11 genetic loci that shape impulsive decision-making

By Dr. Liji Thomas, MDReviewed by Benedette Cuffari, M.Sc.Dec 3 2025

A genome-wide analysis shows how our genes influence snap decisions, and why those same genetic patterns are tied to addiction, mood disorders, obesity, and even brain wiring. 

Study: Genome-wide association study of delay discounting identifies 11 loci and reveals transdiagnostic associations across mental and physical health. Image Credit: Rost9 / Shutterstock.com

A recent study published in Molecular Psychiatry identifies distinct genetic loci associated with delay discounting (DD). It examines how these variants influence physical, behavioral, and neuroimaging traits related to both physical and psychiatric health outcomes.

What is DD?

DD refers to the tendency to choose immediate, smaller rewards over delayed but larger rewards. DD is a heritable trait associated with multiple disorders characterized by impaired impulsivity and decision-making, with higher DD observed in substance use disorders, gambling disorder, attention-deficit hyperactivity disorder (ADHD), and bipolar disorder. Comparatively, obsessive-compulsive disorder or anorexia nervosa are associated with lower DD.

The biological mechanisms involved in DD remain unclear, though it appears to be a potential marker of several clinical, physical, and mental health outcomes.

About the study

The researchers of the current study measured DD using the temporal discounting value. This curve is steeper when immediate gratification is preferred, as compared to a flatter curve when delayed rewards are selected. A previous genome-wide association study (GWAS) on DD provided genetic data for 134,935 participants of the 23andMe cohort, all of whom were of European descent.

After identifying both global and genetic correlations between DD and health outcomes, network analyses were used to identify the different molecular pathways involved in these processes. Multivariate analyses were then used to identify genetic factors that are unique to DD compared to those shared with other cognitive traits, such as educational attainment, intelligence, and executive fuinction.

Polygenic scores (PGS) for DD were developed to quantify the cumulative genetic predisposition for elevated DD. These scores were subsequently applied in a phenome-wide association study (PheWAS) among hospitalized patients.

Study findings

The GWAS analysis revealed eleven significant loci embracing 93 unique DD-associated genes, 20 % of which were located within the ch16p11.2 GWAS locus. Notably, this analysis did not replicate a previously reported association with the chromosomal locus rs6528024 (chrXq13.3).

Observed genetic variants were single-nucleotide polymorphisms (SNPs) that explained 9.9 % of the differences in DD between individuals. Most of the SNPs were present in loci previously associated with risk-taking behaviors, substance abuse, and psychiatric illnesses, as well as mood instability.

DD-associated loci negatively correlated with intelligence, educational status, and executive function. These loci were also negatively associated with household income, while showing positive genetic correlations with anthropometric traits such as body mass index (BMI).

DD correlated with 73 psychiatric, physical, and cognitive traits. However, only a subset of these correlations remained significant after accounting for shared genetic influences with cognitive traits, including education, intelligence, and executive function. These included SUDs, as well as psychiatric disorders like major depression, suicidal attempts, and panic disorder.

Negative genetic correlations were observed between DD and obsessive-compulsive disorder, anorexia nervosa, schizophrenia, bipolar disorder, and cognitive/sociodemographic factors like intelligence, educational attainment, household income, and parental lifespan. This finding is plausible, as academic achievement often requires delayed gratification, sustained effort, and prioritizing long-term goals.

DD polygenic scores positively correlated with irritable bowel syndrome, cardiovascular disease, pain-related traits, and limbic system connectivity. Compared to the control group, functional limbic connectivity was negatively correlated with DD.

Metabolic pathways shared between DD and BMI also overlapped with those associated with schizophrenia, externalizing behaviors, and educational attainment. Some biological processes were only shared between DD and one other trait, like educational status or BMI; however, none were uniquely shared between DD and addiction-related risk factors.

When polygenic scores were assigned to DD, 212 associated disorders were identified in a hospital cohort of nearly 67,000 patients, suggesting that DD is associated with multiple common genetic variants due to its polygenic nature. DD also appears to influence the occurrence of numerous traits, thereby exemplifying its pleiotropic nature.

Conclusions

The current GWAS used a five-fold larger sample than the previous work by the same authors. To this end, eleven genetic loci, including 93 genes, were found to be potentially associated with DD risk.

Rather than demonstrating direct causal effects, the study indicated that a higher genetic predisposition to DD reflects shared biological pathways that overlap with cognitive processing, psychiatric conditions such as addictions or depression, and metabolic health outcomes.

Further work is needed to extend PheWAS performance to a non-European cohort, as the PGS becomes less generally applicable with more distantly genetically related samples.

This work pinpoints neurobiological targets of DD and sets the foundation for future studies that may enable the discovery of better prevention, diagnosis, and treatment mechanisms for a host of conditions.