Clinical and neuropsychological characterization of Jacobsen syndrome (del11q)

Abstract

Background

Jacobsen Syndrome (JS), also known as 11q Deletion Syndrome (del11q), is a rare genetic disorder affecting approximately 1 in 100,000 births that presents with varied clinical manifestations and severities including intellectual disability, psychomotor delays, and distinctive physical traits. This study offers a detailed analysis of the clinical and cognitive profiles of individuals with JS and examines how these characteristics are related to each other and to genetic variables.

Methods

Twenty-nine participants with JS (20 female, mean age 12.48 years, SD = 9.13) underwent standardized assessments assessing cognitive functioning, adaptive behavior, autistic traits, and general psychopathology. A CGH array was used to assess genetic deletions. We employed descriptive and inferential statistical analyses to explore the association between clinical and cognitive characteristics and deletion size.

Results

Sixty percent of participants had verbal language. Mean intelligence quotient was 50.18, the range of adaptive functioning was very broad, and 43% showed behaviors exceeding the ADOS-2 cutoff for autism spectrum classification. A higher cognitive performance was associated with better adaptive skills, including more advanced language skills and with more depressive symptoms or a diagnosis of depression. Larger deletions were associated with more delays in developmental milestones and poorer cognitive functioning. No significant association was found between haploinsufficiency of the KIRREL3 and ARHGAP32 genes and cognitive functioning or autistic characteristics.

Conclusions

Our findings provide deeper insights into the complex relationship between genetic factors and clinical attributes in individuals with JS, revealing notable clinical variability within the JS population. This information may help predict developmental difficulties as genetic findings emerge.

Supplementary Information

The online version contains supplementary material available at 10.1186/s11689-025-09659-9.

Introduction

Jacobsen Syndrome (JS) (OMIM#147791), also recognized as 11q Deletion Syndrome (del11q), is a genetic anomaly occurring at an estimated rate of 1 in 100,000 births, with a female-to-male ratio of 2:1 [1]. Stemming from a deletion on chromosome 11’s long arm, this syndrome manifests with diverse clinical features and varying severity. While the immune and cardiac systems are predominantly affected [2], involvement of additional organs and systems (e.g., kidneys, genitals, endocrine, auditory, or ophthalmological) is also common. Although JS has a heterogeneous clinical expression, its core clinical attributes encompass intellectual disability (ID), psychomotor and physical growth delays, and distinctive physical features, including ocular hypertelorism, down slanting palpebral fissures, strabismus, broad nasal bridge, short nose, thin upper lip, v-shaped mouth, syndactyly, low-set or malformed ears, and toe anomalies [1, 3]. More recently, other facets, such as attention deficits, impulsivity, and features resembling autism have been also documented [4].

Previous studies have established that the size of the genetic deletion in JS may vary among affected individuals. While findings are diverse, with some studies showing no clear relationship between deletion size and clinical outcomes [4, 5], others have indicated a significant correlation. For instance, research suggests a strong link between deletion size and neurocognitive outcomes, with larger deletions being associated with more severe cognitive impairments, including global language deficits and the lowest total intelligence scores [1]. Similarly, other research has shown that larger deletions, particularly those exceeding 12 Mb, are linked to a higher likelihood of severe intellectual disability, with global cognitive scores falling below 50 [3]. Furthermore, haploinsufficiency of some genes included in the 11q region, predominantly KIRRELL3 and ARHGAP32, have been reportedly associated with neurocognitive delay and/or autistic traits in individuals with JS [4, 6–9].

The existing literature examining the neurocognitive profile of individuals with JS reported various cognitive profiles [1, 3, 5], including some individuals with normal cognitive development [9]. Previous studies typically include small samples (10–14 individuals) and have found a wide range of intellectual functioning, with most exhibiting mild intellectual disability [1, 3, 5]. Grossfeld [1] demonstrated a distinctive language profile in participants with JS and mild ID, with a near-normal level of receptive language and mild to moderate impairment in expressive language. Adaptive behavior scores have been reported as low to moderately low [5].

Regarding autistic traits, a study with 17 participants found that 47% met the criteria for autism spectrum disorder (ASD). However, the authors found no correlation between deletion size and the presence of ASD, suggesting that the identified autism “critical region” in distal 11q, which includes four annotated genes such as ARHGAP32, might not be directly implicated in the expression of autistic traits in JS [4]. A case study on the smallest interstitial deletion, which included the deletion of the KIRRELL3 gene, described the subject as having intellectual disability and autism [6].

Despite the available information, prior studies have primarily focused on describing the medical features of JS, with limited information on its cognitive and psychiatric profile. A detailed picture of the autistic symptomatology, including observational and indirect measures, is lacking. A thorough clinical and neurocognitive evaluation can help to identify the specific needs of individuals with JS to guide interventions. Due to the rarity of JS, with only around 250 reported cases globally [10], most studies have included small samples, often with fewer than 14 participants undergoing cognitive assessments, primarily from the United States (U.S), with limited information available from other geographical contexts. The heterogeneous expression of JS and the associated medical and psychiatric complexities underscore the importance of a more thorough phenotypic characterization.

In this study, we aim to describe and analyze the association of genetic, clinical and cognitive characteristics in a Spanish sample of individuals with JS. To this end, we used an extensive set of standardized clinical, cognitive, and behavioral measures including the presence and degree of ID, behavioral problems, linguistic skills, adaptive functioning, and ASD symptoms. We also analyzed the association of these phenotypic characteristics with the deletion size and the presence or absence of haploinsufficiency of the KIRRELL3 and ARHGAP32 genes.

Methods

Participants

The study included 29 participants, 20 females and 9 males, with ages ranging from 2 to 45 years at the time of assessment. Among them, two participants are a mother and daughter, and two others are siblings. All participants were recruited from the Spanish association “11q España” from 2019 to 2021.

The inclusion criteria consisted of having a diagnosis of JS, confirmed through molecular techniques (i.e., MLPA, CGH-array, or FISH), with available information regarding the size and region of the chromosomal rearrangement.

We conducted assessments at University Hospital Gregorio Marañón in Madrid, when possible. During the most restrictive times of the COVID-19 pandemic, some assessments were conducted in the participants’ cities, following healthcare recommendations. All neuropsychological assessments were conducted by the same researcher, a health psychologist with established inter-rater reliability against a gold standard for the Wechsler cognitive tests and the Autism Diagnostic Observation Schedule–2. The hospital ethics committee approved the study. All the participants or a legal representative provided written informed consent prior to participation in the study.

Materials and assessment

Demographic and clinical evaluation

All demographic and clinical information was gathered through an interview with parents and/or other relevant informants and verified with provided medical reports. These interviews included participant’s age at diagnosis, sex, ethnicity, socioeconomic status using the Hollingshead-Redlich scale [11], which ranks socioeconomic status from 1 to 5 (highest to lowest) based on the highest level of education and occupation of the parents. We also gathered participant medical history and subsequently coded using the Cumulative Illness Rating Scale (CIRS) [12]. Additional information collected included psychiatric diagnoses, obstetric complications through the Murray-Lewis Obstetric Complications Scale [13], pharmacological treatment history, and acquisition of developmental milestones.

Behavioral manifestations were assessed using parent-reported questionnaires, applied only to individuals within the age ranges validated for each instrument. The Child Behavior Checklist (CBCL) [14] is a questionnaire for children aged 1.5–5 and 6–18 years that identifies problem behaviors. These behaviors include emotionally reactive, anxious/depressed, withdrawn, somatic complaints, sleep problems, social problems, thought problems, attention problems, rule-breaking, and aggressive behaviors. These scales are grouped into internalizing problems, externalizing problems, and total problems. The Strengths and Difficulties Questionnaire (SDQ) [15] is a brief behavioral and emotional screening questionnaire for children and adolescents from 4 to 17 years old. It has four subscales to measure major difficulties commonly experienced by children and adolescents (conduct problems, hyperactivity-inattention, emotional symptoms, peer problems) and one subscale to assess strengths (prosocial behavior). Both the CBCL and the SDQ provide cutoffs for borderline and clinically relevant altered behaviors. We considered scores above the borderline cutoff as altered behavior. The Aberrant Behavior Checklist-Community (ABC-C) [16] is a 58-item rating scale used to assess maladaptive behaviors across five original dimensions or subscales: Irritability, Hyperactivity, Lethargy/Withdrawal, Stereotypy, and Inappropriate Speech. To allow for relative comparison across subscales, participants’ ABC-C scores in each subscale were divided by the number of items in that subscale, resulting in mean values ranging from 0 to 3 according to the test item scores with the following meaning: 0 = the behavior is not a problem, 1 = the behavior is a mild problem, 2 = the behavior is a moderate problem, 3 = the behavior is a severe problem. Coordination was measured using the Questionnaire for the Diagnosis of Developmental Coordination Disorder [17] for participants from 5 to 14 years old.

Cognitive functioning assessment

We evaluated cognitive functioning primarily using age-appropriate scales. Intelligence quotient (IQ) was measured using the Wechsler Intelligence Scale for Children, 5th Edition [18] for participants aged 6 to 16 years, and the Wechsler Adult Intelligence Scale, 4th Edition [19] for those aged 16 and older. For minimally verbal participants between the ages of 4 and 21, the Wechsler Nonverbal Scale of Ability [20] was administered. All Wechsler scales are standardized with a mean IQ of 100 and a standard deviation of 15. The developmental quotient (DQ) was assessed using the Merrill-Palmer-Revised scales [21], a standardized (mean 100, SD: 15) evaluation of development for children up to 6.5 years.

For participants who could not complete an age-appropriate Wechsler test due to significant difficulty in understanding or responding to instructions, we used the Merrill-Palmer scales to estimate mental age. In these cases, IQ was standardized by calculating it as mental age/chronological age * 100 [22].

Participants for whom we were unable to conduct any cognitive ability tests due to severe disability were considered to have a standard score below 55 for the purposes of comparison in this study.

Language assessment

Participants’ expressive language capacity was clinically observed by the examiner and categorized as: no words, single words, simple sentences, and fluid speech. The criteria for single words and simple sentences were the same as those outlined in the ADOS-2. Single words are defined by their purposeful, contextually appropriate use, with evidence of a variety of words rather than just a few repeated ones. Simple sentences involve the combination of two or more words into basic syntactical structures that are used spontaneously in communication. The criteria used to define “verbal” in this study included the ability to produce simple sentences and fluid speech. Receptive language was evaluated via the Peabody Picture Vocabulary Test, 3rd edition (PPVT-III) [23]. This tool assesses listening and understanding of single-word picture names for people over 2 years and 6 months and offers a value of verbal IQ and mental age. To minimize floor effects in this instrument (given the minimum score of 55), we standardized scores using the formula: (mental age/chronological age*100) obtaining a mean of 100 and a SD of 15 [22].

To assess language ability, we also considered the communication subdomains of receptive and expressive language on the Vineland Adaptive Behavior Scales-3 [24]. The scores for these subdomains are called V-scores and have a mean of 15 and a standard deviation of 3.

Adaptive skills

Adaptive behavior (AB) was assessed using the comprehensive parent/caregiver form of the Vineland Adaptive Behavior Scales-3 (VABS-3) [24], a standardized instrument for ages 0–90 that encompasses four domains with several subdomains: (i) communication (subdomains “expressive”, “receptive” and “written”), (ii) daily living (subdomains “personal”, “domestic” and “community”), (iii) socialization (subdomains “interpersonal relationships”, “play” and “coping skills”), and (iv) motor (subdomains “gross” and “fine”), although the latter only considers children up to 9 years. The domain standard scores range from 20 to 160, with a population mean of 100 and a standard deviation of 15.

Autistic symptomatology

The Autism Diagnostic Observation Schedule–2 (ADOS-2) [25] and the Autism Diagnostic Interview–Revised (ADI-R) [26] were administered to assess and quantify autistic traits [27]. The ADOS-2 is a standardized, semi-structured observation of communication, social interaction, and restricted and repetitive behaviors, with different tasks depending on the age and verbal ability from 12 months to adulthood. It includes different modules tailored to developmental and language level: Module Toddler (T) for children 12–30 months without phrase speech; Module 1 for individuals of any age without phrase speech; Module 2 for those using phrase speech but not fully verbally fluent; Module 3 for verbally fluent children and adolescents; and Module 4 for verbally fluent adolescents and adults. Classification criteria vary by module: Modules T, 1, and 2 rely on exceeding the total score cutoff alone, whereas Modules 3 and 4 require exceeding cutoffs in both Social Affect (SA) and Restricted and Repetitive Behaviors (RRB) domains as well as the total score. The ADOS-2 provides 2 distinct cutoffs for behavioral compatibility, named Autism Spectrum Disorder and Autism cutoffs respectively. We also calculated ADOS-2 calibrated severity score (CSS), scored 0–10 [28] to have a comparable measure of ASD severity across ages and modules. The ADI-R is a structured interview conducted with parents of individuals from 24 months to adulthood that permits an exhaustive assessment of early development encompassing the domains of reciprocal social interactions (A), language and communication (B), restricted, repetitive and stereotyped behaviors and interests (C), and anomalies in neurodevelopment arising before 36 months old (D). It establishes the criteria for autism as exceeding the cutoff points in all four domains. Additionally, the following parent-reported questionnaires caregivers completed: Repetitive Behaviors Scale–Revised (RBS-R) [29], which covers various repetitive and restrictive behaviors, including stereotyped behaviors, self-injurious behaviors, compulsive behaviors, ritualistic behaviors, behavior invariance, and restrictive behaviors. Scores range from 0 to 3 for each item, indicating the absence of the behavior (0), mild [1], moderate [2], or severe [3] problem. Scores for each subscale were divided by the number of items in that subscale, thus resulting in total mean values ranging from 0 to 3. The Social Responsiveness Scale-2 (SRS-2) [30] provides an assessment of the severity of autistic symptoms (awareness, cognition, communication, motivation, mannerisms) in daily contexts of children from 2 years and 5 months to 18 years old; it provides standard scores that are classified into the following groups: within normal limits, mild range, moderate range, and severe range. The Sensory Profile-2 (SP-2) [31] is a questionnaire that measures sensory processing for children aged 3–14 years and provides three classifications of sensory processing: quadrants (including seeking, avoiding, sensitivity, and registration), sensory sections (including auditory, visual, tactile, movement, body position, and oral), and behavioral sections (behavioral, socioemotional, and attentional). The scores are categorized into: “like others,” “less or much less than others,” and “more or much more than others”.

All measures were administered in their Spanish-language versions. Most instruments were officially translated, validated, and standardized for use in the Spanish population, including the Wechsler scales, CBCL, SDQ, DCD-Q, PPVT-III, MP-R, SP-2, and ADOS-2. For certain tools, such as the VABS-3, ABC-C, and SRS-2, although official Spanish translations were used, no normative data are currently available for the Spanish population. Therefore, scoring was based on the original normative samples developed in the U.S. In the case of the ADI-R, a validated Spanish translation was used, but cut-off scores are likewise derived from the original U.S. norms. Lastly, for the Hollingshead-Redlich scale, CIRS, and the Murray-Lewis Obstetric Complications Scale, we used the available Spanish translations, which are commonly employed in clinical and research settings; however, these instruments lack formal validation and standardized normative data for the Spanish population, so original U.S. norms were applied.

Genetic information

Genetic information was retrieved from existing genetic reports to confirm the diagnosis of JS. This included data on the type of genetic test used, the size of the deletion and its chromosomal coordinates, the presence of any other genetic alterations, and the age at diagnosis. For cases where genetic information was obtained from tests other than a CGH-array, we conducted CGH-array testing in site to ensure a consistent measure of deletion size across all samples.

Data analysis

The research data was securely stored and organized using the Research Electronic Data Capture (REDCap) tools, hosted at the Gregorio Marañón Health Research Institute. REDCap is a specialized web-based tool designed to enhance the efficiency of data collection procedures for academic research initiatives [32].

We tested the normality of the data using the Kolmogorov-Smirnoff test. Data were distributed in a non-normal mode for most of the clinical variables; this fact, along with the small sample size, led us to choose non-parametric tests for the inferential analyses. For descriptive analysis of the demographic and clinical variables we employed descriptive statistics (mean, median, standard deviation). We performed chi-square tests (reporting Fisher’s exact test) or Mann-Whitney U tests for comparisons between groups. All demographic and clinical variables were compared among participants based on their intellectual functioning using a cutoff of 55 in IQ or DQ (i.e., borderline or mild or intellectual disability vs. moderate, severe or profound intellectual disability), adaptive skills (cutoff of 70 in VABS-3), presence or absence of ASD according to ADOS-2, and the deletion status of KIRREL3 and ARHGAP32. In addition to the dichotomized analysis, AB (VABS-3 composite score) was also examined as a continuous variable, exploring its associations with other continuous measures using Spearman rank correlation coefficients.

To explore associations between deletion size and behavioral variables, we employed Spearman rank correlation coefficients for quantitative variables and Mann-Whitney U tests for qualitative variables. Statistical significance was determined with a threshold of p < 0.05, while p < 0.10 was considered indicative of a non-significant trend. As measures of effect size, we used odds ratios for Fisher’s exact test, eta squared for the Mann-Whitney U test, and rho for Spearman’s rank correlation. Wherever we do not report effect size, it is due to the inability to calculate it, often because there were no participants in a given group. Additionally, we converted the odds ratios and eta-squared values to Cohen’s d for Fig. 1 to standardize the effect size values presented. We used R version 4.3.2 to generate the figure [33].

Fig. 1.

Distribution of adaptive behavior domain scores (VABS-3) in the sample. Note: Boxplots represent the distribution of standard scores for each VABS-3 domain across participants (N = 28, except Motor Skills, N = 13). Individual data points beyond this range are shown as outliers

Results

Demographic and clinical characteristics of the sample

The study cohort comprised individuals with a mean age of 12 years (SD = 9) and a median of 9 years, with a predominantly female representation (68.9%). All participants were of Caucasian ethnicity. The families represented a range of socioeconomic statuses, encompassing all levels. The mean age at diagnosis was 6 years, with a range from birth to 39 years; the mode and median age at diagnosis were 2 years. Around 60% of the participants displayed simple sentences or fluid speech and 75% showed motor acquisition delay. The mean age of first words was 27 months (median 25 months) and 25 months in the case of first steps without support (median 24 months). In the VABS-3, the mean V-score for the receptive language subdomain was slightly lower than for expressive language (8.32 vs. 9.07), although the difference did not reach statistical significance, with 95% confidence intervals of 6.51–10.13 and 7.28–10.83, respectively. The PPVT-III yielded scores in the low range, with several participants exhibiting a floor effect. Results for standardized scores showed a mean of 39 with a range from 10.8 to 80.7.

Over half of the sample (51.72%) had a comorbid psychiatric/neurodevelopmental disorder, as reported by clinical records. Attention deficit hyperactivity disorder (ADHD) was the most prevalent diagnosis (n = 10), with various comorbidities, including ADHD and obsessive-compulsive disorder (OCD) (n = 1), ADHD and conduct disorder (n = 2), and ADHD co-occurring with conduct disorder and depression (n = 1).

Regarding the medical history, the most frequent somatic conditions were cardiac problems (77.8%), with 22.2% requiring surgical intervention; hematology problems (63%), with 18.5% experiencing significant bleeding episodes; birth (46.2%) and neonatal problems (63%); growth problems (55.6%); and ocular anomalies (51.9%). Among those with ocular anomalies, the most common were refractive defects (59.3%), strabismus (48.1%), and/or ptosis (44.4%).

According to the CBCL, 54.4% of participants had internalizing problems and 54.5% had externalizing problems. In total, 59.1% of the sample exhibited emotional or behavioral problems. The most common specific problems were social problems (68.8%), attention problems (59.1%), withdrawal (50%), isolation/depression (43.8%), thought problems (43.8%), somatic complaints (40.9%), and aggressive behaviors (36.4%). As per the SDQ, 50% of the participants had behavioral difficulties, with the most frequent being hyperactivity (81.25%) and peer relations difficulties (62.5%). 83.3% of the participants had a coordination problem.

All demographic and clinical characteristics can be seen in Table 1.

Table 1.

Demographic and clinical characteristics

Demographic characteristics
Sex (n = 29)	N	%
Female/Male	20/9	68.9/31.0
Age (n = 29)	N	%
0–5 years	5	17.2
6–11 years	12	41.3
12–17 years	5	17.2
≥18 years	7	24.1
	mean (SD)	range
Total	12.48 (9.13)	2–45
Deletion size (n = 29)	mean (SD)	range
Number of MB	9.8 (3.3)	4.0–15.3.0.3
Ethnicity (n = 29)	N	%
Caucasian	29	100
Socioeconomic status (n = 28)	N	%
1- Upper class	6	21.4
2- Upper-middle class	7	25
3- Middle class	6	21.4
4- Lower-middle class	5	17.9
5- Lower class	4	14.3
Language level
Language acquisition (n = 29)	N	%
No words	3	10.3
Single words	9	31
Simple sentences	5	17.2
Fluid speech	12	41.4
PPVT-III IQ (n = 22)	mean (SD)	range
PPVT-III IQ	39.02 (19.94)	10.8–80.7
VABS-3 (n = 28)	mean (SD)	range
VABS-3 receptive	8.32(4.65)	1–17
VABS-3 expressive	9.07(4.61)	1–16
Developmental milestones	N	%
Delayed gait acquisition (> 18 months) (n = 27)	20	74.1
Delayed acquisition of first words (> 2 years) (n = 25)	12	48
Enuresis (> 5 years) (n = 23)	12	52.2
Encopresis (> 4 years) (n = 24)	8	33.3
Psychiatric antecedents
Psychiatric diagnosis (n = 29)	N	%
ADHD	10	34.4
Conduct disorder	5	17.2
Depression	3	10.3
Gender dysphoria	1	3.4
ASD	1	3.4
OCD	1	3.4
*CBCL (N = 22)	N	%
Emotionally reactive (n = 6)	1	16.6
Anxious/depressed (n = 22)	3	13.6
Isolation/Depression (n = 16)	5	31.2
Somatic complaints (n = 22)	9	40.9
Withdrawn (n = 6)	3	50
Sleep problems (n = 6)	0	0
Social problems (n = 16)	11	68.7
Thought problems (n = 16)	7	43.7
Attention problems (n = 22)	13	59
Rule-breaking (n = 16)	2	12.5
Aggressive (n = 22)	8	36.3
Internalizing problems (n = 22)	12	54.5
Externalizing problems (n = 22)	12	54.5
Total problems (n = 22)	13	59
*SDQ (n = 16)	N	%
Emotional Symptoms	3	18.8
Conduct problems	5	31.3
Hyperactivity	13	81.3
Peer relations difficulties	10	62.5
Difficulties with prosocial behaviour	7	43.8
Total	8	50
Coordination (n = 12)	N	%
Coordination disorder	10	83.8
Medical problems	N	%
Birth problems (n = = 26)	12	46.2
Neonatal problems (n = 27)	17	63
Cranial anomalies (n = 26)	12	46.2
Cardiac problems (n = 27)	21	77.8
Cardiac intervention (n = 27)	6	22.2
Hematology problems (n = 27)	17	63
Significant bleeding episodes (n = 27)	5	18.5
Immune system anomalies (n = 27)	8	29.6
Immune system treatment (n = 27)	7	25.9
Feeding difficulties (n = 27)	11	40.7
Weight problems (n = 27)	10	37
Growth problems (n = 27)	15	55.6
Digestive anomaly (n = 27)	9	33.3
Thyroid anomaly (n = 27)	3	11.1
Seizure episodes (n = 27)	1	3.7
Magnetic Resonance Imaging (MRI) findings (n = 23)	17	73.9
Urinary tract anomalies (n = 27)	5	18.5
Genital anomalies (n = 26)	6	23.1
Ocular anomalies (n = 27)	14	51.9
Ptosis (n = 27)	12	44.4
Eyelid anomalie operated (n = 27)	4	14.8
Strabismus (n = 27)	13	48.1
Refractive defects (n = 27)	16	59.3
Hearing loss (n = 27)	6	22.2
Other problems (n = 27)	26	96.3

MB megabases, PPVT-III Peabody Picture Vocabulary Test ·rd edition, VABS-3 Vineland Adaptive Behaviour Scales-3, IQ Intelectual Quotient, ADHD Attention Deficit Hyperactivity Disorder, ASD Autism Spectrum Disorder, OCD Obsessive-Compulsive Disorder, CBCL Child Behavior Checklist, SDQ Strengths and Difficulties Questionnaire

*The different sample sizes (N) in the CBCL scales are due to some scales being specific to participants aged 1.5 to 6 years n = 6) or 6 to 18 years (n = 16), while some scales are common to both groups (n = 22). For the CBCL and the SDQ, we consider the number of participants who score above the borderline or pathological cut-off

Cognitive functioning, adaptive behavior, and autism symptomatology

IQ assessment using the Wechsler intelligence tests (N = 11) indicated an overall mean IQ of 50.18 with a range of 30–75. When calculating the DQ using the Merrill Palmer scale, for participants within the norms of their chronological age (n = 4), the mean was 36 with a range of 10–70. For participants who underwent the Merrill Palmer assessment beyond the age norms of the scale (n = 8), the standardized scores calculated were a mean of 37.84 with a range of 10.8–75.9.

When classified by disability level according to the DSM-IV-TR [34] we found that 17.3% of participants with available cognitive assessment had borderline intellectual functioning, 17.3% mild intellectual disability, 21.7% moderate intellectual disability, 26% severe intellectual disability, and 17.3% profound intellectual disability. None had cognitive functioning within the normal range.

In relation to adaptive skills, parent-reported AB (n = 28) revealed consistent deficits across all domains: communication, daily living skills, socialization, and motor skills, showing a mainly homogenous profile of global impairment with a total mean score of 65.75 (SD = 19.19; range = 26–109).

Figure 1 shows the distribution of standard scores for each VABS-3 domain using boxplots. Further details can be found in Table 2 [see Additional file 1].

Table 2.

Cognitive functioning, adaptive behavior, and autistic traits of the sample

Cognitive functioning (N = 23)
Intellectual level (n = 23)	N	%
Borderline	4	17.3
Mild Intellectual Disability	4	17.3
Moderate Intellectual Disability	5	21.7
Severe Intellectual Disability	6	26
Profound Intellectual Disability	4	17.3
IQ (n = 11)	mean (SD)	range
Wechsler Scale	50.1(16.1)	30–75
DQ (n = 4)	mean (SD)	range
Merrill Palmer-R Development Scale	36 (25)	10–70
Estimated IQ (n = 8)	mean (SD)	range
Mental age/chronological age * 100	37.7	10.8–75.9
Adaptive behavior (N = 28)	mean (SD)	range
VABS-3 Communication (n = 28)	60.57(23.26)	20–108
VABS-3 Daily living skills (n = 28)	63.39(21.69)	13–118
VABS-3 Socialization (n = 28)	68.86(20.89)	32–112
*VABS-3 Motor skills (n = 13)	61.85(19.73)	20–87
VABS-3 Total adaptive composite (n = 28)	65.75(19.19)	26–109
Autistic traits
ADOS-2 (n = 28)	N	%
Nonspectrum	16	55.17
ASD	6	21.42
Autism	6	21.42
ADI-R (n = 27)	N	%
Qualitative abnormalities in reciprocal social interaction	13	44.8
Qualitative abnormalities in communication	10	37
Restricted, repetitive, and stereotyped patterns of behavior	9	31
Anomalies in neurodevelopment arising before 36 months old	26	89.7
Domains A, B, C and D	4	14.8
SRS-2 (n = 20)	N	%
SR Normal	6	30
SR Mild	4	20
SR Moderate	5	25
SR Severe	5	25
RBS-R (n = 24)	mean
Stereotyped behaviour	1.14
Self-injurious behaviour	0.69
Compulsive behaviour	0.52
Ritualistic behaviours	1.26
Behavioural invariance	0.75
Restrictive behaviour	1.45
Sensory Profile (n = 15)	like others (N)	less/more (N)
Quadrants:
Seeking	11	0/4
Avoiding	10	0/5
Sensitivity	7	0/8
Registration	5	0/10
Sections:
Auditory	9	1/5
Visual	9	0/6
Touch	8	0/7
Movement	8	0/7
Body Position	8	0/7
Oral	9	1/5
Conduct	8	0/7
Social Emotional	9	1/5
Attentional	7	0/8

ASD Autism Spectrum Disorder, IQ Intellectual Quotient, DQ Developmental Quotient, VABS-3 Vineland Adaptive Behaviour Scales-3, ADOS-2 Autism Diagnostic Observation Schedule–2, ASD Autism Spectrum Disorder, ADI-R Autism Diagnostic Interview–Revised, SRS-2 Social Responsiveness Scale-2, SR Severity range, RBS-R Repetitive Behaviors Scale–Revised, ADI-R Domain A: Qualitative abnormalities in reciprocal social interaction, Domain B: Qualitative abnormalities in communication, Domain C: Restricted, repetitive, and stereotyped patterns of behavior, Domain D: Anomalies in neurodevelopment arising before 36 months old

Standardized scores are presented using 100 as mean and 15 as standard deviation, except for the VABS-3 receptive and expressive subdomains, which are presented using a mean of 15 and a 3 as standard deviation, and the RBS-R, which includes scores with a severity range from 0 to 3

*The different sample size (n = 13) in the “motor skills” domain of the VABS-3 is due to this domain only being applicable up to 9 years of age

Assessment of autism symptomatology using the ADOS-2 test revealed that 42.8% (7 female and 5 male) of the sample scored over the cutoff for ASD, half of which scored over the more severe cutoff for autism. Median ADOS-2 severity scores were 3 for social affect (SA), 1 for repetitive and restrictive behaviors (RRB), and 2.5 for total severity score. Most participants (89.7%) exhibited developmental alterations before the age of 3 in the ADI-R (n = 27), with only four participants meeting all criteria for autism using this instrument. The mean scores in the RBS-R (n = 24) were generally very low, ranging from 0.15 to 0.46 across the different scales.

In the SRS-2 questionnaire (n = 20), half of the sample fell within a range of moderate to severe impairment, indicating behaviors that significantly interfere with daily social interactions.

The SP-2 (n = 15) revealed that most participants align with the general population, with some scoring above average in certain sensory modalities, namely auditory (33.3%), visual (40%), touch (46.6%), movement (46.6%), body position (47.6%), and oral (33.3%) processing. Regarding sensory quadrants, for sensitivity and registration quadrants, 53.3% and 66.6% of the participants respectively scored above average. As for seeking and avoiding sensory stimuli, approximately 30% of participants scored above average. Only 6.6% scored below the normative range in the sensory sections auditory and oral processing, as well as in the social emotional behavioral section.

We conducted a comparison across all variables between males and females and found no significant differences.

All details about cognitive functioning, AB and autism symptomatology can be found in Table 2.

Comparison based on cognitive functioning, adaptive behavior, and ASD traits

Comparison based on intellectual or developmental quotient

Participants with borderline or mild ID (IQ or DQ > 55) achieved earlier developmental milestones such as taking their first steps without support (p = 0.007, η2 = 0.14) than participants with moderate to profound ID. In terms of language, the group with borderline or mild intellectual disability exhibited higher standard scores in both receptive (p = 0.008, η2 = 0.24) and expressive (p = 0.002, η2 = 0.32) language, as well as higher communication (p = 0.005, OR = 17.00 [2.26–127.74.26.74]) and total (p = 0.020, OR = 9.44 [1.43–62.23]) scores on the VABS-3 when compared to the group with moderate to profound intellectual disability, with strong effect sizes. Regarding psychopathology, participants with borderline or mild intellectual disability had a higher incidence of depression diagnosis (p = 0.010) and were more likely to score in the pathological range for anxious/depressed (p = 0.006), attention problems (p = 0.050), externalizing problems (p = 0.040), and total problems (p = 0.050) as measured by the CBCL. Additionally, this group exhibited higher levels of irritability (p = 0.005, η2 = 0.11) according to the ABC-C. Concerning autistic symptomatology, participants with borderline or mild ID had lower scores in ADI-R Domain B (Qualitative Abnormalities in Communication) (p = 0.020) and showed higher percentages of ritualistic behaviors (such as adhering to schedules, following certain itineraries, and rigidity in play) (p = 0.050, η2 = 0.15) according to the RBS-R test, when compared with participants with moderate to profound ID. They also scored more often outside the normal range in visual processing (p = 0.040) according to the SP-2.

Comparison based on adaptive behavior

Participants with borderline or normal AB (standard score > 70 on VABS-3) demonstrated significantly better outcomes in several developmental milestones and areas, including no delays and/or alterations in crawling acquisition (p = 0.010, OR = 0.026 [0.001–0.538]), gait acquisition (p = 0.006, OR = 0.047 [0.005–0.424]), in fine psychomotor acquisition (p = 0.005, OR = 0.028 [0.002–0.387]), or in the acquisition of gross psychomotor skills (p = 0.009, OR = 0.039 [0.003–0.484]) than the group with low AB. They achieved their first steps without support (p = 0.003, η² = 0.292) and said their first words (p = 0.050, η² = 0.136) earlier. Additionally, they were less likely to show a coordination disorder (p = 0.010).

In terms of psychopathology, the group with borderline or normal AB had a higher prevalence of depression diagnoses (p = 0.010) and lower scores in peer relations difficulties (p = 0.040) as measured by the SDQ, and in stereotypy (p = 0.010, η² = 0.16) according to the ABC-C, than the group with low AB. They also exhibited a milder degree of ID, with a strong effect size (p = 0.020, OR = 9.44 [1.43–62.23]), and superior receptive (p = < 0.001, η² = 0.53) and expressive (p = 0.003, η² = 0.30) language abilities (noting that these are subdomains of the same test) compared to those with low AB. With respect to autism traits, those with borderline or normal AB were less likely to exceed the cutoffs for domains A (p = 0.006) and B (p = 0.050) of the ADI-R than those with low AB. They also showed better communication skills (p = 0.010, η² = 0.13), fewer mannerisms (p = 0.030, η² = 0.28), and lower total scores (p = 0.010, η² = 0.31) on the SRS-2. Moreover, they exhibited less stereotyped behavior (p = 0.010, η² = 0.13) and fewer self-injurious behaviors (p = 0.009, η² = 0.14) than the group with low AB as measured by the RBS-R.

When AB was examined as a continuous measure, significant correlations were observed with most of the same variables identified in the dichotomous analysis. However, additional associations emerged, including age of first words, total severity score on the ADOS-2 (p = 0.020, ρ=–0.44), all domains of the ADI-R, including domain C (p = 0.020, ρ=–0.43) and domain D (p = 0.040, ρ=–0.39), SRS-2 social motivation (p = 0.050, ρ=–0.44), RBS-R behavioral invariance (p = 0.030, ρ=–0.44), and SP-2 registration quadrant (p = 0.050, ρ=–0.50) and movement section (p = 0.010, ρ=–0.62). Additionally, a significant correlation was found with SDQ difficulties in prosocial behavior (p = 0.010, ρ = 0.059). Full results of these analyses are provided in Supplementary Table 3.

Comparison based on ASD traits

No significant relationship was found between meeting the ASD cutoff on the ADOS-2 and any developmental milestones, coordination disorder, deletion size, psychiatric comorbidities or traits, cognitive functioning, language level, or adaptive skills.

Figure 2 shows the effect size for statistically significant comparisons. Further details can be found in Supplementary Table 2 [see Additional file 1].

Fig. 2.

Effect size of demographic and clinical variables between subgroups based on cognition and adaptive behavior. Legend- Effect size of statistically significant differences in demographic and clinical variables between subgroups based on cognitive functioning (mild to moderate intellectual disability vs. severe or profound intellectual disability) and adaptive behavior (higher/lower than 70). Note: To unify the effect sizes presented in the figure, we converted the odds ratios and eta-squared values to Cohen's d

Association of the clinical and cognitive phenotype with the genetic findings

Exploring the genetic markers KIRREL3 and ARHGAP32, we found no significant association between having a deletion of these genes and cognitive functioning scores, presence of language, AB, or ASD as measured by the ADOS-2. However, participants lacking KIRREL3 exhibited a trend towards higher social affect severity (p = 0.09, η² = 0.127) and total severity (p = 0.06, η² = 0.165) scores on the ADOS-2.

Parental genetic testing identified a paternal and a maternal translocation in 3 participants (two of which were siblings). As mentioned, two participants were mother and daughter. The mean deletion size in the del11q region was 9.8 MB, and 9 participants exhibited additional genetic alterations, mainly duplications in other chromosomes. We found an association between a larger deletion size and several developmental milestones and delays, specifically: later age of first steps without support (p = 0.039, r = 0.400), earlier age of suspected developmental disharmony (p = 0.015, r= −0.455), and later age of first words (p = 0.003, r = 0.592) and phrases (p = 0.028, r = 0.607). Larger deletions were also associated with lower cognitive functioning score (p = 0.056, r = 0.403) and higher ABC-C inappropriate speech score (p = 0.013, r = 0.469).

In terms of medical problems, a larger deletion size was associated with neonatal complications issues (p = 0.004, η2 = 0.304), cranial anomalies (p = 0.011, η2 = 0.267), hematological anomalies (p = 0.003, η2 = 0.332) as significant bleeding (p = 0.00111, η2 = 0.420), feeding difficulties (p = 0.028, η2 = 0.179), urinary tract anomalies (p = 0.021, η2 = 0.212) or strabismus (p = 0.031, η2 = 0.183).

Additionally, we conducted a comparison between individuals with only the 11q chromosome deletion and those who had additional genetic anomalies. There were no differences in the size of the 11q deletion between the two groups. Participants with additional genetic anomalies had a higher prevalence of encopresis (p = 0.021, OR = 13.000 [1.701–99.375]), lower cognitive ability scores (p = 0.050, η2 = 0.187), and a higher frequency of low AB in communication as measured by the VABS-3 (p = 0.019, η2 = 0.160). Furthermore, they also showed poorer performance in the expressive language subdomain (p = 0.030, η²=0.169), worse motor skills (p = 0.018, η2 = 0.572), and lower scores in the total VABS-3 score (p = 0.044, η2 = 0.079) compared with those who only had the 11q chromosome deletion without other genetic findings.

Discussion

This study provides the most comprehensive neurocognitive characterization of individuals with Jacobsen syndrome (JS) focusing on clinical, cognitive, behavioral, and genetic aspects to date. Previous studies have included fewer than 14 subjects in behavioral or cognitive assessments [1, 5, 35], with only one study addressing AB [5] and another focusing on ASD [4]. In contrast, we successfully recruited 29 participants from across Spain, representing nearly all individuals registered with this syndrome in the country. This not only makes our sample the largest studied for neurocognitive aspects, but also provides a uniquely detailed and homogeneous characterization in terms of geographic origin and enhances the representativeness of the findings, particularly by providing data from a European population to complement previous studies conducted primarily in the U.S.

Our results confirm and extend previous findings underscoring the heterogeneity of JS and its broad impact across multiple domains, including intellectual functioning, AB, and autism symptomatology.

Clinical and behavioral characteristics

Consistent with earlier studies [1], 68% of our sample were female, compared to 65% in Grossfeld’s cohort with 110 participants. In our study, we conducted a sex-based comparison and found no significant differences between sexes across any of the variables, which suggests that the phenotype is characteristic of the syndrome itself, rather than influenced by sex. A significant proportion of our participants (60%) were verbal, using simple sentences or fluid speech. However, communication abilities and receptive language were markedly impaired, as shown by the low standardized scores on the PPVT-III and the VABS-3 results, which indicated that the mean V-score for the receptive language subdomain was marginally lower than for expressive language, regardless of intellectual capacity. Individuals with a moderate or mild degree of ID (IQ 50–75, n = 8) showed slightly lower scores for receptive than for expressive language (11.88 vs. 13.13), with 95% confidence intervals of 8.34–15.41 and 10.70–15.55.70.55, respectively. This finding contrasts with Grossfeld [1], who noted that 5 out of 6 participants with mild ID (IQ 50–75) had receptive language scores one standard deviation higher than those for expressive language. Nevertheless, they found no differences when considering all intellectual capacities. One factor that may explain this discrepancy is the difference in assessment tools employed across studies, as the previous study used a direct observation test, whereas our study used a parent-reported questionnaire. This highlights the need for standardized tools and assessment homogenization to accurately capture the language profiles of individuals with JS.

Our study also revealed that most participants experienced significant delays in motor and language milestones, with the mean age for first words at 27 months and first steps without support at 25 months. These delays are consistent with previous reports by Grossfeld [1] and Coldren [3].

Psychiatric and neurodevelopmental comorbidities were highly prevalent in our sample, with over half of the participants diagnosed with conditions such as ADHD, which was the most common diagnosis. Although Mattina’s 2009 review reported one case each of schizophrenia and bipolar disorder, we did not observe these diagnoses in our sample [10]. The high prevalence and variability of psychiatric comorbidities underscore the necessity for comprehensive psychiatric evaluations in JS participants to better understand and manage their complex needs.

The most prevalent medical problems in the sample affected the cardiac and hematological systems. Approximately half of the sample experienced birth problems, and over half had complications during the neonatal period. Other frequent issues included cranial anomalies, ocular anomalies, growth problems, and feeding problems. These findings are consistent with those reported in the literature [10]. In the present study, none of the studied medical conditions were associated with developmental variables, cognitive ability, adaptive functioning, psychiatric comorbidities, or autistic traits. This suggests that these medical conditions may not directly influence or contribute to the variability observed in these domains and that medical conditions might be relatively independent of the neurodevelopmental and behavioral profiles specific to JS.

Cognitive functioning

One of the challenges of this study was the difficulty in measuring cognitive abilities in participants with intellectual disabilities across all ages, given the lack of standardized instruments for this purpose. Consequently, we had to standardize scores in cases where age-appropriate tests were unavailable, and in some cases, we were unable to conduct the assessment at all, typically among those who were severely affected in terms of intellectual functioning or had severe attention deficits.

For participants who underwent intellectual assessment, the data revealed a wide range of cognitive abilities, with an overall mean IQ of 50.18, ranging from 30 to 75. This variability is consistent with that reported in previous studies, although we found slightly lower cognitive functioning overall. Grossfeld [1] reported a mean IQ of 49 with scores ranging from 40 to 98, Coldren [3] reported ranges from 40 to 81, and Fisch [5] documented IQ ranges from 36 to 80 and 43 to 79 with means of 63.88 and 62 at different times. The observed variability reflects a range of cognitive abilities, with mild to severe intellectual disability being the most common. Mattina’s review [10], which included 200 reported subjects, noted that mental development is normal or borderline in less than 3% of cases; in our study, no participant had normal cognitive capacity, highlighting the pervasive cognitive impairment in JS.

This study is the first to examine the relationship between cognitive ability, adaptive skills, and the presence of autistic symptomatology across several clinical variables. Although significant associations were found between higher cognitive functioning and various variables, the effect sizes were weak or non-significant in most cases. Therefore, these findings should be interpreted with caution, given the small sample size.

Notably, there was a significant association, with a large effect size (p = 0.02, OR = 9.44 [1.43–62.23]), between higher cognitive functioning (IQ or DQ > 55) and better AB. We also found a significant relationship between higher cognitive functioning (IQ or DQ > 55) and better communication informed by the VABS-3, with strong effect size (p = 0.005) [OR = 17.00 (2.26–127.74)], as well as lower qualitative abnormalities in communication according to the ADI-R Domain B (p = 0.020). These results highlight the potential interconnection of cognitive, adaptive, and language development in JS.

Adaptive behavior

Our study found that AB, as measured by the VABS-3, displayed consistent deficits across all domains, with a total mean score of 65.75 (SD = 19.19; range = 26–109). These findings are consistent with previous research by Fisch [5], who similarly reported AB scores more than two standard deviations below the mean (55.13 and 51.63) in different assessments using also the VABS-3. While the group averages indicate low adaptive functioning, individual variability was considerable, with scores ranging from severely impaired to average functioning. This heterogeneity highlights the complexity of adaptive functioning in JS and the necessity of individualized assessment to properly guide personalized interventions and the design of appropriate educational and therapeutic support strategies.

Participants with borderline or normal AB achieved developmental milestones earlier and demonstrated fewer motor problems compared to those with lower AB scores. They also exhibited superior communication skills, fewer repetitive behaviors, and lower scores on the Social Responsiveness Scale-2 (SRS-2), indicating fewer autism-related behaviors. Furthermore, they were less likely to show qualitative abnormalities in reciprocal social interaction and communication according to the ADI-R, compared to those with low AB. When AB was analyzed as a continuous variable, these associations were largely confirmed, and additional significant correlations emerged with broader autism-related domains (including ADI-R domains C and D, and the ADOS-2 total severity score), social motivation (SRS-2), prosocial difficulties (SDQ), behavioral invariance (RBS-R), and sensory processing patterns (SP-2 registration and movement). This suggests that adaptive functioning in JS is closely intertwined not only with developmental milestones and motor outcomes, but also with social, behavioral, and sensory domains, supporting its role as a multidimensional marker of functional capacity (see Supplementary Table 3).

Our findings showed that higher IQ was associated with more ritualistic behaviors, whereas higher adaptive functioning was linked to lower levels of stereotyped and self-injurious behaviors. Although this may appear as a divergence in the relationship between cognitive and adaptive functioning in relation to autistic symptoms, it can be understood by considering the different components assessed by the RBS-R. While participants with higher cognitive functioning exhibited more ritualistic behaviors—such as insistence on sameness and rigidity—those with better adaptive functioning showed less frequent stereotyped and self-injurious behaviors. These findings are consistent with previous literature suggesting that these behavioral patterns reflect distinct dimensions. Richler [36] identified two separate clusters within restricted and repetitive behaviors (RRBs): repetitive sensorimotor (RSM) behaviors—such as hand and finger mannerisms, complex body movements, repetitive use of objects, and unusual sensory interests—and insistence on sameness (IS) behaviors, which include rituals, compulsions, resistance to change, and rigid adherence to routines. Their results showed that higher nonverbal IQ was associated with milder RSM behaviors but was not related to IS behaviors. In contrast, milder social-communicative impairment was linked to greater severity of IS behaviors. Our findings may thus reflect this distinction between RRB subdomains.

Interestingly, our data suggest that individuals with higher IQ and better adaptive skills, including advanced language abilities, displayed more depressive symptoms/diagnoses, thus suggesting that higher functioning individuals may be at increased risk for depression. This phenomenon can be attributed to several factors. Enhanced self-awareness resulting from superior cognitive and language skills may lead to increased stress and frustration as these individuals become more acutely aware of their limitations. Furthermore, it may be easier to assess affective symptoms in this population due to their advanced communication skills, making these symptoms more apparent. Additionally, advanced language and adaptive skills expose individuals to more social interactions and comparisons, heightening their awareness of social disparities and increasing the likelihood of experiencing discrimination and peer rejection or victimization. This increased exposure can foster feelings of isolation and low self-esteem, thereby increasing the risk of depression. Therefore, while higher cognitive and adaptive functioning typically confer benefits, they can also elevate psychological vulnerability. This highlights the need for comprehensive mental health support tailored to individuals with JS, considering how different factors may influence their psychological well-being.

ASD traits

Assessment of autism symptomatology revealed that 42.8% of the sample received a classification of ASD according to ADOS-2 criteria. This prevalence is comparable to the 47% reported by Akshoomoff [4] and highlights the significant overlap between JS and ASD. It is important to note that the ADOS-2 provides a classification, not a clinical diagnosis, and it was used in this study as part of a broader assessment of autistic traits. Even though nearly half of the sample met criteria according to the ADOS-2, only 14.8% met al.l the criteria according to the ADI-R. This discrepancy can be explained by the different classification thresholds of both assessments. While the ADI-R is based on caregiver report and requires meeting criteria in four specific domains, the ADOS-2 is based on direct observation and relies primarily on the total score (except for Module 4), which can result in an ASD classification for individuals with high social affect scores even when stereotyped or repetitive behaviors are less prominent. Indeed, according to the RBS-R, our participants exhibited very few stereotyped or repetitive movements, which is noteworthy given that this subscale is commonly elevated in populations with ID and ASD [37]. Nevertheless, despite the high rates of autistic traits observed in the sample, the majority of participants did not meet the ADOS-2 cut-off, and only a small proportion exceeded the threshold on the ADI-R. These findings highlight the importance of comprehensive clinical evaluation to determine whether autistic traits in individuals with JS reflect a true diagnosis of ASD. In some cases, these traits may overlap with features commonly seen in other neurodevelopmental conditions, including ID, rather than constituting a distinct autism phenotype. However, it is also possible that some individuals with JS present with an atypical autism profile, differing from that of idiopathic ASD, which may result in subthreshold scores on gold standard instruments despite the presence of clinically relevant symptoms.

Interestingly, we found no significant relationship between meeting the ASD cutoff on the ADOS-2 and various developmental milestones, coordination disorders, deletion size, or other cognitive and behavioral traits. This lack of association could be due to the unique neurodevelopmental and genetic characteristics of JS, which may influence the manifestation of autism traits in a different manner than in idiopathic ASD, where lower IQ is often associated with greater autism severity [38]. Contrary to our expectations, we did not find any statistical differences between individuals who met ASD criteria and those who did not, particularly in relation to sex. Contrary to findings in the general population, where ASD shows a marked male bias, we did not find statistically significant differences in the proportion of males and females meeting ASD criteria in our sample. Akshoomoff [4] found that 80% of males and 33% of females with JS met ASD research criteria, suggesting that while the sex bias persists, females with this deletion have a higher risk compared to the general female population In our study, the proportion of females meeting ASD criteria according to the ADOS-2 (36.8%) was more similar than usual to the proportion in males (55.6%) in idiopathic ASD samples, which may help explain the lack of statistically significant sex differences. These results support the hypothesis that the 11q deletion may confer an elevated risk for ASD traits in both males and females, and that the typical male predominance seen in ASD may not apply in this specific genetic population. Consistent with this, evidence from the literature indicates that sex ratios in ASD tend to be more balanced in rare genetic syndromes [39]. Similarly, in populations with intellectual disability, ASD prevalence rates often show less pronounced sex differences compared to the general population [40]. These parallels suggest that genetic etiology and neurodevelopmental profiles may attenuate the usual male predominance in ASD.

Finally, it is important to contextualize these findings within the broader literature on syndromic autism. Standardized tools such as the ADOS-2 and ADI-R have been widely used in populations with genetic conditions that present with autistic features, including Fragile X syndrome [41–43] and Down syndrome [44, 45]. The ADOS-2 standardization sample also included individuals with a variety of non-ASD neurodevelopmental conditions - such as ID, language disorders, ADHD, mood disorders, early developmental delays, and Down syndrome- reflecting an intention to ensure applicability across diverse developmental profiles [25]. This broader representation supports its potential utility in heterogeneous populations. However, while these tools are considered gold standards for ASD assessment, their clinical utility and psychometric validity have not yet been specifically established for rare populations such as JS. More data are needed to validate their use in this population, particularly given the complex neurodevelopmental profiles and high rates of ID observed in JS.

Genetics

Our study found that a larger deletion size contributes to a more severe cognitive and behavioral phenotype in JS. Specifically, we observed strong correlations between deletion size and key developmental milestones, including independent steps, first words and phrases, and developmental disharmony. Notably, larger deletions were associated with a higher likelihood of medical issues, such as neonatal problems, hematological issues, and significant bleeding episodes (with moderate effect sizes).

Coldren [3] also reported a correlation between larger deletions and lower IQ scores, but noted that severe intellectual disabilities could still occur with smaller deletions, thus suggesting other genetic or environmental factors at play. Our findings support this notion, showing a significant association between deletion size and cognitive outcomes, indicating that the extent of chromosomal deletion plays a notable role in determining intellectual functioning. Given that the presence of additional genetic alterations correlates with worse cognitive outcomes, these alterations may play a role in contributing to higher intellectual disability in individuals with smaller deletions. Notably, the three participants in our sample who exhibited severe or profound disability and had small deletion sizes (around 4 MB) also had an additional genetic anomaly. This supports the idea that severe cognitive impairments can arise even when the chromosomal deletion is relatively small, as noted by Coldren [3]. This contrasts with Fisch [5], who did not find a significant relationship between deletion size and IQ in the correlation he made with 7 participants. These discrepancies may be attributed to various factors, including differences in measurement methods and assessment tools and sample size.

Regarding the haploinsufficient genes KIRREL3 and ARHGAP32, we found no statistically significant relationship between deletions of these genes and cognitive functioning or ASD, as measured by the ADOS-2. However, there was a trend suggesting that participants lacking KIRREL3 might exhibit higher social affect severity and total severity in autism symptomatology. Akshoomoff [4] identified a “critical region” in distal 11q, including ARHGAP32, in 17 subjects with autism. Guerin [6] reported the smallest interstitial deletion including KIRREL3 in a subject with intellectual disability and autism, and Nakamura [8] highlighted the essential role of ARHGAP32 in normal cognitive function in mice, thus suggesting that its deficiency contributes to behavioral deficits. Taken together, available evidence suggests a potential role of KIRREL3 in the neurodevelopmental profile of JS, highlighting the need for further research to confirm these associations.

Limitations and implications

While our study provides valuable insights, it has limitations. First, the sample size, although the largest for a comprehensive neurocognitive study of JS to date, is relatively small, which may limit the generalizability of our findings. This is common in studies of rare genetic conditions like JS. Second, the absence of a comparison group with other neurodevelopmental disorders also restricts our ability to draw definitive conclusions about the specificity of certain phenotypic features to JS. Additionally, our reliance on parent-reported measures for some constructs introduces the potential for reporting bias. Some instruments used in the study, while available in Spanish, lack standardized normative data for the Spanish population, which may limit the direct comparability of scores. Nevertheless, the comprehensive approach used in our study, with inclusion of both observational and indirect measures to address different clinical and behavioral manifestations of this population enhances the reliability and significance of our findings. Furthermore, we decided to dichotomize the adaptive skills, cognitive functioning, and autistic traits based on clinical and conceptual considerations. While this approach facilitated interpretation and grouping, it may have reduced variability and statistical sensitivity. To address this, we also conducted an analysis using AB as a continuous variable, which yielded results largely consistent with the dichotomous approach and provided additional significant associations. This complementary strategy supports the robustness of our conclusions, while also highlighting the value of continuous analyses in future studies with larger samples.

Future research should also include longitudinal studies tracking developmental trajectories in larger cohorts of individuals with JS to elucidate the progression of cognitive and behavioral symptoms over time. Exploring the impact of early intervention strategies and educational support on the development and the functional outcomes of this population could provide valuable insights for clinical practice.

Conclusions

These comprehensive findings contribute to our understanding of the complex interplay between genetic factors and various cognitive aspects in individuals with del11q, emphasizing the heterogeneity within this population. Specifically, our cohort revealed that 60% of participants were verbal. Most of the sample showed broad impairments in adaptive functioning. Their disability levels ranged from borderline intellectual functioning (17.3%) to severe or profound intellectual disability (43.3%). Notably, 43% met the cutoff for ASD classification in the ADOS-2, and over half had a comorbid psychiatric or neurodevelopmental disorder, including a high prevalence of ADHD.

Our study also identified significant relationships between deletion size and developmental, clinical, and cognitive outcomes. Participants with additional genetic alterations exhibited more severe cognitive and behavioral phenotypes. We also found a notable connection between higher cognitive capacity, more adaptive skills, and better language abilities with an increased risk of depression. Further research is warranted to elucidate the underlying mechanisms and potential therapeutic interventions tailored to the specific needs of individuals with del11q such as autistic symptoms or the presence of psychopathology, and to address the demands of their families. This information can also guide educational and professional services addressing the specific needs of people with JS.

Authors’ contributions

Alexandra Garriz-Luis conducted the research study and wrote the article. Covadonga M Díaz-Caneja and Celso Arango contributed as project creators and by reviewing the manuscript. Elisa Rodríguez-Toscando, Mónica Burdeus-Olavarrieta and Mara Parellada contributed by reviewing the manuscript as experts in the field.

Funding

This study was funded by the Spanish Association for 11q España. Drs. Arango, Parellada, and Díaz-Caneja have received support by the Spanish Ministry of Science and Innovation, Instituto de Salud Carlos III (ISCIII) (JR19/00024, PI17/00481, PI19/01024, PI20/00721, PI22/01824, PI23/00625, PI14/02103, PI17/00819, PI20/01382, PI23/00747) co-financed by the European Union, ERDF Funds from the European Commission, “A way of making Europe”, financed by the European Union - NextGenerationEU (PMP21/00051),), CIBERSAM, Madrid Regional Government (B2017/BMD-3740 AGES-CM-2), European Union Structural Funds, European Union Seventh Framework Program, European Union H2020 Program under the Innovative Medicines Initiative 2 Joint Undertaking: Project PRISM-2 (Grant agreement No.101034377), Project AIMS-2-TRIALS (Grant agreement No 777394), Horizon Europe (Grant agreement No.101034377101057182; project Youth-GEMs), the National Institute of Mental Health of the National Institutes of Health under Award Number 1U01MH124639-01 (Project ProNET) and Award Number 5P50MH115846-03 (project FEP-CAUSAL), Fundación Familia Alonso, and Fundación Alicia Koplowitz. Alexandra Garriz has received funding from the Intramural Research Promotion Program of the Health Research Institute Gregorio Marañón University Hospital (IiSGM).

Data availability

No datasets were generated or analysed during the current study.

Declarations

Ethics approval and consent to participate

The ethics committee of the Hospital General Universitario Gregorio Marañón approved the study. All the participants or a legal representative provided written informed consent prior to participation in the study.

Consent for publication

All authors provide their consent for the publication of the manuscript, including any accompanying images or data contained within the manuscript.

Competing interests

Dr. Arango has been a consultant to or has received honoraria or grants from Abbot, Acadia, Ambrosetti, Angelini, Biogen, Boehringer, Gedeon Richter, Janssen Cilag, Lundbeck, Medscape, Menarini, Minerva, Otsuka, Pfizer, Roche, Sage, Servier, Shire, Schering Plough, Sumitomo Dainippon Pharma, Sunovion, Takeda and Teva. Dr. Díaz-Caneja has received honoraria from Angelini and Viatris and travel support from Janssen and Angelini. The rest of the authors report no conflicts of interest related to this work.