Biobank Samples Research Articles

Genetic and Phenotypic Features of Schizophrenia in the UK Biobank

Large-scale biobanks provide important opportunities for mental health research, but selection biases raise questions regarding the comparability of individuals with those in clinical research settings. To compare the genetic liability to psychiatric disorders in individuals with schizophrenia in the UK Biobank with individuals in the Psychiatric Genomics Consortium (PGC) and to compare genetic liability and phenotypic features with participants recruited from clinical settings. This cross-sectional study included participants from the population-based UK Biobank and schizophrenia samples recruited from clinical settings (CLOZUK, CardiffCOGS, Cardiff F-Series, and Cardiff Affected Sib-Pairs). Data were collected between January 1993 and July 2021. Data analysis was conducted between July 2021 and June 2023. A genome-wide association study of UK Biobank schizophrenia case-control status was conducted, and the results were compared with those from the PGC via genetic correlations. To test for differences with the clinical samples, polygenic risk scores (PRS) were calculated for schizophrenia, bipolar disorder, depression, and intelligence using PRS-CS. PRS and phenotypic comparisons were conducted using pairwise logistic regressions. The proportions of individuals with copy number variants associated with schizophrenia were compared using Firth logistic regression. The sample of 517 375 participants included 1438 UK Biobank participants with schizophrenia (550 [38.2%] female; mean [SD] age, 54.7 [8.3] years), 499 475 UK Biobank controls (271 884 [54.4%] female; mean [SD] age, 56.5 [8.1] years), and 4 schizophrenia research samples (4758 [28.9%] female; mean [SD] age, 38.2 [21.0] years). Liability to schizophrenia in UK Biobank was highly correlated with the latest genome-wide association study from the PGC (genetic correlation, 0.98; SE, 0.18) and showed the expected patterns of correlations with other psychiatric disorders. The schizophrenia PRS explained 6.8% of the variance in liability for schizophrenia case status in UK Biobank. UK Biobank participants with schizophrenia had significantly lower schizophrenia PRS than 3 of the clinically ascertained samples and significantly lower rates of schizophrenia-associated copy number variants than the CLOZUK sample. UK Biobank participants with schizophrenia had higher educational attainment and employment rates than the clinically ascertained schizophrenia samples, lower rates of smoking, and a later age of onset of psychosis. Individuals with schizophrenia in the UK Biobank, and likely other volunteer-based biobanks, represent those less severely affected. Their inclusion in wider studies should enhance the representation of the full spectrum of illness severity.

Assessment of Faecal Microbiota Transplant Stability in Deep-Freeze Conditions: A 12-Month ExVivo Viability Analysis.

Faecal microbiota transplantation (FMT) is an established treatment for Clostridioides difficile infection and is under investigation for other conditions. The availability of suitable donors and the logistics of fresh stool preparation present challenges, making frozen, biobanked stools an attractive alternative. This study aimed to evaluate the long-term viability of bacterial populations in faecal samples stored at -80°C for up to 12 months, supporting the feasibility of using frozen grafts for FMT. Fifteen faecal samples from nine healthy donors were processed, mixed with cryoprotectants and stored at -80°C. Samples were assessed at baseline and after 3, 6 and 12 months using quantitative culturing methods to determine the concentration of live bacteria. Quantitative analysis showed no significant decrease in bacterial viability over the 12-month period for both aerobic and anaerobic cultures (p = 0.09). At all timepoints, the coefficients of variability in colony-forming unit (CFU) counts were greater between samples (102 ± 21% and 100 ± 13% for aerobic and anaerobic cultures, respectively) than the variability between measurements of the same sample (30 ± 22% and 30 ± 19%). The study confirmed that faecal microbiota can be preserved with high viability in deep-freeze storage for up to a year, making allogenic FMT from biobanked samples a viable and safer option for patients. However, a multidonor approach may be beneficial to mitigate the risk of viability loss in any single donor sample.

Abstract 993: Comprehensive immunophenotypic strategies to enable equity in remote settings for improved cancer prognosis

Abstract Improved cancer prognosis begins with insights obtained from high quality data during clinical trials. Execution of longitudinal clinical trials in flow cytometry is complex, primarily due to logistical challenges in high quality sample collection. For instance, highly remote indigenous population centers are both disadvantaged in access to healthcare and often underrepresented in clinical trials. This paradox is highlighted in the case of Australian First Nations communities, for which lung cancer prevalence peaks in males at twice the magnitude of the general population. Our group has developed a novel blood “immune signature” that robustly predicts failure to make a clinical response to checkpoint therapies targeting the PD-1/PD-L1 pathway. Encouraged by these groundbreaking findings, which were achieved through applying a comprehensive 38-plex immunophenotyping CyTOF panel to biobanked cancer samples, recent advances in CyTOF technology now give us the opportunity to expand our clinical implementation to remote settings, with a further expanded panel to 50+ markers. CyTOF is the only technology that allows easily implemented remote asynchronous sample collection and the largest immunophenotyping panel that yields reproducible results. Asynchronous collection is uniquely enabled using a stable lyophilized large-scale staining panel and achieving comprehensive marker coverage in one panel minimizes blood sample required. Furthermore, the new technology enables a highly simplified workflow including blood collection and processing in remote locations to enable the simplest clinical trial infrastructure complexity and cost, easily implemented in current hospital lab environments. As such, this study is designed to ultimately demonstrate both clinical impact of the large panel and utility of CyTOF technology for highly simplified and robust workflow for multi-site clinical trials. This project has 3 phases; i) implementation and evaluation of the collection, analysis technique and data management of this new approach across multiple sites, ii) collection of samples for analysis both pre- and post- initiation of therapy to establish efficacy and optimize as necessary, and iii) blinded clinical trial. We will report on the first phase of this project which is implementing new workflow across clinical collection site, data integration and analysis. This workflow would enable highly simplified collection to access indigenous and under-served populations spread across remote sites in Australia. Citation Format: Natalie J. Smith, Michael Cohen, Julie Alipaz, Christina Loh, David King, Barbara Fazekas de St Groth, Helen M. McGuire. Comprehensive immunophenotypic strategies to enable equity in remote settings for improved cancer prognosis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 993.

Thyroid stimulating immunoglobulin concentration is associated with disease activity and predicts response to treatment with intravenous methylprednisolone in patients with Graves' orbitopathy.

Thyroid stimulating immunoglobulins (TSI) play a central role in the pathogenesis of Graves' orbitopathy (GO), while soluble interleukin-2 receptor (sIL-2R) is a marker for T-cell activity. We investigated TSI and sIL-2R levels in relation to thyroid function, disease activity and severity and response to treatment with intravenous methylprednisolone (IVMP) in patients with GO. TSI (bridge-based TSI binding assay), sIL-2R, TSH and fT4 levels were measured in biobank serum samples from 111 GO patients (37 male, 74 female; mean age 49.2 years old) and 25 healthy controls (5 male, 20 female; mean age 39.8 years old). Clinical characteristics and response to treatment were retrospectively retrieved from patient files. Higher sIL-2R levels were observed in GO patients compared to controls (p < 0.001). sIL-2R correlated with fT4 (r = 0.26), TSH (r = -0.40) and TSI (r = 0.21). TSI and sIL-2R concentrations were higher in patients with active compared to inactive GO (p < 0.001 and p < 0.05, respectively). Both TSI and sIL-2R correlated with total clinical activity score (CAS; r = 0.33 and r = 0.28, respectively) and with several individual CAS items. Cut-off levels for predicting active GO were 2.62 IU/L for TSI (AUC = 0.71, sensitivity 69%, specificity 69%) and 428 IU/mL for sIL-2R (AUC = 0.64, sensitivity 62%, specificity 62%). In multivariate testing higher TSI (p < 0.01), higher age (p < 0.001) and longer disease duration (p < 0.01) were associated with disease activity. TSI levels were higher in patients with a poor IVMP response (p = 0.048), while sIL-2R levels did not differ between responders and non-responders. TSI cut-off for predicting IVMP response was 19.4 IU/L (AUC = 0.69, sensitivity 50%, specificity 91%). In multivariate analysis TSI was the only independent predictor of response to IVMP (p < 0.05). High TSI levels are associated with active disease (cut-off 2.62 IU/L) and predict poor response to IVMP treatment (cut-off 19.4 IU/L) in GO. While sIL-2R correlates with disease activity, it is also related to thyroid function, making it less useful as an additional biomarker in GO.

Longitudinal Change in Serum Neurofilament Light Chain in Type 2 Diabetes and Early Diabetic Polyneuropathy: ADDITION-Denmark.

To investigate the longitudinal development of neurofilament light chain (NfL) levels in type 2 diabetes with and without diabetic polyneuropathy (+/-DPN) and to explore the predictive potential of NfL as a biomarker for DPN. We performed retrospective longitudinal case-control analysis of data from 178 participants of the Anglo-Danish-Dutch Study of Intensive Treatment in People with Screen-Detected Diabetes in Primary Care-Denmark (ADDITION-Denmark) cohort of people with screen-detected type 2 diabetes. Biobank samples acquired at the ADDITION-Denmark 5- and 10-year follow-ups were analyzed for serum NfL (s-NfL) using single-molecule array, and the results were compared with established reference material to obtain NfL z-scores. DPN was diagnosed according to Toronto criteria for confirmed DPN at the 10-year follow-up. s-NfL increased over time in +DPN (N = 39) and -DPN participants (N = 139) at levels above normal age-induced s-NfL increase. Longitudinal s-NfL change was greater in +DPN than in -DPN participants (17.4% [95% CI 4.3; 32.2] or 0.31 SD [95% CI 0.03; 0.60] higher s-NfL or NfL z-score increase in +DPN compared with -DPN). s-NfL at the 5-year follow-up was positively associated with nerve conduction studies at the 10-year follow-up (P = 0.02 to <0.001), but not with DPN risk. Areas under the curve (AUCs) for s-NfL were not inferior to AUCs for the Michigan Neuropathy Screening Instrument questionnaire score or vibration detection thresholds. Higher yearly s-NfL increase was associated with higher DPN risk (odds ratio 1.36 [95% CI 1.08; 1.71] per 1 ng/L/year). Our findings suggest that preceding s-NfL trajectories differ slightly between those with and without DPN and imply a possible biomarker value of s-NfL trajectories in DPN.

Glycated albumin in the detection of diabetes during COVID-19 hospitalization.

Diabetes has emerged as an important risk factor for COVID-19 adverse outcomes during hospitalization. We investigated whether the measurement of glycated albumin (GA) may be useful in detecting newly diagnosed diabetes during COVID-19 hospitalization. In this cross-sectional test accuracy study we evaluated HCPA Biobank data and samples from consecutive in-patients, from 30 March 2020 to 20 December 2020. ROC curves were used to analyse the performance of GA to detect newly diagnosed diabetes (patients without a previous diagnosis of diabetes and admission HbA1c ≥6.5%). A total of 184 adults (age 58.6 ± 16.6years) were enrolled, including 31 with newly diagnosed diabetes. GA presented AUCs of 0.739 (95% CI 0.642-0.948) to detect newly diagnosed diabetes. The GA cut-offs of 19.0% was adequate to identify newly diagnosed diabetes with high specificity (85.0%) but low sensitivity (48.4%). GA showed good performance to identify newly diagnosed diabetes and may be useful for identifying adults with the condition in COVID-19-related hospitalization.

ALISTER – Application for lipid stability evaluation and research

Background and aimsIn lipidomic and metabolomic studies, pre-analytical pitfalls enhance the risk of misusing resources such as time and money, as samples that are analyzed may not yield accurate or reliable data due to poor sample handling. Guidance and pre-analytic know-how are necessary for translation of omics technologies into routine clinical testing. The present work aims to enable decision making regarding sample stability in every phase of lipidomics- and metabolomics-centered studies. Materials and methodsData of multiple pre-analytic studies were aggregated into a database. Flexible approaches for evaluating these data were implemented in an RShiny-based web-application, tailored towards broad applicability in clinical and bioanalytic research. ResultsOur “Application for lipid stability evaluation & research” - ALISTER facilitates decision making on blood sample stability during lipidomic and metabolomic studies, such as biomarker research, analysis of biobank samples and clinical testing. The interactive tool gives sampling recommendations when planning sample collection or aids in the assessment of sample quality of experiments retrospectively. ConclusionALISTER is available for use under https://itmp.shinyapps.io/alister/. The application enables and simplifies data-driven decision making concerning pre-analytic blood sample handling and fits the needs of clinical investigations from multiple perspectives.

Exploring the contribution of lifestyle to the impact of education on the risk of cancer through Mendelian randomization analysis

Educational attainment (EA) has been linked to the risk of several types of cancer, despite having no expected direct biological connection. In this paper, we investigate the mediating role of alcohol consumption, smoking, vegetable consumption, fruit consumption and body mass index (BMI) in explaining the effect of EA on 7 cancer groupings. Large-scale genome wide association study (GWAS) results were used to construct the genetic instrument for EA and the lifestyle factors. We conducted GWAS in the UK Biobank sample in up to 335,024 individuals to obtain genetic association data for the cancer outcomes. Univariable and multivariable two-sample Mendelian randomization (MR) analyses and mediation analyses were then conducted to explore the causal effect and mediating proportions of these relations. MR mediation analysis revealed that reduced lifetime smoking index accounted for 81.7% (49.1% to 100%) of the protective effect of higher EA on lower respiratory cancer. Moreover, the effect of higher EA on lower respiratory cancer was mediated through vegetable consumption by 10.2% (4.4% to 15.9%). We found genetic evidence that the effect of EA on groups of cancer is due to behavioural changes in avoiding well established risk factors such as smoking and vegetable consuming.

Patient derived tumoroids of high grade neuroendocrine neoplasms for more personalized therapies

There are no therapeutic predictive biomarkers or representative preclinical models for high-grade gastroenteropancreatic neuroendocrine neoplasms (GEP-NEN), a highly aggressive, fatal, and heterogeneous malignancy. We established patient-derived (PD) tumoroids from biobanked tissue samples of advanced high-grade GEP-NEN patients and applied this model for targeted rapid ex vivo pharmacotyping, next-generation sequencing, and perturbational profiling. We used tissue-matched PD tumoroids to profile individual patients, compared ex vivo drug response to patients’ clinical response to chemotherapy, and investigated treatment-induced adaptive stress responses.PD tumoroids recapitulated biological key features of high-grade GEP-NEN and mimicked clinical response to cisplatin and temozolomide ex vivo. When we investigated treatment-induced adaptive stress responses in PD tumoroids in silico, we discovered and functionally validated Lysine demethylase 5 A and interferon-beta, which act synergistically in combination with cisplatin. Since ex vivo drug response in PD tumoroids matched clinical patient responses to standard-of-care chemotherapeutics for GEP-NEN, our rapid and functional precision oncology approach could expand personalized therapeutic options for patients with advanced high-grade GEP-NEN.

Delineating functional and molecular impact of ex vivo sample handling in precision medicine

Consistent handling of samples is crucial for achieving reproducible molecular and functional testing results in translational research. Here, we used 229 acute myeloid leukemia (AML) patient samples to assess the impact of sample handling on high-throughput functional drug testing, mass spectrometry-based proteomics, and flow cytometry. Our data revealed novel and previously described changes in cell phenotype and drug response dependent on sample biobanking. Specifically, myeloid cells with a CD117 (c-KIT) positive phenotype decreased after biobanking, potentially distorting cell population representations and affecting drugs targeting these cells. Additionally, highly granular AML cell numbers decreased after freezing. Secondly, protein expression levels, as well as sensitivity to drugs targeting cell proliferation, metabolism, tyrosine kinases (e.g., JAK, KIT, FLT3), and BH3 mimetics were notably affected by biobanking. Moreover, drug response profiles of paired fresh and frozen samples showed that freezing samples can lead to systematic errors in drug sensitivity scores. While a high correlation between fresh and frozen for the entire drug library was observed, freezing cells had a considerable impact at an individual level, which could influence outcomes in translational studies. Our study highlights conditions where standardization is needed to improve reproducibility, and where validation of data generated from biobanked cohorts may be particularly important.

Technical optimization of spatially resolved single-cell transcriptomic datasets to study clinical liver disease

Single cell and spatially resolved ‘omic’ techniques have enabled deep characterization of clinical pathologies that remain poorly understood, providing unprecedented insights into molecular mechanisms of disease. However, transcriptomic platforms are costly, limiting sample size, which increases the possibility of pre-analytical variables such as tissue processing and storage procedures impacting RNA quality and downstream analyses. Furthermore, spatial transcriptomics have not yet reached single cell resolution, leading to the development of multiple deconvolution methods to predict individual cell types within each transcriptome ‘spot’ on tissue sections. In this study, we performed spatial transcriptomics and single nucleus RNA sequencing (snRNAseq) on matched specimens from patients with either histologically normal or advanced fibrosis to establish important aspects of tissue handling, data processing, and downstream analyses of biobanked liver samples. We observed that tissue preservation technique impacts transcriptomic data, especially in fibrotic liver. Single cell mapping of the spatial transcriptome using paired snRNAseq data generated a spatially resolved, single cell dataset with 24 unique liver cell phenotypes. We determined that cell–cell interactions predicted using ligand–receptor analysis of snRNAseq data poorly correlated with cellular relationships identified using spatial transcriptomics. Our study provides a framework for generating spatially resolved, single cell datasets to study gene expression and cell–cell interactions in biobanked clinical samples with advanced liver disease.

Cohort profile: Improved Pregnancy Outcomes via Early Detection (IMPROvED), an International Multicentre Prospective Cohort.

Improved Pregnancy Outcomes via Early Detection (IMPROvED) is a multi-centre, European phase IIa clinical study. The primary aim of IMPROvED is to enable the assessment and refinement of innovative prototype preeclampsia risk assessment tests based on emerging biomarker technologies. Here we describe IMPROvED's profile and invite researchers to collaborate. A total of 4,038 low-risk nulliparous singleton pregnancies were recruited from maternity units in Ireland (N=1,501), United Kingdom (N=1,108), The Netherlands (N=810), and Sweden (N=619) between November 2013 to August 2017. Participants were interviewed by a research midwife at ~11 weeks (optional visit), ~15 weeks, ~20 weeks, ~34 weeks' gestation (optional visit), and postpartum (within 72-hours following delivery). Clinical data included information on maternal sociodemographic, medical history, and lifestyle factors collected at ~15 weeks' gestation, and maternal measurements, collected at each study visit. Biobank samples included blood, urine, and hair collected at each study visit throughout pregnancy in all units plus umbilical cord/blood samples collected at birth in Ireland and Sweden. A total of 74.0% (N=2,922) had an uncomplicated pregnancy, 3.1% (N=122) developed preeclampsia, 3.6% (N=143) had a spontaneous preterm birth, and 10.5% (N=416) had a small for gestational age baby. We evaluated a panel of metabolite biomarkers and a panel of protein biomarkers at 15 weeks and 20 weeks' gestation for preeclampsia risk assessment. Their translation into tests with clinical application, as conducted by commercial entities, was hampered by technical issues and changes in test requirements. Work on the panel of proteins was abandoned, while work on the use of metabolite biomarkers for preeclampsia risk assessment is ongoing. In accordance with the original goals of the IMPROvED study, the data and biobank are now available for international collaboration to conduct high quality research into the cause and prevention of adverse pregnancy outcomes.

Neurotrophic-tyrosine receptor kinase gene fusion in papillary thyroid cancer: A clinicogenomic biobank and record linkage study from Finland.

Selective tropomyosin receptor kinase (TRK) inhibitors are approved targeted therapies for patients with solid tumors harboring a neurotrophic tyrosine receptor kinase (NTRK) gene fusion. Country-specific estimates of NTRK gene fusion frequency, and knowledge on the characteristics of affected patients, are limited. We identified patients with histologically-confirmed papillary thyroid cancer (PTC) from Finland's Auria Biobank. TRK protein expression was determined by pan-TRK immunohistochemistry. Immuno-stained tumor samples were scored by a certified pathologist. Gene fusions and other co-occurring gene alterations were identified by next generation sequencing. Patient characteristics and vital status were determined from linked hospital electronic health records (EHRs). Patients were followed from 1 year before PTC diagnosis until death. 6/389 (1.5%) PTC patients had an NTRK gene fusion (all NTRK3); mean age 43.8 years (and none had comorbidities) at PTC diagnosis. Gene fusion partners were EML4 (n = 3), ETV6 (n = 2), and RBPMS (n = 1). Of 3/6 patients with complete EHRs, all received radioactive iodine ablation only and were alive at end of follow-up (median observation, 9.12 years). In conclusion, NTRK gene fusion is infrequent in patients with PTC. Linkage of biobank samples to EHRs is feasible in describing the characteristics and outcomes of patients with PTC and potentially other cancer types.

The Causal Association Between Medication Intake and Increased Risk of Psoriasis.

Psoriasis is a chronic, inflammatory, and papulo-squamous skin disorder without a radical cure. Although previous observational analyses have discovered a relationship between medication intake and increased risk of psoriasis, they are susceptible to confounders. We intend to ascertain if there is a causal association between specific medication intake and increased risk of psoriasis by utilizing the Mendelian randomization (MR) method. We obtained the genome-wide association study (GWAS) data for medication intake (23 types, N = 1809) from UK Biobank samples. And we sourced the GWAS data for psoriasis from the 8th release of the FinnGen database, which included 8,075 psoriasis cases and 330,975 healthy control cases. Then a two-sample MR study was performed to determine their causal association, and inverse-variance-weighted MR (IVW-MR) was applied to calculate the effect estimates. The IVW-MR analysis uncovered a positive correlation between the intake of HMG CoA reductase inhibitors and the increased risk of psoriasis (odds ratio [OR] = 1.167, 95% confidence interval [CI] = 1.084-1.257). Similarly, the use of thyroid preparations (OR=1.080, 95% CI=1.026-1.138), nonsteroidal anti-inflammatory and antirheumatic products (OR=1.406, 95% CI=1.037-1.908), anilides (OR=1.379, 95% CI=1.004-1.894), antihistamines for systemic use (OR=1.341, 95% CI=1.104-1.630), and antihypertensives (OR=1.099, 95% CI=1.016-1.190) were associated with an increased risk of psoriasis. We did not find evidence from IVW-MR for other associations. Our study offers a causal testimony that the intake of HMG CoA reductase inhibitors, thyroid preparations, nonsteroidal anti-inflammatory and antirheumatic products, anilides, antihistamines for systemic use, and antihypertensives will potentially increase the risk of psoriasis.

Measurement of 8-hydroxy-2'-deoxyguanosine in serum and cerebrospinal fluid of horses with neuroaxonal degeneration and other causes of proprioceptive ataxia.

Eight-hydroxy-2'-deoxyguanosine (8-OHdG), a biomarker of oxidative damage evaluated in human neurodegenerative disease, has potential to correlate with postmortem diagnosis of neuroaxonal dystrophy/degenerative myeloencephalopathy (NAD/DM) in horses. We hypothesized that 8-OHdG will be higher in CSF and serum from NAD/DM horses compared with horses with other neurologic diseases (CVSM, EPM) and a control group of neurologically normal horses. We also hypothesized that 8-OHdG will be higher in CSF compared with serum from NAD/DM horses. Fifty client-owned horses with postmortem diagnoses: 20 NAD/DM, 10 CVSM, 10 EPM, and 10 control horses. Serum and CSF samples were obtained between November 2010 and March 2022. Case-control study using biobanked samples was performed and commercial competitive ELISA kit (Highly Sensitive 8-OHdG Check ELISA) utilized. Concentration of 8-OHdG was quantitated in both CSF and serum and compared between groups. No correlation was established between the measures of 8-OHdG in serum and CSF and group. CSF median [8-OHdG] for NAD/DM was 169.9 pg/mL (IQR25-75 : 67.18-210.6), CVSM 157.1 pg/mL (IQR25-75 : 132.1-229.1), EPM 131.4 pg/mL (IQR25-75 : 102.1-193.2), and control 149.8 pg/mL (IQR25-75 : 113.3-196.4). Serum median [8-OHdG] for NAD/DM was 130 pg/mL (IQR25-75 : 51.73-157.2), CVSM 125.8 pg/mL (IQR25-75 : 62.8-170.8), EPM 120.6 pg/mL (IQR25-75 : 87.23-229.7), and control 157.6 pg/mL (IQR25-75 : 97.15-245.6). Poisson regression analysis showed no difference established once confounding variables were considered. Eight-OHdG did not aid in antemortem diagnosis of NAD/DM in this cohort of horses. At the time of diagnosis horses with NAD/DM do not have ongoing oxidative stress.

Diagnostic errors and delay of keratitis fugax hereditaria

Aims/Purpose: To chart misdiagnoses associated with keratitis fugax hereditaria (KFH), an autosomal dominant periodic corneal autoinflammatory disease, and the frequency of misdiagnosed KFH in patients diagnosed with unspecified anterior uveitis, herpes keratitis, or unspecified keratitis.Methods: Charts of patients with genetically confirmed KFH (n = 94) were reviewed. Two Finnish biobanks provided 2037 DNA samples meeting the inclusion criterion of a diagnosis KFH can be misdiagnosed with and the exclusion criterion of having a common underlying cause of anterior uveitis, such as rheumatoid arthritis. The NLRP3 c.61G&gt;C variant was detected using restriction fragment length polymorphism analysis, and Sanger sequencing for confirmation. Age, sex, ocular and other diagnoses, and laboratory results were collected from patients carrying the variant.Results: The time between first symptoms and the diagnosis of KFH ranged from 0 to 62 years (median, 21; interquartile range [IQR], 8–45). Analysis of patient charts revealed that the most common misdiagnoses were acute anterior uveitis (51% of all misdiagnoses/26% of all patients), conjunctivitis (26%/13%), or recurrent erosion (21%/11%). A mild anterior chamber inflammation was observed in 30% of patients, 0.5+ or 1+ by Standardization of Uveitis Nomenclature (SUN) criteria. Of the biobank samples, 12/2037 (0.59%; 95% confidence interval [CI] 0.56%–0.61%) carried the c.61G&gt;C variant: 11 diagnosed with anterior uveitis, and one with unspecified keratitis. Three had previously been diagnosed with KFH. The age range of the 12 variant carriers varied from 38 to 79 (median, 63; IQR, 48–76) with nine females and three males.Conclusions: KFH is most frequently misdiagnosed as anterior uveitis. In Finland, it might be beneficial to add testing for the NLRP3 c.61G&gt;C variant in existing laboratory test packages for anterior uveitis.

Broad consent for biobank research in South Africa - Towards an enabling ethico-legal framework

ABSTRACT Broad consent is permitted by the South African National Department of Health Ethics Guidelines but appears to be prohibited by section 13(1) of the Protection of Personal Information Act 4 of 2013. Additionally, the Act mandates that all personal data (including biobank sample data) be collected for lawful, explicit, and clearly defined purposes. There is possibility for ambiguity in interpretation because of this discrepancy between the two instruments. Given the association between the transfer of samples and data, the long-term nature of biobanking, which makes it impractical to provide too much or enough information because it is simply not available at the time of sample collection, and the various ways that the Protection of Personal Information Act 4 of 2013 have been interpreted, we aim to demonstrate that South Africa’s current regulatory framework should appropriately permit broad consent use for biobank research where the transfer of samples and their associated data are contemplated. In summary, the proposed amendments include removing regulatory ambiguity regarding broad consent use, ensuring adequate safeguards for research participants by specifying rules for data access and personal information processing, and incorporating consent form information requirements into the national Consent Template.

Machine learning analyses reveal circadian clock features predictive of anxiety among UK biobank participants

Mood disorders, including depression and anxiety, affect almost one-fifth of the world’s adult population and are becoming increasingly prevalent. Mutations in circadian clock genes have previously been associated with mood disorders both directly and indirectly through alterations in circadian phase, suggesting that the circadian clock influences multiple molecular pathways involved in mood. By targeting previously identified single nucleotide polymorphisms (SNPs) that have been implicated in anxiety and depressive disorders, we use a combination of statistical and machine learning techniques to investigate associations with the generalized anxiety disorder assessment (GAD-7) scores in a UK Biobank sample of 90,882 individuals. As in previous studies, we observed that females exhibited higher GAD-7 scores than males regardless of genotype. Interestingly, we found no significant effects on anxiety from individual circadian gene variants; only circadian genotypes with multiple SNP variants showed significant associations with anxiety. For both sexes, severe anxiety is associated with a 120-fold increase in odds for individuals with CRY2_AG(rs1083852)/ZBTB20_TT(rs1394593) genotypes and is associated with a near 40-fold reduction in odds for individuals with PER3-A_CG(rs228697)/ZBTB20_TT(rs1394593) genotypes. We also report several sex-specific associations with anxiety. In females, the CRY2/ZBTB20 genotype combination showed a > 200-fold increase in odds of anxiety and PER3/ZBTB20 and CRY1 /PER3-A genotype combinations also appeared as female risk factors. In males, CRY1/PER3-A and PER3-B/ZBTB20 genotype combinations were associated with anxiety risk. Mediation analysis revealed direct associations of CRY2/ZBTB20 variant genotypes with moderate anxiety in females and CRY1/PER3-A variant genotypes with severe anxiety in males. The association of CRY1/PER3-A variant genotypes with severe anxiety in females was partially mediated by extreme evening chronotype. Our results reinforce existing findings that females exhibit stronger anxiety outcomes than males, and provide evidence for circadian gene associations with anxiety, particularly in females. Our analyses only identified significant associations using two-gene combinations, underscoring the importance of combined gene effects on anxiety risk. We describe novel, robust associations between gene combinations involving the ZBTB20 SNP (rs1394593) and risk of anxiety symptoms in a large population sample. Our findings also support previous findings that the ZBTB20 SNP is an important factor in mood disorders, including seasonal affective disorder. Our results suggest that reduced expression of this gene significantly modulates the risk of anxiety symptoms through direct influences on mood-related pathways. Together, these observations provide novel links between the circadian clockwork and anxiety symptoms and identify potential molecular pathways through which clock genes may influence anxiety risk.

Head-to-head comparison of two loop-mediated isothermal amplification (LAMP) kits for diagnosis of malaria in a non-endemic setting

BackgroundLight microscopy and rapid diagnostic tests (RDT) have long been the recommended diagnostic methods for malaria. However, in recent years, loop-mediated isothermal amplification (LAMP) techniques have been shown to offer superior performance, in particular concerning low-grade parasitaemia, by delivering higher sensitivity and specificity with low laboratory capacity requirements in little more than an hour. In this study, the diagnostic performance of two LAMP kits were assessed head-to-head, compared to highly sensitive quantitative real time PCR (qPCR), in a non-endemic setting.MethodsIn this retrospective validation study two LAMP kits; Alethia® Illumigene Malaria kit and HumaTurb Loopamp™ Malaria Pan Detection (PDT) kit, were evaluated head-to-head for detection of Plasmodium-DNA in 133 biobanked blood samples from suspected malaria cases at the Clinical Microbiology Laboratory of Region Skåne, Sweden to determine their diagnostic performance compared to qPCR.ResultsOf the 133 samples tested, qPCR detected Plasmodium DNA in 41 samples (defined as true positives), and the two LAMP methods detected 41 and 37 of those, respectively. The results from the HumaTurb Loopamp™ Malaria PDT kit were in complete congruence with the qPCR, with a sensitivity of 100% (95% CI 91.40–100%) and specificity of 100% (95% CI 96.07–100%). The Alethia® Illumigene Malaria kit had a sensitivity of 90.24% (95% CI 76.87–97.28) and a specificity of 95.65% (95% CI 89.24–98.80) as compared to qPCR.ConclusionsThis head-to-head comparison showed higher performance indicators of the HumaTurb Loopamp™ Malaria PDT kit compared to the Alethia® illumigene Malaria kit for detection of malaria.

Capturing the well-being exposome in poly-environmental scores.

In this study we use aggregated weighted scores of environmental effects to study environmental influences on well-being and happiness. To this end, we split a sample of Netherlands Twin Register (NTR) participants into a training (N = 4857) and test (N = 2077) sample. In the training sample, we use elastic net regression to estimate effect sizes for associations between life satisfaction and two sets of environmental variables: one based on self-report socioenvironmental data, and one based on objective physical environmental data. Based on these effect sizes, we create two poly-environmental scores (PES-S and PES-O, for self-reports and objective data respectively). In the test sample, we perform association analyses between different measures of well-being and the two PESs. We find that the PES-S explains ∼36% of the variance in well-being, while the PES-O does not significantly contribute to the model. Variance in other well-being measures (i.e., different life satisfaction domains, subjective happiness, quality of life, flourishing, psychological well-being, self-rated health, depressive problems, and loneliness) are explained to varying extents by the PESs, ranging from 6.36% (self-rated health) to 36.66% (loneliness). These predictive values did not change during the COVID-19 pandemic (N = 3214). Validating the PES-S in the UK biobank (N = 40,614), we find that the UK biobank PES-S explains about ∼12% of the variance in happiness. Lastly, we examine if there is any indication for gene-environment correlation (rGE), the phenomenon where one's genetic predisposition influences exposure to the environment, by associating the PESs with polygenic scores (PGS) in a sample of Netherlands Twin Register (NTR) and UK Biobank participants. While the PES and PGS were not correlated in the NTR sample, they were correlated in the larger UK biobank sample, indicating the potential presence of rGE. We discuss several limitations pertaining to our dataset, such as a potential influence of common method bias, and reflect on how PESs might be used in future research.