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

Variable Selection for Assessing Risk Factors for Weight and Body fat Gain During the First Year After Kidney Transplantation

Background: Body fat and overall weight gain are common after kidney transplantation and are associated with poor clinical outcomes. Therefore, identification of at-risk patients is relevant for preventive interventions. Clinical Question: What variables influence weight and fat gain in patients in the first year after kidney transplantation? Literature Search Prospective and retrospective cohort studies published in or after 2001 naming fat and/or overall weight gain during the first year after kidney transplantation as outcome variable(s) were systematically searched in Medline/Pubmed in November 2018 and March 2022. Clinical Appraisal: We identified 16 studies examining a wide variety of potential factors influencing weight and fat gain over the first posttransplant years. These included genetic, socio-demographic, behavioral, biomedical, psychological and environmental factors. For a number of variables, study results were contradictory: some studies indicated preventive impacts on weight or fat gain; others concluded that the same factors increased it. Cases were discussed with 2 clinical experts. We eventually agreed on 13 potentially relevant risk factors for post-transplant weight/fat gain: age, gender, genes, income, ethnicity, education, eating habits, physical activity, smoking cessation, baseline BMI, baseline fat, depression and perceived overall wellbeing. Integration into Practice Before integration into clinical practice, a critical evaluation of all potential risk factors' suitability for assessment will be necessary. In addition to feasibility, operational definitions and measurement methods must also be considered. Evaluation: To reduce the list of risk factors to the most relevant, a first testing within a prospectively collected data set is planned.

First Testing of Literature-Based Models for Predicting Increase in Body Weight and Adipose Tissue Mass After Kidney Transplantation

Introduction: Weight gain is a risk factor for poor clinical outcomes following kidney transplantation. Research Question: This study's aim was a first testing of 2 models to identify patients early after kidney transplantation who are at risk for weight gain and increase in adipose tissue mass in the first year after kidney transplantation. Design: The literature-based models were evaluated on longitudinal data of 88, respectively 79 kidney transplant recipients via ordinary and Firth regression, using gains ≥ 5% in weight and adipose tissue mass respectively as primary and secondary endpoints. Results: The models included physical activity, smoking cessation at time of kidney transplantation, self-reported health status, depressive symptomatology, gender, age, education, baseline body mass index and baseline trunk fat as predictors. Area under the curve was 0.797 (95%-CI 0.702 to 0.893) for the weight model and 0.767 (95%-CI 0.656 to 0.878) for the adipose tissue mass model-showing good, respectively fair discriminative ability. For weight gain ≥ 5%, main risk factors were smoking cessation at time of transplantation (OR 16.425, 95%-CI 1.737-155.288) and better self-reported baseline health state (OR 1.068 for each 1-unit increase, 95%-CI 1.012-1.128). For the adipose tissue mass gain ≥ 5%, main risk factor was overweight/obesity (BMI ≥ 25) at baseline (odds ratio 7.659, 95%-CI 1.789-32.789). Conclusions: The models have potential to assess patients' risk for weight or adipose tissue mass gain during the year after transplantation, but further testing is needed before implementation in clinical practice.

Enhancing Research Through the Use of the Genotype-Tissue Expression (GTEx) Database

Despite a growing interest in multi-omic research, individual investigators may struggle to collect large-scale omic data, particularly from human subjects. Publicly available datasets can help to address this problem, including those sponsored by the NIH Common Fund, such as the Genotype-Tissue Expression (GTEx) database. This database contains genotype and expression data obtained from 54 non-diseased tissues in human subjects. But these data are often underutilized, because users may find the browsing tools to be counterintuitive or have difficulty navigating the procedures to request controlled data access. Furthermore, there is limited knowledge of these resources among nurse scientists interested in incorporating such information into their programs of research. This article outlines the procedures for using the GTEx database. Next, we provide one exemplar of using this resource to enhance existing research by investigating expression of dopamine receptor type 2 (DRD2) across brain tissues in human subjects.

Expression of Dopamine-Related Genes in Four Human Brain Regions

A better understanding of dopaminergic gene expression will inform future treatment options for many different neurologic and psychiatric conditions. Here, we utilized the National Institutes of Health’s Genotype-Tissue Expression project (GTEx) dataset to investigate genotype by expression associations in seven dopamine pathway genes (ANKK1, DBH, DRD1, DRD2, DRD3, DRD5, and SLC6A3) in and across four human brain tissues (prefrontal cortex, nucleus accumbens, substantia nigra, and hippocampus). We found that age alters expression of DRD1 in the nucleus accumbens and prefrontal cortex, DRD3 in the nucleus accumbens, and DRD5 in the hippocampus and prefrontal cortex. Sex was associated with expression of DRD5 in substantia nigra and hippocampus, and SLC6A3 in substantia nigra. We found that three linkage disequilibrium blocks of SNPs, all located in DRD2, were associated with alterations in expression across all four tissues. These demographic characteristic associations and these variants should be further investigated for use in screening, diagnosis, and future treatment of neurological and psychiatric conditions.

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.