Interactive molecular causal networks of hypertension using a fast machine learning algorithm MRdualPC.

BACKGROUND: Understanding the complex interactions between genes and their causal effects on diseases is crucial for developing targeted treatments and gaining insight into biological mechanisms. However, the analysis of molecular networks, especially in the context of high-dimensional data, presents significant challenges. METHODS: This study introduces MRdualPC, a computationally tractable algorithm based on the MRPC approach, to infer large-scale causal molecular networks. We apply MRdualPC to investigate the upstream causal transcriptomics influencing hypertension using a comprehensive dataset of kidney genome and transcriptome data. RESULTS: Our algorithm proves to be 100 times faster than MRPC on average in identifying transcriptomics drivers of hypertension. Through clustering, we identify 63 modules with causal driver genes, including 17 modules with extensive causal networks. Notably, we find that genes within one of the causal networks are associated with the electron transport chain and oxidative phosphorylation, previously linked to hypertension. Moreover, the identified causal ancestor genes show an over-representation of blood pressure-related genes. CONCLUSIONS: MRdualPC has the potential for broader applications beyond gene expression data, including multi-omics integration. While there are limitations, such as the need for clustering in large gene expression datasets, our study represents a significant advancement in building causal molecular networks, offering researchers a valuable tool for analyzing big data and investigating complex diseases.

Kidney omics in hypertension: from statistical associations to biological mechanisms and clinical applications.

Hypertension is a major cardiovascular disease risk factor and contributor to premature death globally. Family-based investigations confirmed a significant heritable component of blood pressure (BP), whereas genome-wide association studies revealed >1000 common and rare genetic variants associated with BP and/or hypertension. The kidney is not only an organ of key relevance to BP regulation and the development of hypertension, but it also acts as the tissue mediator of genetic predisposition to hypertension. The identity of kidney genes, pathways, and related mechanisms underlying the genetic associations with BP has started to emerge through integration of genomics with kidney transcriptomics, epigenomics, and other omics as well as through applications of causal inference, such as Mendelian randomization. Single-cell methods further enabled mapping of BP-associated kidney genes to cell types, and in conjunction with other omics, started to illuminate the biological mechanisms underpinning associations of BP-associated genetic variants and kidney genes. Polygenic risk scores derived from genome-wide association studies and refined on kidney omics hold the promise of enhanced diagnostic prediction, whereas kidney omics-informed drug discovery is likely to contribute new therapeutic opportunities for hypertension and hypertension-mediated kidney damage.

Plasma Proteomics of Renal Function: A Transethnic Meta-Analysis and Mendelian Randomization Study.

BACKGROUND: Studies on the relationship between renal function and the human plasma proteome have identified several potential biomarkers. However, investigations have been conducted largely in European populations, and causality of the associations between plasma proteins and kidney function has never been addressed. METHODS: A cross-sectional study of 993 plasma proteins among 2882 participants in four studies of European and admixed ancestries (KORA, INTERVAL, HUNT, QMDiab) identified transethnic associations between eGFR/CKD and proteomic biomarkers. For the replicated associations, two-sample bidirectional Mendelian randomization (MR) was used to investigate potential causal relationships. Publicly available datasets and transcriptomic data from independent studies were used to examine the association between gene expression in kidney tissue and eGFR. RESULTS: In total, 57 plasma proteins were associated with eGFR, including one novel protein. Of these, 23 were additionally associated with CKD. The strongest inferred causal effect was the positive effect of eGFR on testican-2, in line with the known biological role of this protein and the expression of its protein-coding gene (SPOCK2) in renal tissue. We also observed suggestive evidence of an effect of melanoma inhibitory activity (MIA), carbonic anhydrase III, and cystatin-M on eGFR. CONCLUSIONS: In a discovery-replication setting, we identified 57 proteins transethnically associated with eGFR. The revealed causal relationships are an important stepping stone in establishing testican-2 as a clinically relevant physiological marker of kidney disease progression, and point to additional proteins warranting further investigation.

Hypertension and renin-angiotensin system blockers are not associated with expression of angiotensin-converting enzyme 2 (ACE2) in the kidney.

AIMS: Angiotensin-converting enzyme 2 (ACE2) is the cellular entry point for severe acute respiratory syndrome coronavirus (SARS-CoV-2)-the cause of coronavirus disease 2019 (COVID-19). However, the effect of renin-angiotensin system (RAS)-inhibition on ACE2 expression in human tissues of key relevance to blood pressure regulation and COVID-19 infection has not previously been reported. METHODS AND RESULTS: We examined how hypertension, its major metabolic co-phenotypes, and antihypertensive medications relate to ACE2 renal expression using information from up to 436 patients whose kidney transcriptomes were characterized by RNA-sequencing. We further validated some of the key observations in other human tissues and/or a controlled experimental model. Our data reveal increasing expression of ACE2 with age in both human lungs and the kidney. We show no association between renal expression of ACE2 and either hypertension or common types of RAS inhibiting drugs. We demonstrate that renal abundance of ACE2 is positively associated with a biochemical index of kidney function and show a strong enrichment for genes responsible for kidney health and disease in ACE2 co-expression analysis. CONCLUSION: Our results indicate that neither hypertension nor antihypertensive treatment is likely to alter the expression of the key entry receptor for SARS-CoV-2 in the human kidney. Our data further suggest that in the absence of SARS-CoV-2 infection, kidney ACE2 is most likely nephro-protective but the age-related increase in its expression within lungs and kidneys may be relevant to the risk of SARS-CoV-2 infection.

Human Y Chromosome Exerts Pleiotropic Effects on Susceptibility to Atherosclerosis.

OBJECTIVE: The male-specific region of the Y chromosome (MSY) remains one of the most unexplored regions of the genome. We sought to examine how the genetic variants of the MSY influence male susceptibility to coronary artery disease (CAD) and atherosclerosis. Approach and Results: Analysis of 129 133 men from UK Biobank revealed that only one of 7 common MSY haplogroups (haplogroup I1) was associated with CAD-carriers of haplogroup I1 had ≈11% increase in risk of CAD when compared with all other haplogroups combined (odds ratio, 1.11; 95% CI, 1.04-1.18; P=6.8×10-4). Targeted MSY sequencing uncovered 235 variants exclusive to this haplogroup. The haplogroup I1-specific variants showed 2.45- and 1.56-fold respective enrichment for promoter and enhancer chromatin states, in cells/tissues relevant to atherosclerosis, when compared with other MSY variants. Gene set enrichment analysis in CAD-relevant tissues showed that haplogroup I1 was associated with changes in pathways responsible for early and late stages of atherosclerosis development including defence against pathogens, immunity, oxidative phosphorylation, mitochondrial respiration, lipids, coagulation, and extracellular matrix remodeling. UTY was the only Y chromosome gene whose blood expression was associated with haplogroup I1. Experimental reduction of UTY expression in macrophages led to changes in expression of 59 pathways (28 of which overlapped with those associated with haplogroup I1) and a significant reduction in the immune costimulatory signal. CONCLUSIONS: Haplogroup I1 is enriched for regulatory chromatin variants in numerous cells of relevance to CAD and increases cardiovascular risk through proatherosclerotic reprogramming of the transcriptome, partly through UTY.

Uncovering genetic mechanisms of kidney aging through transcriptomics, genomics, and epigenomics.

Nephrons scar and involute during aging, increasing the risk of chronic kidney disease. Little is known, however, about genetic mechanisms of kidney aging. We sought to define the signatures of age on the renal transcriptome using 563 human kidneys. The initial discovery analysis of 260 kidney transcriptomes from the TRANScriptome of renaL humAn TissuE Study (TRANSLATE) and the Cancer Genome Atlas identified 37 age-associated genes. For 19 of those genes, the association with age was replicated in 303 kidney transcriptomes from the Nephroseq resource. Surveying 42 nonrenal tissues from the Genotype-Tissue Expression project revealed that, for approximately a fifth of the replicated genes, the association with age was kidney-specific. Seventy-three percent of the replicated genes were associated with functional or histological parameters of age-related decline in kidney health, including glomerular filtration rate, glomerulosclerosis, interstitial fibrosis, tubular atrophy, and arterial narrowing. Common genetic variants in four of the age-related genes, namely LYG1, PPP1R3C, LTF and TSPYL5, correlated with the trajectory of age-related changes in their renal expression. Integrative analysis of genomic, epigenomic, and transcriptomic information revealed that the observed age-related decline in renal TSPYL5 expression was determined both genetically and epigenetically. Thus, this study revealed robust molecular signatures of the aging kidney and new regulatory mechanisms of age-related change in the kidney transcriptome.

Tick-Tock Chimes the Kidney Clock - from Biology of Renal Ageing to Clinical Applications.

Ageing of the kidney is a multi-dimensional process that occurs simultaneously at the molecular, cellular, histological, anatomical and physiological level. Nephron number and renal cortical volume decline, renal tubules become atrophic and glomeruli become sclerotic with age. These structural changes are accompanied by a decline in glomerular filtration rate, decreased sodium reabsorption and potassium excretion, reduced urinary concentrating capacity and alterations in the endocrine activity of the kidney. However, the pace of progression of these changes is not identical in everyone - individuals of the same age and seemingly similar clinical profile often exhibit stark differences in the age-related decline in renal health. Thus, chronological age poorly reflects the time-dependent changes that occur in the kidney. An ideal measure of renal vitality is biological kidney age - a measure of the age-related changes in physiological function. Replacing chronological age with biological age could provide numerous clinical benefits including improved prognostic accuracy in renal transplantation, better stratification of risk and identification of those who are on a fast trajectory to an age-related drop in kidney health.

Renal Mechanisms of Association between Fibroblast Growth Factor 1 and Blood Pressure.

The fibroblast growth factor 1 (FGF1) gene is expressed primarily in the kidney and may contribute to hypertension. However, the biologic mechanisms underlying the association between FGF1 and BP regulation remain unknown. We report that the major allele of FGF1 single nucleotide polymorphism rs152524 was associated in a dose-dependent manner with systolic BP (P = 9.65 × 10(-5)) and diastolic BP (P = 7.61 × 10(-3)) in a meta-analysis of 14,364 individuals and with renal expression of FGF1 mRNA in 126 human kidneys (P=9.0 × 10(-3)). Next-generation RNA sequencing revealed that upregulated renal expression of FGF1 or of each of the three FGF1 mRNA isoforms individually was associated with higher BP. FGF1-stratified coexpression analysis in two separate collections of human kidneys identified 126 FGF1 partner mRNAs, of which 71 and 63 showed at least nominal association with systolic and diastolic BP, respectively. Of those mRNAs, seven mRNAs in five genes (MME, PTPRO, REN, SLC12A3, and WNK1) had strong prior annotation to BP or hypertension. MME, which encodes an enzyme that degrades circulating natriuretic peptides, showed the strongest differential coexpression with FGF1 between hypertensive and normotensive kidneys. Furthermore, higher level of renal FGF1 expression was associated with lower circulating levels of atrial and brain natriuretic peptides. These findings indicate that FGF1 expression in the kidney is at least under partial genetic control and that renal expression of several FGF1 partner genes involved in the natriuretic peptide catabolism pathway, renin-angiotensin cascade, and sodium handling network may explain the association between FGF1 and BP.

Signatures of miR-181a on the Renal Transcriptome and Blood Pressure.

MicroRNA-181a binds to the 3' untranslated region of messenger RNA (mRNA) for renin, a rate-limiting enzyme of the renin-angiotensin system. Our objective was to determine whether this molecular interaction translates into a clinically meaningful effect on blood pressure and whether circulating miR-181a is a measurable proxy of blood pressure. In 200 human kidneys from the TRANScriptome of renaL humAn TissuE (TRANSLATE) study, renal miR-181a was the sole negative predictor of renin mRNA and a strong correlate of circulating miR-181a. Elevated miR-181a levels correlated positively with systolic and diastolic blood pressure in TRANSLATE, and this association was independent of circulating renin. The association between serum miR-181a and systolic blood pressure was replicated in 199 subjects from the Genetic Regulation of Arterial Pressure of Humans In the Community (GRAPHIC) study. Renal immunohistochemistry and in situ hybridization showed that colocalization of miR-181a and renin was most prominent in collecting ducts where renin is not released into the systemic circulation. Analysis of 69 human kidneys characterized by RNA sequencing revealed that miR-181a was associated with downregulation of four mitochondrial pathways and upregulation of 41 signaling cascades of adaptive immunity and inflammation. We conclude that renal miR-181a has pleiotropic effects on pathways relevant to blood pressure regulation and that circulating levels of miR-181a are both a measurable proxy of renal miR-181a expression and a novel biochemical correlate of blood pressure.

Male-specific region of the Y chromosome and cardiovascular risk: phylogenetic analysis and gene expression studies.

OBJECTIVE: Haplogroup I of male-specific region of the human Y chromosome is associated with 50% increased risk of coronary artery disease. It is not clear to what extent conventional cardiovascular risk factors and genes of the male-specific region may explain this association. APPROACH AND RESULTS: A total of 1988 biologically unrelated men from 4 white European populations were genotyped using 11 Y chromosome single nucleotide polymorphisms and classified into 13 most common European haplogroups. Approximately 75% to 93% of the haplotypic variation of the Y chromosome in all cohorts was attributable to I, R1a, and R1b1b2 lineages. None of traditional cardiovascular risk factors, including body mass index, blood pressures, lipids, glucose, C-reactive protein, creatinine, and insulin resistance, was associated with haplogroup I of the Y chromosome in the joint inverse variance meta-analysis. Fourteen of 15 ubiquitous single-copy genes of the male-specific region were expressed in human macrophages. When compared with men with other haplogroups, carriers of haplogroup I had ≈ 0.61- and 0.64-fold lower expression of ubiquitously transcribed tetratricopeptide repeat, Y-linked gene (UTY) and protein kinase, Y-linked, pseudogene (PRKY) in macrophages (P=0.0001 and P=0.002, respectively). CONCLUSIONS: Coronary artery disease predisposing haplogroup I of the Y chromosome is associated with downregulation of UTY and PRKY genes in macrophages but not with conventional cardiovascular risk factors.

Genetic imputation of kidney transcriptome, proteome and multi-omics illuminates new blood pressure and hypertension targets.

Genetic mechanisms of blood pressure (BP) regulation remain poorly defined. Using kidney-specific epigenomic annotations and 3D genome information we generated and validated gene expression prediction models for the purpose of transcriptome-wide association studies in 700 human kidneys. We identified 889 kidney genes associated with BP of which 399 were prioritised as contributors to BP regulation. Imputation of kidney proteome and microRNAome uncovered 97 renal proteins and 11 miRNAs associated with BP. Integration with plasma proteomics and metabolomics illuminated circulating levels of myo-inositol, 4-guanidinobutanoate and angiotensinogen as downstream effectors of several kidney BP genes (SLC5A11, AGMAT, AGT, respectively). We showed that genetically determined reduction in renal expression may mimic the effects of rare loss-of-function variants on kidney mRNA/protein and lead to an increase in BP (e.g., ENPEP). We demonstrated a strong correlation (r = 0.81) in expression of protein-coding genes between cells harvested from urine and the kidney highlighting a diagnostic potential of urinary cell transcriptomics. We uncovered adenylyl cyclase activators as a repurposing opportunity for hypertension and illustrated examples of BP-elevating effects of anticancer drugs (e.g. tubulin polymerisation inhibitors). Collectively, our studies provide new biological insights into genetic regulation of BP with potential to drive clinical translation in hypertension.

Genome-wide study investigating effector genes and polygenic prediction for kidney function in persons with ancestry from Africa and the Americas.

Chronic kidney disease is a leading cause of death and disability globally and impacts individuals of African ancestry (AFR) or with ancestry in the Americas (AMS) who are under-represented in genome-wide association studies (GWASs) of kidney function. To address this bias, we conducted a large meta-analysis of GWASs of estimated glomerular filtration rate (eGFR) in 145,732 AFR and AMS individuals. We identified 41 loci at genome-wide significance (p < 5 × 10-8), of which two have not been previously reported in any ancestry group. We integrated fine-mapped loci with epigenomic and transcriptomic resources to highlight potential effector genes relevant to kidney physiology and disease, and reveal key regulatory elements and pathways involved in renal function and development. We demonstrate the varying but increased predictive power offered by a multi-ancestry polygenic score for eGFR and highlight the importance of population diversity in GWASs and multi-omics resources to enhance opportunities for clinical translation for all.

Proteasix: a tool for automated and large-scale prediction of proteases involved in naturally occurring peptide generation.

In this study, we have developed Proteasix, an open-source peptide-centric tool that can be used to predict in silico the proteases involved in naturally occurring peptide generation. We developed a curated cleavage site (CS) database, containing 3500 entries about human protease/CS combinations. On top of this database, we built a tool, Proteasix, which allows CS retrieval and protease associations from a list of peptides. To establish the proof of concept of the approach, we used a list of 1388 peptides identified from human urine samples, and compared the prediction to the analysis of 1003 randomly generated amino acid sequences. Metalloprotease activity was predominantly involved in urinary peptide generation, and more particularly to peptides associated with extracellular matrix remodelling, compared to proteins from other origins. In comparison, random sequences returned almost no results, highlighting the specificity of the prediction. This study provides a tool that can facilitate linking of identified protein fragments to predicted protease activity, and therefore into presumed mechanisms of disease. Experiments are needed to confirm the in silico hypotheses; nevertheless, this approach may be of great help to better understand molecular mechanisms of disease, and define new biomarkers, and therapeutic targets.

Towards Faster Gene Expression Prediction via Dimensionality Reduction and Feature Selection.

The majority of genes have a genetic component to their expression. Elastic nets have been shown effective at predicting tissue-specific, individual-level gene expression from genotype data. We apply principal component analysis (PCA), linkage disequilibrium pruning, or the combination of the two to reduce, or generate, a lower-dimensional representation of the genetic variants used as inputs to the elastic net models for the prediction of gene expression. Our results show that, in general, elastic nets attain their best performance when all genetic variants are included as inputs; however, a relatively low number of principal components can effectively summarize the majority of genetic variation while reducing the overall computation time. Specifically, 100 principal components reduce the computational time of the models by over 80% with only an 8% loss in R2. Finally, linkage disequilibrium pruning does not effectively reduce the genetic variants for predicting gene expression. As predictive models are commonly made for over 27,000 genes for more than 50 tissues, PCA may provide an effective method for reducing the computational burden of gene expression analysis.

Telomere therapy for chronic kidney disease.

Chronic kidney disease (CKD) is estimated to affect almost 10% of individuals worldwide and is one of the leading causes of morbidity and mortality. Renal fibrosis, a central pathway in CKD progression (irrespective of etiology), is associated with shortened or dysfunctional telomeres in animal studies. Telomeres are specialized nucleoprotein structures located at the chromosome end that maintain genomic integrity. The mechanisms of associations between telomere length and CKD have not yet been fully elucidated, however, CKD patients with shorter telomere length may have decreased renal function and a higher mortality rate. A plethora of ongoing research has focused on possible therapeutic applications of telomeres with the overall goal to preserve telomere length as a therapy to treat CKD.

Chronic kidney disease or CKD is one of the leading causes of illness and death worldwide. Scarring of the kidney tissue that occurs in CKD has been associated with shorter telomeres in studies using rats. Telomeres, said to act as the cellular 'shoelace caps', maintain the structure of chromosomes, allowing for genetic material inside cells to divide correctly. The length of telomeres (TL) is influenced by diverse factors such as genetics and lifestyle. The underlying processes for the associations between TL and CKD are still not understood, however, patients with CKD and shorter TL have reduced kidney function and an increased death rate. Therefore, research is focused on possible ways to preserve TL and treat CKD.

Adapting Random Forests to Predict Obesity-Associated Gene Expression.

Random forests (RFs) are effective at predicting gene expression from genotype data. However, a comparison of RF regressors and classifiers, including feature selection and encoding, has been under-explored in the context of gene expression prediction. Specifically, we examine the role of ordinal or one-hot encoding and of data balancing via oversam-pling in the prediction of obesity-associated gene expression. Our work shows that RFs compete with PrediXcan in the prediction of obesity-associated gene expression in subcutaneous adipose tissue, a highly relevant tissue to obesity. Additionally, RFs generate predictions for obesity-associated genes where PrediXcan fails to do so.

Effects of iron substitution and anti-site disorder on crystal structures, vibrational, optical and magnetic properties of double perovskites Sr2(Fe1-xNix)TeO6.

The double-perovskite series, Sr2(Fe1-xNix)TeO6 (x = 0, 0.25, 0.50, 0.75, and 1) has been synthesized in polycrystalline form by solid-state reaction at 1300 K in air. Their crystal structures were probed by powder X-ray diffraction at room temperature. Rietveld analysis revealed that all samples crystallize in the monoclinic space group I2/m. The double-perovskite structures ideally contain two alternating types of octahedra (Fe/Ni)2dO6 and (Te)2aO6, tilted in the system (a-a-c0). However, the refinements have shown a complex distribution of all three cations over the two available octahedral sites; 2d (½, ½, 0) and 2a (0, 0, 0). Raman spectroscopy further complements the obtained results, by revealing a tiny increase of the wavenumber of some Raman modes when Fe is substituted by Ni. The optical characteristics of the series were determined by fitting diffuse reflectance UV/Vis spectra enabling the optical band gaps to be derived from Tauc method and derivation of absorption spectra fitting (DASF) techniques. Analyses of the obtained 57Fe Mössbauer hyperfine parameters at room temperature of samples with compositions x = 0, 0.25, 0.50 and 0.75 reveal the presence of Fe3+ in high-spin state with an anti-site disorder of Fe-Ni-Te cations in distorted octahedral environments (site 2d and 2a). The results show that significant correlations exist between the crystal structures and physical properties of double perovskites containing B site transition elements of different charge and size. Temperature-dependent magnetic susceptibility data show magnetic transitions below 40(1) K (38(1) K, 31(1) K, 25(1) K, 20(1) K, and 35(1) K for x = 0, 0.25, 0.50, 0.75, and 1, respectively. A divergence between FC and ZFC curves for all compositions has been observed. The results show that the ground states of the doped materials might be spin glasses or magnetically ordered.

Contributions of obesity to kidney health and disease: insights from Mendelian randomization and the human kidney transcriptomics.

AIMS: Obesity and kidney diseases are common complex disorders with an increasing clinical and economic impact on healthcare around the globe. Our objective was to examine if modifiable anthropometric obesity indices show putatively causal association with kidney health and disease and highlight biological mechanisms of potential relevance to the association between obesity and the kidney. METHODS AND RESULTS: We performed observational, one-sample, two-sample Mendelian randomization (MR) and multivariable MR studies in ∼300 000 participants of white-British ancestry from UK Biobank and participants of predominantly European ancestry from genome-wide association studies. The MR analyses revealed that increasing values of genetically predicted body mass index and waist circumference were causally associated with biochemical indices of renal function, kidney health index (a composite renal outcome derived from blood biochemistry, urine analysis, and International Classification of Disease-based kidney disease diagnoses), and both acute and chronic kidney diseases of different aetiologies including hypertensive renal disease and diabetic nephropathy. Approximately 13-16% and 21-26% of the potentially causal effect of obesity indices on kidney health were mediated by blood pressure and type 2 diabetes, respectively. A total of 61 pathways mapping primarily onto transcriptional/translational regulation, innate and adaptive immunity, and extracellular matrix and metabolism were associated with obesity measures in gene set enrichment analysis in up to 467 kidney transcriptomes. CONCLUSIONS: Our data show that a putatively causal association of obesity with renal health is largely independent of blood pressure and type 2 diabetes and uncover the signatures of obesity on the transcriptome of human kidney.

Investigation of Copy Number Variation in South African Patients With Congenital Heart Defects.

BACKGROUND: Congenital heart disease (CHD) is a leading non-infectious cause of pediatric morbidity and mortality worldwide. Although the etiology of CHD is poorly understood, genetic factors including copy number variants (CNVs) contribute to the risk of CHD in individuals of European ancestry. The presence of rare CNVs in African CHD populations is unknown. This study aimed to identify pathogenic and likely pathogenic CNVs in South African patients with CHD. METHODS: Genotyping was performed on 90 patients with nonsyndromic CHD using the Affymetrix CytoScan HD platform. These data were used to identify large, rare CNVs in known CHD-associated genes and candidate genes. RESULTS: We identified eight CNVs overlapping known CHD-associated genes (GATA4, CRKL, TBX1, FLT4, B3GAT3, NSD1) in six patients. The analysis also revealed CNVs encompassing five candidate genes likely to play a role in the development of CHD (DGCR8, KDM2A, JARID2, FSTL1, CYFIP1) in five patients. One patient was found to have 47, XXY karyotype. We report a total discovery yield of 6.7%, with 5.6% of the cohort carrying pathogenic or likely pathogenic CNVs expected to cause the observed phenotypes. CONCLUSIONS: In this study, we show that chromosomal microarray is an effective technique for identifying CNVs in African patients diagnosed with CHD and have demonstrated results similar to previous CHD genetic studies in Europeans. Novel potential CHD genes were also identified, indicating the value of genetic studies of CHD in ancestrally diverse populations.

Nanoparticle-Enabled Enrichment of Longitudinal Blood Proteomic Fingerprints in Alzheimer's Disease.

Blood-circulating biomarkers have the potential to detect Alzheimer's disease (AD) pathology before clinical symptoms emerge and to improve the outcomes of clinical trials for disease-modifying therapies. Despite recent advances in understanding concomitant systemic abnormalities, there are currently no validated or clinically used blood-based biomarkers for AD. The extremely low concentration of neurodegeneration-associated proteins in blood necessitates the development of analytical platforms to address the "signal-to-noise" issue and to allow an in-depth analysis of the plasma proteome. Here, we aimed to discover and longitudinally track alterations of the blood proteome in a transgenic mouse model of AD, using a nanoparticle-based proteomics enrichment approach. We employed blood-circulating, lipid-based nanoparticles to extract, analyze and monitor AD-specific protein signatures and to systemically uncover molecular pathways associated with AD progression. Our data revealed the existence of multiple proteomic signals in blood, indicative of the asymptomatic stages of AD. Comprehensive analysis of the nanoparticle-recovered blood proteome by label-free liquid chromatography-tandem mass spectrometry resulted in the discovery of AD-monitoring signatures that could discriminate the asymptomatic phase from amyloidopathy and cognitive deterioration. While the majority of differentially abundant plasma proteins were found to be upregulated at the initial asymptomatic stages, the abundance of these molecules was significantly reduced as a result of amyloidosis, suggesting a disease-stage-dependent fluctuation of the AD-specific blood proteome. The potential use of the proposed nano-omics approach to uncover information in the blood that is directly associated with brain neurodegeneration was further exemplified by the recovery of focal adhesion cascade proteins. We herein propose the integration of nanotechnology with already existing proteomic analytical tools in order to enrich the identification of blood-circulating signals of neurodegeneration, reinvigorating the potential clinical utility of the blood proteome at predicting the onset and kinetics of the AD progression trajectory.