David C. Liewald

25.8k total citations · 3 hit papers
37 papers, 2.8k citations indexed

About

David C. Liewald is a scholar working on Genetics, Pediatrics, Perinatology and Child Health and Experimental and Cognitive Psychology. According to data from OpenAlex, David C. Liewald has authored 37 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Genetics, 8 papers in Pediatrics, Perinatology and Child Health and 8 papers in Experimental and Cognitive Psychology. Recurrent topics in David C. Liewald's work include Genetic Associations and Epidemiology (24 papers), Birth, Development, and Health (8 papers) and Cognitive Abilities and Testing (6 papers). David C. Liewald is often cited by papers focused on Genetic Associations and Epidemiology (24 papers), Birth, Development, and Health (8 papers) and Cognitive Abilities and Testing (6 papers). David C. Liewald collaborates with scholars based in United Kingdom, Australia and United States. David C. Liewald's co-authors include Ian J. Deary, Gail Davies, Catharine R. Galé, Andrew M. McIntosh, Stuart J. Ritchie, Sarah E. Harris, Saskia P. Hagenaars, Simon R. Cox, W. David Hill and Mark E. Bastin and has published in prestigious journals such as Nature, Nature Communications and Nature Genetics.

In The Last Decade

David C. Liewald

37 papers receiving 2.8k citations

Hit Papers

Sex Differences in the Adult Human Brain: Evidence from 5... 2016 2026 2019 2022 2018 2016 2023 100 200 300 400

Peers

David C. Liewald
Frank Mentch United States
Saskia P. Hagenaars United Kingdom
J. Eric Schmitt United States
Frank Mentch United States
David C. Liewald
Citations per year, relative to David C. Liewald David C. Liewald (= 1×) peers Frank Mentch

Countries citing papers authored by David C. Liewald

Since Specialization
Citations

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

Fields of papers citing papers by David C. Liewald

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David C. Liewald. 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 David C. Liewald. The network helps show where David C. Liewald may publish in the future.

Co-authorship network of co-authors of David C. Liewald

This figure shows the co-authorship network connecting the top 25 collaborators of David C. Liewald. A scholar is included among the top collaborators of David C. Liewald 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 David C. Liewald. David C. Liewald is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Xia, Charley, Mattia Marchi, Hyeokmoon Kweon, et al.. (2025). Deciphering the influence of socioeconomic status on brain structure: insights from Mendelian randomization. Molecular Psychiatry. 30(10). 4613–4626. 1 indexed citations
2.
Bernabeu, Elena, Daniel L. McCartney, Danni A. Gadd, et al.. (2023). Refining epigenetic prediction of chronological and biological age. Genome Medicine. 15(1). 12–12. 65 indexed citations breakdown →
3.
Hillary, Robert F., Archie Campbell, Lee Murphy, et al.. (2023). Integration of datasets for individual prediction of DNA methylation-based biomarkers. Genome biology. 24(1). 278–278. 1 indexed citations
4.
Xia, Charley, Sarah J. Pickett, David C. Liewald, et al.. (2023). The contributions of mitochondrial and nuclear mitochondrial genetic variation to neuroticism. Nature Communications. 14(1). 3146–3146. 4 indexed citations
5.
Buchanan, Colin R., Mark E. Bastin, Stuart J. Ritchie, et al.. (2020). The effect of network thresholding and weighting on structural brain networks in the UK Biobank. NeuroImage. 211. 116443–116443. 81 indexed citations
6.
Halachev, Mihail, Alison Meynert, Martin S. Taylor, et al.. (2019). Increased ultra-rare variant load in an isolated Scottish population impacts exonic and regulatory regions. PLoS Genetics. 15(11). e1008480–e1008480. 14 indexed citations
7.
Hillary, Robert F., Daniel L. McCartney, Sarah E. Harris, et al.. (2019). Genome and epigenome wide studies of neurological protein biomarkers in the Lothian Birth Cohort 1936. Nature Communications. 10(1). 3160–3160. 36 indexed citations
8.
Hill, W. David, Neil M Davies, Stuart J. Ritchie, et al.. (2019). Genome-wide analysis identifies molecular systems and 149 genetic loci associated with income. Nature Communications. 10(1). 5741–5741. 110 indexed citations
9.
Calvin, Catherine M., Saskia P. Hagenaars, John Gallacher, et al.. (2019). Sex-specific moderation by lifestyle and psychosocial factors on the genetic contributions to adiposity in 112,151 individuals from UK Biobank. Scientific Reports. 9(1). 363–363. 5 indexed citations
10.
Hill, W. David, Alexander Weiß, David C. Liewald, et al.. (2019). Genetic contributions to two special factors of neuroticism are associated with affluence, higher intelligence, better health, and longer life. Molecular Psychiatry. 25(11). 3034–3052. 49 indexed citations
11.
Shen, Xueyi, Lianne M. Reus, Simon R. Cox, et al.. (2017). Subcortical volume and white matter integrity abnormalities in major depressive disorder: findings from UK Biobank imaging data. Scientific Reports. 7(1). 5547–5547. 86 indexed citations
12.
Hagenaars, Saskia P., W. David Hill, Sarah E. Harris, et al.. (2017). Genetic prediction of male pattern baldness. PLoS Genetics. 13(2). e1006594–e1006594. 86 indexed citations
13.
Hagenaars, Saskia P., Simon R. Cox, W. David Hill, et al.. (2017). Genetic contributions to Trail Making Test performance in UK Biobank. Molecular Psychiatry. 23(7). 1575–1583. 19 indexed citations
14.
Harris, Sarah E., Saskia P. Hagenaars, Gail Davies, et al.. (2016). Molecular genetic contributions to self-rated health. International Journal of Epidemiology. 46(3). dyw219–dyw219. 50 indexed citations
15.
Cox, Simon R., Stuart J. Ritchie, Elliot M. Tucker–Drob, et al.. (2016). Ageing and brain white matter structure in 3,513 UK Biobank participants. Nature Communications. 7(1). 13629–13629. 321 indexed citations breakdown →
16.
Hill, W. David, Gail Davies, David C. Liewald, Andrew M. McIntosh, & Ian J. Deary. (2015). Age-Dependent Pleiotropy Between General Cognitive Function and Major Psychiatric Disorders. Biological Psychiatry. 80(4). 266–273. 57 indexed citations
17.
McIntosh, Andrew M., Alan J. Gow, Michelle Luciano, et al.. (2013). Polygenic Risk for Schizophrenia Is Associated with Cognitive Change Between Childhood and Old Age. Biological Psychiatry. 73(10). 938–943. 99 indexed citations
18.
Deary, Ian J., Jian Yang, Gail Davies, et al.. (2012). Genetic contributions to stability and change in intelligence from childhood to old age. Nature. 482(7384). 212–215. 169 indexed citations
19.
Kerr, Shona M., David C. Liewald, Archie Campbell, et al.. (2010). Generation Scotland: Donor DNA Databank; A control DNA resource. BMC Medical Genetics. 11(1). 166–166. 2 indexed citations
20.
Houlihan, Lorna M., Gail Davies, Albert Tenesa, et al.. (2010). Common Variants of Large Effect in F12, KNG1, and HRG Are Associated with Activated Partial Thromboplastin Time. The American Journal of Human Genetics. 86(4). 626–631. 64 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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