Evaluation of the Genetic Association Between Adult Obesity and Neuropsychiatric Disease

Stahel, Priska; Nahmias, Avital; Sud, Shawn; Lee, So Jeong; Pucci, Andrea; Yousseif, Ahmed; Youseff, Alaa; Jackson, Timothy; Urbach, David R.; Okrainec, Allan; Allard, Johane P.; Sockalingam, Sanjeev; Yao, Tony; Barua, Moumita; Jiao, Hong; Mägi, Reedik; Bassett, Anne S.; Paterson, Andrew D.; Dahlman, Ingrid; Batterham, Rachel L.; Dash, Satya

doi:10.2337/db18-1254

Cited by 7 publications

(4 citation statements)

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“…Obesity and NPDs are linked to each other bidirectionally. On one hand, obesity makes a person more vulnerable to anxiety and depression-like behavior and on the other hand presence of any of the NPDs further enhances the risk of obesity in nonobese patients (2)(3)(4).…”

Section: Introductionmentioning

confidence: 99%

Intersections in Neuropsychiatric and Metabolic Disorders: Possible Role of TRPA1 Channels

et al. 2021

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Neuropsychiatric disorders (NPDs) are a huge burden to the patient, their family, and society. NPDs have been greatly associated with cardio-metabolic comorbidities such as obesity, type-2 diabetes mellitus, dysglycaemia, insulin resistance, dyslipidemia, atherosclerosis, and other cardiovascular disorders. Antipsychotics, which are frontline drugs in the treatment of schizophrenia and off-label use in other NPDs, also add to this burden by causing severe metabolic perturbations. Despite decades of research, the mechanism deciphering the link between neuropsychiatric and metabolic disorders is still unclear. In recent years, transient receptor potential Ankyrin 1 (TRPA1) channel has emerged as a potential therapeutic target for modulators. TRPA1 agonists/antagonists have shown efficacy in both neuropsychiatric disorders and appetite regulation and thus provide a crucial link between both. TRPA1 channels are activated by compounds such as cinnamaldehyde, allyl isothiocyanate, allicin and methyl syringate, which are present naturally in food items such as cinnamon, wasabi, mustard, garlic, etc. As these are present in many daily food items, it could also improve patient compliance and reduce the patients’ monetary burden. In this review, we have tried to present evidence of the possible involvement of TRPA1 channels in neuropsychiatric and metabolic disorders and a possible hint towards using TRPA1 modulators to target appetite, lipid metabolism, glucose and insulin homeostasis and inflammation associated with NPDs.

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Section: Introductionmentioning

confidence: 99%

Intersections in Neuropsychiatric and Metabolic Disorders: Possible Role of TRPA1 Channels

et al. 2021

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“…While the 16p11.2 deletion is a well-characterized risk factor for obesity, this implicates the potential role of other NDD CNVs in obesity . The association between NDD CNVs and obesity, including BMI, may be explored further, as studies to date are limited one-off studies of obesity in specific CNV syndromes, with some clinical and molecular reports indicating a need for more systematic, in-depth investigation . As for common risk variants, joint genome-wide association analysis of BMI and an adult-onset NDD, schizophrenia, indicate an overlap of 63 loci (FDR < 0.01), although with variants demonstrating opposite directionality and a negative genetic correlation ( r = −0.11); in another study, risk variants for BMI and schizophrenia were notable for 3-dimensional interaction within dopaminergic neurons .…”

Section: Discussionmentioning

confidence: 99%

Clinical Characterization of Copy Number Variants Associated With Neurodevelopmental Disorders in a Large-scale Multiancestry Biobank

et al. 2022

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IMPORTANCE Past studies identified rare copy number variants (CNVs) as risk factors for neurodevelopmental disorders (NDDs), including autism spectrum disorder and schizophrenia. However, the clinical characterization of NDD CNVs is understudied in population cohorts unselected for neuropsychiatric disorders and in cohorts of diverse ancestry.OBJECTIVE To identify individuals harboring NDD CNVs in a multiancestry biobank and to query their enrichment for select neuropsychiatric disorders as well as association with multiple medical disorders. DESIGN, SETTINGS, AND PARTICIPANTSIn a series of phenotypic enrichment and association analyses, NDD CNVs were clinically characterized among 24 877 participants in the BioMe biobank, an electronic health record-linked biobank derived from the Mount Sinai Health System, New York, New York. Participants were recruited into the biobank since September 2007 across diverse ancestry and medical and neuropsychiatric specialties. For the current analyses, electronic health record data were analyzed from May 2004 through May 2019.MAIN OUTCOMES AND MEASURES NDD CNVs were identified using a consensus of 2 CNV calling algorithms, based on whole-exome sequencing and genotype array data, followed by novel in-silico clinical assessments. RESULTSOf 24 877 participants, 14 586 (58.7%) were female; self-reported ancestry categories included 5965 (24.0%) who were of African ancestry, 7892 (31.7%) who were of European ancestry, and 8536 (34.3%) who were of Hispanic ancestry; and the mean (SD) age was 50.5 (17.3) years. Among 24 877 individuals, the prevalence of 64 NDD CNVs was 2.5% (n = 627), with prevalence varying by locus, corroborating the presence of some relatively highly prevalent NDD CNVs (eg, 15q11.2 deletion/duplication). An aggregate set of NDD CNVs were enriched for congenital disorders (odds ratio, 2.0; 95% CI, 1.1-3.5; P = .01) and major depressive disorder (odds ratio, 1.5; 95% CI, 1.1-2.0; P = .01). In a meta-analysis of medical diagnoses (n = 195 hierarchically clustered diagnostic codes), NDD CNVs were significantly associated with several medical outcomes, including essential hypertension (z score = 3.6; P = 2.8 × 10 −4 ), kidney failure (z score = 3.3; P = 1.1 × 10 −3 ), and obstructive sleep apnea (z score = 3.4; P = 8.1 × 10 −4 ) and, in another analysis, morbid obesity (z score = 3.8; P = 1.3 × 10 −4 ). Further, NDD CNVs were associated with increased body mass index in a multiancestry analysis (β = 0.19; 95% CI, 0.10-0.31; P = .003). For 36 common serum tests, there was no association with NDD CNVs.CONCLUSIONS AND RELEVANCE Clinical features of individuals harboring NDD CNVs were elucidated in a large-scale, multiancestry biobank, identifying enrichments for congenital disorders and major depressive disorder as well as associations with several medical outcomes, including hypertension, kidney failure, and obesity and obesity-related phenotypes, specifically obstructive sleep apnea and increased body mass index. The association between NDD CNVs and obesity outcomes indi...

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“…Conversely, the prevalence of obesity in psychiatric populations ranges from 25% to 60% for bipolar disorder, 30% to 70% for schizophrenia and 20% to 50% for depression 135,136 . Human genetic studies suggest obesity and some neuropsychiatric disorders may have shared genetic aetiology 137,138 . A bi‐directional relationship between mood disorders and obesity has also been proposed 136,139 …”

Section: Obesity As a Multisystem Diseasementioning

confidence: 99%

Obesity as a multisystem disease: Trends in obesity rates and obesity‐related complications

Sarma

Sockalingam

Dash

2021

Diabetes Obesity Metabolism

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192

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Obesity is a chronic multisystem disease associated with increased morbidity and mortality. The increasing prevalence of obesity makes it a major healthcare challenge across both developed and developing countries. Traditional measures such as body mass index do not always identify individuals at increased risk of comorbidities, yet continue to be used in deciding who qualifies for weight loss treatment. A better understanding of how obesity is associated with comorbidities, in particular non‐metabolic conditions, is needed to identify individuals at risk in order to prioritize treatment. For metabolic disorders such as type 2 diabetes (T2D), weight loss can prevent T2D in individuals with prediabetes. It can improve and reverse T2D if weight loss is achieved early in the course of the disease. However, access to effective weight loss treatments is a significant barrier to improved health for people with obesity. In the present paper, we review the rising prevalence of obesity and why it should be classed as a multisystem disease. We will discuss potential mechanisms underlying its association with various comorbidities and how these respond to treatment, with a particular focus on cardiometabolic disease, malignancy and mental health.

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Evaluation of the Genetic Association Between Adult Obesity and Neuropsychiatric Disease

Cited by 7 publications

References 54 publications

Intersections in Neuropsychiatric and Metabolic Disorders: Possible Role of TRPA1 Channels

Intersections in Neuropsychiatric and Metabolic Disorders: Possible Role of TRPA1 Channels

Clinical Characterization of Copy Number Variants Associated With Neurodevelopmental Disorders in a Large-scale Multiancestry Biobank

Obesity as a multisystem disease: Trends in obesity rates and obesity‐related complications

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