Bahareh Sedaghati-Khayat

Background: Genetic risk scores may be useful for analyzing risks for coronary artery disease (CAD). However, comparisons between restricted and genome‐wide scores have been underexplored, particularly for individuals at increased risk by one score but not the other. Here, we compared restricted polygenic risk scores with 181 high‐confidence genetic variants (PRS ₁₈₁ ) and genome‐wide risk scores that encompass 6.6 million single‐nucleotide polymorphisms (GRS _6.6M ). Methods: Data were from the RS (Rotterdam Study; n=11 001), MESA (Multi‐Ethnic Study of Atherosclerosis; n=2685), and the Sanford Health study (n=25 166). We analyzed score associations with CAD (prevalent and incident), age at onset, and lipid medication use. Combined use of both scores was also examined. Results: There were robust associations with CAD per SD of the scores for men (PRS ₁₈₁ : hazard ratio [HR], 1.19 [95% CI, 1.13–1.26]; GRS _6.6M : HR, 1.32 [95% CI, 1.26–1.39]) and women (PRS ₁₈₁ : HR, 1.24 [95% CI, 1.16–1.32]; GRS _6.6M : HR, 1.32 [95% CI, 1.25–1.40]). PRS ₁₈₁ was more strongly associated with early‐onset CAD in men (β=−0.93 [95% CI, −1.36 to −0.50]) and women (β=−0.76 [95% CI, −1.31 to −0.21]). Both scores correlated with lipid medication use, but the scores were also associated with CAD among nonusers. Individuals at high risk by both scores had the highest risk and the earliest age at onset. Conclusions: PRS ₁₈₁ and GRS _6.6M appear to identify different subsets of individuals. Use of both scores together may provide better association information on CAD risk and age at onset than each score alone.

Background: Genetic risk scores hold potential for predicting depression in the general population. These scores must be validated for their associations with relevant characteristics of depression-related phenotypes, such as severity. We validated a genome-wide risk score (GRS) and a restricted polygenic risk score (PRS) for depression based on a meta-analysis of three genome-wide association studies and assessed their associations with depression in three subcohorts of middle-aged and older adults from the Dutch population-based Rotterdam Study. Methods: Of participants with genotype data, 9,198 had longitudinally measured data (mean follow-up: 11.3 years) on three depression-related phenotypes (depressive symptoms, depressive syndrome, and major depressive disorder). Generalized linear models estimated the associations of standardized GRS and PRS with depression phenotypes per subcohort and were then meta-analyzed. One unit of the GRS/PRS represents 1 standard deviation, following z-transformation per cohort. Results: A one unit higher GRS and PRS were associated with any longitudinally measured depression phenotype (odds ratio (OR)_GRS = 1.20 [1.15–1.26], OR_PRS = 1.10 [1.05–1.16]). Effect sizes were highest for episodes of major depressive disorder: for individuals with the 10% highest GRS and PRS, the ORs were 1.99 [1.53–2.57] and 1.51 [1.13–1.99], respectively, compared to the middle 50% of the distribution. Conclusions: The GRS and PRS for depression showed modest associations across multiple depression-related phenotypes in a population-based setting. The strength of associations generally increased with the severity of the phenotype. While effect sizes were generally larger for GRS compared to PRS, the difference was mostly not statistically significant.

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.

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.

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.

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.

High blood pressure is the heritable risk factor for cardiovascular and kidney diseases. Genome-wide association studies(GWAS) on blood pressure traits increase our understanding of its underlying genetic basis. However, a large proportion of GWAS was conducted in Europeans, and some roadblocks deprive other populations to benefit from their results. Iranians population with a high degree of genomic specificity has not been represented in international databases to date, so to fill the gap, we explored the effects of 652,919 genomic variants on Systolic Blood Pressure (SBP), Diastolic Blood Pressure (DBP), and Hypertension (HTN) in 7694 Iranian adults aged 18 and over from Tehran Cardiometabolic Genetic Study (TCGS). We identified consistent signals on ZBED9 associated with HTN in the genome-wide borderline threshold after adjusting for different sets of environmental predictors. Moreover, strong signals on ABHD17C and suggestive signals on FBN1 were detected for DBP and SBP, respectively, while these signals were not consistent in different GWA analysis. Our finding on ZBED9 was confirmed for all BP traits by linkage analysis in an independent sample. We found significant associations with similar direction of effects and allele frequency of genetic variants on ZBED9 with DBP (genome-wide threshold) and HTN (nominal threshold) in GWAS summary data of UK Biobank. Although there is no strong evidence to support the function of ZBED9 in blood pressure regulation, it provides new insight into the pleiotropic effects of hypertension and other cardiovascular diseases.