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      Prenatal Stress and the Developing Brain: Postnatal Environments Promoting Resilience

      , , ,
      Biological Psychiatry
      Elsevier BV

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          Epigenetic programming by maternal behavior.

          Here we report that increased pup licking and grooming (LG) and arched-back nursing (ABN) by rat mothers altered the offspring epigenome at a glucocorticoid receptor (GR) gene promoter in the hippocampus. Offspring of mothers that showed high levels of LG and ABN were found to have differences in DNA methylation, as compared to offspring of 'low-LG-ABN' mothers. These differences emerged over the first week of life, were reversed with cross-fostering, persisted into adulthood and were associated with altered histone acetylation and transcription factor (NGFI-A) binding to the GR promoter. Central infusion of a histone deacetylase inhibitor removed the group differences in histone acetylation, DNA methylation, NGFI-A binding, GR expression and hypothalamic-pituitary-adrenal (HPA) responses to stress, suggesting a causal relation among epigenomic state, GR expression and the maternal effect on stress responses in the offspring. Thus we show that an epigenomic state of a gene can be established through behavioral programming, and it is potentially reversible.
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            More hippocampal neurons in adult mice living in an enriched environment.

            Neurogenesis occurs in the dentate gyrus of the hippocampus throughout the life of a rodent, but the function of these new neurons and the mechanisms that regulate their birth are unknown. Here we show that significantly more new neurons exist in the dentate gyrus of mice exposed to an enriched environment compared with littermates housed in standard cages. We also show, using unbiased stereology, that the enriched mice have a larger hippocampal granule cell layer and 15 per cent more granule cell neurons in the dentate gyrus.
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              Reproducible brain-wide association studies require thousands of individuals

              Magnetic resonance imaging (MRI) has transformed our understanding of the human brain through well-replicated mapping of abilities to specific structures (for example, lesion studies) and functions 1 – 3 (for example, task functional MRI (fMRI)). Mental health research and care have yet to realize similar advances from MRI. A primary challenge has been replicating associations between inter-individual differences in brain structure or function and complex cognitive or mental health phenotypes (brain-wide association studies (BWAS)). Such BWAS have typically relied on sample sizes appropriate for classical brain mapping 4 (the median neuroimaging study sample size is about 25), but potentially too small for capturing reproducible brain–behavioural phenotype associations 5 , 6 . Here we used three of the largest neuroimaging datasets currently available—with a total sample size of around 50,000 individuals—to quantify BWAS effect sizes and reproducibility as a function of sample size. BWAS associations were smaller than previously thought, resulting in statistically underpowered studies, inflated effect sizes and replication failures at typical sample sizes. As sample sizes grew into the thousands, replication rates began to improve and effect size inflation decreased. More robust BWAS effects were detected for functional MRI (versus structural), cognitive tests (versus mental health questionnaires) and multivariate methods (versus univariate). Smaller than expected brain–phenotype associations and variability across population subsamples can explain widespread BWAS replication failures. In contrast to non-BWAS approaches with larger effects (for example, lesions, interventions and within-person), BWAS reproducibility requires samples with thousands of individuals. Combined data from three large studies, with a total sample size of around 50,000 individuals, indicate that many previous studies linking the brain to complex phenotypes have been statistically underpowered, producing inflated and irreproducible effects.
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                Author and article information

                Contributors
                Journal
                Biological Psychiatry
                Biological Psychiatry
                Elsevier BV
                00063223
                May 2023
                May 2023
                : 93
                : 10
                : 942-952
                Article
                10.1016/j.biopsych.2022.11.023
                36870895
                d95c20a4-e175-4418-b641-3a881295d579
                © 2023

                https://www.elsevier.com/tdm/userlicense/1.0/

                http://creativecommons.org/licenses/by/4.0/

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