Randomized 20-year infancy-onset dietary intervention, life-long cardiovascular risk factors and retinal microvasculature.

BACKGROUND AND AIMS: Retinal microvasculature characteristics predict cardiovascular morbidity and mortality. This study investigated associations of lifelong cardiovascular risk factors and effects of dietary intervention on retinal microvasculature in young adulthood. METHODS: The cohort is derived from the longitudinal Special Turku Coronary Risk Factor Intervention Project study. The Special Turku Coronary Risk Factor Intervention Project is a 20-year infancy-onset randomized controlled dietary intervention study with frequent study visits and follow-up extending to age 26 years. The dietary intervention aimed at a heart-healthy diet. Fundus photographs were taken at the 26-year follow-up, and microvascular measures [arteriolar and venular diameters, tortuosity (simple and curvature) and fractal dimensions] were derived (n = 486). Cumulative exposure as the area under the curve for cardiovascular risk factors and dietary components was determined for the longest available time period (e.g. from age 7 months to 26 years). RESULTS: The dietary intervention had a favourable effect on retinal microvasculature resulting in less tortuous arterioles and venules and increased arteriolar fractal dimension in the intervention group when compared with the control group. The intervention effects were found even when controlled for the cumulative cardiovascular risk factors. Reduced lifelong cumulative intake of saturated fats, main target of the intervention, was also associated with less tortuous venules. Several lifelong cumulative risk factors were independently associated with the retinal microvascular measures, e.g. cumulative systolic blood pressure with narrower arterioles. CONCLUSIONS: Infancy-onset 20-year dietary intervention had favourable effects on the retinal microvasculature in young adulthood. Several lifelong cumulative cardiovascular risk factors were independently associated with retinal microvascular structure.

Association of Serum Trimethylamine-N-Oxide Concentration from Childhood to Early Adulthood with Age and Sex.

BACKGROUND: Primary prevention is the cornerstone of cardiometabolic health. In the randomized, controlled Special Turku Coronary Risk Factor Intervention Project (STRIP), dietary counseling intervention was given to children from infancy to 20 years of age and a follow-up was completed at age 26 years. We investigated the associations of age, sex, gut microbiome, and dietary intervention with the gut metabolite and the cardiac biomarker trimethylamine-N-oxide (TMAO). METHODS: Overall, 592 healthy participants (females 46%) from STRIP were investigated. Compared to the control group, the intervention group had received dietary counseling between ages 7 months and 20 years focused on low intakes of saturated fat and cholesterol and the promotion of fruit, vegetable, and whole-grain consumption. TMAO serum concentrations were measured by a liquid chromatography-tandem mass spectrometry method at ages 11, 13, 15, 17, 19, and 26 years. Microbiome composition was assessed using 16S rRNA gene sequencing at 26 years of age. RESULTS: TMAO concentrations increased from age 11 to 26 years in both sexes. At all measurement time points, males showed significantly higher serum TMAO concentrations compared to females, but concentrations were similar between the intervention and control groups. A direct association between TMAO concentrations and reported fiber intake was found in females. Gut microbiome analysis did not reveal associations with TMAO. CONCLUSIONS: TMAO concentration increased from childhood to early adulthood but was not affected by the given dietary intervention. In females, TMAO concentrations could be directly associated with higher fiber intake suggesting sex-specific differences in TMAO metabolism.

Exploring machine learning strategies for predicting cardiovascular disease risk factors from multi-omic data.

BACKGROUND: Machine learning (ML) classifiers are increasingly used for predicting cardiovascular disease (CVD) and related risk factors using omics data, although these outcomes often exhibit categorical nature and class imbalances. However, little is known about which ML classifier, omics data, or upstream dimension reduction strategy has the strongest influence on prediction quality in such settings. Our study aimed to illustrate and compare different machine learning strategies to predict CVD risk factors under different scenarios. METHODS: We compared the use of six ML classifiers in predicting CVD risk factors using blood-derived metabolomics, epigenetics and transcriptomics data. Upstream omic dimension reduction was performed using either unsupervised or semi-supervised autoencoders, whose downstream ML classifier performance we compared. CVD risk factors included systolic and diastolic blood pressure measurements and ultrasound-based biomarkers of left ventricular diastolic dysfunction (LVDD; E/e' ratio, E/A ratio, LAVI) collected from 1,249 Finnish participants, of which 80% were used for model fitting. We predicted individuals with low, high or average levels of CVD risk factors, the latter class being the most common. We constructed multi-omic predictions using a meta-learner that weighted single-omic predictions. Model performance comparisons were based on the F1 score. Finally, we investigated whether learned omic representations from pre-trained semi-supervised autoencoders could improve outcome prediction in an external cohort using transfer learning. RESULTS: Depending on the ML classifier or omic used, the quality of single-omic predictions varied. Multi-omics predictions outperformed single-omics predictions in most cases, particularly in the prediction of individuals with high or low CVD risk factor levels. Semi-supervised autoencoders improved downstream predictions compared to the use of unsupervised autoencoders. In addition, median gains in Area Under the Curve by transfer learning compared to modelling from scratch ranged from 0.09 to 0.14 and 0.07 to 0.11 units for transcriptomic and metabolomic data, respectively. CONCLUSIONS: By illustrating the use of different machine learning strategies in different scenarios, our study provides a platform for researchers to evaluate how the choice of omics, ML classifiers, and dimension reduction can influence the quality of CVD risk factor predictions.

Subclinical atherosclerosis in young adults predicting cardiovascular disease: The Cardiovascular Risk in Young Finns Study.

BACKGROUND AND AIMS: Atherosclerosis is accompanied by pre-clinical vascular changes that can be detected using ultrasound imaging. We examined the value of such pre-clinical features in identifying young adults who are at risk of developing atherosclerotic cardiovascular disease (ASCVD). METHODS: A total of 2641 individuals free of ASCVD were examined at the mean age of 32 years (range 24-45 years) for carotid artery intima-media thickness (IMT) and carotid plaques, carotid artery elasticity, and brachial artery flow-mediated endothelium-dependent vasodilation (FMD). The average follow-up time to event/censoring was 16 years (range 1-17 years). RESULTS: Sixty-seven individuals developed ASCVD (incidence 2.5%). The lowest incidence (1.1%) was observed among those who were estimated of having low risk according to the SCORE2 risk algorithm (<2.5% 10-year risk) and who did not have plaque or high IMT (upper decile). The highest incidence (11.0%) was among those who were estimated of having a high risk (≥2.5% 10-year risk) and had positive ultrasound scan for carotid plaque and/or high IMT (upper decile). Carotid plaque and high IMT remained independently associated with higher risk in multivariate models. The distributions of carotid elasticity indices and brachial FMD did not differ between cases and non-cases. CONCLUSIONS: Screening for carotid plaque and high IMT in young adults may help identify individuals at high risk for future ASCVD.

Long-term tracking and population characteristics of lipoprotein (a) in the Cardiovascular Risk in Young Finns Study.

BACKGROUND AND AIMS: Lipoprotein (a) (Lp(a)) is a causal risk factor for cardiovascular diseases and its levels are under strict genetic control. Therefore, it is hypothesized that the concentration of Lp(a) remains stable throughout life. Finns have lower Lp(a) levels than central Europeans, but it is unknown whether there are differences within Finland, especially between the eastern and western parts of the country with known genetic duality and persistent differences in cardiovascular disease rates. We have examined the long-term stability of Lp(a) levels over 25 years in the Cardiovascular Risk in Young Finns Study (YFS), and the characteristics of individuals with different Lp(a) levels, including their geographical origin within Finland. METHODS: In YFS, the first large baseline examination was conducted in 1980 (baseline age, 3-18 years). Several follow-ups during the past 40 years have been conducted to investigate the determinants of cardiometabolic health. Lp(a) levels have been measured in study years 1986 (N = 2464, ages 9-24 years), 2001 (N = 2281, ages 24-39 years), 2007 (N = 2204, ages 35-45 years) and 2011 (N = 2044, ages 39-49 years). Tracking of Lp(a) was estimated by calculating Spearman's rank order correlations between the study years, and by cross-tabulating how many individuals diagnosed with either elevated or non-elevated Lp(a) levels in 1986, 2001 and 2007 remained in the same category in the latest follow-up in 2011. RESULTS: Spearman's correlation coefficients varied between r = 0.84-0.96. Most individuals (87-94%) who had a high Lp(a) level (>30 mg/dl) in any of the previous study years had a high level also in 2011. On average, the median Lp(a) levels were consistently ∼20% higher in the individuals originating from eastern Finland compared to those from western Finland, but there were no differences in the distribution of known genetic determinants between eastern and western Finns that would have explained the observed difference. CONCLUSIONS: These data confirm that Lp(a) levels remain very stable over the life-course. In line with the genetic duality between eastern and western parts of Finland, we observed about 20% higher Lp(a) levels in individuals originating from eastern Finland compared to those originating from western Finland.

Umbilical cord blood DNA methylation in children who later develop type 1 diabetes.

AIMS/HYPOTHESIS: Distinct DNA methylation patterns have recently been observed to precede type 1 diabetes in whole blood collected from young children. Our aim was to determine whether perinatal DNA methylation is associated with later progression to type 1 diabetes. METHODS: Reduced representation bisulphite sequencing (RRBS) analysis was performed on umbilical cord blood samples collected within the Finnish Type 1 Diabetes Prediction and Prevention (DIPP) Study. Children later diagnosed with type 1 diabetes and/or who tested positive for multiple islet autoantibodies (n = 43) were compared with control individuals (n = 79) who remained autoantibody-negative throughout the DIPP follow-up until 15 years of age. Potential confounding factors related to the pregnancy and the mother were included in the analysis. RESULTS: No differences in the umbilical cord blood methylation patterns were observed between the cases and controls at a false discovery rate <0.05. CONCLUSIONS/INTERPRETATION: Based on our results, differences between children who progress to type 1 diabetes and those who remain healthy throughout childhood are not yet present in the perinatal DNA methylome. However, we cannot exclude the possibility that such differences would be found in a larger dataset.

Permutation-based significance analysis reduces the type 1 error rate in bisulphite sequencing data analysis of human umbilical cord blood samples.

DNA methylation patterns are largely established in-utero and might mediate the impacts of in-utero conditions on later health outcomes. Associations between perinatal DNA methylation marks and pregnancy-related variables, such as maternal age and gestational weight gain, have been earlier studied with methylation microarrays, which typically cover less than 2% of human CpG sites. To detect such associations outside these regions, we chose the bisulphite sequencing approach. We collected and curated clinical data on 200 newborn infants; whose umbilical cord blood samples were analysed with the reduced representation bisulphite sequencing (RRBS) method. A generalized linear mixed-effects model was fit for each high coverage CpG site, followed by spatial and multiple testing adjustment of P values to identify differentially methylated cytosines (DMCs) and regions (DMRs) associated with clinical variables, such as maternal age, mode of delivery, and birth weight. Type 1 error rate was then evaluated with a permutation analysis. We discovered a strong inflation of spatially adjusted P values through the permutation analysis, which we then applied for empirical type 1 error control. The inflation of P values was caused by a common method for spatial adjustment and DMR detection, implemented in tools comb-p and RADMeth. Based on empirically estimated significance thresholds, very little differential methylation was associated with any of the studied clinical variables, other than sex. With this analysis workflow, the sex-associated differentially methylated regions were highly reproducible across studies, technologies, and statistical models.

Multi-Omics Integration in a Twin Cohort and Predictive Modeling of Blood Pressure Values.

Abnormal blood pressure is strongly associated with risk of high-prevalence diseases, making the study of blood pressure a major public health challenge. Although biological mechanisms underlying hypertension at the single omic level have been discovered, multi-omics integrative analyses using continuous variations in blood pressure values remain limited. We used a multi-omics regression-based method, called sparse multi-block partial least square, for integrative, explanatory, and predictive interests in study of systolic and diastolic blood pressure values. Various datasets were obtained from the Finnish Twin Cohort for up to 444 twins. Blocks of omics-including transcriptomic, methylation, metabolomic-data as well as polygenic risk scores and clinical data were integrated into the modeling and supported by cross-validation. The predictive contribution of each omics block when predicting blood pressure values was investigated using external participants from the Young Finns Study. In addition to revealing interesting inter-omics associations, we found that each block of omics heterogeneously improved the predictions of blood pressure values once the multi-omics data were integrated. The modeling revealed a plurality of clinical, transcriptomic, and metabolomic factors consistent with the literature and that play a leading role in explaining unit variations in blood pressure. These findings demonstrate (1) the robustness of our integrative method to harness results obtained by single omics discriminant analyses, and (2) the added value of predictive and exploratory gains of a multi-omics approach in studies of complex phenotypes such as blood pressure.

Glycoprotein Acetyls: A Novel Inflammatory Biomarker of Early Cardiovascular Risk in the Young.

Background Low-grade inflammation in the young may contribute to the early development of cardiovascular disease. We assessed whether circulating levels of glycoprotein acetyls (GlycA) were better able to predict the development of adverse cardiovascular disease risk profiles compared with the more commonly used biomarker high-sensitivity CRP (C-reactive protein). Methods and Results A total of 3306 adolescents and young adults from the Avon Longitudinal Study of Parents and Children (mean age, 15.4±0.3; n=1750) and Cardiovascular Risk in Young Finns Study (mean age, 32.1±5.0; n=1556) were included. Baseline associations between inflammatory biomarkers, body composition, cardiovascular risk factors, and subclinical measures of vascular dysfunction were assessed cross-sectionally in both cohorts. Prospective risk of developing hypertension and metabolic syndrome during 9-to-10-year follow-up were also assessed as surrogate markers for future cardiovascular risk. GlycA showed greater within-subject correlation over 9-to-10-year follow-up in both cohorts compared with CRP, particularly in the younger adolescent group (r=0.36 versus 0.07). In multivariable analyses, GlycA was found to associate with multiple lifestyle-related cardiovascular disease risk factors, cardiometabolic risk factor burden, and vascular dysfunction (eg, mean difference in flow-mediated dilation=-1.2 [-1.8, -0.7]% per z-score increase). In contrast, CRP levels appeared predominantly driven by body mass index and showed little relationship to any measured cardiovascular risk factors or phenotypes. In both cohorts, only GlycA predicted future risk of both hypertension (risk ratio [RR], ≈1.1 per z-score increase for both cohorts) and metabolic syndrome (RR, ≈1.2-1.3 per z-score increase for both cohorts) in 9-to-10-year follow-up. Conclusions Low-grade inflammation captured by the novel biomarker GlycA is associated with adverse cardiovascular risk profiles from as early as adolescence and predicts future risk of hypertension and metabolic syndrome in up to 10-year follow-up. GlycA is a stable inflammatory biomarker which may capture distinct sources of inflammation in the young and may provide a more sensitive measure than CRP for detecting early cardiovascular risk.

Systematic evaluation of the association between hemoglobin levels and metabolic profile implicates beneficial effects of hypoxia.

Activation of the hypoxia-inducible factor (HIF) pathway reprograms energy metabolism. Hemoglobin (Hb) is the main carrier of oxygen. Using its normal variation as a surrogate measure for hypoxia, we explored whether lower Hb levels could lead to healthier metabolic profiles in mice and humans (n = 7175) and used Mendelian randomization (MR) to evaluate potential causality (n = 173,480). The results showed evidence for lower Hb levels being associated with lower body mass index, better glucose tolerance and other metabolic profiles, lower inflammatory load, and blood pressure. Expression of the key HIF target genes SLC2A4 and Slc2a1 in skeletal muscle and adipose tissue, respectively, associated with systolic blood pressure in MR analyses and body weight, liver weight, and adiposity in mice. Last, manipulation of murine Hb levels mediated changes to key metabolic parameters. In conclusion, low-end normal Hb levels may be favorable for metabolic health involving mild chronic activation of the HIF response.

Evaluating the direct effects of childhood adiposity on adult systemic metabolism: a multivariable Mendelian randomization analysis.

BACKGROUND: Individuals who are obese in childhood have an elevated risk of disease in adulthood. However, whether childhood adiposity directly impacts intermediate markers of this risk, independently of adult adiposity, is unclear. In this study, we have simultaneously evaluated the effects of childhood and adulthood body size on 123 systemic molecular biomarkers representing multiple metabolic pathways. METHODS: Two-sample Mendelian randomization (MR) was conducted to estimate the causal effect of childhood body size on a total of 123 nuclear magnetic resonance-based metabolic markers using summary genome-wide association study (GWAS) data from up to 24 925 adults. Multivariable MR was then applied to evaluate the direct effects of childhood body size on these metabolic markers whilst accounting for adult body size. Further MR analyses were undertaken to estimate the potential mediating effects of these circulating metabolites on the risk of coronary artery disease (CAD) in adulthood using a sample of 60 801 cases and 123 504 controls. RESULTS: Univariable analyses provided evidence that childhood body size has an effect on 42 of the 123 metabolic markers assessed (based on P < 4.07 × 10-4). However, the majority of these effects (35/42) substantially attenuated when accounting for adult body size using multivariable MR. We found little evidence that the biomarkers that were potentially influenced directly by childhood body size (leucine, isoleucine and tyrosine) mediate this effect onto adult disease risk. Very-low-density lipoprotein markers provided the strongest evidence of mediating the long-term effect of adiposity on CAD risk. CONCLUSIONS: Our findings suggest that childhood adiposity predominantly exerts its detrimental effect on adult systemic metabolism along a pathway that involves adulthood body size.

Childhood exposure to parental smoking and life-course overweight and central obesity.

OBJECTIVE: To evaluate the association between childhood parental smoking exposure and the risk of overweight/obesity from childhood to adulthood. METHODS: This study leverages the data from two longitudinal population based cohort studies, the Cardiovascular Risk in Young Finns Study between years 1980-2011/2012 (YFS; N = 2,303; baseline age 3-18 years) and the Special Turku Coronary Risk Factor Intervention Project between years 1989-2009/2010 (STRIP; N = 632; baseline age 7 months). Weight, height and waist circumference were measured from childhood to adulthood. Overweight/obesity was defined as body mass index ≥25 kg/m2 in adults and using the Cole criteria in children. Central obesity was defined as waist circumference > 100/90 cm in men/women and as a waist-to-height ratio > 0.50 in children. Statistical analyses were adjusted for age, sex, socioeconomic status, smoking, birth weight, parental ages, diet and physical activity. RESULTS: Childhood parental smoking exposure was associated with increased risk for life-course overweight/obesity (YFS: RR1.13, 95%CI 1.02-1.24; STRIP: RR1.57, 95%CI 1.10-2.26) and central obesity (YFS: RR1.18, 95%CI 1.01-1.38; STRIP: RR1.45, 95%CI 0.98-2.15). CONCLUSIONS: Childhood exposure to parental smoking is associated with increased risk of overweight/obesity over the life-course. KEY MESSAGES Exposure to parental smoking in childhood was associated with increased risk of overweight/obesity, central obesity and adiposity measured by skinfold thickness from childhood to adulthood.

The associations of oxidized lipoprotein lipids with lipoprotein subclass particle concentrations and their lipid compositions. The Cardiovascular Risk in Young Finns Study.

OBJECTIVE: Oxidation of low-density lipoprotein (LDL) may promote atherosclerosis, whereas the reverse transport of oxidized lipids by high-density lipoprotein (HDL) may contribute to atheroprotection. To provide insights into the associations of lipoprotein lipid oxidation markers with lipoprotein subclasses at the population level, we investigated the associations of oxidized HDL lipids (oxHDLlipids) and oxidized LDL lipids (oxLDLlipids) with lipoprotein subclasses in a population-based cross-sectional study of 1395 Finnish adults ages 24-39 years. METHODS: The analysis of oxidized lipids was based on the determination of the baseline level of conjugated dienes in lipoprotein lipids. A high-throughput nuclear magnetic resonance (NMR) platform was used to quantify circulating lipoprotein subclass concentrations and analyze their lipid compositions. RESULTS: OxHDLlipids were mainly not associated with lipoprotein subclass lipid concentrations and lipid composition after adjustment for Apolipoprotein-A1 (Apo-A1), waist circumference and age. OxLDLlipids were associated with several markers of lipoprotein subclass lipid concentrations and composition after adjustment for Apolipoprotein-B (Apo-B), age and waist circumference. Several measures of HDL and LDL subclasses, including phospholipid and triglyceride composition, associated directly with oxLDLlipids. Cholesterol ester and free cholesterol composition in HDL and LDL associated inversely with oxLDLlipids. CONCLUSION: We conclude that these results do not support the idea that HDL's particle size or composition would reflect its functional capacity in the reverse transport of oxidized lipids. On the contrary, oxLDLlipids were associated with the entire lipoprotein subclass profile, including numerous associations with the compositional descriptors of the particles. This is in line with the suggested role of LDL oxidation in atherogenesis.

Serum 25-Hydroxyvitamin D Concentrations at Birth in Children Screened for HLA-DQB1 Conferred Risk for Type 1 Diabetes.

CONTEXT: Vitamin D has several effects on the immune system that might be of relevance for the pathogenesis of type 1 diabetes (T1D). OBJECTIVE: To evaluate whether umbilical cord serum concentrations of 25-hydroxy-vitamin D (25[OH]D) differ in children developing either islet autoimmunity (IA) or overt T1D during childhood and adolescence. DESIGN: Umbilical cord serum samples from 764 children born from 1994 to 2004 with HLA-DQB1 conferred risk for T1D participating in the Type 1 Diabetes Prediction and Prevention Study were analyzed for 25(OH)D using an enzyme immunoassay. SETTING: DIPP clinics in Turku, Oulu, and Tampere University Hospitals, Finland. PARTICIPANTS: Two hundred fifty children who developed T1D diabetes at a median age of 6.7 years (interquartile range [IQR] 4.0 to 10.1 years) and 132 additional case children who developed IA, i.e., positivity for multiple islet autoantibodies. Cases were matched for date of birth, gender, and area of birth with 382 control children who remained autoantibody negative. The median duration of follow up was 9.8 years (IQR 5.7 to 13.1 years). MAIN OUTCOME MEASURE: The median 25(OH)D concentrations. RESULTS: The median 25(OH)D concentration in cord serum was low [31.1 nmol/L (IQR 24.0 to 41.8); 88% <50 nmol/L], but not statistically different between children who developed T1D or IA and their control groups (P = 0.70). The levels were associated mainly with geographical location, year and month of birth, age of the mother, and maternal intake of vitamin D during pregnancy. CONCLUSIONS: The 25(OH)D concentrations at birth are not associated with the development of T1D during childhood.

Enterovirus-associated changes in blood transcriptomic profiles of children with genetic susceptibility to type 1 diabetes.

AIMS/HYPOTHESIS: Enterovirus infections have been associated with the development of type 1 diabetes in multiple studies, but little is known about enterovirus-induced responses in children at risk for developing type 1 diabetes. Our aim was to use genome-wide transcriptomics data to characterise enterovirus-associated changes in whole-blood samples from children with genetic susceptibility to type 1 diabetes. METHODS: Longitudinal whole-blood samples (356 samples in total) collected from 28 pairs of children at increased risk for developing type 1 diabetes were screened for the presence of enterovirus RNA. Seven of these samples were detected as enterovirus-positive, each of them collected from a different child, and transcriptomics data from these children were analysed to understand the individual-level responses associated with enterovirus infections. Transcript clusters with peaking or dropping expression at the time of enterovirus positivity were selected as the enterovirus-associated signals. RESULTS: Strong signs of activation of an interferon response were detected in four children at enterovirus positivity, while transcriptomic changes in the other three children indicated activation of adaptive immune responses. Additionally, a large proportion of the enterovirus-associated changes were specific to individuals. An enterovirus-induced signature was built using 339 genes peaking at enterovirus positivity in four of the children, and 77 of these genes were also upregulated in human peripheral blood mononuclear cells infected in vitro with different enteroviruses. These genes separated the four enterovirus-positive samples clearly from the remaining 352 blood samples analysed. CONCLUSIONS/INTERPRETATION: We have, for the first time, identified enterovirus-associated transcriptomic profiles in whole-blood samples from children with genetic susceptibility to type 1 diabetes. Our results provide a starting point for understanding the individual responses to enterovirus infections in blood and their potential connection to the development of type 1 diabetes. DATA AVAILABILITY: The datasets analysed during the current study are included in this published article and its supplementary information files ( www.btk.fi/research/computational-biomedicine/1234-2 ) or are available from the Gene Expression Omnibus (GEO) repository (accession GSE30211).

Inhaled Sargramostim Induces Resolution of Pulmonary Alveolar Proteinosis in Lysinuric Protein Intolerance.

Pulmonary alveolar proteinosis (PAP) is a potentially fatal complication of lysinuric protein intolerance (LPI), an inherited disorder of cationic amino acid transport. The patients often present with mild respiratory symptoms, which may rapidly progress to acute respiratory failure responding poorly to conventional treatment with steroids and bronchoalveolar lavations (BALs). The pathogenesis of PAP in LPI is still largely unclear. In previous studies, we have shown disturbances in the function and activity of alveolar macrophages of these patients, suggesting that increasing the activity and the number of macrophages by recombinant human GM-CSF (rhuGM-CSF) might be beneficial in this patient group.Two LPI patients with complicated PAP were treated with experimental inhaled rhuGM-CSF (sargramostim) after poor response to maximal conventional therapy. BAL fluid and cell samples from one patient were studied with light microscopy and transmission electron microscopy.Excellent response to therapy was observed in patient 1 with no compliance problems or side effects. Macrophages with myelin figure-like structures were seen in her BAL sample. Slight improvement of the pulmonary function was evident also in patient 2, but the role of sargramostim could not be properly evaluated due to the complicated clinical situation.In conclusion, inhaled rhuGM-CSF might be of benefit in patients with LPI-associated PAP.

Imbalance of plasma amino acids, metabolites and lipids in patients with lysinuric protein intolerance (LPI).

BACKGROUND: Lysinuric protein intolerance (LPI [MIM 222700]) is an aminoaciduria with defective transport of cationic amino acids in epithelial cells in the small intestine and proximal kidney tubules due to mutations in the SLC7A7 gene. LPI is characterized by protein malnutrition, failure to thrive and hyperammonemia. Many patients also suffer from combined hyperlipidemia and chronic kidney disease (CKD) with an unknown etiology. METHODS: Here, we studied the plasma metabolomes of the Finnish LPI patients (n=26) and healthy control individuals (n=19) using a targeted platform for analysis of amino acids as well as two analytical platforms with comprehensive coverage of molecular lipids and polar metabolites. RESULTS: Our results demonstrated that LPI patients have a dichotomy of amino acid profiles, with both decreased essential and increased non-essential amino acids. Altered levels of metabolites participating in pathways such as sugar, energy, amino acid and lipid metabolism were observed. Furthermore, of these metabolites, myo-inositol, threonic acid, 2,5-furandicarboxylic acid, galactaric acid, 4-hydroxyphenylacetic acid, indole-3-acetic acid and beta-aminoisobutyric acid associated significantly (P<0.001) with the CKD status. Lipid analysis showed reduced levels of phosphatidylcholines and elevated levels of triacylglycerols, of which long-chain triacylglycerols associated (P<0.01) with CKD. CONCLUSIONS: This study revealed an amino acid imbalance affecting the basic cellular metabolism, disturbances in plasma lipid composition suggesting hepatic steatosis and fibrosis and novel metabolites correlating with CKD in LPI. In addition, the CKD-associated metabolite profile along with increased nitrite plasma levels suggests that LPI may be characterized by increased oxidative stress and apoptosis, altered microbial metabolism in the intestine and uremic toxicity.

Complement gene variants in relation to autoantibodies to beta cell specific antigens and type 1 diabetes in the TEDDY Study.

A total of 15 SNPs within complement genes and present on the ImmunoChip were analyzed in The Environmental Determinants of Diabetes in the Young (TEDDY) study. A total of 5474 subjects were followed from three months of age until islet autoimmunity (IA: n = 413) and the subsequent onset of type 1 diabetes (n = 115) for a median of 73 months (IQR 54-91). Three SNPs within ITGAM were nominally associated (p < 0.05) with IA: rs1143678 [Hazard ratio; HR 0.80; 95% CI 0.66-0.98; p = 0.032], rs1143683 [HR 0.80; 95% CI 0.65-0.98; p = 0.030] and rs4597342 [HR 1.16; 95% CI 1.01-1.32; p = 0.041]. When type 1 diabetes was the outcome, in DR3/4 subjects, there was nominal significance for two SNPs: rs17615 in CD21 [HR 1.52; 95% CI 1.05-2.20; p = 0.025] and rs4844573 in C4BPA [HR 0.63; 95% CI 0.43-0.92; p = 0.017]. Among DR4/4 subjects, rs2230199 in C3 was significantly associated [HR 3.20; 95% CI 1.75-5.85; p = 0.0002, uncorrected] a significance that withstood Bonferroni correction since it was less than 0.000833 (0.05/60) in the HLA-specific analyses. SNPs within the complement genes may contribute to IA, the first step to type 1 diabetes, with at least one SNP in C3 significantly associated with clinically diagnosed type 1 diabetes.