Aging can do a number on the human brain. Thinking slows, concentration flags, and memory can falter. A study in the January 10 Cell Reports uncovers a dramatic difference between how neurons and glia, the brain’s supporting cells, deal with aging. Researchers led by Rickie Patani and Jernej Ule of University College London in the United Kingdom analyzed gene expression data from more than 400 people between the ages of 16 and 106. Dissecting the data by cell type, the scientists found that glia from older people lose their regional identity. In other words, gene expression in glia from a particular region, such as the hippocampus, becomes more like the glial expression pattern in a different region of the brain. Some of the most striking shifts occurred in parts of the brain affected by Alzheimer’s and Parkinson’s diseases.

Researchers not connected to the study were intrigued by the findings. “It’s a really exciting paper,” Shane Liddelow of Stanford University School of Medicine in California told Alzforum. “The study is the first of its kind to attempt to analyze cell-type specific transcriptomes in aged and very aged brains of humans,” said Liddlelow, who just published a paper reporting how astrocytes become toxic in certain disease states (see Jan 2017 news). Richard Ransohoff from Biogen in Cambridge, Massachusetts, told Alzforum that the findings offer an important opportunity for further research. “If we want to understand how aging contributes to neurodegeneration, this is a good place to start,” he said. Oleg Butovsky of Harvard Medical School in Boston noted that the study dovetails with previous work highlighting the role of microglia in aging and neurodegeneration.

A second paper in the same issue revealed a surprise about these cells. Researchers led by Diego Gomez-Nicola of the University of Southampton in the United Kingdom demonstrated that microglia continue to proliferate rapidly, even when people reach old age. This sustained reproduction would result in relatively more microglia in the brains of older people, and thus could influence measurements of gene expression.

“The single most important risk factor for all neurodegenerative diseases is age,” said Ransohoff. Yet researchers remain uncertain how aging sets the stage for disease. To obtain a broad view of aging’s impact on the brain, Patani, Ule, and first author Lilach Soreq and colleagues compiled microarray measurements of gene expression from two large data sets. The most comprehensive data came from the 1,231 brain samples from 134 individuals analyzed by the UK Brain Expression Consortium. This data includes expression measurements for 10 regions: the frontal cortex, temporal cortex, occipital cortex, intralobular white matter, cerebellum, substantia nigra, putamen, thalamus, hippocampus, and medulla. A second data set from the North American Brain Expression Consortium included samples from 307 people, but only recorded gene expression in the cerebellum and frontal cortex. The researchers also used a third data set, which included measurements from prefrontal cortex, to check their conclusions.

Their analysis found that nine genes altered expression throughout the brain with increasing age. Using expression levels of just these genes, the scientists could predict whether subjects were young (under 45), middle-aged (45 to 74), or 75 or older—although they couldn’t pinpoint age to the year, Ule told Alzforum. The nine include genes that are active specifically in microglia, endothelial cells, and oligodendrocytes. “The reason they are good predictors of age may be that they reflect some generic age-related changes taking place within these three cell types,” Ule wrote to Alzforum.

Expression of other genes also changed with age, but in a cell- and region-specific manner. Overall, neuronal gene expression fell in older subjects, but the regional transcriptional profiles of neurons stayed almost the same. Even as people reached old age, for example, hippocampal neurons still expressed hippocampal genes at about the same levels.

The picture was different for glia. Previous studies have identified regional expression differences in glia such as astrocytes and microglia (Ko et al., 2013; Grabert et al., 2016). Patani, Ule, and colleagues showed that aging modifies these region-specific patterns. In brains from young subjects, for example, oligodendrocyte-specific gene expression in the substantia nigra tracked with that in the medulla and thalamus, whereas hippocampal expression clustered with that in cortical regions. Not so in older individuals. Gene expression patterns in the substantia nigra and the hippocampus diverged from their youthful profiles and converged on each other. The scientists also detected age-related shifts in regional expression of astrocyte-specific genes. Hippocampal astrocytes most closely resembled the cortical astrocytes in young subjects, but white matter and putamen astrocytes in older individuals.

That the hippocampus and substantia nigra show significant gene expression differences with aging may help explain why they are susceptible to some of the first effects of Alzheimer’s and Parkinson’s pathologies, respectively, the authors suggest.

For microglial gene expression, age was more important than location. These cells intrigue researchers who study aging and neurodegenerative diseases. By stoking inflammation, microglia may promote neurodegeneration (see Dec 2016 conference news), and recent work has implicated them in the loss of synapses in AD (see Apr 2016 news). Soreq and colleagues discovered that microglia-specific gene expression differed between younger and older subjects in all brain regions except for the cerebellum. Unlike neurons, microglia typically boosted the activity of their genes with age, probably reflecting the cells’ increased activity in older individuals. Two of the genes that ramped up expression were C1Q and TREM2, which have been linked to AD and other neurodegenerative diseases (see Apr 2016 news). 

“Our paper shows that aging predominantly affects glia,” Patani told Alzforum. The cells have an “identity crisis” during aging, he said. “They lose their tightly regulated regional expression pattern.” In turn, that loss may disrupt their interactions with neurons and thus potentially contribute to the neurodegeneration of diseases like AD and PD, Patani speculated.

One potential confounding factor for this analysis is that the gene expression profile changes don’t necessarily indicate alterations in transcription rates but could instead reflect shifts in cell numbers. To distinguish between these possibilities, the scientists used an automated system to tally cells in the tissue samples. They found that samples from older people contained fewer oligodendrocytes than did those from younger individuals, suggesting that the overall decline in gene expression in these cells might at least partially stem from their reduced abundance. In contrast, the number of small and medium-sized neurons were constant across age groups.  

There were fewer large and extra-large neurons in samples from older individuals, however. These hefty cells include motor and pyramidal neurons, which are involved in many processes in the brain, including learning, memory, and movement initiation. Loss of these large cells could explain the decline in neuron gene expression with age, the researchers noted. Ule cautioned, however, that it’s unclear which of these large neurons are disappearing and whether they are lost or have merely turned off expression of Rbfox3, the marker used to detect them. In the end, the researchers surmise that the observed gene expression alterations probably are a combination of transcription rate changes and cell number fluctuations.

Soreq and colleagues didn’t count microglia. However, Gomez-Nicola, first author Katherine Askew, and colleagues did, and their results challenge conventional wisdom that the immune cells proliferate at a sluggish pace. They tallied microglia in brain samples from mice of different ages and from people who died between 20 and 76 years of age. Their density of microglia didn’t change with age, suggesting that any cells lost over time are quickly replaced. In fact, the researchers estimated that in rodents the microglial cell population turns over every 96 days, 10 times faster than established estimates (Lawson et al., 1992). Human microglia may replicate even faster, their results suggested. “We don’t see significant age-related change in the turnover capacity” of the cells, Gomez-Nicola told Alzforum.

Bruce Yankner of Harvard Medical School noted that proliferation by microglia—or by astrocytes, which also have the ability to reproduce—could contribute to the gene expression changes Soreq and colleagues detected. “A larger proportion of the cell population might be astroglial or microglial in aged brains than in young brains. Hence, gene expression profiling of whole brain tissue samples might over-represent these genes,” he wrote. “In addition, proliferation of specific glial subpopulations might affect some glial genes more than others,” Yankner posited. He thinks that future studies will be able to unravel primary transcriptional alterations from changes in cell populations. “It looks like single-cell RNA sequencing is the best way to address this,” he said.—Mitch Leslie

Mitch Leslie is a freelance writer based in Tucson, Arizona. 

Comments

  1. This is a very interesting set of data that comes at an opportune time in glial research. Soreq et al. shed further insight into glial heterogeneity among different regions in the human brain, and into how aging affects this heterogeneity across cell types. This study is particularly relevant given the remarkable region-specific vulnerability in neural networks in multiple neurologic diseases, and it highlights the importance of understanding whether and how different glial cells contribute to aging and neurodegeneration.

    We have known for many years now that astrocytes are heterogeneous across and within brain regions (Oberheim et al., 2012). Emerging literature in mouse models suggests that microglia are a diverse population as well; their gene expression is shaped by development, age, resident brain region, sex, and gut microbiota (Hickman et al., 2013; Butovsky et al., 2014; Grabert et al., 2016; Matcovitch-Natan et al., 2016). Recently, Barry McColl’s group (Grabert et al., 2016) beautifully showed that mouse microglia have regionally diverse transcriptomic profiles, and potentially differential sensitivities to aging. The microglia data set from Soreq et al. suggests that whereas there may be less regional heterogeneity in microglia gene expression in human brains, microglial transcriptomic profiles change significantly with aging across brain regions. This is in agreement with both Grabert et al. and Joe El Khoury’s data set in acutely isolated microglia from mice (Hickman et al., 2013), which demonstrated that aging is associated with alterations in immune network, including transcripts encoding for cell surface sensing genes. The important next questions will be to understand how much of these transcriptomic changes translate into functional alterations. What do microglia do in the healthy adult brain, and how do their functions alter with aging? Are microglia responding to specific cues that are changing within their local microenvironment, or are they actively contributing to the aging process? Answering these questions would help us understand their remarkable plasticity in the living brain and gain insight into underlying molecular pathways in aging and disease. Furthermore, it will now be crucial for us to look at the single cell level, while also expanding efforts to understand how the different cell types interact to maintain (or destroy) a functional brain.

    There are already suggestions in the literature for how two of the genes found by Soreq et al. to be upregulated in aging, C1q and Trem2, could be affecting the aging nervous system. Ben Barres’ group showed that the deposition of C1q protein on synapses increases dramatically with aging (Stephan et al., 2013). We have recently shown in mouse models of Aβ-related synaptic pathology that C1q is necessary for oligomeric Aβ to induce synapse loss (Hong et al., 2016). An intriguing question posed is whether with aging, the increase of C1q makes surrounding synapses more vulnerable to loss and dysfunction. While the functions of microglial Trem2 at synapses are still yet to be understood, mutations on Trem2 (or DAP12) lead to progressive presenile dementia in Nasu-Hakola disease (Paloneva et al., 2000, and 2002). Trem2 has also been identified to be a significant risk factor for late-onset Alzheimer’s disease (Guerreiro et al., 2013; Jonsson et al., 2013). Exactly by what mechanisms it affects synaptic pathology still need to be elucidated. However, Soreq et al. provide yet another rationale for focusing on microglia-related pathways in the study of aging and age-related diseases of cognitive decline, including Alzheimer’s. 

    References:

    . Heterogeneity of astrocytic form and function. Methods Mol Biol. 2012;814:23-45. PubMed.

    . The microglial sensome revealed by direct RNA sequencing. Nat Neurosci. 2013 Dec;16(12):1896-905. Epub 2013 Oct 27 PubMed.

    . Identification of a unique TGF-β-dependent molecular and functional signature in microglia. Nat Neurosci. 2014 Jan;17(1):131-43. Epub 2013 Dec 8 PubMed.

    . Microglial brain region-dependent diversity and selective regional sensitivities to aging. Nat Neurosci. 2016 Mar;19(3):504-16. Epub 2016 Jan 18 PubMed.

    . Microglia development follows a stepwise program to regulate brain homeostasis. Science. 2016 Aug 19;353(6301):aad8670. Epub 2016 Jun 23 PubMed.

    . A Dramatic Increase of C1q Protein in the CNS during Normal Aging. J Neurosci. 2013 Aug 14;33(33):13460-74. PubMed.

    . Complement and microglia mediate early synapse loss in Alzheimer mouse models. Science. 2016 May 6;352(6286):712-6. Epub 2016 Mar 31 PubMed.

    . Loss-of-function mutations in TYROBP (DAP12) result in a presenile dementia with bone cysts. Nat Genet. 2000 Jul;25(3):357-61. PubMed.

    . Mutations in two genes encoding different subunits of a receptor signaling complex result in an identical disease phenotype. Am J Hum Genet. 2002 Sep;71(3):656-62. PubMed.

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References

News Citations

  1. Microglia Give Astrocytes License to Kill
  2. Inflammation Helps Microglia Clear Amyloid from AD Brains
  3. Paper Alert: Microglia Mediate Synaptic Loss in Early Alzheimer’s Disease

Paper Citations

  1. . Cell type-specific genes show striking and distinct patterns of spatial expression in the mouse brain. Proc Natl Acad Sci U S A. 2013 Feb 19;110(8):3095-100. Epub 2013 Feb 5 PubMed.
  2. . Microglial brain region-dependent diversity and selective regional sensitivities to aging. Nat Neurosci. 2016 Mar;19(3):504-16. Epub 2016 Jan 18 PubMed.
  3. . Turnover of resident microglia in the normal adult mouse brain. Neuroscience. 1992;48(2):405-15. PubMed.

Further Reading

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Primary Papers

  1. . Major Shifts in Glial Regional Identity Are a Transcriptional Hallmark of Human Brain Aging. Cell Rep. 2017 Jan 10;18(2):557-570. PubMed.
  2. . Coupled Proliferation and Apoptosis Maintain the Rapid Turnover of Microglia in the Adult Brain. Cell Rep. 2017 Jan 10;18(2):391-405. PubMed.