Inflammation markers may signal depression in women with type 2 diabetes, but vary based on depression symptoms and measures, according to a new study led by researchers at NYU Rory Meyers College of Nursing.
The findings, published in Frontiers in Psychiatry , highlight both the promise and challenge of identifying biomarkers for depression.
“By identifying specific inflammatory biomarkers linked to different dimensions of mental health, our findings suggest a path toward precision mental health that moves beyond one-size-fits-all approaches,” said study author Nicole Beaulieu Perez, assistant professor at NYU Rory Meyers College of Nursing.
Women with type 2 diabetes are at a higher risk for depression, which can accelerate diabetes complications, impair functioning, and increase their risk of death. Research shows that inflammation may be a key link between depression and type 2 diabetes, as certain inflammatory biomarkers are frequently found in both conditions.
Scientists have yet to identify an objective diagnostic biomarker for depression—for instance, something that can be measured in blood work, a genetic test, or brain scan. To diagnose and measure depression, mental health providers typically use a series of questionnaires; some add up the number of symptoms as a checklist, while other scales are more robust in measuring the severity of various symptoms.
Moreover, depression can look very different from one person to the next, with people experiencing symptoms across multiple domains, including those that are physical (e.g., sleeping too much or too little), mood-related (e.g., persistent sadness), and cognitive (e.g., difficulty concentrating).
“Depression is the most measured construct in all of science, but part of our problem is that we're not defining depression the same—there may be different types, but we're lumping them all together,” said Perez. “The variability in depression symptoms complicates how we diagnose and treat it, particularly in the absence of validated biological markers.”
To better understand the connection between inflammation and various symptoms and measures of depression, Perez and her colleagues studied a group of 38 women with type 2 diabetes; many were also living with HIV. The researchers analyzed blood samples for 10 different inflammatory biomarkers, including CRP, IL-6, IL-4, and IL-8.
They also assessed participants for depression using PROMIS—an NIH-developed series of measures that includes measures of depression, anxiety, sleep, and fatigue using a series of short questionnaires—as well as the CES-D, an older measure that aggregates depression symptoms.
The researchers found that certain inflammatory biomarkers were linked to depression, but it varied depending on the measures and symptoms. For instance, higher levels of depression and anxiety measured using PROMIS were associated with lower levels of IL-4. They found contradictory associations for inflammation markers CRP and IL-6, which were positively correlated with depression as measured by CES-D and negatively correlated when measured using PROMIS. Sleep disturbances measured using PROMIS were associated with IL-8.
“It was interesting to see that, in some cases, the direction of these associations flipped entirely based on which measure of depression we were using,” said Perez.
The findings, while preliminary based on the small number of people studied, suggest that the link between inflammatory biomarkers and depression may not be consistent across all measures or symptoms. More research is needed to tease out the role of inflammation and whether subtypes of depression can be identified based on symptoms and objective biological markers.
“We think there's something going on with inflammation and depression, but if we look closely, we may find that's true for some forms of depression but not others,” said Perez.
In the future, Perez hopes that pairing depression measures with biomarkers like blood tests could provide objectivity in diagnosing depression—which could help further destigmatize mental illness, as well as help clinicians catch it earlier and guide how to treat it.
“Precision mental health has great potential. If we can identify a specific type of depression—for instance, one that appears to be driven by inflammation—this may inform which medications to try to target an underlying biological pathology, hopefully reducing the trial and error often needed to find an effective treatment for depression,” said Perez.
Additional study authors include Maria Paula Gordillo Sierra, Jackie Finik, Jason Fletcher, and Gail D'Eramo Melkus of NYU Meyers; David Hanna, Anjali Sharma, and Kathryn Anastos of Albert Einstein College of Medicine; Leah Helane Rubin of Johns Hopkins University; and Bradley Aouizerat of NYU College of Dentistry. The research was supported by the National Institute of Nursing Research (P20NR018075).
Frontiers in Psychiatry
Disentangling depression in women with diabetes: evidence for measure-dependent associations with interleukin-4 and common inflammatory biomarkers
19-Mar-2026