Can neural network instability in schizophrenia be improved with a very low carbohydrate ketogenic diet?

精神分裂症的神经网络不稳定可以通过极低碳水化合物的生酮饮食来改善吗?

基本信息

  • 批准号:
    10689440
  • 负责人:
  • 金额:
    $ 11.17万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2021
  • 资助国家:
    美国
  • 起止时间:
    2021-09-01 至 2024-08-31
  • 项目状态:
    已结题

项目摘要

Wide ranging cognitive deficits are major drivers of functional decline and poor outcomes in people with schizophrenia (SZ). Antipsychotic medications do not target pathophysiological mechanisms thought to underlie these deficits. In the search for interventions targeting underlying cognitive impairment in schizophrenia, we look comprehensively beyond just the brain and 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, and not just the medications used to treat it, is associated with risk of Type 2 diabetes, cardiovascular morbidity and mortality, and more generally, accelerated aging. Even young people with SZ have increased risk of metabolic disease and cognitive deficits. Sadly, their life span is shortened by 15–20 years. 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. The premise of the work is based on recent evidence that ketogenic diets improve dynamic neural network instability, related to cognitive deficits, aging, and Type 2 diabetes. The rigor of the work rests on findings of (1) poor glucose homeostasis in SZ, (2) neural network instability in SZ, and (3) direct effects of ketosis on network instability. Unknown is whether ketogenic diets can improve network instability in people with SZ. 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 7Tesla 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. We will compare network stability following the two diets and consider the role of metabolic and inflammatory mechanisms in improvement of neural network instability. 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. A controlled ketogenic diet has never been tried in people with SZ, who suffer from both cognitive deficits and insulin resistance. At the end of this 2-year project, we will know 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.
广泛的认知缺陷是导致患者功能下降和预后不良的主要原因 精神分裂症(SZ)。抗精神病药物并不针对被认为是基础的病理生理机制 这些赤字。在寻找针对精神分裂症潜在认知障碍的干预措施时,我们 全面观察大脑之外,以及系统代谢失调的潜在作用。 胰岛素和葡萄糖代谢紊乱在药物治疗中被发现-幼稚的第一集SZ,这表明 SZ本身,而不仅仅是用于治疗它的药物,与患2型糖尿病、心血管疾病的风险有关 发病率和死亡率,更普遍地说,加速衰老。即使是患有SZ的年轻人也会增加风险 代谢性疾病和认知缺陷。可悲的是,它们的寿命缩短了15-20年。 虽然人类大脑的体积只占人体体积的2%,但它消耗了超过20%的能量,因此, 在深圳,大脑特别容易受到葡萄糖代谢失调的影响。而葡萄糖是 酮被认为是大脑的默认燃料,它提供的自由能量多27%,是 为大脑提供能量。酮类预防或改善各种与年龄相关的疾病,生酮饮食(70% 脂肪,20%蛋白质,10%碳水化合物)被认为是一种抗衰老和痴呆症的解毒剂。 这项工作的前提是基于最近的证据,即生酮饮食改善了动态神经网络 不稳定,与认知缺陷、衰老和2型糖尿病有关。这项工作的严谨性取决于(1)的发现 (2)深圳的神经网络不稳定;(3)酮症对神经网络的直接影响 不稳定。尚不清楚生酮饮食是否能改善SZ患者的网络不稳定性。 我们提出了一项基于神经网络的4周生酮饮食的机械性、前瞻性、临床先导研究。 超重/肥胖的SZ不稳定,有胰岛素抵抗的风险。将随机抽取70名SZ(40-65岁) 生酮饮食(n=35)或正常饮食(n=35)。静息状态7Tesla fMRI扫描将在 在四周的节食之后。将使用基线上的认知数据来确定其与网络的关系 在神经典型性疾病中可以看到的不稳定,在深圳也可以看到。我们将比较这两种饮食方式下的网络稳定性 并考虑代谢和炎症机制在改善神经网络不稳定性中的作用。 这项工作将心血管新陈代谢和精神病学结合起来,以解决遇到的两个问题 精神分裂症患者:(1)与认知缺陷相关的神经网络不稳定,(2)胰岛素 耐药性与发病率和死亡率有关。控制性生酮饮食从未在人身上试验过 患有认知缺陷和胰岛素抵抗的SZ患者。在这个为期两年的项目结束时,我们将 了解葡萄糖代谢不足,至少部分是由初级或继发性胰岛素抵抗引起的, 导致精神分裂症网络不稳定,这是加速的病理生理机制 衰老和认知障碍的障碍。

项目成果

期刊论文数量(1)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
The Role of Ketogenic Metabolic Therapy on the Brain in Serious Mental Illness: A Review.
生酮代谢疗法对严重精神疾病中大脑的作用:综述。
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Judith M Ford其他文献

Judith M Ford的其他文献

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{{ truncateString('Judith M Ford', 18)}}的其他基金

CSRD Research Career Scientist Award Application
CSRD研究职业科学家奖申请
  • 批准号:
    10657600
  • 财政年份:
    2022
  • 资助金额:
    $ 11.17万
  • 项目类别:
Secondary data analysis of auditory steady-state response to explore the RDoC cognitive system constructs across the psychosis spectrum
听觉稳态反应的二次数据分析,以探索整个精神病谱系的 RDoC 认知系统结构
  • 批准号:
    10333412
  • 财政年份:
    2021
  • 资助金额:
    $ 11.17万
  • 项目类别:
Can neural network instability in schizophrenia be improved with a very low carbohydrate ketogenic diet?
精神分裂症的神经网络不稳定可以通过极低碳水化合物的生酮饮食来改善吗?
  • 批准号:
    10288095
  • 财政年份:
    2021
  • 资助金额:
    $ 11.17万
  • 项目类别:
Can neural network instability in schizophrenia be improved with a very low carbohydrate ketogenic diet?
精神分裂症的神经网络不稳定可以通过极低碳水化合物的生酮饮食来改善吗?
  • 批准号:
    10517239
  • 财政年份:
    2021
  • 资助金额:
    $ 11.17万
  • 项目类别:
Can neural network instability in schizophrenia be improved with a very low carbohydrate ketogenic diet?
精神分裂症的神经网络不稳定可以通过极低碳水化合物的生酮饮食来改善吗?
  • 批准号:
    10471918
  • 财政年份:
    2021
  • 资助金额:
    $ 11.17万
  • 项目类别:
Neural and cognitive consequences of COVID-19 survival.
COVID-19 生存对神经和认知的影响。
  • 批准号:
    10595562
  • 财政年份:
    2021
  • 资助金额:
    $ 11.17万
  • 项目类别:
Neural and cognitive consequences of COVID-19 survival.
COVID-19 生存对神经和认知的影响。
  • 批准号:
    10368420
  • 财政年份:
    2021
  • 资助金额:
    $ 11.17万
  • 项目类别:
Secondary data analysis of existing data to explore the RDoC construct of agency across the psychosis spectrum using fMRI and EEG
使用 fMRI 和 EEG 对现有数据进行二次数据分析,探索整个精神病谱系的 RDoC 代理结构
  • 批准号:
    9884515
  • 财政年份:
    2020
  • 资助金额:
    $ 11.17万
  • 项目类别:
Predictive Coding Abnormalities in Psychosis: EEG and fMRI
精神病中的预测编码异常:脑电图和功能磁共振成像
  • 批准号:
    9482228
  • 财政年份:
    2017
  • 资助金额:
    $ 11.17万
  • 项目类别:
Neural connectivity and dysconnectivity in schizophrenia: EEG and fMRI studies
精神分裂症的神经连接和连接失调:脑电图和功能磁共振成像研究
  • 批准号:
    8144017
  • 财政年份:
    2011
  • 资助金额:
    $ 11.17万
  • 项目类别:

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