Printer Friendly

Associations between experimental substance use, FAAH-gene variations, impulsivity and sensation seeking.

Substance use disorders are common, complex disorders, characterized by compulsive substance seeking and use despite harmful consequences. The initiation of substance use takes place mainly during adolescence (Plan Nacional sobre Drogas, 2018). An early onset of substance use is associated with a significantly greater risk of later developing a substance use disorder (Chen, Storr, & Anthony, 2009).

Various risk factors for substance use initiation have been identified, including multiple contextual and individual variables (e.g. Blanco, Florez-Salamanca, Secades-Villa, Wang, & Hasin,

2018), and both prevention and treatment strategies must take into account all these factors (Becona, 2018). Among individual variables, personality traits like impulsivity and sensation seeking seem to be particularly relevant. Impulsivity is a multidimensional construct that can be broadly defined as a tendency toward rapid and unplanned reactions without regard to the consequences of these reactions (Stanford et al., 2009). Evidence indicates that impulsivity acts as a determinant factor for substance use initiation (e.g. Fernie et al., 2013; Mitchell & Potenza, 2014; R0mer-Thomsen et al., 2018; Verges, Littlefield, Arriaza, & Alvarado, 2019) and that, in turn, substance use increases subsequent impulsive behaviors (de Wit, 2009). Sensation seeking can be defined as the tendency of the individual to seek out varied, novel and intense experiences and the willingness to take risks for the sake of such experiences (Zuckerman, 1994). Several studies have linked sensation seeking with substance use disorders and have even indicated that it is one of its most powerful predictors (e.g. Ames, Zogg, & Stacy,

2002; Evans-Polce, Schuler, Schulenberg, & Patrick, 2018; Jaffe & Archer, 1987; Malmberg et al., 2012; Martinez-Loredo et al., 2018). Nevertheless, other studies suggest that abnormal sensation seeking values are more likely to be a consequence oi substance use than a preexisting vulnerability factor (Ersche, Turton, Pradhan, Bullmore, & Robbins, 2010).

Beyond personality and related to it, genetic characteristics play an important role in the development of substance use disorders. Data indicate that there are a number of genes, each with a small influence, that interact with each other and with environmental factors, affecting substance use and the likelihood of developing a substance use disorder (e.g. Gray & Squeglia, 2018; Meyers & Dick, 2010). The influence of genetic factors on substance use appears to increase considerably from early adolescence to young adulthood (Rose, Dick, Viken, & Kaprio, 2001). Among genetic variations related to substance use, single nucleotide polymorphisms (SNPs) in the endocannabinoid system may play a relevant role (see Buhler et al., 2015 for a review). The endocannabinoid system is implicated in a variety of cognitive and physiological processes including modulation of learning and memory, as well as brain reward signaling, influencing therefore vulnerability to substance use disorders (Parsons & Hurd, 2015). Among the different components of the endocannabinoid system, the fatty acid amide hydrolase enzyme (FAAH) has received special attention. This enzyme is responsible for the degradation of endocannabinoids and is encoded by its homonym gene FAAH which presents a missense SNP (rs324420/C385A) that reduces the expression and the activity of that enzyme, resulting in increased anandamide levels (Chiang, Gerber, Sipe, & Cravatt, 2004; Dincheva et al, 2015). Several studies have shown an association between FAAH C385A and different phenotypes related to substance use (e.g. Buhler et al., 2014; Sloan et al., 2018; Sipe, Chiang, Gerber, Beutler, & Cravatt, 2002), although the studies as a whole have shown heterogeneous results (Buhler et al., 2015).

The effects of FAAH C385A can depend on its interaction with other SNPs. In this line, Flanagan, Gerber, Cadet, Beutler, and Sipe (2006) revealed a haplotype which included FAAH C385A and its proxy variant rsl2075550 -D = 1, r = 0.1875 in Caucasian individuals- (Michiela & Chanock, 2015). Rsl2075550 is approximately 37 Kb from the C385A locus, in a non-coding region near the FAAH gene, which is likely to affect activator protein binding and expression of this gene (Boyle et al., 2012; Veyrieras et al., 2008). However, there is a deep lack of information about the influence of rsl2075550 on human phenotypes, including those related to substance use.

In addition to different consumption phenotypes, FAAH C385A has been previously associated with impulsivity (Hariri et al, 2009). However, Bidwell et al. (2013) did not find a significant interaction of impulsivity and FAAH-gene variations (including C385A but not rsl2075550) to predict marijuana-related problems. On the other hand, Helfand, Olsen, and Hillard (2017) found that FAAH knockout mice exhibited increased active responses in an operant sensation seeking task. Also, numerous studies have demonstrated a positive correlation between impulsivity and sensation seeking, suggesting a common biological mechanism underlying this association (Hur & Bouchard, 1997). It is reasonable, then, to ask whether impulsivity and sensation seeking operate as endophenotypes between FAAH C385A or rsl2075550 and experimental substance use, understanding as such the exploratory behavior during early stages of substance use (Schindler et al., 2005).

In summary, the objective of this study is to analyze the associations between three sets of variables: phenotypes of experimental substance use, genotypes in two variations involved in the activity of the endocannabinoid system (rsl2075550 and C385A SNPs), and two personality traits and potential endophenotypes (impulsivity and sensation seeking).



We recruited 929 undergraduate students from the Complutense University of Madrid. All of them participated voluntarily and a part received credits for their participation. To reduce the risk of population stratification, only the data of the 861 participants of self-reported European ancestry (76.00% female) were analyzed. Their age ranged from 18 to 40 (M = 20.66, SD = 3.28). They all filled a consumption questionnaire and donated a saliva sample. In addition, 591 of them (77.30% female, mean age = 20.09, SD = 2.78) completed the personality tests. The rest of participants (n = 270, 73.00 % female, mean age = 21.91, SD = 3.88) did not fill these tests, because their application was mistakenly omitted.


Three different self-report questionnaires were used. An ad hoc questionnaire on substance use asked the participant, among other things, whether or not he/she had ever tried alcohol, tobacco, cannabis, cocaine or synthetic drugs (ever tried), the age of first use of each of these substances (age of first use), and which of them he/she had consumed in the past 30 days (currently use).

To assess impulsivity, the Spanish version of the Barrat Impulsiveness Scale-11A, translated and adapted by Oquendo et al. (2001), was administered. The BIS-11 is a self-report questionnaire widely used (Stanford et al., 2009) that contains 30 items, measured on a four-point Likert-type scale. Since the Spanish version of Oquendo et al. (2001) was based on an initial version of BIS-11 [BIS-11A] (Barrat, 1994) and with the aim of making the data comparable to those of studies carried out with the much more used final version [BIS-11] (Patton, Stanford, & Barrat, 1995), only the 24 items common to the two versions have been taken into account (International Society for Research on Impulsivity, 2013). However, the total scores were transformed to the usual scale of 30 to 120 points of this final version by multiplying each of them by 1.25 In this study, Cronbach's alpha coefficient for the questionnaire was 0.75

To assess sensation-seeking, the Spanish version of the Sensation-Seeking Scale Form V (SSS-V) (Zuckerman, Eysenck, & Eysenck, 1978), translated and adapted by Perez and Torrubia (Perez & Torrubia, 1986), was used. The SSS contains 40 yes-no items. The items 10, 11, 14, 23 and 39 were not counted, because they directly ask about the consumption of substances, which would increase the association of sensation seeking with consumption, but the total scores were transformed to the usual scale of 0 to 40 points by multiplying each of them by 1.143. In this study, Cronbach's alpha coefficient for the questionnaire was 0.73. The correlation between SSS-V and BIS-11 total scores was r = .314 (p <001).


Participants first signed two informed consents, one for the collection and use of the data from the questionnaires, and another for the genetic study. They then completed the questionnaires and subsequently donated a saliva sample. The Research Ethics Committee of the Complutense University of Madrid (Faculty of Psychology) approved all procedures.

DNA from saliva was genotyped as previously described by Buhler et al. (2014) and Huertas, Buhler, Echeverry-Alzate, Gimenez, and Lopez-Moreno (2012). Briefly, DNA was collected using Oragene DNA Self-Collection kit (DNA Genotek, Ottawa, Ontario, Canada) and purified from 250-[micro]l aliquots using the ethanol precipitation protocol as described by the manufacturer. TaqMan genotyping was performed using pre-designed and validated TaqMan SNP genotyping assays (Assay ID: rs324420 and rsl275550) for humans from Applied Biosystems (Foster City, CA94404, USA). These genotyping assays were performed with a LightCycler 48011-machine (Roche Diagnostics, Barcelona, Spain) with endpoint genotyping method. Color fluorescence measures after amplification were analyzed with LightCycler 480 endpoint genotyping software version 1.5 (Roche Diagnostics, Barcelona, Spain).

Data analysis

Data regarding the current use of cocaine and synthetic drugs were excluded from the analysis because the number of participants who had consumed these substances in the last 30 days was small (10 and 12 respectively). Consequently, some n per group were too small when analyzing differences in personality or differences in genotypes between participants who have consumed the substances and those who did not. In the same way, the age at which these two substances were first used was also excluded because the number of participants who had ever tried them was small (51 and 59 respectively) and also because this number was very unbalanced between genotypes. This resulted in some n per cell too small when comparing ages in function of genotypes.

Consistent with previous studies (i.e. Buhler et al., 2014) and after a preliminary data inspection, analysis were performed under a dominant genetic model for the C allele of rsl2075550

(CC/CT vs. TT), and for the A allele of FAAH C385A (AA/AC vs. CC).

Statistical analysis was performed using the Statistical Package for the Social Sciences of International Business Machines (IBM SPSS Statistics 22 for Windows, SPSS Inc., Chicago, IL). To test the association between each of these SNPs with the ever tried and currently used variables, we used Pearson's chi-square ([chi square]) with exact significance and the odds ratio (OR, 95%IC), controlling the gender effect by means of the Mantel-Haenszel method. Survival analysis, estimated by the Kaplan-Meier method, was used to assess the association of each SNP with age of first use, and the curves of the genotypes were compared using the Breslow (Generalized Wilcoxon) test.

To assess the association between ever tried I currently used of each substance, as well as each SNP, with the BIS-11 / SSS-V total scores, univariate ANOVAs were used, adding gender as an additional factor (see e.g. Baker & Yardley, 2002). The Pearson's correlation test (r) was applied to measure the strength of the associations between age of first use and the BIS-11 / SSS-V total scores.

We applied the Benjamini-Hochberg correction for multiple tests (Benjamini & Hochberg, 1995), with a false discovery rate of .05


Genetic data

Genotype distribution data of both SNPs are shown in Table 1.

The genotype distributions of both SNPs did not deviate from Hardy-Weinberg equilibrium (FAAH C385A [chi square] = 0.32, p = 0.57, rsl2075550 [chi square] = 1.96, p = 0.16) neither were there significant differences between genotypes in the gender distribution (C385A [chi square] = 2.96, p = 0.23, rsl2075550 [chi square] = 0.12, p = 0.94). Allele frequency distributions of C385A and rsl2075550 were consistent with the NIH LDlink data for European population, where the minor allele frequencies were A (21%) and C (41,3%) respectively (Michiela & Chanock, 2015). In the same way, the distribution of C385A-rsl2075550 haplotype frequency, also shown in Table 1, was consistent with NIH LDlink data for European population.

The p-values of associations between consumption, genotypes and personality traits are summarized in Table 2.

Association consumption - impulsivity I sensation seeking

- BIS-11 questionnaire. BIS-11 total scores were higher in participants who have ever tried tobacco (dif= 4.20, F(\, 585) = 16.516, p < .001, partial if = .027), cannabis (dif = 3.79, F(1, 585) = 10.302, p = .001, partial if = .017) or cocaine (dif = 5.10, F(1, 585) = 5.521, p = .019, partial rf = .009). BIS-11 total scores were also higher in participants with a current use of alcohol (dif= 4.81, F(1, 585) = 14.657, p < .001, partial if = .024), tobacco (dif= 4.48, F(1,585) = 15.323, p < .001, partial if = .026) or cannabis (dif= 4.66, F(1, 585) = 18.087,/? < .001, partial if = .030). In addition, a negative correlation was found between the BIS-11 total scores and age of first use of alcohol (r = -.135, p = .002) or cannabis (r = -.158, p = .002).

- SSS-V questionnaire. As expected, SSS-V total scores were higher in participants who have ever tried alcohol (dif = 5.37, F(1, 587) = 16.365, p < .001, partial if = .027), tobacco (dif= 2.04, F(1, 587) = 12.777, p < .001, partial if = .021), cannabis (dif= 2.96, F(1, 587) = 26.778, p < .001, partial if = .044) or synthetic drugs (dif = 3.93, F(1, 587) = 13.299, p < .001, partial rf = .022). SSS-V total scores were also higher in those participants who currently use alcohol (dif= 2.67, F(1, 587) = 16.165, p < .001, partial if = .027), tobacco (dif= 1.78, F(1, 587) = 12.107, p = .001, partial if = .020) or cannabis (dif= 3.24, F(1, 586) = 31.162, p < .001, partial if = .050). We also found a negative correlation between SSS-V total scores and age of first use of alcohol (r = -.208, p <001) or cannabis (r = -.178, p <001).

Association genotypes - consumption

- SNP rsl2075550. The percentage of participants who had tried each of the substances was lower among T-homozygotes than among C-allele carriers, but this difference reached statistical significance only in the case of cannabis (50.18 % vs 57 64 %, [chi square] = 4 294, p = . 023, odds ratio = 1. 359, p = . 036, 95% CI [1.020-1.811]) and synthetic drugs (4.56 % vs 8.85 %, [chi square] = 5.106, p = .015, odds ratio = 2.046, p = .025, 95% CI [1.094-3.829]), after applying the Benjamini-Hochberg correction for multiple tests. The T homozygotes were also significantly older when they first used cannabis (16.6 years vs 16.2 years, Breslow [chi square] = 5.667, p = .017) and were less likely to be current tobacco users (26.32 % vs 34.90 %, [chi square] = 6.444, p = .011, odds ratio = 1.501, p = .011, 95% CI [1.096-2.055]).

- SNP FAAH C385A. No consumption phenotype was significantly associated with this SNP after applying the Benjamini-Hochberg correction for multiple tests.

Association genotypes - impulsivity/sensation seeking

No significant differences were found between genotypes of FAAH C385A or rsl2075550 in impulsivity or sensation-seeking


In this study, we found for the first time an association of experimental substance use with the rsl2075550 SNP, but we could not find that same association with the C385A SNP We also found an association of experimental substance use with impulsivity and sensation seeking. However, we failed to found an association between any of these genetic variations and any of those personality traits.

The rsl2075550 is a genetic variation practically unknown in terms of its biochemical background or its phenotypic effects. To our knowledge, only three studies have included it. In one of them, Flanagan et al. (2006) found that the A allele of FAAH C385A was associated with the T allele of rsl2075550 in up to 92.6% of Caucasian individuals and in 75.2% of African-American subjects using multiple substances. They proposed a haplotype that contains both SNPs. Given this finding, it could be thought that in our case the association of rsl2075550 with experimental substance use might simply be a result of its association with C385A, since this SNP has been related to different phenotypes of substance use (e.g. Buhler et al., 2014; Sipe et al., 2002). However, in the present study the A allele of FAAH C385A was associated with the T allele of rsl2075550 in 100% of cases, as correspond to the sample of participants from European ancestry, but also the C allele of C385A was associated with the T allele of rsl2075550 in 46% of cases. This is consistent with the LD haplotype calculation for the Iberian population in Spain (Machiela & Chanock, 2015). These results, together with the lack of association between FAAH C385A and the consumption variables analyzed in this study, seem to indicate that the association between rsl2075550 and experimental substance use would not be a consequence of its linkage disequilibrium with FAAH C385A.

In a second study involving rsl2075550, Buhler et al. (2014) failed to found an association between this SNP and intensity of alcohol, tobacco or cannabis consumption. However, the results of the present study indicate that it may be associated with having ever tried some substances, with the age at which they were first used and with having used them in the last 30 days. That is, the TT genotype of this SNP could confer a protective effect against experimental substance use. Since this type of use and risk consumption are partially independent (e.g. Swendsen et al., 2012), this SNP may be related to the first type of use, but not necessary to the second.

To our knowledge, only one study has so far explored the biochemical implications of rsl2075550, demonstrating that it is likely to affect protein binding and FAAH gene expression, as demonstrated in lymphoblastoid cell lines (Veyrieras et al., 2008). However, any functional explanation of the association we have found between this SNP and phenotypes related to experimental substance use would be scarcely justified at the current level of knowledge.

With respect to FAAH C385A, its behavioral consequences in human substance use are still under research (Buhler et al., 2015). The results obtained in this work have not shown a statistically significant association between FAAH C385A and the phenotypes under study, so the effect of this SNP could be more directly related to substance use disorders, which is what has usually been explored, than to experimental substance use.

Extensive empirical evidence indicates that impulsivity and sensation seeking are personality traits associated with substance consumption, particularly in earlier stages of substance use (e.g. Meil et al., 2016; Michell & Potenza, 2014; Moreno et al., 2012). Some studies indicate that substance use increases impulsivity and sensation seeking (e. g. de Wit, 2009; Ersche et al., 2010). However, other studies with both humans (e.g. Farley & Kim-Spoom, 2015; Fernandez-Atarmendi, Martinez-Loredo, Grande-Gosende, Simpson, & Fernandez-Hermida, 2018) and animals (e.g. Belin, Mar, Dalley, Robbins, & Everitt, 2008; Diergaarde et al., 2008) also indicate that impulsivity and sensation seeking increase substance use. Since impulsivity and sensation seeking have been related to the endocannabinoid system (e.g. Helfandet al., 2017; Moreira, Jupp, Belin, & Dalley, 2015; Ucha et al., 2019) they were suitable candidates as endophenotypes between the FAAH gene variations and the phenotypes of experimental substance use analyzed in this study. To our knowledge, there are no previously published data on the association between rsl275550 and impulsivity or sensation seeking, but with respect to the association of C385A with impulsivity, previous studies have obtained contradictory results (Bidwell et al., 2013; Hariri et al., 2009). In the present study we failed to found a significant association between either of the two SNPs and neither of the two personality variables, although our data show an association between these personality variables and experimental substance use on the one hand, and between rsl275550 and some phenotypes of that experimental use on the other. Therefore, it does not seem that impulsivity or sensation seeking, closely related to each other according to our and previous results, operate as endophenotypes between any of the two SNPs and the phenotypes of substance use that we have analyzed.

One limitation of the present study is its exploratory nature. For this reason, three variables related to the experimental use of each of five substances, two personality traits and two SNPs related to the FAAH gene were included. And for this same reason the Benjamini-Hochberg correction for multiple tests was applied. Another limitation is that participants constitute a convenience sample, composed of university students of European ancestry, mostly female. Therefore, the data are not directly generalizable to other populations. Particularly important is that participants were not recruited on the basis of their substance use. Consequently, any generalization to this type of patients should be done with caution. A last limitation is related to the fact that the impulsivity and sensation seeking questionnaires were applied to only 591 of the 861 participants, as indicated in the Participants section, so the conclusions regarding these variables should be interpreted according to that smaller number. The results obtained here will therefore have to be replicated through further studies before drawing definitive conclusions.

In conclusion, we provide first evidence for an association between SNP rsl2075550 and phenotypes of experimental substance use. On the other hand, consistently with previous evidence, we found that impulsivity and sensation seeking are associated with these same phenotypes in our sample of young people of European ancestry, although our data do not permit to establish causal relationships. Nevertheless we failed to found a significant association of rsl2075550 or FAAH C385A SNPs with one or another personality trait. In any case, these results show the importance that genetic and personality differences have in the experimental substance use and in the probability of developing a substance use disorder as a consequence of that use. They also highlight the importance of taking into account these individual differences, together with contextual factors, when designing prevention policies.


This work was supported by Fondo de Investigacion Sanitaria - Red de Trastornos Adictivos - FEDER (RD16/0017/0008), Ministerio de Economia y Competitividad (PEJ-2014-A-17012-C) and Ministerio de Sanidad, Consumo y Bienestar Social - Plan Nacional sobre Drogas (2018-050).


Ames, S., Zogg, J.B., & Stacy, A.W (2002). Implicit cognition, sensation seeking, marijuana use and driving behavior among drug offenders. Personality and Individual Differences, 33, 1055-1072. doi:10.1016/S0191-8869(01)00212-4

Baker, J. R., & Yardley, J. K. (2002). Moderating effect of gender on the relationship between sensation seeking-impulsivity and substance use in adolescents. Journal of Child & Adolescent Substance Abuse, 12, 27-43. doi:10.1300/J029vl2n01_02

Barratt, E. S. (1994). Impulsivity: Integrating cognitive, behavioral. biological and environmental data. In W. B. McCown, J. L. Johnson. & M. B. Shure (Eds.), The Impulsive Client: Theory, Research and Treatment (pp. 39-56). Washington, DC: American Psychological Association.

Becofla, E. (2018). Brain disease or biopsychosocial model in addiction? Remembering the Vietnam Veteran Study. Psicothema, 30, 270-275. doi:107334/psicothema2017303

Benjamini, Y., & Hochberg, Y. (1995). Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society. Series B (Methodological), 57, 289-300. Doi:10.1111/j.2517-6161.1995.tb02Q31.x

Belin, D., Mar, A. C, Dalley, J. W., Robbins, T. W., & Everitt B. J. (2008). High impulsivity predicts the switch to compulsive cocaine-taking. Science, 320, 1352-1355. doi:10.1126/science.H58136

Bidwell, L. C, Metrik, J., McGeary, J., Palmer, R. H., Francazio, S., & Knopik, V. S. (2013). Impulsivity, variation in the cannabinoid receptor (CNR1) and fatty acid amide hydrolase (FAAH) genes, and marijuana-related problems. Journal of Studies on Alcohol and Drugs, 74, 867-878. doi:10.15288/jsad.2013.74.867

Blanco, C, Florez-Salamanca, L., Secades-Villa, R., Wang, S., & Hasin, D. (2018). Predictors of initiation of nicotine, alcohol, cannabis, and cocaine use: Results of the national epidemiologic survey on alcohol and related conditions (NESARC). The American Journal on Addictions, 27, 477-484. doi:10.1111/ajad.l2764

Boyle, A. P., Hong, E. L., Hariharan, M., Cheng, Y., Schaub, M. A., Kasowski, M., ... Snyder, M. (2012). Annotation of functional variation in personal genomes using RegulomeDB. Genome Research, 22, 1790-1797 doi:10.1101/gr.l37323.112

Buhler, K. M., Gine, E., Echeverry-Alzate, V., Calleja-Conde, J., de Fonseca, F R., & Lopez Moreno, J. A. (2015). Common single nucleotide variants underlying drug addiction: More than a decade of research. Addiction Biology, 20, 845-871. doi:10.1111/adb.l2204

Buhler, K. M., Huertas, E., Echeverry-Alzate, V., Gine, E., Molto, E., Montoliu, L., & Lopez-Moreno, J. (2014). Risky alcohol consumption in young people is associated with the fatty acid amide hydrolase gene polymorphism C385A and affective rating of drug pictures. Molecular Genetics and Genomics, 289, 279-289 doi:10.1007/s00438-013-0809-x

Chen, C. Y., Storr, C. L., & Anthony, J. C. (2009). Early-onset drug use and risk for drug dependence problems. Addictive Behaviors, 34, 319-322. doi:10.1016/j.addbeh.2008.10.021

Chiang, K. P., Gerber, A. L., Sipe, J. C, & Cravatt, B. F (2004). Reduced cellular expression and activity of the P129T mutant of human fatty acid amide hydrolase: Evidence for a link between defects in the endocannabinoid system and problem drug use. Human Molecular Genetics, 13, 2113-2119 doi:10.1093/hmg/ddh216

Diergaarde, L., Pattij, T., Poortvliet, I., Hogenboom, F, de Vries, W.. Schoffelmeer, A. N., & De Vries, T. J. (2008). Impulsive choice and impulsive action predict vulnerability to distinct stages of nicotine seeking in rats. Biological Psychiatry, 63, 301-308. doi:10.1016/j.biopsych.200707.011

Dincheva, I., Drysdale, A. T., Hartley, C. A., Johnson, D. C, Jing, D., King, E. C, ... Lee, F S. (2015). FAAH genetic variation enhances fronto-amygdala function in mouse and human. Nature Communications, 6, 1-9 doi:10.1038/ncomms7395

de Wit, H. (2009). Impulsivity as a determinant and consequence of drug use: A review of underlying processes. Addiction Biology, 14, 22-31. doi:10.1111/j. 1369-1600.2008.00129.x

Ersche, K. D., Turton, A. J, Pradhan, S., Bullmore, E. T., & Robbins, T. W. (2010). Drug addiction endophenotypes: Impulsive versus sensation-seeking personality traits. Biological Psychiatry, 68, 110-113. doi:10.1016/j.biopsych.2010.06.015

Evans-Polce, R. J, Schuler, M. S., Schulenberg, J. E., & Patrick, M. A. (2018). Gender- and age-varying associations of sensation seeking and substance use across young adulthood. Addictive Behaviors, 84, 271-277 doi:10.1016/j.addbeh.2018.05.003

Farley, J. P., & Kim-Spoon, J. (2015). Longitudinal associations among impulsivity, friend substance use, and adolescent substance use. Journal of Addict Research andTherapy ,6, 220-226. doi: 10.4172/2155-6105.1000220

Fernandez-Atarmendi, S., Martinez-Loredo, V., Grande-Gosende, A., Simpson, I. C, & Fernandez-Hermida, J. R. (2018). What predicts what? Self-reported and behavioral impulsivity and high-risk patterns of alcohol use in Spanish early adolescents: A 2-year longitudinal study. Alcoholism: Clinical and Experimental Research, 42, 2022-2032. doi:10.1111/acer.l3852

Fernie, G., Peeters, M., Gullo, M. J, Christiansen, P., Cole, J. C, Sumnall, H, & Field, M. (2013). Multiple behavioral impulsivity tasks predict prospective alcohol involvement in adolescents. Addiction, 108, 1916-1923. doi:10.1111/add.l2283

Flanagan, J. M., Gerber, A. L., Cadet, J. L., Beutler, E., & Sipe, J. C. (2006). The fatty acid amide hydrolase 385 AA (P129T) variant: Haplotype analysis of an ancient missense mutation and validation of risk for drug addiction. Human Genetics, 120, 581-588. doi: 10.1007/s00439-006-0250-x

Gray, K. M., & Squeglia, L. M. (2018). Research Review: What have we learned about adolescent substance use? Journal of Child Psychology and Psychiatry, 59, 618-627 doi: 10.1111/jcpp. 12783

Hariri, A. R., Gorka, A., Hyde, L. W., Kimak, M., Haider, I., Ducci, F,...Manuck, S. B. (2009). Divergent effects of genetic variation in endocannabinoid signaling on human threat- and reward-related brain function. Biological Psychiatry, 66, 9-16. doi: 10.1016/j.biopsych. 2008.10.047

Helfand, A. I., Olsen, C. M., & Hillard, C. J. (2017). Cannabinoid receptor 1 and fatty acid amide hydrolase contribute to operant sensation seeking in mice. International Journal of Molecular Sciences, 18(8), 1-13. doi:10.3390/ijmsl8081635

Huertas, E., Buhler, K M., Echeverry-Alzate, V., Gimenez, T., & Lopez-Moreno, J. A. (2012). C957T polymorphism of the dopamine D2 receptor gene is associated with motor learning and heart rate. Genes, Brain and Behavior, 11, 677-683. doi:10.1111/j.l601-183X.2012.00793.x

Hur, Y. M., & Bouchard, T. J. Jr. (1997). The genetic correlation between impulsivity and sensation seeking traits. Behavior Genetics, 27, 455-463. doi: 10.1023/A: 1025674417078

International Society for Research on Impulsivity (2013). BIS 11: BIS-lla Issue. Retrieved from

Jaffe, L. T, & Archer, R. P. (1987). The prediction of drug use among college students from MMPI, MCMI, and sensation seeking scales. Journal of Personality Assessment, 51, 243-253. doi: 10.1207/sl5327752jpa5102_8

Machiela, M. J., & Chanock, S. J. (2015). LDlink: A web-based application for exploring population-specific haplotype structure and linking correlated alleles of possible functional variants. Bioinformatics, 31, 3555-3557 doi: 10.1093/bioinformatics/btv402

Malmberg, M., Kleinjana, M., Overbeek, G., Vermulst, A. A., Lammers, J., & Engels, R. (2013). Are there reciprocal relationships between substance use risk personality profiles and alcohol or tobacco use in early adolescence? Addictive Behaviors, 38, 2851-2859. doi: 10.1016/j.addbeh.2013.08.003

Martinez-Loredo, V., Fernandez-Hermida, J. R., De la Torre-Luque, A., & Fernandez-Artamendi, S. (2018). Polydrug use trajectories and differences in impulsivity among adolescents. International Journal of Clinical and Health Psychology, 18, 235-244. doi: 10.1016/j.ijchp.2018.07003

Meil, W. M., LaPorte, D J, Mills, J. A., Sesti, A., Collins, S. M., & Stiver, A. G. (2016). Sensation seeking and executive deficits in relation to alcohol, tobacco, and marijuana use frequency among university students: Value of ecologically based measures. Addictive Behaviors, 62, 135-144 doi:10.1016/j.addbeh.2016.06.014

Meyers, J. L., & Dick, D. M. (2010). Genetic and environmental risk factors for adolescent-onset substance use disorders. Child and Adolescent Psychiatric Clinics of North America, 19, 465-477 doi: 10.1016/j.chc.2010.03.013

Mitchell, M. R., & Potenza, M. N. (2014). Addictions and personality traits: Impulsivity and related constructs. Current Behavioral Neuroscience Reports, 1, 1-12. doi:10.1007/s40473-013-0001-y

Moreira, F A., Jupp, B., Belin, D., & Dalley, J. W. (2015). Endocannabinoids and striatal function: Implications for addiction-related behaviours. Behavioral Pharmacology, 26, 59-72. doi: 10.1097/FBR0000000000000109

Moreno, M., Estevez, A. F, Zaldivar, F, Montes, J. M., Gutierrez-Ferre, V. E., Esteban, L., ... Flores, P. (2012). Impulsivity differences in recreational cannabis users and binge drinkers in a university population. Drug and Alcohol Dependence, 124,355-362. doi: 10.1016/j. drugalcdep.2012.02.011

Oquendo, M. A., Baca-Garcia, E., Graver, R., Morales, M., Montalvan, V., & Mann, J. (2001). Spanish adaptation of the Barrat Impulsiveness scale (BIS-11). European Journal of Psychiatry, 15, 147-155. doi: 10.1016/j.ijchp.2015.07002

Parsons, L. H, & Hurd, Y. L. (2015). Endocannabinoid signaling in reward and addiction. Nature Reviews Neuroscience, 16, 579-594. doi:10.1038/nrn4004

Perez, X, & Torrubia, R. (1986). Habilidad y validez de la version espanola de la Escala de Busqueda de Sensaciones (Forma V) [Reliability and validity of the Spanish version of the Sensation-Seeking Scale (Form V)]. Revista Latinoamericana de Psicologia, 18(1), 7-22.

Patton, J. H., Stanford, M. S., & Barratt, E. S. (1995). Factor structure of the Barratt impulsiveness scale. Journal of Clinical Psychology, 51, 768-774. doi:10.1002/1097-4679(199511)51:63.0.CO;2-1

Plan Nacional sobre Drogas (2018). Encuesta estatal sobre uso de drogas en estudiantes de ensenanzas secundarias (ESTUDES) 2016-2017 [National survey on the use of drugs in secondary school students]. Madrid: Ministerio de Salud PSel. Retrieved from

Rose, R. J., Dick, D. M., Viken, R. I, & Kaprio, J. (2001). Gene-environment interaction in patterns of adolescent drinking: Regional residency moderates longitudinal influences on alcohol use. Alcoholism Clinical and Experimental Research, 25, 637-643. doi:10.1111/j.1530-0277.2001.tb02261.x

R0mer-Thomsen, K., Caliesen, M. B., Hesse, M., Kvamme, T. L., Pedersen, M. M., Pedersen, M. U., & Voon, V. (2018). Impulsivity traits and addiction-related behaviors in youth. Journal of Behavioral Addictions, 7, 317-330. doi: 10.1556/2006.72018.22

Schindler, A., Thomasius, R., Sack, P. M., Gemeinhardt, B., KUstner, U., & Eckert, J. (2005). Attachment and substance use disorders: A review of the literature and a study in drug dependent adolescents. Attachment & Human Development, 7, 207-228. doi: 10.1080/14616730500173918

Stanford, M. S., Mathias, C. W., Dougherty, D. M., Lake, S. L., Anderson, N. E., & Patton, J. H. (2009). Fifty years of the Barratt Impulsiveness Scale: An update and review. Personality and Individual Differences, 47, 385-395. doi:10.1016/j.paid.2009.04008

Sloan, M. E., Gowin, J. L., Yan, I, Schwandt, M. L., Spagnolo, P. A., Sun, H., ... Ramchandani, V. A. (2018). Severity of alcohol dependence is associated with the fatty acid amide hydrolase Prol29Thr missense variant. Addiction Biology, 23, 474-484. doi:10.1111/adb.l2491

Sipe, J. C, Chiang, K., Gerber, A. L., Beutler, E., & Cravatt, B. E (2002). A missense mutation in human fatty acid amide hydrolase associated with problem drug use. Proceedings of the National Academy of Sciences of the United States of America, 99, 8394-8399. doi: 10.1073/pnas.082235799

Swendsen, J., Burstein, M., Case, B., Conway, K. P., Dierker, L., He, J., & Merikangas, K. R (2012). Use and abuse of alcohol and illicit drugs in US adolescents: Results of the National Comorbidity Survey-Adolescent Supplement. Archives of General Psychiatry, 69, 390-398. doi: 10.1001/archgenpsychiatry 2011.1503

Ucha, M., Roura-Martinez, D., Contreras, A., Pinto-Rivero, S., Orihuel, J., Ambrosio, E., & Higuera-Matas, A. (2019). Impulsive action and impulsive choice are differentially associated with gene expression variations of the GABAA receptor alfa 1 subunit and the CB1 receptor in the lateral and medial orbitofrontal cortices. Frontiers in Behavioral Neuroscience, 13, 1-10. doi:10.3389/fnbeh.2019.00022

Verges, A., Littlefield, A. K., Arriaza, T., & Alvarado, M. (2019). Impulsivity facets and substance use initiation: Acomparison of two models of impulsivity. Addictive Behaviors, 88, 61-66. doi:10.1016/j.addbeh.2018.08.018

Veyrieras, J. B., Kudaravalli, S., Kim, S. Y., Dermitzakis, E. T., Gilad, Y., Stephens, M., & Pritchard, J. K. (2008). High-resolution mapping of expression-QTLs yields insight into human gene regulation. PLOS Genetics, 4(10), 1-15. doi:10.1371/journal.pgen.l000214

Wise, R. A., & Koob, G. F (2014). The development and maintenance of drug addiction. Neuropsychopharmacology, 39, 254-262. doi: 10.1038/npp. 2013.261

Zuckerman, M. (1994). Behavioral Expressions and Biosocial Bases of Sensation Seeking. New York: Cambridge University Press.

Zuckerman, M., Eysenck, S. B., & Eysenck, H. J. (1978). Sensation seeking in England and America: Cross-cultural, age, and sex comparisons. Journal of Consulting and Clinical Psychology, 46(1), 139-149. aoi.T0.1037//0022-006X.46.1.139

Evelio Huertas, Jose A. Lopez-Moreno, Vanessa Fernandez, Victor Echeverry-Alzate, and Kora-M Buhler

Complutense University of Madrid

Received: January 31, 2019 (*) Accepted: May 30, 2019

Corresponding author: Evelio Huertas

Facultad de Psicologia

Complutense University of Madrid

28223 Pozuelo de Alarcon


doi: 10.7334/psicothema2019.27
Table 1 FAAH C38SA and rsl207SSS0 SNPs genotype distribution

C38SA       Male  Female  Total  Male   Female  Total  Male   Female

                  AA                    AC                    CC
n             12     23     35      57    207     264    138    424
%           1,39   2,67   4,07    6,62  24,04   30,66  16.03  49,25
                     CC                    CT                    TT
n             43    130    173      95    308     403     69    216
%           4.99  15,10   20,1   11.03  35.77   46,81   8,01  25.09

C38SA       Total

n           562    861
%           65,27  100
n           285    861
%           33.10  100

Note: Minor allele frequency: 385A = .19; rsl2075550 C = .44.
Haplotype distribution (C385A - rsl2075550): A-C = 0 (0.0%); A-T = 334
(19.4%); C-C = 749 (43.5%); C-T = 639 (37.1%)

Table 2
P-value of significant associations between experimental substance use.
personality traits and SNPs, after Benjamini-Hochberg correction for
multiple tests

                   Questionnaires  SNPs
                   SSS-V   BIS-11  C385A   rsl2075550

Substance use
Ever tried:
alcohol            < .001       -  -       -
tobacco            < .001  < .001  -       -
cannabis           < .001    .001  -       .023
synthetic drugs    < .001          -       .015
cocaine                 -    .019  -       -
Age of first use:
alcohol             <.001   <.001  -       -
tobacco                 -       -  -       -
cannabis            <.001    .002  -       .017
Current use:
alcohol            < .001  < .001  -       -
tobacco              .001  < .001  -       Oil
cannabis           < .001  < .001  -       -
C385A                   :       :  < .001  < .001
SSS-V               <.001   <.001  -       -

Note: The results of the specific statistical analyses for each
association can be found in the Remits section. Current use indicates
whether or not the participant has consumed the substance in the last
30 days
COPYRIGHT 2019 Colegio Oficial De Psicologos Del Principado De Asturias
No portion of this article can be reproduced without the express written permission from the copyright holder.
Copyright 2019 Gale, Cengage Learning. All rights reserved.

Article Details
Printer friendly Cite/link Email Feedback
Author:Huertas, Evelio; Lopez-Moreno, Jose A.; Fernandez, Vanessa; Echeverry-Alzate, Victor; Buhler, Kora-M
Date:Jul 1, 2019
Previous Article:Cortical surface area variations within the dorsolateral prefrontal cortex are better predictors of future cognitive performance than fluid ability...
Next Article:Self-esteem and suicidal behaviour in youth: A meta-analysis of longitudinal studies.

Terms of use | Privacy policy | Copyright © 2020 Farlex, Inc. | Feedback | For webmasters