PhD in Population Genetics, University of Barcelona (2015)
Master of Experimental Biology, University of Cagliari (2011)
Bachelor of Biology, University of Cagliari (2009)
Urine biomarkers reflecting kidney function and handling of dietary sodium and potassium are strongly associated with several common diseases including chronic kidney disease, cardiovascular disease, and diabetes mellitus. Knowledge about the genetic determinants of these biomarkers may shed light on pathophysiological mechanisms underlying the development of these diseases. We performed genome-wide association studies of urinary albumin: creatinine ratio (UACR), urinary potassium: creatinine ratio (UK/UCr), urinary sodium: creatinine ratio (UNa/UCr) and urinary sodium: potassium ratio (UNa/UK) in up to 218,450 (discovery) and 109,166 (replication) unrelated individuals of European ancestry from the UK Biobank. Further, we explored genetic correlations, tissue-specific gene expression, and possible genes implicated in the regulation of these biomarkers. After replication, we identified 19 genome-wide significant independent loci associated with UACR, 6 each with UK/UCr and UNa/UCr, and 4 with UNa/UK. In addition to 22 novel associations, we confirmed several established associations, including between the CUBN locus and microalbuminuria. We detected high pairwise genetic correlation across the urinary biomarkers, and between their levels and several physiological measurements. We highlight GIPR, a potential diabetes drug target, as possibly implicated in the genetic control of urinary potassium excretion, and NRBP1, a locus associated with gout, as plausibly involved in sodium and albumin excretion. Overall, we identified 22 novel genome-wide significant associations with urinary biomarkers and confirmed several previously established associations, providing new insights into the genetic basis of these traits and their connection to chronic diseases.
View details for PubMedID 30910378
AIMS/HYPOTHESIS: Several epidemiological studies have shown an increased risk of atrial fibrillation in individuals with type 2 diabetes or milder forms of dysglycaemia. We aimed to assess whether this relation is causal using a Mendelian randomisation approach.METHODS: Two-sample Mendelian randomisation was used to obtain estimates of the influence of type 2 diabetes, fasting blood glucose (FBG), and HbA1c on the risk of atrial fibrillation. Instrumental variables were constructed using available summary statistics from meta-analyses of genome-wide association studies (GWAS) for type 2 diabetes and associated phenotypes. Pleiotropic SNPs were excluded from the analyses. The most recent GWAS meta-analysis summary statistics for atrial fibrillation, which included over 1 million individuals (approximately 60,000 individuals with atrial fibrillation) was used for outcome analysis.RESULTS: Neither type 2 diabetes (OR 1.01 [95% CI 0.98, 1.03]; p=0.37), nor FBG (OR 0.95 [95% CI 0.82, 1.09] per mmol/l; p=0.49) or HbA1c (OR 1.01 [95% CI, 0.85, 1.17] per mmol/mol [%]; p=0.88) were associated with atrial fibrillation in Mendelian randomisation analyses. We had >80% statistical power to detect ORs of 1.08, 1.06 and 1.09 or larger for type 2 diabetes, FBG and HbA1c, respectively, for associations with atrial fibrillation.CONCLUSIONS/INTERPRETATION: This Mendelian randomisation analysis does not support a causal role of clinical significance between genetically programmed type 2 diabetes, FBG or HbA1c and development of atrial fibrillation. These data suggest that drug treatment to reduce dysglycaemia is unlikely to be an effective strategy for atrial fibrillation prevention.DATA AVAILABILITY: The datasets analysed during the current study are available from the following repository: Nielsen JB, Thorolfsdottir RB, Fritsche LG, et al (2018) GWAS summary statistics for AF (N=60,620 AF cases and 970,216 controls). Center for Statistical Genetics: http://csg.sph.umich.edu/willer/public/afib2018/nielsen-thorolfsdottir-willer-NG2018-AFib-gwas-summary-statistics.tbl.gz.
View details for PubMedID 30810766
BACKGROUND: Varicose veins are a common problem with no approved medical therapies. Although it is believed that varicose vein pathogenesis is multifactorial, there is limited understanding of the genetic and environmental factors that contribute to their formation. Large-scale studies of risk factors for varicose veins may highlight important aspects of pathophysiology and identify groups at increased risk for disease.METHODS: We applied machine learning to agnostically search for risk factors of varicose veins in 493519 individuals in the UK Biobank. Predictors were further studied with univariable and multivariable Cox regression analyses (2441 incident events). A genome-wide association study of varicose veins was also performed among 337536 unrelated individuals (9577 cases) of white British descent, followed by expression quantitative loci and pathway analyses. Because height emerged as a new candidate risk factor, we performed mendelian randomization analyses to assess a potential causal role for height in varicose vein development.RESULTS: Machine learning confirmed several known (age, sex, obesity, pregnancy, history of deep vein thrombosis) and identified several new risk factors for varicose vein disease, including height. After adjustment for traditional risk factors in Cox regression, greater height remained independently associated with varicose veins (hazard ratio for upper versus lower quartile, 1.74; 95% CI, 1.51-2.01; P<0.0001). A genome-wide association study identified 30 new genome-wide significant loci, identifying pathways involved in vascular development and skeletal/limb biology. Mendelian randomization analysis provided evidence that increased height is causally related to varicose veins (inverse-variance weighted: odds ratio, 1.26; P=2.07*10-16).CONCLUSIONS: Using data from nearly a half-million individuals, we present a comprehensive genetic and epidemiological study of varicose veins. We identified novel clinical and genetic risk factors that provide pathophysiological insights and could help future improvements of treatment of varicose vein disease.
View details for PubMedID 30566020
Genome-wide association studies (GWASs) have allowed researchers to identify thousands of single nucleotide polymorphisms (SNPs) and other variants associated with particular complex traits. Previous studies have reported differences in the strength and even the direction of GWAS signals across different populations. These differences could be due to a combination of (1) lack of power, (2) allele frequency differences, (3) linkage disequilibrium (LD) differences, and (4) true differences in causal variant effect sizes. To determine whether properties (1)-(3) on their own might be sufficient to explain the patterns previously noted in strong GWAS signals, we simulated case-control data of European, Asian and African ancestry, applying realistic allele frequencies and LD from 1000 Genomes data but enforcing equal causal effect sizes across populations. Much of the observed differences in strong GWAS signals could indeed be accounted for by allele frequency and LD differences, enhanced by the Euro-centric SNP bias and lower SNP coverage found in older GWAS panels. While we cannot rule out a role for true transethnic effect size differences, our results suggest that strong causal effects may be largely shared among human populations, motivating the use of transethnic data for fine-mapping.
View details for PubMedID 29733446
Low birthweight has been associated with a higher risk of hypertension, type 2 diabetes mellitus (T2D), and cardiovascular disease. The Barker hypothesis posits that intrauterine growth restriction resulting in lower birthweight is causal for these diseases, but causality is difficult to infer from observational studies.We performed regression analyses to assess associations of birthweight with cardiovascular disease and T2D in 237?631 individuals from the UK Biobank. Further, we assessed the causal relationship of such associations using Mendelian randomization.In the observational analyses, birthweight showed inverse associations with systolic and diastolic blood pressure (?, -0.83 and -0.26; per raw unit in outcomes and SD change in birthweight; 95% confidence interval [CI], -0.90 to -0.75 and -0.31 to -0.22, respectively), T2D (odds ratio, 0.83; 95% CI, 0.79-0.87), lipid-lowering treatment (odds ratio, 0.84; 95% CI, 0.81-0.86), and coronary artery disease (hazard ratio, 0.85; 95% CI, 0.78-0.94), whereas the associations with adult body mass index and body fat (?, 0.04 and 0.02; per SD change in outcomes and birthweight; 95% CI, 0.03-0.04 and 0.01-0.02, respectively) were positive. The Mendelian randomization analyses indicated inverse causal associations of birthweight with low-density lipoprotein cholesterol, 2-hour glucose, coronary artery disease, and T2D and positive causal association with body mass index but no associations with blood pressure.Our study indicates that lower birthweight, used as a proxy for intrauterine growth retardation, is causally related with increased susceptibility to coronary artery disease and T2D. This causal relationship is not mediated by adult obesity or hypertension.
View details for PubMedID 29875125
In recent years, several genomic regions have been robustly associated with coronary artery disease (CAD) in different genome-wide association studies (GWASs) conducted mainly in people of European descent. These kinds of data are lacking in African populations, even though heart diseases are a major cause of premature death and disability.Here, 384 single nucleotide polymorphisms (SNPs) in the top four CAD risk regions (1p13, 1q41, 9p21, and 10q11) were genotyped in 274 case-control samples from Morocco and Tunisia, with the aim of analyzing for the first time if the associations found in European populations were transferable to North Africans.The results indicate that, as in Europe, these four genetic regions are also important for CAD risk in North Africa. However, the individual SNPs associated with CAD in Africa are different from those identified in Europe in most cases (1p13, 1q41, and 9p21). Moreover, the seven risk variants identified in North Africans are efficient in discriminating between cases and controls in North African populations, but not in European populations.This study indicates a disparity in markers associated to CAD susceptibility between North Africans and Europeans that may be related to population differences in the chromosomal architecture of these risk regions.
View details for DOI 10.2188/jea.JE20150034
View details for Web of Science ID 000375919300005
View details for PubMedID 26780859
Coronary artery disease (CAD) is a complex disease and the leading cause of death in the world. Populations of different ancestry do not always share the same risk markers. Natural selective processes may be the cause of some of the population differences detected for specific risk mutations.In this study, 384 single nucleotide polymorphisms (SNPs) located in four genomic regions associated with CAD (1p13, 1q41, 9p21 and 10q11) are analysed in a set of 19 populations from Europe, Middle East and North Africa and also in Asian and African samples from the 1000 Genomes Project. The aim of this survey is to explore for the first time whether the genetic variability in these genomic regions is better explained by demography or by natural selection.The results indicate significant differences in the structure of genetic variation and in the LD patterns among populations that probably explain the population disparities found in markers of susceptibility to CAD.The results are consistent with potential signature of positive selection in the 9p21 region and of balancing selection in the 9p21 and 10q11. Specifically, in Europe three CAD risk markers in the 9p21 region (rs9632884, rs1537371 and rs1333042) show consistent signals of positive selection. The results of this study are consistent with a potential selective role of CAD in the configuration of genetic diversity in current human populations.
View details for DOI 10.1371/journal.pone.0134840
View details for Web of Science ID 000359121100080
View details for PubMedID 26252781
Jordan, located in the Levant region, is an area crucial for the investigation of human migration between Africa and Eurasia. However, the genetic history of Jordanians has yet to be clarified, including the origin of the Bedouins today resident in Jordan. Here, we provide new genetic data on autosomal independent markers in two Jordanian population samples (Bedouins and the general population) to begin to examine the genetic diversity inside this country and to provide new information about the genetic position of these populations in the context of the Mediterranean and Middle East area. The markers analyzed were 18 Alu polymorphic insertions characterized by their identity by descent, known ancestral state (lack of insertion), and apparent selective neutrality. The results indicate significant genetic diffferences between Bedouins and general Jordanians (p = 0.038). Whereas Bedouins show a close genetic proximity to North Africans, general Jordanians appear genetically more similar to other Middle East populations. In general, these data are consistent with the hypothesis that Bedouins had an important role in the peopling of Jordan and constitute the original substrate of the current population. However, migration into Jordan in recent years likely has contributed to the diversity among current Jordanian population groups.
View details for DOI 10.3378/027.086.0201
View details for Web of Science ID 000346343500005
View details for PubMedID 25397703