# An impaired glycolysis induces ATP deficiency and reduced cell respiration in stem cells of patients with autism spectrum disorders

François Féron, Damien Caillol, Laure Fourel, Silke Leimkuhler, Olga Iranzo,
Bruno Gepner, Gaëlle Guiraudie-Capraz

► To cite this version:

Francois Féron, Damien Caillol, Laure Fourel, Silke Leimkuhler, Olga Iranzo, et al. An impaired glycolysis induces ATP deficiency and reduced cell respiration in stem cells of patients with autism spectrum disorders. Scientific Reports, 2025, 15 (1), pp.38353. 10.1038/s41598-025-22327-1. hal-05343732

HAL Id: hal-05343732

https://hal.science/hal-05343732v1

Submitted on 3 Nov 2025

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
<figure><img src="image_2.png" /></figure>

OPEN

# An impaired glycolysis induces ATP deficiency and reduced cell respiration in stem cells of patients with autism spectrum disorders

François Féron<fnref n="1" />✉, Damien Caillol<fnref n="1" />,⁴, Laure Fourel<fnref n="1" />, Silke Leimkuhler², Olga Iranzo³, Bruno Gepner<fnref n="1" /> & Gaelle Guiraudie-Capraz<fnref n="1" />

In two previous studies, based on human olfactory ecto-mesenchymal stem cells (OE-MSC) of 11 patients with autism spectrum disorders (ASD) and 11 healthy individuals, we demonstrated that the lower abundance of the enzyme MOCOS (MOlybdenum COfactor Sulfurase) and its associated lower expression of the long non-coding RNA, COSMOC, induces neurotransmission and synaptic defects as well as an exacerbated oxidative stress sensitivity. To move a step further, we assessed whether these defects were associated to a disturbed mitochondrial homeostasis. For that purpose, we used cellular and molecular techniques to quantify mitochondrial metabolism and biogenesis, ATP production and cell respiration in OE-MSCs from the 8 ASD patients of the cohort that display the most severe symptoms. We show here that OE-MSCs from ASD patients, when compared to control individuals, display (i) a reduced expression/abundance of glycolysis-associated transcripts and metabolites, (ii) an overall reduced ATP, mainly due to the impaired glycolysis, (iii) a reduced basal cell respiration and (iv) a modified mitochondrial network. These results are in accordance with some of our previously published data and may explain some of the symptoms – stress, overarousal, seizures, increased or decreased muscle tone, fatigue—observed in autism spectrum disorders.

**Keywords** Autism spectrum disorders, Olfactory stem cells, Glycolysis, ATP, Respiration, Mitochondria

Autism Spectrum Disorders (ASD), which affect around 50 million individuals worldwide<fnref n="1" />, is a major public health issue. With an onset under the age of three, ASD are understood as diseases arising from pre- and/or early post-natal brain developmental anomalies and/or early brain insults/infections. To unveil the molecular mechanisms at play during the misshaping of the developing brain, we chose to study cells representative of the very early stages of ontogeny, namely adult stem cells and, more specifically, human nasal olfactory stem cells². In a first series of experiments, based on a cohort of 11 autistic patients and 11 healthy individuals we demonstrated the reduced expression/production of *MOCOS* and *MOCOS* (MOlybdenum COfactor Sulfurase), an enzyme involved in purine metabolism³, and its associated long non-coding RNA that we named COSMOC⁴. We observed that reduced expression of *MOCOS* and/or COSMOC induces neurotransmission and synaptic defects as well as an exacerbated oxidative stress sensitivity³,⁴.

All these molecules are involved in the synthesis of molybdenum enzymes, which begins in mitochondria with the conversion of guanosine triphosphate (GTP) to cyclic pyranopterin monophosphate (cPMP) by the two active forms of the MOCS1 enzyme (MOCS1A and MOCS1AB)⁵. cPMP is then converted outside the mitochondria via MOCS2 to molybdopterin (MPT), which in turn is further converted to the MOlybdenum COfactor (MOCO) by gephyrin (GPHN). MOCO is the central element of the four human molybdenum enzymes: (i) sulfite oxidase (SUOX) that transforms sulfites into sulfates⁶; (ii) xanthine dehydrogenase (XDH) and aldehyde oxidase (AOX) that catalyse the two-step reaction from hypoxanthine to xanthine and from xanthine to uric acid in purine metabolism⁷; (iii), and is involved in the metabolism of retinaldehyde, respectively, and the mitochondrial amidoxime-reducing component (mARC), a key factor in the N-hydroxylation of prodrugs or N-oxygenated compounds⁸.

<footnote n="1">¹Aix Marseille University, CNRS, INP UMR7051, Marseille, France. ²Department of Molecular Enzymology, Institute of Biochemistry and Biology, University of Potsdam, Potsdam, Germany. ³Aix Marseille Université, Centrale Méditerranée, CNRS, iSm2 UMR 7313, 13397 Marseille, France. ⁴Pathophysiology and Genetics of Neuron and Muscle, Institute NeuroMyoGene, UMR CNRS 5261 - INSERM U1315, Claude Bernard Lyon 1 University, Lyon, France., Lyon, France. ⁵email: francois.feron@univ-amu.fr</footnote>
Many observations have linked autism disorders to mitochondrial dysfunction (for recent reviews⁹, Frye et al., 2024). An exploratory study reported that the majority of lymphocytes from very young ASD children exhibit a reduced activity of oxidative phosphorylation as well as a mitochondrial DNA over-replication¹⁰. In addition to mutations in mitochondrial DNA¹¹⁻¹⁴, recurrent studies found anomalies in (i) electron transport chain (ETC) complex activity¹⁵⁻¹⁹, (ii) Krebs cycle metabolites¹²,²⁰⁻²² and (iii) oxidative stress and redox regulation²³⁻²⁵. However, none of these studies was able to make causal inferences between disturbed mitochondrial metabolism and ASD. To move a step further, we used a panel of cellular and molecular techniques to unveil mitochondrial disturbances in stem cells originating from a peripheral nervous tissue, namely the olfactory mucosa, of 8 ASD patients with severe symptoms and 8 age- and gender-matched healthy individuals.

## Results

### The abundance of many mitochondria-associated metabolites is disrupted in ASD stem cells

Quantification of metabolites between each ASD patient and the mean of 6 control individuals reveals an altered abundance of molecules involved in four mitochondria-related pathways (Fig. 1A,B). For the current analysis, the cut-off value for fold change was set at ±1.5. Among the most striking findings is the lower abundance of adenine and pyruvate in all patients. The lower abundance of the former, together with a lower abundance of adenosine diphosphate (ADP) in 6 out 8 patients, indicate a putative disruption of oxidative phosphorylation. Altered abundance of the latter, combined with a reduced production of glucose-6-phosphate (6/8 patients) and ascorbic acid (7/8), point to a presumed modified glycolysis. It should be noted that ketoglutarate, a molecule involved in the Krebs cycle as well as in carnitine biosynthesis, is present in lower concentration in 7 ASD patients. All the abnormalities in metabolites associated with mitochondria are summarized schematically in Fig. 1C.

### ASD stem cells exhibit a reduced ATP production, basal respiration and proton leak

The widespread deficiency of adenine and, to a lesser extent, ADP led us to consider a disturbance in oxidative phosphorylation. To make sure it was the case, we studied ATP production using the Seahorse apparatus and its various associated protocols. Before examining the data for each individual in more detail, it is essential to note that olfactory stem cells, which are highly proliferative cells just like cancer cells, differ from other somatic cells in that they produce ATP mainly from glycolysis (70%) and not from oxidative phosphorylation (Fig. 2A). We measured the different values obtained after measured with the addition of specific inhibitors (oligomycin, FCCP, rotenone, antimycin A) at various stages of this metabolic pathway, which includes 5 complexes. Overall, ASD patients differ from the control population by a reduction in total ATP production (Fig. 2B). This is primarily due to a very significant decrease in glycolysis-associated ATP production (Fig. 2C), which is not fully compensated for by an increase in ATP produced during oxidative phosphorylation (Fig. 2D).

The seahorse apparatus allowed us to assess whether impaired ATP production was associated with abnormalities in cellular respiration. Figure 2E–G shows the alterations observed in some ASD patients. Stem cells of several patients (3, 7 and 8) exhibit very low basal respiration and the entire ASD arm of the cohort display a statistically significant difference compared with the control arm (Fig. 2E). However, maximal breathing did not differ between the two groups, nor did spare respiratory capacity (unshown data). Similarly, despite a downward trend, there is no difference between the two groups in ATP-production coupled respiration (unshown data). On the other hand, the TSA group differs from the control group by a significant decrease in proton leak (Fig. 2F) and a significant increase in coupling efficiency (Fig. 2G).

### Many glycolysis-related transcripts are present in lower concentrations in ASD stem cells

The unexpected decrease in ATP production from a reduced glycolysis pathway led us to investigate the causes of this lower abundance. To do this, we carried out a transcriptome study based on RNA sequencing. We first analyzed the expression of transcripts involved in glycolysis. As with the metabolome, we set the cut-off value for fold change at ±1.5. Figure 3A shows that the concentration of 6 of the 9 genes involved in the conversion of glucose into pyruvate is disrupted in at least 2 patients. Special mention should be made of patient 4 in whom gene expression is often opposite to that of other members of the ASD group. As a result of this inversion, enolase 2 expression, which is reduced in 7 of the 8 patients, is not significantly different from the control group (Fig. 3B). It is also important to note that the concentration of several glucose and pyruvate transporters is also affected, in variable proportions and sometimes in contradictory directions. All the abnormalities in glycolysis-associated transcripts are summarized schematically in Fig. 3C.

### Stem cells from ASD patients partially rescue ATP production by generating new mitochondria

The metabolome and transcriptome data explain the lower concentration of ATP produced from glycolysis. However, it remains to be explained how stem cells from ASD patients manage to increase the number of ATP molecules derived from oxidative phosphorylation. To understand the mechanisms at work, we incubated the stem cells with a mitochondria-specific fluorescent probe and then analyzed the mitochondrial network. Figure 4A and B are illustrations of the networks visualized in a control individual and an autistic patient. A detailed study of these networks shows an increase in mitochondrial area (Fig. 4C), mitochondrial content (Fig. 4D) and the number of punctate mitochondria (Fig. 4E) in autistic patients. There was also a trend towards an increase in the number of mitochondria but this did not reach statistical significance (Fig. 4F). In order to understand whether this increase in punctate mitochondria is the result of increased fission, at the expense of reduced fusion, we measured by Western blot (Supplementary Fig. 1) the expression of two markers—DRP1 and OPA1—specific to mitochondrial dynamics (Fig. 4G). As shown in Fig. 4H and I, we observe an increase in the
A

Mitochondria-associated metabolites

<table><thead><tr><th></th><th>A1</th><th>A2</th><th>A3</th><th>A4</th><th>A5</th><th>A6</th><th>A7</th><th>A8</th></tr></thead><tbody><tr><td><strong>Oxidative phosphorylation</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Adenine</td><td>-14,9</td><td>-16,4</td><td>-8,5</td><td>-3,5</td><td>-1,9</td><td>-6,1</td><td>-12,9</td><td>-3,4</td></tr><tr><td>ADP</td><td>-1,6</td><td>-49,8</td><td></td><td>-1,7</td><td></td><td>-4,1</td><td>-1,8</td><td>-2,2</td></tr><tr><td><strong>Glycolysis</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Glucose</td><td>1,54</td><td></td><td>1,87</td><td>1,53</td><td></td><td></td><td>1,58</td><td></td></tr><tr><td>Glucose 6-phosphate</td><td>-2,1</td><td>-15,2</td><td>-1,8</td><td>-2,7</td><td>-2,5</td><td>-5,1</td><td>-2,9</td><td></td></tr><tr><td>Pyruvate</td><td>-3,9</td><td>-1,5</td><td>-2,3</td><td>-1,5</td><td>-1,8</td><td>-3,5</td><td>-2</td><td>-2,4</td></tr><tr><td>Lactate</td><td>-1,6</td><td>-3,1</td><td>2,6</td><td>2,6</td><td></td><td>-1,7</td><td></td><td>1,5</td></tr><tr><td>Ascorbic acid</td><td>-7,3</td><td>-1,9</td><td>-2,1</td><td></td><td>-2,9</td><td>-5,5</td><td>-2,6</td><td>-6,7</td></tr><tr><td><strong>Krebs cycle (TCA)</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Citrate</td><td></td><td></td><td></td><td></td><td></td><td>-2,3</td><td>-1,8</td><td></td></tr><tr><td>Ketoglutarate</td><td></td><td>-3,7</td><td></td><td>-2,4</td><td>-1,5</td><td>-2,4</td><td>-4</td><td>-4,4</td><td>-2,4</td></tr><tr><td>Succinate</td><td>-1,9</td><td></td><td></td><td></td><td></td><td>-3,4</td><td></td><td>-2,9</td></tr><tr><td>Fumarate</td><td>-1,9</td><td></td><td>-4,1</td><td></td><td></td><td>-2,6</td><td></td><td>-2,2</td></tr><tr><td>Malate</td><td>-1,7</td><td></td><td>-1,9</td><td></td><td></td><td></td><td>-1,7</td><td>-1,9</td></tr><tr><td>NAD</td><td></td><td>-9,7</td><td></td><td></td><td></td><td></td><td>-3,4</td><td>-1,8</td></tr><tr><td><strong>Carnitine biosynthesis</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>L-Lysine</td><td>1,6</td><td>-12</td><td>1,8</td><td>1,8</td><td>1,9</td><td>-2,1</td><td>1,8</td><td></td></tr><tr><td>N6,N6,N6-Trimethyl-L-lysine</td><td>1,7</td><td>-11,1</td><td>1,6</td><td>1,9</td><td>2,7</td><td>-2,6</td><td>2,2</td><td></td></tr><tr><td>Ascorbic acid</td><td>-7,3</td><td>-1,9</td><td>-2,1</td><td></td><td>-2,9</td><td>-5,5</td><td>-2,6</td><td>-6,7</td></tr><tr><td>Ketoglutarate</td><td>-3,7</td><td></td><td>-2,4</td><td>-1,5</td><td>-2,4</td><td>-4</td><td>-4,4</td><td>-2,4</td></tr><tr><td>Pyridoxamine</td><td>2,4</td><td>-24,3</td><td></td><td>1,8</td><td>-1,7</td><td>-3,9</td><td></td><td>-2,5</td></tr><tr><td>Pyridoxine</td><td>1,7</td><td>-12,7</td><td>1,9</td><td>1,9</td><td>2,1</td><td>-2,1</td><td>2,2</td><td></td></tr><tr><td>L-Camitine</td><td></td><td>-69</td><td>-1,8</td><td>-15,6</td><td>1,6</td><td></td><td>-2,9</td><td>-1,8</td></tr></tbody></table>

B

<figure><img src="image_3.png" /></figure>

C

<figure><img src="image_4.png" /><figcaption>**Fig. 1.** Mitochondria-associated metabolome. (A) Main results for the 4 metabolic pathways occurring, wholly or partially, in the mitochondria of olfactory stem cells from 8 ASD patients and 8 control individuals. The cut-off value for fold change was set at ± 1,5. To varying degrees, all 4 pathways are affected in cells from ASD patients, compared with mean values from control individuals. (B) Box plots demonstrating the underproduction of adenine, adenosine diphosphate, glucose 6 phosphate and pyruvate in the ASD arm of the cohort. (C) Schematic summary of the main findings. The tone of each color correlates with the number of concerned patients. Green: underabundance; orange: overabundance; white: -1,5 > production < +1,5. **, p < 0,01; ***, p < 0,005.</figcaption></figure>
<caption>A</caption>

Olfactory stem cell

<figure><img src="image_5.png" /></figure>

Somatic cell

<figure><img src="image_6.png" /><figcaption>B</figcaption></figure>

Total ATP Production Rate

<figure><img src="image_7.png" /><figcaption>C</figcaption></figure>

glycoATP Production Rate

<figure><img src="image_8.png" /><figcaption>D</figcaption></figure>

mitoATP Production Rate

<figure><img src="image_9.png" /><figcaption>E</figcaption></figure>

<figure><img src="image_10.png" /><figcaption>F</figcaption></figure>

<figure><img src="image_11.png" /><figcaption>G</figcaption></figure>

<figure><img src="image_12.png" /></figure>

**Fig. 2.** ATP production and cell respiration. Using the seahorse apparatus and specific inhibitors—2-deoxy-D-glucose and oligomycin – ATP production and cell respiration were measured in 8 ASD patients and 8 control individuals. (A) Illustration of the relative percentage of mitochondrial ATP and glycolytic ATP in somatic cells and olfactory stem cells from healthy controls. (B–D) Box plots summarizing the total ATP, glycoATP and mitoATP levels. (E–G) Box plots summarizing the statistically significant findings in cell respiration: a decreased basal respiration and proton leak, associated to an increased coupling efficiency, in the ASD arm of the cohort. \* = p < 0.05; \*\* = p < 0.01; \*\*\* = p < 0.005.
A

Glycolysis-associated transcripts

<table><thead><tr><th>Glucose transporters</th><th>A1</th><th>A2</th><th>A3</th><th>A4</th><th>A5</th><th>A6</th><th>A7</th><th>A8</th></tr></thead><tbody><tr><td>SLC2A1</td><td>-2</td><td></td><td>-2</td><td></td><td>-2</td><td>-3</td><td>-2</td><td>-2</td></tr><tr><td>SLC2A3</td><td>-17</td><td>-2</td><td>-2</td><td>1,7</td><td>-2</td><td>-2</td><td>-2</td><td></td></tr><tr><td>SLC5A3</td><td></td><td>-2</td><td>1,6</td><td></td><td>2,4</td><td></td><td>1,5</td><td>-3</td></tr><tr><td>SLC45A1</td><td></td><td></td><td></td><td>-4</td><td></td><td>-2</td><td></td><td>-2</td></tr><tr><th>Glycolysis</th><th>A1</th><th>A2</th><th>A3</th><th>A4</th><th>A5</th><th>A6</th><th>A7</th><th>A8</th></tr><tr><td>Hexokinase 2</td><td>-2</td><td></td><td>-2</td><td>1,6</td><td>-2</td><td>-2</td><td></td><td>-2</td></tr><tr><td>Glucose 6-phosphate isomerase</td><td></td><td></td><td>-2</td><td></td><td></td><td></td><td>-2</td><td></td></tr><tr><td>Phospho-fructokinase platelet</td><td>-2</td><td></td><td>-2</td><td>1,5</td><td></td><td>-2</td><td></td><td></td></tr><tr><td>Aldolase C</td><td></td><td>-3</td><td></td><td>3,1</td><td></td><td>1,8</td><td>-2</td><td></td></tr><tr><td>GAPDH</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Phosphoglycerate kinase</td><td>-2</td><td></td><td>-2</td><td></td><td>-2</td><td></td><td>-2</td><td></td></tr><tr><td>Phosphoglycerate mutase</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Enolase 2</td><td>-4</td><td>-2</td><td>-4</td><td>1,9</td><td>-4</td><td>-4</td><td>-4</td><td>-2</td></tr><tr><td>Pyruvate kinase</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><th>Pyruvate transporters</th><th>A1</th><th>A2</th><th>A3</th><th>A4</th><th>A5</th><th>A6</th><th>A7</th><th>A8</th></tr><tr><td>SLC16A9</td><td></td><td></td><td>-2</td><td>-2</td><td>5,2</td><td>-4</td><td></td><td>1,6</td></tr><tr><td>SLC16A14</td><td>-2</td><td>-3</td><td>-2</td><td>-5</td><td></td><td>-14</td><td>-2</td><td>-4</td></tr></tbody></table>

B

<figure><img src="image_13.png" /></figure>

C

<figure><img src="image_14.png" /><figcaption>**Fig. 3.** Altered expression of glycolysis-associated transcripts in olfactory stem cells. (A) Results for all transcripts involved in glycolysis. Each ASD patient was compared to the mean values of 8 control individuals. The cut-off value for fold change was set at ±1.5. (B) Box plots demonstrating the underexpression of the transporters SLC2A1 and SLC16A14 in the ASD arm of the cohort. (C) Schematic view of the altered expression of transcripts encoding proteins involved in glycolysis. The cut-off value for fold change was set at ±1.5. The tone of each color correlates with the number of concerned patients. Green: under-expression; orange: over-expression; white: -1,5 > expression < +1,5.</figcaption></figure>

expression of DRP1, a marker of mitochondrial fission. Conversely, Fig. 4J and K show an under-expression of OPA1, a marker of mitochondrial fusion. Similar results are obtained when these proteins are compared to actin.

An accumulation of metals in cells exhibiting the highest production rate of mitochondrial
ATP

Out of the 49 chemical elements analyzed, 24 (Cerium, Dysprosium, Eribium, Europium, Gadolium, Hafnium, Holmium, Lanthanum, Lutetium, Mercury, Neodymium, Nickel, Niobium, Praseodymium, Samarium, Scandium, Silver, Terbium, Thullium, Tin, Tungsten, Ytterbium, Yttrium, Zirconium), were not measurable, in all but one individual. The latter, an ASD patient, distinguished himself by accumulating hafnium, nickel, niobium, tungsten, zirconium in his cells. With regard to the other 25 chemicals (Aluminium, Antimony, Arsenicum, Baryum, Berrylium, Bismuth, Cadmium, Cesium, Chromium, Cobalt, Copper, Gallium, Iron, Lead, Lithium, Magnesium, Manganese, Molybdenum, Rubidium, Selenium, Strontium, Thallium, Titanium, Vanadium, Zinc), no significant group differences are observed. However, increased amounts of cobalt, copper iron, magnesium, selenium and zinc are observed in the cells of 3 to 5 ASD patients (Supplementary Fig. 2). Interestingly, in this subpopulation of 5 individuals, 4 of them have the highest rate of mitochondrial ATP production.

Discussion

Using stem cells as a mean to assess disturbances arising during the first steps of ontogeny, the current study demonstrates that, when compared with those of control individuals, cells from ASD patients exhibit (i) a diminished expression/abundance of glycolysis-associated transcripts and metabolites, (ii) an overall reduced ATP production, (iii) a lessened basal cell respiration and (iv) a modified mitochondrial network. These results mostly confirm previously published research.

Transcriptome and metabolome both indicate a reduced glycolysis

Anomalies in the carbohydrate metabolism was described as early as 1985 when a publication described a co-
occurrence of lactic acidosis and autism spectrum disorders in 4 young patients²⁶. Interestingly, the excess
of lactic acid was also associated in one out of four individuals with hyperuricosuria and hyperuricemia.
Subsequently, numerous studies reported elevated levels of lactate and pyruvate and a disturbed production of
<figure><img src="image_15.png" /><figcaption>**Fig. 4.** Dynamics of mitochondria. (A, B) Examples of mitochondria networks labelled with the mitotracker fluorochrome, in control individual (A) and ASD patient (B), scale bar 10 µm. (C–F) Graph bars showing a statistically significant increase in mitochondrial area (C), mitochondrial content (D), number of punctate mitochondria (E) but not in number of mitochondria (F) in the ASD arm of the cohort (6 patients) when compared with the controls (6 individuals). (G) Examples of protein detection (DRP1 and OPA1) using the western blot technique in both arms of the cohort. (H, I) ASD stem cells express more abundantly the DRP1 protein involved in mitochondrial fission. (J, K) ASD stem cells express less abundantly the OPA1 protein involved in mitochondrial fusion. Similar results are obtained when these proteins are compared to actin.
* = p < 0.05.</figcaption></figure>

enzymes associated with these metabolites in serum, plasma, urine, fibroblasts and brain<sup>12,15,22,27-32</sup>. However, the rate of variation of each of these potential biomarkers varies greatly from one study to another, ranging from 17 to 77%<sup>29,30</sup>. Nevertheless, we still need to understand the discrepancy between the results of all these studies, which indicate an increase in lactate and pyruvate, and those of our study, which report a decrease in pyruvate in all ASD patients and a mixed variation (overabundance in 3 patients and deficiency in 3 others).

It can be conjectured that an excess of pyruvate in biological fluids reflects either excessive secretion or low input of this metabolite by the cells, leading to an intracellular deficit, as suggested in the current study by the misexpression of transcripts coding for SLC16A9 and SLC16A14, two pyruvate transporters. Only one previous study assessed the quantity of intracellular lactate and pyruvate in fibroblasts and found an increase in the lactate/pyruvate ratio<sup>12</sup>. The authors do not give the values for each metabolite, but it is conceivable that the increase in this ratio is partly associated with a decrease in pyruvate production. Furthermore, a decrease in pyruvate dehydrogenase activity has been observed in the prefrontal cortex of ASD patients<sup>17</sup>, leading us to imagine either a reduced abundance of upstream pyruvate or a mutation in the gene that would affect the protein's functionality.

At the transcriptome level, we observed an under-expression of many glycolysis-related genes all along the pathway. At one end, we noticed a misexpression, usually an under-expression, of at least 2 of 4 glucose transporters in every patient. This finding is consistent with studies describing a link between neurodevelopmental disorders, including ASD, and gene anomalies, namely variants or deletions<sup>33-38</sup>. However, at the other end, no previous study reported an association between ASD and molecular anomalies for SLC16A9 and SLC16A14, two pyruvate transporters.

Between these two ends, a misexpression of 6 of the 9 transcripts encoding glycolysis-associated proteins was detected in our ASD cohort. Confirmation can be found in previous studies describing a reduced production of the protein hexokinase 2<sup>39</sup> but, more importantly, enolase 2, whose expression is altered in all patients in our cohort, and which is considered by some researchers to be a potential biomarker of ASD<sup>40,41</sup>. In a preliminary proteomic study, based on stem cells of 6 ASD patients and 6 control individuals of our cohort, we observed a misexpression (4 down and 2 up) of the protein ENO2 (data not shown). ENO2 hypermethylation was first found in peripheral blood cells from a cohort of 131 age- and sex-matched pairs of ASD subjects and controls in 15% of ASD patients. This gene alteration led to a reduced abundance (70 and 50%, respectively) of the transcript and protein<sup>42</sup>. Interestingly, this lower intracellular production of enolase is mirrored by a higher abundance in the serum of ASD neonates<sup>43</sup> and ASD children<sup>40,41,44</sup>. However, it must be noted that one study failed to find a significant difference in serum ENO2 between ASD patients and healthy individuals<sup>45</sup>.

## A disrupted biosynthesis of carnitine

As described above, we observed a discrepancy between the lesser abundance of α-ketoglutarate within ASD olfactory stem cells and the upper amount of the same metabolite in a body fluid, namely urine<sup>46</sup> of ASD patients.
Once again, it may be surmised that these divergent results are the consequence of uncontrolled flux of the molecule out of the cell. In any case, according to our metabolic data, it seems that the abnormal production of this acid is predominantly associated with the carnitine biosynthesis pathway and not with the citric acid cycle (Krebs cycle). In fact, stem cells of all ASD patients show a disturbed abundance of at least 4 of the 7 measured carnitine-related molecules. Apart from ketoglutarate and ascorbic acid, which are always less abundant, the other 5 metabolites display a variable balance between higher and lower quantities.

As reported in a review⁴⁷, reduced serum total and free carnitine has been observed in ASD patients⁴⁸, an important finding since this molecule participates to the transport of long-chain fatty acids from the cytosol into the mitochondria. In a large cohort of 213 individuals, 17% of ASD children were found to have elevated in short-chain and long-chain acyl-carnitines⁴⁹. In addition, the imbalance in carnitine biosynthesis is supported by several genetic anomalies. One team, using two different technical approaches, unveiled exonic copy number variants in the genome of ASD patients and identified in a male proband a deletion of TMLHE (trimethyllysine hydroxylase epsilon), the gene that codes for the first enzyme in the biosynthesis of carnitine, located in mitochondria⁵⁰,⁵¹. Homozygous mutations in the gene encoding SLC7A5, an amino acid transporter capable of transporting carnitine, have also been observed in several ASD patients⁵².

A proven carnitine deficiency in some patients suggests that certain symptoms could be improved by supplementation. This was tested in three clinical trials in ASD patients with unknown genetic causes and non-syndromic forms of the disease (for a review⁵³). Two assessment scales—CARS (childhood autism rating scale) and CGIS (clinical global impression scale)—were mainly used to evaluate the course of the disorders. The first trial, randomized placebo-controlled with a dose of 50 mg/kg/day, lasted 3 months and demonstrated an improvement in symptoms, according to the CARS and CGIS, correlated with the level of carnitine in the serum⁵⁴. The second trial, also randomized placebo-controlled but with a dose of 100 mg/kg/day, lasted 6 months and reported an improvement in symptoms according to the CARS criteria but did not observe a link with circulating carnitine levels⁵⁵. The last trial, an open label trial with a dose of 200 mg/kg/day, lasted 8 weeks and observed an improvement according to the CGIS scale⁵⁶.

## A lower abundance of ATP

Our metabolomic data indicate a deficiency of adenine and adenosine diphosphate (ADP) in 8 and 6 ASD patients, respectively. No result being available for adenosine triphosphate (ATP), we measured its production with the Seahorse equipment and protocols. As highly proliferating cells and similarly to cancer cells, stem cells rely primarily on glycolysis, instead of oxidative phosphorylation (OXPHOS), to produce energy from glucose. This metabolic shift is known as the “Warburg effect”⁵⁷ and can be visualized on Fig. 2C. As posited by the altered glycolysis in ASD stem cells described above, a reduced amount of ATP produced by this pathway was observed, a finding consistent with a study showing that cerebral organoids derived for ASD patients exhibit a predominance of glycolysis over OXPHOS and reduced ATP production⁵⁸. Nonetheless, it should be noted that such findings depend on the context and, possibly, the cell type. For example, when faced with acute increases in reactive oxygen species, lymphoblastoid cell lines augment glycolytic reserve⁵⁹.

To compensate for this lack of energy supplied by glucose metabolism, olfactory stem cells produce more ATP through oxidative phosphorylation. However, as this cell type relies heavily on glycolysis for energy, overall ATP production remains deficient. In other cell types, the picture is different. Reduced activity of at least 3 of the 5 respiratory complexes has been observed in muscle cells¹²,⁶⁰,⁶¹ and in lymphoblasts¹⁰ whereas only abnormalities of complex I have been reported in plasma⁶². To explain these discrepancies, the time factor must also be considered. For example, diminished activities of various respiratory complexes were found in different brain areas – cerebellum, frontal, parietal, occipital and temporal cortexes – of young children (4–10 years of age) but not in adults (14–39)⁶³.

The ability of olfactory stem cells to partially remedy their ATP deficit associated with defective glycolysis results from their remarkable mitoplasticity. Thanks to special mitochondrial dynamics, favourable to fission and unfavourable to fusion, cells from ASD patients increased their mitochondrial area and enhanced their ability to produce energy via the electron transport chain. Unsurprisingly, our transcriptomic data indicate an exacerbated expression of genes encoded by mitochondria in ASD cells, with a special mention for NT-ND6 whose expression is on average doubled when compared with control cells (data not shown). Similarly, smaller more fragmented mitochondria were observed in the black and tan, brachyury (BTBR) mouse model of ASD⁶⁴. Atypical mitochondria morphology was also observed in ASD fibroblasts⁶⁵. In other words, mitoplasticity may represent one of the compensatory mechanisms by which ASD cells attempt to adapt to altered energy supply and need.

## A diminished basal respiration

A relatively small number of studies investigated cellular respiration in ASD patients. It was first demonstrated that, at baseline and after exposure to reactive oxygen species, lymphoblastoid cell lines from some children with ASD increase ATP-linked respiration as well as maximal and reserve respiratory capacity⁵⁹,⁶⁶,⁶⁷. The same research group, comparing serum microRNAs between healthy individuals and ASD patients, observed negative correlations between miRNA levels and mitochondrial respiration in a subgroup of patients⁶⁸. In agreement with the former findings, higher respiratory capacities and complex IV activity were reported in a lymphoblastoid cell line derived from an autistic child⁶⁹. Finally, peripheral blood mononuclear cells indicate that patients with ASD have increased respiratory reserve capacity and maximal respiration⁷⁰.

In our study, maximal respiration and spare respiratory capacity are not exacerbated while basal respiration and proton leak are reduced. The cause of these anomalies is not the consequence of a defective expression of gene families – NDUFs (complex I), SDHs (complex II), UQCRs (complex III), COXs (complex IV), ATP5s (complex V) – associated to oxidative phosphorylation since, according to our transcriptomic data, no difference
was observed between ASD patients and control individuals. However, more than the quantity of proteins, it is perhaps their quality that is at stake in this metabolic pathway. Sequencing of the genomes of the 8 autistic patients (data not shown) indicates that they suffer from exonic frameshift deletions in several genes coding for proteins involved in oxidative phosphorylation. Of note, the cells of patients 3, 7 and 8 that display the most altered basal respiration are also those that are affected by the most numerous exonic frameshift deletions -9, 10 and 10 respectively—in complexes IV and V. However, in the absence of a precise assessment of the functional consequences of these deletions, all this remains highly speculative.

## A subpopulation with an overload of eight metals

Numerous studies highlighted a dyshomeostasis of several toxic and essential elements in the ASD population (for recent reviews$^{71-73}$). The results vary according to the analysed tissue – blood, hair, nails, urine – and discordant findings are sometimes observed. However, there is an overall evidence for an association between ASD and, on the one hand, iron, magnesium, zinc deficiency and, on the other hand, copper excess$^{72}$. Conversely, in our study, stem cells from a sub-group of 3–5 ASD patients show increased levels of copper but also of cobalt, iron, magnesium, selenium and zinc. These discordant findings suggest that metal deficiency or excess within the blood may result from enhanced or reduced intracellular concentration. For example, concentrations of copper, magnesium and zinc were found to be higher in the hair cells of ASD patients and not in body fluids for magnesium and zinc$^{74}$.

In the current study, stem cells that accumulate trace elements are those that produce high levels of mitochondrial ATP. This correlation could also be causal. For example, copper is needed for the proper functioning of the electron transport chain$^{75,76}$. This metal is also a cofactor of the copper/zinc superoxide dismutase, a mitochondrial protein that regulates the amount of radical oxygen species generated by oxidative phosphorylation$^{77}$. In addition, copper is a cofactor of ferroxidases and its action is associated with iron uptake$^{78}$, a metal that plays a key role in heme biosynthesis$^{79}$. Similarly, magnesium is required for the activation of copper and zinc superoxide dismutase$^{80}$. Finally, cobalt and selenium are important for neutralizing the deleterious effects of free radicals. However, these two metals are not directly associated with mitochondrial functioning.

## Limits of the study

For the current study and two previous ones, we analyzed stem cells in order to be as close as possible to the first stages of development. However, these cells are highly proliferative and display an unlike metabolism to differentiated cells. This has positive aspects. For example, due to a particularly high level of glycolysis, we were able to demonstrate a defect in ATP production associated with this metabolic pathway. However, this phenomenon should be marginal in cells in which glycolytic ATP represents 7% rather than 70% of the total production of energy molecules.

The reasons for this disturbed glycolysis probably need to be sought at the genomic level. Following sequencing of the genome of stem cells from the cohort of autistic patients, we looked for a possible mutation in the exons of the gene coding for enolase 2, a gene whose transcription is strongly disrupted in all ASD patients. However, we did not observe any such mutation. We therefore need to look for a possible methylation defect in the promoter region of this gene. This experiment is all the more necessary as a study has shown such a phenomenon in peripheral blood cells$^{42}$.

Undoubtedly, the current study is weakened by the small size of the cohort and the findings should be regarded as preliminary, requiring confirmation in larger, independent cohorts. Furthermore, although easily accessible in a healthy, compliant subject, nasal olfactory stem cells are not straightforwardly collected in ASD patients. To confirm our results and possibly use them as biomarkers, it is important to conduct a similar study on peripheral blood cells with a larger cohort of individuals. It would also be interesting to compare the two sexes in order to study any discrepancy.

## Materials and methods

### Culture of human olfactory ecto-mesenchymal stem cells

The current study is a follow up of two previous works$^{3,4}$ based on biopsies from healthy donors and ASD patients. The medical profile of ASD patients has been previously published in a princeps article$^{3}$: the 8 individuals monitored during the current study correspond to the lines 1,2,3,4,7,8,9,11. Procedures were approved by the ethical committee (Comité de Protection des Personnes, files #205016 and #205017). All individuals involved in this study provided informed consent in accordance with the Declaration of Helsinki and French laws relating to biomedical research$^{3,4}$. For the current study, we chose to select 8 ASD patients with the most severe symptoms, i.e. individuals classified as level 3, and 8 age- and sex-matched healthy individuals. According to the DSM-5, those at this level need a great deal of support. In our cohort, 8 of the 11 individuals fall into this category.

Olfactory ecto-mesenchymal stem cells (OE-MSC) were cultivated in proliferating conditions, using DMEM/HAM F12 culture medium (Life Technologies) supplemented with 10% fetal calf serum (Life Technologies) and penicillin/streptomycin (1%) (Life Technologies).

### Metabolome analysis

OE-MSCs from 8 ASD patients and 6 control subjects were incubated with 400 µL of cold methanol (–20 °C) for 30 min, before centrifugation and filtration to remove residual proteins from the samples. After drying under a stream of nitrogen, the dry extract was taken up in 250 µL of a water/acetonitrile mixture (9/1, v/v). Samples were separated using UPLC Ultimate 3000 (Thermo Scientific), coupled to a Q-Exactive Plus quadrupole orbitrap hybrid high-resolution mass spectrometer (HRMS) equipped with an electrospray ionisation source (H-ESI II). Chromatographic separation was carried out on a binary solvent system using two columns, with specific conditions for each. The mass spectrometer was calibrated in positive and negative mode using two
calibration solutions and a solution composed of caffeine, n-butylamine, MRFA (peptide) and Ultramark 1621. Calibration in negative mode was carried out using a solution composed of sodium dodecyl sulphate, a solution of taurocholate and Ultramark 1621. The molecules separated by chromatography were analysed in positive and negative ionisation mode in the same cycle. Mass spectra were recorded using a resolution of 35,000 FWHM for a theoretical mass-to-charge ratio (m/z) of 200. To ensure good analytical repeatability, quality control (QC) samples were prepared by taking an equal amount from each biological sample.

From the list of 187 metabolites identified, two ratios – A/B and 1/(A/B) – were calculated where A corresponds to the quantity of metabolite X for every ASD patient and B corresponds to the mean quantity of the same metabolite in the control population. The cut-off value for fold change was set at ±1.5. The first ratio identifies any higher or lower abundance of metabolites in every patient while the second ratio reflects the percentage associated with these changed concentrations. Only metabolites with an altered abundance in at least 4 ASD patients were used for further analysis.

## Transcriptome analysis

Each RNA sample was quantified on Nanodrop and quality was examined on the Fragment Analyzer (Agilent). 2 µg of total RNA from 16 samples of human (RIN > 9) were used as the starting material in the TruSeq Stranded mRNA Illumina kit according to the manufacturer's instructions. Each library was barcoded using TruSeq_RNA_LT Indexes (Illumina), according to manufacturer's instructions (A001 to A017).

Each library was quantified on Qubit with Qubit® dsDNA HS Assay Kit (Life Technologies) and then, size distribution was examined on the Fragment Analyzer with High Sensitivity NGS Fragment Analysis kit (Agilent), to ensure that the samples were the proper size, no adaptor contamination, and to estimate the sample molarity. Each library was diluted to 4 nM and then pulled together at equimolar ratio. The denaturation was performed with 5 µL of pooled libraries (4 nM) and 5 min incubation with 5 µL of fresh NaOH (0.2N) and then addition of 5 µL of fresh Tris-HCl (200 mM—pH 7), according to manufacturer's instructions.

The dilution of 20 pM pooled libraries was performed with HT1 to a 1.6 pM final concentration.

PhiX library as a 1% spike-in for use as a sequencing control was denatured and diluted, according to manufacturer's instructions, and 1,2 µL was added to denatured and diluted pooled libraries before loading. Finally, libraries were sequenced on a High-output flow cell (400 M clusters) using the NextSeq® 500/550 High Output 150 cycles kit (Illumina), in paired-end 76/76 nt mode, according to manufacturer's instructions.

## ATP quantification

Cellular bioenergetics were measured using the Seahorse XF Cell Mito Stress Test kit, which quantifies the oxygen consumption and ATP production, as previously described by the team⁸¹. Briefly, OE-MSCs were plated, at the density of 15,000 c/well, on 24-well seahorse plates in DMEM/HAM medium a night prior to analysis. Oxygen consumption rate (OCR) after addition of oligomycin (1 µM) was used to estimate the rate of ATP production. Carbonyl cyanide-4-trifluoromethoxy phenylhydrazone (FCCP, 0.5 µM) was added to assess the maximal mitochondrial respiratory capacity. The flux of electrons through complex III and I was blocked with antimycin A (0.5 µM) and rotenone (0.5 µM), respectively. Any residual activity in the presence of these inhibitors was considered as non-mitochondrial OCR. Results were normalized to the number of cells, using a high content screening microscope (Operetta, CLS, Perkin Elmer). Cells from 8 ASD patients and 8 control individuals were analysed.

## Fluorescent labelling of mitochondria

OE-MSCs from control subjects and ASD patients, seeded on glass coverslips, were incubated for 15 min at 37 °C with Mitotracker™ Red CMXRos (50 nM, ThermoFisherScientific) and 1:500 Hoechst blue (ThermoFisher). After rinsing with PBS, cells were fixed with 4% paraformaldehyde for 10 min and rinsed three times with PBS. The coverslips were then mounted on slides with a glue containing ProLong™Gold antifade reagent (ThermoFisher), which limits the loss of fluorescence. Mitochondrial markings were visualised and digitised using confocal microscope (inverted Zeiss Axio Observer Z1 LSM700) equipped with a ×63 (NA 1.4) oil, Plan-Apochromat objective (Zeiss). Cells from 6 ASD patients and 6 control individuals were labelled.

## Analysis of mitochondrial network

The confocal images needing to be improved for increased sharpness, an image processing was adapted from the work of Valente et al. 2017 and Merrill et al. 2017⁸²,⁸³. They were transformed into binary images that were analysed using the “Mitochondrial Morphology” macro-keyboard of Fiji software (https://fiji.sc/), which measures, among other things, mitochondrial interconnectivity and elongation. From the binary image, the ImageJ software allowed to obtain an image of the mitochondrial skeleton, analysed by the ‘Analyze Skeleton’ macro-keyboard, which counts the different mitochondrial elements and branches, with their average and maximum size. Mitochondria were classified according to their organisation, shape and size. Organised in a network or isolated (individual mitochondria), three forms can be distinguished: punctate mitochondria, large/ round mitochondria and rod mitochondria.

## Western blot of proteins involved in fusion/fission of mitochondrial network

Proteins were extracted from 12 OE-MSC pellets (n=6 ASD patients and 6 control subjects). Cells were mechanically lysed using a solution composed of RIPA buffer (Sigma-Aldrich) and 1/100 protease inhibitors (Calbiochem). After 30 min of incubation at 4 °C, followed by sonication (2 min), protein concentrations were determined by a Lowry assay (DC™ Protein Assay, BioRad) and protein samples were stored at –20 °C until use. For SDS-PAGE electrophoreses, 50 µg of protein samples were denatured in 2X Laemmli buffer (Bio Rad) and heated at 95 °C for 5 min. Denatured protein samples were separated on a 12% SDS-PAGE polyacrylamide gel
for 120 min at a constant 0.07 Ampere per gel. Proteins were transferred with the PowerBlotter XL (Invitrogen by ThermoFisher Scientific) onto nitrocellulose membranes (Amersham™ Protran™ Premium 0.2 µm, GE Healthcare), using the Standard Semidry protocol (25 V constant, 0.2A for 60 min) with transfer buffer (0.25 M Tris, 1.92 M glycine, 200 mL methanol and 700 mL osmosed water at pH 8.3). For immunodetection, the non-specific sites were saturated by incubation at room temperature with agitation for 90 min in a solution of 1X PBS/5% milk/0.2% Tween (TWEEN®20, Sigma-Aldrich). The membranes were then incubated overnight at 4 °C in a humidity chamber with the primary antibody diluted in PBS 1X/milk 5%/Tween 0.2%. The following day, after 3 washes with PBS 1X/Tween 0.2%, the membranes were incubated with the peroxidase-coupled secondary antibody (HRP), raised against GAPDH or actin, diluted in PBS 1X/5% milk/Tween 0.2%, at room temperature, under agitation for 80 min. After washing with PBS 1X/Tween0.2%, the proteins of interest were revealed by chemiluminescence using the ECL WesternBlot detector kit (GE Healthcare) and the results were digitised in a UVITEC11Photo Imager (Ubitec Photoimager, Dutscher) using Nine Alliance software (Alliance®Software, UVITEC). For relative quantification, the optical density (OD) of each immunodetected protein band was measured using Fiji software (National Institutes of Health—https://imagej.net/Fiji) and normalised to the OD of the GAPDH band.

## Quantification of metal content

Stem cell pellets from individuals of the whole cohort were lysed and the quantity of 49 metal elements was determined by ICP-MS after microwave acidic mineralization, strictly following the procedure detailed previously (Geoffrey Siraudin et al, 2010) with detection limits of 0.01 ng per million cells for each element. The final measurement is expressed in ng per million cells.

## Statistics

All statistics are presented as mean ± 1 standard error of the mean (SEM). All distributions were tested for normality (Shapiro-Wilk test, significant at 0.05) and homogeneity of variance (Fisher test, significant at 0.05) prior to analysis. Based on the results of these initial tests, the comparisons were carried out either with Student's t-test (normal distribution and homogeneity of variances) or its variant Welch corrected t-test (normal distribution and heterogeneity of variances) or with the Mann-Whitney test (non-normal distribution). The significance scores are: * for p < 0.05, ** for p < 0.01 and *** for p < 0.001. A difference was considered significant if the p-value was less than 0.05. All statistical analyses were carried out using GraphPad Prism software version 8.4.0 for OS X, GraphPad Software, San Diego, California, USA, www.graphpad.com.

## Data availability

Transcriptome data that support the findings of this study have been deposited in the Biostudies Archive with the primary accession code S-BSST1665. Data can be viewed at **:** [**https://www.ebi.ac.uk/biostudies/studie s/S-BSST1665?key=2ed7cedb-3b75-4278-973d-e6ea55299bbb**].

Received: 14 October 2024; Accepted: 26 September 2025

Published online: 03 November 2025

## References

1. Hahler, E.-M. & Elsabbagh, M. Autism: A global perspective. *Curr. Dev. Disord. Rep.* **2**, 58–64 (2015).

2. Delorme, B. et al. The human nose harbors a niche of olfactory ectomesenchymal stem cells displaying neurogenic and osteogenic properties. *Stem Cells Dev.* **19**, 853–866 (2010).

3. Féron, F. et al. Olfactory stem cells reveal MOCOS as a new player in autism spectrum disorders. *Mol. Psychiatry* **21**, 1215–1224 (2016).

4. Rontani, P. et al. Impaired expression of the COSMOC/MOCOS gene unit in ASD patient stem cells. *Mol. Psychiatry* **26**, 1606–1618 (2021).

5. Mendel, R. R. & Kruse, T. Cell biology of molybdenum in plants and humans. *Biochim. Biophys. Acta (BBA) Mol. Cell Res.* **1823**, 1568–1579 (2012).

6. Mendel, R. R. & Schwarz, G. The history of animal and plant sulfite oxidase—a personal view. *Molecules* **28**, 6998 (2023).

7. Bortolotti, M., Polito, L., Battelli, M. G. & Bolognesi, A. Xanthine oxidoreductase: One enzyme for multiple physiological tasks. *Redox Biol.* **41**, 101882 (2021).

8. Struwe, M. A., Scheidig, A. J. & Clement, B. The mitochondrial amidoxime reducing component—from prodrug-activation mechanism to drug-metabolizing enzyme and onward to drug target. *J. Biol. Chem.* **299**, 105306 (2023).

9. Nabi, S. U. et al. Treatment of autism spectrum disorders by mitochondrial-targeted drug: Future of neurological diseases therapeutics. *Curr. Neuropharmacol.* **21**, 1042–1064 (2023).

10. Giulivi, C. et al. Mitochondrial dysfunction in autism. *JAMA* **304**, 2389–2396 (2010).

11. Levinger, L., Giegé, R. & Florentz, C. Pathology-related substitutions in human mitochondrial tRNAle reduce precursor 3' end processing efficiency in vitro. *Nucleic Acids Res.* **31**, 1904–1912 (2003).

12. Weissman, J. R. et al. Mitochondrial disease in autism spectrum disorder patients: A cohort analysis. *PLoS ONE* **3**, e3815 (2008).

13. Napoli, E. et al. Array-CGH analysis in a cohort of phenotypically well-characterized individuals with “essential” autism spectrum disorders. *J. Autism Dev. Disord.* **48**, 442–449 (2018).

14. Hadjixenofontos, A. et al. Evaluating mitochondrial DNA variation in autism spectrum disorders. *Ann. Hum. Genet.* **77**, 9–21 (2013).

15. Haas, R. H. Autism and mitochondrial disease. *Dev. Disabil. Res. Rev.* **16**, 144–153 (2010).

16. Boddaert, N. et al. MRI findings in 77 children with non-syndromic autistic disorder. *PLoS ONE* **4**, e4415 (2009).

17. Gu, F. et al. Alterations in mitochondrial DNA copy number and the activities of electron transport chain complexes and pyruvate dehydrogenase in the frontal cortex from subjects with autism. *Transl. Psychiatry* **3**, e299–e299 (2013).

18. Anitha, A. et al. Brain region-specific altered expression and association of mitochondria-related genes in autism. *Mol. Autism* **3**, 12 (2012).

19. Anitha, A. et al. Downregulation of the expression of mitochondrial electron transport complex genes in autism brains. *Brain Pathol.* **23**, 294–302 (2012).
20. Rossignol, D. A. & Frye, R. E. Mitochondrial dysfunction in autism spectrum disorders: a systematic review and meta-analysis. *Mol. Psychiatry* **17**, 290–314 (2012).

21. Suomalainen, A. et al. FGF-21 as a biomarker for muscle-manifesting mitochondrial respiratory chain deficiencies: a diagnostic study. *Lancet Neurol.* **10**, 806–818 (2011).

22. Filippek, P. A. et al. Mitochondrial dysfunction in autistic patients with 15q inverted duplication. *Ann. Neurol.* **53**, 801–804 (2003).

23. Legido, A. *Effect of a Combination of Carnitine, Coenzyme Q10 and Alpha-Lipoic Acid (MitoCocktail) on Mitochondrial Function and Neurobehavioral Performance in Children with Autism Spectrum Disorder* (IMFAR, 2018).

24. Adams, J. B. et al. The severity of autism is associated with toxic metal body burden and red blood cell glutathione levels. *J. Toxicol.* **2009**, e532640 (2009).

25. Borrás, C. et al. Mitochondria from females exhibit higher antioxidant gene expression and lower oxidative damage than males. *Free Radic. Biol. Med.* **34**, 546–552 (2003).

26. Coleman, M. & Blass, J. P. Autism and lactic acidosis. *J. Autism Dev. Disord.* **15**, 1–8 (1985).

27. Ramirez-Barbieri, G. et al. Alloreactivity and allorecognition of syngeneic and allogeneic mitochondria. *Mitochondrion* **46**, 103–115 (2019).

28. Picard, M., Wallace, D. C. & Burelle, Y. The rise of mitochondria in medicine. *Mitochondrion* **30**, 105–116 (2016).

29. László, A., Horváth, E., Eck, E. & Fekete, M. Serum serotonin, lactate and pyruvate levels in infantile autistic children. *Clin. Chim. Acta* **229**, 205–207 (1994).

30. Arnold, G. L., Hyman, S. L., Mooney, R. A. & Kirby, R. S. Plasma amino acids profiles in children with autism: Potential risk of nutritional deficiencies. *J. Autism Dev. Disord.* **33**, 449–454 (2003).

31. Goh, S., Dong, Z., Zhang, Y., DiMauro, S. & Peterson, B. S. Brain imaging evidence that mitochondrial dysfunction is a neurobiological subtype of autism spectrum disorder. *JAMA Psychiat.* **71**, 665–671 (2014).

32. El-Ansary, A. K., Ben Bacha, A. G. & Al-Ayadhi, L. Y. Proinflammatory and proapoptotic markers in relation to mono and diations in plasma of autistic patients from Saudi Arabia. *J. Neuroinflamm.* **8**, 142 (2011).

33. Mellone, S. et al. The usefulness of a targeted next generation sequencing gene panel in providing molecular diagnosis to patients with a broad spectrum of neurodevelopmental disorders. *Front. Genet.* **13**, 875182 (2022).

34. Mir, A. et al. SLC gene mutations and pediatric neurological disorders: diverse clinical phenotypes in a Saudi Arabian population. *Hum. Genet.* **141**, 81–99 (2022).

35. López-Rivera, J. A. et al. A catalogue of new incidence estimates of monogenic neurodevelopmental disorders caused by de novo variants. *Brain* **143**, 1099–1105 (2020).

36. Lee, B. H., Smith, T. & Paciorkowski, A. R. Autism spectrum disorder and epilepsy: disorders with a shared biology. *Epilepsy Behav.* **47**, 191–201 (2015).

37. Redin, C. et al. Efficient strategy for the molecular diagnosis of intellectual disability using targeted high-throughput sequencing. *J. Med. Genet.* **51**, 724–736 (2014).

38. Srour, M. et al. Dysfunction of the cerebral glucose transporter SLC45A1 in individuals with intellectual disability and epilepsy. *Am. J. Hum. Genet.* **100**, 824–830 (2017).

39. Meyyazhagan, A. et al. Scrutinizing the molecular, biochemical, and cytogenetic attributes in subjects with Rett syndrome (RTT) and their mothers. *Epilepsy Behav.* **111**, 107277 (2020).

40. Stancioiu, F., Bogdan, R. & Dumitrescu, R. Neuron-specific enolase (NSE) as a biomarker for autistic spectrum disease (ASD). *Life* https://doi.org/10.20944/preprints202306.0050.v1 (2023).

41. Ramirez-Celis, A., Edmiston, E., Schauer, J., Vu, T. & Van de Water, J. Peptides of neuron specific enolase as potential ASD biomarkers: From discovery to epitope mapping. *Brain Behav. Immun.* **84**, 200–208 (2020).

42. Wang, Y. et al. Hypermethylation of the enolase gene (ENO2) in autism. *Eur. J. Pediatr.* **173**, 1233–1244 (2014).

43. Lv, M. et al. The neonatal levels of TSB, NSE and CK-BB in autism spectrum disorder from Southern China. *Transl. Neurosci.* **7**, 6–11 (2016).

44. Ayaydin, H. et al. High serum levels of serum 100 beta protein, neuron-specific enolase, tau, active caspase-3, M30 and M65 in children with autism spectrum disorders. *Clin. Psychopharmacol. Neurosci.* **18**, 270–278 (2020).

45. Esnafoglu, E. et al. Evaluation of serum Neuron-specific enolase, S100B, myelin basic protein and glial fibrillary acidic protein as brain specific proteins in children with autism spectrum disorder. *Int. J. Dev. Neurosci.* **61**, 86–91 (2017).

46. Harutyunyan, A. A., Harutyunyan, H. A. & Yenkoyan, K. B. Novel Probable glance at inflammatory scenario development in autistic pathology. *Front. Psychiatry* **12**, 788779 (2021).

47. Demarquoy, C. & Demarquoy, J. Autism and carnitine: A possible link. *World J. Biol. Chem.* **10**, 7–16 (2019).

48. Filippek, P. A., Juranek, J., Nguyen, M. T., Cummings, C. & Gargus, J. J. Relative carnitine deficiency in autism. *J. Autism Dev. Disord.* **34**, 615–623 (2004).

49. Frye, R. E. et al. Effectiveness of methylcobalamin and folinic acid treatment on adaptive behavior in children with autistic disorder is related to glutathione redox status. *Autism Res. Treat.* **2013**, 609705 (2013).

50. Celestino-Soper, P. B. S. et al. Use of array CGH to detect exonic copy number variants throughout the genome in autism families detects a novel deletion in TMLHE. *Hum. Mol. Genet.* **20**, 4360–4370 (2011).

51. Celestino-Soper, P. B. S. et al. A common X-linked inborn error of carnitine biosynthesis may be a risk factor for nondysmorphic autism. *Proc. Natl. Acad. Sci. U. S. A.* **109**, 7974–7981 (2012).

52. Tarlungeanu, D. C. et al. Impaired amino acid transport at the blood brain barrier is a cause of autism spectrum disorder. *Cell* **167**, 1481–1494.e18 (2016).

53. Malaguarnera, M. & Cauli, O. Effects of l-carnitine in patients with autism spectrum disorders: Review of clinical studies. *Molecules* **24**, 4262 (2019).

54. Geier, D. A. et al. A prospective double-blind, randomized clinical trial of levocarnitine to treat autism spectrum disorders. *Med. Sci. Monit.* **17**, PI15-23 (2011).

55. Fahmy, S. F., El-hamamsy, M. H., Zaki, O. K. & Badary, O. A. l-Carnitine supplementation improves the behavioral symptoms in autistic children. *Res. Autism Spectrum Disord.* **7**, 159–166 (2013).

56. Goin-Kochel, R. P. et al. Side effects and behavioral outcomes following high-dose carnitine supplementation among young males with autism spectrum disorder: A pilot study. *Glob. Pediatric Health* **6**, 2333794X19830696 (2019).

57. Warburg, O. On the origin of cancer cells. *Science* **123**, 309–314 (1956).

58. Ilieva, M. & Uchida, S. Functional roles of epitranscriptomic marks in the cardiovascular system and disease: a narrative review. *Ann. Transl. Med.* **10**, 753 (2022).

59. Rose, S. et al. Mitochondrial and redox abnormalities in autism lymphoblastoid cells: a sibling control study. *FASEB J.* **31**, 904–909 (2017).

60. Filiano, J. J., Goldenthal, M. J., Harker Rhodes, C. & Marin-Garcia, J. Mitochondrial dysfunction in patients with hypotonia, epilepsy, autism, and developmental delay: HEADD syndrome. *J. Child. Neurol.* **17**, 435–439 (2002).

61. Shoffner, J. et al. Fever plus mitochondrial disease could be risk factors for autistic regression. *J. Child. Neurol.* **25**, 429–434 (2010).

62. Khemakhem, A. M., Frye, R. E., El-Ansary, A., Al-Ayadhi, L. & Bacha, A. B. Novel biomarkers of metabolic dysfunction is autism spectrum disorder: potential for biological diagnostic markers. *Metab. Brain Dis.* **32**, 1983–1997 (2017).

63. Chauhan, A. et al. Brain region-specific deficit in mitochondrial electron transport chain complexes in children with autism. *J. Neurochem.* **117**, 209–220 (2011).
64. Ahn, Y. et al. Aberrant mitochondrial morphology and function in the BTBR mouse model of autism is improved by two weeks of ketogenic diet. *Int. J. Mol. Sci.* **21**, 3266 (2020).

65. Pecorelli, A., Cervellati, C., Cordone, V., Hayek, J. & Valacchi, G. Compromised immune/inflammatory responses in Rett syndrome. *Free Radic. Biol. Med.* **152**, 100–106 (2020).

66. Rose, S. et al. Oxidative stress induces mitochondrial dysfunction in a subset of autism lymphoblastoid cell lines in a well-matched case control cohort. *PLoS ONE* **9**, e85436 (2014).

67. Rose, S., Wynne, R., Frye, R. E., Melnyk, S. & James, S. J. Increased susceptibility to ethylmercury-induced mitochondrial dysfunction in a subset of autism lymphoblastoid cell lines. *J. Toxicol.* **2015**, e573701 (2015).

68. Jyonouchi, H., Geng, L., Rose, S., Bennuri, S. C. & Frye, R. E. Variations in mitochondrial respiration differ in IL-1β/IL-10 ratio based subgroups in autism spectrum disorders. *Front. Psychiatry* **10**, 71 (2019).

69. Hassan, H., Zakaria, F., Makpol, S. & Karim, N. A. A link between mitochondrial dysregulation and idiopathic autism spectrum disorder (ASD): Alterations in mitochondrial respiratory capacity and membrane potential. *Curr. Issues Mol. Biol.* **43**, 2238–2252 (2021).

70. Gevezova, M. et al. Cellular bioenergetic and metabolic changes in patients with autism spectrum disorder. *Curr. Top. Med. Chem.* **21**, 985–994 (2021).

71. Behl, S., Mehta, S. & Pandey, M. K. Abnormal levels of metal micronutrients and autism spectrum disorder: A perspective review. *Front. Mol. Neurosci.* **13**, 586209 (2020).

72. Baj, J. et al. Autism spectrum disorder: Trace elements imbalances and the pathogenesis and severity of autistic symptoms. *Neurosci. Biobehav. Rev.* **129**, 117–132 (2021).

73. Awadh, S. M., Yaseen, Z. M. & Al-Suwaiyan, M. S. The role of environmental trace element toxicants on autism: A medical biogeochemistry perspective. *Ecotoxicol. Environ. Saf.* **251**, 114561 (2023).

74. Zhai, Q. et al. Disturbance of trace element and gut microbiota profiles as indicators of autism spectrum disorder: A pilot study of Chinese children. *Environ. Res.* **171**, 501–509 (2019).

75. Kim, B.-E., Nevitt, T. & Thiele, D. J. Mechanisms for copper acquisition, distribution and regulation. *Nat. Chem. Biol.* **4**, 176–185 (2008).

76. Turski, M. L. & Thiele, D. J. New roles for copper metabolism in cell proliferation, signaling, and disease. *J. Biol. Chem.* **284**, 717–721 (2009).

77. Mondola, P., Damiano, S., Sasso, A. & Santillo, M. The Cu, Zn superoxide dismutase: Not only a dismutase enzyme. *Front. Physiol.* **7**, 594 (2016).

78. Vallières, C., Holland, S. L. & Avery, S. V. Mitochondrial ferredoxin determines vulnerability of cells to copper excess. *Cell Chem. Biol.* **24**, 1228–1237.e3 (2017).

79. Lill, R. From the discovery to molecular understanding of cellular iron-sulfur protein biogenesis. *Biol. Chem.* **401**, 855–876 (2020).

80. Johnson, M. A., Macdonald, T. L., Mannick, J. B., Conaway, M. R. & Gaston, B. Accelerated S-nitrosothiol breakdown by amyotrophic lateral sclerosis mutant copper, zinc-superoxide dismutase. *J. Biol. Chem.* **276**, 39872–39878 (2001).

81. Ogunkola, M. O., Guiraudie-Capraz, G., Feron, F. & Leimkühler, S. The human mercaptopyruvate sulfurtransferase TUM1 is involved in moco biosynthesis, cytosolic tRNA thiolation and cellular bioenergetics in human embryonic kidney cells. *Biomolecules* **13**, 144 (2023).

82. Valente, A. J., Maddalena, L. A., Robb, E. L., Moradi, F. & Stuart, J. A. A simple ImageJ macro tool for analyzing mitochondrial network morphology in mammalian cell culture. *Acta Histochem.* **119**, 315–326 (2017).

83. Merrill, R. A., Flippo, K. H. & Strack, S. Measuring mitochondrial shape with ImageJ. In *Techniques to Investigate Mitochondrial Function in Neurons* (eds Strack, S. & Usachev, Y. M.) 31–48 (Springer, 2017).

## Acknowledgements

High throughput sequencing was performed at the TGML Platform, supported by grants from Inserm, GIS IBI-SA, Aix-Marseille Université, and ANR-10-INBS-0009-10. We are grateful to Thi Tien Nguyen and Alice Carrier for their help and insight on Seahorse data and to Florence Chaspoul for performing the metallomic study. The work was funded by CNRS (ref MOTISM), Aix-Marseille Université and Fondation de l'Avenir.

## Author contributions

FF, GGC initiated the study. FF, BG set up the cohort and purified the olfactory stem cells. All authors participated in research design. FF, DC, LF, GGC performed assays on mitochondrial dynamics and ATP production. FF, DC, GGC performed transcriptomic and proteomic experiments. SL, OI provided critical suggestions for article writing. All authors have read and agreed to the published version of the manuscript.

## Declarations

### Competing interests

The authors declare no competing interests.

### Additional information

**Supplementary Information** The online version contains supplementary material available at https://doi.org/10.1038/s41598-025-22327-1.

**Correspondence** and requests for materials should be addressed to F.F.

**Reprints and permissions information** is available at www.nature.com/reprints.

**Publisher's note** Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
**Open Access** This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

© The Author(s) 2025