Scientists have identified genetic markers of bipolar disorder

Bipolar disorder is a mental illness characterized by extreme mood swings, with alternating depressive and manic episodes. Past research suggests that bipolar disorder has a strong genetic component and is among the most heritable psychiatric illnesses.

To better understand the genetic factors that increase the risk of developing this mental disorder, neuroscientists and geneticists have conducted a number of genome-wide association studies (GWAS). These are essentially studies that aim to identify specific areas of the human genome that are associated with an increased risk of developing bipolar disorder — these areas are also called BD risk loci.

Although previous work has identified many such regions, the causal single nucleotide polymorphisms (SNPs) in the disorder remain largely unknown. These are the genetic variants that directly contribute to bipolar disorder, rather than simply being associated markers.

Researchers at the Icahn School of Medicine at Mount Sinai and other institutions recently conducted a new study to identify SNPs that directly contribute to the risk of developing the disease. Their findings, published in the journal Nature Neuroscience, were obtained by analyzing large genetic datasets using a variety of statistical techniques, including “fine-mapping” methods.

“This work is the result of a long-standing effort to better understand the genetic architecture of bipolar disorder,” Maria Koromina, the paper’s first author, told Medical Xpress. “Previous GWAS studies have identified 64 genomic regions associated with bipolar disorder, but the causal variants and genes within these regions have often remained unknown.”

The primary goal of this study was to identify potential causal SNPs that increase the risk of developing bipolar disorder, as well as the genes they are associated with. The researchers analyzed data collected by the Psychiatric Genome Consortium (PGC), a large international initiative founded in 2007 that collects genetic and medical data from thousands of people of European descent with mental illnesses, as well as healthy individuals.

“To examine genetic variants that contribute to the risk of bipolar disorder, we applied fine-mapping methods to GWAS data from approximately 41,917 bipolar cases and 371,549 controls of European descent,” Koromina explained.

“We then integrated these findings with brain-cell-specific epigenomic data and various quantitative trait loci (QTLs) to understand how genetic variants affect gene expression, splicing, or methylation. This combined approach allowed us to identify those genetic variants that are more likely to contribute to bipolar disorder risk and match them to candidate genes with higher confidence.”

Using fine mapping, Koromina and her colleagues were able to narrow down the genomic regions identified in previous studies, ultimately identifying 17 SNPs that were most likely to be associated with an increased risk of developing the disorder. They also linked these SNPs to specific genes that regulate brain development and signaling between neurons.

“We identified several likely causal variants and linked them to genes known to play a role in neurodevelopment and synaptic signaling, including SCN2A, TRANK1, CACNA1B, THSD7A, and FURIN,” Koromina said.

"Notably, three of these genes are also highly expressed in intestinal cells, supporting a genetic link between the microbiota-gut-brain axis and bipolar disorder. We also demonstrated that incorporating fine-mapping effects into polygenic risk scores (PRS) improves their predictive accuracy, particularly across ethnic groups."

The findings by Koromina and her colleagues further advance our understanding of bipolar disorder and its genetic basis. The scientists hope that their work will inspire further research aimed at studying the identified genetic variants. In the future, their work may also contribute to the development of therapeutic strategies that take into account the unique genetic profile of each patient.

“Future studies could focus on functional validation of priority genes and variants using models such as CRISPR-edited neuronal cells and brain organoids,” Koromina added. “These experiments will help determine how exactly these variants affect gene regulation and neuronal function. Ultimately, our goal is to transform these genetic data into tools for personalized therapy.”