Biomarker Development Across Psychiatric Disorders

Bio(logical)markers are objective, quantifiable features of any biological process. With respect to human disease, these markers may take the form of genetic mutations (or polymorphisms), proteins, or other molecules found in bodily fluids such as blood and saliva, or even the imaging of organs such as the brain for structural deviations or metabolic patterns. As biomedical research continues to search for ways to implement precision medicine, the identification of reliable biomarkers is essential. However, there is still much work to be done. For widespread clinical utility, the collection of these markers should be noninvasive and cost-effective. Ideally, these molecular signatures or imaging landmarks would not only predict disease susceptibility, but would inform treatment, and offer insight into how patients would tolerate prescribed therapy.

In recent years, the field of cancer research has made notable progress toward liquid biopsies for early cancer detection, as well as prognosis, treatment response, and disease monitoring.¹ Circulating tumor DNA and exosomal microRNAs for example, which are found in body fluids, serve as a surrogate for traditional biopsy or more invasive testing. Now the hope is that similar techniques could be used across a panoply of disease types. But sometimes diagnosis is less clear-cut. Mental health conditions cause immeasurable suffering and can be deadly; yet there is no definitive objective metric to diagnose individuals. Biomarkers may finally be the answer to this long-standing problem, but not without caveats. Highly accurate predictors are difficult to sort through, even with rich datasets.

Biomarkers in psychiatric disorders, nascent and necessary

One in four will experience a clinical mood disorder at some point in their lives.² Extensive delay exists in the time between symptom onset to diagnosis of psychiatric disease. For mood disorders, time to treatment is about 6–8 years, and for anxiety disorders, 9–23 years.³ A shortage of mental healthcare providers coupled with persistent stigma surrounding these conditions contribute to delayed medical evaluation and treatment. Correct diagnosis also relies on subjective feelings, the ability to convey this information, and the physician’s interpretation and previous experience. Often there is comorbidity with other mental health conditions, which may lead to a confusing array of symptoms. Once a diagnosis emerges, treatment options may be subpar, worsen symptoms, have intolerable side-effects, or stop working after some time.

Selective serotonin reuptake inhibitors (SSRIs) and the newer serotonin and norepinephrine reuptake inhibitors (SNRIs) are the prevailing choice of practitioners for treatment, although roughly half of patients do not experience relief. Newer therapies, such as psychedelics, ketamine, and transcranial magnetic stimulation, offer additional options especially for the treatment-resistant. Still, predicting who will respond to which regimen is mostly a mystery; and finding the magic bullet can be an extraordinarily slow and frustrating process.

Prior to COVID, one in eight American adults were taking an antidepressant.⁴ The pandemic fueled an already robust mental health crisis. Anxiety, depression, drug overdose, alcohol-induced death, and suicide all increased over the past few years underscoring the urgency for a more reliable, more efficient approach.⁵ The brain cannot be easily biopsied in living people and obtaining cerebrospinal fluid requires an invasive spinal tap. For these reasons scientists are increasingly pinning hope on biomarker candidates in blood for neuropsychiatric disorders, and in the process, discovering molecular links between these diseases (as well as seemingly unrelated ones).

Finding objective markers amidst multitudinous presentations

The factors underlying mental health disorders are myriad and difficult to disentangle. While symptoms can be common to many psychiatric and neurologic conditions, simultaneously a condition such as depression can have hundreds of different presentations. These afflictions are often polygenic and influenced by epigenetics and environment. However recent work highlights significant advancement in the field. For example, analysis of RNA blood biomarkers in those with anxiety not only ascertained a person’s current state of anxiety, but also successfully matched those in the study to existing medications and supplements.⁶ Through pharmacogenomic analysis, valproate topped the list of successful anxiety treatments, a medication typically used for epilepsy and bipolar disorder. Novel anxiolytic candidates included omega-3 fatty acids and lithium. Estradiol and loperamide (Imodium) also made the cut. Randomly controlled clinical trials corroborate valproate and estradiol findings, but all are older, relatively safe drugs used in clinical practices for decades and therefore can be easily repurposed. Discovering new uses for medications also helps to direct future work to elucidate pathways underlying the biology of anxiety disorders.⁶

Previous work out of the same lab identified both overlapping and distinct RNA markers for depression and bipolar disorder, including those that could be used to help distinguish between the mood disorders.² Similar research described markers for post-traumatic stress disorder. Blood tests derived from this work are being developed for wide-scale use. Eventually mental health blood panels could become part of wellness visits and would allow for the monitoring of biomarkers over time. Precision therapy could become mainstream specifically tailored to constellations of markers, and prevent these conditions from becoming life-threatening.

Biomarkers as windows into shared pathways across diseases (even seemingly unrelated ones)

Mental health disorders have high rates of comorbidity so it is reasonable to expect that a biomarker could cross multiple conditions.⁷ Perhaps more intriguing however, is the link a biomarker may forge between maladies we would assume to be unrelated.

To illustrate, an in silico approach recently revealed 21 potential pleiotropic genes and three biological pathways with a high probability of overlap between schizophrenia and cardiometabolic disease.⁸ One group showed for the first time the association of highly recurrent copy number variations in the gene that encodes a GABA_A receptor subunit with schizophrenia and premenstrual dysphoric disorder.⁹ Another lab discovered three microRNAs and their target genes may contribute to schizophrenia; this regulatory network similarly is associated with higher cardiovascular mortality and lower rates of glioma, phenomena previously described in psychiatric patients. The authors suggest that these associated genes be further investigated for pharmacological intervention.¹⁰

Moving away from one-size-fits-all medicine

A great amount of progress has been made toward identifying potential biomarkers. Mental health conditions, with their many presentations within a disorder combined with shared symptoms between disorders, makes objective methods to properly diagnose and successfully treat, imperative. Much of the research requires further validation before biomarker-based tests can be put to use in the clinic. However, as the field pushes forward, so too do insights into the etiology of many psychiatric conditions and the impending end of excruciating months and years spent sifting through pills and regimens that offer promises of healing but ultimately fail to deliver.

References

1. College of American Pathologists, The “Liquid Biopsy, Accessed September 21, 2023

2. Le-Niculescu, H., Roseberry, K., Gill, S.S. et al. Precision medicine for mood disorders: objective assessment, risk prediction, pharmacogenomics, and repurposed drugs. Mol Psychiatry 26, 2776–2804 (2021). 

3. Wang PS, Berglund P, Olfson M, Pincus HA, Wells KB, Kessler RC. Failure and Delay in Initial Treatment Contact After First Onset of Mental Disorders in the National Comorbidity Survey Replication. Arch Gen Psychiatry. 2005;62(6):603–613. 

4. CDC, National Center for Health Statistics, Antidepressant Use Among Adults: United States, 2015-2018, 

5. Nirmita Panchal , Heather Saunders , Robin Rudowitz, The Implications of COVID-19 for Mental Health and Substance Use, March 20, 2023, KFF.org,

6. Roseberry, K., Le-Niculescu, H., Levey, D.F. et al. Towards precision medicine for anxiety disorders: objective assessment, risk prediction, pharmacogenomics, and repurposed drugs. Mol Psychiatry (2023). 

7. McQuaid RJ. Transdiagnostic biomarker approaches to mental health disorders: Consideration of symptom complexity, comorbidity and context. Brain Behav Immun Health. 2021 Jul 28;16:100303. 

8. Liu H, Sun Y, Zhang X, Li S, Hu D, Xiao L, Chen Y, He L, Wang DW. Integrated Analysis of Summary Statistics to Identify Pleiotropic Genes and Pathways for the Comorbidity of Schizophrenia and Cardiometabolic Disease. Front Psychiatry. 2020 Apr 17;11:256.

9. Ullah A, Long X, Mat WK, Hu T, Khan MI, Hui L, Zhang X, Sun P, Gao M, Wang J, Wang H, Li X, Sun W, Qiao M, Xue H. Highly Recurrent Copy Number Variations in GABRB2 Associated With Schizophrenia and Premenstrual Dysphoric Disorder. Front Psychiatry. 2020 Jun 30;11:572.

10. Cao H, Baranova A, Yue W, Yu H, Zhu Z, Zhang F, Liu D. miRNA-Coordinated Schizophrenia Risk Network Cross-Talk With Cardiovascular Repair and Opposed Gliomagenesis. Front Genet. 2020 Mar 4;11:149.