This experiment is part of the Mental Health Challenge Grant. Browse more projects

Cause and treatment of schizophrenia: ultimate goals of linking the disorder with the immune system

Raised of $5,000 Goal
Funded on 2/13/17
Successfully Funded
  • $10,134
  • 202%
  • Funded
    on 2/13/17



Cells in our bodies communicate with each other in part by using small molecules called microRNAs. Each microRNA is about two ten-millionths the size of one side of one chromosome, so they are indeed small. They are small but powerful in terms of one cell responding to or exerting control over another. Humans use combinations of about 2500 types of standard-format microRNAs as messages, and only about 15 of the 2500 are found exclusively in humans. By far the most abundant of the 15 in human brain is one called miR-941. When miR-941 was discovered in 2012, it was suggested as a key to human intelligence, maybe the capacity to use complex language.

Our lab has discovered (published Dec 2016) that miR-941 as synthesized by white blood cells (leukocytes) is a good predictor of persons presenting a clinician with mental distress who will or will not convert to a diagnosis of schizophrenia within two years. This is important because the clinician must decide whether to advise the patient to begin a course of anti-psychotics; anti-psychotics have serious side-effects. This decision is crucial to the quality of life of the patient.

It turns out that leukocytes also release particles called exosomes (about the size of virus particles). Exosomes are powerful sources of communication between cells because they carry payloads of microRNAs and other substances. In fact, if certain human exosomes are give to a mouse, the mouse can start producing human proteins. We hypothesize that leukocytes release exosomes into blood vessels, thence into blood vessel walls in the brain, with direct or indirect effects in the brain itself. miR-941-carrying exosomes are known to be in blood plasma from experiments by us and others. As an intermediate hypothesis to be tested by our Experiment project, we suggest that levels of exosomal miR-941 will again predict a future diagnosis of schizophrenia or not.  

The company Exiqon ( makes a new technology for isolating and measuring microRNAs in exosomes in blood plasma. To resolve our intermediate hypothesis, we must purchase and apply kits from Exiqon. Then we must evaluate the numbers generated by those assays to conclude or not that miR-941 levels reliably predict schizophrenia.

There is much more background to the story. Especially important are predicted control by miR-941 of several genes including a gene called HIVEP2. HIVEP2 from post mortem brain has been tied by other researchers to schizophrenia. As well, rare mutations in HIVEP2 are known to cause cognitive impairment in children.

But why focus on miR-941, since it might be only a step in a complex sequence of events that causes schizophrenia? Since miR-941 is a small molecule of RNA, its effects might be adjustable, up or down, in the central nervous system of patients. In fact, a new technology has been recently applied to modulate RNA levels to greatly ameliorate the disease spinal muscular atrophy. More generally, many pharmacologist around the world are striving to make levels of RNAs, and in particular  microRNAs, adjustable in patients. If the hypothesis of this experiment is correct, then we will provide pharmacologists with a target for the treatment of schizophrenia.


One challenge is mastery of the technology needed to accurately measure levels of miR-941. Of course the levels of any microRNA in blood plasma are minute, but Exiqon has a strong record of delivering reproducible assays. At every step we will include quality control tests such as confidential inclusion of replicates of one sample; the numbers from a replicated sample should be very similar. There are many other pitfalls associated with running experiments in any RNA lab. Our own experience and publications speak to success in controlling the risks.

Pre Analysis Plan

A strength of our recent papers is heavy use of permutation testing. This means using an algorithm to find a marker or markers to predict an outcome, then randomly mixing the case and control labels at least 1000 times and applying exactly the same algorithm. If and only if the true application provides superior classification of samples to most or all of the pseudo applications, do we presume that there actually is information in the experimental data. Additional tests further challenge the data and algorithm. Only when the tests are passed do we assert that anything has been discovered that is worthy of the ultimate test, namely, application to external data.