Age-related gene expression changes, and transcriptome wide association study of physical and cognitive aging traits, in the Lothian Birth Cohort 1936

Harris, Sarah E.; Riggio, Valentina; Evenden, Louise; Gilchrist, T. L.; McCafferty, Sarah; Murphy, Lee; Wrobel, Nicola; Taylor, Adele M.; Corley, Janie; Pattie, Alison; Cox,; Martin-Ruiz, Carmen; Prendergast, James; Starr, John M.; Marioni, Riccardo E.; Deary, Ian J.

doi:10.18632/aging.101333

Cited by 32 publications

(27 citation statements)

References 64 publications

(68 reference statements)

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“…A similar result was obtained in other analysis using several aging organs -kidney, lung, brain cortex, liver-from humans, mice, and rats [7]. In human lymphoblastoid cells, the proportion was 1:1 [31]. Two studies using whole blood cells found a proportion close to 1.4:1 [32,33].…”

Section: General Transcriptomic Landscape Of Aging In Pfcsupporting

confidence: 86%

Integrative Analysis of Global Gene Expression Identifies Opposite Patterns of Reactive Astrogliosis in Aged Human Prefrontal Cortex

Payán-Gómez¹,

Rodríguez²,

Amador-Muñoz³

et al. 2018

Preprint

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Prefrontal cortex (PFC) is one of the brain regions with more prominent changes in human aging. The molecular processes related to the aging cognitive decline and mood changes are not completely understood. In order to improve our knowledge, we integrated transcriptomic data of four studies of human PFC from old people -58-80 years old- compared with young people -20-40 years old- using a meta-analytic approximation combined with molecular signature analysis. We identified 1816 differentially expressed genes -561 up-regulated and 1256 down-regulated. Pathway analysis revealed down-regulation of synaptic genes with conservation of gene expression of other neuronal regions. Additionally, we identified up-regulation of markers of astrogliosis with transcriptomic signature compatible with A1 neurotoxic astrocytes and A2 neuroprotective astrocytes. Response to interferon is related to A1 astrocytes and the A2 phenotype is mediated in aging by activation of SHH pathway and up-regulation of metallothioneins I and genes of the family EZR -ezrin, radixin, and moesin-. The main conclusions of our study are the confirmation that in aged PFC there is a global dysfunction of the synapses and we reported for the first time opposite phenotypes of astrogliosis because of brain aging.

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“…Gene expression data. Expression data were acquired for the 876 LBC1936 individuals 48 . In summary, peripheral blood mononuclear cells (PBMCs) from 1091 LBC1936 individuals were extracted from whole blood collected at mean age 70 years (S.D.…”

Section: Methodsmentioning

confidence: 99%

“…Frozen LCL pellets were returned to the ECRF Genetics Core, where RNA was extracted using a Qiagen miRNeasy kit, biotin-labelled, and genome-wide gene expression levels measured using Illumina's HumanHT-12 v4 Expression BeadChip which contains 47,231 probes; a control RNA sample was included on each array. Individuals with a signal-to-noise ratio <10 or with fewer than 9000 detected transcripts (P < 0.01) were excluded (n = 130), and only probes expressed in >20% of individuals were retained 48 . The microarray data was quantile normalised using the Bioconductor pacakage lumi 49 , after which probes with no detectable expression were removed, resulting in 38,764 probes.…”

Section: Methodsmentioning

confidence: 99%

Using regulatory variants to detect gene–gene interactions identifies networks of genes linked to cell immortalisation

et al. 2020

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The extent to which the impact of regulatory genetic variants may depend on other factors, such as the expression levels of upstream transcription factors, remains poorly understood. Here we report a framework in which regulatory variants are first aggregated into sets, and using these as estimates of the total cis-genetic effects on a gene we model their nonadditive interactions with the expression of other genes in the genome. Using 1220 lymphoblastoid cell lines across platforms and independent datasets we identify 74 genes where the impact of their regulatory variant-set is linked to the expression levels of networks of distal genes. We show that these networks are predominantly associated with tumourigenesis pathways, through which immortalised cells are able to rapidly proliferate. We consequently present an approach to define gene interaction networks underlying important cellular pathways such as cell immortalisation.

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“…Aging of multi-cellular organisms is a complex biological process involving various molecular alterations such as epigenetic [1], genetic [2], and transcriptional changes [3][4][5][6]. These changes are likely modulated by various environmental factors that can either induce premature aging [7] or decelerate the natural aging rate [8].…”

Section: Introductionmentioning

confidence: 99%

Lung transcriptomic clock predicts premature aging in cigarette smoke-exposed mice

et al. 2020

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Background: Lung aging is characterized by a number of structural alterations including fibrosis, chronic inflammation and the alteration of inflammatory cell composition. Chronic exposure to cigarette smoke (CS) is known to induce similar alterations and may contribute to premature lung aging. Additionally, aging and CS exposure are associated with transcriptional alterations in the lung. The current work aims to explore the interaction between age-and CS-associated transcriptomic perturbations and develop a transcriptomic clock able to predict the biological age and the impact of external factors on lung aging. Results: Our investigations revealed a substantial overlap between transcriptomic response to CS exposure and age-related transcriptomic alterations in the murine lung. Of particular interest is the strong upregulation of immunoglobulin genes with increased age and in response to CS exposure, indicating an important implication of B-cells in lung inflammation associated with aging and smoking. Furthermore, we used a machine learning approach based on Lasso regression to build a transcriptomic age model that can accurately predict chronological age in untreated mice and the deviations associated with certain exposures. Interestingly, CS-exposed-mice were predicted to be prematurely aged in contrast to mice exposed to fresh air or to heated tobacco products (HTPs). The accelerated aging rate associated with CS was reversed upon smoking cessation or switching to HTPs. Additionally, our model was able to predict premature aging associated with thoracic irradiation from an independent public dataset.Conclusions: Aging and CS exposure share common transcriptional alteration patterns in the murine lung. The massive upregulation of B-cell restricted genes during these processes shed light on the contribution of cell composition and particularly immune cells to the measured transcriptomic signal. Through machine learning approach, we show that gene expression changes can be used to accurately monitor the biological age and the modulations associated with certain exposures. Our findings also suggest that the premature lung aging is reversible upon the reduction of harmful exposures.

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“…With aging, the speed of the information processing and of the capacity of short-term and long-term memory decreases; besides, there is an alteration in the impulse control, all these functions depend as much on the modification of the impulse control, as on the integrity of the pfc, the hippocampus and the post-rolandic cortex too (7)(8)(9)(10)(11). Transcriptomics studies of aged pfc have consistently reported decrease of the synapsis function and activation of the neuroglia cells (12)(13)(14)(15). Recently, modifications in the splicing mechanisms associated with the transcriptome in the pfc have been found (16).…”

Section: Introductionmentioning

confidence: 99%

Co-Expression Network Analysis Identifies Possible Hub Genes in Aging of the Human Prefrontal Cortex

et al. 2019

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Introducción: el envejecimiento es el principal factor de riesgo para el desarrollo de enfermedades crónicas como el cáncer, la diabetes, el Parkinson y el Alzheimer. El sistema nervioso central es particularmente susceptible al deterioro funcional progresivo asociado con la edad, entre las regiones cerebrales con mayor compromiso se encuentra la corteza prefrontal (CPF). Estudios de transcriptómica de esta región han identificado como características fundamentales del proceso de envejecimiento la disminución de la función sináptica y la activación de las células de la neuroglia. No es claro cuáles son las causas iniciales, ni los mecanismos moleculares subyacentes a estas alteraciones. El objetivo de este estudio fue identificar genes clave en la desregulación transcriptómica en el envejecimiento de la CPF para avanzar en el conocimiento de este proceso. Materiales y métodos: se hizo un análisis de coexpresión de genes de los transcriptomas de 45 personas entre 60 y 80 años con el de 38 personas entre 20 y 40 años. Las redes fueron visualizadas y analizadas usando Cytoscape, se usó citoHubba para determinar qué genes tenían las mejores características topológicas en las redes de coexpresión. Resultados: se identificaron cinco genes con características topológicas altas. Cuatro de ellos —hpca, cacng3, ca10, plppr4— reprimidos y uno sobreexpresado —Cryab—. Conclusión: los cuatro genes reprimidos se expresan preferencialmente en neuronas y regulan la función sináptica y la plasticidad neuronal, mientras el gen sobreexpresado es típico de células de la glía y se expresa como respuesta a daño neuronal facilitando la mielinización y la regeneración neuronal.

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Age-related gene expression changes, and transcriptome wide association study of physical and cognitive aging traits, in the Lothian Birth Cohort 1936

Cited by 32 publications

References 64 publications

Integrative Analysis of Global Gene Expression Identifies Opposite Patterns of Reactive Astrogliosis in Aged Human Prefrontal Cortex

Using regulatory variants to detect gene–gene interactions identifies networks of genes linked to cell immortalisation

Lung transcriptomic clock predicts premature aging in cigarette smoke-exposed mice

Co-Expression Network Analysis Identifies Possible Hub Genes in Aging of the Human Prefrontal Cortex

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