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. 2023 Dec 5;14(24):4383–4394. doi: 10.1021/acschemneuro.3c00717

Glutathione Depletion and Concomitant Elevation of Susceptibility in Patients with Parkinson’s Disease: State-of-the-Art MR Spectroscopy and Neuropsychological Study

Deepika Shukla †, Anshika Goel †, Pravat K Mandal †,‡,§,*, Shallu Joon †, Khushboo Punjabi †, Yashika Arora †, Rajnish Kumar ∥, Veer Singh Mehta ⊥, Padam Singh #, Joseph C Maroon §, Rishu Bansal ∇, Kanika Sandal †, Rimil Guha Roy †, Avantika Samkaria †, Shallu Sharma †, Sandhya Sandhilya †, Shradha Gaur †, S Parvathi #, Mallika Joshi †
PMCID: PMC10739611  PMID: 38050970

Abstract

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Parkinson’s disease (PD) is characterized by extrapyramidal motor disturbances and nonmotor cognitive impairments which impact activities of daily living. Although the etiology of PD is still obscure, autopsy reports suggest that oxidative stress (OS) is one of the important factors in the pathophysiology of PD. In the current study, we have investigated the impact of OS in PD by measuring the antioxidant glutathione (GSH) levels from the substantia nigra (SN), left hippocampus (LH) and neurotransmitter γ-amino butyric acid (GABA) levels from SN region. Concomitant quantitative susceptibility mapping (QSM) from SN and LH was also acquired from thirty-eight PD patients and 30 age-matched healthy controls (HC). Glutathione levels in the SN region decreased significantly and susceptibility increased significantly in PD compared to HC. Nonsignificant depletion of GABA was observed in the SN region. GSH levels in the LH region were depleted significantly, but LH susceptibility did not alter in the PD cohort compared to HC. Neuropsychological and physical assessment demonstrated significant impairment of cognitive functioning in PD patients compared to HC. GSH depletion was negatively correlated to motor function performance. Multivariate receiver operating characteristic (ROC) curve analysis on the combined effect of GSH, GABA, and susceptibility in the SN region yielded an improved diagnostic accuracy of 86.1% compared to individual diagnostic accuracy based on GSH (65.8%), GABA (57.5%), and susceptibility (69.6%). This is the first comprehensive report in PD demonstrating significant GSH depletion as well as concomitant iron enhancement in the SN region.

Keywords: Parkinson’s disease, substantia nigra, hippocampus, glutathione, GABA, iron, MEGA-PRESS, QSM, neuropsychological assessment

Introduction

Parkinson’s disease (PD) is a progressive neurodegenerative disorder characterized by dopaminergic (DAergic) neuronal loss in the substantia nigra (SN) pars compacta. The disease is also associated with intracellular aggregates of Alpha-synuclein (α-Syn) in the form of Lewy bodies and Lewy neurites.1 The diagnosis of PD is based on predominant motor function deficits, bradykinesia, resting tremors, rigidity, and loss of postural reflexes.2 In addition to motor symptoms, individuals with PD also experience nonmotor manifestations, including challenges in memory and attention, diminished sense of smell, and changes in visual perception.3 The treatment strategies currently available for PD offer symptomatic relief but do not impede the progression of the PD disease process. Laboratory and clinical research have helped to identify various associated factors in PD including oxidative stress (OS),4 neuroinflammation,5 genetic susceptibility, and environmental factors.6 Various research groups are actively striving to identify early diagnostic biomarkers for PD based on the OS hypothesis.

Oxidative stress is characterized by an imbalance between reactive oxygen species (ROS) production and antioxidant defenses, plays a pivotal role in PD. Glutathione (GSH), a crucial antioxidant, is depleted in the brains of PD patients, rendering cells more susceptible to oxidative damage.4,7 Simultaneously, iron accumulation in the SN intensifies ROS generation, exacerbating OS.8 The intricate interplay between GSH and iron further amplifies these effects.9 Understanding these dynamics opens potential therapeutic avenues for PD by addressing GSH replenishment and iron homeostasis to mitigate OS, potentially slowing disease progression.4

The impact of OS in PD has been recognized by multiple autopsy studies revealing a significant reduction in GSH levels within the SN region when compared to age-matched, healthy controls (HC).7 An autopsy study also found that iron levels were significantly elevated (two to three-fold) in the extrapyramidal brain regions (SN, putamen, and caudate nucleus) compared to the cerebral cortex and cerebellum of PD patients.10 Another autopsy study found a nonsignificant increase of iron deposition in the SN area in mild category PD patients, however, there was a significant increase of iron in the SN region of PD patients in the severe category.11 The deposition of iron in the SN region from autopsy studies is also supported by independent MRI-based studies using quantitative susceptibility measurements (QSM).12 No studies, however, have been conducted to date that simultaneously measure both GSH and iron.

The SN holds a pivotal role in PD and is divided into two distinct anatomical parts, the pars compacta (SNpc) containing DAergic neurons and the pars reticulata (SNpr) containing GABAergic neurons. In PD, DAergic neuronal loss primarily occurs in nigrosomes, small clusters of dopaminergic cells within the SNpc.13 This specific degeneration of DAergic neurons in the SNpc is responsible for the core motor symptoms associated with the condition.14 Although the SNpc and SNpr are anatomically in proximity to each other, their functional roles are largely disparate.15 Recent studies utilizing mouse models to map PD progression have unveiled the functional connectivity of the SNpc and SNpr circuits to other brain regions.16 The DAergic neurons in SNpc project to the striatum, putamen, and caudate nuclei modulating the basal ganglia activity between the direct and indirect pathways.17 In contrast, the GABAergic neurons of SNpr function alongside the globus pallidus internus and serve as the final inhibitory pathway of the basal ganglia circuit, projecting to the motor thalamus. GABAergic outputs from the SNpr enable the basal ganglia to exert inhibitory control over several motor areas in the brainstem which in turn control the central pattern generators for the basic motor repertoire including eye–head orientation, locomotion, mouth movements, and vocalization.18 SNpr GABA neurons receive and integrate excitatory, inhibitory, and modulatory inputs that sculpt the default tonic high-frequency firing into a meaningful motor control signal.19 Nonmotor symptoms in PD, however, constitute lack of attention, executive dysfunction, working memory issues, and visuo-spatial impairment.3 Notably, the hippocampus plays an important role in executive function and memory performance suggesting that the hippocampus has a role in PD.20

Our objective is to make a comparative analysis of GSH levels in tandem with susceptibility (metal ions, e.g., iron, etc.) in the SN and hippocampus regions of the PD and age-matched control subjects. The role of the left hippocampus (LH) in PD is an area of ongoing research and discussion. While PD is primarily associated with motor symptoms due to the degeneration of dopaminergic neurons in the SN, it is increasingly recognized that nonmotor symptoms, including cognitive and memory impairments, play a significant role in the disease. The hippocampus is crucial for memory formation and consolidation as well as various cognitive processes. Left hippocampus’ atrophy is more profound in PD patients and researchers have reported that the LH has more atrophy than the right hippocampus. Among PD patients, recognition memory (r = 0.54, P = 0.015) and Mini-Mental State Examination scores (r = 0.56, P = 0.01) correlated with the left hippocampal volume only.21 Neuropsychological scores with the GSH and metal ion correlation analysis are included in this study.

To accomplish these objectives, we have designed state-of-the-art magnetic resonance spectroscopy (MRS) studies as well as susceptibility mapping experiments on PD patients and age-matched healthy controls. We focused on LH for acquiring the MRS data, as the LH is more sensitive to OS in neurodegeneration as evident from our previous study.22 The concomitant measurements of GSH and susceptibility were performed to identify early diagnostic biomarkers of PD noninvasively with high sensitivity and specificity.

Results

We present the detection of GSH and susceptibility from the SN and LH region and GABA from the SH region. Detailed neuropsychological evaluation scores are for the PD and HC groups.

The GABA level from the SN region of the participants was acquired using MEGA-PRESS as per our earlier study protocol23 and GSH from our earlier work.24 The overlay of one representative MRS spectrum of GSH from the SN and LH region as well as the representative GABA level from one PD and one HC is shown in Figure 1.

Figure 1.

Figure 1

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In vivo brain metabolite detection using MEGA-PRESS. Representative spectra from a PD patient (male) and a healthy control (male) (A) GABA in the SN region, (B) GSH in the SN region, and (C) GSH in the LH region for two groups, HC (blue) and PD (red).

The voxel sizes for the SN region 30 × 35 × 25 mm3 (tissue volume 26.2 cm3) and the left hippocampal region 25 × 25 × 25 mm3 (tissue volume 15.6 cm3) are taken in our study. We have taken representative data (one HC and PD patient) to show the spectral pattern of GABA, GSH from SN, as well as GSH from LH. In these spectra, GABA is depleted more but the overall GABA level has a nonsignificant decrease in the PD group (N = 38) compared to HC, (N = 30) (with no statistical significance). However, the overall GSH level in SN or hippocampus is depleted significantly in the PD group (N = 38) compared to HC (N = 30).

Neuroimaging Study Outcomes

The comparative differences in the GSH, GABA, and magnetic susceptibility from the SN region and GSH and susceptibility from the LH region from the PD and HC groups are presented in Figure 3. The mean GSH concentration among the PD patients decreased significantly (p = 0.021) compared to the HC group in the SN region. Similarly, mean GSH concentration in the LH region of PD patients was found depleted significantly (p = 0.0456) compared to HC. In the PD patient group, the mean GABA level in the SN region was reduced (nonsignificant) compared to HC (Table 1). The mean susceptibility in the SN region was found to be significantly increased (p = 0.0109) in PD compared to the HC group. However, no group difference for mean susceptibility value (HC vs PD) was observed in the LH region (p = 0.74).

Figure 3.

Figure 3

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Box-plots for age-matched HC and PD participants for various neuroimaging readouts (A) GSH absolute concentration (mM) in the SN region (*p = 0.021), (B) GABA absolute concentration (mM) in the SN region (p = 0.421, ns), (C) Susceptibility (ppm) in the SN region (*p = 0.009), (D) GSH absolute concentration (mM) in the LH region (*p = 0.046), (E) Susceptibility (ppm) in the LH region (p = 0.734, ns). (*p < 0.05, ns = nonsignificant). Independent t test was used to find out mean difference of parameters among HC and PD.

Table 1. Participant Demographic Characteristics (Age, Gender, and Education); Details with Neuroimaging and Neuropsychological Outcomes.

characteristic HC (30) PD (38) test statistics p-value
age 66.167 ± 7.795 (30) 69.079 ± 7.080 (38) –1.611a 0.112
male, n (%) 20(66.6%) 24 (63.13%)    
female, n (%) 10 (33.3%) 14 (36.84%    
education (years) 14.357 ± 2.792 (28) 12.914 ± 4.032 (35) 1.674a 0.099
neuroimaging readout
SN region GSH (abs) 1.188 ± 0.259 (22) 1.017 ± 0.184 (31) 2.807a 0.007c
GSH (PVC) 1.628 ± 0.321 (22) 1.441 ± 0.249 (31) 2.384a 0.021c
GABA(abs) 3.515 ± 0.819 (24) 3.232 ± 0.862 (33) 1.249a 0.217
GABA (PVC) 4.842 ± 1.159 (24) 4.583 ± 1.213 (33) 0.810a 0.421
susceptibility 0.098 ± 0.035 (24) 0.126 ± 0.037 (28) –2.726a 0.009c
LH region GSH (abs) 1.275 ± 0.192 (21) 1.067 ± 0.194 (18) 3.354a 0.002c
GSH (PVC) 1.411 ± 0.201 (21) 1.261 ± 0.254 (18) 2.067a 0.046c
susceptibility 0.015 ± 0.007 (24) 0.015 ± 0.011 (28) 0.341a 0.734
outcome of neuropsychological assessment
SMMSE 29.467 ± 1.074 (30) 25.946 ± 5.344 (37) 3.912a <0.0001c
CDT 1.517 ± 0.911 (29) 3.028 ± 1.889 (36) –4.225a <0.0001c
HAM-D 0.833 ± 1.838 (24) 4.962 ± 4.045 (26) –3.961b <0.0001c
TMT A 46.643 ± 17.818 (28) 139.100 ± 84.261 (30) –5.871a <0.0001c
TMT B 118.538 ± 58.505 (26) 233.824 ± 126.212 (17) –3.527a 0.002c
AIIMS MOTOR T-score 54.120 ± 14.409 (25) 112.966 ± 27.637 (29) –9.998a <0.0001c
stroop test - word 36.348 ± 8.799 (23) 29 ± 14.171 (16) 1.842a 0.078
stroop test - color 27 ± 10.335 (23) 21.750 ± 11.012 (16) 1.519a 0.137
stroop test - color-word 37.783 ± 8.929 (23) 33.375 ± 7.500 (16) 1.616a 0.115
stroop test - interference 44.913 ± 7.096 (23) 45.938 ± 5.495 (16) –0.485a 0.631
digit span (forward) 8.125 ± 1.296 (24) 7.542 ± 1.865 (24) 1.259a 0.215
digit span (backward) 7.292 ± 1.233 (24) 6.708 ± 1.628 (24) 1.399a 0.168
spatial span (forward) 6.750 ± 1.294 (24) 6.636 ± 1.761 (22) 0.251a 0.803
spatial span (backward) 6.250 ± 1.327 (24) 4.909 ± 1.509 (22) 3.207a 0.003c
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a

Independent t test.

b

Mann–Whitney test.

c

p < 0.05; statistically significant. Abs: Absolute. PVC: Partial volume correction.

Neuropsychological Assessments

Motor function abilities among study participants within groups (PD and HC) were assessed using the AIIMS-MOTOR function subscale of the AIIMS neuropsychological battery.25 The test scores indicated significantly slower motor functions in the PD group compared to HC (t = −9.99; p < 0.0001). The motor function subscale of AIIMS comprehensive neuropsychological battery comprises various items that require the patient to do simple and complex motor movements with both hands and fingers for assessment of spatial organization. The test also requires performing a three-step hand position sequence by learning and repeating it. Further past-pointing tests were also performed using both hands. The finger dexterity of both hands was assessed using glass marbles. The finger oscillation test was also performed using a manual tapper. Additionally, in the motor function subscale motor movement of both feet was also assessed by simple spatial movements. Motor impersistence was measured by fixation of gaze in lateral visual fields. The assessment of oral movement with tongue, teeth, jaw and paper pencil tests in which copying figures were also included which measure construction dyspraxia.

PD patients were also found to have deterioration in global cognition compared to HC using SMMSE26 (t = 3.91; p < 0.0001). PD patients took significantly longer time for the completion of the task in TMT-A27 (t = −5.87; p < 0.0001) and TMT-B27 (t = −3.53; p = 0.002) indicating significant decline in visual attention, processing speed, and executive functioning compared to HC. The poor performance on spatial span (backward) (t = 3.21; p = 0.003) subset of Weschler memory scale28 indicated impairment in the ability to hold information temporarily and perform mental operations. The impairment in visuo-spatial ability was also observed in PD patients compared to HC with poorer performance on CDT29 (t = −4.23; p < 0.0001) (Table 1).

ROC Analysis: Diagnostic Accuracy of the PD Group

ROC analysis was performed to assess the diagnostic utility of GSH concentration and susceptibility level in the SN and LH regions along with their combined effect in differentiating PD from HC (Figure 4 and Table 2). In the SN region, susceptibility levels provide an accuracy of 69.6% (AUC = 0.73, p = 0.005). GSH levels have a differentiating accuracy of 65.8% (AUC = 0.67 and p = 0.035). GABA levels in the SN area were not potentially differentiated in HC and PD groups (p = 0.57). Higher accuracy of 80.5% was achieved when both, GSH and susceptibility in the SN region were used collectively to diagnose PD (AUC = 0.89 and p < 0.0001). The collective use of GSH, GABA, and susceptibility showed an improved performance in differentiating PD from the HC group with 86.1% accuracy and high significance (p < 0.0001).

Figure 4.

Figure 4

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Receiver operator characteristic (ROC) analysis demonstrating the predictive utility of (A) GSH and GABA in the SN region; (B) susceptibility, combined GSH and susceptibility, and combined GSH, GABA, and susceptibility in the SN region; (C) GSH and susceptibility in the LH region; and (D) combined GSH and susceptibility; for disease diagnosis of PD. The reference line indicates the threshold value of AUC (threshold value = 0.5).

Table 2. Diagnostic Accuracy Characteristics (AUC, S.E., Sensitivity, Specificity, PPV, NPV, Accuracy, and p Value) for GSH, GABA, Susceptibility, and Their Combined Effect in the SN and LH Regions To Differentiate HC and PD Groups.

test result variables AUC[95% C.I.] SE sensitivity specificity PPV NPV accuracy p-value
SN region
GSH 0.672[0.522–0.822] 0.077 0.591 0.710 0.617 0.688 0.658 0.035a
GABA 0.544[0.390–0.698] 0.079 0.458 0.667 0.520 0.609 0.575 0.572
susceptibility 0.715[0.555–0.875] 0.082 0.786 0.583 0.705 0.682 0.696 0.019a
GSH + susceptibility 0.836[0.705–0.966] 0.067 0.826 0.778 0.825 0.779 0.805 <0.0001a
GSH + GABA + susceptibility 0.700[0.514–0.887] 0.095 0.864 0.857 0.885 0.833 0.861 0.029a
LH region
GSH 0.709[0.538–0.880] 0.087 0.667 0.778 0.703 0.748 0.729 0.026a
susceptibility 0.594[0.436–0.751] 0.080 0.583 0.679 0.589 0.674 0.637 0.248
GSH + susceptibility 0.744[0.565–0.923] 0.091 0.800 0.632 0.734 0.714 0.726 0.016a
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a

p < 0.05; statistically significant.

The difference in the GSH level in the LH region yields 72.9% accuracy (AUC = 0.709 and p = 0.026) for differentiating PD and HC groups. However, susceptibility in the LH region was not discriminating between the HC and PD groups (p = 0.248). A higher accuracy of 72.6% (p = 0.016) was observed by combining GSH and susceptibility levels in the LH region involving PD compared to HC. Figure 4 represents the diagnostic accuracy tests conducted using multi-ROC analysis for the independent GSH, GABA, and iron levels with their combined effect in both the SN and LH regions to differentiate HC and PD patients.

Discussion

The pathological hallmark of PD is the loss of pigmented dopaminergic neurons in the SNpc, which directly affects motor control.14 A typical neuron of the SN in a PD patient contains low levels of dopamine and neuromelanin. High levels of iron and depleted GSH levels in the SNpc represent a conducive environment for ROS generation.30 Our study adopted comprehensive MRS with MEGA-PRESS and QSM. In this study, 38 PD patients and age-matched 30 HC were included. We observed significant depletion in GSH level with a concomitant significant elevation of iron levels in the bilateral SN of the PD group. When comparing the GABA levels in bilateral SN among the two groups (HC and PD), no statistically significant difference was found. The GSH level in the LH region of the PD patients was depleted significantly compared to HC, but the magnetic susceptibility assessing iron deposition on the LH region of PD did not alter significantly compared to HC. This novel study investigated the role of OS in PD in terms of GSH, GABA, and susceptibility measurements from concurrent SN and LH regions to investigate their effects on motor and cognitive deficits in PD as compared to HC (Table 3). The ROC analysis based on GSH, GABA, and susceptibility differences reported 86.4% sensitivity and 85.7% specificity to discriminate HC from PD patients.

Table 3. Analysis of Experimental Data (GSH, GABA, and Iron Level from Autopsy, In Vivo MRS, or Susceptibility Studies on SN and Hippocampal Area) and the Present Study Outcomesa.

anatomical regions GSH GABA IRON
autopsy observations MRS observation autopsy observation MRS observations autopsy observations QSM observations
substantia nigra ↓(*)31,7,11 ↓ (*)(PS) slight decrease in SNpr (NS),32 light increase in SNpc (NS)32 slight increase (NS),33 slight decrease (NS),34 slight decrease (NS) (PS) ↑ (*)10,11 ↑(*)35,36↑(*)(PS)
hippocampus no data available ↓ (*)(PS) no data available no data available slight increase (NS)11 slight increase (NS),37no difference(PS)
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a

Star (*) denotes the statistically significant outcome (p < 0.05), NS (nonsignificant), PS refers to the present study.

Observed iron level differences from our QSM measurement from the hippocampus are in line with the autopsy reporting of no difference in susceptibility (e.g., iron content) in the hippocampus region in PD (N = 6) versus controls (N = 6).11 Autopsy studies have reported that GSH levels in the SN region are depleted significantly in PD patients as compared to HC and have also been positively correlated with disease severity.11 The current study corroborates these findings, and a significant depletion of GSH was observed in the SN region in patients with PD (Table 1). Correspondingly, nigral GSH level depletion can be considered a potential biomarker to differentiate between PD and the HC group based on ROC analysis (Table 2).

The SNpr region is populated largely by GABAergic neurons. Changes in GABA levels in PD may reflect alterations in the balance between excitatory and inhibitory processes in the cortical basal ganglia-thalamocortical networks involved in motor control.38 However, in vivo studies did not show any difference in SN GABA levels in PD (N = 10) and control (N = 11) groups.39 Another group also measured in vivo GABA concentration in PD (N = 5) and HC (N = 5) using a 7T scanner and no significant change in GABA levels in the SN region was observed between PD and control groups.34 In agreement with the in vivo studies,34 no significant differences in the GABA level were found in the SN region (Table 3). Concentrations of the GABA are very low (nmol/mg tissue weight range) in the brain. An autopsy study reported distinct distribution of GABA in various anatomical regions in HC and PD.32 The GABA concentration range was reported to be 5 nmol/mg tissue weight (for thalamus, postcentral gyrus, the head of the caudate nucleus brain regions), 15–20 nmol/mg tissue weight (for subthalamic nucleus, medial globus pallidus, nucleus accumbens regions) and 25–50 nmol/mg tissue weight (for the substantia pars reticulata, substantia pars compacta) anatomical regions.32 In MRS studies, GABA is detected by either PRESS or MEGA-PRESS sequences. MEGA-PRESS sequence gives results without any ambiguity compared to PRESS sequence. Therefore, the MEGA-PRESS sequence was used in this study for acquiring GABA data.

We have reported a significant depletion of GSH in the LH region, whereas no change in the iron was found. GSH levels in the LH region significantly differed in PD from the HC group but higher accuracy was observed by combining GSH and iron (Table 2).

PD patients are six times more likely to have cognitive impairment than healthy individuals.40 In terms of executive function, our study found impaired ability in PD patients to form and shift an attentional set compared to HC which is similar to existing findings in this domain.41 Consistent with the literature, PD patients performed similar to their healthy equivalents in the domain of verbal memory but were impaired on spatial working memory42 which is likely to be associated with dopamine loss in the striatum and prefrontal cortex and cholinergic dysfunction in the medial temporal structures.43 Evidence also suggests that mild cognitive impairment, primarily in the domain of mental flexibility and working memory constitutes one of the primary cognitive deficits in PD and may be present in as many as 50% of the cases with PD.44 Visuo-spatial deficits in PD were clearly evident in our findings and were also significantly more severe than in HC. Finally, motor functions in the PD group were below par for their age and education versus those of matched healthy counterparts. It is generally associated with dopaminergic nigrostriatal degeneration in the basal ganglia and constitutes the primary dysfunction in PD.45

An MRS study reported a negative correlation between GABA levels at the motor cortex and PD severity, indicating that depleted GABA levels in the motor cortex may play a role in increased motor symptoms in PD.46 However, GABA may have a different neuromodulatory activity on dopamine in the SN region. A study reported that increased GABA levels in the SN lead to gait disturbance in PD patients.47 GABAergic afferent neurons constitute about 70% of the inputs to SNpc dopaminergic neurons and thus their local interaction is a crucial factor in understanding the functioning of the SN as a whole.48 Therefore, alterations in GABAergic neurotransmission may have a role in the development of axial symptoms of PD, and further research is required in this regard.

From a biochemical perspective, aggregation of the intrinsically disordered protein α-Syn into amyloid-rich Lewy bodies is a central event in PD.49 Aggregation of α-Syn in dopaminergic neurons causes their death, leading to the manifestation of clinical symptoms of PD. Although the etiology of PD is multifactorial, aging, increased production of reactive oxygen species (ROS), and cellular oxidative stress constitute the common denominators.50 It has been observed that α-Syn can localize to the mitochondria and contribute to the disruption of key mitochondrial processes which are necessary to keep the redox homeostasis balance.51 This is suggestive of the fact that α-Syn aggregation and cellular oxidative stress are functionally connected.52 Both in vitro and in vivo studies have shown α-Syn to aggregate under oxidation.53 This paves the way for a biochemical cascade of aggregation of α-Syn induced by oxidative stress. α-Syn consists of four methionine residues located at the first, fifth, 116th, and 127th positions. The hydrophobic methionine residues are prone to oxidation and readily react with several ROS to form methionine sulfoxides, which can assume either of two diastereomeric forms, MetO(R) and MetO(S).54 The oxidation of methionine residues has previously been seen to lead to the aggregation of Aβ peptide, a characteristic hallmark of neurodegeneration in Alzheimer’s disease (AD).55 Even though the antioxidative enzyme methionine sulfoxide reductase (MSRs) can reverse this modification, an in-cell nuclear magnetic resonance (NMR) investigation found that MSRs repair the damage only in residues Met1 and Met5. The C-terminal Met116 and Met127 remain oxidatively modified.56 These oxidatively modified Met residues reduce the post-translational phosphorylation of Tyr125 of α-Syn, triggering a molecular cascade that ultimately leads to its fibrillation and aggregation.

In PD, a reduction in the amount of GSH available to neutralize ROS in the brain may trigger increased oxidation of the Met residues of α-Syn. The presence of pro-oxidative metal ions like iron further increases the oxidative load in the brain, making α-Syn more susceptible to oxidation.56,57

Experimental Methods

Participant Recruitment

PD patients were recruited from the outpatient department of Dr. Rajnish Kumar, MD, DM (Senior Neurologist), Department of Neurology and Neurosurgery, Paras Hospitals, Gurgaon. The PD diagnostic criteria (MDS 2015) included the identification of cardinal motor signs of bradykinesia, rigidity, tremor, and postural imbalance.58 Those fulfilling MDS 2015 criteria for PD were confirmed by independent neurologists. HC participants were recruited from HelpAge India, National Capital Region, New Delhi, India. A total of eighty-seven participants (PD (N = 44) and HC (N = 43)) aged 55 years and above were enrolled in this study. The purpose of this study was explained to all the participants and/or to the accompanying relatives, and written informed consent was obtained in the language understood by the patient/relatives.

Participants with a history of head trauma, psychiatric and/or other known neurological conditions, and those with any known contraindication for MRI (metallic implants or claustrophobia) were excluded. HC were also screened for depressive symptoms using Hamilton Depression Rating (HAM – D) and those with a score >7 were excluded from the study. Based on the exclusion criteria, 19 were excluded due to comorbidity (nine HC and three PD), contraindication to MRI (two HC and three PD), and due to cognitive impairment (two HC). HC participants with the Standardized Mini-Mental State Examination (SMMSE) score >24 were included in the study. The study protocol was approved by the institutional human ethics committee at the National Brain Research Centre (NBRC), Gurgaon, and Paras Hospital, Gurgaon, India. Finally, sixty-eight participants completed the study (PD, N = 38 and HC, N = 30) and their data was included for final analysis.

Neuropsychological and Physical Assessments

All participants were administered a battery of neuropsychological tests to assess global cognition, attention, and working memory and a physical assessment for motor function. These tests are Standardised Mini-Mental State Examination (SMMSE),26 attention and processing speed (Trail Making Test-A [TMT-A], executive functions (TMT-B and Stroop Color Word Test),59 working memory (Digit Span subtest from Wechsler Adult Intelligence Scale-IV [WAIS-IV])60 and spatial span subtest Wechsler Memory Scale-III [WMS-III]),28 visuo-spatial functions (Clock Drawing Test, CDT).61 Physical assessment for motor functions was accomplished using AIIMS-MOTOR (All India Institute of Medical Science Neuropsychological Battery-Motor function subtest).25

MRI/QSM Data Acquisition

All proton (1H) MRI/MRS data on PD and HC were acquired using a Philips Achieva 3T scanner at NBRC, India. A three-dimensional Gradient Multi echo Fast Field Echo (mFFE) sequence was used with five echoes to generate phase and magnitude mode brain images to determine susceptibility using an eight-channel SENSitivity Encoding (SENSE) volume head coil. The following experimental parameters were used: FOV = 240 × 200 × 160 mm3, TR = 35 ms, TE = 3.9 ms, δTE (echo time increment) = 5 ms, number of echoes = 5, number of slices (with zero gap) = 160, voxel resolution = 1 × 1 × 1 mm3, total scan time of 4 min 40 s. T1-weighted MRI was acquired using Turbo Field Echo (TFE), FOV (field of view) = 228 × 180 × 160 mm3, TR (repetition time) = 8.4 ms, TE (echo time) = 3.8 ms, flip angle = 8°, voxel resolution = 1 × 1 × 1 mm3, NSA = 1 with total scan time of 5 min 11 s.

MRS Data Acquisition

A dual-tuned (1H/31P) transmit/receiver head coil (Rapid Corporation) was used for MRS data collection.62 GSH and GABA standard solutions of variable concentrations were used as an external reference and were used for the absolute quantitation of in vivo GSH and GABA. In vivo, MRS data for GSH and GABA detection were accomplished using the MEGA-PRESS pulse sequence.24 For anatomical localization of SN and LH, 2D T2-weighted MRI images with turbo spin echo were acquired in all three planes with the following acquisition parameters: TR = 3000 ms; TE = 80 ms; flip angle = 90; turbo factor = 15. The high-resolution MRI images were used as a visual reference for voxel placement on the bilateral SN and LH regions (Figure 1). For the SN area, a voxel size of 30 × 35 × 25 mm3 covering bilateral nigral regions and for the LH area, a voxel of size 25 × 25 × 25 mm3 were placed taking the lower margin of the medial temporal region just above the skull base that served as anatomical reference. Water suppression in each MRS data was accomplished with the CHEmical Shift Selective (CHESS) Suppression pulse sequence.63 GSH data for both the SN and LH regions were acquired from the participants using the parameters, TR/TE = 2500/120 ms, spectral bandwidth = 2 kHz, and number of samples = 2048 with second-order pencil-beam volume shimming.64 Twenty interleaved spectral dynamics (each having an average of 16 signal averages) were acquired with the ON pulse set at 4.40 ppm, followed by the OFF pulse at 5.00 ppm. GSH resonance at 2.80 ppm was detected by applying a MEGA editing pulse set at 4.40 ppm (during the ON experiment) and set at 5 ppm during the OFF experiment.64

The voxel sizes for the SN region 30 × 35 × 25 mm3 (tissue volume 26.2 cm3) and the left hippocampal region 25 × 25 × 25 mm3.(tissue volume 15.6 cm3) are taken in our study. We have taken representative data (one HC and PD patient) to show the spectral representation of GABA, GSH from SN, as well as GSH from LH. In these representative spectra from one patient and control subject, GABA is depleted more, but the overall GABA level in this study shows a nonsignificant decrease in the PD group (N = 38) compared to HC, (N = 30) (with no statistical significance). However, overall GSH level in SN or hippocampus is depleted significantly in the PD group (N = 38) compared to HC (N = 30).

MR Data Processing

QSM Data Processing

QSM data processing was accomplished using the SUMEDHA toolbox.22 The SN region was segmented using the SN segmentation module of the BRAHMA template.65 The LH region was segmented using the recon-all pipeline of FreeSurfer.66 All of the segmented regions were further converted to binary masks. All the masks were visually inspected for correctness and were manually checked using the ITK-SNAP program (http://www.itksnap.org/pmwiki/pmwiki.php) while being overlaid on QSM and T1-weighted images (Figure 2). To minimize the partial volume effects, most inferior and most superior slices of the masks were not included in this analysis, and the voxels at the tissue boundary were also excluded. Individually computed binary masks were applied to the QSM image, and the mean susceptibilities in the regions of interest (SN and LH) were computed. QSM values from the occipital white matter region were considered as the reference in our study as this brain region has been reported to have the least susceptibility variation in HC and PD groups.67

Figure 2.

Figure 2

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Representative axial slices for (A) Substantia nigra mask (red), (B) left hippocampus mask (red) on T1-weighted MRI and QSM image in HC and PD participants (same participants’ data are included for illustration).

MRS Data Processing

All MEGA-PRESS MRS data were processed using the KALPANA signal processing and analysis toolbox.68 MRS voxel was placed on the T2-axial anatomical image from SN and LH regions. Shimming quality was assessed etc. to data acquisition in terms of fwhm (full width at half-maximum). Each individual dynamic was zero-order phase corrected, and the interleaved sum of each of the phase-corrected dynamics (total 10) generated the average of all the ON (averaged-ON) and the OFF (averaged-OFF) spectra, separately. Fitted spectra for these GSH and GABA peaks were used for calculating the peak area for SN and LH brain regions from the study groups (HC and PD).

Absolute Concentration GSH and GABA Determination

The absolute concentration of in vivo GSH ([AbsGSH]) was computed from external reference based on GSH phantom experiments using solutions of various concentrations and was corrected for T1, T2 relaxation times and partial volume effects using the formula given in eq 1.69

graphic file with name cn3c00717_m001.jpg 1

where AUPGSH is the GSH signal intensity; MGSH-SN (0.0048), CGSH-SN (−0.0013), MGSH-LH (0.0026), and CGSH-LH (−0.0008) are slope and intercept values (from SN and LH regions, respectively) obtained from the linearly fitted calibration curve of GSH phantom experiments for SN and LH voxels, respectively (Supporting Information). Published relaxation values of T1GSH-Phantom (350 ms), T1GSH-in vivo (397 ms),70 T2GSH-Phantom (95 ms), T2GSH-in vivo (117 ms)71 were used to calculate the T1 and T2 correction factors for GSH peak. Partial volume correction was performed by removing the CSF fraction (fCSF) from the respective ROI voxel.

In vivo GABA absolute quantitation ([AbsGABA]) was computed from phantom-based external referencing. T1 and T2 relaxation time compensations of GABA and partial volume correction for CSF were applied using the formula given in eq 2.72

graphic file with name cn3c00717_m002.jpg 2

where AUPGABA is the GABA signal intensity; MGABA (0.0021), and CGABA (0.0001) are the slope and intercept values from the linearly fitted calibration curve for SN voxel volume, experimentally determined from GABA phantom experiments. To account for macromolecular contribution to the GABA signal (GABA+) at 3.0 ppm, a MMcor (0.45) scaling factor was used, and GABA editing efficiency was accounted for by the eff (0.5) factor. T1 and T2 correction factors for GABA were computed by using phantom and in vivo relaxation values T1GABAPhantom (2770 ms), T1GABAin vivo (1310 ms),73 T2GABAPhantom (260 ms), T2GABAin vivo (88 ms).74 Partial volume correction was performed by removing the CSF fraction (fCSF) from the respective ROI voxel.

Statistical Analysis

The differences in demographic characteristic variables (i.e., age, gender, education level), neuroimaging outcomes (GSH, GABA, susceptibility values), and neuropsychological scores (for SMMSE, CDT, HAM-D, TMT-A, TMT-B, AIIMS-MOTOR function, Stroop (color and word test), digit span (forward and backward), spatial span (forward and backward)) among study groups (HC and PD) were summarized using mean ± SD for continuous variables and frequency with percentage for categorical variables. These outcome data were assessed using an independent t test or Mann–Whitney test for continuous variables as appropriate and a chi-square (χ2) test for categorical data. The normality of the data was assessed using the Shapiro-Wilk test.

To evaluate the diagnostic parameters based on the neuroimaging outcomes involving both regions of interest (SN and LH) among the study groups (HC and PD), ROC analyses were performed using DeLong criteria.75 Corresponding area under curves (AUCs), standard error (S.E.), optimal cutoff point, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy, and p values were estimated. Multivariate ROC curve analysis was accomplished from the predicted probability values derived from binary logistic regression using neuroimaging outcomes. Significance levels for all the statistical analyses were set at p < 0.05. All statistical analyses were performed using SPSS (version 23.0).

Conclusions

There has been significant progress toward establishing that PD neuropathology may be in part attributed to the depletion of the cellular GSH pool within SN dopaminergic neurons. Accumulation of iron in the SN has also been demonstrated to contribute to oxidative stress during PD. To the best of our knowledge, this is the first time the concentrations of the pro-oxidant iron have been compared with antioxidant GSH in the SN and LH regions together with neuropsychological scores from the same cohort. We conclude that decreased GSH and increased iron in tandem in the SN provide an early diagnostic biomarker for PD. Longitudinal studies with more sample size are warranted. This present study and earlier work on AD have helped us to initiate a major clinical research program (“ASHA”) for blood based novel biomarker development for AD and PD. After validation, this biomarker program would help to screen early PD and mild cognitive impairment (MCI) patients.

Limitations

This study is based on cross-sectional data and therefore does not address the direction or sequential change of events for the association of GSH and iron with PD pathology. The results presented in this cross-sectional study are also limited by a modest sample size. Therefore, the PD stage level analysis (based on the H&Y scale) was not considered. Finally, it is to be noted that SN and LH voxels contained extraneous non-SN and non-LH tissue respectively due to technological limitations. The macromolecular contamination is present in the GABA signal at 3.00 ppm and is generally called GABA+76 and we have used a correction factor to compensate the macromolecular component in GABA level calculation. In our study, we have referred to GABA+ as GABA for simplification purposes.

Acknowledgments

P.K.M. (Principal Investigator) thanks the Department of Biotechnology, (Ministry of Science and Technology, Government of India) for the Tata innovation award (Award No. BT/HRD/01/05/2015 to P.K.M) for this work. P.K.M. highly appreciates and thanks Prof. Peter Barker and Prof. Richard Edden at the Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, USA, for providing the patch of the MEGA-PRESS sequence. Ms. Anushka Mandal is appreciated for color coding of various ROC curves using Adobe Photoshop.

Supporting Information Available

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acschemneuro.3c00717.

  • Calibration of GSH and GABA peak as external reference using in vitro MRS studies (PDF)

Author Contributions

P.KM. (Principal Investigator) conceived the research idea (TATA innovation awarded to PKM). PKM was involved in study design, recruitment of patients and healthy controls, and human ethics clearance. P.K.M. was also involved in M.R.S. and Q.S.M. experiments, conducted a preliminary analysis of MRS data, and wrote the manuscript and involved in Figure preparation and statistical analysis. D.S. was involved in patient study design, recruitment of patients and healthy controls, phantom preparation, human and phantom MRS data acquisition, and post-processing using KALPANA. DS participated in the development for mask design of the SN area for QSM and MRI analysis pipeline for SN brain region, analysis, and interpretation of results, and writing of manuscript and was also involved in study protocol preparation, patient data management, and preliminary statistical analysis of data. A.G. performed QSM experiments and QSM data processing and analysis using the SUMEDHA package developed at the NINS lab, participated in discussion, and involved in writing the manuscript. S.J. performed neuropsychological testing and analysis. K.P. performed the phantom calibration experiments and participated in the discussion. Y.A. was involved in designing the graphical abstract, discussion, figure preparation and writing the manuscript. R.K. and V.S.M. provided PD patients from the neurology OPD at Paras Hospital and participated in discussion. P.S. was involved in statistical analysis of imaging and neuropsychological data and discussion and writing the statistical analysis component. J.C.M. was involved in discussion and writing the manuscript. J.C.M. was involved in discussion and manuscript writing. R.B. was involved in discussion and paper writing. K.S. was involved in coordination with Paras Hospital for patient recruitment. R.G.R. was involved in literature analysis, discussion, and writing the manuscript. A.S. and S.S. were involved in the discussion. S.P. was involved in statistical analysis along with P.S. M.J. was involved in discussion and figure preparation. Courtesy to Biorender (www.biorender.com) for the PD patient sketch in the graphical abstract.

The authors declare no competing financial interest.

Notes

Data will be shared on request.

Supplementary Material

cn3c00717_si_001.pdf (71.2KB, pdf)

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