Inflammation linked to depression in women with diabetes, study finds

Inflammation may help flag depression in women with type 2 diabetes, new research reveals, but the link appears to vary by symptoms and by how depression is measured.

The findings suggest both the promise and the challenge of identifying biomarkers, measurable indicators in blood or other tests, for depression.

Women with type 2 diabetes are at higher risk of depression, which can accelerate diabetes complications, impair functioning and increase the risk of death. Research suggests inflammation may be a key link between the two conditions, as certain inflammatory biomarkers are frequently found in both.

Scientists have yet to identify an objective diagnostic biomarker for depression, such as something measured through blood work, a genetic test or a brain scan.

To diagnose and measure depression, mental health providers usually use questionnaires. Some add up the number of symptoms as a checklist, while others measure the severity of different symptoms.

Depression can also look very different from one person to the next, with symptoms spanning physical effects such as sleeping too much or too little, mood-related issues such as persistent sadness, and cognitive difficulties such as trouble concentrating.

Nicole Beaulieu Perez, assistant professor at NYU Rory Meyers College of Nursing and study author, said: “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.

“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 different symptoms and measures of depression, researchers at NYU Rory Meyers College of Nursing studied 38 women with type 2 diabetes, many of whom were also living with HIV.

They analysed 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 short questionnaires that includes measures of depression, anxiety, sleep and fatigue, as well as the CES-D, an older measure that adds up depression symptoms.

The researchers found that certain inflammatory biomarkers were linked to depression, but the associations varied depending on the measures and symptoms used.

Higher levels of depression and anxiety measured using PROMIS were associated with lower levels of IL-4.

They also found contradictory associations for CRP and IL-6. Both were positively correlated with depression when it was measured using CES-D and negatively correlated when it was measured using PROMIS.

Sleep disturbances measured using PROMIS were associated with IL-8.

Perez said: “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.”

The findings, while preliminary because of 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.

Perez said: “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.”

She said she hoped that in future, pairing depression measures with biomarkers such as blood tests could provide more objectivity in diagnosing depression, which could help further destigmatise mental illness, as well as help clinicians catch it earlier and guide treatment.

Perez said: “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.

“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.”