Metabolomic Profiling of the Malaria Box Reveals Antimalarial Target Pathways.

The threat of widespread drug resistance to frontline antimalarials has renewed the urgency for identifying inexpensive chemotherapeutic compounds that are effective against Plasmodium falciparum, the parasite species responsible for the greatest number of malaria-related deaths worldwide. To aid in the fight against malaria, a recent extensive screening campaign has generated thousands of lead compounds with low micromolar activity against blood stage parasites. A subset of these leads has been compiled by the Medicines for Malaria Venture (MMV) into a collection of structurally diverse compounds known as the MMV Malaria Box. Currently, little is known regarding the activity of these Malaria Box compounds on parasite metabolism during intraerythrocytic development, and a majority of the targets for these drugs have yet to be defined. Here we interrogated the in vitro metabolic effects of 189 drugs (including 169 of the drug-like compounds from the Malaria Box) using ultra-high-performance liquid chromatography-mass spectrometry (UHPLC-MS). The resulting metabolic fingerprints provide information on the parasite biochemical pathways affected by pharmacologic intervention and offer a critical blueprint for selecting and advancing lead compounds as next-generation antimalarial drugs. Our results reveal several major classes of metabolic disruption, which allow us to predict the mode of action (MoA) for many of the Malaria Box compounds. We anticipate that future combination therapies will be greatly informed by these results, allowing for the selection of appropriate drug combinations that simultaneously target multiple metabolic pathways, with the aim of eliminating malaria and forestalling the expansion of drug-resistant parasites in the field.

Association of Loneliness With 10-Year Dementia Risk and Early Markers of Vulnerability for Neurocognitive Decline.

BACKGROUND AND OBJECTIVES: Loneliness is common, and its prevalence is rising. The relationship of loneliness with subsequent dementia and the early preclinical course of Alzheimer disease and related dementia (ADRD) remains unclear. Thus, the primary objective of this study was to determine the association of loneliness with 10-year all-cause dementia risk and early cognitive and neuroanatomic imaging markers of ADRD vulnerability. METHODS: This was a retrospective analysis of prospectively collected data from the population-based Framingham Study cohorts (September 9, 1948-December 31, 2018). Eligible participants had loneliness assessed and were dementia-free at baseline. Loneliness was recorded with the Center for Epidemiologic Studies Depression Scale, defined conservatively as feeling lonely ≥3 days in the past week. The main outcomes were incident dementia over a 10-year period, cognition, and MRI brain volumes and white matter injury. RESULTS: Of 2,308 participants (mean age 73 [SD 9] years, 56% women) who met eligibility in the dementia sample, 14% (329 of 2,308) developed dementia and 6% (144 of 2,308) were lonely. Lonely (versus not lonely) adults had higher 10-year dementia risk (age-, sex-, and education-adjusted hazard ratio 1.54, 95% CI 1.06-2.24). Lonely participants <80 years of age without APOE ε4 alleles had a 3-fold greater risk (adjusted hazard ratio 3.03, 95% CI, 1.63-5.62). Among 1,875 persons without dementia who met eligibility in the cognition sample (mean age 62 [SD 9] years, 54% women), loneliness associated with poorer executive function, lower total cerebral volume, and greater white matter injury. DISCUSSION: Over 10 years of close clinical dementia surveillance in this cohort study, loneliness was associated with increased dementia risk; this tripled in adults whose baseline risk would otherwise be relatively low on the basis of age and genetic risk, representing a majority of the US population. Loneliness was also associated with worse neurocognitive markers of ADRD vulnerability, suggesting an early pathogenic role. These findings may have important clinical and public health implications given observed loneliness trends. CLASSIFICATION OF EVIDENCE: This study provides Class I evidence that loneliness increases the 10-year risk of developing dementia.

Association of Midlife Depressive Symptoms with Regional Amyloid-ß and Tau in the Framingham Heart Study.

BACKGROUND: Depressive symptoms predict increased risk for dementia decades before the emergence of cognitive symptoms. Studies in older adults provide preliminary evidence for an association between depressive symptoms and amyloid-ß (Aß) and tau accumulation. It is unknown if similar alterations are observed in midlife when preventive strategies may be most effective. OBJECTIVE: The study aim was to evaluate the association between depressive symptoms and cerebral Aß and tau in a predominately middle-aged cohort with examination of the apolipoprotein (APOE) ɛ4 allele as a moderator. METHODS: Participants included 201 adults (mean age 53±8 years) who underwent 11C-Pittsburgh Compound B amyloid and 18F-Flortaucipir tau positron emission tomography (PET) imaging. Depressive symptoms were evaluated with the Center for Epidemiological Studies Depression Scale (CES-D) at the time of PET imaging, as well as eight years prior. Associations between depressive symptoms at both timepoints, as well as depression (CES-D≥16), with regional Aß and tau PET retention were evaluated with linear regression adjusting for age and sex. Interactions with the APOE ɛ4 allele were explored. RESULTS: Depressive symptoms and depression were not associated with PET outcomes in the overall sample. However, among APOE ɛ4 allele carriers, there was a significant cross-sectional association between depressive symptoms and increased tau PET uptake in the entorhinal cortex (ß= 0.446, SE = 0.155, p = 0.006) and amygdala (ß= 0.350, SE = 0.133, p = 0.012). CONCLUSION: Although longitudinal studies are necessary, the results suggest that APOE ɛ4 carriers with depressive symptoms may present with higher susceptibility to early tau accumulation in regions integral to affective regulation and memory consolidation.

Individual differences in normal body temperature: longitudinal big data analysis of patient records.

OBJECTIVE: To estimate individual level body temperature and to correlate it with other measures of physiology and health. DESIGN: Observational cohort study. SETTING: Outpatient clinics of a large academic hospital, 2009-14. PARTICIPANTS: 35 488 patients who neither received a diagnosis for infections nor were prescribed antibiotics, in whom temperature was expected to be within normal limits. MAIN OUTCOME MEASURES: Baseline temperatures at individual level, estimated using random effects regression and controlling for ambient conditions at the time of measurement, body site, and time factors. Baseline temperatures were correlated with demographics, medical comorbidities, vital signs, and subsequent one year mortality. RESULTS: In a diverse cohort of 35 488 patients (mean age 52.9 years, 64% women, 41% non-white race) with 243 506 temperature measurements, mean temperature was 36.6°C (95% range 35.7-37.3°C, 99% range 35.3-37.7°C). Several demographic factors were linked to individual level temperature, with older people the coolest (-0.021°C for every decade, P<0.001) and African-American women the hottest (versus white men: 0.052°C, P<0.001). Several comorbidities were linked to lower temperature (eg, hypothyroidism: -0.013°C, P=0.01) or higher temperature (eg, cancer: 0.020, P<0.001), as were physiological measurements (eg, body mass index: 0.002 per m/kg2, P<0.001). Overall, measured factors collectively explained only 8.2% of individual temperature variation. Despite this, unexplained temperature variation was a significant predictor of subsequent mortality: controlling for all measured factors, an increase of 0.149°C (1 SD of individual temperature in the data) was linked to 8.4% higher one year mortality (P=0.014). CONCLUSIONS: Individuals' baseline temperatures showed meaningful variation that was not due solely to measurement error or environmental factors. Baseline temperatures correlated with demographics, comorbid conditions, and physiology, but these factors explained only a small part of individual temperature variation. Unexplained variation in baseline temperature, however, strongly predicted mortality.