Integrating polygenic risk scores in the prediction of type 2 diabetes risk and subtypes in British Pakistanis and Bangladeshis: A population-based cohort study.
Integrating polygenic risk scores in the prediction of type 2 diabetes risk and subtypes in British Pakistanis and Bangladeshis: A population-based cohort study.
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DOI：
10.1371/journal.pmed.1003981
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发表时间：
2022-05
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影响因子：
15.8
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中科院分区：
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2型糖尿病（T2 D）在英国南亚人中非常普遍，但他们在研究中的代表性不足。基因与健康（G&H）是一项针对英国巴基斯坦人和孟加拉人（BPB）的大型人口研究，包括基因组和常规健康数据。我们评估了BPB和欧洲人群（EUR）之间共享T2 D遗传风险的程度。然后，我们研究了T2 D的多基因风险评分（PRS）与现有风险工具（QDiabetes）的整合是否可以改善对偶发疾病的预测和疾病亚型的表征。在这项观察性队列研究中，我们评估了与EUR个体中T2 D相关的常见遗传基因座是否在G&H的22，490名BPB个体中复制。我们在G&H中复制的基因座（n = 76/338，22%）比如果所有EUR确定的基因座都是可转移的（n = 101，30%; p = 0.001）预期的要少。在27个可转移的基因座中，只有9个显示出共享的因果变异的证据。我们构建了T2 D PRS，并将其与临床风险工具（QDiabetes）结合在一个新的综合风险工具（IRT）中，以评估糖尿病事件的风险。为了评估模型性能，我们比较了分类净重新分类指数（NRI）与单独的QDiabetes。在随访10年的13，648例无T2 D患者中，IRT与QDiabetes的NRI为3.2%（95%置信区间（CI）：2.0%-4.4%）。IRT在对年龄小于40岁的个体进行重新分类时表现最好，这些个体仅被QDiabetes视为低风险（NRI 5.6%，95% CI 3.6%至7.6%），他们往往没有合并症且身材苗条。校正QDiabetes评分后，PRS与妊娠糖尿病后进展为T2 D独立相关（PRS的风险比（HR）/SD为1.23，95% CI 1.05 - 1.42，p = 0.028）。通过对糖尿病诊断时的临床特征进行聚类分析，我们复制了先前报道的疾病亚组，包括轻度肥胖相关、轻度肥胖相关和胰岛素抵抗型糖尿病，并显示PRS分布在亚组之间存在差异（p = 0.002）。在该聚类分析中整合PRS揭示了可能的重度胰岛素缺乏性糖尿病（pSIDD）亚组，尽管缺乏胰岛素分泌或抵抗的临床测量。我们还观察到在调整混杂因素后，亚组之间微血管和大血管并发症进展率的差异。研究的局限性包括缺乏外部重复队列，以及缺失或不正确的常规健康数据引起的潜在偏倚。我们对T2 D位点在EUR和BPB之间的可转移性的分析表明，需要进行更大规模的多祖先研究，以更好地阐明疾病的遗传贡献及其各种病因。我们表明，针对这种高风险BPB人群优化的T2 D PRS在BPB中具有潜在的临床应用，在已建立的临床风险算法之上提高了T2 D风险的识别（特别是在年轻人中），并有助于在诊断时识别亚组，这可能有助于将来对疾病的分层护理和治疗。Sam Hodgson及其同事研究了欧洲血统人群中与2型糖尿病相关的常见遗传差异是否可以转移到英国、巴基斯坦和孟加拉血统人群中，将一种新的多基因风险评分与已建立的临床风险评分相结合。与2型糖尿病（T2 D）相关的常见遗传变化已在欧洲血统人群的大型研究中进行了广泛研究。然而，目前尚不清楚这些发现是否可以转移到南亚血统的人身上，他们受到的影响不成比例，但在遗传研究中代表性不足。多基因风险评分（PRS）已成为一种有用的临床工具，可用于改善对谁有/没有发展为T2 D的风险的预测，但它们尚未与常规临床护理中已经使用的现有预测工具一起进行评估，或揭示病情的“亚型”。我们评估了欧洲血统人群中与T2 D相关的常见遗传差异是否可以转移到英国巴基斯坦和孟加拉国（BPB）血统的人群中（n = 18，875）。我们发现这些祖先群体之间的遗传差异是显着的。我们为BPB（n = 13，648）建立了T2 D PRS，并将其与临床风险评分（QDiabetes）相结合。我们的综合风险工具（IRT）改善了T2 D的预测，特别是在年龄小于40岁的个体中，仅被QDiabetes视为低风险。PRS也与妊娠糖尿病影响的妊娠后T2 D的发展相关。最后，我们使用PRS结合标准临床测量，以帮助阐明我们研究人群（n = 5，904）中的T2 D亚组以及未来糖尿病并发症风险的差异。我们的工作强调了在T2 D的遗传研究中需要更多地代表不同的祖先群体。PRS与临床危险因素的整合改善了BPB个体中T2 D的预测，特别是在年轻人中。T2 D PRS有助于在诊断时识别临床上不同的疾病亚组。这些亚组的识别可以支持T2 D护理的分层，以改善健康结果并在未来更有效地分配医疗资源。
Type 2 diabetes (T2D) is highly prevalent in British South Asians, yet they are underrepresented in research. Genes & Health (G&H) is a large, population study of British Pakistanis and Bangladeshis (BPB) comprising genomic and routine health data. We assessed the extent to which genetic risk for T2D is shared between BPB and European populations (EUR). We then investigated whether the integration of a polygenic risk score (PRS) for T2D with an existing risk tool (QDiabetes) could improve prediction of incident disease and the characterisation of disease subtypes. In this observational cohort study, we assessed whether common genetic loci associated with T2D in EUR individuals were replicated in 22,490 BPB individuals in G&H. We replicated fewer loci in G&H (n = 76/338, 22%) than would be expected given power if all EUR-ascertained loci were transferable (n = 101, 30%; p = 0.001). Of the 27 transferable loci that were powered to interrogate this, only 9 showed evidence of shared causal variants. We constructed a T2D PRS and combined it with a clinical risk instrument (QDiabetes) in a novel, integrated risk tool (IRT) to assess risk of incident diabetes. To assess model performance, we compared categorical net reclassification index (NRI) versus QDiabetes alone. In 13,648 patients free from T2D followed up for 10 years, NRI was 3.2% for IRT versus QDiabetes (95% confidence interval (CI): 2.0% to 4.4%). IRT performed best in reclassification of individuals aged less than 40 years deemed low risk by QDiabetes alone (NRI 5.6%, 95% CI 3.6% to 7.6%), who tended to be free from comorbidities and slim. After adjustment for QDiabetes score, PRS was independently associated with progression to T2D after gestational diabetes (hazard ratio (HR) per SD of PRS 1.23, 95% CI 1.05 to 1.42, p = 0.028). Using cluster analysis of clinical features at diabetes diagnosis, we replicated previously reported disease subgroups, including Mild Age-Related, Mild Obesity-related, and Insulin-Resistant Diabetes, and showed that PRS distribution differs between subgroups (p = 0.002). Integrating PRS in this cluster analysis revealed a Probable Severe Insulin Deficient Diabetes (pSIDD) subgroup, despite the absence of clinical measures of insulin secretion or resistance. We also observed differences in rates of progression to micro- and macrovascular complications between subgroups after adjustment for confounders. Study limitations include the absence of an external replication cohort and the potential biases arising from missing or incorrect routine health data. Our analysis of the transferability of T2D loci between EUR and BPB indicates the need for larger, multiancestry studies to better characterise the genetic contribution to disease and its varied aetiology. We show that a T2D PRS optimised for this high-risk BPB population has potential clinical application in BPB, improving the identification of T2D risk (especially in the young) on top of an established clinical risk algorithm and aiding identification of subgroups at diagnosis, which may help future efforts to stratify care and treatment of the disease. Sam Hodgson and colleagues investigate whether the common genetic differences associated with type 2 diabetes in people of European ancestry can be transferred to people of British Pakistani and Bangladeshi ancestry, integrating a novel polygenic risk score with an established clinical risk score. The common genetic changes associated with type 2 diabetes (T2D) have been extensively investigated in large studies of people from European ancestry. However, it is not known whether these findings can be transferred to people of South Asian origin, who are disproportionately affected yet underrepresented in genetic studies. Polygenic risk scores (PRSs) have emerged as a useful clinical tool with which to improve the prediction of who is/is not at risk of developing T2D, but they have not yet been assessed alongside existing predictive tools already used in routine clinical care, or to uncover “subtypes” of the condition. We assessed whether the common genetic differences associated with T2D in people of European ancestry could be transferred to people of British Pakistani and Bangladeshi (BPB) ancestry (n = 18,875). We found genetic differences between these ancestry groups that were significant. We built a T2D PRS for BPB (n = 13,648) and integrated it with a clinical risk score (QDiabetes). Our integrated risk tool (IRT) improved the prediction of T2D, especially in individuals aged less than 40 years deemed low risk by QDiabetes alone. The PRS was also associated with the development of T2D after a pregnancy affected by gestational diabetes. Lastly, we used the PRS, in combination with standard clinical measures, to help elucidate subgroups of T2D in our study population (n = 5,904) and differences in the risk of future diabetes complications. Our work highlights the need for greater representation of diverse ancestry groups in genetic studies of T2D. Integration of a PRS with clinical risk factors improved the prediction of T2D in BPB individuals, especially in the young. The T2D PRS can help to identify clinically distinct disease subgroups at diagnosis. Identification of these subgroups may support stratification of T2D care to improve health outcomes and allocate healthcare resources more efficiently in the future.
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影响因子：
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作者：
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DOI：
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期刊：
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