Computational approach meets biology to connect neural progenitor cells with human disorders

(Press-News.org) For much of the 20th century it was thought that the adult brain was incapable of regeneration. This view has since shifted dramatically and neurogenesis – the birth of new neurons – is now a widely accepted phenomenon in the adult brain, offering promising avenues for treating many neurological conditions. One of the main challenges in the field has been identifying neural stem and progenitor cells (NPCs) responsible for generating these new neurons. NPCs are rare, diverse and difficult to isolate from other brain cells due to overlapping molecular signatures. As a result, understanding their biology – and particularly their role in human brain disorders – has remained elusive.

In a new study published in Stem Cell Reports, a team led by researchers at Baylor College of Medicine and the Jan and Dan Duncan Neurological Research Institute (Duncan NRI) at Texas Children’s Hospital reveals specific genes that define NPCs. Importantly, the team also identified NPC gene mutations potentially implicated in human brain function and neurological conditions, offering new insights into the molecular roots of neurodevelopmental disorders.

“The site of adult neurogenesis is the dentate gyrus in the hippocampus, the center for learning and memory. Compared to other brain regions, this small area of the brain holds a sparse population of NPCs and their progeny,” said co-corresponding author Dr. Mirjana Maletić-Savatić, professor of pediatrics – neurology at Baylor and investigator at the Duncan NRI. “New neurons are made in this area every day and they participate in learning and memory as well as mood control. Understanding neurogenesis is important because it could lead to improving conditions such as dementia, learning disabilities, depression and other related neurological and mental health conditions.”

It’s been challenging to identify NPCs because “these cells are so rare and look so much like their neighbors that it’s been difficult to pinpoint their unique genetic signature,” said co-first author Dr. William T. Choi, who was a graduate student in the Maletić-Savatić lab when he was working on this project and is an attending physician and a post-doctoral fellow at Harvard Medical School.

“We thought that the identification of NPC-specific markers could be successfully achieved by combining computational and experimental approaches,” said co-corresponding author Dr. Zhandong Liu, associate professor of pediatrics – neurology at Baylor and Duncan NRI investigator.

“We used a computational approach called Digital Sorting Algorithm (DSA) that has been developed to analyze heterogeneous data containing mixtures of cell types,” said co-first author Dr. Gerarda Cappuccio, postdoctoral associate in the Maletić-Savatić lab. “With DSA we sifted through complex genetic data to identify which genes are active in NPCs and find unique gene expression patterns, like genetic fingerprints, for these cells. Using this approach, we identified 129 genes that are highly active in NPCs in mice.”

“The critical part of our discovery came when we cross-referenced these genes with human data,” Choi said. “We found that 25 of these genes were already known to cause specific neurological diseases in humans when mutated. Even more exciting, we identified 15 new candidate genes that we anticipate are linked to previously unexplained neurological disorders in patients.”

“Our approach not only sheds light on the molecular architecture of NPCs but also provides a valuable resource for studying the links between neural stem cell biology and human disorders,” Cappuccio said.

The findings illustrate the power of simple computational frameworks to uncover meaningful, novel disease-relevant biology that could directly affect patients by offering new pathways to understanding and potentially treating neurological conditions.

Other contributors to this work include Fatih Semerci, Jill A. Rosenfeld, Toni Claire Tacorda, Guantong Qi, Anthony W. Zoghbi, Yi Zhong, Hu Chen and Pengfei Liu. The authors are affiliated with one or more of the following institutions: Baylor College of Medicine, Duncan NRI, Baylor Genetics laboratories and University of Houston.

This work was supported in part by grants from the National Institute of Aging (1R01AG076942), the Eunice Kennedy Shriver National Institute of Child Health and Human Development of the National Institutes of Health (P50HD103555) and the Genomic and RNA Profiling Core at Baylor College of Medicine. Additional support was provided by Autism Speaks, Cynthia and Antony Petrello Endowment, the NLM Training Program in Biomedical Informatics (T15LM007093), Developmental Biology Training Program (T32HD055200) and BCM Medical Scientist Training Program.

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