Cardiovascular disease prediction and screening using genomics

Polygenic scores, a measure of genome-wide allelic contribution for a trait, have gained attention in the medical research community in recent years and have led to polarised opinions in terms of their clinical importance. A growth in the number and size of genome-wide association studies, enabled by the assembly of large consortia of case-control and cohort studies, and the advent of national biobanks, has led to the discovery of millions of DNA sequence variants associated with thousands of continuous traits of biomedical relevance (e.g. blood pressure) and disease endpoints (e.g. coronary artery disease). This has contributed to the development of thousands of polygenic scores and a heightened interest in their use in disease prediction and screening. This thesis evaluates the clinical utility of polygenic scores mainly in the context of cardiovascular disease prediction and screening. The poor performance of polygenic scores in disease prediction is first demonstrated by analysing the Polygenic Score Catalog that aggregates many published polygenic scores for various disease endpoints. The incremental predictive utility of polygenic scores to currently used cardiovascular risk prediction tools in the UK, based on non-genetic risk factors (e.g. QScores) is then evaluated for various cardiovascular disease endpoints using the appropriate metrics. The thesis also explores the potential application of polygenic scores for the discovery of individuals more likely to carry rare genetic variants, using the example of familial hypercholesterolaemia (FH), the most common monogenic disease, which is still currently highly underdiagnosed worldwide. This section begins by modelling a two-stage population screen for the systematic identification of FH cases in the general adult population, followed by an evaluation of the improvement in FH case detection by the inclusion of environmental predictors and a polygenic score for low-density lipoprotein cholesterol. In conclusion, this thesis puts into perspective the incremental utility of polygenic scores in cardiovascular disease prediction, questioning the claims made on the performance of polygenic scores in prediction. The thesis also explores a potential new avenue of their utility as a tool for aiding with rare variant discovery

LDL-C Concentrations and the 12-SNP LDL-C Score for Polygenic Hypercholesterolaemia in Self-Reported South Asian, Black and Caribbean Participants of the UK Biobank

Background: Monogenic familial hypercholesterolaemia (FH) is an autosomal dominant disorder characterised by elevated low-density lipoprotein cholesterol (LDL-C) concentrations due to monogenic mutations in LDLR, APOB, PCSK9, and APOE. Some mutation-negative patients have a polygenic cause for elevated LDL-C due to a burden of common LDL-C-raising alleles, as demonstrated in people of White British (WB) ancestry using a 12-single nucleotide polymorphism (SNP) score. This score has yet to be evaluated in people of South Asian (SA), and Black and Caribbean (BC) ethnicities. Objectives: 1) Compare the LDL-C and 12-SNP score distributions across the three major ethnic groups in the United Kingdom: WB, SA, and BC individuals; 2) compare the association of the 12-SNP score with LDL-C in these groups; 3) evaluate ethnicity-specific and WB 12-SNP score decile cut-off values, applied to SA and BC ethnicities, in predicting LDL-C concentrations and hypercholesterolaemia (LDL-C>4.9 mmol/L). Methods: The United Kingdom Biobank cohort was used to analyse the LDL-C (adjusted for statin use) and 12-SNP score distributions in self-reported WB (n = 353,166), SA (n = 7,016), and BC (n = 7,082) participants. To evaluate WB and ethnicity-specific 12-SNP score deciles, the total dataset was split 50:50 into a training and testing dataset. Regression analyses (logistic and linear) were used to analyse hypercholesterolaemia (LDL-C>4.9 mmol/L) and LDL-C. Findings: The mean (±SD) measured LDL-C differed significantly between the ethnic groups and was highest in WB [3.73 (±0.85) mmol/L], followed by SA [3.57 (±0.86) mmol/L, p < 2.2 × 10−16], and BC [3.42 (±0.90) mmol/L] participants (p < 2.2 × 10−16). There were significant differences in the mean (±SD) 12-SNP score between WB [0.90 (±0.23)] and BC [0.72 (±0.25), p < 2.2 × 10−16], and WB and SA participants [0.86 (±0.19), p < 2.2 × 10−16]. In all three ethnic groups the 12-SNP score was associated with measured LDL-C [R2 (95% CI): WB = 0.067 (0.065–0.069), BC = 0.080 (0.063–0.097), SA = 0.027 (0.016–0.038)]. The odds ratio and the area under the curve for hypercholesterolaemia were not statistically different when applying ethnicity-specific or WB deciles in all ethnic groups. Interpretation: We provide information on the differences in LDL-C and the 12-SNP score distributions in self-reported WB, SA, and BC individuals of the United Kingdom Biobank. We report the association between the 12-SNP score and LDL-C in these ethnic groups. We evaluate the performance of ethnicity-specific and WB 12-SNP score deciles in predicting LDL-C and hypercholesterolaemia

Modelling a two-stage adult population screen for autosomal dominant familial hypercholesterolaemia: cross-sectional analysis within the UK Biobank

Background: Most people with autosomal dominant familial hypercholesterolaemia (FH) remain undetected, which represents a missed opportunity for coronary heart disease prevention. Objective: To evaluate the performance of two-stage adult population screening for FH. Design: Using data from UK Biobank, we estimated the screening performance of different low-density lipoprotein cholesterol (LDL-C) cut-offs (stage 1) to select adults for DNA sequencing (stage 2) to identify individuals with FH-causing variants inLDLR, APOB, PCSK9andAPOE. We estimated the number of additional FH cases detected by cascade testing of first-degree relatives of index cases and compared the overall approach with screening in childhood. Setting: UK Biobank. Participants: 140 439 unrelated participants of European ancestry from UK Biobank with information on circulating LDL-C concentration and exome sequence. Main outcome measures: For different LDL-C cut-offs, we estimated the detection and false-positive rate, the proportion of individuals who would be referred for DNA sequencing (stage 1 screen positive rate), and the number of FH cases identified by population screening followed by cascade testing. Results: We identified 488 individuals with an FH-causing variant and 139 951 without (prevalence 1 in 288). An LDL-C cut-off of &gt;4.8 mmol/L had a stage 1 detection rate (sensitivity) of 40% (95% CI 36 to 44%) for a false-positive rate of 10% (95% CI 10 to 11%). Detection rate increased at lower LDL-C cut-offs but at the expense of higher false-positive and screen positive rates, and vice versa. Two-stage screening of 100 000 adults using an LDL-C cut-off of 4.8 mmol/L would generate 10 398 stage 1 screen positives for sequencing, detect 138 FH cases and miss 209. Up to 207 additional cases could be detected throughtwo-generationcascade testing of first-degree relatives. By comparison, based on previously published data, childhood screening followed by cascade testing was estimated to detect nearly three times as many affected individuals for around half the sequencing burden. Conclusions: Two-stage adult population screening for FH could help achieve the 25% FH case detection target set in the National Health Service Long Term Plan, but less efficiently than childhood screening and with a greater sequencing requirement

Performance of polygenic risk scores in screening, prediction, and risk stratification: secondary analysis of data in the Polygenic Score Catalog

OBJECTIVE: To clarify the performance of polygenic risk scores in population screening, individual risk prediction, and population risk stratification. DESIGN: Secondary analysis of data in the Polygenic Score Catalog. SETTING: Polygenic Score Catalog, April 2022. Secondary analysis of 3915 performance metric estimates for 926 polygenic risk scores for 310 diseases to generate estimates of performance in population screening, individual risk, and population risk stratification. PARTICIPANTS: Individuals contributing to the published studies in the Polygenic Score Catalog. MAIN OUTCOME MEASURES: Detection rate for a 5% false positive rate (DR5) and the population odds of becoming affected given a positive result; individual odds of becoming affected for a person with a particular polygenic score; and odds of becoming affected for groups of individuals in different portions of a polygenic risk score distribution. Coronary artery disease and breast cancer were used as illustrative examples. RESULTS: For performance in population screening, median DR5 for all polygenic risk scores and all diseases studied was 11% (interquartile range 8-18%). Median DR5 was 12% (9-19%) for polygenic risk scores for coronary artery disease and 10% (9-12%) for breast cancer. The population odds of becoming affected given a positive results were 1:8 for coronary artery disease and 1:21 for breast cancer, with background 10 year odds of 1:19 and 1:41, respectively, which are typical for these diseases at age 50. For individual risk prediction, the corresponding 10 year odds of becoming affected for individuals aged 50 with a polygenic risk score at the 2.5th, 25th, 75th, and 97.5th centiles were 1:54, 1:29, 1:15, and 1:8 for coronary artery disease and 1:91, 1:56, 1:34, and 1:21 for breast cancer. In terms of population risk stratification, at age 50, the risk of coronary artery disease was divided into five groups, with 10 year odds of 1:41 and 1:11 for the lowest and highest quintile groups, respectively. The 10 year odds was 1:7 for the upper 2.5% of the polygenic risk score distribution for coronary artery disease, a group that contributed 7% of cases. The corresponding estimates for breast cancer were 1:72 and 1:26 for the lowest and highest quintile groups, and 1:19 for the upper 2.5% of the distribution, which contributed 6% of cases. CONCLUSION: Polygenic risk scores performed poorly in population screening, individual risk prediction, and population risk stratification. Strong claims about the effect of polygenic risk scores on healthcare seem to be disproportionate to their performance

Nature-based coastal restoration: Development of an early-rearing production protocol of sugar kelp (Saccharina latissima Linnaeus) for bottom planting activities in the Gulf of St-Lawrence (Québec, Canada)

Successful bottom planting of indigenous macroalgae Saccharina latissima aimed at coastal restoration purposes require the mass production in controlled conditions of strongly fixed, healthy sporophytes followed by optimal transfer techniques in order to ensure viability and vigor of the young seedlings about to be directly introduced in the coastal environment. Early development of S. latissima submitted to different combinations of substrate type (natural vs artificial brick-shaped substrate), gametophyte spraying method (water-based vs binder-based) and water velocity (0.1 vs 0.2 m s-1) was evaluated during a growth trial that lasted 42 days. Overall, all experimental groups (8 in triplicate) reached the targeted length of 15 mm between 35-42 days post-seeding. No strong indications that the proposed 2×2×2 factorial design generated long lasting effects on growth and development indicators were observed (thallus length, SGR and % coverage). The observation of no persistent difference in the growth response of S. latissima under all experimental conditions, demonstrates that it is well suited for mass production of seedlings. Our results and evidenced-based practices led us to conclude that the use of an artificial substrate in combination with a binder-based gametophyte pulverization and the application of a velocity 0.2 m s-1 during early-growth could be adopted in a standardized protocol. We argue that 1) artificial substrates (uniform shape, stackable and rough surface) will most likely allow better use of a vessel’s open deck space and adherence of the developing holdfast; 2) the use of a binder may slow down the dehydration of the propagules and promote adhesiveness to the substrate during rearing, handling and transfer operations and under varying flow rates or wave actions respectively and 3) highest velocity should promote the selection of propagules with strongest attachment and thus possibly limit post-transfer dislodgement. We suggest further studies should 1) focus on identifying optimal gametophyte concentration at the spraying step, in order to reduce production costs and maximise productivity of seedling operations and 2) include biomass determination (g of tissue per cm2) in combination to the semi-quantitative density evaluation (% coverage) based on image-analysis, in order to improve our global assessment of growth

Performance of polygenic risk scores in screening, prediction, and risk stratification: secondary analysis of data in the Polygenic Score Catalog.

Peer reviewed: TrueOBJECTIVE: To clarify the performance of polygenic risk scores in population screening, individual risk prediction, and population risk stratification. DESIGN: Secondary analysis of data in the Polygenic Score Catalog. SETTING: Polygenic Score Catalog, April 2022. Secondary analysis of 3915 performance metric estimates for 926 polygenic risk scores for 310 diseases to generate estimates of performance in population screening, individual risk, and population risk stratification. PARTICIPANTS: Individuals contributing to the published studies in the Polygenic Score Catalog. MAIN OUTCOME MEASURES: Detection rate for a 5% false positive rate (DR5) and the population odds of becoming affected given a positive result; individual odds of becoming affected for a person with a particular polygenic score; and odds of becoming affected for groups of individuals in different portions of a polygenic risk score distribution. Coronary artery disease and breast cancer were used as illustrative examples. RESULTS: For performance in population screening, median DR5 for all polygenic risk scores and all diseases studied was 11% (interquartile range 8-18%). Median DR5 was 12% (9-19%) for polygenic risk scores for coronary artery disease and 10% (9-12%) for breast cancer. The population odds of becoming affected given a positive results were 1:8 for coronary artery disease and 1:21 for breast cancer, with background 10 year odds of 1:19 and 1:41, respectively, which are typical for these diseases at age 50. For individual risk prediction, the corresponding 10 year odds of becoming affected for individuals aged 50 with a polygenic risk score at the 2.5th, 25th, 75th, and 97.5th centiles were 1:54, 1:29, 1:15, and 1:8 for coronary artery disease and 1:91, 1:56, 1:34, and 1:21 for breast cancer. In terms of population risk stratification, at age 50, the risk of coronary artery disease was divided into five groups, with 10 year odds of 1:41 and 1:11 for the lowest and highest quintile groups, respectively. The 10 year odds was 1:7 for the upper 2.5% of the polygenic risk score distribution for coronary artery disease, a group that contributed 7% of cases. The corresponding estimates for breast cancer were 1:72 and 1:26 for the lowest and highest quintile groups, and 1:19 for the upper 2.5% of the distribution, which contributed 6% of cases. CONCLUSION: Polygenic risk scores performed poorly in population screening, individual risk prediction, and population risk stratification. Strong claims about the effect of polygenic risk scores on healthcare seem to be disproportionate to their performance

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TIB: RN 5973(2081) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekSIGLEDEGerman