The Relationship between F 2 -Isoprostanes Plasma Levels and Depression Symptoms in Healthy Older Adults.
Karen M SavageLee GogartyAna LeaSaurenne DeleuilKaren NolidinKevin CroftCon StoughPublished in: Antioxidants (Basel, Switzerland) (2022)
The increasing proportion of older citizens in our society reflects a need to better understand age-related biological underpinnings of mood, as depression in older age may be under-diagnosed. Pre-clinical and human studies evidence a relationship between oxidative stress (OS) biomarkers in depression symptoms, and an influence of biological factors such as Body Mass Index (BMI), but focus has been clinical or younger samples, and less is known about patterns in healthy older adults. We investigated these associations with data derived from the Australian Research Council Longevity Study (ARCLI; ANZCTR12611000487910), in 568 healthy adults aged 60-75 years using F 2 -Isoprostanes plasma levels, and controlling for demographic factors, in assessing mood via the Beck Depression Inventory-II, Chalder Fatigue Scale, and General Health Questionnaire 12. Elevated F 2 -Isoprostanes contributed to depressed mood on the BDI-II and reduced general health on the GHQ-12. BMI was positively associated with Chalder Fatigue scores, yet better ratings on the GHQ-12. Females had significantly higher F 2 -Isoprostanes than males. The results suggest that in otherwise healthy older adults, mood and mental health are reduced with increases in oxidative stress markers, exhibiting similar patterns observed in clinical groups. Sex as a factor should be considered when assessing OS levels in systemic pathologies. BMI as a modifiable risk factor for maintenance of mental health, and OS modification through nutrient supplementation, are discussed. The findings contribute to understanding oxidative stress marker patterns in healthy older adults and their potential role in mood symptoms and mental health.
Keyphrases
- sleep quality
- physical activity
- mental health
- body mass index
- oxidative stress
- depressive symptoms
- weight gain
- bipolar disorder
- healthcare
- dna damage
- mental illness
- public health
- ischemia reperfusion injury
- diabetic rats
- deep learning
- induced apoptosis
- endothelial cells
- machine learning
- electronic health record
- mass spectrometry
- high resolution
- risk assessment
- psychometric properties
- endoplasmic reticulum stress