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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Genet.</journal-id>
<journal-title>Frontiers in Genetics</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Genet.</abbrev-journal-title>
<issn pub-type="epub">1664-8021</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="publisher-id">781189</article-id>
<article-id pub-id-type="doi">10.3389/fgene.2021.781189</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Genetics</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Mitochondrial Genome Study Identifies Association Between Primary Open-Angle Glaucoma and Variants in <italic>MT-CYB, MT-ND4</italic> Genes and Haplogroups</article-title>
<alt-title alt-title-type="left-running-head">Lo Faro et&#x20;al.</alt-title>
<alt-title alt-title-type="right-running-head">Mitochondrial Variations in POAG</alt-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Lo Faro</surname>
<given-names>Valeria</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1460618/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Nolte</surname>
<given-names>Ilja M.</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Ten Brink</surname>
<given-names>Jacoline B.</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1572925/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Snieder</surname>
<given-names>Harold</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Jansonius</surname>
<given-names>Nomdo M.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1209607/overview"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Bergen</surname>
<given-names>Arthur A.</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
<xref ref-type="corresp" rid="c001">&#x2a;</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1167782/overview"/>
</contrib>
<contrib contrib-type="collab">
<name>
<surname>Lifelines Cohort Study</surname>
</name>
</contrib>
</contrib-group>
<aff id="aff1">
<sup>1</sup>
<institution>Department of Ophthalmology, University of Groningen, University Medical Center Groningen</institution>, <addr-line>Groningen</addr-line>, <country>Netherlands</country>
</aff>
<aff id="aff2">
<sup>2</sup>
<institution>Department of Clinical Genetics, Amsterdam University Medical Center (AMC)</institution>, <addr-line>Amsterdam</addr-line>, <country>Netherlands</country>
</aff>
<aff id="aff3">
<sup>3</sup>
<institution>Department of Epidemiology, University of Groningen, University Medical Center Groningen</institution>, <addr-line>Groningen</addr-line>, <country>Netherlands</country>
</aff>
<aff id="aff4">
<sup>4</sup>
<institution>Department of Ophthalmology, Amsterdam UMC</institution>, <addr-line>Amsterdam</addr-line>, <country>Netherlands</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>
<bold>Edited by:</bold> <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/118246/overview">Enrico Baruffini</ext-link>, University of Parma, Italy</p>
</fn>
<fn fn-type="edited-by">
<p>
<bold>Reviewed by:</bold> <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/1242376/overview">Mercedes Fernandez-Moreno</ext-link>, Institute of Biomedical Research of A Coru&#xf1;a (INIBIC), Spain</p>
<p>
<ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/1285888/overview">Valentina Emmanuele</ext-link>, Columbia University Irving Medical Center, United&#x20;States</p>
</fn>
<corresp id="c001">&#x2a;Correspondence: Arthur A. Bergen, <email>aabergen@amsterdamumc.nl</email>
</corresp>
<fn fn-type="other">
<p>This article was submitted to Genetics of Common and Rare Diseases, a section of the journal Frontiers in Genetics</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>16</day>
<month>12</month>
<year>2021</year>
</pub-date>
<pub-date pub-type="collection">
<year>2021</year>
</pub-date>
<volume>12</volume>
<elocation-id>781189</elocation-id>
<history>
<date date-type="received">
<day>22</day>
<month>09</month>
<year>2021</year>
</date>
<date date-type="accepted">
<day>29</day>
<month>11</month>
<year>2021</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2021 Lo Faro, Nolte, Ten Brink, Snieder, Jansonius, Bergen and Lifelines Cohort Study.</copyright-statement>
<copyright-year>2021</copyright-year>
<copyright-holder>Lo Faro, Nolte, Ten Brink, Snieder, Jansonius, Bergen and Lifelines Cohort Study</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these&#x20;terms.</p>
</license>
</permissions>
<abstract>
<p>
<bold>Background and purpose:</bold> Primary open-angle glaucoma (POAG) is an optic neuropathy characterized by death of retinal ganglion cells and atrophy of the optic nerve head. The susceptibility of the optic nerve to damage has been shown to be mediated by mitochondrial dysfunction. In this study, we aimed to determine a possible association between mitochondrial SNPs or haplogroups and&#x20;POAG.</p>
<p>
<bold>Methods:</bold> Mitochondrial DNA single nucleotide polymorphisms (mtSNPs) were genotyped using the Illumina Infinium Global Screening Array-24 (GSA) 700K array set. Genetic analyses were performed in a POAG case-control study involving the cohorts, Groningen Longitudinal Glaucoma Study-Lifelines Cohort Study and Amsterdam Glaucoma Study, including 721 patients and 1951 controls in total. We excluded samples not passing quality control for nuclear genotypes and samples with low call rate for mitochondrial variation. The mitochondrial variants were analyzed both as SNPs and haplogroups. These were determined with the bioinformatics software HaploGrep, and logistic regression analysis was used for the association, as well as for&#x20;SNPs.</p>
<p>
<bold>Results:</bold> Meta-analysis of the results from both cohorts revealed a significant association between POAG and the allele A of rs2853496 [odds ratio (OR) &#x3d; 0.64; <italic>p</italic>&#x20;&#x3d; 0.006] within the <italic>MT-ND4</italic> gene, and for the T allele of rs35788393 (OR &#x3d; 0.75; <italic>p</italic>&#x20;&#x3d; 0.041) located in the <italic>MT-CYB</italic> gene. In the mitochondrial haplogroup analysis, the most significant <italic>p</italic>-value was reached by haplogroup K (<italic>p</italic>&#x20;&#x3d; 1.2 &#xd7; 10<sup>&#x2212;05</sup>), which increases the risk of POAG with an OR of 5.8 (95% CI 2.7&#x2013;13.1).</p>
<p>
<bold>Conclusion:</bold> We identified an association between POAG and polymorphisms in the mitochondrial genes <italic>MT-ND4</italic> (rs2853496) and <italic>MT-CYB</italic> (rs35788393), and with haplogroup K. The present study provides further evidence that mitochondrial genome variations are implicated in POAG. Further genetic and functional studies are required to substantiate the association between mitochondrial gene polymorphisms and POAG and to define the pathophysiological mechanisms of mitochondrial dysfunction in glaucoma.</p>
</abstract>
<kwd-group>
<kwd>mitochondrial polymorphism</kwd>
<kwd>mitochondrial haplogroup</kwd>
<kwd>primary open-angle glaucoma (POAG)</kwd>
<kwd>MT-CYB</kwd>
<kwd>MT-ND4</kwd>
<kwd>haplogroup K</kwd>
<kwd>genetic association study</kwd>
</kwd-group>
</article-meta>
</front>
<body>
<sec id="s1">
<title>Introduction</title>
<p>Primary open-angle glaucoma (POAG) is a complex and chronic eye disease characterized by progressive death of retinal ganglion cells (RGCs), which manifests itself initially as visual field loss. Untreated POAG ultimately leads to irreversible blindness (<xref ref-type="bibr" rid="B79">Tham et&#x20;al., 2014</xref>). High intraocular pressure (IOP) is the first and major risk factor identified in patients with POAG (<xref ref-type="bibr" rid="B74">Shaffer, 1996</xref>), in addition other known risk factors are advanced age, myopia, ethnicity, and positive family history for POAG (<xref ref-type="bibr" rid="B32">Gramer and Grehn, 2012</xref>). Nowadays, the only efficacious therapy for protecting the RCGs (from which the axons form the optic nerve) in POAG is directed towards decreasing IOP. POAG is also defined as a genetically complex disease because many genes have been associated with this condition (<xref ref-type="bibr" rid="B80">Thorleifsson et&#x20;al., 2010</xref>; <xref ref-type="bibr" rid="B14">Burdon et&#x20;al., 2011</xref>; <xref ref-type="bibr" rid="B67">Ramdas et&#x20;al., 2011</xref>; <xref ref-type="bibr" rid="B92">Wiggs et&#x20;al., 2011</xref>; <xref ref-type="bibr" rid="B15">Cao et&#x20;al., 2012</xref>; <xref ref-type="bibr" rid="B61">Osman et&#x20;al., 2012</xref>; <xref ref-type="bibr" rid="B50">Liu et&#x20;al., 2013</xref>; <xref ref-type="bibr" rid="B18">Chen et&#x20;al., 2014</xref>; <xref ref-type="bibr" rid="B28">Gharahkhani et&#x20;al., 2014</xref>; <xref ref-type="bibr" rid="B78">Springelkamp et&#x20;al., 2015</xref>; <xref ref-type="bibr" rid="B82">Trikha et&#x20;al., 2015</xref>; <xref ref-type="bibr" rid="B19">Choquet et&#x20;al., 2018</xref>; <xref ref-type="bibr" rid="B63">Pasquale, 2019</xref>). Rearrangements in the DNA and multiple disease genes have been implicated in the pathogenesis of POAG (<xref ref-type="bibr" rid="B23">Davis et&#x20;al., 2011</xref>; <xref ref-type="bibr" rid="B44">Janssen et&#x20;al., 2013</xref>; <xref ref-type="bibr" rid="B49">Liu et&#x20;al., 2014</xref>; <xref ref-type="bibr" rid="B51">Lo Faro et&#x20;al., 2021</xref>). Known disease genes include myocilin (<italic>MYOC</italic>), optineurin (<italic>OPTN</italic>), WD repeat domain 36 (<italic>WDR36</italic>), cytochrome P450 family 1 subfamily B polypeptide 1 (<italic>CYP1B1</italic>), and TANK-binding kinase 1 (<italic>TBK1</italic>) (<xref ref-type="bibr" rid="B44">Janssen et&#x20;al., 2013</xref>). So far, more than 120 chromosomal loci have been discovered through genome-wide association studies (<xref ref-type="bibr" rid="B14">Burdon et&#x20;al., 2011</xref>; <xref ref-type="bibr" rid="B67">Ramdas et&#x20;al., 2011</xref>; <xref ref-type="bibr" rid="B19">Choquet et&#x20;al., 2018</xref>; <xref ref-type="bibr" rid="B29">Gharahkhani et&#x20;al., 2021</xref>). Even so, the disease genes and genetic risk factors identified only explain a small proportion of POAG heritability, and contribute relatively little to understanding the pathogenetic mechanisms. To date, the majority of the genetic studies aim to identify the causes underlying POAG by focusing on the nuclear genome. We and other researchers have postulated that at least part of the remaining POAG heritability might be found in variants in the mitochondrial DNA (mtDNA) (<xref ref-type="bibr" rid="B48">Lascaratos et&#x20;al., 2012</xref>; <xref ref-type="bibr" rid="B60">Osiewacz, 2014</xref>; <xref ref-type="bibr" rid="B94">Williams et&#x20;al., 2017</xref>).</p>
<p>The mitochondrion is an organelle mainly involved in the production of cellular energy with distinct extrachromosomal circular and double-stranded molecules of DNA. The mtDNA is transmitted through the maternal germline and it has a unique subcellular transcription and replication machinery (<xref ref-type="bibr" rid="B86">Vincent and Picard et&#x20;al., 2018</xref>). Mutations in the mtDNA have previously been implicated in cellular energy deficits that lead to ocular degenerative disease (<xref ref-type="bibr" rid="B98">Yu-Wai-Man et&#x20;al., 2011</xref>). Indeed, the mitochondria can be considered as a &#x201c;power plant&#x201d; for the cell, then it is expected that mitochondrial disorders tend to affect more frequently tissues with high energy demand, such as the retina, brain, muscles, heart, and endocrine systems (<xref ref-type="bibr" rid="B88">Wallace, 2010</xref>). A characteristic of the mitochondrial genome (mtGenome) is that it accumulates mutations at a notably faster rate than the nuclear genome. As a result, mtDNA is highly polymorphic. Most likely, this characteristic can be explained by two processes: the lack of protective histones and repair mechanisms, which increase the replication errors, and, given the proximity of mtDNA with the respiratory chain complexes, the exposure to reactive oxygen species (ROS) (<xref ref-type="bibr" rid="B88">Wallace, 2010</xref>; <xref ref-type="bibr" rid="B48">Lascaratos et&#x20;al., 2012</xref>).</p>
<p>Many mitochondrial single-nucleotide polymorphisms (mtSNPs) have become fixed in a variety of populations during human evolution (<xref ref-type="bibr" rid="B98">Yu-Wai-Man et&#x20;al., 2011</xref>; <xref ref-type="bibr" rid="B21">Collins et&#x20;al., 2016</xref>). Due to the exclusive maternal inheritance of mtDNA and the fact that the mtGenome does not recombine, mtSNPs are accumulating and co-transmitted through the maternal lineages (<xref ref-type="bibr" rid="B7">Andersen and Balding et&#x20;al., 2018</xref>). This characteristic allows tracing specific, ancestral patterns of human migration that occurred millennia ago, from Africa to other continents. These specific polymorphic SNP-sets accumulating on the mtDNA, allowed researchers to classify human populations into various mtDNA &#x2018;&#x2018;haplogroups&#x201d;. There are a total of nine known haplogroups that identify individuals with European ancestry. These are named H, I, J, K, T, U, V, W, and X, where haplogroup H represents about 40&#x2013;45% of the total. According to recent studies, specific haplogroups can influence the development of diseases such as POAG, primary angle-closure glaucoma, exfoliation glaucoma, as well as cancer, diabetes, and late-onset neurodegenerative conditions (<xref ref-type="bibr" rid="B37">Herrnstadt et&#x20;al., 2002</xref>; <xref ref-type="bibr" rid="B4">Abu-Amero et&#x20;al., 2008</xref>; <xref ref-type="bibr" rid="B85">van Oven and Kayser, 2009</xref>; <xref ref-type="bibr" rid="B1">Abu-Amero et&#x20;al., 2011a</xref>; <xref ref-type="bibr" rid="B2">Abu-Amero et&#x20;al., 2011b</xref>; <xref ref-type="bibr" rid="B83">Urzua-Traslavina and Carlos, 2014</xref>). The association between mitochondrial haplogroups and POAG has been investigated in few studies, with conflicting results: <xref ref-type="bibr" rid="B8">Andrews et&#x20;al. (2006)</xref>, in a case-control comparison of 140 POAG patients and 75 healthy individuals from England, did not find a difference in the haplogroup distribution between cases and controls (<xref ref-type="bibr" rid="B5">Andrews et&#x20;al., 2006</xref>). In contrast, <xref ref-type="bibr" rid="B21">Collins et&#x20;al. (2016)</xref> found that in African populations the haplogroups L1c2, L1c2b, and L2 were risk factors for POAG (<xref ref-type="bibr" rid="B21">Collins et&#x20;al., 2016</xref>).</p>
<p>An important aspect in the pathophysiology of POAG and similar optic neuropathies is represented by the increased apoptosis of RGCs, and by the functional decay of the trabecular meshwork (TM) (<xref ref-type="bibr" rid="B66">Izzotti et&#x20;al., 2011</xref>; <xref ref-type="bibr" rid="B6">Almasieh et&#x20;al., 2012</xref>). RGCs contain a high number of mitochondria related to their high energy demand. They are especially vulnerable to oxidative damage caused by mitochondrial dysfunction (<xref ref-type="bibr" rid="B53">Sanchez et&#x20;al., 2016</xref>). Apart from POAG, several other optic neuropathies show axonal RGC loss correlated with mitochondrial dysfunction (<xref ref-type="bibr" rid="B40">Howell, 1997</xref>; <xref ref-type="bibr" rid="B41">Howell, 2003</xref>). Two examples are Leber&#x2019;s Hereditary Optic Neuropathy (LHON; OMIM 535000) and autosomal dominant optic atrophy (DOA; OMIM 165500). While LHON is caused by three well-known pathogenic mtDNA mutations in the <italic>MT-ND1, MT-ND4</italic>, and <italic>MT-ND6</italic> genes, DOA is caused by pathogenic mutations within the nuclear <italic>OPA1</italic> gene, which codes for a mitochondrial wall membrane protein (<xref ref-type="bibr" rid="B97">Yu-Wai-Man et&#x20;al., 2009</xref>; <xref ref-type="bibr" rid="B88">Wallace, 2010</xref>; <xref ref-type="bibr" rid="B98">Yu-Wai-Man et&#x20;al., 2011</xref>).</p>
<p>Next to mitochondrial damage in the RGCs, Izzotti and coworkers investigated potential mitochondrial damage in the TM, a tissue involved in POAG via its influence on IOP. By comparing mtDNA deletions in TM from glaucoma patients and controls by qRT-PCR, the authors observed that oxidative damage arising from mitochondrial failure plays a role in the functional decay of the TM (<xref ref-type="bibr" rid="B66">Izzotti et&#x20;al., 2011</xref>). Another, independent line of evidence for mitochondrial involvement in POAG has come from investigations of glaucoma-prone mice: retinal levels of nicotinamide adenine dinucleotide (NAD) decreased with age, rendering neurons vulnerable to disease-related insults. Interestingly, the administration of a redox metabolite NAD&#x2b; and gene therapy of the expression of <italic>Nmnat1</italic>, a key NAD &#x2b; producing enzyme, had a protective effect. At the highest dose tested, 93% of eyes did not develop glaucoma symptomatology, compared to 50% for the control group (<xref ref-type="bibr" rid="B94">Williams et&#x20;al., 2017</xref>).</p>
<p>Given the hypothesis that RGCs degeneration and functional decay of TM in POAG are influenced by mitochondrial dysfunction, we aimed to explore whether POAG is associated with variations in the mtGenome. To this purpose, we conducted two different association analyses further described below. First, we analyzed mtDNA SNPs in order to detect genetic variations potentially associated with the disease. Second, we analyzed the role of major haplogroups.</p>
</sec>
<sec sec-type="materials|methods" id="s2">
<title>Materials and Methods</title>
<sec id="s2-1">
<title>Study Subjects</title>
<p>We performed our association analysis using two case-control studies. The first case-control study consisted of glaucoma cases from the Groningen Longitudinal Glaucoma Study (GLGS), of which a subset of the POAG patients (see below) was genotyped (<italic>n</italic>&#x20;&#x3d; 592) (<xref ref-type="bibr" rid="B36">Heeg et&#x20;al., 2005</xref>). The controls (<italic>n</italic>&#x20;&#x3d; 1841) were selected from the Lifelines Cohort Study and Biobank (LL) and came from the same geographical region as the GLGS cases. This cohort is addressed in this study as the GLGS-LL cohort. They were age-matched with a 1:3 ratio, using the R package MatchIt with nearest-neighbor matching (<xref ref-type="bibr" rid="B38">Ho et&#x20;al., 2011</xref>). The second case-control study consisted of glaucoma cases (<italic>n</italic>&#x20;&#x3d; 129) and controls (<italic>n</italic>&#x20;&#x3d; 110) from the Amsterdam Glaucoma Study (AGS) (<xref ref-type="bibr" rid="B67">Ramdas et&#x20;al., 2011</xref>). All the participants were Dutch and of European-ancestry.</p>
<p>The original GLGS cohort has been described in detail by Heeg and colleagues (<xref ref-type="bibr" rid="B36">Heeg et&#x20;al., 2005</xref>). After the inclusion of the initial cohort in 2000&#x2013;2001, the GLGS continued as a dynamic population, that is, new participants were added during follow-up. We included glaucoma patients who visited the outpatient department of the UMCG in 2015 and who gave written informed consent for a blood sample being taken for genetic analyses. In the GLGS, glaucoma patients showed glaucomatous visual field (VF) loss in at least one eye. For glaucomatous baseline VF loss, two consecutive tests had to be abnormal in at least one eye. Defects had to be compatible with glaucoma and without any other explanation. A VF test before the two baseline tests was discarded to reduce the influence of learning. Those with pseudoexfoliative or pigment dispersion glaucoma or a history of angle-closure or secondary glaucoma were excluded for the current analysis, leaving only POAG patients.</p>
<p>The LL is a multi-disciplinary prospective population-based cohort study examining in a unique three-generation design the health and health-related behaviours of 167,729 persons living in the North of Netherlands. It employs a broad range of investigative procedures in assessing the biomedical, socio-demographic, behavioural, physical and psychological factors which contribute to the health and disease of the general population, with a special focus on multi-morbidity and complex genetics. Participants completed questionnaires, underwent physical examinations, and biological samples including DNA were collected (<xref ref-type="bibr" rid="B72">Scholtens et&#x20;al., 2015</xref>). For the current study, we only included participants without glaucoma and aged 60&#x20;years or older. Glaucoma phenotype was defined using a questionnaire-based glaucoma proxy, a classification algorithm built on questions regarding self-reported eye diseases and glaucoma-specific visual complaints (<xref ref-type="bibr" rid="B59">Neustaeter et&#x20;al., 2020</xref>). Participants were classified as having definite, probable, or possible glaucoma, or as healthy. Lifelines controls used in this study were those individuals classified by the proxy as healthy and from whom the genotyping data was available.</p>
<p>The AGS study includes glaucoma cases and healthy controls collected from eye clinics, meetings of the glaucoma patients&#x2019; association, nursing homes, and fairs for the elderly from all over the Netherlands. The AGS patients underwent ophthalmoscopy and biomicroscopy with a 90-diopter lens, and digital stereo images of the optic nerve head were taken after mydriatic drops. POAG cases had to have glaucomatous optic neuropathy vertical cup-disc ratio (VCDR) &#x3e; 0.7 with corresponding glaucomatous visual field loss in at least one eye or a VCDR &#x2265; 0.8 when no visual field was available (<xref ref-type="bibr" rid="B67">Ramdas et&#x20;al., 2011</xref>). Control subjects from the AGS cohort were selected from unrelated individuals, aged 60&#x20;years or older with a VCDR &#x2264; 0.6 on ophthalmoscopy and fundus photography, and without eye abnormalities.</p>
</sec>
<sec id="s2-2">
<title>Genotyping</title>
<p>Genomic DNA was extracted from the peripheral blood and all individuals were genotyped using the Illumina Infinium Global Screening Array&#xae; (GSA) MultiEthnic Disease beadchip version. This array contains approximately 700,000 SNPs and combines multi-ethnic genome-wide content, curated clinical research variants, and quality control (QC) markers. Specifically, for the mtDNA, this array covers 140 mtDNA SNPs. For these latter SNPs, the raw probe intensities were combined in one dataset and called together with Opticall using the -MT option (<xref ref-type="bibr" rid="B75">Shah et&#x20;al., 2012</xref>). To obtain position, strand orientation, and reference allele of mtDNA for our data, we aligned the genotypes with the Cambridge Reference Sequence (rCRS) (<xref ref-type="bibr" rid="B25">ENCODE Project Consortium 2012</xref>). For further analysis, we considered only variants that could be mapped perfectly with the reference panel. Next, the following quality control (QC) criteria were applied to SNPs level: 95% call rate per mtDNA SNP in the combined set of case and control individuals and heterozygote mitochondrial genotypes were set to missing, allowing only homozygous calls. At DNA sample level the quality control was first conducted in the autosomal chromosomes and exclusion criteria were 1) duplicated sample, 2) excessive heterozygosity rate, 3) sex discordance, 4) the presence of first and/or second-degree relatives (pi-hat &#x3e;0.20), and 5) non-European ancestry.</p>
<p>The genotyping datasets of AGS and GLGS-LL were then imputed in IMPUTE2 (<xref ref-type="bibr" rid="B42">Howie et&#x20;al., 2009</xref>). Before the imputation, monomorphic variants were removed and all samples were assigned to male sex to allow haploid imputation. Then we followed instructions for the imputation of chromosome X. The reference panel used contained 36,960 sequences aligned to mtDNA sequences (<xref ref-type="bibr" rid="B55">McInerney et&#x20;al., 2021</xref>). Variants with imputation quality score less than 0.3 and monomorphic variants were excluded.</p>
</sec>
<sec id="s2-3">
<title>Statistical Analysis</title>
<p>To test for association of the mtDNA SNP markers with glaucoma, logistic regressions were conducted separately for GLGS-LL and AGS, with POAG as outcome and SNP as independent variable, adjusting for age and sex. We choose to analyze the two cohorts separately to avoid risk of batch effects and false positive results caused by population stratification. Only SNPs with a minor allele frequency (MAF) &#x3e; 1% were included in this analysis. To estimate the risks of POAG, odds ratios (ORs) and 95% confidence intervals (CIs) were calculated. Analyses were also performed stratified by sex. The genetic analyses were conducted using PLINK v1.90 (<xref ref-type="bibr" rid="B64">Purcell et&#x20;al., 2007</xref>). Subsequently, we combined the results of the two cohorts by a fixed effects inverse variance weighted meta-analysis using METAL software in which double genomic control was applied (<xref ref-type="bibr" rid="B93">Willer et&#x20;al., 2010</xref>).</p>
<p>A second association analysis was done in the two cohorts separately on reconstructed haplogroups. Since the mtDNA does not recombine, it behaves like a single locus with many alleles making all variants correlated with each other. Mitochondrial haplogroups were estimated from the directly genotyped variants and the haplogroup of each individual was determined with HaploGrep, available at <ext-link ext-link-type="uri" xlink:href="https://haplogrep.i-med.ac.at/">https://haplogrep.i-med.ac.at/</ext-link> (<xref ref-type="bibr" rid="B85">van Oven and Kayser, 2009</xref>; <xref ref-type="bibr" rid="B46">Kloss-Brandst&#xe4;tter et&#x20;al., 2011</xref>). All 140 mtDNA SNPs were entered for the haplogroup determination, and each individual&#x2019;s haplogroup was determined based on PhyloTree build 17 (implemented in HaploGrep 2.1.21.jar). We only included haplogroup assignments with a quality score above 80% (determined by HaploGrep), and with a frequency above 1% (<xref ref-type="bibr" rid="B85">van Oven and Kayser, 2009</xref>; <xref ref-type="bibr" rid="B46">Kloss-Brandst&#xe4;tter et&#x20;al., 2011</xref>). For the association test, sub-haplogroups were first assigned to their respective major haplogroups. We tested each haplogroup against haplogroup H, which is the most common European haplogroup (22.9% in our dataset; see Discussion section), as the reference using logistic regression, adjusting for age and sex (<xref ref-type="bibr" rid="B81">Torroni and Wallace et&#x20;al., 1994</xref>). Chi-square analysis was conducted to determine the effect of specified sub-haplogroup K (K1, K1a1, K1a11, K1a1b2a1, K1a24a, K1a4a, K1a4a1a2a, K1b2a, and K1c1).</p>
<p>Given the hypothesis-free approach of our exploratory study and the risk to test not independent SNPs due to high linkage disequilibrium in mtDNA, we reported nominal significant <italic>p</italic>-values (&#x2264;0.05) (<xref ref-type="bibr" rid="B7">Andersen and Balding et&#x20;al., 2018</xref>). The analyses were performed using RStudio.</p>
</sec>
<sec id="s2-4">
<title>Gene Expression</title>
<p>In order to evaluate gene expression of significant SNPs, we queried the EyeIntegration database v1.05 (<ext-link ext-link-type="uri" xlink:href="https://eyeintegration.nei.nih.gov/">https://eyeintegration.nei.nih.gov/</ext-link>) in cornea, retina, and retinal pigment epithelium (RPE) (<xref ref-type="bibr" rid="B13">Bryan et&#x20;al., 2018</xref>). This database is created by investigators at the National Eye Institute (National Institutes of Health) and contains publicly deposited RNA-seq datasets from human ocular tissues (<xref ref-type="bibr" rid="B13">Bryan et&#x20;al., 2018</xref>). Gene correlation networks were constructed using the kWithin metric to measure the connectivity. Genes with higher connectivity are, theoretically, more likely to be important in gene regulation as perturbations in them will affect the system more than less connected genes. Identified genes, either those closest to significant SNPs or resulting from the gene correlation network, were queried in the Online Mendelian Inheritance in Man (OMIM) database, to identify associated phenotypes (<xref ref-type="bibr" rid="B34">Hamosh, 2004</xref>).</p>
</sec>
<sec id="s2-5">
<title>Ethics Statement</title>
<p>The study followed the tenets of the Declaration of Helsinki and the ethics board of the University Medical Center of Amsterdam (UMC) approved this research (METc submission &#x23; 2013_327). All participants provided written informed consent.</p>
</sec>
</sec>
<sec sec-type="results" id="s3">
<title>Results</title>
<p>A total of 2,672 individuals were included. <xref ref-type="table" rid="T1">Table&#x20;1</xref> shows the demographics of both cohorts.</p>
<table-wrap id="T1" position="float">
<label>TABLE 1</label>
<caption>
<p>Characteristics of the GLGS-LL and AGS cohorts.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th rowspan="2" align="left"/>
<th colspan="2" align="center">GLGS-LL</th>
<th colspan="2" align="center">AGS</th>
</tr>
<tr>
<th align="center">Cases (<italic>n</italic>&#x20;&#x3d; 592)</th>
<th align="center">Controls (<italic>n</italic>&#x20;&#x3d; 1841)</th>
<th align="center">Cases (<italic>n</italic>&#x20;&#x3d; 129)</th>
<th align="center">Controls (<italic>n</italic>&#x20;&#x3d; 110)</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="left">Age [median (IQR)]</td>
<td align="char" char="(">73 (66, 80)</td>
<td align="char" char="(">70 (68, 73)</td>
<td align="char" char="(">73 (65, 79)</td>
<td align="char" char="(">72 (68, 79)</td>
</tr>
<tr>
<td align="left">Sex, female, n (%)</td>
<td align="char" char="(">264 (44.5)</td>
<td align="char" char="(">801 (43.5)</td>
<td align="char" char="(">57 (44.1)</td>
<td align="char" char="(">67 (60.9)</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>IQR: interquartile&#x20;range.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<sec id="s3-1">
<title>Single SNP Analysis</title>
<p>In total, 140 mtSNPs were initially screened on the DNA of our case control populations. Forty SNPs in the GLGS-LL dataset and 39 SNPs in the AGS cohort passed the quality control criteria previously mentioned (see Subjects and Methods section) and were used for further analysis. In the GLGS-LL cohort we excluded 51 SNPs that were monomorphic or had a low MAF. We excluded 49 additional ones for a relatively high missing genotype rate. In the AGS cohort, 101 mtDNA SNPs were monomorphic or had a low MAF but we did not exclude any SNP for high missing genotype rate. After imputation, 69 and 63 variants were retained in the GLGS-LL and AGS cohorts, respectively.</p>
<p>Logistic regression analyses were conducted separately in the GLGS-LL and AGS datasets, where POAG was modelled as the dependent variable and the genotyped variants as the independent variable (<xref ref-type="table" rid="T2">Table&#x20;2</xref>).</p>
<table-wrap id="T2" position="float">
<label>TABLE 2</label>
<caption>
<p>Significant mtDNA single-nucleotide polymorphisms associated with POAG in the GLGS-LL and AGS cohorts, separated for&#x20;sex.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="left"/>
<th align="center">Marker</th>
<th align="center">Single-nucleotide polymorphism</th>
<th align="center">Nearest gene</th>
<th align="center">Effect allele</th>
<th align="center">No effect allele</th>
<th align="center">Frq&#x2a; Case/Control</th>
<th align="center">Odds ratio (95% CI&#x2a;&#x2a;)</th>
<th align="center">
<italic>p</italic>-value</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td colspan="9" align="left">GLGS-LL</td>
</tr>
<tr>
<td align="left">Both sex</td>
<td align="center">
<italic>MitoG11915A</italic>
</td>
<td align="center">rs2853496</td>
<td align="left">
<italic>MT-ND4</italic>
</td>
<td align="center">A</td>
<td align="center">G</td>
<td align="char" char="/">0.006/ 0.023</td>
<td align="char" char="(">0.27 (0.01&#x2013;0.78)</td>
<td align="char" char=".">0.015</td>
</tr>
<tr>
<td align="left">Female</td>
<td align="center">
<italic>MitoG11915A</italic>
</td>
<td align="center">rs2853496</td>
<td align="left">
<italic>MT-ND4</italic>
</td>
<td align="center">A</td>
<td align="center">G</td>
<td align="char" char="/">0.003/0.03</td>
<td align="char" char="(">0.12 (0.016&#x2013;0.88)</td>
<td align="char" char=".">0.038</td>
</tr>
<tr>
<td align="left">Male</td>
<td align="center">
<italic>2010&#x2013;08-MT-723</italic>
</td>
<td align="center">rs879162984</td>
<td align="left">D-loop</td>
<td align="center">A</td>
<td align="center">G</td>
<td align="char" char="/">0.036/0.015</td>
<td align="char" char="(">2.41 (1.12&#x2013;5.2)</td>
<td align="char" char=".">0.024</td>
</tr>
<tr>
<td align="left">
</td>
<td align="center">
<italic>MitoA16163G</italic>
</td>
<td align="center">rs41466049</td>
<td align="left">
<italic>MT-CYB</italic>
</td>
<td align="center">G</td>
<td align="center">A</td>
<td align="char" char="/">0.073/0.046</td>
<td align="char" char="(">1.77 (1.06&#x2013;2.96)</td>
<td align="char" char=".">0.027</td>
</tr>
<tr>
<td colspan="9" align="left">AGS</td>
</tr>
<tr>
<td align="left">Both sex</td>
<td align="center">
<italic>rs2853826</italic>
</td>
<td align="center">
<italic>rs2853826</italic>
</td>
<td align="left">
<italic>MT-ND3</italic>
</td>
<td align="center">G</td>
<td align="center">A</td>
<td align="char" char="/">0.24/0.10</td>
<td align="char" char="(">2.29 (1.11&#x2013;4.69)</td>
<td align="char" char=".">0.023</td>
</tr>
<tr>
<td align="left">
</td>
<td align="center">
<italic>MitoT12706C</italic>
</td>
<td align="center">rs193302956</td>
<td align="left">
<italic>MT-ND5</italic>
</td>
<td align="center">T</td>
<td align="center">C</td>
<td align="char" char="/">0.11/0.045</td>
<td align="char" char="(">3.53 (1.12&#x2013;11.18)</td>
<td align="char" char=".">0.031</td>
</tr>
<tr>
<td align="left">
</td>
<td align="center">
<italic>MitoT491C</italic>
</td>
<td align="center">rs28625645</td>
<td align="left">D-loop</td>
<td align="center">C</td>
<td align="center">T</td>
<td align="char" char="/">0.10/ 0.03</td>
<td align="char" char="(">3.21 (1.001&#x2013;10.34)</td>
<td align="char" char=".">0.049</td>
</tr>
<tr>
<td align="left">Female</td>
<td align="center">
<italic>rs2853826</italic>
</td>
<td align="center">
<italic>rs2853826</italic>
</td>
<td align="left">
<italic>MT-ND3</italic>
</td>
<td align="center">G</td>
<td align="center">A</td>
<td align="char" char="/">0.22/0.075</td>
<td align="char" char="(">3.69 (1.22&#x2013;11.17)</td>
<td align="char" char=".">0.02</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Abbreviations: &#x2a;Frq, frequency of effect allele; &#x2a;&#x2a;CI, confidence interval.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<p>These results were then meta-analyzed for 32 SNPs in common between the two datasets, revealing nominal associations in the mtDNA SNPs rs2853496 (<italic>p</italic>&#x20;&#x3d; 0.006) and rs35788393 (<italic>p</italic>&#x20;&#x3d; 0.041) with POAG, in the sex combined cohorts (<xref ref-type="table" rid="T3">Table&#x20;3</xref>).</p>
<table-wrap id="T3" position="float">
<label>TABLE 3</label>
<caption>
<p>Nominal significant mtDNA SNPs associated with POAG from the meta-analysis of the GLGS-LL and AGS cohorts, conducted in both&#x20;sexes.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="left">SNP</th>
<th align="center">Position</th>
<th align="center">Gene</th>
<th align="center">Effect allele</th>
<th align="center">No effect allele</th>
<th align="center">Odds ratio</th>
<th align="center">
<italic>p</italic>-value</th>
<th align="center">Hetisq</th>
<th align="center">Hetpval</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="left">rs2853496</td>
<td align="center">11,914</td>
<td align="center">
<italic>MT-ND4</italic>
</td>
<td align="center">A</td>
<td align="center">G</td>
<td align="char" char=".">0.64</td>
<td align="char" char=".">0.006</td>
<td align="center">0</td>
<td align="char" char=".">0.92</td>
</tr>
<tr>
<td align="left">rs35788393</td>
<td align="center">15,904</td>
<td align="center">
<italic>MT-CYB</italic>
</td>
<td align="center">T</td>
<td align="center">C</td>
<td align="char" char=".">0.75</td>
<td align="char" char=".">0.041</td>
<td align="center">0</td>
<td align="char" char=".">0.93</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>SNP&#x2014;single nucleotide polymorphism; Hetpval&#x2014;heterogeneity <italic>p</italic>-values from Cochrane&#x2019;s Q statistic; Hetisq&#x2014;heterogeneity index (0&#x2013;100%).</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s3-2">
<title>Haplogroup Analysis</title>
<p>In addition to single SNP association analyses, we also conducted an association test between mitochondrial haplogroups and POAG. The inclusion threshold for this analysis (see methods section) was reached by a total of 235 individuals, i.e.,&#x20;143 cases and 92 controls from the two cohorts that fulfilled the quality criteria. The identified haplogroups were all assigned to one of the European major haplogroups (H, K, and U). <xref ref-type="table" rid="T4">Table&#x20;4</xref> summarizes haplogroup frequency distributions for the cases and controls.</p>
<table-wrap id="T4" position="float">
<label>TABLE 4</label>
<caption>
<p>Haplogroup frequency distributions and their association with the risk of POAG.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="left">Haplogroup</th>
<th align="center">Frq&#x2a; females N (%)</th>
<th align="center">Frq&#x2a; males N (%)</th>
<th align="center">Frq&#x2a; cases N (%)</th>
<th align="center">Frq&#x2a; controls N (%)</th>
<th align="center">Odds ratio</th>
<th align="center">95% CI&#x2a;&#x2a;</th>
<th align="center">
<italic>p</italic>-value</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="left">H</td>
<td align="char" char=".">31 (13.2)</td>
<td align="char" char=".">23 (9.7)</td>
<td align="char" char=".">20 (8.6)</td>
<td align="char" char=".">34 (14.5)</td>
<td align="center">Reference</td>
<td align="center">Reference</td>
<td align="center">Reference</td>
</tr>
<tr>
<td align="left">K</td>
<td align="char" char=".">29 (12.3)</td>
<td align="char" char=".">45 (19.2)</td>
<td align="char" char=".">58 (24.6)</td>
<td align="char" char=".">16 (6.8)</td>
<td align="char" char=".">5.8</td>
<td align="char" char=".">2.7&#x2013;13.1</td>
<td align="char" char=".">1.2 &#xd7; 10-05</td>
</tr>
<tr>
<td align="left">U</td>
<td align="char" char=".">62 (26.4)</td>
<td align="char" char=".">45 (19.2)</td>
<td align="char" char=".">65 (27.7)</td>
<td align="char" char=".">42 (17.8)</td>
<td align="char" char=".">2.61</td>
<td align="char" char=".">1.3&#x2013;5.2</td>
<td align="char" char=".">0.005</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Abbreviations: &#x2a;Frq, frequency of effect allele; &#x2a;&#x2a;CI, confidence interval.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<p>The haplogroup K showed an increased risk effect for POAG, with an OR &#x3d; 5.8 (95% CI &#x3d; 2.7&#x2013;13.1; <italic>p</italic>&#x20;&#x3d; 1.2 &#xd7; 10<sup>&#x2212;05</sup>) and the haplogroup U an OR &#x3d; 2.6 (95% CI &#x3d; 1.3&#x2013;5.2; <italic>p</italic>&#x20;&#x3d; 0.005). We further observed that the haplogroup U was the most common haplogroup (45.5%), followed by haplogroups K (31.4%) and H (22.9%). None of these K sub-haplogroups showed any statistical significance (data not shown). The haplogroup U is phylogenetically connected with the haplogroup K, and was also significantly associated with increased risk of POAG. Therefore, we repeated our analysis combining the haplogroups U and K in the UK cluster and found that UK frequency also differed significantly from the control group (odds ratio 3.5, 95% CI &#x3d; 1.8&#x2013;6.7; <italic>p</italic>&#x20;&#x3d; 0.00012).</p>
</sec>
<sec id="s3-3">
<title>Gene Expression</title>
<p>We queried the two genes located closest to the two identified SNPs (<italic>MT-CYB</italic> and <italic>MT-ND4</italic>) for expression in ocular and nonocular tissues in the EyeIntegration database. We found the highest expression of both <italic>MT-CYB</italic> and <italic>MT-ND4</italic> in the following tissues, respectively: adult retina of 19.56 log2 (TPM &#x2b; 1) and 20.60 log2 (TPM &#x2b; 1), and RPE of 19.59 log2 (TPM &#x2b; 1) and 20.03 log2 (TPM &#x2b; 1). The lowest gene expression was reported in the cornea [11.50 log2 (TPM &#x2b; 1) and 11.97 log2 (TPM &#x2b; 1)] (<xref ref-type="fig" rid="F1">Figure&#x20;1</xref>).</p>
<fig id="F1" position="float">
<label>FIGURE 1</label>
<caption>
<p>Gene expression of <italic>MT-CYB</italic> and <italic>MT-ND4</italic> in different tissues. Gene expression levels of the genes <italic>MT-CYB</italic> and <italic>MT-ND4</italic> according to the EyeIntegration database v1.05 for muscle skeletal, whole blood, cornea, retina and RPE tissues.</p>
</caption>
<graphic xlink:href="fgene-12-781189-g001.tif"/>
</fig>
<p>Gene expression levels of the genes <italic>MT-CYB</italic> and <italic>MT-ND4</italic> according to the EyeIntegration database v1.05 for muscle skeletal, whole blood, cornea, retina and RPE tissues.</p>
<p>We also queried in the EyeIntegration database v1.05 the retina network to examine which genes were the most connected in this network. In the retina network, <italic>MT-CYB</italic> and <italic>MT-ND4</italic> genes have high connectivity with the <italic>POMGNT1</italic> gene (kWithin &#x3d; 18.447). Genes with higher connectivity are, theoretically, more likely to be important in gene regulation because perturbations in them will affect more the system compared to the effect in less connected genes. When we queried the <italic>POMGNT1</italic> gene in the OMIM database, we identified eye phenotypes linked to muscular dystrophy-dystroglycanopathy, in which patients have congenital glaucoma and retinitis pigmentosa (<xref ref-type="bibr" rid="B62">Parton, 2003</xref>).</p>
</sec>
</sec>
<sec sec-type="discussion" id="s4">
<title>Discussion</title>
<p>In this study, we investigated the possible involvement of genetic variation in mitochondria in POAG, by performing an association analysis for mitochondrial SNPs and haplogroups in 721 patients with POAG and 1951 healthy individuals. Based on evidence derived from combined analysis of our datasets, we concluded that two mtSNPs (rs2853496 and rs35788393) are nominal associated with POAG. Our data suggest that the A allele of rs2853496, within the <italic>MT-ND4</italic> gene, and the T allele of rs35788393, located in the <italic>MT-CYB</italic> gene, have a protective effect. With respect to mitochondrial haplogroups, our analyses identified haplogroup K as highly associated with an increased risk of POAG (OR &#x3d; 5.8; 95% CI &#x3d; 2.7&#x2013;13.1; <italic>p</italic>&#x20;&#x3d; 1.2 &#xd7; 10<sup>&#x2212;5</sup>).</p>
<p>Our findings are consistent with evidence from the literature that suggest a potential role of the mtGenome, and more specifically of the genes <italic>MT-ND4</italic> and <italic>MTCYB</italic> in optic neuropathies or glaucoma (<xref ref-type="bibr" rid="B22">Cortopassi and Arnheim et&#x20;al., 1990</xref>; <xref ref-type="bibr" rid="B87">Votruba et&#x20;al., 2004</xref>; <xref ref-type="bibr" rid="B5">Abu-Amero et&#x20;al., 2006</xref>). The <italic>MT-ND4</italic> gene is a protein-coding gene located in the mtDNA, encoding for subunit 4 of complex I (NADH ubiquinone oxidoreductase) (<xref ref-type="bibr" rid="B58">MT-ND4, 2021</xref>). The complex I is the first enzyme of the respiratory chain, a vulnerable site to oxidative stress, also involved in cellular functions like apoptosis (<xref ref-type="bibr" rid="B27">Ferguson et&#x20;al., 1976</xref>). SNPs in subunit 4 of <italic>MT-ND4</italic> can affect the first step of the electron transport chain. Therefore, these mutations may have an impact on mitochondrial respiratory chain function and could result in an alteration of the cellular energy metabolism.</p>
<p>Genetic variations in the <italic>MT-ND4</italic> are implicated in other optic neuropathies. This is the case of LHON, where one of the most prevalent variants that accounts for more than 70% of all cases is the m.11778G &#x3e; A, located in the <italic>MT-ND4</italic> gene (<xref ref-type="bibr" rid="B99">Yu-Wai-Man et&#x20;al., 2014</xref>; <xref ref-type="bibr" rid="B54">Mancuso and Klopstock et&#x20;al., 2019</xref>). LHON is one of the most common inherited optic neuropathies and it is characterized by bilateral optic atrophy and loss of central vision due to loss of RGCs (<xref ref-type="bibr" rid="B70">Sadun, 2002</xref>; <xref ref-type="bibr" rid="B98">Yu-Wai-Man et&#x20;al., 2011</xref>). MtDNA mutations associated with LHON have also been described in animal models: mice with a mutation in the <italic>mt-Nd4</italic> gene show nerve atrophy and RGCs degeneration. Both conditions are also characteristics of LHON in humans (<xref ref-type="bibr" rid="B24">Divi et&#x20;al., 2007</xref>; <xref ref-type="bibr" rid="B47">Koilkonda and Guy, 2011</xref>). In contrast to the mitochondrial mutations identified in LHON cases, in the mitochondrial genome of POAG patients the majority of the mutations were somatic transversions (a replacement of a purine with a pyrimidine, or vice versa), caused by the accumulation of oxidative stress over time (<xref ref-type="bibr" rid="B5">Abu-Amero et&#x20;al., 2006</xref>).</p>
<p>In this study, we also report an association between POAG and the mtDNA variation rs35788393 in the <italic>MT-CYB</italic> gene. The protein product of this gene is involved in the oxidative phosphorylation system. This system is composed of five complexes where the <italic>MT-CYB</italic> gene encodes for the cytochrome b of complex III (that catalyzes the transfer of electrons from ubiquinol to cytochrome c), the only one solely encoded by a mitochondrial gene (<xref ref-type="bibr" rid="B17">Chaussenot et&#x20;al., 2018</xref>). Pathogenic mutations in the <italic>MT-CYB</italic> gene can disrupt the normal activity of the electron transport chain and affect the production of ATP by increasing the production of ROS. This leads to damage of cellular proteins, lipids and nucleic acids via oxidation reactions (<xref ref-type="bibr" rid="B90">West et&#x20;al., 2011</xref>). So far, mutations in <italic>MT-CYB</italic> have been associated with LHON, retinitis pigmentosa and cataract (<xref ref-type="bibr" rid="B12">Brown et&#x20;al., 1992</xref>; <xref ref-type="bibr" rid="B91">Wibrand et&#x20;al., 2001</xref>; <xref ref-type="bibr" rid="B73">Schuelke et&#x20;al., 2002</xref>; <xref ref-type="bibr" rid="B69">Ronchi et&#x20;al., 2011</xref>). Since the <italic>MT-CYB</italic> gene is involved in the production of ATP in the electron transport chain, it is pivotal to explore the possible role of this gene in POAG in future studies.</p>
<p>Genetic variations in both <italic>MT-CYB</italic> and <italic>MT-ND4</italic> genes are able to destabilize the so-called mitochondrial super complex: the physical interaction between mitochondrial complex-I and complex-III. The destabilization of this complex leads to the loss of complex I activity, the major entry point for electrons to the respiratory chain (<xref ref-type="bibr" rid="B43">Hudson et&#x20;al., 2007</xref>). In transgenic mice, loss of complex-I activity showed an increase of ROS levels in the RCGs and optic nerve degeneration (<xref ref-type="bibr" rid="B65">Qi et&#x20;al., 2003</xref>). In human, glaucomatous TM cells have been reported to be more sensitive to the inhibition of complex-I (<xref ref-type="bibr" rid="B9">Banerjee et&#x20;al., 2013</xref>). Indeed, damages in complex-I were observed to contribute to the progressive loss of TM&#xa0;cells in POAG patients due to the excessive mitochondrial ROS production and to the attenuation of the mitochondrial membrane. This decrease reduces the ATP synthesis, driving the cells towards apoptosis (<xref ref-type="bibr" rid="B35">He et&#x20;al., 2008</xref>). Another study comparing both POAG and LHON lymphoblasts found an impairment of the complex-I, where functional defects of this complex were milder in POAG than LHON. This is in accordance with the less severe development of the disease in POAG (<xref ref-type="bibr" rid="B84">Van Bergen et&#x20;al., 2015</xref>). However, more comprehensive investigations are still necessary to define the regulatory function of complex-I that in turn might lead to the increase of the oxidative stress and favor the glaucomatous condition.</p>
<p>To add biological context to our study, we also evaluated bioinformatically which genes were the most highly connected with <italic>MT-CYB</italic> and <italic>MT-ND4</italic> in the retina network (<xref ref-type="bibr" rid="B13">Bryan et&#x20;al., 2018</xref>). Genes highly connected indicate that they are more likely to have an effect in gene regulation. By querying the retina network, we implicated the <italic>POMGNT1</italic> gene (protein O-mannose beta-1,2-N-acetylglucosaminyltransferase-1). <italic>POMGNT1</italic> synthesizes a unique O-mannose sugar chain on &#x3b1;-dystroglycan, the extracellular protein that binds laminin &#x3b1;2 in the extracellular matrix. Reported mutations in the <italic>POMGNT1</italic> gene have enlightened its role in four genetic muscular dystrophy disease entities: 1) Walker&#x2013;Warburg syndrome (OMIM &#x23;253280), 2) the muscle-eye-brain disease (OMIM &#x23;253280)&#x2014;for which patients show ocular symptoms as retinal degeneration, optic atrophy and congenital glaucoma&#x2014;3) congenital muscular dystrophy with mental retardation (OMIM &#x23;613151), and 4) retinitis pigmentosa (OMIM &#x23;606822) (<xref ref-type="bibr" rid="B56">Pihko et&#x20;al., 1995</xref>; <xref ref-type="bibr" rid="B96">Yoshida et&#x20;al., 2001</xref>; <xref ref-type="bibr" rid="B30">Godfrey et&#x20;al., 2007</xref>; <xref ref-type="bibr" rid="B20">Clement et&#x20;al., 2008</xref>; <xref ref-type="bibr" rid="B89">Wang et&#x20;al., 2016</xref>; <xref ref-type="bibr" rid="B95">Xu et&#x20;al., 2016</xref>). The dystroglycan gene (<italic>DAG1</italic>) encodes for &#x3b1;-dystroglycan and &#x3b2;-dystroglycan (<xref ref-type="bibr" rid="B39">Holt et&#x20;al., 2000</xref>). In the retina, dystroglycan is highly expressed in M&#xfc;ller glial, rods and cones at the outer plexiform layer, and plays an important role in retinal function and survival (<xref ref-type="bibr" rid="B71">Schmitz et&#x20;al., 1993</xref>; <xref ref-type="bibr" rid="B57">Montanaro et&#x20;al., 1995</xref>; <xref ref-type="bibr" rid="B10">Blank et&#x20;al., 1999</xref>; <xref ref-type="bibr" rid="B45">Jastrow et&#x20;al., 2006</xref>). The <italic>DAG1</italic> gene is also linked to Muscular dystrophy-dystroglycanopathy (congenital with brain and eye anomalies, OMIM &#x23;616538). Using zebrafish animal models, Gupta et&#x20;al. demonstrated that dystroglycan deficiency caused abnormal development of ganglion cells, lens, and cornea (<xref ref-type="bibr" rid="B33">Gupta et&#x20;al., 2011</xref>). In addition, in a consanguineous Israeli-Arab family a homozygous loss-of-function mutation in the <italic>DAG1</italic> gene was detected in infants with a congenital phenotype consistent with Walker&#x2013;Warburg syndrome. Ocular features in those infants included bilateral corneal opacity and glaucoma (<xref ref-type="bibr" rid="B68">Riemersma et&#x20;al., 2015</xref>). Taken together, these findings suggest that dystroglycan deficiency is strongly correlated with eye abnormalities, including glaucoma. In our view, further studies on the role of <italic>DAG1</italic> and <italic>POMGNT1</italic> genes in the pathomechanisms underlying POAG are warranted.</p>
<p>Another part of our current investigation in POAG was focused on the analysis of potentially associated mtDNA haplogroups. In order to interpret our results, it is important to consider the variations reported in the population distributions of mitochondrial haplotypes in comparison with the frequencies identified in our study (<xref ref-type="bibr" rid="B81">Torroni and Wallace, 1994</xref>). A study conducted in the Netherlands in 680 individuals randomly selected identified that the most common haplogroup was H (45.3%), followed by haplogroups U (25.6%), T (11.6%), J (10.7%) and K (6.3%) (<xref ref-type="bibr" rid="B16">Chaitanya et&#x20;al., 2016</xref>). These frequencies, when present in our POAG dataset, differed from those reported in the general population. Regarding the haplogroup H, it is important to point out that it shows a complex variation with many sub-lineages. In our study, we used data generated by a SNP-chip array, which is able to detect sites that are polymorphic in populations. Therefore, the differences in frequency reported here for the haplogroup H can be attributed to the absence of sites that allows an accurate classification (<xref ref-type="bibr" rid="B52">Loogv&#xe4;li et&#x20;al., 2004</xref>; <xref ref-type="bibr" rid="B77">Pereira et&#x20;al., 2005</xref>). In our study, haplogroup K was the most significant association with POAG. Considering that haplogroup K occurs approximately in 8% of European and 6% in Dutch individuals, we reported a higher frequency of this haplogroup in our POAG cases (24.6%) compared to controls (6.8%). In line with our findings, a meta-analysis conducted in 3,613 individuals affected by LHON from 159 European pedigrees indicated that the risk of visual loss was higher in carriers of the mitochondrial haplogroup K: individual carriers of haplogroup K were more exposed to experience visual loss, whereas individuals carriers of haplogroup H had a lower risk of visual loss (<xref ref-type="bibr" rid="B43">Hudson et&#x20;al., 2007</xref>). The haplogroup association in our study showed a similar outcome: individuals with haplogroup K had a higher risk to develop POAG compared to individuals belonging to haplogroup H. We also observed that the UK cluster shows the same direction of risk. Interestingly, studies conducted in cybrids showed that haplogroup UK are associated with less levels of mitochondrial protein synthesis and respiratory complex IV activities than cybrids from haplogroup H (<xref ref-type="bibr" rid="B31">G&#xf3;mez-Dur&#xe1;n et&#x20;al., 2010</xref>). Therefore, also supported by previous studies, we speculate on the possible link of the mtGenome in the pathogenesis of POAG (<xref ref-type="bibr" rid="B2">Abu-Amero et&#x20;al., 2011b</xref>; <xref ref-type="bibr" rid="B11">Bosley et&#x20;al., 2011</xref>; <xref ref-type="bibr" rid="B21">Collins et&#x20;al., 2016</xref>; <xref ref-type="bibr" rid="B76">Singh et&#x20;al., 2018</xref>). In contrast, a few studies reported that mitochondrial haplogroups did not contribute to the pathogenesis of POAG. Negative associations were found in POAG cohorts from the north east of England, Saudi Arabia and Ghana (<xref ref-type="bibr" rid="B5">Andrews et&#x20;al., 2006</xref>; <xref ref-type="bibr" rid="B4">Abu-Amero et&#x20;al., 2008</xref>, <xref ref-type="bibr" rid="B3">2012</xref>). Combining our data with those of the literature, there is evidence that mitochondrial haplotypes K plays a role in the pathogenesis of POAG, at least in some populations.</p>
<sec id="s4-1">
<title>Strengths and Limitations</title>
<p>Our study had several strengths and limitations. Strong points are: the AGS and GLGS datasets are well defined in terms of diagnosis, design, and method of investigation. In fact, these datasets are clinical cohorts, in which POAG patients received diagnoses by experienced physicians, following strict criteria. In addition, the cohorts used in this study were genotyped on the same array and have been processed applying the same quality control procedures. There are also a number of limitations: first, by nature of the study, we focused only on homoplasmic mtDNA variations, detected in blood but not in potentially relevant ocular tissues. Furthermore, we cannot exclude potential additional influence of nuclear DNA of mitochondrial origin, other genetic variations elsewhere or non-genetic factors. Second, we performed our analyses in samples of European ancestry and for this reason our findings are not, without more research, transferable to other populations. Third, replications in other populations of our results are necessary to corroborate their association with&#x20;POAG.</p>
</sec>
</sec>
<sec sec-type="conclusion" id="s5">
<title>Conclusion</title>
<p>In our study, we identified associations between mitochondrial polymorphisms in the <italic>MT-ND4</italic> and <italic>MT-CYB</italic> genes and POAG, and reported that individuals carrying mtDNA haplogroup K were at the highest risk of developing this eye disease. Our findings support the hypothesis that mitochondria have a role in the pathogenesis of POAG. Nonetheless, further genetic and functional studies are still required to highlight the role of mitochondrial genes, in relation to POAG pathophysiology.</p>
</sec>
<sec id="s6">
<title>Lifelines Cohort Study</title>
<p>
<bold>Raul Aguirre-Gamboa</bold>, Department of Genetics, University of Groningen, University Medical Center Groningen, Netherlands; <bold>Patrick Deelen</bold>, Department of Genetics, University of Groningen, University Medical Center Groningen, Netherlands; <bold>Lude Franke</bold>, Department of Genetics, University of Groningen, University Medical Center Groningen, Netherlands; <bold>Jan A. Kuivenhoven</bold>, Department of Pediatrics, University of Groningen, University Medical Center Groningen, Netherlands; <bold>Esteban A. Lopera Maya</bold>, Department of Genetics, University of Groningen, University Medical Center Groningen, Netherlands; <bold>Ilja M. Nolte</bold>, Department of Epidemiology, University of Groningen, University Medical Center Groningen, Netherlands; <bold>Serena Sanna</bold>, Department of Pediatrics, University of Groningen, University Medical Center Groningen, Netherlands; <bold>Harold Snieder</bold>, Department of Epidemiology, University of Groningen, University Medical Center Groningen, Netherlands; <bold>Morris A. Swertz</bold>, Department of Genetics, University of Groningen, University Medical Center Groningen, Netherlands; <bold>Peter M. Visscher</bold>, Department of Epidemiology, University of Groningen, University Medical Center Groningen, Netherlands, and Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia; <bold>Judith M Vonk</bold>, Department of Epidemiology, University of Groningen, University Medical Center Groningen, Netherlands; <bold>Cisca Wijmenga</bold>, Department of Genetics, University of Groningen, University Medical Center Groningen, Netherlands.</p>
</sec>
</body>
<back>
<sec id="s7">
<title>Data Availability Statement</title>
<p>The data that support the findings of this study are available from Lifelines Biobank but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of Lifelines.</p>
</sec>
<sec id="s8">
<title>Ethics Statement</title>
<p>The studies involving human participants were reviewed and approved by the ethics board of the University Medical Center of Amsterdam (METc submission &#x23; 2013_327). The data analyzed in this study was also obtained from the Lifelines biobank, under project application number OV18_0463. Requests to access this dataset should be directed to Lifelines Research Office (<email>research@lifelines.nl</email>). The patients/participants provided their written informed consent to participate in this study.</p>
</sec>
<sec id="s9">
<title>Author Contributions</title>
<p>VL, IN, and AB conceptualized, designed the experimental setup, performed genetic analyses, and wrote the main manuscript text. JT collected the data and wrote the main manuscript. VL, AB, IN, HS, and NJ supervised the study, interpreted the results and revised the final draft of the manuscript. All authors have read and agreed to the published version of the manuscript.</p>
</sec>
<sec id="s10">
<title>Funding</title>
<p>This project was funded by European Union&#x2019;s Horizon 2020 research and innovation programme under the Marie Sk&#x142;odowska-Curie grant agreement No. 675033 (EGRET plus). Additional funding was provided by the Rotterdamse Stichting Blindenbelangen (Grant ID B20150036). The funding organization had no role in the design, conduct, analysis, or publication of this research. The Lifelines Biobank initiative has been made possible by subsidy from the Dutch Ministry of Health, Welfare and Sport, the Dutch Ministry of Economic Affairs, the University Medical Center Groningen (UMCG the Netherlands), University of Groningen and the Northern Provinces of Netherlands. The Lifelines Biobank initiative has been made possible by funding from the Dutch Ministry of Health,Welfare and Sport, the Dutch Ministry of Economic Affairs, the University Medical Center Groningen(UMCG Netherlands), University of Groningen and the Northern Provinces of the Netherlands. The generation and management of GWAS genotype data for the Lifelines Cohort Study is supported by the UMCG Genetics Lifelines Initiative (UGLI). UGLI is partly supported by a Spinoza Grant from NWO, awarded to Cisca Wijmenga.</p>
</sec>
<sec sec-type="COI-statement" id="s11">
<title>Conflict of Interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec sec-type="disclaimer" id="s12">
<title>Publisher&#x2019;s Note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
</sec>
<ack>
<p>The authors wish to acknowledge the services of the Lifelines Cohort Study, the contributing research centers delivering data to Lifelines, and all the study participants.</p>
</ack>
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