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Li Y, Miao Y, Feng Q, Zhu W, Chen Y, Kang Q, Wang Z, Lu F, Zhang Q. Mitochondrial dysfunction and onset of type 2 diabetes along with its complications: a multi-omics Mendelian randomization and colocalization study. Front Endocrinol (Lausanne) 2024; 15:1401531. [PMID: 39280009 PMCID: PMC11392782 DOI: 10.3389/fendo.2024.1401531] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2024] [Accepted: 08/16/2024] [Indexed: 09/18/2024] Open
Abstract
Background Mitochondrial dysfunction plays a crucial role in Type 2 Diabetes Mellitus (T2DM) and its complications. However, the genetic pathophysiology remains under investigation. Through multi-omics Mendelian Randomization (MR) and colocalization analyses, we identified mitochondrial-related genes causally linked with T2DM and its complications. Methods Summary-level quantitative trait loci data at methylation, RNA, and protein levels were retrieved from European cohort studies. GWAS summary statistics for T2DM and its complications were collected from the DIAGRAM and FinnGen consortiums, respectively. Summary-data-based MR was utilized to estimate the causal effects. The heterogeneity in dependent instrument test assessed horizontal pleiotropy, while colocalization analysis determined whether genes and diseases share the same causal variant. Enrichment analysis, drug target analysis, and phenome-wide MR were conducted to further explore the biological functions, potential drugs, and causal associations with other diseases. Results Integrating evidence from multi-omics, we identified 18 causal mitochondrial-related genes. Enrichment analysis revealed they were not only related to nutrient metabolisms but also to the processes like mitophagy, autophagy, and apoptosis. Among these genes, Tu translation elongation factor mitochondrial (TUFM), 3-hydroxyisobutyryl-CoA hydrolase (HIBCH), and iron-sulfur cluster assembly 2 (ISCA2) were identified as Tier 1 genes, showing causal links with T2DM and strong colocalization evidence. TUFM and ISCA2 were causally associated with an increased risk of T2DM, while HIBCH showed an inverse causal relationship. The causal associations and colocalization effects for TUFM and HIBCH were validated in specific tissues. TUFM was also found to be a risk factor for microvascular complications in T2DM patients including retinopathy, nephropathy, and neuropathy. Furthermore, drug target analysis and phenome-wide MR underscored their significance as potential therapeutic targets. Conclusions This study identified 18 mitochondrial-related genes causally associated with T2DM at multi-omics levels, enhancing the understanding of mitochondrial dysfunction in T2DM and its complications. TUFM, HIBCH, and ISCA2 emerge as potential therapeutic targets for T2DM and its complications.
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Affiliation(s)
- Yang Li
- Department of Endocrinology, First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Yahu Miao
- Department of Endocrinology, First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Qing Feng
- Department of Endocrinology, First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Weixi Zhu
- Department of Endocrinology, First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Yijing Chen
- Department of Endocrinology, First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Qingqing Kang
- Department of Endocrinology, First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Zhen Wang
- Department of Endocrinology, First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Fangting Lu
- Department of Endocrinology, First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Qiu Zhang
- Department of Endocrinology, First Affiliated Hospital of Anhui Medical University, Hefei, China
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Levy D, Kirmani S, Huan T, Van Amburg J, Joehanes R, Uddin MM, Nguyen NQ, Yu B, Brody J, Fornage M, Bressler J, Sotoodehnia N, Ong D, Puddu F, Floyd J, Ballantyne C, Psaty B, Raffield L, Natarajan P, Conneely K, Carson A, Lange L, Ferrier K, Heard-Costa N, Murabito J, Bick A. Epigenome-wide DNA Methylation Association Study of CHIP Provides Insight into Perturbed Gene Regulation. RESEARCH SQUARE 2024:rs.3.rs-4656898. [PMID: 39070619 PMCID: PMC11276001 DOI: 10.21203/rs.3.rs-4656898/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/30/2024]
Abstract
With age, hematopoietic stem cells can acquire somatic mutations in leukemogenic genes that confer a proliferative advantage in a phenomenon termed "clonal hematopoiesis of indeterminate potential" (CHIP). How these mutations confer a proliferative advantage and result in increased risk for numerous age-related diseases remains poorly understood. We conducted a multiracial meta-analysis of epigenome-wide association studies (EWAS) of CHIP and its subtypes in four cohorts (N=8196) to elucidate the molecular mechanisms underlying CHIP and illuminate how these changes influence cardiovascular disease risk. The EWAS findings were functionally validated using human hematopoietic stem cell (HSC) models of CHIP. A total of 9615 CpGs were associated with any CHIP, 5990 with DNMT3A CHIP, 5633 with TET2 CHIP, and 6078 with ASXL1 CHIP (P <1×10-7). CpGs associated with CHIP subtypes overlapped moderately, and the genome-wide DNA methylation directions of effect were opposite for TET2 and DNMT3A CHIP, consistent with their opposing effects on global DNA methylation. There was high directional concordance between the CpGs shared from the meta-EWAS and human edited CHIP HSCs. Expression quantitative trait methylation analysis further identified transcriptomic changes associated with CHIP-associated CpGs. Causal inference analyses revealed 261 CHIP-associated CpGs associated with cardiovascular traits and all-cause mortality (FDR adjusted p-value <0.05). Taken together, our study sheds light on the epigenetic changes impacted by CHIP and their associations with age-related disease outcomes. The novel genes and pathways linked to the epigenetic features of CHIP may serve as therapeutic targets for preventing or treating CHIP-mediated diseases.
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Affiliation(s)
- Daniel Levy
- Framingham Heart Study, Framingham, MA, 01702, USA; Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health
| | - Sara Kirmani
- Framingham Heart Study, Framingham, MA, 01702, USA; Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda
| | | | - Joseph Van Amburg
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center
| | | | | | | | - Bing Yu
- University of Texas Health Science Center at Houston
| | | | - Myriam Fornage
- 1. Institute of Molecular Medicine, McGovern Medical School, The University of Texas Health Science Center 2. Human Genetics Center, Department of Epidemiology, School of Public Health
| | - Jan Bressler
- School of Public Health, University of Texas Health Science Center at Houston
| | | | - David Ong
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
| | | | | | | | | | | | - Pradeep Natarajan
- Broad Institute of Harvard and Massachusetts Institute of Technology
| | | | | | - Leslie Lange
- Division of Biomedical Informatics and Personalized Medicine
| | | | | | - Joanne Murabito
- Section of General Internal Medicine, Boston University Chobanian & Avedisian School of Medicine
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3
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Guirette M, Lan J, McKeown NM, Brown MR, Chen H, de Vries PS, Kim H, Rebholz CM, Morrison AC, Bartz TM, Fretts AM, Guo X, Lemaitre RN, Liu CT, Noordam R, de Mutsert R, Rosendaal FR, Wang CA, Beilin LJ, Mori TA, Oddy WH, Pennell CE, Chai JF, Whitton C, van Dam RM, Liu J, Tai ES, Sim X, Neuhouser ML, Kooperberg C, Tinker LF, Franceschini N, Huan T, Winkler TW, Bentley AR, Gauderman WJ, Heerkens L, Tanaka T, van Rooij J, Munroe PB, Warren HR, Voortman T, Chen H, Rao DC, Levy D, Ma J. Genome-Wide Interaction Analysis With DASH Diet Score Identified Novel Loci for Systolic Blood Pressure. Hypertension 2024; 81:552-560. [PMID: 38226488 PMCID: PMC10922535 DOI: 10.1161/hypertensionaha.123.22334] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Accepted: 12/28/2023] [Indexed: 01/17/2024]
Abstract
BACKGROUND The Dietary Approaches to Stop Hypertension (DASH) diet score lowers blood pressure (BP). We examined interactions between genotype and the DASH diet score in relation to systolic BP. METHODS We analyzed up to 9 420 585 single nucleotide polymorphisms in up to 127 282 individuals of 6 population groups (91% of European population) from the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium (n=35 660) and UK Biobank (n=91 622) and performed European population-specific and cross-population meta-analyses. RESULTS We identified 3 loci in European-specific analyses and an additional 4 loci in cross-population analyses at Pinteraction<5e-8. We observed a consistent interaction between rs117878928 at 15q25.1 (minor allele frequency, 0.03) and the DASH diet score (Pinteraction=4e-8; P for heterogeneity, 0.35) in European population, where the interaction effect size was 0.42±0.09 mm Hg (Pinteraction=9.4e-7) and 0.20±0.06 mm Hg (Pinteraction=0.001) in Cohorts for Heart and Aging Research in Genomic Epidemiology and the UK Biobank, respectively. The 1 Mb region surrounding rs117878928 was enriched with cis-expression quantitative trait loci (eQTL) variants (P=4e-273) and cis-DNA methylation quantitative trait loci variants (P=1e-300). Although the closest gene for rs117878928 is MTHFS, the highest narrow sense heritability accounted by single nucleotide polymorphisms potentially interacting with the DASH diet score in this locus was for gene ST20 at 15q25.1. CONCLUSIONS We demonstrated gene-DASH diet score interaction effects on systolic BP in several loci. Studies with larger diverse populations are needed to validate our findings.
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Affiliation(s)
- Mélanie Guirette
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA (M.G., J.L., J.M.)
| | - Jessie Lan
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA (M.G., J.L., J.M.)
| | - Nicola M McKeown
- Programs of Nutrition, Department of Health Sciences, Sargent College of Health & Rehabilitation Sciences, Boston University, MA (N.M.M.)
| | - Michael R Brown
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston (M.R.B., H.C., P.S.d.V., A.C.M.)
| | - Han Chen
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston (M.R.B., H.C., P.S.d.V., A.C.M.)
| | - Paul S de Vries
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston (M.R.B., H.C., P.S.d.V., A.C.M.)
| | - Hyunju Kim
- Department of Epidemiology (H.K., A.M.F.), Cardiovascular Health Research Unit, University of Washington, Seattle, WA
| | - Casey M Rebholz
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD (C.M.R.)
| | - Alanna C Morrison
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston (M.R.B., H.C., P.S.d.V., A.C.M.)
| | - Traci M Bartz
- Departments of Biostatistics and Medicine (T.M.B.), Cardiovascular Health Research Unit, University of Washington, Seattle, WA
| | - Amanda M Fretts
- Department of Epidemiology (H.K., A.M.F.), Cardiovascular Health Research Unit, University of Washington, Seattle, WA
| | - Xiuqing Guo
- The Lundquist Institute at Harbor-University of California, Los Angeles, Torrance, CA (X.G.)
| | - Rozenn N Lemaitre
- Department of Medicine (R.N.L.), Cardiovascular Health Research Unit, University of Washington, Seattle, WA
| | - Ching-Ti Liu
- Biostatistics, Boston University School of Public Health, MA (C.-T.L.)
| | - Raymond Noordam
- Department of Internal Medicine, Section of Gerontology and Geriatrics (R.N.), Leiden University Medical Center, the Netherlands
| | - Renée de Mutsert
- Department of Clinical Epidemiology (R.d.M., F.R.R.), Leiden University Medical Center, the Netherlands
| | - Frits R Rosendaal
- Department of Clinical Epidemiology (R.d.M., F.R.R.), Leiden University Medical Center, the Netherlands
| | - Carol A Wang
- School of Medicine and Public Health, University of Newcastle, NSW, Australia (C.A.W., C.E.P)
- Mothers' and Babies' Research Program, Hunter Medical Research Institute, NSW, Australia (C.A.W., C.E.P.)
| | - Lawrence J Beilin
- Medical School, Royal Perth Hospital Unit, University of Western Australia, Crawley (L.J.B., T.A.M.)
| | - Trevor A Mori
- Medical School, Royal Perth Hospital Unit, University of Western Australia, Crawley (L.J.B., T.A.M.)
| | - Wendy H Oddy
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Australia (W.H.O.)
| | - Craig E Pennell
- School of Medicine and Public Health, University of Newcastle, NSW, Australia (C.A.W., C.E.P)
- Mothers' and Babies' Research Program, Hunter Medical Research Institute, NSW, Australia (C.A.W., C.E.P.)
| | - Jin Fang Chai
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System (J.F.C., C.W., R.M.v.D., E.S.T., X.S.)
| | - Clare Whitton
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System (J.F.C., C.W., R.M.v.D., E.S.T., X.S.)
- School of Population Health, Curtin University, Perth, Western Australia, Australia (C.W.)
| | - Rob M van Dam
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System (J.F.C., C.W., R.M.v.D., E.S.T., X.S.)
- Department of Exercise and Nutrition Sciences, Milken Institute School of Public Health, The George Washington University (R.M.v.D.)
| | - Jianjun Liu
- Genome Institute of Singapore, Agency for Science, Technology and Research (J.L.)
| | - E Shyong Tai
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System (J.F.C., C.W., R.M.v.D., E.S.T., X.S.)
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore (E.S.T.)
| | - Xueling Sim
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System (J.F.C., C.W., R.M.v.D., E.S.T., X.S.)
| | - Marian L Neuhouser
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA (M.L.N., C.K., L.F.T.)
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA (M.L.N., C.K., L.F.T.)
| | - Lesley F Tinker
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA (M.L.N., C.K., L.F.T.)
| | - Nora Franceschini
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill (N.F.)
| | - TianXiao Huan
- Framingham Heart Study and Population Sciences Branch, National Heart, Lung, and Blood Institute, MA (T.H., D.L.)
| | - Thomas W Winkler
- Department of Genetic Epidemiology, University of Regensburg, Germany (T.W.W.)
| | - Amy R Bentley
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD (A.R.B.)
| | - W James Gauderman
- Division of Biostatistics, Department of Population and Public Health Sciences, University of Southern California (W.J.G.)
| | - Luc Heerkens
- Division of Human Nutrition and Health, Wageningen University & Research, the Netherlands (L.H.)
| | - Toshiko Tanaka
- Longitudinal Studies Section, National Institute on Aging, Baltimore, MD (T.T.)
| | - Jeroen van Rooij
- Department of Internal Medicine (J.v.R.), Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Patricia B Munroe
- Centre of Clinical Pharmacology & Precision Medicine, William Harvey Research Institute, Barts and the London Faculty of Medicine and Dentistry, Queen Mary University of London, United Kingdom (P.B.M., H.R.W.)
| | - Helen R Warren
- Centre of Clinical Pharmacology & Precision Medicine, William Harvey Research Institute, Barts and the London Faculty of Medicine and Dentistry, Queen Mary University of London, United Kingdom (P.B.M., H.R.W.)
| | - Trudy Voortman
- Department of Epidemiology (T.V.), Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Honglei Chen
- Department of Epidemiology and Biostatistics College of Human Medicine, Michigan State University, East Lansing (H.C.)
| | - D C Rao
- Center for Biostatistics and Data Science, Institute for Informatics, Data Science, and Biostatistics, Washington University School of Medicine, St. Louis, MO (D.C.R.)
| | - Daniel Levy
- Framingham Heart Study and Population Sciences Branch, National Heart, Lung, and Blood Institute, MA (T.H., D.L.)
| | - Jiantao Ma
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA (M.G., J.L., J.M.)
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Zhang Y, Wang Q, Xue H, Guo Y, Wei S, Li F, Gong L, Pan W, Jiang P. Epigenetic Regulation of Autophagy in Bone Metabolism. FUNCTION 2024; 5:zqae004. [PMID: 38486976 PMCID: PMC10935486 DOI: 10.1093/function/zqae004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2023] [Revised: 01/18/2024] [Accepted: 01/24/2024] [Indexed: 03/17/2024] Open
Abstract
The skeletal system is crucial for supporting bodily functions, protecting vital organs, facilitating hematopoiesis, and storing essential minerals. Skeletal homeostasis, which includes aspects such as bone density, structural integrity, and regenerative processes, is essential for normal skeletal function. Autophagy, an intricate intracellular mechanism for degrading and recycling cellular components, plays a multifaceted role in bone metabolism. It involves sequestering cellular waste, damaged proteins, and organelles within autophagosomes, which are then degraded and recycled. Autophagy's impact on bone health varies depending on factors such as regulation, cell type, environmental cues, and physiological context. Despite being traditionally considered a cytoplasmic process, autophagy is subject to transcriptional and epigenetic regulation within the nucleus. However, the precise influence of epigenetic regulation, including DNA methylation, histone modifications, and non-coding RNA expression, on cellular fate remains incompletely understood. The interplay between autophagy and epigenetic modifications adds complexity to bone cell regulation. This article provides an in-depth exploration of the intricate interplay between these two regulatory paradigms, with a focus on the epigenetic control of autophagy in bone metabolism. Such an understanding enhances our knowledge of bone metabolism-related disorders and offers insights for the development of targeted therapeutic strategies.
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Affiliation(s)
- Yazhou Zhang
- Department of Foot and Ankle Surgery, Tengzhou Central People’s Hospital, Tengzhou 277500, China
| | - Qianqian Wang
- Department of Pediatric Intensive Care Unit, Tengzhou Central People’s Hospital, Tengzhou 277500, China
| | - Hongjia Xue
- Department of Computer Science, University College London, London, WC1E 6BT, UK
| | - Yujin Guo
- Institute of Clinical Pharmacy & Pharmacology, Jining First People’s Hospital, Jining 272000, China
| | - Shanshan Wei
- Department of Pharmacy, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250000, China
- Department of Graduate, Shandong Academy of Medical Sciences, Shandong First Medical University, Jinan 250000, China
| | - Fengfeng Li
- Department of Neurosurgery, Tengzhou Central People’s Hospital, Tengzhou 277500, China
| | - Linqiang Gong
- Department of Gastroenterology, Tengzhou Central People's Hospital, Tengzhou 277500, China
| | - Weiliang Pan
- Department of Foot and Ankle Surgery, Tengzhou Central People’s Hospital, Tengzhou 277500, China
| | - Pei Jiang
- Translational Pharmaceutical Laboratory, Jining First People’s Hospital, Shandong First Medical University, Jining 272000, China
- Institute of Translational Pharmacy, Jining Medical Research Academy, Jining 272000, China
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Mozhui K, Kim H, Villani F, Haghani A, Sen S, Horvath S. Pleiotropic influence of DNA methylation QTLs on physiological and ageing traits. Epigenetics 2023; 18:2252631. [PMID: 37691384 PMCID: PMC10496549 DOI: 10.1080/15592294.2023.2252631] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Revised: 07/31/2023] [Accepted: 08/16/2023] [Indexed: 09/12/2023] Open
Abstract
DNA methylation is influenced by genetic and non-genetic factors. Here, we chart quantitative trait loci (QTLs) that modulate levels of methylation at highly conserved CpGs using liver methylome data from mouse strains belonging to the BXD family. A regulatory hotspot on chromosome 5 had the highest density of trans-acting methylation QTLs (trans-meQTLs) associated with multiple distant CpGs. We refer to this locus as meQTL.5a. Trans-modulated CpGs showed age-dependent changes and were enriched in developmental genes, including several members of the MODY pathway (maturity onset diabetes of the young). The joint modulation by genotype and ageing resulted in a more 'aged methylome' for BXD strains that inherited the DBA/2J parental allele at meQTL.5a. Further, several gene expression traits, body weight, and lipid levels mapped to meQTL.5a, and there was a modest linkage with lifespan. DNA binding motif and protein-protein interaction enrichment analyses identified the hepatic nuclear factor, Hnf1a (MODY3 gene in humans), as a strong candidate. The pleiotropic effects of meQTL.5a could contribute to variations in body size and metabolic traits, and influence CpG methylation and epigenetic ageing that could have an impact on lifespan.
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Affiliation(s)
- Khyobeni Mozhui
- Department of Preventive Medicine, University of Tennessee Health Science Center, Memphis, TN, USA
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Hyeonju Kim
- Department of Preventive Medicine, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Flavia Villani
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Amin Haghani
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Altos Labs, San Diego, CA, USA
| | - Saunak Sen
- Department of Preventive Medicine, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Altos Labs, San Diego, CA, USA
- Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, USA
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6
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Guirette M, Lan J, McKeown N, Brown MR, Chen H, DE Vries PS, Kim H, Rebholz CM, Morrison AC, Bartz TM, Fretts AM, Guo X, Lemaitre RN, Liu CT, Noordam R, DE Mutsert R, Rosendaal FR, Wang CA, Beilin L, Mori TA, Oddy WH, Pennell CE, Chai JF, Whitton C, VAN Dam RM, Liu J, Tai ES, Sim X, Neuhouser ML, Kooperberg C, Tinker L, Franceschini N, Huan T, Winkler TW, Bentley AR, Gauderman WJ, Heerkens L, Tanaka T, van Rooij J, Munroe PB, Warren HR, Voortman T, Chen H, Rao DC, Levy D, Ma J. Genome-Wide Interaction Analysis with DASH Diet Score Identified Novel Loci for Systolic Blood Pressure. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.11.10.23298402. [PMID: 37986948 PMCID: PMC10659476 DOI: 10.1101/2023.11.10.23298402] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
Objective We examined interactions between genotype and a Dietary Approaches to Stop Hypertension (DASH) diet score in relation to systolic blood pressure (SBP). Methods We analyzed up to 9,420,585 biallelic imputed single nucleotide polymorphisms (SNPs) in up to 127,282 individuals of six population groups (91% of European population) from the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium (CHARGE; n=35,660) and UK Biobank (n=91,622) and performed European population-specific and cross-population meta-analyses. Results We identified three loci in European-specific analyses and an additional four loci in cross-population analyses at P for interaction < 5e-8. We observed a consistent interaction between rs117878928 at 15q25.1 (minor allele frequency = 0.03) and the DASH diet score (P for interaction = 4e-8; P for heterogeneity = 0.35) in European population, where the interaction effect size was 0.42±0.09 mm Hg (P for interaction = 9.4e-7) and 0.20±0.06 mm Hg (P for interaction = 0.001) in CHARGE and the UK Biobank, respectively. The 1 Mb region surrounding rs117878928 was enriched with cis-expression quantitative trait loci (eQTL) variants (P = 4e-273) and cis-DNA methylation quantitative trait loci (mQTL) variants (P = 1e-300). While the closest gene for rs117878928 is MTHFS, the highest narrow sense heritability accounted by SNPs potentially interacting with the DASH diet score in this locus was for gene ST20 at 15q25.1. Conclusion We demonstrated gene-DASH diet score interaction effects on SBP in several loci. Studies with larger diverse populations are needed to validate our findings.
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Affiliation(s)
- Mélanie Guirette
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA
| | - Jessie Lan
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA
| | - Nicola McKeown
- Programs of Nutrition, Department of Health Sciences, Sargent College of Health & Rehabilitation Sciences, Boston University, Boston, MA, USA
| | - Michael R Brown
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Han Chen
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Paul S DE Vries
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Hyunju Kim
- Cardiovascular Health Research Unit, Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Casey M Rebholz
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Alanna C Morrison
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Traci M Bartz
- Cardiovascular Health Research Unit, Departments of Biostatistics and Medicine, University of Washington, Seattle, WA, USA
| | - Amanda M Fretts
- Cardiovascular Health Research Unit, Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Xiuqing Guo
- The Lundquist Institute at Harbor-UCLA, Torrance, CA, USA
| | - Rozenn N Lemaitre
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Ching-Ti Liu
- Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Raymond Noordam
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands
| | - Renée DE Mutsert
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Frits R Rosendaal
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Carol A Wang
- School of Medicine and Public Health, University of Newcastle, NSW, Australia
- Hunter Medical Research Institute, NSW, Australia
| | - Lawrence Beilin
- Medical School, Royal Perth Hospital Unit, University of Western Australia, Crawley, Western Australia, Australia
| | - Trevor A Mori
- Medical School, Royal Perth Hospital Unit, University of Western Australia, Crawley, Western Australia, Australia
| | - Wendy H Oddy
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Australia Saw Swee Hock, School of Public Health, National University of Singapore and National University Health System, Singapore
| | - Craig E Pennell
- School of Medicine and Public Health, University of Newcastle, NSW, Australia
- Hunter Medical Research Institute, NSW, Australia
| | - Jin Fang Chai
- School of Population Health, Curtin University, Perth, Western Australia, Australia
| | - Clare Whitton
- School of Population Health, Curtin University, Perth, Western Australia, Australia
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore
| | - Rob M VAN Dam
- School of Population Health, Curtin University, Perth, Western Australia, Australia
| | - Jianjun Liu
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore
| | - E Shyong Tai
- School of Population Health, Curtin University, Perth, Western Australia, Australia
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Xueling Sim
- School of Population Health, Curtin University, Perth, Western Australia, Australia
| | - Marian L Neuhouser
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Lesley Tinker
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Nora Franceschini
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Tianxiao Huan
- Framingham Heart Study and Population Sciences Branch, NHLBI, Framingham, MA, USA
| | - Thomas W Winkler
- Department of Genetic Epidemiology, University of Regensburg; Regensburg, Germany
| | - Amy R Bentley
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - W James Gauderman
- Division of Biostatistics, Department of Population and Public Health Sciences, University of Southern California; CA, USA
| | - Luc Heerkens
- Division of Human Nutrition and Health, Wageningen University & Research, Wageningen, the Netherlands
| | - Toshiko Tanaka
- Longitudinal Studies Section, National Institute on Aging, Baltimore, MD, USA
| | - Jeroen van Rooij
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Patricia B Munroe
- Centre of Clinical Pharmacology & Precision Medicine, William Harvey Research Institute, Barts and The London Faculty of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Helen R Warren
- Centre of Clinical Pharmacology & Precision Medicine, William Harvey Research Institute, Barts and The London Faculty of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Trudy Voortman
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Honglei Chen
- Department of Epidemiology and Biostatistics College of Human Medicine, Michigan State University, East Lansing, Michigan, USA
| | - D C Rao
- Center for Biostatistics and Data Science, Institute for Informatics, Data Science, and Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Daniel Levy
- Framingham Heart Study and Population Sciences Branch, NHLBI, Framingham, MA, USA
| | - Jiantao Ma
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA
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7
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Sarnowski C, Huan T, Ma Y, Joehanes R, Beiser A, DeCarli CS, Heard-Costa NL, Levy D, Lin H, Liu CT, Liu C, Meigs JB, Satizabal CL, Florez JC, Hivert MF, Dupuis J, De Jager PL, Bennett DA, Seshadri S, Morrison AC. Multi-tissue epigenetic analysis identifies distinct associations underlying insulin resistance and Alzheimer's disease at CPT1A locus. Clin Epigenetics 2023; 15:173. [PMID: 37891690 PMCID: PMC10612362 DOI: 10.1186/s13148-023-01589-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Accepted: 10/20/2023] [Indexed: 10/29/2023] Open
Abstract
BACKGROUND Insulin resistance (IR) is a major risk factor for Alzheimer's disease (AD) dementia. The mechanisms by which IR predisposes to AD are not well-understood. Epigenetic studies may help identify molecular signatures of IR associated with AD, thus improving our understanding of the biological and regulatory mechanisms linking IR and AD. METHODS We conducted an epigenome-wide association study of IR, quantified using the homeostatic model assessment of IR (HOMA-IR) and adjusted for body mass index, in 3,167 participants from the Framingham Heart Study (FHS) without type 2 diabetes at the time of blood draw used for methylation measurement. We identified DNA methylation markers associated with IR at the genome-wide level accounting for multiple testing (P < 1.1 × 10-7) and evaluated their association with neurological traits in participants from the FHS (N = 3040) and the Religious Orders Study/Memory and Aging Project (ROSMAP, N = 707). DNA methylation profiles were measured in blood (FHS) or dorsolateral prefrontal cortex (ROSMAP) using the Illumina HumanMethylation450 BeadChip. Linear regressions (ROSMAP) or mixed-effects models accounting for familial relatedness (FHS) adjusted for age, sex, cohort, self-reported race, batch, and cell type proportions were used to assess associations between DNA methylation and neurological traits accounting for multiple testing. RESULTS We confirmed the strong association of blood DNA methylation with IR at three loci (cg17901584-DHCR24, cg17058475-CPT1A, cg00574958-CPT1A, and cg06500161-ABCG1). In FHS, higher levels of blood DNA methylation at cg00574958 and cg17058475 were both associated with lower IR (P = 2.4 × 10-11 and P = 9.0 × 10-8), larger total brain volumes (P = 0.03 and P = 9.7 × 10-4), and smaller log lateral ventricular volumes (P = 0.07 and P = 0.03). In ROSMAP, higher levels of brain DNA methylation at the same two CPT1A markers were associated with greater risk of cognitive impairment (P = 0.005 and P = 0.02) and higher AD-related indices (CERAD score: P = 5 × 10-4 and 0.001; Braak stage: P = 0.004 and P = 0.01). CONCLUSIONS Our results suggest potentially distinct epigenetic regulatory mechanisms between peripheral blood and dorsolateral prefrontal cortex tissues underlying IR and AD at CPT1A locus.
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Affiliation(s)
- Chloé Sarnowski
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA.
| | - Tianxiao Huan
- Population Sciences Branch, National Heart, Lung and Blood Institutes of Health, Bethesda, MD, USA
| | - Yiyi Ma
- Center for Translational and Computational Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA
| | - Roby Joehanes
- Population Sciences Branch, National Heart, Lung and Blood Institutes of Health, Bethesda, MD, USA
- The Framingham Heart Study, Framingham, MA, USA
| | - Alexa Beiser
- The Framingham Heart Study, Framingham, MA, USA
- Department of Biostatistics, School of Public Health, Boston University, Boston, MA, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | | | - Nancy L Heard-Costa
- The Framingham Heart Study, Framingham, MA, USA
- Department of Biostatistics, School of Public Health, Boston University, Boston, MA, USA
| | - Daniel Levy
- Center for Translational and Computational Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA
- The Framingham Heart Study, Framingham, MA, USA
| | - Honghuang Lin
- Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Ching-Ti Liu
- Department of Biostatistics, School of Public Health, Boston University, Boston, MA, USA
| | - Chunyu Liu
- Department of Biostatistics, School of Public Health, Boston University, Boston, MA, USA
| | - James B Meigs
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Claudia L Satizabal
- The Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, The University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
- Department of Population Health Sciences, The University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Jose C Florez
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine and Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Marie-France Hivert
- Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Harvard University, Boston, MA, USA
- Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Josée Dupuis
- Department of Biostatistics, School of Public Health, Boston University, Boston, MA, USA
- Department of Epidemiology, Biostatistics and Occupational Health, School of Population and Global Health, McGill University, Montreal, Canada
| | - Philip L De Jager
- Center for Translational and Computational Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY, USA
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - Sudha Seshadri
- The Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, The University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Alanna C Morrison
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
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8
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Maimaiti A, Turhon M, Abulaiti A, Dilixiati Y, Zhang F, Axieer A, Kadeer K, Zhang Y, Maimaitili A, Yang X. DNA methylation regulator-mediated modification patterns and risk of intracranial aneurysm: a multi-omics and epigenome-wide association study integrating machine learning, Mendelian randomization, eQTL and mQTL data. J Transl Med 2023; 21:660. [PMID: 37742034 PMCID: PMC10518114 DOI: 10.1186/s12967-023-04512-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Accepted: 09/08/2023] [Indexed: 09/25/2023] Open
Abstract
BACKGROUND Intracranial aneurysms (IAs) pose a significant and intricate challenge. Elucidating the interplay between DNA methylation and IA pathogenesis is paramount to identify potential biomarkers and therapeutic interventions. METHODS We employed a comprehensive bioinformatics investigation of DNA methylation in IA, utilizing a transcriptomics-based methodology that encompassed 100 machine learning algorithms, genome-wide association studies (GWAS), Mendelian randomization (MR), and summary-data-based Mendelian randomization (SMR). Our sophisticated analytical strategy allowed for a systematic assessment of differentially methylated genes and their implications on the onset, progression, and rupture of IA. RESULTS We identified DNA methylation-related genes (MRGs) and associated molecular pathways, and the MR and SMR analyses provided evidence for potential causal links between the observed DNA methylation events and IA predisposition. CONCLUSION These insights not only augment our understanding of the molecular underpinnings of IA but also underscore potential novel biomarkers and therapeutic avenues. Although our study faces inherent limitations and hurdles, it represents a groundbreaking initiative in deciphering the intricate relationship between genetic, epigenetic, and environmental factors implicated in IA pathogenesis.
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Affiliation(s)
- Aierpati Maimaiti
- Department of Neurosurgery, Xinjiang Medical University Affiliated First Hospital, Urumqi, Xinjiang, 830017, People's Republic of China
| | - Mirzat Turhon
- Department of Interventional Neuroradiology, Beijing Neurosurgical Institute, Capital Medical University, 100070, Beijing, People's Republic of China
- Department of Interventional Neuroradiology, Beijing TianTan Hospital, Capital Medical University, Beijing, People's Republic of China
| | - Aimitaji Abulaiti
- Xinjiang Medical University, Urumqi, Xinjiang, People's Republic of China
| | | | - Fujunhui Zhang
- Department of Interventional Neuroradiology, Beijing Neurosurgical Institute, Capital Medical University, 100070, Beijing, People's Republic of China
- Department of Interventional Neuroradiology, Beijing TianTan Hospital, Capital Medical University, Beijing, People's Republic of China
| | - Aximujiang Axieer
- Department of Neurosurgery, Xinjiang Medical University Affiliated First Hospital, Urumqi, Xinjiang, 830017, People's Republic of China
| | - Kaheerman Kadeer
- Department of Neurosurgery, Xinjiang Medical University Affiliated First Hospital, Urumqi, Xinjiang, 830017, People's Republic of China
| | - Yisen Zhang
- Department of Interventional Neuroradiology, Beijing Neurosurgical Institute, Capital Medical University, 100070, Beijing, People's Republic of China.
- Department of Interventional Neuroradiology, Beijing TianTan Hospital, Capital Medical University, Beijing, People's Republic of China.
| | - Aisha Maimaitili
- Department of Neurosurgery, Xinjiang Medical University Affiliated First Hospital, Urumqi, Xinjiang, 830017, People's Republic of China.
| | - Xinjian Yang
- Department of Interventional Neuroradiology, Beijing Neurosurgical Institute, Capital Medical University, 100070, Beijing, People's Republic of China.
- Department of Interventional Neuroradiology, Beijing TianTan Hospital, Capital Medical University, Beijing, People's Republic of China.
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