Characterizing daily physical activity patterns with unsupervised learning via functional mixture models.

Physical inactivity is a significant public health concern. Consideration of inter-individual variations in physical activity (PA) trends can provide additional information about the groups under study to aid intervention design. This study aims to identify latent profiles ("phenotypes") based on daily PA trends among adults living in. This was a secondary analysis of 724 person-level days of accelerometry data from 133 urban-dwelling adults (89% Latinx, age = 19-77 years). We used Actigraph accelerometers and the Actilife software to collect and process 24-hour PA data. We implemented a probabilistic clustering technique based on functional mixture models. Multiple days of data per person were averaged for entry into the models. We evaluated step counts, moderate-intensity PA (MOD), total activity and sedentary minutes as potential model variables. Bayesian Information Criterion (BIC) index was used to select the model that provided the best fit for the data. A 4-cluster resolution provided the best fit for the data (i.e., BIC=-3257, improvements of Δ = 13 and Δ = 7 from 3- and 5-cluster models, respectively). MOD provided the greatest between-cluster discrimination. Phenotype 1 (N = 61) was characterized by a morning peak in PA that declined until bedtime. Later bedtimes and the highest daily PA volume were distinct for phenotype 2 (N = 18), along with a similar peak pattern. Phenotype 3 (N = 29) membership was associated with the lowest PA levels throughout the day. Phenotype 4 was characterized by a more evenly distributed PA during the day, and later waking/bedtimes. Our findings point to distinct, interpretable PA phenotypes based on temporal patterns. Functional clustering of PA data could provide additional actionable points for tailoring behavioral interventions.

Regression and alignment for functional data and network topology.

In the brain, functional connections form a network whose topological organization can be described by graph-theoretic network diagnostics. These include characterizations of the community structure, such as modularity and participation coefficient, which have been shown to change over the course of childhood and adolescence. To investigate if such changes in the functional network are associated with changes in cognitive performance during development, network studies often rely on an arbitrary choice of preprocessing parameters, in particular the proportional threshold of network edges. Because the choice of parameter can impact the value of the network diagnostic, and therefore downstream conclusions, we propose to circumvent that choice by conceptualizing the network diagnostic as a function of the parameter. As opposed to a single value, a network diagnostic curve describes the connectome topology at multiple scales-from the sparsest group of the strongest edges to the entire edge set. To relate these curves to executive function and other covariates, we use scalar-on-function regression, which is more flexible than previous functional data-based models used in network neuroscience. We then consider how systematic differences between networks can manifest in misalignment of diagnostic curves, and consequently propose a supervised curve alignment method that incorporates auxiliary information from other variables. Our algorithm performs both functional regression and alignment via an iterative, penalized, and nonlinear likelihood optimization. The illustrated method has the potential to improve the interpretability and generalizability of neuroscience studies where the goal is to study heterogeneity among a mixture of function- and scalar-valued measures.

Associations of Infant Sleep Characteristics with Childhood Cognitive Outcomes.

OBJECTIVE: The objective of this study was to quantify associations of infant 24-hour sleep duration and nighttime sleep consolidation with later child cognition. METHODS: This study included children from Project Viva, a prospective cohort in Massachusetts with (1) sleep measures in infancy (median age 6.4 months) and (2) child cognition in early childhood (median age 3.2 years) or mid-childhood (median age 7.7 years). Main exposures were parental reports of infant 24-hour sleep duration and nighttime sleep consolidation (% of total daily sleep occurring at nighttime). Cognitive outcomes were (1) early childhood vocabulary and visual-motor abilities and (2) mid-childhood verbal and nonverbal intelligence quotient (IQ), memory, and visual-motor abilities. We examined associations of infant sleep with childhood cognition using linear regression models adjusted for child sex, age, and race or ethnicity; maternal age, education, and parity; and household income. RESULTS: Early and mid-childhood analyses included 1102 and 969 children, respectively. Most mothers reported infant race or ethnicity as White (69%) and were college graduates (71%). The mean infant 24-hour sleep duration was 12.2 ± 2.0 hours, and the mean nighttime sleep consolidation was 76.8% ± 8.8%. Infant 24-hour sleep duration was not associated with any early or mid-childhood outcomes. Higher infant nighttime sleep consolidation was associated with higher mid-childhood verbal intelligence (ß: 0.12 points per % nighttime sleep; 95% CI, 0.01-0.22), but not with any early childhood cognitive measures. CONCLUSION: In this cohort, higher infant nighttime sleep consolidation was associated with higher verbal IQ in mid-childhood. Future studies should investigate causal relationships of infant sleep consolidation with child cognition among diverse populations.

Influence of folic acid and vitamin B12 supplementation on arsenic methylation: A double-blinded, placebo-controlled trial in Bangladeshi children.

BACKGROUND: Inorganic arsenic is metabolized to monomethyl- (MMAs) and dimethyl- (DMAs) species via one-carbon metabolism (OCM); this facilitates urinary arsenic elimination. OCM is influenced by folate and vitamin B12 and previous randomized control trials (RCTs) showed that folic acid (FA) supplementation increases arsenic methylation in adults. This RCT investigated the effects of FA + B12 supplementation on arsenic methylation in children, a key developmental stage where OCM supports growth. METHODS: A total of 240 participants (8-11 years, 53 % female) drinking from wells with arsenic concentrations > 50 µg/L, were encouraged to switch to low arsenic wells and were randomized to receive 400 µg FA + 5 µg B12 or placebo daily for 12-weeks. Urine and blood samples were collected at baseline, week 1 (only urine) and week 12. Generalized estimated equation (GEE) models were used to assess treatment effects on arsenic species in blood and urine. RESULTS: At baseline, the mean ± SD total blood and urinary arsenic were 5.3 ± 2.9 µg/L and 91.2 ± 89.5 µg/L. Overall, total blood and urine arsenic decreased by 11.7% and 17.6%, respectively, at the end of follow up. Compared to placebo, the supplementation group experienced a significant increase in the concentration of blood DMAs by 14.0% (95% CI 5.0, 25.0) and blood secondary methylation index (DMAs/MMAs) by 0.19 (95% CI: 0.09, 0.35) at 12 weeks. Similarly, there was a 1.62% (95% CI: 0.43, 20.83) significantly higher urinary %DMAs and -1.10% (95% CI: -1.73, -0.48) significantly lower urinary %MMAs in the supplementatio group compared to the placebo group after 1 week. The direction of the changes in the urinary %iAs, %MMAs, and %DMAs at week 12 were consistent with those at week 1, though estimates were not significant. Treatment effects were stronger among participants with higher baseline blood arsenic concentrations. Results were consistent across males and females, and participants with higher and lower folate and B12 status at baseline. CONCLUSION: This RCT confirms that FA + B12 supplementation increases arsenic methylation in children as reflected by decreased MMAs and increased DMAs in blood and urine. Nutritional interventions may improve arsenic methylation and elimination in children, potentially reducing arsenic toxicity while also improving nutritional status.

Inverse associations of cord blood mitochondrial DNA copy number with childhood adiposity.

OBJECTIVE: The objective of this study was to examine associations between umbilical cord mitochondrial DNA copy number (mtDNAcn) and adiposity across childhood. METHODS: In a prospective birth cohort of Dominican and African American children from New York City, New York (1998-2006), mtDNAcn was measured in cord blood. Children (N = 336) were evaluated for their height, weight, and bioimpedance at age 5, 7, 9, and 11 years. We used linear mixed-effects models to assess associations of mtDNAcn tertiles in cord blood with child BMI, BMI z scores, fat mass index, and body fat percentage. Latent class growth models and interactions between mtDNAcn and child age or child age2 were used to assess associations between age and adiposity trajectories. RESULTS: BMI was, on average, 1.5 kg/m2 higher (95% CI: 0.58, 2.5) in individuals with mtDNAcn in the low- compared with the middle-mtDNAcn tertile. Results were similar for BMI z score, fat mass index, and body fat percentage. Moreover, children in the low-mtDNAcn group had increased odds of being in an "increasing" or "high-stable" adiposity class. CONCLUSIONS: Lower mtDNAcn at birth may predict greater childhood adiposity, highlighting the potential key role of perinatal mitochondrial function in adiposity during development.

Longitudinal Associations of Food Security with Health and Dietary Factors among Food FARMacy Participants during COVID-19 in New York City.

In cross-sectional studies, food insecurity is associated with adverse health and dietary outcomes. Whether self-reported health and dietary outcomes change in response to improvements in food security has not been examined. We sought to examine how increases in food security are related to changes in health and dietary factors. In this longitudinal, observational study, we included adult participants in a clinical-community emergency food assistance program in New York City from July 2020 to November 2021. Program staff measured food security with a validated six-item measure at program enrollment and six-month re-enrollment. Participants self-reported health and dietary factors (vegetable, fruit, juice, and sugar-sweetened beverage (SSB) consumption frequency). We used multivariable regression to examine associations between change in food security with change in health and dietary factors over six months. Among 310 participants, the mean food security score improved by 1.7 ± 2.3 points over six months. In unadjusted models, each point improvement in food security was associated with increased vegetable (ß = 0.10 times; 95% CI: 0.05-0.15); fruit (ß = 0.08 times; 95% CI: 0.03-0.14); and juice (ß = 0.10 times; 95% CI: 0.05-0.15) consumption. In adjusted models, results remained significant for vegetable and fruit consumption, but not juice. Change in food security was not associated with change in health or SSB outcomes. In this cohort during COVID-19, improved food security was associated with improved vegetable and fruit consumption. Randomized trials that examine the effectiveness of clinical-community partnerships focused on improving food security and nutrition are warranted.

An environmental justice analysis of air pollution emissions in the United States from 1970 to 2010.

Over the last decades, air pollution emissions have decreased substantially; however, inequities in air pollution persist. We evaluate county-level racial/ethnic and socioeconomic disparities in emissions changes from six air pollution source sectors (industry [SO2], energy [SO2, NOx], agriculture [NH3], commercial [NOx], residential [particulate organic carbon], and on-road transportation [NOx]) in the contiguous United States during the 40 years following the Clean Air Act (CAA) enactment (1970-2010). We calculate relative emission changes and examine the differential changes given county demographics using hierarchical nested models. The results show racial/ethnic disparities, particularly in the industry and energy generation source sectors. We also find that median family income is a driver of variation in relative emissions changes in all sectors-counties with median family income >$75 K vs. less generally experience larger relative declines in industry, energy, transportation, residential, and commercial-related emissions. Emissions from most air pollution source sectors have, on a national level, decreased following the United States CAA. In this work, we show that the relative reductions in emissions varied across racial/ethnic and socioeconomic groups.

Regression and Alignment for Functional Data and Network Topology.

In the brain, functional connections form a network whose topological organization can be described by graph-theoretic network diagnostics. These include characterizations of the community structure, such as modularity and participation coefficient, which have been shown to change over the course of childhood and adolescence. To investigate if such changes in the functional network are associated with changes in cognitive performance during development, network studies often rely on an arbitrary choice of pre-processing parameters, in particular the proportional threshold of network edges. Because the choice of parameter can impact the value of the network diagnostic, and therefore downstream conclusions, we propose to circumvent that choice by conceptualizing the network diagnostic as a function of the parameter. As opposed to a single value, a network diagnostic curve describes the connectome topology at multiple scales-from the sparsest group of the strongest edges to the entire edge set. To relate these curves to executive function and other covariates, we use scalar-on-function regression, which is more flexible than previous functional data-based models used in network neuroscience. We then consider how systematic differences between networks can manifest in misalignment of diagnostic curves, and consequently propose a supervised curve alignment method that incorporates auxiliary information from other variables. Our algorithm performs both functional regression and alignment via an iterative, penalized, and nonlinear likelihood optimization. The illustrated method has the potential to improve the interpretability and generalizability of neuroscience studies where the goal is to study heterogeneity among a mixture of function- and scalar-valued measures.

Metabolomic Effects of Folic Acid Supplementation in Adults: Evidence from the FACT Trial.

BACKGROUND: Folic acid (FA) is the oxidized form of folate found in supplements and FA-fortified foods. Most FA is reduced by dihydrofolate reductase to 5-methyltetrahydrofolate (5mTHF); the latter is the form of folate naturally found in foods. Ingestion of FA increases the plasma levels of both 5mTHF and unmetabolized FA (UMFA). Limited information is available on the downstream metabolic effects of FA supplementation, including potential effects associated with UMFA. OBJECTIVE: We aimed to assess the metabolic effects of FA-supplementation, and the associations of plasma 5mTHF and UMFA with the metabolome in FA-naïve Bangladeshi adults. METHODS: Sixty participants were selected from the Folic Acid and Creatine Trial; half received 800 µg FA/day for 12 weeks and half placebo. Plasma metabolome profiles were measured by high-resolution mass spectrometry, including 170 identified metabolites and 26,541 metabolic features. Penalized regression methods were used to assess the associations of targeted metabolites with FA-supplementation, plasma 5mTHF, and plasma UMFA. Pathway analyses were conducted using Mummichog. RESULTS: In penalized models of identified metabolites, FA-supplementation was associated with higher choline. Changes in 5mTHF concentrations were positively associated with metabolites involved in amino acid metabolism (5-hydroxyindoleacetic acid, acetylmethionine, creatinine, guanidinoacetate, hydroxyproline/n-acetylalanine) and 2 fatty acids (docosahexaenoic acid and linoleic acid). Changes in 5mTHF concentrations were negatively associated with acetylglutamate, acetyllysine, carnitine, propionyl carnitine, cinnamic acid, homogentisate, arachidonic acid, and nicotine. UMFA concentrations were associated with lower levels of arachidonic acid. Together, metabolites selected across all models were related to lipids, aromatic amino acid metabolism, and the urea cycle. Analyses of nontargeted metabolic features identified additional pathways associated with FA supplementation. CONCLUSION: In addition to the recapitulation of several expected metabolic changes associated with 5mTHF, we observed additional metabolites/pathways associated with FA-supplementation and UMFA. Further studies are needed to confirm these associations and assess their potential implications for human health. TRIAL REGISTRATION NUMBER: This trial was registered at https://clinicaltrials.gov as NCT01050556.

Method validation for (ultra)-trace element concentrations in urine for small sample volumes in large epidemiological studies: application to the population-based epidemiological multi-ethnic study of atherosclerosis (MESA).

Analysis of essential and non-essential trace elements in urine has emerged as a valuable tool for assessing occupational and environmental exposures, diagnosing nutritional status and guiding public health and health care intervention. Our study focused on the analysis of trace elements in urine samples from the Multi-Ethnic Study of Atherosclerosis (MESA), a precious resource for health research with limited sample volumes. Here we provide a comprehensive and sensitive method for the analysis of 18 elements using only 100 µL of urine. Method sensitivity, accuracy, and precision were assessed. The analysis by inductively coupled plasma mass spectrometry (ICP-MS) included the measurement of antimony (Sb), arsenic (As), barium (Ba), cadmium (Cd), cesium (Cs), cobalt (Co), copper (Cu), gadolinium (Gd), lead (Pb), manganese (Mn), molybdenum (Mo), nickel (Ni), selenium (Se), strontium (Sr), thallium (Tl), tungsten (W), uranium (U), and zinc (Zn). Further, we reported urinary trace element concentrations by covariates including gender, ethnicity/race, smoking and location. The results showed good accuracy and sensitivity of the ICP-MS method with the limit of detections rangings between 0.001 µg L-1 for U to 6.2 µg L-1 for Zn. Intra-day precision for MESA urine analysis varied between 1.4% for Mo and 26% for Mn (average 6.4% for all elements). The average inter-day precision for most elements was <8.5% except for Gd (20%), U (16%) and Mn (19%) due to very low urinary concentrations. Urinary mean concentrations of non-essential elements followed the order of Sr > As > Cs > Ni > Ba > Pb > Cd > Gd > Tl > W > U. The order of urinary mean concentrations for essential trace elements was Zn > Se > Mo > Cu > Co > Mn. Non-adjusted mean concentration of non-essential trace elements in urine from MESA participants follow the order Sr > As > Cs > Ni > Ba > Pb > Cd > Gd > Tl > W > U. The unadjusted urinary mean concentrations of essential trace elements decrease from Zn > Se > Mo > Cu > Co > Mn.

Fine particulate matter composition in American Indian vs. Non-American Indian communities.

BACKGROUND: Fine particulate matter (PM2.5) exposure is a known risk factor for numerous adverse health outcomes, with varying estimates of component-specific effects. Populations with compromised health conditions such as diabetes can be more sensitive to the health impacts of air pollution exposure. Recent trends in PM2.5 in primarily American Indian- (AI-) populated areas examined in previous work declined more gradually compared to the declines observed in the rest of the US. To further investigate components contributing to these findings, we compared trends in concentrations of six PM2.5 components in AI- vs. non-AI-populated counties over time (2000-2017) in the contiguous US. METHODS: We implemented component-specific linear mixed models to estimate differences in annual county-level concentrations of sulfate, nitrate, ammonium, organic matter, black carbon, and mineral dust from well-validated surface PM2.5 models in AI- vs. non-AI-populated counties, using a multi-criteria approach to classify counties as AI- or non-AI-populated. Models adjusted for population density and median household income. We included interaction terms with calendar year to estimate whether concentration differences in AI- vs. non-AI-populated counties varied over time. RESULTS: Our final analysis included 3108 counties, with 199 (6.4%) classified as AI-populated. On average across the study period, adjusted concentrations of all six PM2.5 components in AI-populated counties were significantly lower than in non-AI-populated counties. However, component-specific levels in AI- vs. non-AI-populated counties varied over time: sulfate and ammonium levels were significantly lower in AI- vs. non-AI-populated counties before 2011 but higher after 2011 and nitrate levels were consistently lower in AI-populated counties. CONCLUSIONS: This study indicates time trend differences of specific components by AI-populated county type. Notably, decreases in sulfate and ammonium may contribute to steeper declines in total PM2.5 in non-AI vs. AI-populated counties. These findings provide potential directives for additional monitoring and regulations of key emissions sources impacting tribal lands.

Distinguishing Distinct Neural Systems for Proximal vs Distal Upper Extremity Motor Control After Acute Stroke.

BACKGROUND AND OBJECTIVES: The classic and singular pattern of distal greater than proximal upper extremity motor deficits after acute stroke does not account for the distinct structural and functional organization of circuits for proximal and distal motor control in the healthy CNS. We hypothesized that separate proximal and distal upper extremity clinical syndromes after acute stroke could be distinguished and that patterns of neuroanatomical injury leading to these 2 syndromes would reflect their distinct organization in the intact CNS. METHODS: Proximal and distal components of motor impairment (upper extremity Fugl-Meyer score) and strength (Shoulder Abduction Finger Extension score) were assessed in consecutively recruited patients within 7 days of acute stroke. Partial correlation analysis was used to assess the relationship between proximal and distal motor scores. Functional outcomes including the Box and Blocks Test (BBT), Barthel Index (BI), and modified Rankin scale (mRS) were examined in relation to proximal vs distal motor patterns of deficit. Voxel-based lesion-symptom mapping was used to identify regions of injury associated with proximal vs distal upper extremity motor deficits. RESULTS: A total of 141 consecutive patients (49% female) were assessed 4.0 ± 1.6 (mean ± SD) days after stroke onset. Separate proximal and distal upper extremity motor components were distinguishable after acute stroke (p = 0.002). A pattern of proximal more than distal injury (i.e., relatively preserved distal motor control) was not rare, observed in 23% of acute stroke patients. Patients with relatively preserved distal motor control, even after controlling for total extent of deficit, had better outcomes in the first week and at 90 days poststroke (BBT, ρ = 0.51, p < 0.001; BI, ρ = 0.41, p < 0.001; mRS, ρ = 0.38, p < 0.001). Deficits in proximal motor control were associated with widespread injury to subcortical white and gray matter, while deficits in distal motor control were associated with injury restricted to the posterior aspect of the precentral gyrus, consistent with the organization of proximal vs distal neural circuits in the healthy CNS. DISCUSSION: These results highlight that proximal and distal upper extremity motor systems can be selectively injured by acute stroke, with dissociable deficits and functional consequences. Our findings emphasize how disruption of distinct motor systems can contribute to separable components of poststroke upper extremity hemiparesis.

Exploring Relevant Time Windows in the Association Between PM2.5 Exposure and Amyotrophic Lateral Sclerosis: A Case-Control Study in Denmark.

Studies suggest a link between particulate matter less than or equal to 2.5 µm in diameter (PM2.5) and amyotrophic lateral sclerosis (ALS), but to our knowledge critical exposure windows have not been examined. We performed a case-control study in the Danish population spanning the years 1989-2013. Cases were selected from the Danish National Patient Registry based on International Classification of Diseases codes. Five controls were randomly selected from the Danish Civil Registry and matched to a case on vital status, age, and sex. PM2.5 concentration at residential addresses was assigned using monthly predictions from a dispersion model. We used conditional logistic regression to estimate odds ratios (ORs) and 95% confidence intervals (CIs), adjusting for confounding. We evaluated exposure to averaged PM2.5 concentrations 12-24 months, 2-6 years, and 2-11 years pre-ALS diagnosis; annual lagged exposures up to 11 years prediagnosis; and cumulative associations for exposure in lags 1-5 years and 1-10 years prediagnosis, allowing for varying association estimates by year. We identified 3,983 cases and 19,915 controls. Cumulative exposure to PM2.5 in the period 2-6 years prediagnosis was associated with ALS (OR = 1.06, 95% CI: 0.99, 1.13). Exposures in the second, third, and fourth years prediagnosis were individually associated with higher odds of ALS (e.g., for lag 1, OR = 1.04, 95% CI: 1.00, 1.08). Exposure to PM2.5 within 6 years before diagnosis may represent a critical exposure window for ALS.

Applying principal component pursuit to investigate the association between source-specific fine particulate matter and myocardial infarction hospitalizations in New York City.

The association between fine particulate matter (PM2.5) and cardiovascular outcomes is well established. To evaluate whether source-specific PM2.5 is differentially associated with cardiovascular disease in New York City (NYC), we identified PM2.5 sources and examined the association between source-specific PM2.5 exposure and risk of hospitalization for myocardial infarction (MI). Methods: We adapted principal component pursuit (PCP), a dimensionality-reduction technique previously used in computer vision, as a novel pattern recognition method for environmental mixtures to apportion speciated PM2.5 to its sources. We used data from the NY Department of Health Statewide Planning and Research Cooperative System of daily city-wide counts of MI admissions (2007-2015). We examined associations between same-day, lag 1, and lag 2 source-specific PM2.5 exposure and MI admissions in a time-series analysis, using a quasi-Poisson regression model adjusting for potential confounders. Results: We identified four sources of PM2.5 pollution: crustal, salt, traffic, and regional and detected three single-species factors: cadmium, chromium, and barium. In adjusted models, we observed a 0.40% (95% confidence interval [CI]: -0.21, 1.01%) increase in MI admission rates per 1 µg/m3 increase in traffic PM2.5, a 0.44% (95% CI: -0.04, 0.93%) increase per 1 µg/m3 increase in crustal PM2.5, and a 1.34% (95% CI: -0.46, 3.17%) increase per 1 µg/m3 increase in chromium-related PM2.5, on average. Conclusions: In our NYC study, we identified traffic, crustal dust, and chromium PM2.5 as potentially relevant sources for cardiovascular disease. We also demonstrated the potential utility of PCP as a pattern recognition method for environmental mixtures.

Association of a primary care-based mobile food pantry with child body mass index: A propensity score matched cohort study.

OBJECTIVE: To test the hypothesis that children in Food FARMacia-a six-month food insecurity intervention from May 2019 to January 2020-would have smaller age-adjusted, sex-specific body mass index (BMIz) gains than matched counterparts. METHODS: In this proof-of-concept study, we performed a difference-in-differences (DiD) analysis of a propensity-score matched cohort among paediatric primary care patients aged <6 years with household food insecurity. Children with anthropometric measures prior to and after intervention started were included. The main outcome was child BMIz from standardized clinical anthropometric measurements. We examined differences in child BMIz change between Food FARMacia participants and matched non-participants. RESULTS: Among 454 children with household food insecurity, 265 were included, 44 of whom were in Food FARMacia. Mean child age was 1.48 (SD 1.46) years and most reported Hispanic/Latino ethnicity (84.5%). After propensity score matching, children in Food FARMacia had smaller increases in BMIz (unadjusted DiD -0.28 [-0.52, -0.04]) compared to non-participants in the follow-up period. After adjusting for potential confounders, findings remained statistically significant [adjusted DiD, -0.31 units (95% CI: -0.54, -0.08)]. CONCLUSIONS: In this proof-of-concept cohort study of children in households with food insecurity, a paediatric primary care-based mobile food pantry program was associated with improvement in child BMIz over 6 months.

The Folic Acid and Creatine Trial: Treatment Effects of Supplementation on Arsenic Methylation Indices and Metabolite Concentrations in Blood in a Bangladeshi Population.

BACKGROUND: Chronic arsenic (As) exposure is a global environmental health issue. Inorganic As (InAs) undergoes methylation to monomethyl (MMAs) and dimethyl-arsenical species (DMAs); full methylation to DMAs facilitates urinary excretion and is associated with reduced risk for As-related health outcomes. Nutritional factors, including folate and creatine, influence one-carbon metabolism, the biochemical pathway that provides methyl groups for As methylation. OBJECTIVE: Our aim was to investigate the effects of supplementation with folic acid (FA), creatine, or the two combined on the concentrations of As metabolites and the primary methylation index (PMI: MMAs/InAs) and secondary methylation index (SMI: DMAs/MMAs) in blood in Bangladeshi adults having a wide range of folate status. METHODS: In a randomized, double-blinded, placebo (PBO)-controlled trial, 622 participants were recruited independent of folate status and assigned to one of five treatment arms: a) PBO (n=102), b) 400µg FA/d (400FA; n=153), c) 800µg FA/d (800FA; n=151), d) 3g creatine/d (creatine; n=101), or e) 3g creatine+400µg of FA/d (creatine+400FA; n=103) for 12 wk. For the following 12 wk, half of the FA participants were randomly switched to the PBO while the other half continued FA supplementation. All participants received As-removal water filters at baseline. Blood As (bAs) metabolites were measured at weeks 0, 1, 12, and 24. RESULTS: At baseline, 80.3% (n=489) of participants were folate sufficient (≥9 nmol/L in plasma). In all groups, bAs metabolite concentrations decreased, likely due to filter use; for example, in the PBO group, blood concentrations of MMAs (bMMAs) (geometric mean±geometric standard deviation) decreased from 3.55±1.89µg/L at baseline to 2.73±1.74 at week 1. After 1 wk, the mean within-person increase in SMI for the creatine+400FA group was greater than that of the PBO group (p=0.05). The mean percentage decrease in bMMAs between baseline and week 12 was greater for all treatment groups compared with the PBO group [400FA: -10.4 (95% CI: -11.9, -8.75), 800FA: -9.54 (95% CI: -11.1, -7.97), creatine: -5.85 (95% CI: -8.59, -3.03), creatine+400FA: -8.44 (95% CI: -9.95, -6.90), PBO: -2.02 (95% CI: -4.03, 0.04)], and the percentage increase in blood DMAs (bDMAs) concentrations for the FA-treated groups significantly exceeded that of PBO [400FA: 12.8 (95% CI: 10.5, 15.2), 800FA: 11.3 (95% CI: 8.95, 13.8), creatine+400FA: 7.45 (95% CI: 5.23, 9.71), PBO: -0.15 (95% CI: -2.85, 2.63)]. The mean decrease in PMI and increase in SMI in all FA groups significantly exceeded PBO (p<0.05). Data from week 24 showed evidence of a reversal of treatment effects on As metabolites from week 12 in those who switched from 800FA to PBO, with significant decreases in SMI [-9.0% (95% CI: -3.5, -14.8)] and bDMAs [-5.9% (95% CI: -1.8, -10.2)], whereas PMI and bMMAs concentrations continued to decline [-7.16% (95% CI: -0.48, -14.3) and -3.1% (95% CI: -0.1, -6.2), respectively] for those who remained on 800FA supplementation. CONCLUSIONS: FA supplementation lowered bMMAs and increased bDMAs in a sample of primarily folate-replete adults, whereas creatine supplementation lowered bMMAs. Evidence of the reversal of treatment effects on As metabolites following FA cessation suggests short-term benefits of supplementation and underscores the importance of long-term interventions, such as FA fortification. https://doi.org/10.1289/EHP11270.

How many days are needed? Measurement reliability of wearable device data to assess physical activity.

INTRODUCTION/PURPOSE: Physical activity studies often utilize wearable devices to measure participants' habitual activity levels by averaging values across several valid observation days. These studies face competing demands-available resources and the burden to study participants must be balanced with the goal to obtain reliable measurements of a person's longer-term average. Information about the number of valid observation days required to reliably measure targeted metrics of habitual activity is required to inform study design. METHODS: To date, the number of days required to achieve a desired level of aggregate long-term reliability (typically 0.80) has often been estimated by applying the Spearman-Brown Prophecy formula to short-term test-retest reliability data from studies with single, relatively brief observation windows. Our work, in contrast, utilizes a resampling-based approach to quantify the long-term test-retest reliability of aggregate measures of activity in a cohort of 79 participants who were asked to wear a FitBit Flex every day for approximately one year. RESULTS: The conventional approach can produce reliability estimates that substantially overestimate the actual test-retest reliability. Six or more valid days of observation for each participant appear necessary to obtain 0.80 reliability for the average amount of time spent in light physical activity; 8 and 10 valid days are needed for sedentary time and moderate/vigorous activity respectively. CONCLUSION: Protocols that result in 7-10 valid observation days for each participant may be needed to obtain reliable measurements of key physical activity metrics.

Mitochondrial DNA copy number dynamics and associations with the prenatal environment from birth through adolescence in a population of Dominican and African American children.

Mitochondrial DNA copy number (mtDNAcn) dynamics throughout childhood are poorly understood. We profiled mtDNAcn from birth through adolescence and evaluated how the prenatal environment influences mtDNAcn across childhood. Data were collected from children from New York City followed through 18 years. Using duplexed qRT-PCR, we quantified mtDNAcn relative to nuclear DNA in blood collected from the umbilical cord (n = 450), children aged 5-7 (n = 510), and adolescents aged 15-18 (n = 278). We examined mtDNAcn across childhood with linear mixed-effects models (LMM). Relative mtDNAcn was lowest at birth (mean ± SD: 0.67 ± 0.35) and increased in childhood (1.24 ± 0.50) then slightly declined in adolescence (1.13 ± 0.44). We observed no differences in mtDNAcn by sex or race/ethnicity. mtDNAcn was positively associated with prenatal environmental tobacco smoke exposure (0.077 [ 0.01, 0.14] change in relative mtDNAcn) but negatively associated with maternal completion of high school (-0.066 [-0.13, 0.00]), with the receipt of public assistance at birth (-0.074 [-0.14, -0.01]), and when mother born outside the U.S (-0.061 [-0.13, 0.003]). Infant birth outcomes were not associated with mtDNAcn. MtDNAcn levels were dynamic through childhood and associated with some prenatal factors, underscoring the need for the investigation of longitudinal mtDNAcn for human health research.

Metabolomic changes associated with chronic arsenic exposure in a Bangladeshi population.

Chronic exposure to arsenic (As) remains a global public health concern and our understanding of the biological mechanisms underlying the adverse effects of As exposure remains incomplete. Here, we used a high-resolution metabolomics approach to examine how As affects metabolic pathways in humans. We selected 60 non-smoking adults from the Folic Acid and Creatine Trial (FACT). Inorganic (AsIII, AsV) and organic (monomethylarsonous acid [MMAs], dimethylarsinous Acid [DMAs]) As species were measured in blood and urine collected at baseline and at 12 weeks. Plasma metabolome profiles were measured using untargeted high-resolution mass spectrometry. Associations of blood and urinary As with 170 confirmed metabolites and >26,000 untargeted spectral features were modeled using a metabolome-wide association study (MWAS) approach. Models were adjusted for age, sex, visit, and BMI and corrected for false discovery rate (FDR). In the MWAS screening of confirmed metabolites, 17 were associated with ≥1 blood As species (FDR<0.05), including fatty acids, neurotransmitter metabolites, and amino acids. These results were consistent across blood As species and between blood and urine As. Untargeted MWAS identified 423 spectral features associated with ≥1 blood As species. Unlike the confirmed metabolites, untargeted model results were not consistent across As species, with AsV and DMAs showing distinct association patterns. Mummichog pathway analysis revealed 12 enriched metabolic pathways that overlapped with the 17 identified metabolites, including one carbon metabolism, tricarboxylic acid cycle, fatty acid metabolism, and purine metabolism. Exposure to As may affect numerous essential pathways that underlie the well-characterized associations of As with multiple chronic diseases.

Epidural stimulation of the cervical spinal cord for post-stroke upper-limb paresis.

Cerebral strokes can disrupt descending commands from motor cortical areas to the spinal cord, which can result in permanent motor deficits of the arm and hand. However, below the lesion, the spinal circuits that control movement remain intact and could be targeted by neurotechnologies to restore movement. Here we report results from two participants in a first-in-human study using electrical stimulation of cervical spinal circuits to facilitate arm and hand motor control in chronic post-stroke hemiparesis ( NCT04512690 ). Participants were implanted for 29 d with two linear leads in the dorsolateral epidural space targeting spinal roots C3 to T1 to increase excitation of arm and hand motoneurons. We found that continuous stimulation through selected contacts improved strength (for example, grip force +40% SCS01; +108% SCS02), kinematics (for example, +30% to +40% speed) and functional movements, thereby enabling participants to perform movements that they could not perform without spinal cord stimulation. Both participants retained some of these improvements even without stimulation and no serious adverse events were reported. While we cannot conclusively evaluate safety and efficacy from two participants, our data provide promising, albeit preliminary, evidence that spinal cord stimulation could be an assistive as well as a restorative approach for upper-limb recovery after stroke.