Epigenomic partitioning of a polygenic risk score for asthma reveals distinct genetically driven disease pathways.

BACKGROUND: Individual differences in susceptibility to develop asthma, a heterogeneous chronic inflammatory lung disease, are poorly understood. It remains debated whether genetics can predict asthma risk and how genetic variants modulate the complex pathophysiology of asthma. AIM: To build polygenic risk scores (PRSs) for asthma risk prediction and epigenomically link predictive genetic variants to pathophysiological mechanisms. METHODS: Restricted PRSs were constructed using single nucleotide variants derived from genome-wide association studies and validated using data generated in the Rotterdam Study, a Dutch prospective cohort of 14 926 individuals. Outcomes used were asthma, childhood-onset asthma (COA), adulthood-onset asthma (AOA), eosinophilic asthma, and asthma exacerbations. Genome-wide chromatin analysis data from 19 disease-relevant cell types were used for epigenomic PRS partitioning. RESULTS: PRSs obtained predicted asthma and related outcomes, with the strongest associations observed for COA (2.55 odds ratios per PRS standard deviation, area under the curve of 0.760). PRSs allowed for the classification of individuals into high and low-risk groups. PRS partitioning using epigenomic profiles identified 5 clusters of variants within putative gene regulatory regions linked to specific asthma-relevant cells, genes, and biological pathways. CONCLUSIONS: PRSs were associated with asthma(-related traits) in a Dutch prospective cohort, with substantially higher predictive power observed for COA than for AOA. Importantly, PRS variants could be epigenomically partitioned into clusters of regulatory variants with different pathophysiological association patterns and effect estimates, which likely represent distinct genetically driven disease pathways. Our findings have potential implications for personalized risk mitigation and treatment strategies.

Cohort profile update: Tehran cardiometabolic genetic study.

The Tehran cardiometabolic genetic study (TCGS) is a large population-based cohort study that conducts periodic follow-ups. TCGS has created a comprehensive database comprising 20,367 participants born between 1911 and 2015 selected from four main ongoing studies in a family-based longitudinal framework. The study's primary goal is to identify the potential targets for prevention and intervention for non-communicable diseases that may develop in mid-life and late life. TCGS cohort focuses on cardiovascular, endocrine, metabolic abnormalities, cancers, and some inherited diseases. Since 2017, the TCGS cohort has augmented by encoding all health-related complications, including hospitalization outcomes and self-reports according to ICD11 coding, and verifying consanguineous marriage using genetic markers. This research provides an update on the rationale and design of the study, summarizes its findings, and outlines the objectives for precision medicine.

Coronary Artery Calcium Score and Polygenic Risk Score for the Prediction of Coronary Heart Disease Events.

Importance: Coronary artery calcium score and polygenic risk score have each separately been proposed as novel markers to identify risk of coronary heart disease (CHD), but no prior studies have directly compared these markers in the same cohorts. Objective: To evaluate change in CHD risk prediction when a coronary artery calcium score, a polygenic risk score, or both are added to a traditional risk factor-based model. Design, Setting, and Participants: Two observational population-based studies involving individuals aged 45 years through 79 years of European ancestry and free of clinical CHD at baseline: the Multi-Ethnic Study of Atherosclerosis (MESA) study involved 1991 participants at 6 US centers and the Rotterdam Study (RS) involved 1217 in Rotterdam, the Netherlands. Exposure: Traditional risk factors were used to calculate CHD risk (eg, pooled cohort equations [PCEs]), computed tomography for the coronary artery calcium score, and genotyped samples for a validated polygenic risk score. Main Outcomes and Measures: Model discrimination, calibration, and net reclassification improvement (at the recommended risk threshold of 7.5%) for prediction of incident CHD events were assessed. Results: The median age was 61 years in MESA and 67 years in RS. Both log (coronary artery calcium+1) and polygenic risk score were significantly associated with 10-year risk of incident CHD (hazards ratio per SD, 2.60; 95% CI, 2.08-3.26 and 1.43; 95% CI, 1.20-1.71, respectively), in MESA. The C statistic for the coronary artery calcium score was 0.76 (95% CI, 0.71-0.79) and for the polygenic risk score, 0.69 (95% CI, 0.63-0.71). The change in the C statistic when each was added to the PCEs was 0.09 (95% CI, 0.06-0.13) for the coronary artery calcium score, 0.02 (95% CI, 0.00-0.04) for the polygenic risk score, and 0.10 (95% CI, 0.07-0.14) for both. Overall categorical net reclassification improvement was significant when the coronary artery calcium score (0.19; 95% CI, 0.06-0.28) but was not significant when the polygenic risk score (0.04; 95% CI, -0.05 to 0.10) was added to the PCEs. Calibration of the PCEs and models with coronary artery calcium and/or polygenic risk scores was adequate (all χ2<20). Subgroup analysis stratified by the median age demonstrated similar findings. Similar findings were observed for 10-year risk in RS and in longer-term follow-up in MESA (median, 16.0 years). Conclusions and Relevance: In 2 cohorts of middle-aged to older adults from the US and the Netherlands, the coronary artery calcium score had better discrimination than the polygenic risk score for risk prediction of CHD. In addition, the coronary artery calcium score but not the polygenic risk score significantly improved risk discrimination and risk reclassification for CHD when added to traditional risk factors.

Insulin resistance-related circulating predictive markers in the metabolic syndrome: a systematic review in the Iranian population.

Background: Specific biomarkers for metabolic syndrome (MetS) may improve diagnostic specificity for clinical information. One of the main pathophysiological mechanisms of MetS is insulin resistance (IR). This systematic review aimed to summarize IR-related biomarkers that predict MetS and have been investigated in Iranian populations. Methods: An electronic literature search was done using the PubMed and Scopus databases up to June 2022. The risk of bias was assessed for the selected articles using the instrument suggested by the Joanna Briggs Institute (JBI). This systematic review protocol was registered with PROSPERO (registration number CRD42022372415). Results: Among the reviewed articles, 46 studies investigated the association between IR biomarkers and MetS in the Iranian population. The selected studies were published between 2009 and 2022, with the majority being conducted on adults and seven on children and adolescents. The adult treatment panel III (ATP III) was the most commonly used criteria to define MetS. At least four studies were conducted for each IR biomarker, with LDL-C being the most frequently evaluated biomarker. Some studies have assessed the diagnostic potency of markers using the area under the curve (AUC) with sensitivity, specificity, and an optimal cut-off value. Among the reported values, lipid ratios and the difference between non-HDL-C and LDL-C levels showed the highest AUCs (≥ 0.80) for predicting MetS. Conclusions: Considering the findings of the reviewed studies, fasting insulin, HOMA-IR, leptin, HbA1c, and visfatin levels were positively associated with MetS, whereas adiponectin and ghrelin levels were negatively correlated with this syndrome. Among the investigated IR biomarkers, the association between adiponectin levels and components of MetS was well established. Supplementary Information: The online version contains supplementary material available at 10.1007/s40200-023-01347-6.

Weight-Bearing Physical Activity, Lower-Limb Muscle Mass, and Risk of Knee Osteoarthritis.

Importance: It has been demonstrated that total physical activity is not associated with risk of osteoarthritis. However, the association of different types of physical activity with incident knee osteoarthritis remains unclear. Objective: To determine whether weight-bearing recreational physical activities are associated with increased risk of incident knee osteoarthritis. Design, Setting, and Participants: This prospective cohort study used data from the Rotterdam Study (1996 to 2009), including participants with knee x-ray measurements at baseline and follow-up examinations. Participants with knee osteoarthritis at baseline were excluded. Residents aged 45 years and older of the Ommoord district in the city of Rotterdam in The Netherlands were invited to join the Rotterdam Study (78% response rate). Analysis was conducted in June 2023. Exposure: Total, weight-bearing, and non-weight-bearing recreational physical activities collected by questionnaires at baseline. Main Outcomes and Measures: Incident radiographic knee osteoarthritis measured by knee x-ray was the primary outcome, and incident symptomatic knee osteoarthritis defined by x-ray and knee pain questionnaire was the secondary outcome. The association of different types of recreational physical activity with radiographic knee osteoarthritis was examined using logistic regression within generalized estimating equation framework after adjusting for potential confounders. A prespecified stratification analysis was planned on the basis of lower-limb muscle mass index (LMI) tertiles, measured by dual-energy x-ray absorptiometry. Results: A total of 5003 individuals (2804 women [56.0%]; mean [SD] age, 64.5 [7.9] years) were included. The knee osteoarthritis incident rate was 8.4% (793 of 9483 knees) for a mean (SD) follow-up time of 6.33 (2.46) years. Higher weight-bearing activity was associated with increased odds of incident knee osteoarthritis (odds ratio [OR], 1.22; 95% CI, 1.10-1.35; P < .001), but non-weight-bearing activity was not (OR, 1.04; 95% CI, 0.95-1.15; P = .37). In the analysis stratified by LMI tertiles, the association of weight-bearing activity with incident osteoarthritis was found only among 431 patients in the lowest LMI tertile (OR, 1.53; 95% CI, 1.15-2.04; P = .003), but not among patients in the middle or high LMI tertile. Conclusions and Relevance: The findings of this study suggest that weight-bearing activity is associated with incident knee osteoarthritis in people with low levels of lower-limb muscle mass, which might be a promising avenue for tailored advice for physical activity.

Low-Cost High-Throughput Genotyping for Diagnosing Familial Hypercholesterolemia.

BACKGROUND: Familial hypercholesterolemia (FH) is a common but underdiagnosed genetic disorder characterized by high low-density lipoprotein cholesterol levels and premature cardiovascular disease. Current sequencing methods to diagnose FH are expensive and time-consuming. In this study, we evaluated the accuracy of a low-cost, high-throughput genotyping array for diagnosing FH. METHODS: An Illumina Global Screening Array was customized to include probes for 636 variants, previously classified as FH-causing variants. First, its theoretical coverage was assessed in all FH variant carriers diagnosed through next-generation sequencing between 2016 and 2022 in the Netherlands (n=1772). Next, the performance of the array was validated in another sample of FH variant carriers previously identified in the Dutch FH cascade screening program (n=1268). RESULTS: The theoretical coverage of the array for FH-causing variants was 91.3%. Validation of the array was assessed in a sample of 1268 carriers of whom 1015 carried a variant in LDLR, 250 in APOB, and 3 in PCSK9. The overall sensitivity was 94.7% and increased to 98.2% after excluding participants with variants not included in the array design. Copy number variation analysis yielded a 89.4% sensitivity. In 18 carriers, the array identified a total of 19 additional FH-causing variants. Subsequent DNA analysis confirmed 5 of the additionally identified variants, yielding a false-positive result in 16 subjects (1.3%). CONCLUSIONS: The FH genotyping array is a promising tool for genetically diagnosing FH at low costs and has the potential to greatly increase accessibility to genetic testing for FH. Continuous customization of the array will further improve its performance.

Risk Assessment for Hip and Knee Osteoarthritis Using Polygenic Risk Scores.

OBJECTIVE: Polygenic risk scores (PRS) allow risk stratification using common single-nucleotide polymorphisms (SNPs), and clinical applications are currently explored for several diseases. This study was undertaken to assess the risk of hip and knee osteoarthritis (OA) using PRS. METHODS: We analyzed 12,732 individuals from a population-based cohort from the Rotterdam Study (n = 11,496), a clinical cohort (Cohort Hip and Cohort Knee [CHECK] study; n = 908), and a high-risk cohort of overweight women (Prevention of Knee OA in Overweight Females [PROOF] study; n = 328), for the association of the PRS with prevalence/incidence of radiographic OA, of clinical OA, and of total hip replacement (THR) or total knee replacement (TKR). The hip PRS and knee PRS contained 44 and 24 independent SNPs, respectively, and were derived from a recent genome-wide association study meta-analysis. Standardized PRS (with Z transformation) were used in all analyses. RESULTS: We found a stronger association of the PRS for clinically defined OA compared to radiographic OA phenotypes, and we observed the highest PRS risk stratification for TKR/THR. The odds ratio (OR) per SD was 1.3 for incident THR (95% confidence interval [95% CI] 1.1-1.5) and 1.6 (95% CI 1.3-1.9) for incident TKR in the Rotterdam Study. The knee PRS was associated with incident clinical knee OA in the CHECK study (OR 1.3 [95% CI 1.1-1.5]), but not for the PROOF study (OR 1.2 [95% CI 0.8-1.7]). The OR for OA increased gradually across the PRS distribution, up to 2.1 (95% CI 1.4-3.2) for individuals with the 10% highest PRS compared to the middle 50% of the PRS distribution. CONCLUSION: Our findings validated the association of PRS across OA definitions. Since OA is becoming frequent and primary prevention is not commonly applicable, PRS-based risk assessment could play a role in OA prevention. However, the utility of PRS is dependent on the setting. Further studies are needed to test the integration of genetic risk assessment in diverse health care settings.

Genetic variations of cholesteryl ester transfer protein and diet interactions in relation to lipid profiles and coronary heart disease: a systematic review.

Data on diet-genotype interactions in the prevention or treatment of dyslipidemia have increased remarkably. This systematic review aimed to assess nutrigenetic studies regarding the modulating effect of diet on cholesteryl ester transfer protein (CETP) polymorphisms in relation to metabolic traits. Data were collected through studies published between 2000 and SEP. 2016 using five electronic databases. The quality of eligible studies was assessed using a 12-item quality checklist, derived from the STrengthening the REporting of Genetic Association Studies (STREGA) statement. CETP variants that had associations with lipid profiles in previous studies were extracted for drawing of the linkage disequilibrium (LD) plot. Among CETP variants, the rs9989419 best represented this genome wide association signal across all populations, based on LD r2 estimates from 1000 genomes references. In the 23 found eligible studies (clinical trials and observational), the TaqIB and I405V polymorphisms were the two most intensively studied. Two studies reported the effect of interaction between rs3764261 and diet on lipid levels. Regarding the rs708272 (Taq1B), individuals with the B1 risk allele showed better responses to dietary interventions than those with B2B2 genotype, whereas with I405V, inconsistent results have been reported. Modest alcohol consumption was associated with decreased risk of coronary heart disease among B2 carriers of rs708272. It is concluded that variations in the CETP gene may modulate the effects of dietary components on metabolic traits. These results have been controversial, indicating complex polygenic factors in metabolic response to diet and lack of uniformity in the study conditions and designs.