Publication highlights February 2025 - Proteomics in mental health

An unmet clinical need

The diagnosis, clinical management and treatment of mental health disorders relies significantly on questionnaires based on patient behavior and self-reported data. Increasingly, protein biomarkers are being investigated to provide a solid molecular basis to better understand and manage psychiatric and other mental health disorders.

Discovery of new postpartum depression biomarkers

Postpartum depression (PPD) is a serious mental health condition affecting mothers after childbirth, with significant consequences for maternal well-being, infant development, and family dynamics. Currently, there is a lack of knowledge of the fundamental biological mechanisms underlying PPD, hindering effective diagnosis and treatment.

In a recent biomarker discovery pilot study investigating a cohort of 50 mothers diagnosed with PPD using Olink Explore HT, three novel protein biomarkers were identified with significant disease associations. These biomarkers are newly introduced in the Olink Explore HT library and absent in the Olink Explore 3072 library. They represent a unique discovery that sheds light on previously unknown disease mechanisms underlying PPD. The identified biomarkers are currently undergoing validation and hold the potential to serve as distinctive tools for early detection and treatment response monitoring of PPD.

Please click the link below to access the webinar recording.

Recent publications citing Olink in mental health disorders

Here we summarize some recent studies where Olink panels were used to gain new biological insights into a range of different areas of mental health. Links to the original articles can be accessed at the bottom of this blog.

Social isolation, loneliness & chronic diseases

In a remarkable analysis of the UK Biobank Pharma Proteomics Project (UKB-PPP) dataset, Shen and colleagues identified proteomics signatures significantly associated with social isolation and loneliness (SIL). Leveraging the comprehensive characterization of UKB participants identified multiple proteins associated with SIL, many of which are linked to inflammation, antiviral responses and complement systems. Significantly, over 50% of the markers identified also showed prospective associations with chronic disease (CVD, diabetes, stroke) and mortality, which supports previous observational evidence that SIL may be real risk factors for human morbidity and mortality. Mendelian Randomization analysis further provided evidence for causal links between loneliness and 5 changes in expression levels of 5 proteins linked to chronic diseases (GFRA1, ADM, FABP4, TNFRSF10A and ASGR1).

Matrix metalloproteinases in anxiety & depression

Ghelfi and colleagues used the Olink Target 96 CVD III panel in a hypothesis-driven  study to assess the roles of multiple matrix metalloproteinases (MMPs) in early psychosis, anxiety, and depression. Both metalloproteinases and their inhibitors have been implicated in psychiatric disorders and here they examined a cohort of young adults with various psychiatric disorders (ALSPAC). After adjusting for confounders, a strong association of  the MMP inhibitor, TIMP4 was found with depression and generalized anxiety disorder, as well as for MMP3 with depressive disorders.

Biomarkers of autism spectrum disorder

Biomarkers for early diagnosis and intervention in Autism spectrum disorder (ASD) are currently lacking, and a study by Ali Moussa and colleagues used multiple Olink Target 96 panels to look for ASD-associated proteins in extracellular vesicles (EVs) isolated from patient plasma. The group had previously shown that EVs from neurological sites can cross the blood-brain barrier and provide circulating markers for other neurological diseases. Here they identified 5 markers that were found at lower levels in EVs from ASD patients ( WWP2, HSP27, CLEC1B, CD40, and FRα). Machine learning was then used to derive a high-accuracy diagnostic 6-protein model that could identify ASD vs controls with an Area Under the Curve (AUC) of 0.923.

The proteomics of depression.

Alterations in protein expression preceding the onset of depression could offer valuable insights into its development and help guide future potential interventions. Using the UKB-PPP data resource,  Kang and colleagues examined baseline plasma proteomics in over 46,000 UKB participants in relation to incident depression followed for median of 14.5 years. This identified 157 proteins with expression levels significantly associated with depression, and many of these markers also showed associations to changes in brain structure linked to depression, as well as to well-characterized stress responses. Among these proteins, BTN3A2 was identified as a completely novel biomarker  and Mendelian Randomization provided good evidence for a causal role in incident depression.