Machine learning models forecast DNA sequence variations

Subsequently, the researchers constructed machine learning models aimed at forecasting how specific DNA sequence variations can impact gene regulation and contribute to the development of diseases.

Although these recent findings provide significant insights into the human brain and its disorders, scientists are still in the process of comprehensively mapping the brain.

Dr. James Giordano, the Pellegrino Center professor of neurology and biochemistry at Georgetown University Medical Center, commented on the Science special issue, published on October 13, 2023, which covers research based on The BRAIN Initiative.

He said that “these studies, published in a series of papers in notable medical journals, present the first comprehensive map of molecular mechanisms inherent to specific cell types in discrete areas of the human brain.”

“Taken together, these studies, afford a ‘molecular atlas’ of nodes of cells that are genotypically correlated to the expression of certain structural and functional phenotypes that may be involved in a number of neuropsychiatric conditions.”

– Dr. James Giordano

Dr. Consuelo Walss-Bass, professor of psychiatry and behavioral sciences and director of the Psychiatric Genetics program at UTHealth Houston, noted that “research of [the] human brain has been historically difficult because of limited ability to obtain human brain samples.”

“However, recently, advances in genomic technologies, coupled with increased availability of postmortem brain tissue, have facilitated the generation of multi-level omics data, including epigenomics, transcriptomics, proteomics, in [the] human brain,” she added.

“This is a seminal example of the advances in technology, describing how it is now possible to identify, at the single cell level, DNA regions that are involved in regulating how genes are expressed (genes being ‘turned on or off’). Up till now, there was a lack of technology that allowed for this level of knowledge to be resolved at the individual cell level.”

– Dr. Consuelo Walss-Bass

Future is promising, but more research needed

However, Dr. Stefan Ivantu, consultant psychiatrist at ADHD Specialist, said that he felt researchers still had a long way to go until compiling a true “brain cell Atlas.”

“[I]n my opinion,” he told us, “analyzing 1 million cells is considered a small sample given the complexity of the human brain. Very few [people] are aware that the human brain has on average 86 billion cells that are interacting with each other constantly.”

“What makes it even more difficult are the interactions between the cells, which are far more complex,” he added. “However, with more powerful imagistic and AI tool, we may be able to understand the patterns related to specific conditions.”

In Dr. Ivantu’s view, “[a] more promising field is quantum computing, which this linked with the recent AI advances may be more effective in understanding the human brain.”

Nevertheless, he noted that “[i]t is extremely encouraging that researchers are using more technology for the next steps in understanding the human brain, and I believe this is the right approach.”

Dr. Walss-Bass pointed out that the researchers “have identified areas of the genome in individual brain cells that determine whether a gene will become expressed, that is, turned into RNA and then protein, to perform specific functions.”

“From this, the authors were then able to correlate genes that had been previously associated with schizophrenia and other psychiatric disorders to areas in the DNA where the expression of these genes is being regulated,” she explained.

“Understanding how gene expression is regulated in specific cell types in the brain is a significant advancement that will help to shed light shed light on the neurobiological mechanisms of psychiatric disorders and could lead to development of new therapies to treat these disorders.”

– Dr. Consuelo Walss-Bass

Significant implications for future patients

Dr. Sultan explained that this “research has significant implications for patients and the public.”

“It advances our understanding of the genetic foundations of neuropsychiatric disorders, potentially paving the way for more targeted treatments and precision medicine in neuropsychiatry,” Dr. Sultan explained.

Dr. Ivantu pointed out that, “in the short term, the implications for the patients and the public will be limited. It takes years until a test passes the research phase and gathers the evidence to be implemented in the clinical practice.”

“However,” he noted, “long term we may be able to understand the origin of certain neuropsychiatric disorders and possibly beyond!”

“If the technology becomes effective, this will not only play a role in treating the conditions but even more exciting prevention. Lastly, the most important is setting an example with this study and encouraging the researcher’s community to use AI and technology towards their projects,” Dr. Ivantu explained.

Dr. Ivantu agreed, concluding that “the future looks promising.”