Comorbidity and Cancer Disease Rates among Those at High-Risk for Alzheimer’s Disease: A Population Database Analysis
David Valentine,
Craig C. Teerlink,
James M. Farnham,
Kerry Rowe,
Heydon Kaddas,
JoAnn Tschanz,
John S. K. Kauwe and
Lisa A. Cannon-Albright ()
Additional contact information
David Valentine: Department of Biology, Brigham Young University, Provo, UT 84602, USA
Craig C. Teerlink: Genetic Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT 84132, USA
James M. Farnham: Genetic Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT 84132, USA
Kerry Rowe: National Oncology Program, Veterans Administration, Durham, NC 27705, USA
Heydon Kaddas: Genetic Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT 84132, USA
JoAnn Tschanz: Department of Psychology, Utah State University, Logan, UT 84322, USA
John S. K. Kauwe: Department of Biology, Brigham Young University, Provo, UT 84602, USA
Lisa A. Cannon-Albright: Genetic Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT 84132, USA
IJERPH, 2022, vol. 19, issue 24, 1-9
Abstract:
(1) Importance: Alzheimer’s disease (AD) is complex and only partially understood. Analyzing the relationship between other more treatable or preventable diseases and AD may help in the prevention and the eventual development of treatments for AD. Risk estimation in a high-risk population, rather than a population already affected with AD, may reduce some bias in risk estimates. (2) Objective: To examine the rates of various comorbidities and cancers in individuals at high-risk for AD, but without a clinical diagnosis, relative to individuals from the same population with normal AD risk. (3) Design, Setting, and Participants: We conducted a study using data from the Utah Population Database (UPDB). The UPDB contains linked data from the Utah Cancer Registry, Utah death certificates, the Intermountain Health patient population, and the University of Utah Health patient population. Subjects were selected based on the availability of ancestral data, linked health information, and self-reported biometrics. (4) Results: In total, 75,877 participants who were estimated to be at high risk for AD based on family history, but who did not have an active AD diagnosis, were analyzed. A lower incidence of diabetes (RR = 0.95, 95% CI [0.92,0.97], p < 0.001), hypertension (RR = 0.97, 95% CI [0.95,0.99], p < 0.001), and heart disease (RR = 0.95, 95% CI [0.93,0.98], p < 0.001) was found. There was no difference in rates of cerebrovascular disease or other forms of dementia. Of the 15 types of cancer analyzed: breast (RR = 1.23, 95% CI [1.16, 1.30], p < 0.001); colorectal (RR = 1.30, 95% CI [1.21, 1.39], p < 0.001); kidney (RR = 1.49, 95% CI (1.29, 1.72), p < 0.001); lung (RR = 1.25, 95% CI [1.13, 1.37], p < 0.001); non-Hodgkin’s Lymphoma (RR = 1.29, 95% CI [1.15, 1.44], p < 0.001); pancreas (RR = 1.34, 95% CI [1.16, 1.55], p < 0.001); stomach (RR = 1.59, 95% CI [1.36, 1.86], p < 0.001); and bladder (RR = 1.40, 95% CI [1.25, 1.56], p < 0.001), cancers were observed in significant excess among individuals at high-risk for AD after correction for multiple testing. (5) Conclusions and Relevance: Since age is the greatest risk factor for the development of AD, individuals who reach more advanced ages are at increased risk of developing AD. Consistent with this, people with fewer comorbidities earlier in life are more likely to reach an age where AD becomes a larger risk. Our findings show that individuals at high risk for AD have a decreased incidence of various other diseases. This is further supported by our finding that our high-risk group was also found to have an increased incidence of various cancers, which also increase in risk with age. There is the possibility that a more meaningful or etiological relationship exists among these various comorbidities. Further research into the etiological relationship between AD and these comorbidities may elucidate these possible interactions.
Keywords: Alzheimer’s disease; family history; UPDB; comorbidity; cancer; hypertension; diabetes; dementia (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
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