Disappearing metabolic youthfulness in the cognitively impaired female brain.

Sex differences play a vital role in human brain structure and physiology. Previous reports have proposed evidence hinting at a metabolic advantage in female brains across adulthood. It remained to be determined whether this advantage would be maintained across the spectrum of cognitive impairment, up to and including dementia due to Alzheimer's disease (AD). Here, using a machine-learning algorithm, we explore sex differences in metabolic brain-age derived from fluorodeoxyglucose positron emission tomography imaging among cognitively healthy individuals and those affected by mild cognitive impairment and clinically probable AD. First, we report that cognitively healthy male participants showed a persistently "older" looking brains when compared to healthy female participants in term of metabolic brain age, confirming earlier reports. However, this distinction disappeared among MCI individuals and probable AD patients, and this loss could not be explained by an accompanying neurodegeneration. This would seem to indicate that females have a higher rate of decline in brain glucose metabolism when cognitively impaired to negate their prior advantage.

Associating Type 2 Diabetes Risk Factor Genes and FDG-PET Brain Metabolism in Normal Aging and Alzheimer's Disease.

Background: Several studies have linked type 2 diabetes (T2D) to an increased risk of developing Alzheimer's disease (AD). This has led to an interest in using antidiabetic treatments for the prevention of AD. However, the underlying mechanisms explaining the relationship between T2D and AD have not been completely elucidated. Objective: Our objective was to examine cerebral 18F-fluorodeoxyglucose (FDG) uptake during normal aging and in AD patients in regions associated with diabetes genetic risk factor expression to highlight which genes may serve as potential targets for pharmaceutical intervention. Methods: We calculated regional glucose metabolism differences in units of standardized uptake values (SUVR) for 386 cognitively healthy adults and 335 clinically probable AD patients. We then proceeded to extract gene-expression data from the publicly available Allen Human Brain Atlas (HBA) database. We used the nearest genes to 46 AD- and T2D-associated SNPs previously identified in the literature, and mapped their expression to the same 34 cortical regions in which we calculated SUVRs. SNPs with a donor consistency of 0.40 or greater were selected for further analysis. We evaluated the associations between SUVR and gene-expression across the brain. Results: Of the 46 risk-factor genes, 15 were found to be significantly correlated with FDG-PET brain metabolism in healthy adults and probable AD patients after correction for multiple comparisons. Using multiple regression, we found that five genes explained a total of 72.5% of the SUVR variance across the healthy adult group regions, while four genes explained a total of 79.3% of the SUVR variance across the probable AD group regions. There were significant differences in whole-brain SUVR as a function of allele frequencies for two genes. Conclusions: These results highlight the association between risk factor genes for T2D and regional glucose metabolism during both normal aging and in probable AD. Highlighted genes were associated with mitochondrial stability, vascular maintenance, and glucose intolerance. Pharmacological intervention of these pathways has the potential to improve glucose metabolism during normal again as well as in AD patients.

Selection of the optimal intensity normalization region for FDG-PET studies of normal aging and Alzheimer's disease.

The primary method for measuring brain metabolism in humans is positron emission tomography (PET) imaging using the tracer 18F-fluorodeoxyglucose (FDG). Standardized uptake value ratios (SUVR) are commonly calculated from FDG-PET images to examine intra- and inter-subject effects. Various reference regions are used in the literature of FDG-PET studies of normal aging, making comparison between studies difficult. Our primary objective was to determine the optimal SUVR reference region in the context of healthy aging, using partial volume effect (PVE) and non-PVE corrected data. We calculated quantitative cerebral metabolic rates of glucose (CMRg) from PVE-corrected and non-corrected images from young and older adults. We also investigated regional atrophy using magnetic resonance (MR) images. FreeSurfer 6.0 atlases were used to explore possible reference regions of interest (ROI). Multiple regression was used to predict CMRg data, in each FreeSurfer ROI, with age and sex as predictors. Age had the least effect in predicting CMRg for PVE corrected data in the pons (r2 = 2.83 × 10-3, p = 0.67). For non-PVE corrected data age also had the least effect in predicting CMRg in the pons (r2 = 3.12 × 10-3, p = 0.67). We compared the effects of using the whole brain or the pons as a reference region in PVE corrected data in two regions susceptible to hypometabolism in Alzheimer's disease, the posterior cingulate and precuneus. Using the whole brain as a reference region resulted in non-significant group differences in the posterior cingulate while there were significant differences between all three groups in the precuneus (all p < 0.004). When using the pons as a reference region there was significant differences between all groups for both the posterior cingulate and the precuneus (all p < 0.001). Therefore, the use of the pons as a reference region is more sensitive to hypometabism changes associated with Alzheimer's disease than the whole brain.

Bias-adjustment in neuroimaging-based brain age frameworks: A robust scheme.

The level of prediction error in the brain age estimation frameworks is associated with the authenticity of statistical inference on the basis of regression models. In this paper, we present an efficacious and plain bias-adjustment scheme using chronological age as a covariate through the training set for downgrading the prediction bias in a Brain-age estimation framework. We applied proposed bias-adjustment scheme coupled by a machine learning-based brain age framework on a large set of metabolic brain features acquired from 675 cognitively unimpaired adults through fluorodeoxyglucose positron emission tomography data as the training set to build a robust Brain-age estimation framework. Then, we tested the reliability of proposed bias-adjustment scheme on 75 cognitively unimpaired adults, 561 mild cognitive impairment patients as well as 362 Alzheimer's disease patients as independent test sets. Using the proposed method, we gained a strong R2 of 0.81 between the chronological age and brain estimated age, as well as an excellent mean absolute error of 2.66 years on 75 cognitively unimpaired adults as an independent set; whereas an R2 of 0.24 and a mean absolute error of 4.71 years was achieved without bias-adjustment. The simulation results demonstrated that the proposed bias-adjustment scheme has a strong capability to diminish prediction error in brain age estimation frameworks for clinical settings.

Links Between Metabolic and Structural Changes in the Brain of Cognitively Normal Older Adults: A 4-Year Longitudinal Follow-Up.

We aimed to longitudinally assess the relationship between changing brain energy metabolism (glucose and acetoacetate) and cognition during healthy aging. Participants aged 71 ± 5 year underwent cognitive evaluation and quantitative positron emission tomography (PET) and magnetic resonance imaging (MRI) scans at baseline (N = 25) and two (N = 25) and four (N = 16) years later. During the follow-up, the rate constant for brain extraction of glucose (Kglc) declined by 6%-12% mainly in the temporo-parietal lobes and cingulate gyri (p ≤ 0.05), whereas brain acetoacetate extraction (Kacac) and utilization remained unchanged in all brain regions (p ≥ 0.06). Over the 4 years, cognitive results remained within the normal age range but an age-related decline was observed in processing speed. Kglc in the caudate was directly related to performance on several cognitive tests (r = +0.41 to +0.43, all p ≤ 0.04). Peripheral insulin resistance assessed by the homeostasis model assessment of insulin resistance (HOMA-IR) was significantly inversely related to Kglc in the thalamus (r = -0.44, p = 0.04) and in the caudate (r = -0.43, p = 0.05), and also inversely related to executive function, attention and processing speed (r = -0.45 to -0.53, all p ≤ 0.03). We confirm in a longitudinal setting that the age-related decline in Kglc is directly associated with declining performance on some tests of cognition but does not significantly affect Kacac.

Ketogenic Medium Chain Triglycerides Increase Brain Energy Metabolism in Alzheimer's Disease.

BACKGROUND: In Alzheimer's disease (AD), it is unknown whether the brain can utilize additional ketones as fuel when they are derived from a medium chain triglyceride (MCT) supplement. OBJECTIVE: To assess whether brain ketone uptake in AD increases in response to MCT as it would in young healthy adults. METHODS: Mild-moderate AD patients sequentially consumed 30 g/d of two different MCT supplements, both for one month: a mixture of caprylic (55%) and capric acids (35%) (n = 11), followed by a wash-out and then tricaprylin (95%; n = 6). Brain ketone (11C-acetoacetate) and glucose (FDG) uptake were quantified by PET before and after each MCT intervention. RESULTS: Brain ketone consumption doubled on both types of MCT supplement. The slope of the relationship between plasma ketones and brain ketone uptake was the same as in healthy young adults. Both types of MCT increased total brain energy metabolism by increasing ketone supply without affecting brain glucose utilization. CONCLUSION: Ketones from MCT compensate for the brain glucose deficit in AD in direct proportion to the level of plasma ketones achieved.

Faster progression from MCI to probable AD for carriers of a single-nucleotide polymorphism associated with type 2 diabetes.

Sporadic Alzheimer's disease (AD), as opposed to its autosomal dominant form, is likely caused by a complex interaction of genetic, environmental, and health lifestyle factors. Twin studies indicate that sporadic AD heritability could be between 58% and 79%, around half of which is explained by the ε4 allele of the apolipoprotein E (APOE4). We hypothesized that genes associated with known risk factors for AD, namely hypertension, hypercholesterolemia, obesity, diabetes, and cardiovascular disease, would contribute significantly to the remaining heritability. We analyzed 22 AD-associated single-nucleotide polymorphisms (SNPs), associated with these risk factors, that were included in the sequencing data of the Alzheimer's Disease Neuroimaging Initiative 1 data set, which included 355 participants with mild cognitive impairment (MCI). We built survival models with the selected SNPs to predict progression of MCI to probable AD over the 10-year follow-up of the study. The rs391300 SNP, located on the serine racemase (SRR) gene and linked to increased susceptibility to type 2 diabetes, was associated with progression from MCI to probable AD.

Application of calibrated fMRI in Alzheimer's disease.

Calibrated fMRI based on arterial spin-labeling (ASL) and blood oxygen-dependent contrast (BOLD), combined with periods of hypercapnia and hyperoxia, can provide information on cerebrovascular reactivity (CVR), resting blood flow (CBF), oxygen extraction fraction (OEF), and resting oxidative metabolism (CMRO2). Vascular and metabolic integrity are believed to be affected in Alzheimer's disease (AD), thus, the use of calibrated fMRI in AD may help understand the disease and monitor therapeutic responses in future clinical trials. In the present work, we applied a calibrated fMRI approach referred to as Quantitative O2 (QUO2) in a cohort of probable AD dementia and age-matched control participants. The resulting CBF, OEF and CMRO2 values fell within the range from previous studies using positron emission tomography (PET) with 15O labeling. Moreover, the typical parietotemporal pattern of hypoperfusion and hypometabolism in AD was observed, especially in the precuneus, a particularly vulnerable region. We detected no deficit in frontal CBF, nor in whole grey matter CVR, which supports the hypothesis that the effects observed were associated specifically with AD rather than generalized vascular disease. Some key pitfalls affecting both ASL and BOLD methods were encountered, such as prolonged arterial transit times (particularly in the occipital lobe), the presence of susceptibility artifacts obscuring medial temporal regions, and the challenges associated with the hypercapnic manipulation in AD patients and elderly participants. The present results are encouraging and demonstrate the promise of calibrated fMRI measurements as potential biomarkers in AD. Although CMRO2 can be imaged with 15O PET, the QUO2 method uses more widely available imaging infrastructure, avoids exposure to ionizing radiation, and integrates with other MRI-based measures of brain structure and function.

Regional Brain Glucose Hypometabolism in Young Women with Polycystic Ovary Syndrome: Possible Link to Mild Insulin Resistance.

OBJECTIVE: To investigate whether cerebral metabolic rate of glucose (CMRglu) is altered in normal weight young women with polycystic ovary syndrome (PCOS) who exhibit mild insulin resistance. MATERIALS AND METHODS: Seven women with PCOS were compared to eleven healthy female controls of similar age, education and body mass index. Regional brain glucose uptake was quantified using FDG with dynamic positron emission tomography and magnetic resonance imaging, and its potential relationship with insulin resistance assessed using the updated homeostasis model assessment (HOMA2-IR). A battery of cognitive tests was administered to evaluate working memory, attention and executive function. RESULTS: The PCOS group had 10% higher fasting glucose and 40% higher HOMA2-IR (p ≤ 0.035) compared to the Controls. The PCOS group had 9-14% lower CMRglu in specific regions of the frontal, parietal and temporal cortices (p ≤ 0.018). A significant negative relation was found between the CMRglu and HOMA2-IR mainly in the frontal, parietal and temporal cortices as well as in the hippocampus and the amygdala (p ≤ 0.05). Globally, cognitive performance was normal in both groups but scores on the PASAT test of working memory tended to be low in the PCOS group. CONCLUSIONS: The PCOS group exhibited a pattern of low regional CMRglu that correlated inversely with HOMA2-IR in several brain regions and which resembled the pattern seen in aging and early Alzheimer's disease. These results suggest that a direct association between mild insulin resistance and brain glucose hypometabolism independent of overweight or obesity can exist in young adults in their 20s. Further investigation of the influence of insulin resistance on brain glucose metabolism and cognition in younger and middle-aged adults is warranted.

Lower brain 18F-fluorodeoxyglucose uptake but normal 11C-acetoacetate metabolism in mild Alzheimer's disease dementia.

BACKGROUND: The cerebral metabolic rate of glucose (CMRg) is lower in specific brain regions in Alzheimer's disease (AD). The ketones, acetoacetate and ß-hydroxybutyrate, are the brain's main alternative energy substrates to glucose. OBJECTIVE: To gain insight into brain fuel metabolism in mild AD dementia by determining whether the regional CMR and the rate constant of acetoacetate (CMRa and Ka, respectively) reflect the same metabolic deficit reported for cerebral glucose uptake (CMRg and Kg). METHODS: Mild AD dementia (Mild AD; n = 10, age 76 y) patients were compared with gender- and age-matched cognitively normal older adults (Controls; n = 29, age 75 y) using a PET/MRI protocol and analyzed with both ROI- and voxel-based methods. RESULTS: ROI-based analysis showed 13% lower global CMRg in the gray matter of mild AD dementia versus Controls (34.2 ± 5.0 versus 38.3 ± 4.7 µmol/100 g/min, respectively; p = 0.015), with CMRg and Kg in the parietal cortex, posterior cingulate, and thalamus being the most affected (p ≤ 0.022). Neither global nor regional CMRa or Ka differed between the two groups (all p ≥ 0.188). Voxel-based analysis showed a similar metabolic pattern to ROI-based analysis with seven clusters of significantly lower CMRg in the mild AD dementia group (uncorrected p ≤ 0.005) but with no difference in CMRa. CONCLUSION: Regional brain energy substrate hypometabolism in mild AD dementia may be specific to impaired glucose uptake and/or utilization. This suggests a potential avenue for compensating brain energy deficit in AD dementia with ketones.

Glucose hypometabolism is highly localized, but lower cortical thickness and brain atrophy are widespread in cognitively normal older adults.

Several studies have suggested that glucose hypometabolism may be present in specific brain regions in cognitively normal older adults and could contribute to the risk of subsequent cognitive decline. However, certain methodological shortcomings, including a lack of partial volume effect (PVE) correction or insufficient cognitive testing, confound the interpretation of most studies on this topic. We combined [(18)F]fluorodeoxyglucose ([(18)F]FDG) positron emission tomography (PET) and magnetic resonance (MR) imaging to quantify cerebral metabolic rate of glucose (CMRg) as well as cortical volume and thickness in 43 anatomically defined brain regions from a group of cognitively normal younger (25 ± 3 yr old; n = 25) and older adults (71 ± 9 yr old; n = 31). After correcting for PVE, we observed 11-17% lower CMRg in three specific brain regions of the older group: the superior frontal cortex, the caudal middle frontal cortex, and the caudate (P ≤ 0.01 false discovery rate-corrected). In the older group, cortical volumes and cortical thickness were 13-33 and 7-18% lower, respectively, in multiple brain regions (P ≤ 0.01 FDR correction). There were no differences in CMRg between individuals who were or were not prescribed antihypertensive medication. There were no significant correlations between CMRg and cognitive performance or metabolic parameters measured in fasting plasma. We conclude that highly localized glucose hypometabolism and widespread cortical thinning and atrophy can be present in older adults who are cognitively normal, as assessed using age-normed neuropsychological testing measures.

Brain glucose and acetoacetate metabolism: a comparison of young and older adults.

The extent to which the age-related decline in regional brain glucose uptake also applies to other important brain fuels is presently unknown. Ketones are the brain's major alternative fuel to glucose, so we developed a dual tracer positron emission tomography protocol to quantify and compare regional cerebral metabolic rates for glucose and the ketone, acetoacetate. Twenty healthy young adults (mean age, 26 years) and 24 healthy older adults (mean age, 74 years) were studied. In comparison with younger adults, older adults had 8 ± 6% (mean ± SD) lower cerebral metabolic rates for glucose in gray matter as a whole (p = 0.035), specifically in several frontal, temporal, and subcortical regions, as well as in the cingulate and insula (p ≤ 0.01, false discovery rate correction). The effect of age on cerebral metabolic rates for acetoacetate in gray matter did not reach significance (p = 0.11). Rate constants (min(-1)) of glucose (Kg) and acetoacetate (Ka) were significantly lower (-11 ± 6%; [p = 0.005], and -19 ± 5%; [p = 0.006], respectively) in older adults compared with younger adults. There were differential effects of age on Kg and Ka as seen by significant interaction effects in the caudate (p = 0.030) and post-central gyrus (p = 0.023). The acetoacetate index, which expresses the scaled residuals of the voxel-wise linear regression of glucose on ketone uptake, identifies regions taking up higher or lower amounts of acetoacetate relative to glucose. The acetoacetate index was higher in the caudate of young adults when compared with older adults (p ≤ 0.05 false discovery rate correction). This study provides new information about glucose and ketone metabolism in the human brain and a comparison of the extent to which their regional use changes during normal aging.

Stimulation of mild, sustained ketonemia by medium-chain triacylglycerols in healthy humans: estimated potential contribution to brain energy metabolism.

OBJECTIVE: In humans consuming a normal diet, we investigated 1) the capacity of a medium-chain triacylglycerol (MCT) supplement to stimulate and sustain ketonemia, 2) ¹³C-ß-hydroxybutyrate and ¹³C-trioctanoate metabolism, and 3) the theoretical contribution of the degree of ketonemia achieved to brain energy metabolism. METHODS: Eight healthy adults (26 ± 1 y old) were given an MCT supplement for 4 wk (4 times/d; total of 20 g/d for 1 wk followed by 30 g/d for 3 wk). Ketones, glucose, triacylglycerols, cholesterol, free fatty acids, and insulin were measured over 8 h during two separate metabolic study days before and after MCT supplementation. Using isotope ratio mass spectroscopy, ¹³C-D-ß-hydroxybutyrate and ¹³C-trioctanoate ß-oxidation to ¹³CO2 was measured over 12 h on the pre- and post-MCT metabolic study days. RESULTS: On the post-MCT metabolic study day, plasma ketones (ß-hydroxybutyrate plus acetoacetate) peaked at 476 µM, with a mean value throughout the study day of 290 µM. Post-MCT, ¹³C-trioctanoate ß-oxidation was significantly lower 1 to 8 h later but higher 10 to 12 h later. MCT supplementation did not significantly alter ¹³C-D-ß-hydroxybutyrate oxidation. CONCLUSIONS: This MCT supplementation protocol was mildly and safely ketogenic and had no side effects in healthy humans on their regular diet. This degree of ketonemia is estimated to contribute up to 8% to 9% of brain energy metabolism.

A dual tracer PET-MRI protocol for the quantitative measure of regional brain energy substrates uptake in the rat.

We present a method for comparing the uptake of the brain's two key energy substrates: glucose and ketones (acetoacetate [AcAc] in this case) in the rat. The developed method is a small-animal positron emission tomography (PET) protocol, in which (11)C-AcAc and (18)F-fluorodeoxyglucose ((18)F-FDG) are injected sequentially in each animal. This dual tracer PET acquisition is possible because of the short half-life of (11)C (20.4 min). The rats also undergo a magnetic resonance imaging (MRI) acquisition seven days before the PET protocol. Prior to image analysis, PET and MRI images are coregistered to allow the measurement of regional cerebral uptake (cortex, hippocampus, striatum, and cerebellum). A quantitative measure of (11)C-AcAc and (18)F-FDG brain uptake (cerebral metabolic rate; µmol/100 g/min) is determined by kinetic modeling using the image-derived input function (IDIF) method. Our new dual tracer PET protocol is robust and flexible; the two tracers used can be replaced by different radiotracers to evaluate other processes in the brain. Moreover, our protocol is applicable to the study of brain fuel supply in multiple conditions such as normal aging and neurodegenerative pathologies such as Alzheimer's and Parkinson's diseases.

The ketogenic diet increases brain glucose and ketone uptake in aged rats: a dual tracer PET and volumetric MRI study.

Despite decades of study, it is still unclear whether regional brain glucose uptake is lower in the cognitively healthy elderly. Whether regional brain uptake of ketones (ß-hydroxybutyrate and acetoacetate [AcAc]), the main alternative brain fuel to glucose, changes with age is unknown. We used a sequential, dual tracer positron emission tomography (PET) protocol to quantify brain (18)F-fluorodeoxyglucose ((18)F-FDG) and (11)C-AcAc uptake in two studies with healthy, male Sprague-Dawley rats: (i) Aged (21 months; 21M) versus young (4 months; 4M) rats, and (ii) The effect of a 14 day high-fat ketogenic diet (KD) on brain (18)F-FDG and (11)C-AcAc uptake in 24 month old rats (24M). Similar whole brain volumes assessed by magnetic resonance imaging, were observed in aged 21M versus 4M rats, but the lateral ventricles were 30% larger in the 21M rats (p=0.001). Whole brain cerebral metabolic rates of AcAc (CMR(AcAc)) and glucose (CMR(glc)) did not differ between 21M and 4M rats, but were 28% and 44% higher, respectively, in 24M-KD compared to 24M rats. The region-to-whole brain ratio of CMR(glc) was 37-41% lower in the cortex and 40-45% lower in the cerebellum compared to CMR(AcAc) in 4M and 21M rats. We conclude that a quantitative measure of uptake of the brain's two principal exogenous fuels was generally similar in healthy aged and young rats, that the % of distribution across brain regions differed between ketones and glucose, and that brain uptake of both fuels was stimulated by mild, experimental ketonemia.

Brain fuel metabolism, aging, and Alzheimer's disease.

Lower brain glucose metabolism is present before the onset of clinically measurable cognitive decline in two groups of people at risk of Alzheimer's disease--carriers of apolipoprotein E4, and in those with a maternal family history of AD. Supported by emerging evidence from in vitro and animal studies, these reports suggest that brain hypometabolism may precede and therefore contribute to the neuropathologic cascade leading to cognitive decline in AD. The reason brain hypometabolism develops is unclear but may include defects in brain glucose transport, disrupted glycolysis, and/or impaired mitochondrial function. Methodologic issues presently preclude knowing with certainty whether or not aging in the absence of cognitive impairment is necessarily associated with lower brain glucose metabolism. Nevertheless, aging appears to increase the risk of deteriorating systemic control of glucose utilization, which, in turn, may increase the risk of declining brain glucose uptake, at least in some brain regions. A contributing role of deteriorating glucose availability to or metabolism by the brain in AD does not exclude the opposite effect, i.e., that neurodegenerative processes in AD further decrease brain glucose metabolism because of reduced synaptic functionality and hence reduced energy needs, thereby completing a vicious cycle. Strategies to reduce the risk of AD by breaking this cycle should aim to (1) improve insulin sensitivity by improving systemic glucose utilization, or (2) bypass deteriorating brain glucose metabolism using approaches that safely induce mild, sustainable ketonemia.