Longitudinal regional brain volume changes quantified in normal aging and Alzheimer's APP × PS1 mice using MRI

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a v a i l a b l e a t w w w. s c i e n c e d i r e c t . c o m

w w w. e l s e v i e r. c o m / l o c a t e / b r a i n r e s

Research Report

Longitudinal regional brain volume changes quantified in normal aging and Alzheimer's APP × PS1 mice using MRI Satheesh Maheswaran a , Hervé Barjat b,1 , Daniel Rueckert a , Simon T. Bate c , David R. Howlett b,2 , Lorna Tilling b , Sean C. Smart b,3 , Andreas Pohlmann b,4 , Jill C. Richardson b , Thomas Hartkens d , Derek L.G. Hill d , Neil Upton b , Jo V. Hajnal e , Michael F. James b,⁎,5 a

Department of Computing, Imperial College, London, UK Neurology & Gastrointestinal Centre of Excellence for Drug Discovery, GlaxoSmithKline, Harlow, UK c Statistical Sciences, GlaxoSmithKline, Harlow, UK d IXICO Ltd, The London Bioscience Innovation Centre, London, UK e Imaging Sciences Department, MRC Clinical sciences Centre, Imperial College, London, UK b

A R T I C LE I N FO

AB S T R A C T

Article history:

In humans, mutations of amyloid precursor protein (APP) and presenilins (PS) 1 and 2 are

Accepted 22 February 2009

associated with amyloid deposition, brain structural change and cognitive decline, like in

Available online 9 March 2009

Alzheimer's disease (AD). Mice expressing these proteins have illuminated neurodegenerative disease processes but, unlike in humans, quantitative imaging has

Keywords:

been little used to systematically determine their effects, or those of normal aging, on brain

Aging

structure in vivo. Accordingly, we investigated wildtype (WT) and TASTPM mice

Alzheimer's disease

(expressing human APP695(K595N,

Structural MRI

global and local image registration, allied to a standard digital atlas, provided pairwise

Transgenic

segmentation of 13 brain regions. We found the mature mouse brain, unlike in humans,

APP/PS1

enlarges significantly from 6–14 months old (WT 3.8 ± 1.7%, mean ± SD, P < 0.0001).

TASTPM

Significant changes were also seen in other WT brain regions, providing an anatomical

M596L) × PS1(M146V))

longitudinally using MRI. Automated

benchmark for comparing other mouse strains and models of brain disorder. In TASTPM, progressive amyloidosis and astrogliosis, detected immunohistochemically, reflected even larger whole brain changes (5.1 ± 1.4%, P < 0.0001, transgene × age interaction P = 0.0311). Normalising regional volumes to whole brain measurements revealed significant, prolonged, WT-TASTPM volume differences, suggesting transgene effects establish at

⁎ Corresponding author. Imaging, Immuno-Inflammation CEDD, GlaxoSmithKline, New Frontiers Park (North), Third Avenue, Harlow, Essex CM19 5AD, UK. E-mail address: [email protected] (M.F. James). Abbreviations: AD, Alzheimer's disease; APP, amyloid precursor protein; GFAP, glial fibrillary acid protein; LONI, Laboratory of NeuroImaging at University of California, Los Angeles; mo, months old; TASTPM, Thy-1 APP695 Swedish (K595N, M596L)×Thy-1 PS1 (M146V); WT, wildtype 1 Present address: The Imaging Centre, Department of Enabling Capabilities and Sciences, AstraZeneca, Alderley Park, Cheshire, UK. 2 Present address: Wolfson Centre for Age Related Diseases, King's College London, St Thomas' Street, London, UK. 3 Present address: Department of Radiation Oncology and Biology, University of Oxford, Churchill Hospital, Oxford, UK. 4 Present address: Academic DPU, GlaxoSmithKline R&D Ltd, CRUK Cambridge Research Institute, Cambridge, UK. 5 Present address: The Nineveh Charitable Trust, (www.ninevehtrust.org.uk), UK. 0006-8993/$ – see front matter © 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.brainres.2009.02.045

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<6 months old of age in most regions. As in humans, gray matter-rich regions decline with age (e.g. thalamus, cerebral cortex and caudoputamen); ventricles and white matter (corpus callosum, corticospinal tract, fornix system) increase; in TASTPMs such trends often varied significantly from WT (especially hippocampus). The pervasive, age-related structural changes between WT and AD transgenic mice (and mouse and human) suggest subtle but fundamental species differences and AD transgene effects. © 2009 Elsevier B.V. All rights reserved.

1.

Introduction

Much understanding of the effects on human brain structure of normal aging (Bartzokis et al., 2001; Courchesne et al., 2000; Giedd et al., 1999) and Alzheimer's disease (AD) (e.g. Thompson et al., 2003; Whitwell et al., 2007; and references therein) has come from non-invasive imaging. To gain a direct comparison with the human condition, these methods have begun to be applied to transgenic animals in vivo (for review: Jack et al., 2007) detecting, for example, cerebral metabolic (von Kienlin et al., 2005) and structural (Bock et al., 2006; Delatour et al., 2006; Lerch et al., 2008) changes or impairments. A central hypothesis of AD is that altered processing of neuronal amyloid precursor protein (APP) increases formation of the neurotoxic peptide Aβ1–42, which is deposited as plaques in the brain parenchyma. Associated with the amyloid deposition is neurofibrillary tangle formation, which together are thought to lead to progressive neuronal loss (Masters et al., 2006), cognitive decline (Blennow et al., 2006) and brain atrophy. A small proportion of AD patients express mutations in the APP and presenilin (PS1 and PS2) proteins, or overexpress APP itself (Rovelet-Lecrux et al., 2006). These ‘familial’ AD patients suffer earlier and more rapid amyloid deposition,

brain atrophy and cognitive decline; but their brain changes, although accelerated, are similar in kind to those occurring in late-onset, ‘sporadic’ AD patients without these genetic abnormalities who form the great majority of cases. To understand better the amyloid hypothesis of AD, many types of transgenic mice have been made. Although differing in their background strain, in the number and type of APP and PS mutations expressed (the transgenes), and the promoters that govern transgene expression, they often lead to abundant amyloid deposition and cognitive deficits (for reviews: Higgins and Jacobsen, 2003; McGowan et al., 2006). A large literature shows that this animal research has provided invaluable insights to understand better the consequences of cerebral amyloid deposition and the effects of amyloid lowering and other potential AD therapies in vivo. In this investigation we explored, more comprehensively than previously attempted, the natural history of structural brain change in wildtype (WT) and Alzheimer's transgenic (TASTPM) mice, by imaging longitudinally. We wanted to better understand how regional brain structure may change in vivo, in mature normal animals. Such measurements provide an anatomical benchmark permitting future comparisons with other models of mouse brain disorder. They also employ

Table 1 – Brain region measurements (mm3), ordered by size, and their variation with age in WT and TASTPM mice in vivo (means ± SD). Brain region

nb Cerebral cortex Midbrain– hindbrain Cerebellum Hippocampal formation Caudoputamen Thalamus Corpus callosum Hypothalamus Basal nuclei Corticospinal tract Fornix system Total ventricle c Whole brain

WT

TASTPM

% whole brain a

6 months 9 months 11 months

14 months

6 months 9 months 11 months

14 months

11 27.0 ± 0.49 18.5 ± 0.19

11 139.1 ± 4.96 95.2 ± 3.48

11 139.4 ± 5.48 97.1 ± 3.43

11 139.2 ± 4.16 99.7 ± 3.91

11 139.0 ± 4.71 99.7 ± 5.51‡

16 141.5 ± 6.80 92.1 ± 5.05

13 144.7 ± 6.00 92.2 ± 6.62

9 145.0 ± 7.59 97.2 ± 5.57

4 150.0 ± 8.39† 100.7 ± 5.71‡

10.1 ± 0.35 4.48 ± 0.07

52.2 ± 2.43 23.1 ± 0.84

52.3 ± 2.32 23.4 ± 0.99

52.9 ± 2.55 23.4 ± 1.90

52.8 ± 2.24 23.2 ± 1.77

54.7 ± 3.33 22.6 ± 1.03

55.3 ± 3.70 23.4 ± 1.27

55.6 ± 3.51 24.5 ± 1.26

57.1 ± 4.17† 25.4 ± 1.50‡

3.99 ± 0.10 2.80 ± 0.04 2.56 ± 0.14 2.44 ± 0.02 1.88 ± 0.04 1.09 ± 0.05

20.6 ± 1.01 14.4 ± 0.46 13.2 ± 0.74 12.6 ± 0.48 9.71 ± 0.43 5.65 ± 0.32

20.5 ± 1.06 14.5 ± 0.57 13.9 ± 0.73 13.0 ± 0.57 10.0 ± 0.47 5.98 ± 0.51

20.6 ± 0.80 14.7 ± 0.41 15.1 ± 1.23 13.3 ± 0.51 10.2 ± 0.40 6.41 ± 0.42

20.6 ± 0.97 14.5 ± 0.96 15.3 ± 1.20‡ 13.3 ± 0.62‡ 10.1 ± 0.43† 6.60 ± 0.38‡

21.3 ± 1.89 15.0 ± 0.57 11.6 ± 0.94 12.1 ± 0.46 9.71 ± 0.75 5.21 ± 0.41

21.1 ± 1.82 15.3 ± 0.72 12.2 ± 0.89 12.4 ± 0.59 10.1 ± 0.72 5.54 ± 0.48

21.3 ± 1.85 15.3 ± 0.67 13.4 ± 0.83 12.8 ± 0.51 10.3 ± 0.59 5.85 ± 0.37

22.0 ± 1.97⁎ 15.7 ± 0.75⁎ 14.6 ± 0.79‡ 13.2 ± 0.44‡ 10.6 ± 0.58‡ 6.22 ± 0.22‡

0.89 ± 0.041 0.17 ± 0.01 100 ± 3.23

4.32 ± 0.38 0.88 ± 0.07 516 ± 16.7

4.86 ± 0.50 0.93 ± 0.06 528 ± 15.8

5.09 ± 0.20 0.97 ± 0.06 535 ± 16.5

5.14 ± 0.26‡ 0.98 ± 0.065‡ 535 ± 17.9‡

4.32 ± 0.38 0.84 ± 0.08 512 ± 23.7

4.75 ± 0.50 0.92 ± 0.10 524 ± 26.9

5.01 ± 0.50 0.98 ± 0.11 534 ± 25.7

5.45 ± 0.77‡ 1.05 ± 0.19‡ 553 ± 32.8‡

Comparison between 6 and 14 month measurements: ⁎P < 0.05, †P < 0.01, ‡P < 0.001 assessed using the linear slope coefficients of the random coefficient model. Anatomical definitions follow the LONI mouse brain atlas nomenclature (Fig. 7). a At 6 months of age. b Group size. c Total ventricle comprises the 3rd, 4th and lateral ventricles.

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Fig. 1 – Longitudinal change (%) of regional and whole brain volumes with age (months) in wildtype (WT) and TASTPM mice. Data are compared with the respective 6 month measurements. Selected representative error bars (paired SDs) are shown. In TASTPMs, all regions increase significantly between 6 and 14 mo; in WTs, the corpus callosum, fornix system, total ventricle and whole brain increased significantly.

methods applicable to human imaging. We also wanted to learn how human mutated APP and PS1 transgene expression may modify this pattern for comparison with the human condition. We also conducted an immunohistochemical investigation, complementing a previous quantitative investigation in TASTPM mice (Howlett et al., 2004), to illustrate how progressive amyloid deposition and the reactive inflammatory response may be related to the structural changes we report.

2.

Results

2.1.

Brain structural changes in wildtype mice

Table 1 shows brain region measurements, arranged in descending order, for the TASTPM and WT mice at 6, 9, 11 and 14 months of age (mo) in vivo. Cerebral cortex accounted for 27.0% of the WT whole brain volume at 6 mo, whereas the total ventricle (comprising the 3rd, 4th and lateral ventricles in the atlas) accounted for 0.17%. Table 1 and Fig. 1 show that the whole brain and a number of brain regions increase significantly with age in WT animals. The

most notable examples are the corticospinal tract (17 ± 4.8% increase calculated on a paired basis over 8 months, P < 0.001 as assessed using the linear slope coefficient), corpus callosum (respectively 16 ± 9.3%, P < 0.001), fornix system (12 ± 3.0%, P < 0.001), total ventricle (11± 3.3%, P < 0.001), hypothalamus (6.1 ± 2.7%, P < 0.001), midbrain–hindbrain (4.7 ± 4.5%, P < 0.001), basal nuclei (4.0± 2.1%, P < 0.01), and whole brain (3.8 ± 1.7%, P < 0.001). Cerebral cortex, cerebellum, hippocampal formation, caudoputamen and thalamus showed little overall change (linear slope coefficient P > 0.05). Fig. 2 (left) shows that the whole brain measurements vary between animals but increase with age in all of them. This figure is representative of the other regions in that the changes in brain volume occur very much in parallel.

2.2. TASTPM mice: in vivo structural changes and comparison with WT mice Similar, but larger, changes were detected in the TASTPM mice (Table 1, Fig. 1). The change with age is highly significant (Tables 1 and 2A) and affects every region including the caudoputamen and thalamus (linear slope coefficient P < 0.05) that altered little in WT mice. The ‘Diff’ column in Table 2A indicates that throughout the time course the thalamus and

Fig. 2 – Longitudinal change in individual whole brain volumes (mm3) with age (days). The effect of age was significant; there was also a significant transgene × age interaction. Filled symbols, DSP4; open symbols, vehicle.

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Table 2 – Probability values, ordered by statistical effect, comparing (A) absolute measurements and (B) volumes relative to the whole brain.

P , TASTPM >, TASTPM region > WT region region; > WT <, region; TASTPM <,
cerebellum were larger in TASTPM than WT mice (transgene effects P = 0.0151 and P = 0.0397 respectively, Table 2A), but the corpus callosum (P < 0.0001), corticospinal tract (P = 0.0002), hypothalamus (P = 0.0028) and midbrain–hindbrain (P = 0.0241) were smaller. The increase in the whole brain was greater in the TASTPM (5.1 ± 1.4%) than WT (3.8 ± 1.7%), appearing to be continuous, whereas in WT mice the brain volume levelled off after 11 mo (transgene × age interaction, P = 0.0311, Table 2A). The fact that in the TASTPM mice the increases were similar and progressive (Fig. 2) indicates that it was unlikely that the greater natural attrition of TASTPM mice skewed the predicted trend. Thus the rank order of regional change (corpus callosum to caudoputamen) is very similar in both strains. While at 6 mo the four mice surviving to 14 mo tended to have larger brains than the whole group (526 ± 26 vs. 512 ± 24 mm3), the difference is not significant (P = 0.17). In absolute terms, all TASTPM brain regions increased significantly (Table 1 and Fig. 1). Of the regions that changed little in WT animals, the hippocampal formation increased in TASTPMs on a paired basis by 11 ± 2.6% over 8 months (vs. 0.3 ± 5.2% in WT mice); this transgene × age interaction was highly significant (P < 0.0001 — Table 2A). A similar, though less strong, difference was observed for cerebral cortex (2.4 ± 2.5% vs. − 0.04 ± 3.2% in WT, P = 0.015). Only the caudoputamen declined (linear slope coefficient P < 0.05), by − 2.8 ± 2.7% (vs. 0.1 ± 4.2% in WT, transgene × age interaction P = 0.0726). Taken together, the results indicate that the WT mouse brain increases in size by a small but highly significant amount between 6 and 14 mo (linear slope coefficient P < 0.001, Table 1), as do some underlying brain regions (P-values in the range [0.001, 0.01]). However in the TASTPM mice the brain increases significantly more (linear slope coefficient P < 0.001, Table 1; transgene × age interaction P = 0.0311, Table 2).

2.3. brain

Fig. 3 shows that, relative to their whole brain measurements, the corpus callosum, fornix system and total ventricle noticeably increase with age in both strains of mice whereas in WTs the thalamus, hippocampal formation, cerebral cortex and caudoputamen appear static or decline slightly. Although the hippocampal formation declines somewhat in WT mice (Fig. 3), it increases relative to the whole brain in TASTPM

Regional measurements normalised to the whole

If the regional volumes change with age in line with the whole brain volume, then dividing the regional volumes by the respective whole brain measurement should stabilise the data and generate a ‘flat line’ pattern.

Fig. 3 – Regional volume change (%) with age (months) relative to the whole brain. Data are expressed as % change compared with the relative measurement at 6 mo. Representative paired SDs are shown.

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(transgene × age interaction P < 0.0001 — Table 2B); inversely, the caudoputamen is larger in TASTPM but occupies progressively less of the whole brain volume compared with the WT (transgene × age interaction P = 0.0092). Table 2B shows that, in general, the statistically significant differences detected in the absolute measurements continue to pertain or are extended. Fig. 4 shows the trends over time (as ratios — region:whole brain), modelled as a linear or quadratic fit, arranged in the same order as Table 2. The regions can be sorted into two main groups according to the effects of aging and the size differences between strains. For example, the thalamus, cere-

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bellum, cerebral cortex and caudoputamen (outlined in blue) are regions which are of significantly greater proportion in TASTPM brain than in WT (transgene effect, P-values in the range [<0.0001, 0.0331]), but they decline in proportion with age (age effect, P < 0.0001), more in TASTPM mice than WT mice (except for cerebellum) (transgene × age interaction, Pvalue range [< 0.0092, 0.0235]). Such changes in the caudoputamen, for example, were not detected using the absolute measurements (compare Tables 2A and B). The total ventricle proportion of the whole brain is the inverse of this pattern, increasing rather than decreasing with age (P < 0.0001), more in TASTPM than WT (P = 0.0025).

Fig. 4 – Regional volume change with age (months) relative to the whole brain. Data are ratios (region:whole brain volume) and modelled as a linear or quadratic fit. Blue graph line, TASTPM; red graph line, WT. Blue border: regions where TASTPM>WT, that decline with age, significantly more in TASTPM than WT (except cerebellum); dashed blue border: change in total ventricle that inverts this pattern; red border: regions where TASTPM
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Fig. 6 – Localisation of activated astrocytes in wildtype (A) and, especially, TASTPM brains (B) at 41 weeks. Sagittal sections: frontal is right; dorsal is up; GFAP staining. Abbreviations: BN, basal nuclei (e.g. globus pallidus); Cb WM, cerebellar white matter; CPu, caudoputamen; DG, dentate gyrus; fCtx, frontal cortex; FS, fornix system; HF, hippocampal formation; MBHB, midbrain–hindbrain; Pir, piriform cortex; Th, thalamus; SN, substantia nigra; for other abbreviations see Fig 5. The pale area in the TASTPM dorsal cortex is a processing artefact.

Conversely, the corpus callosum, corticospinal tract, hypothalamus, midbrain–hindbrain and fornix system (outlined in red in Fig. 4) are smaller in TASTPM as a proportion of the whole brain than in WT mice (transgene effect, P-value range [< 0.0001, 0.044]), they increase with age [< 0.0001, 0.0019], the fornix system increasing more in TASTPM than in WT mice (transgene × age interaction P < 0.0001) (Table 2B). By contrast the hippocampal formation (outlined in black to distinguish it) declines somewhat in WT mice but increases

significantly (linear slope coefficient P < 0.001 — Table 1) relative to the whole brain in TASTPM (transgene × age interaction P < 0.0001 — Table 2B).

2.4.

Immunohistochemical changes in WT and TASTPM

Figs. 5 and 6 show that there are major inflammatory changes throughout the forebrain of TASTPM compared with WT mice. These changes increase with age and appear linked to amyloid

Fig. 5 – Representative immunohistochemistry (haemotoxylin counterstain) of WT and TASTPM mouse brain showing the advance of pathology with age. Sections are sagittal, frontal cortex is rightwards, dorsal cortex is uppermost; A–J include the cortex and hippocampus; B–D are comparably aligned, as are E–G and H–J. Insets in H–J are shown in K–M; N–P include cerebellum. Arrows indicate: (C) some GFAP staining in the 24 mo WT corpus callosum and hippocampus, but (D) widespread astrocytosis in 14 mo TASTPM; (L, M) increasing stellate microgliosis from 6–14 mo in TASTPM; (M, green arrow) a plaque deposit apparently replacing DG neuronal cell bodies; (N) absence of Aβ from TASTPM cerebellum apart from an isolated blood vessel; (O, P) GFAP staining in cerebellar white matter in both 6 mo WT and TASTPM. Abbreviations: APP, amyloid precursor protein; CA1, CA3, fields of the hippocampus; cc, corpus callosum; CCtx, cerebral cortex; DG, dentate gyrus; GFAP, glial fibrillary acid protein. Scale bars A–D 200 μm, E–G 400 μm, H–J 200 μm, K 50 μm, L 25 μm, M 50 μm, N 400 μm, O–P 50 μm.

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deposition. Separately, a more limited age-related astrogliosis also develops in other anatomical regions, especially white matter, that appears common to both WT and TASTPM mice. In WT mice no full-length APP is detectable, even at 24 mo (Fig. 5A), whereas there is abundant cellular APP in TASTPM neurons from an early age (Fig. 5B). The expressed full-length APP gives rise to increasing levels of extracellular Aβ42 deposition (Figs. 5E–G), appearing first at about 3–4 mo. Aβ42 deposition is associated with increased inflammation, observed as considerable astrogliosis in the cerebral cortex at 9–14 mo (detected using GFAP expression) (Fig. 5D, Fig. 6) that is absent from even 24 mo WT mice (Fig. 5C). Figs. 5B–D are comparably aligned, so the staining palor of the dorsal cortex in Fig. 5C contrasts clearly with the considerable staining evident in Fig. 5D. In TASTPM stellate microgliosis also appears (detected using iba-1 expression — Figs. 5I–J, insets shown in L–M) from about the age of 5–6 mo where plaque is also increasingly deposited, but more sparsely than the widespread astrogliosis. These inflammatory changes are absent from the hippocampal formation and cerebral cortex of WT mice (Figs. 5H, K). The abundance and widespread distribution of amyloid (Figs. 5F–G), and of astrocytes (Fig. 6) in TASTPM mice by 9– 14 mo strongly suggest a space-occupying effect unless a compensatory loss of the underlying tissues was present. In WT brain activated astroglia appear to increase in number with age, but this increase appears to be limited to areas of axonal bundling and white matter (e.g. corpus callosum, the CA1 and CA3 fields of the hippocampus and the globus pallidus region of the basal nuclei (Fig. 5C, Fig. 6). As in TASTPM, astroglia occur also in the internal and external capsules, the dorsomedial hypothalamic nucleus and the lateral habenula (not shown). This more anatomically-limited astrogliosis perhaps also suggests a space-occupying effect, common to both the WT and TASTPM brains. It seems to occur from an earlier age in TASTPM compared with WT (compare Figs. 5C and D in 24 mo WT and 14 mo TASTPM respectively). By contrast, activated stellate microglia are only occasionally detected in the WT brain at any age. The cerebellum, alone, fails to exhibit significant fulllength APP expression in TASTPM. Aβ deposition appears limited to isolated cerebellar blood vessels (Fig. 5N) despite its abundance elsewhere. However, activated astrocytes are found in cerebellar white matter, in both WT (Fig. 5O) and TASTPM (Fig. 5P) at 6 mo, and in older animals (Fig. 6). Activated microglial cells are identifiable only sparsely in WT and TASTPM cerebellar white matter.

3.

Discussion

This investigation shows that serial MRI of the mouse brain, allied to automated global and local image registration and anatomical labelling techniques, can detect subtle but highly significant local changes in brain structure with normal aging and with Alzheimer's gene expression. Some of the structural changes we detected were unexpected. For example: 1) in mature WT animals (from 6 mo onwards), unlike humans, the brain and some of its regions appear to progressively and significantly increase in size as

they age; 2) the TASTPM brain and its component regions actually grow significantly more than the WT (despite, or possibly because of, the presence of progressive, abundant amyloid deposition and astrogliosis during the time course studied — Figs. 5 and 6); whereas, 3) in the context of the amyloid hypothesis of Alzheimer's disease, the amyloidosis and gliosis observed might be expected to result in an atrophic phenotype.

3.1. Brain structural changes in wildtype mice — comparison with human We observed significant, progressive, whole brain and regional volume increases (including the ventricles) in mature wildtype mice, levelling off at ~ 11 mo. By contrast in humans brain growth plateaus early in maturity, in the mid teens (Courchesne et al., 2000; Giedd et al., 1999), followed by a prolonged period of stability before a very slow decline in later life (Bartzokis et al., 2001; Giedd et al., 1999). Post mortem human studies also have found the thalamus and striatum to decline with age (Haug, 1987). Unlike in humans, growth plate closure is long delayed in rodents (Kilborn et al., 2002). The synchondroses of the neurocranium permit skull enlargement (Jolly and Moore, 1975; Lobe et al., 2006), especially the basisphenoid, basioccipital, presphenoid and supraoccipital bones, up to 60 days of age at least (Vilmann, 1969). But there appears to be no literature on neurocranial change in the mature normal mouse. Assuming the rodent neurocranium can expand in maturity to accommodate brain growth explains how the modestly increased brain volume in the WT mice (3.8%) could occur in the presence of increasing ventricular volume: if the mouse brain were to exist within a rigid box post maturity, as is the case in humans, any uncompensated increase in regional tissue volume should result in a balanced reduction in CSF and/or other tissue volume, which was not observed. Thus, in thinking about how transgenic mice may model human disease at the macroscopic level, natural brain and skull growth may be an underlying ontological feature that must be taken into account. The brain regions change independently of the whole brain and thus normalising the component regional volumes to the whole brain measurement helps to better understand their relative trajectories (Figs. 3 and 4). In humans there is a pattern of progressive, maturity-onset, relative gray matter loss, but white matter and ventricular gain with aging (Bartzokis et al., 2001; Giedd et al., 1999). The ventricles gradually increase from the 4th decade; the hippocampus volume is relatively unchanged until the 7th decade (Scahill et al., 2003). The human pattern of relative gray matter loss, but white matter and ventricular gain with aging, reflects the sequence in the WT mouse, perhaps suggesting common underlying processes. Our measurements of control wildtype, C57Bl6 background, mouse brains in vivo (Table 1) are based on the LONI mouse brain atlas (Fig. 7; MacKenzie-Graham et al. 2004), which is freely available, and therefore the anatomical distinctions made here are fully verifiable. Our data therefore provide a quantitative basis to compare measurements of other mouse strains and models of brain disorder in the future.

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3.2. Brain structural changes in TASTPM mice and immunohistochemistry In TASTPMs all measured brain regions increase their size in absolute terms. This contrasts strongly with AD, where there is progressive atrophy affecting temporal/entorhinal (including thalamus) and parietal regions first, spreading to the frontal cortex when significant cognitive decline is evident (Thompson et al., 2003; Whitwell et al., 2007); sensorimotor cortices are comparatively spared; whole brain volume loss is 5.2% p.a. compared with 0.88% p.a. in controls (Thompson et al., 2003). Ventricular and CSF volumes steadily increase in compensation. Accepting that the rodent neurocranium can expand again helps to explain the modestly greater brain growth in TASTPMs (5.1% vs. 3.8% in WTs) despite increasing ventricular volume (although the ventricular change, ~0.1 mm3, is much smaller than the change in whole brain volume of ≤40 mm3). In thalamus, hippocampal formation and cerebral cortex immunohistochemistry shows that amyloidosis (Figs. 5E–G) and astrogliosis (Fig. 6) are very marked, possibly accounting for the greater volume increase in TASTPM. Aβ occupies ~1.5% of brain area by 10 mo in TASTPM mice (Howlett et al., 2004); the Aβ load plus the associated inflammatory response seem likely to have a greater spatial impact in vivo than a post mortem measurement of Aβ load alone would imply; indeed the thalamus, hippocampal formation, cerebral cortex and caudoputamen are larger in TASTPM than WT at 6 mo by approximately 2–7% (Table 1), consistent with this idea. Expressing the regional brain volumes of the TASTPM relative to their whole brain measurements suggests two main patterns of response to transgene expression that become established by 6 mo (Fig. 4). In pattern 1, an early net negative impact of the transgenes affects the corpus callosum, corticospinal tract, hypothalamus, midbrain–hindbrain and fornix system, which account for a significantly smaller proportion of the brain in TASTPM than in WT; these regions progressively enlarge with age in both strains. By contrast, pattern 2 regions (thalamus, cerebellum, cerebral cortex and caudoputamen) are from an early age proportionately larger in TASTPM than WT mice; but they experience a relative decline with age despite the concurrent increase in Aβ load (Figs. 5E–

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G) and astrogliosis (Fig. 6). Pattern 1 (proportional increase with age, but net negative transgene impact) prevails over pattern 2 (decreased with age, but net positive transgene impact) since over the whole brain the integrated result is progressive enlargement. Nevertheless, the immunohistochemistry shows the presence of increasing amyloidosis (Figs. 5E–G), astrogliosis (Fig. 6) and microgliosis (Figs. 5L–M), indicating that an abnormal brain histopathology is present. Microglia and neuronal dystrophies appear to accumulate in response to amyloid deposition (Meyer-Luehmann et al., 2008). Amyloid deposition is associated with some degree of neuronal loss in TASTPM and other AD transgenics (Howlett et al., 2008; Schmitz et al., 2004), although this is not always observed (see references in Schmitz et al., 2004). The appearance of dystrophic neurites and dark atrophic neurones also suggests a neurodegenerative phenotype in similar mutated APP × PS1 mice (Kurt et al., 2001). Reflecting this pathology, we observed that thalamus and caudoputamen decline in relative volume significantly faster in TASTPM than WT, although cerebral cortex declines less rapidly (Fig. 4). But these effects are small: if neuronal loss is a possible explanation for the accelerated proportional decline of thalamus and caudoputamen in TASTPM, it would be correspondingly difficult to detect post mortem, requiring the use of stereological techniques in carefully chosen areas. The present data are compatible with the hippocampal stereological analysis of Schmitz et al. (2004) who detected a significant decline in CA1-3, but not dentate gyrus (DG) neurons, and no change in the volumes of these cellular regions. They also failed to detect any relationship between neuronal cell numbers and the proportion of (i) the cell layer volume (CA or DG), or (ii) the entire hippocampal volume, occupied by amyloid and astrocytes. It was suggested by Schmitz et al. (2004) that their observations could indicate neuronal loss by both proximate amyloid deposition, and by high intraneuronal levels of Aβ40 and Aβ42 (Fig. 5B) — pointing to the patterns of early volumetric changes identified in the present study. However, perhaps because of the complexity of such studies, Schmitz et al. (2004) included only 6 data points in the correlation; their data, being post mortem, are also necessarily cross-sectional. Compare those data with the present Fig. 2 (which is representative of the data

Fig. 7 – The TASTPM mouse brain segmented in vivo. A–C are respectively transverse, horizontal and sagittal sections through the planes indicated by the yellow cross-hairs. Major regions (colour coded) are indicated using the nomenclature adopted in the LONI mouse brain atlas (http://www.loni.ucla.edu/MAP/): Cb, cerebellum; Cst, corticospinal tract; Hypo, hypothalamus; LatV, lateral ventricle; Olf, olfactory areas; other abbreviations, see Figs. 5 and 6.

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for other brain regions) — if the present data were also crosssectional, then the overlap between the earlier and later timepoints would fail to allow any observation about longitudinal change, despite there being many more datapoints than in Schmitz et al (2004). However, because the present data are longitudinal, it is possible to describe the changes within individuals: accordingly the data show that the increases in the TASTPM hippocampus and other regions, although relatively small, are highly significant. Post mortem stereological analyses carried out in fixed brains (e.g. Schmitz et al., 2004) may also fail to detect any in vivo volumetric changes resulting from potential extracellular fluid changes due to gliosis and amyloidosis (see also Fox et al., 2005, discussed below). Thus TASTPM hippocampus and cerebral cortex may indeed experience neuronal loss compared with WT mice, but in space-filling terms such loss seems offset by amyloid deposition and astrogliosis. The structural data suggest a dominant expansionist tendency in the normal mouse brain, which is augmented in TASTPM (pattern 1), possibly through progressive gliosis and amyloidosis; pattern 1 perhaps also reflects a more fundamental property of the murine brain allowing it to resist the negative consequences of amyloidosis and its sequelae, whereas the human brain succumbs. In part, different regional susceptibilities to transgene expression (contrast the expansion of the hippocampal formation in TASTPM with accelerating thalamic loss) could reflect cytotrophic potential. For example, the hippocampus, the most studied brain region in this regard, responds neurogenetically and volumetrically to external factors, including environmental enrichment as used in the present study (Farmer et al., 2004; Lazarov et al., 2005); neural and nonneural cytogenesis is reported in AD transgenic models (Bondolfi et al., 2002; Jin et al., 2004); astrocytes support neural stem cell survival and differentiation (Jagasia et al., 2006), which may be relevant for both WTs and TASTPMs; soluble APP is also associated with neurogenesis (Caillé et al., 2004; Chen and Tang 2006).

3.3. Comparison with published Alzheimer's transgenic volumetric data In agreement with our data, similar observations of brain volume increase are reported in C57Bl6 control mice, PS2APP (von Kienlin et al., 2005), PS1 and APP/PS1 AD transgenic mice (Delatour et al., 2006; Oberg et al., 2007). Progressive regional brain increases are also observed in WT and PDAPP transgenic mice ≤100 days old (and perhaps beyond) (Redwine et al., 2003). Our callosal data are also consistent with the literature: the corpus callosum is reduced in PDAPP (Redwine et al., 2003) and PSAPP mice (Valla et al., 2006b). The callosal decrement occurs early (Fig. 4), reflecting transgene expression rather than amyloid deposition (Valla et al., 2006a). But there are also differences, especially concerning the hippocampus, the principal region other than the whole brain that has been investigated by others: in PDAPP (Redwine et al., 2003) and APP/PS1 (Oberg et al., 2007) the hippocampus is reportedly smaller than in WT mice (whereas in TASTPM the hippocampal formation enlarges). In PDAPP the whole brain is also reportedly smaller. By contrast, in 6–10 month-old APP

mice the hippocampus:brain area ratio is reduced (Weiss et al., 2002), although in the anteroposterior dimension the hippocampal:brain ratio of ~2 mo PDAPP mice is increased compared with WT mice (Valla et al., 2006a). Similarly, in 16 mo PSAPP mice the hippocampal formation as % hemi-brain area is reduced anteriorly, but increased posteriorly (Valla et al., 2006b). These differences suggest that the age when measured, the method and locus of measurement may be influential. The question of anatomical definition is also important. In the LONI atlas (MacKenzie-Graham et al., 2004; Fig. 7), large anatomical regions that have diverse physiological functions are treated as a whole, including especially the cerebral cortex, midbrain–hindbrain, hippocampal formation and thalamus. But the use of a digital atlas remains valuable because the whole structural analysis process is automated, the investigation can be much more comprehensive, with considerable time-saving and objectivity dividends. The anatomical definitions employed are also verifiable. By subdividing the labels or using the Jacobian maps to detect localised deformations (Lerch et al., 2008; Maheswaran et al., 2008), anatomical resolution could be improved. Background and transgene variations are also relevant to pathophysiological development and could account for strain differences (Ryman and Lamb, 2006). Thus mutant APP expressed in the presence of mutant PS1 shows accelerated amyloid deposition compared with mutant APP expression alone. The detection of significant pyramidal cell loss in 17 mo APP/PS1 mice (Schmitz et al., 2004) employed a model expressing triply-mutated (APP751(KM670/671NL, V717I), PS1M146L) transgenes. The background contributes because inbred mouse strains differ genetically (Beck et al., 2000; Pierce et al., 2003), in brain structure (Chen et al., 2005; Ingram and Jucker, 1999) and in behavioural phenotype (Rogers et al., 1999). The volume increases observed in TASTPM mice, possibly due to abundant amyloid deposition and gliosis, may be compared with the effects of Aβ immunisation on brain volume change in AD. In that study (Fox et al., 2005) a significant decrease in volume measurements occurred in patients that responded immunologically (and cognitively) possibly reflecting, the authors suggested, clearance of Aβ with associated cerebral fluid shifts. However, the pervasive differences observed between the age-related brain changes in mature WT mice and humans indicate that the context of any changes detected in murine disease models must be fully appreciated. Furthermore, the pervasive differences between the transgenic and WT animals already evident by 6 mo (Fig. 4), suggest that a naive interpretation of these models as direct assays for the amyloid hypothesis in AD, or the toxicity of extracellular amyloid, is likely to be unwise. Stereologic investigations of amyloid deposition, astrogliosis and neuronal number (Schmitz et al. 2004) valuably illuminate the discrete cellular processes that underlie the macroscopic structural changes we have identified. Localised regions of change unassociated with the anatomical regions defined by the LONI atlas may also be identified using more focussed, deformation-based morphometry (Maheswaran et al., 2008). Such methods have the advantage of being automatable, and potentially identify changes in vivo rather than post mortem, accruing greatly increased investigative power thereby.

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4.

Experimental procedures

4.1.

Animal handling

Animal experiments complied fully with GSK ethical requirements and the UK Animals (Scientific Procedures) Act 1986. Mice were allowed ad libitum access to feed and water and were housed singly under standard conditions with environmental enrichment. Male TASTPM transgenic mice over-express the Alzheimer's disease (AD)-associated human mutated proteins APP695(K595N, M596L) × PS1(M146V) under the control of the Thy-1 promotor (N.B. the numbering refers to the APP695 sequence; the mutations are the same as in Howlett et al., 2004). Control, wildtype (WT) mice expressed the empty vector. To prevent genetic drift, control and TASTPM mice had been back-crossed for more than 8 generations to fully express the C57Bl6 background. The mice (WT and TASTPM) were divided into two equalsize groups and treated i.p. once per month with the noradrenergic neurotoxin DSP4 (5 mg/kg) or its vehicle (saline 1 ml/kg) putatively to hasten brain changes (Heneka et al., 2006). We did not detect any DSP4-related effects (Fig. 2), so treated and untreated WT (or TASTPM) animals were analysed as one group.

4.2.

Animal preparation for MRI

For MRI, mice were anaesthetised (isoflurane 5% in air:O2 2:1) and hydrated with 0.2 ml sterile saline s.c. The eyes were protected with Lacri-Lube gel (Allergan Pharmaceuticals, Ireland). The head was fixed in a custom-made head holder using tooth, nose and cheek bars. A small air balloon was placed under the chest to monitor respiration via a pressure transducer. Warm mats (Holroyd Components Ltd, Saffron Walden, UK) covered in insulating fabric were homeostatically regulated to about 36 °C using a rectal probe coupled to a temperature controller (Harvard Apparatus Inc). Physiological monitoring of the ventilation rate and core temperature was continuous. After MRI the animal was placed in an incubator (~33 °C) and hydrated with 0.2 ml saline 0.9% s.c. After transfer to its home cage soft diet was provided for up to 5 days. Mice tolerated this imaging regime well and recovered uneventfully. Anaesthesia lasted ~2 h in total. MRI was carried out at 4 timepoints (6, 9, 11 and 14 mo). Although TASTPM numbers declined throughout the study (Table 1), this reflects natural attrition as observed in other studies (unpublished data) and was not related to imaging or culling.

4.3.

MRI acquisition protocols

MRI was performed at 4.7 T (Bruker Biospec: 40 cm magnet, BGA-12 gradient set, Avance console operated via Paravision 3.0.1). Radiofrequency transmission and reception were applied using a 25 mm diameter quadrature birdcage coil (RAPID Biomedical) into which the head holder was inserted to a snug fit. Imaging employed the standard sequences available in Paravision. For structural detail a fat-suppressed T2-weighted scan (termed S1) was performed using 60 contiguous coronal slices, 8 echoes (echo times (TE) 10.6, 21.1, 31.7, 42.3, 52.8, 63.4, 74.0, 84.5 ms), effective echo time ΔTE ~10.5 ms, repetition time 5839 ms, field of view 20 × 20 × 0.312 mm, matrix 256 × 128, that was zero-filled to 256 × 256 points prior to 2D Fourier transformation. The scan time was approximately 12.5 min. It was

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repeated (S2) with the slice position shifted by half a slice thickness (0.156 mm) to aid dense sampling in the slice direction. Scans S3 and S4 were obtained in the same way without moving the animals in case movement during S1 and S2 jeopardised image quality. This imaging was carried out as part of a wider MRI investigation.

4.4.

Checking scanner stability

To check for scanner drift we performed two kinds of quality assurance. Firstly, over several weeks using time-intervals similar to the imaging, we repeatedly imaged a spherical water phantom ~2 cm in diameter doped with Omniscan 0.1%: there was no trend change in phantom signal intensity, position or shape. Secondly we used a complex phantom (Bruker), with 4 equally-spaced geometrical markings nominally 56.5 mm apart, allowing spatial calibration to 0.1 mm. This was imaged before and after the whole experiment: measurements were respectively 56.55 ± 0.17 mm and 56.50 ± 0.10 mm (mean ± SD), a change of − 0.088%.

4.5. Post acquisition image processing — creating a native brain atlas from the LONI atlas The LONI mouse brain atlas from the mouse atlas project (MacKenzie-Graham et al., 2004) was used, with permission, to define the whole brain and its regional segmentation. We created an in-house atlas (Fig. 7) by propagating the anatomical labels from the LONI atlas (which is derived from an ex vivo diffusion-weighted scan segmented into 30 default brain regions) into an in vivo MRI of a 6 month-old C57Bl6 animal. The accuracy of propagation was carefully checked and minor errors in label boundaries were manually corrected. The regions selected for analysis represent the 11 largest regions plus the 3rd, 4th and lateral ventricles (combined as the ‘total ventricle’ since ventricular size is relevant to AD pathology), but excluding the olfactory bulb.

4.6. Post acquisition image processing — image registration Images were aligned by image registration to place them in common data spaces for further comparison and analysis. Registration was based on a 3-stage sequence of global and local transformations (Bock et al., 2006; Maheswaran et al., 2006; Rueckert et al., 1999). Firstly, to obtain an approximate brain segmentation for each animal, an automated brain extraction procedure was performed in which the native brain atlas was globally aligned to each timepoint-1 (6 mo) image using an affine registration with 9 degrees of freedom. To ensure that all brain tissue was included by this process, the segmentation of the whole brain was dilated by 5 voxels. Secondly, we performed a local, non-linear, registration (Rueckert et al., 1999) of the timepoint-1 images to the mouse brain atlas. This warps the atlas images to match the animal's features by manipulating an underlying mesh of control points defined in each animal's native coordinate system. We used a multi-resolution, iterative approach starting with 2 mm spaced control points reducing in 3 steps to 0.25 mm. After non-linear registration the anatomical labels of the brain atlas that demarcate the brain regions were propagated into the space of each timepoint-1 brain to obtain a final segmentation. Thirdly, the timepoint-1 images were used as the targets and the subsequent timepoints of the same brains were aligned with these, using non-rigid registration performed in a pairwise fashion. The volumes of each label (i.e. brain region)

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were then calculated by the integration of Jacobian maps calculated for the required coordinate transformations. The Jacobian specifies the expansion/contraction of each voxel in the image after coordinate transformation, so that summing over all the voxels representing a specific label (transferred from the timepoint-1 images) determines for each animal the growth of each structure from the baseline scan (Boardman et al., 2003).

4.7.

Statistical analysis

Data were analysed using a random coefficient regression model (Longford, 1993) with time (age in days) modelled as a continuous numerical variable. This approach is statistically powerful as it effectively smoothes out each animal's profile over time; it also renders the analysis less susceptible to potential skewing by outliers or absent data. Transgene (TASTPM or WT) was fitted as a fixed effect. To model the random differences between animals a random intercept was fitted for each animal. The trend over time was modelled using either a linear or a quadratic fit if the latter proved to be statistically superior. Differences between the strains (i.e. TASTPM or WT) were assessed using the random coefficient regression model, either averaged over time (the ‘transgene’ effect) or by considering the ‘transgene × age’ interaction; the overall change over time (the ‘age’ effect) was assessed averaged over strain. Changes over time within the strains were also assessed using the linear slope coefficients. The analysis was performed using Proc Mixed in SAS v8.2 (Statistical Analysis Software Institute, Cary, NC, USA). Outliers were taken to be observations with Studentized residuals greater than 4. This value was chosen to remove only extreme cases, affecting ~0.3% of the observations.

The presented data values are expressed as observed means ± SD. 4.8.

Immunohistochemistry

Animals separate from the imaging study (aged 6–24 months) were killed with pentobarbital (Euthatal, Rhone Merieux, ~0.5 ml i.p.); the brains were fixed by immersion in paraformaldehyde (4% in 0.1 M phosphate-buffered saline, PBS, pH 7.4) for a minimum of 48 h. Immunohistochemistry was performed a previously detailed (Howlett et al., 2004; Howlett et al., 2008) on 5 μm thick wax-embedded sections. To detect Aβ we used monoclonal 1E8 (2.4 μg/ml, raised against Aβ13–27 thus detecting ‘total’ Aβ) or monoclonal 20G10 (0.28 μg/ml, raised against Aβ35–42 and selected for its C-terminal Aβ42 specificity). To detect full-length APP a polyclonal against the Cterminus was used (Invitrogen UK, cat no 51-2700). Other antibodies were against glial fibrillary acid protein (GFAP: Chemicon UK, cat no MAB360) for detecting astrocytes, and against ionized calcium binding adaptor molecule 1 (iba1: Wako Chemicals GmbH, Neuss, Germany, cat no 019-19741) for microglia. De-waxed, re-hydrated sections were treated with 85% formic acid for 8 min to enhance Aβ antigenicity. Sections used for GFAP or iba1 were microwaved (2×5 min at 300 W) in 0.01 M citrate buffer pH 6.0 to enhance antigen retrieval. All sections were subsequently incubated in 0.3% H2O2 in PBS for 30 min at room temperature to quench endogenous peroxidase activity followed by washing (3× 5 min) in PBS. Sections were subsequently incubated overnight at 4 °C with primary antibodies; secondary biotinylated antibodies (Vector Laboratories, Peterborough, UK) were visualised using diaminobenzidine according to the manufacturer's data sheets.

Acknowledgments SM, DR, TH, DLGH and JVH acknowledge funding from the GlaxoSmithKline — Imperial College London aADI scheme. We thank Alison Robinson and Jackie Colledge for expert experimental assistance, Kenny Cheng for statistical computations, Stuart Evans and Kim Howell for help with the Figures and Dr AW Toga for kind permission to use the LONI mouse brain atlas; also our anonymous reviewers for comments that improved the manuscript.

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