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  1. Article ; Online: Multi-omics Analyses Identify AKR1A1 as a Biomarker for Diabetic Kidney Disease.

    Li, DengFeng / Hsu, Fang-Chi / Palmer, Nicholette D / Liu, Liang / Choi, Young A / Murea, Mariana / Parks, John S / Bowden, Donald W / Freedman, Barry I / Ma, Lijun

    Diabetes

    2024  

    Abstract: Diabetic kidney disease (DKD) is the leading cause of end-stage kidney disease. As many genes associate with DKD, multi-omics approaches were employed to narrow the list of functional genes, gene products and related pathways providing insights into the ... ...

    Abstract Diabetic kidney disease (DKD) is the leading cause of end-stage kidney disease. As many genes associate with DKD, multi-omics approaches were employed to narrow the list of functional genes, gene products and related pathways providing insights into the pathophysiological mechanisms of DKD. The Kidney Precision Medicine Project human kidney single-cell RNA-sequencing (scRNAseq) dataset and Mendeley Data on human kidney cortex biopsy proteomics were utilized. R package Seurat was used to analyze scRNAseq and subset proximal tubule cells. PathfindR was applied for pathway analysis in cell type-specific differentially expressed genes and R limma package was used to analyze differential protein expression in kidney cortex. A total of 790 differentially expressed genes were identified in proximal tubule cells, including 530 upregulated and 260 downregulated transcripts. Compared with differentially expressed proteins, 24 genes/proteins were in common. An integrated analysis combining protein quantitative trait loci (pQTL), GWAS hits (estimated glomerular filtration rate) and a plasma metabolomics analysis was performed using baseline metabolites predictive of DKD progression in our longitudinal Diabetes Heart Study samples. Aldo-keto reductase family 1 member A1 gene (AKR1A1) was revealed as a potential molecular hub for DKD cellular dysfunction in several cross-linked pathways featured by deficiency of this enzyme.
    Language English
    Publishing date 2024-02-23
    Publishing country United States
    Document type Journal Article
    ZDB-ID 80085-5
    ISSN 1939-327X ; 0012-1797
    ISSN (online) 1939-327X
    ISSN 0012-1797
    DOI 10.2337/db23-0540
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Region-based association tests for sequencing data on survival traits.

    Chien, Li-Chu / Bowden, Donald W / Chiu, Yen-Feng

    Genetic epidemiology

    2017  Volume 41, Issue 6, Page(s) 511–522

    Abstract: Family-based designs enriched with affected subjects and disease associated variants can increase statistical power for identifying functional rare variants. However, few rare variant analysis approaches are available for time-to-event traits in family ... ...

    Abstract Family-based designs enriched with affected subjects and disease associated variants can increase statistical power for identifying functional rare variants. However, few rare variant analysis approaches are available for time-to-event traits in family designs and none of them applicable to the X chromosome. We developed novel pedigree-based burden and kernel association tests for time-to-event outcomes with right censoring for pedigree data, referred to FamRATS (family-based rare variant association tests for survival traits). Cox proportional hazard models were employed to relate a time-to-event trait with rare variants with flexibility to encompass all ranges and collapsing of multiple variants. In addition, the robustness of violating proportional hazard assumptions was investigated for the proposed and four current existing tests, including the conventional population-based Cox proportional model and the burden, kernel, and sum of squares statistic (SSQ) tests for family data. The proposed tests can be applied to large-scale whole-genome sequencing data. They are appropriate for the practical use under a wide range of misspecified Cox models, as well as for population-based, pedigree-based, or hybrid designs. In our extensive simulation study and data example, we showed that the proposed kernel test is the most powerful and robust choice among the proposed burden test and the existing four rare variant survival association tests. When applied to the Diabetes Heart Study, the proposed tests found exome variants of the JAK1 gene on chromosome 1 showed the most significant association with age at onset of type 2 diabetes from the exome-wide analysis.
    Language English
    Publishing date 2017-09
    Publishing country United States
    Document type Journal Article
    ZDB-ID 605785-8
    ISSN 1098-2272 ; 0741-0395
    ISSN (online) 1098-2272
    ISSN 0741-0395
    DOI 10.1002/gepi.22054
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: Methods for estimating insulin resistance from untargeted metabolomics data.

    Hsu, Fang-Chi / Palmer, Nicholette D / Chen, Shyh-Huei / Ng, Maggie C Y / Goodarzi, Mark O / Rotter, Jerome I / Wagenknecht, Lynne E / Bancks, Michael P / Bergman, Richard N / Bowden, Donald W

    Metabolomics : Official journal of the Metabolomic Society

    2023  Volume 19, Issue 8, Page(s) 72

    Abstract: Context: Insulin resistance is associated with multiple complex diseases; however, precise measures of insulin resistance are invasive, expensive, and time-consuming.: Objective: Develop estimation models for measures of insulin resistance, including ...

    Abstract Context: Insulin resistance is associated with multiple complex diseases; however, precise measures of insulin resistance are invasive, expensive, and time-consuming.
    Objective: Develop estimation models for measures of insulin resistance, including insulin sensitivity index (SI) and homeostatic model assessment of insulin resistance (HOMA-IR) from metabolomics data.
    Design: Insulin Resistance Atherosclerosis Family Study (IRASFS).
    Setting: Community based.
    Participants: Mexican Americans (MA) and African Americans (AA).
    Main outcome: Estimation models for measures of insulin resistance, i.e. SI and HOMA-IR.
    Results: Least Absolute Shrinkage and Selection Operator (LASSO) and Elastic Net regression were used to build insulin resistance estimation models from 1274 metabolites combined with clinical data, e.g. age, sex, body mass index (BMI). Metabolite data were transformed using three approaches, i.e. inverse normal transformation, standardization, and Box Cox transformation. The analysis was performed in one MA recruitment site (San Luis Valley, Colorado (SLV); N = 450) and tested in another MA recruitment site (San Antonio, Texas (SA); N = 473). In addition, the two MA recruitment sites were combined and estimation models tested in the AA recruitment sample (Los Angeles, California; N = 495). Estimated and empiric SI were correlated in the SA (r
    Conclusions: We have developed a method for estimating insulin resistance with metabolomics data that has the potential for application to a wide range of biomedical studies and conditions.
    MeSH term(s) Humans ; Insulin Resistance ; Metabolomics ; Atherosclerosis/metabolism
    Language English
    Publishing date 2023-08-09
    Publishing country United States
    Document type Journal Article ; Research Support, N.I.H., Extramural
    ZDB-ID 2250617-2
    ISSN 1573-3890 ; 1573-3882
    ISSN (online) 1573-3890
    ISSN 1573-3882
    DOI 10.1007/s11306-023-02035-5
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Metabolomic profiling of glucose homeostasis in African Americans: the Insulin Resistance Atherosclerosis Family Study (IRAS-FS).

    Okut, Hayrettin / Lu, Yingchang / Palmer, Nicholette D / Chen, Yii-Der Ida / Taylor, Kent D / Norris, Jill M / Lorenzo, Carlos / Rotter, Jerome I / Langefeld, Carl D / Wagenknecht, Lynne E / Bowden, Donald W / Ng, Maggie C Y

    Metabolomics : Official journal of the Metabolomic Society

    2023  Volume 19, Issue 4, Page(s) 35

    Abstract: Introduction: African Americans are at increased risk for type 2 diabetes.: Objectives: This work aimed to examine metabolomic signature of glucose homeostasis in African Americans.: Methods: We used an untargeted liquid chromatography-mass ... ...

    Abstract Introduction: African Americans are at increased risk for type 2 diabetes.
    Objectives: This work aimed to examine metabolomic signature of glucose homeostasis in African Americans.
    Methods: We used an untargeted liquid chromatography-mass spectrometry metabolomic approach to comprehensively profile 727 plasma metabolites among 571 African Americans from the Insulin Resistance Atherosclerosis Family Study (IRAS-FS) and investigate the associations between these metabolites and both the dynamic (S
    Results: We confirmed increased plasma metabolite levels of branched-chain amino acids and their metabolic derivatives, 2-aminoadipate, 2-hydroxybutyrate, glutamate, arginine and its metabolic derivatives, carbohydrate metabolites, and medium- and long-chain fatty acids were associated with insulin resistance, while increased plasma metabolite levels in the glycine, serine and threonine metabolic pathway were associated with insulin sensitivity. We also observed a differential ancestral effect of glutamate on glucose homeostasis with significantly stronger effects observed in African Americans than those previously observed in Mexican Americans.
    Conclusion: We extended the observations that metabolites are useful biomarkers in the identification of prediabetes in individuals at risk of type 2 diabetes in African Americans. We revealed, for the first time, differential ancestral effect of certain metabolites (i.e., glutamate) on glucose homeostasis traits. Our study highlights the need for additional comprehensive metabolomic studies in well-characterized multiethnic cohorts.
    MeSH term(s) Humans ; Atherosclerosis/metabolism ; Black or African American ; Diabetes Mellitus, Type 2/metabolism ; Glucose ; Glutamates ; Homeostasis/physiology ; Insulin Resistance ; Metabolomics
    Chemical Substances Glucose (IY9XDZ35W2) ; Glutamates
    Language English
    Publishing date 2023-04-02
    Publishing country United States
    Document type Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
    ZDB-ID 2250617-2
    ISSN 1573-3890 ; 1573-3882
    ISSN (online) 1573-3890
    ISSN 1573-3882
    DOI 10.1007/s11306-023-01984-1
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: Diabetes: Unravelling the enigma of T2DM and cardiovascular disease.

    Bowden, Donald W / Cox, Amanda J

    Nature reviews. Endocrinology

    2013  Volume 9, Issue 11, Page(s) 632–633

    MeSH term(s) Chromosomes, Human, Pair 1 ; Coronary Disease/epidemiology ; Coronary Disease/genetics ; Diabetes Mellitus, Type 2/epidemiology ; Female ; Glutamate-Ammonia Ligase/genetics ; Glutamic Acid/metabolism ; Humans ; Male
    Chemical Substances Glutamic Acid (3KX376GY7L) ; Glutamate-Ammonia Ligase (EC 6.3.1.2)
    Language English
    Publishing date 2013-10-08
    Publishing country England
    Document type News ; Comment
    ZDB-ID 2489381-X
    ISSN 1759-5037 ; 1759-5029
    ISSN (online) 1759-5037
    ISSN 1759-5029
    DOI 10.1038/nrendo.2013.192
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article ; Online: The challenging search for diabetic nephropathy genes.

    Bowden, Donald W / Freedman, Barry I

    Diabetes

    2012  Volume 61, Issue 8, Page(s) 1923–1924

    MeSH term(s) Diabetes Mellitus, Type 1/epidemiology ; Diabetic Nephropathies/genetics ; Humans
    Language English
    Publishing date 2012-07-20
    Publishing country United States
    Document type Journal Article ; Research Support, N.I.H., Extramural ; Comment
    ZDB-ID 80085-5
    ISSN 1939-327X ; 0012-1797
    ISSN (online) 1939-327X
    ISSN 0012-1797
    DOI 10.2337/db12-0596
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article ; Online: Association of the PTPN1 gene with type 2 diabetes and insulin resistance.

    Bowden, Donald W

    Discovery medicine

    2004  Volume 4, Issue 24, Page(s) 427–432

    Abstract: Extract: An extensive body of evidence suggests that genes are major contributors to type 2 diabetes (T2DM) susceptibility. Until recently efforts to identify T2DM genes have met with limited success. Application of recent advances in high throughput ... ...

    Abstract Extract: An extensive body of evidence suggests that genes are major contributors to type 2 diabetes (T2DM) susceptibility. Until recently efforts to identify T2DM genes have met with limited success. Application of recent advances in high throughput genetics and genetic analysis has revealed evidence for association of protein tyrosine phosphatase N1 gene (PTPN1, a catalytic protein that removes phosphate groups from phosphorylated tyrosine residues) with T2DM and insulin resistance (a condition whereby the body no longer responds to insulin). The evidence suggests that this association is mediated by DNA sequence differences outside the coding region of the PTPN1 gene. Over 10 different genetic studies have concluded that the long arm of human chromosome 20 (20q) is linked to the inheritance of diabetes. One gene that is located in 20q is PTPN1, which encodes the PTP1B protein, a ubiquitously expressed phosphatase (protein tyrosine phosphatase 1B), which dephosphorylates phosphorylated tyrosine residues of the active insulin receptor protein thereby disrupting the insulin signaling pathway.
    Language English
    Publishing date 2004-12
    Publishing country United States
    Document type Journal Article
    ISSN 1944-7930
    ISSN (online) 1944-7930
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article ; Online: Risk factors: Race, renal disease and albuminuria.

    Freedman, Barry I / Bowden, Donald W

    Nature reviews. Nephrology

    2011  Volume 7, Issue 12, Page(s) 679–680

    MeSH term(s) Albuminuria/ethnology ; Albuminuria/etiology ; Continental Population Groups ; Humans ; Incidence ; Kidney Diseases/complications ; Kidney Diseases/ethnology ; Risk Factors ; United States/epidemiology
    Language English
    Publishing date 2011-10-18
    Publishing country England
    Document type News
    ZDB-ID 2490366-8
    ISSN 1759-507X ; 1759-5061
    ISSN (online) 1759-507X
    ISSN 1759-5061
    DOI 10.1038/nrneph.2011.154
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Article: Genetics of kidney disease.

    Bowden, Donald W

    Kidney international. Supplement

    2003  , Issue 83, Page(s) S8–12

    Abstract: Multiple lines of evidence suggest that susceptibility to develop end-stage renal disease (ESRD) has a significant genetic component. These studies include familial aggregation studies, comparisons of incidence rates between different racial or ethnic ... ...

    Abstract Multiple lines of evidence suggest that susceptibility to develop end-stage renal disease (ESRD) has a significant genetic component. These studies include familial aggregation studies, comparisons of incidence rates between different racial or ethnic populations, and segregation analysis. Multiple approaches have been employed in an effort to identify genes that contribute to this genetic susceptibility. Many studies have now been carried out assessing the contribution of specific "candidate genes," that is, genes with functions consistent with involvement in renal pathogenesis. Independent evaluations of specific candidate genes have frequently provided contradictory results. This may be due, in part, to the modest contribution to genetic susceptibility that these genes impart. In contrast to the focused analysis of candidate genes, the genome scan approach employs a comprehensive evaluation of inheritance throughout the genome. The great potential advantage of the genome scan is the ability to identify chromosomal regions harboring novel, previously unrecognized, genes that contribute to renal disease. Results from whole genome scans of family collections are now beginning to appear and give the promise that multiple comprehensive genetic evaluations of end-stage renal disease will soon be available for evaluation.
    MeSH term(s) Genetic Testing ; Humans ; Kidney Failure, Chronic/genetics
    Language English
    Publishing date 2003-02
    Publishing country United States
    Document type Journal Article ; Review
    ZDB-ID 193442-9
    ISSN 2157-1716 ; 0098-6577 ; 2157-1724
    ISSN (online) 2157-1716
    ISSN 0098-6577 ; 2157-1724
    DOI 10.1046/j.1523-1755.63.s83.3.x
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article: Genetics of diabetes complications.

    Bowden, Donald W

    Current diabetes reports

    2003  Volume 2, Issue 2, Page(s) 191–200

    Abstract: Long-term exposure to the hyperglycemia characteristic of diabetes patients leads to serious and frequently disabling or fatal complications. Emerging evidence suggests that genes are a significant contributor to an individual's risk of developing ... ...

    Abstract Long-term exposure to the hyperglycemia characteristic of diabetes patients leads to serious and frequently disabling or fatal complications. Emerging evidence suggests that genes are a significant contributor to an individual's risk of developing complications. This evidence is from evaluations of familial aggregation, differences in incidence in racial and ethnic groups, and statistical analysis of family data. Evidence to date suggests that complication genes are, distinct from the genes contributing to diabetes. Molecular geneticists have taken several approaches to identify genes contributing to complications, ranging from relatively simple analysis of specific candidate genes in small case-control comparisons to systematic evaluations of the human genome using genome scans and linkage analysis in large collections of families. Results suggest that genetic contributions to diabetes complications are diverse and complex in nature, presenting a significant challenge to researchers. Diabetes-affected families are frequently enriched for complications such as cardiovascular disease or nephropathy. In addition to their value in the study of diabetes complications, such families may be valuable resources for understanding cardiovascular disease and nephropathy in the nondiabetic population also.
    MeSH term(s) Diabetes Mellitus, Type 1/complications ; Diabetes Mellitus, Type 1/genetics ; Diabetes Mellitus, Type 2/complications ; Diabetes Mellitus, Type 2/genetics ; Humans
    Language English
    Publishing date 2003-02-25
    Publishing country United States
    Document type Journal Article ; Review
    ZDB-ID 2065167-3
    ISSN 1534-4827
    ISSN 1534-4827
    DOI 10.1007/s11892-002-0080-8
    Database MEDical Literature Analysis and Retrieval System OnLINE

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