Time-frame findings in patients starting OAT (n = 52).

<p>Time-frame findings in patients starting OAT (n = 52).</p

Correlation analysis between INR and warfarin / 3’-hydroxywarfarin in the two cohorts of patients investigated.

<p>Correlation analysis between INR and warfarin / 3’-hydroxywarfarin in the two cohorts of patients investigated.</p

Correlation analyses between: INR, serum warfarin (ng/mL) and 3’-hydroxywarfarin (ng/mL), and the amount of drug (warfarin week) taken by the whole cohort of patients on oral anticoagulant therapy.

<p>Correlation analyses between: INR, serum warfarin (ng/mL) and 3’-hydroxywarfarin (ng/mL), and the amount of drug (warfarin week) taken by the whole cohort of patients on oral anticoagulant therapy.</p

HPLC calibration curves.

<p>Warfarin (1A) and 3’-hydroxywarfarin (1B) calibration curves; R expresses the ratio between the area under the analyte peak (warfarin or 3’-hydroxywarfarin respectively) and the area of the internal standard.</p

Warfarin daily dose for different WRI.

<p>Mean and median warfarin dose increased as WRI increased. WR 0, WRI 1 and WRI 2 classes are as specified in text. Continuous line indicates the median; dashed line indicates the mean, vertical bars indicate the 1^st and 99^th percentile of warfarin day (mg).</p

Genotype distributions in the whole cohort of patients.

<p>Different distributions of <i>CYP2C9</i> haplotypes in the whole cohort of patients stratified by the three <i>VKORC1</i> genotypes according to INR values (A), warfarin and 3’-hydroxywarfarin serum concentration (B, and C respectively), and warfarin week (D).</p

DataSheet1_Host genetics impact on SARS-CoV-2 vaccine-induced immunoglobulin levels and dynamics: The role of TP53, ABO, APOE, ACE2, HLA-A, and CRP genes.docx

Background: Development and worldwide availability of safe and effective vaccines against severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) to fight severe symptoms of coronavirus disease 2019 (COVID-19) and block the pandemic have been a great achievement and stimulated researchers on understanding the efficacy and duration of different vaccine types.Methods: We investigated the levels of anti-SARS-CoV-2 antibodies (IgG) and neutralizing antibodies (NAbs) in 195 healthy adult subjects belonging to the staff of the University-Hospital of Ferrara (Italy) starting from 15 days up to 190 days (about 6 months) after the second dose of the BNT162b2 (Pfizer–BioNTech) mRNA-based vaccine (n = 128) or ChAdOx1 (AstraZeneca) adenovirus-based vaccine (n = 67) using a combined approach of serological and genomics investigations.Results: A strong correlation between IgG and NAb levels was detected during the 190 days of follow-up (r2 = 0.807; p 2 = 0.789; p = 0.0001) and 91–190 days (T2) after vaccination (r2 = 0.764; p = 0.0001) for both vaccine types (r2 = 0.842; p = 0.0001 and r2 = 0.780; p = 0.0001 for mRNA- and adenovirus-based vaccine, respectively). In addition to age (p 1 and P2, respectively, for IgG and NAb distribution) in the whole cohort and/or in the mRNA-based vaccine in the following genes: TP53, rs1042522 (P1 = 0.03; P2 = 0.04); ABO, rs657152 (P1 = 0.01; P2 = 0.03); APOE, rs7412/rs429358 (P1 = 0.0018; P2 = 0.0002); ACE2, rs2285666 (P1 = 0.014; P2 = 0.009); HLA-A, rs2571381/rs2499 (P1 = 0.02; P2 = 0.03); and CRP, rs2808635/rs876538 (P1 = 0.01 and P2 = 0.09).Conclusion: High- or low-responsive subjects can be identified among healthy adult vaccinated subjects after targeted genetic screening. This suggests that favorable genetic backgrounds may support the progression of an effective vaccine-induced immune response, though no definite conclusions can be drawn on the real effectiveness ascribed to a specific vaccine or to the different extent of a genotype-driven humoral response. The interplay between data from the polygenic predictive markers and serological screening stratified by demogeographic information can help to recognize the individual humoral response, accounting for ethnic and geographical differences, in both COVID-19 and anti-SARS-CoV-2 vaccinations.</p

Gene-gene interactions among coding genes of iron-homeostasis proteins and <i>APOE</i>-alleles in cognitive impairment diseases

<div><p>Cognitive impairments of different aetiology share alterations in iron and lipid homeostasis with mutual relationships. Since iron and cholesterol accumulation impact on neurodegenerative disease, the associated gene variants are appealing candidate targets for risk and disease progression assessment. In this light, we explored the role of common single nucleotide polymorphisms (SNPs) in the main iron homeostasis genes and in the main lipoprotein transporter gene (<i>APOE</i>) in a cohort of 765 patients with dementia of different origin: Alzheimer’s disease (AD) n = 276; vascular dementia (VaD), n = 255; mild cognitive impairment (MCI), n = 234; and in normal controls (n = 1086). In details, four genes of iron homeostasis (Hemochromatosis (<i>HFE</i>: C282Y, H63D), Ferroportin (<i>FPN1</i>: -8CG), Hepcidin (<i>HAMP</i>: -582AG), Transferrin (<i>TF</i>: P570S)), and the three major alleles of <i>APOE</i> (<i>APOE</i>2, <i>APOE</i>3, <i>APOE</i>4) were analyzed to explore causative interactions and synergies. In single analysis, <i>HFE</i> 282Y allele yielded a 3-fold risk reduction in the whole cohort of patients (<i>P</i><0.0001), confirmed in AD and VaD, reaching a 5-fold risk reduction in MCI (<i>P =</i> 0.0019). The other iron SNPs slightly associated with risk reduction whereas <i>APOE</i>4 allele resulted in increased risk, reaching more than 7-fold increased risk in AD homozygotes (<i>P</i> = 0.001), confirmed to a lower extent in VaD and MCI (<i>P =</i> 0.038 and <i>P =</i> 0.013 respectively) as well as in the whole group (<i>P</i><0.0001). Comparisons of Mini Mental State Examination (MMSE) among AD showed appreciable lowering in <i>APOE</i>4 carriers (<i>P =</i> 0.038), confirmed in the whole cohort of patients (<i>P =</i> 0.018). In interaction analysis, the <i>HFE</i> 282Y allele completely extinguished the <i>APOE</i>4 allele associated risk. Conversely, the coexistence in patients of a substantial number of iron SNPs accrued the <i>APOE</i>4 detrimental effect on MMSE. Overall, the analysis highlighted how a specific iron-allele burden, defined as different combinations of iron gene variants, might have different effects on cognitive impairment and might modulate the effects of established genetic risk factors such as <i>APOE</i>4. Our results suggest that established genetic risk factors might be affected by specific genetic backgrounds, making patients differently suited to manage iron accumulation adding new genetic insights in neurodegeneration. The recently recognized interconnections between iron and lipids, suggest that these pathways might share more than expected. We therefore extended to additional iron gene variants the newly proposed influencing mechanisms that <i>HFE</i> gene has on cholesterol metabolism. Our results have a strong translational potential promoting new pharmacogenetics studies on therapeutic target identification aimed at optimally tuning brain iron levels.</p></div

Schematic model linking HFE, HAMP and TF to FPN1-APP complex in detoxifying action for balanced iron homeostasis.

<p>The picture highlights the main pathways and molecular mediators involved in iron homeostasis maintenance by FPN1-APP cooperation. HAMP is Hepcidin; TF is Transferrin; TF-R is Transferrin receptor; HFE is Hemochromatosis; FPN is Ferroportin; IRP and IRE are Iron Regulatory Protein and Iron Responsive Element respectively.</p