OBJECTIVE: To support doctors in counselling women with genetic predisposition for breast or gynecologic cancers on endocrine interventions.
METHODS: Evidence on the safety of endocrine interventions for fertility treatment, contraception, hormone replacement therapy after risk-reducing salpingo-oophorectomy (RRSO) or treatment of symptoms during peri- and postmenopause was analysed for carriers of probably pathogenic and pathogenic variants in BRCA1 or BRCA2 (BRCA1/2-pV), in other breast and ovarian cancer genes and the Lynch Syndrome. Cancer risks were compared with data on risks for the general population.
RESULTS: Data on risk modulation of endocrine interventions in women with genetic predisposition is limited. Ovarian hyperstimulation for fertility treatment may be performed. Oral contraceptives should not be used to reduce ovarian cancer risk in BRCA1/2-pV carriers. Premenopausal BRCA1/2-pV carriers and carriers of pV in Lynch Syndrome genes should be offered hormone replacement therapy (HRT) after RRSO, to prevent diseases caused by estrogen deficiency.
CONCLUSIONS: Effect direction and strength of risk modulation by endocrine interventions is similar to the general population. Participation of individuals at risk in prospective registries is recommended.

OBJECTIVE: Emerging research has investigated the potential impact of several modifiable risk factors on the risks of rheumatoid arthritis (RA), but the findings did not yield consistent results. This study aimed to comprehensively explore the genetic causality between modifiable risk factors and the susceptibility of RA risk using the Mendelian randomization (MR) approach.
METHODS: Genetic instruments for modifiable risk factors were selected from several genome-wide association studies at the genome-wide significance level (p < 5 × 10-8), respectively. Summary-level data for RA were sourced from a comprehensive meta-analysis. The causal estimates linking modifiable risk factors to RA risk were assessed using MR analysis with inverse variance weighting (IVW), MR-Egger, weighted, and weighted median methods.
RESULTS: After Bonferroni correction for multiple tests, we found the presence of causality between educational attainment and RA, where there were protective effects of educational attainment (college completion) (odds ratio [OR] = 0.50, 95% CI = 0.36, 0.69, p = 2.87E-05) and educational attainment (years of education) (OR = 0.93, 95% CI = 0.90, 0.96, p = 4.18E-06) on the lower RA risks. Nevertheless, smoking initiation was observed to be associated with increased RA risks (OR = 1.27, 95% CI = 1.09, 1.47, p = .002). Moreover, there was no indication of horizontal pleiotropy of genetic variants during causal inference between modifiable risk factors and RA.
CONCLUSIONS: Our study reveals the genetic causal impacts of educational attainment and smoking on RA risks, suggesting that the early monitoring and recognition of modifiable risk factors would be beneficial for the preventive counseling/treatment strategies for RA.

BACKGROUND: Personality disorders (PD) are characterized by socially dysfunctional behavioral patterns that affect patients and show higher incidence rates within families. Substance abuse disorders (SAD) are exemplified by extensive and prolonged use of substances, including alcohol, nicotine, or illegal drugs. Genetic predisposition for both PD and SAD has been reported to involve gene variants regulating dopaminergic pathways. Yet, discrepancy among reported results necessitates further elucidation of potential hereditary-related risk factors. Because both disorders impose a societal burden, knowledge on the impact of certain genetic backgrounds on these diseases could help develop evidence-based strategies for efficacious treatment approaches.
METHODS: In the present study a systematic review was performed, and the association between dopamine transporter gene polymorphism (SLC6A3), particularly rs28363170 entailing a 40-bp variable number tandem repeat, and PD as well as SAD was investigated recruiting meta-analysis approach.
RESULTS: Initial literature search for PD yielded 1577, from which nine fulfilled eligibility criteria to be used in a meta-analysis including 729 cases and 2113 controls. From the 934 studies retrieved for SAD, only 29 articles with 5221 cases and 4822 controls were used for meta-analysis. A statistically significant association was seen between rs28363170 (for the 9-repeat allele) and PD in European populations according to the co-dominant mode of inheritance. For SAD no statistically significant correlation under any mode of inheritance was observed. There was no indication of time-trend phenomena.
CONCLUSIONS: Our findings demonstrate the association of SLC6A3 gene polymorphism with PD, thus underling the need to understand neurobiological mechanisms inherent to the above disorders to guide treatment strategies under the perspective of personalized medicine.

UNASSIGNED: The causality of autoimmune diseases with frailty has not been firmly established. We conducted this Mendelian randomization (MR) study to unveil the causal associations between autoimmune diseases with frailty.
UNASSIGNED: A MR analyses were performed to explore the relationships between autoimmune disease and frailty, using summary genome-wide association statistics.
UNASSIGNED: Through a comprehensive and meticulous screening process, we incorporated 46, 7, 12, 20, 5, and 53 single nucleotide polymorphisms (SNPs) as instrumental variables (IVs) for hypothyroidism, hyperthyroidism, rheumatoid arthritis (RA), type 1 diabetes (T1D), multiple sclerosis (MS), and overall autoimmune disease, respectively. Our analysis revealed that hypothyroidism (OR = 1.023, 95% CI: 1.008-1.038, p = 0.0015), hyperthyroidism (OR = 1.024, 95% CI: 1.004-1.045, p = 0.0163), RA (OR = 1.031, 95% CI: 1.011-1.052, p = 0.0017), T1D (OR = 1.011, 95% CI: 1.004-1.017, p = 0.0012), and overall autoimmune disease (OR = 1.044, 95% CI: 1.028-1.061, p = 5.32*10^-8) exhibited a positive causal effect on frailty. Conversely, there may be a negative causal association between MS (OR = 0.984, 95% CI: 0.977-0.992, p = 4.87*10^-5) and frailty. Cochran\'s Q test indicated heterogeneity among IVs derived from hypothyroidism, hyperthyroidism, T1D, and overall autoimmune diseases. The MR-Egger regression analyzes revealed an absence of horizontal pleiotropy in any of the conducted analyses.
UNASSIGNED: This study elucidates that hypothyroidism, hyperthyroidism, RA, T1D, and overall autoimmune disease were linked to an elevated risk of frailty. Conversely, MS appears to be associated with a potential decrease in the risk of frailty.

Background: The role of the common FTO gene variant rs9939609 in obesity has been well established, and the FTO gene has a strong association with T2DM. Objective: To investigate the association of FTO gene variant rs9939609 with obesity-related parameters in T2DM and CVD patients. Materials and Methods: In this cross-sectional study, 280 subjects of either sex aged 45.10 ± 9.6 years were randomly divided into four groups, that is, T2DM, T2DM with CVD, nondiabetic with CVD disease, and normal control. These samples were genotyped by ARMS-PCR. The FTO gene association with obesity-related parameters in T2DM and CVD patients was analyzed by SPSS 22. Results: The TT genotype was the most common genotype (46.80%) in our study groups. The minor allele frequency (MAF) was significantly higher in T2DM patients (0.39 vs. 0.28), T2DM patients with CVD (0.43 vs. 0.28), and nondiabetic patients with CVD (0.35 vs. 0.28) as compared to control with p < 0.005. Carriers of the AA genotype of the FTO gene rs9939609 were significantly associated with increased BMI, WC, HbA1C, SBP, DBP, and TGs and lowered HDL cholesterol as compared to the TA and TT genotypes in T2DM and CVD patients with p < 0.005. The FTO gene variant rs9939609 showed a significant association with T2DM and CVD. The AA genotype odds ratio (OR) in T2DM was 1.48 (1.06-2.32), p = 0.006, and in CVD, it was 1.56 (1.04-2.4), p = 0.003. Conclusion: The FTO gene variant rs9939609 has a strong association with T2DM and CVD. The AA genotype of FTO gene variants rs9939609 showed a strong association with most of the risk factors of CVD and T2DM.

Single nucleotide variants (SNVs) can exert substantial and extremely variable impacts on various cellular functions, making accurate predictions of their consequences challenging, albeit crucial especially in clinical settings such as in oncology. Laboratory-based experimental methods for assessing these effects are time-consuming and often impractical, highlighting the importance of in-silico tools for variant impact prediction. However, the performance metrics of currently available tools on breast cancer missense variants from benchmarking databases have not been thoroughly investigated, creating a knowledge gap in the accurate prediction of pathogenicity. In this study, the benchmarking datasets ClinVar and HGMD were used to evaluate 21 Artificial Intelligence (AI)-derived in-silico tools. Missense variants in breast cancer genes were extracted from ClinVar and HGMD professional v2023.1. The HGMD dataset focused on pathogenic variants only, to ensure balance, benign variants for the same genes were included from the ClinVar database. Interestingly, our analysis of both datasets revealed variants across genes with varying penetrance levels like low and moderate in addition to high, reinforcing the value of disease-specific tools. The top-performing tools on ClinVar dataset identified were MutPred (Accuracy = 0.73), Meta-RNN (Accuracy = 0.72), ClinPred (Accuracy = 0.71), Meta-SVM, REVEL, and Fathmm-XF (Accuracy = 0.70). While on HGMD dataset they were ClinPred (Accuracy = 0.72), MetaRNN (Accuracy = 0.71), CADD (Accuracy = 0.69), Fathmm-MKL (Accuracy = 0.68), and Fathmm-XF (Accuracy = 0.67). These findings offer clinicians and researchers valuable insights for selecting, improving, and developing effective in-silico tools for breast cancer pathogenicity prediction. Bridging this knowledge gap contributes to advancing precision medicine and enhancing diagnostic and therapeutic approaches for breast cancer patients with potential implications for other conditions.

This study aims to assess the effect of familial structures on the still-missing heritability estimate and prediction accuracy of Type 2 Diabetes (T2D) using pedigree estimated risk values (ERV) and genomic ERV. We used 11,818 individuals (T2D cases: 2,210) with genotype (649,932 SNPs) and pedigree information from the ongoing periodic cohort study of the Iranian population project. We considered three different familial structure scenarios, including (i) all families, (ii) all families with ≥ 1 generation, and (iii) families with ≥ 1 generation in which both case and control individuals are presented. Comprehensive simulation strategies were implemented to quantify the difference between estimates of [Formula: see text] and [Formula: see text]. A proportion of still-missing heritability in T2D could be explained by overestimation of pedigree-based heritability due to the presence of families with individuals having only one of the two disease statuses. Our research findings underscore the significance of including families with only case/control individuals in cohort studies. The presence of such family structures (as observed in scenarios i and ii) contributes to a more accurate estimation of disease heritability, addressing the underestimation that was previously overlooked in prior research. However, when predicting disease risk, the absence of these families (as seen in scenario iii) can yield the highest prediction accuracy and the strongest correlation with Polygenic Risk Scores. Our findings represent the first evidence of the important contribution of familial structure for heritability estimations and genomic prediction studies in T2D.

BACKGROUND: Drugs targeting disease causal genes are more likely to succeed for that disease. However, complex disease causal genes are not always clear. In contrast, Mendelian disease causal genes are well-known and druggable. Here, we seek an approach to exploit the well characterized biology of Mendelian diseases for complex disease drug discovery, by exploiting evidence of pathogenic processes shared between monogenic and complex disease. One way to find shared disease etiology is clinical association: some Mendelian diseases are known to predispose patients to specific complex diseases (comorbidity). Previous studies link this comorbidity to pleiotropic effects of the Mendelian disease causal genes on the complex disease.
METHODS: In previous work studying incidence of 90 Mendelian and 65 complex diseases, we found 2,908 pairs of clinically associated (comorbid) diseases. Using this clinical signal, we can match each complex disease to a set of Mendelian disease causal genes. We hypothesize that the drugs targeting these genes are potential candidate drugs for the complex disease. We evaluate our candidate drugs using information of current drug indications or investigations.
RESULTS: Our analysis shows that the candidate drugs are enriched among currently investigated or indicated drugs for the relevant complex diseases (odds ratio = 1.84, p = 5.98e-22). Additionally, the candidate drugs are more likely to be in advanced stages of the drug development pipeline. We also present an approach to prioritize Mendelian diseases with particular promise for drug repurposing. Finally, we find that the combination of comorbidity and genetic similarity for a Mendelian disease and cancer pair leads to recommendation of candidate drugs that are enriched for those investigated or indicated.
CONCLUSIONS: Our findings suggest a novel way to take advantage of the rich knowledge about Mendelian disease biology to improve treatment of complex diseases.

BACKGROUND: In this study, we explored the impact of hypothyroidism and thyroid hormone replacement therapy on the risk of developing cardiovascular diseases, including myocardial infarction, heart failure, and cardiac death, via Mendelian randomization analysis.
METHODS: Genetic instrumental variables related to hypothyroidism, levothyroxine treatment (refer to Participants were taking the medication levothyroxine sodium) and adverse cardiovascular events were obtained from a large publicly available genome-wide association study. Two-sample Mendelian randomization analysis was performed via inverse-variance weighting as the primary method. To ensure the reliability of our findings, we performed MR‒Egger regression, Cochran\'s Q statistic, and leave-one-out analysis. Additionally, multivariable Mendelian randomization was employed to regulate confounding factors, including systolic blood pressure (SBP), diastolic blood pressure (DBP), body mass index (BMI), diabetes, cholesterol, low-density lipoprotein (LDL), triglycerides and metformin. A mediation analysis was conducted to assess the mediating effects on the association between exposure and outcome by treating atrial fibrillation and stroke as mediator variables of levothyroxine treatment and bradycardia as mediator variables of hypothyroidism.
RESULTS: Genetically predicted hypothyroidism and levothyroxine treatment were significantly associated with the risk of experiencing myocardial infarction [levothyroxine: odds ratio (OR) 3.75, 95% confidence interval (CI): 1.80-7.80; hypothyroidism: OR: 15.11, 95% CI: 2.93-77.88]. Levothyroxine treatment was also significantly related to the risk of experiencing heart failure (OR: 2.16, 95% CI: 1.21-3.88). However, no associations were detected between hypothyroidism and the risk of experiencing heart failure or between hypothyroidism or levothyroxine treatment and the risk of experiencing cardiac death. After adjusting for confounding factors, the results remained stable. Additionally, mediation analysis indicated that atrial fibrillation and stroke may serve as potential mediators in the relationships between levothyroxine treatment and the risk of experiencing heart failure or myocardial infarction.
CONCLUSIONS: The results of our study suggest a positive association between hypothyroidism and myocardial infarction and highlight the potential effects of levothyroxine treatment, the main thyroid hormone replacement therapy approach, on increasing the risk of experiencing myocardial infarction and heart failure.

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a special kind of chronic interstitial lung disease with insidious onset. Previous studies have revealed that mutations in ZCCHC8 may lead to IPF. The aim of this study is to explore the ZCCHC8 mutations in Chinese IPF patients.
METHODS: Here, we enrolled 124 patients with interstitial lung disease from 2017 to 2023 in our hospital. Whole exome sequencing and Sanger sequencing were employed to explore the genetic lesions of these patients.
RESULTS: Among these 124 patients, a novel mutation (NM_017612: c.1228 C > G/p.P410A) of Zinc Finger CCHC-Type Containing 8 (ZCCHC8)was identified in a family with IPF and chronic obstructive lung disease. As a component of the nuclear exosome-targeting complex that regulates the turnover of human telomerase RNA, ZCCHC8 mutations have been reported may lead to IPF in European population and American population. Functional study confirmed that the novel mutation can disrupt the nucleocytoplasmic localization of ZCCHC8, which further decreased the expression of DKC1 and RTEL1, and finally reduced the length of telomere and led to IPF and related disorders.
CONCLUSIONS: We may first report the ZCCHC8 mutation in Asian population with IPF. Our study broadens the mutation, phenotype, and population spectrum of ZCCHC8 deficiency.