Pharmacogenetic interactions between angiotensin-converting enzyme inhibitor therapy and the angiotensin-converting enzyme deletion polymorphism in patients with congestive heart failure

OBJECTIVES: We evaluated the interaction of angiotensin-converting enzyme (ACE) inhibitor therapy with the effect of the ACE D/I polymorphism on heart failure survival. BACKGROUND: The ACE deletion allele, ACE-D, is associated with increased ACE activity. The utilization of ACE genotyping to predict the impact of ACE inhibitor dose has not been previously evaluated. METHODS: We prospectively studied 479 subjects with systolic dysfunction (left ventricular ejection fraction 0.25 +/- 0.08). Subjects were divided on the basis of ACE inhibitor therapy into low dose (50%, n = 201), or those receiving angiotensin receptor antagonists (n = 51). Patients were genotyped for the ACE D/I polymorphism, followed to the end point of death or cardiac transplantation, and transplant-free survival compared by genotype. RESULTS: The ACE-D allele was associated with an increased risk of events (p = 0.026). In analysis by ACE inhibitor dose, this effect was primarily in the low-dose group (1-year percent event-free survival: II/ID/DD = 86/77/71,2-year = 79/66/59, p = 0.032). In the standard-dose group, the impact was markedly diminished (1-year: II/ID/DD = 91/81/80, 2-year: 77/70/71, p = 0.64). The impact of beta-blockers and high dose ACE inhibitors was greatest in subjects with the ACE DD genotype (p = 0.001) and was less apparent with the II and ID genotypes (p = 0.38). CONCLUSIONS: Higher doses of ACE inhibitors diminished the impact of the ACE-D allele, and the benefits of beta-blockers and high-dose ACE inhibitors appeared maximal for DD patients. Determination of ACE genotype may help target therapy for patients with heart failure.     

Groundhog Day for Medical Artificial Intelligence

Following a boom in investment and overinflated expectations in the 1980s, artificial intelligence entered a period of retrenchment known as the “AI winter.” With advances in the field of machine learning and the availability of large datasets for training various types of artificial neural networks, AI is in another cycle of halcyon days. Although medicine is particularly recalcitrant to change, applications of AI in health care have professionals in fields like radiology worried about the future of their careers and have the public tittering about the prospect of soulless machines making life‐and‐death decisions. Medicine thus appears to be at an inflection point—a kind of Groundhog Day on which either AI will bring a springtime of improved diagnostic and predictive practices or the shadow of public and professional fear will lead to six more metaphorical weeks of winter in medical AI.     

Artificial Intelligence and Black‐Box Medical Decisions: Accuracy versus Explainability

Although decision‐making algorithms are not new to medicine, the availability of vast stores of medical data, gains in computing power, and breakthroughs in machine learning are accelerating the pace of their development, expanding the range of questions they can address, and increasing their predictive power. In many cases, however, the most powerful machine learning techniques purchase diagnostic or predictive accuracy at the expense of our ability to access “the knowledge within the machine.” Without an explanation in terms of reasons or a rationale for particular decisions in individual cases, some commentators regard ceding medical decision‐making to black box systems as contravening the profound moral responsibilities of clinicians. I argue, however, that opaque decisions are more common in medicine than critics realize. Moreover, as Aristotle noted over two millennia ago, when our knowledge of causal systems is incomplete and precarious—as it often is in medicine—the ability to explain how results are produced can be less important than the ability to produce such results and empirically verify their accuracy.     

Spastic paretic hemifacial contracture related to multiple sclerosis: a rare and under-recognized entity

We describe an additional case of spastic paretic hemifacial contracture, an uncommon condition characterized by sustained unilateral contraction of the facial muscles associated with mild ipsilateral facial paresis. This entity has only rarely been associated with multiple sclerosis (MS) and can be mistaken for hemifacial spasm. Early consideration of MS in the differential diagnosis of young patients admitted with these symptoms is essential.     

Immune-mediated neurological syndromes in SARS-CoV-2-infected patients

Journal of Neurology - Evidence of immune-mediated neurological syndromes associated with the severe acute respiratory syndrome coronavirus (SARS-CoV-2) infection is limited. We therefore...     

Mastery,Intimacy, and Stress Resistance during War

The relationship between war-related stressors and emotional and behavioral adjustment during the Israel-Lebanon war was studied on a sample of 220 Israeli students, many of whom had been in combat. Mastery had direct effects on the well-being of both sexes. There was limited support for the stress-buffering effect of intimacy for men, such that those who had less intimate ties were increasingly negatively affected by greater exposure to war-related stressors, whereas those with more intimate relationships were relatively unaffected; the buffering effect applied both to emotions and behavior. No stress-buffering effect of intimate ties was found for women, but women were not affected by war-related stress at this time. The diagnosis post-traumatic stress disorder is examined in terms of the fact that normally healthy populations may be at increased risk of long-term adjustment difficulties following exposure to extreme stress if the threat of recurrence of the stressor continues. Implications for Vietnam veterans are also discussed.     

Synovectomy and total joint arthroplasty for recurrent hemarthroses in the arthropathic joint in hemophilia

Severe hemophiliacs with intractable bleeding into one or more joints despite adequate clotting factor replacement therapy are difficult management problems. Synovectomy has controlled bleeding only in joints without significant arthritic destruction. Total joint replacements have been performed in arthropathic joints, but not when uncontrolled bleeding was a concurrent problem. This report describes a hemophiliac with uncontrolled bleeding into an arthritic knee who was successfully managed by combining synovectomy with total knee replacement.     

Phenomics: the systematic study of phenotypes on a genome-wide scale

Phenomics is an emerging transdiscipline dedicated to the systematic study of phenotypes on a genome-wide scale. New methods for high-throughput genotyping have changed the priority for biomedical research to phenotyping, but the human phenome is vast and its dimensionality remains unknown. Phenomics research strategies capable of linking genetic variation to public health concerns need to prioritize development of mechanistic frameworks that relate neural systems functioning to human behavior. New approaches to phenotype definition will benefit from crossing neuropsychiatric syndromal boundaries, and defining phenotypic features across multiple levels of expression from proteome to syndrome. The demand for high throughput phenotyping may stimulate a migration from conventional laboratory to web-based assessment of behavior, and this offers the promise of dynamic phenotyping—the iterative refinement of phenotype assays based on prior genotype-phenotype associations. Phenotypes that can be studied across species may provide greatest traction, particularly given rapid development in transgenic modeling. Phenomics research demands vertically integrated research teams, novel analytic strategies and informatics infrastructure to help manage complexity. The Consortium for Neuropsychiatric Phenomics at UCLA has been supported by the National Institutes of Health Roadmap Initiative to illustrate these principles, and is developing applications that may help investigators assemble, visualize, and ultimately test multi-level phenomics hypotheses. As the transdiscipline of phenomics matures, and work is extended to large-scale international collaborations, there is promise that systematic new knowledge bases will help fulfill the promise of personalized medicine and the rational diagnosis and treatment of neuropsychiatric syndromes.     

Effect of cigarette smoking on prefrontal cortical function in nondeprived smokers performing the Stroop Task.

Some reports indicate that cigarette smoking can help smokers focus attention, even when they have not abstained from smoking for a substantial period of time (eg, >1 h). Understanding the mechanisms by which smoking affects attention may help in designing smoking cessation treatments. Thirteen nonsmokers and nine smokers participated in two tests of blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI). During fMRI, the participants performed the Stroop Task. There was a 15-min break between the two tests. During the break, each smoker smoked one cigarette. For smokers, the first test began 45-60 min after the last cigarette of ad libitum smoking. The differences in BOLD signal changes between Stroop conditions (ie, incongruent minus congruent) showed a group x test interaction in the right precentral sulcus, including the putative human frontal eye field (FEF). Smokers, but not nonsmokers, showed greater changes (relative to rest) in BOLD signal in the incongruent than in the congruent condition in the first fMRI test but not in the second. Even after brief abstinence from smoking, therefore, smokers exhibit compromised functional efficiency in the right FEF and adjacent precentral sulcus in a test of selective attention; and smoking ameliorates this condition.