Biology subjects

Sah, S.

Publications and source records attributed to Sah, S..

4 recordsLinked to original sources

bioRxiv2024

Cortical synaptic vulnerabilities revealed in a α-synuclein aggregation model of Parkinson's disease

-Synuclein aggregates characterize -synucleinopathies, including Parkinsons disease and Dementia with Lewy bodies. A majority of people with these disorders experience cognitive decline, and its extent correlates with cortical -synuclein pathology. Mechanisms by which pathology targets cortical circuits remain to be understood so that the debilitating non-motor impairments can be addressed. Overt neuronal loss is not a major feature of cortical pathology, but a reduction of presynaptic sites has been reported at late stages of PD. We here define excitatory synapses as neuronal loci affected by -synuclein aggregation, showing that they are progressively lost, and identify temporal and spatial patterns of synaptic vulnerability. Results were obtained in a mouse model using intrastriatal injection of pre-formed -synuclein fibrils to template the aggregation of endogenous -synuclein in cortical neurons. Lewy neurite-like aggregates were predominantly observed in axons. Super-resolved imaging showed -synuclein aggregation within cortical synapses and revealed that synaptic aggregation is most severe proximal to Lewy neurite-like structures and linked to the earliest detectable loss of excitatory synapses. Excitatory synapses also exhibited ultrastructural aberrations, including a redistribution of pre- and post-synaptic protein clusters away from contact sites and reduced synaptic vesicle size. As pathology advanced, VGLUT1-positive intracortical synapses, enriched in -synuclein, were progressively vulnerable in this striatal seeding model, while VGLUT2-positive long-range synapses with minimal -synuclein were spared. Inhibitory synapses were not affected. In agreement with a disruptive role of synaptic -synuclein aggregation, super-resolved mesoscale imaging determined that synaptic but not non-synaptic -synuclein pathology is correlated with excitatory synapse loss. Physiological recordings confirmed impaired excitatory neurotransmission. Pathology propagation tracked cortical connectivity, with intra-column synapse loss correlated between interconnected layers V and II/III. Contralateral areas receiving projections from pathologic layer V also exhibited synapse loss. These findings reveal synapses as principal cellular loci of -synuclein pathology and define how molecular and circuit-based mechanisms underlie the cortical progression of synaptic pathology in -synucleinopathies.

neuroscience↗

bioRxiv2023

Serum Lipidome Profiling Reveals a Distinct Signature of Ovarian Cancer in Korean Women

Distinguishing ovarian cancer (OC) from other gynecological malignancies remains a critical unmet medical need with significant implications for patient survival. However, non-specific symptoms along with our lack of understanding of OC pathogenesis hinder its diagnosis, preventing many women from receiving appropriate medical assistance. Accumulating evidence suggests a link between OC and deregulated lipid metabolism. Most studies, however, are limited by small sample size, particularly for early-stage cases. Furthermore, racial/ethnic differences in OC survival and incidence have been reported, yet most of the studies consist largely of non-Hispanic white women or women with European ancestry. Studies of more diverse racial/ethnic populations are needed to make OC diagnosis and prevention more inclusive. Here, we profiled the serum lipidome of 208 OC, including 93 patients with early-stage OC, and 117 non-OC (other gynecological malignancies) patients of Korean descent. Serum samples were analyzed with a high-coverage liquid chromatography high-resolution mass spectrometry platform, and lipidome alterations were investigated via statistical and machine learning approaches. Results show that lipidome alterations unique to OC were present in Korean women as early as when the cancer is localized, and those changes increase in magnitude as the diseases progresses. Analysis of relative lipid abundances revealed specific patterns for various lipid classes, with most classes showing decreased abundance in OC in comparison to other gynecological diseases. Machine learning methods selected a panel of 17 lipids that discriminated OC from non-OC cases with an AUC of 0.85 for an independent test set. This study provides a systemic analysis of lipidome alterations in human OC, specifically in Korean women, emphasizing the potential of circulating lipids in distinguishing OC from non-OC conditions.

cancer biology↗

bioRxiv2023

Machine Learning Reveals Lipidome Remodeling Dynamics in a Mouse Model of Ovarian Cancer

Ovarian cancer (OC) is one of the deadliest cancers affecting the female reproductive system. It may present little or no symptoms at the early stages, and typically unspecific symptoms at later stages. High-grade serous ovarian cancer (HGSC) is the subtype responsible for most ovarian cancer deaths. However, very little is known about the metabolic course of this disease, particularly in its early stages. In this longitudinal study, we examined the temporal course of serum lipidome changes using a robust HGSC mouse model and machine learning data analysis. Early progression of HGSC was marked by increased levels of phosphatidylcholines and phosphatidylethanolamines. In contrast, later stages featured more diverse lipids alterations, including fatty acids and their derivatives, triglycerides, ceramides, hexosylceramides, sphingomyelins, lysophosphatidylcholines, and phosphatidylinositols. These alterations underscored unique perturbations in cell membrane stability, proliferation, and survival during cancer development and progression, offering potential targets for early detection and prognosis of human ovarian cancer. TeaserTime-resolved lipidome remodeling in an ovarian cancer model is studied through lipidomics and machine learning.

cancer biology↗

bioRxiv2022

Neuronal growth regulator 1 (NEGR1) promotes synaptic targeting of glutamic acid decarboxylase 65 (GAD65)

Neuronal growth regulator 1 (NEGR1) is a glycosylphosphatidylinositol-anchored cell adhesion molecule encoded by an obesity susceptibility gene. We demonstrate that NEGR1 accumulates in GABAergic inhibitory synapses in hypothalamic neurons, a GABA-synthesizing enzyme GAD65 attaches to the plasma membrane, and NEGR1 promotes clustering of GAD65 at the synaptic plasma membrane. GAD65 is removed from the plasma membrane with newly formed vesicles. The association of GAD65 with vesicles results in increased GABA synthesis. In NEGR1 deficient mice, the synaptic targeting of GAD65 is decreased, the GABAergic synapse densities are reduced, and the reinforcing effects of food rewards are blunted. In mice fed a high fat diet, levels of NEGR1 are increased and GAD65 abnormally accumulates at the synaptic plasma membrane. Our results indicate that NEGR1 regulates a previously unknown step required for synaptic targeting and functioning of GAD65, which can be affected by bidirectional changes in NEGR1 levels causing disruptions in the GABAergic signaling controlling feeding behavior.

neuroscience↗