Is Depression Detectable Through Lab Tests?

Measuring depression accurately involves assessing the levels of serotonin and inflammatory molecules in the blood. Psychiatrists use subjective assessments like talking to the patient and observing symptoms to diagnose mental disorders. Measuring the levels of serotonin and inflammatory molecules in the blood can provide objective indicators of depression, leading to a more accurate diagnosis.

The traditional approach of relying solely on subjective statements and assessments is not always effective in identifying mental disorders. Even when symptoms are present, doctors may struggle to interpret them accurately. For instance, bipolar disorder can be easily mistaken for depression, especially since people typically seek help when they are feeling down. Choosing the wrong medication in such cases can trigger a manic episode and exacerbate the disorder. Additionally, depression may be confused with non-psychiatric conditions such as hypothyroidism because their symptoms are quite similar. Therefore, it is crucial to consider objective indicators like blood tests in addition to subjective assessments when diagnosing mental disorders.

Doctors can diagnose non-psychiatric illnesses using a different approach that involves collecting anamnesis and examining biomarkers to determine if a pathogenic process has developed or if the patient is responding to treatment. For instance, X-rays can confirm if a bone is broken, while measuring blood pressure, stroke risk, or taking a blood glucose test can diagnose diabetes. However, mental disorders have not traditionally been diagnosed using these objective measures. It begs the question: why are mental disorders not diagnosed in the same way?

Theories of depression

To identify biomarkers that could indicate depression, researchers need to conduct a thorough study of the disease. Modern science currently only understands the symptoms and physiological changes associated with depression, rather than its underlying causes.

However, numerous hypotheses exist regarding the origins of depression. Some experts believe that negative experiences, such as the loss of a loved one, or systematic cognitive errors that result in negative thinking, may cause depression. Other theories emphasize possible biological causes of depression, which could potentially serve as biomarkers for the condition. Below are some of the most compelling theories.

Hypothesis 1: Monoamines and chemical imbalances as contributing factors

Neurons, highly specialized cells in the nervous system, transmit information using chemical signals through intermediary molecules known as neurotransmitters, including monoamines like norepinephrine, dopamine, and serotonin. Dopamine stimulates motivation, while serotonin regulates mood, and both are essential for functions such as learning, memory, sleep, and motor control. Meanwhile, the hormone norepinephrine boosts alertness, arousal, and concentration, making it a key player in the brain’s reward system.

The monoamine theory suggests that depression occurs due to a deficiency of these three neurotransmitters in the nervous system. To determine biomarkers of depression, researchers measure the concentration of monoamine metabolites in cerebrospinal fluid, blood, and urine, since direct measurement in the living brain is not feasible.

Hypothesis 2: Investigating the relationship between HPA axis hormones and stress

Several studies have linked depression to elevated levels of “stress hormones” such as cortisol, corticotropin, and corticorelin, which are produced by the hypothalamic-pituitary-adrenal (HPA) system. According to the stress hypothesis, depression is caused by disruptions in the HPA axis. Therefore, researchers use biomarkers of depression, such as stress hormone concentrations in urine, blood, saliva, and cerebrospinal fluid, to examine this relationship.

Hypothesis 3: Examining the role of growth factors in neuroplasticity

Depression is often linked to a slowdown in the creation of new neural connections in the brain, called neurogenesis. The hippocampus, a part of the brain, is particularly affected. Antidepressants can help by stimulating neurogenesis and neuron survival. At the molecular level, depression lowers the levels of two important molecules in the blood, brain-derived neurotrophic factor and insulin-like growth factor-1. These molecules are responsible for regulating synaptic plasticity and the growth and maintenance of cells in the body, respectively. Scientists use them as biomarkers of depression.

Studying neurogenesis and biomarkers like brain-derived neurotrophic factor and insulin-like growth factor-1 can help us understand more about depression and develop better treatments for it. Although researchers are still unsure of the exact causes and effects of depression, identifying these markers can aid in diagnosis and treatment.

Hypothesis 4: Investigating the connection between cytokines and neuroinflammation

Cytokines are used by the immune system to either cause or suppress inflammation in the body. They also play a crucial role in brain development and communication between neurons. When proinflammatory cytokines are present in high amounts, they can lead to sleep disturbances, loss of appetite, reduced enjoyment of life, and decreased social ability.

While a common cold is a common occurrence, it serves as an important evolutionary mechanism that allows the body to conserve energy while fighting off the disease and preventing its spread to others. However, prolonged inflammation caused by cytokines can damage brain cells and lead to depression, resulting in chronic effects on the body. Therefore, it is important to monitor the levels of interleukin 1, interleukin 6, tumor necrosis factor, and C-reactive protein in the blood as potential biomarkers of depression.

Final Verdict: Determining the Correct Perspective

Currently, all depression theories are still theoretical. However, it is evident that none of the biomarkers mentioned are precise enough to diagnose depression. Therefore, relying on a single biomarker will not be effective since other psychiatric and non-psychiatric conditions also exhibit the same biomarkers, such as schizophrenia and arthritis.

In 2011, a group of American researchers proposed a new method that involves using a panel of biomarkers to measure various biological abnormalities linked to depression. This panel includes factors such as neuronal, immune, endocrine, and metabolic factors.

The researchers conducted tests on almost 1000 patients to identify 33 immune-neuroendocrine biomarkers. The method proved highly accurate in detecting depression in patients with a first episode of depression but without chronic nonpsychiatric illness. However, the issue remained whether mental disorders can be diagnosed in people with other chronic diseases that affect the same biomarkers as in the panel. Currently, there is no answer to this question.

The diagnostic process for biomarkers can be complex because the same disorders can manifest in different ways. For example, one person with depression may not feel any joy from favorite activities and have a mood that is at zero or worse, while another may complain of headaches and a lack of appetite but not exhibit classic depression symptoms. Therefore, the same set of biomarkers may not work for both cases. In melancholic depression, the HPA axis is often disrupted, while in somatic depression, cortisol and other stress hormones may not be elevated.

Individualized Solutions

Scientists are attempting to determine the subtypes of depression and their neural correlates, while also researching accurate methods for diagnosing mental disorders. However, diagnosing mental disorders has proven to be a complicated task, as it is not possible to simply test blood to determine the presence of disorders like schizophrenia or depression. Despite this challenge, the development of biomarkers shows promise in assisting with tailoring treatments for individual patients, making it a technology to look out for in the future.

Neuroinflammation researchers recommend the measurement of inflammatory cytokines in the blood to prescribe a specific drug based on the results. In 2019, scientists attempted to predict the effectiveness of two common antidepressants, paroxetine and venlafaxine, by using this method. However, they could not identify any unambiguous biomarkers for venlafaxine. In contrast, for paroxetine, the biomarkers identified were interleukin 10, interleukin 6, and tumor necrosis factor-α. It is important to note that the initial level of interleukin 10 determines the effectiveness of paroxetine; a higher abundance of interleukin 10 indicates a better prognosis.

A team of Chinese and American scientists has developed an artificial intelligence program that can predict the effectiveness of drugs by analyzing electroencephalograms. To train the program, they fed it databases containing electroencephalograms and placebo results for antidepressants. The electrical impulses of individuals whose brains are positively affected by antidepressants have been identified in the field of artificial intelligence. When connected to the experiment, the program accurately identified which participants would respond to sertraline treatment based on changes in brain waves. Interestingly, individuals who did not respond to sertraline treatment were found to benefit from psychotherapy and transcranial magnetic stimulation, which were identified by the artificial intelligence program.

Observing the symptoms allows us to move away from the practice of guessing whether an antidepressant will be effective. This new approach has the potential to revolutionize psychiatric practice. Rather than relying on trial and error with antidepressants, it is now possible to identify effective medications in advance or choose an alternative treatment. By doing so, patients with depression can save time, money, and effort, as we no longer need to try multiple medications before finding one that works.