J. Brent Richards

38.9k total citations · 4 hit papers
156 papers, 9.7k citations indexed

About

J. Brent Richards is a scholar working on Genetics, Molecular Biology and Pathology and Forensic Medicine. According to data from OpenAlex, J. Brent Richards has authored 156 papers receiving a total of 9.7k indexed citations (citations by other indexed papers that have themselves been cited), including 82 papers in Genetics, 43 papers in Molecular Biology and 34 papers in Pathology and Forensic Medicine. Recurrent topics in J. Brent Richards's work include Genetic Associations and Epidemiology (66 papers), Bone health and osteoporosis research (29 papers) and Vitamin D Research Studies (18 papers). J. Brent Richards is often cited by papers focused on Genetic Associations and Epidemiology (66 papers), Bone health and osteoporosis research (29 papers) and Vitamin D Research Studies (18 papers). J. Brent Richards collaborates with scholars based in Canada, United Kingdom and United States. J. Brent Richards's co-authors include Nicholas J. Timpson, George Davey Smith, Vincenzo Forgetta, Claudia Langenberg, Tim D. Spector, Celia M.T. Greenwood, Tyler J. VanderWeele, Matthias Egger, Rebecca C. Richmond and Veronika Skrivankova and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

J. Brent Richards

155 papers receiving 9.5k citations

Hit Papers

align trajectories sort by overperformance

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.

Strengthening the Reporting of Observational Studies in Epidemiology Using Mendelian Randomization

2021 1.9k citations Veronika Skrivankova, Rebecca C. Richmond et al. JAMA profile →
Strengthening the reporting of observational studies in epidemiology using mendelian randomisation (STROBE-MR): explanation and elaboration

2021 861 citations Veronika Skrivankova, Rebecca C. Richmond et al. BMJ profile →
Genomic atlas of the plasma metabolome prioritizes metabolites implicated in human diseases

2023 421 citations Tianyuan Lu, U. Pettersson et al. profile →
The health effects of vitamin D supplementation: evidence from human studies

2021 309 citations Despoina Manousaki, Katerina Trajanoska et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
J. Brent Richards Canada	44	3.3k	2.6k	2.0k	1.3k	1.2k	156	9.7k
Fernando Rivadeneira Netherlands	56	1.6k 0.5×	3.0k 1.1×	1.4k 0.7×	1.8k 1.4×	987 0.8×	274	10.8k
Joyce B. J. van Meurs Netherlands	56	1.9k 0.6×	3.3k 1.3×	2.6k 1.3×	1.3k 1.0×	616 0.5×	232	11.5k
Donald W. Bowden United States	59	3.7k 1.1×	4.1k 1.6×	1.0k 0.5×	1.9k 1.5×	1.9k 1.6×	359	14.7k
Karl Insogna United States	66	1.9k 0.6×	5.9k 2.3×	1.4k 0.7×	2.1k 1.6×	689 0.6×	237	15.1k
Jonathan H. Tobias United Kingdom	45	1.7k 0.5×	1.7k 0.6×	1.1k 0.6×	1.3k 1.0×	748 0.6×	255	8.1k
Takayuki Hosoi Japan	47	1.7k 0.5×	3.1k 1.2×	1.1k 0.6×	721 0.6×	405 0.3×	222	8.9k
Philip Haycock United Kingdom	22	6.2k 1.9×	3.4k 1.3×	989 0.5×	2.1k 1.6×	1.9k 1.6×	38	13.1k
Barbara Obermayer‐Pietsch Austria	49	729 0.2×	2.2k 0.8×	2.3k 1.2×	897 0.7×	718 0.6×	259	8.6k
Bonny Specker United States	51	1.6k 0.5×	1.3k 0.5×	1.6k 0.8×	1.5k 1.2×	957 0.8×	185	9.4k
Michael V. Holmes United Kingdom	41	3.5k 1.0×	2.5k 0.9×	730 0.4×	1.6k 1.2×	1.8k 1.5×	137	10.9k

Countries citing papers authored by J. Brent Richards

Since Specialization

Citations

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

Fields of papers citing papers by J. Brent Richards

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by J. Brent Richards. 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 J. Brent Richards. The network helps show where J. Brent Richards may publish in the future.

Co-authorship network of co-authors of J. Brent Richards

This figure shows the co-authorship network connecting the top 25 collaborators of J. Brent Richards. A scholar is included among the top collaborators of J. Brent Richards 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 J. Brent Richards. J. Brent Richards 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

Nakanishi, Tomoko, Julian Willett, Yossi Farjoun, et al.. (2023). Alternative splicing in lung influences COVID-19 severity and respiratory diseases. Nature Communications. 14(1). 6198–6198. 10 indexed citations

Forgetta, Vincenzo, Rui Li, Alexandre Bélisle, et al.. (2022). Cohort profile: genomic data for 26 622 individuals from the Canadian Longitudinal Study on Aging (CLSA). BMJ Open. 12(3). e059021–e059021. 31 indexed citations

Skrivankova, Veronika, Rebecca C. Richmond, Benjamin Woolf, et al.. (2021). Strengthening the Reporting of Observational Studies in Epidemiology Using Mendelian Randomization. JAMA. 326(16). 1614–1614. 1946 indexed citations breakdown →

Harroud, Adil, Despoina Manousaki, Guillaume Butler‐Laporte, et al.. (2021). The relative contributions of obesity, vitamin D, leptin, and adiponectin to multiple sclerosis risk: A Mendelian randomization mediation analysis. Multiple Sclerosis Journal. 27(13). 1994–2000. 31 indexed citations

Yazdanpanah, Nahid, Mojgan Yazdanpanah, Ye Wang, et al.. (2021). Clinically Relevant Circulating Protein Biomarkers for Type 1 Diabetes: Evidence From a Two-Sample Mendelian Randomization Study. Diabetes Care. 45(1). 169–177. 36 indexed citations

Lu, Tianyuan, Vincenzo Forgetta, J. Brent Richards, et al.. (2021). Block coordinate descent algorithm improves variable selection and estimation in error‐in‐variables regression. Genetic Epidemiology. 45(8). 874–890. 5 indexed citations

Peters, Tricia M., Michael V. Holmes, J. Brent Richards, et al.. (2020). Sex Differences in the Risk of Coronary Heart Disease Associated With Type 2 Diabetes: A Mendelian Randomization Analysis. Diabetes Care. 44(2). 556–562. 26 indexed citations

Harroud, Adil, J. Brent Richards, & Sergio E. Baranzini. (2020). Mendelian randomization study shows no causal effects of serum urate levels on the risk of MS. Neurology Neuroimmunology & Neuroinflammation. 8(1). 7 indexed citations

Desch, Karl C., Ayse Bilge Ozel, Matthew Halvorsen, et al.. (2020). Whole-exome sequencing identifies rare variants in STAB2 associated with venous thromboembolic disease. Blood. 136(5). 533–541. 31 indexed citations

10.

Jiang, Lai, Karim Oualkacha, Vanessa Didelez, et al.. (2019). Constrained instruments and their application to Mendelian randomization with pleiotropy. Genetic Epidemiology. 43(4). 373–401. 11 indexed citations

11.

Laurent, Lætitia, Sirui Zhou, Vincenzo Forgetta, et al.. (2019). Identification and Validation of Targets for Osteoporosis: Evidence from Whole exome Sequencing in 42,263 individuals, CRISPR-Cas9 and murine models. Queensland's institutional digital repository (The University of Queensland). 1 indexed citations

12.

Trajanoska, Katerina, John A. Morris, Ling Oei, et al.. (2018). Assessment of the genetic and clinical determinants of fracture risk: genome wide association and mendelian randomisation study. BMJ. 362. k3225–k3225. 171 indexed citations

13.

Tanaka, Ken-ichiro, Yingben Xue, Loan Nguyen‐Yamamoto, et al.. (2018). FAM210A is a novel determinant of bone and muscle structure and strength. Proceedings of the National Academy of Sciences. 115(16). E3759–E3768. 35 indexed citations

14.

Mullin, Benjamin H., Jing Hua Zhao, Suzanne J. Brown, et al.. (2017). Genome-wide association study meta-analysis for quantitative ultrasound parameters of bone identifies five novel loci for broadband ultrasound attenuation. Human Molecular Genetics. 26(14). 2791–2802. 28 indexed citations

15.

Ruth, Katherine S., Purdey J. Campbell, Ee Mun Lim, et al.. (2015). Genome-wide association study with 1000 genomes imputation identifies signals for nine sex hormone-related phenotypes. European Journal of Human Genetics. 24(2). 284–290. 72 indexed citations

16.

Li, Rui, Alexandre Montpetit, Marylène Rousseau, et al.. (2013). Somatic point mutations occurring early in development: a monozygotic twin study. Journal of Medical Genetics. 51(1). 28–34. 53 indexed citations

17.

Zheng, Hou‐Feng, Emma L. Duncan, Laura M. Yerges‐Armstrong, et al.. (2013). Meta-analysis of genome-wide studies identifies MEF2C SNPs associated with bone mineral density at forearm. QUT ePrints (Queensland University of Technology). 1 indexed citations

18.

Xu, Changjiang, Nicholas G. Martin, Zari Dastani, et al.. (2013). Correction: Multiple Regression Methods Show Great Potential for Rare Variant Association Tests. PLoS ONE. 8(3). 1 indexed citations

19.

Zheng, Hou‐Feng, et al.. (2013). Empirical power of very rare variants for common traits and disease: results from sanger sequencing 1998 individuals. European Journal of Human Genetics. 21(9). 1027–1030. 12 indexed citations

20.

Zheng, Hou‐Feng, Timothy D. Spector, & J. Brent Richards. (2011). Insights into the genetics of osteoporosis from recent genome-wide association studies. Expert Reviews in Molecular Medicine. 13. e28–e28. 30 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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