A new study suggests that a person’s genetic predisposition for chronic inflammation helps define a specific subtype of depression linked to metabolic issues. The research also found this genetic liability is connected to antidepressant treatment outcomes in a complex, nonlinear pattern. The findings were published in the journal Genomic Psychiatry.
Major depressive disorder is a condition with wide-ranging symptoms and variable responses to treatment. Many patients do not find relief from initial therapies, a reality that has pushed scientists to search for biological markers that could help explain this diversity and guide more personalized medical care. One area of growing interest is the connection between depression and the body’s immune system, specifically chronic low-grade inflammation. A key blood marker for inflammation is C-reactive protein, which is often found at elevated levels in people with depression.
However, measuring C-reactive protein directly from blood samples can be problematic for research because levels can fluctuate based on diet, infection, or stress. An international team of researchers, led by Alessandro Serretti of Kore University of Enna, Italy, sought a more stable way to investigate the link between inflammation and depression. They turned to genetics, using a tool known as a polygenic score. This score summarizes a person’s inherited, lifelong tendency to have higher or lower levels of C-reactive protein. While previous studies have connected this genetic score to specific depressive symptoms or to treatment outcomes separately, this new research aimed to examine both within the same large group of patients to build a more complete picture.
The investigation involved 1,059 individuals of Caucasian descent who were part of the European Group for the Study of Resistant Depression. All participants had a diagnosis of major depressive disorder and had been receiving antidepressant medication for at least four weeks. Researchers collected detailed clinical information, including the severity of depressive symptoms, which was assessed using the Montgomery–Åsberg Depression Rating Scale. Based on their response to medication, patients were categorized as responders, nonresponders, or as having treatment-resistant depression if they had not responded to two or more different antidepressants.
For each participant, the science team calculated a polygenic score for C-reactive protein. This was accomplished by analyzing each person’s genetic data and applying a statistical model developed from a massive genetic database, the UK Biobank. The resulting score provided a single, stable measure of each individual’s genetic likelihood of having high inflammation. The researchers then used statistical analyses to look for connections between these genetic scores and the patients’ symptoms, clinical characteristics, and their ultimate response to antidepressant treatment.
The results showed a clear link between a higher genetic score for C-reactive protein and a specific profile of symptoms and characteristics. Individuals with a greater genetic tendency for inflammation were more likely to have a higher body mass index and a lower employment status. They also reported less weight loss and appetite reduction during their depressive episodes, which are symptoms associated with metabolic function. The genetic score was not associated with the overall severity of depression or with core emotional symptoms like sadness or pessimism. This suggests that the genetic influence of inflammation is tied to a particular cluster of physical and metabolic symptoms, sometimes referred to as an immunometabolic subtype of depression.
When the researchers examined the connection to treatment outcomes, they discovered a more complicated relationship. The link was not a simple straight line where more inflammation meant a worse outcome. Instead, they observed what is described as a nonlinear or U-shaped pattern. Patients who did not respond to treatment tended to have the lowest genetic scores for C-reactive protein. In contrast, both patients who responded well to their medication and those with treatment-resistant depression had higher genetic scores. The very highest scores were observed in the group with treatment-resistant depression.
This complex finding remained significant even after the researchers statistically accounted for a range of other factors known to influence treatment success, such as the patient’s age, the duration of their illness, and the number of previous antidepressant trials. The genetic score for C-reactive protein independently explained an additional 1.9 percent of the variation in treatment outcomes. While a modest figure, it indicates that genetic information about inflammation provides a unique piece of the puzzle that is not captured by standard clinical measures. This U-shaped relationship echoes previous findings that used direct blood measurements of C-reactive protein, suggesting that both very high and very low levels of inflammation may be associated with different treatment pathways.
The researchers note some limitations of their work. The study’s design was cross-sectional, meaning it captures a single point in time and cannot prove that the genetic predisposition for inflammation causes certain symptoms or treatment outcomes. The participants were treated naturalistically with a variety of medications, which reflects real-world clinical practice but lacks the control of a randomized trial. Additionally, the sample consisted exclusively of individuals with European ancestry, so the findings may not be applicable to people from other backgrounds. The team also suggests that replication in other large studies is needed.
For future research, the authors propose integrating genetic scores with direct measurements of inflammatory biomarkers from blood tests. This combined approach could provide a more powerful tool for understanding both a person’s lifelong tendency and their current inflammatory state. Ultimately, this line of research could help refine psychiatric diagnosis and treatment. By identifying an immunometabolic subtype of depression, it may be possible to develop more targeted therapies. The findings contribute to a growing body of evidence supporting a move away from a “one-size-fits-all” approach to depression, opening the door for inflammation-guided strategies in personalized psychiatry.
The study, “Polygenic liability to C-reactive protein defines immunometabolic depression phenotypes and influences antidepressant therapeutic outcomes,” was authored by Alessandro Serretti, Daniel Souery, Siegfried Kasper, Lucie Bartova, Joseph Zohar, Stuart Montgomery, Panagiotis Ferentinos, Dan Rujescu, Raffaele Ferri, Giuseppe Fanelli, Raffaella Zanardi, Francesco Benedetti, Bernhard T. Baune, and Julien Mendlewicz.
