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Letter to the editor
 Revisiting the Triglyceride–Glucose Index in Parkinson’s Disease: Risk Ractor or Disease Marker?
Shweta Prasadorcid, Tarunya Nagarajorcid, Shubha GS Bhatorcid, Mahima Bhardwajorcid, Pooja Mailankodyorcid, Rohan R Mahaleorcid, Nitish Kambleorcid, Vikram Venkappayya Hollaorcid, Ravi Yadavorcid, Pramod Kumar Palcorresp_iconorcid
Journal of Movement Disorders 2025;18(4):389-392.
DOI: https://doi.org/10.14802/jmd.25222
Published online: August 25, 2025

Department of Neurology, National Institute of Mental Health and Neurosciences, Bengaluru, India

Corresponding author: Pramod Kumar Pal, MD, DM Department of Neurology, National Institute of Mental Health and Neurosciences, Hosur Road, Bengaluru 560029, Karnataka, India / Tel: +91-80-26995147 / Fax: +91-80-26564830 / E-mail: palpramod@hotmail.com
• Received: August 19, 2025   • Accepted: August 25, 2025

Copyright © 2025 The Korean Movement Disorder Society

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Dear Editor,
We read with great interest the recent article by Chang et al. entitled “The Association between the Triglyceride–Glucose Index and the Incidence Risk of Parkinson’s Disease: A Nationwide Cohort Study” [1]. The authors demonstrated that a higher triglyceride–glucose (TyG) index is associated with an increased risk of Parkinson’s disease (PD), particularly in nondiabetic individuals. This large, population-based study from South Korea highlights insulin resistance as a potentially modifiable factor in the pathogenesis of PD and suggests the utility of simple and cost-effective measures of fasting triglyceride and glucose levels as predictive markers to identify at-risk individuals.
Intrigued by the observations of this study, we attempted to evaluate the TyG index in our cohort of hospital patients with PD and healthy controls (HC). These participants are part of a prospective single-center study, the Young and Late-onset Parkinson’s disease study, conducted at the Department of Neurology, National Institute of Mental Health and Neurosciences, Bangalore, India. While Chang et al. [1] reported an elevated TyG index preceding the onset of PD, we observed the opposite pattern in our cohort of established cases of PD. Among 444 patients with PD and 145 HCs, the TyG index was significantly lower in patients with PD than in HCs (8.78±0.63 vs. 8.91±0.61; p=0.019; age-adjusted p=0.002) (Table 1, Supplementary Table 1 in the online-only Data Supplement). The difference remained significant among nondiabetic participants (8.66±0.57 vs. 8.85±0.57; p=0.001). No significant differences were observed among diabetic participants (Table 1). In contrast to the elevated prodromal signal reported by Chang et al. [1], our data from a clinically established cohort suggest that the TyG index decreases once PD-related symptoms develop.
This paradox may be explained by disease stage-related dynamics. In the prodromal phase, insulin resistance may increase neuronal vulnerability. However, in individuals with established disease, there is a marked shift in metabolic parameters. As evidenced by our recent study [2], patients with PD often experience progressive weight loss, a decrease in body mass index, and a reduction in visceral adiposity, which leads to a negative energy balance and lower triglyceride levels. These changes most likely induce a reduction in the TyG index independent of premorbid conditions. Considering this, the TyG index may serve dual roles: as a risk marker, indicated by elevated levels prior to disease onset, and as a disease-state marker, reflected by lower levels in individuals with established PD.
Pharmacotherapy with dopaminergic medication also further influences this trajectory. All our patients were receiving dopaminergic therapy with a mean levodopa equivalent dose greater than 600 mg. Compared with no treatment, levodopa has been reported to reduce lipid-related indices, with reports of lower total cholesterol, triglyceride, and total lipid levels in patients with PD treated with levodopa [3]. The proposed mechanisms include inhibition of hepatic cholesterol biosynthesis, increased oxidative stress causing excess lipid peroxidation, neuroendocrine modulation, and gastrointestinal side effects, which may reduce absorption. These mechanisms lead to a reduction in triglyceride levels and may also affect glucose handling. Therefore, the therapeutic use of levodopa may have contributed to the downward shift observed in our dataset, highlighting treatment status as a critical factor when interpreting TyG.
Further support for this interpretation comes from related indices. In another study, Chang et al. [4] demonstrated that higher triglyceride-to-high-density lipids cholesterol (TG/HDL) ratios were associated with an increased risk of PD in a South Korean population. Compared with HCs, patients with PD in our cohort had lower TG/HDL ratios, paralleling the TyG index results. This concordance across two insulin resistance–related indices further strengthens confidence that these observations reflect real, stage-dependent and therapy-dependent shifts.
Population-related differences are also crucial to consider. The baseline TyG index values in the present study and Indian cohorts [5] are consistently lower than those in the study by Chang et al. [1]. These discrepancies may reflect differences in diet, body composition, and the incidence of metabolic syndrome. Considering this, our finding of lower TyG among Indian patients with PD compared with Indian controls emphasizes the need for population-specific calibration, highlighting that thresholds cannot be applied across regions without contextual adjustment.
There has been recent growing interest in repurposing antidiabetic medications for PD, particularly those aimed at targeting the shared pathways of insulin signaling, energy metabolism, and neuroinflammation [6]. The possible role of glucagon-like peptide-1 receptor agonists such as exenatide and liraglutide; dipeptidyl peptidase-4 inhibitors; and insulin-sensitizing agents such as pioglitazone and metformin in PD therapy has been investigated. The rationale for their use, which aims to improve insulin sensitivity and metabolic resilience, involves the same indices captured by an elevated TyG index [7]. If validated, the TyG index could extend beyond its role as a risk predictor and may serve as a pharmacodynamic biomarker, aiding in identifying patients who are most likely to benefit from metabolic therapies and tracking their response.
These perspectives highlight the conceptual value of the TyG index as a dynamic and context-dependent biomarker. In preclinical and population contexts, an elevated TyG index may indicate greater susceptibility, particularly in nondiabetic individuals, prior to the initiation of glucose- or lipid-lowering therapies. In clinical cohorts, i.e., patients diagnosed with PD, lower values could reflect a convergence of systemic catabolism and dopaminergic treatment effects.
Related indices such as the TG/HDL ratio show a similar pattern, supporting actual biological changes rather than artifactual observations. The growing therapeutic focus on antidiabetic agents also highlights the translational relevance of the TyG index, linking epidemiology with clinical monitoring and therapeutic advances.
In conclusion, Chang et al. [1] provide compelling evidence that the TyG index can predict the risk of PD in the general South Korean population. Our assessment in an Indian cohort of diagnosed patients with PD suggests the possibility of a reduction in TyG index values once the disease process begins. These changes are likely shaped by disease stage, catabolic processes, and exposure to dopaminergic therapy. Confirming these findings will require longitudinal studies spanning prodromal to advanced PD, incorporating treatment data and calibrating against local population norms. The outcomes of such research could establish the role of the TyG index as both a risk marker and a disease- state marker, thereby influencing epidemiological screening, clinical monitoring, and the application of emerging metabolic therapies in PD.
The online-only Data Supplement is available with this article at https://doi.org/10.14802/jmd.25222.

Supplementary Table 1.

Demographic and clinical profile of patients with PD and healthy controls
jmd-25222-Supplementary-Table-1.pdf

Ethics Statement

Recruitment was carried out following ethical approval (NIMHANS/34th IEC (BS&NS DIV)/2022). Written informed consent was obtained from all subjects prior to recruitment in the study.

Conflicts of Interest

The authors have no financial conflicts of interest.

Funding Statement

Subjects included in this study were part of the Young and Late onset Parkinson’s disease (YLOPD) study funded by the Scientific Knowledge for Ageing and Neurological ailments (SKAN) research trust.

Acknowledgments

None

Author Contributions

Conceptualization: Shweta Prasad, Tarunya Nagaraj, Pramod Kumar Pal. Data curation: Tarunya Nagaraj, Shubha GS Bhat, Mahima Bhardwaj. Formal analysis: Shweta Prasad, Tarunya Nagaraj. Funding acquisition: Pramod Kumar Pal. Investigation: Shweta Prasad, Tarunya Nagaraj, Shubha GS Bhat, Mahima Bhardwaj. Methodology: Shweta Prasad, Tarunya Nagaraj, Pramod Kumar Pal. Project administration: Pooja Mailankody, Rohan R Mahale, Nitish Kamble, Vikram Venkappayya Holla, Ravi Yadav, Pramod Kumar Pal. Resources: Pramod Kumar Pal. Supervision: Pooja Mailankody, Rohan R Mahale, Nitish Kamble, Vikram Venkappayya Holla, Ravi Yadav, Pramod Kumar Pal. Writing—original draft: Shweta Prasad, Tarunya Nagaraj. Writing—review & editing: Shweta Prasad, Pooja Mailankody, Rohan R Mahale, Nitish Kamble, Vikram Venkappayya Holla, Ravi Yadav, Pramod Kumar Pal.

Table 1.
Biochemical parameters in patients with PD and HC
Complete cohort
 Non-diabetic
 Diabetic
PD (n=444) HC (n=145) p value p value adjusted* PD (n=358) HC (n=121) p value p value adjusted* PD (n=86) HC (n=24) p value p value adjusted*
Total cholesterol 187.81±42.90 (55–508) 189.46±38.73 (107–299) 0.704 0.003 188.64±41.90 (55–508) 190.23±38.14 (117–296) 0.704 0.121 183.54±46.98 (96–318) 185.48±42.32 (107–299) 0.950 0.763
HDL 46.40±11.80 (18–129) 42.67±9.26 (25–70) <0.001 0.003 46.95±11.47 (18–95) 42.66±9.60 (25–70) <0.001 0.005 44.14±13.23 (25–129) 42.78±7.05 (32–58) 0.820 0.453
LDL 121.80±36.70 (29–242) 126.89±33.90 (49–245) 0.208 0.074 123.04±34.96 (43–237) 127.70±33.31 (49–245) 0.227 0.033 116.93±43.12 (29–242) 122.30±37.70 (60–231) 0.656 0.953
VLDL 29.10±23.36 (8–261) 30.47±16.99 (11–113) 0.087 0.675 27.62±21.33 (8–218) 30.74±17.50 (11–113) 0.014 0.306 35.47±29.78 (14–261) 29.09±14.25 (15–67) 0.221 0.291
Triglycerides 143.18±111.70 (41–1,305) 152.31±84.80 (53–565) 0.040 0.118 135.15±99.36 (41–1,091) 153.54±87.36 (53–565) 0.007 0.029 176.91±149.28 (68–1,305) 145.96±71.45 (74–336) 0.379 0.417
FBS 110.35±40.29 (57–608) 117.59±53.07 (62–344) 0.813 0.002 101.58±35.25 (57–608) 108.36±41.96 (62–334) 0.973 0.019 147.17±39.47 (88–263) 165.34±75.88 (89–344) 0.939 0.096
TyG Index 8.78±0.63 (6.578–11.42) 8.91±0.61 (7.707–10.62) 0.019 0.002 8.66±0.57 (6.578–11.089) 8.85±0.57 (7.707–10.35) 0.001 0.001 9.28±0.63 (8.060–11.429) 9.22±0.71 (8.274–10.629) 0.844 0.806
TG/HDL ratio 3.59±4.50 (0.6–60.61) 3.90±2.70 (0.77–15.69) 0.004 0.220 3.33±4.07 (0.63–60.61) 3.98±2.92 (0.77–15.69) <0.001 0.079 4.67±5.91 (0.60–52.2) 3.53±1.94 (1.65–8.77) 0.529 0.459

Values are presented as mean±standard deviation (min–max) or number (%).

* p value adjusted for age at assessment which was lower in HC compared to PD.

PD, Parkinson’s disease; HC, healthy controls; HDL, high-density lipids; LDL, low-density lipids; VLDL, very low-density lipids; FBS, fasting blood sugar; TyG, triglyceride–glucose; TG/HDL, triglyceride/high-density lipids cholesterol.

  • 1. Chang Y, Park JY, Yun JY, Song TJ. The association between the triglyceride-glucose index and the incidence risk of Parkinson’s disease: a nationwide cohort study. J Mov Disord 2025;18:138–148.ArticlePubMedPMCPDF
  • 2. Farsana MK, Prasad S, Holla VV, Nagaraj T, Bhat SG, Taneja R, et al. Body composition and resting metabolic rate in Parkinson’s disease: a prospective cross-sectional single centre study. Parkinsonism Relat Disord 2025;139:107996.ArticlePubMed
  • 3. Scigliano G, Ronchetti G, Girotti F, Musicco M. Sympathetic modulation by levodopa reduces vascular risk factors in Parkinson disease. Parkinsonism Relat Disord 2009;15:138–143.ArticlePubMed
  • 4. Chang Y, Park JY, Song TJ. Association between triglyceride/high density lipoprotein ratio and incidence risk of Parkinson’s disease: a population-based cohort study. Sci Rep 2025;15:2142.ArticlePubMedPMCPDF
  • 5. Ramalingam S, Kar AK, Senthil R. Comparison of triglyceride/glucose index and related parameters with Indian Diabetes Risk Score assessment in non-diabetic individuals visiting primary healthcare centre-a community-based cross-sectional study. J Family Med Prim Care 2024;13:235–242.ArticlePubMedPMC
  • 6. Aguirre-Vidal Y, Montes S, Mota-López AC, Navarrete-Vázquez G. Antidiabetic drugs in Parkinson’s disease. Clin Park Relat Disord 2024;11:100265.ArticlePubMedPMC
  • 7. Avagimyan A, Pogosova N, Fogacci F, Aghajanova E, Djndoyan Z, Patoulias D, et al. Triglyceride-glucose index (TyG) as a novel biomarker in the era of cardiometabolic medicine. Int J Cardiol 2025;418:132663.ArticlePubMed

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    Citations

    Citations to this article as recorded by  
    • Association between the triglyceride-glucose index and disease severity in non-diabetic Parkinson’s disease patients
      Deyan Zeng, Min Luo, Baojun Zhang, Yan Zhang, Ailan Pang, Xinglong Yang
      Frontiers in Aging Neuroscience.2026;[Epub]     CrossRef

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    Revisiting the Triglyceride–Glucose Index in Parkinson’s Disease: Risk Ractor or Disease Marker?
    Revisiting the Triglyceride–Glucose Index in Parkinson’s Disease: Risk Ractor or Disease Marker?
    Complete cohort
    		 Non-diabetic
    		 Diabetic
    PD (n=444) HC (n=145) p value p value adjusted* PD (n=358) HC (n=121) p value p value adjusted* PD (n=86) HC (n=24) p value p value adjusted*
    Total cholesterol 187.81±42.90 (55–508) 189.46±38.73 (107–299) 0.704 0.003 188.64±41.90 (55–508) 190.23±38.14 (117–296) 0.704 0.121 183.54±46.98 (96–318) 185.48±42.32 (107–299) 0.950 0.763
    HDL 46.40±11.80 (18–129) 42.67±9.26 (25–70) <0.001 0.003 46.95±11.47 (18–95) 42.66±9.60 (25–70) <0.001 0.005 44.14±13.23 (25–129) 42.78±7.05 (32–58) 0.820 0.453
    LDL 121.80±36.70 (29–242) 126.89±33.90 (49–245) 0.208 0.074 123.04±34.96 (43–237) 127.70±33.31 (49–245) 0.227 0.033 116.93±43.12 (29–242) 122.30±37.70 (60–231) 0.656 0.953
    VLDL 29.10±23.36 (8–261) 30.47±16.99 (11–113) 0.087 0.675 27.62±21.33 (8–218) 30.74±17.50 (11–113) 0.014 0.306 35.47±29.78 (14–261) 29.09±14.25 (15–67) 0.221 0.291
    Triglycerides 143.18±111.70 (41–1,305) 152.31±84.80 (53–565) 0.040 0.118 135.15±99.36 (41–1,091) 153.54±87.36 (53–565) 0.007 0.029 176.91±149.28 (68–1,305) 145.96±71.45 (74–336) 0.379 0.417
    FBS 110.35±40.29 (57–608) 117.59±53.07 (62–344) 0.813 0.002 101.58±35.25 (57–608) 108.36±41.96 (62–334) 0.973 0.019 147.17±39.47 (88–263) 165.34±75.88 (89–344) 0.939 0.096
    TyG Index 8.78±0.63 (6.578–11.42) 8.91±0.61 (7.707–10.62) 0.019 0.002 8.66±0.57 (6.578–11.089) 8.85±0.57 (7.707–10.35) 0.001 0.001 9.28±0.63 (8.060–11.429) 9.22±0.71 (8.274–10.629) 0.844 0.806
    TG/HDL ratio 3.59±4.50 (0.6–60.61) 3.90±2.70 (0.77–15.69) 0.004 0.220 3.33±4.07 (0.63–60.61) 3.98±2.92 (0.77–15.69) <0.001 0.079 4.67±5.91 (0.60–52.2) 3.53±1.94 (1.65–8.77) 0.529 0.459
    Table 1. Biochemical parameters in patients with PD and HC

    Values are presented as mean±standard deviation (min–max) or number (%).

    p value adjusted for age at assessment which was lower in HC compared to PD.

    PD, Parkinson’s disease; HC, healthy controls; HDL, high-density lipids; LDL, low-density lipids; VLDL, very low-density lipids; FBS, fasting blood sugar; TyG, triglyceride–glucose; TG/HDL, triglyceride/high-density lipids cholesterol.

    Table 1.

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