Summary: Researchers report that people with a higher genetic predisposition to clinical depression are also more likely to experience physical symptoms such as migraines, chronic pain, and persistent fatigue.
Source: University of Queensland
New research from the University of Queensland shows that individuals with an increased genetic risk for clinical depression are more likely to experience significant physical symptoms—including chronic pain, debilitating fatigue, and migraine—alongside their mental health symptoms.
Dr. Enda Byrne and colleagues at UQ’s Institute for Molecular Bioscience led the study, emphasizing that major depressive disorder carries substantial lifetime risks for both mental and physical health problems.
“Many people who go on to receive a clinical diagnosis of depression first present to clinicians with physical complaints that are distressing and can dramatically reduce quality of life,” Dr. Byrne said. “Recognizing the biological links between depression and somatic symptoms is essential for better diagnosis and care.”
The researchers aimed to clarify how different ways of defining depression in genetic studies affect the identification of genetic risk factors. They found that assessing a wide range of symptoms—both psychological and physical—improves understanding of the condition’s biological basis and strengthens risk prediction for research and clinical use.
Despite recent progress in psychiatric genetics, Dr. Byrne noted that discovering additional genetic factors remains challenging because people with depression vary widely in age, symptom patterns, treatment response, and coexisting mental or medical conditions. He also pointed out that some previous genetic studies included participants who reported general worries or tension but may not have met formal diagnostic criteria for major depressive disorder (MDD).
Working with the QIMR Berghofer Medical Research Institute, the UQ team analyzed data from more than 15,000 volunteers. Participants provided detailed mental health histories, symptom reports, and DNA samples collected via saliva kits. This well-characterized dataset allowed researchers to compare polygenic risk scores (PRSs) derived from differing definitions of depression and to examine how those scores relate to clinical outcomes and somatic symptoms.
“We compared genetic risk estimates based on simple self-report questions, on consultation records, and on clinical diagnoses to see how these different definitions perform,” Dr. Byrne explained. The study showed that higher genetic risk for clinically defined depression was consistently associated with increased likelihood of physical symptoms such as chronic pain, fatigue, and migraine. It was also linked to greater somatic distress—physical complaints that contribute substantially to reduced day-to-day functioning and quality of life.
These results underscore the importance of including broad symptom assessments in genetic research on depression. By accounting for physical as well as psychological symptoms, studies can better capture the full spectrum of the disorder and improve the clinical utility of polygenic risk scores.
About this genetics and depression research news
Author: Press Office
Source: University of Queensland
Contact: Press Office – University of Queensland
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Original Research: Closed access.
“Polygenic Risk Scores Derived From Varying Definitions of Depression and Risk of Depression” by Enda Byrne et al. JAMA Psychiatry
Abstract
Polygenic Risk Scores Derived From Varying Definitions of Depression and Risk of Depression
Importance
Genetic studies that use broad or loosely defined measures of depression may miss genetic influences that are specific to clinically diagnosed major depressive disorder (MDD). This raises important questions about the best way to define depression for genetic research.
Objective
The study aimed to use a large, well-phenotyped sample to test how different genetic definitions of depression affect the estimation of MDD risk and associated clinical features, using polygenic risk scores (PRSs).
Design, Setting, and Participants
This case-control PRS analysis drew patients meeting diagnostic criteria for MDD from the Australian Genetics of Depression Study and included controls and individuals with self-reported depression from the QSkin cohort. The combined dataset provided detailed phenotype information and genetic data collected before September 2018; analysis took place from September 10, 2020, to January 27, 2021.
Main Outcome and Measures
The study evaluated PRSs generated from genome-wide association studies that used different definitions of depression. Researchers assessed how well these scores estimated MDD diagnosis and how they associated with age of onset, adverse childhood experiences, comorbid psychiatric and somatic disorders, and current physical and mental health measures.
Results
The analysis included 12,106 patients meeting MDD criteria (71% female; mean age 42.3 years) and 12,621 control participants with no psychiatric history (55% female; mean age 60.9 years). Effect sizes for PRSs were proportional to the size of the discovery sample: larger discovery samples produced stronger PRS effects. The PRS with the highest predictive power came from a large study of clinically defined MDD, while PRSs derived from administrative hospitalization codes showed smaller effects. When adjusted for discovery sample size, the PRS based on clinically diagnosed MDD was the best estimator of MDD and showed stronger associations with early adverse experiences and somatic distress than PRSs based on broader definitions.
Conclusions and Relevance
The findings suggest that increasing sample sizes can improve the estimation of genetic risk for depression, but depth of clinical information remains important. Future genome-wide association studies should aim for both large sample sizes and detailed phenotyping—capturing the broad range of psychological and physical symptoms—so they can identify genetic risk factors for MDD that might be missed by broader or less detailed definitions of depression.