Regional brain shrinkage over two years: Individual differences and effects of pro-inflammatory genetic polymorphisms

Highlights

• In healthy adults, 10 brain ROI volumes measured manually twice 2 years apart

• Average shrinkage was observed in the medial temporal and orbitofrontal cortices.

• No mean change noted in lateral prefrontal cortex and prefrontal white matter

• Heterogeneity in change was noted in all regions, except the orbitofrontal cortex.

• Pro-inflammatory SNPs were linked to parahippocampal and cerebellar shrinkage.

Abstract

We examined regional changes in brain volume in healthy adults (N = 167, age 19–79 years at baseline; N = 90 at follow-up) over approximately two years. With latent change score models, we evaluated mean change and individual differences in rates of change in 10 anatomically-defined and manually-traced regions of interest (ROIs): lateral prefrontal cortex (LPFC), orbital frontal cortex (OF), prefrontal white matter (PFw), hippocampus (Hc), parahippocampal gyrus (PhG), caudate nucleus (Cd), putamen (Pt), insula (In), cerebellar hemispheres (CbH), and primary visual cortex (VC). Significant mean shrinkage was observed in the Hc, CbH, In, OF, and PhG, and individual differences in change were noted in all regions, except the OF. Pro-inflammatory genetic variants modified shrinkage in PhG and CbH. Carriers of two T alleles of interleukin-1β (IL-1β C-511T, rs16944) and a T allele of methylenetetrahydrofolate reductase (MTHFR C677T, rs1801133) polymorphisms showed increased PhG shrinkage. No effects of a pro-inflammatory polymorphism for C-reactive protein (CRP-286C>A>T, rs3091244) or apolipoprotein (APOE) ε4 allele were noted. These results replicate the pattern of brain shrinkage observed in previous studies, with a notable exception of the LPFC, thus casting doubt on the unique importance of prefrontal cortex in aging. Larger baseline volumes of CbH and In were associated with increased shrinkage, in conflict with the brain reserve hypothesis. Contrary to previous reports, we observed no significant linear effects of age and hypertension on regional brain shrinkage. Our findings warrant further investigation of the effects of neuroinflammation on structural brain change throughout the lifespan.

Introduction

Brain volume declines with age and significant shrinkage occurs in multiple gray and white matter regions within a relatively short time (Driscoll et al., 2009, Fjell et al., 2009, Fjell et al., 2013, Pfefferbaum et al., 1998, Raz et al., 2005, Raz et al., 2010, Raz et al., 2013, Resnick et al., 2003, Scahill et al., 2003). Notably, the magnitude and rate of volume reduction vary across brain regions. Shrinkage is especially pronounced in the cerebellum, tertiary association cortices, medial temporal lobe and neostriatum (Fjell et al., 2009, Raz et al., 2005, Tamnes et al., 2013), whereas primary visual cortex shows minimal age-related deterioration (Fjell et al., 2009, Raz et al., 2005, Raz et al., 2010). The rates of change vary, not only across brain regions, but also across individuals. Understanding individual differences in brain aging and elucidating their mechanisms have been hampered by the daunting number of proposed antecedents, and the cumulative record of the relevant studies remains sparse. Among multiple potential modifiers of the rate and extent of brain aging, vascular risk factors (Jagust, 2013, Raz and Rodrigue, 2006) and neuroinflammation (Finch, 2010, Godbout and Johnson, 2006) have attracted significant attention.

To date, several studies have attempted to gauge the influence of vascular risk (VR) and inflammation on regional brain volumes. Hypertension, a major and probably the most common VR, has been associated with shrinkage and smaller volume of age-sensitive brain regions, such as the hippocampus (Burns et al., 2012, Korf et al., 2004, Raz et al., 2005, Raz et al., 2007a, Raz et al., 2007b), and tertiary association cortices (Raz et al., 2003a, Raz et al., 2005, Raz et al., 2007a, Raz et al., 2007b).

Several biomarkers of inflammation have also been linked to individual differences in brain structure. Elevated circulating levels of pro-inflammatory cytokines (e.g., interleukin (IL)-6, and tumor necrosis factor α), C-reactive protein (CRP), and homocysteine (Hcy) correlate with reduced volumes of the hippocampus, cerebral cortex, and cerebral white matter, as well as increase in the volume of white matter hyperintensities (Bettcher et al., 2012, Choe et al., 2014, den Heijer et al., 2003, Jefferson et al., 2007, Marsland et al., 2008, Raz et al., 2012, Satizabal et al., 2012, Seshadri et al., 2008, Shimomura et al., 2011, Taki et al., 2013, Van Dijk et al., 2005, Williams et al., 2002, but see Feng et al., 2013, Morra et al., 2009, Scott et al., 2004).

In exploring the effects of pro-inflammatory biomarkers on the brain in humans, one must contend with two problems: the inability to manipulate the levels of biomarkers directly through induced inflammation, and the uncertain relationship between blood levels and brain content (Banks et al., 1995). For ethical reasons, blood levels of pro-inflammatory biomarkers cannot be safely manipulated in healthy humans, and there are doubts as to whether human IL-1β can cross the blood–brain barrier (Banks, 2005, Banks et al., 2001), although in rodents, chronic inflammation increases IL-1β gene expression in the hippocampus (Bardou et al., 2013). These challenges can be overcome, at least to some extent, by Mendelian randomization (Katan, 1986), which takes advantage of known genetic variants (single nucleotide polymorphisms; SNPs) that predispose individuals to various levels of the pro-inflammatory biomarkers in the brain and peripheral circulation. Thus, the study of persons with genetic polymorphisms that are associated with variable levels of a given risk factor may shed light on neuroinflammation in correlational studies. To date, several genetic variants associated with vascular health and inflammation have been linked to age-related and individual differences in brain volume and white matter integrity.

Several SNPs associated with various levels of proinflammatory response have been identified. Methylenetetrahydrofolate reductase (MTHFR C677T, rs1801133), a polymorphism of a gene that controls production of the enzyme necessary for metabolizing Hcy, modulates plasma concentration of Hcy (Bathum et al., 2007, de Lau et al., 2010). Variants in the IL-1β gene (e.g., IL-1β C-511T, rs16944) are associated with release of the eponymous cytokine in response to infection (Yarlagadda et al., 2009). Several SNPs that promote inflammation have been associated with structural brain differences. For instance, MTHFR C677T has been linked to smaller white matter volumes and accelerated shrinkage in periventricular fronto-parietal and parieto-occipital regions (Rajagopalan et al., 2011, Rajagopalan et al., 2012). G homozygotes of the polymorphism of the IL-6 gene (IL-6A-174G, rs1800795) have greater hippocampal gray matter volumes than heterozygotes and A homozygotes (Baune et al., 2012). In healthy adult carriers (Raz et al., 2012) the variant T alleles of IL-1β C-511T and CRP-286 C>A>T(rs3091244) polymorphisms are associated with increased burden of white matter hyperintensities (WMH). Notably, none of the extant studies of pro-inflammatory SNPs investigated their effect on rate of change.

Several other polymorphisms have been linked to individual differences in brain volumes and in the rate of age-related declines. The most prominent among these is a well-established genetic risk factor for late-onset Alzheimer's disease (AD; Roses, 1996), and the only consistently reported single-gene marker for longevity (Brooks-Wilson, 2013): the ε4 allele of the APOE gene. The APOE ε4 allele controls availability of the apolipoprotein E (APOE), a major factor in lipid transport. APOE ε4 has also been linked to increased risk of cardiovascular disease (Mahley & Rall, 2000) and hyperlipidemia (Davignon et al., 1988). However, the extant literature concerning the effect of APOE ε4 on brain aging and cognition is contradictory (Reinvang et al., 2013) and some suggest that positive findings may reflect inclusion of participants with incipient pathology (Cherbuin et al., 2007).

Reliance on cross-sectional comparison studies significantly impedes understanding of age-related change (see Raz & Kennedy, 2009 for a review). Although it has been made abundantly clear that cross-sectional studies cannot capture true dynamics of age-related change and the role of various mediators in shaping the age trajectories (e.g., Hofer and Sliwinski, 2001, Lindenberger and Pötter, 1998, Lindenberger et al., 2011, Maxwell and Cole, 2007), longitudinal studies remain relatively scarce. Moreover, a significant share of the extant literature on age-related brain shrinkage is focused solely on the mean change across individuals, without considering individual differences in change. This focus on a measure of central tendency, commonly expressed in a simple autoregressive or a residual regression model, precludes the understanding of differential aging. Whereas development of latent longitudinal methods, such as the latent change score model (LCSM; McArdle, 2008, McArdle, 2009, McArdle and Nesselroade, 1994), enables quantification of individual differences in age-related change, application of these methods is still relatively rare. With a few exceptions (McArdle et al., 2004, Raz et al., 2005, Raz et al., 2010, Raz et al., 2013), most of the extant longitudinal studies (e.g., Fjell et al., 2009, Pfefferbaum et al., 1998, Resnick et al., 2003) are limited to evaluation of mean change.

In this study, our aim was to address the limitations outlined above. First, we aimed to document regional brain changes occurring over two years in healthy adults and replicate previously reported findings. We expected, based on the extant literature, to observe mean shrinkage of the cerebellum, hippocampus, striatum, and prefrontal cortices, but no significant mean change in the volume of the primary visual cortex. Second, we examined individual variation in age-related change in regional brain volumes. Based on previous studies, we hypothesized to find significant variance (i.e., individual differences) in change across all regions of interest (ROIs). Third, we gauged the influence of putative modulators of brain aging trajectories on the rate of change in regional brain volumes. Specifically, we tested the effects of VR factors and biomarkers, such as arterial hypertension, and genetic variants associated with increased pro-inflammatory response, IL-1β C-511T, CRP-286 C>A>T, and MTHFR C677T. In addition, we evaluated the effect of a common genetic risk factor for AD (APOE ε4) on rates of change in regional brain volumes.