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第一章 代谢切换：从葡萄糖到酮体

5D Library › 酮体代谢、β-羟丁酸信号转导与间歇性禁食的生物能量学 · English

第一章 代谢切换：从葡萄糖到酮体

一夜之间发生了什么

马特森等人把进食与禁食之间的燃料转换称为代谢切换：从以葡萄糖为主、由进食后的糖原储备支撑的状态，切换到以脂肪酸和酮体为主的状态 (Mattson et al. 2018)。切换的触发点是肝糖原的减少。本章先算清楚这几种燃料的化学账，再用一个简化的两室模型描述切换的时间进程。

糖与脂肪的竞争：兰德尔循环

1963 年，兰德尔等人在离体心肌和膈肌上发现，脂肪酸的氧化会抑制葡萄糖的利用，他们称之为葡萄糖–脂肪酸循环，后人通常叫它兰德尔循环 (Randle et al. 1963)。机制大致是：脂肪酸氧化产生的乙酰辅酶 A 和 NADH 抑制丙酮酸脱氢酶，柠檬酸积累抑制磷酸果糖激酶，于是葡萄糖的氧化减慢。休与泰格特迈尔后来回顾这一理论时指出，它也有反方向的一半：葡萄糖充足时，丙二酰辅酶 A 抑制脂肪酸进入线粒体，脂肪酸的氧化也被抑制 (Hue and Taegtmeyer 2009)。

这种相互竞争在禁食中有一个重要的生理意义：当肝糖原减少、胰岛素下降时，肌肉和心脏更多地使用脂肪酸，把有限的葡萄糖留给大脑和红细胞这些必须用葡萄糖的组织。

酮体从哪里来

酮体有三种：乙酰乙酸、D-β-羟丁酸（下文简称 BHB）和丙酮。它们由肝脏用脂肪酸制造。脂肪酸在肝细胞线粒体内经 β-氧化生成乙酰辅酶 A；当乙酰辅酶 A 的生成超过三羧酸循环的处理能力时，两分子乙酰辅酶 A 经 HMG-CoA 途径合成一分子乙酰乙酸。乙酰乙酸一部分被 β-羟丁酸脱氢酶用 NADH 还原为 BHB，一部分自发脱羧生成丙酮，丙酮主要随呼吸排出 (Laffel 1999)。

肝脏缺乏利用酮体的关键酶琥珀酰辅酶 A：3-氧酸辅酶 A 转移酶（SCOT），所以它只造酮体、不用酮体，把酮体输出给其他组织。

推导

几种燃料的化学账：每分子产生的 ATP（按现代的 P/O 比，每个 NADH 2.5、每个 FADH2 1.5 个 ATP）、每消耗一分子氧产生的 ATP、呼吸商（二氧化碳与氧的比值），以及肝脏把一分子棕榈酸变成酮体时各方的收支。

# Stoichiometry of fuels. ATP yields use the modern P/O ratios (2.5 ATP per NADH, 1.5 per FADH2),
# 10 ATP per acetyl-CoA through the citric acid cycle, and count activation costs.
#   Glucose: 2 ATP + 2 NADH (glycolysis) + 2 pyruvate -> 2 acetyl-CoA (2 NADH) -> ~32 ATP
#            (30 if cytosolic NADH enters by the glycerol-phosphate shuttle).
#   Palmitate (C16): activation costs 2 ATP equivalents; 7 rounds of beta-oxidation give 7 FADH2,
#            7 NADH and 8 acetyl-CoA -> 106 ATP.
#   D-beta-hydroxybutyrate: BHB -> acetoacetate gives 1 NADH; acetoacetate is activated by
#            succinyl-CoA:3-oxoacid CoA-transferase (SCOT), which uses up the succinyl-CoA that
#            would otherwise have made 1 GTP; then 2 acetyl-CoA -> 21.5 ATP.
#   Acetoacetate: as BHB without the NADH -> 19 ATP.
FUELS = {   # name: (ATP per molecule, O2 consumed, CO2 produced, molar mass g/mol)
    "glucose":      (32.0, 6.0, 6, 180.16),
    "palmitate":    (106.0, 23.0, 16, 256.42),
    "BHB":          (2.5 + 20 - 1, 4.5, 4, 104.10),
    "acetoacetate": (20 - 1, 4.0, 4, 102.09),
}
print("fuel          ATP/molecule   ATP per O2   RQ (CO2/O2)   ATP per gram")
for name, (atp, o2, co2, mm) in FUELS.items():
    print(f"{name:13s} {atp:12.1f} {atp / o2:12.2f} {co2 / o2:13.2f} {atp / mm:14.3f}")

# Ketogenesis in the liver: how many ketone bodies can one palmitate give?
#   palmitate -> 8 acetyl-CoA; 2 acetyl-CoA -> acetoacetate (via HMG-CoA); so at most 4 AcAc.
#   AcAc + NADH -> BHB (beta-hydroxybutyrate dehydrogenase); AcAc -> acetone + CO2 (spontaneous).
acetyl = 16 // 2
print(f"one palmitate -> {acetyl} acetyl-CoA -> at most {acetyl // 2} acetoacetate"
      f" (+ {7} NADH and {7} FADH2 kept by the liver)")
# The liver keeps the beta-oxidation energy: 7 FADH2 + 7 NADH - 2 (activation) = 26 ATP if it
# exports acetoacetate; reducing all 4 to BHB spends 4 NADH (10 ATP), leaving 16.
liver_acac = 7 * 1.5 + 7 * 2.5 - 2
liver_bhb = liver_acac - 4 * 2.5
print(f"ATP kept by the liver per palmitate: {liver_acac:.0f} (exporting acetoacetate) or {liver_bhb:.0f} (exporting BHB)")
print(f"ATP other tissues get from 4 BHB: {4 * 21.5:.0f}; liver + tissues = {liver_bhb + 4 * 21.5:.0f}"
      f" vs {106} burning palmitate whole (the gap = 4 GTP lost at the SCOT step)")
# fuel          ATP/molecule   ATP per O2   RQ (CO2/O2)   ATP per gram
# glucose               32.0         5.33          1.00          0.178
# palmitate            106.0         4.61          0.70          0.413
# BHB                   21.5         4.78          0.89          0.207
# acetoacetate          19.0         4.75          1.00          0.186
# one palmitate -> 8 acetyl-CoA -> at most 4 acetoacetate (+ 7 NADH and 7 FADH2 kept by the liver)
# ATP kept by the liver per palmitate: 26 (exporting acetoacetate) or 16 (exporting BHB)
# ATP other tissues get from 4 BHB: 86; liver + tissues = 102 vs 106 burning palmitate whole (the gap = 4 GTP lost at the SCOT step)

几点值得注意。第一，按每分子氧计算，BHB（4.78）高于脂肪酸（4.61），但低于葡萄糖（5.33）。所以「酮体比葡萄糖更省氧」的说法不成立；它只比脂肪酸省氧。第二，SCOT 这一步消耗了本来会产生一个 GTP 的琥珀酰辅酶 A，所以经由酮体「转手」一次，整个机体比直接燃烧脂肪酸少得到 4 个 ATP（102 对 106），代价约 4%。第三，肝脏在造酮体时已经拿走了 β-氧化的大部分能量（输出 BHB 时自留 16 个 ATP），这正是肝脏在禁食中能够自给自足、又能为大脑供能的原因。

证据

欧文、卡希尔等人在 1967 年对长期禁食的肥胖受试者进行脑血管插管测量，发现禁食数周后，酮体可以提供大脑耗氧量的一半以上，葡萄糖的需求随之大幅下降 (Owen et al. 1967; Cahill 2006)。这项研究推翻了「大脑只能用葡萄糖」的旧观点。需要注意的是，长期禁食是在医学监护下进行的研究，不能作为个人实践的依据。

糖原耗竭的速度

肝脏储存的糖原在成人中大约有几十克到一百多克，具体数量因人、因前一天的饮食而异。罗思曼等人用核磁共振直接测量了禁食期间人肝糖原的变化，发现糖原在禁食的前二十多个小时中持续而大致线性地下降，在这段时间里，肝糖原分解提供的葡萄糖少于全身葡萄糖输出的一半，其余来自糖异生 (Rothman et al. 1991)。

推导

一个简化的两室模型：第一室是肝糖原，第二室是血中 BHB。肝糖原分解随储量减少而减慢；胰岛素/胰高血糖素指数随糖原减少而下降；指数越低，脂肪组织释放的游离脂肪酸越多，肝脏生酮受到的胰岛素「刹车」也越少；组织对酮体的摄取是可饱和的。参数是示意性的，只用来再现文献中大致的时间进程，不是拟合结果。

# A two-compartment model of the metabolic switch during a fast (illustrative, not fitted to data).
# Compartment 1: liver glycogen G (grams). Compartment 2: blood D-beta-hydroxybutyrate K (mmol/L).
# Time t = hours since the end of the evening meal. Ideas built in:
#  * liver glycogen is broken down to support blood glucose, more slowly as the store runs low
#    (it is roughly exhausted after about 24-36 h of fasting in adults);
#  * an insulin-to-glucagon index R falls as glycogen falls (R = 1 well fed, near 0 when exhausted);
#  * as R falls, adipose lipolysis rises (free fatty acids F) and the liver's ketogenesis is
#    released from insulin's brake (the Randle-cycle side: fatty acids then also spare glucose);
#  * ketone uptake by tissues is saturable, so blood levels rise steeply once production exceeds it.
G0 = 90.0                  # g liver glycogen after an evening meal (typical adult range ~ 70-110 g)
def rates(G, K, R_override=None):
    glyco = 3.2 * G / (G + 20.0)                         # g/h glycogenolysis
    R = R_override if R_override is not None else max(0.0, min(1.0, (G / G0) ** 1.5))
    F = 0.35 + 1.15 * (1 - R)                            # mmol/L free fatty acids
    keto = 0.25 * F / (1 + (R / 0.25) ** 2)              # mmol/L per h ketone production
    uptake = 1.0 * K / (K + 2.5)                        # saturable uptake and oxidation
    return glyco, R, F, keto, uptake

def fast(hours, dt=0.01, R_override=None, K0=0.08):
    G, K, out = G0, K0, {}
    for i in range(int(hours / dt) + 1):
        t = i * dt
        glyco, R, F, keto, up = rates(G, K, R_override)
        if abs(t - round(t)) < dt / 2 and round(t) % 6 == 0:
            out[round(t)] = (G, R, F, K)
        G = max(0.0, G - glyco * dt)
        K = max(0.0, K + (keto - up) * dt)
    return out

print(" hours | liver glycogen g | insulin/glucagon index | free fatty acids mM | blood BHB mM")
for t, (G, R, F, K) in fast(72).items():
    print(f"{t:6d} | {G:16.0f} | {R:22.2f} | {F:19.2f} | {K:12.2f}")
# Same model with the insulin index held low by a very-low-carbohydrate (ketogenic) diet:
for R in (0.30, 0.20, 0.10):
    K = fast(240, R_override=R)[240][3]
    print(f"insulin/glucagon index held at {R:.2f} (ketogenic diet): steady blood BHB ~ {K:.2f} mM")
#  hours | liver glycogen g | insulin/glucagon index | free fatty acids mM | blood BHB mM
#      0 |               90 |                   1.00 |                0.35 |         0.08
#      6 |               75 |                   0.75 |                0.63 |         0.03
#     12 |               60 |                   0.54 |                0.88 |         0.07
#     18 |               46 |                   0.36 |                1.08 |         0.17
#     24 |               33 |                   0.22 |                1.24 |         0.37
#     30 |               22 |                   0.12 |                1.36 |         0.69
#     36 |               13 |                   0.06 |                1.44 |         1.03
#     42 |                7 |                   0.02 |                1.48 |         1.27
#     48 |                3 |                   0.01 |                1.49 |         1.40
#     54 |                1 |                   0.00 |                1.50 |         1.46
#     60 |                1 |                   0.00 |                1.50 |         1.48
#     66 |                0 |                   0.00 |                1.50 |         1.49
#     72 |                0 |                   0.00 |                1.50 |         1.50
# insulin/glucagon index held at 0.30 (ketogenic diet): steady blood BHB ~ 0.34 mM
# insulin/glucagon index held at 0.20 (ketogenic diet): steady blood BHB ~ 0.60 mM
# insulin/glucagon index held at 0.10 (ketogenic diet): steady blood BHB ~ 1.06 mM
两室模型中肝糖原与血中 BHB 随禁食时间的变化。虚线标出 12、16、24 与 36 小时。参数是示意性的。

在这个模型中，一夜禁食（12 小时）后血中 BHB 只有约 0.07 mmol/L，与晚饭前几乎没有区别；24 小时约 0.4 mmol/L；36 小时约 1 mmol/L；48 小时后接近 1.5 mmol/L 的平台。这个平台是简化模型的产物；长时间禁食中血酮会在数天到数周内继续升高，可达数 mmol/L (Cahill 2006)。这个形状反映了两件事：只要肝糖原还多，胰岛素就不会降得很低，生酮就受到抑制；而一旦糖原减少到一定程度，生酮的增长快于组织摄取的增长，血酮就较快地升高。

模型给出的数字与教科书中描述的大致范围相符，但需要强调：个人之间的差别很大。前一天吃了多少碳水化合物、运动多少、体型与胰岛素敏感性，都会显著改变曲线的位置。用一般人群的曲线去推断自己的血酮水平，或者反过来，以血酮读数作为是否「禁食成功」的标准，都是不可靠的。

生酮饮食的情形与禁食不同：碳水化合物摄入长期很低，胰岛素指数保持在低水平，血酮稳定在一个平台上。模型中，指数保持在 0.10–0.30 时，BHB 稳定在约 0.3–1.1 mmol/L，与通常所说的「营养性酮症」范围（约 0.5–3 mmol/L）的低端部分重叠。

注

营养性酮症不是酮症酸中毒。 健康人在禁食或生酮饮食中，血中 BHB 通常不超过几个 mmol/L，酸碱平衡由胰岛素的残余分泌与肾脏共同维持。糖尿病酮症酸中毒则发生在胰岛素严重缺乏时，酮体可以升到十几 mmol/L，并伴有血液酸化，是危及生命的急症 (Laffel 1999)。服用 SGLT2 抑制剂的人可能在血糖不高的情况下发生酮症酸中毒，这是本书开头禁忌人群中特别列出它的原因 (Peters et al. 2015; U.S. Food and Drug Administration 2015)。

本章小结

代谢切换的化学基础是兰德尔循环与肝脏生酮。按每分子氧计算，酮体比脂肪酸高效，却比葡萄糖低效；经由酮体转手一次，机体损失约 4% 的 ATP。切换的时间进程由肝糖原决定：一夜禁食几乎不产生酮症，24–36 小时后血酮才明显升高，个体差异很大。下一章讨论一个更有争议的问题：如果酮体并不更省氧，为什么有人认为它让心脏和大脑工作得更好？

参考文献

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Mattson, Mark P., Keelin Moehl, Nathaniel Ghena, Maggie Schmaedick, and Aiwu Cheng. 2018. “Intermittent Metabolic Switching, Neuroplasticity and Brain Health.” Nature Reviews Neuroscience 19 (2): 63–80.
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Peters, Anne L., Elizabeth O. Buschur, John B. Buse, Pejman Cohan, Jamie C. Diner, and Irl B. Hirsch. 2015. “Euglycemic Diabetic Ketoacidosis: A Potential Complication of Treatment with Sodium-Glucose Cotransporter 2 Inhibition.” Diabetes Care 38 (9): 1687–93.
Randle, P. J., P. B. Garland, C. N. Hales, and E. A. Newsholme. 1963. “The Glucose Fatty-Acid Cycle: Its Role in Insulin Sensitivity and the Metabolic Disturbances of Diabetes Mellitus.” The Lancet 281 (7285): 785–89.
Rothman, Douglas L., Inga Magnusson, Lee D. Katz, Robert G. Shulman, and Gerald I. Shulman. 1991. “Quantitation of Hepatic Glycogenolysis and Gluconeogenesis in Fasting Humans with 13C NMR.” Science 254 (5031): 573–76.
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Fan, Y. (2026). Ketone Metabolism, β-Hydroxybutyrate Signalling and the Bioenergetics of Intermittent Fasting: From the Randle Cycle and Epigenetic Inhibition to Autophagy Kinetics, Read Beside Classical Chinese Fasting Texts [酮体代谢、β-羟丁酸信号转导与间歇性禁食的生物能量学] (Version 1.0.0). 5D Library. https://doi.org/10.5281/zenodo.23753263 · Licensed under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0).