Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “Genetic testing algorithm”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 recordsLinked to original sources
PubMed2024

High yield of monogenic short stature in children from Kurdistan, Iraq: A genetic testing algorithm for consanguineous families.

PURPOSE: Genetic testing in consanguineous families advances the general comprehension of pathophysiological pathways. However, short stature (SS) genetics remain unexplored in a defined consanguineous cohort. This study examines a unique pediatric cohort from Sulaimani, Iraq, aiming to inspire a genetic testing algorithm for similar populations. METHODS: Among 280 SS referrals from 2018-2020, 64 children met inclusion criteria (from consanguineous families; height ≤ -2.25 SD), 51 provided informed consent (30 females; 31 syndromic SS) and underwent investigation, primarily via exome sequencing. Prioritized variants were evaluated by the American College of Medical Genetics and Genomics standards. A comparative analysis was conducted by juxtaposing our findings against published gene panels for SS. RESULTS: A genetic cause of SS was elucidated in 31 of 51 (61%) participants. Pathogenic variants were found in genes involved in the GH-IGF-1 axis (GHR and SOX3), thyroid axis (TSHR), growth plate (CTSK, COL1A2, COL10A1, DYM, FN1, LTBP3, MMP13, NPR2, and SHOX), signal transduction (PTPN11), DNA/RNA replication (DNAJC21, GZF1, and LIG4), cytoskeletal structure (CCDC8, FLNA, and PCNT), transmembrane transport (SLC34A3 and SLC7A7), enzyme coding (CYP27B1, GALNS, and GNPTG), and ciliogenesis (CFAP410). Two additional participants had Silver-Russell syndrome and 1 had del22q.11.21. Syndromic SS was predictive in identifying a monogenic condition. Using a gene panel would yield positive results in only 10% to 33% of cases. CONCLUSION: A tailored testing strategy is essential to increase diagnostic yield in children with SS from consanguineous populations.

Humans↗
PubMed2026

Streamlining Diagnosis of Bardet-Biedl Syndrome: New Diagnostic Algorithm With Updated Criteria.

Considerable advances have been made in our understanding of Bardet-Biedl syndrome (BBS), particularly in its core clinical features and molecular genetics, warranting an update to the existing diagnostic criteria framework. Using a rigorous, evidence-based, and consensus-driven process, a multidisciplinary group of international experts and patient-led organizations developed an updated diagnostic algorithm. This algorithm provides practical, updated guidance for clinicians, including a pathway for accurately incorporating genetic findings into the diagnostic process. We recommend that a clinical diagnosis requires either 4 major criteria or 3 major and 2 minor criteria. Revised major criteria are retinal dystrophy, obesity (or overweight in individuals <&#x2009;2&#x2009;years old), congenital anomalies of the kidney and urinary tract or chronic kidney disease, hypogonadism/genital anomalies, neurodevelopmental/neurocognitive manifestations, and postaxial polydactyly. The diagnosis can also be established with a positive genetic testing result in patients exhibiting &#x2265;&#x2009;1 major criterion, provided that genetic findings should be interpreted in the context of the patient's clinical presentation, age, family history, and overlap with related ciliopathies. These consensus criteria offer a simple algorithm incorporating updated definitions for major and minor criteria and genetic testing to support a timely and accurate diagnosis of patients with BBS, inform genetic counseling, and potentially facilitate earlier access to treatment. Trial Registration: CRIBBS Registry; ClinicalTrials.gov: NCT02329210.

Humans↗
PubMed2024

Leveraging clinical intuition to improve accuracy of phenotype-driven prioritization.

PURPOSE: Clinical intuition is commonly incorporated into the differential diagnosis as an assessment of the likelihood of candidate diagnoses based either on the patient population being seen in a specific clinic or on the signs and symptoms of the initial presentation. Algorithms to support diagnostic sequencing in individuals with a suspected rare genetic disease do not yet incorporate intuition and instead assume that each Mendelian disease has an equal pretest probability. METHODS: The LIkelihood Ratio Interpretation of Clinical AbnormaLities (LIRICAL) algorithm calculates the likelihood ratio of clinical manifestations represented by Human Phenotype Ontology terms to rank candidate diagnoses. The initial version of LIRICAL assumed an equal pretest probability for each disease in its calculation of the posttest probability (where the test is diagnostic exome or genome sequencing). We introduce Clinical Intuition for Likelihood Ratios (ClintLR), an extension of the LIRICAL algorithm that boosts the pretest probability of groups of related diseases deemed to be more likely. RESULTS: The average rank of the correct diagnosis in simulations using ClintLR showed a statistically significant improvement over a range of adjustment factors. CONCLUSION: ClintLR successfully encodes clinical intuition to improve ranking of rare diseases in diagnostic sequencing. ClintLR is freely available at https://github.com/TheJacksonLaboratory/ClintLR.

Humans↗
PubMed2025

HCSeeker: A classification tool for human genetic variant hot and cold spots designed for PM1 and benign criteria in the ACMG-AMP guideline.

PURPOSE: The PM1 criterion, which states that a variant is located in a mutational hot spot and/or critical and well-established functional domain without benign variation (such as the active site of an enzyme), is considered moderate evidence for assessing its pathogenicity. Although guidelines from the American College of Medical Genetics and Genomics and the Association for Molecular Pathology are widely adopted, the PM1 criterion remains limited from lacking a reliable database of variant hot spots. Compared with hot spots, cold spots are neglected by the guidelines. To improve variant classification, we suggest including cold spots for supporting benign classifications. Consequently, we have developed the HCSeeker to provide data support for PM1 and the "Benign" criteria. METHODS: HCSeeker uses the Kernel Density Estimation and the Expectation-Maximization algorithm to identify hot- and cold-spot regions. RESULTS: Through HCSeeker, we identified 988 hot spots and 682 cold spots across 889 genes and provided a public database (http://www.genemed.tech/hcseeker/) for researchers and clinicians to query variant locations, facilitating the application of American College of Medical Genetics and Genomics and the Association for Molecular Pathology PM1 or "Benign" criteria. CONCLUSION: We developed the HCSeeker tool, which can effectively identify variant hot and cold spots within genes to enhance the interpretability of gene variants.

Humans↗
PubMed2025

FluxRETAP: a REaction TArget Prioritization genome-scale modeling technique for selecting genetic targets.

MOTIVATION: Metabolic engineering is rapidly evolving as a result of new advances in synthetic biology tools and automation platforms that enable high throughput strain construction, as well as the development of machine learning tools (ML) for biology. However, selecting genetic engineering targets that effectively guide the metabolic engineering process is still challenging. ML can provide predictive power for synthetic biology, but current technical limitations prevent the independent use of ML approaches without previous biological knowledge. RESULTS: Here, we present FluxRETAP, a simple and computationally inexpensive method that leverages the prior mechanistic knowledge embedded in genome-scale models for suggesting targets for genetic overexpression, downregulation or deletion, with the final goal of increasing the production of a desired metabolite. This method can provide a list of desirable engineering targets that can be combined with current ML pipelines. FluxRETAP captured 100% of reaction targets experimentally verified to improve Escherichia coli isoprenol production, 50% of targets that experimentally improved taxadiene production in E. coli and &#x223c;60% of genetic targets from a verified minimal constrained cut-set in Pseudomonas putida, while providing additional high priority targets that could be tested. Overall, FluxRETAP is an efficient algorithm for identifying a prioritized list of testable genetic and reaction targets. AVAILABILITY AND IMPLEMENTATION: FluxRETAP is implemented in python and released under the creative commons license. The implementation and code are freely available at: https://github.com/JBEI/FluxRETAP.

Escherichia coli↗
PubMed1990

Analysis of the inheritance, selection and evolution of growth trajectories.

We present methods for estimating the parameters of inheritance and selection that appear in a quantitative genetic model for the evolution growth trajectories and other "infinite-dimensional" traits that we recently introduced. Two methods for estimating the additive genetic covariance function are developed, a "full" model that fully fits the data and a "reduced" model that generates a smoothed estimate consistent with the sampling errors in the data. By decomposing the covariance function into its eigenvalues and eigenfunctions, it is possible to identify potential evolutionary changes in the population's mean growth trajectory for which there is (and those for which there is not) genetic variation. Algorithms for estimating these quantities, their confidence intervals, and for testing hypotheses about them are developed. These techniques are illustrated by an analysis of early growth in mice. Compatible methods for estimating the selection gradient function acting on growth trajectories in natural or domesticated populations are presented. We show how the estimates for the additive genetic covariance function and the selection gradient function can be used to predict the evolutionary change in a population's mean growth trajectory.

Animals↗
PubMed1990

Maternal serum alpha-fetoprotein (MSAFP) patient-specific risk reporting: its use and misuse.

Fundamental to maternal serum alpha-fetoprotein screening is the clinical utility of the laboratory report. It follows that the scientific form of expression in that report is vital. Professional societies concur that patient-specific risk reporting is the preferred form. However, some intermediate steps being taken to calculate patient-specific risks are invalid because of the erroneous assumption that multiples of the median (MoMs) represent an interlaboratory common currency. The numerous methods by which MoMs may be calculated belie the foregoing assumption.

Algorithms↗
PubMed2025

Distinguishing specific from broad genetic associations between external correlates and common factors.

MOTIVATION: Within the genomic structural equation modelling (genomic SEM) framework, common factors are often used to index shared genetic etiology across constellations of genome-wide associations studies (GWASs) phenotypes. A standard common pathway model, in which a genetic association is estimated between an external GWAS phenotype and a common factor, assumes that all genetic associations between the external GWAS phenotype and the individual indicator phenotypes are mediated through the factor. This assumption can be tested using the QTrait statistic, which compares the common pathway model to an independent pathways model that allows for direct genetic associations between the external GWAS phenotype and the individual indicators of the factor. However, QTrait is not designed to identify either the magnitude or the source of this heterogeneity. RESULTS: We expand upon the QTrait approach by describing an effect size index that quantifies the degree to which the common pathways model is violated, and we provide a systematic approach for empirically identifying specific direct pathways between an external trait and indicator traits. Our method comprises a series of omnibus tests and outlying indicator detection algorithms indexing the heterogeneity of associations between the genetic component of external traits and the individual indicators of common factors. We provide a set of automated functions which we apply to investigate the patterns of genetic associations across a set of external correlates with respect to indicators of general cognitive ability and case-control and proxy GWAS indices of Alzheimer's disease. AVAILABILITY AND IMPLEMENTATION: The Genomic SEM R package and the QTrait function is available at https://github.com/GenomicSEM/GenomicSEM. The QTrait function tutorial is available at https://github.com/GenomicSEM/GenomicSEM/wiki/8.-Tutorials. To ensure reproducibility of the analyses presented in this manuscript, the exact version of the QTrait function used, along with input data and scripts, has been archived on Zenodo (DOI: https://doi.org/10.5281/zenodo.17186083).

Genome-Wide Association Study↗
PubMed2025

Optimized phenotyping of complex morphological traits: enhancing discovery of common and rare genetic variants.

Genotype-phenotype (G-P) analyses for complex morphological traits typically utilize simple, predetermined anatomical measures or features derived via unsupervised dimension reduction techniques (e.g. principal component analysis (PCA) or eigen-shapes). Despite the popularity of these approaches, they do not necessarily reveal axes of phenotypic variation that are genetically relevant. Therefore, we introduce a framework to optimize phenotyping for G-P analyses, such as genome-wide association studies (GWAS) of common variants or rare variant association studies (RVAS) of rare variants. Our strategy is two-fold: (i) we construct a multidimensional feature space spanning a wide range of phenotypic variation, and (ii) within this feature space, we use an optimization algorithm to search for directions or feature combinations that are genetically enriched. To test our approach, we examine human facial shape in the context of GWAS and RVAS. In GWAS, we optimize for phenotypes exhibiting high heritability, estimated from either family data or genomic relatedness measured in unrelated individuals. In RVAS, we optimize for the skewness of phenotype distributions, aiming to detect commingled distributions that suggest single or few genomic loci with major effects. We compare our approach with eigen-shapes as baseline in GWAS involving 8246 individuals of European ancestry and in gene-based tests of rare variants with a subset of 1906 individuals. After applying linkage disequilibrium score regression to our GWAS results, heritability-enriched phenotypes yielded the highest SNP heritability, followed by eigen-shapes, while commingling-based traits displayed the lowest SNP heritability. Heritability-enriched phenotypes also exhibited higher discovery rates, identifying the same number of independent genomic loci as eigen-shapes with a smaller effective number of traits. For RVAS, commingling-based traits resulted in more genes passing the exome-wide significance threshold than eigen-shapes, while heritability-enriched phenotypes lead to only a few associations. Overall, our results demonstrate that optimized phenotyping allows for the extraction of genetically relevant traits that can specifically enhance discovery efforts of common and rare variants, as evidenced by their increased power in facial GWAS and RVAS.

Humans↗
PubMed1992

Improved performance in a prenatal screening programme for Down's syndrome incorporating serum-free hCG subunit analyses.

A prenatal screening programme for Down's syndrome potentially detecting 76 per cent of affected pregnancies in the South Australian general population at an amniocentesis rate of 3.9 per cent was designed following analysis of mid-trimester serum samples from 57 women who carried an affected fetus. This equates to one affected pregnancy being detected for 41 chromosomal analyses performed. For the experimental series, 75.4 per cent of affected pregnancies were detected, while 4.1 per cent of control specimens produced estimated risk odds consistent with further action. A maternal risk odds of birth of a Down's syndrome fetus of 1:420 was taken as the decision value, which is the prevalence of Down's syndrome births to 35-year-old mothers in South Australia. This screening performance was achieved by investigating combinations of serum analytes not previously reported and by refining the calculation of maternal risk odds to include selective weighting of indicator analytes. Combination of the measurements of free alpha-subunits and beta-subunits of chorionic gonadotrophin, alpha-fetoprotein, unconjugated oestriol, and placental lactogen was found to be most effective in indicating Down's syndrome fetuses. In all combinations of analytes tested, replacing the measurements of free alpha-subunits and free beta-subunits of chorionic gonadotrophin with the measurement of intact chorionic gonadotropin produced a less effective screen.

Adult↗
PubMed1992

Conformational analysis of a dinucleotide photodimer with the aid of the genetic algorithm.

The solution structure of the photodimer cis,syn-dUp[]dT is derived with the aid of the genetic algorithm. The conformational space available for the molecule is sampled efficiently using the computer program DENISE and tested against a set of constraints available from nmr experiments. The dominant conformation in solution found with this approach can be described by the following combinations of sugar-phosphate backbone torsion angles: epsilon(t), zeta(t), alpha(+), beta(-ac), and gamma(t). The conformation of the sugars and glycosidic torsion angles are S type and syn, respectively. The cyclobutane ring and pyrimidines are puckered. In addition, other conformations that exist in equilibrium with the first are found. It is concluded that the cyclobutane-pyrimidine system is rigid, whereas the sugar-phosphate backbone is flexible. The solution structures are compared with the crystal structure of the strongly related cyano-ethyl ester of cis,syn-dTp[]dT.

Algorithms↗
PubMed1987

Diagnosing human malformation patterns with a microcomputer: evaluation of two different algorithms.

SYNDROC, a microcomputer-aided differential diagnostic approach to human malformation patterns, is based on a pseudo-Bayesian algorithm. This means that, for each sign, the frequency of this sign in the general population, its frequency in a particular syndrome, and the frequency of that particular syndrome have to be determined. These parameters are easy to find in common syndromes but tend to be difficult for rare or isolated cases. Thus, we implemented a new algorithm called the "descriptive algorithm," which defines a diagnosis by a set of anomalies all having the same weight. To test this algorithm, we analyzed 100 cases representing 100 different syndromes out of the register of the Division of Medical Genetics, Children's Hospital and Medical Center, University of Washington. The descriptive algorithm was allowed to give 3 sets of diagnoses. In 91% of the cases, this algorithm proposed the correct diagnosis (54% in the first window, 28% in the second window, and 9% in the third window). The number of diagnoses proposed was 18.78 +/- 16.57. The same cases were analyzed with the pseudo-Bayesian algorithm. The concordant diagnosis was proposed in 92% of the cases (55% at the top place, 11% at the second place, and 26% at the third place or beyond). The number of diagnoses submitted was 13.5 +/- 11.04. The combined algorithm gave the correct diagnosis in 96% of the cases. This study shows that the descriptive algorithm is as accurate as the pseudo-Bayesian algorithm in diagnosing malformation patterns, but this level is accompanied by an increased number of proposed diagnoses.

Abnormalities, Multiple↗
PubMed1987

Prospects for molecular vaccines in veterinary parasitology.

Despite the profound developments in recombinant DNA technology there is only one marketed recombinant vaccine (for human viral hepatitis B). The development of others proceeds with great difficulty. Molecular vaccines against veterinary parasites are at the utmost pole of complexity in the spectrum of potential vaccines since these parasites are complex eukaryotic organisms, often dwelling at mucosal surfaces where anamnestic responses are problematic, where the immunogenicity of the parasite components is poorly understood and where the effector mechanisms of immunity are unresolved. Cloning a "protective" gene is only the first step, and perhaps the easiest, in a long process which will be necessary to develop vaccines against parasites. Additional steps will involve comprehensive analyses of the immunological responses to ensure that vaccine antigens contain the correct epitopes to induce appropriate immune effector mechanisms for parasite elimination and immunological memory and that these responses are not genetically restricted. The great expectations for recombinant vaccinia-based vaccines must be modified substantially in the light of recent evidence indicating immunological and other constraints on this approach. The use of anti-idiotype vaccines is an underexplored opportunity for practical parasite vaccines since they have several potentially important advantages. The need to include T cell antigenic peptides in peptide vaccines to extend the range of genetic responsiveness and to induce anamnestic responses is now clear. New algorithms for the prediction of such sites exist and these can be tested experimentally with synthetic peptides. There are no major technical obstacles to the development of vaccines for parasites which cannot be overcome. However substantial long term basic research is needed over a range of disciplines to achieve this worthwhile objective.

Animals↗
PubMed2026

Red Flags for Differentiating Desmosomal "Hot-Phase" Cardiomyopathy From Acute Myocarditis.

BACKGROUND: Desmosomal "hot-phase" cardiomyopathy (HPC), characterized by bursts of myocardial inflammation mimicking acute myocarditis (AM), carries relevant risks of adverse outcomes. This study aimed to identify diagnostic "red flags" favoring HPC over AM. METHODS: Patients (n=134) receiving a first diagnosis of AM, proven by endomyocardial biopsy or cardiac magnetic resonance plus troponin elevation, were retrospectively identified at a referral center. HPC was defined by presence of pathogenic desmosomal gene variants (DGVs). Clinical, imaging, and electrical features were compared between HPC cases and controls with gene-negative AM to identify red flags. Diagnostic algorithms were derived and tested in an external multicenter cohort of DGV carriers (n=30). RESULTS: Patients with HPC (n=22; 91% DSP+) were more frequently female (73% versus 24%, P<0.001) and younger than unmatched controls with AM (32&#xb1;14 versus 41&#xb1;14&#x2009;years, P=0.007). When matched 1:1 by age, sex, and presentation, DGV carriers showed distinctive red flags: family history of cardiomyopathy/AM/sudden death; recurrent troponin peaks; persistent left ventricular systolic dysfunction; right ventricular involvement; ring-like late gadolinium enhancement; late gadolinium enhancement persistence or extension; low QRS voltages; life-threatening ventricular arrhythmias at <45&#x2009;years; persistent >1000/24&#x2009;hours ventricular ectopy; and recurrent nonsustained ventricular tachycardia. A "first-contact" algorithm based on female sex and age <30&#x2009;years achieved 77% accuracy, identifying 63% of DGV carriers in the external cohort. An alternative algorithm incorporating ring-like late gadolinium enhancement, right ventricular involvement, and family history showed higher accuracy (93%) and yield (93%). CONCLUSIONS: Myocarditis in DGV carriers predominantly affects young women. A red flag-based approach improves recognition of desmosomal HPC over classic AM.

Humans↗
PubMed1991

Epidemiology of Down syndrome in South Australia, 1960-89.

During 1960-89 687 Down syndrome live births and 46 Down syndrome pregnancy terminations were identified in South Australia. Ascertainment was estimated to be virtually complete. The sex distribution of Down syndrome live births was found to be statistically different from the non-Down syndrome live-birth sex distribution (P less than .01). Smoothed maternal age-specific incidence was derived using both maternal age calculated to the nearest month and a discontinuous-slope regression model. The incidence of Down syndrome at birth for the study period was estimated to be 1.186 Down syndrome births/1,000 live births. Annual population incidence was shown to be correlated with trends in the maternal age distribution of confinements. If current trends in the maternal age distribution of confinements continue, the population incidence of Down syndrome in South Australia is predicted to exceed 1.5 Down syndrome births/1,000 live births during the 1990-94 quinquennium.

Abortion, Spontaneous↗
PubMed1991

A maternal serum screen for trisomy 18: an extension of maternal serum screening for Down syndrome.

The feasibility of extending second-trimester maternal blood screening for Down syndrome so as to include screening for trisomy 18 was examined using stored maternal serum samples collected for neural tube-defect screening. There were 12 samples from trisomy 18 pregnancies and 390 controls. The median maternal serum concentration of alpha-fetoprotein, free alpha-subunit human chorionic gonadotrophin, free beta-subunit human chorionic gonadotrophin, intact human chorionic gonadotrophin, total estriol, unconjugated estriol, estradiol, human placental lactogen, and progesterone were lowered in those pregnancies affected by trisomy 18 when compared with unaffected pregnancies matched for racial origin, maternal age, gestational age, and sample-storage duration. At an estimated odds risk of 1:400, 83.3% of affected pregnancies were detected using an algorithm which combines the maternal age-related risk with the maternal serum concentrations of unconjugated estriol, free alpha-subunit human chorionic gonadotrophin, free beta-subunit human chorionic gonadotrophin, estradiol, and human placental lactogen. The associated false-positive rate was 2.6%. At high risk odds of 1:10, the detection rate was 58.3%, with an associated false-positive rate of 0.3%. beta-Subunit human chorionic gonadotrophin and unconjugated estriol were the most powerful discriminators. It is possible to incorporate into existing Down syndrome screening programs an algorithm for detecting trisomy 18 with high sensitivity and specificity.

Adult↗
PubMed1991

A parallel computing approach to genetic sequence comparison: the master-worker paradigm with interworker communication.

We have implemented a parallel version of a dynamic programming biological sequence comparison algorithm to study the potential applicability of using parallel computers for genetic sequence comparisons. Our parallel program is built using C-Linda, a machine-independent parallel programming language, and was tested on both a 10 CPU Sequent Symmetry and a 64 CPU Intel Hypercube. C-Linda implements a shared associative memory model, "tuple space," through which multiple processes can communicate and coordinate control. In our master-worker (MW) parallel implementation, a master process creates several worker processes, extracts a test sequence and multiple library sequences from a database and stores them in tuple space. Each worker reads the test sequence and then repeatedly extracts library strings from tuple space, performs pairwise sequence comparison using a local comparison algorithm to generate a similarity score, and returns the similarity scores to tuple space. The master collects the scores from tuple space and identifies the best match over all library sequences. We also implemented a method of global interworker communication to reduce the total search time by stopping those string comparisons that had no chance of improving on the current best match. Comparisons of the total run time, speedup, and efficiency were made for parallel and sequential versions of a basic MW implementation as well as versions with the global abort threshold.

Algorithms↗