Laura D. Byham-Gray, Ph.D., RDN, FNKF

School of Health Profession’s Intramural Seed Grant

Byham-Gray (PI)
9/1/22-8/31/24: $35,000.00

Exploring Phenotypes for Predicting Optimal Body Weight and Survival in Patients Treated by Maintenance Hemodialysis

Description:  Our central hypothesis is that there is no single optimal body weight reference norm for patients with CKD. Rather, optimal body weight is an individual-centric concept tailored to each person in accordance with their configuration of disease-related characteristics; i.e., given a specific phenotype, the individual’s optimal body weight will vary accordingly. Until now, existing efforts to address this issue have been hampered by the methodological limitations of modeling disease-specific predictors and then attempting to fit a single model for the entire weight distribution. Hence, an innovative approach is warranted to solve this clinical dilemma for patients diagnosed with CKD. Accessing a large, longitudinal and international database such as the Dialysis Outcomes and Practice Patterns Study in addition to using advanced statistical methods will be instrumental for establishing the weight stratum at which each patient has the lowest risk given their disease phenotype. Using machine learning and traditional statistical methods in tandem will explain not merely what matters for survival at different weight strata, but to understand why it may matter. The outcome of these aims is the initial steps towards the generation of a phenotypic profile for patients so that better precision concerning optimal body weight will eventually be achieved.

Rutgers Busch Biomedical Grant  

Byham-Gray (Co-PI)
9/1/19-8/31/21:  $40,000.00

Image-based DiEtary Assessment in Chronic Kidney Disease (IDEA-CKD)

Description: Protein-energy malnutrition and wasting (PEW) is an independent risk factor for the poor health outcomes and premature death experienced in patients diagnosed with chronic kidney disease (CKD).  Hypermetabolism is theorized as one of the key determinants for PEW.  Achieving energy balance, and therefore optimal nutritional status, requires that daily dietary energy intake (DEI) equate to total energy expenditure (TEE).  Concordant with other chronic diseases as well as the healthy population, our research team has demonstrated how current methods for DEI are inadequate for CKD.  Thus, the objective of this proposal was two-fold:  to develop and validate computational machine learning algorithms for the recognition of food and related quantity using multimodal measurements from joint image and depth sensors. We anticipate that the proposed algorithms will more precisely measure dietary intake than traditional methods, while overcoming many of the barriers for their utilization.

National Kidney Foundation 

Byham-Gray (PI)
10/1/18-9/30/22:  $65,000.00

Bone Outcomes, Nutrition, and Energy Expenditure Study in Chronic Kidney Disease (BONES-CKD) 

Description: While survival is improving among U.S. patients diagnosed with chronic kidney disease, they are still at considerable risk for poor outcomes. One factor explaining the high mortality rate is the presence of malnutrition and muscle wasting which may be associated with compensatory changes in bone and energy metabolism.  This proposed study seeks to explore the relationship of alterations in bone health measures secondary to chronic kidney disease on body composition and energy expenditure.  Accessing our expansive patient network, we will conduct this study among individuals diagnosed with stages 3-5 chronic kidney disease. By examining several bone disease markers, we will be able to determine a) whether mineral and bone disorders influence energy metabolism and b) if these influences are mediated by body composition. This knowledge will allow for earlier and more appropriate intervention and therefore prevent or treat abnormalities in mineral and bone disorders and improve patient outcomes

School of Health Profession’s Intramural Bridge Grant

Byham-Gray (PI)
7/1/17-12/31/19:  $35,000.00

Linking Symptoms to Protein-Energy Wasting in Hemodialysis:  KNOW SIGNS

Description: Patients with stage 5 chronic kidney disease treated by maintenance hemodialysis experience a suboptimal functional status marked by low physical activity levels, prolonged sitting time, sarcopenia, frailty, and a diminished health-related quality of life (HR-QoL). Exercise interventions have shown improvement in functional abilities within this population, but the contribution of nutritional status and/or PEW on these outcomes remains unelucidated. Our study took a comprehensive, multi-faceted approach by documenting functional status through several quantitative measures. Additionally, we integrated the patient voice in order to capture a more thorough analysis of the barriers for improving functional status and outline strategies for overcoming them using a mixed-methods design. Patient engagement is a unique methodological approach that will lay the groundwork for future studies in patient-centered outcomes research.

Agency for Healthcare Research and Quality (AHRQ) 1K18HS023434-01A1  

Byham-Gray (PI)
9/1/15-8/31/18:  $500,000.00

Patient-Centered Approach to Exploring Protein-Energy Wasting in Hemodialysis

Description: The goals of our funded study were to 1) quantitatively assess which of the most meaningful etiological factors identified by patients/ stakeholders are the strongest determinants for PEW among incident dialysis patients in the Comprehensive Dialysis Study (CDS) data set, 2) examine whether a diagnosis of PEW predicts patient-centered outcomes (PCOs) among incident dialysis patients in the CDS dataset, and 3)  critically evaluate, with patients/stakeholders, recently developed algorithms/guidelines in light of findings from goals 1 and 2 to determine their clinical relevance in reversing and/or preventing PEW and improving PCOs

School of Health Profession’s Intramural Bridge Grant

Byham-Gray (PI)
7/1/16-12/31/17: $35,000.00

Exploring Daily Activity and Total Energy Expenditure in the Adult Hemodialysis Population: A pilot study.

Description:  We have investigated one of the largest components of metabolic rate (e.g., calorie needs at rest), but this only explains part of the total energy requirements.  We have not yet examined the calories expended during routine physical activity, and thus, determine its contribution to total energy expenditure (TEE).  An accurate estimation of TEE in dialysis patients will lead to a significant reduction in the inappropriate administration of medical and nutritional therapies. The objective for this proposal was to investigate the TEE in a sample of patients maintained on hemodialysis and compare them to healthy individuals using the latest technologies.  Our central hypothesis is that the amount of energy expended during physical activity is significantly different in hemodialysis patients than in the healthy subjects.  The findings of this novel project will help in establishing more appropriate treatment regimens by providing more effective medical and nutritional care, and therefore, improving patient outcomes.

National Institutes of Diabetes and Digestive Diseases and Kidney Diseases (NIDDK): 1R15DK090593-01A1; 6R15DK090593-02; 3R15DK090593-02S1

Byham-Gray (PI)
9/25/12-8/31/15: $500,000.00

Development and Validation of a Predictive Energy Equation in Hemodialysis

Description: The goals of this study were 1) to determine what clinical factors predict EE in patients diagnosed with stage 5 CKD on MHD; 2) to develop and validate a predictive energy equation that incorporates all of the influencing clinical factors measured in stage 5 CKD patients on MHD; and 3) to further test the clinical utility and application of this equation

Academy of Nutrition & Dietetics   

Byham-Gray (PI)
7/1/14-6/30/16:  $2000.00

Validation of a Handheld Indirect Calorimeter in Patients Diagnosed with Stage 5 Chronic Kidney Disease on Maintenance Hemodialysis

Description: The primary goal of this study was to validate a low-cost handheld IC device (MedGem®) in a pilot sample of patients diagnosed with stage 5 CKD on maintenance hemodialysis (MHD); thereby determining the reliability for use as an alternative to measuring REE in this unique population.

Professional Achievements

Huddleson Award (along with Drs. Anna Parker and Robert Denmark)
Foundation of the Academy of Nutrition and Dietetics
10/2015

Presidential Citation for Outstanding Achievement
University of Delaware, College of Health Sciences
11/2010

Excellence in Teaching Award
RBHS (formerly UMDNJ)-SHRP
5/2010

Joel D. Kopple Award
National Kidney Foundation-Council on Renal Nutrition
4/2010

Susan C. Knapp Excellence in Education Award
National Kidney Foundation-Council on Renal Nutrition
4/2009

Outstanding Service Award
Academy of Nutrition and Dietetics (AND)-Renal Dietitians Dietetic Practice Group (RPG)
10/2007

Dean’s Excellence in Research Award
RBHS (formerly UMDNJ)-SHRP
5/2006

Outstanding Service Award
Academy of Nutrition and Dietetics-Renal Practice Group
10/2000

Selected Publications

Bailey, A, Eltawil, M, Gohel, S, Byham-Gray, LD. Machine Learning Models Using Non-Linear Techniques Improve The Prediction Of Resting Energy Expenditure In Individuals Receiving Hemodialysis. Ann Med.  DOI: 10.1080/07853890.2023.2238182 (in press).

Bailey A, Brody R, Sackey J, Parrott JS, Peters E, Byham-Gray LD. Current methods for developing predictive energy equations in maintenance dialysis are imprecise. Ann Med. 2022;54(1):909-920. doi: 10.1080/07853890.2022.2057581.

Rothpletz-Puglia, P, Brown, TL, Peters, E, Thomas-Hawkins, C, Kaplan, J, Myslinski, MJ, Mysliwiec, J, Parrott, JS, Byham-Gray, LD. Functional Status and Engagement in Physical Activity Among Maintenance Dialysis Patients: A Mixed Methods. Kidney Med 2022; 4(6): doi: 10.1016/ j. xkme.2022.100469.

Byham-Gray, LD, Peters, EN, Rothpletz-Puglia, P.  Patient-centered model for protein-energy wasting:  Stakeholder deliberative panels. 2020 Mar;30(2):137-144. doi: 10.1053/j.jrn.2019.06.001.

Byham-Gray, LD, Parrott, JS, Peters, EN, Gould-Fogerite, SG, Hand, RK, Ahrens, S, Marcus, AF, Fiutem, JJ. Modeling a predictive energy equation specific for maintenance hemodialysis.  2018 Mar;42(3):587-596. doi: 10.1177/0148607117696942.