Hereditary ataxia, or motor incoordination, affects approximately 150,000 Americans and hundreds of thousands of individuals worldwide with onset from as early as mid-childhood. Affected individuals exhibit dysarthria, dysmetria, action tremor, and diadochokinesia. In this review, we consider an array of computational studies derived from experimental observations relevant to human neuropathology. A survey of related studies illustrates the impact of integrating clinical evidence with data from mouse models and computational simulations. Results from these studies may help explain findings in mice, and after extensive laboratory study, may ultimately be translated to ataxic individuals. This inquiry lays a foundation for using computation to understand neurobiochemical and electrophysiological pathophysiology of spinocerebellar ataxias and may contribute to development of therapeutics. The interdisciplinary analysis suggests that computational neurobiology can be an important tool for translational neurology.

Background Whether knowledge of genetic risk for coronary heart disease (CHD) affects health-related outcomes is unknown. We investigated whether incorporating a genetic risk score (GRS) in CHD risk estimates lowers low-density lipoprotein cholesterol (LDL-C) levels. Methods and Results Participants (n=203, 45–65 years old, at intermediate risk for CHD, and not on statins) were randomized to receive their 10-year probability of CHD based either on a conventional risk score (CRS) or CRS + GRS (+GRS). Participants in the +GRS group were stratified as having high (+H-GRS) or average/low (+L-GRS) GRS. Risk was disclosed by a genetic counselor followed by shared decision-making regarding statin therapy with a physician. We compared the primary endpoint of LDL-C levels at 6 months and assessed whether any differences were due to changes in dietary fat intake, physical activity levels or statin use. Participants (mean age 59.4±5 years, 48% men, mean 10-year CHD risk 8.5±4.1%) were allocated to receive either CRS (n=100) or +GRS (n=103). At the end of the study period, the +GRS group had a lower LDL-C than the CRS group (96.5±32.7 vs. 105.9±33.3 mg/dL; P=0.04). +H-GRS participants had lower LDL-C levels (92.3±32.9 mg/dL) than CRS participants (P=0.02) but not +L-GRS participants (100.9±32.2 mg/dL; P=0.18). Statins were initiated more often in the +GRS group than in the CRS group (39% vs. 22%, P<0.01). No significant differences in dietary fat intake and physical activity levels were noted. Conclusions Disclosure of CHD risk estimates that incorporated genetic risk information led to lower LDL-C levels than disclosure of CHD risk based on conventional risk factors alone. Clinical Trial Registration Information ClinicalTrials.gov. Identifier: NCT01936675.

With the advent of novel cancer therapeutics and improved screening, more patients are surviving a cancer diagnosis or living longer with advanced disease. Many of these treatments have associated cardiovascular toxicities that can manifest in both an acute and a delayed fashion. Arrhythmias are an increasingly identified complication with unique management challenges in the cancer population. The purpose of this scientific statement is to summarize the current state of knowledge regarding arrhythmia identification and treatment in patients with cancer. Atrial tachyarrhythmias, particularly atrial fibrillation, are most common, but ventricular arrhythmias, including those related to treatment-induced QT prolongation, and bradyarrhythmias can also occur. Despite increased recognition, dedicated prospective studies evaluating true incidence are lacking. Moreover, few studies have addressed appropriate prevention and treatment strategies. As such, this scientific statement serves to mobilize the cardio-oncology, electrophysiology, and oncology communities to develop clinical and scientific collaborations that will improve the care of patients with cancer who have arrhythmias.