Genetic Risk Scores

Assessment of multi-population polygenic risk scores for lipid traits in African Americans

Polygenic risk scores (PRS) based on genome-wide discoveries are promising predictors or classifiers of disease development, severity, and/or progression for common clinical outcomes. A major limitation of most risk scores is the paucity of genome-wide discoveries in diverse populations, prompting an emphasis to generate these needed data for trans-population and population-specific PRS construction. Given diverse genome-wide discoveries are just now being completed, there has been little opportunity for PRS to be evaluated in diverse populations independent from the discovery efforts. To fill this gap, we leverage here summary data from a recent genome-wide discovery study of lipid traits (HDL-C, LDL-C, triglycerides, and total cholesterol) conducted in diverse populations represented by African Americans, Hispanics, Asians, Native Hawaiians, Native Americans, and others by the Population Architecture using Genomics and Epidemiology (PAGE) Study. We constructed lipid trait PRS using PAGE Study published genetic variants and weights in an independent African American adult patient population linked to de-identified electronic health records and genotypes from the Illumina Metabochip (n = 3,254). Using multi-population lipid trait PRS, we assessed levels of association for their respective lipid traits, clinical outcomes (cardiovascular disease and type 2 diabetes), and common clinical labs. While none of the multi-population PRS were strongly associated with the tested trait or outcome, PRS_LDL-Cwas nominally associated with cardiovascular disease. These data demonstrate the complexity in applying PRS to real-world clinical data even when data from multiple populations are available.

Sex Differences in Clopidogrel Effects Among Young Patients With Acute Coronary Syndrome: A Role for Genetics?

Background

Poorer health outcomes experienced by young women with acute coronary syndrome may be related to sex differences in the safety and efficacy of antiplatelet agents, such as clopidogrel. Polymorphisms in drug metabolism enzyme (cytochrome P450 [CYP] family) genes are independent factors for the variability in response to clopidogrel. However, a sex-specific impact of genetics to explain worse clinical outcomes in women has not been explored extensively. Therefore, our objective was to determine whether an interaction of sex with CYP variants occurs among users of clopidogrel, and if so, its impact on 1-year adverse clinical outcomes.

Methods

We used data from a combined cohort of 2272 patients (median age 49 years; 56% female) hospitalized for acute coronary syndrome. We examined interactions between sex and CYP variants among clopidogrel users at admission and discharge to assess associations with 1-year readmission due to cardiac events.

Results

The case-only analysis of 177 participants on clopidogrel at the time of presentation showed that the risk of an atherothrombotic event was greater in female carriers of the CYP2C9∗3 loss-of-function allele (odds ratio = 3.77, 95% confidence interval = 1.54-9.24). The results of the multivariable logistic regression model for users of clopidogrel at discharge (n = 1733) indicated that women had significantly higher risk of atherothrombotic readmissions at 1 year (odds ratio = 1.55, 95% confidence interval = 1.16-2.07), compared to the risk for men, but the loss-of-function alleles, either individually or through a genetic risk score, were not associated with 1-year readmissions.

Conclusion

This study highlights the need for an improved understanding of the role of sex-by-gene interactions in causing sex differences in drug metabolism.

Circulating Nucleic Acid-Based Biomarkers of Type 2 Diabetes

Type 2 diabetes (T2D) is a deficiency in how the body regulates glucose. Uncontrolled T2D will result in chronic high blood sugar levels, eventually resulting in T2D complications. These complications, such as kidney, eye, and nerve damage, are even harder to treat. Identifying individuals at high risk of developing T2D and its complications is essential for early prevention and treatment. Numerous studies have been done to identify biomarkers for T2D diagnosis and prognosis. This review focuses on recent T2D biomarker studies based on circulating nucleic acids using different omics technologies: genomics, transcriptomics, and epigenomics. Omics studies have profiled biomarker candidates from blood, urine, and other non-invasive samples. Despite methodological differences, several candidate biomarkers were reported for the risk and diagnosis of T2D, the prognosis of T2D complications, and pharmacodynamics of T2D treatments. Future studies should be done to validate the findings in larger samples and blood-based biomarkers in non-invasive samples to support the realization of precision medicine for T2D.

Novel Biomarkers in the Diagnosis of Benign and Malignant Gastrointestinal Diseases

BACKGROUND

Various noninvasive biomarkers have been used in the diagnosis, prognosis, and treatment of different gastrointestinal (GI) diseases for years. Novel technological developments and profound perception of molecular processes related to GI diseases over the last decade have allowed researchers to evaluate genetic, epigenetic, and many other potential molecular biomarkers in different diseases and clinical settings. Here, we present a review of recent and most relevant articles in order to summarize major findings on novel biomarkers in the diagnosis of benign and malignant GI diseases.

SUMMARY

Genetic variations, noncoding RNAs (ncRNAs), cell-free DNA (cfDNA), and microbiome-based biomarkers have been extensively analyzed as potential biomarkers in benign and malignant GI diseases. Multiple single-nucleotide polymorphisms have been linked with a number of GI diseases, and these observations are further being used to build up disease-specific genetic risk scores. Micro-RNAs and long ncRNAs have a large potential as noninvasive biomarkers in the management of inflammatory bowel diseases and GI tumors. Altered microbiome profiles were observed in multiple GI diseases, but most of the findings still lack translational clinical application. As of today, cfDNA appears to be the most potent biomarker for early detection and screening of GI cancers. Key Messages: Novel noninvasive molecular biomarkers show huge potential as useful tools in the diagnostics and management of different GI diseases. However, the use of these biomarkers in real-life clinical practice still remains limited, and further large studies are needed to elucidate the ultimate role of these potential noninvasive clinical tools.

The Relationship of Dietary Pattern and Genetic Risk Score with the Incidence Dyslipidemia: 14-Year Follow-Up Cohort Study

This study was conducted to investigate the relationship between dietary pattern and genetic risk score (GRS) for dyslipidemia risk among Korean adults. Hypercholesterolemia and hypertriglyceridemia defined as total cholesterol ≥240 mg/dL and triglyceride ≥200 mg/dL or use dyslipidemia medication. The GRS was calculated by summing the risk alleles of the selected seven single-nucleotide polymorphisms related to dyslipidemia. Dietary patterns were identified by principal component analysis based on the frequency of 36 food groups, “whole grain and soybean products” pattern, “meat, fish and vegetables” pattern, and “bread and noodle” pattern were identified. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using the multivariate Cox proportional hazards regression model. High intake of a “whole grain and soybean products” pattern decreased risks of hypercholesterolemia (HR: 0.82, 95% CI: 0.72–0.93, p for trend = 0.0006) and hypertriglyceridemia (HR: 0.85, 95% CI: 0.75–0.97, p for trend = 0.0344). In the highest tertile of GRS, the “whole grain and soybean products” pattern was inversely related to hypercholesterolemia risk. Therefore, for people with genotypes that can cause hypercholesterolemia, eating whole grains and soybean products may have a meaningful response, these results could be utilized for genome-based nutrition management.

Differences in clinical and genetic characteristics between early- and late-onset narcolepsy in a Han Chinese cohort

Early- and late-onset narcolepsy constitutes two distinct diagnostic subgroups. However, it is not clear whether symptomology and genetic risk factors differ between early- and late-onset narcoleptics. This study compared clinical data and single-nucleotide polymorphisms (SNPs) between early- and late-onset patients in a large cohort of 899 Han Chinese narcolepsy patients. Blood, cerebrospinal fluid, and clinical data were prospectively collected from patients, and patients were genotyped for 40 previously reported narcolepsy risk-conferring SNPs. Genetic risk scores (GRSs), associations of five different sets of SNPs (GRS1-GRS5) with early- and late-onset narcolepsy, were evaluated using logistic regression and receiver operating characteristic curves. Mean sleep latency was significantly shorter in early-onset cases than in late-onset cases. Symptom severity was greater among late-onset patients, with higher rates of sleep paralysis, hypnagogic hallucinations, health-related quality of life impairment, and concurrent presentation with four or more symptoms. Hypocretin levels did not differ significantly between early- and late-onset cases. Only rs3181077 (CCR1/CCR3) and rs9274477 (HLA-DQB1) were more prevalent among early-onset cases. Only GRS1 (26 SNPs; OR = 1.513, 95% CI: 0.893-2.585; P < 0.05) and GRS5 (6 SNPs; OR = 1.893, 95% CI: 1.204-2.993; P < 0.05) were associated with early-onset narcolepsy, with areas under the receiver operating characteristic curves of 0.731 and 0.732, respectively. Neither GRS1 nor GRS5 included SNPs in HLA regions. Our results indicate that symptomology and genetic risk factors differ between early- and late-onset narcolepsy. This protocol was approved by the Institutional Review Board (IRB) Panels on Medical Human Subjects at Peking University People's Hospital, China (approval No. Yuanlunshenlinyi 86) in October 2011.

Systematic Review of Polygenic Risk Scores for Type 1 and Type 2 Diabetes

Recent studies have led to considerable advances in the identification of genetic variants associated with type 1 and type 2 diabetes. An approach for converting genetic data into a predictive measure of disease susceptibility is to add the risk effects of loci into a polygenic risk score. In order to summarize the recent findings, we conducted a systematic review of studies comparing the accuracy of polygenic risk scores developed during the last two decades. We selected 15 risk scores from three databases (Scopus, Web of Science and PubMed) enrolled in this systematic review. We identified three polygenic risk scores that discriminate between type 1 diabetes patients and healthy people, one that discriminate between type 1 and type 2 diabetes, two that discriminate between type 1 and monogenic diabetes and nine polygenic risk scores that discriminate between type 2 diabetes patients and healthy people. Prediction accuracy of polygenic risk scores was assessed by comparing the area under the curve. The actual benefits, potential obstacles and possible solutions for the implementation of polygenic risk scores in clinical practice were also discussed. Develop strategies to establish the clinical validity of polygenic risk scores by creating a framework for the interpretation of findings and their translation into actual evidence, are the way to demonstrate their utility in medical practice.

Identifying mutation-driven changes in gene functionality that lead to venous thromboembolism

Venous thromboembolism (VTE) is a common hematological disorder. VTE affects millions of people around the world each year and can be fatal. Earlier studies have revealed the possible VTE genetic risk factors in Europeans. The 2018 Critical Assessment of Genome Interpretation (CAGI) challenge had asked participants to distinguish between 66 VTE and 37 non-VTE African American (AA) individuals based on their exome sequencing data. We used variants from AA VTE association studies and VTE genes from DisGeNET database to evaluate VTE risk via four different approaches; two of these methods were most successful at the task. Our best performing method represented each exome as a vector of predicted functional effect scores of variants within the known genes. These exome vectors were then clustered with k-means. This approach achieved 70.8% precision and 69.7% recall in identifying VTE patients. Our second-best ranked method had collapsed the variant effect scores into gene-level function changes, using the same vector clustering approach for patient/control identification. These results show predictability of VTE risk in AA population and highlight the importance of variant-driven gene functional changes in judging disease status. Of course, more in-depth understanding of AA VTE pathogenicity is still needed for more precise predictions.

Genetic Risk Score Predictive of the Plasma Triglyceride Response to an Omega-3 Fatty Acid Supplementation in a Mexican Population

Our group built a genetic risk score (GRS) of the plasma triglyceride (TG) response to an omega-3 (n-3) fatty acid (FA) supplementation in Caucasian Canadians that explained 21.53% of the TG variance. The objective was to refine the GRS by fine mapping and to test its association with the TG response in young Mexican adults. A total of 191 participants underwent a 6-week n-3 FA supplementation providing 2.7g/day of docosahexaenoic and eicosapentaenoic acids. Using quantitative polymerase chain reaction (PCR), 103 single-nucleotide polymorphisms (SNPs) were genotyped. A stepwise regression adjusted for age, sex, and body mass index (BMI) was used to select the strongest SNPs to include in the genetic risk model. A GRS was calculated from the sum of at-risk alleles. The contribution of the GRS to the TG response was assessed by ANCOVA with age, sex, and BMI included in the model. Several differences in allele frequency were observed between Canadians and Mexicans. Five lead SNPs were included in the genetic risk model, in which the GRS accounted for 11.01% of the variance of the TG response (p < 0.0001). These findings highlight the important contribution of genetic factors to the heterogeneity of the TG response to an n-3 FA supplementation among Mexicans.

Genetic Architecture of Primary Open-Angle Glaucoma in Individuals of African Descent: The African Descent and Glaucoma Evaluation Study III

PURPOSE

To find genetic contributions to glaucoma in African Americans.

DESIGN

Cross-sectional, case-control study.

PARTICIPANTS

One thousand eight hundred seventy-five primary open-angle glaucoma (POAG) patients and 1709 controls, self-identified as being of African descent (AD), from the African Descent and Glaucoma Evaluation Study (ADAGES) III and Wake Forest School of Medicine.

METHODS

MegaChip genotypes were imputed to Thousand Genomes data. Association of single nucleotide polymorphisms (SNPs) with POAG and advanced POAG was tested by linear mixed model correcting for relatedness and population stratification. Genetic risk scores were tested by receiver operator characteristic curves (ROC-AUCs).

MAIN OUTCOME MEASURES

Primary open-angle glaucoma defined by visual field loss without other nonocular conditions (n = 1875). Advanced POAG was defined by age-based mean deviation of visual field (n = 946).

RESULTS

Eighteen million two hundred eighty-one thousand nine hundred twenty SNPs met imputation quality of r2 > 0.7 and minor allele frequency > 0.005. Association of a novel locus, EN04, was observed for advanced POAG (rs185815146 β, 0.36; standard error, 0.065; P < 3×10-8). For POAG, an AD signal was observed at the 9p21 European descent (ED) POAG signal (rs79721419; P < 6.5×10-5) independent of the previously observed 9p21 ED signal (rs2383204; P < 2.3×10-5) by conditional analyses. An association with POAG in FNDC3B (rs111698934; P < 3.9×10-5) was observed, not in linkage disequilibrium (LD) with the previously reported ED SNP. Additional previously identified loci associated with POAG in persons of AD were: 8q22, AFAP1, and TMC01. An AUC of 0.62 was observed with an unweighted genetic risk score comprising 11 SNPs in candidate genes. Two additional risk scores were studied by using a penalized matrix decomposition with cross-validation; risk scores of 50 and 400 SNPs were identified with ROC of AUC = 0.74 and AUC = 0.94, respectively.

CONCLUSIONS

A novel association with advanced POAG in the EN04 locus was identified putatively in persons of AD. In addition to this finding, this genome-wide association study in POAG patients of AD contributes to POAG genetics by identification of novel signals in prior loci (9p21), as well as advancing the fine mapping of regions because of shorter average LD (FNDC3B). Although not useful without confirmation and clinical trials, the use of genetic risk scores demonstrated that considerable AD-specific genetic information remains in these data.

Evaluation of Polygenic Determinants of Non-Alcoholic Fatty Liver Disease (NAFLD) By a Candidate Genes Resequencing Strategy

NAFLD is a polygenic condition but the individual and cumulative contribution of identified genes remains to be established. To get additional insight into the genetic architecture of NAFLD, GWAS-identified GCKR, PPP1R3B, NCAN, LYPLAL1 and TM6SF2 genes were resequenced by next generation sequencing in a cohort of 218 NAFLD subjects and 227 controls, where PNPLA3 rs738409 and MBOAT7 rs641738 genotypes were also obtained. A total of 168 sequence variants were detected and 47 were annotated as functional. When all functional variants within each gene were considered, only those in TM6SF2 accumulate in NAFLD subjects compared to controls (P = 0.04). Among individual variants, rs1260326 in GCKR and rs641738 in MBOAT7 (recessive), rs58542926 in TM6SF2 and rs738409 in PNPLA3 (dominant) emerged as associated to NAFLD, with PNPLA3 rs738409 being the strongest predictor (OR 3.12, 95% CI, 1.8-5.5, P < 0.001). A 4-SNPs weighted genetic risk score value >0.28 was associated with a 3-fold increased risk of NAFLD. Interestingly, rs61756425 in PPP1R3B and rs641738 in MBOAT7 genes were predictors of NAFLD severity. Overall, TM6SF2, GCKR, PNPLA3 and MBOAT7 were confirmed to be associated with NAFLD and a score based on these genes was highly predictive of this condition. In addition, PPP1R3B and MBOAT7 might influence NAFLD severity.

Polymorphisms in the SNRPN gene are associated with obesity susceptibility in a Spanish population

BACKGROUND

SNRPN, which codes for the RNA-binding SmN protein, is a candidate gene for Prader-Willi syndrome. One characteristic of this neuroendocrine disorder is hyperphagia resulting in extreme obesity later in life. In the present study, we aimed to assess whether variability within this gene could be implicated in obesity susceptibility.

METHODS

A case-control study was performed including 265 unrelated patients with nonsyndromic and early-onset severe obesity, belonging to high-risk obesity families from Spanish ancestry; 184 healthy control individuals were included representative of the same genetic background and sex-matched. Forty-nine single nucleotide polymorphisms (SNPs) spanning the entire SNRPN gene were selected and genotyped using the Sequenom MassARRAY platform (Sequenom Inc., San Diego, CA, USA).

RESULTS

The four SNPs, rs12905653, rs752874, rs1391516 and rs2047433, were found to be nominally associated with obesity (p < 0.03). The diversity haplotype distribution among cases and controls identified the combination rs12905653-T/rs8028366-A/rs4028395-T as being strongly and inversely associated with obesity (odds ratio = 0.49; p = 0.0006). A genetic risk score was built based on rs12905653, rs1391516 and rs2047433 SNPs and each unit increase in genetic risk score increased the obesity risk by 49% (odds ratio = 1.49, 95% confidence interval = 1.24-1.80).

CONCLUSIONS

To our knowledge, this is the first study reporting an association between variability in the SNRPN gene and the risk of being obese. Interestingly, it was the major allele of each SNP that was found to be associated with the risk of weight gain. Further studies analyzing this locus and the possible additive deleterious capability of SNP combinations could be useful for demonstrating the development of obesity.