CACNB2 Is a Novel Susceptibility Gene for Diabetic Retinopathy in Type 1 Diabetes.
Erkka ValoNiina SandholmAnmol KumarKustaa HietalaAnna SyreeniCarol ForsblomKati Juuti-UusitaloHeli SkottmanMinako ImamuraShiro MaedaPaula A SummanenMarkku LehtoPer-Henrik Groopnull nullPublished in: Diabetes (2019)
Diabetic retinopathy is a common diabetes complication that threatens the eyesight and may eventually lead to acquired visual impairment or blindness. While a substantial heritability has been reported for proliferative diabetic retinopathy (PDR), only a few genetic risk factors have been identified. Using genome-wide sib pair linkage analysis including 361 individuals with type 1 diabetes, we found suggestive evidence of linkage with PDR at chromosome 10p12 overlapping the CACNB2 gene (logarithm of odds = 2.73). Evidence of association between variants in CACNB2 and PDR was also found in association analysis of 4,005 individuals with type 1 diabetes with an odds ratio of 0.83 and P value of 8.6 × 10-4 for rs11014284. Sequencing of CACNB2 revealed two coding variants, R476C/rs202152674 and S502L/rs137886839. CACNB2 is abundantly expressed in retinal cells and encodes the β2 subunit of the L-type calcium channel. Blocking vascular endothelial growth factor (VEGF) by intravitreous anti-VEGF injections is a promising clinical therapy to treat PDR. Our data show that L-type calcium channels regulate VEGF expression and secretion from retinal pigment epithelial cells (ARPE19) and support the role of CACNB2 via regulation of VEGF in the pathogenesis of PDR. However, further genetic and functional studies are necessary to consolidate the findings.
Keyphrases
- diabetic retinopathy
- vascular endothelial growth factor
- genome wide
- copy number
- type diabetes
- dna methylation
- optical coherence tomography
- endothelial cells
- risk factors
- cardiovascular disease
- induced apoptosis
- poor prognosis
- single cell
- gene expression
- transcription factor
- cell cycle arrest
- electronic health record
- ultrasound guided
- human immunodeficiency virus
- big data
- case control
- cell therapy
- data analysis
- long non coding rna
- protein kinase
- platelet rich plasma
- cell death
- artificial intelligence
- cell proliferation