2023 Judge Horace J. Johnson, Jr. Lecture on Race, Law and Policy with Vanita Gupta

School of Law Dean Peter Bo Rutledge gave introductory remarks, while law faculty members Clare Norins and John Meixner co-moderated, and SPIA Dean Matthew Auer provided closing remarks. Vanita Gupta is the 19thUnited States Associate Attorney General and serves as the third-ranking official at the Department of Justice. Associate Attorney General Gupta supervises multiple litigating divisions within the Department of Justice, including the Civil Division, Civil Rights Division, Antitrust Division, Tax Division, and Environmental and Natural Resources Division. She also oversees the grant making components of the Department, including the Office of Justice Programs, the Office on Violence Against Women, and the Office of Community Oriented Policing Services; and supervises the Office for Access to Justice, Office of Information Policy, the Community Relations Service, the Executive Office for United States Trustees, the Foreign Claims Settlement Commission, and the Service members and Veterans Initiative. Associate Attorney General Gupta previously served as the President and Chief Executive Officer of the Leadership Conference on Civil and Human Rights, the nation’s oldest and largest coalition of non-partisan civil rights organizations in the United States. Before serving in that capacity, from October 15, 2014, to January 20, 2017, Associate Attorney General Gupta served as Acting Assistant Attorney General and Head of the Department of Justice’s Civil Rights Division. Appointed by President Barack Obama as the chief civil rights prosecutor for the United States, Associate Attorney General Gupta advanced a wide range of civil rights enforcement matters. Prior to her tenure leading the Civil Rights Division, Associate Attorney General Gupta served as Deputy Legal Director and the Director of the Center for Justice at the American Civil Liberties Union (ACLU). In addition to managing litigation, Associate Attorney General Gupta created and led the ACLU’s Smart Justice Campaign aimed at promoting bipartisan justice reform while keeping communities safe. She began her legal career as an attorney at the NAACP Legal Defense & Educational Fund. Associate Attorney General Gupta graduated magna cum laude from Yale University and received her law degree from New York University School of Law, where later she taught a civil rights litigation clinic for several year

Identifying the spatial and temporal dynamics of molecularly-distinct glioblastoma sub-populations

Glioblastomas (GBMs) are the most aggressive primary brain tumours and have no known cure. Each individual tumour comprises multiple sub-populations of genetically-distinct cells that may respond differently to targeted therapies and may contribute to disappointing clinical trial results. Image-localized biopsy techniques allow multiple biopsies to be taken during surgery and provide information that identifies regions where particular sub-populations occur within an individual GBM, thus providing insight into their regional genetic variability. These sub-populations may also interact with one another in a competitive or cooperative manner; it is important to ascertain the nature of these interactions, as they may have implications for responses to targeted therapies

Global simulation of tropospheric chemistry at 12.5 km resolution : Performance and evaluation of the GEOS-Chem chemical module (v10-1) within the NASA GEOS Earth system model (GEOS-5 ESM)

We present a full-year online global simulation of tropospheric chemistry (158 coupled species) at cubed-sphere c720 ( ∼ 12.5×12.5 km2) resolution in the NASA Goddard Earth Observing System Model version 5 Earth system model (GEOS-5 ESM) with GEOS-Chem as a chemical module (G5NR-chem). The GEOS-Chem module within GEOS uses the exact same code as the offline GEOS-Chem chemical transport model (CTM) developed by a large atmospheric chemistry research community. In this way, continual updates to the GEOS-Chem CTM by that community can be seamlessly passed on to the GEOS chemical module, which remains state of the science and referenceable to the latest version of GEOS-Chem. The 1-year G5NR-chem simulation was conducted to serve as the Nature Run for observing system simulation experiments (OSSEs) in support of the future geostationary satellite constellation for tropospheric chemistry. It required 31 wall-time days on 4707 compute cores with only 24 % of the time spent on the GEOS-Chem chemical module. Results from the GEOS-5 Nature Run with GEOS-Chem chemistry were shown to be consistent to the offline GEOS-Chem CTM and were further compared to global and regional observations. The simulation shows no significant global bias for tropospheric ozone relative to the Ozone Monitoring Instrument (OMI) satellite and is highly correlated with observations spatially and seasonally. It successfully captures the ozone vertical distributions measured by ozonesondes over different regions of the world, as well as observations for ozone and its precursors from the August-September 2013 Studies of Emissions, Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) aircraft campaign over the southeast US. It systematically overestimates surface ozone concentrations by 10 ppbv at sites in the US and Europe, a problem currently being addressed by the GEOS-Chem CTM community and from which the GEOS ESM will benefit through the seamless update of the online code

Discovery of Diverse Small Molecule Chemotypes with Cell-Based PKD1 Inhibitory Activity

Protein kinase D (PKD) is a novel family of serine/threonine kinases regulated by diacylglycerol, which is involved in multiple cellular processes and various pathological conditions. The limited number of cell-active, selective inhibitors has historically restricted biochemical and pharmacological studies of PKD. We now markedly expand the PKD1 inhibitory chemotype inventory with eleven additional novel small molecule PKD1 inhibitors derived from our high throughput screening campaigns. The in vitro IC50s for these eleven compounds ranged in potency from 0.4 to 6.1 µM with all of the evaluated compounds being competitive with ATP. Three of the inhibitors (CID 1893668, (1Z)-1-(3-ethyl-5-methoxy-1,3-benzothiazol-2-ylidene)propan-2-one; CID 2011756, 5-(3-chlorophenyl)-N-[4-(morpholin-4-ylmethyl)phenyl]furan-2-carboxamide; CID 5389142, (6Z)-6-[4-(3-aminopropylamino)-6-methyl-1H-pyrimidin-2-ylidene]cyclohexa-2,4-dien-1-one) inhibited phorbol ester-induced endogenous PKD1 activation in LNCaP prostate cancer cells in a concentration-dependent manner. The specificity of these compounds for PKD1 inhibitory activity was supported by kinase assay counter screens as well as by bioinformatics searches. Moreover, computational analyses of these novel cell-active PKD1 inhibitors indicated that they were structurally distinct from the previously described cell-active PKD1 inhibitors while computational docking of the new cell-active compounds in a highly conserved ATP-binding cleft suggests opportunities for structural modification. In summary, we have discovered novel PKD1 inhibitors with in vitro and cell-based inhibitory activity, thus successfully expanding the structural diversity of small molecule inhibitors available for this important pharmacological target

Meta-Analysis of Gene Level Tests for Rare Variant Association

The vast majority of connections between complex disease and common genetic variants were identified through meta-analysis, a powerful approach that enables large sample sizes while protecting against common artifacts due to population structure, repeated small sample analyses, and/or limitations with sharing individual level data. As the focus of genetic association studies shifts to rare variants, genes and other functional units are becoming the unit of analysis. Here, we propose and evaluate new approaches for performing meta-analysis of rare variant association tests, including burden tests, weighted burden tests, variable threshold tests and tests that allow variants with opposite effects to be grouped together. We show that our approach retains useful features of single variant meta-analytic approaches and demonstrate its utility in a study of blood lipid levels in ∼18,500 individuals genotyped with exome arrays

Genome-wide Association Study of Platelet Count Identifies Ancestry-Specific Loci in Hispanic/Latino Americans

Platelets play an essential role in hemostasis and thrombosis. We performed a genome-wide association study of platelet count in 12,491 participants of the Hispanic Community Health Study/Study of Latinos by using a mixed-model method that accounts for admixture and family relationships. We discovered and replicated associations with five genes (ACTN1, ETV7, GABBR1-MOG, MEF2C, and ZBTB9-BAK1). Our strongest association was with Amerindian-specific variant rs117672662 (p value = 1.16 × 10−28) in ACTN1, a gene implicated in congenital macrothrombocytopenia. rs117672662 exhibited allelic differences in transcriptional activity and protein binding in hematopoietic cells. Our results underscore the value of diverse populations to extend insights into the allelic architecture of complex traits

Mosaic Chromosomal alterations in Blood across ancestries Using Whole-Genome Sequencing

Megabase-scale mosaic chromosomal alterations (mCAs) in blood are prognostic markers for a host of human diseases. Here, to gain a better understanding of mCA rates in genetically diverse populations, we analyzed whole-genome sequencing data from 67,390 individuals from the National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine program. We observed higher sensitivity with whole-genome sequencing data, compared with array-based data, in uncovering mCAs at low mutant cell fractions and found that individuals of European ancestry have the highest rates of autosomal mCAs and the lowest rates of chromosome X mCAs, compared with individuals of African or Hispanic ancestry. Although further studies in diverse populations will be needed to replicate our findings, we report three loci associated with loss of chromosome X, associations between autosomal mCAs and rare variants in DCPS, ADM17, PPP1R16B and TET2 and ancestry-specific variants in ATM and MPL with mCAs in cis

A Framework For Detecting Noncoding Rare-Variant associations of Large-Scale Whole-Genome Sequencing Studies

Large-scale whole-genome sequencing studies have enabled analysis of noncoding rare-variant (RV) associations with complex human diseases and traits. Variant-set analysis is a powerful approach to study RV association. However, existing methods have limited ability in analyzing the noncoding genome. We propose a computationally efficient and robust noncoding RV association detection framework, STAARpipeline, to automatically annotate a whole-genome sequencing study and perform flexible noncoding RV association analysis, including gene-centric analysis and fixed window-based and dynamic window-based non-gene-centric analysis by incorporating variant functional annotations. In gene-centric analysis, STAARpipeline uses STAAR to group noncoding variants based on functional categories of genes and incorporate multiple functional annotations. In non-gene-centric analysis, STAARpipeline uses SCANG-STAAR to incorporate dynamic window sizes and multiple functional annotations. We apply STAARpipeline to identify noncoding RV sets associated with four lipid traits in 21,015 discovery samples from the Trans-Omics for Precision Medicine (TOPMed) program and replicate several of them in an additional 9,123 toPMed samples. We also analyze five non-lipid toPMed traits