Region- and Cell-specific Aneuploidy in Brain Aging and Neurodegeneration

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NEUROSCIENCE 1

NEUROSCIENCE FOREFRONT REVIEW C. E. Shepherd et al. / Neuroscience xxx (2018) xxx–xxx

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Region- and Cell-specific Aneuploidy in Brain Aging and Neurodegeneration

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C. E. Shepherd, a,b* Y. Yang a,b,c and G. M. Halliday a,b,c

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a

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b

School of Medical Sciences, University of New South Wales, Sydney 2031, Australia

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c

Brain and Mind Centre, Sydney Medical School, The University of Sydney, Australia

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Neuroscience Research Australia, Margarete Ainsworth Building, Barker Street, Randwick, Sydney 2031, Australia

Abstract—Variations in genomic DNA content, or aneuploidy, are a well-recognized feature of normal human brain development. Whether changes in the levels of aneuploidy are a factor in Alzheimer’s disease (AD) is less clear, as the data reported to date vary substantially in the levels of aneuploidy detected (0.7–11.5%), possibly due to methodological limitations, but also influenced by individual, regional and cellular heterogeneity as well as variations in cell subtypes. These issues have not been adequately addressed to date. While it is known that the DNA damage response increases with age, the limited human studies investigating aneuploidy in normal aging also show variable results, potentially due to susceptibility to age-related neurodegenerative processes. Neuronal aneuploidy has recently been reported in multiple brain regions in Lewy body disease, but similar genomic changes are not a feature of all synucleinopathies and aneuploidy does not appear to be related to alphasynuclein aggregation. Rather, aneuploidy was associated with Alzheimer’s pathology in the hippocampus and anterior cingulate cortex and neuronal degeneration in the substantia nigra. The association between Alzheimer’s pathology and aneuploidy in regions with limited neurodegeneration is supported by a growing body of in vitro and in vivo data on aneuploidy and beta-amyloid and tau abnormalities. Large-scale studies using high-resolution techniques alongside other sensitive and specific methodologies are now required to assess the true extent of cell- and region-specific aneuploidy in aging and neurodegeneration, and to determine any associations with pathologies. Ó 2018 The Author(s). Published by Elsevier Ltd on behalf of IBRO. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Key words: aging, neurodegeneration, aneuploidy.

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Contents Introduction Genomic diversity in the normal brain Aneuploidy during normal aging Aneuploidy and neurodegeneration Are different brain regions more susceptible to aneuploidy? Are neurons or glia more susceptible to aneuploidy? Abnormal protein deposition and aneuploidy Conclusion Funding Conflicts of interest Contributions References

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*Corresponding author. Address: Neuroscience Research Australia, Margarete Ainsworth Building, Barker Street, Randwick, Sydney 2031, Australia. E-mail addresses: [email protected] (C. E. Shepherd), yue. [email protected] (Y. Yang), [email protected] (G. M. Halliday). Abbreviations: AD, Alzheimer’s disease; FACS, FluorescenceActivated Cell Sorting; FCM, Flow Cytometry; FISH, Fluorescence Insitu Hybridization; MVA, mosaic variegated aneuploidy.

INTRODUCTION

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DNA variations can vary in length from single base pairs to the entire genome. In contrast to polyploidy, where the entire genome is replicated, aneuploidy refers to the alteration of whole chromosomes. The number of chromosomes in an aneuploid cell can either be higher or lower than the diploid content and is referred to as hyperploidy or hypoploidy, respectively. These karyotype alterations can have profound effects on normal cellular function, most notably in cancer where aneuploidy is found in the vast majority of tumor types (Finkel et al., 2007). Aneuploidy also accounts for the majority of spontaneous miscarriages in humans, such as Down, Edwards and Patau Syndromes (Hassold and Hunt, 2001). The majority of Down Syndrome cases are due to constitutional aneuploidy, whereby triplication of chromosome 21 occurs in every cell. In contrast, chromosome aneuploidy in select cells is referred to as mosaic aneuploidy and is illustrated in disorders such as mosaic variegated aneuploidy (MVA). In MVA, monosomy and trisomy occur in specific neural cell types leading to growth

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https://doi.org/10.1016/j.neuroscience.2018.01.050 0306-4522/Ó 2018 The Author(s). Published by Elsevier Ltd on behalf of IBRO. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). 1 Please cite this article in press as: Shepherd CE et al. Region- and Cell-specific Aneuploidy in Brain Aging and Neurodegeneration. Neuroscience (2018), https://doi.org/10.1016/j.neuroscience.2018.01.050

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and mental retardation as well as to high risks of cancer (Kajii et al., 2001; Jacquemont et al., 2002).

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GENOMIC DIVERSITY IN THE NORMAL BRAIN

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Neural genomic mosaicism has previously been identified in the embryonic mouse brain whereby approximately 33% of proliferating neural progenitor cells in the subventricular zone displayed aneuploidy (Rehen et al., 2001). Although recent single-cell sequencing data did not replicate these findings (Knouse et al., 2014), significant genomic variation has been identified in normal human brain development (Yurov et al., 2007; Iourov et al., 2012; Bushman and Chun, 2013) where many of these cells may undergo apoptosis (Blaschke et al., 1996). Indeed, recent studies have demonstrated differential elimination of aneuploid cells by caspasemediated programmed cell death (Peterson et al., 2012), which is known to be an essential process for the control of cerebral shape and size (Haydar et al., 1999). Such mechanisms of regulation are clearly crucial to our development and normal physiological growth and function, and it is now widely recognized that a proportion of aneuploid neurons remain functional and capable of differentiation and integration into normal brain circuitry (Kingsbury et al., 2005). These post-mitotic cells displaying chromosomal mosaicism are thought to give rise to cellular variability and diversity, and participate in normal cellular processes such as cell survival, proliferation and protein synthesis (Torres et al., 2007; Yang et al., 2003a,b). Aneuploidy has also been demonstrated in the adult mouse and human brain, albeit with an estimated lower frequency (Rehen et al., 2001, 2005). Early studies reported conflicting data concerning variations in neuronal DNA content, concluding that most neurons were diploid (reviewed by Arendt (2012)). Studies using cytometrybased methods or Fluorescence-Activated Cell Sorting (FACS) suggest that around 9–12% of adult neurons contain more than diploid DNA content ((Rehen et al., 2005; Mosch et al., 2007; Iourov et al., 2009; Fischer et al., 2012; Arendt et al., 2015) – See Table 1) most likely arising as a result of chromosome mis-segregation during mitosis of neural progenitor cells rather than an attempt at cell cycle re-entry (Mosch et al., 2007; Westra et al., 2008; Yang et al., 2003a,b). In contrast, more recent studies using single-cell next-generation sequencing report much lower levels of neuronal aneuploidy in the adult human frontal cortex ((McConnell et al., 2013; Cai et al., 2014; Knouse et al., 2014; van den Bos et al., 2016) see Table 1). One possible explanation for the discrepancy between studies (0.7–11.5% aneuploidy rates detected) is the technical limitations of the methodologies used. In particular, interphase Fluorescence In-situ Hybridization (FISH) has been criticized due to problems with probe hybridization and probe clustering potentially lending itself vulnerable to significant noise and hence false positive data (see (Bakker et al., 2015) for review). Dual color FISH, with probes mapping to the same chromosome, significantly reduces background noise and the rate of false positive signals, providing a more sensitive

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method to study aneuploidy. Cytometry-based methods confer a significant advantage as they allow high throughput (Arendt et al. (2015) screened 400,000–600,000 cells from each of the 16 cases included in the study), although individual chromosomal gains and losses cannot be detected and hence sensitivity is low. In contrast, singlecell sequencing has high resolution although throughput is low (in general studies assess 100’s rather than 100,000’s of cells) due to the expense of this technique (see (Bakker et al., 2015) for review). There are agreed technical limitations (Box 1) and variations (Table 1) using all methodologies and it is likely that a combination of techniques will provide the definitive answer regarding the true rate of aneuploidy in brain aging and neurodegeneration.

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ANEUPLOIDY DURING NORMAL AGING

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The rise in trisomies with increased maternal age has provided long-standing confirmation that age and chromosomal abnormalities are closely linked. Such observations have been confirmed in studies demonstrating an increase in aneuploidy in fibroblasts taken at various ages from the same donors (Mukherjee and Thomas, 1997) and studies of lymphocyte chromosomes (Moorhead and Heyman, 1983; Buckton et al., 1983; Bolognesi et al., 1999) and buccal cells (Thomas and Fenech, 2008). Animal models deficient in spindle assembly checkpoint proteins, such as BubR1, provide confirmation that progeroid features, including shortened lifespan, impaired wound healing and cataracts, occur as a consequence of aneuploidy (Baker et al., 2004). Whether aneuploidy increases with age in human brain tissue is less well studied. A relatively recent study by Fischer and colleagues quantified the frequency of neurons with a more than diploid DNA content from various cortical regions in 18 cases ranging from 31 to 88 years (Fischer et al., 2012). The data demonstrate a significant decline in DNA content with increasing age, which equated to a 21% difference between individuals who were younger or older than 60 years. The authors postulate that variations in DNA content may compromise neuronal viability with age and render individuals more susceptible to neurodegeneration (Fischer et al., 2012). A major criticism of the study is that some age groups were represented by only three cases, so the findings should be interpreted with caution. Westra and colleagues assessed DNA content variation using Flow Cytometry (FCM), FACS, FISH, southern blotting and quantitative polymerase chain reaction in brain tissue from 25 individuals ranging in age from 35 to 93 years and did not identify any change in frontal or cerebellar cortex DNA content during the aging process (Westra et al., 2010). Other studies have identified constitutional aneuploidy in individuals of various ages (2–86 years) but the numbers of cases analyzed is too low (6 cases) to rigorously address the relationship between aneuploidy and advancing age ((Rehen et al., 2005), see Table 1). Single-cell sequencing experiments using aged individuals (48–93 years (McConnell et al., 2013; Knouse et al., 2014)) did not show higher rates of aneuploidy compared to younger

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C. E. Shepherd et al. / Neuroscience xxx (2018) xxx–xxx Table 1. Aneuploidy in the normal human brain and during aging Aneuploidy

Age (yrs)

Cell types

Brain regions

Technique/ chromosomes tested

References

No DCV

73 ± 5

Substantia nigra

FISH Chr 18 and X

0.5–1% aneuploidy per chromosome Greater tetraploidy in NeuNnegative cells 10% DCV in controls

Young adults

Dopaminergic neurons Neurons & Glia

Cerebellum

FISH 6, 21

Hoglinger et al. (2007) Westra et al. (2008)

71.7 ± 10.3

Neurons

Entorhinal cortex

10% overall rate of aneuploidy in controls 10% constituent neuronal DCV with no regional difference 9.6% neuronal DCV with strong regional variation – entorhinal > temporal > frontal > parietal > occipital 4% aneuploidy. No difference between neurons and glia. Regional and age-associated changes were not robustly addressed (N = 6) 11.5% DCV. No significant regional differences. Decline in DCV with age. 4% increase in neuronal DCV in frontal cortex but no change with age. 2.7% aneuploidy

79 ± 5

Neurons & Glia

Frontal cortex

71.7 ± 10.3

Neurons

Entorhinal cortex Occipital cortex

Chr 17 SBC, CISH, FISH FISH, ICS-MCB for 1,11, 17, 21, X SBC, CISH, PCR of Alu repeats

Arendt et al. (2010) Iourov et al. (2009) Mosch et al. (2007)

75.8 ± 8.2

Neurons

Frontal, temporal, parietal, entorhinal, occipital cortices

SBC

Arendt et al. (2015)

Range 2–86

Neurons & Glia

Frontal cortex Occipital cortex hippocampus

FISH for chromosome 21, FACS

Rehen et al. (2005)

Range 31–88

Neurons

Frontal, entorhinal, temporal, occipital, parietal

SBC

Fischer et al. (2012)

Average 79.1 (range 35–95)

Neurons, glia & lymphocytes

Frontal cortex Cerebellum

FCM, FACS, FISH

Westra et al. (2010)

20–26

Neurons N = 110

Frontal cortex

Single-cell NGS

2.2% aneuploidy

48–70

Neurons N = 89

Frontal cortex

Single-cell NGS

0.7% aneuploidy in neurons. No glial aneuploidy 4% aneuploidy

80

Neurons N = 589 Non-neuronal cells N = 63 Neurons N = 97

Frontal cortex

Single-cell NGS

McConnell et al. (2013) Knouse et al. (2014) van den Bos et al. (2016)

Cortex

Single-cell NGS

Adult

Cai et al. (2014)

FISH – fluorescent in situ hybridization; CISH – chromogenic in-situ hybridization; SBC – slide-based cytometry; FCM – flow cytometry; FACS – fluorescence-activated cell sorting; ICS-MCB – interphase chromosome-specific multicolor banding; PCR – polymerase chain reaction; NGS – Next-Generation Sequencing.

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adults (20–26 years (McConnell et al., 2013)), although the relationship between aneuploidy and aging has not been directly examined in these experiments.

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ANEUPLOIDY AND NEURODEGENERATION

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The relationship between Down syndrome and Alzheimer’s disease (AD) was proposed over 20 years ago (Potter, 1991) and provided the groundwork for research into the link between aneuploidy and neurodegeneration. Indeed, it is known that individuals with Down Syndrome develop pathology that is indistinguishable from AD by the 3rd or 4th decade of life, most likely due to the increased amyloid-beta (Ab) production due to the extra copy of the amyloid precursor protein on chromosome 21. Mothers of Down syndrome children also have an increased likelihood of AD, indicating a possible link

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between these disorders and DNA abnormalities (Migliore et al., 1999). A relationship between aneuploidy and AD has since been substantiated by numerous studies showing a role for aneuploidy, particularly hyperploidy, early in both familial and sporadic AD (Arendt et al., 2010, 2015; Boeras et al., 2008; Bushman et al., 2015; Potter, 1991; Geller and Potter, 1999; Chen et al., 2010; Iourov et al., 2009; Migliore et al., 1999; Mosch et al., 2007; Vincent et al., 1996; Yang et al., 2001; Yang et al., 2003a,b; Yurov et al., 2014) (see Table 2). Previous studies have also demonstrated a 1.5-fold increase in chromosome 21 (encoding the amyloid precursor protein) and a 1.2-fold increase in chromosome 17 (encoding the tau protein) in AD buccal cells, compared with age-matched controls, although no difference in aneuploidy in hippocampal neurons was observed (Thomas and Fenech,

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Box 1. Description of the advantages and technical limitations of the techniques used to detect aneuploidy Description

Advantages

Disadvantages

Fluorescent in situ hybridization

Visualization of chromosome loss or gains through hybridization of chromosome-specific probes

Inexpensive. Able to detect aneuploidy, inversions, CNVs, translocation. Ability to analyze a large number of cells. Ability to analyze tissue architecture

Interphase chromosomespecific multicolor banding Cytometry

Hybridization of multiple probes on one chromosome Fluorescent labeling of all the DNA in a fluid or slide-based cell population and quantitation using scanning or flow cytometry Generation of sequencing libraries from single cells, followed by deep or wholegenome sequencing

Greater specificity than FISH.

Problems with probe hybridization leading to misrepresentation of aneuploidy rates. Limited numbers of chromosomes able to be analyzed. Single-chromosome analysis Individual chromosome copy number gains or losses cannot be detected

Next-Generation Sequencing

196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234

2008). Other studies analyzing neuronal nuclei in postmortem brain tissue did not detect evidence of aneuploidy in the AD brain (Westra et al., 2009; van den Bos et al., 2016), although other studies have shown that cortical hyperploid neurons increase considerably in preclinical AD, decreasing to normal levels as the disease progresses because of their selective death (Arendt et al., 2010, 2015). Hyperploidy has been estimated to account for almost 90% of the cell loss seen in AD (Arendt et al., 2010) with cell proliferation proteins, including cdk4, cdc2, PCNA and Ki67, reported to be increased in AD brain (Nagy et al., 1997; Busser et al., 1998; Smith et al., 1999; Dranovsky et al., 2001; Hoozemans et al., 2002; Pei et al., 2002; Johansson et al., 2003). Cell cycle reentry has been proposed as the root cause of neuronal cell loss at all stages of AD (Yang et al., 2003a,b). Indeed, cell cycle markers have been demonstrated in the brains of individuals with mild cognitive impairment (Keeney et al., 2012), and studies show progression in association with the dementia process (Katsel et al., 2013). A two to three fold increase in DNA content variation has been demonstrated in AD patients compared to elderly controls, with more hyperploidy in AD patients between the age of 60– 70 years than those between 80 and 90 years (Arendt et al., 2015). In contrast, more recent studies using single-cell sequencing in cells from the frontal cortex of individuals with clinical AD ranging from 64–93 years at death did not detect any significant aneuploidy (van den Bos et al., 2016). This study now requires replication in a larger cohort using a combination of sensitive and specific methodologies that are capable of detecting aneuploidy. DNA alterations have also been detected in other neurodegenerative diseases, including Lewy body disease (Hoglinger et al., 2007). Lewy body disease is characterized at post-mortem by the presence of insoluble, neuronal aggregates of the alpha-synuclein protein known as Lewy bodies. These inclusions appear to spread between brain regions in a stereotypic manner, starting in the dorsal motor nucleus of the vagus nerve

High throughput. Does not rely on probe hybridization

Ability to analyze all chromosomes. No effects of variable probe hybridization

Low throughput. Expensive. Potential amplification bias and PCR saturation.

and spreading in a caudal to rostral direction to the pons, substantia nigra, limbic system and eventually to the neocortex (Braak et al., 2003). Stage IV Lewy bodies are found in the substantia nigra where they are found in association with significant neuronal loss in Parkinson’s disease. Alpha-synuclein aggregates also appear in neurites (called Lewy neurites) and glia and current data suggest a possible ‘spread’ of pathology between cells in a prion-like manner (Brundin et al., 2016). Using in situ hybridization methods Hoglinger and colleagues reported duplication of chromosomes 18 and X in 3–4% of remaining substantia nigra dopamine neurons in Parkinson’s disease (Hoglinger et al., 2007). Unfortunately, only a small number of neurons (232) were sampled for analysis but comparative data from a mouse model indicated that hyperploidy preceded neuronal death and is therefore likely to play an important role in the Lewy body disease process (Hoglinger et al., 2007). Analysis of ribosomal DNA content in post-mortem parietal cortex from individuals with Lewy body disease and healthy controls also supports a role for hyperploidy in the Lewy body disease process (Hallgren et al., 2014). Our more recent study investigating aneuploidy in Lewy body diseases using FCM has shown an increase in DNA content (35–40% over control levels) (Yang et al., 2015), consistent with previous studies demonstrating hyperploidy in a small proportion of substantia nigra neurons (Hoglinger et al., 2007). There was a trend for a positive correlation between aneuploidy and neuronal cell loss in the substantia nigra of Lewy body disease cases, supporting the concept that hyperploidy might contribute to the loss of pigmented neurons (Yang et al., 2015). There is additional evidence of increased cell cycle activity in patients with Lewy body disease. In particular, the cell cycle regulator, cyclin B is found in Lewy bodies (Nakamura et al., 1997; Lee et al., 2003) and cell models overexpressing a-synuclein undergo proliferation and accumulation of cyclin B (Lee et al., 2003). However, our more recent studies of aneuploidy in multiple system atrophy suggest

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C. E. Shepherd et al. / Neuroscience xxx (2018) xxx–xxx Table 2. Aneuploidy in neurodegeneration Aneuploidy

Cases & Age (yrs)

Cell types

Brain regions

Technique/chromosomes tested

References

No change from controls

Young controls 22 ± 2 Old controls 69 ± 3 AD 58–93 Controls 71.7 ± 10.3 AD 76.3 ± 8.1 preclinical AD 73.6 ± 6.8 Control 75.8 ± 8.2 AD 75.1 ± 8.5

Neurons & Glia

Hippocampus

FISH 17 & 21

Thomas and Fenech (2008)

Neurons

Entorhinal cortex

Chr 17 SBC, CISH, FISH

Arendt et al. (2010)

Neurons

SBC & CISH

Arendt et al. (2015)

Control 66 AD 80

Neurons & Glia

Frontal, entorhinal, temporal, occipital, parietal Frontal cortex Hippocampus

FACS, FISH

Westra et al. (2009)

Controls (69–82 yrs) AD (69–88 years)

Neurons & Glia

Prefrontal cortex Hippocampus

ICS-MCB, FISH chr 1,7,11,16,17,18, X

Yurov et al. (2014)

AD 79 ± 11 Control 72 ± 19 AD 82.1 Control 79.5

Neurons

Cerebellar dentate

FISH Chr 11

Neurons & Glia

Prefrontal cortex Cerebellum,

FACS FISH & qPCR chr 21

Chen et al. (2010) Bushman et al. (2015)

DLB 80 ± 8 PD 77 ± 7 Controls 77 ± 11 Controls 72 ± 10.3 AD 76 ± 8 AD 80 ± 5 Controls 79 ± 5 Control 75.5 AD 79.7

Neurons & Glia

Substantia nigra Anterior cingulate cortex Hippocampal CA1 Entorhinal cortex Occipital cortex Frontal cortex

FCM

Yang et al. (2015)

SBC, CISH, PCR of Alu repeats FISH, ICS-MCB for 1, 7, 11, 13, 14, 17, 18, 21, X, Y FISH Chr 11, 18 & 21

Mosch et al. (2007) Iourov et al. (2009) Yang et al. (2001)

FISH chr X & 18

Hoglinger et al. (2007) van den Bos et al. (2016)

30–35% increase in neuronal aneuploidy in preclinical AD 2–3-fold increase in AD

No change in AD Tetraploidy only seen in glia 2-fold increase in X chromosome aneuploidy in AD. More in hippocampus 4–23% increase in Chr 11 aneuploidy in AD 8% increase in neuronal DNA content not related to Chr 21. 9% increase in neuronal DCV compared to glia 35–40% increase in neuronal aneuploidy 10–17% increase compared to controls 10-fold increase in chr 21 aneuploidy in AD 3.7% increase in AD

Neurons Neurons & Glia Neurons

2.9–4.3% increase compared to controls 0.6% aneuploidy in neurons No glial aneuploidy

PD

Neurons

AD

No aneuploidy

MSA

Neurons N = 893 Nonneuronal N = 51 Neurons & Glia

Hippocampus Basal nucleus of Meynert Substantia nigra Frontal cortex

Single-cell NGS

Pons

FCM

Yang et al. (2017)

FISH – fluorescent in situ hybridization; CISH – chromogenic in-situ hybridization; SBC – slide-based cytometry; FCM – flow cytometry; FACS – fluorescence-activated cell sorting; ICS-MCB – interphase chromosome-specific multicolor banding; PCR – polymerase chain reaction; NGS – Next-Generation Sequencing; AD – Alzheimer’s disease; DLB – Dementia with Lewy body; PD – Parkinson’s disease; MSA – Multiple System Atrophy.

274 275 276 277 278 279 280 281

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that aneuploidy is not a universal feature across a-synucleinopathies (Yang et al., 2017). Further, no association was observed between cell loss and aneuploidy in other variably affected regions (anterior cingulate cortex and hippocampus) in Lewy body diseases (Yang et al., 2015), supporting the notion that region-specific differences in aneuploidy occur in different neurodegenerative conditions.

ARE DIFFERENT BRAIN REGIONS MORE SUSCEPTIBLE TO ANEUPLOIDY? Alzheimer-type pathologies demonstrate a regional spread throughout the brain (Braak and Braak, 1991;

Thal et al., 2002; Montine et al., 2012). The spread of such changes is thought to reflect regional susceptibilities to disease processes. The cause of these underlying susceptibilities is not yet known, although aneuploidy may represent a potential mechanism. Studies in normal brain tissue have previously reported uniform neuronal DNA content across different cortical regions (Mosch et al., 2007; Fischer et al., 2012) as well as uniform numbers of chromosome 21 in cortical (frontal and occipital) and hippocampal neurons (Rehen et al., 2005). However, others have suggested that neuronal DNA content varies between tissues with differing neuroembryological origins, with increased aneuploidy observed in the frontal cortex compared to the cerebellum (Westra et al., 2010;

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Bushman et al., 2015). Indeed, previous studies of mouse tissue taken from the brain (cerebral cortex and cerebellum) and spleen revealed chromosome- and region-specific aneuploidy that was restricted to the cerebral cortex during aging (Faggioli et al., 2012). These studies are more consistent with results from AD brain tissue demonstrating the average rate of chromosome 21 aneuploidy is increased in hippocampus > cortex > cere bellum in the disease process (Westra et al., 2010; Yurov et al., 2014; Bushman et al., 2015), suggesting that regional aneuploidy may underlie vulnerability to neurodegeneration. This is consistent with a more recent study assessing aneuploidy using slide-based cytometry in five cortical regions from control and AD brain tissue (Arendt et al., 2015). The findings demonstrate noticeable regional differences in DNA content entorhinal > temporal > frontal > parietal > occipital in both control (Montine et al., 2012) and AD cases (Arendt et al., 2015). The observation that identical regions show DNA content variation in the normal aged brain and in AD indicates that similar mechanisms may be at play. The mechanisms that cause genetic mosaicism are currently unclear, although the data demonstrate that genetic heterogeneity underlies vulnerability to AD pathology. The fact that the regional variations were much larger in individuals with AD (10.4% in the occipital cortex compared to 34.7% in the entorhinal cortex) compared to elderly controls (7% in the occipital cortex compared to 12% in the entorhinal cortex) suggests that additional insults may be at play in AD. In contrast to AD, our recent studies of DNA content variation in Lewy body diseases demonstrated no significant regional difference in neuronal aneuploidy in variably affected regions at end-stage disease (substantia nigra, hippocampus and anterior cingulate cortex) (Yang et al., 2015), although region-specific increases in glial aneuploidy were observed, suggesting that cellular variations may also play an important role in this process.

ARE NEURONS OR GLIA MORE SUSCEPTIBLE TO ANEUPLOIDY? Previous studies using a combination of in situ hybridization and cytometry have demonstrated aneuploidy in glia (Rehen et al., 2005; Mosch et al., 2007; Westra et al., 2008; Iourov et al., 2009). Some studies suggest that glial aneuploidy occurs at a comparable rate to that of neuronal cells (Rehen et al., 2005; Iourov et al., 2009) while others suggest that glial aneuploidy is greater (Westra et al., 2008, 2009). Answering this question is difficult using low-resolution techniques such as FISH, as incident rates of aneuploidy have been shown to vary among different chromosomes in both cell types (Rehen et al., 2005; Iourov et al., 2009; Faggioli et al., 2011, 2012). More recent studies using whole-cell sequencing techniques did not detect non-neuronal aneuploidy in the human frontal cortex (van den Bos et al., 2016). While our recent studies support a role for aneuploidy in neurons and glia in brain tissue from Lewy body diseases using FCM, only the large neurons showed a consistent increase in DNA content in the differentially

affected brain regions (Yang et al., 2015). Increased neuronal aneuploidy has been proposed to contribute to neuronal loss in neurodegenerative diseases such as AD (Arendt et al., 2010), whereas changes in human glial cell DNA content are thought to cause enlargement and growth of astroglia, as occurs during astrogliosis (Dalrymple et al., 1994). These findings are consistent with our studies in the substantia nigra of individuals with Lewy body disease, whereby increases in glial aneuploidy showed a negative association with cell density, suggesting that a proportion of non-neuronal cells in this region increase their DNA content to increase their cell number (Yang et al., 2015). Most studies assessing neuronal and non-neuronal aneuploidy have used NeuN as a differentiating marker, although NeuN does not detect all neurons (Duan et al., 2016) and no distinction has been made between microglia and astrocytes or indeed other non-neuronal cell types. Indeed, endothelial cells have also been shown to exhibit DNA damage and initiation of cell cycle reentry in the frontal and temporal cortex at the earliest stages of AD pathology (Garwood et al., 2014), indicating that multiple cell types are capable of undergoing such changes.

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Despite showing variations in DNA content, aneuploid neurons in healthy brain tissue do not express markers of the cell cycle such as cyclin B1, thereby suggesting that these chromosomal abnormalities arise from missegregation in neuronal progenitor cells (Yang et al., 2003a,b). In contrast, a proportion of aneuploid neurons in AD express cell proliferation markers (Mosch et al., 2007), indicating that aneuploidy in AD is due to attempts at cell cycle reentry and DNA synthesis. Unfortunately, attempts at cell division by a mature neuron are considered fatal (Herrup and Busser, 1995) making the identification of the factor/s that cause neurons to enter the cell cycle crucial. The DNA damage theory posits that ineffective repair of DNA damage results in faulty gene expression, cell dysfunction and eventual cell death via reentry into the cell cycle (Copani et al., 2001) resulting in reduced rates of aneuploidy observed at end stage disease (Arendt et al., 2010). The mechanisms that cause DNA damage are manifold and include oxidative stress, abnormal protein production and deposition, and hormone changes to name a few (Kruman et al., 2004; Kuan et al., 2004; Rashidian et al., 2007; Atwood and Bowen, 2015). Knowledge from Down syndrome individuals would suggest that aneuploidy drives the pathological protein changes that underlie AD (Petronis, 1999) and chromosome 21 aneuploidy has certainly been reported in AD (Iourov et al., 2009). However, a large number of in vitro studies suggest that Ab itself is capable of driving aneuploidy. Indeed, rapid and robust chromosome mis-segregation in cultured primary human mammary epithelial cells occurs with synthetic Ab peptide treatment leading to hyperploidy (Granic et al., 2010), and excess Ab is thought to deregulate the mechanical forces that

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govern the spindle formation leading to the generation of defective mitotic structures (Borysov et al., 2011) and possibly aneuploidy. In addition, reduction in the levels of Ab in a transgenic mouse model has been shown to delay the initiation of neuronal cell cycle events, and elimination of b-secretase activity blocks the events (Varvel et al., 2008). Our recent studies assessing the relationship between aneuploidy, protein deposition and neuronal loss in variably affected regions in Lewy body disease brain tissue have demonstrated the degree of neuronal DNA content is closely related to the AD proteins (Ab and tau), but not a-synuclein Lewy bodies, in the anterior cingulate cortex and hippocampus (Yang et al., 2015). These studies support in vitro data demonstrating an important relationship between Ab and aneuploidy, and provide novel data to suggest that these changes are specifically associated with AD pathologies. A previous study by Chen and colleagues (Chen et al., 2010) would suggest that aneuploidy is a precursor to these pathologies as they observed markers of cell cycle reentry in the cerebellar dentate neurons in the absence of tau and Ab. Indeed, cell cycle events have been shown to be present 6 months before the onset of AD pathology in transgenic mice (Yang et al., 2006). Hippocampal kainic acid-evoked neuronal cell death has also been shown to cause an increase in G1 and S phase proteins, and tau and Ab levels peaked immediately after this event (Hernandez-Ortega et al., 2007), indicating that protein changes occur as a downstream consequence of the DNA damage response. What is not clear is whether changes in the soluble forms of these proteins precede aneuploidy, although in vitro studies have shown that oligomeric, but not monomeric, Ab induced DNA synthesis in dissociated cortical neurons (Varvel et al., 2008), and exposure of cultured wild-type neurons to Ab oligomers have been shown to initiate cell cycle re-entry (Seward et al., 2013). Of interest, it has been shown that Ab oligomers fail to induce cell cycle re-entry in tau knockout neurons (Seward et al., 2013), indicating that Ab may also cooperate with tau in this process. Given that Ab proteolysis can both respond to and be driven by senescenceassociated signaling (Hunter et al., 2013), it is likely that both mechanisms may operate in a positive feedback loop.

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The current data demonstrate controversy in the field regarding a role for neuronal aneuploidy in AD. Methods for analyzing aneuploidy such as FISH have been heavily criticized due to significant noise and recent studies have largely focused on high-resolution singlecell sequencing methods. However, throughput is still low using this technique and variations are still evident using all methodologies, suggesting additional variables are at play. Indeed, the data suggest that individual, regional, cellular and disease-specific variations in aneuploidy may be more closely associated with vulnerability to AD pathology and cellular degeneration. Whether aneuploidy underlies normal aging is not clear, although there is compelling evidence for DNA damage

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during the aging process, suggesting the presence of genomic deficits. Larger scale studies using a combination of techniques and addressing regional and cellular variation and associations with pathology and cell loss are now required to determine whether genomic deficits are significant factors in either aging or neurodegeneration.

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FUNDING

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GMH holds a senior principal research fellowship (#1079679) and a Dementia Research Team Grant (#1095127) from the National Health and Medical Research Council of Australia.

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CONFLICTS OF INTEREST

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None of the authors have a financial or personal conflict of interest to declare.

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CONTRIBUTIONS

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Dr Claire Shepherd completed the first draft of the review. Professor Glenda Halliday and Dr Yue Yang provided significant intellectual input to the article.

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REFERENCES

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(Received 10 May 2017, Accepted 23 January 2018) (Available online xxxx)

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