Clinical and environmental influences on metabolic biomarkers collected for newborn screening

Abstract

Objectives Identifying common clinical and environmental factors that influence newborn metabolic biomarkers will improve the utilization of metabolite panels for clinical diagnostic medicine. Design and Methods Environmental effects including gender, season of birth, gestational age, birth weight, feeding method and age at time of collection were evaluated for over 50 metabolites collected by the Iowa Neonatal Metabolic Screening Program on 221,788 newborns over a six year period. Results We replicated well known observations that low birth weight and preterm infants have higher essential amino acids and lower medium and long chain acylcarnitine levels than their term counterparts. Smaller, but still significant, differences were observed for gender and timing of sample collection, specifically the season in which the infant was born. Most intriguing were our findings of higher thyroid stimulating hormone in the winter months (P<1×10−40) which correlated with an increased false positive rate of congenital hypothyroidism in the winter (0.9%) compared to summer (0.6%). Previous studies, conducted globally, have identified an increased prevalence of suspected and confirmed cases of congenital hypothyroidism in the winter months. We found that the percentage of unresolved suspected cases were slightly higher in the winter (0.3% vs 0.2%). Conclusions We identified differences in metabolites by gestational age, birth weight, gender and season. Some are widely reported such as gestational age and birth weight, while others such as the effect of seasonality are not as well studied.

Metabolomics of prematurity: analysis of patterns of amino acids, enzymes, and endocrine markers by categories of gestational age

“…A potential limitation of the study is the possible impact of unmeasured confounding on the relationship between category of prematurity and analyte levels. While we were able to explore the effects of factors such as sex, birth weight, timing of sample collection, receipt of transfusion, and feeding status, other potential confounders may have distorted the relationship between category of prematurity and analyte level (8,14,22). Therefore, the relationships we observed in this study are best interpreted as associations between analytes and prematurity, or factors associated with prematurity such as catabolism, immaturity of enzyme systems, and organ development.…”

“…No trends were noted in the enzymes measured. Although differences in metabolic profile by degree of prematurity have been previously observed, this previous work has primarily focused on how GA may contribute to increased false-positive rates, with the goal of improving the precision of newborn screening in this population (8,9,14). In addition to this important objective, we propose that examining the specific analytes whose levels are influenced by prematurity Articles Wilson et al…”

“…No trends were noted in the enzymes measured. Although differences in metabolic profile by degree of prematurity have been previously observed, this previous work has primarily focused on how GA may contribute to increased false-positive rates, with the goal of improving the precision of newborn screening in this population (8,9,14). In addition to this important objective, we propose that examining the specific analytes whose levels are influenced by prematurity 17-OhP, 17-hydroxyprogesterone; ALA, alanine; ARG, arginine; BIO, biotinidase; CIT, citruline; GALT, galactose 1 phosphate uridyl transferase; GLY, glycine; IRT, immunoreactive trypsinogen; LeU, leucine; MeT, methionine; ORN, ornithine; Pct diff, percent difference; Phe, phenylalanine; Std diff, standardized difference; TSh, thyrotropin-stimulating hormone; TYR, tyrosine; VAL, valine.…”

Analysis and interpretation of acylcarnitine profiles in dried blood spot and plasma of preterm and full-term newborns

“…Defining cutoffs and ranges for these analytes, and ratios between them, for the purpose of newborn screening is challenging, but has recently been validated thanks to international cooperation (7). As reported by Zytkovicz and Ryckman (9,35), preterm infants represent a population that contributes significantly to the false positive rate. There are many reasons for this, including endogenous and metabolic differences due to their lower BW and immaturity, or the effects of treatments administered at the NICU.…”

Damaged goods?: an empirical cohort study of blood specimens collected 12 to 23 hours after birth in newborn screening in California

“…One is the potential increase of false positives (normal screening results reported as positive results) caused by surging endocrine (especially thyroid-stimulating hormone levels) and metabolic imbalances as the result of underdeveloped biological systems and/or birth stress-an effect that is exaggerated in premature or sick babies. [14][15][16][17][18] The increase of false positives is associated with perceived increased burden on parents/families and the health-care system. The other concern is the potential increase of false negatives (true cases reported as negative screening results).…”