Neurobehavioral correlates of obesity are largely heritable

Vainik, Uku; Baker, Travis E.; Dadar, Mahsa; Zeighami, Yashar; Michaud, Andréanne; Alanis, José C. García; Mišić, Bratislav; Collins, D. Louis

doi:10.1073/pnas.1718206115

Cited by 110 publications

(139 citation statements)

References 53 publications

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“…Given that losing weight is a difficult task, the Conscientiousness facets may reflect troubles with adherence to weight loss regimens in people with obesity. The importance of planning and organizing tasks conceptually supports the role that self‐control plays in obesity, which has also been highlighted by research on executive functions and prefrontal cortex . Scarce longitudinal evidence has suggested that obesity could have bidirectional associations with self‐control capabilities, while a Mendelian randomization study suggested that higher education and cognitive ability could cause lower BMI …”

Section: Discussionmentioning

confidence: 99%

“…These weighted NEO PI‐R/3 (a) domain and (b) facet scores were then averaged, yielding either DRS or FRS. We included all NEO PI‐R/3 domains in DRS and all facets in FRS regardless of the magnitude or significance of their respective meta‐analytic weights, as many papers working on polygenic risk scores have shown that the best prediction can generally be achieved when all predictors are included in risk scores, no matter the effect size . The observed BMI was then predicted from the DRS and FRS (all expressed in z scores), controlling for sex, age, age 2 , and education.…”

Section: Methodsmentioning

confidence: 99%

“…The poly‐trait risk score represents as much variance in BMI that can be collectively predicted by the set of traits, be they domains or facets. This approach has already been successfully used in personality research, and it is conceptually very similar to polygenic risk scores widely used in genetics . We expect FRS to explain more variance in BMI than DRS.…”

Section: Introductionmentioning

confidence: 99%

“…This approach has already been successfully used in personality research, [20][21][22] and it is conceptually very similar to polygenic risk scores widely used in genetics. 23,24 We expect FRS to explain more variance in BMI than DRS.…”

Section: Introductionmentioning

confidence: 99%

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Personality‐obesity associations are driven by narrow traits: A meta‐analysis

et al. 2019

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Summary Obesity has inconsistent associations with broad personality domains, possibly because the links pertain to only some facets of these domains. Collating published and unpublished studies (N = 14 848), we meta‐analysed the associations between body mass index (BMI) and Five‐Factor Model personality domains as well as 30 Five‐Factor Model personality facets. At the domain level, BMI had a positive association with Neuroticism and a negative association with Conscientiousness domains. At the facet level, we found associations between BMI and 15 facets from all five personality domains, with only some Neuroticism and Conscientiousness facets among them. Certain personality‐BMI associations were moderated by sample properties, such as proportions of women or participants with obesity; these moderation effects were replicated in the individual‐level analysis. Finally, facet‐based personality “risk” scores accounted for 2.3% of variance in BMI in a separate sample of individuals (N = 3569), 409% more than domain‐based scores. Taken together, personality‐BMI associations are facet specific, and delineating them may help to explain obesity‐related behaviours and inform intervention designs. Preprint and data are available at https://psyarxiv.com/z35vn/.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Personality‐obesity associations are driven by narrow traits: A meta‐analysis

et al. 2019

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“…Obesity is the result of a sustained excessive energy intake (Hall, ), and energy intake is 100% accounted by behaviour (Blundell & Finlayson, ). Furthermore, evidence from genetics and brain imaging suggest that obesity's causes are rooted in the brain (Dagher, ; Vainik et al ., , ; Locke et al ., ). Therefore, individual differences in obesity should at least partly be explained by individual differences in behaviour.…”

Section: Introductionmentioning

confidence: 99%

Uncontrolled eating: a unifying heritable trait linked with obesity, overeating, personality and the brain

Vainik

García‐García

Dagher

2019

Eur J of Neuroscience

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Many eating‐related psychological constructs have been proposed to explain obesity and overeating. However, these constructs, including food addiction, disinhibition, hedonic hunger, emotional eating, binge eating and the like all have similar definitions, emphasizing loss of control over intake. As questionnaires measuring the constructs correlate strongly (r > 0.5) with each other, we propose that these constructs should be reconsidered to be part of a single broad phenotype: uncontrolled eating. Such an approach enables reviewing and meta‐analysing evidence obtained with each individual questionnaire. Here, we describe robust associations between uncontrolled eating, body mass index (BMI), food intake, personality traits and brain systems. Reviewing cross‐sectional and longitudinal data, we show that uncontrolled eating is phenotypically and genetically intertwined with BMI and food intake. We also review evidence on how three psychological constructs are linked with uncontrolled eating: lower cognitive control, higher negative affect and a curvilinear association with reward sensitivity. Uncontrolled eating mediates all three constructs’ associations with BMI and food intake. Finally, we review and meta‐analyse brain systems possibly subserving uncontrolled eating: namely, (i) the dopamine mesolimbic circuit associated with reward sensitivity, (ii) frontal cognitive networks sustaining dietary self‐control and (iii) the hypothalamus‐pituitary‐adrenal axis, amygdala and hippocampus supporting stress reactivity. While there are limits to the explanatory and predictive power of the uncontrolled eating phenotype, we conclude that treating different eating‐related constructs as a single concept, uncontrolled eating, enables drawing robust conclusions on the relationship between food intake and BMI, psychological variables and brain structure and function.

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Association of Body Mass Index and Waist Circumference With Imaging Metrics of Brain Integrity and Functional Connectivity in Children Aged 9 to 10 Years in the US, 2016-2018

et al. 2023

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ImportanceAside from widely known cardiovascular implications, higher weight in children may have negative associations with brain microstructure and neurodevelopment.ObjectiveTo evaluate the association of body mass index (BMI) and waist circumference with imaging metrics that approximate brain health.Design, Setting, and ParticipantsThis cross-sectional study used data from the Adolescent Brain Cognitive Development (ABCD) study to examine the association of BMI and waist circumference with multimodal neuroimaging metrics of brain health in cross-sectional and longitudinal analyses over 2 years. From 2016 to 2018, the multicenter ABCD study recruited more than 11 000 demographically representative children aged 9 to 10 years in the US. Children without any history of neurodevelopmental or psychiatric disorders were included in this study, and a subsample of children who completed 2-year follow-up (34%) was included for longitudinal analysis.ExposuresChildren’s weight, height, waist circumference, age, sex, race and ethnicity, socioeconomic status, handedness, puberty status, and magnetic resonance imaging scanner device were retrieved and included in the analysis.Main Outcomes and MeasuresAssociation of preadolescents’ BMI z scores and waist circumference with neuroimaging indicators of brain health: cortical morphometry, resting-state functional connectivity, and white matter microstructure and cytostructure.ResultsA total of 4576 children (2208 [48.3%] female) at a mean (SD) age of 10.0 years (7.6 months) were included in the baseline cross-sectional analysis. There were 609 (13.3%) Black, 925 (20.2%) Hispanic, and 2565 (56.1%) White participants. Of those, 1567 had complete 2-year clinical and imaging information at a mean (SD) age of 12.0 years (7.7 months). In cross-sectional analyses at both time points, higher BMI and waist circumference were associated with lower microstructural integrity and neurite density, most pronounced in the corpus callosum (fractional anisotropy for BMI and waist circumference at baseline and second year: P &lt; .001; neurite density for BMI at baseline: P &lt; .001; neurite density for waist circumference at baseline: P = .09; neurite density for BMI at second year: P = .002; neurite density for waist circumference at second year: P = .05), reduced functional connectivity in reward- and control-related networks (eg, within the salience network for BMI and waist circumference at baseline and second year: P &lt; .002), and thinner brain cortex (eg, for the right rostral middle frontal for BMI and waist circumference at baseline and second year: P &lt; .001). In longitudinal analysis, higher baseline BMI was most strongly associated with decelerated interval development of the prefrontal cortex (left rostral middle frontal: P = .003) and microstructure and cytostructure of the corpus callosum (fractional anisotropy: P = .01; neurite density: P = .02).Conclusions and RelevanceIn this cross-sectional study, higher BMI and waist circumference among children aged 9 to 10 years were associated with imaging metrics of poorer brain structure and connectivity as well as hindered interval development. Future follow-up data from the ABCD study can reveal long-term neurocognitive implications of excess childhood weight. Imaging metrics that had the strongest association with BMI and waist circumference in this population-level analysis may serve as target biomarkers of brain integrity in future treatment trials of childhood obesity.

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Neurobehavioral correlates of obesity are largely heritable

Cited by 110 publications

References 53 publications

Personality‐obesity associations are driven by narrow traits: A meta‐analysis

Personality‐obesity associations are driven by narrow traits: A meta‐analysis

Uncontrolled eating: a unifying heritable trait linked with obesity, overeating, personality and the brain

Association of Body Mass Index and Waist Circumference With Imaging Metrics of Brain Integrity and Functional Connectivity in Children Aged 9 to 10 Years in the US, 2016-2018

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