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Nicotinamide N-Methyltransferase Expression Decreases in Iron Overload, Exacerbating Toxicity in Mouse Hepatocytes
Tiago Koppe,1–3 Bonnie Patchen,1–3 Aaron Cheng,1–3 Manoj Bhasin,3,4 Chris Vulpe,5 Robert E. Schwartz,6 Jose Maria Moreno-Navarrete,7,8 Jose Manuel Fernandez-Real,7,8 Pavlos Pissios,9 and Paula G. Fraenkel1–3
Iron overload causes the generation of reactive oxygen species that can lead to lasting damage to the liver and other organs. The goal of this study was to identify genes that modify the toxicity of iron overload. We studied the effect of iron overload on the hepatic transcriptional and metabolomic profile in mouse models using a dietary model of iron overload and a genetic model, the hemojuvelin knockout mouse. We then evaluated the correlation of nicotinamide N-methyltransferase (NNMT) expression with body iron stores in human patients and the effect of NNMT knockdown on gene expression and viability in primary mouse hepatocytes. We found that iron overload induced significant changes in the expression of genes and metabolites involved in glucose and nicotinamide metabolism and that NNMT, an enzyme that methylates nicotinamide and regulates hepatic glucose and cholesterol metabolism, is one of the most strongly down-regulated genes in the liver in both genetic and dietary iron overload. We found that hepatic NNMT expression is inversely correlated with serum ferritin levels and serum transferrin saturation in patients who are obese, suggesting that body iron stores regulate human liver NNMT expression. Furthermore, we demonstrated that adenoviral knockdown of NNMT in primary mouse hepatocytes exacerbates ironinduced hepatocyte toxicity and increases expression of transcriptional markers of oxidative and endoplasmic reticulum stress, while overexpression of NNMT partially reversed these effects. Conclusion: Iron overload alters glucose and nicotinamide transcriptional and metabolic pathways in mouse hepatocytes and decreases NNMT expression, while NNMT deficiency worsens the toxic effect of iron overload. For these reasons, NNMT may be a drug target for the prevention of iron-induced hepatotoxicity. (Hepatology Communications 2017;1:803-815)

Introduction
I ron is a critical element in all mammals. It is required for the transport of oxygen throughout the body, for DNA synthesis, and for respiration. Because of its ability to catalyze the production of reactive oxygen species by way of the Fenton reaction,(1) iron excess causes tissue injury and even organ failure. As mammals have no active means of excreting iron, iron homeostasis is regulated by adjusting the amount

of iron absorbed from the diet in the duodenum or released from storage in macrophages. This is accomplished by hepcidin, an iron regulatory peptide hormone that interacts with the iron exporter ferroportin (SLC40a1) to cause its internalization and degradation.(2) The liver is the major source of hepcidin; thus, the liver plays a critical role in sensing and responding to systemic iron overload. Iron sensing in the mouse or human liver occurs through increases in bone morphogenic protein (BMP) expression and activation of

Abbreviations: BMP, bone morphogenic protein; FABP, fatty acid binding protein; FAC, ferric ammonium citrate; FBS, fetal bovine serum; FDR, false discovery rate; FTH, ferritin heavy chain; HJV, hemojuvelin; LC-MS, liquid chromatography–mass spectrometry; LC-MS/MS, tandem liquid chromatography–mass spectrometry; MNAM, N1-methylnicotinamide; NAD1, nicotinamide adenine dinucleotide; NADH, reduced nicotinamide adenine dinucleotide; NADP, nicotinamide adenine dinucleotide phosphate; NAM, nicotinamide; NNMT, nicotinamide N-methyltransferase; PPAR, peroxisome proliferator activated-receptor; SAH, S-adenosyl homocysteine; SAM, S-adenosyl methionine; shRNA, short hairpin RNA; Smad, mothers against decapentaplegic; WT, wild type.
Received March 17, 2017; accepted August 1, 2017. Additional Supporting Information may be found at onlinelibrary.wiley.com/doi/10.1002/hep4.1083/full.

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mothers against decapentaplegic (Smad) signaling.(3-5)
The BMP coreceptor hemojuvelin (HJV) interacts
with BMP receptors on the hepatocyte membrane to
potentiate Smad signaling and increase transcription of
hepcidin. Deficiency in hepcidin or HJV is associated
with iron overload both in human patients and in mouse models.(6-9)
As the prevalence of obesity is rising throughout the developed world and is associated with increased rates of diabetes, hyperlipidemia, and steatohepatitis, the interplay of energy metabolism and iron metabolism is an increasing area of interest.(10) Obesity has been associated with iron deficiency and an impaired response to oral iron supplementation in children and adolescents.(11-13) Although the mechanisms governing the effect of obesity on iron absorption are not completely understood, obesity has been associated with lower serum iron levels but higher serum levels of C-reactive protein, transferrin receptor, ferritin, hepcidin, leptin, and interleukin-

6.(14-16) On the other hand, increased body iron
stores are associated with an increased risk of diabetes mellitus(17) and alterations in hepatic glucose metabolism.(17)
Niacin, also known as vitamin B3, includes nicotinic acid and nicotinamide (NAM).(18) It is an essential
vitamin that has been used for many years to reduce serum cholesterol levels.(19) NAM is a precursor for
nicotinamide adenine dinucleotide (NAD1), the
cofactor for numerous enzymes involved in the oxida-
tion of energy sources and the conversion of carbohydrates to lipids.(18,20) The enzyme nicotinamide
N-methyltransferase (NNMT) (Fig. 1A), alters NAM
to N1-methylnicotinamide (MNAM) using the uni-
versal methyl donor S-adenosyl methionine (SAM).
SAM is converted in the process to S-adenosyl homocysteine (SAH).(21,22) Recent studies have demon-
strated that NNMT deficiency in adipocytes protects
against diet-induced obesity by increasing energy

Supported by the National Institutes of Health (R01 DK085250 to P.G.F.; R01 GM083198 to C.V. and P.G.F.; DK083694 to P.P.; K08 DK101754 to R.E.S.), Conselho Nacional de Desenvolvimento Cientifico e Tecnologico, Brazil (to T.K.), the Harvard College Research Program (to A.C.), the Spanish Ministry of Health (FIS 2015-01934) and Centro de Investigacion Biomedica en Red de Fisiopatologıa de la Obesidad y la Nutricion (an initiative of the Instituto de Salud Carlos III; to J.M.F.), and the Alice Bohmfalk Charitable Trust (to R.E.S.).
Funding sources played no role in the design of the research, writing of the report, or the decision to publish. Copyright VC 2017 The Authors. Hepatology Communications published by Wiley Periodicals, Inc., on behalf of the American Association for the Study of Liver Diseases. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. View this article online at wileyonlinelibrary.com. DOI 10.1002/hep4.1083
Potential conflict of interest: Dr. Fraenkel currently receives salary support from Sanofi, but Sanofi did not fund or design this research and has no commercial interest in this project or responsibility for its content.

ARTICLE INFORMATION:
From the 1Division of Hematology/Oncology and 2Cancer Research Institute, Beth Israel Deaconess Medical Center, Boston, MA; 3Department of Medicine, Harvard Medical School, Boston, MA; 4Division of Interdisciplinary Medicine and Biotechnology, Beth Israel Deaconess Medical Center, Boston, MA; 5Department of Physiological Sciences, University of Florida, Gainesville, FL; 6Division of Gastroenterology and Hepatology, Weill Cornell Medical School, New York, NY; 7Department of Diabetes, Endocrinology and Nutrition, Institut d’Investigacio Biome`dica de Girona, Hospital de Girona Dr. Josep Trueta and Universitat de Girona, Girona, Spain; 8CIBER Fisopatologia de la Obesidad y Nutricion, Instituto de Salud Carlos III, Madrid, Spain; 9Division of Endocrinology, Beth Israel Deaconess
Medical Center, Boston, MA.

ADDRESS CORRESPONDENCE AND REPRINT REQUESTS TO:

Paula G. Fraenkel, M.D. Division of Hematology/Oncology Beth Israel Deaconess Medical Center, CLS 428 330 Brookline Avenue Boston, MA 02215 E-mail: pfraenkel@post.harvard.edu Tel: 1 1-857-998-1785 or

Pavlos Pissios, Ph.D. Division of Endocrinology Beth Israel Deaconess Medical Center, CLS 734 330 Brookline Avenue Boston, MA 02215 Tel: 1 1-617-735-3278 E-mail: ppissios@bidmc.harvard.edu

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FIG. 1. Mouse models reveal the interactions of iron overload and cellular metabolism. (A) The function of NNMT. NNMT catalyzes the methylation of NAM to MNAM and converts the methyl donor SAM to SAH. (B) Dietary and genetic models of iron overload. For the dietary iron-overload model, 5-weekold WT C57BL6 male mice were placed on a soy-free diet (AIN-93G) that was iron deficient (2.5 mg/kg, n 5 3), iron sufficient (37.5 mg/kg, n 5 3), or high iron (1,000 mg/kg, n 5 3). For the genetic iron-overload model, 5-week-old mice that were either WT or HJV–/– gene mice (n 5 2 per group) were maintained on the iron-deficient diet (2.5 mg/kg iron). After 50 days, the mice were killed and RNA and polar metabolites were extracted for next-generation sequencing or LC-MS/ MS analysis, respectively.


expenditure, while NNMT in hepatocytes regulates glucose, lipid, and cholesterol metabolism.(21,22)
In this report, we employed RNA sequencing and metabolomic approaches to identify the pathways affected by iron overload in mouse hepatocytes. We found that pathways regulating glucose and NAM metabolism were significantly altered in both a dietary model of iron overload and a genetic model, the HJV knockout mouse, and that NNMT was significantly down-regulated in both models. In a group of obese patients, we discovered that hepatic NNMT transcript levels inversely correlated with measures of body iron stores, including serum iron, serum ferritin, and serum transferrin saturation levels. Furthermore, we demonstrated that iron loading human or mouse hepatocytes in vitro suppressed NNMT expression. Adenoviral knockdown of NNMT expression in mouse hepatocytes enhanced iron-induced cytotoxicity and increased expression of genes responsive to oxidative or endoplasmic reticulum stress. Taken together, these findings indicate that hepatocyte iron overload suppresses NNMT transcript levels, which in turn exacerbates the toxic effects of iron.

Materials and Methods
MOUSE STRAINS, RNA PREPARATION, AND MEASUREMENT OF NONHEME IRON LEVELS
Ethical approval was obtained from the institutional animal care and use committee of Beth Israel Deaconess Medical Center (Animal Welfare Assurance #A3153-01; Boston, MA) in accord with national and international guidelines. All wild-type (WT) mice were C57BL6 males (Jackson Laboratory, Bar Harbor, ME). Professor Nancy Andrews (Jackson Laboratory) provided HJV knockout (HJV2/2) mice on a C57BL6 background.(7) For the dietary study, at 5 weeks of age, the mice were transitioned to a soy-free diet (AIN93G; Bioserv, Flemington, NJ) containing different amounts of iron per kilogram of food: iron deficient (2.5 mg/kg, n 5 3), iron sufficient (37.5 mg/kg, n 5 3), or iron excess (1,000 mg/kg, n 5 3). For the genetic study, 5-week-old mice that were either WT or HJV–/– (n 5 2 mice per group) were maintained on the irondeficient diet. After 50 days, the mice were killed and

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liver RNA was extracted using the RNeasy Mini Kit (Qiagen, Valencia, CA) according to the manufacturer’s instructions. Hepatic nonheme iron stores were measured using the bathophenanthroline method as described.(23)
RNA SEQUENCING

distinct sample groups were compared by fitting a lin-
ear model for each variable (normalized expression val-
ues) and applying empirical Bayes smoothing to
identify differentially expressed molecules. For path-
way analysis, the differentially expressed molecules (P  0.05 and fold change > 2) were grouped into pathways using Metaboanalyst 3.0.(28)

One microgram of RNA from each sample was sequenced with a HiSeq 2000 (Illumina, Inc., San Diego, CA). Additional bioinformatics and analysis methods are provided in the Supporting Methods. Unsupervised analysis was performed on normalized and preprocessed count data using correlation-based hierarchical clustering and principal component analysis. The normalized count data were compared among groups in an unpaired manner using a negative binomial model to identify differentially expressed genes. The differentially expressed genes were identified on the basis of false discovery rate (FDR) and fold change. To identify the set of genes depicting a strong association with iron dose (i.e., low, iron sufficient, and high), the differential expression profiles from the different groups were further analyzed using self-organizing map clustering.(24) In the genetic iron-overload experiment, an FDR <0.05 and a mean fold change >2 were used to reveal genes that were differentially expressed compared to WT mice. All raw and processed RNA sequencing data can be found at http:// www.ncbi.nlm.nih.gov/geo/ under accession numbers GSE86236 and GSE86292.
Pathway analysis was performed using DAVID Bioinformatics Resources 6.7.(25,26)
METABOLOMICS SAMPLE PREPARATION AND ANALYSIS
We extracted 5-10 mg mouse liver tissue in 80% high-performance liquid chromatography-grade methanol, as described, then lyophilized and resuspended the extract in 20 mL of liquid chromatography–mass spectrometry (LC-MS)-grade water. Next, 5-10 mL of each sample was autoinjected into the QTRAP 5500 tandem LC-MS (LC-MS/MS) system (AB Sciex, LLC, Framingham, MA). Multiquant 2.0 software (AB Sciex, LLC) was used to quantify chromatographic peak areas. The Linear Models for Microarray Analysis package(27) from the Bioconductor project was used to identify differentially expressed molecules among different groups compared to controls. Technical replicates were averaged, and the biologically

QUANTITATIVE REAL-TIME REVERSE-TRANSCRIPTION POLYMERASE CHAIN REACTION
We extracted RNA and generated complementary DNA according to the described method(29) to measure the transcript levels of hepcidin, NNMT, and other genes by quantitative real-time reverse-transcription polymerase chain reaction using primers and probes as described (Supporting Table S1 or available on request). Data shown are means 6 SEM unless otherwise indicated. Student t tests were performed using Prism 6.0c (Graphpad, San Diego, CA). P < 0.05 was considered a significant result.
PRIMARY HUMAN HEPATOCYTES
Cryopreserved human hepatocytes (BioreclamationIVT LLC, Waterbury, NY) were plated at 2 3 105 hepatocytes per well in tissue culture-treated 24-well polystyrene plates (Eppendorf, Hauppauge, NY) coated with rat tail type I collagen (50 lg/mL) patterned into microdomains as described.(30) The hepatocytes were cultured in Dulbecco Modified Eagle Media with high glucose, 10% fetal bovine serum (FBS), 1% insulin, transferrin, selenous acid premix (#354352; BD Biosciences, Bedford, MA), glucagon 7 ng/mL, dexamethasone 40 ng/mL, and 1% penicillin–streptomycin. Seeding of 3T3-J2 murine embryonic fibroblasts (9 3 104 cells in each well of a 24-well plate) occurred 12 hours after initial hepatocyte plating and was followed by replacement of hepatocyte culture medium and addition of ferric ammonium citrate (FAC; Sigma-Aldrich, St. Louis, MO) 24 hours after initial plating. At 24 or 48 hours after initial iron supplementation, cells were either fixed with 4% paraformaldehyde for 15 minutes or lysed for RNA extraction using the RNeasy kit (Qiagen). After washing the fixed cells with phosphate-buffered saline twice, the hepatocytes were stained with HCS Deep Red LipidTOX neutral lipid stain (Thermo Fisher, Waltham, MA), which was added to each well (1:500) for 30 minutes.

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The hepatocytes were then imaged using a Nikon and ferritin levels were determined as described in

Eclipse Ti-E microscope.

Supporting Methods.

ADENOVIRAL VECTORS
Adenoviral vectors containing NNMT complementary DNA or short hairpin RNA (shRNA) against NNMT were constructed previously as described(22) and purified by two rounds of cesium chloride centrifugation. Control viruses contained either green fluorescent protein or irrelevant shRNA. The titers of the purified viruses ranged from 5 3 1010 to 20 3 1010 plaque-forming units/mL.
PRIMARY MOUSE HEPATOCYTE ISOLATION, CULTURE, AND ADENOVIRUS KNOCKDOWN
Primary mouse hepatocytes were isolated from 8week-old C57BL6 male mice by the collagenase perfusion method. Viable hepatocytes were enriched by Percoll gradient centrifugation. The hepatocytes were seeded on collagen-coated plates at a density of 300,000/mL in Williams’ E medium/5% FBS. After a 4-hour attachment period, the medium was replaced with fresh Williams’ E medium/5% FBS. Primary hepatocytes were infected by overnight exposure to adenovirus in Williams’ E medium at a multiplicity of infection of 3 or 10. For NNMT knockdown, the hepatocytes were cultured for 96 hours to allow for the degradation of the endogenous protein. The medium was supplemented with FAC 0-150 lM 24 hours prior to the assessment of viability or extraction of RNA. Viability was assessed using 3-(4,5-dimethylthiazol 2yl)-2,5-diphenyltetrazolium bromide as described.(31)
HUMAN SUBJECT RECRUITMENT
The human subject cohort comprised 53 morbidly obese subjects (9 men, 44 women) undergoing elective bariatric surgery at the Endocrinology Service of the Hospital Universitari de Girona Dr. Josep Trueta (Girona, Spain) as described.(22) All subjects gave written informed consent as part of a research protocol validated and approved by the ethical committee of the Hospital Universitari Dr. Josep Trueta (Comite` d’Etica d’Investigacio Clınica, approval number 2009046) in accordance with the ethical guidelines of the 1975 Declaration of Helsinki. Liver samples and sera were collected at the time of surgery. RNA was extracted, and serum iron, total iron binding capacity,

Results
RNA SEQUENCING IDENTIFIED DIFFERENTIALLY REGULATED GENES IN HEPATIC IRON OVERLOAD
The HJV2/2 mouse exhibits marked hepcidin deficiency that causes a severe iron-overload phenotype resembling the human disease juvenile hemochromatosis. While this provides a useful animal model for iron overload, we also wanted to use a model in which hepcidin transcripts increase in response to iron overload. To achieve this, C57BL6 mice were fed diets containing 2.5, 37.5, or 1,000 mg of iron per kilogram of food to produce iron deficiency, iron sufficiency, or iron overload, respectively (Fig. 1B). After 50 days, the mice were sacrificed and hepatic messenger RNA was extracted for next-generation sequencing while polar hepatic metabolites were isolated for analysis by LC-MS/MS. The RNA integrity number for each sample was >6. Assessments of read duplication, base call frequency, and read quality indicated excellent quality of the data.
As expected, hepatic iron levels rose with increasing iron content in the diet (1.4-fold for iron-sufficient versus iron-deficient diet and 3.1-fold for high-iron versus iron-deficient diet, n 5 3 per group; P 5 0.001 for high-iron diet versus iron-deficient diet) or in the HJV2/2 cohort (18.5-fold for HJV2/2 versus WT, n 5 2 per group; P 5 0.006) (Fig. 2A,D). Liver hepcidin transcript levels also increased with increasing dietary iron content (Fig. 2B) in the WT mice (8-fold for iron-sufficient versus iron-deficient diet and a further 2.6-fold for high-iron versus iron-sufficient diet; P 5 0.011 for iron-sufficient versus iron-deficient diet and P 5 0.001 for iron-sufficient versus high-iron diet). As expected, hepcidin expression was significantly reduced in the HJV2/2 mice (Fig. 2E).
NNMT EXPRESSION DECREASED IN THE LIVERS OF BOTH NUTRITIONALLY AND GENETICALLY IRON OVERLOADED MICE
For the dietary iron-overload study, we used selforganizing maps to identify transcripts that expressed a

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FIG. 2. Dietary and genetic models of iron overload exhibit increased hepatic iron stores and decreased NNMT expression. (A,D) Nonheme iron assays, (B,E) quantitative real-time reverse-transcription polymerase chain reaction analysis of hepcidin, and (C,F) NNMT transcript levels for the (A-C) dietary iron overload, (D-F) HJV–/– mice, and controls. Hepcidin and NNMT expression are reported as fold change over control mice with (B,C) an iron-sufficient diet (37.5 mg/kg) or (E,F) WT mice. Data shown are means 1/2 standard error measurements. * denotes P < 0.05 and ** denotes P < 0.01 by Student t test compared to the (A,B) low-iron group, (C) the iron-sufficient group, or (D-F) WT; n 5 3 mice per group for (A-C) and 2 mice per group for (D-F). Abbreviations: G3PD, glyceraldehyde 3-phosphate dehydrogenase; KO, knockout.



strong association with increasing iron dose, while for the HJV2/2 mice, we used FDR <0.05 and a mean fold change >2 to identify differentially regulated transcripts. We found 128 transcripts that were differentially regulated in the dietary iron study, while 688 transcripts were differentially regulated in the genetic model of iron overload. A total of 28 genes were differentially regulated in both the dietary and genetic ironoverload models. Of these genes, expression level changed in the same direction for 13 genes and in opposite directions for 15 genes (Table 1). Of the genes that were negatively regulated in both models, NNMT was the second most strongly suppressed in both the dietary and genetic iron-overload models. This effect appeared to be hepcidin independent as the dietary iron-overload model exhibits high hepcidin levels while the HJV2/2 mice exhibit low hepcidin levels. We used quantitative real-time polymerase chain reaction to confirm the change in gene expression in both cohorts of mice. NNMT transcript levels decreased significantly in both the dietary and genetic models of iron overload (Fig. 2C,F). Using the DAVID 6.7

algorithm,(25,26) we found that two pathways were significantly altered in the genetic iron-overload model, peroxisome proliferator activated-receptor (PPAR) signaling and Huntington’s disease genes (Table 2). The differentially regulated genes included genes involved in energy metabolism and apoptosis, including several NAM-dependent genes, e.g., malic enzyme 1 (ME1) and reduced NAD [NADH]:ubiquinone oxidoreductase core subunits (Ndufa2, Ndufa7, Ndufb7, and Ndufs7).
ANALYSIS OF METABOLOMIC CHANGES CAUSED BY IRON OVERLOAD
The levels of polar metabolites extracted from the liver were compared between the dietary and genetic models of iron overload and their respective controls to identify the metabolites with absolute fold change >2 and P values 0.05 (Supporting Tables S2-S4). These metabolites were then grouped into pathways using Metaboanalyst 3.0 and ordered by P value. This analysis revealed that pathways involved in glucose and NAM metabolism were

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TABLE 1. TRANSCRIPTS IDENTIFIED AS SIGNIFICANTLY ALTERED IN EXPRESSION IN
BOTH DIETARY AND NUTRITIONAL IRON-OVERLOAD EXPERIMENTS

Gene

Dietary Iron Overload, SOM Vector

Genetic Iron
Overload,
Log2 Fold Change

Q Value*

Direction†

Bhmt Nnmt Tfrc Mup21 Hapln4 Serpina12 Cyp17a1 Apoa4 Robo1 Gbp6 Kbtbd11 Id3 Bmp6 Igfals Syt3 Extl1 Zap70 Serpinb8 Slco1a4 Slc10a2 Pdzk1ip1 Krt23 Fabp5 Gpr110 Hamp2 (HJV) Vtcn1 Lpl Hamp (Hepcidin)

22.06 22 21.99 21.94 21.93 21.78 21.56 21.43 21.33 20.75
1.59 1.84 2.05 22.19 22.09 21.9 21.8 21.64 21.51 21.48 1.28 1.38 1.78 2.01 2.02 2.02 2.04 2.13

21.41 23.35 22.89 21.12 21.29 24.69 21.72
2.37 22.31 21.55
1.9 2.08 2.28 1.62 2 2.16 1.39 3.19 1.25 2.26 22.14 22.26 21.86 21.45 24.23 3.55 21.04 26.41

0.0081 0.0022 0.0022 0.0104 0.0469 0.0022 0.0022 0.0022 0.0022 0.0104 0.0442 0.0104 0.0104 0.0022 0.035 0.0022 0.0437 0.0022 0.0056 0.0022 0.0337 0.0022 0.0022 0.0293 0.0022 0.0359 0.0355 0.0437

S S S S S S S S S S S S S O O O O O O O O O O O O O O O

The change in transcription is expressed as an SOM vector relative to the WT animals and log2 fold change relative to the low iron diet for the dietary iron overload and the genetic ironoverload models, respectively. *Q value is the false discovery rate for the genetic iron-overload study. †S represents transcripts that changed in the same direction; O represents transcripts that changed in opposite directions in the two models of iron overload. Abbreviation: SOM, self-organizing map.

most significantly altered in the dietary iron-overload model (Fig. 3A) and were also highly significant in the genetic iron-overload model (Fig. 3B). Among the differentially regulated metabolites, NAM levels were increased in the livers of WT mice fed the high-iron diet compared to mice fed the low-iron diet (Fig. 3C).

EVALUATION OF NNMT TRANSCRIPT LEVELS IN HUMAN LIVERS
To determine if NNMT expression is associated with iron status in humans, we evaluated NNMT and ferritin heavy chain (FTH) transcript levels in liver biopsies

obtained from 53 patients undergoing elective bariatric surgery and compared them to their serum iron indices. We found that NNMT transcript levels inversely correlated with measures of body iron stores (Fig. 4A-D), including serum ferritin (P 5 0.002), percent transferrin saturation (P 5 0.02), and FTH transcript levels (P < 0.0001), while there was an inverse trend with serum iron (P 5 0.06). To validate whether iron loading suppresses NNMT transcript levels in human hepatocytes, we treated primary human hepatocytes with increasing doses of FAC and found a dose-dependent decrease in NNMT expression (Fig. 5A). Similar to our mouse models of iron overload, we observed decreased expression of acyl-coenzyme A synthetase long-chain family members 3 and 5 (ACSL3 and ACSL5) and fatty acid binding protein 4 (FABP4), all targets of PPAR-a signaling (Fig. 5A). Intriguingly, iron overload also increased lipid accumulation in the hepatocytes (Fig. 5B).

KNOCKDOWN OF NNMT EXACERBATES THE TOXICITY OF IRON OVERLOAD, WHILE NNMT OVEREXPRESSION IMPROVES HEPATOCYTE VIABILITY

To evaluate the effects of NNMT suppression on ironinduced toxicity, we infected primary mouse hepatocytes

TABLE 2. TRANSCRIPTS IN THE PPAR AND

HUNTINGTON’S DISEASE SIGNALING PATHWAYS

EXHIBIT LOWER LEVELS IN THE LIVERS OF HJV–/– MICE COMPARED TO WT MICE

Gene

Log2 Fold Change HJV–/– vs WT

Q Value

Pathway

CD36 ACSL3 ACSL5 Cyp4a12b DBI FABP2 FABP4 FABP5 Lpl ME1 Atp5d BBC3 Bax Ndufa2 Ndufa7 Ndufb7 Ndufs7 Cox7a2l, Gm6969 PolR2E PolR2F Gm8566, SOD1 Uqcr11 Uqcrq

20.74 20.73 20.80 20.42 20.79 20.89 20.32 20.54 20.97 20.63
1.83 2.76 1.52 1.33 1.05 2.25 2.38 1.95 1.37 1.85 3.48 2.56 1.97

5.0 3 1025 1.0 3 1024 1.0 3 1024 5.0 3 1025 3.0 3 1024 3.5 3 1024 5.0 3 1025 5.0 3 1025 5.0 3 1025 1.0 3 1024 4.0 3 1024 7.5 3 1024 1.3 3 1023 1.2 3 1023 2.4 3 1023 5.0 3 1025 5.0 3 1025 2.0 3 1024 1.9 3 1024 1.2 3 1023 3.4 3 1023 4.0 3 1024 7.5 3 1024

PPAR PPAR PPAR PPAR PPAR PPAR PPAR PPAR PPAR PPAR Huntington’s Huntington’s Huntington’s Huntington’s Huntington’s Huntington’s Huntington’s Huntington’s Huntington’s Huntington’s Huntington’s Huntington’s Huntington’s

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FIG. 3. Metabolites involved in glucose and NAM metabolism are differentially regulated in response to iron overload. (A,B) All significantly differentially regulated metabolites were grouped into pathways using Metaboanalyst 3.0 in the (A) dietary and (B) genetic iron-overload models and arranged from most significant (red) to least significant (yellow). (C) Heat map demonstrating a significant increase in NAM level in the dietary iron-overload model. Abbreviations: OBP, octulose-1,8-bisphosphate; CoA, coenzyme A.


with an adenoviral vector encoding shRNA targeting
NNMT or a nontargeting control vector and treated the cells with FAC for 24 hours. We confirmed that the adenoviral vector targeting NNMT significantly decreased NNMT expression (Fig. 6A) while overexpression of NNMT increased NNMT transcript levels (Fig. 6B). Knockdown of NNMT enhanced iron-induced toxicity, as shown by decreased viability of iron-treated hepatocytes with NNMT knockdown compared to iron-treated controls infected with a nontargeting vector (Fig. 6C). In contrast, overexpression of NNMT increased primary mouse hepatocyte viability, even in the presence of iron overload (Fig. 6D). NNMT knockdown also significantly increased the iron-induced expression of FTH and markers of oxidative stress (heme oxygenase 1 and

NAD(P)H quinone dehydrogenase 1) and endoplasmic reticulum stress (activating transcription factor 4) (Fig. 6E). In contrast, overexpression of NNMT significantly reduced iron-induced expression of FTH and activating transcription factor 4 (Fig. 6F).
Discussion
SYSTEMS BIOLOGY OF IRON OVERLOAD
Using two different models of hepatic iron overload, we identified a signature of 28 transcripts that are significantly altered in expression in the setting of

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FIG. 4. NNMT transcript levels inversely correlate with measures of iron stores. Patients undergoing elective bariatric surgery provided liver biopsies and serum samples during their surgery to measure NNMT and FTH transcript levels and serum iron indices. Hepatic NNMT transcript levels inversely correlated with (A) serum ferritin level, (B) serum iron level, (C) hepatic FTH transcript level, (D) serum transferrin saturation; n 5 53 patients.


iron overload. This signature includes several expected changes(32) in the transcriptional profile,
including decreased transferrin receptor and increased BMP6 and Id3 (Table 1). Using the HJV2/2 mice,
which developed nearly 10-fold higher hepatic iron
overload than the dietary model, we were able to
identify two pathways that were significantly altered,
Huntington’s disease genes and PPAR signaling
(Table 2). Several genes in both pathways regulate
energy metabolism and require NAM derivatives for their function. ME1, an NADP-dependent enzyme, generates NADPH for fatty acid biosynthesis and decarboxylates malate, thus connecting the glycolytic and citric acid cycles.(33) Ndufa2, Ndufa7, Ndufb7, Ndufs7 encode subunits of NADH:ubiquinone oxidoreductase, i.e., mitochondrial complex I, which transfers electrons from NADH to the respiratory chain.(34) Under conditions of oxidative stress, complex I dissociates from a larger mitochondrial supercomplex, which can result in increased production of reactive oxygen species by complex I.(34)

A recent transcriptional profile of the rat pancreas in the setting of iron overload demonstrated that one of the PPAR signaling targets, Fabp2, which we identified as down-regulated in our mouse model of iron overload, was significantly down-regulated in ironoverloaded rat pancreas.(35) FABPs are thought to play a role in the intracellular transport of long-chain fatty acids and their acyl-coenzyme A esters. Others have shown in mammalian models that iron overload leads to decreased hepatic PPAR-a expression,(36) decreased protein levels of PPAR-a targets,(37) and alterations in protein levels of enzymes involved in glucose metabolism and fatty acid oxidation.(38) Intriguingly, we observed decreased expression of PPAR signaling targets and increased lipid accumulation in iron-treated human hepatocytes (Fig. 5A,B). Conversely, others have demonstrated(39) that iron chelation reduces steatosis and increases PPAR-c levels in the livers of ob/ob mice, a model of obesity and type 2 diabetes mellitus. Thus, it appears that iron overload may promote hepatic steatosis.

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FIG. 5. The effect of iron loading on primary human hepatocytes. Primary human hepatocytes cultured with increasing doses of iron (FAC 0-60 lM) for (A,B) 24 hours or (B) 48 hours followed by harvesting RNA for quantitative real-time reverse-transcription polymerase chain reaction or fixation and staining for intracellular lipid accumulation with HCS Deep Red LipidTOX (Thermo Fisher). (A) Increasing doses of FAC were associated with decreased transcript levels of NNMT and PPAR-signaling targets ACSL3, ACSL5, and FABP4. * denotes P < 0.05, while ** denotes P < 0.01 compared to no iron control. (B) Treatment with increasing concentrations of iron was also associated with increased lipid staining in the hepatocytes on light microscopy. The scale bar denotes 100 mm.


We found that iron overload increased expression of a variety of pro-apoptotic genes implicated in Huntington’s and other neurodegenerative diseases. Among the iron overload-induced genes was Bax, a proapoptotic protein that is regulated by nuclear factor kappa B and p53 signaling.(40) Bax is up-regulated in the cerebral cortex and striatum in the YAC128 mouse model of Huntington’s disease.(41) In our models, iron overload also increased expression of BCL binding component 3, a pro-apoptotic protein that is involved in neurodegeneration.(42)
NNMT DEFICIENCY EXACERBATES THE TOXIC EFFECTS OF IRON OVERLOAD
Given the finding that iron overload altered the levels of transcripts and metabolites involved in energy and NAM metabolism, we were intrigued to study NNMT further. NNMT has gained attention as a

potential drug target in cancer and obesity(21,22,43,44); however, it has not been previously implicated in the pathophysiology of iron overload. We discovered that NNMT is a significantly repressed transcript in both the nutritional iron-overload model and the HJV–/– mouse. In our metabolomic analysis, dietary iron overload decreased hepatic NNMT transcript levels and increased hepatic NAM levels (Fig. 3C), which is consistent with decreased NNMT activity. We found that NNMT transcript levels negatively correlated with body iron stores in human patients (Fig. 4A-D), which indicates that this association of iron overload and NNMT suppression is likely to be conserved across species. Furthermore, we discovered that adenoviral knockdown of NNMT in mouse hepatocytes exacerbated cytotoxicity and enhanced expression of transcripts associated with oxidative damage and endoplasmic reticulum stress (Fig. 6C,E) while overexpression of NNMT partially reversed the toxic effects of iron overload (Fig. 6D,F). Because of the highly

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FIG. 6. NNMT knockdown exacerbates iron’s hepatotoxicity, while overexpression improves viability. Primary mouse hepatocytes underwent (A,C,D) adenoviral knockdown of NNMT (K) or a nontargeting knockdown (C) or (B,D,F) overexpression of NNMT (O) or overexpression of GFP (C) followed by exposure for 24 hours to (A,E) FAC 30 lM, (C) 50-150 lM, (B,D,F) 100 lM, or (A,B,E,F) water and measurement of transcript levels by quantitative real-time reverse-transcription polymerase chain reaction or (C,D) viability by the MTT assay. NNMT knockdown decreased viability in the setting of iron treatment and increased expression of iron-induced transcripts related to oxidative and endoplasmic reticulum stress, while NNMT overexpression increased viability and decreased the expression of FTH and ATF4, which is a marker of endoplasmic reticulum stress. (E,F) Data shown are mean fold change in transcript abundance of iron-treated cells relative to control cells treated with water only, indicated by the dotted line. *, **, *** denote P < 0.05, P < 0.01, or P < 0.001 compared to controls, respectively, by Student t test; n 5 3 biological replicates per group. Abbreviations: ATF4, activating transcription factor 4; GFP, green fluorescent protein; HMOX1, heme oxygenase 1; KD, knockdown; MTT, 3-(4,5-dimethylthiazol-2yl)-2,5-diphenyltetrazolium bromide; NQO1, NAD(P)H quinone dehydrogenase 1; OE, overexpression.


variable NNMT expression in human livers (Fig. 4), we hypothesize that individuals with low NNMT expression may be predisposed to the adverse consequences of iron overload.
Whether genetic polymorphisms in NNMT increase the risk of liver and cardiovascular disease is an area of ongoing investigation. NNMT’s action generates SAH, which is converted to homocysteine through

SAH hydrolase.(45) Genetic variation in the NNMT locus has been linked to hyperhomocysteinemia,(45) a risk factor for cardiovascular disease. Over 200 single nucleotide polymorphisms have been identified, primarily in the noncoding regions of NNMT. One NNMT polymorphism in the noncoding region, rs694539, has been associated with hyperhomocysteinemia(46) and with nonalcoholic steatohepatitis,(47)

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while another polymorphism in the coding region, rs1941404, is associated with hyperlipidemia.(48) The effect of these genetic polymorphisms on iron homeostasis has not yet been explored.
Mechanistically, NNMT regulates cellular metabolism by diverse pathways, including histone and protein methylation,(21,43) and stabilization of the NAD1-dependent deacetylase sirtuin 1 through generation of MNAM,(22) which serves as both a methyl and NAM sink.(49) In cancer cell lines cultured in physiological levels of methionine, NNMT knockdown increases SAM to SAH ratios, which increases protein methylation, while NNMT overexpression has the opposite effect.(43,44) In vivo models of NNMT deficiency have focused on the effects on glucose and lipid metabolism. Antisense knockdown of NNMT in mice that were fed a high-fat diet decreased the extent of obesity and increased methylation of histone H3 lysine 4 in white adipose tissue.(21) Liver-specific knockdown of NNMT in mice fed a high-fat diet increased serum and liver cholesterol levels, but the addition of NNMT’s product MNAM to the diet reversed these effects.(22)
In conclusion, we describe global changes in gene expression and metabolites in genetic and nutritional iron overload and implicate NNMT for the first time in the metabolic effect of iron. In future studies, we hope to identify the mechanisms by which downregulation of NNMT exacerbates the toxic effects of iron overload and determine whether NNMT may be a drug target for iron-overload syndromes.
Acknowledgment: We thank Dr. Jon Asara, Mass Spectrometry Core, Beth Israel Deaconess Medical Center, for performing the metabolomic analysis.
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Supporting Information
Additional Supporting Information may be found at onlinelibrary.wiley.com/doi/10.1002/hep4.1083/full.

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