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“Brain Rust” in Schizophrenia Revealed by in vivo Redox (NAD+/NADH) Measurement
Fei Du1, Sang-Young Kim1, Bruce M. Cohen1, Xi Chen1, Scott Lukas1, Ann Shinn1, Cagri Yuksel1, Tao Li2, and Dost Ongur1

1McLean Hospital, Harvard Medical School, Belmont, MA, United States, 2West China Hospital, Sichuan University, Chengdu, People's Republic of China

Synopsis

A growing body of evidence suggests that an “immuno-oxidative” pathway including redox dysregulation associated with oxidative stress, mitochondrial dysfunction, neuroinflammation, and cell-mediated immune response may contribute to disruptions in brain activity in schizophrenia (SZ). The aim of this study is to assess possible redox imbalance in SZ patients by using a novel in vivo 31P-MRS technique to measure NAD+ and NADH. Our results revealed a ~40% decrease of NAD+/NADH ratio compared to healthy individuals of similar age, indicating higher levels of oxidative stress in patients with schizophrenia. This work may lead to new strategies to protect the brain from oxidative stress and improve brain function in schizophrenia or the other brain disorders.

Purpose

Schizophrenia (SZ) is a common and severe psychiatric disorder characterized by abnormal cognition and perception. Despite its public health impact and a century of biological research, the pathophysiology of SZ remains poorly understood. A growing body of evidence suggests that an “immuno-oxidative” pathway including oxidative stress, mitochondrial dysfunction, and neuroinflammation may contribute to disruptions in brain circuits in schizophrenia (SZ) (1-3). Nicotinamide adenine dinucleotide (NAD+) and its reduced form NADH have long been implicated in energy metabolism, reductive biosynthesis, and antioxidant activity. While the major biological function of NAD+ is to modulate cellular energy metabolism, mounting evidence indicates that NAD+ is also involved in biological activities such as cell death, calcium homeostasis, gene expression, aging, and immunological functions (4). Despite the crucial roles of NAD+ and NADH in cellular metabolism and physiology, its noninvasive in vivo detection is extremely challenging. Here we demonstrate the feasibility of 31P MRS-based NAD quantification at 4 T MRI scanner and apply this novel method in patients with SZ.

Method

We investigate the brain’s redox state (i.e., NAD+/NADH ratio, RR) in SZ patients with chronic, well-established illness as well as first-episode SZ patients who have not been exposed to the confounding effects of chronic medication treatment and chronic psychosis. We also present data from a first-episode bipolar disorder (BD) cohort, as a psychiatric control group. The participants included 40 healthy controls, 21 chronic SZ, 13 first-episode SZ, and 18 first-episode BD patients. All participants initially underwent structural imaging at a 3 T and 31P MRS measurements were performed on a 4 T MR scanner. NAD+ and NADH concentrations were determined by nonlinear least-square fitting of the model simulated spectra incorporating prior chemical shift and coupling constant information to in vivo resonances obtained from 31P-MRS experiments (5). We validated 31P-MRS based NAD detection method at 4 T with phantom and healthy human subjects as well as Monte-Carlo simulations.

Result and Discussion

We demonstrated (5) excellent agreement between simulated and experimentally measured 31P spectra (Figure 1), and Monte Carlo simulations with different line width and a-ATP SNR values (Figure 2) suggest excellent fitting accuracy for SNR (>40), which was used as a cut off for our in vivo data processing. Figure 3 presents in vivo 31P spectra from media prefrontal cortex of a healthy control participant, showing excellent spectral quality and high SNR. Figure 4 shows in vivo RR data in chronic and first episode SZ patients and matched healthy participants as well as age-dependence. NAD measures and RR show strong age-dependence in healthy individuals, demonstrating replication of RR decline in healthy participants (3) and an extension of this finding to SZ patients. In addition, the youngest participants (age<25) have lower RR than older ones, apparently reversing the age-dependent trend. This finding requires further investigation in children and adolescents. We found RR was significantly reduced by 35% in chronic SZ. This finding was driven by a 47% NADH elevation in chronic SZ with no significant change in NAD+. In addition, first-episode SZ patients had a highly significant 46% reduction in RR compared with healthy controls as well as a more modest 23% reduction compared with first-episode BD patients. To provide a demonstration of NAD abnormalities independent of the fitting procedures and without the other metabolite contributions (e.g. UDPG), Figure 5 shows summed patient and control spectra and the difference between them, clearly demonstrating an elevated NADH signal at -10.63 ppm in chronic SZ compared to controls, without an apparent difference in NAD+ and UDPG. These findings provide an evidence for redox imbalance in the brain in all phases of SZ, potentially reflecting oxidative stress, and suggest that RR may become a biomarker for treatment response and for screening of new therapeutic approaches targeting oxidative stress in SZ.

Conclusion

By applying this novel method to patients with SZ, we found a significant reduction in the NAD+/NADH ratio (RR) in chronically ill SZ patients compared to a matched healthy control group, and in first-episode SZ patients compared to both a matched first-episode BD patient group and a matched healthy control group. Intracellular RR is influenced by multiple cellular signaling events and may constitute a metabolic integrator for local metabolic status within cells. Therefore, our work provides new insights into the pathophysiology of SZ, as well as a biomarker for tracking the impact of treatment interventions.
 This work will lead to new strategies to protect the brain from oxidative stress and improve brain function in schizophrenia.

Acknowledgements

This work was supported by grants from MH092704 (F.D.); NARSAD (F.D.); NARSAD (D.O.); MH094594 (D.O.); MH104449 (D.O.); Program for Neuropsychiatric Research (B.M.C.).

References

1. Giles E. Hardingham, et al. Nature Rev. Neuroscience 2016

2. Du F, et al. JAMA Psychiatry 2014

3. Lu M, et al. Magn Reson Med 2014;

4. Zhu XH, et al. Proc Natl Acad Sci USA 2015;

5. Kim S, et al. Schizophrenial Bull 2016 (in press)

Figures

Figure 1. (a) simulated NAD+ and NADH resonance spectra and (b) experimental measurements from phantom solutions containing various known amounts of NAD+ and NADH show almost identical spectral patterns as observed in phantoms.

Figure 2. Effects of half linewidth (HLW) changes of a-ATP and NAD resonances on NAD measurements. Since the in vivo data with 8 HZ line broadening fitting shows HLW of NAD is 2~4 Hz less than that of a-ATP, the simulations were conducted in the same way. Gray and red lines indicate simulated spectra and fit to model spectra, respectively. (e) The plot of fitting accuracy as function of SNR. (f) Histogram of the “observed” RR results from the Monte Carlo simulation with the addition of noise to “real” RR values of 3 (in black) and 5 (in red).

Figure 3. 31P resonances with 2 Hz line-broadening of a-ATP, NAD+ and NADH as well as fitted results from a representative healthy control with measured RR=4.84.

Figure 4. Age dependence of intracellular NADH level (a) and RR (b) in chronic SZ and matched controls. In addition, in order to visualize the whole trend of redox state age-dependence, data from first-episode SZ and matched controls are also presented. Note that patients with first-episode SZ and younger healthy participants have higher NADH levels and lower RR compared to chronic SZ patients and older healthy participants of the same age, apparently reversing the age-dependent trend. This finding requires further investigation in children and adolescents.

Figure 5. (a) The summed spectra for healthy (black line) and chronic SZ groups (red line) are shown after frequency alignment. The spectral fit of summed spectra for healthy (b) and schizophrenia group (c) are presented to show no difference in UDPG concentration between the groups. Gray and black lines indicate original data and fit, respectively. And green, blue and red lines indicate NAD+, NADH, and UDPG fit in summed spectra. Note that higher NADH content without apparent differences in NAD+ and UDPG concentration is clearly seen in summed spectra of SZ group.

Proc. Intl. Soc. Mag. Reson. Med. 25 (2017)
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