Authors: Marije van Haeringen; Yuri Milaneschi; Femke Lamers; Brenda W.J.H. Penninx; Rick Jansen · Research

How Do Protein Networks Relate to Depression Symptoms?

A study finds links between networks of inflammatory and metabolic proteins and specific depression symptoms.

Source: van Haeringen, M., Milaneschi, Y., Lamers, F., Penninx, B. W. J. H., & Jansen, R. (2022). Dissection of depression heterogeneity using proteomic clusters. Psychological Medicine, 53(8), 2904–2912. https://doi.org/10.1017/S0033291721004888

What you need to know

  • A network of inflammatory and metabolic proteins was associated with major depressive disorder, particularly in patients with certain symptoms.
  • The protein network was most strongly linked to atypical depression symptoms like increased appetite, weight gain, and excessive sleepiness.
  • These findings support the idea of an “immuno-metabolic depression” subtype characterized by both metabolic/inflammatory changes and specific depression symptoms.

Unraveling the complexity of depression

Major depressive disorder (MDD) is a leading cause of disability worldwide, affecting hundreds of millions of people. However, depression is a complex condition - people with the same diagnosis can have very different symptoms and experiences. This complexity has made it challenging for researchers to identify biological markers of depression that could lead to better treatments.

Many studies have found links between depression and changes in inflammatory and metabolic processes in the body. For example, people with depression often have higher levels of inflammatory proteins like C-reactive protein (CRP) in their blood. They may also show changes in metabolic markers related to insulin and fat tissue. However, these biological changes are not seen in all people with depression.

Recent research suggests that certain depression symptoms, particularly those related to changes in sleep, appetite, and energy levels, may be more closely tied to inflammatory and metabolic disruptions. This has led to the idea of an “immuno-metabolic depression” subtype.

To better understand these complex relationships, researchers are now looking at networks of interacting proteins, rather than just individual markers. This network approach may capture the intricate biological processes underlying depression more accurately.

Examining protein networks in depression

A team of researchers in the Netherlands set out to investigate how networks of proteins relate to depression and specific depression symptoms. They analyzed data from 1,621 participants in the Netherlands Study of Depression and Anxiety (NESDA). This included 712 people with current major depression, 483 with a history of depression but not currently depressed, and 426 people who had never had depression or an anxiety disorder.

The researchers measured levels of 171 proteins in participants’ blood samples. These proteins are involved in various processes like hormone signaling, inflammation, and metabolism. Then, they used a technique called weighted correlation network analysis (WGCNA) to identify clusters of proteins that tend to change together.

A key protein network emerges

The analysis revealed six clusters of related proteins. One cluster stood out as being associated with current depression. This network contained 21 proteins involved in inflammation and metabolism, including some that have been linked to depression in previous research:

  • C-reactive protein (CRP) - an inflammatory marker
  • Leptin - a hormone involved in appetite regulation
  • Insulin - a hormone that regulates blood sugar
  • Complement C3 - part of the immune system
  • Fatty acid-binding protein (FABP) - involved in fat metabolism

This protein network was not only linked to having depression overall, but also to specific depression symptoms.

Connecting proteins to symptoms

The researchers looked at how the protein network related to 30 different depression symptoms. They found the strongest links with symptoms that are considered “atypical” features of depression:

  • Increased appetite
  • Weight gain
  • Hypersomnia (excessive sleepiness)
  • Leaden paralysis (a heavy, weighed down feeling in the arms or legs)
  • Low energy

The protein network was also associated with other symptoms like difficulty falling asleep, bodily aches and pains, and panic/anxiety.

These findings align with the idea of an immuno-metabolic depression subtype. This suggests that for some people, depression may involve a cluster of metabolic and inflammatory changes in the body along with a particular set of symptoms.

What does this mean for patients?

This research helps explain why depression can look so different from person to person. It suggests that there may be distinct biological processes underlying different symptom patterns.

For patients with atypical depression symptoms like increased appetite and excessive sleepiness, these findings hint that inflammatory and metabolic factors may be playing a role. In the future, this could potentially lead to more targeted treatments. For example, anti-inflammatory approaches or metabolic interventions might be more helpful for this subgroup of patients.

However, it’s important to note that this is still an emerging area of research. The protein network identified in this study explained only a small portion of the differences between people with and without depression. Many other factors, including genetics, stress, and life experiences, also play important roles in depression.

Looking ahead

This study demonstrates the value of looking at networks of interacting biological markers, rather than single proteins in isolation. It also adds to a growing body of evidence linking metabolic and inflammatory processes to depression, particularly atypical symptom patterns.

Future research will need to further investigate these connections and determine if they can lead to practical applications. Some key questions include:

  • Can measuring these protein networks help predict who will develop depression or who will respond to certain treatments?
  • Are there ways to target this protein network with new depression treatments?
  • How do other factors like stress or genetics interact with these protein networks?

As we continue to unravel the complex biology of depression, the hope is that this knowledge will translate into better, more personalized care for people living with this challenging condition.

Conclusions

  • Depression involves complex biological processes that may differ between individuals with different symptom patterns.
  • A network of inflammatory and metabolic proteins was linked to depression, especially symptoms like increased appetite and excessive sleepiness.
  • This research supports the concept of an “immuno-metabolic depression” subtype, which may require tailored treatment approaches.
  • Studying networks of interacting proteins, rather than individual markers, can provide new insights into the biology of depression.
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