دانلود مقاله ارتباط علی MERTK پلاسما با مرگ و میر ناشی از عفونت

Summary
Introduction
Methods
Results
Discussion
Funding
Author contributions 
Appendix A. Supporting information 
References

Summary
Introduction
Methods
Results
Discussion
Funding
Author contributions 
Appendix A. Supporting information 
References

چکیده
زمینه و هدف: علیرغم مداخلات موجود بهداشت عمومی، ضد میکروبی و واکسن، بیماری های عفونی عامل اصلی مرگ و میر هستند. هدف ما این بود که پیوندهای پروتئومی پلاسما را برای مرگ و میر عفونت تعریف کنیم و سپس از تصادفی سازی مندلی (MR) برای تولید نشانگرهای زیستی استفاده کنیم که ممکن است به طور علّی مرتبط باشند. روش‌ها: ما از داده‌های پروتئومی پلاسمای UK Biobank برای ارتباط 2923 پروتئین پلاسما با مرگ‌ومیر عفونت قبل از 31 دسامبر 2019 (240 رویداد در 52520 شرکت‌کننده) استفاده کردیم. از آنجایی که بسیاری از پروتئین‌های پلاسما نیز مرگ‌ومیر غیرعفونی را پیش‌بینی می‌کنند، ما در تجزیه و تحلیل به استثنای بازماندگان، روی موارد مرتبط با خطر مرگ و میر ناشی از عفونت بیش از 1.5 برابر تمرکز کردیم. سپس از امتیازات صفات کمی پروتئین (pQTS) برای شناسایی اینکه آیا سطوح پروتئین پیش‌بینی‌شده ژنتیکی با مرگ و میر ناشی از عفونت مرتبط است یا خیر، استفاده شد. برای انجام دو نمونه MR، ما یک مطالعه ارتباط ژنومی (GWAS) مرگ و میر عفونت را با استفاده از شرکت‌کنندگان Biobank بریتانیا بدون داده‌های پروتئومی پلاسما انجام دادیم (تعداد = 363953 شامل 984 مرگ ناشی از عفونت). یافته ها: پس از تعدیل عوامل خطر بالینی، 1142 پروتئین پلاسما با خطر مرگ و میر ناشی از عفونت همراه بود (نرخ کشف نادرست <0.05). 259 پروتئین با بیش از 1.5 برابر افزایش خطر عفونت در مقابل مرگ و میر غیرعفونی مرتبط بودند. از این میان، ما تشخیص دادیم که افزایش غلظت MERTK از نظر ژنتیکی با افزایش خطر مرگ و میر ناشی از عفونت مرتبط است. MR از ارتباط علی بین افزایش پروتئین MERTK پلاسما و مرگ و میر ناشی از عفونت پشتیبانی کرد (نسبت شانس 1.46 در واحد؛ 95% فاصله اطمینان (CI): 1.15-1.85؛ p = 0.002).
نتیجه گیری: MERTK پلاسما به طور علّی با مرگ و میر ناشی از عفونت مرتبط است و اکتشاف به عنوان یک هدف درمانی بالقوه را ضروری می کند.

Summary

Background
Infectious diseases are a major cause of mortality in spite of existing public health, anti-microbial and vaccine interventions. We aimed to define plasma proteomic associates of infection mortality and then apply Mendelian randomisation (MR) to yield biomarkers that may be causally associated.

Methods
We used UK Biobank plasma proteomic data to associate 2923 plasma proteins with infection mortality before 31st December 2019 (240 events in 52,520 participants). Since many plasma proteins also predict non-infection mortality, we focussed on those associated with >1.5-fold risk of infection mortality in an analysis excluding survivors. Protein quantitative trait scores (pQTS) were then used to identify whether genetically predicted protein levels also associated with infection mortality. To conduct Two Sample MR, we performed a genome-wide association study (GWAS) of infection mortality using UK Biobank participants without plasma proteomic data (n = 363,953 including 984 infection deaths).

Findings
After adjusting for clinical risk factors, 1142 plasma proteins were associated with risk of infection mortality (false discovery rate <0.05). 259 proteins were associated with >1.5-fold increased risk of infection versus non-infection mortality. Of these, we identified genetically predicted increasing MERTK concentration was associated with increased risk of infection mortality. MR supported a causal association between increasing plasma MERTK protein and infection mortality (odds ratio 1.46 per unit; 95% CI 1.15- 1.85; p = 0.002).

Conclusion
Plasma MERTK is causally associated with infection mortality and warrants exploration as a potential therapeutic target.

Introduction

In spite of the substantial impacts achieved by public health, anti-microbial and vaccine interventions, infectious diseases remain an important cause of death across the world. For example, the Global Burden of Disease Study found that almost 20% of deaths in 2017 were sepsis-related, with marked geographical variation in the incidence and fatal sepsis.1 The risk of infection death also varies markedly within countries, with data from the United Kingdom finding that factors including advancing age, socio-economic deprivation (SED) and multimorbidity are associated with greater risk of infection than non-infection death.2 Whilst socio-economic factors are likely to play a significant role in these disparities, biological factors are also important, for example via altered immune responses to pathogens. Indeed, genome-wide association studies (GWAS) have highlighted immune-related genes, amongst others, as being associated with risk of incident infection.3,4 Extensive research in COVID-19 also shows an important role for host factors in relation to outcome.5,6 In light of the risk of future pandemics, growing anti-microbial resistance (AMR), climate change, urbanisation and demographic shifts,7 understanding the biology of host factors associated with fatal infection is an important goal.

To address this, we used the recently released UK Biobank (UKB) resource (also known as the UKB Pharma Proteomics Project or UKB-PPP) to define 2923 circulating factors that may represent biomarkers or therapeutic targets for infection mortality. We found that a subset of proteins have a high specificity for infection mortality. Of these proteins, we validated only MER proto-oncogene tyrosine kinase (MERTK) in studies using genetically inferred plasma concentrations. Detailed MR analyses suggest that plasma MERTK is causally associated with the long-term risk of infection mortality. This work provides a robust target to focus on and deeper characterisation of the biology underpinning this association has the potential to result in therapeutic approaches that mitigate adverse host factors in people identified to be at high risk of infection death.

Results

Plasma proteomic associates of infection mortality
The UKB cohort study includes baseline UKB-PPP data for 53,029 participants, of whom we excluded 509 (0.96%) due to missing data or absent long-term follow-up data. Within this subgroup, 240 infection deaths and 3551 non-infection deaths occurred before 31st December 2019, during 558,616 person years of follow-up (median 10.8 [IQR 10.2–11.6] years per participant). The most common fatal infections involved the lower respiratory tract (136 events [57.6%]), gastrointestinal tract (39 events [16.5%]), and genitourinary tract (14 events [5.9%]). We defined the association between increasing concentrations of 2923 distinct plasma proteins and infection mortality, in models including baseline socio-demographic factors and comorbidities known to be associated with infection mortality. After accounting for multiple testing, 1142 proteins were associated with the risk of infection mortality, of which 1110 were with higher risk and 32 with lower risk (Fig. 1A and Supplementary Table 1). A complementary analysis applied identical models to define associations of the 2923 proteins with non-infection mortality. After accounting for multiple testing, 1334 proteins were associated with the risk of non-infection mortality, of which 1196 were with higher risk and 138 with lower risk (Fig. 1B and Supplemental Table 1). Hence, it is likely that a substantial proportion of the proteins associated with infection mortality are non-specific associates of mortality per se. As we aimed to focus on those proteins most specifically associated with infection mortality, we repeated our analysis of proteins associated with infection mortality after excluding all subjects who survived during the observation period. Therefore, any protein demonstrating an IRR significantly above one would show greater specificity for infection mortality and any demonstrating an IRR significantly below one would show greater specificity for non-infection mortality. Applying a threshold of IRR > 1.5 in this analysis allowed us to focus on proteins with greater specificity for infection mortality and after accounting for multiple testing 259 proteins reached statistical significance (Fig. 2 and Supplemental Table 2); further inclusion of recruitment centre, participant fasting time, and season of sample collection as covariates did not substantially alter these findings (shown in Supplemental Table 2). To explore the biological themes linking these proteins, we conducted functional enrichment analysis of these 259 proteins, which revealed ‘Signalling Receptor Activity’ (GO:0038023) and ‘Molecular Transducer Activity’ (GO:0060089) as the most statistically significant terms (FDR-adjusted p = 2.4 ×10-9); other enriched GO terms are listed in Supplemental Table 3. These data suggest that the abundance of many plasma proteins is associated with risk of infection mortality, although with only broad biological themes linking these in enrichment analysis.