scholarly journals Monoamine Oxidase A and B Gene Polymorphisms and Negative and Positive Symptoms in Schizophrenia

2012 ◽  
Vol 2012 ◽  
pp. 1-5 ◽  
Author(s):  
Beatriz Camarena ◽  
Ana Fresán ◽  
Alejandro Aguilar ◽  
Raúl Escamilla ◽  
Ricardo Saracco ◽  
...  
Keyword(s):  
Clinical Characteristics ◽  
Large Scale ◽  
Association Studies ◽  
Monoamine Oxidase A ◽  
Final Conclusion ◽  
Polymorphism Analysis ◽  
Anova Analysis ◽  
Genetic Studies ◽  
Control Association ◽  
Affective Flattening

Given that schizophrenia is a heterogeneous disorder, the analysis of clinical characteristics could help to identify homogeneous phenotypes that may be of relevance in genetic studies. Linkage and association studies have suggested that a locus predisposing to schizophrenia may reside within Xp11. We analyzed uVNTR and rs1137070, polymorphisms from MAOA and rs1799836 of MAOB genes to perform single SNP case-control association study in a sample of 344 schizophrenia patients and 124 control subjects. Single polymorphism analysis of uVNTR, rs1137070 and rs1799836 SNPs did not show statistical differences between cases and controls. Multivariate ANOVA analysis of clinical characteristics showed statistical differences between MAOB/rs1799836 and affective flattening scores (F=4.852, P=0.009), and significant association between MAOA/uVNTR and affective flattening in female schizophrenia patients (F=4.236, P=0.016) after Bonferroni’s correction. Our preliminary findings could suggest that severity of affective flattening may be associated by modifier variants of MAOA and MAOB genes in female Mexican patients with schizophrenia. However, further large-scale studies using quantitative symptom-based phenotypes and several candidate variants should be analyzed to obtain a final conclusion.

scholarly journals Parkinson’s Disease in Central Asian and Transcaucasian Countries: A Review of Epidemiology, Genetics, Clinical Characteristics, and Access to Care

2019 ◽  
Vol 2019 ◽  
pp. 1-7
Author(s):  
Rauan Kaiyrzhanov ◽  
Mie Rizig ◽  
Akbota Aitkulova ◽  
Nazira Zharkinbekova ◽  
Chingiz Shashkin ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Clinical Characteristics ◽  
Large Scale ◽  
Age Of Onset ◽  
Genetic Studies ◽  
Related Data ◽  
Central Asian ◽  
The Mean ◽  
Made In

Our understanding of Parkinson’s disease (PD) has significantly accelerated over the last few years, but predominant advances have been made in developed, Western countries. Little is known about PD in the Central Asian (CA) and Transcaucasian (TC) countries. Here, we review the clinical characteristics, treatments used, epidemiology, and genetics of PD in CA and TC countries via a methodological search in MEDLINE, EMBASE, Scopus, Web of Science, and Google Scholar databases. For the acquisition of PD care-related data, the search was extended to the local web resources. Our findings showed that PD prevalence in the region is averaging 62 per 100,000 population. The mean age of onset is 56.4 ± 2.8 in females and 63.3 ± 3.5 in males. Large-scale national studies on PD prevalence from the region are currently lacking. A limited number of genetic studies with small cohorts and inconclusive results were identified. The G2019S LRRK2 mutation, the commonest mutation in PD worldwide, was found in 5.7% of patients with idiopathic PD and 17.6% of familial cases in 153 Uzbek patients. Our review highlighted systematic deficiencies in PD health care in the region including lacks of neurologists specializing in PD, delays in PD diagnosis, absence of specialized PD nurses and PD rehab services, limited access to PD medications and surgery, and the unavailability of PD infusion therapies. Overall, this article demonstrated the paucity of data on this common neurological disorder in CA and TC countries and identified a number of healthcare areas that require an urgent consideration. We conclude that well-designed large-scale epidemiological, genetic, and clinical studies are desperately needed in this region. Healthcare professionals, local and national institutions, and stakeholders must come together to address deficiencies in PD healthcare systems in CA and TC countries.

scholarly journals Medical records-based chronic kidney disease phenotype for clinical care and “big data” observational and genetic studies

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Ning Shang ◽  
Atlas Khan ◽  
Fernanda Polubriaginof ◽  
Francesca Zanoni ◽  
Karla Mehl ◽  
...  
Keyword(s):  
Chronic Kidney Disease ◽  
Kidney Disease ◽  
Medical Records ◽  
Large Scale ◽  
Association Studies ◽  
Clinical Care ◽  
Medical Systems ◽  
Genetic Studies ◽  
Genome Wide ◽  
Independent Case

AbstractChronic Kidney Disease (CKD) represents a slowly progressive disorder that is typically silent until late stages, but early intervention can significantly delay its progression. We designed a portable and scalable electronic CKD phenotype to facilitate early disease recognition and empower large-scale observational and genetic studies of kidney traits. The algorithm uses a combination of rule-based and machine-learning methods to automatically place patients on the staging grid of albuminuria by glomerular filtration rate (“A-by-G” grid). We manually validated the algorithm by 451 chart reviews across three medical systems, demonstrating overall positive predictive value of 95% for CKD cases and 97% for healthy controls. Independent case-control validation using 2350 patient records demonstrated diagnostic specificity of 97% and sensitivity of 87%. Application of the phenotype to 1.3 million patients demonstrated that over 80% of CKD cases are undetected using ICD codes alone. We also demonstrated several large-scale applications of the phenotype, including identifying stage-specific kidney disease comorbidities, in silico estimation of kidney trait heritability in thousands of pedigrees reconstructed from medical records, and biobank-based multicenter genome-wide and phenome-wide association studies.

scholarly journals Effect of the polymorphism BDNF rs6265 G/A in Mexican outpatient children with autism spectrum disorders

Salud Mental ◽  
2018 ◽  
Vol 41 (3) ◽  
pp. 117-121
Author(s):  
Mirna Edith Morales-Marín ◽  
◽  
Miriam Aguilar ◽  
Lilia Albores ◽  
Ana Ballesteros ◽  
...  
Keyword(s):  
Design Method ◽  
Association Studies ◽  
Autism Spectrum ◽  
Case Control ◽  
Polymorphism Analysis ◽  
Control Analysis ◽  
Spectrum Disorders ◽  
Case Control Analysis ◽  
Control Association ◽  
Bdnf Rs6265

Introduction. The study of autistic spectrum disorders (ASD) at the genetic level is extremely important to understand their origin. In Mexico, there are few works addressed from this perspective. Objective. We investigated the role of the Brain Derived Neurotrophic Factor ( BDNF ) gene variant rs6265 G/A for single nucleotide polymorphism analysis in Mexican children with ASD using a case-control association design. Method. We made a pilot study by case-control analysis adjusting by gender, age, and ancestry. Results. Our study found no association between the BDNF rs6265 gene polymorphism and ASD [ p = .419, OR = 1.597 (.514, 4.967)]. Discussion and conclusion. Worldwide, the results of case-control association studies with the rs6265 of BDNF are controversial and do not always replicate. This may be due to the ethnicity of our population and additional factors not studied in the present work. Our study suggests that the SNP rs6265 is not contributing for ASD susceptibility in Mexican population.

scholarly journals A platform for case-control matching enables association studies without genotype sharing

2018 ◽  
Author(s):  
Mykyta Artomov ◽  
Alexander A. Loboda ◽  
Maxim N. Artyomov ◽  
Mark J. Daly
Keyword(s):  
Large Scale ◽  
Association Studies ◽  
Genetic Association Studies ◽  
Case Control ◽  
Human Dna ◽  
The Matrix ◽  
Value Decomposition ◽  
Control Association ◽  
Selection Of ◽  
Control Samples

AbstractAcquiring a sufficiently powered cohort of control samples can be time consuming or, sometimes, impossible. Accordingly, an ability to leverage control samples that were already collected and sequenced elsewhere could dramatically improve power in all genetic association studies. However, since majority of the genotyped and sequenced human DNA samples to date are subject to strict data sharing regulations, large-scale sharing of, in particular, control samples is extremely challenging. Using insights from image recognition, we developed a method allowing selection of the best-matching controls in an external pool of samples that is compliant with personal genotype data protection restrictions. Our approach uses singular value decomposition of the matrix of case genotypes to rank controls in another study by similarity to cases. We demonstrate that this recovers an accurate case-control association analysis for both ultra-rare and common variants and implement and provide online access to a library of ~17,000 controls that enables association studies for case cohorts lacking control subjects.

The Use of Medical Record Linkage for Population and Genetic Studies

1969 ◽  
Vol 08 (01) ◽  
pp. 07-11 ◽  
Author(s):  
H. B. Newcombe
Keyword(s):  
Record Linkage ◽  
Large Scale ◽  
Medical Record Linkage ◽  
Canadian Province ◽  
Genetic Studies ◽  
Parental Characteristics ◽  
Family Histories ◽  
The Family ◽  
Large Populations ◽  
Machine Readable

Methods are described for deriving personal and family histories of birth, marriage, procreation, ill health and death, for large populations, from existing civil registrations of vital events and the routine records of ill health. Computers have been used to group together and »link« the separately derived records pertaining to successive events in the lives of the same individuals and families, rapidly and on a large scale. Most of the records employed are already available as machine readable punchcards and magnetic tapes, for statistical and administrative purposes, and only minor modifications have been made to the manner in which these are produced.As applied to the population of the Canadian province of British Columbia (currently about 2 million people) these methods have already yielded substantial information on the risks of disease: a) in the population, b) in relation to various parental characteristics, and c) as correlated with previous occurrences in the family histories.

scholarly journals Optimized permutation testing for information theoretic measures of multi-gene interactions

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
James M. Kunert-Graf ◽  
Nikita A. Sakhanenko ◽  
David J. Galas
Keyword(s):  
Large Scale ◽  
Permutation Test ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Permutation Testing ◽  
Exact Test ◽  
Information Theoretic ◽  
Information Theoretic Measures ◽  
Full Analysis ◽  
Computational Bottleneck

Abstract Background Permutation testing is often considered the “gold standard” for multi-test significance analysis, as it is an exact test requiring few assumptions about the distribution being computed. However, it can be computationally very expensive, particularly in its naive form in which the full analysis pipeline is re-run after permuting the phenotype labels. This can become intractable in multi-locus genome-wide association studies (GWAS), in which the number of potential interactions to be tested is combinatorially large. Results In this paper, we develop an approach for permutation testing in multi-locus GWAS, specifically focusing on SNP–SNP-phenotype interactions using multivariable measures that can be computed from frequency count tables, such as those based in Information Theory. We find that the computational bottleneck in this process is the construction of the count tables themselves, and that this step can be eliminated at each iteration of the permutation testing by transforming the count tables directly. This leads to a speed-up by a factor of over 103 for a typical permutation test compared to the naive approach. Additionally, this approach is insensitive to the number of samples making it suitable for datasets with large number of samples. Conclusions The proliferation of large-scale datasets with genotype data for hundreds of thousands of individuals enables new and more powerful approaches for the detection of multi-locus genotype-phenotype interactions. Our approach significantly improves the computational tractability of permutation testing for these studies. Moreover, our approach is insensitive to the large number of samples in these modern datasets. The code for performing these computations and replicating the figures in this paper is freely available at https://github.com/kunert/permute-counts.

Power comparison of Cochran-Armitage trend test against allelic and genotypic tests in large-scale case-control genetic association studies

2016 ◽  
Vol 27 (9) ◽  
pp. 2657-2673 ◽  
Author(s):  
Mathieu Emily
Keyword(s):  
Large Scale ◽  
Association Studies ◽  
Disease Model ◽  
Trend Test ◽  
Genome Wide Association Studies ◽  
Power Functions ◽  
Power Comparison ◽  
Powerful Test ◽  
Armitage Trend Test ◽  
Mode Of Inheritance

The Cochran-Armitage trend test (CA) has become a standard procedure for association testing in large-scale genome-wide association studies (GWAS). However, when the disease model is unknown, there is no consensus on the most powerful test to be used between CA, allelic, and genotypic tests. In this article, we tackle the question of whether CA is best suited to single-locus scanning in GWAS and propose a power comparison of CA against allelic and genotypic tests. Our approach relies on the evaluation of the Taylor decompositions of non-centrality parameters, thus allowing an analytical comparison of the power functions of the tests. Compared to simulation-based comparison, our approach offers the advantage of simultaneously accounting for the multidimensionality of the set of features involved in power functions. Although power for CA depends on the sample size, the case-to-control ratio and the minor allelic frequency (MAF), our results first show that it is largely influenced by the mode of inheritance and a deviation from Hardy–Weinberg Equilibrium (HWE). Furthermore, when compared to other tests, CA is shown to be the most powerful test under a multiplicative disease model or when the single-nucleotide polymorphism largely deviates from HWE. In all other situations, CA lacks in power and differences can be substantial, especially for the recessive mode of inheritance. Finally, our results are illustrated by the comparison of the performances of the statistics in two genome scans.

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