Ancestry-specific high-risk gene variant profiling unmasks diabetes-associated genes.

How ancestry-associated genetic variance affects disparities in the risk for polygenic diseases and influences the identification of disease-associated genes warrant a deeper understanding. We hypothesized that the discovery of genes associated with polygenic diseases may be limited by overreliance on single-nucleotide polymorphism (SNP)-based genomic investigation, since most significant variants identified in genome-wide SNP association studies map to introns and intergenic regions of the genome. To overcome such potential limitation, we developed a gene-constrained and function-based analytical method centered on high-risk variants (hrV) that encode frameshifts, stopgains, or splice site disruption. We analyzed the total number of hrV per gene in populations of different ancestry, representing a total of 185 934 subjects. Using this analysis, we developed a quantitative index of hrV (hrVI) across 20 428 genes within each population. We then applied hrVI analysis to the discovery of genes associated with type 2 diabetes mellitus (T2DM), a polygenic disease with ancestry-related disparity. HrVI profiling and gene-to-gene comparisons of ancestry-specific hrV between the case (20 781 subjects) and control (24 440 subjects) populations in the T2DM national repository identified 57 genes associated with T2DM, 40 of which were discoverable only by ancestry-specific analysis. These results illustrate how function-based and ancestry-specific analysis of genetic variations can accelerate the identification of genes associated with polygenic diseases. Besides T2DM, such analysis may facilitate our understanding of the genetic basis for other polygenic diseases that are also greatly influenced by environmental and behavioral factors, such as obesity, hypertension, and Alzheimer's disease.

Examining the Aftermath of Virtual Interviewing on Surgical Residency Matches.

INTRODUCTION: Residency interviews have traditionally been conducted in person; however, COVID-19 forced programs to shift to virtual interviewing. This study delineated the nationwide trends observed after virtual interviewing across multiple application cycles on both surgical residency applicant competitiveness and program workload. METHODS: Publicly available National Residency Matching Program applicant and program data were retrospectively reviewed. Applicant competitiveness was assessed using a validated competitive index (# positions ranked/match rate). Interview types included in-person (2010-2020) or virtual (2021-2023), and programs were classified as general surgery (GS), surgical subspecialty (SS) - orthopedics, otolaryngology and neurosurgery, and integrated specialty (IS) - plastic, thoracic, and vascular surgery. RESULTS: When comparing in-person to virtual cohorts, the competitive index has increased in GS (0.97 ± 0.00 to 1.05 ± 0.01, P < 0.001), SS (0.97 ± 0.02 to 1.06 ± 0.01 P < 0.001), and IS (0.93 ± 0.06 to 1.12 ± 0.03, P = 0.001). United Sates Medical Licensing Examination Step scores and research experiences increased over time in GS and SS (P < 0.05). Program workload, represented by number of applications received per program increased in GS, IS, and SS (P < 0.05), as well as the number of interviews conducted in GS and SS (P < 0.05). Importantly, match rate remained stable in GS and IS, with a decrease in SS (0.69 ± 0.03 to 0.63 ± 0.02, P = 0.04). CONCLUSIONS: The residency application process has been irrevocably changed due to COVID-19. The rise in applicant volume and competitiveness places unique strains on applicants and programs. Additional modifications such as signaling and ACGME guidance are needed to help alleviate strain and ensure that residents and programs alike find their best fit.

Single-Molecule Sizing through Nanocavity Confinement.

An approach relying on nanocavity confinement is developed in this paper for the sizing of nanoscale particles and single biomolecules in solution. The approach, termed nanocavity diffusional sizing (NDS), measures particle residence times within nanofluidic cavities to determine their hydrodynamic radii. Using theoretical modeling and simulations, we show that the residence time of particles within nanocavities above a critical time scale depends on the diffusion coefficient of the particle, which allows the estimation of the particle's size. We demonstrate this approach experimentally through the measurement of particle residence times within nanofluidic cavities using single-molecule confocal microscopy. Our data show that the residence times scale linearly with the sizes of nanoscale colloids, protein aggregates, and single DNA oligonucleotides. NDS thus constitutes a new single molecule optofluidic approach that allows rapid and quantitative sizing of nanoscale particles for potential applications in nanobiotechnology, biophysics, and clinical diagnostics.

N-Terminal Acetylation of α-Synuclein Slows down Its Aggregation Process and Alters the Morphology of the Resulting Aggregates.

Parkinson's disease is associated with the aberrant aggregation of α-synuclein. Although the causes of this process are still unclear, post-translational modifications of α-synuclein are likely to play a modulatory role. Since α-synuclein is constitutively N-terminally acetylated, we investigated how this post-translational modification alters the aggregation behavior of this protein. By applying a three-pronged aggregation kinetics approach, we observed that N-terminal acetylation results in a reduced rate of lipid-induced aggregation and slows down both elongation and fibril-catalyzed aggregate proliferation. An analysis of the amyloid fibrils produced by the aggregation process revealed different morphologies for the acetylated and non-acetylated forms in both lipid-induced aggregation and seed-induced aggregation assays. In addition, we found that fibrils formed by acetylated α-synuclein exhibit a lower ß-sheet content. These findings indicate that N-terminal acetylation of α-synuclein alters its lipid-dependent aggregation behavior, reduces its rate of in vitro aggregation, and affects the structural properties of its fibrillar aggregates.

The Pathological G51D Mutation in Alpha-Synuclein Oligomers Confers Distinct Structural Attributes and Cellular Toxicity.

A wide variety of oligomeric structures are formed during the aggregation of proteins associated with neurodegenerative diseases. Such soluble oligomers are believed to be key toxic species in the related disorders; therefore, identification of the structural determinants of toxicity is of upmost importance. Here, we analysed toxic oligomers of α-synuclein and its pathological variants in order to identify structural features that could be related to toxicity and found a novel structural polymorphism within G51D oligomers. These G51D oligomers can adopt a variety of ß-sheet-rich structures with differing degrees of α-helical content, and the helical structural content of these oligomers correlates with the level of induced cellular dysfunction in SH-SY5Y cells. This structure-function relationship observed in α-synuclein oligomers thus presents the α-helical structure as another potential structural determinant that may be linked with cellular toxicity in amyloid-related proteins.

Rapid Structural, Kinetic, and Immunochemical Analysis of Alpha-Synuclein Oligomers in Solution.

Oligomers comprised of misfolded proteins are implicated as neurotoxins in the pathogenesis of protein misfolding conditions such as Parkinson's and Alzheimer's diseases. Structural, biophysical, and biochemical characterization of these nanoscale protein assemblies is key to understanding their pathology and the design of therapeutic interventions, yet it is challenging due to their heterogeneous, transient nature and low relative abundance in complex mixtures. Here, we demonstrate separation of heterogeneous populations of oligomeric α-synuclein, a protein central to the pathology of Parkinson's disease, in solution using microfluidic free-flow electrophoresis. We characterize nanoscale structural heterogeneity of transient oligomers on a time scale of seconds, at least 2 orders of magnitude faster than conventional techniques. Furthermore, we utilize our platform to analyze oligomer ζ-potential and probe the immunochemistry of wild-type α-synuclein oligomers. Our findings contribute to an improved characterization of α-synuclein oligomers and demonstrate the application of microchip electrophoresis for the free-solution analysis of biological nanoparticle analytes.

siRNA screen identifies QPCT as a druggable target for Huntington's disease.

Huntington's disease (HD) is a currently incurable neurodegenerative condition caused by an abnormally expanded polyglutamine tract in huntingtin (HTT). We identified new modifiers of mutant HTT toxicity by performing a large-scale 'druggable genome' siRNA screen in human cultured cells, followed by hit validation in Drosophila. We focused on glutaminyl cyclase (QPCT), which had one of the strongest effects on mutant HTT-induced toxicity and aggregation in the cell-based siRNA screen and also rescued these phenotypes in Drosophila. We found that QPCT inhibition induced the levels of the molecular chaperone αB-crystallin and reduced the aggregation of diverse proteins. We generated new QPCT inhibitors using in silico methods followed by in vitro screening, which rescued the HD-related phenotypes in cell, Drosophila and zebrafish HD models. Our data reveal a new HD druggable target affecting mutant HTT aggregation and provide proof of principle for a discovery pipeline from druggable genome screen to drug development.

Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review.

BACKGROUND: Health literacy (HL) is the ability to make informed decisions using health information. As health data and information availability increase due to online clinic notes and patient portals, it is important to understand how HL relates to social determinants of health (SDoH) and the place of informatics in mitigating disparities. OBJECTIVE: This systematic literature review aims to examine the role of HL in interactions with SDoH and to identify feasible HL-based interventions that address low patient understanding of health information to improve clinic note-sharing efficacy. METHODS: The review examined 2 databases, Scopus and PubMed, for English-language articles relating to HL and SDoH. We conducted a quantitative analysis of study characteristics and qualitative synthesis to determine the roles of HL and interventions. RESULTS: The results (n=43) were analyzed quantitatively and qualitatively for study characteristics, the role of HL, and interventions. Most articles (n=23) noted that HL was a result of SDoH, but other articles noted that it could also be a mediator for SdoH (n=6) or a modifiable SdoH (n=14) itself. CONCLUSIONS: The multivariable nature of HL indicates that it could form the basis for many interventions to combat low patient understandability, including 4 interventions using informatics-based solutions. HL is a crucial, multidimensional skill in supporting patient understanding of health materials. Designing interventions aimed at improving HL or addressing poor HL in patients can help increase comprehension of health information, including the information contained in clinic notes shared with patients.

α-Synuclein Oligomers Displace Monomeric α-Synuclein from Lipid Membranes.

Parkinson's disease (PD) is an increasingly prevalent and currently incurable neurodegenerative disorder linked to the accumulation of α-synuclein (αS) protein aggregates in the nervous system. While αS binding to membranes in its monomeric state is correlated to its physiological role, αS oligomerization and subsequent aberrant interactions with lipid bilayers have emerged as key steps in PD-associated neurotoxicity. However, little is known of the mechanisms that govern the interactions of oligomeric αS (OαS) with lipid membranes and the factors that modulate such interactions. This is in large part due to experimental challenges underlying studies of OαS-membrane interactions due to their dynamic and transient nature. Here, we address this challenge by using a suite of microfluidics-based assays that enable in-solution quantification of OαS-membrane interactions. We find that OαS bind more strongly to highly curved, rather than flat, lipid membranes. By comparing the membrane-binding properties of OαS and monomeric αS (MαS), we further demonstrate that OαS bind to membranes with up to 150-fold higher affinity than their monomeric counterparts. Moreover, OαS compete with and displace bound MαS from the membrane surface, suggesting that disruption to the functional binding of MαS to membranes may provide an additional toxicity mechanism in PD. These findings present a binding mechanism of oligomers to model membranes, which can potentially be targeted to inhibit the progression of PD.

α-Synuclein oligomers form by secondary nucleation.

Oligomeric species arising during the aggregation of α-synuclein are implicated as a major source of toxicity in Parkinson's disease, and thus a major potential drug target. However, both their mechanism of formation and role in aggregation are largely unresolved. Here we show that, at physiological pH and in the absence of lipid membranes, α-synuclein aggregates form by secondary nucleation, rather than simple primary nucleation, and that this process is enhanced by agitation. Moreover, using a combination of single molecule and bulk level techniques, we identify secondary nucleation on the surfaces of existing fibrils, rather than formation directly from monomers, as the dominant source of oligomers. Our results highlight secondary nucleation as not only the key source of oligomers, but also the main mechanism of aggregate formation, and show that these processes take place under conditions which recapitulate the neutral pH and ionic strength of the cytosol.

Membrane to cortex attachment determines different mechanical phenotypes in LGR5+ and LGR5- colorectal cancer cells.

Colorectal cancer (CRC) tumors are composed of heterogeneous and plastic cell populations, including a pool of cancer stem cells that express LGR5. Whether these distinct cell populations display different mechanical properties, and how these properties might contribute to metastasis is poorly understood. Using CRC patient derived organoids (PDOs), we find that compared to LGR5- cells, LGR5+ cancer stem cells are stiffer, adhere better to the extracellular matrix (ECM), move slower both as single cells and clusters, display higher nuclear YAP, show a higher survival rate in response to mechanical confinement, and form larger transendothelial gaps. These differences are largely explained by the downregulation of the membrane to cortex attachment proteins Ezrin/Radixin/Moesin (ERMs) in the LGR5+ cells. By analyzing single cell RNA-sequencing (scRNA-seq) expression patterns from a patient cohort, we show that this downregulation is a robust signature of colorectal tumors. Our results show that LGR5- cells display a mechanically dynamic phenotype suitable for dissemination from the primary tumor whereas LGR5+ cells display a mechanically stable and resilient phenotype suitable for extravasation and metastatic growth.

GLP-1(28-36) improves ß-cell mass and glucose disposal in streptozotocin-induced diabetic mice and activates cAMP/PKA/ß-catenin signaling in ß-cells in vitro.

Recent studies have demonstrated that the COOH-terminal fragment of the incretin hormone glucagon-like peptide-1 (GLP-1), a nonapeptide GLP-1(28-36)amide, attenuates diabetes and hepatic steatosis in diet-induced obese mice. However, the effect of this nonapeptide in pancreatic ß-cells remains largely unknown. Here, we show that in a streptozotocin-induced mouse diabetes model, GLP-1(28-36)amide improved glucose disposal and increased pancreatic ß-cell mass and ß-cell proliferation. An in vitro investigation revealed that GLP-1(28-36)amide stimulates ß-catenin (ß-cat) Ser(675) phosphorylation in both the clonal INS-1 cell line and rat primary pancreatic islet cells. In INS-1 cells, the stimulation was accompanied by increased nuclear ß-cat content. GLP-1(28-36)amide was also shown to increase cellular cAMP levels, PKA enzymatic activity, and cAMP response element-binding protein (CREB) and cyclic AMP-dependent transcription factor-1 (ATF-1) phosphorylation. Furthermore, GLP-1(28-36)amide treatment enhanced islet insulin secretion and increased the growth of INS-1 cells, which was associated with increased cyclin D1 expression. Finally, PKA inhibition attenuated the effect of GLP-1(28-36)amide on ß-cat Ser(675) phosphorylation and cyclin D1 expression in the INS-1 cell line. We have thus revealed the beneficial effect of GLP-1(28-36)amide in pancreatic ß-cells in vitro and in vivo. Our observations suggest that GLP-1(28-36)amide may exert its effect through the PKA/ß-catenin signaling pathway.

Adopting a metaverse-based workspace to support research team collaboration: a pilot study from an academic health informatics laboratory.

Objective: This study aimed to understand how a metaverse-based (virtual) workspace can be used to support the communication and collaboration in an academic health informatics lab. Materials and Methods: A survey of lab members (n = 14) was analyzed according to a concurrent triangulation mixed methods design. The qualitative survey data were organized according to the Capability, Opportunity, Motivation, Behavior (COM-B) model and combined to generate personas that represent the overall types of lab members. Additionally, scheduled work hours were analyzed quantitatively to complement the findings of the survey feedback. Results: Four personas, representative of different types of virtual workers, were developed using the survey responses. These personas reflected the wide variety of opinions about virtual work among the participants and helped to categorize the most common feedback. The Work Hours Schedule Sheet analysis showed the low number of possible collaboration opportunities that were utilized compared to the number available. Discussion: We found that informal communication and co-location were not supported by the virtual workplace as we had originally planned. To solve this issue, we offer 3 design recommendations for those looking to implement their own virtual informatics lab. First, labs should establish common goals and norms for virtual workplace interactions. Second, labs should carefully plan the virtual space layout to maximize communication opportunities. Finally, labs should work with their platform of choice to address technical limitations for their lab members to improve user experience. Future work includes a formal, theory-guided experiment with consideration on ethical and behavioral impact.

Image-based cell sorting using focused travelling surface acoustic waves.

Sorting cells is an essential primary step in many biological and clinical applications such as high-throughput drug screening, cancer research and cell transplantation. Cell sorting based on their mechanical properties has long been considered as a promising label-free biomarker that could revolutionize the isolation of cells from heterogeneous populations. Recent advances in microfluidic image-based cell analysis combined with subsequent label-free sorting by on-chip actuators demonstrated the possibility of sorting cells based on their physical properties. However, the high purity of sorting is achieved at the expense of a sorting rate that lags behind the analysis throughput. Furthermore, stable and reliable system operation is an important feature in enabling the sorting of small cell fractions from a concentrated heterogeneous population. Here, we present a label-free cell sorting method, based on the use of focused travelling surface acoustic wave (FTSAW) in combination with real-time deformability cytometry (RT-DC). We demonstrate the flexibility and applicability of the method by sorting distinct blood cell types, cell lines and particles based on different physical parameters. Finally, we present a new strategy to sort cells based on their mechanical properties. Our system enables the sorting of up to 400 particles per s. Sorting is therefore possible at high cell concentrations (up to 36 million per ml) while retaining high purity (>92%) for cells with diverse sizes and mechanical properties moving in a highly viscous buffer. Sorting of small cell fraction from a heterogeneous population prepared by processing of small sample volume (10 µl) is also possible and here demonstrated by the 667-fold enrichment of white blood cells (WBCs) from raw diluted whole blood in a continuous 10-hour sorting experiment. The real-time analysis of multiple parameters together with the high sensitivity and high-throughput of our method thus enables new biological and therapeutic applications in the future.

Using Health Forum Data to Assess User Needs for mHealth App Development: A Feasibility Study on Alzheimer's Disease.

Online health forums are used by patients and caregivers as community and information resources, especially for chronic disease management, and could help determine user needs for digital health app design. This study aims to assess the feasibility of using online forum posts on Alzheimer's disease to inform user needs in mobile health application design and whether this process can be automated through text clustering methods. A total of 413 posts were analyzed manually through thematic coding and yielded three themes and nine subthemes for patient and caregiver needs. The external evaluation showed fair to substantial similarity between the automatically and manually derived labels. Four personas were developed to assess the validity of forum-generated needs. These results establish that health forum data can provide sufficient information to understand user needs. However, further refinement of the analysis process and algorithm is necessary to generalize this method to other disease conditions and types of forum data.

Effects of N-terminal Acetylation on the Aggregation of Disease-related α-synuclein Variants.

Mutations in the SNCA gene, which encodes the protein α-synuclein, have been linked with early onset Parkinson's disease. The exact nature of this association, however, is still poorly understood. To investigate this problem, we started from the observation that α-synuclein is constitutively N-terminally acetylated, a post-translational modification that alters the charge and structure of α-synuclein molecules and affects their interaction with lipid membranes, as well as their aggregation process. We thus studied five N-terminal acetylated familial variants (A30P, E46K, H50Q, G51D and A53T) of α-synuclein through a wide range of biophysical assays to probe the microscopic steps in their aggregation process and the structures of the resulting aggregates. Our results reveal a great complexity in the combined effects of the disease-related mutations with N-terminal acetylation on the aggregation of α-synuclein, which underscores the great sensitivity to even relatively small perturbations of the behaviour of this protein.

Microfluidic antibody affinity profiling of alloantibody-HLA interactions in human serum.

Antibody profiling is a fundamental component of understanding the humoral response in a wide range of disease areas. Most currently used approaches operate by capturing antibodies onto functionalised surfaces. Such measurements of surface binding are governed by an overall antibody titre, while the two fundamental molecular parameters, antibody affinity and antibody concentration, are challenging to determine individually from such approaches. Here, by applying microfluidic diffusional sizing (MDS), we show how we can overcome this challenge and demonstrate reliable quantification of alloantibody binding affinity and concentration of alloantibodies binding to Human Leukocyte Antigens (HLA), an extensively used clinical biomarker in organ transplantation, both in buffer and in crude human serum. Capitalising on the ability to vary both serum and HLA concentrations during MDS, we show that both affinity and concentration of HLA-specific antibodies can be determined directly in serum when neither of these parameters is known. Finally, we provide proof of principle in clinical transplant patient sera that our assay enables differentiation of alloantibody reactivity against HLA proteins of highly similar structure, providing information not attainable through currently available techniques. These results outline a path towards detection and in-depth profiling of humoral immunity and may enable further insights into the clinical relevance of antibody reactivity in clinical transplantation and beyond.

Microfluidic antibody profiling after repeated SARS-CoV-2 vaccination links antibody affinity and concentration to impaired immunity and variant escape in patients on anti-CD20 therapy.

Background: Patients with autoimmune/inflammatory conditions on anti-CD20 therapies, such as rituximab, have suboptimal humoral responses to vaccination and are vulnerable to poorer clinical outcomes following SARS-CoV-2 infection. We aimed to examine how the fundamental parameters of antibody responses, namely, affinity and concentration, shape the quality of humoral immunity after vaccination in these patients. Methods: We performed in-depth antibody characterisation in sera collected 4 to 6 weeks after each of three vaccine doses to wild-type (WT) SARS-CoV-2 in rituximab-treated primary vasculitis patients (n = 14) using Luminex and pseudovirus neutralisation assays, whereas we used a novel microfluidic-based immunoassay to quantify polyclonal antibody affinity and concentration against both WT and Omicron (B.1.1.529) variants. We performed comparative antibody profiling at equivalent timepoints in healthy individuals after three antigenic exposures to WT SARS-CoV-2 (one infection and two vaccinations; n = 15) and in convalescent patients after WT SARS-CoV-2 infection (n = 30). Results: Rituximab-treated patients had lower antibody levels and neutralisation titres against both WT and Omicron SARS-CoV-2 variants compared to healthy individuals. Neutralisation capacity was weaker against Omicron versus WT both in rituximab-treated patients and in healthy individuals. In the rituximab cohort, this was driven by lower antibody affinity against Omicron versus WT [median (range) KD: 21.6 (9.7-38.8) nM vs. 4.6 (2.3-44.8) nM, p = 0.0004]. By contrast, healthy individuals with hybrid immunity produced a broader antibody response, a subset of which recognised Omicron with higher affinity than antibodies in rituximab-treated patients [median (range) KD: 1.05 (0.45-1.84) nM vs. 20.25 (13.2-38.8) nM, p = 0.0002], underpinning the stronger serum neutralisation capacity against Omicron in the former group. Rituximab-treated patients had similar anti-WT antibody levels and neutralisation titres to unvaccinated convalescent individuals, despite two more exposures to SARS-CoV-2 antigen. Temporal profiling of the antibody response showed evidence of affinity maturation in healthy convalescent patients after a single SARS-CoV-2 infection, which was not observed in rituximab-treated patients, despite repeated vaccination. Discussion: Our results enrich previous observations of impaired humoral immune responses to SARS-CoV-2 in rituximab-treated patients and highlight the significance of quantitative assessment of serum antibody affinity and concentration in monitoring anti-viral immunity, viral escape, and the evolution of the humoral response.

Continuous population-level monitoring of SARS-CoV-2 seroprevalence in a large European metropolitan region.

Effective public health measures against SARS-CoV-2 require granular knowledge of population-level immune responses. We developed a Tripartite Automated Blood Immunoassay (TRABI) to assess the IgG response against three SARS-CoV-2 proteins. We used TRABI for continuous seromonitoring of hospital patients and blood donors (n = 72'250) in the canton of Zurich from December 2019 to December 2020 (pre-vaccine period). We found that antibodies waned with a half-life of 75 days, whereas the cumulative incidence rose from 2.3% in June 2020 to 12.2% in mid-December 2020. A follow-up health survey indicated that about 10% of patients infected with wildtype SARS-CoV-2 sustained some symptoms at least twelve months post COVID-19. Crucially, we found no evidence of a difference in long-term complications between those whose infection was symptomatic and those with asymptomatic acute infection. The cohort of asymptomatic SARS-CoV-2-infected subjects represents a resource for the study of chronic and possibly unexpected sequelae.

Uncovering the universality of self-replication in protein aggregation and its link to disease.

Fibrillar protein aggregates are a hallmark of a range of human disorders, from prion diseases to dementias, but are also encountered in several functional contexts. Yet, the fundamental links between protein assembly mechanisms and their functional or pathological roles have remained elusive. Here, we analyze the aggregation kinetics of a large set of proteins that self-assemble by a nucleated-growth mechanism, from those associated with disease, over those whose aggregates fulfill functional roles in biology, to those that aggregate only under artificial conditions. We find that, essentially, all such systems, regardless of their biological role, are capable of self-replication. However, for aggregates that have evolved to fulfill a structural role, the rate of self-replication is too low to be significant on the biologically relevant time scale. By contrast, all disease-related proteins are able to self-replicate quickly compared to the time scale of the associated disease. Our findings establish the ubiquity of self-replication and point to its potential importance across aggregation-related disorders.