Validity of hospital diagnostic codes to identify SARS-CoV-2 infections in reference to polymerase chain reaction results: a descriptive study.

BACKGROUND: In 2020, International Statistical Classification of Diseases and Related Health Problems, 10th Revision (ICD-10) codes were created for laboratory-confirmed SARS-CoV-2 infections. We assessed the operating characteristics of ICD-10 discharge diagnostic code U07.1 within the General Medicine Inpatient Initiative (GEMINI). METHODS: GEMINI assembles hospitalization data (including administrative ICD-10 discharge diagnostic codes, laboratory results and demographic data) from hospitals in Ontario, Canada. We studied adults (age ≥ 18 yr) admitted during 2020 and tested at least once for SARS-CoV-2 via polymerase chain reaction (PCR) during (or within 48 h before) hospitalization. With PCR results as the reference standard, we calculated sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for ICD-10 code U07.1 hospital discharge diagnostic codes. Analyses were stratified by demographic data, calendar period and timing of the first test (within or after 48 h of hospital admission). RESULTS: In 11 852 hospitalizations with at least 1 SARS-CoV-2 PCR test, 444 (3.7%) were positive. The sensitivity of code U07.1 to identify SARS-CoV-2 infection was 97.8%, specificity was 99.5%, PPV was 88.2% and NPV was 99.9%. Operating characteristics were similar in most stratified analyses, but the specificity and PPV were lower if the first SARS-CoV-2 test was done more than 48 hours after admission. INTERPRETATION: The sensitivity, specificity, PPV and NPV of code U07.1 were high. This supports using code U07.1 to identify SARS-CoV-2 infection in hospitalization data.

Genetics of longitudinal kidney function in children and adults with systemic lupus erythematosus.

OBJECTIVES: Genome-wide association studies (GWAS) have identified loci associated with estimated glomerular filtration rate (eGFR). Few LN risk loci have been identified to date. We tested the association of SLE and eGFR polygenic risk scores (PRS) with repeated eGFR measures from children and adults with SLE. METHODS: Patients from two tertiary care lupus clinics that met ≥4 ACR and/or SLICC criteria for SLE were genotyped on the Illumina MEGA or Omni1-Quad arrays. PRSs were calculated for SLE and eGFR, using published weighted GWA-significant alleles. eGFR was calculated using the CKD-EPI and Schwartz equations. We tested the effect of eGFR- and SLE-PRSs on eGFR mean and variance, adjusting for age at diagnosis, sex, ancestry, follow-up time, and clinical event flags. RESULTS: We included 1158 SLE patients (37% biopsy-confirmed LN) with 36 733 eGFR measures over a median of 7.6 years (IQR: 3.9-15.3). LN was associated with lower within-person mean eGFR [LN: 93.8 (s.d. 26.4) vs non-LN: 101.6 (s.d. 17.7) mL/min per 1.73 m2; P < 0.0001] and higher variance [LN median: 157.0 (IQR: 89.5, 268.9) vs non-LN median: 84.9 (IQR: 46.9, 138.2) (mL/min per 1.73 m2)2; P < 0.0001]. Increasing SLE-PRSs were associated with lower mean eGFR and greater variance, while increasing eGFR-PRS was associated with increased eGFR mean and variance. CONCLUSION: We observed significant associations between SLE and eGFR PRSs and repeated eGFR measurements, in a large cohort of children and adults with SLE. Longitudinal eGFR may serve as a powerful alternative outcome to LN categories for discovery of LN risk loci.

Genetics of osteonecrosis in children and adults with systemic lupus erythematosus.

OBJECTIVES: Genetics plays an important role in SLE risk, as well as osteonecrosis (ON), a significant and often debilitating complication of SLE. We aimed to identify genetic risk loci for ON in people with childhood-onset (cSLE) and adult-onset (aSLE) SLE. METHODS: We enrolled participants from two tertiary care centres who met classification criteria for SLE. Participants had prospectively collected clinical data and were genotyped on a multiethnic array. Un-genotyped single nucleotide polymorphisms (SNPs) were imputed, and ancestry was inferred using principal components (PCs). Our outcome was symptomatic ON confirmed by imaging. We completed time-to-ON and logistic regression of ON genome-wide association studies (GWASs) with covariates for sex, age of SLE diagnosis, five PCs for ancestry, corticosteroid use and selected SLE manifestations. We conducted separate analyses for cSLE and aSLE and meta-analysed results using inverse-variance weighting. Genome-wide significance was P < 5 × 10-8. RESULTS: The study included 940 participants with SLE, 87% female and 56% with cSLE. ON was present in 7.6% (n = 71). Median age of SLE diagnosis was 16.9 years (interquartile range [IQR]: 13.5, 29.3), with median follow-up of 8.0 years (IQR: 4.2, 15.7). Meta-GWAS of cSLE and aSLE time-to-ON of 4 431 911 SNPs identified a significant Chr.2 SNP, rs34118383 (minor allele frequency = 0.18), intronic to WIPF1 (hazard ratio = 3.2 [95% CI: 2.2, 4.8]; P = 1.0 × 10-8). CONCLUSION: We identified an intronic WIPF1 variant associated with a 3.2 times increased hazard for ON (95% CI: 2.2, 4.8; P = 1.0 × 10-8) during SLE follow-up, independent of corticosteroid exposure. The effect of the SNP on time-to-ON was similar in cSLE and aSLE. This novel discovery represents a potential ON risk locus. Our results warrant replication.

Genome-Wide Sequencing Identified Rare Genetic Variants for Childhood-Onset Monogenic Lupus.

OBJECTIVE: Genetics play an important role in systemic lupus erythematosus (SLE) pathogenesis. We calculated the prevalence of rare variants in known monogenic lupus genes among children suspected of monogenic lupus. METHODS: We completed paired-end genome-wide sequencing (whole genome sequencing [WGS] or whole exome sequencing) in patients suspected of monogenic lupus, and focused on 36 monogenic lupus genes. We prioritized rare (minor allele frequency < 1%) exonic, nonsynonymous, and splice variants with predicted pathogenicity classified as deleterious variants (Combined Annotation Dependent Depletion [CADD], PolyPhen2, and Sorting Intolerant From Tolerant [SIFT] scores). Additional filtering restricted to predicted damaging variants by considering reported zygosity. In those with WGS (n = 69), we examined copy number variants (CNVs) > 1 kb in size. We created additive non-HLA and HLA SLE genetic risk scores (GRSs) using common SLE-risk single-nucleotide polymorphisms. We tested the relationship between SLE GRSs and the number of rare variants with multivariate logistic models, adjusted for sex, ancestry, and age of diagnosis. RESULTS: The cohort included 71 patients, 80% female, with a mean age at diagnosis of 8.9 (SD 3.2) years. We identified predicted damaging variants in 9 (13%) patients who were significantly younger at diagnosis compared to those without a predicted damaging variant (6.8 [SD 2.1] years vs 9.2 [SD 3.2] years, P = 0.01). We did not identify damaging CNVs. There was no significant association between non-HLA or HLA SLE GRSs and the odds of carrying ≥ 1 rare variant in multivariate analyses. CONCLUSION: In a cohort of patients with suspected monogenic lupus who underwent genome-wide sequencing, 13% carried rare predicted damaging variants for monogenic lupus. Additional studies are needed to validate our findings.

Hemophagocytic Lymphohistiocytosis Gene Variants in Childhood-Onset Systemic Lupus Erythematosus With Macrophage Activation Syndrome.

OBJECTIVE: Macrophage activation syndrome (MAS), a life-threatening complication of systemic lupus erythematosus (SLE), resembles familial hemophagocytic lymphohistiocytosis (HLH), an inherited disorder of hyperinflammation. We compared the proportion of patients with childhood-onset SLE (cSLE) with and without MAS who carried low-frequency HLH nonsynonymous variants. METHODS: We enrolled patients from the Lupus Clinic at SickKids, Toronto. Demographic and clinical features were extracted from the SLE database and ancestry was genetically inferred using multiethnic genotyping array data. Patients with MAS (based on expert diagnosis) underwent either paired-end whole-exome sequencing (WES; read depth: 70-118X) or whole-genome sequencing (WGS). Patients without MAS had WGS (read depth: 37-40X). In 16 HLH genes, we prioritized low-frequency (minor allele frequency [MAF] < 0.05) exonic nonsynonymous variants. We compared the proportion of patients with and without MAS carrying HLH variants (Fisher exact test, P < 0.05). MAFs were compared to an ancestrally matched general population (Trans-Omics for Precision Medicine [TOPMed] and Genome Aggregation Database [gnomAD]). RESULTS: The study included 81 patients with cSLE, 19 of whom had MAS. We identified 47 unique low-frequency nonsynonymous HLH variants. There was no difference in the proportion of patients with and without MAS carrying ≥ 1 HLH variants (37% vs 47%, P = 0.44). The MAS cohort did not carry more HLH variants when compared to an ancestrally matched general population. CONCLUSION: In a single-center multiethnic cSLE cohort, we found no difference in the proportion of patients with MAS carrying nonsynonymous HLH genetic variants compared to patients without MAS. To our knowledge, this is the first study to examine the frequency of HLH genetic variants in relation to MAS among patients with cSLE. Future studies are required to validate our findings.

Timing of Childhood-Onset Systemic Lupus Erythematosus Diagnosis Relative to Menarche and the Impact on Final Adult Height.

OBJECTIVE: The aim of this study was to examine the impact of timing of a childhood-onset systemic lupus erythematosus (SLE) diagnosis relative to menarchal status, on final height, accounting for disease-associated factors. METHODS: We conducted a cohort study of female patients age <18 years at childhood-onset SLE diagnosis, followed at a tertiary care pediatric center from July 1982 to March 2016 and restricted to patients with documented age of menarche and final height. We compared final height between patients diagnosed pre- and postmenarche. We tested the association of the timing of childhood-onset SLE diagnosis with final height, adjusted for ethnicity, in linear regression models. We performed subgroup analyses of patients with growth during follow-up, additionally adjusting for average daily corticosteroid dose and disease activity. RESULTS: Of 401 female childhood-onset SLE patients in the study, 115 patients (29%) were diagnosed premenarche and 286 (71%) postmenarche. Patients diagnosed premenarche were older at menarche compared with patients diagnosed postmenarche (mean ± SD age 13.5 ± 1.4 versus 12.5 ± 1.3 years; P < 0.001). The mean ± SD final height for girls diagnosed postmenarche (161.4 ± 6.9 cm) was greater than for those diagnosed premenarche (158.8 ± 7.3 cm; P = 0.001). In regression analysis, those diagnosed postmenarche were significantly taller than those diagnosed premenarche, as adjusted for ethnicity and disease severity (mean ± SD ß = 2.6 ± 0.7 cm; P = 0.0006). CONCLUSION: In this large cohort study of girls with childhood-onset SLE, patients diagnosed postmenarche achieved a taller final height than those diagnosed premenarche, even after accounting for ethnicity and disease severity.

Schizophrenia Genetics and Neuropsychiatric Features in Childhood-onset Systemic Lupus Erythematosus.

OBJECTIVE: We examined the association between schizophrenia genetic susceptibility loci and neuropsychiatric systemic lupus erythematosus (NPSLE) features in childhood-onset SLE (cSLE) participants. METHODS: Study participants from the Lupus Clinic at the Hospital for Sick Children, Toronto, met ≥ 4 of the American College of Rheumatology and/or SLE International Collaborating Clinics SLE classification criteria and were genotyped using the Illumina Multi-Ethnic Global Array or the Global Screening Array. Ungenotyped single-nucleotide polymorphisms (SNPs) were imputed, and ancestry was genetically inferred. We calculated 2 additive schizophrenia-weighted polygenic risk scores (PRS) using (1) genome-wide significant SNPs (P < 5 × 10-8), and (2) an expanded list of SNPs with significance at P < 0.05. We defined 2 outcomes compared to absence of NPSLE features: (1) any NPSLE feature, and (2) subtypes of NPSLE features (psychosis and nonpsychosis NPSLE). We completed logistic and multinomial regressions, first adjusted for inferred ancestry only and then added for variables significantly associated with NPSLE in our cohort (P < 0.05). RESULTS: We included 513 participants with cSLE. Median age at diagnosis was 13.8 years (IQR 11.2-15.6), 83% were female, and 31% were of European ancestry. An increasing schizophrenia genome-wide association PRS was not associated with NPSLE (OR 1.04, 95% CI 0.87-1.26, P = 0.62), nor with the NPSLE subtypes, psychosis (OR 0.97, 95% CI 0.73-1.29, P = 0.84) and other nonpsychosis NPSLE (OR 1.08, 95% CI 0.88-1.34, P = 0.45), in ancestry-adjusted models. Results were similar for the model including covariates (ancestry, malar rash, oral/nasal ulcers, arthritis, lymphopenia, Coombs-positive hemolytic anemia, lupus anticoagulant, and anticardiolipin antibodies) and for the expanded PRS estimates. CONCLUSION: We did not observe an association between known risk loci for schizophrenia and NPSLE in a multiethnic cSLE cohort. This work warrants further validation.

Predicting Macrophage Activation Syndrome in Childhood-onset Systemic Lupus Erythematosus Patients at Diagnosis.

OBJECTIVE: Macrophage activation syndrome (MAS), a life-threatening inflammatory complication, is increasingly recognized in childhood-onset systemic lupus erythematosus (cSLE). It can be a challenge to differentiate active cSLE from MAS. We generated decision rules for discriminating MAS from active cSLE in newly diagnosed patients. METHODS: We conducted a retrospective cohort study of consecutive, newly diagnosed, active cSLE patients with fever, requiring hospital admission to The Hospital for Sick Children from January 2003 to December 2007 (cohort 1) and January 2008 to December 2013 (cohort 2). All patients met ≥ 4 American College of Rheumatology or Systemic Lupus International Collaborating Clinics criteria, and were steroid-naïve and infection-free. MAS was diagnosed based on expert opinion. Recursive partitioning was applied to each cohort to derive a decision rule based on clinical and laboratory features, distinguishing MAS from non-MAS cSLE. Each decision rule was applied to the alternate, independent cohort. Sensitivity and specificity of these decision rules were compared to existing criteria. RESULTS: Cohort 1 (n = 34) and cohort 2 (n = 41) each had 10 patients with MAS. Recursive partitioning in cohort 1 identified ferritin ≥ 699 µg/L as the sole best discriminator between MAS and non-MAS patients (R2 = 0.48), and in cohort 2, ferritin ≥ 1107 µg/L was the best discriminator for MAS, followed by lymphocytes < 0.72 × 103/mm3 (R2 = 0.52). Cross-validation of our decision rules maintained 90-100% sensitivity and 65-85% specificity. CONCLUSION: Our decision rule demonstrated improved performance compared to preliminary guidelines for MAS in cSLE from the Lupus Working Group of the Paediatric Rheumatology European Society and familial hemophagocytic lymphohistiocytosis diagnostic criteria. Validation in independent cohorts is required.