Deciphering osteoarthritis genetics across 826,690 individuals from 9 populations.

Osteoarthritis affects over 300 million people worldwide. Here, we conduct a genome-wide association study meta-analysis across 826,690 individuals (177,517 with osteoarthritis) and identify 100 independently associated risk variants across 11 osteoarthritis phenotypes, 52 of which have not been associated with the disease before. We report thumb and spine osteoarthritis risk variants and identify differences in genetic effects between weight-bearing and non-weight-bearing joints. We identify sex-specific and early age-at-onset osteoarthritis risk loci. We integrate functional genomics data from primary patient tissues (including articular cartilage, subchondral bone, and osteophytic cartilage) and identify high-confidence effector genes. We provide evidence for genetic correlation with phenotypes related to pain, the main disease symptom, and identify likely causal genes linked to neuronal processes. Our results provide insights into key molecular players in disease processes and highlight attractive drug targets to accelerate translation.

An epigenome-wide view of osteoarthritis in primary tissues.

Osteoarthritis is a complex degenerative joint disease. Here, we investigate matched genotype and methylation profiles of primary chondrocytes from macroscopically intact (low-grade) and degraded (high-grade) osteoarthritis cartilage and from synoviocytes collected from 98 osteoarthritis-affected individuals undergoing knee replacement surgery. We perform an epigenome-wide association study of knee cartilage degeneration and report robustly replicating methylation markers, which reveal an etiologic mechanism linked to the migration of epithelial cells. Using machine learning, we derive methylation models of cartilage degeneration, which we validate with 82% accuracy in independent data. We report a genome-wide methylation quantitative trait locus (mQTL) map of articular cartilage and synovium and identify 18 disease-grade-specific mQTLs in osteoarthritis cartilage. We resolve osteoarthritis GWAS loci through causal inference and colocalization analyses and decipher the epigenetic mechanisms that mediate the effect of genotype on disease risk. Together, our findings provide enhanced insights into epigenetic mechanisms underlying osteoarthritis in primary tissues.

Risk of COVID-19 death for people with a pre-existing cancer diagnosis prior to COVID-19-vaccination: A systematic review and meta-analysis.

While previous reviews found a positive association between pre-existing cancer diagnosis and COVID-19-related death, most early studies did not distinguish long-term cancer survivors from those recently diagnosed/treated, nor adjust for important confounders including age. We aimed to consolidate higher-quality evidence on risk of COVID-19-related death for people with recent/active cancer (compared to people without) in the pre-COVID-19-vaccination period. We searched the WHO COVID-19 Global Research Database (20 December 2021), and Medline and Embase (10 May 2023). We included studies adjusting for age and sex, and providing details of cancer status. Risk-of-bias assessment was based on the Newcastle-Ottawa Scale. Pooled adjusted odds or risk ratios (aORs, aRRs) or hazard ratios (aHRs) and 95% confidence intervals (95% CIs) were calculated using generic inverse-variance random-effects models. Random-effects meta-regressions were used to assess associations between effect estimates and time since cancer diagnosis/treatment. Of 23 773 unique title/abstract records, 39 studies were eligible for inclusion (2 low, 17 moderate, 20 high risk of bias). Risk of COVID-19-related death was higher for people with active or recently diagnosed/treated cancer (general population: aOR = 1.48, 95% CI: 1.36-1.61, I2 = 0; people with COVID-19: aOR = 1.58, 95% CI: 1.41-1.77, I2 = 0.58; inpatients with COVID-19: aOR = 1.66, 95% CI: 1.34-2.06, I2 = 0.98). Risks were more elevated for lung (general population: aOR = 3.4, 95% CI: 2.4-4.7) and hematological cancers (general population: aOR = 2.13, 95% CI: 1.68-2.68, I2 = 0.43), and for metastatic cancers. Meta-regression suggested risk of COVID-19-related death decreased with time since diagnosis/treatment, for example, for any/solid cancers, fitted aOR = 1.55 (95% CI: 1.37-1.75) at 1 year and aOR = 0.98 (95% CI: 0.80-1.20) at 5 years post-cancer diagnosis/treatment. In conclusion, before COVID-19-vaccination, risk of COVID-19-related death was higher for people with recent cancer, with risk depending on cancer type and time since diagnosis/treatment.

A molecular map of long non-coding RNA expression, isoform switching and alternative splicing in osteoarthritis.

Osteoarthritis is a prevalent joint disease and a major cause of disability worldwide with no curative therapy. Development of disease-modifying therapies requires a better understanding of the molecular mechanisms underpinning disease. A hallmark of osteoarthritis is cartilage degradation. To define molecular events characterizing osteoarthritis at the whole transcriptome level, we performed deep RNA sequencing in paired samples of low- and high-osteoarthritis grade knee cartilage derived from 124 patients undergoing total joint replacement. We detected differential expression between low- and high-osteoarthritis grade articular cartilage for 365 genes and identified a 38-gene signature in osteoarthritis cartilage by replicating our findings in an independent dataset. We also found differential expression for 25 novel long non-coding RNA genes (lncRNAs) and identified potential lncRNA interactions with RNA-binding proteins in osteoarthritis. We assessed alterations in the relative usage of individual gene transcripts and identified differential transcript usage for 82 genes, including ABI3BP, coding for an extracellular matrix protein, AKT1S1, a negative regulator of the mTOR pathway and TPRM4, coding for a transient receptor potential channel. We further assessed genome-wide differential splicing, for the first time in osteoarthritis, and detected differential splicing for 209 genes, which were enriched for extracellular matrix, proteoglycans and integrin surface interactions terms. In the largest study of its kind in osteoarthritis, we find that isoform and splicing changes, in addition to extensive differences in both coding and non-coding sequence expression, are associated with disease and demonstrate a novel layer of genomic complexity to osteoarthritis pathogenesis.

Medication and procedural abortions before 13 weeks gestation and risk of psychiatric disorders.

BACKGROUND: The proportion of abortions provided by medication in the United States and worldwide has increased greatly since the U.S. Food and Drug Administration approved mifepristone in 2000. While existing research has shown that abortion does not increase risk of mental health problems, no population-based study has examined specifically whether a procedural or medication abortion increases risk of mental health disorders. OBJECTIVE: This study examined whether mental health disorders increased in the shorter and longer-term after a medication or procedural abortion. STUDY DESIGN: Using Danish population registers' data, we conducted a prospective cohort study in which we included 72,424 females born in Denmark between 1980 and 2006, who were ages 12 to 38 during the study period and had a first first-trimester abortion before 13 weeks gestation in 2000 to 2018. Females with no previous psychiatric diagnoses were followed from 1 year before their abortion until their first psychiatric diagnosis, December 31, 2018, emigration from Demark, or death, whichever came first. Risk of any first psychiatric disorder was defined as a recorded psychiatric diagnosis at an in- or out-patient facility from the 1 year after to more than 5 years after a medication or procedural abortion relative to the year beforehand. Results were adjusted for calendar year, age, gestational age, partner status, prior mental and physical health, childbirth history, childhood environment, and parental mental health history. RESULTS: Females having medication (n=37,155) and procedural abortions (n=35,269) had the same risk of any first psychiatric diagnosis in the year after their abortion relative to the year before their abortion (medication abortion adjusted incidence rate ratio [MaIRR]=1.02, 95% confidence interval [CI]: 0.93-1.12; procedural abortion adjusted incidence rate ratio [PaIRR]=0.94, 95% CI: 0.86-1.02). Moreover, as more time from the abortion passed, the risk of a psychiatric diagnoses decreased relative to the year before their abortion for each abortion method (MaIRR 1-2 years after=0.89, 95% CI: 0.80-0.98; PaIRR 1-2 years after=0.81, 95% CI: 0.88-1.05; MaIRR 2-5 years after=0.77, 95% CI: 0.71-0.84; PaIRR 2-5 years after=0.72, 95% CI: 0.67-0.78; MaIRR 5+ years after=0.58, 95% CI: 0.53-0.63; PaIRR 5+ years after=0.54, 95% CI: 0.50-0.58). CONCLUSION: Because the risk of psychiatric diagnoses was the same in the year after relative to the year before a medication and procedural abortion and the risk did not increase as more time after the abortion increased, neither abortion method increased risk of mental health disorders in the shorter or longer-term.

Multiple myeloma incidence, mortality, and prevalence estimates and projections, Australia, 1982-2043: a statistical modelling study.

OBJECTIVES: To examine changes in multiple myeloma incidence and mortality rates during 1982-2018, and to estimate its incidence, mortality, and prevalence for 2019-2043. STUDY DESIGN: Population-based statistical modelling study; analysis of and projections based on Australian Institute of Health and Welfare multiple myeloma incidence, mortality, and survival data. SETTING: Australia, 1982-2018 (historical data) and projections to 2043. MAIN OUTCOME MEASURES: Changes in multiple myeloma incidence and mortality rates, 1982-2018, determined by joinpoint regression analysis (age-standardised to 2021 Australian population); projection of rates to 2043 based on age-period-cohort models; estimated 5- and 30-year prevalence of multiple myeloma (modified counting method). RESULTS: The incidence of multiple myeloma increased during 1982-2018 (eg, annual percentage change [APC], 2006-2018, 1.9%; 95% confidence interval [CI], 1.7-2.2%), but the mortality rate declined during 1990-2018 (APC, -0.4%; 95% CI, -0.5% to -0.2%). The age-standardised incidence rate was projected to increase by 14.9% during 2018-2043, from 8.7 in 2018 to 10.0 (95% CI, 9.4-10.7) new cases per 100 000 population in 2043; the mortality rate was projected to decline by 27.5%, from 4.0 to 2.9 (95% CI, 2.6-3.3) deaths per 100 000 population. The annual number of people newly diagnosed with multiple myeloma was estimated to increase by 89.2%, from 2120 in 2018 to 4012 in 2043; the number of deaths from multiple myeloma was projected to increase by 31.7%, from 979 to 1289. The number of people living with multiple myeloma up to 30 years after initial diagnosis was projected to increase by 163%, from 10 288 in 2018 to 27 093 in 2043, including 13 019 people (48.1%) diagnosed during the preceding five years. CONCLUSION: Although the decline in the mortality rate was projected to continue, the projected increases in the incidence and prevalence of multiple myeloma in Australia over the next 25 years indicate that investment in prevention and early detection research, and planning for prolonged treatment and care, are needed.

Out-of-pocket health care expenses for people with and without cancer, New South Wales, 2020: a cross-sectional study.

OBJECTIVES: To investigate self-reported out-of-pocket health care expenses, both overall and by cost type, for a large population-based sample of Australians, by cancer status and socio-demographic and medical characteristics. STUDY DESIGN: Cross-sectional study. SETTING, PARTICIPANTS: New South Wales residents participating in the 45 and Up Study (recruited aged 45 years or older during 2005-2009) who completed the 2020 follow-up questionnaire; survey responses linked with New South Wales Cancer Registry data. MAIN OUTCOME MEASURES: Proportions of respondents who reported that out-of-pocket health care expenses during the preceding twelve months exceeded $1000 or $10 000; adjusted odds ratios (aORs) for associations with socio-demographic and medical characteristics. RESULTS: Of the 267 357 recruited 45 and Up Study participants, 45 061 completed the 2020 survey (response rate, 53%); 42.7% (95% confidence interval [CI], 42.2-43.1%) reported that overall out-of-pocket health care expenses during the previous year exceeded $1000, including 55.4% (52.1-58.7%) of participants diagnosed in the preceding two years and 44.9% (43.7-46.1%) of participants diagnosed with cancer more than two years ago. After adjustment for socio-demographic factors, out-of-pocket expenses greater than $1000 were more likely to be reported by participants with cancer than by those without cancer (diagnosis in past two years: aOR, 2.06 [95% CI, 1.77-2.40]; diagnosis more than two years ago: aOR, 1.22 [95% CI, 1.15-1.29]). The odds of out-of-pocket expenses exceeding $1000 increased with area-based socio-economic advantage and household income, and were higher for people with private health insurance (v people with Medicare coverage only: aOR, 1.64; 95% CI, 1.53-1.75). Out-of-pocket expenses exceeding $10 000 were also more likely for participants diagnosed with cancer during the past two years (v no cancer: aOR, 3.30; 95% CI, 2.56-4.26). CONCLUSIONS: People diagnosed with cancer during the past two years were much more likely than people without cancer to report twelve-month out-of-pocket health care expenses that exceeded $1000. Out-of-pocket expenses for people with cancer can exacerbate financial strain at a time of vulnerability, and affect health care equity because some people cannot pay for all available treatments.

Female reproductive and hormonal factors and lung cancer mortality among never-smokers: A prospective cohort study of 287 408 Chinese women.

There is growing, but inconsistent evidence suggesting oestrogen may play a key role in lung cancer development, especially among never-smoking women for whom lung cancer risk factors remain largely elusive. Using the China Kadoorie Biobank, a large-scale prospective cohort with 302 510 women aged 30 to 79 years recruited from 10 regions in China during 2004 to 2008, we assessed the risk of lung cancer death among self-reported never-smoking women who were cancer-free at baseline, in relation to age at menarche, age at menopause, time since menopause, prior use of oral contraceptives (OCP), number of livebirths, breastfeeding and age at first livebirth. Women were followed up to December 31, 2016 with linkage to mortality data. Hazard ratios (HR) and 95% confidence intervals (CI) were estimated using Cox regression, adjusting for key confounders including several socio-demographic, environmental and lifestyle factors. Among 287 408 never-smoking women, 814 died from lung cancer with a median follow-up of 10.3 years. Women who had used OCP within 15 years prior to baseline had a significantly higher hazard of lung cancer death compared with never-users: HR = 1.85 (95% CI: 1.14-3.00) and risk increased by 6% with each additional year of use: HR = 1.06 (1.01-1.10). Among parous women, the hazard of lung cancer death increased by 13% with each single livebirth: HR = 1.13 (1.05-1.23); and among post-menopausal women, the risk increased by 2% with each year since menopause: HR = 1.02 (1.01-1.04). These results suggest that reproductive factors which were proxies for lower endogenous oestrogen level, for example, longer duration of OCP use, could play a role in lung cancer development.

Pathways to diagnosis of endometrial and ovarian cancer in the 45 and Up Study cohort.

PURPOSE: To determine pathways to endometrial or ovarian cancer diagnosis by comparing health service utilization between cancer cases and matched cancer-free controls, using linked health records. METHODS: From cancer registry records, we identified 238 incident endometrial and 167 ovarian cancer cases diagnosed during 2006-2013 in the Australian 45 and Up Study cohort (142,973 female participants). Each case was matched to four cancer-free controls on birthdate, sex, place of residence, smoking status, and body mass index. The use of relevant health services during the 13-18-, 7-12-, 0-6-, and 0-1-months pre-diagnosis for cases and the corresponding dates for their matched controls was determined through linkage with subsidized medical services and hospital records. RESULTS: Healthcare utilization diverged between women with cancer and controls in the 0-6-months, particularly 0-1 months, pre-diagnosis. In the 0-1 months, 74.8% of endometrial and 50.3% of ovarian cases visited a gynecologist/gynecological oncologist, 11.3% and 59.3% had a CA125 test, 5.5% and 48.5% an abdominal pelvic CT scan, and 34.5% and 30.5% a transvaginal pelvic ultrasound, respectively (versus ≤ 1% of matched controls). Moreover, 25.1% of ovarian cancer cases visited an emergency department in the 0-1-months pre-diagnosis (versus 1.3% of matched controls), and GP visits were significantly more common for cases than controls in this period. CONCLUSION: Most women with endometrial or ovarian cancer accessed recommended specialists and tests in the 0-1-months pre-diagnosis, but a high proportion of women with ovarian cancer visited an emergency department. This reinforces the importance of timely specialist referral.

Colon and rectal cancer treatment patterns and their associations with clinical, sociodemographic and lifestyle characteristics: analysis of the Australian 45 and Up Study cohort.

BACKGROUND: Colorectal cancer is the third most diagnosed cancer globally and the second leading cause of cancer death. We examined colon and rectal cancer treatment patterns in Australia. METHODS: From cancer registry records, we identified 1,236 and 542 people with incident colon and rectal cancer, respectively, diagnosed during 2006-2013 in the 45 and Up Study cohort (267,357 participants). Cancer treatment and deaths were determined via linkage to routinely collected data, including hospital and medical services records. For colon cancer, we examined treatment categories of "surgery only", "surgery plus chemotherapy", "other treatment" (i.e. other combinations of surgery/chemotherapy/radiotherapy), "no record of cancer-related treatment, died"; and, for rectal cancer, "surgery only", "surgery plus chemotherapy and/or radiotherapy", "other treatment", and "no record of cancer-related treatment, died". We analysed survival, time to first treatment, and characteristics associated with treatment receipt using competing risks regression. RESULTS: 86.4% and 86.5% of people with colon and rectal cancer, respectively, had a record of receiving any treatment ≤2 years post-diagnosis. Of those treated, 93.2% and 90.8% started treatment ≤2 months post-diagnosis, respectively. Characteristics significantly associated with treatment receipt were similar for colon and rectal cancer, with strongest associations for spread of disease and age at diagnosis (p<0.003). For colon cancer, the rate of "no record of cancer-related treatment, died" was higher for people with distant spread of disease (versus localised, subdistribution hazard ratio (SHR)=13.6, 95% confidence interval (CI):5.5-33.9), age ≥75 years (versus age 45-74, SHR=3.6, 95%CI:1.8-7.1), and visiting an emergency department ≤1 month pre-diagnosis (SHR=2.9, 95%CI:1.6-5.2). For rectal cancer, the rate of "surgery plus chemotherapy and/or radiotherapy" was higher for people with regional spread of disease (versus localised, SHR=5.2, 95%CI:3.6-7.7) and lower for people with poorer physical functioning (SHR=0.5, 95%CI:0.3-0.8) or no private health insurance (SHR=0.7, 95%CI:0.5-0.9). CONCLUSION: Before the COVID-19 pandemic, most people with colon or rectal cancer received treatment ≤2 months post-diagnosis, however, treatment patterns varied by spread of disease and age. This work can be used to inform future healthcare requirements, to estimate the impact of cancer control interventions to improve prevention and early diagnosis, and serve as a benchmark to assess treatment delays/disruptions during the pandemic. Future work should examine associations with clinical factors (e.g. performance status at diagnosis) and interdependencies between characteristics such as age, comorbidities, and emergency department visits.

Extending an Antiracism Lens to the Implementation of Precision Public Health Interventions.

Precision public health holds promise to improve disease prevention and health promotion strategies, allowing the right intervention to be delivered to the right population at the right time. Growing concerns underscore the potential for precision-based approaches to exacerbate health disparities by relying on biased data inputs and recapitulating existing access inequities. To achieve its full potential, precision public health must focus on addressing social and structural drivers of health and prominently incorporate equity-related concerns, particularly with respect to race and ethnicity. In this article, we discuss how an antiracism lens could be applied to reduce health disparities and health inequities through equity-informed research, implementation, and evaluation of precision public health interventions. (Am J Public Health. 2023;113(11):1210-1218. https://doi.org/10.2105/AJPH.2023.307386).

Human Genetics Society of Australasia Position Statement: Use of Polygenic Scores in Clinical Practice and Population Health.

Considerable progress continues to be made with regards to the value and use of disease associated polygenic scores (PGS). PGS aim to capture a person's genetic liability to a condition, disease, or a trait, combining information across many risk variants and incorporating their effect sizes. They are already available for clinicians and consumers to order in Australasia. However, debate is ongoing over the readiness of this information for integration into clinical practice and population health. This position statement provides the viewpoint of the Human Genetics Society of Australasia (HGSA) regarding the clinical application of disease-associated PGS in both individual patients and population health. The statement details how PGS are calculated, highlights their breadth of possible application, and examines their current challenges and limitations. We consider fundamental lessons from Mendelian genetics and their continuing relevance to PGS, while also acknowledging the distinct elements of PGS. Use of PGS in practice should be evidence based, and the evidence for the associated benefit, while rapidly emerging, remains limited. Given that clinicians and consumers can already order PGS, their current limitations and key issues warrant consideration. PGS can be developed for most complex conditions and traits and can be used across multiple clinical settings and for population health. The HGSA's view is that further evaluation, including regulatory, implementation and health system evaluation are required before PGS can be routinely implemented in the Australasian healthcare system.

Solid Fuel, Secondhand Smoke, and Lung Cancer Mortality: A Prospective Cohort of 323,794 Chinese Never-Smokers.

Rationale: Household air pollution and secondhand tobacco smoke are known carcinogens for lung cancer, but large-scale estimates of the relationship with lung cancer mortality are lacking. Objectives: Using the large-scale cohort China Kadoorie Biobank, we prospectively investigated associations between these two risk factors and lung cancer death among never-smokers. Methods: The Biobank recruited 512,715 adults aged 30-79 years from 10 regions in China during 2004-2008. Self-reported never-smoking participants were followed up to December 31, 2016, with linkage to mortality data. Total duration of exposure to household air pollution was calculated from self-reported domestic solid fuel use. Exposure to secondhand tobacco smoke was ascertained using exposure at home and/or other places. Hazard ratios and 95% confidence intervals for associations between these two exposures and lung cancer death were estimated using Cox regression, adjusting for key confounders. Measurements and Main Results: There were 979 lung cancer deaths among 323,794 never-smoking participants without a previous cancer diagnosis during 10.2 years of follow-up. There was a log-linear positive association between exposure to household air pollution and lung cancer death, with a 4% increased risk per 5-year increment of exposure (hazard ratio = 1.04; 95% confidence interval = 1.01-1.06; P trend = 0.0034), and participants with 40.1-50.0 years of exposure had the highest risk compared with the never-exposed (hazard ratio = 1.53; 95% confidence interval = 1.13-2.07). The association was largely consistent across various subgroups. No significant association was found between secondhand smoke and lung cancer death. Conclusions: This cohort study provides new prospective evidence suggesting that domestic solid fuel use is associated with lung cancer death among never-smokers.

Family history, obesity, urological factors and diabetic medications and their associations with risk of prostate cancer diagnosis in a large prospective study.

BACKGROUND: Prostate cancer (PC) aetiology is unclear. PC risk was examined in relation to several factors in a large population-based prospective study. METHODS: Male participants were from Sax Institute's 45 and Up Study (Australia) recruited between 2006 and 2009. Questionnaire and linked administrative health data from the Centre for Health Record Linkage and Services Australia were used to identify incident PC, healthcare utilisations, Prostate Specific Antigen (PSA) testing reimbursements and dispensing of metformin and benign prostatic hyperplasia (BPH) prescriptions. Multivariable Cox and Joint Cox regression analyses were used to examine associations by cancer spread, adjusting for various confounders. RESULTS: Of 107,706 eligible men, 4257 developed incident PC up to end 2013. Risk of PC diagnosis increased with: PC family history (versus no family history of cancer; HRadjusted = 1.36; 95% CI:1.21-1.52); father and brother(s) diagnosed with PC (versus cancer-free family history; HRadjusted = 2.20; 95% CI:1.61-2.99); severe lower-urinary-tract symptoms (versus mild; HRadjusted = 1.77; 95% CI:1.53-2.04) and vasectomy (versus none; HRadjusted = 1.08; 95% CI:1.00-1.16). PC risk decreased with dispensed prescriptions (versus none) for BPH (HRadjusted = 0.76; 95% CI:0.69-0.85) and metformin (HRadjusted = 0.57; 95% CI:0.48-0.68). Advanced PC risk increased with vasectomy (HRadjusted = 1.28; 95% CI:1.06-1.55) and being obese (versus normal weight; HRadjusted = 1.31; 95% CI:1.01-1.69). CONCLUSION: Vasectomy and obesity are associated with an increased risk of advanced PC. The reduced risk of localised and advanced PC associated with BPH, and diabetes prescriptions warrants investigation.

Independent evaluation of melanoma polygenic risk scores in UK and Australian prospective cohorts.

BACKGROUND: Previous studies suggest that polygenic risk scores (PRSs) may improve melanoma risk stratification. However, there has been limited independent validation of PRS-based risk prediction, particularly assessment of calibration (comparing predicted to observed risks). OBJECTIVES: To evaluate PRS-based melanoma risk prediction in prospective UK and Australian cohorts with European ancestry. METHODS: We analysed invasive melanoma incidence in the UK Biobank (UKB; n = 395 647, 1651 cases) and a case-cohort nested within the Melbourne Collaborative Cohort Study (MCCS, Australia; n = 4765, 303 cases). Three PRSs were evaluated: 68 single-nucleotide polymorphisms (SNPs) at 54 loci from a 2020 meta-analysis (PRS68), 50 SNPs significant in the 2020 meta-analysis excluding UKB (PRS50) and 45 SNPs at 21 loci known in 2018 (PRS45). Ten-year melanoma risks were calculated from population-level cancer registry data by age group and sex, with and without PRS adjustment. RESULTS: Predicted absolute melanoma risks based on age and sex alone underestimated melanoma incidence in the UKB [ratio of expected/observed cases: E/O = 0·65, 95% confidence interval (CI) 0·62-0·68] and MCCS (E/O = 0·63, 95% CI 0·56-0·72). For UKB, calibration was improved by PRS adjustment, with PRS50-adjusted risks E/O = 0·91, 95% CI 0·87-0·95. The discriminative ability for PRS68- and PRS50-adjusted absolute risks was higher than for risks based on age and sex alone (Δ area under the curve 0·07-0·10, P < 0·0001), and higher than for PRS45-adjusted risks (Δ area under the curve 0·02-0·04, P < 0·001). CONCLUSIONS: A PRS derived from a larger, more diverse meta-analysis improves risk prediction compared with an earlier PRS, and might help tailor melanoma prevention and early detection strategies to different risk levels. Recalibration of absolute risks may be necessary for application to specific populations.

Raking of data from a large Australian cohort study improves generalisability of estimates of prevalence of health and behaviour characteristics and cancer incidence.

BACKGROUND: Health surveys are commonly somewhat non-representative of their target population, potentially limiting the generalisability of prevalence estimates for health/behaviour characteristics and disease to the population. To reduce bias, weighting methods have been developed, though few studies have validated weighted survey estimates against generally accepted high-quality independent population benchmark estimates. METHODS: We applied post-stratification and raking methods to the Australian 45 and Up Study using Census data and compared the resulting prevalence of characteristics to accepted population benchmark estimates and separately, the incidence rates of lung, colorectal, breast and prostate cancer to whole-of-population estimates using Standardised Incidence Ratios (SIRs). RESULTS: The differences between 45 and Up Study and population benchmark estimates narrowed following sufficiently-informed raking, e.g. 13.6% unweighted prevalence of self-reported fair/poor overall health, compared to 17.0% after raking and 17.9% from a population benchmark estimate. Raking also improved generalisability of cancer incidence estimates. For example, unweighted 45 and Up Study versus whole-of-population SIRs were 0.700 (95%CI:0.574-0.848) for male lung cancer and 1.098 (95%CI:1.002-1.204) for prostate cancer, while estimated SIRs after sufficiently-informed raking were 0.828 (95%CI:0.684-0.998) and 1.019 (95%CI:0.926-1.121), respectively. CONCLUSION: Raking may be a useful tool for improving the generalisability of exposure prevalence and disease incidence from surveys to the population.

Lynch syndrome testing of colorectal cancer patients in a high-income country with universal healthcare: a retrospective study of current practice and gaps in seven australian hospitals.

BACKGROUND: To inform effective genomic medicine strategies, it is important to examine current approaches and gaps in well-established applications. Lynch syndrome (LS) causes 3-5% of colorectal cancers (CRCs). While guidelines commonly recommend LS tumour testing of all CRC patients, implementation in health systems is known to be highly variable. To provide insights on the heterogeneity in practice and current bottlenecks in a high-income country with universal healthcare, we characterise the approaches and gaps in LS testing and referral in seven Australian hospitals across three states. METHODS: We obtained surgery, pathology, and genetics services data for 1,624 patients who underwent CRC resections from 01/01/2017 to 31/12/2018 in the included hospitals. RESULTS: Tumour testing approaches differed between hospitals, with 0-19% of patients missing mismatch repair deficiency test results (total 211/1,624 patients). Tumour tests to exclude somatic MLH1 loss were incomplete at five hospitals (42/187 patients). Of 74 patients with tumour tests completed appropriately and indicating high risk of LS, 36 (49%) were missing a record of referral to genetics services for diagnostic testing, with higher missingness for older patients (0% of patients aged ≤ 40 years, 76% of patients aged > 70 years). Of 38 patients with high-risk tumour test results and genetics services referral, diagnostic testing was carried out for 25 (89%) and identified a LS pathogenic/likely pathogenic variant for 11 patients (44% of 25; 0.7% of 1,624 patients). CONCLUSIONS: Given the LS testing and referral gaps, further work is needed to identify strategies for successful integration of LS testing into clinical care, and provide a model for hereditary cancers and broader genomic medicine. Standardised reporting may help clinicians interpret tumour test results and initiate further actions.

Identification of an Optimal TLR8 Ligand by Alternating the Position of 2'-O-Ribose Methylation.

Recognition of RNA by receptors of the innate immune system is regulated by various posttranslational modifications. Different single 2'-O-ribose (2'-O-) methylations have been shown to convert TLR7/TLR8 ligands into specific TLR8 ligands, so we investigated whether the position of 2'-O-methylation is crucial for its function. To this end, we designed different 2'-O-methylated RNA oligoribonucleotides (ORN), investigating their immune activity in various cell systems and analyzing degradation under RNase T2 treatment. We found that the 18S rRNA-derived TLR7/8 ligand, RNA63, was differentially digested as a result of 2'-O-methylation, leading to variations in TLR8 and TLR7 inhibition. The suitability of certain 2'-O-methylated RNA63 derivatives as TLR8 agonists was further demonstrated by the fact that other RNA sequences were only weak TLR8 agonists. We were thus able to identify specific 2'-O-methylated RNA derivatives as optimal TLR8 ligands.

Linking chondrocyte and synovial transcriptional profile to clinical phenotype in osteoarthritis.

OBJECTIVES: To determine how gene expression profiles in osteoarthritis joint tissues relate to patient phenotypes and whether molecular subtypes can be reproducibly captured by a molecular classification algorithm. METHODS: We analysed RNA sequencing data from cartilage and synovium in 113 osteoarthritis patients, applying unsupervised clustering and Multi-Omics Factor Analysis to characterise transcriptional profiles. We tested the association of the molecularly defined patient subgroups with clinical characteristics from electronic health records. RESULTS: We detected two patient subgroups in low-grade cartilage (showing no/minimal degeneration, cartilage normal/softening only), with differences associated with inflammation, extracellular matrix-related and cell adhesion pathways. The high-inflammation subgroup was associated with female sex (OR 4.12, p=0.0024) and prescription of proton pump inhibitors (OR 4.21, p=0.0040). We identified two independent patient subgroupings in osteoarthritis synovium: one related to inflammation and the other to extracellular matrix and cell adhesion processes. A seven-gene classifier including MMP13, APOD, MMP2, MMP1, CYTL1, IL6 and C15orf48 recapitulated the main axis of molecular heterogeneity in low-grade knee osteoarthritis cartilage (correlation ρ=-0.88, p<10-10) and was reproducible in an independent patient cohort (ρ=-0.85, p<10-10). CONCLUSIONS: These data support the reproducible stratification of osteoarthritis patients by molecular subtype and the exploration of new avenues for tailored treatments.