Unraveling the Contribution of Serotonergic Polymorphisms, Prefrontal Alpha Asymmetry, and Individual Alpha Peak Frequency to the Emotion-Related Impulsivity Endophenotype

The unique contribution of the serotonin transporter-linked polymorphic region (5-HTTLPR), intronic region 2 (STin2), and monoamine oxidase A (MAO-A) genes to individual differences in personality traits has been widely explored, and research has shown that certain forms of these polymorphisms relate to impulsivity and impulsivity-related disorders. Humans showing these traits are also described as having an asymmetrical prefrontal cortical activity when compared to others. In this explorative study, we examine the relationship between serotonergic neurotransmission polymorphisms, cortical activity features (prefrontal alpha asymmetry, individual alpha peak frequency [iAPF]), emotion-related and non-emotion-related impulsivity in humans. 5-HTTLPR, MAO-A, and STin2 polymorphisms were assessed in blood taken from 91 participants with high emotion-related impulsivity levels. Sixty-seven participants completed resting electroencephalography and a more comprehensive impulsivity index. In univariate analyses, iAPF correlated with both forms of emotion-related impulsivity. In multiple linear regression models, 5-HTTLPR polymorphism (model 1, adj. R² = 15.2%) and iAPF were significant interacting predictors of emotion-related impulsivity, explaining a large share of the results’ variance (model 2, adj. R² = 21.2%). Carriers of the low transcriptional activity 5-HTTPLR and MAO-A phenotypes obtained higher emotion-related impulsivity scores than others did. No significant results were detected for non-emotion-related impulsivity or for a form of emotion-related impulsivity involving cognitive/motivational reactivity to emotion. Our findings support an endophenotypic approach to impulsivity, showing that tri-allelic 5-HTTLPR polymorphism, iAPF, and their interaction are relevant predictors of one form of emotion-related impulsivity.

A multivariate model of time to conversion from mild cognitive impairment to Alzheimer's disease

The present study was aimed at determining which combination of demographic, genetic, cognitive, neurophysiological, and neuroanatomical factors may predict differences in time to progression from mild cognitive impairment (MCI) to Alzheimer's disease (AD). To this end, a sample of 121 MCIs was followed up during a 5-year period. According to their clinical outcome, MCIs were divided into two subgroups: (i) the "progressive" MCI group (n = 46; mean time to progression 17 ± 9.73 months) and (ii) the "stable" MCI group (n = 75; mean time of follow-up 31.37 ± 14.58 months). Kaplan-Meier survival analyses were applied to explore each variable's relationship with the progression to AD. Once potential predictors were detected, Cox regression analyses were utilized to calculate a parsimonious model to estimate differences in time to progression. The final model included three variables (in order of relevance): left parahippocampal volume (corrected by intracranial volume, LP_ ICV), delayed recall (DR), and left inferior occipital lobe individual alpha peak frequency (LIOL_IAPF). Those MCIs with LP_ICV volume, DR score, and LIOL_IAPF value lower than the defined cutoff had 6 times, 5.5 times, and 3 times higher risk of progression to AD, respectively. Besides, when the categories of the three variables were "unfavorable" (i.e., values below the cutoff), 100% of cases progressed to AD at the end of follow-up. Our results highlighted the relevance of neurophysiological markers as predictors of conversion (LIOL_IAPF) and the importance of multivariate models that combine markers of different nature to predict time to progression from MCI to dementia.

Frequency shift in topography of spontaneous brain rhythms from childhood to adulthood

It has been described that the frequency ranges at which theta, mu and alpha rhythms oscillate is increasing with age. The present report, by analyzing the spontaneous EEG, tries to demonstrate whether there is an increase with age in the frequency at which the cortical structures oscillate. A topographical approach was followed. The spontaneous EEG of one hundredand seventy subjects was recorded. The spectral power (from 0.5 to 45.5 Hz) was obtained by means of the Fast Fourier Transform. Correlations of spatial topographies among the different age groups showed that older groups presented the same topographical maps as younger groups, but oscillating at higher frequencies. The results suggest that the same brain areas oscillate at lower frequencies in children than in older groups, for a broad frequency range. This shift to a higher frequency with age would be a trend in spontaneous brain rhythm development.