Biology subjects

Lah, J.

Publications and source records attributed to Lah, J..

4 recordsLinked to original sources

bioRxiv2025

Multimodal Fusion Analysis of Florbetapir PET and Multiscale Functional Network Connectivity in Alzheimer's Disease

Accumulation of amyloid-beta plaques and disruption of intrinsic brain networks are two important characteristics of Alzheimers disease (AD), yet the relationship between amyloid accumulation and network dysfunction remains unclear. In this study, we integrated [18F]Florbetapir PET and resting-state fMRI (rsfMRI) derived Functional Network Connectivity (FNC) from 552 temporally matched longitudinal PET-rsfMRI sessions across 395 participants spanning Cognitively Normal (CN), Mild Cognitive Impairment (MCI), and AD stages. With a model order of 11, joint Independent Component Analysis (jICA) was applied to the fused PET-FNC data, identifying 11 stable components, of which 9 PET-derived components corresponded to previously characterized brain regions or networks. The multimodal analysis revealed disease progression markers, including (1) a pattern of reduced subject loadings across clinical stages (CN > MCI > AD) in white matter and cerebellar regions, reflecting structural degeneration; (2) increased amyloid accumulation in affected individuals in grey matter regions, particularly in frontal, sensorimotor, extended hippocampal, and default mode network (DMN) regions, accompanied by functional connectivity alterations that reflected both compensatory and disruptive network dynamics. We identified PET-derived components that captured distinct stages of disease progression, with the DMN component emerging as a late-stage biomarker and a white matter component showing early-stage changes with limited progression thereafter. Additionally, several components showed significant variation in loadings between APOE{varepsilon} 4 carriers and non-carriers, linking the multimodal signatures to a well-established genetic risk factor for AD.

neuroscience↗

bioRxiv2023

Analysis of the peptide helicity using ensemble spectroscopic model with re-calibrated parameters

The -helix is the fundamental building block of protein structure. Understanding the physical principles that determine how a specific amino acid sequence defines helicity is a key step towards elucidating the sequence-structure relationship. An established method for quantitation of helix content using circular dichroism (CD) relies on the linear spectroscopic model. In this model, the helix length-correction is not applied to each ensemble conformer individually, rather an average value is assumed for all conformers. Here we assess the validity of this approximation and introduce a more physically realistic ensemble-based analysis of the CD signal. We find that the linear model tends to underestimate peptide helicity, with the difference depending on the ensemble composition. Using a CD dataset covering a broad range of helicities, we re-calibrate spectroscopic parameters (helix and coil baselines) and determine helix-coil parameters for a set of alanine-rich peptides. Our results show that the ensemble model can leverage the small spectroscopic differences between peptide conformers, enabling it to extract more information from the experimental data. We show that some previously poorly-defined quantities, such as helix nucleation constant and heat capacity change associated with helix folding, can be reliably determined using ensemble model. Overall, the presented ensemble-based treatment of the CD signal, together with the re-calibrated values of the spectroscopic baseline parameters, provides a coherent framework for the analysis of the peptide helix content. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=50 SRC="FIGDIR/small/563921v1_ufig1.gif" ALT="Figure 1"> View larger version (7K): org.highwire.dtl.DTLVardef@e10dc8org.highwire.dtl.DTLVardef@14fe8ccorg.highwire.dtl.DTLVardef@13cb2fborg.highwire.dtl.DTLVardef@aafa3_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2021

MLKL D144K mutation activates the necroptotic activity of the N-terminal MLKL domain

Mixed-lineage kinase domain-like protein (MLKL) is an essential effector protein of necroptotic cell death. The four-helix bundle domain (4HB) presented by the first 125 amino acids of the N-terminal domain is sufficient for its necroptotic activity. However, it has been proposed that the subsequent helix H6 of the brace region has a regulatory effect on its necroptotic activity. How the brace region restrains the necroptotic activity of the N-terminal domain of MLKL is currently unknown. Here, we demonstrate the importance of helix H6 to constrain the necroptotic activity. A single amino acid mutation D144K was able to activate the necroptotic activity of the N-terminal domain of MLKL by removing helix H6 away from 4HB domain. This enabled proteins oligomerization and membrane translocation. Moreover, a biophysical comparison revealed that helix H6 becomes partially unstructured due to D144K mutation, leading to a lower overall thermodynamic stability of the mutant protein compared to the wild type.

biochemistry↗

bioRxiv2019

Brain microRNAs associated with late-life depressive symptoms are also associated with cognitive trajectory and dementia

ObjectiveLate-life depression is associated with an increased risk for dementia, but our knowledge of the molecular mechanisms underlying this association is limited. Hence, the authors investigated whether microRNAs, important post-transcriptional regulators of gene expression, contribute to this association.\n\nMethodLate-life depressive symptoms were assessed annually in 300 non-demented participants of the Religious Orders Study and Rush Memory and Aging Project for a mean of seven years using the Center for Epidemiological Studies Depression scale. Participants underwent annual cognitive testing, clinical assessment of cognitive status, and uniform neuropathologic examination after death. microRNAs were profiled from the prefrontal cortex using Nanostring platform. A global microRNA association study of late-life depressive symptoms was performed using linear mixed model adjusting for sex, age, Alzheimers dementia pathological burden, proportions of brain cell types, post-mortem interval, and RNA integrity.\n\nResultsFour brain microRNAs were associated with late-life depressive symptoms at adjusted p<0.05 (miR-484, miR-26b, miR-30d, and miR-197). Lower expressions of these miRNAs were associated with greater depressive symptoms. Furthermore, lower expressions of miR-484 and miR-197 were associated with faster decline of cognitive performance over time. Additionally, lower miR-484 level was associated with higher probability of having Alzheimers dementia. Lastly, the predicted targets of miR-484 were enriched in a brain protein co-expression module involving synaptic transmission and regulation of long-term neuronal synaptic plasticity.\n\nConclusionsThis is the first study to identify brain microRNAs associated with late-life depressive symptoms assessed longitudinally. Additionally, the authors found a link between late-life depressive symptoms and dementia through miR-484 and miR-197.

genomics↗