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Kantojarvi, K.

Publications and source records attributed to Kantojarvi, K..

4 recordsLinked to original sources

BDNF Val66Met polymorphism as putative genetic substrate of music-induced plasticity in auditory prediction

Predictive processing of sounds depends on the constant updating of priors based on exposure to posteriors, which through repeated exposure mediates learning. The result of such corrections to the model is seen in musicians, whose lifelong training results in measurable plasticity of audio-motor brain anatomy and functionality. It has been suggested that the plasticity of auditory predictive processes depends on the interaction between the environment and the individuals genetic substrate. However, empirical evidence to this is still missing. BDNF is a critical genetic factor affecting learning and plasticity, and its widely studied functional variant Val66Met single-nucleotide polymorphism offers a unique opportunity to investigate neuroplastic functional changes occurring upon a years-long training. We hypothesised that BDNF gene variations would be driving neuroplasticity of the auditory cortex in musically trained human participants. To this goal, musicians and non-musicians were recruited and divided in Val/Val and Met carriers and their brain activity measured with magnetoencephalography (MEG) while they listened to a regular auditory sequence containing different types of prediction errors. The auditory cortex responses to prediction errors was enhanced in Val/Val carriers who underwent intensive musical training, compared to Met and non-musicians. Our results point at a role of gene-regulated neurotrophic factors in the neural adaptations of auditory processing after long-term training.

neuroscience↗

Association between COMT gene Val158Met heterozygote polymorphism and enhanced brain predicting processes

Predicting events in the ever-changing environment is a fundamental survival function intrinsic to the physiology of sensory systems, whose efficiency varies among the population. Even though it is established that a major source of such variations is genetic heritage, there are no studies tracking down auditory predicting processes to genetic mutations. Thus, we examined the neurophysiological responses to deviant stimuli recorded with magnetoencephalography (MEG) in 108 healthy participants carrying different variants of the Val158Met single-nucleotide polymorphism (SNP) within the catechol-O-methyltransferase (COMT) gene, which is responsible for the majority of catecholamines degradation in the prefrontal cortex. Our results showed significant amplitude enhancement of neural responses localized within inferior frontal gyrus, superior and middle temporal cortices to deviant auditory stimuli in heterozygote genotype carriers (Val/Met) vs homozygote (Val/Val and Met/Met) carriers. Integrating neurophysiology and genetics, this study provided new and broader insights into the brain mechanisms underlying optimal deviant detection.

neuroscience↗

Nightmares share strong genetic risk with sleep and psychiatric disorders

Nightmares are vivid, extended and extremely dysphoric dreams that awaken the dreamer. Twin studies indicate that nightmare frequency has a heritability between 36 and 51% providing evidence for genetic factors underlying predisposition to nightmares. Furthermore, while cross-sectional epidemiological findings suggest that heavy alcohol usage, traumatic experiences and psychiatric diseases associate with nightmares, the causal relationships between these conditions and nightmares have remained unknown. To examine the biological mechanisms behind nightmares, we performed a genome-wide association study in 28,596 individuals from Finland and the United States. We identified individual genetic variants that predispose to nightmares near MYOF (rs701873, p=2.18e-8) and PTPRJ (rs11039471,p=3.7e-8), a gene previously associated with sleep duration. We found a strong genetic correlation between the frequency of nightmares and traits related to personality and psychiatric disorders; neuroticism (rg=0.59, p=8e-7), post-traumatic stress disorder (PTSD) (rg=0.58, p=0.004) as well as major depressive disorder (rg=0.68, p=7e-4), and sleep traits; and daytime sleepiness (rg=0.62, p=1e-6) and insomnia (rg=0.50, p=1.87e-5). Analysis of directionality using mendelian randomization showed a significant effect from feelings of fed-up (p=0.001), nervous (p=0.004) and miserableness (p=0.0045) to nightmares with no evidence of pleiotropy and no evidence of nightmares predisposing to psychiatric or psychological problems. Our findings suggest that nightmares are caused by unique genetic risk factors, and here we identify the first individual genetic associations. In addition, a substantial effect on nightmares is conveyed through underlying psychological and sleep problems, with psychological problems being causal for nightmares.

genetics↗

Genome-wide association analysis of excessive daytime sleepiness identifies 42 loci that suggest phenotypic subgroups

Excessive daytime sleepiness (EDS) affects 10-20% of the population and is associated with substantial functional deficits. We identified 42 loci for self-reported EDS in GWAS of 452,071 individuals from the UK Biobank, with enrichment for genes expressed in brain tissues and in neuronal transmission pathways. We confirmed the aggregate effect of a genetic risk score of 42 SNPs on EDS in independent Scandinavian cohorts and on other sleep disorders (restless leg syndrome, insomnia) and sleep traits (duration, chronotype, accelerometer-derived sleep efficiency and daytime naps or inactivity). Strong genetic correlations were also seen with obesity, coronary heart disease, psychiatric diseases, cognitive traits and reproductive ageing. EDS variants clustered into two predominant composite phenotypes - sleep propensity and sleep fragmentation - with the former showing stronger evidence for enriched expression in central nervous system tissues, suggesting two unique mechanistic pathways. Mendelian randomization analysis indicated that higher BMI is causally associated with EDS risk, but EDS does not appear to causally influence BMI.

genomics↗