Publications by authors named "Letizia Marullo"

Conventional measurements of fasting and postprandial blood glucose levels investigated in genome-wide association studies (GWAS) cannot capture the effects of DNA variability on 'around the clock' glucoregulatory processes. Here we show that GWAS meta-analysis of glucose measurements under nonstandardized conditions (random glucose (RG)) in 476,326 individuals of diverse ancestries and without diabetes enables locus discovery and innovative pathophysiological observations. We discovered 120 RG loci represented by 150 distinct signals, including 13 with sex-dimorphic effects, two cross-ancestry and seven rare frequency signals.

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  • * A large study involving over 150,000 individuals found that genetic effects on fasting insulin vary by sex, specifically at the IRS1 and ZNF12 gene locations, with women showing higher RNA expression levels for ZNF12.
  • * The findings highlight that fasting insulin in women correlates more strongly with certain conditions like waist-to-hip ratio and anorexia nervosa, indicating that metabolic health differences between sexes may provide insight into their respective genetic influences.
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  • - The study investigates the genetic factors linked to changes in fasting glucose levels over time in nearly 13,807 non-diabetic individuals of European descent, aiming to understand elements that could lead to Type 2 diabetes (T2D).
  • - Researchers found no strong genetic associations (defined as genome-wide significance) with fasting glucose changes, suggesting that any genetic influences are likely to be minimal.
  • - Several genetic loci previously connected to T2D and glucose levels showed nominal associations, and the data collected will serve as a resource for future research on genetic links to T2D and other metabolic traits.
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  • Birth weight variation is affected by both genetic and non-genetic factors from the mother and fetus, influencing long-term health risks like cardio-metabolic issues.
  • A comprehensive analysis involving over half a million participants found 190 genetic signals related to birth weight, with many being newly identified.
  • The study suggests that while maternal genetics can lower a child's birth weight, this does not directly cause higher blood pressure later; instead, genetic factors play a key role in this relationship.
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The aim of the study was to explore the effects of variants at on a range of cardio-metabolic phenotypes. We analyzed the range of variants within Genetics in Brisighella Health Study and genes using an additive genetic model on 18 cardiometabolic phenotypes in a sample of 1645 individuals from the Genetics in Brisighella Health Study and replicated in 10,662 individuals from the Estonian Genome Center University of Tartu. We defined directly the effects of rs3846662:C>A at on apoB levels.

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  • Researchers investigated the impact of maternal genetics on birth weight, an area less studied compared to fetal genetics.
  • They conducted a meta-analysis of genetic data from over 86,000 women of European descent, identifying 10 specific genetic variants linked to offspring birth weight.
  • The study suggests that some maternal genetic factors influence fetal growth primarily through the intrauterine environment rather than shared genetics, indicating potential avenues for addressing birth weight-related health issues.
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To characterize type 2 diabetes (T2D)-associated variation across the allele frequency spectrum, we conducted a meta-analysis of genome-wide association data from 26,676 T2D case and 132,532 control subjects of European ancestry after imputation using the 1000 Genomes multiethnic reference panel. Promising association signals were followed up in additional data sets (of 14,545 or 7,397 T2D case and 38,994 or 71,604 control subjects). We identified 13 novel T2D-associated loci ( < 5 × 10), including variants near the , , and genes.

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Reference panels from the 1000 Genomes (1000G) Project Consortium provide near complete coverage of common and low-frequency genetic variation with minor allele frequency ≥0.5% across European ancestry populations. Within the European Network for Genetic and Genomic Epidemiology (ENGAGE) Consortium, we have undertaken the first large-scale meta-analysis of genome-wide association studies (GWAS), supplemented by 1000G imputation, for four quantitative glycaemic and obesity-related traits, in up to 87,048 individuals of European ancestry.

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Using a genome-wide screen of 9.6 million genetic variants achieved through 1000 Genomes Project imputation in 62,166 samples, we identify association to lipid traits in 93 loci, including 79 previously identified loci with new lead SNPs and 10 new loci, 15 loci with a low-frequency lead SNP and 10 loci with a missense lead SNP, and 2 loci with an accumulation of rare variants. In six loci, SNPs with established function in lipid genetics (CELSR2, GCKR, LIPC and APOE) or candidate missense mutations with predicted damaging function (CD300LG and TM6SF2) explained the locus associations.

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Over the past 8 years, the genetics of complex traits have benefited from an unprecedented advancement in the identification of common variant loci for diseases such as type 2 diabetes (T2D). The ability to undertake genome-wide association studies in large population-based samples for quantitative glycaemic traits has permitted us to explore the hypothesis that models arising from studies in non-diabetic individuals may reflect mechanisms involved in the pathogenesis of diabetes. Amongst 88 T2D risk and 72 glycaemic trait loci, only 29 are shared and show disproportionate magnitudes of phenotypic effects.

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Metabolic syndrome (MetS) has become a health and financial burden worldwide. The MetS definition captures clustering of risk factors that predict higher risk for diabetes mellitus and cardiovascular disease. Our study hypothesis is that additional to genes influencing individual MetS risk factors, genetic variants exist that influence MetS and inflammatory markers forming a predisposing MetS genetic network.

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  • A large study analyzed genetic data from over 133,000 Europeans without diabetes to identify genes linked to blood sugar levels, confirming 53 genetic locations associated with these traits.
  • Out of these, 33 locations also increase the risk for type 2 diabetes, highlighting a connection between insulin levels and factors like fat distribution.
  • The research suggests that there are likely more important genetic factors beyond the ones identified so far, as additional signals were observed when comparing discovery and follow-up studies.
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The impaired capacity of von Willebrand factor to carry factor VIII is identified as type 2N von Willebrand's disease. R854Q is the most common type 2N mutation, and almost the only one identified in Italy. This aim of this study was to ascertain whether R854Q mutations in a cohort of Italian patients with type 2N von Willebrand's disease originated from a single event or recurrent events.

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