# Rare Pathogenic Variants in Mitochondrial and Inflammation-Associated Genes May Lead to Inflammatory Cardiomyopathy in Chagas Disease

Maryem Ouarhache, Sandrine Marquet, Amanda Garage Frade, Ariela Mota Ferreira, Barbara Ianni, Rafael Ribeiro Almeida, Joao Paulo Silva Nunes, Ludmila Rodrigues Pinto Ferreira, Oliveira-Carvalho Rigaud, Darlan Cândido, et al.

► To cite this version:

Maryem Ouarhache, Sandrine Marquet, Amanda Garage Frade, Ariela Mota Ferreira, Barbara Ianni, et al. Rare Pathogenic Variants in Mitochondrial and Inflammation-Associated Genes May Lead to Inflammatory Cardiomyopathy in Chagas Disease. Journal of Clinical Immunology, 2021, 10.1007/s10875-021-01000-y. hal-03162042

HAL Id: hal-03162042

https://amu.hal.science/hal-03162042

Submitted on 8 Mar 2021

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
# Rare Pathogenic Variants in Mitochondrial and Inflammation-Associated Genes May Lead to Inflammatory Cardiomyopathy in Chagas Disease

Maryem Ouarhache¹ · Sandrine Marquet¹,² · Amanda Garage Frade³,⁴ · Ariela Mota Ferreira⁵ · Barbara Ianni⁶ ·

Rafael Ribeiro Almeida³,⁴ · Joao Paulo Silva Nunes³,⁴ · Ludmila Rodrigues Pinto Ferreira³,⁴,⁷ ·

Vagner Oliveira-Carvalho Rigaud³ · Darlan Cândido³ · Charles Mady⁶ · Ricardo Costa Fernandes Zaniratto³ ·

Paula Buck⁶ · Magali Torres² · Frederic Gallardo² · Pauline Andrieux² · Sergio Bydlowsky³,⁴ · Debora Levy³,⁴ ·

Laurent Abel⁸,⁹ · Clareci Silva Cardoso¹⁰ · Omar Ribeiro Santos-Junior¹¹ · Lea Campos Oliveira¹² ·

Claudia Di Lorenzo Oliveira¹⁰ · Maria Do Carmo Nunes¹¹ · Aurelie Cobat⁸,⁹ · Jorge Kalil³,⁴ · Antonio Luiz Ribeiro¹¹ ·

Ester Cerdeira Sabino¹² · Edecio Cunha-Neto³,⁴,¹³ ID ·

Christophe Chevillard¹,² IP

Received: 20 November 2020 / Accepted: 15 February 2021

© The Author(s) 2021

## Abstract

Cardiomyopathies are an important cause of heart failure and sudden cardiac death. Little is known about the role of rare genetic variants in inflammatory cardiomyopathy. Chronic Chagas disease cardiomyopathy (CCC) is an inflammatory cardiomyopathy prevalent in Latin America, developing in 30% of the 6 million patients chronically infected by the protozoan *Trypanosoma cruzi*, while 60% remain free of heart disease (asymptomatic (ASY)). The cytokine interferon-γ and mitochondrial dysfunction are known to play a major pathogenetic role. Chagas disease provides a unique model to probe for genetic variants involved in inflammatory cardiomyopathy.

**Methods** We used whole exome sequencing to study nuclear families containing multiple cases of Chagas disease. We searched for rare pathogenic variants shared by all family members with CCC but absent in infected ASY siblings and in unrelated ASY.

**Results** We identified heterozygous, pathogenic variants linked to CCC in all tested families on 22 distinct genes, from which 20 were mitochondrial or inflammation-related – most of the latter involved in proinflammatory cytokine production. Significantly,

Edecio Cunha-Neto and Christophe Chevillard contributed equally to this work.

<figure><img src="image_2.png" /></figure>

Edecio Cunha-Neto
edicunha@gmail.com

<figure><img src="image_3.png" /></figure>

Christophe Chevillard
christophe.chevillard@univ-amu.fr

¹ INSERM, Aix Marseille university, UMR_906, Marseille, France

² Theories and Approaches of Genomic Complexity (TAGC), INSERM, Aix Marseille university, UMR_1090, Parc Scientifique de Luminy, case 928, 163, avenue de Luminy, 13288 Marseille, France

³ Laboratory of Immunology, Heart Institute (InCor), Hospital das Clínicas and Department of Medicine, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, São Paulo, Brazil

⁴ Institute for Investigation in Immunology, iii-INCT, Instituto Nacional de Ciência e Tecnologia, São Paulo, Brazil

⁵ State University of Montes Claros (Universidade Estadual de Montes Claros), Montes Claros, Minas Gerais, Brazil

⁶ Unidade Clínica de Miocardiopatias, Heart Institute (Incor) Faculdade de Medicina FMUSP, Universidade de Sao Paulo, São Paulo, Brazil

⁷ Departamento Morfologia, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil

⁸ Laboratory of Human Genetics of Infectious Diseases, Necker Branch, Necker Hospital for Sick Children, Paris, France

⁹ Imagine Institute, Paris Descartes University, Paris, France

¹⁰ School of Medicine, Federal University of São João del-Rei, Divinopolis, Brazil

¹¹ Hospital das Clínicas and School of Medicine, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil

¹² Department of Infectious Diseases, and Division of Laboratory Medicine (LIM03) and Institute of Tropical Medicine, Faculdade de Medicina FMUSP, São Paulo, Brazil

¹³ Heart Institute, Laboratory of Clinical Immunology and Allergy-LIM60, University of São Paulo School of Medicine, São Paulo, SP, Brazil
incubation with IFN-γ on a human cardiomyocyte line treated with an inhibitor of dihydroorotate dehydrogenase brequinar (enzyme showing a loss-of-function variant in one family) markedly reduced mitochondrial membrane potential (ΔψM), indicating mitochondrial dysfunction.

**Conclusion** Mitochondrial dysfunction and inflammation may be genetically determined in CCC, driven by rare genetic variants. We hypothesize that CCC-linked genetic variants increase mitochondrial susceptibility to IFN-γ-induced damage in the myocardium, leading to the cardiomyopathy phenotype in Chagas disease. This mechanism may also be operative in other inflammatory cardiomyopathies.

**Keywords** Variants · chagas · cardiomyopathy · pathogenic · mitochondria · inflammation

Introduction

Cardiomyopathies are an important cause of cardiovascular death by heart failure and arrhythmia. Familial cardiomyopathies are a group of Mendelian genetic disorders associated with rare high-impact gene variants altering protein structure and function, mostly involving genes encoding sarcomeric/ structural and calcium handling proteins. Among the acquired causes of cardiomyopathy, an estimated 30% have an infectious etiology, associated with myocarditis [1].

Little is known about the genetic underpinnings of infectious cardiomyopathy. Chagas disease (CD), caused by infection with the protozoan *Trypanosoma cruzi*, is the most common cause of nonischemic cardiomyopathy in Latin America, where 6 million people are infected, causing approximately 10,000 deaths/year due to cardiac compromise [2]. It is transmitted by the reduviid insect vector, by blood transfusion, congenitally, and by ingestion. An estimated 400,000 infected persons live in nonendemic countries, mainly the USA and Europe. Chronic CD cardiomyopathy (CCC) is a chronic inflammatory cardiomyopathy occurring decades after infection with *T. cruzi* [3] in up to 30% of CD patients. ECG abnormalities and heart conduction defects are associated with progressive inflammatory fibrotic and hypertrophic myocardial lesions including the conducting tissue [4] and precede ventricular arrhythmia/sudden cardiac death (SCD) and/or dilated cardiomyopathy with heart failure (HF), the major causes of death in CCC [5]. From the remaining CD patients, 60% persist asymptomatic form (ASY), and 10% develop gastrointestinal motility disorders [6, 7]. CD patients with ECG abnormalities typical of CCC show higher total and cardiac mortality [8]. No adequate treatment is available to prevent the development of chronic heart disease, whose prognosis is worse than dilated cardiomyopathies of other etiologies [3]. New approaches to the treatment of CCC are thus sorely needed. The pathogenesis of CCC is still incompletely understood, although myocardial inflammation and reduced mitochondrial energy metabolism are thought to play a major role in CD and cardiac remodeling and heart failure of any etiology [2, 3]. After acute infection, parasitism is partially controlled by the immune response, and low-grade parasite persistence fuels the

production of inflammatory cytokines like IFN-γ and TNF-α, which is more intense in CCC than ASY patients [9]. A T cell and monocyte-rich chronic myocarditis with fibrosis and hypertrophy is the histopathological hallmark of CCC [10, 11].

IFN-γ is the most abundant cytokine expressed in the CCC myocardium, and transcriptomic analyses of the CCC myocardium show a significant IFN-γ transcriptional signature [10, 12]. IFN-γ treatment induces reduced contractility [13] and fatty acid metabolism of cardiomyocytes [14] and profibrotic changes in fibroblasts and transgenic mice overexpressing IFN-γ develop inflammatory cardiomyopathy [15, 16]. Taken together, evidence suggests IFN-γ is the culprit of CCC. In addition, the myocardium from CCC patients with ventricular dysfunction displays decreased levels of mitochondrial metabolism enzymes [17] and ATP production [18]. IFN-γ has multiple deleterious effects on the cardiomyocyte mitochondria. It induces TNF-alpha and potentiates TNF-alpha-mediated NF-κB signaling, leading to NOS2 production of NO [19, 20] which in the presence of IFN-γ-induced reactive oxygen species turns into peroxynitrite [21] and ensuing mitochondrial fragmentation and reduction of mitochondrial membrane potential, lipid beta-oxidation [14], and ATP generation [22].

High-impact rare gene variants altering protein structure and function underlie Mendelian disease and contribute to complex multifactorial disease. Approximately 10% of acute viral myocarditis (AVM) patients carried rare pathogenic homozygous variants in genes implicated in familial cardiomyopathy [23], suggesting an overlap between genetic and acquired forms of myocarditis and cardiomyopathy. However, the evidence for a role of such variants in the pathogenesis of AVM is circumstantial, as no genetic study has compared AVM patients with virus-infected patients that failed to develop myocarditis. In CD, however, serological tests can readily ascertain *T. cruzi* infection in patients who have developed cardiomyopathy or have remained asymptomatic, decades after the initial infection. This has allowed genetic association studies of common gene polymorphisms between the two *T. cruzi*-exposed groups with divergent cardiac phenotypes, CCC and ASY [2], which have a low individual effect on phenotype. CD thus provides a unique model to probe the
effect of rare pathogenic genetic variants in the susceptibility
towards developing postinfectious cardiomyopathy in
humans.

We hypothesize here that rare genetic variants may lead to
progression towards CCC by increasing cardiomyocyte sus-
ceptibility to inflammatory damage. Whole exome sequenc-
ing (WES) studies in families with multiple disease cases are
an unbiased approach that has been used to identify rare path-
ogenic variants in Mendelian genetic disorders and complex
multifactorial diseases. We used WES to search for rare, high-
impact gene variants linked to CCC in nuclear families con-
taining multiple cases of CD and involved in pathobiological
processes involved in inflammatory cardiomyopathy. Our
analysis disclosed rare heterozygous pathogenic variants in
inflammation-related and mitochondrial genes linked to
CCC cases. Functional testing indicated that IFN-γ caused
significant mitochondrial dysfunction on a human cardiomyo-
cyte line treated with an inhibitor of dihydroorotate dehydro-
genase brequinar (enzyme showing a loss-of-function variant
in one family).

**Patients, Materials, and Methods**

Ethical Issues

This protocol was approved by the INSERM Internal Review
Board and by the Brazilian National Ethics in Research
Commission (CONEP), and written informed consent was
obtained from the patients. All patients enrolled in this study
were over 21 years old. Investigations were conformed to the
principles outlined in the declaration of Helsinki.

Patients

Probands and their nuclear family members were recruited
from the Sami-Trop CD cohort, in rural Minas Gerais state
[24], and the CD outpatient clinic at the Heart Institute/
HCFMUSP.

Nuclear families typically center on a married couple
which may have any number of children. Figure 1 shows the
pedigrees of the 6 selected nuclear families with multiple CD
cases (n = 25), and Table 1 depicts the clinical and demo-
graphic parameters of the studied subjects. Families 1 and 6
came from the Heart Institute, while families 2–5 came from
the Sami-Trop CD cohort.

Blood DNA Preparation and Whole Exome
Sequencing

On EDTA vacutainer tubes, 10 ml of blood was collected. The
genomic DNA of 25 CCC and ASY patients belonging to the
6 families, plus 14 genetically unrelated ASY controls, was

isolated with the QIAamp DNA Blood Midi Kit (Qiagen,
Hilden, Germany). Exome sequencing was performed using
the Ion Proton platform (Life Technologies, Villebon sur
Yvette, France) according to a protocol previously described
[25].

Variant Prioritization

We excluded synonymous, non-exonic polymorphisms, keep-
ing polymorphisms with a minor allele frequency (MAF) of
<1% in at least one public database using the VARAFT filter-
ing and annotation tool (https://varaft.eu) on vcf files. Variant
calls with variant quality (QUAL) ≤60, depth of coverage
(DP) <20, and mapping quality (MQ) ≤40 were filtered out.
Only exonic nonsynonymous damaging variants were kept for
downstream genetic analyses. We searched for variants, inde-
pendently, in each family, under an autosomal dominant or
under autosomal recessive models. In order to identify gene
variants associated with CCC in each family, we selected var-
iants that were shared by all CCC patients and absent in any
and all ASY patients in a given nuclear family, as well as in 14
unrelated ASY controls. We assessed the pathogenic potential
of missense variants using 4 algorithms embedded in VarAft.
Only rare variants tagged as pathogenic (or damaging) were
retained for downstream genetic analyses.

Polymerase Chain Reaction and Sanger Sequencing

For validation, we designed specific primers for each mutation
of interest with Primer3 software (V4.0.0) to amplify genomic
DNAs (online Table 3). PCR amplifications were carried out
with GoTaq polymerase (Promega, Charbonnières-les-Bains,
France) and 1uM of each primer. On Eppendorf thermocycler,
50 µl reactions were carried out. The PCR products were
visualized on agarose gel (1.5% agarose TBE0.5X) and puri-
fied with QIAEXII gel extraction kit (Qiagen) before Sanger
sequencing.

Mitochondrial Membrane Potential Assay

Total mitochondria were stained with MitoTracker green, and
mitochondrial membrane potential (MMP) was evaluated
using the TMRE dye that accumulates in fully polarized, but
not in depolarized mitochondria [26]. We measured TMRE
fluorescence on MitoTracker green-labeled mitochondria.
Cell viability was assessed using LIVE/DEAD™ Fixable
Aqua Dead Cell Stain Kit. All fluorescent dyes were from
Thermo Fisher Scientific, and assays were performed using
live microscopy with the ImageXpress Micro instrument
(Molecular Devices).
<table><caption>**Table 1** Description of the study phenotypes</caption><thead><tr><th>Family</th><th>ID</th><th>Phenotype</th><th>Chagas serology</th><th>Age</th><th>Sex</th><th>LVEF</th></tr></thead><tbody><tr><td colspan="7">A. Chagas disease families</td></tr><tr><td rowspan="4">Family 1</td><td>IC250E</td><td>CCC</td><td>Seropositive</td><td>42</td><td>F</td><td>0.56</td></tr><tr><td>IC252E</td><td>ASY</td><td>Seropositive</td><td>50</td><td>F</td><td>0.68</td></tr><tr><td>IC253E</td><td>ASY</td><td>Seropositive</td><td>54</td><td>F</td><td>0.61</td></tr><tr><td>IC254E</td><td>CCC</td><td>Seropositive</td><td>49</td><td>M</td><td>0.30</td></tr><tr><td rowspan="8">Family 2</td><td>6151</td><td>ASY</td><td>Seropositive</td><td>63</td><td>F</td><td>0.69</td></tr><tr><td>6152</td><td>CCC</td><td>Seropositive</td><td>37</td><td>F</td><td>0.63</td></tr><tr><td>6153</td><td>ASY</td><td>Seropositive</td><td>36</td><td>F</td><td>0.66</td></tr><tr><td>6154</td><td>ASY</td><td>Seropositive</td><td>39</td><td>F</td><td>0.65</td></tr><tr><td>6155</td><td>CCC</td><td>Seropositive</td><td>45</td><td>F</td><td>0.60</td></tr><tr><td>6156</td><td>CCC</td><td>Seropositive</td><td>79</td><td>F</td><td>0.62</td></tr><tr><td>6157</td><td>CCC</td><td>Seropositive</td><td>49</td><td>F</td><td>0.56</td></tr><tr><td>6086</td><td>ASY</td><td>Seropositive</td><td>71</td><td>F</td><td>0.70</td></tr><tr><td rowspan="2">Family 3</td><td>6087</td><td>CCC</td><td>Seropositive</td><td>68</td><td>F</td><td>0.69</td></tr><tr><td>6088</td><td>ASY</td><td>Seropositive</td><td>69</td><td>F</td><td>0.69</td></tr><tr><td rowspan="2">Family 4</td><td>6075</td><td>CCC</td><td>Seropositive</td><td>67</td><td>F</td><td>0.69</td></tr><tr><td>6076</td><td>CCC</td><td>Seropositive</td><td>57</td><td>M</td><td>0.69</td></tr><tr><td rowspan="6">Family 5</td><td>6078</td><td>CCC</td><td>Seropositive</td><td>52</td><td>F</td><td>0.67</td></tr><tr><td>6131</td><td>CCC</td><td>Seropositive</td><td>24</td><td>F</td><td>0.65</td></tr><tr><td>6133</td><td>ASY</td><td>Seropositive</td><td>69</td><td>F</td><td>0.63</td></tr><tr><td>6134</td><td>CCC</td><td>Seropositive</td><td>42</td><td>F</td><td>0.50</td></tr><tr><td>6135</td><td>CCC</td><td>Seropositive</td><td>38</td><td>F</td><td>0.65</td></tr><tr><td>6136</td><td>CCC</td><td>Seropositive</td><td>68</td><td>M</td><td>0.62</td></tr><tr><td rowspan="3">Family 6</td><td>IC174EC</td><td>CCC</td><td>Seropositive</td><td>41</td><td>F</td><td>0.38</td></tr><tr><td>IC190EC</td><td>CCC</td><td>Seropositive</td><td>50</td><td>F</td><td>0.37</td></tr><tr><td>IC191EC</td><td>CCC</td><td>Seropositive</td><td>69</td><td>F</td><td>0.45</td></tr><tr><td colspan="4">Seronegative siblings in family 5</td><td>53.6±14.6</td><td></td><td>0.59±0.11</td></tr><tr><td rowspan="2">Family 5</td><td>6132</td><td>Healthy</td><td>Seronegative</td><td>32</td><td>M</td><td>0.59</td></tr><tr><td>6137</td><td>Healthy</td><td>Seronegative</td><td>30</td><td>M</td><td>0.7</td></tr><tr><td colspan="7">B. Unrelated ASY controls</td></tr><tr><td rowspan="14">Unrelated</td><td>IC33EI</td><td>ASY</td><td>Seropositive</td><td>65</td><td>M</td><td>0.69</td></tr><tr><td>IC45EI</td><td>ASY</td><td>Seropositive</td><td>51</td><td>F</td><td>0.61</td></tr><tr><td>IC49EI</td><td>ASY</td><td>Seropositive</td><td>57</td><td>F</td><td>0.70</td></tr><tr><td>IC69EI</td><td>ASY</td><td>Seropositive</td><td>90</td><td>F</td><td>0.68</td></tr><tr><td>IC92EI</td><td>ASY</td><td>Seropositive</td><td>62</td><td>M</td><td>0.66</td></tr><tr><td>IC95EI</td><td>ASY</td><td>Seropositive</td><td>57</td><td>F</td><td>0.70</td></tr><tr><td>IC106EI</td><td>ASY</td><td>Seropositive</td><td>44</td><td>F</td><td>0.55</td></tr><tr><td>IC111EI</td><td>ASY</td><td>Seropositive</td><td>42</td><td>F</td><td>0.63</td></tr><tr><td>6083</td><td>ASY</td><td>Seropositive</td><td>41</td><td>F</td><td>0.65</td></tr><tr><td>6091</td><td>ASY</td><td>Seropositive</td><td>50</td><td>F</td><td>0.62</td></tr><tr><td>6097</td><td>ASY</td><td>Seropositive</td><td>47</td><td>F</td><td>0.56</td></tr><tr><td>6102</td><td>ASY</td><td>Seropositive</td><td>45</td><td>M</td><td>0.66</td></tr><tr><td>6129</td><td>ASY</td><td>Seropositive</td><td>71</td><td>F</td><td>0.74</td></tr><tr><td>6143</td><td>ASY</td><td>Seropositive</td><td>39</td><td>F</td><td>0.66</td></tr><tr><td colspan="4"></td><td>54.3±14</td><td></td><td>0.65±0.05</td></tr></tbody></table>

LVEF, left ventricular ejection fraction; ASY, asymptomatic form

<figure><img src="image_4.png" /></figure>
<figure><img src="image_5.png" /><figcaption>**Fig. 1** Pedigrees of the six nuclear families included in this study. All patients underwent detailed clinical interview and *T. cruzi* serological tests. *T. cruzi*-seropositive individuals were considered as CCC patients when presenting major ECG abnormalities according to the Minnesota Code classification, modified by Ribeiro et al. [8]. Major ECG abnormalities are cited in online Table 1. The presence of any one of these major ECG changes was associated with a twofold increase in</figcaption></figure>

mortality [8]. *T. cruzi*-seropositive individuals presenting major ECG abnormalities, according to the Minnesota Code classification, modified by Ribeiro et al. [8] were considered as CCC patients. *T. cruzi*-seropositive patients without such ECG findings, with normal echocardiography, and no clinical signs were considered indeterminate forms of CD (ASY) cases

## Results

We performed whole exome sequencing and assessed rare pathogenic gene variants associated with CCC in six nuclear families containing multiple cases of CD families (25 patients) and in a group of unrelated ASY patients (n = 14) who came from CD-endemic rural areas in Brazil. The average age in the CCC and ASY patients in the family groups and the ASY unrelated control were similar, around 54 ± 14 years (Table 1). Pedigrees are shown in Fig. 1.

Whole exome sequencing disclosed that on average, each patient sample contained 41,780 gene variants. Among them, on average, 11,651 variants were located in coding (exonic or splicing) regions and nonsynonymous. We focused on variants characterized by a minor allele frequency < 1% in the databases (ESP6500, 1000G, and ExAC). Under a hypothesis of complete penetrance, for each given family, we selected nonsynonymous exonic or splicing variants shared by all family members with CCC but absent from ASY family members as well as by the unrelated ASY controls. For families 1 to 6, we found 39, 8, 108, 81, 9, and 76 variants fulfilling the above

criteria, respectively, comprising a total of 321 CCC-specific nonsynonymous exonic rare variants. We performed a Reactome (reactome.org) pathways analysis of the 321 CCC-specific variants, prior to any prioritization. We found 8 enriched pathways with a significant false discovery ratio (FDR < 0.05). Pathways were based on a very limited number of genes (6/8 with one or two genes) and thus of limited relevance. At any event, the 8 pathways were related either to interferon signaling or to endosomal/antigen processing/presentation pathways (HLA molecules, BTK) (online Table 4). After the application of our pathogenicity filter with multiple algorithms, we found 102 CCC-specific rare pathogenic variants. After filtering for evolutionary conservation, we found 87 variants. At this point, we prioritized the 87 gene variants in 9 pathobiological processes associated to CD. It highlighted 23 of our candidate genes (corresponding to 25 variants). From these variants, 88% (22/25, contained in 20 genes) were confirmed by Sanger sequencing (Table 2, online Fig. 1). All these 22 variants showed CADD scores above 15, consistent with pathogenicity. Indeed, for information, the CADD score of each variant is also shown in Table 2b. Two
<table><caption>**Table 2** Description of pathogenic variants identified on the 6 nuclear families. A. Genetic data. B. pathogenicity and conservation. C. Participation in select pathobiological processes. D. Frequency of variants in different databases</caption><thead><tr><th>Family</th><th>Gene</th><th>Chr</th><th>Start</th><th>End</th><th>Reference/mutated allele</th><th>Localization</th><th>Type of mutation</th><th>Nucleic acid change</th><th>Amino acid change</th><th>avsnp147</th></tr></thead><tbody><tr><td>1</td><td>LEPR</td><td>1</td><td>66,081,791</td><td>66,081,791</td><td>C/T</td><td>Exonic</td><td>non syn</td><td>exon14 2096C>T (NM_001198687)</td><td>T699M</td><td>rs34499590</td></tr><tr><td>1</td><td>ADCY10</td><td>1</td><td>167,830,254</td><td>167,830,254</td><td>T/C</td><td>Exonic</td><td>non syn</td><td>exon12 1202A>G (NM_001167749)</td><td>Y402C</td><td>rs140663029</td></tr><tr><td>1</td><td>MOCS1</td><td>6</td><td>39,877,666</td><td>39,877,666</td><td>G/A</td><td>Exonic</td><td>non syn</td><td>exon8 1015C>T (NM_005943)</td><td>R339W</td><td>rs148579886</td></tr><tr><td>1</td><td>ADGRG6</td><td>6</td><td>142,724,940</td><td>142,724,940</td><td>G/A</td><td>Exonic; splicing</td><td>non syn</td><td>exon13 1873G>A (NM_001032394)</td><td>A625T</td><td>rs184235213</td></tr><tr><td>1</td><td>AKAP13</td><td>15</td><td>86,124,694</td><td>86,124,694</td><td>T/C</td><td>Exonic</td><td>non syn</td><td>exon7 3395 T>C (NM_006738)</td><td>L1132S</td><td>rs745783128</td></tr><tr><td>2</td><td>OBSCN</td><td>1</td><td>228,464,267</td><td>228,464,267</td><td>G/T</td><td>Exonic</td><td>non syn</td><td>exon22 6337G>T (NM_001098623)</td><td>G2113C</td><td>rs74623201</td></tr><tr><td>3</td><td>APOB</td><td>2</td><td>21,247,996</td><td>21,247,996</td><td>C/A</td><td>Exonic; splicing</td><td>non syn</td><td>exon16 2245G>T (NM_000384)</td><td>D749Y</td><td>.</td></tr><tr><td>3</td><td>MRPS18B</td><td>6</td><td>30,590,612</td><td>30,590,612</td><td>G/A</td><td>Exonic; splicing</td><td>non syn</td><td>exon5 358G>A (NM_014046)</td><td>V120M</td><td>rs116524936</td></tr><tr><td>3</td><td>PKHD1</td><td>6</td><td>51,947,999</td><td>51,947,999</td><td>G/A</td><td>Exonic</td><td>non syn</td><td>exon3 107C>T (NM_138694)</td><td>T36M</td><td>rs137852944</td></tr><tr><td>3</td><td>RNLS</td><td>10</td><td>90,122,344</td><td>90,122,344</td><td>C/T</td><td>Exonic</td><td>non syn</td><td>exon5 665G>A (NM_001031709)</td><td>R222H</td><td>rs191733133</td></tr><tr><td>3</td><td>GIT1</td><td>17</td><td>27,901,773</td><td>27,901,773</td><td>C/T</td><td>Exonic</td><td>non syn</td><td>exon20 2233G>A (NM_014030)</td><td>A745T</td><td>.</td></tr><tr><td>3</td><td>GIT1</td><td>17</td><td>27,910,559</td><td>27,910,559</td><td>C/T</td><td>Exonic</td><td>non syn</td><td>exon2 128G>A (NM_001085454)</td><td>R43H</td><td>.</td></tr><tr><td>3</td><td>LILRA2</td><td>19</td><td>55,098,715</td><td>55,098,715</td><td>C/T</td><td>Exonic</td><td>non syn</td><td>exon6 1267C>T (NM_001290270)</td><td>R423C</td><td>rs149580797</td></tr><tr><td>4</td><td>MAP4K4</td><td>2</td><td>102,440,480</td><td>102,440,480</td><td>A/G</td><td>Exonic</td><td>non syn</td><td>exon4 271A>G (NM_001242559)</td><td>K91E</td><td>.</td></tr><tr><td>4</td><td>SLC11A1</td><td>2</td><td>219,257,728</td><td>219,257,728</td><td>C/T</td><td>Exonic</td><td>non syn</td><td>exon12 1189C>T (NM_000578)</td><td>R397C</td><td>rs74906275</td></tr><tr><td>4</td><td>RPUSD3</td><td>3</td><td>9,880,802</td><td>9,880,802</td><td>C/T</td><td>Exonic</td><td>stopgain</td><td>exon8 806G>A (NM_001351738)</td><td>W269X</td><td>rs142984515</td></tr><tr><td>4</td><td>UMPS</td><td>3</td><td>124,449,406</td><td>124,449,406</td><td>A/G</td><td>Exonic</td><td>non syn</td><td>exon1 88A>G (NM_000373)</td><td>S30G</td><td>rs17843776</td></tr><tr><td>5</td><td>MAML1</td><td>5</td><td>179,192,418</td><td>179,192,418</td><td>G/A</td><td>Exonic</td><td>non syn</td><td>exon2 407G>A (NM_014757)</td><td>G136E</td><td>rs146382198</td></tr><tr><td>5</td><td>DHODH</td><td>16</td><td>72,048,540</td><td>72,048,540</td><td>C/T</td><td>Exonic</td><td>non syn</td><td>exon3 403C>T (NM_001361)</td><td>R135C</td><td>rs201230446</td></tr><tr><td>6</td><td>TNFRSF4</td><td>1</td><td>1,147,467</td><td>1,147,467</td><td>G/C</td><td>Exonic</td><td>non syn</td><td>exon5 489C>G (NM_003327)</td><td>D163E</td><td>.</td></tr><tr><td>6</td><td>APOB</td><td>2</td><td>21,230,419</td><td>21,230,419</td><td>G/C</td><td>Exonic</td><td>non syn</td><td>exon26 9321C>G (NM_000384)</td><td>N3107K</td><td>rs72653101</td></tr><tr><td>6</td><td>SERPINE2</td><td>2</td><td>224,866,427</td><td>224,866,427</td><td>A/G</td><td>Exonic</td><td>non syn</td><td>exon2 191>C (NM_001136528)</td><td>M64T</td><td>rs34078713</td></tr><tr><td colspan="11" style="text-align: left; font-weight: bold;">B</td></tr><tr><td>Family</td><td>Gene</td><td>Amino acid change</td><td>avsnp147</td><td>Polyphen2 HDIV prediction</td><td>Polyphen2 prediction</td><td>SIFT prediction</td><td>UMD prediction</td><td>CADD prediction score</td><td>Consurf conservation score</td><td></td></tr><tr><td>1</td><td>LEPR</td><td>T699M</td><td>rs34499590</td><td>Damaging</td><td>Damaging</td><td>Damaging</td><td>Prob Patho</td><td>26.5</td><td>9</td><td></td></tr><tr><td>1</td><td>ADCY10</td><td>Y402C</td><td>rs140663029</td><td>Damaging</td><td>Damaging</td><td>Damaging</td><td>Poly</td><td>22.2</td><td>6</td><td></td></tr><tr><td>1</td><td>MOCS1</td><td>R339W</td><td>rs148579886</td><td>Damaging</td><td>Damaging</td><td>Damaging</td><td>Patho</td><td>33.0</td><td>8</td><td></td></tr><tr><td>1</td><td>ADGRG6</td><td>A625T</td><td>rs184235213</td><td>Damaging</td><td>Damaging</td><td>Tolerate</td><td>Patho</td><td>26.0</td><td>9</td><td></td></tr><tr><td>1</td><td>AKAP13</td><td>L1132S</td><td>rs745783128</td><td>Damaging</td><td>Damaging</td><td>Damaging</td><td>Prob Patho</td><td>15.6</td><td>7</td><td></td></tr><tr><td>2</td><td>OBSCN</td><td>G2113C</td><td>rs74623201</td><td>Damaging</td><td>Damaging</td><td>Damaging</td><td>Prob Poly</td><td>25.0</td><td>9</td><td></td></tr></tbody></table>

<figure><img src="image_6.png" /></figure>
<table><caption>Table 2 (continued)</caption><tr><td>1</td><td>ADCY10</td><td>Y402C</td><td>X</td><td></td></tr><tr><td></td><td></td><td>r-</td><td></td><td></td></tr><tr><td></td><td></td><td>sl40663029</td><td></td><td></td></tr><tr><td>1</td><td>MOCS1</td><td>R339W</td><td>X</td><td></td></tr><tr><td></td><td></td><td>r-</td><td></td><td></td></tr><tr><td></td><td></td><td>sl48579886</td><td></td><td></td></tr><tr><td>1</td><td>ADGRG6</td><td>A625T</td><td>X</td><td></td></tr><tr><td></td><td></td><td>r-</td><td></td><td></td></tr><tr><td></td><td></td><td>sl84235213</td><td></td><td></td></tr><tr><td>1</td><td>AKAP13</td><td>L1132S</td><td>X</td><td>X</td></tr><tr><td></td><td></td><td>r-</td><td></td><td></td></tr><tr><td></td><td></td><td>sl745783128</td><td></td><td></td></tr><tr><td>2</td><td>OBSCN</td><td>G2113-C</td><td>X</td><td></td></tr><tr><td></td><td></td><td>D749Y</td><td>X</td><td></td></tr><tr><td>3</td><td>APOB</td><td>V120M</td><td>X</td><td>X</td></tr><tr><td>3</td><td>MRPS18-B</td><td></td><td>X</td><td></td></tr><tr><td></td><td></td><td>sl116524936</td><td></td><td></td></tr><tr><td>3</td><td>PKHDI1</td><td>T36M</td><td>X</td><td>X</td></tr><tr><td></td><td></td><td>r-</td><td></td><td></td></tr><tr><td></td><td></td><td>sl137852944</td><td></td><td></td></tr><tr><td>3</td><td>RNLS</td><td>R222H</td><td>X</td><td>X</td></tr><tr><td></td><td></td><td>r-</td><td></td><td></td></tr><tr><td></td><td></td><td>sl191733133</td><td></td><td></td></tr><tr><td>3</td><td>GIT1</td><td>A745T</td><td>X</td><td>X</td></tr><tr><td>3</td><td>GIT1</td><td>R43H</td><td>X</td><td>X</td></tr><tr><td>3</td><td>LILRA2</td><td>R423C</td><td>X</td><td>X</td></tr><tr><td></td><td></td><td>r-</td><td></td><td></td></tr><tr><td></td><td></td><td>sl49580797</td><td></td><td></td></tr><tr><td>4</td><td>MAP4K4</td><td>K91E</td><td>X</td><td>X</td></tr><tr><td>4</td><td>SLC11A1</td><td>R397C</td><td>X</td><td>X</td></tr><tr><td>4</td><td>RPUSD3</td><td>W269X</td><td>X</td><td>X</td></tr><tr><td></td><td></td><td>r-</td><td></td><td></td></tr><tr><td></td><td></td><td>sl42984515</td><td></td><td></td></tr><tr><td>4</td><td>UMPS</td><td>S30G</td><td>X</td><td>X</td></tr><tr><td>5</td><td>MAML1</td><td>G136E</td><td>X</td><td>X</td></tr></table>

<figure><img src="image_7.png" /></figure>
<table><caption>**Table 2** (continued)</caption><thead><tr><th></th><th></th><th></th><th></th><th></th><th></th><th></th></tr></thead><tbody><tr><td></td><td></td><td>r</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td>s137852944</td><td></td><td></td><td></td><td></td></tr><tr><td>3</td><td>RNLS</td><td>R222H</td><td>NA</td><td>0.02%</td><td>0.002%</td><td>NA</td></tr><tr><td></td><td></td><td>r</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td>s191733133</td><td></td><td></td><td></td><td></td></tr><tr><td>3</td><td>GIT1</td><td>A745T</td><td>NA</td><td>NA</td><td>NA</td><td>NA</td></tr><tr><td>3</td><td>GIT1</td><td>R43H</td><td>NA</td><td>NA</td><td>NA</td><td>NA</td></tr><tr><td>3</td><td>LILRA2</td><td>R423C</td><td>0.21%</td><td>0.30%</td><td>0.09%</td><td>0.33%</td></tr><tr><td></td><td></td><td>r</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td>s149580797</td><td></td><td></td><td></td><td></td></tr><tr><td>4</td><td>MAP4K4</td><td>K91E</td><td>NA</td><td>NA</td><td>NA</td><td>NA</td></tr><tr><td>4</td><td>SLC11A1</td><td>R397C</td><td>rs74906275</td><td>0.04%</td><td>0.03%</td><td>NA</td></tr><tr><td>4</td><td>RPUSD3</td><td>W269X</td><td>0.008%</td><td>NA</td><td>0.007%</td><td>NA</td></tr><tr><td></td><td></td><td>r</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td>s142984515</td><td></td><td></td><td></td><td></td></tr><tr><td>4</td><td>UMPS</td><td>S30G</td><td>rs17843776</td><td>0.02%</td><td>0.36%</td><td>0.38%</td></tr><tr><td>5</td><td>MAML1</td><td>G136E</td><td>0.008%</td><td>0.08%</td><td>0.07%</td><td>0.49%</td></tr><tr><td></td><td></td><td>r</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td>s146382198</td><td></td><td></td><td></td><td></td></tr><tr><td>5</td><td>DHODH</td><td>R135C</td><td>0.04%</td><td>0.04%</td><td>0.04%</td><td>0.08%</td></tr><tr><td></td><td></td><td>r</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td>s201230446</td><td></td><td></td><td></td><td></td></tr><tr><td>6</td><td>TNFRSF4</td><td>D163E</td><td>NA</td><td>NA</td><td>NA</td><td>NA</td></tr><tr><td>6</td><td>APOB</td><td>N3107-K</td><td>rs72653101</td><td>NA</td><td>0.0008%</td><td>NA</td></tr><tr><td>6</td><td>SERPIN-E2</td><td>M64T</td><td>rs34078713</td><td>0.78%</td><td>0.30%</td><td>0.75%</td><td>1.15%</td></tr></tbody></table>

Prob, probable or probably; Patho, pathogenic; Poly=poly=polymorphism; Dam, damaging
CMP, cardiomyopathy

We excluded synonymous, non-exonic polymorphisms, keeping polymorphisms with a minor allele frequency (MAF) of <1% in at least one public databases (ESP6500; NHLBI GO Exome Sequencing Project (EVS, ESP6500SLV2 release on http://evs.gs.washington.edu/EVS/); 1000 Genomes (April 2014 data release on http://browser.1000genomes.org/); and Exome Aggregation Consortium (ExAC, January 2015 Version 0.3 data release on http://exac.broadinstitute.org/) using the VARAFT filtering and annotation tool (https://varaft.eu) on vcf files. Variant calls with Variant quality (QUAL) ≤60, depth of coverage (DP) <20, and mapping quality (MQ) ≤40 were filtered out. We also assessed an available Brazilian exome database of 609 elderly individuals from the city of Sao Paulo [18]. Only exonic nonsynonymous damaging variants were kept for downstream genetic analyses. We searched for variants, independently, in each family, under an autosomal dominant or under autosomal recessive models. In order to identify gene variants associated with CCC in each family, we selected variants that were shared by all CCC patients and absent in any and all IF patients in a given nuclear family, as well as in 14 unrelated IF controls. We assessed the pathogenic potential of missense variants using 4 algorithms embedded in VarAft: SIFT (https://sift.bii.a-star.edu.sg/), Polyphen 2 HumDiv and Polyphen 2 HumVar (http://genetics.bwh.harvard.edu/pph2/index.shtml), and UMD-Predictor (http://umd-predictor.eu/). Only rare variants tagged as pathogenic (or damaging) or possibly pathogenic (or probably damaging) in at least three databases and pathogenic/damaging in at least one algorithm were retained for downstream genetic analyses. We validated the abovementioned pathogenicity filter with the Combined Annotation-Dependent Depletion (CADP) tool (http://cadd.gs.washington.edu/score). Evolutionary conservation in the position was determined with the Consurf server (https://consurf.tau.ac.il)

<figure><img src="image_8.png" /></figure>
<figure><img src="image_9.png" /><figcaption>**Fig. 2** Number of genes containing pathogenic variants for each biological process related to cardiomyopathy. Pathway analyses were performed with the Ingenuity Pathways Analysis (IPA®, Qiagen, Redwood City, USA) or Reactome (reactome.org); we also interrogated whether genes participated in 9 biological processes related to the pathophysiology of CCC: inflammation, IFNγ-modulated genes/Th1 response, fibrosis/extracellular matrix, contractility of heart, hypertrophy, arrhythmia, oxidative stress/antioxidant response, familial</figcaption></figure>

cardiomyopathy, and mitochondria-related genes. For these nine additional biological processes, we merged IPA Knowledge Base (IKB) gene lists and published gene lists including the IFNγ induced/repressed gene lists, and Nrf2-modulated genes where appropriate. Mitochondrial gene list was a combination of genes contained in the Mitochondrion Gene Ontology term and Mitocarta 2.0. The gene list for these pathways/processes in online Table 2

pathogenic variant. A striking accumulation of CCC-specific variants (86%) occurred in mitochondrial or inflammation-related genes, and all studied families displayed at least one CCC-associated variant gene belonging to these pathways. The finding that only a single family carried a variant in a gene previously associated with familial cardiomyopathy indicates the genetic landscape, and pathogenesis of CCC is distinct from that of familial cardiomyopathy. Importantly, we also found that IFN-γ potentiated mitochondrial dysfunction caused by an inhibitor of DHODH, a mitochondrial enzyme bearing a loss-of-function mutation (DHODH R135C)

linked with CCC in one of our families, indicating synergy in the induction of mitochondrial dysfunction. To our knowledge, this is the first report that rare heterozygous pathogenic variants in mitochondrial and inflammation-related genes are linked to the development of complex multifactorial inflammatory cardiomyopathy.

Among the 9 mitochondrial genes showing CCC-specific pathogenic variants, 8 are involved in processes leading to mitochondrial ATP production (biogenesis, translation, fatty acid oxidation-FAOx, and the electron transfer chain/oxidative phosphorylation (OXPHOS)). The R135C variant

<figure><img src="image_10.png" /><figcaption>**Fig. 3** Features of the main mitochondrial and inflammation-related genes containing deleterious pathogenic variants associated to CCC</figcaption></figure>

<figure><img src="image_11.png" /></figure>
<figure><img src="image_12.png" /><figcaption>**Fig. 4** IFN-γ and brequinar treatment significantly reduced mitochondrial membrane potential. AC16 human cardiomyocyte cell line was stimulated with or without IFN-γ and with or without brequinar for 48 h. Total mitochondria were stained with MitoTracker green, and mitochondrial membrane potential (MMP) was evaluated using the TMRE dye that accumulates in fully polarized, but not in depolarized</figcaption></figure>

mitochondria. We measured TMRE fluorescence on MitoTracker green-labeled mitochondria. Cell viability was calculated as the ratio of the amount of live cells (propidium iodide-negative) and total cells (propidium iodide-negative plus propidium iodide-positive cells) × 100.
* *p* < 0.05, ** *p* < 0.01, *** *p* < 0.001, and **** *p* < 0.0001

observed in the DHODH gene was the only variant known to lead to complete loss-of-function and mitochondrial dysfunction [27]. Genetic truncation or expression of dominant-negative variants of DHODH, GIT1, RPUSD3, ADCY10, and MOCS1 in cells was shown to cause mitochondrial dysfunction, including reduced mitochondrial membrane potential, respiratory chain/oxidative phosphorylation (OXPHOS) activity, and ATP production [28–30]. Interestingly, patients carrying mutations or animals genetically deficient in 6 genes (DHODH, UMPS, MRPS18B, GIT1, OBSCN, and LEPR) developed cardiac phenotypes [27, 30–34]. Parents of patients with Miller syndrome (homozygous DHODH loss-of-function R135C or other variants; 70% with congenital cardiac abnormalities) carry one copy of the defective gene as members of family 5 but are nevertheless healthy [27]. Animals genetically deficient in MRPS18B and GIT1 showed evidence of mitochondrial dysfunction, altered mitochondrial morphology, and reduced myocardial contractility [35]. Details about the function of affected genes are shown in online Table 5.

Genetic disorders involving mitochondrial genes are the most common congenital genetic syndromes. Mitochondriopathies are caused by homozygous pathogenic rare variants in nuclear-encoded mitochondrial genes or in mitochondrial DNA. Homozygous pathogenic variants of more than 250 of the ~1500 nuclear-encoded mitochondrial genes were identified as causally related to mitochondrial disorders [35]. Each leads to drastic mitochondrial dysfunction and energetic and functional impairment in tissues of high energy demand, causing syndromes affecting single organs

or organ combinations that usually present in early childhood; each clinical syndrome is associated with variants in specific mitochondrial genes [35], and clinical penetrance is variable. The diverse clinical presentation of mitochodriopathies is related to genetic heterogeneity and the central role of mitochondria in multiple processes, including energy generation, antioxidant defenses, Ca++ homeostasis, intracellular signaling, macromolecule and nucleotide biosynthesis, reprogramming nuclear gene expression, and cell death. Interestingly, up to 30% of mitochondriopathy patients develop cardiomyopathy, heart conduction defects, ventricular arrhythmia or sudden cardiac death, and autonomic nervous system imbalance [36], while up to 15% develop gastrointestinal motility disorders including achalasia/megaesophagus and megacolon [37]. The striking similarity between the clinical presentation and proportion of cardiac and digestive disorders in mitochondriopathies and the clinical spectrum of CD [3] suggested the pathogenesis of CCC may be dependent on mitochondrial dysfunction. Indeed, CCC myocardium displays signs of reduced mitochondrial activity and energy production. Decreased mitochondrial rRNA [10], rDNA [38], and in vivo ATP production [18] were observed in the CCC myocardium. Myocardial levels and activity of mitochondrial energy metabolism enzymes ATP synthase and creatine kinase are even lower than in CCC than other cardiomyopathies [17], which might contribute to the worse prognosis of CCC. This is in line with Nisha Garg's group findings implicating myocardial mitochondrial dysfunction and oxidative stress in the pathogenesis of murine models of CCC (reviewed in [39]). IFN-γ and brequinar treatment significantly reduced
mitochondrial membrane potential (ΔψM) on the AC16 hu-
man cardiomyocyte cell line. Significantly, cells treated simul-
taneously with IFN-γ, and brequinar showed an even larger
decrease on ΔψM. This result is consistent with an increased
susceptibility of cells with reduced mitochondrial enzyme ac-
tivity to IFN-γ. Even though the identified genes play impor-
tant roles in mitochondrial energy generation and physiology,
the heterozygous mitochondrial variants did not cause child-
hood signs of altered development typical of
mitochondriopathies and were only associated with progres-
sion to cardiac disease in *T. cruzi*-seropositive patients, whose
age group was typical from CCC patients in general. Taken
together, our results suggest that *T. cruzi*-induced IFN-γ is
necessary to cause clinically significant disease in patients
with heterozygous variants. We propose that long-term expo-
sure to high levels IFN-γ associated with CD – particularly
high in CCC myocardium [40] – is the additional mitochon-
drial insult suffered by carrier of heterozygous mitochondrial
variants that leads them to mitochondrial dysfunction. IFN-γ
has multiple deleterious effects on cardiomyocyte mitochon-
dria. It induces TNF-alpha and potentiates TNF-alpha-
mediated NF-kB signaling, leading to NOS2 production of
NO [41], which in the presence of IFN-γ-induced reactive
oxygen species turns into peroxynitrite [21], and ensuing mi-
tochondrial fragmentation and reduction of mitochondrial
membrane potential, lipid beta-oxidation [14], and ATP gen-
eration [22], leading to cardiomyocyte dysfunction and apo-
ptosis [15]. Variants in the inflammation-related genes may
also lead to a mitochondrial dysfunction phenotype. Gain-of-
function variants of genes linked to NF-kB or MAP kinase
signaling could lead to increased proinflammatory cytokine
production, which might lead to further mitochondrial dys-
function in cardiomyocytes [22], and this mitochondrial dam-
age can be further fueled by IFN-γ [42]. It is thus possible that
the common final pathogenic mechanism for mitochondrial
and inflammation-associated gene variants might involve en-
hancement of IFN-γ-induced cardiac mitochondrial damage.
As mitochondrial damage and release of damage-associated
molecular patterns can itself induce the production of proin-
flammatory cytokines, a self-perpetuating positive feedback
loop between inflammation and mitochondrial damage [43]
may contribute to the chronicity of inflammation in CCC heart
tissue.

Our study has limitations. CCC patients included in the
pedigrees mostly have major diagnostic ECG changes without
left ventricular dysfunction. However, follow-up studies show
that asymptomatic chagasic individuals with ECG abnormal-
ities typical of CCC show higher total and cardiac mortality in
relation to chagasic individuals with normal ECG; up to 50%
of deaths in this groups are due to SCD [6, 8, 44–46].
Similarly, conduction defects and arrhythmias can be the pre-
senting symptoms of genetic mitochondriopathies [47]. Even
though CCC has a progressive character and inflammatory

mediators and mitochondrial dysfunction are key participants
of arrhythmia [48] and heart failure [43], we can only hypoth-
esize that the genetic variants identified in our study may play
a direct role in the inflammation [10, 11] and mitochondrial
dysfunction [17, 38] observed in end-stage CCC.

Conclusion

Results indicate that the genetic contribution to CCC is poly-
genic and driven by several rare variants in genes that differ
between families but are related to mitochondria and inflam-
mation. Results imply that mitochondrial dysfunction and in-
flammation, key processes in the pathophysiology of CCC,
are at least in part genetically determined. To our knowledge,
this is the first report that rare variants in mitochondrial and
inflammation-related genes are linked to complex multifacto-
rial cardiomyopathy. Our results also support the notion of a
two-hit mechanism where IFN-γ and proinflammatory cyto-
kines induced by chronic infection trigger mitochondrial dys-
function and clinical disease in carriers of heterozygous mito-
chondrial gene variants. Indeed, modulation of mitochondrial
damage induced by IFN-γ and other cytokines could perhaps
be a suitable therapeutic target in CCC. Treatment with
mitochondria-protective agents such as antioxidants or ago-
nists of sirtuin-1 and AMP-activated protein kinase (AMPK)
was found to attenuate or even reverse cardiac damage in
mouse models of CCC, by reducing NF-kB activation and
the intensity of chronic myocarditis (reviewed in [38]). To
conclude, it is possible that a similar two-hit mechanism,
whereby genetic variants may increase mitochondrial suscep-
tibility to inflammatory cytokine-induced dysfunction, may be
relevant for the pathogenesis of other inflammatory cardiomy-
opathies and degenerative diseases associated with mitochon-
drial dysfunction.

**Abbreviations** *T. cruzi*, *Trypanosoma cruzi*; CCC, Chronic Chagas cardiomyopathy; CD, Chagas disease; ASY, Asymptomatic form; DCM, Dilated cardiomyopathy; ECG, Electrocardiography; IFN, Interferon; TNF, Tumor necrosis factor; NO, Nitrite oxide; ATP, Adenosine triphosphate; AVM, Acute viral myocarditis; WES, Whole exome sequencing; SCD, Sudden cardiac death; HF, Heart failure; LEPR, Leptin receptor; ADCY10, Adenylate cyclase 10; MOCS1, Molybdenum cofactor synthesis 1; ADGRG6, Adhesion G protein-coupled receptor G6; AKAP13, AKinase-anchoring protein 13; OBSCN, Obscurin; APOB, Apolipoprotein B; MRPS18B, Mitochondrial ribosomal protein S18B; PKHD1, Polycystic kidney and hepatic disease 1; RNLS, Renalase, FAD-dependent amine oxidase; GIT1, G protein-coupled receptor kinase interactor 1; LILRA2, Leukocyte immunoglobulin-like receptor A2; MAP 4 K4, Mitogen-activated protein kinase kinase kinase kinase 4; SLC11A1, Solute carrier family 11 member 1; RPUSD3, RNA pseudouridine synthase D3; UMPS, Uridine monophosphate synthetase; MAML1, Mastermind like transcriptional coactivator 1; DHODH, Dihydroorotate dehydrogenase; TNFRSF4, TNF receptor superfamily member 1; SERPINE2, Serpin family E member 2
**Supplementary Information** The online version contains supplementary material available at https://doi.org/10.1007/s10875-021-01000-y.

**Acknowledgments** We thank all the patients and their relatives.

**Availability of Data and Material** Raw data will be available on request.

**Authors' Contribution** Designed the study: JK, LAR, ECS, ECN, and CC.

Supervised the study as a whole: ECN and CC.

Participated in the recruitment of patients and sample collection: AFF, BI, AMF, CM, PB,

CIC, ORSJ, LCO, CDLO, MDCN, and LAR.

Performed experiments: MO, SM, RRA, JPN, LRPF, SB, DL, VOCR, DC, RCFZ, MT, FG, and PA.

Performed and supervised computational studies: LA, AC, ECN, and CC.

Wrote the manuscript: ECN and CC.

All authors reviewed the results and approved the final version of the manuscript.

**Funding** This work was supported by the Institut National de la Santé et de la Recherche Médicale (INSERM); the Aix-Marseille University (grant number: AMIDEX "International 2018" MITOMUTCHAGAS); the French Agency for Research (Agence Nationale de la Recherche-ANR (grant numbers: "Br-Fr-Chagas," "landscardio"); the CNPq (Brazilian Council for Scientific and Technological Development); the FAPESP (São Paulo State Research Funding Agency Brazil (grant numbers: 2013/50302-3, 2014/50890-5); and the National Institutes of Health/USA (grant numbers: 2 P50 AI098461-02 and 2U19AI098461-06). This project has received funding from the Excellence Initiative of Aix-Marseille University (A\*Midex) a French "Investissements d'Avenir programme"- Institute MarMaRa AMX-19-IET-007. ECN, JK, ALR, and ECS are recipients of productivity awards by CNPq. The funders do not play any role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.

**Declarations**

**Conflict of Interest** The authors declare that they have no conflict of interest.

**Open Access** This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

**References**

1. Schultheiss HP, Fairweather D, Caforio ALP, Escher F, Hershberger RE, Lipshultz SE, et al. Dilated cardiomyopathy. Nat Rev Dis Primers. 2019;5(1):32.

2. Chevillard C, Nunes JPS, Frade AF, Almeida RR, Pandey RP, Nascimento MS, et al. Disease tolerance and pathogen resistance genes may underlie trypanosoma cruzi persistence and differential progression to Chagas disease cardiomyopathy. Front Immunol. 2018;9:2791.

3. Bocchi EA, Bestetti RB, Scanavacca MI, Cunha Neto E, Issa VS. Chronic Chagas heart disease management: from etiology to cardiomyopathy treatment. J Am Coll Cardiol. 2017;70(12):1510-24.

4. Casado J, Davila DF, Donis JH, Torres A, Payares A, Colmenares R, et al. Electrocardiographic abnormalities and left ventricular systolic function in Chagas' heart disease. Int J Cardiol. 1990;27(1): 55-62.

5. Barbosa MP, da Costa Rocha MO, de Oliveira AB, Lombardi F, Ribeiro AL. Efficacy and safety of implantable cardioverter-defibrillators in patients with Chagas disease. Europace. 2013;15(7):957-62.

6. Baroldi G, Oliveira SJ, Silver MD. Sudden and unexpected death in clinically 'silent' Chagas' disease. A hypothesis. Int J Cardiol. 1997;58(3):263-8.

7. Higuchi ML, De Morais CF, Pereira Barreto AC, Lopes EA, Stolf N, Bellotti G, et al. The role of active myocarditis in the development of heart failure in chronic Chagas' disease: a study based on endomyocardial biopsies. Clin Cardiol. 1987;10(11):665-70.

8. Ribeiro AL, Marcolino MS, Prineas RJ, Lima-Costa MF. Electrocardiographic abnormalities in elderly Chagas disease patients: 10-year follow-up of the Bambui cohort study of aging. J Am Heart Assoc. 2014;3(1):e000632.

9. Abel LC, Rizzo LV, Ianni B, Albuquerque F, Bacal F, Carrara D, et al. Chronic Chagas' disease cardiomyopathy patients display an increased IFN-gamma response to trypanosoma cruzi infection. J Autoimmun. 2001;17(1):99-107.

10. Cunha-Neto E, Dzau VJ, Allen PD, Stamatiou D, Benvenutti L, Higuchi ML, et al. Cardiac gene expression profiling provides evidence for cytokinopathy as a molecular mechanism in Chagas' disease cardiomyopathy. Am J Pathol. 2005;167(2):305-13.

11. Nogueira LG, Santos RH, Fiorelli AI, Mairena EC, Benvenuti LA, Bocchi EA, et al. Myocardial gene expression of T-bet, GATA-3, Ror-gammat, FoxP3, and hallmark cytokines in chronic Chagas disease cardiomyopathy: an essentially unopposed TH1-type response. Mediat Inflamm. 2014;2014:914326.

12. Laugier L, Rodrigues Pinto Ferreira L, Moraes Ferreira F, Cabantous S, Frarge Frade A, Ribeiro Almeida R, et al. miRNAs may play a major role in the control of gene expression in key pathobiological processes in Chagas disease cardiomyopathy. Plos Negl Trop Dis. 2020; In press.

13. Patten M, Kramer E, Bunemann J, Wenck C, Thoenes M, Wieland T, et al. Endotoxin and cytokines alter contractile protein expression in cardiac myocytes in vivo. Pflugers Arch. 2001;442(6):920-7.

14. Ni C, Ma P, Wang R, Lou X, Liu X, Qin Y, et al. Doxorubicin-induced cardiotoxicity involves IFNgamma-mediated metabolic reprogramming in cardiomyocytes. J Pathol. 2019;247(3):320-32.

15. Levick SP, Goldspink PH. Could interferon-gamma be a therapeutic target for treating heart failure? Heart Fail Rev. 2014;19(2):227-36.

16. Soares MP, Gozzelino R, Weis S. Tissue damage control in disease tolerance. Trends Immunol. 2014;35(10):483-94.

17. Teixeira PC, Santos RH, Fiorelli AI, Bilate AM, Benvenuti LA, Stolf NA, et al. Selective decrease of components of the creatine kinase system and ATP synthase complex in chronic Chagas disease cardiomyopathy. PLoS Negl Trop Dis. 2011;5(6):e1205.

18. Leme AM, Salemi VM, Parga JR, Ianni BM, Mady C, Weiss RG, et al. Evaluation of the metabolism of high energy phosphates in patients with Chagas' disease. Arq Bras Cardiol. 2010;95(2):264-70.

19. Silva JS, Vespa GN, Cardoso MA, Aliberti JC, Cunha FQ. Tumor necrosis factor alpha mediates resistance to trypanosoma cruzi
infection in mice by inducing nitric oxide production in infected
gamma interferon-activated macrophages. Infect Immun.
1995;63(12):4862-7.

20. Vila-del Sol V, Punzon C, Fresno M. IFN-gamma-induced TNF-alpha expression is regulated by interferon regulatory factors 1 and 8 in mouse macrophages. J Immunol. 2008;181(7):4461-70.

21. Rakshit S, Chandrasekar BS, Saha B, Victor ES, Majumdar S, Nandi D. Interferon-gamma induced cell death: regulation and contributions of nitric oxide, cJun N-terminal kinase, reactive oxygen species and peroxynitrite. Biochim Biophys Acta. 2014;1843(11):2645-61.

22. Buoncervello M, Maccari S, Ascione B, Gambardella L, Marconi M, Spada M, et al. Inflammatory cytokines associated with cancer growth induce mitochondria and cytoskeleton alterations in cardiomyocytes. J Cell Physiol. 2019;234(11):20453-68.

23. Belkaya S, Kontorovich AR, Byun M, Mulero-Navarro S, Bajolle F, Cobat A, et al. Autosomal recessive cardiomyopathy presenting as acute myocarditis. J Am Coll Cardiol. 2017;69(13):1653-65.

24. Cardoso CS, Sabino EC, Oliveira CD, de Oliveira LC, Ferreira AM, Cunha-Neto E, et al. Longitudinal study of patients with chronic Chagas cardiomyopathy in Brazil (SaMi-trop project): a cohort profile. BMJ Open. 2016;6(5):e011181.

25. Marquet S, Bucheton B, Reymond C, Argiro L, El-Safi SH, Kheir MM, et al. Exome sequencing identifies two variants of the alkylglycerol monooxygenase gene as a cause of relapses in visceral leishmaniasis in children, in Sudan. J Infect Dis. 2017;216(1):22-8.

26. Khan R, Lee JE, Yang YM, Liang FX, Sehgal PB. Live-cell imaging of the association of STAT6-GFP with mitochondria. PLoS One. 2013;8(1):e55426.

27. Fang J, Uchiumi T, Yagi M, Matsumoto S, Amamoto R, Takazaki S, et al. Dihydro-orotate dehydrogenase is physically associated with the respiratory complex and its loss leads to mitochondrial dysfunction. Biosci Rep. 2013;33(2):e00021.

28. Arroyo JD, Jourdain AA, Calvo SE, Ballarano CA, Doench JG, Root DE, et al. A genome-wide CRISPR death screen identifies genes essential for oxidative phosphorylation. Cell Metab. 2016;24(6):875-85.

29. Grings M, Seminotti B, Karunanidhi A, Ghaloul-Gonzalez L, Mohsen AW, Wipf P, et al. ETHE1 and MOCS1 deficiencies: disruption of mitochondrial bioenergetics, dynamics, redox homeostasis and endoplasmic reticulum-mitochondria crosstalk in patient fibroblasts. Sci Rep. 2019;9(1):12651.

30. Pang J, Xu X, Getman MR, Shi X, Belmonte SL, Michaloski H, et al. G protein coupled receptor kinase 2 interacting protein 1 (GIT1) is a novel regulator of mitochondrial biogenesis in heart. J Mol Cell Cardiol. 2011;51(5):769-76.

31. Abella V, Scotece M, Conde J, Pino J, Gonzalez-Gay MA, Gomez-Reino JJ, et al. Leptin in the interplay of inflammation, metabolism and immune system disorders. Nat Rev Rheumatol. 2017;13(2):100-9.

32. Ding Y, Liu W, Deng Y, Jomok B, Yang J, Huang W, et al. Trapping cardiac recessive mutants via expression-based insertional mutagenesis screening. Circ Res. 2013;112(4):606-17.

33. Marston S. Obscurin variants and inherited cardiomyopathies. Biophys Rev. 2017;9(3):239-43.

34. Miyazawa S, Furuta S, Hashimoto T. Reduction of beta-oxidation capacity of rat liver mitochondria by feeding orotic acid. Biochim Biophys Acta. 1982;711(3):494-502.

35. Kohda M, Tokuzawa Y, Kishita Y, Nyuzuki H, Moriyama Y, Mizuno Y, et al. A comprehensive genomic analysis reveals the genetic landscape of mitochondrial respiratory chain complex deficiencies. PLoS Genet. 2016;12(1):e1005679.

36. Finsterer J, Kothari S. Cardiac manifestations of primary mitochondrial disorders. Int J Cardiol. 2014;177(3):754-63.

37. Finsterer J, Frank M. Gastrointestinal manifestations of mitochondrial disorders: a systematic review. Ther Adv Gastroenterol. 2017;10(1):142-54.

38. Wan X, Gupta S, Zago MP, Davidson MM, Dousset P, Amoroso A, et al. Defects of mtDNA replication impaired mitochondrial biogenesis during trypanosoma cruzi infection in human cardiomyocytes and chagasic patients: the role of Nrf1/2 and antioxidant response. J Am Heart Assoc. 2012;1(6):e003855.

39. Lopez M, Tanowitz HB, Garg NJ. Pathogenesis of chronic Chagas disease: macrophages, mitochondria, and oxidative stress. Curr Clin Microbiol Rep. 2018;5(1):45-54.

40. Reis MM, Higuchi Mde L, Benvenuti LA, Aiello VD, Gutierrez PS, Bellotti G, et al. An in situ quantitative immunohistochemical study of cytokines and IL-2R+ in chronic human chagasic myocarditis: correlation with the presence of myocardial trypanosoma cruzi antigens. Clin Immunol Immunopathol. 1997;83(2):165-72.

41. Kauppinen A, Suuronen T, Ojala J, Kaarniranta K, Salminen A. Antagonistic crosstalk between NF-kappaB and SIRT1 in the regulation of inflammation and metabolic disorders. Cell Signal. 2013;25(10):1939-48.

42. Lee HJ, Oh YK, Rhee M, Lim JY, Hwang JY, Park YS, et al. The role of STAT1/IRF-1 on synergistic ROS production and loss of mitochondrial transmembrane potential during hepatic cell death induced by LPS/d-GalN. J Mol Biol. 2007;369(4):967-84.

43. Zhou B, Tian R. Mitochondrial dysfunction in pathophysiology of heart failure. J Clin Invest. 2018;128(9):3716-26.

44. Manzullo EC, Chuit R. Risk of death due to chronic chagasic cardiopathy. Mem Inst Oswaldo Cruz. 1999;94(Suppl 1):317-20.

45. Pimenta J, Valente N, Miranda M. Long-term follow up of asymptomatic chagasic individuals with intraventricular conduction disturbances, correlating with non-chagasic patients. Rev Soc Bras Med Trop. 1999;32(6):621-31.

46. Rodriguez-Salas LA, Klein E, Acquatella H, Catalioti F, Davalos VV, Gomez-Mancebo JR, et al. Echocardiographic and clinical predictors of mortality in chronic Chagas' disease. Echocardiography. 1998;15(3):271-8.

47. Bonnet D, Martin D, Pascale De L, Villain E, Jouvet P, Rabier D, et al. Arrhythmias and conduction defects as presenting symptoms of fatty acid oxidation disorders in children. Circulation. 1999;100(22):2248-53.

48. Montaigne D, Marechal X, Lacroix D, Staels B. From cardiac mitochondrial dysfunction to clinical arrhythmias. Int J Cardiol. 2015;184:597-9.

**Publisher's Note** Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.