Cyclin C nuclear release and mitochondrial dysfunction define molecular signatures of MED13L syndrome

Alicia N Campbell; Kendall N Jung; Steven J Doyle; Ekaterina Lebayle; Barbara Corneo; Joanna Feng; Christopher L Ricupero; Jennifer M Bain; Randy Strich

doi:10.1016/j.xhgg.2026.100670

. 2026 Sep 4;7(4):100670. doi: 10.1016/j.xhgg.2026.100670

Cyclin C nuclear release and mitochondrial dysfunction define molecular signatures of MED13L syndrome

Alicia N Campbell ^1,^6,^∗, Kendall N Jung ¹, Steven J Doyle ², Ekaterina Lebayle ³, Barbara Corneo ³, Joanna Feng ⁴, Christopher L Ricupero ⁵, Jennifer M Bain ⁴, Randy Strich ^1,^∗∗

PMCID: PMC13629333 PMID: 42698208

Summary

The mediator kinase module (MKM) coordinates transcriptional programs regulating cellular metabolism, stress responses, and differentiation. Heterozygous variants of MED13L, a core MKM component, cause a neurodevelopmental disorder characterized by variable intellectual disability, developmental delay, hypotonia and motor impairment, and congenital anomalies. However, the molecular basis underlying this clinical heterogeneity is poorly defined. Previously, we identified mitochondrial dysfunction and aberrant nuclear release of another MKM component, cyclin C (CCNC), in a single fibroblast line derived from an individual with MED13L syndrome. Here, we expand these studies across 12 fibroblast lines derived from individuals with 11 distinct MED13L variants. We identify mitochondrial dysfunction as a consistent feature of MED13L variation, characterized by reduced mitochondrial ATP production, decreased mitochondrial DNA abundance, elevated reactive oxygen species, and impaired transcription of genes involved in mitochondrial biogenesis. In parallel, all variant lines exhibit aberrant cytoplasmic CCNC localization, consistent with its established role in mitochondrial fission. Longitudinal analyses further reveal progressive declines in mitochondrial function along with markers associated with premature cellular aging. Importantly, the severity of mitochondrial dysfunction shows an association with variant position within MED13L and with clinical functional measures, suggesting that mutation location may partially predict disease severity. Together, these findings establish mitochondrial dysfunction as a consistent cellular feature of MED13L heterozygosity and identify CCNC mislocalization as a candidate biomarker of MKM disruption. More broadly, this work reveals an intersection between transcriptional control and mitochondrial homeostasis in MED13L syndrome, forming the framework for biomarker-driven therapeutic development in MED13L-associated and related neurodevelopmental disorders.

Keywords: MED13L syndrome, neurodevelopmental disorder, mitochondrial dysfunction, mediator kinase module, cyclin C, genotype-phenotype correlation

Campbell et al. demonstrate that MED13L variants disrupt mitochondrial function in patient-derived fibroblasts, with altered cyclin C localization, impaired mitochondrial energetics, and increased cellular senescence. Variant position influences mitochondrial dysfunction, which is associated with clinical motor severity, linking MED13L genotype to cellular and functional phenotypes.

Introduction

MED13L syndrome is a rare neurodevelopmental disorder characterized by global developmental delay, hypotonia, congenital heart defects, seizures, and variable intellectual disability¹^,²^,³^,⁴ (MED13L syndrome, MIM: 616789; MED13L, MIM: 608771). Despite increasing identification of pathogenic variants in MED13L through clinical sequencing, substantial clinical heterogeneity remains, even among individuals with similar mutations.⁴^,⁵ This variability has complicated efforts to define disease mechanisms and has limited the development of targeted therapies.

MED13L encodes a core structural component of the mediator kinase module (MKM), which also includes its paralog MED13, CDK8 or CDK19, cyclin C (CCNC), and MED12 or MED12L.⁶^,⁷^,⁸ The MKM acts as a regulatory center that integrates transcriptional control with cellular stress responses and differentiation cues, enabling rapid transcriptional reprogramming during developmental transitions and metabolic adaptation.⁸^,⁹^,¹⁰^,¹¹^,¹² Beyond its canonical nuclear role, emerging evidence suggests that MKM activity is linked to mitochondrial regulation through stimulus-dependent re-localization of CCNC.¹³^,¹⁴^,¹⁵^,¹⁶ Under mitochondrial or oxidative stress, a portion of CCNC translocates from the nucleus to the cytosol, where it promotes mitochondrial fission, thereby coupling transcriptional reprogramming to organelle quality control.¹⁴^,¹⁶^,¹⁷ Disruption of this coordinated signaling axis has the potential to impair both nuclear transcriptional programs and mitochondrial homeostasis.

Our previous study of MED13L disruption identified transcriptional dysregulation and mitochondrial abnormalities in limited cellular models.¹⁵ Previous RNA sequencing (RNA-seq) analyses from Ccnc^−/− mouse embryonic fibroblasts (MEFs) identified a transcriptional network governing mitochondrial maintenance, including genes involved in mitochondrial biogenesis, transcription, and nuclease activity.¹⁸^,¹⁹ However, these findings have been derived from small cohorts, and it remains unclear whether mitochondrial dysfunction represents a consistent and defining feature of MED13L syndrome or reflects variant-specific effects.

Importantly, while clinical reports have described metabolic abnormalities in individuals with MED13L syndrome, including elevated lactate, reduced exercise tolerance, and features suggestive of altered bioenergetic regulation, systematic cellular phenotyping across diverse genotypes has not been performed.⁵^,²⁰^,²¹^,²²^,²³ Establishing whether mitochondrial dysfunction represents a consistent and distinguishing cellular feature of MED13L dysfunction would provide critical mechanistic insight and could enable the development of cellular biomarkers for diagnosis and treatment monitoring. Moreover, whether such defects represent static abnormalities or progressive vulnerability has not been examined.

Here, we examine a panel of fibroblasts derived from individuals with heterozygous deletion, nonsense, frameshift, and missense variants in MED13L to investigate shared cellular features. We identify mitochondrial dysfunction as a reproducible phenotype characterized by impaired ATP production, reduced mitochondrial DNA (mtDNA) content, elevated oxidative stress, and altered transcriptional programs governing mitochondrial maintenance. In parallel, we observe aberrant cytoplasmic CCNC localization across variant fibroblast lines, suggesting disruption of MKM-associated signaling. In addition, we observed premature acquisition of senescence-associated phenotypes. Together, these findings implicate mitochondrial dysfunction as a cellular feature of MED13L variation and nominate CCNC mislocalization as a candidate cellular biomarker of MKM disruption and mitochondrial stress. This work establishes a functional link between mediator-associated transcriptional regulation and mitochondrial dynamics, thus expanding the conceptual framework for MED13L syndrome pathophysiology.

Material and methods

Human subjects and fibroblast biopsies

Consent was granted according to institutional review board (IRB) protocols (IRB #AAR7203, Columbia University Irving Medical Center), and procedures were followed in accordance with institutional and national ethical standards. Individuals ranged in age from 60 to 262 months and included seven males and five females. At the time of collection, clinical severity metrics, including Gross Motor Function Classification System (GMFCS) scores, were collected, with scores ranging from 1 to 5 where available.²⁴ Primary human dermal fibroblasts (HDFn) were purchased from ATCC (PCS-201-010) and were used as the control for all experiments. All individuals carried heterozygous pathogenic or likely pathogenic variants in MED13L and included missense, frameshift, nonsense, and exon-deletion alleles annotated from clinical genomic analysis, as determined by prior clinical genetic reports. The fibroblast cultures used in this study were not independently sequenced to confirm the reported MED13L variants. Additionally, investigators were blinded to genotype throughout the experiments. Variant protein domain classifications (intrinsically disordered region [IDR], N-terminal, C-terminal, and medPIWI) were ascribed based on UniProt functional domains (MED13L_Human #Q71F56). MED13L syndrome (MIM: 616789; ICD-10-CM Q87.85) was diagnosed in individuals with a pathogenic or likely pathogenic heterozygous mutation in the MED13L gene (MIM: 608771), located on chromosome 12q24.21. Detailed demographic and molecular information for each fibroblast line, including sex, age at skin biopsy collection, and variant annotation, is provided in Table S1.

Primary dermal fibroblasts were obtained from individuals diagnosed with MED13L syndrome through institutional biobanking protocols at Columbia University Irving Medical Center, Stem Cell Initiative. Detailed protocols can be found in Iannello et al.²⁵ Briefly, fibroblast medium was prepared containing Dulbecco’s modified Eagle’s medium (DMEM) high glucose (Life Technologies, 11960077), 10% heat-inactivated fetal bovine serum (FBS) (Life Technologies, 10082147), 1× penicillin-streptomycin (Life Technologies, 15140122), 1× L-glutamine (Life Technologies, 25030081), and 1× sodium pyruvate (Life Technologies, 11360070) and sterile filtered. Biopsies were collected on either the inner upper arm or lateral upper thigh. An ∼3-mm biopsy was collected and placed in prewarmed fibroblast medium.

One well of a 6-well tissue culture dish was treated with 0.1% gelatin (Millipore Sigma, SF008) for 30 min at 37° and 5% CO₂. Gelatin coating was aspirated, and biopsy was added to the well. The biopsy was pinned to the culture dish using a 30G needle. Warmed fibroblast medium was added to the well, and the lid was replaced. The plate was transferred to standard cell culture conditions with fibroblast medium replaced every 3–4 days.

Culturing dermal fibroblasts

Culturing of initial fibroblasts was completed by the CUIMC Stem Cell Initiative and based on a published protocol.²⁵ Briefly, once the initial fibroblast layer was fully confluent, the medium was aspirated, and additional culturing dishes were prepared with gelatin as before. Cells were washed with 1× DPBS (Corning, MT-21-030-CV). Cells were then released from the dish using 0.25% trypsin-EDTA (Life Technologies, 25200072) and incubated for 2 min at 37°. Trypsin was quenched with fibroblast medium (see protocol above) and resuspended using a pipette. Cells were collected in 15 mL tubes, and an additional 10 mL medium was added before centrifugation for 5 min at 300 × g and room temperature (RT). The supernatant was aspirated, and the cell pellet was resuspended in 1 mL medium, followed by an additional 11 mL. The cell suspension was dispersed across 12-well plates and cultured under conditions previously described.

Characterization of dermal fibroblasts grown from skin biopsy

The fibroblasts were routinely tested for the absence of mycoplasma contamination using a PCR-based kit (e-Myco plus, Intron, 25234). For cell characterization and staining, cells were washed with 1× DPBS (Corning, MT-21-030-CV) and fixed with 4% PFA (Santa Cruz, sc-281692) for 10 min at RT. Cells were washed once more, then permeabilized with 0.1% Triton X-100 (Thermo Fisher Scientific, 85111) in 1× PBS. Cells were blocked with protein blocking buffer (Agilent, ×0909) for 30 min at RT. Cells were stained with appropriate primary and secondary antibodies (see previous publication for full antibody list, dilutions, and manufacturers). Cells were analyzed using fluorescence microscopy.

General cell culture

Fibroblasts were maintained in DMEM (Corning, MT10013CV) supplemented with 10% FBS (Avantor, MP1300500) and 1% penicillin/streptomycin (HyClone, 16777-164) at 37°C and 5% CO₂. Media were replenished every 48–72 h, and cells were passaged using 0.25% Trypsin-EDTA (Gibco, 25-200-114) when they reached ∼80%–90% confluency. Unless otherwise indicated for longitudinal serial-passage experiments, assays were performed using low- to mid-passage fibroblasts (generations 10–35).

Variant annotation and classification

Transcript annotations were based on NM_015335.5. Frameshift variants were annotated by incorporating the number of altered nucleotides and predicted downstream translation distance using NMDetective conventions.²⁶ Missense variants were independently classified using MutPred-LOF.²⁷ Exon-level deletion variants were classified based on predicted effects on transcript structure and translation. Deletions involving one or two consecutive exons were designated small exon deletions; those spanning three or more exons were designated large exon deletions. Deletion variants were evaluated for predicted transcript stability and proximity to the terminal exon junction rather than the predicted reading frame alone. The large exon 3–25 deletion removes the majority of the coding region and was therefore considered a severe truncating allele, and its precise transcript fate could not be confidently determined. Protein domains were based on known structural regions, as annotated in UniProt (MED13L_Human Q71F56). In the map provided, frameshift, missense, and nonsense mutations are indicated on top of the map, while the deletions are shown below. The solid line for the deletions represents the actual missing DNA, while the dotted line indicates the predicted truncation of the remainder of the protein due to the mutation.

RNA isolation and quantitative PCR

Total RNA was extracted using column-based purification with on-column DNase digestion (NEB, 103529-148). cDNA was synthesized using a kit (Thermo Fisher Scientific, FERK1642). Quantitative PCR (qPCR) was performed using SYBR green (Applied Biosystems, 4368702) and a machine (Applied Biosystems, 43-766-00). Gene expression was normalized to the housekeeping gene GAPDH and calculated using the ΔΔC_t method.²⁸ Transcript abundance was expressed as log₂ fold change relative to pooled control fibroblasts. Target gene primers can be found in Table S2.

Immunofluorescence microscopy

Cells were seeded on glass coverslips and grown overnight. The following day, cells were stained with MitoTracker Red (Invitrogen, M7512) and fixed with 4% paraformaldehyde. Permeabilization was performed using 0.2% Triton X-100, followed by blocking in serum-based buffer (Licor, NC1660556). Primary antibodies were added and incubated overnight at 4°C. Antibodies included double-stranded DNA (dsDNA) (DSHB, AB10805293) and CCNC (CST, 68179). Fluorophore-conjugated secondary antibody goat anti-rabbit IgG or goat anti-mouse IgG was applied the next day following washing (Invitrogen, A11008; Invitrogen, A32723). Nuclei were labeled with a mountant containing DAPI. Images were acquired using fluorescence microscopy at identical exposure settings for all conditions on a Keyence BZ-X 710 Inverted Fluorescence Microscope.

Quantification of mitochondrial fragmentation

Mitochondrial morphology was scored blind to genotype and assessed by three separate researchers. Cells were classified as “fragmented” if >50% of the mitochondrial network consisted of punctate or short tubular structures rather than elongated networks. At least 100 cells per cell line were analyzed across replicate experiments, and the percentage of cells exhibiting fragmentation was calculated. See Figure S1 for examples of mitochondrial morphology that were used for quantification purposes.

Seahorse mitochondrial and glycolytic ATP production rate assays

Cellular bioenergetics were quantified using the Seahorse XFe24 or XFp Real-Time ATP Rate Assay. Fibroblasts were seeded into plates at a density of 20,000 cells per well and incubated overnight in standard conditions. On the day of the assay, cells were washed and incubated in Seahorse XF assay medium supplemented with glucose, glutamine, and sodium pyruvate and equilibrated in a non-CO₂ incubator for 45–60 min prior to analysis. Basal oxygen consumption rate (OCR) and proton efflux rate (PER) values were recorded prior to compound injection. Sequential injections were performed according to the manufacturer’s protocol.

Seahorse normalization and quality control

ATP production values were normalized to cell number. Wells containing abnormal OCR/PER traces, loss of adherence, or incomplete drug response were excluded based on Seahorse quality control. Biological replicates represent independently initiated experiments or culture series performed using the same donor-derived fibroblast line, including experiments established from separate cryopreserved vials or independently initiated longitudinal cultures. Technical replicates represent replicate assay wells generated from the same cell preparation. For longitudinal Seahorse experiments, cells from multiple culture wells were pooled at each time point and analyzed in technical duplicate Seahorse wells.

Calculation of mitochondrial and glycolytic ATP production rates

The OCR and extracellular acidification rate (ECAR) values were exported from Wave software and converted to ATP production rates according to Agilent Seahorse Real-Time ATP Rate Assay calculations with plate-specific correction factors. Briefly, ECAR values were first converted to PER by averaging the first three baseline ECAR measurements and applying assay-specific buffer and well volume correction factors. Conversion constants were applied as instructed by the manufacturer and adjusted based on the instrument used (XFp or XFe24). The basal mitochondrial OCR (OCR_basal) was calculated as the average of the first three baseline OCR measurements. Non-mitochondrial respiration was defined as the OCR remaining after rotenone/antimycin A injection and was subtracted from OCR_basal to yield the mitochondrial-derived OCR (mitoOCR). To account for mitochondrial-driven extracellular acidification, mitochondrial PER (mitoPER) was calculated as 0.5× mitoOCR, and this value was subtracted from total PER to obtain glycolytic PER (glycoPER). Glycolytic ATP (glycoATP) production was calculated directly from glycoPER after correction using assay-specific conversion factors. Mitochondrial ATP (mitoATP) production was calculated from the oligomycin-sensitive fraction of respiration. OCR following oligomycin addition was averaged across three time points and subtracted from OCR_basal to determine ATP-linked respiration (OCR_ATP). OCR_ATP values were converted to ATP production rates using manufacturer-provided P/O ratios and plate-specific assay constants. Total ATP production was calculated as the sum of mitoATP and glycoATP production rates. All ATP values were reported as pmol ATP/min and normalized to cell number.

Statistical analysis of longitudinal Seahorse data

To evaluate whether mitoATP production declined progressively with serial passage, time-course Seahorse data were analyzed using nonlinear regression with a straight-line model in GraphPad Prism. For each fibroblast line, mitoATP production values across generations were fit using least-squares regression. Global curve comparison was performed using extra sum-of-squares F-tests to determine whether slopes or y intercepts differed between control and MED13L-variant fibroblasts. Separate comparisons were conducted for slope (rate of change over time) and y intercept (baseline mitoATP). Shared-parameter models were compared against independent fits to assess whether slopes or intercepts were significantly different between datasets.

Senescence-associated β-galactosidase assay

Senescence was evaluated using a fluorogenic β-galactosidase reporter assay (Invitrogen, C10851). Cells were stained according to the manufacturer’s instructions and analyzed with a BD Accuri C6 Plus flow cytometer. Values were analyzed, and background-subtracted fluorescence intensity was calculated for each sample.

BrdU incorporation assay

Cellular proliferation was quantified by bromodeoxyuridine (BrdU) incorporation followed by fluorogenic detection using flow cytometry. MED13L-variant fibroblasts and control fibroblasts were seeded at equivalent densities and grown under standard culture conditions until ∼60%–70% confluency. Cells were pulsed with BrdU (10 μM final concentration) for 24 h to label cells actively undergoing DNA synthesis. Following labeling, cells were washed with PBS, then fixed and permeabilized using 4% paraformaldehyde and 0.2% Triton X-100, respectively. DNA was chemically denatured with 2N HCl, and BrdU was detected using BrdU antibody (Invitrogen, B35130) with overnight incubation at 4°C. BrdU signals were acquired on a BD Accuri C6 Plus flow cytometer as described above. All experiments were performed using at least three independent biological replicates per genotype with technical duplicates.

Cytosolic reactive oxygen species measurement

Cytosolic reactive oxygen species (ROS) was measured using dihydroethidium (DHE), which fluoresces upon oxidation by superoxide. Fibroblasts were seeded into 6-well plates and harvested on the day of the assay according to normal detachment protocol (see above). Cell suspensions were incubated with DHE at 37°C for 20–30 min, protected from light. Cells were then washed and analyzed via flow cytometry. Single-cell suspensions were gated based on forward and side scatter to exclude debris and doublets. Median fluorescence intensity was calculated for each population and normalized to matched control samples included on each run, and background fluorescence was determined by unstained controls.

Mitochondrial ROS measurement

Mitochondrial superoxide production was quantified using MitoSOX Red. Cells were grown in 6-well plates, harvested, and incubated with MitoSOX at 37°C for 30 min protected from light. Cells were washed and analyzed immediately by flow cytometry as described above. All ROS measurements were obtained from a minimum of three independent experiments with several technical replicates within each run.

mtDNA copy number

Total DNA was extracted using Omega Bio-Tek EZNA Tissue DNA Kit (NC0721312). mtDNA copy number was quantified using qPCR with primers targeting mitochondrial gene loci and nuclear reference genes (see Table S2 for primers). Each reaction was run in biological triplicate, with a minimum of two technical duplicates. mtDNA copy number was calculated by normalizing mitochondrial targets to nuclear DNA and expressing values relative to controls.

Clinical and behavioral data collection

Caregiver-reported clinical and behavioral data were obtained from two rare disease research registries: Simons Searchlight and RARE-X. Simons Searchlight is an international natural history and genetics research program that collects standardized phenotypic, behavioral, and developmental information from individuals with rare neurodevelopmental disorders and their caregivers and is sponsored by the Simons Foundation Autism Research Initiative. RARE-X is a patient-driven data collection platform that combines longitudinal clinical and caregiver-reported outcomes across rare disease populations.²⁹ Data from both registries were harmonized to generate unified clinical variables for downstream analyses.

Clinical severity metrics: Composite functional/behavioral scoring

The composite functional/behavioral score utilizes adaptive functioning metrics derived from the Vineland Adaptive Behavior Scales, Third Edition (Vineland-3; VABS-3),³⁰ when available from either registry. Three behavioral domains were incorporated into the composite metric: adaptive behavior composite (ABC), communication, and motor functioning scores. From Simons Searchlight, the Vineland-3 ABC standard score was obtained directly from the ABC standard score field. From RARE-X, the corresponding value was obtained from the vi3_adaptive_composite variable within the Vineland dataset. ABC scores were additionally categorized into severity bins based on current clinical standards: mild (>85), borderline (70–84), or moderate/severe (<70).

To generate the composite metric encompassing all three, each domain score was normalized by Z score standardization using the cohort mean and standard deviation. Communication domain scores were obtained from the Vineland-3 communication domain in either registry and similarly normalized.

Clinical severity metrics: Motor severity score

Motor scores were derived from Vineland-3 gross and fine motor assessments (broad “motor” category) and normalized in the same manner. The final composite functional score was calculated by summing all available normalized domain scores for each individual and dividing by the number of reported domains to account for incomplete datasets or missing variables. Severity thresholds were selected based on conventional interpretation ranges for standardized Vineland-3 domain scores, which are normalized to a mean of 100 and a standard deviation of 15.³¹ This approach enabled incorporation of participants with partial phenotypic data while preserving relative weighting across behavioral domains.

Autism and social trait characterization

Autism and social impairment traits were harmonized across caregiver-reported datasets as described above. Here, datasets were combined to generate an ordinal autism/social trait severity score ranging from 0 to 3. Variables were selected based on overlaps in social functioning and autism-related behavioral constructs between registries.

Autism spectrum disorder (ASD) diagnosis status was first determined using either registry-reported clinical diagnoses or validated autism-related behavioral assessments. Within Simons Searchlight, ASD status was derived from Social Communication Questionnaire (SCQ) and/or Social Responsiveness Scale (SRS) clinical cutoffs or reported diagnoses. Within RARE-X, ASD diagnosis status was obtained from the medical history/diagnosis dataset (ASD_Diagnosis). When available, clinician-reported ASD diagnoses were prioritized over questionnaire-derived classifications. ASD diagnosis was recorded as a binary variable (yes/no).

To harmonize measurements across registries, SCQ scores were categorized into ordinal severity tiers with predefined cutoff ranges: scores <10 were assigned tier 0, scores 10–14 were assigned tier 1, scores 15–21 were assigned tier 2, and scores >21 were assigned tier 3. SCQ scores were stratified into ordinal categories centered around established ASD screening thresholds to facilitate cross-registry analyses.³² SRS T-scores were similarly categorized, with scores <60 assigned tier 0, scores 60–65 assigned tier 1, scores 66–75 assigned tier 2, and scores >75 assigned tier 3. Increasing tier values reflected greater autism-associated symptom severity and social impairment. SRS T-score severity tiers were assigned using established SRS-2 clinical interpretation thresholds.³¹

Within RARE-X, social impairment severity was assessed using Vineland-3 socialization domain scores (vi3_socialization). Scores were converted into ordinal severity tiers such that scores >85 were assigned tier 0, scores 70–84 were assigned tier 1, scores 55–69 were assigned tier 2, and scores <55 were assigned tier 3, with increasing severity corresponding to greater impairment in social functioning.

To align measurements across registries, SCQ severity tier, SRS severity tier, prior ASD diagnosis, and Vineland socialization severity tiers were integrated into a unified “autism trait tier” ranging from 0 to 3. When multiple assessments were available for a single participant, clinician- or caregiver-reported ASD diagnoses were prioritized over questionnaire-derived classifications. The final harmonized autism trait tier was used downstream for genotype-phenotype and behavioral correlation analyses.

Statistical analyses

All statistical analyses were performed using GraphPad Prism. Unless otherwise stated, biological replicates represent independently cultured samples from the same fibroblast line. Replicates were generated from separate thawed cryovials and/or independently maintained cultures derived from the same thawed vial. Technical replicates refer to replicate wells analyzed within the same experiment. For longitudinal experiments, repeated measurements from the same culture were analyzed across serial passages/time points as indicated. For comparisons involving multiple variant groups relative to controls, one-way ANOVA with Dunnett’s post hoc test for multiple comparisons was applied. Linear regression was used to assess relationships between variant position and phenotype metrics. Goodness of fit was evaluated by using R values and slope. Time-course Seahorse data were analyzed using linear regression to assess trends across serial passage. Slopes were compared between control and variant groups. All boxplots indicate median and interquartile range. Scatterplots show individual data points with mean or median and SEM or SD. Sample sizes were chosen based on cell availability. Investigators were blinded to genotype during the entire study until data analysis.

Results

MED13L variants exhibit mitochondrial dysfunction

Our previous report revealed reduced mitoATP production in a single fibroblast line derived from an individual with a MED13L variant [p.Ser1497Phefs∗].¹⁵ To determine whether mitochondrial dysfunction was a common phenotype associated with MED13L syndrome, an additional 12 fibroblast lines were collected and expanded. mitoATP production was quantified using Seahorse metabolic flux analysis. Across the 10 samples analyzed, mitoATP production was significantly reduced relative to the control (human foreskin fibroblasts) in all but one fibroblast line (c.5471delA [p.Asn1824Metfs∗28]), which exhibited a similar trend but did not reach statistical significance. (Figure 1A, open box). The overall reduction in mitoATP varied, with deletion alleles (far right, shades of green) exhibiting the greatest reduction at ∼33% of control. The remainder demonstrated ∼50% reduction in mitoATP production. These results indicate that impaired oxidative phosphorylation is consistently observed in MED13L syndrome fibroblast lines, regardless of mutant class or location.

Previous studies found that mitoATP production deficits are often compensated for by elevated glycoATP production.³³^,³⁴^,³⁵ Therefore, we next assessed glycoATP production in the MED13L-variant fibroblast lines. GlycoATP levels were variable across MED13L variant lines, with several exhibiting values comparable to control, while others displayed reduced glycolytic output (p.Gln1537∗ [c.4609C>T], p.Thr1663Cysfs∗43 [c.4987_4991del], and p.Asn1824Metfs∗28; Figure 1B). However, the p.Pro866Leu (c.2597C>T) missense (red), Ex2del-2 (light green), Ex3-4del (dark green), and c.6533G>A (p.Trp2178∗) (dark blue) variant fibroblast lines exhibited reduced glycoATP production compared to control (blue boxes, Figure 1B). Only Ex2del-1 exhibited elevated glycoATP production (red box, Figure 1B).

To determine whether glycoATP production was sufficient to maintain total cellular energy balance, the total ATP production was calculated as the sum of mitochondrial and glycolytic contributions (mitoATP + glycoATP). All but three fibroblast lines exhibited significantly reduced ATP production (Figure 1C). Two fibroblast lines (p.Asn1824Metfs∗28 and c.4987_4991del [p.Thr1663Cysfs∗43]) exhibited similar ATP production to control (open box, Figure 1C), while the Ex2del-1fibroblast line exhibited higher ATP production due to the elevated glycoATP production (red box). We next examined the relative contribution of glycolytic versus mitoATP production using a glycoATP:mitoATP ratio. While control fibroblasts derived the majority of ATP from mitochondrial sources (approximate ratio value of 0.5; indicating oxidative phosphorylation provided twice as much ATP as glycolysis), several MED13L variant lines exhibited a shift toward increased reliance on glycolysis (p.Gln1537∗, p.Thr1663Cysfs∗43, p.Asn1824Metfs∗28, Ex2del-1, and Ex3-25del; Figure 1D). Together, these findings indicate that impaired mitoATP production is a consistent feature across MED13L-variant fibroblasts, with incomplete and variable glycoATP production.

MED13L variants are associated with aberrant CCNC nuclear release and mitochondrial fragmentation

Our previous study reported a portion of CCNC aberrantly localized to the cytoplasm in an unstressed p.Ser1497Phefs∗ MED13L syndrome fibroblast line.¹⁵ To determine whether this phenotype is consistently observed across additional MED13L-variant fibroblast lines, we examined CCNC localization in the expanded fibroblast cohort using immunofluorescence microscopy. As expected, the only detectable CCNC in the control cell line was nuclear (Figure 2A, top). However, aberrant CCNC cytoplasmic localization was observed in all MED13L-variant fibroblast lines (Figure 2A; see Figures S1 and S2 for additional images). These results indicate that aberrant CCNC nuclear release is a consistent feature across diverse MED13L genotypes.

*MED13L* variants are associated with aberrant CCNC cytoplasmic localization and mitochondrial fragmentation

(A) Representative immunofluorescence images of mitochondrial morphology (red) and CCNC (cyan) in control and *MED13L*-variant fibroblasts as indicated. For each genotype, merged and 4× magnified images (indicated by boxes) are shown. White arrows indicate CCNC-mitochondrial overlap. See Figures S1 and S2 for additional, full-field images.

(B) Percentages of *MED13L* cells exhibiting >50% fragmented mitochondria are shown. Boxes highlight cell lines not displaying elevated mitochondrial fission (n ≥ 100 cells analyzed). Control cells are represented in black, missense variants in red (p.Pro866Leu [P866L]), medPIWI/IDR variants in shades of purple (c.2911_2914delCTGT [p.Leu971Phefs∗36] [L971∗], p.Trp1359∗ [W1359∗], p.Gln1537∗ [Q1537∗], and p.Thr1663Cysfs∗43 [T1663C^fs∗], C-terminal variants in shades of blue (p.Asn1824Metfs∗28 [N1824M^fs∗], and p.Trp2178∗ [W2178∗]), and N-terminal or deletion variants in shades of green (c.442C>T [p.Arg148∗] [R148∗], Ex2del-1, Ex2del-2, Ex3-4del, and Ex3-25del). Examples of mitochondrial fragmentation can be found in Figure S1.

(C) UniProt-derived domain map and mutation locations of *MED13L* syndrome variants. Globular (yellow) and unstructured (blue) protein domains are indicated under the amino acid numbering. Frameshift, missense, and nonsense mutations are shown above the numbering; deletions (solid line) are indicated below. Dotted lines indicate the predicted coding region eliminated by frameshift mutation in deletion alleles. The mutations were grouped based on position, with N-terminal (green) mutations including one frameshift and three deletion alleles (p.Arg148∗ [R148∗], Ex2del, Ex3-4del, and Ex3-25del). The single missense variant (p.Pro866Leu) is represented by a red box (variant type) with a purple border (functional domain classification = IDR). IDR missense and truncation mutations, including those in the MID medPIWI domain (middle globular domain of PIWI/Argonaute-like module), are represented with purple (p.Leu971Phefs∗36 [L971∗], p.Trp1359∗ [W1359∗], p.Gln1537∗ [Q1537∗], and p.Thr1663Cysfs∗43 [T1663C^fs∗]). C-terminal mutations are represented in blue (N1824M^fs∗ and p.Trp2178∗ [W2178∗]).

(D) Fragmented mitochondria phenotype was grouped by *MED13L* mutations as described in (C).

All data represent mean ± IQR or distributions as indicated. Statistical comparisons were performed using one-way ANOVA with Dunnett’s post hoc test comparing genotype or group to controls (∗p < 0.05, ∗∗p < 0.01, and ∗∗∗p < 0.001). See Table S1 for variant details.

We previously demonstrated that CCNC induces mitochondrial fission through activation of the dynamin-like GTPase DRP1.¹⁶^,³⁶ We next assessed mitochondrial morphology in these fibroblasts using the stain MitoTracker Red.³⁷ As expected, the mitochondria in the control cell line appeared reticular with numerous branches (Figure 2A, top). Compared with control cells, MED13L-mutant fibroblasts exhibited striking alterations in mitochondrial morphology, with many cell lines displaying short, punctate mitochondrial fragments rather than elongated reticular networks (Figure 2A; quantified in Figure 2B). However, this phenotype was not uniformly observed across all fibroblast lines. While the majority of MED13L variants exhibited fragmented mitochondria, several lines (c.4077G>A [p.Trp1359∗], c.4609C>T [p.Gln1537∗], and p.Asn1824Metfs∗28; open boxes in Figure 2B) displayed mitochondrial networks more comparable to control cells. These results indicate that fragmented mitochondria are a common, but not universal, feature associated with MED13L dysfunction. In addition, immunofluorescence analysis revealed increased CCNC signal overlapping mitochondrial networks in MED13L-variant fibroblasts relative to controls (arrows, Figure 2B). While this overlap does not demonstrate a direct molecular interaction, the redistribution of CCNC toward mitochondria is consistent with our previous reports linking stress-induced CCNC nuclear release to mitochondrial fragmentation and altered organelle dynamics.¹⁶^,³⁶

One goal of this study was to determine whether mutation type or location can be predictive for MED13L syndrome outcomes. Therefore, MED13L mutations were mapped onto annotated protein domains and grouped accordingly (Figure 2C). Using this mapping to create protein domain bins, this analysis revealed domain-specific differences in mitochondrial morphology. N-terminal mutations (including all deletion mutations), which are predicted to truncate a substantial portion of the protein, exhibited consistently elevated mitochondrial fragmentation (Figure 2D). Conversely, mutations within the IDRs or C-terminal domains were not significantly different from control but did display variability within the group. These findings suggest that mutation location may contribute to variability in mitochondrial morphology, with N-terminal variants associated with more pronounced fragmentation. When considered alongside the consistent cytosolic CCNC localization, these data support the potential use of both mitochondrial fragmentation and CCNC mislocalization as candidate cellular biomarkers of MED13L syndrome.

mtDNA depletion as a potential biomarker of MED13L-associated mitochondrial dysfunction

To assess whether MED13L variants impact mtDNA abundance and organization, we performed immunofluorescence microscopy using antibodies directed against dsDNA in conjunction with MitoTracker Red to observe morphology. Control fibroblasts exhibited dense, widely dispersed mtDNA foci throughout the mitochondrial network (Figure 3A, left, overlapping signal shown in white). However, MED13L-variant fibroblast lines displayed visibly reduced mtDNA foci, with irregular distribution and regions of mitochondria lacking detectable nucleoids (Figure 3A, arrowheads, right two images).

mtDNA depletion and increased oxidative stress are potential biomarkers of *MED13L*-associated mitochondrial dysfunction

(A) Representative immunofluorescence images showing double-stranded DNA (dsDNA; blue) and mitochondria (red) in control and two *MED13L*-variant fibroblasts (p.Pro866Leu [P866L] and p.Asn1824Metfs∗28 [N1824M^fs∗]). Images depict mitochondrial network architecture and the distribution of mitochondrial nucleoids across genotypes.

(B) Relative mitochondrial DNA (mtDNA) copy number in control and *MED13L*-variant fibroblasts quantified by qPCR and normalized to the nuclear DNA standard (see material and methods) (n ≥ 3 biological replicates; technical triplicates).

(C) mtDNA levels in control and mutation groups described in Figure 2.(D) Cytosolic ROS levels measured using dihydroethidium (DHE) and presented as background-subtracted fluorescence values for control, missense, and PTV fibroblast lines (n ≥ 4 biological replicates; technical duplicates).

(E) Quantification of mitochondrial ROS using MitoSOX fluorescence in control and *MED13L*-variant fibroblast classes described in Figure 2. Relative fluorescence intensity (normalized to background) is shown (n ≥ 6 biological replicates; technical duplicates).

All values represent mean ± IQR. Statistical comparisons were performed using one-way ANOVA with Dunnett’s post hoc test. (∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001, and ∗∗∗∗p < 0.0001).

To quantify these observations, the approximate mtDNA copy number was measured by qPCR.³⁸^,³⁹ Strikingly, most MED13L-variant fibroblasts exhibited marked reductions in mtDNA content, with many reaching statistical significance (Figure 3B). Notably, these data revealed that mtDNA depletion represents a shared consequence of mitochondrial dysfunction in MED13L syndrome. Next, we grouped variants according to protein domains, as before, to determine whether mtDNA copy number varied across domains. These results revealed a similar reduction in mtDNA content regardless of the mutation location (Figure 3C). Taken together, these results indicate that the loss of mtDNA content is a consistent phenotype associated with MED13L syndrome fibroblasts and is in parallel with reduced mitoATP production and increased organelle fragmentation.

Previous studies have revealed that extensive mitochondrial fragmentation often leads to elevated ROS due to disruption of the electron transport chain.⁴⁰^,⁴¹^,⁴² Therefore, we investigated whether the MED13L-variant fibroblast lines exhibited altered mitochondrial redox homeostasis. Using fluorophores DHE⁴³ and MitoSOX Red,⁴⁴ we measured cytosolic and mitochondrial ROS levels, respectively. Binning the mutations according to protein domain revealed that both N- and C-terminal mutations resulted in elevated cytosolic ROS, with N-terminal mutations exhibiting a stronger phenotype (Figure 3D). For the IDR mutation, only the c.2597C>T (p.Pro866Leu [P866L]) fibroblast line was examined, which trended upward but did not reach statistical significance. A similar result was obtained for mitochondrial ROS (Figure 3E). Together, these findings identify reduced mtDNA abundance as a consistent feature of MED13L syndrome-associated mitochondrial dysfunction, accompanied by elevated oxidative stress.

MED13L variants display altered transcriptional dysregulation of MKM components and mitochondrial pathways

Prior transcriptional profiling in Ccnc^−/− MEFs revealed downregulation of genes required for mitochondrial maintenance and biogenesis.¹⁸^,¹⁹ In addition, our prior analysis of a single MED13L-variant fibroblast line similarly identified broad transcriptional changes affecting mitochondrial pathways.¹⁵ To determine the extent to which MED13L variants are associated with transcriptional alterations, RT-qPCR analysis was performed on genes involved in mitochondrial biogenesis, metabolism, and MKM function. Across MED13L-variant fibroblasts, we observed a consistent trend of transcriptional dysregulation. Surprisingly, we observed upregulation of other components of the MKM, including MED13, CCNC, and especially MED13L (Figures 4A; detailed in Figures 4B–4D). These results indicate that expression of several MKM genes is increased in MED13L-variant fibroblasts, suggesting a compensatory transcriptional response. Although increased MKM transcript levels were observed, corresponding changes in protein abundance or lower-molecular-weight species (degradation products) were not detected by western blot analysis (Figure S4). This discrepancy is consistent with the presence of post-transcriptional or translational regulatory mechanisms that modulate MKM protein abundance in MED13L variants, although the precise mechanism remains to be determined (Figures S4A–S4C).

Conversely, a subset of genes (PGC1ɑ [PPARGC1A],⁴⁵ SIRT1,⁴⁶ and TFB1M⁴⁷) involved in mitochondrial biogenesis and maintenance consistently displayed reduced mRNA levels in these fibroblast lines. There was an overall reduction in TFB1M mRNA across fibroblast lines tested, with C-terminal mutations showing a more modest phenotype than the control (Figure 4E). In addition, several fibroblast lines, including P866L, p.Trp1359∗, p.Gln1537∗, p.Asn1824Metfs∗28, Ex2del-2, and Ex3-25del, displayed anywhere from a 1- to 8-fold reduction in PGC1α mRNA levels compared to the control, with two of these reaching statistical significance (Figure 4F). Interestingly, of these fibroblast lines, the p.Gln1537∗ and the C-terminal mutant p.Asn1824Metfs∗28 fibroblast lines exhibited normal mitochondrial morphology, as seen in Figure 2B. These results suggest that their mitochondrial dysfunction may be the result of transcriptional, rather than morphological, dysregulation.

Together, these data reveal a conserved transcriptional signature across MED13L-variant fibroblasts characterized by MKM component upregulation coupled with suppression of mitochondrial biogenesis and maintenance factors. Importantly, these results suggest the potential utility of gene expression as a molecular biomarker for MED13L-variant-associated mitochondrial dysfunction.

MED13L variants exhibit reduced proliferative capacity and features of cellular senescence

Senescence is defined by irreversible cell-cycle arrest coupled with an elevated inflammatory response known as the senescence-associated secretory phenotype (SASP).⁴⁸^,⁴⁹ Although many SASP inducers are known, mitochondrial dysfunction is often observed in senescing cells, although the cause-and-effect relationship has not been completely established.⁴⁸^,⁵⁰ Hallmarks of senescence phenotypes include withdrawal from the cell cycle, expression of cyclin-dependent kinase inhibitors, and induction of senescence-related β-galactosidase.⁵¹^,⁵²^,⁵³ Given our finding of mitochondrial dysfunction, we next examined whether MED13L-variant fibroblasts exhibited senescence phenotypes. Late-passage cultures corresponding to ∼40–45 generations were assayed for proliferative capacity by BrdU incorporation assays.⁵³ Across the MED13L variants tested, the proportion of BrdU-positive cells was significantly reduced relative to controls (Figure 5A), indicating decreased proliferative activity.

To further interrogate a potential elevated senescence entry, two additional assays were performed. First, we used RT-qPCR to measure the expression of the cyclin-dependent kinase inhibitor CDKN2A (p16^INK4a or p16), a canonical marker of irreversible growth arrest.⁵⁴^,⁵⁵^,⁵⁶ Four of the five variants examined displayed statistically significant elevation in p16^INK4a (CDKN2A) mRNA compared to the control (Figure 5B). Finally, we quantified senescence-associated β-galactosidase activity using a fluorogenic flow cytometry-based assay.⁵⁷^,⁵⁸ These studies revealed mixed results with P866L and p.Trp2178∗ fibroblast lines expressing elevated β-galactosidase, while the two deletion alleles did not (Figure 5C). Together, these data suggest that late-passage MED13L-variant fibroblasts exhibit reduced proliferative capacity and features consistent with senescence, although individual senescence markers are variably expressed across fibroblast lines. Our finding that individual senescence markers were not uniformly altered across all fibroblast lines is consistent with previous reports demonstrating that no single senescence marker is universally expressed across all senescent cell populations.⁵² These findings suggest that mitochondrial dysfunction in MED13L syndrome may not simply be a static metabolic defect but may actively contribute to cellular aging and loss of tissue homeostasis.

As mitochondrial dysfunction and senescence are closely linked, we next examined whether mitochondrial energetic capacity changed during prolonged culture. mitoATP production was therefore assessed across serial passage in control and MED13L fibroblasts. Three independent cultures from four MED13L-variant fibroblast lines and controls were continuously maintained for ∼40 generations, with mitoATP measurements obtained every ten generations (Figure 5D). At the earliest analyzed time point (generation 10), MED13L fibroblasts already exhibited reduced mitoATP production relative to control cells, consistent with our earlier observations. As cultures aged in vitro, mitoATP production generally declined across serial generations, although the pattern of decline differed between fibroblast lines. Two-way ANOVA identified a significant interaction between fibroblast line and generation number (p = 0.0011), indicating that changes in mitoATP production over time differed by genotype. A significant overall effect of fibroblast line (genotype) was additionally observed (p < 0.0001), whereas generation number alone was not significant. Consistent with this interaction, linear regression analysis revealed distinct longitudinal trajectories among fibroblast lines. Control fibroblasts showed the steepest decline in mitoATP production across serial generations, while several MED13L patient-derived fibroblast lines exhibited reduced mitoATP production from early generations and comparatively little change over time. At later generations, mitoATP production across the lines approached similarly reduced levels. Together, these findings suggest that MED13L patient-derived fibroblasts may enter a reduced bioenergetic state earlier in culture that is maintained across serial passaging, whereas control fibroblasts progressively decline toward a similar state at later generations.

Analysis of total ATP production revealed a similar overall pattern, with MED13L-variant fibroblasts exhibiting persistently impaired energetic output throughout serial passaging (Figure 5E). While certain fibroblast lines maintained relatively stable but chronically reduced ATP levels, others demonstrated more progressive declines across culture duration (P866L, red). Together, these findings indicate that MED13L disruption is associated with senescence-like cellular phenotypes characterized by reduced proliferative capacity, elevated p16^INK4a (CDKN2A) expression, and persistent bioenergetic dysfunction during prolonged culture.

Mitochondrial function is associated with mutation position, participant age, and clinical phenotypes

To determine whether mutation position influenced mitochondrial function, we examined mitoATP production using the previously described mutation location categories, with individual variants distinguished within each positional group (Figure 6A). These results revealed that the N-terminal mutations, which consist mostly of deletions that cause early truncation alleles, exhibited the most severe reduction in ATP production (Figure 6A). The IDR/medPIWI domain mutations were the next most severe, while the C-terminal alleles were the least affected and were statistically different than the N-terminal mutant fibroblast lines. mitoATP production was significantly reduced in the N-terminal group relative to both the IDR/medPIWI and C-terminal groups. However, examination of individual variants revealed substantial heterogeneity within the IDR/medPIWI and C-terminal groups, with values from individual variants spanning a broad range of mitoATP production. Despite this within-group variability, the overall positional effect was maintained, with N-terminal variants associated with more severe impairment of mitochondrial function.

Mitochondrial function is associated with mutation position and participant age

(A) Mitochondrial ATP (mitoATP) production measured in control and *MED13L* patient-derived fibroblasts grouped by variant location (IDR, N-terminal, medPIWI, or C-terminal). Each point represents an independent biological replicate (n ≥ 6 for each individual variant), and individual symbols distinguish fibroblast lines carrying different *MED13L* variants within each positional group.

(B) Glycolytic ATP (glycoATP) production, calculated from proton efflux rates, shown by variant class as in (A), with individual variants distinguished by symbol (n ≥ 6 for each individual variant, including 3 biological replicates).

(C) Relationship between mitoATP production (mean values from Figure 1) and MED13L amino acid position of each variant. Each point represents a fibroblast line carrying a variant at the indicated residue position within the MED13L protein (R = 0.515).

(D) Relationship between total ATP production (mitoATP + glycoATP) and MED13L amino acid position of mutation. Each point represents an individual fibroblast line carrying variants at the indicated residue position. (R = 0.597).

(E) Relationship between mitoATP production and participant age at the time of sample collection, in months (R = 0.697).

(F) Relationship between total ATP production (mitoATP + glycoATP) and participant age at the time of sample collection, in months (R = 0.775).

Lines in (C)–(F) represent lines of best fit following simple linear regression. Corresponding equations are represented on each graph. For (A) and (B), the black circle with “X” representing Ex3-25del, green triangle representing Ex2del, blue diamond representing Ex3-4del, purple square representing p.Thr1663Cysfs∗43, black circle representing p.Trp1359∗, gray triangle representing p.Gln1537∗, open red circle representing p.Pro866Leu, orange triangle representing p.Asn1824Metfs∗28, and pink circle representing p.Trp2178∗. For (C)–(F), the color of the symbol corresponds to the type and/or location of the mutation and is as follows: green, N-terminal deletions; red, missense; purple, IDR/medPIWI nonsense and frameshift; and blue, C-terminal nonsense and frameshift.

Data represent individual biological replicates, with summary statistics displayed as median and interquartile range. Statistical analysis was performed using one-way ANOVA with Dunnett’s post hoc correction for variant-to-control comparisons. (∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001, and ∗∗∗∗p < 0.0001).

To determine whether glycoATP production is different across variant classes, glycoATP production was also assessed (Figure 6B). N-terminal variants generally exhibited reduced glycoATP production relative to control fibroblasts, although considerable variability was observed both within and between positional groups. In particular, fibroblasts carrying the C-terminal p.Asn1824Metfs∗28 variant exhibited elevated glycoATP production relative to controls, whereas this pattern was not observed for the other C-terminal variant, p.Trp2178∗. Elevated glycoATP values were also observed among individual variants within the IDR/medPIWI group. Thus, unlike mitoATP production, glycoATP production did not demonstrate a consistent positional pattern across MED13L variants.

As substantial variability was observed within positional groups, we also examined mitoATP and glycoATP production according to participant sex and mutation type (Figures S7A–S7D). Both male- and female-derived fibroblast lines spanned a broad range of ATP production within the positional groups, without an apparent separation by sex. Similarly, stratification by mutation type revealed overlapping energetic measurements among deletion, missense, nonsense, and frameshift variants, particularly within the IDR/medPIWI and C-terminal groups. These descriptive analyses therefore did not identify an obvious association between sex or mutation type and the observed variability in ATP production.

We next directly assessed the relationship between mutation position and energetic function using simple linear regression analyses. mitoATP production demonstrated a positive relationship with the position of the MED13L amino acid mutation, with more C-terminal variants generally exhibiting higher mitoATP production relative to variants located nearer the N terminus of the protein (R = 0.515; Figure 6C). A similar trend was observed for total ATP production, in which more C-terminal mutations were associated with higher overall energetic output (R = 0.597; Figure 6D). Together, these findings suggest that variants occurring earlier within the MED13L coding sequence are associated with more severe mitochondrial dysfunction.

As clinical severity in neurodevelopmental disorders may also change with age, we next examined whether mitochondrial energetic capacity correlated with participant age at the time of fibroblast collection. In contrast to mutation position, mitoATP production displayed a negative relationship with participant age (R = 0.697; Figure 6E), indicating that fibroblasts derived from older participants generally exhibited lower mitoATP production. Total ATP production similarly declined with increasing participant age (R = 0.775; Figure 6F). Although the cohort size remains limited, these findings raise the possibility that participant age may contribute to variability in mitochondrial energetic function. Additional longitudinal studies will be required to determine whether mitochondrial dysfunction progresses over time in vivo. Collectively, these data demonstrate that mitochondrial dysfunction in MED13L syndrome is heterogeneous and influenced by both mutation position and participant age, with earlier variants and older participant-derived fibroblasts generally exhibiting more severe energetic impairment.

Clinical and caregiver-reported functional measures are associated with MED13L mutation location

To contextualize our molecular analyses, we first summarized clinician-rated and caregiver-reported functional outcomes across multiple standardized assessment tools (see material and methods). First, we examined motor ability scores using the Vineland Adaptive Behavior Scales³⁰^,⁵⁹^,⁶⁰^,⁶¹ incorporating both fine and gross motor skills (see material and methods). These raw scores were plotted against the amino acid location of the MED13L mutation (Figure 7A). This analysis revealed a trend similar to mitoATP production in that the N-terminal mutations exhibited lower motor function than those with more C-terminal mutations. In contrast, no clear relationship was observed between motor scores and participant age within the available dataset (Figure S8), although the number of individuals with complete data was limited.

Clinical and caregiver-reported functional measures associate with *MED13L* mutation location

(A) Vineland motor standard scores (combined gross and fine motor domains) plotted against MED13L amino acid position. Each point represents an individual participant harboring the indicated *MED13L* variant. Linear regression was performed, and the best-fit line is shown (R = 0.659).

(B) Dual-axis comparison of Vineland motor severity scores (R = 0.465; magenta) with mitochondrial ATP (mitoATP; R = 0.669; green) and amino acid location of the variant. Independent linear regression analyses were performed for each variable relative to motor severity.

(C) Composite functional severity scores generated from integrated adaptive, communication, and motor assessments (see material and methods) plotted against MED13L amino acid position. Linear regression and line of best fit are shown (R = 0.641).

(D) Dual-axis comparison of composite functional severity scores (R = 0.4663; magenta line) with mitoATP production (R = 0.6685; green) and MED13L amino acid position. Independent linear regression analyses were performed for each variable relative to composite severity score.

(E) Autism/social trait severity scores generated from harmonized caregiver-reported and clinical behavioral datasets plotted against MED13L amino acid position. Linear regression and line of best fit are shown (R = 0.905, p = 0.0306).

For (A)–(E), amino acid position corresponds to the predicted location of the MED13L protein alteration. Each point represents an individual participant-derived fibroblast line. For (A), (C), and (E), the color of the symbol corresponds to the type and/or location of the mutation and is as follows: green, N-terminal deletions; red, missense; purple, IDR/medPIWI nonsense and frameshift; and blue, C-terminal nonsense and frameshift.

To further evaluate the relationship between clinical severity and mitochondrial dysfunction, mitoATP production and mutation position were simultaneously plotted against motor severity scores using dual y axes (Figure 7B). Independent linear regression analyses demonstrated that reduced mitoATP production was associated with increased motor severity, with earlier variant positions similarly trending toward greater impairment. The parallel regression patterns support a relationship between mutation position, mitochondrial dysfunction, and clinical motor outcomes in MED13L syndrome.

Composite functional/behavioral severity scores, generated from integrated adaptive, motor, and communication outcome measures (as in Figure 7; see material and methods for details), demonstrated a similar positional trend, with more N-terminal MED13L variants associated with greater overall behavioral/functional dysfunction (Figure 7C). To further assess the relationship between composite scores and mitochondrial dysfunction, mitoATP production and MED13L amino acid mutation position were simultaneously plotted against composite scores using dual axes as in Figure 7B. Independent regression analyses demonstrated that lower mitoATP production and earlier variant positions were both associated with increased composite behavioral and functional severity, further linking impaired cellular bioenergetics with multisystem clinical dysfunction.

Finally, autism trait severity revealed an inverse correlation with mutation location. Variants located toward the N-terminal region were associated with higher autism/social trait severity scores, whereas variants positioned more distally within the protein were generally associated with milder social-behavioral phenotypes (Figure 7E). Taken together, these results suggest that mutation location and mitoATP production are associated with clinical variability in MED13L syndrome. While these relationships should be interpreted cautiously given the cohort size, they support a model in which mutation position and cellular bioenergetic status contribute to functional outcomes in affected individuals.

Discussion

Prior MED13L syndrome studies have been limited by small cohorts, heterogeneous clinical presentations, and a lack of mechanistic convergence. Here, using the largest panel of patient-derived MED13L fibroblasts analyzed to date, we identify mitochondrial impairment as a consistent and distinguishing cellular signature across diverse pathogenic variants. Despite substantial heterogeneity in transcriptional and morphological outcomes, many MED13L mutant fibroblast lines exhibited reduced mitochondrial content, diminished ATP production, and marked loss of mtDNA copy number, supporting mitochondrial impairment as a central aspect of MED13L-associated cellular dysfunction. Among the cellular phenotypes examined, reduced mitoATP production emerged as the most reproducible feature across genotypes, suggesting that impaired oxidative bioenergetics may represent a core downstream consequence of MED13L syndrome dysfunction.

These findings are consistent with growing evidence linking mitochondrial dysfunction to neurodevelopmental and neurodegenerative disorders, including conditions characterized by impaired oxidative phosphorylation, reduced mtDNA copy number, and elevated oxidative stress.³³^,³⁵^,⁶²^,⁶³ In this context, the increased cytosolic and mitochondrial ROS observed in MED13L-variant fibroblast lines further support disruption of mitochondrial homeostasis as a contributing feature of disease pathology. Enhanced oxidative stress is associated with several intellectual disability disorders including autism,³⁵^,⁶⁴^,⁶⁵^,⁶⁶^,⁶⁷^,⁶⁸ as well as several neurological syndromes including Friedreich’s ataxia⁶⁹^,⁷⁰^,⁷¹ and Parkinson disease.⁷²^,⁷³^,⁷⁴ Neurons may be especially vulnerable to disruptions in mitochondrial homeostasis because of their high energetic demand, dependence on mitochondrial trafficking, and limited glycolytic reserve. Therefore, the role of mitochondrial dysfunction and elevated oxidative stress observed across MED13L-variant fibroblasts is consistent with pathologies identified for other neurological disorders and supports the possibility that impaired mitochondrial resilience contributes directly to neurodevelopmental dysfunction seen in MED13L syndrome.

A key observation in this study is the consistent cytoplasmic localization of CCNC across all MED13L-variant fibroblast lines. CCNC nuclear release has been previously implicated in stress-responsive mitochondrial fission through interaction with DRP1, suggesting a potential link between MKM dysfunction and altered mitochondrial dynamics.¹⁴^,¹⁶^,³⁶^,⁷⁵ Mitochondrial dynamics are controlled by the opposing activities of mitochondrial fusion (MFN2 and OPA1) and fission (DRP1) factors.⁷⁶^,⁷⁷^,⁷⁸^,⁷⁹^,⁸⁰^,⁸¹^,⁸²^,⁸³^,⁸⁴^,⁸⁵^,⁸⁶ Disruption of this process, such as with OPA1 mutations, results in excessive mitochondrial fragmentation in neurodegenerative diseases such as Charcot-Marie Tooth type 2A and Kjer disease/autosomal-dominant optic atrophy.⁸⁷^,⁸⁸^,⁸⁹^,⁹⁰^,⁹¹^,⁹² Combined with our earlier demonstration of respiratory defects in MED13L fibroblasts, these findings support a model in which MKM dysfunction impairs nuclear regulation of mitochondrial homeostasis as well. While our data do not directly establish causality, the co-occurrence of CCNC mislocalization and mitochondrial fragmentation in many variant lines supports a model in which disruption of MKM-associated signaling contributes to altered mitochondrial structure and function.

Importantly, not all mitochondrial-associated phenotypes were uniformly observed across variant lines. While reduced mitoATP production and mtDNA depletion were highly consistent, mitochondrial morphology, ROS accumulation, and senescence-associated markers displayed greater variability across the cohort. This heterogeneity likely reflects differential effects of variant position, residual protein function, compensatory metabolic adaptation, and the specific genetic background. Nonetheless, the persistence of mitochondrial energetic dysfunction across diverse mutation classes suggests convergence upon a shared downstream cellular phenotype despite substantial molecular and clinical variability.

Our transcriptional analyses further support disruption of coordinated mitochondrial regulatory programs in MED13L syndrome. Previous studies of Ccnc-deficient MEFs identified altered expression of genes involved in mitochondrial maintenance and biogenesis.¹⁸^,¹⁹ Consistent with these findings, MED13L-variant fibroblasts exhibited reduced expression of multiple genes associated with mitochondrial function, including PGC1α (PPARGC1A), SIRT1, and TFB1M. Surprisingly, we also observed increased expression of several MKM-associated transcripts, including MED13, MED13L, and CCNC, across many variant lines, suggesting compensatory transcriptional activation in response to impaired MKM function. However, these increases in transcript abundance were not accompanied by corresponding increases in MED13L protein abundance, as assessed by western blot analysis, indicating that elevated transcript levels alone may be insufficient to restore MKM protein expression (Figures S4A and S4B; quantified in Figure S4C). To further investigate the consequences of truncating MED13L variants, we evaluated MED13L protein expression using antibodies recognizing N-terminal, central, and C-terminal epitopes of MED13L. For clarity, representative immunoblots generated using the commercially available antibody are shown in Figure S4, as all antibodies produced comparable overall patterns of MED13L expression. These findings should be interpreted cautiously. If truncated MED13L proteins are produced, they may be unstable, rapidly degraded, expressed below the detection limit of immunoblotting, or not recognized depending on the retained epitope. Conversely, the preservation of near-normal steady-state MED13L protein levels despite increased MED13L transcript abundance suggests that post-transcriptional regulation and/or altered protein turnover contribute to MED13L homeostasis. Collectively, these observations are consistent with a loss-of-function mechanism arising from reduced functional MED13L dosage and/or impaired protein stability, although the precise molecular fate of variant-derived MED13L proteins will require further investigation. These findings additionally suggest that therapeutic strategies aimed solely at increasing MED13L transcript abundance may not be sufficient to restore MKM function if normal protein expression, stability, or complex assembly cannot also be recovered.

An additional finding of this study is the possibility that mitochondrial dysfunction in MED13L syndrome may represent a progressive rather than static phenotype. Longitudinal analysis revealed a persistent impairment of mitoATP production during extended culture, indicating that MED13L variants compromise metabolic resilience rather than immediately disabling respiration. This progressive vulnerability coincided with premature acquisition of senescence-associated phenotypes, including growth arrest, p16^INK4a (CDKN2A) induction, and accumulation of β-galactosidase-positive cells.⁵⁰^,⁵²^,⁵⁵^,⁵⁷^,⁹³^,⁹⁴^,⁹⁵^,⁹⁶^,⁹⁷ Notably, several MED13L fibroblast lines exhibited persistently reduced mitoATP production beginning at early time points, suggesting that MED13L disruption may establish an early and sustained bioenergetic state resembling later-passage control fibroblasts (P866L, Ex2del, Ex3-4del, and Ex3-25del). These data support a model in which MED13L mutation accelerates cellular aging through cumulative mitochondrial stress rather than causing acute toxicity. Although these findings were observed in vitro, they suggest that impaired mitochondrial resilience may contribute to changes in cellular function over time. Whether similar bioenergetic changes occur during disease progression in vivo remains unknown and will require longitudinal clinical investigation.

Importantly, our findings also suggest that mutation position may partially influence mitochondrial and clinical severity. Earlier truncating and deletion variants were generally associated with greater reductions in mitoATP production, while more C-terminal variants displayed comparatively preserved energetic function. Similar positional relationships were observed for motor function, composite functional and behavioral severity, and autism/social trait scores. Although these analyses remain limited by cohort size, they raise the possibility that disruption of distinct MED13L structural regions differentially impacts MKM stability and downstream mitochondrial regulation. More broadly, these findings support the concept that mutation position may contribute to phenotypic stratification in MED13L syndrome and may help predict cellular bioenergetic dysfunction.

Finally, these results have broader implications for the MKM and related neurodevelopmental disorders. MED12,⁹⁸^,⁹⁹^,¹⁰⁰^,¹⁰¹^,¹⁰² MED12L,¹⁰³ MED13,¹⁰⁴^,¹⁰⁵^,¹⁰⁶ CDK8,¹⁰⁷^,¹⁰⁸^,¹⁰⁹ and CDK19¹¹⁰^,¹¹¹^,¹¹² mutations are linked to phenotypes similar to MED13L syndrome, including developmental delays and intellectual disability.¹¹³ Due to these mutations producing overlapping neurodevelopmental phenotypes, this raises the possibility that mitochondrial dysfunction may represent a broader downstream consequence of MKM disruption. Whether CCNC itself contributes similarly remains unclear, as there have currently been no reports of mutations to this gene. Although constitutive CCNC nuclear release promotes mitochondrial fragmentation, heterozygous Ccnc loss in murine models does not recapitulate severe developmental phenotypes, suggesting that aberrant CCNC localization, rather than simple dosage reduction, may be critical for mitochondrial dysfunction.³⁶^,¹¹⁴

In summary, our work identifies mitochondrial dysfunction as a consistent and quantifiable biomarker of MED13L syndrome. These findings establish a mechanistic foundation for linking MKM dysfunction to impaired mitochondrial homeostasis and provide a framework for therapeutic discovery aimed at restoring mitochondrial integrity. In addition, we find that mutation location correlates with mitochondrial function, suggesting that mutation position may help predict the severity of mitochondrial dysfunction in patient-derived fibroblasts. Several limitations of the study should be considered. This study is based on fibroblast models, which may not fully recapitulate tissue-specific effects in neuronal or cardiac systems.¹¹⁵ Further analysis in neuronal cell models would help establish these phenotypes. Despite fibroblasts not fully recapitulating neuronal biology, patient-derived fibroblasts have proven valuable for identifying conserved mitochondrial and metabolic phenotypes across many neurological disorders, including Alzheimer disease.¹¹⁶^,¹¹⁷^,¹¹⁸^,¹¹⁹^,¹²⁰^,¹²¹^,¹²² In addition, the cohort size limits the ability to definitively resolve the relative contributions of mutation type, position, and individual-specific factors such as age. Future studies incorporating larger cohorts and disease-relevant cell types, including neuronal models, will be important for validating and extending these findings.

Overall, this work identifies mitochondrial dysfunction as a convergent and quantifiable cellular feature of MED13L syndrome and establishes a functional connection between MKM disruption and impaired mitochondrial homeostasis. By defining shared cellular phenotypes across MED13L variants, this study advances the field beyond genotype-based classification and toward a biomarker-informed understanding of mediator-associated neurodevelopmental diseases. These findings provide a framework for future therapeutic strategies aimed at restoring mitochondrial integrity and improving cellular resilience in MED13L syndrome and related MKM-associated disorders.

Data and code availability

This study did not generate/analyze datasets or code. All genotypes are provided throughout the manuscript.

Acknowledgments

We would like to thank the MED13L Foundation for organizing the sample collection, in conjunction with CUIMC. We would also like to thank all of the families and affected individuals for volunteering their time and samples to complete such a large characterization of MED13L syndrome. We thank C. Greuter (University of Iowa) for helpful comments during this study. This work was supported by grants awarded to R.S. and A.N.C. from the MED13L Foundation (www.MED13L.org). The sponsors had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Author contributions

Conceptualization, A.N.C. and R.S.; methodology, A.N.C., K.N.J., J.M.B., E.L., B.C., J.F., and C.L.R.; formal analysis, A.N.C., K.N.J., and S.J.D.; investigation, A.N.C., K.N.J., S.J.D., J.M.B., E.L., B.C., J.F., and C.L.R.; resources, A.N.C., J.M.B., E.L., B.C., J.F., C.L.R., and R.S.; writing – original draft, A.N.C. and R.S.; writing – review & editing, A.N.C., S.J.D., E.L., B.C., J.F., C.L.R., and R.S.; visualization, A.N.C. and R.S.; supervision, A.N.C. and R.S.; project administration, A.N.C., J.M.B., and R.S.; funding acquisition, A.N.C. and R.S.; validation, K.N.J., S.J.D., J.M.B., E.L., B.C., J.F., C.L.R., and R.S.

Declaration of interests

The authors declare no competing interests.

Declaration of generative AI and AI-assisted technologies in the writing process

During the preparation of this work, the authors used Grammarly and OpenAI ChatGPT for final grammar, punctuation, and spelling checks. The authors reviewed and edited the output as needed and take full responsibility for the content of the published article.

Footnotes

Supplemental information can be found online at https://doi.org/10.1016/j.xhgg.2026.100670.

Contributor Information

Alicia N. Campbell, Email: campbe26@rowan.edu.

Randy Strich, Email: strichra@rowan.edu.

Web resources

Impaired Intellectual Development and Distinctive Facial Features With or Without Cardiac Defects, https://www.omim.org/entry/616789?search=616789&highlight=616789
MED13L Foundation, https://med13l.org/
MED13L Genotype, https://www.omim.org/entry/608771?search=med13l&highlight=med13l
OMIM, https://www.omim.org

Supplemental information

Document S1. Figures S1–S8, Tables S1–S5, and

supplemental material and methods

mmc1.pdf^{(1.5MB, pdf)}

Document S2. Article plus supplemental information

mmc2.pdf^{(13.2MB, pdf)}

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Document S1. Figures S1–S8, Tables S1–S5, and

supplemental material and methods

mmc1.pdf^{(1.5MB, pdf)}

Document S2. Article plus supplemental information

mmc2.pdf^{(13.2MB, pdf)}

Data Availability Statement

This study did not generate/analyze datasets or code. All genotypes are provided throughout the manuscript.

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PERMALINK

Cyclin C nuclear release and mitochondrial dysfunction define molecular signatures of MED13L syndrome

Alicia N Campbell

Kendall N Jung

Steven J Doyle

Ekaterina Lebayle

Barbara Corneo

Joanna Feng

Christopher L Ricupero

Jennifer M Bain

Randy Strich

Summary

Introduction

Material and methods

Human subjects and fibroblast biopsies

Culturing dermal fibroblasts

Characterization of dermal fibroblasts grown from skin biopsy

General cell culture

Variant annotation and classification

RNA isolation and quantitative PCR

Immunofluorescence microscopy

Quantification of mitochondrial fragmentation

Seahorse mitochondrial and glycolytic ATP production rate assays

Seahorse normalization and quality control

Calculation of mitochondrial and glycolytic ATP production rates

Statistical analysis of longitudinal Seahorse data

Senescence-associated β-galactosidase assay

BrdU incorporation assay

Cytosolic reactive oxygen species measurement

Mitochondrial ROS measurement

mtDNA copy number

Clinical and behavioral data collection

Clinical severity metrics: Composite functional/behavioral scoring

Clinical severity metrics: Motor severity score

Autism and social trait characterization

Statistical analyses

Results

MED13L variants exhibit mitochondrial dysfunction

Figure 1.

MED13L variants are associated with aberrant CCNC nuclear release and mitochondrial fragmentation

Figure 2.

mtDNA depletion as a potential biomarker of MED13L-associated mitochondrial dysfunction

Figure 3.

MED13L variants display altered transcriptional dysregulation of MKM components and mitochondrial pathways

Figure 4.

MED13L variants exhibit reduced proliferative capacity and features of cellular senescence

Figure 5.

Mitochondrial function is associated with mutation position, participant age, and clinical phenotypes

Figure 6.

Clinical and caregiver-reported functional measures are associated with MED13L mutation location

Figure 7.

Discussion

Data and code availability

Acknowledgments

Author contributions

Declaration of interests

Declaration of generative AI and AI-assisted technologies in the writing process

Footnotes

Contributor Information

Web resources

Supplemental information

References

Associated Data

Supplementary Materials

Data Availability Statement

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