Publications by authors named "Rob Sladek"

Elevated fasting insulin levels (FI), indicative of altered insulin secretion and sensitivity, may precede type 2 diabetes (T2D) and cardiovascular disease onset. In this study, we group FI-associated genetic variants based on their genetic and phenotypic similarities and identify seven clusters with distinct mechanisms contributing to elevated FI levels. Clusters fall into two types: "non-diabetogenic hyperinsulinemia," where clusters are not associated with increased T2D risk, and "diabetogenic hyperinsulinemia," where T2D associations are driven by body fat distribution, liver function, circulating lipids, or inflammation.

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Hyperinsulinemia is a complex and heterogeneous phenotype that characterizes molecular alterations that precede the development of type 2 diabetes (T2D). It results from a complex combination of molecular processes, including insulin secretion and insulin sensitivity, that differ between individuals. To better understand the physiology of hyperinsulinemia and ultimately T2D, we implemented a genetic approach grouping fasting insulin (FI)-associated genetic variants based on their molecular and phenotypic similarities.

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Large-scale gene sequencing studies for complex traits have the potential to identify causal genes with therapeutic implications. We performed gene-based association testing of blood lipid levels with rare (minor allele frequency < 1%) predicted damaging coding variation by using sequence data from >170,000 individuals from multiple ancestries: 97,493 European, 30,025 South Asian, 16,507 African, 16,440 Hispanic/Latino, 10,420 East Asian, and 1,182 Samoan. We identified 35 genes associated with circulating lipid levels; some of these genes have not been previously associated with lipid levels when using rare coding variation from population-based samples.

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Genetic discrimination (GD) is the differential or unfair profiling of an individual on the basis of genetic data. This article summarizes the actions of the Genetic Discrimination Observatory (GDO) in addressing GD and recent developments in GD since late 2020. It shows how GD can take many forms in today's rapidly evolving society.

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Article Synopsis
  • - The study investigates the genetic variants linked to severe monogenic diseases, focusing on the unknown probability (penetrance) of these variants causing disease.
  • - Using exome sequencing data from over 77,000 individuals, researchers examine eight monogenic metabolic diseases, finding that rare variants have a greater impact than common polygenic scores.
  • - Despite the strong effect of rare variants, the average penetrance for monogenic variant carriers is only about 60%, although incorporating polygenic variation helps improve risk prediction for certain conditions.
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The opioid receptor (OPR) family comprises the mu-, delta-, and kappa-opioid, and nociceptin receptors that belong to the superfamily of 7-transmembrane spanning G protein-coupled receptors (GPCRs). The mu-opioid receptor is the main target for clinically used opioid analgesics, and its biology has been extensively studied. The N-terminally truncated 6TM receptors isoform produced through alternative splicing of the OPRM1 gene displays unique signaling and analgesic properties, but it is unclear if other OPRs have the same ability.

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Protein-coding genetic variants that strongly affect disease risk can yield relevant clues to disease pathogenesis. Here we report exome-sequencing analyses of 20,791 individuals with type 2 diabetes (T2D) and 24,440 non-diabetic control participants from 5 ancestries. We identify gene-level associations of rare variants (with minor allele frequencies of less than 0.

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The delta-opioid receptor (DOPr) participates in mediating the effects of opioid analgesics. However, no selective agonists have entered clinical care despite potential to ameliorate many neurological and psychiatric disorders. In an effort to address the drug development challenges, the functional contribution of receptor isoforms created by alternative splicing of the three-exonic coding gene, OPRD1, has been overlooked.

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We aggregated coding variant data for 81,412 type 2 diabetes cases and 370,832 controls of diverse ancestry, identifying 40 coding variant association signals (P < 2.2 × 10); of these, 16 map outside known risk-associated loci. We make two important observations.

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To investigate the genetic basis of type 2 diabetes (T2D) to high resolution, the GoT2D and T2D-GENES consortia catalogued variation from whole-genome sequencing of 2,657 European individuals and exome sequencing of 12,940 individuals of multiple ancestries. Over 27M SNPs, indels, and structural variants were identified, including 99% of low-frequency (minor allele frequency [MAF] 0.1-5%) non-coding variants in the whole-genome sequenced individuals and 99.

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Article Synopsis
  • Researchers analyzed genetic data from over 39,000 people to find new associations linked to glycemic traits and type 2 diabetes risk.
  • They discovered a specific variant (p.Pro50Thr) that increases fasting plasma insulin levels by 12%, particularly in individuals of Finnish descent.
  • This variant is associated with lower insulin sensitivity and a slightly higher risk of developing type 2 diabetes, highlighting its functional impact in glucose regulation.
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The genetic architecture of common traits, including the number, frequency, and effect sizes of inherited variants that contribute to individual risk, has been long debated. Genome-wide association studies have identified scores of common variants associated with type 2 diabetes, but in aggregate, these explain only a fraction of the heritability of this disease. Here, to test the hypothesis that lower-frequency variants explain much of the remainder, the GoT2D and T2D-GENES consortia performed whole-genome sequencing in 2,657 European individuals with and without diabetes, and exome sequencing in 12,940 individuals from five ancestry groups.

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We performed fine mapping of 39 established type 2 diabetes (T2D) loci in 27,206 cases and 57,574 controls of European ancestry. We identified 49 distinct association signals at these loci, including five mapping in or near KCNQ1. 'Credible sets' of the variants most likely to drive each distinct signal mapped predominantly to noncoding sequence, implying that association with T2D is mediated through gene regulation.

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Motivation: The analysis of large biological datasets often requires complex processing pipelines that run for a long time on large computational infrastructures. We designed and implemented a simple script-like programming language with a clean and minimalist syntax to develop and manage pipeline execution and provide robustness to various types of software and hardware failures as well as portability.

Results: We introduce the BigDataScript (BDS) programming language for data processing pipelines, which improves abstraction from hardware resources and assists with robustness.

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We demonstrate a new platform, convex lens-induced nanoscale templating (CLINT), for dynamic manipulation and trapping of single DNA molecules. In the CLINT technique, the curved surface of a convex lens is used to deform a flexible coverslip above a substrate containing embedded nanotopography, creating a nanoscale gap that can be adjusted during an experiment to confine molecules within the embedded nanostructures. Critically, CLINT has the capability of transforming a macroscale flow cell into a nanofluidic device without the need for permanent direct bonding, thus simplifying sample loading, providing greater accessibility of the surface for functionalization, and enabling dynamic manipulation of confinement during device operation.

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The limited ability of common variants to account for the genetic contribution to complex disease has prompted searches for rare variants of large effect, to partly explain the 'missing heritability'. Analyses of genome-wide genotyping data have identified genomic structural variants (GSVs) as a source of such rare causal variants. Recent studies have reported multiple GSV loci associated with risk of obesity.

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Anaemia is a chief determinant of global ill health, contributing to cognitive impairment, growth retardation and impaired physical capacity. To understand further the genetic factors influencing red blood cells, we carried out a genome-wide association study of haemoglobin concentration and related parameters in up to 135,367 individuals. Here we identify 75 independent genetic loci associated with one or more red blood cell phenotypes at P < 10(-8), which together explain 4-9% of the phenotypic variance per trait.

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Common diseases such as type 2 diabetes are phenotypically heterogeneous. Obesity is a major risk factor for type 2 diabetes, but patients vary appreciably in body mass index. We hypothesized that the genetic predisposition to the disease may be different in lean (BMI<25 Kg/m²) compared to obese cases (BMI≥30 Kg/m²).

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Variable number tandem repeats (VNTRs) constitute a relatively under-examined class of genomic variants in the context of complex disease because of their sequence complexity and the challenges in assaying them. Recent large-scale genome-wide copy number variant mapping and association efforts have highlighted the need for improved methodology for association studies using these complex polymorphisms. Here we describe the in-depth investigation of a complex region on chromosome 8p21.

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Circulating levels of adiponectin, a hormone produced predominantly by adipocytes, are highly heritable and are inversely associated with type 2 diabetes mellitus (T2D) and other metabolic traits. We conducted a meta-analysis of genome-wide association studies in 39,883 individuals of European ancestry to identify genes associated with metabolic disease. We identified 8 novel loci associated with adiponectin levels and confirmed 2 previously reported loci (P = 4.

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The stresses encountered during islet isolation and culture may have deleterious effects on beta-cell physiology. However, the biological response of human islet cells to isolation remains poorly characterized. A better understanding of the network of signaling pathways induced by islet isolation and culturing may lead to strategies aimed at improving islet graft survival and function.

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African Americans are disproportionately affected by type 2 diabetes (T2DM) yet few studies have examined T2DM using genome-wide association approaches in this ethnicity. The aim of this study was to identify genes associated with T2DM in the African American population. We performed a Genome Wide Association Study (GWAS) using the Affymetrix 6.

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