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Record W7161944009 · doi:10.82308/20153

An exploration of the contribution of paraoxonase 1 genetic variants, homocysteine, and nutritional factors on the risk of small-for-gestational age birth

2012· dissertation· en· W7161944009 on OpenAlexaboutno aff
Laura Maclagan

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicParaoxonase enzyme and polymorphisms
Canadian institutionsnot available
Fundersnot available
KeywordsPON1Small for gestational ageParaoxonasePopulationBirth weightHyperhomocysteinemiaHomocysteineLow birth weight

Abstract

fetched live from OpenAlex

Small-for-gestational age (SGA) births are defined as babies who are born at less than the 10th percentile of weight for their sex and gestational age based on population growth standards1. SGA babies may be at risk for type II diabetes, cardiovascular disease, and hypertension later in life, although the exact biological mechanisms behind SGA birth are not fully understood1. Paraoxonase 1 (PON1) genetic variants are known to influence the ability of PON1 enzymes to prevent oxidative damage by hydrolyzing phospholipids, lipid peroxide by-products, and amino acid by-products such as homocysteine (Hcy)2. Infante-Rivard has previously shown that PON1 polymorphisms and Hcy concentrations (albeit in an unexpected protective direction for the latter) are associated with SGA birth3-4, however, their joint contribution to the risk of SGA birth has not been studied. The objective of this thesis is to explore the gene-environment interactions between three functional PON1 variants and plasma Hcy concentrations as well as food folate consumption (lentils) and folic acid vitamin supplementation on the risk of SGA birth. The present study uses data from births of infants at a university hospital in Montreal, Quebec. 493 case mothers and 472 control mothers provided informed consent to participate in the study. Cases were SGA babies born from May 1998 to June 2000, and controls were appropriate-for-gestational-age (AGA) babies born at the same hospital during the same time period4. Three PON1 genetic variants were analyzed in this study (C108T, L55M and Q192R). Information regarding Hcy concentrations and nutritional variables such as lentil and folate-containing vitamin consumption was collected and analyzed. Case-control, case-only and case-parent trio study designs were used and the data analyzed using unconditional logistic regression and Poisson log-linear models.Results indicate that mothers with wild type PON1 108CC genotypes and high Hcy concentrations (≥ 90th percentile) may be protected against SGA birth compared to those with lower Hcy concentrations (<90th percentile) after adjustment for gestational age, sex of the fetus, and ethnicity (OR=0.52, 95% CI [0.25, 1.05]). This effect was shown to be similar for the PON1 L55M polymorphism, in both maternal and fetal models. Individuals with the PON1 55MM genotype and high Hcy levels were shown to be at an increased risk of SGA birth compared to those with low Hcy levels after adjustment for the same covariates (maternal model, OR=1.38, 95% CI [0.46, 4.17]). Results from case-only and case-parent trio designs generally concur with those of the case-control study design. PON1 polymorphisms appear to modify the effect of Hcy on the risk of SGA birth; however, the results of this study are generally non-significant and more work is needed to characterize this relationship as well as the biological mechanism behind this effect.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.259
Threshold uncertainty score0.495

Codex and Gemma teacher scores by category

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

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 head0.023
GPT teacher head0.261
Teacher spread0.238 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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".

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Citations0
Published2012
Admission routes1
Has abstractyes

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