Hemodialysis Related Symptoms, Gut Microbiota, and Lifestyle Factors: A Correlational Pilot Study

Friday, 20 July 2018

Seon-Yoon Chung, PhD, RN1
Jennifer Barnes, PhD, RD, LDN2
Kim Schafer Astroth, PhD, RN1
(1)Mennonite College of Nursing, Illinois State University, Normal, IL, USA
(2)Department of Family and Consumer Sciences, Illinois State University, Normal, IL, USA


End stage renal disease (ESRD) affects more than 660,000 Americans and annually costs Medicare approximately $31 billion to treat the disease (United States Renal Data System, 2015). Due to the kidney disease and related comorbid conditions as well as treatment of these, patients experience multiple symptoms, subjective and individualized unpleasant sensations, including fatigue, pain, pruritus, anorexia, and irritability (Almutary, Bonner, & Douglas, 2013; A. Amro et al., 2015; Amin Amro, Waldum, Dammen, Miaskowski, & Os, 2014; Kwok, Yuen, Yong, & Tse, 2015). Symptoms are important cues that reflect functional or structural abnormalities in the body that are experienced by patients. Symptoms impair patients’ quality of life (QOL) and have been associated with depression and even predict mortality in some cases (A. Amro et al., 2015; Amin Amro et al., 2014).

Burgeoning evidence suggest that gastrointestinal (GI) microbiota regulate physiologic homeostasis in the human body that may influence the symptoms (Clemente, Ursell, Parfrey, & Knight, 2012; Sommer & Bäckhed, 2013; Tremaroli & Bäckhed, 2012). Although precise mechanism of its contributions is unclear, studies have revealed profound alterations of the GI microbiota in patients with ESRD (Crespo-Salgado et al., 2016; Vaziri et al., 2013; F. Wang et al., 2012; I.-K. Wang et al., 2012). Intestinal dysbiosis, the disruption in the normal intestinal flora, is proposed to be associated with decreased consumption of dietary fiber (Kalantar-zadeh et al., 2016; Sirich, 2014), frequent use of antibiotics(Ferrer, dos Santos, Ott, & Moya, 2013), alterations of intestinal barrier (Sabatino et al., 2015), uremic toxin (Kikuchi, Ueno, Itoh, Suda, & Hattori, 2017), and metabolic acidosis (Kraut, 2016), conditions that are often seen in patients with chronic kidney disease (CKD).

Recent studies have proposed that prebiotic supplementation such as dietary fiber may ameliorate progression of CKD by serving as food for the GI microbiota to beneficially modulate the gut microbiota in patients with CKD (Chiavaroli, Mirrahimi, Sievenpiper, Jenkins, & Darling, 2015). Moreover, emerging studies focus on the influence of physical activity on composition of gut microbiota, further suggesting the possibility of using diet and physical activity as ways to optimize GI microbiota to prevent the progression of CKD and development of complications such as adverse symptoms (Cerdá et al., 2016; Howden, Coombes, & Isbel, 2015).

The purpose of this study was to determine the association among the type of GI microbiota that patients receiving hemodialysis harbor, symptom clusters experienced by them, and their lifestyle factors. We propose that the GI microbial dysbiosis contributes to the adverse symptoms experienced in this group of patients and that lifestyle factors may be used to optimize microbial composition and alleviate adverse symptoms.


This is a cross-sectional correlational pilot study (N=20). Participants are recruited at a local dialysis clinic. Inclusion criteria are 1) English speaking, 2) aged 18 and above, 3) receiving hemodialysis, and 4) experiencing 2 or more symptoms related to kidney disease. Patients are included in the study regardless of the gender, race, socio-economic level. Patients 1) receiving peritoneal dialysis, 2) had kidney transplantation, 3) have a diagnosed gastrointestinal illness such as inflammatory bowel disease, or 4) have received antibiotics or probiotics in the past 3 months are excluded.

Survey data collected include 1) Socio-demographic and health characteristics, 2) Diet behavior, 3) Physical activity, and 4) Dialysis symptoms. Socio-demographics and health characteristics are collected using a questionnaire while information about medical history, comorbidities, list of medications, blood lab results (complete blood count, chemistry profile/ basic metabolic panel, inflammatory markers), and anthropometrics such as weight and height are collected from medical records. Dietary behavior is measured using Block Dialysis Food Frequency Questionnaire and physical activity is measured using the International Physical Activity Questionnaire short form. Presence, severity and frequency of the symptoms as well as the level of distress experienced by CKD patients since last dialysis treatment are measured using Dialysis Frequency, Severity, and Symptom Burden Index (DFSSBI). All surveys are conducted at the dialysis center during patients’ regular dialysis session or before or after the session depending on the participant’s preferences. Stool specimen will be collected using a feces container with screw cap at participant's home to measure GI microbiota. As stool samples are collected by participants at home, participants will transport the frozen samples to the dialysis center when they are coming in for their next visit, in an insulated bag with ice-pack that has been provided to them together with stool collection kit.

Stool samples will be biologically analyzed to extract, amplify, and sequence bacterial DNA to determine the gut microbial composition. Fecal DNA will be extracted using a PowerLyzer PowerSoil DNA Isolation Kit (Mo Bio Laboratories, Inc., Carlsbad, CA USA) according to manufacturer’s instructions. Then, bacterial genes will be amplified using a Fluidigm Access Array system in the W. M. Keck Center for Biotechnology, University of Illinois. Following amplification, the quality of the amplicon pools will be checked and amplicon region and size will be confirmed and purified. Illumina sequencing will be performed on a MiSeq using v3 reagents (Illumina Inc., San Diego, CA) prior to high-throughput sequencing on an Illumina MiSeq. Sequence data will be analyzed with QIIME 1.9.1. High quality (quality value > 25) sequences were clustered into operational taxonomic units (OTUs) using closed reference OTU picking against the 13-8 Greengenes database (97% similarity) for the bacterial and archaeal sequences. Descriptive statistics will be used to characterize the socio-demographics. Hierarchical clustering will be used to cluster symptom experience and the GI microbial communities each. Generalized linear models will be used to determine the association between the microbial community and symptom clusters as well as the influence of diet and physical activity on the microbial community and symptom clusters. All statistical analyses will be conducted using SPSS (v.24) and R (v. 3.3.0).


The results from this study will serve as a foundation for large-scale studies that will ultimately contribute to symptom management and improved quality of life in patients with ESRD by optimizing gut microbial composition using modifiable lifestyle factors.


The results from this study are particularly relevant in nursing because nurses are at the frontline, interacting with the patients with ESRD on a routine basis. The basic knowledge about the GI microbial structures and their association with symptom clusters gained from this study may allow nurses to provide evidence-based care that contributes to promoting optimal microbial structure using modifiable lifestyle factors, thereby alleviating the symptoms experienced by patients with ESRD and ultimately improving their quality of life.