scholarly journals Blood Pressure Genome-Wide Association Studies, Missing Heritability, and Omnigenics

Author(s):  
Brian J. Morris
2019 ◽  
Vol 19 (10) ◽  
pp. 731-738
Author(s):  
Xingchen Wang ◽  
Xingbo Mo ◽  
Huan Zhang ◽  
Yonghong Zhang ◽  
Yueping Shen

Purpose: Phosphorylation-related SNP (phosSNP) is a non-synonymous SNP that might influence protein phosphorylation status. The aim of this study was to assess the effect of phosSNPs on blood pressure (BP), coronary artery disease (CAD) and ischemic stroke (IS). Methods: We examined the association of phosSNPs with BP, CAD and IS in shared data from genome-wide association studies (GWAS) and tested if the disease loci were enriched with phosSNPs. Furthermore, we performed quantitative trait locus analysis to find out if the identified phosSNPs have impacts on gene expression, protein and metabolite levels. Results: We found numerous phosSNPs for systolic BP (count=148), diastolic BP (count=206), CAD (count=20) and IS (count=4). The most significant phosSNPs for SBP, DBP, CAD and IS were rs1801131 in MTHFR, rs3184504 in SH2B3, rs35212307 in WDR12 and rs3184504 in SH2B3, respectively. Our analyses revealed that the associated SNPs identified by the original GWAS were significantly enriched with phosSNPs and many well-known genes predisposing to cardiovascular diseases contain significant phosSNPs. We found that BP, CAD and IS shared for phosSNPs in loci that contain functional genes involve in cardiovascular diseases, e.g., rs11556924 (ZC3HC1), rs1971819 (ICA1L), rs3184504 (SH2B3), rs3739998 (JCAD), rs903160 (SMG6). Four phosSNPs in ADAMTS7 were significantly associated with CAD, including the known functional SNP rs3825807. Moreover, the identified phosSNPs seemed to have the potential to affect transcription regulation and serum levels of numerous cardiovascular diseases-related proteins and metabolites. Conclusion: The findings suggested that phosSNPs may play important roles in BP regulation and the pathological mechanisms of CAD and IS.


Circulation ◽  
2020 ◽  
Vol 141 (Suppl_1) ◽  
Author(s):  
Myriam Fornage ◽  
Daokun Sun ◽  
Melissa A Richard ◽  
Solomon K Musani ◽  
Yun Ju Sung ◽  
...  

Background: Genome-wide association studies (GWAS) have identified hundreds of genetic loci for blood pressure (BP) traits and advanced our understanding of BP regulation and hypertension etiology. Psychological and social factors are known to influence BP and risk of cardiovascular diseases. Accounting for psychosocial factors may help identify BP loci and extend our knowledge of its genetic architecture. Methods: To identify novel BP loci, we carried out genome-wide association meta-analyses of systolic, diastolic, pulse, and mean arterial BP taking into account the interaction effects of genetic variants with three psychosocial factors: depressive symptomatology, trait anxiety, and social support. Analyses were performed using a two-stage design in a sample of up to 128,894 adults from 5 ancestry groups. Results: In the combined meta-analyses of Stages 1 and 2, we identified 59 loci (p <5e-8), including nine novel BP loci. The novel associations were observed mostly with pulse pressure, with fewer observed with mean arterial pressure. Five novel loci were identified in African ancestry, and all but one showed patterns of interaction with at least one psychosocial factor. Functional annotation of the novel loci supports a major role for genes implicated in the immune response ( PLCL2 ), synaptic function and neurotransmission ( LIN7A, PFIA2 ), as well as genes previously implicated in neuropsychiatric or stress-related disorders ( FSTL5, CHODL ). Conclusion: These findings underscore the importance of considering psychological and social factors in gene discovery for BP, especially in non-European populations.


Author(s):  
Venexia M Walker ◽  
Sean Harrison ◽  
Alice R Carter ◽  
Dipender Gill ◽  
Ioanna Tzoulaki ◽  
...  

Introduction: Genome-wide association studies (GWASs) often adjust for covariates, correct for medication use, or select on medication users. If these summary statistics are used in two-sample Mendelian randomization analyses, estimates may be biased. We used simulations to investigate how GWAS adjustment, correction and selection affects these estimates and performed an analysis in UK Biobank to provide an empirical example. Methods: We simulated six GWASs: no adjustment for a covariate, correction for medication use, or selection on medication users; adjustment only; selection only; correction only; both adjustment and selection; and both adjustment and correction. We then ran two-sample Mendelian randomization analyses using these GWASs to evaluate bias. We also performed equivalent GWASs using empirical data from 318,147 participants in UK Biobank with systolic blood pressure as the exposure and body mass index as the covariate and ran two-sample Mendelian randomization with coronary heart disease as the outcome. Results: The simulation showed that estimates from GWASs with selection can produce biased two-sample Mendelian randomization estimates. Yet, we observed relatively little difference between empirical estimates of the effect of systolic blood pressure on coronary artery disease across the six scenarios. Conclusions: Given the potential for bias from using GWASs with selection on Mendelian randomization estimates demonstrated in our simulation, and the reduced sample size of these GWAS, this approach should be deprioritized. However, based on our empirical results, using adjusted, corrected or selected GWASs is unlikely to make a large difference to two-sample Mendelian randomization estimates in practice.


PLoS ONE ◽  
2021 ◽  
Vol 16 (2) ◽  
pp. e0246436
Author(s):  
Zhaoying Li ◽  
Weijing Wang ◽  
Xiaocao Tian ◽  
Haiping Duan ◽  
Chunsheng Xu ◽  
...  

Recently, new loci related to body mass index (BMI) or blood pressure (BP) have been identified respectively in genome-wide association studies (GWAS). However, limited studies focused on jointly associated genetic variance between systolic pressure (SBP), diastolic pressure (DBP) and BMI. Therefore, a bivariate twin study was performed to explore the genetic variants associated with BMI-SBP, BMI-DBP and SBP-DBP. A total of 380 twin pairs (137 dizygotic pairs and 243 monozygotic pairs) recruited from Qingdao Twin Registry system were used to access the genetic correlations (0.2108 for BMI-SBP, 0.2345 for BMI-DBP, and 0.6942 for SBP-DBP, respectively) by bivariate Cholesky decomposition model. Bivariate GWAS in 137 dizygotic pairs nominated 27 single identified 27 quantitative trait nucleotides (QTNs) for BMI and SBP, 27 QTNs for BMI and DBP, and 25 QTNs for SBP and DBP with the suggestive P-value threshold of 1×10−5. After imputation, we found eight SNPs, one for both BMI-SBP and SBP-DBP, and eight for SBP-DBP, exceed significant statistic level. Expression quantitative trait loci analysis identified rs4794029 as new significant eQTL in tissues related to BMI and SBP. Also, we found 6 new significant eQTLs (rs4400367, rs10113750, rs11776003, rs3739327, rs55978930, and rs4794029) in tissues were related to SBP and DBP. Gene-based analysis identified nominally associated genes (P < 0.05) with BMI-SBP, BMI-DBP, and SBP-DBP, respectively, such as PHOSPHO1, GNGT2, KEAP1, and S1PR5. In the pathway analysis, we found some pathways associated with BMI-SBP, BMI-DBP and SBP-DBP, such as prion diseases, IL5 pathway, cyclin E associated events during G1/S transition, TGF beta signaling pathway, G βγ signaling through PI3Kγ, prolactin receptor signaling etc. These findings may enrich the results of genetic variants related to BMI and BP traits, and provide some evidences to future study the pathogenesis of hypertension and obesity in the northern Chinese population.


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