University Of California Los Angeles

NIH Research Projects · FY 2025 · 2022-09

PROJECT SUMMARY Alpha oscillations, 8-12Hz fluctuations in neural signals, are robust across species, covary with states of attention, and are impacted in multiple disorder states, and in recent years have become a candidate biomarker of attention system efficacy, particularly in disorders of attention such as attention deficit hyperactivity disorder (ADHD). Yet, despite this broad acceptance of alpha oscillations as an attention read-out signal, significant questions remain regarding the mechanisms and thus interpretation of alpha oscillations. The goal of our research is to answer the central question of whether the neurocognitive mechanisms of alpha oscillations are strictly attentional or whether they more closely reflect other mechanisms such as local processing dynamics or system-wide tonic alertness. To address this question, we will record EEG and fMRI concurrently in human participants, and employ causal models, to identify functional connectivity (3T scanning) and laminar activation (7T scanning) of visual cortex during alpha modulations across different task contexts. We aim to test (1) if alpha increases reflect cortical suppression or tonic alertness, (2) if alpha decreases reflect cortical enhancement or local information flow, and, (3) if alpha modulations reflect top-down signals or if they are a passive by-product of either cortico-cortical or thalamo-cortical drivers. The results will directly impact interpretation of alpha oscillations as a biomarker of attention-system efficacy in ADHD and related conditions, outlining a model that can be targeted in treatment or monitoring of attention deficits in ADHD. By accounting for variability in existing findings, this work will also differentiate between two theoretical frameworks of alpha oscillations and speak to recent debates on whether alpha oscillations are a correlate or a product of top-down signals.

NIH Research Projects · FY 2025 · 2022-09

Abstract Pressure injuries (PrIs), commonly located over bony prominences, are local areas of damage to the skin and underlying soft tissue caused by pressure and shear forces. These painful, dangerous, costly, and preventable injuries in nursing home (NH) residents are associated with reduced quality of life and mortality. This embedded pragmatic stepped wedge cluster clinical trial, using a mixed-methods approach for all residents in 8 NHs, will examine use of subepidermal moisture (SEM) assessment results as a cue for nursing staff to initiate PrI prevention. SEM assessment, a biophysical measure that senses changes in skin characteristics, detects early pressure damage by identifying subclinical signs of PrI. SEM use is an innovative addition to current PrI prevention care that is currently initiated upon a positive risk assessment and/or a visual inspection of skin discoloration. Significant damage exists by the time erythema or purple skin is observed. Lag time between pressure-induced tissue damage and visual detection of skin discoloration delays nursing actions to prevent PrIs. Discoloration is more difficult to discern in persons with dark skin tones, making skin damage detection more challenging for residents from minority or under-represented racial/ethnic groups than those with lighter skin tones; thus, producing a health disparity. The study will incorporate SEM assessment into PrI prevention standard-of-care and conduct the intervention over a 9-month period. The study aims are to: 1) determine if early pressure damage detected by SEM assessment at time of visual skin observation of NH resident sacral and heel areas is effective in cueing initiation of NH standard PrI prevention; 2) examine the association between NH standard PrI prevention and SEM assessment and NH residents’ characteristics (age, gender, risk, skin tone, race, ethnicity, BMI, cognitive status) and their interactions on individual NH residents with regard to initiation of NH standard PrI prevention and PrI occurrence; and, 3) explore if SEM usability, NH, and nursing staff characteristics influence the adoption and assimilation of early PrI detection and subsequent PrI prevention practices. Current NH PrI prevention protocols and periodic safety and care checks will be performed. Sample will be comprised of all residents at intervention start and those newly admitted during the 9-month intervention period. An intention to treat approach will be used for quantitative analyses with resident data accrued throughout the intervention period included in analyses. Cueing effectiveness will be determined by evaluating the initiation of PrI prevention strategies in relation to SEM values and the development of PrI during the intervention. Mixed effects regression models for clustered/repeated measures will use electronic health record data and SEM assessment values modeled to predict initiation of PrI prevention actions. Qualitative analyses will be applied to focus group data with comparison to cueing effectiveness findings. Study results will advance knowledge about clinically assessed PrI risk-level and contribute to future redesign of preventive nursing practices and refinement of PrI prevention guidelines.

NIH Research Projects · FY 2025 · 2022-09

PROJECT SUMMARY / ABSTRACT The candidate requests support for a five-year program of training and research to better understand how electronic health record phenotyping and other computational methods applied to existing medical record data can bolster detection and prediction of suicide attempts by children ages 10 to 17. In the proposed training plan, the candidate will build upon her previous experiences in social psychology, clinical informatics, and clinical child and adolescent psychiatry to perform a multidisciplinary project at the University of California, Los Angeles Health System. Her training plan includes developing skills and knowledge in 1) analysis of natural language (text) data, 2) development of risk algorithms in healthcare settings to improve suicide prevention, 3) basic qualitative research skills including modified Delphi Panel approach, and 4) the responsible conduct of research. Suicide is the second leading cause of death of young people over 10 years old in the United States and suicide attempts among children are common, costly and preventable. There is an urgent need to close the gap between risk prediction algorithms and clinically-useable tools that can enhance medical decision- making for providers and families. This study proposes that electronic health record phenotyping, a method of standardizing case detection using clinical note text and structured medical record data, may offer improved detection and personalized risk prediction for children, thus complementing existing suicide prevention efforts. In the proposed research, using a cross-sectional design, Aim 1 will focus on adaptation of electronic health record phenotyping to detect emergency department visits for suicide attempts by children using electronic health records. Then, using a case-control design, Aim 2 will focus on development of risk prediction models of emergency department visits for suicide attempts by children using longitudinal electronic health records over two years. Aim 3 will focus on assessment of the validity, acceptability, usability, feasibility, and overall utility of a personalized risk prediction prototype with case simulations using a modified Delphi panel approach. This plan will parallel a training plan building skills and knowledge to bridge informatics, computational methods, and clinical child psychiatry. In the long term, this research is an initial step to enhance signal detection and support prediction of suicide attempts, in turn, setting the stage for deployment of personalized approaches to prevention in clinical settings where providers, youth, and families may directly benefit.

NIH Research Projects · FY 2025 · 2022-09

Project Summary/Abstract There are over 20 million Asians in the US, 60% of whom are immigrants. By 2055, this demographic is expected to surpass Hispanics to become the largest immigrant group in the country. This includes 1.5 million undocumented Asians, who experience greater barriers to access than their documented peers. Despite these trends, national health statistics often lump Asians into an “other” category or exclude them entirely. For Asian immigrant women, who report greater odds of unintended pregnancies and are less likely to use sexual and reproductive health (SRH) care compared to their US-born counterparts, detailed SRH data accounting for their diversity of social, economic, and political experiences is critical to addressing SRH inequities in their growing community. Moreover, past studies treat immigration status as a binary (documented/undocumented) and static variable; however, there is increasing recognition that there is a hierarchy of statuses and that status can change across the life of an immigrant. Building on the PI’s past work with Asian immigrants, the goal of this study is to provide critical SRH data among the most diverse sample of Asian immigrant women to date. We propose to establish the first multi-city, sequential mixed-methods study of the SRH of Asian women across multiple ethnicities and immigration statuses, including naturalized citizens, lawful permanent residents, temporary workers and students, DACA recipients, and undocumented immigrants. Guided by the social ecological model and life course perspective, this study will assess multilevel factors that mediate and moderate associations between immigration status and SRH care use. We first conduct 48 qualitative life history interviews to examine how sociopolitical experiences of immigration statuses act as barriers to SRH care use over time (Aim 1). Next, using a novel starfish sampling method used to recruit hidden populations, we will recruit 2,000 Asian immigrant women aged 18-49 years, including an oversampling of the four largest undocumented Asian ethnicities (Indian, Chinese, Filipinos, and Koreans) in cities with the highest numbers of Asian immigrants (Los Angeles, New York City, Houston, and Atlanta). Using quantitative survey data, we will 1) examine how immigration status is associated with use of recent SRH services; 2) explore histories of immigration statuses and assess cumulative risks on SRH care use during sensitive periods (e.g. childhood, adolescence, adulthood) (Aim 2); 3) and examine mediators and moderators (Aim 3). In order to improve the quality, relevance, and accessibility of our research, we will partner with the National Asian Pacific American Women’s Forum (NAPAWF), the first national Asian reproductive justice organization, and its chapters located in each of our cities of interest. In addition, we will closely engage the knowledge, expertise, and sensitivities of local community-based organizations throughout California, New York, Texas, and Georgia. Our short-term goal is to identify and inform multi-level SRH outreach and intervention efforts, which will help us achieve our long-term goal to improve the SRH equity of immigrants, families, and communities.

NIH Research Projects · FY 2025 · 2022-09

Project summary Nausea is an unpleasant sensation of visceral malaise often accompanied by an involuntary urge to vomit. Nausea responses to toxin ingestion and infection are evolutionarily beneficial survival behaviors that avoid or expel toxins which may cause peripheral tissue damage. However, the sensation of nausea can also be maladaptive, as many treatments for cancer, diabetes, and other illnesses induce nausea as a major side effect, while current anti-emetic drugs have only limited efficacy. Known as the “chemoreceptors trigger zone” for nausea, the area postrema is a brain circumventricular sensory organ critical for nausea and vomiting. Neurons in the area postrema occupy a unique anatomical location with a deficient blood-brain barrier, and can be regulated by inputs from both the humoral routes and the gastrointestinal tract. However, little is known about how area postrema neurons contribute to the mechanisms of nausea and its related aversive behaviors. Using single-nucleus RNA-sequencing combined with genetic and behavioral studies, we have recently discovered a population of the area postrema neurons that, in response to emetic cues, induce nausea-associated aversive behaviors in mice. Here, I propose a multi-tiered approach, based on these preliminary findings, to investigate the humoral and vagal inputs to the chemosensory circuit of the area postrema and how they contribute to nausea. First, I will identify humoral cues that act through the area postrema aversion-promoting excitatory neuron types by testing a panel of nausea-inducing or anorexigenic humoral stimuli (Aim 1). Next, I will map and identify vagal inputs to the genetically defined area postrema excitatory neuron types using viral tracing and channelrhodopsin-assisted circuit mapping techniques (Aim 2). These experiments will reveal how vagal inputs and humoral cues can regulate the functions of the area postrema neurons which mediate nausea-associated aversive behaviors. Following this training, I will be poised to transition to the R00 phase of my career and establish a unique independent research program incorporating targeted cell-type manipulation in vomiting animal models (Aim 3). These studies will elucidate the cellular and neural mechanisms nausea and may guide the design of novel anti-emetic therapies. Central to this proposal is the mentorship of Dr. Stephen Liberles, an expert in internal sensations, Dr. Brad Lowell, an expert in functional circuit mapping, Dr. Frank Reimann, an expert in gut hormone signaling, Dr. Chenghua Gu, a leader in blood-brain barrier mechanisms, and Dr. Charles Horn, an expert in vomiting models and nausea physiology. They will provide career guidance and help me achieve my training goals. In my application I have outlined a comprehensive plan for acquiring the conceptual, technical, and professional skills that will enable my transition to an independent research position.

NIH Research Projects · FY 2025 · 2022-09

Project Summary/Abstract: Technological developments now make it possible to target specific, clinically relevant brain regions in patients using non-invasive neuromodulation. The effects of neuromodulation presumably propagate beyond the directly targeted brain regions through brain networks. To characterize this targeting of networks and thereby optimize neuromodulation, the proposed research aims to map the engagement of neural circuitry by a specific modality (transcranial direct current stimulation (tDCS)) in a specific clinical population (depression). Depression is characterized by dysfunction of the dorso-fronto-limbic network, with hypoactive left dorsolateral prefrontal cortex (DLPFC) and hyperactive right DLPFC. As investigational treatments for depression, these regions have been targeted using anodal and cathodal tDCS respectively, which are hypothesized to depolarize and hyperpolarize neurons (respectively), thereby counteracting pathological neural activity. K99 Aim 1 will use functional MRI (fMRI) during tDCS administration to investigate stimulation-specific activity and connectivity changes in the dorso-fronto-limbic network resulting from left DLPFC anodal tDCS. K99 Aim 2 will investigate whether tDCS induced activity changes are amplified in the same network when anodal left DLPFC tDCS is delivered concurrently with a salient cognitive task (2-back working memory). Work in model systems suggests that synaptic co-activation by a task during tDCS administration should enhance induced plasticity, and evidence of a super-additive two-way interaction of tDCS and task would provide presumptive evidence of target engagement to motivate future investigations of a tDCS-plus-task protocol. The R00 phase will follow up on the K99 phase's anodal tDCS research by focusing on cathodal tDCS. R00 Aim 1 will investigate stimulation-specific activity and connectivity changes in the dorso-fronto-limbic network induced by right DLPFC cathodal tDCS. R00 Aim 2 will investigate significant interactions between cathodal tDCS and the same DLPFC-coactivating cognitive task. For all aims, measurements will be carried out using a novel imaging approach employing spatially focal high- definition tDCS and concurrent blood oxygenation level dependent (BOLD) fMRI. This research is in line with the mission of NIMH/DNBBS, supporting interdisciplinary research into the modulation of clinically relevant neural circuits. My tDCS work to date has built upon my engineering background, using MRI to validate the precise delivery of tDCS in vivo. The proposed aims take the next logical step in this research, by using imaging to understand the response of brain circuits to such precisely delivered neuromodulation. To facilitate this work and help me achieve my long term goal of becoming an independent investigator in imaging-guided neuromodulation (applied to developing novel treatments for mental health disorders), training components to improve my expertise in pertinent areas of neuroscience (focusing on brain circuits and their pathology in neuropsychiatric disorders), clinical research and fMRI methodologies are proposed. The scientific aims address fundamental open questions in tDCS neuromodulation and are highly synergistic with the training objectives.

NIH Research Projects · FY 2025 · 2022-09

PROJECT SUMMARY Low-Dose Computed Tomography (LDCT) has been demonstrated to reduce lung cancer mortality by 20% for high-risk current and former smokers. However, 25% of the subjects in the NLST demonstrated abnormalities and a large fraction of those lesions were determined to be false-positives. There is an unmet need to accurately and non-invasively identify early-stage aggressive lung cancers and distinguish lesions that are life threatening from those that are not. Recently cell-free DNA (cfDNA) in human blood has emerged as an ideal source for cancer detection. In this proposal, we develop an integrated system, CancerRadar, consisting of (1) an experimental assay, cfMethyl-Seq, for cost-effective genome-wide methylation profiling of cfDNA, offering >10 fold enrichment over Whole Genome Bisulfite Sequencing (WGBS) in profiling CpG islands; and (2) a computational framework to extract various information from cfMethyl-Seq data, including cfDNA methylation, cfDNA fragment size, copy number variation (CNV), and microbial composition, and perform multi-feature ensemble learning for detecting malignant lung nodule and locating its primary tumor sites. We will validate CancerRadar with several clinical cohorts. Compared to the commonly used small panels focusing on one type of markers, CancerRadar profiles and integrates genome-wide profiles of multiple genetic/epigenetic features, therefore can robustly capture the very small proportion of tumor-derived cfDNA fragments, comprehensively diagnose patients with heterogeneous cancer pathogenesis, and learn and exploit newly significant features as training sample size grow.

NIH Research Projects · FY 2024 · 2022-09

Project Summary/Abstract Thailand has the highest HIV prevalence rate in the Asian-Pacific region, with an estimated 1.2% of its adult population infected. Currently there are 0.5 million of PLWH living in Thailand, with a handful of populations more vulnerable to HIV, including men who have sex with men (MSM) (9.2-40%), transgender individuals (12%), sex workers (1-16%), and substance users (19%). Also, the overall mortality rate among Thai PLWH was 3.56%. This high mortality rate explained the notable HIV treatment cascade issues in Thailand. An important reason is HIV-related stigma still poses significant barriers for Thai PLWH to access healthcare and carry out health-protective behaviors to engage in care, including adherence to medications. The purpose of this study is to culturally adapt and evaluate the feasibility of a 4 weekly 2-hour group-based stigma reduction intervention protocol to promote health engagement. The scientific premise is, Buddhist-Thai culture provides a unique cultural context for Thai PLWH to understand HIV stigma and sufferings. Our hypothesis is that Thai PLWH will display lower internal stigma and more care engagement following the intervention. This study addresses the critical need to optimize care engagement through addressing HIV stigma within the local cultural contexts. Our long-term goal is comprehensive, culturally-sensitive stigma reduction intervention for Thai PLWH. We will conduct a mixed-methods study with two study phases. In Phase 1, we will collect qualitative data through conducting 30 in-depth interviews with Thai PLWH to revise our cultural conceptualization of stigma process. In Phase 2, we will conduct a pilot randomized-controlled trial (RCT) to test the feasibility, acceptability, and preliminary efficacy of the adapted stigma reduction intervention among 80 Thai PLWH. Innovations include: 1. proposing a cultural approach to examining HIV stigma and intervention, to increase feasibility and acceptability for PLWH in Thailand, and allow for generalizability of findings to other PLWH populations in countries influenced by Buddhist culture; and 2. contributing to further expanding the toolbox of interventions for HIV stigma reduction, given many modern interventions have adapted principles of Buddhist philosophy. Aims are to: 1. Follow the ADAPT-ITT model to culturally adapt an evidence-based stigma reduction intervention (Phase 1). 2. Evaluate the feasibility, acceptability, and preliminary efficacy with a randomized-controlled trial among 80 Thai PLWH and assess outcomes with both subjective and objective measures (Phase 2). 3. Revise and finalize the study protocols for future project operation by documenting emerging difficulties and solutions throughout this pilot project implementation. Culturally-sensitive stigma reduction intervention is a promising intervention to assist Thai PLWH in decreasing internal stigma and promoting health engagement, and hence help address HIV epidemics in this underserved population.

NIH Research Projects · FY 2025 · 2022-09

PROJECT SUMMARY My long-term goal is to reconstruct limbs that have lost function due to injury or disease. To achieve this goal, my research program combines surgical and mechanical design in a paradigm called anatomics, in which body and machine are co-engineered in pursuit of superior bionic performance. In this proposal, I apply an anatomics- centered approach to the surgical treatment of limb pathology. The human body is made up of compliant (“flexible”) structures that are fundamental to basic function. Joints, the highly-compliant structures that link bones together, are perhaps the most important of these structures for human movement. The nuanced relationships between load and deformation (called “compliance”) in joint tissues dictate how internal and external forces are converted to limb motion. Disruption of inherent biological compliance is often devastating to the body’s ability to move in a healthy way. This disruption can occur as a result of injury or disease, or even the reconstructive procedures intended to alleviate limb pathology. In severe cases, the pain and disability caused by changes to limb compliance are so intense, and treatment options so limited, that patients choose to amputate their viable but dysfunctional limb in search of relief. Unfortunately, there is currently no way to correct the compliance of biological joints and tissues when they are disrupted; this creates enormous challenges for the increasing number of patients with limb pathology, who are often left to live with limbs that are viable but non- functional. In response to this need, I propose a novel class of compliant implantable prostheses that would enable pathological joint compliance to be corrected, and function restored. With support from the New Innovator Award, I will advance a novel compliant limb reconstruction (CLR) pipeline capable of generating joint-and- pathology-specific implant mechanics, and apply this pipeline to design implants for two limb pathologies with urgent unmet clinical needs. I will then fabricate and validate these implants, collecting critical data to support early feasibility studies in human subjects. This work will form the foundation for future initiatives supporting refinement of the CLR pipeline, and is the first step toward a research program that uses the approach to target many different pathologies across all of the body’s joints. I expect that the proposed research will transform the clinical paradigm for treatment of limb pathology, opening the door to revolutionary new salvage options that alleviate pain, restore function, and prevent amputation.

NIH Research Projects · FY 2025 · 2022-09

PROJECT SUMMARY Acne vulgaris, or acne, is a disease of the pilosebaceous unit (PSU). Acne is ranked third among chronic skin diseases for causing disability and medical expense and is a major cause of psychological stress in young people. One factor contributing to acne is Cutibacterium acnes, the major bacterial species in the PSU. Using C. acnes as a model to study the interaction between the microbiome and the host immune response, we: 1) previously demonstrated the presence of IL-17 in acne skin lesions and 2) recently discovered that C. acnes phylotypes associated with acne (CA) or healthy skin (CH) differentially regulate the fate of TH17 cells to develop into non-antimicrobial (n-AMTH17) and antimicrobial (AMTH17) subsets. AMTH17 cells release T cell extracellular traps (TETs) and directly kill C. acnes and other bacteria pathogens. To date, the mechanisms by which C. acnes phylotypes induce TETs and their biological impact in acne are unknown. Therefore, our proposed research is innovative because we will define the immune landscape of the acne lesions, provide mechanistic insights into the biological impact of TH17-TET formation in acne, and identify novel immune pathways and potential biomarkers that can be targeted for acne therapy. This is important as future strategies could be developed to modulate TH17 function. Additionally, maintaining the balance among the different phylotypes of C. acnes may represent a strategy for novel probiotic design. The identification of C. acnes ligands will further elucidate the specificity of host receptors involved in microbial surveillance and lead to the development of novel therapeutic approaches skin diseases caused by dysbiosis. to control acne and other human Our central hypothesis is that innate activation of TH17 cells leads to induction of antimicrobial mechanisms, including TETs, which contribute to host defense against C. acnes and other bacteria. To elucidate this, we will determine the antimicrobial mechanisms of AMTH17 cells against C. acnes (Aim 1), investigate the role of AMTH17 cells in acne inflammation (Aim 2), and identify the C. acnes ligands that induce AMTH17 differentiation (Aim 3). Our preliminary findings support the premise that healthy skin commensals are critical to the education of our immune system and our overall defense against pathogens. Our strategy will include: classical immunological techniques involving T cell cloning to dissect the immune effector functions that underlie TH17-mediated antimicrobial host defense; microbiome sequencing of C. acnes phylotypes that inhabit donor biopsies to define how interactions within the skin microbiome and the host immune response influences acne development; high-resolution time-lapse imaging to define mechanisms of TET release and chromatin dynamics that occur during TET formation; scanning electron microscopy to delimit extracellular trap formation in human T cells; and state-of-the-art single cell RNA-seq experiments to compute T cell gene signatures and to define the T cell types and immune circuits present in acne lesions. Additional state-of-the- art methodologies include the use of high affinity capture of cellular interactomes, coupled with mass spectrometry-based proteomics, lipidomics and carbohydrate HPAEC-PAD analysis to identify C. acnes ligands and endogenous complexes. This contribution is significant as, our studies will make significant conceptual advances in our understanding of T cell–antimicrobial defense mechanisms, and allow major advances in the understanding of the immune networks in acne that can be targeted for therapy

NIH Research Projects · FY 2025 · 2022-09

PROJECT SUMMARY Abdominal cancers are a devastating cause of morbidity and mortality worldwide. For example, hepatocellular carcinoma (HCC) has a grim five-year survival rate of less than 20% and is the fastest rising cause of cancer- related deaths in the U.S. Early and accurate diagnosis is crucial, as curative treatment is feasible by surgical resection and/or focal ablation. Compared to surgery, focal ablation reduces hospital stay, increases preservation of surrounding normal tissues, and decreases treatment-related morbidities. However, focal ablation still faces critical limitations in applicability and effectiveness due to inadequate image guidance and procedural accuracy provided by current approaches. Consequently, there is a pressing need to establish new minimally invasive interventions to improve the diagnosis and treatment of abdominal cancers. Conventional abdominal interventions rely on image guidance by ultrasound and/or computed tomography (CT), which can fail to provide sufficient visualization of the cancerous lesions. In addition, CT utilizes ionizing radiation and cannot be used for real-time imaging throughout an intervention. Magnetic resonance imaging (MRI) has crucial advantages that make it ideal for real-time guidance of abdominal interventions: it is the best and/or only way to visualize HCC and several types of abdominal cancers, has no ionizing radiation, and has the potential for real- time imaging of abdominal organs that are constantly in motion. However, current real-time MRI suffers from compromises in image quality, time latency, and difficulties in tracking the devices and tissue targets during motion. Furthermore, the narrow physical space of MRI scanners severely impedes the physician’s access to the patient inside the scanner during imaging. As a result, current MRI-guided interventions require cumbersome workflows that hamper the accuracy and efficiency. The objective of this proposal is to overcome these challenges and enable real-time MRI-guided abdominal interventions. The interdisciplinary research team will leverage synergistic innovations in (1) real-time MRI and computer-aided guidance methods, (2) MRI-compatible robotics, and (3) computer-aided feedback control methods and interactive user interfaces to create a new real-time MRI-guided robotic system. The system will be evaluated in programmable dynamic tissue phantoms and in vivo pig liver models to achieve safe, accurate, and efficient needle placement in moving targets – the foundation for all abdominal interventions. This new robotic system will enable next-generation real-time MRI-guided interventions that can positively impact the diagnosis and treatment of patients with liver tumors and abdominal cancers.

NIH Research Projects · FY 2024 · 2022-09

Project Summary Chronic inflammation has emerged as a potential pathway linking low-socioeconomic status (SES) with disease risk; however, the development of SES disparities in inflammatory risk from adolescence to adulthood is not well understood and there remains uncertainty over the underlying pathways. This transitional period often involves normative changes in social relationships and sleep behavior. Given that psychosocial stress and sleep disruption have both been implicated in inflammatory pathways, the transition from adolescence to adulthood may be an ideal developmental period to assess SES associations with inflammation and elucidate the psychosocial and biobehavioral factors that may underlie these associations. The present study will utilize two independent datasets to assess SES links with inflammation at multiple levels, i.e., via circulating levels of inflammatory markers and via gene expression of inflammatory pathways. The research will identify potential psychosocial factors (i.e., social isolation, stress, discrimination) and biobehavioral factors (i.e., changes in sleep duration and quality) that may explain how SES creates risk for a pro-inflammatory state. Data from the first study were collected as a part of a longitudinal study of adolescent health and experiences, in which N=350 youth were followed from the 10th/11th grade into 3-years post-high school. Adolescents reported on psychosocial experiences, measured sleep via actigraphy for 8 nights, and provided dried blood spot (DBS) samples to assess inflammation. Data from the second study will be collected from N=150 young adults of diverse socioeconomic backgrounds at three time points throughout the first year of college, in which participants report on psychosocial experiences during the transition to college, report on their sleep duration and quality, and provide a DBS sample. The two datasets will be used to address three aims: 1) investigate the relationship between SES and inflammation across the transition from adolescence to adulthood, 2) identify psychosocial experiences that link SES with inflammation and 3) examine the role of sleep in the association between SES and inflammation. It is hypothesized that low-SES will be significantly associated with inflammatory risk, and that low-SES youth will show greater increases in inflammation over time. Secondly, it is hypothesized that low-SES will be associated with adverse psychosocial experiences and that these experiences will statistically mediate associations between SES and inflammation. Finally, it is hypothesized that low-SES will be associated with poorer quality sleep, and that disruptions to sleep will statistically mediate associations between SES and inflammation. Findings from this work will contribute to the literature’s understanding of the biologic embedding of SES in health and can be used to inform interventions aimed at reducing health risk for low-SES youth.

NIH Research Projects · FY 2026 · 2022-09

PROJECT SUMMARY The proposed study will investigate midlife women's relationships and support exchanges with their late- adolescent and adult children, as well as with other relatives and non-relatives, and the implications of these relationships and exchanges for women's psychosocial well-being in a rural sub-Saharan setting. The study will leverage and expand upon a unique panel database consisting of five rounds of survey and qualitative data collected from rural women between 2006 and 2018 as part of the project Men's Migrations and Women's Lives in Mozambique. We propose to extend this existing panel by conducting two new waves of survey and qualitative data collection three years apart. The new data will focus on material, instrumental, and socio- emotional support exchanges between panel participants and their children, relatives, in-laws, and non- relatives and on panel participants' life satisfaction, happiness, self-efficacy, depression, anxiety, and related psychosocial outcomes. The analyses of the dynamics of social interactions and exchanges and of their consequences for women's psychosocial well-being between the two proposed waves will integrate the existing panel data on participants' marital and reproductive trajectories, experience of husband's labor migration, history of co-residence with children and investment in their health and education, as well as changes in women's physical health and economic conditions, to elicit longer-term processes that shape the outcomes of interest. The project will be carried out by an experienced bi-national multidisciplinary team with complementary expertise and a long record of successful research collaboration. The results of the study will contribute to greater understanding of midlife rural women's health and well-being in rapidly changing resource-limited patriarchal settings and will inform policies aimed at improving the welfare of this large and vulnerable population segment.

NIH Research Projects · FY 2025 · 2022-09

Project Summary/Abstract In an innovative scientific partnership between researchers, the UC Office of the President (UCOP), and Intermountain Healthcare, we will leverage existing electronic health record (EHR), insurance claims and DPP cohort data to examine the long-term effectiveness and cost-effectiveness of the Diabetes Prevention Program (DPP), as well as barriers and facilitators of participation in DPP in real-world settings. We proposed a rigorous evaluation using diverse data sources from the University of California (UC), which is a multi-campus university system and one of the largest employers in the State of California, and Intermountain Healthcare, which is a three-state regional health network. We will create a merged multi- ethnic and geographically diverse electronic cohort of adults at-risk of developing type 2 diabetes who enrolled in DPP and propensity-matched controls who did not enroll in DPP. We will include all DPP delivery models that have been in existence for nearly a decade in both systems. To assess the effectiveness of real-world DPP delivery, we will examine percent weight change at 5-years follow-up among adults at risk for developing type 2 diabetes, comparing those who completed DPP with those who did not enroll, and also comparing those who started but did not complete DPP with those who did not enroll (primary outcome). Secondary outcomes will examine changes in cardiovascular risk factors (e.g., blood pressure, tobacco use), rates of incident type 2 diabetes and diabetes-related healthcare service utilization and related costs. To assess the cost-effectiveness of real-world DPP delivery, we will estimate cost per case of type 2 diabetes prevented and cost per quality-adjusted life years (QALYs) gained at 5-years follow-up. We will also examine whether long-term effectiveness and cost-effectiveness vary by several factors, including DPP entry criteria (e.g., blood test vs. risk test), program delivery mode, social determinants of health, age group, or race and ethnicity. To examine barriers and facilitators to DPP participation, we will survey a representative subset of DPP participants and non-participants. We will leverage our team's expertise in DPP evaluation and track record of collaboration, and we will work closely with the coordinating center to carry out this comprehensive multi-site evaluation study. Findings from this study will inform future UC System and Intermountain Healthcare strategies addressing obesity and type 2 diabetes prevention, as well as dissemination of effective strategies to other large university systems, healthcare systems and employers.

NIH Research Projects · FY 2024 · 2022-09

Quantitative image features (QIFs) such as radiomic and deep features hold enormous potential to improve the detection, diagnosis, and treatment assessment of a wide range of diseases. Generated from clinically acquired Computed Tomography (CT) scans, QIFs represent small pixel-wise changes that may be early indicators of disease progression. However, detecting these changes is complicated by variations in how CT scans are acquired and reconstructed. Ensuring repeatable and reproducible QIFs is necessary for developing predictive models that achieve consistent performance across different clinical settings. This project's premise is that QIFs are sensitive to CT parameters such as radiation dose level, slice thickness, reconstruction kernel, and reconstruction method. The combined interactions among these parameters result in unique image conditions, each yielding its own QIF value. Moreover, some clinical tasks and algorithms are more sensitive to differences in QIF values than others. We hypothesize that a systematic, task-dependent framework to characterize the impact of variability in CT parameters and effectively mitigate them will result in more consistent QIF values and the performance of prediction models. Three interrelated innovations will be pursued in this work: 1) a novel framework for characterizing the impact of different acquisition and reconstruction parameters on QIFs and ML models using patient scans with known clinical outcomes in multiple domains; 2) a systematic approach for selecting an optimal mitigation technique and evaluating the impact of normalization; and 3) an open-source software toolkit that formalizes the process of CT normalization, addressing real- world use cases developed by academic and industry collaborators. In Aim 1, we will evaluate how multiple CT parameters influence QIF values and model performance. Utilizing metrics of agreement and a heat map- based visualization, we will determine under which image acquisition and reconstruction conditions the QIFs and model performance are consistent. In Aim 2, we will assess and enhance normalization techniques for mitigating the impact of differences in acquisition and reconstruction, targeting the set of imaging conditions that are most relevant to a clinical task. In Aim 3, we will engage a spectrum of external stakeholders to guide the development and adoption of a software toolkit called CT-NORM. Three distinct clinical domains will drive our efforts: lung nodule detection (which relies on identifying small regions of high contrast differences to identify nodules), interstitial lung disease quantification (which depends on characterizing texture differences), and ischemic core assessment (which relies on detecting low contrast differences in brain tissue). CT-NORM will provide the scientific community with an approach and a unified toolkit to characterize and mitigate the impact of reconstruction and acquisition parameters on QIFs and prediction model performance. By addressing critical sources of variability, we will improve the process of generating QIFs and facilitate the discovery of precise and reproducible imaging phenotypes of disease.

NIH Research Projects · FY 2026 · 2022-09

Project Summary The goal of this project is to better understand the regulation and function of RNA derived from retrotransposable elements (RTEs) in Alzheimer’s disease (AD), with a focus on double-stranded RNAs (dsRNAs). RTEs occupy roughly 40% of the human genome. They constitute a major subgroup of transposons, defined as genomic sequences that mobilize using a ‘copy-and-paste’ mechanism where an RNA intermediate is involved. To date, most RTEs have lost the ability to mobilize to new locations, at least in normal physiological conditions. However, these elements may still retain regulatory activities through expression of RTE-derived RNAs. This functional aspect is particularly relevant in the human brain, where RTE expression is highest compared to other tissues. Given the multi-copy nature of each family of RTEs, their transcripts often form dsRNA structures, resulted from repetitive sequence content, bi-directional transcription or natural sense-antisense transcript pairs. Numerous studies have shown that aberrant expression of cellular dsRNAs is related to the pathogenesis of various human diseases. Recently, increasing evidence supports the existence of enhanced RNA expression from RTEs in neurodegenerative diseases, including AD. This expression leads to accumulation of dsRNAs in neurons, which is correlated with, for example, loss of nuclear TDP-43 or burden of tau tangles. As a result of dsRNA accumulation, type I IFN response may be elicited in neurons, which may contribute to AD pathogenesis. In this project, we aim to determine the identity and origin of AD-relevant dsRNAs derived from RTEs and experimentally validate their functional relevance in neurons. In addition, we will examine the impact of RNA-binding proteins (including ADAR1) on RTE-derived dsRNAs and their functional relevance to AD. This work will allow a previously unattained level of understanding of the regulation and function of RTE-derived dsRNAs in AD and provide new insights to better understand RTE-related disease mechanisms.

NIH Research Projects · FY 2025 · 2022-09

PROJECT ABSTRACT The accumulation of epidemiologic evidence on the roles that policies, systems and environments (PSE) play in influencing health behaviors such as eating and physical activity has led to increased interest in applying the socio-ecological framework and community-engaged approaches to the development of “multi- level interventions” targeting at-risk communities. Evaluation of such innovative interventions, often to address social determinants of health and reduce health disparities, is often challenged as it may be impractical to use the `gold-standard' cluster randomized trial design. Further, the social and behavioral science theories that provide the foundation for the development of interventions may be overlooked when efforts are made to scale- up an intervention. Systems science methods, which have been used to investigate complex causal mechanisms, have been proposed as an alternative for evaluating such interventions. However, their application, which typically involves computational modeling, requires researchers from disparate disciplines to integrate their knowledge and skills at a level that can be difficult to attain. The proposed summer research education program aims to create a learning environment that will support the training of researchers from diverse disciplines to collaborate effectively with each other and with community stakeholders, with the goal of accelerating the translation of research into practice. Specifically, over three summers, it will (i) provide 75 researchers (pre-docs, postdocs, investigators) interested in addressing social determinants of health, with the basic knowledge and skills necessary for applying systems science and data science methods, while also (ii) providing more advanced knowledge and skills to apply either of these methods as well as foundational knowledge of social and behavioral science theories and approaches, to researchers in quantitative methods-focused disciplines (such as math, computer science, biostatistics). In addition, this program will also (iii) provide a three-week practicum to 30 of the 75 trainees who are interested in gaining hands-on experience in working with large datasets. The proposed program will consist of two components: (i) a 3-week curriculum consisting of virtual didactic sessions with learning activities; and (ii) a 3-week practicum for a subset of trainees who will work closely with each other to build and refine agent-based models and interpret results for policy-makers with the engagement of stakeholders. The recruitment and selection plan will be developed with an equity lens, and with an Advisory Committee providing guidance and oversight. To create the learning environment for this training program, we will select applicants to create a cohort that is also diverse in academic background and lived experiences.

NIH Research Projects · FY 2025 · 2022-09

PROJECT SUMMARY This project builds on the scientific premise of understanding the precise molecular mechanisms involved in the development of right ventricular failure (RVF) secondary to pulmonary hypertension (PH). PH-RVF is a significant prognostic determinant of morbidity and mortality in PH and is characterized by remodeling and fibrosis. Despite the importance of RV function in PH, the mechanistic details of RVF secondary to PH remain elusive. Although current therapies targeting pulmonary vasculature do offer some functional improvement for PH patients, yet no approved therapies are available till date that directly target the failing RV. The goal of this project is to highlight specific molecular mechanisms responsible for remodeling and fibrosis in the RV that may be targeted as novel therapeutic strategies for PH-induced RVF. This proposal utilizes state-of-the-art RV bulk-RNA sequencing analysis from two pre-clinical rat models of severe PH highlighting endothelial-to-mesenchymal-transition (EndMT) as the top upregulated pathway and Snai1 (Snail) as a novel network hub promoting the development of EndMT and fibrosis in RVF via Snai1-LOXL2-CTGF axis. This proposal tests the hypothesis that PH-RVF is associated with EndMT and fibrosis governed by Snai1-LOXL2-CTGF axis through chromatin remodeling in the RV. Targeting Snai1 and/or LOXL2 could serve as novel therapeutic strategies for PH-RVF. The proposal has the following aims: Aim 1. Determine the mechanistic role of Snai1-LOXL2-CTGF axis in regulating RV EndMT in PH-RVF in vivo and in vitro. Aim 2. Determine the mechanistic role of Snai1-LOXL2-CTGF axis in regulating RV fibrosis in PH-RVF in vivo and in vitro. Aim 3. Investigate the mechanistic basis of Snai1 and/or LOXL2 knockdown as novel therapeutic strategies for PH-RVF in vivo and in vitro. The proposed studies are significant, since they will highlight the importance of targeting Snai1 and its related network in vivo and in vitro to inhibit EndMT and fibrosis and rescue RVF. The proposed studies are innovative, since they will employ tissue/cell- specific analysis to identify and characterize novel therapeutic targets that are highly regulated by tissue/cell- specific Snai1/LOXL2 knockdown/overexpression in the RVs of rats with PH-induced RVF (in vivo studies) as well as Snai1/LOXL2 knockdown/overexpression in human coronary artery endothelial cells, and human cardiac fibroblasts (in vitro studies). Upon completion, the proposed studies will have identified and addressed the current gap in knowledge in the molecular basis of development of PH-induced RVF. The investigations will yield important insights into the role of Snai1 and its co-partners in RV remodeling in RVF and may lead to development of novel RV-specific therapeutic strategies.

NIH Research Projects · FY 2025 · 2022-09

Project Summary/ Abstract: Drug adverse events have been estimated to contribute to 16% of healthcare spending in the US, and less than 10% of new treatments reach the clinic, suggesting we need better models for anticipating drug effects. Intriguingly, cells have multiplexed, and cascading effects in response to stimuli, such as drug therapies. For instance, a drug stimulus can induce multiple outcomes including modifying disease symptoms or causing undesirable side-effects, and further, drugs can influence proteins downstream of their intended targets. Yet, drug therapies are not routinely designed with their multiplexed, cascading effects or multi- protein binding properties in mind because we lack quantitative mechanistic models for understanding these interesting cellular effects. Protein-protein interaction (PPI) network models have identified downstream proteins associated with diseases and side-effects relevant to drug therapies, demonstrating the ability to link multiplexed outcomes with a stimulus. These associative models are insufficient for prioritizing drug target proteins because PPI networks lack mechanistic detail to describe the magnitude or relative contribution of cellular responses to multi-protein stimuli. The overall objective of this research is to derive quantitative relationships between multi- protein stimuli and downstream response proteins using clinical data. This proposal is innovative because of the context-specific interaction (CSI) approach: compared to other PPI network approaches, CSI analysis demonstrated a 50% and 76-95% improvement in prediction accuracy and precision, respectively, when identifying severe adverse events using PPIs downstream of drug targets and the emphasis on clinical data integration. This approach emphasized the importance of learning PPI network parameters using phenotype- specific data to better understand all network-associated phenotypes and demonstrated the feasibility of deriving mechanistic details in PPI network models. This program is significant because it stands to reduce overall side- effects and increase therapeutic efficacy by advancing a better understanding of cellular multiplexed responses to multi-protein stimuli. Further, I have demonstrated consistent productivity and the flexibility and adaptability in pursuing research projects to establish a distinguished independent career.

NIH Research Projects · FY 2026 · 2022-09

PROJECT SUMMARY/ABSTRACT We previously reported (2) on the soluble amyloid precursor protein alpha (sAPPα)-enhancing effects of tropisetron (F03). Highly brain-permeable F03 is approved in 49 countries for the treatment of post-operative nausea and vomiting (PONV) and is a multifunctional ligand: it is a potent 5-HT3 serotonin receptor (5-HT3R) antagonist (Ki ~ 3 nM), a partial α7 nicotinic acetylcholine receptor (α7nAChR) agonist (Ki ~ 450 nM), and binds to the extracellular domain of amyloid precursor protein (eAPP). In our studies, we found F03 increases sAPPα and also significantly decreases the phospho-tau (p-tau)/total tau (t-tau) ratio in two Alzheimer's disease (AD) mouse models. We show that F03 can also reduce corticotropin-releasing factor (CRF) induced p-tau/tau increase in vitro. Hyperphosphorylation of tau leads to toxic tau oligomers and ultimately formation of neurofibrillary tangles (NFTs) in AD brain and is closely correlated with cognitive decline (34); thus, decreasing tau phosphorylation is a critical target for new therapeutic approaches for AD and tauopathies. Based on reports that sAPPα reduces the p-tau/t-tau ratio through suppression of activity of the kinase GSK3β (9), we plan to assess the ability of our sAPPα enhancers to reduce the p-tau/t-tau ratio in vitro and in vivo. A key goal of the project is to identify optimized small molecule sAPPα-enhancing, p-tau/t-tau lowering compounds that improve cognition in murine AD models, for further development as a novel therapy for AD. An additional goal would be to elucidate the underlying mechanism of action (MOA) of sAPPα enhancement and related reduction in the p- tau/t-tau ratio. In Aim 1, we would test F03 and analogs we have in-hand as well as new analogs from Aim 2 in SH-SY5Y cells and 3xTg-AD primary neurons to establish EC50s for sAPPα enhancement and p-tau/t-tau decreases. Prioritized compounds would be evaluated for receptor binding and APP binding. Tertiary testing will be in induced pluripotent stem cell (iPSC)-derived neurons from AD subjects and includes synaptic spine density quantification. In Aim 2, medicinal chemistry would be used to design new chemical entity (NCE) analogs in a iterative fashion with receptor and APP binding along with enhanced drug-like properties and oral brain permeability. In Aim 3, ADME studies on analogs include solubility, microsomal stability, protein binding, parallel artificial membrane permeability assay (PAMPA) analysis, and in vivo pharmacokinetics (PK). Optimal candidates would undergo safety (including hERG) and off-target panel profiling along with analyses of effect on other kinases and of tau phosphorylation sites. In Aim 4 in vivo testing, including acute studies on select candidates to evaluate effect on intracerebroventricular (ICV) delivered CRF induced p-tau/t-tau increases in brain in 3xTg-AD mice. Active candidates would be tested in chronic 4-week efficacy studies in 3xTg-AD and ApoE4-5XFAD AD model mice. Readouts would include behavioral and histopathology analysis, including hippocampal neurite load and neuronal spine density. Biochemical outcomes include p-tau/t-tau ratio, sAPPα and Aβ. Mechanistic studies by phosphoproteomics used for correlations between readouts and cognition.

NIH Research Projects · FY 2025 · 2022-09

Project Summary/Abstract Patients with end-stage kidney disease (ESKD), who use hemodialysis as their kidney replacement method, require vascular access in the form of an arteriovenous fistula, arteriovenous graft, or central venous catheter to receive life-sustaining hemodialysis. Providers and patients face selection of a vascular access type without adequate evidence of likely outcomes. To overcome this key barrier, the goal of this R01 proposal is to optimize the patient experience of vascular access decision-making by a) developing an interactive, evidence-based guide to vascular access outcomes that incorporates a prognostic model for short and long-term outcomes of vascular access and b) identifying best practices for utilization of the guide during the clinician-patient encounter. To do so, a novel, large-scale data source that contains multi-institutional granular data regarding vascular access operations and their short and long-term outcomes will be created by linking the Vascular Quality Initiative Vascular Access Registry (VQIVAR) to the United States Renal Data Systems Registry (USRDS) and Medicare claims. Prognostic models will be developed, by using traditional statistical approaches (e.g., logistic regression, Kaplan-Meier estimates) and machine learning methods (e.g., Bayesian networks, random forests) to predict outcomes that are meaningful to patients (revision procedures, repeat vascular access operation), and compare these models using technical metrics (e.g., sensitivity/specificity). The best-performing models will be selected and tested for external validity in a local UCLA population. Simultaneously, a mixed-methods approach will be used to engage patient and provider stakeholders to collaborate in creation and implementation of the proposed guide to vascular access outcomes, assessing the: 1) preferred means of communication with the clinician during the vascular access decision-making encounter; 2) optimal methods for incorporating the guide (including the prognostic model) into the decision-making process; and 3) satisfaction with iterative versions of the guide. The Specific Aims are: Aim 1 Design, evaluate and test the externally validity of the prognostic models for hemodialysis vascular access outcomes, to be used in vascular access decision-making, generated from VQIVAR data linked to USRDS and Medicare claims using statistical and machine learning methods and validated in a UCLA cohort with model calibration. Aim 2 Identify best practices for the clinician-patient vascular access decision-making interaction by using a mixed methods approach that includes individual interviews, direct observation, and quantitative satisfaction and preference scales. Aim 3 Create and refine an interactive guide to vascular access outcomes based on the best-performing prognostic model created in Aim 1, that allows for personalization with each patient’s characteristics, by engaging patient and provider stakeholders in an iterative fashion to incorporate their feedback and arrive at a final guide.

NIH Research Projects · FY 2025 · 2022-09

PROJECT SUMMARY The adult human brain is comprised of numerous cell types exhibiting specific transcriptomic and epigenomic signatures associated with their spatial location, connectivity, and function. Although systematic efforts are underway to characterize cell types in the adult human brain, the transitional cell types and cell states in developing human brains are not fully defined. Our project will use epigenomic and three-dimensional (3D) chromosomal architectural information to classify developmental cell types and identify key regulatory dynamics that may underlie cellular lineage commitment and maturation. Single-cell DNA methylation and chromatin accessibility profiles have been successfully used to de novo identify distinct cell types in developing and adult brains. The single-nucleus joint profiling of DNA methylation and chromatin conformation by sn-m3C-seq provides unique information to identify enhancer-gene looping and provides a resource to link genetic variants associated with neuropsychiatric disorders to genes. Cell types identified with epigenomic information will be integrated with spatial transcriptomic signatures using our innovative single-cell joint profiling method of transcriptome and DNA methylation snmCT-seq. We will determine the spatial and temporal dynamics of developing brain cell types using multiplexed RNA in situ and Digital Spatial Profiling (DSP) assays. We will apply state-of-the-art approaches to integrate multiple data modalities to identify progenitor and transitional cell types, lineage-specific regulatory elements, and enhancer-gene 3D interactions. We will construct cell-type- specific predictive models of cellular trajectory and gene regulation during brain development by integrating transcription factor-gene interaction information with time- and pseudotime-series genomics data. The cell type and regulatory elements catalog of human brain development generated by our project will aid the identification of developing brain cell types involved in neuropsychiatric disorders and regulatory regions susceptible to perturbation by disease-associated variants.

NIH Research Projects · FY 2025 · 2022-09

Project Summary Temperature is critical to all life activities and regulates biological processes at various levels. Cells not only detect temperature changes through their unique temperature-sensitive molecular machineries but also adapt with appropriate responses to maintain their inherent functions. Despite the fundamental involvement of temperature in biological processes, the molecular mechanism by which cells produce and use heat is largely unknown. Our aim to develop atomically precise nanoarchitectures as both stimulators and thermometers to study various temperature-sensitive molecules down to the sub-cellular level. The study will investigate spatio-temporal temperature variations, including organelle-specific thermogenesis to develop the intrinsic connections between temperature and cell functions. The proposed study will combine nanoarchitectures with our recent demonstrated ultrafast optical spectroscopy, structural characterizations, and atomistic-to-microscope multiscale modeling framework to design, measure, and analyze the molecular-level thermal-biological interactions. The new approach will quantify intracellular temperature changes at the microscopic level in large difference from those assumed at a water environment at the macroscopic level. We expect the employment of new nano-architecture will uncover novel mechanisms and fundamental understandings of intracellular temperature-assisted functions.

NIH Research Projects · FY 2025 · 2022-09

ABSTRACT / PROJECT SUMMARY Overall The overall goal of the UCLA/UCSD Acne Center for Research Translation (Acne CORT) is to bring together scientists with expertise in different aspects of microbiology, lipid metabolism and immunology to engage in translational research to study the interaction between the microbiota, lipid metabolism and the host immune response in acne. Cutibacterium acnes is the dominant bacterium of the pilosebaceous unit (PSebU), the initial site where acne lesions develop, and is considered to be one of the key contributing factors in the pathogenesis of acne. The UCLA/UCSD Research Project is based on our recent findings using transcriptomics, metagenomics and lipidomics, establishing the goal to link together these diverse biologic responses into a model that may explain the pathogenesis of acne. The UCLA/UCSD Research Project (Modlin, Gallo), “Acne: a disease of lipid metabolism, microbiome and the immune response”, will initially focus studies on the role of TREM2 macrophages and adipogenic fibroblasts in the pathogenesis of acne. Our preliminary data using from single cell RNA-sequencing (scRNA-seq) and spatial-sequencing identified these two cell populations as over-represented in acne lesions, with gene programs reflecting their link to altered lipid metabolism. The project investigators will obtain acne biopsy specimens (Hata, Kim), then address the link between the immune response in acne lesions to the microbiome and lipid metabolism. The Research Project will be supported by a UCLA Bioinformatics Core (Pellegrini, Yang) to analyze scRNA-seq and spatial-seq of acne lesions, a UCSD Microbiology and Metagenomics Core (Gallo, O'Neill) to isolate and characterize C. acnes strains, and lipidomics analysis (Bensinger, UCLA) of biopsy specimens and key cell types derived in vitro. Ultimately, the Bioinformatics Core will use mergeomics to combine data from transcriptomics, metagenomics and lipidomics to create a network model of the pathogenesis of acne. The Administrative Core will facilitate research interactions between the projects with: i) research seminars, an Enrichment Program and Advisory Board meeting; ii) a Pilot and Feasibility Project Program to extend the research base; and, iii) plans to utilize the resources and environment at UCLA/UCSD including core facilities, the UCLA and UCSD Clinical and Translational Science Awards (CTSA) Program Centers as well as the mentoring programs for medical and graduate students, postdoctoral fellows, dermatology trainees and junior faculty. The proposed studies will provide new insights into how lipid metabolism and the skin microbiome shape cutaneous immune responses contributing to inflammation, with the potential for intervention in skin disease.

NIH Research Projects · FY 2024 · 2022-08

PROJECT SUMMARY / ABSTRACT This proposal is to develop and implement methods for quantifying geographic disparities, within Sub-Saharan African countries, in the opportunity for people living with HIV (PLHIV) to access antiretroviral therapy (ART); and to identify optimal strategies for reducing such disparities. The methods that we will develop constitute a novel analytic framework, which we will use to complete our three Specific Aims: (1) First, we will develop a spatial interaction model which can be applied in any SSA country to estimate the geographic opportunity to access ART and to identify disparities in this opportunity. We will apply the model to Malawi, which has one of the most severe HIV epidemics in the world, and where our previous studies have shown that PLHIV face substantial geographic disparities in accessing HIV care. To do so we will analyze a series of datasets, including the nationwide Malawi Population-based HIV Impact Assessments [MPHIAs]; the MPHIAs were collected in 2015/16 and 2020/21, spanning a period when ART coverage increased substantially. (2) Second, we will quantify the geographic relationship between the opportunity to access ART and its actual utilization, and determine the degree to which this relationship changed between the two timepoints. (3) Third, we will use our modeling framework in further analyses of the MPHIA 2020/21 dataset with the objective of identifying optimal strategies to reduce geographic disparities in the opportunity to access ART; both through the location of new healthcare facilities (HCFs) and through the allocation of additional supplies of ART. We will conduct these studies through a U.S.-Malawi collaborative team.