Biology subjects

Tin, A.

Publications and source records attributed to Tin, A..

8 recordsLinked to original sources

bioRxiv2022

RAPTOR: A Five-Safes approach to a secure, cloud native and serverless genomics data repository

Genomic researchers are increasingly utilizing commercial cloud platforms (CCPs) to manage their data and analytics needs. Commercial clouds allow researchers to grow their storage and analytics capacity on demand, keeping pace with expanding project data footprints and enabling researchers to avoid large capital expenditures while paying only for IT capacity consumed by their project. Cloud computing also allows researchers to overcome common network and storage bottlenecks encountered when combining or re-analysing large datasets. However, cloud computing presents a new set of challenges. Without adequate security controls, the risk of unauthorised access may be higher for data stored on the cloud. In addition, regulators are increasingly mandating data access patterns and specific security protocols on the storage and use of genomic data to safeguard rights of the study participants. While CCPs provide tools for security and regulatory compliance, utilising these tools to build the necessary controls required for cloud solutions is not trivial as such skill sets are not commonly found in a genomics lab. The Research Assets Provisioning and Tracking Online Repository (RAPTOR) by the Genome Institute of Singapore is a cloud native genomics data repository and analytics platform focusing on security and regulatory compliance. Using a "five-safes" framework (Safe Purpose, Safe People, Safe Settings, Safe Data and Safe Output), RAPTOR provides security and governance controls to data contributors and users leveraging cloud computing for sharing and analysis of large genomic datasets without the risk of security breaches or running afoul of regulations. RAPTOR can also enable data federation with other genomic data repositories using GA4GH community-defined standards, allowing researchers to boost the statistical power of their work and overcome geographic and ancestry limitations of data sets

genomics↗

bioRxiv2021

Adduction Induces Large Optic Nerve Head Deformations in Subjects with Normal Tension Glaucoma

Purpose: To assess optic nerve head (ONH) deformations and strains during adduction, abduction, and intraocular pressure (IOP) elevation in subjects with high-tension glaucoma (HTG) and normal-tension glaucoma (NTG). Design: Clinic-based cross-sectional study. Participants: 114 HTG subjects and 114 NTG subjects. Methods. We recruited 228 subjects (114 subjects with HTG [pre-treatment IOP > 21mmHg] and 114 with NTG [pre-treatment IOP < 21mmHg]). For each subject, we imaged the ONH using spectral-domain optical coherence tomography (OCT) under the following conditions: (1) primary gaze, (2) 20 degree adduction, (3) 20 degree abduction, and (4) primary gaze with acute IOP elevation (to approximately 33 mmHg) achieved through ophthalmodynamometry. For each OCT volume, we automatically segmented the prelaminar tissue (PLT), the choroid, the sclera and the lamina cribrosa (LC) using a deep learning algorithm. We also digitally aligned the OCT volumes obtained from (2)-(4) to the primary gaze volume (1) before performing digital volume correlation (DVC) analysis to quantify IOP- and gaze-induced ONH tissues three-dimensional displacements and effective strain (a local measure of tissue deformation) for all scenarios. Main Outcome Measures: Three-dimensional ONH displacements and strains. Results: Across all subjects, adduction generated high effective strain (4.2 {+/-} 1.4%) in the ONH tissues with no significant difference (p>0.05) with those induced by IOP elevation (4.5 {+/-} 1.5%); while abduction generated significantly lower (p = 0.014) effective strain (3.8 {+/-} 1.1%). Interestingly, the LC of HTG subjects exhibited significantly higher effective strain than those of NTG subjects under IOP elevation (HTG:4.6 {+/-} 1.7% vs NTG:4.1 {+/-} 1.5%, p = 0.047). Conversely, the LC tissue of NTG subjects exhibited significantly higher effective strain than those of HTG subjects under adduction (NTG: 4.9 {+/-} 1.9% vs HTG: 4.0 {+/-} 1.4%, p = 0.041). Conclusion: We found that adduction produced comparable strains and displacements as IOP elevation. We also found that NTG subjects experienced higher strains due to adduction than HTG subjects, while HTG subjects experienced higher strain due to IOP elevation than NTG subjects - and that these differences were most pronounced in the LC tissue.

bioengineering↗

bioRxiv2021

Large Bi-Ethnic Study of Plasma Proteome Leads to Comprehensive Mapping of cis-pQTL and Models for Proteome-wide Association Studies

Improved understanding of genetic regulation of proteome can facilitate the identification of causal mechanisms for complex traits. We analyzed data on 4,657 plasma proteins from 7,213 European American (EA) and 1,871 African American (AA) individuals from the ARIC study, and further replicated findings on 467 AA individuals from the AASK study. Here we identified 2,004 proteins in EA and 1,618 in AA, with majority overlapping, which showed associations with common variants in cis-regions. Availability of AA samples led to smaller credible sets and significant number of population-specific cis-pQTLs. Elastic-net produced powerful models for protein prediction in both populations. An application of proteome-wide association studies (PWAS) to serum urate and gout, implicated several proteins, including IL1RN, revealing the promise of the drug anakinra to treat acute gout flares. Our study demonstrates the value of large and diverse ancestry study for genetic mechanisms of molecular phenotypes and their relationship with complex traits.

genetics↗

bioRxiv2020

Polygenic Risk Scores for Kidney Function to the Circulating Proteome, and Incident Kidney Diseases: the Atherosclerosis Risk in Communities Study

Genome-wide association studies (GWAS) have revealed numerous loci for kidney function (estimated glomerular filtration rate, eGFR). The relationship of polygenic predictors of eGFR, risk of incident adverse kidney outcomes, and the plasma proteome is not known. We developed a genome-wide polygenic risk score (PRS) using a weighted average of 1.2 million SNPs for eGFR using the LDpred algorithm, summary statistics generated by a European-ancestry (EA) meta-analysis of the CKDGen Consortium (N=558,423) and UK Biobank GWAS for eGFR (90% of the cohort; N=289,432), followed by best parameter selection using data from the remaining 10% of the UK Biobank (N=32,159). We then tested the association of the PRS among 8,886 EA participants in the Atherosclerosis Risk in Communities (ARIC) study (mean age: 54{+/-}6 years, 53% female) with incident chronic kidney disease (CKD), end stage kidney disease (ESKD), kidney failure (KF), and acute kidney injury (AKI). We also examined 4,877 plasma proteins measured at two time points (visit 3 (1993-95) and visit 5 (2011-13)) in relation to the PRS and compared associations between the proteome and eGFR itself. All models were adjusted for age, sex, center, and the first 10 principal components of ancestry. The developed PRS had an R2 for eGFR of 0.07 in ARIC. Over 30 years of follow up, the number of incident CKD, ESKD, KF, and AKI were 2,959, 137, 470, and 1,723, respectively. The PRS showed significant associations with all outcomes: hazard ratios (95% CI) per 1 SD lower PRS were 1.33 (1.28, 1.39), 1.20 (1.00, 1.42), 1.17 (1.06, 1.28), and 1.07 (1.02, 1.12) for incident CKD, ESKD, KF, and AKI respectively. The PRS was significantly associated (Bonferroni threshold P<1.02 x 10-5) with 108 proteins at both time points. The strongest associations were with cystatin-C (a marker of kidney function used in clinical practice), collagen alpha-1 (XV) chain, and desmocollin-2. All significant correlations with the PRS were negative, except those of testican-2 and angiostatin. Correlations of proteins with eGFR were much stronger than those with the PRS. Overall, we demonstrated that the PRS for eGFR is now sufficiently strong to capture risk for a spectrum of incident kidney diseases as well as broadly influence the plasma proteome.

genetics↗

bioRxiv2020

Multiethnic catalog of structural variants and their translational impact for disease phenotypes across 19,652 genomes

Genome sequencing at population scale provides unprecedented access to the genetic foundations of human phenotypic diversity, but genotype-phenotype association analyses limited to small variants have failed to comprehensively characterize the genetic architecture of human health and disease because they ignore structural variants (SVs) known to contribute to phenotypic variation and pathogenic conditions1-3. Here we demonstrate the significance of SVs when assessing genotype-phenotype associations and the importance of ethnic diversity in study design by analyzing SVs across 19,652 individuals and the translational impact on 4,156 aptamerbased proteomic measurements across 4,021 multi-ethnic samples. The majority of 304,533 SVs detected are rare, although we identified 2,336 protein-coding genes impacted by common SVs.\ We identified 64 significant SV-protein associations that comprise 36 cis- and 28 trans-acting relationships, and 21 distinct SV regions overlapped with genome-wide association study loci. These findings represent a more comprehensive mapping of regulatory and translational endophenotypes underlying health and disease.

genomics↗

bioRxiv2019

Kidney Function and Blood Pressure: A Bi-directional Mendelian Randomisation Study

ObjectiveTo evaluate the bi-directional causal relation between kidney function and blood pressure. DesignMendelian randomisation study. SettingWe performed two-sample Mendelian randomisation analyses. Genetic instruments of kidney function traits were selected from summary statistics of genome-wide association studies (GWAS) of glomerular filtration rate estimated from serum creatinine (eGFRcr) and blood urea nitrogen (BUN) and were required to be associated with both eGFRcr and BUN to ensure that the instruments were more likely to represent the underlying kidney function. Genetic instruments of blood pressure were selected from summary statistics of GWAS of systolic and diastolic blood pressure. We investigated Mendelian randomisation hypothesis using several alternative approaches, including methods that are most robust to the presence of horizontal pleiotropy. ParticipantsThe summary statistics of eGFRcr included 567,460 participants from 54 cohorts, and the summary statistics of BUN included 243,031 participants from 48 cohorts from the Chronic Kidney Disease Genetics (CKDGen) Consortium. The summary statistics of systolic and diastolic blood pressure included 757,601 participants from the UK Biobank and 78 cohorts from the International Consortium for Blood Pressure (ICBP). ResultsSignificant evidence supported the causal effects of higher kidney function on lower blood pressure with multiple methods. Based on the mode-based Mendelian randomisation analysis approach, known for its robustness to the presence of pleiotropic effect, the effect estimate for 1 SD higher in eGFRcr was -0.17 SD unit (95 % CI: -0.09 to -0.24) in systolic blood pressure (SBP) and -0.15 SD unit (95% CI: -0.07 to -0.22) in diastolic blood pressure (DBP). In contrast, the causal effects of blood pressure on kidney function were not statistically significant. ConclusionsMendelian randomisation analyses support causal effects of higher kidney function on lower blood pressure. These results suggest preventing kidney function decline can reduce the public health burden of hypertension.

genetics↗

bioRxiv2019

Mitochondrial DNA Copy Number (mtDNA-CN) Can Influence Mortality and Cardiovascular Disease via Methylation of Nuclear DNA CpGs

BackgroundMitochondrial DNA copy number (mtDNA-CN) has been associated with a variety of aging-related diseases, including all-cause mortality. However, the mechanism by which mtDNA-CN influences disease is not currently understood. One such mechanism may be through regulation of nuclear gene expression via the modification of nuclear DNA (nDNA) methylation. MethodsTo investigate this hypothesis, we assessed the relationship between mtDNA-CN and nDNA methylation in 2,507 African American (AA) and European American (EA) participants from the Atherosclerosis Risk in Communities (ARIC) study. To validate our findings we assayed an additional 2,528 participants from the Cardiovascular Health Study (CHS) (N=533) and Framingham Heart Study (FHS) (N=1,995). We further assessed the effect of experimental modification of mtDNA-CN through knockout of TFAM, a regulator of mtDNA replication, via CRISPR-Cas9. ResultsThirty-four independent CpGs were associated with mtDNA-CN at genome-wide significance (P<5x10-8). Meta-analysis across all cohorts identified six mtDNA-CN associated CpGs at genome-wide significance (P<5x10-8). Additionally, over half of these CpGs were associated with phenotypes known to be associated with mtDNA-CN, including coronary heart disease, cardiovascular disease, and mortality. Experimental modification of mtDNA-CN demonstrated that modulation of mtDNA-CN directly drives changes in nDNA methylation and gene expression of specific CpGs and nearby transcripts. Strikingly, the neuroactive ligand receptor interaction KEGG pathway was found to be highly overrepresented in the ARIC cohort (P= 5.24x10-12), as well as the TFAM knockout methylation (P=4.41x10-4) and expression (P=4.30x10-4) studies. ConclusionsThese results demonstrate that changes in mtDNA-CN influence nDNA methylation at specific loci and result in differential expression of specific genes that may impact human health and disease via altered cell signaling.

genomics↗

bioRxiv2019

GSTM1 copy number is not associated with risk of kidney failure in a large cohort

Deletion of glutathione S-transferase {micro}1 (GSTM1) is common in populations and has been asserted to associate with chronic kidney disease progression in some research studies. The association needs to be validated. We estimated GSTM1 copy number using whole exome sequencing data in the DiscovEHR cohort. Kidney failure was defined as requiring dialysis or receiving kidney transplant using data from the electronic health record and linkage to the United States Renal Data System, or the most recent eGFR < 15 ml/min/1.73m2. In a cohort of 46,983 unrelated participants, 28.8% of blacks and 52.1% of whites had 0 copies of GSTM1. Over a mean of 9.2 years follow-up, 645 kidney failure events were observed in 46,187 white participants, and 28 in 796 black participants. No significant association was observed between GSTM1 copy number and kidney failure in Cox regression adjusting for age, sex, BMI, smoking status, genetic principal components, or co-morbid conditions (hypertension, diabetes, heart failure, coronary artery disease, and stroke), whether using a genotypic, dominant, or recessive model. In sensitivity analyses, GSTM1 copy number was not associated with kidney failure in participants that were 45 years or older at baseline, had baseline eGFR < 60 ml/min per 1.73 m2, or with baseline year between 1996-2002. In conclusion, we found no association between GSTM1 copy number and kidney failure in a large cohort study.\n\nTranslational StatementDeletion of GSTM1 has been shown to be associated with higher risk of kidney failure. However, inconsistent results have been reported. We used electronic health record and whole exome sequencing data of a large cohort from a single healthcare system to evaluate the association between GSTM1 copy number and risk of kidney failure. We found no significant association between GSTM1 copy number and risk of kidney failure overall, or in multiple sensitivity and subgroup analyses.

genetics↗