Causal inference at the population level

Three elements are needed to formalize a causal quantity at the population level: response, treatment, and the causal element, which are introduced here by notation. Inclusion of two essential causal assumptions, the monitoring and illumination assumptions, in a function distinguishes causal from association analyses. The discussion provides insight into causal inference

Unraveling the functional role of the orphan solute carrier, SLC22A24 in the transport of steroid conjugates through metabolomic and genome-wide association studies.

Variation in steroid hormone levels has wide implications for health and disease. The genes encoding the proteins involved in steroid disposition represent key determinants of interindividual variation in steroid levels and ultimately, their effects. Beginning with metabolomic data from genome-wide association studies (GWAS), we observed that genetic variants in the orphan transporter, SLC22A24 were significantly associated with levels of androsterone glucuronide and etiocholanolone glucuronide (sentinel SNPs p-value <1x10-30). In cells over-expressing human or various mammalian orthologs of SLC22A24, we showed that steroid conjugates and bile acids were substrates of the transporter. Phylogenetic, genomic, and transcriptomic analyses suggested that SLC22A24 has a specialized role in the kidney and appears to function in the reabsorption of organic anions, and in particular, anionic steroids. Phenome-wide analysis showed that functional variants of SLC22A24 are associated with human disease such as cardiovascular diseases and acne, which have been linked to dysregulated steroid metabolism. Collectively, these functional genomic studies reveal a previously uncharacterized protein involved in steroid homeostasis, opening up new possibilities for SLC22A24 as a pharmacological target for regulating steroid levels

Risk factor correlates of platelet and leukocyte markers assessed by flow cytometry in a population-based sample

Background—Platelet and leukocyte products are involved in atherothrombosis. However, the determinants of of platelet and leukocyte markers assessed by flow cytometry have not been documented in a population-based sample. Methods and results—We performed flow cytometry on blood from participants (n=1,894) in the Atherosclerosis Risk in Communities (ARIC) Carotid MRI Study. Cellular aggregates and multiple platelet and leukocyte markers, such as myeloperoxidase in granulocytes and toll-like receptor-4, CD14, and CD45 in monocytes, were quantified. Their cross-sectional associations with demographic and risk factors were assessed using multiple linear regression. Mean values of most cellular markers and aggregates were considerably higher in blacks than whites (p<0.01). There were some differences in cellular markers between men and women, but little association with age. LDL-cholesterol was associated positively with several markers (toll-like receptor-4 and myeloperoxidase in granulocytes and CD162 in lymphocytes). Lipid lowering therapy tended to show opposite associations. Smokers had much higher granulocyte myeloperoxidase than nonsmokers. However, most other correlations between risk factors and cellular markers were nonsignificant. Conclusions—Race/ethnicity, sex, and to a lesser degree LDL-cholesterol and lipid-lowering therapy, but few other risk factors, were correlated with markers of cellular activation in this population-based study

Associations of NINJ2 sequence variants with incident ischemic stroke in the Cohorts for Heart and Aging in Genomic Epidemiology (CHARGE) consortium

Background&lt;p&gt;&lt;/p&gt; Stroke, the leading neurologic cause of death and disability, has a substantial genetic component. We previously conducted a genome-wide association study (GWAS) in four prospective studies from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and demonstrated that sequence variants near the NINJ2 gene are associated with incident ischemic stroke. Here, we sought to fine-map functional variants in the region and evaluate the contribution of rare variants to ischemic stroke risk.&lt;p&gt;&lt;/p&gt; Methods and Results&lt;p&gt;&lt;/p&gt; We sequenced 196 kb around NINJ2 on chromosome 12p13 among 3,986 European ancestry participants, including 475 ischemic stroke cases, from the Atherosclerosis Risk in Communities Study, Cardiovascular Health Study, and Framingham Heart Study. Meta-analyses of single-variant tests for 425 common variants (minor allele frequency [MAF] ≥ 1%) confirmed the original GWAS results and identified an independent intronic variant, rs34166160 (MAF = 0.012), most significantly associated with incident ischemic stroke (HR = 1.80, p = 0.0003). Aggregating 278 putatively-functional variants with MAF≤ 1% using count statistics, we observed a nominally statistically significant association, with the burden of rare NINJ2 variants contributing to decreased ischemic stroke incidence (HR = 0.81; p = 0.026).&lt;p&gt;&lt;/p&gt; Conclusion&lt;p&gt;&lt;/p&gt; Common and rare variants in the NINJ2 region were nominally associated with incident ischemic stroke among a subset of CHARGE participants. Allelic heterogeneity at this locus, caused by multiple rare, low frequency, and common variants with disparate effects on risk, may explain the difficulties in replicating the original GWAS results. Additional studies that take into account the complex allelic architecture at this locus are needed to confirm these findings

Drug-gene interactions of antihypertensive medications and risk of incident cardiovascular disease: a pharmacogenomics study from the CHARGE consortium

Background Hypertension is a major risk factor for a spectrum of cardiovascular diseases (CVD), including myocardial infarction, sudden death, and stroke. In the US, over 65 million people have high blood pressure and a large proportion of these individuals are prescribed antihypertensive medications. Although large long-term clinical trials conducted in the last several decades have identified a number of effective antihypertensive treatments that reduce the risk of future clinical complications, responses to therapy and protection from cardiovascular events vary among individuals. Methods Using a genome-wide association study among 21,267 participants with pharmaceutically treated hypertension, we explored the hypothesis that genetic variants might influence or modify the effectiveness of common antihypertensive therapies on the risk of major cardiovascular outcomes. The classes of drug treatments included angiotensin-converting enzyme inhibitors, beta-blockers, calcium channel blockers, and diuretics. In the setting of the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, each study performed array-based genome-wide genotyping, imputed to HapMap Phase II reference panels, and used additive genetic models in proportional hazards or logistic regression models to evaluate drug-gene interactions for each of four therapeutic drug classes. We used meta-analysis to combine study-specific interaction estimates for approximately 2 million single nucleotide polymorphisms (SNPs) in a discovery analysis among 15,375 European Ancestry participants (3,527 CVD cases) with targeted follow-up in a case-only study of 1,751 European Ancestry GenHAT participants as well as among 4,141 African-Americans (1,267 CVD cases). Results Although drug-SNP interactions were biologically plausible, exposures and outcomes were well measured, and power was sufficient to detect modest interactions, we did not identify any statistically significant interactions from the four antihypertensive therapy meta-analyses (Pinteraction &gt; 5.0×10−8). Similarly, findings were null for meta-analyses restricted to 66 SNPs with significant main effects on coronary artery disease or blood pressure from large published genome-wide association studies (Pinteraction ≥ 0.01). Our results suggest that there are no major pharmacogenetic influences of common SNPs on the relationship between blood pressure medications and the risk of incident CVD

Five Blood Pressure Loci Identified by an Updated Genome-Wide Linkage Scan: Meta-Analysis of the Family Blood Pressure Program

Background A preliminary genome-wide linkage analysis of blood pressure in the Family Blood Pressure Program (FBPP) was reported previously. We harnessed the power and ethnic diversity of the final pooled FBPP dataset to identify novel loci for blood pressure thereby enhancing localization of genes containing less common variants with large effects on blood pressure levels and hypertension. Methods We performed one overall and 4 race-specific meta-analyses of genome-wide blood pressure linkage scans using data on 4,226African-American, 2,154 Asian, 4,229 Caucasian, and 2,435 Mexican- American participants (total N = 13,044). Variance components models were fit to measured (raw) blood pressure levels and two types of antihypertensive medication adjusted blood pressure phenotypes within each of 10 subgroups defined by race and network. A modified Fisher's method was used to combine the P values for each linkage marker across the 10 subgroups. Results Five quantitative trait loci (QTLs) were detected on chromosomes 6p22.3, 8q23.1, 20q13.12, 21q21.1, and 21q21.3 based on significant linkage evidence (defined by logarithm of odds (lod) score ≥3) in at least one meta-analysis and lod scores ≥1 in at least 2 subgroups defined by network and race. The chromosome 8q23.1 locus was supported by Asian-, Caucasian-, and Mexican-American-specific meta-analyses. Conclusions The new QTLs reported justify new candidate gene studies. They may help support results from genome-wide association studies (GWAS) that fall in these QTL regions but fail to achieve the genome-wide significance. American Journal of Hypertension advance online publication 9 December 2010;doi:10.1038/ajh.2010.23

The Implementation Science For Genomic Health Translation (insight) Study in Epilepsy: Protocol For a Learning Health Care System

BACKGROUND: Genomic medicine is poised to improve care for common complex diseases such as epilepsy, but additional clinical informatics and implementation science research is needed for it to become a part of the standard of care. Epilepsy is an exemplary complex neurological disorder for which DNA diagnostics have shown to be advantageous for patient care. OBJECTIVE: We designed the Implementation Science for Genomic Health Translation (INSIGHT) study to leverage the fact that both the clinic and testing laboratory control the development and customization of their respective electronic health records and clinical reporting platforms. Through INSIGHT, we can rapidly prototype and benchmark novel approaches to incorporating clinical genomics into patient care. Of particular interest are clinical decision support tools that take advantage of domain knowledge from clinical genomics and can be rapidly adjusted based on feedback from clinicians. METHODS: Building on previously developed evidence and infrastructure components, our model includes the following: establishment of an intervention-ready genomic knowledge base for patient care, creation of a health informatics platform and linking it to a clinical genomics reporting system, and scaling and evaluation of INSIGHT following established implementation science principles. RESULTS: INSIGHT was approved by the Institutional Review Board at the University of Texas Health Science Center at Houston on May 15, 2020, and is designed as a 2-year proof-of-concept study beginning in December 2021. By design, 120 patients from the Texas Comprehensive Epilepsy Program are to be enrolled to test the INSIGHT workflow. Initial results are expected in the first half of 2023. CONCLUSIONS: INSIGHT\u27s domain-specific, practical but generalizable approach may help catalyze a pathway to accelerate translation of genomic knowledge into impactful interventions in patient care. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/25576

Orthostatic hypotension and novel blood pressure-associated gene variants: Genetics of Postural Hemodynamics (GPH) Consortium

Aims: Orthostatic hypotension (OH), an independent predictor of mortality and cardiovascular events, strongly correlates with hypertension. Recent genome-wide studies have identified new loci influencing blood pressure (BP) in populations, but their impact on OH remains unknown. Methods and Results: A total of 38 970 men and women of European ancestry from five population-based cohorts were included, of whom 2656 (6.8%) met the diagnostic criteria for OH (systolic/diastolic BP drop ≥20/10 mmHg within 3 min of standing). Thirty-one recently discovered BP-associated single nucleotide polymorphisms (SNPs) were examined using an additive genetic model and the major allele as referent. Relations between OH, orthostatic systolic BP response, and genetic variants were assessed by inverse variance-weighted meta-analysis. We found Bonferroni adjusted (P < 0.0016) significant evidence for association between OH and the EBF1 locus (rs11953630, per-minor-allele odds ratio, 95% confidence interval: 0.90, 0.85–0.96; P = 0.001), and nominal evidence (P < 0.05) for CYP17A1 (rs11191548: 0.85, 0.75–0.95; P = 0.005), and NPR3-C5orf23 (rs1173771: 0.92, 0.87–0.98; P= 0.009) loci. Among subjects not taking BP-lowering drugs, three SNPs within the NPPA/NPPB locus were nominally associated with increased risk of OH (rs17367504: 1.13, 1.02–1.24; P = 0.02, rs198358: 1.10, 1.01–1.20; P = 0.04, and rs5068: 1.22, 1.04–1.43; P = 0.01). Moreover, an ADM variant was nominally associated with continuous orthostatic systolic BP response in the adjusted model (P= 0.04). Conclusion: The overall association between common gene variants in BP loci and OH was generally weak and the direction of effect inconsistent with resting BP findings. These results suggest that OH and resting BP share few genetic components