doctoral dissertation
Leon Deutsch (Author), Blaž Stres (Mentor)

Abstract

Human metabolism was studied in three different projects focusing on different levels of inactivity. Urine, liquor and serum metabolomics were used to assess the impact of nusinersen treatment in patients with spinal muscular atrophy. Urine samples were contrasted with samples from matching healthy cohort. In the PreTerm project, metabolomics (fecal and urine) and fecal microbial metagenomics were used to assess the differences between preterm and full-term born adults. In the X-Adapt project, urinary metabolomics was used to evaluate the 10-day training regime and the differences between trained and untrained individuals. In all projects, classification models based on different data sets were developed as a proof of principle and to foster their use in future studies or possibly in medical diagnostics. In addition, two workflows (GUMPP and MAGO tool) and a method to study physicochemical parameters (minimum pressure of piercing strength) were developed to study the microbiome and its environment, respectively. The final work resulted in the creation of the first Slovenian urine 1H-NMR database, which consists of 1200 urine metabolomes from different projects (PlanHab, Spinal Muscular Atrophy, X-Adapt, PreTerm, Healthy males and females) measured by 1H-NMR, outlining the baseline for future extensions. The entire database can be used to build machine-learning models for classification between different diseases or levels of physical activity at a national level.

Keywords

bioinformatics;metabolomics;metagenomcis;physical inactivity;data integration;systems biology;microbiome;urine;nuclear magnetic spectrometry;

Data

Language: English
Year of publishing:
Typology: 2.08 - Doctoral Dissertation
Organization: UL BF - Biotechnical Faculty
Publisher: [L. Deutsch]
UDC: 579:004(043.3)
COBISS: 132071939 Link will open in a new window
Views: 33
Downloads: 6
Average score: 0 (0 votes)
Metadata: JSON JSON-RDF JSON-LD TURTLE N-TRIPLES XML RDFA MICRODATA DC-XML DC-RDF RDF

Other data

Secondary language: Slovenian
Secondary title: Bioinformacijska integracija mikrobiomskih in metabolomskih podatkov v translacijskem kontekstu
Secondary abstract: V okviru večih projektov smo preučevali metabolome preiskovancev z različnimi stopnjami neaktivnosti. Za oceno učinka zdravljenja z zdravilom nusinersen pri bolnikih s spinalno mišično atrofijo smo uporabili metabolomiko urina, likvorja in seruma. Dodatne vzorce urina smo primerjali s tistimi iz zdrave kontrolne skupine. V projektu PreTerm smo s kombinacijo metabolomike fecesa in urina ter z metagenomiko fekalnega mikrobioma raziskovali razlike med predčasno in pravočasno rojenimi odraslimi. V projektu X-Adapt smo z metabolomiko urina ocenili učinke 10-dnevnega režima treninga in razlik med treniranimi in netreniranimi posamezniki. V vseh projektih smo na zbranih podatkih razvili modele za razvrščanje skupin z namenom razvoja analitskih poti ter prikaza možnostjo uporabe teh modelov v prihodnjih študijah ali morda v medicinski diagnostiki. Poleg tega sta bila razvita dva cevovoda (orodje GUMPP in MAGO) ter metoda za preučevanje fizikalno-kemijskih parametrov (minimalna prebodna sila) za preučevanje mikrobioma in njegovega okolja. Končni rezultat analize je bila izdelava prve slovenske metabolomske baze podatkov 1H-NMR urina, ki jo sestavlja 1200 metabolomov urina iz različnih projektov (PlanHab, Spinalna mišična atrofija, X-Adapt, PreTerm, Zdravi moški in ženske), merjenih z 1H-NMR, ki predstavljajo osnovo za prihodnje razširitve iz novih projektov. Celotno bazo podatkov je mogoče uporabiti za gradnjo modelov strojnega učenja za razvrščanje med različnimi boleznimi ali stopnjami telesne aktivnosti na nacionalni ravni.
Secondary keywords: bioinformatika;metabolomika;metagenomika;fizikalna inaktivnost;integracija podatkov;sistemska biologija;mikrobiom;urin;jedrska magnetna resonanca;doktorska disertacija;
Type (COBISS): Doctoral dissertation
Study programme: 0
Embargo end date (OpenAIRE): 1970-01-01
Thesis comment: Univ. v Ljubljani, Biotehniška fak.
Pages: 1 spletni vir (1 datoteka PDF (XI, 205 str.)
ID: 17238886
Recommended works: