Seasonal forecasts of North Atlantic tropical cyclone activity in the North American Multi-Model Ensemble

The North American Multi-Model Ensemble (NMME)-Phase II models are evaluated in terms of their retrospective seasonal forecast skill of the North Atlantic (NA) tropical cyclone (TC) activity, with a focus on TC frequency. The TC identification and tracking algorithm is modified to accommodate model data at daily resolution. It is also applied to three reanalysis products at the spatial and temporal resolution of the NMME-Phase II ensemble to allow for a more objective estimation of forecast skill. When used with the reanalysis data, the TC tracking generates realistic climatological distributions of the NA TC formation and tracks, and represents the interannual variability of the NA TC frequency quite well. Forecasts with the multi-model ensemble (MME) when initialized in April and later tend to have skill in predicting the NA seasonal TC counts (and TC days). At longer leads, the skill is low or marginal, although one of the models produces skillful forecasts when initialized as early as January and February. At short lead times, while demonstrating the highest skill levels the MME also tends to significantly outperform the individual models and attain skill comparable to the reanalysis. In addition, the short-lead MME forecasts are quite reliable. At regional scales, the skill is rather limited and mostly present in the western tropical NA and the Caribbean Sea. It is found that the overall MME forecast skill is limited by poor representation of the low-frequency variability in the predicted TC frequency, and large fluctuations in skill on decadal time scales. Addressing these deficiencies is thought to increase the value of the NMME ensemble in providing operational guidance

Genetic Determinants of Circulating Sphingolipid Concentrations in European Populations

Sphingolipids have essential roles as structural components of cell membranes and in cell signalling, and disruption of their metabolism causes several diseases, with diverse neurological, psychiatric, and metabolic consequences. Increasingly, variants within a few of the genes that encode enzymes involved in sphingolipid metabolism are being associated with complex disease phenotypes. Direct experimental evidence supports a role of specific sphingolipid species in several common complex chronic disease processes including atherosclerotic plaque formation, myocardial infarction (MI), cardiomyopathy, pancreatic beta-cell failure, insulin resistance, and type 2 diabetes mellitus. Therefore, sphingolipids represent novel and important intermediate phenotypes for genetic analysis, yet little is known about the major genetic variants that influence their circulating levels in the general population. We performed a genome-wide association study (GWAS) between 318,237 single-nucleotide polymorphisms (SNPs) and levels of circulating sphingomyelin (SM), dihydrosphingomyelin (Dih-SM), ceramide (Cer), and glucosylceramide (GluCer) single lipid species (33 traits); and 43 matched metabolite ratios measured in 4,400 subjects from five diverse European populations. Associated variants (32) in five genomic regions were identified with genome-wide significant corrected p-values ranging down to 9.08 x 10(-66). The strongest associations were observed in or near 7 genes functionally involved in ceramide biosynthesis and trafficking: SPTLC3, LASS4, SGPP1, ATP10D, and FADS1-3. Variants in 3 loci (ATP10D, FADS3, and SPTLC3) associate with MI in a series of three German MI studies. An additional 70 variants across 23 candidate genes involved in sphingolipid-metabolizing pathways also demonstrate association (p = 10(-4) or less). Circulating concentrations of several key components in sphingolipid metabolism are thus under strong genetic control, and variants in these loci can be tested for a role in the development of common cardiovascular, metabolic, neurological, and psychiatric diseases

Copy Number Variation across European Populations

Genome analysis provides a powerful approach to test for evidence of genetic variation within and between geographical regions and local populations. Copy number variants which comprise insertions, deletions and duplications of genomic sequence provide one such convenient and informative source. Here, we investigate copy number variants from genome wide scans of single nucleotide polymorphisms in three European population isolates, the island of Vis in Croatia, the islands of Orkney in Scotland and the South Tyrol in Italy. We show that whereas the overall copy number variant frequencies are similar between populations, their distribution is highly specific to the population of origin, a finding which is supported by evidence for increased kinship correlation for specific copy number variants within populations

Family-based Genome-wide Association Study of South Indian Pedigrees Supports WNT7B as a Central Corneal Thickness Locus

Purpose To identify genetic risk factors contributing to central corneal thickness (CCT) in individuals from South India, a population with a high prevalence of ocular disorders. Methods: One hundred ninety-five individuals from 15 large South Indian pedigrees were genotyped using the Omni2.5 bead array. Family-based association for CCT was conducted using the score test in MERLIN. Results: Genome-wide association study (GWAS) identified strongest association for single nucleotide polymorphisms (SNPs) in the first intron of WNT7B and CCT (top SNP rs9330813; β = −0.57, 95% confidence interval [CI]: −0.78 to −0.36; P = 1.7 × 10−7). We further investigated rs9330813 in a Latino cohort and four independent European cohorts. A meta-analysis of these data sets demonstrated statistically significant association between rs9330813 and CCT (β = −3.94, 95% CI: −5.23 to −2.66; P = 1.7 × 10−9). WNT7B SNPs located in the same genomic region that includes rs9330813 have previously been associated with CCT in Latinos but with other ocular quantitative traits related to myopia (corneal curvature and axial length) in a Japanese population (rs10453441 and rs200329677). To evaluate the specificity of the observed WNT7B association with CCT in the South Indian families, we completed an ocular phenome-wide association study (PheWAS) for the top WNT7B SNPs using 45 ocular traits measured in these same families including corneal curvature and axial length. The ocular PheWAS results indicate that in the South Indian families WNT7B SNPs are primarily associated with CCT. Conclusions: The results indicate robust evidence for association between WNT7B SNPs and CCT in South Indian pedigrees, and suggest that WNT7B SNPs can have population-specific effects on ocular quantitative traits

When do myopia genes have their effect? Comparison of genetic risks between children and adults

Previous studies have identified many genetic loci for refractive error and myopia. We aimed to investigate the effect of these loci on ocular biometry as a function of age in children, adolescents, and adults. The study population consisted of three age groups identified from the international CREAM consortium: 5,490 individuals aged 25 years. All participants had undergone standard ophthalmic examination including measurements of axial length (AL) and corneal radius (CR). We examined the lead SNP at all 39 currently known genetic loci for refractive error identified from genome-wide association studies (GWAS), as well as a combined genetic risk score (GRS). The beta coefficient for association between SNP genotype or GRS versus AL/CR was compared across the three age groups, adjusting for age, sex, and principal components. Analyses were Bonferroni-corrected. In the age group <10 years, three loci (GJD2, CHRNG, ZIC2) were associated with AL/CR. In the age group 10–25 years, four loci (BMP2, KCNQ5, A2BP1, CACNA1D) were associated; and in adults 20 loci were associated. Association with GRS increased with age; β = 0.0016 per risk allele (P = 2 × 10–8) in <10 years, 0.0033 (P = 5 × 10–15) in 10- to 25-year-olds, and 0.0048 (P = 1 × 10–72) in adults. Genes with strongest effects (LAMA2, GJD2) had an early effect that increased with age. Our results provide insights on the age span during which myopia genes exert their effect. These insights form the basis for understanding the mechanisms underlying high and pathological myopia

Genetic correlations between diabetes and glaucoma: an analysis of continuous and dichotomous phenotypes

Purpose: A genetic correlation is the proportion of phenotypic variance between traits that is shared on a genetic basis. Here we explore genetic correlations between diabetes- and glaucoma-related traits.Design: Cross-sectional study.Methods: We assembled genome-wide association study summary statistics from European-derived participants regarding diabetes-related traits like fasting blood sugar (FBS) and type 2 diabetes (T2D) and glaucoma-related traits (intraocular pressure (IOP), central corneal thickness (CCT), corneal hysteresis (CH), corneal resistance factor (CRF), cup-disc ratio (CDR), and primary open-angle glaucoma (POAG)). We included data from the National Eye Institute Glaucoma Human Genetics Collaboration Heritable Overall Operational Database, the UK Biobank and the International Glaucoma Genetics Consortium. We calculated genetic correlation (rg) between traits using linkage disequilibrium score regression. We also calculated genetic correlations between IOP, CCT and selected diabetes-related traits based on individual level phenotype data in two Northern European population-based samples using pedigree information and Sequential Oligogenic Linkage Analysis Routines (SOLAR).Results: Overall, there was little rg between diabetes- and glaucoma-related traits. Specifically, we found a non-significant negative correlation between T2D and POAG (rg=-0.14; p=0.16). Using SOLAR, the genetic correlations between measured IOP, CCT, FBS, fasting insulin and hemoglobin A1c, were null. In contrast, genetic correlations between IOP and POAG (rg ≥0.45; p≤3.0E-04) and between CDR and POAG were high (rg =0.57; p=2.8E-10). However, genetic correlations between corneal properties (CCT, CRF and CH) and POAG were low (rg range: -0.18 - 0.11) and non-significant (p≥0.07).Conclusion: These analyses suggest there is limited genetic correlation between diabetes- and glaucoma-related traits

Associations with photoreceptor thickness measures in the UK Biobank.

Spectral-domain OCT (SD-OCT) provides high resolution images enabling identification of individual retinal layers. We included 32,923 participants aged 40-69 years old from UK Biobank. Questionnaires, physical examination, and eye examination including SD-OCT imaging were performed. SD OCT measured photoreceptor layer thickness includes photoreceptor layer thickness: inner nuclear layer-retinal pigment epithelium (INL-RPE) and the specific sublayers of the photoreceptor: inner nuclear layer-external limiting membrane (INL-ELM); external limiting membrane-inner segment outer segment (ELM-ISOS); and inner segment outer segment-retinal pigment epithelium (ISOS-RPE). In multivariate regression models, the total average INL-RPE was observed to be thinner in older aged, females, Black ethnicity, smokers, participants with higher systolic blood pressure, more negative refractive error, lower IOPcc and lower corneal hysteresis. The overall INL-ELM, ELM-ISOS and ISOS-RPE thickness was significantly associated with sex and race. Total average of INL-ELM thickness was additionally associated with age and refractive error, while ELM-ISOS was additionally associated with age, smoking status, SBP and refractive error; and ISOS-RPE was additionally associated with smoking status, IOPcc and corneal hysteresis. Hence, we found novel associations of ethnicity, smoking, systolic blood pressure, refraction, IOPcc and corneal hysteresis with photoreceptor thickness

Common Variants at 10 Genomic Loci Influence Hemoglobin A(1C) Levels via Glycemic and Nonglycemic Pathways

OBJECTIVE-Glycated hemoglobin (HbA(1c)), used to monitor and diagnose diabetes, is influenced by average glycemia over a 2- to 3-month period. Genetic factors affecting expression, turnover, and abnormal glycation of hemoglobin could also be associated with increased levels of HbA(1c). We aimed to identify such genetic factors and investigate the extent to which they influence diabetes classification based on HbA(1c) levels.RESEARCH DESIGN AND METHODS-We studied associations with HbA(1c) in up to 46,368 nondiabetic adults of European descent from 23 genome-wide association studies (GWAS) and 8 cohorts with de novo genotyped single nucleotide polymorphisms (SNPs). We combined studies using inverse-variance meta-analysis and tested mediation by glycemia using conditional analyses. We estimated the global effect of HbA(1c) loci using a multilocus risk score, and used net reclassification to estimate genetic effects on diabetes screening.RESULTS-Ten loci reached genome-wide significant association with HbA(1c), including six new loci near FN3K (lead SNP/P value, rs1046896/P = 1.6 x 10(-26)), HFE (rs1800562/P = 2.6 x 10(-20)), TMPRSS6 (rs855791/P = 2.7 x 10(-14)), ANK1 (rs4737009/P = 6.1 x 10(-12)), SPTA1 (rs2779116/P = 2.8 x 10(-9)) and ATP11A/TUBGCP3 (rs7998202/P = 5.2 x 10(-9)), and four known HbA(1c) loci: HK1 (rs16926246/P = 3.1 x 10(-54)), MTNR1B (rs1387153/P = 4.0 X 10(-11)), GCK (rs1799884/P = 1.5 x 10(-20)) and G6PC2/ABCB11 (rs552976/P = 8.2 x 10(-18)). We show that associations with HbA(1c) are partly a function of hyperglycemia associated with 3 of the 10 loci (GCK, G6PC2 and MTNR1B). The seven nonglycemic loci accounted for a 0.19 (%HbA(1c)) difference between the extreme 10% tails of the risk score, and would reclassify similar to 2% of a general white population screened for diabetes with HbA(1c).CONCLUSIONS-GWAS identified 10 genetic loci reproducibly associated with HbA(1c). Six are novel and seven map to loci where rarer variants cause hereditary anemias and iron storage disorders. Common variants at these loci likely influence HbA(1c) levels via erythrocyte biology, and confer a small but detectable reclassification of diabetes diagnosis by HbA(1c) Diabetes 59: 3229-3239, 201

Biological, clinical and population relevance of 95 loci for blood lipids.

Plasma concentrations of total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol and triglycerides are among the most important risk factors for coronary artery disease (CAD) and are targets for therapeutic intervention. We screened the genome for common variants associated with plasma lipids in &gt;100,000 individuals of European ancestry. Here we report 95 significantly associated loci (P &lt; 5 x 10(-8)), with 59 showing genome-wide significant association with lipid traits for the first time. The newly reported associations include single nucleotide polymorphisms (SNPs) near known lipid regulators (for example, CYP7A1, NPC1L1 and SCARB1) as well as in scores of loci not previously implicated in lipoprotein metabolism. The 95 loci contribute not only to normal variation in lipid traits but also to extreme lipid phenotypes and have an impact on lipid traits in three non-European populations (East Asians, South Asians and African Americans). Our results identify several novel loci associated with plasma lipids that are also associated with CAD. Finally, we validated three of the novel genes-GALNT2, PPP1R3B and TTC39B-with experiments in mouse models. Taken together, our findings provide the foundation to develop a broader biological understanding of lipoprotein metabolism and to identify new therapeutic opportunities for the prevention of CAD