Profile
I hold a Degree in ‘Statistics’ (Sapienza University, Rome, 2004) and a PhD in ‘Public Health and Education’ (University of Pavia, Italy, 2009; including 2-year visiting PhD student at Prof. Balding's group, Imperial College London), with a thesis on meta-analytic methods for family-based genetic association studies.
A successful post-doc (2009-2012) at the UCL Institute of Ophthalmology (London) with the publication of the first genome-wide association study (GWAS) of age-related macular degeneration (AMD) in the UK (Cipriani et al., HMG, 2012) led me to be recognised as an expert in the complex genetics of AMD both in the UK and internationally. I have been an active analyst of the International AMD Genomics Consortium (IAMDGC) with several other high-impact publications (see publication list).
I was then funded through a 5-year NIHR-BRC grant (2012-2017) as the referent genetic statistician at Moorfields Eye Hospital and the UCL Institute of Ophthalmology, where I expanded my research activities beyond complex genetics into rare disease diagnostics and gene discovery, and built a solid network of collaborators that landed my current affiliation at QMUL, first as a ‘Senior Bioinformatics Research Fellow’ (2017-2020, Prof. Smedley’s group), then as a faculty member ('Lecturer' in Statistical Genomics [March 2020 -July 2022], progressing to ‘Senior Lecturer’ in August 2022).
I am a member of the Centre for Translational Bioinformatics.
Twitter: @QMUL_C4TB.
I am a Fellow at the Queen Mary's Digital Environment Research Institute (DERI) (August 2022 - present).
Research
Group members
- Miss Apoorva Sarah Perepogu (MSc in Bioinformatics student, 2022-2023); project title: “Extending the rare variant burden analysis to the non-coding genome with an application to the 100,000 Genomes Project data”
- Miss Amy Evans (Barts charity PhD student, 2023- ); project title: “Genetic determinants of pituitary adenomas”
Contact me at v.cipriani@qmul.ac.uk or check out my Twitter account @Val3Cipriani for currently available PhD student and post-doc research positions.
Alumni
- Miss Catherine Kelly (MSc in Bioinformatics, 2020-2021); Kelly C, …Cipriani V, Phenotype-aware prioritisation of rare Mendelian disease variants. Trends Genet, 38:1271-1283, 2022
- Miss Penpitcha Thawong (MSc in Bioinformatics, 2018-2019); Cipriani V, …, Thawong P, et al. An Improved Phenotype-Driven Tool for Rare Mendelian Variant Prioritization: Benchmarking Exomiser on Real Patient Whole-Exome Data. Genes, 11:460, 2020
Summary
My research aims to help elucidate the genetic determinants of both common complex and rare Mendelian human diseases by using cutting-edge computational tools in genotyping and sequencing association studies. The divide between common and rare diseases has been decreasing over the past years with many common disorders presenting with their closely linked monogenic familial forms, as well as many Mendelian disorders showing incomplete penetrance and variable expressivity due, for example, to the effect of modifier genes and/or environmental factors.
I am currently involved in many national and international human genetic projects, including studies of the complex genetics of age-related macular degeneration (AMD) and the analysis of genomic data from the 100,000 Genomes Project (100KGP) and the University College London (UCL) exome consortium (UCLex).
My research output has a high clinical impact with potential implications for novel therapeutics in complex genetics and demonstrated increases in the diagnostic yield in rare diseases.
Exomiser; rare disease diagnostics and gene discovery
I have been an active member of the Monarch Initiative and Human Phenotype Ontology community, contributing to the improvement and assessment of flagship Exomiser tool for phenotype-based variant prioritisation. Such tools often lack extensive validation on real patient data. I have recently shown an effective Exomiser performance on a large rare disease whole-exome patient dataset (Cipriani et al., Genes, 2020) and supervised an in-depth review of phenotype-based variant prioritisation tools (Kelly et al., Trends Genet, 2022). Furthermore, I co-led the application of an Exomiser-based gene burden analysis pipeline to the pilot phase of the 100KGP pilot (Smedley&Smith&Martin&Thomas&McDonagh&Cipriani&Ellingford&Arno&Tucci& Vandrovcova&Chan&Williams et al., NEJM, 2021) that has already resulted in three confirmed gene discoveries (including Bourinaris&Smedley&Cipriani et al., EJHG, 2020) as well as new gene discoveries (Park&Tucci&Cipriani et al., Genet Med, 2022).
Family-based genetic association analyses
I have recently led a comprehensive analysis that used a combination of haplotype-sharing, genotyping and sequencing family-based methods and successfully identified non-coding SNVs and duplications in 13 families affected by rare autosomal dominant North Carolina macular dystrophy (NCMD) (Cipriani et al., Sci Rep, 2017). This was a long-awaited result, with the chromosome 5 linkage region for this disorder being known for 15 years. These results have recently triggered further studies that gained insights into the cis-regulatory mechanisms of NCMD and support that NCMD is a retinal enhanceropathy (Van de Sompele et al., bioRxiv 2022.03.08.481329, 2022).
Complex genetics of age-related macular degeneration
I was the leading statistician for the first genome-wide association study (GWAS) of AMD in the UK (Cipriani et al., HMG, 2012). The study allowed me to become a member of the International AMD Genomics Consortium (IAMDGC). The IAMDGC performed the largest GWAS of AMD with the discovery of 16 novel risk loci. I presented the corresponding findings at the 64th ASHG meeting (San Diego, 2014) and contributed to the last IAMDGC GWAS manuscript (Fritsche et al., Nat Genet, 2016). Building on this experience, I have been pursuing a much-needed dissection of the well-established AMD-association at the CFH locus (known since 2005) with national and international experts in AMD and the complement system. I have led a wealth of statistical genetic data analyses that brought to the identification of FHR proteins as major players in AMD pathogenesis with concrete potential implications for complement inhibiting therapeutics (e.g., Complement Therapeutics Limited, CTx) (Cipriani et al, AJHG, 2021; Cipriani et al, Nat Commun, 2020).
I am a Senior Editor for the Annals of Human Genetics.
Publications
Google scholar statistics (as of June 2023), Citations: 5134; h-index: 23; i10-index: 31
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Cipriani V, Vestito L, Magavern EF et al. (2025). Rare disease gene association discovery in the 100,000 Genomes Project.
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Vestito L, Cipriani V, Smedley D (2025). 3 Computational genomics and bioinformatics.
QMRO:
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Vestito L, Jacobsen JOB, Walker S et al. . Efficient reinterpretation of rare disease cases using Exomiser.
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Gorman BR, Voloudakis G, Igo RP et al. (2024). Genome-wide association analyses identify distinct genetic architectures for age-related macular degeneration across ancestries.
QMRO:
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Leong IUS, Cabrera CP, Cipriani V et al. (2025). Large-Scale Pharmacogenomics Analysis of Patients With Cancer Within the 100,000 Genomes Project Combining Whole-Genome Sequencing and Medical Records to Inform Clinical Practice.
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Benkirane M, Bonhomme M, Morsy H et al. (2024). De novo and inherited monoallelic variants in TUBA4A cause ataxia and spasticity.
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Ishida M, Vestito L, Maharaj A et al. . Novel insights into genetic causes of childhood growth failure from patients recruited to the 100 000 Genomes Project.
QMRO:
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Park J, Tucci A, Cipriani V et al. (2023). Heterozygous UCHL1 loss-of-function variants cause a neurodegenerative disorder with spasticity, ataxia, neuropathy, and optic atrophy.
QMRO:
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Pavinato L, Stanic J, Barzasi M et al. (2023). Missense variants in RPH3A cause defects in excitatory synaptic function and are associated with a clinically variable neurodevelopmental disorder.
QMRO:
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Clark R, Lee SS-Y, Du R et al. (2023). A new polygenic score for refractive error improves detection of children at risk of high myopia but not the prediction of those at risk of myopic macular degeneration.
QMRO:
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