Sherry Ann Brown

Computational neurobiology is a useful tool in translational neurology: the example of ataxia

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.

Systems biology approaches to adverse drug effects: the example of cardio-oncology

Increased awareness of the cardiovascular toxic effects of chemotherapy has led to the emergence of cardio-oncology (or onco-cardiology), which focuses on screening, monitoring and treatment of patients with cardiovascular dysfunctions resulting from chemotherapy. Anthracyclines, such as doxorubicin, and HER2 inhibitors, such as trastuzumab, both have cardiotoxic effects. The biological rationale, mechanisms of action and cardiotoxicity profiles of these two classes of drugs, however, are completely different, suggesting that cardiotoxic effects can occur in a range of different ways. Advances in genomics and proteomics have implicated several genomic variants and biological pathways that can influence the susceptibility to cardiotoxicity from these, and other drugs. Established pathways include multidrug resistance proteins, energy utilization pathways, oxidative stress, cytoskeletal regulation and apoptosis. Gene-expression profiles that have revealed perturbed pathways have vastly increased our knowledge of the complex processes involved in crosstalk between tumours and cardiac function. Utilization of mathematical and computational modelling can complement pharmacogenomics and improve individual patient outcomes. Such endeavours should enable identification of variations in cardiotoxicity, particularly in those patients who are at risk of not recovering, even with the institution of cardioprotective therapy. The application of systems biology holds substantial potential to advance our understanding of chemotherapy-induced cardiotoxicity.

Quadrilateral Space Syndrome: The Mayo Clinic Experience With a New Classification System and Case Series

Quadrilateral space syndrome (QSS) arises from compression or mechanical injury to the axillary nerve or the posterior circumflex humeral artery (PCHA) as they pass through the quadrilateral space (QS). Quadrilateral space syndrome is an uncommon cause of paresthesia and an underdiagnosed cause of digital ischemia in overhead athletes. Quadrilateral space syndrome can present with neurogenic symptoms (pain and weakness) secondary to axillary nerve compression. In addition, repeated abduction and external rotation of the arm is felt to lead to injury of the PCHA within the QSS. This often results in PCHA thrombosis and aneurysm formation, with distal emboli. Because of relative infrequency, QSS is rarely diagnosed on evaluation of athletes with such symptoms. We report on 9 patients who presented at Mayo Clinic with QSS. Differential diagnosis, a new classification system, and the management of QSS are discussed, with a comprehensive literature review. The following search terms were used on PubMed: axillary nerve, posterior circumflex humeral artery, quadrilateral space, and quadrangular space. Articles were selected if they described patients with symptoms from axillary nerve entrapment or PCHA thrombosis, or if related screening or imaging methods were assessed. References available within the obtained articles were also pursued. There was no date or language restriction for article inclusion; 5 studies in languages besides English were reported in German, French, Spanish, Turkish, and Chinese.

Incorporating a Genetic Risk Score into Coronary Heart Disease Risk Estimates: Effect on LDL Cholesterol Levels (the MIGENES Clinical Trial)

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 of age, at intermediate risk for CHD, and not on statins) were randomly assigned 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 or average/low GRS. Risk was disclosed by a genetic counselor followed by shared decision making regarding statin therapy with a physician. We compared the primary end point of LDL-C levels at 6 months and assessed whether any differences were attributable 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 versus 105.9±33.3 mg/dL; P=0.04). Participants with high GRS had lower LDL-C levels (92.3±32.9 mg/dL) than CRS participants (P=0.02) but not participants with low GRS (100.9±32.2 mg/dL; P=0.18). Statins were initiated more often in the +GRS group than in the CRS group (39% versus 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— URL: http://www.clinicaltrials.gov. Unique identifier: NCT01936675.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.nnMethods and Results— Participants (n=203, 45–65 years of age, at intermediate risk for CHD, and not on statins) were randomly assigned 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 or average/low GRS. Risk was disclosed by a genetic counselor followed by shared decision making regarding statin therapy with a physician. We compared the primary end point of LDL-C levels at 6 months and assessed whether any differences were attributable 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 versus 105.9±33.3 mg/dL; P =0.04). Participants with high GRS had lower LDL-C levels (92.3±32.9 mg/dL) than CRS participants ( P =0.02) but not participants with low GRS (100.9±32.2 mg/dL; P =0.18). Statins were initiated more often in the +GRS group than in the CRS group (39% versus 22%, P <0.01). No significant differences in dietary fat intake and physical activity levels were noted.nnConclusions— 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.nnClinical Trial Registration— URL: . Unique identifier: [NCT01936675][1].nn# CLINICAL PERSPECTIVE {#article-title-33}nn [1]: /lookup/external-ref?link_type=CLINTRIALGOV&access_num=NCT01936675&atom=%2Fcirculationaha%2F133%2F12%2F1181.atom

Pharmacogenomic Impact of CYP2C19 Variation on Clopidogrel Therapy in Precision Cardiovascular Medicine

Variability in response to antiplatelet therapy can be explained in part by pharmacogenomics, particularly of the CYP450 enzyme encoded by CYP2C19. Loss-of-function and gain-of-function variants help explain these interindividual differences. Individuals may carry multiple variants, with linkage disequilibrium noted among some alleles. In the current pharmacogenomics era, genomic variation in CYP2C19 has led to the definition of pharmacokinetic phenotypes for response to antiplatelet therapy, in particular, clopidogrel. Individuals may be classified as poor, intermediate, extensive, or ultrarapid metabolizers, based on whether they carry wild type or polymorphic CYP2C19 alleles. Variant alleles differentially impact platelet reactivity, concentration of plasma clopidogrel metabolites, and clinical outcomes. Interestingly, response to clopidogrel appears to be modulated by additional factors, such as sociodemographic characteristics, risk factors for ischemic heart disease, and drug-drug interactions. Furthermore, systems medicine studies suggest that a broader approach may be required to adequately assess, predict, preempt, and manage variation in antiplatelet response. Transcriptomics, epigenomics, exposomics, miRNAomics, proteomics, metabolomics, microbiomics, and mathematical, computational, and molecular modeling should be integrated with pharmacogenomics for enhanced prediction and individualized care. In this review of pharmacogenomic variation of CYP450, a systems medicine approach is described for tailoring antiplatelet therapy in clinical practice of precision cardiovascular medicine.

Shared decision-making following disclosure of coronary heart disease genetic risk: results from a randomized clinical trial

Whether disclosure of genetic risk for coronary heart disease (CHD) influences shared decision-making (SDM) regarding use of statins to reduce CHD risk is unknown. We randomized 207 patients, age 45–65u2005years, at intermediate CHD risk, and not on statins, to receive the 10-year risk of CHD based on conventional risk factors alone (n=103) or in combination with a genetic risk score (n=104). A genetic counselor disclosed this information followed by a physician visit for SDM regarding statin therapy. A novel decision aid was used in both encounters to disclose the CHD risk estimates and facilitate SDM regarding statin use. Patients reported their decision quality and physician visit satisfaction using validated surveys. There were no statistically significant differences between the two groups in the SDM score, satisfaction with the clinical encounter, perception of the quality of the discussion or of participation in decision-making and physician visit satisfaction scores. Quantitative analyses of a random subset of 80 video-recorded encounters using the OPTION5 scale also showed no significant difference in SDM between the two groups. Disclosure of CHD genetic risk using an electronic health record-linked decision aid did not adversely affect SDM or patients’ satisfaction with the clinical encounter. Trial registration number NCT01936675; Results.

Motivation, Perception, and Treatment Beliefs in the Myocardial Infarction Genes (MI-GENES) Randomized Clinical Trial

Little is known about individuals’ motivation, perception, and treatment beliefs towards the use of genetic information in risk estimates for coronary heart disease (CHD). In this study, participants at intermediate 10-year risk of CHD were randomized to receive either their estimated conventional risk score (CRS) alone, or a CRS and a genetic risk score (GRS), by a genetic counselor. Surveys on motivation to participate in and perception of genetic testing for CHD were administered at 3xa0months and treatment beliefs at 6xa0months following risk disclosure. Survey responses used Likert scales. Linear and logistic regression were used for analysis. Overall, motivation to participate in genomic clinical trials was favorable and did not differ between the CRS and GRS groups (16.95xa0±xa00.82 vs. 17.58xa0±xa00.83, pxa0=xa00.091), but participants who initially received their GRS indicated a greater desire to find ways to improve health as a reason for participation (OR: 0.53 (95%CI: 0.29, 0.94), pxa0=xa00.028). Perception of genetic testing was also favorable in both groups (15.29xa0±xa00.39 vs. 15.12xa0±xa00.40, pxa0=xa00.835). Participants who initially received their GRS were more inclined to recommend genetic testing to family and friends (9.95xa0±xa01.88 vs. 10.52xa0±xa02.17, pxa0=xa00.023). In the MI-GENES study, motivation to participate in and perception of genetic testing among study participants were overall favorable. Genetic risk disclosure was associated with increased motivation to recommend genetic testing to family and friends.

Disclosing Genetic Risk for Coronary Heart Disease: Attitudes Toward Personal Information in Health Records

INTRODUCTIONnIncorporating genetic risk information in electronic health records (EHRs) will facilitate implementation of genomic medicine in clinical practice. However, little is known about patients attitudes toward incorporation of genetic risk information as a component of personal health information in EHRs. This study investigated whether disclosure of a genetic risk score (GRS) for coronary heart disease influences attitudes toward incorporation of personal health information including genetic risk in EHRs.nnnMETHODSnParticipants aged 45-65 years with intermediate 10-year coronary heart disease risk were randomized to receive a conventional risk score (CRS) alone or with a GRS from a genetic counselor, followed by shared decision making with a physician using the same standard presentation and information templates for all study participants. The CRS and GRS were then incorporated into the EHR and made accessible to both patients and physicians. Baseline and post-disclosure surveys were completed to assess whether attitudes differed by GRS disclosure. Data were collected from 2013 to 2015 and analyzed in 2015-2016.nnnRESULTSnGRS and CRS participants reported similar positive attitudes toward incorporation of genetic risk information in the EHR. Compared with CRS participants, participants with high GRS were more concerned about the confidentiality of genetic risk information (OR=3.67, 95% CI=1.29, 12.32, p=0.01). Post-disclosure, frequency of patient portal access was associated with positive attitudes.nnnCONCLUSIONSnParticipants in this study of coronary heart disease risk disclosure overall had positive attitudes toward incorporation of genetic risk information in EHRs, although those who received genetic risk information had concerns about confidentiality.

Acute renal allograft dysfunction due to cecal volvulus: a case report

PurposeAmong kidney transplant recipients with acute kidney injury, the differential diagnosis must be broadened to include conditions such as rejection, immunocompromised host infections, anatomic pathologies, and recurrent or de novo glomerular diseases. In this case report, we describe an unusual cause of acute renal allograft injury due to external compression of the allograft ureter.MethodsRetrospective review; case report.ResultsThe patient developed acute kidney injury of the renal allograft due to external compression of the allograft ureter coincident with a cecal volvulus. The patient underwent lysis of adhesions, right hemicolectomy, and end ileostomy creation with resolution of acute kidney injury.ConclusionsCecal volvulus is an uncommon cause of bowel obstruction and is often associated with adhesions following abdominal surgery. To our knowledge, cecal volvulus has not previously been reported as a direct contributor to acute kidney injury. This case highlights the need for a systematic approach to the patient with acute kidney injury and the special considerations involved in the diagnosis of renal failure in the kidney transplant population.