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.     

Human heart disease: lessons from human pluripotent stem cell-derived cardiomyocytes

Technical advances in generating and phenotyping cardiomyocytes from human pluripotent stem cells (hPSC-CMs) are now driving their wider acceptance as in vitro models to understand human heart disease and discover therapeutic targets that may lead to new compounds for clinical use. Current literature clearly shows that hPSC-CMs recapitulate many molecular, cellular, and functional aspects of human heart pathophysiology and their responses to cardioactive drugs. Here, we provide a comprehensive overview of hPSC-CMs models that have been described to date and highlight their most recent and remarkable contributions to research on cardiovascular diseases and disorders with cardiac traits. We conclude discussing immediate challenges, limitations, and emerging solutions.     

Melatonin,mitochondria, and the metabolic syndrome

A number of risk factors for cardiovascular disease including hyperinsulinemia, glucose intolerance, dyslipidemia, obesity, and elevated blood pressure are collectively known as metabolic syndrome (MS). Since mitochondrial activity is modulated by the availability of energy in cells, the disruption of key regulators of metabolism in MS not only affects the activity of mitochondria but also their dynamics and turnover. Therefore, a link of MS with mitochondrial dysfunction has been suspected since long. As a chronobiotic/cytoprotective agent, melatonin has a special place in prevention and treatment of MS. Melatonin levels are reduced in diseases associated with insulin resistance like MS. Melatonin improves sleep efficiency and has antioxidant and anti-inflammatory properties, partly for its role as a metabolic regulator and mitochondrial protector. We discuss in the present review the several cytoprotective melatonin actions that attenuate inflammatory responses in MS. The clinical data that support the potential therapeutical value of melatonin in human MS are reviewed.     

Palaeoclimatic distribution models predict Pleistocene refuges for the Neotropical harvestman Geraeocormobius sylvarum (Arachnida: Opiliones: Gonyleptidae)

This paper primarily aims to test a Pleistocene refuge-type scenario, as previously proposed for the gonyleptid Geraeocormobius sylvarum, a semi-deciduous forests dweller in subtropical Argentina, Brazil and Paraguay. Palaeodistributional models of this species were built using MaxEnt for two Last Glacial Maximum (LGM = 21,000 years ago) simulations – Community Climate System Model (CCSM) and Model for Interdisciplinary Research on Climate (MIROC) – and for 6000 years ago (?6k = HCO, the Holocene climatic optimum). Both LGM models retrieved a fragmented pattern. For CCSM, range was split into multiple, scattered fragments. MIROC resulted in very few patches, with a decided range reduction because of a strong humidity drop. Models for ?6k recovered a moderate range expansion. No past connection between the core area and the yungas was predicted. Analysis of variables importance showed that two precipitation predictors (bc18, precipitation warmest quarter; bc14, precipitation driest month) and two temperature predictors (bc7, temperature annual range; bc9, mean temperature driest quarter) scored as the most influencing overall. The Limiting Factor analysis recognized them as limiting too, in different parts of the species range. LGM palaeomodels of G. sylvarum are compatible with the refuge hypothesis invoked in previous molecular analyses, to explain the high genetic diversity found in the core area. Additionally, the results reinforced the hypothesis of the recent anthropogenic origin of the yungas disjunct populations.     

Forecasting key US macroeconomic variables with a factor‐augmented Qual VAR

In this paper, we first extract factors from a monthly dataset of 130 macroeconomic and financial variables. These extracted factors are then used to construct a factor‐augmented qualitative vector autoregressive (FA‐Qual VAR) model to forecast industrial production growth, inflation, the Federal funds rate, and the term spread based on a pseudo out‐of‐sample recursive forecasting exercise over an out‐of‐sample period of 1980:1 to 2014:12, using an in‐sample period of 1960:1 to 1979:12. Short‐, medium‐, and long‐run horizons of 1, 6, 12, and 24 months ahead are considered. The forecast from the FA‐Qual VAR is compared with that of a standard VAR model, a Qual VAR model, and a factor‐augmented VAR (FAVAR). In general, we observe that the FA‐Qual VAR tends to perform significantly better than the VAR, Qual VAR and FAVAR (barring some exceptions relative to the latter). In addition, we find that the Qual VARs are also well equipped in forecasting probability of recessions when compared to probit models.