Computationally defined and in vitro validated putative genomic safe harbour loci for transgene expression in human cells.

Selection of the target site is an inherent question for any project aiming for directed transgene integration. Genomic safe harbour (GSH) loci have been proposed as safe sites in the human genome for transgene integration. Although several sites have been characterised for transgene integration in the literature, most of these do not meet criteria set out for a GSH and the limited set that do have not been characterised extensively. Here, we conducted a computational analysis using publicly available data to identify 25 unique putative GSH loci that reside in active chromosomal compartments. We validated stable transgene expression and minimal disruption of the native transcriptome in three GSH sites in vitro using human embryonic stem cells (hESCs) and their differentiated progeny. Furthermore, for easy targeted transgene expression, we have engineered constitutive landing pad expression constructs into the three validated GSH in hESCs.

Primary health level screening for postpartum depression during well-child visits: Prevalence, associated risk factors, and breastfeeding.

Postpartum depression (PPD) is a public health problem that is associated with detrimental effects on the wellbeing of the mother, child and family. Early detection for PPD at the primary health level provides an opportunity for intervention. We aim to examine: (1) the prevalence rate of PPD in the primary care population, (2) acceptance and attendance rates of intervention for women who screened positive for PPD, (3) sociodemographic and maternal risk factors of PPD, and (4) the impact of PPD on breastfeeding. We implemented a mother-child dyadic screening program using the modified Patient Health Questionnaire-2 during routine well-child visits at 2 or 3 months postpartum between July 2019 and December 2021. We performed multivariable logistic regression to identify independent risk factors for PPD and described using adjusted odds ratio (OR) with corresponding 95 % confidence intervals. Among 5561 mothers, the prevalence rate of probable PPD was 2.4 %. About half (54.4 %) of mothers who screened positive accepted intervention and of these, about two-thirds accepted onward referrals to tertiary care and community mental health service, with higher attendance at the latter. In the final adjusted model, mothers who had probable PPD were more likely to be older than age 35 years (OR 1.88, 95 % CI 1.05-3.45; p < 0.05) and not breastfeeding (OR 1.9, 95 % CI 1.06-3.38; p < 0.05). Overall, our findings highlight the importance of early PPD screening and management in primary care. These findings can help inform maternal mental health service development and utilization, thereby optimizing maternal and infant outcomes.

A five-safes approach to a secure and scalable genomics data repository.

Genomic researchers increasingly utilize commercial cloud service providers (CSPs) to manage data and analytics needs. CSPs allow researchers to grow Information Technology (IT) infrastructure on demand to overcome bottlenecks when combining large datasets. However, without adequate security controls, the risk of unauthorized access may be higher for data stored on the cloud. Additionally, regulators are mandating data access patterns and specific security protocols for the storage and use of genomic data. While CSP provides tools for security and regulatory compliance, building the necessary controls required for cloud solutions is not trivial. Research Assets Provisioning and Tracking Online Repository (RAPTOR) by the Genome Institute of Singapore is a cloud-native genomics data repository and analytics platform that implements a "five-safes" framework to provide security and governance controls to data contributors and users, leveraging CSP for sharing and analysis of genomic datasets without the risk of security breaches or running afoul of regulations.

Analysis of clinically relevant variants from ancestrally diverse Asian genomes.

Asian populations are under-represented in human genomics research. Here, we characterize clinically significant genetic variation in 9051 genomes representing East Asian, South Asian, and severely under-represented Austronesian-speaking Southeast Asian ancestries. We observe disparate genetic risk burden attributable to ancestry-specific recurrent variants and identify individuals with variants specific to ancestries discordant to their self-reported ethnicity, mostly due to cryptic admixture. About 27% of severe recessive disorder genes with appreciable carrier frequencies in Asians are missed by carrier screening panels, and we estimate 0.5% Asian couples at-risk of having an affected child. Prevalence of medically-actionable variant carriers is 3.4% and a further 1.6% harbour variants with potential for pathogenic classification upon additional clinical/experimental evidence. We profile 23 pharmacogenes with high-confidence gene-drug associations and find 22.4% of Asians at-risk of Centers for Disease Control and Prevention Tier 1 genetic conditions concurrently harbour pharmacogenetic variants with actionable phenotypes, highlighting the benefits of pre-emptive pharmacogenomics. Our findings illuminate the diversity in genetic disease epidemiology and opportunities for precision medicine for a large, diverse Asian population.

Tracking the molecular evolution and transmission patterns of SARS-CoV-2 lineage B.1.466.2 in Indonesia based on genomic surveillance data.

BACKGROUND: As a new epi-center of COVID-19 in Asia and a densely populated developing country, Indonesia is facing unprecedented challenges in public health. SARS-CoV-2 lineage B.1.466.2 was reported to be an indigenous dominant strain in Indonesia (once second only to the Delta variant). However, it remains unclear how this variant evolved and spread within such an archipelagic nation. METHODS: For statistical description, the spatiotemporal distributions of the B.1.466.2 variant were plotted using the publicly accessible metadata in GISAID. A total of 1302 complete genome sequences of Indonesian B.1.466.2 strains with high coverage were downloaded from the GISAID's EpiCoV database on 28 August 2021. To determine the molecular evolutionary characteristics, we performed a time-scaled phylogenetic analysis using the maximum likelihood algorithm and called the single nucleotide variants taking the Wuhan-Hu-1 sequence as reference. To investigate the spatiotemporal transmission patterns, we estimated two dynamic parameters (effective population size and effective reproduction number) and reconstructed the phylogeography among different islands. RESULTS: As of the end of August 2021, nearly 85% of the global SARS-CoV-2 lineage B.1.466.2 sequences (including the first one) were obtained from Indonesia. This variant was estimated to account for over 50% of Indonesia's daily infections during the period of March-May 2021. The time-scaled phylogeny suggested that SARS-CoV-2 lineage B.1.466.2 circulating in Indonesia might have originated from Java Island in mid-June 2020 and had evolved into two disproportional and distinct sub-lineages. High-frequency non-synonymous mutations were mostly found in the spike and NSP3; the S-D614G/N439K/P681R co-mutations were identified in its larger sub-lineage. The demographic history was inferred to have experienced four phases, with an exponential growth from October 2020 to February 2021. The effective reproduction number was estimated to have reached its peak (11.18) in late December 2020 and dropped to be less than one after early May 2021. The relevant phylogeography showed that Java and Sumatra might successively act as epi-centers and form a stable transmission loop. Additionally, several long-distance transmission links across seas were revealed. CONCLUSIONS: SARS-CoV-2 variants circulating in the tropical archipelago may follow unique patterns of evolution and transmission. Continuous, extensive and targeted genomic surveillance is essential.

The Struggle to Fit in: A Qualitative Study on the Sense of Belonging and Well-being of Deaf People in Ipoh, Perak, Malaysia.

The sense of belonging plays an important role in a person's well-being. It also acts as a protective factor against mental distress. Deaf people struggle to fit into the dominant hearing society due to communication barriers. The multi-languages used in Malaysian families add to this communication challenge. Communication breakdown leaves the deaf person socially excluded while a poor sense of belonging also increases their vulnerability to mental health issues. Hence, this study explored the deaf person's sense of belonging and well-being through their social experiences in Malaysia. Baumeister's need-to-belong theory served as the theoretical framework of this study. An Ethnographic approach with in-depth interviews and participant observation was used to explore the social experiences of six Chinese deaf adults, aged 20-37, residing in Ipoh. Their hearing parents were interviewed as well to obtain parents' perspective of the child's well-being in the earlier years. Participants were selected using the purposive and snowballing sampling method. Upon data saturation, thematic analysis was used to identify themes, patterns, and interpret its meanings. The main themes that emerged from the data was the "struggle to fit in", "emotional effect", and "quality social connections". Findings of this study can be used in the formation of policies and strategies to ensure that deaf individuals are not excluded from their communities. Cultivating an inclusive community and developing the deaf community offers a better sense of belonging, which would help increase well-being of deaf people. Future research may focus on deaf identity and well-being of deaf youth in Malaysia.

Cybervictimization and Depression among Adolescents: Coping Strategies as Mediators.

Studies have shown the relationships among cybervictimization, coping strategies, and depression, but no study has examined the mechanism that links the three variables. Accordingly, this study used the transactional model of stress and coping theory as a conceptual framework and proposed that coping strategies are mediators for the effects of cybervictimization on depression. A total of 387 adolescents were recruited by using the purposive sampling method. The results showed that cybervictimization is not directly associated with depression. All the coping strategies are found to be associated with cybervictimization, but only the avoidant coping strategy is the statistical mediator for the effects of cybervictimization on depression. This study's findings suggest that the transactional model of stress and coping theory may provide a framework in the area of cyberbullying and recommend more actions to be taken in order to reduce the use of avoidance coping strategies among victims of cyberbullying.

Safety and target engagement of an oral small-molecule sequestrant in adolescents with autism spectrum disorder: an open-label phase 1b/2a trial.

Autism spectrum disorder (ASD) is defined by hallmark behaviors involving reduced communication and social interaction as well as repetitive activities and restricted interests. ASD represents a broad spectrum, from minimally affected individuals to those requiring intense support, with additional manifestations often including anxiety, irritability/aggression and altered sensory processing. Gastrointestinal (GI) issues are also common in ASD, and studies have identified changes in the gut microbiome of individuals with ASD compared to control populations, complementing recent findings of differences in gut-derived metabolites in feces and circulation. However, a role for the GI tract or microbiome in ASD remains controversial. Here we report that an oral GI-restricted adsorbent (AB-2004) that has affinity for small aromatic or phenolic molecules relieves anxiety-like behaviors that are driven by a gut microbial metabolite in mice. Accordingly, a pilot human study was designed and completed to evaluate the safety of AB-2004 in an open-label, single-cohort, multiple-ascending-dose clinical trial that enrolled 30 adolescents with ASD and GI symptoms in New Zealand and Australia. AB-2004 was shown to have good safety and tolerability across all dose levels, and no drug-related serious adverse events were identified. Significant reductions in specific urinary and plasma levels of gut bacterial metabolites were observed between baseline and end of AB-2004 treatment, demonstrating likely target engagement. Furthermore, we observed improvements in multiple exploratory behavioral endpoints, most significantly in post hoc analysis of anxiety and irritability, as well as GI health, after 8 weeks of treatment. These results from an open-label study (trial registration no. ACTRN12618001956291) suggest that targeting gut-derived metabolites with an oral adsorbent is a safe and well-tolerated approach to improving symptoms associated with ASD, thereby emboldening larger placebo-controlled trials.

Early Spatiotemporal Patterns and Population Characteristics of the COVID-19 Pandemic in Southeast Asia.

This observational study aims to investigate the early disease patterns of coronavirus disease 2019 (COVID-19) in Southeast Asia, consequently providing historical experience for further interventions. Data were extracted from official websites of the WHO and health authorities of relevant countries. A total of 1346 confirmed cases of COVID-19, with 217 recoveries and 18 deaths, were reported in Southeast Asia as of 16 March 2020. The basic reproductive number (R0) of COVID-19 in the region was estimated as 2.51 (95% CI:2.31 to 2.73), and there were significant geographical variations at the subregional level. Early transmission dynamics were examined with an exponential regression model: y = 0.30e0.13x (p < 0.01, R2 = 0.96), which could help predict short-term incidence. Country-level disease burden was positively correlated with Human Development Index (r = 0.86, p < 0.01). A potential early shift in spatial diffusion patterns and a spatiotemporal cluster occurring in Malaysia and Singapore were detected. Demographic analyses of 925 confirmed cases indicated a median age of 44 years and a sex ratio (male/female) of 1.25. Age may play a significant role in both susceptibilities and outcomes. The COVID-19 situation in Southeast Asia is challenging and unevenly geographically distributed. Hence, enhanced real-time surveillance and more efficient resource allocation are urgently needed.

Molecular Phylogenesis and Spatiotemporal Spread of SARS-CoV-2 in Southeast Asia.

Background: The ongoing coronavirus disease 2019 (COVID-19) pandemic has posed an unprecedented challenge to public health in Southeast Asia, a tropical region with limited resources. This study aimed to investigate the evolutionary dynamics and spatiotemporal patterns of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the region. Materials and Methods: A total of 1491 complete SARS-CoV-2 genome sequences from 10 Southeast Asian countries were downloaded from the Global Initiative on Sharing Avian Influenza Data (GISAID) database on November 17, 2020. The evolutionary relationships were assessed using maximum likelihood (ML) and time-scaled Bayesian phylogenetic analyses, and the phylogenetic clustering was tested using principal component analysis (PCA). The spatial patterns of SARS-CoV-2 spread within Southeast Asia were inferred using the Bayesian stochastic search variable selection (BSSVS) model. The effective population size (Ne) trajectory was inferred using the Bayesian Skygrid model. Results: Four major clades (including one potentially endemic) were identified based on the maximum clade credibility (MCC) tree. Similar clustering was yielded by PCA; the first three PCs explained 46.9% of the total genomic variations among the samples. The time to the most recent common ancestor (tMRCA) and the evolutionary rate of SARS-CoV-2 circulating in Southeast Asia were estimated to be November 28, 2019 (September 7, 2019 to January 4, 2020) and 1.446 × 10-3 (1.292 × 10-3 to 1.613 × 10-3) substitutions per site per year, respectively. Singapore and Thailand were the two most probable root positions, with posterior probabilities of 0.549 and 0.413, respectively. There were high-support transmission links (Bayes factors exceeding 1,000) in Singapore, Malaysia, and Indonesia; Malaysia involved the highest number (7) of inferred transmission links within the region. A twice-accelerated viral population expansion, followed by a temporary setback, was inferred during the early stages of the pandemic in Southeast Asia. Conclusions: With available genomic data, we illustrate the phylogeography and phylodynamics of SARS-CoV-2 circulating in Southeast Asia. Continuous genomic surveillance and enhanced strategic collaboration should be listed as priorities to curb the pandemic, especially for regional communities dominated by developing countries.

RCA2: a scalable supervised clustering algorithm that reduces batch effects in scRNA-seq data.

The transcriptomic diversity of cell types in the human body can be analysed in unprecedented detail using single cell (SC) technologies. Unsupervised clustering of SC transcriptomes, which is the default technique for defining cell types, is prone to group cells by technical, rather than biological, variation. Compared to de-novo (unsupervised) clustering, we demonstrate using multiple benchmarks that supervised clustering, which uses reference transcriptomes as a guide, is robust to batch effects and data quality artifacts. Here, we present RCA2, the first algorithm to combine reference projection (batch effect robustness) with graph-based clustering (scalability). In addition, RCA2 provides a user-friendly framework incorporating multiple commonly used downstream analysis modules. RCA2 also provides new reference panels for human and mouse and supports generation of custom panels. Furthermore, RCA2 facilitates cell type-specific QC, which is essential for accurate clustering of data from heterogeneous tissues. We demonstrate the advantages of RCA2 on SC data from human bone marrow, healthy PBMCs and PBMCs from COVID-19 patients. Scalable supervised clustering methods such as RCA2 will facilitate unified analysis of cohort-scale SC datasets.

Non-intrusive wastewater surveillance for monitoring of a residential building for COVID-19 cases.

Wastewater-based surveillance for SARS-CoV-2 has been used for the early warning of transmission or objective trending of the population-level disease prevalence. Here, we describe a new use-case of conducting targeted wastewater surveillance to complement clinical testing for case identification in a small community at risk of COVID-19 transmission. On 2 July 2020, a cluster of COVID-19 cases in two unrelated households residing on different floors in the same stack of an apartment building was reported in Singapore. After cases were conveyed to healthcare facilities and six healthy household contacts were quarantined in their respective apartments, wastewater surveillance was implemented for the entire residential block. SARS-CoV-2 was subsequently detected in wastewaters in an increasing frequency and concentration, despite the absence of confirmed COVID-19 cases, suggesting the presence of fresh case/s in the building. Phone interviews of six residents in quarantine revealed that no one was symptomatic (fever/respiratory illness). However, when nasopharyngeal swabs from six quarantined residents were tested by PCR tests, one was positive for SARS-CoV-2. The positive case reported episodes of diarrhea and the case's stool sample was also positive for SARS-CoV-2, explaining the SARS-CoV-2 spikes observed in wastewaters. After the case was conveyed to a healthcare facility, wastewaters continued to yield positive signals for five days, though with a decreasing intensity. This was attributed to the return of recovered cases, who had continued to shed the virus. Our findings demonstrate the utility of wastewater surveillance as a non-intrusive tool to monitor high-risk COVID-19 premises, which is able to trigger individual tests for case detection, highlighting a new use-case for wastewater testing.

scConsensus: combining supervised and unsupervised clustering for cell type identification in single-cell RNA sequencing data.

BACKGROUND: Clustering is a crucial step in the analysis of single-cell data. Clusters identified in an unsupervised manner are typically annotated to cell types based on differentially expressed genes. In contrast, supervised methods use a reference panel of labelled transcriptomes to guide both clustering and cell type identification. Supervised and unsupervised clustering approaches have their distinct advantages and limitations. Therefore, they can lead to different but often complementary clustering results. Hence, a consensus approach leveraging the merits of both clustering paradigms could result in a more accurate clustering and a more precise cell type annotation. RESULTS: We present SCCONSENSUS, an [Formula: see text] framework for generating a consensus clustering by (1) integrating results from both unsupervised and supervised approaches and (2) refining the consensus clusters using differentially expressed genes. The value of our approach is demonstrated on several existing single-cell RNA sequencing datasets, including data from sorted PBMC sub-populations. CONCLUSIONS: SCCONSENSUS combines the merits of unsupervised and supervised approaches to partition cells with better cluster separation and homogeneity, thereby increasing our confidence in detecting distinct cell types. SCCONSENSUS is implemented in [Formula: see text] and is freely available on GitHub at https://github.com/prabhakarlab/scConsensus .

Experimental and bioinformatics considerations in cancer application of single cell genomics.

Single cell genomics offers an unprecedented resolution to interrogate genetic heterogeneity in a patient's tumour at the intercellular level. However, the DNA yield per cell is insufficient for today's sequencing library preparation protocols. This necessitates DNA amplification which is a key source of experimental noise. We provide an evaluation of two protocols using micro-fluidics based amplification for whole exome sequencing, which is an experimental scenario commonly used in single cell genomics. The results highlight their respective biases and relative strengths in identification of single nucleotide variations. Towards this end, we introduce a workflow SoVaTSiC, which allows for quality evaluation and somatic variant identification of single cell data. As proof of concept, the framework was applied to study a lung adenocarcinoma tumour. The analysis provides insights into tumour phylogeny by identifying key mutational events in lung adenocarcinoma evolution. The consequence of this inference is supported by the histology of the tumour and demonstrates usefulness of the approach.

An integrative model of pathway convergence in genetically heterogeneous blast crisis chronic myeloid leukemia.

Targeted therapies against the BCR-ABL1 kinase have revolutionized treatment of chronic phase (CP) chronic myeloid leukemia (CML). In contrast, management of blast crisis (BC) CML remains challenging because BC cells acquire complex molecular alterations that confer stemness features to progenitor populations and resistance to BCR-ABL1 tyrosine kinase inhibitors. Comprehensive models of BC transformation have proved elusive because of the rarity and genetic heterogeneity of BC, but are important for developing biomarkers predicting BC progression and effective therapies. To better understand BC, we performed an integrated multiomics analysis of 74 CP and BC samples using whole-genome and exome sequencing, transcriptome and methylome profiling, and chromatin immunoprecipitation followed by high-throughput sequencing. Employing pathway-based analysis, we found the BC genome was significantly enriched for mutations affecting components of the polycomb repressive complex (PRC) pathway. While transcriptomically, BC progenitors were enriched and depleted for PRC1- and PRC2-related gene sets respectively. By integrating our data sets, we determined that BC progenitors undergo PRC-driven epigenetic reprogramming toward a convergent transcriptomic state. Specifically, PRC2 directs BC DNA hypermethylation, which in turn silences key genes involved in myeloid differentiation and tumor suppressor function via so-called epigenetic switching, whereas PRC1 represses an overlapping and distinct set of genes, including novel BC tumor suppressors. On the basis of these observations, we developed an integrated model of BC that facilitated the identification of combinatorial therapies capable of reversing BC reprogramming (decitabine+PRC1 inhibitors), novel PRC-silenced tumor suppressor genes (NR4A2), and gene expression signatures predictive of disease progression and drug resistance in CP.

Factors predicting one-year post-surgical mortality amongst older Asian patients undergoing moderate to major non-cardiac surgery - a retrospective cohort study.

BACKGROUND: While short-term perioperative outcomes have been well studied in Western surgical populations, the aim of this study is to look at the one-year perioperative mortality and its associated factors in an Asian surgical population after non-cardiac surgery. METHODS: A retrospective cohort study of 2163 patients aged above 45 undergoing non-cardiac surgery in a university-affiliated tertiary hospital from January to July 2015 was performed. Relevant demographic, clinical and surgical data were analysed to elicit their relationship to mortality at one year after surgery. A univariate analysis was first performed to identify significant variables with p-values ≤ 0.2, which were then analysed using Firth multiple logistic regression to calculate the adjusted odds ratio. RESULTS: The one-year mortality in our surgical population was 5.9%. The significant factors that increased one-year mortality include smoking (adjusted OR 2.17 (1.02-4.45), p = 0.044), anaemia (adjusted OR 1.32 (1.16-1.47), p < 0.001, for every 1 g/dL drop in haemoglobin level), lower BMI (adjusted OR 0.93 (0.87-0.98), p = 0.005, for every 1 point increase in BMI), Malay and Indian ethnicity (adjusted OR 2.68 (1.53-4.65), p = 0.001), peripheral vascular disease (adjusted OR 4.21 (1.62-10.38), p = 0.004), advanced age (adjusted OR 1.04 (1.01-1.06), p = 0.004, for every one year increase in age), emergency surgery (adjusted OR 2.26 (1.29-3.15), p = 0.005) and malignancy (adjusted OR 3.20 (1.85-5.52), p < 0.001). CONCLUSIONS: Our study shows that modifiable risk factors such as malnutrition, anaemia and smoking which affect short term mortality extend beyond the immediate perioperative period into longer term outcomes. Identification and optimization of this subset of patients are therefore vital. Further similar large studies should be done to develop a risk scoring system for post-operative long-term outcomes. This would aid clinicians in risk stratification, counselling and surgical planning, which will help in patients' decision making and care planning.

Metabolic reprogramming of oncogene-addicted cancer cells to OXPHOS as a mechanism of drug resistance.

The ability to selectively eradicate oncogene-addicted tumors while reducing systemic toxicity has endeared targeted therapies as a treatment strategy. Nevertheless, development of acquired resistance limits the benefits and durability of such a regime. Here we report evidence of enhanced reliance on mitochondrial oxidative phosphorylation (OXPHOS) in oncogene-addicted cancers manifesting acquired resistance to targeted therapies. To that effect, we describe a novel OXPHOS targeting activity of the small molecule compound, OPB-51602 (OPB). Of note, a priori treatment with OPB restored sensitivity to targeted therapies. Furthermore, cancer cells exhibiting stemness markers also showed selective reliance on OXPHOS and enhanced sensitivity to OPB. Importantly, in a subset of patients who developed secondary resistance to EGFR tyrosine kinase inhibitor (TKI), OPB treatment resulted in decrease in metabolic activity and reduction in tumor size. Collectively, we show here a switch to mitochondrial OXPHOS as a key driver of targeted drug resistance in oncogene-addicted cancers. This metabolic vulnerability is exploited by a novel OXPHOS inhibitor, which also shows promise in the clinical setting.

Tumor-derived circulating endothelial cell clusters in colorectal cancer.

Clusters of tumor cells are often observed in the blood of cancer patients. These structures have been described as malignant entities for more than 50 years, although their comprehensive characterization is lacking. Contrary to current consensus, we demonstrate that a discrete population of circulating cell clusters isolated from the blood of colorectal cancer patients are not cancerous but consist of tumor-derived endothelial cells. These clusters express both epithelial and mesenchymal markers, consistent with previous reports on circulating tumor cell (CTC) phenotyping. However, unlike CTCs, they do not mirror the genetic variations of matched tumors. Transcriptomic analysis of single clusters revealed that these structures exhibit an endothelial phenotype and can be traced back to the tumor endothelium. Further results show that tumor-derived endothelial clusters do not form by coagulation or by outgrowth of single circulating endothelial cells, supporting a direct release of clusters from the tumor vasculature. The isolation and enumeration of these benign clusters distinguished healthy volunteers from treatment-naïve as well as pathological early-stage (≤IIA) colorectal cancer patients with high accuracy, suggesting that tumor-derived circulating endothelial cell clusters could be used as a means of noninvasive screening for colorectal cancer. In contrast to CTCs, tumor-derived endothelial cell clusters may also provide important information about the underlying tumor vasculature at the time of diagnosis, during treatment, and throughout the course of the disease.