Evidence supports an important link between mitochondrial DNA (mtDNA) variation and adverse drug reactions such as idiosyncratic drug-induced liver injury (iDILI). Here, we describe the generation of HepG2-derived transmitochondrial cybrids, to investigate the impact of mtDNA variation on mitochondrial (dys)function and susceptibility to iDILI. This study created 10 cybrid cell lines, each containing distinct mitochondrial genotypes of haplogroup H or haplogroup J backgrounds.HepG2 cells were depleted of mtDNA to make rho zero cells, before the introduction of known mitochondrial genotypes using platelets from healthy volunteers (n=10), thus generating 10 transmitochondrial cybrid cell lines. The mitochondrial function of each was assessed at basal state and following treatment with compounds associated with iDILI; flutamide, 2-hydroxyflutamide, and tolcapone, and their less toxic counterparts bicalutamide and entacapone utilizing ATP assays and extracellular flux analysis.Whilst only slight variations in basal mitochondrial function were observed between haplogroups H and J, haplogroup-specific responses were observed to the mitotoxic drugs. Haplogroup J showed increased susceptibility to inhibition by flutamide, 2-hydroxyflutamide, and tolcapone, via effects on selected mitochondrial complexes (I and II), and an uncoupling of the respiratory chain.This study demonstrates that HepG2 transmitochondrial cybrids can be created to contain the mitochondrial genotype of any individual of interest. This provides a practical and reproducible system to investigate the cellular consequences of variation in the mitochondrial genome, against a constant nuclear background. Additionally, the results show that inter-individual variation in mitochondrial haplogroup may be a factor in determining sensitivity to mitochondrial toxicants.This work was supported by the Centre for Drug Safety Science supported by the Medical Research Council, United Kingdom (Grant Number G0700654); and GlaxoSmithKline as part of an MRC-CASE studentship (grant number MR/L006758/1). Drug-induced liver injury (DILI) is a leading cause of acute liver failure in the western world . AlthougDrug-induced mitochondrial dysfunction is one of the mechanisms implicated in the onset of DILI. This is supported by the fact that 50% of drugs with a black box warning for hepatotoxicity also contain a mitochondrial liability, with many associated specifically with iDILI . It is hDespite limitations regarding physiological relevance, HepG2 cells remain valuable as one of the most commonly used preclinical cell lines for the in vitro assessment of DILI . One of Here, we describe the generation and testing of transmitochondrial cybrids (herein referred to as cybrids) as a reproducible in vitro model of personalized mtDNA variation. Cybrids are typically produced by the fusion of enucleated cells (cytoplasts) or anucleate cells (e.g. platelets) with cells that have been depleted of their mtDNA (rho zero [ρ0] cells) . When cyThis study aimed to generate a panel of HepG2 transmitochondrial cybrids, and utilize them in a proof of principle study, to investigate the effect of mtDNA variants upon mitochondrial function and susceptibility to drug-induced mitochondrial dysfunction. Despite the acknowledged limitations of the HepG2 model, they remain an important mainstay of pharmaceutical preclinical testing for hepatotoxicity . TherefoThe effects of mtDNA variation on drug-induced mitochondrial dysfunction were assessed by the treatment of cybrids with a panel of compounds with a known clinical association with DILI and proven mitochondrial liabilities; flutamide, 2-hydroxyflutamide, and tolcapone. The non-hepatotoxic structural counterparts bicalutamide and entacapone were also investigated for comparison. Flutamide, a non-steroidal antiandrogen for the treatment of prostate cancer, has a boxed warning for hepatotoxicity and is a known inhibitor of mitochondrial complex I . 2-hydroGenerating a panel of personalized transmitochondrial cybrids offers a novel and unique in vitro model for idiosyncratic hepatotoxicity, allowing us to begin to map the functional effects of mitochondrial genotype. See max of the compounds  (No significant differences in oxidative phosphorylation parameters were observed between haplogroup H and J cybrids . This ma 3.9 µM) . HoweverIndividual complex-driven maximal respiration, herein referred to as complex activity, was measured in permeabilized cells . ComplexFlutamide was selected as a paradigm hepatotoxin that induces mitochondrial dysfunction via inhibition of the electron transport chain. Previous work has demonstrated that conditions of an acute metabolic switch, i.e., galactose-media, are required to circumvent the Crabtree effect and reveal the mitochondrial dysfunction induced by flutamide . TherefoXF respirometric analysis  revealed2-hydroxyflutamide is the major circulating form of flutamide when it is administered clinically. When cybrids were treated with ≥33 M 2-hydroxyflutamide a substantial, concentration-dependent decrease in ATP level was evident. However, there was no significant difference in responses between haplogroup H and J cybrids .XF respirometric analysis  revealedTo further understand the cause of such differences in bioenergetic parameters, the effect of flutamide (complex I inhibitor) and 2-hydroxyflutamide (complex I and II inhibitors) on complex activity was measured across the cybrid cell lines . When trIn line with the known mechanism, 2-hydroxyflutamide decreased the activity of complexes I and II in both haplogroups . HaplogrAlthough haplogroup J cybrids consistently showed higher complex I and II activity at basal  and remaTolcapone is a hepatotoxin that induces mitochondrial dysfunction via uncoupling of the electron transport chain. In the galactose test system, tolcapone induced a greater effect in haplogroup J than in haplogroup H cybrids. Specifically, cellular ATP levels were significantly lower in haplogroup J cybrids following treatment with tolcapone  . These eThe pattern of changes to the parameters of oxidative phosphorylation that were induced by tolcapone is characteristic of its role as an uncoupler . SpecifiThe results from this study offer important insights into the potential mechanisms underlying the onset of iDILI in certain individuals. In the case of tolcapone, four cases of liver failure among 100,000 individuals taking the drug, led to a black box warning and a switch to entacapone an alternative in-class compound. However, as entacapone has been reported to be less efficacious than tolcapone, the ability to make the drug selection based on the personalized risk of iDILI, would be of great value .Cells were exposed to bicalutamide and entacapone as the non-hepatotoxic structural counterparts of flutamide and tolcapone, respectively to investigate whether haplogroup-specific differences are still evident. In line with previous work , resultsEntacapone induced a weaker decline in ATP levels compared to tolcapone, with a 50% decrease not reached at the highest concentrations tested , reflectResearch has begun to understand the role that mitochondrial DNA plays in defining an individual’s susceptibility to adverse drug reactions . HoweverThis research provides new evidence for the role of mitochondrial genotype in the onset of idiosyncratic ADRs. It has shown that haplogroup J cybrids display an increased susceptibility to tolcapone-induced decrease in ATP and to mitochondrial dysfunction induced by 2-hydroxyflutamide, which supports previous findings on the increased sensitivity of haplogroup J to mitotoxicants . ImportaIn conclusion, this study has established a novel, in vitro model that provides a preclinical representation of the interindividual variation underpinning iDILI, thereby offering much greater translatability to clinical scenarios compared with the current, homogenous preclinical models. These proof-of-principle studies have provided evidence that mitochondrial genotype is a factor determining individual susceptibility to hepatotoxins that target the mitochondria. Therefore, these established lines should be utilized for future in-depth characterization and testing of additional putative hepatotoxic compounds to shed further light on the impact of mitochondrial DNA variation on (idiosyncratic) drug-induced liver injury as well as establishing the potential importance of the mitochondrial genome in personalized medicine.All forms of DMEM were purchased from Life Technologies . HepG2 cells were purchased from the European Collection of Cell Cultures . Cytotoxicity detection kits were purchased from Roche Diagnostics Ltd . Clear and white 96-well plates were purchased from Fisher Scientific  and Greiner Bio-One , respectively. All XF assay consumables were purchased from Agilent Technologies . All other reagents and chemicals were purchased from Sigma Aldrich  unless otherwise stated.Ten healthy volunteers were recalled from the previously established HLA-typed archive to give blood, described in CVCL_0027) (≤passage 7) were cultured and passaged as required in HepG2 ρ0 cell medium  in the presence of ethidium bromide . During this period, EtBr was removed for 48 hr every two weeks to help maintain cell viability. Following eight weeks’ exposure, EtBr was removed from a subset of cells for one week before characterization to ensure cells were devoid of mtDNA i.e., were ρ0 cells. If a ρ0 cell phenotype was not evident, cells were returned to EtBr treatment at the same dose before removal for another week and re-testing. This was continued until a ρ0 cell population was observed. All cells were tested monthly to ensure an absence of mycoplasma contamination.For a schematic representation of HepG2 cybrid generation see 2 was used (1 µg/mL) to prevent platelet activation.Healthy volunteers, five from haplogroup H, and five from haplogroup J donated whole blood from which platelets were isolated according to methods previously described . Briefly6) were centrifuged  and resuspended in Ca2+-free DMEM . This ρ0 cell suspension was overlayed onto isolated platelets using a Pasteur pipette to minimize disruption to the platelet pellet. The cell mixture was then centrifuged  to form a multi-layered pellet of platelets and HepG2 ρ0 cells.For an overview of the fusion experimental procedure see Following centrifugation, the supernatant was removed and polyethylene glycol  was added before resuspending the cell pellet (30 s) and incubating for 1 min. At the end of the incubation period, HepG2 ρ0 cell medium (30 mL) was added. A further 10-fold or twofold dilution with HepG2 ρ0 cell medium was performed before seeding into 96-well, 12-well, and 6-well plates.Two days post-fusion, the media was replaced with a fresh HepG2 ρ0 cell medium. After a further two days, this was replaced with media consisting of equal volumes of HepG2 ρ0 medium and cybrid selection medium . Finally, two days later, the media was switched to a 100% cybrid selection medium. ρ0 cells are auxotrophic for pyruvate and uridine, so the absence of these two constituents was the basis for the selection of successfully fused cells i.e., HepG2 cybrids. Cells remaining after selection were characterized to ensure a HepG2 cybrid phenotype by measuring the expression and function of mtDNAencoded proteins see  . Cells HepG2 wild-type (WT) cells and HepG2 rho zero (ρ0) cells were seeded at 30,000 cells/well in a 24-well plate in either ρ0 cell media (contains pyruvate and uridine) or selection media (devoid of pyruvate and uridine). On days 1, 3, 5, and 7 of culture, cells were collected by trypsinization and counted, following which the growth rate was calculated. Rho zero cells are auxotrophic for pyruvate and uridine, but WT cells are not, therefore, the absence of cell growth in selection media indicated the complete loss of mtDNA. For characterisation data see DNA extraction from HepG2 WT, HepG2 ρ0, and HepG2 cybrid cells was performed using a DNA mini kit  according to the manufacturer’s instructions. Sample DNA concentrations and quality were then quantified using a Quant-iT PicoGreen dsDNA Assay Kit and nanodrop spectrophotometry, respectively .Real-time PCR was carried out using two primers for regions of mtDNA; a custom sequence and ND-1 (complex I subunit) and two primers for regions of nuclear DNA; telomerase reverse transcriptase (TERT) and RNase P  . See Tab20 (2 μL), and 10 ng DNA (2 μL) from each sample were combined to give a final sample concentration of 1 ng/µL in each well. Real-time PCR was then carried out using the viiA7 RT-PCR system . MtDNA copies per cell were calculated on the basis that each nuclear DNA primer was present in diploid copies per cell and used the following formula, where x1=nuclear DNA primer cycle threshold (Ct) value, x2=mtDNA primer Ct value: mtDNA copies per cell = 2 (2(x1-x2)) , a nuclear DNA primer (0.5 μL), mtDNA primer (0.5 μL), dH(x1-x2)) . For detgel electrophoresis (SDS-PAGE) using 4–12% Bis-Tris gel  in MOPS buffer ).HepG2 ρ0, HepG2 WT, or HepG2 cybrid cells were lysed using sonication and 10 µg of lysate protein was resolved by sodium dodecyl sulphate-polyacrylamide 20) and blocked using 10% non-fat dried milk in Tris Buffered Saline-Tween .This gel was then transferred to a nitrocellulose membrane  in transfer buffer  (0.20% v/v in 10% non-fat dried milk in TBS-T). This was followed by anti-mouse secondary antibody (0.01% v/v in 10% non-fat dried milk in TBS-T) before visualization using an ECL system . For characterization data see Blocking solution was removed using TBS-T and the membrane was probed for CI-20, CII-30, CIII-core2, CIV-I, and CV-alpha subunits of complexes I-V of the electron transport chain using MitoProfile Total OXPHOS Human WB Antibody Cocktail . ECAR can be indicative of the glycolytic rate of the cell, however, it also takes into account changes in ECAR due to oxidative phosphorylation . Therefogly, proton production rate attributed to glycolysis; PPRresp, proton production rate attributed to respiration; PPRtot, total proton production rate; ECAR, extracellular acidification rate; BP, buffering power; max H+/O2, derived acidification for the metabolic transformation of glucose oxidation; OCRtot, total oxygen consumption rate; OCRrot, oxygen consumption rate following rotenone injection (Abbreviations: PPRnjection .2). Cells were then washed three times in serum-free galactose medium  before the addition of galactose medium (50 μL) and further incubation . This acute metabolic modification is sufficient to allow the identification of drugs that induce mitochondrial dysfunction, by reducing the ATP yield from glycolysis, thereby increasing reliance on OXPHOS for ATP production. Flutamide, 2-hydroxyflutamide, tolcapone, bicalutamide, and entacapone were each serially diluted to generate a concentration range of 0.01–300 µM in galactose medium. Diluted compounds (50 µL) were then added to each well  and cells were incubated  before conducting assays to assess mitochondrial function and cytotoxicity. All assays used ≤0.5% DMSO as vehicle control.HepG2 cybrids were collected by trypsinization and seeded on a collagen-coated flat-bottomed 96-well plate in cybrid maintenance medium  and incubated  and ATP standard curve solutions to a white-walled 96-well plate. ATP assay mix  was then added and bioluminescence was measured .LDH release was determined by the assessment of 25 L supernatant and 10 L cell lysate from each well, before measurement, using the cytotoxicity detection kit and reading at 490 nm. LDH release was calculated as LDH supernatant/(supernatant + lysate).Protein content was determined using cell lysate (10 µL) and protein standards (10 µL). BCA assay fluorescence was then measured at 570 nm.2) overnight.HepG2 cybrids were collected by trypsinization and seeded on a collagen-coated XFe96 cell culture microplate  and incubated  before the replacement of culture medium with 175 µL of unbuffered Seahorse XF base medium supplemented with glucose (25 mM), L-glutamine (2 mM), sodium pyruvate (1 mM), pre-warmed to 37 °C (pH 7.4). Following an equilibration period, measurements were taken to establish a basal oxygen consumption rate (OCR) before the acute injection of each of the five test compounds (7.8–500 µM). Following compound injection, a mitochondrial stress test consisting, of sequential injections of oligomycin , FCCP , and rotenone/antimycin A , was performed.Please refer to 2; 5 mM, mannitol; 220 mM, sucrose; 70 mM, KH2PO4; 10 mM, HEPES; 2 mM, EGTA; 1 mM, BSA; 0.4% w/v) containing constituents to permeabilize cells and stimulate oxygen consumption via complex I , complex II , complex III , or complex IV ; 0.5 mM, antimycin A; 2 mM, BSA; 30 mM, PMP; 1 nM). Following a basal measurement (no equilibration period) of three cycles of mix (30 s), wait (30 s) and measure (2 min), flutamide or 2-hydroxyflutamide  was injected followed by a mitochondrial stress test as detailed previously, only each measurement cycle was 3 min rather than 6 min.Please refer to In total, 10 distinct cybrid cell lines  were generated, one from each recruited volunteer. Each population was tested as an independent experiment (n=1), therefore, giving a total of n=5 for each cybrid cell line/volunteer. Each independent experiment contained a minimum of three technical replicates.Platelets were provided to the investigator blinded to haplogroup, to avoid bias; therefore, cybrid generation, experiments, and subsequent data analyses were performed on cybrids for which the haplogroup was unknown. Unblinding occurred at the stage at which datasets were combined to enable the subsequent statistical comparison of haplogroup H vs haplogroup J.Parameters for comparison were predefined to discourage statistical bias during analyses. These were, for both the assessment of mitochondrial function and drug-induced mitochondrial dysfunction: basal, maximum, and ATP-linked respiration, spare respiratory capacity, proton leak, and complex I-IV activity.All statistical analysis was conducted in R version 4.2.0. Each dataset was analyzed using a linear mixed model with the subject fitted as a random effect and the haplogroup fitted as a fixed effect. The dose-response relationship within each haplogroup was modeled using a polynomial to degree 3 and fitted to the log10 concentration. The untreated group was also included and given a concentration of log10(1). The exception to this was in the model fitted to assess the effect of flutamide and 2-hydroxyflutamide upon respiratory complex I and II where a polynomial to degree 2 was used as the experiments only contained five concentrations. Post-hoc tests were then obtained from the fitted models to compare the mean response between the two haplogroups. For the models with the fitted polynomials, this comparison was made at the mean concentration i.e., in the middle of the fitted dose-response curve. The results of all statistical tests can be viewed in  The aim of this study was to demonstrate the role of varying mitochondrial DNA levels as an important factor in drug-induced cell injury, hence creating a novel in vitro model which was representative of the diversity in mitochondrial genotype. The authors take a clever approach by using cybrid cell lines to test the role of mtDNA variations, both mutational load, and DNA level, and propose that such cell models could be potentially representative of mitochondrial genome diversity. Their findings provide evidence that these mechanisms could play a role in individual susceptibility to hepatic adverse drug reactions. This also adds an important understanding of the role of mitochondria in the onset of drug-induced toxicity. public reviews designed to be posted alongside the preprint for the benefit of readers; (ii) feedback on the manuscript for the authors, including requests for revisions, shown below. We also include an acceptance summary that explains what the editors found interesting or important about the work.Our editorial process produces two outputs: (i) Decision letter after peer review:[Editors’ note: the authors submitted for reconsideration following the decision after peer review. What follows is the decision letter after the first round of review.]eLife. Your article has been reviewed by 2 peer reviewers, and the evaluation has been overseen by a Reviewing Editor and a Senior Editor. The reviewers have opted to remain anonymous.Thank you for submitting the paper "The generation of HepG2 transmitochondrial cybrids to reveal the role of mitochondrial genotype in idiosyncratic drug-induced liver injury: a translational in vitro study" for consideration by Comments to the Authors:eLife.We are sorry to say that, after consultation with the reviewers, we have decided that this work will not be considered further for publication by In this manuscript, Amy Ball et al., use HepG2 cell-derived mitochondrial Cybrids to study the effects of drug-induced liver injury. The aim here is to demonstrate the role of varying mitochondrial DNA levels as an important factor in drug-induced cell injury. The authors use Cybrid cell lines derived from Rho zero HepG2 Cells and H- and J haplotypes of blood cells from human donors. The use of cybrid cell lines to test the role of mtDNA variations, both mutational load, and DNA level, is an excellent idea. However, this manuscript contains many serious defects in terms of concept and experimental approach.Weaknesses: A major weakness is the use of HepG2 cells which is derived from a human hepatic tumor. Its genotype and metabolic profile are substantially altered from the normal hepatic cells. As the authors noted, one example is the absence of many inducible microsomal CYPs. The effects of Hydroxyflutamide, the metabolic product on mitochondrial function are not the same as the effects of flutamide hydroxylated in cells by the action of endogenously expressed CYPs.Another important drawback is that the analysis is strictly dependent on respiratory flux analysis. It is not clear why mtDNA contents are not analyzed. To that matter it is not clear if the mtDNA contents in donor haplotypes H and J are indeed different and how much different. Using two haplogroups with unknown mtDNA contents is not sufficient. One needs to generate cell lines containing multiple levels of mtDNA under the same nuclear DNA background.Reviewer #1 (Recommendations for the authors):Line 87: Is haplogroup J more strongly linked to iDILI than haplogroup H? If so, please note and comment upon this.Line 134: At first I thought it odd to discuss a non-statistically significant result, but I do think it's a good point that there seem to be systematic differences between the groups when you look across the entire dose-response curve. At least for the proton leak and maybe even basal OCR – I'm not totally sure about the spare respiratory capacity. Perhaps there is a way to perform statistical comparisons between the curves. Or perhaps you could perform curve fits of Hill functions and see if there are statistically significant differences in the fit parameters (similar to what you did with EC50 comparisons in a later section). It may be worth consulting with a statistician to see if this would be okay, or if it would be considered p-hacking.As a general comment, the SI seems like it could use a little more polish. If I wanted to reproduce your cybrid generation method, I would look to the SI to understand how to evaluate them. But unfortunately, the SI doesn't do a super great job of citing references that explain previously-used methods in better detail.Line 535: text should be moved above the figure.Line 544 Table: Looks like a formatting issue pushed some blank table space to the next page. Also, what is "custom"?Line 553 Figure: It looks like ρ_0 is mis-labeled on the left figure.Line 559: Section S4: please include a citation so readers could learn more about these methods.eLife. Your revised article has been evaluated by Mone Zaidi (Senior Editor) and a Reviewing Editor.Thank you for resubmitting your work entitled "The generation of HepG2 transmitochondrial cybrids to reveal the role of mitochondrial genotype in idiosyncratic drug-induced liver injury: a translational in vitro study" for further consideration by The manuscript has been improved but there are some remaining issues that need to be addressed, as outlined below:Please address Comments from Reviewer #3. The limitations should be included in the Discussion section.Reviewer #3 (Recommendations for the authors):1) In this report, the authors describe the creation of transmitochondrial HepG2 cell cybrids to investigate the influence of variation in mitochondrial DNA on the susceptibility of cells to drug-induced toxicity. They propose that the production of such cell models has the potential to be representative of mitochondrial genome diversity across the population and their findings provide evidence that these mechanisms could play a role in individual susceptibility to hepatic adverse drug reactions. Although the results from their work only show modest differences between the haplogroups tested, this work is valuable to the field as it provides clear evidence that mtDNA variation influences susceptibility to drug-induced mitochondrial dysfunction and cell death. For many years the link between mtDNA and adverse drug reactions has been postulated by leaders in the field, and I believe that the publication of this work will enable rapid expansion in this area of research. Furthermore, the repurposing of transmitochondrial cybrid cells for studying drug safety brings a powerful new tool to toxicological research which could find utility in academia, and as the authors suggest, drug development. Overall, the data is robust and well analysed and the interpretations and conclusions made by the authors are appropriate.2) In this work, the authors have generated several novel cell lines, each with distinct mitochondrial DNA content, to investigate whether individual variation in mitochondrial genotype can influence susceptibility to hepatotoxicity. The novelty of this model is its creation from HepG2 cells making it not only practical and reproducible but also relevant to preclinical testing during drug development. The results from this work indicate that variation in the mitochondrial genome does play a role in susceptibility to some hepatotoxins, but that this is a complex relationship that may only be one small factor in predisposing an individual to risk of an adverse drug reaction. In this report, only two classes of compounds are examined in the transmitochondrial cybrids, and the results from these suggest that these mechanisms are highly compound-specific. Therefore, it is difficult to extrapolate whether the same mechanisms would be evident across a wider variety of compounds. Another major limitation comes from the lack of diversity of mitochondrial haplogroups that are represented in the cybrids, which are made up of only haplogroup J and H. These two haplogroups are close phylogenetic relations. The addition of more diversity in the panel to increase phylogenetic coverage may uncover greater differences. Finally, the findings would be more robust, if transmitochondrial cybrids were created from different individuals, but of the same haplogroup subclade to see if the same effects would be replicated.Overall summary - for many years the link between mitochondrial DNA and adverse drug reactions has been postulated by leaders in the field, and despite caveats mentioned above, this work provides a first proof of principle that this is a contributing factor and provides novel methodology and tools to enable this area of research to expand. Specifically, the repurposing of transmitochondrial cybrid cells for studying drug safety brings a powerful new tool to toxicological research which could find utility in academia, and as the authors suggest, drug development.Specific feedback to the authors.There are several points that the authors should consider:1) The process of creating the HepG2 rho(0) cells using ethidium bromide has the potential to not only deplete mitochondrial DNA, but also damage genomic DNA. Have the authors any data to support the fidelity of the original HepG2 cell line? Furthermore, does the whole process (rho (0) generation and repopulation with mtDNA) have the potential to introduce differences between the cell lines so they no longer maintain the consistent HepG2 parental cell background that is essential for this model to be useful?2) As a tumour-derived cell lineHepG2 cells suffer from a lack of physiological relevance. They contain low levels of both phase I and II drug-metabolising enzymes, transporters, and secondary structures. This limits the translatability of any findings to humans and also makes them unsuitable for testing any compounds where a metabolite of the drug is required for toxicity. Why did the authors not produce these models in a more physiologically relevant system e.g. HepaRG cells.3) Are the test concentrations used in the manuscript relevant for the in vivo concentrations in man? The authors should provide these Cmax concentrations in the manuscript. This is important if this model is to be useful during preclinical development. [Editors’ note: The authors appealed the original decision. What follows is the authors’ response to the first round of review.]Comments to the Authors:In this manuscript, Amy Ball et al., use HepG2 cell-derived mitochondrial Cybrids to study the effects of drug-induced liver injury. The aim here is to demonstrate the role of varying mitochondrial DNA levels as an important factor in drug-induced cell injury. The authors use Cybrid cell lines derived from Rho zero HepG2 Cells and H- and J haplotypes of blood cells from human donors. The use of cybrid cell lines to test the role of mtDNA variations, both mutational load, and DNA level, is an excellent idea. However, this manuscript contains many serious defects in terms of concept and experimental approach.Weaknesses: A major weakness is the use of HepG2 cells which is derived from a human hepatic tumor. Its genotype and metabolic profile are substantially altered from the normal hepatic cells. As the authors noted, one example is the absence of many inducible microsomal CYPs. The effects of Hydroxyflutamide, the metabolic product on mitochondrial function are not the same as the effects of flutamide hydroxylated in cells by the action of endogenously expressed CYPs.The limitations of HepG2 cells are commented upon in the manuscript and are widely acknowledged across the toxicology sector. However, despite these limitations, HepG2 cells remain an important mainstay of pharmaceutical preclinical testing for hepatotoxicity as long as the parameters of their “fit-for-purpose” are clearly defined. Therefore, their use in this study is appropriate. Moreover, due to the widespread use of HepG2 cells in preclinical toxicity testing, their conversion into cybrid cells is both highly relevant and useful to both the pharmaceutical industry and academic research, see our previous publication . This statement has been included in the manuscript . Additionally, cybrid cells cannot be generated in the “gold standard” model for drug-induced liver injury, primary human hepatocytes, as these do not undergo division and rapidly de-differentiate over a 24 h period, see our previous publication .Concerning whether it is appropriate to use 2-hydroxyflutamide to recapitulate the in vivo effects of hydroxyflutamide, it should be noted that the 2-hydroxy flutamide used in this study is structurally identical to the endogenous, CYP-mediated 2-hydroxylated metabolite. Specifically, upon administration, flutamide undergoes extensive first-pass metabolism, primarily by conversion to 2-hydroxyflutamide via cytochrome P450 1A2 (CYP1A2), followed by glucuronidation before excretion. It is known that following a single 250 mg dose of flutamide, its maximum plasma concentration (Cmax) is 72.2 nM, yet the Cmax of 2-hydroxyflutamide is 4.4 μM (PMID: 3169114). Flutamide is considered to be a pro-drug for 2-hydroxyflutamide. Therefore, given the identical chemical structures, and lack of any contrary literature upon this point, we disagree with this comment that “The effects of Hydroxyflutamide, the metabolic product on mitochondrial function are not the same as the effects of flutamide hydroxylated in cells by the action of endogenously expressed CYPs.” We have previously published using this in vitro model . It should be noted that the lack of CYP enzymes in this model allows us to specifically separate toxic mechanisms due to the parent compound and the major hydroxy metabolite. This point has been included in the revised manuscript .Another important drawback is that the analysis is strictly dependent on respiratory flux analysis. It is not clear why mtDNA contents are not analyzed. To that matter it is not clear if the mtDNA contents in donor haplotypes H and J are indeed different and how much different. Using two haplogroups with unknown mtDNA contents is not sufficient. One needs to generate cell lines containing multiple levels of mtDNA under the same nuclear DNA background.We would like to provide further clarification on this point. We have supposed that by “mtDNA contents”, the reviewer is referring to a need to quantify absolutely the mtDNA copy number within each cybrid cell line, and not the whole mitochondrial genome sequence which we do have for each of the cybrid cell lines created. We believe that this line of enquiry, looking at mtDNA content, is out of scope for the research presented herein, which aims to evaluate whether specific single nucleotide polymorphisms, and/or haplogroups, may play a contributory role in determining individual susceptibility to mitotoxins. That said, in our most recent projects utilising the cybrid cells we have quantified mtDNA content, and no significant differences in mtDNA levels were apparent at a basal level. Additionally, it is our experience that mtDNA content (in terms of copy number) is highly temporally variable. Finally, with regards to the additional suggestion to manipulate mtDNA levels in the cybrid cells, to further manipulate the mtDNA levels in these cybrid cells following their already extensive modification would not add to the scientific understanding of how specific single nucleotide polymorphisms, and/or haplogroups, contribute to individual susceptibility to mitotoxins.In addition, we would like to point out that H and J are each a dataset which is comprised of distinct cybrid cell lines (5 haplogroup J cybrid lines and 5 haplogroup H cybrid lines) not a single cell line from each, which may have been assumed by the reviewer. Our newly created figures (refer to point 2.2) more clearly show the results from each cell line, rather than as a single average (mean) value. We believe that this represents the data and its variability more clearly.Reviewer #1 (Recommendations for the authors):Line 87: Is haplogroup J more strongly linked to iDILI than haplogroup H? If so, please note and comment upon this.Haplogroup J is reported to be more susceptible to toxic mechanisms for example see PMID: 29486301, however, no previous work has looked specifically at haplogroup J and idiosyncratic DILI. We have expanded on this point in the revised manuscript .Line 134: At first I thought it odd to discuss a non-statistically significant result, but I do think it's a good point that there seem to be systematic differences between the groups when you look across the entire dose-response curve. At least for the proton leak and maybe even basal OCR – I'm not totally sure about the spare respiratory capacity. Perhaps there is a way to perform statistical comparisons between the curves. Or perhaps you could perform curve fits of Hill functions and see if there are statistically significant differences in the fit parameters (similar to what you did with EC50 comparisons in a later section). It may be worth consulting with a statistician to see if this would be okay, or if it would be considered p-hacking.As a general comment, the SI seems like it could use a little more polish. If I wanted to reproduce your cybrid generation method, I would look to the SI to understand how to evaluate them. But unfortunately, the SI doesn't do a super great job of citing references that explain previously-used methods in better detail.Thank you for these comments, we have consulted with Mark Lennon, Director of Statistics at GSK, to review our analytical methods. He advised us that our previous analysis was not optimal due to its dependence on multiple comparisons, which reduced power. Therefore, we have reanalysed all data sets using a linear mixed model with the subject fitted as a random effect and the haplogroup fitted as a fixed effect. The dose-response relationship within each haplogroup was modelled using a polynomial to degree 3 or degree 2, as appropriate, and fitted to the log10 concentration. Post-hoc tests were then obtained from the fitted models to compare the mean response between the two haplogroups. For the models with the fitted polynomials, this comparison was made at the mean concentration i.e. in the middle of the fitted dose-response curve. See updated methodology .Not only has this alternative analysis revealed additional relationships, but the figures now graphically represent the variation within each haplogroup as each cybrid cell is now plotted as a separate point on the graphs.We believe that this further analysis has strengthened the interpretation and conclusions of the dataset and improved the manuscript.Line 535: text should be moved above the figure.Line 544 Table: Looks like a formatting issue pushed some blank table space to the next page. Also, what is "custom"?Line 553 Figure: It looks like ρ_0 is mis-labeled on the left figure.Line 559: Section S4: please include a citation so readers could learn more about these methods.We have corrected these errors. Please note that all supplementary material is now included in the main article. The generation and characterisation of the transmitochondrial cybrids, previously included as supplementary information, can now be found in the methods section.[Editors’ note: what follows is the authors’ response to the second round of review.]The manuscript has been improved but there are some remaining issues that need to be addressed, as outlined below:Please address Comments from Reviewer #3. The limitations should be included in the Discussion section.Reviewer #3 (Recommendations for the authors):Specific feedback to the authors.There are several points that the authors should consider:1) The process of creating the HepG2 rho(0) cells using ethidium bromide has the potential to not only deplete mitochondrial DNA, but also damage genomic DNA. Have the authors any data to support the fidelity of the original HepG2 cell line? Furthermore, does the whole process (rho (0) generation and repopulation with mtDNA) have the potential to introduce differences between the cell lines so they no longer maintain the consistent HepG2 parental cell background that is essential for this model to be useful?This is an important consideration of these transmitochondrial cybrid cells and have included reference to this limitation in the discussion . Although we have no data to support fidelity of HepG2 cells after EtBr treatment we describe the additional mitigation steps taken by us to minimise off-target cellular effects when generating the cybrid cells.2) As a tumour-derived cell lineHepG2 cells suffer from a lack of physiological relevance. They contain low levels of both phase I and II drug-metabolising enzymes, transporters, and secondary structures. This limits the translatability of any findings to humans and also makes them unsuitable for testing any compounds where a metabolite of the drug is required for toxicity. Why did the authors not produce these models in a more physiologically relevant system e.g. HepaRG cells.We are in agreement with the reviewer on this issue and note it ourselves . However, the creation of cybrid cells from cell lines such as HepaRG is problematic due to the length of the process to create the cells, which is not compatible with HepaRG growth and differentiation protocols which must be strictly adhered to. For example, specifically, the cloning of HepaRG cells is not possible since any deviation from the recommended cell densities can induce the transformation of cells. We also think that there are some advantages of using HepG2 cells, and we have further described these in the discussion .3) Are the test concentrations used in the manuscript relevant for the in vivo concentrations in man? The authors should provide these Cmax concentrations in the manuscript. This is important if this model is to be useful during preclinical development.We thank reviewer 3 for this helpful comment. This information has now been added to the manuscript .


Cooperation, acoustically signaled through vocal convergence, is facilitated when group members are more similar. Excessive vocal convergence may, however, weaken individual recognizability. This study aimed to explore whether constraints to convergence can arise in circumstances where interlocutors need to enhance their vocal individuality. Therefore, we tested the effects of group size (3 and 5 interactants) on vocal convergence and individualization in a social communication scenario in which individual recognition by voice is at stake.In an interactive game, players had to recognize each other through their voices while solving a cooperative task online. The vocal similarity was quantified through similarities in speaker i-vectors obtained through probabilistic linear discriminant analysis (PLDA). Speaker recognition performance was measured through the system Equal Error Rate (EER).Vocal similarity between-speakers increased with a larger group size which indicates a higher cooperative vocal behavior. At the same time, there was an increase in EER for the same speakers between the smaller and the larger group size, meaning a decrease in overall recognition performance.The decrease in vocal individualization in the larger group size suggests that ingroup cooperation and social cohesion conveyed through acoustic convergence have priority over individualization in larger groups of unacquainted speakers. The ten1.1.How can individuals express cooperation in speech communication? During social interactions, cooperation typically manifests itself through convergent accommodation, i.e., the tendency of individuals to adjust aspects of their verbal and nonverbal behaviour towards those of their interlocutors in communicative encounters . We modulated the parameter of group size to test the hypotheses that (1) individualisation increases with increasing group size of communication partners; (2) higher individualization in larger groups leads to better voice recognition. Given that divergence or maintenance are strategies to emphasize distinctiveness from others  expected others’ cooperation; (2) perceived collective efficacy; (3) perceived conflict of interest, Here we propose an experimental design to study the trade-off between vocal accommodation and voice individualization in humans. One option to carry out this task might have been to replicate the communicative scenario tested in marmoset communication, i.e., short versus long distance communication. We, however, refrained from replicating such a setting because of the known effects of talker-to-listener distance (henceforth TLD) on the variation of speech acoustics. It has been repeatedly shown that talkers spontaneously adjust their way of speaking in response to the increasing distance from the listeners, with consequences on various acoustic parameters, such as duration, intensity, fundamental frequency (f0) and formant frequencies  can be used to study the effect of group size on individuals’ propensity to cooperate or enhance individuality? Accommodation and vocal individuality have been measured through a wide variety of spectral and temporal features with considerable inconsistency across studies, depending on the particular feature or set of acoustic features under examination see a.o. . Both phvia some statistical processes that de-correlate the obtained information.Among the multitude of spectral and temporal features cueing individuality and accomodation, here, we used Mel Frequency Cepstral Coefficients (MFCC) as a numeric acoustic representation of speech information that is highly salient to humans . MFCCs avia probabilistic linear discriminant analysis (PLDA), a statistical method for maximizing between-speaker and minimizing within-speaker differences.To understand whether humans would carry out individualization over convergent accommodation with increasing group size, we calculated the acoustic distances of their i-vector representations  when playing in groups of 3 and 5 players, as well as within-speaker acoustic variability in in-game and post-game sessions. The similarity between i-vector representations was obtained in Vocalize 1.2.The two alternative hypotheses mentioned above concerning the effect of group size on cooperation vs. individualization (Aim 1) are more precisely reformulated in relation to PLDA scoring:Hypothesis 1a: Individualization, acoustically manifested through divergence or maintenance, is expected to be more prevalent, if players' incentive to maximize their recognizability in larger groups prevails over cooperation. Hence, the average PLDA scores for between-speaker comparisons were expected to decrease from group N = 3 to N = 5 (henceforth: group 3 and group 5 respectively). Hypothesis 1a is henceforth referred to as the individualization hypothesis.Hypothesis 1b: Cooperation, acoustically manifested through convergence, is expected to prevail over individualization in a larger group, if players prioritize group cohesion and affiliation as well as collective effort to complete the game over competing against each other in the interest of being recognized. Acoustically, we expected that the average PLDA scores for between-speaker comparisons would be higher when samples were obtained from group 5 than from group 3. Hypothesis 1b is henceforth referred to as the cooperation hypothesis.Regarding within-speaker acoustic variability between in-game and post-game recordings, we predicted lower variability in post-game recordings, taken in isolation, as compared to in-game sessions.Between the two game sessions, the individualization hypothesis would be confirmed if lower variability is found in group 5 compared to 3. On the other hand, the cooperative hypothesis would be supported if higher variability is found in recordings obtained in group 5 for the effect of the higher influence players exert on each other.To examine the effect of individualization or convergence on voice recognition (Aim 2), we tested the speaker verification performance of the iVector/PLDA VOCALIZE system when post-game recordings were compared to the corresponding in-game recordings in group 3 and 5, in terms of Equal Error Rate (EER) using the software Biometrics Version 2019A. EER is a metric for a recognition system performance, corresponding to equal miss and false alarm rate. The lower the EER, the higher the recognition performance of the system. If the cooperation hypothesis holds , we expected the EER to be higher when post-game recordings are compared to in-game recordings in group 5 than in group 3. Alternatively, if the individualization hypothesis is tenable , EER is lower when post-game recordings are compared to in-game recordings in group 5 compared to group 3.The results of this study about the constraints to cooperative accommodation are relevant from an evolutionary perspective since they will shed further light on whether natural selection has also endowed humans  with the flexibility to privilege vocal accommodation or individuality depending on communicative circumstances. From a socio-psychological point of view, the results will contribute to a further understanding of human variability in cooperative behavior and team-building dynamics without visual cues. Additionally, with this research we will also collect further evidence about the implications of phonetic convergence on voice processing.2.2.1.Game-based techniques have been proved to be successful in eliciting semi-spontaneous (yet somewhat controlled) speech, as well as studying the suprasegmental properties of speech  and in f2.1.1.time course of the conversation . Participants declared they had no known vision, no hearing, or linguistic impairment. To minimize the effect of idiosyncratic segmental realizations on voice recognition, all were auditorily pre-screened for comparable pronunciation patterns by a trained phonetician. The focus was on segmental features since they were shown to be used more than suprasegmental features in Swiss German dialect recognition . Therefo2.3.The experiment consisted of three main sessions: training, in-game, and post-game sessions.Training: One month before the start of the experimental session, every player received the game instructions via email and contacted the experimenter when they felt ready to start the training. During the training, individual players got familiar with the spaces of the online playroom and practiced the game mechanics with the experimenter . The game mechanics for both game sessions are summarized as follows:· All players move the first card from the cardholder to the hand area. Cards in the hand area are not visible to other players (step 1).First round of the game:· The player whose first card has the same number of dots as the one in the boneyard starts the game (step 2).· The player greets (step 3) , reveals her identity  (step 4), says what is on the card she has and the one she is looking for  (step 5). This procedure repeats until all players have revealed their identities .From the second round onwards:· The player who has a card matching the number of dots as the card in the boneyard starts the new round of the game (step 2), greets the participants (step 3) but does not reveal her identity (step 4 omitted). She says what is on the card she has and the one she is looking for (step 5) and after that the experimenter launches the Zoom poll (step 6). All players guess the identity of the speaker holding the turn. The player holding the turn clicks on the option “I am the player” (step 7).· Once all players have voted, the experimenter shares the results of the poll (step 8). No correct answer is given, but it will be shown how often each given option was voted.· A new player continues the game and the procedure repeats until all players have finished their cards. Step 4 happens only in the first round of the game (familiarization), while Steps 6, 7 and 8 from the second round onwards. The intersession interval was of about 2 h. Post-game sessions: One month after the in-game sessions, the five players were invited again to record the utterances they had produced during the match  in single Zoom sessions. We took this set of recordings as a baseline since the players’ performance could not be influenced either by the acoustic behavior of the other players or by the need to be recognized.via Zoom on the local computer of the experimenter. Participants used their in-built microphones and headphones when playing the game. The option “Record a separate audio file for each participant” from the Zoom recording setting was enabled to obtain all participants’ audio streams as separate audio files. Every participant’s audio tracks from in-game and post-game sessions were converted from their original format (.m4a) to .wav format using Adobe Audition 2021 .The experimenter’s role in both the in-game and post-game recordings was consistent and limited to recalling the game instructions and marking the transition between different game rounds. He did not actively participate in playing the game. In in-game and post-game sessions, the speech performance was audio-recorded 2.4.The speech corpus comprises 80 recordings of a 27–29-word long carrier texts in Bernese German, transcribed according to Dieth’s spelling . An exameng. Hello. I am Player three. I have the dominoes card with three red tiles, and I am looking for the dominoes card with two green tiles. Who has this dominoes card? Thank you).(1) Hallo. I bi d Spilerin 3. I ha dr Dominostei mit dä 3 rotä Pünkt. I sueche nachem Dominostei mit dä 2 grüene Pünkt. Het öpper dä Dominostei? Merci , 25 in group 5 (5 speakers * 5 game rounds), and 40 from post-game sessions. Of this latter set of recordings:· 30 utterances for re-recording were derived from the three players playing in groups 3 and 5 [3 players * 10 rounds (5 rounds in group 3 + 5 rounds in group 5)].· 10 utterances for re-recording were derived from the two players playing only in group 5 [2 players * 5 rounds].Henceforth, we will refer to the speakers playing in both game sessions as Speaker A, Speaker B and Speaker C. Object of analysis for the present study are the utterances produced in-game and post-game sessions by Speak A, Speak B, and Speak C.2.5.For every dataset recording, 15-dimension MFCCs  were calvs Speaker B; Speaker A vs Speaker C and Speaker B vs Speaker C) as a random factor . Given the evidence that during conversation, accommodation can evolve dynamically between turns  on PLDA scores for different speaker comparisons using Linear Mixed Effect Models. To account for speaker variability in accommodation behavior  we enteren turns , we alsoTo examine within-speaker variability in in-game and post-game sessions, we calculated the average consecutive difference PLDA (henceforth ACD_PLDA) for each speaker and game, in-game and post-game sessions  = 61.19, p < 0.001]. Regarding the direction of the effect , χ2(2) = 0.265, p = 0.875].Concerning aim 1, i.e., to understand whether humans would privilege individualization over convergent accommodation with increasing group size, the results of the statistical analysis showed a significant main effect of Group (5 compared to 3) on PLDA scores for between-speaker comparisons [As for the effect of group size on within-speaker acoustic variability across the experiment sessions, Speaker A and B behaved according to the predictions of the cooperative hypothesis. As shown in Concerning aim 2, i.e., to understand the effect of individualization or convergence on the verification performance of the automatic recognition system VOCALIZE, the results show that Equal Error Rate (EER) is larger when post-game recordings are compared to in-game recordings in group 5 (9.64%) than to those in group 3 (6.33%)  bottom. 4.In the current study, we introduced a novel game-based method to investigate the trade-off between cooperative accommodation and voice individualization in situations wherein voice recognition was at stake. Inspired by findings from animal communication  and humaor individualization, our results point in favor of the cooperation hypothesis. Unlike findings in animal communication showing that group size has a positive impact on the degree of individuality in vocalizations across taxa and within-species  are needed to confirm the observed prevalent cooperation in larger groups, the findings of this study support the importance of eliciting accommodation with engaging game-based techniques  but alsoThe raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.Participants gave their informed consent to participate in the study and were paid for their participation. The study was conducted within the guidelines of the Ethics Committee of the Zürich University Faculty of Arts and Social Sciences.EP and VD conceived and designed the experiment, revised the manuscript and discussed milestones. EP conducted the experiment, analysed the data and drafted the manuscript. All authors contributed to the article and approved the submitted version.This study was supported by the NCCR Evolving Language, Swiss National Science Foundation Agreement #51NF40_180888.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


The panels were intended to diagnose at-risk NASH (NIS4), presence of NASH (OWLiver) or fibrosis stages >2, >3 or 4 (enhanced liver fibrosis (ELF) test, PROC3 and FibroMeter VCTE). The prespecified performance metric was an area under the receiver operating characteristic curve (AUROC) ≥0.7 and superiority over alanine aminotransferase for disease activity and the FIB-4 test for fibrosis severity. Multiple biomarkers met these metrics. NIS4 had an AUROC of 0.81  for at-risk NASH. The AUROCs of the ELF test, PROC3 and FibroMeterVCTE for clinically significant fibrosis (≥stage 2), advanced fibrosis (≥stage 3) or cirrhosis (stage 4), respectively, were all ≥0.8. ELF and FibroMeter VCTE outperformed FIB-4 for all fibrosis endpoints. These data represent a milestone toward qualification of several biomarker panels for at-risk NASH and also fibrosis severity in individuals with NAFLD.There are no approved diagnostic biomarkers for at-risk non-alcoholic steatohepatitis (NASH), defined by the presence of NASH, high histological activity and fibrosis stage ≥2, which is associated with higher incidence of liver-related events and mortality. FNIH-NIMBLE is a multi-stakeholder project to support regulatory approval of NASH-related biomarkers. The diagnostic performance of five blood-based panels was evaluated in an observational (NASH CRN DB2) cohort ( The NIMBLE biomarker qualification project evaluated the diagnostic performance of five blood-based biomarkers in a cohort of individuals with non-alcoholic fatty liver disease and showed good discriminative performance over commonly used laboratory tests in detecting various stages of non-alcoholic steatohepatitis progression. The presence of non-alcoholic steatohepatitis (NASH), an active form of NAFLD, and liver fibrosis stage 2 or higher is linked to an increased incidence of liver-related adverse clinical outcomes and death and is also referred to as ‘at-risk’ NASH4. Identification of individuals with at-risk NASH for therapy is a cornerstone for clinical care and inclusion in therapeutic trials5.Non-alcoholic fatty liver disease (NAFLD) is a leading cause of liver-related morbidity and mortality8. This has spurred much work to establish non-invasive tests (NITs) to diagnose NASH and fibrosis, yet none has met the evidentiary requirements needed for regulatory qualification. The lack of regulatory approval limits availability of these tests for widespread clinical use. It also hinders patient recruitment into clinical trials and their further development for treatment response monitoring. From a public health point of view, the lack of approved biomarker panels for diagnostic purposes is, thus, a major barrier to access to care and drug development9. Although progress has been made in retrospective comparative assessment of NITs10, evidence gaps remain for full qualification. Development of such NITs to regulatory standards remains a major unmet need for the field.Histological evaluation of liver biopsy sections is the reference standard for diagnosis of NASH as well as quantification of disease activity and fibrosis stage, but it requires an invasive liver biopsy with its associated risks and limitations, hindering its widespread use11. Drug development tools are developed and validated in the context of a specific drug development program, and the approval is limited in a narrowly defined context of use. Academic consensus is another pathway, but it is limited by lack of standardized reported outcomes and publications based on studies that are not designed to meet typical regulatory standards. Biomarker qualification is the third pathway. It is a process wherein regulatory agencies agree that a given biomarker, when used in a specific clinical setting to answer a specific question, provides actionable information with a prespecified level of certainty11.There are three general pathways for regulatory approval of biomarker panels12. It includes consideration of the analytic robustness of the assay and clear definition of the clinical settings and boundaries within which the biomarker assays work. It further requires rigorous assessment of sensitivity and specificity for its intended use and validation across relevant populations. Finally, it also includes an assessment of benefit versus the risks of misclassification. The overall use case is defined by the context of use, which defines who the test will be used on and the clinical setting where it will be used, the purpose of the test, the read-out and its interpretation and the decisions that will emanate from the read-out. The purpose can be diagnostic, prognostic, predictive, disease monitoring or assessment of treatment response13. Together, this represents a substantial amount of data, which, for practical logistic reasons, are usually generated in a multi-step manner.Regulators recognize collaborative initiatives and consortia as a vehicle to tackle the qualification process9. It represents a collaborative effort involving the FNIH, the US Food and Drug Administration (FDA), academics and 14 industry partners to qualify biomarkers for diagnostic enrichment of ‘at-risk’ NASH and its subcomponents. NIMBLE has an imaging workstream and a circulating biomarker workstream. The current study is the final report of stage 1 of the NIMBLE project’s circulating biomarker workstream and represents a collaboration between the NIMBLE circulating biomarker workstream and the adult clinical centers and the data coordinating center of the NASH Clinical Research Network (NASH CRN) of the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)  was established by the federal government of the United States as a platform to enable public–private partnerships, bringing multiple federal agencies together with academics, industry partners and other relevant stakeholders to solve problems of great public health importance. The Non-Invasive Biomarkers for Metabolic Liver Disease (NIMBLE) project was commissioned by the FNIH to qualify NITs for NAFLD14. The proposed context of use was for diagnostic enrichment for at-risk NASH and its components—that is, presence of NASH, high histological disease activity and specific fibrosis thresholds, for example clinically significant fibrosis (≥stage 2), advanced fibrosis (≥stage 3) or cirrhosis (stage 4), in a population with NAFLD or risk factors for NAFLD. A successful diagnostic enrichment biomarker is expected to select for patients with a higher likelihood of meeting the criteria for at-risk NASH in a subsequent liver biopsy, thus reducing the number of patients who undergo this procedure unnecessarily and improving the efficiency of the process to select patients in need of clinical intervention and/or suitable for participation in NASH clinical trials.The first step in the biomarker qualification path is regulatory acceptance of a letter of intent establishing the scientific roadmap to be taken. A NIMBLE study letter of intent for the circulating biomarkers in the current study has been accepted by the FDA, a critical step in the qualification process15. Since the design of NIMBLE, additional panels have emerged—for example, the FAST, Agile and ADAPT scores; the qualification of these is expected to follow the roadmap established by the letter of intent for NIMBLE17. A separate qualification effort for the FAST score is underway already.The panels chosen represent the first wave of circulating biomarkers going through this qualification effort and included NIS4 , OWLiver , PROC3 , enhanced liver fibrosis (ELF)  test and the FibroMeter VCTE . The latter was chosen as the best vibration controlled transient elastography (VCTE)-linked panel at the time when NIMBLE was designedThe goal of the current step in the qualification process was not to identify novel biomarkers or to determine which biomarker is the best but to rigorously determine the sensitivity and specificity of each of the biomarker panels in a curated cohort with a balanced distribution of fibrosis stage and to compare their performance to commonly used laboratory tests for the same purpose used by the general medical community. The data would inform the further development of the selected biomarkers and provide the foundation for a full qualification plan for these panels which, after acceptance by the FDA, will support their qualification with or without additional data from stage 2 as a final step. This critical step thus moves the field closer to having qualified NITs that can be used to identify individuals with at-risk NASH and its subcomponents for both routine practice and drug development.n = 222; stage 1: n = 114; stage 2: n = 262; stage 3: n = 277; and stage 4: n = 198). A total of 1,073 individuals meeting the eligibility criteria were, thus, included for this analysis  for the diagnosis of NASH, high NAFLD activity score or varying severity of hepatic fibrosis in a population with NAFLD (Extended Data Table n = 396) as this analysis was limited to individuals who had a VCTE examination within 6 months of the liver biopsy. The baseline features of this subset were similar to the larger cohort . This is correlated with a higher risk of liver outcomes and is the target population for most clinical trials4. The prespecified analytic approach for this study was, first, to establish that the area under the receiver operating characteristic curve (AUROC) was at least 0.7 and superior to the unit line—that is, the 95% confidence limits did not intersect 0.5. Second, it was to establish superiority over alanine aminotransferase (ALT), a universally used measure of liver injury for over five decades, for biomarkers intended to assess disease activity and FIB-4 for biomarkers intended to evaluate fibrosis. These were selected because of the amount of pre-existing literature on these biomarkers at the time when NIMBLE was conceived20 and their wide availability for use by the medical community21. The FIB-4 test also provides prognostic information with a step-wise increase in mortality from 0.07 to 0.3 to 2.5 per 100 person-years in individuals with FIB-3 <1.3, 1.3–2.6 and >2.6, further supporting its use as a comparator23. Other markers for liver injury, such as CK18, were not considered as comparators because they are not universally available or used by the general medical community to assess liver injury. Superiority over ALT and FIB-4 were considered a pragmatic initial step to move to final qualification; biomarker panels that could not meaningfully outperform such simple laboratory measures to inform decision-making would not be suitable for further qualification studies.At-risk NASH was defined as presence of steatohepatitis with an NAFLD activity score ≥4 and fibrosis stage ≥2 (refs. n = 539 within the full cohort). The sensitivity and specificity of NIS4 for this diagnosis were 78.1% and 73.6%, respectively, with an AUROC of 0.815 at the optimal cutpoint (Table P < 0.001 NIS4 versus both) . OWLiver provided the results in categorical format, which did not permit generation of an AUROC; it diagnosed NASH with a sensitivity of 77.3% and a specificity of 66.8%.NIS4 and the OWLiver tests had an intended use to diagnose NASH (Extended Data Table P < 0.001). The specificity and sensitivity of NIS4 were 57.8% and 46.2%, respectively, when sensitivity and specificity were locked at 90%. Under both conditions, the diagnostic performance of NIS4 was significantly superior to ALT (P < 0.001 for both) (Table A high NAFLD activity score (NAS) is a component of at-risk NASH. The AUROC  for NIS4 was significantly superior to ALT , the comparator for panels intended to diagnose high activity (h) Table .19). NIS4 (P < 0.001), ELF (P < 0.01) and FibroMeter VCTE (P < 0.001) were all significantly superior to FIB-4. However, the overall AUROC for PROC3 was not superior to FIB-4. Similar data were obtained when the performance of these panels with sensitivity and specificity constrained at 90% were evaluated , ELF 0.828), PROC3 (0.8) and FibroMeter VCTE (0.841). Their respective sensitivity and specificity at their Youden cutoff are provided in Table 8, PROC3 P < 0.001 versus FIB4), PROC3  versus FIB-4) and FibroMeter VCTE . A secondary analysis of NIS4 for advanced fibrosis provided an AUROC of 0.78 (P = NS versus FIB4). The sensitivity with specificity fixed at 90% were 50.3% and 54.2%, whereas the specificity was 55.3% and 59.6% with sensitivity fixed at 90% for ELF and FibroMeter VCTE, respectively; for both analyses, ELF and FibroMeter VCTE were superior to FIB-4  , ELF  and 0.897 for FibroMeter VCTE (P = 0.002 versus FIB-4). The sensitivity of ELF and FibroMeter VCTE at the Youden cutpoint were 82.1% and 94.2%, and the specificities were 73.3% and 70.4%, respectively. Their performance at 90% sensitivity  and 90% specificity  were also significantly superior to FIB-4  , advanced fibrosis (≥stage 3) and cirrhosis (stage 4) in individuals with NAFLD. These data inform the development and approval of the full qualification plan that will define the final set of studies needed for regulatory approval for diagnostic enrichment tools for NASHThis study has implications for the approval of biomarkers for diagnostic evaluation of at-risk NASH and its components. The definition of the sensitivity and specificity for each biomarker for each of its intended uses in individuals with NAFLD sets the stage for its validation in other cohorts, retrospective and prospective, with varying prevalence of each phenotype evaluated as the final step for qualification. The current study was a first step to determine if the biomarker panels not only identified the relevant phenotypes based on their intended use but also if they were superior to some commonly used clinical laboratory tools, such as ALT and FIB-4. These will serve as criteria, to be finalized with feedback from the FDA, to move the panels with the most promising performance metrics to the final qualification steps.5.Another implication of the current study is that, along with the approved letter of intent, it establishes a roadmap for qualification of biomarkers for diagnostic enrichment. This regulatory roadmap is also likely to be used by other panels, such as FAST, ADAPT and Agile, that were developed after NIMBLE was initiated and are also strong candidates to be moved forward for qualification. The establishment of qualified biomarkers for diagnostic enrichment will also set the stage for their use for disease monitoring and treatment response biomarkers, which will be critically needed to establish a surrogate endpoint based on NITs alone. In this respect, the diagnosis of cirrhosis is particularly relevant because progression to cirrhosis as assessed histologically is already a generally accepted surrogate endpoint to assess therapeutic efficacy24. Using these tests to identify patients for clinical trials in such settings is likely to have many false positives, resulting in high screen fail rates. The negative predictive value (NPV) for FIB4, as well as all of the biomarker panels evaluated, ranged from 98% to 99.7% when the population prevalence of advanced fibrosis was 1%  has been shown to identify individuals with NASH and advanced fibrosis or at-risk NASH, respectively, and may provide such toolsFor patients with advanced fibrosis or cirrhosis, a mistaken diagnosis of absence of these phenotypes may cause them to be followed without surveillance for hepatocellular cancer or gastro-esophageal varices, which are needed for those with cirrhosis. The overall high NPVs suggest that the risks are, in general, low. Conversely, overdiagnosis due to modest PPVs may result in redundant additional testing, including liver biopsy with its associated risks. ELF and FibroMeter VCTE can identify 82–94% of true-positive cases of cirrhosis but may also overdiagnose some patients for cirrhosis in clinics with high prevalence of cirrhosis ) and baseline samples from clinical trials (PIVENS and FLINT) across 12 NIDDK NASH CRN clinical sites . It is a post hoc analysis of samples and clinical–histological data from selected individuals from these studies who met the criteria for the current study. These studies were approved by the individual site institutional review boards (IRBs) for these studies, and all patients provided informed consent, including the use of their blood samples for additional analyses. The current study was performed on a de-identified clinical dataset and on blood samples of such individuals who had blood samples drawn and frozen within 180 d of a liver biopsy. A list of individual site IRB approvals is provided as Supplementary Table This study was approved as an ancillary study of the NASH CRN, and the study samples were curated from the NASH CRN biorepository that was linked to the DB1 and DB2 registry studies and from baseline samples from the PIVENS and FLINT trials NASH (borderline or definite)NAS ≥4Clinically significant fibrosis (fibrosis stage ≥2)Advanced fibrosis (stages 3 or 4)Cirrhosis (stage 4)In individuals with NAFLD or with risk-factors for NAFLD, to serve as a diagnostic enrichment tool for the identification of various histological phenotypes of NAFLD, intended for selection for participation in NAFLD/NASH clinical trials and/or drug treatment. Individuals who were overweight or obese, or who had other features of metabolic syndrome, were considered to be at risk for NAFLD30. The histological data from the CRN database were used for this analysis.The study population was curated from the CRN patient base to ensure sufficient number of individuals with and without the histological phenotypes of interest and a balanced distribution of fibrosis stages to avoid fibrosis spectrum bias. These included patients with biopsy-proven NAFLD who had stored serum obtained within 180 d of a liver biopsy. Patients were derived from four different NASH CRN studies; these included the non-interventional registry studies (DB1 and DB2) and the PIVENS and FLINT clinical trials. The results of the clinical trials were previously published. For patients in DB2, baseline biopsy and serum samples were used from the time of entry, whereas, for DB1, biopsies performed both at baseline and during follow-up were considered. For the clinical trials, only baseline samples and biopsy data before randomization were included. The liver biopsies had already been read and scored by the pathology committee of the NASH CRN using previously published methodsThe study population was specifically curated to include enough patients with or without clinically significant fibrosis (≥stage 2), advanced fibrosis (≥stage 3) or cirrhosis (stage 4) to be powered to robustly assess sensitivity and specificity. It is important to note that this does not reflect the prevalence of advanced fibrosis in the general population or even routine clinic populations, and the sensitivity and specificity data from this study will be used to confirm the predictive values of the biomarker panels for their intended uses in the final qualification step in stage 2 of NIMBLE. The current analysis included aliquots from a serum sample obtained within 180 d of an evaluable liver biopsy demonstrating NAFLD. For FibroMeter VCTE, a liver stiffness measurement was required within 180 d of the biopsy. Exclusion criteria included pregnancy at the time of sample collection or biopsy, comorbid liver diseases, use of drugs known to cause steatosis, non-availability of minimum required serum, bariatric surgery within 3 years before biopsy, prior liver transplant and known primary or secondary malignancy of the liver.Serum biomarker panels selected by the NIMBLE circulating workstream were reviewed and approved by the project team, NASH CRN ancillary study and steering committees and accepted by the FDA in the letter of intent for their qualification. These included:34: based on mir34a, hemoglobin A1c, α2-macroglobulin and YKL-40NIS435: based on triglyceride species with variable number of saturated fatty acidsOWLiver36: based on type III procollagen peptide, hyaluronic acid and TIMP-1ELF test37: procollagen-3 fragment reflective of fibrogenesisPROC338: based on liver stiffness measurement by VCTE, age, gender, α2-macroglobulin, international normalized ratio (INR), platelet count, AST and gamma-glutamyl transferase (GGT)FibroMeter VCTEThe intended use of NIS4 was to diagnose at-risk NASH and its components, whereas the OWLiver panelsʼ intended use was to diagnose the presence of NASH , which deposited these in the CRN data warehouse. The CRN then released the meta-data linked to the barcodes to Cytel, which implemented the prespecified statistical analysis plan without involvement of individual vendors whose panels were tested. The NIMBLE circulating workstream and statistical team then jointly reviewed the results and interpreted the data.The study plan was summarized in a letter of intent approved by the FDA31. The key measures included the presence of steatohepatitis and individual severity grades for steatosis (0–3), lobular inflammation (0–2), hepatocellular ballooning (0–2) and fibrosis stage (0–4). The NAS was computed from the scores for steatosis, ballooning and inflammation, whereas ‘at-risk’ NASH was computed from the presence of its components39.The pathology committee of the NASH CRN performed the histological assessment, masked to clinical and laboratory data, using an established and validated protocol19. The rationale for the use of ALT as a marker of liver injury is that it has been used by the general medical community for this purpose for many decades despite its limitations in the context of NAFLD. FIB-4 was used as the comparator for fibrosis because it is a widely available test that does not require special testing. Although VCTE is widely used in clinical practice, it is not approved by the FDA or the European Medicines Agency as a diagnostic tool for any stage of fibrosis. It was, therefore, not permissible to use it as the comparator, and a VCTE-based test, FibroMeter VCTE, was one of the panels being tested. The imaging workstream of NIMBLE will separately report on VCTE and other ultrasound-based tools and also magnetic resonance imaging (MRI)-based measures. It is important to note that, if the biomarker panels could not outperform these very simple tools, they would not move forward with additional qualification efforts. The sensitivity and specificity were computed at the Youden cutpoint. The sensitivity was further estimated, keeping specificity fixed at 90%, and, conversely, specificity was measured, keeping the sensitivity fixed at 90%. Finally, the PPVs and NPVs were computed at various prevalence of specific NAFLD phenotypes. Missing data were assumed to be missing at random from the statistical analysis, as they resulted from sample handling and laboratory issues independent of the relationship between biomarkers and histology; complete case analysis was done.Two pre-specified performance metrics formed the basis for hypothesis testing. First, that the AUROC for each panel would be 0.7 or higher for its intended use with 95% confidence limits that would not intersect 0.5. Next, the biomarker performance would be superior to commonly used blood-based laboratory aids for their intended use. The AUROC of each panel was, therefore, compared to that of ALT for diagnosis of NASH or NAS ≥4 and FIB-4, a commonly used laboratory aid based on age, AST, ALT and platelet counts, for diagnosis of fibrosis severityFurther information on research design is available in the Any methods, additional references, Nature Portfolio reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at 10.1038/s41591-023-02539-6.Supplementary InformationList of IRB protocol approval numbers per study and siteReporting Summary


TET2 -/- and increased survival of JAK2 V617F cells. Mutations in TET2 and JAK2 are frequently observed in clonal hematopoiesis of indeterminate potential (CHIP), a phenomenon characterized by somatic mutations in hematopoietic stem and progenitor cells and associated with increased risk for myeloid malignancy, cardiovascular disease, and all-cause mortality  as compared to air. Further, the authors observed a corresponding quantitative decrease in the hematopoietic stem cell compartment, but not one that was not functionally apparent in re-population assays.TET2 and ASXL1, propagating an inflammatory milieu that provides a selective growth advantage to existing CHIP clones  as compared with non-WTC firefighters . In miceASXL1. The two genes modeled in the current study, TET2 and JAK2, have not been found to be associated with smoking in large population studies from the UK BioBank and a cohort of cancer patients from Memorial Sloan Kettering Cancer Center  and of particular risk for neoplastic progression . So, forDN conceived and wrote the first draft and JM edited and revised the manuscript.