Preventable Emergency Hospital Admissions Among Adults With Intellectual Disability in England.

PURPOSE: Adults with intellectual disabilities experience poorer physical health and health care quality, but there is limited information on the potential for reducing emergency hospital admissions in this population. We describe overall and preventable emergency admissions for adults with vs without intellectual disabilities in England and assess differences in primary care management before admission for 2 common ambulatory care-sensitive conditions (ACSCs). METHODS: We used electronic records to study a cohort of 16,666 adults with intellectual disabilities and 113,562 age-, sex-, and practice-matched adults without intellectual disabilities from 343 English family practices. Incident rate ratios (IRRs) from conditional Poisson regression were analyzed for all emergency and preventable emergency admissions. Primary care management of lower respiratory tract infections and urinary tract infections, as exemplar ACSCs, before admission were compared in unmatched analysis between adults with and without intellectual disabilities. RESULTS: The overall rate for emergency admissions for adults with vs without intellectual disabilities was 182 vs 68 per 1,000 per year (IRR = 2.82; 95% CI, 2.66-2.98). ACSCs accounted for 33.7% of emergency admissions among the former compared with 17.3% among the latter (IRR = 5.62; 95% CI, 5.14-6.13); adjusting for comorbidity, smoking, and deprivation did not fully explain the difference (IRR = 3.60; 95% CI, 3.25-3.99). Although adults with intellectual disability were at nearly 5 times higher risk for admission for lower respiratory tract infections and urinary tract infections, they had similar primary care use, investigation, and management before admission as the general population. CONCLUSIONS: Adults with intellectual disabilities are at high risk for preventable emergency admissions. Identifying strategies for better detecting and managing ACSCs, including lower respiratory and urinary tract infections, in primary care could reduce hospitalizations.

Identification of susceptibility loci for colorectal cancer in a genome-wide meta-analysis.

To identify common variants influencing colorectal cancer (CRC) risk, we performed a meta-analysis of five genome-wide association studies, comprising 5626 cases and 7817 controls of European descent. We conducted replication of top ranked single nucleotide polymorphisms (SNPs) in additional series totalling 14 037 cases and 15 937 controls, identifying a new CRC risk locus at 10q24.2 [rs1035209; odds ratio (OR) = 1.13, P = 4.54 × 10(-11)]. We also performed meta-analysis of our studies, with previously published data, of several recently purported CRC risk loci. We failed to find convincing evidence for a previously reported genome-wide association at rs11903757 (2q32.3). Of the three additional loci for which evidence of an association in Europeans has been previously described we failed to show an association between rs59336 (12q24.21) and CRC risk. However, for the other two SNPs, our analyses demonstrated new, formally significant associations with CRC. These are rs3217810 intronic in CCND2 (12p13.32; OR = 1.19, P = 2.16 × 10(-10)) and rs10911251 near LAMC1 (1q25.3; OR = 1.09, P = 1.75 × 10(-8)). Additionally, we found some evidence to support a relationship between, rs647161, rs2423297 and rs10774214 and CRC risk originally identified in East Asians in our European datasets. Our findings provide further insights into the genetic and biological basis of inherited genetic susceptibility to CRC.

Inherited genetic susceptibility to monoclonal gammopathy of unknown significance.

Monoclonal gammopathy of undetermined significance (MGUS) is present in ∼2% of individuals age >50 years. The increased risk of multiple myeloma (MM) in relatives of individuals with MGUS is consistent with MGUS being a marker of inherited genetic susceptibility to MM. Common single-nucleotide polymorphisms (SNPs) at 2p23.3 (rs6746082), 3p22.1 (rs1052501), 3q26.2 (rs10936599), 6p21.33 (rs2285803), 7p15.3 (rs4487645), 17p11.2 (rs4273077), and 22q13.1 (rs877529) have recently been shown to influence MM risk. To examine the impact of these 7 SNPs on MGUS, we analyzed two case-control series totaling 492 cases and 7306 controls. Each SNP independently influenced MGUS risk with statistically significant associations (P < .02) for rs1052501, rs2285803, rs4487645, and rs4273077. SNP associations were independent, with risk increasing with a larger number of risk alleles carried (per allele odds ratio, 1.18; P < 10(-7)). Collectively these data are consistent with a polygenic model of disease susceptibility to MGUS.

Mortality Among Adults With Intellectual Disability in England: Comparisons With the General Population.

OBJECTIVES: To describe mortality among adults with intellectual disability in England in comparison with the general population. METHODS: We conducted a cohort study from 2009 to 2013 using data from 343 general practices. Adults with intellectual disability (n = 16 666; 656 deaths) were compared with age-, gender-, and practice-matched controls (n = 113 562; 1358 deaths). RESULTS: Adults with intellectual disability had higher mortality rates than controls (hazard ratio [HR] = 3.6; 95% confidence interval [CI] = 3.3, 3.9). This risk remained high after adjustment for comorbidity, smoking, and deprivation (HR = 3.1; 95% CI = 2.7, 3.4); it was even higher among adults with intellectual disability and Down syndrome or epilepsy. A total of 37.0% of all deaths among adults with intellectual disability were classified as being amenable to health care intervention, compared with 22.5% in the general population (HR = 5.9; 95% CI = 5.1, 6.8). CONCLUSIONS: Mortality among adults with intellectual disability is markedly elevated in comparison with the general population, with more than a third of deaths potentially amenable to health care interventions. This mortality disparity suggests the need to improve access to, and quality of, health care among people with intellectual disability.

Deciphering the genetic architecture of low-penetrance susceptibility to colorectal cancer.

Recent genome-wide association studies (GWASs) have identified common variants at 16 autosomal regions influencing the risk of developing colorectal cancer (CRC). To decipher the genetic basis of the association signals at these loci, we performed a meta-analysis of data from five GWASs, totalling 5626 cases and 7817 controls, using imputation to recover un-typed genotypes. To enhance our ability to discover low-frequency risk variants, in addition to using 1000 Genomes Project data as a reference panel, we made use of high-coverage sequencing data on 253 individuals, 199 with early-onset familial CRC. For 13 of the regions, it was possible to refine the association signal identifying a smaller region of interest likely to harbour the functional variant. Our analysis did not provide evidence that any of the associations at the 16 loci being a consequence of synthetic associations rather than linkage disequilibrium with a common risk variant.

Deciphering the 8q24.21 association for glioma.

We have previously identified tagSNPs at 8q24.21 influencing glioma risk. We have sought to fine-map the location of the functional basis of this association using data from four genome-wide association studies, comprising a total of 4147 glioma cases and 7435 controls. To improve marker density across the 700 kb region, we imputed genotypes using 1000 Genomes Project data and high-coverage sequencing data generated on 253 individuals. Analysis revealed an imputed low-frequency SNP rs55705857 (P = 2.24 × 10(-38)) which was sufficient to fully capture the 8q24.21 association. Analysis by glioma subtype showed the association with rs55705857 confined to non-glioblastoma multiforme (non-GBM) tumours (P = 1.07 × 10(-67)). Validation of the non-GBM association was shown in three additional datasets (625 non-GBM cases, 2412 controls; P = 1.41 × 10(-28)). In the pooled analysis, the odds ratio for low-grade glioma associated with rs55705857 was 4.3 (P = 2.31 × 10(-94)). rs55705857 maps to a highly evolutionarily conserved sequence within the long non-coding RNA CCDC26 raising the possibility of direct functionality. These data provide additional insights into the aetiological basis of glioma development.

Variation at 10p12.2 and 10p14 influences risk of childhood B-cell acute lymphoblastic leukemia and phenotype.

Acute lymphoblastic leukemia (ALL) is the major pediatric cancer diagnosed in economically developed countries with B-cell precursor (BCP)-ALL, accounting for approximately 70% of ALL. Recent genome-wide association studies (GWAS) have provided the first unambiguous evidence for common inherited susceptibility to BCP-ALL, identifying susceptibility loci at 7p12.2, 9p21.3, 10q21.2, and 14q11.2. To identify additional BCP-ALL susceptibility loci, we conducted a GWAS and performed a meta-analysis with a published GWAS totaling 1658 cases and 4723 controls, with validation in 1449 cases and 1488 controls. Combined analysis identified novel loci mapping to 10p12.2 (rs10828317, odds ratio [OR] = 1.23; P = 2.30 × 10(-9)) and 10p14 marked by rs3824662 (OR = 1.31; P = 8.62 × 10(-12)). The single nucleotide polymorphism rs10828317 is responsible for the N215S polymorphism in exon 7 of PIP4K2A, and rs3824662 localizes to intron 3 of the transcription factor and putative tumor suppressor gene GATA3. The rs10828317 association was shown to be specifically associated with hyperdiploid ALL, whereas the rs3824662-associated risk was confined to nonhyperdiploid non-TEL-AML1 + ALL. The risk allele of rs3824662 was correlated with older age at diagnosis (P < .001) and significantly worse event-free survivorship (P < .0001). These findings provide further insights into the genetic and biological basis of inherited genetic susceptibility to BCP-ALL and the influence of constitutional genotype on disease development.

Chromosome 7p11.2 (EGFR) variation influences glioma risk.

While gliomas are the most common primary brain tumors, their etiology is largely unknown. To identify novel risk loci for glioma, we conducted genome-wide association (GWA) analysis of two case-control series from France and Germany (2269 cases and 2500 controls). Pooling these data with previously reported UK and US GWA studies provided data on 4147 glioma cases and 7435 controls genotyped for 424 460 common tagging single-nucleotide polymorphisms. Using these data, we demonstrate two statistically independent associations between glioma and rs11979158 and rs2252586, at 7p11.2 which encompasses the EGFR gene (population-corrected statistics, P(c) = 7.72 × 10(-8) and 2.09 × 10(-8), respectively). Both associations were independent of tumor subtype, and were independent of EGFR amplification, p16INK4a deletion and IDH1 mutation status in tumors; compatible with driver effects of the variants on glioma development. These findings show that variation in 7p11.2 is a determinant of inherited glioma risk.

MHC variation and risk of childhood B-cell precursor acute lymphoblastic leukemia.

A role for specific human leukocyte antigen (HLA) variants in the etiology of childhood acute lymphoblastic leukemia (ALL) has been extensively studied over the last 30 years, but no unambiguous association has been identified. To comprehensively study the relationship between genetic variation within the 4.5 Mb major histocompatibility complex genomic region and precursor B-cell (BCP) ALL risk, we analyzed 1075 observed and 8176 imputed single nucleotide polymorphisms and their related haplotypes in 824 BCP-ALL cases and 4737 controls. Using these genotypes we also imputed both common and rare alleles at class I (HLA-A, HLA-B, and HLA-C) and class II (HLA-DRB1, HLA-DQA1, and HLA-DQB1) HLA loci. Overall, we found no statistically significant association between variants and BCP-ALL risk. We conclude that major histocompatibility complex-defined variation in immune-mediated response is unlikely to be a major risk factor for BCP-ALL.

Insight in glioma susceptibility through an analysis of 6p22.3, 12p13.33-12.1, 17q22-23.2 and 18q23 SNP genotypes in familial and non-familial glioma.

The risk of glioma has consistently been shown to be increased twofold in relatives of patients with primary brain tumors (PBT). A recent genome-wide linkage study of glioma families provided evidence for a disease locus on 17q12-21.32, with the possibility of four additional risk loci at 6p22.3, 12p13.33-12.1, 17q22-23.2, and 18q23. To identify the underlying genetic variants responsible for the linkage signals, we compared the genotype frequencies of 5,122 SNPs mapping to these five regions in 88 glioma cases with and 1,100 cases without a family history of PBT (discovery study). An additional series of 84 familial and 903 non-familial cases were used to replicate associations. In the discovery study, 12 SNPs showed significant associations with family history of PBT (P < 0.001). In the replication study, two of the 12 SNPs were confirmed: 12p13.33-12.1 PRMT8 rs17780102 (P = 0.031) and 17q12-21.32 SPOP rs650461 (P = 0.025). In the combined analysis of discovery and replication studies, the strongest associations were attained at four SNPs: 12p13.33-12.1 PRMT8 rs17780102 (P = 0.0001), SOX5 rs7305773 (P = 0.0001) and STKY1 rs2418087 (P = 0.0003), and 17q12-21.32 SPOP rs6504618 (P = 0.0006). Further, a significant gene-dosage effect was found for increased risk of family history of PBT with these four SNPs in the combined data set (P(trend) <1.0 × 10(-8)). The results support the linkage finding that some loci in the 12p13.33-12.1 and 17q12-q21.32 may contribute to gliomagenesis and suggest potential target genes underscoring linkage signals.

Genome-wide homozygosity signatures and childhood acute lymphoblastic leukemia risk.

Recent studies have reported that regions of homozygosity (ROH) in the genome are detectable in outbred populations and can be associated with an increased risk of malignancy. To examine whether homozygosity is associated with an increased risk of developing childhood B-cell precursor acute lymphoblastic leukemia (BCP-ALL), we analyzed 824 ALL cases and 2398 controls genotyped for 292 200 tagging SNPs. Across the genome, cumulative distribution of ROH was not significantly different between cases and controls. Four common ROH at 10p11.2-10q11.21, 1p31.1, 19p13.2-3, and 20q11.1-23 were, however, associated with ALL risk at P less than .01 (including 1 ROH to which the erythropoietin receptor [EPOR] gene maps, P = .005) but were nonsignificant after adjusting for multiple testing. Our findings make it unlikely that levels of measured homozygosity, caused by autozygosity, uniparental isodisomy, or hemizygosity, play a major role in defining BCP-ALL risk in predominantly outbred populations.

Verification of the susceptibility loci on 7p12.2, 10q21.2, and 14q11.2 in precursor B-cell acute lymphoblastic leukemia of childhood.

Recent genome-wide association data have implicated genetic variation at 7p12.2 (IKZF1), 10q21.2 (ARIDB5), and 14q11.2 (CEBPE) in the etiology of B-cell childhood acute lymphoblastic leukemia (ALL). To verify and further examine the relationship between these variants and ALL risk, we genotyped 1384 cases of precursor B-cell childhood ALL and 1877 controls from Germany and the United Kingdom. The combined data provided statistically significant support for an association between genotype at each of these loci and ALL risk; odds ratios (OR), 1.69 (P = 7.51 x10(-22)), 1.80 (P = 5.90 x 10(-28)), and 1.27 (P = 4.90 x 10(-6)), respectively. Furthermore, the risk of ALL increases with an increasing numbers of variant alleles for the 3 loci (OR(per-allele) = 1.53, 95% confidence interval, 1.44-1.62; P(trend) = 3.49 x 10(-42)), consistent with a polygenic model of disease susceptibility. These data provide unambiguous evidence for the role of these variants in defining ALL risk underscoring approximately 64% of cases.

Allergy and glioma risk: test of association by genotype.

Although epidemiological studies have suggested an association between atopy and glioma risk, these observations have been based on self-reporting of allergic conditions raising the possibility that associations may be noncausal and arise as a consequence of bias, reverse causation or other artifacts. Genetic information provides an alternative approach to investigate the relationship avoiding such biases. We analyzed 1,878 glioma cases and 3,670 controls for variants at 2q12, 5q12.1, 11q13 and 17q21 that are associated with asthma or eczema risk at p < 5.0 × 10(-7) . The SNP rs7216389, which tags the 3' flanking region of ORMDL3 at 17q21 and has been associated with childhood asthma, was correlated with increased glioma risk (OR = 1.10; 95% CI: 1.01-1.19). These data provide evidence for a correlation between asthma susceptibility and glioma risk and illustrate the value of using genetics as an investigative tool for developing etiological hypotheses.

Genome-wide association studies for detecting cancer susceptibility.

Genome-wide association (GWA) studies search for genetic variants, across the entire genome, which display differences in frequencies between cases and controls. Studies in PubMed using the keywords 'genomewide association' and 'cancer' are reported together with selected literature. Since 2007, GWA studies have successfully yielded risk loci for most common cancers. Findings have provided insights into the biological basis of cancer susceptibility implicating previously unsuspected genes in tumourogenesis. The variants identified typically account for only a small proportion of the familial risk of cancer and thus their application for individual risk prediction is poor. Furthermore, the genotyped variants are unlikely to be directly causal and identifying the causal basis is a major challenge. Methodological developments are desirable to fully utilize existing data sets and to enable more complex models of inherited predisposition to be investigated. Annotation of low frequency variation coupled with next-generation sequencing is making the search for rare disease-causing variants a realistic prospect.

Rationale for an international consortium to study inherited genetic susceptibility to childhood acute lymphoblastic leukemia.

Acute lymphoblastic leukemia is the major pediatric cancer in developed countries. To date most association studies of acute lymphoblastic leukemia have been based on the candidate gene approach and have evaluated a restricted number of polymorphisms. Such studies have served to highlight difficulties in conducting statistically and methodologically rigorous investigations into acute lymphoblastic leukemia risk. Recent genome-wide association studies of childhood acute lymphoblastic leukemia have provided robust evidence that common variation at four genetic loci confers a modest increase in risk. The accumulated experience to date and relative lack of success of initial efforts to identify novel acute lymphoblastic leukemia predisposition loci emphasize the need for alternative study designs and methods. The International Childhood Acute Lymphoblastic Leukaemia Genetics Consortium includes 12 research groups in Europe, Asia, the Middle East and the Americas engaged in studying the genetics of acute lymphoblastic leukemia. The initial goal of this consortium is to identify and characterize low-penetrance susceptibility variants for acute lymphoblastic leukemia through association-based analyses. Efforts to develop genome-wide association studies of acute lymphoblastic leukemia, in terms of both sample size and single nucleotide polymorphism coverage, and to increase the number of single nucleotide polymorphisms taken forward to large-scale replication should lead to the identification of additional novel risk variants for acute lymphoblastic leukemia. Ethnic differences in the risk of acute lymphoblastic leukemia are well recognized and thus in assessing the interplay between inherited and non-genetic risk factors, analyses using different population cohorts with different incidence rates are likely to be highly informative. Given that the frequency of many acute lymphoblastic leukemia subgroups is small, identifying differential effects will realistically only be possible through multi-center pooled analyses. Here, we review the rationale for identifying genetic risk variants for acute lymphoblastic leukemia and our proposed strategy for establishing the International Childhood Acute Lymphoblastic Leukaemia Genetics Consortium.

Inherited variation in immune genes and pathways and glioblastoma risk.

To determine whether inherited variations in immune function single-nucleotide polymorphisms (SNPs), genes or pathways affect glioblastoma risk, we analyzed data from recent genome-wide association studies in conjunction with predefined immune function genes and pathways. Gene and pathway analyses were conducted on two independent data sets using 6629 SNPs in 911 genes on 17 immune pathways from 525 glioblastoma cases and 602 controls from the University of California, San Francisco (UCSF) and a subset of 6029 SNPs in 893 genes from 531 cases and 1782 controls from MD Anderson (MDA). To further assess consistency of SNP-level associations, we also compared data from the UK (266 cases and 2482 controls) and the Mayo Clinic (114 cases and 111 controls). Although three correlated epidermal growth factor receptor (EGFR) SNPs were consistently associated with glioblastoma in all four data sets (Mantel-Haenzel P values = 1 × 10⁻5 to 4 × 10⁻³), independent replication is required as genome-wide significance was not attained. In gene-level analyses, eight immune function genes were significantly (minP < 0.05) associated with glioblastoma; the IL-2RA (CD25) cytokine gene had the smallest minP values in both UCSF (minP = 0.01) and MDA (minP = 0.001) data sets. The IL-2RA receptor is found on the surface of regulatory T cells potentially contributing to immunosuppression characteristic of the glioblastoma microenvironment. In pathway correlation analyses, cytokine signaling and adhesion-extravasation-migration pathways showed similar associations with glioblastoma risk in both MDA and UCSF data sets. Our findings represent the first systematic description of immune genes and pathways that characterize glioblastoma risk.

Interaction between 5 genetic variants and allergy in glioma risk.

The etiology of glioma is barely known. Epidemiologic studies have provided evidence for an inverse relation between glioma risk and allergic disease. Genome-wide association data have identified common genetic variants at 5p15.33 (rs2736100, TERT), 8q24.21 (rs4295627, CCDC26), 9p21.3 (rs4977756, CDKN2A-CDKN2B), 11q23.3 (rs498872, PHLDB1), and 20q13.33 (rs6010620, RTEL1) as determinants of glioma risk. The authors investigated whether there is interaction between the effects of allergy and these 5 variants on glioma risk. Data from 5 case-control studies carried out in Denmark, Finland, Sweden, and the United Kingdom (2000-2004) were used, totaling 1,029 cases and 1,668 controls. Risk was inversely associated with asthma, hay fever, eczema, and "any allergy," significantly for each factor except asthma, and was significantly positively associated with number of risk alleles for each of the 5 single nucleotide polymorphisms. There was interaction between asthma and rs498872 (greater protective effect of asthma with increasing number of risk alleles; per-allele interaction odds ratio (OR) = 0.65, P = 0.041), between "any allergy" and rs4977756 (smaller protective effect; interaction OR = 1.27, P = 0.047), and between "any allergy" and rs6010620 (greater protective effect; interaction OR = 0.70, P = 0.017). Case-only analyses provided further support for atopy interactions for rs4977756 and rs498872. This study provides evidence for possible gene-environment interactions in glioma development.

Inference from genome-wide association studies using a novel Markov model.

In this paper we propose a Bayesian modeling approach to the analysis of genome-wide association studies based on single nucleotide polymorphism (SNP) data. Our latent seed model combines various aspects of k-means clustering, hidden Markov models (HMMs) and logistic regression into a fully Bayesian model. It is fitted using the Markov chain Monte Carlo stochastic simulation method, with Metropolis-Hastings update steps. The approach is flexible, both in allowing different types of genetic models, and because it can be easily extended while remaining computationally feasible due to the use of fast algorithms for HMMs. It allows for inference primarily on the location of the causal locus and also on other parameters of interest. The latent seed model is used here to analyze three data sets, using both synthetic and real disease phenotypes with real SNP data, and shows promising results. Our method is able to correctly identify the causal locus in examples where single SNP analysis is both successful and unsuccessful at identifying the causal SNP.

Glycemic Control and Risk of Infections Among People With Type 1 or Type 2 Diabetes in a Large Primary Care Cohort Study.

OBJECTIVE: Diabetes mellitus (DM) increases the risk of infections, but the effect of better control has not been thoroughly investigated. RESEARCH DESIGN AND METHODS: With the use of English primary care data, average glycated hemoglobin (HbA1c) during 2008-2009 was estimated for 85,312 patients with DM ages 40-89 years. Infection rates during 2010-2015 compiled from primary care, linked hospital, and mortality records were estimated across 18 infection categories and further summarized as any requiring a prescription or hospitalization or as cause of death. Poisson regression was used to estimate adjusted incidence rate ratios (IRRs) by HbA1c categories across all DM, and type 1 and type 2 DM separately. IRRs also were compared with 153,341 age-sex-practice-matched controls without DM. Attributable fractions (AF%) among patients with DM were estimated for an optimal control scenario (HbA1c 6-7% [42-53 mmol/mol]). RESULTS: Long-term infection risk rose with increasing HbA1c for most outcomes. Compared with patients without DM, those with DM and optimal control (HbA1c 6-7% [42-53 mmol/mol], IRR 1.41 [95% CI 1.36-1.47]) and poor control (≥11% [97 mmol/mol], 4.70 [4.24-5.21]) had elevated hospitalization risks for infection. In patients with type 1 DM and poor control, this risk was even greater (IRR 8.47 [5.86-12.24]). Comparisons within patients with DM confirmed the risk of hospitalization with poor control (2.70 [2.43-3.00]) after adjustment for duration and other confounders. AF% of poor control were high for serious infections, particularly bone and joint (46%), endocarditis (26%), tuberculosis (24%), sepsis (21%), infection-related hospitalization (17%), and mortality (16%). CONCLUSIONS: Poor glycemic control is powerfully associated with serious infections and should be a high priority.

Risk of Infection in Type 1 and Type 2 Diabetes Compared With the General Population: A Matched Cohort Study.

OBJECTIVE: We describe in detail the burden of infections in adults with diabetes within a large national population cohort. We also compare infection rates between patients with type 1 and type 2 diabetes mellitus (T1DM and T2DM). RESEARCH DESIGN AND METHODS: A retrospective cohort study compared 102,493 English primary care patients aged 40-89 years with a diabetes diagnosis by 2008 (n = 5,863 T1DM and n = 96,630 T2DM) with 203,518 age-sex-practice-matched control subjects without diabetes. Infection rates during 2008-2015, compiled from primary care and linked hospital and mortality records, were compared across 19 individual infection categories. These were further summarized as any requiring a prescription or hospitalization or as cause of death. Poisson regression was used to estimate incidence rate ratios (IRRs) between 1) people with diabetes and control subjects and 2) T1DM and T2DM adjusted for age, sex, smoking, BMI, and deprivation. RESULTS: Compared with control subjects without diabetes, patients with diabetes had higher rates for all infections, with the highest IRRs seen for bone and joint infections, sepsis, and cellulitis. IRRs for infection-related hospitalizations were 3.71 (95% CI 3.27-4.21) for T1DM and 1.88 (95% CI 1.83-1.92) for T2DM. A direct comparison of types confirmed higher adjusted risks for T1DM versus T2DM (death from infection IRR 2.19 [95% CI 1.75-2.74]). We estimate that 6% of infection-related hospitalizations and 12% of infection-related deaths were attributable to diabetes. CONCLUSIONS: People with diabetes, particularly T1DM, are at increased risk of serious infection, representing an important population burden. Strategies that reduce the risk of developing severe infections and poor treatment outcomes are under-researched and should be explored.