Depression is a prevalent mental health disorder that imposes a substantial burden on global health and is a significant risk factor for suicide. It is anticipated that depression will become the second leading cause of disease burden worldwide within the next two decades, highlighting the urgency of addressing this public health issue (1). A robust body of literature further substantiates the strong association between depression and various chronic physical conditions (2, 3). Consequently, early identification and diagnosis of depression are essential for timely intervention and recovery.

The atherogenic index of plasma (AIP), calculated as the logarithmic ratio of triglycerides (TG) to high-density lipoprotein cholesterol (HDL-C), is widely utilized to evaluate lipid metabolic disorders (4, 5). Emerging research has implicated dyslipidemia in the etiology and progression of depression, with AIP gaining recognition as a relevant lipid marker in this context (6, 7). Although originally designed to predict the risk of atherosclerosis (8), recent findings have suggested a potential link between AIP and the incidence of depression (9, 10), proposing AIP as a potential biomarker for depressive disorders.

The bidirectional relationship between diabetes mellitus (DM) and depression is well-established, with each condition significantly elevating the risk of the other (11). Insulin resistance (IR), a core feature of DM, is also implicated in the pathophysiology of depression, and may represent a state-dependent metabolic dysfunction in individuals with depression (12, 13). Notably, AIP has been strongly associated with the onset of prediabetes mellitus (Pre-DM) and DM, with elevated AIP levels reflecting the severity of IR (14, 15). Given these links, AIP may serve as a valuable indicator of dysregulated glucose metabolism and a potential predictor of depression in individuals with impaired glucose metabolism, a condition that has also been associated with poorer psychiatric outcomes and treatment response in prior studies (16). However, to date, no studies have comprehensively examined the relationship between AIP and depression across varying glucose metabolism status. Large-scale cohort studies are warranted to elucidate this relationship and to identify novel biomarkers that could facilitate the early detection of depressive symptoms and prompt intervention.

This study, utilizing data from the China Health and Retirement Longitudinal Study (CHARLS), seeks to explore the association between AIP and depression in middle-aged and older adults with differing glucose metabolism status. The findings aim to provide robust population-based evidence to clarify the potential role of AIP as a biomarker for depression.

This study offers new evidence on the relationship between AIP levels and depression in middle-aged and older adults with varying glucose metabolic statuses. Our analysis reveals a positive correlation between elevated AIP levels and the risk of depression, characterized by a nonlinear association. This effect was particularly marked in individuals with abnormal glucose metabolism, including those with Pre-DM and DM. These findings suggest that baseline AIP may serve as a valuable biomarker for identifying individuals at higher risk of depression, particularly in those with glucose metabolism disorders. Additionally, maintaining lower AIP levels could offer a strategic target for the primary prevention of depression in these populations.

Depression, a prevalent psychological disorder, manifests as persistent feelings of sadness, diminished interest in activities, and cognitive, behavioral, or physical symptoms (22, 23). It is a significant contributor to morbidity, increasing the risk of suicide and susceptibility to various diseases, particularly cardiovascular disease (CVD) (24). Previous studies have consistently demonstrated a close association between CVD and depression, with both conditions sharing overlapping pathophysiological mechanisms (25, 26). Epidemiological data consistently highlight an increased risk of cardiovascular events in individuals with depressive symptoms (27).

As a marker linked to atherosclerosis and inflammation, AIP has emerged as a potential biomarker with significant implications for predicting both CVD and depression (28, 29). Notably, research by Sandra et al. found that individuals with depression exhibited significantly elevated AIP levels (5). A large study using data from the National Health and Nutrition Examination Survey (NHANES) from 2005 to 2018, encompassing 12,453 participants, demonstrated an L-shaped relationship between AIP and depression, with a critical threshold at 0.289 (10). A Above this threshold, higher AIP levels were associated with a significantly increased risk of depression. Similar findings were reported by Ye et al., who observed that elevated AIP levels correlated with greater susceptibility to depressive symptoms (9). A retrospective cross-sectional study from Brazil also demonstrated a relationship between elevated AIP levels and an increased prevalence of depression (5). However, this study had limitations, including the exclusion of individuals aged 65 and older and a small sample size of 331 participants, limiting the generalizability of the findings. Given that older adults are more prone to lipid metabolism disorders and depression due to reduced metabolic rates and social interactions, these limitations warrant further investigation (30). Our study, which included 7,723 participants aged 45 years and older, provides robust evidence of a significant positive association between elevated AIP levels and depressive symptoms. These findings underscore the importance of AIP as a potential predictor of depression (9). Further research elucidating the role of AIP in mood disorders and its interplay with cardiovascular health could advance our understanding of the biological pathways linking these conditions.

Importantly, our study revealed significant differences in the association between the AIP and depressive symptoms among individuals with DM and Pre-DM, whereas no significant association was observed in the normoglycemic group. DM is characterized by disruptions in glucose and lipid metabolism, predisposing individuals to atherogenic dyslipidemia and heightened cardiovascular risk (31). Elevated AIP levels have been linked to insulin resistance, and individuals with DM commonly exhibit higher AIP values (32). Consequently, the coexistence of DM may exacerbate the atherogenic effects associated with elevated AIP levels, thereby contributing to the onset and progression of depressive symptoms. Previous research has established DM as a major risk factor for both CVD and depression (33, 34). A large-scale cross-sectional survey identified a positive correlation between elevated AIP levels and an increased risk of Pre-DM and DM (35), while a separate prospective cohort study demonstrated that major depressive disorder increases the likelihood of DM-related complications (36), However, no studies to date have confirmed the predictive value of baseline AIP levels for depression in individuals with glucose metabolism disorders. Our findings indicate that elevated baseline AIP levels are associated with new-onset depression in Pre-DM and DM patients. In contrast, the RCS curve in the NGR group remained relatively flat, indicating no clear association between AIP and depression. Clinically, this may suggest that among individuals with preserved glucose homeostasis, the impact of lipid-derived atherogenic burden as measured by AIP on neuropsychiatric outcomes such as depression is less pronounced, potentially due to a lower level of systemic metabolic disturbance and inflammatory activation. Therefore, measuring AIP levels in middle-aged and older individuals with abnormal glucose metabolism may have clinical significance, as AIP could potentially serve as a biomarker to predict and identify the risk of depression.

The pathophysiology underlying the relationship between AIP and depression is complex and remains poorly understood, though several potential mechanisms may be involved. The association between AIP and depression could be partially attributed to shared pathways, such as inflammation, oxidative stress, and endothelial dysfunction, all of which are implicated in the progression of both depression and CVD (37, 38). Studies have demonstrated that depression is often accompanied by elevated levels of pro-inflammatory markers, including C-reactive protein and interleukin-6 (39, 40). which not only contribute to the development of depression but also increase the risk of lipid metabolism disorders (41, 42). Dietary factors, particularly high-carbohydrate and high-fat intake, can exacerbate lipid metabolism dysregulation, leading to increased oxidative stress (43). Under physiological conditions, oxidative stress induces the production of reactive oxygen species, which, in turn, stimulate the production of antioxidants to regulate oxidative levels (44). However, persistent oxidative stress may overwhelm these regulatory mechanisms, ultimately leading to sustained inflammation and depression (45). Furthermore, excessive lipid intake has been associated with glial cell accumulation, which can impair hippocampal neurons and elevate the risk of depression (46). These biological processes may result in structural changes in the vasculature and brain, potentially exacerbating depressive symptoms or facilitating the development of CVD.

Our second key finding is the significant interaction between AIP and glucose metabolism status, indicating that the association between AIP and depression is particularly pronounced in individuals with Pre-DM and DM. Several mechanisms may underlie this relationship. Dyslipidemia, through various pathways, can impair pancreatic function and reduce insulin sensitivity, thereby exacerbating the progression of Pre-DM and DM (47, 48). Supporting this, a cross-sectional study demonstrated a strong correlation between elevated AIP levels, increased risk of insulin resistance, and the onset of DM (32). Approximately half of DM patients, both fasting and postprandial, present with elevated triglycerides or reduced HDL-C levels, a pattern frequently observed in individuals with insulin resistance or impaired glucose tolerance (49). Elevated triglyceride concentrations increase free fatty acid levels, impairing insulin sensitivity and contributing to abnormal glucose metabolism (50). In recent years, the relationship between glucose metabolism status and depression has garnered increasing attention. Evidence from psychiatric populations has shown that impaired glucose metabolism may be linked to poorer treatment outcomes, further underscoring the relevance of metabolic status in shaping depression trajectories (16). The bidirectional nature of the DM-depression link is well-established: DM is associated with a 20% increased risk of depression, while depression confers a 60% increased risk of developing DM (51). An independent prospective cohort study further reported that major depressive disorder significantly increases the likelihood of DM-related complications (36). Various biological mechanisms have been proposed to explain the DM-depression association across the life course, including the activation of innate immunity, dysregulation of the acute-phase inflammatory response, chronic dysfunction of the hypothalamic-pituitary-adrenal axis, circadian rhythm disturbances, and insulin resistance (52, 53). The coexistence of DM may exacerbate the atherogenic effects of elevated AIP, thereby contributing to the onset and progression of depressive symptoms.

Given this context, effectively addressing dyslipidemia and maintaining an optimal lipid profile in patients with abnormal glucose metabolism is crucial for the prevention and treatment of depressive symptoms. Our study suggests that AIP may be a valuable biomarker for predicting depression risk in middle-aged and older Chinese adults with glucose metabolism disorders, as we observed a significant association between elevated AIP levels and depression risk in Pre-DM and DM participants. These findings underscore the importance of optimizing cardiovascular health in managing depression among diabetic individuals and provide new perspectives for developing risk stratification and intervention strategies for mental health disorders. Given its simplicity, cost-effectiveness, and widespread availability in clinical settings, AIP screening could be feasibly integrated into routine metabolic assessments among high-risk individuals, particularly those with impaired glucose regulation. Physiological indices like AIP offer quantifiable measures for assessing depressive symptoms, enabling targeted interventions that could contribute to the primary prevention of depression. Furthermore, continued research is necessary to identify additional risk factors that can predict depression, facilitating early preventive strategies.

This study has several limitations. First, the analysis focused solely on baseline AIP levels without accounting for longitudinal variations in AIP over the course of follow-up. This limits the capacity to infer the dynamic relationship between AIP and depressive symptoms. Second, although several potential confounders were adjusted for in the analysis, the potential influence of residual or unmeasured confounding factors cannot be entirely excluded. In particular, information on lipid-lowering medications such as statins was not available in the current CHARLS dataset, which may have influenced AIP levels but could not be accounted for in this analysis. Future studies should aim to incorporate detailed medication data to more accurately control for this potential confounder. Third, the possibility that depressive symptoms may influence metabolic parameters such as lipid levels cannot be fully excluded. Additionally, the CHARLS database lacks precise information on the timing of depression onset, which limited our ability to perform time-to-event analyses based on exact incidence dates. Future studies with more frequent follow-up assessments are needed to clarify the temporal nature of this relationship. Lastly, the study population was restricted to individuals of Chinese ethnicity, and the generalizability of the findings to other ethnic groups or populations remains uncertain. Further research should strive to account for potential confounding variables and examine these relationships in more diverse populations to enhance the broader applicability of the results.

This study identified a significant association between elevated AIP levels and an increased risk of depression in middle-aged and older adults, particularly those with Pre-DM and DM. AIP holds potential as a biomarker for depression risk stratification in individuals with glucose metabolism disorders.