In this study, we found a differential influence of obesity on brain structure and brain metabolism. Higher BMI was associated with increased brain metabolic activity (mainly driven by the younger individuals), but at the same time with less cortical thickness. The regions affected did not overlap with the typical AD vulnerable areas. Furthermore, BMI was not associated with core CSF AD biomarkers suggesting that these changes are independent of an underlying AD pathophysiology.
We first analyzed the relationship between brain metabolism and BMI. Few previous studies, two cross-sectional and three longitudinal, have assessed the relationship between brain metabolism and obesity in middle aged individuals [23, 24, 26–28]. The cross-sectional studies presented conflicting evidence. Wang et al. observed higher brain metabolism in parietal cortices in 20 middle-aged participants with morbid obesity as compared with 10 lean controls, while Volkow et al. found a negative relationship between BMI and FDG uptake in prefrontal areas [27, 28]. Of note, only 3 of the 21 participants evaluated in the latter study had BMIs in the obesity range . All three longitudinal studies assessed brain metabolism in middle-aged individuals with morbid obesity before and after bariatric surgery-induced weight loss [23, 24, 26]. Marques et al. described brain hypermetabolism in 17 women with severe obesity as compared with 16 lean controls, which normalized after weight loss . Brain metabolism normalization in this study was associated to cognitive improvement . Tuulari et al. and Rebelos et al. did not observe differences in brain metabolism between participants suffering from morbid obesity and controls in fasting conditions, but both found higher insulin-stimulated FDG uptake [24, 26]. The low number of controls in these two studies (n = 7 and n = 12, respectively) might have limited the statistical power to detect subtle differences during fasting conditions. Nonetheless, in both studies brain metabolic abnormalities normalized after bariatric-surgery [24, 26]. Only one previous study assessed the relationship between BMI and brain FDG uptake in healthy elderly. This study, also in the ADNI cohort, included 222 participants and also showed higher brain metabolic activity in relation with higher BMI mostly in women . Altogether, our results and the aforementioned studies suggest that obesity is associated to increased FDG uptake in the brain.
We also evaluated the relationship between obesity and cortical thickness in the same sample. In accordance with previous results from our group and others, we observed cortical thinning associated with increasing BMI [9, 22, 39–41].
The regions affected by atrophy and higher metabolism in our study showed little overlap with the typical vulnerable AD regions. Importantly, we did not find any association between BMI and the CTh and brain metabolism in two of the most commonly used AD signatures [34, 35]. Furthermore, we did not find any association between BMI and CSF amyloid or tau levels. The inclusion of CSF biomarkers in the analyses yielded qualitatively the same results and the stratified analyses by amyloid positivity showed a similar pattern of changes. Altogether, these results suggest that the aforementioned cortical alterations are independent of an underlying AD process.
Other cross-sectional studies in cognitively normal controls showed greater amyloid and tau burden associated with lower late life BMI [17, 18, 42]. On the contrary, the only two previous longitudinal studies showed greater amyloid deposition late in life in relation with mid-life obesity [15, 16] Discrepancies between mid-life and late-life studies might be explained by reverse causation (i.e. AD related weight loss in preclinical AD), selection and survival biases (i.e higher mortality and dementia risk in persons with obese might determine that only those specially protected against obesity consequences survived or/and maintained normal cognition late in life) or by the existence of additive and/or competing risk (i.e obesity not only promote neurodegeneration throughout AD pathophysiological mechanisms and therefore only those with lower AD burden remain cognitively normal late in life) [9, 29, 30, 43]. In order to minimize the confounding effect of weight loss on the impact of obesity on the different biomarkers, we excluded those subjects with significant weight loss [9, 30]. Nonetheless, we cannot completely rule out the existence of a residual bias. In any case, our results reinforce the notion that obesity impacts on brain metabolism and structure by mechanisms not directly related with preclinical AD.
The mechanisms mediating the structural and metabolic brain abnormalities in individuals with obesity are beyond the objectives of the present work, and deserve further research . Our study suggests that different mechanisms might underlie the finding of less cortical thickness and higher brain metabolism associated with a higher BMI. First, there was little overlap between the areas. Second, the relationship between age and brain metabolism, but not that of age and brain structure, was modified by excess of body weight. Younger participants drove the increased brain metabolism. Finally, the stratified analyses by amyloid positivity showed that the increased metabolism with BMI was mainly present in amyloid negative individuals while diminished CTh with BMI was present regardless of amyloid status. The finding of higher brain metabolism with increased BMI is relatively unexpected. We hypothesize that this finding might reflect obesity-induced neuroinflammation and astroglyosis. Interestingly, in the aforementioned studies with subjects who underwent bariatric surgery, higher FDG cerebral uptake correlated with markers of systemic inflammation [23, 24]. In this sense, although brain glucose metabolism is considered a marker of neuronal activity, FDG-PET signal has recently been demonstrated to be also located in astrocytes . In addition, animal studies combining FDG-PET and PET with tracers for activated microglia confirmed a highly co-localized signal of increase of glucose metabolism and neuroinflammation in both wild-type aging mice and in AD transgenic mice [45, 46]. Interestingly, in wild-type mice uncoupling glucose metabolism and neuroinflammation was observed at older ages, i.e neuroinflammation persisted but glucose metabolism returned to baseline values. This late-life uncoupling has been attributed to the progression of age-dependent neurodegeneration . In this same line, a triple tracer study performed in AD transgenic mice showed age-dependent microglial activation which positively correlates with amyloid load and brain metabolism. Nonetheless, in this study brain hypermetabolism was observed specially at younger ages and declined in relation to increasing amyloid burden. Therefore, synaptic dysfunction might mask inflammation-related hypermetabolism . Further studies are required to better understand the contribution of peripheral and central nervous system inflammation or other mechanisms to the brain metabolic changes which are present in obesity.
Our study has limitations. First, as it is cross-sectional, causal relationship between BMI and brain neuroimaging abnormalities cannot be assessed. Second, there is a significant bias in the ADNI cohort, which excluded participants with large vascular burden and is mainly composed by Caucasian participants. This selection bias might explain the healthier than expected phenotype of cognitively healthy ADNI participants with obesity in our cohort. Of note, we did not find the, otherwise, expected correlation between BMI and fasting plasmatic glucose and systolic or diastolic blood pressure. Third, there is evidence that both insulin resistance and variability in fasting glucose levels can affect FDG uptake among cognitively normal middle-aged individuals [47, 48]. Given that there is sparse data available in ADNI to better characterize the glucometabolic status in our subjects, the degree of increases in FDG uptake reported here needs to be confirmed among individuals with more detailed evaluation of glucose tolerance status and appropriate measures of insulin sensitivity. Nonetheless, it should be underscored that no significant correlation between fasting glucose levels and BMI was found in our cohort and that impact of insulin sensitivity on brain metabolism was not consistent among studies [23, 24, 26, 48, 49]. Fourth, other relevant variables closely related to body weight, including dietary habits and physical activity, which have been previously related to brain health, are not available in ADNI.