Citations

Aberrant connectivity is implicated in many neurological and psychiatric disorders, including Alzheimer’s disease and schizophrenia. However, other than a few disease-associated candidate genes, we know little about the degree to which genetics play a role in the brain networks; we know even less about specific genes that influence brain connections. Twin and family-based studies can generate estimates of overall genetic influences on a trait, but genome-wide association scans (GWASs) can screen the genome for specific variants influencing the brain or risk for disease. To identify the heritability of various brain connections, we scanned healthy young adult twins with high-field, high-angular resolution diffusion MRI. We adapted GWASs to screen the brain’s connectivity pattern, allowing us to discover genetic variants that affect the human brain’s wiring. The association of connectivity with the SPON1 variant at rs2618516 on chromosome 11 (11p15.2) reached connectome-wide, genome-wide significance after stringent statistical corrections were enforced, and it was replicated in an independent subsample. rs2618516 was shown to affect brain structure in an elderly population with varying degrees of dementia. Older people who carried the connectivity variant had significantly milder clinical dementia scores and lower risk of Alzheimer’s disease. As a posthoc analysis, we conducted GWASs on several organizational and topological network measures derived from the matrices to discover variants in and around genes associated with autism ( MACROD2 ), development ( NEDD4 ), and mental retardation ( UBE2A ) significantly associated with connectivity. Connectome-wide, genome-wide screening offers substantial promise to discover genes affecting brain connectivity and risk for brain diseases.

Background— Measurement of hospital quality has traditionally focused on processes of care and postprocedure outcomes. Appropriateness measures for percutaneous coronary intervention (PCI) assess quality as it relates to patient selection and the decision to perform PCI. The association between patient selection for PCI and processes of care and postprocedural outcomes is unknown. Methods and Results— We included 203 531 patients undergoing nonacute (elective) PCI from 779 hospitals participating in the National Cardiovascular Data Registry (NCDR) CathPCI Registry between July 2009 and April 2011. We examined the association between a hospital's proportion of nonacute PCIs categorized as inappropriate by the 2009 Appropriate Use Criteria (AUC) for Coronary Revascularization and in-hospital mortality, bleeding complications, and use of optimal guideline-directed medical therapy at discharge (ie, aspirin, thienopyridines, and statins). When categorized as hospital tertiles, the range of inappropriate PCI was 0.0% to 8.1% in the lowest tertile, 8.1% to 15.2% in the middle tertile, and 15.2% to 58.6% in the highest tertile. Compared with lowest-tertile hospitals, mortality was not significantly different at middle-tertile (adjusted odds ratio [OR], 0.93; 95% confidence interval [CI], 0.73–1.19) or highest-tertile hospitals (OR, 1.12; 95% CI, 0.88–1.43; P =0.35 for differences between tertiles). Similarly, risk-adjusted bleeding did not vary significantly (middle-tertile OR, 1.13; 95% CI, 1.02–1.16; highest-tertile OR, 1.02; 95% CI, 0.91–1.16; P =0.07 for differences between tertiles) nor did use of optimal medical therapy at discharge (85.3% versus 85.7% versus 85.2%; P =0.58). Conclusions— In a national cohort of nonacute PCIs, a hospital's proportion of inappropriate PCIs was not associated with in-hospital mortality, bleeding, or medical therapy at discharge. This suggests PCI appropriateness measures aspects of hospital PCI quality that are independent of how well the procedure is performed. Therefore, PCI appropriateness and postprocedural outcomes are both important metrics to inform PCI quality.