Multimodal brain predictors of current weight and weight gain in children enrolled in the ABCD study ®.
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ABSTRACT:
SUBMITTER: Adise S
PROVIDER: S-EPMC8066422 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:ObjectiveThis archival project (a) examined potential risk and protective factors for hazards in the homes of Spanish-speaking immigrant Latino families and (b) provided an independent examination of the SafeCare®+ Home Safety module adapted for Latino families at high risk for child neglect.MethodsThe sample comprised 92 Latina caregivers of young children enrolled in SafeCare®+.ResultsResults of the negative binomial regression model of predictors of home hazards before the Home Safety module found none of the factors were significant. The longitudinal analysis with a negative binomial model found significant effects both during (b = -0.905, p < .001) and after (b = -2.118, p < .001) the intervention. Depression was negatively associated with the number of hazards (b = -0.026, p < .05, β = -.1858).ConclusionsSupport for application of SafeCare®+ Home Safety module to prevent access to hazards for Latino children was found.
| S-EPMC6543967 | biostudies-literature
Project description:BackgroundThere are significant knowledge gaps of the vulnerabilities faced by youth from families with histories of alcohol or substance misuse. This study aimed to provide a comprehensive assessment of problems experienced by substance-naive children with positive family histories of substance misuse (FHP).MethodsBaseline data from up to 11,873 children (52.1 % male), aged 9.0-10.9 years (M = 9.9 ± 0.6), enrolled in the US-based Adolescent Brain Cognitive Development Study® were utilized. Mixed models tested cross-sectional associations between family history of substance misuse, assessed categorically and continuously, with neurobiological, cognitive, behavioral, and psychological outcomes, when controlling for confounding factors, including family history of psychopathology, and correcting for multiple comparisons.ResultsOne in four (26.3 %) youth were categorized as FHP (defined as ≥ one parent or ≥ two grandparents with misuse history). Controlling for confounding, FHP youth exhibited thinner whole cortices and greater surface area in frontal and occipital regions than youth with no such history (|ds|≥0.04, ps<.001). FHP youth experienced greater psychopathology and sleep disturbance (|ds|≥0.36, ps<.001) and were more likely to be diagnosed with multiple mental disorders (odds ratios≥1.22, ps<.001), with severity of effects dependent on family history density of substance misuse. Differences in cognition, impulsivity, and motivation were non-significant. Psychopathology, mental disorders, and sleep disturbance were negatively correlated with various neural indices (|rs|=0.01-0.05, ps<.05).ConclusionsAt age 9-10 years, FHP youth can experience numerous problems, with psychopathology and mental disorders being some of the most significant. Therefore, prevention efforts should target psychopathology vulnerabilities in FHP children.
| S-EPMC7750301 | biostudies-literature
Project description:BackgroundDepression is the leading cause of disability worldwide with > 50% of cases emerging before the age of 25 years. Large-scale neuroimaging studies in depression implicate robust structural brain differences in the disorder. However, most studies have been conducted in adults and therefore, the temporal origins of depression-related imaging features remain largely unknown. This has important implications for understanding aetiology and informing timings of potential intervention.MethodsHere, we examine associations between brain structure (cortical metrics and white matter microstructural integrity) and depression ratings (from caregiver and child), in a large sample (N = 8634) of early adolescents (9 to 11 years old) from the US-based, Adolescent Brain and Cognitive Development (ABCD) Study®. Data was collected from 2016 to 2018.FindingsWe report significantly decreased global cortical and white matter metrics, and regionally in frontal, limbic and temporal areas in adolescent depression (Cohen's d = -0⋅018 to -0⋅041, β = -0·019 to -0⋅057). Further, we report consistently stronger imaging associations for caregiver-reported compared to child-reported depression ratings. Divergences between reports (caregiver vs child) were found to significantly relate to negative socio-environmental factors (e.g., family conflict, absolute β = 0⋅048 to 0⋅169).InterpretationDepression ratings in early adolescence were associated with similar imaging findings to those seen in adult depression samples, suggesting neuroanatomical abnormalities may be present early in the disease course, arguing for the importance of early intervention. Associations between socio-environmental factors and reporter discrepancy warrant further consideration, both in the wider context of the assessment of adolescent psychopathology, and in relation to their role in aetiology.FundingWellcome Trust (References: 104036/Z/14/Z and 220857/Z/20/Z) and the Medical Research Council (MRC, Reference: MC_PC_17209).
| S-EPMC8608869 | biostudies-literature
Project description:BackgroundWhile identifying risk factors for adolescent depression is critical for early prevention and intervention, most studies have sought to understand the role of isolated factors rather than across a broad set of factors. Here, we sought to examine multi-level factors that maximize the prediction of depression symptoms in US children participating in the Adolescent Brain and Cognitive Development (ABCD) study.MethodsA total of 7,995 participants from ABCD (version 3.0 release) provided complete data at baseline and 1-year follow-up data. Depression symptoms were measured with the Child Behavior Checklist. Predictive features included child demographic, environmental, and structural and resting-state fMRI variables, parental depression history and demographic characteristics. We used linear (elastic net regression, EN) and non-linear (gradient-boosted trees, GBT) predictive models to identify which set of features maximized prediction of depression symptoms at baseline and, separately, at 1-year follow-up.ResultsBoth linear and non-linear models achieved comparable results for predicting baseline (EN: MAE = 3.757; R2 = 0.156; GBT: MAE = 3.761; R2 = 0.147) and 1-year follow-up (EN: MAE = 4.255; R2 = 0.103; GBT: MAE = 4.262; R2 = 0.089) depression. Parental history of depression, greater family conflict, and shorter child sleep duration were among the top predictors of concurrent and future child depression symptoms across both models. Although resting-state fMRI features were relatively weaker predictors, functional connectivity of the caudate was consistently the strongest neural feature associated with depression symptoms at both timepoints.ConclusionsConsistent with prior research, parental mental health, family environment, and child sleep quality are important risk factors for youth depression. Functional connectivity of the caudate is a relatively weaker predictor of depression symptoms but may represent a biomarker for depression risk.
| S-EPMC9489813 | biostudies-literature
Project description:The prevalence of obesity in children and adolescents worldwide has quadrupled since 1975 and is a key predictor of obesity later in life. Previous work has consistently observed relationships between macroscale measures of reward-related brain regions (e.g., the nucleus accumbens [NAcc]) and unhealthy eating behaviors and outcomes; however, the mechanisms underlying these associations remain unclear. Recent work has highlighted a potential role of neuroinflammation in the NAcc in animal models of diet-induced obesity. Here, we leverage a diffusion MRI technique, restriction spectrum imaging, to probe the microstructure (cellular density) of subcortical brain regions. More specifically, we test the hypothesis that the cell density of reward-related regions is associated with obesity-related metrics and early weight gain. In a large cohort of nine- and ten-year-olds enrolled in the Adolescent Brain Cognitive Development (ABCD) study, we demonstrate that cellular density in the NAcc is related to individual differences in waist circumference at baseline and is predictive of increases in waist circumference after 1 y. These findings suggest a neurobiological mechanism for pediatric obesity consistent with rodent work showing that high saturated fat diets increase gliosis and neuroinflammation in reward-related brain regions, which in turn lead to further unhealthy eating and obesity.
| S-EPMC7604478 | biostudies-literature
Project description:Altered Gene Expression in Antipsychotic Induced Weight Gain
| PRJEB31532 | ENA
Project description:Excessive gestational weight gain (EGWG) places women at increased risk for complications during pregnancy and also increases the likelihood that they will remain overweight after pregnancy. The Institute of Medicine (IOM) has recommended weight gain guidelines based on pre-pregnancy body mass index (BMI), but evidence-based strategies to achieve these goals are limited.This review discusses factors associated with EGWG with the goal of identifying targets for future intervention.A search was performed using the PubMed database to identify all English-language papers published between 1995 and 2014 related to excessive weight gain in pregnancy. Papers were grouped by theme: preconception BMI, sociodemographics, diet and exercise, psychosocial characteristics, and type of prenatal care.Studies found that women who were overweight or obese at the time of conception were at higher risk of EGWG and that increased physical activity protected against EGWG. Studies on diet and sociodemographic characteristics were inconclusive. Psychological factors, specifically accurate perceptions of BMI, also appear to play a role in EGWG. Limited studies on methods of prenatal care delivery did not show improvement of weight parameters with group compared to one-on-one visits.Pre-pregnancy BMI is most strongly associated with EGWG, indicating that healthy weight habits throughout adult life may be especially important in periods of expected weight change, such as pregnancy. To decrease EGWG, providers should focus on improving pre-conception BMI through appropriate counseling on healthy eating and increased physical activity as well as encouraging pregnant women to continue moderate exercise during pregnancy when appropriate.
| S-EPMC4756783 | biostudies-other
Project description:The mechanisms behind weight gain following deep brain stimulation (DBS) surgery seem to be multifactorial and suspected depending on the target, either the subthalamic nucleus (STN) or the globus pallidus internus (GPi). Decreased energy expenditure following motor improvement and behavioral and/or metabolic changes are possible explanations. Focusing on GPi target, our objective was to analyze correlations between changes in brain metabolism (measured with PET) and weight gain following GPi-DBS in patients with Parkinson's disease (PD). Body mass index was calculated and brain activity prospectively measured using 2-deoxy-2[18F]fluoro-D-glucose PET four months before and four months after the start of GPi-DBS in 19 PD patients. Dopaminergic medication was included in the analysis to control for its possible influence on brain metabolism. Body mass index increased significantly by 0.66 ± 1.3 kg/m2 (p = 0.040). There were correlations between weight gain and changes in brain metabolism in premotor areas, including the left and right superior gyri (Brodmann area, BA 6), left superior gyrus (BA 8), the dorsolateral prefrontal cortex (right middle gyrus, BAs 9 and 46), and the left and right somatosensory association cortices (BA 7). However, we found no correlation between weight gain and metabolic changes in limbic and associative areas. Additionally, there was a trend toward a correlation between reduced dyskinesia and weight gain (r = 0.428, p = 0.067). These findings suggest that, unlike STN-DBS, motor improvement is the major contributing factor for weight gain following GPi-DBS PD, confirming the motor selectivity of this target.
| S-EPMC4829218 | biostudies-other
Project description:ObjectivesTo characterize the rapid weight gain (RWG) phenotype associated with the onset of childhood narcolepsy and to determine whether it could constitute a marker of severity of the disease.MethodsRWG was defined using the BMI z-score slope reported to one year (>0.67 SD) from symptom onset to disease diagnosis. We compared the clinical, metabolic, and sleep characteristics between patients with or without RWG at diagnosis. Pharmacological management, anthropometric, and clinical progression were also evaluated during the follow-up.ResultsA total of 84 de novo narcoleptic pediatric patients were included; their median age at diagnosis was 12.0 years; 59.5% boys, 90.5% cataplexy, and 98.7% HLA-DQB1*06:02, 57% had RWG profile. RWG patients were younger at diagnosis than non-RWG patients, despite a shorter diagnostic delay. They had a higher BMI z-score and a higher prevalence of obesity at diagnosis, but not at symptom onset, and higher adapted Epworth Sleepiness Scale and Insomnia Severity Index scores than non-RWG patients. No differences on nocturnal polysomnography and multiple sleep latency tests were found between groups at disease diagnosis. After a median follow-up of 5 years, RWG patients still had a higher BMI z-score and a higher prevalence of obesity despite benefiting from the same therapeutic management and displaying improvement in sleepiness and school difficulties.ConclusionsNarcoleptic RWG patients were younger, sleepier, and the prevalence of obesity was higher at diagnosis despite a shorter diagnostic delay than that of non-RWG patients. These patients had also a higher risk of developing a long-term obesity, despite a positive progression of their narcoleptic symptoms. RGW could then represent a maker of a more severe phenotype of childhood narcolepsy, which should inspire a prompt and more offensive management to prevent obesity and its complications.
| S-EPMC9062543 | biostudies-literature
Project description:Post-diagnosis weight gain in breast cancer patients has been associated with increased cancer recurrence and mortality. Our study was designed to identify risk factors for this weight gain and create a predictive model to identify a high-risk population for targeted interventions.Chart review was conducted on 459 breast cancer patients from Northwestern Robert H. Lurie Cancer Centre to obtain weights and body mass indices (BMIs) over an 18-month period from diagnosis. We also recorded tumour characteristics, demographics, clinical factors, and treatment regimens. Blood samples were genotyped for 14 single-nucleotide polymorphisms (SNPs) in fat mass and obesity-associated protein (FTO) and adiponectin pathway genes (ADIPOQ and ADIPOR1).In all, 56% of patients had >0.5 kg m(-2) increase in BMI from diagnosis to 18 months, with average BMI and weight gain of 1.9 kg m(-2) and 5.1 kg, respectively. Our best predictive model was a primarily SNP-based model incorporating all 14 FTO and adiponectin pathway SNPs studied, their epistatic interactions, and age and BMI at diagnosis, with area under receiver operating characteristic curve of 0.85 for 18-month weight gain.We created a powerful risk prediction model that can identify breast cancer patients at high risk for weight gain.
| S-EPMC3749587 | biostudies-literature