Clinical frailty and polypharmacy in older emergency critical care patients: a single-centre retrospective case series.

BACKGROUND AND OBJECTIVES: Admission of complex and frail patients to critical care units is common. Little is known about the relationship between clinical frailty and polypharmacy measures in critical care patients or how a critical care admission affects polypharmacy.We sought to: (1) Describe the extent and relationship between clinical frailty and polypharmacy in a cohort of older emergency general critical care patients, and to (2) Describe the effect of the critical care pathway on patient polypharmacy measures. METHODS: A retrospective evaluation was undertaken in all patients ≥70 years of age, admitted as emergencies to the general critical care units of a single large UK academic hospital, over a 2-year period (March 2016 to February 2018) (n=762). Patient Clinical Frailty Scale (CFS) and polypharmacy measures on admission were described and association was tested. Medication changes and documentation on care transitions were analysed in a randomly selected convenience cohort of critical care survivors (n=77). RESULTS: On admission patients had a median of 9 (5;12) medicines, of which a median of 3 (2;5) were high-risk medicines. Polypharmacy (5-9 medicines) and hyperpolypharmacy (≥10 medicines) occurred in 80.7% (615/762) and 43.2% (329/762) of patients, respectively. A degree of frailty was the standard (median CFS 4 (3;5)) with 45.7% (348/762) CFS 4-5 and 20% (153/762) CFS ≥6. The patient median CFS increased by 1 with polypharmacy classification increments (p<0.001). In the survivor cohort, a median of 6 (4;8) and 5 (4;8) medication changes occurred on critical care and hospital discharges, respectively. A minority of patients had detailed medication continuity plans on care transitions. CONCLUSIONS: Polypharmacy and frailty were very common in this UK single-centre cohort of older emergency critical care patients. There was a significant association between the degree of polypharmacy and frailty score. The critical care pathway created extensive changes in patient medication therapy. Medication changes on care transitions often lacked detailed documentation.

Common and rare variant associations with clonal haematopoiesis phenotypes.

Clonal haematopoiesis involves the expansion of certain blood cell lineages and has been associated with ageing and adverse health outcomes1-5. Here we use exome sequence data on 628,388 individuals to identify 40,208 carriers of clonal haematopoiesis of indeterminate potential (CHIP). Using genome-wide and exome-wide association analyses, we identify 24 loci (21 of which are novel) where germline genetic variation influences predisposition to CHIP, including missense variants in the lymphocytic antigen coding gene LY75, which are associated with reduced incidence of CHIP. We also identify novel rare variant associations with clonal haematopoiesis and telomere length. Analysis of 5,041 health traits from the UK Biobank (UKB) found relationships between CHIP and severe COVID-19 outcomes, cardiovascular disease, haematologic traits, malignancy, smoking, obesity, infection and all-cause mortality. Longitudinal and Mendelian randomization analyses revealed that CHIP is associated with solid cancers, including non-melanoma skin cancer and lung cancer, and that CHIP linked to DNMT3A is associated with the subsequent development of myeloid but not lymphoid leukaemias. Additionally, contrary to previous findings from the initial 50,000 UKB exomes6, our results in the full sample do not support a role for IL-6 inhibition in reducing the risk of cardiovascular disease among CHIP carriers. Our findings demonstrate that CHIP represents a complex set of heterogeneous phenotypes with shared and unique germline genetic causes and varied clinical implications.

Breath analysis for detection and trajectory monitoring of acute respiratory distress syndrome in swine.

Despite the enormous impact on human health, acute respiratory distress syndrome (ARDS) is poorly defined, and its timely diagnosis is difficult, as is tracking the course of the syndrome. The objective of this pilot study was to explore the utility of breath collection and analysis methodologies to detect ARDS through changes in the volatile organic compound (VOC) profiles present in breath. Five male Yorkshire mix swine were studied and ARDS was induced using both direct and indirect lung injury. An automated portable gas chromatography device developed in-house was used for point of care breath analysis and to monitor swine breath hourly, starting from initiation of the experiment until the development of ARDS, which was adjudicated based on the Berlin criteria at the breath sampling points and confirmed by lung biopsy at the end of the experiment. A total of 67 breath samples (chromatograms) were collected and analysed. Through machine learning, principal component analysis and linear discrimination analysis, seven VOC biomarkers were identified that distinguished ARDS. These represent seven of the nine biomarkers found in our breath analysis study of human ARDS, corroborating our findings. We also demonstrated that breath analysis detects changes 1-6 h earlier than the clinical adjudication based on the Berlin criteria. The findings provide proof of concept that breath analysis can be used to identify early changes associated with ARDS pathogenesis in swine. Its clinical application could provide intensive care clinicians with a noninvasive diagnostic tool for early detection and continuous monitoring of ARDS.

Exome sequencing and analysis of 454,787 UK Biobank participants.

A major goal in human genetics is to use natural variation to understand the phenotypic consequences of altering each protein-coding gene in the genome. Here we used exome sequencing1 to explore protein-altering variants and their consequences in 454,787 participants in the UK Biobank study2. We identified 12 million coding variants, including around 1 million loss-of-function and around 1.8 million deleterious missense variants. When these were tested for association with 3,994 health-related traits, we found 564 genes with trait associations at P ≤ 2.18 × 10-11. Rare variant associations were enriched in loci from genome-wide association studies (GWAS), but most (91%) were independent of common variant signals. We discovered several risk-increasing associations with traits related to liver disease, eye disease and cancer, among others, as well as risk-lowering associations for hypertension (SLC9A3R2), diabetes (MAP3K15, FAM234A) and asthma (SLC27A3). Six genes were associated with brain imaging phenotypes, including two involved in neural development (GBE1, PLD1). Of the signals available and powered for replication in an independent cohort, 81% were confirmed; furthermore, association signals were generally consistent across individuals of European, Asian and African ancestry. We illustrate the ability of exome sequencing to identify gene-trait associations, elucidate gene function and pinpoint effector genes that underlie GWAS signals at scale.

Rapid breath analysis for acute respiratory distress syndrome diagnostics using a portable two-dimensional gas chromatography device.

Acute respiratory distress syndrome (ARDS) is the most severe form of acute lung injury, responsible for high mortality and long-term morbidity. As a dynamic syndrome with multiple etiologies, its timely diagnosis is difficult as is tracking the course of the syndrome. Therefore, there is a significant need for early, rapid detection and diagnosis as well as clinical trajectory monitoring of ARDS. Here, we report our work on using human breath to differentiate ARDS and non-ARDS causes of respiratory failure. A fully automated portable 2-dimensional gas chromatography device with high peak capacity (> 200 at the resolution of 1), high sensitivity (sub-ppb), and rapid analysis capability (~ 30 min) was designed and made in-house for on-site analysis of patients' breath. A total of 85 breath samples from 48 ARDS patients and controls were collected. Ninety-seven elution peaks were separated and detected in 13 min. An algorithm based on machine learning, principal component analysis (PCA), and linear discriminant analysis (LDA) was developed. As compared to the adjudications done by physicians based on the Berlin criteria, our device and algorithm achieved an overall accuracy of 87.1% with 94.1% positive predictive value and 82.4% negative predictive value. The high overall accuracy and high positive predicative value suggest that the breath analysis method can accurately diagnose ARDS. The ability to continuously and non-invasively monitor exhaled breath for early diagnosis, disease trajectory tracking, and outcome prediction monitoring of ARDS may have a significant impact on changing practice and improving patient outcomes. Graphical abstract.

NPHS2 V260E Is a Frequent Cause of Steroid-Resistant Nephrotic Syndrome in Black South African Children.

INTRODUCTION: In South Africa (SA), steroid-resistant nephrotic syndrome (SRNS) is more frequent in black than in Indian children. METHODS: Seeking a genetic basis for this disparity, we enrolled 33 Indian and 31 black children with steroid-sensitive nephrotic syndrome (SSNS) and SRNS from KwaZulu-Natal, SA; SRNS children underwent kidney biopsy. We sequenced NPHS2 and genotyped APOL1 in 15 SSNS and 64 SRNS unrelated patients and 104 controls and replicated results in 18 black patients with steroid-resistant focal segmental glomerulosclerosis (SR-FSGS). Known FSGS genes (n = 21) were sequenced in a subset of patients. RESULTS: Homozygosity for NPHS2 V260E was found in 8 of 30 black children with SRNS (27%); all 260E/E carriers had SR-FSGS. Combining SR-FSGS patients from the 2 groups, 14 of 42 (33%) were homozygous for V260E. One black control was heterozygous for V260E; no Indian patients or controls were carriers. Haplotype analysis indicated that homozygosity for V260E was not explained by cryptic consanguinity. Children with NPHS2 260E/E developed SRNS at earlier age than noncarriers (34 vs. 78 months, P = 0.01), and none achieved partial or complete remission (0% vs. 47%, P = 0.002). APOL1 variants did not associate with NS. Sequencing FSGS genes identified a CD2AP predicted pathogenic variant in the heterozygous state in 1 Indian case with SR-FSGS. CONCLUSION: NPHS2 260E/E was present in one-third of black FSGS patients, was absent in black controls and Indian patients, and affected patients were unresponsive to therapy. Genotyping V260E in black children from South Africa with NS will identify a substantial group with SR-FSGS, potentially sparing these children biopsy and ineffective steroid treatment.

Transethnic, Genome-Wide Analysis Reveals Immune-Related Risk Alleles and Phenotypic Correlates in Pediatric Steroid-Sensitive Nephrotic Syndrome.

Background Steroid-sensitive nephrotic syndrome (SSNS) is a childhood disease with unclear pathophysiology and genetic architecture. We investigated the genomic basis of SSNS in children recruited in Europe and the biopsy-based North American NEPTUNE cohort.Methods We performed three ancestry-matched, genome-wide association studies (GWAS) in 273 children with NS (Children Cohort Nephrosis and Virus [NEPHROVIR] cohort: 132 European, 56 African, and 85 Maghrebian) followed by independent replication in 112 European children, transethnic meta-analysis, and conditional analysis. GWAS alleles were used to perform glomerular cis-expression quantitative trait loci studies in 39 children in the NEPTUNE cohort and epidemiologic studies in GWAS and NEPTUNE (97 children) cohorts.Results Transethnic meta-analysis identified one SSNS-associated single-nucleotide polymorphism (SNP) rs1063348 in the 3' untranslated region of HLA-DQB1 (P=9.3×10-23). Conditional analysis identified two additional independent risk alleles upstream of HLA-DRB1 (rs28366266, P=3.7×10-11) and in the 3' untranslated region of BTNL2 (rs9348883, P=9.4×10-7) within introns of HCG23 and LOC101929163 These three risk alleles were independent of the risk haplotype DRB1*07:01-DQA1*02:01-DQB1*02:02 identified in European patients. Increased burden of risk alleles across independent loci was associated with higher odds of SSNS. Increased burden of risk alleles across independent loci was associated with higher odds of SSNS, with younger age of onset across all cohorts, and with increased odds of complete remission across histologies in NEPTUNE children. rs1063348 associated with decreased glomerular expression of HLA-DRB1, HLA-DRB5, and HLA-DQB1.Conclusions Transethnic GWAS empowered discovery of three independent risk SNPs for pediatric SSNS. Characterization of these SNPs provide an entry for understanding immune dysregulation in NS and introducing a genomically defined classification.

Exome-wide Association Study Identifies GREB1L Mutations in Congenital Kidney Malformations.

Renal agenesis and hypodysplasia (RHD) are major causes of pediatric chronic kidney disease and are highly genetically heterogeneous. We conducted whole-exome sequencing in 202 case subjects with RHD and identified diagnostic mutations in genes known to be associated with RHD in 7/202 case subjects. In an additional affected individual with RHD and a congenital heart defect, we found a homozygous loss-of-function (LOF) variant in SLIT3, recapitulating phenotypes reported with Slit3 inactivation in the mouse. To identify genes associated with RHD, we performed an exome-wide association study with 195 unresolved case subjects and 6,905 control subjects. The top signal resided in GREB1L, a gene implicated previously in Hoxb1 and Shha signaling in zebrafish. The significance of the association, which was p = 2.0 × 10-5 for novel LOF, increased to p = 4.1 × 10-6 for LOF and deleterious missense variants combined, and augmented further after accounting for segregation and de novo inheritance of rare variants (joint p = 2.3 × 10-7). Finally, CRISPR/Cas9 disruption or knockdown of greb1l in zebrafish caused specific pronephric defects, which were rescued by wild-type human GREB1L mRNA, but not mRNA containing alleles identified in case subjects. Together, our study provides insight into the genetic landscape of kidney malformations in humans, presents multiple candidates, and identifies SLIT3 and GREB1L as genes implicated in the pathogenesis of RHD.

Using Population Genetics to Interrogate the Monogenic Nephrotic Syndrome Diagnosis in a Case Cohort.

To maximize clinical benefits of genetic screening of patients with nephrotic syndrome (NS) to diagnose monogenic causes, reliably distinguishing NS-causing variants from the background of rare, noncausal variants prevalent in all genomes is vital. To determine the prevalence of monogenic NS in a North American case cohort while accounting for background prevalence of genetic variation, we sequenced 21 implicated monogenic NS genes in 312 participants from the Nephrotic Syndrome Study Network and 61 putative controls from the 1000 Genomes Project (1000G). These analyses were extended to available sequence data from approximately 2500 subjects from the 1000G. A typical pathogenicity filter identified causal variants for NS in 4.2% of patients and 5.8% of subjects from the 1000G. We devised a more stringent pathogenicity filtering strategy, reducing background prevalence of causal variants to 1.5%. When applying this stringent filter to patients, prevalence of monogenic NS was 2.9%; of these patients, 67% were pediatric, and 44% had FSGS on biopsy. The rate of complete remission did not associate with monogenic classification. Thus, we identified factors contributing to inaccurate monogenic classification of NS and developed a more accurate variant filtering strategy. The prevalence and clinical correlates of monogenic NS in this sporadically affected cohort differ substantially from those reported for patients referred for genetic analysis. Particularly in unselected, population-based cases, considering putative causal variants in known NS genes from a probabilistic rather than a deterministic perspective may be more precise. We also introduce GeneVetter, a web tool for monogenic assessment of rare disease.

Integrative Genomics Identifies Novel Associations with APOL1 Risk Genotypes in Black NEPTUNE Subjects.

APOL1 variants have been associated with renal phenotypes in blacks. To refine clinical outcomes and discover mechanisms of APOL1-associated kidney injury, we analyzed clinical and genomic datasets derived from 90 black subjects in the Nephrotic Syndrome Study Network (NEPTUNE), stratified by APOL1 risk genotype. Ninety subjects with proteinuria ≥0.5 g/d were enrolled at first biopsy for primary nephrotic syndrome and followed. Clinical outcomes were determined, and renal histomorphometry and sequencing of Mendelian nephrotic syndrome genes were performed. APOL1 variants were genotyped, and glomerular and tubulointerstitial transcriptomes from protocol renal biopsy cores were analyzed for differential and correlative gene expression. Analyses were performed under the recessive model (high-risk genotype defined by two risk alleles). APOL1 high-risk genotype was significantly associated with a 17 ml/min per 1.73 m(2) lower eGFR and a 69% reduction in the probability of complete remission at any time, independent of histologic diagnosis. Neither APOL1 risk group was enriched for Mendelian mutations. On renal biopsy, high-risk genotype was associated with increased fractional interstitial area, interstitial fibrosis, and tubular atrophy. Risk genotype was not associated with intrarenal APOL1 mRNA expression levels. Differential expression analysis demonstrated an increased steady-state level of five genes associated with the high-risk genotype (CXCL9, CXCL11, and UBD in glomerulus; SNOR14B and MUC13 in tubulointerstitium). APOL1 tubulointerstitial coexpression analysis showed coexpression of APOL1 mRNA levels with a group of intrarenal transcripts that together were associated with increased interstitial fibrosis and tubular atrophy. These data indicate the high-risk APOL1 genotype confers renal risk across histopathologic diagnoses.

A simulation to analyze feature selection methods utilizing gene ontology for gene expression classification.

Gene expression profile classification is a pivotal research domain assisting in the transformation from traditional to personalized medicine. A major challenge associated with gene expression data classification is the small number of samples relative to the large number of genes. To address this problem, researchers have devised various feature selection algorithms to reduce the number of genes. Recent studies have been experimenting with the use of semantic similarity between genes in Gene Ontology (GO) as a method to improve feature selection. While there are few studies that discuss how to use GO for feature selection, there is no simulation study that addresses when to use GO-based feature selection. To investigate this, we developed a novel simulation, which generates binary class datasets, where the differentially expressed genes between two classes have some underlying relationship in GO. This allows us to investigate the effects of various factors such as the relative connectedness of the underlying genes in GO, the mean magnitude of separation between differentially expressed genes denoted by δ, and the number of training samples. Our simulation results suggest that the connectedness in GO of the differentially expressed genes for a biological condition is the primary factor for determining the efficacy of GO-based feature selection. In particular, as the connectedness of differentially expressed genes increases, the classification accuracy improvement increases. To quantify this notion of connectedness, we defined a measure called Biological Condition Annotation Level BCAL(G), where G is a graph of differentially expressed genes. Our main conclusions with respect to GO-based feature selection are the following: (1) it increases classification accuracy when BCAL(G) ≥ 0.696; (2) it decreases classification accuracy when BCAL(G) ≤ 0.389; (3) it provides marginal accuracy improvement when 0.389