A Recessively Inherited Risk Locus on Chromosome 13q22-31 Conferring Susceptibility to Schizophrenia

Exploring Schizophrenia Classification Through Multimodal MRI and Deep Graph Neural Networks: Unveiling Brain Region-Specific Weight Discrepancies and Their Association With Cell-Type Specific Transcriptomic Features

BACKGROUND AND HYPOTHESIS

Schizophrenia (SZ) is a prevalent mental disorder that imposes significant health burdens. Diagnostic accuracy remains challenging due to clinical subjectivity. To address this issue, we explore magnetic resonance imaging (MRI) as a tool to enhance SZ diagnosis and provide objective references and biomarkers. Using deep learning with graph convolution, we represent MRI data as graphs, aligning with brain structure, and improving feature extraction, and classification. Integration of multiple modalities is expected to enhance classification.

STUDY DESIGN

Our study enrolled 683 SZ patients and 606 healthy controls from 7 hospitals, collecting structural MRI and functional MRI data. Both data types were represented as graphs, processed by 2 graph attention networks, and fused for classification. Grad-CAM with graph convolution ensured interpretability, and partial least squares analyzed gene expression in brain regions.

STUDY RESULTS

Our method excelled in the classification task, achieving 83.32% accuracy, 83.41% sensitivity, and 83.20% specificity in 10-fold cross-validation, surpassing traditional methods. And our multimodal approach outperformed unimodal methods. Grad-CAM identified potential brain biomarkers consistent with gene analysis and prior research.

CONCLUSIONS

Our study demonstrates the effectiveness of deep learning with graph attention networks, surpassing previous SZ diagnostic methods. Multimodal MRI's superiority over unimodal MRI confirms our initial hypothesis. Identifying potential brain biomarkers alongside gene biomarkers holds promise for advancing objective SZ diagnosis and research in SZ.

In memory of Professor Iain Wilkinson: cognitive and neuroimaging endophenotypes in a consanguineous schizophrenia multiplex family

BACKGROUND

Schizophrenia endophenotypes may help elucidate functional effects of genetic risk variants in multiply affected consanguineous families that segregate recessive risk alleles of large effect size. We studied the association between a schizophrenia risk locus involving a 6.1Mb homozygous region on chromosome 13q22-31 in a consanguineous multiplex family and cognitive functioning, haemodynamic response and white matter integrity using neuroimaging.

METHODS

We performed CANTAB neuropsychological testing on four affected family members (all homozygous for the risk locus), ten unaffected family members (seven homozygous and three heterozygous) and ten healthy volunteers, and tested neuronal responses on fMRI during an n-back working memory task, and white matter integrity on diffusion tensor imaging (DTI) on four affected and six unaffected family members (four homozygous and two heterozygous) and three healthy volunteers. For cognitive comparisons we used a linear mixed model (Kruskal-Wallis) test, followed by posthoc Dunn's pairwise tests with a Bonferroni adjustment. For fMRI analysis, we counted voxels exceeding the p < 0.05 corrected threshold. DTI analysis was observational.

RESULTS

Family members with schizophrenia and unaffected family members homozygous for the risk haplotype showed attention (p < 0.01) and working memory deficits (p < 0.01) compared with healthy controls; a neural activation laterality bias towards the right prefrontal cortex (voxels reaching p < 0.05, corrected) and observed lower fractional anisotropy in the anterior cingulate cortex and left dorsolateral prefrontal cortex.

CONCLUSIONS

In this family, homozygosity at the 13q risk locus was associated with impaired cognition, white matter integrity, and altered laterality of neural activation.

Late-Onset Autosomal Dominant Macular Degeneration Caused by Deletion of the CRX Gene

PURPOSE

To characterize the phenotype observed in a case series with macular disease and determine the cause.

DESIGN

Multicenter case series.

PARTICIPANTS

Six families (7 patients) with sporadic or multiplex macular disease with onset at 20 to 78 years, and 1 patient with age-related macular degeneration.

METHODS

Patients underwent ophthalmic examination; exome, genome, or targeted sequencing; and/or polymerase chain reaction (PCR) amplification of the breakpoint, followed by cloning and Sanger sequencing or direct Sanger sequencing.

MAIN OUTCOME MEASURES

Clinical phenotypes, genomic findings, and a hypothesis explaining the mechanism underlying disease in these patients.

RESULTS

All 8 cases carried the same deletion encompassing the genes TPRX1, CRX, and SULT2A1, which was absent from 382 control individuals screened by breakpoint PCR and 13 096 Clinical Genetics patients with a range of other inherited conditions screened by array comparative genomic hybridization. Microsatellite genotypes showed that these 7 families are not closely related, but genotypes immediately adjacent to the deletion breakpoints suggest they may share a distant common ancestor.

CONCLUSIONS

Previous studies had found that carriers for a single defective CRX allele that was predicted to produce no functional CRX protein had a normal ocular phenotype. Here, we show that CRX whole-gene deletion in fact does cause a dominant late-onset macular disease.

RGS3 and IL1RAPL1 missense variants implicate defective neurotransmission in early-onset inherited schizophrenias

BACKGROUND

Schizophrenia is characterized by hallucinations, delusions and disorganized behaviour. Recessive or X-linked transmissions are rarely described for common psychiatric disorders. We examined the genetics of psychosis to identify rare large-effect variants in patients with extreme schizophrenia.

METHODS

We recruited 2 consanguineous families, each with patients affected by early-onset, severe, treatment-resistant schizophrenia. We performed exome sequencing for all participants. We checked variant rarity in public databases and with ethnically matched controls. We performed in silico analyses to assess the effects of the variants on proteins.

RESULTS

Structured clinical evaluations supported diagnoses of schizophrenia in all patients and phenotypic absence in the unaffected individuals. Data analyses identified multiple variants. Only 1 variant per family was predicted as pathogenic by prediction tools. A homozygous c.649C > T:p.(Arg217Cys) variant in RGS3 and a hemizygous c.700A > G:p.(Thr234Ala) variant in IL1RAPL1 affected evolutionary conserved amino acid residues and were the most likely causes of phenotype in the patients of each family. Variants were ultra-rare in publicly available databases and absent from the DNA of 400 ethnically matched controls. RGS3 is implicated in modulating sensory behaviour in Caenorhabditis elegans. Variants of IL1RAPL1 are known to cause nonsyndromic X-linked intellectual disability with or without human behavioural dysfunction.

LIMITATIONS

Each variant is unique to a particular family's patients, and findings may not be replicated.

CONCLUSION

Our work suggests that some rare variants may be involved in causing inherited psychosis or schizophrenia. Variant-specific functional studies will elucidate the pathophysiology relevant to schizophrenias and motivate translation to personalized therapeutics.