Biology subjects

Rusinek, H.

Publications and source records attributed to Rusinek, H..

4 recordsLinked to original sources

bioRxiv2026

Hypertension is related to a slower radiotracer removal from lateral ventricles

BackgroundImpairment of brain waste removal contributes to Alzheimers disease etiology and progression. Although hypertension is a risk factor for dementia, little is known about how it affects measures of clearance in human brain. MethodsCross-sectional (n=159) and longitudinal (n=94) analysis of the relationship between blood pressure (BP) and brain clearance. The estimate of brain clearance was measured using positron emission tomography (PET) as the rate of radiotracer (MK-6240) efflux from the lateral ventricles in the 10-30-minute window after tracer injection. We also examined cerebral blood flow, PET-derived tau deposition in the medial temporal lobe, cognition and plasma biomarkers of neurodegeneration. At baseline we compared participants with (n=88) and without (n=71) hypertension. For longitudinal analyses we defined two groups based on systolic BP trajectories from baseline to follow-up: as long-term controlled (n=76) or uncontrolled BP (n=18). ResultsAt baseline, subjects with hypertension had lower ventricular clearance than normotensive controls (Cohens d=0.53, p=0.001). Over the course of the observation period (median 1.85 years) subjects in the uncontrolled BP group experienced a steeper reduction in clearance rates ({beta}=-5.88) than subjects in the controlled BP group ({beta}=-0.81, interaction p=0.039). ConclusionsOur study suggests that hypertension impairs brain clearance of fluids.

neuroscience↗

bioRxiv2026

Distinct Hippocampal Cellular Pathologies Influence Cognition Across Diagnostic Categories, also distinguishing Schizophrenia from Affective Psychoses

Introduction: Total and social cognition deficits independently predict functioning in psychosis, but targeting these in clinical trials are unsuccessful in improving function. The admixture of schizophrenia and affective psychoses cases could be a roadblock if these differ in cellular pathology. Methods: We examined cognitive functioning (MATRICS) and hippocampal cellular pathologies based on metabolite biomarker concentrations (1H-MRSI), using categorical and transdiagnostic classifications in 80 participants: 22 non-psychotic affective disorder (NP-aff), 25 healthy controls (HC), and 33 with psychosis (Psy), including 20 schizophrenia and 13 affective psychoses (aff-P) cases. Results: NP-aff and HC had similar total cognition (46.64{+/-}12.01 vs 41.10{+/-}17.88), both superior to Psy (28.34{+/-} 12.34; p's<0.01). Mean metabolite concentrations were similar across all groups but showed significant within-group associations to cognitive tests. For HC, total cognition, working memory and reasoning deficits were associated with reduced neuronal integrity (-.414, -.422, -.433, p's<.05), although no biomarker predicted total cognition in the clinical groups. FFor NP-aff, elevated myelin/membrane concentrations accompanied cognitive deficits; significantly so for visual learning deficits (.446, p<.05), which were also associated with decreased glia (-.503, p<.05). Opposite NP-aff, reduced myelin/membrane concentrations predicted cognitive deficits in Psy (-.514, p<.05). Separating schizophrenia from aff-P on social cognition showed reduced glutamate/excitation in schizophrenia (-.673, p<.05) ibut higher myelin/membrane turnover and neuronal integrity concentrations in aff-P (.575, .581, p's<.05). Conclusions: Schizophrenia and affective psychosis significantly differed for biomarkers of cellular pathology related to social cognition. Distinctly different underpinnings for cognition were also identified for other groups, aligning with DSM-5 and ICD disorder based categories. These findings include support for heterogeneous, but not transdiagnostic, conceptualizations of cognition and psychosis.

pathology↗

bioRxiv2026

Do Symptom Domains Have Similar Cellular Underpinnings Across Psychiatric Diagnoses: Evidence from 3D Hippocampal MR Spectroscopy

Introduction: The NIMH Research Domain Criteria (RDoC) posits similar cellular pathologies for particular symptom domains across diagnostic categories. Conversely, knowledge that these differ could advance treatment discovery, especially for affective and non-affective psychoses, as studies usually intermix them. Methods: We tested this by comparing metabolite biomarker concentrations for cellular pathologies from whole hippocampal proton magnetic spectroscopic imaging (1H MRSI) with symptoms from the original and five factor PANSS, and the Hamilton Depression and Young Mania Scales. Participants were 26 healthy controls; 22 non-psychotic affective cases (NP-aff); and 33 with psychosis (including 20 schizophrenia (Scz) and 13 affective psychosis (aff-P) cases). Results: PANSS activation factor was related to reductions in all cellular component biomarkers in Scz, including glia, membrane turnover, neural integrity, glutaminergic neurotransmission, and energy metabolism (p's<.05), but only to energy metabolism in NP-aff (p=.03). Biomarkers for mood symptoms also varied across categories, suggesting gliosis for mania and depression in HC (p's[≤].025), but increased membrane turnover for mania in aff-P (p=.015), and decreased neural integrity and energy metabolism for depression in Scz (p's<.05). In contrast, negative symptoms and autistic preoccupation were related to reduced glia in both NP-aff and aff-P (p's<.05). Autistic preoccupation in Scz was related to both reduced glia and membrane turnover (p's<.05). Only Scz showed a significant finding for positive symptoms, specifically reduced membrane turnover (p=.018). Discussion: These results suggest both distinct and similar cellular pathologies for symptoms across diagnoses, including affective and non-affective psychoses. The differences support categorizing disorders and stratifying different psychoses in research rather than transdiagnostic approaches.

pathology↗

bioRxiv2025

A Low-dimensional Manifold Representation of the Human Brain Aging Continuum

Brain aging involves complex structural changes that challenge traditional analytical methods and hinder personalized assessment of brain health. Integrating regional brain alterations into a unified, interpretable representation is difficult due to the high dimensionality of neuroimaging data. Here, we projected regional brain volumes from the Human Connectome Project Aging Dataset onto a low-dimensional manifold that reflects underlying neuroanatomical constraints. We then built a transparent framework on the manifold to estimate brain age and identify key regional drivers of the estimate. By analyzing local neighborhoods on the manifold, we identified distinct structural aging trajectories, including pronounced frontal atrophy occurring predominantly in males. This approach provides a biologically interpretable means of characterizing individual brain-aging patterns, reveals heterogeneous aging pathways, and supports more personalized assessments and insights into the aging process. TeaserA manifold representation can map brain aging patterns across regions and reveal distinct trajectories

bioengineering↗