OBJECTIVES: Studies have reported promising results regarding artificial intelligence (AI) as a tool for improved mammographic screening interpretive performance. We analyzed AI malignancy risk scores from two versions of the same commercial AI model.

MATERIALS AND METHODS: This retrospective cohort study used data from 117,709 screening examinations performed in BreastScreen Norway 2009-2018. The mammograms were processed by two versions of the commercially available AI model, Transpara (version 1.7 and 2.1). The distributions of exam-level risk scores (AI score 1-10) and risk categories were evaluated for both AI versions on all examinations, including 737 screen-detected and 200 interval cancers. Scores between 1-7 were categorized as low risk, 8-9 as intermediate risk, and 10 as high risk of malignancy.

RESULTS: Area under the receiver operating curve was 0.908 (95% CI: 0.986-0.920) for version 1.7 and 0.928 (95% CI: 0.917-0.939) for 2.1 when screen-detected and interval cancers were considered as positive cases (p < 0.001). A total of 87.1% (642/737) and 93.5% (689/737) of the screen-detected cancers had an AI score of 10 with version 1.7 and 2.1, respectively. Among interval cancers, 45.0% (90/200) had AI score 10 with version 1.7 and 44.5% (89/200) had AI score 10 with version 2.1.

CONCLUSION: A higher proportion of screen-detected breast cancers had the highest AI score of 10 with the newer version of the AI model compared to the older version. For interval cancers, there was no difference in the proportion of cases assigned to the highest score between the two versions.

KEY POINTS: Question Studies have reported promising results regarding the use of AI in mammography screening, but comparisons of updated versus older versions are less studied. Findings In our study, 87.1% (642/737) of the screen-detected cancers were classified with a high malignancy risk score by the old version, while it was 93.5% (689/737) for the newer version. Clinical relevance Understanding how version updates of AI models might impact screening mammography performance will be important for future quality assurance and validation of AI models.

Schizophrenia is a severe mental illness with high heritability, but its underlying mechanisms are poorly understood. We meta-analyzed large-scale brain transcriptomic data from mice harboring individual loss-of-function mutations in seven schizophrenia risk genes (Akap11, Dagla, Gria3, Grin2a, Sp4, Srrm2, Zmym2). While all studied brain regions were affected, the striatum and the thalamus emerged as key brain regions of convergence. Striatum showed downregulation of synapse- and oxidative phosphorylation-related gene sets in all models. In the thalamus, mutants separated into two groups based on transcriptomic phenotype: synapse-related gene sets were upregulated in mutants with only schizophrenia and bipolar association, and were downregulated in mutants that are associated with developmental delay/intellectual disability in addition to schizophrenia. Overall, our meta-analysis reveals convergence and divergence in brain transcriptomic phenotype in these schizophrenia genetic models, supports the involvement of striatal disturbance and synapse dysfunction in schizophrenia, and points to a key role of the thalamus.

Loss-of-function mutations in AKAP11 (a protein kinase A (PKA)-binding protein) greatly increase the risk of bipolar disorder and schizophrenia. To determine the neurobiological functions of AKAP11, we conduct multi-omic and neurobiological analyses of Akap11 mutant mouse brains. We find that AKAP11 is a key regulator of PKA proteostasis in the brain whose loss leads to dramatically increased levels of PKA subunits and phosphorylated PKA substrates, especially in synapses. Akap11 mutant mice show extensive transcriptomic changes throughout the brain, including prominent decreases in synapse-related genes sets. Gene expression is highly impacted in spiny projection neurons of the striatum, a brain region implicated in motivation, cognition and psychotic disorders. Real-time measurements of PKA activity reveal elevated basal PKA activity in the striatum of Akap11^-/- mice, with exaggerated additional response to dopamine receptor antagonists. Behaviorally, Akap11 mutant mice show abnormally prolonged locomotor response to amphetamine, deficits in associative learning and contextual discrimination, as well as depression-like behaviors. Our study connects molecular changes to circuit dysfunction and behavioral disturbance in a genetically valid animal model of psychotic disorder.

Synapse dysfunction and loss are hallmarks of neurodegenerative diseases that correlate with cognitive decline. However, the mechanisms and therapeutic strategies to prevent or reverse synaptic damage remain elusive. In this Review, we discuss recent advances in understanding the molecular and cellular pathways that impair synapses in neurodegenerative diseases, including the effects of protein aggregation and neuroinflammation. We also highlight emerging therapeutic approaches that aim to restore synaptic function and integrity, such as enhancing synaptic plasticity, preventing synaptotoxicity, modulating neuronal network activity and targeting immune signalling. We discuss the preclinical and clinical evidence for each strategy, as well as the challenges and opportunities for developing effective synapse-targeting therapeutics for neurodegenerative diseases.

Human genetic studies have revealed rare missense and protein-truncating variants in GRIN2A, encoding for the GluN2A subunit of the NMDA receptors, that confer significant risk for schizophrenia (SCZ). Mutations in GRIN2A are also associated with epilepsy and developmental delay/intellectual disability (DD/ID). However, it remains enigmatic how alterations to the same protein can result in diverse clinical phenotypes. Here, we performed functional characterization of human GluN1/GluN2A heteromeric NMDA receptors that contain SCZ-linked GluN2A variants, and compared them to NMDA receptors with GluN2A variants associated with epilepsy or DD/ID. Our findings demonstrate that SCZ-associated GRIN2A variants were predominantly loss-of-function (LoF), whereas epilepsy and DD/ID-associated variants resulted in both gain- and loss-of-function phenotypes. We additionally show that M653I and S809R, LoF GRIN2A variants associated with DD/ID, exert a dominant-negative effect when co-expressed with a wild-type GluN2A, whereas E58Ter and Y698C, SCZ-linked LoF variants, and A727T, an epilepsy-linked LoF variant, do not. These data offer a potential mechanism by which SCZ/epilepsy and DD/ID-linked variants can cause different effects on receptor function and therefore result in divergent pathological outcomes.

A genetically valid animal model could transform our understanding of schizophrenia (SCZ) disease mechanisms. Rare heterozygous loss-of-function (LoF) mutations in GRIN2A, encoding a subunit of the NMDA receptor, greatly increase the risk of SCZ. By transcriptomic, proteomic, and behavioral analyses, we report that heterozygous Grin2a mutant mice show (1) large-scale gene expression changes across multiple brain regions and in neuronal (excitatory and inhibitory) and non-neuronal cells (astrocytes and oligodendrocytes), (2) evidence of hypoactivity in the prefrontal cortex (PFC) and hyperactivity in the hippocampus and striatum, (3) an elevated dopamine signaling in the striatum and hypersensitivity to amphetamine-induced hyperlocomotion (AIH), (4) altered cholesterol biosynthesis in astrocytes, (5) a reduction in glutamatergic receptor signaling proteins in the synapse, and (6) an aberrant locomotor pattern opposite of that induced by antipsychotic drugs. These findings reveal potential pathophysiologic mechanisms, provide support for both the “hypo-glutamate” and “hyper-dopamine” hypotheses of SCZ, and underscore the utility of Grin2a-deficient mice as a genetic model of SCZ. 

The complex functions of neuronal synapses depend on their tightly interconnected protein network, and their dysregulation is implicated in the pathogenesis of autism spectrum disorders and schizophrenia. However, it remains unclear how synaptic molecular networks are altered biochemically in these disorders. Here, we apply multiplexed imaging to probe the effects of RNAi knockdown of 16 autism- and schizophrenia-associated genes on the simultaneous joint distribution of 10 synaptic proteins, observing several protein composition phenotypes associated with these risk genes. We apply Bayesian network analysis to infer hierarchical dependencies among eight excitatory synaptic proteins, yielding predictive relationships that can only be accessed with single-synapse, multiprotein measurements performed simultaneously in situ. Finally, we find that central features of the network are affected similarly across several distinct gene knockdowns. These results offer insight into the convergent molecular etiology of these widespread disorders and provide a general framework to probe subcellular molecular networks.

Schizophrenia is a debilitating psychiatric disorder that affects millions of people worldwide; however, its etiology is poorly understood at the molecular and neurobiological levels. A particularly important advance in recent years is the discovery of rare genetic variants associated with a greatly increased risk of developing schizophrenia. These primarily loss-of-function variants are found in genes that overlap with those implicated by common variants and are involved in the regulation of glutamate signaling, synaptic function, DNA transcription, and chromatin remodeling. Animal models harboring mutations in these large-effect schizophrenia risk genes show promise in providing additional insights into the molecular mechanisms of the disease.

Synaptic dysfunction is implicated in the pathophysiology of schizophrenia (SCZ) and bipolar disorder (BP). We use quantitative mass spectrometry to carry out deep, unbiased proteomic profiling of synapses purified from the dorsolateral prefrontal cortex of 35 cases of SCZ, 35 cases of BP, and 35 controls. Compared with controls, SCZ and BP synapses show substantial and similar proteomic alterations. Network analyses reveal upregulation of proteins associated with autophagy and certain vesicle transport pathways and downregulation of proteins related to synaptic, mitochondrial, and ribosomal function in the synapses of individuals with SCZ or BP. Some of the same pathways are similarly dysregulated in the synaptic proteome of mutant mice deficient in Akap11, a recently discovered shared risk gene for SCZ and BP. Our work provides biological insights into molecular dysfunction at the synapse in SCZ and BP and serves as a resource for understanding the pathophysiology of these disorders.

Disability in multiple sclerosis (MS) is driven in part by the failure of remyelination and progressive neurodegeneration. Microglia, and specifically triggering receptor expressed on myeloid cells 2 (TREM2), a factor highly expressed in microglia, have been shown to play an important role in remyelination. Here, using a focal demyelination model in the brain, we demonstrate that demyelination is persistent in TREM2 knockout mice, lasting more than 6 weeks after lysolecithin injection and resulting in substantial neurodegeneration. We also find that TREM2 knockout mice exhibit an altered glial response following demyelination. TREM2 knockout microglia demonstrate defects in migration and phagocytosis of myelin debris. In addition, human monocyte-derived macrophages from subjects with a TREM2 mutation prevalent in human disease also show a defect in myelin debris phagocytosis. Together, we highlight the central role of TREM2 signaling in remyelination and neuroprotection. These findings provide insights into how chronic demyelination might lead to axonal damage and could help identify novel neuroprotective therapeutic targets for MS.