Androgen deprivation therapy and cognitive decline-associations with brain connectomes, endocrine status, and risk genotypes.

BACKGROUND: Evidence suggests that prostate cancer (PC) patients undergoing androgen deprivation therapy (ADT) are at risk for cognitive decline (CD), but the underlying mechanisms are less clear. In the present study, changes in cognitive performance and structural brain connectomes in PC patients undergoing ADT were assessed, and associations of cognitive changes with endocrine status and risk genotypes were explored. METHODS: Thirty-seven PC patients underwent cognitive assessment, structural MRI, and provided blood samples prior to ADT and after 6 months of treatment. Twenty-seven age- and education-matched healthy controls (HCs) underwent the same assessments. CD was determined using a standardized regression-based approach and defined as z-scores ≤ -1.64. Changes in brain connectomes were evaluated using graph theory. Associations of CD with testosterone levels and genotypes (APOE, COMT, BDNF) were explored. RESULTS: Compared with HCs, PC patients demonstrated reduced testosterone levels (p < 0.01) and higher rates of decline for 13 out of 15 cognitive outcomes, with three outcomes related to two cognitive domains, i.e., verbal memory and visuospatial learning and memory, reaching statistical significance (p ≤ 0.01-0.04). Testosterone level changes did not predict CD. COMT Met homozygote PC patients evidenced larger reductions in visuospatial memory compared with Val carriers (p = 0.02). No between-group differences were observed in brain connectomes across time, and no effects were found of APOE and BDNF. CONCLUSIONS: Our results indicate that PC patients undergoing ADT may evidence CD, and that COMT Met homozygotes may be at increased risk of CD. The results did not reveal changes in brain connectomes or testosterone levels as underlying mechanisms. More research evaluating the role of ADT-related disruption of the dynamics of the hypothalamic-pituitary-gonadal axis is needed.

Cognitive training for improving executive function in chemotherapy-treated breast cancer survivors.

BACKGROUND: A majority of breast cancer (BC) survivors, particularly those treated with chemotherapy, experience long-term cognitive deficits that significantly reduce quality of life. Among the cognitive domains most commonly affected include executive functions (EF), such as working memory, cognitive flexibility, multitasking, planning, and attention. Previous studies in other populations have shown that cognitive training, a behavioral method for treating cognitive deficits, can result in significant improvements in a number of cognitive skills, including EF. MATERIALS AND METHODS: In this study, we conducted a randomized controlled trial to investigate the feasibility and preliminary effectiveness of a novel, online EF training program in long-term BC survivors. A total of 41 BC survivors (21 active, 20 wait list) completed the 48 session training program over 12 weeks. The participants were, on average, 6 years after therapy. RESULTS: Cognitive training led to significant improvements in cognitive flexibility, verbal fluency and processing speed, with marginally significant downstream improvements in verbal memory as assessed via standardized measures. Self-ratings of EF skills, including planning, organizing, and task monitoring, also were improved in the active group compared with the wait list group. CONCLUSIONS: Our findings suggest that EF skills may be improved even in long-term survivors by using a computerized, home-based intervention program. These improvements may potentially include subjective EF skills, which suggest a transfer of the training program to real-world behaviors.

Anomalous gray matter structural networks in major depressive disorder.

BACKGROUND: Major depressive disorder (MDD) is characterized by abnormalities in structure, function, and connectivity in several brain regions. Few studies have examined how these regions are organized in the brain or investigated network-level structural aberrations that might be associated with depression. METHODS: We used graph analysis to examine the gray matter structural networks of individuals diagnosed with MDD (n = 93) and a demographically similar healthy comparison group (n = 151) with no history of psychopathology. The efficiency of structural networks for processing information was determined by quantifying local interconnectivity (clustering) and global integration (path length). We also compared the groups on the contributions of high-degree nodes (i.e., hubs) and regional network measures, including degree (number of connections in a node) and betweenness (fraction of short path connections in a node). RESULTS: Depressed participants had significantly decreased clustering in their brain networks across a range of network densities. Compared with control subjects, depressed participants had fewer hubs primarily in medial frontal and medial temporal areas, had higher degree in the left supramarginal gyrus and right gyrus rectus, and had higher betweenness in the right amygdala and left medial orbitofrontal gyrus. CONCLUSIONS: Networks of depressed individuals are characterized by a less efficient organization involving decreased regional connectivity compared with control subjects. Regional connections in the amygdala and medial prefrontal cortex may play a role in maintaining or adapting to depressive pathology. This is the first report of anomalous large-scale gray matter structural networks in MDD and provides new insights concerning the neurobiological mechanisms associated with this disorder.