Evidence-Based Assessment of Genes in Dilated Cardiomyopathy.

BACKGROUND: Each of the cardiomyopathies, classically categorized as hypertrophic cardiomyopathy, dilated cardiomyopathy (DCM), and arrhythmogenic right ventricular cardiomyopathy, has a signature genetic theme. Hypertrophic cardiomyopathy and arrhythmogenic right ventricular cardiomyopathy are largely understood as genetic diseases of sarcomere or desmosome proteins, respectively. In contrast, >250 genes spanning >10 gene ontologies have been implicated in DCM, representing a complex and diverse genetic architecture. To clarify this, a systematic curation of evidence to establish the relationship of genes with DCM was conducted. METHODS: An international panel with clinical and scientific expertise in DCM genetics evaluated evidence supporting monogenic relationships of genes with idiopathic DCM. The panel used the Clinical Genome Resource semiquantitative gene-disease clinical validity classification framework with modifications for DCM genetics to classify genes into categories on the basis of the strength of currently available evidence. Representation of DCM genes on clinically available genetic testing panels was evaluated. RESULTS: Fifty-one genes with human genetic evidence were curated. Twelve genes (23%) from 8 gene ontologies were classified as having definitive (BAG3, DES, FLNC, LMNA, MYH7, PLN, RBM20, SCN5A, TNNC1, TNNT2, TTN) or strong (DSP) evidence. Seven genes (14%; ACTC1, ACTN2, JPH2, NEXN, TNNI3, TPM1, VCL) including 2 additional ontologies were classified as moderate evidence; these genes are likely to emerge as strong or definitive with additional evidence. Of these 19 genes, 6 were similarly classified for hypertrophic cardiomyopathy and 3 for arrhythmogenic right ventricular cardiomyopathy. Of the remaining 32 genes (63%), 25 (49%) had limited evidence, 4 (8%) were disputed, 2 (4%) had no disease relationship, and 1 (2%) was supported by animal model data only. Of the 16 evaluated clinical genetic testing panels, most definitive genes were included, but panels also included numerous genes with minimal human evidence. CONCLUSIONS: In the curation of 51 genes, 19 had high evidence (12 definitive/strong, 7 moderate). It is notable that these 19 genes explain only a minority of cases, leaving the remainder of DCM genetic architecture incompletely addressed. Clinical genetic testing panels include most high-evidence genes; however, genes lacking robust evidence are also commonly included. We recommend that high-evidence DCM genes be used for clinical practice and that caution be exercised in the interpretation of variants in variable-evidence DCM genes.

The impact of early age at first childbirth on maternal and infant health.

The objective of this review was to assess whether early age at first childbirth is associated with increased risk of poor pregnancy outcomes. Early age at childbirth is variously defined in studies of its effect on maternal and infant health. In this systematic review, we limit analysis to studies of at least moderate quality that examine first births among young mothers, where young maternal age is defined as low gynaecological age (≤ 2 years since menarche) or as a chronological age ≤ 16 years at conception or delivery. We conduct meta-analyses for specific maternal or infant health outcomes when there are at least three moderate quality studies that define the exposure and outcome in a similar manner and provide odds ratios or risk ratios as their effect estimates. We conclude that the overall evidence of effect for very young maternal age (<15 years or <2 years post-menarche) on infant outcomes is moderate; that is, future studies are likely to refine the estimate of effect or precision but not to change the conclusion. Evidence points to an impact of young maternal age on low birthweight and preterm birth, which may mediate other infant outcomes such as neonatal mortality. The evidence that young maternal age increases risk for maternal anaemia is also fairly strong, although information on other nutritional outcomes and maternal morbidity/mortality is less clear. Many of the differences observed among older teenagers with respect to infant outcomes may be because of socio-economic or behavioural differences, although these may vary by country/setting. Future, high quality observational studies in low income settings are recommended in order to address the question of generalisability of evidence. In particular, studies in low income countries need to consider low gynaecological age, rather than simply chronological age, as an exposure. As well, country-specific studies should measure the minimum age at which childbearing for teens has similar associations with health as childbearing for adults. This 'tipping point' may vary by the underlying physical and nutritional health of girls and young women.