Next Article in Journal
Mitochondrial Oxidative Stress Is the General Reason for Apoptosis Induced by Different-Valence Heavy Metals in Cells and Mitochondria
Next Article in Special Issue
Exogenous IL-17A Alleviates Social Behavior Deficits and Increases Neurogenesis in a Murine Model of Autism Spectrum Disorders
Previous Article in Journal
Unusual Presentation of SET::NUP214-Associated Concomitant Hematological Neoplasm in a Child—Diagnostic and Treatment Struggle
Previous Article in Special Issue
Metabolomics: Perspectives on Clinical Employment in Autism Spectrum Disorder
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
IJMS
Volume 24
Issue 19
10.3390/ijms241914460
ijms-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Ketogenic Diet Affects Sleep Architecture in C57BL/6J Wild Type and Fragile X Mice

by
Pamela R. Westmark
1,
Aaron K. Gholston
1,2,
Timothy J. Swietlik
1,
Rama K. Maganti
1 and
Cara J. Westmark
1,2,*
1
Department of Neurology, University of Wisconsin, Madison, WI 53706, USA
2
Molecular Environmental Toxicology Center, University of Wisconsin, Madison, WI 53706, USA
*
Author to whom correspondence should be addressed.
Int. J. Mol. Sci. 2023, 24(19), 14460; https://0-doi-org.brum.beds.ac.uk/10.3390/ijms241914460
Submission received: 8 August 2023 / Revised: 15 September 2023 / Accepted: 18 September 2023 / Published: 22 September 2023
(This article belongs to the Special Issue From Molecular Mechanism to Therapy in Autism Spectrum Disorder)
Browse Figures
Review Reports Versions Notes

Abstract

:
Nearly half of children with fragile X syndrome experience sleep problems including trouble falling asleep and frequent nighttime awakenings. The goals here were to assess sleep–wake cycles in mice in response to Fmr1 genotype and a dietary intervention that reduces hyperactivity. Electroencephalography (EEG) results were compared with published rest–activity patterns to determine if actigraphy is a viable surrogate for sleep EEG. Specifically, sleep–wake patterns in adult wild type and Fmr1KO littermate mice were recorded after EEG electrode implantation and the recordings manually scored for vigilance states. The data indicated that Fmr1KO mice exhibited sleep–wake patterns similar to wild type littermates when maintained on a control purified ingredient diet. Treatment with a high-fat, low-carbohydrate ketogenic diet increased the percentage of non-rapid eye movement (NREM) sleep in both wild type and Fmr1KO mice during the dark cycle, which corresponded to decreased activity levels. Treatment with a ketogenic diet flattened diurnal sleep periodicity in both wild type and Fmr1KO mice. Differences in several sleep microstructure outcomes (number and length of sleep and wake bouts) supported the altered sleep states in response to a ketogenic diet and were correlated with altered rest–activity cycles. While actigraphy may be a less expensive, reduced labor surrogate for sleep EEG during the dark cycle, daytime resting in mice did not correlate with EEG sleep states.

1. Introduction

Fragile X syndrome (FXS) is a rare developmental disability with an estimated prevalence of 1 in 5000 [1]. Loss of expression of the RNA binding protein fragile X messenger ribonucleoprotein (FMRP) in FXS results in intellectual disability, autism, and seizures [1]. Many FXS phenotypes are manifested in Fmr1KO mice which lack expression of FMRP [2]; however, there has been difficulty translating promising therapeutics from the mouse model to human clinical trials. The development of validated outcome measures that translate between preclinical and clinical studies is a critical need for the FXS community [3]. Here we examined sleep architecture in Fmr1KO mice comparing EEG sleep measures to published actigraphy findings. We also explored the effects of ketogenic diet (KD) therapy, which has been shown to reduce hyperactivity and seizures in Fmr1KO mice [4], on sleep measures. We hypothesize that sleep states will be altered in Fmr1KO mice and rescued with KD.
Parents report that nearly half of children with FXS experience sleep difficulties with the most frequent issues involving sleep onset insomnia, reduced total sleep time and frequent awakenings [5,6,7,8,9,10,11,12]. Sleep disorders observed include obstructive sleep apnea (OSA) and nocturnal enuresis [6,12,13,14,15]. Polysomnography studies in FXS subjects showed a higher percentage of stage 1 non-rapid eye movement (NREM) sleep, a lower percentage of rapid eye movement (REM) sleep, and an increase in REM latency compared to normal controls indicative of disrupted sleep microstructure [16,17]. Considering the essential role that sleep plays in learning and memory consolidation, rescuing sleep deficits in FXS may be therapeutic, and sleep electroencephalography (EEG) and actigraphy may be viable outcome measures that translate between preclinical and clinical FXS studies. Thus, it is important to discern if there are altered sleep phenotypes in FXS preclinical models such as the Fmr1KO mouse.
The classic KD was introduced in 1921 to replace starvation in the treatment of seizures and is in use today to treat drug refractory epilepsy [18]. KDs are high in fat with moderate levels of protein and low carbohydrate. They force the body into a state of ketosis where ketones are used as the energy source instead of glucose. In recent years, the KD has become the new fad diet for weight loss and is being tested in numerous neurological models [19]. Recent studies in human and rodent models of autism indicate that the KD improves core behavioral symptoms [20,21,22,23,24,25,26,27,28]. There is an established link between circadian dysfunction and FXS-related proteins and accumulating evidence that the KD rewires the circadian clock [29,30,31,32,33,34,35,36,37,38,39]. Circadian rhythms are the 24-h cycles generated by a master pacemaker located in the suprachiasmatic nuclei (SCN) of the anterior hypothalamus of mammals. They control locomotor activity, feeding behavior, sleep–wake patterns, and other physiological and metabolic pathways. The importance of diet and circadian rhythm to sleep behavior are well recognized [30,35]. The KD decreases the hyperexcitability of in vitro epileptic networks, improves diurnal rhythmicity in epileptic mice, and improves slow-wave sleep and sleep quality in children with refractory epilepsy [39,40,41,42]. These findings prompt the hypothesis that the KD may be beneficial in attenuating sleep disturbances in FXS.
This study compares sleep states acquired by sleep EEG to published rest–activity cycles attained by actigraphy. EEG is the gold standard clinical tool employed in sleep research [43]; however, the clinical feasibility of overnight polysomnography is reduced in persons with developmental disabilities. While actigraphy is a convenient and indirect way of assessing sleep measures, details on sleep microstructure cannot be obtained. Actigraphy offers several advantages over polysomnography for preclinical research including 24-7 continuous recordings, ease of use, less invasive, and reduced cost [44]. Sleep measured by EEG can provide details of the sleep microarchitecture.

2. Results

2.1. Study Design

WT and Fmr1KO male littermate mice were randomly weaned onto control and KD at postnatal day 18 (P18), maintained on respective diets throughout the study, and tested for EEG sleep phenotypes at 5–6 months of age (Figure 1 and Figure S1). Similar to our prior study [4], there was significantly reduced body weight and increased blood ketones in WT and Fmr1KO mice in response to KD (Figure S2). EEG recordings were collected for 7 days and days 4 and 6 scored manually for sleep states (Figure S3, hypnograms).

2.2. Differences in 24-h Vigilance State Distribution Are Diet Dependent

Neither 24- nor 12-h time bins indicated WT versus Fmr1 genotype-specific effects in the percent of time spent awake, asleep or in NREM or REM sleep in mice fed AIN-76A purified ingredient diet (Figure 2 and Table S1 (statistics)). Conversely, KD increased % NREM sleep by 13% in WT versus Fmr1KO mice. KD significantly reduced % time awake in both genotypes (21%↓ WT and 12%↓ Fmr1KO) and elevated % NREM (29%↑ WT and 18%↑ Fmr1KO) compared to AIN-76 controls.

2.3. KD Increases Time Spent in Sleep during the Dark Cycle

Mice are nocturnal with higher activity levels during the dark cycle and increased sleep during the light cycle. Binning the data by light and dark cycles indicated that KD increased time spent in NREM sleep during lights off in both genotypes, but significantly more in WT compared to Fmr1KO. Thus, a genotype-specific effect was observed when mice were fed KD with a 15% decrease in NREM sleep during the dark cycle in Fmr1KO compared to WT. The KD significantly decreased % wake time by 34% in WT and 23% in Fmr1KO and increased % NREM sleep by 79% in WT and 54% in Fmr1KO during the dark cycle compared to respective controls maintained on AIN-76A (Figure 2 and Figure S4 (pie charts) and Table S1). The KD decreased REM sleep by 27% in WT and 24% in Fmr1KO during the light cycle and increased REM sleep during the dark cycle by 84% in WT and 55% in Fmr1KO.

2.4. Sleep EEG Selectively Correlates with Actigraphy Findings during the Dark Cycle

We previously assessed rest–activity patterns in adult Fmr1KO mice by actigraphy in response to KD under the same treatment protocol used here (commencing at P18) and binning the data by 6-h increments (Figure 2D in [4]) and did not observe genotype-specific differences in rest–activity patterns. There were significantly decreased activity levels in both halves of the dark cycle (Zeitgeber hours, Z12–18 and Z18–24) and the first half of the light cycle (Z0–6) in both WT and Fmr1KO mice fed KD versus control diet. Activity levels were low in all cohorts during the second half of the light cycle (Table 1). Binning the EEG data into 6-h increments for direct comparison with the actigraphy data indicates concurrence regarding the absence of genotype-specific effects and decreased wake state during the dark cycle in WT and Fmr1KO mice fed KD (Figure S5 and Table S1). A point of convergence between the EEG and actigraphy data is that percent wake time during the first half of the light cycle did not correlate with activity levels as all cohorts exhibited equivalent % wake time by EEG but KD cohorts had decreased activity counts compared to AIN-76A cohorts.
Further division of the data into 2-h bins (Figure 3 and Table S1) confirms decreased wake time in both WT and Fmr1KO mice fed KD during the dark cycle, specifically during the first half of the dark cycle and during the 2 h immediately before the transition to the light phase. There is also a genotype-specific difference with 26% increased wake time in Fmr1KO compared to WT mice fed KD during the final 2 h of the dark cycle. The KD blunts both wake state peaks during the dark period through increased NREM and REM sleep. The % NREM and % total sleep were the inverse of the wake data with highly statistically significant differences between all AIN-76A and KD cohorts during the dark cycle. Of note, there is a trend throughout the dark cycle that KD makes WT mice sleepier than Fmr1KO as evidenced by increased % NREM that reaches statistical significance during the final 2-h bin. REM sleep was significantly decreased during both halves of the light cycle and increased during both halves of the dark cycle in response to KD in both WT and Fmr1KO mice. Specifically, the KD blunted the REM peak (Z4–6 h, lights on) and the REM trough (Z16–18, lights off) in both WT and Fmr1KO mice. Overall, treatment with KD flattened diurnal sleep periodicity curves in both wild type and Fmr1KO mice, actigraphy results only concurred with sleep EEG during the dark cycle when mice should be awake, and EEG identified decreased REM sleep in response to KD during the light cycle irrespective of activity levels. There was a single 2-h bin (final 2 h of light cycle) where WT mice fed AIN-76A exhibited increased total % sleep compared to Fmr1KO fed AIN-76A.

2.5. KD Increases the Number of Wake, NREM and REM Bouts in WT Mice during the Dark Cycle

Sleep microarchitecture analysis included the number and length of wake, sleep, NREM and REM bouts over 24-h and 12-h bins. There were no genotype-specific differences in bout number in mice fed AIN-76A (Figure 4 and Table S1). In mice treated with KD, Fmr1KO mice exhibited a decreased number of wake, sleep and NREM bouts over the 24-h period and during the dark cycle compared to WT. Diet-specific effects included statistically significant increases in wake, sleep and NREM bout number as a function of KD in WT mice over the 24-h period and during the 12-h dark cycle as well as an increased number of REM bouts in both WT and Fmr1KO during the dark cycle. In addition, sleep bout number was increased in WT mice with KD during the light cycle and REM bout number was decreased in Fmr1KO mice with KD during the light cycle.

2.6. KD Decreases the Length of Wake Bouts in Mice during the Dark Cycle

The average length of wake bouts during the 12-h dark cycle was significantly reduced in response to KD in WT and Fmr1KO mice (Figure 5 and Table S1). The average reduction was 157 s for WT and 93 s for Fmr1KO. The reduced length of wake bouts in conjunction with an increased or equivalent number of wake bouts during the dark cycle indicates that the length of the wake bouts underlies reduced % wake time in response to KD during the dark phase. The average length of sleep bouts during the light cycle was significantly lower in WT mice in response to KD, which in conjunction with an increased number of sleep bouts, equates with equal % sleep in WT mice irrespective of diet. The average length of NREM bouts during the dark cycle was significantly higher in Fmr1KO mice in response to KD, which in conjunction with an equivalent number of bouts, indicates that increased % NREM sleep is primarily due to increased bout length whereas increased % NREM sleep during the dark cycle in WT mice in response to KD is primarily attributed to increased bout number.
Analysis of the single longest wake bout over the 24-h period indicates a 64% and 45% decrease in bout length in WT and Fmr1KO mice, respectively, in response to KD (Figure S6 and Table S1). There was also a 13% decrease in the longest REM bout in WT mice in response to KD over the 24-h period. KD caused a statistically significant average decrease of 19 min in the latency time to the first sleep bout in WT mice (Figure S7 and Table S1).
During the EEG scoring for sleep states, an EEG pattern was observed that suggested the mice were trying to enter REM but failing. To be scored as REM, the EEG pattern needed to exhibit seven or more epochs (an epoch is a 4-s period) of low amplitude/high frequency waves. Upon secondary analysis of the EEG recordings, instances of 1–6 epochs of low amplitude/high frequency waves were tallied as failed attempts to enter REM. The percentage of failed REM attempts indicates a statistically significant 20% decrease in failed REM attempts in Fmr1KO mice compared to WT fed AIN-76A during the dark cycle (Figure 6). This was the only genotype-specific EEG phenotype observed with the control diet.

2.7. Fmr1KO Mice Do Not Exhibit Epileptic Activity on Sleep EEG

Epilepsy is a comorbid phenotype in FXS that manifests as benign focal epilepsy of childhood (BFEC) with predominantly nocturnal focal motor seizures and a characteristic EEG pattern with morphologically distinct centrotemporal discharges activated by sleep [45,46]. Similar to Pietropaolo and colleagues [47], we did not observe seizures, absences or interictal events in any WT or Fmr1KO mouse in scored EEG recordings.

3. Discussion

The identification of comparable outcome measures that can be feasibly employed in both preclinical mouse and clinical human studies is an important need for the FXS field [48]. Considering the pivotal role sleep plays in memory consolidation and its association with epileptiform activity, dysfunctional sleep in FXS may underly numerous disease phenotypes. We assessed sleep states in Fmr1KO mice by EEG and asked if actigraphy could serve as an easier implemented, less expensive surrogate for sleep EEG. We found similar sleep–wake patterns in wild type and Fmr1KO mice maintained on a control diet, and that sleep states did not correlate with activity levels during the light cycle when nocturnal animals sleep. These data suggest that sleep is not a viable preclinical outcome measure that translates between mouse and human models of FXS and that actigraphy, while a viable outcome measure, is not an absolute surrogate for sleep EEG in mice in our experience.
Mouse and fly models of FXS exhibit altered activity states and circadian rhythms, which potentially mirror the sleep disturbances observed in patients with the disorder. FMRP-related proteins are associated with increased [2,47,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73], decreased [74], and no change [47,54,59,70,75,76,77,78,79,80,81,82,83,84] in measures of locomotor activity in Fmr1KO model organisms. Of note, testing in Fmr1KO mice was conducted by Saré and colleagues who employed a home-cage monitoring system that assessed activity counts as a surrogate for sleep during the light and dark phases as a function of age over six consecutive days where sleep was defined as 40 s of inactivity [85]. Juvenile Fmr1KO mice (P21) do not differ from controls. There is reduced “sleep” in adult Fmr1KO mice (P70 and P180) selectively during the light phase compared to controls. Thus, “sleep” disturbances emerge during the later stages of brain maturation. Their methodology resembles our actigraphy assessment of rest–activity in Fmr1KO mice where we observe hyperactivity in Fmr1KO mice [4], which concurs with most of the literature. Neither study found genotype-specific differences in habituation to the novel housing conditions. Both studies found increased activity in adult mice selectively during the light phase compared to controls, albeit we selectively found the difference during the first half of the light cycle and lost statistical significance if we binned in 12-h timeframes. Saré and colleagues found a 6–8% increase in activity counts during the 12-h light cycle in adult Fmr1KO mice, and we found a 38% increase during the first 6 h of the light cycle. Numerous environmental factors can affect the outcome and magnitude of rodent behavioral studies. The disadvantage of actigraphy testing as a surrogate for sleep is lack of data on sleep stages and bout duration, while the disadvantages of EEG testing are the invasiveness of the surgery, implantation of electrodes, weight and restriction of the wires attached to the headcap, and the inability to test juvenile mice due to limitations with attaching and maintaining the electrode headcap.
Recent studies in FXS human and rodent models identify enhanced resting state gamma power and reduced inter-trial coherence of sound-evoked gamma oscillations as common EEG biomarkers [86,87,88,89,90,91,92,93,94,95,96,97]. There is also evidence of exaggerated theta power in subjects with FXS and abnormal hippocampal theta–gamma phase amplitude coupling in Fmr1KO mice [98,99,100]. Furthermore, in vivo electrophysiological studies in the hippocampal CA1 region of Fmr1KO mice indicate a deficit in REM sleep due to a reduction in the frequency of REM bouts (60 min test session during the light phase), which is consistent with sleep architecture abnormalities in FXS patients [101]. Considering the documented prevalence of sleep problems in FXS, we were surprised we did not find differences in REM or NREM sleep in Fmr1KO mice over 24-h test periods. Our three-channel EEG methodology is less precise than the published 18-tetrode microdrive technology but also less invasive. We did not find altered wake or sleep (NREM, REM) states as a function of Fmr1 genotype with electrodes implanted in the right frontal and left parietal cortices of the brain and with the mice maintained on a control AIN-76A diet. We also did not find differences in the number and/or length of wake, NREM or REM bouts as a function of Fmr1 genotype. While scoring EEG, we observed a pattern whereby mice appeared to be trying to enter REM but failing. This was the only genotype-specific difference we found between WT and Fmr1KO mice maintained on AIN-76A diet from weaning.
An important question regarding EEG outcomes is response to treatment. Prior studies assessing sleep by home-cage monitoring found that the GABAB agonist R-baclofen and the mTOR inhibitor rapamycin did not rescue deficits in the light phase [85,102]. In fact, rapamycin reduced “sleep” duration and had adverse effects on social behavior in both adult WT and Fmr1KO mice. Herein, we also find that total sleep, as assessed by EEG, did not differ during the light cycle with KD therapy, which is highly effective at reducing audiogenic-induced seizures (AGS) in Fmr1KO mice tested during the light cycle [4]. NREM sleep did not change with KD during the light cycle, but REM sleep was reduced. We chose to test the effect of KD on sleep EEG in Fmr1KO mice because the KD is proving therapeutic for many disease states that are comorbid with FXS, including epilepsy and autism; individuals with FXS present with an abnormal fatty acid profile [103]; and our prior work indicated that KD was as or more effective than the best metabotropic glutamate receptor 5 (mGluR5) inhibitors tested in the AGS assay.
We found that a KD increased NREM and REM sleep during the dark cycle in both WT and Fmr1KO mice, which corresponds to reduced activity levels in the actigraphy assay; however, REM sleep was reduced in mice in response to a KD during the light cycle, which did not correlate with activity counts. These data suggest that the mice were awake longer but not moving during the light cycle when nocturnal animals should be sleeping. BAER-101, a selective GABAA agonist, reduces delta power in Fmr1KO mice during the light cycle during a 5-min period free of excessive movement [104]. Others have demonstrated states of quiet rest or quiet wakefulness in WT rats (3–9 Hz activity) when the Fmr1KO rat cortex remains activated (18–52 Hz) [105]. Thus, the KD and GABA agonists may increase quiet rest in mice. Decreased REM sleep during lights on is suggestive of keto insomnia, which is a lack of sleep reported by humans during the early days of KD introduction. Increased NREM and REM sleep in mice during lights off is suggestive of somnogenic (sleepiness) effects of the KD during a time when the mice are expected to be active. In contrast, in humans, a KD reduces nocturnal awakenings and improves excessive daytime sleepiness [106].
The mechanism underlying KD-induced changes in sleep architecture in C57BL/6J mice remain to be determined. Protein-enriched food (casein; three-fold over the standard 18% by weight), but not sugar or fat enrichment, has been shown to decrease the percent awakenings in response to stimulation with a corresponding decrease in the number of sleep and wake bouts [107]. Here, the KD, which has decreased protein (8.6%) versus the control diet (18%) caused increased percent awakenings (albeit without stimulation) as there was an increased number of wake, sleep, NREM and REM bouts during the dark cycle in WT C57BL/6J mice suggesting that dietary protein content affects arousal. Similarly, the length of sleep bouts and % REM were increased with high protein in the diet, and we found decreased length of sleep bouts and % REM during the light cycle with the KD, which contained lower protein. Thus, suboptimal protein content of the diet may affect multiple sleep macro- and microarchitecture phenotypes.
Alternatively, or in addition to protein, ketones may underly alterations in sleep structure in response to a KD. Others have tested the effects of a KD plus medium chain triglycerides (MCT) on sleep in mice and found increased ketone levels and reduced REM sleep duration during the light cycle [108]. Their treatment started at 8 weeks of age, and they did not observe decreased body weight. NREM sleep and wakefulness were not affected, but slow wave sleep (delta/theta ratio) during NREM increased during the active phase with KD-MCT. We also observed increased ketones and reduced REM sleep during the light cycle, but we have significantly reduced body weight. In addition, our % wake and % NREM sleep during the light cycle were also unaffected and our % NREM increased during the dark cycle. As the two studies have similar findings, the data suggest that our significantly reduced body weight in response to KD is not a confounding factor interfering with sleep architecture.
Aberrant signaling through metabotropic glutamate receptor 5 (mGluR5), the most studied therapeutic target for FXS [109], may contribute to sleep phenotypes in FXS. Knockout mice lacking mGluR5 do not exhibit altered sleep phenotypes during the light cycle under baseline conditions; however, they do exhibit lack of recovery sleep after sleep deprivation including decreased REM and NREM sleep compared to WT littermates [110]. Similarly, we did not find differences in REM or NREM sleep between WT and Fmr1KO mice fed control diet, but the KD diet caused a trend for decreased % NREM throughout the dark cycle in Fmr1KO versus WT that reached statistical significance around the dark/light transition (Z22–24 and Z2–4). Thus, stress whether in the form of sleep deprivation or a stringent diet, may exacerbate sleep deficits in Fmr1KO mice. Fmr1KO mice overexpress amyloid precursor protein (APP) through an mGluR5-dependent pathway [111], and the J20 mouse model of Alzheimer’s disease that over-expresses APP with familial mutations exhibits a deficit in REM sleep, which is rescued with the mGluR5 inhibitor CTEP. CTEP also improves NREM delta and sigma power but did not correct rest–activity rhythms or alter other behavioral outcomes [112]. The effect of mGluR5 inhibitors on sleep states in Fmr1KO mice remains to be determined.
The limitations of this study include testing adult animals, as larger deficits may be observed during postnatal development, as well as the labor-intensive requirement for manual scoring of the EEG recordings. We tested adult mice in this preliminary study due to technical limitations with the weight of the EEG headcaps compared to mouse body weight and because postnatal animals are rapidly growing, including the skull, which could interfere with headcap stability. We only tested male mice in this study due to the labor-intensive nature of manually scoring the sleep EEG, which required an average of 4–6 h per mouse per 24-h period scored, and because KD selectively attenuates seizures, reduces body weight, and decreases activity levels in male but not female Fmr1KO mice. We are in the process of scoring sleep EEG in adult Fmr1KO mice commencing KD therapy at 3 months of age, where Fmr1KO mice exhibit a 38% increase in hyperactivity during the first half of the light cycle (Figure 3 in [4]). Increased hyperactivity in Fmr1KO mice selectively during the beginning of the light cycle concurs with the sleep phenotype in the human disorder where children with FXS have trouble falling asleep. The lack of hyperactivity here in Fmr1KO mice treated from the time of weaning may be due to a therapeutic effect of the control diet (AIN-76A) compared to standard chows. The effects of diet on sleep architecture and resultant improvements in disease phenotypes remain to be determined in FXS models.
In conclusion, this study provides substantial data on sleep EEG outcomes in mice as a function of Fmr1 genotype and KD. Several sleep outcome measures agreed with rest–activity data in Fmr1KO mice, but selectively during the dark cycle (mouse wake cycle) and not during the light cycle (mouse sleep time). These data suggest that actigraphy is not a viable surrogate to assess sleep states per se in mice. Actigraphy and sleep EEG outcomes during the mouse active cycle responded to KD treatment in the same direction. Thus, actigraphy may afford the ability to monitor mice of all ages over a longer period in preclinical studies without surgery, headcap implantation or risk of destabilization of the headcap, while wrist or ankle actigraphy bracelets could approximate resting versus active states and response to interventions in human clinical trials for FXS. The lack of evidence for improved sleep during the light cycle in Fmr1KO mice suggests that the ketogenic diet may not be beneficial in treating sleep problems associated with the disorder, albeit there are significant effects on seizures and activity levels.

4. Materials and Methods

4.1. Materials

A detailed list of materials with supplier information is provided (Figure S8).

4.2. Mice

The Fmr1tm4Cgr (Fmr1KO) mice were originally developed by the Dutch–Belgian FXS Consortium and backcrossed > 11 times to FVB mice [2]. They were backcrossed into the C57BL/6J background by Dr. Bill Greenough’s laboratory (University of Illinois at Urbana-Champaign) and distributed to other laboratories. We have maintained the Fmr1KO mice in the C57BL/6J background at the University of Wisconsin-Madison for over 15 years with occasional backcrossing with C57BL/6J mice from Jackson Laboratories to avoid genetic drift. Breeding pair for these experiments were housed in static microisolator cages with ad libitum access to food (Teklad 2019) and water in a temperature- and humidity-controlled vivarium on a 12-h light cycle. The bedding (Shepherd’s Cob + Plus, ¼ inch cob) contained nesting material as the only source of environmental enrichment. All animal husbandry, surgery and euthanasia procedures were performed under NIH and an approved University of Wisconsin-Madison animal care protocol administered through the Research Animal Resources Center with oversight from the Institutional Animal Care and Use Committee (IACUC). Fmr1 genotypes were determined by PCR analysis of DNA extracted from tail biopsies with HotStarTaq polymerase (Qiagen Inc, Germantown, MD, USA; catalog #203205) and Jackson Laboratories’ (Bar Harbor, ME, USA) primer sequences oIMR2060 [mutant forward; 5′-CAC GAG ACT AGT GAG ACG TG-3′], oIMR6734 [wild type (WT) forward; 5′-TGT GAT AGA ATA TGC AGC ATG TGA-3′], and oIMR6735 [common reverse; 5′-CTT CTG GCA CCT CCA GCT T-3′], which produces PCR products of 400 base pairs (Fmr1KO) and 131 base pairs (WT). Heterozygote females exhibit both the 400 and 131 base pair bands. Fmr1HET females were bred with Fmr1KO males and generated WT and Fmr1KO male littermate mice for the described experiments. Experimental animals were derived from multiple breeding pairs as recommended [113,114]. Mice were randomly weaned onto control and KD at postnatal day 18 (P18), maintained on respective diets throughout the study, and tested for EEG sleep phenotypes at 5–6 months of age (Figure 1 and Figure S1). Some of the mice [AIN-76A (n = 3), WT fed a KD (n = 2), Fmr1KO fed AIN-76A (n = 6), and Fmr1KO fed a KD (n = 5)] completed a previously described KD treatment and behavioral battery (Figure 2 of [4]) before EEG. The remaining mice were generated to increase sample sizes and were experimentally naïve prior to EEG electrode implantation albeit diet treatments. Mice were socially housed prior to surgery and individually housed after EEG electrode implantation. Cohorts included AIN-76A (n = 12), WT fed KD (n = 9), Fmr1KO fed AIN-76A (n = 16), and Fmr1KO fed KD (n = 13).

4.3. EEG Electrode Implantation

Right frontal, left parietal, and occipital electrodes were placed along with two stainless steel wire electrodes in nuchal muscles for EMG under isoflurane anesthesia according to methods described previously [112] (Figure S9). The occipital electrode served as the ground and as the reference electrode for the surgical recording procedure. Mice were allowed to recover from surgery for 3 days prior to transfer to tethered EEG recording setups with mice housed individually in Plexiglas® chambers for sleep recording. EEG signals were acquired for 7 days (across the light and dark cycles) on an XLTEK machine (Natus, Madison, WI) with a 512 Hz sampling rate. EDF Browser software (v.2.40) was used to convert Natus EEG recordings into files compatible with Sirenia® Sleep Pro software v.1.3.2 (Pinnacle Technology, Lawrence, KS, USA). EEG signals from days 4 and 6 were scored by hand with Sirenia® Sleep Pro software v1.3.2 in 4-s epochs for wake, REM, and NREM states by two scorers blinded with respect to treatment group as previously described [112,115,116]. Waking epochs were identified as those with high EMG amplitude, and epochs with little EMG activity were scored as sleep. Specific sleep states were scored based on predominant EEG power where NREM was associated with low frequency and high amplitude delta (1–4 Hz) activity and REM was associated with increased frequency but low amplitude theta (5–7 Hz) activity. Sample EEG recordings scored for wake, NREM and REM states are shown in Figure S10 with hypnograms for all scored mice provided in Figure S3. Data were binned into 2-, 6-, 12- and 24-h increments for analyses.

4.4. Biometrics

Ketone and glucose levels were assessed in urine or blood as indicated in the figure legend using a Precision Xtra blood glucose and ketone monitoring system (Abbott Diabetes Care Inc., Alameda, CA, USA). For urine samples, mice were gently restrained at the neck and urine collected. For blood samples, mice were anesthetized with isoflurane and blood collected from the inferior vena cava and assayed for ketone and glucose levels with a Precision Xtra meter. Low off-scale glucose meter readings were adjusted to 20 mg/dL. High off-scale glucose meter readings were adjusted to 500 mg/dL. High off-scale ketone meter readings were adjusted to 8.0 mmol/L. Blood samples were collected during the light phase after 4 h fasting.

4.5. Statistical Analysis

Data were analyzed with Microsoft 365 ExcelTM version 2306 and Prism version 10.0.0 (153) software. The vast majority of the data passed the D’Agostino & Pearson test for normal Gaussian distribution and all data were analyzed similarly with parametric ANOVA tests. Average data are presented ±SEM and statistical significance determined by 2-way ANOVA with Tukey’s multiple comparison test (Table S1). The number of subjects, genotype and treatment details are included in the figure legends.

Supplementary Materials

The following supporting information can be downloaded at: https://0-www-mdpi-com.brum.beds.ac.uk/article/10.3390/ijms241914460/s1.

Author Contributions

Conceptualization, C.J.W.; methodology, P.R.W. and R.K.M.; EEG surgeries, P.R.W.; EEG scoring, A.K.G., T.J.S. and P.R.W.; data curation, P.R.W.; formal analysis, P.R.W. and C.J.W.; writing—original draft preparation, P.R.W. and C.J.W.; writing—review and editing, P.R.W., A.K.G., T.J.S., R.K.M. and C.J.W.; visualization, P.R.W. and C.J.W.; supervision, P.R.W. and C.J.W.; resources, R.K.M. and C.J.W.; project administration, C.J.W.; funding acquisition, C.J.W. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Clinical and Translational Science Award (CTSA) program through the National Center for Advancing Translational Sciences (NCATS) grant UL1TR002373, the University of Wisconsin-Madison Alzheimer’s Disease Research Center (ADRC) grant P50-AG033514, University of Wisconsin Molecular Environmental Toxicology Training Grant R25 ES020720, University of Wisconsin-Madison Department of Neurology start-up funds, and FRAXA Research Foundation.

Institutional Review Board Statement

The animal study protocol was approved by the Institutional Review Board of the University of Wisconsin (protocol code M005224; approved 19 February 2016) for studies involving animals.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data are contained within the article or supplementary materials. Sirenia EEG/EMG files are available from the corresponding author upon request.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Hagerman, R.J.; Berry-Kravis, E.; Hazlett, H.C.; Bailey, D.B.; Moine, H.; Kooy, R.F.; Tassone, F.; Gantois, I.; Sonenberg, N.; Mandel, J.L.; et al. Fragile X syndrome. Nat. Rev. Dis. Primers 2017, 3, 17065. [Google Scholar] [CrossRef] [PubMed]
  2. Dutch-Belgian Fragile X Consortium. Fmr1 knockout mice: A model to study fragile X mental retardation. The Dutch-Belgian Fragile X Consortium. Cell 1994, 78, 23–33. [Google Scholar]
  3. Berry-Kravis, E.; Hessl, D.; Abbeduto, L.; Reiss, A.L.; Beckel-Mitchener, A.; Urv, T.K.; Groups, O.M.W. Outcome measures for clinical trials in fragile X syndrome. J. Dev. Behav. Pediatr. 2013, 34, 508–522. [Google Scholar] [CrossRef]
  4. Westmark, P.R.; Gutierrez, A.; Gholston, A.K.; Wilmer, T.M.; Westmark, C.J. Preclinical testing of the ketogenic diet in fragile X mice. Neurochem. Int. 2020, 134, 104687. [Google Scholar] [CrossRef] [PubMed]
  5. Kaufmann, W.E.; Kidd, S.A.; Andrews, H.F.; Budimirovic, D.B.; Esler, A.; Haas-Givler, B.; Stackhouse, T.; Riley, C.; Peacock, G.; Sherman, S.L.; et al. Autism Spectrum Disorder in Fragile X Syndrome: Cooccurring Conditions and Current Treatment. Pediatrics 2017, 139 (Suppl. S3), S194–S206. [Google Scholar] [CrossRef]
  6. Angriman, M.; Caravale, B.; Novelli, L.; Ferri, R.; Bruni, O. Sleep in children with neurodevelopmental disabilities. Neuropediatrics 2015, 46, 199–210. [Google Scholar] [CrossRef]
  7. Kronk, R.; Bishop, E.E.; Raspa, M.; Bickel, J.O.; Mandel, D.A.; Bailey, D.B. Prevalence, nature, and correlates of sleep problems among children with fragile X syndrome based on a large scale parent survey. Sleep 2010, 33, 679–687. [Google Scholar] [CrossRef]
  8. Kronk, R.; Dahl, R.; Noll, R. Caregiver reports of sleep problems on a convenience sample of children with fragile X syndrome. Am. J. Intellect. Dev. Disabil. 2009, 114, 383–392. [Google Scholar] [CrossRef] [PubMed]
  9. Gould, E.L.; Loesch, D.Z.; Martin, M.J.; Hagerman, R.J.; Armstrong, S.M.; Huggins, R.M. Melatonin profiles and sleep characteristics in boys with fragile X syndrome: A preliminary study. Am. J. Med. Genet. 2000, 95, 307–315. [Google Scholar] [CrossRef]
  10. Kidd, S.A.; Lachiewicz, A.; Barbouth, D.; Blitz, R.K.; Delahunty, C.; McBrien, D.; Visootsak, J.; Berry-Kravis, E. Fragile X syndrome: A review of associated medical problems. Pediatrics 2014, 134, 995–1005. [Google Scholar] [CrossRef]
  11. Agar, G.; Brown, C.; Sutherland, D.; Coulborn, S.; Oliver, C.; Richards, C. Sleep disorders in rare genetic syndromes: A meta-analysis of prevalence and profile. Mol. Autism 2021, 12, 18. [Google Scholar] [CrossRef]
  12. Budimirovic, D.B.; Protic, D.D.; Delahunty, C.M.; Andrews, H.F.; Choo, T.H.; Xu, Q.; Berry-Kravis, E.; Kaufmann, W.E.; FORWARD Consortium. Sleep problems in fragile X syndrome: Cross-sectional analysis of a large clinic-based cohort. Am. J. Med. Genet. A 2022, 188, 1029–1039. [Google Scholar] [CrossRef]
  13. Tirosh, E.; Borochowitz, Z. Sleep apnea in fragile X syndrome. Am. J. Med. Genet. 1992, 43, 124–127. [Google Scholar] [CrossRef] [PubMed]
  14. Niemczyk, J.; von Gontard, A.; Equit, M.; Bauer, K.; Naumann, T.; Wagner, C.; Curfs, L. Detailed assessment of incontinence in boys with fragile-X-syndrome in a home setting. Eur. J. Pediatr. 2016, 175, 1325–1334. [Google Scholar] [CrossRef]
  15. Carotenuto, M.; Roccella, M.; Pisani, F.; Matricardi, S.; Verrotti, A.; Farello, G.; Operto, F.F.; Bitetti, I.; Precenzano, F.; Messina, G.; et al. Polysomnographic Findings in Fragile X Syndrome Children with EEG Abnormalities. Behav. Neurol. 2019, 2019, 5202808. [Google Scholar] [CrossRef]
  16. Musumeci, S.A.; Ferri, R.; Elia, M.; Del Gracco, S.; Scuderi, C.; Stefanini, M.C.; Castano, A.; Azan, G. Sleep Neurophysiology in Fragile X Patients. Dev. Brain Dysfunct. 1995, 8, 218–222. [Google Scholar]
  17. Miano, S.; Bruni, O.; Elia, M.; Scifo, L.; Smerieri, A.; Trovato, A.; Verrillo, E.; Terzano, M.G.; Ferri, R. Sleep phenotypes of intellectual disability: A polysomnographic evaluation in subjects with Down syndrome and Fragile-X syndrome. Clin. Neurophysiol. 2008, 119, 1242–1247. [Google Scholar] [CrossRef] [PubMed]
  18. Balietti, M.; Casoli, T.; Di Stefano, G.; Giorgetti, B.; Aicardi, G.; Fattoretti, P. Ketogenic diets: An historical antiepileptic therapy with promising potentialities for the aging brain. Ageing Res. Rev. 2010, 9, 273–279. [Google Scholar] [CrossRef]
  19. Stafstrom, C.E.; Rho, J.M. The ketogenic diet as a treatment paradigm for diverse neurological disorders. Front. Pharmacol. 2012, 3, 59. [Google Scholar] [CrossRef] [PubMed]
  20. El-Rashidy, O.; El-Baz, F.; El-Gendy, Y.; Khalaf, R.; Reda, D.; Saad, K. Ketogenic diet versus gluten free casein free diet in autistic children: A case-control study. Metab. Brain Dis. 2017, 32, 1935–1941. [Google Scholar] [CrossRef] [PubMed]
  21. Spilioti, M.; Evangeliou, A.E.; Tramma, D.; Theodoridou, Z.; Metaxas, S.; Michailidi, E.; Bonti, E.; Frysira, H.; Haidopoulou, A.; Asprangathou, D.; et al. Evidence for treatable inborn errors of metabolism in a cohort of 187 Greek patients with autism spectrum disorder (ASD). Front. Hum. Neurosci. 2013, 7, 858. [Google Scholar] [CrossRef]
  22. Evangeliou, A.; Vlachonikolis, I.; Mihailidou, H.; Spilioti, M.; Skarpalezou, A.; Makaronas, N.; Prokopiou, A.; Christodoulou, P.; Liapi-Adamidou, G.; Helidonis, E.; et al. Application of a ketogenic diet in children with autistic behavior: Pilot study. J. Child. Neurol. 2003, 18, 113–118. [Google Scholar] [CrossRef] [PubMed]
  23. Kasprowska-Liśkiewicz, D.; Liśkiewicz, A.D.; Nowacka-Chmielewska, M.M.; Nowicka, J.; Małecki, A.; Barski, J.J. The ketogenic diet affects the social behavior of young male rats. Physiol. Behav. 2017, 179, 168–177. [Google Scholar] [CrossRef] [PubMed]
  24. Ruskin, D.N.; Fortin, J.A.; Bisnauth, S.N.; Masino, S.A. Ketogenic diets improve behaviors associated with autism spectrum disorder in a sex-specific manner in the EL mouse. Physiol. Behav. 2017, 168, 138–145. [Google Scholar] [CrossRef]
  25. Ruskin, D.N.; Murphy, M.I.; Slade, S.L.; Masino, S.A. Ketogenic diet improves behaviors in a maternal immune activation model of autism spectrum disorder. PLoS ONE 2017, 12, e0171643. [Google Scholar] [CrossRef] [PubMed]
  26. Ruskin, D.N.; Svedova, J.; Cote, J.L.; Sandau, U.; Rho, J.M.; Kawamura, M.; Boison, D.; Masino, S.A. Ketogenic diet improves core symptoms of autism in BTBR mice. PLoS ONE 2013, 8, e65021. [Google Scholar] [CrossRef]
  27. Verpeut, J.L.; DiCicco-Bloom, E.; Bello, N.T. Ketogenic diet exposure during the juvenile period increases social behaviors and forebrain neural activation in adult Engrailed 2 null mice. Physiol. Behav. 2016, 161, 90–98. [Google Scholar] [CrossRef]
  28. Dai, Y.; Zhao, Y.; Tomi, M.; Shin, B.C.; Thamotharan, S.; Mazarati, A.; Sankar, R.; Wang, E.A.; Cepeda, C.; Levine, M.S.; et al. Sex-Specific Life Course Changes in the Neuro-Metabolic Phenotype of Glut3 Null Heterozygous Mice: Ketogenic Diet Ameliorates Electroencephalographic Seizures and Improves Sociability. Endocrinology 2017, 158, 936–949. [Google Scholar] [CrossRef]
  29. Zhang, J.; Fang, Z.; Jud, C.; Vansteensel, M.J.; Kaasik, K.; Lee, C.C.; Albrecht, U.; Tamanini, F.; Meijer, J.H.; Oostra, B.A.; et al. Fragile X-related proteins regulate mammalian circadian behavioral rhythms. Am. J. Hum. Genet. 2008, 83, 43–52. [Google Scholar] [CrossRef]
  30. Allen, C.N. Circadian rhythms, diet, and neuronal excitability. Epilepsia 2008, 49 (Suppl. S8), 124–126. [Google Scholar] [CrossRef]
  31. Genzer, Y.; Dadon, M.; Burg, C.; Chapnik, N.; Froy, O. Effect of dietary fat and the circadian clock on the expression of brain-derived neurotrophic factor (BDNF). Mol. Cell Endocrinol. 2016, 430, 49–55. [Google Scholar] [CrossRef]
  32. Genzer, Y.; Dadon, M.; Burg, C.; Chapnik, N.; Froy, O. Ketogenic diet delays the phase of circadian rhythms and does not affect AMP-activated protein kinase (AMPK) in mouse liver. Mol. Cell Endocrinol. 2015, 417, 124–130. [Google Scholar] [CrossRef] [PubMed]
  33. Greenhill, C. Metabolism: Ketogenic diet rewires circadian clock. Nat. Rev. Endocrinol. 2017, 13, 626. [Google Scholar] [CrossRef] [PubMed]
  34. Nakao, R.; Shimba, S.; Oishi, K. Ketogenic diet induces expression of the muscle circadian gene Slc25a25 via neural pathway that might be involved in muscle thermogenesis. Sci. Rep. 2017, 7, 2885. [Google Scholar] [CrossRef]
  35. Oike, H. Modulation of circadian clocks by nutrients and food factors. Biosci. Biotechnol. Biochem. 2017, 81, 863–870. [Google Scholar] [CrossRef] [PubMed]
  36. Oishi, K.; Uchida, D.; Ohkura, N.; Doi, R.; Ishida, N.; Kadota, K.; Horie, S. Ketogenic diet disrupts the circadian clock and increases hypofibrinolytic risk by inducing expression of plasminogen activator inhibitor-1. Arterioscler. Thromb. Vasc. Biol. 2009, 29, 1571–1577. [Google Scholar] [CrossRef]
  37. Oishi, K.; Uchida, D.; Ohkura, N.; Horie, S. PPARα deficiency augments a ketogenic diet-induced circadian PAI-1 expression possibly through PPARγ activation in the liver. Biochem. Biophys. Res. Commun. 2010, 401, 313–318. [Google Scholar] [CrossRef]
  38. Tognini, P.; Murakami, M.; Liu, Y.; Eckel-Mahan, K.L.; Newman, J.C.; Verdin, E.; Baldi, P.; Sassone-Corsi, P. Distinct Circadian Signatures in Liver and Gut Clocks Revealed by Ketogenic Diet. Cell Metab. 2017, 26, 523–538.e5. [Google Scholar] [CrossRef]
  39. Fenoglio-Simeone, K.A.; Wilke, J.C.; Milligan, H.L.; Allen, C.N.; Rho, J.M.; Maganti, R.K. Ketogenic diet treatment abolishes seizure periodicity and improves diurnal rhythmicity in epileptic Kcna1-null mice. Epilepsia 2009, 50, 2027–2034. [Google Scholar] [CrossRef]
  40. Simeone, T.A.; Samson, K.K.; Matthews, S.A.; Simeone, K.A. In vivo ketogenic diet treatment attenuates pathologic sharp waves and high frequency oscillations in in vitro hippocampal slices from epileptic Kv 1.1α knockout mice. Epilepsia 2014, 55, e44–e49. [Google Scholar] [CrossRef]
  41. Jain, S.V.; Glauser, T.A. Effects of epilepsy treatments on sleep architecture and daytime sleepiness: An evidence-based review of objective sleep metrics. Epilepsia 2014, 55, 26–37. [Google Scholar] [CrossRef]
  42. Hallböök, T.; Lundgren, J.; Rosén, I. Ketogenic diet improves sleep quality in children with therapy-resistant epilepsy. Epilepsia 2007, 48, 59–65. [Google Scholar] [CrossRef]
  43. Campbell, I.G. EEG recording and analysis for sleep research. Curr. Protoc. Neurosci. 2009, 49, 10.2.1–10.2.19. [Google Scholar] [CrossRef]
  44. Ancoli-Israel, S.; Cole, R.; Alessi, C.; Chambers, M.; Moorcroft, W.; Pollak, C.P. The role of actigraphy in the study of sleep and circadian rhythms. Sleep 2003, 26, 342–392. [Google Scholar] [CrossRef] [PubMed]
  45. Berry-Kravis, E. Epilepsy in fragile X syndrome. Dev. Med. Child. Neurol. 2002, 44, 724–728. [Google Scholar] [CrossRef]
  46. Musumeci, S.A.; Colognola, R.M.; Ferri, R.; Gigli, G.L.; Petrella, M.A.; Sanfilippo, S.; Bergonzi, P.; Tassinari, C.A. Fragile-X syndrome: A particular epileptogenic EEG pattern. Epilepsia 1988, 29, 41–47. [Google Scholar] [CrossRef]
  47. Pietropaolo, S.; Guilleminot, A.; Martin, B.; D’Amato, F.R.; Crusio, W.E. Genetic-background modulation of core and variable autistic-like symptoms in Fmr1 knock-out mice. PLoS ONE 2011, 6, e17073. [Google Scholar] [CrossRef] [PubMed]
  48. Berry-Kravis, E.; Knox, A.; Hervey, C. Targeted treatments for fragile X syndrome. J. Neurodev. Disord. 2011, 3, 193–210. [Google Scholar] [CrossRef]
  49. Peier, A.M.; McIlwain, K.L.; Kenneson, A.; Warren, S.T.; Paylor, R.; Nelson, D.L. (Over)correction of FMR1 deficiency with YAC transgenics: Behavioral and physical features. Hum. Mol. Genet. 2000, 9, 1145–1159. [Google Scholar] [CrossRef]
  50. Inoue, S.; Shimoda, M.; Nishinokubi, I.; Siomi, M.C.; Okamura, M.; Nakamura, A.; Kobayashi, S.; Ishida, N.; Siomi, H. A role for the Drosophila fragile X-related gene in circadian output. Curr. Biol. 2002, 12, 1331–1335. [Google Scholar] [CrossRef] [PubMed]
  51. Mineur, Y.S.; Sluyter, F.; de Wit, S.; Oostra, B.A.; Crusio, W.E. Behavioral and neuroanatomical characterization of the Fmr1 knockout mouse. Hippocampus 2002, 12, 39–46. [Google Scholar] [CrossRef]
  52. Qin, M.; Kang, J.; Smith, C.B. Increased rates of cerebral glucose metabolism in a mouse model of fragile X mental retardation. Proc. Natl. Acad. Sci. USA 2002, 99, 15758–15763. [Google Scholar] [CrossRef]
  53. Dockendorff, T.C.; Su, H.S.; McBride, S.M.; Yang, Z.; Choi, C.H.; Siwicki, K.K.; Sehgal, A.; Jongens, T.A. Drosophila lacking dfmr1 activity show defects in circadian output and fail to maintain courtship interest. Neuron 2002, 34, 973–984. [Google Scholar] [CrossRef]
  54. Spencer, C.M.; Alekseyenko, O.; Serysheva, E.; Yuva-Paylor, L.A.; Paylor, R. Altered anxiety-related and social behaviors in the Fmr1 knockout mouse model of fragile X syndrome. Genes. Brain Behav. 2005, 4, 420–430. [Google Scholar] [CrossRef]
  55. Qin, M.; Kang, J.; Smith, C.B. A null mutation for Fmr1 in female mice: Effects on regional cerebral metabolic rate for glucose and relationship to behavior. Neuroscience 2005, 135, 999–1009. [Google Scholar] [CrossRef] [PubMed]
  56. Sekine, T.; Yamaguchi, T.; Hamano, K.; Siomi, H.; Saez, L.; Ishida, N.; Shimoda, M. Circadian phenotypes of Drosophila fragile x mutants in alternative genetic backgrounds. Zool. Sci. 2008, 25, 561–571. [Google Scholar] [CrossRef] [PubMed]
  57. Bushey, D.; Tononi, G.; Cirelli, C. The Drosophila fragile X mental retardation gene regulates sleep need. J. Neurosci. 2009, 29, 1948–1961. [Google Scholar] [CrossRef] [PubMed]
  58. Yuskaitis, C.J.; Mines, M.A.; King, M.K.; Sweatt, J.D.; Miller, C.A.; Jope, R.S. Lithium ameliorates altered glycogen synthase kinase-3 and behavior in a mouse model of fragile X syndrome. Biochem. Pharmacol. 2010, 79, 632–646. [Google Scholar] [CrossRef]
  59. Baker, K.B.; Wray, S.P.; Ritter, R.; Mason, S.; Lanthorn, T.H.; Savelieva, K.V. Male and female Fmr1 knockout mice on C57 albino background exhibit spatial learning and memory impairments. Genes. Brain Behav. 2010, 9, 562–574. [Google Scholar] [CrossRef]
  60. Liu, Z.H.; Chuang, D.M.; Smith, C.B. Lithium ameliorates phenotypic deficits in a mouse model of fragile X syndrome. Int. J. Neuropsychopharmacol. 2011, 14, 618–630. [Google Scholar] [CrossRef]
  61. Olmos-Serrano, J.L.; Corbin, J.G.; Burns, M.P. The GABA(A) receptor agonist THIP ameliorates specific behavioral deficits in the mouse model of fragile X syndrome. Dev. Neurosci. 2011, 33, 395–403. [Google Scholar] [CrossRef]
  62. Pacey, L.K.; Doss, L.; Cifelli, C.; van der Kooy, D.; Heximer, S.P.; Hampson, D.R. Genetic deletion of regulator of G-protein signaling 4 (RGS4) rescues a subset of fragile X related phenotypes in the FMR1 knockout mouse. Mol. Cell Neurosci. 2011, 46, 563–572. [Google Scholar] [CrossRef]
  63. Spencer, C.M.; Alekseyenko, O.; Hamilton, S.M.; Thomas, A.M.; Serysheva, E.; Yuva-Paylor, L.A.; Paylor, R. Modifying behavioral phenotypes in Fmr1KO mice: Genetic background differences reveal autistic-like responses. Autism Res. 2011, 4, 40–56. [Google Scholar] [CrossRef]
  64. Uutela, M.; Lindholm, J.; Louhivuori, V.; Wei, H.; Louhivuori, L.M.; Pertovaara, A.; Akerman, K.; Castrén, E.; Castrén, M.L. Reduction of BDNF expression in Fmr1 knockout mice worsens cognitive deficits but improves hyperactivity and sensorimotor deficits. Genes. Brain Behav. 2012, 11, 513–523. [Google Scholar] [CrossRef]
  65. Uutela, M.; Lindholm, J.; Rantamäki, T.; Umemori, J.; Hunter, K.; Võikar, V.; Castrén, M.L. Distinctive behavioral and cellular responses to fluoxetine in the mouse model for Fragile X syndrome. Front. Cell Neurosci. 2014, 8, 150. [Google Scholar] [CrossRef] [PubMed]
  66. Wrenn, C.C.; Heitzer, A.M.; Roth, A.K.; Nawrocki, L.; Valdovinos, M.G. Effects of clonidine and methylphenidate on motor activity in Fmr1 knockout mice. Neurosci. Lett. 2015, 585, 109–113. [Google Scholar] [CrossRef]
  67. Sørensen, E.M.; Bertelsen, F.; Weikop, P.; Skovborg, M.M.; Banke, T.; Drasbek, K.R.; Scheel-Krüger, J. Hyperactivity and lack of social discrimination in the adolescent Fmr1 knockout mouse. Behav. Pharmacol. 2015, 26, 733–740. [Google Scholar] [CrossRef] [PubMed]
  68. Saré, R.M.; Levine, M.; Smith, C.B. Behavioral Phenotype of Fmr1 Knock-Out Mice during Active Phase in an Altered Light/Dark Cycle. eNeuro 2016, 3. [Google Scholar] [CrossRef] [PubMed]
  69. Schaefer, T.L.; Davenport, M.H.; Grainger, L.M.; Robinson, C.K.; Earnheart, A.T.; Stegman, M.S.; Lang, A.L.; Ashworth, A.A.; Molinaro, G.; Huber, K.M.; et al. Acamprosate in a mouse model of fragile X syndrome: Modulation of spontaneous cortical activity, ERK1/2 activation, locomotor behavior, and anxiety. J. Neurodev. Disord. 2017, 9, 6. [Google Scholar] [CrossRef]
  70. Nolan, S.O.; Reynolds, C.D.; Smith, G.D.; Holley, A.J.; Escobar, B.; Chandler, M.A.; Volquardsen, M.; Jefferson, T.; Pandian, A.; Smith, T.; et al. Deletion of. Brain Behav. 2017, 7, e00800. [Google Scholar] [CrossRef]
  71. Kashima, R.; Redmond, P.L.; Ghatpande, P.; Roy, S.; Kornberg, T.B.; Hanke, T.; Knapp, S.; Lagna, G.; Hata, A. Hyperactive locomotion in a Drosophila model is a functional readout for the synaptic abnormalities underlying fragile X syndrome. Sci. Signal. 2017, 10, eaai8133. [Google Scholar] [CrossRef] [PubMed]
  72. Gauducheau, M.; Lemaire-Mayo, V.; D’Amato, F.R.; Oddi, D.; Crusio, W.E.; Pietropaolo, S. Age-specific autistic-like behaviors in heterozygous Fmr1-KO female mice. Autism Res. 2017, 10, 1067–1078. [Google Scholar] [CrossRef] [PubMed]
  73. Hu, J.; Chen, L.; Yin, J.; Yin, H.; Huang, Y.; Tian, J. Hyperactivity, Memory Defects, and Craniofacial Abnormalities in Zebrafish fmr1 Mutant Larvae. Behav. Genet. 2020, 50, 152–160. [Google Scholar] [CrossRef]
  74. Van Alphen, B.; Yap, M.H.; Kirszenblat, L.; Kottler, B.; van Swinderen, B. A dynamic deep sleep stage in Drosophila. J. Neurosci. 2013, 33, 6917–6927. [Google Scholar] [CrossRef]
  75. Nielsen, D.M.; Derber, W.J.; McClellan, D.A.; Crnic, L.S. Alterations in the auditory startle response in Fmr1 targeted mutant mouse models of fragile X syndrome. Brain Res. 2002, 927, 8–17. [Google Scholar] [CrossRef] [PubMed]
  76. Yan, Q.J.; Asafo-Adjei, P.K.; Arnold, H.M.; Brown, R.E.; Bauchwitz, R.P. A phenotypic and molecular characterization of the fmr1-tm1Cgr fragile X mouse. Genes. Brain Behav. 2004, 3, 337–359. [Google Scholar] [CrossRef]
  77. Yan, Q.J.; Rammal, M.; Tranfaglia, M.; Bauchwitz, R.P. Suppression of two major Fragile X Syndrome mouse model phenotypes by the mGluR5 antagonist MPEP. Neuropharmacology 2005, 49, 1053–1066. [Google Scholar] [CrossRef]
  78. Veeraragavan, S.; Bui, N.; Perkins, J.R.; Yuva-Paylor, L.A.; Paylor, R. The modulation of fragile X behaviors by the muscarinic M4 antagonist, tropicamide. Behav. Neurosci. 2011, 125, 783–790. [Google Scholar] [CrossRef]
  79. Veeraragavan, S.; Graham, D.; Bui, N.; Yuva-Paylor, L.A.; Wess, J.; Paylor, R. Genetic reduction of muscarinic M4 receptor modulates analgesic response and acoustic startle response in a mouse model of fragile X syndrome (FXS). Behav. Brain Res. 2012, 228, 1–8. [Google Scholar] [CrossRef] [PubMed]
  80. Thomas, A.M.; Bui, N.; Perkins, J.R.; Yuva-Paylor, L.A.; Paylor, R. Group I metabotropic glutamate receptor antagonists alter select behaviors in a mouse model for fragile X syndrome. Psychopharmacology 2012, 219, 47–58. [Google Scholar] [CrossRef]
  81. Goebel-Goody, S.M.; Wilson-Wallis, E.D.; Royston, S.; Tagliatela, S.M.; Naegele, J.R.; Lombroso, P.J. Genetic manipulation of STEP reverses behavioral abnormalities in a fragile X syndrome mouse model. Genes. Brain Behav. 2012, 11, 586–600. [Google Scholar] [CrossRef] [PubMed]
  82. Kim, L.; He, L.; Maaswinkel, H.; Zhu, L.; Sirotkin, H.; Weng, W. Anxiety, hyperactivity and stereotypy in a zebrafish model of fragile X syndrome and autism spectrum disorder. Prog. Neuropsychopharmacol. Biol. Psychiatry 2014, 55, 40–49. [Google Scholar] [CrossRef]
  83. Hodges, S.L.; Nolan, S.O.; Reynolds, C.D.; Lugo, J.N. Spectral and temporal properties of calls reveal deficits in ultrasonic vocalizations of adult Fmr1 knockout mice. Behav. Brain Res. 2017, 332, 50–58. [Google Scholar] [CrossRef]
  84. Bonasera, S.J.; Chaudoin, T.R.; Goulding, E.H.; Mittek, M.; Dunaevsky, A. Decreased home cage movement and oromotor impairments in adult Fmr1-KO mice. Genes. Brain Behav. 2017, 16, 564–573. [Google Scholar] [CrossRef] [PubMed]
  85. Saré, R.M.; Harkless, L.; Levine, M.; Torossian, A.; Sheeler, C.A.; Smith, C.B. Deficient Sleep in Mouse Models of Fragile X Syndrome. Front. Mol. Neurosci. 2017, 10, 280. [Google Scholar] [CrossRef]
  86. Ethridge, L.E.; White, S.P.; Mosconi, M.W.; Wang, J.; Byerly, M.J.; Sweeney, J.A. Reduced habituation of auditory evoked potentials indicate cortical hyper-excitability in Fragile X Syndrome. Transl. Psychiatry 2016, 6, e787. [Google Scholar] [CrossRef] [PubMed]
  87. Ethridge, L.E.; White, S.P.; Mosconi, M.W.; Wang, J.; Pedapati, E.V.; Erickson, C.A.; Byerly, M.J.; Sweeney, J.A. Neural synchronization deficits linked to cortical hyper-excitability and auditory hypersensitivity in fragile X syndrome. Mol. Autism 2017, 8, 22. [Google Scholar] [CrossRef]
  88. Wang, J.; Ethridge, L.E.; Mosconi, M.W.; White, S.P.; Binder, D.K.; Pedapati, E.V.; Erickson, C.A.; Byerly, M.J.; Sweeney, J.A. A resting EEG study of neocortical hyperexcitability and altered functional connectivity in fragile X syndrome. J. Neurodev. Disord. 2017, 9, 11. [Google Scholar] [CrossRef] [PubMed]
  89. Sinclair, D.; Featherstone, R.; Naschek, M.; Nam, J.; Du, A.; Wright, S.; Pance, K.; Melnychenko, O.; Weger, R.; Akuzawa, S.; et al. GABA-B Agonist Baclofen Normalizes Auditory-Evoked Neural Oscillations and Behavioral Deficits in the Fmr1 knockout mouse model of fragile X syndrome. eNeuro 2017, 4. [Google Scholar] [CrossRef]
  90. Lovelace, J.W.; Ethell, I.M.; Binder, D.K.; Razak, K.A. Translation-relevant EEG phenotypes in a mouse model of Fragile X Syndrome. Neurobiol. Dis. 2018, 115, 39–48. [Google Scholar] [CrossRef]
  91. Wen, T.H.; Lovelace, J.W.; Ethell, I.M.; Binder, D.K.; Razak, K.A. Developmental Changes in EEG Phenotypes in a Mouse Model of Fragile X Syndrome. Neuroscience 2019, 398, 126–143. [Google Scholar] [CrossRef] [PubMed]
  92. Jonak, C.R.; Lovelace, J.W.; Ethell, I.M.; Razak, K.A.; Binder, D.K. Multielectrode array analysis of EEG biomarkers in a mouse model of Fragile X Syndrome. Neurobiol. Dis. 2020, 138, 104794. [Google Scholar] [CrossRef] [PubMed]
  93. Lovelace, J.W.; Rais, M.; Palacios, A.R.; Shuai, X.S.; Bishay, S.; Popa, O.; Pirbhoy, P.S.; Binder, D.K.; Nelson, D.L.; Ethell, I.M.; et al. Deletion of Fmr1 from Forebrain Excitatory Neurons Triggers Abnormal Cellular, EEG, and Behavioral Phenotypes in the Auditory Cortex of a Mouse Model of Fragile X Syndrome. Cereb. Cortex 2020, 30, 969–988. [Google Scholar] [CrossRef]
  94. Jonak, C.R.; Sandhu, M.S.; Assad, S.A.; Barbosa, J.A.; Makhija, M.; Binder, D.K. The PDE10A Inhibitor TAK-063 Reverses Sound-Evoked EEG Abnormalities in a Mouse Model of Fragile X Syndrome. Neurotherapeutics 2021, 18, 1175–1187. [Google Scholar] [CrossRef] [PubMed]
  95. Saraf, T.S.; McGlynn, R.P.; Bhatavdekar, O.M.; Booth, R.G.; Canal, C.E. FPT, a 2-Aminotetralin, Is a Potent Serotonin 5-HT. ACS Chem. Neurosci. 2022, 13, 3629–3640. [Google Scholar] [CrossRef]
  96. Wong, H.; Hooper, A.W.M.; Niibori, Y.; Lee, S.J.; Hategan, L.A.; Zhang, L.; Karumuthil-Melethil, S.; Till, S.M.; Kind, P.C.; Danos, O.; et al. Sexually dimorphic patterns in electroencephalography power spectrum and autism-related behaviors in a rat model of fragile X syndrome. Neurobiol. Dis. 2020, 146, 105118. [Google Scholar] [CrossRef] [PubMed]
  97. Kenny, A.; Wright, D.; Stanfield, A.C. EEG as a translational biomarker and outcome measure in fragile X syndrome. Transl. Psychiatry 2022, 12, 34. [Google Scholar] [CrossRef]
  98. Van der Molen, M.J.; Van der Molen, M.W. Reduced alpha and exaggerated theta power during the resting-state EEG in fragile X syndrome. Biol. Psychol. 2013, 92, 216–219. [Google Scholar] [CrossRef]
  99. Radwan, B.; Dvorak, D.; Fenton, A.A. Impaired cognitive discrimination and discoordination of coupled theta-gamma oscillations in Fmr1 knockout mice. Neurobiol. Dis. 2016, 88, 125–138. [Google Scholar] [CrossRef]
  100. Arbab, T.; Battaglia, F.P.; Pennartz, C.M.A.; Bosman, C.A. Abnormal hippocampal theta and gamma hypersynchrony produces network and spike timing disturbances in the Fmr1-KO mouse model of Fragile X syndrome. Neurobiol. Dis. 2018, 114, 65–73. [Google Scholar] [CrossRef]
  101. Boone, C.E.; Davoudi, H.; Harrold, J.B.; Foster, D.J. Abnormal Sleep Architecture and Hippocampal Circuit Dysfunction in a Mouse Model of Fragile X Syndrome. Neuroscience 2018, 384, 275–289. [Google Scholar] [CrossRef]
  102. Saré, R.M.; Song, A.; Loutaev, I.; Cook, A.; Maita, I.; Lemons, A.; Sheeler, C.; Smith, C.B. Negative Effects of Chronic Rapamycin Treatment on Behavior in a Mouse Model of Fragile X Syndrome. Front. Mol. Neurosci. 2017, 10, 452. [Google Scholar] [CrossRef]
  103. Abolghasemi, A.; Carullo, M.P.; Aguilera, E.C.; Laroui, A.; Plantefeve, R.; Rojas, D.; Benachenhou, S.; Ramírez, M.V.; Proteau-Lemieux, M.; Lepage, J.F.; et al. Alteration of Fatty Acid Profile in Fragile X Syndrome. Int. J. Mol. Sci. 2022, 23, 10815. [Google Scholar] [CrossRef]
  104. Schaefer, T.L.; Ashworth, A.A.; Tiwari, D.; Tomasek, M.P.; Parkins, E.V.; White, A.R.; Snider, A.; Davenport, M.H.; Grainger, L.M.; Becker, R.A.; et al. GABA. Front. Psychiatry 2021, 12, 678090. [Google Scholar] [CrossRef] [PubMed]
  105. Berzhanskaya, J.; Phillips, M.A.; Gorin, A.; Lai, C.; Shen, J.; Colonnese, M.T. Disrupted Cortical State Regulation in a Rat Model of Fragile X Syndrome. Cereb. Cortex 2017, 27, 1386–1400. [Google Scholar] [CrossRef]
  106. Masi, D.; Spoltore, M.E.; Rossetti, R.; Watanabe, M.; Tozzi, R.; Caputi, A.; Risi, R.; Balena, A.; Gandini, O.; Mariani, S.; et al. The Influence of Ketone Bodies on Circadian Processes Regarding Appetite, Sleep and Hormone Release: A Systematic Review of the Literature. Nutrients 2022, 14, 1410. [Google Scholar] [CrossRef] [PubMed]
  107. Titos, I.; Juginović, A.; Vaccaro, A.; Nambara, K.; Gorelik, P.; Mazor, O.; Rogulja, D. A gut-secreted peptide suppresses arousability from sleep. Cell 2023, 186, 2273–2274. [Google Scholar] [CrossRef] [PubMed]
  108. Zhuang, H.; Fujikura, Y.; Ohkura, N.; Higo-Yamamoto, S.; Mishima, T.; Oishi, K. A ketogenic diet containing medium-chain triglycerides reduces REM sleep duration without significant influence on mouse circadian phenotypes. Food Res. Int. 2023, 169, 112852. [Google Scholar] [CrossRef]
  109. Bear, M.F.; Huber, K.M.; Warren, S.T. The mGluR theory of fragile X mental retardation. Trends Neurosci. 2004, 27, 370–377. [Google Scholar] [CrossRef] [PubMed]
  110. Holst, S.C.; Sousek, A.; Hefti, K.; Saberi-Moghadam, S.; Buck, A.; Ametamey, S.M.; Scheidegger, M.; Franken, P.; Henning, A.; Seifritz, E.; et al. Cerebral mGluR5 availability contributes to elevated sleep need and behavioral adjustment after sleep deprivation. Elife 2017, 6, e28751. [Google Scholar] [CrossRef] [PubMed]
  111. Westmark, C.J.; Malter, J.S. FMRP mediates mGluR5-dependent translation of amyloid precursor protein. PLoS Biol. 2007, 5, e52. [Google Scholar] [CrossRef]
  112. Filon, M.J.; Wallace, E.; Wright, S.; Douglas, D.J.; Steinberg, L.I.; Verkuilen, C.L.; Westmark, P.R.; Maganti, R.K.; Westmark, C.J. Sleep and diurnal rest-activity rhythm disturbances in a mouse model of Alzheimer’s disease. Sleep 2020, 43, zsaa087. [Google Scholar] [CrossRef] [PubMed]
  113. Crusio, W.E. Flanking gene and genetic background problems in genetically manipulated mice. Biol. Psychiatry 2004, 56, 381–385. [Google Scholar] [CrossRef] [PubMed]
  114. Crusio, W.E.; Goldowitz, D.; Holmes, A.; Wolfer, D. Standards for the publication of mouse mutant studies. Genes. Brain Behav. 2009, 8, 1–4. [Google Scholar] [CrossRef]
  115. Wallace, E.; Kim, D.Y.; Kim, K.M.; Chen, S.; Blair Braden, B.; Williams, J.; Jasso, K.; Garcia, A.; Rho, J.M.; Bimonte-Nelson, H.; et al. Differential effects of duration of sleep fragmentation on spatial learning and synaptic plasticity in pubertal mice. Brain Res. 2015, 1615, 116–128. [Google Scholar] [CrossRef] [PubMed]
  116. Wallace, E.; Wright, S.; Schoenike, B.; Roopra, A.; Rho, J.M.; Maganti, R.K. Altered circadian rhythms and oscillation of clock genes and sirtuin 1 in a model of sudden unexpected death in epilepsy. Epilepsia 2018, 59, 1527–1539. [Google Scholar] [CrossRef] [PubMed]
Ijms 24 14460 g001
Figure 1. Study Design. Male WT and Fmr1KO mice were randomized to AIN-76A versus KD at P18. At 5 months of age, mice underwent surgery for EEG/EMG electrode implantation followed by EEG recordings over 7 days and data analysis. Mice were weighed on the day of surgery. Blood samples were tested for glucose and ketone levels at the time of euthanization. Representative sleep stage hypnograms as a function of genotype and diet are shown where yellow = wake state, blue = NREM sleep, and red = REM sleep.
Figure 1. Study Design. Male WT and Fmr1KO mice were randomized to AIN-76A versus KD at P18. At 5 months of age, mice underwent surgery for EEG/EMG electrode implantation followed by EEG recordings over 7 days and data analysis. Mice were weighed on the day of surgery. Blood samples were tested for glucose and ketone levels at the time of euthanization. Representative sleep stage hypnograms as a function of genotype and diet are shown where yellow = wake state, blue = NREM sleep, and red = REM sleep.
Ijms 24 14460 g001
Ijms 24 14460 g002
Figure 2. Effect of KD on Sleep Architecture in WT and Fmr1KO Mice as a Function of Light and Dark Cycles. EEG/EMG recordings were scored for wake, sleep, NREM and REM activity and the data parsed into 24-h full day and 12-h light/dark bins starting at Zeitgeber time zero. The average percent sleep state was plotted versus bin for (A) % wake, (B) % sleep, (C) % NREM, and (D) % REM. Mouse cohorts included WT fed AIN-76A (n = 12), WT fed KD (n = 9), Fmr1KO fed AIN-76A (n = 16), and Fmr1KO fed KD (n = 13). Statistics with GraphPad Prism included 2-way ANOVA with post-hoc Tukey multiple comparison tests. Key for statistical significance: * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001.
Figure 2. Effect of KD on Sleep Architecture in WT and Fmr1KO Mice as a Function of Light and Dark Cycles. EEG/EMG recordings were scored for wake, sleep, NREM and REM activity and the data parsed into 24-h full day and 12-h light/dark bins starting at Zeitgeber time zero. The average percent sleep state was plotted versus bin for (A) % wake, (B) % sleep, (C) % NREM, and (D) % REM. Mouse cohorts included WT fed AIN-76A (n = 12), WT fed KD (n = 9), Fmr1KO fed AIN-76A (n = 16), and Fmr1KO fed KD (n = 13). Statistics with GraphPad Prism included 2-way ANOVA with post-hoc Tukey multiple comparison tests. Key for statistical significance: * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001.
Ijms 24 14460 g002
Ijms 24 14460 g003
Figure 3. Effect of KD on Sleep Architecture in WT and Fmr1KO Mice as a Function of Time of Day. EEG/EMG recordings were scored for wake, sleep, NREM and REM activity and the data parsed into 2-h bins starting at Z0 (lights on). The average percent sleep state was plotted versus 2-h time bins for (A) % wake, (B) % sleep, (C) % NREM, and (D) % REM. Mouse cohorts included WT fed AIN-76A (n = 12), WT fed KD (n = 9), Fmr1KO fed AIN-76A (n = 16), and Fmr1KO fed KD (n = 13). Statistics with GraphPad Prism included 2-way ANOVA with repeated measures and post-hoc Tukey multiple comparison tests. Key for statistical significance: WT/AIN-76A versus Fmr1KO/AIN-76A = “a”, WT/AIN-76A versus WT/KD = “b”, WT/AIN-76A versus Fmr1KO/KD = “c”, Fmr1KO/AIN-76A versus WT/KD = “d”, Fmr1KO/AIN-76A versus Fmr1KO/KD = “e”, and WT/KD versus Fmr1KO/KD = “f”; and aa p < 0.01, b p < 0.05, bb p < 0.01, bbb p < 0.001, bbbb p < 0.0001, c p < 0.05, cc p < 0.01, ccc p < 0.001, cccc p < 0.0001, d p < 0.05, dd p < 0.01, ddd p < 0.001, dddd p < 0.0001, e p < 0.05, ee p < 0.01, eeee p < 0.0001, f p < 0.05, ff p < 0.01.
Figure 3. Effect of KD on Sleep Architecture in WT and Fmr1KO Mice as a Function of Time of Day. EEG/EMG recordings were scored for wake, sleep, NREM and REM activity and the data parsed into 2-h bins starting at Z0 (lights on). The average percent sleep state was plotted versus 2-h time bins for (A) % wake, (B) % sleep, (C) % NREM, and (D) % REM. Mouse cohorts included WT fed AIN-76A (n = 12), WT fed KD (n = 9), Fmr1KO fed AIN-76A (n = 16), and Fmr1KO fed KD (n = 13). Statistics with GraphPad Prism included 2-way ANOVA with repeated measures and post-hoc Tukey multiple comparison tests. Key for statistical significance: WT/AIN-76A versus Fmr1KO/AIN-76A = “a”, WT/AIN-76A versus WT/KD = “b”, WT/AIN-76A versus Fmr1KO/KD = “c”, Fmr1KO/AIN-76A versus WT/KD = “d”, Fmr1KO/AIN-76A versus Fmr1KO/KD = “e”, and WT/KD versus Fmr1KO/KD = “f”; and aa p < 0.01, b p < 0.05, bb p < 0.01, bbb p < 0.001, bbbb p < 0.0001, c p < 0.05, cc p < 0.01, ccc p < 0.001, cccc p < 0.0001, d p < 0.05, dd p < 0.01, ddd p < 0.001, dddd p < 0.0001, e p < 0.05, ee p < 0.01, eeee p < 0.0001, f p < 0.05, ff p < 0.01.
Ijms 24 14460 g003
Ijms 24 14460 g004
Figure 4. Effect of KD on Sleep Micro-Architecture (Number of Bouts) in WT and Fmr1KO Mice as a Function of Light and Dark Cycles. EEG/EMG recordings were scored for wake, sleep, NREM and REM activity and the data parsed into 24-h full day and 12-h light/dark bins starting at Z0. The average number of sleep/wake state bouts was plotted versus bin for (A) wake bouts, (B) sleep bouts, (C) NREM bouts, and (D) REM bouts. Mouse cohorts included WT fed AIN-76A (n = 12), WT fed KD (n = 9), Fmr1KO fed AIN-76A (n = 16), and Fmr1KO fed KD (n = 13). Statistics with GraphPad Prism included 2-way ANOVA with post-hoc Tukey multiple comparison tests. Key for statistical significance: * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001.
Figure 4. Effect of KD on Sleep Micro-Architecture (Number of Bouts) in WT and Fmr1KO Mice as a Function of Light and Dark Cycles. EEG/EMG recordings were scored for wake, sleep, NREM and REM activity and the data parsed into 24-h full day and 12-h light/dark bins starting at Z0. The average number of sleep/wake state bouts was plotted versus bin for (A) wake bouts, (B) sleep bouts, (C) NREM bouts, and (D) REM bouts. Mouse cohorts included WT fed AIN-76A (n = 12), WT fed KD (n = 9), Fmr1KO fed AIN-76A (n = 16), and Fmr1KO fed KD (n = 13). Statistics with GraphPad Prism included 2-way ANOVA with post-hoc Tukey multiple comparison tests. Key for statistical significance: * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001.
Ijms 24 14460 g004
Ijms 24 14460 g005
Figure 5. Effect of KD on Sleep Micro-Architecture (Length of Bouts) in WT and Fmr1KO Mice as a Function of Light and Dark Cycles. EEG/EMG recordings were scored for wake, sleep, NREM and REM activity and the data parsed into 24-h full day and 12-h light/dark bins starting at Z0. The average length of time of sleep/wake bouts was plotted versus bin for (A) wake bouts, (B) sleep bouts, (C) NREM bouts, and (D) REM bouts. Mouse cohorts included WT fed AIN-76A (n = 12), WT fed KD (n = 9), Fmr1KO fed AIN-76A (n = 16), and Fmr1KO fed KD (n = 13). Statistics with GraphPad Prism included 2-way ANOVA with post-hoc Tukey multiple comparison tests. Key for statistical significance: * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001.
Figure 5. Effect of KD on Sleep Micro-Architecture (Length of Bouts) in WT and Fmr1KO Mice as a Function of Light and Dark Cycles. EEG/EMG recordings were scored for wake, sleep, NREM and REM activity and the data parsed into 24-h full day and 12-h light/dark bins starting at Z0. The average length of time of sleep/wake bouts was plotted versus bin for (A) wake bouts, (B) sleep bouts, (C) NREM bouts, and (D) REM bouts. Mouse cohorts included WT fed AIN-76A (n = 12), WT fed KD (n = 9), Fmr1KO fed AIN-76A (n = 16), and Fmr1KO fed KD (n = 13). Statistics with GraphPad Prism included 2-way ANOVA with post-hoc Tukey multiple comparison tests. Key for statistical significance: * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001.
Ijms 24 14460 g005
Ijms 24 14460 g006
Figure 6. Effect of KD on Ability to Enter REM Sleep in WT and Fmr1KO Mice. EEG/EMG recordings were scored for the number of failed attempts to enter REM and expressed as a percentage of total attempts. Mouse cohorts included WT fed AIN-76A (n = 12), WT fed KD (n = 9), Fmr1KO fed AIN-76A (n = 16), and Fmr1KO fed KD (n = 13). Statistics with GraphPad Prism included 2-way ANOVA with post-hoc Tukey multiple comparison tests. Key for statistical significance: * p < 0.05.
Figure 6. Effect of KD on Ability to Enter REM Sleep in WT and Fmr1KO Mice. EEG/EMG recordings were scored for the number of failed attempts to enter REM and expressed as a percentage of total attempts. Mouse cohorts included WT fed AIN-76A (n = 12), WT fed KD (n = 9), Fmr1KO fed AIN-76A (n = 16), and Fmr1KO fed KD (n = 13). Statistics with GraphPad Prism included 2-way ANOVA with post-hoc Tukey multiple comparison tests. Key for statistical significance: * p < 0.05.
Ijms 24 14460 g006
Table 1. Comparison of Rest/Activity with Sleep Phenotypes in Male WT and Fmr1KO Mice.
Table 1. Comparison of Rest/Activity with Sleep Phenotypes in Male WT and Fmr1KO Mice.
TreatmentActigraphy [4]Sleep EEG Concur
KD start at P18
Genotype effectsnone (AIN-76A)WT ↑ sleep (AIN-76A Z10–12)-
Fmr1KO ↑ activity (KD Z0–6) ([4] Figure 2D)Fmr1KO ↑ wake and ↓ sleep, NREM (KD Z2–4) (Figure 3)✓
Fmr1KO ↑ wake and ↓ NREM (KD Z22–24) (Figure 3)-
Diet effectsKD ↓ activity (WT and Fmr1KO Z0–6) ([4] Figure 2D)KD ↓ REM Z0–12 (Figure 2 and Figure S5)-
KD ↓ activity (WT and Fmr1KO Z12–24) ([4] Figure 2D)KD ↑ sleep, NREM, REM (WT and Fmr1KO Z12–24) (Figure 2 and Figure S5)✓
KD start at 2–3 months of age
Genotype effectsFmr1KO ↑ activity (AIN76A Z0–6) ([4] Figure 3E)TBD-
Diet effectsKD ↓ activity (Fmr1KO Z12-24) ([4] Figure 3E)TBD-
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Westmark, P.R.; Gholston, A.K.; Swietlik, T.J.; Maganti, R.K.; Westmark, C.J. Ketogenic Diet Affects Sleep Architecture in C57BL/6J Wild Type and Fragile X Mice. Int. J. Mol. Sci. 2023, 24, 14460. https://0-doi-org.brum.beds.ac.uk/10.3390/ijms241914460

AMA Style

Westmark PR, Gholston AK, Swietlik TJ, Maganti RK, Westmark CJ. Ketogenic Diet Affects Sleep Architecture in C57BL/6J Wild Type and Fragile X Mice. International Journal of Molecular Sciences. 2023; 24(19):14460. https://0-doi-org.brum.beds.ac.uk/10.3390/ijms241914460

Chicago/Turabian Style

Westmark, Pamela R., Aaron K. Gholston, Timothy J. Swietlik, Rama K. Maganti, and Cara J. Westmark. 2023. "Ketogenic Diet Affects Sleep Architecture in C57BL/6J Wild Type and Fragile X Mice" International Journal of Molecular Sciences 24, no. 19: 14460. https://0-doi-org.brum.beds.ac.uk/10.3390/ijms241914460

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop