A genome-wide association study (GWAS) among almost 2.8 million individuals has revealed a causal link between irritable bowel syndrome (IBS) and elevated triglyceride levels.
IBS affects between 5% and 15% of the general population, is more common in women, and considerably reduces quality of life. It is known as a disorder of gut–brain interaction, but understanding of underlying disease mechanisms is limited, which has hindered the development of effective biomarkers and mechanism-based therapies.
“Our findings support a more integrated view of IBS that extends beyond the traditional gut–brain axis,” said lead author Mauro D’Amato, PhD, professor of medical genetics at LUM University in Bari, Italy, and Ikerbasque research professor at CIC bioGUNE in Bilbao, Spain. “The specific pathways we highlighted may contribute to mechanism-based patient stratifications and the identification of new or existing drugs to be tested in patients who do not respond to current therapies.”
D’Amato and colleagues used genetic, questionnaire, and electronic health records (EHR) data for 2,775,539 individuals from 22 international biobanks, to investigate the genetic architecture of IBS across three case definitions (self-reported, Rome III criteria, and International Classification of Diseases criteria), three subtypes (IBS-C, characterized by constipation; IBS-D, characterized by diarrhea; and IBS-Mixed, which combines both), and by ancestry.
They found that IBS is an heritable condition among people of European ancestry but not among those of other ancestries. However, the investigators that caution that the finding should not be interpreted as “evidence against a genetic contribution to IBS in these [non-European] populations,” rather that the data they had was not powerful enough to prove a link.
Further analyses revealed 35 regions of the human genome associated with IBS risk. While several of these regions involved the brain and enteric nervous system, the researchers also identified a strong, unexpected overlap with cardiometabolic traits.
Specifically, they demonstrated a likely causal link between genetic liability for IBS and elevated levels of blood triglycerides, which was not explained by BMI.
“This association of IBS with pro-atherogenic lipid profiles is consistent with large-scale observational studies that have repeatedly documented a strong link between IBS and metabolic syndrome, including cardiovascular traits and elevated triglycerides, but not BMI,” write D’Amato and co-authors in Gut.
The molecular basis for the connection was a single nucleotide polymorphism in the gene for glucokinase regulatory protein (GKRP), which is a regulator of triglyceride metabolism. The variant is also associated with metabolic dysfunction-associated fatty liver disease, supporting a shared metabolic background.
“We have long known that IBS involves a complex dialogue between the gut and the brain, but these results show that the conversation includes the body’s metabolic system too,” said D’Amato. “The genetic link to triglyceride regulation and liver function gives us a completely new framework for understanding the condition.”
The researchers also looked for potential drug targets. They identified 276 chemical agents with possible therapeutic relevance, of which 156 had a defined mechanism of action. These included many with known applications in the treatment of IBS and related symptoms, including off-label prescriptions (nortriptyline, sertraline, lorazepam, curcumin, and capsaicin) as well others that are typically used to treat cardiovascular conditions (urapidil, fenoldopam, indapamide, nicardipine, picotamide, torsemide), and triglyceride-modifying compounds (rosuvastatin, simvastatin).
The remaining 120 small molecules, without a known target or mechanism of act, could represent “potential novel opportunities for translational research in IBS,” D’Amato and co-authors suggest.
They conclude that their findings provide “the most comprehensive assessment to date of IBS genetic architecture, its subtypes, and the biological and translational inferences that can be drawn from common-variant association signals.”
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