RESUMEN
Data-driven computational analysis is becoming increasingly important in biomedical research, as the amount of data being generated continues to grow. However, the lack of practices of sharing research outputs, such as data, source code and methods, affects transparency and reproducibility of studies, which are critical to the advancement of science. Many published studies are not reproducible due to insufficient documentation, code, and data being shared. We conducted a comprehensive analysis of 453 manuscripts published between 2016-2021 and found that 50.1% of them fail to share the analytical code. Even among those that did disclose their code, a vast majority failed to offer additional research outputs, such as data. Furthermore, only one in ten articles organized their code in a structured and reproducible manner. We discovered a significant association between the presence of code availability statements and increased code availability. Additionally, a greater proportion of studies conducting secondary analyses were inclined to share their code compared to those conducting primary analyses. In light of our findings, we propose raising awareness of code sharing practices and taking immediate steps to enhance code availability to improve reproducibility in biomedical research. By increasing transparency and reproducibility, we can promote scientific rigor, encourage collaboration, and accelerate scientific discoveries. We must prioritize open science practices, including sharing code, data, and other research products, to ensure that biomedical research can be replicated and built upon by others in the scientific community.
RESUMEN
BACKGROUND: Abdominal obesity increases the risk for non-alcoholic fatty liver disease (NAFLD), now known as metabolic dysfunction-associated steatotic liver disease (MASLD). METHODS: To elucidate the directional cell-type level biological mechanisms underlying the association between abdominal obesity and MASLD, we integrated adipose and liver single nucleus RNA-sequencing and bulk cis-expression quantitative trait locus (eQTL) data with the UK Biobank genome-wide association study (GWAS) data using colocalization. Then we used colocalized cis-eQTL variants as instrumental variables in Mendelian randomization (MR) analyses, followed by functional validation experiments on the target genes of the cis-eQTL variants. FINDINGS: We identified 17 colocalized abdominal obesity GWAS variants, regulating 17 adipose cell-type marker genes. Incorporating these 17 variants into MR discovers a putative tissue-of-origin, cell-type-aware causal effect of abdominal obesity on MASLD consistently with multiple MR methods without significant evidence for pleiotropy or heterogeneity. Single cell data confirm the adipocyte-enriched mean expression of the 17 genes. Our cellular experiments across human adipogenesis identify risk variant -specific epigenetic and transcriptional mechanisms. Knocking down two of the 17 genes, PPP2R5A and SH3PXD2B, shows a marked decrease in adipocyte lipidation and significantly alters adipocyte function and adipogenesis regulator genes, including DGAT2, LPL, ADIPOQ, PPARG, and SREBF1. Furthermore, the 17 genes capture a characteristic MASLD expression signature in subcutaneous adipose tissue. INTERPRETATION: Overall, we discover a significant cell-type level effect of abdominal obesity on MASLD and trace its biological effect to adipogenesis. FUNDING: NIH grants R01HG010505, R01DK132775, and R01HL170604; the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (Grant No. 802825), Academy of Finland (Grants Nos. 333021), the Finnish Foundation for Cardiovascular Research the Sigrid Jusélius Foundation and the Jane and Aatos Erkko Foundation; American Association for the Study of Liver Diseases (AASLD) Advanced Transplant Hepatology award and NIH/NIDDK (P30DK41301) Pilot and Feasibility award; NIH/NIEHS F32 award (F32ES034668); Finnish Diabetes Research Foundation, Kuopio University Hospital Project grant (EVO/VTR grants 2005-2021), the Academy of Finland grant (Contract no. 138006); Academy of Finland (Grant Nos 335443, 314383, 272376 and 266286), Sigrid Jusélius Foundation, Finnish Medical Foundation, Finnish Diabetes Research Foundation, Novo Nordisk Foundation (#NNF20OC0060547, NNF17OC0027232, NNF10OC1013354) and Government Research Funds to Helsinki University Hospital; Orion Research Foundation, Maud Kuistila Foundation, Finish Medical Foundation, and University of Helsinki.
Asunto(s)
Predisposición Genética a la Enfermedad , Estudio de Asociación del Genoma Completo , Obesidad Abdominal , Sitios de Carácter Cuantitativo , Humanos , Obesidad Abdominal/genética , Enfermedad del Hígado Graso no Alcohólico/genética , Enfermedad del Hígado Graso no Alcohólico/patología , Enfermedad del Hígado Graso no Alcohólico/metabolismo , Polimorfismo de Nucleótido Simple , Análisis de Secuencia de ARN , Proteína Fosfatasa 2/genética , Proteína Fosfatasa 2/metabolismo , Núcleo Celular/metabolismo , Núcleo Celular/genética , Adipogénesis/genética , Análisis de la Célula Individual , Regulación de la Expresión GénicaRESUMEN
Data-driven computational analysis is becoming increasingly important in biomedical research, as the amount of data being generated continues to grow. However, the lack of practices of sharing research outputs, such as data, source code and methods, affects transparency and reproducibility of studies, which are critical to the advancement of science. Many published studies are not reproducible due to insufficient documentation, code, and data being shared. We conducted a comprehensive analysis of 453 manuscripts published between 2016-2021 and found that 50.1% of them fail to share the analytical code. Even among those that did disclose their code, a vast majority failed to offer additional research outputs, such as data. Furthermore, only one in ten papers organized their code in a structured and reproducible manner. We discovered a significant association between the presence of code availability statements and increased code availability (p=2.71×10-9). Additionally, a greater proportion of studies conducting secondary analyses were inclined to share their code compared to those conducting primary analyses (p=1.15*10-07). In light of our findings, we propose raising awareness of code sharing practices and taking immediate steps to enhance code availability to improve reproducibility in biomedical research. By increasing transparency and reproducibility, we can promote scientific rigor, encourage collaboration, and accelerate scientific discoveries. We must prioritize open science practices, including sharing code, data, and other research products, to ensure that biomedical research can be replicated and built upon by others in the scientific community.
RESUMEN
BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) is a fast-growing, underdiagnosed, epidemic. We hypothesise that obesity-related inflammation compromises adipose tissue functions, preventing efficient fat storage, and thus driving ectopic fat accumulation into the liver. METHODS: To identify adipose-based mechanisms and potential serum biomarker candidates (SBCs) for NAFLD, we utilise dual-tissue RNA-sequencing (RNA-seq) data in adipose tissue and liver, paired with histology-based NAFLD diagnosis, from the same individuals in a cohort of obese individuals. We first scan for genes that are differentially expressed (DE) for NAFLD in obese individuals' subcutaneous adipose tissue but not in their liver; encode proteins secreted to serum; and show preferential adipose expression. Then the identified genes are filtered to key adipose-origin NAFLD genes by best subset analysis, knockdown experiments during human preadipocyte differentiation, recombinant protein treatment experiments in human liver HepG2 cells, and genetic analysis. FINDINGS: We discover a set of genes, including 10 SBCs, that may modulate NAFLD pathogenesis by impacting adipose tissue function. Based on best subset analysis, we further follow-up on two SBCs CCDC80 and SOD3 by knockdown in human preadipocytes and subsequent differentiation experiments, which show that they modulate crucial adipogenesis genes, LPL, SREBPF1, and LEP. We also show that treatment of the liver HepG2 cells with the CCDC80 and SOD3 recombinant proteins impacts genes related to steatosis and lipid processing, including PPARA, NFE2L2, and RNF128. Finally, utilizing the adipose NAFLD DE gene cis-regulatory variants associated with serum triglycerides (TGs) in extensive genome-wide association studies (GWASs), we demonstrate a unidirectional effect of serum TGs on NAFLD with Mendelian Randomization (MR) analysis. We also demonstrate that a single SNP regulating one of the SBC genes, rs2845885, produces a significant MR result by itself. This supports the conclusion that genetically regulated adipose expression of the NAFLD DE genes may contribute to NAFLD through changes in serum TG levels. INTERPRETATION: Our results from the dual-tissue transcriptomics screening improve the understanding of obesity-related NAFLD by providing a targeted set of 10 adipose tissue-active genes as new serum biomarker candidates for the currently grossly underdiagnosed fatty liver disease. FUNDING: The work was supported by NIH grants R01HG010505 and R01DK132775. The Genotype-Tissue Expression (GTEx) Project was supported by the Common Fund of the Office of the Director of the National Institutes of Health, and by NCI, NHGRI, NHLBI, NIDA, NIMH, and NINDS. The KOBS study (J. P.) was supported by the Finnish Diabetes Research Foundation, Kuopio University Hospital Project grant (EVO/VTR grants 2005-2019), and the Academy of Finland grant (Contract no. 138006). This study was funded by the European Research Council under the European Union's Horizon 2020 research and innovation program (Grant No. 802825 to M. U. K.). K. H. P. was funded by the Academy of Finland (grant numbers 272376, 266286, 314383, and 335443), the Finnish Medical Foundation, Gyllenberg Foundation, Novo Nordisk Foundation (grant numbers NNF10OC1013354, NNF17OC0027232, and NNF20OC0060547), Finnish Diabetes Research Foundation, Finnish Foundation for Cardiovascular Research, University of Helsinki, and Helsinki University Hospital and Government Research Funds. I. S. was funded by the Instrumentarium Science Foundation. Personal grants to U. T. A. were received from the Matti and Vappu Maukonen Foundation, Ella och Georg Ehrnrooths Stiftelse and the Finnish Foundation for Cardiovascular Research.
Asunto(s)
Enfermedad del Hígado Graso no Alcohólico , Humanos , Enfermedad del Hígado Graso no Alcohólico/genética , Enfermedad del Hígado Graso no Alcohólico/complicaciones , Estudio de Asociación del Genoma Completo , Obesidad/complicaciones , Obesidad/genética , Obesidad/metabolismo , Hígado/metabolismo , Biomarcadores/metabolismoRESUMEN
BACKGROUND: Hepatocellular carcinoma (HCC) is a common primary liver cancer with poor overall survival. We hypothesized that there are HCC-associated cell-types that impact patient survival. METHODS: We combined liver single nucleus (snRNA-seq), single cell (scRNA-seq), and bulk RNA-sequencing (RNA-seq) data to search for cell-type differences in HCC. To first identify cell-types in HCC, adjacent non-tumor tissue, and normal liver, we integrated single-cell level data from a healthy liver cohort (n = 9 non-HCC samples) collected in the Strasbourg University Hospital; an HCC cohort (n = 1 non-HCC, n = 14 HCC-tumor, and n = 14 adjacent non-tumor samples) collected in the Singapore General Hospital and National University; and another HCC cohort (n = 3 HCC-tumor and n = 3 adjacent non-tumor samples) collected in the Dumont-UCLA Liver Cancer Center. We then leveraged these single cell level data to decompose the cell-types in liver bulk RNA-seq data from HCC patients' tumor (n = 361) and adjacent non-tumor tissue (n = 49) from the Cancer Genome Atlas (TCGA) multi-center cohort. For replication, we decomposed 221 HCC and 209 adjacent non-tumor liver microarray samples from the Liver Cancer Institute (LCI) cohort collected by the Liver Cancer Institute and Zhongshan Hospital of Fudan University. RESULTS: We discovered a tumor-associated proliferative cell-type, Prol (80.4% tumor cells), enriched for cell cycle and mitosis genes. In the liver bulk tissue from the TCGA cohort, the proportion of the Prol cell-type is significantly increased in HCC and associates with a worse overall survival. Independently from our decomposition analysis, we reciprocally show that Prol nuclei/cells significantly over-express both tumor-elevated and survival-decreasing genes obtained from the bulk tissue. Our replication analysis in the LCI cohort confirmed that an increased estimated proportion of the Prol cell-type in HCC is a significant marker for a shorter overall survival. Finally, we show that somatic mutations in the tumor suppressor genes TP53 and RB1 are linked to an increase of the Prol cell-type in HCC. CONCLUSIONS: By integrating liver single cell, single nucleus, and bulk expression data from multiple cohorts we identified a proliferating cell-type (Prol) enriched in HCC tumors, associated with a decreased overall survival, and linked to TP53 and RB1 somatic mutations.