Can Neural Network Instability in Schizophrenia be Improved With a Very Low Carbohydrate Ketogenic Diet?
a study on Schizophrenia
Cognitive deficits are major drivers of functional decline and poor outcomes in people with schizophrenia (SZ). In the search for interventions targeting underlying cognitive impairment in schizophrenia, we look to the potential role of dysfunctional systemic metabolism. Disrupted insulin and glucose metabolism are seen in medication-naïve first-episode SZ, suggesting that SZ itself is associated with risk of Type 2 diabetes, cardiovascular morbidity and mortality, and more generally, accelerated aging. Although the human brain is 2% of the body's volume, it consumes over 20% of its energy, and accordingly, the brain is particularly vulnerable to the dysregulation of glucose metabolism seen in SZ. While glucose is considered to be the brain's default fuel, ketones provide 27% more free energy and are a major source of energy for the brain. Ketones prevent or improve various age-associated diseases, and a ketogenic diet (70% fat, 20% protein, 10% carbohydrates) has been posited as an anti-aging and dementia antidote. Recent evidence suggests that ketogenic diets improve dynamic neural network instability, related to cognitive deficits, aging, and Type 2 diabetes. We propose a mechanistic, prospective, clinical pilot study of a 4-week ketogenic diet on neural network instability in overweight/obese SZ, at risk for insulin resistance. Seventy SZ (40-65 years old) will be randomized to a ketogenic diet (n=35) or diet-as-usual (n=35). Resting state 7 Tesla fMRI scans will be acquired before and after the 4-week diets. Cognitive data at baseline will be used to determine if its relationship with network instability, seen in neurotypicals, is also seen in SZ. Network stability following the two diets will be compared, and the role of metabolic and inflammatory mechanisms in improvement of neural network instability will be considered. This work brings together cardiovascular metabolism and psychiatry to address two problems experienced by people with schizophrenia: (1) neural network instability associated with cognitive deficits, and (2) insulin resistance associated with morbidity and mortality. At the end of this 2-year project, it will be known if deficient glucose metabolism, at least partially mediated by primary or secondary insulin-resistance, contributes to network instability in schizophrenia, a pathophysiological mechanism underlying accelerated aging and cognitive impairment in the disorder.
The diagnosis of schizophrenia (SZ) has traditionally been based on "positive symptoms," such as delusions and hallucinations, and "negative symptoms," such as anhedonia and amotivation. Although not part of the diagnostic criteria, wide ranging cognitive deficits are common, and they are major drivers of functional decline, as well as poor social and occupational outcomes experienced as illness chronicity sets in. While antipsychotic medications treat positive symptoms, they do not improve cognitive deficits in SZ, nor do they target pathophysiological mechanisms thought to underlie these deficits. Accordingly, in the search for interventions targeting brain dysfunction underlying cognitive impairment in SZ, the investigators will look comprehensively beyond the brain to the potential role of dysfunctional systemic metabolism, given that obesity, insulin resistance, and associated systemic inflammation are co-morbidities with SZ. Modern anti-psychotic medications disrupt metabolic homeostasis, which may contribute to the brain dysconnectivity thought to underlie cognitive deficits in SZ. However, schizophrenia itself has been associated with disrupted insulin and glucose metabolism, reported appearing well before the advent of antipsychotic treatment, and consistent with a recent meta-analysis indicating that these metabolic disturbances have been repeatedly observed in medication-naïve first-episode SZ. In fact, SZ and insulin resistance have been genetically linked. Thus, SZ itself is associated with metabolic disease, while the anti-psychotic medications used to treat SZ acutely induce insulin resistance, independent of food intake and weight gain, compounding the metabolic susceptibilities of SZ patients. The cause-and-consequence relationship of SZ and insulin resistance is unknown, and whether re-establishing metabolic homeostasis improves the underlying neural substrates of cognition is also unknown. The brain is an obligate "glucovore" and is particularly vulnerable to changes in glucose metabolism. Robust energy demands of the brain cannot be met by lipid transformation, and during times of glucose deprivation, they must be satisfied by ketone bodies. Disrupted central glucose metabolism, as observed in SZ patients, modulates peripheral metabolism by re-allocation of nutrients towards a brain-centric focus to maintain critical central functions. Low-carbohydrate high fat, or ketogenic, diets are an emerging therapy for insulin resistance, Type 2 diabetes, and associated co-morbidities. Increased ketones prevent or improve the symptoms of various age-associated diseases, reduce inflammation and the production of reactive oxygen species, and upregulate mitochondria in the brain. In addition, ketogenic diets have shown promise in a very small number of SZ patients, but without the needed controls. The premise of this proposal is based on a recent paper showing a ketogenic diet reduced 7T resting state fMRI neural network dynamic instability, a measure of how long a network of independent nodes maintains a stable connection. Instability is related to cognitive deficits, aging, and Type 2 diabetes in neurotypical adults. The investigator's fMRI data show similar network dynamic instability in SZ, adding to a larger literature showing static brain network dysconnectivity underlying neurocognitive deficits. Unknown is whether network instability in SZ can be rescued with a ketogenic diet, and whether improvements are mediated by ketogenic diet-induced increases in available ketone bodies as brain fuel, and/or with associated reductions in systemic inflammation and indices of metabolic syndrome. The rigor of the proposed work rests on findings of (a) poor glucose homeostasis in SZ, (b) neural network instability in SZ, and (c) direct effects of ketosis on network instability in neurotypical adults. Unknown is how ketogenic diets might improve network instability in overweight/obese SZ with risk of insulin resistance. The investigators propose a mechanistic, prospective, pilot clinical study comparing 4-weeks of ketogenic diet (KETO) vs. diet as usual (DAU) on neural network instability in SZ. They will randomize 70 overweight/obese SZ (40-65 years old, balanced for sex) to KETO (n=35) or DAU (n=35). KETO meals will be delivered to participants by Metabolic Meals. Metabolic, inflammatory, and 7T MRI data will be acquired before and after the 4-week diet. Aim 1: Assess changes in network instability with KETO and DAU in SZ over the 4-week period. Hypothesis 1: KETO, relative to DAU, will improve network stability. Aim 2: Establish metabolic and inflammatory indices as correlates of change in network instability with the KETO diet. Hypothesis 2: Improvements in network stability will be correlated with increased circulating ketone levels, and improved insulin sensitivity, reduced visceral fat, weight loss, and reduced systemic inflammation. Aim 3: Assess neuropsychological function at baseline to determine whether it is correlated with baseline network instability in SZ, similar to what has been reported in neurotypical adults. Hypothesis 3: Cognitive deficits will be related to network instability in SZ at baseline. The over-arching hypothesis is: Disrupted metabolic homeostasis contributes to neural network instability in SZ and that induction of ketosis restores it.
Schizophrenia ketogenic diet metabolic syndrome fMRI functional connectivity
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San Francisco California 94121 United States
Lead Scientist at UCSF
- Judith Ford, PhD
Professor, Psychiatry, School of Medicine. Authored (or co-authored) 165 research publications
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