Tom G. Richardson

10.1k total citations · 3 hit papers
92 papers, 2.8k citations indexed

About

Tom G. Richardson is a scholar working on Genetics, Molecular Biology and Pediatrics, Perinatology and Child Health. According to data from OpenAlex, Tom G. Richardson has authored 92 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 71 papers in Genetics, 28 papers in Molecular Biology and 17 papers in Pediatrics, Perinatology and Child Health. Recurrent topics in Tom G. Richardson's work include Genetic Associations and Epidemiology (63 papers), Birth, Development, and Health (13 papers) and Bioinformatics and Genomic Networks (13 papers). Tom G. Richardson is often cited by papers focused on Genetic Associations and Epidemiology (63 papers), Birth, Development, and Health (13 papers) and Bioinformatics and Genomic Networks (13 papers). Tom G. Richardson collaborates with scholars based in United Kingdom, United States and Denmark. Tom G. Richardson's co-authors include George Davey Smith, Eleanor Sanderson, Michael V. Holmes, Brian A. Ference, Mika Ala‐Korpela, Gibran Hemani, Tom R. Gaunt, Tom Palmer, Benjamin Elsworth and Kate Tilling and has published in prestigious journals such as The Lancet, Nature Communications and PLoS ONE.

In The Last Decade

Tom G. Richardson

88 papers receiving 2.8k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Evaluating the relationship between circulating lipoprotein lipids and apolipoproteins with risk of coronary heart disease: A multivariable Mendelian randomisation analysis

2020 491 citations Tom G. Richardson, Eleanor Sanderson et al. PLoS Medicine profile →
Use of genetic variation to separate the effects of early and later life adiposity on disease risk: mendelian randomisation study

2020 178 citations Tom G. Richardson, Eleanor Sanderson et al. profile →
Characterising metabolomic signatures of lipid-modifying therapies through drug target mendelian randomisation

2022 159 citations Tom G. Richardson, Qin Wang et al. profile →

Peers

Tom G. Richardson

GENET

EPIDE

SURGE

EDM

James R Staley United Kingdom

Benjamin Woolf United Kingdom

Alanna C. Morrison United States

N. Charlotte Onland‐Moret Netherlands

Verena Zuber United Kingdom

Sayuko Kobes United States

Valeriia Haberland United Kingdom

Laure El ghormli United States

Praveen Surendran United Kingdom

Charles Laurin United States

James R Staley United Kingdom

Tom G. Richardson

1.5k ×1.2

GENET

902 ×1.1

482 ×1.0

EPIDE

345 ×0.8

SURGE

286 ×0.8

EDM

Citations per year, relative to Tom G. Richardson Tom G. Richardson (= 1×) peers James R Staley

Countries citing papers authored by Tom G. Richardson

Since Specialization

Citations

This map shows the geographic impact of Tom G. Richardson's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Tom G. Richardson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tom G. Richardson more than expected).

Fields of papers citing papers by Tom G. Richardson

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tom G. Richardson. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Tom G. Richardson. The network helps show where Tom G. Richardson may publish in the future.

Co-authorship network of co-authors of Tom G. Richardson

This figure shows the co-authorship network connecting the top 25 collaborators of Tom G. Richardson. A scholar is included among the top collaborators of Tom G. Richardson based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Tom G. Richardson. Tom G. Richardson is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Power, Grace M., Tom Palmer, Nicole M. Warrington, et al.. (2025). A structural mean modeling Mendelian randomization approach to investigate the lifecourse effect of adiposity: applied and methodological considerations. American Journal of Epidemiology. 195(1). 21–31.

Zhang, Lanyue, Rainer Malik, Tom G. Richardson, et al.. (2025). The genomic architecture of circulating cytokine levels points to drug targets for immune-related diseases. Communications Biology. 8(1). 34–34. 1 indexed citations

Wootton, Robyn E., Jasmine Khouja, Tom G. Richardson, et al.. (2024). Exploring pleiotropy in Mendelian randomisation analyses: What are genetic variants associated with ‘cigarette smoking initiation’ really capturing?. Genetic Epidemiology. 49(1). e22583–e22583. 2 indexed citations

Power, Grace M., Naomi Warne, Helen Bould, et al.. (2024). The role of body image dissatisfaction in the relationship between body size and disordered eating and self-harm: complimentary Mendelian randomization and mediation analyses. Molecular Psychiatry. 30(2). 521–531.

Beaumont, Robin N., Jessica Tyrrell, Grace M. Power, et al.. (2023). Genetic evidence that high BMI in childhood has a protective effect on intermediate diabetes traits, including measures of insulin sensitivity and secretion, after accounting for BMI in adulthood. Diabetologia. 66(8). 1472–1480. 5 indexed citations

Stender, Stefan, George Davey Smith, & Tom G. Richardson. (2023). Genetic variation and elevated liver enzymes during childhood, adolescence and early adulthood. International Journal of Epidemiology. 52(5). 1341–1349. 2 indexed citations

Fang, Si, James Yarmolinsky, Dipender Gill, et al.. (2023). Association between genetically proxied PCSK9 inhibition and prostate cancer risk: A Mendelian randomisation study. PLoS Medicine. 20(1). e1003988–e1003988. 30 indexed citations

Wei, Yuxia, Tom G. Richardson, Yiqiang Zhan, & Sofia Carlsson. (2023). Childhood adiposity and novel subtypes of adult-onset diabetes: a Mendelian randomisation and genome-wide genetic correlation study. Diabetologia. 66(6). 1052–1056. 5 indexed citations

Wang, Qin, Tom G. Richardson, Eleanor Sanderson, et al.. (2022). A phenome-wide bidirectional Mendelian randomization analysis of atrial fibrillation. International Journal of Epidemiology. 51(4). 1153–1166. 25 indexed citations

10.

Fang, Si, Gibran Hemani, Tom G. Richardson, Tom R. Gaunt, & George Davey Smith. (2022). Evaluating and implementing block jackknife resampling Mendelian randomization to mitigate bias induced by overlapping samples. Human Molecular Genetics. 32(2). 192–203. 15 indexed citations

11.

Sanderson, Eleanor, Tom G. Richardson, Gibran Hemani, & George Davey Smith. (2021). The use of negative control outcomes in Mendelian randomization to detect potential population stratification. International Journal of Epidemiology. 50(4). 1350–1361. 61 indexed citations

12.

Richardson, Tom G., Juha Mykkänen, Katja Pahkala, et al.. (2021). Evaluating the direct effects of childhood adiposity on adult systemic metabolism: a multivariable Mendelian randomization analysis. International Journal of Epidemiology. 50(5). 1580–1592. 34 indexed citations

13.

Harroud, Adil, Ruth E. Mitchell, Tom G. Richardson, et al.. (2021). Childhood obesity and multiple sclerosis: A Mendelian randomization study. Multiple Sclerosis Journal. 27(14). 2150–2158. 33 indexed citations

14.

Leu, Costin, Tom G. Richardson, Tobias Kaufmann, et al.. (2020). Pleiotropy of polygenic factors associated with focal and generalized epilepsy in the general population. PLoS ONE. 15(4). e0232292–e0232292. 14 indexed citations

15.

Smith, George Davey, et al.. (2019). Integrating Mendelian randomization and multiple-trait colocalization to uncover cell-specific inflammatory drivers of autoimmune and atopic disease. Human Molecular Genetics. 28(19). 3293–3300. 31 indexed citations

16.

Zheng, Jie, Tom G. Richardson, Louise A C Millard, et al.. (2018). PhenoSpD: an integrated toolkit for phenotypic correlation estimation and multiple testing correction using GWAS summary statistics. GigaScience. 7(8). 40 indexed citations

17.

Erzurumluoglu, A. Mesut, Denis Baird, Tom G. Richardson, Nicholas J. Timpson, & Santiago Rodrı́guez. (2018). Using Y-Chromosomal Haplogroups in Genetic Association Studies and Suggested Implications. Genes. 9(1). 45–45. 4 indexed citations

18.

Richardson, Tom G., Nicholas J. Timpson, Colin Campbell, & Tom R. Gaunt. (2016). A pathway-centric approach to rare variant association analysis. European Journal of Human Genetics. 25(1). 123–129. 10 indexed citations

19.

Erzurumluoglu, A. Mesut, Santiago Rodrı́guez, Hashem A. Shihab, et al.. (2015). Identifying Highly Penetrant Disease Causal Mutations Using Next Generation Sequencing: Guide to Whole Process. BioMed Research International. 2015. 1–16. 7 indexed citations

20.

Richardson, Tom G.. (2008). Inhibitory control in psychiatric disorders- a review of neuropsychological and neuroimaging research.. 7. 2 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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