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Artikel ; 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.
Sprache	Englisch
Erscheinungsdatum	2024-02-23
Erscheinungsland	United States
Dokumenttyp	Journal Article
ZDB-ID	80085-5
ISSN	1939-327X ; 0012-1797
ISSN (online)	1939-327X
ISSN	0012-1797
DOI	10.2337/db23-0540
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel ; 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 Band 19, Heft 4, Seite(n) 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-Begriff(e)	Humans ; Atherosclerosis/metabolism ; Black or African American ; Diabetes Mellitus, Type 2/metabolism ; Glucose ; Glutamates ; Homeostasis/physiology ; Insulin Resistance ; Metabolomics
Chemische Substanzen	Glucose (IY9XDZ35W2) ; Glutamates
Sprache	Englisch
Erscheinungsdatum	2023-04-02
Erscheinungsland	United States
Dokumenttyp	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
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel ; 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 Band 19, Heft 8, Seite(n) 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-Begriff(e)	Humans ; Insulin Resistance ; Metabolomics ; Atherosclerosis/metabolism
Sprache	Englisch
Erscheinungsdatum	2023-08-09
Erscheinungsland	United States
Dokumenttyp	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
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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

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

Genetic epidemiology

2017 Band 41, Heft 6, Seite(n) 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.
Sprache	Englisch
Erscheinungsdatum	2017-09
Erscheinungsland	United States
Dokumenttyp	Journal Article
ZDB-ID	605785-8
ISSN	1098-2272 ; 0741-0395
ISSN (online)	1098-2272
ISSN	0741-0395
DOI	10.1002/gepi.22054
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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

Bowden, Donald W / Cox, Amanda J

Nature reviews. Endocrinology

2013 Band 9, Heft 11, Seite(n) 632–633

Mesh-Begriff(e)	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
Chemische Substanzen	Glutamic Acid (3KX376GY7L) ; Glutamate-Ammonia Ligase (EC 6.3.1.2)
Sprache	Englisch
Erscheinungsdatum	2013-10-08
Erscheinungsland	England
Dokumenttyp	News ; Comment
ZDB-ID	2489381-X
ISSN	1759-5037 ; 1759-5029
ISSN (online)	1759-5037
ISSN	1759-5029
DOI	10.1038/nrendo.2013.192
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel ; Online: The challenging search for diabetic nephropathy genes.

Bowden, Donald W / Freedman, Barry I

Diabetes

2012 Band 61, Heft 8, Seite(n) 1923–1924

Mesh-Begriff(e)	Diabetes Mellitus, Type 1/epidemiology ; Diabetic Nephropathies/genetics ; Humans
Sprache	Englisch
Erscheinungsdatum	2012-07-20
Erscheinungsland	United States
Dokumenttyp	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
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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

Bowden, Donald W

Discovery medicine

2004 Band 4, Heft 24, Seite(n) 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.
Sprache	Englisch
Erscheinungsdatum	2004-12
Erscheinungsland	United States
Dokumenttyp	Journal Article
ISSN	1944-7930
ISSN (online)	1944-7930
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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

Freedman, Barry I / Bowden, Donald W

Nature reviews. Nephrology

2011 Band 7, Heft 12, Seite(n) 679–680

Mesh-Begriff(e)	Albuminuria/ethnology ; Albuminuria/etiology ; Continental Population Groups ; Humans ; Incidence ; Kidney Diseases/complications ; Kidney Diseases/ethnology ; Risk Factors ; United States/epidemiology
Sprache	Englisch
Erscheinungsdatum	2011-10-18
Erscheinungsland	England
Dokumenttyp	News
ZDB-ID	2490366-8
ISSN	1759-507X ; 1759-5061
ISSN (online)	1759-507X
ISSN	1759-5061
DOI	10.1038/nrneph.2011.154
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel: Genetics of kidney disease.

Bowden, Donald W

Kidney international. Supplement

2003 , Heft 83, Seite(n) 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-Begriff(e)	Genetic Testing ; Humans ; Kidney Failure, Chronic/genetics
Sprache	Englisch
Erscheinungsdatum	2003-02
Erscheinungsland	United States
Dokumenttyp	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
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel: Genetics of diabetes complications.

Bowden, Donald W

Current diabetes reports

2003 Band 2, Heft 2, Seite(n) 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-Begriff(e)	Diabetes Mellitus, Type 1/complications ; Diabetes Mellitus, Type 1/genetics ; Diabetes Mellitus, Type 2/complications ; Diabetes Mellitus, Type 2/genetics ; Humans
Sprache	Englisch
Erscheinungsdatum	2003-02-25
Erscheinungsland	United States
Dokumenttyp	Journal Article ; Review
ZDB-ID	2065167-3
ISSN	1534-4827
ISSN	1534-4827
DOI	10.1007/s11892-002-0080-8
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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