Correlation between serum IGF-1 and EGF levels and neuropsychiatric and cognitive in Parkinson's disease patients

A Prospective Cohort Study on the Effects of Repeated Acute Stress on Cortisol Awakening Response and Immune Function in Military Medical Students

Background: The cortisol awakening response (CAR) is a pivotal component of the body's stress response, yet its dynamics under repeated acute stress and its interplay with immune biomarkers remain inadequately understood. Methods: This study examined 80 second-year military medical students undergoing a 5-day intensive surgical simulation designed to elicit stress responses. Salivary samples were collected daily upon waking and 30 min thereafter to measure cortisol and a panel of cytokines using bead-based multiplex ELISA. Results: Analysis revealed a significant blunting of the CAR on the third day of training (p = 0.00006), followed by a recovery on the fourth day (p = 0.0005). Concurrently, specific cytokines such as CXCL1 (r = 0.2, p = 0.0005), IL-6 (r = 0.13, p = 0.02), IL-10 (r = 0.14, p = 0.02), and VEGF-A (r = 0.17, p = 0.003) displayed patterns correlating with the CAR, with increased strength of associations observed when assessing cytokine levels against the CAR of the preceding day (CXCL1 r = 0.41, p = 0.0002. IL-6 r = 0.38, p = 0.0006. IL-10 r = 0.3, p = 0.008. VEGF-A r = 0.41, p = 0.0002). Conclusions: These results suggest a temporal relationship between stress-induced cortisol dynamics and immune regulation. The CAR pattern demonstrated in this study may represent induction of and recovery from psychological burnout. Moreover, the observed cytokine associations provide insight into the mechanisms by which stress can influence immune function. The results may have broader implications for managing stress in high-performance environments, such as military and medical professions, and for identifying individuals at risk of stress-related immune suppression.

Association between serum insulin-like growth factor 1 and osteoporosis risk in Parkinson's disease: a cross-sectional study

OBJECTIVE

To examine the correlation between serum insulin-like growth factor 1 (IGF-1) and osteoporosis (OP) in Parkinson's disease (PD).

METHODS

We retrospectively analyzed clinical data from 105 PD patients (PD group) and 78 individuals in the health examination group (HC group). We compared general clinical data and serum IGF-1 levels between the two groups. PD patients were further categorized into PD with OP (50 cases) and PD without OP (55 cases) based on dual-energy X-ray absorptiometry (DXA) results for bone density. We compared general clinical data and serum IGF-1 levels between these two subgroups. Pearson correlation coefficient analysis was conducted to assess the relationship between serum IGF-1 levels and bone density at the lumbar spine and left femoral neck. Multifactorial logistic regression analysis was performed to identify risk factors for PD with OP.

RESULTS

Serum IGF-1 levels were significantly lower in the PD group compared to the HC group (P < 0.05). Pearson correlation analysis revealed a positive association between serum IGF-1 levels and both lumbar spine and left femoral neck bone densities (r = 0.653, P < 0.001; r = 0.625, P < 0.001). Multivariate logistic regression analysis identified decreased serum IGF-1 levels, lower uric acid levels, and higher H-Y stage as risk factors for PD with OP (P < 0.05).

CONCLUSION

Reduced levels of serum IGF-1, uric acid, and an increased H-Y stage are closely linked to osteoporosis in PD. Elevating serum levels of IGF-1 and uric acid may potentially offer therapeutic avenues for PD with osteoporosis.

Association between serum IGF‑1 levels and non-motor symptoms in Parkinson's disease

AIMS

We aimed to measure serum insulin-like growth factor 1 (IGF-1) levels in Parkinson's disease (PD) patients and assess their correlation with non-motor symptoms (NMS).

BACKGROUND

Emerging evidence suggests that abnormal levels of IGF-1 play a crucial role in the development of PD.

OBJECTIVE

Further systematic research is needed to explore the potential roles of abnormal IGF-1 levels in NMS of PD.

METHODS

The study enrolled a total of 129 PD patients and 130 healthy controls (HCs). Within the PD cohort, 74 patients were classified as being in the early stage, while 55 were in the moderate stage.

RESULTS

This study found no significant difference in serum IGF-1 levels between PD patients and HC. Further analysis revealed no significant difference in IGF-1 levels between early-stage PD and those in the moderate stages. Linear regression analysis indicated a significant association between serum IGF-1 levels and Nonmotor Symptom Scale (NMSS) scores in PD patients. Linear regression analysis revealed significant correlations between serum IGF-1 levels and general cognitive function, information processing speed, and executive function in PD patients. Furthermore, lower serum IGF-1 levels were associated with fatigue in PD patients.

CONCLUSIONS

In summary, our study suggests a potential association between serum IGF-1 levels and specific NMS in patients with PD. These findings highlight the importance of long-term follow-up studies to determine whether serum biomarkers can serve as valuable tools for early detection of NMS in PD.

Investigating the Genetic Association of 40 Biochemical Indicators with Parkinson's Disease

The mechanisms of Parkinson's disease (PD) are not fully understood, which hinders the development of effective therapies. Research indicates that lower levels of biochemical indicators like bilirubin, vitamin D, and cholesterol may elevate the risk of PD. However, clinical studies on abnormal levels of biochemical indicators in PD patients' circulation are inconsistent, leading to ongoing debate about their association with PD. Here, we investigate the genetic correlation between 40 biochemical indicators and PD using a bidirectional two-sample Mendelian randomization (MR) approach to uncover potential causal relationships. Data from genome-wide association studies (GWAS) were utilized, with genetic variations from specific lineages serving as instrumental variables (IVs). The methodology followed the STROBE-MR checklist and adhered to the three principal assumptions of MR. Statistical analyses employed methods including inverse variance weighting (IVW), MR-Egger, weighted median, and weighted mode. Biochemical indicators including albumin, C-reactive protein (CRP), and sex hormone-binding globulin (SHBG) showed significant associations with PD risk. Elevated levels of albumin (OR = 1.246, 95% CI 1.006-1.542, P = 0.043) and SHBG (OR = 1.239, 95% CI 1.065-1.439, P = 0.005) were linked to higher PD risk. Conversely, increased CRP levels (OR = 0.663, 95% CI 0.517-0.851; P = 0.001) could potentially lower PD risk. The robustness of the results was confirmed through various MR analysis techniques, including assessments of directional pleiotropy and heterogeneity using MR-Egger intercept and MR-PRESSO methods. This study systematically reveals, for the first time at the genetic level, the relationship between 40 biochemical indicators and PD risk. Our research verifies the role of inflammation in PD and provides new genetic evidence, further advancing the understanding of PD pathogenesis. The study shows a positive correlation between albumin and SHBG with PD risk and a negative correlation between CRP and PD risk. This study identifies for the first time that SHBG may be involved in the onset of PD and potentially worsen disease progression.

Aging-related biomarkers for the diagnosis of Parkinson's disease based on bioinformatics analysis and machine learning

Parkinson's disease (PD) is a multifactorial disease that lacks reliable biomarkers for its diagnosis. It is now clear that aging is the greatest risk factor for developing PD. Therefore, it is necessary to identify novel biomarkers associated with aging in PD. In this study, we downloaded aging-related genes from the Human Ageing Gene Database. To screen and verify biomarkers for PD, we used whole-blood RNA-Seq data from 11 PD patients and 13 healthy control (HC) subjects as a training dataset and three datasets retrieved from the Gene Expression Omnibus (GEO) database as validation datasets. Using the limma package in R, 1435 differentially expressed genes (DEGs) were found in the training dataset. Of these genes, 29 genes were found to occur in both DEGs and 307 aging-related genes. By using machine learning algorithms (LASSO, RF, SVM, and RR), Venn diagrams, and LASSO regression, four of these genes were determined to be potential PD biomarkers; these were further validated in external validation datasets and by qRT-PCR in the peripheral blood mononuclear cells (PBMCs) of 10 PD patients and 10 HC subjects. Based on the biomarkers, a diagnostic model was developed that had reliable predictive ability for PD. Two of the identified biomarkers demonstrated a meaningful correlation with immune cell infiltration status in the PD patients and HC subjects. In conclusion, four aging-related genes were identified as robust diagnostic biomarkers and may serve as potential targets for PD therapeutics.

Biomarkers of Parkinson's Disease: From Basic Research to Clinical Practice

Parkinson's disease (PD) is a common neurodegenerative disease characterized pathologically by dopaminergic neuron loss and the formation of Lewy bodies, which are enriched with aggregated α-synuclein (α-syn). PD currently has no cure, but therapeutic strategies are available to alleviate symptoms. Early diagnosis can greatly improve therapeutic interventions, but the clinical diagnosis of PD remains challenging and depends mainly on clinical features and imaging tests. Efficient and specific biomarkers are crucial for the diagnosis, monitoring, and evaluation of PD. Here, we reviewed the biomarkers of PD in different tissues and biofluids, along with the current clinical biochemical detection methods. We found that the sensitivity and specificity of single biomarkers are limited, and selecting appropriate indicators for combined detection can improve the diagnostic accuracy of PD.

Role of the Insulin-like Growth Factor System in Neurodegenerative Disease

The insulin-like growth factor (IGF) system has paracrine and endocrine roles in the central nervous system. There is evidence that IGF signalling pathways have roles in the pathophysiology of neurodegenerative disease. This review focusses on Alzheimer's disease and Parkinson's disease, the two most common neurodegenerative disorders that are increasing in prevalence globally in relation to the aging population and the increasing prevalence of obesity and type 2 diabetes. Rodent models used in the study of the molecular pathways involved in neurodegeneration are described. However, currently, no animal model fully replicates these diseases. Mice with triple mutations in APP, PSEN and MAPT show promise as models for the testing of novel Alzheimer's therapies. While a causal relationship is not proven, the fact that age, obesity and T2D are risk factors in both strengthens the case for the involvement of the IGF system in these disorders. The IGF system is an attractive target for new approaches to management; however, there are gaps in our understanding that first need to be addressed. These include a focus beyond IGF-I on other members of the IGF system, including IGF-II, IGF-binding proteins and the type 2 IGF receptor.

Causal relationship between circulating insulin-like growth factor-1 and Parkinson's disease: a two-sample Mendelian randomization study

Background

Linear associations between circulating insulin-like growth factor-1 (IGF-1) levels and Parkinson's disease (PD) have been evidenced in observational studies. Yet, the causal relationship between IGF-1 levels and PD remains obscure. We conducted Mendelian randomization to examine the correlation between genetically predicted IGF-1 levels and PD.

Methods

By reviewing genome-wide association studies (GWAS) that are publicly accessible, we uncovered SNPs linked to both serum concentrations of IGF-1 and PD. A two-sample Mendelian randomization (MR) analysis was carried out to evaluate the individual effect of IGF-1 on PD.

Results

In a primary causal effects model in MR analysis, employing the inverse-variance weighted (IVW) method, IGF-1 levels exhibited a notable association with the risk of PD (OR, 1.020, 95% CI, 1.003-1.038, p = 0.0215). Multiple evaluations revealed that horizontal pleiotropy was improbable to distort the main results (MR-Egger: P PD intercept =0.719), and no bias was detected by leave-one-out analysis.

Conclusion

This study unearthed evidence indicating that heightened IGF-1 levels might be causally correlated with an increased risk of PD.

Lacking P2X7-receptors protects substantia nigra dopaminergic neurons and hippocampal-related cognitive performance from the deleterious effects of high-fat diet exposure in adult male mice

BACKGROUND

Dietary fat consumption, involved in the pathogenesis of insulin resistance and impaired glucose metabolism, is linked with decline in cognitive functions, dementia, and development of Parkinson's disease and Alzheimer's disease. Mature IL-1β, requiring the activation of the P2X7 receptor (P2X7R)-inflammasome complex, is an important mediator of neuroinflammation. The aim of the study was to test whether P2X7R activation might interfere with systemic and cerebral metabolic homeostasis.

METHODS

We treated WT and P2X7R KO mice with a high-fat diet (HFD) for 16 weeks, evaluating the effects on the Substantia Nigra and Hippocampus, target areas of damage in several forms of cognitive impairment.

RESULTS

HFD-treated WT and P2X7R KO mice showed a different brain mRNA profile of Insulin and Igf-1, with these genes and relative receptors, more expressed in KO mice. Unlike P2X7R KO mice, WT mice treated with HFD displayed a diameter reduction in dopaminergic neurons in the Substantia Nigra, accompanied by an increased IBA1 expression in this area; they also showed poor performances during Y-Maze and Morris Water Maze, tasks involving Hippocampus activity. Conversely, Parkin, whose reduction might promote neuronal cell death, was increased in the brain of P2X7R KO animals.

CONCLUSION

We report for the first time that HFD induces damage in dopaminergic neurons of the Substantia Nigra and a Hippocampus-related worse cognitive performance, both attenuated in the absence of P2X7R. The involved mechanisms might differ in the two brain areas, with a predominant role of inflammation in the Substantia Nigra and a metabolic derangement in the Hippocampus.

Harnessing IGF-1 and IL-2 as biomarkers for calcineurin activity to tailor optimal FK506 dosage in α-synucleinopathies

Introduction: Rise in Calcium (Ca2+) and hyperactive Ca2+-dependent phosphatase calcineurin represent two key determinants of a-synuclein (a-syn) pathobiology implicated in Parkinson's Disease (PD) and other neurodegenerative diseases. Calcineurin activity can be inhibited with FK506, a Food and Drug Administration (FDA)-approved compound. Our previous work demonstrated a protective effect of low doses of FK506 against a-syn pathology in various models of a-syn related pathobiology. Methods: Control and a-syn-expressing mice (12-18 months old) were injected with vehicle or two single doses of FK506 administered 4 days apart. Cerebral cortex and serum from these mice were collected and assayed using a meso scale discovery quickplex SQ 120 for cytokines and Enzyme-linked immunosorbent assay for IGF-1. Results: In this study we present evidence that reducing calcineurin activity with FK506 in a-syn transgenic mice increased insulin growth factor (IGF-1), while simultaneously decreasing IL-2 levels in both cerebral cortex and serum. Discussion: The highly conserved Ca2+/calcineurin signaling pathway is known to be affected in a-syn-dependent human disease. FK506, an already approved drug for other uses, exhibits high brain penetrance and a proven safety profile. IL-2 and IGF-1 are produced throughout life and can be measured using standard clinical methods. Our findings provide two potential biomarkers that could guide a clinical trial of FK506 in PD patients, without posing significant logistical or regulatory challenges.

Sarcosine May Induce EGF Production or Inhibit the Decline in EGF Concentrations in Patients with Chronic Schizophrenia (Results of the PULSAR Study)

Sarcosine (N-methylglycine), a glutamatergic modulator, reduces the primary negative symptoms of schizophrenia. These beneficial changes might be mediated by trophic factors such as epidermal growth factor (EGF). We assessed associations between initial serum EGF levels or changes in serum EGF levels and symptom severity during the addition of sarcosine to stable antipsychotic treatment and thereby evaluated the associations between glutamatergic modulation, clinical changes and peripheral EGF concentrations. Fifty-eight subjects with a diagnosis of chronic schizophrenia with dominant negative symptoms, stably treated with antipsychotics, completed a prospective 6-month, randomized, double-blind, placebo-controlled study. Subjects received orally 2 g of sarcosine (n = 28) or placebo (n = 30) daily. Serum EGF levels and symptom severity (using the Positive and Negative Syndrome Scale (PANSS) and the Calgary Depression Scale for Schizophrenia (CDSS)) were assessed at baseline, 6-week and 6-month follow-up. Augmentation antipsychotic treatment with sarcosine had no effect on EGF serum levels at any time points. Only the sarcosine group showed a significant improvement in negative symptoms, general psychopathology subscales and the overall PANSS score. We found a reduction in serum EGF levels in the placebo group, but levels in the sarcosine remained stable during the study. Our data indicate that improvement in negative symptoms due to sarcosine augmentation is not directly mediated by EGF, but effective treatment may induce the production or block the decrease in EGF concentrations, which indicates the neuroprotective effect of treatment and confirms the relationship between neuroprotection and EGF levels.