Genetic and clinical evidence of mitochondrial dysfunction in autism spectrum disorder and intellectual disability

Abstract

Clinical conditions commonly associated with mitochondrial disorders (CAMDs) are often present in autism spectrum disorders (ASD) and intellectual disability (ID). Therefore, the mitochondrial dysfunction hypothesis has been proposed as a transversal mechanism that may function in both disorders. Here, we investigated the presence of conditions associated with mitochondrial disorders and mitochondrial DNA (mtDNA) alterations in 122 subjects who presented ASD with ID (ASD group), 115 subjects who presented ID but not ASD (ID group) and 112 healthy controls (HC group). We assessed in the three study groups the presence of the clinical conditions through a questionnaire and the mtDNA content of two mitochondrial genes, MT-ND1 and MT-ND4, by qPCR. The mtDNA sequences of 98 ASD and 95 ID subjects were obtained by mtDNA-targeted next generation sequencing and analysed through the MToolBox pipeline to identify mtDNA mutations. Subjects with ASD and ID showed higher frequencies of constipation, edema, seizures, vision alterations, strabismus and sphincter incontinence than HCs subjects. ASD and ID subjects showed significantly lower mtDNA content than HCs in both MT-ND1 and MT-ND4 genes. In addition, we identified 49 putative pathogenic variants with a heteroplasmy level higher than 60%: 8 missense, 29 rRNA and 12 tRNA variants. A total of 28.6% of ASD and 30.5% of ID subjects carried at least one putative pathogenic mtDNA mutation. The high frequency of CAMDs, the low mtDNA content and the presence of putative pathogenic mtDNA mutations observed in both ASD and ID subjects are evidence of mitochondrial dysfunction in ASD and ID.

Introduction

Autism spectrum disorders (ASDs) are a group of severe neurodevelopmental disorders with an onset in the early stages of development. People affected by ASD tend to suffer persistent deficits in social communication, social interaction and restricted or repetitive patterns of behavior, interests, or activities (1). The median worldwide prevalence of ASD is 1–2%, and a similar prevalence is reported in the dataset of adults only (2). Intellectual disability (ID) is characterized by both intellectual and adaptive functional deficits in conceptual, social and practical domains, affecting 2–3% of the population (3). The onset of ID occurs during the developmental period. Both ASD and ID are strongly associated and show a high comorbidity (2,4). In children, 18 to 70% of patients with ASD also present ID and up to 40% of subjects with ID also present ASD (5,6). In adulthood, approximately one-fifth of subjects with ASD are diagnosed with ID (7).

ASD also occurs with other frequent medical comorbidities, such as epilepsy, sensory abnormalities, motor deficits, sleep abnormalities, gastrointestinal disturbances, feeding and nutritional problems, metabolic syndrome and immune conditions (7–9). In fact, more than 70% of subjects with ASD have concurrent medical, developmental or psychiatric disorders (2). Interestingly, many of the above mentioned clinical characteristics are conditions that are commonly associated with mitochondrial disorders (CAMDs). Mitochondrial disorders comprise a collection of individual rare syndromes produced by defects in either the mitochondrial DNA (mtDNA) or nuclear DNA that result in mitochondrial dysfunction. Impaired mitochondria affect most organ systems to different extents, producing a wide spectrum of phenotypes; however, little is known about the cascade of events involved in such diverse, rare syndromes (10,11). Interestingly, mitochondrial dysfunction has been described in both subjects with ASD (12,13) and ID (14) and has been suggested as a possible neurobiological subtype of ASD (15).

Mitochondria are key organelles required for energy production, and their proper function is therefore crucial for tissues with a high metabolic demand, such as the nervous system. Mitochondria have their own genome, known as mtDNA, which comprises a 16 569-bp, double-stranded, maternally inherited, circular molecule that contains the genetic information necessary for the synthesis of 13 essential polypeptides in the mitochondrial respiratory chain (16). Unlike nuclear DNA that is only present in two copies per cell, the mtDNA content varies, depending on the energy requirements. Each mitochondrion may present 2 to 10 mtDNA molecules, and each cell can contain several mitochondria (17). Interestingly, the mtDNA content is related to anthropometric indices (18) and has been proposed as a biomarker of mitochondrial dysfunction involved in conditions such as diabetes, obesity, cancer, HIV complications, aging (19) and autism (20).

The genetic architecture of ASD and ID is complex, with several types of genetic variants known to be associated with both conditions, although many of the genetic factors are unknown (3,4). Furthermore, despite the evidence of mitochondrial dysfunction in subjects with ASD and ID, the study of mtDNA has been neglected even it may contribute to the genetic bases of both conditions. Therefore, we tested the hypothesis that, in adulthood, CAMDs comorbidity is frequently present in ASD and ID compared with a control group. In addition, we investigated whether alterations in the mtDNA sequence were present in ASD and ID and whether the mtDNA content in ASD and ID cases differed from controls.

Results

CAMDs

We compared the frequency of CAMDs among the three groups (Table 1). Constipation, edema (referred to as venous insufficiency and other venous alterations), seizures, vision alterations, strabismus and sphincter incontinence were more frequent in the ASD group than in the HC group. All these conditions were also more frequent in the ID group than in the HC group. Other factors, such as temperature changes, diabetes, hypertension and cancer, were also more frequent in the ID group than in the HC group, but did not reach statistical significance. Conditions present in less than 5% of subjects that were not reported in the ASD and ID groups are: headache, migraine, diarrhea, abdominal pain, nausea, kinetosis, severe fatigue, fibromyalgia, dysautonomia, arthritis, muscular weakness, deafness, stroke, heart disease, hypercholesterolemia, kidney disease, hypoglycemia, and hypothyroidism.

Table 1.

Percentage of subjects in the three study groups presenting conditions commonly associated with mitochondrial disorders (CAMDs)

Conditions	HCn = 112	ASDn = 122	IDn = 115	Statistics
				Compared groups	χ2	P
Specific conditions with frequency >5% in the study groups
Constipation	17.0	73.8	57.4	HC vs. ASD	75.403	<0.001
				HC vs. ID	38.496	<0.001
				ASD vs. ID	7.060	0.008
Edema	3.6	15.6	27.8	HC vs. ASD	9.357	0.002
				HC vs. ID	24.478	<0.001
				ASD vs. ID	5.262	0.021
Seizures	0	63.9	42.6	HC vs. ASD	107.059	<0.001
				HC vs. ID	59.918	<0.001
				ASD vs. ID	10.820	0.001
Vision alterations	5.4	18.0	33.9	HC vs. ASD	8.762	0.003
				HC vs. ID	28.458	<0.001
				ASD vs. ID	7.810	0.005
Strabismus	1.8	10.7	13.0	HC vs. ASD	7.647	0.006
				HC vs. ID	10.268	0.001
				ASD vs. ID	0.328	0.567
Sphincters incontinence	0	66.4	31.3	HC vs. ASD	113.400	<0.001
				HC vs. ID	40.994	<0.001
				ASD vs. ID	29.160	<0.001
Other conditions grouped into organ systems
Nervous system	15.2	100	100	HC vs. ASD	174.207	<0.001
				HC vs. ID	167.747	<0.001
				ASD vs. ID	—	—
Gastro-intestinal	4.5	5.7	1.7	HC vs. ASD	0.195	0.659
				HC vs. ID	0.646	0.422
				ASD vs. ID	1.612	0.204
Cardio-vascular	29.5	13.9	32.2	HC vs. ASD	5.287	0.021
				HC vs. ID	0.195	0.659
				ASD vs. ID	11.194	<0.001
Musculo-skeletal	2.7	0	0	HC vs. ASD	—	—
				HC vs. ID	—	—
				ASD vs. ID	—	—
Endocrine	12.5	8.2	17.4	HC vs. ASD	1.175	0.278
				HC vs. ID	0.071	0.790
				ASD vs. ID	4.527	<0.033

HC: healthy controls; ASD: autism spectrum disorder; ID: intellectual disability.

Significant differences are indicated in boldface.

mtDNA copy number

The mtDNA copy number, namely, the number of mtDNA molecules per white blood cell, differed among the three study groups (ASD, ID, and HC). Age, BMI and the number of cigarettes smoked per day were correlated with the mtDNA copy number; therefore, these factors were included as covariates in the general linear analysis comparing the mtDNA content between groups. The mtDNA copy number measured using either the MT-ND1 or the MT-ND4 genes was lower in the ASD and ID groups than in the HC group and was also significantly lower in the ID group than in the ASD group (Fig. 1). The deletion ratio was higher in both the ASD and ID groups than in the HC group, although significant differences were only present when the HC and ASD groups were compared.

Figure 1.

Estimated marginal means of the MT-ND1 and MT-ND4 genes and the deletion ratio in the three study groups. HC: healthy controls; ASD: autism spectrum disorder; ID: intellectual disability; n.s.: not significant; *P < 0.05; **P < 0.01; ***P < 0.001.

Putative pathogenic mtDNA variants

Among the 193 sequenced subjects, MToolBox (21) identified 664 variants of clinical interest. After applying the selection criteria for pathogenicity prediction, we identified 57 (29.5%) subjects who carried 49 putative pathogenic variants, with a heteroplasmy level ≥ 60%. In the ASD group, 28 subjects carried 37 variants, whereas 29 subjects in the ID group carried 28 variants (Table 2). Notably, 11 variants were present in more than one subject and 12 subjects carried more than one putative pathogenic variant.

Table 2.

Putatively pathogenic variants present in the study sample

N	Variant	AA change	Freq.	dbSNP ID	Samples	Locus	Homo/ heteroplasmy	Disease score
Non-synonymous variants
1	m.8663A>C	Q46P	0		ID074	MT-ATP6	0.79	0.889
2	m.8936T>A	L137H	0		A003, ID009, ID036, ID055, ID069, ID073, ID074, ID104, ID112		0.60–0.97	0.855
3	m.11039C>T	L94F	0		ID071	MT-ND4	0.99	0.702
4	m.11268C>T	T170I	0.0010		A095, ID015		1	0.739
5	m.13855C>A	L507M	0		ID070	MT-ND5	1	0.686
6	m.15132T>C	M129T	0.0002		A117	MT-CYB	1	0.821
7	m.15482T>C	S246P	0		ID038		1	0.559
8	m.15597T>C	V284A	0		A059		1	0.581
rRNA variants
1	m.680T>C		0.0006		A099	MT-RNR1	1
2	m.720T>C		0		A070		0.99
3	m.736C>T		0		ID057		1
4	m.851A>G		0	rs28502491	A092, ID011		0.96–1
5	m.870C>T		0.0005		ID116		1
6	m.1007G>A		0.0010	rs111033213	A051		0.99
7	m.1120C>T		0.0005	rs727505171	ID007		1
8	m.1211G>A		0.0010	rs397515725	A063, A095, ID015, ID042		1
9	m.1303G>A		0.0023		A021		1
10	m.1537C>T		0.0003		ID108		1
11	m.1555A>Ga		0.0032	rs267606617	A043, A054, ID018		0.99–1
12	m.1717T>Ca		0.0007		ID076	MT-RNR2	1
13	m.1821A>G		0.0008		ID105		1
14	m.1834T>C		0.0007		A078, A089, A156		1
15	m.2141T>C		0.0031		ID112		1
16	m.2222T>C		0		ID061, ID087		1
17	m.2223A>G		0		ID038		1
18	m.2234C>T		0		ID017		1
19	m.2244T>G		0		ID011		1
20	m.2398A>G		0		A068		1
21	m.2407T>C		0		ID024		1
22	m.2524A>C		0.0001		A096		1
23	m.2702G>A		0.0020		A067		1
24	m.2746T>C		0.0005	rs28663331	A090		1
25	m.2775A>G		0		ID061, ID087		1
26	m.2792A>C		0.0001		A057		1
27	m.2969A>G		0.0002		ID065		1
28	m.3203A>G		0.0009		ID055		1
29	m.3213A>Ga		0.0003		A098		1
tRNA variants
1	m.4310A>G		0.0008		ID085	MT-TI	1
2	m.4336T>C		0.0220	rs41456348	A059, ID004	MT-TQ	0.98–1	0.4
3	m.4388A>G		0.0002	rs375986475	ID036	MT-TQ	1
4	m.4435A>Ga		0.0010		A079, ID037	MT-TM	0.95–1	0.35
5	m.5605A>G		0.0003		A152	MT-TA	1
6	m.10007T>C		0.0010	rs201906571	A009	MT-TG	1
7	m.12142A>Ga		0.0001		A125	MT-TH	1
8	m.12193A>G		0		A084		1
9	m.14684C>T		0.0009		A003	MT-TE	1
10	m.14687A>G		0.0098	rs200189658	ID112		1	0.65
11	m.15913C>T		0.0003		ID065	MT-TT	0.99
12	m.15946C>T		0.0032	rs202014122	A014, A045		0.99–1

N: nucleotide; AA: amino acid; Freq. frequency; dbSNP: Single Nucleotide Polymorphism data base; A: autism spectrum disorder; ID: intellectual disability; MT: mitochondrial; CO1: cytochrome c oxidase subunit 1; ATP6: ATP synthase subunit 6; ND3: NADH dehydrogenase subunit 3; CYB: cytochrome b; RNR1: 12S ribosomal RNA; RNR2: 16S ribosomal RNA; TF = tRNA-Phenylalanine; TI = tRNA-Isoleucine; TQ = tRNA-Glutamine; TM = tRNA-Metionine; TA = tRNA-Alanine; TD: tRNA-Aspartic acid; TG = tRNA-Glycine; TH = tRNA-Histidine; TE = tRNA-Glutamic; TT = tRNA-Threonine.

a

Reported by Wang et al. (36).

Frequency of the variants was retrieved from 8686 complete European human genomes present in HmtDB in July 2017 (44).

Non-synonymous variants

In the present study, eight non-synonymous variants fulfilled the cut-off prioritization criteria previously described as pathogenic. All were missense variants, none of them have been previously associated with a disease or health condition and, notably, three of them were not previously reported: m.8663A > C and m.8936T > A in the MT-ATP6 gene and m.15597T > C in the MT-CYB gene.

rRNA variants

We identified 29 putative pathogenic rRNA variants based on the criterion of nucleotide variability ≤ 0.0097 and a heteroplasmy level higher than 60%. All variants, with the exception of m.2398A > G, have been previously reported. Interestingly, two of the 29 variants were reported to be associated with disease in MITOMAP: m.1537C > T was reported to be associated with maternally inherited or aminoglycoside-induced deafness, and the subject bearing this mutation actually suffered from this condition; and m.1555A > G was confirmed to be associated with deafness in MITOMAP, ClinVar and OMIM (http://omim.org/entry/561000#0001). However, only the oldest of the three subjects presenting the variant showed deafness (Table 3).

Table 3.

Clinical characteristics reported to be associated with mtDNA variants present in the study sample

Variant	Locus	Heteroplasmy	Subjects	Age	Gender	Deafness	Migraine	AD/PD	Hypertension	Visual loss	MMRF
m.1537C>T	MT-RNR1	1	ID108	60	M	+	NE	−	−	−	−
m.1555A>G	MT-RNR1	1	ID018	33	M	−	NE	−	−	+	−
		1	A043	43	F	−	NE	−	−	−	−
		1	A054	54	F	+	NE	−	−	−	−
m.4336T>C	MT-TQ	0.98	A059	38	M	−	NE	−	+	−	−
		1	ID004	63	F	−	NE	+	−	−	−
m.4388A>G	MT-TQ	1	ID036	36	F	−	NE	−	+	−	−
m.4435A>G	MT-TM	1	ID037	40	F	−	NE	−	+	−	−
		0.96	A079	39	M	−	NE	−	+	−	−
m.14687A>G	MT-TE	1	ID112	21	M	−	NE	−	+	+	−

ID: intellectual disability; A: autism spectrum disorder; M: male; F: female; NE: not evaluable; AD: Alzheimer’s disease; PD: Parkinson’s disease; MMRF: Mitochondrial Myopathy and Respiratory Failure; MT: mitochondrial; RNR1: 12S ribosomal RNA; TQ: tRNA-Glutamine; TM: tRNA-Metionine; TE = tRNA-Glutamic acid.

Plus (+) or minus (−) symbol indicates the presence or absence of the clinical characteristic in the study subject.

Reported clinical conditions with each variant are shaded: 1537 C > T, deafness (MITOMAP); 1555 A > G, maternally inherited or aminoglycoside-induced deafness (MITOMAP); 4336 T > C, AD and PD, hearing loss and migraine (MITOMAP), sensorineural deafness and migraine (ClinVar and OMIM); 4388 A > G, possible hypertension factor (MITOMAP); 4435 A > G, hypertension and modifying factor of Leber’s hereditary optic neuropathy phenotype (MITOMAP); 14687 A > G, MMRF (MITOMAP).

Other conditions not reported to be associated with the variants but present in the study subjects: epilepsy (ID108, A043, A054, A059, ID004, ID112); constipation (ID018, A043, A054, A059, ID036, ID037, ID112); cardiac disease (A059, ID004) and diabetes (ID112).

tRNA variants

We identified 12 putative pathogenic tRNA variants, four of them have been previously associated with several conditions; deafness, Alzheimer’s disease, hypertension and visual loss were present in some study subjects, but mitochondrial myopathy and respiratory failure was not (Table 3).

mtDNA variants of uncertain significance

In addition, we have identified other putative pathogenic variants with a heteroplasmy percentage ≤ 60% (Supplementary Material, Table S1). Furthermore, several variants were also present in subjects with ASD and ID. Among them, it is worth mentioning variants located in the MT-D-LOOP and MT-ORIL non-previously reported or with low nucleotide variability (Supplementary Material, Table S2). Some variants have previously been reported to be associated with various conditions in MITOMAP (Supplementary Material, Table S3), although they did not fulfill the selection criteria for identification as putatively pathogenic using the MToolBox priorization criteria.

Each ASD and ID subject was assigned to a European mitochondrial haplogroup (Supplementary Material, Table S4). The frequencies of the most common haplogroups in the two study groups, ASD and ID, did not differ from the reported frequencies in healthy subjects (data not shown) selected from a population-based sample in the same geographic region (22). Furthermore, putative pathogenic variants were not specific for a single haplotype, as we observed the following ratios of putative pathogenic variants within a haplogroup/number of total subjects within the same haplogroup: 23/91H, 3/18J, 2/12K, 2/5L, 2/4M, 2/3N, 7/16T, 13/32U, 2/10V and 1/6W.

Datasets of mtDNA sequences and clinical data from participants are available at the European Genome-phenome Archive (EGA, https://ega-archive.org) with the study reference number EGAS00001002750.

Discussion

CAMDs

Few studies have been performed on the physical health of adults with ASD, although some medical comorbidities that are present in infancy persist into adulthood (9,23). Subjects with ID experience more extensive psychiatric and behavioral disorders and other medical conditions in addition to visual, dental and hearing problems (24). However, the percentages of comorbid conditions in ASD and ID studies vary, depending on the methodology of the study, and are often difficult to compare. Even among ASD studies, the results are difficult to compare due to different percentages of ID among study subjects (7,25). In the present study, we identified constipation, edema, seizures, vision alterations, strabismus and sphincter incontinence as the most prevalent comorbid conditions present in both subjects with ASD and ID compared with HCs. Constipation, seizures and sphincter incontinence were also more prevalent in subjects with ASD than in subjects with ID, whereas edema and vision alterations were more prevalent in subjects with ID than in subjects with ASD. Notably, in our study subjects with ID were on average 12 years older than subjects with ASD, and, therefore, we cannot exclude the possibility that edema and vision alterations were more prevalent in subjects with ID because they were older. Moreover, ID was more severe in patients who fulfilled the criteria for ASD than in subjects who did not, and, therefore, the high percentage of subjects presenting constipation, seizures and sphincter incontinence may be associated with the severe ID rather than ASD.

mtDNA copy number

We analysed MT-ND1 and MT-ND4, two of the seven mtDNA-encoded genes of complex I. Both subjects with ASD and ID presented lower MT-ND1 and MT-ND4 contents than HC subjects, indicating that the number of mtDNA copies was reduced in subjects with ASD and ID compared with that in HCs. Previous studies conducted in peripheral blood cells from children with ASD have reported an elevated mtDNA copy number compared with that in healthy children (26) and unaffected siblings (27). Notably, all these studies were conducted in children, whereas our study was conducted in adult subjects. The peripheral blood mtDNA content is associated with sex and age and is influenced by several variables, such as platelet and white blood cell counts and estroprogesterone intake (28). Regarding age, the mtDNA content increases until the fifth decade of life and then declines in older subjects (28). In the present study, we compared the mtDNA content after correcting for covariates that correlate with the mtDNA content, and we conclusively identified lower mtDNA content in subjects with ASD and ID than in HCs. The low peripheral blood mtDNA content in ASD and ID suggests a transversal mitochondrial dysfunction that can affect several tissues.

Regarding the deletion ratio, which is directly related to the presence of the common deletion, we observed that patients with ASD exhibited significantly higher ratios than HCs. Therefore, the common deletion was more frequent in the ASD group than in the HC group. We included all the confounding factors in the analysis, and significant differences were only observed for the ASD group. In a study that included 10 children with ASD, deletions of the MT-ND4 gene were reported in five subjects, and the deletion ratio was higher in 2 of 10 children (29).

mtDNA variants

Mitochondrial function, structure and cell size are altered by mtDNA heteroplasmy (30). Since the disease manifests at the heteroplasmic threshold in the range of 0.60 to 0.95 for most pathogenic mutations (31), we selected putative pathogenic variants exhibiting heteroplasmy levels higher than 60%. The present study identified that 26.6% of ASD patients and 30.5% of ID subjects had a putative pathogenic mutation suggesting that part of the genetic risk factors involved in ASD and ID can be located in mtDNA. Mitochondrial dysfunction and mtDNA implications have been broadly proposed in the etiology of ASD, however, only a few studies have analysed the mtDNA sequence in subjects with ASD (32–35). Recently, Wang et al. primarily compared the mtDNA sequence between children with ASD and their non-autistic siblings and identified that predicted pathogenic mutations conferred an increased risk of ASD. In addition, this risk was most pronounced in families with probands who exhibited a diminished intelligence quotient and/or impaired social behavior (36). The authors used whole-exome sequencing, unlike our study that performed mtDNA-targeted deep sequencing, and therefore, we obtained a higher mean deep coverage of 512X than the 141X coverage obtained in the previous study. Additionally, we analyse the mtDNA data using the MToolBox phylogeny-based prioritization workflow which uses the mtDNA sequences from 14 144 healthy individuals to select the variants that are more likely to be pathogenic (37). Most of the putative pathogenic variants we identified have not been previously been associated with ASD, with the exception of m.1555A > G, MT-RNR1; m.1717T > C, MT-RNR2; m.3213A > G, MT-RNR2; m.4435A > G, MT-TM and m.12142A > G, MT-TH that were identified by Wang et al. Each variant was present in a unique family; however, high-confidence heteroplasmic data were not reported for all three members in four out the five variants, and only 1717T > C, 4435A > G and 12142A > G were reported in ASD patients while no data were available for the other two variants. Regarding ID, our study is the first to analyse the entire mtDNA of subjects with ID using next generation sequencing via mtDNA-targeted deep sequencing. We reported a large number of putative pathogenic mtDNA variants; however, we could not confirm that all variants were implicated in ID or ASD because pathogenicity must be demonstrated by functional studies. In addition, high percentages of pathogenic mtDNA mutations have been described in the general population. Approximately one in 200 healthy subjects carries a pathogenic mtDNA variant; however, the heteroplasmy levels were less than 0.60 (38). Recently, the analyses of the 1000 Genomes Project have identified that 20% of subjects harbor heteroplasmies reported to be implicated in disease although positions with heteroplasmy levels larger than 0.60 showed a reduction in pathogenicity (39). The present study identified that one in four subjects with ASD or ID carry a pathogenic mtDNA variant with heteroplasmy > 0.60. Therefore, in addition to the known nuclear genetic alterations involved in ASD and ID, we identified mtDNA variants that may contribute to the genetic architecture of both clinical conditions.

It is worth mentioning that six variants present in four subjects with ASD (4%) and six subjects with ID (6%) have previously been associated with clinical conditions; all variants were present in rRNA and tRNA genes and had heteroplasmy levels higher than 0.95. Some of the clinical conditions were present in the subjects, whereas others were not. For example, the m.4336T > C has been reported to be associated with Alzheimer’s disease, and one of the two carriers, who was 63 years old, suffered from this condition. We cannot exclude the possibility that the other subject may develop the disease in the future, since at the time of the study this subject was 38 years old. Similarly, the m.1555A > G variant is associated with deafness, and the oldest subject of the three carriers was deaf, whereas the other two younger subjects were not. These two patients are predisposed to aminoglycoside-induced ototoxicity, and, therefore, aminoglycoside treatments must be avoided. Regarding tRNA variants, they are reported in MITOMAP as ‘possibly benign’ or ‘likely benign’ based on database frequencies, nature of the nucleotide change and conservation score. However, clinical history, heteroplasmy data or functional studies are not included in retrieving tRNA pathogenicity scores and, therefore, they should be further evaluated to discard pathogenicity.

Much additional work is needed to elucidate the role of putative pathogenic mtDNA mutations in mitochondrial function and to determine whether these variants are related to ID, ASD, and/or CAMDs. A limitation of the present study is that some of the rare rRNA and tRNA variants for which RNA disease scores are not yet available may be specific to our population and not related with clinical conditions. Finally, we studied ASD subjects with concurrent ID because our sample was obtained from institutionalized subjects who presented with low-functioning ASD. Therefore, our results should not be generalized to all subjects with ASD, although they may be generalized to subjects with ID.

In summary, our study identified 1) a high frequency of conditions commonly associated with mitochondrial disorders that occurred concomitantly with 2) low mtDNA content and 3) the presence putative pathogenic mtDNA mutations in subjects with ASD and ID. Based on these findings, subjects with ASD and ID may present mitochondrial dysfunction. Future research will elucidate whether the screening for mtDNA alterations in ASD and ID can be as appropriate as the screening for nuclear DNA alterations.

Materials and Methods

Study design

In this cross-sectional study, DNA samples and clinical data from adult Caucasian white subjects recruited at the Intellectual Disability and Developmental Disorders Research Unit of the Group Pere Mata in Reus (www.peremata.com, Catalonia, Spain) and from adult healthy controls were analysed. All participants were over 18 years old. Informed written consent was obtained from the relatives or other legal guardians of all institutionalized subjects and from healthy individuals. The Ethical Committee of Hospital Sant Joan de Reus approved the study.

Participants

The sample consisted of three groups: 122 subjects with a severe or profound intellectual disability who fulfilled the diagnostic criteria for autism spectrum disorders (ASD), 115 subjects with a severe or profound ID who did not fulfill the diagnostic criteria for ASD, and 112 healthy controls (HCs) (Table 4). ASD and ID were diagnosed according to the Diagnostic and Statistical Manual of Mental Disorders, 4th Edition, Text Revision (DSM-IV-TR) criteria. The ASD diagnosis was confirmed using the Autism Diagnostic Interview-Revised (ADI-R) (40). The Childhood Autism Rating Scale (CARS) (41) was used to measure autism severity in the ASD group and to explore autism features in the ID group. Given the difficulty in diagnosing ASD in persons with a severe and profound intellectual disability, only patients showing both evaluations (DSM-IV-TR and ADI-R) positive were included in the ASD group.

Table 4.

Characteristics of the sample

	HCN = 112	ASDN = 122	IDN = 115	Compared groups	Statistics
Gender
Male, N (%)	50 (44.6)	80 (65.5)	74 (64.3)	HC vs. ASD	χ2=10.4; P=0.001
				HC vs. ID	χ2=13.0; P=0.003
Female, N (%)	62 (55.4)	42 (34.4)	41 (35.7)
				ASD vs. ID	χ2=0.1; P=0.843
Age in years (mean, SD)	42.4 (11.4)	40.7 (8.3)	52.1 (12.4)	HC vs. ASD	t= 1.3; P=0.194
				HC vs. ID	t = −6.1; P<0.001
				ASD vs. ID	t = −8.3; P<0.001
BMI in kg/m2 (mean, SD)	24.1 (3.1)	25.1 (4.9)	27.3 (5.5)	HC vs. ASD	t = −1.7; P=0.086
				HC vs. ID	t = −5.4; P<0.001
				ASD vs. ID	t = −3.3; p<0.001
Tobacco consumption in c/d, (mean, SD)	3.2 (6.5)	0.2 (1.2)	0.8 (3.4)	HC vs. ASD	t = 4.9; P<0.001
				HC vs. ID	t = 3.4; P=0.001
				ASD vs. ID	t = −2.1; P=0.041
Chromosomal alterations, N (%)	–	37 (30.3)	10 (8.7)	ASD vs. ID	χ2=17.7; P<0.001
ID Severity
Severe, N (%)		16 (13.1)	69 (60%)	ASD vs. ID	χ2=55.3; P<0.001
Profound, N (%)		106 (86.9)	46 (40%)
CARS score (mean, SD)	–	42.6 (5.9)	21.8 (4.4)	ASD vs. ID	t=28.9; P<0.001
Treatment, N (%)
Antipsychotic	–	66 (54.1)	64 (55.6)	ASD vs. ID	χ2=0.1; P=0.810
Anticholinergic	–	16 (13.1)	17 (14.8)		χ2=0.1; P=0.711
Benzodiazepines	–	72 (59.0)	61 (53.0)		χ2=0.9; P=0.354
Antidepressant	–	11 (9.0)	18 (15.7)		χ2=2.4; P=0.119
Antiepileptic	–	50 (41.0)	33 (28.7)		χ2=3.9; P=0.047
Mood stabilizers	–	57 (46.7)	49 (42.6)		χ2=0.4; P=0.525
Antihypertensive	–	2 (1.6)	13 (12.7)		χ2=9.3; P=0.002
Analgesics	–	15 (12.3)	21 (21.3)		χ2=1.6; P=0.201
Laxative	–	51 (41.8)	61 (53.0)		χ2=3.0; P=0.083
Antithyroid	–	2 (1.6)	4 (3.5)		χ2=0.8; P=0.368

HC: healthy controls; ASD: autism spectrum disorder; ID: intellectual disability; N: number of cases; BMI: body mass index; c/d: cigarettes smoked per day; CARS: Childhood Autism Rating Scale.

Significant differences are indicated in boldface.

Clinical data

ASD and ID

A trained psychiatrist reviewed the clinical record of each participant to collect sociodemographic, anthropometric, medication use, family history and neurodevelopment features. In conjunction with the referring physician of each participant, the psychiatrist completed a questionnaire focused on CAMDs, which are divided into the following categories: migraine headaches, peripheral neurovascular disorders, gastrointestinal dysmotility, neurological disorders, cardiac abnormalities, skeletal muscle disorders, endocrine disorders, and constitutional disorders. The same questionnaire has been used in previous studies to identify maternal inheritance in disorders with presumed mitochondrial dysfunction (42–44) and the presence of clinical features associated with mitochondrial disorders among relatives of patients with schizophrenia (45). Some conditions present in the questionnaire, such as questions regarding headache, migraine or fatigue, could not be properly assessed because of the severity of the ID of the subjects.

HCs

The same psychiatrist who obtained data from subjects in the ASD and ID groups collected sociodemographic, anthropometric and family history data, and completed the CAMDs questionnaire for HCs. Participants who had no personal, first- or second-degree relatives with antecedents of severe mental disorders were selected for inclusion in the control group.

DNA extraction

Total DNA was obtained from peripheral blood mononuclear cells from fasting subjects using the Gentra^® PureGene reagent (Qiagen, Barcelona, Spain), according to the manufacturer’s instructions. DNA concentrations were quantified using a NanoDrop spectrophotometer (Thermo Fisher Scientific, Madrid, Spain).

mtDNA-targeted next generation sequencing

The entire mtDNA was amplified using three pairs of mtDNA-specific primers that produced three overlapping PCR fragments; A: 6928 base pairs (bp), positions 569–7497; B: 7050 bp, positions 5061–12 111; and C: 6867 bp, position 11 107–1405. Long-range PCR was performed using 10 ng of DNA with Expand Long Range dNTPack (Roche, Barcelona, Spain), and the PCR products were purified using the QIAquick PCR Purification kit (Qiagen, Barcelona, Spain), according to the manufacturer's instructions. Nineteen blood samples from the ASD group and 15 blood samples from the ID group were discarded, as they did not amplify any of the mtDNA fragments. Finally, the three PCR fragments from each individual were mixed in equimolar ratios, and each sample was prepared for sequencing in an Ion Torrent Personal Genome Machine (PGM, Fisher Scientific, Madrid, Spain), according to the manufacturer’s user guide. Seven multiplexed sequencing runs (32 samples per run) were performed on Ion 316 chips (Fisher Scientific, Madrid, Spain). After filtering, sequences from five subjects with ASD and five subjects with ID were discarded because of low-quality reads. We obtained an average of 60 000 high-quality reads from 98 subjects with ASD and 95 subjects with ID that were analysed using MToolBox (21) that assembles mtDNA starting from NGS data, assigns haplogroup and prioritizes mtDNA variants of clinical interest according to Santorsola et al. (37) for non synonymous variants and Diroma et al. (46) for rRNA and tRNA variants. Briefly, using 14 144 complete sequences from healthy individuals available in HmtDB (47), the process reports rare or private variants, the nucleotide variability, a disease score based on several predictors of pathogenicity for non-synonymous variants and an RNA pathogenicity prediction for rRNA and tRNA variants based on published data (37,46). Finally, information about the variants associated with clinical outcomes present in MITOMAP (www.mitomap.org), ClinVar (https://www.ncbi.nlm.nih.gov/clinvar/), OMIM (https://omim.org) and dbSNP (https://www.ncbi.nlm.nih.gov/SNP/) was obtained through MToolBox, together with data on homoplasmy and heteroplasmy (homoplasmy refers to a cell that has a uniform collection of mtDNA—either completely normal mtDNA or completely mutant mtDNA—and heteroplasmy refers to a cell with different proportions of normal and mutant mtDNA). Regarding heteroplasmy, we set the cut-off to 0.1, and therefore, variants with low levels of heteroplasmy (< 10%) were not reported. The mean coverage obtained was 512. Variants are reported according to the revised Cambridge Reference Sequence (rCRS) of the human mtDNA, GenBank sequence NC_012920 gi: 251831106.

Selection criteria for the pathogenicity prediction

Non-synonymous variants

We selected putative pathogenic non-synonymous variants that fulfilled the two cut-off prioritization criteria described by Santorsola et al., (37) diseases score > 0.4311 and nucleotide variability < 0.0026. The disease score is based on the weighted mean of the probabilities that an amino acid substitution may affect gene/protein function provided by the pathogenicity predictors SIFT, Polyphen-2, MutPred, SNPs&GO, PhD-SNP and PANTHER.

rRNA and tRNA variants

The RNA prediction score retrieved by MToolBox was based on published data, and the pathogenic range was established between 0.35 and 1 (46). Thus, variants that have not previously been associated with diseases have no RNA prediction score. Based on our results, we selected putative pathogenic rRNA or tRNA variants presenting an RNA prediction score ≥ 0.35 or a nucleotide variability ≤ 0.0097.

Heteroplasmy level

For most of the described pathogenic mutations, the disease manifests when the heteroplasmic threshold ranges from 0.60 to 0.95, depending on the mutation and cell type (31). Therefore, we only considered variants that presented heteroplasmy levels higher than 60% as putatively pathogenic.

Quantification of the mtDNA copy number

We measured the mtDNA content in total DNA using quantitative real-time PCR (qPCR). Two mtDNA regions were selected as target regions: MT-ND1 and MT-ND4 genes. Nuclear RPPH1 (corresponding to the RNase P enzyme), a single-copy nuclear gene, was selected as the reference gene. The mtDNA content was calculated for each sample and region using the 2^-ΔCq method (ΔCq = Cq of the mitochondrial gene—Cq of the reference gene). The mtDNA content was calculated as the ratio between the number of copies of the mitochondrial genome and the number of copies of the nuclear genome (mtDNA/nDNA). MT-ND1 is a rarely deleted region and MT-ND4 is located in the major arc of mtDNA and deleted in 97% of all common deletions (17). Therefore, the MT-ND1/MT-ND4 ratio indicates the deletion ratio. Details regarding qPCR reactions and quality control have been published previously (17,48).

Statistical analyses

The normality of the distributions of continuous variables was explored using the Kolmogorov-Smirnov normality test. Chi-square tests were used to compare the presence of CAMDs among the study groups. Spearman’s correlation analysis was used to explore the correlation between the mtDNA content of the two studied mtDNA regions and age, body mass index (BMI) and smoking habits. A general linear model was used to identify whether the mtDNA content in the three study groups differed after adjusting for age, BMI and number of cigarettes smoked per day as covariates. Data were processed using IBM SPSS Statistics for Windows, Version 23.0 (IBM Corp., Armonk, NY) and Prism, Version 5 (Graphpad, La Jolla, CA).

Supplementary Material

Supplementary Material is available at HMG online.

Acknowledgements

We are grateful to the subjects who participated in the study, and we also acknowledge the technicians from the Biobanc-IISPV in Reus (http://www.iispv.cat) for managing the samples and the physicians who helped collect the data related to the CAMDs conditions.

Conflict of Interest statement. None declared.

Funding

Instituto de Salud Carlos III of the Spanish Ministry of Science and Innovation in Spain [grant numbers PS09/01052 and PI12/01885 to L.M.] and FEDER. H.T. was the recipient of a FI-DGR, and G.M. was the recipient of a BP-DGR scholarship, both of which were from the Generalitat de Catalunya.

Author notes

Alba Valiente-Pallejà, Helena Torrell and Gerard Muntané have equally contributed to the work.