Towards the Design of a Smartphone-Based Biofeedback Breathing Training: Indentifying Diaphragmatic Breathing Patterns From a Smartphones\u27 Microphone

Asthma, diabetes, hypertension, or major depression are non-communicable diseases (NCDs) and impose a major burden on global health. Stress is linked to both the causes and consequences of NCDs and it has been shown that biofeedback-based breathing trainings (BBTs) are effective in coping with stress. Here, diaphragmatic breathing, i.e. deep abdominal breathing, belongs to the most distinguished breathing techniques. However, high costs and low scalability of state-of-the-art BBTs that require expensive medical hardware and health professionals, represent a significant barrier for their widespread adoption. Health information technology has the potential to address this important practical problem. Particularly, it has been shown that a smartphone microphone has the ability to record audio signals from exhalation in a quality that can be compared to professional respiratory devices. As this finding is highly relevant for low-cost and scalable smartphone-based BBTs (SBBT) and – to the best of our knowledge - because it has not been investigated so far, we aim to design and evaluate the efficacy of such a SBBT. As a very first step, we apply design-science research and investigate in this research-in-progress the relationship of diaphragmatic breathing and its acoustic components by just using a smartphone’s microphone. For that purpose, we review related work and develop our hypotheses based on justificatory knowledge from physiology, physics and acoustics. We finally describe a laboratory study that is used to test our hypotheses. We conclude with a brief outlook on future work

Early detection of mild cognitive impairment with in-home sensors to monitor behavior patterns in community-dwelling senior citizens in Singapore: Cross-sectional feasibility study

Singapore Management University; National Medical Research Council’s Healthcare Research Scholarshi

Association of eGFR-Related Loci Identified by GWAS with Incident CKD and ESRD

Family studies suggest a genetic component to the etiology of chronic kidney disease (CKD) and end stage renal disease (ESRD). Previously, we identified 16 loci for eGFR in genome-wide association studies, but the associations of these single nucleotide polymorphisms (SNPs) for incident CKD or ESRD are unknown. We thus investigated the association of these loci with incident CKD in 26,308 individuals of European ancestry free of CKD at baseline drawn from eight population-based cohorts followed for a median of 7.2 years (including 2,122 incident CKD cases defined as eGFR <60ml/min/1.73m2 at follow-up) and with ESRD in four case-control studies in subjects of European ancestry (3,775 cases, 4,577 controls). SNPs at 11 of the 16 loci (UMOD, PRKAG2, ANXA9, DAB2, SHROOM3, DACH1, STC1, SLC34A1, ALMS1/NAT8, UBE2Q2, and GCKR) were associated with incident CKD; p-values ranged from p = 4.1e-9 in UMOD to p = 0.03 in GCKR. After adjusting for baseline eGFR, six of these loci remained significantly associated with incident CKD (UMOD, PRKAG2, ANXA9, DAB2, DACH1, and STC1). SNPs in UMOD (OR = 0.92, p = 0.04) and GCKR (OR = 0.93, p = 0.03) were nominally associated with ESRD. In summary, the majority of eGFR-related loci are either associated or show a strong trend towards association with incident CKD, but have modest associations with ESRD in individuals of European descent. Additional work is required to characterize the association of genetic determinants of CKD and ESRD at different stages of disease progression

1000 Genomes-based meta-analysis identifies 10 novel loci for kidney function

HapMap imputed genome-wide association studies (GWAS) have revealed &gt;50 loci at which common variants with minor allele frequency &gt;5% are associated with kidney function. GWAS using more complete reference sets for imputation, such as those from The 1000 Genomes project, promise to identify novel loci that have been missed by previous efforts. To investigate the value of such a more complete variant catalog, we conducted a GWAS meta-analysis of kidney function based on the estimated glomerular filtration rate (eGFR) in 110,517 European ancestry participants using 1000 Genomes imputed data. We identified 10 novel loci with p-value &lt; 5 × 10(-8) previously missed by HapMap-based GWAS. Six of these loci (HOXD8, ARL15, PIK3R1, EYA4, ASTN2, and EPB41L3) are tagged by common SNPs unique to the 1000 Genomes reference panel. Using pathway analysis, we identified 39 significant (FDR &lt; 0.05) genes and 127 significantly (FDR &lt; 0.05) enriched gene sets, which were missed by our previous analyses. Among those, the 10 identified novel genes are part of pathways of kidney development, carbohydrate metabolism, cardiac septum development and glucose metabolism. These results highlight the utility of re-imputing from denser reference panels, until whole-genome sequencing becomes feasible in large samples

Integration of genome-wide association studies with biological knowledge identifies six novel genes related to kidney function

In conducting genome-wide association studies (GWAS), analytical approaches leveraging biological information may further understanding of the pathophysiology of clinical traits. To discover novel associations with estimated glomerular filtration rate (eGFR), a measure of kidney function, we developed a strategy for integrating prior biological knowledge into the existing GWAS data for eGFR from the CKDGen Consortium. Our strategy focuses on single nucleotide polymorphism (SNPs) in genes that are connected by functional evidence, determined by literature mining and gene ontology (GO) hierarchies, to genes near previously validated eGFR associations. It then requires association thresholds consistent with multiple testing, and finally evaluates novel candidates by independent replication. Among the samples of European ancestry, we identified a genome-wide significant SNP in FBXL20 (P = 5.6 × 10−9) in meta-analysis of all available data, and additional SNPs at the INHBC, LRP2, PLEKHA1, SLC3A2 and SLC7A6 genes meeting multiple-testing corrected significance for replication and overall P-values of 4.5 × 10−4-2.2 × 10−7. Neither the novel PLEKHA1 nor FBXL20 associations, both further supported by association with eGFR among African Americans and with transcript abundance, would have been implicated by eGFR candidate gene approaches. LRP2, encoding the megalin receptor, was identified through connection with the previously known eGFR gene DAB2 and extends understanding of the megalin system in kidney function. These findings highlight integration of existing genome-wide association data with independent biological knowledge to uncover novel candidate eGFR associations, including candidates lacking known connections to kidney-specific pathways. The strategy may also be applicable to other clinical phenotypes, although more testing will be needed to assess its potential for discovery in genera

Genome-wide association and functional follow-up reveals new loci for kidney function

Chronic kidney disease (CKD) is an important public health problem with a genetic component. We performed genome-wide association studies in up to 130,600 European ancestry participants overall, and stratified for key CKD risk factors. We uncovered 6 new loci in association with estimated glomerular filtration rate (eGFR), the primary clinical measure of CKD, in or near MPPED2, DDX1, SLC47A1, CDK12, CASP9, and INO80. Morpholino knockdown of mpped2 and casp9 in zebrafish embryos revealed podocyte and tubular abnormalities with altered dextran clearance, suggesting a role for these genes in renal function. By providing new insights into genes that regulate renal function, these results could further our understanding of the pathogenesis of CKD

Genome-wide association meta-analyses and fine-mapping elucidate pathways influencing albuminuria

Abstract: Increased levels of the urinary albumin-to-creatinine ratio (UACR) are associated with higher risk of kidney disease progression and cardiovascular events, but underlying mechanisms are incompletely understood. Here, we conduct trans-ethnic (n = 564,257) and European-ancestry specific meta-analyses of genome-wide association studies of UACR, including ancestry- and diabetes-specific analyses, and identify 68 UACR-associated loci. Genetic correlation analyses and risk score associations in an independent electronic medical records database (n = 192,868) reveal connections with proteinuria, hyperlipidemia, gout, and hypertension. Fine-mapping and trans-Omics analyses with gene expression in 47 tissues and plasma protein levels implicate genes potentially operating through differential expression in kidney (including TGFB1, MUC1, PRKCI, and OAF), and allow coupling of UACR associations to altered plasma OAF concentrations. Knockdown of OAF and PRKCI orthologs in Drosophila nephrocytes reduces albumin endocytosis. Silencing fly PRKCI further impairs slit diaphragm formation. These results generate a priority list of genes and pathways for translational research to reduce albuminuria