Mucormycosis in Australia: Contemporary epidemiology and outcomes

Mucormycosis is the second most common cause of invasive mould infection and causes disease in diverse hosts, including those who are immuno-competent. We conducted a multicentre retrospective study of proven and probable cases of mucormycosis diagnosed between 2004–2012 to determine the epidemiology and outcome determinants in Australia. Seventy-four cases were identified (63 proven, 11 probable). The majority (54.1%) were caused by Rhizopus spp. Patients who sustained trauma were more likely to have non-Rhizopus infections relative to patients without trauma (OR 9.0, p 0.001, 95% CI 2.1–42.8). Haematological malignancy (48.6%), chemotherapy (42.9%), corticosteroids (52.7%), diabetes mellitus (27%) and trauma (22.9%) were the most common co-morbidities or risk factors. Rheumatological/autoimmune disorders occurred in nine (12.1%) instances. Eight (10.8%) cases had no underlying co-morbidity and were more likely to have associated trauma (7/8; 87.5% versus 10/66; 15.2%; p <0.001). Disseminated infection was common (39.2%). Apophysomyces spp. and Saksenaea spp. caused infection in immuno-competent hosts, most frequently associated with trauma and affected sites other than lung and sinuses. The 180-day mortality was 56.7%. The strongest predictors of mortality were rheumatological/autoimmune disorder (OR = 24.0, p 0.038 95% CI 1.2–481.4), haematological malignancy (OR = 7.7, p 0.001, 95% CI 2.3–25.2) and admission to intensive care unit (OR = 4.2, p 0.02, 95% CI 1.3–13.8). Most deaths occurred within one month. Thereafter we observed divergence in survival between the haematological and non-haematological populations (p 0.006). The mortality of mucormycosis remains particularly high in the immuno-compromised host. Underlying rheumatological/autoimmune disorders are a previously under-appreciated risk for infection and poor outcome

Integrating sequence and array data to create an improved 1000 Genomes Project haplotype reference panel

A major use of the 1000 Genomes Project (1000GP) data is genotype imputation in genome-wide association studies (GWAS). Here we develop a method to estimate haplotypes from low-coverage sequencing data that can take advantage of single-nucleotide polymorphism (SNP) microarray genotypes on the same samples. First the SNP array data are phased to build a backbone (or 'scaffold') of haplotypes across each chromosome. We then phase the sequence data 'onto' this haplotype scaffold. This approach can take advantage of relatedness between sequenced and non-sequenced samples to improve accuracy. We use this method to create a new 1000GP haplotype reference set for use by the human genetic community. Using a set of validation genotypes at SNP and bi-allelic indels we show that these haplotypes have lower genotype discordance and improved imputation performance into downstream GWAS samples, especially at low-frequency variants. © 2014 Macmillan Publishers Limited. All rights reserved