Role of Genetic Variation in the Cannabinoid Type 1 Receptor Gene (
            <i>CNR1</i>
            ) in the Pathophysiology of Human Obesity

Schleinitz, Dorit; Carmienke, Solveig; Böttcher, Yvonne; Tönjes, Anke; Berndt, Janin; Klöting, Nora; Enigk, Beate; Müller, I.; Dietrich, Katharina; Breitfeld, Jana; Scholz, Gerhard H.; Engeli, Stefan; Stümvoll, Michael; Blüher, Matthias; Kovacs, Peter

doi:10.2217/pgs.10.42

Cited by 16 publications

(11 citation statements)

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The rationale for including the case-control design in this comparison is that, often in clinical practice, diseases such as hypertension and obesity are defined by setting a threshold for quantitative traits [Chobanian et al, 2003; Expert Committee on the Diagnosis and Classification of Diabetes Mellitus, 2003]. Despite the potential gain by using a quantitative trait, many case-control studies of this nature have been performed [Niu et al, 2010; Yamada et al, 2006; Lin et al, 2010; Schleinitz et al, 2010]. Performance of different designs is evaluated as NCP ratio, using the cross-sectional design as a reference.…”

Section: Discussionmentioning

confidence: 99%

Using extreme phenotype sampling to identify the rare causal variants of quantitative traits in association studies

Li¹,

Lewinger²,

Gauderman³

et al. 2011

Genetic Epidemiology

124

118

View full text Add to dashboard Cite

Variants identified in recent genome-wide association studies based on the common-disease common-variant hypothesis are far from fully explaining the hereditability of complex traits. Rare variants may, in part, explain some of the missing hereditability. Here, we explored the advantage of the extreme phenotype sampling in rare-variant analysis and refined this design framework for future large-scale association studies on quantitative traits. We first proposed a power calculation approach for a likelihood-based analysis method. We then used this approach to demonstrate the potential advantages of extreme phenotype sampling for rare variants. Next, we discussed how this design can influence future sequencing-based association studies from a cost-efficiency (with the phenotyping cost included) perspective. Moreover, we discussed the potential of a two-stage design with the extreme sample as the first stage and the remaining nonextreme subjects as the second stage. We demonstrated that this two-stage design is a cost-efficient alternative to the one-stage cross-sectional design or traditional two-stage design. We then discussed the analysis strategies for this extreme two-stage design and proposed a corresponding design optimization procedure. To address many practical concerns, for example measurement error or phenotypic heterogeneity at the very extremes, we examined an approach in which individuals with very extreme phenotypes are discarded. We demonstrated that even with a substantial proportion of these extreme individuals discarded, an extreme-based sampling can still be more efficient. Finally, we expanded the current analysis and design framework to accommodate the CMC approach where multiple rare-variants in the same gene region are analyzed jointly.

show abstract

Section: Discussionmentioning

confidence: 99%

Using extreme phenotype sampling to identify the rare causal variants of quantitative traits in association studies

Li¹,

Lewinger²,

Gauderman³

et al. 2011

Genetic Epidemiology

124

118

View full text Add to dashboard Cite

show abstract

“…This could explain the association of obesity with genes involved with DA neurotransmission, such as the DRD2 Taq I A1 allele, which has been associated with addiction (4). Similarly, there are genes at the intersection between reward and homeostatic pathways, like the cannabinoid receptor 1 ( CNR1 ) gene, variations in which have been associated with BMI and obesity risk by most studies (5), as well as with addiction (6). And, let us also remember in this context that endogenous opioids are involved in hedonic responses to food and to drugs and that the functional A118G polymorphism in the μ-opioid receptor gene ( OPRM1 ) has been associated with vulnerability for binge-eating disorders (7) and alcoholism (8).…”

Section: Genetic Overlapsmentioning

confidence: 99%

The Addictive Dimensionality of Obesity

Volkow

Wang

Tomasi

et al. 2013

Biological Psychiatry

321

236

View full text Add to dashboard Cite

Our brains are hardwired to respond and seek immediate rewards. Thus, it is not surprising that many people overeat, which in some can result in obesity, whereas others take drugs, which in some can result in addiction. Though food intake and body weight are under homeostatic regulation, when highly palatable food is available, the ability to resist the urge to eat hinges on self-control. There is no homeostatic regulator to check the intake of drugs (including alcohol); thus, regulation of drug consumption is mostly driven by self-control or unwanted effects (i.e., sedation for alcohol). Disruption in both the neurobiological processes that underlie sensitivity to reward and those that underlie inhibitory control can lead to compulsive food intake in some individuals and compulsive drug intake in others. There is increasing evidence that disruption of energy homeostasis can affect the reward circuitry and that overconsumption of rewarding food can lead to changes in the reward circuitry that result in compulsive food intake akin to the phenotype seen with addiction. Addiction research has produced new evidence that hints at significant commonalities between the neural substrates underlying the disease of addiction and at least some forms of obesity. This recognition has spurred a healthy debate to try and ascertain the extent to which these complex and dimensional disorders overlap and whether or not a deeper understanding of the crosstalk between the homeostatic and reward systems will usher in unique opportunities for prevention and treatment of both obesity and drug addiction.

show abstract

“…Recently, the Sorbs have been successfully utilized in candidate gene and genome-wide association studies of height and metabolic syndrome traits. [13][14][15][16][17] Although these studies are suggestive of the power of using the Sorbs for mapping, they do not make clear the extent to which Sorbs are a genetic isolate.…”

Section: Introductionmentioning

confidence: 96%

Genetic variation in the Sorbs of eastern Germany in the context of broader European genetic diversity

et al. 2011

Self Cite

View full text Add to dashboard Cite

Population isolates have long been of interest to genetic epidemiologists because of their potential to increase power to detect disease-causing genetic variants. The Sorbs of Germany are considered as cultural and linguistic isolates and have recently been the focus of disease association mapping efforts. They are thought to have settled in their present location in eastern Germany after a westward migration from a largely Slavic-speaking territory during the Middle Ages. To examine Sorbian genetic diversity within the context of other European populations, we analyzed genotype data for over 30 000 autosomal single-nucleotide polymorphisms from over 200 Sorbs individuals. We compare the Sorbs with other European individuals, including samples from population isolates. Despite their geographical proximity to German speakers, the Sorbs showed greatest genetic similarity to Polish and Czech individuals, consistent with the linguistic proximity of Sorbian to other West Slavic languages. The Sorbs also showed evidence of subtle levels of genetic isolation in comparison with samples from non-isolated European populations. The level of genetic isolation was less than that observed for the Sardinians and French Basque, who were clear outliers on multiple measures of isolation. The finding of the Sorbs as only a minor genetic isolate demonstrates the need to genetically characterize putative population isolates, as they possess a wide range of levels of isolation because of their different demographic histories.

show abstract

Role of Genetic Variation in the Cannabinoid Type 1 Receptor Gene ( CNR1 ) in the Pathophysiology of Human Obesity

Abstract: The data suggest that common genetic variation in the CNR1 gene does not influence mRNA expression in adipose tissue nor does it play a significant role in the pathophysiology of obesity in German and Sorbian populations.

Cited by 16 publications

References 36 publications

Using extreme phenotype sampling to identify the rare causal variants of quantitative traits in association studies

Using extreme phenotype sampling to identify the rare causal variants of quantitative traits in association studies

The Addictive Dimensionality of Obesity

Genetic variation in the Sorbs of eastern Germany in the context of broader European genetic diversity

Contact Info

Product

Resources

About