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      Older Molecular Brain Age in Severe Mental Illness

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          Abstract

          Psychiatric disorders are associated with accelerated aging and enhanced risk for neurodegenerative disorders. Brain aging is associated with molecular, cellular and structural changes that are robust on the group-level, yet show substantial inter-individual variability. Here we assessed deviations in gene expression from normal age-dependent trajectories, and tested their validity as predictors of risk for major mental illnesses and neurodegenerative disorders. We performed large-scale gene expression and genotype analyses in postmortem samples of two frontal cortical brain regions from 214 control subjects aged 20–90 years. Individual estimates of “molecular age” were derived from age-dependent genes, identified by robust regression analysis. Deviation from chronological age was defined as “delta age”. Genetic variants associated with deviations from normal gene expression patterns were identified by expression quantitative trait loci (cis-eQTL) of age-dependent genes or genome-wide association study (GWAS) on delta age, combined into distinct polygenic risk scores (PRS cis-eQTL and PRS GWAS), and tested for predicting brain disorders or pathology in independent postmortem expression datasets and clinical cohorts. In these validation datasets, molecular ages, defined by 68 and 76 age-related genes for two brain regions respectively, were positively correlated with chronological ages (r=0.88/0.91), elevated in bipolar disorder (BP) and schizophrenia (SCZ), and unchanged in major depressive disorder (MDD). Exploratory analyses in independent clinical datasets show that PRSs were associated with SCZ and MDD diagnostics, and with cognition in SCZ and pathology in Alzheimer’s disease (AD). These results suggest that older molecular brain aging is a common feature of severe mental illnesses and neurodegeneration.

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          Most cited references31

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          DNA methylation age of human tissues and cell types

          Background It is not yet known whether DNA methylation levels can be used to accurately predict age across a broad spectrum of human tissues and cell types, nor whether the resulting age prediction is a biologically meaningful measure. Results I developed a multi-tissue predictor of age that allows one to estimate the DNA methylation age of most tissues and cell types. The predictor, which is freely available, was developed using 8,000 samples from 82 Illumina DNA methylation array datasets, encompassing 51 healthy tissues and cell types. I found that DNA methylation age has the following properties: first, it is close to zero for embryonic and induced pluripotent stem cells; second, it correlates with cell passage number; third, it gives rise to a highly heritable measure of age acceleration; and, fourth, it is applicable to chimpanzee tissues. Analysis of 6,000 cancer samples from 32 datasets showed that all of the considered 20 cancer types exhibit significant age acceleration, with an average of 36 years. Low age-acceleration of cancer tissue is associated with a high number of somatic mutations and TP53 mutations, while mutations in steroid receptors greatly accelerate DNA methylation age in breast cancer. Finally, I characterize the 353 CpG sites that together form an aging clock in terms of chromatin states and tissue variance. Conclusions I propose that DNA methylation age measures the cumulative effect of an epigenetic maintenance system. This novel epigenetic clock can be used to address a host of questions in developmental biology, cancer and aging research.
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            Gene regulation and DNA damage in the ageing human brain.

            The ageing of the human brain is a cause of cognitive decline in the elderly and the major risk factor for Alzheimer's disease. The time in life when brain ageing begins is undefined. Here we show that transcriptional profiling of the human frontal cortex from individuals ranging from 26 to 106 years of age defines a set of genes with reduced expression after age 40. These genes play central roles in synaptic plasticity, vesicular transport and mitochondrial function. This is followed by induction of stress response, antioxidant and DNA repair genes. DNA damage is markedly increased in the promoters of genes with reduced expression in the aged cortex. Moreover, these gene promoters are selectively damaged by oxidative stress in cultured human neurons, and show reduced base-excision DNA repair. Thus, DNA damage may reduce the expression of selectively vulnerable genes involved in learning, memory and neuronal survival, initiating a programme of brain ageing that starts early in adult life.
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              Excess early mortality in schizophrenia.

              Schizophrenia is often referred to as one of the most severe mental disorders, primarily because of the very high mortality rates of those with the disorder. This article reviews the literature on excess early mortality in persons with schizophrenia and suggests reasons for the high mortality as well as possible ways to reduce it. Persons with schizophrenia have an exceptionally short life expectancy. High mortality is found in all age groups, resulting in a life expectancy of approximately 20 years below that of the general population. Evidence suggests that persons with schizophrenia may not have seen the same improvement in life expectancy as the general population during the past decades. Thus, the mortality gap not only persists but may actually have increased. The most urgent research agenda concerns primary candidates for modifiable risk factors contributing to this excess mortality, i.e., side effects of treatment and lifestyle factors, as well as sufficient prevention and treatment of physical comorbidity.
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                Author and article information

                Journal
                9607835
                20545
                Mol Psychiatry
                Mol Psychiatry
                Molecular psychiatry
                1359-4184
                1476-5578
                20 July 2020
                06 July 2020
                July 2021
                13 October 2021
                : 26
                : 7
                : 3646-3656
                Affiliations
                [1 ]Department of Biostatistics, Graduate school of Public Health, University of Pittsburgh, Pittsburgh, PA 15261, USA
                [2 ]Division of Biostatistics, Medical College of Wisconsin, Milwaukee, WI 53226
                [3 ]Department of Mathematical Sciences, Florida Atlantic University, Boca Raton, FL 33431, USA
                [4 ]Department of Epidemiology and Biostatistics, University of Maryland, College Park, MD 20742, USA
                [5 ]Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA 15312, USA
                [6 ]Campbell Family Mental Health Research Institute of CAMH, Department of Psychiatry, University of Toronto, Toronto, M5T1R8, ON, Canada
                [7 ]Institute of Medical Science, University of Toronto, Toronto, ON, Canada
                [8 ]Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD 21205, USA
                [9 ]Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
                [10 ]Department of Psychiatry, Washington University, St. Louis, MO 63130, USA
                [11 ]Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA 15261, USA
                [12 ]Department of Pharmacology and Toxicology, University of Toronto, Toronto, M5T1R8, ON, Canada
                Author notes
                [* ]To whom correspondence should be addressed. ctseng@ 123456pitt.edu (GCT) or Etienne.sibille@ 123456camh.ca (ES)
                Article
                NIHMS1607033
                10.1038/s41380-020-0834-1
                7785531
                32632206
                59702750-3774-4f4a-b1c5-c0492afc4ae3

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                History
                Categories
                Article

                Molecular medicine
                aging,molecular age,transcriptome,genetic,cis-eqtl,polygenic risk score
                Molecular medicine
                aging, molecular age, transcriptome, genetic, cis-eqtl, polygenic risk score

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