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Purpose Of Review: Lipoprotein (a) [Lp(a)] is a highly atherogenic lipoprotein species. A unique feature of Lp(a) is the strong genetic determination of its concentration. The LPA gene is responsible for up to 90% of the variance in Lp(a), but other genes also have an impact.
Recent Findings: Genome-wide associations studies indicate that the APOE gene, encoding apolipoprotein E (apoE), is the second most important locus modulating Lp(a) concentrations. Population studies clearly show that carriers of the apoE2 variant (ε2) display reduced Lp(a) levels, the lowest concentrations being observed in ε2/ε2 homozygotes. This genotype can lead predisposed adults to develop dysbetalipoproteinemia, a lipid disorder characterized by sharp elevations in cholesterol and triglycerides. However, dysbetalipoproteinemia does not significantly modulate circulating Lp(a). Mechanistically, apoE appears to impair the production but not the catabolism of Lp(a). These observations underline the complexity of Lp(a) metabolism and provide key insights into the pathways governing Lp(a) synthesis and secretion.
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http://dx.doi.org/10.1007/s11883-022-01016-8 | DOI Listing |
Protein Cell
August 2025
Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai 200433, China.
Cardiovascular disease (CVD) research is hindered by limited comprehensive analyses of plasma proteome across disease subtypes. Here, we systematically investigated the associations between plasma proteins and cardiovascular outcomes in 53,026 UK Biobank participants over a 14-year follow-up. Association analyses identified 3,089 significant associations involving 892 unique protein analytes across 13 CVD outcomes.
View Article and Find Full Text PDFAlpha Psychiatry
August 2025
Experimental Research Center of Medical and Psychological Science, School of Psychology, Third Military Medical University, 400038 Chongqing, China.
Objective: To tailor culturally sensitive interventional strategies for safeguarding adolescents' mental health, this study investigated the role of perceived parental involvement in predicting depressive symptoms among Chinese adolescents, considering family socioeconomic status (SES).
Methods: A cluster convenience sampling method recruited 21,818 participants from 48 middle schools across 29 provinces in China. The perceived parental involvement (PPI) Scale and the Chinese version of the center for epidemiologic studies depression scale (CES-D) assessed parental involvement and depressive symptoms, respectively.
Turk Kardiyol Dern Ars
September 2025
Department of Cardiology, Koç University School of Medicine, Istanbul, Türkiye.
Objective: Coronary artery calcification (CAC) and osteoporosis are common age-related conditions that may share underlying mechanisms such as inflammation and lipid dysregulation. Lipoprotein(a) [Lp(a)] has been suggested as a potential contributor to both processes. This study aims to investigate the relationship between CAC, bone mineral density (BMD), and Lp(a) levels in a statin-naive elderly population.
View Article and Find Full Text PDFAlcohol Clin Exp Res (Hoboken)
September 2025
Office of the Clinical Director, National Institute on Alcohol Abuse and Alcoholism, Bethesda, Maryland, USA.
Background: Impulsivity is a multidimensional construct that is associated with problematic alcohol use and alcohol use disorder (AUD). Modeling within-person clustering of impulsivity facets has the potential to aid clinical case conceptualization, and examining associations with resilience and well-being outcomes can inform strength-based intervention approaches. In this study, we utilized latent profile analysis (LPA) to capture the clustering of trait impulsivity facets and tested resilience as a mediational pathway linking impulsivity latent profiles to problematic alcohol use and quality of life domains.
View Article and Find Full Text PDFJ Behav Med
September 2025
Department of Psychology, University of Wisconsin-La Crosse, La Crosse, WI, USA.
Latent profile analysis (LPA) is in the finite mixture model analysis family and identifies subgroups by participants' responses to continuous variables (i.e., indicators); participants' probable membership in each subgroup is based on the similarity between the subgroup's prototypical responses and the person's unique responses.
View Article and Find Full Text PDF