Heiko Runz

Recent epidemiological studies show a strong reduction in the incidence of Alzheimer's disease in patients treated with cholesterol-lowering statins. Moreover, elevated Abeta42 levels and the varepsilon4 allele of the lipid-carrier apolipoprotein E are regarded as risk factors for sporadic and familial Alzheimer's disease. Here we demonstrate that the widely used cholesterol-lowering drugs simvastatin and lovastatin reduce intracellular and extracellular levels of Abeta42 and Abeta40 peptides in primary cultures of hippocampal neurons and mixed cortical neurons. Likewise, guinea pigs treated with high doses of simvastatin showed a strong and reversible reduction of cerebral Abeta42 and Abeta40 levels in the cerebrospinal fluid and brain homogenate. These results suggest that lipids are playing an important role in the development of Alzheimer's disease. Lowered levels of Abeta42 may provide the mechanism for the observed reduced incidence of dementia in statin-treated patients and may open up avenues for therapeutic interventions.

Identifying genetic variants associated with circulating protein concentrations (protein quantitative trait loci; pQTLs) and integrating them with variants from genome-wide association studies (GWAS) may illuminate the proteome's causal role in disease and bridge a knowledge gap regarding SNP-disease associations. We provide the results of GWAS of 71 high-value cardiovascular disease proteins in 6861 Framingham Heart Study participants and independent external replication. We report the mapping of over 16,000 pQTL variants and their functional relevance. We provide an integrated plasma protein-QTL database. Thirteen proteins harbor pQTL variants that match coronary disease-risk variants from GWAS or test causal for coronary disease by Mendelian randomization. Eight of these proteins predict new-onset cardiovascular disease events in Framingham participants. We demonstrate that identifying pQTLs, integrating them with GWAS results, employing Mendelian randomization, and prospectively testing protein-trait associations holds potential for elucidating causal genes, proteins, and pathways for cardiovascular disease and may identify targets for its prevention and treatment.