Clin Mol Hepatol > Volume 31(2); 2025 > Article
Ciociola, Dutta, Sasidharan, Kovooru, Noto, Pennisi, Petta, Mirarchi, Maurotti, Scopacasa, Tirinato, Candeloro, Henricsson, Lindén, Jamialahmadi, Pujia, Mancina, and Romeo: Downregulation of the MARC1 p.A165 risk allele reduces hepatocyte lipid content by increasing beta-oxidation

ABSTRACT

Background/Aims

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a global epidemic. The disease has a strong genetic component, and a common missense variant (rs2642438) in the mitochondrial amidoxime-reducing component 1 (MARC1) gene confers protection against its onset and severity. However, there are contrasting results regarding the mechanisms that promote this protection.

Methods

We downregulated MARC1 in primary human hepatocytes (PHHs) using short interfering RNA (siRNA). We measured neutral lipid content by Oil-Red O staining and fatty acid oxidation by radiolabeled tracers. We also performed RNA-sequencing and proteomic analysis using LC-MS. Additionally, we analyzed data from 239,075 participants from the UK Biobank.

Results

Downregulation of MARC1 reduced neutral lipid content in PHHs homozygous for the wild type (p.A165, risk), but not for the mutant (p.T165, protective), allele. We found that this reduction was mediated by increased fatty acid utilization via β-oxidation. Consistent with these results, we found that the levels of 3-hydroxybutyrate, a by-product of β-oxidation, were higher in carriers of the rs2642438 minor allele among samples from the UK biobank, indicating higher β-oxidation in these individuals. Moreover, downregulation of the MARC1 p.A165 variant resulted in a more favorable phenotype by reducing ferroptosis and reactive oxygen species levels.

Conclusions

MARC1 downregulation in carriers of the risk allele results in lower hepatocyte neutral lipids content due to higher β-oxidation, while upregulating beneficial pathways involved in cell survival.

Graphical Abstract

INTRODUCTION

Metabolic dysfunction-associated steatotic liver disease (MASLD), formerly known as nonalcoholic fatty liver disease (NAFLD) [1], affects a staggering one-quarter of the global population, posing a significant health burden [2-4]. MASLD comprises a spectrum of conditions, ranging from isolated hepatic steatosis, potentially progressing to metabolic dysfunction-associated steatohepatitis (MASH), which is marked by inflammation and fibrotic scaring of the liver, which can ultimately lead to cirrhosis and hepatocellular carcinoma. Lifestyle modification and emerging pharmacological approaches offer promising treatment for MASLD. However, given the heterogeneous nature and complexity of MASLD the disease still pose a significant clinical challenge. For example, bariatric surgery is effective for treating MASLD in individuals with obesity [5]. However, there are many people with MASLD who are not overweight, and thus this option is not suitable for treatment at the population level. Recently, resmetirom, a thyroid hormone beta receptor agonist, has been approved by the US Food and Drug Administration to treat MASH and fibrosis. However, only 1 in 4 study participants responded with a meaningful reduction in fibrosis [6], making the identification of novel therapeutics still of paramount importance.
MASLD has a strong genetic component, with a common variant in the PNPLA3 gene exhibiting the most robust effect size. Other common variants in GCKR, TM6SF2 and MBOAT7 also contribute to MASLD risk [7-9]. A genome-wide association study (GWAS) for an all-cause liver cirrhosis phenotype identified a common missense variant (rs2642438) in the mitochondrial amidoxime-reducing component 1 (MARC1) gene as an additional genetic determinant of MASLD [10]. The MARC1 rs2642438 minor allele robustly associates with lower liver triglycerides, reduced transaminase levels, and protection against cirrhosis and hepatocellular carcinoma [10]. Interestingly, the protective effect of the MARC1 variant extends to alcoholic liver disease [11].
The MARC1 rs2642438 results in an amino acid substitution from alanine (A) to threonine (T) at position 165 of the protein (p.A165T), leading to reduced protein stability and higher proteasomal degradation [12-14]. Altogether, this these data suggest that the downregulation in the levels of hepatic MARC1 may potentially be beneficial in reducing the risk of liver steatosis.
However, the molecular mechanisms underlying MARC1-related protection against MASLD remain inconclusive. It has been shown that MARC1 p.A165 downregulation does not affect de novo lipogenesis or fatty acid oxidation in primary human hepatocytes (PHHs), despite a decrease in 3-hydroxybutyrate (3HB), a by-product of β-oxidation [15]. In contrast [16], overexpression of the protective, but not of the risk allele, of MARC1 resulted in a higher oxygen consumption rate in hepatoma cells, as measured by Seahorse assay, suggesting a gain of function of the protective mutant protein. However, MARC1-downregulation in primary human adipocytes resulted in an upregulation of CPT1A, the gene coding a key β-oxidation enzyme [16], suggesting the variant is a loss of function.
Given these contradictory observations we sought to elucidate the specific mechanisms underlying the MARC1-related protective effect against MASLD in PHHs. Here, we present findings that shed light on the complex role of MARC1 in regulating hepatic lipid homeostasis and cellular stress responses.

MATERIALS AND METHODS

Cell culture

Cryopreserved PHHs were obtained from the commercial vendor, BioIVT. They were seeded with CP media and maintained with HI media (BioIVT). Detailed methods are available in the supplementary information.

siRNA transfection

Cells were transiently transfected for 48 hours, with scramble siRNA 30 nM (AM4611; ThermoFisher Scientific, Cleveland, OH, USA) or MARC1 siRNA (mix of s34872, s34873, s34874; concentration 30 nM each; Thermo Fisher Scientific) with Lipofectamine 3000, as per the manufacturer’s instructions. PHH maintenance medium (HI medium, BioIVT) was used for transfection and maintenance in PHH experiments.

RNA-sequencing analysis

Total RNA was extracted using miRNeasy Tissue/cells Advanced Mini Kit (QiaGen Inc., Valencia, CA, USA). Reads were aligned to GRCh38 reference genome by STAR53 (v2.7.10a) and gene-level read counts were quantified by RSEM52 (v1.3.3) software against the Ensembl (release 107). The DESeq2 R package (v.1.38.3) was used to perform a differential expression analysis. The resulting P-values were adjusted using Benjamini and Hochberg’s approach for controlling the false discovery rate (FDR).

Proteomic sample preparation

Details for the experiment are provided in supplementary information. Samples were processed using a modified SP3 method [17]. The protein abundance ratio was transformed into the log2 ratio and a t-test was performed. Using the enrichment analysis from FerrDB [18] database for ferroptosis, a list of proteins for each driver, regulator or suppressor of ferroptosis was obtained and the heatmap of the proteins was plotted from our proteomics data using the fold change values. The odds ratio (OR) of ferroptosis-related proteins in the list of all significantly different levels of proteins after MARC1 downregulation is shown.

Oil-Red-O (ORO) staining

Forty-eight hours after transfection, cells were subjected to ORO staining (Sigma-Aldrich, St. Louis, MO, USA) and counterstained using DAPI (Sigma-Aldrich) as previously performed [19]. Images were captured at 40X magnification with NIS-Element 5.30.04 software (Nikon Instruments, Inc., Melville, NY, USA) and analyzed using an in-house macro in ImageJ (v.1.52h, NIH). ORO-stained neutral lipid content was normalized to the number of DAPI stained nuclei.

β-oxidation assay

The β-oxidation rate was assessed as previously described [19,20]. Cells were incubated with HI medium supplemented with 8.3 µCi/mL [3H]palmitate (PerkinElmer, Denton, TX, USA) and 110 µM PA (Avanti Polar Lipids, Alabaster, AL, USA)) and 1% BSA for 2 hours. Cell media were collected and centrifuged at 12,000 rpm for 5 minutes after adding 50 μL of 20% BSA and 27 μL of 70% perchloric acid. The supernatant was collected, and the radioactivity of the water-soluble fraction was quantified by liquid scintillation counting (Beckman Coulter, Brea, CA, USA). Data were normalized for the number of cells.

Western blotting

For Western blot analysis in cell lysate, total proteins were obtained using M-PER® containing a complete protease inhibitor cocktail (Sigma-Aldrich). For ApoB100 detection, cell media were collected and subjected to ultracentrifugation at a potassium bromide (KBr) density of 1.063 g/mL to separate TG-rich-lipoproteins (TRL) fraction. Proteins were then separated by 10% (for ATG7), 12% (for MARC1) or 6% (for ApoB100) SDS-PAGE and transferred to nitrocellulose membranes (Amersham; Cytiva, Buckinghamshire, UK).

Statistical analysis

Data are presented as mean±standard deviation. P-values were calculated using a non-parametric Mann-Whitney test unless specified otherwise. Statistical analysis was performed using GraphPad Prism version 9 (San Diego, CA, USA). All the reported P-values are two-sided. The P-values<0.05 were considered statistically significant.
The association between MARC1 rs2642438 and rank inverse transformed 3-hydoxybutyrate in Europeans from the UK Biobank (n=239,075) was performed using linear regression analysis in REGENIE adjusting for age, sex, age×sex, age2 and age2×sex, body mass index, first 10 genomic principal components and array batch [21,22].
Detailed method for all the other experiments and descriptions are available in the supplementary information.

RESULTS

Downregulation of the MARC1 p.A165 risk allele reduces hepatocyte neutral lipid content

To test the effect of MARC1 ablation on intracellular triglyceride homeostasis, we downregulated MARC1 by siRNA in PHHs carrying genes encoding for the wild-type (p.A165) risk or the (p.T165) protective protein. We found that a 70% reduction in MARC1 gene expression (Fig. 1C) resulted in lower intracellular neutral lipid content, as measured by Oil-Red-O staining and its quantification in hepatocytes homozygote for the risk allele (Fig. 1A) but not in the protective allele (Fig. 1B). Next, we repeated the same experiment in four different cell lines homozygous for the risk allele; namely, HepG2, HuH7, Hep3B2 and HepaRG with virtually identical results (Supplementary Fig. 1). We also repeated the same experiment in another PHH donor that was homozygous for the risk allele and observed similar results (Supplementary Fig. 2A). Next, to test the effect of the p.A165T substitution at the protein level, we measured the intracellular MARC1 protein levels by Western blotting in PHHs homozygous for either the risk or the protective allele (Fig. 1D). We detected a 50% reduction in protein levels in PHHs homozygous for the protective compared to the risk allele. These findings align with previous studies demonstrating accelerated degradation of the protein encoded by the protective allele [12].
To further understand the molecular mechanisms underlying the protection conferred by the downregulation of MARC1, we focused on PHHs from donors homozygous for the wild-type (risk) allele.

Downregulation of the MARC1 p.A165 risk allele promotes fatty acid catabolism via increased β-oxidation

In hepatocytes, lipid accumulation can be due to perturbation of three major pathways: a) β-oxidation; b) secretion of triglyceride-rich ApoB100-containing lipoproteins; or c) de novo lipogenesis. Thus, we examined the effect of MARC1 downregulation on these 3 major pathways. We found that downregulation of MARC1 p.A165 (risk) resulted in higher β-oxidation as measured by radioactive tracers in PHHs (Fig. 2A; Supplementary Fig. 2B). We did not see differences in a) ApoB100 secretion as measured by Western blotting, b) triglycerides concentrations in the culture media as measured by mass spectrometry analysis (MS) (Fig. 2B; Supplementary Fig. 2EH) or c) in intracellular de novo triglyceride biosynthesis media as by radiolabelled glycerol incorporation into triglycerides (Fig. 2C; Supplementary Fig. 2C). In contrast, downregulation of MARC1 p.T165 (protective) did not have any differences in these pathways (Supplementary Fig. 3).
Next, to examine the impact of high fatty acid stress on lipid metabolism, we incubated PHHs homozygous for either the risk or protective allele with a 300 µM fatty acid mixture (oleic acid and palmitic acid, 1:1 ratio; for 48 hours). Similar to the previous experiment (Fig. 2A), we found that MARC1 p.A165 (risk) downregulation resulted in an increased β-oxidation, nearly doubling the rate (Fig. 2D). In contrast, β-oxidation levels remained unchanged in the cells expressing MARC1 p.T165 (protective) (Fig. 2D). We did not detect differences in ApoB100 protein level in the triglyceride-rich lipoprotein, as quantified by Western blot, and in triglyceride levels as measured by MS analysis regardless of the MARC1 genotype (Fig. 2E). These data suggest that MARC1 p.A165 downregulation reduces intracellular neutral lipids content primarily by increasing fatty acid breakdown via elevated β-oxidation.
To translate our results to humans, we examined the 3HB plasma levels, a proxy of β-oxidation, produced primarily in the liver [23,24], in carriers of the MARC1 rs2642438 variant (encoding for the p.A165T substitution) in 239,075 individuals from the UK Biobank (Fig. 2F). The data was adjusted for different clinical conditions that can potentially affect β-oxidation. The minor allele encoding for the mutant p. T165 protein was associated with higher levels of 3-HB demonstrating that inactivation of MARC1 results in higher β-oxidation.

MARC1 p.A165 knockout affects intracellular lipid composition

To investigate lipid quantity and composition in cells with a stable ablation of MARC1, we used CRISPR/Cas9-mediated stable KO HepG2 cells (homozygous for the risk allele). Raman imaging was utilized to analyze lipids based on unambiguous lipidic Raman markers, like the intensity ratio between CH2 vibrations (2,850 and 2,880 cm-1) and CH3 vibrations (2,930 cm-1) [25,26]. Total lipid content was calculated for each cell as the ratio of lipid-assigned areas to total cell area (Fig. 3A, 3B, Supplementary Figs. 4, 5), and we observed lower total lipid content in MARC1 KO cells.
Based on the spectral characteristics there were three levels of saturations as shown by different colors superimposed on optical images of the cells (Fig. 3A); namely, saturated fatty acids (SFAs), monounsaturated fatty acids (MUFAs) and di-unsaturated fatty acids (DUFAs) (Fig. 3C). An area-based quantification of these lipid species (Fig. 3D) showed that in MARC1 KO cells there were lower levels of SFAs-MUFAs and MUFAs, with slightly increased level of DUFAs.
Next, we performed basis analysis (BA) including a spectral base with calibration curves for unsaturated and saturated cholesterol esters (CEs) (Supplementary Fig. 6). We generated fluorescence-like pseudo-color images of cells (Fig. 3E) and quantified the results (Fig. 3F), which showed lower saturated CEs content in MARC1 KO cells with no changes in unsaturated CEs compared to mock cells.

The fatty acid metabolism, tricarboxylic acid cycle (TCA), and oxidative phosphorylation pathways are upregulated after MARC1 downregulation

To gain insight into the intracellular pathways modified by MARC1 downregulation, we performed transcriptomic analyses of PHHs homozygous for the risk allele. Among 13,787 identified transcripts, 65 were significant at P<0.05 after adjusting for multiple testing. Among these, 19 genes were downregulated and 46 were upregulated. The top 30 differentially expressed genes (DEGs) are represented in Figure 4A, 4B. Furthermore, we performed pathway enrichment analysis of all the significant DEGs and found the result showed that ‘xenobiotic metabolism’ was downregulated, whereas ‘fatty acid metabolism’ was upregulated after MARC1 downregulation (Supplementary Fig. 7). To further confirm the results, we performed proteomic analyses (n=3) by using LC-MS3 in cells transfected with either scramble siRNA or MARC1 siRNA. Among the 3,900 proteins identified, 367 were differentially expressed (P-value<0.05). Among these, 185 proteins were lower and 182 proteins were higher. The top 30 differentially expressed proteins and MARC1 are plotted in a heatmap (Fig. 4C). Among these top 30 proteins, the genes for 5 of them (ALCAM, IL6ST, GOLGA4, STEAP3 and SCAMP1) were also differentially expressed in the same direction in the transcriptomic analyses (Fig. 4A). Notably, consistent with the transcriptomic results, we observed upregulation of the ‘fatty acid metabolism’ pathway after MARC1 downregulation, as found in pathway enrichment analysis (Supplementary Fig. 8). Additionally, ‘oxidative phosphorylation’, ‘ROS pathway’, and ‘TCA cycle pathway’ were upregulated after MARC1 downregulation. Upregulation of all these pathways is consistent with higher mitochondrial activity favouring fatty acid breakdown and activation of downstream metabolic pathways.
Collectively, our results from radioactive tracer studies, UKBB human genetics data, transcriptomics and proteomics in PHHs support the notion that MARC1 downregulation results in higher fatty acids utilization via elevated β-oxidation.

Ferroptosis suppressor proteins are upregulated after MARC1 downregulation

In our proteomic analyses, we observed that ‘heme metabolism’ and associated pathways were enriched in MARC1 downregulated cells (Supplementary Fig. 8). Ferroptosis has been shown to be an important pathway in MASLD susceptibility [27,28]. Therefore, we next performed a targeted analysis where we examined the status of ferroptosis (suppressor, regulator or driver of ferroptosis) by examining the 185 downregulated and 182 upregulated proteins. Notably, we found that only the ferroptosis suppressor proteins were upregulated in MARC1 downregulated cells (Fig. 4DE), whereas drivers of ferroptosis did not change.

MARC1 downregulation reduces reactive oxygen species levels

To gain insights into how MARC1 downregulation may be beneficial in reducing the risk of MASLD, we examined cellular stress responses in PHHs. MARC1 downregulation resulted in lower levels of ROS (Fig. 5A), suggesting an improvement in the cellular redox state.
Next, to test lipid peroxidation levels, we incubated PHHs with a polyunsaturated fatty acid (PUFA) mixture of 200 µM linoleic acid (LA) and 200 µM arachidonic acid (AA) for 48 hours. Due to their high degree of unsaturation, PUFAs are more susceptible to free radical attack, leading to lipid peroxidation. Incubating cells with PUFAs essentially creates a controlled environment rich in substrates prone to lipid peroxidation. We did not observe differences in lipid peroxidation levels as measured by 4-hydroxynonenal (4HNE) staining after MARC1 downregulation (Fig. 5B). Additionally, we did not observe any alterations in lipophagy, a cellular process responsible for the degradation of lipids. This was measured by changes in the protein levels of autophagy-related gene 7 (ATG7) by Western blotting, or in other markers as quantified by our proteomics analysis (Fig. 5C, 5D).

DISCUSSION

The main finding of this work is that the MARC1 rs2642438 minor allele encoding the p.T165 variant results in lower hepatocyte triglyceride content by increasing β-oxidation in PHHs. Moreover, the downregulation of MARC1 p.A165 results in a more favourable phenotype by reducing ferroptosis and ROS levels.
We started by examining PHHs from human donors homozygous for either the risk (p.A165) or the protective (p.T165) allele of MARC1, incubated with different fatty acid concentrations. Downregulation of MARC1 reduced neutral lipid content in hepatocytes homozygous for the wild-type (and risk) allele (p.A165) but not in those homozygous for the protective allele (p.T165). Moreover, when we compared protein levels between MARC1 p.A165 and p.T165, we observed ~50% reduction of MARC1 protein levels in hepatocytes with the protective (p.T165) allele. This is consistent with our previous observation that the MARC1 rs2642438 variant is a loss of function and that the protein levels are lower due to increased proteasomal degradation [12].
Intracellular triglyceride homeostasis in hepatocytes is governed by three fundamental pathways; namely, β-oxidation, de novo lipogenesis and lipoprotein-mediated lipid secretion. β-oxidation breaks down fatty acids to produce viable energy, whereas de novo lipogenesis is the process whereby new fatty acids are synthesized, usually in the presence of a positive caloric balance [29], and lipoprotein-mediated lipid secretion is used to secrete lipid species from the hepatocytes.
Previous studies have reported contradictory results regarding the means by which MARC1 affects hepatocyte lipid homeostasis. It has been shown that MARC1 p.A165 downregulation does not affect de novo lipogenesis or fatty acid oxidation in PHHs, despite a decrease in 3-HB, indicating decreased β-oxidation [15]. In contrast [16], overexpression of the protective, but not of the risk allele, of MARC1, resulted in a higher oxygen consumption rate in hepatoma cells, as measured by Seahorse assay, suggesting a gain of function of the protective mutant protein. However, MARC1 downregulation in primary human adipocytes resulted in an upregulation of CPT1A, a key β-oxidation enzyme [16], suggesting the variant is a loss of function.
Here, we demonstrate that MARC1 (p.A165) downregulation reduces intracellular lipid content by increasing fatty acid utilization via elevated β-oxidation in PHHs. We were able to show this outcome by using 3 different methodologies: a) radioactive tracers, b) transcriptomics, and c) proteomics. Moreover, we demonstrate that MARC1 ablation modifies the quality of lipid species, as observed by Raman spectroscopy in MARC1 KO HepG2 cells. Indeed, MARC1 ablation resulted in lower levels of saturated and monounsaturated fatty acids and lower levels of cholesterol esterified with saturated fatty acids. The relevance of these qualitative changes for liver disease remains to be determined.
Finally, to test the translatability of our findings in humans, we examined differences in plasma levels of 3-HB in participants of the UK Biobank stratified by MARC1 rs2642438. 3HB is synthesized primarily in hepatocytes as a by-product of β-oxidation and secreted into the bloodstream as a ketone body and therefore serves as a proxy for the activity of hepatocyte β-oxidation. Consistent with our data in PHHs in vitro, circulating 3-HB levels were higher in carriers of the rs2642438 minor allele compared to wild-type individuals, indicating higher β-oxidation activity in these people.
Among the intracellular pathways, lipophagy is a specialized form of autophagy where lipid droplets are specifically targeted for lysosomal degradation [30]. However, we observed no difference in the lipophagy markers after MARC1 downregulation.
Ferroptosis plays a pivotal role in the progression of liver disease [31]. While ferroptosis can target dysfunctional cells, excessive cell death mediated by ferroptosis can lead to inflammation and worsening of MASLD. We observed that the ferroptosis suppressor proteins were upregulated in MARC1 downregulated PHHs in our proteomic analysis. This strongly indicates that MARC1 downregulation leads to reduced ferroptosis in PHHs.
As MARC1 is located in the mitochondrial outer membrane [12,14,32,33], and mitochondrial dysfunction leads to elevated cellular ROS levels [34], we measured the overall levels of ROS after MARC1 downregulation in PHHs. Interestingly, even though MARC1 downregulation leads to higher fatty acid degradation through β-oxidation, the ROS levels in the PHHs were reduced.
Under physiological conditions, ROS are produced during the β-oxidation process, especially in the case of incomplete shuttling of electrons in the electron transfer chain (ETC) [34,35]. However, in the presence of either an efficient mitochondrial antioxidant pathway or efficient ETC, cellular ROS levels are reduced [34,36]. Overall, the reduction in ROS is compatible with the beneficial effect of the MARC1 variant against MASLD. We should note that measurement of the oxygen consumption rate could have strengthened our omics-based findings that downstream pathways of β-oxidation and mitochondrial activity were upregulated after MARC1 downregulation. This remains a limitation of this study. However, our results are consistent with two other studies on MARC1 in different models that, showed increased levels of antioxidant pathways after MARC1 downregulation [16,37], although, we did not observe any change in the lipid-peroxidation level after MARC1 downregulation, as quantified by 4-HNE immunofluorescence in PHHs.
In conclusion, our results demonstrate that MARC1 inhibition in carriers of the risk protein results in lower hepatocyte lipids due to higher β-oxidation. Moreover, MARC1 downregulation upregulates beneficial pathways involved in cell survival. These data suggest that downregulation of MARC1 may be a potential strategy to reduce liver steatosis in humans.

FOOTNOTES

Authors’ contribution
EC and TD contributed to study design, data collection, data analysis, data interpretation and manuscript drafting. KS, LK were involved in data interpretation and manuscript drafting; FRN, AM, GP and MH were involved in data collection and visualization; SM, BS, LT, PC were involved in data collection, visualization, and methodology. OJ was involved in data interpretation, methodology, and manuscript drafting. SP, AP were involved in supervision. DL contributed to supervision, data interpretation, methodology and manuscript drafting. RMM contributed to study design, supervision, data interpretations, methodology, discussion and wrote the manuscript. SR led this study with conceptualization, funding acquisition, supervision, data interpretations, methodology and wrote the manuscript. All the authors red and approved the final version for publication.
Acknowledgements
The authors thank the staff and participants of the UKBB. This research has been conducted using the UK Biobank resource. Proteomic analysis was performed at the Proteomics Core Facility, Sahlgrenska academy, Gothenburg University, with financial support from SciLifeLab and BioMS. Annika Thorsell is specially acknowledged for her contributions in the proteomic experiments and writing the corresponding methods.
Funding: S.R. was supported by the Swedish Cancerfonden (22 2270 Pj), the Swedish Research Council (Vetenskapsradet (VR), 2023-02079), the Swedish state under the Agreement between the Swedish government and the county councils (the ALF agreement, ALFGBG-965360), the Swedish Heart Lung Foundation (20220334), the Novonordisk Distinguished Investigator Grant - Endocrinology and Metabolism (NNF23OC0082114), the Novonordisk Project grants in Endocrinology and Metabolism (NNF24OC0091535) and AstraZeneca Agreement for Research.
Conflicts of Interest
S.R. has been consulting for AstraZeneca, GSK, Celgene Corporation, Ribo-cure AB and Pfizer in the last 5 years and received the research grant from AstraZeneca. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results. D.L. and M.H. are AstraZeneca employees and hold shares in AstraZeneca. All other authors have none to declare.

SUPPLEMENTAL MATERIAL

Supplementary material is available at Clinical and Molecular Hepatology website (http://www.e-cmh.org).
Supplementary Materials and Methods.
cmh-2024-0642-Supplementary-Materials-Method.pdf
Supplementary Table 1.
Details of primary human hepatocytes donors used
cmh-2024-0642-Supplementary-Table-1.pdf
Supplementary Figure 1.
MARC1 downregulation decreases the intracellular fat content. Human hepatoma cell lines (HepG2, HuH7 and Hep3B2) and terminally differentiated hepatic cells (HepaRG) were seeded in 24-well plates (3×104 cells/well) and transfected after 24 hours with siSCR or siMARC1. Forty-eight hours after transfection, cells were subjected to ORO staining (red) and DAPI (blue) to stain nuclei. Pictures were obtained using Nikon ECLIPSE Ni-E microscope at 40X magnification with software NIS-Element 5.30.04 (Nikon Instruments Inc., Melville, NY, USA) and analyzed using an in-house macro in ImageJ (v.1.52h, NIH). Neutral lipid content was normalized to the number of nuclei. Data shown as average of 6–9 independent experiments (±standard deviation), with the total ORO area divided by the number of nuclei in the field. Each experiment on average had 12 image acquisitions, and the data are shown as pooled from independent experiments. The P-value was calculated by Mann–Whitney nonparametric test. MARC1 downregulation efficiency in the respective experiments is shown by real-time qPCR results. MARC1, mitochondrial amidoxime-reducing component 1; siSCR, scramble siRNA; siMARC1, MARC1 siRNA; ORO, Oil-Red-O.
cmh-2024-0642-Supplementary-Figure-1.pdf
Supplementary Figure 2.
MARC1 downregulation increases β-oxidation but does not affect de novo lipogenesis and triglyceride-rich lipoprotein secretion in PHH. (A) PHH from a donor homozygous for MARC1 p.A165 risk allele was (200,000 cells/well in 24-well plates) transfected with siSCR or siMARC1 and stained for ORO. The ORO area in the pictures was quantified using ImageJ. Objective: 40X, DAPI: blue, ORO: red. Scale bar=100 µm. Data are shown as average and±standard deviation of 9 images. The P-value for ORO quantification was calculated by Mann-Whitney non-parametric analysis. (B) β-oxidation was assessed in the media collected from cells after MARC1 downregulation and 2 hours incubation with 8.3 μCi/mL [3H] palmitate and 110 µM palmitate. Data were normalized for number of cells (n=6). (C) Newly synthesized triglycerides were isolated from hepatocytes, separated by one-dimensional TLC and quantified by liquid scintillation counter after MARC1 downregulation and 5 hours incubation with 6 μCi/mL [3H] glycerol and 1.5 mM glycerol (n=6). (D) MARC1 mRNA level was measured by qPCR. (E, F) Triglyceride-rich lipoproteins were isolated from media by ultracentrifugation. Levels of the ApoB100 protein were measured by western blotting (n=4). (G) TG levels in media were assessed by mass spectrometry (n=3). (H) Triglyceride level, normalized by mean ApoB100 protein, as measured by Western blotting. The P-value was calculated by Mann-Whitney non-parametric analysis. DPM/no. of cells, Disintegrations per min/number of cells; RU, relative unit; AU, arbitrary unit; R1-R4, experimental replicates. MARC1, mitochondrial amidoxime-reducing component 1; PHH, primary human hepatocytes; siSCR, scramble siRNA; siMARC1, MARC1 siRNA; TG, triglycerides.
cmh-2024-0642-Supplementary-Figure-2.pdf
Supplementary Figure 3.
MARC1 downregulation does not show changes in β-oxidation, DNL and triglyceride-rich lipoprotein secretion in PHH homozygous for protective allele. PHH from donor homozygous for MARC1 protective were seeded, transfected with siSCR or siMARC1. (A) β-oxidation was assessed in the media collected from cells after MARC1 downregulation and 2 hours incubation with 8.3 μCi/mL [3H] palmitate and 0.11 mM palmitate (n=6). Data were normalized for number of cells. (B) Newly synthesized triglycerides were isolated from hepatocytes, separated by one-dimensional TLC and quantified by liquid scintillation counter after MARC1 downregulation and 5 hours incubation with 6 μCi/mL [3H] glycerol and 1.5 mM glycerol (n=6). (C) MARC1 RNA level was measured by qPCR. Triglyceride-rich lipoproteins were isolated from media by ultracentrifugation. (D, E) Levels of the ApoB100 protein were measured by western blotting. (E) TG levels were assessed by MS. (G) Triglyceride level, normalized by ApoB100 protein, as measured by Western blotting. The P-value was calculated by Mann-Whitney non-parametric analysis. DPM/no. of cells, disintegrations per min/number of cells; RU, relative unit; AU, arbitrary unit; R1-R3, experimental replicates. MARC1, mitochondrial amidoxime-reducing component 1; PHH, primary human hepatocytes; siSCR, scramble siRNA; siMARC1, MARC1 siRNA; TG, triglycerides; TLC, thin-layer chromatography.
cmh-2024-0642-Supplementary-Figure-3.pdf
Supplementary Figure 4.
Multivariate analysis applied to Raman datasets of MOCK and MARC1 KO cell lines. A combination of PCA and KCA was performed on cell lines to identify the common spectral features of cells of the same line. According to cluster average spectra, different subcellular components were identified for MOCK (top panel) and MARC1 KO (bottom panel) cells. The same color labels were used for both cell lines, where blue and cyan indicate nuclear and perinuclear regions, lime indicates mitochondria and Cytochrome C rich regions, green indicates cytosol and outer membrane. All the reddish colors (red, magenta and purple) were used for lipid areas with different compositions. MARC1, mitochondrial amidoxime-reducing component 1; KO, knockout; KCA, K-means clustering analysis.
cmh-2024-0642-Supplementary-Figure-4.pdf
Supplementary Figure 5.
KCA study of lipid unsaturation. KCA was performed on a full lipid dataset to assess different unsaturation clusters. According to cluster average spectra (bottom panel), three major classes were identified: a mixture of SFAs-MUFAs (red), MUFAs (purple) and DUFAs (blue). The areas corresponding to these three classes are overlaid with optical pictures of MOCK (top panel) and MARC1 KO (middle panel) cells. MARC1, mitochondrial amidoxime-reducing component 1; KCA, K-means clustering analysis; SFA, saturated; MUFA, monounsaturated; DUFA, di-unsaturated; KO, knockout.
cmh-2024-0642-Supplementary-Figure-5.pdf
Supplementary Figure 6.
BA study of CEs of saturated and unsaturated FAs. BA was performed using a common basis of spectra made of nuclear, cytosol and lipid curves, along with two curves (bottom panel) for CEs of saturated (red) and unsaturated (green) FAs. BA resulted in pseudo-color images for MOCK (top panel) and MARC1 KO (middle panel) cells, where blue was used for nuclei, gray for cytosol, yellow for lipids and obviously red for CEs of saturated FAs and green for CEs of unsaturated FAs. BA, basis analysis; CE,cholesterol ester; FA, fatty acid; MARC1, mitochondrial amidoxime-reducing component 1; KO, knockout.
cmh-2024-0642-Supplementary-Figure-6.pdf
Supplementary Figure 7.
Transcriptomics: pathway enrichment analysis of 19 downregulated genes including MARC1, and 46 upregulated genes using EnrichR. MARC1, mitochondrial amidoxime-reducing component 1.
cmh-2024-0642-Supplementary-Figure-7.pdf
Supplementary Figure 8.
Proteomics: pathway enrichment analysis of 185 downregulated proteins including MARC1, and 182 upregulated proteins using EnrichR. MARC1, mitochondrial amidoxime-reducing component 1.
cmh-2024-0642-Supplementary-Figure-8.pdf

Figure 1.
MARC1 p.A165 risk allele downregulation decreases the intracellular fat content in human primary hepatocytes (PHHs). PHHs from donor homozygous for MARC1 rs2642438 p.A165 risk (A) or p.T165 protective (B) allele were seeded (100,000 live cells/well in 8 chamber slides), transfected with siSCR or siMARC1. The cells were incubated with or without increasing concentration of FA mixture (palmitic acid+oleic acid in 1:1 ratio; conjugated in 1% [w/v] BSA in HI media; 0 µM; 30 µM FA or 300 µM FA concentration). Forty-eight hours post-transfection, cells were fixed in 4% PFA and stained with ORO staining. The ORO area in the pictures was quantified using ImageJ. Objective: 40X, DAPI: Blue, ORO: red. Scale bar=100 µm. Data are shown as mean±standard deviation of on average 12 images from 4 experimental replicates. The P-value for ORO quantification was calculated by Mann-Whitney non-parametric test. MARC1 mRNA level was measured by real-time qPCR (C). Western blot of PHH homozygous for the risk (p.A165) or protective (p.T165) protein. Cell lysates were run in 12% SDS-PAGE, blotted against MARC1 and CNX, and quantified using ImageLab software (D). Data are shown after normalization with CNX. Statistical test for Western blot was performed using unpaired Student’s t-test. RU, relative unit; R1-R3, experimental replicates; FA, fatty acid mixture of palmitic acid and oleic acid in same proportion (1:1); CNX, calnexin; MARC1,mitochondrial amidoxime-reducing component 1; ORO, Oil-Red-O; PHH, primary human hepatocytes; siSCR, scramble siRNA; siMARC1, MARC1 siRNA.

cmh-2024-0642f1.jpg
Figure 2.
MARC1 p.A165 risk allele downregulation increases β-oxidation. PHHs from donor homozygous for the MARC1 rs2642438 risk allele (p.A165) were transfected with siSCR or siMARC1. β-oxidation was assessed in the media collected from cells without or with MARC1 downregulation after 2 hours incubation with 8.3 μCi/mL [3H] palmitate and 110 µM palmitate (A). Triglyceride-rich lipoproteins were isolated from media by ultracentrifugation. Levels of the ApoB100 protein were measured by western blotting; triglycerides levels in media were assessed by MS and normalized to ApoB100 protein level (B). Data are shown as mean±standard deviation of 3 experiments. Newly synthesized triglycerides were isolated from hepatocytes, separated by one-dimensional thin layer chromatography and quantified by liquid scintillation counter without or with MARC1 downregulation after 5 hours incubation with 6 μCi/mL [3H] glycerol and 1.5 mM glycerol (C). PHH with either risk allele (p.A165) or protective allele (p.T165) were incubated with 300 µM fatty acid (oleic acid and palmitic acid 1:1 ratio) and transfected with siRNA either for scramble (siSCR) or MARC1 (siMARC1) for 48 hours, and then assessed for: β-oxidation in the media collected from PHH after incubation with 8.3 μCi/mL [3H] palmitate and 110 µM palmitate for 2 hours (D); ApoB100 levels from triglyceride-rich lipoproteins measured by Western blot, triglyceride measured by MS and normalized to ApoB100 protein levels either for the PHH with risk allele (p.A165) or protective allele (p.T165) (E). Plasma 3-hydroxybutyrate level from the UKBB was stratified based on the rs2642438 genotype in total n=239,075 individuals and adjusted for body mass index and additional clinical conditions (F). Data for radiolabeled experiments (β-oxidation and de novo triglyceride synthesis) were normalized for number of cells. The P-value was calculated by Mann-Whitney non-parametric analysis. DPM/n cells, disintegrations per min/number of cells; RU, relative unit; AU, arbitrary unit; R1-R3 (experimental replicates); CI, confidence interval; FA, fatty acid; TG, triglyceride; TAG, triacylglycerol; siSCR, scramble siRNA; siMARC1, MARC1 siRNA; PHH, primary human hepatocytes; NA, no additional clinical condition; PRS-HFC, polygenic risk score for high fat content in liver; LDL-C, low density lipoproteins containing cholesterol; HTN, hypertension; CLD, chronic liver disease; CVD, cardiovascular disease; Joint, adjusted for all the conditions mentioned above.

cmh-2024-0642f2.jpg
Figure 3.
MARC1 p.A165 knockout affects intracellular lipid composition. Lipid species with different degree of unsaturation overlaid on optical images of three representative cells per line (A); red denotes overlapping SFAs and MUFAs, purple denotes MUFAs dominated regions, and blue denotes DUFAs regions. Overall lipid content of MOCK and MARC1 KO cells, measured as the ratio of the total lipid area over the cell area (B). Calibration chart calculated as a Voronoi diagram from spectral data measured on pure FAs with different unsaturation degrees (black dots in the chart), considering Raman intensity ratio between peaks at 1,265 and 1,300 cm-1 (horizontal axis), upshift of the t(CH2) vibration peak at about 1,298 cm-1 (vertical axis), and unsaturation ratio NC=C /NCH2 of pure FAs (color intensity) (C); the same parameters of horizontal and vertical axes are also calculated for the three lipid clusters (colored triangles), whose positions in the chart identify their unsaturation ratio. Quantification of the different FAs composition, calculated as the ratio between the area of a single type of FA (SFA-MUFA, MUFA or DUFA) over the whole area per cell (D). Basis Analysis of the cellular full datasets, using a basis composed of spectra of nucleus (blue), cytosol (gray), lipids (yellow) added with spectra for CEs of saturated (red) and unsaturated (green) FAs (E). Expression of CEs of saturated (red) and unsaturated (green) FAs computed from panel (E) as ratio of red (green) areas over the whole cell area (F). Data are shown as mean±standard deviation. The P-values were calculated by Mann-Whitney non-parametric test. MARC1, mitochondrial amidoxime-reducing component 1; SFA, saturated fatty acids; MUFA, monounsaturated fatty acid; DUFA, di-unsaturated fatty acid; KO, knockout; FA, fatty acid; CE,cholesterol ester.

cmh-2024-0642f3.jpg
Figure 4.
Proteins suppressing ferroptosis are upregulated after MARC1 p.A165 risk allele downregulation. Transcriptomic and proteomic analyses of five/three technical replicates of PHH homozygous for the MARC1 risk allele transfected with SCR siRNA or MARC1 siRNA. Top 30 differentially expressed genes after MARC1 downregulation as quantified by RNA-seq analysis of PHHs (A). Red colour in the name of the genes marks consistent result with proteomics. Volcano plot of RNA-seq data, depicting significant genes; cut off used for log2 fold change 0.5 (B). Top 30 differential protein levels after MARC1 downregulation in PHHs, as detected by LC-MS (C). Colour intensity is plotted as the fold change value from average raw protein abundance. Red colour in the name of the proteins signifies consistent result with transcriptomic data. Proteins involved in ferroptosis were overrepresented as detected in LC-MS data (D). Using FerrDB database’s overrepresentation analysis, a list of proteins for each driver, regulator or suppressor of ferroptosis was obtained and the heatmap of the proteins is plotted. Odds ratio of ferroptosis related proteins after MARC1 downregulation (E). MARC1, mitochondrial amidoxime-reducing component 1; PHH,primary human hepatocytes; siRNA, short interfering RNA.

cmh-2024-0642f4.jpg
Figure 5.
MARC1 p.A165 risk allele downregulation reduces ROS levels. Overall ROS production level in PHHs homozygous for the MARC1 risk allele (40,000 cells/well in a 96-well plate), transfected with either SCR siRNA or MARC1 siRNA (A). Forty-eight hours posttransfection, medium was replaced with 20 µM DCFDA solution for 45 minutes. Fluorescence intensity was measured on fluorescence plate reader (SpectraMax i3) at Ex/Em 485/535 nm. Lipid peroxidation level as measured by 4HNE, a lipid peroxidation marker, immunofluorescence quantification in PHH homozygous for the risk allele with or without MARC1 downregulation (B). 200,000 PHHs/well in a 24well plate were seeded and transfected with scramble or MARC1 siRNA for 48 hours. The cells were incubated with a polyunsaturated fatty acid mixture (200 µM linoleic acid and 200 µM arachidonic acid, conjugated with 1% BSA) for 48 hours. 4HNE area was quantified by ImageJ. Objective: 20X, DAPI: Blue, 4HNE: Green. Scale bar=100 µm. Data are shown as mean±SD of 4 technical replicates, each with 12 images. The P-value for 4HNE quantification was calculated by Mann-Whitney non-parametric test. Levels of the ATG7 protein measured by Western blotting and its quantification in cell lysates of PHH homozygous for the risk allele without or with MARC1 downregulation (C). CNX was used as loading control. Data were normalized to CNX and expressed as mean±SD. Heatmap of the proteins related to lipophagy and detected in the proteomics data (D). Data is shown in fold change value. MARC1, mitochondrial amidoxime-reducing component 1; ROS, reactive oxygen species; siRNA, short interfering RNA; 4HNE, 4-hydroxynonenal; SD, standard deviation; ATG7, autophagy-related gene 7; CNX, calnexin.

cmh-2024-0642f5.jpg

cmh-2024-0642f6.jpg

Abbreviations

AA
arachidonic acid
ATG7
autophagy-related gene 7
BA
basis analysis
CE
cholesterol ester
DEG
differentially expressed gene
ETC
electron transfer chain
FDR
false discovery rate
GWAS
genome-wide association study
KBr
potassium bromide
KO
knockout
LA
linoleic acid
LD
lipid droplet
MARC1
mitochondrial amidoxime-reducing component 1
MASH
metabolic dysfunction-associated steatohepatitis
MASLD
metabolic dysfunction-associated steatotic liver disease
NAFLD
non-alcoholic fatty liver disease
OCR
oxygen consumption rate
ORO
Oil-Red-O
PHH
primary human hepatocytes
PUFA
polyunsaturated fatty acid
ROS
reactive oxygen species
siRNA
short interfering RNA
TCA
tricarboxylic acid cycle
TRL
TG-rich-lipoproteins
3HB
3-hydroxybutyrate
4HNE
4-hydroxynonenal

REFERENCES

1. Valenti L, Aghemo A, Forner A, Petta S, Romeo S, Nahon P. Measuring the impact of the updated Steatotic liver disease nomenclature and definition. Liver Int 2023;43:2340-2342.
crossref pmid
2. Younossi ZM, Golabi P, Paik JM, Henry A, Van Dongen C, Henry L. The global epidemiology of nonalcoholic fatty liver disease (NAFLD) and nonalcoholic steatohepatitis (NASH): a systematic review. Hepatology 2023;77:1335-1347.
crossref pmid pmc
3. Rinella ME, Lazarus JV, Ratziu V, Francque SM, Sanyal AJ, Kanwal F, et al. A multisociety Delphi consensus statement on new fatty liver disease nomenclature. Hepatology 2023;78:1966-1986.
pmid
4. Huang DQ, El-Serag HB, Loomba R. Global epidemiology of NAFLD-related HCC: trends, predictions, risk factors and prevention. Nat Rev Gastroenterol Hepatol 2021;18:223-238.
crossref pmid pmc pdf
5. Mingrone G, Panunzi S, De Gaetano A, Guidone C, Iaconelli A, Capristo E, et al. Metabolic surgery versus conventional medical therapy in patients with type 2 diabetes: 10-year follow-up of an open-label, single-centre, randomised controlled trial. Lancet 2021;397:293-304.
crossref pmid
6. Harrison SA, Bedossa P, Guy CD, Schattenberg JM, Loomba R, Taub R, et al. A phase 3, randomized, controlled trial of resmetirom in NASH with liver fibrosis. N Engl J Med 2024;390:497-509.
pmid
7. Mancina RM, Dongiovanni P, Petta S, Pingitore P, Meroni M, Rametta R, et al. The MBOAT7-TMC4 variant rs641738 increases risk of nonalcoholic fatty liver disease in individuals of European descent. Gastroenterology 2016;150:1219-1230 e6.
crossref pmid pmc
8. Speliotes EK, Yerges-Armstrong LM, Wu J, Hernaez R, Kim LJ, Palmer CD, et al. Genome-wide association analysis identifies variants associated with nonalcoholic fatty liver disease that have distinct effects on metabolic traits. PLoS Genet 2011;7:e1001324.
crossref pmid pmc
9. Kozlitina J, Smagris E, Stender S, Nordestgaard BG, Zhou HH, Tybjaerg-Hansen A, et al. Exome-wide association study identifies a TM6SF2 variant that confers susceptibility to nonalcoholic fatty liver disease. Nat Genet 2014;46:352-356.
crossref pmid pmc pdf
10. Emdin CA, Haas ME, Khera AV, Aragam K, Chaffin M, Klarin D, et al. A missense variant in Mitochondrial Amidoxime Reducing Component 1 gene and protection against liver disease. PLoS Genet 2020;16:e1008629.
crossref pmid pmc
11. Innes H, Buch S, Hutchinson S, Guha IN, Morling JR, Barnes E, et al. Genome-wide association study for alcohol-related cirrhosis identifies risk loci in MARC1 and HNRNPUL1. Gastroenterology 2020;159:1276-1289.e7.
crossref pmid
12. Dutta T, Sasidharan K, Ciociola E, Pennisi G, Noto FR, Kovooru L, et al. Mitochondrial amidoxime‐reducing component 1 p. Ala165Thr increases protein degradation mediated by the proteasome. Liver Int 2024;44:2091-2092.
pmid pmc
13. Hou W, Watson C, Cecconie T, Bolaki MN, Brady JJ, Lu Q, et al. Biochemical and functional characterization of the p. A165T missense variant of mitochondrial amidoxime-reducing component 1. J Biol Chem 2024;300:107353.
crossref pmid pmc
14. Wu M, Tie M, Hu L, Yang Y, Chen Y, Ferguson D, et al. Fatty liver disease protective MTARC1 p. A165T variant reduces the protein stability of MTARC1. Biochem Biophys Res Commun 2024;702:149655.
crossref pmid pmc
15. Lewis LC, Chen L, Hameed LS, Kitchen RR, Maroteau C, Nagarajan SR, et al. Hepatocyte mARC1 promotes fatty liver disease. JHEP Rep 2023;5:100693.
crossref pmid pmc
16. Jones AK, Bajrami B, Campbell MK, Erzurumluoglu AM, Guo Q, Chen H, et al. mARC1 in MASLD: Modulation of lipid accumulation in human hepatocytes and adipocytes. Hepatol Commun 2024;8:e0365.
crossref pmid pmc
17. Perez-Riverol Y, Bai J, Bandla C, Garcia-Seisdedos D, Hewapathirana S, Kamatchinathan S, et al. The PRIDE database resources in 2022: a hub for mass spectrometry-based proteomics evidences. Nucleic Acids Res 2022;50:D543-D552.
crossref pmid pmc pdf
18. Zhou N, Yuan X, Du Q, Zhang Z, Shi X, Bao J, et al. FerrDb V2: update of the manually curated database of ferroptosis regulators and ferroptosis-disease associations. Nucleic Acids Res 2023;51:D571-D582.
crossref pmid pmc pdf
19. Mancina RM, Sasidharan K, Lindblom A, Wei Y, Ciociola E, Jamialahmadi O, et al. PSD3 downregulation confers protection against fatty liver disease. Nat Metab 2022;4:60-75.
crossref pmid pmc pdf
20. Hansson PK, Asztély AK, Clapham JC, Schreyer SA. Glucose and fatty acid metabolism in McA-RH7777 hepatoma cells vs. rat primary hepatocytes: responsiveness to nutrient availability. Biochim Biophys Acta 2004;1684:54-62.
crossref pmid
21. Mbatchou J, Barnard L, Backman J, Marcketta A, Kosmicki JA, Ziyatdinov A, et al. Computationally efficient whole-genome regression for quantitative and binary traits. Nat Genet 2021;53:1097-1103.
crossref pmid pdf
22. Jamialahmadi O, Mancina RM, Ciociola E, Tavaglione F, Luukkonen PK, Baselli G, et al. Exome-wide association study on alanine aminotransferase identifies sequence variants in the GPAM and APOE associated with fatty liver disease. Gastroenterology 2021;160:1634-1646.e7.
crossref pmid
23. Li K, Wang WH, Wu JB, Xiao WH. β-hydroxybutyrate: A crucial therapeutic target for diverse liver diseases. Biomed Pharmacother 2023;165:115191.
crossref pmid
24. Feng S, Wang H, Liu J, Aa J, Zhou F, Wang G. Multi-dimensional roles of ketone bodies in cancer biology: Opportunities for cancer therapy. Pharmacol Res 2019;150:104500.
crossref pmid
25. Pagliari F, Sogne E, Panella D, Perozziello G, Liberale C, Das G, et al. Correlative raman-electron-light (CREL) microscopy analysis of lipid droplets in melanoma cancer stem cells. Biosensors (Basel) 2022;12:1102.
crossref pmid pmc
26. Christoph K, Thomas K, Richard HWF, Reiner S. Identification of organelles and vesicles in single cells by Raman microspectroscopic mapping. Vibrational Spectroscopy 2005;38:85-93.
crossref
27. Peleman C, Hellemans S, Veeckmans G, Arras W, Zheng H, Koeken I, et al. Ferroptosis is a targetable detrimental factor in metabolic dysfunction-associated steatotic liver disease. Cell Death Differ 2024;31:1113-1126.
crossref pmid pmc pdf
28. Peleman C, Francque S, Berghe TV. Emerging role of ferroptosis in metabolic dysfunction-associated steatotic liver disease: revisiting hepatic lipid peroxidation. EBioMedicine 2024;102:105088.
crossref pmid pmc
29. Sanders FW, Griffin JL. De novo lipogenesis in the liver in health and disease: more than just a shunting yard for glucose. Biol Rev Camb Philos Soc 2016;91:452-468.
crossref pmid pmc pdf
30. Zhang S, Peng X, Yang S, Li X, Huang M, Wei S, et al. The regulation, function, and role of lipophagy, a form of selective autophagy, in metabolic disorders. Cell Death Dis 2022;13:132.
crossref pmid pmc pdf
31. Chen J, Li X, Ge C, Min J, Wang F. The multifaceted role of ferroptosis in liver disease. Cell Death Differ 2022;29:467-480.
crossref pmid pmc pdf
32. Struwe MA, Clement B, Scheidig A. The clinically relevant MTARC1 p. Ala165Thr variant impacts neither the fold nor active site architecture of the human mARC1 protein. Hepatol Commun 2022;6:3277-3278.
crossref pmid pmc pdf
33. Mukhopadhyay B, Marietta C, Shen PH, Oiseni A, Mirshahi F, Mazzu M, et al. A patient-based iPSC-derived hepatocyte model of alcohol-associated cirrhosis reveals bioenergetic insights into disease pathogenesis. Nat Commun 2024;15:2869.
crossref pmid pmc pdf
34. Karkucinska-Wieckowska A, Simoes ICM, Kalinowski P, Lebiedzinska-Arciszewska M, Zieniewicz K, Milkiewicz P, et al. Mitochondria, oxidative stress and nonalcoholic fatty liver disease: A complex relationship. Eur J Clin Invest 2022;52:e13622.
pmid
35. Lockman KA, Baren JP, Pemberton CJ, Baghdadi H, Burgess KE, Plevris-Papaioannou N, et al. Oxidative stress rather than triglyceride accumulation is a determinant of mitochondrial dysfunction in in vitro models of hepatic cellular steatosis. Liver Int 2012;32:1079-1092.
crossref pmid
36. Kumar A, Sharma A, Duseja A, Das A, Dhiman RK, Chawla YK, et al. Patients with nonalcoholic fatty liver disease (NAFLD) have higher oxidative stress in comparison to chronic viral hepatitis. J Clin Exp Hepatol 2013;3:12-18.
crossref pmid pmc
37. Janik MK, Smyk W, Kruk B, Szczepankiewicz B, Gornicka B, Lebiedzinska-Arciszewska M, et al. MARC1 p.A165T variant is associated with decreased markers of liver injury and enhanced antioxidant capacity in autoimmune hepatitis. Sci Rep 2021;11:24407.
crossref pmid pmc pdf

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