Impact of nine common type 2 diabetes risk polymorphisms in Asian Indian Sikhs: PPARG2 (Pro12Ala), IGF2BP2, TCF7L2 and FTO variants confer a significant risk

<p>Abstract</p> <p>Background</p> <p>Recent genome-wide association (GWA) studies have identified several unsuspected genes associated with type 2 diabetes (T2D) with previously unknown functions. In this investigation, we have examined the role of 9 most significant SNPs reported in GWA studies: [peroxisome proliferator-activated receptor gamma 2 (<it>PPARG2</it>; rs 1801282); insulin-like growth factor two binding protein 2 (<it>IGF2BP2</it>; rs 4402960); cyclin-dependent kinase 5, a regulatory subunit-associated protein1-like 1 (<it>CDK5</it>; rs7754840); a zinc transporter and member of solute carrier family 30 (<it>SLC30A8</it>; rs13266634); a variant found near cyclin-dependent kinase inhibitor 2A (<it>CDKN2A</it>; rs10811661); hematopoietically expressed homeobox (<it>HHEX</it>; rs 1111875); transcription factor-7-like 2 (<it>TCF7L2</it>; rs 10885409); potassium inwardly rectifying channel subfamily J member 11(<it>KCNJ11</it>; rs 5219); and fat mass obesity-associated gene (<it>FTO</it>; rs 9939609)].</p> <p>Methods</p> <p>We genotyped these SNPs in a case-control sample of 918 individuals consisting of 532 T2D cases and 386 normal glucose tolerant (NGT) subjects of an Asian Sikh community from North India. We tested the association between T2D and each SNP using unconditional logistic regression before and after adjusting for age, gender, and other covariates. We also examined the impact of these variants on body mass index (BMI), waist to hip ratio (WHR), fasting insulin, and glucose and lipid levels using multiple linear regression analysis.</p> <p>Results</p> <p>Four of the nine SNPs revealed a significant association with T2D; <it>PPARG2 </it>(Pro12Ala) [odds ratio (OR) 0.12; 95% confidence interval (CI) (0.03–0.52); p = 0.005], <it>IGF2BP2 </it>[OR 1.37; 95% CI (1.04–1.82); p = 0.027], <it>TCF7L2 </it>[OR 1.64; 95% CI (1.20–2.24); p = 0.001] and <it>FTO </it>[OR 1.46; 95% CI (1.11–1.93); p = 0.007] after adjusting for age, sex and BMI. Multiple linear regression analysis revealed significant association of two of nine investigated loci with diabetes-related quantitative traits. The 'C' (risk) allele of <it>CDK5 </it>(rs 7754840) was significantly associated with decreased HDL-cholesterol levels in both NGT (p = 0.005) and combined (NGT and T2D) (0.005) groups. The less common 'C' (risk) allele of <it>TCF7L2 </it>(rs 10885409) was associated with increased LDL-cholesterol (p = 0.010) in NGT and total and LDL-cholesterol levels (p = 0.008; p = 0.003, respectively) in combined cohort.</p> <p>Conclusion</p> <p>To our knowledge, this is first study reporting the role of some recently emerged loci with T2D in a high risk population of Asian Indian origin. Further investigations are warranted to understand the pathway-based functional implications of these important loci in T2D pathophysiology in different ethnicities.</p

Forest area estimation and reporting: implications for conservation, management and REDD

Periodic estimation, monitoring and reporting on area under forest and plantation types and afforestation rates are critical to forest and biodiversity conservation, sustainable forest management and for meeting international commitments. This article is aimed at assessing the adequacy of the current monitoring and reporting approach adopted in India in the context of new challenges of conservation and reporting to international conventions and agencies. The analysis shows that the current mode of monitoring and reporting of forest area is inadequate to meet the national and international requirements. India could be potentially over-reporting the area under forests by including many non-forest tree categories such as commercial plantations of coconut, cashew, coffee and rubber, and fruit orchards. India may also be under-reporting deforestation by reporting only gross forest area at the state and national levels. There is a need for monitoring and reporting of forest cover, deforestation and afforestation rates according to categories such as (i) natural/primary forest, (ii) secondary/degraded forests, (iii) forest plantations, (iv) commercial plantations, (v) fruit orchards and (vi) scattered trees

The Sedimentary Geochemistry and Paleoenvironments Project.

Authors thank the donors of The American Chemical Society Petroleum Research Fund for partial support of SGP website development (61017-ND2). EAS is funded by National Science Foundation grant (NSF) EAR-1922966. BGS authors (JE, PW) publish with permission of the Executive Director of the British Geological Survey, UKRI.Publisher PDFPeer reviewe