Next-generation equipment and procedures for combined resonant column and torsional shear testing

In this dissertation, work aimed at developing next-generation equipment and procedures for combined resonant column and torsional shear (RCTS) testing are detailed. The work in this dissertation covers three key areas of RCTS testing that need improvement to reach the next level of RCTS testing. The first area involved improvement in measurement resolution with modern control and monitoring equipment. Concurrently, original software was written to enhance the efficiency, accuracy, and repeatability of the test. The second area involved advancing concepts for evaluating and modeling nonlinear behavior of soil, which was done in part by using raw RCTS test data collected and stored from 2013-2017. The third area involved evaluating and modifying the design of the existing RCTS device to accommodate higher levels of shearing strain and provide higher loading capacity. First, when testing at small shear strains (< 0.001%) within the linear-elastic range of soils, very small excitation voltages must be used and very small voltages are recorded from the RCTS sensors. Obtaining accurate measurements in the linear-elastic range is critically important when testing at low confining pressures (in the range of 0.1 to 1 atm). In traditional RCTS data acquisition systems, very small recorded voltages are lost due to limited resolution of the control and monitoring subsystems. Concurrently, the very small recorded voltages are generally heavily contaminated by environmental background noise that invalidates the automated process for reducing raw data into engineering results. Control and monitoring equipment and software were developed that can enhance the measurement and data reduction process when making low-strain measurements. Second, testing of soil in the nonlinear shear strain range (typically greater than 0.001%) is a complex process that departs from traditional dynamic models for single-degree-of-freedom (SDOF) systems. Traditionally, RCTS results from testing in the nonlinear shear strain range involve slight adaptation of traditional SDOF models to obtain nonlinear relationships. Nonlinear dynamics model concepts were taken from literature and adapted to better understand and model nonlinear behavior of soils in RCTS testing. Furthermore, development of nonlinear models at moderate strains help to bridge the spectrum of soil testing which tends to divide into evaluating soils at small to moderate strains (< 0.2%) or at large strains (≥ 0.2%). Third, when testing soils at large shearing strains (> 0.2%), traditional RCTS systems are physically or electronically limited. At higher confining pressures (> 2 atm) where soils become quite stiff, the traditional RCTS control equipment is electronically incapable of driving enough torque output to strain soils in shear above desired levels (> 0.1%). At low confining pressures ( 0.5%). An RCTS testing device was designed that has a torque-output capacity at least three times greater than a traditional RCTS device and an allowable degree of twist that can generate shearing strains above 1%.Civil, Architectural, and Environmental Engineerin

Type 2 Diabetes Variants Disrupt Function of SLC16A11 through Two Distinct Mechanisms

Type 2 diabetes (T2D) affects Latinos at twice the rate seen in populations of European descent. We recently identified a risk haplotype spanning SLC16A11 that explains ∼20% of the increased T2D prevalence in Mexico. Here, through genetic fine-mapping, we define a set of tightly linked variants likely to contain the causal allele(s). We show that variants on the T2D-associated haplotype have two distinct effects: (1) decreasing SLC16A11 expression in liver and (2) disrupting a key interaction with basigin, thereby reducing cell-surface localization. Both independent mechanisms reduce SLC16A11 function and suggest SLC16A11 is the causal gene at this locus. To gain insight into how SLC16A11 disruption impacts T2D risk, we demonstrate that SLC16A11 is a proton-coupled monocarboxylate transporter and that genetic perturbation of SLC16A11 induces changes in fatty acid and lipid metabolism that are associated with increased T2D risk. Our findings suggest that increasing SLC16A11 function could be therapeutically beneficial for T2D. Video Abstract [Figure presented] Keywords: type 2 diabetes (T2D); genetics; disease mechanism; SLC16A11; MCT11; solute carrier (SLC); monocarboxylates; fatty acid metabolism; lipid metabolism; precision medicin

Rare coding variants in PLCG2, ABI3, and TREM2 implicate microglial-mediated innate immunity in Alzheimer's disease

We identified rare coding variants associated with Alzheimer’s disease (AD) in a 3-stage case-control study of 85,133 subjects. In stage 1, 34,174 samples were genotyped using a whole-exome microarray. In stage 2, we tested associated variants (P<1×10-4) in 35,962 independent samples using de novo genotyping and imputed genotypes. In stage 3, an additional 14,997 samples were used to test the most significant stage 2 associations (P<5×10-8) using imputed genotypes. We observed 3 novel genome-wide significant (GWS) AD associated non-synonymous variants; a protective variant in PLCG2 (rs72824905/p.P522R, P=5.38×10-10, OR=0.68, MAFcases=0.0059, MAFcontrols=0.0093), a risk variant in ABI3 (rs616338/p.S209F, P=4.56×10-10, OR=1.43, MAFcases=0.011, MAFcontrols=0.008), and a novel GWS variant in TREM2 (rs143332484/p.R62H, P=1.55×10-14, OR=1.67, MAFcases=0.0143, MAFcontrols=0.0089), a known AD susceptibility gene. These protein-coding changes are in genes highly expressed in microglia and highlight an immune-related protein-protein interaction network enriched for previously identified AD risk genes. These genetic findings provide additional evidence that the microglia-mediated innate immune response contributes directly to AD development

Genetic associations at 53 loci highlight cell types and biological pathways relevant for kidney function.

Reduced glomerular filtration rate defines chronic kidney disease and is associated with cardiovascular and all-cause mortality. We conducted a meta-analysis of genome-wide association studies for estimated glomerular filtration rate (eGFR), combining data across 133,413 individuals with replication in up to 42,166 individuals. We identify 24 new and confirm 29 previously identified loci. Of these 53 loci, 19 associate with eGFR among individuals with diabetes. Using bioinformatics, we show that identified genes at eGFR loci are enriched for expression in kidney tissues and in pathways relevant for kidney development and transmembrane transporter activity, kidney structure, and regulation of glucose metabolism. Chromatin state mapping and DNase I hypersensitivity analyses across adult tissues demonstrate preferential mapping of associated variants to regulatory regions in kidney but not extra-renal tissues. These findings suggest that genetic determinants of eGFR are mediated largely through direct effects within the kidney and highlight important cell types and biological pathways

Stroke genetics informs drug discovery and risk prediction across ancestries

Previous genome-wide association studies (GWASs) of stroke — the second leading cause of death worldwide — were conducted predominantly in populations of European ancestry1,2. Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis3, and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach4, we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry5. Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries