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Genome-wide linkage analysis is a powerful prenatal diagnostic tool in families with unknown genetic defects.

ABSTRACT: Genome-wide linkage analysis is an established tool to map inherited diseases. To our knowledge it has not been used in prenatal diagnostics of any genetic disorder. We present a family with a severe recessive mental retardation syndrome, where the mother wished pregnancy termination to avoid delivering another affected child. By genome-wide scanning using the Affymetrix (Santa Clara, CA, USA) 10k chip we were able to establish the disease haplotype. Without knowing the exact genetic defect, we excluded the condition in the fetus. The woman finally gave birth to a healthy baby. We suggest that genome-wide linkage analysis--based on either SNP mapping or full-genome sequencing--is a very useful tool in prenatal diagnostics of diseases.

SUBMITTER: Arelin M

PROVIDER: S-EPMC3598323 | biostudies-literature | 2013 Apr

REPOSITORIES: biostudies-literature

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Genome-wide linkage analysis is a powerful prenatal diagnostic tool in families with unknown genetic defects.

Arélin Maria M Schulze Bernt B Müller-Myhsok Bertram B Horn Denise D Diers Alexander A Uhlenberg Birgit B Nürnberg Peter P Nürnberg Gudrun G Becker Christian C Mundlos Stefan S Lindner Tom H TH Sperling Karl K Hoffmann Katrin K

European journal of human genetics : EJHG 20121003 4

Genome-wide linkage analysis is an established tool to map inherited diseases. To our knowledge it has not been used in prenatal diagnostics of any genetic disorder. We present a family with a severe recessive mental retardation syndrome, where the mother wished pregnancy termination to avoid delivering another affected child. By genome-wide scanning using the Affymetrix (Santa Clara, CA, USA) 10k chip we were able to establish the disease haplotype. Without knowing the exact genetic defect, we ...[more]

PMID: 23032112

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Data linkage: a powerful research tool with potential problems.

Project description:BackgroundPolicy makers, clinicians and researchers are demonstrating increasing interest in using data linked from multiple sources to support measurement of clinical performance and patient health outcomes. However, the utility of data linkage may be compromised by sub-optimal or incomplete linkage, leading to systematic bias. In this study, we synthesize the evidence identifying participant or population characteristics that can influence the validity and completeness of data linkage and may be associated with systematic bias in reported outcomes.MethodsA narrative review, using structured search methods was undertaken. Key words "data linkage" and Mesh term "medical record linkage" were applied to Medline, EMBASE and CINAHL databases between 1991 and 2007. Abstract inclusion criteria were; the article attempted an empirical evaluation of methodological issues relating to data linkage and reported on patient characteristics, the study design included analysis of matched versus unmatched records, and the report was in English. Included articles were grouped thematically according to patient characteristics that were compared between matched and unmatched records.ResultsThe search identified 1810 articles of which 33 (1.8%) met inclusion criteria. There was marked heterogeneity in study methods and factors investigated. Characteristics that were unevenly distributed among matched and unmatched records were; age (72% of studies), sex (50% of studies), race (64% of studies), geographical/hospital site (93% of studies), socio-economic status (82% of studies) and health status (72% of studies).ConclusionA number of relevant patient or population factors may be associated with incomplete data linkage resulting in systematic bias in reported clinical outcomes. Readers should consider these factors in interpreting the reported results of data linkage studies.

| S-EPMC3271236 | biostudies-literature

Genome-wide linkage analysis in Spanish melanoma-prone families

Project description:This SuperSeries is composed of the SubSeries listed below.

2019-01-01 | GSE109208 | GEO

Genome-wide linkage analysis in Spanish melanoma-prone families [Round2]

Project description:The main genetic factors for familial melanoma remain unknown in more than 75% of families. CDKN2A is mutated in around 20% of melanoma-prone families. Other high-risk melanoma susceptibility genes explain less than 3% of families studied to date. We performed the first genome-wide linkage analysis in CDKN2A-negative Spanish melanoma-prone families to identify novel melanoma susceptibility loci. We included 68 individuals from 2, 3 and 6 families with 2, 3 and at least 4 melanoma cases. We detected a locus with significant linkage evidence at 11q14.1-q14.3, with a maximum het-TLOD of 3.449 (rs12285365:A>G), using evidence from multiple pedigrees. The genes contained by the subregion with the strongest linkage evidence were: DLG2, PRSS23, FZD4 and TMEM135. We also detected several regions with suggestive linkage evidence (TLOD>1.9) (1q, 6p, 7p, 11q, 12p, 13q) including the region previously detected in melanoma-prone families from Sweden at 3q29. The family specific analysis revealed three loci with suggestive linkage evidence for family #1: 1q31.1-q32.1 (max. TLOD 2.447), 6p24.3-p22.3 (max. TLOD 2.409) and 11q13.3-q21 (max. TLOD 2.654). Future next generation sequencing studies of these regions may allow the identification of new melanoma susceptibility genetic factors.

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Genome-wide linkage analysis in Spanish melanoma-prone families [Round1]

2019-01-01 | GSE109206 | GEO

Genome-wide linkage analysis of families with primary hyperhidrosis.

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| S-EPMC7773265 | biostudies-literature

Genome-wide linkage scan identifies two novel genetic loci for coronary artery disease: in GeneQuest families.

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| S-EPMC4259362 | biostudies-literature

Diagnostic tool for the identification of MLL rearrangements including unknown partner genes.

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| S-EPMC544299 | biostudies-literature

Genetic epidemiology and genome-wide linkage analysis of carotid artery ultrasound traits in multigenerational African ancestry families.

Project description:Intima-media thickness, adventitial diameter and lumen diameter are indicators of cardiovascular disease risk. The influence of genetic factors on these measures in African ancestry populations is not well defined. Therefore, we estimated heritability and performed genome-wide linkage analysis of carotid ultrasound traits in 7 multigenerational families of African ancestry.A total of 395 individuals (7 pedigrees; mean family size = 56; 2392 relative pairs) aged ?18 years had a common carotid artery ultrasound scan. Statistical analyses were conducted using pedigree-based maximum likelihood methods.Significant covariates included age, sex, body mass index or height and waist, and systolic blood pressure. Residual heritabilities ranged from 0.35 ± 0.10 to 0.64 ± 0.12 (P < 0.0001). We identified a novel quantitative trait locus for adventitial and lumen diameters on chromosome 11 (max LOD = 4.09, 133 cm).Further fine mapping of this region may identify specific mutations predisposing to subclinical vascular disease among African ancestry individuals.

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Genome-Wide Linkage Analysis of Large Multiple Multigenerational Families Identifies Novel Genetic Loci for Coronary Artery Disease.

Project description:Coronary artery disease (CAD) is the leading cause of death, and genetic factors contribute significantly to risk of CAD. This study aims to identify new CAD genetic loci through a large-scale linkage analysis of 24 large and multigenerational families with 433 family members (GeneQuest II). All family members were genotyped with markers spaced by every 10?cM and a model-free nonparametric linkage (NPL-all) analysis was carried out. Two highly significant CAD loci were identified on chromosome 17q21.2 (NPL score of 6.20) and 7p22.2 (NPL score of 5.19). We also identified four loci with significant NPL scores between 4.09 and 4.99 on 2q33.3, 3q29, 5q13.2 and 9q22.33. Similar analyses in individual families confirmed the six significant CAD loci and identified seven new highly significant linkages on 9p24.2, 9q34.2, 12q13.13, 15q26.1, 17q22, 20p12.3, and 22q12.1, and two significant loci on 2q11.2 and 11q14.1. Two loci on 3q29 and 9q22.33 were also successfully replicated in our previous linkage analysis of 428 nuclear families. Moreover, two published risk variants, SNP rs46522 in UBE2Z and SNP rs6725887 in WDR12 by GWAS, were found within the 17q21.2 and 2q33.3 loci. These studies lay a foundation for future identification of causative variants and genes for CAD.

| S-EPMC5511258 | biostudies-literature

VaRank: a simple and powerful tool for ranking genetic variants.

Project description:Background. Most genetic disorders are caused by single nucleotide variations (SNVs) or small insertion/deletions (indels). High throughput sequencing has broadened the catalogue of human variation, including common polymorphisms, rare variations or disease causing mutations. However, identifying one variation among hundreds or thousands of others is still a complex task for biologists, geneticists and clinicians. Results. We have developed VaRank, a command-line tool for the ranking of genetic variants detected by high-throughput sequencing. VaRank scores and prioritizes variants annotated either by Alamut Batch or SnpEff. A barcode allows users to quickly view the presence/absence of variants (with homozygote/heterozygote status) in analyzed samples. VaRank supports the commonly used VCF input format for variants analysis thus allowing it to be easily integrated into NGS bioinformatics analysis pipelines. VaRank has been successfully applied to disease-gene identification as well as to molecular diagnostics setup for several hundred patients. Conclusions. VaRank is implemented in Tcl/Tk, a scripting language which is platform-independent but has been tested only on Unix environment. The source code is available under the GNU GPL, and together with sample data and detailed documentation can be downloaded from http://www.lbgi.fr/VaRank/.

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