Substantial anti-gout effect conferred by common and rare dysfunctional variants of URAT1/SLC22A12

Abstract Objectives Gout, caused by chronic elevation of serum uric acid levels, is the commonest form of inflammatory arthritis. The causative effect of common and rare variants of ATP-binding cassette transporter G2 (ABCG2/BCRP) on gout risk has been studied, but, little attention has been paid to the effect of common (rs121907892, p. W258X) and rare variants of urate transporter 1 (URAT1/SLC22A12) on gout, despite dysfunctional variants of URAT1 having been identified as pathophysiological causes of renal hypouricemia. Methods To address this important but overlooked issue, we investigated the effects of these URAT1 variants on gout susceptibility, using targeted exon sequencing on 480 clinically-defined gout cases and 480 controls of Japanese male in combination with a series of functional analyses of newly-identified URAT1 variants. Results Our results show that both common and rare dysfunctional variants of URAT1 markedly decrease the risk of gout (OR 0.0338, reciprocal OR 29.6, p = 7.66 × 1 0 −8). Interestingly, we also found that the URAT1-related protective effect on gout eclipsed the ABCG2-related causative effect (OR 2.30 – 3.32). Our findings reveal only one dysfunctional variant of URAT1 to have a substantial anti-gout effect, even in the presence of causative variants of ABCG2, a “gout gene”. Conclusion Our findings provide a better understanding of gout/hyperuricemia and its aetiology that is highly relevant to personalized health care. The substantial anti-gout effect of common and rare variants of URAT1 identified in the present study support the genetic concept of a ‘Common Disease, Multiple Common and Rare Variant’ model.

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CONVOLUTIONAL NEURAL NETWORKS, ANALYTICAL ALGORITHMS, AND PERSONALIZED HEALTH CARE: EMBRACING THE MASSIVE DATA ANALYSIS CAPABILITIES OF DEEP LEARNING ARTIFICIAL INTELLIGENCE SYSTEMS TO COMPLEMENT AND IMPROVE MEDICAL SERVICES

American Journal of Medical Research ◽

10.22381/ajmr5220187 ◽

2018 ◽

Vol 5 (2) ◽

pp. 52 ◽

Cited By ~ 1

Keyword(s):

Artificial Intelligence ◽

Neural Networks ◽

Health Care ◽

Deep Learning ◽

Data Analysis ◽

Convolutional Neural Networks ◽

Massive Data ◽

Personalized Health ◽

Personalized Health Care ◽

Artificial Intelligence Systems

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Personalized health care: From theory to practice

Biotechnology Journal ◽

10.1002/biot.201100297 ◽

2011 ◽

Vol 7 (8) ◽

pp. 973-979 ◽

Cited By ~ 49

Author(s):

Ralph Snyderman

Keyword(s):

Health Care ◽

Theory To Practice ◽

Personalized Health ◽

Personalized Health Care

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Fucosyltransferase Gene Polymorphisms and Lewisb-Negative Status Are Frequent in Swedish Newborns, With Implications for Infectious Disease Susceptibility and Personalized Medicine

Journal of the Pediatric Infectious Diseases Society ◽

10.1093/jpids/piy085 ◽

2018 ◽

Vol 8 (6) ◽

pp. 507-518 ◽

Cited By ~ 4

Author(s):

Jovanka R King ◽

Jezabel Varadé ◽

Lennart Hammarström

Keyword(s):

Disease Susceptibility ◽

Blood Group Antigens ◽

Nucleotide Polymorphisms ◽

Nested Polymerase Chain Reaction ◽

Single Nucleotide ◽

Fucosyltransferase Gene ◽

Genotyping Method ◽

Personalized Health ◽

Personalized Health Care

Abstract Background Single-nucleotide polymorphisms (SNPs) in the fucosyltransferase genes FUT2 and FUT3 have been associated with susceptibility to various infectious and inflammatory disorders. FUT variations influence the expression of human histo-blood group antigens (HBGAs) (H-type 1 and Lewis), which are highly expressed in the gut and play an important role in microbial attachment, metabolism, colonization, and shaping of the microbiome. In particular, FUT polymorphisms confer susceptibility to specific rotavirus and norovirus genotypes, which has important global health implications. Methods We designed a genotyping method using a nested polymerase chain reaction approach to determine the frequency of SNPs in FUT2 and FUT3, thereby inferring the prevalence of Lewisb-positive, Lewisb-negative, secretor, and nonsecretor phenotypes in 520 Swedish newborns. Results There was an increased frequency of homozygotes for the minor allele for 1 SNP in FUT2 and 4 SNPs in FUT3. Overall, 37.3% of newborns were found to have Lewis b negative phenotypes (Le (a+b−) or Le (a−b−). Using our new, sensitive genotyping method, we were able to genetically define the Le (a−b−) individuals based on their secretor status and found that the frequency of Lewis b negative newborns in our cohort was 28%. Conclusions Given the high frequency of fucosyltransferase polymorphisms observed in our newborn cohort and the implications for disease susceptibility, FUT genotyping might play a future role in personalized health care, including recommendations for disease screening, therapy, and vaccination.

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Supporting Personalized Health Care With Social Media Analytics: An Application to Hypothyroidism

ACM Transactions on Computing for Healthcare ◽

10.1145/3468781 ◽

2022 ◽

Vol 3 (1) ◽

pp. 1-28

Author(s):

Giorgio Grani ◽

Andrea Lenzi ◽

Paola Velardi

Keyword(s):

Social Media ◽

Data Extraction ◽

Social Media Analytics ◽

Text Compression ◽

Emotional States ◽

Agglomerative Clustering ◽

Detection Model ◽

Analytic Process ◽

Personalized Health ◽

Personalized Health Care

Social media analytics can considerably contribute to understanding health conditions beyond clinical practice, by capturing patients’ discussions and feelings about their quality of life in relation to disease treatments. In this article, we propose a methodology to support a detailed analysis of the therapeutic experience in patients affected by a specific disease, as it emerges from health forums. As a use case to test the proposed methodology, we analyze the experience of patients affected by hypothyroidism and their reactions to standard therapies. Our approach is based on a data extraction and filtering pipeline, a novel topic detection model named Generative Text Compression with Agglomerative Clustering Summarization ( GTCACS ), and an in-depth data analytic process. We advance the state of the art on automated detection of adverse drug reactions ( ADRs ) since, rather than simply detecting and classifying positive or negative reactions to a therapy, we are capable of providing a fine characterization of patients along different dimensions, such as co-morbidities, symptoms, and emotional states.

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Design and Implementation of a Personalized Health-Care System

Convergence and Hybrid Information Technology - Communications in Computer and Information Science ◽

10.1007/978-3-642-32692-9_29 ◽

2012 ◽

pp. 218-225

Author(s):

Jun-Il Choi ◽

Joong Hyuk Chang

Keyword(s):

Health Care ◽

Health Care System ◽

Design And Implementation ◽

Personalized Health ◽

Personalized Health Care ◽

Care System

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Abstract 46: Whole Genome Sequence Analysis Of Blood Pressure Phenotypes In The Trans-omics For Precision Medicine And Centers For Common Disease Genomics Programs

Circulation ◽

10.1161/circ.141.suppl_1.46 ◽

2020 ◽

Vol 141 (Suppl_1) ◽

Cited By ~ 2

Author(s):

Tanika N Kelly ◽

Xiao Sun ◽

Jennifer A Brody ◽

Sarah A Gagliano ◽

Karen Y He ◽

...

Keyword(s):

Blood Pressure ◽

Precision Medicine ◽

Rare Variants ◽

Minor Allele ◽

Common Disease ◽

Whole Genome ◽

Genome Wide ◽

Novel Variants ◽

Discovery Stage ◽

Genome Wide Significance

Background: Although genome-wide association studies (GWAS) have made important strides in localizing genomic regions associated with blood pressure (BP) phenotypes, the causal mechanisms underlying the vast majority of identified signals remain to be elucidated. Whole genome sequencing (WGS) provides an opportunity for novel genomic discoveries and high-resolution refinement of identified GWAS signals. Methods: This multi-stage genomic study of BP was conducted in an ancestrally diverse sample of up to 735,905 participants from 20 cohorts. In the discovery stage WGS study, variants with minor allele counts >10 were tested for association with systolic BP (SBP), diastolic BP (DBP), and hypertension (HTN) among 50,755 participants from the Trans-Omics for Precision Medicine and Centers for Common Disease Genomics programs using the Analysis Commons cloud based platform. Variants achieving suggestive genome-wide significance (P<1х10 -6 ) were tested for replication among UK Biobank (N=383,145) and Million Veterans Program (N=318,891) participants with GWAS data imputed to the TOPMed and 1000 Genomes reference panels, respectively. Results: Discovery stage analyses identified 63 novel loci suggestively associated with BP. As expected, most of these variants (81%) had minor allele frequencies (MAFs)<1%. Although none achieved genome-wide significance (P<5х10 -8 ) in joint analyses of discovery and replication stages, two rare variants had consistent effect directions and achieved nominal significance in replication analyses, including one for DBP at CHL1 (rs932205533; MAF=1.2х10 -4 ; joint β=18.0; joint P=7.4х10 -8 ) and one for SBP at MACROD2 (rs752530366; MAF=8.6х10 -4 ; joint β=-5.1; joint P=3.8х10 -6 ). A total of 44 novel variants from previously reported loci (r 2 <0.1 with previously reported variants) were also identified in the discovery stage analyses, including 31 rare variants with large effect sizes (70%). Nine common variants from these loci achieved genome-wide significance in joint analyses. Variants for SBP included ones at NPPB (rs12406089; MAF=0.34; joint β=-0.58; joint P=2.7х10 -79 ), AC137675.1 (rs2643826; MAF=0.56; joint β=0.56; joint P=1.5х10 -45 ), NEIL2 (rs804264; MAF=0.35; joint β=0.28; joint P=4.7х10 -20 ), CACNB2 (rs11014204; MAF=0.21; joint β=-0.53; joint P=6.8х10 -57 ), OVOL1 (rs557675; MAF=0.43; joint β=-0.25; joint P=1.9х10 -17 ), RP11-654D12.2 (rs8014582; MAF=0.05; joint β=-0.52; joint P=6.7х10 -13 ), and ATXN2 (rs35350651; MAF=0.67; joint β=-0.39; joint P=3.4х10 -38 ). Novel variants for DBP at INSR (rs36150639; MAF=0.45; joint β=-0.29; joint P=2.5х10 -27 ) and HTN at TBX3 (rs2891546; MAF=0.17; joint OR=0.95; joint P=3.1х10 -14 ) were also identified. Conclusion: WGS studies in large multi-ancestry samples can identify novel signals at previously reported GWAS loci, helping to localize causal genes and variants for BP.

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How to Make Your Work Really Influence Future Healthcare

Advances in Healthcare Information Systems and Administration - Design, Development, and Integration of Reliable Electronic Healthcare Platforms ◽

10.4018/978-1-5225-1724-5.ch016 ◽

2017 ◽

pp. 271-296 ◽

Cited By ~ 1

Author(s):

Aleš Bourek

Keyword(s):

Health Care ◽

Policy Implementation ◽

Health Systems ◽

Healthcare Systems ◽

Ordinary People ◽

Future Health ◽

Policy Makers ◽

Healthcare Environments ◽

Personalized Health ◽

Personalized Health Care

Future health systems, besides traditional areas defined and addressed since 1980, face the advent of Proactive, Predictive, Prospective, Preventive, Participative and Personalized health care (HC). Reliable e-health platforms can help us with these challenges. They should be designed and implemented in a way to help ordinary people achieve extraordinary results. Even the best projects addressing HC systems improvement are not automatically qualified for implementation unless adopted by policy makers. The introduction of strategies with a potential for healthcare systems improvement to policy makers is necessary but difficult because of the complexity of the addressed issue. Illustrated on four projects, selected from the 25 the author participated in, from 1993 to 2016, principles, processes and attitudes found beneficial for successful policy implementation in various healthcare environments, are presented, to help with the integration of reliable electronic healthcare platforms into coming healthcare systems.

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Involvement of the 14-3-3 Gene Family in Autism Spectrum Disorder and Schizophrenia: Genetics, Transcriptomics and Functional Analyses

Journal of Clinical Medicine ◽

10.3390/jcm9061851 ◽

2020 ◽

Vol 9 (6) ◽

pp. 1851

Author(s):

Bàrbara Torrico ◽

Ester Antón-Galindo ◽

Noèlia Fernàndez-Castillo ◽

Eva Rojo-Francàs ◽

Sadaf Ghorbani ◽

...

Keyword(s):

Autism Spectrum Disorder ◽

Psychiatric Disorders ◽

Rare Variants ◽

Neurological Diseases ◽

Autism Spectrum ◽

Spectrum Disorder ◽

Risk Variants ◽

Whole Exome ◽

Target Binding ◽

Functional Analyses

The 14-3-3 protein family are molecular chaperones involved in several biological functions and neurological diseases. We previously pinpointed YWHAZ (encoding 14-3-3ζ) as a candidate gene for autism spectrum disorder (ASD) through a whole-exome sequencing study, which identified a frameshift variant within the gene (c.659-660insT, p.L220Ffs*18). Here, we explored the contribution of the seven human 14-3-3 family members in ASD and other psychiatric disorders by investigating the: (i) functional impact of the 14-3-3ζ mutation p.L220Ffs*18 by assessing solubility, target binding and dimerization; (ii) contribution of common risk variants in 14-3-3 genes to ASD and additional psychiatric disorders; (iii) burden of rare variants in ASD and schizophrenia; and iv) 14-3-3 gene expression using ASD and schizophrenia transcriptomic data. We found that the mutant 14-3-3ζ protein had decreased solubility and lost its ability to form heterodimers and bind to its target tyrosine hydroxylase. Gene-based analyses using publicly available datasets revealed that common variants in YWHAE contribute to schizophrenia (p = 6.6 × 10−7), whereas ultra-rare variants were found enriched in ASD across the 14-3-3 genes (p = 0.017) and in schizophrenia for YWHAZ (meta-p = 0.017). Furthermore, expression of 14-3-3 genes was altered in post-mortem brains of ASD and schizophrenia patients. Our study supports a role for the 14-3-3 family in ASD and schizophrenia.

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