James Yarmolinsky

15.1k total citations · 2 hit papers
30 papers, 7.1k citations indexed

About

James Yarmolinsky is a scholar working on Genetics, Cancer Research and Endocrinology, Diabetes and Metabolism. According to data from OpenAlex, James Yarmolinsky has authored 30 papers receiving a total of 7.1k indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Genetics, 8 papers in Cancer Research and 7 papers in Endocrinology, Diabetes and Metabolism. Recurrent topics in James Yarmolinsky's work include Genetic Associations and Epidemiology (16 papers), Cancer, Lipids, and Metabolism (4 papers) and Lipoproteins and Cardiovascular Health (4 papers). James Yarmolinsky is often cited by papers focused on Genetic Associations and Epidemiology (16 papers), Cancer, Lipids, and Metabolism (4 papers) and Lipoproteins and Cardiovascular Health (4 papers). James Yarmolinsky collaborates with scholars based in United Kingdom, United States and Brazil. James Yarmolinsky's co-authors include George Davey Smith, Nicholas J. Timpson, Richard M. Martin, Caroline L. Relton, Ryan Langdon, Kaitlin H. Wade, Philip Haycock, David M. Evans, Stephen Burgess and Vanessa Y. Tan and has published in prestigious journals such as JAMA, Nature Communications and PLoS ONE.

In The Last Decade

James Yarmolinsky

28 papers receiving 7.1k 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.

The MR-Base platform supports systematic causal inference across the human phenome

2018 4.4k citations Gibran Hemani, Kaitlin H. Wade et al. profile →
Strengthening the Reporting of Observational Studies in Epidemiology Using Mendelian Randomization

2021 1.9k citations Veronika Skrivankova, Rebecca C. Richmond et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
James Yarmolinsky United Kingdom	17	3.2k	1.8k	1.1k	954	824	30	7.1k
Fabiola Del Greco M Italy	25	3.2k 1.0×	1.6k 0.9×	1.0k 0.9×	873 0.9×	695 0.8×	38	6.7k
Ron Do United States	27	3.8k 1.2×	2.5k 1.4×	1.1k 1.0×	918 1.0×	932 1.1×	90	8.1k
Kaitlin H. Wade United Kingdom	23	3.2k 1.0×	1.7k 1.0×	970 0.9×	954 1.0×	622 0.8×	55	6.8k
Marie Verbanck France	12	2.5k 0.8×	1.5k 0.8×	908 0.8×	876 0.9×	616 0.7×	20	5.6k
Rebecca C. Richmond United Kingdom	33	2.4k 0.7×	2.1k 1.2×	909 0.8×	1.1k 1.1×	623 0.8×	99	7.1k
Hashem A. Shihab United Kingdom	15	3.5k 1.1×	3.0k 1.7×	793 0.7×	720 0.8×	548 0.7×	23	7.2k
Denis Baird United Kingdom	8	2.6k 0.8×	1.4k 0.8×	799 0.7×	667 0.7×	528 0.6×	17	5.2k
Ryan Langdon United Kingdom	13	2.4k 0.7×	1.5k 0.8×	761 0.7×	650 0.7×	460 0.6×	21	5.2k
J. Brent Richards Canada	44	3.3k 1.0×	2.6k 1.5×	1.2k 1.1×	1.3k 1.3×	852 1.0×	156	9.7k
Charles Laurin United States	9	2.6k 0.8×	1.3k 0.7×	743 0.7×	629 0.7×	487 0.6×	15	5.0k

Countries citing papers authored by James Yarmolinsky

Since Specialization

Citations

This map shows the geographic impact of James Yarmolinsky'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 James Yarmolinsky with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites James Yarmolinsky more than expected).

Fields of papers citing papers by James Yarmolinsky

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by James Yarmolinsky. 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 James Yarmolinsky. The network helps show where James Yarmolinsky may publish in the future.

Co-authorship network of co-authors of James Yarmolinsky

This figure shows the co-authorship network connecting the top 25 collaborators of James Yarmolinsky. A scholar is included among the top collaborators of James Yarmolinsky 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 James Yarmolinsky. James Yarmolinsky 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

Yarmolinsky, James, Fotios Koskeridis, Yi-An Ko, et al.. (2025). Blood pressure, plasma proteins, and cardiovascular diseases: a network Mendelian randomization and observational study. European Heart Journal. 47(3). 331–342. 1 indexed citations

Tan, Vanessa Y., James Yarmolinsky, Yadi Zheng, et al.. (2025). The Effect of Circulating Proteins and Their Role in Mediating Adiposity’s Effect on Endometrial Cancer Risk: Mendelian Randomization and Colocalization Analyses. Cancer Epidemiology Biomarkers & Prevention. 34(9). 1534–1543.

Smith, A.C., Georg Otto, Yi-An Ko, et al.. (2025). Identification of protein targets for dyslipidaemia and cardiovascular diseases among people with South Asian ancestry: a mendelian randomisation study. The Lancet Regional Health - Southeast Asia. 39. 100621–100621. 1 indexed citations

Yuan, Shuai, Jie Chen, Sizheng Steven Zhao, et al.. (2025). GWAS identifies genetic loci, lifestyle factors and circulating biomarkers that are risk factors for sarcoidosis. Nature Communications. 16(1). 2481–2481. 3 indexed citations

Yarmolinsky, James, Dipender Gill, Marie‐Joe Dib, et al.. (2024). Mendelian Randomization and Bayesian Colocalization Analysis Implicate Glycoprotein VI as a Potential Drug Target for Cardioembolic Stroke in South Asian Populations. Journal of the American Heart Association. 13(16). e035008–e035008. 5 indexed citations

Martin, Richard M., et al.. (2024). Investigating the association between genetically proxied circulating levels of immune checkpoint proteins and cancer survival: protocol for a Mendelian randomisation analysis. BMJ Open. 14(2). e075981–e075981. 2 indexed citations

Zhao, Sizheng Steven, Thurkka Rajeswaran, Sarah Mackie, & James Yarmolinsky. (2023). Genetically proxied IL-1 receptor antagonism and risk of polymyalgia rheumatica. Lara D. Veeken. 63(2). e43–e44. 1 indexed citations

Mitchell, Ruth E., April Hartley, Venexia Walker, et al.. (2023). Strategies to investigate and mitigate collider bias in genetic and Mendelian randomisation studies of disease progression. PLoS Genetics. 19(2). e1010596–e1010596. 35 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

10.

Woolf, Benjamin, Skanda Rajasundaram, Héléne T. Cronjé, et al.. (2023). A drug target for erectile dysfunction to help improve fertility, sexual activity, and wellbeing: mendelian randomisation study. BMJ. 383. e076197–e076197. 18 indexed citations

11.

Woolf, Benjamin, Veronika Skrivankova, Julian P. T. Higgins, et al.. (2022). Investigating the transparency of reporting in two-sample summary data Mendelian randomization studies using the MR-Base platform. International Journal of Epidemiology. 51(6). 1943–1956. 29 indexed citations

12.

Joharatnam‐Hogan, Nalinie, Leo Alexandre, James Yarmolinsky, et al.. (2021). Statins as Potential Chemoprevention or Therapeutic Agents in Cancer: a Model for Evaluating Repurposed Drugs. Current Oncology Reports. 23(3). 29–29. 24 indexed citations

13.

Robinson, Tim, Richard M. Martin, & James Yarmolinsky. (2020). Mendelian randomisation analysis of circulating adipokines and C‐reactive protein on breast cancer risk. International Journal of Cancer. 147(6). 1597–1603. 20 indexed citations

14.

Arathimos, Ryan, Raquel Granell, Philip Haycock, et al.. (2019). Genetic and observational evidence supports a causal role of sex hormones on the development of asthma. Thorax. 74(7). 633–642. 26 indexed citations

15.

Yarmolinsky, James, Caroline L. Relton, Artitaya Lophatananon, et al.. (2019). Appraising the role of previously reported risk factors in epithelial ovarian cancer risk: A Mendelian randomization analysis. PLoS Medicine. 16(8). e1002893–e1002893. 58 indexed citations

16.

Yarmolinsky, James, Kaitlin H. Wade, Rebecca C. Richmond, et al.. (2018). Causal Inference in Cancer Epidemiology: What Is the Role of Mendelian Randomization?. Cancer Epidemiology Biomarkers & Prevention. 27(9). 995–1010. 105 indexed citations

17.

Yarmolinsky, James, Ryan Langdon, Carolina Bonilla, et al.. (2018). Mendelian randomization does not support serum calcium in prostate cancer risk. Cancer Causes & Control. 29(11). 1073–1080. 7 indexed citations

18.

Yarmolinsky, James, Carolina Bonilla, Philip Haycock, et al.. (2018). Circulating Selenium and Prostate Cancer Risk: A Mendelian Randomization Analysis. JNCI Journal of the National Cancer Institute. 110(9). 1035–1038. 71 indexed citations

19.

Yarmolinsky, James, et al.. (2016). Plasminogen activator inhibitor-1 and type 2 diabetes: a systematic review and meta-analysis of observational studies. Scientific Reports. 6(1). 17714–17714. 89 indexed citations

20.

Yarmolinsky, James, Bruce Bartholow Duncan, Lloyd E. Chambless, et al.. (2015). Artificially Sweetened Beverage Consumption Is Positively Associated with Newly Diagnosed Diabetes in Normal-Weight but Not in Overweight or Obese Brazilian Adults. Journal of Nutrition. 146(2). 290–297. 16 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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