Circulating FGF21 is induced by prolonged fasting in humans. To test whether FGF21 is induced by fasting in humans, we serially measured circulating levels over the course of a 10-day fast in healthy human volunteers. We recruited volunteers ranging in age from 22.4 to 48.3 years, who were normal to slightly overweight. Baseline clinical characteristics are listed in Table 1. All female subjects were premenopausal and had regular menstrual cycles. BMIs ranged from 22.7 to 29.3 kg/m2, and baseline serum glucose levels were all within the normal fasting range (<100 mg/dl). Baseline FGF21 levels were similar to the pre-baseline FGF21 levels (median [interquartile range]: pre-baseline = 124 [46, 491] pg/ml vs. day 0 = 182 [50, 304] pg/ml, P = 0.33). Consistent with previous studies (25), there was a trend toward positive associations between baseline insulin and homeostatic model assessment for insulin resistance (HOMA-IR) and baseline FGF21 levels (Supplemental Figure 1; supplemental material available online with this article; doi:10.1172/JCI83349DS1). Then, over the course of the fast, FGF21 levels significantly increased (P = 0.02), with mean FGF21 levels on day 10 that were 4-fold higher than mean baseline (day 0) levels (day 0: mean ± SEM = 188 ± 46 pg/ml vs. day 10 = 799 ± 189 pg/ml, P < 0.03) (Figure 1). Only 1 subject did not have an increase in FGF21 levels on day 10 as compared with baseline levels (baseline FGF21 level: 452 pg/ml and day-10 FGF21 level: 230 pg/ml). Remarkably, FGF21 levels declined in most subjects during the early phase of the fast, and it was only in the later stages of the fasting protocol (days 7–10) that we observed a marked surge in FGF21 levels (Figure 1). We also considered the possibility that we were measuring the accumulation of inactive FGF21. Therefore, we re-measured our samples using an assay specific for the intact protein (Supplemental Figure 2). These measurements were consistent with those of the initial finding, therefore providing independent confirmation for the late, fasting-mediated surge in functional FGF21. While these data provide strong evidence in support of FGF21 as a fasting-induced hormone, the unexpected trajectory of FGF21 levels raises the possibility that FGF21, as reflected in circulating levels, has a role in the late adaptive starvation response.

Figure 1 Circulating FGF21 is induced by prolonged fasting in humans. (A) Spaghetti plot showing serial FGF21 serum measurements over a 10-day fasting period. (B) Fasting FGF21 data displayed with Tukey box plots. After an initial downward trend in serum FGF21 levels, a significant surge in circulating FGF21 was observed at the 10-day time point when compared with baseline values. P < 0.03, paired t test.

Table 1 Baseline characteristics of the study subjects

Fasting-induced FGF21 does not lead to induction of thermogenic fat in humans. Although seemingly paradoxical, FGF21 has consistently been implicated in the induction of adaptive thermogenesis in WAT (10–14); therefore, we considered the possibility that fasting-induced circulating FGF21 would drive thermogenesis. We performed pre- and post-fasting PET/MRI scans of 7 of the human subjects who completed the study (8 subjects had a baseline scan). At baseline, 5 of 8 subjects (62.5%) or 5 of 7 (71.4%) of the study completers showed areas of fluorodeoxyglucose (FDG) activity in supraclavicular and neck fat after cooling that were consistent with BAT. On day 10, which coincided with a marked increase in circulating FGF21 levels, we found that FDG activity in supraclavicular and neck fat disappeared in all 5 of the subjects who had detectable thermogenic adipose tissue at baseline (Figure 2A, binomial test, P < 0.05).

Figure 2 Human fasting is associated with downregulation of thermogenic activity in adipose tissue. (A) FDG-PET/MRI images of a representative subject before and after the 10-day fast. In coronal FDG-PET images (top row), arrows indicate FDG uptake in the cervical and supraclavicular regions at baseline, which disappeared with fasting. T1-weighted MRI images (middle row) and fused FDG-PET/MRI images (bottom row) localized FDG uptake to adipose tissue, consistent with BAT. Of the 5 subjects with detectable BAT at baseline, none had significant areas of FDG avidity after 10 days of fasting. P < 0.05, binomial test. (B) qPCR performed on human periumbilical sWAT samples collected at baseline and on days 1 and 10 of fasting showed fasting-mediated downregulation of transcriptional regulators of the thermogenic program. Data are expressed as the mean ± SEM and were analyzed by repeated-measures ANOVA and Dunnett’s test for multiple comparisons (n = 7). Note: UCP1 was measured but not detectable; PRDM16 data represent a subset of 5 subjects with detectable transcript levels. *P < 0.05, **P < 0.01. (C) Resting energy expenditure measured by indirect calorimetry. Note that the y axis starts at 800 kcal/d. (D) Serial circulating adiponectin during human fasting. Data are normalized to baseline values and displayed as Tukey box plots. P < 0.01, paired t test. Mean baseline adiponectin level: 9.9 μg/ml ± 5.7 (SD). Note that the y axis starts at 50%. (E) Serial circulating total T3 levels during human fasting. Data are normalized to baseline values and displayed as a Tukey box plot. P < 0.01, baseline level compared with day 10 using a Wilcoxon signed-rank test. Median baseline T3 level with interquartile range: 116.6 ng/dl (99.3, 129.7). Note that the y axis starts at 50%. (F) qPCR performed on the samples analyzed in B demonstrate fasting-mediated downregulation of thyroid effector genes in human sWAT. Repeated-measures ANOVA and Dunnett’s test for multiple comparisons were used to analyze the data, which are presented as the mean ± SEM. *P < 0.05, **P < 0.01, ***P < 0.005.

We also performed quantitative PCR (qPCR) on periumbilical fat biopsy samples collected at baseline and on days 1 and 10 to assess the expression of key genes involved in the thermogenic program. We did not reliably detect uncoupling protein 1 (UCP1) at any of the time points, which may be due to the fact that thermogenic activity is not typically seen with FDG imaging at the sampling site, including in the present study. We did, however, observe downregulation of other key transcriptional regulators of the thermogenic program, including CIDEA and PPARγ coactivator 1 α (PGC1A) (Figure 2B). These data must be interpreted with caution, given the sampling site; however, the effect of fasting on key transcriptional regulators of the thermogenic program is consistent with the PET imaging data in demonstrating a fasting-mediated suppression of thermogenesis, while coinciding with the reduced energy expenditure observed during starvation (Figure 2C).

Because the effects of supraphysiologic FGF21 on energy expenditure in fed mice appear to be dependent on adiponectin, and FGF21 potently stimulates adiponectin secretion in mice (26, 27) and humans (15), we also measured the dynamics of adiponectin in this fasting study. Although adiponectin levels have previously been shown to be stable during a 72-hour fast (28), the known inverse association between measures of adiposity and circulating adiponectin (29) provided an additional rationale to test whether adiponectin levels would rise concurrently with FGF21 levels in the setting of weight loss during a prolonged fast. We found the opposite, however, as there was a modest decline in circulating adiponectin levels in all subjects completing the fast (Figure 2D). Together, these data suggest that the FGF21/adiponectin axis is not functional in humans in the context of starvation. Because the downstream effects of FGF21 may be context specific, these data do not exclude the possibility that FGF21 actions on adipose tissue, such as stimulation of adiponectin or thermogenesis, are evident in the fed state or after administration of supraphysiologic doses.

Given that the fasting-mediated reduction in energy expenditure has been linked to decreased thyroid hormone levels, we also examined the thyroid axis by measuring triiodothyronine (T3) levels and the transcription of thyroid hormone effector genes to determine whether these were associated with changes in FGF21 levels. Consistent with previous studies (30), we found that T3 levels decreased with fasting; T3 levels dropped by day 3 of the fast, and the lower levels were maintained throughout the remainder of the fast (Figure 2E). All subjects had final-fast-day T3 levels that were lower than their baseline levels. In addition, in human WAT, the thyroid effector genes were generally downregulated by fasting (Figure 2F), including significant reductions in the thyroid hormone receptors α1 and β1 (TRAC1 and THRB), thyroid hormone–responsive spot 14 (S14), and sterol regulatory element–binding protein 1c (SREBP1c). We observed similar results in murine WAT (Supplemental Figure 3). The time course of T3 reduction did not correlate with the fasting-mediated increase in FGF21 levels, nor were starvation-induced FGF21 levels associated with indices of resting energy expenditure. These data are consistent with those of prior studies demonstrating that the effects of FGF21 and T3 on energy expenditure are largely independent (31, 32) and support the concept that any potential effect of FGF21 that promotes BAT activity or increases energy expenditure is overwhelmed in the starvation state by regulatory forces favoring energy conservation.

FGF21 is not a causal mediator of the ketogenic response in humans. FGF21 was originally described as a mediator of the starvation-induced ketogenic response in mice (1–3), although this has not been consistently shown in all studies. In fact, a study of FGF21-null mice demonstrated an increase in ketogenesis after a 24-hour fast (33). In humans, supraphysiologic administration of an FGF21 analog results in a rise in serum ketones (15). This provided the rationale to test whether circulating FGF21 in humans is causally linked to ketosis. During the 10-day fast, we found a marked induction of ketones (P < 0.01 at all time points, corrected for multiple comparisons) in the serum (Figure 3A), with peak levels achieved between days 1 and 3 of fasting. Importantly, ketone dynamics during fasting differed markedly from that of circulating FGF21, with ketone levels rising prior to the rise in FGF21 levels (Figure 3B). At the time point at which an individual’s ketone levels rose at least 10-fold compared with baseline, the mean change in FGF21 levels from baseline was –38 ± 47 pg/ml. Importantly, there was no significant difference between FGF21 levels at baseline compared with FGF21 levels at the time point at which ketone levels increased by at least 10-fold (P = 0.43).

Figure 3 FGF21 does not drive ketogenesis in human fasting. (A) Serial serum ketone measurements during fasting in humans. Ketones were significantly elevated in the serum by the first fasting day and remained elevated for the duration of the fast. Data are shown as Tukey box plots. Kruskal-Wallis test, followed by the Dunn’s correction for multiple comparisons. P < 0.01 at all time points. (B) Line plot overlay of serum FGF21 and ketone levels in fasting humans. The onset of ketogenesis occurred by day 1 of fasting during the initial downward trend in serum FGF21 levels. Serum FGF21 peaked on day 10 of fasting, approximately 7 days after achievement of near-peak ketone levels. (C) Fasting in C57BL/6 mice (n = 5/time point) led to significantly elevated serum FGF21 levels after 6 or 24 hours of fasting compared with baseline measurements in the fed state. ANOVA and Dunnett’s multiple comparisons correction. Data are shown as Tukey box plots. (D) Ketones were measured in the same serum samples as in C (n = 5/time point). Ketones were not significantly elevated until the 24-hour time point. ANOVA and Dunnett’s multiple comparisons correction. Data are shown as Tukey box plots. β-OH-butyrate, β-hydroxybutyrate.

As a comparison, we also performed a similar analysis in WT C57BL/6 mice subjected to fasting for up to 24 hours, followed by 6 hours of refeeding. In these mice, we detected an early induction of FGF21 in serum after only 6 hours of fasting that became more elevated at the 24-hour time point (Figure 3C). Because mice are known to rapidly lose weight during fasting, this raises the question of whether interspecies differences in weight loss rates could explain the difference in FGF21 dynamics. Indeed, the C57BL/6 mice used in this study lost an average of 17.4% ± 1.6% (SD) of their BW over a 24-hour fasting period, whereas the human subjects lost 9.2% ± 0.93% (SD) of their BW over the 10-day fast. However, human subjects had already lost the majority of the weight (6.6% ± 3.7% of their initial BW) at the time of their increase in FGF21 levels. In contrast, mice showed an increase in circulating FGF21 levels 6 hours into the fast, when they had lost only 2.9% ± 3.6% of their BW. This suggests that the interspecies difference is not solely due to differences in the rates of weight loss. Moreover, consistent with the previously demonstrated role of FGF21 in the ketogenic response in mice, we found that the FGF21 release into serum preceded the elevation in serum ketones, which were significantly elevated at the 24-hour time point (Figure 3D). Therefore, these data reveal an interspecies difference in both the time scale of FGF21 release and its temporal relationship to the ketogenic response in starvation. Whereas the time course of FGF21 release in mice is consistent with a role in ketogenesis, our data strongly suggest that circulating FGF21 is not a key driver of fasting-induced ketogenesis in humans.

Fasting-induced FGF21 and the late response to starvation. To develop new hypotheses for FGF21 function during human starvation, we performed exploratory analyses of the association of FGF21 with other biologically plausible measures of physiology and metabolism. Among other changes, we observed that subjects lost weight, reduced their energy expenditure, and altered their lipid trafficking over the course of the 10-day fast (Supplemental Figure 4). However, none of the changes in these variables were significantly correlated with the change in FGF21 levels at day 10 over baseline levels (Supplemental Table 1).

We then focused specifically on metabolic processes previously linked to prolonged starvation, including (a) the development of relative peripheral insulin resistance and (b) the breakdown of tissue protein for use as an alternate fuel source. In examining serially measured variables with biologically plausible relationships with the metabolic adaptation to starvation, we observed that only insulin, HOMA-IR, nonesterified fatty acids (NEFA), and serum transaminases displayed late changes grossly resembling the dynamics of FGF21 (Figure 4). We therefore performed a longitudinal analysis of the association of these variables with log-transformed FGF21 using a mixed-effects model. Random effects were included for each subject, and a first-order autocorrelation structure grouped by subject was fit to model the time correlation in the error terms.

Figure 4 Correlation of FGF21 with serum markers of late starvation in humans. Parameters for A–E are displayed as Tukey box plots with a line graph of mean serum FGF21 values (red) superimposed for reference. (A) Serum insulin levels. (B) HOMA-IR levels. (C) Serum NEFA. (D) Serum ALT levels. (E) Serum AST levels.

The longitudinal analysis showed no significant effect of insulin, HOMA-IR, or NEFA on FGF21 levels (Table 2), consistent with the notion that the induction of FGF21 is not directly related to the alterations in peripheral tissue insulin signaling. In contrast, in unadjusted analyses, both serum transaminases — aspartate aminotransferase (AST) and alanine aminotransferase (ALT) — had significant predictive effects on FGF21. After adjustment for the repeated analyses, the effect of AST remained significant (P = 0.04).

Table 2 Longitudinal analysis of predictors of log-transformed FGF21 using a mixed-effects model

While ALT is typically more specific to liver cell death, AST is liberated by tissue breakdown in a wide variety of tissues including skeletal muscle and rbc. The analysis suggesting an association between AST and FGF21 during fasting is thus consistent with the concept that FGF21 has a role in the latter stages of the human adaptive starvation response, when tissue stress becomes evident by transaminase release and when glucose homeostasis is increasingly reliant on the shunting of liberated amino acids to gluconeogenesis in the liver. The role of FGF21 and peripheral tissue fuel shifting in the late starvation response is also strongly supported by investigations in mice (3, 5, 34). Therefore, unlike ketogenesis, this link between FGF21 and the late starvation response in humans suggests this as a conserved physiological role for fasting-induced FGF21.

Although this study was not designed to measure tissue catabolism and fuel shifting, we explored this hypothesis further with additional secondary analyses of indirectly related indices of circulating amino acids and body mass. Classic starvation studies conducted in obese subjects by Cahill and colleagues (35) suggested that although circulating amino acid levels were largely related to kidney excretion, circulating levels of certain amino acids surged within the approximate time window of the FGF21 surge. On the basis of this work, we measured glutamine, branched-chain amino acids, and glucagon in the stored serum samples. We observed a gradual reduction in glutamine and a surge in branched-chain amino acids approximately 3 days into the fast, similar to the findings of Cahill and colleagues (ref. 35 and Figure 5, A–C). However, these variables were not significantly correlated with FGF21 levels in a longitudinal analysis, likely reflecting the diverse factors affecting circulating amino acid levels.

Figure 5 Correlation of FGF21 with weight loss in humans. (A) Serum glutamine levels are displayed as a Tukey box plot. Note that the y axis starts at 0.4 mM. (B) Serum branched-chain amino acids are displayed as a Tukey box plot. (C) Serum glucagon levels are displayed as a Tukey box plot. For A–C, the line graphs of mean serum FGF21 values (red) are superimposed for reference. (D) Tukey box plot displaying daily cumulative weight loss in the fasting human subjects. (E) Individual FGF21 measurements are plotted in relation to the absolute amount of weight loss. Each subject is plotted using a different color, with the dots ranging from unfilled to solid as a function of the duration of fasting. In a longitudinal model, there was a significant association between FGF21 levels and weight loss (P = 0.049); this relationship remained significant when controlling for sex (P = 0.026).

In our initial analyses, we found no association between FGF21 and BMI, percentage of body fat, or visceral adipose tissue when looking at the change from baseline to the final day of fasting (Supplemental Table 1), nor did we find an association between baseline BMI and onset of FGF21 induction. To further explore the time course of weight loss as a potential indicator of adaptive fuel shifting to conserve muscle mass, we reviewed the subjects’ charts and collected the daily body mass measurements to allow a longitudinal analysis. We observed no significant association between FGF21 levels and total weight or percentage of weight loss; however, we observed a statistically significant positive association between FGF21 levels and absolute weight loss (P = 0.049, Figure 5, D and E). Unexpectedly, subjects with the most weight loss had the most delayed upregulation of their FGF21 levels (Figure 5E). Since weight loss not normalized to BW is correlated with sex, we included sex as an additional fixed effect in the model, but the effect of weight loss remained significant (P = 0.026). We hypothesize that these data, together with the transaminase data, suggest that each individual has a threshold of fasting-mediated weight loss that, when exceeded, is manifested by markers of tissue stress and breakdown and FGF21 release.

Tissue-specific transcription regulation of FGF21 pathway genes with fasting in mice and humans. Because of the absence of a clear link between fasting-induced FGF21 and previously predicted functional outcomes, such as induction of ketogenesis and adipose thermogenesis, we hypothesized that the hormonal activities of FGF21 may be further regulated at the level of target tissues and therefore profiled the transcriptional activity of FGF21 and related genes as an indication of tissue-specific FGF21 activity. We first performed transcriptional analysis in the mouse, which allowed a comparison of FGF21 pathway genes across metabolically relevant tissues. Because the fasting-mediated induction of circulating FGF21 is thought to occur primarily in the liver, we analyzed the mouse liver during fasting and refeeding as a positive control. As expected, we found a marked early fasting–mediated increase in the transcriptional activity of FGF21 pathway genes in the mouse liver, an effect that was largely reversed during refeeding (Figure 6A). This included a significant increase in the transcription of a key transcriptional determinant of FGF21, PPARα (Ppara), Fgf21 itself, and a key component of the FGF21 receptor complex, klotho β (Klb) (Figure 6A). Relative to the liver, FGF21 transcriptional activity in both skeletal muscle and WAT was significantly lower, consistent with a previous report that the liver is the dominant source of circulating FGF21 (36). Although fasting did not result in significantly altered FGF21 transcript levels in skeletal muscle, we did observe an increase in fibroblast growth factor receptor 1 (Fgfr1) and a significant increase in the levels of the downstream glucose transporter 1 (Glut1), perhaps due to a hormonal effect of elevated circulating FGF21 (Figure 6B). In contrast to the upregulation of FGF21 in the liver, fasting led to a decline in FGF21 pathway genes in WAT that was statistically significant for Pparg and Klb (Figure 6C). With refeeding, the fasting effect was reversed and, in some instances, markedly increased above the baseline fed state.

Figure 6 Divergent tissue-specific transcriptional activity of the FGF21 pathway genes with fasting. (A) Bar graph (mean ± SEM) of qPCR measurements of FGF21 pathway genes in murine liver in the fed and fasted states (n = 5). (B) Bar graph (mean ± SEM) of qPCR measurements of FGF21 pathway genes in murine skeletal muscle in the fed and fasted states (n = 5). (C) Bar graph (mean ± SEM) of qPCR measurements of FGF21 pathway genes in murine inguinal sWAT in the fed and fasted states (n = 5). For A–C, data were compared using ANOVA and Sidak’s correction of multiple comparisons (baseline vs. 6 and 24 hours of fasting, 24 hours of fasting vs. refed). (D) Bar graph (mean ± SEM) of qPCR measurements of FGF21 pathway genes in human periumbilical sWAT. Repeated measurements made at baseline and on days 1 and 10 of fasting. Fasting measurements were normalized to baseline measurements. *P < 0.05, **P < 0.01, ***P < 0.005, repeated-measures ANOVA, with Dunnett’s correction of multiple comparisons (n = 7).

Using periumbilical biopsy specimens collected from the human subjects at baseline (day 0) and on days 1 and 10, we were also able to measure the effect of fasting on FGF21 pathway activity in human WAT. We found that fasting was associated with downregulation of FGF21 transcriptional activity (Figure 6D). Similar to the mouse, however, the FGF21 qPCR amplification plots revealed low cycle threshold values for human WAT samples (median [interquartile range] = 35.8 [34.8, 36.9]), consistent with the concept that local regulation of WAT FGF21 production does not contribute significantly to circulating levels of FGF21 (36). Relative to baseline measurements, KLB was markedly downregulated in s.c. WAT (sWAT) biopsy samples at day 1 and day 10, and FGFR1 was significantly reduced at the day-10 time point (Figure 6D). These data suggest similarities in the adipose tissue response to fasting in mice and humans with respect to FGF21 pathway genes. The transcriptional downregulation of FGF21 receptors in WAT with fasting may render WAT resistant to the fasting-mediated increase in FGF21 levels, which offers one potential explanation for why the fasting-mediated increase in FGF21 levels did not translate into activation of a thermogenic program in WAT or stimulation of adiponectin release. Moreover, these data are consistent with the concept that FGF21 activity during fasting is differentially regulated in a tissue-specific manner, in part by transcriptionally modulating components of the FGF21 receptor complex.