Lactosylceramides (LacCers) are glycosphingolipids that play essential roles in physiological and pathological processes across immune, endocrine, and neurological systems, with mechanistic studies demonstrating that LacCers modulate inflammatory signalling, oxidative stress responses, membrane microdomain organisation, and control aspects of mitochondrial function. Historically, LacCers were quantified predominantly as a total lipid subclass, limiting the ability to discern how individual species contribute to biological processes in clinical contexts. Recent advances in mass spectrometry based lipidomics now enable LacCer species to be resolved by acyl-chain length and saturation, offering far greater biochemical and clinical insights.

In this narrative review, we examine evidence from population based lipidomic studies describing how LacCer composition varies across healthy and diseased states.

In metabolic and vascular disorders, multiple studies report elevations in specific short- and medium-chain LacCer species, whereas patterns involving longer-chain species appear more heterogeneous. Altered LacCer profiles have also been described in neurodegenerative disease, chronic kidney disease, and cancers, with species-level differences varying by disease-context, tissue type, and analytical platform.

Our findings describe disease- and tissue-specific variations in LacCer acyl-chain composition, underscoring the value of species-level resolution for mechanistic understanding and informing the application of LacCer profiles in future biomarker and therapeutic studies.

Emerging evidence suggests that metabolic and hormonal disturbances in polycystic ovary syndrome (PCOS) may increase vulnerability to neurodegenerative disorders. However, the link between PCOS and Alzheimer’s disease (AD)-related pathology remains unclear.

In this cross-sectional study, plasma levels of β-amyloid (Aβ40, Aβ42), phosphorylated tau (p-tau181), neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) were quantified in women with PCOS and age-matched controls. Homeostasis model assessment of insulin resistance (HOMA-IR), inflammatory cytokines (IL-6, TNF-α) and hormonal parameters were assessed. Mediation and moderation analyses were conducted to explore metabolic and hormonal pathways underlying biomarker alterations.

Among 400 women (200 PCOS, 200 controls), age and BMI were comparable (P > 0.05). Compared with controls, PCOS participants had increased Aβ40, p-tau181, NfL and GFAP, a slightly higher Aβ42, and a lower Aβ42/40 ratio (all P < 0.05). p-tau181 correlated positively with HOMA-IR (r = 0.41) and IL-6 (r = 0.36), while Aβ42/40 ratio correlated negatively with HOMA-IR (r = –0.27). In multivariable analysis, p-tau181 (aOR = 1.34, 95% CI 1.05–1.71), IL-6 (aOR = 1.19) and TNF-α (aOR = 1.14) were independent predictors of insulin resistance. Mediation analysis indicated that HOMA-IR, IL-6 and TNF-α jointly mediated ∼ 71% of the PCOS–p-tau181 association, suggesting a metabolic–inflammatory pathway linking PCOS to AD-related tau pathology.

PCOS is linked to peripheral markers of early Alzheimer’s pathology, largely mediated by insulin resistance and inflammation. PCOS may provide a clinical context to explore metabolic–inflammatory contributors to early neurodegenerative changes.

Major depressive disorder is a prevalent and debilitating mental health condition contributing to a growing global burden. Late-life depression (LLD), affecting individuals over 60 years of age, is further associated with elevated risks for cardiovascular diseases, cognitive decline, and dementia. Treatment responses vary widely, potentially due to underlying neurodegeneration and cellular senescence. We aimed to explore blood-based biomarkers related to Alzheimer’s disease and senescence-associated secretory phenotype (SASP) proteins, seeking to identify biological underpinnings of LLD and their association with response to psychotherapy.

We performed a secondary analysis of the Cognitive Behavioral Therapy for Late-Life Depression (CBTlate) trial in 228 participants aged 60 years and older with a diagnosis of LLD. Depression trajectories were compared using clustering. In participants with available plasma samples, biomarker data were generated post hoc. We assessed associations between biomarkers and depression trajectories, biomarker dynamics, and their ability to predict treatment response.

Two depression trajectories were identified: persistently high stable Geriatric Depression Scale (GDS) scores (hsGDS) and decreasing scores over time (dGDS). The hsGDS group had more severe baseline depression (p = 2.88 × 10−6), anxiety (p = 4.39 × 10−4), and sleep disorders (p = 1.09 × 10−3), and was more likely to have a history of major depression (p = 0.01) and mild cognitive impairment (p = 0.01). Biomarker analysis revealed elevated baseline plasma neurofilament light chain (NfL, p = 2.51 × 10−2) and reduced C-X-C Motif Chemokine Ligand 5 (CXCL5, p = 2.83 × 10−2) in the hsGDS group. Including CXCL5 in predictive models improved trajectory differentiation (p = 3.94 × 10−3).

Cellular aging biomarkers like CXCL5 may improve understanding of LLD and guide personalized therapeutic interventions.

Late-life depression (LLD) arises from a complex interplay among biological, psychological, and social factors. Biologically, three main hypotheses have been proposed to explain the distinct clinical features of LLD. The vascular hypothesis supports vascular-related white matter changes in the development of LLD, while the neurodegenerative hypothesis suggests that LLD might be a prodrome of neurodegenerative diseases. The inflammatory hypothesis, which is the main focus of this review, posits that heightened inflammation underlies LLD directly or indirectly through neurodegenerative and microvascular alterations.

This is a non-systematic review on the role played by inflammation in the pathophysiology of LLD and the related opportunities to define biomarkers and therapeutic targets. We searched PubMed from January 2010 through March 2025 for relevant English-language studies.

Patients with LLD have elevated circulating levels of inflammatory biomarkers (e.g., C-reactive protein and interleukin-6) as well as evidence of neuroinflammation. Although the exact origin of this inflammatory profile remains unclear, it is thought to be exacerbated by immune cell senescence and the presence of physical comorbidities, including cardiovascular and metabolic diseases. Pharmacological (e.g., selective serotonin receptor inhibitors) and non-pharmacological (e.g., diet, physical interventions) approaches for LLD seem to exert their therapeutic effect, at least in part, through inflammation-related mechanisms.

Recognizing the unique features of LLD compared to depression in other periods of life is an important step toward its proper management. More specifically, understanding the role of inflammation in LLD holds both theoretical and practical implications, including anti-inflammatory or immune-based strategies as potential therapeutic interventions.

We aimed to compare and link the total scores of the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA), two common global cognitive screeners.

2,325 memory clinic patients (63.2 ± 8.6 years; 43% female) with a variety of diagnoses, including subjective cognitive decline, mild cognitive impairment, and dementia due to various etiologies completed the MMSE and MoCA concurrently. We described both screeners, including at the item level. Then, using linear regressions, we investigated how age, sex, education, and diagnosis affected total scores on both instruments. Next, in linear mixed models, we treated the two screeners as repeated measures and analyzed the influence of these characteristics on the relationship between the instruments’ total scores. Finally, we linked total scores using equipercentile equating, accounting for relevant patient characteristics.

MMSE scores (mean ± standard deviation: 25.0 ± 4.6) were higher than MoCA scores (21.2 ± 5.4), and MMSE items generally showed less variation than MoCA items. Both instruments’ scores were individually influenced by age, sex, education, and diagnosis. The relationship between the screeners was moderated by age (estimate = −0.01, 95% confidence interval = [−0.03, −0.00]), education (0.14 [0.10, 0.18]), and diagnosis. These were accounted for when producing crosswalk tables based on equipercentile equating.

Accounting for the influence of patient characteristics, we created crosswalk tables to convert MMSE scores to MoCA scores, and vice versa. These tables may facilitate collaboration between clinicians and researchers and could allow larger, pooled analyses of global cognitive functioning in older adults.

Anxiety is a common comorbid feature of late-life depression (LLD) and is associated with poorer global cognitive functioning independent of depression severity. However, little is known about whether comorbid anxiety is associated with a domain-specific pattern of cognitive dysfunction. We therefore examined group differences (LLD with and without comorbid anxiety) in cognitive functioning performance across multiple domains.

Older adults with major depressive disorder (N = 228, ages 65–91) were evaluated for anxiety and depression severity, and cognitive functioning (learning, memory, language, processing speed, executive functioning, working memory, and visuospatial functioning). Ordinary least squares regression adjusting for age, sex, education, and concurrent depression severity examined anxiety group differences in performance on tests of cognitive functioning.

Significant group differences emerged for confrontation naming and visuospatial functioning, as well as for verbal fluency, working memory, and inhibition with lower performance for LLD with comorbid anxiety compared to LLD only, controlling for depression severity.

Performance patterns identified among older adults with LLD and comorbid anxiety resemble neuropsychological profiles typically seen in neurodegenerative diseases of aging. These findings have potential implications for etiological considerations in the interpretation of neuropsychological profiles.