PACE: a Novel Eating Behavior Phenotype to Assess Risk for Obesity in Middle Childhood.

BACKGROUND: Behavioral phenotypes that predict future weight gain are needed to identify children susceptible to obesity. OBJECTIVES: This prospective study developed an eating behavior risk score to predict change in adiposity over 1 y in children. METHODS: Data from 6 baseline visits (Time 1, T1) and a 1-y follow-up visit (Time 2, T2) were collected from 76, 7- to 8-y-old healthy children recruited from Central Pennsylvania. At T1, children had body mass index (BMI) percentiles <90 and were classified with either high (n = 33; maternal BMI ≥30 kg/m2) or low (n = 43; maternal BMI ≤25 kg/m2) familial risk for obesity. Appetitive traits and eating behaviors were assessed at T1. Adiposity was measured at T1 and T2 using dual-energy x-ray absorptiometry, with a main outcome of fat mass index (FMI; total body fat mass divided by height in meters squared). Hierarchical linear regressions determined which eating measures improved prediction of T2 FMI after adjustment for covariates in the baseline model (T1 FMI, sex, income, familial risk, and Tanner stage). RESULTS: Four eating measures-Portion susceptibility, Appetitive traits, loss of control eating, and eating rate-were combined into a standardized summary score called PACE. PACE improved the baseline model to predict 80% variance in T2 FMI. PACE was positively associated with the increase in FMI in children from T1 to T2, independent of familial risk (r = 0.58, P < 0.001). Although PACE was higher in girls than boys (P < 0.05), it did not differ by familial risk, income, or education. CONCLUSIONS: PACE represents a cumulative eating behavior risk score that predicts adiposity gain over 1 y in middle childhood. If PACE similarly predicts adiposity gain in a cohort with greater racial and socioeconomic diversity, it will inform the development of interventions to prevent obesity. This trial was registered at clinicaltrials.gov as NCT03341247.

The Cerebellar Response to Visual Portion Size Cues Is Associated with the Portion Size Effect in Children.

The neural mechanisms underlying susceptibility to eating more in response to large portions (i.e., the portion size effect) remain unclear. Thus, the present study examined how neural responses to portion size relate to changes in weight and energy consumed as portions increase. Associations were examined across brain regions traditionally implicated in appetite control (i.e., an appetitive network) as well as the cerebellum, which has recently been implicated in appetite-related processes. Children without obesity (i.e., BMI-for-age-and-sex percentile < 90; N = 63; 55% female) viewed images of larger and smaller portions of food during fMRI and, in separate sessions, ate four meals that varied in portion size. Individual-level linear and quadratic associations between intake (kcal, grams) and portion size (i.e., portion size slopes) were estimated. The response to portion size in cerebellar lobules IV-VI was associated with the quadratic portion size slope estimated from gram intake; a greater response to images depicting smaller compared to larger portions was associated with steeper increases in intake with increasing portion sizes. Within the appetitive network, neural responses were not associated with portion size slopes. A decreased cerebellar response to larger amounts of food may increase children's susceptibility to overeating when excessively large portions are served.

Does 'portion size' matter? Brain responses to food and non-food cues presented in varying amounts.

Larger portions of food elicit greater intake than smaller portions of food, particularly when foods are high in energy density (kcal/g; ED). The neural mechanisms underlying this effect remain unclear. The present study used fMRI to assess brain activation to food (higher-ED, lower-ED) and non-food (office supplies) images presented in larger and smaller (i.e., age-appropriate) amounts in 61, 7-8-year-olds (29 male, 32 female) without obesity. Larger amounts of food increased activation in bilateral visual and right parahippocampal areas compared to smaller amounts; greater activation to food amount (larger > smaller) in this cluster was associated with smaller increases in food intake as portions increased. Activation to amount (larger > smaller) was stronger for food than office supplies in primary and secondary visual areas, but, for office supplies only, extended into bilateral parahippocampus, inferior parietal cortex, and additional visual areas (e.g., V7). Activation was greater for higher-vs. lower-ED food images in ventromedial prefrontal cortex for both larger and smaller amounts of food; however, this activation extended into left lateral orbital frontal cortex for smaller amounts only. Activation to food cues did not differ by familial risk for obesity. These results highlight potentially distinct neural pathways for encoding food energy content and quantity.

Parameter Space and Potential for Biomarker Development in 25 Years of fMRI Drug Cue Reactivity: A Systematic Review.

Importance: In the last 25 years, functional magnetic resonance imaging drug cue reactivity (FDCR) studies have characterized some core aspects in the neurobiology of drug addiction. However, no FDCR-derived biomarkers have been approved for treatment development or clinical adoption. Traversing this translational gap requires a systematic assessment of the FDCR literature evidence, its heterogeneity, and an evaluation of possible clinical uses of FDCR-derived biomarkers. Objective: To summarize the state of the field of FDCR, assess their potential for biomarker development, and outline a clear process for biomarker qualification to guide future research and validation efforts. Evidence Review: The PubMed and Medline databases were searched for every original FDCR investigation published from database inception until December 2022. Collected data covered study design, participant characteristics, FDCR task design, and whether each study provided evidence that might potentially help develop susceptibility, diagnostic, response, prognostic, predictive, or severity biomarkers for 1 or more addictive disorders. Findings: There were 415 FDCR studies published between 1998 and 2022. Most focused on nicotine (122 [29.6%]), alcohol (120 [29.2%]), or cocaine (46 [11.1%]), and most used visual cues (354 [85.3%]). Together, these studies recruited 19 311 participants, including 13 812 individuals with past or current substance use disorders. Most studies could potentially support biomarker development, including diagnostic (143 [32.7%]), treatment response (141 [32.3%]), severity (84 [19.2%]), prognostic (30 [6.9%]), predictive (25 [5.7%]), monitoring (12 [2.7%]), and susceptibility (2 [0.5%]) biomarkers. A total of 155 interventional studies used FDCR, mostly to investigate pharmacological (67 [43.2%]) or cognitive/behavioral (51 [32.9%]) interventions; 141 studies used FDCR as a response measure, of which 125 (88.7%) reported significant interventional FDCR alterations; and 25 studies used FDCR as an intervention outcome predictor, with 24 (96%) finding significant associations between FDCR markers and treatment outcomes. Conclusions and Relevance: Based on this systematic review and the proposed biomarker development framework, there is a pathway for the development and regulatory qualification of FDCR-based biomarkers of addiction and recovery. Further validation could support the use of FDCR-derived measures, potentially accelerating treatment development and improving diagnostic, prognostic, and predictive clinical judgments.