Publications by authors named "Langenberg C"

Article Synopsis
  • - The research identifies 389 genetic signals related to the timing of menarche (first menstrual period) in up to 370,000 women, showing how genetics influence this aspect of puberty and link it to adult diseases.
  • - Findings indicate that about 7.4% of the population variation in menarche age can be explained by these genetic signals, with a notable enrichment of associated genes in neural tissues.
  • - The study suggests that the timing of puberty has causal relationships with certain cancers, independently of factors like body mass index (BMI), highlighting the intricate genetic factors influencing puberty and its long-term health effects.
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The Y chromosome is frequently lost in hematopoietic cells, which represents the most common somatic alteration in men. However, the mechanisms that regulate mosaic loss of chromosome Y (mLOY), and its clinical relevance, are unknown. We used genotype-array-intensity data and sequence reads from 85,542 men to identify 19 genomic regions (P < 5 × 10) that are associated with mLOY.

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  • 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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Height is a highly heritable, classic polygenic trait with approximately 700 common associated variants identified through genome-wide association studies so far. Here, we report 83 height-associated coding variants with lower minor-allele frequencies (in the range of 0.1-4.

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Excessive alcohol consumption is a major public health problem worldwide. Although drinking habits are known to be inherited, few genes have been identified that are robustly linked to alcohol drinking. We conducted a genome-wide association metaanalysis and replication study among >105,000 individuals of European ancestry and identified β-Klotho (KLB) as a locus associated with alcohol consumption (rs11940694; P = 9.

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Background: Statin treatment and variants in the gene encoding HMG-CoA reductase are associated with reductions in both the concentration of LDL cholesterol and the risk of coronary heart disease, but also with modest hyperglycaemia, increased bodyweight, and modestly increased risk of type 2 diabetes, which in no way offsets their substantial benefits. We sought to investigate the associations of LDL cholesterol-lowering PCSK9 variants with type 2 diabetes and related biomarkers to gauge the likely effects of PCSK9 inhibitors on diabetes risk.

Methods: In this mendelian randomisation study, we used data from cohort studies, randomised controlled trials, case control studies, and genetic consortia to estimate associations of PCSK9 genetic variants with LDL cholesterol, fasting blood glucose, HbA, fasting insulin, bodyweight, waist-to-hip ratio, BMI, and risk of type 2 diabetes, using a standardised analysis plan, meta-analyses, and weighted gene-centric scores.

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  • Higher levels of branched-chain amino acids (BCAAs) like isoleucine, leucine, and valine are linked to an increased risk of type 2 diabetes, suggesting a need to explore if this relationship is causal.
  • A comprehensive genetic analysis of nearly 17,000 individuals identified key genomic regions associated with BCAA levels, particularly a strong association near the PPM1K gene, which plays a role in BCAA metabolism.
  • In a larger analysis involving nearly 48,000 diabetes cases and 267,000 controls, genetically predicted higher BCAA levels correlated with significantly increased odds of developing type 2 diabetes, supporting the premise that higher BCAAs may contribute to diabetes risk, though limitations in
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Article Synopsis
  • * Our method calculated averaged principal components (AvPCs) that represent body shape, with the first four AvPCs accounting for over 99% of the variability and showing heritability linked to cardiometabolic outcomes.
  • * We conducted genome-wide association studies across 65 studies and identified six new genetic loci associated with different AvPCs, emphasizing that analyzing multiple traits can uncover complex genetic factors that single-trait analyses might miss.
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Background: Cross-sectional genome-wide association studies have identified hundreds of loci associated with blood lipids and related cardiovascular traits, but few genetic association studies have focused on long-term changes in blood lipids.

Methods: Participants from the GLACIER Study (Nmax = 3492) were genotyped with the MetaboChip array, from which 29 387 SNPs (single nucleotide polymorphisms; replication, fine-mapping regions and wildcard SNPs for lipid traits) were extracted for association tests with 10-year change in total cholesterol (ΔTC) and triglycerides (ΔTG). Four additional prospective cohort studies (MDC, PIVUS, ULSAM, MRC Ely; Nmax = 8263 participants) were used for replication.

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Insulin resistance is a key mediator of obesity-related cardiometabolic disease, yet the mechanisms underlying this link remain obscure. Using an integrative genomic approach, we identify 53 genomic regions associated with insulin resistance phenotypes (higher fasting insulin levels adjusted for BMI, lower HDL cholesterol levels and higher triglyceride levels) and provide evidence that their link with higher cardiometabolic risk is underpinned by an association with lower adipose mass in peripheral compartments. Using these 53 loci, we show a polygenic contribution to familial partial lipodystrophy type 1, a severe form of insulin resistance, and highlight shared molecular mechanisms in common/mild and rare/severe insulin resistance.

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Background: Blood-based or urinary biomarkers may play a role in quantifying the future risk of type 2 diabetes (T2D) and in understanding possible aetiological pathways to disease. However, no systematic review has been conducted that has identified and provided an overview of available biomarkers for incident T2D. We aimed to systematically review the associations of biomarkers with risk of developing T2D and to highlight evidence gaps in the existing literature regarding the predictive and aetiological value of these biomarkers and to direct future research in this field.

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Large-scale whole-genome sequence data sets offer novel opportunities to identify genetic variation underlying human traits. Here we apply genotype imputation based on whole-genome sequence data from the UK10K and 1000 Genomes Project into 35,981 study participants of European ancestry, followed by association analysis with 20 quantitative cardiometabolic and hematological traits. We describe 17 new associations, including 6 rare (minor allele frequency (MAF) < 1%) or low-frequency (1% < MAF < 5%) variants with platelet count (PLT), red blood cell indices (MCH and MCV) and HDL cholesterol.

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Importance: Low-density lipoprotein cholesterol (LDL-C)-lowering alleles in or near NPC1L1 or HMGCR, encoding the respective molecular targets of ezetimibe and statins, have previously been used as proxies to study the efficacy of these lipid-lowering drugs. Alleles near HMGCR are associated with a higher risk of type 2 diabetes, similar to the increased incidence of new-onset diabetes associated with statin treatment in randomized clinical trials. It is unknown whether alleles near NPC1L1 are associated with the risk of type 2 diabetes.

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Article Synopsis
  • Birth weight (BW) is influenced by both fetal and maternal factors and is linked to the risk of metabolic diseases like type 2 diabetes and cardiovascular issues in adulthood.
  • A study involving over 153,000 individuals identified 60 genetic regions associated with BW that explain about 15% of its variation and revealed negative correlations between BW and risks for conditions like high blood pressure and heart disease.
  • Genetic analysis suggested that the relationship between lower BW and higher future cardiometabolic risks is driven by shared genetic effects, highlighting key biological processes involved.
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To dissect the genetic architecture of blood pressure and assess effects on target organ damage, we analyzed 128,272 SNPs from targeted and genome-wide arrays in 201,529 individuals of European ancestry, and genotypes from an additional 140,886 individuals were used for validation. We identified 66 blood pressure-associated loci, of which 17 were new; 15 harbored multiple distinct association signals. The 66 index SNPs were enriched for cis-regulatory elements, particularly in vascular endothelial cells, consistent with a primary role in blood pressure control through modulation of vascular tone across multiple tissues.

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High blood pressure is a major risk factor for cardiovascular disease and premature death. However, there is limited knowledge on specific causal genes and pathways. To better understand the genetics of blood pressure, we genotyped 242,296 rare, low-frequency and common genetic variants in up to 192,763 individuals and used ∼155,063 samples for independent replication.

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Background: Whether and how n-3 and n-6 polyunsaturated fatty acids (PUFAs) are related to type 2 diabetes (T2D) is debated. Objectively measured plasma PUFAs can help to clarify these associations.

Methods And Findings: Plasma phospholipid PUFAs were measured by gas chromatography among 12,132 incident T2D cases and 15,919 subcohort participants in the European Prospective Investigation into Cancer and Nutrition (EPIC)-InterAct study across eight European countries.

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Genome-wide association studies (GWAS) have found few common variants that influence fasting measures of insulin sensitivity. We hypothesized that a GWAS of an integrated assessment of fasting and dynamic measures of insulin sensitivity would detect novel common variants. We performed a GWAS of the modified Stumvoll Insulin Sensitivity Index (ISI) within the Meta-Analyses of Glucose and Insulin-Related Traits Consortium.

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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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Article Synopsis
  • The article with DOI 10.1371/journal.pgen.1005378 has been revised to correct previous errors.
  • The corrections enhance the accuracy and clarity of the findings presented.
  • Researchers and readers are encouraged to refer to the updated version for the most reliable information.
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Impaired kidney function, as measured by reduced estimated glomerular filtration rate (eGFR), has been associated with increased risk of coronary heart disease (CHD) in observational studies, but it is unclear whether this association is causal or the result of confounding or reverse causation. In this study we applied Mendelian randomisation analysis using 17 genetic variants previously associated with eGFR to investigate the causal role of kidney function on CHD. We used 13,145 participants from the UCL-LSHTM-Edinburgh-Bristol (UCLEB) Consortium and 194,427 participants from the Coronary ARtery DIsease Genome-wide Replication and Meta-analysis plus Coronary Artery Disease (CARDIoGRAMplusC4D) consortium.

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Red blood cell (RBC) traits are routinely measured in clinical practice as important markers of health. Deviations from the physiological ranges are usually a sign of disease, although variation between healthy individuals also occurs, at least partly due to genetic factors. Recent large scale genetic studies identified loci associated with one or more of these traits; further characterization of known loci and identification of new loci is necessary to better understand their role in health and disease and to identify potential molecular mechanisms.

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Regulatory authorities have indicated that new drugs to treat type 2 diabetes (T2D) should not be associated with an unacceptable increase in cardiovascular risk. Human genetics may be able to guide development of antidiabetic therapies by predicting cardiovascular and other health endpoints. We therefore investigated the association of variants in six genes that encode drug targets for obesity or T2D with a range of metabolic traits in up to 11,806 individuals by targeted exome sequencing and follow-up in 39,979 individuals by targeted genotyping, with additional in silico follow-up in consortia.

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Recent genetic studies have identified some alleles that are associated with higher BMI but lower risk of type 2 diabetes, hypertension, and heart disease. These "favorable adiposity" alleles are collectively associated with lower insulin levels and higher subcutaneous-to-visceral adipose tissue ratio and may protect from disease through higher adipose storage capacity. We aimed to use data from 164,609 individuals from the UK Biobank and five other studies to replicate associations between a genetic score of 11 favorable adiposity variants and adiposity and risk of disease, to test for interactions between BMI and favorable adiposity genetics, and to test effects separately in men and women.

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