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To accelerate medical breakthroughs, the All of Us Research Program aims to collect data from over one million participants. This report outlines processes used to construct the All of Us Social Determinants of Health (SDOH) survey and presents the psychometric characteristics of SDOH survey measures in All of Us. A consensus process was used to select SDOH measures, prioritizing concepts validated in diverse populations and other national cohort surveys. Survey item non-response was calculated, and Cronbachs alpha was used to analyze psychometric properties of scales. Multivariable logistic regression models were used to examine associations between demographic categories and item non-response. Twenty-nine percent (N = 117,783) of eligible All of Us participants submitted SDOH survey data for these analyses. Most scales had less than 5% incalculable scores due to item non-response. Patterns of item non-response were seen by racial identity, educational attainment, income level, survey language, and age. Internal consistency reliability was greater than 0.80 for almost all scales and most demographic groups. The SDOH survey demonstrated good to excellent reliability across several measures and within multiple populations underrepresented in biomedical research. Bias due to survey non-response and item non-response will be monitored and addressed as the survey is fielded more completely.

Abstract Large mammals with general habitat needs can persist throughout mixed used landscapes, however, human-wildlife conflict frequently leads to their restriction to protected areas. Conservation efforts, especially for reducing conflicts with humans, can enhance tolerance of humans towards species like Asian elephants (Elephas maximus) in human-dominated landscapes. Here, we examine how elephant use in the Chure Terai Madhesh Landscape (CTML) covering the entire elephant range of Nepal changed between 2012 and 2020 in relationship to protection status and environmental conditions. We systematically surveyed ~ 42,000 km2 of potential habitat, by dividing the study area into 159 grid cells of 15 × 15 km2 and recorded elephant signs during the cool, dry season in three years (2012, 2018 and 2020). We analyzed the survey data in a single-species, multi-season (dynamic) occupancy modeling framework to test hypotheses regarding the influence of environmental conditions and protected area status on landscape use by elephants over time. The best-supported model included protected area effects on initial use, colonization, and detection probability as well as temporal variation in colonization and detection probability. Initial use and colonization rates were higher in protected areas, however elephants increasingly used cells located both inside and outside the protected areas, and the difference in use between protected areas and outside declined as elephants use became prevalent across most of the landscape. While elephant use was patchily distributed in the first year of surveys consistent with past descriptions of four sub-populations, elephant use consolidated into a western and eastern region in subsequent years with a gap in their distribution occurring between Chitwan and Bardiya National Parks. Our manuscript highlights the increasing landscape use by elephants in both protected areas and areas outside protected areas and suggests that management interventions that focus on reducing conflicts can promote greater use of both protected areas and areas outside of protected areas.

Abstract Identifying cancer risk groups by multi-omics has attracted researchers in their quest to find biomarkers from diverse risk-related omics. Stratifying the patients into cancer risk groups using genomics is essential for clinicians for pre-prevention treatment to improve the survival time for patients and identify the appropriate therapy strategies. This study proposes a multi-omics framework that can extract the features from various omics simultaneously. The framework employs autoencoders to learn the non-linear representation of the data and applies tensor analysis for feature learning. Further, the clustering method is used to stratify the patients into multiple cancer risk groups. Several omics were included in the experiments, namely methylation, somatic copy-number variation (SCNV), micro RNA (miRNA) and RNA sequencing (RNAseq) from two cancer types, including Glioma and Breast Invasive Carcinoma from the TCGA dataset. The results of this study are promising, as evidenced by the survival analysis and classification models, which outperformed the state-of-the-art. The patients can be significantly (p-value

Abstract To accelerate medical breakthroughs, the All of Us Research Program aims to collect data from over one million participants. This report outlines processes used to construct the All of Us Social Determinants of Health (SDOH) survey and presents the psychometric characteristics of SDOH survey measures in All of Us. A consensus process was used to select SDOH measures, prioritizing concepts validated in diverse populations and other national cohort surveys. Survey item non-response was calculated, and Cronbach’s alpha was used to analyze psychometric properties of scales. Multivariable logistic regression models were used to examine associations between demographic categories and item non-response. Twenty-nine percent (N = 117,783) of eligible All of Us participants submitted SDOH survey data for these analyses. Most scales had less than 5% incalculable scores due to item non-response. Patterns of item non-response were seen by racial identity, educational attainment, income level, survey language, and age. Internal consistency reliability was greater than 0.80 for almost all scales and most demographic groups. The SDOH survey demonstrated good to excellent reliability across several measures and within multiple populations underrepresented in biomedical research. Bias due to survey non-response and item non-response will be monitored and addressed as the survey is fielded more completely.

Abstract Huntington's disease (HD) is a progressive neurodegenerative disorder caused by CAG trinucleotide repeat expansions in exon 1 of the HTT gene. In addition to germline CAG expansions, somatic repeat expansions in neurons also contribute to HD pathogenesis. The DNA mismatch repair gene, MSH3, identified as a genetic modifier of HD onset and progression, promotes somatic CAG expansions, and thus presents a potential therapeutic target. However, what extent of MSH3 protein reduction is needed to attenuate somatic CAG expansions and elicit therapeutic benefits in HD disease models is less clear. In our study, we employed potent di-siRNAs to silence mouse Msh3 mRNA expression in a dose-dependent manner in HdhQ111/+ mice and correlated somatic Htt CAG instability with MSH3 protein levels from simultaneously isolated DNA and protein after siRNA treatment. Our results reveal a linear correlation with a proportionality constant of ~ 1 between the prevention of somatic Htt CAG expansions and MSH3 protein expression in vivo, supporting MSH3 as a rate-limiting step in somatic expansions. Intriguingly, despite a 75% reduction in MSH3 protein levels, striatal nuclear HTT aggregates remained unchanged. We also note that evidence for nuclear Msh3 mRNA that is inaccessible to RNA interference was found, and that MSH6 protein in the striatum was upregulated following MSH3 knockdown in HdhQ111/+ mice. These results provide important clues to address critical questions for the development of therapeutic molecules targeting MSH3 as a potential therapeutic target for HD.

Abstract Optic disc pit maculopathy (ODP-M) is a rare complication of optic disc pit which can cause irreversible visual impairment. The aim of this study is to evaluate the anatomical and functional outcomes and pattern of resolution of ODP-M following vitrectomy with posterior vitreous detachment (PVD) induction and scleral tissue plug for treatment of ODP-M without ILM peeling, laser or use of long term gas/tamponade or head positioning. This retrospective study included 7 patients with ODP-M, meeting the inclusion criteria. Patients were followed up for 6 months. Complete anatomical success was defined as “Total resolution of all the fluid in retinal compartments”. All of the patients had complete resolution of the optic pit maculopathy following surgery. The mean duration for complete resolution was 18.3 weeks. Pattern of resolution of ODP-M was found to be resolution of the subretinal fluid (SRF) followed by disappearance of the retinoschitic lesions (RL) and finally disappearance of macular edema (ME). The proposed minimally invasive procedure (MIP) can produce comparably good and equally reliable results for the treatment of ODP-M.

Abstract Exposure to particulate matter less than 2.5 µm in diameter (PM2.5) is a cause of concern in cities and major emission regions of northern India. An intensive field campaign involving the states of Punjab, Haryana and Delhi national capital region (NCR) was conducted in 2022 using 29 Compact and Useful PM2.5 Instrument with Gas sensors (CUPI-Gs). Continuous observations show that the PM2.5 in the region increased gradually from

Abstract Land-use conversion affects soil organic carbon (SOC) dynamics. Therefore, an in-depth study of change in SOC, SOC pool, fractions of SOC and enzymatic activities of soil microbial biomass carbon (SMBC) and dehydrogenase (DHA) with the conversion of forest land to jhum, fallow jhum and settle cultivation use has been undertaken on the hills of Arunachal Pradesh of India. Geo-referenced soil samples from eight different locations, each from different land uses were collected at three depth. One part of the soil sample had been used for the analysis of SOC and its carbon fraction. The second portion was kept in a deep freezer for determining SMBC and DHA. The third part was used for the analysis of bulk density. The result revealed that the highest loss of SOC pool was recorded in jhum land (41.8 to 13.4%), and the labile carbon was also found to decrease in jhum land. The highest SMBC was observed on the surface soil of the natural forest; the highest DHA was found in the natural forest; and the lowest DHA was recorded in jhum land. This study found that the converting natural forest to jhum reduces SOC storage, enzymatic activities and C fractions significantly whereas fallow jhum shows sign of recovery because all of these parameters improved when compared to the jhum land-use system. This study also confirms that the fallow period helps restore the initial situation.

Abstract Aerosols play important roles in modulations of cloud properties and hydrological cycle by decreasing the size of cloud droplets with the increase of aerosols under the condition of fixed liquid water path, which is known as the first aerosol indirect effect or Twomey-effect or microphysical effect. Using high-quality aerosol data from surface observations and statistically decoupling the influence of meteorological factors, we show that highly loaded aerosols can counter this microphysical effect through the radiative effect to result both the decrease and increase of cloud droplet size depending on liquid water path in water clouds. The radiative effect due to increased aerosols reduces the moisture content, but increases the atmospheric stability at higher altitudes, generating conditions favorable for cloud top entrainment and cloud droplet coalescence. Such radiatively driven cloud droplet coalescence process is relatively stronger in thicker clouds to counter relatively weaker microphysical effect, resulting the increase of cloud droplet size with the increase of aerosol loading; and vice-versa in thinner clouds. Overall, the study suggests the prevalence of both negative and positive relationships between cloud droplet size and aerosol loading in highly polluted regions.

Abstract Serum N-glycan profiling studies during the past decades have shown robust associations between N-glycan changes and various biological conditions, including infections, in humans. Similar studies are scarcer for other mammals, despite the tremendous potential of serum N-glycans as biomarkers for infectious diseases in animal models of human disease and in the veterinary context. To expand the knowledge of serum N-glycan profiles in important mammalian model systems, in this study, we combined MALDI-TOF-MS analysis and HILIC-UPLC profiling of released N-glycans together with glycosidase treatments to characterize the glycan structures present in rhesus macaque serum. We used this baseline to monitor changes in serum N-glycans during infection with Brugia malayi, a parasitic nematode of humans responsible for lymphatic filariasis, in a longitudinal cohort of infected rhesus macaques. Alterations of the HILIC-UPLC profile, notably of abundant structures, became evident as early as 5 weeks post-infection. Given its prominent role in the immune response, contribution of immunoglobulin G to serum N-glycans was investigated. Finally, comparison with similar N-glycan profiling performed during infection with the dog heartworm Dirofilaria immitis suggests that many changes observed in rhesus macaque serum N-glycans are specific for lymphatic filariasis.

Abstract Evidence suggests that β-secretase (BACE1), which cleaves Amyloid Precursor Protein (APP) to form sAPPβ and amyloid-β, is elevated in Alzheimer's disease (AD) brains and biofluids and, thus, BACE1 is a therapeutic target for this devastating disease. The direct product of BACE1 cleavage of APP, sAPPβ, serves as a surrogate marker of BACE1 activity in the central nervous system. This biomarker could be utilized to better understand normal APP processing, aberrant processing in the disease setting, and modulations to processing during therapeutic intervention. In this paper, we present a method for measuring the metabolism of sAPPβ and another APP proteolytic product, sAPPα, in vivo in humans using stable isotope labeling kinetics, paired with immunoprecipitation and liquid chromatography/tandem mass spectrometry. The method presented herein is robust, reproducible, and precise, and allows for the study of these analytes by taking into account their full dynamic potential as opposed to the traditional methods of absolute concentration quantitation that only provide a static view of a dynamic system. A study of in vivo cerebrospinal fluid sAPPβ and sAPPα kinetics using these methods could reveal novel insights into pathophysiological mechanisms of AD, such as increased BACE1 processing of APP.

Abstract Muscle diseases share common pathological features suggesting common underlying mechanisms. We hypothesized there is a common set of genes dysregulated across muscle diseases compared to healthy muscle and that these genes correlate with severity of muscle disease. We performed meta-analysis of transcriptional profiles of muscle biopsies from human muscle diseases and healthy controls. Studies obtained from public microarray repositories fulfilling quality criteria were divided into six categories: (i) immobility, (ii) inflammatory myopathies, (iii) intensive care unit (ICU) acquired weakness (ICUAW), (iv) congenital muscle diseases, (v) chronic systemic diseases, (vi) motor neuron disease. Patient cohorts were separated in discovery and validation cohorts retaining roughly equal proportions of samples for the disease categories. To remove bias towards a specific muscle disease category we repeated the meta-analysis five times by removing data sets corresponding to one muscle disease class at a time in a “leave-one-disease-out” analysis. We used 636 muscle tissue samples from 30 independent cohorts to identify a 52 gene signature (36 up-regulated and 16 down-regulated genes). We validated the discriminatory power of this signature in 657 muscle biopsies from 12 additional patient cohorts encompassing five categories of muscle diseases with an area under the receiver operating characteristic curve of 0.91, 83% sensitivity, and 85.3% specificity. The expression score of the gene signature inversely correlated with quadriceps muscle mass (r = −0.50, p-value = 0.011) in ICUAW and shoulder abduction strength (r = −0.77, p-value = 0.014) in amyotrophic lateral sclerosis (ALS). The signature also positively correlated with histologic assessment of muscle atrophy in ALS (r = 0.88, p-value = 1.62 × 10–3) and fibrosis in muscular dystrophy (Jonckheere trend test p-value = 4.45 × 10–9). Our results identify a conserved transcriptional signature associated with clinical and histologic muscle disease severity. Several genes in this conserved signature have not been previously associated with muscle disease severity.

Abstract Non-Alcoholic Fatty Liver Disease (NAFLD) is a progressive liver disease that affects up to 30% of worldwide population, of which up to 25% progress to Non-Alcoholic SteatoHepatitis (NASH), a severe form of the disease that involves inflammation and predisposes the patient to liver cirrhosis. Despite its epidemic proportions, there is no reliable diagnostics that generalizes to global patient population for distinguishing NASH from NAFLD. We performed a comprehensive multicohort analysis of publicly available transcriptome data of liver biopsies from Healthy Controls (HC), NAFLD and NASH patients. Altogether we analyzed 812 samples from 12 different datasets across 7 countries, encompassing real world patient heterogeneity. We used 7 datasets for discovery and 5 datasets were held-out for independent validation. Altogether we identified 130 genes significantly differentially expressed in NASH versus a mixed group of NAFLD and HC. We show that our signature is not driven by one particular group (NAFLD or HC) and reflects true biological signal. Using a forward search we were able to downselect to a parsimonious set of 19 mRNA signature with mean AUROC of 0.98 in discovery and 0.79 in independent validation. Methods for consistent diagnosis of NASH relative to NAFLD are urgently needed. We showed that gene expression data combined with advanced statistical methodology holds the potential to serve basis for development of such diagnostic tests for the unmet clinical need.

Abstract Enlarged perivascular spaces (EPVS), specifically in stroke patients, has been shown to strongly correlate with other measures of small vessel disease and cognitive impairment at 1 year follow-up. Typical grading of EPVS is often challenging and time consuming and is usually based on a subjective visual rating scale. The purpose of the current study was to develop an interpretable, 3D neural network for grading enlarged perivascular spaces (EPVS) severity at the level of the basal ganglia using clinical-grade imaging in a heterogenous acute stroke cohort, in the context of total cerebral small vessel disease (CSVD) burden. T2-weighted images from a retrospective cohort of 262 acute stroke patients, collected in 2015 from 5 regional medical centers, were used for analyses. Patients were given a label of 0 for none-to-mild EPVS (

Abstract Predicting the severity of COVID-19 remains an unmet medical need. Our objective was to develop a blood-based host-gene-expression classifier for the severity of viral infections and validate it in independent data, including COVID-19. We developed a logistic regression-based classifier for the severity of viral infections and validated it in multiple viral infection settings including COVID-19. We used training data (N = 705) from 21 retrospective transcriptomic clinical studies of influenza and other viral illnesses looking at a preselected panel of host immune response messenger RNAs. We selected 6 host RNAs and trained logistic regression classifier with a cross-validation area under curve of 0.90 for predicting 30-day mortality in viral illnesses. Next, in 1417 samples across 21 independent retrospective cohorts the locked 6-RNA classifier had an area under curve of 0.94 for discriminating patients with severe vs. non-severe infection. Next, in independent cohorts of prospectively (N = 97) and retrospectively (N = 100) enrolled patients with confirmed COVID-19, the classifier had an area under curve of 0.89 and 0.87, respectively, for identifying patients with severe respiratory failure or 30-day mortality. Finally, we developed a loop-mediated isothermal gene expression assay for the 6-messenger-RNA panel to facilitate implementation as a rapid assay. With further study, the classifier could assist in the risk assessment of COVID-19 and other acute viral infections patients to determine severity and level of care, thereby improving patient management and reducing healthcare burden.

Abstract Two strains of mice (BALB/c and CB6F1) were vaccinated with a range of Bacille Calmette-Guérin (BCG) Danish doses from 3 × 105 to 30 CFU/mouse, followed by aerosol infection with Mtb (H37Rv or West-Beijing HN878 strain). The results indicated that both strains of mice when infected with HN878 exhibited significant protection in their lungs with BCG doses at 3 × 105—3000 CFU (BALB/c) and 3 × 105—300 CFU (CB6F1). Whereas, a significant protection was seen in both strains of mice with BCG doses at 3 × 105—300 CFU when infected with H37Rv. A significant increase in the frequencies of BCG-specific IFNγ+ IL2+ TNFα+ CD4 T cells in the BCG doses at 3 × 105—3000 CFU (BALB/c) and 3 × 105—300 CFU (CB6F1) was seen. The IFNγ+ IL2+ TNFα+ CD4 T cells correlated with the Mtb burden in the lungs of HN878 infected mice (BALB/c and CB6F1) whereas, IFNγ+ TNFα+ CD4 T cells correlated with the BALB/c mice infected with H37Rv or HN878. The BCG dose at 3000 CFU (an equivalent single human dose in the mice by body weight) is protective in both strains of mice infected with H37Rv or HN878 and may serve an interesting dose to test new TB vaccine in a preclinical animal model.

Abstract Several clinical calculators predict intensive care unit (ICU) mortality, however these are cumbersome and often require 24 h of data to calculate. Retrospective studies have demonstrated the utility of whole blood transcriptomic analysis in predicting mortality. In this study, we tested prospective validation of an 11-gene messenger RNA (mRNA) score in an ICU population. Whole blood mRNA from 70 subjects in the Stanford ICU Biobank with samples collected within 24 h of Emergency Department presentation were used to calculate an 11-gene mRNA score. We found that the 11-gene score was highly associated with 60-day mortality, with an area under the receiver operating characteristic curve of 0.68 in all patients, 0.77 in shock patients, and 0.98 in patients whose primary determinant of prognosis was acute illness. Subjects with the highest quartile of mRNA scores were more likely to die in hospital (40% vs 7%, p 24 h after emergency department presentation. Tests will target a 30-min turnaround time, allowing for rapid results early in admission. Moving forward, this test may provide valuable real-time prognostic information to improve triage decisions and allow for enrichment of clinical trials.

Abstract COVID-19 related restrictions lowered particulate matter and trace gas concentrations across cities around the world, providing a natural opportunity to study effects of anthropogenic activities on emissions of air pollutants. In this paper, the impact of sudden suspension of human activities on air pollution was analyzed by studying the change in satellite retrieved NO2 concentrations and top-down NOx emission over the urban and rural areas around Delhi. NO2 was chosen for being the most indicative of emission intensity due to its short lifetime of the order of a few hours in the planetary boundary layer. We present a robust temporal comparison of Ozone Monitoring Instrument (OMI) retrieved NO2 column density during the lockdown with the counterfactual baseline concentrations, extrapolated from the long-term trend and seasonal cycle components of NO2 using observations during 2015 to 2019. NO2 concentration in the urban area of Delhi experienced an anomalous relative change ranging from 60.0% decline during the Phase 1 of lockdown (March 25–April 13, 2020) to 3.4% during the post-lockdown Phase 5. In contrast, we find no substantial reduction in NO2 concentrations over the rural areas. To segregate the impact of the lockdown from the meteorology, weekly top-down NOx emissions were estimated from high-resolution TROPOspheric Monitoring Instrument (TROPOMI) retrieved NO2 by accounting for horizontal advection derived from the steady state continuity equation. NOx emissions from urban Delhi and power plants exhibited a mean decline of 72.2% and 53.4% respectively in Phase 1 compared to the pre-lockdown business-as-usual phase. Emission estimates over urban areas and power-plants showed a good correlation with activity reports, suggesting the applicability of this approach for studying emission changes. A higher anomaly in emission estimates suggests that comparison of only concentration change, without accounting for the dynamical and photochemical conditions, may mislead evaluation of lockdown impact. Our results shall also have a broader impact for optimizing bottom-up emission inventories.

Abstract Pleistocene glaciations facilitated climatic oscillations that caused for enormous heterogeneity in landscapes, and consequently affected demography and distribution patterns of the mountain endemic species. In this context, we investigated demographic history and population genetic structure of red panda, distributed along the geographical proximity in the southern edge of the Qinghai-Tibetan Plateau. Bayesian based phylogeny demonstrated that red panda diverged about 0.30 million years ago (CI 0.23–0.39) into two phylogenetic (sub) species, that correspond to the middle-late Pleistocene transition. The observed intraspecific clades with respect to Himalayan and Chinese red panda indicated restricted gene flow resulting from the Pleistocene glaciations in the eastern and southern Tibetan Plateau. We found Himalayan red panda population at least in KL-India declined abruptly in last 5–10 thousand years after being under demographic equilibrium. We suggest revisiting the ongoing conservation activities through cross border collaboration by developing multi-nationals, and multi-lateral species-oriented conservation action plans to support the red panda populations in transboundary landscapes.