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:
    10471918
  • 负责人:
  • 金额:
    $ 19.16万
  • 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.
广泛的认知缺陷是功能下降和不良结果的主要驱动因素, 精神分裂症(SZ)。抗精神病药物并不针对被认为是 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 全面地看待大脑以外的问题,以及系统代谢功能障碍的潜在作用。 胰岛素和葡萄糖代谢紊乱见于药物初治的首次发病SZ,表明 SZ本身,而不仅仅是用于治疗它的药物,与2型糖尿病,心血管疾病, 发病率和死亡率,以及更普遍的加速老化。即使是SZ的年轻人也增加了风险 代谢性疾病和认知缺陷。不幸的是,它们的寿命缩短了15-20年。 虽然人脑只占人体体积的2%,但它消耗了人体20%以上的能量,因此, 脑特别容易受到SZ中所见的葡萄糖代谢失调的影响。虽然葡萄糖是 被认为是大脑的默认燃料,酮提供27%以上的自由能,是大脑的主要来源。 大脑的能量。酮预防或改善各种年龄相关疾病,生酮饮食(70%) 脂肪,20%蛋白质,10%碳水化合物)被认为是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,生酮饮食改善动态神经网络 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。 SZ中葡萄糖稳态差,(2)SZ中神经网络不稳定,和(3)酮症对网络的直接影响 不稳定尚不清楚生酮饮食是否可以改善SZ患者的网络不稳定性。 我们提出了一个机制,前瞻性,临床试点研究的4周生酮饮食神经网络 超重/肥胖SZ不稳定,有胰岛素抵抗风险。将对70例SZ(40-65岁)进行随机化 生酮饮食(n=35)或常规饮食(n=35)。静息状态7特斯拉fMRI扫描将在 在4周的饮食之后。基线时的认知数据将用于确定其与网络的关系 不稳定,见于神经型,也见于SZ。我们将比较两种饮食后的网络稳定性 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。 这项工作汇集了心血管代谢和精神病学,以解决两个问题的经验 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 与发病率和死亡率相关的耐药性。控制生酮饮食从未在人类身上尝试过 与SZ,谁患有认知缺陷和胰岛素抵抗。在这个为期两年的项目结束时,我们将 了解葡萄糖代谢缺陷,至少部分由原发性或继发性胰岛素抵抗介导, 导致精神分裂症的网络不稳定,这是一种加速的病理生理机制, 衰老和认知障碍。

项目成果

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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:
    $ 19.16万
  • 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:
    $ 19.16万
  • 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:
    10689440
  • 财政年份:
    2021
  • 资助金额:
    $ 19.16万
  • 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:
    $ 19.16万
  • 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:
    $ 19.16万
  • 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:
    $ 19.16万
  • 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:
    $ 19.16万
  • 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:
    $ 19.16万
  • 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:
    $ 19.16万
  • 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:
    $ 19.16万
  • 项目类别:

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