publications

2024

1. Sociodemographic factors and research experience impact MD-PhD program acceptance

   Darnell K. Adrian Williams, Briana Christophers, Timothy Keyes, Rachit Kumar, Michael C. Granovetter, Alexandria Adigun, Justin Olivera, Jehron Pura-Bryant, Chynna Smith, Chiemeka Okafor, and 3 more authors

   JCI Insight, Feb 2024

   Publisher: American Society for Clinical Investigation

   DOI
2. Global Genotype by Environment Prediction Competition Reveals That Diverse Modeling Strategies Can Deliver Satisfactory Maize Yield Estimates

   Jacob D. Washburn, José Ignacio Varela, Alencar Xavier, Qiuyue Chen, David Ertl, Joseph L. Gage, James B. Holland, Dayane Cristina Lima, Maria Cinta Romay, Marco Lopez-Cruz, and 49 more authors

   Sep 2024

   Pages: 2024.09.13.612969 Section: New Results

   Abs DOI

   Predicting phenotypes from a combination of genetic and environmental factors is a grand challenge of modern biology. Slight improvements in this area have the potential to save lives, improve food and fuel security, permit better care of the planet, and create other positive outcomes. In 2022 and 2023 the first open-to-the-public Genomes to Fields (G2F) initiative Genotype by Environment (GxE) prediction competition was held using a large dataset including genomic variation, phenotype and weather measurements and field management notes, gathered by the project over nine years. The competition attracted registrants from around the world with representation from academic, government, industry, and non-profit institutions as well as unaffiliated. These participants came from diverse disciplines include plant science, animal science, breeding, statistics, computational biology and others. Some participants had no formal genetics or plant-related training, and some were just beginning their graduate education. The teams applied varied methods and strategies, providing a wealth of modeling knowledge based on a common dataset. The winner’s strategy involved two models combining machine learning and traditional breeding tools: one model emphasized environment using features extracted by Random Forest, Ridge Regression and Least-squares, and one focused on genetics. Other high-performing teams’ methods included quantitative genetics, classical machine learning/deep learning, mechanistic models, and model ensembles. The dataset factors used, such as genetics; weather; and management data, were also diverse, demonstrating that no single model or strategy is far superior to all others within the context of this competition.

3. The Alzheimer’s Knowledge Base: A Knowledge Graph for Alzheimer Disease Research

   Joseph D. Romano, Van Truong, Rachit Kumar, Mythreye Venkatesan, Britney E. Graham, Yun Hao, Nick Matsumoto, Xi Li, Zhiping Wang, Marylyn D. Ritchie, and 2 more authors

   Journal of Medical Internet Research, Apr 2024

   Company: Journal of Medical Internet Research Distributor: Journal of Medical Internet Research Institution: Journal of Medical Internet Research Label: Journal of Medical Internet Research Publisher: JMIR Publications Inc., Toronto, Canada

   Abs DOI

   Background: As global populations age and become susceptible to neurodegenerative illnesses, new therapies for Alzheimer disease (AD) are urgently needed. Existing data resources for drug discovery and repurposing fail to capture relationships central to the disease’s etiology and response to drugs. Objective: We designed the Alzheimer’s Knowledge Base (AlzKB) to alleviate this need by providing a comprehensive knowledge representation of AD etiology and candidate therapeutics. Methods: We designed the AlzKB as a large, heterogeneous graph knowledge base assembled using 22 diverse external data sources describing biological and pharmaceutical entities at different levels of organization (eg, chemicals, genes, anatomy, and diseases). AlzKB uses a Web Ontology Language 2 ontology to enforce semantic consistency and allow for ontological inference. We provide a public version of AlzKB and allow users to run and modify local versions of the knowledge base. Results: AlzKB is freely available on the web and currently contains 118,902 entities with 1,309,527 relationships between those entities. To demonstrate its value, we used graph data science and machine learning to (1) propose new therapeutic targets based on similarities of AD to Parkinson disease and (2) repurpose existing drugs that may treat AD. For each use case, AlzKB recovers known therapeutic associations while proposing biologically plausible new ones. Conclusions: AlzKB is a new, publicly available knowledge resource that enables researchers to discover complex translational associations for AD drug discovery. Through 2 use cases, we show that it is a valuable tool for proposing novel therapeutic hypotheses based on public biomedical knowledge.

4. Accelerating Genome- and Phenome-Wide Association Studies using GPUs – A case study using data from the Million Veteran Program

   Alex Rodriguez, Youngdae Kim, Tarak Nath Nandi, Karl Keat, Rachit Kumar, Rohan Bhukar, Mitchell Conery, Molei Liu, John Hessington, Ketan Maheshwari, and 15 more authors

   May 2024

   Pages: 2024.05.17.594583 Section: New Results

   Abs DOI

   The expansion of biobanks has significantly propelled genomic discoveries yet the sheer scale of data within these repositories poses formidable computational hurdles, particularly in handling extensive matrix operations required by prevailing statistical frameworks. In this work, we introduce computational optimizations to the SAIGE (Scalable and Accurate Implementation of Generalized Mixed Model) algorithm, notably employing a GPU-based distributed computing approach to tackle these challenges. We applied these optimizations to conduct a large-scale genome-wide association study (GWAS) across 2,068 phenotypes derived from electronic health records of 635,969 diverse participants from the Veterans Affairs (VA) Million Veteran Program (MVP). Our strategies enabled scaling up the analysis to over 6,000 nodes on the Department of Energy (DOE) Oak Ridge Leadership Computing Facility (OLCF) Summit High-Performance Computer (HPC), resulting in a 20-fold acceleration compared to the baseline model. We also provide a Docker container with our optimizations that was successfully used on multiple cloud infrastructures on UK Biobank and All of Us datasets where we showed significant time and cost benefits over the baseline SAIGE model.

5. Biomechanical analysis of complications following T10-Pelvis spinal fusion: A population based computational study

   Austin Q. Nguyen, Christian Rodriguez, Rachit Kumar, Sachin Gupta, Dennis E. Anderson, and Comron Saifi

   Journal of Biomechanics, Mar 2024

   Abs DOI

   Proximal junctional kyphosis (PJK) and proximal junctional failure (PJF) are challenging complications of long fusion constructs for the treatment of adult spinal deformity. The objective of this study is to understand the biomechanical stresses proximal to the upper instrumentation of a T10-pelvis fusion in a large patient cohort. The pre-fusion models were subject-specific thoracolumbar spine models that incorporate the height, weight, spine curvature, and muscle morphology of 250 individuals from the Framingham Heart Study Multidetector CT Study. To create post-fusion models, the subject-specific models were further modified to eliminate motion between the intervertebral joints from T10 to the pelvis. OpenSim analysis tools were used to calculate the medial lateral shear force, anterior posterior shear force, and compressive force on the T9 vertebra during the static postures. Differences between pre-fusion and post-fusion T9 biomechanics were consistent between increased segmental mobility and unchanged segmental mobility conditions. For all static postures, compression decreased (p \textless 0. 0005). Anterior-posterior shear force significantly increased (p \textless 0. 0005) during axial twist and significantly increased (p \textless 0. 0005) during trunk flexion. Medial lateral shear force significantly increased (p \textless 0. 0005) during axial twist. This computational study provided the first use of subject-specific models to investigate the biomechanics of long spinal fusions. Patients undergoing T10-Pelvis fusion were predicted to have increased shear forces and decreased compressive force at the T9 vertebra, independent of change in segmental mobility. The computational model shows potential for the investigation of spinal fusion biomechanics to reduce the risk of PJK or PJF.

6. Genetic Algorithm Selection of Interacting Features (GASIF) for Selecting Biological Gene-Gene Interactions

   Rachit Kumar, David Zhang, and Marylyn DeRiggi Ritchie

   In Proceedings of the Genetic and Evolutionary Computation Conference, Jul 2024

   Abs DOI

   Feature interactions are particularly useful in modeling biological effects, such as gene-gene interactions, but are difficult to model due to the exponential increase in the feature space. We present GASIF, a Genetic Algorithm that selects features and their interactions for the purposes of solving a supervised classification problem, designed for the identification of gene-gene interactions. GASIF works by constructing individuals with a collection of chromosomes that represent a subset of features and their interactions. It then determines individual fitness as a combination of the number of unique features used and the cross-validation performance of a logistic regression classifier trained on that feature subset with an ElasticNet penalty. A variety of intuitive operations are used to select, mate, and mutate individuals from generation to generation to limit the search space of features and interactions. We evaluate this Genetic Algorithm on a real-world dataset of human brain transcriptomic data from neuropathologically normal postmortem samples and pathologically confirmed late-onset Alzheimer’s disease individuals and determine the face validity of the gene-gene interactions that it identifies. Across multiple iterations of GASIF, we consistently identified the same features and interactions as most informative, all of which relate to genes known to be implicated in Alzheimer’s disease.

7. SABER: Statistical Identification of Loci of Interest in GWAS Summary Statistics using a Bayesian Gaussian Mixture Model

   Rachit Kumar, Rasika Venkatesh, and Marylyn D. Ritchie

   AMIA Summits on Translational Science Proceedings, May 2024

   Abs

   Genome-wide association studies (GWAS) remain a popular method for identifying novel genetic associations with human phenotypes and have provided many insights into the etiology of many diseases. However, GWAS provide limited support for how a genetic association might contribute to disease due to inherent limitations, such as linkage disequilibrium. As such, many methods that operate on GWAS summary statistics have been developed to generate evidence for functional pathways or for variants of interest, but they require defining the genomic region bounds for loci of interest. At present, there are limited methods for determining these bounds in a rigorous, reproducible way. We present a novel statistical method, Statistical Analysis for Bayesian Estimation of Regions (SABER), that uses Bayesian Gaussian mixture models to reproducibly generate ratios that quantify whether particular genomic positions represent the bounds of loci of interest and can be used to delineate genomic regions for downstream analyses.

8. Pathways and barriers to becoming physician-scientists for first-generation individuals

   Briana Christophers, Briana Macedo, Jessica Weng, Michael C. Granovetter, Rachit Kumar, Chynna Smith, Olaf S. Andersen, and Catharine Boothroyd

   Mar 2024

   Pages: 2024.03.17.24304448

   Abs DOI

   Introduction Physician-scientists are uniquely positioned to contribute translational research that will impact patient care and our understanding of disease. Having a diverse cadre of physician-scientists is critical to ensuring that the biomedical research enterprise explores the breadth of problems affecting the nation’s health. The National Institutes of Health has identified diversity, including educational background, to be important for the biomedical workforce. In 2020, less than ten percent of MD-PhD program matriculants were the first in their families to pursue higher education (first-generation) despite the majority of the US population having less than a Bachelor’s degree. Little is known about the specific challenges that first-generation students face, which makes it challenging to address this gap in matriculation. Methods This qualitative study used a phenomenological approach to examine the experiences of first-generation individuals, from the applicant stage to the early-career stage. We conducted semi-structured interviews with 41 participants and analyzed responses in accordance with a networked ecological systems theory. Results The interviews revealed that first-generation individuals put together a patchwork of support. Whereas many MD-PhD trainees struggle at some point in their training, first-generation individuals tend to lack a support system that may provide proactive advice and prepare them for milestones. Interviews shared a common sentiment of isolation due to both a lack of social capital within medicine and academia, as well as a growing disconnect from their families and community. Discussion Key interventions that would support first-generation students include greater access to high-quality information about the pathway, tailored mentorship throughout training, and more financial resources at the application stage. Trainees and early career physician-scientists seek more flexibility, opportunities for finding community, financial guidance and options, and mentorship around building their careers.

2023

1. The fourth annual Carnegie Mellon Libraries hackathon for biomedical data management, knowledge graphs, and deep learning

   Jędrzej Kubica, Rachit Kumar, Glenda Tan, Van Q. Truong, David Enoma, Nicholas Cooley, Minhyek Jeon, Chiao-Feng Lin, Minh Tran, Amrita Roy Choudhury, and 10 more authors

   Nov 2023

   Abs DOI

   In October 2023, a group of 44 scientists hailing from several U.S. states, Canada, Poland, and Switzerland came together for a hybrid in-person and virtual hackathon. The event was jointly hosted by Carnegie Mellon University Libraries and DNAnexus, a California-based cloud computing and bioinformatics company. This collaborative effort revolved around the theme of “Data Management and Graph Extraction for Large Transformer Models in the Biomedical Space.” In the spirit of fostering collaboration, participants organized themselves into five teams, which ultimately resulted in the successful completion of four hackathon projects. These projects encompassed a wide range of topics, from detecting features contributing to virus susceptibility to validating models using knowledge graphs. Repositories for the hackathon projects are available at https://github.com/collaborativebioinformatics. We hope that the insights and experiences shared by these teams, as detailed in the following manuscript, will prove valuable to the broader scientific community.

2. Aging and Visual Presentations in MRI Environments

   Jenny Walker, Rachit Kumar, Marvin Hoo, and Mark E. Wheeler

   Proceedings of the International Symposium on Human Factors and Ergonomics in Health Care, Mar 2023

   Publisher: SAGE Publications

   Abs DOI

   As individuals age, their vision tends to decline. These changes are natural, but often neglected when designing tasks for both older and younger adults. For instance, many MRI machine set-ups include in-bore displays. Ongoing work in our lab suggests that some older adults have issues seeing stimuli on these displays if there is a visual noise component. This is a problem that did not occur with younger adult samples. Therefore, this work provides an example of how this concern was addressed using a psychophysical thresholding technique. We hope that our experience will inform others who are facing similar issues and/or seeking suggestions for improving their patient and participants’ scanning experiences.

3. Extending Tree-Based Automated Machine Learning to Biomedical Image and Text Data Using Custom Feature Extractors

   Rachit Kumar, Joseph Romano, Marylyn Ritchie, and Jason Moore

   In Proceedings of the Companion Conference on Genetic and Evolutionary Computation, Jul 2023

   Abs DOI

   Automated machine learning (AutoML) has allowed for many innovations in biomedical data science; however, most AutoML approaches do not support image or text data. To rectify this, we implemented four feature extractors in the Tree-based Pipeline Optimization Tool (TPOT) to make TPOT with Feature Extraction (TPOT-FE), an automated machine learning system that uses genetic programming (GP) to create ideal pipelines for a classification or regression task. These feature extractors enable TPOT-FE to build pipelines that can analyze non-tabular data, including text and images, which are increasingly common biomedical big data modalities that can contain rich quantities of information. We evaluate this approach on six image datasets and four text datasets, including three biomedical datasets, and show that TPOT-FE is able to consistently construct and optimize classification pipelines on all of the datasets.

2022

1. Quality Control Procedures for Genome-Wide Association Studies

   Van Q. Truong, Jakob A. Woerner, Tess A. Cherlin, Yuki Bradford, Anastasia M. Lucas, Chelsea C. Okeh, Manu K. Shivakumar, Daniel H. Hui, Rachit Kumar, Milton Pividori, and 5 more authors

   Current Protocols, Nov 2022

   _eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/cpz1.603

   Abs DOI

   Genome-wide association studies (GWAS) are being conducted at an unprecedented rate in population-based cohorts and have increased our understanding of the pathophysiology of many complex diseases. Regardless of the context, the practical utility of this information ultimately depends upon the quality of the data used for statistical analyses. Quality control (QC) procedures for GWAS are constantly evolving. Here, we enumerate some of the challenges in QC of genotyped GWAS data and describe the approaches involving genotype imputation of a sample dataset along with post-imputation quality assurance, thereby minimizing potential bias and error in GWAS results. We discuss common issues associated with QC of the GWAS data (genotyped and imputed), including data file formats, software packages for data manipulation and analysis, sex chromosome anomalies, sample identity, sample relatedness, population substructure, batch effects, and marker quality. We provide detailed guidelines along with a sample dataset to suggest current best practices and discuss areas of ongoing and future research. © 2022 Wiley Periodicals LLC.

2. Structural and Functional Hippocampal Correlations in Environmental Enrichment During the Adolescent to Adulthood Transition in Mice

   Francis A. M. Manno, Rachit Kumar, Ziqi An, Muhammad Shehzad Khan, Junfeng Su, Jiaming Liu, Ed X. Wu, Jufang He, Yanqiu Feng, and Condon Lau

   Frontiers in Systems Neuroscience, Feb 2022

   Abs DOI

   Environmental enrichment is known to induce neuronal changes; however, the underlying structural and functional factors involved are not fully known and remain an active area of study. To investigate these factors, we assessed enriched environment (EE) and standard environment (SE) control mice over 30 days using structural and functional MRI methods. Naïve adult male mice (n = 30, ≈20 g, C57BL/B6J, postnatal day 60 initial scan) were divided into SE and EE groups and scanned before and after 30 days. Structural analyses included volumetry based on manual segmentation as well as diffusion tensor imaging (DTI). Functional analyses included seed-based analysis (SBA), independent component analysis (ICA), the amplitude of low-frequency fluctuation (ALFF), and fractional ALFF (fALFF). Structural results indicated that environmental enrichment led to an increase in the volumes of cornu ammonis 1 (CA1) and dentate gyrus. Structural results indicated changes in radial diffusivity and mean diffusivity in the visual cortex and secondary somatosensory cortex after EE. Furthermore, SBA and ICA indicated an increase in resting-state functional MRI (rsfMRI) functional connectivity in the hippocampus. Using parallel structural and functional analyses, we have demonstrated coexistent structural and functional changes in the hippocampal subdivision CA1. Future research should map alterations temporally during environmental enrichment to investigate the initiation of these structural and functional changes.

3. Environmental enrichment leads to behavioral circadian shifts enhancing brain-wide functional connectivity between sensory cortices and eliciting increased hippocampal spiking

   Francis A. M. Manno, Ziqi An, Rachit Kumar, Junfeng Su, Jiaming Liu, Ed X. Wu, Jufang He, Yanqiu Feng, and Condon Lau

   NeuroImage, May 2022

   Abs DOI

   Environmental enrichment induces widespread neuronal changes, but the initiation of the cascade is unknown. We ascertained the critical period of divergence between environmental enriched (EE) and standard environment (SE) mice using continuous infrared (IR) videography, functional magnetic resonance imaging (fMRI), and neuron level calcium imaging. Naïve adult male mice (n = 285, C57BL/6J, postnatal day 60) were divided into SE and EE groups. We assessed the linear time-series of motion activity using a novel structural break test which examined the dataset for change in circadian and day-by-day motion activity. fMRI was used to map brain-wide response using a functional connectome analysis pipeline. Awake calcium imaging was performed on the dorsal CA1 pyramidal layer. We found the preeminent behavioral feature in EE was a forward shift in the circadian rhythm, prolongation of activity in the dark photoperiod, and overall decreased motion activity. The crepuscular period of dusk was seen as the critical period of divergence between EE and SE mice. The functional processes at dusk in EE included increased functional connectivity in the visual cortex, motor cortex, retrosplenial granular cortex, and cingulate cortex using seed-based analysis. Network based statistics found a modulated functional connectome in EE concentrated in two hubs: the hippocampal formation and isocortical network. These hubs experienced a higher node degree and significant enhanced edge connectivity. Calcium imaging revealed increased spikes per second and maximum firing rate in the dorsal CA1 pyramidal layer, in addition to location (anterior-posterior and medial-lateral) effect size differences between EE and SE. The emergence of functional-neuronal changes due to enrichment consisted of enhanced hippocampal-isocortex functional connectivity and CA1 neuronal increased spiking linked to a circadian shift during the dusk period. Future studies should explore the molecular consequences of enrichment inducing shifts in the circadian period.

4. The Virtual Summer Research Program: supporting future physician-scientists from underrepresented backgrounds

   Briana Macedo, Briana Christophers, Rio Barrere-Cain, Yentli Soto Albrecht, Michael C. Granovetter, Rachit Kumar, Dania Daye, Elizabeth Bhoj, Lawrence Brass, and Jose Alexandre Rodrigues

   Journal of Clinical and Translational Science, Aug 2022

   Abs DOI

   Introduction: Physician-scientist training programs expect applicants to have had extensive research experience prior to applying. Even at the best of times, this leaves individuals from underserved and underrepresented backgrounds at a competitive disadvantage, especially those remote from major academic centers. The COVID-19 pandemic exacerbated that disadvantage by closing research laboratories and suspending summer research opportunities. Methods: The Virtual Summer Research Program (VSRP) was designed to combat this shortfall by helping participating students become better informed and better prepared for applying to MD/DO–PhD programs. 156 participants were recruited from historically black colleges and universities and from national organizations for underrepresented trainees. Participants were paired with medical school faculty members and current MD/DO–PhD students from 35 participating institutions. The program lasted for at least 4 weeks and included a short research project, interactive sessions, journal clubs, social events, and attendance at a regional American Physician Scientists Association conference. Results: In follow-up surveys, participants reported improvements in their science-related skills and in their confidence in becoming a physician-scientist, applying to training programs, and navigating mentorship relationships. A follow-up study completed one year later indicated that participants felt they had benefited from an enhanced skill set, long-term relationships with their mentors, and connections to the physician-scientist community at large. Discussion: The results suggest that VSRP met its primary goals, which were to provide a diverse group of trainees with mentors, provide skills and resources for MD/DO–PhD application and matriculation and to support the development of longitudinal relationships between VSRP mentees and APSA. VSRP provides an approach that can be applied at an even larger scale when the constraints caused by a global pandemic have lifted.

5. Intraoperative Hypotension Is Not Correlated With Acute Kidney Injury During Spinal Fusion Surgery

   Rachel Blue, Alexis Gutierrez, Hasan S. Ahmad, Maya Alexis, Rachit Kumar, Michael Spadola, Connor Wathen, Mitchell Weinstein, and Dmitriy Petrov

   International Journal of Spine Surgery, Dec 2022

   Abs DOI

   Background Intraoperative hypotension (IOH) has been found to be associated with organ damage, including cardiac injury and acute kidney injury (AKI). However, to our knowledge, this relationship has not been studied in a neurosurgery-specific patient population. In this report, we review our institutional experience to understand the magnitude of association between IOH in spinal fusion operations and incidence of postoperative AKI. Methods This retrospective cohort study included 910 patients who underwent posterior spinal fusion procedures performed in the prone position. Intraoperative variables collected and analyzed include minute-by-minute mean arterial pressure (MAP) from an arterial catheter, intermittent blood pressure cuff readings, volume of administered intravenous fluids, urine output, and all relevant vitals and administered medications. The electronic medical record was queried for additional patient data. IOH was defined as MAP \textless65 mm Hg for greater than 10 minutes. The primary endpoints of the study were presence and staging of AKI ( [Kidney Disease: Improving Global Outcomes] consensus classification), postoperative ileus, and postoperative troponin leak. Results Using a partial correlation analysis, no association was found between IOH metrics (IOH occurrence, IOH duration \textgreater10 minutes, and total IOH time) and any outcome metrics, including AKI, except for vasopressor usage and estimated blood loss. Patient age at surgery was not associated with any outcome variables. The lack of association between IOH and AKI contrasts with existing literature; this could be due to underlying differences in our patient population or could highlight a more complex relationship between IOH and AKI than previously understood. Conclusion Occurrence and duration of IOH were not associated with AKI, postoperative ileus, troponin leak, length of stay, or any other major outcome variables in spinal fusion patients. Clinical Relevance These findings depart from previous literature showing a correlation between IOH and AKI and provide level 3 evidence clinically relevant to spinal surgery. Further research is needed to better understand the exact nature of this relationship. Level of Evidence 3.

2021

1. Supporting Equity and Inclusion of Deaf and Hard-of-Hearing Individuals in Professional Organizations

   Julia Jones Huyck, Kelsey L. Anbuhl, Brad N. Buran, Henry J. Adler, Samuel R. Atcherson, Ozan Cakmak, Robert T. Dwyer, Morgan Eddolls, Fadhel El May, Juergen-Theodor Fraenzer, and 32 more authors

   Frontiers in Education, Oct 2021

   Abs DOI

   Disability is an important and often overlooked component of diversity. Individuals with disabilities bring a rare perspective to science, technology, engineering, mathematics, and medicine (STEMM) because of their unique experiences approaching complex issues related to health and disability, navigating the healthcare system, creatively solving problems unfamiliar to many individuals without disabilities, managing time and resources that are limited by physical or mental constraints, and advocating for themselves and others in the disabled community. Yet, individuals with disabilities are underrepresented in STEMM. Professional organizations can address this underrepresentation by recruiting individuals with disabilities for leadership opportunities, easing financial burdens, providing equal access, fostering peer-mentor groups, and establishing a culture of equity and inclusion spanning all facets of diversity. We are a group of deaf and hard-of-hearing (D/HH) engineers, scientists, and clinicians, most of whom are active in clinical practice and/or auditory research. We have worked within our professional societies to improve access and inclusion for D/HH individuals and others with disabilities. We describe how different models of disability inform our understanding of disability as a form of diversity. We address heterogeneity within disabled communities, including intersectionality between disability and other forms of diversity. We highlight how the Association for Research in Otolaryngology has supported our efforts to reduce ableism and promote access and inclusion for D/HH individuals. We also discuss future directions and challenges. The tools and approaches discussed here can be applied by other professional organizations to include individuals with all forms of diversity in STEMM.

2. Hearing loss impacts gray and white matter across the lifespan: Systematic review, meta-analysis and meta-regression

   Francis A.M. Manno, Raul Rodríguez-Cruces, Rachit Kumar, J. Tilak Ratnanather, and Condon Lau

   NeuroImage, May 2021

   Abs DOI

   Hearing loss is a heterogeneous disorder thought to affect brain reorganization across the lifespan. Here, structural alterations of the brain due to hearing loss are assessed by using unique effect size metrics based on Cohen’s d and Hedges’ g. These metrics are used to map coordinates of gray matter (GM) and white matter (WM) alterations from bilateral congenital and acquired hearing loss populations. A systematic review and meta-analysis revealed m = 72 studies with structural alterations measured with magnetic resonance imaging (MRI) (bilateral = 64, unilateral = 8). The bilateral studies categorized hearing loss into congenital and acquired cases (n = 7,445) and control cases (n = 2,924), containing 66,545 datapoint metrics. Hearing loss was found to affect GM and underlying WM in nearly every region of the brain. In congenital hearing loss, GM decreased most in the frontal lobe. Similarly, acquired hearing loss had a decrease in frontal lobe GM, albeit the insula was most decreased. In congenital, WM underlying the frontal lobe GM was most decreased. In congenital, the right hemisphere was more negatively impacted than the left hemisphere; however, in acquired, this was the opposite. The WM alterations most frequently underlined GM alterations in congenital hearing loss, while acquired hearing loss studies did not frequently assess the WM metric. Future studies should use the endophenotype of hearing loss as a prognostic template for discerning clinical outcomes.

3. Structural Alterations in a Rat Model of Short-Term Conductive Hearing Loss Are Associated With Reduced Resting State Functional Connectivity

   Francis A. M. Manno, Ziqi An, Rachit Kumar, Ed X. Wu, Jufang He, Yanqiu Feng, and Condon Lau

   Frontiers in Systems Neuroscience, Aug 2021

   Abs DOI

   Conductive hearing loss (CHL) results in attenuation of air conducted sound reaching the inner ear. How a change in air conducted sound alters the auditory system resulting in cortical alterations is not well understood. Here, we have assessed structural and functional magnetic resonance imaging (MRI) in an adult (P60) rat model of short-term conductive hearing loss (1 week). Diffusion tensor imaging (DTI) revealed fractional anisotropy (FA) and axial diffusivity alterations after hearing loss that circumscribed the auditory cortex (AC). Tractography found the lateral lemniscus tract leading to the bilateral inferior colliculus (IC) was reduced. For baseline comparison, DTI and tractography alterations were not found for the somatosensory cortex. To determine functional connectivity changes due to hearing loss, seed-based analysis (SBA) and independent component analysis (ICA) were performed. Short term conductive hearing loss altered functional connectivity in the AC and IC, but not the somatosensory cortex. The results present an exploratory neuroimaging assessment of structural alterations coupled to a change in functional connectivity after conductive hearing loss. The results and implications for humans consist of structural-functional brain alterations following short term hearing loss in adults.

2020

1. Glymphatic clearance of simulated silicon dispersion in mouse brain analyzed by laser induced breakdown spectroscopy

   Muhammad Shehzad Khan, Rachit Kumar, Sinai H. C. Manno, Irfan Ahmed, Alan Wing Lun Law, Raul R. Cruces, Victor Ma, William C. Cho, Shuk Han Cheng, and Condon Lau

   Heliyon, Apr 2020

   Abs DOI

   Silicon-based devices, such as neural probes, are increasingly used as electrodes for receiving electrical signals from neural tissue. Neural probes used chronically have been known to induce inflammation and elicit an immune response. The current study detects and evaluates silicon dispersion from a concentrated source in the mouse brain using laser induced breakdown spectroscopy. Element lines for Si (I) were found at the injection site at approximately 288 nm at 3hr post-implantation, even with tissue perfusion, indicating possible infusion into neural tissue. At 24hr and 1-week post-implantation, no silicon lines were found, indicating clearance. An isolated immune response was found by CD68 macrophage response at 24hr post injection. Future studies should measure chronic silicon exposure to determine if the inflammatory response is proportional to silicon administration. The present type of protocol, coupling laser induced breakdown spectroscopy, neuroimaging, histology, immunohistochemistry, and determination of clearance could be used to investigate the glymphatic system and different tissue states such as in disease (e.g. Alzheimer’s).

2. Challenges and advice for MD/PhD applicants who are underrepresented in medicine

   Carl Bannerman, Natalie Guzman, Rachit Kumar, Chelsea Nnebe, Jordan Setayesh, Amitej Venapally, and Jonathan H. Sussman

   Molecular Biology of the Cell, Nov 2020

   Abs DOI

   The importance of diversity is self-evident in medicine and medical research. Not only does diversity result in more impactful scientific work, but diverse teams of researchers and clinicians are necessary to address health disparities and improve the health of underserved communities. MD/PhD programs serve an important role in training physician-scientists, so it is critical to ensure that MD/PhD students represent diverse backgrounds and experiences. Groups who are underrepresented in medicine and the biomedical sciences include individuals from certain racial and ethnic backgrounds, individuals with disabilities, individuals from disadvantaged backgrounds, and women. However, underrepresented students are routinely discouraged from applying to MD/PhD programs due to a range of factors. These factors include the significant cost of applying, which can be prohibitive for many students, the paucity of diverse mentors who share common experiences, as well as applicants’ perceptions that there is inadequate support and inclusion from within MD/PhD programs. By providing advice to students who are underrepresented in medicine and describing steps programs can take to recruit and support minority applicants, we hope to encourage more students to consider the MD/PhD career path that will yield a more productive and equitable scientific and medical community.