Publications by authors named "Michael PreuSS"

Article Synopsis
  • Latin Americans are often overlooked in genetic studies, which can widen gaps in personalized medicine due to the challenges of accessing genetic data and consent processes.
  • The Genetics of Latin American Diversity (GLAD) Project compiles genetic information from over 53,000 individuals across various regions to explore diverse ancestry and gene flow in the Americas.
  • GLAD includes a tool called GLAD-match to align external genetic samples with its database while protecting individual privacy, thus supporting more inclusive genomic research and enhancing personalized medicine for Latin Americans.
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  • Whole genome sequencing (WGS) helps identify rare genetic variants that may explain the missing heritability of coronary artery disease (CAD) by analyzing 4,949 cases and 17,494 controls from the NHLBI TOPMed program.
  • The study estimates that the heritability of CAD is around 34.3%, with ultra-rare variants contributing about 50%, especially those with low linkage disequilibrium.
  • Functional annotations show significant enrichment of CAD heritability, highlighting the importance of ultra-rare variants and specific regulatory mechanisms in different cells as major factors influencing genetic risk for the disease.
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Obesity is a major risk factor for a myriad of diseases, affecting >600 million people worldwide. Genome-wide association studies (GWASs) have identified hundreds of genetic variants that influence body mass index (BMI), a commonly used metric to assess obesity risk. Most variants are non-coding and likely act through regulating genes nearby.

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  • Type 2 diabetes (T2D) is a complex disease influenced by various genetic factors and molecular mechanisms that vary by cell type and ancestry.
  • In a large study involving over 2.5 million individuals, researchers identified 1,289 significant genetic associations linked to T2D, including 145 new loci not previously reported.
  • The study categorized T2D signals into eight distinct clusters based on their connections to cardiometabolic traits and showed that these genetic profiles are linked to vascular complications, emphasizing the role of obesity-related processes across different ancestry groups.
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  • - A new multi-ancestry genome-wide association study (GWAS) of major depression (MD) analyzed data from 88,316 cases and 902,757 controls, representing various ancestries including African, East Asian, South Asian, and Hispanic/Latin American.
  • - The study discovered 53 novel genetic loci significantly linked to MD, with fewer existing European ancestry loci proving relevant to other ancestry groups.
  • - A transcriptome-wide association study in this research identified 205 new genes associated with MD, highlighting the importance of diverse ancestry in genetic research for better understanding and finding relevant genes.
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Here we present BridgePRS, a novel Bayesian polygenic risk score (PRS) method that leverages shared genetic effects across ancestries to increase PRS portability. We evaluate BridgePRS via simulations and real UK Biobank data across 19 traits in individuals of African, South Asian and East Asian ancestry, using both UK Biobank and Biobank Japan genome-wide association study summary statistics; out-of-cohort validation is performed in the Mount Sinai (New York) BioMe biobank. BridgePRS is compared with the leading alternative, PRS-CSx, and two other PRS methods.

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Background: The branched chain amino acids (BCAA) leucine, isoleucine, and valine are essential nutrients that have been associated with diabetes, cancers, and cardiovascular diseases. Observational studies suggest that BCAAs exert homogeneous phenotypic effects, but these findings are inconsistent with results from experimental human and animal studies.

Methods: Hypothesizing that inconsistencies between observational and experimental BCAA studies reflect bias from shared lifestyle and genetic factors in observational studies, we used data from the UK Biobank and applied multivariable Mendelian randomization causal inference methods designed to address these biases.

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Background: Preoperative fasting reduces the risk of pulmonary aspiration during anaesthesia, and 2-h fasting for clear fluids has commonly been recommended. Based on recent evidence of shorter fasting times being safe, the Swiss Society of Paediatric Anaesthesia began recommending 1-h fasting for clear fluids in 2018. This prospective, observational, multi-institutional cohort study aimed to investigate the incidence of adverse respiratory events after implementing the new national recommendation.

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  • A recent study analyzed genetic data from over 156,000 prostate cancer cases and 788,000 controls from diverse populations, significantly increasing the representation of non-European participants.
  • Researchers identified 187 new genetic risk variants for prostate cancer, bringing the total to 451, enhancing understanding of genetic factors across different ancestries.
  • The developed genetic risk score (GRS) showed varying risk levels for prostate cancer among different ancestry groups, highlighting its potential for better risk assessment, especially in men of African descent.
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  • Megabase-scale mosaic chromosomal alterations (mCAs) in blood can indicate the risk of various human diseases, and this study analyzes whole-genome sequencing data from 67,390 individuals to better understand mCA rates across different genetic backgrounds.
  • The research found that whole-genome sequencing is more effective than traditional methods for detecting mCAs, revealing that individuals of European ancestry have higher rates of autosomal mCAs and lower rates of chromosome X mCAs compared to those of African or Hispanic ancestry.
  • The study identifies three genetic loci linked to chromosome X loss and associates rare variants in specific genes (DCPS, ADM17, PPP1R16B, and TET2) with autosomal mCAs
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  • Long non-coding RNAs (lncRNAs) play crucial roles in regulating lipid metabolism and have been studied in relation to genetic variants and complex traits.
  • This research utilized high-coverage whole-genome sequencing of over 66,000 diverse participants to assess how rare variants in lncRNA genes affect blood lipid levels, using a statistical framework to analyze the associations.
  • The study found 83 lncRNA variants significantly linked to lipid levels, with many being independent of common genetic variations, and replicated a majority of these findings with data from another large cohort.
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  • Obesity poses a significant public health challenge and is linked to high mortality rates, with prior studies focusing mostly on European populations.
  • This research utilized whole-genome sequencing data from a diverse group of 88,873 individuals, finding 18 new signals associated with body mass index (BMI) and highlighting a novel SNP prevalent among people of African descent.
  • The study emphasizes the importance of diverse genetic data in identifying new obesity-related variants, moving us closer to personalized medical interventions for this crisis.
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Introduction: The independent and causal cardiovascular disease risk factor lipoprotein(a) (Lp(a)) is elevated in >1.5 billion individuals worldwide, but studies have prioritised European populations.

Methods: Here, we examined how ancestrally diverse studies could clarify Lp(a)'s genetic architecture, inform efforts examining application of Lp(a) polygenic risk scores (PRS), enable causal inference and identify unexpected Lp(a) phenotypic effects using data from African (n=25 208), East Asian (n=2895), European (n=362 558), South Asian (n=8192) and Hispanic/Latino (n=8946) populations.

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Article Synopsis
  • Long non-coding RNAs (lncRNAs) play key roles in regulating biological functions, and new genomic studies allow researchers to explore their connection to complex traits, like blood lipid levels.
  • This research involved high-coverage whole genome sequencing from over 66,000 participants, focusing on the influence of rare variants in 165,375 lncRNA genes on lipid variability.
  • The study found 83 rare lncRNA variant sets linked to blood lipid levels, with many of these associations being independent of common variants, suggesting potential new avenues for therapeutic interventions.
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Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes. To characterise the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study (GWAS) data from 2,535,601 individuals (39.7% non-European ancestry), including 428,452 T2D cases.

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Background: Genetic factors play an important role in prostate cancer (PCa) susceptibility.

Objective: To discover common genetic variants contributing to the risk of PCa in men of African ancestry.

Design, Setting, And Participants: We conducted a meta-analysis of ten genome-wide association studies consisting of 19378 cases and 61620 controls of African ancestry.

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Polygenic Risk Scores (PRS) have huge potential to contribute to biomedical research and to a future of precision medicine, but to date their calculation relies largely on Europeanancestry GWAS data. This global bias makes most PRS substantially less accurate in individuals of non-European ancestry. Here we present , a novel Bayesian PRS method that leverages shared genetic effects across ancestries to increase the accuracy of PRS in non-European populations.

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Genome-wide association studies have identified over five hundred loci that contribute to variation in type 2 diabetes (T2D), an established risk factor for many diseases. However, the mechanisms and extent through which these loci contribute to subsequent outcomes remain elusive. We hypothesized that combinations of T2D-associated variants acting on tissue-specific regulatory elements might account for greater risk for tissue-specific outcomes, leading to diversity in T2D disease progression.

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Background: Calcific aortic stenosis (CAS) is the most common valvular heart disease in older adults and has no effective preventive therapies. Genome-wide association studies (GWAS) can identify genes influencing disease and may help prioritize therapeutic targets for CAS.

Methods: We performed a GWAS and gene association study of 14 451 patients with CAS and 398 544 controls in the Million Veteran Program.

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  • Researchers compiled a comprehensive catalog of 355,667 structural variants (SVs) from DNA data, with over half being novel, to better understand the relationship between SVs and diseases.
  • The study involved rigorous methods to ensure high-quality variant identification, showing over 90% accuracy compared to previous genetic assemblies.
  • This catalog reveals significant connections between SVs and various health traits, identifying 690 specific regions that may influence medically relevant genes, providing a crucial resource for disease research.
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Biobanks facilitate genome-wide association studies (GWASs), which have mapped genomic loci across a range of human diseases and traits. However, most biobanks are primarily composed of individuals of European ancestry. We introduce the Global Biobank Meta-analysis Initiative (GBMI)-a collaborative network of 23 biobanks from 4 continents representing more than 2.

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Ever larger Structural Variant (SV) catalogs highlighting the diversity within and between populations help researchers better understand the links between SVs and disease. The identification of SVs from DNA sequence data is non-trivial and requires a balance between comprehensiveness and precision. Here we present a catalog of 355,667 SVs (59.

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Understanding corrosion mechanisms is of importance for reducing the global cost of corrosion. While the properties of engineering components are considered at a macroscopic scale, corrosion occurs at micro or nano scale and is influenced by local microstructural variations inherent to engineering alloys. However, studying such complex microstructures that involve multiple length scales requires a multitude of advanced experimental procedures.

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Background: Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery.

Results: To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches.

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