The diagnosis of schizophrenia (SZ) and bipolar disorder (BPD) as 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, 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. Modern anti-psychotic medications disrupt metabolic homeostasis,
which may contribute to the brain dysconnectivity thought to underlie cognitive deficits.
However, both SZ and BPD have 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 these metabolic disturbances. In fact,
insulin resistance and both SZ and BPD have been genetically linked. Thus, SZ and BPD
themselves are associated with metabolic disease, while the anti-psychotic medications
acutely induce insulin resistance, independent of food intake and weight gain,
compounding the associated metabolic susceptibilities. The cause-and-consequence
relationship of these disorders 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 and BPD 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, 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 and BPD, adding to a larger literature
showing static brain network dysconnectivity underlying neurocognitive deficits. Unknown
is whether network instability 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 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
and BPD, (b) neural network instability in SZ and BPD, 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 and BPD 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 and BPD. They will randomize 70 SZ and BPD (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 and BD 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 and BD, similar to what has been
reported in neurotypical adults. Hypothesis 3: Cognitive deficits will be related to
network instability in SZ and BD at baseline. The over-arching hypothesis is: Disrupted
metabolic homeostasis contributes to neural network instability in SZ and BD and that
induction of ketosis restores it.
