2020
DOI: 10.1016/j.mito.2019.10.005
|View full text |Cite
|
Sign up to set email alerts
|

Growth and differentiation factor 15 as a biomarker for mitochondrial myopathy

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
42
0

Year Published

2020
2020
2024
2024

Publication Types

Select...
7

Relationship

1
6

Authors

Journals

citations
Cited by 41 publications
(42 citation statements)
references
References 18 publications
0
42
0
Order By: Relevance
“…At structural levels, p53 directly in uences mitochondrial respiration and impairs clearance of defective mitochondria [27,28], leading to mitochondrial dysfunction, a well-known driver of biologic ageing [29]. Consistently, emerging studies have proposed GDF-15 as a speci c biomarker of mitochondrial disorder [30,31]. In further support of GDF-15 as a marker of ageing, GDF-15…”
Section: Discussionmentioning
confidence: 88%
“…At structural levels, p53 directly in uences mitochondrial respiration and impairs clearance of defective mitochondria [27,28], leading to mitochondrial dysfunction, a well-known driver of biologic ageing [29]. Consistently, emerging studies have proposed GDF-15 as a speci c biomarker of mitochondrial disorder [30,31]. In further support of GDF-15 as a marker of ageing, GDF-15…”
Section: Discussionmentioning
confidence: 88%
“…Increased serum GDF-15 levels have been associated with MD originated by different mutations and clinical conditions [21][22][23][24]. In different cohorts of MD patients, GDF-15 positively correlated with FGF-21, but usually showing a higher sensitivity for MD diagnosis than the latter [23,[25][26][27]. Notably, GDF-15 levels also increase as a response to stress and inflammation, and as a result, the blood concentration of GDF-15 is elevated in a variety of cardiovascular diseases, including heart failure and atherosclerosis, as well as in insulin resistance, renal insufficiency [28], and multiple sclerosis [29].…”
Section: Introductionmentioning
confidence: 99%
“…The study sample included 18 recreational male athletes (mean ± SD age: 41.7 ± 5.0 years, BMI: 23.6 ± 1.8). Sample size was dependent on availability of volunteers and was not based on power calculations; however, sample size was in the range of that resulting from power calculations in studies of individuals at rest and after a single bout of exercise (Yatsuga et al, 2015;Poulsen et al, 2020). The median (interquartile range, IQR) years of training was 7 (5-11) years and the median (IQR) of weekly training hours was 6 (5-8) h/week.…”
Section: Methodsmentioning
confidence: 99%