Plasma growth differentiation factor 15: a novel tool to detect early changes of hereditary transthyretin amyloidosis

Okada, Masamitsu; Misumi, Yohei; Masuda, Teruaki; Takashio, Seiji; Tasaki, Masayoshi; Matsushita, Haruo; Ueda, Akihiko; Inoue, Yasuteru; Nomura, Toshiya; Nakajima, Makoto; Yamashita, Taro; Shinriki, Satoru; Matsui, Hirotaka; Tsujita, Kenichi; Ando, Yukio; Ueda, Mitsuharu

doi:10.1002/ehf2.13176

Cited by 5 publications

(2 citation statements)

References 28 publications

(50 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“… 75 Lesion of the sciatic nerve induces Gdf15 expression in mice, 75 for which secretion by Schwann cells is the major source, while treatment of the sciatic nerve lesion site with GDF15 promotes regeneration of motor axons and improves lower-limb sensory function, 77 thus emphasizing the specific function of GDF15 in neurons. Increased serum GDF15 has been reported also in other diseases affecting the peripheral nerves such as hereditary TTR amyloidosis, 78 and Gdf15 gene expression is elevated in Gars mut CMT mouse models, where its induction was associated with activation of the integrated stress response. 44 We therefore hypothesise that in CMT GDF15 is secreted to promote regeneration of peripheral neurons following nerve insult, which contributes to elevation of circulatory GDF15 in the serum.…”

Section: Discussionmentioning

confidence: 87%

NCAM1 and GDF15 are biomarkers of Charcot-Marie-Tooth disease in patients and mice

Kagiava

Vendredy

Spaulding

et al. 2022

Brain

View full text Add to dashboard Cite

Molecular markers, scalable for clinical use are critical for the development of effective treatments, and for design of clinical trials. Here, we identify proteins in sera of patients and mouse models with Charcot-Marie-Tooth disease (CMT) with characteristics that make them suitable as biomarkers in clinical practice and therapeutic trials. We collected serum from mouse models of CMT1A (C61 het), CMT2D (GarsC201R, GarsP278KY), CMT1X (Gjb1-null), CMT2L (Hspb8K141N) and from CMT patients with genotypes including CMT1A (PMP22d), CMT2D (GARS), CMT2N (AARS) and other rare genetic forms of CMT. The severity of neuropathy in the patients was assessed by the CMT Neuropathy Examination Score (CMTES). We performed multitargeted proteomics on both sample sets to identify proteins elevated across multiple mouse models and CMT patients. Selected proteins and additional potential biomarkers, such as growth differentiation factor 15 (GDF15) and cell free mitochondrial DNA were validated by ELISA and quantitative PCR, respectively. We propose that neural cell adhesion molecule 1 (NCAM1) is a candidate biomarker for CMT, as it was elevated in Gjb1-null, Hspb8K141N, GarsC201R and GarsP278KY mice, as well as in patients with both demyelinating (CMT1A) and axonal (CMT2D, CMT2N) forms of CMT. We show that NCAM1 may reflect disease severity, demonstrated by a progressive increase in mouse models with time and a significant positive correlation with CMTES neuropathy severity in patients. The increase in NCAM1 may reflect muscle regeneration triggered by denervation, which could potentially track disease progression or the effect of treatments. We found that member proteins of the complement system were elevated in Gjb1-null and Hspb8K141Nmouse models, as well as in patients with both demyelinating and axonal CMT, indicating possible complement activation at the impaired nerve terminals. However, complement proteins did not correlate with the severity of neuropathy measured on the CMTES scale. Although the complement system does not seem to be a prognostic biomarker, we do show complement elevation to be a common disease feature of CMT, which may be of interest as a therapeutic target.. We also identify serum GDF15 as a highly sensitive diagnostic biomarker, which was elevated in all CMT genotypes as well as in Hspb8K141N, Gjb1-null, GarsC201R and GarsP278KY mouse models. Although we cannot fully explain its origin, it may reflect increased stress response or metabolic disturbances in CMT. Further large and longitudinal patient studies should be performed to establish the value of these proteins as diagnostic and prognostic molecular biomarkers for CMT.

show abstract

Section: Discussionmentioning

confidence: 87%

NCAM1 and GDF15 are biomarkers of Charcot-Marie-Tooth disease in patients and mice

Kagiava

Vendredy

Spaulding

et al. 2022

Brain

View full text Add to dashboard Cite

show abstract

“…The pulmonary veins that enter the left atrium return the oxygenated blood to the heart. Blood enters the left ventricle from the left atrium and the aorta will deliver the oxygenated blood to every region of the body when the left ventricle pumps blood there [8]- [10].…”

Section: Introductionmentioning

confidence: 99%

Optimization of Amyloidosis Detection Method for Right Ventricle and Its Deployment Using Machine Learning (ML) Approach

Dhanatwal¹,

Jyothi²,

Kumar³

2023

View full text Add to dashboard Cite

When an aberrant protein called amyloid accumulates in our organs and tissues, it causes amyloidosis. When it happens, both their form and functionality are impacted and amyloidosis is a critical medical condition that may result in organ failure that is serious and may be lethal. In this present study, the author discussed about the amyloidosis in the right ventricle of the heart and its detection using the Machine Learning (ML). The methodology used for this research includes an infrastructure of amyloidosis detection, created by using supervised and unsupervised learning technique. The results show the precise diagnosis is crucial since the details of ailment will have a significant impact on the kind of therapy we get. The infrastructure gathers user input initially, which is utilised to prepare the data afterwards. Unsupervised data from the right ventricle is collected and supplied to the machine learning cycle after an effective data translation and model development. The study concludes that typical supervised machine learning datasets were used to train the algorithms. These methods may eventually enable longitudinal, automated, and objective monitoring of patients' ventricular function. Machine learning for vast and small datasets of Cardiac Amyloidosis (CA) and cardiac straining and functional parameters offers appealing diagnostics prediction accuracy for CA diagnosis when compared to state-of-the-art methods. The future potential of this research is the infrastructure can be used in an effective manner for the diagnosis of major diseases.

show abstract

Plasma growth differentiation factor 15: a novel tool to detect early changes of hereditary transthyretin amyloidosis

et al. 2020

Self Cite

View full text Add to dashboard Cite

Aims Hereditary transthyretin (ATTRv) amyloidosis is the most frequent and representative form of autosomal dominant hereditary systemic amyloidosis. Disease-modifying treatments of the disease are more effective during the early stages, and we require biomarkers to detect early pathological changes for prompt diagnosis. This study aimed to investigate whether plasma growth differentiation factor 15 (GDF-15) levels could aid detection of early pathological changes in ATTRv amyloidosis. Methods and results We retrospectively studied 32 patients with ATTRv amyloidosis, eight asymptomatic TTR mutation carriers, and eight healthy volunteers. We evaluated plasma GDF-15 levels in these subjects as related to levels of brain natriuretic peptide and high-sensitivity troponin T, echocardiographic features, 99m Tc-pyrophosphate (PYP) scans, and cardiac magnetic resonance imaging findings. Plasma GDF-15 levels significantly increased even in asymptomatic TTR mutation carriers compared with healthy volunteers (P < 0.01). Plasma GDF-15 levels were significantly correlated with plasma brain natriuretic peptide values (P < 0.01), serum high-sensitivity troponin T values (P < 0.05), and interventricular septal thickness at end-diastole (P < 0.01) in patients with ATTRv amyloidosis. Plasma GDF-15 levels in patients with PYP-positive ATTRv amyloidosis were significantly higher than those in patients with PYP-negative ATTRv amyloidosis (P < 0.01). Plasma GDF-15 levels in patients with late gadolinium enhancement-positive ATTRv amyloidosis were significantly higher than those in patients with late gadolinium enhancement-negative ATTRv amyloidosis (P < 0.01). Groups of patients with different TTR genotypes manifested different plasma GDF-15 levels. Conclusions Growth differentiation factor 15 may reflect early pathological changes of ATTRv amyloidosis.

show abstract

Plasma growth differentiation factor 15: a novel tool to detect early changes of hereditary transthyretin amyloidosis

Cited by 5 publications

References 28 publications

NCAM1 and GDF15 are biomarkers of Charcot-Marie-Tooth disease in patients and mice

NCAM1 and GDF15 are biomarkers of Charcot-Marie-Tooth disease in patients and mice

Optimization of Amyloidosis Detection Method for Right Ventricle and Its Deployment Using Machine Learning (ML) Approach

Plasma growth differentiation factor 15: a novel tool to detect early changes of hereditary transthyretin amyloidosis

Contact Info

Product

Resources

About