Prediction of vascular aging based on smartphone acquired PPG signals.

Photoplethysmography (PPG) measured by smartphone has the potential for a large scale, non-invasive, and easy-to-use screening tool. Vascular aging is linked to increased arterial stiffness, which can be measured by PPG. We investigate the feasibility of using PPG to predict healthy vascular aging (HVA) based on two approaches: machine learning (ML) and deep learning (DL). We performed data preprocessing, including detrending, demodulating, and denoising on the raw PPG signals. For ML, ridge penalized regression has been applied to 38 features extracted from PPG, whereas for DL several convolutional neural networks (CNNs) have been applied to the whole PPG signals as input. The analysis has been conducted using the crowd-sourced Heart for Heart data. The prediction performance of ML using two features (AUC of 94.7%) - the a wave of the second derivative PPG and tpr, including four covariates, sex, height, weight, and smoking - was similar to that of the best performing CNN, 12-layer ResNet (AUC of 95.3%). Without having the heavy computational cost of DL, ML might be advantageous in finding potential biomarkers for HVA prediction. The whole workflow of the procedure is clearly described, and open software has been made available to facilitate replication of the results.

Roux-Y Gastric Bypass and Sleeve Gastrectomy directly change gut microbiota composition independent of surgery type.

Bariatric surgery in morbid obesity, either through sleeve gastrectomy (SG) or Roux-Y gastric bypass (RYGB), leads to sustainable weight loss, improvement of metabolic disorders and changes in intestinal microbiota. Yet, the relationship between changes in gut microbiota, weight loss and surgical procedure remains incompletely understood. We determined temporal changes in microbiota composition in 45 obese patients undergoing crash diet followed by SG (n = 22) or RYGB (n = 23). Intestinal microbiota composition was determined before intervention (baseline, S1), 2 weeks after crash diet (S2), and 1 week (S3), 3 months (S4) and 6 months (S5) after surgery. Relative to S1, the microbial diversity index declined at S2 and S3 (p < 0.05), and gradually returned to baseline levels at S5. Rikenellaceae relative abundance increased and Ruminococcaceae and Streptococcaceae abundance decreased at S2 (p < 0.05). At S3, Bifidobacteriaceae abundance decreased, whereas those of Streptococcaceae and Enterobacteriaceae increased (p < 0.05). Increased weight loss between S3-S5 was not associated with major changes in microbiota composition. No significant differences appeared between both surgical procedures. In conclusion, undergoing a crash diet and bariatric surgery were associated with an immediate but temporary decline in microbial diversity, with immediate and permanent changes in microbiota composition, independent of surgery type.

Human Plasma N-glycosylation as Analyzed by Matrix-Assisted Laser Desorption/Ionization-Fourier Transform Ion Cyclotron Resonance-MS Associates with Markers of Inflammation and Metabolic Health.

Glycosylation is an abundant co- and post-translational protein modification of importance to protein processing and activity. Although not template-defined, glycosylation does reflect the biological state of an organism and is a high-potential biomarker for disease and patient stratification. However, to interpret a complex but informative sample like the total plasma N-glycome, it is important to establish its baseline association with plasma protein levels and systemic processes. Thus far, large-scale studies (n >200) of the total plasma N-glycome have been performed with methods of chromatographic and electrophoretic separation, which, although being informative, are limited in resolving the structural complexity of plasma N-glycans. MS has the opportunity to contribute additional information on, among others, antennarity, sialylation, and the identity of high-mannose type species.Here, we have used matrix-assisted laser desorption/ionization (MALDI)-Fourier transform ion cyclotron resonance (FTICR)-MS to study the total plasma N-glycome of 2144 healthy middle-aged individuals from the Leiden Longevity Study, to allow association analysis with markers of metabolic health and inflammation. To achieve this, N-glycans were enzymatically released from their protein backbones, labeled at the reducing end with 2-aminobenzoic acid, and following purification analyzed by negative ion mode intermediate pressure MALDI-FTICR-MS. In doing so, we achieved the relative quantification of 61 glycan compositions, ranging from Hex4HexNAc2 to Hex7HexNAc6dHex1Neu5Ac4, as well as that of 39 glycosylation traits derived thereof. Next to confirming known associations of glycosylation with age and sex by MALDI-FTICR-MS, we report novel associations with C-reactive protein (CRP), interleukin 6 (IL-6), body mass index (BMI), leptin, adiponectin, HDL cholesterol, triglycerides (TG), insulin, gamma-glutamyl transferase (GGT), alanine aminotransferase (ALT), and smoking. Overall, the bisection, galactosylation, and sialylation of diantennary species, the sialylation of tetraantennary species, and the size of high-mannose species proved to be important plasma characteristics associated with inflammation and metabolic health.

A Genome-Wide Association Study Identifies the Skin Color Genes IRF4, MC1R, ASIP, and BNC2 Influencing Facial Pigmented Spots.

Facial pigmented spots are a common skin aging feature, but genetic predisposition has yet to be thoroughly investigated. We conducted a genome-wide association study for pigmented spots in 2,844 Dutch Europeans from the Rotterdam Study (mean age: 66.9±8.0 years; 47% male). Using semi-automated image analysis of high-resolution digital facial photographs, facial pigmented spots were quantified as the percentage of affected skin area (mean women: 2.0% ±0.9, men: 0.9% ±0.6). We identified genome-wide significant association with pigmented spots at three genetic loci: IRF4 (rs12203592, P=1.8 × 10(-27)), MC1R (compound heterozygosity score, P=2.3 × 10(-24)), and RALY/ASIP (rs6059655, P=1.9 × 10(-9)). In addition, after adjustment for the other three top-associated loci the BNC2 locus demonstrated significant association (rs62543565, P=2.3 × 10(-8)). The association signals observed at all four loci were successfully replicated (P<0.05) in an independent Dutch cohort (Leiden Longevity Study n=599). Although the four genes have previously been associated with skin color variation and skin cancer risk, all association signals remained highly significant (P<2 × 10(-8)) when conditioning the association analyses on skin color. We conclude that genetic variations in IRF4, MC1R, RALY/ASIP, and BNC2 contribute to the acquired amount of facial pigmented spots during aging, through pathways independent of the basal melanin production.

Loci associated with N-glycosylation of human immunoglobulin G show pleiotropy with autoimmune diseases and haematological cancers.

Glycosylation of immunoglobulin G (IgG) influences IgG effector function by modulating binding to Fc receptors. To identify genetic loci associated with IgG glycosylation, we quantitated N-linked IgG glycans using two approaches. After isolating IgG from human plasma, we performed 77 quantitative measurements of N-glycosylation using ultra-performance liquid chromatography (UPLC) in 2,247 individuals from four European discovery populations. In parallel, we measured IgG N-glycans using MALDI-TOF mass spectrometry (MS) in a replication cohort of 1,848 Europeans. Meta-analysis of genome-wide association study (GWAS) results identified 9 genome-wide significant loci (P<2.27 × 10(-9)) in the discovery analysis and two of the same loci (B4GALT1 and MGAT3) in the replication cohort. Four loci contained genes encoding glycosyltransferases (ST6GAL1, B4GALT1, FUT8, and MGAT3), while the remaining 5 contained genes that have not been previously implicated in protein glycosylation (IKZF1, IL6ST-ANKRD55, ABCF2-SMARCD3, SUV420H1, and SMARCB1-DERL3). However, most of them have been strongly associated with autoimmune and inflammatory conditions (e.g., systemic lupus erythematosus, rheumatoid arthritis, ulcerative colitis, Crohn's disease, diabetes type 1, multiple sclerosis, Graves' disease, celiac disease, nodular sclerosis) and/or haematological cancers (acute lymphoblastic leukaemia, Hodgkin lymphoma, and multiple myeloma). Follow-up functional experiments in haplodeficient Ikzf1 knock-out mice showed the same general pattern of changes in IgG glycosylation as identified in the meta-analysis. As IKZF1 was associated with multiple IgG N-glycan traits, we explored biomarker potential of affected N-glycans in 101 cases with SLE and 183 matched controls and demonstrated substantial discriminative power in a ROC-curve analysis (area under the curve = 0.842). Our study shows that it is possible to identify new loci that control glycosylation of a single plasma protein using GWAS. The results may also provide an explanation for the reported pleiotropy and antagonistic effects of loci involved in autoimmune diseases and haematological cancer.

Quantitative polymerase chain reaction-based analysis of podocyturia is a feasible diagnostic tool in preeclampsia.

Preeclampsia is a significant cause of maternal and fetal morbidity and mortality worldwide. A clinically useful screening test that can predict development of preeclampsia at an early stage is urgently needed. The detection of podocyturia by immunohistochemistry after cell culture has been noted as a reliable marker for preeclampsia. However, this method is laborious and carries the risk of cell culture contamination. The aim of this study was to investigate the diagnostic value of quantitative polymerase chain reaction as a rapid method to detect preeclampsia. Clean-catch urine samples were collected from preeclamptic (n=35), healthy pregnant (n=34), and healthy nonpregnant (n=12) women. Furthermore, a control group of women with gestational hypertension (n=5) was included. Quantitative polymerase chain reaction analysis was performed for podocyte-specific markers. Receiver operating characteristic curve analyses were performed. Significantly elevated mRNA levels of nephrin, podocin, and vascular endothelial growth factor were detected in preeclamptic women compared with healthy pregnant and healthy nonpregnant controls. In addition, significantly elevated levels of nephrin mRNA were detected in urine of preeclamptic women compared with women with gestational hypertension. A positive correlation (ρ=0.82; P<0.0001) was observed between nephrin and vascular endothelial growth factor mRNA levels in preeclamptic women. Receiver operating characteristic curve analyses demonstrated a strong ability of this method to discriminate between the different study groups. Quantitative polymerase chain reaction analysis of podocyte-specific molecules in urine samples is a rapid and reliable method to quantify podocyturia. We demonstrate that this method distinguishes preeclamptic patients from healthy controls and women with gestational hypertension. This method may be a tool for the detection of preeclampsia at an earlier stage, thereby preventing maternal and fetal morbidity and mortality.

Haplotype estimation from fuzzy genotypes using penalized likelihood.

The Composite Link Model is a generalization of the generalized linear model in which expected values of observed counts are constructed as a sum of generalized linear components. When combined with penalized likelihood, it provides a powerful and elegant way to estimate haplotype probabilities from observed genotypes. Uncertain ("fuzzy") genotypes, like those resulting from AFLP scores, can be handled by adding an extra layer to the model. We describe the model and the estimation algorithm. We apply it to a data set of accurate human single nucleotide polymorphism (SNP) and to a data set of fuzzy tomato AFLP scores.

Genome-wide association study identifies a single major locus contributing to survival into old age; the APOE locus revisited.

By studying the loci that contribute to human longevity, we aim to identify mechanisms that contribute to healthy aging. To identify such loci, we performed a genome-wide association study (GWAS) comparing 403 unrelated nonagenarians from long-living families included in the Leiden Longevity Study (LLS) and 1670 younger population controls. The strongest candidate SNPs from this GWAS have been analyzed in a meta-analysis of nonagenarian cases from the Rotterdam Study, Leiden 85-plus study, and Danish 1905 cohort. Only one of the 62 prioritized SNPs from the GWAS analysis (P<1×10(-4) ) showed genome-wide significance with survival into old age in the meta-analysis of 4149 nonagenarian cases and 7582 younger controls [OR=0.71 (95% CI 0.65-0.77), P=3.39 × 10(-17) ]. This SNP, rs2075650, is located in TOMM40 at chromosome 19q13.32 close to the apolipoprotein E (APOE) gene. Although there was only moderate linkage disequilibrium between rs2075650 and the ApoE ε4 defining SNP rs429358, we could not find an APOE-independent effect of rs2075650 on longevity, either in cross-sectional or in longitudinal analyses. As expected, rs429358 associated with metabolic phenotypes in the offspring of the nonagenarian cases from the LLS and their partners. In addition, we observed a novel association between this locus and serum levels of IGF-1 in women (P=0.005). In conclusion, the major locus determining familial longevity up to high age as detected by GWAS was marked by rs2075650, which tags the deleterious effects of the ApoE ε4 allele. No other major longevity locus was found.

Single nucleotide polymorphisms in antigen processing machinery component ERAP1 significantly associate with clinical outcome in cervical carcinoma.

Genetic variation of the antigen processing machinery (APM) components TAP2, LMP7, and ERAP1 is related to cervical carcinoma risk, although the relation with expression and clinical outcome remains unknown. We have investigated the occurrence of APM component single nucleotide polymorphisms (SNPs) in cervical carcinoma. Twelve nonsynonymous, coding SNPs in the TAP1, TAP2, LMP2, LMP7, and ERAP1 genes were genotyped in 75 cervical carcinoma patients with known APM component and HLA class I expression levels. Individual genotype distributions were assessed for association with APM component expression, various histopathological parameters and survival. Genotype distributions at the ERAP1-56 and ERAP1-127 loci were significantly associated with overall survival (OS); haplotype construction spanning these two SNPs revealed that the combination of a major allele at ERAP1-56 and a minor allele at ERAP1-127 was significantly associated with survival, homozygosity for this haplotype being associated with decreased OS (5-year survival 50% vs. 70 and 81% for complete absence or heterozygosity for this haplotype, respectively; P = 0.021). Heterozygosity for this haplotype was an independent predictor for better OS in multivariate analysis (HR = 0.219; P = 0.014). These data indicate that genetic variation in APM component genes, particularly ERAP1, is an important contributing factor in cervical carcinogenesis, progressive tumor growth and survival. The location of the ERAP1-127 SNP in the peptidase M1 domain of the ERAP1 aminopeptidase suggests the possibility of direct functional consequences of variation at this locus.

Genetic variation of antigen processing machinery components and association with cervical carcinoma.

The antigen processing machinery (APM) plays an important role in immune recognition of virally infected and transformed cells. Defective expression of several APM components is associated with progression and clinical outcome in cervical carcinoma. Genetic variation in the genes encoding APM components is known to be associated with risk of occurrence of several malignancies. However, only limited evidence exists supporting the role of single nucleotide polymorphisms (SNPs) in APM components in cervical carcinoma. We have therefore investigated the occurrence of APM component SNP genotypes and haplotypes in cervical carcinoma. Thirteen coding SNPs in the LMP2, LMP7, TAP1, TAP2, and ERAP1 genes were genotyped in 127 cervical carcinoma patients and 124 controls. Individual genotype and allele distributions were assessed by single-marker analysis. Effects of various SNP combinations were estimated by haplotype construction and subsequent haplotype interaction analysis. Significant haplotypes were modeled on disease risk. Allele distributions at the LMP7-145, TAP2-651, ERAP1-127, and ERAP1-730 loci differed significantly between cases and controls with the major allele at the LMP7 and TAP2 loci and the minor allele at both ERAP1 loci associated with increased cervical carcinoma risk. A combination of the two haplotypes spanning these loci was associated with a three-fold increased risk (OR = 3.024; P << 0.001); approximately 12% of all cervical carcinoma occurrences were attributable to this combination. Our data indicate that combined genetic variation in the TAP2, LMP7, and ERAP1 genes is associated with increased cervical carcinoma risk.