38 research outputs found

    Health outcomes in offspring born to survivors of childhood cancers following assisted reproductive technologies

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    Purpose: An increasing number of childhood cancer survivors are using assisted reproductive technologies (ART) to overcome treatment-related fertility impairment. We report perinatal and health outcomes of offspring born to survivors following ART. Methods: The FeCt Multicenter Offspring Study surveyed the health of offspring of childhood cancer survivors. Health outcomes in offspring born to survivors following ART (n = 57, 4.6%) or after spontaneous conception (n = 1182) were assessed in the German cohort (n = 1239) using bivariate analysis. Findings were put into the context of the general German population by health outcome assessment in 1:1 matched-pair analysis (n = 2478). Results: Nearly twice the survivors used ART compared with numbers reported for the German general population (4.6% vs. 2.6%). Successful pregnancies were achieved after a median of two cycles, mainly using non-cryopreserved oocytes/sperm. Multiple sibling births (p < 0.001, 28.1% vs. 3.0%) and low birth weight (p = 0.008; OR = 2.659, 95% CI = 1.258-5.621) occurred significantly more often in offspring born to survivors who utilized ART than spontaneously conceived children, whereas similar percentages were born preterm or too small for their gestational age. ART did not increase the prevalence of childhood cancer or congenital malformations in offspring born to survivors. Conclusion: ART use by childhood cancer survivors was successful with both fresh and cryopreserved oocytes/sperm, and did not influence perinatal health or health outcomes when known confounders were taken into account. Implications for cancer survivors: Oncofertility is an important component of patient care. Our study implicates that the utilization of ART by adult survivors of childhood cancer does not put offspring at additional risk for adverse perinatal or health outcomes

    Genetic and lifestyle risk factors for MRI-defined brain infarcts in a population-based setting.

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    OBJECTIVE: To explore genetic and lifestyle risk factors of MRI-defined brain infarcts (BI) in large population-based cohorts. METHODS: We performed meta-analyses of genome-wide association studies (GWAS) and examined associations of vascular risk factors and their genetic risk scores (GRS) with MRI-defined BI and a subset of BI, namely, small subcortical BI (SSBI), in 18 population-based cohorts (n = 20,949) from 5 ethnicities (3,726 with BI, 2,021 with SSBI). Top loci were followed up in 7 population-based cohorts (n = 6,862; 1,483 with BI, 630 with SBBI), and we tested associations with related phenotypes including ischemic stroke and pathologically defined BI. RESULTS: The mean prevalence was 17.7% for BI and 10.5% for SSBI, steeply rising after age 65. Two loci showed genome-wide significant association with BI: FBN2, p = 1.77 × 10-8; and LINC00539/ZDHHC20, p = 5.82 × 10-9. Both have been associated with blood pressure (BP)-related phenotypes, but did not replicate in the smaller follow-up sample or show associations with related phenotypes. Age- and sex-adjusted associations with BI and SSBI were observed for BP traits (p value for BI, p [BI] = 9.38 × 10-25; p [SSBI] = 5.23 × 10-14 for hypertension), smoking (p [BI] = 4.4 × 10-10; p [SSBI] = 1.2 × 10-4), diabetes (p [BI] = 1.7 × 10-8; p [SSBI] = 2.8 × 10-3), previous cardiovascular disease (p [BI] = 1.0 × 10-18; p [SSBI] = 2.3 × 10-7), stroke (p [BI] = 3.9 × 10-69; p [SSBI] = 3.2 × 10-24), and MRI-defined white matter hyperintensity burden (p [BI] = 1.43 × 10-157; p [SSBI] = 3.16 × 10-106), but not with body mass index or cholesterol. GRS of BP traits were associated with BI and SSBI (p ≤ 0.0022), without indication of directional pleiotropy. CONCLUSION: In this multiethnic GWAS meta-analysis, including over 20,000 population-based participants, we identified genetic risk loci for BI requiring validation once additional large datasets become available. High BP, including genetically determined, was the most significant modifiable, causal risk factor for BI
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