EMPIRICAL INVESTIGATION OF PRIVATIZATION PROCESS IN PAKISTAN: EVIDENCE FROM STATISTICAL EXPERIENCE

Why privatization processes fall short to deliver expected result in Pakistan. To answer this question, current study aims is to examine the privatization process in the Pakistan. The privatization process is dividing into four sections, privatization policy, buyer selection in the privatization process, assets evaluation and the factors affecting the development after privatization. The main objective of the study is to see the influence of development after privatization on the relationship between privatization policy, buyer selection in the privatization process, assets Evaluation and Privatization process improvement. Detailed survey based on the structured questionnaire is enquired through random sampling technique. Structured Equation Model (SEM) has been used for making an analysis. The finding of the study concludes that development process privatization mediates the between privatization policy, buyer selection in the privatization process, assets Evaluation and Privatization process improvement.  The findings of the study advocate that the privatization policy, buyer selection process, assets evaluation methods must be in line with the objective of government and line ministry. This effort may help for getting the optimum level of result from privatization process

EMPIRICAL INVESTIGATION OF PRIVATIZATION PROCESS IN PAKISTAN: EVIDENCE FROM STATISTICAL EXPERIENCE

Why privatization processes fall short to deliver expected result in Pakistan. To answer this question, current study aims is to examine the privatization process in the Pakistan. The privatization process is dividing into four sections, privatization policy, buyer selection in the privatization process, assets evaluation and the factors affecting the development after privatization. The main objective of the study is to see the influence of development after privatization on the relationship between privatization policy, buyer selection in the privatization process, assets Evaluation and Privatization process improvement. Detailed survey based on the structured questionnaire is enquired through random sampling technique. Structured Equation Model (SEM) has been used for making an analysis. The finding of the study concludes that development process privatization mediates the between privatization policy, buyer selection in the privatization process, assets Evaluation and Privatization process improvement.  The findings of the study advocate that the privatization policy, buyer selection process, assets evaluation methods must be in line with the objective of government and line ministry. This effort may help for getting the optimum level of result from privatization process

Effects of Renin-Angiotensin system blockers on outcomes from COVID-19: a systematic review and meta-analysis of randomised controlled trials

Background and aims: Randomized controlled trials (RCTs) have assessed the effects of renin–angiotensin system (RAS) blockers in adults with coronavirus disease 2019 (COVID-19). This meta-analysis provides estimates of the safety and efficacy of treatment with (vs. without) RAS blockers from these trials. Methods: PubMed, Web of Science, and ClinicalTrials.gov were searched (1 March–12 April 2023). Event/patient numbers were extracted, comparing angiotensin-converting enzyme (ACE) inhibitor/angiotensin-receptor blocker (ARB) treatment with no treatment, for the outcomes: intensive care unit (ICU) admission, mechanical ventilation, vasopressor use, acute kidney injury (AKI), renal replacement therapy (RRT), acute myocardial infarction, stroke/transient ischaemic attack, heart failure, thromboembolic events, and all-cause death. Fixed-effects meta-analysis estimates were pooled. Results: Sixteen RCTs including 3492 patients were analysed. Compared with discontinuation of RAS blockers, continuation was not associated with increased risk of ICU [risk ratio (RR) 0.96, 0.66–1.41], ventilation (RR 0.77, 0.55–1.09), vasopressors (RR 0.92, 0.58–1.44), AKI (RR 1.01, 0.40–2.56), RRT (RR 1.01, 0.46–2.21), or thromboembolic events (RR 1.07, 0.36–3.19). RAS blocker initiation was not associated with increased risk of ICU (RR 0.71, 0.47–1.08), ventilation (RR 1.12, 0.91–1.38), AKI (RR 1.28, 0.89–1.86), RRT (RR 1.66, 0.89–3.12), or thromboembolic events (RR 1.20, 0.06–23.70), although vasopressor use increased (RR 1.27, 1.02–1.57). The RR for all-cause death in the continuation/discontinuation trials was 1.24 (0.80–1.92), and 1.22 (0.96–1.55) in the initiation trials. In patients with severe/critical COVID-19, RAS blocker initiation increased the risk of all-cause death (RR 1.31, 1.01–1.72). Conclusion: ACE inhibitors and ARBs may be continued in non-severe COVID-19 infection, where indicated. Conversely, initiation of RAS blockers may be harmful in critically ill patients. PROSPERO registration number: CRD42023408926

The trans-ancestral genomic architecture of glycemic traits

Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 x 10(-8)), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution. A trans-ancestry meta-analysis of GWAS of glycemic traits in up to 281,416 individuals identifies 99 novel loci, of which one quarter was found due to the multi-ancestry approach, which also improves fine-mapping of credible variant sets.Peer reviewe

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Funding GMP, PN, and CW are supported by NHLBI R01HL127564. GMP and PN are supported by R01HL142711. AG acknowledge support from the Wellcome Trust (201543/B/16/Z), European Union Seventh Framework Programme FP7/2007–2013 under grant agreement no. HEALTH-F2-2013–601456 (CVGenes@Target) & the TriPartite Immunometabolism Consortium [TrIC]-Novo Nordisk Foundation’s Grant number NNF15CC0018486. JMM is supported by American Diabetes Association Innovative and Clinical Translational Award 1–19-ICTS-068. SR was supported by the Academy of Finland Center of Excellence in Complex Disease Genetics (Grant No 312062), the Finnish Foundation for Cardiovascular Research, the Sigrid Juselius Foundation, and University of Helsinki HiLIFE Fellow and Grand Challenge grants. EW was supported by the Finnish innovation fund Sitra (EW) and Finska Läkaresällskapet. CNS was supported by American Heart Association Postdoctoral Fellowships 15POST24470131 and 17POST33650016. Charles N Rotimi is supported by Z01HG200362. Zhe Wang, Michael H Preuss, and Ruth JF Loos are supported by R01HL142302. NJT is a Wellcome Trust Investigator (202802/Z/16/Z), is the PI of the Avon Longitudinal Study of Parents and Children (MRC & WT 217065/Z/19/Z), is supported by the University of Bristol NIHR Biomedical Research Centre (BRC-1215–2001) and the MRC Integrative Epidemiology Unit (MC_UU_00011), and works within the CRUK Integrative Cancer Epidemiology Programme (C18281/A19169). Ruth E Mitchell is a member of the MRC Integrative Epidemiology Unit at the University of Bristol funded by the MRC (MC_UU_00011/1). Simon Haworth is supported by the UK National Institute for Health Research Academic Clinical Fellowship. Paul S. de Vries was supported by American Heart Association grant number 18CDA34110116. Julia Ramierz acknowledges support by the People Programme of the European Union’s Seventh Framework Programme grant n° 608765 and Marie Sklodowska-Curie grant n° 786833. Maria Sabater-Lleal is supported by a Miguel Servet contract from the ISCIII Spanish Health Institute (CP17/00142) and co-financed by the European Social Fund. Jian Yang is funded by the Westlake Education Foundation. Olga Giannakopoulou has received funding from the British Heart Foundation (BHF) (FS/14/66/3129). CHARGE Consortium cohorts were supported by R01HL105756. Study-specific acknowledgements are available in the Additional file 32: Supplementary Note. The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute; the National Institutes of Health; or the U.S. Department of Health and Human Services.Peer reviewedPublisher PD

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Publisher Copyright: © 2022, The Author(s).Background: Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results: To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions: Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.Peer reviewe

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Abstract Background Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Background: Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results: To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions: Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk

The power of genetic diversity in genome-wide association studies of lipids

Elevated blood lipid levels are heritable risk factors of cardiovascular disease with varying prevalence worldwide due to differing dietary patterns and medication use(1). Despite advances in prevention and treatment, particularly through the lowering of low-density lipoprotein cholesterol levels(2), heart disease remains the leading cause of death worldwide(3). Genome-wide association studies (GWAS) of blood lipid levels have led to important biological and clinical insights, as well as new drug targets, for cardiovascular disease. However, most previous GWAS(4–23) have been conducted in European ancestry populations and may have missed genetic variants contributing to lipid level variation in other ancestry groups due to differences in allele frequencies, effect sizes, and linkage-disequilibrium (LD) patterns(24). Here we conduct a multi-ancestry genome-wide genetic discovery meta-analysis of lipid levels in ~1.65 million individuals, including 350,000 of non-European ancestries. We quantify the gain in studying non-European ancestries and provide evidence to support expanding recruitment into new ancestries even with relatively smaller sample sizes. We find that increasing diversity rather than studying additional European ancestry individuals results in substantial improvements in fine-mapping functional variants and portability of polygenic prediction (evaluated in N~295,000 from 6 ancestries), with modest gains in the number of discovered loci and ancestry-specific variants. As GWAS expands its emphasis beyond identifying genes and fundamental biology towards using genetic variants for preventive and precision medicine(25), we anticipate that increased participant diversity will lead to more accurate and equitable(26) application of polygenic scores in clinical practice