Collaboration Projects

Study Rationale

Currently available pharmacological treatments often fail to alleviate symptoms for many individuals with bipolar disorder and the field has a need for high-throughput drug screens that can identify new candidates.

Hypothesis

The predictive power of omic scale datasets and AI has a transformative potential in healthcare.

Study Design

Discovery Research Team Tam and the Brain Omics Platform are leveraging the largest single-cell omic level datasets from samples of people with bipolar with novel drug prediction algorithms. The researchers aim to find novel drug predictions from single-cell multi-omic data by growing organoids to harvest for single-cell sequencing. Additionally, teams will test drug predictions on the brain organoid system.

Impact on Diagnosis & Treatment

This research can potentially better classify bipolar presentation among a diverse population as well as outline heterogeneous responses to drugs at the single cell level. The work can also inform the drug prediction results by providing data on real-time responses under the effect of drug treatment. These results can further iterate on drug prediction and design.

Study Rationale

There is growing evidence that familial mitochondrial genetic disorders can play a part in the presentation of bipolar disorder. Bipolar is also linked to abnormalities in circadian function and a possible interplay between cellular energy levels, as regulated by mitochondria, and disordered sleep.

Hypothesis

Mitochondrial abnormalities in sleep-regulating neurons cause the sleep dysfunction that characterizes bipolar disorder.

Study Design

Elizabeth Jonas from Discovery Research Team Blumberg demonstrated that brain organoids from the cells of individuals with bipolar exhibit an increased mitochondrial leak. Building on those key findings, Discovery Research Team Kauer will measure mitochondrial function in a mouse model generated using viruses designed by Lief Fenno for CRISPR-mediated deletion of bipolar-associated genes in sleep-regulating neurons in mice. They will conversely virally manipulate mitochondrial function in a mouse model and measure sleep function and neuronal activity. Together, these findings will explain the relationship between mitochondrial dysfunction and aberrant sleep patterns.

Impact on Diagnosis & Treatment

The project aims to determine whether mitochondrial dysfunction seen in individuals with bipolar disorder contributes to the well-documented abnormal sleep patterns that characterize bipolar. This could provide advances in the etiological understanding of bipolar disorder and lead to novel treatment strategies.

Study Rationale

Both the dopamine system and the Clock gene are strongly associated with bipolar disorder, but the mechanisms by which they contribute to symptoms are unknown.

Hypothesis

Disruption of the Clock gene within dopamine neurons leads to proteomic maladaptations that underlie bipolar-associated changes in brain activity and behavior.

Study Design

Discovery Research Team Kauer and the Brain Omics Platform are collaborating to identify maladaptations in dopamine neurons of the ventral tegmental area with loss of Clock, which likely drive functional changes in neural activity and bipolar disorder-associated behaviors. The researchers are characterizing such adaptations both in the baseline state and in response to a sleep loss stress challenge, associated with mood cycling in bipolar disorder. In addition, they will intersect the data from this project with complementary datasets from the human brain in the Brain Omics Platform.

Impact on Diagnosis & Treatment

This project will provide the first opportunity to start distinguishing between the primary molecular maladaptations driven by genetic risk variants that regulate synaptic, cellular, and circuit function from those that occur in response to disease-relevant external stimuli in the context of these variants.

Study Rationale

Altogether, the etiology of bipolar disorder is poorly understood, particularly the extent to which distinct bipolar-associated genetic mutations converge on one or more pathogenic mechanisms.

Hypothesis

Diverse risk variants converge on a smaller number of shared biological functions.

Study Design

Hongying Shen from Discovery Research Team Blumberg and Ben Neale from the Genetics Platform are identifying common pathways affected by both common and rare genetic risk variants and probing those prioritized pathways with targeted drug candidates. This work will apply a highly scalable CRISPR screen to evaluate the impact of bipolar disorder risk gene variation.

Impact on Diagnosis & Treatment

This work will identify points of molecular and cellular convergence of bipolar disorder risk genes that can be used to prioritize biological pathways for therapeutic intervention. It will provide crucial insights into the functional mechanisms underlying bipolar disorder, making improved novel and tailored therapeutic strategies possible.