Exploration of human serum lipoprotein supramolecular phospholipids using statistical heterospectroscopy in n-Dimensions (SHY-n): Identification of potential cardiovascular risk biomarkers related to SARS-CoV-2 infection

SARS-CoV-2 infection causes a significant reduction in lipoprotein-bound serum phospholipids give rise to supramolecular phospholipid composite (SPC) signals observed in diffusion and relaxation edited 1H NMR spectra. To characterize the chemical structural components and compartmental location of SPC and to understand further its possible diagnostic properties, we applied a Statistical HeterospectroscopY in n-dimensions (SHY-n) approach. This involved statistically linking a series of orthogonal measurements made on the same samples, using independent analytical techniques and instruments, to identify the major individual phospholipid components giving rise to the SPC signals. Thus, an integrated model for SARS-CoV-2 positive and control adults is presented that relates three identified diagnostic subregions of the SPC signal envelope (SPC1, SPC2, and SPC3) generated using diffusion and relaxation edited (DIRE) NMR spectroscopy to lipoprotein and lipid measurements obtained by in vitro diagnostic NMR spectroscopy and ultrahigh-performance liquid chromatography–tandem mass spectrometry (UHPLC–MS/MS). The SPC signals were then correlated sequentially with (a) total phospholipids in lipoprotein subfractions; (b) apolipoproteins B100, A1, and A2 in different lipoproteins and subcompartments; and (c) MS-measured total serum phosphatidylcholines present in the NMR detection range (i.e., PCs: 16.0,18.2; 18.0,18.1; 18.2,18.2; 16.0,18.1; 16.0,20.4; 18.0,18.2; 18.1,18.2), lysophosphatidylcholines (LPCs: 16.0 and 18.2), and sphingomyelin (SM 22.1). The SPC3/SPC2 ratio correlated strongly (r = 0.86) with the apolipoprotein B100/A1 ratio, a well-established marker of cardiovascular disease risk that is markedly elevated during acute SARS-CoV-2 infection. These data indicate the considerable potential of using a serum SPC measurement as a metric of cardiovascular risk based on a single NMR experiment. This is of specific interest in relation to understanding the potential for increased cardiovascular risk in COVID-19 patients and risk persistence in post-acute COVID-19 syndrome (PACS)

Mapping child growth failure across low- and middle-income countries

Child growth failure (CGF), manifested as stunting, wasting, and underweight, is associated with high 5 mortality and increased risks of cognitive, physical, and metabolic impairments. Children in low- and middle-income countries (LMICs) face the highest levels of CGF globally. Here we illustrate national and subnational variation of under-5 CGF indicators across LMICs, providing 2000–2017 annual estimates mapped at a high spatial resolution and aggregated to policy-relevant administrative units and national levels. Despite remarkable declines over the study period, many LMICs remain far from the World Health 10 Organization’s ambitious Global Nutrition Targets to reduce stunting by 40% and wasting to less than 5% by 2025. Large disparities in prevalence and rates of progress exist across regions, countries, and within countries; our maps identify areas where high prevalence persists even within nations otherwise succeeding in reducing overall CGF prevalence. By highlighting where subnational disparities exist and the highest-need populations reside, these geospatial estimates can support policy-makers in planning locally 15 tailored interventions and efficient directing of resources to accelerate progress in reducing CGF and its health implications

Mapping disparities in education across low- and middle-income countries

Analyses of the proportions of individuals who have completed key levels of schooling across all low- and middle-income countries from 2000 to 2017 reveal inequalities across countries as well as within populations. Educational attainment is an important social determinant of maternal, newborn, and child health(1-3). As a tool for promoting gender equity, it has gained increasing traction in popular media, international aid strategies, and global agenda-setting(4-6). The global health agenda is increasingly focused on evidence of precision public health, which illustrates the subnational distribution of disease and illness(7,8); however, an agenda focused on future equity must integrate comparable evidence on the distribution of social determinants of health(9-11). Here we expand on the available precision SDG evidence by estimating the subnational distribution of educational attainment, including the proportions of individuals who have completed key levels of schooling, across all low- and middle-income countries from 2000 to 2017. Previous analyses have focused on geographical disparities in average attainment across Africa or for specific countries, but-to our knowledge-no analysis has examined the subnational proportions of individuals who completed specific levels of education across all low- and middle-income countries(12-14). By geolocating subnational data for more than 184 million person-years across 528 data sources, we precisely identify inequalities across geography as well as within populations.Peer reviewe

Hepatic levels of S-adenosylmethionine regulate the adaptive response to fasting

26 p.-6 fig.-1 tab.-1 graph. abst.There has been an intense focus to uncover the molecular mechanisms by which fasting triggers the adaptive cellular responses in the major organs of the body. Here, we show that in mice, hepatic S-adenosylmethionine (SAMe)—the principal methyl donor—acts as a metabolic sensor of nutrition to fine-tune the catabolic-fasting response by modulating phosphatidylethanolamine N-methyltransferase (PEMT) activity, endoplasmic reticulum-mitochondria contacts, β-oxidation, and ATP production in the liver, together with FGF21-mediated lipolysis and thermogenesis in adipose tissues. Notably, we show that glucagon induces the expression of the hepatic SAMe-synthesizing enzyme methionine adenosyltransferase α1 (MAT1A), which translocates to mitochondria-associated membranes. This leads to the production of this metabolite at these sites, which acts as a brake to prevent excessive β-oxidation and mitochondrial ATP synthesis and thereby endoplasmic reticulum stress and liver injury. This work provides important insights into the previously undescribed function of SAMe as a new arm of the metabolic adaptation to fasting.M.V.-R. is supported by Proyecto PID2020-119486RB-100 (funded by MCIN/AEI/10.13039/501100011033), Gilead Sciences International Research Scholars Program in Liver Disease, Acción Estratégica Ciberehd Emergentes 2018 (ISCIII), Fundación BBVA, HORIZON-TMA-MSCA-Doctoral Networks 2021 (101073094), and Redes de Investigación 2022 (RED2022-134485-T). M.L.M.-C. is supported by La CAIXA Foundation (LCF/PR/HP17/52190004), Proyecto PID2020-117116RB-I00 (funded by MCIN/AEI/10.13039/501100011033), Ayudas Fundación BBVA a equipos de investigación científica (Umbrella 2018), and AECC Scientific Foundation (Rare Cancers 2017). A.W. is supported by RTI2018-097503-B-I00 and PID2021-127169OB-I00, (funded by MCIN/AEI/10.13039/501100011033) and by “ERDF A way of making Europe,” Xunta de Galicia (Ayudas PRO-ERC), Fundación Mutua Madrileña, and European Community’s H2020 Framework Programme (ERC Consolidator grant no. 865157 and MSCA Doctoral Networks 2021 no. 101073094). C.M. is supported by CIBERNED. P.A. is supported by Ayudas para apoyar grupos de investigación del sistema Universitario Vasco (IT1476-22), PID2021-124425OB-I00 (funded by MCIN/AEI/10.13039/501100011033 and “ERDF A way of making Europe,” MCI/UE/ISCiii [PMP21/00080], and UPV/EHU [COLAB20/01]). M.F. and M.G.B. are supported by PID2019-105739GB-I00 and PID2020-115472GB-I00, respectively (funded by MCIN/AEI/10.13039/501100011033). M.G.B. is supported by Xunta de Galicia (ED431C 2019/013). C.A., T.L.-D., and J.B.-V. are recipients of pre-doctoral fellowships from Xunta de Galicia (ED481A-2020/046, ED481A-2018/042, and ED481A 2021/244, respectively). T.C.D. is supported by Fundación Científica AECC. A.T.-R. is a recipient of a pre-doctoral fellowship from Fundación Científica AECC. S.V.A. and C.R. are recipients of Margarita Salas postdoc grants under the “Plan de Recuperación Transformación” program funded by the Spanish Ministry of Universities with European Union’s NextGeneration EU funds (2021/PER/00020 and MU-21-UP2021-03071902373A, respectively). T.C.D., A.S.-R., and M.T.-C. are recipients of Ayuda RYC2020-029316-I, PRE2019/088960, and BES-2016/078493, respectively, supported by MCIN/AEI/10.13039/501100011033 and by El FSE invierte en tu futuro. S.L.-O. is a recipient of a pre-doctoral fellowship from the Departamento de Educación del Gobierno Vasco (PRE_2018_1_0372). P.A.-G. is recipient of a FPU pre-doctoral fellowship from the Ministry of Education (FPU19/02704). CIC bioGUNE is supported by Ayuda CEX2021-001136-S financiada por MCIN/AEI/10.13039/501100011033. A.B.-C. was funded by predoctoral contract PFIS (FI19/00240) from Instituto de Salud Carlos III (ISCIII) co-funded by Fondo Social Europeo (FSE), and A.D.-L. was funded by contract Juan Rodés (JR17/00016) from ISCIII. A.B.-C. is a Miguel Servet researcher (CPII22/00008) from ISCIII.Peer reviewe

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Redox regulation of KV7 channels through EF3 hand of calmodulin

Neuronal KV7 channels, important regulators of cell excitability, are among the most sensitive proteins to reactive oxygen species. The S2S3 linker of the voltage sensor was reported as a site-mediating redox modulation of the channels. Recent structural insights reveal potential interactions between this linker and the Ca2+-binding loop of the third EF-hand of calmodulin (CaM), which embraces an antiparallel fork formed by the C-terminal helices A and B, constituting the calcium responsive domain (CRD). We found that precluding Ca2+ binding to the EF3 hand, but not to EF1, EF2, or EF4 hands, abolishes oxidation-induced enhancement of KV7.4 currents. Monitoring FRET (Fluorescence Resonance Energy Transfer) between helices A and B using purified CRDs tagged with fluorescent proteins, we observed that S2S3 peptides cause a reversal of the signal in the presence of Ca2+ but have no effect in the absence of this cation or if the peptide is oxidized. The capacity of loading EF3 with Ca2+ is essential for this reversal of the FRET signal, whereas the consequences of obliterating Ca2+ binding to EF1, EF2, or EF4 are negligible. Furthermore, we show that EF3 is critical for translating Ca2+ signals to reorient the AB fork. Our data are consistent with the proposal that oxidation of cysteine residues in the S2S3 loop relieves KV7 channels from a constitutive inhibition imposed by interactions between the EF3 hand of CaM which is crucial for this signaling

Structural basis of pyrrole polymerization in human porphobilinogen deaminase

Human porphobilinogen deaminase (PBGD), the third enzyme in the heme pathway, catalyzes four times a single reaction to convert porphobilinogen into hydroxymethylbilane. Remarkably, PBGD employs a single active site during the process, with a distinct yet chemically equivalent bond formed each time. The four intermediate complexes of the enzyme have been biochemically validated and they can be isolated but they have never been structurally characterized other than the apo- and holo-enzyme bound to the cofactor. We present crystal structures for two human PBGD intermediates: PBGD loaded with the cofactor and with the reaction intermediate containing two additional substrate pyrrole rings. These results, combined with SAXS and NMR experiments, allow us to propose a mechanism for the reaction progression that requires less structural rearrangements than previously suggested: the enzyme slides a flexible loop over the growing-product active site cavity. The structures and the mechanism proposed for this essential reaction explain how a set of missense mutations result in acute intermittent porphyria

J-edited dIffusional proton nuclear magnetic resonance spectroscopic measurement of glycoprotein and supramolecular phospholipid biomarkers of inflammation in human serum.

Proton nuclear magnetic resonance (NMR) N-acetyl signals (Glyc) from glycoproteins and supramolecular phospholipids composite peak (SPC) from phospholipid quaternary nitrogen methyls in subcompartments of lipoprotein particles) can give important systemic metabolic information, but their absolute quantification is compromised by overlap with interfering resonances from lipoprotein lipids themselves. We present a J-Edited DIffusional (JEDI) proton NMR spectroscopic approach to selectively augment signals from the inflammatory marker peaks Glyc and SPCs in blood serum NMR spectra, which enables direct integration of peaks associated with molecules found in specific compartments. We explore a range of pulse sequences that allow editing based on peak J-modulation, translational diffusion, and T2 relaxation time and validate them for untreated blood serum samples from SARS-CoV-2 infected patients (n = 116) as well as samples from healthy controls and pregnant women with physiological inflammation and hyperlipidemia (n = 631). The data show that JEDI is an improved approach to selectively investigate inflammatory signals in serum and may have widespread diagnostic applicability to disease states associated with systemic inflammation