Population evidence generally points toward lower dementia incidence after cancer and lower cancer incidence after dementia, although results differ by cancer type, dementia subtype, population and analytical design. In a cohort of 3,021,508 adults aged 60 or older, a previous cancer diagnosis was associated with a 25% lower subsequent dementia risk (HR 0.75, 95% CI 0.74–0.76). The association remained after adjustment for competing mortality (SHR 0.56, 95% CI 0.55–0.56), while Mendelian-randomization analysis yielded a smaller inverse association between genetically predicted cancer susceptibility and Alzheimer’s disease (OR 0.97, 95% CI 0.95–0.99). A bidirectional meta-analysis found 8% to 14% lower risks among cancer survivors for all-cause dementia, Alzheimer’s disease and vascular dementia, while dementia was associated with approximately 25% lower subsequent cancer risk.

These findings are sensitive to ascertainment and analysis. In UK Biobank, neither prevalent nor incident cancer was significantly associated with Alzheimer’s disease. All-cause dementia diagnoses rose during the first year after an incident cancer diagnosis (HR 1.83, 95% CI 1.42–2.36) before attenuating toward the null, a pattern compatible with detection bias caused by increased healthcare contact, treatment-related cognitive symptoms or diagnostic investigation. Rotterdam Study dementia estimates ranged from RR 0.71 to 1.10, depending on how cancer exposure, confounding, selective survival and death were addressed. Reduced screening after dementia, delayed diagnosis and long preclinical phases further complicate causal interpretation.

Evidence beyond diagnostic records nevertheless suggests a possible biological component. In a community autopsy cohort of 785 people, including 190 with a history of cancer, cancer was associated with lower odds of advanced Braak neurofibrillary-tangle stages (OR 0.38, 95% CI 0.26–0.55), neuritic plaques (OR 0.52, 95% CI 0.36–0.75) and cerebral amyloid angiopathy, but not with TDP-43, α-synuclein or cerebrovascular pathology. Genetic-correlation and transcriptome-wide association analyses also identified opposing associations across Alzheimer’s disease and several cancers involving cell-cycle regulation, apoptosis, DNA-damage responses and metabolism. The pattern is not uniform across neurodegenerative disorders, including Parkinson’s disease and melanoma, so it does not support a universal cancer–neurodegeneration antagonism.

Breast and prostate cancers illustrate why tumor effects must be separated from endocrine treatment. Estrogen- and androgen-receptor signaling supports tumor growth while also regulating neuronal metabolism, mitochondrial function, synaptic activity, vascular homeostasis and inflammation. Among 70,701 Korean breast cancer survivors, Alzheimer’s disease risk was 8% lower than among 180,265 controls (SHR 0.92, 95% CI 0.86–0.98), but the association did not persist in landmark analyses restricted to more than five years of survival. A Swedish study of 26,741 five-year survivors found no overall association with dementia, Alzheimer’s disease or vascular dementia, although diagnosis after age 65 was associated with a 35% higher Alzheimer’s disease risk (SHR 1.35, 95% CI 1.05–1.75).

Treatment findings are also heterogeneous. In a US claims cohort of 57,843 women with breast cancer, hormone-modulating therapy was associated with lower Alzheimer’s disease incidence (RR 0.82, 95% CI 0.75–0.90) and dementia incidence (RR 0.88, 95% CI 0.83–0.93). A SEER–Medicare analysis of 18,808 women aged 65 or older found a smaller reduction in Alzheimer’s disease and related dementias (HR 0.93, 95% CI 0.88–0.98), varying by age, race and treatment class. For prostate cancer, a meta-analysis of 28 studies with approximately 2.54 million participants associated androgen-deprivation therapy with 20% higher all-cause dementia risk (HR 1.20, 95% CI 1.11–1.29) and 26% higher Alzheimer’s disease risk (HR 1.26, 95% CI 1.10–1.43). Individual cohorts have not consistently reproduced these associations, so the pooled findings do not establish causality.

The review describes overlapping insulin/IGF–PI3K–AKT, mTOR, AMPK, mitochondrial, cell-cycle, chaperone and autophagy–lysosomal pathways with context-dependent consequences. Tumors use them for metabolic adaptation, proliferation, apoptosis resistance and proteotoxic-stress tolerance, whereas Alzheimer’s disease involves energetic failure, impaired proteostasis and neuronal degeneration. Evidence comes mainly from human tissue, cancer-cell systems, organoids and animal models rather than direct studies of people with both diseases, making these biologically plausible contributors rather than demonstrated explanations of inverse comorbidity.

Protein self-assembly provides another possible bridge. In Alzheimer’s-model mice, lung, prostate and colon tumors secreted cystatin C, which interacted with amyloid-beta and activated TREM2-dependent microglial clearance. Disrupting TREM2 or mutating cystatin C eliminated the effects, establishing causality in that experimental system. Other preclinical studies found that amyloid-beta, human islet amyloid polypeptide and calcitonin could alter cancer-cell fitness, but uncertain physiological concentrations, aggregation states and selectivity over nonmalignant cells limit interpretation. Human plasma findings do not support a straightforward systemic anticancer effect, and melanoma-secreted amyloid-beta has promoted brain metastasis experimentally.

The bounded conclusion is that inverse comorbidity may reflect interacting epidemiological, endocrine, metabolic, proteostatic and protein-assembly mechanisms rather than one pathway. The authors recommend treatment-aware longitudinal studies that distinguish cancer subtype and stage from treatment class, dose and duration; incorporate amyloid and tau biomarkers, neuroimaging, endocrine markers and metabolic profiles; and test molecular interactions at physiologically relevant concentrations and aggregation states in patient-derived organoids, immune-competent cocultures and animal models. Whether the tumor-derived cystatin C–TREM2 pathway or other preclinical mechanisms contribute materially to inverse comorbidity in humans remains unknown.

Subject of Research: Epidemiological and experimental evidence on inverse comorbidity between cancer and Alzheimer’s disease

Article Title: Cancer–Alzheimer inverse comorbidity from epidemiology to protein self-assembly

Article References: Zhang, Y., Wang, L., Wei, J., Shuzan, N., & Zheng, J. (2026). Cancer–Alzheimer inverse comorbidity from epidemiology to protein self-assembly. Frontiers in Endocrinology, 17, Article 1992522. https://doi.org/10.3389/fendo.2026.1992522

Image Credits: AI Generated

DOI: 10.3389/fendo.2026.1992522

Keywords: cancer, Alzheimer’s disease, inverse comorbidity, epidemiology, endocrine therapy, amyloid-beta, protein self-assembly, proteostasis, dementia risk, Alzheimer, inverse, comorbidity

The research team, led by Yee-Yin Hoo and Nirmala Bhoo-Pathy of Universiti Malaya, together with collaborators from Flinders University, UNSW Sydney, and hospitals across Malaysia, applied a statistical technique called latent class analysis (LCA) to data from 1,117 adults with breast or colorectal cancer drawn from two Malaysian cohorts. Unlike traditional approaches that treat every combination of conditions as equivalent, LCA is a person-centered method that identifies hidden subgroups—latent classes—within a population based on the co-occurrence of characteristics. In this case, the researchers grouped each patient’s record-verified comorbidities into 20 categories and let the algorithm reveal whether distinct patterns of illness existed beneath the surface of the raw counts.

The results were striking. Overall, 695 patients—62.2 percent of the cohort—had at least one comorbidity, with hypertension, dyslipidaemia, diabetes, and obesity emerging as the most prevalent conditions. But the latent class analysis uncovered something far more informative than prevalence figures: three distinct comorbidity profiles. The largest group, comprising 723 patients, had low comorbidity. A second group of 368 patients displayed a clustered cardiovascular-kidney-metabolic (CKM) pattern, combining heart, kidney, and metabolic conditions. A third, much smaller group of just 26 patients exhibited a multisystem pattern, with conditions spread across multiple organ systems.

What makes these findings particularly compelling is how differently the three groups fared despite superficially similar index scores. All 26 patients in the multisystem group and half of those in the CKM group had a modified Charlson Comorbidity Index of 3 or higher—scores conventionally interpreted as indicating substantial comorbidity burden. Yet the two groups behaved very differently in clinical terms. The CKM group was considerably older than the low-comorbidity group, with a mean age of 62 years compared to 51 years, but their ECOG performance status and their receipt of cancer treatment were statistically indistinguishable from the low-comorbidity class.

The multisystem group told a different story entirely. These patients had nearly four times the odds of having poor performance status, defined as an ECOG score of 2 or higher, compared to the low-comorbidity group, with an adjusted odds ratio of 4.04 (95 percent confidence interval 1.50–10.84). More dramatically, they had only one-tenth the odds of receiving chemotherapy (adjusted odds ratio 0.10, 95 percent confidence interval 0.04–0.25) and roughly one-seventh the odds of receiving anti-HER2 therapy (adjusted odds ratio 0.14, 95 percent confidence interval 0.02–0.86). These are not marginal differences; they represent a fundamental divergence in how the healthcare system responds to patients whose illnesses are distributed across multiple organ systems rather than clustered within one metabolic pathway.

The implications reach beyond Malaysia. Comorbidity is conventionally summarized as a count or index—a practice that, as the authors note, treats different combinations of conditions as though they were interchangeable. Prior systematic reviews have found no gold standard for measuring comorbidity in cancer populations, and the Charlson Comorbidity Index, while widely used, has been criticized for its clinimetric limitations. By demonstrating that pattern matters, the Malaysian study adds a new dimension to an ongoing international debate about how to capture the true complexity of patients with cancer who also carry other chronic diseases.

Particularly noteworthy is the finding that patients in the CKM class—despite carrying cardiovascular and renal comorbidities that would traditionally raise red flags—had performance status and treatment receipt similar to those with low comorbidity. This is a double-edged result. On one hand, it suggests that clinicians in this setting are not withholding standard cancer therapies from patients with heart, kidney, and metabolic conditions, which is reassuring from an equity perspective. On the other hand, as the authors emphasize, it highlights risks that are not reflected by performance status alone. Cardiovascular and renal comorbidities can influence drug dosing, increase the likelihood of treatment-related toxicity, and elevate long-term cardiovascular mortality, even when a patient appears functionally fit at diagnosis.

The concept of cardiovascular-kidney-metabolic health has gained substantial momentum in recent years, notably through a presidential advisory from the American Heart Association that framed CKM syndrome as an integrated continuum rather than a collection of separate diseases. Recent real-world data analyses have shown that CKM syndrome stage predicts cardiovascular outcomes in cancer patients, and international cardio-oncology guidelines from the European Society of Cardiology now explicitly address the management of patients with cancer who have pre-existing cardiovascular conditions. The Malaysian study extends this framework into a multiethnic Asian setting, where the epidemiology of cardiometabolic disease differs markedly from that of high-income Western populations.

Malaysia itself provides a compelling backdrop for this research. As an upper-middle-income country with a multiethnic population comprising Malay, Chinese, and Indian communities, Malaysia occupies an important position in global cancer epidemiology. Southeast Asia has seen rapidly rising cancer incidence, and the region’s health systems face the dual burden of infectious and chronic non-communicable diseases. The two parent cohorts—the Happiness Registry, funded by Novartis Malaysia, focusing on advanced breast cancer, and a colorectal cancer cohort supported by Malaysia’s Long-Term Research Grant Scheme—were designed to capture real-world patterns of care in this setting. The funders had no role in the study design, analysis, or reporting of the present secondary analysis.

The authors are careful to note limitations. The multisystem class, with only 26 patients, requires validation in independent cohorts before its associations can be considered definitive. The study also relied on record-verified comorbidities grouped into 20 categories, which, while more granular than many prior studies, still involves clinical judgment about how conditions should be classified. Nevertheless, the core message stands: comorbidity patterns revealed differences that counts alone would have missed. For a field that has long relied on blunt indices to guide treatment decisions, the study offers a methodological upgrade—one that could ultimately help clinicians identify which patients with cancer and comorbidity need closer monitoring, which need modified treatment plans, and which can proceed with standard care despite carrying substantial additional disease burden.

Subject of Research: Comorbidity patterns and their associations with performance status and treatment receipt in breast and colorectal cancers in a multiethnic Asian setting: a latent class analysis

Article Title: Comorbidity patterns and their associations with performance status and treatment receipt in breast and colorectal cancers in a multiethnic Asian setting: a latent class analysis

Article References: Hoo, Y.-Y., Ng, H. S., Danaee, M., Koczwara, B., Ramalingam, S., Subramaniam, S., Abdul Satar, N. F., Thiagarajan, M., Yip, C. H., & Bhoo-Pathy, N. (2026). Comorbidity patterns and their associations with performance status and treatment receipt in breast and colorectal cancers in a multiethnic Asian setting: a latent class analysis. Supportive Care in Cancer, 34(11), Article 1106. https://doi.org/10.1007/s00520-026-11338-x

Image Credits: AI Generated

DOI: 10.1007/s00520-026-11338-x

Keywords: Comorbidity, patterns, associations, performance, status, treatment, receipt, breast, colorectal, cancers, multiethnic, Asian

Researchers led by Heather A. Hayes of Southern California University of Health Sciences, working with colleagues at the University of Utah and Intermountain Health, examined which clinical and non-clinical factors were associated with discharge to an IRF versus an SNF among people hospitalized with acute ischemic stroke. Their findings, published in Frontiers in Rehabilitation Sciences, reveal a striking pattern: after accounting for stroke severity, comorbidity, and functional status, the factors most consistently tied to placement were increasing age and greater comorbidity burden, while several social and insurance-related factors that appeared influential at first glance faded away under statistical adjustment.

The study focused on a carefully restricted population: 236 adults who had been independent and community-dwelling before their stroke. This design choice matters. Prior research on post-acute placement has often examined clinical or sociodemographic predictors in isolation, without determining whether contextual factors remain associated with IRF versus SNF placement among patients with comparable pre-stroke independence once standardized measures of stroke severity and function are considered concurrently. By limiting the cohort to previously independent individuals and incorporating objective measures alongside demographic and contextual characteristics, the researchers sought to determine whether variation in rehabilitation placement persists even when important clinical indicators of rehabilitation need are accounted for.

The cohort was drawn from a single health system, the University of Utah, with data collected between January 1, 2020 and July 31, 2024. The IRF group of 171 participants was enrolled prospectively, with informed consent, while the SNF group of 65 participants was identified retrospectively from the health system’s enterprise data warehouse, because prospective recruitment was disrupted during 2020–2022 by the COVID-19 pandemic. All participants had confirmed ischemic stroke verified by imaging, and all had been living independently in the community before their stroke, a fact documented through routine questioning by physical or occupational therapists and recorded in discrete chart fields.

The clinical variables the team examined were comprehensive. Stroke severity was measured with the National Institutes of Health Stroke Scale (NIHSS), which evaluates 11 areas and ranges from 0 to 42 points. Comorbidity burden was quantified with the Charlson Comorbidity Index (CCI). Functional status during acute hospitalization was captured with the Activity Measure for Post-Acute Care (AM-PAC)

The AM-PAC “6-Clicks” instrument deserves particular attention because of how it is used in routine care. It is a brief functional assessment that hospital therapists are required to complete, capturing three distinct domains: Basic Mobility, which reflects movements such as transfers and walking; Daily Activities, which covers self-care and everyday tasks; and Applied Cognition, which addresses thinking and communication skills in practical contexts. Because these measures are collected as part of standard workflow rather than as special research assessments, they offer a snapshot of how patients actually present during the acute admission, not just how they perform under study conditions. In this cohort, the researchers also recorded whether patients showed signs of neglect, a condition in which stroke survivors fail to attend to one side of their body or environment, drawing on both the NIHSS and clinical chart review.

The statistical approach distinguished between two levels of evidence. In univariable analyses, where each factor is considered on its own, several characteristics appeared to matter: younger age, cohabitating marital status, living with family, having assistance available, shorter hospital length of stay, private insurance, and even higher NIHSS scores were all associated with greater odds of going to an IRF. That last finding may seem counterintuitive, since more severe strokes might be expected to push patients toward less intensive settings, but it likely reflects the reality that patients with very mild strokes are sometimes discharged home directly, leaving the IRF population enriched for those with measurable rehabilitation needs.

The picture changed substantially once the researchers moved to multivariable analysis, which considers all factors simultaneously. In that adjusted model, only two variables retained independent associations with discharge destination: increasing age, with an odds ratio of 0.95 per year of age, and greater comorbidity burden on the Charlson Comorbidity Index, with an odds ratio of 0.85 per point. Both confidence intervals excluded the null value, indicating statistically reliable associations. Notably, NIHSS scores and AM-PAC Daily Activities scores were no longer associated with placement after adjustment, and marital status, which had appeared influential in univariable analysis, also lost its association. This pattern suggests that the apparent influence of social support and insurance type in simpler analyses may have been entangled with age and comorbidity rather than operating as truly independent drivers of placement decisions.

The odds ratios, while modest in magnitude, translate into meaningful differences across the age spectrum typical of stroke populations. A difference of twenty years in age, for example, corresponds to roughly a threefold difference in the odds of IRF placement when the per-year odds ratio of 0.95 is compounded. Similarly, each additional point on the Charlson Comorbidity Index, which weights conditions such as diabetes, heart failure, and prior malignancy, steadily reduces the likelihood of IRF discharge. Because the study population was restricted to people who had been independent before their stroke, these associations cannot be attributed to pre-existing disability, strengthening the conclusion that age and comorbidity themselves are shaping placement decisions.

The finding that functional status measured during the acute hospitalization did not differ significantly between the two groups, despite their different destinations, is among the most thought-provoking results. If patients going to SNFs and IRFs had comparable AM-PAC scores and similar stroke severity, then the divergence in placement suggests that factors beyond measured rehabilitation need are at work. The authors’ framing of these as non-clinical factors is deliberate: age and comorbidity are clinical in a broad sense, but they are not direct measures of current functional capacity or rehabilitation potential. They may instead serve as proxies for how clinicians, families, and payers perceive a patient’s ability to tolerate intensive therapy, or for expectations about recovery trajectory that are not captured by standardized assessments.

The policy context helps explain why this matters. Medicare regulations require that IRF patients be able to participate in at least three hours of therapy per day, five to six days per week, and demonstrate capacity for measurable functional improvement. These criteria are inherently judgment-laden: predicting who can tolerate intensive therapy and who will improve is not an exact science, and clinicians may reasonably weigh age and comorbidity when making such predictions. But if those judgments systematically channel older patients and those with chronic conditions toward less intensive settings, even when their measured function and stroke severity are comparable to peers who go to IRFs, then some patients may be receiving less rehabilitation than guidelines would suggest is optimal during the critical early recovery window.

The timing of the study window adds an important layer of interpretation. Data collection spanned January 2020 through July 2024, a period encompassing the acute disruptions of the COVID-19 pandemic and its aftermath on hospital operations, rehabilitation capacity, and discharge planning norms. The retrospective identification of the SNF cohort was itself a consequence of pandemic-related disruption to prospective recruitment. While the researchers applied consistent variable definitions across both cohorts, differences in how prospective and retrospective data were ascertained represent a methodological consideration when interpreting the results.

Several limitations frame the findings appropriately. The single health system sample, drawn from an academic medical center in Utah, may not generalize to regions with different rehabilitation capacity, payer mixes, or discharge planning cultures. The sample size of 236, while adequate for the adjusted analyses performed, limits the precision with which less common characteristics could be evaluated. Additionally, the study captured placement at discharge from acute care but did not follow patients forward to compare functional outcomes between those who went to IRFs versus SNFs, so the findings speak to placement patterns rather than to the consequences of those patterns for recovery.

Nevertheless, the study’s central contribution is clear: among previously independent stroke survivors with comparable measured rehabilitation need, who ends up where is shaped substantially by age and comorbidity. This raises questions worth pursuing, including whether these factors reflect appropriate clinical judgment about therapy tolerance, implicit biases in discharge planning, structural constraints such as insurance coverage and bed availability, or some combination of all three. Understanding which of these mechanisms drives the observed associations will be essential if the goal is to ensure that stroke survivors’ access to intensive rehabilitation during the first ninety days after stroke, the period most critical for optimizing functional recovery, is determined by their rehabilitation potential rather than by characteristics that merely travel alongside it.

Subject of Research: Non-clinical and clinical factors associated with post-acute rehabilitation placement after acute ischemic stroke

Article Title: Different rehabilitation destinations: non-clinical factors associated with inpatient rehabilitation versus skilled nursing placement

Article References: Hayes, H. A., Zhang, C., Xiang, S., Smith, B., Williams, P., Presson, A. P., & French, M. (2026). Different rehabilitation destinations: non-clinical factors associated with inpatient rehabilitation versus skilled nursing placement. Frontiers in Rehabilitation Sciences, 7, Article 1984193. https://doi.org/10.3389/fresc.2026.1984193

Image Credits: AI Generated

DOI: 10.3389/fresc.2026.1984193

Keywords: stroke rehabilitation, inpatient rehabilitation facility, skilled nursing facility, discharge planning, post-acute care, NIHSS, Charlson Comorbidity Index, AM-PAC, health disparities, age, comorbidity, ischemic stroke

Functional tic-like behaviors sit at the conceptual intersection of two very different categories of illness. Tourette syndrome and other persistent tic disorders are neurodevelopmental conditions: tics typically begin in childhood, progress in a characteristic head-to-toe, or rostro-caudal, pattern, peak in severity during early adolescence, and affect boys more often than girls, with frequent comorbid attention deficit hyperactivity disorder and obsessive-compulsive disorder. Functional neurological disorders, by contrast, produce neurological symptoms—weakness, abnormal movements, seizure-like episodes—that are inconsistent with identifiable structural or neurochemical pathology and are instead thought to arise from disruptions in functional brain connectivity, network dynamics, and attentional processing. Functional tic-like behaviors borrow features from both worlds, which is precisely why distinguishing them from Tourette syndrome matters: the conditions carry different prognoses and respond to different treatments.

The pandemic was not the first time tic-like symptoms spread through a social network. In 2011 and 2012, a cluster of sudden-onset tics swept through a high school in Le Roy, New York, affecting eighteen adolescents and one young adult; the New York State Department of Health ultimately characterized the outbreak as mass psychogenic illness, with intense media coverage suspected of amplifying symptoms. What changed with COVID-19 was scale and speed. Social media platforms offered a global transmission channel, and a 2024 population-representative German survey estimated the prevalence of social media-induced tic-like illness at between 0.17 and 0.36 percent. In one Australian pediatric clinic, functional tic-like presentations rose from roughly 2 percent of tic cases in 2018 to 36 percent in 2021, and a Boston movement disorder clinic documented an 8.6-fold increase in new functional tic presentations from pre- to post-pandemic periods while developmental tic presentations remained flat.

To organize this fast-moving literature, the Johns Hopkins-led team followed PRISMA systematic review guidelines, searching PubMed and PsycINFO with terms covering tics, Tourette syndrome, and functional neurological presentations. They included English-language studies reporting clinical data on functional tic-like behaviors with at least eight participants, excluding single case reports, non-human work, and commentaries. Thirty-nine studies survived screening, spanning case series, cross-sectional comparisons, case-control designs, and a small number of prospective cohorts. Because many reports drew on the same clinical samples—the Danish national clinic in Herlev, the Hannover and Birmingham specialist services, the University of Calgary tic registry—the authors synthesized findings qualitatively by study sample and conceptual domain rather than pooling numbers, and they appraised methodological quality using the Joanna Briggs Institute critical appraisal tools, with blinded dual-rating of a stratified quarter of the studies showing substantial inter-rater agreement.

Demographically, the syndrome is distinctive. Functional tic-like behaviors begin predominantly in adolescence, with average ages of onset across studies clustering between 13 and 15 years, in contrast to the childhood onset of Tourette syndrome. Clinical registries report female-to-male ratios between roughly 7:1 and 9:1, and gender-diverse individuals are markedly overrepresented, with 37 to 45 percent of participants in several cohorts identifying as gender-diverse—far above population base rates. One report found that gender diversity was more strongly associated with functional tic-like behaviors than biological sex itself. Notably, the German social media-induced illness cohort was an exception, with an even sex distribution that investigators attributed to the male sex of the German YouTube creator proposed as the outbreak’s virtual index case, underscoring how modelled identity can shape who develops symptoms.

Phenomenologically, the review confirms a recognizable profile: abrupt, often explosive onset of complex motor movements and vocalizations that reach peak severity within about a month in most patients, without the rostro-caudal progression typical of Tourette syndrome. The movements themselves range from simple head jerks to directed actions—hitting, throwing, kicking, self-biting—accompanied by socially inappropriate vocalizations, coprolalia, and echoing phenomena. Several features stand out as particularly suggestive of the functional form, including self-injurious behavior, coprophenomena, tic attacks, and symptoms that worsen in the presence of others. The combination of self-injury plus coprophenomena is highly specific to functional tic-like behaviors in several reports, though not diagnostic in isolation. Evidence on premonitory urges and suppressibility is genuinely mixed, with some studies reporting reduced urges and poor suppressibility and others finding the opposite; one direct comparison of Tourette syndrome, functional tic-like behaviors, and comorbid presentations found no differences among the three groups, a finding the authors interpret as reflecting suggestibility and variability in symptom expression.

Psychiatric comorbidity is the rule rather than the exception. An international registry spanning ten centers in eight countries found that up to 80 percent of patients had at least one co-occurring psychiatric condition, with anxiety disorders exceeding 60 percent in most cohorts and mood disorders ranging from 10 to 72 percent. Comorbid Tourette syndrome itself appears in 15 to 50 percent of cases, and other functional neurological symptoms in 16 to 80 percent. By contrast, the classic neurodevelopmental comorbidities of Tourette syndrome—OCD and ADHD—appear at comparatively lower rates in the functional group, and absence of obsessive-compulsive tic-related behaviors and absence of family history of tics were the strongest predictors of a functional diagnosis in one controlled study. Strikingly, after correcting for age and sex, one Danish comparison found psychiatric comorbidity rates did not differ significantly between groups, suggesting the comorbidity profile is shifted rather than simply heavier.

The clinical course is more variable than the onset. A large international registry reported a median symptom duration of twelve months, with spontaneous remission occurring in about 20 percent of patients—though in most of those cases, symptoms later returned. Prospective follow-up studies identified three broad trajectories: global improvement or remission, improvement with persisting impairment, and persistence or worsening with significant disability. Roughly two-thirds of adolescents in a UK tertiary study improved or recovered, but a substantial minority showed no change or deterioration, and about 40 percent of one retrospective cohort developed additional functional neurological symptoms over time, a phenoconversion pattern that raises concern about long-term outcomes. Better prognosis was associated with younger age at onset, shorter time to correct diagnosis, male sex, and discontinuation of secondary gain, while the presence of other functional symptoms and higher baseline severity predicted worse trajectories.

Treatment findings are the most sobering part of the review. Standard Tourette syndrome pharmacotherapy appears largely ineffective: an international registry found that among 122 patients treated with clonidine, guanfacine, aripiprazole, or risperidone, 73 to 89 percent showed no improvement, and any benefit was partial and transient. The Comprehensive Behavioral Intervention for Tics, the frontline behavioral treatment for Tourette syndrome, conferred no advantage over other psychotherapeutic modalities in the one report examining it. More promising signals emerged from treatments targeting the anxiety and mood comorbidities that pervade the condition—cognitive behavioral therapy, serotonin reuptake inhibitors, and psychoeducation all showed retrospective evidence of benefit, and a prospective cohort linked CBT for anxiety or depression to lower tic severity at six months. But only two intervention studies of any kind were identified, both uncontrolled single-arm designs, and neither specified the therapeutic target.

The review’s authors are careful about what their synthesis can and cannot establish. Most of the underlying evidence is retrospective, comorbidity was typically assessed clinically rather than with standardized instruments, no study employed a genuine longitudinal comparative cohort design, and consensus diagnostic criteria remain absent from the field, although the European Society for the Study of Tourette Syndrome’s 2022 criteria showed high retrospective sensitivity in one large series. What the 39 studies collectively establish is that functional tic-like behaviors are a real, distinct, and clinically recognizable entity—not a TikTok fad but a stress-sensitive, socially transmissible functional movement disorder that exploded into visibility during a period of global isolation and now demands randomized trials, validated diagnostic criteria, and mechanistic research. For clinicians, the immediate message is practical: recognizing the profile—adolescent onset, female predominance, abrupt complex symptoms, absent tic history—can shorten time to diagnosis, which is itself one of the few consistent predictors of recovery.

Subject of Research: Demographic, phenomenological, and clinical characterization of functional tic-like behaviors

Article Title: A systematic review to characterize functional tic-like behaviors

Article References: Gary, J. B., Shaw, J. S., & McGuire, J. F. (2026). A systematic review to characterize functional tic-like behaviors. Frontiers in Child and Adolescent Psychiatry, 5, Article 1936806. https://doi.org/10.3389/frcha.2026.1936806

Image Credits: AI Generated

DOI: 10.3389/frcha.2026.1936806

Keywords: functional tic-like behaviors, Tourette syndrome, functional neurological disorder, COVID-19 pandemic, social media, adolescent mental health, systematic review, tic disorders, psychogenic tics, comorbidity, cognitive behavioral therapy, social contagion

The clinical observation that first drew attention to calcium in schizophrenia is deceptively simple. Hypocalcemia, a lowered concentration of calcium in the blood, has been consistently reported in patients with the disorder, yet clinicians have long treated it as a sequela rather than a causal determinant. A large cohort analysis did associate hypocalcemia with use of the atypical antipsychotic risperidone, and antipsychotics are known to modulate the immune system and bone metabolism, producing secondary metabolic effects that are well documented in this population. Recent interpretations of akathisia, the distressing syndrome of inner restlessness and objective fidgeting, rocking and pacing that can accompany antipsychotic therapy, also implicate the calcium channel blockade that these drugs perform. Evidence from a Mendelian randomization study adds a genetic dimension, suggesting that calcium regulatory hormones are linked to psychiatric phenotypes and that innate differences in calcium regulation could influence both disease biology and individual sensitivity to drug-induced movement disorders.

Calcium channels themselves have a strong neuropsychiatric pedigree. Mutations and polymorphisms in these channels have been associated with the onset of migraine, cerebellar ataxia, autism, depression, bipolar disorder and schizophrenia. Because calcium entry through voltage-gated channels depolarizes the cell surface membrane and triggers gene expression, secretion and contraction in neuronal cells, any inherited or acquired disturbance of channel function has the potential to reshape synaptic plasticity across the brain. The authors emphasize that a host of vulnerability factors, including unhealthy lifestyle, reduced physical activity, smoking, poor diet and genetic elements, confer risk for schizophrenia, and that a substantial number of patients are predisposed to the cumulative side effects of their medications. All of these factors converge on systemic changes, especially along immune and metabolic trajectories.

The genuinely new perspective comes from the immune side. The research group previously demonstrated elevated levels of soluble Suppressor of Tumorigenicity-2, or sST2, a member of the interleukin-1 family, during the exacerbation of psychosis. When sST2 binds IL-33, it dampens the effects of that alarmin cytokine, and in schizophrenia sST2 was found to exert beneficial effects by negatively correlating with scores reflecting negative symptoms. In a subsequent study of 27 patients with schizophrenia in remission, the team observed something unexpected: a statistically significant positive correlation between serum sST2 concentrations and calcium levels, with a correlation coefficient of 0.454 and a p value of 0.020. These findings suggest a connection between calcium and a key substrate of sterile inflammation in the disorder, positioning calcium as a potential regulator of immune-metabolic signaling rather than a passive bystander.

To understand why this correlation matters, one must follow calcium into the endoplasmic reticulum, the intracellular store that fine-tunes signaling in neurons and pancreatic beta cells alike. A review by Luiz Bergantin provided critical insights into the functional implications of dysregulated intracellular calcium released from the endoplasmic reticulum, unfolding the basis of cyclic adenosine monophosphate stimulation in schizophrenia, asthma and diabetes. Under this framework, increased intracellular calcium concentration may precede dysregulation of the dopamine system, airway smooth muscle hypercontractility and decreased insulin release. In other words, a single intracellular disturbance could set the stage for the dopaminergic dysfunction of psychosis, the bronchial hypercontractility of asthma and the insulin secretory failure of diabetes simultaneously.

The molecular bridge between these processes is the protein Disrupted-In-Schizophrenia 1, or DISC1, one of the most significant susceptibility genes for the disorder. DISC1 is localized to the endoplasmic reticulum membrane and functionally interacts with components that regulate calcium release. Loss of DISC1 function leads to dysregulation of calcium handling, with increased release of the ion into the cytosol. Based on these findings, DISC1 acts as a fine-tuning regulator of calcium release from the endoplasmic reticulum and of intracellular calcium dynamics, while its dysfunction produces significant disruption of intracellular signaling. These disturbances are accompanied by disruption of synaptic homeostasis and of dopaminergic and glutamatergic neurotransmission, which are central characteristics of schizophrenia. Mutations in DISC1 have been shown to alter the functioning of IP3 receptors and voltage-gated calcium channels, directly implicating endoplasmic reticulum calcium dynamics in major mental illness.

Pancreatic beta cells tell a parallel story. Under conditions of chronic hyperinsulinemia and endoplasmic reticulum stress, the synthesis of proinsulin and the organelle’s regulatory role in maintaining intracellular calcium homeostasis are disrupted, accompanied by increased calcium leakage from the endoplasmic reticulum and a resulting chronic rise in cytosolic calcium. This imbalance may begin with enhanced insulin secretion, but over time it depletes secretory capacity and drives functional decompensation of the beta cells. Chronically elevated cytosolic calcium activates calcium-dependent proteases, mitochondrial pathways and oxidative stress, leading to apoptotic mechanisms and loss of beta-cell mass. Chronic low-grade inflammation through secreted cytokines further enhances endoplasmic reticulum stress and destabilizes calcium homeostasis, creating a vicious cycle in which immune signaling and calcium handling destroy each other’s equilibrium.

The IL-33/ST2 pathway weaves the immune and metabolic threads together. Under physiological conditions, IL-33 activates regulatory T cells and type 2 innate lymphoid cells, promoting an anti-inflammatory milieu and adipose thermogenesis. In obesity, however, an expression-function paradox emerges: although IL-33 expression is elevated in obese adipose tissue, effector cell dysfunction impairs its protective attributes, including sST2-mediated neutralization. The authors also draw parallels between the immune responses of asthma, the prototype of a type 2 immune response, and schizophrenia, noting that patients with the psychiatric disorder appear to have a more pronounced type 2 immune response, as indicated by elevated sST2 during exacerbations, a response that may be corrected with antipsychotics. Repeated exacerbations in both diseases, accompanied by inflammation in the microvascular network, could lead to deterioration of joint tissues, fibrosis and gliosis. Consistent with this, one etiological model of asthma proposed calcium elevation within the endoplasmic reticulum as an endogenous inducer of inflammation, and in vitro studies observed that ST2 was less expressed in bronchial epithelial cells in asthma, with stimulation by IL-33 increasing intracellular calcium in that proinflammatory environment.

The clinical implications are considerable. A meta-review of first-episode psychosis has framed the condition as a multisystem disorder, with central nervous system, immune, cardiometabolic and endocrine alterations present from the outset, and the authors suggest that calcium is involved not only in early programming but in the orchestration of a unique immunometabolic and mental profile later in life. Cumulative effects could drive neurodegeneration and neuroprogression in patients, and frequent exacerbations and deterioration may be linked to disturbances in calcium/ST2 dynamics. Inflammation and calcium homeostasis are among the hallmarks of aging pathways used to identify potential frailty biomarkers. A considerable number of patients with schizophrenia have chronic low-grade inflammation and constitute an inflammatory subgroup of the disorder, with notable immune differences observed in those resistant to conventional therapy. Immune markers are increasingly suggested as potential targets of pharmacotherapy, and the IL-33/ST2 signaling pathway is emerging as a viable new target across neuroinflammatory conditions, since targeting sST2 could attenuate neuroinflammation and promote repair mechanisms in the brain.

Novel antipsychotic drugs are already moving in this direction. The Trace Amine-Associated Receptor 1 agonist has been demonstrated to reduce microglia-mediated inflammatory response, acts as an inhibitory modulator of the dopaminergic system, and is considered a promising new target for improving beta-cell health in type 2 diabetes. Notably, TAAR1 impacts the signaling and internal mobilization of calcium, and the authors argue that the crosstalk among TAAR1, calcium and the IL-33/ST2 pathway needs further exploration in schizophrenia. Improvement of the negative and cognitive symptoms with more viable anti-inflammatory or immunomodulatory agents should be the main focus of future pharmacotherapeutic strategies. The authors close with a call to incorporate these findings rapidly into clinical practice: a better understanding of calcium-dependent immune-metabolic signaling may improve the identification of biologically distinct schizophrenia phenotypes and of patients at increased risk of metabolic comorbidity, and future studies should determine whether calcium/ST2 interactions could serve as clinically relevant biomarkers or therapeutic targets. If the hypothesis holds, the ion that fires every synapse may also explain why the mind and the metabolism fail together.

Subject of Research: Calcium at the crossroads of the immunometabolic signaling and comorbidity in schizophrenia

Article Title: Calcium at the crossroads of the immunometabolic signaling and comorbidity in schizophrenia

Article References: Borovcanin, M. M., Debnath, M., Janicijevic, S. M., Petrovic, I., Muric, N., & Janjic, V. (2026). Calcium at the crossroads of the immunometabolic signaling and comorbidity in schizophrenia. Frontiers in Synaptic Neuroscience, 18, Article 1882307. https://doi.org/10.3389/fnsyn.2026.1882307

Image Credits: AI Generated

DOI: 10.3389/fnsyn.2026.1882307

Keywords: calcium signaling, schizophrenia, sST2, IL-33/ST2 pathway, DISC1, immunometabolism, Calcium, crossroads, immunometabolic, signaling, comorbidity, scientific research

The project, known as MapCoBD (Mapping the natural course of comorbid bipolar disorder via integration of multimodal data), is a 12-month naturalistic observational study led by researchers at the University of Cagliari, the University of Padova, and collaborating institutions across Italy and Canada. Its central question is deceptively simple: does the year-long clinical course of bipolar disorder differ between people with classic episodic illness and those whose bipolar disorder is complicated by ADHD or BPD? The answer could reshape how psychiatrists understand, monitor, and treat one of the most disabling conditions in medicine, which ranks among the top ten causes of disability and mortality worldwide.

The rationale for the study rests on a striking gap in the literature. Classic episodic bipolar disorder — the reference point for nearly everything psychiatry knows about the illness — is characterized by a later age of onset, low rates of comorbidity, and familial loading for the disorder. By contrast, people with bipolar disorder and comorbid BPD show greater psychiatric complexity, elevated suicide-related morbidity, and increased long-term hospital utilization, while those with comorbid ADHD face a lower quality of life, more mood episodes, higher rates of substance abuse and dependence, and worse overall functioning. Despite these well-documented clinical burdens, almost no longitudinal study has systematically compared the actual trajectories of these three groups while simultaneously measuring the biology that might underlie their differences.

MapCoBD will recruit 150 individuals with bipolar disorder at two Italian clinical sites, the University of Cagliari and the University of Catanzaro, dividing them into three groups of 50: classic episodic bipolar disorder, bipolar disorder with comorbid ADHD, and bipolar disorder with comorbid BPD. Each participant will be assessed at baseline, six months, and twelve months, with a battery spanning mood symptom ratings, neuropsychological testing, fasting blood sampling, and structural brain MRI at 3 Tesla. Crucially, the study does not stop at periodic snapshots. Every participant will complete daily mood ratings throughout the entire year, allowing researchers to capture the fine-grained texture of mood instability that episodic clinic visits inevitably miss.

The primary endpoint is a measure the researchers call illness burden: the proportion of evaluable follow-up days spent with moderate-to-severe psychopathological symptoms, derived from the prospective NIMH Life Chart Method. Each day is classified as either meeting or not meeting this threshold, and the resulting score ranges from zero — no days of significant symptoms — to one, meaning moderate-to-severe symptoms throughout the entire interval. Mathematically, the measure corresponds to the normalized area under the curve of a daily binary illness indicator, a formulation that turns a year of lived experience into a single, comparable number across all three groups. Daily affective ratings will separately characterize mood instability as a secondary outcome.

Beneath the clinical monitoring lies an equally sophisticated molecular program. At each visit, fasting blood samples collected between 8:00 and 10:00 a.m. will yield serum, plasma, and RNA for analysis of three biological systems chosen for their relevance to mood regulation and stress responsivity. The first is the endocannabinoid system, a critical modulator of synaptic plasticity and emotional processing whose dysregulation has been implicated in bipolar disorder; large-scale genetic studies have even found enrichment of endocannabinoid signaling gene sets in bipolar disorder risk loci. The second is inflammation, with a panel of 120 cytokines, growth factors, and chemokines quantified through a multiplex antibody array — a choice grounded in meta-analyses showing consistently elevated pro-inflammatory cytokines such as IL-6 and TNF-α across mood states. The third is the tryptophan–kynurenine pathway, the metabolic route that converts the amino acid tryptophan into neuroactive compounds ranging from the neuroprotective kynurenic acid to the neurotoxic quinolinic acid, thereby forming a direct biochemical bridge between immune activation and brain function.

The technical machinery behind these measurements is formidable. Endocannabinoids including anandamide and 2-arachidonoylglycerol, along with their catabolic enzymes and receptor targets, will be quantified using liquid chromatography tandem mass spectrometry, PCR, and western blotting. Kynurenine pathway metabolites will be measured with high-performance liquid chromatography and tandem mass spectrometry, with enzymatic activity inferred from ratios such as kynurenine-to-tryptophan for IDO and TDO activity, and kynurenic acid-to-quinolinic acid for the balance of NMDA receptor antagonism and agonism. MicroRNA profiles — capturing epigenetic regulation — will be sequenced on an Illumina NextSeq 2000 after careful quality control and normalization. Meanwhile, the MRI protocol includes diffusion-weighted imaging for white matter tract reconstruction and resting-state functional connectivity analyses performed with the CONN toolbox and SPM 12, examining both region-to-region and seed-to-voxel connectivity.

Perhaps the most forward-looking element of the protocol is its use of machine learning to weave these data streams together. Because the number of measured features will far exceed the 150 participants, the researchers will apply dimensionality reduction techniques such as LASSO and principal component analysis before training supervised algorithms including penalized logistic regression, random forests, support vector machines, and extreme gradient boosting. Two predictive tasks are planned: a multiclass classification distinguishing the three clinical groups, and prediction of longitudinal mood instability and illness burden. To guard against the overfitting that plagues high-dimensional psychiatric data, all preprocessing, feature selection, and hyperparameter tuning will be confined to inner folds of a repeated nested cross-validation scheme, with held-out data touched only for final evaluation. Feature importance will be interpreted using permutation importance and SHAP values, and the team is explicit that any signatures emerging from these analyses are exploratory and will require independent validation before any clinical use.

The hypotheses are clinically pointed. The researchers expect both comorbid groups to show greater illness burden and mood instability than the episodic reference group, but with distinct flavors: the BPD-comorbid group is anticipated to display greater affective instability and impulsivity, while the ADHD-comorbid group is expected to show more prominent attentional and neuropsychological impairment. This distinction matters because emotional dysregulation, impulsivity, and attentional difficulties overlap heavily across ADHD, BPD, and bipolar disorder itself, often complicating diagnosis and treatment planning. If the study finds that these overlapping symptoms track with distinguishable biological signatures — say, different inflammatory profiles, kynurenine metabolite ratios, or patterns of anterior cingulate connectivity — it would suggest that the comorbid presentations are not merely more severe versions of bipolar disorder but biologically distinct trajectories in their own right.

The implications, if the hypotheses hold, could extend from the clinic to the broader philosophy of psychiatric diagnosis. Evidence of distinguishable longitudinal profiles could push clinicians toward more systematic screening for ADHD and BPD in bipolar patients, and toward comorbidity-sensitive monitoring — closer tracking of emotional volatility in one group, more rigorous assessment of executive function in another. Repeated biological sampling may also reveal whether molecular alterations are stable traits of the comorbid profiles or state-dependent echoes of mood fluctuation, a question that cross-sectional studies have never been able to answer. The authors are careful to note the limitations: the naturalistic design precludes causal inference, a 12-month window may not capture the full cyclicity of the illness, and the sample size is modest for machine-learning analyses. Recruitment is already well underway, with 110 individuals tested at baseline. But if MapCoBD succeeds in linking the daily texture of mood to the molecular currents beneath it, the study could mark a decisive step toward precision psychiatry for one of the world’s most burdensome mental illnesses.

Subject of Research: A longitudinal multimodal study protocol comparing the clinical course and biological signatures of bipolar disorder with and without comorbid ADHD or borderline personality disorder

Article Title: Mapping the natural course of comorbid bipolar disorder via integration of multimodal data (MapCoBD): a study protocol

Article References: Comai, S., Morena, M., Steardo, L., Jr, Squassina, A., Pisanu, C., Meloni, A., Congiu, D., Lazzardi, S., Pinna, M., Contu, M., Nasini, S., Barzon, B., Zuliani, A. M., Dall'Acqua, S., Balestrieri, A., Campolongo, P., Pullano, I., Iazzolino, A. M., de Filippis, R., … Manchia, M. (2026). Mapping the natural course of comorbid bipolar disorder via integration of multimodal data (MapCoBD): a study protocol. Frontiers in Human Neuroscience, 20, Article 1924416. https://doi.org/10.3389/fnhum.2026.1924416

Image Credits: AI Generated

DOI: 10.3389/fnhum.2026.1924416

Keywords: bipolar disorder, ADHD, borderline personality disorder, comorbidity, endocannabinoids, inflammation, kynurenine pathway, microRNA, neuroimaging, machine learning, mood instability, biomarkers

The research team, led by Yuan-Yuei Chen of Tri-Service General Hospital and National Defense Medical University in Taipei, together with colleagues including Chung-Ching Wang, drew on nationwide population-based databases in Taiwan to identify older workers who were diagnosed with cancer between 2004 and 2015. Taiwan’s comprehensive national health insurance system and linked administrative registries make it an unusually powerful setting for this kind of epidemiological work, allowing researchers to follow large numbers of patients over long periods with minimal loss to follow-up. The team used Cox proportional hazards models, a mainstay of survival analysis, to identify which sociodemographic, clinical, and work-related factors were associated with returning to work, and Kaplan–Meier analyses to compare long-term survival between survivors who returned to work and those who did not.

The statistical approach deserves a moment of explanation, because it shapes how the findings should be read. Cox proportional hazards models estimate the hazard—the instantaneous risk—of an event occurring at any given time, relative to a reference group, while adjusting for other variables in the model. In this study, the outcome of interest was the cause-specific hazard of returning to work during follow-up. Kaplan–Meier analyses, by contrast, produce survival curves that visually track the proportion of patients still alive over time, allowing researchers to compare mortality trajectories between groups. When the curves for two groups separate, that separation signals a difference in survival experience; when the separation widens over the follow-up period, it suggests the difference is growing.

What did the models reveal? Several factors were associated with a lower cause-specific hazard of returning to work among older survivors. Older age itself was a barrier, which is perhaps unsurprising given that advancing age brings both greater physical burdens from treatment and closer proximity to conventional retirement. Male sex was also linked to a lower hazard of returning to work, as were selected comorbidities—additional chronic conditions beyond the cancer itself. Receipt of chemotherapy or radiotherapy predicted a lower likelihood of returning to work, consistent with the well-documented fatigue, cognitive changes, and functional limitations that can accompany these treatments. Interestingly, higher income and engagement in physically demanding occupations were also associated with a reduced hazard of returning to work, a pattern that may reflect the physical toll of manual labor on older bodies recovering from cancer, as well as the possibility that higher-income workers face less financial pressure to resume employment quickly.

On the other side of the ledger, survivors diagnosed at earlier cancer stages had a higher cause-specific hazard of returning to work compared with those diagnosed at more advanced stages, and patients with colorectal, breast, or prostate cancer were more likely to return to work than the corresponding reference groups. These cancer types often carry relatively favorable prognoses and are associated with treatment regimens that may be less disabling than those for other malignancies. The stage effect is particularly intuitive: earlier-stage disease typically requires less aggressive therapy and leaves patients with better preserved functional capacity, making a return to the workplace more feasible.

The most eye-catching result, however, concerns survival. The researchers found that survival differed significantly between survivors who returned to work and those who did not, across all cancer stages. The separation of the Kaplan–Meier survival curves was more pronounced among patients with stage III or IV disease, suggesting that the association between returning to work and survival was especially visible in those with advanced cancer. Most importantly, in the Cox models, returning to work was independently associated with a reduced risk of all-cause mortality. In other words, even after accounting for other measurable factors, older survivors who went back to work died at a lower rate during follow-up than those who did not.

What could explain such an association? The authors are careful to frame returning to work as a marker that reflects both clinical recovery and broader social reintegration, rather than claiming that employment itself directly prolongs life. This distinction matters. Survivors well enough to work are, by definition, healthier on average than those who cannot work, a phenomenon epidemiologists call confounding by indication or, in this context, the healthy worker effect. Yet the relationship is unlikely to be purely one-directional. A substantial body of prior research links physical activity to lower mortality, including large analyses such as the PURE study spanning 130,000 people across 17 countries and meta-analyses of 71 prospective cohorts showing a dose-response relationship between physical activity and cancer mortality. Work, particularly for older adults, can provide structured activity, cognitive stimulation, social contact, and a sense of purpose—factors that other studies have tied to better health outcomes among cancer survivors and older adults generally.

The study also sits within a broader scientific conversation about aging and cancer. Researchers have described an aging-cancer cycle in which the biology of aging—cellular senescence, frailty, and declining tissue resilience—both increases cancer risk and complicates recovery, while cancer and its treatments can themselves accelerate aspects of aging. Comorbidity is a central player in this cycle: prior studies have shown that additional chronic conditions worsen mortality and quality of life among survivors of colorectal, breast, and other cancers. Depression, too, has been linked to elevated cancer mortality in recent meta-analyses. Against this backdrop, the new findings suggest that sustained work participation might be one tangible, measurable dimension of successful survivorship in older adults—one that occupational health services, rehabilitation programs, and employers could actively support rather than passively observe.

The practical implications are significant for societies with rapidly aging workforces. Taiwan, like many countries, is confronting the economic and social challenges of population aging, and policymakers there have explicitly promoted active aging and aging in place. If returning to work after cancer is a signal of resilience and reintegration, then survivorship-focused interventions—gradual return-to-work schedules, workplace accommodations, vocational rehabilitation, and coordination between oncology teams and occupational physicians—could help more older survivors achieve it. Prior studies of interdisciplinary rehabilitation programs in breast and prostate cancer survivors have shown that structured support can improve occupational reintegration, and research on barriers to return-to-work has repeatedly identified employer attitudes, symptom burden, and lack of guidance as modifiable obstacles. The Taiwanese study’s authors conclude that survivors who returned to work experienced more favorable survival outcomes, highlighting the importance of supportive, survivorship-focused interventions that facilitate sustained work participation among older adults. As the global population of older cancer survivors continues to grow, the question is shifting from whether elderly patients can return to work to how medicine and society can help them do so—and whether doing so might, in turn, help them live longer, more engaged lives.

Subject of Research: Return to work and long-term survival among elderly cancer survivors

Article Title: Return to work in elderly population with cancer

Article References: Chen, Y.-Y., Chen, Y.-J., Wu, W.-T., & Wang, C.-C. (2026). Return to work in elderly population with cancer. Supportive Care in Cancer, 34(10), Article 960. https://doi.org/10.1007/s00520-026-11201-z

Image Credits: AI Generated

DOI: 10.1007/s00520-026-11201-z

Keywords: return to work, cancer survivors, elderly, survival analysis, Cox proportional hazards, Kaplan–Meier, Taiwan, comorbidity, occupational health, cancer rehabilitation, gerontology, survivorship

The study, led by Ajay Pandey and senior author Raj Chovatiya, drew on the National Ambulatory Medical Care Survey, a federally administered dataset that captures representative snapshots of visits to office-based physicians across the country. By pooling survey waves from 2003 through 2015, the researchers assembled a weighted sample of approximately 12.4 billion ambulatory care visits, an enormous denominator that allowed them to examine relatively uncommon diagnoses with meaningful statistical precision. Within that population, roughly 0.10 percent of visits involved seborrheic dermatitis and 0.23 percent involved psoriasis, figures that reflect the share of routine outpatient encounters rather than the prevalence of the diseases in the general population.

The central result was striking in its symmetry. Patients with psoriasis had more than eightfold increased odds of having a comorbid seborrheic dermatitis diagnosis, with an adjusted odds ratio of 8.36 and a 95 percent confidence interval running from 4.28 to 16.32. When the analysis was reversed, patients with seborrheic dermatitis showed nearly identical odds of also having psoriasis, at an adjusted odds ratio of 8.19. Both associations were highly statistically significant, with p values below 0.0001. The bidirectional consistency matters because it argues against a one-way artifact, such as dermatologists simply being more likely to note a second diagnosis once one inflammatory skin disease is already on the chart.

To understand why this overlap exists, it helps to look at the biology the two diseases share. Seborrheic dermatitis is classically associated with the lipophilic yeast Malassezia, which colonizes sebum-rich areas of the skin such as the scalp, eyebrows, nasolabial folds, and chest. The yeast is not simply an infection; rather, its metabolic activity and presence appear to trigger an innate immune response involving inflammasome activation and downstream T helper cell signaling. Psoriasis, by contrast, is driven by a cascade centered on interleukin-23 and interleukin-17, producing the accelerated keratinocyte proliferation and plaques that define the disease. Yet the two pathways converge in important ways, including shared involvement of T helper 17 signaling, antimicrobial peptide dysregulation, and defects in the skin barrier that permit both microbial colonization and inflammatory amplification.

This immunological common ground is what gave rise to the term sebopsoriasis, describing patients whose clinical presentation blends features of both conditions, often in the scalp and facial regions where the diseases are difficult to distinguish. Previous systematic reviews and meta-analyses, including work published by overlapping author groups in 2024, had suggested an elevated co-occurrence of the two diseases in clinical studies. What the new analysis adds is population-level evidence drawn from ordinary outpatient practice rather than from specialized referral centers, where selection bias could inflate apparent associations. The consistency of the eightfold signal across such a broad, nationally representative sample strengthens the case that the comorbidity is genuine rather than an artifact of tertiary care.

Perhaps the most clinically consequential finding, however, concerned what did not differ. The researchers examined healthcare resource utilization metrics, including the time patients spent with their physicians and the number of healthcare visits, and found no significant differences among patients with psoriasis alone, seborrheic dermatitis alone, or both conditions together. On the surface, that might suggest that comorbid disease does not impose a heavier burden on the healthcare system. But the authors caution that these are coarse measures. A single office visit may absorb substantial complexity without registering as longer or more frequent, and the survey data cannot capture prescriptions filled, emergency department use, or the cumulative toll of managing two chronic conditions simultaneously.

Where the groups clearly diverged was in prescribing patterns. Patients carrying both diagnoses were significantly more likely to receive topical antifungal agents, combination topical corticosteroid and vitamin D analog formulations, and topical sulfur preparations. They were also numerically the most likely to be prescribed systemic antibiotics, topical corticosteroids, and topical salicylic acid. That prescription fingerprint tells a story of therapeutic improvisation. Combination corticosteroid and vitamin D analog products are a mainstay of psoriasis treatment, while antifungals target the Malassezia-driven component of seborrheic dermatitis. Patients with both diseases appear to receive a blended regimen that addresses both inflammatory axes at once, even though no formal treatment guidelines exist for the overlap syndrome.

The absence of dedicated guidance is precisely why the authors argue that more research is needed. If sebopsoriasis represents a distinct immunological phenotype rather than simple coincidence, it may respond differently to emerging targeted therapies. Recent dermatology literature has explored phosphodiesterase 4 inhibitor-responsive dermatoses as an emerging concept, and expert consensus panels have weighed the risks of long-term topical corticosteroid therapy against newer advanced topical treatments for inflammatory skin disease. Multi-omics studies published in 2025 have begun identifying shared diagnostic targets between seborrheic dermatitis and scalp psoriasis, hinting that molecular signatures could eventually guide therapy selection for patients whose disease straddles the two diagnoses.

There are also broader implications for how the conditions are studied. A 2026 retrospective cohort study reported bidirectional associations between seborrheic dermatitis and a range of epithelial barrier diseases, and separate JAMA Dermatology work documented elevated rates of epithelial barrier diseases among adults with seborrheic dermatitis. Taken together with the new ambulatory care analysis, a picture emerges of seborrheic dermatitis not as an isolated cosmetic nuisance but as a condition embedded in a wider network of barrier and immune dysfunction. That reframing could influence screening practices, encouraging clinicians who diagnose one inflammatory skin disease to consider whether a second, subtly different process is also at play, particularly in overlapping anatomical territories.

The study is not without limitations, and the authors are careful about what their data can and cannot show. Cross-sectional survey data capture associations at single points in time and cannot establish that one disease causes the other, nor can they distinguish whether the comorbidity reflects shared genetic susceptibility, common environmental triggers such as Malassezia colonization and barrier injury, or diagnostic clustering by physicians. The weighted prevalence figures describe visits rather than people, so they cannot be read directly as population prevalence. Still, with an effect size as large as eightfold in both directions, drawn from billions of weighted encounters, the signal is difficult to dismiss. For the millions of patients living with these chronic, relapsing conditions, the message is that the boundary between dandruff’s inflammatory cousin and psoriasis may be blurrier than the clinic’s diagnostic codes suggest, and that treatment for one may need to account for the other.

Subject of Research: The association between seborrheic dermatitis and psoriasis and its impact on healthcare utilization and prescribing patterns in the United States

Article Title: Association of seborrheic dermatitis and psoriasis and impact on healthcare utilization in the United States

Article References: Pandey, A., Hopkins, T., Maher, S., & Chovatiya, R. (2026). Association of seborrheic dermatitis and psoriasis and impact on healthcare utilization in the United States. Archives of Dermatological Research, 318(1), Article 399. https://doi.org/10.1007/s00403-026-04886-z

Image Credits: AI Generated

DOI: 10.1007/s00403-026-04886-z

Keywords: seborrheic dermatitis, psoriasis, sebopsoriasis, comorbidity, dermatology, healthcare utilization, NAMCS, Malassezia, topical corticosteroids, skin barrier, inflammatory skin disease, prescribing patterns

The team, led by Neng Dong with colleagues Dehui Guo and Lili Jiang, recruited participants between January 2020 and December 2023 and analyzed their questionnaire responses using symptom network analysis, a statistical framework borrowed from graph theory. In this approach, each symptom becomes a node, and the statistical associations between symptoms become edges connecting those nodes. Instead of asking whether depression and anxiety are related in aggregate, the method asks which specific symptoms are most strongly wired to which others, and which nodes hold the network together if information or activation flows through it.

What the researchers found was striking for how sparse it was. The final network contained 41 nodes but only 20 non-zero edges, giving a density of just 2.44 percent. Twenty-six of the nodes were completely isolated, statistically disconnected from everything else. For a field that often assumes comorbid symptoms are densely interwoven, that picture is a reminder that associations between symptoms in questionnaire data can be fragile, dependent on measurement choices, and far from universal.

Within that sparse structure, however, a clear hierarchy of influence emerged. Psychic anxiety, scored as item 10 on the Hamilton Depression Rating Scale, showed both the highest node strength, a measure of how strongly a symptom connects to its neighbors, and the highest bridge strength, a measure of how strongly it links different symptom communities, in this case bridging the domains of depression, anxiety, and sleep. Four of the remaining top five strength positions belonged to individual components of the Pittsburgh Sleep Quality Index: subjective sleep quality, sleep disturbances, daytime dysfunction, and sleep latency, the time it takes to fall asleep.

That pattern is clinically evocative. It suggests that the mental agitation of depression and the fragmented architecture of poor sleep may act as statistical crossroads, the points where depressive and anxious complaints touch. If future research confirms such a role, patients whose depression is dominated by inner restlessness and broken sleep might deserve particularly careful assessment, since these features could mark the fault lines along which comorbidity develops.

The authors were careful, however, to prevent their findings from hardening into premature conclusions. Node strength and bridge strength were treated strictly as descriptive properties of the observed correlations, not as causal or interventional indices. A symptom that scores high on these measures is not necessarily a driver of the disorder, and targeting it clinically does not guarantee benefit. Network centrality, the authors stress, describes the shape of statistical association, not the mechanics of illness.

The team also ran an unusually thorough set of robustness checks. Because some questionnaire items had missing values, they generated 20 multiple-imputation datasets, estimated a Spearman correlation matrix on each, and averaged the results before applying the EBICglasso regularization procedure with a tuning parameter of 0.5, a technique that suppresses weak, likely spurious edges. The rank ordering of the strongest nodes remained stable across these imputations, with median Spearman correlations of 0.931 for node strength and 0.956 for bridge strength. It also held up in a complete-case analysis, in a subgroup of patients with more severe depression defined by a Hamilton score of 14 or above, in a network pruned to control for overlapping item content, and in an alternative ordinal estimation based on the cor_auto procedure. A redundancy check using the Goldbricker tool found no nodes so similar that they should be collapsed.

One sensitivity analysis, though, delivered a cautionary twist. When the researchers replaced the seven individual Pittsburgh Sleep Quality Index components with a single global sleep-quality score, the apparent prominence of sleep in the network faded markedly. In other words, the strong showing of sleep nodes depended partly on the fine-grained way sleep was measured. A coarser instrument might never have revealed sleep as a hub at all. That is a methodological lesson with wide implications for network psychiatry: the granularity of measurement can shape, and sometimes inflate, the apparent centrality of a symptom domain.

The practical takeaway is deliberately modest. The authors conclude that careful clinical assessment of anxiety and sleep in depression remains worthwhile, because these domains emerged as the most statistically prominent features of the comorbid symptom network. But they explicitly warn against reading the results as a roadmap for treatment targets. The data are cross-sectional, drawn from a single outpatient hospital, and cannot establish which symptoms cause which, whether the patterns replicate across cultures and settings, or whether interventions aimed at psychic anxiety or specific sleep components would alter the course of depressive illness.

Even so, the study adds a valuable piece to an evolving picture of depression as a heterogeneous network rather than a monolith. It shows that even in a sample of moderately to severely depressed outpatients, most symptom connections are weak or absent, while a small handful of features, led by psychic anxiety and the texture of disturbed sleep, carry disproportionate statistical weight. Whether those hubs prove to be genuine levers of illness or merely artifacts of how we measure distress will be the question that longitudinal and interventional studies must now answer.

Subject of Research: Symptom network analysis of comorbid anxiety and sleep symptoms in major depressive disorder

Article Title: Psychic anxiety and sleep components in major depression: a symptom network analysis of comorbid symptoms

Article References: Dong, N., Guo, D., & Jiang, L. (2026). Psychic anxiety and sleep components in major depression: a symptom network analysis of comorbid symptoms. BMC Psychiatry. https://doi.org/10.1186/s12888-026-08109-7

Image Credits: AI Generated

DOI: 10.1186/s12888-026-08109-7

Keywords: major depressive disorder, symptom network analysis, psychic anxiety, sleep quality, PSQI, HAM-D, bridge symptoms, comorbidity, network psychiatry, EBICglasso, cross-sectional study, Psychic

The study, led by researchers at The Affiliated Central Hospital of Dalian University of Technology and published in BMC Cancer, followed 920 women who had survived at least five years after their ovarian cancer diagnosis. Rather than tracking them from diagnosis, the investigators anchored all follow-up at the fifth anniversary of the diagnosis, a technique known as a landmark analysis. Each woman entered the analysis at the later of that anniversary and her UK Biobank enrollment, ensuring that the risk estimates reflect mortality genuinely occurring in the survivorship period rather than deaths that happened before the landmark. Of the 920 survivors, 845 also had whole-exome sequencing data available, allowing the team to probe whether inherited variants in DNA repair genes shaped long-term outcomes.

During post-entry follow-up, 322 deaths occurred among the survivors. The largest share, 183 deaths, was attributable to ovarian cancer itself. Cardiovascular disease claimed 58 lives, second primary malignancies 42, and other non-cancer causes 39. To quantify these risks properly, the researchers used the Aalen–Johansen estimator to compute cause-specific cumulative incidence, a statistical approach that accounts for competing risks, meaning that a woman who dies of a heart attack can no longer die of ovarian cancer, so treating all deaths as equal would distort the picture. Five years after the survivorship landmark, the cumulative incidence of ovarian cancer death stood at 15.6 percent, while the combined incidence of all competing causes of death was 7.5 percent.

The gap between those two figures is statistically striking. The adjusted risk difference was minus 8.1 percentage points, with a 95 percent confidence interval running from minus 10.4 to minus 5.8, indicating that ovarian cancer mortality remained firmly predominant among five-year survivors as a whole. For the clinical community, this is a sobering counterpoint to the optimism that often accompanies the five-year survival milestone. It suggests that ovarian cancer survivors need continued, disease-focused surveillance well beyond the period when most follow-up schedules begin to taper off, and that late recurrence or progression remains a dominant threat even in a population often informally considered cured.

Yet the study also reveals that this predominance is not uniform. When the researchers stratified their analysis, the advantage of ovarian cancer death over competing causes weakened and the confidence intervals came to include zero among three groups: survivors aged 65 or older, those carrying more than two comorbid conditions, and those living in the highest tertile of socioeconomic deprivation. In other words, among older, sicker, and poorer survivors, deaths from cardiovascular disease and other non-cancer causes become nearly as likely as deaths from the original cancer. This finding reframes survivorship care as a genuinely multidisciplinary enterprise, one in which cardiometabolic health and social circumstances matter alongside oncological surveillance.

The risk factors for each cause of death followed distinct patterns. Advanced stage and serous histology, the most aggressive and common subtype of ovarian cancer, were associated mainly with ovarian cancer mortality, reflecting the biological behavior of the malignancy itself. By contrast, older age, greater deprivation, a higher comorbidity burden, adiposity, and current smoking were linked primarily to cardiovascular mortality. The comorbidity effect was particularly dramatic: women with more than two comorbidities had a subdistribution hazard ratio of 3.32 for cardiovascular death, with a 95 percent confidence interval of 1.86 to 5.92, meaning their risk was more than triple that of women with fewer coexisting conditions. These are modifiable or manageable factors, which gives the finding practical weight for clinicians designing survivorship programs.

Perhaps the most intriguing result came from the genomic analysis. Carriers of germline variants in homologous recombination repair genes, the same family of genes that includes BRCA1 and BRCA2 and that has long been known to raise ovarian cancer risk, faced markedly higher mortality from second primary malignancies than non-carriers. The subdistribution hazard ratio was 3.74, with a 95 percent confidence interval of 1.88 to 7.42. Homologous recombination repair is a cellular mechanism that fixes double-strand breaks in DNA, and inherited defects in this pathway impair the body’s ability to prevent cancer-causing mutations from accumulating. The new data suggest that this vulnerability does not disappear after an initial cancer diagnosis; instead, it continues to expose survivors to elevated risk of entirely new malignancies over the long term.

The authors themselves flag an important caveat: that genomic estimate rests on few events, so it should be interpreted as hypothesis-generating rather than definitive. Even so, the finding points toward a future in which germline genetic status becomes part of routine survivorship risk stratification. Women carrying HRR variants might warrant intensified screening for second cancers, while the broader survivor population could benefit from aggressive management of cardiovascular risk factors such as smoking, obesity, and coexisting chronic disease. Because many chemotherapy regimens, including platinum agents used widely in ovarian cancer, can themselves stress the cardiovascular system, the high comorbidity and adiposity signals in the data underscore how treatment and lifestyle interact over decades.

The methodology deserves attention as well. Competing-risk statistics such as the Fine–Gray and cause-specific Cox models used here are often absent from survivorship studies, which frequently report all-cause mortality and thereby blur together deaths from fundamentally different mechanisms. By separating ovarian cancer deaths from cardiovascular, second-cancer, and other deaths, and by quantifying cumulative incidence with proper confidence intervals, this study provides a template for how large biobank-linked cohorts can generate clinically actionable survivorship evidence. The use of linked UK Biobank data, with its combination of clinical records, socioeconomic indicators, biochemical measurements, and whole-exome sequencing, is what made the multimodal risk analysis possible in the first place.

The broader message for the estimated hundreds of thousands of women worldwide living beyond five years after ovarian cancer is twofold. First, vigilance against the original cancer remains justified; ovarian cancer was still the single largest cause of late death in this cohort, with a cumulative incidence nearly twice that of all competing causes combined. Second, survivorship is not only about cancer. Older survivors, those with multiple chronic conditions, and those facing socioeconomic deprivation face cardiovascular risks that rival their oncological ones, and inherited DNA repair defects quietly raise the specter of new cancers decades later. Tailored, risk-stratified follow-up, informed by stage, histology, comorbidity, deprivation, and genotype, could convert these statistical insights into longer and healthier lives for a growing population of long-term survivors.

Subject of Research: Cause-specific mortality patterns and clinical, genomic, biochemical, and socioeconomic risk determinants among five-year ovarian cancer survivors

Article Title: Cause-specific mortality and multimodal risk determinants among 5-year ovarian cancer survivors

Article References: Yang, Y., Wang, Y., Jiao, Y., & Wang, J. (2026). Cause-specific mortality and multimodal risk determinants among 5-year ovarian cancer survivors. BMC Cancer. https://doi.org/10.1186/s12885-026-16866-7

Image Credits: AI Generated

DOI: 10.1186/s12885-026-16866-7

Keywords: ovarian cancer, cancer survivorship, cause-specific mortality, competing risks, homologous recombination repair, cardiovascular mortality, second primary malignancy, UK Biobank, comorbidity, socioeconomic deprivation, Fine-Gray model, Aalen-Johansen estimator