution-based, cross-sectional study design was used. Setting: The study was conducted in selected public health facilities from May to June 2022. Participants: The study population consisted of pregnant women who lived for at least 6 months in the study area and who attended antenatal care follow-up at selected public health facilities during the study period. Pregnant women who lived for less than six months in the study area and those who were critically ill were excluded from the study. Results: 487 respondents participated in this study with a 100% response rate. More than half (50.7%) of pregnant mothers were undernourished. The significant factors associated with maternal undernutrition during pregnancy in this study were mothers with no formal education (AOR = 5.050; 95% CI: 1.470- 17.346), a history of illness during pregnancy (AOR = 2.089; 95% CI: 1.246-3.504), and eating frequency of meals less than or equal to three times per day (AOR = 3.292; 95% CI: 1.040- 10.42). Poor nutritional knowledge (AOR = 5.588; 95% CI: 2.921-10.689), poor household (HH) wealth status (AOR = 4.774; 95% CI: 2.216- 10.285), and mothers who had >= 4 pregnancies were included (AOR = 0.852; 95% CI: 342-0.989). Conclusion: The magnitude of Undernutrition among pregnant women was 50.7%. Significant associations with Undernutrition were found in mothers with no formal education, poor dietary knowledge, a meal frequency of three or fewer times per day, a history of illness during pregnancy, lower and medium household wealth status, and those who had experienced four or more pregnancies while attending antenatal care (ANC) services at public health facilities.

Background. Tobacco smoke exposure, quantified by serum cotinine, is associated with cardiovascular, metabolic, and sleep-related health risks. The relationship between biomarker-verified tobacco smoke exposure and objectively measured, free-living wrist-worn ambient light patterns has not been examined in a nationally representative U.S. adult sample. Methods. We analyzed NHANES 2011-2014 cross-sectional data from 6,937 adults aged >20 years with valid serum cotinine and wrist-worn Physical Activity Monitor (PAM) ambient light data. Seven light outcomes were modeled using survey-weighted linear regression with log2(cotinine+1) as the continuous exposure across four covariate adjustment levels. Benjamini-Hochberg false discovery rate (FDR) correction was applied across the 7 outcomes within each model. Results. In Model 2 (adjusted for age, sex, race/ethnicity, education, poverty-income ratio, BMI, and survey cycle; N = 6,350), higher serum cotinine was associated with significantly higher nighttime light (beta = +0.024, 95% CI: 0.010, 0.038; p-FDR = 0.014) and lower evening light (beta = -0.031, 95% CI: -0.055, -0.008; p-FDR = 0.042). In exploratory behavioral models without alcohol (Model 3a; N = 5,766), both nighttime and evening associations remained FDR-significant. After additional adjustment for alcohol, which substantially reduced the sample due to 37.6% missingness (Model 3b; N = 3,866), the nighttime association attenuated below the FDR threshold, while the evening association remained FDR-significant. Categorical analyses showed progressively higher nighttime light across cotinine groups, and a hypothesis-generating sex interaction was identified (p-interaction = 0.001). Conclusions. Higher serum cotinine concentrations were associated with higher nighttime and lower evening ambient light after sociodemographic adjustment. Attenuation after behavioral adjustment and the cross-sectional design preclude causal inference. Longitudinal studies with formal mediation analyses are needed to clarify the temporal ordering and mechanisms linking tobacco smoke exposure, smoking-related behaviors, and personal light-dark cycle patterns.

Polygenic risk scores (PRSs) are emerging as powerful tools for quantifying inherited risk for common diseases and, in some cases, are approaching clinical implementation. A major concern for PRS implementation is their limited accuracy in non-European populations, particularly in those of African ancestry. However, past evaluations have focused on metrics such as relative risk or AUC, which do not capture background risk arising from contextual factors. We introduce a novel measure of variable importance, the conditional average derivative estimator (CADE), to evaluate PRS utility across diverse contexts and populations within absolute risk models that integrate PRSs with other relevant risk factors. We illustrate this framework by integrating PRSs for breast and prostate cancer within age-specific absolute risk models for incidence and mortality fit using individual-level data from the All of Us Research Program with inputs from the National Cancer Institute SEER cancer registry. Our projections show that although the PRSs are known to have the lowest discriminatory accuracy in African Americans (AA), there are contexts in which they provide greater utility, such as for the stratification of prostate cancer risk and mortality, where the CADE values for AA were 2- and 7-fold higher than for European Americans. These findings suggest that conclusions about the limited clinical utility of PRS in non-European populations may be premature and underscore the need to quantify PRS risk-stratification utility at the absolute-risk level, while accounting for disease onset, survival, and broader health and economic factors.

Background Cardiovascular-kidney-metabolic (CKM) syndrome integrates adiposity, metabolic risk, kidney dysfunction, and cardiovascular disease in a prevention-oriented framework. National estimates across 1999-2023 NHANES and future burden remain limited. Methods We analyzed US adults aged 20 years from 11 NHANES cycles, 1999-2000 through August 2021-August 2023. CKM stage 0-4 was assigned using harmonized examination, laboratory, medication, and questionnaire data. Prevalence was survey-weighted and standardized to the 2010 US Census adult population. Decade trends used survey-weighted logistic regression adjusted for age, sex, and race and ethnicity. Exploratory 2040 and 2050 projections combined NHANES prevalence models with US Census projections under population-aging-only, trend-continuation, and risk-improvement scenarios. Results Among 62,890 eligible adults, 62,888 had sufficient CKM data. In 2021-2023, age-standardized prevalence was 87.9% (95% CI, 86.5%-89.4%) for CKM stage 1 and 62.0% (95% CI, 60.1%-63.8%) for stages 2-4. Stage 2 accounted for 50.1% (95% CI, 48.2%-51.9%) and stages 3-4 for 11.9% (95% CI, 11.0%-12.7%). From 1999-2000 to 2021-2023, any CKM increased by 4.6 percentage points (95% CI, 2.4 to 6.9; P<0.001), whereas stages 2-4 changed by 2.1 percentage points (95% CI, 5.1 to 0.8; P=0.156). In adjusted decade models, any CKM increased (OR, 1.28; 95% CI, 1.19-1.38; P<0.001), while stages 2-4 showed no significant linear trend (OR, 0.95; 95% CI, 0.89-1.01; P=0.084). Excess adiposity and diabetes increased, dyslipidemia declined, and hypertension, chronic kidney disease, and clinical cardiovascular disease were stable. With population aging alone, projected stages 2-4 burden rose from 164.8 million adults in 2023 to 193.7 million in 2050; under risk improvement, it was 147.7 million. Conclusions CKM syndrome remained highly prevalent among US adults. Although later stages did not increase significantly, population aging may expand the absolute care burden unless broad risk improvement occurs.

Ultra-processed food (UPF) may contribute to increased energy intake and weight gain, but evidence synthesis from randomised controlled trials (RCT) is lacking. A pre-registered systematic review and meta-analysis of RCTs was conducted comparing UPF with less processed food (LPF) on energy intake and/or body weight in humans. Secondary analyses (meta-regression and sub-group) examined effects of UPF on appetite sensations, eating rate, palatability and considered the role of nutrient profile in explaining results. Ten eligible studies were included. UPF trial arms tended to have higher energy intake (standardised mean differences [SMDs]=0.18-0.44), but statistical significance varied between analytic models. Weight gain (SMD=0.65) and eating rate (SMD=0.96) were significantly greater in UPF trial arms. No significant differences in palatability, appetite sensations or energy intake later in the day were observed. Diets (UPF vs. LPF) used in trials were not matched for nutrient profile. Effects on energy intake varied if UPFs were higher (SMD=0.71) or similar (SMD=0.02) in energy density. Current RCTs are suggestive that UPFs may increase energy intake and body weight; however, results may be explained by energy density of foods used. Further research is needed to understand whether the level of processing impacts health outcomes independent to nutrient profile.

Background. Nascent findings suggest that people with attention-deficit/hyperactivity disorder (ADHD) experience higher rates of mortality. To date, study samples have been insufficiently well-characterized to examine the mechanisms via which this neurodevelopmental condition elevates mortality risk. Methods. We used data from the 2007 and 2011 waves of the US National Health Interview Survey, a general population-based cohort study comprising 52097 adults (28675 women) aged 18 years or older at baseline. ADHD diagnosis and an array of demographic, socioeconomic, lifestyle, and co-morbidity (somatic and psychiatric) covariates were self-reported. Findings. At baseline, compared with unaffected individuals, participants with ADHD were more likely to be socioeconomically disadvantaged, smoke cigarettes, consume alcohol, and report symptoms of psychological distress. A median 7.75 years of mortality surveillance (range: 7.25-12.25) gave rise to 6597 deaths from all-causes. After adjustment for age, sex, ethnicity, and survey year, ADHD was associated with a markedly elevated risk of death (hazard ratio [95% confidence interval]: 1.58 [1.20-2.09]). Statistical adjustment for socioeconomic circumstances (11% attenuation), physical co-morbidities (15%), and lifestyle factors (17%) had only a modest impact on the ADHD-death gradient, with the greatest explanatory power apparent for symptoms of depression and anxiety (58%). The magnitude of the association of ADHD with mortality was commensurate to that for several well-established risk factors such as poverty (1.66 [1.55-1.78]), hypertension (1.41 [1.32-1.51]), and diabetes (1.71 [1.59-1.85]) but somewhat lower than cigarette smoking (2.51 [2.29-2.76]) after controlling for age, sex, ethnicity, and survey year. Associations between ADHD and cause-specific mortality from cardiovascular disease, cancer, and chronic respiratory disease were inconclusive. Interpretation. In the present study, the influence of ADHD on total mortality appears to be largely embodied via a series of malleable characteristics, particularly mental illness. If confirmed elsewhere, these results raise the possibility that risk factor modification via standard pharmacological and behavioral interventions could help reduce rates of premature mortality in this patient group. Funding. This paper received no direct funding. GDB is supported by the UK Medical Research Council (MR/P023444/1) and the US National Institute on Aging (1R56AG052519-01, 1R01AG052519-01A1).

Introduction: While growing evidence suggests that music training supports child development, few long-term randomized controlled trials (RCTs) have rigorously tested these claims. Moreover, it remains unclear whether the benefits are confined to music-specific domains or extend to higher-order cognitive functions such as inhibitory control (IC), a core executive function associated with long-term outcomes in academic achievement, career success, socio-emotional health, and physical well-being. This paper presents the protocol for the Extracurricular Activity and Child Early Learning and Development (EXCEL) trial, an RCT designed to assess the feasibility of a long-term music training program focusing on the brain and behavioral correlates of IC. Methods: A total of 126 children, aged 6 to 8 years and residing in neighborhoods with limited resources in Los Angeles, were individually randomized to either a music (intervention) or theatre (active control) after-school program. Both programs were delivered over 24 months by established community arts organizations. Eligibility criteria included: average intellectual functioning, no major medical or psychiatric conditions, and MRI eligibility. Children with prior formal music training exceeding six months or severe hearing impairment were excluded. Before the intervention began, all participants completed baseline behavioral and neuroimaging assessments. The primary trial aim was to assess the effects of extended music training, relative to theatre training, on changes in measures of IC (i.e., Go/No-Go task and delayed gratification) and related neural functional activation. A secondary interim aim of the trial was to evaluate the feasibility of conducting a long-term RCT of music education in a first cohort, measured by participant retention, adherence to the program, willingness to continue at the 12-month mark, and fidelity. Progress: Recruitment, screening, baseline testing, randomization, and program enrollment began in August 2022, and after-school programming began in October 2022. The randomized interventions and all data for the first cohort (N = 42) have been collected. Intervention and active control programs for a second cohort are ongoing and will end in Fall 2026. Discussion: This paper reports the EXCEL trial protocol and provides feasibility estimates for implementing a long-term randomized controlled trial of music training in real-world, community-based settings with children. While similar neuroimaging RCTs are currently underway in Europe, the EXCEL trial is among the first in the United States to integrate longitudinal neuroimaging with arts intervention. Findings will inform the viability of scaling such programs and contribute to our understanding of how sustained music engagement may influence the development of inhibitory control circuitry in childhood.

Background: Alpha-1 antitrypsin deficiency (AATD) caused by the PI*ZZ mutation (Glu342Lys) results in hepatic accumulation of misfolded AAT-Z protein and reduced circulating AAT levels, leading to progressive liver disease and emphysema. Gene correction therapy represents a potentially curative approach by directly correcting the underlying genetic defect. We report the first case of successful hepatic gene correction with early histological and functional assessment. Methods/Case presentation: We report the case of a 66-year-old male patient with PI*ZZ AATD who underwent gene correction therapy within the YOLT-202 phase I/Ia clinical trial (clinical trial.gov ID NCT07193615). Ten weeks post treatment a liver biopsy was performed to re-evaluate pre-existing F2 liver fibrosis as measured by elastography before entering the study. Serum samples allowed functional assessment of the AAT-mediated elastase inhibition. Results: Liver biopsy did not show signs of hepatic inflammation and demonstrated 54% (Sanger) and 57% (Illumina) gene correction rate of the PI*ZZ variant on the DNA level with no bystander edits or off-target effects. Following a transient elevation of transaminases during the early post-treatment period, liver enzymes normalized. Monthly serum AAT measurements demonstrated biologically active and stable therapeutic levels throughout follow-up. Conclusions: This case demonstrates efficient and precise hepatic gene correction without concerning histological alterations and with substantial improvement of functional parameters, supporting the feasibility and safety of gene editing approaches for AATD.

Abstract Background. Area-level cancer disparities are routinely estimated from public county data in which rates based on small counts (fewer than 16 cases or deaths) are suppressed. Analysts typically drop suppressed counties (complete-case analysis). Because suppression depends on case counts tied to population size and demographic composition, this missingness may be informative, but its effect on the disparity estimate has not, to our knowledge, been quantified. Methods. In a cross-sectional ecological study of 3,143 U.S. counties (analytic sample 3,018 with computable exposure) using one frozen public release of NCI State Cancer Profiles incidence and mortality data and ACS 2018-2022 5-year data, we estimated the most- versus least-deprived ICE(race+income) quintile rate ratio (RR) and rate difference for female breast, stomach, and cervix cancers under four suppression-handling methods: complete-case, available-case, bounding, and model-based small-area estimation. We characterized which counties were erased, and, following the ADEMP framework, ran a Monte Carlo simulation (1,000 replicates per cell; Monte Carlo standard error of bias approximately 0.0025) calibrated to the release to measure bias against a known truth. Analyses were pre-registered. Results. The suppressed fraction rose with rarity: 7.4% of counties for breast, 61.3% for stomach, and 75.7% for cervix incidence. Suppression was concentrated in the most-deprived quintile (cervix, 81.8% suppressed vs 63.8% least-deprived) and overwhelmingly removed rural rather than minority residents (cervix: 81% of the rural but 9% of the minority population erased). For breast (little suppression) the RR was 0.87 (95% CI 0.85-0.89) and identical across methods; for cervix incidence the complete-case RR (1.56) exceeded the model-based estimate (1.50), and for cervix mortality (91% suppressed) complete-case (1.86) exceeded model-based (1.56) by 16% with a wide bounding interval (1.88-2.62). In calibrated simulation, population-weighted complete-case bias was small (less than 2%) at the observed deprivation-county-size correlation and grew with rarity, threshold, and unweighted aggregation; its direction was conditional, becoming positive (over-estimation) as deprived counties became smaller. Conclusions. Complete-case handling of suppressed counties over-estimates rare-cancer area disparities relative to methods that retain them, while silently erasing most of the rural and most-deprived communities the estimate is meant to represent. The effect is negligible for common cancers and grows with rarity. Public-data disparity analyses should report the suppressed fraction and use bounded or model-based estimates by default. Keywords: cancer disparities; small-count suppression; Index of Concentration at the Extremes; informative missingness; small-area estimation; rural health.

Background: The traditional wealth index, based on principal component analysis (PCA), used in the Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS), suffers from urban bias, distorting estimates of health inequality. We compared the traditional index (PEAR1) with an alternative two-component polychoric PCA index (POLY2) using annual expenditure from 12 LSMS surveys as the gold standard to determine which provides more accurate SEP measures for equitable policy targeting. Methods: We compared the traditional wealth index (PEAR1) with a two-component polychoric PCA approach (POLY2) using 12 LSMS (Living Standards Measurement Study) surveys (2015-2022) from 12 African countries. Annual household consumption expenditure was the gold standard. We assessed agreement using weighted Cohen's kappa and validated against education (proportion of households with secondary or higher education) using the concentration index (CIX) and slope index of inequality (SII). Results: The POLY2 index showed higher agreement with expenditure quintiles (average national weighted kappa = 43.3%) than the PEAR1 index (35.1%), with notable improvements in urban (43.5% vs. 27.5%) and rural (35.3% vs. 22.4%) areas. POLY2 also attenuated extreme household distributions observed in PEAR1. Education validation showed that POLY2 produced intermediate inequality gradients between the flatter expenditure-based gradient and the steeper PEAR1-based gradient. Conclusion: The POLY2 wealth index is superior to the traditional index, reducing urban-rural bias and providing more accurate socioeconomic classifications. Its adoption in large-scale surveys such as DHS and MICS is recommended to improve equitable monitoring of health inequalities in low- and middle-income countries.

Diabetic peripheral neuropathy (DPN) is a common and disabling condition for which no disease-modifying therapies are available. Glycemic and metabolic drivers do not fully explain why only a subset of individuals with diabetes develop DPN, and genetic contributors remain poorly defined. We aimed to perform a multi-population genome-wide association study (GWAS) of DPN to highlight potential new etiological pathways and therapeutic targets. Methods We performed a multi-population GWAS of neuropathy in people with and without diabetes using the VA Million Veteran Program and UK Biobank, followed by replication in the All of Us Research Program (AoU), and gene-based and gene-set analyses to identify implicated pathways. Causal relationships between circulating serine levels and DPN were further tested using two sample Mendelian randomization. To further evaluate pathogenic potential, we analyzed rare, high impact variants in GWAS implicated genes among individuals with unresolved inherited neuropathies using the GENESIS platform. Findings Among individuals with type 2 diabetes, we identified seven genome wide significant loci (p<5x10-): PHGDH and PSPH (key serine synthesis genes), TEAD1, CYP4F11, LARGE1, FTO, and COBLL1. No loci were significant in individuals without diabetes or with type 1 diabetes. Four loci (PHGDH, TEAD1, FTO and CYP4F11) replicated in AoU (p <0.05). Mendelian randomization demonstrated that higher genetically predicted serine levels were associated with lower DPN risk, consistent with a causal role of serine metabolism in disease pathogenesis. Rare-variant burden analyses revealed associations of predicted deleterious variants with inherited neuropathy case status in PHGDH (odds ratio [OR] 12.7 [95% CI 7.9, 20.4]), PSPH (OR 8.5 [7.2, 10.2]), PHKG1 (OR 4.8 [3.7, 6.3]), and LARGE1 (OR 0.007 [0.0004, 0.1]). Interpretation Convergent genetic evidence across common and rare variation implicates serine synthesis as a key pathway in DPN. These findings link diabetic and inherited neuropathies through a shared metabolic mechanism, identifying serine metabolism as a potential therapeutic target.

PURPOSE: Alzheimer disease (AD) is associated with cognitive impairment, brain atrophy, and elevated amyloid-beta and tau. The study aimed to characterize regional atrophy associated with elevated amyloid-beta and tau, as measured by [18F]florbetapir (FBP) and [18F]flortaucipir (FTP) positron emission tomography (PET), respectively, and determine whether combining PET and atrophy data improves the prediction of cognitive impairment. METHODS: Alzheimer Disease Neuroimaging Initiative data (n = 381) were retrospectively analyzed. PET results were correlated with cortical thickness, gray matter (GM) volumes, Mini-Mental State Examination, and Montreal Cognitive Assessment. Linear/logistic regression and area under the curve (AUC) were used to evaluate for significant correlations and compare performances in distinguishing cognitive impairment, respectively. RESULTS: Incremental loss of cortical thickness and GM volume was observed from FBP-/FTP- (n = 205) to single PET-positive (FBP+/FTP-, n = 133; FBP-/FTP+, n = 5) and FBP+/FTP+ (n = 38) groups, particularly in the temporal and parietal lobes. FBP+/FTP+ showed the most severe cortical thickness loss in the entorhinal cortex, temporal lobe GM atrophy, and cognitive impairment. Adding brain atrophy as the third variable resulted in higher odds ratios and improved AUCs for cognitive impairment, with FBP+/FTP+/temporal GM or entorhinal cortical atrophy+ demonstrating the strongest associations with cognitive impairment. CONCLUSION: A multimodal approach combining PET and MRI may help improve the assessment of cognitive impairment in AD.

Background Electronic health record documentation patterns may reflect workflow complexity, monitoring intensity, and operational strain in intensive care settings. However, documentation-derived features can be sensitive to local documentation culture, data capture systems, and outcome definitions. Retrospective validation across multiple datasets is therefore needed before these signals are used in workflow intelligence or clinical AI governance tools. Objective To evaluate whether documentation-density and documentation-timing features show reproducible retrospective signal for ICU workflow complexity and long-stay proxy outcomes across de-identified critical care datasets, while distinguishing workflow and long-stay associations from unsupported claims about mortality prediction, burden reduction, or deployment readiness. Methods We synthesized retrospective validation results from de-identified ICU and workflow datasets generated through a prespecified documentation-density validation program. Feature families included Documentation Burden Score style features, Shift-End Documentation Rate style features, documentation reliability style metadata, and all-documentation feature sets where available. Outcomes included long ICU length of stay proxies, mortality where available, and workflow proxy endpoints. Models compared baseline feature sets with enhanced models containing documentation-density or workflow features. Performance was summarized using area under the receiver operating characteristic curve, Brier score where reported, delta AUROC, bootstrap confidence intervals where reported, and label-shuffle controls where available. Results The strongest external long-stay proxy evidence came from the NWICU chartevents analysis, which included 28,612 ICU stays, 20,267 stays with chart events, and 9,619,759 chart events. For ICU length of stay greater than the median, baseline AUROC was 0.5252. Enhanced AUROC was 0.9512 for Documentation Burden Score features, 0.9214 for Shift-End Documentation Rate features, 0.8470 for documentation reliability style features, and 0.9517 for all documentation features. Corresponding label-shuffle enhanced AUROCs were near random, ranging from 0.4897 to 0.5064. For ICU length of stay greater than the 75th percentile, baseline AUROC was 0.5155. Enhanced AUROC was 0.9433 for Documentation Burden Score features, 0.9194 for Shift-End Documentation Rate features, 0.8118 for documentation reliability style features, and 0.9427 for all documentation features, with label-shuffle enhanced AUROCs from 0.4836 to 0.4999. Additional retrospective support was observed in eICU workflow analyses, HiRID first-24-hour documentation-density analyses, MIMIC-IV HF ICU internal analyses, MIMIC-IV-Note metadata extensions, and nursing-chart or lab density proxy analyses. However, cross-institution discrimination transfer was weak without recalibration, and several analyses remained proxy validations rather than final clinical validations. Conclusions Documentation-density and documentation-timing features show promising retrospective signal for ICU workflow complexity and long-stay proxy outcomes, especially in NWICU chartevents and selected internal dataset-specific analyses. These findings support further preregistered, prospective, silent-mode validation of documentation-derived workflow intelligence. They do not establish prospective clinical performance, mortality reduction, clinician burden reduction, autonomous deterioration prediction, or deployment readiness.