Open Access

Comprehensive analysis of mitochondrial DNA variants, mitochondrial DNA copy number and oxidative damage in psoriatic arthritis

  • Authors:
    • Materah Salem Alwehaidah
    • Manhel Alsabbagh
    • Ghada Al-Kafaji
  • View Affiliations

  • Published online on: September 26, 2023     https://doi.org/10.3892/br.2023.1667
  • Article Number: 85
  • Copyright: © Alwehaidah et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

Growing evidence suggests that abnormalities in mitochondrial DNA (mtDNA) are involved in the pathogenesis of various inflammatory and immuno‑mediated diseases. The present study analysed the entire mitochondrial genome by next‑generation sequencing (NGS) in 23 patients with psoriatic arthritis (PsA) and 20 healthy controls to identify PsA‑related variants. Changes in mtDNA copy number (mtDNAcn) were also evaluated by quantitative polymerase chain reaction (qPCR) and mtDNA oxidative damage was measured using an 8‑hydroxy‑2'‑deoxyguanosine assay. NGS analysis revealed a total of 435 variants including 187 in patients with PsA only and 122 in controls only. Additionally, 126 common variants were found, of which 2 variants differed significantly in their frequencies among patients and controls (P<0.05), and may be associated with susceptibility to PsA. A total of 33 missense variants in mtDNA‑encoded genes for complexes I, III, IV and V were identified only in patients with PsA. Of them, 25 variants were predicted to be deleterious by affecting the functions and structures of encoded proteins, and 13 variants were predicted to affect protein's stability. mtDNAcn analysis revealed decreased mtDNA content in patients with PsA compared with controls (P=0.0001) but the decrease in mtDNAcn was not correlated with patients' age or inflammatory biomarkers (P>0.05). Moreover, a higher level of oxidative damage was observed in patients with PsA compared with controls (P=0.03). The results of the present comprehensive analysis of mtDNA in PsA revealed that certain mtDNA variants may be implicated in the predisposition/pathogenesis of PsA, highlighting the importance of NGS in the identification of mtDNA variants in PsA. The current results also demonstrated that decreased mtDNAcn in PsA may be a consequence of increased oxidative stress. These data provide valuable insights into the contribution of mtDNA defects to the pathogenesis of PsA. Additional studies in larger cohorts are needed to elucidate the role of mtDNA defects in PsA.

Introduction

Psoriatic arthritis (PsA) is a heterogeneous chronic immune-mediated disease characterized by musculoskeletal inflammation. Numerous patients develop PsA on the background of psoriasis, a skin condition of scaly erythematous plaques that commonly affects the extensor surfaces of the elbows and knees, and other parts of the body (1-3). The onset of PsA often occurs between the age of 30 and 50 years but may arise at any point throughout a patient's lifetime. The clinical manifestations of PsA vary greatly between patients and range from relatively mild to severe disease, and disease flares can alternate with periods of remission (4). Due to the shared similarities in the clinical presentation of PsA and other arthritic diseases such as rheumatoid arthritis (RA) and osteoarthritis (OA), PsA is frequently undiagnosed and/or misdiagnosed (5). However, six clinical domains are involved in PsA including peripheral arthritis, enthesitis, dactylitis, psoriasis, psoriatic nail disease and axial disease (6).

Although the aetiology of PsA is not fully understood, genetics, epigenetics and environmental factors contribute to abnormal immune responses and disease expression (7). At the genetics level, both human leukocyte antigen (HLA) and non-HLA genes have been associated with PsA (7). Moreover, 33-50% of patients with PsA have at least one first-degree relatives who are also affected by psoriasis or PsA (8). Previous studies have shown that mitochondrial dysfunction contributes significantly to the pathogenesis of PsA by modulating innate immunity via redox-sensitive inflammatory pathways (9,10). Oxidative stress can disrupt redox signalling and cause molecular damage, which impacts angiogenesis, inflammation and immune cell function (11). Mitochondria produce most of the cellular energy through the process of oxidative phosphorylation (OXPHOS) and are also the major site of reactive oxygen species (ROS). Besides their central role in cellular metabolism, mitochondria also participate in other important cellular processes such as innate immune, inflammatory and stress responses (12). Mitochondria have their own genome called mitochondrial DNA (mtDNA), which is a double-stranded molecule encoding 37 genes. In total, 13 of the mtDNA genes are involved in the OXPHOS and the remaining genes are essential in assembling amino acids into functional proteins (13). mtDNA presents in multiple copies (1,000-10,000 copies) per cell, resulting in both homoplasmic and heteroplasmic mtDNA variants. Moreover, the mtDNA copy number (mtDNAcn) is regulated in a tissue-specific manner (14) and correlates positively with the number of mitochondria, and thus is considered an indicator of mitochondrial function (15). Numerous factors make mtDNA particularly vulnerable to ROS and oxidative damage, including its proximity to the site of the electron transport chain (ETC), absence of protective histones and inadequate DNA repair capacity (16). Oxidative stress is an important source of mitochondrial genomic instability and can induce mtDNA variations and copy number changes, which may lead to abnormalities in mitochondrial function (17,18). Both mtDNA variants and copy number alterations have been implicated in human aging and various pathological conditions including mitochondrial disorders, cancer, and neurodegenerative diseases (19,20).

Harty et al (21) evaluated the total mtDNA mutational load in PsA/RA using a mitochondrial random capture assay, which revealed a significant increase in the frequency of mtDNA variants in synovial tissue from patients with RA and PsA compared with controls. However, mitochondrial random capture assay has limitations such as low sensitivity and inability to detect heteroplasmy, which is an important characteristic of numerous mtDNA-related diseases. Previously, next-generation sequencing (NGS) has emerged as a robust technique for screening the mitochondrial genome. It enables comprehensive analysis of the entire mitochondrial genome for the detection of common and rare mtDNA variants, mtDNA disease-associated variants, and accurate measurement of heteroplasmy (22). Since no previous studies have analysed the entire mitochondrial genome or evaluated changes in mtDNAcn and oxidative stress in PsA, the present study aimed to investigate mtDNA variants related to PsA and/or associated with the risk of PsA via NGS. The present study also aimed to examine changes in mtDNAcn as well as evaluate mtDNA oxidative damage in patients with PsA and healthy controls.

Materials and methods

Study subjects

A total of 43 subjects including 23 patients with PsA and 20 healthy controls were enrolled in the present study. Patients with PsA were recruited from the out-patient clinic at the Department of Rheumatology of Mubarak Hospital, (City of Kuwait, State of Kuwait). The patients fulfilled the classification criteria for PsA (CASPAR). Patients with other inflammatory or autoimmune diseases were excluded from study (23). Clinicopathological characteristics of patients (including sex and age distribution) are presented in Table I.

Table I

Demographic and clinical data of patients with psoriatic arthritis and controls.

Table I

Demographic and clinical data of patients with psoriatic arthritis and controls.

CharacteristicsPsAControlsP-value
Number of subjects2320 
Sex  0.6
     Male, n (%)11(48)8(50) 
     Female, n (%)12(52)12(50) 
Age, years (mean ± SD)39±330±1.30.01
C-Reactive protein, mg/dl5±0.90.1±0.050.02
Rheumatoid factor, U/ml21±20.4±0.02<0.001
Erythrocyte sedimentation28±92.6±10.003
rate, mm/h   
Medications   
     Topical treatment4  
     Systemic treatment19  
     Methotrexate4  
     Adalimumab8  
     Etanercept3  
     Secukinumab2  
     Ixekizumab2  

Healthy control individuals without inflammatory dermatoses or autoimmune diseases were recruited from the Central Blood Bank, State of Kuwait. Basic clinical characteristics and laboratory data were obtained from the medical and electronic records of patients and controls. Written informed consent was obtained from all participants under protocols approved by Kuwait University and Ministry of Health (City of Kuwait, State of Kuwait) (approval no. 2018/496).

Extraction of genomic DNA

Blood samples (5 ml) were collected in EDTA tubes from the participants and centrifuged at 4˚Cn 1,000 x g for 15 min to separate the buffy coat which was subjected to genomic DNA extraction using QIA amp DNA Mini kit (cat. no. 51304; Qiagen GmbΗ) according to the manufacturer's instructions as previously described (24). Briefly, a mixture of 200 µl buffy coat, 20 µl protease and 200 µl lysis buffer was incubated at 56˚C for 10 min and then centrifuged at 20,000 x g for 1 min at 4˚C. Next, absolute ethanol (200 µl) was added and centrifuged at 6,000 x g for 1 min followed by washing with 500 µl washing buffer. The mixture was then centrifuged at room temperature at 6,000 x g for 1 min and then at 20,000 x g for 3 min. Genomic DNA was eluted with 200 µl elution buffer after incubation at room temperature for 1 min and centrifugation at 6,000 x g for 1 min at room temperature. The DNA samples were quantified and assessed for purity using a NanoDrop ND-1000 ultraviolet-visible light spectrophotometer (Thermo Fisher Scientific, Inc.).

Mitochondrial genome sequencing

The entire mitochondrial genome was sequenced using the S5™XL NGS system (Applied Biosystems; Thermo Fisher Scientific, Inc.) according to the manufacturer's protocol, as previously described (25). After library preparation and purification, the raw data were automatically transferred from the Ion Torrent S5 XL sequencer to the Torrent Suite software version 5.0 (Applied Biosystems; Thermo Fisher Scientific, Inc.), which allowed the conversion of the raw voltage semiconductor sequencing data into DNA base calls. For identification of variants, the Ion Torrent Variant Caller plug-in, Ion Reporter software version 5.2. and Torrent Variant Caller version 5.2 (Applied Biosystems; Thermo Fisher Scientific, Inc.) were used. For alignment, the Revised Cambridge Reference Sequence of the Human mtDNA (NC_012920.1) was applied as a reference mitochondrial sequence (26). The average throughput of the Ion 520 chip was 3.5 Mb. The sequence data sets were registered in the Sequence Read Archive repository (reference no. PRJNA 928743).

Bioinformatics analysis

The impact of nonsynonymous mtDNA variants on protein function and structure was determined using three in-silico prediction tools used: i) Combined Annotation Dependent Depletion (CADD): Incorporates multiple annotations including conservation and functional information into one tool and categorizes variants as benign or deleterious using a machine learning approach. Variants with scores ≥20 were predicted to be deleterious (27); ii) CONsensus DELeteriousness (Condell): Integrates the output of five algorithms including Pfam E-value (Logre), MAPP, Mutation Assessor, Polyphen2, and SIFT to assess the outcome of nonsynonymous single nucleotide variants (SNVs) on protein function. Variants with scores ≥0.5 were predicted to be deleterious (28); and iii) Protein Variation Effect Analyzer (PROVEAN) predicts the impact of an amino acid substitution or indel on protein function. PROVEAN performance is comparable to SIFT or PolyPhen-2 and it can process a large number of protein variants. Variants with scores ≤-2.5 were predicted to be deleterious, while those with scores >-2.5 were considered neutral (29).

Analysis of protein stability

Analysis of the impact of nonsynonymous mtDNA variants on protein stability was conducted using Site-Directed Mutator (SDM), which is a statistical potential energy function that uses environment-specific amino acid substitution frequencies within the family of homologous proteins of known (3-D) structures to calculate a stability score, which is analogous to the free energy difference between the wild-type and mutant protein (30). A change in the Gibbs free energy for protein stability is expressed as ΔΔG (30).

Determination of relative mtDNAcn

Quantitative polymerase chain reaction (qPCR) was used to determine the mtDNAcn relative to nuclear DNA (nDNA). Mitochondrial NADH dehydrogenase subunit 2 (ND2) was used as a target gene for the amplification of mtDNA with the following primers: forward, 5'-CAC AGA AGC TGC CAT CAA GTA-3' and reverse, 5'-CCG GAG AGT ATA TTG TTG AAG AG-3'; while nuclear b2-microglobulin (β2M) was used as a reference gene for the amplification of nDNA with the following primers: forward, 5'-CCA GCA GAG AAT GGA AAG TCA A-3' and reverse, 5'-TCT CTC TCC ATT CTT CAG TAA GTC AAC T-3'. The PCR mixture contained 10 ng genomic DNA, 1X SYBR1 Green PCR Master Mix (Applied Biosystems; Thermo Fisher Scientific, Inc.), forward and reverse primers (50 nM each), and nuclease-free water to a final volume of 10 µl. PCR was performed in a 7900HT real-time PCR System (Applied Biosystems; Thermo Fisher Scientific, Inc.) using the following thermocycling conditions: Initial denaturation at 95˚C for 10 min, followed by 40 cycles of 95˚C for 10 sec, 60˚C for 30 sec and 72˚C for 30 sec. The experiments were performed in duplicate and non-template control was included in each run. Relative quantitation of mtDNAcn was performed using the 2-ΔΔCq method (31) by obtaining the Cq values of the ND2 and β2M genes, and then the ΔCq (Cq ND2-Cq β2M) values for cases and controls were calculated.

Determination of mtDNA oxidative damage

8-Hydroxyl 2'-deoxyguanosine (8-OHdG) is one of the most common markers of oxidative DNA lesions and is widely applied for the measurement of oxidative DNA damage (32,33). In the detection of oxidative damage with 8-OHdG, the marker does not deform the DNA structure but causes inhibition of Taq DNA polymerase during PCR. Therefore, the presence of 8-OHdG in a certain region of mtDNA can be digested by formamidopyrimidine [fapy]-DNA glycosylase (FPG) which breaks the DNA fragment at the lesion site and reduces further amplification of this particular region. In the present study, 8-OHdG assay was conducted to measure mtDNA oxidative damage by qPCR. A total of 100 ng DNA was incubated for 1 h at 37˚C in a 10 µl of reaction mixture containing 1 U FPG enzyme (New England Bio Labs, Inc), 1X NEB buffer and 0.1 mg/ml bovine serum albumin (New England Bio Labs, Inc). Next, the digested DNA was amplified by PCR under the same aforementioned cycling protocol and conditions. DNA damage was measured as ΔCq (ΔCq=Cq treated-Cq untreated). The presence of oxidative damage in DNA after treatment of FPG reduces the PCR efficiency and increases the Ct value.

Statistical analysis

Statistical analysis of data was performed using SPSS software (version 23; IBM Corp.). The normal distribution of data was first evaluated using the Kolmogorov-Smirnov test. Accordingly, the comparisons of variables between patients and controls were conducted using the χ2 test for categorical variables and the Mann-Whitney test for normally distributed variables. The Fisher's exact test was used to assess differences in the frequency of variants between patients and controls and the odds ratio (OR) and 95% confidence interval (CI) were reported. P≤0.05 was considered to indicate a statistically significant difference.

Results

Characteristics of the study subjects

The demographic and clinical data of patients with PsA (n=23) and healthy control individuals (n=20) are presented in Table I. The sex ratio (male: female) was 11:12 for patients and 8:12 for controls. There was no significant difference in sex distribution between PsA and controls (P=0.6), but there was a significant difference in mean age between the two groups (P=0.01). The clinical inflammatory marker C-reactive protein (CRP) (0-0.8 mg/dl), rheumatoid factor (RF) (0-20 U/ml), and erythrocyte sedimentation rate (ESR) (0-20 mm/hr) were all higher than the normal range in patients with PsA. The mean value of CRP, RF and ESR were significantly higher in PsA patients compared with controls (P<0.05). Patients were under the following medications: Topical treatment with corticosteroid cream (n=4), or systemic treatment (n=19) including Methotrexate (n=4), Adalimumab (n=8), Etanercept (n=3), Secukinumab (n=2) and Ixekizumab (n=2).

mtDNA sequence variants identification

A total of 435 mtDNA sequence variants were identified in 43 samples. Among them, 187 (43%) variants were exclusive for patients with PsA, and 122 (28%) variants were found in control individuals only (Fig. 1). In both patients and controls, the highest number of variants was observed in the D-loop region, while the lowest number of variants was observed in the tRNAs genes. In protein-coding genes of patients with PsA, there were 152 variants including 33 nonsynonymous and 92 synonymous silent variants. By contrast, in protein-coding genes of control individuals, there were 76 variants, including 18 non-synonymous and 58 synonymous silent variants.

Particularly, a higher number of variants were observed in the MT-ND4, MT-ND5 and MT-CYB genes. A higher number of variants in the MT-ND4, and MT-CYB genes was also observed in patients than in controls. Moreover, the majority of mtDNA variants in patients and controls were homoplasmy accounting for 183 and 118, respectively, compared with the small number of heteroplasmy variants (n=4) in each group. Details of the identified variants in patients or controls as well as their localization in different mtDNA regions are shown in Table II. Notably, of non-synonymous variants in controls only, 4640C>A in the MT-ND2 gene was reported as a pathogenic variant causing Leber optic atrophy according to the Mito Map (https://www.mitomap.org/MITOMAP) and ClinVar (https://www.ncbi.nlm.nih.gov/clinvar/) databases.

Table II

Details of mtDNA variants exclusive for patients with psoriatic arthritis or controls.

Table II

Details of mtDNA variants exclusive for patients with psoriatic arthritis or controls.

Non-coding region
 PatientsControls 
LocusVariantType of variantAmino acid changers ID Homoplasmy/HeteroplasmyVariantVariant typeAffected amino acidrs ID Homoplasmy/Heteroplasmy
D-loopm.57T>TCInsertion rs21245905Heteroplasmym.143G>ASubstitution rs375589100Homoplasmy
D-loopm.72A>GSubstitution rs869183622Heteroplasmym.178A>GSubstitution Not providedHomoplasmy
D-loopm.93A>GSubstitution rs369034419Homoplasmym.182C>TSubstitution rs41473347Homoplasmy
D-loopm.153A>GSubstitution rs370716192Homoplasmym.185 G>TSubstitution rs879015046Homoplasmy
D-loopm.189A>GSubstitution rs371543232Homoplasmym.199T>CSubstitution rs72619362Homoplasmy
D-loopm.200A>GSubstitution rs372099630Homoplasmym.250 T>CSubstitution Not providedHomoplasmy
D-loopm.207G>ASubstitution rs369669319Homoplasmym.285C>TSubstitution rs201801609Homoplasmy
D-loopm.215A>GSubstitution rs879219259Homoplasmym.357A>GSubstitution rs28678375Homoplasmy
D-loopm.217T>CSubstitution rs41531144Homoplasmym.385A>GSubstitution rs201801609Homoplasmy
D-loopm.235A>GSubstitution rs3937037Homoplasmym.497C>TSubstitution rs28660704Homoplasmy
D-loopm.236T>CSubstitution rs375896687Homoplasmym.16093T>CSubstitution rs2853511Heteroplasmy
D-loopm.340C>TSubstitution rs117394573Homoplasmym.16150C>TSubstitution rs879004379Homoplasmy
D-loopm.508A/GSubstitution rs113683159Homoplasmym.16163 A>GSubstitution rs41479950Homoplasmy
D-loopm.524 C>CACInsertion Not providedHeteroplasmym.16185C>TSubstitution rs1556424787Homoplasmy
D-loopm.16041A>GSubstitution rs369904200Homoplasmym.16186C>TSubstitution rs879166752Homoplasmy
D-loopm.16051A>GSubstitution rs117565943Homoplasmym.16224T>CSubstitution rs386420031Homoplasmy
D-loopm.16067C>TSubstitution rs1556424732Homoplasmym.16232C>ASubstitution rs1603225749Homoplasmy
D-loopm.16111C>TSubstitution rs35315169Homoplasmym.16249T>CSubstitution rs372301309Homoplasmy
D-loopm.16124T>CSubstitution rs386829272Homoplasmym.16264C>GSubstitution rs878922147Homoplasmy
D-loopm.16148C>TSubstitution rs201893071Homoplasmym.16288T>CSubstitution rs386829301Homoplasmy
D-loopm.16178T>CSubstitution rs1603225705Homoplasmym.16293A>GSubstitution rs878890610Homoplasmy
D-loop m.16179CA-AAA>CAA§Deletion rs371240719Heteroplasmym.16296C>TSubstitution rs879138789Homoplasmy
D-loopm.16183A>TSubstitution rs28671493Homoplasmym.16318A>TSubstitution rs879067317Homoplasmy
D-loopm.16192C>TSubstitution rs879025248Homoplasmym.16319G>ASubstitution rs35105996Homoplasmy
D-loopm.16201C>TSubstitution Not providedHomoplasmym.16343A>GSubstitution rs374065731Homoplasmy
D-loopm.16214C>TSubstitution rs368055283Homoplasmym.16380C>TSubstitution rs878952395Homoplasmy
D-loopm.16217T>CSubstitution rs35134837Homoplasmym.16381T>CSubstitution rs1556424876Homoplasmy
D-loopm.16219A>GSubstitution rs878960666Homoplasmym.16526G>ASubstitution rs386829315Homoplasmy
D-loopm.16230A>GSubstitution rs2853514Homoplasmy     
D-loopm.16234C>TSubstitution rs368259300Homoplasmy     
D-loopm.16289A>GSubstitution rs1603225781Homoplasmy     
D-loopm.16290C>TSubstitution rs386828866Homoplasmy     
D-loopm.16295C>TSubstitution rs878874012Homoplasmy     
D-loopm.16300A>GSubstitution rs879082592Homoplasmy     
D-loopm.16301C>TSubstitution rs879194775Homoplasmy     
D-loopm.16304T>CSubstitution rs386829305Homoplasmy     
D-loopm.16320C>TSubstitution rs62581338Homoplasmy     
D-loopm.16324T>CSubstitution rs1556424863Homoplasmy     
D-loopm.16399A>GSubstitution rs139001869Homoplasmy     
rRNA genes
MT-RNR1 (12sRNA)m.961T>CSubstitution rs3888511Homoplasmym.954C>TSubstitution Not providedHomoplasmy
MT-RNR1 (12sRNA)m.1008A>GSubstitution rs727504505Homoplasmym.980T>CSubstitution rs397515731Homoplasmy
MT-RNR1 (12sRNA)m.1048C>TSubstitution rs2000974Homoplasmym.1018G>ASubstitution rs2856982Homoplasmy
MT-RNR1 (12sRNA)m.1442G>ASubstitution rs28358573Homoplasmym.1189T>CSubstitution rs28358571Homoplasmy
MT-RNR1 (12sRNA)m.1598G>ASubstitution rs3135027Homoplasmy     
MT-RNR2 (16sRNA)m.2028G>ASubstitution rs2124591154Homoplasmym.1733C>TSubstitution rs878868960Homoplasmy
MT-RNR2 (16sRNA)m.2245A>GSubstitution rs3020600Homoplasmym.1738T>CSubstitution rs28358574Homoplasmy
MT-RNR2 (16sRNA)m.2259C>TSubstitution rs201336470Homoplasmym.2218C>TSubstitution rs200813159Homoplasmy
MT-RNR2 (16sRNA)m.2283C>TSubstitution rs200131896Homoplasmym.2380C>TSubstitution rs1556422622Homoplasmy
MT-RNR2 (16sRNA)m.2484C>TSubstitution rs2124591301Homoplasmym.2768A>GSubstitution rs3895615Homoplasmy
MT-RNR2 (16sRNA)m.2626T>CSubstitution rs879158835Homoplasmym.2772C>TSubstitution rs200221487Homoplasmy
MT-RNR2 (16sRNA)m.3221A>GSubstitution rs1556422691Homoplasmym.2833A>GSubstitution rs3928312Homoplasmy
MT-RNR2 (16sRNA)     m.3158A>ATInsertion rs1556422679Homoplasmy
MT-RNR2 (16sRNA)     m.3221A>GSubstitution rs1556422691Homoplasmy
tRNA genes
MT-TV (tRNA)m.1676A>GSubstitution rs1603218612Homoplasmy     
MT-TL1 (tRNA)m.3387T>CSubstitution rs1569483877Homoplasmym.3277G>ASubstitution rs386828902Homoplasmy
MT-TQ (tRNA)m.4454T>CSubstitution rs11510098Homoplasmy     
MT-TA (tRNA)m.5603C>TSubstitution rs369496446Homoplasmym.5655T>CSubstitution rs1556423019Homoplasmy
MT-TS1 (tRNA)m.7476C>TSubstitution rs201950015Homoplasmym.7474G>CSubstitution rs2068703713Heteroplasmy
MT-TS1 (tRNA)m.7570A>GSubstitution rs1556423311Homoplasmy     
MT-TD (tRNA)     m.7581T>CSubstitution rs201582552Homoplasmy
MT-TK (tRNA)m.8292G>ASubstitution rs1556423422Homoplasmy     
MT-TG (tRNA)m.10042A>GSubstitution rs1603222643Homoplasmym.10034T>CSubstitution rs41347846Homoplasmy
MT-TH (tRNA)m.12171A>GSubstitution rs1603223589Homoplasmy     
MT-TH(tRNA)m.12175T>CSubstitution rs1057520099Homoplasmy     
MT-TT (tRNA)m.15907A>GSubstitution rs41383248Homoplasmy     
MT-ND1m.3516C>ASilentp.leu70=rs2854132Homoplasmym.3438G>ASilentp.Gly44=rs377699338Homoplasmy
MT-ND1m.3720A>GSilentp.Gln138=rs41355750Homoplasmym.3546C>ASilentp.Thr80=rs1556422747Homoplasmy
MT-ND1m.3834G>ASilentp.Leu176=rs372080842Homoplasmym.3591G>ASilentp.Leu95=rs1556422757Homoplasmy
MT-ND1m.3873A>GSilentp.Thr189=rs386828925Homoplasmym.3666G>ASilentp.Gly120=rs28357968Homoplasmy
MT-ND1m.4104A>GSilentp.Leu266=rs1117205Homoplasmym.3693G>ASilentp.Leu129=rs193303027Homoplasmy
MT-ND1m.4188A>GSilentp.Leu294=Not providedHomoplasmym.3741C>TSilentp.Thr145=rs878907222Homoplasmy
MT-ND2m.4688T>CSilentp.Ala73=rs878853056Homoplasmym.4640C>AMissensep.Ile57Metrs387906426Homoplasmy
MT-ND2m.4695T>CMissensep.Phe76Leurs1556422885Homoplasmym.4774T>TGInsertion Not providedHeteroplasmy
MT-ND2m.4703T>CSilentp.Asn78=rs386828949Homoplasmym.4991G>ASilentp.Gln174=rs386828958Homoplasmy
MT-ND2m.4742T>CSilentp,Asn91=rs1553139137Homoplasmym.5036A>GSilentp.Trp189=rs28357982Homoplasmy
MT-ND2m.5075T>CSilentp,IIe202=rs1603219767Homoplasmym.5046G>AMissensep.Val193Ilers878927053Homoplasmy
MT-ND2m.5090T>CSilentp.IIe207=Not providedHomoplasmym.5120A>GSilentp.Leu217=rs1603219790Homoplasmy
MT-ND2m.5165C>TSilentp.Arg232rs1556422959Homoplasmym.5333T>CSilentp.Leu288=rs1603219906Homoplasmy
MT-ND2m.5300C>TSilentp.IIe277=rs376259646Homoplasmym.5360C>TSilentp.IIe297=rs879217723Homoplasmy
MT-ND2m.5390A>GSilentp. Met307=rs41333444Homoplasmym.5393T>CSilentp.Ser308=rs28357987Homoplasmy
MT-ND2m.5442T>CMissensep.Phe325Leurs3020601Homoplasmym.5480A>GSilentp.Leu337=rs1603219977Homoplasmy
MT-ND2m.5492T>CSilentp.Pro341=rs377109345Homoplasmy     
MT-ND2m.5493T>CMissensep.Phe342Leurs1603219983Homoplasmy     
MT-CO1m.5981T>CSilentp.Ala26=rs1603220211Homoplasmym.6026G>ASilentp.Leu41=rs879112886Homoplasmy
MT-CO1m.6045C>TSilentp.Leu48=rs879061193Homoplasmym.6216T>CSilentp.Leu105=rs367837524Homoplasmy
MT-CO1m.6179G>ASilentp.Met92=rs374303341Homoplasmym.6261G>AMissensep.Ala120Thrrs201262114Homoplasmy
MT-CO1m.6185T>CSilentp.Phe94=rs1029272Homoplasmym.6446G>ASilentp.Thr181=rs386420010Homoplasmy
MT-CO1m.6257G>ASilentp.Val118=rs2856983Homoplasmym.6521C>TSilentp.IIe 206=Not providedHomoplasmy
MT-CO1m.6366G>AMissensep.Val155Ilers370673798Homoplasmym.6548C>TSilentp.Leu215=rs28358870Homoplasmy
MT-CO1m.6497T>CSilentp.Ser198=rs1556423143Homoplasmym.6680T>CSilentp.Thr259=rs41352249Homoplasmy
MT-CO1m.6515T>CSilentp.Ala204=rs878998677Homoplasmym.6989A>GSilentp.Ser362=rs1978001Homoplasmy
MT-CO1m.6546C>TMissensep.Leu215Phers1603220531Homoplasmym.7325A>GSilentp.Glu474=rs1556423269Homoplasmy
MT-CO1m.6599A>GSilentp.Gln232rs879012660Homoplasmy     
MT-CO1m.6962G>ASilentp.Leu353=rs1970771Homoplasmy     
MT-CO1m.7028C>TSilentp.Ala375=rs2015062Homoplasmy     
MT-CO1m.7193T>CSilentp.Phe430=rs1603220829Homoplasmy     
MT-CO2m.7861T>CSilentp.Asp92=rs368623956Homoplasmym.7673A>GMissensep.Ile30Valrs1569484167Homoplasmy
MT-CO2m.8014A>TSilentp.Val143=rs879223416Homoplasmym.7711T>CSilentp.Leu42=rs372012410Homoplasmy
MT-CO2m.8053A>GSilentp.Ser156=rs56041322Homoplasmym.7867C>TSilentp.Ser94=rs9783079Homoplasmy
MT-CO2m.8179A>GSilentp.Glu198=rs1603221317Homoplasmym.8137C>TSilentp.Phe148=rs879043235Homoplasmy
MT-CO2     m.8155G>ASilentp.Gly190=rs374052533Homoplasmy
MT-ATP8m.8386C>TSilentp.Thr7=rs1603221443Homoplasmy     
MT-ATP8m.8428C>TSilentp.Phe21=rs1116905Homoplasmy     
MT-ATP8m.8460A>GMissensep.Asn32Serrs1116906Homoplasmy     
MT-ATP8m.8472T>CSilentp.Pro36=rs386829037Homoplasmy     
MT-ATP8m.8554A>GMissensep.Ile10Valrs1603221583Homoplasmy     
MT-ATP6m.8618T>CMissensep.Ile31Thrrs28358885Homoplasmym.8655C>TSilentp.IIe43=rs2853822Homoplasmy
MT-ATP6m.8705T>CMissense:p.Met60Thrrs878959404Homoplasmym.8684C>TMissensep.Thr53Ilers201336180Homoplasmy
MT-ATP6m.8860A>GMissensep.Thr112Alars2001031Homoplasmym.8978T>CMissensep.Ile151Thrrs1603221954Homoplasmy
MT-ATP6m.8958C>TSilentp.IIe144=rs1603221942Homoplasmym.9157G>AMissensep.Ala211Thrrs1556423625Homoplasmy
MT-ATP6m.9007A>GMissensep.Thr161Alars1603221973Homoplasmy     
MT-ATP6m.9042C>TSilentp.His172=rs3020605Homoplasmy     
MT-ATP6m.9103T>CMissensep.Thr161Alars1603222077Homoplasmy     
MT-CO3m.9336A>GMissensep.Met44Leurs28474779Homoplasmym.9302C>TSilentp.Ala32=rs878986141Homoplasmy
MT-CO3m.9347A>GSilentp.Leu47=rs2853824Homoplasmym.9656T>CSilentp.Ser150=rs1556423706Homoplasmy
MT-CO3m.9494A>GSilentp.Gly96=rs1556423680Homoplasmym.9899T>CSilentp.His231=rs41345446Homoplasmy
MT-CO3m.9509T>CSilentp.Phe101=rs375478739Homoplasmym.9956A>GSilentp.Leu250=rs1603222594Homoplasmy
MT-CO3m.9545A>GSilentp.Gly113=rs878853022Homoplasmy     
MT-CO3m.9575G>ASilentp.Pro123=rs372078920Homoplasmy     
MT-CO3m.9755G>ASilentp.Glu183=rs2856985Homoplasmy     
MT-CO3m.9776C>TSilentp.Asp190=Not providedHomoplasmy     
MT-CO3m.9818C>TSilentp.His204rs2854139Homoplasmy     
MT-CO3m.9948G>AMissensep.Val248Ilers1556423747Homoplasmy     
MT-ND3m.10101T>CSilentp.Leu15=rs1603222669Homoplasmym.10084T>CMissensep.Ile9Thrrs41487950Homoplasmy
MT-ND3m.10143G>AMissensep.Gly29Serrs202131419Homoplasmym.10142C>TSilentp.Asn28=rs878969753Homoplasmy
MT-ND3m.10184C>TSilentp.Asp42=Not providedHomoplasmym.10238T>CSilentp.IIe60=rs193302927Homoplasmy
MT-ND3m.10275T>CSilentp.Leu73=rs373277477Homoplasmym.10289A>GSilentp.Trp77=rs1556423796Homoplasmy
MT-ND4Lm.10499A>GSilentp.Leu10=rs1057520074Homoplasmym.10550A>GSilentp.Met27=rs28358280Homoplasmy
MT-ND4Lm.10556C>TSilentp.Ser29=rs1603222890Homoplasmym.10586G>ASilentp.Ser39=rs28358281Homoplasmy
MT-ND4Lm.10589G>ASilentp.Leu40=rs2853487Homoplasmy     
MT-ND4Lm.10628C>TSilentp. Ser53=Not providedHomoplasmy     
MT-ND4Lm.10632T>CSilentp.Leu55=rs878888873Homoplasmy     
MT-ND4Lm.10664C>TSilentp.Val65=rs193302933Homoplasmy     
MT-ND4m.10819A>GSilentp.Lys20=rs28358283Homoplasmym.10822C>TSilentp.His21=rs879041592Homoplasmy
MT-ND4m.10876A>GSilentp.Leu39=rs879036391Homoplasmym.11299T>CSilentp.Thr180=rs28358285Homoplasmy
MT-ND4m.10915T>CMissensep.Cys52Trprs2857285Homoplasmym.11476C>TSilentp.Gly239=rs386829131Homoplasmy
MT-ND4m.11002A>GSilentp.Gln81=rs386829114Homoplasmy     
MT-ND4m.11016G>AMissensep.Ser86Thrrs28594904Homoplasmy     
MT-ND4m.11050T>CSilentp.Ser97=rs1603223077Homoplasmy     
MT-ND4m.11143C>TSilentp.Pro128=rs1556423898Homoplasmy     
MT-ND4m.11172A>GMissensep.Asn138Serrs2853489Homoplasmy     
MT-ND4m.11176G>ASilentp.Gln139=rs2853490Homoplasmy     
MT-ND4m.11287T>CSilentp.IIe176=rs386829125Homoplasmy     
MT-ND4m.11377G>ASilentp.Lys206=rs193302938Homoplasmy     
MT-ND4m.11440G>ASilentp.Gly227=rs386829130Homoplasmy     
MT-ND4m.11590A>GSilentp.Leu277=rs370318850Homoplasmy     
MT-ND4m.11641A>GSilentp.Met294=rs2853494Homoplasmy     
MT-ND4m.11776T>CSilentp.Ser339=rs28396842Homoplasmy     
MT-ND4m.11935T>CSilentp.Thr392=rs1603223480Homoplasmy     
MT-ND4m.12007G>ASilentp.Trp416=rs2853497Homoplasmy     
MT-ND4m.12061C>TSilentp.Asn434=rs1556424043Homoplasmy     
MT-ND5m.12570A>GSilentp.Leu78=rs1603223816Homoplasmym.12403C>TMissensep.Leu23Phers879096684Homoplasmy
MT-ND5m.12720A>GSilentp.Met128=rs2853500Homoplasmym.12501G>ASilentp.Met55=rs28397767Homoplasmy
MT-ND5m.12771G>ASilentp.Glu145=rs878865822Homoplasmym.12633C>ASilentp.Ser99=rs3926883Homoplasmy
MT-ND5m.12876C>TSilentp.IIe180=rs1603223952Homoplasmym.12879T>CSilentp.Gly181=rs1556424182Homoplasmy
MT-ND5m.13020T>CSilentp.Gly228=rs75577869Homoplasmym.12950A>CMissensep.Asn205Thrrs201361958Homoplasmy
MT-ND5m.13116C>TSilentp.Leu260=rs1603224049Homoplasmym.13104A>GSilentp.Gly256=rs878871104Homoplasmy
MT-ND5m.13158A>GSilentp.Gln274=rs1556424229Homoplasmym.13422A>GSilentp.Leu362=rs386829180Homoplasmy
MT-ND5m.13276A>GMissensep.Met314Leurs2853502Homoplasmym.13500T>CSilentp.Gly388=rs879066842Homoplasmy
MT-ND5m.13419A>GSilentp.Gly361=rs1603224182Homoplasmym.13530C>TSilentp.Thr398=rs2068736572Homoplasmy
MT-ND5m.13734T>CSilentp.Phe466=rs41421644Homoplasmym.13780A>GMissensep.Ile482Valrs41358152Homoplasmy
MT-ND5m.13759G>AMissensep.Ala475Thrrs386420024Homoplasmym.13789T>CMissensep.Tyr485Hisrs28359179Homoplasmy
MT-ND5m.13813G>AMissensep.Val493Ilers1556424332Homoplasmym.13880C>AMissensep.Ser515Tyrrs28359181Homoplasmy
MT-ND5m.13886T>CMissensep.Leu517Prors28359182Homoplasmym.14070A>GSilentp.Ser578=rs879201732Homoplasmy
MT-ND5m.13967C>TMissensep.Thr544Metrs386829197Homoplasmym.14110T>CMissensep.Phe592Leurs371451099Homoplasmy
MT-ND5m.14053A>GMissensep.Thr573Alars200134839Homoplasmym.14139A>GSilentp.Leu601=rs878918283Homoplasmy
MT-ND6m.14212T>CSilentp.Val154=rs28357672Homoplasmym.14178T>CMissensep.Ile166Valrs28357671Homoplasmy
MT-ND6m.14284C>TSilentp.Glu130=rs28357673Homoplasmym.14203A>GSilentp.Gly157=rs1569484633Homoplasmy
MT-ND6m.14308T>CSilentp.Gly122=rs28357674Homoplasmym.14287T>CSilentp.Gly129=rs1603224652Homoplasmy
MT-ND6m.14494T>CSilentp.Leu60=rs879250748Homoplasmym.14364G>ASilentp Leu104=rs879086798Homoplasmy
MT-ND6m.14562C>TMissensep.Val38Ilers1603224791Homoplasmym.14497A>GSilentp.Tyr59=rs1556424454Homoplasmy
MT-ND6m.14587A>GSilentp.Gly29=rs1556424469Homoplasmym.14560G>ASilentp.Val38=rs28357676Homoplasmy
MT-ND6m.14634T>CMissensep.Met14Valrs1603224816Homoplasmy     
MT-CYBm.14755A>GSilentp.Pro3=rs1603224856Homoplasmym.14769A>GMissensep.Asn8Serrs28357679Homoplasmy
MT-CYBm.14839A>GSilentp.Trp31=rs1603224921Homoplasmym.14774C>TSilentp.Leu10=rs1556424490Homoplasmy
MT-CYBm.14862C>TMissensep.Ala39Valrs1603224933Homoplasmym.15077G>AMissensep.Glu111Lysrs201943501Homoplasmy
MT-CYBm.14872C>TSilentp.IIe42=rs878879194Homoplasmym.15115T>CSilentp.Thr123=rs879035822Homoplasmy
MT-CYBm.15136C>TSilentp.Gly130=rs2854124Homoplasmym.15217G>ASilentp.Gly157=rs193302989Homoplasmy
MT-CYBm.15172G>TSilentp.Gly142=rs367572771Homoplasmym.15454T>CSilentp.Leu236=rs879015290Homoplasmy
MT-CYBm.15218A>GMissensep.Thr158Alars2853506Homoplasmym.15865A>GSilentp.Glu373=rs879154157Homoplasmy
MT-CYBm.15257G>AMissensep.Asp171Asnrs41518645Homoplasmy     
MT-CYBm.15314G>AMissensep.Ala190Thrrs527236176Homoplasmy     
MT-CYBm.15403C>TSilentp.Thr219=rs1603225258Homoplasmy     
MT-CYBm.15431G>AMissensep.Ala229Thrrs193302993Homoplasmy     
MT-CYBm.15468C>TMissensep.Thr241Metrs1603225301Homoplasmy     
MT-CYBm.15490C>TSilentp.Asp248=rs1603225311Homoplasmy     
MT-CYBm.15530T>CSilentp.Leu262=rs1556424600Homoplasmy     
MT-CYBm.15646C>TSilentp.IIe300=rs879113411Homoplasmy     
MT-CYBm.15679A>GSilentp.Lys311=rs1603225420Homoplasmy     
MT-CYBm.15735C>TMissensep.Ala330Valrs1603225446Homoplasmy     
MT-CYBm.15799A>GSilentp.Gly351=rs1603225506Homoplasmy     

In addition, 126 (28.9%) mtDNA variants were common for both patients with PsA and controls (Appendix I). The frequency of two common variants differed significantly between the two groups. The substitution variant m.152T>C in the D-loop region was found in 26% of patients and 55% of controls (OR=0.3, 95% CI=0.1-0.5, P=0.02), whereas the silent variant m.15301G>A in the MT-CYB gene was found in 30% of patients and 10% of controls (OR=3.8, 95% CI=1-8, P=0.04). The remaining variants showed no significant differences in their prevalence among patients or controls (P>0.05).

Variants with amino acid substitutions in patients with PsA and their impact on protein function and protein stability

Out of 187 (43%) mtDNA variants detected only in patients with PsA, 33 missense variants in mtDNA-encoding genes of complexes I, III, IV, and V resulted in amino acid substitutions.

Bioinformatics analysis using CADD, Condel, and PROVEAN was conducted to determine the potential impact of 33 missense variants that detected in PsA patients, on protein function and structure. The analysis predicted 25 variants to be deleterious by at least one bioinformatics tool (Table III). The highest impact on protein function and structure (by all three in-silico algorithms) was predicted for 2 variants, namely the m.11172A>G variant (referred to as rs2853489 polymorphism) in the MT-ND4 gene and the m.15257G>A variant (referred to as rs41518645 polymorphism) in the MT-CYB gene. The allelic frequencies of these variants in the gnome AD database were 0.0007. and 0.01, respectively.

Table III

mtDNA variants with amino acid substitutions in patients with psoriatic arthritis and their impact on protein function and structure.

Table III

mtDNA variants with amino acid substitutions in patients with psoriatic arthritis and their impact on protein function and structure.

 Prediction
GeneVariantVariant typeAmino acid changers IDMAFCADD/scoreCondel/scorePROVEAN/score
MT-ND2m.4695T>CMissensep.Phe76Leurs15564228850.0003Neutral/5.35Neutral/0.07Neutral/1,2
MT-ND2m.5442T>CMissensep.Phe325Leurs30206010.00478Neutral/0.03Neutral/0.28Neutral/0.7
MT-ND2m.5493T>CMissensep.Phe342Leurs16032199830.007Neutral/12.34Neutral/0.31Neutral/0.52
MT-CO1m.6366G>AMissensep.Val155Ilers3706737980.0018Neutral/0.01Deleterious/1Neutral/-1.1
MT-CO1m.6546C>TMissensep.Leu215Phers16032205310.0002Neutral/6.11 Deleterious/0.84Neutral/-0.45
MT-ATP8m.8460A>GMissensep.Asn32Serrs11169060.00094Neutral/12Neutral/0.27Neutral/-1.6
MT-ATP8m.8554A>GMissensep.Ile10Valrs16032215830.0001Neutral/7.68 Deleterious/0.54Neutral/0.18
MT-ATP6m.8618T>CMissensep.Ile31Thrrs283588850.009Neutral/5.55 Deleterious/0.5Neutral/2
MT-ATP6m.8705T>CMissensep.Met60Thrrs8789594040.0043Neutral/0.5 Deleterious/0.75Neutral/0.32
MT-ATP6m.8860A>GMissensep.Thr112Alars20010310.99Neutral/6.13 Deleterious/0.81 Deleterious/-3.9
MT-ATP6m.9007A>GMissensep.Thr161Alars16032219730.0058Deleterious/23Neutral/0.06 Deleterious/-3.5
MT-ATP6m.9103T>CMissensep.Thr161Alars16032220770.00045Neutral/9.74Deleterious/1 Deleterious/-2.5
MT-CO3m.9336A>GMissensep.Met44Leurs284747790.0004Neutral/0.01 Deleterious/0.68Neutral/-0.32
MT-CO3m.9948G>AMissensep.Val248Ilers15564237470.0012Neutral/9.11 Deleterious/0.65Neutral/-0.84
MT-ND3m.10143G>AMissensep.Gly29Serrs2021314190.0015Neutral/5.51 Deleterious/0.96Neutral/1.9
MT-ND4m.10915T>CMissensep.Cys52Trprs28572850.02Neutral/16.8Neutral/0.36Neutral/0.37
MT-ND4m.11016G>AMissensep.Ser86Thrrs285949040.004Neutral/0.11 Deleterious/0.68Neutral/0.21
MT-ND4m.11172A>GMissensep.Asn138Serrs28534890.0007Deleterious/20 Deleterious/0.69 Deleterious/-3.5
MT-ND5m.13276A>GMissensep.Met314Leurs28535020.00169Neutral/14Neutral/0.12Neutral/0.2
MT-ND5m.13759G>AMissensep.Ala475Thrrs3864200240.0143Neutral/0.69 Deleterious/0.73Neutral /1.6
MT-ND5m.13813G>AMissensep.Val493Ilers15564243320.0013Neutral/6.86 Deleterious/0.74Neutral/-0.37
MT-ND5m.13886T>CMissensep.Leu517Prors283591820.0018Neutral/9.6 Deleterious/0.6Neutral/0.23
MT-ND5m.13967 C>TMissensep.Thr544Metrs3868291970.0011Neutral/1.23 Deleterious/0.61Neutral/0.85
MT-ND5m.14053 A>GMissensep.Thr573Alars2001348390.002Neutral/0.17 Deleterious/0.76Neutral/1.8
MT-ND6m.14562 C>TMissensep.Val38Ilers16032247910.0002Neutral/1.7 Deleterious/0.8Neutral/0.06
MT-ND6m.14634 T>CMissensep.Met14Valrs16032248160.0011Neutral/12Neutral/0.17Neutral/0.001
MT-CYBm.14862 C>TMissensep. Ala39Valrs16032249330.0007Neutral/17.5 Deleterious/0.65Neutral/1.4
MT-CYBm.15218 A>GMissensep.Thr158Alars28535060.03Neutral/13.3Neutral/0.29Neutral/-1.6
MT-CYBm.15257 G>AMissensep.Asp171Asnrs415186450.01 Deleterious/23.5 Deleterious/0.67 Deleterious/-3.5
MT-CYBm.15314 G>AMissensep.Ala190Thrrs5272361760.002Neutral/16.4 Deleterious/0.61Neutral/-1.6
MT-CYBm.15431 G>AMissensep.Ala229Thrrs1933029930.002 Deleterious/24.4 Deleterious/0.61Neutral/-0.22
MT-CYBm.15468 C>TMissensep.Thr241Metrs16032253010.0004 Deleterious/20.8Neutral/0.41Neutral/-0.81
MT-CYBm.15735 C>TMissensep.Ala330Valrs16032254460.0001Deleterious/22 Deleterious/0.78Neutral/-1.7

In total, 5 other variants were predicted to be deleterious by two in-silico algorithms tools: 3 variants in the MT-ATP6 gene namely m.8860A>G (referred to as rs2001031 polymorphism), m.9007A>G (referred to as rs1603221973 polymorphism) and m.9103T>C (referred as rs1603222077 polymorphism); and 2 variants in the MT-CYB gene namely m.15431G>A (referred to as rs193302993 polymorphism) and m.15735C>T (referred to as rs1603225446 polymorphism). With the exception of the MT-ATP6 variant m.8860A>G with an allelic frequency of 0.99, all other variants had allelic frequencies of <0.01 in the gnome AD database (https://gnomad.broadinstitute.org/).

In addition, 18 other variants were predicted to be deleterious by one of the in-silico algorithms tools. These included 2 variants in the MT-CO1 gene, 1 variant in the MT-ATP8 gene, 2 variants in the MT-ATP6 gene, 2 variants in the MT-CO3, 1 variant in the MT-ND3 gene, 1 variant in the MT-ND4 gene, 5 variants in the MT-ND5 gene, 1 variant in the MT-ND6 gene and 3 variants in the MT-CYB gene. The majority of these variants also had low allelic frequencies (<0.01) in the gnome AD database.

In subsequent analysis, the deleterious mtDNA variants were further evaluated for their effect on protein stability using SDM. In SMD, a stability score is calculated using environment-specific amino acid substitution frequencies within the family of homologous proteins of known 3-D structures (30). All variants in mtDNA-encoded genes of complexes I, III and IV were examined at the level of protein stability. However, the effect of variants in the MT-ATP6 and MT-ATP8 genes of complex V could not be demonstrated as the human 3-D structures were not available for complex V proteins.

As shown in Table IV, SDM predicted 19 destabilizing variants in mtDNA-encoded genes of complexes I, III and IV. Of them, 13 variants were predicted to decrease the stability of encoded proteins, including 1 variant in the MT-CO1 gene (m.6546C>T), 2 variants in the MT-CO3 gene (m.9336A>G and m.9948G>A), 1 variant in the MT-ND3 gene (m.10143G>A), 2 variants in the MT-ND4 gene (m.11016G>A and m.11172A>G), 3 variants in the MT-ND5 gene (m.13759G>A, m.13813G>A and m.13886T>C), and 4 variants in the MT-CYB gene (m.14862C>T, m.15314G>A, m.15431G>A, and m.15735C>T). Furthermore, 6 variants were found to increase the stability of encoded proteins: 1 variant in the MT-CO1 gene (m.6366G>A), 2 variants in the MT-ND5 gene (m.13967C>T and m.14053A>G), 1 variant in the MT-ND6 gene (m.14562C>T) and 2 variants in the MT-CYB gene (m.15257G>A and m.15468C>T).

Table IV

Deleterious mtDNA variants in patients with psoriatic arthritis and their impact on protein stability.

Table IV

Deleterious mtDNA variants in patients with psoriatic arthritis and their impact on protein stability.

 SDM
GeneVariantVariant typeAmino acid changers IDDDGStability outcome
MT-CO1m.6366G>AMissensep.Val155Ilers3706737980.68Increased
MT-CO1m.6546C>TMissensep.Leu215Phers1603220531-0.09Decreased
MT-ATP8m.8554A>GMissensep.Ile10Valrs1603221583NPNP
MT-ATP6m.8618T>CMissensep.Ile31Thrrs28358885NPNP
MT-ATP6m.8705T>CMissensep.Met60Thrrs878959404NPNP
MT-ATP6m.8860A>GMissensep.Thr112Alars2001031NPNP
MT-ATP6m.9007A>GMissensep.Thr161Alars1603221973NPNP
MT-ATP6m.9103T>CMissensep.Thr161Alars1603222077NPNP
MT-CO3m.9336A>GMissensep.Met44Leurs28474779-0.44Decreased
MT-CO3m.9948G>AMissensep.Val248Ilers1556423747-0.94Decreased
MT-ND3m.10143G>AMissensep.Gly29Serrs202131419-0.41Decreased
MT-ND4m.11016G>AMissensep.Ser86Thrrs28594904-0.69Decreased
MT-ND4m.11172A>GMissensep.Asn138Serrs2853489-0.64Decreased
MT-ND5m.13759G>AMissensep.Ala475Thrrs386420024-0.66Decreased
MT-ND5m.13813G>AMissensep.Val493Ilers1556424332-0.38Decreased
MT-ND5m.13886T>CMissensep.Leu517Prors28359182-1.5Decreased
MT-ND5m.13967C>TMissensep.Thr544Metrs3868291970.014Increased
MT-ND5m.14053A>GMissensep.Thr573Alars2001348391.53Increased
MT-ND6m.14562C>TMissensep.Val38Ilers16032247910.35Increased
MT-CYBm.14862C>TMissensep.Ala39Valrs1603224933-0.409Decreased
MT-CYBm.15257G>AMissensep.Asp171Asnrs415186450.39Increased
MT-CYBm.15314G>AMissensep.Ala190Thrrs527236176-1.53Decreased
MT-CYBm.15431G>AMissensep.Ala229Thrrs193302993-2.05Decreased
MT-CYBm.15468C>TMissensep.Thr241Metrs16032253011.19Increased
MT-CYBm.15735C>TMissensep.Ala330Valrs1603225446-0.84Decreased
Relative leukocyte mtDNAcn

Using qPCR, the relative mtDNAcn was determined in the leukocytes of patients with PsA (n=23) and healthy controls (n=20). The results showed a 3.44-fold reduction in mtDNAcn in patients with PsA compared with controls. The mean ± SD mtDNAcn was 93.3±10 in patients vs. 321±29 in controls (P=0.0001) (Fig. 2).

mtDNA oxidative damage

mtDNA oxidative damage was assessed using qPCR by measuring the 8-OHdG content in patients with PsA and controls. The ΔCq value of the difference between the Cq value of DNA samples treated with FPG and the Cq value of DNA samples without FPG treatment was calculated. The results showed a 2-fold increase in the level of mtDNA oxidative damage in patients with PsA compared with controls. The ΔCq value was 0.98±0.29 in patients vs. 0.49±0.3 in controls (P=0.03) (Fig. 3).

Discussion

PsA is a chronic inflammatory disease, which presents in a significant number of individuals with psoriasis (1-3). PsA is widely regarded as a multi-factorial disease with underlying autoimmune mechanisms including infiltration of plasma cells and mononuclear cells that are observed in both psoriatic plaque and PsA articular space (7). Mitochondrial dysfunction plays an important role in the pathogenesis of PsA by modulating innate immunity via redox-sensitive inflammatory pathways or directly through activation of the inflammatory response (9,10). An imbalance in oxidant-antioxidant mitochondrial system results in oxidative stress, which can induce mtDNA variations and copy number changes leading to mitochondrial functional impairment (17,18). Currently, there is limited knowledge on whether abnormalities in mtDNA a possible factor could be involved in PsA.

The present study sequenced the entire mitochondrial genome using NGS, a high-throughput and sensitive method with the ability to detect any variants (22), investigated changes in mtDNAcn and evaluated mtDNA oxidative damage in patients with PsA and healthy controls.

Analysis of the entire mitochondrial genome revealed a total of 435 variants, distributed across all regions of the mtDNA. These included 187 (43%) variants exclusively found in patients with PsA, and 122 (28%) only present in control individuals. A higher number of variants were observed in the D-loop region in both patients and controls, whereas a higher number of variants in mtDNA-coding genes was found in patients compared with controls, particularly in the MT-ND4, MT-ND5, and MT-CYB genes. In addition, common mtDNA variants (126, 28.9%) were identified among patients and controls. The frequency of two specific variants differed significantly (P<0.05) between the two groups and may be linked with the susceptibility to PsA. Namely, the D-loop m.152T>C variant occurred in 26% of patients and 55% of controls (OR=0.3, 95% CI=0.1-0.5, P=0.02) and may confer a protective role against PsA. The D-loop (non-coding or control region) contains essential regulatory sequences for replication and transcription (34). Although the majority of harmful variants are removed by natural selection, some of these variants are introduced in certain populations and may influence the risk of developing certain disorders (35), whereas other variants such as m.152T>C may be selectively beneficial on some genetic backgrounds. Additionally, the silent m.15301G>A variant in the MT-CYB gene occurred in 30% of patients and 10% of controls (OR=3.8, 95% CI=1-8, P=0.04) and may be associated with the risk of developing PsA. Synonymous variants in protein-coding genes are generally considered to be silent with no effect on protein function. However, previous studies have shown that silent variants can significantly alter gene expression by affecting the stability and folding of mRNA (36,37), and can also influence the rate of translation and posttranslational modification of proteins (38).

mtDNA variants that cause changes in amino acid sequences of protein-coding genes have been implicated in the pathogenicity of numerous diseases such as rheumatoid arthritis (RA) (39). In the present study, analysis of mtDNA in patients with PsA only revealed 33 missense variants in mtDNA-encoded genes of the ETC. In total, 25 of these variants were predicted to have deleterious effects on encoded proteins by 1-3 bioinformatics tools (CADD, Condel and PROVEAN).

Specifically, 2 missense transition variants in MT-ND4 gene and MT-CYB gene were predicted to have the highest impact on protein function and structure by all three in silico algorithms tools. Moreover, 5 mtDNA variants were predicted to be deleterious by two in silico algorithms tools, including 3 variants in the MT-ATP6 gene and 2 variants in the MT-CYB gene. A total of 18 other variants in all mtDNA-encoded complexes of the ETC were predicted to be deleterious by one of the in silico algorithms tools. The majority of these variants are considered rare with low allelic frequencies <0.01 in the gnome AD database.

Protein function and stability are closely related to protein structure. Variants that cause amino acid alterations can markedly change protein structure (30,40). Particularly, the unique amino acid sequence of a protein is reflected in its folded structure, which is important to perform proper biological function. Changes in the hydration status of a protein also affect protein folding (41). Hydrophobic interactions are important for protein folding, and changes in hydrophobicity can lead to a collapse of the protein chain in an aqueous environment (42). The polarity of amino acids also promotes appropriate folding by interacting with the water solvent, thus affecting protein stability (41). All the identified deleterious missense variants in the current study produce amino acids that are different from the usual amino acids at that position and alter the function of proteins. For instance, the MT-ND4 m.11172A>G variant causes changes in amino acid from Asparagine to Serine (p.Asn138Ser), while the MT-CYB m.15257G>A variant causes changes in amino acid from Asparagine to Aspartic acid (p.Asp171Asn). Asparagine is a hydrophilic uncharged polar amino acid, whereas serine is a neutral uncharged polar amino acid, and aspartic acid is a hydrophilic negatively charged polar amino acid.

Previous studies have demonstrated that protein flexibility is a key factor for its catalytic activity (43), and increased stability of thermophilic proteins has been shown to be associated with loss of protein flexibility and reduced enzymatic activity at low temperatures (44,45). Furthermore, high stability of proteins leads to increased proteolytic resistance, which make them difficult to regulate, particularly during cell signalling (46). It has been also shown that variants causing increased protein stability can lead to protein malfunction in human diseases, such as the stabilizing homozygous variant S37A in patients with parathyroid adenomas (47) and the Parkinson disease-associated A30P stabilizing variant in human neuroblastoma cells (48).

Analysis of the impact of deleterious variants on protein stability in present study revealed 19 destabilizing variants in mtDNA-encoded genes of complexes I, III and IV. Of them, 13 variants in different mtDNA-encoded complexes of the ETC were predicted to decrease protein stability. Moreover, 6 variants were found to increase the stability of encoded proteins. These variants may affect the stabilizing interaction within folded proteins, leading to protein instability and malfunction.

The mitochondrial OXPHOS system comprises four multi-enzymatic respiratory complexes (namely I-IV) and ATP synthase and is embedded in the inner mitochondrial membrane. A total of 4 of these complexes (I, III, IV and V) are encoded by both nDNA and mtDNA genes. Complex I (NADH: ubiquinone oxidoreductase) is one of the main contributors to ROS production within the mitochondrial matrix, which is a major cause of cellular oxidative stress and is associated with neuromuscular diseases and aging (49-52). mtDNA-encoded genes of complex I are hotspots for pathological variants (19). Such variants affect complex I assembly and activity leading to complex I deficiency with increased ROS production (51-55). Particularly, variants in mitochondrial complex I genes have been previously reported to be associated with severe erosive arthritis and to be implicated in the pathogenesis of RA (39). Complex III (bc1 complex; ubiquinol cytochrome c reductase) has been also identified as a main producer of superoxide within the mitochondrial respiratory chain (56,57). Previous studies have revealed that deleterious variants in the MT-CYB gene caused isolated complex III deficiency, leading to a variety of human diseases such as cardiomyopathy, encephalomyopathy, and Leber hereditary optic neuropathy (58-61). Complex IV or cytochrome c oxidase (COX) is one of the major regulation sites for OXPHOS and deficiency in the activity of COX has been linked to a variety of diseases (62). ATP6 and ATP8 are mtDNA-encoded subunits of the ATP synthase of complex V, which utilizes the energy provided by the proton electrochemical gradient across the inner membrane during OXPHOS and synthesizes ATP from ADP (63). Variants in MT-ATP8 gene can disturb the stability and function of complex V, affecting ATP production (64). In a previous study by Du et al (39), a higher rate of mtDNA variants in complex V was found in patients with RA compared with controls, suggesting that these variants may be associated with susceptibility to RA. Variants in complex V were also linked to ROS production and apoptosis pathways, and associated with RA progression (39).

Integrity of mtDNA which encodes essential proteins of the ETC subunits is mandatory for normal mitochondrial function (13). Improper function of ETC can enhance ROS production, which is implicated in psoriatic inflammation and PsA (9,65). Improper function of ETC can enhance ROS production, which is implicated in psoriatic inflammation and PsA (9,65). The deleterious mtDNA variants in patients with PsA identified in the present study were not detected in control individuals; were located in functionally/structurally important sites of mtDNA-encoded subunits of the ETC; and resulted in protein instability. Thus, these variants may be disease-related and could play a role in the pathogenicity of PsA.

There are several copies per cell of mtDNA, resulting in both homoplasmy (identical mtDNA) and heteroplasmy (mixture of mutated and wild-type mtDNA). In the present study, a higher rate of homoplasmic variants was detected compared with heteroplasmic variants. While most pathogenic mtDNA variants are heteroplasmic, the clinical expression of diseases is determined by the level of heteroplasmy. In this context, mitochondrial dysfunction becomes clinically apparent when the percentage of mutant mtDNA exceeds a certain threshold level. Instead, some mtDNA diseases such as Leber hereditary optic neuropathy are caused by homoplasmic variants (66). Pathogenic homoplasmic variants have been also reported in diseases such as Leigh syndrome (67) and multiple sclerosis (68), and may increase the risk of type 2 diabetes (69) and neurodegenerative diseases (70). Importantly, the phenotypic expression of homoplasmic variants can be tissue-specific, suggesting that incomplete penetrance and unidentified nuclear genetic and/or environmental factors are likely to contribute to the disease phenotype (66).

The present results also revealed a significant reduction in mtDNAcn in leukocytes of patients with PsA compared with healthy controls. mtDNAcn is an important indicator of mitochondrial biogenesis and function (15). Consequently, changes in mtDNA content could contribute to various pathological conditions (20). Low mtDNAcn was previously reported in numerous diseases such as OA (71). In our previous study, decreased mtDNAcn in patients with psoriasis was found compared with controls (24). Decreased mtDNAcn is associated with oxidative stress-induced mtDNA damage and poor oxidative capacity which can lead to a reduction in mitochondrial function and subsequent disruption of cellular functions which could affect several tissues (24,72).

The present study also found a higher level of mtDNA oxidative damage in patients with PsA compared with controls. It is well established that mtDNA is more susceptible to oxidative damage and has a higher mutational rate than nDNA (16). Oxidative damage to mtDNA can impair mitochondrial bioenergetics and causes defective mitochondrial ATP generation, which leads to further mitochondrial dysfunction and increased ROS production. Therefore, decreased mtDNAcn in patients with PsA may be a consequence of mtDNA oxidative damage.

In conclusion, the present study identified a number of unique variants in patients with PsA only or healthy controls only, as well as common variants in patients and controls, two of which may be associated with the susceptibility to PsA, and also identified various missense variants that were present only in patients with PsA and were predicted to be deleterious with important effect on the function and stability of encoded proteins. In addition, lower mtDNAcn and higher levels of mtDNA oxidative damage were found in patients with PsA compared with controls. Taken together, the present findings suggested that impaired mitochondrial function due to deleterious mtDNA variants, low mtDNAcn, and oxidative damage may be contributory factors in the pathogenesis of PsA. To the best of our knowledge, the present study is the first comprehensive analysis of mtDNA in PsA. However, the present study is limited by the small number of subjects enrolled; thus, additional large-scale studies are warranted to further elucidate the role of mtDNA defects in PsA. Moreover, the possible effect of nuclear genes and environmental factors on mitochondrial genetics in PsA should be considered in future studies. In addition, to provide an improved estimate of mtDNA damage, several regions within the mtDNA genome including the D-loop region should be targeted in future studies.

Supplementary Material

Common mtDNA variants among PsA patients and controls.

Acknowledgements

The authors would like to express their gratitude to Dr Betsy Sheena at research sector of Faculty of Sciences, Kuwait University (State of Kuwait) for the next generation sequencing data analysis and also the authors would like to acknowledge the next generation sequencing facility under the project GS01/02.

Funding

Funding: No funding was received.

Availability of data and materials

The datasets generated and/or analysed during the current study are available in the Sequence Read Archive (SRA) repository with reference PRJNA 928743 (accession no. https://www.ncbi.nlm.nih.gov/sra/PRJNA928743).

Authors' contributions

MSA was the project administrator, was responsible for the conceptualization, methodology, investigation, acquisition of resources/funding and the data curation of the present study. MSA, GAK and MA implemented formal analysis. MSA and GAK confirm the authenticity of all raw data. MSA and GAK wrote the original draft, reviewed and edited the manuscript. All authors have read and approved the final version of the manuscript.

Ethics approval and consent to participate

The present study was conducted according to the guidelines of the Declaration of Helsinki and approved (approval no. 2018/496) by the Health Science Center Ethics Committee at Kuwait University and Health and Medical Research Committee in the Ministry of Health (City of Kuwait, State of Kuwait). Informed consent was obtained from all subjects involved in the study.

Patient consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

References

1 

Alinaghi F, Calov M, Kristensen LE, Gladman DD, Coates LC, Jullien D, Gottlieb AB, Gisondi P, Wu JJ, Thyssen JP and Egeberg A: Prevalence of psoriatic arthritis in patients with psoriasis: A systematic review and meta-analysis of observational and clinical studies. J Am Acad Dermatol. 80:251–265 e219. 2019.PubMed/NCBI View Article : Google Scholar

2 

Ocampo DV and Gladman D: Psoriatic arthritis. F1000Res. 8(F1000)2019.PubMed/NCBI View Article : Google Scholar

3 

Karmacharya P, Chakradhar R and Ogdie A: The epidemiology of psoriatic arthritis: A literature review. Best Pract Res Clin Rheumatol. 35(101692)2021.PubMed/NCBI View Article : Google Scholar

4 

Sukhov A, Adamopoulos IE and Maverakis E: Interactions of the immune system with skin and bone tissue in psoriatic arthritis: A comprehensive review. Clin Rev Allergy Immunol. 51:87–99. 2016.PubMed/NCBI View Article : Google Scholar

5 

Saalfeld W, Mixon AM, Zelie J and Lydon EJ: Differentiating psoriatic arthritis from osteoarthritis and rheumatoid arthritis: A narrative review and guide for advanced practice providers. Rheumatol Ther. 8:1493–1517. 2021.PubMed/NCBI View Article : Google Scholar

6 

Gladman DD, Mease PJ, Healy P, Helliwell PS, Fitzgerald O, Cauli A, Lubrano E, Krueger GG, van der Heijde D, Veale DJ, et al: Outcome measures in psoriatic arthritis. J Rheumatol. 34:1159–1166. 2007.PubMed/NCBI

7 

Carvalho AL and Hedrich CM: The molecular pathophysiology of psoriatic arthritis-the complex interplay between genetic predisposition, epigenetics factors, and the microbiome. Front Mol Biosci. 8(662047)2021.PubMed/NCBI View Article : Google Scholar

8 

Eder L, Haddad A, Rosen CF, Lee KA, Chandran V, Cook R and Gladman DD: The incidence and risk factors for psoriatic arthritis in patients with psoriasis: A prospective cohort study. Arthritis Rheumatol. 68:915–923. 2016.PubMed/NCBI View Article : Google Scholar

9 

Mizuguchi S, Gotoh K, Nakashima Y, Setoyama D, Takata Y, Ohga S and Kang D: Mitochondrial reactive oxygen species are essential for the development of psoriatic inflammation. Front Immunol. 12(714897)2021.PubMed/NCBI View Article : Google Scholar

10 

Therianou A, Vasiadi M, Delivanis DA, Petrakopoulou T, Katsarou-Katsari A, Antoniou C, Stratigos A, Tsilioni I, Katsambas A, Rigopoulos D and Theoharides TC: Mitochondrial dysfunction in affected skin and increased mitochondrial DNA in serum from patients with psoriasis. Exp Dermatol. 28:72–75. 2019.PubMed/NCBI View Article : Google Scholar

11 

Lin X and Huang T: Oxidative stress in psoriasis and potential therapeutic use of antioxidants. Free Radic Res. 50:585–595. 2016.PubMed/NCBI View Article : Google Scholar

12 

Osellame LD, Blacker TS and Duchen MR: Cellular and molecular mechanisms of mitochondrial function. Best Pract Res Clin Endocrinol Metab. 26:711–723. 2012.PubMed/NCBI View Article : Google Scholar

13 

Garcia I, Jones E, Ramos M, Innis-Whitehouse W and Gilkerson R: The little big genome: The organization of mitochondrial DNA. Front Biosci (Landmark Ed). 22:710–721. 2017.PubMed/NCBI View Article : Google Scholar

14 

Burr SP, Pezet M and Chinnery PF: Mitochondrial DNA heteroplasmy and purifying selection in the mammalian female germ line. Dev Growth Differ. 60:21–32. 2018.PubMed/NCBI View Article : Google Scholar

15 

Montier LL, Deng JJ and Bai Y: Number matters: Control of mammalian mitochondrial DNA copy number. J Genet Genomics. 36:125–131. 2009.PubMed/NCBI View Article : Google Scholar

16 

Bohr VA, Stevnsner T and de Souza-Pinto NC: Mitochondrial DNA repair of oxidative damage in mammalian cells. Gene. 286:127–134. 2002.PubMed/NCBI View Article : Google Scholar

17 

Pagano G, Talamanca AA, Castello G, Cordero MD, d'Ischia M, Gadaleta MN, Pallardó FV, Petrović S, Tiano L and Zatterale A: Oxidative stress and mitochondrial dysfunction across broad-ranging pathologies: Toward mitochondria-targeted clinical strategies. Oxid Med Cell Longev. 2014(541230)2014.PubMed/NCBI View Article : Google Scholar

18 

Liu CS, Tsai CS, Kuo CL, Chen HW, Lii CK, Ma YS and Wei YH: Oxidative stress-related alteration of the copy number of mitochondrial DNA in human leukocytes. Free Radic Res. 37:1307–1317. 2003.PubMed/NCBI View Article : Google Scholar

19 

Taylor RW and Turnbull DM: Mitochondrial DNA mutations in human disease. Nat Rev Genet. 6:389–402. 2005.PubMed/NCBI View Article : Google Scholar

20 

Filograna R, Mennuni M, Alsina D and Larsson NG: Mitochondrial DNA copy number in human disease: The more the better? FEBS Lett. 595:976–1002. 2021.PubMed/NCBI View Article : Google Scholar

21 

Harty LC, Biniecka M, O'Sullivan J, Fox E, Mulhall K, Veale DJ and Fearon U: Mitochondrial mutagenesis correlates with the local inflammatory environment in arthritis. Ann Rheum Dis. 71:582–588. 2012.PubMed/NCBI View Article : Google Scholar

22 

Zhang W, Cui H and Wong LJ: Comprehensive one-step molecular analyses of mitochondrial genome by massively parallel sequencing. Clin Chem. 58:1322–1331. 2012.PubMed/NCBI View Article : Google Scholar

23 

Taylor W, Gladman D, Helliwell P, Marchesoni A, Mease P and Mielants H: CASPAR Study Group. Classification criteria for psoriatic arthritis: Development of new criteria from a large international study. Arthritis Rheum. 54:2665–2673. 2006.PubMed/NCBI View Article : Google Scholar

24 

Alwehaidah MS, AlFadhli S and Al-Kafaji G: Leukocyte mitochondrial DNA copy number is a potential non-invasive biomarker for psoriasis. PLoS One. 17(e0270714)2022.PubMed/NCBI View Article : Google Scholar

25 

Alwehaidah MS, Al-Kafaji G, Bakhiet M and Alfadhli S: Next-generation sequencing of the whole mitochondrial genome identifies novel and common variants in patients with psoriasis, type 2 diabetes mellitus and psoriasis with comorbid type 2 diabetes mellitus. Biomed Rep. 14(41)2021.PubMed/NCBI View Article : Google Scholar

26 

Bandelt HJ, Kloss-Brandstatter A, Richards MB, Yao YG and Logan I: The case for the continuing use of the revised Cambridge reference sequence (rCRS) and the standardization of notation in human mitochondrial DNA studies. J Hum Genet. 59:66–77. 2014.PubMed/NCBI View Article : Google Scholar

27 

Dong C, Wei P, Jian X, Gibbs R, Boerwinkle E, Wang K and Liu X: Comparison and integration of deleteriousness prediction methods for nonsynonymous SNVs in whole exome sequencing studies. Hum Mol Genet. 24:2125–2137. 2015.PubMed/NCBI View Article : Google Scholar

28 

Gonzalez-Perez A and Lopez-Bigas N: Improving the assessment of the outcome of nonsynonymous SNVs with a consensus deleteriousness score, Condel. Am J Hum Genet. 88:440–449. 2011.PubMed/NCBI View Article : Google Scholar

29 

Choi Y and Chan AP: PROVEAN web server: A tool to predict the functional effect of amino acid substitutions and indels. Bioinformatics. 31:2745–2747. 2015.PubMed/NCBI View Article : Google Scholar

30 

Pandurangan AP, Ochoa-Montano B, Ascher DB and Blundell TL: SDM: A server for predicting effects of mutations on protein stability. Nucleic Acids Res. 45:W229–W235. 2017.PubMed/NCBI View Article : Google Scholar

31 

Livak KJ and Schmittgen TD: Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) method. Methods. 25:402–408. 2001.PubMed/NCBI View Article : Google Scholar

32 

Lin PH, Lee SH, Su CP and Wei YH: Oxidative damage to mitochondrial DNA in atrial muscle of patients with atrial fibrillation. Free Radic Biol Med. 35:1310–1318. 2003.PubMed/NCBI View Article : Google Scholar

33 

Movassaghi S, Jafari S, Falahati K, Ataei M, Sanati MH and Jadali Z: Quantification of mitochondrial DNA damage and copy number in circulating blood of patients with systemic sclerosis by a qPCR-based assay. An Bras Dermatol. 95:314–319. 2020.PubMed/NCBI View Article : Google Scholar

34 

Suissa S, Wang Z, Poole J, Wittkopp S, Feder J, Shutt TE, Wallace DC, Shadel GS and Mishmar D: Ancient mtDNA genetic variants modulate mtDNA transcription and replication. PLoS Genet. 5(e1000474)2009.PubMed/NCBI View Article : Google Scholar

35 

Fan W, Waymire KG, Narula N, Li P, Rocher C, Coskun PE, Vannan MA, Narula J, Macgregor GR and Wallace DCA: mouse model of mitochondrial disease reveals germline selection against severe mtDNA mutations. Science. 319:958–962. 2008.PubMed/NCBI View Article : Google Scholar

36 

Komar AA: Genetics. SNPs, silent but not invisible. Science. 315:466–467. 2007.PubMed/NCBI View Article : Google Scholar

37 

Shabalina SA, Spiridonov NA and Kashina A: Sounds of silence: Synonymous nucleotides as a key to biological regulation and complexity. Nucleic Acids Res. 41:2073–2094. 2013.PubMed/NCBI View Article : Google Scholar

38 

Kimchi-Sarfaty C, Oh JM, Kim IW, Sauna ZE, Calcagno AM, Ambudkar SV and Gottesman MM: A ‘silent’ polymorphism in the MDR1 gene changes substrate specificity. Science. 315:525–528. 2007.PubMed/NCBI View Article : Google Scholar

39 

Du J, Yu S, Wang D, Chen S, Chen S, Zheng Y, Wang N, Chen S, Li J and Shen B: Germline and somatic mtDNA mutation spectrum of rheumatoid arthritis patients in the Taizhou area, China. Rheumatology (Oxford). 59:2982–2991. 2020.PubMed/NCBI View Article : Google Scholar

40 

Schaefer C and Rost B: Predict impact of single amino acid change upon protein structure. BMC Genomics. 13 (Suppl 4)(S4)2012.PubMed/NCBI View Article : Google Scholar

41 

Kauzmann W: Some factors in the interpretation of protein denaturation. Adv Protein Chem. 14:1–63. 1959.PubMed/NCBI View Article : Google Scholar

42 

Aznauryan M, Nettels D, Holla A, Hofmann H and Schuler B: Single-molecule spectroscopy of cold denaturation and the temperature-induced collapse of unfolded proteins. J Am Chem Soc. 135:14040–14043. 2013.PubMed/NCBI View Article : Google Scholar

43 

Karamitros CS, Murray K, Winemiller B, Lamb C, Stone EM, D'Arcy S, Johnson KA and Georgiou G: Leveraging intrinsic flexibility to engineer enhanced enzyme catalytic activity. Proc Natl Acad Sci USA. 119(e2118979119)2022.PubMed/NCBI View Article : Google Scholar

44 

Counago R, Wilson CJ, Pena MI, Wittung-Stafshede P and Shamoo Y: An adaptive mutation in adenylate kinase that increases organismal fitness is linked to stability-activity trade-offs. Protein Eng Des Sel. 21:19–27. 2008.PubMed/NCBI View Article : Google Scholar

45 

Jaenicke R: Protein stability and molecular adaptation to extreme conditions. Eur J Biochem. 202:715–728. 1991.PubMed/NCBI View Article : Google Scholar

46 

DePristo MA, Weinreich DM and Hartl DL: Missense meanderings in sequence space: A biophysical view of protein evolution. Nat Rev Genet. 6:678–687. 2005.PubMed/NCBI View Article : Google Scholar

47 

Bjorklund P, Lindberg D, Akerstrom G and Westin G: Stabilizing mutation of CTNNB1/beta-catenin and protein accumulation analyzed in a large series of parathyroid tumors of Swedish patients. Mol Cancer. 7(53)2008.PubMed/NCBI View Article : Google Scholar

48 

Song W, Patel A, Qureshi HY, Han D, Schipper HM and Paudel HK: The Parkinson disease-associated A30P mutation stabilizes alpha-synuclein against proteasomal degradation triggered by heme oxygenase-1 over-expression in human neuroblastoma cells. J Neurochem. 110:719–733. 2009.PubMed/NCBI View Article : Google Scholar

49 

Hirst J, King MS and Pryde KR: The production of reactive oxygen species by complex I. Biochem Soc Trans. 36:976–980. 2008.PubMed/NCBI View Article : Google Scholar

50 

Murphy MP: How mitochondria produce reactive oxygen species. Biochem J. 417:1–13. 2009.PubMed/NCBI View Article : Google Scholar

51 

Malfatti E, Bugiani M, Invernizzi F, de Souza CF, Farina L, Carrara F, Lamantea E, Antozzi C, Confalonieri P, Sanseverino MT, et al: Novel mutations of ND genes in complex I deficiency associated with mitochondrial encephalopathy. Brain. 130:1894–1904. 2007.PubMed/NCBI View Article : Google Scholar

52 

Rodenburg RJ: Mitochondrial complex I-linked disease. Biochim Biophys Acta. 1857:938–945. 2016.PubMed/NCBI View Article : Google Scholar

53 

Hofhaus G and Attardi G: Lack of assembly of mitochondrial DNA-encoded subunits of respiratory NADH dehydrogenase and loss of enzyme activity in a human cell mutant lacking the mitochondrial ND4 gene product. EMBO J. 12:3043–3048. 1993.PubMed/NCBI View Article : Google Scholar

54 

Bai Y and Attardi G: The mtDNA-encoded ND6 subunit of mitochondrial NADH dehydrogenase is essential for the assembly of the membrane arm and the respiratory function of the enzyme. EMBO J. 17:4848–4858. 1998.PubMed/NCBI View Article : Google Scholar

55 

Bai Y, Hu P, Park JS, Deng JH, Song X, Chomyn A, Yagi T and Attardi G: Genetic and functional analysis of mitochondrial DNA-encoded complex I genes. Ann N Y Acad Sci. 1011:272–283. 2004.PubMed/NCBI View Article : Google Scholar

56 

Muller FL, Liu Y and Van Remmen H: Complex III releases superoxide to both sides of the inner mitochondrial membrane. J Biol Chem. 279:49064–49073. 2004.PubMed/NCBI View Article : Google Scholar

57 

Bleier L and Drose S: Superoxide generation by complex III: From mechanistic rationales to functional consequences. Biochim Biophys Acta. 1827:1320–1331. 2013.PubMed/NCBI View Article : Google Scholar

58 

Keightley JA, Anitori R, Burton MD, Quan F, Buist NR and Kennaway NG: Mitochondrial encephalomyopathy and complex III deficiency associated with a stop-codon mutation in the cytochrome b gene. Am J Hum Genet. 67:1400–1410. 2000.PubMed/NCBI View Article : Google Scholar

59 

Carossa V, Ghelli A, Tropeano CV, Valentino ML, Iommarini L, Maresca A, Caporali L, La Morgia C, Liguori R, Barboni P, et al: A novel in-frame 18-bp microdeletion in MT-CYB causes a multisystem disorder with prominent exercise intolerance. Hum Mutat. 35:954–958. 2014.PubMed/NCBI View Article : Google Scholar

60 

Emmanuele V, Sotiriou E, Rios PG, Ganesh J, Ichord R, Foley AR, Akman HO and Dimauro S: A novel mutation in the mitochondrial DNA cytochrome b gene (MTCYB) in a patient with mitochondrial encephalomyopathy, lactic acidosis, and strokelike episodes syndrome. J Child Neurol. 28:236–242. 2013.PubMed/NCBI View Article : Google Scholar

61 

Amaral-Fernandes MS, Marcondes AM, do Amor Divino Miranda PM, Maciel-Guerra AT and Sartorato EL: Mutations for Leber hereditary optic neuropathy in patients with alcohol and tobacco optic neuropathy. Mol Vis. 17:3175–3179. 2011.PubMed/NCBI

62 

Li Y, Park JS, Deng JH and Bai Y: Cytochrome c oxidase subunit IV is essential for assembly and respiratory function of the enzyme complex. J Bioenerg Biomembr. 38:283–291. 2006.PubMed/NCBI View Article : Google Scholar

63 

Jonckheere AI, Smeitink JA and Rodenburg RJ: Mitochondrial ATP synthase: Architecture, function and pathology. J Inherit Metab Dis. 35:211–225. 2012.PubMed/NCBI View Article : Google Scholar

64 

Dautant A, Meier T, Hahn A, Tribouillard-Tanvier D, di Rago JP and Kucharczyk R: ATP synthase diseases of mitochondrial genetic origin. Front Physiol. 9(329)2018.PubMed/NCBI View Article : Google Scholar

65 

Coto-Segura P, Santos-Juanes J, Gomez J, Alvarez V, Díaz M, Alonso B, Corao AI and Coto E: Common European mitochondrial haplogroups in the risk for psoriasis and psoriatic arthritis. Genet Test Mol Biomarkers. 16:621–623. 2012.PubMed/NCBI View Article : Google Scholar

66 

Gomes TM, Ng YS, Pickett SJ, Turnbull DM and Vincent AE: Mitochondrial DNA disorders: From pathogenic variants to preventing transmission. Hum Mol Genet. 30:R245–R253. 2021.PubMed/NCBI View Article : Google Scholar

67 

Negishi Y, Hattori A, Takeshita E, Sakai C, Ando N, Ito T, Goto Y and Saitoh S: Homoplasmy of a mitochondrial 3697G>A mutation causes Leigh syndrome. J Hum Genet. 59:405–407. 2014.PubMed/NCBI View Article : Google Scholar

68 

Al-Kafaji G, Alharbi MA, Alkandari H, Salem AH and Bakhiet M: Analysis of the entire mitochondrial genome reveals Leber's hereditary optic neuropathy mitochondrial DNA mutations in an Arab cohort with multiple sclerosis. Sci Rep. 12(11099)2022.PubMed/NCBI View Article : Google Scholar

69 

Crispim D, Estivalet AAF, Roisenberg I, Gross JL and Canani LH: Prevalence of 15 mitochondrial DNA mutations among type 2 diabetic patients with or without clinical characteristics of maternally inherited diabetes and deafness. Arq Bras Endocrinol Metabol. 52:1228–1235. 2008.PubMed/NCBI View Article : Google Scholar

70 

Keogh MJ and Chinnery PF: Mitochondrial DNA mutations in neurodegeneration. Biochim Biophys Acta. 1847:1401–1411. 2015.PubMed/NCBI View Article : Google Scholar

71 

Zhan D, Tanavalee A, Tantavisut S, Ngarmukos S, Edwards SW and Honsawek S: Relationships between blood leukocyte mitochondrial DNA copy number and inflammatory cytokines in knee osteoarthritis. J Zhejiang Univ Sci B. 21:42–52. 2020.PubMed/NCBI View Article : Google Scholar

72 

Al-Kafaji G, Bakheit HF, Alharbi MA, Farahat AA, Jailani M, Ebrahin BH and Bakhiet M: Mitochondrial DNA copy number in peripheral blood as a potential non-invasive biomarker for multiple sclerosis. Neuromolecular Med. 22:304–313. 2020.PubMed/NCBI View Article : Google Scholar

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Spandidos Publications style
Alwehaidah MS, Alsabbagh M and Al-Kafaji G: Comprehensive analysis of mitochondrial DNA variants, mitochondrial DNA copy number and oxidative damage in psoriatic arthritis. Biomed Rep 19: 85, 2023
APA
Alwehaidah, M.S., Alsabbagh, M., & Al-Kafaji, G. (2023). Comprehensive analysis of mitochondrial DNA variants, mitochondrial DNA copy number and oxidative damage in psoriatic arthritis. Biomedical Reports, 19, 85. https://doi.org/10.3892/br.2023.1667
MLA
Alwehaidah, M. S., Alsabbagh, M., Al-Kafaji, G."Comprehensive analysis of mitochondrial DNA variants, mitochondrial DNA copy number and oxidative damage in psoriatic arthritis". Biomedical Reports 19.5 (2023): 85.
Chicago
Alwehaidah, M. S., Alsabbagh, M., Al-Kafaji, G."Comprehensive analysis of mitochondrial DNA variants, mitochondrial DNA copy number and oxidative damage in psoriatic arthritis". Biomedical Reports 19, no. 5 (2023): 85. https://doi.org/10.3892/br.2023.1667