THU0018 GENETIC FACTORS AND RESPONSE TO RITUXIMAB THERAPY IN SLE

2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 222-223
Author(s):  
L. Liu ◽  
A. Amar ◽  
J. Robinson ◽  
I. N. Bruce ◽  
D. Morris ◽  
...  
Keyword(s):  
Risk Score ◽  
Genetic Risk ◽  
Risk Scores ◽  
Research Centre ◽  
Fc Gamma Receptor ◽  
Genetic Risk Scores ◽  
Gamma Receptor ◽  
Genome Wide ◽  
Receptor Locus ◽  
Damage Accrual

Background:The biologic drug Rituximab (anti-CD20) is used therapeutically in SLE, however the clinical response to the therapy, which is expensive, is quite variable. Factors influencing the efficacy have been challenging to determine. The MRC funded MASTERPLANS consortium has investigated prognostic factors that determine the therapeutic response to biologic therapy in SLE. Genetics has not been studied on a large scale in this context. SLE is a complex clinical phenotype, it is likewise a complex genetic trait, although it has recently been shown that polygenic risk scores do have a relationship to the severity of the disease (1). In addition, genetic risk factors for SLE, coded at the IgG Fc gamma receptor locus, have the potential to influence antibody-dependent cell-mediated cytotoxicity.Objectives:To determine whether the genetics influences the clinical outcome of therapy with Rituximab. The study used both genome-wide data in the form of genetic risk scores as well as specific genetic data at a candidate locus, namely the IgG Fc gamma receptor locusMethods:Samples from the BILAG Biologics Register (BILAG BR) of individuals treated with Rituximab were subject to genome-wide genotyping with Illumina GSA V2 chip. Genetic risk scores (GRS) were calculated through a weighted risk sum. Genetic variation at the IgG Fc gamma receptor locus is not captured well on genotyping chips and hence common coding and copy number variation was studied using Multiplex Ligation-dependent Probe Amplification (MLPA) and sequencing.Results:BILAG-BR samples for SLE part of receiving Rituximab therapy were genotyped on GSA chip, 573 samples passed QC and were used in principal components analysis (PCA), among them, 310 samples both have RTX treatment information and GRS calculated. Examining the population using PCA in the informative samples revealed that the largest distinction, European versus African ancestry did not correlate with Rituximab response. When GRS was determined in the Responders versus the Non-responders there was a weak correlation with those with a higher risk score showing a tendency to be in the responder group (Fig. 1). We also examined variation at the IgG Fc gamma receptor locus, polymorphisms of which are associated with SLE and have been correlated with therapeutic outcome in lymphoma (2). In a subset of the BILAG-BR cohort, we show that carriage of the SLE risk allele atFCGR3A(158F) was enriched in the ‘responder at some point’ group compared to the non-responder group (P=0.03, Chi-square).Conclusion:We present preliminary data indicating that genetics at both the genome wide level and at theFCGRlocus show some influence on the outcome of therapy with Rituximab in SLE; more data are required in order to draw firm conclusions.References:[1]Reid S et al. High genetic risk score is associated with early disease onset, damage accrual and decreased survival in systemic lupus erythematosus.Ann Rheum Dis.2019 Dec 11. [Epub ahead of print][2]Weng WK, Levy R. Two immunoglobulin G fragment C receptor polymorphisms independently predict response to rituximab in patients with follicular lymphoma. J Clin Oncol. 2003;21(21):3940–3947.Acknowledgments:King’s and GSTT Biomedical Research Centre and M01665X/1MRC Stratified Medicine grantDisclosure of Interests:Lu Liu: None declared, Ariella Amar: None declared, James Robinson: None declared, Ian N. Bruce Grant/research support from: Genzyme Sanofi, GSK, and UCB, Consultant of: Eli Lilly, AstraZeneca, UCB, Iltoo, and Merck Serono, Speakers bureau: UCB, David Morris: None declared, Tim Vyse: None declared

scholarly journals Assessing the clinical utility of genetic risk scores for targeted cancer screening

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Carly A. Conran ◽  
Zhuqing Shi ◽  
William Kyle Resurreccion ◽  
Rong Na ◽  
Brian T. Helfand ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Primary Care ◽  
High Risk ◽  
Risk Score ◽  
Genetic Risk ◽  
Clinical Utility ◽  
Low Risk ◽  
Risk Scores ◽  
Average Risk ◽  
Genetic Risk Scores

Abstract Background Genome-wide association studies have identified thousands of disease-associated single nucleotide polymorphisms (SNPs). A subset of these SNPs may be additively combined to generate genetic risk scores (GRSs) that confer risk for a specific disease. Although the clinical validity of GRSs to predict risk of specific diseases has been well established, there is still a great need to determine their clinical utility by applying GRSs in primary care for cancer risk assessment and targeted intervention. Methods This clinical study involved 281 primary care patients without a personal history of breast, prostate or colorectal cancer who were 40–70 years old. DNA was obtained from a pre-existing biobank at NorthShore University HealthSystem. GRSs for colorectal cancer and breast or prostate cancer were calculated and shared with participants through their primary care provider. Additional data was gathered using questionnaires as well as electronic medical record information. A t-test or Chi-square test was applied for comparison of demographic and key clinical variables among different groups. Results The median age of the 281 participants was 58 years and the majority were female (66.6%). One hundred one (36.9%) participants received 2 low risk scores, 99 (35.2%) received 1 low risk and 1 average risk score, 37 (13.2%) received 1 low risk and 1 high risk score, 23 (8.2%) received 2 average risk scores, 21 (7.5%) received 1 average risk and 1 high risk score, and no one received 2 high risk scores. Before receiving GRSs, younger patients and women reported significantly more worry about risk of developing cancer. After receiving GRSs, those who received at least one high GRS reported significantly more worry about developing cancer. There were no significant differences found between gender, age, or GRS with regards to participants’ reported optimism about their future health neither before nor after receiving GRS results. Conclusions Genetic risk scores that quantify an individual’s risk of developing breast, prostate and colorectal cancers as compared with a race-defined population average risk have potential clinical utility as a tool for risk stratification and to guide cancer screening in a primary care setting.

scholarly journals Interaction between Genetic Risk Scores for reduced pulmonary function and smoking, asthma and endotoxin

Thorax ◽  
2021 ◽  
pp. thoraxjnl-2020-215624
Author(s):  
Sinjini Sikdar ◽  
Annah B Wyss ◽  
Mi Kyeong Lee ◽  
Thanh T Hoang ◽  
Marie Richards ◽  
...  
Keyword(s):  
Pulmonary Function ◽  
Genetic Risk ◽  
Association Studies ◽  
European Ancestry ◽  
Risk Scores ◽  
P Value ◽  
Genome Wide Association Studies ◽  
Inverse Association ◽  
Genetic Risk Scores ◽  
Genome Wide

RationaleGenome-wide association studies (GWASs) have identified numerous loci associated with lower pulmonary function. Pulmonary function is strongly related to smoking and has also been associated with asthma and dust endotoxin. At the individual SNP level, genome-wide analyses of pulmonary function have not identified appreciable evidence for gene by environment interactions. Genetic Risk Scores (GRSs) may enhance power to identify gene–environment interactions, but studies are few.MethodsWe analysed 2844 individuals of European ancestry with 1000 Genomes imputed GWAS data from a case–control study of adult asthma nested within a US agricultural cohort. Pulmonary function traits were FEV1, FVC and FEV1/FVC. Using data from a recent large meta-analysis of GWAS, we constructed a weighted GRS for each trait by combining the top (p value<5×10−9) genetic variants, after clumping based on distance (±250 kb) and linkage disequilibrium (r2=0.5). We used linear regression, adjusting for relevant covariates, to estimate associations of each trait with its GRS and to assess interactions.ResultsEach trait was highly significantly associated with its GRS (all three p values<8.9×10−8). The inverse association of the GRS with FEV1/FVC was stronger for current smokers (pinteraction=0.017) or former smokers (pinteraction=0.064) when compared with never smokers and among asthmatics compared with non-asthmatics (pinteraction=0.053). No significant interactions were observed between any GRS and house dust endotoxin.ConclusionsEvaluation of interactions using GRSs supports a greater impact of increased genetic susceptibility on reduced pulmonary function in the presence of smoking or asthma.

scholarly journals Sexual Differences in Genetic Predisposition of Coronary Artery Disease

2020 ◽  
Author(s):  
Yunfeng Huang ◽  
Qin Hui ◽  
Marta Gwinn ◽  
Yi-Juan Hu ◽  
Arshed A. Quyyumi ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Risk Score ◽  
Genetic Risk ◽  
Genetic Risk Score ◽  
Risk Scores ◽  
Men And Women ◽  
High Genetic Risk ◽  
Genome Wide ◽  
Artery Disease

Background - The genomic structure that contributes to the risk of coronary artery disease (CAD) can be evaluated as a risk score of multiple variants. However, sex differences have not been fully examined in applications of genetic risk score of CAD. Methods - Using data from the UK Biobank, we constructed a CAD genetic risk score based on all known loci, three mediating trait-based (blood pressure, lipids, body mass index) sub-scores, and a genome-wide polygenic risk score based on 1.1 million variants. The differences in genetic associations with prevalent and incident CAD between men and women were investigated among 317,509 unrelated individuals of European ancestry. We also assessed interactions with sex for 161 individual loci included in the comprehensive genetic risk score. Results - For both prevalent and incident CAD, the associations of comprehensive and genome-wide genetic risk scores were stronger among men than women. Using a score of 161 loci, we observed a 2.4 times higher risk for incident CAD comparing men with high genetic risk to men with low genetic risk, but an 80 percent greater risk comparing women with high genetic risk to women with low genetic risk. (interaction p=0.002). Of the three sub-scores, the blood pressure-associated sub-score exhibited sex differences (interaction p=0.0004 per SD increase in sub-score). Analysis of individual variants identified a novel gene-sex interaction at locus 21q22.11 . Conclusions - Sexual differences in genetic predisposition should be considered in future studies of coronary artery disease, and genetic risk scores should not be assumed to perform equally well in men and women.

scholarly journals Genetic risk score for ovarian cancer based on chromosomal-scale length variation

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Christopher Toh ◽  
James P. Brody
Keyword(s):  
Ovarian Cancer ◽  
Confidence Interval ◽  
Risk Score ◽  
Genetic Risk ◽  
Germ Line ◽  
Genetic Risk Score ◽  
Risk Scores ◽  
Length Variation ◽  
Genetic Risk Scores ◽  
Scale Length

Abstract Introduction Twin studies indicate that a substantial fraction of ovarian cancers should be predictable from genetic testing. Genetic risk scores can stratify women into different classes of risk. Higher risk women can be treated or screened for ovarian cancer, which should reduce ovarian cancer death rates. However, current ovarian cancer genetic risk scores do not work that well. We developed a genetic risk score based on variations in the length of chromosomes. Methods We evaluated this genetic risk score using data collected by The Cancer Genome Atlas. We synthesized a dataset of 414 women who had ovarian serous carcinoma and 4225 women who had no form of ovarian cancer. We characterized each woman by 22 numbers, representing the length of each chromosome in their germ line DNA. We used a gradient boosting machine to build a classifier that can predict whether a woman had been diagnosed with ovarian cancer. Results The genetic risk score based on chromosomal-scale length variation could stratify women such that the highest 20% had a 160x risk (95% confidence interval 50x-450x) compared to the lowest 20%. The genetic risk score we developed had an area under the curve of the receiver operating characteristic curve of 0.88 (95% confidence interval 0.86–0.91). Conclusion A genetic risk score based on chromosomal-scale length variation of germ line DNA provides an effective means of predicting whether or not a woman will develop ovarian cancer.

scholarly journals Relationship between Genetic Risk and Age of Diagnosis of Systemic Lupus Erythematosus

2020 ◽  
pp. jrheum.200002
Author(s):  
Daniela Dominguez ◽  
Sylvia Kamphuis ◽  
Joseph Beyene ◽  
Joan Wither ◽  
John B. Harley ◽  
...  
Keyword(s):  
Risk Score ◽  
Lupus Erythematosus ◽  
Genetic Risk ◽  
Genetic Risk Score ◽  
Risk Scores ◽  
Ancestral Population ◽  
Childhood Onset ◽  
Genetic Risk Scores ◽  
Risk Alleles ◽  
Age Of Diagnosis

Objective Specific risk alleles for childhood-onset SLE (cSLE) versus adult-onset SLE (aSLE) patients have not been identified. The aims of this study were to determine if: 1) There is an association between non-HLA-related genetic risk score (GRS) and age of SLE diagnosis; and if 2) There is an association between HLA-related genetic risk score and age of SLE diagnosis. Methods Genomic DNA was obtained from 2,001 multi-ethnic patients and genotyped using the Immunochip. Following quality control, genetic risk counting (GRCS), weighted (GRWS) and standardized counting (GRSCS) and standardized weighted (GRSWS) scores were calculated based on independent SNPs from validated SLE-loci. Scores were analyzed in a regression model and adjusted by sex and ancestral population. Results The analysed cohort consisted of 1,540 patients: 1,351 females and 189 males (675 cSLE and 865 aSLE). There were significant negative associations with age of SLE diagnosis p=0.011 and r2=0.175 for GRWS, p=0.008 and r2=0.178 for GRSCS, p=0.002 and r2=0.176 for GRSWS for all non-HLA genetic risk scores (higher GRS the lower the age of diagnosis.) All HLA genetic risk scores showed significant positive associations with age of diagnosis p=0.049 and r2=0.176 for GRCS, p=0.022 and r2=0.176 for GRWS, p=0.022 and r2=0.176 for GRSCS, p=0.011 and r2=0.177 for GRSWS: higher genetic scores correlated with higher age of diagnosis. Conclusion Our data suggested that there is a linear relationship between genetic risk and age of SLE diagnosis and that HLA and non-HLA genetic risk scores are associated with age of diagnosis in opposite directions.

scholarly journals Evaluation of genetic risk scores for lipid levels using genome-wide markers in the Framingham Heart Study

2009 ◽  
Vol 3 (Suppl 7) ◽  
pp. S46 ◽  
Author(s):  
Stephen R Piccolo ◽  
Ryan P Abo ◽  
Kristina Allen-Brady ◽  
Nicola J Camp ◽  
Stacey Knight ◽  
...  
Keyword(s):  
Genetic Risk ◽  
Framingham Heart Study ◽  
Risk Scores ◽  
Lipid Levels ◽  
Genetic Risk Scores ◽  
Genome Wide ◽  
Heart Study

scholarly journals Genetic risk score for ovarian cancer based on chromosomal-scale length variation.

2020 ◽  
Author(s):  
Chris Toh ◽  
James P Brody
Keyword(s):  
Ovarian Cancer ◽  
Confidence Interval ◽  
Risk Score ◽  
Genetic Risk ◽  
Germ Line ◽  
Genetic Risk Score ◽  
Risk Scores ◽  
Length Variation ◽  
Genetic Risk Scores ◽  
Scale Length

Introduction. Twin studies indicate that a substantial fraction of ovarian cancers should be predictable from genetic testing. Genetic risk scores can stratify women into different classes of risk. Higher risk women can be treated or screened for ovarian cancer, which should reduce overall death rates due to ovarian cancer. However, current ovarian cancer genetic risk scores, based on SNPs, do not work that well. We developed a genetic risk score based on structural variation, quantified by variations in the length of chromosomes. Methods. We evaluated this genetic risk score using data collected by The Cancer Genome Atlas. From this dataset, we synthesized a dataset of 414 women who had ovarian serous carcinoma and 4225 women who had no form of ovarian cancer. We characterized each woman by 22 numbers, representing the length of each chromosome in their germ line DNA. We used a gradient boosting machine, a machine learning algorithm, to build a classifier that can predict whether a woman had been diagnosed with ovarian cancer in this dataset. Results. The genetic risk score based on chromosomal-scale length variation could stratify women such that the highest 20% had a 160x risk (95% confidence interval 50x-450x) compared to the lowest 20%. The genetic risk score we developed had an area under the curve of the receiver operating characteristic curve of 0.88 (estimated 95% confidence interval 0.86-0.91). Conclusion. A genetic risk score based on chromosomal-scale length variation of germ line DNA provides an effective means of predicting whether or not a woman will develop ovarian cancer.

scholarly journals Genetic Risk Score for Ovarian Cancer Based on Chromosomal-scale Length Variation

2020 ◽  
Author(s):  
Chris Toh ◽  
James Brody
Keyword(s):  
Ovarian Cancer ◽  
Confidence Interval ◽  
Risk Score ◽  
Genetic Risk ◽  
Germ Line ◽  
Genetic Risk Score ◽  
Risk Scores ◽  
Length Variation ◽  
Genetic Risk Scores ◽  
Scale Length

Abstract Introduction.Twin studies indicate thata substantial fraction of ovarian cancers should be predictable from genetic testing. Genetic risk scores can stratify women into different classes of risk. Higher risk women can be treated or screened for ovarian cancer, which should reduce overall death rates due to ovarian cancer. However, current ovarian cancer genetic risk scores, based on SNPs, do not work that well. We developed a genetic risk score based on structural variation, quantified by variations in the length of chromosomes.Methods. We evaluated this genetic risk score using data collected by The Cancer Genome Atlas. From this dataset, we synthesized a dataset of 414 women who had ovarian serous carcinoma and 4225 women who had no form of ovarian cancer. We characterized each woman by 22 numbers, representing the length of each chromosome in their germ line DNA. We used a gradient boosting machine, a machine learning algorithm, to build a classifier that can predict whether a woman had been diagnosed with ovarian cancer in this dataset.Results. The genetic risk score based on chromosomal-scale length variation could stratify women such that the highest 20% had a 160x risk (95% confidence interval 50x-450x) compared to the lowest 20%. The genetic risk score we developed had an area under the curve of the receiver operating characteristic curve of 0.88 (estimated 95% confidence interval 0.86-0.91).Conclusion. A genetic risk score based on chromosomal-scale length variation of germ line DNA provides an effective means of predicting whether or not a woman will develop ovarian cancer.

scholarly journals Assessing the Clinical Utility of Genetic Risk Scores for Targeted Cancer Screening

2020 ◽  
Author(s):  
Carly Ann Conran ◽  
Zhuqing Shi ◽  
William Kyle Resurreccion ◽  
Rong Na ◽  
Brian T. Helfand ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Primary Care ◽  
High Risk ◽  
Risk Score ◽  
Genetic Risk ◽  
Clinical Utility ◽  
Low Risk ◽  
Risk Scores ◽  
Average Risk ◽  
Genetic Risk Scores

Abstract Background: Genome-wide association studies have identified thousands of disease-associated single nucleotide polymorphisms (SNPs). A subset of these SNPs may be additively combined to generate genetic risk scores (GRSs) that confer risk for a specific disease. Although the clinical validity of GRSs to predict risk of specific diseases has been well established, there is still a great need to determine their clinical utility by applying GRSs in primary care for cancer risk assessment and targeted intervention.Methods: This clinical study involved 281 primary care patients without a personal history of breast, prostate or colorectal cancer who were 40-70 years old. DNA was obtained from a pre-existing biobank at NorthShore University HealthSystem. GRSs for colorectal cancer and breast or prostate cancer were calculated and shared with participants through their primary care provider. Additional data was gathered using questionnaires as well as electronic medical record information. A t-test or Chi-square test was applied for comparison of demographic and key clinical variables among different groups.Results: The median age of the 281 participants was 58 years and the majority were female (66.6%). One hundred one (36.9%) participants received 2 low risk scores, 99 (35.2%) received 1 low risk and 1 average risk score, 37 (13.2%) received 1 low risk and 1 high risk score, 23 (8.2%) received 2 average risk scores, 21 (7.5%) received 1 average risk and 1 high risk score, and no one received 2 high risk scores. Before receiving GRSs, younger patients and women reported significantly more worry about risk of developing cancer. After receiving GRSs, those who received at least one high GRS reported significantly more worry about developing cancer. There were no significant differences found between gender, age, or GRS with regards to participants’ reported optimism about their future health neither before nor after receiving GRS results.Conclusions: Genetic risk scores that quantify an individual’s risk of developing breast, prostate and colorectal cancers as compared with a race-defined population average risk have potential clinical utility as a tool for risk stratification and to guide cancer screening in a primary care setting.

scholarly journals Genetic determinants of glucose levels in pregnancy: genetic risk scores analysis and GWAS in the Norwegian STORK cohort

2018 ◽  
Vol 179 (6) ◽  
pp. 363-372 ◽  
Author(s):  
Gunn-Helen Moen ◽  
Marissa LeBlanc ◽  
Christine Sommer ◽  
Rashmi B Prasad ◽  
Tove Lekva ◽  
...  
Keyword(s):  
Pregnant Women ◽  
Genetic Risk ◽  
Association Studies ◽  
Risk Scores ◽  
Oral Glucose ◽  
Genome Wide Association Studies ◽  
Shape Information ◽  
Genetic Risk Scores ◽  
Genome Wide ◽  
In Pregnancy

Objective Hyperglycaemia during pregnancy increases the risk of adverse health outcomes in mother and child, but the genetic aetiology is scarcely studied. Our aims were to (1) assess the overlapping genetic aetiology between the pregnant and non-pregnant population and (2) assess the importance of genome-wide polygenic contributions to glucose traits during pregnancy, by exploring whether genetic risk scores (GRSs) for fasting glucose (FG), 2-h glucose (2hG), type 2 diabetes (T2D) and BMI in non-pregnant individuals were associated with glucose measures in pregnant women. Methods We genotyped 529 Norwegian pregnant women and constructed GRS from known genome-wide significant variants and SNPs weakly associated (p > 5 × 10−8) with FG, 2hG, BMI and T2D from external genome-wide association studies (GWAS) and examined the association between these scores and glucose measures at gestational weeks 14–16 and 30–32. We also performed GWAS of FG, 2hG and shape information from the glucose curve during an oral glucose tolerance test (OGTT). Results GRSFG explained similar variance during pregnancy as in the non-pregnant population (~5%). GRSBMI and GRST2D explained up to 1.3% of the variation in the glucose traits in pregnancy. If we included variants more weakly associated with these traits, GRS2hG and GRST2D explained up to 2.4% of the variation in the glucose traits in pregnancy, highlighting the importance of polygenic contributions. Conclusions Our results suggest overlap in the genetic aetiology of FG in pregnant and non-pregnant individuals. This was less apparent with 2hG, suggesting potential differences in postprandial glucose metabolism inside and outside of pregnancy.

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