4. DISCUSSÃO
4.4 Relevância clínica
O sobrepeso ou obesidade, que se desenvolve sob um balanço energético positivo crônico, são caracterizados pelo acúmulo de tecido adiposo e aumento da massa corporal. Portanto, a redução desse excesso de massa adiposa é o principal objetivo da abordagem clínica da prevenção primária da MetS (GADDE et al., 2018; HEYMSFIELD;
WADDEN, 2017). O TRF pode ser uma estratégia eficiente para promover a perda de peso e reduzir o perímetro de cintura naqueles indivíduos que não conseguem aderir a dietas que alteram o padrão nutricional diária do indivíduo. Além disso, pode ser uma estratégia que demanda menor tempo para implantação e explicação ao paciente no contexto clínico de atendimento em saúde. Em indivíduos com baixa carga severidade de MetS, avaliados por meio do Z-MetS, alterações a nível da análise metabolômica podem ocorrer previamente às alterações em biomarcadores clínicos clássicos e podem contribuir para melhora do perfil metabólico e redução de eventos adversos futuros.
4.2 Limitações
Este estudo não foi um ensaio clínico randomizado e não inclui aspectos nutricionais detalhados da dieta dos sujeitos da amostra, pois encontramos dados conflitantes relatados pelos indivíduos, como descrição incompleta da quantidade de alimentos ingeridos, frequência das refeições e tipo de alimentos (ex.: tipo de arroz ingerido). No entanto, o autorrelato da ingestão alimentar pode diferir ou subestimar o valor real, oferecendo uma análise inconclusiva e enganosa (SCHOELLER et al., 2013; DHURANDHAR et al., 2015). A restrição energética é o principal fator que leva à perda de peso independentemente do tipo de dieta (FREIRE, 2020). Portanto, é viável supor que foi alcançada uma redução na energia total consumida, considerando que o gasto energético se manteve constante.
Em nosso estudo selecionamos intencionalmente um grupo amostral que obteve maior perda de peso com o protocolo de TRF. Esse viés de seleção amostral pode limitar nossos resultados para outras pessoas que não alcançam a mesma perda de peso.
Kloecker et al., (2019), em uma meta-análise, demonstraram uma dose-resposta entre perda de peso e redução na ingestão de energia. Portanto, pode-se supor que a perda de peso foi maior naquelas mulheres que apresentaram mais déficit no balanço energético.
Uma análise metabolômica não direcionada após 3 meses de um protocolo de TRF foi realizada com uma ideia inicial de analisar os efeitos crônicos dessa intervenção. Porém, como grande parte das mulheres permaneciam realizando TRF, mesmo após o fim do protocolo e na fase da segunda coleta. Não podemos distinguir se nossos achados
representam efeitos crônicos ou agudos da TRF. Por fim, nosso estudo envolveu a análise do metaboloma do plasma, resultados diferentes podem ser esperados ao realizar a análise em outros tecidos, como músculos, fígado ou tecido adiposo.
5 CONCLUSÃO
O TRF é uma estratégia dietética eficaz para promover a perda de peso e diminuir o perímetro de cintura sem alterar o Z-MetS. Na análise metabolômica, as vias que participam do metabolismo energético estão em grande parte presentes em mulheres que se submeteram ao programa de TRF e podem participar de processos fisiológicos na perda de peso e melhora do perfil metabólica. O ciclo da glicose-alanina e β-oxidação de ácidos graxos de cadeia muito longa foram significativamente enriquecidos e podem implicar em alterações metabólicas importantes durante a perda de peso, contribuindo para a promoção da prevenção primária no contexto do sobrepeso e obesidade.
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ANEXO 1
Metabolomic Data Analysis with MetaboAnalyst 5.0
Name: guest1199084766715613791
March 14, 2023
1 Background
MSEA or Metabolite Set Enrichment Analysis is a way to identify biologically meaningful patterns that are signi cantly enriched in quantitative metabolomic data. In conventional approaches, metabolites are evaluated individually for their signi cance under conditions of study. Those compounds that have passed certain signi cance level are then combined to see if any meaningful patterns can be discerned. In contrast, MSEA directly investigates if a set of functionally related metabolites without the need to preselect compounds based on some arbitrary cut-o threshold. It has the potential to identify subtle but consistent changes among a group of related compounds, which may go undetected with the conventional approaches.
Essentially, MSEA is a metabolomic version of the popular GSEA (Gene Set Enrichment Analysis) software with its own collection of metabolite set libraries as well as an implementation of user-friendly web-interfaces. GSEA is widely used in genomics data analysis and has proven to be a powerful alterna- tive to conventional approaches. For more information, please refer to the original paper by Subramanian A, and a nice review paper by Nam D, Kim SY. 1. 2
2 MSEA Overview
Metabolite set enrichment analysis consists of four steps - data input, data processing, data analysis, and results download. Di erent analysis procedures are performed based on di erent input types. In addition, users can also browse and search the metabolite set libraries as well as upload their self-de ned metabolite sets for enrichment analysis.
Users can also perform metabolite name mapping between a variety of compound names, synonyms, and major database identi ers.
3 Data Input
There are three enrichment analysis algorithms o ered by MSEA. Accordingly, three di erent types of data inputs are required by these three approaches:
A list of important compound names - entered as a one column data (Over Representation Analysis
(ORA));
A single measured bio uid (urine, blood, CSF) sample- entered as tab separated
two-column data with the rst column for compound name, and the second for concentration values (Single Sample Pro ling (SSP));
1 SubramanianGene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression pro les., Proc Natl Acad Sci USA. 2005 102(43): 15545-50
2 Nam D, Kim SY. Gene-set approach for expression pattern analysis, Brie ngs in Bioinformatics. 2008 9(3): 189-197.