KIAA0319 Genotype Predicts the Number of Past Concussions in a Division I Football Team: A Pilot Study.

This candidate gene study evaluated the relationship of a past history of concussion with single nucleotide polymorphisms (SNPs) in nine genes in a small cohort (N = 87) of a nationally ranked Division I football team. Genes and SNPs studied were selected based on their published connection to brain injury and brain development, as well as impulsivity. We used multinomial logistic regression analysis (MLRA) to quantify how well genotype predicted the number of previously diagnosed concussions (three categories: none, one, two or more), while covarying race and number of years participating in football. The rs4504469 SNP for KIAA0319 was the only locus that significantly predicted number of previously diagnosed concussions (p = 0.005, meeting Bonferroni correction for multiple comparisons). The KIAA0319 results raise the hypothesis that having the CT or TT genotype of KIAA0319 may be predictive of a lower incidence of previously diagnosed concussion. This finding raises a number of hypotheses for future pre-clinical research, particularly whether alterations in neural organization related to KIAA0319 rs4504469 lead to reduced susceptibility for lasting head trauma, or greater resilience in the face of repeated subconcussive injury.

Recent Self-Reported Cannabis Use Is Associated With the Biometrics of Delta-9-Tetrahydrocannabinol.

OBJECTIVE: Research typically characterizes cannabis use by self-report of cannabis intake frequency. In an effort to better understand relationships between measures of cannabis use, we evaluated if Δ-9-tetrahydrocannabinol (THC) and metabolite concentrations (biometrics) were associated with a calibrated timeline followback (TLFB) assessment of cannabis use. METHOD: Participants were 35 young adult male cannabis users who completed a calibrated TLFB measure of cannabis use over the past 30 days, including time of last use. The calibration required participants handling four plastic bags of a cannabis substitute (0.25, 0.5, 1.0, and 3.5 grams) to quantify cannabis consumed. Participants provided blood and urine samples for analysis of THC and metabolites, at two independent laboratories. Participants abstained from cannabis use on the day of sample collection. We tested Pearson correlations between the calibrated TLFB measures and cannabis biometrics. RESULTS: Strong correlations were seen between urine and blood biometrics (all r > .73, all p < .001). TLFB measures of times of use and grams of cannabis consumed were significantly related to each biometric, including urine 11-nor-9-carboxy-Δ9-tetrahydrocannabinol (THCCOOH) and blood THC, 11-hydroxy-THC (11-OH-THC), THCCOOH, THCCOOH-glucuronide (times of use: r > .48-.61, all p < .05; grams: r > .40-.49, all p < .05). CONCLUSIONS: This study extends prior work to show TLFB methods significantly relate to an extended array of cannabis biometrics. The calibration of cannabis intake in grams was associated with each biometric, although the simple TLFB measure of times of use produced the strongest relationships with all five biometrics. These findings suggest that combined self-report and biometric data together convey the complexity of cannabis use, but allow that either the use of calibrated TLFB measures or biometrics may be sufficient for assessment of cannabis use in research.

Keypress-Based Musical Preference Is Both Individual and Lawful.

Musical preference is highly individualized and is an area of active study to develop methods for its quantification. Recently, preference-based behavior, associated with activity in brain reward circuitry, has been shown to follow lawful, quantifiable patterns, despite broad variation across individuals. These patterns, observed using a keypress paradigm with visual stimuli, form the basis for relative preference theory (RPT). Here, we sought to determine if such patterns extend to non-visual domains (i.e., audition) and dynamic stimuli, potentially providing a method to supplement psychometric, physiological, and neuroimaging approaches to preference quantification. For this study, we adapted our keypress paradigm to two sets of stimuli consisting of seventeenth to twenty-first century western art music (Classical) and twentieth to twenty-first century jazz and popular music (Popular). We studied a pilot sample and then a separate primary experimental sample with this paradigm, and used iterative mathematical modeling to determine if RPT relationships were observed with high R2 fits. We further assessed the extent of heterogeneity in the rank ordering of keypress-based responses across subjects. As expected, individual rank orderings of preferences were quite heterogeneous, yet we observed mathematical patterns fitting these data similar to those observed previously with visual stimuli. These patterns in music preference were recurrent across two cohorts and two stimulus sets, and scaled between individual and group data, adhering to the requirements for lawfulness. Our findings suggest a general neuroscience framework that predicts human approach/avoidance behavior, while also allowing for individual differences and the broad diversity of human choices; the resulting framework may offer novel approaches to advancing music neuroscience, or its applications to medicine and recommendation systems.