scholarly journals Large-scale association analysis provides insights into the genetic architecture and pathophysiology of type 2 diabetes

2012 ◽  
Vol 44 (9) ◽  
pp. 981-990 ◽  
Author(s):  
2020 ◽  
Vol 8 (1) ◽  
pp. e001140
Author(s):  
Xinpei Wang ◽  
Jinzhu Jia ◽  
Tao Huang

ObjectiveWe aimed to estimate genetic correlation, identify shared loci and test causality between leptin levels and type 2 diabetes (T2D).Research design and methodsOur study consists of three parts. First, we calculated the genetic correlation of leptin levels and T2D or glycemic traits by using linkage disequilibrium score regression analysis. Second, we conducted a large-scale genome-wide cross-trait meta-analysis using cross-phenotype association to identify shared loci between trait pairs that showed significant genetic correlations in the first part. In the end, we carried out a bidirectional MR analysis to find out whether there is a causal relationship between leptin levels and T2D or glycemic traits.ResultsWe found positive genetic correlations between leptin levels and T2D (Rg=0.3165, p=0.0227), fasting insulin (FI) (Rg=0.517, p=0.0076), homeostasis model assessment-insulin resistance (HOMA-IR) (Rg=0.4785, p=0.0196), as well as surrogate estimates of β-cell function (HOMA-β) (Rg=0.4456, p=0.0214). We identified 12 shared loci between leptin levels and T2D, 1 locus between leptin levels and FI, 1 locus between leptin levels and HOMA-IR, and 1 locus between leptin levels and HOMA-β. We newly identified eight loci that did not achieve genome-wide significance in trait-specific genome-wide association studies. These shared genes were enriched in pancreas, thyroid gland, skeletal muscle, placenta, liver and cerebral cortex. In addition, we found that 1-SD increase in HOMA-IR was causally associated with a 0.329 ng/mL increase in leptin levels (β=0.329, p=0.001).ConclusionsOur results have shown the shared genetic architecture between leptin levels and T2D and found causality of HOMA-IR on leptin levels, shedding light on the molecular mechanisms underlying the association between leptin levels and T2D.


2010 ◽  
Vol 42 (7) ◽  
pp. 579-589 ◽  
Author(s):  
Benjamin F Voight ◽  
◽  
Laura J Scott ◽  
Valgerdur Steinthorsdottir ◽  
Andrew P Morris ◽  
...  

2011 ◽  
Vol 43 (4) ◽  
pp. 388-388 ◽  
Author(s):  
Benjamin F Voight ◽  
◽  
Laura J Scott ◽  
Valgerdur Steinthorsdottir ◽  
Andrew P Morris ◽  
...  

Diabetes ◽  
2005 ◽  
Vol 54 (8) ◽  
pp. 2487-2491 ◽  
Author(s):  
M. N. Weedon ◽  
K. R. Owen ◽  
B. Shields ◽  
G. Hitman ◽  
M. Walker ◽  
...  

2010 ◽  
Vol 11 (1) ◽  
Author(s):  
Vesna Boraska ◽  
Nigel W Rayner ◽  
Christopher J Groves ◽  
Timothy M Frayling ◽  
Mahamadou Diakite ◽  
...  

Diabetes ◽  
2018 ◽  
Vol 67 (Supplement 1) ◽  
pp. 2393-PUB
Author(s):  
KENICHIRO TAKAHASHI ◽  
MINORI SHINODA ◽  
RIKA SAKAMOTO ◽  
JUN SUZUKI ◽  
TADASHI YAMAKAWA ◽  
...  

2014 ◽  
Vol 20 (22) ◽  
pp. 3610-3619 ◽  
Author(s):  
F.K. Kavvoura ◽  
M. Pappa ◽  
E. Evangelou ◽  
E.E. Ntzani

2021 ◽  
Vol 10 (1) ◽  
pp. e001087
Author(s):  
Tarek F Radwan ◽  
Yvette Agyako ◽  
Alireza Ettefaghian ◽  
Tahira Kamran ◽  
Omar Din ◽  
...  

A quality improvement (QI) scheme was launched in 2017, covering a large group of 25 general practices working with a deprived registered population. The aim was to improve the measurable quality of care in a population where type 2 diabetes (T2D) care had previously proved challenging. A complex set of QI interventions were co-designed by a team of primary care clinicians and educationalists and managers. These interventions included organisation-wide goal setting, using a data-driven approach, ensuring staff engagement, implementing an educational programme for pharmacists, facilitating web-based QI learning at-scale and using methods which ensured sustainability. This programme was used to optimise the management of T2D through improving the eight care processes and three treatment targets which form part of the annual national diabetes audit for patients with T2D. With the implemented improvement interventions, there was significant improvement in all care processes and all treatment targets for patients with diabetes. Achievement of all the eight care processes improved by 46.0% (p<0.001) while achievement of all three treatment targets improved by 13.5% (p<0.001). The QI programme provides an example of a data-driven large-scale multicomponent intervention delivered in primary care in ethnically diverse and socially deprived areas.


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