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Sulaiman et al. J Transl Genet Genom 2020;4:159-87 I https://doi.org/10.20517/jtgg.2020.27 Page 177

CHALLENGES IN DIAGNOSING MITOCHONDRIAL DISEASES
Even though quite significant publications of disease-causing mutations are available, challenges remain on
how to improve the diagnosis of these mitochondrial diseases in clinical settings, as the rate of detection
for disease-causing mutations is only 25%-50% of cases [180,184,192] . Most of the diagnosis approaches are using
the NGS technologies, in which the first step is to use the WES approach, followed by a muscle biopsy if
more confirmation is needed for the pathogenicity [180] . Various reasons can explain the failure to detect
mtDNA mutations in some patients, such as the existence of the difficult-to-detect mutations, including the
recurrent de novo mutations [233] , splice site defects, mutations in deep intronic or repeated sequences, and
others [180,184,192] . One way to address such limitation is to use trio sequencing of parents and child to allow
for accurate detections of these difficult-to-detect mutations, as used by the Deciphering Developmental
Disorders Project [234] , and the Genomics England 100,000 Genomes (100K) Project [235] .

With the problems of heteroplasmic mtDNA mutations, many recommend that sequencing of muscle DNA
is needed to complement the WES findings, especially with the low mutant load. Since most patients with
mitochondrial diseases are usually carrying a mixture of wild-type and mutated mtDNA (heteroplasmic),
their clinical manifestations of the disease also depend on the ratio of the mutated to wild-type mtDNA [236] .
Some of these low-frequency heteroplasmy variants can turn into deleterious high heteroplasmy variants [237] ,
and could thereby further complicate the diagnosis. Integrated analysis of the omics can also help to improve
the diagnosis, as multiple omic findings could verify the accuracy of the results. An example is a cohort study
of adult mitochondrial disease patients with the mtDNA mutation m.3243 A à G, in which the combined
analysis of proteomics and metabolomics of their urine samples showed very distinct alterations in lysosomal
proteins, calcium-binding proteins, and antioxidant defenses [238] . Importantly, these changes were evident
in the asymptomatic carriers of m.3243A>G [238] , therefore suggesting the plausibility of a new and early
screening strategy of this type of mutation in the patients and their families.

Another issue is the presence of the NUMTs that could interfere with WES or WGS data interpretation
and analysis [194] . The indirect method using the WES/WGS data to identify the mitochondrial mutations
is a favorable approach due to its cost-effectiveness and high reproducibility. However, the presence of the
NUMTs gives some ambiguity to the results [184,191] . Thus, some studies have opted for an addition of the
mitochondrial isolation step in the workflow before RNA extraction and sequencing steps to eliminate
the NUMTs. However, the resources used are enormous and labor-intensive [191] . Similarly, the proteomic
approach for the mitochondrial study also faces the challenges of getting pure mitochondrial proteins [208] .
To enrich these mitochondria, many methods have been developed, including the mechanical or chemical
disruption method, the differential centrifugation method, and recently introduced magnetic device
method [239-241] . However, mitochondrial proteins have dynamic ranges; thus, the samples usually undergo
fractionation to reduce their complexity before the analysis [208] , which could increase the cost and time
spent for each additional procedure. Most studies use sodium dodecyl sulfate (SDS) polyacrylamide gel
electrophoresis (PAGE), and gel slicing to separate the proteins, followed by high-performance LC-MS
analysis [208,239,242-244] . Despite the vast potential of these proteomic applications to diagnose mitochondrial
disease, the problems lie within the diversity and tissue-specific expression of these mitochondrial proteins.
Currently, only indirect measurements are available to detect them [208] . Moreover, the lack of methods to
differentiate between the mitochondrial and cytoplasmic functions of these proteins [208] also contribute to
the problems. In addition, there are also the issues of technical expertise to use the proteome interactome
analysis tools, and the expensive cost to run the comprehensive proteome profiling [208] . Therefore, innovative
approaches and advancement of the proteomic applications in the future are needed to solve these issues,
and hopefully to increase the potential of these proteomic applications in diagnosing mitochondrial diseases.

Another improvement for the diagnosis of mitochondrial disease using the genetic data is to perform
periodic reanalysis of WES/WGS data of the patients, using various or newly improved bioinformatic