Polygenic risk scores aggregate an individual’s burden of risk alleles to estimate overall genetic risk for a specific trait or disease. Polygenic risk scores derived from Genome-Wide Association Studies of European populations perform poorly for other ancestral groups. Given the potential for future clinical utility, underperformance of polygenic risk score prediction in South Asian populations has the potential to reinforce health inequalities. To determine whether European-derived polygenic risk scores underperform at Multiple Sclerosis prediction in a South Asian population compared with a European-ancestry cohort, we used data from two longitudinal genetic cohort studies: Genes & Health (2015-), a study of ∼50,000 British-Bangladeshi and British-Pakistani individuals, and UK Biobank (2006-), which is comprised of ∼500,000 predominantly White British individuals. We compared individuals with and without Multiple Sclerosis in both studies (Genes and Health: NCases=42, NControl=40,490; UK Biobank: NCases=2091, NControl=374,866). Polygenic risk scores were calculated using clumping-and-thresholding with risk allele effect sizes from the largest Multiple Sclerosis Genome-Wide Association Study to date. Scores were calculated with and without the Major Histocompatibility Complex region, the most influential locus in determining Multiple Sclerosis risk. Polygenic risk scire prediction was evaluated using Nagelkerke’s pseudo-R2 metric adjusted for case ascertainment, age, sex, and the first four genetic principal components. We found that, as expected, European-derived polygenic risk scores perform poorly in the Genes and Health cohort, explaining 1.1% (including the Major Histocompatibility Complex) and 1.5% (excluding the Major Histocompatibility Complex) of disease risk. In contrast, Multiple Sclerosis polygenic risk scores explained 4.8% (including the Major Histocompatibility Complex) and 2.8% (excluding the Major Histocompatibility Complex) of disease risk in European-ancestry UK Biobank participants. These findings suggest that polygenic risk score prediction of Multiple Sclerosis based on European Genome-Wide Association Study results is less accurate in a South Asian population. Genetic studies of ancestrally-diverse populations are required to ensure that polygenic risk scores can be useful across ancestries.

Background We investigated which clinical and sociodemographic characteristics were associated with unhealthy patterns of weight gain amongst adults living in England during the pandemic. Methods With the approval of NHS England we conducted an observational cohort study of Body Mass Index (BMI) changes between March 2015 and March 2022 using the OpenSAFELY–TPP platform. We estimated individual rates of weight gain before and during the pandemic, and identified individuals with rapid weight gain (>0.5kg/m2/year) in each period. We also estimated the change in rate of weight gain between the prepandemic and pandemic period and defined extreme-accelerators as the ten percent of individuals with the greatest increase (>1.84kg/m2/year). We estimated associations with these outcomes using multivariate logistic regression. Findings We extracted data on 17,742,365 adults (50.1% female, 76.1% White British). Median BMI increased from 27.8kg/m2[IQR:24.3 to 32.1] in 2019 (March 2019 to February 2020) to 28.0kg/m2[24.4 to 32.6] in 2021. Rapid pandemic weight gain (n=3,214,155) was associated with female sex (male vs female: aOR 0.76 [95%CI:0.76 to 0.76]); younger age (50 to 59 years vs 18 to 29 years: aOR 0.60 [0.60 to 0.61]); White British ethnicity (Black Caribbean vs White British: aOR 0.91 [0.89 to 0.94]); deprivation (least–deprived–IMD–quintile vs most–deprived:aOR 0.77 [0.77 to 0.78]); and long-term conditions, of which mental health conditions had the greatest effect (e.g. depression (aOR 1.18[1.17 to 1.18])). Similar characteristics increased risk of extreme acceleration (n=2,768,695). Interpretation We found female sex, younger age, deprivation and mental health conditions increased risk of unhealthy patterns of pandemic weight gain. This highlights the need to incorporate sociodemographic, physical, and mental health characteristics when formulating post-pandemic research, policies, and interventions targeting BMI. Funding NIHR

BackgroundThe population prevalence of multimorbidity (the existence of at least 2 or more long-term conditions (LTCs) in an individual) is increasing among young adults, particularly in minority ethnic groups and individuals living in socioeconomically deprived areas. In this study, we applied a data-driven approach to identify clusters of individuals who had an early onset multimorbidity in an ethnically and socioeconomically diverse population. We identified associations between clusters and a range of health outcomes.Methods and findingsWe analysed the electronic health records from 837,869 individuals in England with early onset multimorbidity (aged between 16 and 39 years old when the second LTC was recorded) using linked primary and secondary care data between 2010 and 2020 from the Clinical Practice Research Datalink GOLD (CPRD GOLD). A total of 204 LTCs were included. Latent class analysis stratified by ethnicity unveiled 4 clusters of multimorbidity in White groups and 3 clusters in South Asian and Black groups. We found that early onset multimorbidity is the most common form of multimorbidity among minority ethnic (59% and 56%, in the South Asian and Black populations, respectively) in the UK compared to the White population (42%). At the end of the study, 4% of the White early onset multimorbidity population had died compared to 2% of the South Asian and Black populations, however, the latter groups died younger and lost more years of life. The three ethnic groups displayed a cluster of individuals with increased rates of primary care consultations, hospitalisations, long-term prescribing, and odds of mortality. These presented a combination of physical and mental health conditions that are common across all groups (hypertension, depression and painful conditions being the leading conditions). However, they also presented exclusive LTCs and had different sociodemographic profiles: Whites were mostly men (54%), South Asian and Black groups were more socioeconomically deprived than White groups, with a consistent deprivation gradient across all multimorbidity clusters. In White groups, the highest risk cluster was more socioeconomically deprived than the lowest risk cluster.ConclusionsThese findings emphasise the need to identify, prevent and manage multimorbidity early in the life course. Our work provides additional insights into the need to ensure healthcare improvements are equitable and reach those from socioeconomically deprived and diverse groups who are disproportionately and more severely affected by multimorbidity.

Background Social prescribing (SP) usually involves linking patients in primary care with services provided by the voluntary and community sector. Preliminary evidence suggests that SP may offer a means of connecting patients with community-based health promotion activities, potentially contributing to the prevention of long-term conditions, such as type 2 diabetes (T2D). Methods Using mixed-methods realist evaluation, we explored the possible contribution of SP to individual-level prevention of T2D in a multi-ethnic, socio-economically deprived population in London, UK. We made comparisons with an existing prevention programme (NHS Diabetes Prevention Programme (NDPP)) where relevant and possible. Anonymised primary care electronic health record data of 447,360 people 18+ with an active GP registration between December 2016 and February 2022 were analysed using quantitative methods. Qualitative data (interviews with 11 primary care clinicians, 11 social prescribers, 13 community organisations and 8 SP users at high risk of T2D; 36 hours of ethnographic observations of SP and NDPP sessions; and relevant documents) were analysed thematically. Data were integrated using visual means and realist methods. Results People at high risk of T2D were four times more likely to be referred into SP than the eligible general population (RR 4.31 (95% CI 4.17–4.46)), with adjustment for socio-demographic variables resulting in attenuation (RR 1.33 (95% CI 1.27–1.39)). More people at risk of T2D were referred to SP than to NDPP, which could be explained by the broad referral criteria for SP and highly supportive (proactive, welcoming) environments. Holistic and sustained SP allowed acknowledgement of patients’ wider socio-economic constraints and provision of long-term personalised care. The fact that SP was embedded within the local community and primary care infrastructure facilitated the timely exchange of information and cross-referrals across providers, resulting in enhanced service responsiveness. Conclusions Our study suggests that SP may offer an opportunity for individual-level T2D prevention to shift away from standardised, targeted and short-term strategies to approaches that are increasingly personalised, inclusive and long-term. Primary care-based SP seems most ideally placed to deliver such approaches where practitioners, providers and commissioners work collectively to achieve holistic, accessible, sustained and integrated services.

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