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Статті в журналах з теми "Clinical and genetic analysis"

Автор: Grafiati

Опубліковано: 8 березня 2025

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1

Kingston, H. M. "ABC of clinical genetics. DNA analysis in genetic disorders." BMJ 299, no. 6692 (July 15, 1989): 170–74. http://dx.doi.org/10.1136/bmj.299.6692.170.

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2

Sax, Christina M., and David B. Flannery. "Craniofrontonasal dysplasia: clinical and genetic analysis." Clinical Genetics 29, no. 6 (April 23, 2008): 508–15. http://dx.doi.org/10.1111/j.1399-0004.1986.tb00552.x.

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3

Bonifati, Vincenzo, Edito Fabrizio, Nicola Vanacore, Michele De Mari, and Giuseppe Meco. "Familial Parkinson’s Disease: A Clinical Genetic Analysis." Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques 22, no. 4 (November 1995): 272–79. http://dx.doi.org/10.1017/s0317167100039469.

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AbstractObjectiveTo study the frequency, clinical features and clinical genetics of familial Parkinson’s disease (PD).MethodsFamily history for PD and tremors was studied in 100 consecutive PD cases. Spouses served as controls. Clinical features were compared between personally verified familial and sporadic PD cases, from the same consecutive clinical series. Clinical genetic analysis was performed in a larger group of non-consecutive multicase PD families.ResultsFamily history for PD was positive in 24% of consecutive PD cases and in 6% of spouse controls (p < 0.001). When family history for isolated tremor is also considered, the number of positive cases rises to 43% compared with 9% in controls (p < 0.001). Nine of the consecutive cases had at least one living affected relative, for a total of 20 familial PD cases. These familial cases showed an earlier onset age when compared with sporadic ones from the same consecutive series. Within 22 non-consecutive PD families with at least two living and personally examined PD cases (total 52 PD cases), the crude segregation ratios were similar for parents and siblings and the lifetime cumulative risks approached 0.4 in siblings and tended to be comparable, but at later ages, in parents. Ancestral relatives were all unilaterally distributed. In some families, anticipation of onset age in new generations was observed.ConclusionsThe frequency of positive family history for PD and for PD and tremor is higher among PD cases than controls. Familial and sporadic PD only differ in onset age. The clinical genetic analyses support autosomal dominant inheritance with strongly age-related penetrance as most likely in familial PD.

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4

Hampel, Heather, Robin E. Grubs, Carol S. Walton, Emma Nguyen, Daniel H. Breidenbach, Steve Nettles, Meagan Corliss, et al. "Genetic Counseling Practice Analysis." Journal of Genetic Counseling 18, no. 3 (March 11, 2009): 205–16. http://dx.doi.org/10.1007/s10897-009-9216-1.

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5

Pittman, Alan, and John Hardy. "Genetic Analysis in Neurology." JAMA Neurology 70, no. 6 (June 1, 2013): 696. http://dx.doi.org/10.1001/jamaneurol.2013.2068.

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6

Millichap, J. Gordon. "Clinical and Genetic Analysis of Myoclonus-Dystonia." Pediatric Neurology Briefs 23, no. 7 (July 1, 2009): 53. http://dx.doi.org/10.15844/pedneurbriefs-23-7-7.

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7

TSUNEKAWA, Katsuhiko, and Masami MURAKAMI. "Clinical Application of Genetic Analysis in Obesity." Oleoscience 10, no. 10 (2010): 351–57. http://dx.doi.org/10.5650/oleoscience.10.351.

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8

Reddy, P. Leema, and Raji P. Grewal. "Friedreich's ataxia: A clinical and genetic analysis." Clinical Neurology and Neurosurgery 109, no. 2 (February 2007): 200–202. http://dx.doi.org/10.1016/j.clineuro.2006.09.003.

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9

Quarrell, O. "Primer of Genetic Analysis." Journal of Medical Genetics 25, no. 5 (May 1, 1988): 359. http://dx.doi.org/10.1136/jmg.25.5.359-a.

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10

Togo, M., T. Toda, L. A. Nguyen, S. Kubota, K. Tsukamoto, H. Satoh, M. Hara, et al. "Genetic analysis of phytosterolaemia." Journal of Inherited Metabolic Disease 24, no. 1 (February 2001): 43–50. http://dx.doi.org/10.1023/a:1005650605042.

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11

Marcuzzi, Annalisa, Elisa Piscianz, Giulio Kleiner, Alberto Tommasini, Giovanni Maria Severini, Lorenzo Monasta, and Sergio Crovella. "Clinical Genetic Testing of Periodic Fever Syndromes." BioMed Research International 2013 (2013): 1–8. http://dx.doi.org/10.1155/2013/501305.

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Periodic fever syndromes (PFSs) are a wide group of autoinflammatory diseases. Due to some clinical overlap between different PFSs, differential diagnosis can be a difficult challenge. Nowadays, there are no universally agreed recommendations for most PFSs, and near half of patients may remain without a genetic diagnosis even after performing multiple-gene analyses. Molecular analysis of periodic fevers’ causative genes can improve patient quality of life by providing early and accurate diagnosis and allowing the administration of appropriate treatment. In this paper we focus our discussion on effective usefulness of genetic diagnosis of PFSs. The aim of this paper is to establish how much can the diagnostic system improve, in order to increase the success of PFS diagnosis. The mayor expectation in the near future will be addressed to the so-called next generation sequencing approach. Although the application of bioinformatics to high-throughput genetic analysis could allow the identification of complex genotypes, the complexity of this definition will hardly result in a clear contribution for the physician. In our opinion, however, to obtain the best from this new development a rule should always be kept well in mind: use genetics only to answer specific clinical questions.

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12

Rainero, Innocenzo, Alessandro Vacca, Flora Govone, Annalisa Gai, Lorenzo Pinessi, and Elisa Rubino. "Migraine: Genetic Variants and Clinical Phenotypes." Current Medicinal Chemistry 26, no. 34 (December 12, 2019): 6207–21. http://dx.doi.org/10.2174/0929867325666180719120215.

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Migraine is a common, chronic neurovascular disorder caused by a complex interaction between genetic and environmental risk factors. In the last two decades, molecular genetics of migraine have been intensively investigated. In a few cases, migraine is transmitted as a monogenic disorder, and the disease phenotype cosegregates with mutations in different genes like CACNA1A, ATP1A2, SCN1A, KCNK18, and NOTCH3. In the common forms of migraine, candidate genes as well as genome-wide association studies have shown that a large number of genetic variants may increase the risk of developing migraine. At present, few studies investigated the genotype-phenotype correlation in patients with migraine. The purpose of this review was to discuss recent studies investigating the relationship between different genetic variants and the clinical characteristics of migraine. Analysis of genotype-phenotype correlations in migraineurs is complicated by several confounding factors and, to date, only polymorphisms of the MTHFR gene have been shown to have an effect on migraine phenotype. Additional genomic studies and network analyses are needed to clarify the complex pathways underlying migraine and its clinical phenotypes.

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13

Johnson, Scott C., David J. Marshall, Gerda Harms, Christie M. Miller, Christopher B. Sherrill, Edward L. Beaty, Scott A. Lederer, et al. "Multiplexed Genetic Analysis Using an Expanded Genetic Alphabet." Clinical Chemistry 50, no. 11 (November 1, 2004): 2019–27. http://dx.doi.org/10.1373/clinchem.2004.034330.

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Abstract Background: All states require some kind of testing for newborns, but the policies are far from standardized. In some states, newborn screening may include genetic tests for a wide range of targets, but the costs and complexities of the newer genetic tests inhibit expansion of newborn screening. We describe the development and technical evaluation of a multiplex platform that may foster increased newborn genetic screening. Methods: MultiCode® PLx involves three major steps: PCR, target-specific extension, and liquid chip decoding. Each step is performed in the same reaction vessel, and the test is completed in ∼3 h. For site-specific labeling and room-temperature decoding, we use an additional base pair constructed from isoguanosine and isocytidine. We used the method to test for mutations within the cystic fibrosis transmembrane conductance regulator (CFTR) gene. The developed test was performed manually and by automated liquid handling. Initially, 225 samples with a range of genotypes were tested retrospectively with the method. A prospective study used samples from >400 newborns. Results: In the retrospective study, 99.1% of samples were correctly genotyped with no incorrect calls made. In the perspective study, 95% of the samples were correctly genotyped for all targets, and there were no incorrect calls. Conclusions: The unique genetic multiplexing platform was successfully able to test for 31 targets within the CFTR gene and provides accurate genotype assignments in a clinical setting.

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14

Guerreiro, Rita, Eleanna Kara, Isabelle Le Ber, Jose Bras, Jonathan D. Rohrer, Ricardo Taipa, Tammaryn Lashley, et al. "Genetic Analysis of Inherited Leukodystrophies." JAMA Neurology 70, no. 7 (July 1, 2013): 875. http://dx.doi.org/10.1001/jamaneurol.2013.698.

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15

Morton, N. E. "Genetic Data Analysis. Methods for Discrete Population Genetic Data." Journal of Medical Genetics 29, no. 3 (March 1, 1992): 216. http://dx.doi.org/10.1136/jmg.29.3.216.

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16

Aston, C. E., and S. R. Wilson. "Genetic analysis workshop III: Multipoint linkage analysis." Genetic Epidemiology 2, no. 2 (1985): 199–200. http://dx.doi.org/10.1002/gepi.1370020212.

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17

Nowrin, Shifat A., Mohammad Khursheed Alam, and Rehana Basri. "Genetic analysis: future diagnostic tool in clinical Orthodontics." Bangladesh Journal of Medical Science 14, no. 3 (June 20, 2015): 310–11. http://dx.doi.org/10.3329/bjms.v14i3.20929.

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18

Yamauchi, Makoto, Takatoshi Yotsuyanagi, Kanae Ikeda, Mayu Yoshikawa, Satoshi Urushidate, Makoto Mikami, and Kenichi Kamo. "Clinical and genetic analysis of microtia in Japan." Journal of Plastic Surgery and Hand Surgery 46, no. 5 (September 24, 2012): 330–34. http://dx.doi.org/10.3109/2000656x.2012.700018.

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19

Boettcher, P. J., J. C. M. Dekkers, L. D. Warnick, and S. J. Wells. "Genetic Analysis of Clinical Lameness in Dairy Cattle." Journal of Dairy Science 81, no. 4 (April 1998): 1148–56. http://dx.doi.org/10.3168/jds.s0022-0302(98)75677-2.

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20

Huang, Dan, Qiong Zhou, Yun-Qi Chao, and Chao-Chun Zou. "Clinical features and genetic analysis of childhood sitosterolemia." Medicine 98, no. 15 (April 2019): e15013. http://dx.doi.org/10.1097/md.0000000000015013.

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21

Eller, P. "Wolfram syndrome: a clinical and molecular genetic analysis." Journal of Medical Genetics 38, no. 11 (November 1, 2001): 37e—37. http://dx.doi.org/10.1136/jmg.38.11.e37.

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22

Machado, RA, HAR Pontes, FR Pires, HM Silveira, A. Bufalino, R. Carlos, FM Tuji, et al. "Clinical and genetic analysis of patients with cherubism." Oral Diseases 23, no. 8 (July 21, 2017): 1109–15. http://dx.doi.org/10.1111/odi.12705.

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23

Forand, Pamela E., Susan J. Kunselman, Jeffrey M. Drazen, Elliot Israel, Anthony Pillari, Trina J. Armstrong, and Terry B. Britton. "Genetic Analysis in the Asthma Clinical Research Network." Controlled Clinical Trials 22, no. 6 (December 2001): S196—S206. http://dx.doi.org/10.1016/s0197-2456(01)00163-5.

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24

Emi, Mitsuru, and Shigeo Ohta. "Genetic analysis and clinical application in polygenic diseases." Nippon Ika Daigaku Zasshi 66, no. 5 (1999): 308. http://dx.doi.org/10.1272/jnms.66.308.

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25

Evans, A. E. "Recent advances in clinical, cellular and genetic analysis." European Journal of Cancer 31, no. 4 (January 1995): 428. http://dx.doi.org/10.1016/0959-8049(95)00005-4.

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26

Ohkuma, Aya, Satoru Noguchi, Hideo Sugie, May Christine V. Malicdan, Tokiko Fukuda, Kunio Shimazu, Luis Carlos López, et al. "Clinical and genetic analysis of lipid storage myopathies." Muscle & Nerve 39, no. 3 (March 2009): 333–42. http://dx.doi.org/10.1002/mus.21167.

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27

Maassen, J. Antonie. "Mitochondrial diabetes: Pathophysiology, clinical presentation, and genetic analysis." American Journal of Medical Genetics 115, no. 1 (May 30, 2002): 66–70. http://dx.doi.org/10.1002/ajmg.10346.

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28

Deng, Qiong, Fang Fu, Qiuxia Yu, Ru Li, Fucheng Li, Dan Wang, Tingying Lei, Xin Yang, and Can Liao. "Nonimmune hydrops fetalis: Genetic analysis and clinical outcome." Prenatal Diagnosis 40, no. 7 (May 3, 2020): 803–12. http://dx.doi.org/10.1002/pd.5691.

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29

Kopeikina, E. V., S. P. Shevchenko, and L. F. Gulyaeva. "CLINICAL AND MOLECULAR GENETIC ANALYSIS OF THYROID CANCER." Sibirskij medicinskij vestnik 8, no. 4 (2024): 31–34. https://doi.org/10.31549/2541-8289-2024-8-4-31-34.

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Анотація:

The article discusses the prevalence of various forms of thyroid cancer and analyzes approaches to this disease. It was stated that according to TCGA data, many mutations are detected in papillary thyroid cancer, but the most common are mutations in the genes: BRAF, NRAS, RET, TP53 and ATM. The studies show that the mutational spectra of thyroid cancer are quite poor, which may indicate the need to search for epigenetic markers, such as microRNA, genome methylation which may expand the possibilities in the treatment of oncological pathology, including thyroid cancer.

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30

Kaufman, David, Margaret Curnutte, and Amy L. McGuire. "Clinical Integration of Next Generation Sequencing: A Policy Analysis." Journal of Law, Medicine & Ethics 42, S1 (2014): 5–8. http://dx.doi.org/10.1111/jlme.12158.

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In 1996, President Clinton offered a promissory vision for human genetics when he said: “I think it won't be too many years before parents will be able to go home from the hospital with their newborn babies with a genetic map in their hands that will tell them, here's what your child's future will likely be like.”The rapid evolution of genetic sequencing technologies has advanced that vision. In October 2006, the cost of sequencing an entire human genome was $10.4 million; by 2014 the cost had decreased a thousand fold. The term next generation sequencing (NGS) describes a variety of laboratory methods that allow efficient determination of the precise order of nucleotides in a DNA sequence. The papers in this issue of the Journal of Law, Medicine & Ethics focus on “clinical NGS,” which refers to rapid DNA sequencing using second-, third- and fourth-generation sequencing technologies to perform genome-wide sequencing of multiple genes or alleles for clinical prognostic, diagnostic, and therapeutic purposes.

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31

Takenaka, Katsunobu, Noboru Sakai, and Akio Koizumi. "Genetic Analysis in Cerebrovascular Disorders." Japanese Journal of Neurosurgery 12, no. 3 (2003): 161–65. http://dx.doi.org/10.7887/jcns.12.161.

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32

Read, A. P. "Analysis of Human Genetic Linkage." Journal of Medical Genetics 29, no. 9 (September 1, 1992): 680. http://dx.doi.org/10.1136/jmg.29.9.680.

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33

Edwards, J. H. "Analysis of Human Genetic Linkage." Journal of Medical Genetics 25, no. 12 (December 1, 1988): 862–64. http://dx.doi.org/10.1136/jmg.25.12.862.

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34

Harnden, D. G. "Genetic Analysis of Tumour Suppression." Journal of Medical Genetics 27, no. 1 (January 1, 1990): 70–71. http://dx.doi.org/10.1136/jmg.27.1.70-a.

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35

Gardiner, R. M. "Genetic analysis of Batten disease." Journal of Inherited Metabolic Disease 16, no. 4 (1993): 787–90. http://dx.doi.org/10.1007/bf00711910.

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36

Baltimore, J. Ott. "Analysis of Human Genetic Linkage." Annals of Human Genetics 50, no. 1 (January 1986): 101–2. http://dx.doi.org/10.1111/j.1469-1809.1986.tb01944.x.

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37

Witte, J. S. "Genetic analysis with hierarchical models." Genetic Epidemiology 14, no. 6 (1997): 1137–42. http://dx.doi.org/10.1002/(sici)1098-2272(1997)14:6<1137::aid-gepi96>3.0.co;2-h.

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38

Maccluer, Jean W., Catherine T. Falk, and Diane K. Wagener. "Genetic analysis workshop III: Summary." Genetic Epidemiology 2, no. 2 (1985): 185–98. http://dx.doi.org/10.1002/gepi.1370020211.

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39

Anderson, Commission Members: E., S. Berkovic, O. Dulac, M. Gardiner, S. Jain, M. Laue Friis, D. Lindhout, et al. "ILAE Genetics Commission Conference Report: Molecular Analysis of Complex Genetic Epilepsies." Epilepsia 43, no. 12 (December 2002): 1600–1602. http://dx.doi.org/10.1046/j.1528-1157.2002.t01-1-04312.x.

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40

Whitworth, James, Jon Hoffman, Cyril Chapman, Kai Ren Ong, Fiona Lalloo, D. Gareth Evans, and Eamonn R. Maher. "A clinical and genetic analysis of multiple primary cancer referrals to genetics services." European Journal of Human Genetics 23, no. 5 (September 24, 2014): 581–87. http://dx.doi.org/10.1038/ejhg.2014.157.

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41

Bhatia, Neha S., Jiin Ying Lim, Carine Bonnard, Jyn-Ling Kuan, Maggie Brett, Heming Wei, Breana Cham, et al. "Singapore Undiagnosed Disease Program: Genomic Analysis aids Diagnosis and Clinical Management." Archives of Disease in Childhood 106, no. 1 (August 20, 2020): 31–37. http://dx.doi.org/10.1136/archdischild-2020-319180.

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Анотація:

ObjectiveUse next-generation sequencing (NGS) technology to improve our diagnostic yield in patients with suspected genetic disorders in the Asian setting.DesignA diagnostic study conducted between 2014 and 2019 (and ongoing) under the Singapore Undiagnosed Disease Program. Date of last analysis was 1 July 2019.SettingInpatient and outpatient genetics service at two large academic centres in Singapore.PatientsInclusion criteria: patients suspected of genetic disorders, based on abnormal antenatal ultrasound, multiple congenital anomalies and developmental delay. Exclusion criteria: patients with known genetic disorders, either after clinical assessment or investigations (such as karyotype or chromosomal microarray).InterventionsUse of NGS technology—whole exome sequencing (WES) or whole genome sequencing (WGS).Main outcome measures(1) Diagnostic yield by sequencing type, (2) diagnostic yield by phenotypical categories, (3) reduction in time to diagnosis and (4) change in clinical outcomes and management.ResultsWe demonstrate a 37.8% diagnostic yield for WES (n=172) and a 33.3% yield for WGS (n=24). The yield was higher when sequencing was conducted on trios (40.2%), as well as for certain phenotypes (neuromuscular, 54%, and skeletal dysplasia, 50%). In addition to aiding genetic counselling in 100% of the families, a positive result led to a change in treatment in 27% of patients.ConclusionGenomic sequencing is an effective method for diagnosing rare disease or previous ‘undiagnosed’ disease. The clinical utility of WES/WGS is seen in the shortened time to diagnosis and the discovery of novel variants. Additionally, reaching a diagnosis significantly impacts families and leads to alteration in management of these patients.

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42

Маркова, Т. В., В. М. Кенис, Е. В. Мельченко, Т. С. Нагорнова, А. А. Орлова, Н. И. Вассерман, Е. Ю. Захарова, and Е. Л. Дадали. "Clinical and genetic characteristics of genetic skeletal disorders." Nauchno-prakticheskii zhurnal «Medicinskaia genetika», no. 8(217) (August 31, 2020): 50–51. http://dx.doi.org/10.25557/2073-7998.2020.08.50-51.

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Представлены результаты анализа эффективности использования методов анализа ДНК для диагностики наследственных скелетных дисплазий (НСД) на основе анализа выборки из 270 российских пациентов. Показано, что использование различных молекулярно-генетических методов позволяет уточнить диагноз у 74% больных с клиническими и рентгенологическими признаками системных поражений скелета. Подсчитаны частоты встречаемости восьми групп НСД. Показано, что наиболее часто диагностируются FGFR3-хондродисплазии, коллагенопатии и болезни, обусловленные нарушением сульфатного обмена, на долю которых приходится 67,5% от всех диагностированных НСД. The effectiveness of DNA analysis for diagnostics of genetic skeletal disorders (GSD) based on the investigation of the data of 270 Russian patients was evaluated. The usage of various molecular genetic methods allows to clarify the diagnosis in 74% of patients with clinical and radiological signs of systemic skeletal disorders. The incidence of 8 most common groups of NSD was calculated. It has been shown that the most commonly diagnosed conditions included FGFR3-relared chondrodysplasias, collagenopathies and diseases caused by impaired sulfate metabolism, which account for 67.5% of all diagnosed NSD.

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43

Stubbe, Annika, Dragan Primorac, and Wolfgang Höppner. "Molecular genetics analysis of osteogenesis imperfecta in clinical practice." Paediatria Croatica 61, no. 3 (September 30, 2017): 141–46. http://dx.doi.org/10.13112/pc.523.

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Osteogenesis imperfecta (OI) is characterized by fractures with minimal or absent trauma, representing a continuum ranging fromperinatal lethality through individuals with severe skeletal deformities to nearly asymptomatic individuals with mild predispositionto fractures. Diagnosis of OI is an interdisciplinary task based on family and/or patient history of fractures combined with characteristicphysical fi ndings. Radiographic examination reveals fractures of varying ages and stages of healing, wormian bones, and osteopenia.As there is no defi nitive test for OI, molecular genetic testing by next generation sequencing (NGS) of COL1A1 and COL1A2 andup to 12 other genes is essential to confi rm the genetic background. Therefore, we designed a NGS gene panel comprising 12 genesinvolved in OI or severe osteoporosis. Here we report results in a cohort of 11 apparently sporadic young patients with OI, all off springof unaff ected parents, who were referred to orthopaedic surgery at Sv. Katarina Special Hospital (Zabok/Zagreb, Croatia). Tenof these 11 patients could be classifi ed genetically. Overall, three genes with diff erent percent relating to the whole cohort wereinvolved: COL1A1 (63.6%), COL1A2 (18.18%) and WNT1 (9.09%).Key words: osteogenesis imperfecta; molecular genetics - analysis

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44

Lara, Letícia A. de C., Ivan Pocrnic, Thiago de P. Oliveira, R. Chris Gaynor, and Gregor Gorjanc. "Temporal and genomic analysis of additive genetic variance in breeding programmes." Heredity 128, no. 1 (December 15, 2021): 21–32. http://dx.doi.org/10.1038/s41437-021-00485-y.

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AbstractGenetic variance is a central parameter in quantitative genetics and breeding. Assessing changes in genetic variance over time as well as the genome is therefore of high interest. Here, we extend a previously proposed framework for temporal analysis of genetic variance using the pedigree-based model, to a new framework for temporal and genomic analysis of genetic variance using marker-based models. To this end, we describe the theory of partitioning genetic variance into genic variance and within-chromosome and between-chromosome linkage-disequilibrium, and how to estimate these variance components from a marker-based model fitted to observed phenotype and marker data. The new framework involves three steps: (i) fitting a marker-based model to data, (ii) sampling realisations of marker effects from the fitted model and for each sample calculating realisations of genetic values and (iii) calculating the variance of sampled genetic values by time and genome partitions. Analysing time partitions indicates breeding programme sustainability, while analysing genome partitions indicates contributions from chromosomes and chromosome pairs and linkage-disequilibrium. We demonstrate the framework with a simulated breeding programme involving a complex trait. Results show good concordance between simulated and estimated variances, provided that the fitted model is capturing genetic complexity of a trait. We observe a reduction of genetic variance due to selection and drift changing allele frequencies, and due to selection inducing negative linkage-disequilibrium.

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45

Pelotti, Susi, Stefania Ceccardi, Milena Alù, Federica Lugaresi, Rachele Trane, Mirella Falconi, Carla Bini, and Alberto Cicognani. "Cancerous Tissues in Forensic Genetic Analysis." Genetic Testing 11, no. 4 (December 2007): 397–400. http://dx.doi.org/10.1089/gte.2007.0004.

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46

Ellington, Lee, Debra Roter, William N. Dudley, Bonnie J. Baty, Renn Upchurch, Susan Larson, Jean E. Wylie, Ken R. Smith, and Jeffrey R. Botkin. "Communication Analysis of BRCA1 Genetic Counseling." Journal of Genetic Counseling 14, no. 5 (October 2005): 377–86. http://dx.doi.org/10.1007/s10897-005-3660-3.

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47

Cruz-Utrilla, Alejandro, Natalia Gallego-Zazo, Jair Antonio Tenorio-Castaño, Inmaculada Guillén, Alba Torrent-Vernetta, Amparo Moya-Bonora, Carlos Labrandero, et al. "Clinical Implications of the Genetic Background in Pediatric Pulmonary Arterial Hypertension: Data from the Spanish REHIPED Registry." International Journal of Molecular Sciences 23, no. 18 (September 9, 2022): 10433. http://dx.doi.org/10.3390/ijms231810433.

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Background: Pulmonary arterial hypertension (PAH) is a severe and rare disease with an important genetic background. The influence of genetic testing in the clinical classification of pediatric PAH is not well known and genetics could influence management and prognosis. Objectives: The aim of this work was to identify the molecular fingerprint of PH children in the REgistro de pacientes con HIpertensión Pulmonar PEDiátrica (REHIPED), and to investigate if genetics could have an impact in clinical reclassification and prognosis. Methods: We included pediatric patients with a genetic analysis from REHIPED. From 2011 onward, successive genetic techniques have been carried out. Before genetic diagnosis, patients were classified according to their clinical and hemodynamic data in five groups. After genetic analysis, the patients were reclassified. The impact of genetics in survival free of lung transplantation was estimated by Kaplan–Meier curves. Results: Ninety-eight patients were included for the analysis. Before the genetic diagnoses, there were idiopathic PAH forms in 53.1%, PAH associated with congenital heart disease in 30.6%, pulmonary veno-occlusive disease—PVOD—in 6.1%, familial PAH in 5.1%, and associated forms with multisystemic disorders—MSD—in 5.1% of the patients. Pathogenic or likely pathogenic variants were found in 44 patients (44.9%). After a genetic analysis, 28.6% of the cohort was “reclassified”, with the groups of heritable PAH, heritable PVOD, TBX4, and MSD increasing up to 18.4%, 8.2%, 4.1%, and 12.2%, respectively. The MSD forms had the worst survival rates, followed by PVOD. Conclusions: Genetic testing changed the clinical classification of a significant proportion of patients. This reclassification showed relevant prognostic implications.

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48

Biesecker, Leslie G. "Clinical Commentary: The Law of Unintended Ethics." Journal of Law, Medicine & Ethics 25, no. 1 (1997): 16–18. http://dx.doi.org/10.1111/j.1748-720x.1997.tb01390.x.

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The law of unintended consequences is generally applied to technological advances that solve one problem but cause another. In this view, the problem created may be worse than that which was solved, hence the law is used as an argument against technological advances. Concern about intent and consequence comes to mind when reading the article by Ronald Green on parental decision making and prenatal genetics. Green's analysis, combined with the realities of genetic practice, raises questions about parental power, eugenics, and the interests of children affected by genetic or congenital disorders. Green proposes rules and draws conclusions that are not useful for clinicians and that promise harm to families and individuals affected by genetic disorders. Green's analysis may be an example of a corollary that could be viewed as the Law of Unintended Ethics.Green's paper begins with an apparently contradictory dual thesis. First, he supports unfettered parental decision making about their fetuses and children. Second, he suggests that we should strive to give our children lives unimpaired by serious genetic (or congenital) disorders.

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Marini, Carla, Ingrid E. Scheffer, Kathryn M. Crossland, Bronwyn E. Grinton, Fiona L. Phillips, Jacinta M. McMahon, Samantha J. Turner, et al. "Genetic Architecture of Idiopathic Generalized Epilepsy: Clinical Genetic Analysis of 55 Multiplex Families." Epilepsia 45, no. 5 (May 2004): 467–78. http://dx.doi.org/10.1111/j.0013-9580.2004.46803.x.

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50

Kitamura, Yutaka, Kazuo Shimizu, Shigeo Tanaka, and Mitsuru Emi. "Genetic analysis and clinical application in polygenic diseases. Genetic alterations in thyroid carcinomas." Nippon Ika Daigaku Zasshi 66, no. 5 (1999): 319–23. http://dx.doi.org/10.1272/jnms.66.319.

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