Biology subjects

Paunio, T.

Publications and source records attributed to Paunio, T..

8 recordsLinked to original sources

bioRxiv2025

Temporal Associations Between Human Milk Metabolites and the Infant Gut Microbiome and metabolome

IntroductionHuman milk is vital in establishing a healthy infant gut microbiome. Gut microbes and their metabolites are important for host development. However, our understanding of how milk metabolites are connected to the gut microbiome and metabolome in early-life remains limited. We aimed to investigate associations between the human milk metabolome and the gut microbiome in infancy. MethodsThe fecal and milk samples were collected at 2.5 (n=283), 6 (n=129) and 14 (n=65) months of age. Gut microbiota was analyzed with amplicon sequencing, the gut metabolome was analyzed with gas chromatography-mass spectrometry and liquid chromatography-mass spectrometry, and milk metabolites were analyzed with proton nuclear magnetic resonance. ResultsBifidobacterium and other butyrate producers were associated with ethanolamine and methionine level in the milk, in a time-dependent manner. Elevated milk fucosylated oligosaccharide, LNFP-I and caprylate concentrations were positively associated with secondary bile acid levels following the introduction of solid foods. Additionally, acidic oligosaccharides 3-SL and 6-SL were positively associated with long-chain carbohydrates prior to solid food introduction, however negatively associated thereafter. ConclusionOur results highlight that milk metabolites are associated with biologically relevant gut microbial metabolites. Only limited associations were observed between milk composition and the microbiome, which differed between early and late infancy. This suggests milk metabolome may differentially influence microbial metabolism depending on dietary diversity and/or the maturity of the microbiome. ImportanceIts essential to raise awareness about breastfeeding and its variety of health benefits. Expanding our understanding of how human milk small molecules with potential bioactivity interact with the gut microbiome can help highlight these positive effects. Exploratory studies of human milk composition with gut microbial metabolites may support achieving this goal. Furthermore, understanding of biological effects of different components in human milk is important, and it can help to develop strategies to ensure optimal growth and development of an infant regardless of the breastfeeding status of the child.

microbiology↗

bioRxiv2021

Genetic polymorphisms in COMT and BDNF influence synchronization dynamics of human neuronal oscillations

Neuronal oscillations, their inter-areal synchronization, and scale-free dynamics constitute fundamental mechanisms for cognition by regulating communication in neuronal networks. These oscillatory dynamics have large inter-individual variability that is partly heritable. However, the genetic underpinnings of oscillatory dynamics have remained poorly understood. We recorded resting-state magnetoencephalography (MEG) from 82 healthy participants and investigated whether oscillation dynamics were influenced by genetic polymorphisms in Catechol-O-methyltransferase (COMT) Val158Met and brain-derived neurotrophic factor (BDNF) Val66Met. Both COMT and BDNF polymorphisms influenced local oscillation amplitudes and their long-range temporal correlations (LRTCs), while only BDNF polymorphism affected the strength of large-scale synchronization. Our findings demonstrate that COMT and BDNF genetic polymorphisms contribute to inter-individual variability in local and large-scale synchronization dynamics of neuronal oscillations. Comparison of these results to computational modelling of near-critical synchronization dynamics further suggested that COMT and BDNF polymorphisms influenced local oscillations by modulating the excitation-inhibition balance according to the brain criticality framework.

neuroscience↗

bioRxiv2021

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↗

bioRxiv2020

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↗

bioRxiv2019

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↗

bioRxiv2018

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↗

bioRxiv2018

Variants in regulatory elements of PDE4D associate with Major Mental Illness in the Finnish population

We have previously reported a replicable association between variants at the PDE4D gene and familial schizophrenia in a Finnish cohort. In order to identify the potential functional mutations alluded to by these previous findings, we sequenced the 1.5Mb of the PDE4D genomic locus in 20 families (consisting of 96 individuals, and 79 independent chromosomes), followed by two stages of genotyping across 6,668 individuals from multiple Finnish cohorts for major mental illnesses. We identified 4,570 SNPs across the PDE4D gene, with 380 associated to schizophrenia (p[≤]0.05). Importantly, two of these variants, rs35278 and rs165940, are located at transcription factor binding sites, and displayed replicable association in the two-stage enlargement of the familial schizophrenia cohort, (combined statistics for rs35278 p=0.0012; OR=1.18, 95% CI 1.06-1.32; and rs165940 p=0.0016; OR=1.27, 95% CI 1.13-1.41). Further analysis using additional cohorts and endophenotypes revealed that rs165940 principally associates within the psychosis (p=0.025, OR=1.18, 95% CI 1.07-1.30) and cognitive domains of major mental illnesses (g-score p=0.044, beta=-0.033). Specifically, the cognitive domains represented verbal learning and memory (p=0.0091, beta=-0.044) and verbal working memory (p=0.0062, beta=-0.036). Moreover, expression data from the GTEx database demonstrated that rs165940 significantly correlates with the mRNA expression levels of PDE4D in the cerebellum (p-value=0.04; m-value=0.9), demonstrating a potential functional consequence for this variant. Thus, rs165940 represents the most likely functional variant for major mental illness at the PDE4D locus in the Finnish population, increasing risk broadly to psychotic disorders.

genetics↗

bioRxiv2016

The NDE1 Genomic Locus Affects Treatment of Psychiatric Illness through Gene Expression Changes Related to MicroRNA-484

Genetic studies of familial schizophrenia in Finland have observed significant associations with a group of biologically related genes, DISC1, NDE1, NDEL1, PDE4B and PDE4D, the \"DISC1 network\". Here, we utilize gene expression and psychoactive medication use data to study their biological consequences and potential treatment implications. Gene expression levels were determined in 64 individuals from 18 families, whilst prescription medication information has been collected over a ten-year period for 931 affected individuals. We demonstrate that the NDE1 SNP rs2242549 associates with significant changes in gene expression for 2,908 probes (2,542 genes), of which 794 probes (719 genes) were replicable. A significant number of the genes altered were predicted targets of microRNA-484 (p=3.0x10-8), located on a non-coding exon of NDE1. Variants within the NDE1 locus also displayed significant genotype by gender interaction to early cessation of psychoactive medications metabolized by CYP2C19. Furthermore, we demonstrate that miR-484 can affect the expression of CYP2C19 in a cell culture system. Thus, variation at the NDE1 locus may alter risk of mental illness, in part through modification of miR-484, and such modification alters treatment response to specific psychoactive medications, leading to the potential for use of this locus in targeting treatment.

genetics↗