Key inflammatory mechanisms underlying heart failure.

Inflammation plays a central role in the development of heart failure, especially in heart failure with preserved ejection fraction (HFpEF). Furthermore, the inflammatory response enables the induction of regenerative processes following acute myocardial injury. Recent studies in humans and animals have greatly advanced our understanding of the underlying mechanisms behind these adaptations. Importantly, inflammation can have both beneficial and detrimental effects, dependent on its extent, localization, and duration. Therefore, modulation of cardiac inflammation has been suggested as an attractive target for the treatment of heart failure, which has been investigated in numerous clinical trials. This review discusses key inflammatory mechanisms contributing to the pathogenesis of heart failure and their potential impact as therapeutic targets.

Examination of the current top candidate genes for AD in a genome-wide association study.

With the advent of technologies that allow simultaneous genotyping of thousands of single-nucleotide polymorphisms (SNPs) across the genome, the genetic contributions to complex diseases can be explored at an unprecedented detail. This study is among the first to apply the genome-wide association study (GWAS) approach to Alzheimer disease (AD). We present our GWAS results from the German population for genes included in the 'Top Results' list on the AlzGene database website. In addition to the apolipoprotein E locus, we identified nominally significant association signals in six of the ten genes investigated, albeit predominantly for SNPs other than those already published as being disease associated. Further, all of the four AD genes previously identified through GWAS also showed nominally significant association signals in our data. The results of our comparative study reinforce the necessity for replication and validation, not only of GWAS but also of candidate gene case-control studies, in different populations. Furthermore, cross-platform comparison of genotyping results can also identify new association signals. Finally, our data confirm that GWAS, regardless of the platform, are valuable for the identification of genetic variants associated with AD.