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Статті в журналах з теми "Genetic risk of disease"

Автор: Grafiati

Опубліковано: 11 березня 2023

Оновлено: 31 липня 2025

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1

Sawikr, Yousef, Khlid G. ALqathafy, and Ibrahim S. Ibrahem. "Biochemical Markers and Genetic Risk Factors in Alzheimer's Disease." International Journal of Research Publication and Reviews 4, no. 12 (2023): 890–93. http://dx.doi.org/10.55248/gengpi.4.1223.123328.

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2

Roberts, Robert. "Molecular genetics: Cardiac disease and risk-related genes-Genetic risk factors." Clinical Cardiology 18, S4 (1995): IV13—IV19. http://dx.doi.org/10.1002/clc.4960181604.

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3

Alonso, Lorena, Ignasi Morán, Cecilia Salvoro, and David Torrents. "In Search of Complex Disease Risk through Genome Wide Association Studies." Mathematics 9, no. 23 (2021): 3083. http://dx.doi.org/10.3390/math9233083.

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The identification and characterisation of genomic changes (variants) that can lead to human diseases is one of the central aims of biomedical research. The generation of catalogues of genetic variants that have an impact on specific diseases is the basis of Personalised Medicine, where diagnoses and treatment protocols are selected according to each patient’s profile. In this context, the study of complex diseases, such as Type 2 diabetes or cardiovascular alterations, is fundamental. However, these diseases result from the combination of multiple genetic and environmental factors, which make

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4

Bloch, Michael J. "Genetic risk scores and coronary heart disease risk." Journal of the American Society of Hypertension 9, no. 8 (2015): 580–81. http://dx.doi.org/10.1016/j.jash.2015.06.010.

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5

Bin, Paola, Emanuele Capasso, Mariano Paternoster, et al. "Genetic risk in insurance field." Open Medicine 13, no. 1 (2018): 294–97. http://dx.doi.org/10.1515/med-2018-0045.

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AbstractThe risk-delimiting tools available to insurance companies are therefore substantial and it is also possible to argue that a margin of uncertainty is a natural component of the insurance contract.Despite this, businesses look at the potential of predictive medicine, and in particular the growing understanding of genetic mechanisms that support many common diseases.In particular, the rapid development of genetics has led many insurance companies to glimpse in the predictive diagnosis of disease by genetic testing the possibility of extending the calculation of the individual risk of dev

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6

Akushevich, Igor, Arseniy Yashkin, Julia Kravchenko, Svetlana Ukraintseva, and Anatoliy Yashin. "EFFECTS OF MEDICARE COMORBIDITIES, SELF-REPORTED FACTORS, AND POLYGENIC RISK SCORES IN RISKS OF AD/ADRD." Innovation in Aging 3, Supplement_1 (2019): S484. http://dx.doi.org/10.1093/geroni/igz038.1798.

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Abstract At this time there is no consensus on the origin, development, and progression of Alzheimer’s Disease and related dementias (AD/ADRD) and the extent to which variation in the effects of potential risk factors affects the risk for this disorder is underexplored. In this paper we used HRS-Medicare-genetics data to evaluate the effects of risk factors from three groups: i) Medicare-based indicators of chronic diseases that have shown an association with AD/ADRD in the literature, ii) individual heath state, behavior, functional status, education and socioeconomic status, and iii) polygen

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7

McDonald, B. A., and C. Linde. "Disease resistance and pathogen population genetic." Plant Protection Science 38, SI 1 - 6th Conf EFPP 2002 (2002): 245–48. http://dx.doi.org/10.17221/10375-pps.

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Plant pathologists have seen many boom-and-bust cycles following the deployment of resistant varieties. These cycles result when pathogen populations adapt to the presence of a major resistance gene by evolving a new population that can overcome this resistance gene. The breakdown of genetic resistance is due to the evolution of the local pathogen population because of selection for mutants, recombinants, or immigrants that are better adapted to the resistant cultivar. To understand the process that leads to breakdown of a resistance gene, we need to understand the processes that govern pathog

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8

ÇAKIRGÖZ, Onur, and Süleyman SEVİNÇ. "A Dynamic Method and Program for Disease-Based Genetic Classification of Individuals." Journal of Emerging Computer Technologies 3, no. 1 (2024): 12–20. http://dx.doi.org/10.57020/ject.1375605.

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Personalized medicine is gaining increasing importance. However, genetic-based diseases have different underlying genetic factors, requiring separate relative risk models for each disease. In addition to these difficulties, comparing individuals according to their genetic characteristics and determining a personalized treatment method based on this, is a separate problem which is very difficult to do manually. In this study, a dynamic classification method and program is proposed for disease-based classification of individuals according to their genetic characteristics. To the best of our know

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9

Lombardi, Rosa, Federica Iuculano, Giada Pallini, Silvia Fargion, and Anna Ludovica Fracanzani. "Nutrients, Genetic Factors, and Their Interaction in Non-Alcoholic Fatty Liver Disease and Cardiovascular Disease." International Journal of Molecular Sciences 21, no. 22 (2020): 8761. http://dx.doi.org/10.3390/ijms21228761.

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Non-alcoholic fatty liver disease (NAFLD) is the most common chronic liver disease in Western countries and expose patients to increased risk of hepatic and cardiovascular (CV) morbidity and mortality. Both environmental factors and genetic predisposition contribute to the risk. An inappropriate diet, rich in refined carbohydrates, especially fructose, and saturated fats, and poor in fibers, polyunsaturated fats, and vitamins is one of the main key factors, as well as the polymorphism of patatin-like phospholipase domain containing 3 (PNPLA3 gene) for NAFLD and the apolipoproteins and the pero

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10

Liddell, M. B., S. Lovestone, and M. J. Owen. "Genetic risk of Alzheimer's disease: advising relatives." British Journal of Psychiatry 178, no. 1 (2001): 7–11. http://dx.doi.org/10.1192/bjp.178.1.7.

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BackgroundClinicians are increasingly asked by relatives of patients with Alzheimer's disease to advise on their genetic risk of developing Alzheimer's disease in later life. Many clinicians find this a difficult question to answer.AimsTo provide information for old age psychiatrists wishing to advise relatives of their risk of developing Alzheimer's disease.MethodA selective review of the key literature on the genetic epidemiology of Alzheimer's disease.ResultsCurrently a DNA diagnosis is attainable in some 70% of families with autosomal dominant Alzheimer's disease. In first-degree relatives

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11

Skrzypa, Marzena, Natalia Potocka, Halina Bartosik-Psujek, and Izabela Zawlik. "Genetic risk factors of Alzheimer’s disease." European Journal of Clinical and Experimental Medicine 17, no. 1 (2019): 57–66. http://dx.doi.org/10.15584/ejcem.2019.1.10.

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12

Jostins, Luke, and Jeffrey C. Barrett. "Genetic risk prediction in complex disease." Human Molecular Genetics 20, R2 (2011): R182—R188. http://dx.doi.org/10.1093/hmg/ddr378.

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13

Secko, D. "Alzheimer's disease: genetic variables and risk." Canadian Medical Association Journal 172, no. 5 (2005): 627. http://dx.doi.org/10.1503/cmaj.050111.

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14

Billingsley, K. J., S. Bandres-Ciga, S. Saez-Atienzar, and A. B. Singleton. "Genetic risk factors in Parkinson’s disease." Cell and Tissue Research 373, no. 1 (2018): 9–20. http://dx.doi.org/10.1007/s00441-018-2817-y.

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15

Alliey, Ney. "Genetic Variants And Risk Of Disease." European Neuropsychopharmacology 29 (2019): S715—S716. http://dx.doi.org/10.1016/j.euroneuro.2017.06.025.

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16

Bradshaw, Elizabeth. "CD33 GENETIC RISK IN ALZHEIMER'S DISEASE." Alzheimer's & Dementia 13, no. 7 (2017): P1448. http://dx.doi.org/10.1016/j.jalz.2017.07.488.

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17

Tilley, L., K. Morgan, and N. Kalsheker. "Genetic risk factors in Alzheimer's disease." Molecular Pathology 51, no. 6 (1998): 293–304. http://dx.doi.org/10.1136/mp.51.6.293.

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18

Sharabitdinova, Gulshad Gafurkhanovna. "GENETIC RISK FACTORS FOR CARDIOVASCULAR DISEASE." Theoretical & Applied Science 59, no. 03 (2018): 240–43. http://dx.doi.org/10.15863/tas.2018.03.59.41.

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19

Pimenova, Anna A., Towfique Raj, and Alison M. Goate. "Untangling Genetic Risk for Alzheimer’s Disease." Biological Psychiatry 83, no. 4 (2018): 300–310. http://dx.doi.org/10.1016/j.biopsych.2017.05.014.

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20

Wood, Nicholas W. "Genetic risk factors in parkinson's disease." Annals of Neurology 44, S1 (1998): S58—S62. http://dx.doi.org/10.1002/ana.410440709.

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21

Jabloner, Anna. "Relative Risk." Social Analysis 65, no. 4 (2021): 111–30. http://dx.doi.org/10.3167/sa.2021.650406.

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Genetic counselors in the US assess disease risks by drawing on family histories, genetic tests, and patients’ racial, ethnic, national, or religious self-identifications. The bodily risks of kinship articulated by family histories can be defused by genetic tests that highlight the contingency of biological inheritance and decouple kinship from genetics. However, such tests, as well as self-identifying patients, also entwine genetic risk with older indicators of kinship: biologically understood race and ethnicity. Across these scales, counselors calculate relative risks to the future health of

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22

Pekmezović, Tatjana. "Gene-Environment Interaction: A Genetic-Epidemiological Approach." Journal of Medical Biochemistry 29, no. 3 (2010): 131–34. http://dx.doi.org/10.2478/v10011-010-0021-z.

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Gene-Environment Interaction: A Genetic-Epidemiological ApproachClassical epidemiology addresses the distribution and determinants of diseases in populations, and the factors associated with disease causation, with the aim of preventing disease. Both genetic and environmental factors may contribute to susceptibility, and it is still unclear how these factors interact in their influence on risk. Genetic epidemiology is the field which incorporates concepts and methods from different disciplines including epidemiology, genetics, biostatistics, clinical and molecular medicine, and their interacti

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23

Knowles, Joshua W., and Euan A. Ashley. "Cardiovascular disease: The rise of the genetic risk score." PLOS Medicine 15, no. 3 (2018): e1002546. http://dx.doi.org/10.1371/journal.pmed.1002546.

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24

Vaskimo, Lotta M., Georgy Gomon, Najib Naamane, Heather J. Cordell, Arthur Pratt, and Rachel Knevel. "The Application of Genetic Risk Scores in Rheumatic Diseases: A Perspective." Genes 14, no. 12 (2023): 2167. http://dx.doi.org/10.3390/genes14122167.

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Modest effect sizes have limited the clinical applicability of genetic associations with rheumatic diseases. Genetic risk scores (GRSs) have emerged as a promising solution to translate genetics into useful tools. In this review, we provide an overview of the recent literature on GRSs in rheumatic diseases. We describe six categories for which GRSs are used: (a) disease (outcome) prediction, (b) genetic commonalities between diseases, (c) disease differentiation, (d) interplay between genetics and environmental factors, (e) heritability and transferability, and (f) detecting causal relationshi

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25

Asatryan, Babken, and Argelia Medeiros-Domingo. "Molecular and genetic insights into progressive cardiac conduction disease." EP Europace 21, no. 8 (2019): 1145–58. http://dx.doi.org/10.1093/europace/euz109.

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Abstract Progressive cardiac conduction disease (PCCD) is often a primarily genetic disorder, with clinical and genetic overlaps with other inherited cardiac and metabolic diseases. A number of genes have been implicated in PCCD pathogenesis with or without structural heart disease or systemic manifestations. Precise genetic diagnosis contributes to risk stratification, better selection of specific therapy and allows familiar cascade screening. Cardiologists should be aware of the different phenotypes emerging from different gene-mutations and the potential risk of sudden cardiac death. Geneti

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26

Ashraf, Tariq, Taseer Ahmed, Mehir-un-Nisa Iqbal, and Asif Nadeem. "Genetics and Ischemic Heart Disease: Should We Opt for Genetic Testing for Primary Prevention?" Pakistan Heart Journal 56, no. 3 (2023): 193–94. http://dx.doi.org/10.47144/phj.v56i3.2642.

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Cardiovascular diseases (CVD) are a prevalent health concern within the general population of Pakistan, where the average lifespan is notably lower than the global average, with men typically living to 67 years and women to 69 years. According to the 2019 Global Burden of Disease study, Pakistan had an estimated age-standardized incidence rate of CVD at 918.18 per 100,000 (compared to the global rate of 684.33 per 100,000), along with an age-standardized death rate of 357.88 per 100,000 (globally, this rate is 239.85 per 100,000).1 Coronary heart disease (CHD), as revealed by the Framingham He

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27

Nuha Majeed Farhan, Lubab Mohammed Awad, and Intisar Masier Abd. "The Role of Genetics in Neurological Disorders: From Rare Diseases to Common Conditions." Academic International Journal of Medical Update 2, no. 2 (2024): 35–43. http://dx.doi.org/10.59675/u226.

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Neurological disorders result from neurological diseases affecting the brain, spinal cord and peripheral nerves and include rare genetic diseases like Huntington’s disease and spinal muscular atrophy, as well as common diseases such as Alzheimer’s, Parkinson’s disease and epilepsy. These conditions are strongly influenced by genetics, and genetics contribute to the onset, the progression of the disease, the severity of symptoms and treatment responsiveness. Genetics is relevant not only to inheritance, but also to de novo mutations, polygenic risk factors and gene environment interactions that

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28

Zeng, Lingyao, Ioanna Ntalla, Thorsten Kessler, et al. "Genetically modulated educational attainment and coronary disease risk." European Heart Journal 40, no. 29 (2019): 2413–20. http://dx.doi.org/10.1093/eurheartj/ehz328.

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Abstract Aims Genetic disposition and lifestyle factors are understood as independent components underlying the risk of multiple diseases. In this study, we aim to investigate the interplay between genetics, educational attainment—an important denominator of lifestyle—and coronary artery disease (CAD) risk. Methods and results Based on the effect sizes of 74 genetic variants associated with educational attainment, we calculated a ‘genetic education score’ in 13 080 cases and 14 471 controls and observed an inverse correlation between the score and risk of CAD [P = 1.52 × 10−8; odds ratio (OR)

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29

Curtis, Catherine L., Allon Goldberg, Jeffrey A. Kleim, and Steven L. Wolf. "Translating Genomic Advances to Physical Therapist Practice: A Closer Look at the Nature and Nurture of Common Diseases." Physical Therapy 96, no. 4 (2016): 570–80. http://dx.doi.org/10.2522/ptj.20150112.

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The Human Genome Project and the International HapMap Project have yielded new understanding of the influence of the human genome on health and disease, advancing health care in significant ways. In personalized medicine, genetic factors are used to identify disease risk and tailor preventive and therapeutic regimens. Insight into the genetic bases of cellular processes is revealing the causes of disease and effects of exercise. Many diseases known to have a major lifestyle contribution are highly influenced by common genetic variants. Genetic variants are associated with increased risk for co

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30

Leonenko, Ganna, Maryam Shoai, Eftychia Bellou, et al. "Genetic risk for alzheimer disease is distinct from genetic risk for amyloid deposition." Annals of Neurology 86, no. 3 (2019): 427–35. http://dx.doi.org/10.1002/ana.25530.

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31

Abraham, Gad, Loes Rutten-Jacobs, and Michael Inouye. "Risk Prediction Using Polygenic Risk Scores for Prevention of Stroke and Other Cardiovascular Diseases." Stroke 52, no. 9 (2021): 2983–91. http://dx.doi.org/10.1161/strokeaha.120.032619.

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Early prediction of risk of cardiovascular disease (CVD), including stroke, is a cornerstone of disease prevention. Clinical risk scores have been widely used for predicting CVD risk from known risk factors. Most CVDs have a substantial genetic component, which also has been confirmed for stroke in recent gene discovery efforts. However, the role of genetics in prediction of risk of CVD, including stroke, has been limited to testing for highly penetrant monogenic disorders. In contrast, the importance of polygenic variation, the aggregated effect of many common genetic variants across the geno

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32

Pfeffer, Tobias J., Stefan Pietzsch, and Denise Hilfiker-Kleiner. "Common genetic predisposition for heart failure and cancer." Herz 45, no. 7 (2020): 632–36. http://dx.doi.org/10.1007/s00059-020-04953-9.

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Abstract Cardiovascular diseases and cancer are major causes of mortality in industrialized societies. They share common risk factors (e.g., genetics, lifestyle, age, infection, toxins, and pollution) and might also mutually promote the onset of the respective other disease. Cancer can affect cardiac function directly while antitumor therapies may have acute- and/or late-onset cardiotoxic effects. Recent studies suggest that heart failure might promote tumorigenesis and tumor progression. In both cancer and cardiovascular diseases, genetic predisposition is implicated in the disease onset and

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33

O’Connor, David, Amir Enshaei, Jack Bartram, et al. "Genotype-Specific Minimal Residual Disease Interpretation Improves Stratification in Pediatric Acute Lymphoblastic Leukemia." Journal of Clinical Oncology 36, no. 1 (2018): 34–43. http://dx.doi.org/10.1200/jco.2017.74.0449.

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Purpose Minimal residual disease (MRD) and genetic abnormalities are important risk factors for outcome in acute lymphoblastic leukemia. Current risk algorithms dichotomize MRD data and do not assimilate genetics when assigning MRD risk, which reduces predictive accuracy. The aim of our study was to exploit the full power of MRD by examining it as a continuous variable and to integrate it with genetics. Patients and Methods We used a population-based cohort of 3,113 patients who were treated in UKALL2003, with a median follow-up of 7 years. MRD was evaluated by polymerase chain reaction analys

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34

Hall, Ashley, Sara Bandres-Ciga, Monica Diez-Fairen, John P. Quinn, and Kimberley J. Billingsley. "Genetic Risk Profiling in Parkinson’s Disease and Utilizing Genetics to Gain Insight into Disease-Related Biological Pathways." International Journal of Molecular Sciences 21, no. 19 (2020): 7332. http://dx.doi.org/10.3390/ijms21197332.

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Parkinson’s disease (PD) is a complex disorder underpinned by both environmental and genetic factors. The latter only began to be understood around two decades ago, but since then great inroads have rapidly been made into deconvoluting the genetic component of PD. In particular, recent large-scale projects such as genome-wide association (GWA) studies have provided insight into the genetic risk factors associated with genetically ‘’complex’’ PD (PD that cannot readily be attributed to single deleterious mutations). Here, we discuss the plethora of genetic information provided by PD GWA studies

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35

McHugh, Jessica. "Shared genetic risk for Behçet disease and Crohn's disease." Nature Reviews Rheumatology 13, no. 4 (2017): 197. http://dx.doi.org/10.1038/nrrheum.2017.30.

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36

Logue, Mark W., Shoumita Dasgupta, and Lindsay A. Farrer. "Genetics of Alzheimer’s Disease in the African American Population." Journal of Clinical Medicine 12, no. 16 (2023): 5189. http://dx.doi.org/10.3390/jcm12165189.

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Black/African American (AA) individuals have a higher risk of Alzheimer’s disease (AD) than White non-Hispanic persons of European ancestry (EUR) for reasons that may include economic disparities, cardiovascular health, quality of education, and biases in the methods used to diagnose AD. AD is also heritable, and some of the differences in risk may be due to genetics. Many AD-associated variants have been identified by candidate gene studies, genome-wide association studies (GWAS), and genome-sequencing studies. However, most of these studies have been performed using EUR cohorts. In this pape

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37

Yun, Jae-Seung. "Polygenic risk score: a useful clinical instrument for disease prediction and risk categorization." Cardiovascular Prevention and Pharmacotherapy 4, no. 1 (2022): 13–17. http://dx.doi.org/10.36011/cpp.2022.4.e7.

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Genetic information is one of the essential components of precision medicine. Over the past decade, substantial progress has been made, such as low-cost, high-throughput genotyping arrays, advances in statistical techniques, and progressively larger discovery datasets, enabling the discovery of alleles contributing to common diseases, such as coronary artery disease and type 2 diabetes. The polygenic risk score (PRS) represents the aggregate contribution of numerous common genetic variants, individually conferring small to moderate effects, and can be used as a marker of genetic risk for major

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38

Wachirawit, Angkatavanich. "Genetic Risks of Cardiovascular Diseases." International Journal of Healthcare Sciences 10, no. 1 (2022): 161–67. https://doi.org/10.5281/zenodo.6890951.

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<strong>Abstract:</strong> Coronary Heart Disease (CHD) is the number one cause of death in the current world. Since numerous reasons heighten the risk of CHD, this review will focus only on genetic risk factors. Known for its ability to analyze and enhance chromosome mapping by garnering tons of human tests by its agnostic approach, conducting Genome-Wide Association Studies (GWAS) to examine genetic patterns in patients has perceived many undiscovered hidden genes. For instance, Sortilin is a gene vitally linked to cardiovascular diseases (CVD) risks and plasma LDL cholesterol levels. Moreov

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39

Blauwendraat, Cornelis, Xylena Reed, Lynne Krohn, et al. "Genetic modifiers of risk and age at onset in GBA associated Parkinson’s disease and Lewy body dementia." Brain 143, no. 1 (2019): 234–48. http://dx.doi.org/10.1093/brain/awz350.

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Abstract Parkinson’s disease is a genetically complex disorder. Multiple genes have been shown to contribute to the risk of Parkinson’s disease, and currently 90 independent risk variants have been identified by genome-wide association studies. Thus far, a number of genes (including SNCA, LRRK2, and GBA) have been shown to contain variability across a spectrum of frequency and effect, from rare, highly penetrant variants to common risk alleles with small effect sizes. Variants in GBA, encoding the enzyme glucocerebrosidase, are associated with Lewy body diseases such as Parkinson’s disease and

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40

Treff, Nathan R., Diego Marin, Louis Lello, Stephen Hsu, and Laurent C. A. M. Tellier. "PREIMPLANTATION GENETIC TESTING: Preimplantation genetic testing for polygenic disease risk." Reproduction 160, no. 5 (2020): A13—A17. http://dx.doi.org/10.1530/rep-20-0071.

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Since its introduction to clinical practice, preimplantation genetic testing (PGT) has become a standard of care for couples at risk of having children with monogenic disease and for chromosomal aneuploidy to improve outcomes for patients with infertility. The primary objective of PGT is to reduce the risk of miscarriage and genetic disease and to improve the success of infertility treatment with the delivery of a healthy child. Until recently, the application of PGT to more common but complex polygenic disease was not possible, as the genetic contribution to polygenic disease has been difficu

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41

Celeghin, Rudy, Gaetano Thiene, Barbara Bauce, Cristina Basso, and Kalliopi Pilichou. "Genetics in cardiovascular diseases." Italian Journal of Medicine 13, no. 3 (2019): 137–51. http://dx.doi.org/10.4081/itjm.2019.1186.

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Cardiovascular diseases (CVDs) are a wide group of disorders affecting the heart and blood vessels, including coronary artery, valve, pericardial, conduction system, myocardial and vascular diseases, either congenital or acquired, which can be also heritable. The advent of next generation sequencing (NGS) was accompanied by quick advances in understanding the genetic basis of human diseases, prompting translation of genetics to the clinic. Precision medicine is based on these findings and on the role of genetic testing to improve the diagnosis, to identify individuals with previously unrecogni

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Semaev, Sergey, and Elena Shakhtshneider. "Genetic Risk Score for Coronary Heart Disease: Review." Journal of Personalized Medicine 10, no. 4 (2020): 239. http://dx.doi.org/10.3390/jpm10040239.

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The present review deals with the stages of creation, methods of calculation, and the use of a genetic risk score for coronary heart disease in various populations. The concept of risk factors is generally recognized on the basis of the results of epidemiological studies in the 20th century; according to this concept, the high prevalence of diseases of the circulatory system is due to lifestyle characteristics and associated risk factors. An important and relevant task for the healthcare system is to identify the population segments most susceptible to cardiovascular diseases (CVDs). The level

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43

MURATA, Mitsuru, Koichi KAWANO, Yumiko MATSUBARA, et al. "Genetic risk factors for coronary artery disease." Journal of Japan Atherosclerosis Society 26, no. 1 (1998): 9–15. http://dx.doi.org/10.5551/jat1973.26.1_9.

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44

Sato, Naoyuki. "Alzheimer disease and non-genetic risk factors." Nippon Ronen Igakkai Zasshi. Japanese Journal of Geriatrics 49, no. 3 (2012): 311–13. http://dx.doi.org/10.3143/geriatrics.49.311.

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45

Lim, Gregory B. "Fitness ameliorates genetic risk of heart disease." Nature Reviews Cardiology 15, no. 7 (2018): 380. http://dx.doi.org/10.1038/s41569-018-0019-7.

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46

Araújo, F., A. Santos, V. Araújo, et al. "Genetic Risk Factors in Acute Coronary Disease." Pathophysiology of Haemostasis and Thrombosis 29, no. 4 (1999): 212–18. http://dx.doi.org/10.1159/000022504.

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47

Iwaki, Hirotaka, Cornelis Blauwendraat, Hampton L. Leonard, et al. "Genetic risk of Parkinson disease and progression:." Neurology Genetics 5, no. 4 (2019): e348. http://dx.doi.org/10.1212/nxg.0000000000000348.

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ObjectiveTo determine if any association between previously identified alleles that confer risk for Parkinson disease and variables measuring disease progression.MethodsWe evaluated the association between 31 risk variants and variables measuring disease progression. A total of 23,423 visits by 4,307 patients of European ancestry from 13 longitudinal cohorts in Europe, North America, and Australia were analyzed.ResultsWe confirmed the importance of GBA on phenotypes. GBA variants were associated with the development of daytime sleepiness (p.N370S: hazard ratio [HR] 3.28 [1.69–6.34]) and possib

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48

Bourgey, M., G. Calcagno, N. Tinto, et al. "HLA related genetic risk for coeliac disease." Gut 56, no. 8 (2007): 1054–59. http://dx.doi.org/10.1136/gut.2006.108530.

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49

Wilson, Carol. "Lipids and cardiovascular disease risk: genetic insights." Nature Reviews Endocrinology 6, no. 11 (2010): 598. http://dx.doi.org/10.1038/nrendo.2010.165.

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50

Baum, Andrew, Andrea L. Friedman, and Sandra G. Zakowski. "Stress and genetic testing for disease risk." Health Psychology 16, no. 1 (1997): 8–19. http://dx.doi.org/10.1037/0278-6133.16.1.8.

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