👤 Pia Bernasconi

Elevated lipoprotein(a) [Lp(a)] levels have been strongly related to cardiovascular (CV) risk. However, its association with Hypertension Mediated Organ Damage (HMOD) and CV events in the primary prevention setting remains unclear. To evaluate in these patients, the correlation between Lp(a) levels and: (i) heart, vessels and kidney HMOD and; (ii) CV events and all-cause mortality in a primary prevention setting. 747 low CV risk subjects were recruited between 2009 and 2014. HMOD was assessed through Pulse Wave Velocity, carotid Intima-Media Thickness (IMT), presence of carotid plaques, Left Ventricular Hypertrophy (LVH) and Ejection Fraction and glomerular filtration rate. All-cause mortality and CV events up to 2021 were retrieved by electronic health records, for a median follow-up time of 10 years (I-III quartiles 9.6-11.1). Mean age was 50.8 ± 13.0 years and 63.5% of the subjects were men. The prevalence of hypertension was 37.9%, dyslipidemia 67.2%, smoking 17.8%, and diabetes mellitus 8.7%. Median Lp(a) value was 17 mg/dL (5.9-56.0), and 26.5% of patients had values above 50 mg/dL. Regarding HMOD, 10.3% subjects had arterial stiffness, 7.2% increased IMT, 19.8% carotid plaques while only 0.7% had LVH. No significant correlation was found between Lp(a) levels and indices of subclinical HMOD. Furthermore, no relationship was found between CV events and all-cause mortality and Lp(a) levels. In this primary prevention cohort, elevated Lp(a) levels were not associated with significant structural damage to the heart, carotid arteries, or increased aortic stiffness and were not associated with CV events and all-cause mortality. Show less

The application of Machine Learning (ML) to genetic individual-level data represents a foreseeable advancement for the field, which is still in its infancy. Here, we aimed to evaluate the feasibility and accuracy of an ML-based model for disease risk prediction applied to Primary Biliary Cholangitis (PBC). Genome-wide significant variants identified in subjects of European ancestry in the recently released second international meta-analysis of GWAS in PBC were used as input data. Quality-checked, individual genomic data from two Italian cohorts were used. The ML included the following steps: import of genotype and phenotype data, genetic variant selection, supervised classification of PBC by genotype, generation of "if-then" rules for disease prediction by logic learning machine (LLM), and model validation in a different cohort. The training cohort included 1345 individuals: 444 were PBC cases and 901 were healthy controls. After pre-processing, 41,899 variants entered the analysis. Several configurations of parameters related to feature selection were simulated. The best LLM model reached an Accuracy of 71.7%, a Matthews correlation coefficient of 0.29, a Youden's value of 0.21, a Sensitivity of 0.28, a Specificity of 0.93, a Positive Predictive Value of 0.66, and a Negative Predictive Value of 0.72. Thirty-eight rules were generated. The rule with the highest covering (19.14) included the following genes: RIN3, KANSL1, TIMMDC1, TNPO3. The validation cohort included 834 individuals: 255 cases and 579 controls. By applying the ruleset derived in the training cohort, the Area under the Curve of the model was 0.73. This study represents the first illustration of an ML model applied to common variants associated with PBC. Our approach is computationally feasible, leverages individual-level data to generate intelligible rules, and can be used for disease prediction in at-risk individuals. Show less

Congenital myasthenic syndromes are rare genetic disorders compromising neuromuscular transmission. The defects are mainly mutations in the muscle acetylcholine receptor, or associated proteins rapsyn and Dok-7. We analyzed three unrelated Italian patients with typical clinical features of congenital myasthenic syndrome, who all benefitted from cholinesterase inhibitors. We found five mutations: a previously unreported homozygous alphaG378D mutation in the CHRNA1 gene, a previously unreported heterozygous epsilonY8X mutation associated with a known heterozygous epsilonM292del deletion in the CHRNE gene, and the common heterozygous N88K mutation associated with a previously unreported heterozygous IVS1 + 2T > G splice site mutation in the RAPSN gene. All three patients had two mutant alleles; parents or offspring with a single mutated allele were asymptomatic, thus all mutations exerted their effects recessively. The previously unreported mutations are likely to reduce the number of AChRs at the motor endplate, although the alphaG378D mutation might produce a mild fast channel syndrome. The alphaG378D mutation was recessive, but recessive CHRNA1 mutations have rarely been reported previously, so studies on the effect of this mutation at the cellular level would be of interest. Show less

HIV-1 infected individuals have an increased cardiovascular risk which is partially mediated by dyslipidemia. Single nucleotide polymorphisms in multiple genes involved in lipid transport and metabolism are presumed to modulate the risk of dyslipidemia in response to antiretroviral therapy. The contribution to dyslipidemia of 20 selected single nucleotide polymorphisms of 13 genes reported in the literature to be associated with plasma lipid levels (ABCA1, ADRB2, APOA5, APOC3, APOE, CETP, LIPC, LIPG, LPL, MDR1, MTP, SCARB1, and TNF) was assessed by longitudinally modeling more than 4400 plasma lipid determinations in 438 antiretroviral therapy-treated participants during a median period of 4.8 years. An exploratory genetic score was tested that takes into account the cumulative contribution of multiple gene variants to plasma lipids. Variants of ABCA1, APOA5, APOC3, APOE, and CETP contributed to plasma triglyceride levels, particularly in the setting of ritonavir-containing antiretroviral therapy. Variants of APOA5 and CETP contributed to high-density lipoprotein-cholesterol levels. Variants of CETP and LIPG contributed to non-high-density lipoprotein-cholesterol levels, a finding not reported previously. Sustained hypertriglyceridemia and low high-density lipoprotein-cholesterol during the study period was significantly associated with the genetic score. Single nucleotide polymorphisms of ABCA1, APOA5, APOC3, APOE, and CETP contribute to plasma triglyceride and high-density lipoprotein-cholesterol levels during antiretroviral therapy exposure. Genetic profiling may contribute to the identification of patients at risk for antiretroviral therapy-related dyslipidemia. Show less

Single-nucleotide polymorphisms in genes involved in lipoprotein and adipocyte metabolism may explain why dyslipidemia and lipoatrophy occur in some but not all antiretroviral therapy (ART)-treated individuals. We evaluated the contribution of APOC3 -482C-->T, -455T-->C, and 3238C-->G; epsilon 2 and epsilon 4 alleles of APOE; and TNF -238G-->A to dyslipidemia and lipoatrophy by longitudinally modeling >2600 lipid determinations and 2328 lipoatrophy assessments in 329 ART-treated patients during a median follow-up period of 3.4 years. In human immunodeficiency virus (HIV)-infected individuals, the effects of variant alleles of APOE on plasma cholesterol and triglyceride levels and of APOC3 on plasma triglyceride levels were comparable to those reported in the general population. However, when treated with ritonavir, individuals with unfavorable genotypes of APOC3 and [corrected] APOE were at risk of extreme hypertriglyceridemia. They had median plasma triglyceride levels of 7.33 mmol/L, compared with 3.08 mmol/L in the absence of ART. The net effect of the APOE*APOC3*ritonavir interaction was an increase in plasma triglyceride levels of 2.23 mmol/L. No association between TNF -238G-->A and lipoatrophy was observed. Variant alleles of APOE and APOC3 contribute to an unfavorable lipid profile in patients with HIV. Interactions between genotypes and ART can lead to severe hyperlipidemia. Genetic analysis may identify patients at high risk for severe ritonavir-associated hypertriglyceridemia. Show less