Utafiti huu unatumia mfumo wa Evaluation of Autism Gene Link Evidence (EAGLE) ili kutenganisha kwa utaratibu zaidi jeni zinazoonyesha uhusiano wa kijeni wenye nguvu kweli na autism spectrum disorder (ASD) kutoka kwa jeni zinazohusishwa na neurodevelopmental disorders kwa ujumla. Watafiti walitathmini candidate genes 222; katika matokeo makuu waliripoti kwamba uhusiano wa jeni 78 na ASD ulikuwa katika kiwango cha ushahidi cha “definitive”, jeni 43 “moderate” na jeni 99 “limited”. Jeni 10 zenye EAGLE score ya juu zaidi zimeorodheshwa kama NRXN1, SCN2A, MECP2, CHD8, RNU4-2, DDX3X, SHANK3, PTEN, FOXP1 na MBD5.

Tofauti kuu ya EAGLE ni kwamba haiichukulii moja kwa moja jeni kuwa “autism gene” kwa sababu tu imehusishwa kwa ujumla na intellectual disability au neurodevelopmental disorder nyingine. Mfumo hu-score kwa pamoja kiwango cha uthibitisho wa ASD diagnosis kwa watu ambao genetic variants zimeripotiwa, variant class, inheritance pattern, population frequency na experimental evidence. Watafiti wanahoji kwamba approach hii inaruhusu gene–ASD relationship kutathminiwa kwenye kiwango endelevu cha nguvu ya ushahidi.

Mbali na gene curation, utafiti unachunguza rare variants katika cohorts za MSSNG, Simons Simplex Collection (SSC) na SPARK; variants zinazojirudia katika genetic ancestry groups tofauti; biological functions za genes; developmental expression patterns katika human brain; neuronal expression profiles katika single-cell level; na available mouse models pamoja na protein research tools. Imeripotiwa kwamba genes zinazohusishwa kwa nguvu na ASD na EAGLE zinaonyesha patterns zinazojitokeza hasa katika biological clusters zinazohusiana na prenatal brain development, regulation of gene expression, neurogenesis, synaptic processes, learning na behavior.

Kwa mtazamo wa Uturuki, utafiti unaonyesha distinction muhimu ya kimawazo katika kutafsiri genetic test reports na “autism gene panel” lists za research: kuwa jeni ina uhusiano mkubwa na broad neurodevelopmental disorder group hakumaanishi kwamba jeni hiyo hiyo imehusishwa na ASD kwa nguvu na specificity sawa. Hata hivyo, EAGLE classification peke yake haionyeshi kwamba individual variant ni pathogenic, kwamba mtu atapata autism, au kwamba treatment fulani inafaa. Kwa clinical genetics practice nchini Uturuki, local laboratory validation, current clinical guidelines, variant-level interpretation na specialist assessment zinahitajika pia.

Tatizo kuu ambalo utafiti unajaribu kutatua ni lipi?

Katika autism genetics, gene lists nyingi hutumiwa; lakini research groups na clinical resources tofauti haziclassify jeni zilezile katika kiwango sawa cha ushahidi. Watafiti wanasema hali hii inaweza kutokana na ukubwa wa genome cohorts, sequencing technologies zinazotumiwa, na hasa kuchanganywa kwa ASD na category pana zaidi ya neurodevelopmental disorder (NDD).

Neurodevelopmental disorders ni category pana inayojumuisha, pamoja na ASD, intellectual disability, language disorders, learning disorders, epilepsy na attention-deficit/hyperactivity disorder. Disorders hizi mara nyingi zinaweza kuonekana pamoja; lakini assumption kuu ya utafiti ni kwamba kutathmini genetic evidence kwa namna iliyo specific iwezekanavyo kwa ASD phenotype kunaweza kutoa additional information ya clinical na biological.

EAGLE ni nini?

EAGLE ni kifupi cha “Evaluation of Autism Gene Link Evidence”. Mfumo hutumia ClinGen gene–disease validity approach lakini huongeza pia kiwango cha uthibitisho wa ASD phenotype katika scoring ya genetic evidence.

Katika high-scoring case evidence, umuhimu unawekwa kwenye ASD diagnosis kuungwa mkono na accepted diagnostic frameworks kama ADOS, ADI-R au DSM. Kwa hiyo variant katika case ambayo imeripoti tu “neurodevelopmental delay” au “intellectual disability” haipati automatically uzito uleule kama ASD-specific evidence.

Genes zina-scorewa vipi?

Katika EAGLE curation, genomic evidence na experimental evidence hutathminiwa kama components tofauti. Katika case-level genomic scoring, mambo yafuatayo huzingatiwa:

• proposed mutation mechanism,
• genotyping method,
• functional variant class,
• inheritance pattern,
• allele frequency katika population,
• kiwango cha uthibitisho wa ASD phenotype.

Experimental evidence pia hu-scorewa kwa kutumia EAGLE experimental evidence matrix; case scores kutoka independent cases na experimental scores hujumlishwa ili kuunda total EAGLE score ya gene.

Source inataja possible classification levels sita: definitive, strong, moderate, limited, disputed na refuted. Sifa nyingine ya EAGLE ni kwamba hata baada ya kufikia “definitive”, score inaweza kuendelea kuongezeka kadri new evidence inavyoongezeka. Hivyo depth of evidence inaweza kulinganishwa hata kati ya strong genes zilizo katika category moja.

Nini kilipatikana katika tathmini ya genes 222?

Main text ya utafiti inasema kwamba candidate genes 222 zilifanyiwa manual curation kwa EAGLE. Katika main results:

• genes 78: definitive evidence,
• genes 43: moderate evidence,
• genes 99: limited evidence

ziliripotiwa. Zaidi ya hayo MSL3 ilitambuliwa tofauti kama “strong”, RELN kama “disputed” na CNTNAP2 kama “refuted”.

Ni muhimu kutaja kwamba categories hizi hazijareconciled kikamilifu kwa namba ndani ya source. Abstract na discussion zinaripoti limited genes 99, huku panel husika ya Figure 1 ikiwa na kichwa “EAGLE Limited (N=100)”. Pia, ikiwa 78 definitive, 43 moderate na 99 limited zinaongezewa categories za strong, disputed na refuted kama independent groups, total inayopatikana haipatani mathematically na reported total ya 222. Kwa hiyo hakuna reclassification isiyopo kwenye source iliyofanywa hapa.

Genes zenye EAGLE score ya juu zaidi ni zipi?

Source inaorodhesha top 10 genes kwa mpangilio huu:

1. NRXN1
2. SCN2A
3. MECP2
4. CHD8
5. RNU4-2
6. DDX3X
7. SHANK3
8. PTEN
9. FOXP1
10. MBD5

Main text pia inatoa exact numeric scores kwa baadhi ya genes. NRXN1 ina 143,75, SCN2A 109,3, CHD8 97,65, SHANK3 74,85 na PTEN 63,15 EAGLE points. Mifano ya PTCHD1-AS 33,6; ASTN2 15,75 na CACNA1D 12,7 pia inajadiliwa kuonyesha kwamba method inaweza kutathmini variant mechanisms tofauti.

“Definitive ASD gene” inamaanisha nini?

Katika EAGLE context, “definitive” ni gene-level classification inayoonyesha kwamba scientific relationship kati ya gene fulani na ASD inaungwa mkono na strong case na experimental evidence. Haimaanishi kwamba kila variant katika gene hiyo ni disease-causing au kwamba kila mtu anayebeba variant atapata ASD.

Kwa mfano, utafiti unasisitiza kwamba variant classes tofauti ndani ya gene moja zinaweza kuonyesha relationship kupitia mechanisms tofauti. Gain-of-function mechanisms zinajadiliwa kwa BRAF na CACNA1D; hasa N-terminal deletions kwa NRXN1; na LoF, missense na structural variants kwa SHANK3.

Ni genome cohorts zipi kubwa zilizochambuliwa?

Ili kutathmini rare variant frequency, affected individual mmoja kwa kila family alichukuliwa na ASD cohorts tatu kubwa zikachunguzwa:

Jumla ya groups hizi tatu ni unrelated ASD cases 10.801. Kwa de novo variant analysis, kwa sababu genetic data ya mother na father ilihitajika, subgroup tofauti ya watu 9.123 ilitumika: MSSNG 3.368, SSC 2.393 na SPARK 3.362.

Kwa sababu relationship ya CNTNAP2 na ASD iliwekwa katika refuted class na EAGLE, rare variant analysis ilitathmini 221 kati ya genes 222.

Ni variant types zipi zilizochunguzwa?

Utafiti ulilenga rare variants zenye gnomAD allele frequency chini ya %1. Classes zilizochunguzwa zilifafanuliwa kama:

• loss-of-function (LoF) single-nucleotide variants,
• missense variants,
• insertions na deletions chini ya base pairs 50,
• copy-number variants (CNV) zinazoathiri exons

.

Je, genes zilezile zinaonekana katika genetic ancestry groups tofauti?

Watafiti waliona domination ya genetic discoveries na samples za European ancestry kama limitation muhimu na wakaangalia kama rare variants zinajirudia katika ancestry groups tofauti.

Principal component analysis na Random Forest classifier zilitumika kwa ancestry estimation. Reference groups zilijumuisha African, South Asian, East Asian, European, Middle Eastern na Indigenous American ancestry. Sample iliwekwa kwenye group husika ikiwa Random Forest prediction probability ilikuwa zaidi ya %50.

Kulingana na rates zilizoripotiwa kwenye source:

• katika 37 kati ya 78 definitive genes (%47,4),
• katika 12 kati ya 43 moderate genes (%27,9),
• katika 17 kati ya limited genes 99 zilizoripotiwa kwenye source (%17)

variant ilionekana katika zaidi ya genetic ancestry group moja.

NRXN1 deletions, SCN2A LoF variants na CHD8 missense variants zimetolewa kama mifano ya variants zinazojirudia across ancestry groups. Deletion na duplication katika MBD5 na DMD; duplication na LoF katika CHD2 na EHMT1; na LoF na missense variants katika SHANK3 ziliripotiwa katika ancestry groups zaidi ya moja.

Analysis hii haithibitishi kwamba risk ni sawa katika ancestry groups zote. Watafiti wanasisitiza kwamba whole-genome sequencing data ya ASD katika non-European populations bado ni ndogo zaidi.

Kwa nini kuna tofauti kati ya EAGLE, SFARI na ClinGen?

EAGLE hu-score evidence inayohusiana na verified ASD phenotype pekee, huku ClinGen ID/ASD approach inaweza kutathmini intellectual disability na/au ASD phenotypes pamoja. SFARI-Gene hutumia curation framework tofauti.

Katika utafiti, main lists mbili ziliundwa kwa comparative calculations na EAGLE:

• EAGLE-definitive: n=78,
• ID-predominant: genes n=69 ambazo ni limited katika EAGLE lakini definitive/high-confidence katika ClinGen au SFARI.

Watafiti wanatest hypothesis kwamba list ya pili inaweza kuendeshwa zaidi na intellectual disability au broad NDD phenotype kuliko ASD. Jina “ID-predominant” ni analytical classification ya study hii; halimaanishi kwamba genes hazina relationship yoyote na ASD.

Nini kilipatikana katika SFARI comparison?

Inaelezwa kwamba kufikia October 2025 SFARI ilikuwa na high-confidence genes 240 na 171 kati yao pia zilikuwa curated na EAGLE. Kati ya genes 171:

• 68 (%39,8) EAGLE-definitive,
• 39 (%22,8) EAGLE-moderate,
• 63 (%36,8) EAGLE-limited,
• 1 (%0,6) disputed

ziliripotiwa. Kwa kuwa sub-counts hizi zinajumlisha 171, comparison hii ni internally consistent arithmetically.

Je, kuna number issue ndani ya source katika ClinGen comparison?

Ndiyo. Text inasema kwamba 94 genes zilizochukuliwa definitive na ClinGen ID/ASD-GCEP pia zilikuwa curated na EAGLE. Lakini mara moja baadaye inasema 49 genes ni definitive, 23 moderate na 25 limited. Jumla ya namba hizi tatu ni 97.

Zaidi ya hayo, percentages %50,5, %23,7 na %25,8 zinajumlisha %100 na zinaendana na distribution ya 49/23/25. Source haielezi tofauti kati ya 94 na 97. Kwa hiyo Verianla explanation haijaunganisha values hizi ili kutengeneza namba mpya.

Je, biological functions za genes ni sawa?

Hapana. Watafiti walitumia g.Profiler na Cytoscape Enrichment Map kulinganisha biological processes ambako EAGLE-definitive na ID-predominant genes zime-enriched.

Jumla ya gene-set clusters 24 zilitambuliwa, na 16 kati yake ziliripotiwa ku-enriched katika EAGLE-definitive genes pekee. Hakuna functional cluster specific kwa ID-predominant genes iliyotambuliwa.

Main shared enriched areas kwa lists zote mbili ni:

• neurogenesis na neuron differentiation,
• central nervous system development,
• synapse specialization na regulation of neuronal processes,
• chromatin binding.

Clusters zilizotofautiana hasa katika EAGLE-definitive genes zilijumuisha regulation of DNA-templated transcription, epigenetic regulation of gene expression, regulation of methyltransferase activity, learning-memory-cognition-behavior na regulation of phosphorylation.

Figure 2 inaonyesha nini?

Figure 2 inaonyesha enriched biological gene sets kama network. Kila node inawakilisha gene set, huku functions zinazokaribiana zikiwakilishwa kama functional clusters kubwa zaidi. Kuonekana kwa network inayohusiana na EAGLE-definitive genes kuwa pana na dense zaidi katika regions nyingi kunatoa visual summary ya differences katika quantitative enrichment analysis.

Hata hivyo, network hii peke yake haithibitishi kwamba biological pathway fulani inasababisha ASD. Analysis inaonyesha functional annotations ambako predefined gene lists zime-overrepresented statistically.

Gene expression katika human brain ilichunguzwaje?

RNA sequencing data kutoka BrainSpan database zilitumika kwa human brain samples 42, awali zikiwa na cortical na subcortical structures 26. Samples ziligawanywa katika developmental periods tano:

• fetal period,
• infancy,
• childhood,
• adolescence,
• adulthood.

Kwa sharti la kuwepo kwa sufficiently independent samples, analysis ilipunguzwa hadi brain structures 18. Kwa sababu BrainSpan expression data haikupatikana kwa PTCHD1-AS, genes 77 zilitumika badala ya 78 katika EAGLE-definitive expression analysis.

Ni brain regions zipi zilijitokeza katika prenatal period?

Imeripotiwa kwamba EAGLE-definitive genes zilionyesha higher relative expression patterns kuliko ID-predominant genes hasa katika prenatal development. Source inasisitiza:

• primary motor cortex (M1C),
• primary somatosensory cortex (S1C),
• inferior parietal cortex (IPC)

.

Ni structure ipi inajitokeza baada ya kuzaliwa?

Katika postnatal period, relative expression ya EAGLE-definitive genes katika cerebellum iliripotiwa kubaki juu katika all four postnatal developmental periods, huku greatest difference ikionekana katika infancy.

Figure 3 inalinganisha relative expression patterns za gene lists mbili kwenye lateral na midsagittal brain views kutoka fetal period hadi adulthood. Maps hizi hazimaanishi kwamba genes zina-expressiwa katika specific brain region pekee; zinaonyesha relative differences katika standardized mean expression patterns za gene lists.

Ni data gani ilitumika katika single-cell level?

Kwa cellular analysis, developing human neocortex atlas ya BRAIN Initiative Cell Atlas Network ilitumika. Source dataset ilikuwa na nuclei 232.328 kutoka prefrontal cortex na primary visual cortex na cell types 33 zilizofafanuliwa transcriptomically.

Nuclei hizi zilitoka kwenye human neocortex samples 38 na zilijumuisha first trimester, second trimester, third trimester, infancy na adolescence.

Ni cell types zipi zilionyesha tofauti?

Katika second trimester, distinct expression patterns katika EAGLE-definitive genes ziliripotiwa hasa katika intermediate progenitor cell (IPC-EN) group ya excitatory neurons na newborn glutamatergic excitatory neurons.

Kwa kiwango kidogo zaidi, increased relative expression specific kwa EAGLE-definitive list ilionekana pia katika immature intratelencephalic na non-intratelencephalic excitatory neurons. Katika inhibitory neuron groups, immature cells zinazotokana na dorsal lateral ganglionic eminence na caudal ganglionic eminence ziliripotiwa kuwa na higher expression katika EAGLE-definitive genes.

Katika third trimester, oligodendrocyte precursor cells na microglia zilikuwa miongoni mwa cell groups zilizoonyesha variable expression differences kubwa zaidi kati ya gene lists mbili.

Mouse models zilitathminiwaje?

Watafiti walitumia 78 EAGLE-definitive genes kama starting point na wakafanya curation ya genetic mouse models zilizopo kwenye literature. Behaviors ziligawanywa katika groups tano kuu:

• social interaction,
• social communication / ultrasonic vocalization,
• repetitive behavior,
• learning na memory,
• motor functions.

Kati ya top 10 EAGLE genes, isipokuwa Ddx3x na Rnu4-2, genes nane ziliripoti abnormalities zinazohusiana na social interaction katika available mouse models. Hata hivyo, models nyingi hazikuonyesha phenotype sawa katika social tests zote.

Kwa mfano, baadhi ya models zenye Nrxn1α, Scn2a, Chd8 au Shank3 mutations zilionyesha normal behavior katika simpler sociability tests lakini differences katika more challenging tasks kama social novelty preference. Models zinazolenga different isoforms za gene ileile pia ziliripotiwa kuzalisha phenotypes tofauti.

Mouse results hizi si direct model ya ASD diagnosis kwa humans. Lengo la utafiti ni ku-map available biological tools kwa mechanistic na preclinical study ya specific genes.

X chromosome na sex analysis vilionyesha nini?

Katika EAGLE, 25 X-linked genes zilitathminiwa. Case-level evidence component ilikuwa na males 381 na females 299; genes nane zili-classifywa definitive, nne moderate na 13 limited.

Baada ya kuondoa MECP2 na DDX3X, male:female ratio katika case counts kwa definitive na moderate X-linked genes ilitolewa kama 6,89: males 262 na females 38; two-sided Wilcoxon rank-sum test p=7,339×10⁻⁴.

Kwa definitive autosomal genes, source inaripoti ratio ya 2,96: males 2.247 na females 758; p=2,367×10⁻¹¹. Katika ID-predominant autosomal genes, ratio ya 4,05 ilitolewa: males 300 na females 74; p=3,253×10⁻¹².

Namba hizi si epidemiological ratios zinazopima upya ASD prevalence katika population. Zinalinganisha distribution ya individuals walioingia kwenye EAGLE case-level evidence evaluation.

Ni resources gani nyingine zilizokusanywa kwa preclinical research?

Mbali na mouse models, watafiti walifanya curation ya protein resources zinazoweza kurahisisha study ya EAGLE-definitive genes katika cellular na translational research.

Experimental protein structures, PDB records, resolved protein regions, recombinant expression systems, availability ya purified proteins na knock-out-validated renewable antibodies zilikusanywa kutoka sources kama Structural Genomics Consortium, Protein Data Bank, UniProt na YCharOS.

Links pia zilitolewa kwa induced pluripotent stem cell na organoid resources zilizopo katika Simons Searchlight. Hizi si new organoid au mouse experiments zilizotengenezwa katika laboratory ya study; ni scientific curation ya existing preclinical resources.

Matokeo yanayoungwa mkono na utafiti

• EAGLE inatoa protocol-based curation approach inayotathmini gene–ASD relationship si kwa broad NDD category pekee bali kwa evidence inayotegemea verified ASD phenotype.
• Main text inaripoti definitive EAGLE evidence ya ASD kwa genes 78.
• NRXN1, SCN2A, MECP2, CHD8, RNU4-2, DDX3X, SHANK3, PTEN, FOXP1 na MBD5 zimetolewa kama top 10 highest-scoring genes.
• Recurring rare variants across ancestry groups ziliripotiwa mara nyingi zaidi katika definitive genes kuliko katika moderate na limited groups.
• EAGLE-definitive na ID-predominant lists zinaonyesha differences katika biological pathways, brain development na cell-type expression patterns.
• Prenatal cortical na postnatal cerebellar expression patterns zinajitokeza katika EAGLE-definitive genes.
• Utafiti unakusanya available mouse models na protein-based research tools kwa definitive genes kwa planning ya preclinical research.

Matokeo ambayo utafiti hauungi mkono au haujathibitisha

• Kubeba variant yoyote katika mojawapo ya genes hizi peke yake hakumaanishi ASD diagnosis.
• Definitive classification ya gene haimaanishi kwamba variants zote katika gene hiyo ni pathogenic.
• Utafiti haujatest katika prospective patient group clinical diagnostic sensitivity au specificity ya kutumia genes 78.
• EAGLE haichukui nafasi ya clinical variant classification system; study inafanya curation ya evidence ya gene–phenotype relationship.
• Brain na single-cell expression differences peke yake hazionyeshi kwamba specific cell types causally husababisha ASD.
• Social au repetitive behavior changes katika mouse models si direct equivalents za autism kwa humans.
• Utafiti haujatest new ASD treatment wala kuonyesha treatment efficacy.
• Kuonekana kwa variant katika genetic ancestry groups tofauti hakuthibitishi kwamba variant ina penetrance au effect sawa katika populations zote.

Mbinu na Matokeo ya Utafiti

Components kuu za utafiti

Main numbers zilizoripotiwa kwenye source katika EAGLE classification

Kwa sababu category totals za source hazijareconciled kikamilifu internally, table hii inaonyesha scientific reporting kama ilivyo; numbers hazijareclassifywa na Verianla.

Rare variant analysis

Total ya de novo subgroup haipaswi kusomwa kama direct subset relationship ya cohort counts katika column ya general “one affected individual per family”; source inafafanua available parental genetic data kwa de novo analysis tofauti.

Genetic ancestry groups

Main trend iliyoonekana kwenye source ni kwamba recurring rare variants katika genetic ancestry groups tofauti zimeripotiwa mara nyingi zaidi katika group yenye stronger EAGLE evidence ya gene–ASD relationship.

Gene-set enrichment analysis

BrainSpan analysis

BICAN single-nucleus transcriptomic analysis

Numeric na reporting issues muhimu ndani ya source

Mismatch kati ya genes 222 na category totals: Source inasema genes 222 zilicuratewa, na genes 78 definitive, 43 moderate na 99 limited zilipatikana. MSL3 strong, RELN disputed na CNTNAP2 refuted pia zimetolewa tofauti. Ikiwa categories zote zinachukuliwa independent, total hailingani na 222.

Limited gene count: Text inaripoti limited genes 99, lakini heading ya relevant panel katika Figure 1 inasema N=100.

Definitive percentage: Results section inatoa %34,6 kwa genes 78 definitive; percentage hii hailingani kikamilifu na total n=222 katika paragraph hiyo hiyo. Source haielezi sababu.

ClinGen comparison: Text inasema kuna common definitive ClinGen genes 94, lakini EAGLE subclasses ni 49 definitive + 23 moderate + 25 limited, sawa na genes 97.

Definitive threshold display: Text inasema definitive classification threshold ni score=12, huku Figure 1 panel heading ikisema “Score >12”. Difference hii ya exact boundary condition haijaelezwa katika source.

Differences hizi hazimaanishi kwamba main EAGLE approach ni invalid; lakini zinaonyesha kwamba published category counts zinapaswa kukaguliwa dhidi ya updated curation records za source authors kabla ya kubadilishwa moja kwa moja kuwa clinical list katika secondary use.

Dokezo la Chanzo na Mbinu

Jina kamili la kazi asilia: Genes/variants for diagnostic testing and pre-clinical research in autism spectrum disorder

Waandishi: Nelson Bautista Salazar; Olivia Rennie; Worrawat Engchuan; Julian Moran; Vinicius Furlan; Xiaopu Zhou; Natalia Rivera-Alfaro; Jennifer L. Howe; Ny Hoang; Kristian Torres-Bonilla; Kristof Bosovicar; Katlin Brauer Massirer; Carl Laflamme; Aled Edwards; Karun K. Singh; Sangyoon Y. Ko; Marla Mendes de Aquino; Jacob A.S. Vorstman; Stephen W. Scherer.

Mpangilio wa waandishi: Mpangilio hapo juu ni original author order iliyotolewa katika source.

Equal contribution: Source haijaonyesha equal first authorship wala equal contribution statement.

Corresponding authors: Jacob A.S. Vorstman — jacob.vorstman@sickkids.ca; Stephen W. Scherer — stephen.scherer@sickkids.ca.

Institutional affiliations: Genetics and Genome Biology Program, The Hospital for Sick Children; Department of Molecular Genetics, University of Toronto; Temerty Faculty of Medicine, University of Toronto; The Centre for Applied Genomics, The Hospital for Sick Children; Department of Genetic Counselling, The Hospital for Sick Children; Autism Research Unit, The Hospital for Sick Children; Structural Genomics Consortium, Campinas, Brazil; Center for Medicinal Chemistry (CQMED) na Center for Molecular Biology and Genetic Engineering (CBMEG), Universidade Estadual de Campinas; Structural Genomics Consortium, University Health Network/University of Toronto; Structural Genomics Consortium, Montreal Neurological Institute-Hospital, McGill University; School of Pharmaceutical Sciences, Faculty of Medicine, University of Ottawa; Krembil Research Institute, University Health Network na Department of Laboratory Medicine and Pathobiology, University of Toronto; Program in Neurosciences & Mental Health, The Hospital for Sick Children; Department of Brain and Cognitive Sciences, KAIST; Department of Psychiatry, The Hospital for Sick Children; Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto; McLaughlin Centre, Toronto.

Aina ya source: Preprint; manual scientific curation, secondary analysis ya existing genome cohorts, bioinformatics analysis na preclinical resource compilation.

Peer-review status: Kazi hii ni preprint na haijapitia peer review. Source inaeleza wazi kwamba study haipaswi kutumika kuongoza clinical practice.

Publication platform: medRxiv.

Peer-reviewed journal: Hakuna peer-reviewed journal publication iliyotajwa katika version hii.

Original publisher: Kwa kuwa version hii si journal article, haina peer-reviewed journal publisher; kazi imesambazwa kwenye medRxiv kama preprint.

Version: medRxiv v1.

Publication date: 22 Juni 2026.

DOI:10.64898/2026.06.19.26356063

Official source:medRxiv official preprint record

License: Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0).

Ethics approval: The Hospital for Sick Children Research Ethics Board, REB# 1000080561.

Funding: Support imeripotiwa kutoka University of Toronto McLaughlin Centre, Canadian Institutes of Health Research, Genome Canada/Ontario Genomics Institute, Canada Foundation for Innovation, Autism Speaks, Ontario Brain Institute na SickKids Foundation. Jacob A.S. Vorstman ni SickKids Psychiatry Associates Chair in Developmental Psychopathology; Stephen W. Scherer ni Northbridge Chair in Paediatric Research.

Data availability: Imeelezwa kwamba data generated na analyzed katika study zinapatikana katika article na supplementary materials. Individual EAGLE gene curation files zinaweza kuombwa kutoka corresponding authors na EAGLE curations zinasasishwa mara kwa mara.

Code availability: Source inatoa EAGLE_Manuscript GitHub repository kwa code iliyotumika katika raw-data processing na analysis.

Author contributions: Jacob A.S. Vorstman na Stephen W. Scherer walihusika katika conceptualization na development ya EAGLE framework; Nelson Bautista Salazar na Olivia Rennie katika manual curation ya genes 222; Worrawat Engchuan katika BrainSpan na BICAN gene-expression analyses; Marla Mendes de Aquino katika rare-variant analysis. Contributions za waandishi wengine katika protein annotation, antibody research, data interpretation, writing, review na editing zimeelezwa kwa undani katika source.

Conflict of interest: Stephen W. Scherer alifichua kwamba wakati wa study alihudumu katika Scientific Advisory Committees za Population Bio, Deep Genomics na Diploid Genomics; na kwamba baadhi ya intellectual property rights zinazotokana na research katika The Hospital for Sick Children zilikuwa licensed kwa Athena Diagnostics na Population Bio. Jacob A.S. Vorstman aliripoti consultancy kwa NoBias Therapeutics Inc. kwa design ya clinical study katika watoto wenye 22q11.2 deletion. Source inasema relationships hizi hazikuathiri interpretation wala presentation ya data. Waandishi wengine hawakuripoti conflict of interest.

Maelezo haya ya Verianla yanategemea tu version iliyowasilishwa ya Bautista Salazar na colleagues kwa scientific findings za study. External verification ilitumika tu kuangalia preprint identity, DOI na current publication status; hakuna new ASD gene, clinical diagnostic rate au biological result iliyoongezwa kutoka nje.

Main study iliyopakiwa inarejelea supplementary materials kama Supplementary Figure 1–6 na Supplementary Table S1–S6; supplementary files zote hazipo ndani ya main document ya pages 39 iliyowasilishwa. Kwa hiyo Verianla text imetumia numeric results zinazosomeka moja kwa moja katika main study na haijakisia gene au data kutoka unseen supplementary tables.

Source ina baadhi ya internal inconsistencies kuhusu category distribution ya total genes 222, limited gene count, definitive percentage, ClinGen common gene count na definitive score threshold display. Differences hizi hazijasahihishwa kimya kimya. Hasa ikiwa gene list itatengenezwa kwa clinical au diagnostic purpose, updated EAGLE records na independent clinical variant assessment zinapaswa kukaguliwa tofauti.