| Title |
Advances in understanding the genetic basis of diabetic kidney disease
|
|---|---|
| Published in |
Acta Diabetologica, August 2018
|
| DOI | 10.1007/s00592-018-1193-0 |
| Pubmed ID | |
| Authors |
Man Li, Marcus G. Pezzolesi |
| Abstract |
Diabetic kidney disease (DKD) is a devastating complication of Type 1 and Type 2 diabetes and leads to increased morbidity and mortality. Earlier work in families has provided strong evidence that heredity is a major determinant of DKD. Previous linkage analyses and candidate gene studies have identified potential DKD genes; however, such approaches have largely been unsuccessful. Genome-wide association studies (GWAS) have made significant contribution in identifying SNPs associated with common complex diseases. Thanks to advanced technology, new analytical approaches, and international research collaborations, many DKD GWASs have reported unique genes, highlighted novel biological pathways and suggested new disease mechanisms. This review summarizes the current state of GWAS technology; findings from GWASs of DKD and its related traits conducted over the past 15 years and discuss the future of this field. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 3 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 34 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 6 | 18% |
| Student > Ph. D. Student | 5 | 15% |
| Student > Postgraduate | 3 | 9% |
| Student > Master | 3 | 9% |
| Student > Doctoral Student | 2 | 6% |
| Other | 2 | 6% |
| Unknown | 13 | 38% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 6 | 18% |
| Medicine and Dentistry | 4 | 12% |
| Pharmacology, Toxicology and Pharmaceutical Science | 3 | 9% |
| Agricultural and Biological Sciences | 3 | 9% |
| Nursing and Health Professions | 1 | 3% |
| Other | 2 | 6% |
| Unknown | 15 | 44% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 07 November 2021.
All research outputs
#14,138,420
of 23,099,576 outputs
Outputs from Acta Diabetologica
#470
of 932 outputs
Outputs of similar age
#179,386
of 330,726 outputs
Outputs of similar age from Acta Diabetologica
#8
of 31 outputs
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We're also able to compare this research output to 31 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 67% of its contemporaries.