4.7 Article

Genetic risk assessment based on association and prediction studies

Related references

Note: Only part of the references are listed.
Article Biochemical Research Methods

Hypertension Risk Prediction Based on SNPs by Machine Learning Models

S. Ali Lajevardi et al.

Summary: This study used various machine learning methods to predict the risk of hypertension by analyzing genetic markers. The final results indicate that machine learning approaches can successfully predict the risk of hypertension at a young age and identify significant SNPs that affect hypertension.

CURRENT BIOINFORMATICS (2023)

Review Biochemical Research Methods

Dealing with dimensionality: the application of machine learning to multi-omics data

Dylan Feldner-Busztin et al.

Summary: Motivated by the need to automate information extraction from large datasets, machine learning methods are employed for integrative joint analysis of diverse omics data. A systematic assessment of the literature reveals the widespread use of dimensionality reduction methods and models that can handle datasets with limited samples. The Cancer Genome Atlas dataset has a significant impact on the field.

BIOINFORMATICS (2023)

Review Medicine, General & Internal

Hepatocellular Carcinoma in Hepatitis B Virus-Infected Patients and the Role of Hepatitis B Surface Antigen (HBsAg)

Satinder P. Kaur et al.

Summary: Hepatitis B virus (HBV) infection is one of the main risk factors for hepatocellular carcinoma (HCC), and the risk of HCC is not completely eliminated even after viral suppression. Cirrhosis, HBV viral DNA levels, age, male gender, the immune response, and a combination of obesity and diabetes are among the main risk factors for HCC. Active viral replication and long-standing inflammation are associated with a higher risk of HCC. Treatment of HBV with nucleos(t)ide analogues can decrease the risk of HCC.

JOURNAL OF CLINICAL MEDICINE (2022)

Article Multidisciplinary Sciences

A machine learning-based SNP-set analysis approach for identifying disease-associated susceptibility loci

Princess P. Silva et al.

Summary: Identifying disease-associated susceptibility loci is a pressing and crucial challenge in modeling complex diseases. This study proposed an integrated framework combining random forest and cluster analysis to discover disease-associated susceptibility loci. By applying this framework to hepatitis B virus surface antigen (HBsAg) seroclearance GWAS data, three susceptibility loci possibly associated with HBsAg seroclearance were identified. These findings have the potential to advance our understanding of complex disease etiologies and improve disease risk assessment for patients.

SCIENTIFIC REPORTS (2022)

Article Cardiac & Cardiovascular Systems

Genome-wide association study on coronary artery disease in type 1 diabetes Suggests beta-dufensin 127 as a risk locus

Anni A. Antikainen et al.

Summary: This study aimed to identify genetic loci increasing coronary artery disease (CAD) susceptibility in individuals with type 1 diabetes (T1D). Two loci, CDKN2B-AS1 and DEFB127, were found to be significantly associated with CAD in T1D individuals. Additionally, the study explored the function of other genetic loci and found that general population risk variants were modestly but significantly associated with CAD in T1D.

CARDIOVASCULAR RESEARCH (2021)

Article Multidisciplinary Sciences

Investigating the relationship between the SNCA gene and cognitive abilities in idiopathic Parkinson's disease using machine learning

Mehrafarin Ramezani et al.

Summary: By using machine learning techniques, this study identified the association between demographics, genetic variants and brain structures with global cognition in Parkinson's disease patients. A specific genetic variant in the SNCA gene was found to be significantly associated with global cognition, attention and visuospatial abilities in PD patients.

SCIENTIFIC REPORTS (2021)

Article Genetics & Heredity

PIP-SNP: a pipeline for processing SNP data featured as linkage disequilibrium bin mapping, genotype imputing and marker synthesizing

Wenchao Zhang et al.

Summary: This study tackles the challenges of high dimensionality of SNP genotypes and missing value imputation in genome-wide association studies. It utilizes a stochastic process to describe SNP signals, calculates autocorrelation coefficients to construct LD bins, and employs a k-nearest neighbors algorithm for genotype imputation. Novel methods for finding synthetic markers and evaluating information loss or conservation are proposed, resulting in satisfactory performance on real-life SNP data.

NAR GENOMICS AND BIOINFORMATICS (2021)

Article Genetics & Heredity

Revisiting the genome-wide significance threshold for common variant GWAS

Zhongsheng Chen et al.

Summary: This study reassessed the genome-wide significance threshold in GWAS by comparing different multiple testing strategies. The findings suggest that relaxing the P-value threshold can increase discovery rates but also lead to higher false positive rates. FDR and Bayesian FDR are shown to be well controlled for different sample sizes in this context.

G3-GENES GENOMES GENETICS (2021)

Review Endocrinology & Metabolism

Association is not prediction: A landscape of confused reporting in diabetes - A systematic review

Tibor V. Varga et al.

DIABETES RESEARCH AND CLINICAL PRACTICE (2020)

Article Biotechnology & Applied Microbiology

Prediction Model of HBsAg Seroclearance in Patients with Chronic HBV Infection

Jing Cao et al.

BIOMED RESEARCH INTERNATIONAL (2020)

Review Genetics & Heredity

Machine Learning SNP Based Prediction for Precision Medicine

Daniel Sik Wai Ho et al.

FRONTIERS IN GENETICS (2019)

Review Genetics & Heredity

Benefits and limitations of genome-wide association studies

Vivian Tam et al.

NATURE REVIEWS GENETICS (2019)

Article Multidisciplinary Sciences

Machine learning approach to single nucleotide polymorphism-based asthma prediction

Joverlyn Gaudillo et al.

PLOS ONE (2019)

Article Gastroenterology & Hepatology

Effects of Diabetes and Glycemic Control on Risk of Hepatocellular Carcinoma After Seroclearance of Hepatitis B Surface Antigen

Terry Cheuk-Fung Yip et al.

CLINICAL GASTROENTEROLOGY AND HEPATOLOGY (2018)

Editorial Material Biochemical Research Methods

The curse(s) of dimensionality

Naomi Altman et al.

NATURE METHODS (2018)

Article Gastroenterology & Hepatology

Impact of age and gender on risk of hepatocellular carcinoma after hepatitis B surface antigen seroclearance

Terry Cheuk-Fung Yip et al.

JOURNAL OF HEPATOLOGY (2017)

Article Multidisciplinary Sciences

Association analysis identifies 65 new breast cancer risk loci

Kyriaki Michailidou et al.

NATURE (2017)

Article Genetics & Heredity

The Human Microbiome and the Missing Heritability Problem

Santiago Sandoval-Motta et al.

Frontiers in Genetics (2017)

Article Public, Environmental & Occupational Health

Current Challenges and New Opportunities for Gene-Environment Interaction Studies of Complex Diseases

Kimberly McAllister et al.

AMERICAN JOURNAL OF EPIDEMIOLOGY (2017)

Article Cell Biology

Genomic risk prediction of complex human disease and its clinical application

Gad Abraham et al.

CURRENT OPINION IN GENETICS & DEVELOPMENT (2015)

Proceedings Paper Computer Science, Theory & Methods

A classification algorithm for high-dimensional data

Asim Roy

INNS CONFERENCE ON BIG DATA 2015 PROGRAM (2015)

Review Ophthalmology

Understanding and checking the assumptions of linear regression: a primer for medical researchers

Robert J. Casson et al.

CLINICAL AND EXPERIMENTAL OPHTHALMOLOGY (2014)

Review Genetics & Heredity

Systems genetics approaches to understand complex traits

Mete Civelek et al.

NATURE REVIEWS GENETICS (2014)

Article Multidisciplinary Sciences

Exploiting SNP Correlations within Random Forest for Genome-Wide Association Studies

Vincent Botta et al.

PLOS ONE (2014)

Article History & Philosophy Of Science

GENES AND NON-MENDELIAN DISEASES dealing with complexity

Bertrand Jordan

PERSPECTIVES IN BIOLOGY AND MEDICINE (2014)

Article Biochemical Research Methods

Breast cancer prediction using genome wide single nucleotide polymorphism data

Mohsen Hajiloo et al.

BMC BIOINFORMATICS (2013)

Article Biochemistry & Molecular Biology

Linking disease associations with regulatory information in the human genome

Marc A. Schaub et al.

GENOME RESEARCH (2012)

Review Biotechnology & Applied Microbiology

Random forests for genomic data analysis

Xi Chen et al.

GENOMICS (2012)

Article Biochemistry & Molecular Biology

A systematic characterization of genes underlying both complex and Mendelian diseases

Wenfei Jin et al.

HUMAN MOLECULAR GENETICS (2012)

Review Biotechnology & Applied Microbiology

What is complex about complex disorders?

Kevin J. Mitchell

GENOME BIOLOGY (2012)

Review Biochemistry & Molecular Biology

A Polygenic Approach to the Study of Polygenic Diseases

D. Lvovs et al.

ACTA NATURAE (2012)

Article Gastroenterology & Hepatology

HBsAg Seroclearance in Chronic Hepatitis B Implications for Hepatocellular Carcinoma

Ji Hoon Kim et al.

JOURNAL OF CLINICAL GASTROENTEROLOGY (2011)

Article Genetics & Heredity

Risk Prediction Using Genome-Wide Association Studies

Charles Kooperberg et al.

GENETIC EPIDEMIOLOGY (2010)

Review Genetics & Heredity

VIEWPOINT Missing heritability and strategies for finding the underlying causes of complex disease

Evan E. Eichler et al.

NATURE REVIEWS GENETICS (2010)

Review Multidisciplinary Sciences

Finding the missing heritability of complex diseases

Teri A. Manolio et al.

NATURE (2009)