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Record W2611168687 · doi:10.25011/cim.v30i4.2860

Genetic characterization of two autosomal recessive disorders, Majewski-like and cerebral atrophy syndromes

2007· article· en· W2611168687 on OpenAlexvenueaboutno aff
Piya Lahiry, John F. Robinson, Victoria Mok Siu, Erik G. Puffenberger, K. Strauss, R A Hegele, C. Anthony Rupar

Bibliographic record

VenueClinical and investigative medicine · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic and Kidney Cyst Diseases
Canadian institutionsnot available
Fundersnot available
KeywordsGeneticsLocus (genetics)BiologyCandidate geneMicrocephalyCerebral atrophyPsychomotor retardationPolydactylyDisease gene identificationPopulationAtrophyMedicineGenePathologyMutationExome sequencing

Abstract

fetched live from OpenAlex

Introduction: We recently identified two lethal recessive disorders segregating within the same Old Order Amish pedigree. The first disorder, Majewski-like syndrome (MLS), has features that overlap with both Majewski short rib-polydactyly syndrome and hydrolethalus syndrome. MLS is a lethal multi-system disorder that affects the development of the brain, adrenal glands, pituitary gland and bone. The second disorder, cerebral atrophy syndrome (CAS), is characterized by progressive and global loss of brain tissue. Affected children present early in life with microcephaly, seizures, and psychomotor retardation, and possess distinctive MRI findings. The objective of this study was to identify the genetic bases of these disorders to provide prompt and reliable diagnosis for families. Methods: Assuming recessive inheritance and mutation homogeneity (autozygosity), we used Affymetrix 10,000-single nucleotide polymorphism (10K-SNP) to genotype all affected individuals and identify candidate regions. SNP data were analyzed using Agilent GT autozygosity mapping software. LOD scores were used to identify candidate regions, and genes within these regions were prioritized for sequencing. Results and Conclusion: Because the Ontario Anabaptist population is relatively small, genetically isolated, and historically young, we were able to robustly map candidate regions using relatively low marker density and only a few affected individuals. Our preliminary data is consistent with the clinical observation that MLS and CAS segregate independently, as recessive conditions, within the pedigree. Thus far, we have sequenced 12 genes within the MLS locus, all of which were normal. For CAS, autozygosity mapping yielded two loci with comparable linkage scores, one of which contained no observable mutations. Once the causative mutations have been identified for MLS and CAS, we intend to study their population frequencies and also to pursue in vitro studies of gene and protein functions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.083
Threshold uncertainty score0.166

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.037
GPT teacher head0.307
Teacher spread0.271 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2007
Admission routes2
Has abstractyes

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