Published in Nature Health, the study by Wu, Yang, Cheng and colleagues followed 1,298 people from middle and later adulthood into older age. Researchers examined blood samples collected at four time points over two decades and measured 10,776 circulating protein markers. This scale allowed the team to move beyond the conventional study of a small number of clinical biomarkers and instead examine the temporal behavior of thousands of proteins simultaneously. The result is described as the first comprehensive map of long-term proteomic stability, revealing that the bloodstream is not governed by one universal pattern of ageing-related change.

Proteins circulating in the blood perform an enormous range of functions. They transport hormones and nutrients, regulate immune reactions, influence clotting, communicate between organs and help repair or remodel tissues. Their concentrations can be affected by genetic variation, diet, infection, medication, inflammation and organ function. Because of this complexity, two people of the same chronological age may have very different molecular profiles. The new study focused on a central question: when a protein level differs between individuals, does that difference represent a stable biological trait, or is it simply a temporary fluctuation?

The answer varied sharply across the proteome. Certain proteins maintained highly individual-specific levels across the 20-year observation period, effectively acting as molecular fingerprints. Other proteins were far more volatile, changing in response to life stage or health status. This heterogeneity distinguishes the broader proteome from routine clinical markers, whose within-person stability is generally more uniform. In technical terms, the researchers examined how much of the total variation in protein abundance was attributable to persistent differences between individuals and how much reflected changes within the same person over time. The balance between these two forms of variation differed considerably from one protein to another.

The researchers also found that long-term protein stability was largely preserved across sex and across the life stages represented in the cohort. That result suggests that many protein-specific patterns are not simply temporary features of adulthood or older age. At the same time, selected proteins displayed changes that may signal transitions between stages of life. These shifts could reflect evolving immune regulation, metabolic remodeling or changes in the function of tissues and organs. Rather than portraying ageing as a uniform molecular decline, the findings support a more nuanced model in which some biological systems remain tightly regulated while others become increasingly dynamic.

Genetics appeared to be a major influence on the most stable proteins. Proteins with persistent, person-specific levels were strongly shaped by inherited factors, indicating that an individual’s long-term circulating profile may be partly encoded in their genome. These stable proteins were also enriched for functions mediated through the circulation, particularly immune regulation. This does not mean that their concentrations are immune to environmental influences or disease. Instead, it suggests that genetic architecture helps establish a personal operating range, or homeostatic set point, against which later deviations can be measured.

That concept formed the basis for the study’s clinical applications. The investigators used stable proteins to construct biological fingerprints and then tested whether these molecular patterns could improve health prediction. In validation analyses using data from the UK Biobank, they defined a sparse and reliable protein panel for estimating biological age. Unlike chronological age, which counts years since birth, biological-age measures attempt to capture the accumulated condition of physiological systems. The researchers reported that the protein-based panel improved biological-age prediction and strengthened its association with ageing-related outcomes, suggesting that a carefully selected subset of stable markers may provide more useful information than simply measuring thousands of proteins indiscriminately.

The study also addressed a critical problem in risk assessment: whether a biomarker represents a person’s enduring susceptibility or merely a momentary response. The researchers distinguished lifelong-stable risk biomarkers from volatile markers for cardiovascular disease and dementia. This distinction could eventually help clinicians interpret blood tests more intelligently. A persistently elevated protein may indicate a long-term biological predisposition, whereas a rapidly changing protein may be more informative as an early warning signal of an active disease process. Both types can be clinically valuable, but they answer different questions and should not necessarily be treated in the same way.

Perhaps the most striking application involved 21 proteins used to define personalized homeostatic baselines. Instead of comparing every patient with a population average, this approach establishes what is normal for that individual and then searches for meaningful departures. The researchers reported that deviations from these personal baselines independently predicted mortality. The signals spanned metabolic, immune and tissue-remodeling pathways, implying that disruption of homeostasis can emerge across several physiological systems at once. The finding raises the possibility that future blood tests could detect a person’s loss of biological balance before conventional diagnostic thresholds are crossed.

The study does not mean that a single protein profile can determine an individual’s future, nor that routine medical testing should immediately be replaced. Protein concentrations are influenced by factors ranging from acute infection to medication use, and translating population-level associations into clinical decisions requires careful replication and prospective testing. Nevertheless, the work provides a framework for separating stable biological identity from short-term molecular noise. By combining long-term observation, broad proteomic measurement and external validation, it points toward a form of precision medicine built not only on disease thresholds, but also on each person’s own molecular history. The bloodstream, these results suggest, is both a record of who we are and a sensitive readout of when our internal systems begin to drift.

Subject of Research: Long-term stability and temporal dynamics of the human blood proteome during ageing and disease.

Article Title: Temporal dynamics of the human blood proteome in ageing and disease

Article References: Wu, W., Yang, Z., Cheng, L. et al. “Temporal dynamics of the human blood proteome in ageing and disease.” Nature Health (2026). https://doi.org/10.1038/s44360-026-00183-1

Image Credits: AI Generated

DOI: https://doi.org/10.1038/s44360-026-00183-1

Keywords: blood proteome, protein stability, ageing, systemic homeostasis, precision medicine, biological age, cardiovascular disease, dementia, mortality, personalized biomarkers, UK Biobank, immune regulation

The need for such predictive tools is particularly urgent in Japan, one of the world’s most rapidly aging societies. Nearly 60 percent of Japanese adults aged 85 and older already receive some form of support through the country’s Long-Term Care Insurance system. Yet disability often develops gradually, through a combination of declining muscle strength, reduced physical resilience, chronic disease, inflammation, and impaired organ function. By the time a person has difficulty walking, bathing, or managing daily activities, opportunities for prevention may already be limited. A reliable biological warning signal could allow healthcare professionals to intervene while older adults still retain enough physical capacity to benefit from exercise, nutritional counseling, rehabilitation, and other supportive measures.

The research team, led by Associate Professor Yusuke Osawa of Keio University’s Graduate School of Health Management, analyzed plasma samples from participants in the Kawasaki Aging Well-being Project, or KAWP. The discovery analysis included 230 adults who were free of disability when their blood was collected and who were followed for approximately 4.5 years. Rather than selecting biomarkers based only on pre-existing theories, the investigators used a data-driven screening strategy to examine 29 circulating proteins. Machine-learning methods and multivariable statistical models were then used to test whether protein concentrations were linked to the later development of disability or death.

Two proteins stood out consistently. Participants with higher levels of B2M and cystatin C were more likely to become disabled during follow-up. In statistical terms, each increase in B2M was associated with a hazard ratio of 1.35 for future disability, while the corresponding hazard ratio for cystatin C was 1.42. A hazard ratio above one indicates an elevated likelihood of experiencing the outcome over time, although it does not mean that every person with a high value will become disabled. Importantly, the associations remained after the researchers adjusted for age, sex, kidney function, lifestyle characteristics, and other potential confounding factors. This suggests that the proteins may capture aspects of biological vulnerability not fully reflected by conventional clinical measurements.

Cystatin C is a small protein produced by most nucleated cells and filtered from the blood by the kidneys. Because its concentration is less dependent on muscle mass than creatinine, the conventional marker used to estimate kidney function, cystatin C can be particularly informative in very old adults, whose muscle mass may be substantially reduced. B2M is also connected to kidney clearance, but it has an additional biological significance. It forms part of major histocompatibility complex class I molecules found on the surface of nearly all nucleated cells and can rise in conditions involving immune activation, inflammation, and altered filtration. In this sense, elevated B2M may reflect both impaired renal handling and persistent immune-system stimulation.

The researchers next asked whether the discovery could be reproduced outside Japan. They turned to the Invecchiare in Chianti, or InCHIANTI, study, a long-running investigation of aging in Italy that followed participants for as long as 15 years. In that independent population, higher concentrations of B2M and cystatin C were again associated with an increased risk of disability, particularly among adults aged 80 and older. Replication across geographically and culturally different cohorts is a crucial test for any proposed biomarker because it helps determine whether an association reflects a broadly shared biological process rather than a feature unique to one study population, healthcare system, or lifestyle pattern.

Not every signal from the Japanese analysis survived this external test. Epidermal growth factor and interferon gamma-induced protein 10 were initially associated with mortality, but their relationships were not consistently reproduced in the Italian cohort. The contrast strengthens the significance of the B2M and cystatin C findings: the two proteins were not merely part of a large list of statistically interesting molecules, but were among the markers showing the most durable connection with disability across populations. Still, the study is observational. It demonstrates association, not proof that raising or lowering either protein directly causes functional decline. The biomarkers may be indicators of several underlying processes rather than independent drivers of disability.

The biological picture emerging from the study is consistent with the concept of “inflammaging,” the gradual increase in low-grade immune activation that accompanies aging. Unlike an acute infection, inflammaging may persist quietly for years, contributing to vascular damage, muscle wasting, impaired repair, and reduced physiological reserve. Kidney dysfunction can add another layer of risk by allowing metabolic waste products and signaling molecules to accumulate in the circulation. In an 85-year-old, even modest changes in renal function or inflammatory activity may have consequences because the body’s ability to compensate for stress is already diminished. B2M and cystatin C could therefore act as accessible readouts of overlapping processes that precede visible disability.

“Our findings suggest that preserving healthy aging requires attention not only to diseases but also to the biological processes that precede disability,” Professor Yasumichi Arai of Keio University said. Earlier identification of high-risk individuals could create a window for interventions before decline becomes irreversible. Dr. Osawa noted that both proteins can already be measured using standard clinical assays, making them more practical than experimental markers that require specialized laboratory platforms. A future screening approach might combine B2M and cystatin C with information about gait speed, grip strength, nutrition, medication use, cognition, and social circumstances. Such a tool would not predict an individual’s fate, but could help direct limited preventive resources toward people most likely to benefit.

The study’s results point toward a shift in how healthcare systems think about longevity. Extending life without preserving mobility and self-sufficiency can leave older adults and families facing years of escalating care needs. Blood-based risk assessment could eventually support a more proactive model, in which clinicians monitor biological changes before a person requires long-term assistance. The next steps will include determining whether repeated measurements improve prediction, identifying clinically meaningful threshold values, and testing whether targeted interventions can alter outcomes in people with elevated B2M or cystatin C. For now, the findings offer a scientifically grounded lead: in the oldest-old, two familiar blood proteins may provide an early glimpse of the path toward disability—and a chance to change it.

Subject of Research: People

Article Title: Plasma proteins associated with disability and mortality risks in Japanese community-dwelling octogenarians

News Publication Date: 27-Jun-2026

Web References: https://doi.org/10.1007/s11357-026-02377-7; https://www.k-ris.keio.ac.jp/html/100007234_en.html

References: GeroScience. “Plasma proteins associated with disability and mortality risks in Japanese community-dwelling octogenarians.” DOI: 10.1007/s11357-026-02377-7.

Image Credits: Dr. Yusuke Osawa, Keio University, Japan

Keywords: aging, disability risk, biomarkers, beta-2-microglobulin, B2M, cystatin C, kidney function, inflammaging, healthy aging, long-term care, gerontology, blood proteins, preventive medicine, older adults, GeroScience

Schizophrenia, a complex and debilitating mental disorder characterized by psychosis, hallucinations, and cognitive disruption, has long challenged scientists due to its multifactorial etiology involving both genetic and environmental components. Though GWAS have previously identified numerous genetic variants associated with schizophrenia, the clinical interpretation of these findings remains obscure without mechanistic links to biological intermediates. The current study pioneers this integration by exploring how aggregated genetic risk translates to quantifiable changes in circulating proteins, offering unprecedented insight into the molecular consequences of genetic liability for psychosis.

The research team utilized polygenic scores, which aggregate the small effects of thousands of genetic variants across the genome into a single predictive metric of schizophrenia risk. This score was calculated for tens of thousands of participants within the UK Biobank, a massive repository of genetic, proteomic, and health data from over half a million individuals. By correlating PRS with levels of myriad blood-based proteins measured via high-throughput multiplex assays, the investigators aimed to identify protein signatures that mediate the relationship between genetic risk and the eventual diagnosis of psychotic disorders.

Crucially, this approach transcends traditional case-control studies by leveraging continuous measures of genetic risk and intermediate protein traits, affording greater statistical power and revealing subtle biomolecular cascades that characterize schizophrenia pathogenesis. The integration of proteomics acts as a bridge, connecting genomic susceptibility loci to downstream biological pathways implicated in neuronal function, inflammation, and immune regulation—domains increasingly recognized as central to schizophrenia’s etiology.

Among the most striking findings was the identification of several proteins whose concentrations in the blood correlated both with heightened schizophrenia polygenic scores and with clinically confirmed psychosis diagnoses. These proteins implicate diverse biological systems, including synaptic remodeling, neuroinflammation, and myelination processes, which may underlie the neurodevelopmental disruptions observed in schizophrenia patients. Such biomarkers not only enhance our understanding of disease mechanisms but suggest novel targets for therapeutic intervention.

The study employed rigorous statistical models designed to adjust for confounding factors such as age, sex, ancestry, and medication status, ensuring that detected associations reflect genuine biological links rather than spurious correlations. By harnessing the depth and breadth of the UK Biobank dataset, the researchers achieved a level of robustness rarely attainable in psychiatric genetics, where heterogeneity and phenotypic complexity often impede conclusive insights.

Importantly, the findings hint at the potential future utility of combined polygenic and proteomic profiling as a predictive tool for stratifying individuals at high risk of developing psychosis before symptom onset. Early identification could pave the way for preemptive clinical interventions, tailoring treatments to an individual’s molecular risk profile and perhaps ameliorating disease severity or even preventing progression altogether.

Furthermore, the results challenge the classical view of schizophrenia purely as a brain disorder by demonstrating that peripheral blood proteins reflect central nervous system pathological processes. This peripheral signature opens up more accessible avenues for monitoring disease state and therapeutic efficacy through minimally invasive blood tests, facilitating longitudinal studies and precision psychiatry.

The intersection of genetics and proteomics also fosters the identification of biological pathways shared across psychiatric disorders, shedding light on why schizophrenia frequently co-occurs with mood disorders and other neuropsychiatric conditions. By mapping protein networks impacted by genetic risk variants, the study provides a scaffold upon which future research can build to unravel the complex biological web that shapes mental health.

This comprehensive analysis exemplifies the power of combining large-scale biobanks with cutting-edge omics technologies, marking a critical step toward decoding the biological underpinnings of psychiatric illness. Through this integrative lens, schizophrenia emerges not as a monolithic disease entity but as a constellation of molecular dysfunctions orchestrated by a polygenic genetic background and manifesting through measurable protein perturbations.

Looking ahead, expanding such integrative analyses to include longitudinal proteomic measurements, neuroimaging data, and environmental exposures will further refine our understanding of causality and trajectory in psychosis. As multi-omics datasets grow increasingly available, machine learning and systems biology approaches will be instrumental in extracting actionable insights from this complex data landscape.

In summary, the research advances a paradigm shift in psychiatric genomics: moving beyond static genetic associations towards dynamic biomolecular networks that mediate disease risk. By pinpointing specific proteins linked to schizophrenia polygenic scores and psychosis diagnosis, the study sets the stage for biomarker-guided clinical care, improved risk assessment, and targeted drug development in a field desperately in need of transformative breakthroughs.

The confluence of large-scale genetic data and proteomics analytics presented here exemplifies an era of precision psychiatry that harnesses the molecular heterogeneity of schizophrenia to tailor individualized interventions. This investigative framework not only enriches our fundamental biology knowledge but holds promise to alleviate the considerable human and societal burden posed by psychotic disorders.

Such pioneering work underscores the imperative for continued investment in genetic epidemiology and biomarker discovery initiatives. By forging these multi-disciplinary alliances, we edge closer to demystifying schizophrenia’s complexity, improving lives through earlier diagnosis, personalized treatment modalities, and ultimately, prevention strategies informed by robust molecular evidence.

This landmark study signals a future where psychiatric diagnosis and management are increasingly defined by biological metrics rather than solely clinical observations, heralding a new era in mental health care with improved outcomes borne from integrative science and technological innovation.

Subject of Research: Genetics and proteomics of schizophrenia and psychosis diagnosis

Article Title: The relationship between schizophrenia polygenic scores, blood-based proteins and psychosis diagnosis in the UK Biobank

Article References:
Kendall, K.M., Legge, S.E., Fenner, E. et al. The relationship between schizophrenia polygenic scores, blood-based proteins and psychosis diagnosis in the UK Biobank. Schizophr (2026). https://doi.org/10.1038/s41537-025-00725-8

Image Credits: AI Generated