July 1: The study, a collaboration between scientists at the University of Chicago and Endeavor Health, measured gene expression and chromatin accessibility of active neurons to understand the impact of variants identified by genome-wide association studies that are associated with the risk for neuropsychiatric disorders.
The results, published in Science, uncovered several new links to disease that had been hidden previously by studies of only unstimulated neurons, including processes that increase cholesterol in patients with schizophrenia.
“This is one of the first studies to show that by systematically investigating variants with multiomic profiling of neuronal activation, you can unravel those hidden genetic effects that might have been missed by just studying post-mortem brains or cells in a resting state,” said the study’s leading senior author Jubao Duan, PhD, Charles R. Walgreen Research Chair and Director of Functional Genomics in Psychiatry at the Center for Psychiatric Genetics at Endeavor Health, and Professor of Psychiatry and Behavioral Neuroscience at UChicago.
Stimulating neurons to unmask functional noncoding variants
GWAS is a commonly used approach to identify genetic variants associated with common diseases like schizophrenia. For example, researchers might compare genome sequences of a large group of people with a specific disease with another set of sequences from healthy individuals. The differences identified in the disease group could point to genetic variants that affect disease risk and warrant further study.
Most human diseases are not caused by a single genetic variation, however, especially neuropsychiatric disorders. Instead, they are the result of a complex interaction of multiple genes, environmental factors, and a host of other variables. As a result, GWAS often identifies variants across many regions in the genome that are associated with a disease, mostly non-coding DNA sequences that do not contain instructions for building proteins.
These non-coding sequences make up most of the genome and often affect how nearby sections of coding DNA are expressed. These regulatory effects are a vital part of genetic machinery, but they aren’t apparent when studying cells and tissues in a resting, inactive state.
To understand regulatory effects of genetic variants in active neurons, the researchers in the new study used induced pluripotent stem cells , a type of stem cell that can be coaxed into developing into any type of cell. In this case, stem cells collected from healthy individuals and patients with schizophrenia were converted into neurons.
After stimulating the cells with potassium chloride to model neuron activation, they measured levels of RNA transcription and epigenetic changes in terms of genome accessibility , revealing widespread differences in the active cells. The team identified tens of thousands stimulation-specific genetic variants that regulate gene expression and chromatin openness.
Genetic connections to cholesterol metabolism
When the team combined this new information with GWAS data, they spotted many risk variants and genes whose effects could be detected only from active neurons, including ones involved in lipid and cholesterol synthesis and metabolism in patients with schizophrenia.
“The GWAS data can tell you a variant is interesting but doesn’t tell you why it’s interesting or under what circumstances. Now, with our data, we can make better sense of the GWAS findings,” said Xin He, PhD, Professor of Human Genetics at UChicago and co-senior author of the study.
The team identified two genes of interest, CPT1C and CROT, that are regulated by schizophrenia risk variants flagged by GWAS. Both are known metabolic genes; notably, CPT1C plays an important role in lipid metabolism in neurons to maintain active connections among synapses. Interestingly, when the cells were stimulated, the team found stronger activity of lipid and cholesterol synthesis genes in neurons derived from schizophrenia patients, compared with those from healthy controls.
Previous studies have found higher levels of cholesterol in brain tissue and blood samples from patients with schizophrenia. It’s not clear if this is an underlying cause, the result of disease progression, or the effects of antipsychotic medications, but the clear genetic links to these processes are intriguing.
“Our genetic data provided evidence that if you perturb these metabolic genes, you increase the risk of schizophrenia,” He said.
Combined with other parts of the study, “we now have multiple lines of evidence supporting the importance of lipid metabolism not only for schizophrenia, but also for autism and perhaps other neuropsychiatric disorders,” Duan added.
The researchers want to continue similar studies using other types of stimulation, to see how different types of cell activity influence genetic risk variants. “The GWAS provides an initial map, but there is still a lot of uncharted territory in that map. We’d like to explore that using different types of stimulation or by growing different types of neurons to discover their functions too,” Duan said.
The study, “Single-cell multiomics of neuron activation reveals context-specific genetics of brain disorders,” was supported by the National Institutes of Health. Additional authors include Lifan Liang, Siwei Zhang, Zicheng Wang, Hanwen Zhang, Chuxuan Li, Christina Thapa, Emily K. Oh, David Sirkin, Xiaotong Sun, Alexandra Barishman, Ada McCarroll, Alexandra C. Duhe, Sheng Qian, Xiaoyuan Zhong, Brendan Jamison, Whitney Wood, Alena Kozlova, Zhiping P. Pang, and Alan R. Sanders.
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