ObjectiveTo analyze the prevalence of dyslipidemia and related influencing factors in patients with early-onset schizophrenia (EOS).MethodsWe recruited 289 pediatric and adolescent EOS patients from October 2021 to June 2024 in the Third People’s Hospital of Fuyang. Researchers gathered comprehensive demographic and clinical records. Utilizing the 2023 Chinese Guidelines for Lipid Management, they calculated dyslipidemia prevalence and the incidence of irregularities in total cholesterol, triglycerides, LDL cholesterol, HDL cholesterol, and non-HDL cholesterol. Subsequently, differences in dyslipidemia among different genders, body mass index, and antipsychotic medication groups were analyzed. Finally, independent influencing factors of dyslipidemia in EOS patients were explored.ResultsThe overall prevalence of dyslipidemia was 24.9% (72/289), with abnormal rates of TG, TC, HDL-C, LDL-C, and non-HDL-C being 15.9%, 6.6%, 6.6%, 4.2%, and 7.3%, respectively. Male patients, those who were overweight or obese, and those taking two antipsychotic drugs had significantly higher rates of dyslipidemia. Regression analysis showed that male gender (OR = 2.04, P = 0.016), overweight/obesity (OR = 4.55, P < 0.001), body roundness index (OR = 1.53, P = 0.005), and the use of two antipsychotic drugs (OR = 1.90, P = 0.030) were risk factors for dyslipidemia in EOS patients.ConclusionThe prevalence of dyslipidemia in EOS patients is relatively high. When monitoring lipid levels in clinical practice, particular attention should be paid to male patients, those who are overweight or obese, and those receiving combined drug therapy.
Cerebellar dysconnectivity in schizophrenia spectrum: task-based functional connectivity analysis and cognitive stratification
IntroductionSchizophrenia is conceptualized as a disorder of brain network dysconnectivity, yet relationships between neural alterations, cognitive deficits, and genetic risk remain unclear.MethodsWe examined 86 participants: schizophrenia patients (SCZ), unaffected siblings (SCZ-SIB), healthy controls (CON), and control siblings (CON-SIB). We used a multiscale graph-theoretic analysis of task-based fMRI during N-back working memory and unsupervised clinical-cognitive clustering.ResultsWe found that reduced cerebellum-sensorimotor (CER-SM) and cerebellum-cingulo-opercular (CER-CO) connectivity during the 1-back condition robustly discriminated SCZ from CON (AUC = 0.89). Critically, these dysconnectivity patterns were linked to clinical state, present in SCZ vs. SCZ-SIB but absent in SCZ-SIB vs. CON-SIB, suggesting illness expression rather than familial risk. Unsupervised clustering revealed three data-driven subtypes with distinct cognitive- symptomatic profiles: subtype 1 with relative preservation of verbal abilities (predominantly controls), subtype 2 with marked fluid cognitive impairment (enriched in SCZ), and subtype 3 with intermediate performance with working memory sparing (mixed composition). Cerebellar-cortical hypoconnectivity showed graded alignment across these profiles.DiscussionThese findings demonstrate that cerebellar dysconnectivity is most detectable under moderate cognitive load, tracks with clinical state, and covaries with transdiagnostic cognitive profiles, advancing circuit-based understanding of schizophrenia heterogeneity.
Top 5 Firms Engineering Healthcare in the CNS Space
Central nervous system (CNS) treatments are having a major comeback. These five precision medicine players plan to ride the resurgence.
After a decade of stagnation, the CNS space is seeing a revival in sales and R&D spending as the market was last year projected to surpass $80 billion for the first time since 2013 and hit around $127 billion.
Recent landmark approvals have brought attention back to the CNS, including the U.S. Food and Drug Administration (FDA)’s greenlight of Eisai/Biogen’s lecanemab (Leqembi) for the treatment of Alzheimer’s disease in 2023, and the FDA approval of Bristol-Myers Squibb’s schizophrenia treatment xanomeline/trospium chloride (Cobenfy) in 2024.
At the same time, Johnson & Johnson’s depression treatment, esketamine (Spravato), is on its way to blockbuster status, showcasing the growth potential of the CNS market.
These successes accompany an emerging shift in psychiatry clinical trials from subjective rating scales to more objective endpoints, including digital and physiological measures, with the potential to better tailor treatments to a patient’s biological makeup.
Startups and scaleups are attracting increasing investor attention for their potential to change the way we treat CNS conditions. Check out our list of the most exciting companies that have netted the biggest investor dollars.
1. Aerska
Founded: 2025 | Headquarters: Dublin, Ireland
Aerska’s name is derived from an Irish proverb stating that people survive in each other’s shelter, emphasising the strength of its team.
This team includes co-founder Jack O’Meara, previously co-founder of the liver-focused RNA interference (RNAi) biotech Ochre Bio, who is driven by the experience of loved ones suffering from Alzheimer’s disease.
Aerska is developing RNAi therapies for neurodegenerative conditions, including Parkinson’s and Alzheimer’s disease.
While there are already FDA-approved RNAi therapies on the market, such as Alnylam’s patisiran (Onpattro), these are typically focused on liver and cardiometabolic conditions rather than the CNS.
Aerska’s technology consists of antibody “brain shuttles” that bind to proteins on the blood-brain barrier (BBB). They then carry a payload RNA into the brain.
The payload, which is designed based on data-driven patient stratification and disease biomarkers, then silences specific genes driving the disease.
Aerska has already raised $60 million since its launch, including a $21 million seed round in October 2025 and a $39 million Series A round in February 2026, co-led by EQT Life Sciences and age1.
The company, which has research operations in the U.K., is using the latest funding to drive its pipeline programs toward clinical testing.
2. Beacon Biosignals
Founded: 2019 | Headquarters: Boston, Massachusetts, U.S.
Beacon Biosignals was co-founded by a team including its CEO—MIT neuroscientist Jacob Donoghue, MD, PhD—and its CTO, the machine learning researcher Jarrett Revels.
Boasting more than 100 employees, the company’s goal is to provide objective biomarkers in drug development that neurology and psychiatry have traditionally lacked compared with other areas of precision medicine.
Its FDA-cleared Waveband device measures the brain’s activity, known as electroencephalography (EEG), while patients sleep at home. The EEG data is then stored, quality-controlled, and fed into AI models that can guide the design of clinical trials.
For example, Beacon’s EEG data can identify patients with Alzheimer’s disease who have worse outcomes and might need a more targeted treatment or a different clinical trial than other patients.
Beacon raised $27 million in a Series A round in 2021 and an oversubscribed Series B round worth $86 million in November 2025.
The B round, which included investors such as Innoviva, Google Ventures, and Nexus NeuroTech, will help the startup to accelerate the discovery of neurobiomarkers and broaden clinical adoption of the technology.
Beacon acquired the French sleep monitoring company Dreem in 2023 to access its monitoring data and headband technology. Beacon then acquired the Ohio-based CleveMed in April 2025 to harness technology measuring breathing, oxygen, and other signals.
3. Brainomix
Founded: 2010 | Headquarters: Oxford, U.K.
Brainomix was founded by a team including CEO Michalis Papadakis, PhD, who was scientific director of the preclinical stroke lab at the University of Oxford.
Brainomix is dedicated to speeding up patient care in cases of stroke, where speedy treatment is key.
Brainomix’s flagship product, Brainomix 360 Stroke, is designed to harness AI to interpret brain scans and detect blood clots in patients with stroke, speeding up clinical decision-making.
The product involves a group of tools that automatically analyze images, including results from computed tomography (CT), CT angiography, magnetic resonance imaging (MRI), and CT perfusion.
Brainomix’s technology doubled the rate of thrombectomy treatment in patients with stroke and reduced hospital triage and transfer delays, according to a 2025 study.
The University of Oxford spinout is at a commercial stage, with operations in more than 20 countries, and is expanding into the U.S.
Brainomix raised a $21.2 million Series B round in 2021 and extended its Series C round from $6.5 million in March 2025 to $25.4 million in February 2026, with leading investors including Parkwalk Advisors and Hostplus. The proceeds will fuel the company’s expansion into the U.S. market.
Brainomix has also partnered with heavyweights, including Nvidia, Boehringer Ingelheim, Medtronic, and GE Healthcare.
Brainomix also has a product dedicated to disease monitoring in pulmonary fibrosis.
4. Circular Genomics
Founded: 2021 | Headquarters: San Diego, California, U.S.
Circular Genomics was spun out of the University of New Mexico, with its founders including CSO Nikolaos Mellios, PhD, and Alexander Hafez, PhD.
The company later moved its headquarters from Albuquerque to San Diego in March 2025 to access scientific and operational know-how from Eli Lilly at Lilly Gateway Labs.
Circular Genomics aims to equip medical professionals with a blood test to detect CNS conditions early, in addition to stratifying and guiding the treatment of patients.
Its technology involves using a polymerase chain reaction (PCR) test of a patient’s blood sample to screen for specific circular RNA molecules produced in the brain that can cross into the blood and be measured as a biomarker of disease in the CNS.
Commercially launched in 2024, Circular Genomics’ MindLight SSRI Antidepressant Response Test predicts whether a patient will benefit from common antidepressants called SSRIs with around 77% accuracy. This is designed to predict a patient’s most suitable antidepressants without needing months of trial-and-error approaches.
The company is applying its technology in Alzheimer’s disease, where the approvals of disease-modifying therapies such as Leqembi have led to demand for tests that can detect the disease at earlier stages than traditional tests.
Circular Genomics raised $15 million in a Mountain Group Partners-led Series A round in December 2025 to finance the development of its technology and expansion of its technology in Alzheimer’s disease.
The company also has its sights on other CNS conditions, including multiple sclerosis and Parkinson’s disease.
5. Omniscient Neurotechnology
Founded: 2019 | Headquarters: Sydney, Australia
Omniscient (o8t)’s founders include CMO Michael Sughrue, MD, a neurosurgeon aiming to improve anatomy maps for other surgeons, and machine learning expert Stephane Doyen, PhD.
o8t’s FDA-approved product Quicktome involves using a patient’s MRI brain scans and AI models to map out a patient’s brain circuitry. These maps, accessible from an electronic tablet, can guide surgery to minimize the risk of brain damage compared to using a generalized anatomical diagram.
Quicktome is already in use at major hospitals around the world, including major centers in the U.S. Its partners include U.S. surgical support firm META Dynamic and the U.S. medical device innovation center, The Jacobs Institute.
o8t has raised more than $60 million, and bagged $14 million (AUD 20 million) in January 2026 as part of a Series D round targeted to reach $25 million (AUD 36 million). The round was led by Australia’s National Reconstruction Fund (NRFC) and OIF Ventures, with the aim of keeping the company based in Australia.
The funding is earmarked to fuel the development and commercialization of Quicktome, and grow o8t’s Australian workforce by more than 40. The company also has operations in Atlanta, Georgia, U.S.
o8t also plans to expand the technology into high-growth markets, including brain computer interface targeting, stroke and traumatic brain injury.
Jonathan Smith, PhD, is a freelance science journalist based in the U.K. and Spain. He previously worked in Berlin as a reporter and news editor at Labiotech, a website covering the biotech industry. Prior to this, he completed a PhD in behavioral neurobiology at the University of Leicester and freelanced for the U.K. organizations Research Media and Society of Experimental Biology. He has also written for medwireNews, Biopharma Reporter, and Outsourcing Pharma.
The post Top 5 Firms Engineering Healthcare in the CNS Space appeared first on Inside Precision Medicine.
Opinion: When my child is in psychosis, the pediatric health care system can’t help us
I am sitting in a firm recliner with a wipeable surface during a two-day hospital admission for testing at our local children’s hospital. The chair is designed for durability, not sleep. The pillow beneath my head is flat and smells faintly of disinfectant. A thin hospital blanket scratches against my arms as I shift, unsuccessfully, trying to rest. The room is dim but never quiet. Monitors beep. Machines hum. Footsteps pass the door. Hospital noise does not fade. It embeds itself in the nervous system.
My 13-year-old is finally asleep. His thin body is curled beneath a blanket identical to mine. One shoulder peeks out, bruised from repeated injections of calming medication. A neon orange bandage marks the most recent one, given about an hour ago. I watch his chest rise and fall and allow myself a brief moment of relief.
<![CDATA[New analysis links traumatic brain injury to later psychosis, prompting long-term screening and follow-up.]]>
Pilot Study of Sensor-Informed Smartphone-based Mental Health Interventions for Mood in Early Psychosis: A Micro-Randomized Trial
Conditions: Psychosis; Anxiety; Depression; Rumination
Interventions: Behavioral: Smartphone-based Mindfulness Exercise; Behavioral: Smartphone-based Psychoeducation; Behavioral: Neutral Control Message
Sponsors: Mclean Hospital
Not yet recruiting
Interventions: Behavioral: Smartphone-based Mindfulness Exercise; Behavioral: Smartphone-based Psychoeducation; Behavioral: Neutral Control Message
Sponsors: Mclean Hospital
Not yet recruiting
Impact of abnormal metabolic-immunoinflammatory pathway on splenomegaly in patients with chronic schizophrenia and exploration of risk factors: case-control study
ObjectiveThis study aimed to identify risk factors for splenomegaly in chronic schizophrenia patients and clarify associations among metabolic−immunoinflammatory pathways, psychiatric symptoms and splenomegaly. The findings will help optimize somatic monitoring and intervention strategies.MethodsA case−control design was used. A total of 426 patients were assigned to splenomegaly (n= 165) and non−splenomegaly (n= 261) groups according to abdominal ultrasound. Demographic data, clinical information, and antipsychotic use were collected. Mental symptoms were assessed by the Positive and Negative Syndrome Scale. Hematological indicators were detected, and abdominal ultrasound was performed to evaluate spleen morphology and fatty liver occurrence. SPSS 24.0 was used for statistical analysis, including univariate analysis and binary logistic regression to screen influencing factors of splenomegaly.ResultsThe splenomegaly group had significantly higher levels of lipoprotein(a), cholesterol, triglycerides, HbA1c, CRP, IL-6 and β2-microglobulin than the non-splenomegaly group (all p < 0.05). The incidence of fatty liver and PANSS negative symptom score were significantly higher in the splenomegaly group, while the usage rate of aripiprazole was lower (p< 0.05). Binary logistic regression showed that HbA1c (OR = 1.797, p = 0.046) and PANSS negative symptom score (OR = 2.258, p = 0.003) were independently associated with splenomegaly. Aripiprazole use was associated with lower odds of splenomegaly (OR = 0.656, p = 0.041).ConclusionSplenomegaly in chronic schizophrenia patients is closely linked to metabolic abnormalities and immunoinflammatory activation. Prominent negative symptoms are independently associated with splenomegaly and may serve as an early warning signal. Aripiprazole use is independently associated with reduced odds of splenomegaly.
Beyond dopamine blockade: mechanistic humility and the rise of muscarinic, TAAR1, and glutamatergic pathways in schizophrenia
The approval of the first non–dopamine-blocking therapy for schizophrenia marks a defining moment in psychiatry. Muscarinic M1/M4 modulation, alongside emerging TAAR1 and glutamatergic pathways, signals a shift beyond dopamine dominance toward circuit-level integration. These advances embody mechanistic humility: the scientific courage to prioritize clinical signal over mechanistic certainty. It is the scientific curiosity to revisit older hypotheses, question single-pathway models, and integrate multiple mechanisms. Building on the recognition of dopamine blockade’s experiential burdens, this new era guides psychiatry toward a pluralistic framework. The challenge for 2026 is not to replace dopamine, but to rebalance it, moving from receptor blockade dominance to circuit modulation informed pluralistic treatment. This evolution aims to restore harmony not just among neural circuits, but within the lived experience of patients.
Mass Media Narratives of Psychiatric Adverse Events Associated With Generative AI Chatbots: Rapid Scoping Review
<strong>Background:</strong> Generative artificial intelligence (AI) chatbots have rapidly entered public use, including in contexts involving emotional support and mental health–related interactions. Although these systems are increasingly accessible, concerns have emerged regarding potential adverse psychiatric outcomes reported in public discourse, including psychosis, suicidal ideation, self-harm, and suicide. However, these reports largely originate from journalistic accounts rather than systematically verified clinical data. <strong>Objective:</strong> This rapid scoping review aimed to systematically map and characterize mass media narratives describing alleged adverse psychiatric outcomes temporally associated with generative AI chatbot interactions. <strong>Methods:</strong> A rapid scoping review methodology was applied to publicly accessible news articles identified primarily through Google News searches. Articles published from November 2022 onward were screened for eligibility if they described a specific case in which psychiatric deterioration or crisis was temporally linked to generative AI use. Data were extracted using a structured coding template capturing article characteristics, demographic information, AI platform features, interaction intensity, outcome type and severity, type of evidence reported, and causal attribution language. Descriptive statistics and cross-tabulations were performed. <strong>Results:</strong> A total of 71 news articles representing 36 unique cases were included. Suicide death was the most frequently reported outcome (35/61, 57.4% cases with complete severity coding), followed by psychiatric hospitalization (12/61, 19.7%). Fatal outcomes were disproportionately represented among minors (19/21, 90.5%) compared with adults (17/35, 48.6%). ChatGPT was the most frequently cited platform (51/71, 71.8%), followed by Character AI (10/71, 14.1%). Causal attribution most commonly referenced AI system behavior (45/61, 73.8%), and the term “alleged” was the predominant causal descriptor (33/61, 54.1%). Evidence sources were primarily chat logs or screenshots (34/61, 55.7%), while police or medical documentation was rare (1/61, 1.6%). Regulatory calls were present in 51 of 60 (85%) articles with nonmissing data. <strong>Conclusions:</strong> Mass media reporting of generative AI–related psychiatric harms is concentrated around severe outcomes, particularly suicide deaths among youth, and is frequently framed within regulatory and corporate accountability narratives. While causality cannot be established from media reports, consistent patterns of high-intensity interactions, user vulnerability, and limited safeguard reporting highlight the need for structured safety surveillance, transparent AI risk auditing, and clearer governance frameworks. As generative AI becomes increasingly integrated into everyday psychosocial contexts, systematic research and formal safety monitoring will be necessary to determine whether media-reported harms correspond to verifiable clinical risk patterns.
[Comment] Lived experience perspectives on the development of a Psychosis Metabolic Risk Calculator (PsyMetRiC)
In this issue of The Lancet Psychiatry, Benjamin Perry and colleagues1 present a collaboratively developed, refined, and externally validated risk prediction tool (the Psychosis Metabolic Risk Calculator [PsyMetRiC]) that is clinically available, and that can separately predict the risk of clinically significant weight gain, metabolic syndrome, and type 2 diabetes in young people with psychosis. Key to the collaborative development of PsyMetRiC has been the involvement of young people with a lived experience of psychosis, supported by the McPin Foundation and Equally Well UK.