Modelling the role of enzymatic pathways in the metabolism of docosahexaenoic acid by monocytes and its association with osteoarthritic pain.

Chronic pain is a major cause of disability and suffering in osteoarthritis (OA) patients. Endogenous specialised pro-resolving molecules (SPMs) curtail pro-inflammatory responses. One of the SPM intermediate oxylipins, 17-hydroxydocasahexaenoic acid (17-HDHA, a metabolite of docosahexaenoic acid (DHA)), is significantly associated with OA pain. The aim of this multidisciplinary work is to develop a mathematical model to describe the contributions of enzymatic pathways (and the genes that encode them) to the metabolism of DHA by monocytes and to the levels of the down-stream metabolites, 17-HDHA and 14-hydroxydocasahexaenoic acid (14-HDHA), motivated by novel clinical data from a study involving 30 participants with OA. The data include measurements of oxylipin levels, mRNA levels, measures of OA severity and self-reported pain scores. We propose a system of ordinary differential equations to characterise associations between the different datasets, in order to determine the homeostatic concentrations of DHA, 17-HDHA and 14-HDHA, dependent upon the gene expression of the associated metabolic enzymes. Using parameter-fitting methods, local sensitivity and uncertainty analysis, the model is shown to fit well qualitatively to experimental data. The model suggests that up-regulation of some ALOX genes may lead to the down-regulation of 17-HDHA and that dosing with 17-HDHA increases the production of resolvins, which helps to down-regulate the inflammatory response. More generally, we explore the challenges and limitations of modelling real data, in particular individual variability, and also discuss the value of gathering additional experimental data motivated by the modelling insights.

Osteoarthritis in the UK Armed Forces: a review of its impact, treatment and future research.

Within the UK Armed Forces, musculoskeletal injuries account for over half of all medical downgrades and discharges. Data from other Armed Forces show that osteoarthritis (OA), more common in military personnel, is likely to contribute to this, both in its primary form and following injury (post-traumatic OA, PTOA), which typically presents in the third or fourth decade. OA is not a progressive 'wear and tear' disease, as previously thought, but a heterogenous condition with multiple aetiologies and modulators, including joint damage, abnormal morphology, altered biomechanics, genetics, low-grade inflammation and dysregulated metabolism. Currently, clinical diagnosis, based on symptomatic or radiological criteria, is followed by supportive measures, including education, exercise, analgesia, potentially surgical intervention, with a particular focus on exercise rehabilitation within the UK military. Developments in OA have led to a new paradigm of organ failure, with an emphasis on early diagnosis and risk stratification, prevention strategies (primary, secondary and tertiary) and improved aetiological classification using genotypes and phenotypes to guide management, with the introduction of biological markers (biomarkers) potentially having a role in all these areas. In the UK Armed Forces, there are multiple research studies focused on OA risk factors, epidemiology, biomarkers and effectiveness of different interventions. This review aims to highlight OA, especially PTOA, as an important diagnosis to consider in serving personnel, outline current and future management options, and detail current research trends within the Defence Medical Services.

Harmonising knee pain patient-reported outcomes: a systematic literature review and meta-analysis of Patient Acceptable Symptom State (PASS) and individual participant data (IPD).

OBJECTIVE: In order to facilitate data pooling between studies, we explored harmonisation of patient-reported outcome measures (PROMs) in people with knee pain due to osteoarthritis or knee trauma, using the Patient Acceptable Symptom State scores (PASS) as a criterion. METHODS: We undertook a systematic literature review (SLR) of PASS scores, and performed individual participant data (IPD) analysis of score distributions from concurrently completed PROM pairs. Numerical rating scales (NRS), visual analogue scales, KOOS and WOMAC pain questionnaires were standardised to 0 to 100 (worst) scales. Meta-regression explored associations of PASS. Bland Altman plots compared PROM scores within individuals using IPD from WebEx, KICK, MenTOR and NEKO studies. RESULTS: SLR identified 18 studies reporting PASS in people with knee pain. Pooled standardised PASS was 27 (95% CI: 21 to 35; n = 6,339). PASS was statistically similar for each standardised PROM. Lower PASS was associated with lower baseline pain (ß = 0.49, P = 0.01) and longer time from treatment initiation (Q = 6.35, P = 0.04). PASS scores were lowest in ligament rupture (12, 95% CI: 11 to 13), but similar between knee osteoarthritis (31, 95% CI: 26 to 36) and meniscal tear (27, 95% CI: 20 to 35). In IPD, standardised PROMs each revealed similar group mean scores, but scores within individuals diverged between PROMs (LoA between -7 to -38 and +25 to 52). CONCLUSION: Different standardised PROMs give similar PASS thresholds in group data. PASS thresholds may be affected more by patient and treatment characteristics than between PROMs. However, different PROMs give divergent scores within individuals, possibly reflecting different experiences of pain.

A consensus-based framework for conducting and reporting osteoarthritis phenotype research.

BACKGROUND: The concept of osteoarthritis (OA) heterogeneity is evolving and gaining renewed interest. According to this concept, distinct subtypes of OA need to be defined that will likely require recognition in research design and different approaches to clinical management. Although seemingly plausible, a wide range of views exist on how best to operationalize this concept. The current project aimed to provide consensus-based definitions and recommendations that together create a framework for conducting and reporting OA phenotype research. METHODS: A panel of 25 members with expertise in OA phenotype research was composed. First, panel members participated in an online Delphi exercise to provide a number of basic definitions and statements relating to OA phenotypes and OA phenotype research. Second, panel members provided input on a set of recommendations for reporting on OA phenotype studies. RESULTS: Four Delphi rounds were required to achieve sufficient agreement on 11 definitions and statements. OA phenotypes were defined as subtypes of OA that share distinct underlying pathobiological and pain mechanisms and their structural and functional consequences. Reporting recommendations pertaining to the study characteristics, study population, data collection, statistical analysis, and appraisal of OA phenotype studies were provided. CONCLUSIONS: This study provides a number of consensus-based definitions and recommendations relating to OA phenotypes. The resulting framework is intended to facilitate research on OA phenotypes and increase combined efforts to develop effective OA phenotype classification. Success in this endeavor will hopefully translate into more effective, differentiated OA management that will benefit a multitude of OA patients.

Microarray analyses of the dorsal root ganglia support a role for innate neuro-immune pathways in persistent pain in experimental osteoarthritis.

OBJECTIVE: Following destabilization of the medial meniscus (DMM), mice develop experimental osteoarthritis (OA) and associated pain behaviors that are dependent on the stage of disease. We aimed to describe changes in gene expression in knee-innervating dorsal root ganglia (DRG) after surgery, in order to identify molecular pathways associated with three pre-defined pain phenotypes: "post-surgical pain", "early-stage OA pain", and "persistent OA pain". DESIGN: We performed DMM or sham surgery in 10-week old male C57BL/6 mice and harvested L3-L5 DRG 4, 8, and 16 weeks after surgery or from age-matched naïve mice (n = 3/group). RNA was extracted and an Affymetrix Mouse Transcriptome Array 1.0 was performed. Three pain phenotypes were defined: "post-surgical pain" (sham and DMM 4-week vs 14-week old naïve), "early OA pain" (DMM 4-week vs sham 4-week), and "persistent OA pain" (DMM 8- and 16-week vs naïve and sham 8- and 16-week). 'Top hit' genes were defined as P < 0.001. Pathway analysis (Ingenuity Pathway Analysis) was conducted using differentially expressed genes defined as P < 0.05. In addition, we performed qPCR for Ngf and immunohistochemistry for F4/80+ macrophages in the DRG. RESULTS: For each phenotype, top hit genes identified a small number of differentially expressed genes, some of which have been previously associated with pain (7/67 for "post-surgical pain"; 2/14 for "early OA pain"; 8/37 for "persistent OA pain"). Overlap between groups was limited, with 8 genes differentially regulated (P < 0.05) in all three phenotypes. Pathway analysis showed that in the persistent OA pain phase many of the functions of differentially regulated genes are related to immune cell recruitment and activation. Genes previously linked to OA pain (CX3CL1, CCL2, TLR1, and NGF) were upregulated in this phenotype and contributed to activation of the neuroinflammation canonical pathway. In separate sets of mice, we confirmed that Ngf was elevated in the DRG 8 weeks after DMM (P = 0.03), and numbers of F4/80+ macrophages were increased 16 weeks after DMM (P = 0.002 vs Sham). CONCLUSION: These transcriptomics findings support the idea that distinct molecular pathways discriminate early from persistent OA pain. Pathway analysis suggests neuroimmune interactions in the DRG contribute to initiation and maintenance of pain in OA.

Metabolic syndrome and osteoarthritis pain: common molecular mechanisms and potential therapeutic implications.

There is no clear evidence from epidemiological and animal studies of a direct link between metabolic syndrome (MetS) and cartilage degeneration in osteoarthritis (OA) once body mass index (BMI) has been considered. However, recent epidemiological studies indicate a significant role for MetS in predicting increased knee pain after adjustment for BMI. This implies there are mechanisms that underlie both MetS and OA pain. In addition to the common systemic inflammatory and pro-inflammatory components of the two disorders, there are other molecular mechanisms that may link MetS and OA pain. These include regulation of the endocannabinoid system, activation of the transient receptor potential cation channel vanilloid subfamily member 1 (TRPV1) channel and gut dysbiosis. These three mechanisms are interlinked and are the target of therapeutic dietary or pharmacological interventions. Exploring and understanding these mechanisms may help improve outcomes for both pain and metabolic comorbidities affecting individuals with OA.

Thresholds of ultrasound synovial abnormalities for knee osteoarthritis - a cross sectional study in the general population.

OBJECTIVE: To establish "normal" ranges for synovial thickness and effusion detected by ultrasound (US) and to determine cut-offs associated with knee pain (KP) and radiographic knee osteoarthritis (RKOA) in the community. METHODS: 147 women and 152 men ≥40 years old were randomly selected from the Nottingham KP and Related Health in the Community (KPIC) cohort (n = 9506). The "normal" range was established using the percentile method in 163 participants who had no KP and no RKOA. Optimal (maximum sensitivity and specificity) and high specificity (90%) cut-offs were established using receiver operating characteristic (ROC) curve analysis in a comparison between people with both KP and RKOA and normal controls. RESULTS: Effusion and synovial hypertrophy differed by gender but not by age or laterality, therefore gender-specific reference limits were estimated. However, the "normal" ranges between men and women were similar for effusion (0-10.3 mm vs 0-9.8 mm), but different for synovial hypertrophy (0-6.8 mm vs 0-5.4 mm). Power Doppler Signal (PDS) in the healthy controls was uncommon (1.2% in men and 0.0% in women). The optimal cut-off was 7.4 mm for men and 5.3 mm for women for effusion, and 3.7 and 1.6 for hypertrophy respectively. The high specificity cut-off was 8.9 for men and 7.8 for women for effusion, and 5.8 and 4.2 for hypertrophy respectively. CONCLUSIONS: US effusion and synovial hypertrophy but not PDS are common, but differ by gender, in community-derived people without painful knee OA. Currently used cut-offs for abnormality need reappraisal.

Contribution of central and peripheral risk factors to prevalence, incidence and progression of knee pain: a community-based cohort study.

AIM: To explore risk factors that may influence knee pain (KP) through central or peripheral mechanisms. METHODS: A questionnaire-based prospective community cohort study with KP defined as pain in or around a knee on most days for at least a month. Baseline prevalence, and one year incidence and progression (KP worsening) were examined. Central (e.g., Pain Catastrophizing Scale (PCS)) and peripheral (e.g., significant injury) risk factors were examined. Adjusted odds ratio (OR) and 95% confidence interval (CI) were calculated using logistic regression. Proportional risk contribution (PRC) was estimated using receiver-operator-characteristic (ROC) analysis. RESULTS: Of 9506 baseline participants, 4288 (45%) had KP (men 1826; women, 2462). KP incidence was 12% (men 11%, women 13%), and KP progression 19% (men 16%, women 21%) at one year. While both central and peripheral factors contributed to prevalence, central factors contributed more to progression, and peripheral factors more to incidence of KP. For example, although PCS (OR 2.06, 95% CI 1.88-2.25) and injury (5.62, 4.92-6.42) associated with KP prevalence, PCS associated with progression (2.27, 1.83-2.83) but not incidence (1.14, 0.86-1.52), whereas injury more strongly associated with incidence (69.27, 24.15-198.7) than progression (2.52, 1.48-4.30). The PRC of central and peripheral factors were 19% and 23% for prevalence, 14% and 29% for incidence, and 29% and 5% for progression, respectively. CONCLUSIONS: Both central and peripheral risk factors influence KP but relative contributions may differ in terms of development (mainly peripheral) and progression (mainly central). Further study of such relative contributions may inform primary and secondary prevention strategies.

Knee pain and related health in the community study (KPIC): a cohort study protocol.

BACKGROUND: The incidence, progression and related risk factors for recent-onset knee pain (KP) remain uncertain. This study aims to examine the natural history of KP including incidence and progression and to identify possible phenotypes and their associated risk factors. METHODS: A prospective community-based cohort of men and women aged 40 years or over within the East Midlands region (UK) will be recruited via a postal questionnaire from their general practices. The questionnaire will enquire about: presence and onset of KP; pain severity (0­10 numerical rating scale (NRS)); pain catastrophizing and neuropathic-like pain (NP) using the painDETECT questionnaires (definite NP scores ≥19­38); risk factors for KP and/ or osteoarthritis (OA) (age, body mass index, constitutional knee alignment, nodal OA, index: ring finger length (2D4D) ratio); quality of life (SF12); and mental health (Hospital Anxiety and Depression Scale). Clinical assessments will be undertaken in a sample of 400 participants comprising three groups: early KP (≤3 year's duration), established KP (>3 years) and no KP. Assessments will include knee radiographs (standing semi-flexed and 30(0) skyline views); knee ultrasound (synovial effusion, hypertrophy, and Doppler activity); quantitative sensory testing; muscle strength (quadriceps, hip abductor, and hand-grip); balance; gait analysis (GAITrite); and biomarker sampling. A repeat questionnaire will be sent to responders at years 1 and 3. The baseline early KP group will undergo repeat assessments at year 1 (apart from radiographs) and year 3 (with radiographs). Any incident KP individuals identified at year 1 or 3 questionnaires will have clinical and radiographic assessments at the respective time points. DISCUSSION: Baseline data will be used to examine risk factors for early onset KP and to identify KP phenotypes. Subsequent prospective data, at least to Year 3, will allow examination of the natural history of KP and risk factors for incidence and progression. TRIAL REGISTRATION: The study was registered on the clinicaltrials.gov portal: NCT02098070) on the 14th of March 2014.

Pain in knee osteoarthritis is associated with variation in the neurokinin 1/substance P receptor (TACR1) gene.

BACKGROUND: Substance P (SP) is a pain- and inflammation-related neuropeptide which preferentially binds to the neurokinin receptor 1 (NK1 ). SP and NK1 receptors have been implicated in joint pain, inflammation and damage in animal models and human studies of osteoarthritis (OA). The aim of this study was to test if genetic variation at the neurokinin 1 receptor gene (TACR1) is associated with pain in individuals with radiographic knee OA. METHODS: Participants from the Genetics of OA and Lifestyle study were used for the discovery group (n = 1615). Genotype data for six SNPs selected to cover most variation in the TACR1 gene were used to test for an association with symptomatic OA. Replication analysis was performed using data from the Chingford 1000 Women Study, Hertfordshire Cohort Study, Tasmanian Older Adult Cohort Study and the Clearwater OA Study. In total, n = 1715 symptomatic OA and n = 735 asymptomatic OA individuals were analysed. RESULTS: Out of six SNPs tested in the TACR1 gene, one (rs11688000) showed a nominally significant association with a decreased risk of symptomatic OA in the discovery cohort. This was then replicated in four additional cohorts. After adjusting for age, gender, body mass index and radiographic severity, the G (minor) allele at rs11688000 was associated with a decreased risk of symptomatic OA compared to asymptomatic OA cases (p = 9.90 × 10-4 , OR = 0.79 95% 0.68-0.90 after meta-analysis). CONCLUSIONS: This study supports a contribution from the TACR1 gene in human OA pain, supporting further investigation of this gene's function in OA. SIGNIFICANCE: This study contributes to the knowledge of the genetics of painful osteoarthritis, a condition which affects millions of individuals worldwide. Specifically, a contribution from the TACR1 gene to modulating pain sensitivity in osteoarthritis is suggested.

Gut microbiome diversity and high-fibre intake are related to lower long-term weight gain.

BACKGROUND: Cross-sectional studies suggest that the microbes in the human gut have a role in obesity by influencing the human body's ability to extract and store calories. The aim of this study was to assess if there is a correlation between change in body weight over time and gut microbiome composition. METHODS: We analysed 16S ribosomal RNA gene sequence data derived from the faecal samples of 1632 healthy females from TwinsUK to investigate the association between gut microbiome measured cross-sectionally and longitudinal weight gain (adjusted for caloric intake and baseline body mass index). Dietary fibre intake was investigated as a possible modifier. RESULTS: Less than half of the variation in long-term weight change was found to be heritable (h2=0.41 (0.31, 0.47)). Gut microbiota diversity was negatively associated with long-term weight gain, whereas it was positively correlated with fibre intake. Nine bacterial operational taxonomic units (OTUs) were significantly associated with weight gain after adjusting for covariates, family relatedness and multiple testing (false discovery rate <0.05). OTUs associated with lower long-term weight gain included those assigned to Ruminococcaceae (associated in mice with improved energy metabolism) and Lachnospiraceae. A Bacterioides species OTU was associated with increased risk of weight gain but this appears to be driven by its correlation with lower levels of diversity. CONCLUSIONS: High gut microbiome diversity, high-fibre intake and OTUs implicated in animal models of improved energy metabolism are all correlated with lower term weight gain in humans independently of calorie intake and other confounders.

Untangling the relationship between diet and visceral fat mass through blood metabolomics and gut microbiome profiling.

BACKGROUND/OBJECTIVES: Higher visceral fat mass (VFM) is associated with an increased risk for developing cardio-metabolic diseases. The mechanisms by which an unhealthy diet pattern may influence visceral fat (VF) development has yet to be examined through cutting-edge multi-omic methods. Therefore, our objective was to examine the dietary influences on VFM and identify gut microbiome and metabolite profiles that link food intakes to VFM. SUBJECTS/METHODS: In 2218 twins with VFM, food intake and metabolomics data available we identified food intakes most strongly associated with VFM in 50% of the sample, then constructed and tested the 'VFM diet score' in the remainder of the sample. Using linear regression (adjusted for covariates, including body mass index and total fat mass), we investigated associations between the VFM diet score, the blood metabolomics profile and the fecal microbiome (n=889), and confirmed these associations with VFM. We replicated top findings in monozygotic (MZ) twins discordant (⩾1 s.d. apart) for VFM, matched for age, sex and the baseline genetic sequence. RESULTS: Four metabolites were associated with the VFM diet score and VFM: hippurate, alpha-hydroxyisovalerate, bilirubin (Z,Z) and butyrylcarnitine. We replicated associations between VFM and the diet score (beta (s.e.): 0.281 (0.091); P=0.002), butyrylcarnitine (0.199 (0.087); P=0.023) and hippurate (-0.297 (0.095); P=0.002) in VFM-discordant MZ twins. We identified a single species, Eubacterium dolichum to be associated with the VFM diet score (0.042 (0.011), P=8.47 × 10-5), VFM (0.057 (0.019), P=2.73 × 10-3) and hippurate (-0.075 (0.032), P=0.021). Moreover, higher blood hippurate was associated with elevated adipose tissue expression neuroglobin, with roles in cellular oxygen homeostasis (0.016 (0.004), P=9.82x10-6). CONCLUSIONS: We linked a dietary VFM score and VFM to E. dolichum and four metabolites in the blood. In particular, the relationship between hippurate, a metabolite derived from microbial metabolism of dietary polyphenols, and reduced VFM, the microbiome and increased adipose tissue expression of neuroglobin provides potential mechanistic insight into the influence of diet on VFM.

KIR haplotypes are associated with late-onset type 1 diabetes in European-American families.

Classical human leukocyte antigens (HLA) genes confer the strongest, but not the only, genetic susceptibility to type 1 diabetes. Killer cell immunoglobulin-like receptors (KIR), on natural killer (NK) cells, bind ligands including class I HLA. We examined presence or absence, with copy number, of KIR loci in 1698 individuals, from 339 multiplex type 1 diabetes families, from the Human Biological Data Interchange, previously genotyped for HLA. Combining family data with KIR copy number information allowed assignment of haplotypes using identity by descent. This is the first disease study to use KIR copy number typing and unambiguously define haplotypes by gene transmission. KIR A1 haplotypes were positively associated with T1D in the subset of patients without the high T1D risk HLA genotype, DR3/DR4 (odds ratio=1.29, P=0.0096). The data point to a role for KIR in type 1 diabetes risk in late-onset patients. In the top quartile (age of onset>14), KIR A2 haplotype was overtransmitted (63.4%, odds ratio=1.73, P=0.024) and KIR B haplotypes were undertransmitted (41.1%, odds ratio=0.70, P=0.0052) to patients. The data suggest that inhibitory 'A' haplotypes are predisposing and stimulatory 'B' haplotypes confer protection in both DR3/DR4-negative and late-onset patient groups.

Large scale meta-analysis of urinary C-terminal telopeptide, serum cartilage oligomeric protein and matrix metalloprotease degraded type II collagen and their role in prevalence, incidence and progression of osteoarthritis.

OBJECTIVE: To evaluate the role of three cartilage-derived biomarkers on osteoarthritis (OA): urinary C-terminal telopeptide (uCTX-II), serum cartilage oligomeric protein (sCOMP), and serum MMP degraded type II collagen (sC2M). SUBJECTS AND METHODS: Samples from 3582 individuals from the Rotterdam Study, the Genetics osteoArthritis and Progression (GARP), the Chingford Study and the TwinsUK cohort were assayed using enzyme-linked immune sorbent assays. Log10 of concentration levels were correlated with risk of hip, hand and knee OA, hip and knee OA severity and incidence, and progression of knee OA, adjusting for age, gender and body mass index (BMI). Results were meta-analysed to assess overall significance. RESULTS: After adjusting for covariates, sCOMP was associated with knee OA and hip and knee OA incidence. Furthermore, sC2M was associated with knee OA incidence and progression. After adjustment for multiple tests (Bonferroni P < 0.002) only the association between sCOMP and knee OA remained significant (odds ratio (OR) = 3.26 (95%CI 1.63-10.1) P = 0.0008 for each standard deviation (SD) increase in biomarker levels). Levels of uCTX-II were significantly associated with risk of hand, hip and knee OA, progression and incidence of knee OA. A receiver operating characteristics (ROC) analysis showed a consistent improvement in prediction of knee OA progression from an average area under the curve (AUC) is 0.646 for age, sex and BMI alone to an AUC = 0.668 including uCTX-II for prediction. CONCLUSIONS: uCTX-II is the most informative biochemical marker for prediction of OA. Both sCOMP and C2M showed some association with OA, thus indicating that they are descriptive of disease activity.

Prediction model for knee osteoarthritis incidence, including clinical, genetic and biochemical risk factors.

OBJECTIVE: To develop and validate a prognostic model for incident knee osteoarthritis (KOA) in a general population and determine the value of different risk factor groups to prediction. METHODS: The prognostic model was developed in 2628 individuals from the Rotterdam Study-I (RS-I). Univariate and multivariate analyses were performed for questionnaire/easily obtainable variables, imaging variables, genetic and biochemical markers. The extended multivariate model was tested on discrimination (receiver operating characteristic curve and area under the curve (AUC)) in two other population-based cohorts: Rotterdam Study-II and Chingford Study. RESULTS: In RS-I, there was moderate predictive value for incident KOA based on the genetic score alone in subjects aged <65 years (AUC 0.65), while it was only 0.55 for subjects aged ≥65 years. The AUC for gender, age and body mass index (BMI) in prediction for KOA was 0.66. Addition of the questionnaire variables, genetic score or biochemical marker urinary C-terminal cross-linked telopeptide of type II collagen to the model did not change the AUC. However, when adding the knee baseline KL score to the model the AUC increased to 0.79. Applying external validation, similar results were observed in the Rotterdam Study-II and the Chingford Study. CONCLUSIONS: Easy obtainable 'Questionnaire' variables, genetic markers, OA at other joint sites and biochemical markers add only modestly to the prediction of KOA incidence using age, gender and BMI in an elderly population. Doubtful minor radiographic degenerative features in the knee, however, are a very strong predictor of future KOA. This is an important finding, as many radiologists do not report minor degenerative changes in the knee.

Use of class I and class II HLA loci for predicting age at onset of type 1 diabetes in multiple populations.

AIMS/HYPOTHESIS: The study aimed to assess, in multiple populations, the role of HLA alleles on early and late age at onset of type 1 diabetes. METHODS: Stepwise linear regression models were used to determine which HLA class I and class II risk alleles to include. High-resolution genotyping data for patients from the Type 1 Diabetes Genetics Consortium (T1DGC) collection (n = 2,278) and four independent cohorts from Denmark, Sardinia and the USA (Human Biological Data Interchange [HBDI] and Joslin Diabetes Center) (n = 1,324) (total n = 3,602) were used to assess the role of HLA variation on age of onset and predict early onset (age ≤ 5 years) and late onset (age ≥ 15 years) of type 1 diabetes. RESULTS: In addition to carriage of HLA class I alleles A*24:02, B*39:06, B*44:03 and B*18:01, HLA class II DRB1-DQB1 loci significantly contributed to age at onset, explaining 3.4% of its variance in the combined data. HLA genotypes, together with sex, were able to predict late onset in all cohorts studied, with AUC values ranging from 0.58 to 0.63. Similar AUC values (0.59-0.70) were obtained for early onset for most cohorts, except in the Sardinian study, in which none of the models tested had significant predictive power. CONCLUSIONS/INTERPRETATION: HLA associations with age of onset are consistent across most white populations and HLA information can predict some of the risk of early and late onset of type 1 diabetes. Considerable heterogeneity was observed between Sardinian and other populations, particularly with regard to early age of onset.

Race-specific type 1 diabetes risk of HLA-DR7 haplotypes.

The aim of this study was to test the hypothesis that closely related human leukocyte antigen (HLA) haplotypes containing the DRB1*07:01 gene ['DR7' (DRB1*07:01-DQA1*02:01-DQB1*02:01g or DRB1*07:01-DQA1*03:01-DQB1*02:01g) haplotypes] derived from European and African populations differ in their genetic susceptibility for type 1 diabetes (T1D) depending on the DQ-α molecule present. A combined total of 98 African American T1D patients from the Type 1 Diabetes Genetics Consortium and from Children's Hospital and Research Center Oakland were genotyped for the HLA class II loci DRB1, DQA1, and DQB1. DNA samples extracted from newborn blood spot cards from African Americans born in California (n = 947) were used as a population-based control group. Among African American cases, the European-derived DRB1*07:01-DQA1*02:01-DQB1*02:01g haplotype was protective for T1D risk (odds ratio (OR) = 0.34; 95% confidence interval (CI) 0.14-0.78; P < 0.011), but the African-derived DRB1*07:01-DQA1*03:01-DQB1*02:01g haplotype increased T1D risk (OR = 3.96; 95% CI 1.94-8.08; P < 5.5E-05). The effect of DRB1*07:01-DQB1*02:01g on T1D susceptibility depends on the DQA1 allele. DRB1*07:01-DQA1*02:01-DQB1*02:01g is protective for T1D; however, the presence of DQA1*03:01 on the DRB1*07:01-DQB1*02:01g haplotype not only renders the DR7 haplotype not protective but also creates a haplotype with significant T1D risk. These data underscore the importance of assessing genetic effects within ethnic context.