Increased habenular connectivity in opioid users is associated with an α5 subunit nicotinic receptor genetic variant

Abstract

Background and Objectives Opioid use disorder (OUD) is a chronic disorder with relapse based on both desire for reinforcement (craving) and avoidance of withdrawal. The aversive aspect of dependence and relapse has been associated with a small brain structure called the habenula, which expresses large numbers of both opioid and nicotinic receptors. Additionally, opioid withdrawal symptoms can be induced in opioid-treated rodents by blocking not only opioid, but also nicotinic receptors. This receptor co-localization and cross-induction of withdrawal therefore might lead to genetic variation in the nicotinic receptor influencing development of human opioid dependence through its impact on the aversive components of opioid dependence. Methods We studied habenular resting state functional connectivity with related brain structures, specifically the striatum. We compared abstinent psychiatric patients who use opioids (N=51) to psychiatric patients who don’t (N=254) to identify an endophenotype of opioid use that focused on withdrawal avoidance and aversion rather than the more commonly examined craving aspects of relapse. Results We found that habenula – striatal connectivity was stronger in opioid-using patients. Increased habenula-striatum connectivity was observed in opioid-using patients with the low risk rs16969968 GG genotype, but not in patients carrying the high risk AG or AA genotypes. Conclusions We propose that increased habenula – striatum functional connectivity may be modulated by the nicotinic receptor variant rs16969968 and may lead to increased opioid use. Scientific Significance Our data uncovered a promising brain target for development of novel anti-addiction therapies and may help the development of personalized therapies against opioid abuse.

Classifying suicidal behavior with resting‐state functional connectivity and structural neuroimaging

“…Psychiatric inpatients ( N = 423) were recruited from the Menninger Clinic in Houston, Texas as a part of the McNair Initiative for Neuroscience Discovery—Menninger/Baylor (MIND‐MB) research study . Inpatients were eligible if mentally stable enough to participate, had no contraindications for magnetic resonance imaging (MRI), and gave signed, informed consent (procedures were approved by the Institutional Review Board).…”

“…The habenular circuit has been implicated in depression . We created the habenula left and right ROIs manually in SPM8 (one individually placed voxel per side) according to previous publications from our lab . The locus coeruleus, dorsal raphe, median raphe, substantia nigra, and ventral tegmental area (VTA) are all a part of habenular circuitry , and they have been implicated in depression and in some cases suicidal behavior specifically .…”

Insular resting state functional connectivity is associated with gut microbiota diversity

“…Anterior cingulate cortex and striatum were defined as in the Automated Anatomical Labeling (AAL) atlas (Tzourio-Mazoyer et al, 2002). The habenula was manually defined for each participant as two individual bilateral voxels using the T1 image as guide, as in (Curtis et al, 2017). Functional images were down-sampled to 3 9 3 9 3 to mitigate partial volume issues.…”

Altered habenula resting state functional connectivity in deprived veteran tobacco smokers: A pilot study

“…Furthermore, Peng et al (2018) found that structural connectivity of the lingual gyrus differentiated heavy smokers from light smokers and controls: Heavy smokers had significantly greater white matter atrophy of the lingual gyrus. Although no previous research has found aberrant habenula-lingual connectivity in smokers, habenula-lingual abnormalities in individuals with schizophrenia (Zhang et al, 2017) and high "negative connectivity" between the habenula and lingual gyrus in both healthy controls and psychiatric patients have been reported (Curtis et al, 2017;Ely et al, 2016).…”

“…As a part of the first-level analysis, we chose our seeds of interest, the right and left habenula. The seeds were manually created for each participant using the participant's structural T1 MRI as a guide (Curtis et al, 2017). Correlation maps were produced by extracting the BOLD time-course from the habenula seed, followed by generating Pearson's correlation coefficients between the seed time course and the time courses of all other voxels in the brain.…”