Mobility Patterns and Mental Health During the COVID-19 Pandemic: Longitudinal Observational Study Using Smartphone Mobility Data

<strong>Background:</strong> The COVID-19 pandemic disrupted mobility globally, but its mental health implications remain difficult to characterize because most studies relied on lockdown status, population-level mobility indicators, or self-reported mobility. These approaches may miss individual differences in actual movement patterns and cannot fully examine bidirectional relationships between mobility and mental health. Individual-level smartphone geolocation data may provide a more objective and temporally aligned measure of mobility during periods of societal disruption. <strong>Objective:</strong> This study aimed to use individual-level Google location history (GLH) data and population-level Google community mobility reports (GCMRs) to examine concurrent and longitudinal relationships between pandemic-era mobility patterns and mental health symptoms in Hong Kong. <strong>Methods:</strong> This study analyzed data from the CU-COVID19 cohort study, an online longitudinal survey study of the psychological impact of the pandemic in Hong Kong. Mental health symptoms over the previous 14 days were assessed at baseline, 6 months, and 12 months using the 9-item Patient Health Questionnaire, the 7-item Generalized Anxiety Disorder scale, and the 4-item PTSD Checklist for DSM-5. Participants provided retrospective GLH data reflecting their mobility during the corresponding 14-day survey periods. The analytic sample included 145 participants with baseline GLH data, of whom 110 had 6-month follow-up data and 49 had data available at all 3 assessment waves. GLH data were used to derive mobility factors representing journey diversity, immobility, and remoteness. Population-level mobility during the same 14-day periods was measured using Hong Kong GCMR residential stay data. Concurrent mediation models examined whether individual mobility mediated associations between population-level residential stay and mental health symptoms. Longitudinal models examined bidirectional associations between changes in individual mobility and mental health across 6-month intervals. <strong>Results:</strong> Population-level residential stay was not directly associated with mental health. In concurrent mediation models, higher population-level residential stay was associated with lower individual journey diversity (β=–0.36; <i>P</i>&lt;.001), and lower journey diversity was associated with higher depression (β=–0.29; <i>P</i>=.02) and posttraumatic stress disorder (PTSD) (β=–0.35; <i>P</i>=.002). Bootstrapped indirect effects suggested mediation through journey diversity for depressive symptoms (β=0.11, 95% CI 0.02-0.25) and PTSD symptoms (β=0.13, 95% CI 0.05-0.27), although the depression-related indirect effect became less robust after adjustment for local and individual COVID-19 infection indicators. Longitudinally, higher baseline depressive symptoms predicted subsequent reductions in journey diversity (β=–0.15; <i>P</i>=.02), and reductions in journey diversity predicted higher subsequent depressive symptoms (β=–0.43; <i>P</i>=.008). <strong>Conclusions:</strong> Individual-level mobility patterns, particularly lower journey diversity, showed more consistent associations with mental health symptoms than population-level residential stay. Findings suggest bidirectional relationships between mobility and mental health and demonstrate the potential of smartphone geolocation data for digital phenotyping. However, the modest and self-selected sample, limited GCMR availability, and observational design require cautious interpretation.

ALS Could Be Predicted Years Before Symptoms, Proteomics Study Finds

Neurodegenerative diseases are typically defined by the presence of characteristic clinical phenotypes. However, it is increasingly recognized that early intervention could give people the best chance for meaningful positive effects. As a result, early detection and prevention are becoming major priorities.

Months to several years before amyotrophic lateral sclerosis (ALS) symptoms arise, levels of certain blood proteins may dramatically shift. By anticipating the arrival of symptoms, investigators could intervene with preventative therapies before the irreversible motor neuron damage that is characteristic of ALS sets in.

In this study, researchers analyzed data from the long-running, National Institutes of Health (NIH)-funded Pre-symptomatic Familial ALS (Pre-fALS) study, to identify a lineup of key proteins that may predict the emergence of clinically manifest ALS.

This work is published in Nature Medicine in the paper, “Longitudinal plasma proteomics predict phenoconversion to clinically manifest ALS.”

“If someone carrying an ALS-associated genetic variant had asked me in the past when they would become symptomatic, I would have struggled to provide a reasonable estimate,” said Michael Benatar, MD, PhD, professor of neurology and public health sciences at the University of Miami. “These biomarkers give us a far better idea of the timing, allowing us to estimate the time to symptom onset with an average error of about 18 months. That’s something we can work with.”

For nearly 20 years, the Pre-fALS study has collected data and biological samples from people who are at significantly elevated genetic risk for ALS but have not yet progressed, or phenoconverted, to the disease. While this cohort is unique, permitting the examination of presymptomatic ALS, recent studies suggest that findings from Pre-fALS are likely relevant to the broader population.

In 2017, an analysis of ten Pre-fALS participants who had developed symptoms showed that neurofilament light chain (NfL), a structural protein in neurons, spiked in their blood in the months preceding ALS phenoconversion. As more study participants have begun showing symptoms or signs of disease, new opportunities to search for other pre-symptomatic ALS biomarkers have emerged.

Now, using Olink Explore, investigators report a high-throughput, proteomic study on 516 serially collected plasma samples from 137 study participants; 33 phenoconverters, 35 patients with ALS, 10 pre-symptomatic pathogenic variant carriers and 59 controls.

The team identified 92 whose levels differed in people before they eventually showed symptoms. Using machine-learning techniques, the authors tested how various combinations of proteins could predict future risk of phenoconversion. Characterizing the longitudinal trajectory of these proteins, they identified a core panel of 19 proteins (including NfL) which, collectively, the authors note, predicted phenoconversion over the 0.5-year to 5-year time horizons and yielded estimates of time to phenoconversion with a mean absolute error of 1.6 years.

They also produced similar results using data from the UK Biobank, which, despite some limitations, is more representative of the general population than the genetically predisposed cohort of Pre-fALS.

“With preventative gene-targeting treatments now becoming available, there is a particularly urgent need for reliable biofluid-based signatures that indicate near-term onset in individuals that carry ALS risk genes,” said Amy Bany Adams, PhD, acting director of NIH’s National Institute of Neurological Disorders and Stroke (NINDS).

Tofersen, a drug approved for symptomatic ALS, is currently being evaluated as a preventative therapeutic in pre-symptomatic ALS through ATLAS, a clinical trial designed by Benatar in partnership with the company Biogen. ATLAS will test whether starting treatment shortly before symptoms appear could avert or delay the onset of ALS.

“This is all possible because of the members of the carrier community who believe in our mission of preventing ALS and have supported and participated in our research. It has been one of my life’s greatest privileges to give something back,” Benatar said.

The post ALS Could Be Predicted Years Before Symptoms, Proteomics Study Finds appeared first on GEN – Genetic Engineering and Biotechnology News.

Daily Multivitamin May Help Older Adults Maintain Cardiovascular Function

A daily multivitamin-mineral supplement modestly improved cardiovascular-related functional health in older adults over three years, according to a secondary analysis of the large COSMOS randomized clinical trial. The findings suggest that routine multivitamin use may help preserve day-to-day physical functioning as people age, particularly among those with certain preexisting cardiovascular conditions.

The research was presented July 27 at NUTRITION 2026, the annual meeting of the American Society for Nutrition.

The findings add to a growing body of evidence from the COSMOS trial suggesting that daily multivitamin supplementation may support healthy aging. Previous analyses reported modest improvements in cognitive function and slower biological aging, although multivitamins have not been shown to reduce major cardiovascular events.

The analysis included 16,027 participants from the COcoa Supplement and Multivitamin Outcomes Study (COSMOS), a randomized, double-blind, placebo-controlled trial that enrolled 21,442 U.S. adults without major cardiovascular disease at baseline. Men were at least 60 years old, and women were at least 65 years old when they entered the study.

Investigators evaluated participants’ responses to the Kansas City Cardiomyopathy Questionnaire (KCCQ), a validated patient-reported measure of cardiovascular health status. The questionnaire assesses physical function, symptom burden, and an overall clinical summary score reflecting the combined impact of both.

Participants assigned to receive a daily multivitamin experienced small but statistically significant improvements in symptom burden compared with those receiving placebo. While the supplements did not significantly improve physical ability scores overall, they produced a modest improvement in the overall clinical summary score.

“The results provide new evidence that a daily multivitamin modestly improved cardiovascular-related functional health, with more pronounced benefits in those with existing carotid stenosis,” the investigators concluded.

The largest benefits were seen in participants with carotid stenosis, a narrowing of the carotid arteries that increases the risk of stroke. Among the 122 participants with the condition, multivitamin supplementation produced clinically meaningful improvements in cardiovascular functional health scores, suggesting this subgroup may derive greater benefit than the broader study population.

The researchers noted that maintaining cardiovascular functional health has practical implications for older adults. Improvements in symptom burden may translate into greater ease performing everyday activities such as dressing, bathing, walking, climbing stairs, and completing household chores. Reduced fatigue, shortness of breath, and swelling could also help older adults remain active and independent.

The trial also evaluated cocoa extract supplementation, but it did not improve cardiovascular functional health in the study population overall. However, a subgroup analysis suggested cocoa extract helped preserve symptom burden scores among participants with heart failure, indicating that additional studies may be warranted in patients with established cardiovascular disease.

Unlike many nutrition studies that focus on disease prevention, this analysis examined how supplementation affected participants’ daily functioning and quality of life.

The investigators cautioned that the observed improvements with multivitamin use were modest and should not be viewed as a replacement for established healthy lifestyle measures such as maintaining a nutritious diet and engaging in regular physical activity.

Because this was a secondary analysis, the findings should be considered hypothesis-generating. The authors said future targeted clinical trials are needed to determine whether specific groups of older adults—particularly those with carotid stenosis or other cardiovascular conditions—may experience greater functional benefits from daily multivitamin supplementation.

The post Daily Multivitamin May Help Older Adults Maintain Cardiovascular Function appeared first on Inside Precision Medicine.

MapLight’s Schizophrenia Candidate Has Mixed Results at Phase II

MapLight Therapeutics announced this week that its candidate drug for treatment of schizophrenia had achieved its primary endpoint in a Phase II trial, but only at the twice daily dose tested in the trial.

As reported by the California-based company, while participants of the trial who were given the candidate drug, ML-007C-MA, once a day did show some signs of improvement it was not statistically significant.

ML-007C-MA is a combined muscarinic agonist (betovumeline) and peripherally acting anticholinergic (fesoterodine). It acts by turning on two receptors in the brain, M1 and M4.

M1 is the main receptor the drug is trying to stimulate in the brain cortex and hippocampus, where it is linked to cognition, attention, and possibly some aspects of psychosis. Turning on M4 also helps by acting like a brake on the overactive signaling that contributes to hallucinations and delusions. Betovumeline activates both M1 and M4 centrally, while fesoterodine is there mainly to block unwanted side effects outside the brain, like gastrointestinal issues.

In this study, MapLight randomized 307 adults with an acute exacerbation of schizophrenia to treatment with either a twice daily or once daily treatment with ML-007C-MA or placebo for five weeks.

At five weeks, patients given the twice daily dose had a statistically significant and clinically meaningful reduction in Positive and Negative Syndrome Scale (PANSS) total score of 4.5 points compared to placebo. Cognitive scores were also better in the twice daily group versus placebo.

While this result is positive overall, the non-statistically significant result for the once daily dose proved unpopular with investors and company shares on the Nasdaq fell 40% after the announcement.

In September 2024, Cobenfy, the first muscarinic M1/M4 agonist drug for treatment of schizophrenia was approved by the FDA. Now owned by BMS, Cobenfy will be the main competitor for ML-007C-MA if approved.

Cobenfy was groundbreaking because it was the first new mechanism of action for schizophrenia in decades, moving beyond dopamine blockade to a muscarinic approach and targeting both hallucinations and delusions as well as the more cognitive aspects of the disease, which are not well treated with other drugs.

Despite the approval of Cobenfy, a number of other competitors developing treatments for schizophrenia have failed in recent years. Whether MapLight can succeed at Phase III with ML-007C-MA—which is also being tested as a treatment for psychosis linked to Alzheimer’s disease—and compete with Cobenfy, remains to be seen.

The post MapLight’s Schizophrenia Candidate Has Mixed Results at Phase II appeared first on Inside Precision Medicine.

Large Genomic Atlas Maps How Pregnancy Shapes Maternal Biology

Pregnancy is often described clinically through its complications: gestational diabetes, hypertensive disorders, fetal growth restriction, preterm birth. But beneath those diagnoses is a moving biological system. Maternal metabolism, immunity, hematology and endocrine function are continuously adapting to fetal development, and standard reference ranges only capture part of that complexity.

A new Nature Genetics study puts genomics into that timeline. Using noninvasive prenatal testing data from up to 121,579 unrelated Chinese pregnancies, researchers mapped genetic associations across 111 prenatal and postnatal phenotypes, from blood counts and glucose markers to liver enzymes, thyroid function, serum screening scores, non-invasive prenatal testing (NIPT) risk scores, gestational disorders and birth outcomes. The result is what the authors call “a dynamic genetic atlas of human gestation.”

Turning routine NIPT into a genomic resource

The scale of the study is notable because it uses data already generated in routine care. NIPT produces low-depth sequencing data from maternal plasma, primarily to screen for fetal aneuploidy. Here, the team used those data to infer maternal genotypes and link them to longitudinal clinical measurements from two hospitals in Shenzhen.

Across the 111 gestational phenotypes, the researchers identified 4,688 independent genome-wide significant signals, including 1,703 associations not previously reported for the same or related traits. Many new signals appeared in areas that have been relatively underexplored, including maternal serum screening and NIPT-based trisomy risk scores.

Prenatal screening outputs are usually interpreted as biochemical or fetal-risk measures. This study suggests that maternal genetic background also contributes to variation in some of those scores, which could eventually matter for calibration of risk models.

Pregnancy is not a static genetic context

The more interesting message is not just that gestational traits are heritable. It is that some genetic effects appear to be specific to pregnancy.

By comparing gestational results with nonpregnant female datasets from BioBank Japan and the Taiwan Biobank, the researchers found that 7.8% of high-confidence signals across 30 phenotypes were gestation-specific. These loci were enriched in pathways linked to fetal development, pregnancy maintenance, growth regulation and hormonal adaptation, with genes such as IGF1, ESR1, and PPARG emerging as network hubs.

The study also captured time-varying genetic effects. For 24 complete blood count traits measured repeatedly across pregnancy and postpartum, 18.7% of associated variants showed genotype-by-gestational-timing interactions. In other words, the effect of a variant could strengthen, weaken or shift depending on whether a patient was in the first trimester, late gestation, delivery or postpartum period.

For precision medicine, that is the key point. Pregnancy is not simply a confounder in female health studies; it is a distinct biological state with its own genetic architecture.

Pregnancy as an early health signal

The authors also connected gestational phenotypes with 80 later-life diseases and medication-use traits in BioBank Japan. Genetic correlation and Mendelian randomization analyses linked gestational glycemic traits with diabetes risk, and gestational adiposity, lipids and blood pressure with cardiovascular outcomes.

These results support the idea of pregnancy as an early-life cardiometabolic stress test. However, the interpretation needs care. When the researchers adjusted for related phenotypes from the Taiwan Biobank, many associations were attenuated, suggesting that pregnancy may reveal pre-existing genetic susceptibility rather than directly causing later disease.

The study is therefore less about predicting individual outcomes today than building the architecture for doing so tomorrow. Its limitations are important: the cohort was Chinese, several rarer complications such as preeclampsia were underpowered, and fetal-versus-maternal genetic contributions still need to be separated.

Even so, the direction is clear. Routine prenatal data may become more than a snapshot of pregnancy status. Combined with genomics, it could help define who is adapting normally, who is deviating early, and who may need closer follow-up long after delivery.

The post Large Genomic Atlas Maps How Pregnancy Shapes Maternal Biology appeared first on Inside Precision Medicine.

How lasers could help provide fuel for nuclear reactors

Outside the small town of Paducah, Kentucky, a wealth of uranium is locked away in thousands of storage cylinders filled with waste material from a now-closed nuclear enrichment facility. Lasers could help get it out.

A company called Global Laser Enrichment (GLE) is looking to reprocess this old material with a new technology called laser enrichment. It could be more efficient than conventional enrichment methods, allowing the company to refresh the material and produce feedstock at the same concentration as a natural mined source. And in the future, the company claims, laser enrichment could be used to make material for nuclear fuel, including the kind used in advanced reactors.

Nuclear power provides about 9% of global electricity today, and that fraction could tick up as major world powers like the US and China look to build new reactors, including some based on next-generation technology. New, cheaper methods to obtain fuel could help ensure that those nuclear projects stay on track.

Naturally occurring uranium is largely made up of uranium-238 (over 99%) and uranium-235 (about 0.7%). Uranium-235 is the fissile type, meaning that, when hit with slow low-energy neutrons, it can sustain a chain reaction that generates electricity. So reactors generally use material with a higher concentration of U-235 than what’s pulled from the ground. Today’s conventional reactors usually use low-enriched uranium, typically is about 5% U-235, though some advanced reactor designs will use fuel that’s up to 20% U-235.

Today, centrifuges are the dominant tech used to enrich uranium. The equipment essentially takes uranium-containing material and spins it around incredibly quickly, so the heavier material (which contains U-238) spins out to the edge, while the lighter material (which has U-235) stays closer to the center. (If you’ve ever swung a mustard bottle to get the last of it out, you’ve used the same basic idea behind a centrifuge.) Then the material that has a higher concentration of U-235 can go on to be made into nuclear fuel.

Laser enrichment, on the other hand, takes advantage of the fact that all molecules vibrate and rotate at an atomic scale in ways that depend on their specific material. Even different uranium isotopes have distinct fingerprints.

Lasers are so precise they can target one particular material (like molecules that contain U-235, for example). If you shine a laser at a mixture, you can selectively excite just the material you’re targeting, giving it a bit more energy. This changes the way it behaves, which can make it easier to separate out the material you want using chemical or physical methods.

A wide range of separation approaches have been developed in research and industry. Some aim to electrically charge U-235 atoms, allowing them to be moved with electrostatic or magnetic fields. Others change how the material reacts chemically. 

The details of GLE’s specific technology are classified, and company officials declined to share how the process works. 

There’s been interest in using lasers for uranium enrichment for decades, says Charles Forsberg, a principal research scientist in nuclear science and engineering at MIT. 

However, in their early days lasers tended to be high-maintenance, unstable and difficult to operate. They’ve improved dramatically, making laser enrichment a more attractive prospect than it was during the early research.

Even more than technological improvements, a recent geopolitical shift could boost new enrichment technology. Russia has the largest uranium enrichment ecosystem in the world, and the country has historically dominated the market. “Nobody in the West was going to build a new enrichment plant while the Russians flooded the world with enriched uranium,” says Forsberg. 

Since the start of the Ukraine war, however, countries including the US and UK have taken steps to limit or ban imports of Russian uranium. That’s opened the door for companies to set up new enrichment operations, including some that use new technologies, Forsberg says.

Demand for fuel is increasing as countries look beyond Russia for uranium supply. “The gap is just becoming bigger and bigger, and this technology is right in the middle,” says Christo Liebenberg, president of LIS Technologies, one of the companies aiming to build laser enrichment capacity in the US.

LIS Technologies was founded in 2023, and the company recently purchased a 200-acre site in Oak Ridge, Tennessee. It’s currently in the pre-application process with the US Nuclear Regulatory Commission for its facility. The company plans to take in natural-grade uranium and make a product that’s roughly 5% U-235, though it hopes to eventually make more concentrated material that can be used as fuel for next-generation reactors.

GLE is taking a different approach: Rather than using its technology to enrich freshly mined material to the 5% concentration that can be used in fuels, it’s hoping to start by rehabilitating old waste.

The company has a contract with the US Department of Energy to reprocess waste material at the enrichment site in Paducah. The facility could enrich up to 200,000 metric tons of material that contains small amounts of uranium leftover from an older enrichment process.

GLE is taking the material that’s at least 0.25% U-235 and enriching it to about 0.7%. That material can then be further processed and slotted into the uranium supply chain in place of freshly mined material. “It’s kind of like a large aboveground uranium mine for us,” says Nima Ashkeboussi, vice president of government relations and communications at GLE.

While each one of its units is more complex and expensive than a centrifuge, far fewer are needed to do the same work. A similar centrifugation plant would have many thousands of centrifuges working together, but a full-scale plant using GLE’s laser enrichment process would have fewer than a thousand of its units, says Stephen Long, the company’s CEO. Up-front investment should be smaller, and operating costs are also expected to be lower, partly because the process uses less energy than centrifuges, Long says.

GLE has a testing facility in Wilmington, North Carolina. In fall 2025, the company completed a demonstration pilot, processing several hundred kilograms of uranium. It decommissioned that system and is currently putting together a new demonstration at the North Carolina plant, which would show how the technology works at commercial scale.

The company also applied for a license with the US Nuclear Regulatory Commission for its proposed facility in Paducah. The final safety evaluation should be finished in November, and the final approval should come in 2027, Long says. The plan is to start processing material at the plant by 2030.

In the long run, there’s plenty of uranium on the planet to keep reactors running for decades. But as interest in nuclear power grows and the geopolitics of fuel shift, there could be short-term gaps or price spikes that alternative sources could help smooth out.

Laser enrichment plants could turn out to be cheaper than existing technologies, says Stephen Greene, a senior fellow at the Nuclear Innovation Alliance. But as with most new technologies, “you don’t really know until you try to build one.”

STAT+: Ahead of hearing, FDA questions the efficacy of Capricor’s Duchenne drug

The Food and Drug Administration said Monday that Capricor Therapeutics’ stem cell treatment for Duchenne muscular dystrophy did not meet the objectives of a Phase 3 trial — contrary to the company’s claims last year.

Capricor said in December that the drug, known as deramiocel, met both the primary and secondary endpoints in a large, randomized study. It was a striking result in a fatal, childhood disease that has proven stubbornly difficult to treat, despite immense advances in genetic medicine. 

The data were also notable for coming primarily in teenagers and young men who have already lost the ability to walk, a population with few options. The drug appeared to both preserve their upper-arm function and stave off the heart failure most patients eventually experience, Capricor had said. 

Continue to STAT+ to read the full story…

Research progress on the α-synuclein-lysosome axis in Parkinson’s disease: molecular mechanisms of protein aggregation, autophagy dysfunction, and therapeutic targeting

Parkinson’s disease (PD) is the second most prevalent neurodegenerative disorder worldwide, characterized pathologically by the loss of dopaminergic neurons in the substantia nigra and the formation of Lewy bodies, which predominantly consist of misfolded α-synuclein (α-Syn) aggregates. Recent advances have highlighted the critical role of the interplay between α-Syn and lysosomal function, termed the α-Syn-lysosome axis, as a central mechanism underlying PD pathogenesis. This review systematically summarizes the molecular mechanisms driving α-Syn aggregation and the lysosomal dysfunction contributing to impaired autophagy-lysosome pathway (ALP) activity. We further discuss emerging therapeutic strategies targeting this axis to restore lysosomal function and mitigate α-Syn toxicity. By integrating the latest findings from molecular biology, cell biology, and preclinical studies, this article aims to elucidate the complex regulatory network of the α-Syn-lysosome axis and provide a theoretical foundation for the development of novel therapeutic interventions for PD.

From clinical phenotypes to molecular precision: multimodal biomarkers for progressive supranuclear palsy

Progressive Supranuclear Palsy (PSP) is the most prevalent primary 4R-tauopathy, characterized by the pathogenic accumulation of misfolded tau protein within neurons and glial cells. Historically, clinical diagnosis relied upon the identification of Richardson’s Syndrome, however, the recognition of diverse clinical phenotypes that overlap with Parkinson’s disease, corticobasal syndrome, and frontotemporal dementia has complicated the diagnostic landscape and hindered the success of developing therapeutic interventions. As the field transitions toward a precision medicine paradigm, there is a growing need for validated biomarkers that can provide molecular specificity, facilitate early diagnosis, and accurately track disease progression. This paper reviews the recent advancements in neuroimaging and fluid-based biomarkers, assessing their potential to delineate PSP from similar neurodegenerative conditions and unlock the 4R-tau therapeutic pipeline. In the domain of neuroimaging, while structural magnetic resonance imaging (MRI) and the Magnetic Resonance Parkinsonism Index (MRPI) continue to provide measures of subcortical atrophy, the emergence of second-generation tau-selective positron emission tomography (PET) radioligands represents a transformative shift. New tau PET tracers offer the ability to visualize tau pathology in vivo, providing a more direct assessment of the underlying proteinopathy than traditional volumetric measures. These advancements are complemented by significant progress in fluid biomarkers. Plasma phosphorylated tau at residue 217 (p-tau217) has gained prominence as a robust marker for Alzheimer’s disease, and its primary utility in PSP research currently serves as a critical negative signature to exclude amyloid-associated co-pathology. In contrast, novel assays targeting microtubule-binding region tau fragments show burgeoning potential for the specific identification of 4R-tau isoforms. Furthermore, neurofilament light chain (NfL) has been firmly established as a sensitive, albeit non-specific, indicator of neuroaxonal injury and clinical severity. Additional advancements with digital health approaches and electrophysiological assessments add to the opportunities for improved objective measures. This review concludes that the shift from clinical-only diagnostic criteria to a biomarker-enabled molecular framework is the necessary catalyst for developing effective disease-modifying therapies for PSP and related 4R-tauopathies. The synthesis of these multimodal biomarkers into a unified framework will be essential to improve participant stratification, enable the use of adaptive trial models, and provide supportive evidence of target engagement for future clinical trials.

Synaptic mechanisms for differential severity of social preference deficits in male and female mice induced by diminished activity-dependent BDNF

Males are more commonly diagnosed with autism spectrum disorder (ASD) than females with a ratio of about 4–1. However, the neural mechanisms underlying the sex differences in ASD are unknown. Social deficits are the core symptoms of patients with ASD. Previous studies showed that diminished activity-dependent brain-derived neurotrophic factor (BDNF) signaling induced differential severity of autism-like social preference deficits in male and female mice by using a mouse model with genetic knock-in of human BDNF methionine (Met) allele, which significantly decreased activity-dependent BDNF release without affecting basal BDNF secretion. Here, we investigated the synaptic mechanisms for diminished activity-dependent BDNF-induced differential severity of social preference deficits in males and females. The prefrontal cortex (PFC) is a critical brain region for social behaviors. Whole-cell patch-clamp brain slice recordings showed that diminished activity-dependent BDNF signaling differentially increased the frequency of spontaneous action potentials (sAPs) of pyramidal neurons in the PFC of male and female BDNF+/Met mice. The frequency of sAPs in male BDNF+/Met mice was higher than in female BDNF+/Met mice. Diminished activity-dependent BDNF signaling differentially enhanced excitatory synaptic transmission and dampened inhibitory synaptic transmission of pyramidal neurons at pre- and post- synapses in males and females, which were mediated by dysregulated transcriptional levels of key synaptic genes. Chemogenetic inhibition of pyramidal neurons in the PFC of BDNF+/Met mice was sufficient to ameliorate autism-like social preference deficits in males and females. This study reveals synaptic mechanisms underlying the differential severity of social preference deficit in male and female BDNF+/Met mice, which provides a potential neural basis for sex differences in male and female ASD patients with and without the BDNF Val66Met SNP.