In a recent study published in the JAMA Network Open, a group of researchers determined if carbohydrate, lipid, and apolipoprotein (Apo) biomarkers are linked to the future development of depression, anxiety, and stress-related disorders in a large Swedish cohort.
Study: Metabolic Profile and Long-Term Risk of Depression, Anxiety, and Stress-Related Disorders. Image Credit: hikrcn / Shutterstock
Background
About one-third of people experience depression, anxiety, and stress-related disorders in their lifetime, with growing evidence suggesting a link between these psychiatric conditions and metabolic dysregulation, such as lipid and glucose abnormalities that trigger inflammation. This inflammation may increase the risk of psychiatric disorders by affecting brain health. However, existing research on metabolic biomarkers and their association with psychiatric disorders has been inconsistent, often limited by methodological issues like short follow-up periods and reliance on self-reported depression measures, mainly in older adults. Furthermore, there is a notable gap in research on the connection between these biomarkers and anxiety or stress-related disorders, particularly the long-term effects of Apo's. Further research is crucial to clarify these associations and explore potential preventative and therapeutic strategies.
About the study
The Swedish Apolipoprotein-Related Mortality Risk (AMORIS) cohort, spanning from 1985 to 1996 and predominantly in the Stockholm region, includes 812,073 participants (49% men, 51% women) who underwent routine health screenings or were referred for laboratory testing due to health conditions. For this study, 211,200 participants over 16, free from mental disorders at baseline and with at least one biomarker measurement, were selected. Mental disorder histories were confirmed using the Swedish Patient Register, employing various International Classification of Diseases (ICD) revisions for accuracy.
The study included a broad spectrum of stress-related conditions, with both primary and secondary diagnoses considered. Biomarkers of interest include glucose, cholesterol types, triglycerides, apolipoproteins, and their ratios, analyzed by consistent laboratory methods. Covariates like sex, age, fasting status, socioeconomic status, and birth country were also recorded, offering a detailed background for each participant.
Statistical analysis involved Cox proportional hazards regression models to explore the relationship between initial biomarker levels and the risk of psychiatric disorders, adjusting for relevant covariates and employing both categorical and continuous variable analyses. Sensitivity analyses further refined these findings by focusing on employed individuals, outpatient referrals and excluding those with missing socioeconomic data. A case-control study embedded within the larger cohort provided a longitudinal perspective, examining biomarker trends up to 30 years before diagnosis, with controls matched to cases by sex, age, and enrollment year.
Study results
In the substantial cohort of 211,200 participants, consisting of 58% males and 42% females, with the vast majority born in Sweden (89.4%), the study observed notable trends over a mean (SD) follow-up period of 21 years. The participants had an average age of 42.1 years at their first blood sampling, with diagnoses of depression, anxiety, or stress-related disorders emerging at a mean age of 60.5 years. The incidence rates for these disorders varied, with depression, anxiety, and stress-related disorders recorded at rates of 21.5, 16.6, and 10.5 per 10,000 person-years, respectively. Notably, a segment of the cohort was diagnosed with multiple disorders, yet only 0.4% received diagnoses across all three categories.
The analysis revealed a correlation between metabolic biomarker levels and psychiatric health risks. Elevated glucose and triglyceride (TG) levels significantly increased the risk of psychiatric disorders, whereas higher levels of high-density lipoprotein cholesterol (HDL-C) offered a protective effect. The delineation of risk did not change markedly between low and normal glucose levels, suggesting a particular risk threshold. This pattern persisted across gender lines and when evaluating each psychiatric condition individually, reinforcing the robustness of these findings.
Further analysis, specifically among employed individuals, yielded consistent results with the primary analysis, underscoring the relationship between metabolic health and psychiatric conditions regardless of employment status. When examining the impact of outpatient care referrals on biomarker measurements, the associations remained similar for glucose and TGs, though the protective role of HDL-C lessened. Additionally, higher levels of low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), ApoB, and the ApoB/ApoA-I ratio were inversely associated with the risk of psychiatric disorders, indicating a complex interplay between various lipid biomarkers and mental health.
Socioeconomic status also emerged as a significant factor, with lower incidence rates of psychiatric disorders observed among those with higher socioeconomic standing. This trend held true even after adjusting for potential confounders, including missing socioeconomic data, further emphasizing the socioeconomic gradient in psychiatric disorder risk.
Longitudinal analysis, tracking biomarker levels up to 30 years prior to diagnosis, illustrated that patients eventually diagnosed with anxiety, depression, or stress-related disorders exhibited consistently higher levels of TGs, glucose, and TC two decades before diagnosis. Additionally, higher levels of ApoA-I and ApoB were noted in the decade leading up to diagnosis, indicating a prolonged period of metabolic dysregulation preceding psychiatric diagnoses.
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