Samantha J Bayer1, Gee Su Yang, Debra E Lyon. 1. Author Affiliations: Department of Biobehavioral Nursing Science, University of Florida College of Nursing, Gainesville.
Abstract
BACKGROUND: Depressive symptoms are highly prevalent in breast cancer patients. These symptoms can contribute to lower treatment adherence, increased healthcare charges, and higher mortality rates. Growing evidence suggests that genetic variations may be associated with depressive symptom susceptibility. OBJECTIVE: To comprehensively review current findings on the association of genetic variations with depressive symptoms in breast cancer patients. METHODS: A literature search was conducted using keywords such as gene variation, single-nucleotide polymorphism, depression/depressive symptoms, and breast cancer. Four hundred articles were retrieved from PubMed, Web of Science, CINAHL, and PsycINFO, yielding 9 full-text, data-based articles. The study quality was assessed using the STrengthening the REporting of Genetic Association studies guideline. RESULTS: Genetic polymorphisms in brain-derived neurotrophic factor (BDNF), interferon γ receptor 1 (IFNGR1), interleukin-6 (IL-6), tumor necrosis factor α (TNFA), and IL-1B were found to be associated with depressive symptoms among breast cancer patients. The role of serotonin transporter gene linked promotor region (5-HTTLPR) functional polymorphisms on depressive symptoms was inconclusive. The overall quality of reporting results and methods was medium. CONCLUSIONS: This is the first review of genetic variations related to differences in levels of depressive symptoms among breast cancer patients. Genetic polymorphisms in inflammatory, neuronal system, and signal transduction pathways can influence the susceptibility. However, more research regarding this topic is needed to further clarify genetic risk factors. IMPLICATIONS FOR PRACTICE: Healthcare providers may determine patients at higher risk of developing depression and symptom outcomes if genetic biomarkers with good sensitivity/specificity are provided. This knowledge can potentially help the development of personalized treatment and decision making for those patients.
BACKGROUND: Depressive symptoms are highly prevalent in breast cancer patients. These symptoms can contribute to lower treatment adherence, increased healthcare charges, and higher mortality rates. Growing evidence suggests that genetic variations may be associated with depressive symptom susceptibility. OBJECTIVE: To comprehensively review current findings on the association of genetic variations with depressive symptoms in breast cancer patients. METHODS: A literature search was conducted using keywords such as gene variation, single-nucleotide polymorphism, depression/depressive symptoms, and breast cancer. Four hundred articles were retrieved from PubMed, Web of Science, CINAHL, and PsycINFO, yielding 9 full-text, data-based articles. The study quality was assessed using the STrengthening the REporting of Genetic Association studies guideline. RESULTS: Genetic polymorphisms in brain-derived neurotrophic factor (BDNF), interferon γ receptor 1 (IFNGR1), interleukin-6 (IL-6), tumor necrosis factor α (TNFA), and IL-1B were found to be associated with depressive symptoms among breast cancer patients. The role of serotonin transporter gene linked promotor region (5-HTTLPR) functional polymorphisms on depressive symptoms was inconclusive. The overall quality of reporting results and methods was medium. CONCLUSIONS: This is the first review of genetic variations related to differences in levels of depressive symptoms among breast cancer patients. Genetic polymorphisms in inflammatory, neuronal system, and signal transduction pathways can influence the susceptibility. However, more research regarding this topic is needed to further clarify genetic risk factors. IMPLICATIONS FOR PRACTICE: Healthcare providers may determine patients at higher risk of developing depression and symptom outcomes if genetic biomarkers with good sensitivity/specificity are provided. This knowledge can potentially help the development of personalized treatment and decision making for those patients.