Jabbari, Reza

Importance Sudden infant death syndrome (SIDS) remains a leading cause of death during the first year of life. The etiology of SIDS is complex and remains largely unknown. Objective To evaluate whether siblings of children who died of SIDS have a higher risk of SIDS compared with the general pediatric population. Design, Setting, and Participants This register-based cohort study used Danish nationwide registers. Participants were all infants (<1 year) in Denmark between January 1, 1978, and December 31, 2016, including siblings of children who died of SIDS. Siblings were followed up from the index cases’ date of SIDS, date of birth, or immigration, whichever came first, and until age 1 year, emigration, developing SIDS, death, or study end. The median (IQR) follow-up was 1 (1-1) year. Data analysis was conducted from January 2017 to October 2022. Main Outcomes and Measures Standardized incidence ratios (SIRs) of SIDS were calculated with Poisson regression models relative to the general population. Results In a population of 2 666 834 consecutive births (1 395 199 [52%] male), 1540 infants died of SIDS (median [IQR] age at SIDS, 3 [2-4] months) during a 39-year study period. A total of 2384 younger siblings (cases) to index cases (first sibling with SIDS) were identified. A higher rate of SIDS was observed among siblings compared with the general population, with SIRs of 4.27 (95% CI, 2.13-8.53) after adjustment for sex, age, and calendar year and of 3.50 (95% CI, 1.75-7.01) after further adjustment for mother’s age (<29 years vs ≥29 years) and education (high school vs after high school). Conclusions and Relevance In this nationwide study, having a sibling who died of SIDS was associated with a 4-fold higher risk of SIDS compared with the general population. Shared genetic and/or environmental factors may contribute to the observed clustering of SIDS. The family history of SIDS should be considered when assessing SIDS risk in clinical settings. A multidisciplinary genetic evaluation of families with SIDS could provide additional evidence.

Background: Long QT syndrome (LQTS) is a rare genetic disorder and a major preventable cause of sudden cardiac death in the young. A causal rare genetic variant with large effect size is identified in up to 80% of probands (genotype positive) and cascade family screening shows incomplete penetrance of genetic variants. Furthermore, a proportion of cases meeting diagnostic criteria for LQTS remain genetically elusive despite genetic testing of established genes (genotype negative). These observations raise the possibility that common genetic variants with small effect size contribute to the clinical picture of LQTS. This study aimed to characterize and quantify the contribution of common genetic variation to LQTS disease susceptibility. Methods: We conducted genome-wide association studies followed by transethnic meta-analysis in 1656 unrelated patients with LQTS of European or Japanese ancestry and 9890 controls to identify susceptibility single nucleotide polymorphisms. We estimated the common variant heritability of LQTS and tested the genetic correlation between LQTS susceptibility and other cardiac traits. Furthermore, we tested the aggregate effect of the 68 single nucleotide polymorphisms previously associated with the QT-interval in the general population using a polygenic risk score. Results: Genome-wide association analysis identified 3 loci associated with LQTS at genome-wide statistical significance ( P <5×10 −8 ) near NOS1AP , KCNQ1 , and KLF12 , and 1 missense variant in KCNE1 (p.Asp85Asn) at the suggestive threshold ( P <10 −6 ). Heritability analyses showed that ≈15% of variance in overall LQTS susceptibility was attributable to common genetic variation ( h2SNP 0.148; standard error 0.019). LQTS susceptibility showed a strong genome-wide genetic correlation with the QT-interval in the general population (r g =0.40; P =3.2×10 −3 ). The polygenic risk score comprising common variants previously associated with the QT-interval in the general population was greater in LQTS cases compared with controls ( P <10−13), and it is notable that, among patients with LQTS, this polygenic risk score was greater in patients who were genotype negative compared with those who were genotype positive ( P <0.005). Conclusions: This work establishes an important role for common genetic variation in susceptibility to LQTS. We demonstrate overlap between genetic control of the QT-interval in the general population and genetic factors contributing to LQTS susceptibility. Using polygenic risk score analyses aggregating common genetic variants that modulate the QT-interval in the general population, we provide evidence for a polygenic architecture in genotype negative LQTS.