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- Smati, S., et al.
(author)
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Integrative study of diet-induced mouse models of NAFLD identifies PPARα as a sexually dimorphic drug target
- 2022
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In: Gut. - : BMJ Publishing Group. - 0017-5749 .- 1468-3288. ; 71:4, s. 807-821
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Journal article (peer-reviewed)abstract
- We evaluated the influence of sex on the pathophysiology of non-alcoholic fatty liver disease (NAFLD). We investigated diet-induced phenotypic responses to define sex-specific regulation between healthy liver and NAFLD to identify influential pathways in different preclinical murine models and their relevance in humans. Different models of diet-induced NAFLD (high-fat diet, choline-deficient high-fat diet, Western diet or Western diet supplemented with fructose and glucose in drinking water) were compared with a control diet in male and female mice. We performed metabolic phenotyping, including plasma biochemistry and liver histology, untargeted large-scale approaches (liver metabolome, lipidome and transcriptome), gene expression profiling and network analysis to identify sex-specific pathways in the mouse liver. The different diets induced sex-specific responses that illustrated an increased susceptibility to NAFLD in male mice. The most severe lipid accumulation and inflammation/fibrosis occurred in males receiving the high-fat diet and Western diet, respectively. Sex-biased hepatic gene signatures were identified for these different dietary challenges. The peroxisome proliferator-activated receptor α (PPARα) co-expression network was identified as sexually dimorphic, and in vivo experiments in mice demonstrated that hepatocyte PPARα determines a sex-specific response to fasting and treatment with pemafibrate, a selective PPARα agonist. Liver molecular signatures in humans also provided evidence of sexually dimorphic gene expression profiles and the sex-specific co-expression network for PPARα. These findings underscore the sex specificity of NAFLD pathophysiology in preclinical studies and identify PPARα as a pivotal, sexually dimorphic, pharmacological target. NCT02390232.
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2. |
- Tian, Yu, et al.
(author)
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Genome-Wide Interaction Analysis of Genetic Variants With Menopausal Hormone Therapy for Colorectal Cancer Risk
- 2022
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In: Journal of the National Cancer Institute. - : Oxford University Press. - 0027-8874 .- 1460-2105. ; 114:8, s. 1135-1148
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Journal article (peer-reviewed)abstract
- BACKGROUND: The use of menopausal hormone therapy (MHT) may interact with genetic variants to influence colorectal cancer (CRC) risk. METHODS: We conducted a genome-wide, gene-environment interaction between single nucleotide polymorphisms and the use of any MHT, estrogen only, and combined estrogen-progestogen therapy with CRC risk, among 28 486 postmenopausal women (11 519 CRC patients and 16 967 participants without CRC) from 38 studies, using logistic regression, 2-step method, and 2- or 3-degree-of-freedom joint test. A set-based score test was applied for rare genetic variants. RESULTS: The use of any MHT, estrogen only and estrogen-progestogen were associated with a reduced CRC risk (odds ratio [OR] = 0.71, 95% confidence interval [CI] = 0.64 to 0.78; OR = 0.65, 95% CI = 0.53 to 0.79; and OR = 0.73, 95% CI = 0.59 to 0.90, respectively). The 2-step method identified a statistically significant interaction between a GRIN2B variant rs117868593 and MHT use, whereby MHT-associated CRC risk was statistically significantly reduced in women with the GG genotype (OR = 0.68, 95% CI = 0.64 to 0.72) but not within strata of GC or CC genotypes. A statistically significant interaction between a DCBLD1 intronic variant at 6q22.1 (rs10782186) and MHT use was identified by the 2-degree-of-freedom joint test. The MHT-associated CRC risk was reduced with increasing number of rs10782186-C alleles, showing odds ratios of 0.78 (95% CI = 0.70 to 0.87) for TT, 0.68 (95% CI = 0.63 to 0.73) for TC, and 0.66 (95% CI = 0.60 to 0.74) for CC genotypes. In addition, 5 genes in rare variant analysis showed suggestive interactions with MHT (2-sided P < 1.2 × 10-4). CONCLUSION: Genetic variants that modify the association between MHT and CRC risk were identified, offering new insights into pathways of CRC carcinogenesis and potential mechanisms involved.
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3. |
- Ambikan, Anoop T., et al.
(author)
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Multi-omics personalized network analyses highlight progressive disruption of central metabolism associated with COVID-19 severity
- 2022
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In: Cell systems. - : Elsevier BV. - 2405-4712 .- 2405-4720. ; 13:8, s. 665-681
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Journal article (peer-reviewed)abstract
- The clinical outcome and disease severity in coronavirus disease 2019 (COVID-19) are heterogeneous, and the progression or fatality of the disease cannot be explained by a single factor like age or comorbidities. In this study, we used system-wide network-based system biology analysis using whole blood RNA sequencing, immunophenotyping by flow cytometry, plasma metabolomics, and single-cell-type metabolo-mics of monocytes to identify the potential determinants of COVID-19 severity at personalized and group levels. Digital cell quantification and immunophenotyping of the mononuclear phagocytes indicated a sub-stantial role in coordinating the immune cells that mediate COVID-19 severity. Stratum-specific and person-alized genome-scale metabolic modeling indicated monocarboxylate transporter family genes (e.g., SLC16A6), nucleoside transporter genes (e.g., SLC29A1), and metabolites such as a-ketoglutarate, succi-nate, malate, and butyrate could play a crucial role in COVID-19 severity. Metabolic perturbations targeting the central metabolic pathway (TCA cycle) can be an alternate treatment strategy in severe COVID-19.
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