Large-Scale Multi-Omics Studies Provide New Insights into Blood Pressure Regulation

Recent genome-wide association studies uncovered part of blood pressure’s heritability. However, there is still a vast gap between genetics and biology that needs to be bridged. Here, we followed up blood pressure genome-wide summary statistics of over 750,000 individuals, leveraging comprehensive epigenomic and transcriptomic data from blood with a follow-up in cardiovascular tissues to prioritise likely causal genes and underlying blood pressure mechanisms. We first prioritised genes based on coding consequences, multilayer molecular associations, blood pressure-associated expression levels, and coregulation evidence. Next, we followed up the prioritised genes in multilayer studies of genomics, epigenomics, and transcriptomics, functional enrichment, and their potential suitability as drug targets. Our analyses yielded 1880 likely causal genes for blood pressure, tens of which are targets of the available licensed drugs. We identified 34 novel genes for blood pressure, supported by more than one source of biological evidence. Twenty-eight (82%) of these new genes were successfully replicated by transcriptome-wide association analyses in a large independent cohort (n = ~220,000). We also found a substantial mediating role for epigenetic regulation of the prioritised genes. Our results provide new insights into genetic regulation of blood pressure in terms of likely causal genes and involved biological pathways offering opportunities for future translation into clinical practice

Effects of climate change on grassland biodiversity and productivity: the need for a diversity of models

There is increasing evidence that the impact of climate change on the productivity of grasslands will at least partly depend on their biodiversity. A high level of biodiversity may confer stability to grassland ecosystems against environmental change, but there are also direct effects of biodiversity on the quantity and quality of grassland productivity. To explain the manifold interactions, and to predict future climatic responses, models may be used. However, models designed for studying the interaction between biodiversity and productivity tend to be structurally different from models for studying the effects of climatic impacts. Here we review the literature on the impacts of climate change on biodiversity and productivity of grasslands. We first discuss the availability of data for model development. Then we analyse strengths and weaknesses of three types of model: ecological, process-based and integrated. We discuss the merits of this model diversity and the scope for merging different model types

Using Mendelian randomisation to identify opportunities for type 2 diabetes prevention by repurposing medications used for lipid management

Background: Maintaining a healthy lifestyle to reduce type 2 diabetes (T2D) risk is challenging and additional strategies for T2D prevention are needed. We evaluated several lipid control medications as potential therapeutic options for T2D prevention using tissue-specific predicted gene expression summary statistics in a two-sample Mendelian randomisation (MR) design. Methods: Large-scale European genome-wide summary statistics for lipids and T2D were leveraged in our multi-stage analysis to estimate changes in either lipid levels or T2D risk driven by tissue-specific predicted gene expression. We incorporated tissue-specific predicted gene expression summary statistics to proxy therapeutic effects of three lipid control medications [i.e., statins, icosapent ethyl (IPE), and proprotein convertase subtilisin/kexin type-9 inhibitors (PCSK-9i)] on T2D susceptibility using two-sample Mendelian randomisation (MR). Findings: IPE, as proxied via increased FADS1 expression, was predicted to lower triglycerides and was associated with a 53% reduced risk of T2D. Statins and PCSK-9i, as proxied by reduced HMGCR and PCSK9 expression, respectively, were predicted to lower LDL-C levels but were not associated with T2D susceptibility. Interpretation: Triglyceride lowering via IPE may reduce the risk of developing T2D in populations of European ancestry. However, experimental validation using animal models is needed to substantiate our results and to motivate randomized control trials (RCTs) for IPE as putative treatment for T2D prevention. Funding: Only summary statistics were used in this analysis. Funding information is detailed under Acknowledgments. © 2022Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Determination of the E2/M1 Ratio in the \gamma N \to \Delta(1232) Transition from a Simultaneous Measurement of p(\vec{\gamma},p)\pi^0 and p(\vec{\gamma},\pi^+)n

Tagged linearly polarized photons have been used at the Mainz Microtron MAMI for simultaneous measurements of the p(\vec{\gamma},p)\pi^0 and p(\vec{\gamma},\pi^+)n reaction channels to study the \gamma N \to \Delta(1232) transition. The energy dependence of the magnetic dipole M_{1+}^{3/2} and electric quadrupole E_{1+}^{3/2} amplitudes have been extracted from these data in the photon energy range from 270 to 420 MeV. The E2/M1 ratio for the \gamma N \to \Delta(1232) transition has been determined to be - (2.5+-0.1_{stat}+-0.2_{sys}) % at the resonance position delta_{33}=90^0.Comment: 25 pages Latex including 13 postscript figures submitted for publication in Phys. Rev.

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P &lt; 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.</p

MEMS 411: B2 Striker Group Final Design Report

Design a golf striker that can accomplish all the holes set forth by the ASME 2023 design competition and could be attached to a robot without major design modifications

Large-Scale Multi-Omics Studies Provide New Insights into Blood Pressure Regulation

Recent genome-wide association studies uncovered part of blood pressure's heritability. However, there is still a vast gap between genetics and biology that needs to be bridged. Here, we followed up blood pressure genome-wide summary statistics of over 750,000 individuals, leveraging comprehensive epigenomic and transcriptomic data from blood with a follow-up in cardiovascular tissues to prioritise likely causal genes and underlying blood pressure mechanisms. We first prioritised genes based on coding consequences, multilayer molecular associations, blood pressure-associated expression levels, and coregulation evidence. Next, we followed up the prioritised genes in multilayer studies of genomics, epigenomics, and transcriptomics, functional enrichment, and their potential suitability as drug targets. Our analyses yielded 1880 likely causal genes for blood pressure, tens of which are targets of the available licensed drugs. We identified 34 novel genes for blood pressure, supported by more than one source of biological evidence. Twenty-eight (82%) of these new genes were successfully replicated by transcriptome-wide association analyses in a large independent cohort (n = ~220,000). We also found a substantial mediating role for epigenetic regulation of the prioritised genes. Our results provide new insights into genetic regulation of blood pressure in terms of likely causal genes and involved biological pathways offering opportunities for future translation into clinical practice

Discovery of 318 novel loci for type-2 diabetes and related micro- and macrovascular outcomes among 1.4 million participants in a multi-ethnic meta-analysis.

We investigated type 2 diabetes (T2D) genetic susceptibility in a multi-ethnic meta-analysis of 228,499 cases and 1,178,783 controls in the Million Veteran Program, DIAMANTE, Biobank Japan, and other studies. We identified 558 autosomal and 10 X-chromosome T2D-associated variants, of which 286 autosomal and 7 X-chromosome variants were previously unreported. Ancestry-specific analyses identified 25 additional novel T2D-susceptibility variants. Transcriptome-wide association analysis detected 3,568 T2D-associations with T2D-colocalized genetically predicted gene expression of 804 genes in 52 tissues, of which 687 are novel. Fifty-four of these genes are known to interact with FDA-approved drugs and chemical compounds. T2D polygenic risk score was strongly associated with increased risk of T2D-related retinopathy, and showed evidence for association with chronic kidney disease (CKD), neuropathy, and peripheral artery disease (PAD). We investigated the genetic etiology of T2D-related vascular outcomes in MVP and observed statistical SNP-T2D interactions at 13 variants, including 3 for coronary heart disease, 1 for PAD, 2 for stroke, 4 for retinopathy, 2 for CKD, and 1 for neuropathy. Our findings may identify potential novel therapeutic targets for T2D and genomic pathways that link T2D and its vascular outcomes.This research was also supported by funding from: the Department of Veterans Affairs award I01-BX003362 (P.S.T. and K.M.C) and the VA Informatics and Computing Infrastructure (VINCI) VA HSR RES 130457 (S.L.D) B.F.V. acknowledges support for this work from the NIH/NIDDK (DK101478), the NIH/NHGRI (HG010067) and a Linda Pechenik Montague Investigator award. K.M.C, S.M.D, J.M.G, C.J.O, L.S.P, and P.S.T. are supported by the VA Cooperative Studies Program. S.M.D. is supported by the Veterans Administration [IK2-CX001780]. D.K. is supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health [T32 HL007734]. L.S.P. is supported in part by VA awards I01-CX001025, and I01CX001737, NIH awards R21DK099716, U01 DK091958, U01 DK098246, P30DK111024, and R03AI133172, and a Cystic Fibrosis Foundation award PHILLI12A0. We thank all study participants for their contribution. Data on T2D have been contributed by investigators from DIAMANTE Consortium, Biobank Japan, Malmö Diet and Cancer Study, PennCath, MedStar, Pakistan Genomic Resource, Penn Medicine Biobank, and Regeneron Genetics Center. Data on stroke were provided by MEGASTROKE investigators, and data on CKD have been contributed by CKDgen investigators. Data on alpha and beta islet cells have been contributed by the HPAP Consortium. Data on coronary artery disease have been contributed by the CARDIoGRAMplusC4D investigators. We thank dr. Josep Maria Mercader and dr. Aaron Leong for careful review and comments

An Exome-wide Association Study for Type 2 Diabetes–Attributed End-Stage Kidney Disease in African Americans

Introduction: Compared with European Americans, African Americans (AAs) are at higher risk for developing end-stage kidney disease (ESKD). Genome-wide association studies (GWAS) have identified >70 genetic variants associated with kidney function and chronic kidney disease (CKD) in patients with and without diabetes. However, these variants explain a small proportion of disease liability. This study examined the contribution of coding genetic variants for risk of type 2 diabetes (T2D)-attributed ESKD and advanced CKD in AAs. Methods: Exome sequencing was performed in 456 AA T2D-ESKD cases, and 936 AA nondiabetic, non-nephropathy control individuals at the discovery stage. A mixed logistic regression model was used for association analysis. Nominal associations (P < 0.05) were replicated in an additional 2020 T2D-ESKD cases and 1121 nondiabetic, non-nephropathy control individuals. A meta-analysis combining 4533 discovery and replication samples was performed. Putative T2D-ESKD associations were tested in additional 1910 nondiabetic ESKD and 219 T2D-ESKD cases, as well as 912 AA nondiabetic non-nephropathy control individuals. Results: A total of 11 suggestive T2D-ESKD associations (P < 1 x 10−4) from 8 loci (PLEKHN1, NADK, RAD51AP2, RREB1, PEX6, GRM8, PRX, APOL1) were apparent in the meta-analysis. Exclusion of APOL1 renal-risk genotype carriers identified 3 additional suggestive loci (OTUD7B, IFITM3, DLGAP5). Rs41302867 in RREB1 displayed consistent association with T2D-ESKD and nondiabetic ESKD (odds ratio: 0.47; P = 1.2 x 10−6 in 4605 all-cause ESKD and 2969 nondiabetic non-nephropathy control individuals). Conclusion: Our findings suggest that coding genetic variants are implicated in predisposition to T2D-ESKD in AAs. Keywords: African Americans, chronic kidney disease, end-stage kidney disease, exome sequencing, genetics, type 2 diabete