Development of a New Technique for Quantifying Mitochondrial DNA in Single Muscle Fibers

Mitochondrial diseases (MDs) are the most common metabolic disorders. Due to their great clinical and genetic heterogeneity, their diagnosis relies exclusively on the identification of pathogenic variants in nuclear genes or in mitochondrial DNA (mtDNA). However, to date, 50% of affected patients remain without a definitive diagnosis. The advent of next-generation sequencing (NGS) has improved diagnostic yield, but many identified variants remain of uncertain significance (VUS), preventing a definitive diagnosis. The clinical interpretation of these newly identified rare variants therefore represents a major challenge.

In the context of MDs, one of the major criteria for mtDNA variant pathogenicity is a good correlation between heteroplasmy level and tissue or cellular involvement. Heteroplasmy refers to the coexistence, within the same cell or tissue, of mutated and non-mutated mtDNA molecules. Pathogenic mtDNA variants are most often heteroplasmic, with the most affected tissues harboring a higher proportion of mutated mtDNA. In muscle biopsies from patients with MDs, muscle fibers may show a cytochrome c oxidase (COX) enzymatic deficiency (COX-negative fibers), reflecting dysfunction of the mitochondrial respiratory chain (MRC). Single-fiber analysis makes it possible to isolate muscle fibers by LASER microdissection and to quantify the heteroplasmy level of a variant within them. The presence of a high heteroplasmy level in COX-negative fibers, in contrast to fibers without deficiency (COX-positive fibers), is strong evidence supporting the pathogenicity of the variant. In previous projects, we tested two variant quantification techniques (PCR-RFLP and NGS), but these methods remain too labor-intensive or costly and are therefore difficult to maintain in routine practice.

This pilot study aims to develop a new method for quantifying heteroplasmy levels using digital PCR. Faster and less expensive, this approach could simplify technical implementation and reduce analysis costs, thereby facilitating its integration into clinical practice. Initially, a feasibility study will begin with validation of digital PCR on DNA extracted from blood samples of two patients carrying pathogenic variants identified in a previous study (AOI 2017 IDRCB: 2017-A00688-45). This validation will compare digital PCR with the PCR-RFLP method for heteroplasmy quantification and assess the reliability and reproducibility of the technique. Once validation is achieved, digital PCR will be tested on DNA extracted from microdissected muscle fibers from the same patients to evaluate its feasibility at the single-fiber level, with comparison to PCR-RFLP results. If feasibility at the single-fiber level is confirmed, the method will then be tested in four new patients from the Mitochondrial Diseases Reference Center, in whom variants of uncertain significance have been identified and for whom muscle biopsies with COX-negative fibers are available. Additional samples (blood, urine, and buccal swabs) will be collected to assess heteroplasmy levels across different tissues. If validated, this technique could be applied to a larger number of patients and integrated into the diagnostic strategy for mitochondrial diseases.

Moreover, digital PCR could also be used to quantify mtDNA copy number, an essential biomarker for monitoring patients with MDs. To this end, mtDNA is partitioned into thousands of nanowells, and absolute quantification is obtained by counting fluorescent signals emitted by positive partitions, with a nuclear DNA probe serving as an internal control. This validation will be performed using the same blood samples and muscle fibers, by comparing digital PCR results with those obtained using the reference method, quantitative PCR (qPCR).

The primary objective of this study is to reduce diagnostic odysseys by simplifying existing methods. In addition, the application of digital PCR to quantify mtDNA copy number could offer new perspectives, particularly as a biomarker for patient monitoring and the development of clinical trials.