Åke Lernmark

47.1k total citations · 7 hit papers
710 papers, 26.1k citations indexed

About

Åke Lernmark is a scholar working on Genetics, Surgery and Endocrinology, Diabetes and Metabolism. According to data from OpenAlex, Åke Lernmark has authored 710 papers receiving a total of 26.1k indexed citations (citations by other indexed papers that have themselves been cited), including 564 papers in Genetics, 506 papers in Surgery and 405 papers in Endocrinology, Diabetes and Metabolism. Recurrent topics in Åke Lernmark's work include Diabetes and associated disorders (547 papers), Pancreatic function and diabetes (487 papers) and Diabetes Management and Research (326 papers). Åke Lernmark is often cited by papers focused on Diabetes and associated disorders (547 papers), Pancreatic function and diabetes (487 papers) and Diabetes Management and Research (326 papers). Åke Lernmark collaborates with scholars based in United States, Sweden and Germany. Åke Lernmark's co-authors include Mona Landin‐Olsson, William Hagopian, G. Sundkvist, Bo Hellman, Johnny Ludvigsson, Jeffrey P. Krischer, Ingrid Kockum, Desmond Schatz, Flemming Pociot and Ezio Bonifacio and has published in prestigious journals such as Nature, Science and New England Journal of Medicine.

In The Last Decade

Åke Lernmark

694 papers receiving 25.0k citations

Hit Papers

Type 1 diabetes mellitus 1982 2026 1996 2011 2017 2015 2011 1982 2016 250 500 750
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.

  1. Type 1 diabetes mellitus
    2017 938 citations Soffia Guðbjörnsdóttir, Ezio Bonifacio et al. profile →
  2. Staging Presymptomatic Type 1 Diabetes: A Scientific Statement of JDRF, the Endocrine Society, and the American Diabetes Association
    2015 735 citations Jessica L. Dunne, Jeffrey P. Krischer et al. Diabetes Care profile →
  3. Guidelines and Recommendations for Laboratory Analysis in the Diagnosis and Management of Diabetes Mellitus
    2011 710 citations David B. Sacks, Mark A. Arnold et al. profile →
  4. Autoantibodies in newly diagnosed diabetic children immunoprecipitate human pancreatic islet cell proteins
    1982 409 citations Johnny Ludvigsson, Åke Lernmark et al. profile →
  5. Genetic risk factors for type 1 diabetes
    2016 373 citations Flemming Pociot, Åke Lernmark profile →
  6. The 6 year incidence of diabetes-associated autoantibodies in genetically at-risk children: the TEDDY study
    2015 295 citations Jeffrey P. Krischer, Kristian Lynch et al. Diabetologia profile →
  7. Guidelines and Recommendations for Laboratory Analysis in the Diagnosis and Management of Diabetes Mellitus
    2023 116 citations David B. Sacks, Mark A. Arnold et al. Diabetes Care profile →

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Åke Lernmark 17.2k 14.7k 13.4k 4.1k 3.9k 710 26.1k
George S. Eisenbarth 26.0k 1.5× 19.6k 1.3× 18.6k 1.4× 4.6k 1.1× 9.0k 2.3× 510 37.0k
Ezio Bonifacio 13.9k 0.8× 12.2k 0.8× 10.8k 0.8× 2.3k 0.5× 3.6k 0.9× 354 20.4k
Desmond Schatz 11.0k 0.6× 8.6k 0.6× 9.4k 0.7× 3.4k 0.8× 2.8k 0.7× 301 17.8k
Kevan C. Herold 10.5k 0.6× 9.1k 0.6× 8.6k 0.6× 2.7k 0.7× 6.0k 1.5× 278 20.0k
Jørn Nerup 7.8k 0.5× 6.1k 0.4× 5.7k 0.4× 2.5k 0.6× 3.6k 0.9× 256 15.0k
Jerome I. Rotter 8.3k 0.5× 5.5k 0.4× 3.5k 0.3× 6.1k 1.5× 3.4k 0.9× 494 22.0k
Leonard C. Harrison 7.1k 0.4× 5.5k 0.4× 4.5k 0.3× 3.0k 0.7× 5.3k 1.4× 329 14.9k
Flemming Pociot 7.2k 0.4× 5.2k 0.4× 3.9k 0.3× 4.6k 1.1× 4.5k 1.1× 326 16.2k
Burkhard Göke 3.2k 0.2× 6.1k 0.4× 6.4k 0.5× 6.0k 1.4× 2.7k 0.7× 423 20.1k
Hubert Kolb 5.1k 0.3× 4.7k 0.3× 4.6k 0.3× 4.4k 1.1× 4.6k 1.2× 309 17.6k

Countries citing papers authored by Åke Lernmark

Since Specialization
Citations

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

Fields of papers citing papers by Åke Lernmark

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Åke Lernmark

This figure shows the co-authorship network connecting the top 25 collaborators of Åke Lernmark. A scholar is included among the top collaborators of Åke Lernmark 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 Åke Lernmark. Åke Lernmark 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.
Zhao, Lue Ping, George K. Papadopoulos, Jay S. Skyler, et al.. (2024). Progression to type 1 diabetes in the DPT-1 and TN07 clinical trials is critically associated with specific residues in HLA-DQA1-B1 heterodimers. Diabetologia. 67(11). 2481–2493.
2.
Teixeira, Pedro Filipe, Tadej Battelino, Annelie Carlsson, et al.. (2024). Assisting the implementation of screening for type 1 diabetes by using artificial intelligence on publicly available data. Diabetologia. 67(6). 985–994. 7 indexed citations
3.
Warncke, Katharina, Roy Tamura, Desmond Schatz, et al.. (2024). The Influence of Pubertal Development on Autoantibody Appearance and Progression to Type 1 Diabetes in the TEDDY Study. Journal of the Endocrine Society. 8(7). bvae103–bvae103.
4.
Sacks, David B., Mark A. Arnold, George L. Bakris, et al.. (2023). Guidelines and Recommendations for Laboratory Analysis in the Diagnosis and Management of Diabetes Mellitus. Diabetes Care. 46(10). e151–e199. 116 indexed citations breakdown →
5.
Salami, Falastin, Roy Tamura, Åke Lernmark, et al.. (2022). HbA1c as a time predictive biomarker for an additional islet autoantibody and type 1 diabetes in seroconverted TEDDY children. Pediatric Diabetes. 23(8). 1586–1593. 12 indexed citations
6.
Kwon, Bum Chul, Peter Achenbach, Vibha Anand, et al.. (2022). Islet Autoantibody Levels Differentiate Progression Trajectories in Individuals With Presymptomatic Type 1 Diabetes. Diabetes. 71(12). 2632–2641. 2 indexed citations
7.
Kwon, Bum Chul, Vibha Anand, Peter Achenbach, et al.. (2022). Progression of type 1 diabetes from latency to symptomatic disease is predicted by distinct autoimmune trajectories. Nature Communications. 13(1). 1514–1514. 22 indexed citations
8.
Johnson, Suzanne Bennett, Kristian Lynch, Roswith Roth, et al.. (2021). First-appearing islet autoantibodies for type 1 diabetes in young children: maternal life events during pregnancy and the child’s genetic risk. Diabetologia. 64(3). 591–602. 7 indexed citations
9.
Lernmark, Åke, Ezio Bonifacio, William Hagopian, et al.. (2021). Transcriptional networks in at-risk individuals identify signatures of type 1 diabetes progression. Science Translational Medicine. 13(587). 29 indexed citations
10.
Aydemir, Özkan, Janelle A. Noble, Jeffrey A. Bailey, et al.. (2019). Genetic Variation Within the HLA-DRA1 Gene Modulates Susceptibility to Type 1 Diabetes in HLA-DR3 Homozygotes. Diabetes. 68(7). 1523–1527. 13 indexed citations
11.
Sharma, Ashok, Xiang Liu, David Hadley, et al.. (2018). Identification of non-HLA genes associated with development of islet autoimmunity and type 1 diabetes in the prospective TEDDY cohort. Journal of Autoimmunity. 89. 90–100. 44 indexed citations
12.
13.
Krischer, Jeffrey P., Kristian Lynch, Åke Lernmark, et al.. (2017). Genetic and Environmental Interactions Modify the Risk of Diabetes-Related Autoimmunity by 6 Years of Age: The TEDDY Study. Diabetes Care. 40(9). 1194–1202. 130 indexed citations
14.
Svensson, Jannet, Anita Ramelius, Stefanie Eising, et al.. (2008). Decreasing humoral activity in siblings of type 1 diabetes children over a ten year period with increasing incidence of the disease. Lund University Publications (Lund University). 1 indexed citations
15.
Notkins, Abner Louis & Åke Lernmark. (2001). Autoimmune type 1 diabetes: resolved and unresolved issues. Journal of Clinical Investigation. 108(9). 1247–1252. 75 indexed citations
16.
Notkins, Abner Louis & Åke Lernmark. (2001). Autoimmune type 1 diabetes: resolved and unresolved issues. Journal of Clinical Investigation. 108(9). 1247–1252. 223 indexed citations
17.
Grubin, C. E., T. Daniels, Bert Toivola, et al.. (1994). A novel radioligand binding assay to determine diagnostic accuracy of isoform-specific glutamic acid decarboxylase antibodies in childhood IDDM. Diabetologia. 37(4). 344–350. 351 indexed citations
18.
Kockum, Ingrid, Ralf Waßmuth, Eva Holmberg, B Michelsen, & Åke Lernmark. (1994). Inheritance of MHC class II genes in IDDM studied in population-based affected and control families. Diabetologia. 37(11). 1105–1112. 13 indexed citations
19.
Claes, G, et al.. (1975). Glucagon and Insulin Release from the Allografted Canine Pancreas. European Surgical Research. 7(3). 170–180. 1 indexed citations
20.
Danielsson, Anna, et al.. (1969). Beobachtungen zum Wirkungsmechanismus des hypoglykämisch wirksamen Sulfonylharnstoff-Präparates HB 419.. Lund University Publications (Lund University). 5 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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