scispace - formally typeset
L

Luisa Bernardinelli

Researcher at University of Pavia

Publications -  88
Citations -  7276

Luisa Bernardinelli is an academic researcher from University of Pavia. The author has contributed to research in topics: Population & Internal medicine. The author has an hindex of 31, co-authored 75 publications receiving 6604 citations. Previous affiliations of Luisa Bernardinelli include University of Cambridge & Medical Research Council.

Papers
More filters
Journal ArticleDOI

Analysis of immune-related loci identifies 48 new susceptibility variants for multiple sclerosis

Ashley Beecham, +206 more
- 01 Nov 2013 - 
TL;DR: This study enhances the catalog of multiple sclerosis risk variants and illustrates the value of fine mapping in the resolution of GWAS signals.
Journal ArticleDOI

Genome-wide meta-analyses identify multiple loci associated with smoking behavior

Helena Furberg, +123 more
- 01 May 2010 - 
TL;DR: A meta-analyses of several smoking phenotypes within cohorts of the Tobacco and Genetics Consortium found the strongest association was a synonymous 15q25 SNP in the nicotinic receptor gene CHRNA3, and three loci associated with number of cigarettes smoked per day were identified.
Journal ArticleDOI

Genome-wide association of early-onset myocardial infarction with single nucleotide polymorphisms and copy number variants.

Sekar Kathiresan, +118 more
- 08 Feb 2009 - 
TL;DR: SNPs at nine loci were reproducibly associated with myocardial infarction, but tests of common and rare CNVs failed to identify additional associations with my Cardiovascular Infarction risk.
Journal ArticleDOI

New susceptibility locus for coronary artery disease on chromosome 3q22.3

Jeanette Erdmann, +60 more
- 01 Mar 2009 - 
TL;DR: A three-stage analysis of genome-wide SNP data in 1,222 German individuals with myocardial infarction and 1,298 controls is presented and suggestive association with a locus on 12q24.31 near HNF1A-C12orf43 is identified.
Journal ArticleDOI

Bayesian analysis of space—time variation in disease risk

TL;DR: A Bayesian model in which both area-specific intercept and trend are modelled as random effects and correlation between them is allowed for is proposed, an extension of that originally proposed for disease mapping.