Meta-analysis of genome-wide association data and large-scale replication identifies additional susceptibility loci for type 2 diabetes

Genome-wide association (GWA) studies have identified multiple loci at which common variants modestly but reproducibly influence risk of type 2 diabetes (T2D). Established associations to common and rare variants explain only a small proportion of the heritability of T2D. As previously published analyses had limited power to identify variants with modest effects, we carried out meta-analysis of three T2D GWA scans comprising 10,128 individuals of European descent and approximately 2.2 million SNPs (directly genotyped and imputed), followed by replication testing in an independent sample with an effective sample size of up to 53,975. We detected at least six previously unknown loci with robust evidence for association, including the JAZF1 (P = 5.0 x 10(-14)), CDC123-CAMK1D (P = 1.2 x 10(-10)), TSPAN8-LGR5 (P = 1.1 x 10(-9)), THADA (P = 1.1 x 10(-9)), ADAMTS9 (P = 1.2 x 10(-8)) and NOTCH2 (P = 4.1 x 10(-8)) gene regions. Our results illustrate the value of large discovery and follow-up samples for gaining further insights into the inherited basis of T2D.     

Common variants at 12q14 and 12q24 are associated with hippocampal volume

Aging is associated with reductions in hippocampal volume that are accelerated by Alzheimer's disease and vascular risk factors. Our genome-wide association study (GWAS) of dementia-free persons (n = 9,232) identified 46 SNPs at four loci with P values of <4.0 × 10(-7). In two additional samples (n = 2,318), associations were replicated at 12q14 within MSRB3-WIF1 (discovery and replication; rs17178006; P = 5.3 × 10(-11)) and at 12q24 near HRK-FBXW8 (rs7294919; P = 2.9 × 10(-11)). Remaining associations included one SNP at 2q24 within DPP4 (rs6741949; P = 2.9 × 10(-7)) and nine SNPs at 9p33 within ASTN2 (rs7852872; P = 1.0 × 10(-7)); along with the chromosome 12 associations, these loci were also associated with hippocampal volume (P < 0.05) in a third younger, more heterogeneous sample (n = 7,794). The SNP in ASTN2 also showed suggestive association with decline in cognition in a largely independent sample (n = 1,563). These associations implicate genes related to apoptosis (HRK), development (WIF1), oxidative stress (MSR3B), ubiquitination (FBXW8) and neuronal migration (ASTN2), as well as enzymes targeted by new diabetes medications (DPP4), indicating new genetic influences on hippocampal size and possibly the risk of cognitive decline and dementia.     

Subcellular trafficking of the substrate transporters GLUT4 and CD36 in cardiomyocytes

Cardiomyocytes use glucose as well as fatty acids for ATP production. These substrates are transported into the cell by glucose transporter 4 (GLUT4) and the fatty acid transporter CD36. Besides being located at the sarcolemma, GLUT4 and CD36 are stored in intracellular compartments. Raised plasma insulin concentrations and increased cardiac work will stimulate GLUT4 as well as CD36 to translocate to the sarcolemma. As so far studied, signaling pathways that regulate GLUT4 translocation similarly affect CD36 translocation. During the development of insulin resistance and type 2 diabetes, CD36 becomes permanently localized at the sarcolemma, whereas GLUT4 internalizes. This juxtaposed positioning of GLUT4 and CD36 is important for aberrant substrate uptake in the diabetic heart: chronically increased fatty acid uptake at the expense of glucose. To explain the differences in subcellular localization of GLUT4 and CD36 in type 2 diabetes, recent research has focused on the role of proteins involved in trafficking of cargo between subcellular compartments. Several of these proteins appear to be similarly involved in both GLUT4 and CD36 translocation. Others, however, have different roles in either GLUT4 or CD36 translocation. These trafficking components, which are differently involved in GLUT4 or CD36 translocation, may be considered novel targets for the development of therapies to restore the imbalanced substrate utilization that occurs in obesity, insulin resistance and diabetic cardiomyopathy.     

Joint analysis is more efficient than replication-based analysis for two-stage genome-wide association studies

Genome-wide association is a promising approach to identify common genetic variants that predispose to human disease. Because of the high cost of genotyping hundreds of thousands of markers on thousands of subjects, genome-wide association studies often follow a staged design in which a proportion (pi(samples)) of the available samples are genotyped on a large number of markers in stage 1, and a proportion (pi(samples)) of these markers are later followed up by genotyping them on the remaining samples in stage 2. The standard strategy for analyzing such two-stage data is to view stage 2 as a replication study and focus on findings that reach statistical significance when stage 2 data are considered alone. We demonstrate that the alternative strategy of jointly analyzing the data from both stages almost always results in increased power to detect genetic association, despite the need to use more stringent significance levels, even when effect sizes differ between the two stages. We recommend joint analysis for all two-stage genome-wide association studies, especially when a relatively large proportion of the samples are genotyped in stage 1 (pi(samples) >or= 0.30), and a relatively large proportion of markers are selected for follow-up in stage 2 (pi(markers) >or= 0.01).