Psychiatry 2019 Projects

Project Title: Neurocognitive characterization of Childhood-onset Obsessive-Compulsive Spectrum Disorders

Faculty Mentor’s Name: Carol Mathews
Email: carolmathews@ufl.edu

Student’s Name: Rachel Gilbert
Email: rgilbert1648@ufl.edu

Project Description:

Childhood-onset Obsessive-Compulsive Spectrum Disorders (OCSD) are a group of neuropsychiatric disorders characterized by repetitive thoughts and behaviors. They include Obsessive-compulsive disorder, Tourette syndrome, Chronic/Persistent Tick disorder, Trichotillomania, and Excoriation Disorder. As a group, these disorders are polygenic, highly heritable, and also highly comorbid amongst the group and with other neuropsychiatric and developmental disorders (e.g. autism spectrum disorders) (1-4). Onset is typically seen in school age children (ages 8-12) and together affects approximately 5% of the population (5, 6). Additionally, OCSD cause significant functional impairment and distress for individuals and caretakers.

OCSD symptomology has been implicated in abnormal top-down cortical control, more specifically abnormal regulation of the cortico-striatal-thalamo-cortical (CSTC) circuitry. This impaired regulation is thought to play a significant role in the pathophysiology of OCSD with atypical performance monitoring, response inhibition, and goal directed behavior (7,8). As well, challenges in frontally mediated neurocognitive processes such as cognitive flexibility, set shifting, emotional reactivity, and regulation have clinically characterized OCSD (9,10). As previously mentioned, these clinical phenotypes are highly heritable and thus the inclusion of genetic analysis alongside behavioral categorization may offer insight into the nature of these neurocognitive challenges in OCSD, as well as improved diagnosis and treatment.

Project Title: New-onset depression in patients with new medical diagnoses: a scoping review

Faculty Mentor’s Name: Kevin Wang
Email: kwang@ufl.edu

Student’s Name: Taylor Gianangelo
Email: gianangelo@ufl.edu

Project Description:

Depression is a common and debilitating psychiatric disorder that affects more than 300 million people around the world (1). It is especially burdensome when accompanying other medical conditions. New-onset depression has been associated with many new medical diagnoses such as cancer, chronic lung disease, and heart disease (2). In addition, onset of depression following acute medical events, such as traumatic brain injury (TBI) and stroke, is common (3,4). Post-stroke depression impedes recovery, hinders return to independence, and decreases long-term survival of affected patients (3). Furthermore, studies have shown that patients who suffer a myocardial infarction and subsequently develop depression are at an increased risk for cardiac mortality (5).

These examples suggest that new-onset depression following a new medical diagnosis or acute medical event may be distinct from major depressive disorder (MDD), and it is possible that such a difference could be detected at the molecular level via various biomarkers. Biomarkers that may play a role in depression can be divided into numerous descriptive groups, such as transcriptomic, proteomic, genomic, and telomeric (6). Within the class of non-coding transcriptomic biomarkers, microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) have shown significant potential to serve as reliable biomarkers for depression (6,7). Special attention has been given to miRNAs, which regulate many cellular and molecular pathways (8).

To date, an example that bridges the ideas of new-onset depression in medical populations and biomarkers for depression can be seen in patients who have experienced a TBI. One study has concluded that preexisting hyperlipidemia in patients who suffered a TBI was associated with a 1.72-fold increased incidence in the development of depression; this suggests that preexisting hyperlipidemia could be used to predict, and possibly prevent, the development of depression in these patients (4). To this end, the overall goals of this project are to review medical conditions associated with new-onset depression and to discuss potential biomarkers that can aid in identifying patients who are at risk of developing depression and in evaluating response to depression treatment.

  1. Depression. Fact sheets. World Health Organization, 2018.
  2. Polsky D, Doshi JA, Marcus S, et al. Long-term Risk for Depressive Symptoms After a Medical Diagnosis. Arch Intern Med. 2005; 165: 1260-6.
  3. Salinas J, Beiser A, Himali JJ, Rosand J, Seshadri S and Dunn EC. Factors Associated With New-Onset Depression After Stroke. J Neuropsychiatry Clin Neurosci. 2016; 28: 286-91.
  4. Wee HY, Ho CH, Liang FW, et al. Increased risk of new-onset depression in patients with traumatic brain injury and hyperlipidemia: the important role of statin medications. J Clin Psychiatry. 2016; 77: 505-11.
  5. Dickens C, McGowan L, Percival C, et al. New onset depression following myocardial infarction predicts cardiac mortality. Psychosom Med. 2008; 70: 450-5.
  6. Gururajan A, Clarke G, Dinan TG and Cryan JF. Molecular biomarkers of depression. Neurosci Biobehav Rev. 2016; 64: 101-33.
  7. Lopez JP, Kos A and Turecki G. Major depression and its treatment: microRNAs as peripheral biomarkers of diagnosis and treatment response. Curr Opin Psychiatry. 2018; 31: 7-16.
  8. Tavakolizadeh J, Roshanaei K, Salmaninejad A, et al. MicroRNAs and exosomes in depression: Potential diagnostic biomarkers. J Cell Biochem. 2018; 119: 3783-97.

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