Heterogeneity in statin responses explained by variation in the human gut microbiome.

BACKGROUND: Statins remain one of the most prescribed medications worldwide. While effective in decreasing atherosclerotic cardiovascular disease risk, statin use is associated with adverse effects for a subset of patients, including disrupted metabolic control and increased risk of type 2 diabetes. METHODS: We investigated the potential role of the gut microbiome in modifying patient responses to statin therapy across two independent cohorts (discovery n = 1,848, validation n = 991). Microbiome composition was assessed in these cohorts using stool 16S rRNA amplicon and shotgun metagenomic sequencing, respectively. Microbiome associations with markers of statin on-target and adverse effects were tested via a covariate-adjusted interaction analysis framework, utilizing blood metabolomics, clinical laboratory tests, genomics, and demographics data. FINDINGS: The hydrolyzed substrate for 3-hydroxy-3-methylglutarate-coenzyme-A (HMG-CoA) reductase, HMG, emerged as a promising marker for statin on-target effects in cross-sectional cohorts. Plasma HMG levels reflected both statin therapy intensity and known genetic markers for variable statin responses. Through exploring gut microbiome associations between blood-derived measures of statin effectiveness and adverse metabolic effects of statins, we find that heterogeneity in statin responses was consistently associated with variation in the gut microbiome across two independent cohorts. A Bacteroides-enriched and diversity-depleted gut microbiome was associated with more intense statin responses, both in terms of on-target and adverse effects. CONCLUSIONS: With further study and refinement, gut microbiome monitoring may help inform precision statin treatment. FUNDING: This research was supported by the M.J. Murdock Charitable Trust, WRF, NAM Catalyst Award, and NIH grant U19AG023122 awarded by the NIA.

Manifestations of Alzheimer's disease genetic risk in the blood are evident in a multiomic analysis in healthy adults aged 18 to 90.

Genetics play an important role in late-onset Alzheimer's Disease (AD) etiology and dozens of genetic variants have been implicated in AD risk through large-scale GWAS meta-analyses. However, the precise mechanistic effects of most of these variants have yet to be determined. Deeply phenotyped cohort data can reveal physiological changes associated with genetic risk for AD across an age spectrum that may provide clues to the biology of the disease. We utilized over 2000 high-quality quantitative measurements obtained from blood of 2831 cognitively normal adult clients of a consumer-based scientific wellness company, each with CLIA-certified whole-genome sequencing data. Measurements included: clinical laboratory blood tests, targeted chip-based proteomics, and metabolomics. We performed a phenome-wide association study utilizing this diverse blood marker data and 25 known AD genetic variants and an AD-specific polygenic risk score (PGRS), adjusting for sex, age, vendor (for clinical labs), and the first four genetic principal components; sex-SNP interactions were also assessed. We observed statistically significant SNP-analyte associations for five genetic variants after correction for multiple testing (for SNPs in or near NYAP1, ABCA7, INPP5D, and APOE), with effects detectable from early adulthood. The ABCA7 SNP and the APOE2 and APOE4 encoding alleles were associated with lipid variability, as seen in previous studies; in addition, six novel proteins were associated with the e2 allele. The most statistically significant finding was between the NYAP1 variant and PILRA and PILRB protein levels, supporting previous functional genomic studies in the identification of a putative causal variant within the PILRA gene. We did not observe associations between the PGRS and any analyte. Sex modified the effects of four genetic variants, with multiple interrelated immune-modulating effects associated with the PICALM variant. In post-hoc analysis, sex-stratified GWAS results from an independent AD case-control meta-analysis supported sex-specific disease effects of the PICALM variant, highlighting the importance of sex as a biological variable. Known AD genetic variation influenced lipid metabolism and immune response systems in a population of non-AD individuals, with associations observed from early adulthood onward. Further research is needed to determine whether and how these effects are implicated in early-stage biological pathways to AD. These analyses aim to complement ongoing work on the functional interpretation of AD-associated genetic variants.

Multiple early factors anticipate post-acute COVID-19 sequelae.

Post-acute sequelae of COVID-19 (PASC) represent an emerging global crisis. However, quantifiable risk factors for PASC and their biological associations are poorly resolved. We executed a deep multi-omic, longitudinal investigation of 309 COVID-19 patients from initial diagnosis to convalescence (2-3 months later), integrated with clinical data and patient-reported symptoms. We resolved four PASC-anticipating risk factors at the time of initial COVID-19 diagnosis: type 2 diabetes, SARS-CoV-2 RNAemia, Epstein-Barr virus viremia, and specific auto-antibodies. In patients with gastrointestinal PASC, SARS-CoV-2-specific and CMV-specific CD8+ T cells exhibited unique dynamics during recovery from COVID-19. Analysis of symptom-associated immunological signatures revealed coordinated immunity polarization into four endotypes, exhibiting divergent acute severity and PASC. We find that immunological associations between PASC factors diminish over time, leading to distinct convalescent immune states. Detectability of most PASC factors at COVID-19 diagnosis emphasizes the importance of early disease measurements for understanding emergent chronic conditions and suggests PASC treatment strategies.

Integrated analysis of plasma and single immune cells uncovers metabolic changes in individuals with COVID-19.

A better understanding of the metabolic alterations in immune cells during severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection may elucidate the wide diversity of clinical symptoms experienced by individuals with coronavirus disease 2019 (COVID-19). Here, we report the metabolic changes associated with the peripheral immune response of 198 individuals with COVID-19 through an integrated analysis of plasma metabolite and protein levels as well as single-cell multiomics analyses from serial blood draws collected during the first week after clinical diagnosis. We document the emergence of rare but metabolically dominant T cell subpopulations and find that increasing disease severity correlates with a bifurcation of monocytes into two metabolically distinct subsets. This integrated analysis reveals a robust interplay between plasma metabolites and cell-type-specific metabolic reprogramming networks that is associated with disease severity and could predict survival.

Ambulatory Risk Models for the Long-Term Prevention of Sepsis: Retrospective Study.

BACKGROUND: Sepsis is a life-threatening condition that can rapidly lead to organ damage and death. Existing risk scores predict outcomes for patients who have already become acutely ill. OBJECTIVE: We aimed to develop a model for identifying patients at risk of getting sepsis within 2 years in order to support the reduction of sepsis morbidity and mortality. METHODS: Machine learning was applied to 2,683,049 electronic health records (EHRs) with over 64 million encounters across five states to develop models for predicting a patient's risk of getting sepsis within 2 years. Features were selected to be easily obtainable from a patient's chart in real time during ambulatory encounters. RESULTS: The models showed consistent prediction scores, with the highest area under the receiver operating characteristic curve of 0.82 and a positive likelihood ratio of 2.9 achieved with gradient boosting on all features combined. Predictive features included age, sex, ethnicity, average ambulatory heart rate, standard deviation of BMI, and the number of prior medical conditions and procedures. The findings identified both known and potential new risk factors for long-term sepsis. Model variations also illustrated trade-offs between incrementally higher accuracy, implementability, and interpretability. CONCLUSIONS: Accurate implementable models were developed to predict the 2-year risk of sepsis, using EHR data that is easy to obtain from ambulatory encounters. These results help advance the understanding of sepsis and provide a foundation for future trials of risk-informed preventive care.

Multi-cohort analysis of host immune response identifies conserved protective and detrimental modules associated with severity across viruses.

Viral infections induce a conserved host response distinct from bacterial infections. We hypothesized that the conserved response is associated with disease severity and is distinct between patients with different outcomes. To test this, we integrated 4,780 blood transcriptome profiles from patients aged 0 to 90 years infected with one of 16 viruses, including SARS-CoV-2, Ebola, chikungunya, and influenza, across 34 cohorts from 18 countries, and single-cell RNA sequencing profiles of 702,970 immune cells from 289 samples across three cohorts. Severe viral infection was associated with increased hematopoiesis, myelopoiesis, and myeloid-derived suppressor cells. We identified protective and detrimental gene modules that defined distinct trajectories associated with mild versus severe outcomes. The interferon response was decoupled from the protective host response in patients with severe outcomes. These findings were consistent, irrespective of age and virus, and provide insights to accelerate the development of diagnostics and host-directed therapies to improve global pandemic preparedness.

Characteristics and Factors Associated with COVID-19 Infection, Hospitalization, and Mortality Across Race and Ethnicity.

Background: Data on the characteristics of COVID-19 patients disaggregated by race/ethnicity remain limited. We evaluated the sociodemographic and clinical characteristics of patients across racial/ethnic groups and assessed their associations with COVID-19 outcomes. Methods: This retrospective cohort study examined 629,953 patients tested for SARS-CoV-2 in a large health system spanning California, Oregon, and Washington between March 1 and December 31, 2020. Sociodemographic and clinical characteristics were obtained from electronic health records. Odds of SARS-CoV-2 infection, COVID-19 hospitalization, and in-hospital death were assessed with multivariate logistic regression. Results: 570,298 patients with known race/ethnicity were tested for SARS-CoV-2, of whom 27.8% were non-White minorities. 54,645 individuals tested positive, with minorities representing 50.1%. Hispanics represented 34.3% of infections but only 13.4% of tests. While generally younger than White patients, Hispanics had higher rates of diabetes but fewer other comorbidities. 8,536 patients were hospitalized and 1,246 died, of whom 56.1% and 54.4% were non-White, respectively. Racial/ethnic distributions of outcomes across the health system tracked with state-level statistics. Increased odds of testing positive and hospitalization were associated with all minority races/ethnicities. Hispanic patients also exhibited increased morbidity, and Hispanic race/ethnicity was associated with in-hospital mortality (OR: 1.39 [95% CI: 1.14-1.70]). Conclusion: Major healthcare disparities were evident, especially among Hispanics who tested positive at a higher rate, required excess hospitalization and mechanical ventilation, and had higher odds of in-hospital mortality despite younger age. Targeted, culturally-responsive interventions and equitable vaccine development and distribution are needed to address the increased risk of poorer COVID-19 outcomes among minority populations.

Characteristics and Factors Associated With Coronavirus Disease 2019 Infection, Hospitalization, and Mortality Across Race and Ethnicity.

BACKGROUND: Data on the characteristics of coronavirus disease 2019 (COVID-19) patients disaggregated by race/ethnicity remains limited. We evaluated the sociodemographic and clinical characteristics of patients across racial/ethnic groups and assessed their associations with COVID-19 outcomes. METHODS: This retrospective cohort study examined 629 953 patients tested for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in a large health system spanning California, Oregon, and Washington between March 1 and December 31, 2020. Sociodemographic and clinical characteristics were obtained from electronic health records. Odds of SARS-CoV-2 infection, COVID-19 hospitalization, and in-hospital death were assessed with multivariate logistic regression. RESULTS: A total of 570 298 patients with known race/ethnicity were tested for SARS-CoV-2, of whom 27.8% were non-White minorities: 54 645 individuals tested positive, with minorities representing 50.1%. Hispanics represented 34.3% of infections but only 13.4% of tests. Although generally younger than White patients, Hispanics had higher rates of diabetes but fewer other comorbidities. A total of 8536 patients were hospitalized and 1246 died, of whom 56.1% and 54.4% were non-White, respectively. Racial/ethnic distributions of outcomes across the health system tracked with state-level statistics. Increased odds of testing positive and hospitalization were associated with all minority races/ethnicities. Hispanic patients also exhibited increased morbidity, and Hispanic race/ethnicity was associated with in-hospital mortality (odds ratio [OR], 1.39; 95% confidence interval [CI], 1.14-1.70). CONCLUSION: Major healthcare disparities were evident, especially among Hispanics who tested positive at a higher rate, required excess hospitalization and mechanical ventilation, and had higher odds of in-hospital mortality despite younger age. Targeted, culturally responsive interventions and equitable vaccine development and distribution are needed to address the increased risk of poorer COVID-19 outcomes among minority populations.

Multi-Omics Resolves a Sharp Disease-State Shift between Mild and Moderate COVID-19.

We present an integrated analysis of the clinical measurements, immune cells, and plasma multi-omics of 139 COVID-19 patients representing all levels of disease severity, from serial blood draws collected during the first week of infection following diagnosis. We identify a major shift between mild and moderate disease, at which point elevated inflammatory signaling is accompanied by the loss of specific classes of metabolites and metabolic processes. Within this stressed plasma environment at moderate disease, multiple unusual immune cell phenotypes emerge and amplify with increasing disease severity. We condensed over 120,000 immune features into a single axis to capture how different immune cell classes coordinate in response to SARS-CoV-2. This immune-response axis independently aligns with the major plasma composition changes, with clinical metrics of blood clotting, and with the sharp transition between mild and moderate disease. This study suggests that moderate disease may provide the most effective setting for therapeutic intervention.

Health and disease markers correlate with gut microbiome composition across thousands of people.

Variation in the human gut microbiome can reflect host lifestyle and behaviors and influence disease biomarker levels in the blood. Understanding the relationships between gut microbes and host phenotypes are critical for understanding wellness and disease. Here, we examine associations between the gut microbiota and ~150 host phenotypic features across ~3,400 individuals. We identify major axes of taxonomic variance in the gut and a putative diversity maximum along the Firmicutes-to-Bacteroidetes axis. Our analyses reveal both known and unknown associations between microbiome composition and host clinical markers and lifestyle factors, including host-microbe associations that are composition-specific. These results suggest potential opportunities for targeted interventions that alter the composition of the microbiome to improve host health. By uncovering the interrelationships between host diet and lifestyle factors, clinical blood markers, and the human gut microbiome at the population-scale, our results serve as a roadmap for future studies on host-microbe interactions and interventions.

Multiomic Immunophenotyping of COVID-19 Patients Reveals Early Infection Trajectories.

Host immune responses play central roles in controlling SARS-CoV2 infection, yet remain incompletely characterized and understood. Here, we present a comprehensive immune response map spanning 454 proteins and 847 metabolites in plasma integrated with single-cell multi-omic assays of PBMCs in which whole transcriptome, 192 surface proteins, and T and B cell receptor sequence were co-analyzed within the context of clinical measures from 50 COVID19 patient samples. Our study reveals novel cellular subpopulations, such as proliferative exhausted CD8 + and CD4 + T cells, and cytotoxic CD4 + T cells, that may be features of severe COVID-19 infection. We condensed over 1 million immune features into a single immune response axis that independently aligns with many clinical features and is also strongly associated with disease severity. Our study represents an important resource towards understanding the heterogeneous immune responses of COVID-19 patients and may provide key information for informing therapeutic development.

Early lexical development of children raised in institutional care in Russia.

Children abandoned to institutions display a host of developmental delays, including those involving general cognition and language. The majority of published studies focus on children over 3 years of age; little is known about whether these delays may be detected earlier when children undergo rapid lexical development. To investigate the early language development of children raised in institutional settings in the Russian Federation, we compared a group of children in institutional care (n = 36; 8-35 months) to their age-matched peers raised in biological families, who have never been institutionalized (n = 72) using the Russian version of the CDI. The results suggest that institutionalization is associated with pronounced delays in children's early language development with large and robust effect sizes. Among children with a history of institutionalization, these delays are also associated with difficulties in Daily Living skills, communication, and socialization.

Genome-Wide Homozygosity Mapping Reveals Genes Associated With Cognitive Ability in Children From Saudi Arabia.

Recent studies of the genetic foundations of cognitive ability rely on large samples (in extreme, hundreds of thousands) of individuals from relatively outbred populations of mostly European ancestry. Hypothesizing that the genetic foundation of cognitive ability depends on the broader population-specific genetic context, we performed a genome-wide association study and homozygosity mapping of cognitive ability estimates obtained through latent variable modeling in a sample of 354 children from a consanguineous population of Saudi Arabia. Approximately half of the sample demonstrated significantly elevated homozygosity levels indicative of inbreeding, and among those with elevated levels, homozygosity was negatively associated with cognitive ability. Further homozygosity mapping identified a specific run, inclusive of the GRIA4 gene, that survived corrections for multiple testing for association with cognitive ability. The results suggest that in a consanguineous population, a notable proportion of the variance in cognitive ability in the normal range in children might be regulated by population-specific mechanisms such as patterns of elevated homozygosity. This observation has implications for the field's understanding of the etiological bases of intelligence and its variability around the world.

Effects of early social deprivation on epigenetic statuses and adaptive behavior of young children: A study based on a cohort of institutionalized infants and toddlers.

Early social deprivation (i.e., an insufficiency or lack of parental care) has been identified as a significant adverse early experience that may affect multiple facets of child development and cause long-term outcomes in physical and mental health, cognition and behavior. Current research provides growing evidence that epigenetic reprogramming may be a mechanism modulating these effects of early adversities. This work aimed to investigate the impact of early institutionalization-the immersion in an extreme socially depriving environment in humans-on the epigenome and adaptive behavior of young children up to 4 years of age. We conducted a cross-sectional study involving two comparison groups: 29 children raised in orphanages and 29 children raised in biological families. Genome-wide DNA methylation profiles of blood cells were obtained using the Illumina MethylationEPIC array; the level of child adaptive functioning was assessed using the Vineland Adaptive Behavior Scales-II. In comparison to children raised in families, children residing in orphanages had both statistically significant deficits in multiple adaptive behavior domains and statistically significant differences in DNA methylation states. Moreover, some of these methylation states may directly modulate the behavioral deficits; according to preliminary estimates, about 7-14% of the deviation of adaptive behavior between groups of children may be determined by their difference in DNA methylation profiles. The duration of institutionalization had a significant impact on both the adaptive level and DNA methylation status of institutionalized children.

Language Outcomes in Adults with a History of Institutionalization: Behavioral and Neurophysiological Characterization.

Impoverished early care environments are associated with developmental deficits in children raised in institutional settings. Despite the accumulation of evidence regarding deficits in general cognitive functioning in this population, less is known about the impact of institutionalization on language development at the level of brain and behavior. We examined language outcomes in young adults and adolescents raised in institutions (n = 23) as compared to their socioeconomic status and age peers raised in biological families (n = 24) using a behavioral language assessment and linguistic event-related potentials (ERPs). Controlling for intelligence, adults with a history of institutionalization demonstrated deficits in lexical and grammatical development and spelling. Analyses of ERP data revealed significant group differences in the dynamic processing of linguistic stimuli. Adults with a history of institutionalization displayed reduced neural sensitivity to violations of word expectancy, leading to reduced condition effects for temporo-spatial factors that tentatively corresponded to the N200, P300/N400, and phonological mismatch negativity. The results suggest that language is a vulnerable domain in adults with a history of institutionalization, the deficits in which are not explained by general developmental delays, and point to the pivotal role of early linguistic environment in the development of the neural networks involved in language processing.

Common variation within the SETBP1 gene is associated with reading-related skills and patterns of functional neural activation.

Epidemiological population studies highlight the presence of substantial individual variability in reading skill, with approximately 5-10% of individuals characterized as having specific reading disability (SRD). Despite reported substantial heritability, typical for a complex trait, the specifics of the connections between reading and the genome are not understood. Recently, the SETBP1 gene has been implicated in several complex neurodevelopmental syndromes and disorders that impact language. Here, we examined the relationship between common polymorphisms in this gene, reading, and reading associated behaviors using data from an ongoing project on the genetic basis of SRD (n = 135). In addition, an exploratory analysis was conducted to examine the relationship between SETBP1 and brain activation using functional magnetic resonance imaging (fMRI; n = 73). Gene-based analyses revealed a significant association between SETBP1 and phonological working memory, with rs7230525 as the strongest associated single nucleotide polymorphism (SNP). fMRI analysis revealed that the rs7230525-T allele is associated with functional neural activation during reading and listening to words and pseudowords in the right inferior parietal lobule (IPL). These findings suggest that common genetic variation within SETBP1 is associated with reading behavior and reading-related brain activation patterns in the general population.

DNA methylation alterations in the genome of a toddler with cri-du-chat syndrome.

This manuscript reports on genomewide epigenetic alterations in cri-du-chat syndrome related to a partial aneusomy of chromosome 5. A systematic analysis of these alterations will open up new possibilities for the prognostic evaluation of CDCS patients and the development of new therapeutic interventions for reducing the severity of the disease.

What Reading Disability? Evidence for Multiple Latent Profiles of Struggling Readers in a Large Russian Sibpair Sample With at Least One Sibling at Risk for Reading Difficulties.

In this study, we performed a latent profile analysis of reading and related skills in a large ( n = 733) sibpair sample of Russian readers at risk for reading difficulties. The analysis suggested the presence of seven latent profiles, of which two were characterized by relatively high performance on measures of spelling and reading comprehension and the remaining five included severely as well as moderately affected readers with deficits in the domains of phonological, orthographic, and morphological processing. The results suggest that the development and manifestation of reading difficulties in Russian is mappable on a complex pattern of interactions between different types and severities of processing deficits. The results point to the psychological reality of multiple different suboptimal patterns of deficits in reading and reading-related skills and support the multifactorial view of the disorder, with intriguing implications for future neurobiological studies.

The BDNF Val66Met polymorphism is associated with structural neuroanatomical differences in young children.

The brain-derived neurotrophic factor (BDNF) Val66Met single nucleotide polymorphism (SNP) has been associated with individual differences in brain structure and function, and cognition. Research on BDNF's influence on brain and cognition has largely been limited to adults, and little is known about the association of this gene, and specifically the Val66Met polymorphism, with developing brain structure and emerging cognitive functions in children. We performed a targeted genetic association analysis on cortical thickness, surface area, and subcortical volume in 78 children (ages 6-10) who were Val homozygotes (homozygous Val/Val carriers) or Met carriers (Val/Met, Met/Met) for the Val66Met locus using Atlas-based brain segmentation. We observed greater cortical thickness for Val homozygotes in regions supporting declarative memory systems (anterior temporal pole/entorhinal cortex), consistent with adult findings. Met carriers had greater surface area in the prefrontal and parietal cortices and greater cortical thickness in lateral occipital/parietal cortex in contrast to prior adult findings that may relate to performance on cognitive tasks supported by these regions in Met carriers. Finally, we found larger right hippocampal volume in Met carriers, although inconsistent with adult findings (generally reports larger volumes for Val homozygotes), is consistent with a recent finding in children. Gene expression levels vary across different brain regions and across development and our findings highlight the need to consider this developmental change in explorations of BDNF-brain relationships. The impact of the BDNF Val66Met polymorphism on the structure of the developing brain therefore reflects regionally-specific developmental changes in BDNF expression and cortical maturation trajectories.