All participants gave written consent and experimental procedures were approved by the institutional review board (IRB # 201204036 Title: ‘Mapping the Human Connectome: Structure, Function, and Heritability’). Structural MRI scans from both twin siblings were available for n=86 identical and n=83 fraternal twin pairs. ![]() The study population was composed of non-twin siblings (n=447), monozygotic (identical) twins (n=206) and dizygotic (fraternal) twins (n=222) from n=380 families. ![]() For additional information on eligibility criteria of the original study, we refer to previously published detailed descriptions 21, 22. In a second step, we estimated heritability of BMI and of predefined brain regions that we found to be associated with BMI, by using available twin data only.įor this study, data were drawn from the publicly available Human Connectome Project (HCP) database (i.e., S500 and S900 data releases that included a total of n=875 healthy young to middle-aged adults with structural MRI (i.e. In a first step, we investigated associations between BMI and regional GMV in a sample of 875 healthy young adults, who were non-twin siblings, dizygotic or monozygotic twin pairs. We utilized structural neuroimaging data from the Human Connectome Project, a large scale neuroimaging study with open access data that investigates human brain networks and behavioral correlates under consideration of genetic and environmental influences 21. BMI) and the heritability of obesity-associated structural brain alterations, hypothesizing high degrees of heritability – particularly for brain regions that form part in dopaminergic reward pathways. In this study, we aimed to investigate associations between regional GMV, body weight (i.e. Previous twin studies have shown varying degrees of estimated heritability for regional brain volume, thus indicating differing susceptibilities with respect to genetic and environmental influences 20. Twin studies provide a powerful approach for heritability analyses of complex traits, such as obesity, by comparing monozygotic and dizygotic twins. It is possible that at least some regional brain volume differences reflect central endophenotypes leading to unhealthy eating and excess adiposity. Given evidence of volumetric brain differences and genetic influences, an important question is the degree to which obesity-related structural brain differences are heritable. the Taq1A A1 allele) and of the μ-opioid receptor (OPRM1) to obesity, binge eating disorder and addictive behavior in general 18, 19. In addition, evidence for a genetically determined behavioral phenotype with altered reward sensitivity (thus favoring unhealthy eating patterns) is provided by multiple studies that have linked genetic variants of the dopamine receptor D2 (DRD2) gene (i.e. Certain genetic variants are common and carry significant risk of increased adiposity for example, variations in the FTO gene (i.e., fat mass and obesity associated protein), where those homozygous for the risk allele have an increased risk for obesity (HR 1.67), on average weighing 3–4 kg more than non-carriers 17. Obesity and BMI have been shown to be highly heritable, generally on a polygenic basis 15, 16. Similar results were reported by Yokum et al., linking prefrontal GMV with future weight gain in a sample of young women 14 however, reported brain regions of these studies differed with respect to the exact locations. insular and prefrontal cortex) was reported in subjects with high risk for obesity, possibly indicating that structural brain differences are predisposing to obesity 13. Intriguingly, reduced gray matter volume (GMV) of similar brain regions (i.e. In addition, a number of neuroimaging studies have found obesity to be associated with functional and structural alterations of the brain including prefrontal cortical, insular and striatal regions critically involved in executive functioning, reward processing and interoception 5– 12. ![]() Both animal and human studies have documented dysfunctional dopaminergic central pathways and the effects on reward-related and motivated behavior to be key neurophysiological contributors to the behavioral phenotype leading to obesity 2– 4. Hence, increasing efforts are being made to enhance our understanding of the neurobiological underpinnings that may promote and/or follow unhealthy eating patterns and the development of obesity. As of 2011/2012 70% of the adult US population were estimated to be overweight or obese with a body mass index (BMI) exceeding 25 kg/m 2 1.Īccumulation of excess adipose tissue is generally a result of unhealthy eating patterns and chronically positive energy balance, further promoted by the western “obesogenic” environment, where an abundance of unhealthy energy dense foods is readily available at any time. The rising prevalence of obesity remains unchecked in industrialized societies.
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