In vivo Evidence for Cerebral Bioenergetic Abnormalities in Schizophrenia Measured Using ³¹P Magnetization Transfer Spectroscopy

Abstract

Context:

Abnormalities in neural activity and cerebral bioenergetics have been observed in schizophrenia (SZ). Further defining energy metabolism anomalies would provide crucial information about molecular mechanisms underlying SZ and may be valuable for developing novel treatment strategies.

Objective:

To investigate cerebral bioenergetics in SZ via measurement of creatine kinase (CK) activity using in vivo ³¹P magnetization transfer (MT) spectroscopy.

Design:

Cross-sectional case-control study.

Setting:

Clinical services and brain imaging center of an academic psychiatric hospital.

Participants:

26 participants with chronic SZ (including a subgroup diagnosed with schizoaffective disorder) and 26 age- and sex-matched healthy controls (25 usable MRS datasets from the latter).

Main Outcome Measures:

The primary outcome measure was the forward rate constant (k_f) of the CK enzyme in the frontal lobe. We also collected independent measures of brain parenchymal pH and steady-state metabolite ratios of high energy phosphate-containing compounds (PCr and ATP), inorganic phosphate (Pi), and the two membrane phospholipids PDE and PME.

Results:

There was a substantial (22%) and statistically significant (p=0.003) reduction in CK k_f in SZ. In addition, intracellular pH was significantly reduced (7.00 vs. 7.03; p=0.007) in this condition. PCr/ATP, Pi/ATP, and PME/ATP ratios were not substantially altered in SZ, but there was a significant (p=0.015) reduction in the PDE/ATP ratio. The abnormalities were similar between SZ and schizoaffective disorder.

Conclusion:

Using a novel ³¹P-MT-MRS approach, we provide direct and compelling evidence for a specific bioenergetic abnormality in SZ. Reduced k_f of the CK enzyme is consistent with an abnormality in storage and utilization of brain energy. The intracellular pH reduction suggests a relative increase in the contribution of glycolysis to ATP synthesis, providing convergent evidence for bioenergetic abnormalities in SZ. The similar PCr/ATP ratios in SZ and healthy subjects suggest that the underlying bioenergetics abnormality is not associated with change in this metabolite ratio.

INTRODUCTION

Schizophrenia (SZ) is a common and severe brain disorder associated with poor functional outcome. Several lines of evidence suggest that mitochondrial and bioenergetic abnormalities are associated with SZ^1-3. These include abnormal levels of metabolites involved in energy metabolism [phosphocreatine (PCr) and adenosine triphosphate (ATP)] reported using ³¹P- magnetic resonance spectroscopy (MRS)^4-7, creatine (Cr), reported using ¹H-MRS^4,8, dysfunctional oxidative phosphorylation⁹, as well as altered mitochondria related gene expression^{2, 10} observed in postmortem studies. Since energy production is essential for numerous metabolic pathways and for neurotransmitter cycling in the brain, abnormalities in these processes will impact all aspects of brain function. In vivo probes of mitochondrial function and energy metabolism would provide crucial information to characterize the exact bioenergetic abnormalities in SZ and delineate their relationship to pathophysiology and symptom formation.

Adenosine triphosphate (ATP), a high-energy phosphate (HEP) compound, is essential for all physiological mechanisms that require energy in living tissues. In the human brain, the majority of ATP is used to restore cell membrane ion gradients and to regulate enzyme activity and signaling pathways^{11, 12}. ATP is formed from adenosine diphosphate (ADP) and inorganic phosphate (Pi) in mitochondria primarily through oxidative phosphorylation catalyzed by the enzyme ATP synthase (ATP_syn)¹¹. This process is tightly coupled to the reversible creatine kinase (CK) reaction, that transfers HEP moieties from ATP to Cr to generate a storage of HEP bonds in PCr or draws on PCr to restore levels of ATP¹³. Thus, PCr acts as a HEP reservoir and maintains stable ATP levels during altered neuronal activity^{14, 15}. The chemical exchange of phosphate moieties between PCr↔ATP↔Pi plays a fundamental role in cerebral bioenergetics and brain function. In principle, these chemical exchange rates can be measured explicitly and noninvasively using in vivo ³¹P magnetization transfer spectroscopy (³¹P-MT-MRS)^15-19. This dynamic MRS approach relies on saturating the signal from one HEP containing metabolite (e.g. either PCr or ATP) and observing the loss of signal in the other metabolite with progressive MRS acquisitions. The rate of this signal loss is related to the rate of HEP transfer via the CK reaction. Note that this approach reports overall CK reaction rate and cannot distinguish CK signal from the mitochondria and cytosol.

Despite suggestions of abnormal mitochondrial and bioenergetic function in the frontal lobe in SZ, CK and ATP_syn reaction rates have not previously been measured in this condition in vivo. This approach examines specific biological processes directly involved in bioenergetics, as opposed to generic glucose or oxygen metabolic rates available through other methodologies such as PET. Therefore, the information to be gleaned may be especially relevant to molecular pathophysiology and treatment development for neuropsychiatric conditions. We recently implemented the ³¹P-MT-MRS approach on a 4T MRI scanner at our center to accomplish this goal²⁰. Here, we report the results of our primary measure in this experiment, the CK reaction rate in the human frontal lobe in SZ and age- and sex- matched controls.

We hypothesized that we would find a reduced CK reaction rate in SZ, consistent with the literature on mitochondrial and bioenergetics abnormalities in this condition. We focused on the prefrontal cortex because this is where the majority of bioenergetic abnormalities in SZ are reported^{7, 21, 22}. Although the ATP_syn reaction is also of interest, it is more challenging to quantify (see ^{18, 20, 23}) and we could not measure this reaction reliably in the current clinical study where scan time was shorter and volume of interest smaller than in our previous work (unpublished data). As part of the ³¹P-MT-MRS experiment, we also measured parenchymal pH, magnesium ion concentration, the intrinsic T₁ (longitudinal relaxation time in the absence of chemical exchange) of PCr, and steady state ratios of HEP-containing metabolites as secondary measures. We hypothesized that we would see a reduction in pH reflecting elevated lactic acid levels due to higher relative glycolysis rates compensating for bioenergetic dysfunction. We could not entertain a directional hypothesis on metabolite ratio levels because of discrepancies in the past literature.

METHODS

Human subjects

See Supplemental Materials for details of our IRB-approved human subjects procedures and Table 1 for subject characteristics.

Table 1.

Demographic and clinical characteristics of study participants

	Healthy Control (N=26)	Schizophrenia (N=26)	Statistical Evaluation
Age (years)	31.9±8.9	34.5±8.4	p = 0.27
Sex	14M,12F	13M,13F	χ2=0.077; p=0.78
BMI	24.4±3.7	28.5±4.8	p = 0.001
Education*	6.5±1.8	5.1±1.5	p = 0.005
Parental SES	6.0±2.3	6.1±2.3	p = 0.82
Age at onset	--	24.5±7.9
Lifetime number of suicide attempts	--	0.7±1.6
Lifetime number of hospitalizations	--	5.5±3.9
MADRS	--	11.9±10.6
YMRS	--	9.2±6.0
MCAS	--	44.7±6.9
PANSS	--	56.7±17.4
NAART	110.8±7.7	108.3±11.0	p = 0.36
Lithium	--	3
Anticonvulsants	--	8
SGAs	--	18
FGAs	--	2
CPZ equivalents	--	392.3±470.8
Benzodiazepines	--	11

Abbreviations: SES: Socioeconomic status; SGA: second generation antipsychotic; FGA: first generation antipsychotic. Other abbreviations as in the text.

Parental SES calculated according to the Hollingshead scale.

^*Education code: 3: graduated high school; 4: part college; 5: graduated 2 year college; 6: graduated 4 year college; 7: part graduate/professional school; 8: completed graduate/professional school

MRI and In vivo ³¹P MRS experiments

The diagnostic scan was performed in a Siemens 3 Tesla Trio scanner (Erlangen, Germany); details as in previous publications²⁴. All ³¹P-MT-MRS study related acquisitions were conducted using a 4T whole-body scanner interfaced with a Varian INOVA console. Brain anatomic imaging and ³¹P-MRS were acquired by a specially designed half-helmet head coil with dual-tuned frequency channels (proton, quadrature surface coil, and phosphate, 7-cm surface coil) placed on the forehead. Each channel has independent transmission and receiver functions with dedicated decoupling.

First, a rapid 2D gradient-recalled echo image was used to acquire single images in three dimensions. This permitted rapid determination of subject position; the subject was repositioned if necessary. Manual global shimming of unsuppressed water signal was then undertaken, yielding a global water linewidth of ≤ 24 Hz. High-contrast T₂-weighted sagittal and axial images were acquired to serve as an anatomical guide to position MRS voxels. Localized shimming with a voxel of 6×6×4 cm³ on the prefrontal lobe was performed manually to further minimize local field inhomogeneity for ³¹P-MRS.

The ³¹P signal was acquired using a ³¹P surface coil with outer-volume saturation¹⁶ (Figure 1). The ³¹P MT pulse sequence and experimental design have been described in previous papers^{17, 18} and see Supplemental Materials.

Figure 1.

T₂-weighted brain anatomic imaging (in the sagittal orientation) and the sensitivity profile (6×6×4 cm³) of the 7-cm ³¹P surface coil placed over the forehead. In order to delineate the ³¹P sensitivity region of the surface coil with outer-volume saturation in the current experiment, 1D profiles of Pi signal along three orthogonal dimensions were acquired from a phantom (14-cm diameter cylindrical bottle) with inorganic phosphate solution ([Pi] = 0.6 M and pH = 7.1).

³¹P Spectrum processing

The ³¹P spectra were analyzed in the time domain using the AMARES algorithm within the jMRUI-software package²⁵. See Supplemental Materials for details.

Quantification of pH

Brain pH was estimated based on the chemical shift difference in ppm between Pi and PCr²⁶.

Forward rate constant and flux of CK reaction measured by ³¹P-MT-MRS

The chemical exchange reaction among PCr and ATP as well as the relative chemical reaction parameters are as follows^{26, 27}:

$$PCr+MgAD{P}^{-}+H^{+}\stackrel{CK}{\leftrightarrow }Cr+MgAT{P}^{-2}$$ (1)

$$k_f=k\times [H^{+}]\times [ADP]$$ (2)

$$K_{eq}^{CK}=\frac{[ADP]\times [H^{+}]\times [PCr]}{[Cr]\times [ATP]}$$ (3)

where k_f (s⁻¹) and K_eq^CK are the pseudo first-order forward rate constant and equilibrium constant of the CK reaction, respectively. In Equation 2, k is a parameter related to the CK enzyme activity, partially modulated by the concentration of the CK enzyme or its 3D structure. Specifically, k_f can be determined by the experiments using progressive saturation on the γ-ATP resonance, where the magnetizations of PCr is governed by Equation 4²⁸:

$$M_s(t)=M_0\left[\left(\frac{k_f}{\alpha }\right)e^{-\alpha t}+\left(\frac{1}{\alpha T_1}\right)\right]with\alpha =k_f+\frac{1}{T_1}$$ (4)

In this equation, M_s and M₀ are the magnetization of PCr at saturation time (t) and Boltzmann thermal equilibrium condition, respectively. T₁ is the intrinsic spin-lattice relaxation time of PCr. Therefore, the k_f of the CK reaction and the T₁ of PCr can be determined by fitting the experimental data to a single exponential decay. Seven saturation time points (0, 0.48, 1.89, 3.78, 6.61, 8.50, 12.28 s) were applied in the current study.

Lastly, the chemical reaction flux (F) is calculated by Equation 5:

$$F(\mu mol∕g∕\text{min})=60\times k_f\times [M]∕1.1$$ (5)

where [M] is the metabolite concentration (μmol/ml) of PCr, determined via the PCr/β-ATP ratio assuming [ATP]=3.0 mM²⁹. Note that here we assumed a fixed ATP concentration/ Everywhere else in this manuscript we have used metabolite ratios instead. The chemical reaction fluxes were converted to the well-accepted units of μmol/g/min using an assumed brain tissue density of 1.1g/ml^{17, 18}.

Statistical approach

See Supplemental Materials for details of our statistical approach.

RESULTS

Forward rate constants and fluxes

The quality control measure of linewidth (in Hz) of the PCr resonance with 10 Hz line broadening in the magnetization transfer experiment did not differ for the first or last acquired spectra between the HC and SZ groups (19.2±1.8 vs. 20.8±5.7, p=0.173; and 20.3±2.2 vs. 22.0±5.8, p=0.163, respectively). Likewise, PCr SNR did not differ between the HC and SZ groups (19.2±6.6 vs. 16.4±7.6, p=0.199, respectively).

The principle of the magnetization transfer experiment is depicted in Figure 2. The intrinsic T₁, k_f, and flux parameters were determined as previously described (Table 2). The SZ group showed a substantial (22%) and highly statistically significant reduction in CK k_f [F(51,3)=9.580; p=0.003] (Figure 3). There was no difference in this measure between patients diagnosed with SZ and schizoaffective disorder (p=0.193). We also calculated the flux through this reaction although this was not our primary measure. This parameter was decreased by 19% in SZ [F(51,3)=6.264; p=0.032]. Finally, intrinsic T1 relaxation time was similar in SZ and HC subjects (Table 2).

Figure 2.

In vivo ³¹P spectra with 10-Hz line broadening in the absence and presence of saturating γ-ATP resonance (illustrated by the back arrows) demonstrated in left and right columns, respectively. The spectra on top and bottom rows were acquired from a representative SZ and HC subject, respectively. Saturation time was 12.28 s. All resonance peaks are labeled in the lowest spectrum. The magnetization of PCr was reduced by 56% and 43% for the HC and SZ subject, respectively. pH was calculated via pH = 6.77 + log{(δ–3.29)/(5.68–δ)} where δ is the distance between the chemical shifts of PCr and Pi. Note this distance is different in the SZ and HC groups (aligned by vertical lines across the two spectra), indicating parenchymal pH reduction in SZ.

Table 2.

Results of ³¹P-MT-MRS Measurements in the Human Frontal Lobe of Schizophrenia and Healthy Controls

		Schizophrenia (N=26)	Healthy control (N=26)	Statistics (p value)
Magnetization ratio	PCr/β-ATP	1.35±0.24	1.36±0.17	0.705
	Pi/β-ATP	0.44±0.09	0.42±0.07	0.473
	PDE/β-ATP	0.91±0.19	1.05±0.19	0.015
	PME/β-ATP	1.05±0.14	1.09±0.16	0.544
pH		7.00±0.02	7.03±0.01	0.0072
1M*/M0 of PCr		0.50±0.12	0.43±0.07	0.013
Rate constant kf (−1s) of CK		0.21±0.07	0.27±0.06	0.003
T1(s) of PCr		5.21±1.24	5.03±1.09	0.67
Chemical exchange flux of CK (μmol/g/min)		49.93±21.95	61.43±16.08	0.032
[Mg2+] (mmol/L)		0.149±0.026	0.145±0.027	0.590

^1.Magnetization ratios between steady-state saturation (M*, 12.28s saturation time) and control (M⁰), unsaturated.

^2.Including adjustment for BMI

Figure 3.

Dependence of the PCr signal on γ-ATP saturation time for SZ (diamond, n=26) and HC (circle, N=25). The peak integrals for PCr represent the normalized M_s/M₀ ratios. The intrinsic spin-lattice relaxation times of PCr (T₁^int) and the forward rate constants ($k_f^{PCr\to ATP}$) were determined from these data by regression analyses using the Equation 4 described above.

pH measurements

There was a significant reduction in parenchymal pH in SZ as compared with healthy controls even after controlling for BMI [F(50,4)=8.039; p=0.007] (Table 2). This reduction of 0.03 pH units corresponds to an elevation of about 7% in proton concentration.

Phosphate metabolites ratios

Metabolite/ATP ratios are presented in Table 2. We reported metabolite level results using β-ATP as internal reference to control for subject-specific sources of variance. There were no between-group differences in any metabolite ratio except for the significant reduction in PDE/β-ATP [F(52,3)=6.348; p=0.015] in SZ compared to HC. In addition, magnesium ion concentrations, [Mg²⁺] deduced from the chemical shift of β-ATP³⁰ were calculated and were similar in SZ and HC subjects (Table 2).

Additional analyses

There were no significant correlations between spectroscopic parameters and demographic variables for both groups or clinical variables for the patient group. Of note, the negative correlation between BMI and intracellular pH approached the significance threshold (R=−0.496) when including both subject groups. BMI was therefore included as a covariate in the model involving intracellular pH, as described above. In addition, we created a correlation matrix between the independent parameters k_f, intracellular pH, and the 4 metabolite ratios reported in Table 2 but found only one correlation with R>0.5 in this matrix in either patient or control groups: Specifically, there was a negative correlation between intracellular pH and PCr/γ-ATP in HC (R=−0.583) but not in the SZ group (R=0.100) (Figure 4).

Figure 4.

The relationship between pH and the PCr/γ-ATP ratio in both HC (blue circles) and SZ (red diamond).

DISCUSSION

Using a novel ³¹P-MT-MRS approach, we report abnormalities in the reaction rate/flux through the CK enzyme system in chronically ill patients with SZ when compared with matched healthy controls. We also report a reduction in intracellular pH in the same patients, suggesting a relative increase in contribution of glycolysis to ATP synthesis, with resultant build-up of lactic acid. Importantly, we do not see a change in relative PCr or ATP levels (quantified as PCr/Pi, ATP/Pi, PCr/PME, ATP/PME ratios). This is important because changes in enzyme reaction rate are not necessarily accompanied by changes in levels of substrate or product. Thus, the reaction rate measure provides an additional, complementary, approach.

This is a direct in vivo demonstration of bioenergetic abnormalities in SZ. Note that the subgroups of patients with SZ and schizoaffective disorder had comparable abnormalities, suggesting that there is no diagnostic specificity to our findings in regards to these two conditions. In the healthy brain, energy utilization primarily supports glutamatergic neurotransmitter cycling³¹. Therefore bioenergetic abnormalities in SZ are likely to have implications for neuronal and circuit activity. Our current work does not provide information about brain regions other than the prefrontal cortex, nor about specific contributions from WM or GM. With future technical improvements (e.g. localization to smaller voxels to enable WM- or GM-dominant voxels, and chemical shift imaging to collect data from other brain regions³²), we hope to probe these issues more deeply. Since the current data come from both WM and GM, we expect that there may be abnormalities in both.

Mitochondrial and other bioenergetic abnormalities have been suggested by previous genetic, postmortem as well as neuroimaging studies in SZ^{2, 9}. The postmortem and genetic studies provide strong and converging evidence in this regard^{2, 33-36}. However, the exact abnormalities are uncertain, and there are discrepancies in the literature on neuroimaging studies. For example, elevations in ATP levels have been reported in drug naïve-1st episode SZ^{5, 6} but others^{7, 37-39} have found no significant difference. Likewise reported PCr levels have been variable with both increases^{40, 41} and no change being observed²¹. Alterations in PME and PDE in SZ are also debated^{39, 42.} Since these two metabolites are precursors and breakdown products of cell membrane metabolism, respectively, they may also reflect bioenergetic abnormalities related to cell membrane metabolism. Freely mobile PME levels may be reduced^{3, 6, 40, 43, 44} or normal^{45, 46} in both chronic and first episode SZ patients while PDE levels may be elevated ^{3, 6, 40, 43, 44}, low or normal^{47, 48} in the same groups. The preponderance of the studies report reduced PME and elevated PDE in SZ, consistent with accelerated phospholipid metabolism in this condition. The discrepancies likely arise due to differences in MRS methodology, selection of subjects, phases of illness, and medication regimens.

The CK reaction

³¹P MRS studies of bioenergetic dysfunction in neuropsychiatric disorders including SZ typically measure steady-state levels of HEP metabolites. By contrast, we assessed the reaction rate for a key enzyme in bioenergetics in the current study. This approach may focus attention on specific molecular targets and processes in the pathophysiology of SZ that may lead to development of new treatment interventions. On the other hand, the MRS signal we utilized cannot pinpoint CK abnormalities in mitochondria vs. cytosol and subcellular localization needs to be probed further in future work. In addition, the relationship between forward and reverse reaction rates and between the CK reaction and other systems may complicate interpretation of our findings. It is reassuring to note that our previous work showed that the CK and ATPase reactions are in approximate equilibrium in the human brain¹⁴. In addition, the ATPase reaction rate is approximately equal to the ATP oxidative synthesis rate^{17, 23, 49}. Finally, the CK and ATPase reaction rates are correlated with brain activity levels across a wide range¹⁷. These findings suggest that our MRS measures reflect meaningful indices of brain activity at a “macro” level. Our finding of reduced CK k_f suggests that the machinery of energy metabolism is dysfunctional in SZ⁵⁰. Thus, ATP availability might be compromised, especially at times of high demand such as during brain activation. The hypothesis of a breakdown in energy production in SZ is testable since the ³¹P MT MRS approach can be coupled with sensory or cognitive stimulation paradigms or neuromodulation therapies such as transcranial magnetic stimulation.

What explains the 22% reduction in the k_f of CK in SZ? As described in Equation 2, this parameter is determined by proton and ADP concentrations as well as a constant k, which describes the intrinsic activity of the CK enzyme. The reduction of 0.03 pH units we observe in SZ corresponds to a 7% elevation in [H⁺]. This could account for about a third of the CK enzyme abnormality. The concentration of ADP (typically reported as 0.3 mM) is too low to be measured directly. However, β-ADP makes a minor contribution to the γ-ATP resonance we quantified. Therefore, substantial changes in β-ADP would be reflected as minor differences in calculated γ-ATP and β-ATP levels (these two would normally be identical). However, we did not observe any difference between PDE/γ-ATP vs PDE/β-ATP or any of the other metabolite/γ-ATP vs metabolite/β-ATP ratios. Therefore, we suggest that abnormal CK enzyme activity in SZ may at least partially be a result of alterations in k, the constant reflecting enzyme concentration and/or molecular structure. This conclusion is supported by several lines of evidence: postmortem studies have identified abnormalities in CK enzyme activity³⁴ as well as oxidative phosphorylation^{9, 51} and mitochondria related genes and gene expression^{10, 52, 53} in SZ. Taken together, this is a picture of an underlying failure of energy production in SZ.

One potential shortcoming of this framework is that reductions in CK k_f may be compensated for by other systems, for instance, glycolysis and the adenylate cyclase reacton (2ADP↔ATP+AMP) . We cannot rule this out in the current work, and future studies may be needed to identify whether compensation is taking place.

pH findings

Another observation in the current study is consistent with bioenergetic abnormalities in SZ: reduction in intracellular pH. Importantly, intracellular pH was correlated negatively with BMI in our study. This relationship suggests that abnormal peripheral metabolism (manifesting as elevated BMI) may in fact be associated with abnormal brain metabolism (manifesting as reduced intracellular pH). There is parallel evidence supporting this intriguing finding from other systems⁵⁰. This interesting finding needs to be pursued in future studies. Since BMI differed significantly between the HC and SZ groups in this study, we added it to our analyses as a covariate. The reduced intracellular pH in the SZ group remained significant even after adjusting for BMI.

Reduced intracellular pH indicates that oxidative phosphorylation is compromised in SZ, leading to a relative increase in the contribution of glycolysis to ATP synthesis with subsequent buildup of lactic acid⁵⁴. Intracellular pH is independent of the CK reaction; therefore this finding suggests that bioenergetic abnormalities are widespread in SZ. One intriguing suggestion is the coupling between glycolysis and the adenylate cyclase reacton (2ADP↔ATP+AMP) that is upregulated when the CK reaction and oxidative phosphorylation are failing⁵⁵. Because HEP metabolite ratios were normal in the present study, this pattern suggests that despite a relatively higher reliance on glycolysis, a less efficient means of energy production, the brain is able to maintain baseline levels of important metabolites in SZ. Our observation of reduced intracellular pH agrees with a prior report of elevated CSF lactic acid in SZ⁵⁶, however, several other groups have reported decreased^57, elevated⁵⁸ or normal pH in SZ^{45, 59} in the prefrontal cortex or other brain regions. In the present study, we also observed a negative correlation of intracellular pH with PCr/r-ATP in HC but not SZ subjects. This correlation would be expected on the basis of Equation 3. The fact that it is not found in SZ may suggest subtle abnormalities in data quality and measurement error in this group, or perhaps an abnormal Keq for the CK reaction.

Metabolite Levels

The only statistically significant change we observed in metabolite ratios was a reduction in PDE/ATP in SZ (~12%). The magnitude of this reduction was smaller than that of abnormalities in CK k_f and intracellular pH and it was not accompanied by changes in PME. In addition, most previous papers report PDE elevations, not reductions. This pattern has led to the proposal of an accelerated phospholipid metabolism hypothesis in SZ since PDE is a breakdown product of membrane phospholipids. Our finding of reduced PDE without a change in PME is not consistent with this literature, although it is not the first to be discrepant⁶⁰. Reductions in PDE in this study may arise from global atrophy in SZ or from changes in GM and WM composition in the voxel of interest.

Limitations

In vivo ³¹P-MT-MRS provides an attractive non-invasive approach for directly studying bioenergetics/mitochondrial function associated with brain activity changes^{16-18, 61}. However, low signal-to-noise ratio (SNR) is a limitation of this approach because of the intrinsically low nuclear gyromagnetic ratio of ³¹P and the low concentration of some of the metabolites studied (such as Pi at ~1 mM). Therefore, we had to collect data from a relatively large brain region using a dedicated surface coil to achieve sufficient SNR. As shown in Figure 2, the majority of acquired signal comes from a 6x6x4 cm region in the frontal lobes. Outer volume suppression ensured exclusion of signal from HEP-rich extracranial muscle. We previously showed that rates for the CK and ATP_syn/ATP_ase reactions can be calculated in the human frontal lobe non-invasively at 4T²⁰. However, we found in this study that we could not achieve sufficient SNR to quantify the less sensitive ATP_syn reaction due to smaller voxels and short scan times. In addition, we do not have inter-assay reliability calculations available.

A related limitation is the relatively long acquisition time. Current measurements were performed with a 14 s repetition time at approximately fully relaxed conditions in order to minimize the confounding effects of B₁ inhomogeneity of ³¹P surface coil. Some novel ³¹P-MT-MRS approaches such as FAST and TRIST aim to measure the same chemical reaction fluxes^{62, 63}. Recently, we developed a novel ³¹P-MT-MRS approach (T₁^nom), aimed at rapidly mapping energy-ATP metabolic fluxes^{64, 65}. Using this approach, only 2 spectra are needed to calculate CK and ATP_syn reaction rates, as long as the intrinsic relaxation time T₁ of PCr is known and is constant across groups and times. Acquisition time is significantly shorter with this approach, enabling improved SNR, increased spatial/temporal resolution, and higher reliability^{61, 62}. In the current work we showed that the intrinsic relaxation time T₁ is not apparently different between SZ and HC, laying the groundwork for rapid acquisition ³¹P-MT-MRS in future studies. A related limitation is the fact that we did not correct the results for voxel composition of grey and white matter. This is because of our use of a surface coil for excitation. The resulting B₁ inhomogeneity creates uncertainty as to where in the region the optimized 90 degree flip angle is found, leading to differential contribution of signal from different regions. But this does not affect our measurement of the CK kinetics and relative metabolite ratios because ³¹P data were collected at fully relaxed condition. All signal acquired from regions within our volume of interest will follow the same decay curve with increased saturation time since this does not depend on absolute signal intensity. Likewise, the peak area ratios will be the same from all different regions at fully relaxed condition. Calculating contributions from each region within the volume of interest (6×6×4 cm³) to each of the spectra is possible from our measured ³¹P sensitivity three-dimensional profiles. However, further voxel segmentation would be complicated because imaging was acquired by ¹H quadrature surface coil. While it is possible to calculate signal contribution from inhomogeneous fields^{66, 67}, we would need to compile data acquired using 2 different coils for our purposes and this has not been previously validated. An added complication is the loss of both grey and white matter in schizophrenia which would lead to unpredictable voxel compositions. Loss of grey matter may impact our findings more but given the current limitations we are not able to ascertain the specific impact from each tissue type.

Another limitation of this study is that most SZ patients in this study were taking medication. We cannot exclude the possibility that our results are secondary to medication effects. Future studies with adequate sized groups of patients on and off medication are needed to fully address this issue. However, we did not observe any correlations between any of our neuroimaging measures and CPZ equivalents. In addition, the effects of antipsychotic medication on brain bioenergetics is complex and dependent on type of medication. See Supplemental Materials for a detailed discussion of this important topic.

One final limitation is that we report metabolites concentration ratios, and not absolute metabolite concentrations, which could be obtained using an external-reference with known concentration and matched electromagnetic properties with the human brain. However, this is time consuming and can be confounded by factors such as RF coil loading, especially at high field. We chose a more reliable and popularly used method, internal-referencing. We considered reporting PCr/Total ³¹P signal and ATP/Total ³¹P signal ratios, but we chose ATP ratios because we were particularly interested in the more biologically relevant ratios PCr/ATP and Pi/ATP. This approach meant, however, that we did not separately examine ATP concentrations in SZ and HC in this study. This is not ideal because ATP itself is a HEP and there is concern that it may be abnormal in conditions of bioenergetics compromise. Still, the pattern of our findings (no abnormalities in PCr/ATP, Pi/ATP, or PME/ATP accompanied by reduced PDE/ATP in SZ) suggests no major abnormalities in ATP. The literature is conflicting on this point and additional studies dedicated to quantifying ATP concentrations are needed to settle the issue. Note that this issue is relevant only for metabolite concentration quantification and not for CK k_f, intracellular pH, and T₁ relaxation time calculations.

In summary, we measured CK reaction rates, intracellular pH, and HEP metabolite levels in the human frontal lobe in SZ and HC using a novel ³¹P-MT-MRS approach. The forward rate constant and flux for the CK enzyme were significantly reduced, as was intracellular pH in SZ patients, but there were no metabolite concentration ratio abnormalities, except for a modest reduction in PDE. Our findings suggest abnormalities in the CK reaction and in glycolysis in SZ, and these processes may underlie abnormal neurotransmission and information processing in this disorder.