Biology subjects

van Heel, D. A.

Publications and source records attributed to van Heel, D. A..

4 recordsLinked to original sources

bioRxiv2022

PIK3R3 is a candidate regulator of platelet count in people of Bangladeshi ancestry

Platelets are mediators of cardiovascular disease and are regulated by complex sets of interacting genes. To reveal new regulatory loci for platelet count (PLT), we performed genome-wide association studies (GWAS) in 20,218 Bangladeshi (BAN) and 9,198 Pakistani (PAK) individuals from the Genes and Health study. Most significantly associated loci (p <5 x10-8) replicated findings in prior transethnic GWAS. However, the BAN locus defined by rs946528 (chr1:46019890) did not associate with PLT in the PAK analysis but was in the same linkage disequilibrium block as PLT-associated variants in prior East Asian GWAS. The single independent association signal was refined to a 95% credible set of 343 variants spanning eight coding genes. Functional annotation, mapping to megakaryocyte regulatory regions and colocalization with whole blood eQTLs identified the most likely mediator of the PLT phenotype to be PIK3R3 encoding a regulator of phosphoinositol 3-kinase, widely linked elsewhere to adverse cardiovascular phenotypes.

genomics↗

bioRxiv2020

Fine-scale population structure and demographic history of British Pakistanis

Previous genetic and public health research in the Pakistani population has focused on the role of consanguinity in increasing recessive disease risk, but little is known about its recent population history or the effects of endogamy. Here, we investigate fine-scale population structure, history and consanguinity patterns using genetic and questionnaire data from >4,000 British Pakistani individuals, mostly with roots in Azad Kashmir and Punjab. We reveal strong recent population structure driven by the biraderi social stratification system. We find that all subgroups have had low effective population sizes (Ne) over the last 50 generations, with some showing a decrease in Ne 15-20 generations ago that has resulted in extensive identity-by-descent sharing and increased homozygosity. Using new theory, we show that the footprint of regions of homozygosity in the two largest subgroups is about twice that expected naively based on the self-reported consanguinity rates and the inferred historical Ne trajectory. These results demonstrate the impact of the cultural practices of endogamy and consanguinity on population structure and genomic diversity in British Pakistanis, and have important implications for medical genetic studies.

genomics↗

bioRxiv2019

Evaluating potential drug targets through human loss-of-function genetic variation

Human genetics has informed the clinical development of new drugs, and is beginning to influence the selection of new drug targets. Large-scale DNA sequencing studies have created a catalogue of naturally occurring genetic variants predicted to cause loss of function in human genes, which in principle should provide powerful in vivo models of human genetic "knockouts" to complement model organism knockout studies and inform drug development. Here, we consider the use of predicted loss-of-function (pLoF) variation catalogued in the Genome Aggregation Database (gnomAD) for the evaluation of genes as potential drug targets. Many drug targets, including the targets of highly successful inhibitors such as aspirin and statins, are under natural selection at least as extreme as known haploinsufficient genes, with pLoF variants almost completely depleted from the population. Thus, metrics of gene essentiality should not be used to eliminate genes from consideration as potential targets. The identification of individual humans harboring "knockouts" (biallelic gene inactivation), followed by individual recall and deep phenotyping, is highly valuable to study gene function. In most genes, pLoF alleles are sufficiently rare that ascertainment will be largely limited to heterozygous individuals in outbred populations. Sampling of diverse bottlenecked populations and consanguineous individuals will aid in identification of total "knockouts". Careful filtering and curation of pLoF variants in a gene of interest is necessary in order to identify true LoF individuals for follow-up, and the positional distribution or frequency of true LoF variants may reveal important disease biology. Our analysis suggests that the value of pLoF variant data for drug discovery lies in deep curation informed by the nature of the drug and its indication, as well as the biology of the gene, followed by recall-by-genotype studies in targeted populations.

genomics↗

bioRxiv2017

Causal Analyses, Statistical Efficiency And Phenotypic Precision Through Recall-By-Genotype Study Design

Genome-wide association studies have been useful in identifying common genetic variants related to a variety of complex traits and diseases; however, they are often limited in their ability to inform about underlying biology. Whilst bioinformatics analyses, studies of cells, animal models and applied genetic epidemiology have provided some understanding of genetic associations or causal pathways, there is a need for new genetic studies that elucidate causal relationships and mechanisms in a cost-effective, precise and statistically efficient fashion. We discuss the motivation for and the characteristics of the Recall-by-Genotype (RbG) study design, an approach that enables genotype-directed deep-phenotyping and improvement in drawing causal inferences. Specifically, we present RbG designs using single and multiple variants and discuss the inferential properties, analytical approaches and applications of both. We consider the efficiency of the RbG approach, the likely value of RbG studies for the causal investigation of disease aetiology and the practicalities of incorporating genotypic data into population studies in the context of the RbG study design. Finally, we provide a catalogue of the UK-based resources for such studies, an online tool to aid the design of new RbG studies and discuss future developments of this approach.

genetics↗