Autism Spectrum Disorder (ASD)
Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder that may have some genetic component. Affected kids may have impairment in social communication, repetitive behavior, and sometimes developmental delays. The diagnosis occurs very early, usually by the time the child is around 2 years old.
Our lab works with parents of children with ASD, trying to better understand the changes that occur in the children's brain cells in the hope to find treatment that will improve the kids' social and communicative skills. Some of the parents come to the lab routinely to follow their children's cells that are growing in the lab.
Currently in the lab, we have reprogrammed induced pluripotent stem cells (iPSCs) from children that carry several types of mutations or variations that cause ASD and different developmental delays. Among these we have produced human iPSCs from several children with genetic variations in the IQSEC2 gene, Shank3 gene, UBTF gene, the 17p11.2 deletion syndrome, 7q11.23 (7Dup) syndrome, and the SLC1A4 gene
Our model system using human derived neurons and brain organoids is well-suited to measure the changes in the children's neurons to first seek their neurophysiological changes and to then target these changes with drugs that will later be suggested as possible treatment
Reprogrammed in the lab using Sendai Vectors
White blood cells from a child with ASD
iPSCs from a child with ASD deletion syndrome
Differentiation into hippocampal neurons
Hippocampal neurons from a child with ASD
Parkinson’s disease (PD)
Parkinson’s disease was first described in 1817 by James Parkinson. He described it as a “shaking pulsy”; involuntary tremulous motion with lessened muscular power. Patients with PD experience movement difficulties with three cardinal signs: tremor, rigidity and bradykinesia. Other non-motor symptoms include loss of smell, dementia, sleep disorders, reduced bowel movement and more. Pathological examination of patients’ brains shows aggregates of the α-synuclein protein in the patients’ nerve cells. These aggregates are termed Lewy bodies and are considered a hallmark of Parkinson’s disease. These aggregates are hypothesized to cause the severe loss of dopaminergic neurons in the patients’ substantia nigra pars compacta, an area in the midbrain, very densely populated by dopaminergic neurons that indirectly regulate fine motor movement.
​
There are a few genes in which mutations were shown to have a causative effect of this disease. These include mutations in the alpha synuclein (SNCA), leucine rich repeat kinase 2 (LRRK2), parkin RBR E3 ubiquitin protein ligase (PRKN), PTEN-induced kinase 1 (PINK1), glucosylceramidase beta (GBA) and Parkinsonism associated deglycase (PARK7). There are many more genes associated with the disease, but without a definite causative role. However, these mutations account for about 15% of the Parkinson’s cases, while the rest of the cases are considered sporadic, and the disease cause is not known.
​
We have fibroblasts that were reprogrammed into iPSCs from human patients with different PD causing mutations, as well as sporadic PD. We differentiate them into dopaminergic neuronal cultures and into midbrain organoids enriched with dopaminergic neurons. We see a distinct electrophysiological phenotype that is common to dopaminergic neurons that were derived from PD patients, and we are investigating how these physiological alterations that we see when the neurons are young, trigger a cascade of events that eventually lead to cell death that is specific to dopaminergic neurons in PD.
​
Bipolar disorder (BD)
Already at the 1st century Aretaeus of Cappadocia, a Greek physician, wrote about a link between mania and depression “Melancholia is the beginning and a part of mania. The development of a mania is really a worsening of the disease (melancholia) rather than a change into another disease”. Many centuries later psychiatrists and physicians such as Teophilus Bonet (17th century), Jean-Pierre Falret (19th century) and Jules Baillarger (19th century) also described a disease where mania and depression cycle within the same patient. The term bipolar (two poles) first appeared in the American Psychiatric Association’s Diagonostic and Statistical Manual of Mental Disorders (DSM) in 1980.
​
Bipolar disorder (BD) is a progressive psychiatric disorder with 1-2% prevalence worldwide. Patients experience recurrent episodes of depression and mania and are at a high risk of suicide. The first line of treatment usually involves lithium derivatives. While lithium helps many BD patients, unfortunately not all respond with a good outcome to lithium treatment. The genetics of BD is complex with many associations, but no genes that were identified as causative. This genetic heterogeneity has challenged the development of animal and cellular models, and the available animal models do not fully recapitulate the disease phenotype. The use of neurons derived from iPSCs of human patients has allowed us to identify a physiological phenotype of hyperexcitability in hippocampal neurons that were derived from BD patients. BD hippocampal neurons have a remarkable ability to sustain activity over long periods of time.
Interestingly we had shown that BD neurons share a common phenotype of hyperexcitability but divide into sub-populations with distinct features. Neurons derived from patients who respond to lithium treatment are fast spiking, while those derived from patients who do not respond to lithium are physiologically unstable and strongly shift their excitability with small changes in their environment. Overall these two sub classes are so different from one another, that it is possible to predict directly from physiological measurements of these neurons which of the patients will respond to lithium.
Stern et al. Molecular Psychiatry 2018
After measuring the neurophysiological properties of dentate gyrus and CA3 pyramidal hippocampal neurons, we were able to reveal alteration in ionic currents that cause the hyperexcitability. Further, we observed that hippocampal neurons derived from BD patients who do not respond to lithium, possess a physiological instability causing them to shift drastically between hypoexcitable and hyperexcitable states, leaving the neuronal network in a multi-excitatory state and possibly contributing to affective lability in BD patients. Strikingly, over prolonged recordings, the BD network sometimes self-organizes in a global hypoexcitability state, and sometimes in a global hyperexcitability state.
While the healthy brain consists of neurons with similar excitability, the BD brain consists of a large proportion of neurons that are very hyperexcitable or hypoexcitable. Conditions occur occasionally that causes a global shift towards super activity and sometimes towards complete inactivity, suggesting behavioral states such as mania and depression
Stern et al. Biological Psychiatry 2019
Stern et al. Biological Psychiatry 2020
​
Biomarkers for drug response
Precision medicine has revolutionized cancer treatment by the use of new techniques such as DNA sequencing. This revolution has increased survival rates dramatically. Other fields of medicine, such as psychiatric disorders are lagging far behind due to lack of investment along with the complexity of these disorders. Owing to a limited understanding of the pathophysiology of these disorders, treatment options follow a trial-and-error strategy, sometime having months and years pass until finding a suitable drug. During this time, the patients are practically untreated, and often deteriorate to a point of no return, losing their work place, their friends and their ability to function in society. This is truly unfortunate, since especially in psychiatric disorders, sometime small interventions can save a life both figuratively and literally.
​
Multiple studies suggest sub populations within different psychiatric disorders. Within each sub-population, the symptoms are more homogeneous, sometimes they share familial genomic associations, and their response to certain drugs may be similar. Our previous work with bipolar disorder also suggests sub populations in which the physiology is so different that drug
response can be predicted. We have a large set of immortalized lymphoblasts from patients with characterized drug response and we use different biological features from these lymphoblasts to predict drug response in psychiatric patients. We are developing computational models to build classification schemes to find the most suitable drugs.
Stern et al. Open Biology 2018
​
​
We have developed a neural network-based algorithm that can precisely predict how a bipolar disorder patient would respond to lithium treatment. This method is cheap, fast, and reliable. An invention disclosure was submitted. Check out the exciting results in Mizrahi at al.
_edited.jpg)
_edited.jpg)
_edited.jpg){kind=small}
_edited.jpg){kind=small}
LOG2FoldChange
Analysis of RNA sequencing results confirms that there are many differentially expressed genes between LCLs of bipolar disorder patients who respond to lithium and those who do not respond to lithium. We have used these genes to construct an algorithm that can predict if a bipolar disorder patient would respond to lithium treatment.
Developing Methods for Improving Brain Organoids
The development of brain organoids of the past few years allows us to study brain disorders in these excellent models for the human brain. Brain organoids self-assemble and create brain-like structures that mimic the human brain. They are made standardly by embedding three-dimensional embryoid bodies in droplets of Matrigel that provide a scaffold for more complex tissue growth. However, as they grow in size, the diffusion of nutrients to their centers reduces and they suffer from necrotic cores. We are developing organoids in synthetic gels with lower strain modulus that allow for better diffusion and therefore there is reduced cell death in the cores of the organoids, and in addition the neurons in the organoids are much more active.
Improved brain organoids. a. A brightfield image of an organoid that was developed in a synthetic gel. b. A fluorescence image of neurons inside an organoid. c. Electrical activity of neurons inside a synthetic gel. The neurons fire repetitively and synchronically creating periodic network bursts. d. In Matrigel imbedded organoids the activity is more sparse and less synchronized.