Rare cases of monogenic obesity, which may respond to specific therapeutics, can remain undetected in populations in which polygenic obesity is prevalent. This study examined rare DNA variation in established monogenic obesity genes within a community using whole-exome sequence data from 6803 longitudinally studied individuals.
Exome data across 15 monogenic obesity genes were analyzed for nonsynonymous variants observed in any child with a maximum BMI z score > 2 (N = 279) but not observed in a child with a maximum BMI z score ≤ 0 (n = 1542) or that occurred in adults in the top 5th percentile of BMI (n = 263) but not in adults below the median BMI (n = 2629). Variants were then functionally analyzed using luciferase assays.
The comparisons between cases of obesity and controls identified eight missense variants in six genes: DYRK1B, KSR2, MC4R, NTRK2, PCSK1, and SIM1. Among these, MC4R p.A303P and p.R165G were previously shown to impair MC4R function. Functional analyses of the remaining six variants suggest that KSR2 p.I402F and p.T193I and NTRK2 p.S249Y alter protein function.
In addition to MC4R, rare missense variants in KSR2 and NTRK2 may potentially explain the severe obesity observed for the carriers.
Bariatric surgery reduces sweet-liking, but mechanisms remain unclear. We examined related brain responses.
A total of 24 nondiabetic bariatric surgery and 21 control participants with normal weight to overweight were recruited for an observational controlled cohort study. They underwent sucrose taste testing outside the scanner followed by stimulation with 0.40M and 0.10M sucrose compared with water during functional magnetic resonance imaging. A total of 21 bariatric participants repeated these procedures after surgery.
Perceived sweet intensity was not different among the control, presurgery, or postsurgery groups. Bariatric participants' preferred sweet concentration decreased after surgery (0.52M to 0.29M; p = 0.008). Brain reward system (ventral tegmental area, ventral striatum, and orbitofrontal cortex) region of interest analysis showed that 0.40M sucrose activation (but not 0.10M) decreased after surgery. Sensory region (primary somatosensory and primary taste cortex) 0.40M sucrose activation was unchanged by surgery and did not differ between control and bariatric participants. Primary taste cortex activation to 0.10M sucrose solution was greater in postsurgical bariatric participants compared with control participants.
Bariatric surgery reduces the reward system response to sweet taste in women with obesity without affecting activity in sensory regions, which is consistent with reduced drive to consume sweet foods.
Epicardial adipose tissue (EAT) quantity is associated with poor cardiovascular outcomes. However, the quality of EAT may be of incremental prognostic value. Cardiac magnetic resonance (CMR) is the gold standard for tissue characterization but has never been applied for EAT quality assessment. We aimed to investigate EAT quality measured on CMR T1 mapping as a predictor of poor outcomes in an all-comer cohort.
We investigated the association of EAT area and EAT T1 times (EAT-T1) with a composite endpoint of nonfatal myocardial infarction, heart failure hospitalization, and all-cause death.
A total of 966 participants were included (47.2% female; mean age: 58.4 years) in this prospective observational CMR registry. Mean EAT area and EAT-T1 were 7.3 cm2 and 268 ms, respectively. On linear regression, EAT-T1 was not associated with markers of obesity, dyslipidemia, or comorbidities such as diabetes (p > 0.05 for all). During a follow-up of 57.7 months, a total of 280 (29.0%) events occurred. EAT-T1 was independently associated (adjusted hazard ratio per SD: 1.202; 95% CI: 1.022–1.413; p = 0.026) with the composite endpoint when adjusted for established clinical risk.
EAT quality (as assessed via CMR T1 times), but not EAT quantity, is independently associated with a composite endpoint of nonfatal myocardial infarction, heart failure hospitalization, and all-cause death.
The objective of this study was to project the cost-effectiveness of implementing the Healthy Weight Clinic (HWC), a primary care-based intervention for 6- to 12-year-old children with overweight or obesity, at federally qualified health centers (FQHCs) nationally.
We estimated intervention costs from a health care sector and societal perspective and used BMI change estimates from the HWC trial. Our microsimulation of national HWC implementation among all FQHCs from 2023 to 2032 estimated cost per child and per quality-adjusted life year (QALY) gained and projected impact on obesity prevalence by race and ethnicity. Probabilistic sensitivity analyses assessed uncertainty around estimates.
National implementation is projected to reach 888,000 children over 10 years, with a mean intervention cost of $456 (95% uncertainty interval [UI]: $409–$506) per child to the health care sector and $211 (95% UI: $175–$251) to families (e.g., time participating). Assuming effect maintenance, national implementation could result in 2070 (95% UI: 859–3220) QALYs gained and save $14.6 million (95% UI: $5.6–$23.5 million) in health care costs over 10 years, yielding a net cost of $278,000 (95% CI: $177,000–$679,000) per QALY gained. We project greater reductions in obesity prevalence among Hispanic/Latino and Black versus White populations.
The HWC is relatively low-cost per child and projected to reduce obesity disparities if implemented nationally in FQHCs.
The increasing prevalence of and inequities in childhood obesity demand improved access to effective treatment. The SmartMoves curriculum used in Bright Bodies, a proven-effective, intensive health behavior and lifestyle treatment (IHBLT), was disseminated to ≥30 US sites from 2003 to 2018. We aimed to identify barriers to and facilitators of IHBLT implementation/sustainment.
We surveyed and interviewed key informants about experiences acquiring/implementing SmartMoves. In parallel, we analyzed and then integrated survey findings and themes from interviews using the constant comparative method.
Participants from 16 sites (53%) completed surveys, and 12 participants at 10 sites completed interviews. The 11 sites (63%) that implemented SmartMoves varied in both use of training opportunities/materials and fidelity to program components. In interviews, demand for obesity programming, organizational priorities, and partnerships facilitated implementation. Seven sites discontinued SmartMoves prior to the COVID-19 pandemic. Funding insecurity and insufficient staffing emerged as dominant barriers to implementation/sustainment discussed by all interviewees, and some also noted participants' competing demands and the program's fit with population as challenges.
System- and organizational-level barriers impeded sustainment of an evidence-based IHBLT program. Adequate funding could enable sufficient staffing and training to promote fidelity to the intervention's core functions and adaptation to fit local populations/context.
The objective of this study was to explore how dietary macronutrient composition influences postprandial appetite hormone responses and subsequent energy intake.
A total of 20 adults (mean [SEM], age 30 [1] years, BMI 27.8 [1.3] kg/m2, n = 8 with normal weight, n = 6 with overweight, n = 6 with obesity) consumed a low-fat (LF) diet (10% fat, 75% carbohydrate) and a low-carbohydrate (LC) diet (10% carbohydrate, 75% fat) for 2 weeks each in an inpatient randomized crossover design. At the end of each diet, participants consumed isocaloric macronutrient-representative breakfast test meals, and 6-h postprandial responses were measured. Ad libitum energy intake was measured for the rest of the day.
The LC meal resulted in greater mean postprandial plasma active glucagon-like peptide-1 (GLP-1; LC: 6.44 [0.78] pg/mL, LF: 2.46 [0.26] pg/mL; p < 0.0001), total glucose-dependent insulinotropic polypeptide (GIP; LC: 578 [60] pg/mL, LF: 319 [37] pg/mL; p = 0.0004), and peptide YY (PYY; LC: 65.6 [5.6] pg/mL, LF: 50.7 [3.8] pg/mL; p = 0.02), whereas total ghrelin (LC: 184 [25] pg/mL, LF: 261 [47] pg/mL; p = 0.0009), active ghrelin (LC: 91 [9] pg/mL, LF: 232 [28] pg/mL; p < 0.0001), and leptin (LC: 26.9 [6.5] ng/mL, LF: 35.2 [7.5] ng/mL; p = 0.01) were lower compared with LF. Participants ate more during LC at lunch (244 [85] kcal; p = 0.01) and dinner (193 [86] kcal; p = 0.04), increasing total subsequent energy intake for the day compared with LF (551 [103] kcal; p < 0.0001).
In the short term, endogenous gut-derived appetite hormones do not necessarily determine ad libitum energy intake.
Owing to the global obesity epidemic, understanding the regulatory mechanisms of glucose and lipid metabolism has become increasingly important. The dopaminergic system, including dopamine, dopamine receptors, dopamine transporters, and other components, is involved in numerous physiological and pathological processes. However, the mechanism of action of the dopaminergic system in glucose and lipid metabolism is poorly understood. In this review, we examine the role of the dopaminergic system in glucose and lipid metabolism.
The dopaminergic system regulates glucose and lipid metabolism through several mechanisms. It regulates various activities at the central level, including appetite control and decision-making, which contribute to regulating body weight and energy metabolism. In the pituitary gland, dopamine inhibits prolactin production and promotes insulin secretion through dopamine receptor 2. Furthermore, it can influence various physiological components in the peripheral system, such as pancreatic β cells, glucagon-like peptide-1, adipocytes, hepatocytes, and muscle, by regulating insulin and glucagon secretion, glucose uptake and use, and fatty acid metabolism.
The role of dopamine in regulating glucose and lipid metabolism has significant implications for the physiology and pathogenesis of disease. The potential therapeutic value of dopamine lies in its effects on metabolic disorders.
The objective of this study was to estimate the effects of trimester-specific gestational weight gain (GWG) on small and large (compared with appropriate) for gestational age (i.e., SGA, LGA, and AGA) by prepregnancy BMI classifications.
We conducted a cohort study of pregnancies in a national network of community health care organizations, stratifying by prepregnancy BMI (n = 20,676 with normal weight; 19,156 with overweight; 11,647 with obesity class I; 5124 with obesity class II; and 3197 with obesity class III). SGA and LGA (vs. AGA) were modeled as a function of trimester 1, 2, or 3 GWG rate, previous trimester(s) GWG rate, and maternal characteristics using modified Poisson regression.
GWG rates ranged from weight loss to substantial gains. GWG-LGA associations were strongest in trimester 1 (risk ratio [RR] range for 10th vs. 50th percentile GWG, across BMI categories: 0.60–0.73). GWG-SGA associations were strongest in lower BMI categories and in trimester 2; RRs were 1.62, 1.40, and 1.17 for prepregnancy normal weight, obesity class I, and obesity class III, respectively, with curvilinear associations for class II and III.
Among people with prepregnancy obesity class II or III, GWG rate is associated with higher LGA risk in a dose-dependent manner, including understudied ranges of weight loss, but with weak associations with SGA.
The American Academy of Pediatrics recommends that pediatric practices help families make lifestyle changes to improve BMI, but provider time and access to treatment are limited. This study compared the effectiveness of two pediatric practice-based referral interventions in reducing BMI.
In this cluster-randomized clinical trial, 20 pediatric primary care practices were randomized to telephonic coaching (Fitline Coaching) or mailed workbook (Fitline Workbook). Parents and their 8- to 12-year-old children with BMI ≥ 85th percentile completed assessments at baseline and at 6 and 12 months post baseline. Primary outcomes were 12-month BMI percentile and z score.
A total of 501 children and their parents received Fitline Coaching (n = 243) or Fitline Workbook (n = 258); 26.8% had overweight, 55.4% had obesity, and 17.8% had severe obesity. Mean (SD) age was 10.5 (1.4), and 47.5% were female. BMI percentile improved in both groups; 12-month decline in continuous BMI z score was not statistically significant in either group. However, 20.8% of telephonic coaching participants and 12.4% of workbook participants achieved a clinically significant reduction of at least 0.25 in BMI z score, a significant between-group difference (p = 0.0415).
Both low-intensity interventions were acceptable and produced modest improvements in BMI percentile. One in five children in the telephonic coaching condition achieved clinically meaningful BMI z score improvements. However, more research is needed before such a program could be recommended for pediatric primary care practice.
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