About

Kristen E. Howell, PhD, MPH, is an Assistant Professor in Epidemiology & Biostatistics at the School of Public Health, Texas A&M University. Her educational background includes a BS in Biology from the University of Oklahoma, an MPH in Epidemiology from Emory University, and a PhD in Epidemiology from the University of Memphis. Her research focuses on health outcomes among adolescents and young adults with sickle cell disease, including health literacy, transition to adult care, and barriers to evidence-based care. She has contributed to studies assessing transition readiness, healthcare utilization, and the use of wearable technology in pediatric cancer survivors. Dr. Howell's work aims to improve health care strategies and outcomes for vulnerable populations, particularly those affected by sickle cell disease.

Research topics

• Medicine
• Internal medicine
• Biology
• Genetics
• Virology
• Oncology

Selected publications

• Identification and Developmental Analysis of the Facial Characteristics Associated with Sickle Cell Disease using Machine Learning

  medRxiv · 2026-03-10

  articleOpen access

  Abstract Background Sickle cell disease (SCD) is a common inherited genetic disorder and contributor to global childhood mortality and morbidity. In the Democratic Republic of the Congo, nearly 40,000 newborns, approximately 2% of all newborns, are estimated to be affected each year. Despite progress in the treatment and care of the disorder, its detection and management in lower-resource settings remain challenging. Methods We collected 308 front facing photos of patients and their age-and sex-matched controls aged from 5 months to 19 years in the Democratic Republic of the Congo. Facial features were extracted and categorized into geometric and texture-based descriptors. A support vector machine ranked features according to their relevance for distinguishing SCD patients from controls. Results The facial analysis algorithm identified eight geometric and six texture discriminative features that were significantly different between the cohorts. An explainable machine learning model identified sickle cell disease with 79.5% accuracy using a combination of six geometric features: distance between medial and lateral canthi, angle at nasal ala, distance from nasion to philtrum, distance from medial canthi to the columella, distance from columella to the lower lip, and distance between nasal alae. SCD related features were identified to become increasingly discriminative with age. Conclusion These findings demonstrate the potential machine learning based methodologies to be leveraged to inform point-of-care tools in the screening and management of sickle cell disease. The discriminative facial features identified here may provide further opportunities into Artificial-Intelligence based diagnostics and personalized care strategies of sickle cell disease.

  PublisherDOI

• Spinal Orthotics

  2025-05-19

  book-chapterSenior author

  Upon completing this chapter, the reader should: Understand common spinal pathologies necessitating orthotic treatment. Recall basic indications, contraindications, and mechanics of spinal orthoses. Recall therapeutic implications of spinal pathologies and orthotic usage. Understand the role of chest orthoses for pectus carinatum. Understand benefits from the partnership between orthotist and therapist for management success.

  PublisherDOI

• Author response: Genetic inactivation of zinc transporter SLC39A5 improves liver function and hyperglycemia in obesogenic settings

  2024-12-13

  peer-reviewOpen access
  PublisherDOI

• Using an mHealth approach to collect patient-generated health data for predicting adverse health outcomes among adult survivors of childhood cancer

  Frontiers in Oncology · 2024-05-10 · 6 citations

  articleOpen access1st author

  Introduction: Cancer therapies predispose childhood cancer survivors to various treatment-related late effects, which contribute to a higher symptom burden, chronic health conditions (CHCs), and premature mortality. Regular monitoring of symptoms between clinic visits is useful for timely medical consultation and interventions that can improve quality of life (QOL). The Health Share Study aims to utilize mHealth to collect patient-generated health data (PGHD; daily symptoms, momentary physical health status) and develop survivor-specific risk prediction scores for mitigating adverse health outcomes including poor QOL and emergency room admissions. These personalized risk scores will be integrated into the hospital-based electronic health record (EHR) system to facilitate clinician communications with survivors for timely management of late effects. Methods: This prospective study will recruit 600 adult survivors of childhood cancer from the St. Jude Lifetime Cohort study. Data collection include 20 daily symptoms via a smartphone, objective physical health data (physical activity intensity, sleep performance, and biometric data including resting heart rate, heart rate variability, oxygen saturation, and physical stress) via a wearable activity monitor, patient-reported outcomes (poor QOL, unplanned healthcare utilization) via a smartphone, and clinically ascertained outcomes (physical performance deficits, onset of/worsening CHCs) assessed in the survivorship clinic. Participants will complete health surveys and physical/functional assessments in the clinic at baseline, 2) report daily symptoms, wear an activity monitor, measure blood pressure at home over 4 months, and 3) complete health surveys and physical/functional assessments in the clinic 1 and 2 years from the baseline. Socio-demographic and clinical data abstracted from the EHR will be included in the analysis. We will invite 20 cancer survivors to investigate suitable formats to display predicted risk information on a dashboard and 10 clinicians to suggest evidence-based risk management strategies for adverse health outcomes. Analysis: Machine and statistical learning will be used in prediction modeling. Both approaches can handle a large number of predictors, including longitudinal patterns of daily symptoms/other PGHD, along with cancer treatments and socio-demographics. Conclusion: The individualized risk prediction scores and added communications between providers and survivors have the potential to improve survivorship care and outcomes by identifying early clinical presentations of adverse events.

  PublisherOA PDFDOI

• P1.13A.09 RYZ101 (225Ac-DOTATATE) + Carboplatin + Etoposide + Atezolizumab in Somatostatin Receptor Expressing Extensive-Stage Small-Cell Lung Cancer

  Journal of Thoracic Oncology · 2024-10-01 · 1 citations

  articleOpen access
  PublisherOA PDFDOI

• Genetic inactivation of zinc transporter SLC39A5 improves liver function and hyperglycemia in obesogenic settings

  eLife · 2024-12-13 · 3 citations

  articleOpen access

  Recent studies have revealed a role for zinc in insulin secretion and glucose homeostasis. Randomized placebo-controlled zinc supplementation trials have demonstrated improved glycemic traits in patients with type II diabetes (T2D). Moreover, rare loss-of-function variants in the zinc efflux transporter SLC30A8 reduce T2D risk. Despite this accumulated evidence, a mechanistic understanding of how zinc influences systemic glucose homeostasis and consequently T2D risk remains unclear. To further explore the relationship between zinc and metabolic traits, we searched the exome database of the Regeneron Genetics Center-Geisinger Health System DiscovEHR cohort for genes that regulate zinc levels and associate with changes in metabolic traits. We then explored our main finding using in vitro and in vivo models. We identified rare loss-of-function (LOF) variants (MAF <1%) in Solute Carrier Family 39, Member 5 ( SLC39A5 ) associated with increased circulating zinc (p=4.9 × 10 -4 ). Trans-ancestry meta-analysis across four studies exhibited a nominal association of SLC39A5 LOF variants with decreased T2D risk. To explore the mechanisms underlying these associations, we generated mice lacking Slc39a5. Slc39a5 -/- mice display improved liver function and reduced hyperglycemia when challenged with congenital or diet-induced obesity. These improvements result from elevated hepatic zinc levels and concomitant activation of hepatic AMPK and AKT signaling, in part due to zinc-mediated inhibition of hepatic protein phosphatase activity. Furthermore, under conditions of diet-induced non-alcoholic steatohepatitis (NASH), Slc39a5 -/- mice display significantly attenuated fibrosis and inflammation. Taken together, these results suggest SLC39A5 as a potential therapeutic target for non-alcoholic fatty liver disease (NAFLD) due to metabolic derangements including T2D.

  PublisherDOI

• Using mHealth Technology to Evaluate Daily Symptom Burden Among Adult Survivors of Childhood Cancer: A Feasibility Study

  Preprints.org · 2024-07-30

  preprintOpen access1st authorCorresponding

  Background: Cancer therapies predispose survivors to a high symptom burden. This study utilized mobile health (mHealth) technology to assess the feasibility of collecting daily symptoms from adult survivors of childhood cancer and evaluate symptom fluctuation and associations with future health-related quality-of-life (HRQOL). Methods: A prospective study using an mHealth platform to distribute a 20-item cancer-related symptom survey (5 consecutive days each month) and an HRQOL survey (the day after symptom survey) over 3 consecutive months to participants from the Childhood Cancer Survivor Study. PROMIS-29 Profile and Neuro-QOL assessed HRQOL. Daily symptom burden was calculated by summing the severity (mild, moderate, or severe) of 20 symptoms. Univariate linear mixed-effects models analyzed total, person-to-person, day-to-day, and month-to-month variability for the burden of 20 individual symptoms. Multivariable linear regression analyzed the association between daily symptom burden in the first month and HRQOL in the third month, adjusting covariates. Results: Out of the 60 survivors invited, 41 participated in this study (68% enrollment rate); 83% reported their symptoms ≥3 times and 95% reported HRQOL, both in each week across 3 months. Variability of daily symptom burden differed from person-to-person (74%), day-to-day (18%), and month-to-month (8%). Higher first-month symptom burden was associated with poorer HRQOL related to anxiety (regression coefficient: 6.56; 95%CI: 4.10-9.02), depression (6.32; 95%CI: 3.18-9.47), fatigue (7.93; 95%CI: 5.11-10.80), sleep (6.07; 95%CI: 3.43-8.70), pain (5.16; 95%CI: 2.11-8.22), and cognitive function (-6.89; 95%CI: -10.00 to -3.79) in the third month. Conclusion: Daily assessment reveals fluctuations in symptomology, and higher symptom burden was associated with poorer HRQOL in the future. Utilizing mHealth technology for daily symptom assessment improves our understanding of symptom dynamics and sources of variability.

  PublisherOA PDFDOI

• Using mHealth Technology to Evaluate Daily Symptom Burden among Adult Survivors of Childhood Cancer: A Feasibility Study

  Cancers · 2024-08-27 · 6 citations

  articleOpen access1st author

  BACKGROUND: Cancer therapies predispose survivors to a high symptom burden. This study utilized mobile health (mHealth) technology to assess the feasibility of collecting daily symptoms from adult survivors of childhood cancer to evaluate symptom fluctuation and associations with future health-related quality-of-life (HRQOL). METHODS: This prospective study used an mHealth platform to distribute a 20-item cancer-related symptom survey (5 consecutive days each month) and an HRQOL survey (the day after the symptom survey) over 3 consecutive months to participants from the Childhood Cancer Survivor Study. These surveys comprised a PROMIS-29 Profile and Neuro-QOL assessed HRQOL. Daily symptom burden was calculated by summing the severity (mild, moderate, or severe) of 20 symptoms. Univariate linear mixed-effects models were used to analyze total, person-to-person, day-to-day, and month-to-month variability for the burden of 20 individual symptoms. Multivariable linear regression was used to analyze the association between daily symptom burden in the first month and HRQOL in the third month, adjusted for covariates. RESULTS: Out of the 60 survivors invited, 41 participated in this study (68% enrollment rate); 83% reported their symptoms ≥3 times and 95% reported HRQOL in each study week across 3 months. Variability of daily symptom burden differed from person-to-person (74%), day-to-day (18%), and month-to-month (8%). Higher first-month symptom burden was associated with poorer HRQOL related to anxiety (regression coefficient: 6.56; 95% CI: 4.10-9.02), depression (6.32; 95% CI: 3.18-9.47), fatigue (7.93; 95% CI: 5.11-10.80), sleep (6.07; 95% CI: 3.43-8.70), pain (5.16; 95% CI: 2.11-8.22), and cognitive function (-6.89; 95% CI: -10.00 to -3.79) in the third month. CONCLUSIONS: Daily assessment revealed fluctuations in symptomology, and higher symptom burden was associated with poorer HRQOL in the future. Utilizing mHealth technology for daily symptom assessment improves our understanding of symptom dynamics and sources of variability.

  PublisherOA PDFDOI

• Depression, sleep and pain affect instrumental activities of daily living through cognitive functioning in adults with sickle cell disease: A report from the Sickle Cell Disease Implementation Consortium

  British Journal of Haematology · 2024-11-20 · 4 citations

  articleOpen access

  Summary Depression, disrupted sleep and pain are common comorbidities in sickle cell disease. We tested (1) if these comorbidities are associated with attention/executive functioning, processing speed and instrumental activities of daily living (IADLs), which describe complex skills that support independence, and (2) if cognitive symptoms mediate the relationship between comorbidities and IADLs. Participants ( n = 2417) completed patient‐reported outcome measures through the Sickle Cell Disease Implementation Consortium. Mean age of participants was 28 years and HbSS/Sβ 0 genotypes were prevalent (73%). Comorbidities of depression, pain frequency and disrupted sleep were associated with processing speed and attention/executive functioning (all p < 0.01) when controlling for stroke and demographics. IADLs were associated with depression, pain, sleep, attention/executive functioning, income (<$25 000) (all p < 0.001) and genotype ( p = 0.0025) after controlling for covariates. The indirect effects of attention/executive functioning and processing speed were both significant ( p < 0.001) in mediation models that examined pathways between comorbidities and IADLs. Attention/executive functioning accounted for 17.5% of the relationship between depression and IADLs and sleep and IADLs. Processing speed explained 10% of the relationship between sleep and IADLs and 8% of the relationship between depression and IADLs. Managing comorbidities should be prioritized to mitigate cognitive symptoms and improve complex daily living skills.

  PublisherOA PDFDOI

• Gaps during pediatric to adult care transfer escalate acute resource utilization in sickle cell disease

  Blood Advances · 2024-05-29 · 9 citations

  articleOpen access1st authorCorresponding

  ABSTRACT: Guidelines recommend transfer to adult health care within 6 months of completing pediatric care; however, this has not been studied in sickle cell disease (SCD). We hypothesized that longer transfer gaps are associated with increased resource utilization. Transfer gaps were defined as the time between the last pediatric and first adult visits. We estimated the association between varying transfer gaps and the rates of inpatient, emergency department (ED), and outpatient visits, using negative binomial regression. Health care utilization was evaluated in a mid-south comprehensive program for a follow-up period of up to 8 years (2012-2020) and was restricted to the first 2 years of adult health care. In total, 183 young adults (YAs) with SCD (51% male, 67% HbSS/HbSβ0-thalassemia) were transferred to adult health care between 2012 and 2018. YAs with transfer gaps ≥6 months compared with <2 months had 2.01 (95% confidence interval [CI], 1.31-3.11) times the rate of hospitalizations in the 8-year follow-up and 1.89 (95% CI, 1.17-3.04) when restricted to the first 2 years of adult health care. In the first 2 years of adult care, those with transfer gaps ≥6 months compared with <2 months, had 1.75 (95% CI, 1.10-2.80) times the rate of ED encounters. Those with gaps ≥2 to <6 months compared with <2 months had 0.71 (95 % CI, 0.53-0.95) times the rate of outpatient visits. Among YAs with SCD, a longer transfer gap was associated with increased inpatient and decreased outpatient encounters in adult health care and more ED encounters in the first 2 years of adult health care. Strategies to reduce the transfer gaps are needed.

  PublisherOA PDFDOI

Frequent coauthors

• Jane S. Hankins

  St. Jude Children's Research Hospital

  12 shared

• Joacy G. Mathias

  Duke University Hospital

  11 shared

• Jerlym S. Porter

  St. Jude Children's Research Hospital

  9 shared

• Aris N. Economides

  Regeneron (United States)

  8 shared

• Shek Man Chim

  Regeneron (United States)

  8 shared

• Alan R. Shuldiner

  Regeneron (United States)

  8 shared

• Sylvie Lantuéjoul

  Centre de Recherche en Cancérologie de Lyon

  8 shared

• Sheila Anderson

  St. Jude Children's Research Hospital

  7 shared

Education

• Doctor of Philosophy, Epidemiology and Biostatistics

  University of Memphis

  2021

• Master of Public Health, Epidemiology

  Emory University

  2018

• Bachelors of Science, Biology

  University of Oklahoma

  2016

Awards & honors

• University of Memphis School of Public Health Student Achiev…