Mutations in LMF1 cause combined lipase deficiency and severe hypertriglyceridemia

Hypertriglyceridemia is a hallmark of many disorders, including metabolic syndrome, diabetes, atherosclerosis and obesity. A well-known cause is the deficiency of lipoprotein lipase (LPL), a key enzyme in plasma triglyceride hydrolysis. Mice carrying the combined lipase deficiency (cld) mutation show severe hypertriglyceridemia owing to a decrease in the activity of LPL and a related enzyme, hepatic lipase (HL), caused by impaired maturation of nascent LPL and hepatic lipase polypeptides in the endoplasmic reticulum (ER). Here we identify the gene containing the cld mutation as Tmem112 and rename it Lmf1 (Lipase maturation factor 1). Lmf1 encodes a transmembrane protein with an evolutionarily conserved domain of unknown function that localizes to the ER. A human subject homozygous for a deleterious mutation in LMF1 also shows combined lipase deficiency with concomitant hypertriglyceridemia and associated disorders. Thus, through its profound effect on lipase activity, LMF1 emerges as an important candidate gene in hypertriglyceridemia.     

Mutations in TTBK2, encoding a kinase implicated in tau phosphorylation, segregate with spinocerebellar ataxia type 11

The microtubule-associated protein tau (encoded by MAPT) and several tau kinases have been implicated in neurodegeneration, but only MAPT has a proven role in disease. We identified mutations in the gene encoding tau tubulin kinase 2 (TTBK2) as the cause of spinocerebellar ataxia type 11. Affected brain tissue showed substantial cerebellar degeneration and tau deposition. These data suggest that TTBK2 is important in the tau cascade and in spinocerebellar degeneration.     

Yield curve forecast combinations based on bond portfolio performance

We propose an economically motivated forecast combination strategy in which model weights are related to portfolio returns obtained by a given forecast model. An empirical application based on an optimal mean–variance bond portfolio problem is used to highlight the advantages of the proposed approach with respect to combination methods based on statistical measures of forecast accuracy. We compute average net excess returns, standard deviation, and the Sharpe ratio of bond portfolios obtained with nine alternative yield curve specifications, as well as with 12 different forecast combination strategies. Return‐based forecast combination schemes clearly outperformed approaches based on statistical measures of forecast accuracy in terms of economic criteria. Moreover, return‐based approaches that dynamically select only the model with highest weight each period and discard all other models delivered even better results, evidencing not only the advantages of trimming forecast combinations but also the ability of the proposed approach to detect best‐performing models. To analyze the robustness of our results, different levels of risk aversion and a different dataset are considered.     

Do IMF fiscal forecasts add value?

We used a panel of 29 advanced and emerging market countries to investigate whether the IMF's World Economic Outlook (WEO) fiscal forecasts add value in terms of forecast accuracy and information content, relative to private sector forecasts (from Consensus Economics). We find that: (i) WEO forecasts are not significantly less accurate than Consensus forecasts; (ii) WEO and Consensus forecasts tend to mutually encompass one another; and (iii) each source of forecasts appears to contain some information that is not embedded in the other source.