Human milk is a complex fluid comprised of myriad substances, with one of the most abundant substances being a group of complex carbohydrates referred to as human milk oligosaccharides (HMOs). There ...has been some evidence that HMO profiles differ in populations, but few studies have rigorously explored this variability.
We tested the hypothesis that HMO profiles differ in diverse populations of healthy women. Next, we examined relations between HMO and maternal anthropometric and reproductive indexes and indirectly examined whether differences were likely related to genetic or environmental variations.
In this cross-sectional, observational study, milk was collected from a total of 410 healthy, breastfeeding women in 11 international cohorts and analyzed for HMOs by using high-performance liquid chromatography.
There was an effect of the cohort (
< 0.05) on concentrations of almost all HMOs. For instance, the mean 3-fucosyllactose concentration was >4 times higher in milk collected in Sweden than in milk collected in rural Gambia (mean ± SEM: 473 ± 55 compared with 103 ± 16 nmol/mL, respectively;
< 0.05), and disialyllacto-
-tetraose (DSLNT) concentrations ranged from 216 ± 14 nmol/mL (in Sweden) to 870 ± 68 nmol/mL (in rural Gambia) (
< 0.05). Maternal age, time postpartum, weight, and body mass index were all correlated with several HMOs, and multiple differences in HMOs e.g., lacto-
-neotetrose and DSLNT were shown between ethnically similar (and likely genetically similar) populations who were living in different locations, which suggests that the environment may play a role in regulating the synthesis of HMOs.
The results of this study support our hypothesis that normal HMO concentrations and profiles vary geographically, even in healthy women. Targeted genomic analyses are required to determine whether these differences are due at least in part to genetic variation. A careful examination of sociocultural, behavioral, and environmental factors is needed to determine their roles in this regard. This study was registered at clinicaltrials.gov as NCT02670278.
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CMK, GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Neonatal gastrointestinal (GI) bacterial community structure may be related to bacterial communities of the mother, including those of her milk. However, very little is known about the diversity in ...and relationships among complex bacterial communities in mother-infant dyads.
Our primary objective was to assess whether microbiomes of milk are associated with those of oral and fecal samples of healthy lactating women and their infants.
Samples were collected 9 times from day 2 to 6 mo postpartum from 21 healthy lactating women and their infants. Milk was collected via complete breast expression, oral samples via swabs, and fecal samples from tissue (mothers) and diapers (infants). Microbiomes were characterized using high-throughput sequencing of the 16S ribosomal RNA (rRNA) gene. Alpha and beta diversity indices were used to compare microbiomes across time and sample types. Membership and composition of microbiomes were analyzed using nonmetric multidimensional scaling and canonical correlation analysis (CCA). The contribution of various bacterial communities of the mother-infant dyad to both milk and infant fecal bacterial communities were estimated using SourceTracker2.
Bacterial community structures were relatively unique to each sample type. The most abundant genus in milk and maternal and infant oral samples was Streptococcus (47.1% ± 2.3%, 53.9% ± 1.3%, and 69.1% ± 1.8%, respectively), whereas Bacteroides were predominant in maternal and infant fecal microbiomes (22.9% ± 1.3% and 21.4% ± 2.4%, respectively). The milk microbiome was more similar to the infant oral microbiome than the infant fecal microbiome. However, CCA suggested strong associations between the complex microbial communities of milk and those of all other sample types collected.
These findings suggest complex microbial interactions between breastfeeding mothers and their infants and support the hypothesis that variation in the milk microbiome may influence the infant GI microbiome.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The utilization of (13)C-labeled vaccenic acid (VA) by lactating dairy cows to synthesize cis-9, trans-11 conjugated linoleic acid (CLA) was investigated. Primiparous ruminally cannulated Holstein ...cows (n = 3) were abomasally infused with 1.5 g of VA-1-(13)C. Blood and milk samples were taken frequently before and after VA infusion. Milk and plasma lipid were extracted using chloroform:methanol. Plasma lipid was separated into triacylglycerol (TG), cholesterol ester (CE), phospholipid (PL), nonesterified fatty acid (NEFA), and mono- and diacylglycerol (MDG) fractions. Lipid was methylated, converted to dimethyl disulfide and Diels-Alder adducts, and analyzed by GC-MS. Increased enrichment of (13)C was determined using a 2-sample t test for each sample time compared with -24 h, with significance declared at P < 0.05. Enrichment in milk fat VA was detected at 4 (3.0%), 8 (8.3%), 12 (4.1%), 16 (2.2%), and 20 h (0.8%). Enrichment in VA was also detected in plasma TG, NEFA, PL, and MDG. Enrichment in milk fat cis-9, trans-11 CLA, the Delta9-desaturase product of VA, was detected at 4 (2.6%), 8 (6.6%), 12 (3.4%), 16 (1.7%), and 24 h (0.7%). Enrichment was not detected in cis-9, trans-11 CLA for any plasma lipid fraction. Modeling of the data showed the exponential decay in (13)C enrichment over time for both VA and cis-9, trans-11 CLA in milk fat. Conversion of dietary VA to cis-9, trans-11 CLA endogenously was confirmed with the mammary gland being the primary site of Delta9-desaturase activity; approximately 80% of milk fat cis-9, trans-11 CLA originated from VA.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The fecal microbiota has been characterized in some adult populations, but little is known about its community structure during lactation.
We characterized the maternal fecal microbiome during ...lactation and explored possible mediating factors such as nutrition.
Fecal samples were collected from 20 lactating women from 2 d to 6 mo postpartum, and bacterial taxa were characterized with the use of high-throughput sequencing. Bacterial community structure (at each taxonomic level) and relations between bacterial taxa and environmental and dietary variables were visualized and analyzed with the use of stacked bar charts, principal component analysis, and multivariate analyses such as nonmetric multidimensional scaling and canonical correlation analysis.
Complex bacterial community structure was somewhat similar to those previously published for other adult populations (although there were some notable differences), and there were no clear associations with time postpartum or anthropometric or environmental variables. However, Spearman rank correlations suggested that increased intake of pantothenic acid, riboflavin, vitamin B-6, and vitamin B-12 were related to increased relative abundance of Prevotella (r = 0.45, 0.39, 0.34, and 0.24, respectively; P ≤ 0.01) and decreased relative abundance of Bacteroides (r = -0.55, -0.46, -0.32, and -0.35, respectively; P ≤ 0.01). Intakes of copper, magnesium, manganese, and molybdenum were positively associated with Firmicutes (r = 0.33, 0.38, 0.44, and 0.51, respectively; P ≤ 0.01) and negatively associated with Bacteroidetes (r = -0.38, -0.44, -0.48, and -0.53, respectively; P ≤ 0.01). Overall, data consistently suggest that increased consumption of a more nutrient- and calorie-rich diet was positively associated with relative abundance of Firmicutes.
The fecal microbiome of lactating women is relatively stable in the postpartum period and somewhat similar to that of other adult populations. Variation in dietary constituents may be related to that of relative abundance of individual bacterial taxa. Controlled dietary intervention studies will be required to determine whether these associations are causal in nature.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The human milk microbiome has been somewhat characterized, but little is known about changes over time and relations with maternal factors such as nutrient intake.
We sought to characterize the human ...milk microbiome and described associations with maternal nutrient intake, time postpartum, delivery mode, and body mass index (BMI; in kg/m2).
Milk samples (n = 104) and 24-h diet recalls were collected 9 times from 21 healthy lactating women from day 2 to 6 mo postpartum. Women were classified by BMI as healthy weight (<25) or overweight or obese (≥25). Bacterial taxa were characterized with the use of the high-throughput sequencing of the 16S ribosomal RNA gene.
The milk microbiome was relatively constant over time, although there were small changes in some of the lesser-abundant genera. Relative abundances of several taxa were associated with BMI, delivery mode, and infant sex. For instance, overweight and obese mothers produced milk with a higher relative abundance of Granulicatella than did healthy-weight women (1.8% ± 0.6% compared with 0.4% ± 0.2%, respectively; P < 0.05). Relative abundances of several bacterial taxa were also associated with variations in maternal dietary intake. For example, intakes of saturated fatty acids (rs = −0.59; P = 0.005) and monounsaturated fatty acids (rs = −0.46; P = 0.036) were inversely associated with the relative abundance of Corynebacterium; total carbohydrates (rs = −0.54; P = 0.011), disaccharides (rs = −0.47; P = 0.031), and lactose (rs = −0.51; P = 0.018) were negatively associated with Firmicutes; and protein consumption was positively correlated with the relative abundance of Gemella (rs = 0.46; P = 0.037).
Factors associated with variations in the human milk microbiome are complex and may include maternal nutrient intake, maternal BMI, delivery mode, and infant sex. Future studies designed to investigate the relation between maternal nutrient intake and the milk microbiome should strive to also evaluate dietary supplement usage and analyze the collected milk for its nutrient content.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Rituximab was approved by the United States Food and Drug Administration (FDA) as a first-line agent for treatment of advanced diffuse large B-cell lymphoma (DLBCL) in February 2006. We conducted ...this population-based study to determine if the results from the clinical trials have translated into survival benefit in the general population.
We selected patients with advanced diffuse large B-cell lymphoma from the Surveillance, Epidemiology, and End RESULTS (SEER) 18 database, and calculated relative survival rates for patients diagnosed from 2002-2005 (pre-rituximab) and 2006-2009 (post-rituximab). We used the Z-test in the SEER*Stat to compare relative survival rates of patients categorized by race (White, Black, or Others), gender (male, female), and age groups (<60, 60+ years).
One-year relative survival in Whites and Others improved significantly in the post-rituximab era compared to the pre-rituximab era (64.80±0.6% vs. 61.3±0.6%; p=0.0002 and 64.5±1.9% vs. 54.9±2.2%; p=0.0011, respectively). The 3-year relative survival improved significantly in Whites and Others in the post-rituximab era compared to the pre-rituximab era (53.7±0.7% vs. 50.3±0.7%; p=0.0001 and 52.0±2.3% vs. 40.8±2.3%; p=0.0002, respectively). However, no significant improvements were observed in 1-year and 3-year relative survival in Blacks, and in young males during the post-rituximab era compared to the pre-rituximab era.
The relative survival rates among young males and 'Black' patients with advanced diffuse large B-cell lymphoma have not improved during the post-rituximab era.
Abstract
Disparities in cancer care have been documented. However, less is known about the disparities in diffuse large B-cell lymphoma (DLBCL). We reviewed the Surveillance, Epidemiology and End ...Results database to evaluate disparities in receipt of radiotherapy (RT) and relative survival among patients diagnosed with stage I DLBCL between 1998 and 2008 on the basis of age, sex and ethnicity. African Americans and other races were significantly less likely to receive RT compared to Caucasians (adjusted odds ratio OR of 0.743 and 0.81, respectively). Similarly, patients aged 60 + years and males were less likely to receive RT compared to their counterparts (p < 0.001). Caucasian race, younger age and female sex were associated with better survival among patients receiving RT. This study showed that 38.2% of patients with stage I DLBCL received radiotherapy. Survival rates were significantly higher for patients who received RT.
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DOBA, IJS, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
The primary objective was to determine if Angus bull fertility varied by number of sperm inseminated. A secondary objective was to characterize the potential impact of random variation on fertility ...using two identical sperm per dose treatments, which differed only in straw color. Computer-assisted sperm analysis (CASA) and flow cytometry (FC) were used to identify post-thaw sperm characteristics associated with field fertility differences between bulls. Ejaculates from five Angus bulls were collected, extended, and cryopreserved at 10, 20, 20 or 40 × 106 sperm per dose in color-coded 0.5-mL French straws. Multiparous cows (n = 4866) from ten Brazilian farms were synchronized for first-service timed artificial insemination (TAI). Bull identification and straw color were recorded at TAI. Pregnancy per TAI (P/TAI) did not differ between sperm doses (43.8, 45.3, 43.8 and 47.1% for 10, 20, 20 or 40 × 106 sperm respectively; P = 0.31) nor was there an interaction between bull and dose (P = 0.53). The P/TAI differed between bulls and ranged from 40.7 to 48.1% (P < 0.01). The overall P/TAI between the two control groups were not different (45.3 vs 43.8%); however, the numerical variation within bull ranged from 0.5 to 4.9 percentage points. Numerous CASA and FC post-thaw sperm characteristics differed among bulls (P < 0.05), but these characteristics did not explain the fertility difference between bulls. Principal component analysis provided a multivariate description of the CASA and FC data, where three principal components (Prin1, Prin2, and Prin3) accounted for a combined total of 88.7% of the data variability. The primary components of each PCA axis were flow cytometric measures of sperm viability and DNA fragmentation (Prin1), and CASA-derived sperm movement patterns (Prin2) and motility (Prin3); however, the relative influence of these characteristics varied by bull. Although fertility differences between bulls were detected, neither sperm per dose nor post-thaw in vitro sperm analyses (CASA and FC) were able to explain the observed differences in field fertility between bulls, further illustrating the difficulties in predicting bull fertility.
•The objective was to determine if bull fertility varied by sperm dose inseminated.•Treatments were 10, 20 and 40 × 106 sperm per dose.•Pregnancy per timed AI did not differ between sperm doses.•Pregnancy per timed AI was different between bulls.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Rituximab was approved by FDA as first line agent for treatment of advanced diffuse large B-cell lymphoma (DLBCL) on February 2006. We conducted this population based study to determine if the ...results from clinical trials have translated into survival benefit in general population.
We selected patients with advanced diffuse large B cell lymphoma (Distant stage based on LRD Summary Staging 1998+ in SEER*Stat) from Surveillance, Epidemiology, and End Results (SEER) 18 database (1973-2010), and calculated relative survival rates for patients diagnosed from 2002-2005(pre-rituximab) and March 2006 to 2009 (post-rituximab). We used Z-test in the SEER*Stat to compare the relative survival rates in cohorts categorized by race (white, black and other), gender, and age groups (<60 and 60+). The “Cansurv” software, and specifically, Cox proportional hazard function were used to investigate the influence of age (<60 ; 60+ years), sex (male; female), race (white; black; others) and marital status (married; single; separated/divorced/widowed) on the relative survival.
A total of 15627 patients with advanced stage DLBCL as the only primary cancer were identified. Patients were predominantly white of non-Hispanic, non-Spanish/non-Latino origin, males, belonging to the older age category and married. The median age at the diagnosis was 65 years. One-year relative survival in ‘Whites' and ‘Others' improved significantly in post-rituximab era compared to pre-rituximab era (64.80 ± 0.6% vs 61.3 ± 0.6%; p= 0.0002 and 64.5 ± 1.9% vs 54.9 ± 2.2%; p= 0.0011, respectively). Also, three year relative survival improved significantly in ‘Whites' and ‘Others' in post-rituximab era compared to pre-rituximab era (53.7 ± 0.7% vs 50.3 ± 0.7%; p= 0.0001 and 52.0 ± 2.3% vs 40.8 ± 2.3%; p= 0.0002, respectively). However, no significant improvement were observed in one-year and three-year relative survival in blacks, during post rituximab era comapared to pre-rituximab era. Interestingly, in pre-rituximab era, relative survival in blacks was comparable to that of whites, but it was significantly better than that of others (p<.05).
Although there was significant improvement in one- and three-year relative survival in young females, old males and old females, no significant improvement (p>.05) in survival was observed in the young males. Factors such as young age, female sex, non-Hispanic origin, white race, married status and post-rituximab era were associated with significantly better survival (p<.05).
The relative survival rates among young males and black patients with advanced diffuse large B cell lymphoma has not improved during post-rituximab era.
No relevant conflicts of interest to declare.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
There is scarcity of data on differences in survival in acute myeloid leukemia (AML) patients by ethnicity. We utilized data from the Surveillance Epidemiology and End Result (SEER) database to ...investigate the ethnic disparities of survival in general U.S. population.
The SEER-18 Registry was used to identify adult (>=18) patients with AML as the only or the first primary cancer diagnosed from 1992 to 2010. We only included cases which were microscopically confirmed and actively followed. Cases that were alive without survival time, those resulted in death certificate/autopsy, and those with ethnicity recorded as unknown were excluded from this study. A total of 29,477 patients (54.5% males) were identified. For the subsequent analyses, various cohorts were formed. Age group cohorts included: 18-44 (5394; 18.3%), 45-54 (3751; 12.7%), 55-64 (4913; 16.7%), 65-74 (6513; 22.1%) and 75+ (8906; 30.2%). The total study period was divided into four groups, 1992-1995 (3409; 11.6%), 1996-2000 (5816; 19.7%), 2001-2005 (9984; 33.9%) and 2006-2010 (10268; 34.8%) for the survival analyses over time. Ethnic stratification used included White (21338; 72.4%), African American (AA: 2322; 7.9%), Asians/Pacific Islanders (A/PI: 2389; 8.1%), Native American/Alaskan Natives (NA/AN: 137; 0.5%) and Hispanics (3291; 11.2%). NA/AN categories were excluded from the final analysis due to their small numbers. Kaplan Meier (KM) curve and log rank test were used to evaluate association between patient characteristics and survival in overall population, OS, and AML-specific survival(AMLSS). Cox proportional hazards model was used for the analysis of association between patient characteristics and survival. Statistical analyses were carried out using SPSS version 16.0.0
Median age at diagnosis for the patient population was 66 years. Median follow-up period was 6.17 years for the whole population.
Median OS for whole population was 6 months with highest survival among Hispanics and lowest among Whites (10 months versus 5 months, p <0.001). The AMLSS was highest for Hispanics and lowest for Whites (24 months versus 12 months, p <0.001). Median OS and AMLSS deteriorated significantly with advancing age (p<0.001). The median OS and AMLSS were the same for males and females (p>0.05), in overall population. OS for females were better than males among AA and Hispanic patients (p value <0.001). AMLS survival was better for A/PI females compared to males (median AMLSS 22 months vs. 17 months, p =0.015). When comparing survival among year of diagnosis cohorts, OS as well as AMLSS were comparable among 1992-1995 and 1996-2000 cohorts, (p>0.05); however, there was a gradual improvement in the more recent time period cohorts.
Results of the proportional hazard models indicated that when compared to Whites, the OS was best for A/PI and worst for AA patients (HR= 0.933, p= 0.006, and HR = 1.139, p <0.001 ,respectively). The OS was higher for females, younger patients, and for patients diagnosed during recent time period cohorts. Similarly, AMLS survival among Hispanics and AA was comparable to whites and, best for Asians/PI (HR 0.911, p =0.003).
This study demonstrated significant differences in survival rates among AML patients belonging to various ethnic groups with highest OS and AMLSS among A/PI AML patients.
No relevant conflicts of interest to declare.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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