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Record W3152412374

Role of modifier gene SLC6A14 in Cystic Fibrosis and the path to personalized medicine

2018· dissertation· en· W3152412374 on OpenAlexaboutno aff
Saumel B Ahmadi

Bibliographic record

VenueTSpace · 2018
Typedissertation
Languageen
FieldMedicine
TopicCystic Fibrosis Research Advances
Canadian institutionsnot available
Fundersnot available
KeywordsCystic fibrosisPersonalized medicineMedicineInternal medicineBioinformaticsBiology
DOInot available

Abstract

fetched live from OpenAlex

Cystic Fibrosis (CF) is the most common fatal genetic disorder in Canada. It is a multi-system disorder caused by mutations in the CFTR gene, expressed in epithelial tissues. Decrease in lung function over time is the most common cause of morbidity and mortality in CF. However, affliction to other organs systems like the gastro-intestinal system, also contributes to significant disease burden. Variation in disease severity among CF patients is well established, attributable to CFTR gene and modifier gene mutations. There are over 2,000 disease causing mutations in the CFTR gene. F508del is the most common CF causing mutation present on at least one allele in 90% of the CF population. However, patients bearing the same F508del mutation on both alleles also exhibit a tremendous variation in disease severity, which has been attributed to modifier gene mutations. Two FDA approved drugs that work directly on CFTR protein – Ivacaftor and Lumacaftor, are shown to have a heterogenous response in CF patients. The heterogeneity in response has also been attributed to modifier genes. With a greater understanding of modifier genes and CFTR genetics, the variation in patient responses to currently available CF therapies could be explained. This has led to efforts for in vitro phenotypic profiling of individual patient derived tissues, in the context of CF. Towards this we developed the apical CFTR conductance assay, to measure CFTR function in vitro using cultured airway epithelia from individual patients. Later we applied this technology to murine intestinal tissue to understand the mechanism of a genetic modifier of Cystic Fibrosis – SLC6A14, which was a top hit in a recent genome wide association study. Using a murine CF model and a SLC6A14 knockout mouse, we discovered that SLC6A14 modifies the intestinal phenotype of CF by regulating the fluid secretory capacity of the CF affected epithelium, via the nitric-oxide pathway. Thus, we explored the biologic basis of SLC6A14 as a modifier of CF. Taken together, the studies described in this thesis will facilitate the path towards personalized medicine in CF.

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)0.001
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.014
GPT teacher head0.355
Teacher spread0.341 · 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
Published2018
Admission routes1
Has abstractyes

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