UMB Digital Archive

Scholarship & History

The UMB Digital Archive is a service of the Health Sciences and Human Services Library (HS/HSL) that collects, preserves, and distributes the academic works of the University of Maryland, Baltimore. It is a place that digitally captures the historical record of the campus.

 

  • Family History, Genetic Risk Factors, and Risk of Multiple Primary Cancers

    He, Shisi; Berndt, Sonja I.; Mitchell, Braxton D. (2023)
    Multiple primary cancers (MPC), often called second cancers, occur when more than one tumor arises in a patient from different cellular origins at different sites or presents with different histologies or morphologies [1, 2]. With improvements in the early detection and treatment of cancer over the years, both the population of cancer survivors and the chance of developing a new primary cancer has grown [3-5]. However, the etiology of MPC is not well understood. Established and suspected risk factors for MPC include host-related factors (e.g., primary immune deficiency), medical and lifestyle factors (e.g., immunosuppression, chemotherapy), environmental exposures (e.g., arsenic), and genetic factors (e.g., Lynch syndrome)[1]. However, many of the established factors, such as radiation and chemotherapy, only account for a small fraction of the risk [6]. Most research investigating genetic factors for MPC has focused on known cancer syndromes (e.g., Li-Fraumeni syndrome) and rare genetic variants with little research on the contribution of common variants. To understand the heritable risk of MPC, the first project aimed to understand if a family history of cancer is a risk factor for MPC. I also tested if there was a linear relationship between the number of cancers in the family history and MPC. The second project aimed to find common genetic variants associated with MPC. Molecular factors, such as inflammatory factors, insulin-like growth factor, and telomere length (TL), are also hypothesized to play a role in the development of cancer. Telomeres are DNA-nucleoprotein complex at the termini of eukaryotic chromosomes that protect the chromosome from degradation [7]. Telomeres are important in cell division and senescence and critical for chromosomal stability. Progressive telomere shortening occurs naturally with aging, and telomere attrition has been associated with some age-related diseases [7]; however, the relationship with cancer is complex. Despite the expectation of higher cancer risk with shortened telomere length, studies of measured TL have not always found that to be true. A meta-analysis including 121 studies conducted on blood cells did not find associations between TL and overall cancer risk; however, they found both positive and negative associations when stratified by cancer type [8]. Previous studies focused on certain primary cancers, while the relationship between TL and the risk of MPC is not well understood. Association studies with measured TL may be more susceptible to confounding by environmental and lifestyle factors. TL is highly heritable [9, 10], and 197 common genetic variants have been found associated with the leukocyte TL [11]. The advantage of using genetically predicted TL is that it uses germline genotypes that are present from birth and are uncorrelated with environmental exposures. The third study aimed to understand whether genetically predicted TL is associated with the risk of MPC. In summary, the overall objective of this dissertation is to provide insight into the etiology of MPC. The specific aims of the study are to: 1. To examine the association between a family history of cancers and the risk of MPC 2. To identify common genetic variants associated with the risk of MPC 3. To examine the association between genetically-predicted telomere length and MPC To our knowledge, this dissertation project is one of the first studies to examine the role of family history, genetically predicted telomere length and common genetic variants in relationship to the risk of MPC. The results will contribute to our understanding of the etiology of MPC and may suggest biological mechanisms and potential biomarkers for future studies.
  • County-level factors associated with a mismatch between opioid overdose mortality and availability of opioid treatment facilities

    Rizk, John; Saini, Jannat; Kim, Kyungha; Pathan, Uzma; Qato, Danya (2024-04-05)
    Opioid overdose deaths in the United States remain a major public health crisis. Little is known about counties with high rates of opioid overdose mortality but low availability of opioid use disorder (OUD) treatment facilities. We sought to identify characteristics of United States (US) counties with high rates of opioid overdose mortality and low rates of opioid treatment facilities. Rates of overdose mortality from 3,130 US counties were compared with availability of opioid treatment facilities that prescribed or allowed medications for OUD (MOUD), from 2018- 2019. The outcome variable, “risk-availability mismatch” county, was a binary indicator of a high rate (above national average) of opioid overdose mortality with a low (below national average) rate of opioid treatment facilities. Covariates of interest included county-level sociodemographics and rates of insurance, unemployment, educational attainment, poverty, urbanicity, opioid prescribing, depression, heart disease, Gini index, and Theil index. Multilevel logistic regression, accounting for the clustering of counties within states, was used to determine associations with being a “risk-availability mismatch” county. Of 3,130 counties, 1,203 (38.4%) had high rates of opioid overdose mortality. A total of 1,098 counties (35.1%) lacked a publicly-available opioid treatment facility in 2019. In the adjusted model, counties with an additional 1% of: white residents (odds ratio, OR, 1.02; 95% CI, 1.01-1.03), unemployment (OR, 1.11; 95% CI, 1.05-1.19), and residents without insurance (OR, 1.04; 95% CI, 1.01-1.08) had increased odds of being a mismatch county. Counties that were metropolitan (versus non-metropolitan) had an increased odds of being a mismatch county (OR, 1.85; 95% CI, 1.45-2.38). Assessing mismatch between treatment availability and need provides useful information to characterize counties that require greater public health investment. Interventions to reduce overdose mortality are unlikely to be effective if they do not take into account diverse upstream factors, including sociodemographics, disease burden, and geographic context of communities.
  • Associations of Metabolites with Physical Activity in the Amish

    Tiner, Jessica; Beitelshees, Amber L.; Mitchell, Braxton D. (2024-04-05)
  • (Some) Known Stroke Susceptibility Loci Show Differential Effects by Age

    McArdle, Patrick F.; Ryan, K.; Nabi, N.; Gaynor, Brady J.; Cole, John Walden; Mitchell, Braxton D.; Kittner, Steven J. (2024-04-24)
  • Using Best Practice Advisory to Boost Compliance Rate with Program Guidelines

    Omoruyi, Adeola; Connolly, Mary Ellen; Yedla, Saleena; Jones Swings, Taylor (2024-04-09)

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