You will be shown an abstract from a biomedical research paper. Given this abstract, your task is to extract all unique entities of the following types: ["Outcome", "Participant", "Intervention"].

Please return the output as a JSON object of the format: {"Participant" : ["patients with COPD", ...], "Intervention" : ["Atenolol", ...], "Outcome" : ["blood pressure", ...]}. The keys should be entity types and values should be lists of extracted entities belonging to the corresponding type. If you cannot find entities belonging to a specific type, the value should be [].

Only output the JSON object and do not include any additional text.

Abstract:

Genetic associations with lipoprotein subfractions provide information on their biological nature . Adverse levels of lipoproteins are highly heritable and constitute risk factors for cardiovascular outcomes . Hitherto , genome-wide association studies revealed 95 lipid-associated loci . However , due to the small effect sizes of these associations large sample numbers ( > 100 000 samples ) were needed . Here we show that analyzing more refined lipid phenotypes , namely lipoprotein subfractions , can increase the number of significantly associated loci compared with bulk high-density lipoprotein and low-density lipoprotein analysis in a study with identical sample numbers . Moreover , lipoprotein subfractions provide novel insight into the human lipid metabolism . We measured 15 lipoprotein subfractions ( L1-L15 ) in 1791 samples using ( 1 ) H-NMR ( nuclear magnetic resonance ) spectroscopy . Using cluster analyses , we quantified inter-relationships among lipoprotein subfractions . Additionally , we analyzed associations with subfractions at known lipid loci . We identified five distinct groups of subfractions : one ( L1 ) was only marginally captured by serum lipids and therefore extends our knowledge of lipoprotein biochemistry . During a lipid-tolerance test , L1 lost its special position . In the association analysis , we found that eight loci ( LIPC , CETP , PLTP , FADS1-2-3 , SORT1 , GCKR , APOB , APOA1 ) were associated with the subfractions , whereas only four loci ( CETP , SORT1 , GCKR , APOA1 ) were associated with serum lipids . For LIPC , we observed a 10-fold increase in the variance explained by our regression models . In conclusion , NMR-based fine mapping of lipoprotein subfractions provides novel information on their biological nature and strengthens the associations with genetic loci . Future clinical studies are now needed to investigate their biomedical relevance .
{"Intervention": ["subfractions", "low-density lipoprotein", "high-density lipoprotein", "15 lipoprotein subfractions ( L1-L15 )", "lipoproteins", "L1", "lipoprotein subfractions"], "Outcome": [], "Participant": ["15 lipoprotein subfractions ( L1-L15 ) in 1791 samples using ( 1 ) H-NMR ( nuclear magnetic resonance ) spectroscopy .", "lipoprotein subfractions"]}