Current opinion in lipidology最新文献

Purpose of review: Our understanding of the genetic regulation of lipoprotein(a) [Lp(a)] is hindered by the complex structure of the LPA gene, limited non-European datasets and its elusive cellular receptor(s). This review summarizes recent efforts and advances providing new insights on its genetic architecture, variability across ancestries and regulators beyond the LPA gene.

Recent findings: Impressive advances in DNA sequencing and bioinformatics now resolve LPA variants and kringle IV-type 2 copy number at scale. This provides new reference datasets and enables tools that unlock hidden variation also from already available sequencing datasets. In parallel, genetic studies broaden our understanding of the regulation of Lp(a) across ancestries and improve genetic risk scores. Finally, while recent studies implicate new mechanisms for Lp(a) uptake, upcoming genome-wide gene knockout screens allow comprehensive, agnostic scans for regulators and receptors. Puzzlingly, this still converges on the LDL receptor, whose exact role in Lp(a) uptake remains enigmatic.

Summary: Technological advances establish a foundation for more accurate genetic risk assessment across ancestries. These advances are enhancing our understanding of Lp(a) regulation and build a framework for future integrative genetic studies, which may shed new light on the evolution of the Lp(a) trait, adding important context for its physiological and clinical relevance.

Purpose of review: More than 95% of human genes undergo alternative pre-mRNA processing based on cell type, developmental stages, and environmental stimuli, among other factors. Not all alternatively spliced mRNAs are translated to proteins, and some of the noncoding mRNA isoforms play vital roles in cellular homeostasis. This review summarizes protein coding and noncoding RNA isoforms reported for key genes involved in lipoprotein metabolism, and emerging technologies that can be exploited to specifically induce a desired isoform.

Recent findings: As sequencing technologies become more accessible, more variations in gene transcripts are being detected. Publicly available databases collate these as they arise, but not all of them are captured. Additionally, the function, if any, of many of these alternatively spliced transcripts is currently unknown. Novel strategies to investigate specific transcripts are also continuously evolving.

Summary: Most human genes are alternatively spliced, generating various mRNAs and protein isoforms. Any cis or trans factors that alter the balance of these isoforms can have deleterious effects. The fundamental knowledge on the role of each isoform in maintaining cellular health is currently lacking. Emerging technologies which allow modulation of natural mRNA splicing can be used to further our understanding of natural isoform expression and function.

Purpose of review: The purpose of this report is to summarize evidence supporting the use of nonfasting lipid testing for cardiovascular risk assessment, the potential reasons nonfasting lipid testing predicts cardiovascular risk better than fasting measurement, and to provide a preliminary survey of the status of adoption of nonfasting lipid testing by individual physicians and patients.

Recent findings: There is increased awareness of the importance of remnant lipoprotein cholesterol, which is increased after eating, as a key factor predicting risk for ischemic vascular disease. Nonfasting lipid measurement is now recommended in guidelines and consensus statements worldwide, but has not yet been adopted in many countries. Preliminary evidence suggests physician's practice of requesting a fasting glucose along with a lipid profile is decreasing over time, but still limits implementation of nonfasting lipid testing. Patient's perception of the optimal conditions for lipid testing as well as their preferred time of day to perform the test may also be limiting adoption of nonfasting measurements.

Summary: Nonfasting testing is now accepted as the preferred method of lipid measurement for cardiovascular risk prediction and lipid target achievement. Further acceptance of nonfasting lipid testing requires increased awareness by physicians and patients of the rationale for this recommendation.

Purpose of review: To critically examine the emerging evidence linking ultra-processed food (UPF) consumption to chronic kidney disease (CKD), with a particular focus on prevention strategies, biological mechanisms, and implications for dietary guidelines and public health policy.

Recent findings: Recent systematic reviews and meta-analyses consistently report a positive association between high UPF consumption and CKD risk. Mechanistic insights suggest roles for food additives, altered nutrient bioavailability, and inflammatory pathways, while omics-based studies offer preliminary biomarker candidates. The KDIGO 2024 guidelines now emphasize dietary interventions, including reduced UPF consumption, as a core component of CKD management.

Summary: The findings support limiting UPF consumption as part of CKD prevention strategies. Nonetheless, the evidence base is largely derived from overlapping observational studies, with limited original research published in the considered timeframe. Moreover, the scarcity of recent original studies, methodological inconsistencies in UPF classification and CKD outcome definitions, highlight the urgent need for further research and standardization of approaches. Integrating precision nutrition and validated biomarkers into nephrology could enhance individualized dietary recommendations and public health interventions.

Purpose of review: Type 2 diabetes (T2D) is a heterogeneous, progressive metabolic disease and a major contributor to cardiovascular disease worldwide. Current prevention strategies, centred on population-level lifestyle recommendations, have had limited success, highlighting the need for more comprehensive approaches that account for interindividual variation in intervention response.

Recent findings: Although discrete T2D subtypes using genomics or clinical variables have been proposed for targeted diabetes prevention and care strategies, emerging evidence supports a more dynamic view of heterogeneity as a continuous spectrum of metabolic dysfunction. Continuous glucose monitoring and multiomics profiling have shown promises in detecting early metabolic dysfunction in individuals with normal glycemia.

Summary: In this review, we synthesize advances in modelling T2D phenotypic continuum and highlight how emerging technologies, including continuous glucose monitoring and multiomics profiling, can detect early metabolic dysregulation. We also discuss methodological challenges, such as the need for standardized deep phenotyping, robust analytic frameworks, and inclusion of diverse populations to ensure equity in translation. Finally, we outline future directions for translating these insights into scalable, mechanism-informed interventions that address glycaemic progression from subclinical changes to more advanced forms of the disease.

Purpose of review: Well conducted, prospective, blood-based biomarker studies on dementia risk are growing, providing valuable insights into disease mechanisms that precede clinical symptoms. These investigations are crucial for advancing our understanding of dementia pathology and identifying early biological changes.

Recent findings: Emerging evidence shows that proteins detected in peripheral tissues and the circulatory system can also play a role in neurological diseases. Both neuronal and nonbrain-specific proteins have been associated with dementia prior to symptom onset, highlighting the complex and multisystem nature of disease development. Of the 11 studies included in this review that focused on prospective studies of dementia that applied plasma proteomics, 36 proteins were identified in at least two independent cohorts, suggesting that blood-based proteomics detects consistent protein levels that may be altered years before dementia diagnosis.

Summary: Blood-based biomarkers hold promise for early diagnosis, patient stratification, and mechanistic research in dementia. The observed overlap in protein profiles across studies suggests we are beginning to uncover systemic biological differences that contribute to disease progression.

Purpose of review: Lipoprotein(a), Lp(a), is a genetically determined, lifelong risk factor for atherosclerotic cardiovascular disease (ASCVD). Despite broad guideline support for universal one-time testing, Lp(a) measurement remains rare in clinical practice. This review summarizes recent advances in machine learning-based strategies that can enhance the efficiency, yield, and equity of Lp(a) screening.

Recent findings: To date, three studies have developed and validated machine learning models to identify individuals with elevated Lp(a) using routinely available clinical variables. The ARISE framework, derived from the UK Biobank and validated across multiple US cohorts, reduced the number needed to test by more than 50% while maintaining consistent discrimination across demographic subgroups. Additional studies have confirmed the feasibility of decision-tree and neural network models to improve case finding for elevated Lp(a) in both clinical and population-based settings.

Summary: Machine learning-based strategies provide a scalable means of operationalizing universal Lp(a) testing recommendations within health systems. When developed using unbiased data, externally validated, and assessed for fairness and interpretability, these models can support systematic identification of individuals with elevated Lp(a) and integration of Lp(a) measurement into routine cardiovascular risk assessment.

Purpose of review: Greenlanders differ from other populations in terms of traditional lifestyle and genetic architecture. This might have a great impact on lipid levels in the population and the spectrum of genetic variants associated with lipid traits. Here, we review recent advances in lipid genetics in Greenlanders and highlight the potential of moving from single lipid trait analyses to more comprehensive lipidomic profiling.

Recent findings: Genetic association studies in the Greenlandic population have identified variants, including PCSK9 (rs12117661), LDLR (rs730882082), and SI (rs781470490), associated with large effects on triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol, and total cholesterol (TC) levels, as well as altered risk of cardiovascular disease (CVD). These variants are common in the Greenlandic population and explain more lipid variation than variants observed in Europeans. Accordingly, European-derived polygenic scores (PGSs) underperform in Greenlanders, but including the Greenlandic variants increases the performance of lipid PGSs. Lipidomic profiling has the potential to reveal strong cardiometabolic-risk signatures.

Summary: The Greenlandic population harbors high-impact variants in PCSK9, LDLR, and SI, particularly affecting the levels of TG, LDL-C, and TC. Obtaining information on these variants could facilitate earlier detection and potentially prevention of CVD, and advance precision medicine for Greenlanders.

Purpose of review: Elevated plasma lipoprotein(a) [Lp(a)] is a causal and independent risk factor for atherosclerotic cardiovascular disease and an emerging therapeutic target. Over the past 15 years, many medical bodies from around the world have released scientific statements and clinical guidelines regarding Lp(a). This review tracks how recommendations on Lp(a) have evolved over this timeframe.

Recent findings: Powerful studies demonstrating the independent association of elevated Lp(a) in large numbers of patients have been published. The data allowed a more precise formulation of risk categories for Lp(a) levels and of models for how a given level of Lp(a) in a moderate-risk to high-risk primary prevention patient might inform management of modifiable risk factors such as LDL cholesterol. Guidelines and statements have increasingly recommended universal screening for elevated Lp(a) and have identified elevated Lp(a) as a risk-enhancing or amplifying factor. However, some gaps and inconsistencies remain.

Summary: Ongoing cardiovascular outcomes trials of potent Lp(a)-lowering therapies will inform clinical use of Lp(a) in the future. Presently, consensus is building for measurement of Lp(a) in all adults and for incorporation of Lp(a) levels into clinical decision-making for prevention of cardiovascular disease. However, caution is warranted as the evidence base underlying this consensus has several important missing pieces.

Purpose of review: Low-grade systemic inflammation, as determined by high-sensitivity C-Reactive Protein (hsCRP), plays a significant role in the progression and development of atherosclerotic cardiovascular disease (ASCVD) and is recognized as a risk enhancer for increased incidence of major adverse cardiovascular events (MACE). (In 2024, the US Food and Drug Administration approved colchicine, as the first anti-inflammatory agent for secondary cardiovascular prevention. While this step signified a translational milestone, recent neutral colchicine trials such as CLEAR- SYNERGY, have reignited controversy regarding the overall efficacy of colchicine, and the need for alternative anti-inflammatory therapies. As the understanding of inflammation's role in atherosclerosis grows, questions persist about the best management strategies and future therapeutic options. This review aims to provide an updated summary that includes insights from recent key trials, explores investigational anti-inflammatory treatments, and discusses considerations for future trial designs.

Recent findings: This review will encompass recent trials involving colchicine, IL-1 antagonists, and interluekin-6 Inhibitors.

Summary: In this review, we will discuss mechanisms of inflammation as they pertain to ASCVD, significant contemporary trials, novel anti-inflammatory therapies, and considerations for future trial designs.