Obesity associated with increased brain-age from mid-life

The link between obesity and adverse health outcomes such as diabetes, cancer and cardiovascular disease is well-established and poses a major challenge to current and future health care provision. Moreover, it is increasingly recognized that obesity may act to accelerate or advance the onset of age-related changes such as neurodegeneration, either directly or through associated co-morbidities (Doherty 2011). These associations, taken together with the increased rate of obesity in elderly populations (Flegal et al. 2012) render it critical to understand the full impact of obesity on brain health, in particular as evidence suggests that adverse outcomes may be mitigated through intervention (Gunstad et al. 2011).

A number of strands of evidence have related biological processes associated with obesity to changes found in normal aging. For example, as with normal aging, obesity increases oxidative stress (Furukawa et al. 2004), and promotes inflammation through the production of pro-inflammatory cytokines produced in adipose tissue (Arnoldussen et al. 2014; Chung et al. 2009). In turn, cytokines and pro-inflammatory markers such as IL-6 and TNF-alpha have been linked to cognitive decline (Chung et al. 2009; Griffin 2006; Wilson et al. 2002), and have been shown to be up-regulated in regions undergoing neurodegeneration (Wilson et al. 2002). Inflammatory biomarkers have been associated with increased brain atrophy – a common marker of aging (Jefferson et al. 2007), as have other endophenotypes such as shortened telomere length (Wikgren et al. 2014). Conversely, a considerable body of evidence exists suggesting that caloric restriction may be neuroprotective, leading to a delay or slowing of aging (Colman et al. 2009, 2014; Masoro 2005; Sohal and Weindruch 1996), a reduction in age-related apoptosis (Someya et al. 2007), and age-related production of pro-inflammatory cytokines (Kalani et al. 2006; Spaulding et al. 1997).

In short, the growing body of literature that relates common markers of aging to those observed in obesity supports the hypothesis that obesity may accelerate or advance the onset of brain aging. However direct studies in support of this link are lacking. For example, while many studies have reported a link between increased BMI and declining cognitive function (Cournot et al. 2006; Debette et al. 2011), as well as increased risk of dementia and Alzheimer’s Disease (Gustafson et al. 2004; Whitmer et al. 2005; Xu et al. 2011), other studies contradict these findings (Qizilbash et al. 2015), and indeed it has even been suggested that lower, rather than higher, body mass may be predictive of the onset of AD in the years immediately preceding the onset of clinical symptoms (Fielding et al. 2013; Knopman et al., 2007). The literature on brain structural changes too is complex. While many studies report a negative correlation between BMI and grey matter volume (increased BMI linked to lower GMV) (Brooks et al. 2013; Debette et al. 2014; Gunstad et al. 2008;Hassenstab et al. 2012; Veit et al. 2014), other reports are contradictory (Haltia et al. 2007; Pannacciulli et al. 2007; Sharkey et al. 2015). More significantly, despite a considerable number of often highly powered studies across the adult lifespan (Taki et al. 2008), there is a conspicuous lack of either global findings related to obesity, or evidence of an aging interaction (for a review, see Willette and Kapogiannis 2015).

Thus while current neuroimaging evidence certainly suggests altered brain structure is association with obesity, it fails to support the hypothesis that obesity influences age-related atrophy of the brain. There are a number for reasons for why this might be. Different tissue types in the brain age at different rates (Walhovd et al. 2005), perhaps limiting the sensitivity of cross-sectional studies over limited age-periods. Moreover there is a complex and somewhat compensatory interaction between the change in cortical thickness and surface area (Storsve et al. 2014), that may confound analysis by morphometric methods such as voxel-based morphometry (VBM) commonly employed in structural studies of obesity. In addition, VBM methods are designed to obviate global changes in favour of regional analyses. If obesity, like aging affects the brain globally, it may be the case that a significant global interaction may be obfuscated. Analysis of white matter too may be confounded. While some studies suggest obesity and inflammation are both associated with smaller fractional anisotropy (FA) in diffusion tensor imaging (DTI) (Stanek et al. 2011; Verstynen et al. 2013), it is also the case that additional factors related to obesity and aging such as blood pressure are positively associated with FA (Verstynen et al. 2013), raising the possibility that competing effects may hamper identification of an age-by-BMI interaction. The alternative to these propositions is that obesity may increase the rate of aging of brain tissue, but that these effects are subtle and within the scope of normal aging parameters.

In this cross-sectional population-based study, we assessed the impact of obesity on brain structure across the adult lifespan using global parameters of volume, cortical thickness and surface area. The goal of our study was to establish the overall effect of obesity on grey (i.e. cortical thickness, surface area) and white matter, to determine whether obesity affected tissue types differentially, and crucially to investigate whether obesity was associated with an increase in brain-age, evaluated with reference to lean controls. We were particularly interested in whether changes associated with obesity (i.e. deviations from lean age-matched controls) might occur during a particular vulnerable period.