GWAS and transcriptional analysis prioritize ITPR1 and CNTN4 for a serum uric acid 3p26 QTL in Mexican Americans

Chittoor, Geetha; Kent, Jack W.; Almeida, Marcio; Puppala, Sobha; Farook, Vidya S.; Cole, Shelley A.; Haack, Karin; Göring, Harald H.H.; MacCluer, Jean W.; Curran, Joanne E.; Carless, Melanie A.; Johnson, Matthew P.; Moses, Eric K.; Almasy, Laura; Mahaney, Michael C.; Lehman, Donna M.; Duggirala, Ravindranath; Comuzzie, Anthony G.; Blangero, John; Voruganti, V. Saroja

doi:10.1186/s12864-016-2594-5

Cited by 13 publications

(9 citation statements)

References 58 publications

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“…The final result would be a significant decrease in uric acid circulating level. In contrast to these results, On the other hand, several studies agree with our results favoring the view that reduced uric acid in MS is secondary to its peroxynitrite scavenging activity during inflammatory disease activity, rather than a primary deficiency [16,37,38]. Also, in this study it was found that urinary uric acid level was lower in SPMS than RRMS and inversely correlated with disability score (EDSS and number of relapses) which agree with Markowitz et al [39] who found that inosine treatment (precursor of uric acid) increased serum uric acid levels and was associated with a significant decrease in the number of gadolinium enhanced lesions and improved EDSS.…”

Section: Discussionsupporting

confidence: 77%

Urinary Urea, Uric Acid and Hippuric Acid as Potential Biomarkers in Multiple Sclerosis Patients

et al. 2017

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Urine is a proven source of metabolite biomarkers and has the potential to be a rapid, noninvasive, inexpensive, and efficient diagnostic tool for various human diseases. Despite these advantages, urine is an under-investigated source of biomarkers for multiple sclerosis (MS). The objective was to investigate the level of some urinary metabolites (urea, uric acid and hippuric acid) in patients with MS and correlate their levels to the severity of the disease, MS subtypes and MS treatment. The urine samples were collected from 73 MS patients-48 with RRMS and 25 with SPMS- and age matched 75 healthy controls. The values of urinary urea, uric acid and hippuric acid in MS patients were significantly decreased, and these metabolites in SPMS pattern showed significantly decrease than RRMS pattern. Also showed significant inverse correlation with expanded disability status scale and number of relapses. Accordingly, they may act as a potential urinary biomarkers for MS, and correlate to disease progression.

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Section: Discussionsupporting

confidence: 77%

Urinary Urea, Uric Acid and Hippuric Acid as Potential Biomarkers in Multiple Sclerosis Patients

et al. 2017

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“…40 Furthermore, genetic variants in CNTN4 are associated with elevated serum uric acid, thromboxane A2 formation and with an excess of cardiovascular events. 41,42 Our results showed that rs60314379, located in GRK4, was asso- has been associated with genetic and acquired hypertension. [43][44][45] Differential functional expression of GRK family proteins in human myocardial tissues has shown that, although GRK2, GRK3, and GRK5 expression is abundant, GRK4, GRK6 and GRK7 transcripts are only scarcely detectable in the healthy human heart.…”

Section: Cumulative Effects Of the 35 Genetic Variants On Cardiovasmentioning

confidence: 59%

“…Mutations in CNTN4 in humans are associated with 3p deletion syndrome and autism spectrum disorders 40 . Furthermore, genetic variants in CNTN4 are associated with elevated serum uric acid, thromboxane A2 formation and with an excess of cardiovascular events 41,42 …”

Section: Discussionmentioning

confidence: 99%

Genetic risk score constructed from common genetic variants is associated with cardiovascular disease risk in type 2 diabetes mellitus

Cheng

Lin

Liang

et al. 2021

The Journal of Gene Medicine

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Background: Patients with type 2 diabetes mellitus (T2DM) experience a twofold increased risk of cardiovascular diseases. Genome-wide association studies (GWAS) have identified T2DM susceptibility genetic variants. Interestingly, the genetic variants associated with cardiovascular disease risk in T2DM Han Chinese remain to be elucidated. The present study aimed to investigate the genetic variants associated with cardiovascular disease risk in T2DM. Methods: We performed bootstrapping, GWAS and an investigation of genetic variants associated with cardiovascular disease risk in a discovery T2DM cohort and in a replication cohort. The discovery cohort included 326 cardiovascular disease patients and 1209 noncardiovascular disease patients. The replication cohort included 68 cardiovascular disease patients and 317 noncardiovascular disease patients. The main outcome measures were genetic variants for genetic risk score (GRS) in cardiovascular disease risk in T2DM. Results: In total, 35 genetic variants were associated with cardiovascular disease risk. A GRS was generated by combining risk alleles from these variants weighted by their estimated effect sizes (log odds ratio [OR]). T2DM patients with weighted GRS ≥ 12.63 had an approximately 15-fold increase in cardiovascular disease risk (odds ratio = 15.67, 95% confidence interval [CI] = 10.33-24.00) compared to patients with weighted GRS < 10.39. With the addition of weighted GRS, receiver-operating characteristic curves showed that area under the curve with conventional risk factors was improved from 0.719 (95% CI = 0.689-0.750) to 0.888 (95% CI = 0.866-0.910). Conclusions: These 35 genetic variants are associated with cardiovascular disease risk in T2DM, alone and cumulatively. T2DM patients with higher levels of weighted genetic risk score have higher cardiovascular disease risks.

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“…Solute carrier family 22 member 1 exhibited the strongest interaction with ABCG2, which is expressed in the kidney and mediates the transport of xenobiotics, endogenous organic anions and urate (43). PRKG2 exhibited the strongest interaction with inositol 1,4,5-trisphosphate receptor type 1, which was previously reported to be associated with high serum uric acid concentrations (44). In the next step, all 79 candidate genes in the PPI network were used in the BP with ClueGO plugin.…”

Section: Functional Analysis Of the Co-expression And Ppi Networkmentioning

confidence: 99%

Unraveling the genetic causes in large pedigrees with gout by whole‑exome sequencing

et al. 2020

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Gout is a common type of inflammatory arthritis that is clinically and genetically heterogeneous. The genetic aetiology remains unclear, and mainly relies on previous genome-wide association studies focused on sporadic cases. The present study aimed to identify the genetic basis of gout in three families using whole-exome sequencing (WES). WES was performed in the probands, and family members were involved in the co-segregation analysis. In total, three deleterious rare or novel missense mutations were identified in ATP-binding cassette super-family G member 2 (ABCG2), protein kinase CGMP-dependent 2 (PRKG2) and adrenoceptor β3 (ADRB3) genes in three different families. In addition, certain gout-associated candidate genes were revealed to be shared among the co-expression and protein-protein interaction (PPI) networks of ABCG2, PRKG2 and ADRB3. Furthermore, the disease ontology analysis of the genes present in the co-expression network exhibited significant (P<0.05) enrichment in hyperuricemia, gout, cardiovascular system disease and metabolic disease. In addition, genes involved in the PPI network were significantly enriched in the purine nucleoside monophosphate biosynthetic process, urate transport and biological processes associated with glycose metabolism. Collectively, to the best of our knowledge, the present study was the first to use WES to identify three candidate rare or novel deleterious mutations in three families with gout. The present results provided novel insights that may improve the current understanding of the molecular genetic basis underlying gout. Importantly, the present results may facilitate the improvement of clinical diagnosis and the development of novel personalized therapies.

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GWAS and transcriptional analysis prioritize ITPR1 and CNTN4 for a serum uric acid 3p26 QTL in Mexican Americans

Cited by 13 publications

References 58 publications

Urinary Urea, Uric Acid and Hippuric Acid as Potential Biomarkers in Multiple Sclerosis Patients

Urinary Urea, Uric Acid and Hippuric Acid as Potential Biomarkers in Multiple Sclerosis Patients

Genetic risk score constructed from common genetic variants is associated with cardiovascular disease risk in type 2 diabetes mellitus

Unraveling the genetic causes in large pedigrees with gout by whole‑exome sequencing

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