Publications by authors named "Michael A Province"

Triglyceride (TG)/HDL-C ratio (THR) is a surrogate predictor of hyperinsulinemia. To identify novel genetic loci for THR change over time (ΔTHR), we conducted genome-wide association study (GWAS) and genome-wide linkage scan (GWLS) among nondiabetic Europeans from the Long Life Family Study (n = 1,384). Subjects with diabetes or on dyslipidemia medications were excluded.

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  • A randomized controlled trial was conducted in Bangladesh on children aged 12-18 months, comparing a microbiome-directed complementary food (MDCF-2) with a calorically dense standard food, revealing better weight-for-length improvement in those treated with MDCF-2.
  • The study also found significant protein and microbiome changes associated with the recovery process, suggesting potential biomarkers for treatment response and the need for further research on MDCF efficacy.
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  • * We found 17 genetic loci associated with sleep duration impacting lipid levels, with 10 of them being newly identified and linked to sleep-related disturbances in lipid metabolism.
  • * The research points to potential drug targets that could lead to new treatments for lipid-related issues in individuals with sleep problems, highlighting the connection between sleep patterns and cardiovascular health.
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  • Genome-wide association studies have found numerous genetic loci linked to glycemic traits, but connecting these loci to specific genes and biological pathways remains a challenge.
  • Researchers conducted meta-analyses of exome-array studies across four glycemic traits, analyzing data from over 144,000 participants, which led to the identification of coding variant associations in more than 60 genes.
  • The study revealed significant pathways related to insulin secretion, zinc transport, and fatty acid metabolism, enhancing understanding of glycemic regulation and making data available for further research.
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  • The Long Life Family Study looked at nearly 5,000 people from families known for living a long time to find out how genes affect heart health risks.
  • Researchers used special methods to analyze different traits related to heart problems and found 64 important genes, 29 of which were also seen in another study called the Framingham Heart Study.
  • Some key discoveries showed links between certain genes and heart disease, obesity, and inflammation related to fats in the body, highlighting how these genes might impact health.
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Studying relationships between longitudinal changes in omics variables and risks of events requires specific methodologies for joint analyses of longitudinal and time-to-event outcomes. We applied two such approaches (joint models [JM], stochastic process models [SPM]) to longitudinal metabolomics data from the Long Life Family Study focusing on understudied associations of longitudinal changes in lysophosphatidylcholines (LPC) with mortality and aging-related outcomes (23 LPC species, 5,790 measurements of each in 4,011 participants, 1,431 of whom died during follow-up). JM analyses found that higher levels of the majority of LPC species were associated with lower mortality risks, with the largest effect size observed for LPC 15:0/0:0 (hazard ratio: 0.

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Aims/hypothesis: Triglyceride (TG) /High density lipoprotein cholesterol (HDL-C) ratio (THR) represents a single surrogate predictor of hyperinsulinemia or insulin resistance that is associated with premature aging processes, risk of diabetes and increased mortality. To identify novel genetic loci for THR change over time (ΔTHR), we conducted genome-wide association study (GWAS) and genome-wide linkage scan (GWLS) among subjects of European ancestry who had complete data from two exams collected about seven years apart from the Long Life Family Study (LLFS, n=1384), a study with familial clustering of exceptional longevity in the US and Denmark.

Methods: Subjects with diabetes or using medications for dyslipidemia were excluded from this analysis.

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  • * A randomized controlled trial inBangladesh tested a microbiota-directed complementary food (MDCF-2) against a ready-to-use supplementary food (RUSF) in children transitioning from SAM to MAM, finding MDCF-2 led to better weight gain improvements.
  • * The study also identified 215 beneficial plasma proteins associated with improved growth and demonstrated changes in the children's gut microbiome, highlighting specific bacterial strains that may help in recovery, suggesting a need for further research on MDCF's effectiveness and potential treatment markers.
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Patients with chronic kidney disease (CKD) have increased oxidative stress and chronic inflammation, which may escalate the production of advanced glycation end-products (AGEs). High soluble receptor for AGE (sRAGE) and low estimated glomerular filtration rate (eGFR) levels are associated with CKD and aging. We evaluated whether eGFR calculated from creatinine and cystatin C share pleiotropic genetic factors with sRAGE.

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Over Several years, we have developed a system for assuring the quality of whole genome sequence (WGS) data in the LLFS families. We have focused on providing data to identify germline genetic variants with the aim of releasing as many variants on as many individuals as possible. We aim to assure the quality of the individual calls.

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  • * The study analyzed changes in HbA1c in a group of non-diabetic Europeans to identify genetic variants influencing these changes, using advanced modeling techniques.
  • * A significant gene variant (rs56340929) was found to explain a notable portion of the variation in HbA1c levels and was supported by additional data, suggesting a new genetic link to HbA1c in non-diabetic individuals.
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Background & Aims: Steatotic liver disease (SLD), characterized by elevated liver fat content (LFC), is influenced by genetics and diet. However, whether diet has a differential effect based on genetic risk is not well-characterized. We aimed to determine how genetic factors interact with diet to affect SLD in a large national biobank.

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Although both short and long sleep duration are associated with elevated hypertension risk, our understanding of their interplay with biological pathways governing blood pressure remains limited. To address this, we carried out genome-wide cross-population gene-by-short-sleep and long-sleep duration interaction analyses for three blood pressure traits (systolic, diastolic, and pulse pressure) in 811,405 individuals from diverse population groups. We discover 22 novel gene-sleep duration interaction loci for blood pressure, mapped to genes involved in neurological, thyroidal, bone metabolism, and hematopoietic pathways.

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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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Patients with chronic kidney disease (CKD) have increased oxidative stress and chronic inflammation, which may escalate the production of advanced glycation end-products (AGE). High soluble receptor for AGE (sRAGE) and low estimated glomerular filtration rate (eGFR) levels are associated with CKD and aging. We evaluated whether eGFR calculated from creatinine and cystatin C share pleiotropic genetic factors with sRAGE.

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Biomarker identification is critical for precise disease diagnosis and understanding disease pathogenesis in omics data analysis, like using fold change and regression analysis. Graph neural networks (GNNs) have been the dominant deep learning model for analyzing graph-structured data. However, we found two major limitations of existing GNNs in omics data analysis, i.

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  • Nonalcoholic fatty liver disease (NAFLD) is widespread, partly genetic, and currently lacks effective treatment options.
  • A genome-wide association study (GWAS) identified several genetic variants linked to NAFLD, focusing on genes related to metabolism and liver function.
  • Genetic risk factors can help classify NAFLD into subtypes and significantly increase the risk of severe liver complications, potentially aiding in the development of targeted therapies.
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Background: A recent study suggested that the protective effect of familial longevity becomes negligible for centenarians. However, the authors assessed the dependence on familial longevity in centenarians by comparing centenarians with 1 parent surviving to age 80+ to centenarians whose same-sexed parent did not survive to age 80. Here we test whether the protective effect of familial longevity persists after age 100 using more restrictive definitions of long-lived families.

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Associations of single nucleotide polymorphisms (SNPs) of the lipid gene with Alzheimer's (AD) and coronary heart disease (CHD) and potentially causal mediation effects of their risk factors, high-density lipoprotein cholesterol (HDL-C) and triglycerides (TG), were examined in two samples of European ancestry from the US (22,712 individuals 587/2,608 AD/CHD cases) and the UK Biobank (UKB) (232,341 individuals; 809/15,269 AD/CHD cases). Our results suggest that these associations can be regulated by several biological mechanisms and shaped by exogenous exposures. Two patterns of associations (represented by rs17145750 and rs6967028) were identified.

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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 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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  • Common SNPs may account for 40-50% of human height variation, and this study identifies 12,111 SNPs linked to height from a large sample of 5.4 million individuals.
  • These SNPs cluster in 7,209 genomic segments, encompassing about 21% of the genome and showing varying densities enriched in relevant genes.
  • While these SNPs explain a substantial portion of height variance in European populations (40-45%), their predictive power is lower (10-24%) in other ancestries, suggesting a need for more research to enhance understanding in diverse populations.
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  • Researchers studied the genetic connections to blood fats using data from 1.6 million people from different backgrounds to understand why certain fats are higher or lower in the body.
  • They looked at special genes and how they interact in the liver and fat cells, finding that the liver plays a big part in controlling fat levels.
  • Two specific genes, CREBRF and RRBP1, were highlighted as important in understanding how our bodies manage fats due to strong supporting evidence.
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  • Reduced glomerular filtration rate (GFR) is a precursor to kidney failure, influenced by factors like genetics and diabetes (DM), but the interaction between these factors is not well understood.
  • A large-scale genome-wide association study (GWAS) analyzed eGFR across almost 1.5 million individuals, revealing distinct genetic loci that differ between those with and without diabetes.
  • The findings identified potential new targets for drug development aimed at protecting kidney function, highlighting that many drug interventions could be effective for both diabetic and non-diabetic populations.
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