Expression levels of obesity-related genes are associated with weight change in kidney transplant recipients

Exploring the nexus: The place of kidney diseases within the cardiovascular-kidney-metabolic syndrome spectrum

Cardiovascular-kidney-metabolic (CKM) syndrome and chronic kidney disease (CKD) are two significant comorbidities affecting a large proportion of the general population with considerable crosstalk. In addition to substantial co-incidence of CKD and CKM syndrome in epidemiological studies, clinical and pre-clinical studies have identified similar pathophysiological pathways leading to both entities. Patients with CKM syndrome are more prone to develop acute kidney injury and CKD, while therapeutic alternatives and their success rates are considerably lower in such patient groups. Nevertheless, the association between CKM syndrome and CKD or ESKD is bidirectional rather than being a cause-effect relationship as patients with CKD are also prone to develop peripheral insulin resistance, high blood pressure, and dyslipidemia. Furthermore, such patients are less likely to receive kidney transplantation in addition to the higher allograft dysfunction risk. We hereby aim to evaluate the association in-between kidney diseases and CKM syndrome, including epidemiological data, pre-clinical studies with pathophysiological pathways, and potential therapeutic perspectives.

Post-transplant diabetes mellitus: Findings in nutritional status and body composition

INTRODUCTION

Weight gain and changes in body composition are associated with the onset of diabetes after kidney transplantation, and detailing these changes can help prevent this situation. The study aimed to assess the prevalence of diabetes mellitus after kidney transplantation and changes in the nutritional status and body composition in patients with diabetes one year from surgery.

MATERIALS AND METHODS

This survey was a single-center, prospective cohort study. Twenty-nine patients over 18 years old who underwent isolated kidney transplantation, without diabetes, were included and followed up for one year. At hospital discharge after transplantation and one year later, anthropometric (weight, height and abdominal circumference), body composition (electrical bioimpedance), routine biochemical and dietary intake assessments were performed.

RESULTS

Most of the patients were male (75%), and the mean age was 48.0±11.8 years old. In the first-year post-surgery 27.6% of patients had DM and the diagnosis was made, on average, 4 months after transplantation. The group with diabetes had, from the beginning to the end of the study, greater weight and body fat, especially abdominal fat. The non-diabetic group, after one year, showed an increase in phase angle, body weight and body masses, more pronounced of fat-free mass, when compared with fat mass gain.

CONCLUSIONS

Both groups showed weight gain, but in the non-diabetic group these changes can be interpreted as an improvement in the nutritional profile. Metabolic abnormalities associated with immunosuppression and eating habits, combination that maintains increased the risk for diabetes for long time, keeping this group with priority in nutritional care.

High-dimensionality Data Analysis of Pharmacological Systems Associated with Complex Diseases

It is widely accepted that molecular reductionist views of highly complex human physiologic activity, e.g., the aging process, as well as therapeutic drug efficacy are largely oversimplifications. Currently some of the most effective appreciation of biologic disease and drug response complexity is achieved using high-dimensionality (H-D) data streams from transcriptomic, proteomic, metabolomics, or epigenomic pipelines. Multiple H-D data sets are now common and freely accessible for complex diseases such as metabolic syndrome, cardiovascular disease, and neurodegenerative conditions such as Alzheimer's disease. Over the last decade our ability to interrogate these high-dimensionality data streams has been profoundly enhanced through the development and implementation of highly effective bioinformatic platforms. Employing these computational approaches to understand the complexity of age-related diseases provides a facile mechanism to then synergize this pathologic appreciation with a similar level of understanding of therapeutic-mediated signaling. For informative pathology and drug-based analytics that are able to generate meaningful therapeutic insight across diverse data streams, novel informatics processes such as latent semantic indexing and topological data analyses will likely be important. Elucidation of H-D molecular disease signatures from diverse data streams will likely generate and refine new therapeutic strategies that will be designed with a cognizance of a realistic appreciation of the complexity of human age-related disease and drug effects. We contend that informatic platforms should be synergistic with more advanced chemical/drug and phenotypic cellular/tissue-based analytical predictive models to assist in either de novo drug prioritization or effective repurposing for the intervention of aging-related diseases. SIGNIFICANCE STATEMENT: All diseases, as well as pharmacological mechanisms, are far more complex than previously thought a decade ago. With the advent of commonplace access to technologies that produce large volumes of high-dimensionality data (e.g., transcriptomics, proteomics, metabolomics), it is now imperative that effective tools to appreciate this highly nuanced data are developed. Being able to appreciate the subtleties of high-dimensionality data will allow molecular pharmacologists to develop the most effective multidimensional therapeutics with effectively engineered efficacy profiles.

Gene co-expression networks are associated with obesity-related traits in kidney transplant recipients

Background

Obesity is common among kidney transplant recipients; However biological mediators of obesity are not well understood in this population. Because subcutaneous adipose tissue can be easily obtained during kidney transplant surgery, it provides a unique avenue for studying the mechanisms of obesity for this group. Although differential gene expression patterns were previously profiled for kidney transplant patients, gene co-expression patterns can shed light on gene modules not yet explored on the coordinative behaviors of gene transcription in biological and disease processes from a systems perspective.

Methods

In this study, we collected 29 demographic and clinical variables and matching microarray expression data for 26 kidney transplant patients. We conducted Weighted Gene Correlation Network Analysis (WGCNA) for 5758 genes with the highest average expression levels and related gene co-expression to clinical traits.

Results

A total of 35 co-expression modules were detected, two of which showed associations with obesity-related traits, mainly at baseline. Gene Ontology (GO) enrichment was found for these two clinical trait-associated modules. One module consisting of 129 genes was enriched for a variety of processes, including cellular homeostasis and immune responses. The other module consisting of 36 genes was enriched for tissue development processes.

Conclusions

Our study generated gene co-expression modules associated with obesity-related traits in kidney transplant patients and provided new insights regarding the cellular biological processes underlying obesity in this population.

The RXFP3 receptor is functionally associated with cellular responses to oxidative stress and DNA damage

DNA damage response (DDR) processes, often caused by oxidative stress, are important in aging and -related disorders. We recently showed that G protein-coupled receptor (GPCR) kinase interacting protein 2 (GIT2) plays a key role in both DNA damage and oxidative stress. Multiple tissue analyses in GIT2KO mice demonstrated that GIT2 expression affects the GPCR relaxin family peptide 3 receptor (RXFP3), and is thus a therapeutically-targetable system. RXFP3 and GIT2 play similar roles in metabolic aging processes. Gaining a detailed understanding of the RXFP3-GIT2 functional relationship could aid the development of novel anti-aging therapies. We determined the connection between RXFP3 and GIT2 by investigating the role of RXFP3 in oxidative stress and DDR. Analyzing the effects of oxidizing (H₂O₂) and DNA-damaging (camptothecin) stressors on the interacting partners of RXFP3 using Affinity Purification-Mass Spectrometry, we found multiple proteins linked to DDR and cell cycle control. RXFP3 expression increased in response to DNA damage, overexpression, and Relaxin 3-mediated stimulation of RXFP3 reduced phosphorylation of DNA damage marker H2AX, and repair protein BRCA1, moderating DNA damage. Our data suggests an RXFP3-GIT2 system that could regulate cellular degradation after DNA damage, and could be a novel mechanism for mitigating the rate of age-related damage accumulation.

Combining clinical and molecular data in regression prediction models: insights from a simulation study

Data integration, i.e. the use of different sources of information for data analysis, is becoming one of the most important topics in modern statistics. Especially in, but not limited to, biomedical applications, a relevant issue is the combination of low-dimensional (e.g. clinical data) and high-dimensional (e.g. molecular data such as gene expressions) data sources in a prediction model. Not only the different characteristics of the data, but also the complex correlation structure within and between the two data sources, pose challenging issues. In this paper, we investigate these issues via simulations, providing some useful insight into strategies to combine low- and high-dimensional data in a regression prediction model. In particular, we focus on the effect of the correlation structure on the results, while accounting for the influence of our specific choices in the design of the simulation study.

Enhanced Molecular Appreciation of Psychiatric Disorders Through High-Dimensionality Data Acquisition and Analytics

The initial diagnosis, molecular investigation, treatment, and posttreatment care of major psychiatric disorders (schizophrenia and bipolar depression) are all still significantly hindered by the current inability to define these disorders in an explicit molecular signaling manner. High-dimensionality data analytics, using large datastreams from transcriptomic, proteomic, or metabolomic investigations, will likely advance both the appreciation of the molecular nature of major psychiatric disorders and simultaneously enhance our ability to more efficiently diagnose and treat these debilitating conditions. High-dimensionality data analysis in psychiatric research has been heterogeneous in aims and methods and limited by insufficient sample sizes, poorly defined case definitions, methodological inhomogeneity, and confounding results. All of these issues combine to constrain the conclusions that can be extracted from them. Here, we discuss possibilities for overcoming methodological challenges through the implementation of transcriptomic, proteomic, or metabolomics signatures in psychiatric diagnosis and offer an outlook for future investigations. To fulfill the promise of intelligent high-dimensionality data-based differential diagnosis in mental disease diagnosis and treatment, future research will need large, well-defined cohorts in combination with state-of-the-art technologies.

GRK5 - A Functional Bridge Between Cardiovascular and Neurodegenerative Disorders

Complex aging-triggered disorders are multifactorial programs that comprise a myriad of alterations in interconnected protein networks over a broad range of tissues. It is evident that rather than being randomly organized events, pathophysiologies that possess a strong aging component such as cardiovascular diseases (hypertensions, atherosclerosis, and vascular stiffening) and neurodegenerative conditions (dementia, Alzheimer's disease, mild cognitive impairment, Parkinson's disease), in essence represent a subtly modified version of the intricate molecular programs already in place for normal aging. To control such multidimensional activities there are layers of trophic protein control across these networks mediated by so-called "keystone" proteins. We propose that these "keystones" coordinate and interconnect multiple signaling pathways to control whole somatic activities such as aging-related disease etiology. Given its ability to control multiple receptor sensitivities and its broad protein-protein interactomic nature, we propose that G protein coupled receptor kinase 5 (GRK5) represents one of these key network controllers. Considerable data has emerged, suggesting that GRK5 acts as a bridging factor, allowing signaling regulation in pathophysiological settings to control the connectivity between both the cardiovascular and neurophysiological complications of aging.

β-Arrestin Based Receptor Signaling Paradigms: Potential Therapeutic Targets for Complex Age-Related Disorders

G protein coupled receptors (GPCRs) were first characterized as signal transducers that elicit downstream effects through modulation of guanine (G) nucleotide-binding proteins. The pharmacotherapeutic exploitation of this signaling paradigm has created a drug-based field covering nearly 50% of the current pharmacopeia. Since the groundbreaking discoveries of the late 1990s to the present day, it is now clear however that GPCRs can also generate productive signaling cascades through the modulation of β-arrestin functionality. β-Arrestins were first thought to only regulate receptor desensitization and internalization - exemplified by the action of visual arrestin with respect to rhodopsin desensitization. Nearly 20 years ago, it was found that rather than controlling GPCR signal termination, productive β-arrestin dependent GPCR signaling paradigms were highly dependent on multi-protein complex formation and generated long-lasting cellular effects, in contrast to G protein signaling which is transient and functions through soluble second messenger systems. β-Arrestin signaling was then first shown to activate mitogen activated protein kinase signaling in a G protein-independent manner and eventually initiate protein transcription - thus controlling expression patterns of downstream proteins. While the possibility of developing β-arrestin biased or functionally selective ligands is now being investigated, no additional research has been performed on its possible contextual specificity in treating age-related disorders. The ability of β-arrestin-dependent signaling to control complex and multidimensional protein expression patterns makes this therapeutic strategy feasible, as treating complex age-related disorders will likely require therapeutics that can exert network-level efficacy profiles. It is our understanding that therapeutically targeting G protein-independent effectors such as β-arrestin will aid in the development of precision medicines with tailored efficacy profiles for disease/age-specific contextualities.

G Protein-Coupled Receptor Systems as Crucial Regulators of DNA Damage Response Processes

G protein-coupled receptors (GPCRs) and their associated proteins represent one of the most diverse cellular signaling systems involved in both physiological and pathophysiological processes. Aging represents perhaps the most complex biological process in humans and involves a progressive degradation of systemic integrity and physiological resilience. This is in part mediated by age-related aberrations in energy metabolism, mitochondrial function, protein folding and sorting, inflammatory activity and genomic stability. Indeed, an increased rate of unrepaired DNA damage is considered to be one of the 'hallmarks' of aging. Over the last two decades our appreciation of the complexity of GPCR signaling systems has expanded their functional signaling repertoire. One such example of this is the incipient role of GPCRs and GPCR-interacting proteins in DNA damage and repair mechanisms. Emerging data now suggest that GPCRs could function as stress sensors for intracellular damage, e.g., oxidative stress. Given this role of GPCRs in the DNA damage response process, coupled to the effective history of drug targeting of these receptors, this suggests that one important future activity of GPCR therapeutics is the rational control of DNA damage repair systems.

New-onset obesity after liver transplantation-outcomes and risk factors: the Swiss Transplant Cohort Study

Weight gain after liver transplantation (LTx) facilitates development of new-onset obesity; however, its risk factors and outcomes are poorly understood. We identified the impact of new-onset obesity on cardiovascular events (CVEs) and patient survival, and risk factors for new-onset obesity. Multiple Cox regression models examined risk factors for CVEs, patient survival, and new-onset obesity in 253 adults (mean age 52.2 ± 11.6 years, male gender 63.6%, mean follow up 5.7 ± 2.1 years). Cumulative incidence of post-LTx CVE was 28.1%; that of new-onset obesity was 21.3%. Regardless of CVE at LTx, post-LTx CVEs were predicted by new-onset obesity [Hazard Ratio (HR), 2.95; P = 0.002] and higher age at LTx (HR, 1.05; P < 0.001). In patients without known pre-LTx CVEs (n = 214), risk factors for post-LTx CVEs were new-onset obesity (HR, 2.59; P = 0.014) and higher age (HR, 1.04; P = 0.001). Survival was not associated with new-onset obesity (P = 0.696). Alcoholic liver disease predicted new-onset obesity (HR, 3.37; P = 0.025), female gender was protective (HR, 0.39; P = 0.034). In 114 patients with available genetic data, alcoholic liver disease (HR, 12.82; P = 0.014) and hepatocellular carcinoma (HR, 10.02; P = 0.048) predicted new-onset obesity, and genetics remained borderline significant (HR, 1.07; P = 0.071). Early introduction of post-LTx weight management programs may suggest a potential pathway to reduce CVE risk.

Nutritional status, energy expenditure, and protein oxidative stress after kidney transplantation

OBJECTIVES

To evaluate the association between nutritional status, resting energy expenditure (REE), and protein oxidative stress in patients after kidney transplantation (KT).

METHODOLOGY

The study evaluated 35 patients transplanted at the time of hospital discharge and 3 months after regarding: body composition, REE (by indirect calorimetry), and injury factor (IF); serum urea, creatinine, glucose, albumin, total protein, advanced oxidation protein products (AOPP), vitamin C.

RESULTS

Three months after discharge, there was an improvement in renal function, nutritional status, and oxidative stress, with a standardization in the REE/kg. There was an increase in body weight, mainly in fat mass. The correlations showed that a greater cold ischemia time resulted in a deeper decline in vitamin C; a longer hospital length stay resulted in a greater reduction in AOPP; the higher preoperative body weight showed greater increases in body fat and glucose after transplantation. For decreases in REE and IF, there were increases in total protein. Finally, at hospital discharge there was a greater gain in weight, lower albumin, and total protein among individuals who had rejection episodes.

DISCUSSION

The KT improves many of metabolic abnormalities, with the improvement of nutritional status, oxidative stress, and normalization of REE.

Characterization of Body Composition and Fat Mass Distribution 1 Year After Kidney Transplantation

PURPOSE

In some recipients, significant weight gain occurs after kidney transplantation. Weight gain is associated with poor outcomes, particularly increased cardiovascular risk. In this study, we characterized changes in body mass index and body fat mass and compared them based on gender and race.

METHODS

Fifty-two kidney transplant recipients (aged ≥18 years old, 50% men, 58% African American) were enrolled into a prospective study. Body mass index and body fat mass were measured at baseline and 12 months posttransplant. Body fat mass was determined by dual-energy X-ray absorptiometry.

RESULTS

The mean increase in body weight was 3.7kg at 12 months; 36.5% (n=19) gained at least 10% of their baseline body weight. Body mass index, percentage of total body fat, and trunk fat were significantly increased. In subgroups, women and African American showed significant increases in body mass index and body fat measures. More participants were classified as obese based on total body fat compared to body mass index. Calories from fat were significantly increased at 12 months and associated with increased body mass index, total body fat, and trunk fat. Days of physical activity were significantly increased.

CONCLUSION

Both body mass index and total body fat mass were significantly increased at 12 months following kidney transplantation, especially for women and African Americans. Importantly, more participants were classified as obese based on total body fat compared to body mass index. Relevant nutrition and physical intervention should be provided, and both body mass index and body fat mass should be evaluated when monitoring weight gain.

Weighted Genetic Risk Scores and Prediction of Weight Gain in Solid Organ Transplant Populations

Background

Polygenic obesity in Solid Organ Transplant (SOT) populations is considered a risk factor for the development of metabolic abnormalities and graft survival. Few studies to date have studied the genetics of weight gain in SOT recipients. We aimed to determine whether weighted genetic risk scores (w-GRS) integrating genetic polymorphisms from GWAS studies (SNP group#1 and SNP group#2) and from Candidate Gene studies (SNP group#3) influence BMI in SOT populations and if they predict ≥10% weight gain (WG) one year after transplantation. To do so, two samples (n_A = 995, n_B = 156) were obtained from naturalistic studies and three w-GRS were constructed and tested for association with BMI over time. Prediction of 10% WG at one year after transplantation was assessed with models containing genetic and clinical factors.

Results

w-GRS were associated with BMI in sample A and B combined (BMI increased by 0.14 and 0.11 units per additional risk allele in SNP group#1 and #2, respectively, p-values<0.008). w-GRS of SNP group#3 showed an effect of 0.01 kg/m² per additional risk allele when combining sample A and B (p-value 0.04). Models with genetic factors performed better than models without in predicting 10% WG at one year after transplantation.

Conclusions

This is the first study in SOT evaluating extensively the association of w-GRS with BMI and the influence of clinical and genetic factors on 10% of WG one year after transplantation, showing the importance of integrating genetic factors in the final model. Genetics of obesity among SOT recipients remains an important issue and can contribute to treatment personalization and prediction of WG after transplantation.

Post-transplantation diabetes-state of the art

With increasing success in overcoming the immunological and infectious challenges accompanying solid organ transplantation, susceptibility to post-transplant diabetes and cardiovascular disease has assumed increasing importance. Although some guidance is available from diabetes-related literature pertaining to the general population, some aspects are unique to solid organ allograft recipients. Both insulin resistance and β-cell dysfunction are generally agreed to contribute to development and manifestation of post-transplant diabetes, but controversy continues about which is most important and to what extent post-transplant diabetes is a distinct entity or simply a variant of type 2 diabetes with transplant-specific components. The optimum method and timing for detection and diagnosis of post-transplant diabetes remains an area of uncertainty. However, the greatest needs are to: address the absence of contemporary data for incidence and clinical outcomes associated with post-transplant diabetes; establish the role of glycaemic control; and assess the role of new diabetic therapies in prevention and management of post-transplant diabetes. We place the present knowledge base in the context of other advances in transplantation, challenge some existing ideas, and examine the potential role of emerging diabetes therapies. In highlighting existing deficiencies, we hope to provide direction for future research that will ultimately reduce incidence and improve management of post-transplant diabetes.

A Prospective Study of Depression and Weight Change After Kidney Transplant

Context:

Kidney transplant recipients have great risk for gaining significant weight (upward of 10 kg) in the first year posttransplant. Clinical depression can occur in response to life situations and is associated with weight gain.

Objective:

To explore the association between demographic characteristics, weight change, and depression posttransplantation.

Design:

Secondary data analysis on longitudinal data collected for a larger observational study. Demographic characteristics, weight, and Center for Epidemiologic Studies Depression Scale (CES-D) data were obtained at baseline (BL) (time of transplantation), 6, and 12 months posttransplant. The CES-D scores were compared among time points using means, standard deviations, correlations, t tests, and chi-square as well as by multiple regression modeling.

Setting:

Regional transplant center in the mid-south United States.

Participants:

Forty-seven kidney transplant recipients (55% female, 57% African American, mean age 52.5 years). Weight change ranged from −18.1 to +24.8 kg.

Results:

In all, 62% reported baseline CES-D scores indicative of depression, with lower scores indicating less psychological distress at 6 and 12 months (47% and 49%, respectively). We found no significant differences among CES-D scores at any time point. Regression models found age, race, gender, and weight change to be predictive of CES-D scores at 6 months ( P = .04, R2 = .137). Age was the most influential ( P = .008), with older individuals more likely to obtain higher CES-D scores. Since the experience of depression is common at transplant and during the first year, it is important that transplant recipients be evaluated for depression early in the recovery period.

Oxidative stress is associated with weight gain in recipients at 12-months following kidney transplantation

OBJECTIVE

Weight gain after kidney transplantation (Tx) is considered a risk factor for poor outcomes. Increased oxidative stress is associated with not only chronic renal disease and Tx, but also obesity and cardiovascular disease. The aim of this pilot study was to test whether oxidative stress is related to weight gain at 12-months after kidney Tx and to obtain preliminary insight into potential mechanisms involved.

DESIGN & METHODS

Recipients (n=33) were classified into two groups; weight loss and weight gain, based on their weight changes at 12-months post-transplant. Total antioxidant capacity (TAOC) and lipid peroxidation (TBARS) were measured to evaluate oxidative stress from plasma at baseline and 12-months. A secondary data analysis was conducted to identify potential gene regulation.

RESULTS

Seventeen recipients lost (-6.63±5.52kg), and sixteen recipients gained weight (8.94±6.18kg). TAOC was significantly decreased at 12-months compared to baseline for the total group, however, there was no significant difference between groups at either time point. TBARS was higher in weight gain group, at both time points, and it was significantly higher at 12-months (p=0.012). Gene expression profiling analysis showed that 7 transcripts annotated to reactive oxygen species related genes in adipose tissue were expressed significantly lower in weight gain group at baseline, which might be a negative feedback mechanism to reduce oxidative stress.

CONCLUSION

These results may indicate that elevated oxidative stress (TBARS) is associated with weight gain after kidney Tx and that incorporating early clinical prevention strategies known to decrease oxidative stress could be recommended.

A Pilot Study of Demographic and Dopaminergic Genetic Contributions to Weight Change in Kidney Transplant Recipients

Kidney transplant recipients often experience a significant amount of weight gain in the first year post-transplantation. While demographic factors such as age, race, and sex have been associated with weight gain in this population, these factors do not explain all of the variability seen. A number of studies have suggested that genetics also plays a critical role in weight changes. Recently, alterations in the activity of the neurotransmitter dopamine have been associated with weight change, and gene expression studies in kidney transplant recipients have supported this association. The purpose of this pilot study is to first examine the feasibility and methodology, and then to examine the associations of age, race, sex, and genotype for 13 SNPs and 3 VNTRs in 9 dopaminergic pathway genes (ANKK1, DRD2, DRD3, DRD4, SLC6A3/DAT1, MAOA, MAOB, COMT, CPE) for associations with percent weight change at 12 months post-transplantation. Seventy kidney transplant recipients had demographic and clinical data collected as a part of a larger observational study. DNA was extracted from repository buffy coat samples taken at the time of transplant, and genotyped using Taqman and PCR based methods. Three SNPs were independently associated with percent weight change: ANKK1 rs1800497 (r = -0.28, p = 0.05), SLC6A3/DAT1 rs6347 (p = 0.046), and CPE rs1946816 (p = 0.028). Stepwise regression modelling confirmed the combined associations of age (p = 0.0021), DRD4 VNTR 4/5 genotype (p = 0.0074), and SLC6A3/DAT1 rs6347 CC genotype (p = 0.0009) and TT genotype (p = 0.0004) with percent weight change in a smaller sample (n = 35) of these kidney transplant recipients that had complete genotyping. These associations indicate that there may be a genetic, and an age component to weight changes post transplantation.

Neurogenetic and Neuroimaging Evidence for a Conceptual Model of Dopaminergic Contributions to Obesity

As the incidence of obesity continues to rise, clinicians and researchers alike are seeking explanations for why some people become obese while others do not. While caloric intake and physical activity most certainly play a role, some individuals continue to gain weight despite careful attention to these factors. Increasing evidence suggests that genetics may play a role, with one potential explanation being genetic variability in genes within the neurotransmitter dopamine pathway. This variability can lead to a disordered experience with the rewarding properties of food. This review of literature examines the extant knowledge about the relationship between obesity and the dopaminergic reward pathways in the brain, with particularly strong evidence provided from neuroimaging and neurogenetic data. Pubmed, Google Scholar, and Cumulative Index to Nursing and Allied Health Literature searches were conducted with the search terms dopamine, obesity, weight gain, food addiction, brain regions relevant to the mesocortical and mesolimbic (reward) pathways, and relevant dopaminergic genes and receptors. These terms returned over 200 articles. Other than a few sentinel articles, articles were published between 1993 and 2013. These data suggest a conceptual model for obesity that emphasizes dopaminergic genetic contributions as well as more traditional risk factors for obesity, such as demographics (age, race, and gender), physical activity, diet, and medications. A greater understanding of variables contributing to weight gain and obesity is imperative for effective clinical treatment.

Obesity and organ transplantation: successes, failures, and opportunities

The increasing rate of societal obesity is also affecting the transplant world through obesity in candidates and donors as well as its posttransplant repercussions. Being overweight and obese has been shown to have significant effects on both short- and long-term complications as well as patient and graft survival. However, much of the comorbidity can be controlled or prevented with careful patient selection and aggressive management. A team approach to managing obesity and its comorbidities both pre- and posttransplant is essential for successful transplant outcomes. Complicating understanding the results of obesity research is the inclusion different weight categories, use of listing vs transplant weights, patient populations large enough for statistical power, and changes in transplant management, especially immunosuppression protocols, anti-infection protocols, and operative techniques. Much more research is needed regarding many elements, including safe weight loss before transplantation, prevention of weight gain after transplant, genomic influences, and the role of bariatric surgery in the transplant process.