The Interplay Between Risky Sexual Behaviors and Alcohol Dependence: Genome-Wide Association and Neuroimaging Support for LHPP as a Risk Gene

Abstract

To identify genetic mechanisms involved in the interplay of risky sexual behaviors (RSBs) and alcohol dependence (AD), we conducted genome-wide gene-by-AD (GW-GxAD) analyses of RSB in 3924 alcohol-exposed and sexually experienced subjects. RSBs were defined as a score based on lifetime experiences of unprotected sex and multiple sexual partners. Diagnosis of lifetime AD was defined by DSM-IV criteria. To follow-up the genetic findings, functional magnetic resonance imaging analyses were conducted in an independent sample. A trans-population genome-wide significant signal was identified in LHPP (rs34997829; z = − 5.573, p = 2.51 × 10 ) in the monetary incentive delay task. In conclusion, LHPP locus is associated to AD-RSB interaction; and with brain circuitries previously implicated in the inhibition of risky behavior and impulsiveness, emotional regulation, and impulse control/ error monitoring. Thus, LHPP is a strong candidate to influence RSB and STD risk in the context of AD.

S100A10 identified in a genome-wide gene × cannabis dependence interaction analysis of risky sexual behaviours

“…Although the shared genetic liability to addictive behaviours is surely correl ated to other behaviours, such as impulsivity and sensation-seeking, our current findings appear to be specific to CaD. Indeed, there is no overlapping between the current findings and the results of our previous genome-wide gene × alcohol dependence analysis of RSB, 16 and the present S100A10 result appears to be in line with our previous GWAS of CaD.…”

“…Recently, we conducted genome-wide investigations of RSB, identifying molecular mechanisms supporting the role of substance dependencies and other psychiatric disorders in moderating the genetic predisposition to RSB and its consequences. 16,17 In the present study, we conducted a genome-wide gene × cannabis dependence analysis of RSB in a cohort of cannabisexposed and sexually experienced African-American and European-American participants. Information regarding CaD and RSB was derived using the Semi-Structured Assessment for Drug Dependence and Alcoholism (SSADDA).…”

Ancestry‐specific and sex‐specific risk alleles identified in a genome‐wide gene‐by‐alcohol dependence interaction study of risky sexual behaviors

“…RSBs and AD were determined using items from the SSADDA. Detailed information regarding the phenotypic definitions are available in our previous report [Polimanti et al, 2017b]. Briefly, RSBs were defined as a score based on lifetime experiences of unprotected sex and multiple sexual partners using questions from the SSADDA section on antisocial personality: I35B (‘Have you ever had sex with 10 different people within a single year?’) and I37 (‘Have you more than once had unprotected sex (without a condom) with someone you believed could give you a disease, or when you had a disease that could be spread that way?’).…”

“…We included only subjects who reported having ever consumed more than 3 drinks in a 24-hour period (i.e., more than minimally alcohol exposed) and had ever had sexual intercourse with least 10 sexual partners (i.e., sexually experienced). The characteristics of the study population are reported in our previous trans-population GW-GxAD analysis of RSB [Polimanti et al, 2017b] (Supplemental Table 1). …”

“…A recent genome-wide association study of sexual behaviors reported a genetic correlation between reproductive and behavioral traits [Day et al, 2016] and a phenome-wide scan indicated that alcohol risk alleles are associated with reproductive health traits [Polimanti et al, 2016]. Our trans-population genome-wide gene-by-alcohol dependence (GW-GxAD) analysis of RSB identified LHPP as a risk locus, linking genetic risk and AD to RSB and sexually transmitted disease [Polimanti et al, 2017b]. To provide a deeper understanding of these findings, we investigated ancestry, sex, and ancestry-by-sex, because both ancestry and sex could contribute to specific risk mechanisms [Polimanti et al, 2015].…”