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Publications

Date Revised: September 2026

Thank you to all the families for participating in Simons Searchlight. Through your involvement, we aim to assist researchers and geneticists worldwide in understanding genetic disorders affecting you or your family.

The research conducted using Simons Searchlight data has resulted in numerous published papers. These papers undergo a peer-review process, where other scientists assess and validate the research before publication in scientific journals. Additionally, some findings are shared via preprints, allowing rapid dissemination of information to the scientific community.

Many of the publications feature the name “Simons Variation in Individuals Project” (SimonsVIP), which was the original name of our research program, now known as Simons Searchlight.

The listed articles are organized from newest to oldest. You can explore publications by specific genetic conditions using the categories below.

As of September 2026, Simons Searchlight has contributed to 144 publications and preprints, and we will continue to summarize new publications.

For accessibility, the Simons Foundation encourages researchers to make their publications open access. If you cannot access a journal article, we recommend reaching out to the last author listed on the paper to request a copy.

Understanding Publication Reference Titles:

-The article title is followed by publication details, including where and when it was published.
– If there are more than three authors, we use “et al.” to represent additional contributors.
– Journals are referenced using shorthand names.

Disclaimer: Please be aware that papers posted on medRxiv (pronounced med-archive) or bioRxiv (pronounced bio-archive) are not peer-reviewed or edited before online publication. In contrast, all other articles listed here have undergone review by fellow researchers to ensure quality and accuracy. While posting on medRxiv or bioRxiv allows researchers to share findings quickly, the final published results may differ after undergoing formal peer review for journal publication.

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Genetic Condition
Year of Publication
144 Publications
Discovering the gene-brain-behavior link in autism via generative machine learning
  • The researchers used machine learning to study how brain mass is distributed and how it changes. This technique allowed the researchers to examine cell movement, organization, and cell changes in the brain. The researchers hypothesized that machine learning could detect more subtle changes in the brain than the human eye. Show More
  • The researchers studied brain images from Simons Searchlight participants, including 48 with 16p11.2 deletion and 40 who were 16p11.2 duplication carriers. The researchers also studied 118 people with no genetic conditions.
  • The researchers found that genetic cohorts are more unique based on white matter distribution (parts that look white on brain imaging and are involved in transmitting brain signals) than gray matter distribution (parts that appear gray on brain imaging and are involved in receiving brain signals).
  • The researchers suggested that nearly everyone with a deletion or duplication had detectable brain structure changes. Consistent with other research, the researchers found that people with 16p11.2 deletions have tissue overgrowth and people with 16p11.2 duplications have tissue undergrowth. With issues in brain areas associated with processing emotions, abilities to perceive visible space in their environment, ability to handle multiple sensory inputs, and language.
  • The researchers used three-dimensional (3D) transport-based morphometry (TBM) to assign scores to specific medical features in people with 16p11.2 deletion or duplication syndrome.
  • A negative TBM score in gray or white matter was associated with having an articulation disorder (an inability to make speech sounds).
  • The researchers suggested that certain common changes in the brain matter of the cerebral cortex of 16p11.2 deletion carriers or duplication carriers were linked to IQ levels. The cerebral cortex is the outer layer of the human brain.
  • This research was supported by a grant from the Simons Foundation Autism Research Initiative (SFARI). Show Less
Sci Adv 10, eadl5307 (2024)
Kundu et al.
Full Article

16p11.2 deletion
16p11.2 duplication
2024

Nav1.2 channel mutations preventing fast inactivation lead to SCN2A encephalopathy
  • Genetic variants in SCN2A-related syndrome result in a gain of function, a loss of function, or a mixed function of the SCN2A protein. It is not always obvious how a change in the SCN2A gene will affect the SCN2A protein. To better understand this requires testing in the research laboratory. Show More
  • Researchers tested different SCN2A genetic variants to learn how they would affect the SCN2A protein, called the Nav1.2 channel. Variants that affect protein function can result in abnormal brain cell activity.
  • The researchers used some SCN2A data from Simons Searchlight.
  • The researchers studied the following missense variants: p.Asn1662Asp, p.Leu1657Pro, p.Pro1658Ser, p.Ala1659Val, p.Phe1651Cys, p.Met1501Val, and p.Met1501Thr.
  • The researchers found that the p.Pro1658Ser, p.Ala1659Val, p.Phe1651Cys, p.Met1501Val, and p.Met1501Thr variants resulted in a gain of function SCN2A protein and over excitability of the Nav1.2 channel.
  • Variants p.Asn1662Asp and p.Leu1657Pro caused a Nav1.2 channel that could not be turned off, resulting in the early-infantile developmental and epileptic encephalopathy medical features associated with a gain of function.
  • The researchers suggested that their method is better at detecting the subtle variant differences in SCN2A as compared with other techniques. Importantly, other techniques might conclude that p.Asn1662Asp and p.Leu1657Pro are loss of function variants. Show Less
Brain Awae213, (2024)
Berecki et al.
Full Article

SCN2A
2024

Motor difficulties in 16p11.2 copy number variation
  • The researchers studied the differences in motor abilities in people with 16p11.2 deletions and duplications. Show More
  • The researchers studied Simons Searchlight participants, including 133 who were 16p11.2 deletion carriers, 122 who were 16p11.2 duplication carriers, and 388 family members who did not carry a genetic variant.
  • For some measures of motor function, the researchers found that 16p11.2 deletion carriers had more difficulties than duplication carriers. 16p11.2 deletion carriers were more likely to be diagnosed with developmental coordination disorder, were more likely to report difficulty with coordination, and had impaired performance on an executive function test. But, the researchers found no differences between 16p11.2 deletion and duplication carriers with respect to age of first walking or impairment in walking.
  • 16p11.2 deletion carriers were less likely than duplication carriers to have tremors and difficulty with gross movements of arms and fingerprint dexterity.
  • Overall, the researchers suggested that people with 16p11.2 deletions might have more difficulty with gross motor issues, whereas people with 16p11.2 duplications might have more issues with fine motor skills.
  • The researchers did not find a link between IQ and coordination or motor speed. Show Less
Autism Res 17, 906-916 (2024)
Jutla et al.
Full Article

16p11.2 deletion
16p11.2 duplication
2024

SETBP1 haploinsufficiency and related disorders clinical and neurobehavioral phenotype study
  • This study used Simons Searchlight genetic, behavioral, and clinical data to describe the neurodevelopmental profile and clinical characteristics of people with genetic variants that cause SETBP1 haploinsufficiency disorder (SETBP1-HD) and SETBP1 related disorders (SETBP1-RD). SETBP1 variants associated with Schinzel-Giedion syndrome in the specific amino acid region of SETBP1 862-873 were not included in this analysis. Show More
  • The researchers studied 34 Simons Searchlight participants, including 28 with SETBP1-HD and 6 with SETBP1-RD.
  • The publication included a review of medical history, Vineland Adaptive Behavior Scales 3 (VABS-3), Child Behavior Checklist (CBCL), Social Responsiveness Scale (SRS-2), Social Communication Questionnaire (SCQ), Children’s Sleep Habits Questionnaire (CSHQ), sleep surveys, brief development update, and Background History Form.
  • This is the first study in which researchers compared the medical features of people with SETBP1-HD and SETBP1-RD.
  • The researchers found that there were clinical features in common between participants with SETBP1-HD and SETBP1-RD, such as intellectual disability and developmental delay, speech and language impairment, hypotonia, attention issues, gastrointestinal issues, vision issues, sleep issues, autistic traits, and high pain tolerance.
  • The researchers thought that participants with SETBP1-RD had more heart and orthopedic issues, as well as difficulty in bowel control and higher risks for somatic issues, than participants with SETBP1-HD.
  • Participants with SETBP1-HD were better with interpersonal relationships, but had more difficulty with communication, motor skills, and functioning safely and independently within the community, according to the VABS-3.
  • As participants got older, new challenges arose. Participants with SETBP1-RD tended to develop more restrictive and repetitive behaviors. Participants with SETBP1-HD had an increase in overall behavioral and emotional problems. Show Less
Clin Genet Epub ahead of print, (2024)
Oyler et al.
Full Article

SETBP1
2024

Challenges in multi-task learning for fMRI-based diagnosis: Benefits for psychiatric conditions and CNVs would likely require thousands of patients
  • The researchers aimed to use computer machine learning to see if it is possible to detect and diagnose certain genetic conditions from brain imaging. They collected resting-state functional magnetic resonance imaging (rs-fMRI) data for 7 different copy number variants. Show More
  • Imaging data from Simons Searchlight participants with a 16p11.2 deletion, 16p11.2 duplication, 1q21.1 deletion, and 1q21.1 duplication were included in this research, as well as data from other research studies.
  • rs-fMRI images from 2,872 individuals were included from people with a 1q21.1 deletion, 1q21.1 duplication, 15q11.2 deletion, 16p11.2 deletion, 16p11.2 duplication, 22q11.2 deletion, and 22q11.2 duplication. These images were compared to images from people with no genetic diagnosis. The researchers also obtained images from people diagnosed with attention-deficit/hyperactivity disorder (ADHD), autism, schizophrenia, and bipolar disorder.
  • Once the researchers completed the machine learning process, they compared their results with images from the UK Biobank, which contains data from 30,185 people.
  • The researchers described the method used, called multi-task learning, and how they applied it to the various image datasets.
  • The researchers found that overall, multi-task learning might be a possible predictor of the sex and age of a person with no genetic diagnosis in the UK Biobank.
  • The researchers found that it was difficult to use machine learning to diagnose ADHD, autism, schizophrenia, bipolar disorder, or any of the copy number variants tested in this study. 22q11.2 deletion had the highest accuracy (about 90 percent), whereas schizophrenia, bipolar disorder, 16p11.2 deletion, 16p11.2 duplication, and 1q21.1 deletion reached over 70 percent accuracy, in one particular model tested. The findings were not always consistent in the other types of machine learning models.
  • The researchers indicated that the sample size of the image set used for machine learning was a very important factor for detecting a diagnosis correctly. Show Less
Imaging Neurosci 2, 1-20 (2024)
Harvey et al.
Full Article

16p11.2 deletion
16p11.2 duplication
1q21.1 deletion
1q21.1 duplication
2024

A comparison of symptom profiles in probands with 16p11.2 deletion and duplication syndromes: Repetitive behavior and psychosis proneness
  • Simons Searchlight data was used at Bucknell University in an honors thesis. Show More
  • The student looked at repetitive behavior and psychosis spectrum behavior in 116 people with a 16p11.2 deletion and 59 people with a 16p11.2 duplication. The study also included 32 people with no genetic diagnosis.
  • The student used information from 3 surveys: the Childhood Routines Inventory-Revised, the Childhood Oxford-Liverpool Inventory of Feelings and Experiences, and the Child Behavior Checklist.
  • The student found that, in general, people with a 16p11.2 duplication had more severe maladaptive repetitive behaviors and psychosis symptoms than people with a 16p11.2 deletion.
  • People with a 16p11.2 duplication more often had repetitive, compulsive-like behaviors and were prone to psychosis.
  • People with a 16p11.2 deletion had more issues with socializing, which was suggested to be a sign of autism in this group.
  • Finally, males with a 16p11.2 duplication were more affected on these surveys compared with females who had a 16p11.2 duplication. No differences were found between males and females with a 16p11.2 deletion.
  • Simons Searchlight is excited that these data are being used by young researchers, perhaps inspiring them to do more research on neurodevelopmental conditions. Show Less
Bucknell University, Honors Theses 686, (2024)
Rakauskas
Full Article

16p11.2 deletion
16p11.2 duplication
2024

Motor phenotypes associated with genetic neurodevelopmental disorders
  • The researchers studied the motor abilities of Simons Searchlight participants with genetic neurodevelopmental disorders. Show More
  • This study included 959 Simons Searchlight participants with 57 unique genetic conditions. The average ages for developmental milestones were described for people with autism and no intellectual disability (ID), people with autism and ID, and people with ID without autism. For genetic communities where the clinical spectrum was outside the Simons Searchlight community average, the researchers provide more details about that community.
  • The average age that people learned to sit unsupported was 11 months, and people with ID without autism learned to sit later on average (13 months). People with autism and no ID or autism and ID learned to sit around 10 months.
  • People with GRIN1-related syndrome learned to sit at an average age of 26 months.
  • The average age of walking in the Simons Searchlight study was 25 months. Children with ID without autism had a later average age of walking, about 29 months. Children with autism and no ID were walking around 23 months of age, and children with autism and ID were walking by the age of 26 months.
  • The average age of walking for people with CTNNB1-related syndrome was around 37 months. For people with HNRNPH2-related syndrome, it was around 42 months.
  • Some people with the following genetic conditions were not yet walking over the age of 1.5 years: ARID1B, CHAMP1, CTNNB1, GRIN1, GRIN2B, HNRNPH2, PPP2R1A, PPP2R5D, SCN2A, STXBP1, and TBR1.
  • The majority of people in Simons Searchlight reported having low muscle tone – 577 out of 696 people or 83 percent.
  • About 10 percent of people (73 out of 696 people) reported being diagnosed with cerebral palsy (CP). The following genetic conditions had at least one person with CP: ADNP, ASXL3, AUTS2, CHAMP1, CSNK2A1, CTNNB1, DDX3X, DYRK1A, FOXP1, GRIN2B, HIVEP2, HNRNPH2, IRF2BPL, PPP2R1A, PPP2R5D, PTCHD1, SCN2A, SETBP1, SETD5, STXBP1, and SYNGAP1.
  • The researchers explained that CP is a descriptive term and does not explain why a person has a CP diagnosis. People should still have genetic testing when they have CP, and one does not contradict the other. Show Less
Ann Clin Transl Neurol Epub ahead of print, (2024)
Almansa et al.
Full Article

All Genes
2024