Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 5 de 5
Filtrar
Mais filtros










Base de dados
Intervalo de ano de publicação
1.
iScience ; 25(9): 104860, 2022 Sep 16.
Artigo em Inglês | MEDLINE | ID: mdl-36046194

RESUMO

Prenatal maternal mental health is a global health challenge with poorly defined biological mechanisms. We used maternal blood samples collected during the second trimester from a Singaporean longitudinal birth cohort study to examine the association between inter-individual genome-wide DNA methylation and prenatal maternal depressive symptoms. We found that (1) the maternal methylome was significantly associated with prenatal maternal depressive symptoms only in mothers with a female fetus; and (2) this sex-dependent association was observed in a comparable, UK-based birth cohort study. Qualitative analyses showed fetal sex-specific differences in genomic features of depression-related CpGs and genes mapped from these CpGs in mothers with female fetuses implicated in a depression-associated WNT/ß-catenin signaling pathway. These same genes also showed enriched expression in brain regions linked to major depressive disorder. We also found similar female-specific associations with fetal-facing placenta methylome. Our fetal sex-specific findings provide evidence for maternal-fetal interactions as a mechanism for intergenerational transmission.

3.
Biol Psychiatry ; 91(3): 303-312, 2022 02 01.
Artigo em Inglês | MEDLINE | ID: mdl-34756561

RESUMO

BACKGROUND: The fetal origins of mental health is a well-established framework that currently lacks a robust index of the biological embedding of prenatal adversity. The Pediatric-Buccal-Epigenetic (PedBE) clock is a novel epigenetic tool that associates with aspects of the prenatal environment, but additional validation in longitudinal datasets is required. Likewise, the relationship between prenatal maternal mental health and the PedBE clock has not been described. METHODS: Longitudinal cohorts from the Netherlands (Basal Influences on Baby Development [BIBO] n = 165) and Singapore (Growing Up in Singapore Towards Healthy Outcomes [GUSTO] n = 340) provided data on prenatal maternal anxiety and longitudinal assessments of buccal cell-derived genome-wide DNA methylation assessed at 6 and 10 years of age in BIBO, and at 3, 9, and 48 months of age in GUSTO. Measures of epigenetic age acceleration were calculated using the PedBE clock and benchmarked against an established multi-tissue epigenetic predictor. RESULTS: Prenatal maternal anxiety predicted child PedBE epigenetic age acceleration in both cohorts, with effects largely restricted to males and not females. These results were independent of obstetric, socioeconomic, and genetic risk factors, with a larger effect size for prenatal anxiety than depression. PedBE age acceleration predicted increased externalizing symptoms in males from mid- to late childhood in the BIBO cohort only. CONCLUSIONS: These findings point to the fetal origins of epigenetic age acceleration and reveal an increased sensitivity in males. Convergent evidence underscores the societal importance of providing timely and effective mental health support to pregnant individuals, which may have lasting consequences for both mother and child.


Assuntos
Epigênese Genética , Epigenômica , Envelhecimento , Ansiedade/genética , Criança , Metilação de DNA , Feminino , Humanos , Masculino , Gravidez
4.
Front Neurosci ; 14: 198, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32256307

RESUMO

Variations in serotoninergic signaling have been related to behavioral outcomes. Alterations in the genome, such as DNA methylation and histone modifications, are affected by serotonin neurotransmission. The amygdala is an important brain region involved in emotional responses and impulsivity, which receives serotoninergic input. In addition, studies suggest that the serotonin transporter gene network may interact with the environment and influence the risk for psychiatric disorders. We propose to investigate whether/how interactions between the exposure to early life adversity and serotonin transporter gene network in the amygdala associate with behavioral disorders. We constructed a co-expression-based polygenic risk score (ePRS) reflecting variations in the function of the serotonin transporter gene network in the amygdala and investigated its interaction with postnatal adversity on attention problems in two independent cohorts from Canada and Singapore. We also described how interactions between ePRS-5-HTT and postnatal adversity exposure predict brain gray matter density and variation in DNA methylation across the genome. We observed that the expression-based polygenic risk score, reflecting the function of the amygdala 5-HTT gene network, interacts with postnatal adversity, to predict attention and hyperactivity problems across both cohorts. Also, both postnatal adversity score and amygdala ePRS-5-HTT score, as well as their interaction, were observed to be associated with variation in DNA methylation across the genome. Variations in gray matter density in brain regions linked to attentional processes were also correlated to our ePRS score. These results confirm that the amygdala 5-HTT gene network is strongly associated with ADHD-related behaviors, brain cortical density, and epigenetic changes in the context of adversity in young children.

5.
IEEE Trans Neural Netw Learn Syst ; 29(9): 4140-4151, 2018 09.
Artigo em Inglês | MEDLINE | ID: mdl-29990028

RESUMO

In a real brain, the act of perception is a bidirectional process, depending on both feedforward sensory pathways and feedback pathways that carry expectations. We are interested in how such a neural network might emerge from a biologically plausible learning rule. Other neural network learning methods either only apply to feedforward networks, or employ assumptions (such as weight copying) that render them unlikely in a real brain. Predictive estimators (PEs) offer a better solution to this bidirectional learning scenario. However, PEs also depend on weight copying. In this paper, we propose the symmetric PE (SPE), an architecture that can learn both feedforward and feedback connection weights individually using only locally available information. We demonstrate that the SPE can learn complicated mappings without the use of weight copying. The SPE networks also show promise in deeper architectures.


Assuntos
Encéfalo , Aprendizado Profundo , Modelos Neurológicos , Redes Neurais de Computação , Encéfalo/fisiologia , Previsões , Humanos
SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA
...