ORCID Profile
0000-0001-8776-6719
Current Organisations
Fondazione Human Technopole
,
NHS Blood and Transplant
,
University of Cambridge
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Sociology | Consumption and Everyday Life | Environmental Sociology | Sociology and Social Studies of Science and Technology
Expanding Knowledge through Studies of Human Society | Residential Energy Conservation and Efficiency |
Publisher: Springer Science and Business Media LLC
Date: 10-2018
Publisher: Springer Science and Business Media LLC
Date: 25-11-2027
Publisher: Elsevier BV
Date: 08-2020
Publisher: Cold Spring Harbor Laboratory
Date: 27-09-2021
DOI: 10.1101/2021.09.24.21264079
Abstract: Metabolic biomarker data quantified by nuclear magnetic resonance (NMR) spectroscopy has recently become available in UK Biobank. Here, we describe procedures for quality control and removal of technical variation for this biomarker data, comprising 249 circulating metabolites, lipids, and lipoprotein sub-fractions on approximately 121,000 participants. We identify and characterise technical and biological factors associated with in idual biomarkers and find that linear effects on in idual biomarkers can combine in a non-linear fashion for 61 composite biomarkers and 81 biomarker ratios. We create an R package, ukbnmr, for extracting and normalising the metabolic biomarker data, then use ukbnmr to remove unwanted variation from the UK Biobank data. We make available code for re-deriving the 61 composite biomarkers and 81 ratios, and for further derivation of 76 additional biomarker ratios of potential biological significance. Finally, we demonstrate that removal of technical variation leads to increased signal for genetic and epidemiological studies of the NMR metabolic biomarkers in UK Biobank.
Publisher: Elsevier BV
Date: 03-2011
Publisher: Massachusetts Medical Society
Date: 04-10-2012
Publisher: Springer Science and Business Media LLC
Date: 10-2021
DOI: 10.1038/S41588-021-00944-6
Abstract: Telomeres, the end fragments of chromosomes, play key roles in cellular proliferation and senescence. Here we characterize the genetic architecture of naturally occurring variation in leukocyte telomere length (LTL) and identify causal links between LTL and biomedical phenotypes in 472,174 well-characterized UK Biobank participants. We identified 197 independent sentinel variants associated with LTL at 138 genomic loci (108 new). Genetically determined differences in LTL were associated with multiple biological traits, ranging from height to bone marrow function, as well as several diseases spanning neoplastic, vascular and inflammatory pathologies. Finally, we estimated that, at the age of 40 years, people with an LTL s.d. shorter than the population mean had a 2.5-year-lower life expectancy compared with the group with ≥1 s.d. longer LDL. Overall, we furnish new insights into the genetic regulation of LTL, reveal wide-ranging influences of LTL on physiological traits, diseases and longevity, and provide a powerful resource available to the global research community.
Publisher: Springer Science and Business Media LLC
Date: 10-08-2023
DOI: 10.1186/S13063-023-07473-Z
Abstract: Vasovagal reactions (VVRs) are the most common acute complications of blood donation. Responsible for substantial morbidity, they also reduce the likelihood of repeated donations and are disruptive and costly for blood services. Although blood establishments worldwide have adopted different strategies to prevent VVRs (including water loading and applied muscle tension [AMT]), robust evidence is limited. The Strategies to Improve Donor Experiences (STRIDES) trial aims to reliably assess the impact of four different interventions to prevent VVRs among blood donors. STRIDES is a cluster-randomised cross-over/stepped-wedge factorial trial of four interventions to reduce VVRs involving about 1.4 million whole blood donors enrolled from all 73 blood donation sites (mobile teams and donor centres) of National Health Service Blood and Transplant (NHSBT) in England. Each site (“cluster”) has been randomly allocated to receive one or more interventions during a 36-month period, using principles of cross-over, stepped-wedge and factorial trial design to assign the sequence of interventions. Each of the four interventions is compared to NHSBT’s current practices: (i) 500-ml isotonic drink before donation ( vs current 500-ml plain water) (ii) 3-min rest on donation chair after donation ( vs current 2 min) (iii) new modified AMT ( vs current practice of AMT) and (iv) psychosocial intervention using preparatory materials ( vs current practice of nothing). The primary outcome is the number of in-session VVRs with loss of consciousness (i.e. episodes involving loss of consciousness of any duration, with or without additional complications). Secondary outcomes include all in-session VVRs (i.e. with and without loss of consciousness), all delayed VVRs (i.e. those occurring after leaving the venue) and any in-session non-VVR adverse events or reactions. The STRIDES trial should yield novel information about interventions, singly and in combination, for the prevention of VVRs, with the aim of generating policy-shaping evidence to help inform blood services to improve donor health, donor experience, and service efficiency. ISRCTN: 10412338. Registration date: October 24, 2019.
Publisher: Elsevier BV
Date: 09-2020
Publisher: Cold Spring Harbor Laboratory
Date: 22-10-2022
DOI: 10.1101/2022.10.20.22281120
Abstract: To provide quantitative evidence of the use of polygenic risk scores (PRS) for systematically identifying in iduals for invitation for full formal cardiovascular disease (CVD) risk assessment. 108,685 participants aged 40-69, with measured biomarkers, linked primary care records and genetic data in UK Biobank were used for model derivation and population health modelling. Prioritisation tools using age, PRS for coronary artery disease and stroke, and conventional risk factors for CVD available within longitudinal primary care records were derived using sex-specific Cox models. Rescaling to account for the healthy cohort effect, we modelled the implications of initiating guideline-recommended statin therapy after prioritising in iduals for invitation to a formal CVD risk assessment. 1,838 CVD events were observed over median follow up of 8.2 years. If primary care records were used to prioritise in iduals for formal risk assessment using age- and sex-specific thresholds corresponding to 5% false negative rates then we would capture 65% and 43% events amongst men and women respectively. The numbers of men and women needed to be screened to prevent one CVD event (NNS) are 74 and 140 respectively. In contrast, adding PRS to both prioritisation and formal assessments, and selecting thresholds to capture the same number of events resulted in a NNS of 60 for men and 90 for women. The use of PRS together with primary care records to prioritise in iduals at highest risk of a CVD event for a formal CVD risk assessment can more efficiently prioritise those who need interventions the most than using primary care records alone. This could lead to better allocation of resources by reducing the number of formal risk assessments in primary care while still preventing the same number CVD events.
Publisher: American Medical Association (AMA)
Date: 22-07-2009
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 08-2010
DOI: 10.1161/CIRCGENETICS.109.906180
Abstract: Evidence is sparse about the genetic determinants of major lipids in Pakistanis. Variants (n=45 000) across 2000 genes were assessed in 3200 Pakistanis and compared with 2450 Germans using the same gene array and similar lipid assays. We also did a meta-analysis of selected lipid-related variants in Europeans. Pakistani genetic architecture was distinct from that of several ethnic groups represented in international reference s les. Forty-one variants at 14 loci were significantly associated with levels of HDL-C, triglyceride, or LDL-C. The most significant lipid-related variants identified among Pakistanis corresponded to genes previously shown to be relevant to Europeans, such as CETP associated with HDL-C levels (rs711752 P −13 ), APOA5/ZNF259 (rs651821 P −13 ) and GCKR (rs1260326 P −13 ) with triglyceride levels and CELSR2 variants with LDL-C levels (rs646776 P −9 ). For Pakistanis, these 41 variants explained 6.2%, 7.1%, and 0.9% of the variation in HDL-C, triglyceride, and LDL-C, respectively. Compared with Europeans, the allele frequency of rs662799 in APOA5 among Pakistanis was higher and its impact on triglyceride concentration was greater ( P -value for difference −4 ). Several lipid-related genetic variants are common to Pakistanis and Europeans, though they explain only a modest proportion of population variation in lipid concentration. Allelic frequencies and effect sizes of lipid-related variants can differ between Pakistanis and Europeans.
Publisher: Elsevier BV
Date: 2010
Publisher: Springer Science and Business Media LLC
Date: 08-07-2021
DOI: 10.1038/S41586-021-03767-X
Abstract: The genetic make-up of an in idual contributes to the susceptibility and response to viral infection. Although environmental, clinical and social factors have a role in the chance of exposure to SARS-CoV-2 and the severity of COVID-19 1,2 , host genetics may also be important. Identifying host-specific genetic factors may reveal biological mechanisms of therapeutic relevance and clarify causal relationships of modifiable environmental risk factors for SARS-CoV-2 infection and outcomes. We formed a global network of researchers to investigate the role of human genetics in SARS-CoV-2 infection and COVID-19 severity. Here we describe the results of three genome-wide association meta-analyses that consist of up to 49,562 patients with COVID-19 from 46 studies across 19 countries. We report 13 genome-wide significant loci that are associated with SARS-CoV-2 infection or severe manifestations of COVID-19. Several of these loci correspond to previously documented associations to lung or autoimmune and inflammatory diseases 3–7 . They also represent potentially actionable mechanisms in response to infection. Mendelian randomization analyses support a causal role for smoking and body-mass index for severe COVID-19 although not for type II diabetes. The identification of novel host genetic factors associated with COVID-19 was made possible by the community of human genetics researchers coming together to prioritize the sharing of data, results, resources and analytical frameworks. This working model of international collaboration underscores what is possible for future genetic discoveries in emerging pandemics, or indeed for any complex human disease.
Publisher: Oxford University Press (OUP)
Date: 23-07-2012
DOI: 10.1093/IJE/DYS086
Publisher: Elsevier BV
Date: 08-2014
Publisher: Oxford University Press (OUP)
Date: 03-05-2010
DOI: 10.1093/IJE/DYQ063
Publisher: Wiley
Date: 20-12-2014
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 18-06-2019
DOI: 10.1161/CIRCULATIONAHA.118.038813
Abstract: There is uncertainty about the relevance of animal foods to the pathogenesis of ischemic heart disease (IHD). We examined meat, fish, dairy products, and eggs and risk for IHD in the pan-European EPIC cohort (European Prospective Investigation Into Cancer and Nutrition). In this prospective study of 409 885 men and women in 9 European countries, diet was assessed with validated questionnaires and calibrated with 24-hour recalls. Lipids and blood pressure were measured in a subs le. During a mean of 12.6 years of follow-up, 7198 participants had a myocardial infarction or died of IHD. The relationships of animal foods with risk were examined with Cox regression with adjustment for other animal foods and relevant covariates. The hazard ratio (HR) for IHD was 1.19 (95% CI, 1.06–1.33) for a 100-g/d increment in intake of red and processed meat, and this remained significant after exclusion of the first 4 years of follow-up (HR, 1.25 [95% CI, 1.09–1.42]). Risk was inversely associated with intakes of yogurt (HR, 0.93 [95% CI, 0.89–0.98] per 100-g/d increment), cheese (HR, 0.92 [95% CI, 0.86–0.98] per 30-g/d increment), and eggs (HR, 0.93 [95% CI, 0.88–0.99] per 20-g/d increment) the associations with yogurt and eggs were attenuated and nonsignificant after exclusion of the first 4 years of follow-up. Risk was not significantly associated with intakes of poultry, fish, or milk. In analyses modeling dietary substitutions, replacement of 100 kcal/d from red and processed meat with 100 kcal/d from fatty fish, yogurt, cheese, or eggs was associated with ≈20% lower risk of IHD. Consumption of red and processed meat was positively associated with serum non–high-density lipoprotein cholesterol concentration and systolic blood pressure, and consumption of cheese was inversely associated with serum non–high-density lipoprotein cholesterol. Risk for IHD was positively associated with consumption of red and processed meat and inversely associated with consumption of yogurt, cheese, and eggs, although the associations with yogurt and eggs may be influenced by reverse causation bias. It is not clear whether the associations with red and processed meat and cheese reflect causality, but they were consistent with the associations of these foods with plasma non–high-density lipoprotein cholesterol and for red and processed meat with systolic blood pressure, which could mediate such effects.
Publisher: JMIR Publications Inc.
Date: 10-02-2022
DOI: 10.2196/31885
Abstract: Although the burden of premature myocardial infarction (MI) is high in Malaysia, direct evidence on the determinants of MI in this multi-ethnic population remains sparse. The Malaysian Acute Vascular Events Risk (MAVERIK) study is a retrospective case-control study established to investigate the genomic, lipid-related, and other determinants of acute MI in Malaysia. In this paper, we report the study protocol and early results. By June 2019, we had enrolled approximately 2500 patients with their first MI and 2500 controls without cardiovascular disease, who were frequency-matched by age, sex, and ethnicity, from 17 hospitals in Malaysia. For each participant, serum and whole blood have been collected and stored. Clinical, demographic, and behavioral information has been obtained using a 200-item questionnaire. Tobacco consumption, a history of diabetes, hypertension, markers of visceral adiposity, indicators of lower socioeconomic status, and a family history of coronary disease were more prevalent in cases than in controls. Adjusted (age and sex) logistic regression models for traditional risk factors indicated that current smoking (odds ratio [OR] 4.11, 95% CI 3.56-4.75 P .001), previous smoking (OR 1.34, 95% CI 1.12-1.60 P=.001), a history of high blood pressure (OR 2.13, 95% CI 1.86-2.44 P .001), a history of diabetes mellitus (OR 2.72, 95% CI 2.34-3.17 P .001), a family history of coronary heart disease (OR 1.28, 95% CI 1.07-1.55 P=.009), and obesity (BMI kg/m2 OR 1.19, 95% CI 1.05-1.34 P=.009) were associated with MI in age- and sex-adjusted models. The MAVERIK study can serve as a useful platform to investigate genetic and other risk factors for MI in an understudied Southeast Asian population. It should help to hasten the discovery of disease-causing pathways and inform regionally appropriate strategies that optimize public health action. RR1-10.2196/31885
Publisher: Elsevier BV
Date: 03-2012
Publisher: American Medical Association (AMA)
Date: 20-06-2012
Publisher: Cold Spring Harbor Laboratory
Date: 18-02-2020
DOI: 10.1101/2020.02.17.952788
Abstract: Polygenic scores (PGSs) for blood cell traits can be constructed using summary statistics from genome-wide association studies. As the selection of variants and the modelling of their interactions in PGSs may be limited by univariate analysis, therefore, such a conventional method may yield sub-optional performance. This study evaluated the relative effectiveness of four machine learning and deep learning methods, as well as a univariate method, in the construction of PGSs for 26 blood cell traits, using data from UK Biobank (n=~400,000) and INTERVAL (n=~40,000). Our results showed that learning methods can improve PGSs construction for nearly every blood cell trait considered, with this superiority explained by the ability of machine learning methods to capture interactions among variants. This study also demonstrated that populations can be well stratified by the PGSs of these blood cell traits, even for traits that exhibit large differences between ages and sexes, suggesting potential for disease prevention. As our study found genetic correlations between the PGSs for blood cell traits and PGSs for several common human diseases (recapitulating well-known associations between the blood cell traits themselves and certain diseases), it suggests that blood cell traits may be indicators or/and mediators for a variety of common disorders via shared genetic variants and functional pathways.
Publisher: Springer Science and Business Media LLC
Date: 07-01-2019
DOI: 10.1038/S41380-018-0313-0
Abstract: Smoking is a major heritable and modifiable risk factor for many diseases, including cancer, common respiratory disorders and cardiovascular diseases. Fourteen genetic loci have previously been associated with smoking behaviour-related traits. We tested up to 235,116 single nucleotide variants (SNVs) on the exome-array for association with smoking initiation, cigarettes per day, pack-years, and smoking cessation in a fixed effects meta-analysis of up to 61 studies (up to 346,813 participants). In a subset of 112,811 participants, a further one million SNVs were also genotyped and tested for association with the four smoking behaviour traits. SNV-trait associations with P 5 × 10 −8 in either analysis were taken forward for replication in up to 275,596 independent participants from UK Biobank. Lastly, a meta-analysis of the discovery and replication studies was performed. Sixteen SNVs were associated with at least one of the smoking behaviour traits ( P 5 × 10 −8 ) in the discovery s les. Ten novel SNVs, including rs12616219 near TMEM182 , were followed-up and five of them (rs462779 in REV3L , rs12780116 in CNNM2 , rs1190736 in GPR101 , rs11539157 in PJA1 , and rs12616219 near TMEM182 ) replicated at a Bonferroni significance threshold ( P 4.5 × 10 −3 ) with consistent direction of effect. A further 35 SNVs were associated with smoking behaviour traits in the discovery plus replication meta-analysis (up to 622,409 participants) including a rare SNV, rs150493199, in CCDC141 and two low-frequency SNVs in CEP350 and HDGFRP2 . Functional follow-up implied that decreased expression of REV3L may lower the probability of smoking initiation. The novel loci will facilitate understanding the genetic aetiology of smoking behaviour and may lead to the identification of potential drug targets for smoking prevention and/or cessation.
Publisher: Cold Spring Harbor Laboratory
Date: 31-03-2022
DOI: 10.1101/2022.03.25.22272958
Abstract: Understanding how genetic variants influence disease risk and complex traits (variant-to-function) is one of the major challenges in human genetics. Here we present a model-driven framework to leverage human genome-scale metabolic networks to define how genetic variants affect biochemical reaction fluxes across major human tissues, including skeletal muscle, adipose, liver, brain and heart. As proof of concept, we build personalised organ-specific metabolic flux models for 524,615 in iduals of the INTERVAL and UK Biobank cohorts and perform a fluxome-wide association study (FWAS) to identify 4,411 associations between personalised flux values and the concentration of metabolites in blood. Furthermore, we apply FWAS to identify 97 metabolic fluxes associated with the risk of developing coronary artery disease, many of which are linked to processes previously described to play in role in the disease. Our work demonstrates that genetically personalised metabolic models can elucidate the downstream effects of genetic variants on biochemical reactions involved in common human diseases.
Publisher: Wiley
Date: 30-03-2009
DOI: 10.1002/SIM.3530
Publisher: Elsevier BV
Date: 08-2016
Publisher: Springer Science and Business Media LLC
Date: 23-11-2020
Publisher: Wiley
Date: 10-02-2009
DOI: 10.1002/SIM.3378
Abstract: Many measures have been proposed to summarize the prognostic ability of the Cox proportional hazards (CPH) survival model, although none is universally accepted for general use. By contrast, little work has been done to summarize the prognostic ability of the stratified CPH model such measures would be useful in analyses of in idual participant data from multiple studies, data from multi-centre studies, and in single study analysis where stratification is used to avoid making assumptions of proportional hazards. We have chosen three measures developed for the unstratified CPH model (Schemper and Henderson's V , Harrell's C-index and Royston and Sauerbrei's D), adapted them for use with the stratified CPH model and demonstrated how their values can be represented over time. Although each of these measures is promising in principle, we found the measure of explained variation V very difficult to apply when data are combined from several studies with differing durations of participant follow-up. The two other measures considered, D and the C-index, were more applicable under such circumstances. We illustrate the methods using in idual participant data from several prospective epidemiological studies of chronic disease outcomes.
Publisher: American Diabetes Association
Date: 09-02-2016
DOI: 10.2337/DC15-0257
Abstract: Observational studies show an association between ferritin and type 2 diabetes (T2D), suggesting a role of high iron stores in T2D development. However, ferritin is influenced by factors other than iron stores, which is less the case for other biomarkers of iron metabolism. We investigated associations of ferritin, transferrin saturation (TSAT), serum iron, and transferrin with T2D incidence to clarify the role of iron in the pathogenesis of T2D. The European Prospective Investigation into Cancer and Nutrition–InterAct study includes 12,403 incident T2D cases and a representative subcohort of 16,154 in iduals from a European cohort with 3.99 million person-years of follow-up. We studied the prospective association of ferritin, TSAT, serum iron, and transferrin with incident T2D in 11,052 cases and a random subcohort of 15,182 in iduals and assessed whether these associations differed by subgroups of the population. Higher levels of ferritin and transferrin were associated with a higher risk of T2D (hazard ratio [HR] [95% CI] in men and women, respectively: 1.07 [1.01–1.12] and 1.12 [1.05–1.19] per 100 μg/L higher ferritin level 1.11 [1.00–1.24] and 1.22 [1.12–1.33] per 0.5 g/L higher transferrin level) after adjustment for age, center, BMI, physical activity, smoking status, education, hs-CRP, alanine aminotransferase, and γ-glutamyl transferase. Elevated TSAT (≥45% vs. & %) was associated with a lower risk of T2D in women (0.68 [0.54–0.86]) but was not statistically significantly associated in men (0.90 [0.75–1.08]). Serum iron was not associated with T2D. The association of ferritin with T2D was stronger among leaner in iduals (Pinteraction & 0.01). The pattern of association of TSAT and transferrin with T2D suggests that the underlying relationship between iron stores and T2D is more complex than the simple link suggested by the association of ferritin with T2D.
Publisher: Oxford University Press (OUP)
Date: 13-06-2017
DOI: 10.1093/AJE/KWX149
Publisher: Springer Science and Business Media LLC
Date: 02-2017
DOI: 10.1038/NATURE21039
Publisher: Massachusetts Medical Society
Date: 03-03-2011
Publisher: Public Library of Science (PLoS)
Date: 30-07-2013
Publisher: Springer Science and Business Media LLC
Date: 03-06-2019
DOI: 10.1038/S41588-019-0447-2
Abstract: An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Publisher: American Medical Association (AMA)
Date: 26-03-2014
Publisher: Elsevier BV
Date: 04-2018
Publisher: Wiley
Date: 03-01-2020
DOI: 10.1111/OBR.12989
Publisher: Cold Spring Harbor Laboratory
Date: 19-01-2018
DOI: 10.1101/250712
Abstract: Coronary artery disease (CAD) has substantial heritability and a polygenic architecture however, genomic risk scores have not yet leveraged the totality of genetic information available nor been externally tested at population-scale to show potential utility in primary prevention. Using a meta-analytic approach to combine large-scale genome-wide and targeted genetic association data, we developed a new genomic risk score for CAD (metaGRS), consisting of 1.7 million genetic variants. We externally tested metaGRS, in idually and in combination with available conventional risk factors, in 22,242 CAD cases and 460,387 non-cases from UK Biobank. In UK Biobank, a standard deviation increase in metaGRS had a hazard ratio (HR) of 1.71 (95% CI 1.68–1.73) for CAD, greater than any other externally tested genetic risk score. In iduals in the top 20% of the metaGRS distribution had a HR of 4.17 (95% CI 3.97–4.38) compared with those in the bottom 20%. The metaGRS had higher C-index (C=0.623, 95% CI 0.615–0.631) for incident CAD than any of four conventional factors (smoking, diabetes, hypertension, and body mass index), and addition of the metaGRS to a model of conventional risk factors increased C-index by 3.7%. In in iduals on lipid-lowering or anti-hypertensive medications at recruitment, metaGRS hazard for incident CAD was significantly but only partially attenuated with HR of 2.83 (95% CI 2.61– 3.07) between the top and bottom 20% of the metaGRS distribution. Recent genetic association studies have yielded enough information to meaningfully stratify in iduals using the metaGRS for CAD risk in both early and later life, thus enabling targeted primary intervention in combination with conventional risk factors. The metaGRS effect was partially attenuated by lipid and blood pressure-lowering medication, however other prevention strategies will be required to fully benefit from earlier genomic risk stratification. National Health and Medical Research Council of Australia, British Heart Foundation, Australian Heart Foundation.
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 08-2023
Abstract: The aim of this study was to provide quantitative evidence of the use of polygenic risk scores for systematically identifying in iduals for invitation for full formal cardiovascular disease (CVD) risk assessment. A total of 108 685 participants aged 40 to 69 years, with measured biomarkers, linked primary care records, and genetic data in UK Biobank were used for model derivation and population health modeling. Prioritization tools using age, polygenic risk scores for coronary artery disease and stroke, and conventional risk factors for CVD available within longitudinal primary care records were derived using sex‐specific Cox models. We modeled the implications of initiating guideline‐recommended statin therapy after prioritizing in iduals for invitation to a formal CVD risk assessment. If primary care records were used to prioritize in iduals for formal risk assessment using age‐ and sex‐specific thresholds corresponding to 5% false‐negative rates, then the numbers of men and women needed to be screened to prevent 1 CVD event are 149 and 280, respectively. In contrast, adding polygenic risk scores to both prioritization and formal assessments, and selecting thresholds to capture the same number of events, resulted in a number needed to screen of 116 for men and 180 for women. Using both polygenic risk scores and primary care records to prioritize in iduals at highest risk of a CVD event for a formal CVD risk assessment can efficiently prioritize those who need interventions the most than using primary care records alone. This could lead to better allocation of resources by reducing the number of risk assessments in primary care while still preventing the same number of CVD events.
Publisher: Cold Spring Harbor Laboratory
Date: 19-12-2019
DOI: 10.1101/2019.12.14.876474
Abstract: Common human diseases are frequently polygenic in architecture, comprising a large number of risk alleles with small effects spread across the genome 1–3 . Polygenic scores (PGSs) aggregate these alleles into a metric which represents an in idual’s genetic predisposition to a specific disease. PGSs have shown promise for early risk prediction 4–7 , and there is potential to use PGSs to understand disease biology in parallel 8 . Here, we investigate the role plasma protein levels play in cardiometabolic disease risk in a cohort of 3,087 healthy in iduals using PGSs. We found PGSs for coronary artery disease (CAD), type 2 diabetes (T2D), chronic kidney disease (CKD), and ischaemic stroke (IS) were associated with levels of 49 plasma proteins. These associations were polygenic in architecture, largely independent of cis protein QTLs, and robust to environmental variation. Over a median 7.7 years follow-up, 28 of these plasma proteins were associated with future myocardial infarction (MI) or T2D events, 16 of which were causal mediators between polygenic risk and incident disease. These protein mediators of polygenic disease risk included targets of approved therapies which may have repurposing potential. Our results demonstrate that PGSs can identify proteins with causal roles in disease, and may have utility in drug development.
Publisher: Oxford University Press (OUP)
Date: 22-11-2018
Publisher: Elsevier BV
Date: 10-2018
Publisher: JMIR Publications Inc.
Date: 09-07-2021
Abstract: lthough the burden of premature myocardial infarction (MI) is high in Malaysia, direct evidence on the determinants of MI in this multi-ethnic population remains sparse. he Malaysian Acute Vascular Events Risk (MAVERIK) study is a retrospective case-control study established to investigate the genomic, lipid-related, and other determinants of acute MI in Malaysia. In this paper, we report the study protocol and early results. y June 2019, we had enrolled approximately 2500 patients with their first MI and 2500 controls without cardiovascular disease, who were frequency-matched by age, sex, and ethnicity, from 17 hospitals in Malaysia. For each participant, serum and whole blood have been collected and stored. Clinical, demographic, and behavioral information has been obtained using a 200-item questionnaire. obacco consumption, a history of diabetes, hypertension, markers of visceral adiposity, indicators of lower socioeconomic status, and a family history of coronary disease were more prevalent in cases than in controls. Adjusted (age and sex) logistic regression models for traditional risk factors indicated that current smoking (odds ratio [OR] 4.11, 95% CI 3.56-4.75 i P /i & .001), previous smoking (OR 1.34, 95% CI 1.12-1.60 i P /i =.001), a history of high blood pressure (OR 2.13, 95% CI 1.86-2.44 i P /i & .001), a history of diabetes mellitus (OR 2.72, 95% CI 2.34-3.17 i P /i & .001), a family history of coronary heart disease (OR 1.28, 95% CI 1.07-1.55 i P /i =.009), and obesity (BMI & kg/m sup /sup OR 1.19, 95% CI 1.05-1.34 i P /i =.009) were associated with MI in age- and sex-adjusted models. he MAVERIK study can serve as a useful platform to investigate genetic and other risk factors for MI in an understudied Southeast Asian population. It should help to hasten the discovery of disease-causing pathways and inform regionally appropriate strategies that optimize public health action. R1-10.2196/31885
Publisher: American Medical Association (AMA)
Date: 24-03-2008
DOI: 10.1001/ARCHINTE.168.6.598
Abstract: Large-scale prospective data are needed to determine whether associations between lipoprotein(a) (Lp[a]) and coronary heart disease (CHD) risk are independent of established risk factors, to characterize the shape of this relationship, and to quantify associations in relevant subgroups. Levels of Lp(a) were measured in s les obtained at baseline from 2047 patients who had first-ever nonfatal myocardial infarction or who died of CHD during the study and from 3921 control participants in the Reykjavik Study (n=18 569), as well as in paired s les obtained 12 years apart from 372 participants to quantify within-person fluctuations. Baseline Lp(a) levels had little or no correlation with known cardiovascular risk factors, such as age, sex, total cholesterol level, and blood pressure. The Lp(a) values were highly consistent from decade to decade, with a regression dilution ratio (calculated on the log scale) of 0.92 (95% confidence interval, 0.85-0.99). The odds ratio for CHD, unaltered after adjustment for several established risk factors (age, sex, smoking status, blood pressure, total cholesterol, triglycerides level, diabetes mellitus, and body mass index), was 1.60 (95% confidence interval, 1.38-1.85) in a comparison of extreme thirds of baseline Lp(a) levels. Odds ratios were progressively higher with increasing Lp(a) levels and did not vary materially by several in idual- or study-level characteristics. There are independent, continuous associations between Lp(a) levels and risk of future CHD in a broad range of in iduals. Levels of Lp(a) are highly stable within in iduals across many years and are only weakly correlated with known risk factors. Further assessment of their possible role in CHD prevention is warranted.
Publisher: Springer Science and Business Media LLC
Date: 08-11-2021
Publisher: Springer Science and Business Media LLC
Date: 18-09-2007
DOI: 10.1007/S10654-007-9165-7
Abstract: Many long-term prospective studies have reported on associations of cardiovascular diseases with circulating lipid markers and/or inflammatory markers. Studies have not, however, generally been designed to provide reliable estimates under different circumstances and to correct for within-person variability. The Emerging Risk Factors Collaboration has established a central database on over 1.1 million participants from 104 prospective population-based studies, in which subsets have information on lipid and inflammatory markers, other characteristics, as well as major cardiovascular morbidity and cause-specific mortality. Information on repeat measurements on relevant characteristics has been collected in approximately 340,000 participants to enable estimation of and correction for within-person variability. Re-analysis of in idual data will yield up to approximately 69,000 incident fatal or nonfatal first ever major cardiovascular outcomes recorded during about 11.7 million person years at risk. The primary analyses will involve age-specific regression models in people without known baseline cardiovascular disease in relation to fatal or nonfatal first ever coronary heart disease outcomes. This initiative will characterize more precisely and in greater detail than has previously been possible the shape and strength of the age- and sex-specific associations of several lipid and inflammatory markers with incident coronary heart disease outcomes (and, secondarily, with other incident cardiovascular outcomes) under a wide range of circumstances. It will, therefore, help to determine to what extent such associations are independent from possible confounding factors and to what extent such markers (separately and in combination) provide incremental predictive value.
Publisher: Oxford University Press (OUP)
Date: 22-12-2013
DOI: 10.1093/AJE/KWT298
Publisher: Elsevier BV
Date: 06-2017
Publisher: Elsevier BV
Date: 12-2021
Publisher: Springer Science and Business Media LLC
Date: 18-02-2019
Publisher: Wiley
Date: 15-04-2009
DOI: 10.1002/SIM.3540
Publisher: Cold Spring Harbor Laboratory
Date: 03-02-2020
DOI: 10.1101/2020.02.02.20020065
Abstract: Blood cells play essential roles in human health, underpinning physiological processes such as immunity, oxygen transport, and clotting, which when perturbed cause a significant health burden. Here we integrate data from UK Biobank and a large-scale international collaborative effort, including 563,946 European ancestry participants, and discover 5,106 new genetic variants independently associated with 29 blood cell phenotypes covering the full allele frequency spectrum of variation impacting hematopoiesis. We holistically characterize the genetic architecture of hematopoiesis, assess the relevance of the omnigenic model to blood cell phenotypes, delineate relevant hematopoietic cell states influenced by regulatory genetic variants and gene networks, identify novel splice-altering variants mediating the associations, and assess the polygenic prediction potential for blood cell traits and clinical disorders at the interface of complex and Mendelian genetics. These results show the power of large-scale blood cell GWAS to interrogate clinically meaningful variants across the full allelic spectrum of human variation.
Publisher: Elsevier BV
Date: 11-2018
Publisher: Oxford University Press (OUP)
Date: 29-05-2023
DOI: 10.1093/EURHEARTJ/EHAD260
Abstract: To develop and validate a recalibrated prediction model (SCORE2-Diabetes) to estimate the 10-year risk of cardiovascular disease (CVD) in in iduals with type 2 diabetes in Europe. SCORE2-Diabetes was developed by extending SCORE2 algorithms using in idual-participant data from four large-scale datasets comprising 229 460 participants (43 706 CVD events) with type 2 diabetes and without previous CVD. Sex-specific competing risk-adjusted models were used including conventional risk factors (i.e. age, smoking, systolic blood pressure, total, and HDL-cholesterol), as well as diabetes-related variables (i.e. age at diabetes diagnosis, glycated haemoglobin [HbA1c] and creatinine-based estimated glomerular filtration rate [eGFR]). Models were recalibrated to CVD incidence in four European risk regions. External validation included 217 036 further in iduals (38 602 CVD events), and showed good discrimination, and improvement over SCORE2 (C-index change from 0.009 to 0.031). Regional calibration was satisfactory. SCORE2-Diabetes risk predictions varied several-fold, depending on in iduals’ levels of diabetes-related factors. For ex le, in the moderate-risk region, the estimated 10-year CVD risk was 11% for a 60-year-old man, non-smoker, with type 2 diabetes, average conventional risk factors, HbA1c of 50 mmol/mol, eGFR of 90 mL/min/1.73 m2, and age at diabetes diagnosis of 60 years. By contrast, the estimated risk was 17% in a similar man, with HbA1c of 70 mmol/mol, eGFR of 60 mL/min/1.73 m2, and age at diabetes diagnosis of 50 years. For a woman with the same characteristics, the risk was 8% and 13%, respectively. SCORE2-Diabetes, a new algorithm developed, calibrated, and validated to predict 10-year risk of CVD in in iduals with type 2 diabetes, enhances identification of in iduals at higher risk of developing CVD across Europe.
Publisher: Wiley
Date: 04-09-2017
DOI: 10.1111/TRF.14307
Abstract: We compared donor and general population demographics over time to provide insight into current donation patterns and the future adequacy of the blood supply. Seventeen blood center members of the Biomedical Excellence for Safer Transfusion (BEST) Collaborative from 12 countries provided the number of donors and people in the general population by demographic category for 2001 and 2011, changes in age criteria, and percentage of first-time donors. We calculated the median age of donors and the general population and determined the percentage of each group in age and sex cohorts. Age criteria vary, with upper limits recently liberalized in several countries. In 2011, the percentage of first-time donors ranged from 10% to 41%. The median age of the donor and general population increased from 2001 to 2011 in most countries, as did the percentage of the general population over 60. The youngest donor cohort is overrepresented to a variable degree this tendency increased over time. Although still underrepresented, older donors contributed more in 2011. A large middle-aged cohort is aging at a rate exceeding the progression of time, while 25- to 45-year-olds are relatively underrepresented. All participating countries are experiencing aging of their general population. Donor demographics differ substantially between countries this can be only partly explained by population demographics and age criteria. Many countries have an aging middle-aged donor and population cohort and are increasingly relying on their youngest donors to contribute disproportionately to the blood supply.
Publisher: Elsevier BV
Date: 06-2019
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 12-2022
DOI: 10.1161/CIRCGEN.121.003598
Abstract: A key goal of precision medicine is to disaggregate common, complex diseases into discrete molecular subtypes. Rare coding variants in the low-density lipoprotein receptor gene ( LDLR ) are identified in 1% to 2% of coronary artery disease (CAD) patients, defining a molecular subtype with risk driven by hypercholesterolemia. To search for additional subtypes, we compared the frequency of rare, predicted loss-of-function and damaging missense variants aggregated within a given gene in 41 081 CAD cases versus 217 115 controls. Rare variants in LDLR were most strongly associated with CAD, present in 1% of cases and associated with 4.4-fold increased CAD risk. A second subtype was characterized by variants in endothelial nitric oxide synthase gene ( NOS3 ), a key enzyme regulating vascular tone, endothelial function, and platelet aggregation. A rare predicted loss-of-function or damaging missense variants in NOS3 was present in 0.6% of cases and associated with 2.42-fold increased risk of CAD (95% CI, 1.80–3.26 P =5.50×10 −9 ). These variants were associated with higher systolic blood pressure (+3.25 mm Hg [95% CI, 1.86–4.65] P =5.00×10 −6 ) and increased risk of hypertension (adjusted odds ratio 1.31 [95% CI, 1.14–1.51] P =2.00×10 −4 ) but not circulating cholesterol concentrations, suggesting that, beyond lipid pathways, nitric oxide synthesis is a key nonlipid driver of CAD risk. Beyond LDLR , we identified an additional nonlipid molecular subtype of CAD characterized by rare variants in the NOS3 gene.
Publisher: Elsevier BV
Date: 10-2019
Publisher: Cold Spring Harbor Laboratory
Date: 17-04-2022
DOI: 10.1101/2022.04.17.488593
Abstract: Genetically predicted levels of multi-omic traits can uncover the molecular underpinnings of common phenotypes in a highly efficient manner. Here, we utilised a large cohort (INTERVAL N=50,000 participants) with extensive multi-omic data for plasma proteomics (SomaScan, N=3,175 Olink, N=4,822), plasma metabolomics (Metabolon HD4, N=8,153), serum metabolomics (Nightingale, N=37,359), and whole blood Illumina RNA sequencing (N=4,136). We used machine learning to train genetic scores for 17,227 molecular traits, including 10,521 which reached Bonferroni-adjusted significance. We evaluated genetic score performances in external validation across European, Asian and African American ancestries, and assessed their longitudinal stability within erse in iduals. We demonstrated the utility of these multi-omic genetic scores by quantifying the genetic control of biological pathways and by generating a synthetic multi-omic dataset of UK Biobank to identify disease associations using a phenome-wide scan. Finally, we developed a portal ( OmicsPred.org ) to facilitate public access to all genetic scores and validation results as well as to serve as a platform for future extensions and enhancements of multi-omic genetic scores.
Publisher: Public Library of Science (PLoS)
Date: 14-01-2021
DOI: 10.1371/JOURNAL.PMED.1003498
Abstract: Polygenic risk scores (PRSs) can stratify populations into cardiovascular disease (CVD) risk groups. We aimed to quantify the potential advantage of adding information on PRSs to conventional risk factors in the primary prevention of CVD. Using data from UK Biobank on 306,654 in iduals without a history of CVD and not on lipid-lowering treatments (mean age [SD]: 56.0 [8.0] years females: 57% median follow-up: 8.1 years), we calculated measures of risk discrimination and reclassification upon addition of PRSs to risk factors in a conventional risk prediction model (i.e., age, sex, systolic blood pressure, smoking status, history of diabetes, and total and high-density lipoprotein cholesterol). We then modelled the implications of initiating guideline-recommended statin therapy in a primary care setting using incidence rates from 2.1 million in iduals from the Clinical Practice Research Datalink. The C-index, a measure of risk discrimination, was 0.710 (95% CI 0.703–0.717) for a CVD prediction model containing conventional risk predictors alone. Addition of information on PRSs increased the C-index by 0.012 (95% CI 0.009–0.015), and resulted in continuous net reclassification improvements of about 10% and 12% in cases and non-cases, respectively. If a PRS were assessed in the entire UK primary care population aged 40–75 years, assuming that statin therapy would be initiated in accordance with the UK National Institute for Health and Care Excellence guidelines (i.e., for persons with a predicted risk of ≥10% and for those with certain other risk factors, such as diabetes, irrespective of their 10-year predicted risk), then it could help prevent 1 additional CVD event for approximately every 5,750 in iduals screened. By contrast, targeted assessment only among people at intermediate (i.e., 5% to %) 10-year CVD risk could help prevent 1 additional CVD event for approximately every 340 in iduals screened. Such a targeted strategy could help prevent 7% more CVD events than conventional risk prediction alone. Potential gains afforded by assessment of PRSs on top of conventional risk factors would be about 1.5-fold greater than those provided by assessment of C-reactive protein, a plasma biomarker included in some risk prediction guidelines. Potential limitations of this study include its restriction to European ancestry participants and a lack of health economic evaluation. Our results suggest that addition of PRSs to conventional risk factors can modestly enhance prediction of first-onset CVD and could translate into population health benefits if used at scale.
Publisher: Springer Science and Business Media LLC
Date: 16-03-2021
Publisher: American Medical Association (AMA)
Date: 07-07-2015
Publisher: American Medical Association (AMA)
Date: 11-11-2009
Publisher: Elsevier BV
Date: 09-2020
Publisher: Springer Science and Business Media LLC
Date: 05-2015
Publisher: Elsevier BV
Date: 06-2010
Publisher: Cold Spring Harbor Laboratory
Date: 22-08-2019
DOI: 10.1101/744565
Abstract: There is debate about the value of adding information on genetic and other molecular markers to conventional cardiovascular disease (CVD) risk predictors. Using data on 306,654 in iduals without a history of CVD from UK Biobank, we calculated measures of risk-discrimination and reclassification upon addition of polygenic risk scores (PRS) and a panel of 27 clinical biochemistry markers to a conventional risk prediction model (i.e., including age, sex, systolic blood pressure, smoking status, history of diabetes, total cholesterol and HDL cholesterol). We then modelled implications of initiating guideline-recommended statin therapy after the assessment of molecular markers for a UK primary-care setting. The C-index was 0.710 (95% CI, 0.703-0.717) for a CVD prediction model containing conventional risk predictors alone. The C-index increased by similar amounts when adding information on PRS or biochemistry markers (0.011 and 0.014, respectively P .001), and it increased still further (0.022 P .001) when information on both was combined. Among cases and controls, continuous net reclassification improvements were about 12% and 19%, respectively, when both PRS and biochemistry markers were added. If PRS and biochemistry markers were to be assessed in the entire primary care population aged 40-75, then it could help prevent one additional CVD event for every 893 in iduals screened. By contrast, targeted assessment only among people at intermediate (i.e., 5-10%) 10-year CVD risk could help prevent one additional CVD event for every 233 in iduals screened. This targeted strategy could help reclassify 16% of the intermediate-risk group to the high-risk (i.e., ≥10%) category, preventing 11% more CVD events than conventional risk prediction. Adding information on both PRS and selected biochemistry markers moderately enhanced CVD predictive accuracy and could improve primary prevention of CVD. However, our modelling suggested that targeted assessment of molecular markers among in iduals at intermediate-risk would be more efficient than blanket approaches.
Publisher: Wiley
Date: 09-09-2011
DOI: 10.1002/SIM.4362
Publisher: American Medical Association (AMA)
Date: 02-2019
Publisher: Springer Science and Business Media LLC
Date: 22-12-2017
Publisher: American Association for the Advancement of Science (AAAS)
Date: 11-03-2016
Abstract: Coronary heart disease is a tale of two forms of plasma cholesterol. In contrast to the well-established effects of “bad” cholesterol (LDL-C), the role of “good” cholesterol (HDL-C) is mysterious. Elevated HDL-C correlates with a lower risk of heart disease, yet drugs that raise HDL-C levels do not reduce risk. Zanoni et al. found that some people with exceptionally high levels of HDL-C carry a rare sequence variant in the gene encoding the major HDL-C receptor, scavenger receptor BI. This variant destroys the receptor's ability to take up HDL-C. Interestingly, people with this variant have a higher risk of heart disease despite having high levels of HDL-C. Science , this issue p. 1166
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 07-2021
Abstract: Studies on the plasma proteome of renal function have identified several biomarkers, but have lacked replication, were limited to European populations, and/or did not investigate causality with eGFR. Among four cohorts in a transethnic cross-sectional study, 57 plasma proteins were associated with eGFR, 23 of them also with CKD. Furthermore, Mendelian randomization and gene expression analyses in kidney tissue highlighted testican-2 as a physiological marker of kidney disease progression with potential clinical relevance, and identified a few additional proteins warranting further investigation. Studies on the relationship between renal function and the human plasma proteome have identified several potential biomarkers. However, investigations have been conducted largely in European populations, and causality of the associations between plasma proteins and kidney function has never been addressed. A cross-sectional study of 993 plasma proteins among 2882 participants in four studies of European and admixed ancestries (KORA, INTERVAL, HUNT, QMDiab) identified transethnic associations between eGFR/CKD and proteomic biomarkers. For the replicated associations, two-s le bidirectional Mendelian randomization (MR) was used to investigate potential causal relationships. Publicly available datasets and transcriptomic data from independent studies were used to examine the association between gene expression in kidney tissue and eGFR. In total, 57 plasma proteins were associated with eGFR, including one novel protein. Of these, 23 were additionally associated with CKD. The strongest inferred causal effect was the positive effect of eGFR on testican-2, in line with the known biological role of this protein and the expression of its protein-coding gene ( SPOCK2 ) in renal tissue. We also observed suggestive evidence of an effect of melanoma inhibitory activity (MIA), carbonic anhydrase III, and cystatin-M on eGFR. In a discovery-replication setting, we identified 57 proteins transethnically associated with eGFR. The revealed causal relationships are an important stepping stone in establishing testican-2 as a clinically relevant physiological marker of kidney disease progression, and point to additional proteins warranting further investigation.
Publisher: American College of Physicians
Date: 30-01-2018
DOI: 10.7326/M17-1235
Publisher: Elsevier BV
Date: 04-2015
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
Start Date: 2015
End Date: 06-2018
Amount: $370,000.00
Funder: Australian Research Council
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