The Lipid Energy Model: Reimagining Lipoprotein Function in the Context of Carbohydrate-Restricted Diets.

When lean people adopt carbohydrate-restricted diets (CRDs), they may develop a lipid profile consisting of elevated LDL-cholesterol (LDL-C) and HDL-cholesterol (HDL-C) with low triglycerides (TGs). The magnitude of this lipid profile correlates with BMI such that those with lower BMI exhibit larger increases in both LDL-C and HDL-C. The inverse association between BMI and LDL-C and HDL-C change on CRD contributed to the discovery of a subset of individuals-termed Lean Mass Hyper-Responders (LMHR)-who, despite normal pre-diet LDL-C, as compared to non-LMHR (mean levels of 148 and 145 mg/dL, respectively), exhibited a pronounced hyperlipidemic response to a CRD, with mean LDL-C and HDL-C levels increasing to 320 and 99 mg/dL, respectively, in the context of mean TG of 47 mg/dL. In some LMHR, LDL-C levels may be in excess of 500 mg/dL, again, with relatively normal pre-diet LDL-C and absent of genetic findings indicative of familial hypercholesterolemia in those who have been tested. The Lipid Energy Model (LEM) attempts to explain this metabolic phenomenon by positing that, with carbohydrate restriction in lean persons, the increased dependence on fat as a metabolic substrate drives increased hepatic secretion and peripheral uptake of TG contained within very low-density lipoproteins (VLDL) by lipoprotein lipase, resulting in marked elevations of LDL-C and HDL-C, and low TG. Herein, we review the core features of the LEM. We review several existing lines of evidence supporting the model and suggest ways to test the model's predictions.

Mechanisms of Risk Reduction in the Clinical Practice of Alzheimer's Disease Prevention.

Alzheimer's disease (AD) is a neurodegenerative dementia that affects nearly 50 million people worldwide and is a major source of morbidity, mortality, and healthcare expenditure. While there have been many attempts to develop disease-modifying therapies for late-onset AD, none have so far shown efficacy in humans. However, the long latency between the initial neuronal changes and onset of symptoms, the ability to identify patients at risk based on family history and genetic markers, and the emergence of AD biomarkers for preclinical disease suggests that early risk-reducing interventions may be able to decrease the incidence of, delay or prevent AD. In this review, we discuss six mechanisms-dysregulation of glucose metabolism, inflammation, oxidative stress, trophic factor release, amyloid burden, and calcium toxicity-involved in AD pathogenesis that offer promising targets for risk-reducing interventions. In addition, we offer a blueprint for a multi-modality AD risk reduction program that can be clinically implemented with the current state of knowledge. Focused risk reduction aimed at particular pathological factors may transform AD to a preventable disorder in select cases.