12 research outputs found
Clinical evaluation, biochemistry and genetic polymorphism analysis for the diagnosis of lactose intolerance in a population from northeastern Brazil
OBJECTIVE: This work aimed to evaluate and correlate symptoms, biochemical blood test results and single nucleotide polymorphisms for lactose intolerance diagnosis. METHOD: A cross-sectional study was conducted in Fortaleza, Ceará, Brazil, with a total of 119 patients, 54 of whom were lactose intolerant. Clinical evaluation and biochemical blood tests were conducted after lactose ingestion and blood samples were collected for genotyping evaluation. In particular, the single nucleotide polymorphisms C>;T-13910 and G>;A-22018 were analyzed by restriction fragment length polymorphism/polymerase chain reaction and validated by DNA sequencing. RESULTS: Lactose-intolerant patients presented with more symptoms of flatulence (81.4%), bloating (68.5%), borborygmus (59.3%) and diarrhea (46.3%) compared with non-lactose-intolerant patients (
Biomarkers of Environmental Enteropathy, Inflammation, Stunting, and Impaired Growth in Children in Northeast Brazil
Critical to the design and assessment of interventions for enteropathy and its developmental consequences in children living in impoverished conditions are non-invasive biomarkers that can detect intestinal damage and predict its effects on growth and development. We therefore assessed fecal, urinary and systemic biomarkers of enteropathy and growth predictors in 375 6–26 month-old children with varying degrees of malnutrition (stunting or wasting) in Northeast Brazil. 301 of these children returned for followup anthropometry after 2-6m. Biomarkers that correlated with stunting included plasma IgA anti-LPS and anti-FliC, zonulin (if >12m old), and intestinal FABP (I-FABP, suggesting prior barrier disruption); and with citrulline, tryptophan and with lower serum amyloid A (SAA) (suggesting impaired defenses). In contrast, subsequent growth was predicted in those with higher fecal MPO or A1AT and also by higher L/M, plasma LPS, I-FABP and SAA (showing intestinal barrier disruption and inflammation). Better growth was predicted in girls with higher plasma citrulline and in boys with higher plasma tryptophan. Interactions were also seen with fecal MPO and neopterin in predicting subsequent growth impairment. Biomarkers clustered into markers of 1) functional intestinal barrier disruption and translocation, 2) structural intestinal barrier disruption and inflammation and 3) systemic inflammation. Principle components pathway analyses also showed that L/M with %L, I-FABP and MPO associate with impaired growth, while also (like MPO) associating with a systemic inflammation cluster of kynurenine, LBP, sCD14, SAA and K/T. Systemic evidence of LPS translocation associated with stunting, while markers of barrier disruption or repair (A1AT and Reg1 with low zonulin) associated with fecal MPO and neopterin. We conclude that key noninvasive biomarkers of intestinal barrier disruption, LPS translocation and of intestinal and systemic inflammation can help elucidate how we recognize, understand, and assess effective interventions for enteropathy and its growth and developmental consequences in children in impoverished settings
Fecal MPO, Fecal alpha-1-antitrypsin (A1AT), and plasma LPS, FABP and SAA each predicts subsequent growth impairment.
<p>a: For MPO, <i>p</i> = 0.028; n = 266 when correcting for age and gender, and independent of breastfeeding status (that showed no correlation in these 6-26m old children) and of age. b: For A1AT, n = 237; <i>p</i> = 0.042; and A1AT also correlates with “catchup WAZ” as well, <i>p</i> = 0.035 after correcting for age and gender. c: For urine L/M, higher values correlated (controlling for age and gender) with impaired growth (delta HAZ) (<i>r</i> = -0.173; <i>p</i> = 0.009; n = 230). d: For plasma LPS (ie lower LUM), higher values correlated with impaired growth (delta HAZ) (<i>r</i> = 0.151; <i>p</i> = 0.017; n = 251). e: For plasma FABP, higher values correlated with impaired growth (delta HAZ) (r = -0.134; <i>p</i> = 0.042; n = 231). f: For plasma SAA, higher values correlated with impaired growth (delta HAZ) (r = -0.132; p = 0.046; n = 231).</p
Path model, using Principle Components Analyses (Equamax rotation solution maximizing independence of groups) showing associations among 1) Barrier (green), 2) Local Gut (orange) and 3) Systemic (pink) sets of biomarkers, as well as their predictive utility regarding linear growth.
<p>Path model, using Principle Components Analyses (Equamax rotation solution maximizing independence of groups) showing associations among 1) Barrier (green), 2) Local Gut (orange) and 3) Systemic (pink) sets of biomarkers, as well as their predictive utility regarding linear growth.</p
Cluster dendrogram with Pearson correlations among those biomarkers with ≥274 values showing three main groups: 1) translocation markers, LPS and IgA and IgG anti-LPS or FliC as well as zonulin and the 2 potential predictors of subsequent growth, tryptophan and citrulline; 2) predominantly systemic responses to disrupted barrier function and translocation; and 3) markers of specific intestinal barrier disruption or local intestinal inflammation.
<p>As discussed, groups 1 and 3 may predispose to group 2 systemic responses in associating with each other as shown in the heat map as would fit our concept of the pathogenesis of enteropathy.</p
Demographic information for study participants (Children and caregivers; n = 375 at study start, except where otherwise noted).
<p>Demographic information for study participants (Children and caregivers; n = 375 at study start, except where otherwise noted).</p
Frequencies of biomarker testing, including 13 tests on plasma, 4 on fecal and L/M absorption testing on urine as shown.
<p>*Of 326 children with samples obtained within 1 month of study start.</p
Heat map showing all significant partial Pearson correlations of barrier and systemic biomarkers with HAZ or WAZ at enrollment (ie. study start, ss) or with changes in (Δ) HAZ or WAZ.
<p>Significant correlations (at p<0.05; * = p<0.01) between biomarkers and growth, controlling for child age and gender. HAZ = height for age Z score; WAZ = weight for age z score; ss = study start; Δ = change in HAZ or WAZ at 2-6m followup; numbers range from 230 to 292 except for zonulin at age >12m where n = 172. Full r, p and df values are provided in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0158772#pone.0158772.s002" target="_blank">S1 Table</a>.</p