A guide to establishing, implementing, and optimizing diversity, equity, inclusion, and accessibility (DEIA) committees.

Diversity, equity, inclusion, and accessibility (DEIA) efforts are increasingly recognized as critical for the success of academic institutions. These efforts are facilitated mainly through the formation of dedicated DEIA committees. DEIA committees enhance professional development and create a more inclusive environment, which benefits all members of the institution. Although leadership and faculty membership have recognized the importance and necessity of DEIA, the roles of DEIA committees may be more ambiguous. Although leadership and faculty may seek to support DEIA at their institutions, they may not always fully understand the necessity of these committees or how to successfully create a committee, foster and promote its success, and sustain its impact. Thus, here, we offer a background rationale and guide for strategically setting up DEIA committees for success and impact within an academic institution with applicability to scientific societies.

Solvent Composition Can Have a Measurable Influence on the Ion Mobility-Derived Collision Cross Section of Small Molecules.

Ion mobility (IM) is an important analytical technique for increasing identification coverage of metabolites in untargeted studies, especially when integrated into traditional liquid chromatography-mass spectrometry workflows. While there has been extensive work surrounding best practices to obtain and standardize collision cross section (CCS) measurements necessary for comparing across different IM techniques and laboratories, there has been little investigation into experimental factors beyond the mobility separation region that could potentially influence CCS measurements. The first-principles derived CCS of 15 chemical standards were evaluated across 27 aqueous:organic solvent compositions using a high-precision drift tube instrument. A small but measurable dependency of the CCS on the solvent composition was observed, with the larger analytes from this study (m/z > 400) exhibiting a characteristic increase in CCS at the intermediate (40-60%) solvent compositions. Parallels to the behavior of solvent viscosity and protonation site tautomers (protomers) were noted, although the origin of these solvent-dependent CCS trends is as yet unclear. Taken together, these findings document a solvent dependency on CCS, which, while minor (<0.5%), identifies an important need for reporting the solvent system when utilizing CCS in comparative ion mobility studies.

PATHWAYS ASSOCIATED WITH POSITIVE SEPSIS SURVIVAL OUTCOMES IN AFRICAN AMERICAN/BLACK AND NON-HISPANIC WHITE PATIENTS WITH URINARY TRACT INFECTION.

ABSTRACT: Urinary tract infections (UTIs) are a common cause of sepsis worldwide. Annually, more than 60,000 US deaths can be attributed to sepsis secondary to UTIs, and African American/Black adults have higher incidence and case-fatality rates than non-Hispanic White adults. Molecular-level factors that may help partially explain differences in sepsis survival outcomes between African American/Black and Non-Hispanic White adults are not clear. In this study, patient samples (N = 166) from the Protocolized Care for Early Septic Shock cohort were analyzed using discovery-based plasma proteomics. Patients had sepsis secondary to UTIs and were stratified according to self-identified racial background and sepsis survival outcomes. Proteomics results suggest patient heterogeneity across mechanisms driving survival from sepsis secondary to UTIs. Differentially expressed proteins (n = 122, false discovery rate-adjusted P < 0.05) in Non-Hispanic White sepsis survivors were primarily in immune system pathways, while differentially expressed proteins (n = 47, false discovery rate-adjusted P < 0.05) in African American/Black patients were mostly in metabolic pathways. However, in all patients, regardless of racial background, there were 16 differentially expressed proteins in sepsis survivors involved in translation initiation and shutdown pathways. These pathways are potential targets for prognostic intervention. Overall, this study provides information about molecular factors that may help explain disparities in sepsis survival outcomes among African American/Black and Non-Hispanic White patients with primary UTIs.

Juneteenth in STEMM and the barriers to equitable science.

We are 52 Black scientists. Here, we establish the context of Juneteenth in STEMM and discuss the barriers Black scientists face, the struggles they endure, and the lack of recognition they receive. We review racism's history in science and provide institutional-level solutions to reduce the burdens on Black scientists.

Establishing Quality Control Procedures for Large-Scale Plasma Proteomics Analyses.

Proteomics research has been transformed due to high-throughput liquid chromatography (LC-MS/MS) tandem mass spectrometry instruments combined with highly sophisticated automated sample preparation and multiplexing workflows. However, scaling proteomics experiments to large sample cohorts (hundreds to thousands) requires thoughtful quality control (QC) protocols. Robust QC protocols can help with reproducibility, quantitative accuracy, and provide opportunities for more decisive troubleshooting. Our laboratory conducted a plasma proteomics study of a cohort of N = 335 patient samples using tandem mass tag (TMTpro) 16-plex batches. Over the course of a 10-month data acquisition period for this cohort we collected 271 pooled QC LC-MS/MS result files obtained from MS/MS analysis of a patient-derived pooled plasma sample, representative of the entire cohort population. This sample was tagged with TMTzero or TMTpro reagents and used to inform the daily performance of the LC-MS/MS instruments and to allow within and across sample batch normalization. Analytical variability of a number of instrumental and data analysis metrics including protein and peptide identifications, peptide spectral matches (PSMs), number of obtained MS/MS spectra, average peptide abundance, percent of peptides with a Δ m/z between ±0.003 Da, percent of MS/MS spectra obtained at the maximum injection time, and the retention time of selected tracking peptides were evaluated to help inform the design of a robust LC-MS/MS QC workflow for use in future cohort studies. This study also led to general tips for using selected metrics to inform real-time troubleshooting of LC-MS/MS performance issues with daily QC checks.

Multi-omic characterization of brain changes in the vascular endothelial growth factor family during aging and Alzheimer's disease.

The vascular endothelial growth factor (VEGF) signaling family has been implicated in neuroprotection and clinical progression in Alzheimer's disease (AD). Previous work in postmortem human dorsolateral prefrontal cortex demonstrated that higher transcript levels of VEGFB, PGF, FLT1, and FLT4 are associated with AD dementia, worse cognitive outcomes, and higher AD neuropathology. To expand prior work, we leveraged bulk RNA sequencing data, single nucleus RNA (snRNA) sequencing, and both tandem mass tag and selected reaction monitoring mass spectrometry proteomic measures from the post-mortem brain. Outcomes included AD diagnosis, cognition, and AD neuropathology. We replicated previously reported VEGFB and FLT1 results, whereby higher expression was associated with worse outcomes, and snRNA results suggest microglia, oligodendrocytes, and endothelia may play a central role in these associations. Additionally, FLT4 and NRP2 expression were associated with better cognitive outcomes. This study provides a comprehensive molecular picture of the VEGF signaling family in cognitive aging and AD and critical insight towards the biomarker and therapeutic potential of VEGF family members in AD.

Enhanced Multiplexing Technology for Proteomics.

The identification of thousands of proteins and their relative levels of expression has furthered understanding of biological processes and disease and stimulated new systems biology hypotheses. Quantitative proteomics workflows that rely on analytical assays such as mass spectrometry have facilitated high-throughput measurements of proteins partially due to multiplexing. Multiplexing allows proteome differences across multiple samples to be measured simultaneously, resulting in more accurate quantitation, increased statistical robustness, reduced analysis times, and lower experimental costs. The number of samples that can be multiplexed has evolved from as few as two to more than 50, with studies involving more than 10 samples being denoted as enhanced multiplexing or hyperplexing. In this review, we give an update on emerging multiplexing proteomics techniques and highlight advantages and limitations for enhanced multiplexing strategies.

Mechanisms by Which Cultural-Centric Narrative Influences Interest in ADRD Research Among African American Adults.

BACKGROUND AND OBJECTIVES: Insufficient ethnoracial diversity is a pervasive challenge in Alzheimer's disease (AD) research. The Recruitment Innovations for Diversity Enhancement (RIDE) is grounded in the premise that culturally informed narratives of research participation can inspire individuals from a given culture-sharing group to consider research enrollment. This study examines factors associated with interest in AD research among Black or African American adults following exposure to RIDE narrative campaign materials. RESEARCH DESIGN AND METHODS: A community-based sample of 500 Black or African American adults viewed RIDE narrative materials online and completed a survey of perceptions about research, AD risk, and likelihood of enrolling in AD research. Logistic regression examined predictors and mediators of self-reported likelihood of participating in AD research. RESULTS: Most (72%) participants reported interest in being contacted for AD research opportunities. After controlling for key variables, prior experience with clinical research and trust in medical researchers emerged as independent predictors of likelihood of enrolling in AD research. Perceived burden of AD research partially mediated the effects of prior research experience and trust on likelihood of enrollment. Perceived benefits of AD research also played a mediating role, accounting for over one third of the effect of trust on likelihood of enrollment. DISCUSSION AND IMPLICATIONS: This study advances the field's understanding of how narrative may function to enhance diversity in AD research. Findings suggest that participant narratives should address experiences regarding the burdens and potential benefits of AD research participation as these factors may influence decisions leading to subsequent research enrollment.

A Prospective Cohort Protocol for the Remnant Investigation in Sepsis Study.

BACKGROUND: Sepsis is a common and deadly syndrome, accounting for more than 11 million deaths annually. To mature a deeper understanding of the host and pathogen mechanisms contributing to poor outcomes in sepsis, and thereby possibly inform new therapeutic targets, sophisticated, and expensive biorepositories are typically required. We propose that remnant biospecimens are an alternative for mechanistic sepsis research, although the viability and scientific value of such remnants are unknown. METHODS AND RESULTS: The Remnant Biospecimen Investigation in Sepsis study is a prospective cohort study of 225 adults (age ≥ 18 yr) presenting to the emergency department with community sepsis, defined as sepsis-3 criteria within 6 hours of arrival. The primary objective was to determine the scientific value of a remnant biospecimen repository in sepsis linked to clinical phenotyping in the electronic health record. We will study candidate multiomic readouts of sepsis biology, governed by a conceptual model, and determine the precision, accuracy, integrity, and comparability of proteins, small molecules, lipids, and pathogen sequencing in remnant biospecimens compared with paired biospecimens obtained according to research protocols. Paired biospecimens will include plasma from sodium-heparin, EDTA, sodium fluoride, and citrate tubes. CONCLUSIONS: The study has received approval from the University of Pittsburgh Human Research Protection Office (Study 21120013). Recruitment began on October 25, 2022, with planned release of primary results anticipated in 2024. Results will be made available to the public, the funders, critical care societies, laboratory medicine scientists, and other researchers.

Proteomic changes associated with racial background and sepsis survival outcomes.

Intra-abdominal infection is a common cause of sepsis, and intra-abdominal sepsis leads to ∼156 000 U.S. deaths annually. African American/Black adults have higher incidence and mortality rates from sepsis compared to Non-Hispanic White adults. A limited number of studies have traced survival outcomes to molecular changes; however, these studies primarily only included Non-Hispanic White adults. Our goal is to better understand molecular changes that may contribute to differences in sepsis survival in African American/Black and Non-Hispanic White adults with primary intra-abdominal infection. We employed discovery-based plasma proteomics of patient samples from the Protocolized Care for Early Septic Shock (ProCESS) cohort (N = 107). We identified 49 proteins involved in the acute phase response and complement system whose expression levels are associated with both survival outcome and racial background. Additionally, 82 proteins differentially-expressed in survivors were specific to African American/Black or Non-Hispanic White patients, suggesting molecular-level heterogeneity in sepsis patients in key inflammatory pathways. A smaller, robust set of 19 proteins were in common in African American/Black and Non-Hispanic White survivors and may represent potential universal molecular changes in sepsis. Overall, this study identifies molecular factors that may contribute to differences in survival outcomes in African American/Black patients that are not fully explained by socioeconomic or other non-biological factors.

Advancements in automation for plasma proteomics sample preparation.

Automation is necessary to increase sample processing throughput for large-scale clinical analyses. Replacement of manual pipettes with robotic liquid handler systems is especially helpful in processing blood-based samples, such as plasma and serum. These samples are very heterogenous, and protein expression can vary greatly from sample-to-sample, even for healthy controls. Detection of true biological changes requires that variation from sample preparation steps and downstream analytical detection methods, such as mass spectrometry, remains low. In this mini-review, we discuss plasma proteomics protocols and the benefits of automation towards enabling detection of low abundant proteins and providing low sample error and increased sample throughput. This discussion includes considerations for automation of major sample depletion and/or enrichment strategies for plasma toward mass spectrometry detection.

Quantitative proteomics to study aging in rabbit spleen tissues.

Aging is a process that occurs in tissues and across species, leading to the degradation of many biological processes. We previously demonstrated that rabbits are a feasible model for studying aging due to their genetic homology and relatively short lifespan in comparison to humans. We utilized a cPILOT multiplexing strategy to identify proteomic changes in spleen tissues of young, middle, and old aged rabbits. We identified 63 proteins that change significantly (p < 0.05) with age and notably these proteins relate to nucleotide and RNA binding, DNA repair, actin regulation, and immune system pathways. Here, we explore the implications of aging in the spleen and demonstrate the utility of a rabbit model to understand aging processes.

Exposing the Brain Proteomic Signatures of Alzheimer's Disease in Diverse Racial Groups: Leveraging Multiple Data Sets and Machine Learning.

Recent studies have highlighted that the proteome can be used to identify potential biomarker candidates for Alzheimer's disease (AD) in diverse cohorts. Furthermore, the racial and ethnic background of participants is an important factor to consider to ensure the effectiveness of potential biomarkers for representative populations. A promising approach to survey potential biomarker candidates for diagnosing AD in diverse cohorts is the application of machine learning to proteomics data sets. Herein, we leveraged six existing bottom-up proteomics data sets, which included non-Hispanic White, African American/Black, and Hispanic participants, to study protein changes in AD and cognitively unimpaired participants. Machine learning models were applied to these data sets and resulted in the identification of amyloid-ß precursor protein (APP) and heat shock protein ß-1 (HSPB1) as two proteins that have high ability to distinguish AD; however, each protein's performance varied based upon the racial and ethnic background of the participants. HSPB1 particularly was helpful for generating high areas under the curve (AUCs) for African American/Black participants. Overall, HSPB1 improved the performance of the machine learning models when combined with APP and/or participant age and is a potential candidate that should be further explored in AD biomarker discovery efforts.

Benchmarking the proteomic profile of animal models of mesial temporal epilepsy.

OBJECTIVES: We compared the proteomic signatures of the hippocampal lesion induced in three different animal models of mesial temporal lobe epilepsy with hippocampal sclerosis (MTLE+HS): the systemic pilocarpine model (PILO), the intracerebroventricular kainic acid model (KA), and the perforant pathway stimulation model (PPS). METHODS: We used shotgun proteomics to analyze the proteomes and find enriched biological pathways of the dorsal and ventral dentate gyrus (DG) isolated from the hippocampi of the three animal models. We also compared the proteomes obtained in the animal models to that from the DG of patients with pharmacoresistant MTLE+HS. RESULTS: We found that each animal model presents specific profiles of proteomic changes. The PILO model showed responses predominantly related to neuronal excitatory imbalance. The KA model revealed alterations mainly in synaptic activity. The PPS model displayed abnormalities in metabolism and oxidative stress. We also identified common biological pathways enriched in all three models, such as inflammation and immune response, which were also observed in tissue from patients. However, none of the models could recapitulate the profile of molecular changes observed in tissue from patients. SIGNIFICANCE: Our results indicate that each model has its own set of biological responses leading to epilepsy. Thus, it seems that only using a combination of the three models may one replicate more closely the mechanisms underlying MTLE+HS as seen in patients.

Targeted Lipidomics To Measure Phospholipids and Sphingomyelins in Plasma: A Pilot Study To Understand the Impact of Race/Ethnicity in Alzheimer's Disease.

The number of people suffering from Alzheimer's disease (AD) is increasing rapidly every year. One aspect of AD that is often overlooked is the disproportionate incidence of AD among African American/Black populations. With the recent development of novel assays for lipidomics analysis in recent times, there has been a drastic increase in the number of studies focusing on changes of lipids in AD. However, very few of these studies have focused on or even included samples from African American/Black individuals samples. In this study, we aimed to determine if the lipidome in AD is universal across non-Hispanic White and African American/Black individuals. To accomplish this, a targeted mass spectrometry lipidomics analysis was performed on plasma samples (N = 113) obtained from cognitively normal (CN, N = 54) and AD (N = 59) individuals from African American/Black (N = 56) and non-Hispanic White (N = 57) backgrounds. Five lipids (PS 18:0_18:0, PS 18:0_20:0, PC 16:0_22:6, PC 18:0_22:6, and PS 18:1_22:6) were altered between AD and CN sample groups (p value < 0.05). Upon racial stratification, there were notable differences in lipids that were unique to African American/Black or non-Hispanic White individuals. PS 20:0_20:1 was reduced in AD in samples from non-Hispanic White but not African American/Black adults. We also tested whether race/ethnicity significantly modified the association between lipids and AD status by including a race × diagnosis interaction term in a linear regression model. PS 20:0_20:1 showed a significant interaction (p = 0.004). The discovery of lipid changes in AD in this study suggests that identifying relevant lipid biomarkers for diagnosis will require diversity in sample cohorts.

ABCA7, a Genetic Risk Factor Associated with Alzheimer's Disease Risk in African Americans.

African American/Black adults are twice as likely to have Alzheimer's disease (AD) compared to non-Hispanic White adults. Genetics partially contributes to this disparity in AD risk, among other factors, as there are several genetic variants associated with AD that are more prevalent in individuals of African or European ancestry. The phospholipid-transporting ATPase ABCA7 (ABCA7) gene has stronger associations with AD risk in individuals with African ancestry than in individuals with European ancestry. In fact, ABCA7 has been shown to have a stronger effect size than the apolipoprotein E (APOE) ɛ4 allele in African American/Black adults. ABCA7 is a transmembrane protein involved in lipid homeostasis and phagocytosis. ABCA7 dysfunction is associated with increased amyloid-beta production, reduced amyloid-beta clearance, impaired microglial response to inflammation, and endoplasmic reticulum stress. This review explores the impact of ABCA7 mutations that increase AD risk in African American/Black adults on ABCA7 structure and function and their contributions to AD pathogenesis. The combination of biochemical/biophysical and 'omics-based studies of these variants needed to elucidate their downstream impact and molecular contributions to AD pathogenesis is highlighted.

Dataset of why inclusion matters for Alzheimer's disease biomarker discovery in plasma.

Here we present a plasma proteomics dataset that was generated to understand the importance of self-reported race for biomarker discovery in Alzheimer's disease. This dataset is related to the article "Why inclusion matters for Alzheimer's disease biomarker discovery in plasma" [1]. Plasma samples were obtained from clinically diagnosed Alzheimer's disease and cognitively normal adults of African American/Black and non-Hispanic White racial and ethnic backgrounds. Plasma was immunodepleted, digested, and isobarically tagged with commercial reagents. Tagged peptides were fractionated using high pH fractionation and resulting fractions analysed by liquid chromatography - mass spectrometry (LC-MS/MS & MS3) analysis on an Orbitrap Fusion Lumos mass spectrometer. The resulting data was processed using Proteome Discoverer to produce a list of identified proteins with corresponding tandem mass tag (TMT) intensity information.

Why Inclusion Matters for Alzheimer's Disease Biomarker Discovery in Plasma.

BACKGROUND: African American/Black adults have a disproportionate incidence of Alzheimer's disease (AD) and are underrepresented in biomarker discovery efforts. OBJECTIVE: This study aimed to identify potential diagnostic biomarkers for AD using a combination of proteomics and machine learning approaches in a cohort that included African American/Black adults. METHODS: We conducted a discovery-based plasma proteomics study on plasma samples (N = 113) obtained from clinically diagnosed AD and cognitively normal adults that were self-reported African American/Black or non-Hispanic White. Sets of differentially-expressed proteins were then classified using a support vector machine (SVM) to identify biomarker candidates. RESULTS: In total, 740 proteins were identified of which, 25 differentially-expressed proteins in AD came from comparisons within a single racial and ethnic background group. Six proteins were differentially-expressed in AD regardless of racial and ethnic background. Supervised classification by SVM yielded an area under the curve (AUC) of 0.91 and accuracy of 86%for differentiating AD in samples from non-Hispanic White adults when trained with differentially-expressed proteins unique to that group. However, the same model yielded an AUC of 0.49 and accuracy of 47%for differentiating AD in samples from African American/Black adults. Other covariates such as age, APOE4 status, sex, and years of education were found to improve the model mostly in the samples from non-Hispanic White adults for classifying AD. CONCLUSION: These results demonstrate the importance of study designs in AD biomarker discovery, which must include diverse racial and ethnic groups such as African American/Black adults to develop effective biomarkers.

Automation of On-Resin Enrichment of S-Nitrosylated Proteins for Oxidized Cysteine-Selective cPILOT.

S-Nitrosylation (SNO) is a cysteine post-translational modification that increases with normal aging and is present in Alzheimer's disease and other aging-related illnesses. Detection of SNO-modified proteins can be challenging; however, we previously developed a robust quantitative proteomics approach termed "Oxidized Cysteine-Selective combined precursor isobaric labeling and isobaric tagging (OxcyscPILOT)" that allows for detection of endogenous SNO-modified proteins. OxcyscPILOT involves enrichment of SNO-modified proteins using a thiol-based resin. This enrichment is performed manually, and wash steps with the resin require numerous stages and buffer reagents. The goal of this study is to transfer the manual protocol to an automated liquid handler system in order to reduce wash steps, increase sample throughput, and minimize experimental error. In order to accomplish this, we evaluated the Biomek i7 liquid handler automated workstation and a Positive Pressure ALP (PPA) apparatus to conduct automated on-resin enrichment. Our findings provide starting pressure conditions for the use of PPA in an automated OxcyscPILOT proteomics workflow that could be transferred to other robotic liquid handling systems.

Brain expression of the vascular endothelial growth factor gene family in cognitive aging and alzheimer's disease.

Vascular endothelial growth factor (VEGF) is associated with the clinical manifestation of Alzheimer's disease (AD). However, the role of the VEGF gene family in neuroprotection is complex due to the number of biological pathways they regulate. This study explored associations between brain expression of VEGF genes with cognitive performance and AD pathology. Genetic, cognitive, and neuropathology data were acquired from the Religious Orders Study and Rush Memory and Aging Project. Expression of ten VEGF ligand and receptor genes was quantified using RNA sequencing of prefrontal cortex tissue. Global cognitive composite scores were calculated from 17 neuropsychological tests. ß-amyloid and tau burden were measured at autopsy. Participants (n = 531) included individuals with normal cognition (n = 180), mild cognitive impairment (n = 148), or AD dementia (n = 203). Mean age at death was 89 years and 37% were male. Higher prefrontal cortex expression of VEGFB, FLT4, FLT1, and PGF was associated with worse cognitive trajectories (p ≤ 0.01). Increased expression of VEGFB and FLT4 was also associated with lower cognition scores at the last visit before death (p ≤ 0.01). VEGFB, FLT4, and FLT1 were upregulated among AD dementia compared with normal cognition participants (p ≤ 0.03). All four genes associated with cognition related to elevated ß-amyloid (p ≤ 0.01) and/or tau burden (p ≤ 0.03). VEGF ligand and receptor genes, specifically genes relevant to FLT4 and FLT1 receptor signaling, are associated with cognition, longitudinal cognitive decline, and AD neuropathology. Future work should confirm these observations at the protein level to better understand how changes in VEGF transcription and translation relate to neurodegenerative disease.