We are in the midst of a second scientific revolution or paradigm shift in autism research. From the late 1940s through the ‘60s, the dominant view was that autism is caused by poor parenting. According to Frith (1991), Leo Kanner, the first formulator of the autism syndrome, held this belief for a few years around 1944.
Scientists discovered in the 1970s that autism is not caused by poor parenting and is highly heritable – marking the first paradigm shift. Since at the time there was no evidence of cell, tissue or organ failure occurring after birth in autism it seemed reasonable to assume that autism is biologically determined, once and for all, entirely before birth.
There is an increasing awareness that the etiopathology of autism often involves morbid events occurring in the brain after birth. This suggests that post-natal pathological events could heavily contribute to onset of autism and characterizes the second paradigm shift. In fact, very little brain abnormality, if any at all, is found in newborns who will later receive a diagnosis of autism (Elsabbagh and Johnson, 2010). Brain imaging has established that there is an early post-natal peak of brain overdevelopment (high cerebral volume) in idiopathic autism spectrum disorder (ASD) at about one year of age, followed by overcompensation (low cerebral volume) in later childhood, followed by normalization (normal cerebral volume) in puberty and early adolescence; a pattern termed “triphasic”(Lange et al., 2015; Zielinski et al., 2014). The post-natal anomaly of MRI termed cortical anisotropy also peaks and reaches significance soon after birth in idiopathic autism, then dips and then normalizes, suggesting that subtle dysplasia of tertiary cortex and/or migrational disorder also follows the triphasic developmental pattern. See Braun, Achim & Tahakian (2017) for a meta-analysis of the macro- and ultrastructural MRI literature supporting and expanding that point of view.
The now well established “epigenetic failure” etiology of autism (Ciernia and LaSalle, 2016), the “imbalanced microbiote” etiology (Vuong and Hsiao, 2017), the “immune/inflammatory” etiology (Masi et al., 2015), and the “defective gamma aminobutyric acid (GABA)-conversion” etiology (Ben-Ari, 2015) are all post-natal. These new perspectives on post-natal etiologies of autism led LeBlanc and Fagiolini (2011) to propose that there exists a critical post-natal period of vulnerability to autistic brain disorder in infancy. The “defective GABA-conversion” etiology of autism is particularly relevant to the high risk of epilepsy known to affect people with idiopathic autism.
Severe seizures, as in West (WS), Lennox-Gastaud (LGS), Dravet or Ohtahara syndromes, or uninterrupted prolonged electrical paroxysm as in
Nevertheless, even if epileptic seizures might not, of themselves, be a cause of autism, age at seizure on set in autism could time-tag (flag) post-natal central nervous system disturbance leading directly to autism. In particular, excessive neocortical synaptic excitability could be an obvious such vector (Brix et al., 2015; Brooks-Kayal, 2010; Kang and Barnes, 2013; Markram et al., 2007; Nelson and Valakh, 2015; Rubenstein and Merzenich, 2003). Weakness of the neural GABA inhibitory network is a commonly evoked mechanism postulated to underlie this anomaly in the autistic brain (Ben-Ari, 2015; Brix et al., 2015; Bozzi et al., 2018; Kang and Barns, 2013; Van Kooten et al., 2005). Commensurately, patients with autism are averse to many sorts of stimulation (Oberman et al., 2007) and report feeling over-stimulated at all times (Grandin, 1992).
Idiopathic autism comprises a high risk of epilepsy, i.e., between 15% to 32% (Clarke et al., 2005; Matsuo et al., 2010; Tuchman et al., 2009). This is much higher than the 4% to 7.6% lifetime risk of epilepsy in the general population (Fiest et al., 2017; Pellock et al., 2016). When starting with epileptic cohorts, one also finds a high risk of autism that ranges from 5% to 35% according to the study and the type of epilepsy (Berg et al., 2011; Hesdorffer et al., 2011; Saemundsen et al., 2007). Patients with idiopathic autism remain so after their epilepsy is controlled by anticonvulsants (Wong, 1993; Tuchman, 2000), by vagal nerve stimulation (Danielsson et al., 2008) or by surgery, although their autistic symptoms may be slightly alleviated by these treatments (Nass et al., 1999; Szabó et al., 1999; Zaroff et al., 2005).
A general law of developmental psychopathology and neuropathology was proposed by Braun (2000):
On the other hand, it is also possible that age at seizure onset is a rather distinct marker of autism, independent of the global severity of brain morbidities affecting neurological patients at high risk for autistic comorbidity. Viewed in this manner, there could exist a specific interval, some time after birth; a critical period of vulnerability to some very specific insult to the brain selectively damaging only the brain structures necessary for implementation of interpersonal, social functions and abilities. This critical period could start quite early in life but not necessarily at birth (see LeBlanc and Fagiolini, 2011, for a detailed articulation of this proposal).
The first seizures occurring in idiopathic autism typically appear at around 4.7 to 14 years of age depending on the study (Mouridsen et al., 1999; Hara, 2007; Amiet et al., 2013), later than the age at which autism can be established which is now about two years of age. However, brains suffer before the first seizures manifest themselves (Berg et al., 2011) which means that endotypes or “essential comorbidities” accompanying certain epilepsies could still contribute to risk of autism.
Clarke and colleagues (2005), Juneja and colleagues (2018) and Reilly and colleagues (2014) reported epileptic case series typically seen by neurologists specialized in epilepsy. Such cases comprise a mixture of idiopathic and syndromic (typically more severe) epilepsies. They found that early seizure onset characterized autism. However, several studies of exceptionally large samples of cases, not limited to medical clinics specialized in epilepsy, found no link between idiopathic autism and early onset of seizures in what seemed to be mostly “idiopathic” (typically rather benign) epilepsy (Jokiranta et al., 2014; Wirrell et al., 2017).
As far as we could determine, age at seizure onset in autism has not yet been meta-analysed. At present, age at seizure onset is usually not documented in research on autism and epilepsy. When it is, types of epilepsy, types of central nervous system morbidity, presence/absence of autism and presence/absence of intellectual disability, are usually not fully documented. Given the state of current research on the association between epilepsy and autism, it is understandable that some authors have doubted that epilepsy is, in itself, a risk factor for autism at all in any respect (Pavone et al., 2004; Tharp, 2004), while others have reserved judgment in expectation of convincing data (Gabis et al., 2005).
There are several hundred developmental neuropathologies that involve high risk of autism (Iossifov et al., 2012) and a varied minority of them, also involve a substantial risk of epilepsy. In these conditions, it could reasonably be expected that a high risk of epilepsy and a high risk of intellectual disability (ID) could conjointly carry a particular high risk of autism. However, even in the domain of so-called “secondary” or “syndromic” autism (autism thought to be caused by a well identified brain disorder), it has not been conclusively established that early onset seizures, of themselves, consistently contribute to risk of autism.
Only a few neurodevelopmental syndromes or contexts have been found to significantly carry increased risk of secondary autism significantly in association with earlier seizure onset. This has been reported in tuberous sclerosis complex (TSC), typically an autosomic monogenic pathology with high risk of epilepsy and autism (Asano et al., 2001; Numis et al., 2011). Humphrey and colleagues (2004) described two monozygotic twins with TSC, the first with autism and the second without. The first had his first seizure at three months and the other at seven months. Bakke and colleagues (2018) found that early seizure onset significantly associated with autism in Angelman syndrome which is another syndrome that is typically autosomic, monogenic and also carries a high risk of autism. In their study of 48 cases, age at seizure onset was negatively associated with the severity of autism ratings (r = -0.61, p = 0.006). Trivisano and colleagues (2018) found that early seizure onset significantly characterizes autism in patients with the X-linked
The research questions were the following: Does early onset epilepsy characterize cases with autism more than similar cases without autism in a wide array of specific biodevelopmental, neurological, neuropsychological, genetic or epileptological conditions? If so, is there a specific interval of the lifespan during which this effect is particularly and typically statistically significant? and Are there any brain morbidities that are common in, and specific to, these neuropathological conditions?
A literature search was conducted using Google Scholar to find articles presenting a single case or a case series of patients in which each case (to be included here) had been individually characterized for age at seizure onset and had also been determined to be autistic or not. These were the only two inclusion criteria.
Age at seizure onset was coded in days. Reports specifying only age in months or years at seizure onset were accepted and age was converted to days. Any determination of age less precise than to the year was excluded from the present report. For example, cases whose seizure onset was described as occurring in “childhood” or “adolescence” or “adulthood” were excluded.
Cases “last seen before two years of age” were excluded because autism cannot be reliably determined before that age. Cases without a specific mention of age last seen but with context indicating follow up any time from late infancy on were included, and age last seen was then coded as “missing”. The median age last seen (follow up) of the patients with autism was 3467 days, mean = 4303 days, SD = 3223 days, N = 1606: age last seen was missing in 284 cases with autism (15%). The median age last seen of the patients without autism was 3650 days, mean = 5004 days, SD = 4376, N = 4336. Age last seen was missing in 587 cases (12%). The cases without autism were significantly older at last evaluation than the cases with autism (Mann-Whitney U ranks Z = 3.4, p = 0.001). Cases characterized as obtunded, prostrate, or unresponsive were also excluded. However, we cannot guarantee that all such latter cases were excluded because some reports did not cover those dimensions explicitly.
The diagnostic criteria of autism, both in the APA and ICD diagnostic psychiatry manuals, in all the revisions, have included three types of symptoms, one more heavily weighted (interpersonal/social isolation) and the others relatively less heavily weighted (underdeveloped language, stereotypic/repetitive behavior). To be included in the present investigation and coded as autistic, a case had to be explicitly labeled autistic. Absence of mention of autism was insufficient to characterize a case as non-autistic.
For a case to be categorized as non-autistic, one of the following six criteria had to apply: A case (or the case series) was explicitly declared as non-autistic. The methodology specified that patients were evaluated for autism and then cases not labeled with autism were considered non-autistic. A table with a series of clinical cases included an explicit “autism” category with a rating of “present” versus “absent”. A case series included at least one case explicitly diagnosed with autism (it was then assumed that undiagnosed cases did not have autism). A case was explicitly termed behaviorally or psychiatrically “normal”. A case received a formal psychiatric diagnosis (e.g., attention-deficit/hyperactivity disorder, obsessive-compulsive disorder, depression) or neuropsychological diagnosis other than intellectual deficiency (e.g., Landau-Kleffner syndrome) with no mention of autism.
Many aspects of the epilepsy itself, of the epileptological, genetic, neurological or IQ test findings were noted qualitatively. These characterizations as a whole will henceforth be referred to as the
We retained, for statistical analysis, 24 such codes pertaining directly to details and characteristics of the patient’s epilepsy. For example, these codes detailed epilepsy characteristics such as scalp location, severity, tractability, type of seizure, etc. (described in Table 1 of the results section). There were 43 codes pertaining to single gene mutations on autosomes (described in Table 2 of the results section), 14 codes pertaining to single gene mutations on the X-chromosome (described in Table 3 of the results section), and 9 codes pertaining to whole or partial chromosome aberrations (described in Table 4 of the results section). Magnetic resonance imaging is one of the most informative neurological investigations currently available. In the case of autism, innovation in imaging has constantly and rapidly generated new descriptions of morbidity (e.g., subependymal giant cell astrocytoma or SEGA, radial migration tracks to nodular heterotopias in tuberous sclerosis, delayed myelination, focal cortical dysplasia, etc.). We retained 40 codes for MRI determinations (described in Table 5 of the results section). Finally, there were neuropathologically relevant conditions determinable from clinical neurology or from medical workups or IQ testing rather than MRI. These generated 32 codes (described in Table 6 of the results section). The list of these 162
Tests of a difference between autists and non-autists with regard to age at seizure onset in various epileptic conditions
Epileptic condition | Number of autistic patients | Number of non-autistic patients | Median age at seizure onset of the autistic patients (days) | Median age at seizure onset of the non-autistic patients (days) | Whole sample coefficient of variation (%) | Mann-Whitney Z (Δ between ranks) | P |
---|---|---|---|---|---|---|---|
Intractable epilepsy+ | 1146 | 2923 | 272 | 730 | 147 | 12.0 | 2.9e-33 |
Temporal lobe focus # | 128 | 639 | 546 | 1825 | 112 | 7.7 | 1.4e-14 |
Partial seizure | 187 | 828 | 300 | 1095 | 141 | 7.1 | 1.4e-12 |
Generalized tonic/clonic seizure | 621 | 1603 | 365 | 660 | 146 | 5.7 | 1.1 e-8 |
Frontal lobe focus # | 132 | 384 | 610 | 1460 | 114 | 5.3 | 1.2e-7 |
Focal seizure (not further specified) | 283 | 861 | 330 | 1095 | 133 | 5.0 | 5.3e-7 |
Absence seizure | 177 | 507 | 700 | 1278 | 106 | 4.5 | 0.000006 |
Status epilepticus awake | 154 | 299 | 240 | 330 | 154 | 2.9 | 0.003 |
ESES/CSWSS | 67 | 439 | 1277 | 1642 | 70 | 2.7 | 0.007 |
Non-refractory epilepsy | 260 | 999 | 390 | 600 | 165 | 2.4 | 0.018 |
Lennox-Gastaut syndrome | 61 | 152 | 395 | 815 | 116 | 2.3 | 0.020 |
Parietal lobe focus # | 12 | 39 | 375 | 1825 | 168 | 2.3 | 0.023 |
Infantile spasm | 234 | 364 | 120 | 150 | 183 | 2.2 | 0.027 |
Febrile seizure | 175 | 436 | 270 | 365 | 136 | 2.2 | 0.028 |
Occipital lobe focus # | 51 | 175 | 730 | 1095 | 100 | 2.2 | 0.030 |
Tonic seizure | 101 | 236 | 300 | 232 | 158 | -1.9 | 0.064 |
Dravet/SMEI syndrome | 136 | 235 | 180 | 180 | 249 | 1.8 | 0.071 |
West syndrome/hypsarrhythmia | 107 | 186 | 128 | 150 | 205 | 1.7 | 0.092 |
Atonic (drop) seizure | 87 | 172 | 450 | 720 | 101 | 1.6 | 0.114 |
Gastroenteritis-triggered seizure onset | 4 | 178 | 1225 | 570 | 108 | -1.2 | 0.238 |
Ohtahara syndrome/suppression burst | 25 | 60 | 5 | 3 | 265 | 1.0 | 0.930 |
Idiopathic epilepsy * | 320 | 1539 | 1460 | 1463 | 106 | 0.9 | 0.384 |
Myoclonic seizure | 211 | 497 | 330 | 365 | 140 | 0.8 | 0.400 |
Vaccine-contiguous seizure onset | 31 | 36 | 180 | 180 | 123 | 0.3 | 0.800 |
Intractable epilepsy was either reported as “intractable” or “refractory” or seizures were reported to have occurred during at least a year
Temporal, frontal, parietal or occipital focus was coded here as any ictal or interictal electrical anomaly limited to a single lobe: the focus could be unilateral or bilateral
Idiopathic epilepsy in the current report consisted of cases reported with no explanation or even a hypothesis of the etiology of the epilepsy
Tests of a difference between autists and non-autists regarding age at seizure onset in subsamples with a mutation of a single gene on an autosome
Mutated gene and its cytogenetic location | Number of autistic patients | Number of non-autistic patients | Median age at seizure onset of the autistic patients (days) | Median age at seizure onset of the non-autistic patients (days) | Whole sample coefficient of variation (%) | Mann-Whitney Z (△ between ranks) | p |
---|---|---|---|---|---|---|---|
DEPDC5/22q12.2-q12.3 mutation | 8 | 27 | 51 | 1095 | 116 | 3.9 | 0.00009 |
CNTNAP2/7q35-q36 mutation | 10 | 17 | 270 | 730 | 187 | 3.2 | 0.001 |
UBE3A/15q11.2 mutation | 81 | 33 | 730 | 1825 | 108 | 2.6 | 0.010 |
SCN1A/2q24.3 mutation | 126 | 277 | 180 | 180 | 188 | 1.9 | 0.053 |
ASXL3/18q12. 1 mutation | 5 | 5 | 730 | 2190 | 154 | 1.8 | 0.074 |
SLC6A1/3p25.3 mutation | 15 | 23 | 1085 | 540 | 66 | -1.7 | 0.082 |
SCN2A/2q24.3 mutation | 15 | 23 | 6 | 240 | 279 | 1.7 | 0.083 |
PTEN/10q23.31 mutation | 5 | 10 | 42 | 2373 | 132 | 1.7 | 0.085 |
HCN1/5p12 mutation | 6 | 29 | 225 | 270 | 119 | 1.7 | 0.095 |
FOLR1/11q13.4 mutation | 4 | 8 | 1577 | 41 | 148 | -1.7 | 0.109 |
EEF1A2/20q13.33 mutation | 5 | 15 | 120 | 90 | 178 | -1.6 | 0.114 |
PNPO/17q21.32 mutation | 5 | 31 | 5 | 1 | 385 | -1.6 | 0.207 |
HNRNPU/1q44 mutation | 6 | 10 | 318 | 392 | 82 | 1.5 | 0.125 |
KCNA2/1p13.3 mutation | 4 | 14 | 180 | 293 | 207 | 1.5 | 0.134 |
ANKRD11/16q24.3 mutation | 7 | 8 | 1095 | 365 | 98 | -1.5 | 0.143 |
KCNB1/20q13.13 mutation | 12 | 23 | 378 | 270 | 82 | -1.4 | 0.151 |
Miscellaneous mutations* | 167 | 455 | 547 | 720 | 146 | 1.4 | 0.163 |
ALDH7A1/5q23.2 mutation | 5 | 25 | 2 | 270 | 223 | 1.3 | 0.195 |
KCNT1/9q34.3 mutation | 7 | 10 | 270 | 913 | 227 | 1.2 | 0.221 |
TSC1/9q34.13 mutation | 6 | 21 | 215 | 540 | 103 | 1.1 | 0.316 |
PACS2/14q32.33 mutation | 4 | 9 | 34 | 4 | 257 | -1.1 | 0.330 |
CUX2/12q24.11-q24.12 mutation | 4 | 7 | 273 | 180 | 200 | -10.0 | 0.412 |
SETD1B/12q24.31 mutation | 9 | 3 | 990 | 180 | 95 | -0.9 | 0.354 |
STXBP1/9q34/mutation | 26 | 39 | 44 | 30 | 152 | -0.9 | 0.355 |
MEF2C/5q14.3 mutation | 16 | 16 | 345 | 300 | 71 | -0.9 | 0.395 |
GABRA1/5q34 mutation | 6 | 26 | 330 | 240 | 198 | -0.7 | 0.465 |
NF1/17q11.2 mutation | 4 | 42 | 1004 | 1789 | 116 | 0.7 | 0.486 |
CHD2/15q26.1 mutation | 23 | 35 | 730 | 875 | 94 | 0.6 | 0.528 |
TSC2/16p13.3 mutation | 46 | 50 | 180 | 150 | 267 | -0.5 | 0.605 |
NBEA/13q13.3 mutation | 9 | 6 | 720 | 720 | 139 | 0.5 | 0.607 |
GABRG2/5q34 mutation | 4 | 8 | 405 | 660 | 82 | 0.4 | 0.669 |
MBD5/2q23.1 mutation | 8 | 12 | 560 | 986 | 116 | 0.4 | 0.670 |
FOXG1/14q12 mutation | 3 | 12 | 150 | 180 | 255 | -0.3 | 0.770 |
SPTAN1/9q34.11 mutation | 4 | 23 | 195 | 120 | 211 | -0.3 | 0.756 |
KCNQ3/8q24.22 mutation | 8 | 8 | 900 | 1004 | 90 | 0.3 | 0.792 |
SCN8A/12q13.13 mutation | 16 | 57 | 180 | 165 | 140 | -0.3 | 0.794 |
KCNQ2/20q13.33 mutation | 13 | 60 | 4 | 3 | 282 | -0.2 | 0.838 |
SYNGAP1/6p21.32 mutation | 26 | 34 | 900 | 785 | 75 | -0.2 | 0.840 |
GRIN2A/16p13.2 mutation | 13 | 48 | 1460 | 1460 | 497 | 0.2 | 0.880 |
GABRB3/15q12 mutation | 8 | 4 | 180 | 270 | 226 | 0.1 | 0.898 |
POGZ/1q21.3 mutation | 6 | 9 | 1186 | 912 | 69 | -0.1 | 0.906 |
DNM1/9q34.11 mutation | 5 | 15 | 210 | 210 | 58 | 0.1 | 0.930 |
SHANK3/22q13.33 mutation | 7 | 13 | 2555 | 2555 | 68 | 00.0 | 10.0 |
The label “Miscellaneous mutations” assembled all cases with a mutation too infrequent in the current database to appear in the table.
Tests of a difference between autists and non-autists regarding age at seizure onset in subsamples with a mutation of a single gene located on the X chromosome
Mutated gene and its cytogenetic location | Number of autistic patients | Number of non-autistic patients | Median age at seizure onset of the autistic patients (days) | Median age at seizure onset of the non-autistic patients (days) | Whole sample coefficient of variation (%) | Mann-Whitney Z (△ between ranks) | p |
---|---|---|---|---|---|---|---|
PCDH19/Xq22.1 mutation | 130 | 192 | 270 | 315 | 127 | 3.1 | 0.002 |
SLC6A8/Xq28 mutation | 18 | 13 | 1278 | 2555 | 75 | 1.3 | 0.185 |
MECP2/Xq28 mutation | 13 | 11 | 1095 | 730 | 101 | -10.0 | 0.361 |
KIAA2022/Xq13.3 mutation | 8 | 4 | 420 | 605 | 110 | 10.0 | 0.368 |
FMR1/Xq27.3 mutation | 10 | 16 | 1460 | 913 | 79 | -0.9 | 0.354 |
SYN1/Xp11.3 mutation | 3 | 8 | 1450 | 3103 | 123 | 0.9 | 0.376 |
CNKSR2/Xp22.12 mutation | 3 | 16 | 730 | 1077 | 78 | 0.9 | 0.392 |
WDR45/Xp11.23 mutation | 3 | 15 | 780 | 450 | 116 | -0.8 | 0.426 |
ARX/Xp21.3 mutation | 5 | 10 | 30 | 120 | 286 | 0.4 | 0.664 |
CDKL5/Xp22.13 mutation | 63 | 35 | 42 | 45 | 343 | 0.3 | 0.747 |
PIGA/Xp22.2 mutation | 5 | 5 | 180 | 150 | 106 | -0.3 | 0.750 |
IQSEC2/Xp11.22 mutation | 16 | 10 | 730 | 730 | 111 | 0.2 | 0.811 |
SPTAN1/9q34.11 mutation | 14 | 5 | 528 | 540 | 141 | 0.1 | 0.888 |
SLC9A6/Xq26.3 mutation | 14 | 5 | 529 | 540 | 136 | 0.1 | 0.888 |
Tests of a difference between autists and non-autists regarding age at seizure onset in subsamples with a mutation defined only by cytogenetic location (involving several candidate genes)
Cytogenetic location of the mutation | Number of autistic patients | Number of non-autistic patients | Median age at seizure onset of the autistic patients (days) | Median age at seizure onset of the non-autistic patients (days) | Whole sample coefficient of variation (%) | Mann-Whitney Z (△ between ranks) | p |
---|---|---|---|---|---|---|---|
22q11.2 mutation | 9 | 39 | 1460 | 330 | 131 | -1.6 | 0.114 |
Ring20 mutation | 7 | 52 | 3285 | 2008 | 71 | -1.4 | 0.151 |
7q11.23 mutation | 8 | 22 | 270 | 495 | 146 | 1.3 | 0.188 |
9q21.13 mutation | 8 | 5 | 1607 | 1278 | 74 | -0.8 | 0.419 |
16p11.2 mutation | 7 | 43 | 240 | 180 | 254 | 0.6 | 0.519 |
2q24.3 mutation | 10 | 10 | 38 | 17 | 287 | -0.5 | 0.593 |
Xp22.31 mutation | 3 | 11 | 3650 | 2190 | 66 | -0.5 | 0.640 |
Trisomy-21 | 10 | 8 | 225 | 236 | 85 | 0.4 | 0.655 |
15q13.3 mutation | 5 | 30 | 3285 | 3468 | 64 | 0.1 | 0.906 |
Tests of a difference between autists and non-autists regarding age at seizure onset in subsamples with various MRI anomalies
Neurologic morbidity | Number of autistic patients | Number of non-autistic patients | Median age at seizure onset of the autistic patients (days) | Median age at seizure onset of the non-autistic patients (days) | Whole sample coefficient of variation (%) | Mann-Whitney Z (△ between ranks) | p |
---|---|---|---|---|---|---|---|
Abnormal MRI | 625 | 1704 | 300 | 720 | 156 | 7.4 | 1.1e-13 |
Focal temporal lobe damage* | 96 | 299 | 240 | 1825 | 130 | 7.1 | 1.1e-12 |
Cortical dysplasia | 187 | 400 | 210 | 730 | 168 | 5.7 | 1.4e-8 |
Focal frontal lobe damage* | 85 | 196 | 240 | 1021 | 147 | 4.5 | 0.000007 |
Subcortical dysplasia | 115 | 206 | 330 | 1020 | 152 | 4.4 | 0.00001 |
Tumor@ | 35 | 114 | 300 | 1806 | 138 | 4.1 | 0.00004 |
Hippocampal sclerosis | 18 | 76 | 210 | 1460 | 118 | 40.0 | 0.00007 |
Nodular periventricular heterotopia | 40 | 53 | 233 | 1020 | 190 | 3.9 | 0.0001 |
Focal parietal lobe damage* | 43 | 142 | 180 | 1369 | 163 | 3.6 | 0.0004 |
Focal occipital lobe damage* | 27 | 121 | 330 | 1062 | 168 | 3.4 | 0.001 |
Thin corpus callosum | 81 | 142 | 690 | 150 | 185 | -2.9 | 0.004 |
Thick cortex | 10 | 14 | 195 | 1460 | 108 | 2.7 | 0.007 |
Dysembryoplastic neuroepithelial tumor | 7 | 45 | 730 | 2993 | 86 | 2.6 | 0.009 |
Gray/white matter boundary blurring | 9 | 12 | 300 | 1004 | 141 | 2.5 | 0.013 |
Delayed myelination | 50 | 95 | 270 | 120 | 181 | -20.0 | 0.050 |
Arterovenous malformation¢ | 11 | 34 | 210 | 695 | 161 | 1.5 | 0.144 |
Ulegyria | 3 | 9 | 912 | 2555 | 84 | 1.4 | 0.165 |
Cerebellar anomaly+ | 62 | 76 | 635 | 730 | 144 | 1.4 | 0.172 |
Double cortex | 3 | 27 | 1460 | 2190 | 56 | 1.4 | 0.176 |
Encephalomalacia | 7 | 12 | 243 | 874 | 120 | 1.4 | 0.170 |
Hypothalamic hamartoma | 27 | 122 | 365 | 420 | 173 | 1.3 | 0.194 |
Central nervous system cyst△ | 27 | 63 | 365 | 365 | 173 | 1.2 | 0.225 |
Specific white matter anomaly# | 44 | 92 | 390 | 730 | 126 | 1.2 | 0.232 |
Dilated CSF space(s) | 89 | 176 | 474 | 378 | 163 | -1.2 | 0.856 |
Chiari or Dandy Walker malformation | 14 | 18 | 1275 | 1825 | 82 | 0.8 | 0.447 |
Cerebral atrophy | 146 | 301 | 345 | 360 | 183 | 10.0 | 0.296 |
Cerebrovascular accident | 18 | 91 | 315 | 240 | 227 | -10.0 | 0.302 |
Polymicrogyria | 7 | 40 | 570 | 1037 | 129 | 10.0 | 0.310 |
Arachnoid cyst | 14 | 26 | 195 | 365 | 145 | 10.0 | 0.320 |
Gliosis | 13 | 35 | 1132 | 1095 | 145 | -0.8 | 0.403 |
Encephalomalacia | 3 | 14 | 365 | 555 | 129 | 0.8 | 0.432 |
Any gyral/sulcal malformation | 18 | 94 | 1186 | 1095 | 121 | -0.4 | 0.706 |
Schizencephaly or porencephaly | 3 | 20 | 1095 | 1369 | 113 | 0.4 | 0.714 |
Hemimegalencephaly | 8 | 8 | 6 | 30 | 350 | 0.4 | 0.721 |
Subependymal giant cell astrocytoma (SEGA)μ | 22 | 24 | 218 | 240 | 143 | 0.4 | 0.724 |
Lissencephaly | 4 | 6 | 769 | 105 | 160 | -0.2 | 0.831 |
Periventricular leukomalacia | 8 | 25 | 345 | 730 | 107 | 0.1 | 0.950 |
Pachygyria | 10 | 30 | 1642 | 1095 | 114 | -00.0 | 0.963 |
– “Focal” damage to a lobe was not coded as being necessarily exclusive to the lobe but it did have to involve no more than three of four lobes (F,T,P,O); △ - Excludes arachnoid cyst; # - Usually white matter hyperintensity (excludes delayed myelination); μ - SEGA was reported only in cases with tuberous sclerosis; + - Usually atrophy @ - Usually ganglioglioma or astrocytoma (excludes SEGA); ¢ - Mostly Sturge-Weber syndrome.
Tests of a difference between autists and non-autists regarding age at seizure onset in subsamples with medical diagnoses not primarily based on MRI or in subsamples not receiving surgery for intractable epilepsy
Neurologic morbidity | Number of autistic patients | Number of non-autistic patients | Median age at seizure onset of the autistic patients (days) | Median age at seizure onset of the non-autistic patients (days) | Whole sample coefficient of variation (%) | Mann-Whitney Z (△ between ranks) | p |
---|---|---|---|---|---|---|---|
Epilepsy surgery | 168 | 595 | 210 | 1095 | 138 | 9.2 | 2.4e-20 |
Angelman syndrome phenotype | 91 | 54 | 730 | 1630 | 106 | 3.2 | 0.001 |
Tuberous sclerosis phenotype | 162 | 238 | 180 | 210 | 246 | 3.1 | 0.002 |
Vagus nerve stimulation | 61 | 199 | 365 | 1095 | 124 | 2.6 | 0.009 |
Neonatal adenylosuccinate lyase deficiency | 22 | 8 | 84 | 1460 | 114 | 2.1 | 0.032 |
Kabuki syndrome | 4 | 13 | 195 | 1095 | 87 | 20.0 | 0.045 |
Maternal diabetes | 6 | 6 | 273 | 730 | 77 | 1.9 | 0.053 |
Neonatal pyridoxin deficiency | 13 | 104 | 14 | 2 | 660 | -1.9 | 0.057 |
Neonatal/infantile hypoglycemia | 13 | 51 | 180 | 730 | 100 | 1.9 | 0.059 |
Hypotonia documented at birth | 45 | 49 | 540 | 330 | 143 | -1.9 | 0.062 |
KBG syndrome | 8 | 10 | 2738 | 468 | 84 | -1.8 | 0.074 |
Bainbridge-Ropers syndrome | 5 | 5 | 2190 | 730 | 154 | -1.8 | 0.074 |
Various metabolic syndromes # | 18 | 24 | 278 | 730 | 141 | 1.6 | 0.117 |
Hydrocephaly | 8 | 24 | 210 | 727 | 143 | 1.5 | 0.127 |
Encephalitis | 26 | 69 | 695 | 1450 | 110 | 1.5 | 0.137 |
Low Apgar score (<7) | 4 | 17 | 90 | 453 | 140 | 1.4 | 0.150 |
Microcephaly (OFC)@ | 170 | 254 | 365 | 270 | 162 | -1.4 | 0.174 |
Intellectual deficiency | 950 | 1475 | 360 | 365 | 146 | 1.2 | 0.219 |
Temple-Baraitser syndrome | 3 | 9 | 985 | 270 | 134 | -1.2 | 0.226 |
Cerebrovascular accident | 18 | 91 | 315 | 240 | 227 | -10.0 | 0.302 |
Rett syndrome phenotype | 49 | 26 | 960 | 730 | 112 | -10.0 | 0.330 |
Cornelia De Lange syndrome | 11 | 19 | 1333 | 150 | 128 | -10.0 | 0.331 |
Neonatal folate deficiency | 10 | 17 | 635 | 132 | 133 | -0.9 | 0.393 |
Congenital hyperbilirubinemia | 11 | 9 | 300 | 1095 | 133 | 0.8 | 0.403 |
Nicolaides-Baraitser syndrome | 12 | 19 | 638 | 540 | 118 | -0.8 | 0.428 |
Any severe fetal distress or at birth | 155 | 262 | 450 | 365 | 151 | -0.9 | 0.372 |
Williams-Beuren syndrome | 6 | 16 | 303 | 635 | 138 | 0.9 | 0.376 |
Phelan-McDermid syndrome | 25 | 12 | 2555 | 2008 | 66 | -0.6 | 0.569 |
Asphyxia/anoxia at birth | 28 | 54 | 387 | 348 | 144 | -0.5 | 0.649 |
Autoimmune encephalitis* | 3 | 22 | 1934 | 2445 | 60 | 0.3 | 0.738 |
Periventricular leukomalacia | 8 | 16 | 345 | 1004 | 103 | 0.3 | 0.787 |
Macrocephaly (OFC)@ | 40 | 52 | 365 | 870 | 144 | 0.2 | 0.822 |
Various mitochondrial syndromes | 18 | 8 | 450 | 1095 | 123 | 0.2 | 0.845 |
Head trauma | 6 | 33 | 2463 | 2555 | 114 | 00.0 | 0.969 |
– All cases had Rasmussen’s encephalitis except one autist who had anti-NMDA receptor encephalitis; @ OFC – occipitofrontal circumference (3 percentile limit), measured at birth except occasionally in childhood.
Most distributions of age at seizure onset in the various neuropathological conditions failed the Kolmogorov-Smirnov tests of normality and had coefficients of variation so high (see figure 1c) as to preclude parametric testing. Accordingly, the non-parametric Mann-Whitney U test was used for all comparisons of age at seizure onset of independent samples, namely the autistic versus non-autistic patients, and central tendencies will be reported as medians rather than means (Tables 1 to 6 and figure 1 of the Results section). Each table ranks the conditions by decreasing Mann-Whitney Z value of the difference in ranks between the cases with versus without autism. To be included as a row in any table, a
A total of6792 cases with epilepsy were collected and individually characterized for the present report. The list of 1440 references from which the cases were drawn in Word format is associated with the present report as a Supplementary data file. A PDF version of each of these 1440 articles is available upon request from the first author. The SPSS file used for statistical analysis, or converted to Excel for English language viewers, are available from the first author, allowing for complete verification of all raw data and statistics.
The 162 statistical inference tests reported in Tables 1 to 6 replicated all five relevant significant findings previously reported in the literature and reviewed by us in the introduction. Tuberous sclerosis, the
Beyond replication of previous findings, results expand the
To determine why certain neuropathological conditions present the
Of the 162 neuropathological conditions, 39 (24%) did yield a significant difference. Of the latter, 38 (97%) respected Braun’s principle (Reilly et al., 2014) as well as the LeBlanc et al proposal (LeBlanc and Fagiolini, 2011), i.e., the cases with autism had earlier seizure onset and the ensemble revealed a tight post-natal critical period. The only exception was the “thin callosum” condition (row 11 of table 5) which significantly associated later seizure onset with autism. Altogether, the standard effect in secondary (or syndromic) autism, when significant, is earlier seizure onset in the cases with autism, i.e., the
The
Overview and depiction of age at seizure onset in autism vs non-autism and consideration of possible arti-factual interpretations
Overview of tables 1 to 6 in a single figure (Figure 1) was planned to help the reader get a sense of the general profile of the findings (the 162 rows of tables 1 to 6) and gage alternative explanations of the profile of effects, other than clinically meaningful, i.e., as artifacts. To this end, we scatterplotted the 162 effects, expressed as the Mann-Whitney Z values of the difference between ranks, in ordinate, and various parameters in abscissa. The main findings are depicted in Panel A of figure 1, illustrating that significant autism-specific effects of age at seizure onset a) virtually always consisted of earlier onset in the cases with autism than the cases without autism, and b) occurred during a clearly post-natal period of vulnerability
Could the global period of vulnerability to the
None of the
There were 29
In short, the
In the present study, the main carrier of the
It is possible that intractability of seizures is the main driver of the
As will be detailed in the next two sections, we propose that there is a second very important factor in the
Another major carrier of the
In the present study the prevalence and timing of FCD’s role in the
FCD is the most common cause of medically refractory epilepsy (Kabat and Król, 2012). Several reports of repeat MRI in children describe undetectability of FCD at first MRI reading but salient detection upon a repeat MRI (Jeon et al., 2017; Yoshida et al., 2008). Evidence from MRI and from post-mortem histology (Miyata et al., 2013; Spreafico, 2010) has recently established that FCD progresses after birth by exacerbating or entailing any combination of the following: focal white/grey matter blurring, proliferation of localized patches of abnormally giant cortical neurons, focal changes in cortical and callosal thickness, focal neuronal heterotopia (or dyslamination), post-natal brain enlargement, focal disruption of myelin, focal calcification, ganglioglioma, and even focal gyral/sulcal malformation (polymicrogyria, ulegyria, pachygyria, lissencephaly, schizencephaly). Adverse perinatal events such as asphyxia, brain bleeds and shunted hydrocephaly are significantly associated with FCD (with the latter always detected later with MRI), and several authors reporting these findings believe that the former causes the latter more than the latter the former (Redfearn et al., 2005). Most importantly for our purposes here, several findings have documented synaptic and chemical changes in FCD, occurring after a post-natal interval, thought to directly cause seizure onset (Marin-Valencia et al., 2014).
We note that Angelman syndrome (AS), however, could be in a special category; not explainable by FCD. AS, which significantly manifested the
In the present study, another major carrier of the autism-specific early seizure onset effect was morbidity occurring in the social brain, far more than other brain areas. In their authoritative and exhaustive review of the social
An