Detail
Článek
Článek online
FT
Medvik - BMČ
  • Je něco špatně v tomto záznamu ?

Potential major depressive disorder biomarkers in pediatric population - a pilot study

M. Krivosova, M. Grendar, I. Hrtanek, I. Ondrejka, I. Tonhajzerova, N. Sekaninova, L. Bona Olexova, D. Mokra, J. Mokry

. 2020 ; 69 (Suppl 3) : S523-S532. [pub] 20201231
. 2020 ; 96 (Suppl 3) : S523-S532. [pub] 20201231

Jazyk angličtina Země Česko

Typ dokumentu časopisecké články

Perzistentní odkaz   https://www.medvik.cz/link/bmc21028091

Mental disorders affect 10-20 % of the young population in the world. Major depressive disorder (MDD) is a common mental disease with a multifactorial and not clearly explained pathophysiology. Many cases remain undetected and untreated, which influences patients' physical and mental health and their quality of life also in adulthood. The aim of our pilot study was to assess the prediction value of selected potential biomarkers, including blood cell counts, blood cell ratios, and parameters like peroxiredoxin 1 (PRDX1), tenascin C (TNC) and type IV collagen (COL4) between depressive pediatric patients and healthy peers and to evaluate a short effect of antidepressant treatment. In this study, 27 young depressive patients and 26 non-depressed age-matched controls were included. Blood analyses and immunological assays using commercial kits were performed. Platelet count was the only blood parameter for which the case/control status was statistically significant (p=0.01) in a regression model controlling for the age and gender differences. The results from ELISA analyses showed that the case/control status is a significant predictor of the parameters PRDX1 (p=0.05) and COL4 (p=0.009) in respective regression model considering the age and gender differences between MDD patients and controls. A major finding of this study is that values of platelet count, monocyte to lymphocyte ratio, white blood cell, and monocyte counts were assessed by the Random Forest machine learning algorithm as relevant predictors for discrimination between MDD patients and healthy controls with a power of prediction AUC=0.749.

Citace poskytuje Crossref.org

Bibliografie atd.

Literatura

000      
00000naa a2200000 a 4500
001      
bmc21028091
003      
CZ-PrNML
005      
20230112095647.0
007      
ta
008      
211105s2020 xr d f 000 0|eng||
009      
AR
024    7_
$a 10.33549/physiolres.934590 $2 doi
035    __
$a (PubMed)33476174
040    __
$a ABA008 $b cze $d ABA008 $e AACR2
041    0_
$a eng
044    __
$a xr
100    1_
$a Krivošová, Michaela, $d 1994- $7 xx0267037 $u Department of Pharmacology, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Martin, Slovak Republic
245    10
$a Potential major depressive disorder biomarkers in pediatric population - a pilot study / $c M. Krivosova, M. Grendar, I. Hrtanek, I. Ondrejka, I. Tonhajzerova, N. Sekaninova, L. Bona Olexova, D. Mokra, J. Mokry
504    __
$a Literatura
520    9_
$a Mental disorders affect 10-20 % of the young population in the world. Major depressive disorder (MDD) is a common mental disease with a multifactorial and not clearly explained pathophysiology. Many cases remain undetected and untreated, which influences patients' physical and mental health and their quality of life also in adulthood. The aim of our pilot study was to assess the prediction value of selected potential biomarkers, including blood cell counts, blood cell ratios, and parameters like peroxiredoxin 1 (PRDX1), tenascin C (TNC) and type IV collagen (COL4) between depressive pediatric patients and healthy peers and to evaluate a short effect of antidepressant treatment. In this study, 27 young depressive patients and 26 non-depressed age-matched controls were included. Blood analyses and immunological assays using commercial kits were performed. Platelet count was the only blood parameter for which the case/control status was statistically significant (p=0.01) in a regression model controlling for the age and gender differences. The results from ELISA analyses showed that the case/control status is a significant predictor of the parameters PRDX1 (p=0.05) and COL4 (p=0.009) in respective regression model considering the age and gender differences between MDD patients and controls. A major finding of this study is that values of platelet count, monocyte to lymphocyte ratio, white blood cell, and monocyte counts were assessed by the Random Forest machine learning algorithm as relevant predictors for discrimination between MDD patients and healthy controls with a power of prediction AUC=0.749.
650    _2
$a mladiství $7 D000293
650    _2
$a biologické markery $x analýza $7 D015415
650    _2
$a studie případů a kontrol $7 D016022
650    _2
$a depresivní porucha unipolární $x diagnóza $x epidemiologie $x psychologie $7 D003865
650    _2
$a ženské pohlaví $7 D005260
650    _2
$a lidé $7 D006801
650    _2
$a mužské pohlaví $7 D008297
650    _2
$a pilotní projekty $7 D010865
650    _2
$a kvalita života $7 D011788
651    _2
$a Slovenská republika $x epidemiologie $7 D018154
655    _2
$a časopisecké články $7 D016428
700    1_
$a Grendár, Marián, $d 1969- $7 xx0242991 $u Bioinformatics Unit of Biomedical Centre Martin, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Slovak Republic
700    1_
$a Hrtánek, Igor, $d 1982- $7 xx0267117 $u Psychiatric Clinic, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava and University Hospital Martin, Slovak Republic
700    1_
$a Ondrejka, Igor $7 xx0105387 $u Psychiatric Clinic, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava and University Hospital Martin, Slovak Republic
700    1_
$a Tonhajzerová, Ingrid $7 xx0105807 $u Department of Physiology, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Slovak Republic
700    1_
$a Sekaninová, Nikola $7 xx0257292 $u Department of Physiology, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Slovak Republic
700    1_
$a Olexová, Lucia $7 xx0257396 $u Department of Physiology, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Slovak Republic
700    1_
$a Mokrá, Daniela $7 xx0105806 $u Department of Physiology, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Slovak Republic
700    1_
$a Mokrý, Juraj, $d 1975- $7 xx0222150 $u Department of Pharmacology, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Slovak Republic
773    0_
$w MED00003824 $t Physiological research $x 1802-9973 $g Roč. 69, Suppl 3 (2020), s. S523-S532
773    0_
$t Proceedings of the ... Physiological days $x 1802-9973 $g Roč. 96, Suppl 3 (2020), s. S523-S532 $w MED00183838
856    41
$u https://pubmed.ncbi.nlm.nih.gov/33476174 $y Pubmed
910    __
$a ABA008 $b A 4120 $c 266 $y p $z 0
990    __
$a 20211105 $b ABA008
991    __
$a 20230112095641 $b ABA008
999    __
$a ok $b bmc $g 1728704 $s 1148636
BAS    __
$a 3
BAS    __
$a PreBMC
BMC    __
$a 2020 $b 69 $c Suppl 3 $d S523-S532 $e 20201231 $i 1802-9973 $m Physiological research $n Physiol. Res. (Print) $x MED00003824
BMC    __
$a 2020 $b 96 $c Suppl 3 $d S523-S532 $e 20201231 $i 1802-9973 $m Proceedings of the ... Physiological days $x MED00183838
LZP    __
$b NLK118 $a Pubmed-20211105

Najít záznam

Citační ukazatele

Pouze přihlášení uživatelé

Možnosti archivace