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

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

Funding Information: 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 : 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. 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

Handheld Electrochemical Workstation for Serum Albumin Measurement

This paper presents a novel handheld electrochemical workstation for serum albumin measurement. The system consists of a multi-path potentiostat module which performs electrochemical measurements on disposable test strip. The strip provides a port for applying blood sample. The test strip consists of 3 electrochemical cells for redundancy and parallel testing. The 3 sets of 3 electrodes (Working, Reference and Counter electrodes) are screen printed on a Polyethylene Terephthalate (PET) substrate. The system provides the unique capability of performing Cyclic Voltammetry and Chrono Amperometry measurements in three parallel paths. The system is very generic and flexible, with user defined inputs for voltage, sweep rate and time through 5 inch capacitive touch screen. The experimental results can be stored on micro SD card and the data is accessible with USB or Bluetooth interface. This paper reports an extensive characterization of system through several tests conducted on standard redox solution. The system is then validated for human serum albumin measurement, using clinical samples. This is the first ever point of care handheld diagnostic device in the world for human serum albumin measurement

Creatinine-Iron Complex and Its Use in Electrochemical Measurement of Urine Creatinine

A non-enzymatic electrochemical technique for creatinine sensing is presented, exploiting iron binding property of creatinine. Disposable carbon printed electrodes layered with FeCl3 coated cotton fiber membranes are used to sense creatinine from 10 to 245 mg/dl, on clinical urine samples. The energy-dispersive X-ray spectroscopy analysis confirms the presence of Fe(III) dry chemistry on cotton membrane. Creatinine binding with Fe(III) is verified with UV analysis, with a corresponding decrease in Fe(III) reduction current in cyclic voltammetry. The disposable test strips are interfaced with multi-potentiostat point of care (POC) hand-held device, working in amperometry mode. The results obtained on POC biosensors demonstrate good correlation (R-2 = 0.91) with Jaffe method laboratory gold standard. The intra-assay variability is less than 7.1%. The statistical bias as revealed from the Bland-Altman analysis indicates that the POC results are within 95% confidence interval. This POC device does not require any sample preparation step and provides sample to result in less than a minute. FeCl3 sensing chemistry is robust against urine albumin interference, which is especially significant for accurate estimation of albumin to creatinine ratio. The non-enzymatic nature of disposable test strips results in highly stable and robust operation of the POC device over a large range of temperature variations

Aza-heterocyclic Receptors for Direct Electron Transfer Hemoglobin Biosensor

Direct Electron Transfer biosensors, facilitating direct communication between the biomolecule of interest and electrode surface, are preferable compared to enzymatic and mediator based sensors. Although hemoglobin (Hb) contains four redox active iron centres, direct detection is not possible due to inaccessibility of iron centres and formation of dimers, blocking electron transfer. Through the coordination of iron with aza-heterocyclic receptors-pyridine and imidazole-we report a cost effective, highly sensitive and simple electrochemical Hb sensor using cyclic voltammetry and chronoamperometry. The receptor can be either in the form of liquid micro-droplet mixed with blood or dry chemistry embedded in paper membrane on top of screen printed carbon electrodes. We demonstrate excellent linearity and robustness against interference using clinical samples. A truly point of care technology is demonstrated by integrating disposable test strips with handheld reader, enabling finger prick to result in less than a minute

Application of a Nanotechnology-Based, Point-of-Care Diagnostic Device in Diabetic Kidney Disease.

Introduction Early detection of diabetes mellitus (DM) and diabetic kidney disease (DKD) is important for preventing end-stage renal failure and reducing cardiovascular complications. Availability of a validated point-of-care (PoC) device that can measure various DKD markers would be useful in this respect, especially in resource-poor parts of the world. Methods We validated a novel nanotechnology-based multianalyte PoC device (minimally invasive and does not require trained medical personnel) against laboratory gold standard tests for the detection of 5 biomarkers related to management of DM and DKD. The prospective study was funded by an International Society of Nephrology American Nephrologists of Indian Origin grant in 2 phases: (i) proof of concept: random samples were tested for the analytes with the PoC device and correlated with the laboratory gold standard; and (ii) clinical validation in a well-characterized cohort of patients. A nonenzymatic- and nonantibody-based electrochemical PoC device for quantitative measurement of markers-glycosylated hemoglobin (HbA), hemoglobin, serum albumin, microalbuminuria, urine creatinine, and albumin-to-creatinine ratio-was developed and used in this study. The disposable strips were interfaced with a multipotentiostat hand-held PoC device (3.7-V rechargeable lithium battery, 5-inch touch screen, Bluetooth enabled) working in amperometry mode, which provided the results in <1 minute. Data were analyzed using linearity plots and Bland-Altman difference plot analysis. Results A total of 4717 individuals were screened during the study (phase 1: 2576 and phase 2: 2141.) In phase 2, samples were tested in 529 subjects (346 females)-120 subjects with type 1 DM, 255 subjects with type 2 DM, 54 subjects without DM, 400 subjects with stage 2 chronic kidney disease, and 30 subjects with stage 3 chronic kidney disease. Conclusion A nanotechnology-based PoC device for quantitative measurement of HbA, hemoglobin, serum albumin, microalbuminuria, and the urine albumin-to-creatinine ratio was developed for detection of early DKD and showed excellent correlation between the device and laboratory results. This device has the potential for early detection of DM and/or DKD, especially in remote communities in underserved areas of the world where prevalence of diabetes is rapidly increasing

A saturated map of common genetic variants associated with human height

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40–50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes1. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel2) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10–20% (14–24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries.</p

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