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Article ; Online: Integrated omics analysis of coronary artery calcifications and myocardial infarction: the Framingham Heart Study.

Møller, Amalie Lykkemark / Vasan, Ramachandran S / Levy, Daniel / Andersson, Charlotte / Lin, Honghuang

2023 Volume 13, Issue 1, Page(s) 21581

Abstract: Gene function can be described using various measures. We integrated association studies of three types of omics data to provide insights into the pathophysiology of subclinical coronary disease and myocardial infarction (MI). Using multivariable ... ...

Abstract	Gene function can be described using various measures. We integrated association studies of three types of omics data to provide insights into the pathophysiology of subclinical coronary disease and myocardial infarction (MI). Using multivariable regression models, we associated: (1) single nucleotide polymorphism, (2) DNA methylation, and (3) gene expression with coronary artery calcification (CAC) scores and MI. Among 3106 participants of the Framingham Heart Study, 65 (2.1%) had prevalent MI and 60 (1.9%) had incident MI, median CAC value was 67.8 [IQR 10.8, 274.9], and 1403 (45.2%) had CAC scores > 0 (prevalent CAC). Prevalent CAC was associated with AHRR (linked to smoking) and EXOC3 (affecting platelet function and promoting hemostasis). CAC score was associated with VWA1 (extracellular matrix protein associated with cartilage structure in endomysium). For prevalent MI we identified FYTTD1 (down-regulated in familial hypercholesterolemia) and PINK1 (linked to cardiac tissue homeostasis and ischemia-reperfusion injury). Incident MI was associated with IRX3 (enhancing browning of white adipose tissue) and STXBP3 (controlling trafficking of glucose transporter type 4 to plasma). Using an integrative trans-omics approach, we identified both putatively novel and known candidate genes associated with CAC and MI. Replication of findings is warranted.
MeSH term(s)	Humans ; Risk Factors ; Coronary Artery Disease/epidemiology ; Coronary Artery Disease/genetics ; Myocardial Infarction/epidemiology ; Myocardial Infarction/genetics ; Myocardial Infarction/complications ; Longitudinal Studies ; Vascular Calcification/genetics ; Vascular Calcification/complications
Language	English
Publishing date	2023-12-07
Publishing country	England
Document type	Journal Article
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-023-48848-1
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Article: Exploring cognitive progression subtypes in the Framingham Heart Study.

Ding, Huitong / Wang, Biqi / Hamel, Alexander P / Karjadi, Cody / Ang, Ting F A / Au, Rhoda / Lin, Honghuang

Alzheimer's & dementia (Amsterdam, Netherlands)

2024 Volume 16, Issue 1, Page(s) e12574

Abstract: Introduction: Alzheimer's disease (AD) is a heterogeneous disorder characterized by complex underlying neuropathology that is not fully understood. This study aimed to identify cognitive progression subtypes and examine their correlation with clinical ... ...

Abstract	Introduction: Alzheimer's disease (AD) is a heterogeneous disorder characterized by complex underlying neuropathology that is not fully understood. This study aimed to identify cognitive progression subtypes and examine their correlation with clinical outcomes. Methods: Participants of this study were recruited from the Framingham Heart Study. The Subtype and Stage Inference (SuStaIn) method was used to identify cognitive progression subtypes based on eight cognitive domains. Results: Three cognitive progression subtypes were identified, including verbal learning (Subtype 1), abstract reasoning (Subtype 2), and visual memory (Subtype 3). These subtypes represent different domains of cognitive decline during the progression of AD. Significant differences in age of onset among the different subtypes were also observed. A higher SuStaIn stage was significantly associated with increased mortality risk. Discussion: This study provides a characterization of AD heterogeneity in cognitive progression, emphasizing the importance of developing personalized approaches for risk stratification and intervention. Highlights: We used the Subtype and Stage Inference (SuStaIn) method to identify three cognitive progression subtypes.Different subtypes have significant variations in age of onset.Higher stages of progression are associated with increased mortality risk.
Language	English
Publishing date	2024-03-21
Publishing country	United States
Document type	Journal Article
ZDB-ID	2832898-X
ISSN	2352-8729
ISSN	2352-8729
DOI	10.1002/dad2.12574
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Article ; Online: Transcriptomic Heterogeneity of Alzheimer's Disease Associated with Lipid Genetic Risk.

Miao, Xiao / Liu, Weifeng / Fan, Bin / Lin, Honghuang

Neuromolecular medicine

2020 Volume 22, Issue 4, Page(s) 534–541

Abstract: Alzheimer's disease (AD) is a multifactorial disease that affects more than 5 million Americans. Multiple pathways might be involved in the AD pathogenesis. The implication of lipid genetic susceptibility on brain gene expression is yet to be ... ...

Abstract	Alzheimer's disease (AD) is a multifactorial disease that affects more than 5 million Americans. Multiple pathways might be involved in the AD pathogenesis. The implication of lipid genetic susceptibility on brain gene expression is yet to be investigated. The current study included 192 brain samples from AD patients who were enrolled in the ROSMAP study. The samples were genotyped and imputed to the HRC Reference Panel. Lipid polygenetic risk score was constructed from the weighted sum of genetic variants associated with low-density lipoprotein cholesterol (LDL-C). The gene expression was profiled by RNA sequencing, and the association of gene expression with lipid polygenetic risk scores was tested by linear regression models adjusted for age, sex and APOE e4 alleles. Three genes were found to associate with lipid polygenetic risk scores, including HMCN2 (P = 3.6 × 10
MeSH term(s)	Adaptor Proteins, Signal Transducing/genetics ; Aged ; Aged, 80 and over ; Alzheimer Disease/genetics ; Alzheimer Disease/metabolism ; Apolipoprotein E4/genetics ; Cholesterol, LDL/metabolism ; Educational Status ; Female ; Gene Regulatory Networks ; Genetic Association Studies ; Genetic Predisposition to Disease ; Humans ; LIM Domain Proteins/genetics ; Male ; Molecular Sequence Annotation ; Prospective Studies ; Risk ; Transcription Factors/genetics ; Transcriptome
Chemical Substances	Adaptor Proteins, Signal Transducing ; Apolipoprotein E4 ; Cholesterol, LDL ; FHL5 protein, human ; LIM Domain Proteins ; PDLIM5 protein, human ; Transcription Factors
Language	English
Publishing date	2020-08-29
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	2077809-0
ISSN	1559-1174 ; 1535-1084
ISSN (online)	1559-1174
ISSN	1535-1084
DOI	10.1007/s12017-020-08610-6
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Article: Association of lifestyle with deep learning predicted electrocardiographic age.

Zhang, Cuili / Miao, Xiao / Wang, Biqi / Thomas, Robert J / Ribeiro, Antônio H / Brant, Luisa C C / Ribeiro, Antonio L P / Lin, Honghuang

Frontiers in cardiovascular medicine

2023 Volume 10, Page(s) 1160091

Abstract: Background: People age at different rates. Biological age is a risk factor for many chronic diseases independent of chronological age. A good lifestyle is known to improve overall health, but its association with biological age is unclear.: Methods: ... ...

Abstract	Background: People age at different rates. Biological age is a risk factor for many chronic diseases independent of chronological age. A good lifestyle is known to improve overall health, but its association with biological age is unclear. Methods: This study included participants from the UK Biobank who had undergone 12-lead resting electrocardiography (ECG). Biological age was estimated by a deep learning model (defined as ECG-age), and the difference between ECG-age and chronological age was defined as Δage. Participants were further categorized into an ideal (score 4), intermediate (scores 2 and 3) or unfavorable lifestyle (score 0 or 1). Four lifestyle factors were investigated, including diet, alcohol consumption, physical activity, and smoking. Linear regression models were used to examine the association between lifestyle factors and Δage, and the models were adjusted for sex and chronological age. Results: This study included 44,094 individuals (mean age 64 ± 8, 51.4% females). A significant correlation was observed between predicted biological age and chronological age (correlation coefficient = 0.54, Conclusion: In this large contemporary population, a strong association was observed between all four studied healthy lifestyle factors and deaccelerated aging. Our study underscores the importance of a healthy lifestyle to reduce the burden of aging-related diseases.
Language	English
Publishing date	2023-04-24
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2781496-8
ISSN	2297-055X
ISSN	2297-055X
DOI	10.3389/fcvm.2023.1160091
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Article ; Online: The bidirectional association between atrial fibrillation and myocardial infarction.

Frederiksen, Tanja Charlotte / Dahm, Christina Catherine / Preis, Sarah R / Lin, Honghuang / Trinquart, Ludovic / Benjamin, Emelia J / Kornej, Jelena

Nature reviews. Cardiology

2023 Volume 20, Issue 9, Page(s) 631–644

Abstract: Atrial fibrillation (AF) is associated with an increased risk of myocardial infarction (MI) and vice versa. This bidirectional association relies on shared risk factors as well as on several direct and indirect mechanisms, including inflammation, atrial ... ...

Abstract	Atrial fibrillation (AF) is associated with an increased risk of myocardial infarction (MI) and vice versa. This bidirectional association relies on shared risk factors as well as on several direct and indirect mechanisms, including inflammation, atrial ischaemia, left ventricular remodelling, myocardial oxygen supply-demand mismatch and coronary artery embolism, through which one condition can predispose to the other. Patients with both AF and MI are at greater risk of stroke, heart failure and death than patients with only one of the conditions. In this Review, we describe the bidirectional association between AF and MI. We discuss the pathogenic basis of this bidirectional relationship, describe the risk of adverse outcomes when the two conditions coexist, and review current data and guidelines on the prevention and management of both conditions. We also identify important gaps in the literature and propose directions for future research on the bidirectional association between AF and MI. The Review also features a summary of methodological approaches for the study of bidirectional associations in population-based studies.
MeSH term(s)	Humans ; Atrial Fibrillation/complications ; Atrial Fibrillation/epidemiology ; Myocardial Infarction/etiology ; Myocardial Infarction/complications ; Coronary Artery Disease ; Heart Atria ; Heart Failure ; Risk Factors
Language	English
Publishing date	2023-04-17
Publishing country	England
Document type	Journal Article ; Review
ZDB-ID	2490375-9
ISSN	1759-5010 ; 1759-5002
ISSN (online)	1759-5010
ISSN	1759-5002
DOI	10.1038/s41569-023-00857-3
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Article ; Online: Multimodal Machine Learning for 10-Year Dementia Risk Prediction: The Framingham Heart Study.

Ding, Huitong / Mandapati, Amiya / Hamel, Alexander P / Karjadi, Cody / Ang, Ting F A / Xia, Weiming / Au, Rhoda / Lin, Honghuang

Journal of Alzheimer's disease : JAD

2023 Volume 96, Issue 1, Page(s) 277–286

Abstract: Background: Early prediction of dementia risk is crucial for effective interventions. Given the known etiologic heterogeneity, machine learning methods leveraging multimodal data, such as clinical manifestations, neuroimaging biomarkers, and well- ... ...

Abstract	Background: Early prediction of dementia risk is crucial for effective interventions. Given the known etiologic heterogeneity, machine learning methods leveraging multimodal data, such as clinical manifestations, neuroimaging biomarkers, and well-documented risk factors, could predict dementia more accurately than single modal data. Objective: This study aims to develop machine learning models that capitalize on neuropsychological (NP) tests, magnetic resonance imaging (MRI) measures, and clinical risk factors for 10-year dementia prediction. Methods: This study included participants from the Framingham Heart Study, and various data modalities such as NP tests, MRI measures, and demographic variables were collected. CatBoost was used with Optuna hyperparameter optimization to create prediction models for 10-year dementia risk using different combinations of data modalities. The contribution of each modality and feature for the prediction task was also quantified using Shapley values. Results: This study included 1,031 participants with normal cognitive status at baseline (age 75±5 years, 55.3% women), of whom 205 were diagnosed with dementia during the 10-year follow-up. The model built on three modalities demonstrated the best dementia prediction performance (AUC 0.90±0.01) compared to single modality models (AUC range: 0.82-0.84). MRI measures contributed most to dementia prediction (mean absolute Shapley value: 3.19), suggesting the necessity of multimodal inputs. Conclusion: This study shows that a multimodal machine learning framework had a superior performance for 10-year dementia risk prediction. The model can be used to increase vigilance for cognitive deterioration and select high-risk individuals for early intervention and risk management.
MeSH term(s)	Humans ; Female ; Aged ; Aged, 80 and over ; Male ; Alzheimer Disease/pathology ; Cognitive Dysfunction/diagnosis ; Longitudinal Studies ; Neuroimaging/methods ; Magnetic Resonance Imaging/methods ; Machine Learning
Language	English
Publishing date	2023-09-09
Publishing country	Netherlands
Document type	Journal Article ; Research Support, U.S. Gov't, Non-P.H.S. ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	1440127-7
ISSN	1875-8908 ; 1387-2877
ISSN (online)	1875-8908
ISSN	1387-2877
DOI	10.3233/JAD-230496
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Article ; Online: Obesity impacts the expression of Alzheimer's disease-related genes: The Framingham Heart Study.

Charisis, Sokratis / Lin, Honghuang / Ray, Roshni / Joehanes, Roby / Beiser, Alexa S / Levy, Daniel / Seshadri, Sudha / Sargurupremraj, Muralidharan / Satizabal, Claudia L

Alzheimer's & dementia : the journal of the Alzheimer's Association

2023 Volume 19, Issue 8, Page(s) 3496–3505

Abstract: Introduction: We investigated associations of obesity with the expression of Alzheimer's disease (AD)-related genes in a large community-based cohort.: Methods: The sample consisted of 5619 participants from the Framingham Heart Study. Obesity ... ...

Abstract	Introduction: We investigated associations of obesity with the expression of Alzheimer's disease (AD)-related genes in a large community-based cohort. Methods: The sample consisted of 5619 participants from the Framingham Heart Study. Obesity metrics included body mass index (BMI) and waist-to-hip ratio (WHR). Gene expression was measured for a set of 74 AD-related genes, derived by integrating genome-wide association study results with functional genomics data. Results: Obesity metrics were associated with the expression of 21 AD-related genes. The strongest associations were observed with CLU, CD2AP, KLC3, and FCER1G. Unique associations were noted with TSPAN14, SLC24A4 for BMI, and ZSCAN21, BCKDK for WHR. After adjustment for cardiovascular risk factors, 13 associations remained significant for BMI and 8 for WHR. Dichotomous obesity metrics exhibited unique associations with EPHX2 for BMI, and with TSPAN14 for WHR. Discussion: Obesity was associated with AD-related gene expression; these findings shed light on the molecular pathways linking obesity to AD.
MeSH term(s)	Humans ; Risk Factors ; Genome-Wide Association Study ; Alzheimer Disease/genetics ; Alzheimer Disease/complications ; Obesity/genetics ; Obesity/complications ; Body Mass Index ; Longitudinal Studies
Language	English
Publishing date	2023-02-22
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, N.I.H., Intramural ; Research Support, Non-U.S. Gov't
ZDB-ID	2211627-8
ISSN	1552-5279 ; 1552-5260
ISSN (online)	1552-5279
ISSN	1552-5260
DOI	10.1002/alz.12954
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Article ; Online: Microarray data analysis of gene expression evolution.

Lin, Honghuang

Gene regulation and systems biology

2009 Volume 3, Page(s) 211–214

Abstract: Microarrays are becoming a widely used tool to study gene expression evolution. A recent paper by Wang and Rekaya describes a comprehensive study of gene expression evolution by microarray. The work provides a perspective to study gene expression ... ...

Abstract	Microarrays are becoming a widely used tool to study gene expression evolution. A recent paper by Wang and Rekaya describes a comprehensive study of gene expression evolution by microarray. The work provides a perspective to study gene expression evolution in terms of functional enrichment and promoter conservation. It was found that gene expression patterns are highly conserved in some biological processes, but the correlation between promoter and gene expression is insignificant. This scope of this work and future improvement to study gene expression evolution will be discussed in this article.
Language	English
Publishing date	2009-11-27
Publishing country	United States
Document type	Journal Article
ISSN	1177-6250
ISSN (online)	1177-6250
DOI	10.4137/grsb.s2997
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Article ; Online: Tissue-specific Network Analysis of Genetic Variants Associated with Coronary Artery Disease.

Miao, Xiao / Chen, Xinlin / Xie, Zhijun / Lin, Honghuang

Scientific reports

2018 Volume 8, Issue 1, Page(s) 11492

Abstract: Coronary artery disease (CAD) is a leading cause of death worldwide. Recent genome-wide association studies have identified more than one hundred susceptibility loci associated with CAD. However, the underlying mechanism of these genetic loci to CAD ... ...

Abstract	Coronary artery disease (CAD) is a leading cause of death worldwide. Recent genome-wide association studies have identified more than one hundred susceptibility loci associated with CAD. However, the underlying mechanism of these genetic loci to CAD susceptibility is still largely unknown. We performed a tissue-specific network analysis of CAD using the summary statistics from one of the largest genome-wide association studies. Variant-level associations were summarized into gene-level associations, and a CAD-related interaction network was built using experimentally validated gene interactions and gene coexpression in coronary artery. The network contained 102 genes, of which 53 were significantly associated with CAD. Pathway enrichment analysis revealed that many genes in the network were involved in the regulation of peripheral arteries. In summary, we performed a tissue-specific network analysis and found abnormalities in the peripheral arteries might be an important pathway underlying the pathogenesis of CAD. Future functional characterization might further validate our findings and identify potential therapeutic targets for CAD.
MeSH term(s)	Coronary Artery Disease/genetics ; Gene Regulatory Networks/genetics ; Genetic Loci/genetics ; Genetic Predisposition to Disease/genetics ; Genome-Wide Association Study/methods ; Humans ; Polymorphism, Single Nucleotide/genetics
Language	English
Publishing date	2018-07-31
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-018-29904-7
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Article: Integrative methylation score to identify epigenetic modifications associated with lipid changes resulting from fenofibrate treatment in families.

Wang, Biqi / DeStefano, Anita L / Lin, Honghuang

BMC proceedings

2018 Volume 12, Issue Suppl 9, Page(s) 28

Abstract: Epigenome-wide association studies (EWAS) have traditionally focused on the association test of single epigenetic markers with complex traits. However, it is possible that multiple cytosine-phosphate-guanine (CpG) sites at the same locus could jointly ... ...

Abstract	Epigenome-wide association studies (EWAS) have traditionally focused on the association test of single epigenetic markers with complex traits. However, it is possible that multiple cytosine-phosphate-guanine (CpG) sites at the same locus could jointly exert their effects on human traits. Therefore, a region-based test that combines multiple markers could be more powerful. We used 2 different region-based tests to investigate the association between changes in DNA methylation and drug response, including the median methylation level test (MMLT) and sequence kernel association test (SKAT). No genes were found to be significantly associated with the drug response (for triglycerides, the false discovery rate ranged from 0.855 to 0.999; for high-density lipoprotein cholesterol, and the false discovery rate ranged from 0.584 to 0.915). Further evidence is needed to explore potential application of gene-level methylation association analysis.
Language	English
Publishing date	2018-09-17
Publishing country	England
Document type	Journal Article
ZDB-ID	2411867-9
ISSN	1753-6561
ISSN	1753-6561
DOI	10.1186/s12919-018-0125-x
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