Obesity, Psychological Distress, and Resting State Connectivity of the Hippocampus and Amygdala Among Women With Early-Stage Breast Cancer

Association between malnutrition and anxiety in cancer patients-a retrospective study

INTRODUCTION

The total number of cancer-related deaths and new cancer cases in 2020 was 19.3 billion and 10.8 billion, respectively. Therefore, prevention, diagnosis, and treatment of neoplastic disease, as well as management of comorbidities, are of paramount importance. In this regards, poor nutritional status and mental disorders are comorbidity conditions frequently observed in cancer patients. The aim of this study was to assess the association between malnutrition and anxiety in hospitalized adult cancer patients.

METHODS

This is a retrospective study. Nutrition Risk Screening (NRS) 2002, body mass index (BMI), daily calorie intake, and weight difference between admission and discharge were used to evaluate nutritional status. Anxiety was assessed with the Hospital Anxiety and Depression Scale (HADS-A). Ordered logistic and linear logistic regressions adjusted for sex and age were used to estimate the association between malnutrition and anxiety in cancer patients.

RESULTS

A total of 90 patients were included. Higher NRS risk [aβ = 0.85; 95% CI (0.28-1.42); p = 0.004], disease stage [aβ = 0.77; 95% CI (0.08-1.47); p = 0.029], and cachexia [aβ = 2.20; 95% CI (0.75-3.65); p = 0.003] were significantly associated with anxiety symptoms. Moreover, cancer site different than gastrointestinal cancers was associated with a lower risk of anxiety symptoms [aβ =  - 2.11; 95% CI (- 3.55/ - 0.66); p = 0.005].

CONCLUSION

In the current study, we found a relatively high rate of malnourished patients, indicating the importance of routinely assessing nutritional status and screening cancer patients for mental health issues. This approach could help physicians to treat both in a timely manner, thereby significantly reducing the burden of the disease and improving the quality of life of patients.

Independent effects of posttraumatic stress disorder diagnosis and metabolic syndrome status on prefrontal cortical thickness and subcortical gray matter volumes

INTRODUCTION

Posttraumatic stress disorder (PTSD) and metabolic syndrome (MetS) are associated with overlapping brain structural differences. These often involve brain structures involved in the regulation of appetite, food intake, satiety, and reward processing. We examined the individual and interactive effects of PTSD diagnosis and MetS on cortical thickness and subcortical gray matter volumes in patients with PTSD (n = 104) compared to trauma-exposed controls (n = 97).

METHODS

Multivariate models were constructed for FreeSurfer-generated prefrontal cortical thickness and subcortical gray matter regions-of-interest (ROIs) to explore the effects of PTSD diagnosis and MetS as predictors, adjusting for relevant socio-demographic and clinical covariates. Individual prefrontal cortical and subcortical limbic ROIs were also selected based on a priori evidence of their involvement in both PTSD and MetS.

RESULTS

The mean age of the sample (n = 201; 78% female) was 41.6 (SD, 13.1) years. PTSD and MetS status showed independent associations with prefrontal cortical thickness and subcortical gray matter volumes across multiple ROIs, adjusting for age, sex, scanner sequence, alcohol, and tobacco use.

CONCLUSIONS

PTSD and MetS are independently associated with brain structural differences, including thinner prefrontal cortical thickness and smaller subcortical gray matter volumes, across multiple ROIs implicated in the hedonic and homeostatic regulation of food intake.

Breast cancer survivors with pain: an examination of the relationships between body mass index, physical activity, and symptom burden

PURPOSE

Overweight and obesity are common for breast cancer survivors and associated with high symptom burden (i.e., pain, fatigue, depressive symptoms). Physical activity may protect breast cancer survivors with higher body mass indexes (BMI) from increased symptoms. However, the role of physical activity in buffering the relationship between higher BMI and greater symptoms is unclear.

METHODS

Baseline data from a randomized trial investigating Pain Coping Skills Training among breast cancer survivors (N = 327) with pain were used to examine the relationship between self-reported BMI (kg/m2) and physical activity level (Rapid Assessment of Physical Activity; suboptimal vs. optimal) with pain (Brief Pain Inventory; severity and interference), fatigue (PROMIS-Fatigue short form), and depressive symptoms (Center for Epidemiological Studies Depression Scale). Analyses were conducted in SPSS. Hayes PROCESS macro (Model 1) assessed whether physical activity moderated the relationship between BMI and symptoms.

RESULTS

Lower BMI (B = .06, p < .01) and optimal physical activity (B =  - .69, p < .01) were independently associated with lower pain interference. Lower BMI was also associated with lower pain severity (B = .04, p < .001). Neither BMI nor physical activity was associated with fatigue or depressive symptoms. Physical activity did not moderate the relationship between BMI and symptoms.

CONCLUSIONS

Among breast cancer survivors experiencing pain, higher BMI and being less physically active were related to greater pain (i.e., severity and/or interference). Physical activity did not buffer the relationships between BMI and pain, fatigue, and depressive symptoms, suggesting that physical activity alone may not be sufficient to influence the strength of the relationships between BMI and symptoms.

Cardiorespiratory fitness is associated with hippocampal resting state connectivity in women newly diagnosed with breast cancer

Background

Breast cancer and its treatment are associated with aberrant patterns of resting state functional connectivity (rsFC) between the hippocampus and several areas of the brain, which may account for poorer cognitive outcomes in patients. Higher cardiorespiratory fitness (CRF) has been associated with enhanced rsFC and cognitive performance; however, these associations have not been well studied in breast cancer. We examined the relationship between CRF, rsFC of the hippocampus, and cognitive performance among women newly diagnosed with breast cancer.

Methods

Thirty-four postmenopausal women newly diagnosed with Stage 0-IIIa breast cancer (Mage = 63.59 ± 5.73) were enrolled in a 6-month randomized controlled trial of aerobic exercise vs. usual care. During baseline assessments, participants completed functional brain imaging, a submaximal CRF test, and cognitive testing. Whole-brain, seed-based analyses were used to examine the relationship between CRF and hippocampal rsFC, with age, years of education, and framewise displacement included as covariates. Cognition was measured with a battery of validated neurocognitive measures, reduced to seven composite factors.

Results

Higher CRF was positively associated with greater rsFC of the hippocampus to a cluster within the dorsomedial and dorsolateral frontal cortex (z-max = 4.37, p = 0.003, cluster extent = 1,020 voxels). Connectivity within cluster peaks was not significantly related to cognitive factors (all ps > 0.05).

Discussion

CRF was positively associated with hippocampal rsFC to frontal cortex structures, comprising a network of regions commonly suppressed in breast cancer. Future longitudinal research is needed to explore whether baseline rsFC predicts long-term cognitive resilience in breast cancer.

A training program for researchers in population neuroimaging: Early experiences

Recent advances in neuroimaging create groundbreaking opportunities to better understand human neurological and psychiatric diseases, but also bring new challenges. With the advent of more and more sophisticated and efficient multimodal image processing software, we can now study much larger populations and integrate information from multiple modalities. In consequence, investigators that use neuroimaging techniques must also understand and apply principles of population sampling and contemporary data analytic techniques. The next generation of neuroimaging researchers must be skilled in numerous previously distinct disciplines and so a new integrated model of training is needed. This tutorial presents the rationale for such a new training model and presents the results from the first years of the training program focused on population neuroimaging of Alzheimer's Disease. This approach is applicable to other areas of population neuroimaging.