Abstract

Objective

   Prolonged fasting (PF), defined as abstaining from energy intake for ≥4
   consecutive days, has gained interest as a potential health
   intervention. However, the biological effects of PF on the plasma
   proteome are not well understood.

Methods

   In this study, we investigated the effects of a medically supervised
   water-only fast (mean duration: 9.8 ± 3.1 days), followed by 5.3 ± 2.4
   days of guided refeeding, in 20 middle-aged volunteers (mean age: 52.2
   ± 11.8 years; BMI: 28.8 ± 6.4 kg/m^2).

Results

   Fasting resulted in a 7.7% mean weight loss and significant increases
   in serum beta-hydroxybutyrate (BHB), confirming adherence. Untargeted
   high-dimensional plasma proteomics (SOMAScan, 1,317 proteins) revealed
   multiple adaptations to PF, including preservation of skeletal muscle
   and bone, enhanced lysosomal biogenesis, increased lipid metabolism via
   PPARα signaling, and reduced amyloid fiber formation. Notably, PF
   significantly reduced circulating amyloid beta proteins Aβ40 and Aβ42,
   key components of brain amyloid plaques. In addition, PF induced an
   acute inflammatory response, characterized by elevated plasma
   C-reactive protein (CRP), hepcidin, midkine, and interleukin 8 (IL-8),
   among others. A retrospective cohort analysis of 1,422 individuals
   undergoing modified fasting confirmed increased CRP levels (from 2.8 ±
   0.1 to 4.3 ± 0.2 mg/L). The acute phase response, associated with
   transforming growth factor (TGF)-β signaling, was accompanied by
   increased platelet degranulation and upregulation of the complement and
   coagulation cascade, validated by ELISAs in blood and urine.

Conclusions

   While the acute inflammatory response during PF may serve as a
   transient adaptive mechanism, it raises concerns regarding potential
   cardiometabolic effects that could persist after refeeding. Further
   investigation is warranted to elucidate the long-term molecular and
   clinical implications of PF across diverse populations.

   Keywords: Prolonged fasting, Proteomics, Cardiometabolic, Inflammation

Highlights

     * •
       Prolonged water-only fasting induces weight loss, metabolic
       ketosis, and enhances lipid metabolism in volunteers.
     * •
       Prolonged fasting reduces circulating amyloid beta proteins, a key
       component of brain amyloid plaques.
     * •
       Prolonged fasting triggers inflammation and platelet activation,
       potentially impacting cardiometabolic health.

1. Introduction

   Prolonged fasting (PF), defined as abstaining from energy intake for ≥4
   consecutive days [[51]1], has been practiced throughout history for
   cultural, spiritual, and health-related reasons. Recently, it has
   gained renewed attention as a potential intervention to promote health
   and longevity by mitigating cellular aging, reducing inflammation, and
   lowering the risk of cardiovascular disease and cancer [[52]2,[53]3].
   However, the systemic biological adaptations to PF and its effects on
   inflammation remain unclear. Advances in high-throughput proteomics now
   enable the simultaneous measurement of thousands of plasma proteins
   with high specificity, providing a unique opportunity to investigate
   molecular adaptations to fasting and refeeding. Such an approach
   addresses the limitations of earlier studies, which were constrained to
   examining only a small number of specific preselected proteins.

   In this study, we examined 20 volunteers attending a fasting clinic
   before, during, and after an average 10-day water-only fast, followed
   by an average of 5 days of supervised refeeding with a plant-based
   diet. Using untargeted plasma proteomics with SOMAScan, we identified
   both potential benefits and drawbacks of PF and refeeding at the
   molecular level. PF triggered a significant shift in 6.6% of the plasma
   proteome; however, less than 1% of these proteins remained
   significantly altered after refeeding, supporting a transient effect.
   Contrary to our hypothesis, the primary outcome was a significant
   increase in inflammation and cytokine signaling via TGF-β, confirming
   that PF elevates inflammation. Additionally, we observed alterations in
   neutrophil and platelet degranulation, along with well-documented
   changes in IGF and PPARα signaling, key regulators of growth and lipid
   metabolism, respectively. Limited nutrient availability activated the
   PTEN, STAT3, and MAPK pathways, critical signal transducers that
   regulate cell proliferation in response to external stimuli. Notably,
   this study is the first to report that PF significantly reduced amyloid
   fiber formation and lowered circulating amyloid beta proteins Aβ40 and
   Aβ42, even though it did not affect their ratio. The findings were
   validated through targeted mass spectrometry and ELISAs in blood and
   urine samples, as well as in two external cohorts undergoing similar PF
   regimens. While PF is commonly associated with health benefits such as
   weight loss, our findings suggest its effects are more complex and
   multifaceted, with potential physiological benefits and drawbacks that
   require an individualized approach to fasting interventions.

2. Results

   We recruited 20 middle-aged volunteers (mean age: 52.2 ± 11.8 years;
   mean BMI: 28.8 ± 6.4 kg/m^2), including 11 women and 9 men.
   Participants were approached by the study team at TrueNorth Health
   Center, a facility offering medically supervised fasting. The study
   team operated independently from the Center. Volunteers followed a
   fasting and refeeding regimen, consisting of an average 9.8 ± 3.1-day
   water-only fast, followed by an average 5.3 ± 2.4 days of guided
   refeeding (Methods). Both fasting and refeeding procedures were based
   on previously established protocols [[54]4,[55]5]. Blood and urine
   samples were collected between 6 and 8 am to minimize diurnal
   variability, processed immediately, and stored at −80 °C for analysis.
   We conducted an untargeted high-dimensional proteomic analysis using
   SOMAScan, measuring plasma levels of 1,317 proteins [[56]6]. In
   addition, targeted mass spectrometry and ELISAs were employed to
   quantify specific biomarkers in blood and urine. The results were
   compared with two independent datasets of PF and modified fasting in
   humans, from Pietzner et al. (2024) and Wilhelmi de Toledo et al.
   (2019).

   At baseline, the average body weight of the volunteers was
   85.6 ± 25.6 kg in women and 87.9 ± 15.4 kg in men. By the end of the
   fasting period, participants experienced significant weight loss, with
   women losing 6.3 ± 1.7 kg and men losing 6.9 ± 2.2 kg (p < 0.0001),
   corresponding to reductions of 7.6% and 7.8% of baseline body weight,
   respectively. BMI decreased by an average of 2.2 ± 0.5 kg/m^2
   (p < 0.0001), a fractional decrease of 7.6%, while waist circumference
   was reduced by 6% (p < 0.0001). These reductions in body weight, BMI,
   and waist circumference persisted through the refeeding period
   ([57]Table 1). Mild adverse events were common, including headaches,
   weakness, fatigue, insomnia, dry mouth, and orthostatic hypotension
   ([58]Figure S1), prompting the transition to a broth and/or juice fast
   in six participants. Other adverse events included severe abdominal
   pain and diarrhea (n = 1), hypokalemia (n = 1), arrhythmias (n = 1),
   and dizziness and palpitations (n = 1). When feasible, blood and urine
   samples collected before this transition were used for analysis
   ([59]Figure S2). Adherence was high, with all participants exhibiting a
   physiological fasting response, as evidenced by significantly elevated
   serum beta-hydroxybutyrate (BHB) concentrations (p < 0.0001), which
   normalized during refeeding ([60]Table 1). The fasting-induced increase
   in BHB and its normalization with refeeding were significantly
   correlated with changes in inflammatory markers (midkine and IL-8),
   metabolic regulators (FGF19, leptin receptor, chemerin, growth hormone
   receptor), and MAPK signaling, a crucial mediator of cell proliferation
   ([61]Figure S3).

Table 1.

   Anthropometric measures and cardiometabolic effects of prolonged
   fasting in humans.
   Baseline Mean SD Fasting Mean SD P-value (Fasting vs Baseline)
   Refeeding Mean SD P-value (Refeeding vs Baseline)
   Sex, Female (%) 11 (55%) – – – – – – –
   Age (years) 52.2 11.8 – – – – – –
   Height (cm) 173.4 10.8 – – – – – –
   Weight (kg) 86.6 20.6 80.0 19.5 <0.0001 80.5 18.9 <0.0001
   BMI (kg/m^2) 28.8 6.4 26.6 6.2 <0.0001 26.7 6.0 <0.0001
   Waist (cm) 96.4 12.7 90.6 12.9 <0.0001 90.7 11.7 <0.0001
   DPB (mmHg) 72.1 8.7 64.5 6.7 0.0030 67.7 7.3 0.1857
   SBP (mmHg) 123.9 10.2 118.1 12.4 0.0301 116.8 12.1 0.0296
   β-hydroxybutyrate (mmol/L) 0.6 0.9 5.0 1.0 <0.0001 0.4 0.3 0.6215
   Glucose (mg/dL) 85.7 10.4 70.3 10.5 0.0002 92.8 9.7 0.0155
   HOMA-IR 1.7 1.5 0.8 1.1 0.0006 2.2 1.4 0.0266
   C-reactive protein (mg/dL) 1.7 1.5 3.9 3.8 0.0004 3.4 9.9 0.6542
   Total cholesterol (mg/dL) 192.0 33.5 216.6 47.8 0.0327 168.2 34.5
   0.0006
   HDL cholesterol (mg/dL) 56.8 19.2 47.8 12.3 0.0015 44.6 10.9 0.0007
   Triglycerides (mg/dL) 102.8 46.2 125.4 37.4 0.0745 135.2 47.2 0.0008
   LDL cholesterol (mg/dL) 108.4 37.4 131.6 55.5 0.0898 96.7 30.4 0.041
   Non-HDL cholesterol (mg/dL) 135.3 34.0 168.8 47.9 0.0061 123.6 33.5
   0.0523
   Total cholesterol:HDL ratio 3.8 1.5 4.8 1.5 0.0024 4.0 1.1 0.6152
   ALT (IU/L) 21.9 11.4 35.9 20.3 0.0003 34.4 19.4 0.0006
   AST (IU/L) 22.8 8.5 37.6 17.2 <0.0001 31.5 17.9 0.0350
   [62]Open in a new tab

   Data expressed as mean ± SD. Statistical significance was calculated
   using paired, 2-tailed Student's t or Wilcoxon signed rank test for
   non-normally distributed data. N = 20 participants, except for
   cholesterol measurements and triglycerides (N = 19). Significance
   levels are indicated as p-values.

2.1. Proteomics adaptations to prolonged fasting in humans

   We found that 6.6% of protein targets (n = 86/1317) exhibited
   significant changes by the end of fasting (adjusted p < 0.05), with 74
   proteins decreasing and 12 increasing ([63]Figure 1A). However, after
   five days of gradual refeeding, only 12 proteins (<1%) remained
   significantly altered, indicating that most fasting-induced proteomic
   changes are transient. The most significantly reduced proteins included
   key regulators of muscle homeostasis, such as inhibin beta A
   (INHBA, −3.3 fold, adjusted p = 9.07E-05), myostatin (−2 fold, adjusted
   p = 0.000466), and GDF11/8 (−1.6 fold, adjusted p = 0.000757), all
   members of the TGF-β superfamily ([64]Figure 1B). These proteins are
   vital for muscle regulation, likely reflecting the body's adaptive
   response to fasting, balancing muscle preservation with tissue repair
   during nutrient deprivation [[65]7]. Interestingly, inhibiting GDF11
   and myostatin has been linked to increased bone density and strength
   through enhanced osteoblast activity and suppressed osteoclastogenesis
   [[66]8,[67]9]. Consistent with this, plasma parathyroid hormone (PTH)
   levels decreased by 2.1-fold (adjusted p = 0.0045), suggesting a
   compensatory hormonal adjustment during fasting to slow bone loss.
   Under conditions of energy deprivation, the insulin-sensitizing
   adipokine adiponectin also decreased from 5643 ± 3282 ng/mL to
   4275 ± 2519 ng/mL (p < 0.0001) ([68]Figure 1C).

Figure 1.

   [69]Figure 1
   [70]Open in a new tab

   Proteomics adaptations to prolonged fasting in humans. (A) Volcano plot
   of differentially expressed SOMAScan plasma proteins during fasting
   from N = 15 participants. Significance cut-off adjusted p < 0.05.
   FC = End of Fasting/Baseline. (B) Individual changes in highlighted
   proteins from (A) normalized to baseline during fasting and refeeding.
   Each dot represents protein levels in each participant (N = 15).
   Adjusted p-value calculated with one-way ANOVA. (C) Absolute levels of
   plasma adiponectin measured by ELISA across three time points. Each dot
   represents levels in each participant (N = 20). (D) Volcano plot of
   differentially enriched canonical pathways in IPA with predicted
   activation (orange) or inhibition (blue). Input = 1,255 mapped SOMAScan
   proteins from (A). (E-F-G) Absolute levels of plasma Aβ42, Aβ40, and
   their ratio measured by IP-LC-MS/MS across three timepoints. N = 20
   participants. Statistical analysis is described in the Methods for each
   analysis. Significance levels are indicated as adjusted p-values,
   ∗p < 0.05, ∗∗p < 0.01, and ∗∗∗p < 0.001. For all graphs, BL = Baseline,
   EF = End of Fasting, ER = End of Refeeding.

   In contrast, proteins involved in energy, glucose, and bile acid
   metabolism significantly increased, with PPARα emerging as a key
   activated pathway ([71]Figures 1D, [72]S4). Regulated by free fatty
   acids, PPARα drives hepatic lipid metabolism and ketogenesis, a vital
   fasting adaptation. Another major fasting-activated pathway was the
   CLEAR (Coordinated Lysosomal Expression and Regulation) network, which
   governs lysosomal biogenesis and function. This pathway is crucial for
   autophagy and exocytosis, both essential for cellular maintenance and
   adaptation to nutrient scarcity. The gut hormone FGF19 also increased
   1.8-fold (adjusted p = 0.048) ([73]Figure 1B), playing a crucial role
   in energy metabolism by regulating bile acid synthesis, enhancing
   glucose utilization, and promoting hepatocyte proliferation [[74]10].
   In addition, the soluble leptin receptor increased significantly
   (2.2-fold, adjusted p = 0.002), facilitating appetite regulation by
   regulating leptin bioavailability in the bloodstream [[75]11,[76]12].
   The significant increases in FGF19 and the soluble leptin receptor were
   previously reported in an independent cohort undergoing a 7-day
   water-only fast by Pietzner et al. (2024) [[77]13]. This comparative
   cohort of 12 participants experienced an average weight loss of
   5.7 ± 0.8 kg, representing a 7.4% reduction in baseline body weight.
   Comparative proteomics analysis of both cohorts at the 7-day endpoint
   identified an overlap of 44 significantly decreased and 5 significantly
   increased proteins, with no discrepancies between studies
   ([78]Figure S5). Despite methodological differences (Olink vs.
   SOMAScan), Reactome pathway enrichment analysis revealed that most
   altered pathways were common to both datasets, particularly those
   related to neutrophil and platelet degranulation, as well as
   interleukin, MAPK, and PI3K/AKT signaling ([79]Figure S6). The findings
   highlight the highly conserved and universal nature of the
   physiological response to water-only PF.

   Additionally, PF was associated with a reduction in synaptogenesis
   pathways and amyloid fibril formation ([80]Figures 1D, [81]S4). An
   increasing trend in brain-derived neurotrophic factor (BDNF) levels was
   observed (1.32-fold, adjusted p = 0.18), which may support previous
   evidence of fasting's neuroprotective effects [[82]14]. While the
   predicted decrease in fibrillar formation was not specific to amyloid
   beta proteins, we hypothesize that it could reflect lower circulating
   amyloid beta levels. To investigate this, plasma levels of amyloid beta
   (Aβ) 42, 40, and the Aβ42/Aβ40 ratio - a diagnostic biomarker for brain
   amyloid plaques [[83]15]- were measured using mass spectrometry
   [[84]16,[85]17]. Interestingly, PF significantly reduced plasma
   concentrations of both Aβ42 and Aβ40 ([86]Figure 1E–G), suggesting
   either a decreased production rate or accelerated degradation of these
   amyloid peptides during fasting, with levels returning to baseline
   after refeeding. Even though the reduction in individual Aβ components
   may have potential beneficial implications for amyloidosis, the
   Aβ42/Aβ40 ratio, which is the validated biomarker used clinically to
   identify individuals with brain amyloid plaques [[87]18,[88]19],
   remained unchanged.

2.2. Prolonged fasting increases inflammation

   The primary outcome of our study was inflammation. SOMAScan plasma
   proteomics analysis revealed significant increases in well-established
   inflammatory markers, including hepcidin, ferritin, midkine, matrix
   metalloproteinase 9, IL-8, and platelet-activating factor
   acetylhydrolase (PAFAH or PLA2G7) ([89]Figure 2A,B). Contrary to our
   initial hypothesis that fasting would exert an anti-inflammatory
   effect, PF led to a pronounced 129% increase in circulating
   high-sensitivity C-reactive protein (hsCRP) levels measured by ELISA
   (Wilcoxon's p = 0.0004, ANOVA p = 0.0070), with levels returning to
   baseline after refeeding in all but one participant ([90]Table 1,
   [91]Figure 2C). The significant rise in hsCRP was positively correlated
   with C5 (involved in inflammation) and LILRB2 (regulating inflammation
   and axonal regeneration), and negatively associated with PCI
   (SERPINA5), hemojuvelin, and MED1 (adipogenesis) ([92]Figure 2D). At
   the pathway level, CRP was significantly associated with the TGF-β
   signaling pathway and the complement and coagulation cascade
   ([93]Figure 2E), suggesting that PF may activate the innate immune
   response through inflammation. To validate these findings in a broader
   population, we retrospectively analyzed data from 1,422 individuals who
   underwent medically supervised modified fasting at the
   Buchinger-Wilhelmi Clinic in Germany [[94]5]. In this comparative
   cohort, the average fasting duration was 8.2 ± 0.1 days, with an
   average weight loss of 4.3 ± 2.0 kg. Notably, 66.6% of participants
   experienced a significant increase in plasma CRP levels
   ([95]Figure 2F), confirming the acute inflammatory effect of PF across
   a larger cohort. Importantly, this increase in CRP was observed
   regardless of fasting duration (5, 10, 15, or 20 days).

Figure 2.

   [96]Figure 2
   [97]Open in a new tab

   Prolonged fasting increases inflammation. (A) All significantly
   upregulated SOMAScan proteins (n = 12) during fasting normalized to
   baseline (targets from volcano plot in [98]Figure 2A). Pro-inflammatory
   proteins are shown with light red background. N = 15 participants.
   FC = End of Fasting/Baseline (B) Individual changes in 6 inflammatory
   proteins from panel A during fasting and refeeding. Each dot represents
   protein levels in each participant. (C) Absolute hsCRP levels in the
   blood of each participant (N = 20) measured by ELISA across three time
   points. (D) Significantly correlated proteomic targets to CRP changes
   during fasting and refeeding (positive effect size = same changes;
   negative effect size = inverse changes). (E) Significantly enriched
   KEGG pathways relative to CRP changes. (F) Validation of CRP changes in
   an independent fasting cohort of 1,422 participants. Measurements of
   weight and CRP at baseline (BL, blue) and end of fasting (EF, orange)
   timepoints. The same variables are plotted by fasting length category.
   5d = 5 day fast, 10d = 10 day fast, 15d = 15 day fast, 20d = 20 day
   fast. Median, interquartile range, and outliers are shown, with notches
   representing the 95% confidence intervals. Statistical analysis is
   described in the Methods for each analysis. Significance levels are
   indicated as adjusted p-values, ∗p < 0.05, ∗∗p < 0.01, and
   ∗∗∗p < 0.001. For all graphs, BL = Baseline, EF = End of Fasting,
   ER = End of Refeeding.

   We also observed a significant increase in liver transaminases AST and
   ALT during fasting, with levels rising by 65% and 64%, respectively,
   and remaining elevated during refeeding ([99]Table 1). This elevation
   in liver enzymes, indicative of hepatic stress, was also observed in
   the Buchinger-Wilhelmi Clinic validation cohort ([100]Fig. S7). The
   concurrent rise in liver enzymes and inflammatory markers highlights
   the need for medical monitoring of individuals undergoing PF
   interventions.

2.3. Fasting and refeeding elevate biomarkers of platelet activation and
degranulation

   An unexpected finding was the observed increase in biomarkers and
   pathways associated with platelet activity during PF ([101]Figure 3).
   Reactome pathway enrichment analysis of the SOMAScan data revealed that
   PF influenced platelet degranulation, a process that facilitates
   thrombin generation by releasing fibrinogen and von Willebrand factor
   (vWF) from alpha granules at injury sites [[102]20]. Even though
   prothrombin levels remained unchanged (1-fold, adjusted p = 0.85), vWF
   and its receptor, soluble glycoprotein Ib alpha (GP1Bα), were mildly
   increased ([103]Figure 3A), correlating with elevated chemokines (e.g.,
   IL-8, CCL7, CCL11) ([104]Figure 3B). To confirm platelet degranulation,
   we measured urinary 11-dehydro-TXB2 levels via ELISA, an enzymatic
   product in the TXA2/TXB2 pathway primarily derived from activated
   platelets via cyclooxygenase-1 activity. Surprisingly, 11-dehydro-TXB2
   levels rose by 21% during fasting and 36% post-refeeding
   ([105]Figure 3C), with no change in platelet counts ([106]Figure 3D),
   indicating that increased degranulation, rather than heightened
   platelet production, drove the effect [[107]21]. Urinary
   11-dehydro-TXB2 is a gold standard biomarker of platelet activation and
   cardiovascular risk [[108]22]. The Framingham study highlights its
   predictive value for all-cause mortality, cardiovascular death, and
   major arterial events [[109]23]. In the ASCEND trial, it was
   significantly associated with future vascular events in nearly 8,000
   diabetic participants [[110]24,[111]25]. Therefore, our findings reveal
   a PF-induced phenotype characterized by interconnected inflammation and
   platelet activation, potentially affecting thrombotic risk in
   individuals with pre-existing conditions.

Figure 3.

   [112]Figure 3
   [113]Open in a new tab

   Fasting and refeeding elevate biomarkers of platelet activation and
   degranulation. (A) Individual changes in 4 platelet-associated proteins
   from SOMAScan normalized to baseline during fasting and refeeding. Each
   dot represents protein levels in each participant (N = 15). Adjusted
   p-value calculated with one-way ANOVA. (B) Volcano plot of vWF (effect
   size) on all 1,317 SOMAScan proteins during combined fasting and
   refeeding. Significance cut-off adjusted p < 0.01. N = 15 participants.
   (C) KEGG pathway enrichment analysis for proteins associated with vWF.
   Fold enrichments in KEGG pathway analysis are shown relative to fold
   changes for vWF. (D) Absolute TXB2 levels in the urine of each
   participant (N = 20) across three time points. (E) Absolute platelet
   counts in the blood of each participant (N = 20) across three time
   points. Statistical analysis is described in the Methods for each
   analysis. Significance levels are indicated as adjusted p-values,
   ∗p < 0.05, ∗∗p < 0.01, and ∗∗∗p < 0.001. For all graphs, BL = Baseline,
   EF = End of Fasting, ER = End of Refeeding.

2.4. Prolonged fasting affects cardiometabolic biomarkers

   In our study, PF induced significant changes in lipid profiles,
   including increases in plasma total cholesterol, non-HDL cholesterol,
   LDL cholesterol, and the total cholesterol/HDL ratio, all of which
   reversed after refeeding ([114]Table 1). Plasma triglycerides steadily
   increased, peaking with a 32% rise post-refeeding. Proteomics analysis
   revealed a significant 1.49-fold reduction in proprotein convertase
   subtilisin/kexin type 9 (PCSK9) (adjusted p = 0.008) at the end of
   fasting ([115]Figure 1B). This reduction likely decreased PCSK9 binding
   to LDL receptors, thereby preventing their degradation in liver cells
   [[116]26].

   In addition to lipid changes, serum glucose levels decreased from
   85.7 mg/dL to 70.3 mg/dL (18%) during fasting ([117]Table 1),
   reflecting the rewiring of whole-body metabolism upon depletion of
   glucose stores. Similarly, the adipokines chemerin (−1.7-fold, adjusted
   p = 0.0002) and fetuin B (FETUB) (−1.8-fold, adjusted p = 6.05E-05)
   were also decreased ([118]Figure 1A, B) [[119]25,[120]26]. During
   refeeding, glucose levels and HOMA-IR, an indicator of insulin
   resistance, increased significantly, reflecting enhanced glucose
   availability with the reintroduction of food.

2.5. Fasting and refeeding do not induce systemic changes in oxidation status

   While fasting has been suggested to reduce oxidative stress in animal
   models [[121]27], our proteomic analysis revealed a decrease in
   superoxide dismutase 3 (SOD3) levels (−1.3-fold, adjusted p = 0.003),
   an extracellular antioxidant enzyme crucial for redox balance.
   Additionally, the expected improvements in in vivo oxidation status
   were not observed. Using the validated urinary biomarker of lipid
   oxidation 8-iso-prostaglandin F2α [[122]25,[123]28], we found a
   heterogeneous oxidative response to fasting and refeeding. The result
   suggests that PF does not universally reduce oxidative stress in humans
   ([124]Fig. S8).

3. Discussion

   Throughout human evolution, extended periods of food scarcity were
   common, shaping metabolic flexibility as a survival mechanism. In the
   context of the global obesity epidemic, fasting has resurged as a
   popular, sometimes extreme, weight-loss strategy [[125]2,[126]29].
   However, the body's adaptations to PF and its potential health effects
   remain poorly understood. Our study offers a comprehensive proteomic
   analysis of the responses to PF and refeeding, uncovering both
   beneficial and potentially detrimental effects. Consistent with
   previous research [[127]13], we uncovered changes in multiple proteins
   involved in skeletal muscle and bone homeostasis (INHBA, myostatin,
   GDF11/8, PTH). Interestingly, exogenous GDF11 has been shown to
   function as a calorie restriction mimetic in mice, stimulating
   adiponectin secretion and improving insulin sensitivity [[128]30]. The
   acute inflammatory response triggered by PF warrants further
   investigation to clarify its clinical significance, and it is
   consistent with a clinical study demonstrating that a 10-day water-only
   fast triggers an inflammatory transcriptional signature in adipose
   tissue [[129]31]. In our study, inflammation was accompanied by
   evidence of platelet degranulation, raising concerns as elevated
   urinary TXB2 has been linked to accelerated atherogenesis and increased
   cardiovascular risk [[130]24,[131]32]. The inflammatory profile
   characterized by elevated hsCRP, IL-8, and activation of TGF-β and
   complement pathways resembles the hallmark features of trained immunity
   [[132]33], suggesting that PF may serve as an endogenous trigger for
   this adaptive immune mechanism. However, the immune effects of PF are
   complex and context-dependent, with evidence supporting fasting-induced
   modulation of immunosenescence and immune response during immunotherapy
   [[133]2,[134][34], [135][35], [136][36]].

   Prior studies of the adipose tissue transcriptome have linked
   inflammatory pathways to insulin resistance [[137][37], [138][38],
   [139][39]]. Consistently, our data show that PF is associated with
   elevated HOMA-IR. Additionally, increased triglycerides and liver
   transaminases suggest that prolonged nutrient deprivation, unlike
   moderate calorie restriction, may disrupt lipoprotein metabolism and
   liver function [[140][40], [141][41], [142][42], [143][43]].

   Furthermore, this study is the first to demonstrate that PF lowers
   plasma Aβ42 and Aβ40, key components of amyloid plaques implicated in
   Alzheimer's disease pathology [[144]44]. These findings suggest that
   nutrient deprivation alters amyloid precursor protein (APP) expression
   or processing, influencing either the production or clearance of plasma
   Aβ42 and Aβ40. Importantly, PF did not affect the Aβ42/40 ratio, a
   validated biomarker for brain amyloid plaques [[145]18]. This supports
   the notion that the Aβ42/40 ratio, rather than individual
   concentrations, is a robust biomarker, as it accounts for
   inter-individual variability in pre-analytical conditions [[146]45] and
   presence of comorbidities [[147]46].

   Our study has several strengths and limitations. Strengths include the
   use of two methodologies (mass spectrometry and ELISA) across
   biological samples (plasma and urine), which yielded consistent
   findings. Multiple biomarkers were assessed in an untargeted approach,
   reducing reliance on a single marker, and results were validated in two
   independent cohorts. Limitations include the single-arm design with a
   lack of control group, the small sample size, and the variability in
   fasting and refeeding durations decided by the volunteers.

   In summary, our study reveals a multifaceted proteomic response to PF,
   extending beyond the traditional adipose-centric or energy homeostasis
   framework. We identified elevated biomarkers related to muscle and bone
   preservation, reduced amyloid formation, increased inflammation and
   platelet activity, and lipid metabolism. By conducting a comparative
   analysis in an independent cohort, we identify a universal signature of
   the physiological response to water-only PF, observing no differences
   between studies despite variations in cohort characteristics and
   methodology. However, we also observed substantial inter-individual
   variability at the molecular level, emphasizing the need for
   personalized fasting regimens. In contrast, oxidation status remained
   unchanged, with no evidence of antioxidant effects. The acute
   inflammatory response, also observed in an independent cohort, may
   reflect a positive adaptive mechanism. However, it also raises concerns
   about a potentially adverse cardiometabolic phenotype, particularly for
   individuals with thrombotic conditions or unstable atherosclerotic
   plaques. This mirrors data from exercise interventions, where acute
   vigorous physical activity can transiently increase cardiovascular
   risk, particularly in untrained individuals or those with underlying
   conditions. However, with appropriate progressive training, long-term
   beneficial adaptations occur, leading to reduced cardiovascular
   mortality [[148]47]. Unlike exercise, where dose-response relationships
   and adaptations are well-established, our understanding of how repeated
   PF bouts impact long-term molecular, metabolic, and clinical outcomes
   remains limited, highlighting the need for further research.

CRediT authorship contribution statement

   Serena Commissati: Methodology, Investigation. Maria Lastra Cagigas:
   Writing – original draft, Visualization, Funding acquisition, Formal
   analysis, Data curation. Andrius Masedunskas: Writing – review &
   editing, Visualization, Software, Formal analysis. Giovanna Petrucci:
   Methodology, Data curation. Valeria Tosti: Methodology, Data curation.
   Isabella De Ciutiis: Writing – review & editing. Gayathiri Rajakumar:
   Writing – review & editing. Kristopher M. Kirmess: Writing – review &
   editing, Methodology. Matthew R. Meyer: Writing – review & editing,
   Methodology. Alan Goldhamer: Writing – review & editing, Resources.
   Brian K. Kennedy: Writing – review & editing, Supervision, Resources.
   Duaa Hatem: Methodology. Bianca Rocca: Writing – review & editing,
   Validation, Methodology, Data curation. Giovanni Fiorito: Writing –
   review & editing, Visualization, Validation, Software, Formal analysis.
   Luigi Fontana: Writing – review & editing, Writing – original draft,
   Supervision, Resources, Project administration, Investigation, Funding
   acquisition, Conceptualization.

Declaration of competing interest

   A.G. is the founder of TrueNorth Health Center, a private facility that
   offers medically supervised fasting interventions. K.M.K. and M.R.M.
   are employed by C[2]N Diagnostics. The other authors report no
   conflicts of interest. The funding sources were not involved in any
   form with the findings presented in the study. The article was not
   commissioned. No author was precluded access to data.

Acknowledgments