Arginine vasopressin regulates the renal Na+-Cl- and Na+-K+-Cl- cotransporters through with-no-lysine kinase 4 and inhibitor 1 phosphorylation.

Vasopressin regulates water homeostasis via the V2 receptor in the kidney at least in part through protein kinase A (PKA) activation. Vasopressin, through an unknown pathway, upregulates the activity and phosphorylation of Na+-Cl- cotransporter (NCC) and Na+-K+-2Cl- cotransporter 2 (NKCC2) by Ste20-related proline/alanine-rich kinase (SPAK) and oxidative stress-responsive kinase 1 (OSR1), which are regulated by the with-no-lysine kinase (WNK) family. Phosphorylation of WNK4 at PKA consensus motifs may be involved. Inhibitor 1 (I1), a protein phosphatase 1 (PP1) inhibitor, may also play a role. In human embryonic kidney (HEK)-293 cells, we assessed the phosphorylation of WNK4, SPAK, NCC, or NKCC2 in response to forskolin or desmopressin. WNK4 and cotransporter phosphorylation were studied in desmopressin-infused WNK4-/- mice and in tubule suspensions. In HEK-293 cells, only wild-type WNK4 but not WNK1, WNK3, or a WNK4 mutant lacking PKA phosphorylation motifs could upregulate SPAK or cotransporter phosphorylation in response to forskolin or desmopressin. I1 transfection maximized SPAK phosphorylation in response to forskolin in the presence of WNK4 but not of mutant WNK4 lacking PP1 regulation. We observed direct PP1 regulation of NKCC2 dephosphorylation but not of NCC or SPAK in the absence of WNK4. WNK4-/- mice with desmopressin treatment did not increase SPAK/OSR1, NCC, or NKCC2 phosphorylation. In stimulated tubule suspensions from WNK4-/- mice, upregulation of pNKCC2 was reduced, whereas upregulation of SPAK phosphorylation was absent. These findings suggest that WNK4 is a central node in which kinase and phosphatase signaling converge to connect cAMP signaling to the SPAK/OSR1-NCC/NKCC2 pathway.NEW & NOTEWORTHY With-no-lysine kinases regulate the phosphorylation and activity of the Na+-Cl- and Na+-K+-2Cl- cotransporters. This pathway is modulated by arginine vasopressin (AVP). However, the link between AVP and WNK signaling remains unknown. Here, we show that AVP activates WNK4 through increased phosphorylation at putative protein kinase A-regulated sites and decreases its dephosphorylation by protein phosphatase 1. This work increases our understanding of the signaling pathways mediating AVP actions in the kidney.

AnthropoAge, a novel approach to integrate body composition into the estimation of biological age.

Aging is believed to occur across multiple domains, one of which is body composition; however, attempts to integrate it into biological age (BA) have been limited. Here, we consider the sex-dependent role of anthropometry for the prediction of 10-year all-cause mortality using data from 18,794 NHANES participants to generate and validate a new BA metric. Our data-driven approach pointed to sex-specific contributors for BA estimation: WHtR, arm and thigh circumferences for men; weight, WHtR, thigh circumference, subscapular and triceps skinfolds for women. We used these measurements to generate AnthropoAge, which predicted all-cause mortality (AUROC 0.876, 95%CI 0.864-0.887) and cause-specific mortality independently of ethnicity, sex, and comorbidities; AnthropoAge was a better predictor than PhenoAge for cerebrovascular, Alzheimer, and COPD mortality. A metric of age acceleration was also derived and used to assess sexual dimorphisms linked to accelerated aging, where women had an increase in overall body mass plus an important subcutaneous to visceral fat redistribution, and men displayed a marked decrease in fat and muscle mass. Finally, we showed that consideration of multiple BA metrics may identify unique aging trajectories with increased mortality (HR for multidomain acceleration 2.43, 95%CI 2.25-2.62) and comorbidity profiles. A simplified version of AnthropoAge (S-AnthropoAge) was generated using only BMI and WHtR, all results were preserved using this metric. In conclusion, AnthropoAge is a useful proxy of BA that captures cause-specific mortality and sex dimorphisms in body composition, and it could be used for future multidomain assessments of aging to better characterize the heterogeneity of this phenomenon.

Elevated serum uric acid is a facilitating mechanism for insulin resistance mediated accumulation of visceral adipose tissue.

OBJECTIVE: Serum uric acid (SUA) has been associated with cardiometabolic conditions such as insulin resistance (IR) and visceral adipose tissue (VAT) accumulation. Here, we aimed to clarify a unifying mechanism linking elevated SUA to IR and VAT. METHODS: We conducted analyses in 226 subjects from the UIEM cohort with both euglycemic hyperinsulinemic clamp (EHC) and dual X-ray absorptiometry (DXA) measurements for IR and VAT accumulation and explored the role of SUA and adiponectin by developing a network of causal mediation analyses to assess their impact on IR and VAT. These models were then translated to two population-based cohorts comprising 6337 subjects from NHANES 2003-2004 and 2011-2012 cycles in the US and ENSANUT Medio Camino 2016 in Mexico, using HOMA2IR and adipoIR as indicators of peripheral and adipose tissue IR, and METS-VF as a surrogate for VAT accumulation. RESULTS: SUA has a mediating role inside a bidirectional relationship between IR and visceral obesity, which was similar using either gold standard measurements or surrogate measures for IR and VAT. Furthermore, adiponectin acts as a linking mediator between elevated SUA and both peripheral IR and VAT accumulation. The proportion of the mechanism for IR-mediated (in either peripheral or adipose tissue) VAT accumulation was greater, compared to VAT-mediated IR accumulation (10.53% [9.23%-12.00%] to 5.44% [3.78%-7.00%]). Normal-range SUA levels can be used to rule-out underlying cardio-metabolic abnormalities in both men and women. CONCLUSIONS: Elevated SUA acts as a mediator inside the bidirectional relationship between IR and VAT accumulation and these observations could be applicable at a phenotype scale.

Comprehensive Evaluation of the Impact of Sociodemographic Inequalities on Adverse Outcomes and Excess Mortality During the Coronavirus Disease 2019 (COVID-19) Pandemic in Mexico City.

BACKGROUND: The impact of the coronavirus disease 2019 (COVID-19) pandemic in Mexico City has been sharp, as several social inequalities at all levels coexist. Here we conducted an in-depth evaluation of the impact of individual and municipal-level social inequalities on the COVID-19 pandemic in Mexico City. METHODS: We analyzed suspected severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) cases, from the Mexico City Epidemiological Surveillance System from 24 February 2020 to 31 March 2021. COVID-19 outcomes included rates of hospitalization, severe COVID-19, invasive mechanical ventilation, and mortality. We evaluated socioeconomic occupation as an individual risk, and social lag, which captures municipal-level social vulnerability, and urban population density as proxies of structural risk factors. Impact of reductions in vehicular mobility on COVID-19 rates and the influence of risk factors were also assessed. Finally, we assessed discrepancies in COVID-19 and non-COVID-19 excess mortality using death certificates from the general civil registry. RESULTS: We detected vulnerable groups who belonged to economically unfavored sectors and experienced increased risk of COVID-19 outcomes. Cases living in marginalized municipalities with high population density experienced greater risk for COVID-19 outcomes. Additionally, policies to reduce vehicular mobility had differential impacts modified by social lag and urban population density. Finally, we report an under-registry of COVID-19 deaths along with an excess mortality closely related to marginalized and densely populated communities in an ambulatory setting. This could be attributable to a negative impact of modified hospital admission criteria during the pandemic. CONCLUSIONS: Socioeconomic occupation and municipality-wide factors played a significant role in shaping the course of the COVID-19 pandemic in Mexico City.

Diagnostic performance and clinical implications of rapid SARS-CoV-2 antigen testing in Mexico using real-world nationwide COVID-19 registry data.

BACKGROUND: SARS-CoV-2 testing capacity is important to monitor epidemic dynamics and as a mitigation strategy. Given difficulties of large-scale quantitative reverse transcription polymerase chain reaction (qRT-PCR) implementation, rapid antigen tests (Rapid Ag-T) have been proposed as alternatives in settings like Mexico. Here, we evaluated diagnostic performance of Rapid Ag-T for SARS-CoV-2 infection and its associated clinical implications compared to qRT-PCR testing in Mexico. METHODS: We analyzed data from the COVID-19 registry of the Mexican General Directorate of Epidemiology up to April 30th, 2021 (n = 6,632,938) and cases with both qRT-PCR and Rapid Ag-T (n = 216,388). We evaluated diagnostic performance using accuracy measures and assessed time-dependent changes in the Area Under the Receiver Operating Characteristic curve (AUROC). We also explored test discordances as predictors of hospitalization, intubation, severe COVID-19 and mortality. RESULTS: Rapid Ag-T is primarily used in Mexico City. Rapid Ag-T have low sensitivity 37.6% (95%CI 36.6-38.7), high specificity 95.5% (95%CI 95.1-95.8) and acceptable positive 86.1% (95%CI 85.0-86.6) and negative predictive values 67.2% (95%CI 66.2-69.2). Rapid Ag-T has optimal diagnostic performance up to days 3 after symptom onset, and its performance is modified by testing location, comorbidity, and age. qRT-PCR (-) / Rapid Ag-T (+) cases had higher risk of adverse COVID-19 outcomes (HR 1.54 95% CI 1.41-1.68) and were older, qRT-PCR (+)/ Rapid Ag-T(-) cases had slightly higher risk or adverse outcomes and ≥7 days from symptom onset (HR 1.53 95% CI 1.48-1.59). Cases detected with rapid Ag-T were younger, without comorbidities, and milder COVID-19 course. CONCLUSIONS: Rapid Ag-T could be used as an alternative to qRT-PCR for large scale SARS-CoV-2 testing in Mexico. Interpretation of Rapid Ag-T results should be done with caution to minimize the risk associated with false negative results.

Adaptive Metabolic and Inflammatory Responses Identified Using Accelerated Aging Metrics Are Linked to Adverse Outcomes in Severe SARS-CoV-2 Infection.

BACKGROUND: Chronological age (CA) is a predictor of adverse coronavirus disease 2019 (COVID-19) outcomes; however, CA alone does not capture individual responses to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Here, we evaluated the influence of aging metrics PhenoAge and PhenoAgeAccel to predict adverse COVID-19 outcomes. Furthermore, we sought to model adaptive metabolic and inflammatory responses to severe SARS-CoV-2 infection using individual PhenoAge components. METHOD: In this retrospective cohort study, we assessed cases admitted to a COVID-19 reference center in Mexico City. PhenoAge and PhenoAgeAccel were estimated using laboratory values at admission. Cox proportional hazards models were fitted to estimate risk for COVID-19 lethality and adverse outcomes (intensive care unit admission, intubation, or death). To explore reproducible patterns which model adaptive responses to SARS-CoV-2 infection, we used k-means clustering using PhenoAge components. RESULTS: We included 1068 subjects of whom 222 presented critical illness and 218 died. PhenoAge was a better predictor of adverse outcomes and lethality compared to CA and SpO2 and its predictive capacity was sustained for all age groups. Patients with responses associated to PhenoAgeAccel >0 had higher risk of death and critical illness compared to those with lower values (log-rank p < .001). Using unsupervised clustering, we identified 4 adaptive responses to SARS-CoV-2 infection: (i) inflammaging associated with CA, (ii) metabolic dysfunction associated with cardiometabolic comorbidities, (iii) unfavorable hematological response, and (iv) response associated with favorable outcomes. CONCLUSIONS: Adaptive responses related to accelerated aging metrics are linked to adverse COVID-19 outcomes and have unique and distinguishable features. PhenoAge is a better predictor of adverse outcomes compared to CA.

Unequal Impact of Structural Health Determinants and Comorbidity on COVID-19 Severity and Lethality in Older Mexican Adults: Considerations Beyond Chronological Aging.

BACKGROUND: COVID-19 has had a disproportionate impact on older adults. Mexico's population is younger, yet COVID-19's impact on older adults is comparable to countries with older population structures. Here, we aim to identify health and structural determinants that increase susceptibility to COVID-19 in older Mexican adults beyond chronological aging. METHODS: We analyzed confirmed COVID-19 cases in older adults using data from the General Directorate of Epidemiology of Mexican Ministry of Health. We modeled risk factors for increased COVID-19 severity and mortality, using mixed models to incorporate multilevel data concerning healthcare access and marginalization. We also evaluated structural factors and comorbidity profiles compared to chronological age for COVID-19 mortality risk prediction. RESULTS: We analyzed 20 804 confirmed SARS-CoV-2 cases in adults aged 60 and older. Male sex, smoking, diabetes, and obesity were associated with pneumonia, hospitalization, and intensive care unit (ICU) admission in older adults, CKD and COPD were associated with hospitalization. High social lag indexes and access to private care were predictors of COVID-19 severity and mortality. Age was not a predictor of COVID-19 severity in individuals without comorbidities and combination of structural factors and comorbidities were better predictors of COVID-19 lethality and severity compared to chronological age alone. COVID-19 baseline lethality hazards were heterogeneously distributed across Mexican municipalities, particularly when comparing urban and rural areas. CONCLUSIONS: Structural factors and comorbidity explain excess risk for COVID-19 severity and mortality over chronological age in older Mexican adults. Clinical decision-making related to COVID-19 should focus away from chronological aging onto more a comprehensive geriatric care approach.

Profiling Cases With Nonrespiratory Symptoms and Asymptomatic Severe Acute Respiratory Syndrome Coronavirus 2 Infections in Mexico City.

We profiled cases with nonrespiratory symptoms (NRS) and asymptomatic severe acute respiratory syndrome coronavirus 2 infections assessed within Mexico City's Epidemiological Surveillance System. Initially asymptomatic or NRS cases have decreased risk of adverse outcomes compared with cases with respiratory symptoms. Comorbidity and age influence symptom development in initially asymptomatic cases.

Assessing the Burden of Coronavirus Disease 2019 (COVID-19) Among Healthcare Workers in Mexico City: A Data-Driven Call to Action.

BACKGROUND: Healthcare workers (HCWs) could be at increased occupational risk for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections due to increased exposure. Information regarding the burden of coronavirus disease 2019 (COVID-19) epidemic in HCWs living in Mexico is scarce. Here, we aimed to explore the epidemiology, symptoms, and risk factors associated with adverse outcomes in HCWs in Mexico City. METHODS: We explored data collected by the National Epidemiological Surveillance System in Mexico City, in HCWs who underwent real-time reverse transcription polymerase chain reaction (RT-PCR) test. We explored COVID-19 outcomes in HCWs and the performance of symptoms to detect SARS-CoV-2 infection. RESULTS: As of 20 September 2020, 57 758 HCWs were tested for SARS-CoV-2 and 17 531 were confirmed (30.35%); 6610 were nurses (37.70%), 4910 physicians (28.0%), 267 dentists (1.52%), and 5744 laboratory personnel and other HCWs (32.76%). Overall, 2378 HCWs required hospitalization (4.12%), 2648 developed severe COVID-19 (4.58%), and 336 required mechanical-ventilatory support (.58%). Lethality was recorded in 472 (.82%) cases. We identified 635 asymptomatic SARS-CoV-2 infections (3.62%). Compared with general population, HCWs had higher incidence, testing, asymptomatic cases, and mortality rates. No individual symptom offers adequate performance to detect SARS-CoV2. Older HCWs with chronic noncommunicable diseases and severe respiratory symptoms were associated with higher risk for adverse outcome; physicians were at higher risk compared with nurses and other HCWs. CONCLUSIONS: We report a high prevalence of SARS-CoV-2 infection in HCWs in Mexico City. Symptoms as a screening method are not efficient to discern those HCWs with a positive PCR-RT test. Particular attention should focus on HCWs with risk factors to prevent adverse outcomes.

Clinical characterization of data-driven diabetes subgroups in Mexicans using a reproducible machine learning approach.

INTRODUCTION: Previous reports in European populations demonstrated the existence of five data-driven adult-onset diabetes subgroups. Here, we use self-normalizing neural networks (SNNN) to improve reproducibility of these data-driven diabetes subgroups in Mexican cohorts to extend its application to more diverse settings. RESEARCH DESIGN AND METHODS: We trained SNNN and compared it with k-means clustering to classify diabetes subgroups in a multiethnic and representative population-based National Health and Nutrition Examination Survey (NHANES) datasets with all available measures (training sample: NHANES-III, n=1132; validation sample: NHANES 1999-2006, n=626). SNNN models were then applied to four Mexican cohorts (SIGMA-UIEM, n=1521; Metabolic Syndrome cohort, n=6144; ENSANUT 2016, n=614 and CAIPaDi, n=1608) to characterize diabetes subgroups in Mexicans according to treatment response, risk for chronic complications and risk factors for the incidence of each subgroup. RESULTS: SNNN yielded four reproducible clinical profiles (obesity related, insulin deficient, insulin resistant, age related) in NHANES and Mexican cohorts even without C-peptide measurements. We observed in a population-based survey a high prevalence of the insulin-deficient form (41.25%, 95% CI 41.02% to 41.48%), followed by obesity-related (33.60%, 95% CI 33.40% to 33.79%), age-related (14.72%, 95% CI 14.63% to 14.82%) and severe insulin-resistant groups. A significant association was found between the SLC16A11 diabetes risk variant and the obesity-related subgroup (OR 1.42, 95% CI 1.10 to 1.83, p=0.008). Among incident cases, we observed a greater incidence of mild obesity-related diabetes (n=149, 45.0%). In a diabetes outpatient clinic cohort, we observed increased 1-year risk (HR 1.59, 95% CI 1.01 to 2.51) and 2-year risk (HR 1.94, 95% CI 1.13 to 3.31) for incident retinopathy in the insulin-deficient group and decreased 2-year diabetic retinopathy risk for the obesity-related subgroup (HR 0.49, 95% CI 0.27 to 0.89). CONCLUSIONS: Diabetes subgroup phenotypes are reproducible using SNNN; our algorithm is available as web-based tool. Application of these models allowed for better characterization of diabetes subgroups and risk factors in Mexicans that could have clinical applications.

Predicting Mortality Due to SARS-CoV-2: A Mechanistic Score Relating Obesity and Diabetes to COVID-19 Outcomes in Mexico.

BACKGROUND: The SARS-CoV-2 outbreak poses a challenge to health care systems due to its high complication rates in patients with cardiometabolic diseases. Here, we identify risk factors and propose a clinical score to predict COVID-19 lethality, including specific factors for diabetes and obesity, and its role in improving risk prediction. METHODS: We obtained data of confirmed and negative COVID-19 cases and their demographic and health characteristics from the General Directorate of Epidemiology of the Mexican Ministry of Health. We investigated specific risk factors associated to COVID-19 positivity and mortality and explored the impact of diabetes and obesity on modifying COVID-19-related lethality. Finally, we built a clinical score to predict COVID-19 lethality. RESULTS: Among the 177 133 subjects at the time of writing this report (May 18, 2020), we observed 51 633 subjects with SARS-CoV-2 and 5,332 deaths. Risk factors for lethality in COVID-19 include early-onset diabetes, obesity, chronic obstructive pulmonary disease, advanced age, hypertension, immunosuppression, and chronic kidney disease (CKD); we observed that obesity mediates 49.5% of the effect of diabetes on COVID-19 lethality. Early-onset diabetes conferred an increased risk of hospitalization and obesity conferred an increased risk for intensive care unit admission and intubation. Our predictive score for COVID-19 lethality included age ≥ 65 years, diabetes, early-onset diabetes, obesity, age < 40 years, CKD, hypertension, and immunosuppression and significantly discriminates lethal from non-lethal COVID-19 cases (C-statistic = 0.823). CONCLUSIONS: Here, we propose a mechanistic approach to evaluate the risk for complications and lethality attributable to COVID-19, considering the effect of obesity and diabetes in Mexico. Our score offers a clinical tool for quick determination of high-risk susceptibility patients in a first-contact scenario.