Key Highlights:
  • There are distinct connectivity alterations between large-scale brain networks in depression.
  • Connectivity can be used to subtype depression when symptoms cannot. 
  • Advances in connectomics will drive future individualized depression treatments.

Major depressive disorder (MDD) as a mental illness is commonly communicated as a chemical imbalance in the brain, causing changes in a person’s mood, energy, and concentration. However, our understanding of the disorder has improved such that we now understand that these chemical imbalances cause shifts in the way regions and networks of the brain communicate, generating the variety of symptoms which define it1-3.

 

Growing evidence from brain imaging studies supports that changes in functional connectivity—the coordinated activity between different brain regions—plays a critical role in the progression of the disease4. Connectomics is a tool that allows for streamlined investigation of connectivity and could lead to more effective, individualized treatments for MDD.

 

 

What is Major Depressive Disorder (MDD)?

MDD is one of the most common psychiatric disorders, affecting at least five percent of the world’s population4,5. Individuals suffering from MDD experience persistently low moods, feelings of hopelessness, and anhedonia, also known as the inability to feel pleasure4,5. Nearly two-thirds of people with MDD have suicidal ideation, and roughly 15% of those affected die by suicide4

 

The symptoms of MDD disrupt one’s ability to carry out their day-to-day responsibilities and place undue strain on relationships and career performance. Worryingly, MDD carries high comorbidities with developing substance use disorders, obsessive-compulsive disorder, bipolar disorder, and anxiety4.

Current Treatment Options for Depression

 

Antidepressant medication is the frontline treatment for MDD and is normally administered in conjunction with psychotherapy4. However, these frontline medications are only effective in roughly 50% of patients who present with MDD, leaving a large proportion of sufferers as “treatment resistant”, unlikely to reach remission with basic pharmaceutical intervention6. Neurostimulation via transcranial magnetic stimulation (TMS) or electroconvulsive therapy (ECT) are employed when pharmaceutical approaches are ineffective or cause intolerable side effects like sexual dysfunction and weight gain4,7,8.

There is no “silver bullet” treatment for depression, and each of the above carry their own unique drawbacks. For instance, Cognitive Behavioural Therapy is known to be highly variable and produce a weak response when used in isolation to treat depression9. While ECT is more effective, it is highly invasive and can cause memory loss and changes in blood pressure - hence why it is usually a last resort treatment10. No silver bullet exists to treat depression because depression is not just one disease. It is ultimately defined by its heterogeneity, and it is unique to each sufferer. For this reason, a more personalized approach to depression, such as the one offered by connectomics, becomes a necessity to determine optimal treatment pathways.


Puzzle Pill

Figure 1.  The most common treatment option for MDD is antidepressants

 

Depression as a Personalized Disorder

 

Research has confirmed a long-suspected idea about depression—it isn’t a single disorder, but many4.

Drysdale et al. investigated nearly 1,200 depression patients, and successfully identified four distinct subtypes based upon connectivity alterations in the limbic system and frontostriatal pathways (subcortical pathways which feed into the default mode, salience, and central executive networks)11,12. By clustering subjects based upon network abnormalities, researchers developed sensitive, highly-specific neuroimaging biomarkers to differentiate depression subtypes11.

In another paper, resting-state fMRI revealed that patients with treatment-resistant depression had more localized network alterations than those patients who responded to treatment8. While both groups had disruptions to prefrontal-limbic-thalamic connectivity, treatment-resistant depression was characterized by stark alterations to prefrontal-limbic connectivity13.

Future work could provide psychiatrists and psychologists with the information they need to treat the patient’s depression subtype rather than the current generalized approach. In addition, identifying abnormal network connectivity could provide targets for neurostimulation techniques like TMS.

Connectivity Alterations in Depression

 

A number of academic publications have highlighted underlying neural changes during the presence of depressive symptoms. The limbic system appears to play a prominent role in the progression of these symptoms - likely due to its role in emotional regulation. Functional connectivity analyses have consistently demonstrated abnormal communication patterns between limbic system circuits and areas of the prefrontal cortex, which encode cognition 14,15.

Moreover, Fang et al. recently utilized structural connectivity to delineate depressive patients from healthy controls, identifying that greater connectivity between frontal areas and the limbic system as the key biomarker for categorizing individuals 16.

Successful antidepressant treatment regimes also appear to target these same systems, as it was recently observed that functional connectivity changes between the dorsolateral prefrontal cortex (dlPFC) and insula cortex were associated with early treatment responses 17

 

Brain Networks Associated with Depression

 

Research has associated depression with significant disruptions to connectivity in many key brain networks—tightly coupled brain regions that fluctuate in activity together during a task or at rest.  

These networks and their contributions to depressive symptoms are:  

  • The salience network undergoes structural changes during depression, reducing in volume and increasing in coupling with the Default Mode Network, likely underpinning the characteristic changes in mood during MDD18.
  • The sensorimotor network which demonstrates altered functional connectivity which scales with Depression intensity, and manifests feelings of fatigue, heaviness of limbs, and body and chest discomfort19.
  • The visual system receives and processes visual stimuli. In MDD, retinal input to the visual system is compromised, causing deficiencies in contrast interpretation, and perceptual loss of complex visual information20.
  • The limbic system, the core network for emotion, reactions to new stimuli, and memory - during depression induces feelings of detachment from self and others, as well as emotional reactivity21.
  • The default mode network (DMN) which has reliably demonstrated heightened functional connectivity in MDD, relating directly to the severity and length of depressive episodes. The DMN additionally encodes self-referential thought, future thinking, and autobiographical memory, functions which become compromised in MDD22.

Identifying and characterizing alterations in these important brain networks is the first step to advancing our understanding of depression.

 

Salience Network-1

Figure 2.  The salience network is one of many networks associated with symptoms of depression

 

The Future: Depression Therapy with Connectomics

 

Recently, connectomics has been used to explore the heterogeneity of depression. Siddiqi et al identified that independent depressive symptoms and their severity are driven by different connections between the major brain networks which underpin the disorder. Namely, anxiogenic symptoms were driven by connections from the Default Mode Network, whereas dysphoric symptoms - such as sadness and anhedonia - were driven by connections arising from the salience network23.

 

Picture 1

Figure 3. Color map of brain areas responsible for Anxiosomatic vs. Dysphoric symptoms of depression - adapted from Siddiqi et al., 2020

 

Moreover, evaluating an individual’s unique depression via their own brain connectivity enabled these researchers to adopt a more personalized neurostimulatory approach to effectively treat their patients symptoms. Another study, the Stanford Accelerated Intelligent Neuromodulation Therapy (SAINT), adopted a similar approach, targeting unique brain regions with TMS based on their patients' underlying functional connectivity. This study found that 90.5% of the MDD patients investigated met remission criteria after five days of treatment, demonstrating the time-saving and effective response of leveraging connectomics to treat MDD24

 

Connectomics is an exciting tool for studying depression, and it is clear that the human connectome plays an important role in the symptoms which define it. As the field of connectomics continues to progress, future individualized treatments may soon be uncovered.

References

Expand for full list of references
    1. Drago T, O'Regan PW, Welaratne I, et al. A comprehensive regional neurochemical theory in depression: a protocol for the systematic review and meta-analysis of 1H-MRS studies in major depressive disorder. Syst Rev. 2018;7(1):158. Published 2018 Oct 12. doi:10.1186/s13643-018-0830-6
    2. Luykx JJ, Laban KG, van den Heuvel MP, et al. Region and state specific glutamate downregulation in major depressive disorder: a meta-analysis of (1)H-MRS findings. Neurosci Biobehav Rev. 2012;36(1):198-205. doi:10.1016/j.neubiorev.2011.05.014
    3. Fakhoury M. Revisiting the Serotonin Hypothesis: Implications for Major Depressive Disorders. Mol Neurobiol. 2016;53(5):2778-2786. doi:10.1007/s12035-015-9152-z
    1. Bains N, Abdijadid S. Major Depressive Disorder. In: StatPearls. Treasure Island (FL)2021.
    2. Pedersen CB, Mors O, Bertelsen A, et al. A comprehensive nationwide study of the incidence rate and lifetime risk for treated mental disorders. JAMA Psychiatry. 2014;71(5):573-581.
    3. Gaynes BN, Rush AJ, Trivedi MH, Wisniewski SR, Spencer D, Fava M. The STAR*D study: treating depression in the real world. Cleve Clin J Med. 2008;75(1):57-66. doi:10.3949/CCJM.75.1.57
    4. Teng M, Khoo AL, Zhao YJ, et al. Neurostimulation therapies in major depressive disorder: A decision-analytic model. Early Interv Psychiatry. 2021;15(6):1531-1541.
    5. Gafoor R, Booth HP, Gulliford MC. Antidepressant utilisation and incidence of weight gain during 10 years' follow-up: population based cohort study. BMJ. 2018;361:k1951.
    6. Zhang A, Borhneimer LA, Weaver A, et al. Cognitive behavioral therapy for primary care depression and anxiety: a secondary meta-analytic review using robust variance estimation in meta-regression. Journal of Behavioral Medicine. 2019;42(6):1117-1141. doi:10.1007/S10865-019-00046-Z/TABLES/5
    7. Electroconvulsive therapy (ECT) - Beyond Blue. Accessed May 6, 2022. https://www.beyondblue.org.au/the-facts/depression/treatments-for-depression/medical-treatments-for-depression/electroconvulsive-therapy-ect
    8. Drysdale AT, Grosenick L, Downar J, et al. Resting-state connectivity biomarkers define neurophysiological subtypes of depression. Nat Med. 2017;23(1):28-38.
    9. Kalivas PW, Volkow N, Seamans J. Unmanageable motivation in addiction: a pathology in prefrontal-accumbens glutamate transmission. Neuron. 2005;45(5):647-650.
    10. Lui S, Wu Q, Qiu L, et al. Resting-state functional connectivity in treatment-resistant depression. Am J Psychiatry. 2011;168(6):642-648.
    11. Anand A, Li Y, Wang Y, et al. Activity and connectivity of brain mood regulating circuit in depression: a functional magnetic resonance study. Biol Psychiatry. 2005;57(10):1079-1088.
    12. Kaiser RH, Whitfield-Gabrieli S, Dillon DG, et al. Dynamic Resting-State Functional Connectivity in Major Depression. Neuropsychopharmacology. 2016;41(7):1822-1830.
    13. Fang P, Zeng LL, Shen H, et al. Increased Cortical-Limbic Anatomical Network Connectivity in Major Depression Revealed by Diffusion Tensor Imaging. PLOS ONE. 2012;7(9):e45972. doi:10.1371/JOURNAL.PONE.0045972
    14. Yuan H, Zhu X, Tang W, Cai Y, Shi S, Luo Q. Connectivity between the anterior insula and dorsolateral prefrontal cortex links early symptom improvement to treatment response. J Affect Disord. 2020;260:490-497.
    15. Shao J, Meng C, Tahmasian M, Brandl F, Yang Q, Luo G, Luo C, Yao D, Gao L, Riedl V, Wohlschläger A, Sorg C. Common and distinct changes of default mode and salience network in schizophrenia and major depression. Brain Imaging Behav. 2018;12(6):1708-1719. doi:10.1007/S11682-018-9838-8
    16. Ray D, Bezmaternykh D, Mel’nikov M, Friston KJ, Das M. Altered effective connectivity in sensorimotor cortices is a signature of severity and clinical course in depression. Proc Natl Acad Sci U S A. 2021;118(40). doi:10.1073/PNAS.2105730118/-/DCSUPPLEMENTAL
    17. Salmela V, Socada L, Söderholm J, Heikkilä R, Lahti J, Ekelund J, Isometsä E. Reduced visual contrast suppression during major depressive episodes. J Psychiatry Neurosci. 2021;46(2):E222-E231. doi:10.1503/JPN.200091
    18. Buchheim A, Viviani R, Kessler H, Kächele H, Cierpka M, Roth G, George C, Kernberg OF, Bruns G, Taubner S. Changes in Prefrontal-Limbic Function in Major Depression after 15 Months of Long-Term Psychotherapy. PLOS ONE. 2012;7(3):e33745. doi:10.1371/JOURNAL.PONE.0033745
    19. Sambataro F, Wolf ND, Pennuto M, Vasic N, Wolf RC. Revisiting default mode network function in major depression: evidence for disrupted subsystem connectivity. Psychol Med. 2014;44(10):2041-2051. doi:10.1017/S0033291713002596
    20. Siddiqi SH, Taylor SF, Cooke D, Pascual-Leone A, George MS, Fox MD. Distinct Symptom-Specific Treatment Targets for Circuit-Based Neuromodulation. Am J Psychiatry. 2020;177(5):435-446. doi:10.1176/appi.ajp.2019.19090915
    21. Cole EJ, Stimpson KH, Bentzley BS, et al. Stanford accelerated intelligent neuromodulation therapy for treatment-resistant depression. American Journal of Psychiatry. 2020;177(8):716-726. doi:10.1176/APPI.AJP.2019.19070720/ASSET/IMAGES/LARGE/APPI.AJP.2019.19070720F3.JPEG